/**
 * Minified by jsDelivr using Terser v5.39.0.
 * Original file: /npm/modelscript@2.4.0/build/modelscript.umd.js
 *
 * Do NOT use SRI with dynamically generated files! More information: https://www.jsdelivr.com/using-sri-with-dynamic-files
 */
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Object.prototype.toString.call(t)}function pad(t){return t<10?"0"+t.toString(10):t.toString(10)}inspect.colors={bold:[1,22],italic:[3,23],underline:[4,24],inverse:[7,27],white:[37,39],grey:[90,39],black:[30,39],blue:[34,39],cyan:[36,39],green:[32,39],magenta:[35,39],red:[31,39],yellow:[33,39]},inspect.styles={special:"cyan",number:"yellow",boolean:"yellow",undefined:"grey",null:"bold",string:"green",date:"magenta",regexp:"red"};var months=["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"];function timestamp(){var t=new Date,e=[pad(t.getHours()),pad(t.getMinutes()),pad(t.getSeconds())].join(":");return[t.getDate(),months[t.getMonth()],e].join(" ")}function log(){console.log("%s - %s",timestamp(),format.apply(null,arguments))}function _extend(t,e){if(!e||!isObject(e))return t;for(var r=Object.keys(e),n=r.length;n--;)t[r[n]]=e[r[n]];return t}function hasOwnProperty(t,e){return Object.prototype.hasOwnProperty.call(t,e)}var util={inherits:inherits$1,_extend:_extend,log:log,isBuffer:isBuffer$1,isPrimitive:isPrimitive,isFunction:isFunction$1,isError:isError,isDate:isDate,isObject:isObject,isRegExp:isRegExp,isUndefined:isUndefined,isSymbol:isSymbol,isString:isString,isNumber:isNumber,isNullOrUndefined:isNullOrUndefined,isNull:isNull,isBoolean:isBoolean,isArray:isArray$1,inspect:inspect,deprecate:deprecate,format:format,debuglog:debuglog},util$1=Object.freeze({format:format,deprecate:deprecate,debuglog:debuglog,inspect:inspect,isArray:isArray$1,isBoolean:isBoolean,isNull:isNull,isNullOrUndefined:isNullOrUndefined,isNumber:isNumber,isString:isString,isSymbol:isSymbol,isUndefined:isUndefined,isRegExp:isRegExp,isObject:isObject,isDate:isDate,isError:isError,isFunction:isFunction$1,isPrimitive:isPrimitive,isBuffer:isBuffer$1,log:log,inherits:inherits$1,_extend:_extend,default:util}),domain;function EventHandlers(){}function EventEmitter(){EventEmitter.init.call(this)}function $getMaxListeners(t){return void 0===t._maxListeners?EventEmitter.defaultMaxListeners:t._maxListeners}function emitNone(t,e,r){if(e)t.call(r);else for(var n=t.length,i=arrayClone(t,n),o=0;o<n;++o)i[o].call(r)}function emitOne(t,e,r,n){if(e)t.call(r,n);else for(var i=t.length,o=arrayClone(t,i),s=0;s<i;++s)o[s].call(r,n)}function emitTwo(t,e,r,n,i){if(e)t.call(r,n,i);else for(var o=t.length,s=arrayClone(t,o),a=0;a<o;++a)s[a].call(r,n,i)}function emitThree(t,e,r,n,i,o){if(e)t.call(r,n,i,o);else for(var s=t.length,a=arrayClone(t,s),u=0;u<s;++u)a[u].call(r,n,i,o)}function emitMany(t,e,r,n){if(e)t.apply(r,n);else for(var i=t.length,o=arrayClone(t,i),s=0;s<i;++s)o[s].apply(r,n)}function _addListener(t,e,r,n){var i,o,s;if("function"!=typeof r)throw new TypeError('"listener" argument must be a function');if((o=t._events)?(o.newListener&&(t.emit("newListener",e,r.listener?r.listener:r),o=t._events),s=o[e]):(o=t._events=new EventHandlers,t._eventsCount=0),s){if("function"==typeof s?s=o[e]=n?[r,s]:[s,r]:n?s.unshift(r):s.push(r),!s.warned&&(i=$getMaxListeners(t))&&i>0&&s.length>i){s.warned=!0;var a=new Error("Possible EventEmitter memory leak detected. 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this.on(t,_onceWrap(this,t,e)),this},EventEmitter.prototype.prependOnceListener=function(t,e){if("function"!=typeof e)throw new TypeError('"listener" argument must be a function');return this.prependListener(t,_onceWrap(this,t,e)),this},EventEmitter.prototype.removeListener=function(t,e){var r,n,i,o,s;if("function"!=typeof e)throw new TypeError('"listener" argument must be a function');if(!(n=this._events))return this;if(!(r=n[t]))return this;if(r===e||r.listener&&r.listener===e)0==--this._eventsCount?this._events=new EventHandlers:(delete n[t],n.removeListener&&this.emit("removeListener",t,r.listener||e));else if("function"!=typeof r){for(i=-1,o=r.length;o-- >0;)if(r[o]===e||r[o].listener&&r[o].listener===e){s=r[o].listener,i=o;break}if(i<0)return this;if(1===r.length){if(r[0]=void 0,0==--this._eventsCount)return this._events=new EventHandlers,this;delete n[t]}else spliceOne(r,i);n.removeListener&&this.emit("removeListener",t,s||e)}return this},EventEmitter.prototype.removeAllListeners=function(t){var e,r;if(!(r=this._events))return this;if(!r.removeListener)return 0===arguments.length?(this._events=new EventHandlers,this._eventsCount=0):r[t]&&(0==--this._eventsCount?this._events=new EventHandlers:delete r[t]),this;if(0===arguments.length){for(var n,i=Object.keys(r),o=0;o<i.length;++o)"removeListener"!==(n=i[o])&&this.removeAllListeners(n);return this.removeAllListeners("removeListener"),this._events=new EventHandlers,this._eventsCount=0,this}if("function"==typeof(e=r[t]))this.removeListener(t,e);else if(e)do{this.removeListener(t,e[e.length-1])}while(e[0]);return this},EventEmitter.prototype.listeners=function(t){var e,r=this._events;return r&&(e=r[t])?"function"==typeof e?[e.listener||e]:unwrapListeners(e):[]},EventEmitter.listenerCount=function(t,e){return"function"==typeof t.listenerCount?t.listenerCount(e):listenerCount.call(t,e)},EventEmitter.prototype.listenerCount=listenerCount,EventEmitter.prototype.eventNames=function(){return this._eventsCount>0?Reflect.ownKeys(this._events):[]};var events=Object.freeze({default:EventEmitter,EventEmitter:EventEmitter});function BufferList(){this.head=null,this.tail=null,this.length=0}BufferList.prototype.push=function(t){var e={data:t,next:null};this.length>0?this.tail.next=e:this.head=e,this.tail=e,++this.length},BufferList.prototype.unshift=function(t){var e={data:t,next:this.head};0===this.length&&(this.tail=e),this.head=e,++this.length},BufferList.prototype.shift=function(){if(0!==this.length){var t=this.head.data;return 1===this.length?this.head=this.tail=null:this.head=this.head.next,--this.length,t}},BufferList.prototype.clear=function(){this.head=this.tail=null,this.length=0},BufferList.prototype.join=function(t){if(0===this.length)return"";for(var e=this.head,r=""+e.data;e=e.next;)r+=t+e.data;return r},BufferList.prototype.concat=function(t){if(0===this.length)return Buffer.alloc(0);if(1===this.length)return this.head.data;for(var e=Buffer.allocUnsafe(t>>>0),r=this.head,n=0;r;)r.data.copy(e,n),n+=r.data.length,r=r.next;return e};var isBufferEncoding=Buffer.isEncoding||function(t){switch(t&&t.toLowerCase()){case"hex":case"utf8":case"utf-8":case"ascii":case"binary":case"base64":case"ucs2":case"ucs-2":case"utf16le":case"utf-16le":case"raw":return!0;default:return!1}};function assertEncoding(t){if(t&&!isBufferEncoding(t))throw new Error("Unknown encoding: "+t)}function StringDecoder(t){switch(this.encoding=(t||"utf8").toLowerCase().replace(/[-_]/,""),assertEncoding(t),this.encoding){case"utf8":this.surrogateSize=3;break;case"ucs2":case"utf16le":this.surrogateSize=2,this.detectIncompleteChar=utf16DetectIncompleteChar;break;case"base64":this.surrogateSize=3,this.detectIncompleteChar=base64DetectIncompleteChar;break;default:return void(this.write=passThroughWrite)}this.charBuffer=new Buffer(6),this.charReceived=0,this.charLength=0}function passThroughWrite(t){return t.toString(this.encoding)}function utf16DetectIncompleteChar(t){this.charReceived=t.length%2,this.charLength=this.charReceived?2:0}function base64DetectIncompleteChar(t){this.charReceived=t.length%3,this.charLength=this.charReceived?3:0}StringDecoder.prototype.write=function(t){for(var e="";this.charLength;){var r=t.length>=this.charLength-this.charReceived?this.charLength-this.charReceived:t.length;if(t.copy(this.charBuffer,this.charReceived,0,r),this.charReceived+=r,this.charReceived<this.charLength)return"";if(t=t.slice(r,t.length),!((i=(e=this.charBuffer.slice(0,this.charLength).toString(this.encoding)).charCodeAt(e.length-1))>=55296&&i<=56319)){if(this.charReceived=this.charLength=0,0===t.length)return e;break}this.charLength+=this.surrogateSize,e=""}this.detectIncompleteChar(t);var n=t.length;this.charLength&&(t.copy(this.charBuffer,0,t.length-this.charReceived,n),n-=this.charReceived);var i;n=(e+=t.toString(this.encoding,0,n)).length-1;if((i=e.charCodeAt(n))>=55296&&i<=56319){var o=this.surrogateSize;return this.charLength+=o,this.charReceived+=o,this.charBuffer.copy(this.charBuffer,o,0,o),t.copy(this.charBuffer,0,0,o),e.substring(0,n)}return e},StringDecoder.prototype.detectIncompleteChar=function(t){for(var e=t.length>=3?3:t.length;e>0;e--){var r=t[t.length-e];if(1==e&&r>>5==6){this.charLength=2;break}if(e<=2&&r>>4==14){this.charLength=3;break}if(e<=3&&r>>3==30){this.charLength=4;break}}this.charReceived=e},StringDecoder.prototype.end=function(t){var e="";if(t&&t.length&&(e=this.write(t)),this.charReceived){var r=this.charReceived,n=this.charBuffer,i=this.encoding;e+=n.slice(0,r).toString(i)}return e},Readable.ReadableState=ReadableState;var debug=debuglog("stream");function prependListener(t,e,r){if("function"==typeof t.prependListener)return t.prependListener(e,r);t._events&&t._events[e]?Array.isArray(t._events[e])?t._events[e].unshift(r):t._events[e]=[r,t._events[e]]:t.on(e,r)}function listenerCount$1(t,e){return t.listeners(e).length}function ReadableState(t,e){t=t||{},this.objectMode=!!t.objectMode,e instanceof Duplex&&(this.objectMode=this.objectMode||!!t.readableObjectMode);var r=t.highWaterMark,n=this.objectMode?16:16384;this.highWaterMark=r||0===r?r:n,this.highWaterMark=~~this.highWaterMark,this.buffer=new BufferList,this.length=0,this.pipes=null,this.pipesCount=0,this.flowing=null,this.ended=!1,this.endEmitted=!1,this.reading=!1,this.sync=!0,this.needReadable=!1,this.emittedReadable=!1,this.readableListening=!1,this.resumeScheduled=!1,this.defaultEncoding=t.defaultEncoding||"utf8",this.ranOut=!1,this.awaitDrain=0,this.readingMore=!1,this.decoder=null,this.encoding=null,t.encoding&&(this.decoder=new StringDecoder(t.encoding),this.encoding=t.encoding)}function Readable(t){if(!(this instanceof Readable))return new Readable(t);this._readableState=new ReadableState(t,this),this.readable=!0,t&&"function"==typeof t.read&&(this._read=t.read),EventEmitter.call(this)}function readableAddChunk(t,e,r,n,i){var o=chunkInvalid(e,r);if(o)t.emit("error",o);else if(null===r)e.reading=!1,onEofChunk(t,e);else if(e.objectMode||r&&r.length>0)if(e.ended&&!i){var s=new Error("stream.push() after EOF");t.emit("error",s)}else if(e.endEmitted&&i){var a=new Error("stream.unshift() after end event");t.emit("error",a)}else{var u;!e.decoder||i||n||(r=e.decoder.write(r),u=!e.objectMode&&0===r.length),i||(e.reading=!1),u||(e.flowing&&0===e.length&&!e.sync?(t.emit("data",r),t.read(0)):(e.length+=e.objectMode?1:r.length,i?e.buffer.unshift(r):e.buffer.push(r),e.needReadable&&emitReadable(t))),maybeReadMore(t,e)}else i||(e.reading=!1);return needMoreData(e)}function needMoreData(t){return!t.ended&&(t.needReadable||t.length<t.highWaterMark||0===t.length)}inherits$1(Readable,EventEmitter),Readable.prototype.push=function(t,e){var r=this._readableState;return r.objectMode||"string"!=typeof t||(e=e||r.defaultEncoding)!==r.encoding&&(t=Buffer.from(t,e),e=""),readableAddChunk(this,r,t,e,!1)},Readable.prototype.unshift=function(t){return readableAddChunk(this,this._readableState,t,"",!0)},Readable.prototype.isPaused=function(){return!1===this._readableState.flowing},Readable.prototype.setEncoding=function(t){return this._readableState.decoder=new StringDecoder(t),this._readableState.encoding=t,this};var MAX_HWM=8388608;function computeNewHighWaterMark(t){return t>=MAX_HWM?t=MAX_HWM:(t--,t|=t>>>1,t|=t>>>2,t|=t>>>4,t|=t>>>8,t|=t>>>16,t++),t}function howMuchToRead(t,e){return t<=0||0===e.length&&e.ended?0:e.objectMode?1:t!=t?e.flowing&&e.length?e.buffer.head.data.length:e.length:(t>e.highWaterMark&&(e.highWaterMark=computeNewHighWaterMark(t)),t<=e.length?t:e.ended?e.length:(e.needReadable=!0,0))}function chunkInvalid(t,e){var r=null;return isBuffer(e)||"string"==typeof e||null==e||t.objectMode||(r=new TypeError("Invalid non-string/buffer chunk")),r}function onEofChunk(t,e){if(!e.ended){if(e.decoder){var r=e.decoder.end();r&&r.length&&(e.buffer.push(r),e.length+=e.objectMode?1:r.length)}e.ended=!0,emitReadable(t)}}function emitReadable(t){var e=t._readableState;e.needReadable=!1,e.emittedReadable||(debug("emitReadable",e.flowing),e.emittedReadable=!0,e.sync?nextTick(emitReadable_,t):emitReadable_(t))}function emitReadable_(t){debug("emit readable"),t.emit("readable"),flow(t)}function maybeReadMore(t,e){e.readingMore||(e.readingMore=!0,nextTick(maybeReadMore_,t,e))}function maybeReadMore_(t,e){for(var r=e.length;!e.reading&&!e.flowing&&!e.ended&&e.length<e.highWaterMark&&(debug("maybeReadMore read 0"),t.read(0),r!==e.length);)r=e.length;e.readingMore=!1}function pipeOnDrain(t){return function(){var e=t._readableState;debug("pipeOnDrain",e.awaitDrain),e.awaitDrain&&e.awaitDrain--,0===e.awaitDrain&&t.listeners("data").length&&(e.flowing=!0,flow(t))}}function nReadingNextTick(t){debug("readable nexttick read 0"),t.read(0)}function resume(t,e){e.resumeScheduled||(e.resumeScheduled=!0,nextTick(resume_,t,e))}function resume_(t,e){e.reading||(debug("resume read 0"),t.read(0)),e.resumeScheduled=!1,e.awaitDrain=0,t.emit("resume"),flow(t),e.flowing&&!e.reading&&t.read(0)}function flow(t){var e=t._readableState;for(debug("flow",e.flowing);e.flowing&&null!==t.read(););}function fromList(t,e){return 0===e.length?null:(e.objectMode?r=e.buffer.shift():!t||t>=e.length?(r=e.decoder?e.buffer.join(""):1===e.buffer.length?e.buffer.head.data:e.buffer.concat(e.length),e.buffer.clear()):r=fromListPartial(t,e.buffer,e.decoder),r);var r}function fromListPartial(t,e,r){var n;return t<e.head.data.length?(n=e.head.data.slice(0,t),e.head.data=e.head.data.slice(t)):n=t===e.head.data.length?e.shift():r?copyFromBufferString(t,e):copyFromBuffer(t,e),n}function copyFromBufferString(t,e){var r=e.head,n=1,i=r.data;for(t-=i.length;r=r.next;){var o=r.data,s=t>o.length?o.length:t;if(s===o.length?i+=o:i+=o.slice(0,t),0===(t-=s)){s===o.length?(++n,r.next?e.head=r.next:e.head=e.tail=null):(e.head=r,r.data=o.slice(s));break}++n}return e.length-=n,i}function copyFromBuffer(t,e){var r=Buffer.allocUnsafe(t),n=e.head,i=1;for(n.data.copy(r),t-=n.data.length;n=n.next;){var o=n.data,s=t>o.length?o.length:t;if(o.copy(r,r.length-t,0,s),0===(t-=s)){s===o.length?(++i,n.next?e.head=n.next:e.head=e.tail=null):(e.head=n,n.data=o.slice(s));break}++i}return e.length-=i,r}function endReadable(t){var e=t._readableState;if(e.length>0)throw new Error('"endReadable()" called on non-empty stream');e.endEmitted||(e.ended=!0,nextTick(endReadableNT,e,t))}function endReadableNT(t,e){t.endEmitted||0!==t.length||(t.endEmitted=!0,e.readable=!1,e.emit("end"))}function forEach(t,e){for(var r=0,n=t.length;r<n;r++)e(t[r],r)}function indexOf(t,e){for(var r=0,n=t.length;r<n;r++)if(t[r]===e)return r;return-1}function nop(){}function WriteReq(t,e,r){this.chunk=t,this.encoding=e,this.callback=r,this.next=null}function WritableState(t,e){Object.defineProperty(this,"buffer",{get:deprecate((function(){return this.getBuffer()}),"_writableState.buffer is deprecated. Use _writableState.getBuffer instead.")}),t=t||{},this.objectMode=!!t.objectMode,e instanceof Duplex&&(this.objectMode=this.objectMode||!!t.writableObjectMode);var r=t.highWaterMark,n=this.objectMode?16:16384;this.highWaterMark=r||0===r?r:n,this.highWaterMark=~~this.highWaterMark,this.needDrain=!1,this.ending=!1,this.ended=!1,this.finished=!1;var i=!1===t.decodeStrings;this.decodeStrings=!i,this.defaultEncoding=t.defaultEncoding||"utf8",this.length=0,this.writing=!1,this.corked=0,this.sync=!0,this.bufferProcessing=!1,this.onwrite=function(t){onwrite(e,t)},this.writecb=null,this.writelen=0,this.bufferedRequest=null,this.lastBufferedRequest=null,this.pendingcb=0,this.prefinished=!1,this.errorEmitted=!1,this.bufferedRequestCount=0,this.corkedRequestsFree=new CorkedRequest(this)}function Writable(t){if(!(this instanceof Writable||this instanceof Duplex))return new Writable(t);this._writableState=new WritableState(t,this),this.writable=!0,t&&("function"==typeof t.write&&(this._write=t.write),"function"==typeof t.writev&&(this._writev=t.writev)),EventEmitter.call(this)}function writeAfterEnd(t,e){var r=new Error("write after end");t.emit("error",r),nextTick(e,r)}function validChunk(t,e,r,n){var i=!0,o=!1;return null===r?o=new TypeError("May not write null values to stream"):Buffer.isBuffer(r)||"string"==typeof r||void 0===r||e.objectMode||(o=new TypeError("Invalid non-string/buffer chunk")),o&&(t.emit("error",o),nextTick(n,o),i=!1),i}function decodeChunk(t,e,r){return t.objectMode||!1===t.decodeStrings||"string"!=typeof e||(e=Buffer.from(e,r)),e}function writeOrBuffer(t,e,r,n,i){r=decodeChunk(e,r,n),Buffer.isBuffer(r)&&(n="buffer");var o=e.objectMode?1:r.length;e.length+=o;var s=e.length<e.highWaterMark;if(s||(e.needDrain=!0),e.writing||e.corked){var a=e.lastBufferedRequest;e.lastBufferedRequest=new WriteReq(r,n,i),a?a.next=e.lastBufferedRequest:e.bufferedRequest=e.lastBufferedRequest,e.bufferedRequestCount+=1}else doWrite(t,e,!1,o,r,n,i);return s}function doWrite(t,e,r,n,i,o,s){e.writelen=n,e.writecb=s,e.writing=!0,e.sync=!0,r?t._writev(i,e.onwrite):t._write(i,o,e.onwrite),e.sync=!1}function onwriteError(t,e,r,n,i){--e.pendingcb,r?nextTick(i,n):i(n),t._writableState.errorEmitted=!0,t.emit("error",n)}function onwriteStateUpdate(t){t.writing=!1,t.writecb=null,t.length-=t.writelen,t.writelen=0}function onwrite(t,e){var r=t._writableState,n=r.sync,i=r.writecb;if(onwriteStateUpdate(r),e)onwriteError(t,r,n,e,i);else{var o=needFinish(r);o||r.corked||r.bufferProcessing||!r.bufferedRequest||clearBuffer(t,r),n?nextTick(afterWrite,t,r,o,i):afterWrite(t,r,o,i)}}function afterWrite(t,e,r,n){r||onwriteDrain(t,e),e.pendingcb--,n(),finishMaybe(t,e)}function onwriteDrain(t,e){0===e.length&&e.needDrain&&(e.needDrain=!1,t.emit("drain"))}function clearBuffer(t,e){e.bufferProcessing=!0;var r=e.bufferedRequest;if(t._writev&&r&&r.next){var n=e.bufferedRequestCount,i=new Array(n),o=e.corkedRequestsFree;o.entry=r;for(var s=0;r;)i[s]=r,r=r.next,s+=1;doWrite(t,e,!0,e.length,i,"",o.finish),e.pendingcb++,e.lastBufferedRequest=null,o.next?(e.corkedRequestsFree=o.next,o.next=null):e.corkedRequestsFree=new CorkedRequest(e)}else{for(;r;){var a=r.chunk,u=r.encoding,h=r.callback;if(doWrite(t,e,!1,e.objectMode?1:a.length,a,u,h),r=r.next,e.writing)break}null===r&&(e.lastBufferedRequest=null)}e.bufferedRequestCount=0,e.bufferedRequest=r,e.bufferProcessing=!1}function needFinish(t){return t.ending&&0===t.length&&null===t.bufferedRequest&&!t.finished&&!t.writing}function prefinish(t,e){e.prefinished||(e.prefinished=!0,t.emit("prefinish"))}function finishMaybe(t,e){var r=needFinish(e);return r&&(0===e.pendingcb?(prefinish(t,e),e.finished=!0,t.emit("finish")):prefinish(t,e)),r}function endWritable(t,e,r){e.ending=!0,finishMaybe(t,e),r&&(e.finished?nextTick(r):t.once("finish",r)),e.ended=!0,t.writable=!1}function CorkedRequest(t){var e=this;this.next=null,this.entry=null,this.finish=function(r){var n=e.entry;for(e.entry=null;n;){var i=n.callback;t.pendingcb--,i(r),n=n.next}t.corkedRequestsFree?t.corkedRequestsFree.next=e:t.corkedRequestsFree=e}}Readable.prototype.read=function(t){debug("read",t),t=parseInt(t,10);var e=this._readableState,r=t;if(0!==t&&(e.emittedReadable=!1),0===t&&e.needReadable&&(e.length>=e.highWaterMark||e.ended))return debug("read: emitReadable",e.length,e.ended),0===e.length&&e.ended?endReadable(this):emitReadable(this),null;if(0===(t=howMuchToRead(t,e))&&e.ended)return 0===e.length&&endReadable(this),null;var n,i=e.needReadable;return debug("need readable",i),(0===e.length||e.length-t<e.highWaterMark)&&debug("length less than watermark",i=!0),e.ended||e.reading?debug("reading or ended",i=!1):i&&(debug("do read"),e.reading=!0,e.sync=!0,0===e.length&&(e.needReadable=!0),this._read(e.highWaterMark),e.sync=!1,e.reading||(t=howMuchToRead(r,e))),null===(n=t>0?fromList(t,e):null)?(e.needReadable=!0,t=0):e.length-=t,0===e.length&&(e.ended||(e.needReadable=!0),r!==t&&e.ended&&endReadable(this)),null!==n&&this.emit("data",n),n},Readable.prototype._read=function(t){this.emit("error",new Error("not implemented"))},Readable.prototype.pipe=function(t,e){var r=this,n=this._readableState;switch(n.pipesCount){case 0:n.pipes=t;break;case 1:n.pipes=[n.pipes,t];break;default:n.pipes.push(t)}n.pipesCount+=1,debug("pipe count=%d opts=%j",n.pipesCount,e);var i=!e||!1!==e.end?s:h;function o(t){debug("onunpipe"),t===r&&h()}function s(){debug("onend"),t.end()}n.endEmitted?nextTick(i):r.once("end",i),t.on("unpipe",o);var a=pipeOnDrain(r);t.on("drain",a);var u=!1;function h(){debug("cleanup"),t.removeListener("close",m),t.removeListener("finish",p),t.removeListener("drain",a),t.removeListener("error",f),t.removeListener("unpipe",o),r.removeListener("end",s),r.removeListener("end",h),r.removeListener("data",l),u=!0,!n.awaitDrain||t._writableState&&!t._writableState.needDrain||a()}var c=!1;function l(e){debug("ondata"),c=!1,!1!==t.write(e)||c||((1===n.pipesCount&&n.pipes===t||n.pipesCount>1&&-1!==indexOf(n.pipes,t))&&!u&&(debug("false write response, pause",r._readableState.awaitDrain),r._readableState.awaitDrain++,c=!0),r.pause())}function f(e){debug("onerror",e),d(),t.removeListener("error",f),0===listenerCount$1(t,"error")&&t.emit("error",e)}function m(){t.removeListener("finish",p),d()}function p(){debug("onfinish"),t.removeListener("close",m),d()}function d(){debug("unpipe"),r.unpipe(t)}return r.on("data",l),prependListener(t,"error",f),t.once("close",m),t.once("finish",p),t.emit("pipe",r),n.flowing||(debug("pipe resume"),r.resume()),t},Readable.prototype.unpipe=function(t){var e=this._readableState;if(0===e.pipesCount)return this;if(1===e.pipesCount)return t&&t!==e.pipes||(t||(t=e.pipes),e.pipes=null,e.pipesCount=0,e.flowing=!1,t&&t.emit("unpipe",this)),this;if(!t){var r=e.pipes,n=e.pipesCount;e.pipes=null,e.pipesCount=0,e.flowing=!1;for(var i=0;i<n;i++)r[i].emit("unpipe",this);return this}var o=indexOf(e.pipes,t);return-1===o||(e.pipes.splice(o,1),e.pipesCount-=1,1===e.pipesCount&&(e.pipes=e.pipes[0]),t.emit("unpipe",this)),this},Readable.prototype.on=function(t,e){var r=EventEmitter.prototype.on.call(this,t,e);if("data"===t)!1!==this._readableState.flowing&&this.resume();else if("readable"===t){var n=this._readableState;n.endEmitted||n.readableListening||(n.readableListening=n.needReadable=!0,n.emittedReadable=!1,n.reading?n.length&&emitReadable(this,n):nextTick(nReadingNextTick,this))}return r},Readable.prototype.addListener=Readable.prototype.on,Readable.prototype.resume=function(){var t=this._readableState;return t.flowing||(debug("resume"),t.flowing=!0,resume(this,t)),this},Readable.prototype.pause=function(){return debug("call pause flowing=%j",this._readableState.flowing),!1!==this._readableState.flowing&&(debug("pause"),this._readableState.flowing=!1,this.emit("pause")),this},Readable.prototype.wrap=function(t){var e=this._readableState,r=!1,n=this;for(var i in t.on("end",(function(){if(debug("wrapped end"),e.decoder&&!e.ended){var t=e.decoder.end();t&&t.length&&n.push(t)}n.push(null)})),t.on("data",(function(i){(debug("wrapped data"),e.decoder&&(i=e.decoder.write(i)),e.objectMode&&null==i)||(e.objectMode||i&&i.length)&&(n.push(i)||(r=!0,t.pause()))})),t)void 0===this[i]&&"function"==typeof t[i]&&(this[i]=function(e){return function(){return t[e].apply(t,arguments)}}(i));return forEach(["error","close","destroy","pause","resume"],(function(e){t.on(e,n.emit.bind(n,e))})),n._read=function(e){debug("wrapped _read",e),r&&(r=!1,t.resume())},n},Readable._fromList=fromList,Writable.WritableState=WritableState,inherits$1(Writable,EventEmitter),WritableState.prototype.getBuffer=function(){for(var t=this.bufferedRequest,e=[];t;)e.push(t),t=t.next;return e},Writable.prototype.pipe=function(){this.emit("error",new Error("Cannot pipe, not readable"))},Writable.prototype.write=function(t,e,r){var n=this._writableState,i=!1;return"function"==typeof e&&(r=e,e=null),Buffer.isBuffer(t)?e="buffer":e||(e=n.defaultEncoding),"function"!=typeof r&&(r=nop),n.ended?writeAfterEnd(this,r):validChunk(this,n,t,r)&&(n.pendingcb++,i=writeOrBuffer(this,n,t,e,r)),i},Writable.prototype.cork=function(){this._writableState.corked++},Writable.prototype.uncork=function(){var t=this._writableState;t.corked&&(t.corked--,t.writing||t.corked||t.finished||t.bufferProcessing||!t.bufferedRequest||clearBuffer(this,t))},Writable.prototype.setDefaultEncoding=function(t){if("string"==typeof t&&(t=t.toLowerCase()),!(["hex","utf8","utf-8","ascii","binary","base64","ucs2","ucs-2","utf16le","utf-16le","raw"].indexOf((t+"").toLowerCase())>-1))throw new TypeError("Unknown encoding: "+t);return this._writableState.defaultEncoding=t,this},Writable.prototype._write=function(t,e,r){r(new Error("not implemented"))},Writable.prototype._writev=null,Writable.prototype.end=function(t,e,r){var n=this._writableState;"function"==typeof t?(r=t,t=null,e=null):"function"==typeof e&&(r=e,e=null),null!=t&&this.write(t,e),n.corked&&(n.corked=1,this.uncork()),n.ending||n.finished||endWritable(this,n,r)},inherits$1(Duplex,Readable);for(var keys=Object.keys(Writable.prototype),v=0;v<keys.length;v++){var method=keys[v];Duplex.prototype[method]||(Duplex.prototype[method]=Writable.prototype[method])}function Duplex(t){if(!(this instanceof Duplex))return new Duplex(t);Readable.call(this,t),Writable.call(this,t),t&&!1===t.readable&&(this.readable=!1),t&&!1===t.writable&&(this.writable=!1),this.allowHalfOpen=!0,t&&!1===t.allowHalfOpen&&(this.allowHalfOpen=!1),this.once("end",onend)}function onend(){this.allowHalfOpen||this._writableState.ended||nextTick(onEndNT,this)}function onEndNT(t){t.end()}function TransformState(t){this.afterTransform=function(e,r){return afterTransform(t,e,r)},this.needTransform=!1,this.transforming=!1,this.writecb=null,this.writechunk=null,this.writeencoding=null}function afterTransform(t,e,r){var n=t._transformState;n.transforming=!1;var i=n.writecb;if(!i)return t.emit("error",new Error("no writecb in Transform class"));n.writechunk=null,n.writecb=null,null!=r&&t.push(r),i(e);var o=t._readableState;o.reading=!1,(o.needReadable||o.length<o.highWaterMark)&&t._read(o.highWaterMark)}function Transform(t){if(!(this instanceof Transform))return new Transform(t);Duplex.call(this,t),this._transformState=new TransformState(this);var e=this;this._readableState.needReadable=!0,this._readableState.sync=!1,t&&("function"==typeof t.transform&&(this._transform=t.transform),"function"==typeof t.flush&&(this._flush=t.flush)),this.once("prefinish",(function(){"function"==typeof this._flush?this._flush((function(t){done(e,t)})):done(e)}))}function done(t,e){if(e)return t.emit("error",e);var r=t._writableState,n=t._transformState;if(r.length)throw new Error("Calling transform done when ws.length != 0");if(n.transforming)throw new Error("Calling transform done when still transforming");return t.push(null)}function PassThrough(t){if(!(this instanceof PassThrough))return new PassThrough(t);Transform.call(this,t)}function Stream(){EventEmitter.call(this)}inherits$1(Transform,Duplex),Transform.prototype.push=function(t,e){return this._transformState.needTransform=!1,Duplex.prototype.push.call(this,t,e)},Transform.prototype._transform=function(t,e,r){throw new Error("Not implemented")},Transform.prototype._write=function(t,e,r){var n=this._transformState;if(n.writecb=r,n.writechunk=t,n.writeencoding=e,!n.transforming){var i=this._readableState;(n.needTransform||i.needReadable||i.length<i.highWaterMark)&&this._read(i.highWaterMark)}},Transform.prototype._read=function(t){var e=this._transformState;null!==e.writechunk&&e.writecb&&!e.transforming?(e.transforming=!0,this._transform(e.writechunk,e.writeencoding,e.afterTransform)):e.needTransform=!0},inherits$1(PassThrough,Transform),PassThrough.prototype._transform=function(t,e,r){r(null,t)},inherits$1(Stream,EventEmitter),Stream.Readable=Readable,Stream.Writable=Writable,Stream.Duplex=Duplex,Stream.Transform=Transform,Stream.PassThrough=PassThrough,Stream.Stream=Stream,Stream.prototype.pipe=function(t,e){var r=this;function n(e){t.writable&&!1===t.write(e)&&r.pause&&r.pause()}function i(){r.readable&&r.resume&&r.resume()}r.on("data",n),t.on("drain",i),t._isStdio||e&&!1===e.end||(r.on("end",s),r.on("close",a));var o=!1;function s(){o||(o=!0,t.end())}function a(){o||(o=!0,"function"==typeof t.destroy&&t.destroy())}function u(t){if(h(),0===EventEmitter.listenerCount(this,"error"))throw t}function h(){r.removeListener("data",n),t.removeListener("drain",i),r.removeListener("end",s),r.removeListener("close",a),r.removeListener("error",u),t.removeListener("error",u),r.removeListener("end",h),r.removeListener("close",h),t.removeListener("close",h)}return r.on("error",u),t.on("error",u),r.on("end",h),r.on("close",h),t.on("close",h),t.emit("pipe",r),t};var stream=Object.freeze({default:Stream,Readable:Readable,Writable:Writable,Duplex:Duplex,Transform:Transform,PassThrough:PassThrough,Stream:Stream}),rStates={UNSENT:0,OPENED:1,HEADERS_RECEIVED:2,LOADING:3,DONE:4};function IncomingMessage(t,e,r){var n,i=this;if(Readable.call(i),i._mode=r,i.headers={},i.rawHeaders=[],i.trailers={},i.rawTrailers=[],i.on("end",(function(){nextTick((function(){i.emit("close")}))})),"fetch"===r){i._fetchResponse=e,i.url=e.url,i.statusCode=e.status,i.statusMessage=e.statusText;for(var o,s,a=e.headers[Symbol.iterator]();o=(s=a.next()).value,!s.done;)i.headers[o[0].toLowerCase()]=o[1],i.rawHeaders.push(o[0],o[1]);var u=e.body.getReader();(n=function(){u.read().then((function(t){i._destroyed||(t.done?i.push(null):(i.push(new Buffer(t.value)),n()))}))})()}else{if(i._xhr=t,i._pos=0,i.url=t.responseURL,i.statusCode=t.status,i.statusMessage=t.statusText,t.getAllResponseHeaders().split(/\r?\n/).forEach((function(t){var e=t.match(/^([^:]+):\s*(.*)/);if(e){var r=e[1].toLowerCase();"set-cookie"===r?(void 0===i.headers[r]&&(i.headers[r]=[]),i.headers[r].push(e[2])):void 0!==i.headers[r]?i.headers[r]+=", "+e[2]:i.headers[r]=e[2],i.rawHeaders.push(e[1],e[2])}})),i._charset="x-user-defined",!overrideMimeType){var h=i.rawHeaders["mime-type"];if(h){var c=h.match(/;\s*charset=([^;])(;|$)/);c&&(i._charset=c[1].toLowerCase())}i._charset||(i._charset="utf-8")}}}function toArrayBuffer(t){if(t instanceof Uint8Array){if(0===t.byteOffset&&t.byteLength===t.buffer.byteLength)return t.buffer;if("function"==typeof t.buffer.slice)return t.buffer.slice(t.byteOffset,t.byteOffset+t.byteLength)}if(isBuffer(t)){for(var e=new Uint8Array(t.length),r=t.length,n=0;n<r;n++)e[n]=t[n];return e.buffer}throw new Error("Argument must be a Buffer")}function decideMode(t,e){return hasFetch&&e?"fetch":mozchunkedarraybuffer?"moz-chunked-arraybuffer":msstream?"ms-stream":arraybuffer&&t?"arraybuffer":vbArray&&t?"text:vbarray":"text"}function ClientRequest(t){var e,r=this;Writable.call(r),r._opts=t,r._body=[],r._headers={},t.auth&&r.setHeader("Authorization","Basic "+new Buffer(t.auth).toString("base64")),Object.keys(t.headers).forEach((function(e){r.setHeader(e,t.headers[e])}));var n=!0;if("disable-fetch"===t.mode)n=!1,e=!0;else if("prefer-streaming"===t.mode)e=!1;else if("allow-wrong-content-type"===t.mode)e=!overrideMimeType;else{if(t.mode&&"default"!==t.mode&&"prefer-fast"!==t.mode)throw new Error("Invalid value for opts.mode");e=!0}r._mode=decideMode(e,n),r.on("finish",(function(){r._onFinish()}))}inherits$1(IncomingMessage,Readable),IncomingMessage.prototype._read=function(){},IncomingMessage.prototype._onXHRProgress=function(){var t=this,e=t._xhr,r=null;switch(t._mode){case"text:vbarray":if(e.readyState!==rStates.DONE)break;try{r=new global$1.VBArray(e.responseBody).toArray()}catch(t){}if(null!==r){t.push(new Buffer(r));break}case"text":try{r=e.responseText}catch(e){t._mode="text:vbarray";break}if(r.length>t._pos){var n=r.substr(t._pos);if("x-user-defined"===t._charset){for(var i=new Buffer(n.length),o=0;o<n.length;o++)i[o]=255&n.charCodeAt(o);t.push(i)}else t.push(n,t._charset);t._pos=r.length}break;case"arraybuffer":if(e.readyState!==rStates.DONE||!e.response)break;r=e.response,t.push(new Buffer(new Uint8Array(r)));break;case"moz-chunked-arraybuffer":if(r=e.response,e.readyState!==rStates.LOADING||!r)break;t.push(new Buffer(new Uint8Array(r)));break;case"ms-stream":if(r=e.response,e.readyState!==rStates.LOADING)break;var s=new global$1.MSStreamReader;s.onprogress=function(){s.result.byteLength>t._pos&&(t.push(new Buffer(new Uint8Array(s.result.slice(t._pos)))),t._pos=s.result.byteLength)},s.onload=function(){t.push(null)},s.readAsArrayBuffer(r)}t._xhr.readyState===rStates.DONE&&"ms-stream"!==t._mode&&t.push(null)},inherits$1(ClientRequest,Writable);var unsafeHeaders=["accept-charset","accept-encoding","access-control-request-headers","access-control-request-method","connection","content-length","cookie","cookie2","date","dnt","expect","host","keep-alive","origin","referer","te","trailer","transfer-encoding","upgrade","user-agent","via"];function statusValid(t){try{var e=t.status;return null!==e&&0!==e}catch(t){return!1}}ClientRequest.prototype.setHeader=function(t,e){var r=t.toLowerCase();-1===unsafeHeaders.indexOf(r)&&(this._headers[r]={name:t,value:e})},ClientRequest.prototype.getHeader=function(t){return this._headers[t.toLowerCase()].value},ClientRequest.prototype.removeHeader=function(t){delete this._headers[t.toLowerCase()]},ClientRequest.prototype._onFinish=function(){var t=this;if(!t._destroyed){var e,r=t._opts,n=t._headers;if("POST"!==r.method&&"PUT"!==r.method&&"PATCH"!==r.method||(e=blobConstructor()?new global$1.Blob(t._body.map((function(t){return toArrayBuffer(t)})),{type:(n["content-type"]||{}).value||""}):Buffer.concat(t._body).toString()),"fetch"===t._mode){var i=Object.keys(n).map((function(t){return[n[t].name,n[t].value]}));global$1.fetch(t._opts.url,{method:t._opts.method,headers:i,body:e,mode:"cors",credentials:r.withCredentials?"include":"same-origin"}).then((function(e){t._fetchResponse=e,t._connect()}),(function(e){t.emit("error",e)}))}else{var o=t._xhr=new global$1.XMLHttpRequest;try{o.open(t._opts.method,t._opts.url,!0)}catch(e){return void nextTick((function(){t.emit("error",e)}))}"responseType"in o&&(o.responseType=t._mode.split(":")[0]),"withCredentials"in o&&(o.withCredentials=!!r.withCredentials),"text"===t._mode&&"overrideMimeType"in o&&o.overrideMimeType("text/plain; charset=x-user-defined"),Object.keys(n).forEach((function(t){o.setRequestHeader(n[t].name,n[t].value)})),t._response=null,o.onreadystatechange=function(){switch(o.readyState){case rStates.LOADING:case rStates.DONE:t._onXHRProgress()}},"moz-chunked-arraybuffer"===t._mode&&(o.onprogress=function(){t._onXHRProgress()}),o.onerror=function(){t._destroyed||t.emit("error",new Error("XHR error"))};try{o.send(e)}catch(e){return void nextTick((function(){t.emit("error",e)}))}}}},ClientRequest.prototype._onXHRProgress=function(){var 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/*! https://mths.be/punycode v1.4.1 by @mathias */
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Transform$2.call(this,e),this._options=e||{},this.param=defParam(t),this.param._options=this._options,this.started=!1,this.recordNum=0,this.lineNumber=0,this._csvLineBuffer="",this.lastIndex=0,this.param.forked&&(this.param.forked=!1,this.workerNum=2),this.flushCb=null,this.processEnd=!1,this.sequenceBuffer=[],this._needJson=null,this._needEmitResult=null,this._needEmitFinalResult=null,this._needEmitHeader=null,this._needEmitJson=null,this._needPush=null,this._needEmitCsv=null,this._csvTransf=null,this.finalResult=[],this.on("error",emitDone(this)),this.on("end",emitDone(this)),this.initWorker(),nextTick(function(){null===this._needEmitFinalResult&&(this._needEmitFinalResult=this.listeners("end_parsed").length>0),null===this._needEmitResult&&(this._needEmitResult=this.listeners("record_parsed").length>0),null===this._needEmitJson&&(this._needEmitJson=this.listeners("json").length>0),null===this._needEmitHeader&&(this._needEmitHeader=this.listeners("header").length>0),null===this._needEmitCsv&&(this._needEmitCsv=this.listeners("csv").length>0),null===this._needJson&&(this._needJson=this._needEmitJson||this._needEmitFinalResult||this._needEmitResult||this.transform||this._options.objectMode),null===this._needPush&&(this._needPush=this.listeners("data").length>0||this.listeners("readable").length>0),this.param._needParseJson=this._needJson||this._needPush}.bind(this)),this}function emitDone(t){return function(e){t._hasDone||(t._hasDone=!0,nextTick((function(){t.emit("done",e)})))}}function bufFromString(t){var e=Buffer.byteLength(t),r=Buffer.allocUnsafe?Buffer.allocUnsafe(e):new Buffer(e);return r.write(t),r}function configIgnoreIncludeColumns(t){if(t._postIgnoreColumns){for(var e=0;e<t.ignoreColumns.length;e++){var r=t.ignoreColumns[e];if("string"==typeof r){var n=t._headers.indexOf(r);t.ignoreColumns[e]=n>-1?n:-1}}t.ignoreColumns.sort((function(t,e){return e-t}))}if(t._postIncludeColumns)for(e=0;e<t.includeColumns.length;e++){var i=t.includeColumns[e];if("string"==typeof i){n=t._headers.indexOf(i);t.includeColumns[e]=n>-1?n:-1}}t.ignoreColumns=lodash.uniq(t.ignoreColumns),t.includeColumns=lodash.uniq(t.includeColumns)}util$2.inherits(Converter,Transform$2),Converter.prototype._transform=function(t,e,r){var n=(t=this.prepareData(t)).length-1,i=null;if(128&t[n]){for(;128==(192&t[n]);)n--;n--}if(n!=t.length-1){i=t.slice(n+1),t=t.slice(0,n+1);var o=r,s=this;r=function(){s._csvLineBuffer?s._csvLineBuffer=Buffer.concat([bufFromString(s._csvLineBuffer,"utf8"),i]):s._csvLineBuffer=i,o()}}t=t.toString("utf8"),!1===this.started&&(this.started=!0,t=stripBom_1(t),this.param.toArrayString&&this._needPush&&this.push("["+eol$1,"utf8"));s=this;this.preProcessRaw(t,(function(t){t&&t.length>0?s.processData(t,r):r()}))},Converter.prototype.prepareData=function(t){return this._csvLineBuffer&&this._csvLineBuffer.length>0?("string"==typeof this._csvLineBuffer&&(this._csvLineBuffer=bufFromString(this._csvLineBuffer)),Buffer.concat([this._csvLineBuffer,t])):t},Converter.prototype.setPartialData=function(t){this._csvLineBuffer=t},Converter.prototype.processData=function(t,e){var r=this.param;r.ignoreEmpty&&!r._headers&&(t=t.trimLeft());var n=fileline(t,this.param);if(n.lines.length>0)if(this.preProcessLine&&"function"==typeof this.preProcessLine&&(n.lines=this._preProcessLines(n.lines,this.lastIndex)),r._headers)if(r.workerNum<=1){var i=fileLineToCSVLine(n,r);this.setPartialData(i.partial);var o=linesToJson(i.lines,r,this.recordNum);this.processResult(o),this.lastIndex+=o.length,this.recordNum+=o.length,e()}else this.workerProcess(n,e);else this.processHead(n,e);else this.setPartialData(n.partial),e()},Converter.prototype._preProcessLines=function(t,e){for(var r=[],n=0,i=t.length;n<i;n++){var o=this.preProcessLine(t[n],e+n+1);"string"==typeof o?r.push(o):(r.push(t[n]),this.emit("error",new Error("preProcessLine should return a string but got: "+JSON.stringify(o))))}return r},Converter.prototype.initWorker=function(){var t=this.param.workerNum-1;t>0&&(workerMgr$1=workerMgr_1,this.workerMgr=workerMgr$1(),this.workerMgr.initWorker(t,this.param))},Converter.prototype.preRawData=function(t){return this.preProcessRaw=t,this},Converter.prototype.preFileLine=function(t){return this.preProcessLine=t,this},Converter.prototype.workerProcess=function(t,e){var r=this,n=t,i=this.getEol();this.setPartialData(n.partial),this.workerMgr.sendWorker(n.lines.join(i)+i,this.lastIndex,e,(function(t,e){var n,i=r.sequenceBuffer[0];if(i.idx===e){i.result=t;for(var o=[];r.sequenceBuffer[0]&&r.sequenceBuffer[0].result;)n=r.sequenceBuffer.shift(),o=o.concat(n.result);r.processResult(o),r.recordNum+=o.length}else for(var s=0,a=r.sequenceBuffer.length;s<a;s++)if((n=r.sequenceBuffer[s]).idx===e){n.result=t;break}})),this.sequenceBuffer.push({idx:this.lastIndex,result:null}),this.lastIndex+=n.lines.length},Converter.prototype.processHead=function(t,e){var r=this.param;if(r._headers)return e();r._needFilterRow=!1;var n=t.lines,i="",o=[];if(!r.noheader)for(;n.length;){var s=i+n.shift(),a=rowSplit(s,r);if(a.closed){o=a.cols,i="";break}i=s+this.getEol()}if(r._needFilterRow=!0,!r.noheader&&0===o.length)return this.setPartialData(i),e();r.noheader?r.headers?r._headers=r.headers:r._headers=[]:r.headers?r._headers=r.headers:r._headers=o,configIgnoreIncludeColumns(r),r._headers=filterRow(r._headers,r),this._needEmitHeader&&this.param._headers&&this.emit("header",this.param._headers);n=fileLineToCSVLine(t,r);this.setPartialData(n.partial),this.param.workerNum>1&&this.workerMgr.setParams(r);var u=linesToJson(n.lines,r,0);this.processResult(u),this.lastIndex+=u.length,this.recordNum+=u.length,e()},Converter.prototype.processResult=function(t){for(var e=0,r=t.length;e<r;e++){var n=t[e];n.err?this.emit("error",n.err):this.emitResult(n)}},Converter.prototype.emitResult=function(t){var e=t.index,r=(this.param,t.row),n=t.json,i=null,o=null;"string"==typeof n?o=n:i=n,null===i&&this._needJson&&(i=JSON.parse(o),"string"==typeof r&&(r=JSON.parse(r))),this.transform&&"function"==typeof this.transform&&(this.transform(i,r,e),o=null),this._needEmitJson&&this.emit("json",i,e),this._needEmitCsv&&("string"==typeof r&&(r=JSON.parse(r)),this.emit("csv",r,e)),this.param.constructResult&&this._needEmitFinalResult&&this.finalResult.push(i),this._needEmitResult&&this.emit("record_parsed",i,r,e),this.param.toArrayString&&e>0&&this._needPush&&this.push(","+eol$1),this._options&&this._options.objectMode?this.push(i):this._needPush&&(null===o&&(o=JSON.stringify(i)),this.push(this.param.toArrayString?o:o+eol$1,"utf8"))},Converter.prototype.preProcessRaw=function(t,e){e(t)},Converter.prototype.preProcessLine=function(t,e){return t},Converter.prototype._flush=function(t){var e=this;if(this.flushCb=function(){e.emit("end_parsed",e.finalResult),e.workerMgr&&e.workerMgr.destroyWorker(),t(),e._needPush||e.emit("end")},this._csvLineBuffer.length>0){var r=this.getEol();this._csvLineBuffer[this._csvLineBuffer.length-1]!==r&&(this._csvLineBuffer+=r),this.processData(this._csvLineBuffer,function(){this.checkAndFlush()}.bind(this))}else this.checkAndFlush()},Converter.prototype.checkAndFlush=function(){0!==this._csvLineBuffer.length&&this.emit("error",CSVError_1.unclosed_quote(this.recordNum,this._csvLineBuffer),this._csvLineBuffer),this.param.toArrayString&&this._needPush&&this.push(eol$1+"]","utf8"),this.workerMgr&&this.workerMgr.isRunning()?this.workerMgr.drain=function(){this.flushCb()}.bind(this):this.flushCb()},Converter.prototype.getEol=function(t){if(!this.param.eol&&t){for(var e=0,r=t.length;e<r;e++){if("\r"===t[e])return"\n"===t[e+1]?this.param.eol="\r\n":this.param.eol="\r",this.param.eol;if("\n"===t[e])return this.param.eol="\n",this.param.eol}this.param.eol=eol$1}return this.param.eol||eol$1},Converter.prototype.fromFile=function(t,e,r){var n=require$$0$2,i=null;return"object"==typeof e&&void 0===r&&(r=e,e=null),this.wrapCallback(e,(function(){i&&i.destroy&&i.destroy()})),n.exists(t,function(e){e?(i=n.createReadStream(t,r)).pipe(this):this.emit("error",new Error("File not exists"))}.bind(this)),this},Converter.prototype.fromStream=function(t,e){return e&&"function"==typeof e&&this.wrapCallback(e),t.pipe(this),this},Converter.prototype.transf=function(t){return this.transform=t,this},Converter.prototype.fromString=function(t,e){return"string"!=typeof t&&e&&"function"==typeof e?e(new Error("Passed CSV Data is not a string.")):(e&&"function"==typeof e&&this.wrapCallback(e,(function(){})),nextTick(function(){this.end(t)}.bind(this)),this)},Converter.prototype.wrapCallback=function(t,e){void 0===e&&(e=function(){}),t&&"function"==typeof t&&this.once("end_parsed",function(e){this.hasError||t(null,e)}.bind(this)),this.once("error",function(r){this.hasError=!0,t&&"function"==typeof t&&t(r),e()}.bind(this))};var Converter_1=Converter,core=createCommonjsModule((function(t){t.exports=function(e,r){return new t.exports.Converter(e,r)},t.exports.Converter=Converter_1})),core_1=core.Converter,http$2=http$1&&http||http$1;function startWebServer(t){var e={port:(t=t||{}).port||"8801",urlpath:t.urlpath||"/parseCSV"},r=http$2.createServer();return r.on("request",(function(t,r){t.url===e.urlpath&&"POST"===t.method?t.pipe(new Converter_1({constructResult:!1})).pipe(r):r.end("Please post data to: "+e.urlpath)})),r.listen(e.port),console.log("CSV Web Server Listen On:"+e.port),console.log("POST to "+e.urlpath+" with CSV data to get parsed."),r}var startWebServer_1=startWebServer,webServer={startWebServer:startWebServer_1},web=webServer;function _initConverter(){var t=new Converter_1,e=!1,r=process.stdout;return t.on("record_parsed",(function(t){e&&r.write(",\n"),r.write(JSON.stringify(t)),!1===e&&(e=!0)})),r.write("[\n"),t.on("end_parsed",(function(){r.write("\n]")})),t.on("error",(function(t){console.error(t),process.exit(-1)})),t}function convertFile(t){_initConverter().from(t)}function convertString(t){_initConverter().from(t)}var convertFile_1=convertFile,convertString_1=convertString,main$1={convertFile:convertFile_1,convertString:convertString_1},cli=main$1,web$1=web,cli$1=cli,interfaces={web:web$1,cli:cli$1},core$1=core,csv2json=core,interfaces$1=interfaces;csv2json.core=core$1,csv2json.interfaces=interfaces$1;var csvtojson=csv2json;async function loadCSVURI(t,e){const r=(t.search("https","gi"),get);return new Promise(((n,i)=>{const o=[],s=Object.assign({checkType:!0},e),a=r(t,(t=>{csvtojson(s).fromStream(t).on("json",(t=>{o.push(t)})).on("error",(t=>i(t))).on("done",(t=>t?i(t):n(o)))}));a.on("error",i)}))}async function loadCSV(t,e){return validUrl.isUri(t)?loadCSVURI(t,e):new Promise(((r,n)=>{const i=[],o=Object.assign({checkType:!0},e);csvtojson(o).fromFile(t).on("json",(t=>{i.push(t)})).on("error",(t=>n(t))).on("done",(t=>t?n(t):r(i)))}))}async function loadTSV(t,e){return loadCSV(t,Object.assign({checkType:!0},e,{delimiter:"\t"}))}var csvUtils=Object.freeze({loadCSVURI:loadCSVURI,loadCSV:loadCSV,loadTSV:loadTSV});Symbol.species||(Symbol.species=Symbol.for("@@species"));class LuDecomposition$$1{constructor(t){var e,r,n,i,o,s,a,u,h,c=(t=WrapperMatrix2D.checkMatrix(t)).clone(),l=c.rows,f=c.columns,m=new Array(l),p=1;for(e=0;e<l;e++)m[e]=e;for(u=new Array(l),r=0;r<f;r++){for(e=0;e<l;e++)u[e]=c.get(e,r);for(e=0;e<l;e++){for(h=Math.min(e,r),o=0,n=0;n<h;n++)o+=c.get(e,n)*u[n];u[e]-=o,c.set(e,r,u[e])}for(i=r,e=r+1;e<l;e++)Math.abs(u[e])>Math.abs(u[i])&&(i=e);if(i!==r){for(n=0;n<f;n++)s=c.get(i,n),c.set(i,n,c.get(r,n)),c.set(r,n,s);a=m[i],m[i]=m[r],m[r]=a,p=-p}if(r<l&&0!==c.get(r,r))for(e=r+1;e<l;e++)c.set(e,r,c.get(e,r)/c.get(r,r))}this.LU=c,this.pivotVector=m,this.pivotSign=p}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=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,n,i,o=t.columns,s=t.subMatrixRow(this.pivotVector,0,o-1),a=e.columns;for(i=0;i<a;i++)for(r=i+1;r<a;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i];for(i=a-1;i>=0;i--){for(n=0;n<o;n++)s[i][n]/=e[i][i];for(r=0;r<i;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i]}return s}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,n=new Matrix(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i>o?t[i][o]:i===o?1:0;return n}get upperTriangularMatrix(){for(var t=this.LU,e=t.rows,r=t.columns,n=new Matrix(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i<=o?t[i][o]:0;return n}get pivotPermutationVector(){return this.pivotVector.slice()}}function hypotenuse(t,e){var r=0;return Math.abs(t)>Math.abs(e)?(r=e/t,Math.abs(t)*Math.sqrt(1+r*r)):0!==e?(r=t/e,Math.abs(e)*Math.sqrt(1+r*r)):0}function getFilled2DArray(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}class SingularValueDecomposition$$1{constructor(t,e={}){var r=(t=WrapperMatrix2D.checkMatrix(t)).rows,n=t.columns,i=Math.min(r,n);const{computeLeftSingularVectors:o=!0,computeRightSingularVectors:s=!0,autoTranspose:a=!1}=e;var u,h=Boolean(o),c=Boolean(s),l=!1;if(r<n)if(a){r=(u=t.transpose()).rows,n=u.columns,l=!0;var f=h;h=c,c=f}else u=t.clone(),console.warn("Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose");else u=t.clone();var m,p,d,g,v,w,y,b,x,M,_,$,S,R,E,C,k,A,T,O,I,D=new Array(Math.min(r+1,n)),P=getFilled2DArray(r,i,0),V=getFilled2DArray(n,n,0),j=new Array(n),L=new Array(r),N=Math.min(r-1,n),B=Math.max(0,Math.min(n-2,r));for(d=0,M=Math.max(N,B);d<M;d++){if(d<N){for(D[d]=0,m=d;m<r;m++)D[d]=hypotenuse(D[d],u[m][d]);if(0!==D[d]){for(u[d][d]<0&&(D[d]=-D[d]),m=d;m<r;m++)u[m][d]/=D[d];u[d][d]+=1}D[d]=-D[d]}for(p=d+1;p<n;p++){if(d<N&&0!==D[d]){for(v=0,m=d;m<r;m++)v+=u[m][d]*u[m][p];for(v=-v/u[d][d],m=d;m<r;m++)u[m][p]+=v*u[m][d]}j[p]=u[d][p]}if(h&&d<N)for(m=d;m<r;m++)P[m][d]=u[m][d];if(d<B){for(j[d]=0,m=d+1;m<n;m++)j[d]=hypotenuse(j[d],j[m]);if(0!==j[d]){for(j[d+1]<0&&(j[d]=0-j[d]),m=d+1;m<n;m++)j[m]/=j[d];j[d+1]+=1}if(j[d]=-j[d],d+1<r&&0!==j[d]){for(m=d+1;m<r;m++)L[m]=0;for(p=d+1;p<n;p++)for(m=d+1;m<r;m++)L[m]+=j[p]*u[m][p];for(p=d+1;p<n;p++)for(v=-j[p]/j[d+1],m=d+1;m<r;m++)u[m][p]+=v*L[m]}if(c)for(m=d+1;m<n;m++)V[m][d]=j[m]}}if(g=Math.min(n,r+1),N<n&&(D[N]=u[N][N]),r<g&&(D[g-1]=0),B+1<g&&(j[B]=u[B][g-1]),j[g-1]=0,h){for(p=N;p<i;p++){for(m=0;m<r;m++)P[m][p]=0;P[p][p]=1}for(d=N-1;d>=0;d--)if(0!==D[d]){for(p=d+1;p<i;p++){for(v=0,m=d;m<r;m++)v+=P[m][d]*P[m][p];for(v=-v/P[d][d],m=d;m<r;m++)P[m][p]+=v*P[m][d]}for(m=d;m<r;m++)P[m][d]=-P[m][d];for(P[d][d]=1+P[d][d],m=0;m<d-1;m++)P[m][d]=0}else{for(m=0;m<r;m++)P[m][d]=0;P[d][d]=1}}if(c)for(d=n-1;d>=0;d--){if(d<B&&0!==j[d])for(p=d+1;p<n;p++){for(v=0,m=d+1;m<n;m++)v+=V[m][d]*V[m][p];for(v=-v/V[d+1][d],m=d+1;m<n;m++)V[m][p]+=v*V[m][d]}for(m=0;m<n;m++)V[m][d]=0;V[d][d]=1}for(var F=g-1,z=Number.EPSILON;g>0;){for(d=g-2;d>=-1&&-1!==d;d--)if(Math.abs(j[d])<=z*(Math.abs(D[d])+Math.abs(D[d+1]))){j[d]=0;break}if(d===g-2)_=4;else{for(w=g-1;w>=d&&w!==d;w--)if(v=(w!==g?Math.abs(j[w]):0)+(w!==d+1?Math.abs(j[w-1]):0),Math.abs(D[w])<=z*v){D[w]=0;break}w===d?_=3:w===g-1?_=1:(_=2,d=w)}switch(d++,_){case 1:for(y=j[g-2],j[g-2]=0,p=g-2;p>=d;p--)if(v=hypotenuse(D[p],y),b=D[p]/v,x=y/v,D[p]=v,p!==d&&(y=-x*j[p-1],j[p-1]=b*j[p-1]),c)for(m=0;m<n;m++)v=b*V[m][p]+x*V[m][g-1],V[m][g-1]=-x*V[m][p]+b*V[m][g-1],V[m][p]=v;break;case 2:for(y=j[d-1],j[d-1]=0,p=d;p<g;p++)if(v=hypotenuse(D[p],y),b=D[p]/v,x=y/v,D[p]=v,y=-x*j[p],j[p]=b*j[p],h)for(m=0;m<r;m++)v=b*P[m][p]+x*P[m][d-1],P[m][d-1]=-x*P[m][p]+b*P[m][d-1],P[m][p]=v;break;case 3:for($=Math.max(Math.abs(D[g-1]),Math.abs(D[g-2]),Math.abs(j[g-2]),Math.abs(D[d]),Math.abs(j[d])),S=D[g-1]/$,R=D[g-2]/$,E=j[g-2]/$,C=D[d]/$,k=j[d]/$,T=S*E*(S*E),O=0,0===(A=((R+S)*(R-S)+E*E)/2)&&0===T||(O=Math.sqrt(A*A+T),A<0&&(O=-O),O=T/(A+O)),y=(C+S)*(C-S)+O,I=C*k,p=d;p<g-1;p++){if(b=y/(v=hypotenuse(y,I)),x=I/v,p!==d&&(j[p-1]=v),y=b*D[p]+x*j[p],j[p]=b*j[p]-x*D[p],I=x*D[p+1],D[p+1]=b*D[p+1],c)for(m=0;m<n;m++)v=b*V[m][p]+x*V[m][p+1],V[m][p+1]=-x*V[m][p]+b*V[m][p+1],V[m][p]=v;if(b=y/(v=hypotenuse(y,I)),x=I/v,D[p]=v,y=b*j[p]+x*D[p+1],D[p+1]=-x*j[p]+b*D[p+1],I=x*j[p+1],j[p+1]=b*j[p+1],h&&p<r-1)for(m=0;m<r;m++)v=b*P[m][p]+x*P[m][p+1],P[m][p+1]=-x*P[m][p]+b*P[m][p+1],P[m][p]=v}j[g-2]=y;break;case 4:if(D[d]<=0&&(D[d]=D[d]<0?-D[d]:0,c))for(m=0;m<=F;m++)V[m][d]=-V[m][d];for(;d<F&&!(D[d]>=D[d+1]);){if(v=D[d],D[d]=D[d+1],D[d+1]=v,c&&d<n-1)for(m=0;m<n;m++)v=V[m][d+1],V[m][d+1]=V[m][d],V[m][d]=v;if(h&&d<r-1)for(m=0;m<r;m++)v=P[m][d+1],P[m][d+1]=P[m][d],P[m][d]=v;d++}g--}}if(l){var q=V;V=P,P=q}this.m=r,this.n=n,this.s=D,this.U=P,this.V=V}solve(t){var e,r=t,n=this.threshold,i=this.s.length,o=Matrix.zeros(i,i);for(e=0;e<i;e++)Math.abs(this.s[e])<=n?o[e][e]=0:o[e][e]=1/this.s[e];var s,a,u,h=this.U,c=this.rightSingularVectors,l=c.mmul(o),f=c.rows,m=h.length,p=Matrix.zeros(f,m);for(e=0;e<f;e++)for(s=0;s<m;s++){for(u=0,a=0;a<i;a++)u+=l[e][a]*h[s][a];p[e][s]=u}return p.mmul(r)}solveForDiagonal(t){return this.solve(Matrix.diag(t))}inverse(){var t,e,r=this.V,n=this.threshold,i=r.length,o=r[0].length,s=new Matrix(i,this.s.length);for(t=0;t<i;t++)for(e=0;e<o;e++)Math.abs(this.s[e])>n?s[t][e]=r[t][e]/this.s[e]:s[t][e]=0;var a,u,h=this.U,c=h.length,l=h[0].length,f=new Matrix(i,c);for(t=0;t<i;t++)for(e=0;e<c;e++){for(u=0,a=0;a<l;a++)u+=s[t][a]*h[e][a];f[t][e]=u}return f}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 Matrix.isMatrix(this.U)||(this.U=new Matrix(this.U)),this.U}get rightSingularVectors(){return Matrix.isMatrix(this.V)||(this.V=new Matrix(this.V)),this.V}get diagonalMatrix(){return Matrix.diag(this.s)}}function max(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=t[0],r=1;r<t.length;r++)t[r]>e&&(e=t[r]);return e}function min(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=t[0],r=1;r<t.length;r++)t[r]<e&&(e=t[r]);return e}function rescale(t,e={}){if(!Array.isArray(t))throw new TypeError("input must be an array");if(0===t.length)throw new TypeError("input must not be empty");let r;if(void 0!==e.output){if(!Array.isArray(e.output))throw new TypeError("output option must be an array if specified");r=e.output}else r=new Array(t.length);const n=min(t),i=max(t);if(n===i)throw new RangeError("minimum and maximum input values are equal. Cannot rescale a constant array");const{min:o=(e.autoMinMax?n:0),max:s=(e.autoMinMax?i:1)}=e;if(o>=s)throw new RangeError("min option must be smaller than max option");const a=(s-o)/(i-n);for(var u=0;u<t.length;u++)r[u]=(t[u]-n)*a+o;return r}function checkRowIndex(t,e,r){var n=r?t.rows:t.rows-1;if(e<0||e>n)throw new RangeError("Row index out of range")}function checkColumnIndex(t,e,r){var n=r?t.columns:t.columns-1;if(e<0||e>n)throw new RangeError("Column index out of range")}function checkRowVector(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.columns)throw new RangeError("vector size must be the same as the number of columns");return e}function checkColumnVector(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.rows)throw new RangeError("vector size must be the same as the number of rows");return e}function checkIndices(t,e,r){return{row:checkRowIndices(t,e),column:checkColumnIndices(t,r)}}function checkRowIndices(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for row indices");if(e.some((e=>e<0||e>=t.rows)))throw new RangeError("row indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkColumnIndices(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for column indices");var r=e.some((e=>e<0||e>=t.columns));if(r)throw new RangeError("column indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkRange(t,e,r,n,i){if(5!==arguments.length)throw new TypeError("Invalid argument type");if(Array.from(arguments).slice(1).some((function(t){return"number"!=typeof t})))throw new TypeError("Invalid argument type");if(e>r||n>i||e<0||e>=t.rows||r<0||r>=t.rows||n<0||n>=t.columns||i<0||i>=t.columns)throw new RangeError("Submatrix indices are out of range")}function sumByRow(t){for(var e=Matrix.zeros(t.rows,1),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(r,0,e.get(r,0)+t.get(r,n));return e}function sumByColumn(t){for(var e=Matrix.zeros(1,t.columns),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(0,n,e.get(0,n)+t.get(r,n));return e}function sumAll(t){for(var e=0,r=0;r<t.rows;r++)for(var n=0;n<t.columns;n++)e+=t.get(r,n);return e}class BaseView extends(AbstractMatrix()){constructor(t,e,r){super(),this.matrix=t,this.rows=e,this.columns=r}static get[Symbol.species](){return Matrix}}class MatrixTransposeView extends BaseView{constructor(t){super(t,t.columns,t.rows)}set(t,e,r){return this.matrix.set(e,t,r),this}get(t,e){return this.matrix.get(e,t)}}class MatrixRowView extends BaseView{constructor(t,e){super(t,1,t.columns),this.row=e}set(t,e,r){return this.matrix.set(this.row,e,r),this}get(t,e){return this.matrix.get(this.row,e)}}class MatrixSubView extends BaseView{constructor(t,e,r,n,i){checkRange(t,e,r,n,i),super(t,r-e+1,i-n+1),this.startRow=e,this.startColumn=n}set(t,e,r){return this.matrix.set(this.startRow+t,this.startColumn+e,r),this}get(t,e){return this.matrix.get(this.startRow+t,this.startColumn+e)}}class MatrixSelectionView extends BaseView{constructor(t,e,r){var n=checkIndices(t,e,r);super(t,n.row.length,n.column.length),this.rowIndices=n.row,this.columnIndices=n.column}set(t,e,r){return this.matrix.set(this.rowIndices[t],this.columnIndices[e],r),this}get(t,e){return this.matrix.get(this.rowIndices[t],this.columnIndices[e])}}class MatrixRowSelectionView extends BaseView{constructor(t,e){super(t,(e=checkRowIndices(t,e)).length,t.columns),this.rowIndices=e}set(t,e,r){return this.matrix.set(this.rowIndices[t],e,r),this}get(t,e){return this.matrix.get(this.rowIndices[t],e)}}class MatrixColumnSelectionView extends BaseView{constructor(t,e){e=checkColumnIndices(t,e),super(t,t.rows,e.length),this.columnIndices=e}set(t,e,r){return this.matrix.set(t,this.columnIndices[e],r),this}get(t,e){return this.matrix.get(t,this.columnIndices[e])}}class MatrixColumnView extends BaseView{constructor(t,e){super(t,t.rows,1),this.column=e}set(t,e,r){return this.matrix.set(t,this.column,r),this}get(t){return this.matrix.get(t,this.column)}}class MatrixFlipRowView extends BaseView{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(this.rows-t-1,e,r),this}get(t,e){return this.matrix.get(this.rows-t-1,e)}}class MatrixFlipColumnView extends BaseView{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(t,this.columns-e-1,r),this}get(t,e){return this.matrix.get(t,this.columns-e-1)}}function AbstractMatrix(t){void 0===t&&(t=Object);class e extends t{static get[Symbol.species](){return this}static from1DArray(t,e,r){if(t*e!==r.length)throw new RangeError("Data length does not match given dimensions");for(var n=new this(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r[i*e+o]);return n}static rowVector(t){for(var e=new this(1,t.length),r=0;r<t.length;r++)e.set(0,r,t[r]);return e}static columnVector(t){for(var e=new this(t.length,1),r=0;r<t.length;r++)e.set(r,0,t[r]);return e}static empty(t,e){return new this(t,e)}static zeros(t,e){return this.empty(t,e).fill(0)}static ones(t,e){return this.empty(t,e).fill(1)}static rand(t,e,r){void 0===r&&(r=Math.random);for(var n=this.empty(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r());return n}static randInt(t,e,r,n){void 0===r&&(r=1e3),void 0===n&&(n=Math.random);for(var i=this.empty(t,e),o=0;o<t;o++)for(var s=0;s<e;s++){var a=Math.floor(n()*r);i.set(o,s,a)}return i}static eye(t,e,r){void 0===e&&(e=t),void 0===r&&(r=1);for(var n=Math.min(t,e),i=this.zeros(t,e),o=0;o<n;o++)i.set(o,o,r);return i}static diag(t,e,r){var n=t.length;void 0===e&&(e=n),void 0===r&&(r=e);for(var i=Math.min(n,e,r),o=this.zeros(e,r),s=0;s<i;s++)o.set(s,s,t[s]);return o}static min(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.min(t.get(o,s),e.get(o,s)));return i}static max(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.max(t.get(o,s),e.get(o,s)));return i}static checkMatrix(t){return e.isMatrix(t)?t:new this(t)}static isMatrix(t){return null!=t&&"Matrix"===t.klass}get size(){return this.rows*this.columns}apply(t){if("function"!=typeof t)throw new TypeError("callback must be a function");for(var e=this.rows,r=this.columns,n=0;n<e;n++)for(var i=0;i<r;i++)t.call(this,n,i);return this}to1DArray(){for(var t=new Array(this.size),e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t[e*this.columns+r]=this.get(e,r);return t}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}isRowVector(){return 1===this.rows}isColumnVector(){return 1===this.columns}isVector(){return 1===this.rows||1===this.columns}isSquare(){return this.rows===this.columns}isSymmetric(){if(this.isSquare()){for(var t=0;t<this.rows;t++)for(var e=0;e<=t;e++)if(this.get(t,e)!==this.get(e,t))return!1;return!0}return!1}set(t,e,r){throw new Error("set method is unimplemented")}get(t,e){throw new Error("get method is unimplemented")}repeat(t,e){t=t||1,e=e||1;for(var r=new this.constructor[Symbol.species](this.rows*t,this.columns*e),n=0;n<t;n++)for(var i=0;i<e;i++)r.setSubMatrix(this,this.rows*n,this.columns*i);return r}fill(t){for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,t);return this}neg(){return this.mulS(-1)}getRow(t){checkRowIndex(this,t);for(var e=new Array(this.columns),r=0;r<this.columns;r++)e[r]=this.get(t,r);return e}getRowVector(t){return this.constructor.rowVector(this.getRow(t))}setRow(t,e){checkRowIndex(this,t),e=checkRowVector(this,e);for(var r=0;r<this.columns;r++)this.set(t,r,e[r]);return this}swapRows(t,e){checkRowIndex(this,t),checkRowIndex(this,e);for(var r=0;r<this.columns;r++){var n=this.get(t,r);this.set(t,r,this.get(e,r)),this.set(e,r,n)}return this}getColumn(t){checkColumnIndex(this,t);for(var e=new Array(this.rows),r=0;r<this.rows;r++)e[r]=this.get(r,t);return e}getColumnVector(t){return this.constructor.columnVector(this.getColumn(t))}setColumn(t,e){checkColumnIndex(this,t),e=checkColumnVector(this,e);for(var r=0;r<this.rows;r++)this.set(r,t,e[r]);return this}swapColumns(t,e){checkColumnIndex(this,t),checkColumnIndex(this,e);for(var r=0;r<this.rows;r++){var n=this.get(r,t);this.set(r,t,this.get(r,e)),this.set(r,e,n)}return this}addRowVector(t){t=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}subRowVector(t){t=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=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=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=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=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=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=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){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){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){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){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){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){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){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){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){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){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 sumByRow(this);case"column":return sumByColumn(this);default:return 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);const 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),c=(r+u)*(n+h),l=(s+u)*n,f=r*(o-h),m=u*(a-n),p=(r+i)*h,d=c+m-p+(i-u)*(a+h),g=f+p,v=l+m,w=c-l+f+(s-r)*(n+o);return e.set(0,0,d),e.set(0,1,g),e.set(1,0,v),e.set(1,1,w),e}strassen3x3(t){var e=new this.constructor[Symbol.species](3,3);const 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),c=this.get(2,2),l=t.get(0,0),f=t.get(0,1),m=t.get(0,2),p=t.get(1,0),d=t.get(1,1),g=t.get(1,2),v=t.get(2,0),w=t.get(2,1),y=t.get(2,2),b=(r-o)*(-f+d),x=(-r+o+s)*(l-f+d),M=(o+s)*(-l+f),_=r*l,$=(-r+u+h)*(l-m+g),S=(-r+u)*(m-g),R=(u+h)*(-l+m),E=(-i+h+c)*(d+v-w),C=(i-c)*(d-w),k=i*v,A=(h+c)*(-v+w),T=(-i+s+a)*(g+v-y),O=(i-a)*(g-y),I=(s+a)*(-v+y),D=_+k+n*p,P=(r+n+i-o-s-h-c)*d+x+M+_+E+k+A,V=_+$+R+(r+n+i-s-a-u-h)*g+k+T+I,j=b+s*(-l+f+p-d-g-v+y)+x+_+k+T+O,L=b+x+M+_+a*w,N=k+T+O+I+o*m,B=_+$+S+h*(-l+m+p-d-g-v+w)+E+C+k,F=E+C+k+A+u*f,z=_+$+S+R+c*y;return e.set(0,0,D),e.set(0,1,P),e.set(0,2,V),e.set(1,0,j),e.set(1,1,L),e.set(1,2,N),e.set(2,0,B),e.set(2,1,F),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 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),u=parseInt(r.columns/2),h=r.subMatrix(0,s-1,0,u-1),c=n.subMatrix(0,s-1,0,u-1),l=r.subMatrix(0,s-1,u,r.columns-1),f=n.subMatrix(0,s-1,u,n.columns-1),m=r.subMatrix(s,r.rows-1,0,u-1),p=n.subMatrix(s,n.rows-1,0,u-1),d=r.subMatrix(s,r.rows-1,u,r.columns-1),g=n.subMatrix(s,n.rows-1,u,n.columns-1),v=t(e.add(h,d),e.add(c,g),s,u),w=t(e.add(m,d),c,s,u),y=t(h,e.sub(f,g),s,u),b=t(d,e.sub(p,c),s,u),x=t(e.add(h,l),g,s,u),M=t(e.sub(m,h),e.add(c,f),s,u),_=t(e.sub(l,d),e.add(p,g),s,u),$=e.add(v,b);$.sub(x),$.add(_);var S=e.add(y,x),R=e.add(w,b),E=e.sub(v,w);E.add(y),E.add(M);var C=e.zeros(2*$.rows,2*$.columns);return(C=(C=(C=(C=C.setSubMatrix($,0,0)).setSubMatrix(S,$.rows,0)).setSubMatrix(R,0,$.columns)).setSubMatrix(E,$.rows,$.columns)).subMatrix(0,i-1,0,o-1)}(r=a(r,u,h),t=a(t,u,h),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),n=0;n<this.rows;n++){var i=rescale(this.getRow(n),{min:t,max:e});r.setRow(n,i)}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),n=0;n<this.columns;n++){var i=rescale(this.getColumn(n),{min:t,max:e});r.setColumn(n,i)}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){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 s=r;s<=n;s++)i[o-t][s-r]=this.get(o,s);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){checkRange(this,e,e+(t=this.constructor.checkMatrix(t)).rows-1,r,r+t.columns-1);for(var n=0;n<t.rows;n++)for(var i=0;i<t.columns;i++)this[e+n][r+i]=t.get(n,i);return this}selection(t,e){for(var r=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],s=0;s<r.column.length;s++){var a=r.column[s];n[i][s]=this.get(o,a)}return n}trace(){for(var t=Math.min(this.rows,this.columns),e=0,r=0;r<t;r++)e+=this.get(r,r);return e}transposeView(){return new MatrixTransposeView(this)}rowView(t){return checkRowIndex(this,t),new MatrixRowView(this,t)}columnView(t){return checkColumnIndex(this,t),new MatrixColumnView(this,t)}flipRowView(){return new MatrixFlipRowView(this)}flipColumnView(){return new MatrixFlipColumnView(this)}subMatrixView(t,e,r,n){return new MatrixSubView(this,t,e,r,n)}selectionView(t,e){return new MatrixSelectionView(this,t,e)}rowSelectionView(t){return new MatrixRowSelectionView(this,t)}columnSelectionView(t){return new MatrixColumnSelectionView(this,t)}det(){var t,e,r,n,i,o;if(this.isSquare())return 2===this.columns?(t=this.get(0,0),e=this.get(0,1),r=this.get(1,0),t*this.get(1,1)-e*r):3===this.columns?(n=this.selectionView([1,2],[1,2]),i=this.selectionView([1,2],[0,2]),o=this.selectionView([1,2],[0,1]),t=this.get(0,0),e=this.get(0,1),r=this.get(0,2),t*n.det()-e*i.det()+r*o.det()):new LuDecomposition$$1(this).determinant;throw Error("Determinant can only be calculated for a square matrix.")}pseudoInverse(t){void 0===t&&(t=Number.EPSILON);for(var e=new SingularValueDecomposition$$1(this,{autoTranspose:!0}),r=e.leftSingularVectors,n=e.rightSingularVectors,i=e.diagonal,o=0;o<i.length;o++)Math.abs(i[o])>t?i[o]=1/i[o]:i[o]=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 n,i="\n(function %name%(matrix, %args%) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(%args%);\n})\n",o=i,s=eval;for(var a of[["+","add"],["-","sub","subtract"],["*","mul","multiply"],["/","div","divide"],["%","mod","modulus"],["&","and"],["|","or"],["^","xor"],["<<","leftShift"],[">>","signPropagatingRightShift"],[">>>","rightShift","zeroFillRightShift"]]){var u=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",{name:a[1],op:a[0]})),h=s(S("\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, this.get(i, j) %op% value);\n        }\n    }\n    return this;\n})\n",{name:a[1]+"S",op:a[0]})),c=s(S("\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, this.get(i, j) %op% matrix.get(i, j));\n        }\n    }\n    return this;\n})\n",{name:a[1]+"M",op:a[0]})),l=s(S("\n(function %name%(matrix, value) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(value);\n})\n",{name:a[1]}));for(n=1;n<a.length;n++)e.prototype[a[n]]=u,e.prototype[a[n]+"S"]=h,e.prototype[a[n]+"M"]=c,e[a[n]]=l}var f=[["~","not"]];for(var m 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){f.push(["Math."+t,t])})),f)){var p=s(S("\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:m[1],method:m[0]})),d=s(S("\n(function %name%(matrix) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%();\n})\n",{name:m[1]}));for(n=1;n<m.length;n++)e.prototype[m[n]]=p,e[m[n]]=d}for(var g of[["Math.pow",1,"pow"]]){var v="arg0";for(n=1;n<g[1];n++)v+=`, arg${n}`;if(1!==g[1]){var w=s(S("\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:g[2],method:g[0],args:v})),y=s(S(i,{name:g[2],args:v}));for(n=2;n<g.length;n++)e.prototype[g[n]]=w,e[g[n]]=y}else{var b={name:g[2],args:v,method:g[0]},x=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",b)),M=s(S("\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",b)),_=s(S("\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",b)),$=s(S(o,b));for(n=2;n<g.length;n++)e.prototype[g[n]]=x,e.prototype[g[n]+"M"]=_,e.prototype[g[n]+"S"]=M,e[g[n]]=$}}function S(t,e){for(var r in e)t=t.replace(new RegExp("%"+r+"%","g"),e[r]);return t}return e}class Matrix extends(AbstractMatrix(Array)){constructor(t,e){var r;if(1===arguments.length&&"number"==typeof t)return new Array(t);if(Matrix.isMatrix(t))return t.clone();if(Number.isInteger(t)&&t>0){if(super(t),!(Number.isInteger(e)&&e>0))throw new TypeError("nColumns must be a positive integer");for(r=0;r<t;r++)this[r]=new Array(e)}else{if(!Array.isArray(t))throw new TypeError("First argument must be a positive number or an array");{const n=t;if(t=n.length,"number"!=typeof(e=n[0].length)||0===e)throw new TypeError("Data must be a 2D array with at least one element");for(super(t),r=0;r<t;r++){if(n[r].length!==e)throw new RangeError("Inconsistent array dimensions");this[r]=[].concat(n[r])}}}return this.rows=t,this.columns=e,this}set(t,e,r){return this[t][e]=r,this}get(t,e){return this[t][e]}removeRow(t){if(checkRowIndex(this,t),1===this.rows)throw new RangeError("A matrix cannot have less than one row");return this.splice(t,1),this.rows-=1,this}addRow(t,e){return void 0===e&&(e=t,t=this.rows),checkRowIndex(this,t,!0),e=checkRowVector(this,e,!0),this.splice(t,0,e),this.rows+=1,this}removeColumn(t){if(checkColumnIndex(this,t),1===this.columns)throw new RangeError("A matrix cannot have less than one column");for(var e=0;e<this.rows;e++)this[e].splice(t,1);return this.columns-=1,this}addColumn(t,e){void 0===e&&(e=t,t=this.columns),checkColumnIndex(this,t,!0),e=checkColumnVector(this,e);for(var r=0;r<this.rows;r++)this[r].splice(t,0,e[r]);return this.columns+=1,this}}class WrapperMatrix1D extends(AbstractMatrix()){constructor(t,e={}){const{rows:r=1}=e;if(t.length%r!=0)throw new Error("the data length is not divisible by the number of rows");super(),this.rows=r,this.columns=t.length/r,this.data=t}set(t,e,r){var n=this._calculateIndex(t,e);return this.data[n]=r,this}get(t,e){var r=this._calculateIndex(t,e);return this.data[r]}_calculateIndex(t,e){return t*this.columns+e}static get[Symbol.species](){return Matrix}}class WrapperMatrix2D extends(AbstractMatrix()){constructor(t){super(),this.data=t,this.rows=t.length,this.columns=t[0].length}set(t,e,r){return this.data[t][e]=r,this}get(t,e){return this.data[t][e]}static get[Symbol.species](){return Matrix}}function mean(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 toDiscreteDistribution(t,e){for(var r=new Array(e).fill(0),n=0;n<t.length;++n)r[t[n]]+=1/t.length;return Matrix.rowVector(r)}function giniImpurity(t){if(0===t.length)return 0;for(var e=toDiscreteDistribution(t,getNumberOfClasses(t))[0],r=0,n=0;n<e.length;++n)r+=e[n]*e[n];return 1-r}function getNumberOfClasses(t){return t.filter((function(t,e,r){return r.indexOf(t)===e})).length}function giniGain(t,e){for(var r=0,n=["greater","lesser"],i=0;i<n.length;++i){var o=e[n[i]];r+=giniImpurity(o)*o.length/t.length}return giniImpurity(t)-r}function squaredError(t){for(var e=t.length,r=mean(t),n=0,i=0;i<e;++i){var o=t[i];n+=(o-r)*(o-r)}return n}function regressionError(t,e){for(var r=0,n=["greater","lesser"],i=0;i<n.length;++i){r+=squaredError(e[n[i]])}return r}function matrixSplitter(t,e,r,n){for(var i=[],o=[],s=[],a=[],u=0;u<t.rows;++u)t[u][r]<n?(i.push(t[u]),s.push(e[u])):(o.push(t[u]),a.push(e[u]));return{greaterX:o,greaterY:a,lesserX:i,lesserY:s}}function mean$1(t,e){return(t+e)/2}function zip(t,e){if(t.length!==e.length)throw new TypeError("Error on zip: the size of a: "+t.length+" is different from b: "+e.length);for(var r=new Array(t.length),n=0;n<t.length;++n)r[n]=[t[n],e[n]];return r}const gainFunctions={gini:giniGain,regression:regressionError},splitFunctions={mean:mean$1};class TreeNode{constructor(t){this.kind=t.kind,this.gainFunction=t.gainFunction,this.splitFunction=t.splitFunction,this.minNumSamples=t.minNumSamples,this.maxDepth=t.maxDepth}bestSplit(t,e){for(var r,n,i="classifier"===this.kind?-1/0:1/0,o="classifier"===this.kind?(t,e)=>t>e:(t,e)=>t<e,s=0;s<t.rows;++s)for(var a=t[s],u=this.featureSplit(a,e),h=0;h<u.length;++h){var c=u[h],l=this.split(a,e,c),f=gainFunctions[this.gainFunction](e,l);o(f,i)&&(r=s,n=c,i=f)}return{maxGain:i,maxColumn:r,maxValue:n}}split(t,e,r){for(var n=[],i=[],o=0;o<t.length;++o)t[o]<r?n.push(e[o]):i.push(e[o]);return{greater:i,lesser:n}}featureSplit(t,e){var r=[],n=zip(t,e);n.sort((function(t,e){return t[0]-e[0]}));for(var i=1;i<n.length;++i)n[i-1][1]!==n[i][1]&&r.push(splitFunctions[this.splitFunction](n[i-1][0],n[i][0]));return r}calculatePrediction(t){if("classifier"===this.kind){if(this.distribution=toDiscreteDistribution(t,getNumberOfClasses(t)),0===this.distribution.columns)throw new TypeError("Error on calculate the prediction")}else this.distribution=mean(t)}train(t,e,r,n){if(t.rows<=this.minNumSamples)this.calculatePrediction(e);else{void 0===n&&(n=0);var i=t.transpose(),o=this.bestSplit(i,e);this.splitValue=o.maxValue,this.splitColumn=o.maxColumn,this.gain=o.maxGain;var s=matrixSplitter(t,e,this.splitColumn,this.splitValue);if(r<this.maxDepth&&this.gain>.01&&this.gain!==n&&s.lesserX.length>0&&s.greaterX.length>0){this.left=new TreeNode(this),this.right=new TreeNode(this);var a=new Matrix(s.lesserX),u=new Matrix(s.greaterX);this.left.train(a,s.lesserY,r+1,this.gain),this.right.train(u,s.greaterY,r+1,this.gain)}else this.calculatePrediction(e)}}classify(t){return this.right&&this.left?t[this.splitColumn]<this.splitValue?this.left.classify(t):this.right.classify(t):this.distribution}setNodeParameters(t){void 0!==t.distribution?this.distribution=t.distribution.constructor===Array?new Matrix(t.distribution):t.distribution:(this.distribution=void 0,this.splitValue=t.splitValue,this.splitColumn=t.splitColumn,this.gain=t.gain,this.left=new TreeNode(this),this.right=new TreeNode(this),t.left!=={}&&this.left.setNodeParameters(t.left),t.right!=={}&&this.right.setNodeParameters(t.right))}}const defaultOptions={gainFunction:"gini",splitFunction:"mean",minNumSamples:3,maxDepth:1/0};class DecisionTreeClassifier{constructor(t,e){!0===t?(this.options=e.options,this.root=new TreeNode(e.options),this.root.setNodeParameters(e.root)):(this.options=Object.assign({},defaultOptions,t),this.options.kind="classifier")}train(t,e){this.root=new TreeNode(this.options),t=Matrix.checkMatrix(t),this.root.train(t,e,0,null)}predict(t){t=Matrix.checkMatrix(t);for(var e=new Array(t.rows),r=0;r<t.rows;++r)e[r]=this.root.classify(t.getRow(r)).maxRowIndex(0)[1];return e}toJSON(){return{options:this.options,root:this.root,name:"DTClassifier"}}static load(t){if("DTClassifier"!==t.name)throw new RangeError("Invalid model: "+t.name);return new DecisionTreeClassifier(!0,t)}}const defaultOptions$1={gainFunction:"regression",splitFunction:"mean",minNumSamples:3,maxDepth:1/0};class DecisionTreeRegression{constructor(t,e){!0===t?(this.options=e.options,this.root=new TreeNode(e.options),this.root.setNodeParameters(e.root)):(this.options=Object.assign({},defaultOptions$1,t),this.options.kind="regression")}train(t,e){this.root=new TreeNode(this.options),void 0===t[0].length&&(t=Matrix.columnVector(t)),t=Matrix.checkMatrix(t),this.root.train(t,e,0)}predict(t){void 0!==t[0]&&void 0===t[0].length&&(t=Matrix.columnVector(t)),t=Matrix.checkMatrix(t);for(var e=new Array(t.rows),r=0;r<t.rows;++r)e[r]=this.root.classify(t.getRow(r));return e}toJSON(){return{options:this.options,root:this.root,name:"DTRegression"}}static load(t){if("DTRegression"!==t.name)throw new RangeError("Invalid model:"+t.name);return new DecisionTreeRegression(!0,t)}}var src=Object.freeze({DecisionTreeClassifier:DecisionTreeClassifier,DecisionTreeRegression:DecisionTreeRegression});class LuDecomposition$$1{constructor(t){var e,r,n,i,o,s,a,u,h,c=(t=WrapperMatrix2D$1.checkMatrix(t)).clone(),l=c.rows,f=c.columns,m=new Array(l),p=1;for(e=0;e<l;e++)m[e]=e;for(u=new Array(l),r=0;r<f;r++){for(e=0;e<l;e++)u[e]=c.get(e,r);for(e=0;e<l;e++){for(h=Math.min(e,r),o=0,n=0;n<h;n++)o+=c.get(e,n)*u[n];u[e]-=o,c.set(e,r,u[e])}for(i=r,e=r+1;e<l;e++)Math.abs(u[e])>Math.abs(u[i])&&(i=e);if(i!==r){for(n=0;n<f;n++)s=c.get(i,n),c.set(i,n,c.get(r,n)),c.set(r,n,s);a=m[i],m[i]=m[r],m[r]=a,p=-p}if(r<l&&0!==c.get(r,r))for(e=r+1;e<l;e++)c.set(e,r,c.get(e,r)/c.get(r,r))}this.LU=c,this.pivotVector=m,this.pivotSign=p}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=Matrix$1.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,n,i,o=t.columns,s=t.subMatrixRow(this.pivotVector,0,o-1),a=e.columns;for(i=0;i<a;i++)for(r=i+1;r<a;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i];for(i=a-1;i>=0;i--){for(n=0;n<o;n++)s[i][n]/=e[i][i];for(r=0;r<i;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i]}return s}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,n=new Matrix$1(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i>o?t[i][o]:i===o?1:0;return n}get upperTriangularMatrix(){for(var t=this.LU,e=t.rows,r=t.columns,n=new Matrix$1(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i<=o?t[i][o]:0;return n}get pivotPermutationVector(){return this.pivotVector.slice()}}function hypotenuse$1(t,e){var r=0;return Math.abs(t)>Math.abs(e)?(r=e/t,Math.abs(t)*Math.sqrt(1+r*r)):0!==e?(r=t/e,Math.abs(e)*Math.sqrt(1+r*r)):0}function getFilled2DArray$1(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}class SingularValueDecomposition$$1{constructor(t,e={}){var r=(t=WrapperMatrix2D$1.checkMatrix(t)).rows,n=t.columns;const{computeLeftSingularVectors:i=!0,computeRightSingularVectors:o=!0,autoTranspose:s=!1}=e;var a,u=Boolean(i),h=Boolean(o),c=!1;if(r<n)if(s){r=(a=t.transpose()).rows,n=a.columns,c=!0;var l=u;u=h,h=l}else a=t.clone(),console.warn("Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose");else a=t.clone();var f=Math.min(r,n),m=Math.min(r+1,n),p=new Array(m),d=getFilled2DArray$1(r,f,0),g=getFilled2DArray$1(n,n,0),v=new Array(n),w=new Array(r),y=new Array(m);for(let t=0;t<m;t++)y[t]=t;var b=Math.min(r-1,n),x=Math.max(0,Math.min(n-2,r)),M=Math.max(b,x);for(let t=0;t<M;t++){if(t<b){p[t]=0;for(let e=t;e<r;e++)p[t]=hypotenuse$1(p[t],a[e][t]);if(0!==p[t]){a[t][t]<0&&(p[t]=-p[t]);for(let e=t;e<r;e++)a[e][t]/=p[t];a[t][t]+=1}p[t]=-p[t]}for(let e=t+1;e<n;e++){if(t<b&&0!==p[t]){let n=0;for(let i=t;i<r;i++)n+=a[i][t]*a[i][e];n=-n/a[t][t];for(let i=t;i<r;i++)a[i][e]+=n*a[i][t]}v[e]=a[t][e]}if(u&&t<b)for(let e=t;e<r;e++)d[e][t]=a[e][t];if(t<x){v[t]=0;for(let e=t+1;e<n;e++)v[t]=hypotenuse$1(v[t],v[e]);if(0!==v[t]){v[t+1]<0&&(v[t]=0-v[t]);for(let e=t+1;e<n;e++)v[e]/=v[t];v[t+1]+=1}if(v[t]=-v[t],t+1<r&&0!==v[t]){for(let e=t+1;e<r;e++)w[e]=0;for(let e=t+1;e<r;e++)for(let r=t+1;r<n;r++)w[e]+=v[r]*a[e][r];for(let e=t+1;e<n;e++){let n=-v[e]/v[t+1];for(let i=t+1;i<r;i++)a[i][e]+=n*w[i]}}if(h)for(let e=t+1;e<n;e++)g[e][t]=v[e]}}let _=Math.min(n,r+1);if(b<n&&(p[b]=a[b][b]),r<_&&(p[_-1]=0),x+1<_&&(v[x]=a[x][_-1]),v[_-1]=0,u){for(let t=b;t<f;t++){for(let e=0;e<r;e++)d[e][t]=0;d[t][t]=1}for(let t=b-1;t>=0;t--)if(0!==p[t]){for(let e=t+1;e<f;e++){let n=0;for(let i=t;i<r;i++)n+=d[i][t]*d[i][e];n=-n/d[t][t];for(let i=t;i<r;i++)d[i][e]+=n*d[i][t]}for(let e=t;e<r;e++)d[e][t]=-d[e][t];d[t][t]=1+d[t][t];for(let e=0;e<t-1;e++)d[e][t]=0}else{for(let e=0;e<r;e++)d[e][t]=0;d[t][t]=1}}if(h)for(let t=n-1;t>=0;t--){if(t<x&&0!==v[t])for(let e=t+1;e<n;e++){let r=0;for(let i=t+1;i<n;i++)r+=g[i][t]*g[i][e];r=-r/g[t+1][t];for(let i=t+1;i<n;i++)g[i][e]+=r*g[i][t]}for(let e=0;e<n;e++)g[e][t]=0;g[t][t]=1}for(var $=_-1,S=Number.EPSILON;_>0;){let t,e;for(t=_-2;t>=-1&&-1!==t;t--){const e=Number.MIN_VALUE+S*Math.abs(p[t]+Math.abs(p[t+1]));if(Math.abs(v[t])<=e||Number.isNaN(v[t])){v[t]=0;break}}if(t===_-2)e=4;else{let r;for(r=_-1;r>=t&&r!==t;r--){let e=(r!==_?Math.abs(v[r]):0)+(r!==t+1?Math.abs(v[r-1]):0);if(Math.abs(p[r])<=S*e){p[r]=0;break}}r===t?e=3:r===_-1?e=1:(e=2,t=r)}switch(t++,e){case 1:{let e=v[_-2];v[_-2]=0;for(let r=_-2;r>=t;r--){let i=hypotenuse$1(p[r],e),o=p[r]/i,s=e/i;if(p[r]=i,r!==t&&(e=-s*v[r-1],v[r-1]=o*v[r-1]),h)for(let t=0;t<n;t++)i=o*g[t][r]+s*g[t][_-1],g[t][_-1]=-s*g[t][r]+o*g[t][_-1],g[t][r]=i}break}case 2:{let e=v[t-1];v[t-1]=0;for(let n=t;n<_;n++){let i=hypotenuse$1(p[n],e),o=p[n]/i,s=e/i;if(p[n]=i,e=-s*v[n],v[n]=o*v[n],u)for(let e=0;e<r;e++)i=o*d[e][n]+s*d[e][t-1],d[e][t-1]=-s*d[e][n]+o*d[e][t-1],d[e][n]=i}break}case 3:{const e=Math.max(Math.abs(p[_-1]),Math.abs(p[_-2]),Math.abs(v[_-2]),Math.abs(p[t]),Math.abs(v[t])),i=p[_-1]/e,o=p[_-2]/e,s=v[_-2]/e,a=p[t]/e,c=v[t]/e,l=((o+i)*(o-i)+s*s)/2,f=i*s*(i*s);let m=0;0===l&&0===f||(m=l<0?0-Math.sqrt(l*l+f):Math.sqrt(l*l+f),m=f/(l+m));let w=(a+i)*(a-i)+m,y=a*c;for(let e=t;e<_-1;e++){let i=hypotenuse$1(w,y);0===i&&(i=Number.MIN_VALUE);let o=w/i,s=y/i;if(e!==t&&(v[e-1]=i),w=o*p[e]+s*v[e],v[e]=o*v[e]-s*p[e],y=s*p[e+1],p[e+1]=o*p[e+1],h)for(let t=0;t<n;t++)i=o*g[t][e]+s*g[t][e+1],g[t][e+1]=-s*g[t][e]+o*g[t][e+1],g[t][e]=i;if(i=hypotenuse$1(w,y),0===i&&(i=Number.MIN_VALUE),o=w/i,s=y/i,p[e]=i,w=o*v[e]+s*p[e+1],p[e+1]=-s*v[e]+o*p[e+1],y=s*v[e+1],v[e+1]=o*v[e+1],u&&e<r-1)for(let t=0;t<r;t++)i=o*d[t][e]+s*d[t][e+1],d[t][e+1]=-s*d[t][e]+o*d[t][e+1],d[t][e]=i}v[_-2]=w;break}case 4:if(p[t]<=0&&(p[t]=p[t]<0?-p[t]:0,h))for(let e=0;e<=$;e++)g[e][t]=-g[e][t];for(;t<$&&!(p[t]>=p[t+1]);){let e=p[t];if(p[t]=p[t+1],p[t+1]=e,h&&t<n-1)for(let r=0;r<n;r++)e=g[r][t+1],g[r][t+1]=g[r][t],g[r][t]=e;if(u&&t<r-1)for(let n=0;n<r;n++)e=d[n][t+1],d[n][t+1]=d[n][t],d[n][t]=e;t++}_--}}if(c){var R=g;g=d,d=R}this.m=r,this.n=n,this.s=p,this.U=d,this.V=g}solve(t){var e=t,r=this.threshold,n=this.s.length,i=Matrix$1.zeros(n,n);for(let t=0;t<n;t++)Math.abs(this.s[t])<=r?i[t][t]=0:i[t][t]=1/this.s[t];var o=this.U,s=this.rightSingularVectors,a=s.mmul(i),u=s.rows,h=o.length,c=Matrix$1.zeros(u,h);for(let t=0;t<u;t++)for(let e=0;e<h;e++){let r=0;for(let i=0;i<n;i++)r+=a[t][i]*o[e][i];c[t][e]=r}return c.mmul(e)}solveForDiagonal(t){return this.solve(Matrix$1.diag(t))}inverse(){var t=this.V,e=this.threshold,r=t.length,n=t[0].length,i=new Matrix$1(r,this.s.length);for(let o=0;o<r;o++)for(let r=0;r<n;r++)Math.abs(this.s[r])>e?i[o][r]=t[o][r]/this.s[r]:i[o][r]=0;var o=this.U,s=o.length,a=o[0].length,u=new Matrix$1(r,s);for(let t=0;t<r;t++)for(let e=0;e<s;e++){let r=0;for(let n=0;n<a;n++)r+=i[t][n]*o[e][n];u[t][e]=r}return u}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 Matrix$1.isMatrix(this.U)||(this.U=new Matrix$1(this.U)),this.U}get rightSingularVectors(){return Matrix$1.isMatrix(this.V)||(this.V=new Matrix$1(this.V)),this.V}get diagonalMatrix(){return Matrix$1.diag(this.s)}}function checkRowIndex$1(t,e,r){var n=r?t.rows:t.rows-1;if(e<0||e>n)throw new RangeError("Row index out of range")}function checkColumnIndex$1(t,e,r){var n=r?t.columns:t.columns-1;if(e<0||e>n)throw new RangeError("Column index out of range")}function checkRowVector$1(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.columns)throw new RangeError("vector size must be the same as the number of columns");return e}function checkColumnVector$1(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.rows)throw new RangeError("vector size must be the same as the number of rows");return e}function checkIndices$1(t,e,r){return{row:checkRowIndices$1(t,e),column:checkColumnIndices$1(t,r)}}function checkRowIndices$1(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for row indices");if(e.some((e=>e<0||e>=t.rows)))throw new RangeError("row indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkColumnIndices$1(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for column indices");var r=e.some((e=>e<0||e>=t.columns));if(r)throw new RangeError("column indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkRange$1(t,e,r,n,i){if(5!==arguments.length)throw new RangeError("expected 4 arguments");if(checkNumber("startRow",e),checkNumber("endRow",r),checkNumber("startColumn",n),checkNumber("endColumn",i),e>r||n>i||e<0||e>=t.rows||r<0||r>=t.rows||n<0||n>=t.columns||i<0||i>=t.columns)throw new RangeError("Submatrix indices are out of range")}function sumByRow$1(t){for(var e=Matrix$1.zeros(t.rows,1),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(r,0,e.get(r,0)+t.get(r,n));return e}function sumByColumn$1(t){for(var e=Matrix$1.zeros(1,t.columns),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(0,n,e.get(0,n)+t.get(r,n));return e}function sumAll$1(t){for(var e=0,r=0;r<t.rows;r++)for(var n=0;n<t.columns;n++)e+=t.get(r,n);return e}function checkNumber(t,e){if("number"!=typeof e)throw new TypeError(`${t} must be a number`)}class BaseView$1 extends(AbstractMatrix$1()){constructor(t,e,r){super(),this.matrix=t,this.rows=e,this.columns=r}static get[Symbol.species](){return Matrix$1}}class MatrixTransposeView$1 extends BaseView$1{constructor(t){super(t,t.columns,t.rows)}set(t,e,r){return this.matrix.set(e,t,r),this}get(t,e){return this.matrix.get(e,t)}}class MatrixRowView$1 extends BaseView$1{constructor(t,e){super(t,1,t.columns),this.row=e}set(t,e,r){return this.matrix.set(this.row,e,r),this}get(t,e){return this.matrix.get(this.row,e)}}class MatrixSubView$1 extends BaseView$1{constructor(t,e,r,n,i){checkRange$1(t,e,r,n,i),super(t,r-e+1,i-n+1),this.startRow=e,this.startColumn=n}set(t,e,r){return this.matrix.set(this.startRow+t,this.startColumn+e,r),this}get(t,e){return this.matrix.get(this.startRow+t,this.startColumn+e)}}class MatrixSelectionView$1 extends BaseView$1{constructor(t,e,r){var n=checkIndices$1(t,e,r);super(t,n.row.length,n.column.length),this.rowIndices=n.row,this.columnIndices=n.column}set(t,e,r){return this.matrix.set(this.rowIndices[t],this.columnIndices[e],r),this}get(t,e){return this.matrix.get(this.rowIndices[t],this.columnIndices[e])}}class MatrixRowSelectionView$1 extends BaseView$1{constructor(t,e){super(t,(e=checkRowIndices$1(t,e)).length,t.columns),this.rowIndices=e}set(t,e,r){return this.matrix.set(this.rowIndices[t],e,r),this}get(t,e){return this.matrix.get(this.rowIndices[t],e)}}class MatrixColumnSelectionView$1 extends BaseView$1{constructor(t,e){e=checkColumnIndices$1(t,e),super(t,t.rows,e.length),this.columnIndices=e}set(t,e,r){return this.matrix.set(t,this.columnIndices[e],r),this}get(t,e){return this.matrix.get(t,this.columnIndices[e])}}class MatrixColumnView$1 extends BaseView$1{constructor(t,e){super(t,t.rows,1),this.column=e}set(t,e,r){return this.matrix.set(t,this.column,r),this}get(t){return this.matrix.get(t,this.column)}}class MatrixFlipRowView$1 extends BaseView$1{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(this.rows-t-1,e,r),this}get(t,e){return this.matrix.get(this.rows-t-1,e)}}class MatrixFlipColumnView$1 extends BaseView$1{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(t,this.columns-e-1,r),this}get(t,e){return this.matrix.get(t,this.columns-e-1)}}function AbstractMatrix$1(t){void 0===t&&(t=Object);class e extends t{static get[Symbol.species](){return this}static from1DArray(t,e,r){if(t*e!==r.length)throw new RangeError("Data length does not match given dimensions");for(var n=new this(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r[i*e+o]);return n}static rowVector(t){for(var e=new this(1,t.length),r=0;r<t.length;r++)e.set(0,r,t[r]);return e}static columnVector(t){for(var e=new this(t.length,1),r=0;r<t.length;r++)e.set(r,0,t[r]);return e}static empty(t,e){return new this(t,e)}static zeros(t,e){return this.empty(t,e).fill(0)}static ones(t,e){return this.empty(t,e).fill(1)}static rand(t,e,r){void 0===r&&(r=Math.random);for(var n=this.empty(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r());return n}static randInt(t,e,r,n){void 0===r&&(r=1e3),void 0===n&&(n=Math.random);for(var i=this.empty(t,e),o=0;o<t;o++)for(var s=0;s<e;s++){var a=Math.floor(n()*r);i.set(o,s,a)}return i}static eye(t,e,r){void 0===e&&(e=t),void 0===r&&(r=1);for(var n=Math.min(t,e),i=this.zeros(t,e),o=0;o<n;o++)i.set(o,o,r);return i}static diag(t,e,r){var n=t.length;void 0===e&&(e=n),void 0===r&&(r=e);for(var i=Math.min(n,e,r),o=this.zeros(e,r),s=0;s<i;s++)o.set(s,s,t[s]);return o}static min(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.min(t.get(o,s),e.get(o,s)));return i}static max(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.max(t.get(o,s),e.get(o,s)));return i}static checkMatrix(t){return e.isMatrix(t)?t:new this(t)}static isMatrix(t){return null!=t&&"Matrix"===t.klass}get size(){return this.rows*this.columns}apply(t){if("function"!=typeof t)throw new TypeError("callback must be a function");for(var e=this.rows,r=this.columns,n=0;n<e;n++)for(var i=0;i<r;i++)t.call(this,n,i);return this}to1DArray(){for(var t=new Array(this.size),e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t[e*this.columns+r]=this.get(e,r);return t}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}isRowVector(){return 1===this.rows}isColumnVector(){return 1===this.columns}isVector(){return 1===this.rows||1===this.columns}isSquare(){return this.rows===this.columns}isSymmetric(){if(this.isSquare()){for(var t=0;t<this.rows;t++)for(var e=0;e<=t;e++)if(this.get(t,e)!==this.get(e,t))return!1;return!0}return!1}set(t,e,r){throw new Error("set method is unimplemented")}get(t,e){throw new Error("get method is unimplemented")}repeat(t,e){t=t||1,e=e||1;for(var r=new this.constructor[Symbol.species](this.rows*t,this.columns*e),n=0;n<t;n++)for(var i=0;i<e;i++)r.setSubMatrix(this,this.rows*n,this.columns*i);return r}fill(t){for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,t);return this}neg(){return this.mulS(-1)}getRow(t){checkRowIndex$1(this,t);for(var e=new Array(this.columns),r=0;r<this.columns;r++)e[r]=this.get(t,r);return e}getRowVector(t){return this.constructor.rowVector(this.getRow(t))}setRow(t,e){checkRowIndex$1(this,t),e=checkRowVector$1(this,e);for(var r=0;r<this.columns;r++)this.set(t,r,e[r]);return this}swapRows(t,e){checkRowIndex$1(this,t),checkRowIndex$1(this,e);for(var r=0;r<this.columns;r++){var n=this.get(t,r);this.set(t,r,this.get(e,r)),this.set(e,r,n)}return this}getColumn(t){checkColumnIndex$1(this,t);for(var e=new Array(this.rows),r=0;r<this.rows;r++)e[r]=this.get(r,t);return e}getColumnVector(t){return this.constructor.columnVector(this.getColumn(t))}setColumn(t,e){checkColumnIndex$1(this,t),e=checkColumnVector$1(this,e);for(var r=0;r<this.rows;r++)this.set(r,t,e[r]);return this}swapColumns(t,e){checkColumnIndex$1(this,t),checkColumnIndex$1(this,e);for(var r=0;r<this.rows;r++){var n=this.get(r,t);this.set(r,t,this.get(r,e)),this.set(r,e,n)}return this}addRowVector(t){t=checkRowVector$1(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}subRowVector(t){t=checkRowVector$1(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=checkRowVector$1(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=checkRowVector$1(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=checkColumnVector$1(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=checkColumnVector$1(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=checkColumnVector$1(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=checkColumnVector$1(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){checkRowIndex$1(this,t);for(var r=0;r<this.columns;r++)this.set(t,r,this.get(t,r)*e);return this}mulColumn(t,e){checkColumnIndex$1(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){checkRowIndex$1(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){checkRowIndex$1(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){checkRowIndex$1(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){checkRowIndex$1(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){checkColumnIndex$1(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){checkColumnIndex$1(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){checkColumnIndex$1(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){checkColumnIndex$1(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 sumByRow$1(this);case"column":return sumByColumn$1(this);default:return sumAll$1(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);const 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),c=(r+u)*(n+h),l=(s+u)*n,f=r*(o-h),m=u*(a-n),p=(r+i)*h,d=c+m-p+(i-u)*(a+h),g=f+p,v=l+m,w=c-l+f+(s-r)*(n+o);return e.set(0,0,d),e.set(0,1,g),e.set(1,0,v),e.set(1,1,w),e}strassen3x3(t){var e=new this.constructor[Symbol.species](3,3);const 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),c=this.get(2,2),l=t.get(0,0),f=t.get(0,1),m=t.get(0,2),p=t.get(1,0),d=t.get(1,1),g=t.get(1,2),v=t.get(2,0),w=t.get(2,1),y=t.get(2,2),b=(r-o)*(-f+d),x=(-r+o+s)*(l-f+d),M=(o+s)*(-l+f),_=r*l,$=(-r+u+h)*(l-m+g),S=(-r+u)*(m-g),R=(u+h)*(-l+m),E=(-i+h+c)*(d+v-w),C=(i-c)*(d-w),k=i*v,A=(h+c)*(-v+w),T=(-i+s+a)*(g+v-y),O=(i-a)*(g-y),I=(s+a)*(-v+y),D=_+k+n*p,P=(r+n+i-o-s-h-c)*d+x+M+_+E+k+A,V=_+$+R+(r+n+i-s-a-u-h)*g+k+T+I,j=b+s*(-l+f+p-d-g-v+y)+x+_+k+T+O,L=b+x+M+_+a*w,N=k+T+O+I+o*m,B=_+$+S+h*(-l+m+p-d-g-v+w)+E+C+k,F=E+C+k+A+u*f,z=_+$+S+R+c*y;return e.set(0,0,D),e.set(0,1,P),e.set(0,2,V),e.set(1,0,j),e.set(1,1,L),e.set(1,2,N),e.set(2,0,B),e.set(2,1,F),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 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),u=parseInt(r.columns/2,10),h=r.subMatrix(0,s-1,0,u-1),c=n.subMatrix(0,s-1,0,u-1),l=r.subMatrix(0,s-1,u,r.columns-1),f=n.subMatrix(0,s-1,u,n.columns-1),m=r.subMatrix(s,r.rows-1,0,u-1),p=n.subMatrix(s,n.rows-1,0,u-1),d=r.subMatrix(s,r.rows-1,u,r.columns-1),g=n.subMatrix(s,n.rows-1,u,n.columns-1),v=t(e.add(h,d),e.add(c,g),s,u),w=t(e.add(m,d),c,s,u),y=t(h,e.sub(f,g),s,u),b=t(d,e.sub(p,c),s,u),x=t(e.add(h,l),g,s,u),M=t(e.sub(m,h),e.add(c,f),s,u),_=t(e.sub(l,d),e.add(p,g),s,u),$=e.add(v,b);$.sub(x),$.add(_);var S=e.add(y,x),R=e.add(w,b),E=e.sub(v,w);E.add(y),E.add(M);var C=e.zeros(2*$.rows,2*$.columns);return(C=(C=(C=(C=C.setSubMatrix($,0,0)).setSubMatrix(S,$.rows,0)).setSubMatrix(R,0,$.columns)).setSubMatrix(E,$.rows,$.columns)).subMatrix(0,i-1,0,o-1)}(r=a(r,u,h),t=a(t,u,h),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),n=0;n<this.rows;n++){var i=rescale(this.getRow(n),{min:t,max:e});r.setRow(n,i)}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),n=0;n<this.columns;n++){var i=rescale(this.getColumn(n),{min:t,max:e});r.setColumn(n,i)}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){checkRange$1(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 s=r;s<=n;s++)i[o-t][s-r]=this.get(o,s);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){checkRange$1(this,e,e+(t=this.constructor.checkMatrix(t)).rows-1,r,r+t.columns-1);for(var n=0;n<t.rows;n++)for(var i=0;i<t.columns;i++)this[e+n][r+i]=t.get(n,i);return this}selection(t,e){for(var r=checkIndices$1(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],s=0;s<r.column.length;s++){var a=r.column[s];n[i][s]=this.get(o,a)}return n}trace(){for(var t=Math.min(this.rows,this.columns),e=0,r=0;r<t;r++)e+=this.get(r,r);return e}transposeView(){return new MatrixTransposeView$1(this)}rowView(t){return checkRowIndex$1(this,t),new MatrixRowView$1(this,t)}columnView(t){return checkColumnIndex$1(this,t),new MatrixColumnView$1(this,t)}flipRowView(){return new MatrixFlipRowView$1(this)}flipColumnView(){return new MatrixFlipColumnView$1(this)}subMatrixView(t,e,r,n){return new MatrixSubView$1(this,t,e,r,n)}selectionView(t,e){return new MatrixSelectionView$1(this,t,e)}rowSelectionView(t){return new MatrixRowSelectionView$1(this,t)}columnSelectionView(t){return new MatrixColumnSelectionView$1(this,t)}det(){var t,e,r,n,i,o;if(this.isSquare())return 2===this.columns?(t=this.get(0,0),e=this.get(0,1),r=this.get(1,0),t*this.get(1,1)-e*r):3===this.columns?(n=this.selectionView([1,2],[1,2]),i=this.selectionView([1,2],[0,2]),o=this.selectionView([1,2],[0,1]),t=this.get(0,0),e=this.get(0,1),r=this.get(0,2),t*n.det()-e*i.det()+r*o.det()):new LuDecomposition$$1(this).determinant;throw Error("Determinant can only be calculated for a square matrix.")}pseudoInverse(t){void 0===t&&(t=Number.EPSILON);for(var e=new SingularValueDecomposition$$1(this,{autoTranspose:!0}),r=e.leftSingularVectors,n=e.rightSingularVectors,i=e.diagonal,o=0;o<i.length;o++)Math.abs(i[o])>t?i[o]=1/i[o]:i[o]=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 n,i="\n(function %name%(matrix, %args%) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(%args%);\n})\n",o=i,s=eval;for(var a of[["+","add"],["-","sub","subtract"],["*","mul","multiply"],["/","div","divide"],["%","mod","modulus"],["&","and"],["|","or"],["^","xor"],["<<","leftShift"],[">>","signPropagatingRightShift"],[">>>","rightShift","zeroFillRightShift"]]){var u=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",{name:a[1],op:a[0]})),h=s(S("\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, this.get(i, j) %op% value);\n        }\n    }\n    return this;\n})\n",{name:`${a[1]}S`,op:a[0]})),c=s(S("\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, this.get(i, j) %op% matrix.get(i, j));\n        }\n    }\n    return this;\n})\n",{name:`${a[1]}M`,op:a[0]})),l=s(S("\n(function %name%(matrix, value) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(value);\n})\n",{name:a[1]}));for(n=1;n<a.length;n++)e.prototype[a[n]]=u,e.prototype[`${a[n]}S`]=h,e.prototype[`${a[n]}M`]=c,e[a[n]]=l}var f=[["~","not"]];for(var m 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){f.push([`Math.${t}`,t])})),f)){var p=s(S("\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:m[1],method:m[0]})),d=s(S("\n(function %name%(matrix) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%();\n})\n",{name:m[1]}));for(n=1;n<m.length;n++)e.prototype[m[n]]=p,e[m[n]]=d}for(var g of[["Math.pow",1,"pow"]]){var v="arg0";for(n=1;n<g[1];n++)v+=`, arg${n}`;if(1!==g[1]){var w=s(S("\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:g[2],method:g[0],args:v})),y=s(S(i,{name:g[2],args:v}));for(n=2;n<g.length;n++)e.prototype[g[n]]=w,e[g[n]]=y}else{var b={name:g[2],args:v,method:g[0]},x=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",b)),M=s(S("\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",b)),_=s(S("\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",b)),$=s(S(o,b));for(n=2;n<g.length;n++)e.prototype[g[n]]=x,e.prototype[`${g[n]}M`]=_,e.prototype[`${g[n]}S`]=M,e[g[n]]=$}}function S(t,e){for(var r in e)t=t.replace(new RegExp(`%${r}%`,"g"),e[r]);return t}return e}class Matrix$1 extends(AbstractMatrix$1(Array)){constructor(t,e){var r;if(1===arguments.length&&"number"==typeof t)return new Array(t);if(Matrix$1.isMatrix(t))return t.clone();if(Number.isInteger(t)&&t>0){if(super(t),!(Number.isInteger(e)&&e>0))throw new TypeError("nColumns must be a positive integer");for(r=0;r<t;r++)this[r]=new Array(e)}else{if(!Array.isArray(t))throw new TypeError("First argument must be a positive number or an array");{const n=t;if(t=n.length,"number"!=typeof(e=n[0].length)||0===e)throw new TypeError("Data must be a 2D array with at least one element");for(super(t),r=0;r<t;r++){if(n[r].length!==e)throw new RangeError("Inconsistent array dimensions");this[r]=[].concat(n[r])}}}return this.rows=t,this.columns=e,this}set(t,e,r){return this[t][e]=r,this}get(t,e){return this[t][e]}removeRow(t){if(checkRowIndex$1(this,t),1===this.rows)throw new RangeError("A matrix cannot have less than one row");return this.splice(t,1),this.rows-=1,this}addRow(t,e){return void 0===e&&(e=t,t=this.rows),checkRowIndex$1(this,t,!0),e=checkRowVector$1(this,e,!0),this.splice(t,0,e),this.rows+=1,this}removeColumn(t){if(checkColumnIndex$1(this,t),1===this.columns)throw new RangeError("A matrix cannot have less than one column");for(var e=0;e<this.rows;e++)this[e].splice(t,1);return this.columns-=1,this}addColumn(t,e){void 0===e&&(e=t,t=this.columns),checkColumnIndex$1(this,t,!0),e=checkColumnVector$1(this,e);for(var r=0;r<this.rows;r++)this[r].splice(t,0,e[r]);return this.columns+=1,this}}class WrapperMatrix1D$1 extends(AbstractMatrix$1()){constructor(t,e={}){const{rows:r=1}=e;if(t.length%r!=0)throw new Error("the data length is not divisible by the number of rows");super(),this.rows=r,this.columns=t.length/r,this.data=t}set(t,e,r){var n=this._calculateIndex(t,e);return this.data[n]=r,this}get(t,e){var r=this._calculateIndex(t,e);return this.data[r]}_calculateIndex(t,e){return t*this.columns+e}static get[Symbol.species](){return Matrix$1}}class WrapperMatrix2D$1 extends(AbstractMatrix$1()){constructor(t){super(),this.data=t,this.rows=t.length,this.columns=t[0].length}set(t,e,r){return this.data[t][e]=r,this}get(t,e){return this.data[t][e]}static get[Symbol.species](){return Matrix$1}}function wrap$1(t,e){if(Array.isArray(t))return t[0]&&Array.isArray(t[0])?new WrapperMatrix2D$1(t):new WrapperMatrix1D$1(t,e);throw new Error("the argument is not an array")}class QrDecomposition$$1{constructor(t){var e,r,n,i,o=(t=WrapperMatrix2D$1.checkMatrix(t)).clone(),s=t.rows,a=t.columns,u=new Array(a);for(n=0;n<a;n++){var h=0;for(e=n;e<s;e++)h=hypotenuse$1(h,o.get(e,n));if(0!==h){for(o.get(n,n)<0&&(h=-h),e=n;e<s;e++)o.set(e,n,o.get(e,n)/h);for(o.set(n,n,o.get(n,n)+1),r=n+1;r<a;r++){for(i=0,e=n;e<s;e++)i+=o.get(e,n)*o.get(e,r);for(i=-i/o.get(n,n),e=n;e<s;e++)o.set(e,r,o.get(e,r)+i*o.get(e,n))}}u[n]=-h}this.QR=o,this.Rdiag=u}solve(t){t=Matrix$1.checkMatrix(t);var e=this.QR,r=e.rows;if(t.rows!==r)throw new Error("Matrix row dimensions must agree");if(!this.isFullRank())throw new Error("Matrix is rank deficient");var n,i,o,s,a=t.columns,u=t.clone(),h=e.columns;for(o=0;o<h;o++)for(i=0;i<a;i++){for(s=0,n=o;n<r;n++)s+=e[n][o]*u[n][i];for(s=-s/e[o][o],n=o;n<r;n++)u[n][i]+=s*e[n][o]}for(o=h-1;o>=0;o--){for(i=0;i<a;i++)u[o][i]/=this.Rdiag[o];for(n=0;n<o;n++)for(i=0;i<a;i++)u[n][i]-=u[o][i]*e[n][o]}return u.subMatrix(0,h-1,0,a-1)}isFullRank(){for(var t=this.QR.columns,e=0;e<t;e++)if(0===this.Rdiag[e])return!1;return!0}get upperTriangularMatrix(){var t,e,r=this.QR,n=r.columns,i=new Matrix$1(n,n);for(t=0;t<n;t++)for(e=0;e<n;e++)i[t][e]=t<e?r[t][e]:t===e?this.Rdiag[t]:0;return i}get orthogonalMatrix(){var t,e,r,n,i=this.QR,o=i.rows,s=i.columns,a=new Matrix$1(o,s);for(r=s-1;r>=0;r--){for(t=0;t<o;t++)a[t][r]=0;for(a[r][r]=1,e=r;e<s;e++)if(0!==i[r][r]){for(n=0,t=r;t<o;t++)n+=i[t][r]*a[t][e];for(n=-n/i[r][r],t=r;t<o;t++)a[t][e]+=n*i[t][r]}}return a}}function inverse$$1(t,e=!1){return t=WrapperMatrix2D$1.checkMatrix(t),e?new SingularValueDecomposition$$1(t).inverse():solve$$1(t,Matrix$1.eye(t.rows))}function solve$$1(t,e,r=!1){return t=WrapperMatrix2D$1.checkMatrix(t),e=WrapperMatrix2D$1.checkMatrix(e),r?new SingularValueDecomposition$$1(t).solve(e):t.isSquare()?new LuDecomposition$$1(t).solve(e):new QrDecomposition$$1(t).solve(e)}function xrange(t,e){for(var r=[],n=0;n<t;n++)n!==e&&r.push(n);return r}function dependenciesOneRow(t,e,r,n=1e-9,i=1e-9){if(t>i)return new Array(e.rows+1).fill(0);for(var o=e.addRow(r,[0]),s=0;s<o.rows;s++)Math.abs(o.get(s,0))<n&&o.set(s,0,0);return o.to1DArray()}function linearDependencies(t,e={}){const{thresholdValue:r=1e-9,thresholdError:n=1e-9}=e;for(var i=t.rows,o=new Matrix$1(i,i),s=0;s<i;s++){var a=Matrix$1.columnVector(t.getRow(s)),u=t.subMatrixRow(xrange(i,s)).transposeView(),h=new SingularValueDecomposition$$1(u).solve(a),c=max(Matrix$1.sub(a,u.mmul(h)).abs().to1DArray());o.setRow(s,dependenciesOneRow(c,h,s,r,n))}return o}class EigenvalueDecomposition$$1{constructor(t,e={}){const{assumeSymmetric:r=!1}=e;if(!(t=WrapperMatrix2D$1.checkMatrix(t)).isSquare())throw new Error("Matrix is not a square matrix");var n,i,o=t.columns,s=getFilled2DArray$1(o,o,0),a=new Array(o),u=new Array(o),h=t;if(!!r||t.isSymmetric()){for(n=0;n<o;n++)for(i=0;i<o;i++)s[n][i]=h.get(n,i);tred2$1(o,u,a,s),tql2$1(o,u,a,s)}else{var c=getFilled2DArray$1(o,o,0),l=new Array(o);for(i=0;i<o;i++)for(n=0;n<o;n++)c[n][i]=h.get(n,i);orthes$1(o,c,l,s),hqr2$1(o,u,a,s,c)}this.n=o,this.e=u,this.d=a,this.V=s}get realEigenvalues(){return this.d}get imaginaryEigenvalues(){return this.e}get eigenvectorMatrix(){return Matrix$1.isMatrix(this.V)||(this.V=new Matrix$1(this.V)),this.V}get diagonalMatrix(){var t,e,r=this.n,n=this.e,i=this.d,o=new Matrix$1(r,r);for(t=0;t<r;t++){for(e=0;e<r;e++)o[t][e]=0;o[t][t]=i[t],n[t]>0?o[t][t+1]=n[t]:n[t]<0&&(o[t][t-1]=n[t])}return o}}function tred2$1(t,e,r,n){var i,o,s,a,u,h,c,l;for(u=0;u<t;u++)r[u]=n[t-1][u];for(a=t-1;a>0;a--){for(l=0,s=0,h=0;h<a;h++)l+=Math.abs(r[h]);if(0===l)for(e[a]=r[a-1],u=0;u<a;u++)r[u]=n[a-1][u],n[a][u]=0,n[u][a]=0;else{for(h=0;h<a;h++)r[h]/=l,s+=r[h]*r[h];for(i=r[a-1],o=Math.sqrt(s),i>0&&(o=-o),e[a]=l*o,s-=i*o,r[a-1]=i-o,u=0;u<a;u++)e[u]=0;for(u=0;u<a;u++){for(i=r[u],n[u][a]=i,o=e[u]+n[u][u]*i,h=u+1;h<=a-1;h++)o+=n[h][u]*r[h],e[h]+=n[h][u]*i;e[u]=o}for(i=0,u=0;u<a;u++)e[u]/=s,i+=e[u]*r[u];for(c=i/(s+s),u=0;u<a;u++)e[u]-=c*r[u];for(u=0;u<a;u++){for(i=r[u],o=e[u],h=u;h<=a-1;h++)n[h][u]-=i*e[h]+o*r[h];r[u]=n[a-1][u],n[a][u]=0}}r[a]=s}for(a=0;a<t-1;a++){if(n[t-1][a]=n[a][a],n[a][a]=1,0!==(s=r[a+1])){for(h=0;h<=a;h++)r[h]=n[h][a+1]/s;for(u=0;u<=a;u++){for(o=0,h=0;h<=a;h++)o+=n[h][a+1]*n[h][u];for(h=0;h<=a;h++)n[h][u]-=o*r[h]}}for(h=0;h<=a;h++)n[h][a+1]=0}for(u=0;u<t;u++)r[u]=n[t-1][u],n[t-1][u]=0;n[t-1][t-1]=1,e[0]=0}function tql2$1(t,e,r,n){var i,o,s,a,u,h,c,l,f,m,p,d,g,v,w,y;for(s=1;s<t;s++)e[s-1]=e[s];e[t-1]=0;var b=0,x=0,M=Number.EPSILON;for(h=0;h<t;h++){for(x=Math.max(x,Math.abs(r[h])+Math.abs(e[h])),c=h;c<t&&!(Math.abs(e[c])<=M*x);)c++;if(c>h)do{for(i=r[h],f=hypotenuse$1(l=(r[h+1]-i)/(2*e[h]),1),l<0&&(f=-f),r[h]=e[h]/(l+f),r[h+1]=e[h]*(l+f),m=r[h+1],o=i-r[h],s=h+2;s<t;s++)r[s]-=o;for(b+=o,l=r[c],d=p=1,g=p,v=e[h+1],w=0,y=0,s=c-1;s>=h;s--)for(g=d,d=p,y=w,i=p*e[s],o=p*l,f=hypotenuse$1(l,e[s]),e[s+1]=w*f,w=e[s]/f,l=(p=l/f)*r[s]-w*i,r[s+1]=o+w*(p*i+w*r[s]),u=0;u<t;u++)o=n[u][s+1],n[u][s+1]=w*n[u][s]+p*o,n[u][s]=p*n[u][s]-w*o;l=-w*y*g*v*e[h]/m,e[h]=w*l,r[h]=p*l}while(Math.abs(e[h])>M*x);r[h]=r[h]+b,e[h]=0}for(s=0;s<t-1;s++){for(u=s,l=r[s],a=s+1;a<t;a++)r[a]<l&&(u=a,l=r[a]);if(u!==s)for(r[u]=r[s],r[s]=l,a=0;a<t;a++)l=n[a][s],n[a][s]=n[a][u],n[a][u]=l}}function orthes$1(t,e,r,n){var i,o,s,a,u,h,c,l=t-1;for(h=1;h<=l-1;h++){for(c=0,a=h;a<=l;a++)c+=Math.abs(e[a][h-1]);if(0!==c){for(s=0,a=l;a>=h;a--)r[a]=e[a][h-1]/c,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=l;a>=h;a--)i+=r[a]*e[a][u];for(i/=s,a=h;a<=l;a++)e[a][u]-=i*r[a]}for(a=0;a<=l;a++){for(i=0,u=l;u>=h;u--)i+=r[u]*e[a][u];for(i/=s,u=h;u<=l;u++)e[a][u]-=i*r[u]}r[h]=c*r[h],e[h][h-1]=c*o}}for(a=0;a<t;a++)for(u=0;u<t;u++)n[a][u]=a===u?1:0;for(h=l-1;h>=1;h--)if(0!==e[h][h-1]){for(a=h+1;a<=l;a++)r[a]=e[a][h-1];for(u=h;u<=l;u++){for(o=0,a=h;a<=l;a++)o+=r[a]*n[a][u];for(o=o/r[h]/e[h][h-1],a=h;a<=l;a++)n[a][u]+=o*r[a]}}}function hqr2$1(t,e,r,n,i){var 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r=o.integer(t.getTime(),e.getTime());return function(t){return new Date(r(t))}},u.date=function(t,e){return o.date(t,e)(this.engine)},"function"==typeof commonjsRequire?t.exports=o:(v=e[r],o.noConflict=function(){return e[r]=v,this},e[r]=o)}(commonjsGlobal)}));function checkFloat(t){return t>0&&t<=1}function examplesBaggingWithReplacement(t,e,r){var n=random.engines.mt19937(),i=random.integer(0,t.rows-1);if(void 0===r)n=n.autoSeed();else{if(!Number.isInteger(r))throw new RangeError(`Expected seed must be undefined or integer not ${r}`);n=n.seed(r)}for(var o=new Array(t.rows),s=new Array(t.rows),a=0;a<t.rows;++a){var u=i(n);o[a]=t[u],s[a]=e[u]}return{X:new Matrix$1(o),y:s}}function featureBagging(t,e,r,n){if(t.columns<e)throw new RangeError("N should be less or equal to the number of columns of X");var i=random.integer(0,t.columns-1),o=random.engines.mt19937();if(void 0===n)o=o.autoSeed();else{if(!Number.isInteger(n))throw new RangeError(`Expected seed must be undefined or integer not ${n}`);o=o.seed(n)}var s=new Matrix$1(t.rows,e);if(r)for(var a=new Array(e),u=0;u<e;++u){var h=i(o);a[u]=h,s.setColumn(u,t.getColumn(h))}else{for(a=new Set,h=i(o),u=0;u<e;++u){for(;a.has(h);)h=i(o);s.setColumn(u,t.getColumn(h)),a.add(h)}a=Array.from(a)}return{X:s,usedIndex:a}}class RandomForestBase{constructor(t,e){if(!0===t){this.replacement=e.replacement,this.maxFeatures=e.maxFeatures,this.nEstimators=e.nEstimators,this.treeOptions=e.treeOptions,this.isClassifier=e.isClassifier,this.seed=e.seed,this.n=e.n,this.indexes=e.indexes,this.useSampleBagging=e.useSampleBagging;var r=this.isClassifier?DecisionTreeClassifier:DecisionTreeRegression;this.estimators=e.estimators.map((t=>r.load(t)))}else this.replacement=t.replacement,this.maxFeatures=t.maxFeatures,this.nEstimators=t.nEstimators,this.treeOptions=t.treeOptions,this.isClassifier=t.isClassifier,this.seed=t.seed,this.useSampleBagging=t.useSampleBagging}train(t,e){if(t=Matrix$1.checkMatrix(t),this.maxFeatures=this.maxFeatures||t.columns,checkFloat(this.maxFeatures))this.n=Math.floor(t.columns*this.maxFeatures);else{if(!Number.isInteger(this.maxFeatures))throw new RangeError(`Cannot process the maxFeatures parameter ${this.maxFeatures}`);if(this.maxFeatures>t.columns)throw new RangeError(`The maxFeatures parameter should be less than ${t.columns}`);this.n=this.maxFeatures}if(this.isClassifier)var r=DecisionTreeClassifier;else r=DecisionTreeRegression;this.estimators=new Array(this.nEstimators),this.indexes=new Array(this.nEstimators);for(var n=0;n<this.nEstimators;++n){var i=this.useSampleBagging?examplesBaggingWithReplacement(t,e,this.seed):{X:t,y:e},o=i.X,s=i.y;o=(i=featureBagging(o,this.n,this.replacement,this.seed)).X,this.indexes[n]=i.usedIndex,this.estimators[n]=new r(this.treeOptions),this.estimators[n].train(o,s)}}selection(t){throw new Error("Abstract method 'selection' not implemented!")}predict(t){var e=new Array(this.nEstimators);t=Matrix$1.checkMatrix(t);for(var r=0;r<this.nEstimators;++r){var n=t.columnSelectionView(this.indexes[r]);e[r]=this.estimators[r].predict(n)}e=new WrapperMatrix2D$1(e).transposeView();var i=new Array(e.rows);for(r=0;r<e.rows;++r)i[r]=this.selection(e.getRow(r));return i}toJSON(){return{indexes:this.indexes,n:this.n,replacement:this.replacement,maxFeatures:this.maxFeatures,nEstimators:this.nEstimators,treeOptions:this.treeOptions,isClassifier:this.isClassifier,seed:this.seed,estimators:this.estimators.map((t=>t.toJSON())),useSampleBagging:this.useSampleBagging}}}const defaultOptions$2={maxFeatures:1,replacement:!0,nEstimators:10,seed:42,useSampleBagging:!1};class RandomForestClassifier extends RandomForestBase{constructor(t,e){!0===t?super(!0,e.baseModel):((t=Object.assign({},defaultOptions$2,t)).isClassifier=!0,super(t))}selection(t){return mode(t)}toJSON(){return{baseModel:super.toJSON(),name:"RFClassifier"}}static load(t){if("RFClassifier"!==t.name)throw new RangeError(`Invalid model: ${t.name}`);return new RandomForestClassifier(!0,t)}}function mode(t){return t.sort(((e,r)=>t.filter((t=>t===e)).length-t.filter((t=>t===r)).length)).pop()}var medianQuickselect_min=createCommonjsModule((function(t){!function(){function e(t){for(var e=0,i=t.length-1,o=void 0,s=void 0,a=void 0,u=n(e,i);;){if(i<=e)return t[u];if(i==e+1)return t[e]>t[i]&&r(t,e,i),t[u];for(t[o=n(e,i)]>t[i]&&r(t,o,i),t[e]>t[i]&&r(t,e,i),t[o]>t[e]&&r(t,o,e),r(t,o,e+1),s=e+1,a=i;;){do{s++}while(t[e]>t[s]);do{a--}while(t[a]>t[e]);if(a<s)break;r(t,s,a)}r(t,e,a),a<=u&&(e=s),a>=u&&(i=a-1)}}var r=function(t,e,r){var n;return n=[t[r],t[e]],t[e]=n[0],t[r]=n[1],n},n=function(t,e){return~~((t+e)/2)};t.exports?t.exports=e:window.median=e}()}));function median(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");return medianQuickselect_min(t.slice())}const selectionMethods={mean:mean,median:median},defaultOptions$3={maxFeatures:1,replacement:!1,nEstimators:10,treeOptions:{},selectionMethod:"mean",seed:42,useSampleBagging:!1};class RandomForestRegression extends RandomForestBase{constructor(t,e){if(!0===t)super(!0,e.baseModel),this.selectionMethod=e.selectionMethod;else{if("mean"!==(t=Object.assign({},defaultOptions$3,t)).selectionMethod&&"median"!==t.selectionMethod)throw new RangeError(`Unsupported selection method ${t.selectionMethod}`);t.isClassifier=!1,super(t),this.selectionMethod=t.selectionMethod}}selection(t){return selectionMethods[this.selectionMethod](t)}toJSON(){return{baseModel:super.toJSON(),selectionMethod:this.selectionMethod,name:"RFRegression"}}static load(t){if("RFRegression"!==t.name)throw new RangeError(`Invalid model: ${t.name}`);return new RandomForestRegression(!0,t)}}var src$1=Object.freeze({RandomForestClassifier:RandomForestClassifier,RandomForestRegression:RandomForestRegression});Symbol.species||(Symbol.species=Symbol.for("@@species"));class LuDecomposition$$1{constructor(t){var e,r,n,i,o,s,a,u,h,c=(t=WrapperMatrix2D$2.checkMatrix(t)).clone(),l=c.rows,f=c.columns,m=new Array(l),p=1;for(e=0;e<l;e++)m[e]=e;for(u=new Array(l),r=0;r<f;r++){for(e=0;e<l;e++)u[e]=c.get(e,r);for(e=0;e<l;e++){for(h=Math.min(e,r),o=0,n=0;n<h;n++)o+=c.get(e,n)*u[n];u[e]-=o,c.set(e,r,u[e])}for(i=r,e=r+1;e<l;e++)Math.abs(u[e])>Math.abs(u[i])&&(i=e);if(i!==r){for(n=0;n<f;n++)s=c.get(i,n),c.set(i,n,c.get(r,n)),c.set(r,n,s);a=m[i],m[i]=m[r],m[r]=a,p=-p}if(r<l&&0!==c.get(r,r))for(e=r+1;e<l;e++)c.set(e,r,c.get(e,r)/c.get(r,r))}this.LU=c,this.pivotVector=m,this.pivotSign=p}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=Matrix$2.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,n,i,o=t.columns,s=t.subMatrixRow(this.pivotVector,0,o-1),a=e.columns;for(i=0;i<a;i++)for(r=i+1;r<a;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i];for(i=a-1;i>=0;i--){for(n=0;n<o;n++)s[i][n]/=e[i][i];for(r=0;r<i;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i]}return s}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,n=new Matrix$2(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i>o?t[i][o]:i===o?1:0;return n}get upperTriangularMatrix(){for(var t=this.LU,e=t.rows,r=t.columns,n=new Matrix$2(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i<=o?t[i][o]:0;return n}get pivotPermutationVector(){return this.pivotVector.slice()}}function hypotenuse$2(t,e){var r=0;return Math.abs(t)>Math.abs(e)?(r=e/t,Math.abs(t)*Math.sqrt(1+r*r)):0!==e?(r=t/e,Math.abs(e)*Math.sqrt(1+r*r)):0}function getFilled2DArray$2(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}class SingularValueDecomposition$$1{constructor(t,e={}){var r=(t=WrapperMatrix2D$2.checkMatrix(t)).rows,n=t.columns,i=Math.min(r,n);const{computeLeftSingularVectors:o=!0,computeRightSingularVectors:s=!0,autoTranspose:a=!1}=e;var u,h=Boolean(o),c=Boolean(s),l=!1;if(r<n)if(a){r=(u=t.transpose()).rows,n=u.columns,l=!0;var f=h;h=c,c=f}else u=t.clone(),console.warn("Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose");else u=t.clone();var m,p,d,g,v,w,y,b,x,M,_,$,S,R,E,C,k,A,T,O,I,D=new Array(Math.min(r+1,n)),P=getFilled2DArray$2(r,i,0),V=getFilled2DArray$2(n,n,0),j=new Array(n),L=new Array(r),N=Math.min(r-1,n),B=Math.max(0,Math.min(n-2,r));for(d=0,M=Math.max(N,B);d<M;d++){if(d<N){for(D[d]=0,m=d;m<r;m++)D[d]=hypotenuse$2(D[d],u[m][d]);if(0!==D[d]){for(u[d][d]<0&&(D[d]=-D[d]),m=d;m<r;m++)u[m][d]/=D[d];u[d][d]+=1}D[d]=-D[d]}for(p=d+1;p<n;p++){if(d<N&&0!==D[d]){for(v=0,m=d;m<r;m++)v+=u[m][d]*u[m][p];for(v=-v/u[d][d],m=d;m<r;m++)u[m][p]+=v*u[m][d]}j[p]=u[d][p]}if(h&&d<N)for(m=d;m<r;m++)P[m][d]=u[m][d];if(d<B){for(j[d]=0,m=d+1;m<n;m++)j[d]=hypotenuse$2(j[d],j[m]);if(0!==j[d]){for(j[d+1]<0&&(j[d]=0-j[d]),m=d+1;m<n;m++)j[m]/=j[d];j[d+1]+=1}if(j[d]=-j[d],d+1<r&&0!==j[d]){for(m=d+1;m<r;m++)L[m]=0;for(p=d+1;p<n;p++)for(m=d+1;m<r;m++)L[m]+=j[p]*u[m][p];for(p=d+1;p<n;p++)for(v=-j[p]/j[d+1],m=d+1;m<r;m++)u[m][p]+=v*L[m]}if(c)for(m=d+1;m<n;m++)V[m][d]=j[m]}}if(g=Math.min(n,r+1),N<n&&(D[N]=u[N][N]),r<g&&(D[g-1]=0),B+1<g&&(j[B]=u[B][g-1]),j[g-1]=0,h){for(p=N;p<i;p++){for(m=0;m<r;m++)P[m][p]=0;P[p][p]=1}for(d=N-1;d>=0;d--)if(0!==D[d]){for(p=d+1;p<i;p++){for(v=0,m=d;m<r;m++)v+=P[m][d]*P[m][p];for(v=-v/P[d][d],m=d;m<r;m++)P[m][p]+=v*P[m][d]}for(m=d;m<r;m++)P[m][d]=-P[m][d];for(P[d][d]=1+P[d][d],m=0;m<d-1;m++)P[m][d]=0}else{for(m=0;m<r;m++)P[m][d]=0;P[d][d]=1}}if(c)for(d=n-1;d>=0;d--){if(d<B&&0!==j[d])for(p=d+1;p<n;p++){for(v=0,m=d+1;m<n;m++)v+=V[m][d]*V[m][p];for(v=-v/V[d+1][d],m=d+1;m<n;m++)V[m][p]+=v*V[m][d]}for(m=0;m<n;m++)V[m][d]=0;V[d][d]=1}for(var F=g-1,z=Number.EPSILON;g>0;){for(d=g-2;d>=-1&&-1!==d;d--)if(Math.abs(j[d])<=z*(Math.abs(D[d])+Math.abs(D[d+1]))){j[d]=0;break}if(d===g-2)_=4;else{for(w=g-1;w>=d&&w!==d;w--)if(v=(w!==g?Math.abs(j[w]):0)+(w!==d+1?Math.abs(j[w-1]):0),Math.abs(D[w])<=z*v){D[w]=0;break}w===d?_=3:w===g-1?_=1:(_=2,d=w)}switch(d++,_){case 1:for(y=j[g-2],j[g-2]=0,p=g-2;p>=d;p--)if(v=hypotenuse$2(D[p],y),b=D[p]/v,x=y/v,D[p]=v,p!==d&&(y=-x*j[p-1],j[p-1]=b*j[p-1]),c)for(m=0;m<n;m++)v=b*V[m][p]+x*V[m][g-1],V[m][g-1]=-x*V[m][p]+b*V[m][g-1],V[m][p]=v;break;case 2:for(y=j[d-1],j[d-1]=0,p=d;p<g;p++)if(v=hypotenuse$2(D[p],y),b=D[p]/v,x=y/v,D[p]=v,y=-x*j[p],j[p]=b*j[p],h)for(m=0;m<r;m++)v=b*P[m][p]+x*P[m][d-1],P[m][d-1]=-x*P[m][p]+b*P[m][d-1],P[m][p]=v;break;case 3:for($=Math.max(Math.abs(D[g-1]),Math.abs(D[g-2]),Math.abs(j[g-2]),Math.abs(D[d]),Math.abs(j[d])),S=D[g-1]/$,R=D[g-2]/$,E=j[g-2]/$,C=D[d]/$,k=j[d]/$,T=S*E*(S*E),O=0,0===(A=((R+S)*(R-S)+E*E)/2)&&0===T||(O=Math.sqrt(A*A+T),A<0&&(O=-O),O=T/(A+O)),y=(C+S)*(C-S)+O,I=C*k,p=d;p<g-1;p++){if(b=y/(v=hypotenuse$2(y,I)),x=I/v,p!==d&&(j[p-1]=v),y=b*D[p]+x*j[p],j[p]=b*j[p]-x*D[p],I=x*D[p+1],D[p+1]=b*D[p+1],c)for(m=0;m<n;m++)v=b*V[m][p]+x*V[m][p+1],V[m][p+1]=-x*V[m][p]+b*V[m][p+1],V[m][p]=v;if(b=y/(v=hypotenuse$2(y,I)),x=I/v,D[p]=v,y=b*j[p]+x*D[p+1],D[p+1]=-x*j[p]+b*D[p+1],I=x*j[p+1],j[p+1]=b*j[p+1],h&&p<r-1)for(m=0;m<r;m++)v=b*P[m][p]+x*P[m][p+1],P[m][p+1]=-x*P[m][p]+b*P[m][p+1],P[m][p]=v}j[g-2]=y;break;case 4:if(D[d]<=0&&(D[d]=D[d]<0?-D[d]:0,c))for(m=0;m<=F;m++)V[m][d]=-V[m][d];for(;d<F&&!(D[d]>=D[d+1]);){if(v=D[d],D[d]=D[d+1],D[d+1]=v,c&&d<n-1)for(m=0;m<n;m++)v=V[m][d+1],V[m][d+1]=V[m][d],V[m][d]=v;if(h&&d<r-1)for(m=0;m<r;m++)v=P[m][d+1],P[m][d+1]=P[m][d],P[m][d]=v;d++}g--}}if(l){var q=V;V=P,P=q}this.m=r,this.n=n,this.s=D,this.U=P,this.V=V}solve(t){var e,r=t,n=this.threshold,i=this.s.length,o=Matrix$2.zeros(i,i);for(e=0;e<i;e++)Math.abs(this.s[e])<=n?o[e][e]=0:o[e][e]=1/this.s[e];var s,a,u,h=this.U,c=this.rightSingularVectors,l=c.mmul(o),f=c.rows,m=h.length,p=Matrix$2.zeros(f,m);for(e=0;e<f;e++)for(s=0;s<m;s++){for(u=0,a=0;a<i;a++)u+=l[e][a]*h[s][a];p[e][s]=u}return p.mmul(r)}solveForDiagonal(t){return this.solve(Matrix$2.diag(t))}inverse(){var t,e,r=this.V,n=this.threshold,i=r.length,o=r[0].length,s=new Matrix$2(i,this.s.length);for(t=0;t<i;t++)for(e=0;e<o;e++)Math.abs(this.s[e])>n?s[t][e]=r[t][e]/this.s[e]:s[t][e]=0;var a,u,h=this.U,c=h.length,l=h[0].length,f=new Matrix$2(i,c);for(t=0;t<i;t++)for(e=0;e<c;e++){for(u=0,a=0;a<l;a++)u+=s[t][a]*h[e][a];f[t][e]=u}return f}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 Matrix$2.isMatrix(this.U)||(this.U=new Matrix$2(this.U)),this.U}get rightSingularVectors(){return Matrix$2.isMatrix(this.V)||(this.V=new Matrix$2(this.V)),this.V}get diagonalMatrix(){return Matrix$2.diag(this.s)}}function checkRowIndex$2(t,e,r){var n=r?t.rows:t.rows-1;if(e<0||e>n)throw new RangeError("Row index out of range")}function checkColumnIndex$2(t,e,r){var n=r?t.columns:t.columns-1;if(e<0||e>n)throw new RangeError("Column index out of range")}function checkRowVector$2(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.columns)throw new RangeError("vector size must be the same as the number of columns");return e}function checkColumnVector$2(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.rows)throw new RangeError("vector size must be the same as the number of rows");return e}function checkIndices$2(t,e,r){return{row:checkRowIndices$2(t,e),column:checkColumnIndices$2(t,r)}}function checkRowIndices$2(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for row indices");if(e.some((e=>e<0||e>=t.rows)))throw new RangeError("row indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkColumnIndices$2(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for column indices");var r=e.some((e=>e<0||e>=t.columns));if(r)throw new RangeError("column indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkRange$2(t,e,r,n,i){if(5!==arguments.length)throw new TypeError("Invalid argument type");if(Array.from(arguments).slice(1).some((function(t){return"number"!=typeof t})))throw new TypeError("Invalid argument type");if(e>r||n>i||e<0||e>=t.rows||r<0||r>=t.rows||n<0||n>=t.columns||i<0||i>=t.columns)throw new RangeError("Submatrix indices are out of range")}function sumByRow$2(t){for(var e=Matrix$2.zeros(t.rows,1),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(r,0,e.get(r,0)+t.get(r,n));return e}function sumByColumn$2(t){for(var e=Matrix$2.zeros(1,t.columns),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(0,n,e.get(0,n)+t.get(r,n));return e}function sumAll$2(t){for(var e=0,r=0;r<t.rows;r++)for(var n=0;n<t.columns;n++)e+=t.get(r,n);return e}class BaseView$2 extends(AbstractMatrix$2()){constructor(t,e,r){super(),this.matrix=t,this.rows=e,this.columns=r}static get[Symbol.species](){return Matrix$2}}class MatrixTransposeView$2 extends BaseView$2{constructor(t){super(t,t.columns,t.rows)}set(t,e,r){return this.matrix.set(e,t,r),this}get(t,e){return this.matrix.get(e,t)}}class MatrixRowView$2 extends BaseView$2{constructor(t,e){super(t,1,t.columns),this.row=e}set(t,e,r){return this.matrix.set(this.row,e,r),this}get(t,e){return this.matrix.get(this.row,e)}}class MatrixSubView$2 extends BaseView$2{constructor(t,e,r,n,i){checkRange$2(t,e,r,n,i),super(t,r-e+1,i-n+1),this.startRow=e,this.startColumn=n}set(t,e,r){return this.matrix.set(this.startRow+t,this.startColumn+e,r),this}get(t,e){return this.matrix.get(this.startRow+t,this.startColumn+e)}}class MatrixSelectionView$2 extends BaseView$2{constructor(t,e,r){var n=checkIndices$2(t,e,r);super(t,n.row.length,n.column.length),this.rowIndices=n.row,this.columnIndices=n.column}set(t,e,r){return this.matrix.set(this.rowIndices[t],this.columnIndices[e],r),this}get(t,e){return this.matrix.get(this.rowIndices[t],this.columnIndices[e])}}class MatrixRowSelectionView$2 extends BaseView$2{constructor(t,e){super(t,(e=checkRowIndices$2(t,e)).length,t.columns),this.rowIndices=e}set(t,e,r){return this.matrix.set(this.rowIndices[t],e,r),this}get(t,e){return this.matrix.get(this.rowIndices[t],e)}}class MatrixColumnSelectionView$2 extends BaseView$2{constructor(t,e){e=checkColumnIndices$2(t,e),super(t,t.rows,e.length),this.columnIndices=e}set(t,e,r){return this.matrix.set(t,this.columnIndices[e],r),this}get(t,e){return this.matrix.get(t,this.columnIndices[e])}}class MatrixColumnView$2 extends BaseView$2{constructor(t,e){super(t,t.rows,1),this.column=e}set(t,e,r){return this.matrix.set(t,this.column,r),this}get(t){return this.matrix.get(t,this.column)}}class MatrixFlipRowView$2 extends BaseView$2{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(this.rows-t-1,e,r),this}get(t,e){return this.matrix.get(this.rows-t-1,e)}}class MatrixFlipColumnView$2 extends BaseView$2{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(t,this.columns-e-1,r),this}get(t,e){return this.matrix.get(t,this.columns-e-1)}}function AbstractMatrix$2(t){void 0===t&&(t=Object);class e extends t{static get[Symbol.species](){return this}static from1DArray(t,e,r){if(t*e!==r.length)throw new RangeError("Data length does not match given dimensions");for(var n=new this(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r[i*e+o]);return n}static rowVector(t){for(var e=new this(1,t.length),r=0;r<t.length;r++)e.set(0,r,t[r]);return e}static columnVector(t){for(var e=new this(t.length,1),r=0;r<t.length;r++)e.set(r,0,t[r]);return e}static empty(t,e){return new this(t,e)}static zeros(t,e){return this.empty(t,e).fill(0)}static ones(t,e){return this.empty(t,e).fill(1)}static rand(t,e,r){void 0===r&&(r=Math.random);for(var n=this.empty(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r());return n}static randInt(t,e,r,n){void 0===r&&(r=1e3),void 0===n&&(n=Math.random);for(var i=this.empty(t,e),o=0;o<t;o++)for(var s=0;s<e;s++){var a=Math.floor(n()*r);i.set(o,s,a)}return i}static eye(t,e,r){void 0===e&&(e=t),void 0===r&&(r=1);for(var n=Math.min(t,e),i=this.zeros(t,e),o=0;o<n;o++)i.set(o,o,r);return i}static diag(t,e,r){var n=t.length;void 0===e&&(e=n),void 0===r&&(r=e);for(var i=Math.min(n,e,r),o=this.zeros(e,r),s=0;s<i;s++)o.set(s,s,t[s]);return o}static min(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.min(t.get(o,s),e.get(o,s)));return i}static max(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.max(t.get(o,s),e.get(o,s)));return i}static checkMatrix(t){return e.isMatrix(t)?t:new this(t)}static isMatrix(t){return null!=t&&"Matrix"===t.klass}get size(){return this.rows*this.columns}apply(t){if("function"!=typeof t)throw new TypeError("callback must be a function");for(var e=this.rows,r=this.columns,n=0;n<e;n++)for(var i=0;i<r;i++)t.call(this,n,i);return this}to1DArray(){for(var t=new Array(this.size),e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t[e*this.columns+r]=this.get(e,r);return t}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}isRowVector(){return 1===this.rows}isColumnVector(){return 1===this.columns}isVector(){return 1===this.rows||1===this.columns}isSquare(){return this.rows===this.columns}isSymmetric(){if(this.isSquare()){for(var t=0;t<this.rows;t++)for(var e=0;e<=t;e++)if(this.get(t,e)!==this.get(e,t))return!1;return!0}return!1}set(t,e,r){throw new Error("set method is unimplemented")}get(t,e){throw new Error("get method is unimplemented")}repeat(t,e){t=t||1,e=e||1;for(var r=new this.constructor[Symbol.species](this.rows*t,this.columns*e),n=0;n<t;n++)for(var i=0;i<e;i++)r.setSubMatrix(this,this.rows*n,this.columns*i);return r}fill(t){for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,t);return this}neg(){return this.mulS(-1)}getRow(t){checkRowIndex$2(this,t);for(var e=new Array(this.columns),r=0;r<this.columns;r++)e[r]=this.get(t,r);return e}getRowVector(t){return this.constructor.rowVector(this.getRow(t))}setRow(t,e){checkRowIndex$2(this,t),e=checkRowVector$2(this,e);for(var r=0;r<this.columns;r++)this.set(t,r,e[r]);return this}swapRows(t,e){checkRowIndex$2(this,t),checkRowIndex$2(this,e);for(var r=0;r<this.columns;r++){var n=this.get(t,r);this.set(t,r,this.get(e,r)),this.set(e,r,n)}return this}getColumn(t){checkColumnIndex$2(this,t);for(var e=new Array(this.rows),r=0;r<this.rows;r++)e[r]=this.get(r,t);return e}getColumnVector(t){return this.constructor.columnVector(this.getColumn(t))}setColumn(t,e){checkColumnIndex$2(this,t),e=checkColumnVector$2(this,e);for(var r=0;r<this.rows;r++)this.set(r,t,e[r]);return this}swapColumns(t,e){checkColumnIndex$2(this,t),checkColumnIndex$2(this,e);for(var r=0;r<this.rows;r++){var n=this.get(r,t);this.set(r,t,this.get(r,e)),this.set(r,e,n)}return this}addRowVector(t){t=checkRowVector$2(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}subRowVector(t){t=checkRowVector$2(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=checkRowVector$2(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=checkRowVector$2(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=checkColumnVector$2(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=checkColumnVector$2(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=checkColumnVector$2(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=checkColumnVector$2(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){checkRowIndex$2(this,t);for(var r=0;r<this.columns;r++)this.set(t,r,this.get(t,r)*e);return this}mulColumn(t,e){checkColumnIndex$2(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){checkRowIndex$2(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){checkRowIndex$2(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){checkRowIndex$2(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){checkRowIndex$2(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){checkColumnIndex$2(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){checkColumnIndex$2(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){checkColumnIndex$2(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){checkColumnIndex$2(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 sumByRow$2(this);case"column":return sumByColumn$2(this);default:return sumAll$2(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);const 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),c=(r+u)*(n+h),l=(s+u)*n,f=r*(o-h),m=u*(a-n),p=(r+i)*h,d=c+m-p+(i-u)*(a+h),g=f+p,v=l+m,w=c-l+f+(s-r)*(n+o);return e.set(0,0,d),e.set(0,1,g),e.set(1,0,v),e.set(1,1,w),e}strassen3x3(t){var e=new this.constructor[Symbol.species](3,3);const 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),c=this.get(2,2),l=t.get(0,0),f=t.get(0,1),m=t.get(0,2),p=t.get(1,0),d=t.get(1,1),g=t.get(1,2),v=t.get(2,0),w=t.get(2,1),y=t.get(2,2),b=(r-o)*(-f+d),x=(-r+o+s)*(l-f+d),M=(o+s)*(-l+f),_=r*l,$=(-r+u+h)*(l-m+g),S=(-r+u)*(m-g),R=(u+h)*(-l+m),E=(-i+h+c)*(d+v-w),C=(i-c)*(d-w),k=i*v,A=(h+c)*(-v+w),T=(-i+s+a)*(g+v-y),O=(i-a)*(g-y),I=(s+a)*(-v+y),D=_+k+n*p,P=(r+n+i-o-s-h-c)*d+x+M+_+E+k+A,V=_+$+R+(r+n+i-s-a-u-h)*g+k+T+I,j=b+s*(-l+f+p-d-g-v+y)+x+_+k+T+O,L=b+x+M+_+a*w,N=k+T+O+I+o*m,B=_+$+S+h*(-l+m+p-d-g-v+w)+E+C+k,F=E+C+k+A+u*f,z=_+$+S+R+c*y;return e.set(0,0,D),e.set(0,1,P),e.set(0,2,V),e.set(1,0,j),e.set(1,1,L),e.set(1,2,N),e.set(2,0,B),e.set(2,1,F),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 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),u=parseInt(r.columns/2),h=r.subMatrix(0,s-1,0,u-1),c=n.subMatrix(0,s-1,0,u-1),l=r.subMatrix(0,s-1,u,r.columns-1),f=n.subMatrix(0,s-1,u,n.columns-1),m=r.subMatrix(s,r.rows-1,0,u-1),p=n.subMatrix(s,n.rows-1,0,u-1),d=r.subMatrix(s,r.rows-1,u,r.columns-1),g=n.subMatrix(s,n.rows-1,u,n.columns-1),v=t(e.add(h,d),e.add(c,g),s,u),w=t(e.add(m,d),c,s,u),y=t(h,e.sub(f,g),s,u),b=t(d,e.sub(p,c),s,u),x=t(e.add(h,l),g,s,u),M=t(e.sub(m,h),e.add(c,f),s,u),_=t(e.sub(l,d),e.add(p,g),s,u),$=e.add(v,b);$.sub(x),$.add(_);var S=e.add(y,x),R=e.add(w,b),E=e.sub(v,w);E.add(y),E.add(M);var C=e.zeros(2*$.rows,2*$.columns);return(C=(C=(C=(C=C.setSubMatrix($,0,0)).setSubMatrix(S,$.rows,0)).setSubMatrix(R,0,$.columns)).setSubMatrix(E,$.rows,$.columns)).subMatrix(0,i-1,0,o-1)}(r=a(r,u,h),t=a(t,u,h),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),n=0;n<this.rows;n++){var i=rescale(this.getRow(n),{min:t,max:e});r.setRow(n,i)}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),n=0;n<this.columns;n++){var i=rescale(this.getColumn(n),{min:t,max:e});r.setColumn(n,i)}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){checkRange$2(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 s=r;s<=n;s++)i[o-t][s-r]=this.get(o,s);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){checkRange$2(this,e,e+(t=this.constructor.checkMatrix(t)).rows-1,r,r+t.columns-1);for(var n=0;n<t.rows;n++)for(var i=0;i<t.columns;i++)this[e+n][r+i]=t.get(n,i);return this}selection(t,e){for(var r=checkIndices$2(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],s=0;s<r.column.length;s++){var a=r.column[s];n[i][s]=this.get(o,a)}return n}trace(){for(var t=Math.min(this.rows,this.columns),e=0,r=0;r<t;r++)e+=this.get(r,r);return e}transposeView(){return new MatrixTransposeView$2(this)}rowView(t){return checkRowIndex$2(this,t),new MatrixRowView$2(this,t)}columnView(t){return checkColumnIndex$2(this,t),new MatrixColumnView$2(this,t)}flipRowView(){return new MatrixFlipRowView$2(this)}flipColumnView(){return new MatrixFlipColumnView$2(this)}subMatrixView(t,e,r,n){return new MatrixSubView$2(this,t,e,r,n)}selectionView(t,e){return new MatrixSelectionView$2(this,t,e)}rowSelectionView(t){return new MatrixRowSelectionView$2(this,t)}columnSelectionView(t){return new MatrixColumnSelectionView$2(this,t)}det(){var t,e,r,n,i,o;if(this.isSquare())return 2===this.columns?(t=this.get(0,0),e=this.get(0,1),r=this.get(1,0),t*this.get(1,1)-e*r):3===this.columns?(n=this.selectionView([1,2],[1,2]),i=this.selectionView([1,2],[0,2]),o=this.selectionView([1,2],[0,1]),t=this.get(0,0),e=this.get(0,1),r=this.get(0,2),t*n.det()-e*i.det()+r*o.det()):new LuDecomposition$$1(this).determinant;throw Error("Determinant can only be calculated for a square matrix.")}pseudoInverse(t){void 0===t&&(t=Number.EPSILON);for(var e=new SingularValueDecomposition$$1(this,{autoTranspose:!0}),r=e.leftSingularVectors,n=e.rightSingularVectors,i=e.diagonal,o=0;o<i.length;o++)Math.abs(i[o])>t?i[o]=1/i[o]:i[o]=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 n,i="\n(function %name%(matrix, %args%) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(%args%);\n})\n",o=i,s=eval;for(var a of[["+","add"],["-","sub","subtract"],["*","mul","multiply"],["/","div","divide"],["%","mod","modulus"],["&","and"],["|","or"],["^","xor"],["<<","leftShift"],[">>","signPropagatingRightShift"],[">>>","rightShift","zeroFillRightShift"]]){var u=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",{name:a[1],op:a[0]})),h=s(S("\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, this.get(i, j) %op% value);\n        }\n    }\n    return this;\n})\n",{name:a[1]+"S",op:a[0]})),c=s(S("\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, this.get(i, j) %op% matrix.get(i, j));\n        }\n    }\n    return this;\n})\n",{name:a[1]+"M",op:a[0]})),l=s(S("\n(function %name%(matrix, value) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(value);\n})\n",{name:a[1]}));for(n=1;n<a.length;n++)e.prototype[a[n]]=u,e.prototype[a[n]+"S"]=h,e.prototype[a[n]+"M"]=c,e[a[n]]=l}var f=[["~","not"]];for(var m 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){f.push(["Math."+t,t])})),f)){var p=s(S("\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:m[1],method:m[0]})),d=s(S("\n(function %name%(matrix) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%();\n})\n",{name:m[1]}));for(n=1;n<m.length;n++)e.prototype[m[n]]=p,e[m[n]]=d}for(var g of[["Math.pow",1,"pow"]]){var v="arg0";for(n=1;n<g[1];n++)v+=`, arg${n}`;if(1!==g[1]){var w=s(S("\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:g[2],method:g[0],args:v})),y=s(S(i,{name:g[2],args:v}));for(n=2;n<g.length;n++)e.prototype[g[n]]=w,e[g[n]]=y}else{var b={name:g[2],args:v,method:g[0]},x=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",b)),M=s(S("\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",b)),_=s(S("\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",b)),$=s(S(o,b));for(n=2;n<g.length;n++)e.prototype[g[n]]=x,e.prototype[g[n]+"M"]=_,e.prototype[g[n]+"S"]=M,e[g[n]]=$}}function S(t,e){for(var r in e)t=t.replace(new RegExp("%"+r+"%","g"),e[r]);return t}return e}class Matrix$2 extends(AbstractMatrix$2(Array)){constructor(t,e){var r;if(1===arguments.length&&"number"==typeof t)return new Array(t);if(Matrix$2.isMatrix(t))return t.clone();if(Number.isInteger(t)&&t>0){if(super(t),!(Number.isInteger(e)&&e>0))throw new TypeError("nColumns must be a positive integer");for(r=0;r<t;r++)this[r]=new Array(e)}else{if(!Array.isArray(t))throw new TypeError("First argument must be a positive number or an array");{const n=t;if(t=n.length,"number"!=typeof(e=n[0].length)||0===e)throw new TypeError("Data must be a 2D array with at least one element");for(super(t),r=0;r<t;r++){if(n[r].length!==e)throw new RangeError("Inconsistent array dimensions");this[r]=[].concat(n[r])}}}return this.rows=t,this.columns=e,this}set(t,e,r){return this[t][e]=r,this}get(t,e){return this[t][e]}removeRow(t){if(checkRowIndex$2(this,t),1===this.rows)throw new RangeError("A matrix cannot have less than one row");return this.splice(t,1),this.rows-=1,this}addRow(t,e){return void 0===e&&(e=t,t=this.rows),checkRowIndex$2(this,t,!0),e=checkRowVector$2(this,e,!0),this.splice(t,0,e),this.rows+=1,this}removeColumn(t){if(checkColumnIndex$2(this,t),1===this.columns)throw new RangeError("A matrix cannot have less than one column");for(var e=0;e<this.rows;e++)this[e].splice(t,1);return this.columns-=1,this}addColumn(t,e){void 0===e&&(e=t,t=this.columns),checkColumnIndex$2(this,t,!0),e=checkColumnVector$2(this,e);for(var r=0;r<this.rows;r++)this[r].splice(t,0,e[r]);return this.columns+=1,this}}class WrapperMatrix1D$2 extends(AbstractMatrix$2()){constructor(t,e={}){const{rows:r=1}=e;if(t.length%r!=0)throw new Error("the data length is not divisible by the number of rows");super(),this.rows=r,this.columns=t.length/r,this.data=t}set(t,e,r){var n=this._calculateIndex(t,e);return this.data[n]=r,this}get(t,e){var r=this._calculateIndex(t,e);return this.data[r]}_calculateIndex(t,e){return t*this.columns+e}static get[Symbol.species](){return Matrix$2}}class WrapperMatrix2D$2 extends(AbstractMatrix$2()){constructor(t){super(),this.data=t,this.rows=t.length,this.columns=t[0].length}set(t,e,r){return this.data[t][e]=r,this}get(t,e){return this.data[t][e]}static get[Symbol.species](){return Matrix$2}}function wrap$2(t,e){if(Array.isArray(t))return t[0]&&Array.isArray(t[0])?new WrapperMatrix2D$2(t):new WrapperMatrix1D$2(t,e);throw new Error("the argument is not an array")}class QrDecomposition$$1{constructor(t){var e,r,n,i,o=(t=WrapperMatrix2D$2.checkMatrix(t)).clone(),s=t.rows,a=t.columns,u=new Array(a);for(n=0;n<a;n++){var h=0;for(e=n;e<s;e++)h=hypotenuse$2(h,o.get(e,n));if(0!==h){for(o.get(n,n)<0&&(h=-h),e=n;e<s;e++)o.set(e,n,o.get(e,n)/h);for(o.set(n,n,o.get(n,n)+1),r=n+1;r<a;r++){for(i=0,e=n;e<s;e++)i+=o.get(e,n)*o.get(e,r);for(i=-i/o.get(n,n),e=n;e<s;e++)o.set(e,r,o.get(e,r)+i*o.get(e,n))}}u[n]=-h}this.QR=o,this.Rdiag=u}solve(t){t=Matrix$2.checkMatrix(t);var e=this.QR,r=e.rows;if(t.rows!==r)throw new Error("Matrix row dimensions must agree");if(!this.isFullRank())throw new Error("Matrix is rank deficient");var n,i,o,s,a=t.columns,u=t.clone(),h=e.columns;for(o=0;o<h;o++)for(i=0;i<a;i++){for(s=0,n=o;n<r;n++)s+=e[n][o]*u[n][i];for(s=-s/e[o][o],n=o;n<r;n++)u[n][i]+=s*e[n][o]}for(o=h-1;o>=0;o--){for(i=0;i<a;i++)u[o][i]/=this.Rdiag[o];for(n=0;n<o;n++)for(i=0;i<a;i++)u[n][i]-=u[o][i]*e[n][o]}return u.subMatrix(0,h-1,0,a-1)}isFullRank(){for(var t=this.QR.columns,e=0;e<t;e++)if(0===this.Rdiag[e])return!1;return!0}get upperTriangularMatrix(){var t,e,r=this.QR,n=r.columns,i=new Matrix$2(n,n);for(t=0;t<n;t++)for(e=0;e<n;e++)i[t][e]=t<e?r[t][e]:t===e?this.Rdiag[t]:0;return i}get orthogonalMatrix(){var t,e,r,n,i=this.QR,o=i.rows,s=i.columns,a=new Matrix$2(o,s);for(r=s-1;r>=0;r--){for(t=0;t<o;t++)a[t][r]=0;for(a[r][r]=1,e=r;e<s;e++)if(0!==i[r][r]){for(n=0,t=r;t<o;t++)n+=i[t][r]*a[t][e];for(n=-n/i[r][r],t=r;t<o;t++)a[t][e]+=n*i[t][r]}}return a}}function inverse$$1(t,e=!1){return t=WrapperMatrix2D$2.checkMatrix(t),e?new SingularValueDecomposition$$1(t).inverse():solve$$1(t,Matrix$2.eye(t.rows))}function solve$$1(t,e,r=!1){return t=WrapperMatrix2D$2.checkMatrix(t),e=WrapperMatrix2D$2.checkMatrix(e),r?new SingularValueDecomposition$$1(t).solve(e):t.isSquare()?new LuDecomposition$$1(t).solve(e):new QrDecomposition$$1(t).solve(e)}class EigenvalueDecomposition$$1{constructor(t,e={}){const{assumeSymmetric:r=!1}=e;if(!(t=WrapperMatrix2D$2.checkMatrix(t)).isSquare())throw new Error("Matrix is not a square matrix");var n,i,o=t.columns,s=getFilled2DArray$2(o,o,0),a=new Array(o),u=new Array(o),h=t;if(!!r||t.isSymmetric()){for(n=0;n<o;n++)for(i=0;i<o;i++)s[n][i]=h.get(n,i);tred2$2(o,u,a,s),tql2$2(o,u,a,s)}else{var c=getFilled2DArray$2(o,o,0),l=new Array(o);for(i=0;i<o;i++)for(n=0;n<o;n++)c[n][i]=h.get(n,i);orthes$2(o,c,l,s),hqr2$2(o,u,a,s,c)}this.n=o,this.e=u,this.d=a,this.V=s}get realEigenvalues(){return this.d}get imaginaryEigenvalues(){return this.e}get eigenvectorMatrix(){return Matrix$2.isMatrix(this.V)||(this.V=new Matrix$2(this.V)),this.V}get diagonalMatrix(){var t,e,r=this.n,n=this.e,i=this.d,o=new Matrix$2(r,r);for(t=0;t<r;t++){for(e=0;e<r;e++)o[t][e]=0;o[t][t]=i[t],n[t]>0?o[t][t+1]=n[t]:n[t]<0&&(o[t][t-1]=n[t])}return o}}function tred2$2(t,e,r,n){var i,o,s,a,u,h,c,l;for(u=0;u<t;u++)r[u]=n[t-1][u];for(a=t-1;a>0;a--){for(l=0,s=0,h=0;h<a;h++)l+=Math.abs(r[h]);if(0===l)for(e[a]=r[a-1],u=0;u<a;u++)r[u]=n[a-1][u],n[a][u]=0,n[u][a]=0;else{for(h=0;h<a;h++)r[h]/=l,s+=r[h]*r[h];for(i=r[a-1],o=Math.sqrt(s),i>0&&(o=-o),e[a]=l*o,s-=i*o,r[a-1]=i-o,u=0;u<a;u++)e[u]=0;for(u=0;u<a;u++){for(i=r[u],n[u][a]=i,o=e[u]+n[u][u]*i,h=u+1;h<=a-1;h++)o+=n[h][u]*r[h],e[h]+=n[h][u]*i;e[u]=o}for(i=0,u=0;u<a;u++)e[u]/=s,i+=e[u]*r[u];for(c=i/(s+s),u=0;u<a;u++)e[u]-=c*r[u];for(u=0;u<a;u++){for(i=r[u],o=e[u],h=u;h<=a-1;h++)n[h][u]-=i*e[h]+o*r[h];r[u]=n[a-1][u],n[a][u]=0}}r[a]=s}for(a=0;a<t-1;a++){if(n[t-1][a]=n[a][a],n[a][a]=1,0!==(s=r[a+1])){for(h=0;h<=a;h++)r[h]=n[h][a+1]/s;for(u=0;u<=a;u++){for(o=0,h=0;h<=a;h++)o+=n[h][a+1]*n[h][u];for(h=0;h<=a;h++)n[h][u]-=o*r[h]}}for(h=0;h<=a;h++)n[h][a+1]=0}for(u=0;u<t;u++)r[u]=n[t-1][u],n[t-1][u]=0;n[t-1][t-1]=1,e[0]=0}function tql2$2(t,e,r,n){var i,o,s,a,u,h,c,l,f,m,p,d,g,v,w,y;for(s=1;s<t;s++)e[s-1]=e[s];e[t-1]=0;var b=0,x=0,M=Number.EPSILON;for(h=0;h<t;h++){for(x=Math.max(x,Math.abs(r[h])+Math.abs(e[h])),c=h;c<t&&!(Math.abs(e[c])<=M*x);)c++;if(c>h)do{for(i=r[h],f=hypotenuse$2(l=(r[h+1]-i)/(2*e[h]),1),l<0&&(f=-f),r[h]=e[h]/(l+f),r[h+1]=e[h]*(l+f),m=r[h+1],o=i-r[h],s=h+2;s<t;s++)r[s]-=o;for(b+=o,l=r[c],d=p=1,g=p,v=e[h+1],w=0,y=0,s=c-1;s>=h;s--)for(g=d,d=p,y=w,i=p*e[s],o=p*l,f=hypotenuse$2(l,e[s]),e[s+1]=w*f,w=e[s]/f,l=(p=l/f)*r[s]-w*i,r[s+1]=o+w*(p*i+w*r[s]),u=0;u<t;u++)o=n[u][s+1],n[u][s+1]=w*n[u][s]+p*o,n[u][s]=p*n[u][s]-w*o;l=-w*y*g*v*e[h]/m,e[h]=w*l,r[h]=p*l}while(Math.abs(e[h])>M*x);r[h]=r[h]+b,e[h]=0}for(s=0;s<t-1;s++){for(u=s,l=r[s],a=s+1;a<t;a++)r[a]<l&&(u=a,l=r[a]);if(u!==s)for(r[u]=r[s],r[s]=l,a=0;a<t;a++)l=n[a][s],n[a][s]=n[a][u],n[a][u]=l}}function orthes$2(t,e,r,n){var i,o,s,a,u,h,c,l=t-1;for(h=1;h<=l-1;h++){for(c=0,a=h;a<=l;a++)c+=Math.abs(e[a][h-1]);if(0!==c){for(s=0,a=l;a>=h;a--)r[a]=e[a][h-1]/c,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=l;a>=h;a--)i+=r[a]*e[a][u];for(i/=s,a=h;a<=l;a++)e[a][u]-=i*r[a]}for(a=0;a<=l;a++){for(i=0,u=l;u>=h;u--)i+=r[u]*e[a][u];for(i/=s,u=h;u<=l;u++)e[a][u]-=i*r[u]}r[h]=c*r[h],e[h][h-1]=c*o}}for(a=0;a<t;a++)for(u=0;u<t;u++)n[a][u]=a===u?1:0;for(h=l-1;h>=1;h--)if(0!==e[h][h-1]){for(a=h+1;a<=l;a++)r[a]=e[a][h-1];for(u=h;u<=l;u++){for(o=0,a=h;a<=l;a++)o+=r[a]*n[a][u];for(o=o/r[h]/e[h][h-1],a=h;a<=l;a++)n[a][u]+=o*r[a]}}}function hqr2$2(t,e,r,n,i){var o,s,a,u,h,c,l,f,m,p,d,g,v,w,y,b=t-1,x=t-1,M=Number.EPSILON,_=0,$=0,S=0,R=0,E=0,C=0,k=0,A=0;for(o=0;o<t;o++)for((o<0||o>x)&&(r[o]=i[o][o],e[o]=0),s=Math.max(o-1,0);s<t;s++)$+=Math.abs(i[o][s]);for(;b>=0;){for(u=b;u>0&&(0===(C=Math.abs(i[u-1][u-1])+Math.abs(i[u][u]))&&(C=$),!(Math.abs(i[u][u-1])<M*C));)u--;if(u===b)i[b][b]=i[b][b]+_,r[b]=i[b][b],e[b]=0,b--,A=0;else if(u===b-1){if(l=i[b][b-1]*i[b-1][b],R=(S=(i[b-1][b-1]-i[b][b])/2)*S+l,k=Math.sqrt(Math.abs(R)),i[b][b]=i[b][b]+_,i[b-1][b-1]=i[b-1][b-1]+_,f=i[b][b],R>=0){for(k=S>=0?S+k:S-k,r[b-1]=f+k,r[b]=r[b-1],0!==k&&(r[b]=f-l/k),e[b-1]=0,e[b]=0,S=(f=i[b][b-1])/(C=Math.abs(f)+Math.abs(k)),R=k/C,S/=E=Math.sqrt(S*S+R*R),R/=E,s=b-1;s<t;s++)k=i[b-1][s],i[b-1][s]=R*k+S*i[b][s],i[b][s]=R*i[b][s]-S*k;for(o=0;o<=b;o++)k=i[o][b-1],i[o][b-1]=R*k+S*i[o][b],i[o][b]=R*i[o][b]-S*k;for(o=0;o<=x;o++)k=n[o][b-1],n[o][b-1]=R*k+S*n[o][b],n[o][b]=R*n[o][b]-S*k}else r[b-1]=f+S,r[b]=f+S,e[b-1]=k,e[b]=-k;b-=2,A=0}else{if(f=i[b][b],m=0,l=0,u<b&&(m=i[b-1][b-1],l=i[b][b-1]*i[b-1][b]),10===A){for(_+=f,o=0;o<=b;o++)i[o][o]-=f;f=m=.75*(C=Math.abs(i[b][b-1])+Math.abs(i[b-1][b-2])),l=-.4375*C*C}if(30===A&&(C=(C=(m-f)/2)*C+l)>0){for(C=Math.sqrt(C),m<f&&(C=-C),C=f-l/((m-f)/2+C),o=0;o<=b;o++)i[o][o]-=C;_+=C,f=m=l=.964}for(A+=1,h=b-2;h>=u&&(S=((E=f-(k=i[h][h]))*(C=m-k)-l)/i[h+1][h]+i[h][h+1],R=i[h+1][h+1]-k-E-C,E=i[h+2][h+1],S/=C=Math.abs(S)+Math.abs(R)+Math.abs(E),R/=C,E/=C,h!==u)&&!(Math.abs(i[h][h-1])*(Math.abs(R)+Math.abs(E))<M*(Math.abs(S)*(Math.abs(i[h-1][h-1])+Math.abs(k)+Math.abs(i[h+1][h+1]))));)h--;for(o=h+2;o<=b;o++)i[o][o-2]=0,o>h+2&&(i[o][o-3]=0);for(a=h;a<=b-1&&(w=a!==b-1,a!==h&&(S=i[a][a-1],R=i[a+1][a-1],E=w?i[a+2][a-1]:0,0!==(f=Math.abs(S)+Math.abs(R)+Math.abs(E))&&(S/=f,R/=f,E/=f)),0!==f);a++)if(C=Math.sqrt(S*S+R*R+E*E),S<0&&(C=-C),0!==C){for(a!==h?i[a][a-1]=-C*f:u!==h&&(i[a][a-1]=-i[a][a-1]),f=(S+=C)/C,m=R/C,k=E/C,R/=S,E/=S,s=a;s<t;s++)S=i[a][s]+R*i[a+1][s],w&&(S+=E*i[a+2][s],i[a+2][s]=i[a+2][s]-S*k),i[a][s]=i[a][s]-S*f,i[a+1][s]=i[a+1][s]-S*m;for(o=0;o<=Math.min(b,a+3);o++)S=f*i[o][a]+m*i[o][a+1],w&&(S+=k*i[o][a+2],i[o][a+2]=i[o][a+2]-S*E),i[o][a]=i[o][a]-S,i[o][a+1]=i[o][a+1]-S*R;for(o=0;o<=x;o++)S=f*n[o][a]+m*n[o][a+1],w&&(S+=k*n[o][a+2],n[o][a+2]=n[o][a+2]-S*E),n[o][a]=n[o][a]-S,n[o][a+1]=n[o][a+1]-S*R}}}if(0!==$){for(b=t-1;b>=0;b--)if(S=r[b],0===(R=e[b]))for(u=b,i[b][b]=1,o=b-1;o>=0;o--){for(l=i[o][o]-S,E=0,s=u;s<=b;s++)E+=i[o][s]*i[s][b];if(e[o]<0)k=l,C=E;else if(u=o,0===e[o]?i[o][b]=0!==l?-E/l:-E/(M*$):(f=i[o][o+1],m=i[o+1][o],c=(f*C-k*E)/(R=(r[o]-S)*(r[o]-S)+e[o]*e[o]),i[o][b]=c,i[o+1][b]=Math.abs(f)>Math.abs(k)?(-E-l*c)/f:(-C-m*c)/k),M*(c=Math.abs(i[o][b]))*c>1)for(s=o;s<=b;s++)i[s][b]=i[s][b]/c}else if(R<0)for(u=b-1,Math.abs(i[b][b-1])>Math.abs(i[b-1][b])?(i[b-1][b-1]=R/i[b][b-1],i[b-1][b]=-(i[b][b]-S)/i[b][b-1]):(y=cdiv$2(0,-i[b-1][b],i[b-1][b-1]-S,R),i[b-1][b-1]=y[0],i[b-1][b]=y[1]),i[b][b-1]=0,i[b][b]=1,o=b-2;o>=0;o--){for(p=0,d=0,s=u;s<=b;s++)p+=i[o][s]*i[s][b-1],d+=i[o][s]*i[s][b];if(l=i[o][o]-S,e[o]<0)k=l,E=p,C=d;else if(u=o,0===e[o]?(y=cdiv$2(-p,-d,l,R),i[o][b-1]=y[0],i[o][b]=y[1]):(f=i[o][o+1],m=i[o+1][o],g=(r[o]-S)*(r[o]-S)+e[o]*e[o]-R*R,v=2*(r[o]-S)*R,0===g&&0===v&&(g=M*$*(Math.abs(l)+Math.abs(R)+Math.abs(f)+Math.abs(m)+Math.abs(k))),y=cdiv$2(f*E-k*p+R*d,f*C-k*d-R*p,g,v),i[o][b-1]=y[0],i[o][b]=y[1],Math.abs(f)>Math.abs(k)+Math.abs(R)?(i[o+1][b-1]=(-p-l*i[o][b-1]+R*i[o][b])/f,i[o+1][b]=(-d-l*i[o][b]-R*i[o][b-1])/f):(y=cdiv$2(-E-m*i[o][b-1],-C-m*i[o][b],k,R),i[o+1][b-1]=y[0],i[o+1][b]=y[1])),M*(c=Math.max(Math.abs(i[o][b-1]),Math.abs(i[o][b])))*c>1)for(s=o;s<=b;s++)i[s][b-1]=i[s][b-1]/c,i[s][b]=i[s][b]/c}for(o=0;o<t;o++)if(o<0||o>x)for(s=o;s<t;s++)n[o][s]=i[o][s];for(s=t-1;s>=0;s--)for(o=0;o<=x;o++){for(k=0,a=0;a<=Math.min(s,x);a++)k+=n[o][a]*i[a][s];n[o][s]=k}}}function cdiv$2(t,e,r,n){var i,o;return Math.abs(r)>Math.abs(n)?[(t+(i=n/r)*e)/(o=r+i*n),(e-i*t)/o]:[((i=r/n)*t+e)/(o=n+i*r),(i*e-t)/o]}class CholeskyDecomposition$$1{constructor(t){if(!(t=WrapperMatrix2D$2.checkMatrix(t)).isSymmetric())throw new Error("Matrix is not symmetric");var e,r,n,i=t,o=i.rows,s=new Matrix$2(o,o),a=!0;for(r=0;r<o;r++){var u=s[r],h=0;for(n=0;n<r;n++){var c=s[n],l=0;for(e=0;e<n;e++)l+=c[e]*u[e];u[n]=l=(i.get(r,n)-l)/s[n][n],h+=l*l}for(a&=(h=i.get(r,r)-h)>0,s[r][r]=Math.sqrt(Math.max(h,0)),n=r+1;n<o;n++)s[r][n]=0}if(!a)throw new Error("Matrix is not positive definite");this.L=s}solve(t){t=WrapperMatrix2D$2.checkMatrix(t);var e=this.L,r=e.rows;if(t.rows!==r)throw new Error("Matrix dimensions do not match");var n,i,o,s=t.columns,a=t.clone();for(o=0;o<r;o++)for(i=0;i<s;i++){for(n=0;n<o;n++)a[o][i]-=a[n][i]*e[o][n];a[o][i]/=e[o][o]}for(o=r-1;o>=0;o--)for(i=0;i<s;i++){for(n=o+1;n<r;n++)a[o][i]-=a[n][i]*e[n][o];a[o][i]/=e[o][o]}return a}get lowerTriangularMatrix(){return this.L}}var src$2=Object.freeze({default:Matrix$2,Matrix:Matrix$2,abstractMatrix:AbstractMatrix$2,wrap:wrap$2,WrapperMatrix2D:WrapperMatrix2D$2,WrapperMatrix1D:WrapperMatrix1D$2,solve:solve$$1,inverse:inverse$$1,SingularValueDecomposition:SingularValueDecomposition$$1,SVD:SingularValueDecomposition$$1,EigenvalueDecomposition:EigenvalueDecomposition$$1,EVD:EigenvalueDecomposition$$1,CholeskyDecomposition:CholeskyDecomposition$$1,CHO:CholeskyDecomposition$$1,LuDecomposition:LuDecomposition$$1,LU:LuDecomposition$$1,QrDecomposition:QrDecomposition$$1,QR:QrDecomposition$$1}),array=createCommonjsModule((function(t,e){function r(t,e){return t-e}e.sum=function(t){for(var e=0,r=0;r<t.length;r++)e+=t[r];return e},e.max=function(t){for(var e=t[0],r=t.length,n=1;n<r;n++)t[n]>e&&(e=t[n]);return e},e.min=function(t){for(var e=t[0],r=t.length,n=1;n<r;n++)t[n]<e&&(e=t[n]);return e},e.minMax=function(t){for(var e=t[0],r=t[0],n=t.length,i=1;i<n;i++)t[i]<e&&(e=t[i]),t[i]>r&&(r=t[i]);return{min:e,max:r}},e.arithmeticMean=function(t){for(var e=0,r=t.length,n=0;n<r;n++)e+=t[n];return e/r},e.mean=e.arithmeticMean,e.geometricMean=function(t){for(var e=1,r=t.length,n=0;n<r;n++)e*=t[n];return Math.pow(e,1/r)},e.logMean=function(t){for(var e=0,r=t.length,n=0;n<r;n++)e+=Math.log(t[n]);return e/r},e.grandMean=function(t,e){for(var r=0,n=0,i=t.length,o=0;o<i;o++)r+=e[o]*t[o],n+=e[o];return r/n},e.truncatedMean=function(t,e,n){void 0===n&&(n=!1),n||(t=[].concat(t).sort(r));for(var i=t.length,o=Math.floor(i*e),s=0,a=o;a<i-o;a++)s+=t[a];return s/(i-2*o)},e.harmonicMean=function(t){for(var e=0,r=t.length,n=0;n<r;n++){if(0===t[n])throw new RangeError("value at index "+n+"is zero");e+=1/t[n]}return r/e},e.contraHarmonicMean=function(t){for(var e=0,r=0,n=t.length,i=0;i<n;i++)e+=t[i]*t[i],r+=t[i];if(r<0)throw new RangeError("sum of values is negative");return e/r},e.median=function(t,e){void 0===e&&(e=!1),e||(t=[].concat(t).sort(r));var n=t.length,i=Math.floor(n/2);return n%2==0?.5*(t[i-1]+t[i]):t[i]},e.variance=function(t,r){void 0===r&&(r=!0);for(var n=e.mean(t),i=0,o=t.length,s=0;s<o;s++){var a=t[s]-n;i+=a*a}return r?i/(o-1):i/o},e.standardDeviation=function(t,r){return Math.sqrt(e.variance(t,r))},e.standardError=function(t){return e.standardDeviation(t)/Math.sqrt(t.length)},e.robustMeanAndStdev=function(t){var e=0,n=t.length,i=0;for(i=0;i<n;i++)e+=t[i];e/=n;var o=new Array(n);for(i=0;i<n;i++)o[i]=Math.abs(t[i]-e);return o.sort(r),{mean:e,stdev:n%2==1?o[(n-1)/2]/.6745:.5*(o[n/2]+o[n/2-1])/.6745}},e.quartiles=function(t,n){void 0===n&&(n=!1),n||(t=[].concat(t).sort(r));var i=t.length/4;return{q1:t[Math.ceil(i)-1],q2:e.median(t,!0),q3:t[Math.ceil(3*i)-1]}},e.pooledStandardDeviation=function(t,r){return Math.sqrt(e.pooledVariance(t,r))},e.pooledVariance=function(t,r){void 0===r&&(r=!0);for(var n=0,i=0,o=t.length,s=0;s<o;s++){var a=t[s],u=e.variance(a);n+=(a.length-1)*u,i+=r?a.length-1:a.length}return n/i},e.mode=function(t){var e,r=t.length,n=new Array(r);for(e=0;e<r;e++)n[e]=0;var i=new Array(r),o=0;for(e=0;e<r;e++){var s=i.indexOf(t[e]);s>=0?n[s]++:(i[o]=t[e],n[o]=1,o++)}var a=0,u=0;for(e=0;e<o;e++)n[e]>a&&(a=n[e],u=e);return i[u]},e.covariance=function(t,r,n){void 0===n&&(n=!0);var i=e.mean(t),o=e.mean(r);if(t.length!==r.length)throw"Vectors do not have the same dimensions";for(var s=0,a=t.length,u=0;u<a;u++){s+=(t[u]-i)*(r[u]-o)}return n?s/(a-1):s/a},e.skewness=function(t,r){void 0===r&&(r=!0);for(var n=e.mean(t),i=0,o=0,s=t.length,a=0;a<s;a++){var u=t[a]-n;i+=u*u,o+=u*u*u}var h=i/s,c=o/s/Math.pow(h,1.5);return r?Math.sqrt(s*(s-1))/(s-2)*c:c},e.kurtosis=function(t,r){void 0===r&&(r=!0);for(var n=e.mean(t),i=t.length,o=0,s=0,a=0;a<i;a++){var u=t[a]-n;o+=u*u,s+=u*u*u*u}var h=o/i;if(r){var c=o/(i-1);return i*(i+1)/((i-1)*(i-2)*(i-3))*(s/(c*c))-3*((i-1)*(i-1)/((i-2)*(i-3)))}return s/i/(h*h)-3},e.entropy=function(t,e){void 0===e&&(e=0);for(var r=0,n=t.length,i=0;i<n;i++)r+=t[i]*Math.log(t[i]+e);return-r},e.weightedMean=function(t,e){for(var r=0,n=t.length,i=0;i<n;i++)r+=t[i]*e[i];return r},e.weightedStandardDeviation=function(t,r){return Math.sqrt(e.weightedVariance(t,r))},e.weightedVariance=function(t,r){for(var n=e.weightedMean(t,r),i=0,o=t.length,s=0,a=0,u=0;u<o;u++){var h=t[u]-n,c=r[u];i+=c*(h*h),a+=c,s+=c*c}return i*(a/(a*a-s))},e.center=function(t,r){void 0===r&&(r=!1);var n=t;r||(n=[].concat(t));for(var i=e.mean(n),o=n.length,s=0;s<o;s++)n[s]-=i},e.standardize=function(t,r,n){void 0===r&&(r=e.standardDeviation(t)),void 0===n&&(n=!1);for(var i=t.length,o=n?t:new Array(i),s=0;s<i;s++)o[s]=t[s]/r;return o},e.cumulativeSum=function(t){var e=t.length,r=new Array(e);r[0]=t[0];for(var n=1;n<e;n++)r[n]=r[n-1]+t[n];return r}})),array_1=array.sum,array_2=array.max,array_3=array.min,array_4=array.minMax,array_5=array.arithmeticMean,array_6=array.mean,array_7=array.geometricMean,array_8=array.logMean,array_9=array.grandMean,array_10=array.truncatedMean,array_11=array.harmonicMean,array_12=array.contraHarmonicMean,array_13=array.median,array_14=array.variance,array_15=array.standardDeviation,array_16=array.standardError,array_17=array.robustMeanAndStdev,array_18=array.quartiles,array_19=array.pooledStandardDeviation,array_20=array.pooledVariance,array_21=array.mode,array_22=array.covariance,array_23=array.skewness,array_24=array.kurtosis,array_25=array.entropy,array_26=array.weightedMean,array_27=array.weightedStandardDeviation,array_28=array.weightedVariance,array_29=array.center,array_30=array.standardize,array_31=array.cumulativeSum,matrix=createCommonjsModule((function(t,e){function r(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,c=0,l=0;l<i;l++)u+=c=t[l][a]-r[a],h+=c*c;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,n=t[0].length,i=new Array(n),o=0;o<n;o++){for(var s=new Array(e),a=0;a<e;a++)s[a]=t[a][o];s.sort(r);var u=s.length;i[o]=u%2==0?.5*(s[u/2]+s[u/2-1]):s[Math.floor(u/2)]}return i},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 c=u.indexOf(t[r][e]);c>=0?s[c]++:(u[h]=t[r][e],s[h]=1,h++)}var l=0,f=0;for(r=0;r<h;r++)s[r]>l&&(l=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,c=0;c<i;c++){var l=t[c][a]-n[a];u+=l*l,h+=l*l*l}var f=u/i,m=h/i/Math.pow(f,1.5);if(r){var p=Math.sqrt(i*(i-1)),d=i-2;s[a]=p/d*m}else s[a]=m}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,c=0;c<i;c++){var l=t[c][a]-n[a];u+=l*l,h+=l*l*l*l}var f=u/i,m=h/i;if(r){var p=u/(i-1),d=i*(i+1)/((i-1)*(i-2)*(i-3)),g=h/(p*p),v=(i-1)*(i-1)/((i-2)*(i-3));s[a]=d*g-3*v}else s[a]=m/(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,c,l=t[0].length;if(0===n){for(s=new Array(l),a=0;a<l;a++)s[a]=new Array(l);for(a=0;a<l;a++)for(u=a;u<l;u++){for(h=0,c=0;c<o;c++)h+=(t[c][u]-i[u])*(t[c][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,c=0;c<l;c++)h+=(t[u][c]-i[u])*(t[a][c]-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 c=0,l=0,f=s.length;l<f;l++)c+=s[l][n]*s[l][r];c/=a-1,h[r][n]=c,h[n][r]=c}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],c=t[i];for(o=0,s=h.length;o<s;o++)0===r[o]||isNaN(r[o])||(h[o]=c[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,c=0,l=0;l<i;l++){var f=t[l][a]-n[a],m=r[l];u+=m*(f*f),c+=m,h+=m*m}s[a]=u*(c/(c*c-h))}return s},e.weightedMean=function(t,e,r){void 0===r&&(r=0);var n=t.length;if(0===n)return[];var i,o,s,a,u,h,c=t[0].length;if(0===r){for(i=new Array(c),o=0;o<c;o++)i[o]=0;for(o=0;o<n;o++)for(h=t[o],u=e[o],a=0;a<c;a++)i[a]+=h[a]*u}else{if(1!==r)throw new Error("Invalid dimension");for(i=new Array(n),o=0;o<n;o++)i[o]=0;for(a=0;a<n;a++)for(h=t[a],u=e[a],o=0;o<c;o++)i[a]+=h[o]*u}var l=array.sum(e);if(0!==l)for(o=0,s=i.length;o<s;o++)i[o]/=l;return i},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,c,l,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(l=0,c=0;c<s;c++)l+=r[c]*(t[c][h]-n[h])*(t[c][u]-n[u]);a[u][h]=l*i,a[h][u]=l*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(l=0,c=0;c<f;c++)l+=r[c]*(t[h][c]-n[h])*(t[u][c]-n[u]);a[u][h]=l*i,a[h][u]=l*i}}return a}})),matrix_1=matrix.max,matrix_2=matrix.min,matrix_3=matrix.minMax,matrix_4=matrix.entropy,matrix_5=matrix.mean,matrix_6=matrix.sum,matrix_7=matrix.product,matrix_8=matrix.standardDeviation,matrix_9=matrix.variance,matrix_10=matrix.median,matrix_11=matrix.mode,matrix_12=matrix.skewness,matrix_13=matrix.kurtosis,matrix_14=matrix.standardError,matrix_15=matrix.covariance,matrix_16=matrix.scatter,matrix_17=matrix.correlation,matrix_18=matrix.zScores,matrix_19=matrix.center,matrix_20=matrix.standardize,matrix_21=matrix.weightedVariance,matrix_22=matrix.weightedMean,matrix_23=matrix.weightedCovariance,matrix_24=matrix.weightedScatter;const Matrix$3=src$2.Matrix,EVD=src$2.EVD,SVD=src$2.SVD,mean$2=matrix.mean,stdev=matrix.standardDeviation,defaultOptions$4={isCovarianceMatrix:!1,center:!0,scale:!1};class PCA{constructor(t,e){if(!0===t){const t=e;return this.center=t.center,this.scale=t.scale,this.means=t.means,this.stdevs=t.stdevs,this.U=Matrix$3.checkMatrix(t.U),void(this.S=t.S)}if(e=Object.assign({},defaultOptions$4,e),this.center=!1,this.scale=!1,this.means=null,this.stdevs=null,e.isCovarianceMatrix)this._computeFromCovarianceMatrix(t);else if("boolean"==typeof e.useCovarianceMatrix?e.useCovarianceMatrix:t.length>t[0].length){const r=(t=this._adjust(t,e)).transposeView().mmul(t).div(t.rows-1);this._computeFromCovarianceMatrix(r)}else{t=this._adjust(t,e);var r=new SVD(t,{computeLeftSingularVectors:!1,computeRightSingularVectors:!0,autoTranspose:!0});this.U=r.rightSingularVectors;const i=r.diagonal,o=new Array(i.length);for(var n=0;n<i.length;n++)o[n]=i[n]*i[n]/(t.length-1);this.S=o}}static load(t){if("PCA"!==t.name)throw new RangeError("Invalid model: "+t.name);return new PCA(!0,t)}predict(t,e={}){const{nComponents:r=this.U.columns}=e;t=new Matrix$3(t),this.center&&(t.subRowVector(this.means),this.scale&&t.divRowVector(this.stdevs));var n=t.mmul(this.U);return n.subMatrix(0,n.rows-1,0,r-1)}getExplainedVariance(){for(var t=0,e=0;e<this.S.length;e++)t+=this.S[e];return this.S.map((e=>e/t))}getCumulativeVariance(){for(var t=this.getExplainedVariance(),e=1;e<t.length;e++)t[e]+=t[e-1];return t}getEigenvectors(){return this.U}getEigenvalues(){return this.S}getStandardDeviations(){return this.S.map((t=>Math.sqrt(t)))}getLoadings(){return this.U.transpose()}toJSON(){return{name:"PCA",center:this.center,scale:this.scale,means:this.means,stdevs:this.stdevs,U:this.U,S:this.S}}_adjust(t,e){if(this.center=!!e.center,this.scale=!!e.scale,t=new Matrix$3(t),this.center){const e=mean$2(t),n=this.scale?stdev(t,e,!0):null;if(this.means=e,t.subRowVector(e),this.scale){for(var r=0;r<n.length;r++)if(0===n[r])throw new RangeError("Cannot scale the dataset (standard deviation is zero at index "+r);this.stdevs=n,t.divRowVector(n)}}return t}_computeFromCovarianceMatrix(t){const e=new EVD(t,{assumeSymmetric:!0});this.U=e.eigenvectorMatrix;for(var r=0;r<this.U.length;r++)this.U[r].reverse();this.S=e.realEigenvalues.reverse()}}var pca=PCA;function squaredEuclidean(t,e){for(var r=0,n=0;n<t.length;n++)r+=(t[n]-e[n])*(t[n]-e[n]);return r}function euclidean(t,e){return Math.sqrt(squaredEuclidean(t,e))}var euclidean_1=euclidean;euclidean.squared=squaredEuclidean;var heap=createCommonjsModule((function(t,e){(function(){var e,r,n,i,o,s,a,u,h,c,l,f,m,p,d;n=Math.floor,c=Math.min,r=function(t,e){return t<e?-1:t>e?1:0},h=function(t,e,i,o,s){var a;if(null==i&&(i=0),null==s&&(s=r),i<0)throw new Error("lo must be non-negative");for(null==o&&(o=t.length);i<o;)s(e,t[a=n((i+o)/2)])<0?o=a:i=a+1;return[].splice.apply(t,[i,i-i].concat(e)),e},s=function(t,e,n){return null==n&&(n=r),t.push(e),p(t,0,t.length-1,n)},o=function(t,e){var n,i;return null==e&&(e=r),n=t.pop(),t.length?(i=t[0],t[0]=n,d(t,0,e)):i=n,i},u=function(t,e,n){var i;return null==n&&(n=r),i=t[0],t[0]=e,d(t,0,n),i},a=function(t,e,n){var i;return null==n&&(n=r),t.length&&n(t[0],e)<0&&(e=(i=[t[0],e])[0],t[0]=i[1],d(t,0,n)),e},i=function(t,e){var i,o,s,a,u,h;for(null==e&&(e=r),u=[],o=0,s=(a=function(){h=[];for(var e=0,r=n(t.length/2);0<=r?e<r:e>r;0<=r?e++:e--)h.push(e);return h}.apply(this).reverse()).length;o<s;o++)i=a[o],u.push(d(t,i,e));return u},m=function(t,e,n){var i;if(null==n&&(n=r),-1!==(i=t.indexOf(e)))return p(t,0,i,n),d(t,i,n)},l=function(t,e,n){var o,s,u,h,c;if(null==n&&(n=r),!(s=t.slice(0,e)).length)return s;for(i(s,n),u=0,h=(c=t.slice(e)).length;u<h;u++)o=c[u],a(s,o,n);return s.sort(n).reverse()},f=function(t,e,n){var s,a,u,l,f,m,p,d,g;if(null==n&&(n=r),10*e<=t.length){if(!(u=t.slice(0,e).sort(n)).length)return u;for(a=u[u.length-1],l=0,m=(p=t.slice(e)).length;l<m;l++)n(s=p[l],a)<0&&(h(u,s,0,null,n),u.pop(),a=u[u.length-1]);return u}for(i(t,n),g=[],f=0,d=c(e,t.length);0<=d?f<d:f>d;0<=d?++f:--f)g.push(o(t,n));return g},p=function(t,e,n,i){var o,s,a;for(null==i&&(i=r),o=t[n];n>e&&i(o,s=t[a=n-1>>1])<0;)t[n]=s,n=a;return t[n]=o},d=function(t,e,n){var i,o,s,a,u;for(null==n&&(n=r),o=t.length,u=e,s=t[e],i=2*e+1;i<o;)(a=i+1)<o&&!(n(t[i],t[a])<0)&&(i=a),t[e]=t[i],i=2*(e=i)+1;return t[e]=s,p(t,u,e,n)},e=function(){function t(t){this.cmp=null!=t?t:r,this.nodes=[]}return t.push=s,t.pop=o,t.replace=u,t.pushpop=a,t.heapify=i,t.updateItem=m,t.nlargest=l,t.nsmallest=f,t.prototype.push=function(t){return s(this.nodes,t,this.cmp)},t.prototype.pop=function(){return o(this.nodes,this.cmp)},t.prototype.peek=function(){return this.nodes[0]},t.prototype.contains=function(t){return-1!==this.nodes.indexOf(t)},t.prototype.replace=function(t){return u(this.nodes,t,this.cmp)},t.prototype.pushpop=function(t){return a(this.nodes,t,this.cmp)},t.prototype.heapify=function(){return i(this.nodes,this.cmp)},t.prototype.updateItem=function(t){return m(this.nodes,t,this.cmp)},t.prototype.clear=function(){return this.nodes=[]},t.prototype.empty=function(){return 0===this.nodes.length},t.prototype.size=function(){return this.nodes.length},t.prototype.clone=function(){var e;return(e=new t).nodes=this.nodes.slice(0),e},t.prototype.toArray=function(){return this.nodes.slice(0)},t.prototype.insert=t.prototype.push,t.prototype.top=t.prototype.peek,t.prototype.front=t.prototype.peek,t.prototype.has=t.prototype.contains,t.prototype.copy=t.prototype.clone,t}(),t.exports=e}).call(commonjsGlobal)})),heap$1=heap;function Cluster(){this.children=[],this.distance=-1,this.index=[]}Cluster.prototype.cut=function(t){if(t<0)throw new RangeError("Threshold too small");var e=new Cluster;e.children=this.children,e.distance=this.distance,e.index=this.index;for(var r=[e],n=[];r.length>0;){var i=r.shift();t>=i.distance?n.push(i):r=r.concat(i.children)}return n},Cluster.prototype.group=function(t){if(!Number.isInteger(t)||t<1)throw new RangeError("Number of groups must be a positive integer");const e=new heap$1((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 n=new Cluster;return n.children=e.toArray(),n.distance=this.distance,n},Cluster.prototype.traverse=function(t){!function t(e,r){if(r(e),e.children)for(var n=e.children.length-1;n>=0;n--)t(e.children[n],r)}(this,t)};var Cluster_1=Cluster;function ClusterLeaf(t){Cluster_1.call(this),this.index=t,this.distance=0,this.children=[]}util$2.inherits(ClusterLeaf,Cluster_1);var ClusterLeaf_1=ClusterLeaf;function distanceMatrix(t,e){const r=t.length;let n=Array.from({length:r}).map((()=>Array.from({length:r})));for(let i=0;i<r;i++)for(let r=0;r<=i;r++)n[i][r]=e(t[i],t[r]);for(let t=0;t<r;t++)for(let e=t+1;e<r;e++)n[t][e]=n[e][t];return n}var src$3=distanceMatrix;function simpleLink(t,e,r){for(var n=1e101,i=0;i<t.length;i++)for(var o=0;o<e.length;o++){var s=r[t[i]][e[o]];n=Math.min(s,n)}return n}function completeLink(t,e,r){for(var n=-1,i=0;i<t.length;i++)for(var o=0;o<e.length;o++){var s=r[t[i]][e[o]];n=Math.max(s,n)}return n}function averageLink(t,e,r){for(var n=0,i=0;i<t.length;i++)for(var o=0;o<e.length;o++)n+=r[t[i]][e[o]];return n/(t.length*e.length)}function centroidLink(t,e,r){for(var n=new Array(t.length*e.length),i=0;i<t.length;i++)for(var o=0;o<e.length;o++)n[i*e.length+o]=r[t[i]][e[o]];return median$1(n)}function wardLink(t,e,r){return centroidLink(t,e,r)*t.length*e.length/(t.length+e.length)}function compareNumbers(t,e){return t-e}function median$1(t,e){void 0===e&&(e=!1),e||(t=[].concat(t).sort(compareNumbers));var r=t.length,n=Math.floor(r/2);return r%2==0?.5*(t[n-1]+t[n]):t[n]}var defaultOptions$5={disFunc:euclidean_1,kind:"single",isDistanceMatrix:!1};function agnes(t,e){e=Object.assign({},defaultOptions$5,e);var r=t.length,n=t;if(e.isDistanceMatrix||(n=src$3(t,e.disFunc)),"string"==typeof e.kind)switch(e.kind){case"single":e.kind=simpleLink;break;case"complete":e.kind=completeLink;break;case"average":e.kind=averageLink;break;case"centroid":e.kind=centroidLink;break;case"ward":e.kind=wardLink;break;default:throw new RangeError("Unknown kind of similarity")}else if("function"!=typeof e.kind)throw new TypeError("Undefined kind of similarity");for(var i=new Array(r),o=0;o<n.length;o++)i[o]=new ClusterLeaf_1(o);for(var s=1e6,a={},u=0;i.length>1;){a={},s=1e6;for(var h=0;h<i.length;h++)for(var c=h+1;c<i.length;c++){var l,f;if(i[h]instanceof ClusterLeaf_1)l=[i[h].index];else{l=new Array(i[h].index.length);for(var m=0;m<l.length;m++)l[m]=i[h].index[m].index}if(i[c]instanceof ClusterLeaf_1)f=[i[c].index];else{f=new Array(i[c].index.length);for(var p=0;p<f.length;p++)f[p]=i[c].index[p].index}(u=e.kind(l,f,n).toFixed(4))in a?a[u].push([i[h],i[c]]):a[u]=[[i[h],i[c]]],s=Math.min(u,s)}for(var d,g=a[s.toFixed(4)],v=new Array(g.length),w=0;g.length>0;){d=g.shift();for(var y=0;y<g.length;y++){if(g[y].filter((function(t){return-1!==d.indexOf(t)})).length>0){var b=g[y].filter((function(t){return-1===d.indexOf(t)}));d=d.concat(b),g.splice(y--,1)}}v[w++]=d}v.length=w;for(var x=0;x<v.length;x++){var M=new Cluster_1;M.children=v[x].concat(),M.distance=s,M.index=new Array(r);for(var _=0,$=0;$<v[x].length;$++)v[x][$]instanceof ClusterLeaf_1?M.index[_++]=v[x][$]:(_+=v[x][$].index.length,M.index=v[x][$].index.concat(M.index)),i.splice(i.indexOf(v[x][$]),1);M.index.length=_,i.push(M)}}return i[0]}var agnes_1=agnes;function simpleLink$1(t,e,r){for(var n=1e101,i=0;i<t.length;i++)for(var o=i;o<e.length;o++){var s=r(t[i],e[o]);n=Math.min(s,n)}return n}function completeLink$1(t,e,r){for(var n=-1,i=0;i<t.length;i++)for(var o=i;o<e.length;o++){var s=r(t[i],e[o]);n=Math.max(s,n)}return n}function averageLink$1(t,e,r){for(var n=0,i=0;i<t.length;i++)for(var o=0;o<e.length;o++)n+=r(t[i],e[o]);return n/(t.length*e.length)}function centroidLink$1(t,e,r){for(var n=0,i=0,o=0,s=0,a=0;a<t.length;a++)n+=t[a][0],i+=t[a][1];for(var u=0;u<e.length;u++)o+=e[u][0],s+=e[u][1];return r([n/=t.length,i/=t.length],[o/=e.length,s/=e.length])}function wardLink$1(t,e,r){for(var n=0,i=0,o=0,s=0,a=0;a<t.length;a++)n+=t[a][0],i+=t[a][1];for(var u=0;u<e.length;u++)o+=e[u][0],s+=e[u][1];return r([n/=t.length,i/=t.length],[o/=e.length,s/=e.length])*t.length*e.length/(t.length+e.length)}function diff(t,e,r){for(var n={d:0,p:0},i=new Array(t[0].length),o=0;o<t[0].length;o++)i[o]=e[t[0][o]];for(var s,a,u=new Array(t[1].length),h=0;h<t[1].length;h++)u[h]=e[t[1][h]];for(var c=0;c<i.length;c++){s=0;for(var l=0;l<i.length;l++)c!==l&&(s+=r(i[c],i[l]));s/=i.length-1,a=0;for(var f=0;f<u.length;f++)a+=r(i[c],u[f]);s-(a/=u.length)>n.d&&(n.d=s-a,n.p=c)}return n}var defaultOptions$6={dist:euclidean_1,kind:"single"};function intrDist(t,e,r){for(var n=0,i=0,o=0;o<t.length;o++)for(var s=o;s<t.length;s++)n+=r(e[t[o].index],e[t[s].index]),i++;return n/i}function diana(t,e){if("string"==typeof(e=Object.assign({},defaultOptions$6,e)).kind)switch(e.kind){case"single":e.kind=simpleLink$1;break;case"complete":e.kind=completeLink$1;break;case"average":e.kind=averageLink$1;break;case"centroid":e.kind=centroidLink$1;break;case"ward":e.kind=wardLink$1;break;default:throw new RangeError("Unknown kind of similarity")}else if("function"!=typeof e.kind)throw new TypeError("Undefined kind of similarity");var r,n,i,o,s,a=new Cluster_1;a.children=new Array(t.length),a.index=new Array(t.length);for(var u=0;u<t.length;u++)a.children[u]=new ClusterLeaf_1(u),a.index[u]=new ClusterLeaf_1(u);a.distance=intrDist(a.index,t,e.dist);for(var h=[a];h.length>0;){n=0,i=0;for(var c=0;c<h.length;c++){r=0;for(var l=0;l<h[c].length;l++)for(var f=l+1;f<h[c].length;f++)r=Math.max(e.dist(t[h[c].index[l].index],t[h[c].index[f].index]),r);r>n&&(n=r,i=c)}if(n=0,2===h[i].index.length)h[i].children=[h[i].index[0],h[i].index[1]],h[i].distance=e.dist(t[h[i].index[0].index],t[h[i].index[1].index]);else if(3===h[i].index.length){h[i].children=[h[i].index[0],h[i].index[1],h[i].index[2]];var m=[e.dist(t[h[i].index[0].index],t[h[i].index[1].index]),e.dist(t[h[i].index[1].index],t[h[i].index[2].index])];h[i].distance=(m[0]+m[1])/2}else{for(var p=new Cluster_1,d=new Cluster_1,g=[new Array(h[i].index.length),[]],v=0;v<g[0].length;v++)g[0][v]=v;for(var w=0;w<g[0].length;w++){o=0;for(var y=0;y<g[0].length;y++)w!==y&&(o+=e.dist(t[h[i].index[g[0][y]].index],t[h[i].index[g[0][w]].index]));(o/=g[0].length-1)>n&&(n=o,s=w)}for(g[1]=[s],g[0].splice(s,1),o=diff(g,t,e.dist);o.d>0;)g[1].push(g[0][o.p]),g[0].splice(o.p,1),o=diff(g,t,e.dist);var b=new Array(g[0].length);p.index=new Array(g[0].length);for(var x=0;x<b.length;x++)b[x]=t[h[i].index[g[0][x]].index],p.index[x]=h[i].index[g[0][x]],p.children[x]=h[i].index[g[0][x]];var M=new Array(g[1].length);d.index=new Array(g[1].length);for(var _=0;_<M.length;_++)M[_]=t[h[i].index[g[1][_]].index],d.index[_]=h[i].index[g[1][_]],d.children[_]=h[i].index[g[1][_]];p.distance=intrDist(p.index,t,e.dist),d.distance=intrDist(d.index,t,e.dist),h.push(p),h.push(d),h[i].children=[p,d]}h.splice(i,1)}return a}var diana_1=diana,agnes$1=agnes_1,diana$1=diana_1,src$4={agnes:agnes$1,diana:diana$1};const squaredDistance=euclidean_1.squared,defaultOptions$7={distanceFunction:squaredDistance,similarityFunction:!1,returnVector:!1};function nearestVector(t,e,r){const n=(r=r||defaultOptions$7).distanceFunction||defaultOptions$7.distanceFunction,i=r.similarityFunction||defaultOptions$7.similarityFunction,o=r.returnVector||defaultOptions$7.returnVector;var s=-1;if("function"==typeof i)for(var a=Number.MIN_VALUE,u=0;u<t.length;u++){var h=i(e,t[u]);h>a&&(a=h,s=u)}else{if("function"!=typeof n)throw new Error("A similarity or distance function it's required");for(var c=Number.MAX_VALUE,l=0;l<t.length;l++){var f=n(e,t[l]);f<c&&(c=f,s=l)}}return o?t[s]:s}var src$5=nearestVector;function calculateDistanceMatrix(t,e){for(var r=new Array(t.length),n=0;n<t.length;++n)for(var i=n;i<t.length;++i){r[n]||(r[n]=new Array(t.length)),r[i]||(r[i]=new Array(t.length));const o=e(t[n],t[i]);r[n][i]=o,r[i][n]=o}return r}function updateClusterID(t,e,r,n){for(var i=0;i<t.length;i++)r[i]=src$5(e,t[i],{distanceFunction:n});return r}function updateCenters(t,e,r){const n=t[0].length;for(var i=new Array(r),o=new Array(r),s=0;s<r;s++){i[s]=new Array(n),o[s]=0;for(var a=0;a<n;a++)i[s][a]=0}for(var u=0;u<t.length;u++){o[e[u]]++;for(var h=0;h<n;h++)i[e[u]][h]+=t[u][h]}for(var c=0;c<r;c++)for(var l=0;l<n;l++)i[c][l]/=o[c];return i}function converged(t,e,r,n){for(var i=0;i<t.length;i++)if(r(t[i],e[i])>n)return!1;return!0}var updateClusterID_1=updateClusterID,updateCenters_1=updateCenters,calculateDistanceMatrix_1=calculateDistanceMatrix,converged_1=converged,utils={updateClusterID:updateClusterID_1,updateCenters:updateCenters_1,calculateDistanceMatrix:calculateDistanceMatrix_1,converged:converged_1},Picker=createCommonjsModule((function(t){(function(e){var r;(r=t.exports?t.exports:this.RandomSelection={}).Picker=function(t){this._originalOptions=t,this._remainingOptions=[]},r.Picker.prototype={pick:function(){0===this._remainingOptions.length&&(this._remainingOptions=function(t){for(var e=[],r=0;r<t.length;r++)e.push(t[r]);return e}(this._originalOptions));var t=Math.floor(Math.random()*this._remainingOptions.length);return this._remainingOptions.splice(t,1)[0]}}}).call(commonjsGlobal)}));const Picker$1=Picker.Picker;function random$1(t,e){const r=new Picker$1(t);for(var n=new Array(e),i=0;i<e;++i)n[i]=r.pick();return n}function mostDistant(t,e,r){var n=new Array(e);if(n[0]=Math.floor(Math.random()*t.length),e>1){for(var i={dist:-1,index:-1},o=0;o<t.length;++o)r[n[0]][o]>i.dist&&(i.dist=r[n[0]][o],i.index=o);if(n[1]=i.index,e>2)for(var s=2;s<e;++s){for(var a={dist:-1,index:-1},u=0;u<t.length;++u){for(var h={dist:Number.MAX_VALUE,index:-1},c=0;c<s;++c)r[c][u]<h.dist&&-1===n.indexOf(u)&&(h={dist:r[c][u],index:u});h.dist!==Number.MAX_VALUE&&h.dist>a.dist&&(a=Object.assign({},h))}n[s]=a.index}}return n.map((e=>t[e]))}var random_1=random$1,mostDistant_1=mostDistant,initialization={random:random_1,mostDistant:mostDistant_1};const distanceSymbol=Symbol("distance");function KMeansResult(t,e,r,n,i){this.clusters=t,this.centroids=e,this.converged=r,this.iterations=n,this[distanceSymbol]=i}KMeansResult.prototype.nearest=function(t){var e=new Array(t.length),r=this.centroids.map((function(t){return t.centroid}));return utils.updateClusterID(t,r,e,this[distanceSymbol])},KMeansResult.prototype.computeInformation=function(t){for(var e=this.centroids.map((function(t){return{centroid:t,error:0,size:0}})),r=0;r<t.length;r++)e[this.clusters[r]].error+=this[distanceSymbol](t[r],this.centroids[this.clusters[r]]),e[this.clusters[r]].size++;for(var n=0;n<this.centroids.length;n++)e[n].error/=e[n].size;return new KMeansResult(this.clusters,e,this.converged,this.iterations,this[distanceSymbol])};var KMeansResult_1=KMeansResult;const squaredDistance$1=euclidean_1.squared,defaultOptions$8={maxIterations:100,tolerance:1e-6,withIterations:!1,initialization:"mostDistant",distanceFunction:squaredDistance$1};function step(t,e,r,n,i,o){r=utils.updateClusterID(e,t,r,i.distanceFunction);var s=utils.updateCenters(e,r,n),a=utils.converged(s,t,i.distanceFunction,i.tolerance);return new KMeansResult_1(r,s,a,o,i.distanceFunction)}function*kmeansGenerator(t,e,r,n,i){for(var o,s=!1,a=0;!s&&a<i.maxIterations;)o=step(t,e,r,n,i,++a),yield o.computeInformation(e),s=o.converged,t=o.centroids}function kmeans(t,e,r){if(r=Object.assign({},defaultOptions$8,r),e<=0||e>t.length||!Number.isInteger(e))throw new Error("K should be a positive integer bigger than the number of points");var n;if(Array.isArray(r.initialization)){if(r.initialization.length!==e)throw new Error("The initial centers should have the same length as K");n=r.initialization}else switch(r.initialization){case"random":n=initialization.random(t,e);break;case"mostDistant":n=initialization.mostDistant(t,e,utils.calculateDistanceMatrix(t,r.distanceFunction));break;default:throw new Error('Unknown initialization method: "'+r.initialization+'"')}0===r.maxIterations&&(r.maxIterations=Number.MAX_VALUE);var i=new Array(t.length);if(r.withIterations)return kmeansGenerator(n,t,i,e,r);for(var o,s=!1,a=0;!s&&a<r.maxIterations;)s=(o=step(n,t,i,e,r,++a)).converged,n=o.centroids;return o.computeInformation(t)}var kmeans_1=kmeans;const squaredEuclidean$1=euclidean_1.squared,defaultOptions$9={sigma:1};class GaussianKernel{constructor(t){t=Object.assign({},defaultOptions$9,t),this.sigma=t.sigma,this.divisor=2*t.sigma*t.sigma}compute(t,e){const r=squaredEuclidean$1(t,e);return Math.exp(-r/this.divisor)}}var gaussianKernel=GaussianKernel;const defaultOptions$a={degree:1,constant:1,scale:1};class PolynomialKernel{constructor(t){t=Object.assign({},defaultOptions$a,t),this.degree=t.degree,this.constant=t.constant,this.scale=t.scale}compute(t,e){for(var r=0,n=0;n<t.length;n++)r+=t[n]*e[n];return Math.pow(this.scale*r+this.constant,this.degree)}}var polynomialKernel=PolynomialKernel;const defaultOptions$b={sigma:1,degree:1};class ANOVAKernel{constructor(t){t=Object.assign({},defaultOptions$b,t),this.sigma=t.sigma,this.degree=t.degree}compute(t,e){for(var r=0,n=Math.min(t.length,e.length),i=1;i<=n;++i)r+=Math.pow(Math.exp(-this.sigma*Math.pow(Math.pow(t[i-1],i)-Math.pow(e[i-1],i),2)),this.degree);return r}}var anovaKernel=ANOVAKernel;const squaredEuclidean$2=euclidean_1.squared,defaultOptions$c={sigma:1};class CauchyKernel{constructor(t){t=Object.assign({},defaultOptions$c,t),this.sigma=t.sigma}compute(t,e){return 1/(1+squaredEuclidean$2(t,e)/(this.sigma*this.sigma))}}var cauchyKernel=CauchyKernel;const defaultOptions$d={sigma:1};class ExponentialKernel{constructor(t){t=Object.assign({},defaultOptions$d,t),this.sigma=t.sigma,this.divisor=2*t.sigma*t.sigma}compute(t,e){const r=euclidean_1(t,e);return Math.exp(-r/this.divisor)}}var exponentialKernel=ExponentialKernel;class HistogramIntersectionKernel{compute(t,e){for(var r=Math.min(t.length,e.length),n=0,i=0;i<r;++i)n+=Math.min(t[i],e[i]);return n}}var histogramIntersectionKernel=HistogramIntersectionKernel;const defaultOptions$e={sigma:1};class LaplacianKernel{constructor(t){t=Object.assign({},defaultOptions$e,t),this.sigma=t.sigma}compute(t,e){const r=euclidean_1(t,e);return Math.exp(-r/this.sigma)}}var laplacianKernel=LaplacianKernel;const squaredEuclidean$3=euclidean_1.squared,defaultOptions$f={constant:1};class MultiquadraticKernel{constructor(t){t=Object.assign({},defaultOptions$f,t),this.constant=t.constant}compute(t,e){return Math.sqrt(squaredEuclidean$3(t,e)+this.constant*this.constant)}}var multiquadraticKernel=MultiquadraticKernel;const squaredEuclidean$4=euclidean_1.squared,defaultOptions$g={constant:1};class RationalQuadraticKernel{constructor(t){t=Object.assign({},defaultOptions$g,t),this.constant=t.constant}compute(t,e){const r=squaredEuclidean$4(t,e);return 1-r/(r+this.constant)}}var rationalQuadraticKernel=RationalQuadraticKernel;const defaultOptions$h={alpha:.01,constant:-Math.E};class SigmoidKernel{constructor(t){t=Object.assign({},defaultOptions$h,t),this.alpha=t.alpha,this.constant=t.constant}compute(t,e){for(var r=0,n=0;n<t.length;n++)r+=t[n]*e[n];return Math.tanh(this.alpha*r+this.constant)}}var sigmoidKernel=SigmoidKernel;const Matrix$4=require$$0$3.Matrix,kernelType={gaussian:gaussianKernel,rbf:gaussianKernel,polynomial:polynomialKernel,poly:polynomialKernel,anova:anovaKernel,cauchy:cauchyKernel,exponential:exponentialKernel,histogram:histogramIntersectionKernel,min:histogramIntersectionKernel,laplacian:laplacianKernel,multiquadratic:multiquadraticKernel,rational:rationalQuadraticKernel,sigmoid:sigmoidKernel,mlp:sigmoidKernel};class Kernel{constructor(t,e){if(this.kernelType=t,"linear"!==t)if("string"==typeof t){t=t.toLowerCase();var r=kernelType[t];if(!r)throw new Error("unsupported kernel type: "+t);this.kernelFunction=new r(e)}else{if("object"!=typeof t||"function"!=typeof t.compute)throw new TypeError("first argument must be a valid kernel type or instance");this.kernelFunction=t}}compute(t,e){if(void 0===e&&(e=t),"linear"===this.kernelType)return new Matrix$4(t).mmul(new Matrix$4(e).transposeView());const r=new Matrix$4(t.length,e.length);var n,i;if(t===e)for(n=0;n<t.length;n++)for(i=n;i<t.length;i++)r[n][i]=r[i][n]=this.kernelFunction.compute(t[n],t[i]);else for(n=0;n<t.length;n++)for(i=0;i<e.length;i++)r[n][i]=this.kernelFunction.compute(t[n],e[i]);return r}}var kernel=Kernel,array$1=array,matrix$1=matrix,mlStat={array:array$1,matrix:matrix$1};const stat=mlStat.array;var defaultOptions$i={C:1,tol:1e-4,maxPasses:10,maxIterations:1e4,kernel:"linear",alphaTol:1e-6,random:Math.random,whitening:!0};function SVM(t){this.options=Object.assign({},defaultOptions$i,t),this.kernel=new kernel(this.options.kernel,this.options.kernelOptions),this.b=0}SVM.prototype.train=function(t,e){if(t.length!==e.length)throw new Error("Features and labels should have the same length");if(t.length<2)throw new Error("Cannot train with less than 2 observations");if(this._trained=!1,this._loaded=!1,this.N=e.length,this.D=t[0].length,this.options.whitening){this.X=new Array(this.N);for(var r=0;r<this.N;r++)this.X[r]=new Array(this.D);this.minMax=new Array(this.D);for(var n=0;n<this.D;n++){var i=new Array(this.N);for(r=0;r<this.N;r++)i[r]=t[r][n];for(this.minMax[n]=stat.minMax(i),r=0;r<this.N;r++)this.X[r][n]=(t[r][n]-this.minMax[n].min)/(this.minMax[n].max-this.minMax[n].min)}}else this.X=t;this.Y=e,this.b=0,this.W=void 0;var o=this.kernel.compute(this.X),s=e.length,a=new Array(s).fill(0);this.alphas=a;for(var u=0;u<s;u++)a[u]=0;for(var h=0,c=0,l=0,f=0,m=0,p=0,d=0,g=0,v=0,w=0,y=0;f<this.options.maxPasses&&l<this.options.maxIterations;){var b=0;for(r=0;r<s;r++)if(m=this._marginOnePrecomputed(r,o)-e[r],e[r]*m<-this.options.tol&&a[r]<this.options.C||e[r]*m>this.options.tol&&a[r]>0){for(n=r;n===r;)n=Math.floor(this.options.random()*s);if(p=this._marginOnePrecomputed(n,o)-e[n],d=a[r],g=a[n],e[r]===e[n]?(v=Math.max(0,d+g-this.options.C),w=Math.min(this.options.C,d+g)):(v=Math.max(0,g-d),w=Math.min(this.options.C,this.options.C+g+d)),Math.abs(v-w)<1e-4)continue;if((y=2*o[r][n]-o[r][r]-o[n][n])>=0)continue;var x=a[n]-e[n]*(m-p)/y;if(x>w?x=w:x<v&&(x=v),Math.abs(g-x)<.001)continue;a[n]=x,a[r]=a[r]+e[r]*e[n]*(g-x),h=this.b-m-e[r]*(a[r]-d)*o[r][r]-e[n]*(a[n]-g)*o[r][n],c=this.b-p-e[r]*(a[r]-d)*o[r][n]-e[n]*(a[n]-g)*o[n][n],this.b=(h+c)/2,a[r]<this.options.C&&a[r]>0&&(this.b=h),a[n]<this.options.C&&a[n]>0&&(this.b=c),b+=1}l++,0===b?f+=1:f=0}if(l===this.options.maxIterations)throw new Error("max iterations reached");if(this.iterations=l,"linear"===this.options.kernel){this.W=new Array(this.D);for(var M=0;M<this.D;M++){this.W[M]=0;for(var _=0;_<s;_++)this.W[M]+=e[_]*a[_]*this.X[_][M]}}var $=[],S=[],R=[];for(this._supportVectorIdx=[],r=0;r<this.N;r++)this.alphas[r]>this.options.alphaTol&&($.push(this.X[r]),S.push(e[r]),R.push(this.alphas[r]),this._supportVectorIdx.push(r));this.X=$,this.Y=S,this.N=$.length,this.alphas=R,this._trained=!0},SVM.prototype.predictOne=function(t){return this.marginOne(t)>0?1:-1},SVM.prototype.predict=function(t){if(!this._trained&&!this._loaded)throw new Error("Cannot predict, you need to train the SVM first");return Array.isArray(t)&&Array.isArray(t[0])?t.map(this.predictOne.bind(this)):this.predictOne(t)},SVM.prototype.marginOne=function(t,e){this.options.whitening&&!e&&(t=this._applyWhitening(t));var r,n=this.b;if("linear"===this.options.kernel&&this.W)for(r=0;r<this.W.length;r++)n+=this.W[r]*t[r];else for(r=0;r<this.N;r++)n+=this.alphas[r]*this.Y[r]*this.kernel.compute([t],[this.X[r]])[0][0];return n},SVM.prototype._marginOnePrecomputed=function(t,e){var r,n=this.b;for(r=0;r<this.N;r++)n+=this.alphas[r]*this.Y[r]*e[t][r];return n},SVM.prototype.margin=function(t){return Array.isArray(t)?t.map(this.marginOne.bind(this)):this.marginOne(t)},SVM.prototype.supportVectors=function(){if(!this._trained&&!this._loaded)throw new Error("Cannot get support vectors, you need to train the SVM first");if(this._loaded&&"linear"===this.options.kernel)throw new Error("Cannot get support vectors from saved linear model, you need to train the SVM to have them");return this._supportVectorIdx},SVM.load=function(t){this._loaded=!0,this._trained=!1;var e=new SVM(t.options);return"linear"===t.options.kernel?(e.W=t.W.slice(),e.D=e.W.length):(e.X=t.X.slice(),e.Y=t.Y.slice(),e.alphas=t.alphas.slice(),e.N=e.X.length,e.D=e.X[0].length),e.minMax=t.minMax,e.b=t.b,e._loaded=!0,e._trained=!1,e},SVM.prototype.toJSON=function(){if(!this._trained&&!this._loaded)throw new Error("Cannot export, you need to train the SVM first");var t={};return t.options=Object.assign({},this.options),t.b=this.b,t.minMax=this.minMax,"linear"===t.options.kernel?t.W=this.W.slice():(t.X=this.X.slice(),t.Y=this.Y.slice(),t.alphas=this.alphas.slice()),t},SVM.prototype._applyWhitening=function(t){if(!this.minMax)throw new Error("Could not apply whitening");for(var e=new Array(t.length),r=0;r<t.length;r++)e[r]=(t[r]-this.minMax[r].min)/(this.minMax[r].max-this.minMax[r].min);return e};var svm=SVM;Symbol.species||(Symbol.species=Symbol.for("@@species"));class LuDecomposition$$1{constructor(t){var e,r,n,i,o,s,a,u,h,c=(t=WrapperMatrix2D$3.checkMatrix(t)).clone(),l=c.rows,f=c.columns,m=new Array(l),p=1;for(e=0;e<l;e++)m[e]=e;for(u=new Array(l),r=0;r<f;r++){for(e=0;e<l;e++)u[e]=c.get(e,r);for(e=0;e<l;e++){for(h=Math.min(e,r),o=0,n=0;n<h;n++)o+=c.get(e,n)*u[n];u[e]-=o,c.set(e,r,u[e])}for(i=r,e=r+1;e<l;e++)Math.abs(u[e])>Math.abs(u[i])&&(i=e);if(i!==r){for(n=0;n<f;n++)s=c.get(i,n),c.set(i,n,c.get(r,n)),c.set(r,n,s);a=m[i],m[i]=m[r],m[r]=a,p=-p}if(r<l&&0!==c.get(r,r))for(e=r+1;e<l;e++)c.set(e,r,c.get(e,r)/c.get(r,r))}this.LU=c,this.pivotVector=m,this.pivotSign=p}isSingular(){for(var t=this.LU,e=t.columns,r=0;r<e;r++)if(0===t[r][r])return!0;return!1}solve(t){t=Matrix$5.checkMatrix(t);var e=this.LU;if(e.rows!==t.rows)throw new Error("Invalid matrix dimensions");if(this.isSingular())throw new Error("LU matrix is singular");var r,n,i,o=t.columns,s=t.subMatrixRow(this.pivotVector,0,o-1),a=e.columns;for(i=0;i<a;i++)for(r=i+1;r<a;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i];for(i=a-1;i>=0;i--){for(n=0;n<o;n++)s[i][n]/=e[i][i];for(r=0;r<i;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i]}return s}get determinant(){var t=this.LU;if(!t.isSquare())throw new Error("Matrix must be square");for(var e=this.pivotSign,r=t.columns,n=0;n<r;n++)e*=t[n][n];return e}get lowerTriangularMatrix(){for(var t=this.LU,e=t.rows,r=t.columns,n=new Matrix$5(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i>o?t[i][o]:i===o?1:0;return n}get upperTriangularMatrix(){for(var t=this.LU,e=t.rows,r=t.columns,n=new Matrix$5(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i<=o?t[i][o]:0;return n}get pivotPermutationVector(){return this.pivotVector.slice()}}function hypotenuse$3(t,e){var r=0;return Math.abs(t)>Math.abs(e)?(r=e/t,Math.abs(t)*Math.sqrt(1+r*r)):0!==e?(r=t/e,Math.abs(e)*Math.sqrt(1+r*r)):0}function getFilled2DArray$3(t,e,r){for(var n=new Array(t),i=0;i<t;i++){n[i]=new Array(e);for(var o=0;o<e;o++)n[i][o]=r}return n}class SingularValueDecomposition$$1{constructor(t,e={}){var r=(t=WrapperMatrix2D$3.checkMatrix(t)).rows,n=t.columns,i=Math.min(r,n);const{computeLeftSingularVectors:o=!0,computeRightSingularVectors:s=!0,autoTranspose:a=!1}=e;var u,h=Boolean(o),c=Boolean(s),l=!1;if(r<n)if(a){r=(u=t.transpose()).rows,n=u.columns,l=!0;var f=h;h=c,c=f}else u=t.clone(),console.warn("Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose");else u=t.clone();var m,p,d,g,v,w,y,b,x,M,_,$,S,R,E,C,k,A,T,O,I,D=new Array(Math.min(r+1,n)),P=getFilled2DArray$3(r,i,0),V=getFilled2DArray$3(n,n,0),j=new Array(n),L=new Array(r),N=Math.min(r-1,n),B=Math.max(0,Math.min(n-2,r));for(d=0,M=Math.max(N,B);d<M;d++){if(d<N){for(D[d]=0,m=d;m<r;m++)D[d]=hypotenuse$3(D[d],u[m][d]);if(0!==D[d]){for(u[d][d]<0&&(D[d]=-D[d]),m=d;m<r;m++)u[m][d]/=D[d];u[d][d]+=1}D[d]=-D[d]}for(p=d+1;p<n;p++){if(d<N&&0!==D[d]){for(v=0,m=d;m<r;m++)v+=u[m][d]*u[m][p];for(v=-v/u[d][d],m=d;m<r;m++)u[m][p]+=v*u[m][d]}j[p]=u[d][p]}if(h&&d<N)for(m=d;m<r;m++)P[m][d]=u[m][d];if(d<B){for(j[d]=0,m=d+1;m<n;m++)j[d]=hypotenuse$3(j[d],j[m]);if(0!==j[d]){for(j[d+1]<0&&(j[d]=0-j[d]),m=d+1;m<n;m++)j[m]/=j[d];j[d+1]+=1}if(j[d]=-j[d],d+1<r&&0!==j[d]){for(m=d+1;m<r;m++)L[m]=0;for(p=d+1;p<n;p++)for(m=d+1;m<r;m++)L[m]+=j[p]*u[m][p];for(p=d+1;p<n;p++)for(v=-j[p]/j[d+1],m=d+1;m<r;m++)u[m][p]+=v*L[m]}if(c)for(m=d+1;m<n;m++)V[m][d]=j[m]}}if(g=Math.min(n,r+1),N<n&&(D[N]=u[N][N]),r<g&&(D[g-1]=0),B+1<g&&(j[B]=u[B][g-1]),j[g-1]=0,h){for(p=N;p<i;p++){for(m=0;m<r;m++)P[m][p]=0;P[p][p]=1}for(d=N-1;d>=0;d--)if(0!==D[d]){for(p=d+1;p<i;p++){for(v=0,m=d;m<r;m++)v+=P[m][d]*P[m][p];for(v=-v/P[d][d],m=d;m<r;m++)P[m][p]+=v*P[m][d]}for(m=d;m<r;m++)P[m][d]=-P[m][d];for(P[d][d]=1+P[d][d],m=0;m<d-1;m++)P[m][d]=0}else{for(m=0;m<r;m++)P[m][d]=0;P[d][d]=1}}if(c)for(d=n-1;d>=0;d--){if(d<B&&0!==j[d])for(p=d+1;p<n;p++){for(v=0,m=d+1;m<n;m++)v+=V[m][d]*V[m][p];for(v=-v/V[d+1][d],m=d+1;m<n;m++)V[m][p]+=v*V[m][d]}for(m=0;m<n;m++)V[m][d]=0;V[d][d]=1}for(var F=g-1,z=Number.EPSILON;g>0;){for(d=g-2;d>=-1&&-1!==d;d--)if(Math.abs(j[d])<=z*(Math.abs(D[d])+Math.abs(D[d+1]))){j[d]=0;break}if(d===g-2)_=4;else{for(w=g-1;w>=d&&w!==d;w--)if(v=(w!==g?Math.abs(j[w]):0)+(w!==d+1?Math.abs(j[w-1]):0),Math.abs(D[w])<=z*v){D[w]=0;break}w===d?_=3:w===g-1?_=1:(_=2,d=w)}switch(d++,_){case 1:for(y=j[g-2],j[g-2]=0,p=g-2;p>=d;p--)if(v=hypotenuse$3(D[p],y),b=D[p]/v,x=y/v,D[p]=v,p!==d&&(y=-x*j[p-1],j[p-1]=b*j[p-1]),c)for(m=0;m<n;m++)v=b*V[m][p]+x*V[m][g-1],V[m][g-1]=-x*V[m][p]+b*V[m][g-1],V[m][p]=v;break;case 2:for(y=j[d-1],j[d-1]=0,p=d;p<g;p++)if(v=hypotenuse$3(D[p],y),b=D[p]/v,x=y/v,D[p]=v,y=-x*j[p],j[p]=b*j[p],h)for(m=0;m<r;m++)v=b*P[m][p]+x*P[m][d-1],P[m][d-1]=-x*P[m][p]+b*P[m][d-1],P[m][p]=v;break;case 3:for($=Math.max(Math.abs(D[g-1]),Math.abs(D[g-2]),Math.abs(j[g-2]),Math.abs(D[d]),Math.abs(j[d])),S=D[g-1]/$,R=D[g-2]/$,E=j[g-2]/$,C=D[d]/$,k=j[d]/$,T=S*E*(S*E),O=0,0===(A=((R+S)*(R-S)+E*E)/2)&&0===T||(O=Math.sqrt(A*A+T),A<0&&(O=-O),O=T/(A+O)),y=(C+S)*(C-S)+O,I=C*k,p=d;p<g-1;p++){if(b=y/(v=hypotenuse$3(y,I)),x=I/v,p!==d&&(j[p-1]=v),y=b*D[p]+x*j[p],j[p]=b*j[p]-x*D[p],I=x*D[p+1],D[p+1]=b*D[p+1],c)for(m=0;m<n;m++)v=b*V[m][p]+x*V[m][p+1],V[m][p+1]=-x*V[m][p]+b*V[m][p+1],V[m][p]=v;if(b=y/(v=hypotenuse$3(y,I)),x=I/v,D[p]=v,y=b*j[p]+x*D[p+1],D[p+1]=-x*j[p]+b*D[p+1],I=x*j[p+1],j[p+1]=b*j[p+1],h&&p<r-1)for(m=0;m<r;m++)v=b*P[m][p]+x*P[m][p+1],P[m][p+1]=-x*P[m][p]+b*P[m][p+1],P[m][p]=v}j[g-2]=y;break;case 4:if(D[d]<=0&&(D[d]=D[d]<0?-D[d]:0,c))for(m=0;m<=F;m++)V[m][d]=-V[m][d];for(;d<F&&!(D[d]>=D[d+1]);){if(v=D[d],D[d]=D[d+1],D[d+1]=v,c&&d<n-1)for(m=0;m<n;m++)v=V[m][d+1],V[m][d+1]=V[m][d],V[m][d]=v;if(h&&d<r-1)for(m=0;m<r;m++)v=P[m][d+1],P[m][d+1]=P[m][d],P[m][d]=v;d++}g--}}if(l){var q=V;V=P,P=q}this.m=r,this.n=n,this.s=D,this.U=P,this.V=V}solve(t){var e,r=t,n=this.threshold,i=this.s.length,o=Matrix$5.zeros(i,i);for(e=0;e<i;e++)Math.abs(this.s[e])<=n?o[e][e]=0:o[e][e]=1/this.s[e];var s,a,u,h=this.U,c=this.rightSingularVectors,l=c.mmul(o),f=c.rows,m=h.length,p=Matrix$5.zeros(f,m);for(e=0;e<f;e++)for(s=0;s<m;s++){for(u=0,a=0;a<i;a++)u+=l[e][a]*h[s][a];p[e][s]=u}return p.mmul(r)}solveForDiagonal(t){return this.solve(Matrix$5.diag(t))}inverse(){var t,e,r=this.V,n=this.threshold,i=r.length,o=r[0].length,s=new Matrix$5(i,this.s.length);for(t=0;t<i;t++)for(e=0;e<o;e++)Math.abs(this.s[e])>n?s[t][e]=r[t][e]/this.s[e]:s[t][e]=0;var a,u,h=this.U,c=h.length,l=h[0].length,f=new Matrix$5(i,c);for(t=0;t<i;t++)for(e=0;e<c;e++){for(u=0,a=0;a<l;a++)u+=s[t][a]*h[e][a];f[t][e]=u}return f}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 Matrix$5.isMatrix(this.U)||(this.U=new Matrix$5(this.U)),this.U}get rightSingularVectors(){return Matrix$5.isMatrix(this.V)||(this.V=new Matrix$5(this.V)),this.V}get diagonalMatrix(){return Matrix$5.diag(this.s)}}function checkRowIndex$3(t,e,r){var n=r?t.rows:t.rows-1;if(e<0||e>n)throw new RangeError("Row index out of range")}function checkColumnIndex$3(t,e,r){var n=r?t.columns:t.columns-1;if(e<0||e>n)throw new RangeError("Column index out of range")}function checkRowVector$3(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.columns)throw new RangeError("vector size must be the same as the number of columns");return e}function checkColumnVector$3(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.rows)throw new RangeError("vector size must be the same as the number of rows");return e}function checkIndices$3(t,e,r){return{row:checkRowIndices$3(t,e),column:checkColumnIndices$3(t,r)}}function checkRowIndices$3(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for row indices");if(e.some((e=>e<0||e>=t.rows)))throw new RangeError("row indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkColumnIndices$3(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for column indices");var r=e.some((e=>e<0||e>=t.columns));if(r)throw new RangeError("column indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkRange$3(t,e,r,n,i){if(5!==arguments.length)throw new TypeError("Invalid argument type");if(Array.from(arguments).slice(1).some((function(t){return"number"!=typeof t})))throw new TypeError("Invalid argument type");if(e>r||n>i||e<0||e>=t.rows||r<0||r>=t.rows||n<0||n>=t.columns||i<0||i>=t.columns)throw new RangeError("Submatrix indices are out of range")}function sumByRow$3(t){for(var e=Matrix$5.zeros(t.rows,1),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(r,0,e.get(r,0)+t.get(r,n));return e}function sumByColumn$3(t){for(var e=Matrix$5.zeros(1,t.columns),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(0,n,e.get(0,n)+t.get(r,n));return e}function sumAll$3(t){for(var e=0,r=0;r<t.rows;r++)for(var n=0;n<t.columns;n++)e+=t.get(r,n);return e}class BaseView$3 extends(AbstractMatrix$3()){constructor(t,e,r){super(),this.matrix=t,this.rows=e,this.columns=r}static get[Symbol.species](){return Matrix$5}}class MatrixTransposeView$3 extends BaseView$3{constructor(t){super(t,t.columns,t.rows)}set(t,e,r){return this.matrix.set(e,t,r),this}get(t,e){return this.matrix.get(e,t)}}class MatrixRowView$3 extends BaseView$3{constructor(t,e){super(t,1,t.columns),this.row=e}set(t,e,r){return this.matrix.set(this.row,e,r),this}get(t,e){return this.matrix.get(this.row,e)}}class MatrixSubView$3 extends BaseView$3{constructor(t,e,r,n,i){checkRange$3(t,e,r,n,i),super(t,r-e+1,i-n+1),this.startRow=e,this.startColumn=n}set(t,e,r){return this.matrix.set(this.startRow+t,this.startColumn+e,r),this}get(t,e){return this.matrix.get(this.startRow+t,this.startColumn+e)}}class MatrixSelectionView$3 extends BaseView$3{constructor(t,e,r){var n=checkIndices$3(t,e,r);super(t,n.row.length,n.column.length),this.rowIndices=n.row,this.columnIndices=n.column}set(t,e,r){return this.matrix.set(this.rowIndices[t],this.columnIndices[e],r),this}get(t,e){return this.matrix.get(this.rowIndices[t],this.columnIndices[e])}}class MatrixRowSelectionView$3 extends BaseView$3{constructor(t,e){super(t,(e=checkRowIndices$3(t,e)).length,t.columns),this.rowIndices=e}set(t,e,r){return this.matrix.set(this.rowIndices[t],e,r),this}get(t,e){return this.matrix.get(this.rowIndices[t],e)}}class MatrixColumnSelectionView$3 extends BaseView$3{constructor(t,e){e=checkColumnIndices$3(t,e),super(t,t.rows,e.length),this.columnIndices=e}set(t,e,r){return this.matrix.set(t,this.columnIndices[e],r),this}get(t,e){return this.matrix.get(t,this.columnIndices[e])}}class MatrixColumnView$3 extends BaseView$3{constructor(t,e){super(t,t.rows,1),this.column=e}set(t,e,r){return this.matrix.set(t,this.column,r),this}get(t){return this.matrix.get(t,this.column)}}class MatrixFlipRowView$3 extends BaseView$3{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(this.rows-t-1,e,r),this}get(t,e){return this.matrix.get(this.rows-t-1,e)}}class MatrixFlipColumnView$3 extends BaseView$3{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(t,this.columns-e-1,r),this}get(t,e){return this.matrix.get(t,this.columns-e-1)}}function AbstractMatrix$3(t){void 0===t&&(t=Object);class e extends t{static get[Symbol.species](){return this}static from1DArray(t,e,r){if(t*e!==r.length)throw new RangeError("Data length does not match given dimensions");for(var n=new this(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r[i*e+o]);return n}static rowVector(t){for(var e=new this(1,t.length),r=0;r<t.length;r++)e.set(0,r,t[r]);return e}static columnVector(t){for(var e=new this(t.length,1),r=0;r<t.length;r++)e.set(r,0,t[r]);return e}static empty(t,e){return new this(t,e)}static zeros(t,e){return this.empty(t,e).fill(0)}static ones(t,e){return this.empty(t,e).fill(1)}static rand(t,e,r){void 0===r&&(r=Math.random);for(var n=this.empty(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r());return n}static randInt(t,e,r,n){void 0===r&&(r=1e3),void 0===n&&(n=Math.random);for(var i=this.empty(t,e),o=0;o<t;o++)for(var s=0;s<e;s++){var a=Math.floor(n()*r);i.set(o,s,a)}return i}static eye(t,e,r){void 0===e&&(e=t),void 0===r&&(r=1);for(var n=Math.min(t,e),i=this.zeros(t,e),o=0;o<n;o++)i.set(o,o,r);return i}static diag(t,e,r){var n=t.length;void 0===e&&(e=n),void 0===r&&(r=e);for(var i=Math.min(n,e,r),o=this.zeros(e,r),s=0;s<i;s++)o.set(s,s,t[s]);return o}static min(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.min(t.get(o,s),e.get(o,s)));return i}static max(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.max(t.get(o,s),e.get(o,s)));return i}static checkMatrix(t){return e.isMatrix(t)?t:new this(t)}static isMatrix(t){return null!=t&&"Matrix"===t.klass}get size(){return this.rows*this.columns}apply(t){if("function"!=typeof t)throw new TypeError("callback must be a function");for(var e=this.rows,r=this.columns,n=0;n<e;n++)for(var i=0;i<r;i++)t.call(this,n,i);return this}to1DArray(){for(var t=new Array(this.size),e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t[e*this.columns+r]=this.get(e,r);return t}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}isRowVector(){return 1===this.rows}isColumnVector(){return 1===this.columns}isVector(){return 1===this.rows||1===this.columns}isSquare(){return this.rows===this.columns}isSymmetric(){if(this.isSquare()){for(var t=0;t<this.rows;t++)for(var e=0;e<=t;e++)if(this.get(t,e)!==this.get(e,t))return!1;return!0}return!1}set(t,e,r){throw new Error("set method is unimplemented")}get(t,e){throw new Error("get method is unimplemented")}repeat(t,e){t=t||1,e=e||1;for(var r=new this.constructor[Symbol.species](this.rows*t,this.columns*e),n=0;n<t;n++)for(var i=0;i<e;i++)r.setSubMatrix(this,this.rows*n,this.columns*i);return r}fill(t){for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,t);return this}neg(){return this.mulS(-1)}getRow(t){checkRowIndex$3(this,t);for(var e=new Array(this.columns),r=0;r<this.columns;r++)e[r]=this.get(t,r);return e}getRowVector(t){return this.constructor.rowVector(this.getRow(t))}setRow(t,e){checkRowIndex$3(this,t),e=checkRowVector$3(this,e);for(var r=0;r<this.columns;r++)this.set(t,r,e[r]);return this}swapRows(t,e){checkRowIndex$3(this,t),checkRowIndex$3(this,e);for(var r=0;r<this.columns;r++){var n=this.get(t,r);this.set(t,r,this.get(e,r)),this.set(e,r,n)}return this}getColumn(t){checkColumnIndex$3(this,t);for(var e=new Array(this.rows),r=0;r<this.rows;r++)e[r]=this.get(r,t);return e}getColumnVector(t){return this.constructor.columnVector(this.getColumn(t))}setColumn(t,e){checkColumnIndex$3(this,t),e=checkColumnVector$3(this,e);for(var r=0;r<this.rows;r++)this.set(r,t,e[r]);return this}swapColumns(t,e){checkColumnIndex$3(this,t),checkColumnIndex$3(this,e);for(var r=0;r<this.rows;r++){var n=this.get(r,t);this.set(r,t,this.get(r,e)),this.set(r,e,n)}return this}addRowVector(t){t=checkRowVector$3(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}subRowVector(t){t=checkRowVector$3(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=checkRowVector$3(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=checkRowVector$3(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=checkColumnVector$3(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=checkColumnVector$3(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=checkColumnVector$3(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=checkColumnVector$3(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){checkRowIndex$3(this,t);for(var r=0;r<this.columns;r++)this.set(t,r,this.get(t,r)*e);return this}mulColumn(t,e){checkColumnIndex$3(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){checkRowIndex$3(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){checkRowIndex$3(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){checkRowIndex$3(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){checkRowIndex$3(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){checkColumnIndex$3(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){checkColumnIndex$3(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){checkColumnIndex$3(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){checkColumnIndex$3(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 sumByRow$3(this);case"column":return sumByColumn$3(this);default:return sumAll$3(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: ${t}`)}cumulativeSum(){for(var t=0,e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t+=this.get(e,r),this.set(e,r,t);return this}dot(t){e.isMatrix(t)&&(t=t.to1DArray());var r=this.to1DArray();if(r.length!==t.length)throw new RangeError("vectors do not have the same size");for(var n=0,i=0;i<r.length;i++)n+=r[i]*t[i];return n}mmul(t){t=this.constructor.checkMatrix(t),this.columns!==t.rows&&console.warn("Number of columns of left matrix are not equal to number of rows of right matrix.");for(var e=this.rows,r=this.columns,n=t.columns,i=new this.constructor[Symbol.species](e,n),o=new Array(r),s=0;s<n;s++){for(var a=0;a<r;a++)o[a]=t.get(a,s);for(var u=0;u<e;u++){var h=0;for(a=0;a<r;a++)h+=this.get(u,a)*o[a];i.set(u,s,h)}}return i}strassen2x2(t){var e=new this.constructor[Symbol.species](2,2);const r=this.get(0,0),n=t.get(0,0),i=this.get(0,1),o=t.get(0,1),s=this.get(1,0),a=t.get(1,0),u=this.get(1,1),h=t.get(1,1),c=(r+u)*(n+h),l=(s+u)*n,f=r*(o-h),m=u*(a-n),p=(r+i)*h,d=c+m-p+(i-u)*(a+h),g=f+p,v=l+m,w=c-l+f+(s-r)*(n+o);return e.set(0,0,d),e.set(0,1,g),e.set(1,0,v),e.set(1,1,w),e}strassen3x3(t){var e=new this.constructor[Symbol.species](3,3);const r=this.get(0,0),n=this.get(0,1),i=this.get(0,2),o=this.get(1,0),s=this.get(1,1),a=this.get(1,2),u=this.get(2,0),h=this.get(2,1),c=this.get(2,2),l=t.get(0,0),f=t.get(0,1),m=t.get(0,2),p=t.get(1,0),d=t.get(1,1),g=t.get(1,2),v=t.get(2,0),w=t.get(2,1),y=t.get(2,2),b=(r-o)*(-f+d),x=(-r+o+s)*(l-f+d),M=(o+s)*(-l+f),_=r*l,$=(-r+u+h)*(l-m+g),S=(-r+u)*(m-g),R=(u+h)*(-l+m),E=(-i+h+c)*(d+v-w),C=(i-c)*(d-w),k=i*v,A=(h+c)*(-v+w),T=(-i+s+a)*(g+v-y),O=(i-a)*(g-y),I=(s+a)*(-v+y),D=_+k+n*p,P=(r+n+i-o-s-h-c)*d+x+M+_+E+k+A,V=_+$+R+(r+n+i-s-a-u-h)*g+k+T+I,j=b+s*(-l+f+p-d-g-v+y)+x+_+k+T+O,L=b+x+M+_+a*w,N=k+T+O+I+o*m,B=_+$+S+h*(-l+m+p-d-g-v+w)+E+C+k,F=E+C+k+A+u*f,z=_+$+S+R+c*y;return e.set(0,0,D),e.set(0,1,P),e.set(0,2,V),e.set(1,0,j),e.set(1,1,L),e.set(1,2,N),e.set(2,0,B),e.set(2,1,F),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 ${s} matrix: dimensions do not match.`);var u=Math.max(n,o),h=Math.max(i,s);return function t(r,n,i,o){if(i<=512||o<=512)return r.mmul(n);i%2==1&&o%2==1?(r=a(r,i+1,o+1),n=a(n,i+1,o+1)):i%2==1?(r=a(r,i+1,o),n=a(n,i+1,o)):o%2==1&&(r=a(r,i,o+1),n=a(n,i,o+1));var s=parseInt(r.rows/2),u=parseInt(r.columns/2),h=r.subMatrix(0,s-1,0,u-1),c=n.subMatrix(0,s-1,0,u-1),l=r.subMatrix(0,s-1,u,r.columns-1),f=n.subMatrix(0,s-1,u,n.columns-1),m=r.subMatrix(s,r.rows-1,0,u-1),p=n.subMatrix(s,n.rows-1,0,u-1),d=r.subMatrix(s,r.rows-1,u,r.columns-1),g=n.subMatrix(s,n.rows-1,u,n.columns-1),v=t(e.add(h,d),e.add(c,g),s,u),w=t(e.add(m,d),c,s,u),y=t(h,e.sub(f,g),s,u),b=t(d,e.sub(p,c),s,u),x=t(e.add(h,l),g,s,u),M=t(e.sub(m,h),e.add(c,f),s,u),_=t(e.sub(l,d),e.add(p,g),s,u),$=e.add(v,b);$.sub(x),$.add(_);var S=e.add(y,x),R=e.add(w,b),E=e.sub(v,w);E.add(y),E.add(M);var C=e.zeros(2*$.rows,2*$.columns);return(C=(C=(C=(C=C.setSubMatrix($,0,0)).setSubMatrix(S,$.rows,0)).setSubMatrix(R,0,$.columns)).setSubMatrix(E,$.rows,$.columns)).subMatrix(0,i-1,0,o-1)}(r=a(r,u,h),t=a(t,u,h),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),n=0;n<this.rows;n++){var i=rescale(this.getRow(n),{min:t,max:e});r.setRow(n,i)}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),n=0;n<this.columns;n++){var i=rescale(this.getColumn(n),{min:t,max:e});r.setColumn(n,i)}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){checkRange$3(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 s=r;s<=n;s++)i[o-t][s-r]=this.get(o,s);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){checkRange$3(this,e,e+(t=this.constructor.checkMatrix(t)).rows-1,r,r+t.columns-1);for(var n=0;n<t.rows;n++)for(var i=0;i<t.columns;i++)this[e+n][r+i]=t.get(n,i);return this}selection(t,e){for(var r=checkIndices$3(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],s=0;s<r.column.length;s++){var a=r.column[s];n[i][s]=this.get(o,a)}return n}trace(){for(var t=Math.min(this.rows,this.columns),e=0,r=0;r<t;r++)e+=this.get(r,r);return e}transposeView(){return new MatrixTransposeView$3(this)}rowView(t){return checkRowIndex$3(this,t),new MatrixRowView$3(this,t)}columnView(t){return checkColumnIndex$3(this,t),new MatrixColumnView$3(this,t)}flipRowView(){return new MatrixFlipRowView$3(this)}flipColumnView(){return new MatrixFlipColumnView$3(this)}subMatrixView(t,e,r,n){return new MatrixSubView$3(this,t,e,r,n)}selectionView(t,e){return new MatrixSelectionView$3(this,t,e)}rowSelectionView(t){return new MatrixRowSelectionView$3(this,t)}columnSelectionView(t){return new MatrixColumnSelectionView$3(this,t)}det(){var t,e,r,n,i,o;if(this.isSquare())return 2===this.columns?(t=this.get(0,0),e=this.get(0,1),r=this.get(1,0),t*this.get(1,1)-e*r):3===this.columns?(n=this.selectionView([1,2],[1,2]),i=this.selectionView([1,2],[0,2]),o=this.selectionView([1,2],[0,1]),t=this.get(0,0),e=this.get(0,1),r=this.get(0,2),t*n.det()-e*i.det()+r*o.det()):new LuDecomposition$$1(this).determinant;throw Error("Determinant can only be calculated for a square matrix.")}pseudoInverse(t){void 0===t&&(t=Number.EPSILON);for(var e=new SingularValueDecomposition$$1(this,{autoTranspose:!0}),r=e.leftSingularVectors,n=e.rightSingularVectors,i=e.diagonal,o=0;o<i.length;o++)Math.abs(i[o])>t?i[o]=1/i[o]:i[o]=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 n,i="\n(function %name%(matrix, %args%) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(%args%);\n})\n",o=i,s=eval;for(var a of[["+","add"],["-","sub","subtract"],["*","mul","multiply"],["/","div","divide"],["%","mod","modulus"],["&","and"],["|","or"],["^","xor"],["<<","leftShift"],[">>","signPropagatingRightShift"],[">>>","rightShift","zeroFillRightShift"]]){var u=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",{name:a[1],op:a[0]})),h=s(S("\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, this.get(i, j) %op% value);\n        }\n    }\n    return this;\n})\n",{name:a[1]+"S",op:a[0]})),c=s(S("\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, this.get(i, j) %op% matrix.get(i, j));\n        }\n    }\n    return this;\n})\n",{name:a[1]+"M",op:a[0]})),l=s(S("\n(function %name%(matrix, value) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(value);\n})\n",{name:a[1]}));for(n=1;n<a.length;n++)e.prototype[a[n]]=u,e.prototype[a[n]+"S"]=h,e.prototype[a[n]+"M"]=c,e[a[n]]=l}var f=[["~","not"]];for(var m 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){f.push(["Math."+t,t])})),f)){var p=s(S("\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:m[1],method:m[0]})),d=s(S("\n(function %name%(matrix) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%();\n})\n",{name:m[1]}));for(n=1;n<m.length;n++)e.prototype[m[n]]=p,e[m[n]]=d}for(var g of[["Math.pow",1,"pow"]]){var v="arg0";for(n=1;n<g[1];n++)v+=`, arg${n}`;if(1!==g[1]){var w=s(S("\n(function %name%(%args%) {\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j), %args%));\n        }\n    }\n    return this;\n})\n",{name:g[2],method:g[0],args:v})),y=s(S(i,{name:g[2],args:v}));for(n=2;n<g.length;n++)e.prototype[g[n]]=w,e[g[n]]=y}else{var b={name:g[2],args:v,method:g[0]},x=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",b)),M=s(S("\n(function %name%S(value) {\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j), value));\n        }\n    }\n    return this;\n})\n",b)),_=s(S("\n(function %name%M(matrix) {\n    matrix = this.constructor.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n        this.columns !== matrix.columns) {\n        throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j), matrix.get(i, j)));\n        }\n    }\n    return this;\n})\n",b)),$=s(S(o,b));for(n=2;n<g.length;n++)e.prototype[g[n]]=x,e.prototype[g[n]+"M"]=_,e.prototype[g[n]+"S"]=M,e[g[n]]=$}}function S(t,e){for(var r in e)t=t.replace(new RegExp("%"+r+"%","g"),e[r]);return t}return e}class Matrix$5 extends(AbstractMatrix$3(Array)){constructor(t,e){var r;if(1===arguments.length&&"number"==typeof t)return new Array(t);if(Matrix$5.isMatrix(t))return t.clone();if(Number.isInteger(t)&&t>0){if(super(t),!(Number.isInteger(e)&&e>0))throw new TypeError("nColumns must be a positive integer");for(r=0;r<t;r++)this[r]=new Array(e)}else{if(!Array.isArray(t))throw new TypeError("First argument must be a positive number or an array");{const n=t;if(t=n.length,"number"!=typeof(e=n[0].length)||0===e)throw new TypeError("Data must be a 2D array with at least one element");for(super(t),r=0;r<t;r++){if(n[r].length!==e)throw new RangeError("Inconsistent array dimensions");this[r]=[].concat(n[r])}}}return this.rows=t,this.columns=e,this}set(t,e,r){return this[t][e]=r,this}get(t,e){return this[t][e]}removeRow(t){if(checkRowIndex$3(this,t),1===this.rows)throw new RangeError("A matrix cannot have less than one row");return this.splice(t,1),this.rows-=1,this}addRow(t,e){return void 0===e&&(e=t,t=this.rows),checkRowIndex$3(this,t,!0),e=checkRowVector$3(this,e,!0),this.splice(t,0,e),this.rows+=1,this}removeColumn(t){if(checkColumnIndex$3(this,t),1===this.columns)throw new RangeError("A matrix cannot have less than one column");for(var e=0;e<this.rows;e++)this[e].splice(t,1);return this.columns-=1,this}addColumn(t,e){void 0===e&&(e=t,t=this.columns),checkColumnIndex$3(this,t,!0),e=checkColumnVector$3(this,e);for(var r=0;r<this.rows;r++)this[r].splice(t,0,e[r]);return this.columns+=1,this}}class WrapperMatrix1D$3 extends(AbstractMatrix$3()){constructor(t,e={}){const{rows:r=1}=e;if(t.length%r!=0)throw new Error("the data length is not divisible by the number of rows");super(),this.rows=r,this.columns=t.length/r,this.data=t}set(t,e,r){var n=this._calculateIndex(t,e);return this.data[n]=r,this}get(t,e){var r=this._calculateIndex(t,e);return this.data[r]}_calculateIndex(t,e){return t*this.columns+e}static get[Symbol.species](){return Matrix$5}}class WrapperMatrix2D$3 extends(AbstractMatrix$3()){constructor(t){super(),this.data=t,this.rows=t.length,this.columns=t[0].length}set(t,e,r){return this.data[t][e]=r,this}get(t,e){return this.data[t][e]}static get[Symbol.species](){return Matrix$5}}function separateClasses(t,e){for(var r=t.columns,n=0,i=new Array(1e4),o=0;o<e.length;o++)void 0===i[e[o]]&&(i[e[o]]=0,n++),i[e[o]]++;var s=new Array(n),a=new Array(n);for(o=0;o<n;++o)s[o]=new Matrix$5(i[o],r),a[o]=0;for(o=0;o<t.rows;++o)s[e[o]].setRow(a[e[o]],t.getRow(o)),a[e[o]]++;return s}class GaussianNB{constructor(t,e){t&&(this.means=e.means,this.calculateProbabilities=e.calculateProbabilities)}train(t,e){var r=Math.sqrt(2*Math.PI);if((t=Matrix$5.checkMatrix(t)).rows!==e.length)throw new RangeError("the size of the training set and the training labels must be the same.");var n=separateClasses(t,e),i=new Array(n.length);this.means=new Array(n.length);for(var o=0;o<n.length;++o){var s=mlStat.matrix.mean(n[o]),a=mlStat.matrix.standardDeviation(n[o],s),u=Math.log(n[o].rows/t.rows);i[o]=new Array(s.length+1),i[o][0]=u;for(var h=1;h<s.length+1;++h){var c=a[h-1];i[o][h]=[1/(r*c),-2*c*c]}this.means[o]=s}this.calculateProbabilities=i}predict(t){if(t[0].length===this.calculateProbabilities[0].length)throw new RangeError("the dataset must have the same features as the training set");for(var e=new Array(t.length),r=0;r<e.length;++r)e[r]=getCurrentClass(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 GaussianNB(!0,t)}}function getCurrentClass(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+=calculateLogProbability(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 calculateLogProbability(t,e,r,n){return t-=e,Math.log(r*Math.exp(t*t/n))}class MultinomialNB{constructor(t){t&&(this.conditionalProbability=Matrix$5.checkMatrix(t.conditionalProbability),this.priorProbability=Matrix$5.checkMatrix(t.priorProbability))}train(t,e){if((t=Matrix$5.checkMatrix(t)).rows!==e.length)throw new RangeError("the size of the training set and the training labels must be the same.");var r=separateClasses(t,e);this.priorProbability=new Matrix$5(r.length,1);for(var n=0;n<r.length;++n)this.priorProbability[n][0]=Math.log(r[n].length/t.rows);var i=t.columns;for(this.conditionalProbability=new Matrix$5(r.length,i),n=0;n<r.length;++n){var o=Matrix$5.checkMatrix(r[n]),s=o.sum()+i;this.conditionalProbability.setRow(n,o.sum("column").add(1).div(s).apply(matrixLog))}}predict(t){t=Matrix$5.checkMatrix(t);for(var e=new Array(t.rows),r=0;r<t.rows;++r){var n=t.getRowVector(r);e[r]=this.conditionalProbability.clone().mulRowVector(n).sum("row").add(this.priorProbability).maxIndex()[0]}return e}toJSON(){return{name:"MultinomialNB",priorProbability:this.priorProbability,conditionalProbability:this.conditionalProbability}}static load(t){if("MultinomialNB"!==t.name)throw new RangeError(`${t.name} is not a Multinomial Naive Bayes`);return new MultinomialNB(t)}}function matrixLog(t,e){this[t][e]=Math.log(this[t][e])}var src$6=Object.freeze({GaussianNB:GaussianNB,MultinomialNB:MultinomialNB});
/*
             * 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 Node(t,e,r){this.obj=t,this.left=null,this.right=null,this.parent=r,this.dimension=e}class KDTree{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=buildTree(t,0,null,this.dimensions)}else this.dimensions=t.dimensions,this.root=t,restoreParent(this.root);this.metric=e}toJSON(){const t=toJSONImpl(this.root,!0);return t.dimensions=this.dimensions,t}nearest(t,e,r){const n=this.metric,i=this.dimensions;var o;const s=new BinaryHeap((function(t){return-t[1]}));if(r)for(o=0;o<e;o+=1)s.push([null,r]);this.root&&function r(o){const a=i[o.dimension],u=n(t,o.obj),h={};var c,l,f,m;function p(t,r){s.push([t,r]),s.size()>e&&s.pop()}for(m=0;m<i.length;m+=1)m===o.dimension?h[i[m]]=t[i[m]]:h[i[m]]=o.obj[i[m]];l=n(h,o.obj),null!==o.right||null!==o.left?(r(c=null===o.right?o.left:null===o.left?o.right:t[a]<o.obj[a]?o.left:o.right),(s.size()<e||u<s.peek()[1])&&p(o,u),(s.size()<e||Math.abs(l)<s.peek()[1])&&null!==(f=c===o.left?o.right:o.left)&&r(f)):(s.size()<e||u<s.peek()[1])&&p(o,u)}(this.root);const a=[];for(o=0;o<Math.min(e,s.content.length);o+=1)s.content[o][0]&&a.push([s.content[o][0].obj,s.content[o][1]]);return a}}function toJSONImpl(t){const e=new Node(t.obj,t.dimension,null);return t.left&&(e.left=toJSONImpl(t.left)),t.right&&(e.right=toJSONImpl(t.right)),e}function buildTree(t,e,r,n){const i=e%n.length;if(0===t.length)return null;if(1===t.length)return new Node(t[0],i,r);t.sort(((t,e)=>t[n[i]]-e[n[i]]));const o=Math.floor(t.length/2),s=new Node(t[o],i,r);return s.left=buildTree(t.slice(0,o),e+1,s,n),s.right=buildTree(t.slice(o+1),e+1,s,n),s}function restoreParent(t){t.left&&(t.left.parent=t,restoreParent(t.left)),t.right&&(t.right.parent=t,restoreParent(t.right))}class BinaryHeap{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;){const 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}}}class KNN{constructor(t,e,r={}){if(!0===t){const t=e;return this.kdTree=new KDTree(t.kdTree,r),this.k=t.k,this.classes=new Set(t.classes),void(this.isEuclidean=t.isEuclidean)}const n=new Set(e),{distance:i=euclidean_1,k:o=n.size+1}=r,s=new Array(t.length);for(var a=0;a<s.length;++a)s[a]=t[a].slice();for(a=0;a<e.length;++a)s[a].push(e[a]);this.kdTree=new KDTree(s,i),this.k=o,this.classes=n,this.isEuclidean=i===euclidean_1}static load(t,e=euclidean_1){if("KNN"!==t.name)throw new Error("invalid model: "+t.name);if(!t.isEuclidean&&e===euclidean_1)throw new Error("a custom distance function was used to create the model. Please provide it again");if(t.isEuclidean&&e!==euclidean_1)throw new Error("the model was created with the default distance function. Do not load it with another one");return new KNN(!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 getSinglePrediction(this,t);if(Array.isArray(t[0])&&"number"==typeof t[0][0]){const r=new Array(t.length);for(var e=0;e<t.length;e++)r[e]=getSinglePrediction(this,t[e]);return r}}throw new TypeError("dataset to predict must be an array or a matrix")}}function getSinglePrediction(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],c=++n[h];c>o&&(i=h,o=c)}return i}var src$7=Object.freeze({default:KNN});function norm(t){return Math.sqrt(t.clone().apply(pow2array).sum())}function pow2array(t,e){return this[t][e]=this[t][e]*this[t][e],this}function initializeMatrices(t,e){if(e)for(var r=0;r<t.length;++r)for(var n=0;n<t[r].length;++n){var i=t[r][n];t[r][n]=null!==i?new Matrix$1(t[r][n]):void 0}else for(r=0;r<t.length;++r)t[r]=new Matrix$1(t[r]);return t}class PLS{constructor(t,e){if(!0===t)this.meanX=e.meanX,this.stdDevX=e.stdDevX,this.meanY=e.meanY,this.stdDevY=e.stdDevY,this.PBQ=Matrix$1.checkMatrix(e.PBQ),this.R2X=e.R2X,this.scale=e.scale,this.scaleMethod=e.scaleMethod,this.tolerance=e.tolerance;else{var{tolerance:r=1e-5,scale:n=!0}=t;this.tolerance=r,this.scale=n,this.latentVectors=t.latentVectors}}train(t,e){if(t=Matrix$1.checkMatrix(t),e=Matrix$1.checkMatrix(e),t.length!==e.length)throw new RangeError("The number of X rows must be equal to the number of Y rows");this.meanX=matrix.mean(t),this.stdDevX=matrix.standardDeviation(t,this.meanX,!0),this.meanY=matrix.mean(e),this.stdDevY=matrix.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,n=t.columns,i=e.rows,o=e.columns,s=t.clone().mul(t).sum(),a=e.clone().mul(e).sum(),u=this.tolerance,h=this.latentVectors,c=Matrix$1.zeros(r,h),l=Matrix$1.zeros(n,h),f=Matrix$1.zeros(i,h),m=Matrix$1.zeros(o,h),p=Matrix$1.zeros(h,h),d=l.clone(),g=0;norm(e)>u&&g<h;){for(var v=t.transpose(),w=e.transpose(),y=maxSumColIndex(t.clone().mulM(t)),b=maxSumColIndex(e.clone().mulM(e)),x=t.getColumnVector(y),M=e.getColumnVector(b),_=Matrix$1.zeros(r,1);norm(x.clone().sub(_))>u;){var $=v.mmul(M);$.div(norm($)),_=x,x=t.mmul($);var S=w.mmul(x);S.div(norm(S)),M=e.mmul(S)}_=x;var R=v.mmul(_),E=_.transpose().mmul(_)[0][0],C=R.div(E),k=norm(C);C.div(k),_.mul(k),$.mul(k),R=M.transpose().mmul(_),E=_.transpose().mmul(_)[0][0];var A=R.div(E)[0][0];t.sub(_.mmul(C.transpose())),e.sub(_.clone().mul(A).mmul(S.transpose())),c.setColumn(g,_),l.setColumn(g,C),f.setColumn(g,M),m.setColumn(g,S),d.setColumn(g,$),p[g][g]=A,g++}g--,c=c.subMatrix(0,c.rows-1,0,g),l=l.subMatrix(0,l.rows-1,0,g),f=f.subMatrix(0,f.rows-1,0,g),m=m.subMatrix(0,m.rows-1,0,g),d=d.subMatrix(0,d.rows-1,0,g),p=p.subMatrix(0,g,0,g),this.ssqYcal=a,this.E=t,this.F=e,this.T=c,this.P=l,this.U=f,this.Q=m,this.W=d,this.B=p,this.PBQ=l.mmul(p).mmul(m.transpose()),this.R2X=_.transpose().mmul(_).mmul(C.transpose().mmul(C)).div(s)[0][0]}predict(t){var e=Matrix$1.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 this.R2X}toJSON(){return{name:"PLS",R2X:this.R2X,meanX:this.meanX,stdDevX:this.stdDevX,meanY:this.meanY,stdDevY:this.stdDevY,PBQ:this.PBQ,tolerance:this.tolerance,scale:this.scale}}static load(t){if("PLS"!==t.name)throw new RangeError("Invalid model: "+t.name);return new PLS(!0,t)}}function maxSumColIndex(t){return t.sum("column").maxIndex()[0]}class KOPLS{constructor(t,e){if(!0===t)this.trainingSet=new Matrix$1(e.trainingSet),this.YLoadingMat=new Matrix$1(e.YLoadingMat),this.SigmaPow=new Matrix$1(e.SigmaPow),this.YScoreMat=new Matrix$1(e.YScoreMat),this.predScoreMat=initializeMatrices(e.predScoreMat,!1),this.YOrthLoadingVec=initializeMatrices(e.YOrthLoadingVec,!1),this.YOrthEigen=e.YOrthEigen,this.YOrthScoreMat=initializeMatrices(e.YOrthScoreMat,!1),this.toNorm=initializeMatrices(e.toNorm,!1),this.TURegressionCoeff=initializeMatrices(e.TURegressionCoeff,!1),this.kernelX=initializeMatrices(e.kernelX,!0),this.kernel=e.kernel,this.orthogonalComp=e.orthogonalComp,this.predictiveComp=e.predictiveComp;else{if(void 0===t.predictiveComponents)throw new RangeError("no predictive components found!");if(void 0===t.orthogonalComponents)throw new RangeError("no orthogonal components found!");if(void 0===t.kernel)throw new RangeError("no kernel found!");this.orthogonalComp=t.orthogonalComponents,this.predictiveComp=t.predictiveComponents,this.kernel=t.kernel}}train(t,e){t=Matrix$1.checkMatrix(t),e=Matrix$1.checkMatrix(e),this.trainingSet=t.clone();var r=this.kernel.compute(t),n=Matrix$1.eye(r.rows,r.rows,1),i=r;(r=new Matrix$1(this.orthogonalComp+1,this.orthogonalComp+1))[0][0]=i;var o=new SingularValueDecomposition$$1(e.transpose().mmul(r[0][0]).mmul(e),{computeLeftSingularVectors:!0,computeRightSingularVectors:!1}),s=o.leftSingularVectors,a=o.diagonalMatrix;s=s.subMatrix(0,s.rows-1,0,this.predictiveComp-1),a=a.subMatrix(0,this.predictiveComp-1,0,this.predictiveComp-1);var u=e.mmul(s),h=new Array(this.orthogonalComp+1),c=new Array(this.orthogonalComp+1),l=new Array(this.orthogonalComp),f=new Array(this.orthogonalComp),m=new Array(this.orthogonalComp),p=new Array(this.orthogonalComp),d=Matrix$1.pow(a,-.5);d.apply((function(t,e){this[t][e]===1/0&&(this[t][e]=0)}));for(var g=0;g<this.orthogonalComp;++g){h[g]=r[0][g].transpose().mmul(u).mmul(d);var v=h[g].transpose();c[g]=inverse$$1(v.mmul(h[g])).mmul(v).mmul(u);var w=(o=new SingularValueDecomposition$$1(v.mmul(Matrix$1.sub(r[g][g],h[g].mmul(v))).mmul(h[g]),{computeLeftSingularVectors:!0,computeRightSingularVectors:!1})).leftSingularVectors,y=o.diagonalMatrix;f[g]=w.subMatrix(0,w.rows-1,0,0),m[g]=y[0][0],l[g]=Matrix$1.sub(r[g][g],h[g].mmul(v)).mmul(h[g]).mmul(f[g]).mul(Math.pow(m[g],-.5));var b=l[g].transpose();p[g]=Matrix$1.sqrt(b.mmul(l[g])),l[g]=l[g].divRowVector(p[g]);var x=Matrix$1.sub(n,l[g].mmul(l[g].transpose()));r[0][g+1]=r[0][g].mmul(x),r[g+1][g+1]=x.mmul(r[g][g]).mmul(x)}var M=h[this.orthogonalComp]=r[0][this.orthogonalComp].transpose().mmul(u).mmul(d),_=M.transpose();c[this.orthogonalComp]=inverse$$1(_.mmul(M)).mmul(_).mmul(u),this.YLoadingMat=s,this.SigmaPow=d,this.YScoreMat=u,this.predScoreMat=h,this.YOrthLoadingVec=f,this.YOrthEigen=m,this.YOrthScoreMat=l,this.toNorm=p,this.TURegressionCoeff=c,this.kernelX=r}predict(t){var e=this.kernel.compute(t,this.trainingSet),r=e;(e=new Matrix$1(this.orthogonalComp+1,this.orthogonalComp+1))[0][0]=r;var n,i=new Array(this.orthogonalComp),o=new Array(this.orthogonalComp);for(n=0;n<this.orthogonalComp;++n){o[n]=e[n][0].mmul(this.YScoreMat).mmul(this.SigmaPow),i[n]=Matrix$1.sub(e[n][n],o[n].mmul(this.predScoreMat[n].transpose())).mmul(this.predScoreMat[n]).mmul(this.YOrthLoadingVec[n]).mul(Math.pow(this.YOrthEigen[n],-.5)),i[n]=i[n].divRowVector(this.toNorm[n]);var s=this.YOrthScoreMat[n].transpose();e[n+1][0]=Matrix$1.sub(e[n][0],i[n].mmul(s).mmul(this.kernelX[0][n].transpose()));var a=Matrix$1.sub(e[n][0],e[n][n].mmul(this.YOrthScoreMat[n]).mmul(s)),u=i[n].mmul(s).mmul(this.kernelX[n][n]),h=u.mmul(this.YOrthScoreMat[n]).mmul(s);e[n+1][n+1]=a.sub(u).add(h)}return o[n]=e[n][0].mmul(this.YScoreMat).mmul(this.SigmaPow),{prediction:o[n].mmul(this.TURegressionCoeff[n]).mmul(this.YLoadingMat.transpose()),predScoreMat:o,predYOrthVectors:i}}toJSON(){return{name:"K-OPLS",YLoadingMat:this.YLoadingMat,SigmaPow:this.SigmaPow,YScoreMat:this.YScoreMat,predScoreMat:this.predScoreMat,YOrthLoadingVec:this.YOrthLoadingVec,YOrthEigen:this.YOrthEigen,YOrthScoreMat:this.YOrthScoreMat,toNorm:this.toNorm,TURegressionCoeff:this.TURegressionCoeff,kernelX:this.kernelX,trainingSet:this.trainingSet,orthogonalComp:this.orthogonalComp,predictiveComp:this.predictiveComp}}static load(t,e){if("K-OPLS"!==t.name)throw new RangeError("Invalid model: "+t.name);if(!e)throw new RangeError("You must provide a kernel for the model!");return t.kernel=e,new KOPLS(!0,t)}}var src$8=Object.freeze({PLS:PLS,KOPLS:KOPLS});class ConfusionMatrix{constructor(t,e){if(t.length!==t[0].length)throw new Error("Confusion matrix must be square");if(e.length!==t.length)throw new Error("Confusion matrix and labels should have the same length");this.labels=e,this.matrix=t}static fromLabels(t,e,r={}){if(e.length!==t.length)throw new Error("predicted and actual must have the same length");let n;n=r.labels?new Set(r.labels):new Set([...t,...e]),n=Array.from(n),r.sort&&n.sort(r.sort);const i=Array.from({length:n.length});for(let t=0;t<i.length;t++)i[t]=new Array(i.length),i[t].fill(0);for(let r=0;r<e.length;r++){const o=n.indexOf(t[r]),s=n.indexOf(e[r]);o>=0&&s>=0&&i[o][s]++}return new ConfusionMatrix(i,n)}getMatrix(){return this.matrix}getLabels(){return this.labels}getTotalCount(){let t=0;for(var e=0;e<this.matrix.length;e++)for(var r=0;r<this.matrix.length;r++)t+=this.matrix[e][r];return t}getTrueCount(){for(var t=0,e=0;e<this.matrix.length;e++)t+=this.matrix[e][e];return t}getFalseCount(){return this.getTotalCount()-this.getTrueCount()}getTruePositiveCount(t){const e=this.getIndex(t);return this.matrix[e][e]}getTrueNegativeCount(t){const e=this.getIndex(t);for(var r=0,n=0;n<this.matrix.length;n++)for(var i=0;i<this.matrix.length;i++)n!==e&&i!==e&&(r+=this.matrix[n][i]);return r}getFalsePositiveCount(t){const e=this.getIndex(t);for(var r=0,n=0;n<this.matrix.length;n++)n!==e&&(r+=this.matrix[n][e]);return r}getFalseNegativeCount(t){const e=this.getIndex(t);for(var r=0,n=0;n<this.matrix.length;n++)n!==e&&(r+=this.matrix[e][n]);return r}getPositiveCount(t){return this.getTruePositiveCount(t)+this.getFalseNegativeCount(t)}getNegativeCount(t){return this.getTrueNegativeCount(t)+this.getFalsePositiveCount(t)}getIndex(t){const e=this.labels.indexOf(t);if(-1===e)throw new Error("The label does not exist");return e}getTruePositiveRate(t){return this.getTruePositiveCount(t)/this.getPositiveCount(t)}getTrueNegativeRate(t){return this.getTrueNegativeCount(t)/this.getNegativeCount(t)}getPositivePredictiveValue(t){const e=this.getTruePositiveCount(t);return e/(e+this.getFalsePositiveCount(t))}getNegativePredictiveValue(t){const e=this.getTrueNegativeCount(t);return e/(e+this.getFalseNegativeCount(t))}getFalseNegativeRate(t){return 1-this.getTruePositiveRate(t)}getFalsePositiveRate(t){return 1-this.getTrueNegativeRate(t)}getFalseDiscoveryRate(t){const e=this.getFalsePositiveCount(t);return e/(e+this.getTruePositiveCount(t))}getFalseOmissionRate(t){const e=this.getFalseNegativeCount(t);return e/(e+this.getTruePositiveCount(t))}getF1Score(t){const e=this.getTruePositiveCount(t);return 2*e/(2*e+this.getFalsePositiveCount(t)+this.getFalseNegativeCount(t))}getMatthewsCorrelationCoefficient(t){const e=this.getTruePositiveCount(t),r=this.getTrueNegativeCount(t),n=this.getFalsePositiveCount(t),i=this.getFalseNegativeCount(t);return(e*r-n*i)/Math.sqrt((e+n)*(e+i)*(r+n)*(r+i))}getInformedness(t){return this.getTruePositiveRate(t)+this.getTrueNegativeRate(t)-1}getMarkedness(t){return this.getPositivePredictiveValue(t)+this.getNegativePredictiveValue(t)-1}getConfusionTable(t){return[[this.getTruePositiveCount(t),this.getFalseNegativeCount(t)],[this.getFalsePositiveCount(t),this.getTrueNegativeCount(t)]]}getAccuracy(){let t=0,e=0;for(var r=0;r<this.matrix.length;r++)for(var n=0;n<this.matrix.length;n++)r===n?t+=this.matrix[r][n]:e+=this.matrix[r][n];return t/(t+e)}getCount(t,e){const r=this.getIndex(t),n=this.getIndex(e);return this.matrix[r][n]}get accuracy(){return this.getAccuracy()}get total(){return this.getTotalCount()}}var src$9=ConfusionMatrix;const defaultOptions$j={mode:"index"};var src$a=function*(t,e,r){r=Object.assign({},defaultOptions$j,r);for(var n,i,o,s=new Array(e),a=new Array(t),u=new Array(e),h=new Array(e+2),c=0;c<e;c++)s[c]=c,u[c]=c<e-t?0:1;for(c=0;c<t;c++)a[c]=e-t+c;for(c=0;c<h.length;c++)h[c]=0===c?e+1:c<=e-t?0:c<=e?c-e+t:-2;function l(){var t,e,r;for(e=1;h[e]<=0;)e++;if(0===h[e-1]){for(t=e-1;1!==t;t--)h[t]=-1;h[e]=0,n=o=0,h[1]=1,i=e-1}else{e>1&&(h[e-1]=0);do{e++}while(h[e]>0);for(r=e-1,t=e;0===h[t];)h[t++]=-1;if(-1===h[t])h[t]=h[r],o=h[r]-1,n=t-1,i=r-1,h[r]=-1;else{if(t===h[0])return 0;h[e]=h[t],o=h[t]-1,h[t]=0,n=e-1,i=t-1}}return 1}if("index"===r.mode)for(yield a.slice();l();)a[o]=s[n],yield a.slice();else{if("mask"!==r.mode)throw new Error("Invalid mode");for(yield u.slice();l();)u[n]=1,u[i]=0,yield u.slice()}};const CV={};function check(t,e){if(t.length!==e.length)throw new Error("features and labels should have the same length")}function initMatrix(t,e){return new Array(t).fill(0).map((()=>new Array(e).fill(0)))}function getDistinct(t){var e=new Set;for(let r=0;r<t.length;r++)e.add(t[r]);return Array.from(e)}function validate(t,e,r,n,i,o,s,a){const{testFeatures:u,trainFeatures:h,testLabels:c,trainLabels:l}=getTrainTest(e,r,i,o);var f;t.prototype.train?(f=new t(n)).train(h,l):f=new t(h,l,n),updateConfusionMatrix(s,c,f.predict(u),a)}function validateWithCallback(t,e,r,n,i,o,s){const{testFeatures:a,trainFeatures:u,testLabels:h,trainLabels:c}=getTrainTest(t,e,r,n);updateConfusionMatrix(i,h,s(u,c,a),o)}function updateConfusionMatrix(t,e,r,n){for(var i=0;i<r.length;i++){const o=n.indexOf(e[i]),s=n.indexOf(r[i]);(o<0||s<0)&&console.warn(`ignore unknown predicted label ${r[i]}`),t[o][s]++}}function getTrainTest(t,e,r,n){return{testFeatures:r.map((function(e){return t[e]})),trainFeatures:n.map((function(e){return t[e]})),testLabels:r.map((function(t){return e[t]})),trainLabels:n.map((function(t){return e[t]}))}}CV.leaveOneOut=function(t,e,r,n){if("function"==typeof r){var i=r;return r=e,e=t,CV.leavePOut(e,r,1,i)}return CV.leavePOut(t,e,r,n,1)},CV.leavePOut=function(t,e,r,n,i){if("function"==typeof n){var o=n;i=r,r=e,e=t}check(e,r);const s=getDistinct(r),a=initMatrix(s.length,s.length);var u=e.length,h=src$a(i,u),c=new Array(u);for(let t=0;t<u;t++)c[t]=t;for(const i of h){var l=c.slice();for(let t=i.length-1;t>=0;t--)l.splice(i[t],1);o?validateWithCallback(e,r,i,l,a,s,o):validate(t,e,r,n,i,l,a,s)}return new src$9(a,s)},CV.kFold=function(t,e,r,n,i){if("function"==typeof n){var o=n;i=r,r=e,e=t}check(e,r);const s=getDistinct(r),a=initMatrix(s.length,s.length);for(var u=e.length,h=new Array(u),c=0;c<u;c++)h[c]=c;for(var l=Math.floor(u/i),f=[],m=[];h.length;){var p=Math.floor(Math.random()*h.length);f.push(h[p]),h.splice(p,1),f.length===l&&(m.push(f),f=[])}for(f.length&&m.push(f),m=m.slice(0,i),c=0;c<m.length;c++){for(var d=m[c],g=[],v=0;v<m.length;v++)v!==c&&(g=g.concat(m[v]));o?validateWithCallback(e,r,d,g,a,s,o):validate(t,e,r,n,d,g,a,s)}return new src$9(a,s)};var src$b=CV,Matrix$6=require$$0$3.Matrix;function sumRow(t){for(var e=Matrix$6.zeros(t.rows,1),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e[r][0]+=t[r][n];return e}function sumCol(t){for(var e=Matrix$6.zeros(1,t.columns),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e[0][n]+=t[r][n];return e}function dictOutputs(t){for(var e={},r={},n=0,i=0;i<t.length;i+=1)void 0===e[t[i]]&&(e[t[i]]=n,r[n]=t[i],n++);return{inputs:e,outputs:r}}var utils$1={dictOutputs:dictOutputs,sumCol:sumCol,sumRow:sumRow};function logistic(t){return 1/(1+Math.exp(-t))}function expELU(t,e){return t<0?e*(Math.exp(t)-1):t}function softExponential(t,e){return e<0?-Math.log(1-e*(t+e))/e:e>0?(Math.exp(e*t)-1)/e+e:t}function softExponentialPrime(t,e){return e<0?1/(1-e*(e+t)):Math.exp(e*t)}const ACTIVATION_FUNCTIONS={tanh:{activation:Math.tanh,derivate:t=>1-t*t},identity:{activation:t=>t,derivate:()=>1},logistic:{activation:logistic,derivate:t=>logistic(t)*(1-logistic(t))},arctan:{activation:Math.atan,derivate:t=>1/(t*t+1)},softsign:{activation:t=>t/(1+Math.abs(t)),derivate:t=>1/((1+Math.abs(t))*(1+Math.abs(t)))},relu:{activation:t=>t<0?0:t,derivate:t=>t<0?0:1},softplus:{activation:t=>Math.log(1+Math.exp(t)),derivate:t=>1/(1+Math.exp(-t))},bent:{activation:t=>(Math.sqrt(t*t+1)-1)/2+t,derivate:t=>t/(2*Math.sqrt(t*t+1))+1},sinusoid:{activation:Math.sin,derivate:Math.cos},sinc:{activation:t=>0===t?1:Math.sin(t)/t,derivate:t=>0===t?0:Math.cos(t)/t-Math.sin(t)/(t*t)},gaussian:{activation:t=>Math.exp(-t*t),derivate:t=>-2*t*Math.exp(-t*t)},"parametric-relu":{activation:(t,e)=>t<0?e*t:t,derivate:(t,e)=>t<0?e:1},"exponential-elu":{activation:expELU,derivate:(t,e)=>t<0?expELU(t,e)+e:1},"soft-exponential":{activation:softExponential,derivate:softExponentialPrime}};var activationFunctions=ACTIVATION_FUNCTIONS,Matrix$7=require$$0$3.Matrix;class Layer{constructor(t){this.inputSize=t.inputSize,this.outputSize=t.outputSize,this.regularization=t.regularization,this.epsilon=t.epsilon,this.activation=t.activation,this.activationParam=t.activationParam;var e=activationFunctions[t.activation],r=e.activation.length,n=r>1?r=>e.activation(r,t.activationParam):e.activation,i=r>1?r=>e.derivate(r,t.activationParam):e.derivate;this.activationFunction=function(t,e){this[t][e]=n(this[t][e])},this.derivate=function(t,e){this[t][e]=i(this[t][e])},t.model?(this.W=Matrix$7.checkMatrix(t.W),this.b=Matrix$7.checkMatrix(t.b)):(this.W=Matrix$7.rand(this.inputSize,this.outputSize),this.b=Matrix$7.zeros(1,this.outputSize),this.W.apply((function(e,r){this[e][r]/=Math.sqrt(t.inputSize)})))}forward(t){var e=t.mmul(this.W).addRowVector(this.b);return e.apply(this.activationFunction),this.a=e.clone(),e}backpropagation(t,e){this.dW=e.transposeView().mmul(t),this.db=utils$1.sumCol(t);var r=e.clone();return t.mmul(this.W.transposeView()).mul(r.apply(this.derivate))}update(){this.dW.add(this.W.clone().mul(this.regularization)),this.W.add(this.dW.mul(-this.epsilon)),this.b.add(this.db.mul(-this.epsilon))}toJSON(){return{model:"Layer",inputSize:this.inputSize,outputSize:this.outputSize,regularization:this.regularization,epsilon:this.epsilon,activation:this.activation,W:this.W,b:this.b}}static load(t){if("Layer"!==t.model)throw new RangeError("the current model is not a Layer model");return new Layer(t)}}var Layer_1=Layer;class OutputLayer extends Layer_1{constructor(t){super(t),this.activationFunction=function(t,e){this[t][e]=Math.exp(this[t][e])}}static load(t){if("Layer"!==t.model)throw new RangeError("the current model is not a Layer model");return new OutputLayer(t)}}var OutputLayer_1=OutputLayer;const Matrix$8=require$$0$3.Matrix;class FeedForwardNeuralNetworks{constructor(t){if((t=t||{}).model){this.hiddenLayers=t.hiddenLayers,this.iterations=t.iterations,this.learningRate=t.learningRate,this.regularization=t.regularization,this.dicts=t.dicts,this.activation=t.activation,this.activationParam=t.activationParam,this.model=new Array(t.layers.length);for(var e=0;e<this.model.length-1;++e)this.model[e]=Layer_1.load(t.layers[e]);this.model[this.model.length-1]=OutputLayer_1.load(t.layers[this.model.length-1])}else this.hiddenLayers=t.hiddenLayers||[10],this.iterations=t.iterations||50,this.learningRate=t.learningRate||.01,this.regularization=t.regularization||.01,this.activation=t.activation||"tanh",this.activationParam=t.activationParam||1,this.activation in Object.keys(activationFunctions)||(this.activation="tanh")}buildNetwork(t,e){var r=this.hiddenLayers.length-1+2;this.model=new Array(r),this.model[0]=new Layer_1({inputSize:t,outputSize:this.hiddenLayers[0],activation:this.activation,activationParam:this.activationParam,regularization:this.regularization,epsilon:this.learningRate});for(var n=1;n<this.hiddenLayers.length;++n)this.model[n]=new Layer_1({inputSize:this.hiddenLayers[n-1],outputSize:this.hiddenLayers[n],activation:this.activation,activationParam:this.activationParam,regularization:this.regularization,epsilon:this.learningRate});this.model[r-1]=new OutputLayer_1({inputSize:this.hiddenLayers[this.hiddenLayers.length-1],outputSize:e,activation:this.activation,activationParam:this.activationParam,regularization:this.regularization,epsilon:this.learningRate})}train(t,e){t=Matrix$8.checkMatrix(t),this.dicts=utils$1.dictOutputs(e);var r=t.columns,n=Object.keys(this.dicts.inputs).length;this.buildNetwork(r,n);for(var i=0;i<this.iterations;++i){var o=this.propagate(t);this.backpropagation(t,e,o)}}propagate(t){for(var e=t,r=0;r<this.model.length;++r)e=this.model[r].forward(e);return e.divColumnVector(utils$1.sumRow(e))}backpropagation(t,e,r){for(var n=0;n<r.length;++n)r[n][this.dicts.inputs[e[n]]]-=1;var i=r;for(n=this.model.length-1;n>=0;--n){var o=n>0?this.model[n-1].a:t;i=this.model[n].backpropagation(i,o)}for(n=0;n<this.model.length;++n)this.model[n].update()}predict(t){t=Matrix$8.checkMatrix(t);for(var e=new Array(t.rows),r=this.propagate(t),n=0;n<t.rows;++n)e[n]=this.dicts.outputs[r.maxRowIndex(n)[1]];return e}toJSON(){for(var t={model:"FNN",hiddenLayers:this.hiddenLayers,iterations:this.iterations,learningRate:this.learningRate,regularization:this.regularization,activation:this.activation,activationParam:this.activationParam,dicts:this.dicts,layers:new Array(this.model.length)},e=0;e<this.model.length;++e)t.layers[e]=this.model[e].toJSON();return t}static load(t){if("FNN"!==t.model)throw new RangeError("the current model is not a feed forward network");return new FeedForwardNeuralNetworks(t)}}var FeedForwardNeuralNetwork=FeedForwardNeuralNetworks;function NodeSquare(t,e,r,n){this.x=t,this.y=e,this.weights=r,this.som=n,this.neighbors={}}NodeSquare.prototype.adjustWeights=function(t,e,r){for(var n=0,i=this.weights.length;n<i;n++)this.weights[n]+=e*r*(t[n]-this.weights[n])},NodeSquare.prototype.getDistance=function(t){return Math.max(Math.abs(this.x-t.x),Math.abs(this.y-t.y))},NodeSquare.prototype.getDistanceTorus=function(t){var e=Math.abs(this.x-t.x),r=Math.abs(this.y-t.y);return Math.max(Math.min(e,this.som.gridDim.x-e),Math.min(r,this.som.gridDim.y-r))},NodeSquare.prototype.getNeighbors=function(t){if(!this.neighbors[t]){var e,r,n,i;if(this.neighbors[t]=new Array(2),this[t]>0?e=this[t]-1:this.som.torus&&(e=this.som.gridDim[t]-1),void 0!==e)"x"===t?(r=e,n=this.y):(r=this.x,n=e),this.neighbors[t][0]=this.som.nodes[r][n];this[t]<this.som.gridDim[t]-1?i=this[t]+1:this.som.torus&&(i=0),void 0!==i&&("x"===t?(r=i,n=this.y):(r=this.x,n=i),this.neighbors[t][1]=this.som.nodes[r][n])}return this.neighbors[t]},NodeSquare.prototype.getPos=function(t,e){var r,n,i=this.getNeighbors(t),o=this.som.distance;i[0]?i[1]?o(e,i[0].weights)<o(e,i[1].weights)?(r=i[0],n=-1):(r=i[1],n=1):(r=i[0],n=-1):(r=i[1],n=1);var s=1-o(e,this.weights),a=1-o(e,r.weights);return.5+.5*((s-a)/(2-s-a))*n},NodeSquare.prototype.getPosition=function(t){return[this.getPos("x",t),this.getPos("y",t)]};var nodeSquare=NodeSquare;function NodeHexagonal(t,e,r,n){nodeSquare.call(this,t,e,r,n),this.hX=t-Math.floor(e/2),this.z=0-this.hX-e}NodeHexagonal.prototype=new nodeSquare,NodeHexagonal.prototype.constructor=NodeHexagonal,NodeHexagonal.prototype.getDistance=function(t){return Math.max(Math.abs(this.hX-t.hX),Math.abs(this.y-t.y),Math.abs(this.z-t.z))},NodeHexagonal.prototype.getDistanceTorus=function(t){var e=Math.abs(this.hX-t.hX),r=Math.abs(this.y-t.y),n=Math.abs(this.z-t.z);return Math.max(Math.min(e,this.som.gridDim.x-e),Math.min(r,this.som.gridDim.y-r),Math.min(n,this.som.gridDim.z-n))},NodeHexagonal.prototype.getPosition=function(){throw new Error("Unimplemented : cannot get position of the points for hexagonal grid")};var nodeHexagonal=NodeHexagonal,defaultOptions$k={fields:3,randomizer:Math.random,distance:squareEuclidean,iterations:10,learningRate:.1,gridType:"rect",torus:!0,method:"random"};function SOM(t,e,r,n){for(var i in this.x=t,this.y=e,r=r||{},this.options={},defaultOptions$k)r.hasOwnProperty(i)?this.options[i]=r[i]:this.options[i]=defaultOptions$k[i];if("number"==typeof this.options.fields)this.numWeights=this.options.fields;else{if(!Array.isArray(this.options.fields))throw new Error("Invalid fields definition");this.numWeights=this.options.fields.length;var o=getConverters(this.options.fields);this.extractor=o.extractor,this.creator=o.creator}if("rect"===this.options.gridType)this.nodeType=nodeSquare,this.gridDim={x:t,y:e};else{this.nodeType=nodeHexagonal;var s=this.x-Math.floor(this.y/2);this.gridDim={x:s,y:this.y,z:-(0-s-this.y)}}if(this.torus=this.options.torus,this.distanceMethod=this.torus?"getDistanceTorus":"getDistance",this.distance=this.options.distance,this.maxDistance=getMaxDistance(this.distance,this.numWeights),!0!==n){if(!(t>0&&e>0))throw new Error("x and y must be positive");this.times={findBMU:0,adjust:0},this.randomizer=this.options.randomizer,this.iterationCount=0,this.iterations=this.options.iterations,this.startLearningRate=this.learningRate=this.options.learningRate,this.mapRadius=Math.floor(Math.max(t,e)/2),this.algorithmMethod=this.options.method,this._initNodes(),this.done=!1}else this.done=!0}function getConverters(t){for(var e=t.length,r=new Array(e),n=new Array(e),i=0;i<e;i++)r[i]=getNormalizer(t[i].range),n[i]=getDenormalizer(t[i].range);return{extractor:function(n){for(var i=new Array(e),o=0;o<e;o++)i[o]=r[o](n[t[o].name]);return i},creator:function(r){for(var i={},o=0;o<e;o++)i[t[o].name]=n[o](r[o]);return i}}}function getNormalizer(t){return function(e){return(e-t[0])/(t[1]-t[0])}}function getDenormalizer(t){return function(e){return t[0]+e*(t[1]-t[0])}}function squareEuclidean(t,e){for(var r=0,n=0,i=t.length;n<i;n++)r+=(t[n]-e[n])*(t[n]-e[n]);return r}function getRandomValue(t,e){return t[Math.floor(e()*t.length)]}function getMaxDistance(t,e){for(var r=new Array(e),n=new Array(e),i=0;i<e;i++)r[i]=0,n[i]=1;return t(r,n)}SOM.load=function loadModel(model,distance){if("SOM"===model.name){var x=model.data.length,y=model.data[0].length;distance?model.options.distance=distance:model.options.distance&&(model.options.distance=eval("("+model.options.distance+")"));var som=new SOM(x,y,model.options,!0);som.nodes=new Array(x);for(var i=0;i<x;i++){som.nodes[i]=new Array(y);for(var j=0;j<y;j++)som.nodes[i][j]=new som.nodeType(i,j,model.data[i][j],som)}return som}throw new Error("expecting a SOM model")},SOM.prototype.export=function(t){if(!this.done)throw new Error("model is not ready yet");var e={name:"SOM"};e.options={fields:this.options.fields,gridType:this.options.gridType,torus:this.options.torus},e.data=new Array(this.x);for(var r=0;r<this.x;r++){e.data[r]=new Array(this.y);for(var n=0;n<this.y;n++)e.data[r][n]=this.nodes[r][n].weights}return t&&(e.options.distance=this.distance.toString()),e},SOM.prototype._initNodes=function(){var t,e,r,n=Date.now();for(this.nodes=new Array(this.x),t=0;t<this.x;t++)for(this.nodes[t]=new Array(this.y),e=0;e<this.y;e++){var i=new Array(this.numWeights);for(r=0;r<this.numWeights;r++)i[r]=this.randomizer();this.nodes[t][e]=new this.nodeType(t,e,i,this)}this.times.initNodes=Date.now()-n},SOM.prototype.setTraining=function(t){if(this.trainingSet)throw new Error("training set has already been set");var e,r=Date.now(),n=t,i=t.length;if(this.extractor)for(n=new Array(i),e=0;e<i;e++)n[e]=this.extractor(t[e]);this.numIterations=this.iterations*i,"random"===this.algorithmMethod?this.timeConstant=this.numIterations/Math.log(this.mapRadius):this.timeConstant=i/Math.log(this.mapRadius),this.trainingSet=n,this.times.setTraining=Date.now()-r},SOM.prototype.trainOne=function(){return!this.done&&(this.numIterations-- >0?("random"===this.algorithmMethod?(t=this.mapRadius*Math.exp(-this.iterationCount/this.timeConstant),e=getRandomValue(this.trainingSet,this.randomizer),this._adjust(e,t),this.learningRate=this.startLearningRate*Math.exp(-this.iterationCount/this.numIterations)):(r=-Math.floor(this.iterationCount/this.trainingSet.length),t=this.mapRadius*Math.exp(r/this.timeConstant),e=this.trainingSet[this.iterationCount%this.trainingSet.length],this._adjust(e,t),(this.iterationCount+1)%this.trainingSet.length==0&&(this.learningRate=this.startLearningRate*Math.exp(r/Math.floor(this.numIterations/this.trainingSet.length)))),this.iterationCount++,!0):(this.done=!0,!1));var t,e,r},SOM.prototype._adjust=function(t,e){var r,n,i,o,s=Date.now(),a=this._findBestMatchingUnit(t),u=Date.now();this.times.findBMU+=u-s;var h=Math.floor(e),c=a.x-h,l=a.x+h,f=a.y-h,m=a.y+h;for(r=c;r<=l;r++){var p=r;for(r<0?p+=this.x:r>=this.x&&(p-=this.x),n=f;n<=m;n++){var d=n;n<0?d+=this.y:n>=this.y&&(d-=this.y),(i=a[this.distanceMethod](this.nodes[p][d]))<e&&(o=Math.exp(-i/(2*e)),this.nodes[p][d].adjustWeights(t,this.learningRate,o))}}this.times.adjust+=Date.now()-u},SOM.prototype.train=function(t){if(!this.done)for(this.setTraining(t);this.trainOne(););},SOM.prototype.getConvertedNodes=function(){for(var t=new Array(this.x),e=0;e<this.x;e++){t[e]=new Array(this.y);for(var r=0;r<this.y;r++){var n=this.nodes[e][r];t[e][r]=this.creator?this.creator(n.weights):n.weights}}return t},SOM.prototype._findBestMatchingUnit=function(t){for(var e,r,n=1/0,i=0;i<this.x;i++)for(var o=0;o<this.y;o++)(r=this.distance(this.nodes[i][o].weights,t))<n&&(n=r,e=this.nodes[i][o]);return e},SOM.prototype.predict=function(t,e){if("boolean"==typeof t&&(e=t,t=null),t||(t=this.trainingSet),Array.isArray(t)&&(Array.isArray(t[0])||"object"==typeof t[0])){var r=this;return t.map((function(t){return r._predict(t,e)}))}return this._predict(t,e)},SOM.prototype._predict=function(t,e){Array.isArray(t)||(t=this.extractor(t));var r=this._findBestMatchingUnit(t),n=[r.x,r.y];return e&&(n[2]=r.getPosition(t)),n},SOM.prototype.getQuantizationError=function(){for(var t=this.getFit(),e=t.length,r=0,n=0;n<e;n++)r+=t[n];return r/e},SOM.prototype.getFit=function(t){t||(t=this.trainingSet);for(var e,r=t.length,n=new Array(r),i=0;i<r;i++)e=this._findBestMatchingUnit(t[i]),n[i]=Math.sqrt(this.distance(t[i],e.weights));return n};var src$c=SOM;function maybeToPrecision(t,e){return t<0?(t=0-t,"number"==typeof e?"- "+t.toPrecision(e):"- "+t.toString()):"number"==typeof e?t.toPrecision(e):t.toString()}function checkArraySize(t,e){if(!Array.isArray(t)||!Array.isArray(e))throw new TypeError("x and y must be arrays");if(t.length!==e.length)throw new RangeError("x and y arrays must have the same length")}class BaseRegression{constructor(){if(new.target===BaseRegression)throw new Error("BaseRegression must be subclassed")}predict(t){if("number"==typeof t)return this._predict(t);if(Array.isArray(t)){const e=new Array(t.length);for(let r=0;r<t.length;r++)e[r]=this._predict(t[r]);return e}throw new TypeError("x must be a number or array")}_predict(){throw new Error("_predict must be implemented")}train(){}toString(){return""}toLaTeX(){return""}score(t,e){if(!Array.isArray(t)||!Array.isArray(e)||t.length!==e.length)throw new Error("x and y must be arrays of the same length");const r=t.length,n=new Array(r);for(let e=0;e<r;e++)n[e]=this._predict(t[e]);let i=0,o=0,s=0,a=0,u=0,h=0,c=0;for(let t=0;t<r;t++)i+=n[t],o+=e[t],u+=n[t]*n[t],h+=e[t]*e[t],c+=n[t]*e[t],0!==e[t]&&(s+=(e[t]-n[t])*(e[t]-n[t])/e[t]),a=(e[t]-n[t])*(e[t]-n[t]);const l=(r*c-i*o)/Math.sqrt((r*u-i*i)*(r*h-o*o));return{r:l,r2:l*l,chi2:s,rmsd:a*a/r}}}class SimpleLinearRegression extends BaseRegression{constructor(t,e){super(),!0===t?(this.slope=e.slope,this.intercept=e.intercept,this.coefficients=[e.intercept,e.slope]):(checkArraySize(t,e),regress(this,t,e))}toJSON(){return{name:"simpleLinearRegression",slope:this.slope,intercept:this.intercept}}_predict(t){return this.slope*t+this.intercept}computeX(t){return(t-this.intercept)/this.slope}toString(t){let e="f(x) = ";if(0!==this.slope){const r=maybeToPrecision(this.slope,t);if(e+=("1"===r?"":r+" * ")+"x",this.intercept){const r=Math.abs(this.intercept);e+=` ${r===this.intercept?"+":"-"} ${maybeToPrecision(r,t)}`}}else e+=maybeToPrecision(this.intercept,t);return e}toLaTeX(t){return this.toString(t)}static load(t){if("simpleLinearRegression"!==t.name)throw new TypeError("not a SLR model");return new SimpleLinearRegression(!0,t)}}function regress(t,e,r){const n=e.length;let i=0,o=0,s=0,a=0;for(let t=0;t<n;t++)i+=e[t],o+=r[t],s+=e[t]*e[t],a+=e[t]*r[t];const u=n*a-i*o;t.slope=u/(n*s-i*i),t.intercept=1/n*o-t.slope*(1/n)*i,t.coefficients=[t.intercept,t.slope]}class PolynomialRegression extends BaseRegression{constructor(t,e,r){super(),!0===t?(this.degree=e.degree,this.powers=e.powers,this.coefficients=e.coefficients):(checkArraySize(t,e),regress$1(this,t,e,r))}_predict(t){let e=0;for(let r=0;r<this.powers.length;r++)e+=this.coefficients[r]*Math.pow(t,this.powers[r]);return e}toJSON(){return{name:"polynomialRegression",degree:this.degree,powers:this.powers,coefficients:this.coefficients}}toString(t){return this._toFormula(t,!1)}toLaTeX(t){return this._toFormula(t,!0)}_toFormula(t,e){let r="^",n="",i=" * ";e&&(r="^{",n="}",i="");let o="",s="";for(let e=0;e<this.coefficients.length;e++)s="",0!==this.coefficients[e]&&(s=0===this.powers[e]?maybeToPrecision(this.coefficients[e],t):1===this.powers[e]?maybeToPrecision(this.coefficients[e],t)+i+"x":maybeToPrecision(this.coefficients[e],t)+i+"x"+r+this.powers[e]+n,this.coefficients[e]>0&&e!==this.coefficients.length-1?s=" + "+s:e!==this.coefficients.length-1&&(s=" "+s)),o=s+o;return"+"===o.charAt(0)&&(o=o.slice(1)),"f(x) = "+o}static load(t){if("polynomialRegression"!==t.name)throw new TypeError("not a polynomial regression model");return new PolynomialRegression(!0,t)}}function regress$1(t,e,r,n){const i=e.length;let o;if(Array.isArray(n))o=n,n=o.length;else{n++,o=new Array(n);for(let t=0;t<n;t++)o[t]=t}const s=new Matrix$1(i,n),a=new Matrix$1([r]);for(let t=0;t<n;t++)for(let r=0;r<i;r++)0===o[t]?s[r][t]=1:s[r][t]=Math.pow(e[r],o[t]);const u=s.transposeView(),h=u.mmul(s),c=u.mmul(a.transposeView());t.degree=n-1,t.powers=o,t.coefficients=solve$$1(h,c).to1DArray()}class ExponentialRegression extends BaseRegression{constructor(t,e){super(),!0===t?(this.A=e.A,this.B=e.B):(checkArraySize(t,e),regress$2(this,t,e))}_predict(t){return this.B*Math.exp(t*this.A)}toJSON(){return{name:"exponentialRegression",A:this.A,B:this.B}}toString(t){return"f(x) = "+maybeToPrecision(this.B,t)+" * e^("+maybeToPrecision(this.A,t)+" * x)"}toLaTeX(t){return this.A>=0?"f(x) = "+maybeToPrecision(this.B,t)+"e^{"+maybeToPrecision(this.A,t)+"x}":"f(x) = \\frac{"+maybeToPrecision(this.B,t)+"}{e^{"+maybeToPrecision(-this.A,t)+"x}}"}static load(t){if("exponentialRegression"!==t.name)throw new TypeError("not a exponential regression model");return new ExponentialRegression(!0,t)}}function regress$2(t,e,r){const n=e.length,i=new Array(n);for(let t=0;t<n;t++)i[t]=Math.log(r[t]);const o=new SimpleLinearRegression(e,i);t.A=o.slope,t.B=Math.exp(o.intercept)}class PowerRegression extends BaseRegression{constructor(t,e){super(),!0===t?(this.A=e.A,this.B=e.B):(checkArraySize(t,e),regress$3(this,t,e))}_predict(t){return this.A*Math.pow(t,this.B)}toJSON(){return{name:"powerRegression",A:this.A,B:this.B}}toString(t){return"f(x) = "+maybeToPrecision(this.A,t)+" * x^"+maybeToPrecision(this.B,t)}toLaTeX(t){return this.B>=0?"f(x) = "+maybeToPrecision(this.A,t)+"x^{"+maybeToPrecision(this.B,t)+"}":"f(x) = \\frac{"+maybeToPrecision(this.A,t)+"}{x^{"+maybeToPrecision(-this.B,t)+"}}"}static load(t){if("powerRegression"!==t.name)throw new TypeError("not a power regression model");return new PowerRegression(!0,t)}}function regress$3(t,e,r){const n=e.length,i=new Array(n),o=new Array(n);for(let t=0;t<n;t++)i[t]=Math.log(e[t]),o[t]=Math.log(r[t]);const s=new SimpleLinearRegression(i,o);t.A=Math.exp(s.intercept),t.B=s.slope}class MultivariateLinearRegression extends BaseRegression{constructor(t,e,r={}){const{intercept:n=!0,statistics:i=!0}=r;if(super(),this.statistics=i,!0===t)this.weights=e.weights,this.inputs=e.inputs,this.outputs=e.outputs,this.intercept=e.intercept;else{t=new Matrix$1(t),n&&t.addColumn(new Array(t.length).fill(1));const r=new SingularValueDecomposition$$1(t,{autoTranspose:!0}).solve(e);if(this.weights=r.to2DArray(),this.inputs=t[0].length,this.outputs=e[0].length,n&&this.inputs--,this.intercept=n,i){const n=t.mmul(r),i=new Matrix$1(e).addM(n.neg()).to2DArray().map((t=>Math.pow(t[0],2))).reduce(((t,e)=>t+e))/(e.length-t.columns);this.stdError=Math.sqrt(i),this.stdErrorMatrix=t.transposeView().mmul(t).pseudoInverse().mul(i),this.stdErrors=this.stdErrorMatrix.diagonal().map((t=>Math.sqrt(t))),this.tStats=this.weights.map(((t,e)=>0===this.stdErrors[e]?0:t[0]/this.stdErrors[e]))}}}predict(t){if(Array.isArray(t)){if("number"==typeof t[0])return this._predict(t);if(Array.isArray(t[0])){const e=new Array(t.length);for(let r=0;r<t.length;r++)e[r]=this._predict(t[r]);return e}}throw new TypeError("x must be a matrix or array of numbers")}_predict(t){const e=new Array(this.outputs);if(this.intercept)for(let t=0;t<this.outputs;t++)e[t]=this.weights[this.inputs][t];else e.fill(0);for(let r=0;r<this.inputs;r++)for(let n=0;n<this.outputs;n++)e[n]+=this.weights[r][n]*t[r];return e}score(){throw new Error("score method is not implemented yet")}toJSON(){return{name:"multivariateLinearRegression",weights:this.weights,inputs:this.inputs,outputs:this.outputs,intercept:this.intercept,summary:this.statistics?{regressionStatistics:{standardError:this.stdError,observations:this.outputs},variables:this.weights.map(((t,e)=>({label:e===this.weights.length-1?"Intercept":`X Variable ${e+1}`,coefficients:t,standardError:this.stdErrors[e],tStat:this.tStats[e]})))}:void 0}}static load(t){if("multivariateLinearRegression"!==t.name)throw new Error("not a MLR model");return new MultivariateLinearRegression(!0,t)}}class PotentialRegression extends BaseRegression{constructor(t,e,r){if(super(),!0===t)this.A=e.A,this.M=e.M;else{if(t.length!==e.length)throw new RangeError("input and output array have a different length");var n=new PolynomialRegression(t,e,[r]);this.A=n.coefficients[0],this.M=r}}_predict(t){return this.A*Math.pow(t,this.M)}toJSON(){return{name:"potentialRegression",A:this.A,M:this.M}}toString(t){return"f(x) = "+maybeToPrecision(this.A,t)+" * x^"+this.M}toLaTeX(t){return this.M>=0?"f(x) = "+maybeToPrecision(this.A,t)+"x^{"+this.M+"}":"f(x) = \\frac{"+maybeToPrecision(this.A,t)+"}{x^{"+-this.M+"}}"}static load(t){if("potentialRegression"!==t.name)throw new TypeError("not a potential regression model");return new PotentialRegression(!0,t)}}const defaultOptions$l={lambda:.1,kernelType:"gaussian",kernelOptions:{},computeCoefficient:!1};class KernelRidgeRegression extends BaseRegression{constructor(t,e,r){if(super(),!0===t)this.alpha=e.alpha,this.inputs=e.inputs,this.kernelType=e.kernelType,this.kernelOptions=e.kernelOptions,this.kernel=new kernel(e.kernelType,e.kernelOptions);else{r=Object.assign({},defaultOptions$l,r);const n=new kernel(r.kernelType,r.kernelOptions),i=n.compute(t),o=t.length;i.add(Matrix$1.eye(o,o).mul(r.lambda)),this.alpha=solve$$1(i,e),this.inputs=t,this.kernelType=r.kernelType,this.kernelOptions=r.kernelOptions,this.kernel=n}}_predict(t){return this.kernel.compute([t],this.inputs).mmul(this.alpha)[0]}toJSON(){return{name:"kernelRidgeRegression",alpha:this.alpha,inputs:this.inputs,kernelType:this.kernelType,kernelOptions:this.kernelOptions}}static load(t){if("kernelRidgeRegression"!==t.name)throw new TypeError("not a KRR model");return new KernelRidgeRegression(!0,t)}}const defaultOptions$m={order:2};class PolynomialFitRegression2D extends BaseRegression{constructor(t,e,r){super(),!0===t?(this.coefficients=Matrix$1.columnVector(e.coefficients),this.order=e.order,e.r&&(this.r=e.r,this.r2=e.r2),e.chi2&&(this.chi2=e.chi2)):(r=Object.assign({},defaultOptions$m,r),this.order=r.order,this.coefficients=[],this.X=t,this.y=e,this.train(this.X,this.y,r))}train(t,e){if(Matrix$1.isMatrix(t)||(t=new Matrix$1(t)),Matrix$1.isMatrix(e)||(e=Matrix$1.columnVector(e)),e.rows!==t.rows&&(e=e.transpose()),2!==t.columns)throw new RangeError("You give X with "+t.columns+" columns and it must be 2");if(t.rows!==e.rows)throw new RangeError("X and y must have the same rows");var r=t.rows,n=(this.order+2)*(this.order+1)/2;this.coefficients=new Array(n);var i=t.getColumnVector(0),o=t.getColumnVector(1),s=1/i.clone().apply(abs).max(),a=1/o.clone().apply(abs).max(),u=1/e.clone().apply(abs).max();i.mulColumn(0,s),o.mulColumn(0,a),e.mulColumn(0,u);for(var h=new Matrix$1(r,n),c=0,l=0;l<=this.order;++l)for(var f=this.order-l,m=0;m<=f;++m){var p=powColVector(i,l).mulColumnVector(powColVector(o,m));h.setColumn(c,p),c++}var d=new SingularValueDecomposition$$1(h.transpose(),{computeLeftSingularVectors:!0,computeRightSingularVectors:!0,autoTranspose:!1}),g=Matrix$1.rowVector(d.diagonal);g=g.apply((function(t,e){this[t][e]>=1e-15?this[t][e]=1/this[t][e]:this[t][e]=0}));var v=Matrix$1.zeros(r,n);for(l=0;l<n;++l)v[l][l]=g[0][l];g=v;var w=d.rightSingularVectors,y=d.leftSingularVectors;for(this.coefficients=y.mmul(g.transpose()).mmul(w.transpose()).mmul(e),c=0,l=0;l<=n;++l)for(f=this.order-l,m=0;m<=f;++m)this.coefficients[c][0]=this.coefficients[c][0]*Math.pow(s,l)*Math.pow(a,m)/u,c++}_predict(t){for(var e=t[0],r=t[1],n=0,i=0,o=0;o<=this.order;o++)for(var s=0;s<=this.order-o;s++)n+=Math.pow(e,o)*Math.pow(r,s)*this.coefficients[i][0],i++;return n}toJSON(){return{name:"polyfit2D",order:this.order,coefficients:this.coefficients}}static load(t){if("polyfit2D"!==t.name)throw new TypeError("not a polyfit2D model");return new PolynomialFitRegression2D(!0,t)}}function powColVector(t,e){for(var r=t.clone(),n=0;n<t.rows;++n)r[n][0]=Math.pow(r[n][0],e);return r}function abs(t,e){this[t][e]=Math.abs(this[t][e])}const median$2=array$1.median;class TheilSenRegression extends BaseRegression{constructor(t,e){super(),!0===t?(this.slope=e.slope,this.intercept=e.intercept,this.coefficients=e.coefficients):(checkArraySize(t,e),theilSen(this,t,e))}toJSON(){return{name:"TheilSenRegression",slope:this.slope,intercept:this.intercept}}_predict(t){return this.slope*t+this.intercept}computeX(t){return(t-this.intercept)/this.slope}toString(t){var e="f(x) = ";if(this.slope){var r=maybeToPrecision(this.slope,t);if(e+=(Math.abs(r-1)<1e-5?"":r+" * ")+"x",this.intercept){var n=Math.abs(this.intercept);e+=" "+(n===this.intercept?"+":"-")+" "+maybeToPrecision(n,t)}}else e+=maybeToPrecision(this.intercept,t);return e}toLaTeX(t){return this.toString(t)}static load(t){if("TheilSenRegression"!==t.name)throw new TypeError("not a Theil-Sen model");return new TheilSenRegression(!0,t)}}function theilSen(t,e,r){let n=e.length,i=new Array(n*n),o=0;for(let t=0;t<n;++t)for(let s=t+1;s<n;++s)e[t]!==e[s]&&(i[o++]=(r[s]-r[t])/(e[s]-e[t]));i.length=o;let s=median$2(i),a=new Array(n);for(let t=0;t<n;++t)a[t]=r[t]-s*e[t];t.slope=s,t.intercept=median$2(a),t.coefficients=[t.intercept,t.slope]}class RobustPolynomialRegression extends BaseRegression{constructor(t,e,r){super(),!0===t?(this.degree=e.degree,this.powers=e.powers,this.coefficients=e.coefficients):(checkArraySize(t,e),robustPolynomial(this,t,e,r))}toJSON(){return{name:"robustPolynomialRegression",degree:this.degree,powers:this.powers,coefficients:this.coefficients}}_predict(t){return predict(t,this.powers,this.coefficients)}toString(t){return this._toFormula(t,!1)}toLaTeX(t){return this._toFormula(t,!0)}_toFormula(t,e){let r="^",n="",i=" * ";e&&(r="^{",n="}",i="");let o="",s="";for(let e=0;e<this.coefficients.length;e++)s="",0!==this.coefficients[e]&&(s=0===this.powers[e]?maybeToPrecision(this.coefficients[e],t):1===this.powers[e]?maybeToPrecision(this.coefficients[e],t)+i+"x":maybeToPrecision(this.coefficients[e],t)+i+"x"+r+this.powers[e]+n,this.coefficients[e]>0&&e!==this.coefficients.length-1?s=" + "+s:e!==this.coefficients.length-1&&(s=" "+s)),o=s+o;return"+"===o.charAt(0)&&(o=o.slice(1)),"f(x) = "+o}static load(t){if("robustPolynomialRegression"!==t.name)throw new TypeError("not a RobustPolynomialRegression model");return new RobustPolynomialRegression(!0,t)}}function robustPolynomial(t,e,r,n){let i=new Array(n);for(let t=0;t<n;t++)i[t]=t;const o=getRandomTuples(e,r,n);for(var s,a=0;a<o.length;a++){for(var u=calcCoefficients(o[a],i),h=e.slice(),c=0;c<e.length;c++)h[c]=r[c]-predict(e[c],i,u),h[c]={residual:h[c]*h[c],coefficients:u};var l=residualsMedian(h);(!s||l.residual<s.residual)&&(s=l)}t.degree=n,t.powers=i,t.coefficients=s.coefficients}function getRandomTuples(t,e,r){for(var n=Math.floor(t.length/r),i=new Array(n),o=0;o<t.length;o++){for(var s=Math.floor(Math.random()*n),a=0;a<t.length;){if(!i[s]){i[s]=[{x:t[o],y:e[o]}];break}if(i[s].length<r){i[s].push({x:t[o],y:e[o]});break}a++,s=(s+1)%n}if(a===t.length)return i}return i}function calcCoefficients(t,e){for(var r=t.slice(),n=t.slice(),i=0;i<r.length;i++){n[i]=[t[i].y],r[i]=new Array(e.length);for(var o=0;o<e.length;o++)r[i][o]=Math.pow(t[i].x,e[o])}return solve$$1(r,n).to1DArray()}function predict(t,e,r){let n=0;for(let i=0;i<e.length;i++)n+=r[i]*Math.pow(t,e[i]);return n}function residualsMedian(t){t.sort(((t,e)=>t.residual-e.residual));var e=t.length,r=Math.floor(e/2);return e%2==0?t[r-1]:t[r]}const NLR={PotentialRegression:PotentialRegression};var src$d=Object.freeze({NLR:NLR,NonLinearRegression:NLR,SimpleLinearRegression:SimpleLinearRegression,SLR:SimpleLinearRegression,PolynomialRegression:PolynomialRegression,ExponentialRegression:ExponentialRegression,PowerRegression:PowerRegression,MultivariateLinearRegression:MultivariateLinearRegression,KernelRidgeRegression:KernelRidgeRegression,KRR:KernelRidgeRegression,PolinomialFitting2D:PolynomialFitRegression2D,TheilSenRegression:TheilSenRegression,RobustPolynomialRegression:RobustPolynomialRegression});function errorCalculation(t,e,r){var n=0;const i=r(e);for(var o=0;o<t.x.length;o++)n+=Math.abs(t.y[o]-i(t.x[o]));return n}function gradientFunction(t,e,r,n,i){const o=r.length,s=t.x.length;for(var a=new Array(o),u=0;u<o;u++){a[u]=new Array(s);var h=r.concat();h[u]+=n;for(var c=i(h),l=0;l<s;l++)a[u][l]=e[l]-c(t.x[l])}return new require$$0$3.Matrix(a)}function matrixFunction(t,e){const r=t.x.length;for(var n=new Array(r),i=0;i<r;i++)n[i]=t.y[i]-e[i];return new require$$0$3.Matrix([n])}function step$1(t,e,r,n,i){var o=require$$0$3.Matrix.eye(e.length).mul(r*n*n),s=t.x.length,a=new Array(s);const u=i(e);for(var h=0;h<s;h++)a[h]=u(t.x[h]);var c=gradientFunction(t,a,e,n,i),l=matrixFunction(t,a).transposeView(),f=require$$0$3.inverse(o.add(c.mmul(c.transposeView())));return(e=(e=new require$$0$3.Matrix([e])).sub(f.mmul(c).mmul(l).mul(n).transposeView())).to1DArray()}function levenbergMarquardt(t,e,r={}){let{maxIterations:n=100,gradientDifference:i=.1,damping:o=0,errorTolerance:s=.01,initialValues:a}=r;if(o<=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 u=a||new Array(e.length).fill(1);if(!Array.isArray(u))throw new Error("initialValues must be an array");for(var h=errorCalculation(t,u,e),c=h<=s,l=0;l<n&&!c;l++)c=(h=errorCalculation(t,u=step$1(t,u,o,i,e),e))<=s;return{parameterValues:u,parameterError:h,iterations:l}}var lib=levenbergMarquardt,newArray_1=newArray;function newArray(t,e){t=t||0;for(var r=new Array(t),n=0;n<t;n++)r[n]=e;return r}var binarySearch=function(t,e,r,n,i){var o,s;if(void 0===n)n=0;else if((n|=0)<0||n>=t.length)throw new RangeError("invalid lower bound");if(void 0===i)i=t.length-1;else if((i|=0)<n||i>=t.length)throw new RangeError("invalid upper bound");for(;n<=i;)if((s=+r(t[o=n+(i-n>>1)],e,o,t))<0)n=o+1;else{if(!(s>0))return o;i=o-1}return~n},numberIsNan=Number.isNaN||function(t){return t!=t};function assertNum(t){if("number"!=typeof t||numberIsNan(t))throw new TypeError("Expected a number")}var asc=function(t,e){return assertNum(t),assertNum(e),t-e},desc=function(t,e){return assertNum(t),assertNum(e),e-t},numSort={asc:asc,desc:desc};const sortAsc=numSort.asc,largestPrime=2147483647,primeNumbers=[largestPrime,5,11,23,47,97,197,397,797,1597,3203,6421,12853,25717,51437,102877,205759,411527,823117,1646237,3292489,6584983,13169977,26339969,52679969,105359939,210719881,421439783,842879579,1685759167,433,877,1759,3527,7057,14143,28289,56591,113189,226379,452759,905551,1811107,3622219,7244441,14488931,28977863,57955739,115911563,231823147,463646329,927292699,1854585413,953,1907,3821,7643,15287,30577,61169,122347,244703,489407,978821,1957651,3915341,7830701,15661423,31322867,62645741,125291483,250582987,501165979,1002331963,2004663929,1039,2081,4177,8363,16729,33461,66923,133853,267713,535481,1070981,2141977,4283963,8567929,17135863,34271747,68543509,137087021,274174111,548348231,1096696463,31,67,137,277,557,1117,2237,4481,8963,17929,35863,71741,143483,286973,573953,1147921,2295859,4591721,9183457,18366923,36733847,73467739,146935499,293871013,587742049,1175484103,599,1201,2411,4831,9677,19373,38747,77509,155027,310081,620171,1240361,2480729,4961459,9922933,19845871,39691759,79383533,158767069,317534141,635068283,1270136683,311,631,1277,2557,5119,10243,20507,41017,82037,164089,328213,656429,1312867,2625761,5251529,10503061,21006137,42012281,84024581,168049163,336098327,672196673,1344393353,3,7,17,37,79,163,331,673,1361,2729,5471,10949,21911,43853,87719,175447,350899,701819,1403641,2807303,5614657,11229331,22458671,44917381,89834777,179669557,359339171,718678369,1437356741,43,89,179,359,719,1439,2879,5779,11579,23159,46327,92657,185323,370661,741337,1482707,2965421,5930887,11861791,23723597,47447201,94894427,189788857,379577741,759155483,1518310967,379,761,1523,3049,6101,12203,24407,48817,97649,195311,390647,781301,1562611,3125257,6250537,12501169,25002389,50004791,100009607,200019221,400038451,800076929,1600153859,13,29,59,127,257,521,1049,2099,4201,8419,16843,33703,67409,134837,269683,539389,1078787,2157587,4315183,8630387,17260781,34521589,69043189,138086407,276172823,552345671,1104691373,19,41,83,167,337,677,1361,2729,5471,10949,21911,43853,87719,175447,350899,701819,1403641,2807303,5614657,11229331,22458671,44917381,89834777,179669557,359339171,718678369,1437356741,53,107,223,449,907,1823,3659,7321,14653,29311,58631,117269,234539,469099,938207,1876417,3752839,7505681,15011389,30022781,60045577,120091177,240182359,480364727,960729461,1921458943];function nextPrime(t){let e=binarySearch(primeNumbers,t,sortAsc);return e<0&&(e=~e),primeNumbers[e]}primeNumbers.sort(sortAsc);var nextPrime_1=nextPrime,largestPrime_1=largestPrime,primeFinder={nextPrime:nextPrime_1,largestPrime:largestPrime_1};const nextPrime$1=primeFinder.nextPrime,largestPrime$1=primeFinder.largestPrime,FREE=0,FULL=1,REMOVED=2,defaultInitialCapacity=150,defaultMinLoadFactor=1/6,defaultMaxLoadFactor=2/3;class HashTable{constructor(t={}){if(t instanceof HashTable)return this.table=t.table.slice(),this.values=t.values.slice(),this.state=t.state.slice(),this.minLoadFactor=t.minLoadFactor,this.maxLoadFactor=t.maxLoadFactor,this.distinct=t.distinct,this.freeEntries=t.freeEntries,this.lowWaterMark=t.lowWaterMark,void(this.highWaterMark=t.maxLoadFactor);const e=void 0===t.initialCapacity?defaultInitialCapacity:t.initialCapacity;if(e<0)throw new RangeError(`initial capacity must not be less than zero: ${e}`);const r=void 0===t.minLoadFactor?defaultMinLoadFactor:t.minLoadFactor,n=void 0===t.maxLoadFactor?defaultMaxLoadFactor:t.maxLoadFactor;if(r<0||r>=1)throw new RangeError(`invalid minLoadFactor: ${r}`);if(n<=0||n>=1)throw new RangeError(`invalid maxLoadFactor: ${n}`);if(r>=n)throw new RangeError(`minLoadFactor (${r}) must be smaller than maxLoadFactor (${n})`);let i=e;i=i/n|0,i=nextPrime$1(i),0===i&&(i=1),this.table=newArray_1(i,0),this.values=newArray_1(i,0),this.state=newArray_1(i,0),this.minLoadFactor=r,this.maxLoadFactor=i===largestPrime$1?1:n,this.distinct=0,this.freeEntries=i,this.lowWaterMark=0,this.highWaterMark=chooseHighWaterMark(i,this.maxLoadFactor)}clone(){return new HashTable(this)}get size(){return this.distinct}get(t){const e=this.indexOfKey(t);return e<0?0:this.values[e]}set(t,e){let r=this.indexOfInsertion(t);if(r<0)return r=-r-1,this.values[r]=e,!1;if(this.distinct>this.highWaterMark){const r=chooseGrowCapacity(this.distinct+1,this.minLoadFactor,this.maxLoadFactor);return this.rehash(r),this.set(t,e)}if(this.table[r]=t,this.values[r]=e,this.state[r]===FREE&&this.freeEntries--,this.state[r]=FULL,this.distinct++,this.freeEntries<1){const t=chooseGrowCapacity(this.distinct+1,this.minLoadFactor,this.maxLoadFactor);this.rehash(t)}return!0}remove(t,e){const r=this.indexOfKey(t);return!(r<0)&&(this.state[r]=REMOVED,this.distinct--,e||this.maybeShrinkCapacity(),!0)}delete(t,e){const r=this.indexOfKey(t);return!(r<0)&&(this.state[r]=FREE,this.distinct--,e||this.maybeShrinkCapacity(),!0)}maybeShrinkCapacity(){if(this.distinct<this.lowWaterMark){const t=chooseShrinkCapacity(this.distinct,this.minLoadFactor,this.maxLoadFactor);this.rehash(t)}}containsKey(t){return this.indexOfKey(t)>=0}indexOfKey(t){const e=this.table,r=this.state,n=this.table.length,i=2147483647&t;let o=i%n,s=i%(n-2);for(0===s&&(s=1);r[o]!==FREE&&(r[o]===REMOVED||e[o]!==t);)o-=s,o<0&&(o+=n);return r[o]===FREE?-1:o}containsValue(t){return this.indexOfValue(t)>=0}indexOfValue(t){const e=this.values,r=this.state;for(var n=0;n<r.length;n++)if(r[n]===FULL&&e[n]===t)return n;return-1}indexOfInsertion(t){const e=this.table,r=this.state,n=e.length,i=2147483647&t;let o=i%n,s=i%(n-2);for(0===s&&(s=1);r[o]===FULL&&e[o]!==t;)o-=s,o<0&&(o+=n);if(r[o]===REMOVED){const i=o;for(;r[o]!==FREE&&(r[o]===REMOVED||e[o]!==t);)o-=s,o<0&&(o+=n);r[o]===FREE&&(o=i)}return r[o]===FULL?-o-1:o}ensureCapacity(t){if(this.table.length<t){const e=nextPrime$1(t);this.rehash(e)}}rehash(t){const e=this.table.length;if(t<=this.distinct)throw new Error("Unexpected");const r=this.table,n=this.values,i=this.state,o=newArray_1(t,0),s=newArray_1(t,0),a=newArray_1(t,0);this.lowWaterMark=chooseLowWaterMark(t,this.minLoadFactor),this.highWaterMark=chooseHighWaterMark(t,this.maxLoadFactor),this.table=o,this.values=s,this.state=a,this.freeEntries=t-this.distinct;for(var u=0;u<e;u++)if(i[u]===FULL){var h=r[u],c=this.indexOfInsertion(h);o[c]=h,s[c]=n[u],a[c]=FULL}}forEachKey(t){for(var e=0;e<this.state.length;e++)if(this.state[e]===FULL&&!t(this.table[e]))return!1;return!0}forEachValue(t){for(var e=0;e<this.state.length;e++)if(this.state[e]===FULL&&!t(this.values[e]))return!1;return!0}forEachPair(t){for(var e=0;e<this.state.length;e++)if(this.state[e]===FULL&&!t(this.table[e],this.values[e]))return!1;return!0}}var HashTable_1=HashTable;function chooseLowWaterMark(t,e){return t*e|0}function chooseHighWaterMark(t,e){return Math.min(t-2,t*e|0)}function chooseGrowCapacity(t,e,r){return nextPrime$1(Math.max(t+1,4*t/(3*e+r)|0))}function chooseShrinkCapacity(t,e,r){return nextPrime$1(Math.max(t+1,4*t/(e+3*r)|0))}class SparseMatrix{constructor(t,e,r={}){if(t instanceof SparseMatrix){const e=t;this._init(e.rows,e.columns,e.elements.clone(),e.threshold)}else if(Array.isArray(t)){const s=t;t=s.length,r=e||{},e=s[0].length,this._init(t,e,new HashTable_1(r),r.threshold);for(var n=0;n<t;n++)for(var i=0;i<e;i++){var o=s[n][i];this.threshold&&Math.abs(o)<this.threshold&&(o=0),0!==o&&this.elements.set(n*e+i,s[n][i])}}else this._init(t,e,new HashTable_1(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){const r=Math.min(t,e),n=new SparseMatrix(t,e,{initialCapacity:r});for(var i=0;i<r;i++)n.set(i,i,1);return n}clone(){return new SparseMatrix(this)}to2DArray(){const t=new Array(this.rows);for(var 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(){let t=this.columns,e=-1;return this.forEachNonZero(((r,n,i)=>{let 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.");const 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){const 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)=>{const n=e/this.columns|0,i=e%this.columns;let 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(){const t=this.cardinality,e=new Array(t),r=new Array(t),n=new Array(t);var 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(){let t=new SparseMatrix(this.columns,this.rows,{initialCapacity:this.cardinality});return this.forEachNonZero(((e,r,n)=>(t.set(r,e,n),n))),t}}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";const operators=[["+","add"],["-","sub","subtract"],["*","mul","multiply"],["/","div","divide"],["%","mod","modulus"],["&","and"],["|","or"],["^","xor"],["<<","leftShift"],[">>","signPropagatingRightShift"],[">>>","rightShift","zeroFillRightShift"]];for(const operator of operators)for(let 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"]];["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){methods.push(["Math."+t,t])}));for(const method of methods)for(let i=1;i<method.length;i++)SparseMatrix.prototype[method[i]]=eval(fillTemplateFunction(inplaceMethod,{name:method[i],method:method[0]})),SparseMatrix[method[i]]=eval(fillTemplateFunction(staticMethod,{name:method[i]}));function fillTemplateFunction(t,e){for(const r in e)t=t.replace(new RegExp("%"+r+"%","g"),e[r]);return t}var src$e=Object.freeze({SparseMatrix:SparseMatrix}),additiveSymmetric=function(t,e){for(var r=0,n=t.length,i=0;r<n;r++)i+=(t[r]-e[r])*(t[r]-e[r])*(t[r]+e[r])/(t[r]*e[r]);return 2*i},avg=function(t,e){for(var r=t.length,n=0,i=0,o=0,s=0;s<r;s++)i+=o=Math.abs(t[s]-e[s]),n<o&&(n=o);return(n+i)/2},bhattacharyya=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=Math.sqrt(t[i]*e[i]);return-Math.log(n)},canberra=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=Math.abs(t[i]-e[i])/(t[i]+e[i]);return n},chebyshev=function(t,e){for(var r=t.length,n=0,i=0,o=0;o<r;o++)n<(i=Math.abs(t[o]-e[o]))&&(n=i);return n},clark=function(t,e){for(var r=0,n=t.length,i=0;r<n;r++)i+=Math.sqrt((t[r]-e[r])*(t[r]-e[r])/((t[r]+e[r])*(t[r]+e[r])));return 2*i},czekanowski=function(t,e){for(var r=0,n=0,i=0;i<t.length;i++)r+=Math.min(t[i],e[i]),n+=t[i]+e[i];return 2*r/n},czekanowski$1=function(t,e){return 1-czekanowski(t,e)},dice=function(t,e){for(var r=t.length,n=0,i=0,o=0,s=0;s<r;s++)n+=t[s]*t[s],i+=e[s]*e[s],o+=(t[s]-e[s])*(t[s]-e[s]);return o/(n+i)},divergence=function(t,e){for(var r=0,n=t.length,i=0;r<n;r++)i+=(t[r]-e[r])*(t[r]-e[r])/((t[r]+e[r])*(t[r]+e[r]));return 2*i},fidelity=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=Math.sqrt(t[i]*e[i]);return n},gower=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=Math.abs(t[i]-e[i]);return n/r},harmonicMean=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=t[i]*e[i]/(t[i]+e[i]);return 2*n},hellinger=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=Math.sqrt(t[i]*e[i]);return 2*Math.sqrt(1-n)},innerProduct=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=t[i]*e[i];return n},intersection=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=Math.min(t[i],e[i]);return 1-n},jaccard=function(t,e){for(var r=t.length,n=0,i=0,o=0,s=0,a=0;a<r;a++)n+=t[a]*e[a],i+=t[a]*t[a],o+=e[a]*e[a],s+=(t[a]-e[a])*(t[a]-e[a]);return s/(i+o-n)},jeffreys=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=(t[i]-e[i])*Math.log(t[i]/e[i]);return n},jensenDifference=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=(t[i]*Math.log(t[i])+e[i]*Math.log(e[i]))/2-(t[i]+e[i])/2*Math.log((t[i]+e[i])/2);return n},jensenShannon=function(t,e){for(var r=t.length,n=0,i=0,o=0;o<r;o++)n+=t[o]*Math.log(2*t[o]/(t[o]+e[o])),i+=e[o]*Math.log(2*e[o]/(t[o]+e[o]));return(n+i)/2},kdivergence=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=t[i]*Math.log(2*t[i]/(t[i]+e[i]));return n},kulczynski=function(t,e){for(var r=t.length,n=0,i=0,o=0;o<r;o++)n+=Math.abs(t[o]-e[o]),i+=Math.min(t[o],e[o]);return n/i},kullbackLeibler=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=t[i]*Math.log(t[i]/e[i]);return n},kumarHassebrook=function(t,e){for(var r=t.length,n=0,i=0,o=0,s=0;s<r;s++)n+=t[s]*e[s],i+=t[s]*t[s],o+=e[s]*e[s];return n/(i+o-n)},kumarJohnson=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=Math.pow(t[i]*t[i]-e[i]*e[i],2)/(2*Math.pow(t[i]*e[i],1.5));return n},lorentzian=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=Math.log(Math.abs(t[i]-e[i])+1);return n},manhattan=function(t,e){for(var r=0,n=t.length,i=0;r<n;r++)i+=Math.abs(t[r]-e[r]);return i},matusita=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=Math.sqrt(t[i]*e[i]);return Math.sqrt(2-2*n)},minkowski=function(t,e,r){for(var n=0,i=t.length,o=0;n<i;n++)o+=Math.pow(Math.abs(t[n]-e[n]),r);return Math.pow(o,1/r)},motyka=function(t,e){for(var r=t.length,n=0,i=0,o=0;o<r;o++)n+=Math.min(t[o],e[o]),i+=t[o]+e[o];return 1-n/i},neyman=function(t,e){for(var r=0,n=t.length,i=0;r<n;r++)i+=(t[r]-e[r])*(t[r]-e[r])/t[r];return i},pearson=function(t,e){for(var r=0,n=t.length,i=0;r<n;r++)i+=(t[r]-e[r])*(t[r]-e[r])/e[r];return i},probabilisticSymmetric=function(t,e){for(var r=0,n=t.length,i=0;r<n;r++)i+=(t[r]-e[r])*(t[r]-e[r])/(t[r]+e[r]);return 2*i},ruzicka=function(t,e){for(var r=t.length,n=0,i=0,o=0;o<r;o++)n+=Math.min(t[o],e[o]),i+=Math.max(t[o],e[o]);return n/i},soergel=function(t,e){for(var r=t.length,n=0,i=0,o=0;o<r;o++)n+=Math.abs(t[o]-e[o]),i+=Math.max(t[o],e[o]);return n/i},sorensen=function(t,e){for(var r=t.length,n=0,i=0,o=0;o<r;o++)n+=Math.abs(t[o]-e[o]),i+=t[o]+e[o];return n/i},squared=function(t,e){for(var r=0,n=t.length,i=0;r<n;r++)i+=(t[r]-e[r])*(t[r]-e[r])/(t[r]+e[r]);return i},squaredChord=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=(Math.sqrt(t[i])-Math.sqrt(e[i]))*(Math.sqrt(t[i])-Math.sqrt(e[i]));return n},taneja=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=(t[i]+e[i])/2*Math.log((t[i]+e[i])/(2*Math.sqrt(t[i]*e[i])));return n},tanimoto=function(t,e,r){if(r){for(var n=0,i=0,o=0;o<t.length;o++)n+=t[o]&&e[o],i+=t[o]||e[o];return 0===i?1:n/i}for(var s=t.length,a=0,u=0,h=0,c=0;c<s;c++)a+=t[c],u+=e[c],h+=Math.min(t[c],e[c]);return 1-(a+u-2*h)/(a+u-h)},tanimoto$1=function(t,e,r){if(r)return 1-tanimoto(t,e,r);for(var n=t.length,i=0,o=0,s=0,a=0;a<n;a++)i+=t[a],o+=e[a],s+=Math.min(t[a],e[a]);return(i+o-2*s)/(i+o-s)},topsoe=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=t[i]*Math.log(2*t[i]/(t[i]+e[i]))+e[i]*Math.log(2*e[i]/(t[i]+e[i]));return n};function createTree(t,e,r,n,i,o){if(o=o||.01,!(n-r<(i=i||.16))){for(var s=0,a=0;t[a]<n;a++)t[a]>r&&(s+=e[a]);if(!(s<o)){for(var u=0,h=0;t[h]<n;h++)t[a]>r&&(u+=t[h]*e[h]);if(!((u/=s)-r<1e-5||n-u<1e-5))return u-r<i/4?createTree(t,e,u,n,i,o):n-u<i/4?createTree(t,e,r,u,i,o):{sum:s,center:u,left:createTree(t,e,r,u,i,o),right:createTree(t,e,u,n,i,o)}}}}function S(t,e,r,n,i){return void 0===t||void 0===e?0:n*(r*Math.min(t.sum,e.sum)/Math.max(t.sum,e.sum)+(1-r)*Math.exp(-i*Math.abs(t.center-e.center)))+(1-n)*(S(t.left,e.left,r,n,i)+S(t.right,e.right,r,n,i))}var defaultOptions$n={minWindow:.16,threshold:.01,alpha:.1,beta:.33,gamma:.001};function tree(t,e,r,n,i){for(var o in i=i||{},defaultOptions$n)i.hasOwnProperty(o)||(i[o]=defaultOptions$n[o]);return S(t.sum?t:createTree(t.x,t.y,r,n,i.minWindow,i.threshold),e.sum?e:createTree(e.x,e.y,r,n,i.minWindow,i.threshold),i.alpha,i.beta,i.gamma)}var src$f={calc:tree,createTree:createTree},waveHedges=function(t,e){for(var r=t.length,n=0,i=0;i<r;i++)n+=1-Math.min(t[i],e[i])/Math.max(t[i],e[i]);return n},additiveSymmetric$1=additiveSymmetric,avg$1=avg,bhattacharyya$1=bhattacharyya,canberra$1=canberra,chebyshev$1=chebyshev,clark$1=clark,czekanowski$2=czekanowski$1,dice$1=dice,divergence$1=divergence,euclidean$1=euclidean_1,fidelity$1=fidelity,gower$1=gower,harmonicMean$1=harmonicMean,hellinger$1=hellinger,innerProduct$1=innerProduct,intersection$1=intersection,jaccard$1=jaccard,jeffreys$1=jeffreys,jensenDifference$1=jensenDifference,jensenShannon$1=jensenShannon,kdivergence$1=kdivergence,kulczynski$1=kulczynski,kullbackLeibler$1=kullbackLeibler,kumarHassebrook$1=kumarHassebrook,kumarJohnson$1=kumarJohnson,lorentzian$1=lorentzian,manhattan$1=manhattan,matusita$1=matusita,minkowski$1=minkowski,motyka$1=motyka,neyman$1=neyman,pearson$1=pearson,probabilisticSymmetric$1=probabilisticSymmetric,ruzicka$1=ruzicka,soergel$1=soergel,sorensen$1=sorensen,squared$1=squared,squaredChord$1=squaredChord,squaredEuclidean$5=euclidean_1.squared,taneja$1=taneja,tanimoto$2=tanimoto$1,topsoe$1=topsoe,tree$1=src$f,waveHedges$1=waveHedges,distances={additiveSymmetric:additiveSymmetric$1,avg:avg$1,bhattacharyya:bhattacharyya$1,canberra:canberra$1,chebyshev:chebyshev$1,clark:clark$1,czekanowski:czekanowski$2,dice:dice$1,divergence:divergence$1,euclidean:euclidean$1,fidelity:fidelity$1,gower:gower$1,harmonicMean:harmonicMean$1,hellinger:hellinger$1,innerProduct:innerProduct$1,intersection:intersection$1,jaccard:jaccard$1,jeffreys:jeffreys$1,jensenDifference:jensenDifference$1,jensenShannon:jensenShannon$1,kdivergence:kdivergence$1,kulczynski:kulczynski$1,kullbackLeibler:kullbackLeibler$1,kumarHassebrook:kumarHassebrook$1,kumarJohnson:kumarJohnson$1,lorentzian:lorentzian$1,manhattan:manhattan$1,matusita:matusita$1,minkowski:minkowski$1,motyka:motyka$1,neyman:neyman$1,pearson:pearson$1,probabilisticSymmetric:probabilisticSymmetric$1,ruzicka:ruzicka$1,soergel:soergel$1,sorensen:sorensen$1,squared:squared$1,squaredChord:squaredChord$1,squaredEuclidean:squaredEuclidean$5,taneja:taneja$1,tanimoto:tanimoto$2,topsoe:topsoe$1,tree:tree$1,waveHedges:waveHedges$1},cosine=function(t,e){for(var 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0===arguments[0]?Date.now():arguments[0];!function(t,e){if(!(t instanceof e))throw new TypeError("Cannot call a class as a function")}(this,t),this.state=new Uint32Array(4),this.init(e)}return r(t,[{key:"init",value:function(t){this.state[0]=t,this.state[1]=0,this.state[2]=0,this.state[3]=0;for(var e=1;e<8;e++)this.state[3&e]^=e+(r=1812433253,n=this.state[e-1&3]^this.state[e-1&3]>>>30>>>0,i=void 0,i=65535&(r>>>=0),((r-i)*(n>>>=0)>>>0)+i*n>>>0)>>>0;var r,n,i,o;0===(o=this).state[0]&&0===o.state[1]&&0===o.state[2]&&0===o.state[3]&&(o.state[0]=88,o.state[1]=83,o.state[2]=65,o.state[3]=68);for(e=0;e<8;e++)u(this)}},{key:"getUint32",value:function(){return u(this),this.state[3]+this.state[2]>>>0}},{key:"getFloat",value:function(){return(this.getUint32()>>>8)*n}},{key:"random",get:function(){return this._random||(this._random=this.getFloat.bind(this)),this._random}}]),t}();e.default=i;var o=15,s=18,a=11;function u(t){var e=t.state[0];e^=e<<o,e^=e>>>s,e^=t.state[3]<<a,t.state[0]=t.state[1],t.state[1]=t.state[2],t.state[2]=t.state[3],t.state[3]=e}t.exports=e.default}));unwrapExports(xsaddEs5);var acc=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=(t.tn[n]+t.tp[n])/(e-1);return r},err=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.fn[n]+t.fp[n]/(e-1);return r},fpr=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.fp[n]/t.nNeg;return r},tpr=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.tp[n]/t.nPos;return r},fnr=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.fn[n]/t.nPos;return r},tnr=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.tn[n]/t.nNeg;return r},ppv=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.fp[n]+t.tp[n]!==0?t.tp[n]/(t.fp[n]+t.tp[n]):0;return r},npv=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.fn[n]+t.tn[n]!==0?t.tn[n]/(t.fn[n]+t.tn[n]):0;return r},pcfall=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.fp[n]+t.tp[n]!==0?1-t.tp[n]/(t.fp[n]+t.tp[n]):1;return r},pcmiss=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.fn[n]+t.tn[n]!==0?1-t.tn[n]/(t.fn[n]+t.tn[n]):1;return r},lift=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=0!==t.nPosPred[n]?t.tp[n]/t.nPos/(t.nPosPred[n]/t.nSamples):0;return r},rpp=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.nPosPred[n]/t.nSamples;return r},rnp=t=>{const e=t.cutoffs.length,r=new Array(e);for(var n=0;n<e;n++)r[n]=t.nNegPred[n]/t.nSamples;return r},threshold=t=>{const e=t.cutoffs.slice();return e[0]=e[1],e},measures={acc:acc,err:err,fpr:fpr,tpr:tpr,fnr:fnr,tnr:tnr,ppv:ppv,npv:npv,pcfall:pcfall,pcmiss:pcmiss,lift:lift,rpp:rpp,rnp:rnp,threshold:threshold};class Performance{constructor(t,e,r){if(r=r||{},t.length!==e.length||t[0].length!==e[0].length)throw new Error("dimensions of prediction and target do not match");const n=t.length,i=t[0].length,o=!r.max,s=[];if(r.all)for(var a=0;a<n;a++)for(var u=0;u<i;u++)s.push({pred:t[a][u],targ:e[a][u]});else{if(n<3||n!==i)throw new Error('When "all" option is false, the prediction matrix must be square and have at least 3 columns');for(a=0;a<n-1;a++)for(u=a+1;u<i;u++)s.push({pred:t[a][u],targ:e[a][u]})}o?s.sort(((t,e)=>t.pred-e.pred)):s.sort(((t,e)=>e.pred-t.pred));const h=this.cutoffs=[o?Number.MIN_VALUE:Number.MAX_VALUE],c=this.fp=[0],l=this.tp=[0];var f=0,m=0,p=s[0].pred,d=0,g=0;for(a=0;a<s.length;a++)s[a].pred!==p&&(h.push(p),c.push(g),l.push(d),p=s[a].pred),s[a].targ?(f++,d++):(m++,g++);h.push(p),c.push(g),l.push(d);const v=h.length,w=this.fn=new Array(v),y=this.tn=new Array(v),b=this.nPosPred=new Array(v),x=this.nNegPred=new Array(v);for(a=0;a<v;a++)w[a]=f-l[a],y[a]=m-c[a],b[a]=l[a]+c[a],x[a]=y[a]+w[a];this.nPos=f,this.nNeg=m,this.nSamples=f+m}getMeasure(t){if("string"!=typeof t)throw new Error("No measure specified");if(!measures[t])throw new Error(`The specified measure (${t}) does not exist`);return measures[t](this)}getAURC(){const t=this.cutoffs.length,e=new Array(t),r=new Array(t);for(var n=0;n<t;n++)e[n]=this.fp[n]/this.nNeg,r[n]=this.tp[n]/this.nPos;var i=0;for(n=1;n<t;n++)i+=.5*(e[n]-e[n-1])*(r[n]+r[n-1]);return i}getAUDC(){const t=this.cutoffs.length,e=new Array(t),r=new Array(t);for(var n=0;n<t;n++)e[n]=this.fn[n]/this.nPos,r[n]=this.fp[n]/this.nNeg;var i=0;for(n=1;n<t;n++)i+=.5*(e[n]+e[n-1])*(r[n]-r[n-1]);return i}getDistribution(t){t=t||{};for(var e=this.cutoffs.length,r=t.xMin||Math.floor(100*this.cutoffs[e-1])/100,n=t.xMax||Math.ceil(100*this.cutoffs[1])/100,i=t.interval||Math.floor((n-r)/20*1e7-1)/1e7,o=[],s=[],a=[],u=[],h=[],c=this.tp[e-1],l=0,f=this.fp[e-1],m=0,p=r,d=e-1;p<=n;p+=i){for(;this.cutoffs[d]<p;)d--;o.push(p);var g=c-l-this.tp[d],v=f-m-this.fp[d];l+=g,m+=v,s.push(v),a.push(g),u.push(100-(f-this.fp[d])/f*100),h.push(100-(c-this.tp[d])/c*100)}return{xLabels:o,interValues:s,intraValues:a,interCumPercent:u,intraCumPercent:h}}}Performance.names={acc:"Accuracy",err:"Error rate",fpr:"False positive rate",tpr:"True positive rate",fnr:"False negative rate",tnr:"True negative rate",ppv:"Positive predictive value",npv:"Negative predictive value",pcfall:"Prediction-conditioned fallout",pcmiss:"Prediction-conditioned miss",lift:"Lift value",rpp:"Rate of positive predictions",rnp:"Rate of negative predictions",threshold:"Threshold"};var src$h=Performance,hasOwn=Object.prototype.hasOwnProperty,toStr=Object.prototype.toString,isArray$4=function(t){return"function"==typeof Array.isArray?Array.isArray(t):"[object Array]"===toStr.call(t)},isPlainObject=function(t){if(!t||"[object Object]"!==toStr.call(t))return!1;var e,r=hasOwn.call(t,"constructor"),n=t.constructor&&t.constructor.prototype&&hasOwn.call(t.constructor.prototype,"isPrototypeOf");if(t.constructor&&!r&&!n)return!1;for(e in t);return void 0===e||hasOwn.call(t,e)},extend=function t(){var e,r,n,i,o,s,a=arguments[0],u=1,h=arguments.length,c=!1;for("boolean"==typeof a&&(c=a,a=arguments[1]||{},u=2),(null==a||"object"!=typeof a&&"function"!=typeof a)&&(a={});u<h;++u)if(null!=(e=arguments[u]))for(r in e)n=a[r],a!==(i=e[r])&&(c&&i&&(isPlainObject(i)||(o=isArray$4(i)))?(o?(o=!1,s=n&&isArray$4(n)?n:[]):s=n&&isPlainObject(n)?n:{},a[r]=t(c,s,i)):void 0!==i&&(a[r]=i));return a},defaultOptions$o={size:1,value:0};function arrayCase(t,e){var r=t.length;"number"==typeof e.size&&(e.size=[e.size,e.size]);var n,i,o=r+e.size[0]+e.size[1];if(e.output){if(e.output.length!==o)throw new RangeError("Wrong output size");n=e.output}else n=new Array(o);if("circular"===e.value)for(i=0;i<o;i++)i<e.size[0]?n[i]=t[(r-e.size[0]%r+i)%r]:i<e.size[0]+r?n[i]=t[i-e.size[0]]:n[i]=t[(i-e.size[0])%r];else if("replicate"===e.value)for(i=0;i<o;i++)i<e.size[0]?n[i]=t[0]:i<e.size[0]+r?n[i]=t[i-e.size[0]]:n[i]=t[r-1];else if("symmetric"===e.value){if(e.size[0]>r||e.size[1]>r)throw new RangeError("expanded value should not be bigger than the data length");for(i=0;i<o;i++)i<e.size[0]?n[i]=t[e.size[0]-1-i]:i<e.size[0]+r?n[i]=t[i-e.size[0]]:n[i]=t[2*r+e.size[0]-i-1]}else for(i=0;i<o;i++)i<e.size[0]?n[i]=e.value:i<e.size[0]+r?n[i]=t[i-e.size[0]]:n[i]=e.value;return n}function matrixCase(t,e){t.length,t[0].length;throw void 0===e.size[0]&&(e.size=[e.size,e.size,e.size,e.size]),new Error("matrix not supported yet, sorry")}function padArray(t,e){if(e=extend({},defaultOptions$o,e),Array.isArray(t))return Array.isArray(t[0])?matrixCase(t,e):arrayCase(t,e);throw new TypeError("data should be an array")}var src$i=padArray,Matrix$9=require$$0$3.Matrix,inverse$4=require$$0$3.inverse,defaultOptions$p={windowSize:5,derivative:1,polynomial:2,pad:"none",padValue:"replicate"};function SavitzkyGolay(t,e,r){if((r=extend({},defaultOptions$p,r)).windowSize%2==0||r.windowSize<5||!Number.isInteger(r.windowSize))throw new RangeError("Invalid window size (should be odd and at least 5 integer number)");if(r.derivative<0||!Number.isInteger(r.derivative))throw new RangeError("Derivative should be a positive integer");if(r.polynomial<1||!Number.isInteger(r.polynomial))throw new RangeError("Polynomial should be a positive integer");var n,i,o=Math.floor(r.windowSize/2);"pre"===r.pad&&(t=src$i(t,{size:o,value:r.padValue}));var s=new Array(t.length-2*o);if(5!==r.windowSize||2!==r.polynomial||1!==r.derivative&&2!==r.derivative){for(var a=Matrix$9.ones(r.windowSize,r.polynomial+1),u=-(r.windowSize-1)/2,h=0;h<a.length;h++)for(var c=0;c<a[h].length;c++)u+1===0&&0===c||(a[h][c]=Math.pow(u+h,c));var l=a.transposeView();n=(n=inverse$4(l.mmul(a)).mmul(l))[r.derivative],i=1}else 1===r.derivative?(n=[-2,-1,0,1,2],i=10):(n=[2,-1,-2,-1,2],i=7);for(var f=i*Math.pow(e,r.derivative),m=o;m<t.length-o;m++){for(var p=0,d=0;d<n.length;d++)p+=n[d]*t[d+m-o]/f;s[m-o]=p}return"post"===r.pad&&(s=src$i(s,{size:o,value:r.padValue})),s}var src$j=SavitzkyGolay,defaultOptions$q={windowSize:9,derivative:0,polynomial:3};function SavitzkyGolay$1(t,e,r){if((r=extend({},defaultOptions$q,r)).windowSize%2==0||r.windowSize<5||!Number.isInteger(r.windowSize))throw new RangeError("Invalid window size (should be odd and at least 5 integer number)");if(r.windowSize>t.length)throw new RangeError("Window size is higher than the data length "+r.windowSize+">"+t.length);if(r.derivative<0||!Number.isInteger(r.derivative))throw new RangeError("Derivative should be a positive integer");if(r.polynomial<1||!Number.isInteger(r.polynomial))throw new RangeError("Polynomial should be a positive integer");r.polynomial>=6&&console.warn("You should not use polynomial grade higher than 5 if you are not sure that your data arises from such a model. Possible polynomial oscillation problems");var n=r.windowSize,i=Math.floor(n/2),o=t.length,s=new Array(o),a=fullWeights(n,r.polynomial,r.derivative),u=0,h=!0;"[object Array]"===Object.prototype.toString.call(e)?h=!1:u=Math.pow(e,r.derivative);for(var c=0;c<i;c++){for(var l=a[i-c-1],f=a[i+c+1],m=0,p=0,d=0;d<n;d++)m+=l[d]*t[d],p+=f[d]*t[o-n+d-1];h?(s[i-c-1]=m/u,s[o-i+c]=p/u):(u=getHs(e,i-c-1,i,r.derivative),s[i-c-1]=m/u,u=getHs(e,o-i+c,i,r.derivative),s[o-i+c]=p/u)}var g=a[i];for(c=n;c<o+1;c++){var v=0;for(d=0;d<n;d++)v+=g[d]*t[d+c-n];h||(u=getHs(e,c-i-1,i,r.derivative)),s[c-i-1]=v/u}return s}function getHs(t,e,r,n){for(var i=0,o=0,s=e-r;s<e+r;s++)s>=0&&s<t.length-1&&(i+=t[s+1]-t[s],o++);return Math.pow(i/o,n)}function GramPoly(t,e,r,n){return r>0?(4*r-2)/(r*(2*e-r+1))*(t*GramPoly(t,e,r-1,n)+n*GramPoly(t,e,r-1,n-1))-(r-1)*(2*e+r)/(r*(2*e-r+1))*GramPoly(t,e,r-2,n):0==r&&0==n?1:0}function GenFact(t,e){var r=1;if(t>=e)for(var n=t-e+1;n<=t;n++)r*=n;return r}function Weight(t,e,r,n,i){for(var o=0,s=0;s<=n;s++)o+=(2*s+1)*(GenFact(2*r,s)/GenFact(2*r+s+1,s+1))*GramPoly(t,r,s,0)*GramPoly(e,r,s,i);return o}function fullWeights(t,e,r){for(var n=new Array(t),i=Math.floor(t/2),o=-i;o<=i;o++){n[o+i]=new Array(t);for(var s=-i;s<=i;s++)n[o+i][s+i]=Weight(s,o,i,e,r)}return n}for(var src$k=SavitzkyGolay$1,ans=new Array(256),i=0;i<256;i++){for(var num=i,c=0;num;)num&=num-1,c++;ans[i]=c}var creator=ans;function count(t){for(var e=0,r=0;r<t.length;r++)e+=creator[255&t[r]]+creator[t[r]>>8&255]+creator[t[r]>>16&255]+creator[t[r]>>24&255];return e}function and(t,e){for(var r=new Array(t.length),n=0;n<t.length;n++)r[n]=t[n]&e[n];return r}function or(t,e){for(var r=new Array(t.length),n=0;n<t.length;n++)r[n]=t[n]|e[n];return r}function xor(t,e){for(var r=new Array(t.length),n=0;n<t.length;n++)r[n]=t[n]^e[n];return r}function not(t){for(var e=new Array(t.length),r=0;r<e.length;r++)e[r]=~t[r];return e}function getBit(t,e){var r=1<<31-e%32;return Boolean(t[e>>5]&r)}function setBit(t,e,r){var 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src$l={count:count,and:and,or:or,xor:xor,not:not,getBit:getBit,setBit:setBit,toBinaryString:toBinaryString,parseBinaryString:parseBinaryString,toHexString:toHexString,parseHexString:parseHexString,toDebug:toDebug};const Stat=mlStat.array;function coordArrayToPoints(t,e){if(t.length%e!=0)throw new RangeError("Dimensions number must be accordance with the size of the array.");for(var r=t.length/e,n=new Array(r),i=0,o=0;o<t.length;o+=e){for(var s=new Array(e),a=0;a<e;++a)s[a]=t[o+a];n[i]=s,i++}return n}function coordArrayToCoordMatrix(t,e){if(t.length%e!=0)throw new RangeError("Dimensions number must be accordance with the size of the array.");for(var r=new Array(e),n=t.length/e,i=0;i<r.length;i++)r[i]=new Array(n);for(i=0;i<t.length;i+=e)for(var o=0;o<e;++o){var s=Math.floor(i/e);r[o][s]=t[i+o]}return r}function coordMatrixToCoordArray(t){for(var e=new Array(t.length*t[0].length),r=0,n=0;n<t[0].length;++n)for(var i=0;i<t.length;++i)e[r]=t[i][n],++r;return e}function transpose(t){for(var 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ArrayUtils={coordArrayToPoints:coordArrayToPoints,coordArrayToCoordMatrix:coordArrayToCoordMatrix,coordMatrixToCoordArray:coordMatrixToCoordArray,coordMatrixToPoints:transpose,pointsToCoordArray:pointsToCoordArray,pointsToCoordMatrix:transpose,applyDotProduct:applyDotProduct,scale:scale};function getEquallySpacedData(t,e,r={}){var n=t.length;t.length>1&&t[0]>t[1]&&(t=t.slice().reverse(),e=e.slice().reverse());var{from:i=t[0],to:o=t[n-1],variant:s="smooth",numberOfPoints:a=100}=r;if(n!==e.length)throw new RangeError("the x and y vector doesn't have the same size.");if("number"!=typeof i||isNaN(i))throw new RangeError("'from' option must be a number");if("number"!=typeof o||isNaN(o))throw new RangeError("'to' option must be a number");var u=i>o;if(u&&([i,o]=[o,i]),"number"!=typeof a||isNaN(a))throw new RangeError("'numberOfPoints' option must be a number");if(a<1)throw new RangeError("the number of points must be at least 1");var h="slot"===s?getEquallySpacedSlot(t,e,i,o,a):getEquallySpacedSmooth(t,e,i,o,a);return u?h.reverse():h}function getEquallySpacedSmooth(t,e,r,n,i){var o=t.length,s=(n-r)/(i-1),a=s/2,u=new Array(i),h=t[1]-t[0],c=t[o-1]-t[o-2],l=r-a,f=r+a,m=Number.MIN_VALUE,p=0,d=t[0]-h,g=0,v=0,w=0,y=0,b=0,x=0,M=0,_=0;t:for(;;){for(m<=l&&l<=d&&(b=v+($=integral(0,l-m,w,p)));d-f>=0;){var $=integral(0,f-m,w,p);if(x=v+$,u[_++]=(x-b)/s,_===i)break t;l=f,f+=s,b=x}v+=integral(m,d,w,y),m=d,p=g,M<o?(d=t[M],g=e[M],M++):M===o&&(d+=c,g=0),y=-(w=(g-p)/(d-m))*m+p}return u}function getEquallySpacedSlot(t,e,r,n,i){var o=t.length,s=(n-r)/(i-1),a=s/2,u=t[t.length-1]-t[t.length-2],h=r-a,c=new Array(i),l=h,f=h+s,m=-Number.MAX_VALUE,p=0,d=t[0],g=e[0],v=0,w=!0,y=0,b=0,x=1,M=0;t:for(;;){if(m>=d)throw new Error("x must be an increasing serie");for(;m-f>0;){if(w&&(b++,w=!1),c[M]=b<=0?0:y/b,++M===i)break t;l=f,f+=s,y=0,b=0}m>l&&(y+=p,b++),(m===-Number.MAX_VALUE||v>1)&&b--,m=d,p=g,x<o?(d=t[x],g=e[x],x++):(d+=u,g=0,v++)}return c}function integral(t,e,r,n){return.5*r*e*e+n*e-(.5*r*t*t+n*t)}var getEquallySpacedData_1=getEquallySpacedData,integral_1=integral,getEquallySpaced={getEquallySpacedData:getEquallySpacedData_1,integral:integral_1},SNV_1=SNV,Stat$1=mlStat.array;function SNV(t){for(var e=Stat$1.mean(t),r=Stat$1.standardDeviation(t),n=t.slice(),i=0;i<t.length;i++)n[i]=(n[i]-e)/r;return n}var snv={SNV:SNV_1},src$m=createCommonjsModule((function(t,e){t.exports=e=ArrayUtils,e.getEquallySpacedData=getEquallySpaced.getEquallySpacedData,e.SNV=snv.SNV})),src_1$2=src$m.getEquallySpacedData,src_2$2=src$m.SNV,require$$5=src$7&&KNN||src$7,src$n=createCommonjsModule((function(t,e){const 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isNaN(e)&&r?e:isNaN(e)&&!1===r?isNaN(o)?t:o:e},h=t.map(u).map((t=>isNaN(t)?e:t));return{components:{average:i,standard_dev:o,maximum:s,minimum:a},scale:u,descale:t=>{const e=t*(s-a)+i;return isNaN(e)&&r?e:isNaN(e)&&!1===r?isNaN(o)?t:o:e},values:h}}function approximateZPercentile(t,e=!0){if(t<-6.5)return 0;if(t>6.5)return 1;let r=1,n=0,i=1,o=0,s=Math.exp(-23);for(;Math.abs(i)>s;)i=.3989422804*Math.pow(-1,o)*Math.pow(t,o)/(2*o+1)/Math.pow(2,o)*Math.pow(t,o+1)/r,n+=i,o++,r*=o;return n+=.5,e?1-n:n}function getSafePropertyName(t){return t.replace(/[^\w\s]/gi,"_")}function forecastErrors(t,e){if(t.length!==e.length)throw new Error(`Actuals length (${t.length}) must equal Estimates length (${e.length})`);return t.map(((t,r)=>t-e[r]))}function meanForecastError(t,e){const r=forecastErrors(t,e);return avg$2(r)}function meanAbsoluteDeviation(t,e){const r=forecastErrors(t,e).map((t=>Math.abs(t)));return avg$2(r)}function trackingSignal(t,e){return 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fpnode=createCommonjsModule((function(t,e){Object.defineProperty(e,"__esModule",{value:!0});var r=function(){function t(t,e){void 0===t&&(t=null),void 0===e&&(e=null),this.item=t,this.parent=e,this.support=1,this.nextSameItemNode=null,this._children=[]}return Object.defineProperty(t.prototype,"children",{get:function(){return this._children},enumerable:!0,configurable:!0}),t.prototype.upsertChild=function(e,r,n){void 0===n&&(n=1);var i=this.getChild(e);return i?i.support+=n:((i=new t(e,this)).support=n,this._children.push(i),r&&r(i)),i},t.prototype.getChild=function(t){return this._children.find((function(e){return e.item==t}))},t}();e.FPNode=r}));unwrapExports(fpnode);var fpnode_1=fpnode.FPNode,fptree=createCommonjsModule((function(t,e){Object.defineProperty(e,"__esModule",{value:!0});var r=function(){function t(t,e){this.supports=t,this._support=e,this._isInit=!1,this.root=new fpnode.FPNode,this._firstInserted={},this._lastInserted={}}return 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t=this._v(t,"r"),e=this._v(e,"r",0),0===(r=this._v(r,"nn",1))?t===e?1/0:0:1/(r*Math.sqrt(2*PI))*exp(-(t-e)*(t-e)/(2*r*r))},rnorm:function(t,e,r){t=this._v(t,"n"),e=this._v(e,"r",0),r=this._v(r,"nn",1);for(var n=[],i=0;i<t;i++){var o,s,a,u;do{a=(o=2*this.prng()-1)*o+(s=2*this.prng()-1)*s}while(a>1);u=e+r*(u=Math.sqrt(-2*ln(a)/a)*o),n.push(u)}return n},dpois:function(t,e){return t=this._v(t,"nni"),0===(e=this._v(e,"nn"))?0===t?1:0:pow(e,t)*exp(-e)/this._factorial(t)},rpois:function(t,e){t=this._v(t,"n"),e=this._v(e,"pos");for(var r=[],n=0;n<t;n++)if(e<30){var i=exp(-e),o=1,s=0;do{s++,o*=this.prng()}while(o>i);r.push(s-1)}else{o=e/1e4,s=0;for(var a=0;a<1e4;a++)this.prng()<o&&s++;r[n]=s}return r},dunif:function(t,e,r){if(t=this._v(t,"r"),(e=this._v(e,"r",0))>(r=this._v(r,"r",1)))throw new Error("Minimum value cannot be greater than maximum value");return t<e||t>r?0:e===r?1/0:1/(r-e)},runif:function(t,e,r){if(t=this._v(t,"n"),(e=this._v(e,"r",0))>(r=this._v(r,"r",1)))throw new Error("Minimum value cannot be greater than maximum value");for(var n=[],i=0;i<t;i++){var o=e+this.prng()*(r-e);n.push(o)}return n},rword:function(t,e){t=this._v(t,"n");var r=(e=this._v(e,"str","abcdefghijklmnopqrstuvwxyz")).split("");return this.sample(r,t,!0).join("")},sample:function(t,e,r,n){if(t=this._v(t,"a"),e=this._v(e,"n",t.length),void 0===r&&(r=!1),!r&&t.length<e)throw new Error("You cannot select "+e+" items from an array of length "+t.length+" without replacement");if(void 0===n){n=[];for(var i=0;i<t.length;i++)n[i]=1}for(var o=this._getCumulativeProbs(n,t.length),s=[],a=0;a<e;a++){var u=this._sampleOneIndex(o);r?s[a]=t[u]:(s[a]=t.splice(u,1)[0],n.splice(u,1),n.length&&(o=this._getCumulativeProbs(n,t.length)))}return s},visualize:function(data,domID,options){var defaultOptions={lag:1e3,blank:"",inf:"&infin;",loop:!0,conditions:"",arrivalTimes:!1,arrivalSymbol:'<span class="pd-arrival">&#8226;</span>',arrivalFlashTime:.25,significantDigits:0};for(var property in void 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update=function(){elem.innerHTML=format(data[i]),++i===len&&(i=0),options.loop||0!==i?setTimeout(update,options.lag):setTimeout((function(){elem.innerHTML=options.blank}),options.lag)};update()}},_getCumulativeProbs:function(t,e){if(void 0===e)throw new Error("An error occurred: len was not sent to _getCumulativeProbs");if(t.length!==e)throw new Error("Probabilities for sample must be same length as the array to sample from");var r=[];if(void 0!==t){if((t=this._v(t,"a")).length!==e)throw new Error("Probabilities array must be the same length as the array you are sampling from");var n=0;t.map(function(t){t=this._v(t,"nn"),n+=t,r.push(n)}.bind(this));for(var i=0;i<r.length;i++)r[i]=r[i]/n;return r}},_sampleOneIndex:function(t){for(var e=this.prng(),r=0;e>t[r];)r++;return r},_factorial:function(t){for(var e=1,r=2;r<=t;r++)e*=r;return e},_v:function(t,e,r){if(null==t&&null!=r)return r;switch(e){case"a":if(!Array.isArray(t)||!t.length)throw new Error("Expected an array of length 1 or 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long");return t}},rfml:function(t,e,r,n,i){t=this._v(t,"n"),e=this._v(e,"nni",1),void 0===r&&(r=this.prng),n=this._v(n,"n",1e4),void 0===i&&(i={});for(var o=[],s=0;s<t;s++){var a=0,u=e,h=r();if(0===e)o[s]=0;else{do{this.prng()<h?(u++,i[String(s)+"_"+String(a)]={problems:u,p:h,result:1}):(u--,i[String(s)+"_"+String(a)]={problems:u,p:h,result:-1}),a++}while(u>0&&a<n);a===n&&(a=-1),o[s]=a}}return o},ruf:function(t){t=this._v(t,"n");for(var e=[],r=0;r<t;r++)e[r]=this.rexp(1,this.prng())[0];return e}},probabilityDistributions_1=probabilityDistributions.prng,probabilityDistributions_2=probabilityDistributions.rbeta,probabilityDistributions_3=probabilityDistributions.rbinom,probabilityDistributions_4=probabilityDistributions.rcauchy,probabilityDistributions_5=probabilityDistributions.rchisq,probabilityDistributions_6=probabilityDistributions.dexp,probabilityDistributions_7=probabilityDistributions.rexp,probabilityDistributions_8=probabilityDistributions.rf,probabilityDistributions_9=probabilityDistributions.rgamma,probabilityDistributions_10=probabilityDistributions.rint,probabilityDistributions_11=probabilityDistributions.rlaplace,probabilityDistributions_12=probabilityDistributions.rlnorm,probabilityDistributions_13=probabilityDistributions.rnbinom,probabilityDistributions_14=probabilityDistributions.dnorm,probabilityDistributions_15=probabilityDistributions.rnorm,probabilityDistributions_16=probabilityDistributions.dpois,probabilityDistributions_17=probabilityDistributions.rpois,probabilityDistributions_18=probabilityDistributions.dunif,probabilityDistributions_19=probabilityDistributions.runif,probabilityDistributions_20=probabilityDistributions.rword,probabilityDistributions_21=probabilityDistributions.sample,probabilityDistributions_22=probabilityDistributions.visualize,probabilityDistributions_23=probabilityDistributions._getCumulativeProbs,probabilityDistributions_24=probabilityDistributions._sampleOneIndex,probabilityDistributions_25=probabilityDistributions._factorial,probabilityDistributions_26=probabilityDistributions._v,probabilityDistributions_27=probabilityDistributions.rfml,probabilityDistributions_28=probabilityDistributions.ruf,probabilty=Object.freeze({default:probabilityDistributions,__moduleExports:probabilityDistributions,prng:probabilityDistributions_1,rbeta:probabilityDistributions_2,rbinom:probabilityDistributions_3,rcauchy:probabilityDistributions_4,rchisq:probabilityDistributions_5,dexp:probabilityDistributions_6,rexp:probabilityDistributions_7,rf:probabilityDistributions_8,rgamma:probabilityDistributions_9,rint:probabilityDistributions_10,rlaplace:probabilityDistributions_11,rlnorm:probabilityDistributions_12,rnbinom:probabilityDistributions_13,dnorm:probabilityDistributions_14,rnorm:probabilityDistributions_15,dpois:probabilityDistributions_16,rpois:probabilityDistributions_17,dunif:probabilityDistributions_18,runif:probabilityDistributions_19,rword:probabilityDistributions_20,sample:probabilityDistributions_21,visualize:probabilityDistributions_22,_getCumulativeProbs:probabilityDistributions_23,_sampleOneIndex:probabilityDistributions_24,_factorial:probabilityDistributions_25,_v:probabilityDistributions_26,rfml:probabilityDistributions_27,ruf:probabilityDistributions_28});const PD=Object.assign({},probabilty);Symbol.species||(Symbol.species=Symbol.for("@@species"));class LuDecomposition$$1{constructor(t){var e,r,n,i,o,s,a,u,h,c=(t=WrapperMatrix2D$4.checkMatrix(t)).clone(),l=c.rows,f=c.columns,m=new Array(l),p=1;for(e=0;e<l;e++)m[e]=e;for(u=new Array(l),r=0;r<f;r++){for(e=0;e<l;e++)u[e]=c.get(e,r);for(e=0;e<l;e++){for(h=Math.min(e,r),o=0,n=0;n<h;n++)o+=c.get(e,n)*u[n];u[e]-=o,c.set(e,r,u[e])}for(i=r,e=r+1;e<l;e++)Math.abs(u[e])>Math.abs(u[i])&&(i=e);if(i!==r){for(n=0;n<f;n++)s=c.get(i,n),c.set(i,n,c.get(r,n)),c.set(r,n,s);a=m[i],m[i]=m[r],m[r]=a,p=-p}if(r<l&&0!==c.get(r,r))for(e=r+1;e<l;e++)c.set(e,r,c.get(e,r)/c.get(r,r))}this.LU=c,this.pivotVector=m,this.pivotSign=p}isSingular(){for(var t=this.LU,e=t.columns,r=0;r<e;r++)if(0===t[r][r])return!0;return!1}solve(t){t=Matrix$a.checkMatrix(t);var e=this.LU;if(e.rows!==t.rows)throw new Error("Invalid matrix dimensions");if(this.isSingular())throw new Error("LU matrix is singular");var r,n,i,o=t.columns,s=t.subMatrixRow(this.pivotVector,0,o-1),a=e.columns;for(i=0;i<a;i++)for(r=i+1;r<a;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i];for(i=a-1;i>=0;i--){for(n=0;n<o;n++)s[i][n]/=e[i][i];for(r=0;r<i;r++)for(n=0;n<o;n++)s[r][n]-=s[i][n]*e[r][i]}return s}get determinant(){var t=this.LU;if(!t.isSquare())throw new Error("Matrix must be square");for(var e=this.pivotSign,r=t.columns,n=0;n<r;n++)e*=t[n][n];return e}get lowerTriangularMatrix(){for(var t=this.LU,e=t.rows,r=t.columns,n=new Matrix$a(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i>o?t[i][o]:i===o?1:0;return n}get upperTriangularMatrix(){for(var t=this.LU,e=t.rows,r=t.columns,n=new Matrix$a(e,r),i=0;i<e;i++)for(var o=0;o<r;o++)n[i][o]=i<=o?t[i][o]:0;return n}get pivotPermutationVector(){return this.pivotVector.slice()}}function hypotenuse$4(t,e){var r=0;return Math.abs(t)>Math.abs(e)?(r=e/t,Math.abs(t)*Math.sqrt(1+r*r)):0!==e?(r=t/e,Math.abs(e)*Math.sqrt(1+r*r)):0}function getFilled2DArray$4(t,e,r){for(var n=new Array(t),i=0;i<t;i++){n[i]=new Array(e);for(var o=0;o<e;o++)n[i][o]=r}return n}class SingularValueDecomposition$$1{constructor(t,e={}){var r=(t=WrapperMatrix2D$4.checkMatrix(t)).rows,n=t.columns,i=Math.min(r,n);const{computeLeftSingularVectors:o=!0,computeRightSingularVectors:s=!0,autoTranspose:a=!1}=e;var u,h=Boolean(o),c=Boolean(s),l=!1;if(r<n)if(a){r=(u=t.transpose()).rows,n=u.columns,l=!0;var f=h;h=c,c=f}else u=t.clone(),console.warn("Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose");else u=t.clone();var m,p,d,g,v,w,y,b,x,M,_,$,S,R,E,C,k,A,T,O,I,D=new Array(Math.min(r+1,n)),P=getFilled2DArray$4(r,i,0),V=getFilled2DArray$4(n,n,0),j=new Array(n),L=new Array(r),N=Math.min(r-1,n),B=Math.max(0,Math.min(n-2,r));for(d=0,M=Math.max(N,B);d<M;d++){if(d<N){for(D[d]=0,m=d;m<r;m++)D[d]=hypotenuse$4(D[d],u[m][d]);if(0!==D[d]){for(u[d][d]<0&&(D[d]=-D[d]),m=d;m<r;m++)u[m][d]/=D[d];u[d][d]+=1}D[d]=-D[d]}for(p=d+1;p<n;p++){if(d<N&&0!==D[d]){for(v=0,m=d;m<r;m++)v+=u[m][d]*u[m][p];for(v=-v/u[d][d],m=d;m<r;m++)u[m][p]+=v*u[m][d]}j[p]=u[d][p]}if(h&&d<N)for(m=d;m<r;m++)P[m][d]=u[m][d];if(d<B){for(j[d]=0,m=d+1;m<n;m++)j[d]=hypotenuse$4(j[d],j[m]);if(0!==j[d]){for(j[d+1]<0&&(j[d]=0-j[d]),m=d+1;m<n;m++)j[m]/=j[d];j[d+1]+=1}if(j[d]=-j[d],d+1<r&&0!==j[d]){for(m=d+1;m<r;m++)L[m]=0;for(p=d+1;p<n;p++)for(m=d+1;m<r;m++)L[m]+=j[p]*u[m][p];for(p=d+1;p<n;p++)for(v=-j[p]/j[d+1],m=d+1;m<r;m++)u[m][p]+=v*L[m]}if(c)for(m=d+1;m<n;m++)V[m][d]=j[m]}}if(g=Math.min(n,r+1),N<n&&(D[N]=u[N][N]),r<g&&(D[g-1]=0),B+1<g&&(j[B]=u[B][g-1]),j[g-1]=0,h){for(p=N;p<i;p++){for(m=0;m<r;m++)P[m][p]=0;P[p][p]=1}for(d=N-1;d>=0;d--)if(0!==D[d]){for(p=d+1;p<i;p++){for(v=0,m=d;m<r;m++)v+=P[m][d]*P[m][p];for(v=-v/P[d][d],m=d;m<r;m++)P[m][p]+=v*P[m][d]}for(m=d;m<r;m++)P[m][d]=-P[m][d];for(P[d][d]=1+P[d][d],m=0;m<d-1;m++)P[m][d]=0}else{for(m=0;m<r;m++)P[m][d]=0;P[d][d]=1}}if(c)for(d=n-1;d>=0;d--){if(d<B&&0!==j[d])for(p=d+1;p<n;p++){for(v=0,m=d+1;m<n;m++)v+=V[m][d]*V[m][p];for(v=-v/V[d+1][d],m=d+1;m<n;m++)V[m][p]+=v*V[m][d]}for(m=0;m<n;m++)V[m][d]=0;V[d][d]=1}for(var F=g-1,z=Number.EPSILON;g>0;){for(d=g-2;d>=-1&&-1!==d;d--)if(Math.abs(j[d])<=z*(Math.abs(D[d])+Math.abs(D[d+1]))){j[d]=0;break}if(d===g-2)_=4;else{for(w=g-1;w>=d&&w!==d;w--)if(v=(w!==g?Math.abs(j[w]):0)+(w!==d+1?Math.abs(j[w-1]):0),Math.abs(D[w])<=z*v){D[w]=0;break}w===d?_=3:w===g-1?_=1:(_=2,d=w)}switch(d++,_){case 1:for(y=j[g-2],j[g-2]=0,p=g-2;p>=d;p--)if(v=hypotenuse$4(D[p],y),b=D[p]/v,x=y/v,D[p]=v,p!==d&&(y=-x*j[p-1],j[p-1]=b*j[p-1]),c)for(m=0;m<n;m++)v=b*V[m][p]+x*V[m][g-1],V[m][g-1]=-x*V[m][p]+b*V[m][g-1],V[m][p]=v;break;case 2:for(y=j[d-1],j[d-1]=0,p=d;p<g;p++)if(v=hypotenuse$4(D[p],y),b=D[p]/v,x=y/v,D[p]=v,y=-x*j[p],j[p]=b*j[p],h)for(m=0;m<r;m++)v=b*P[m][p]+x*P[m][d-1],P[m][d-1]=-x*P[m][p]+b*P[m][d-1],P[m][p]=v;break;case 3:for($=Math.max(Math.abs(D[g-1]),Math.abs(D[g-2]),Math.abs(j[g-2]),Math.abs(D[d]),Math.abs(j[d])),S=D[g-1]/$,R=D[g-2]/$,E=j[g-2]/$,C=D[d]/$,k=j[d]/$,T=S*E*(S*E),O=0,0===(A=((R+S)*(R-S)+E*E)/2)&&0===T||(O=Math.sqrt(A*A+T),A<0&&(O=-O),O=T/(A+O)),y=(C+S)*(C-S)+O,I=C*k,p=d;p<g-1;p++){if(b=y/(v=hypotenuse$4(y,I)),x=I/v,p!==d&&(j[p-1]=v),y=b*D[p]+x*j[p],j[p]=b*j[p]-x*D[p],I=x*D[p+1],D[p+1]=b*D[p+1],c)for(m=0;m<n;m++)v=b*V[m][p]+x*V[m][p+1],V[m][p+1]=-x*V[m][p]+b*V[m][p+1],V[m][p]=v;if(b=y/(v=hypotenuse$4(y,I)),x=I/v,D[p]=v,y=b*j[p]+x*D[p+1],D[p+1]=-x*j[p]+b*D[p+1],I=x*j[p+1],j[p+1]=b*j[p+1],h&&p<r-1)for(m=0;m<r;m++)v=b*P[m][p]+x*P[m][p+1],P[m][p+1]=-x*P[m][p]+b*P[m][p+1],P[m][p]=v}j[g-2]=y;break;case 4:if(D[d]<=0&&(D[d]=D[d]<0?-D[d]:0,c))for(m=0;m<=F;m++)V[m][d]=-V[m][d];for(;d<F&&!(D[d]>=D[d+1]);){if(v=D[d],D[d]=D[d+1],D[d+1]=v,c&&d<n-1)for(m=0;m<n;m++)v=V[m][d+1],V[m][d+1]=V[m][d],V[m][d]=v;if(h&&d<r-1)for(m=0;m<r;m++)v=P[m][d+1],P[m][d+1]=P[m][d],P[m][d]=v;d++}g--}}if(l){var q=V;V=P,P=q}this.m=r,this.n=n,this.s=D,this.U=P,this.V=V}solve(t){var e,r=t,n=this.threshold,i=this.s.length,o=Matrix$a.zeros(i,i);for(e=0;e<i;e++)Math.abs(this.s[e])<=n?o[e][e]=0:o[e][e]=1/this.s[e];var s,a,u,h=this.U,c=this.rightSingularVectors,l=c.mmul(o),f=c.rows,m=h.length,p=Matrix$a.zeros(f,m);for(e=0;e<f;e++)for(s=0;s<m;s++){for(u=0,a=0;a<i;a++)u+=l[e][a]*h[s][a];p[e][s]=u}return p.mmul(r)}solveForDiagonal(t){return this.solve(Matrix$a.diag(t))}inverse(){var t,e,r=this.V,n=this.threshold,i=r.length,o=r[0].length,s=new Matrix$a(i,this.s.length);for(t=0;t<i;t++)for(e=0;e<o;e++)Math.abs(this.s[e])>n?s[t][e]=r[t][e]/this.s[e]:s[t][e]=0;var a,u,h=this.U,c=h.length,l=h[0].length,f=new Matrix$a(i,c);for(t=0;t<i;t++)for(e=0;e<c;e++){for(u=0,a=0;a<l;a++)u+=s[t][a]*h[e][a];f[t][e]=u}return f}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 Matrix$a.isMatrix(this.U)||(this.U=new Matrix$a(this.U)),this.U}get rightSingularVectors(){return Matrix$a.isMatrix(this.V)||(this.V=new Matrix$a(this.V)),this.V}get diagonalMatrix(){return Matrix$a.diag(this.s)}}function checkRowIndex$4(t,e,r){var n=r?t.rows:t.rows-1;if(e<0||e>n)throw new RangeError("Row index out of range")}function checkColumnIndex$4(t,e,r){var n=r?t.columns:t.columns-1;if(e<0||e>n)throw new RangeError("Column index out of range")}function checkRowVector$4(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.columns)throw new RangeError("vector size must be the same as the number of columns");return e}function checkColumnVector$4(t,e){if(e.to1DArray&&(e=e.to1DArray()),e.length!==t.rows)throw new RangeError("vector size must be the same as the number of rows");return e}function checkIndices$4(t,e,r){return{row:checkRowIndices$4(t,e),column:checkColumnIndices$4(t,r)}}function checkRowIndices$4(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for row indices");if(e.some((e=>e<0||e>=t.rows)))throw new RangeError("row indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkColumnIndices$4(t,e){if("object"!=typeof e)throw new TypeError("unexpected type for column indices");var r=e.some((e=>e<0||e>=t.columns));if(r)throw new RangeError("column indices are out of range");return Array.isArray(e)||(e=Array.from(e)),e}function checkRange$4(t,e,r,n,i){if(5!==arguments.length)throw new TypeError("Invalid argument type");if(Array.from(arguments).slice(1).some((function(t){return"number"!=typeof t})))throw new TypeError("Invalid argument type");if(e>r||n>i||e<0||e>=t.rows||r<0||r>=t.rows||n<0||n>=t.columns||i<0||i>=t.columns)throw new RangeError("Submatrix indices are out of range")}function sumByRow$4(t){for(var e=Matrix$a.zeros(t.rows,1),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(r,0,e.get(r,0)+t.get(r,n));return e}function sumByColumn$4(t){for(var e=Matrix$a.zeros(1,t.columns),r=0;r<t.rows;++r)for(var n=0;n<t.columns;++n)e.set(0,n,e.get(0,n)+t.get(r,n));return e}function sumAll$4(t){for(var e=0,r=0;r<t.rows;r++)for(var n=0;n<t.columns;n++)e+=t.get(r,n);return e}class BaseView$4 extends(AbstractMatrix$4()){constructor(t,e,r){super(),this.matrix=t,this.rows=e,this.columns=r}static get[Symbol.species](){return Matrix$a}}class MatrixTransposeView$4 extends BaseView$4{constructor(t){super(t,t.columns,t.rows)}set(t,e,r){return this.matrix.set(e,t,r),this}get(t,e){return this.matrix.get(e,t)}}class MatrixRowView$4 extends BaseView$4{constructor(t,e){super(t,1,t.columns),this.row=e}set(t,e,r){return this.matrix.set(this.row,e,r),this}get(t,e){return this.matrix.get(this.row,e)}}class MatrixSubView$4 extends BaseView$4{constructor(t,e,r,n,i){checkRange$4(t,e,r,n,i),super(t,r-e+1,i-n+1),this.startRow=e,this.startColumn=n}set(t,e,r){return this.matrix.set(this.startRow+t,this.startColumn+e,r),this}get(t,e){return this.matrix.get(this.startRow+t,this.startColumn+e)}}class MatrixSelectionView$4 extends BaseView$4{constructor(t,e,r){var n=checkIndices$4(t,e,r);super(t,n.row.length,n.column.length),this.rowIndices=n.row,this.columnIndices=n.column}set(t,e,r){return this.matrix.set(this.rowIndices[t],this.columnIndices[e],r),this}get(t,e){return this.matrix.get(this.rowIndices[t],this.columnIndices[e])}}class MatrixRowSelectionView$4 extends BaseView$4{constructor(t,e){super(t,(e=checkRowIndices$4(t,e)).length,t.columns),this.rowIndices=e}set(t,e,r){return this.matrix.set(this.rowIndices[t],e,r),this}get(t,e){return this.matrix.get(this.rowIndices[t],e)}}class MatrixColumnSelectionView$4 extends BaseView$4{constructor(t,e){e=checkColumnIndices$4(t,e),super(t,t.rows,e.length),this.columnIndices=e}set(t,e,r){return this.matrix.set(t,this.columnIndices[e],r),this}get(t,e){return this.matrix.get(t,this.columnIndices[e])}}class MatrixColumnView$4 extends BaseView$4{constructor(t,e){super(t,t.rows,1),this.column=e}set(t,e,r){return this.matrix.set(t,this.column,r),this}get(t){return this.matrix.get(t,this.column)}}class MatrixFlipRowView$4 extends BaseView$4{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(this.rows-t-1,e,r),this}get(t,e){return this.matrix.get(this.rows-t-1,e)}}class MatrixFlipColumnView$4 extends BaseView$4{constructor(t){super(t,t.rows,t.columns)}set(t,e,r){return this.matrix.set(t,this.columns-e-1,r),this}get(t,e){return this.matrix.get(t,this.columns-e-1)}}function AbstractMatrix$4(t){void 0===t&&(t=Object);class e extends t{static get[Symbol.species](){return this}static from1DArray(t,e,r){if(t*e!==r.length)throw new RangeError("Data length does not match given dimensions");for(var n=new this(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r[i*e+o]);return n}static rowVector(t){for(var e=new this(1,t.length),r=0;r<t.length;r++)e.set(0,r,t[r]);return e}static columnVector(t){for(var e=new this(t.length,1),r=0;r<t.length;r++)e.set(r,0,t[r]);return e}static empty(t,e){return new this(t,e)}static zeros(t,e){return this.empty(t,e).fill(0)}static ones(t,e){return this.empty(t,e).fill(1)}static rand(t,e,r){void 0===r&&(r=Math.random);for(var n=this.empty(t,e),i=0;i<t;i++)for(var o=0;o<e;o++)n.set(i,o,r());return n}static randInt(t,e,r,n){void 0===r&&(r=1e3),void 0===n&&(n=Math.random);for(var i=this.empty(t,e),o=0;o<t;o++)for(var s=0;s<e;s++){var a=Math.floor(n()*r);i.set(o,s,a)}return i}static eye(t,e,r){void 0===e&&(e=t),void 0===r&&(r=1);for(var n=Math.min(t,e),i=this.zeros(t,e),o=0;o<n;o++)i.set(o,o,r);return i}static diag(t,e,r){var n=t.length;void 0===e&&(e=n),void 0===r&&(r=e);for(var i=Math.min(n,e,r),o=this.zeros(e,r),s=0;s<i;s++)o.set(s,s,t[s]);return o}static min(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.min(t.get(o,s),e.get(o,s)));return i}static max(t,e){t=this.checkMatrix(t),e=this.checkMatrix(e);for(var r=t.rows,n=t.columns,i=new this(r,n),o=0;o<r;o++)for(var s=0;s<n;s++)i.set(o,s,Math.max(t.get(o,s),e.get(o,s)));return i}static checkMatrix(t){return e.isMatrix(t)?t:new this(t)}static isMatrix(t){return null!=t&&"Matrix"===t.klass}get size(){return this.rows*this.columns}apply(t){if("function"!=typeof t)throw new TypeError("callback must be a function");for(var e=this.rows,r=this.columns,n=0;n<e;n++)for(var i=0;i<r;i++)t.call(this,n,i);return this}to1DArray(){for(var t=new Array(this.size),e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t[e*this.columns+r]=this.get(e,r);return t}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}isRowVector(){return 1===this.rows}isColumnVector(){return 1===this.columns}isVector(){return 1===this.rows||1===this.columns}isSquare(){return this.rows===this.columns}isSymmetric(){if(this.isSquare()){for(var t=0;t<this.rows;t++)for(var e=0;e<=t;e++)if(this.get(t,e)!==this.get(e,t))return!1;return!0}return!1}set(t,e,r){throw new Error("set method is unimplemented")}get(t,e){throw new Error("get method is unimplemented")}repeat(t,e){t=t||1,e=e||1;for(var r=new this.constructor[Symbol.species](this.rows*t,this.columns*e),n=0;n<t;n++)for(var i=0;i<e;i++)r.setSubMatrix(this,this.rows*n,this.columns*i);return r}fill(t){for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,t);return this}neg(){return this.mulS(-1)}getRow(t){checkRowIndex$4(this,t);for(var e=new Array(this.columns),r=0;r<this.columns;r++)e[r]=this.get(t,r);return e}getRowVector(t){return this.constructor.rowVector(this.getRow(t))}setRow(t,e){checkRowIndex$4(this,t),e=checkRowVector$4(this,e);for(var r=0;r<this.columns;r++)this.set(t,r,e[r]);return this}swapRows(t,e){checkRowIndex$4(this,t),checkRowIndex$4(this,e);for(var r=0;r<this.columns;r++){var n=this.get(t,r);this.set(t,r,this.get(e,r)),this.set(e,r,n)}return this}getColumn(t){checkColumnIndex$4(this,t);for(var e=new Array(this.rows),r=0;r<this.rows;r++)e[r]=this.get(r,t);return e}getColumnVector(t){return this.constructor.columnVector(this.getColumn(t))}setColumn(t,e){checkColumnIndex$4(this,t),e=checkColumnVector$4(this,e);for(var r=0;r<this.rows;r++)this.set(r,t,e[r]);return this}swapColumns(t,e){checkColumnIndex$4(this,t),checkColumnIndex$4(this,e);for(var r=0;r<this.rows;r++){var n=this.get(r,t);this.set(r,t,this.get(r,e)),this.set(r,e,n)}return this}addRowVector(t){t=checkRowVector$4(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}subRowVector(t){t=checkRowVector$4(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=checkRowVector$4(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=checkRowVector$4(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=checkColumnVector$4(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=checkColumnVector$4(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=checkColumnVector$4(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=checkColumnVector$4(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){checkRowIndex$4(this,t);for(var r=0;r<this.columns;r++)this.set(t,r,this.get(t,r)*e);return this}mulColumn(t,e){checkColumnIndex$4(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){checkRowIndex$4(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){checkRowIndex$4(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){checkRowIndex$4(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){checkRowIndex$4(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){checkColumnIndex$4(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){checkColumnIndex$4(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){checkColumnIndex$4(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){checkColumnIndex$4(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 sumByRow$4(this);case"column":return sumByColumn$4(this);default:return sumAll$4(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: ${t}`)}cumulativeSum(){for(var t=0,e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t+=this.get(e,r),this.set(e,r,t);return this}dot(t){e.isMatrix(t)&&(t=t.to1DArray());var r=this.to1DArray();if(r.length!==t.length)throw new RangeError("vectors do not have the same size");for(var n=0,i=0;i<r.length;i++)n+=r[i]*t[i];return n}mmul(t){t=this.constructor.checkMatrix(t),this.columns!==t.rows&&console.warn("Number of columns of left matrix are not equal to number of rows of right matrix.");for(var e=this.rows,r=this.columns,n=t.columns,i=new this.constructor[Symbol.species](e,n),o=new Array(r),s=0;s<n;s++){for(var a=0;a<r;a++)o[a]=t.get(a,s);for(var u=0;u<e;u++){var h=0;for(a=0;a<r;a++)h+=this.get(u,a)*o[a];i.set(u,s,h)}}return i}strassen2x2(t){var e=new this.constructor[Symbol.species](2,2);const r=this.get(0,0),n=t.get(0,0),i=this.get(0,1),o=t.get(0,1),s=this.get(1,0),a=t.get(1,0),u=this.get(1,1),h=t.get(1,1),c=(r+u)*(n+h),l=(s+u)*n,f=r*(o-h),m=u*(a-n),p=(r+i)*h,d=c+m-p+(i-u)*(a+h),g=f+p,v=l+m,w=c-l+f+(s-r)*(n+o);return e.set(0,0,d),e.set(0,1,g),e.set(1,0,v),e.set(1,1,w),e}strassen3x3(t){var e=new this.constructor[Symbol.species](3,3);const r=this.get(0,0),n=this.get(0,1),i=this.get(0,2),o=this.get(1,0),s=this.get(1,1),a=this.get(1,2),u=this.get(2,0),h=this.get(2,1),c=this.get(2,2),l=t.get(0,0),f=t.get(0,1),m=t.get(0,2),p=t.get(1,0),d=t.get(1,1),g=t.get(1,2),v=t.get(2,0),w=t.get(2,1),y=t.get(2,2),b=(r-o)*(-f+d),x=(-r+o+s)*(l-f+d),M=(o+s)*(-l+f),_=r*l,$=(-r+u+h)*(l-m+g),S=(-r+u)*(m-g),R=(u+h)*(-l+m),E=(-i+h+c)*(d+v-w),C=(i-c)*(d-w),k=i*v,A=(h+c)*(-v+w),T=(-i+s+a)*(g+v-y),O=(i-a)*(g-y),I=(s+a)*(-v+y),D=_+k+n*p,P=(r+n+i-o-s-h-c)*d+x+M+_+E+k+A,V=_+$+R+(r+n+i-s-a-u-h)*g+k+T+I,j=b+s*(-l+f+p-d-g-v+y)+x+_+k+T+O,L=b+x+M+_+a*w,N=k+T+O+I+o*m,B=_+$+S+h*(-l+m+p-d-g-v+w)+E+C+k,F=E+C+k+A+u*f,z=_+$+S+R+c*y;return e.set(0,0,D),e.set(0,1,P),e.set(0,2,V),e.set(1,0,j),e.set(1,1,L),e.set(1,2,N),e.set(2,0,B),e.set(2,1,F),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 ${s} matrix: dimensions do not match.`);var u=Math.max(n,o),h=Math.max(i,s);return function t(r,n,i,o){if(i<=512||o<=512)return r.mmul(n);i%2==1&&o%2==1?(r=a(r,i+1,o+1),n=a(n,i+1,o+1)):i%2==1?(r=a(r,i+1,o),n=a(n,i+1,o)):o%2==1&&(r=a(r,i,o+1),n=a(n,i,o+1));var s=parseInt(r.rows/2),u=parseInt(r.columns/2),h=r.subMatrix(0,s-1,0,u-1),c=n.subMatrix(0,s-1,0,u-1),l=r.subMatrix(0,s-1,u,r.columns-1),f=n.subMatrix(0,s-1,u,n.columns-1),m=r.subMatrix(s,r.rows-1,0,u-1),p=n.subMatrix(s,n.rows-1,0,u-1),d=r.subMatrix(s,r.rows-1,u,r.columns-1),g=n.subMatrix(s,n.rows-1,u,n.columns-1),v=t(e.add(h,d),e.add(c,g),s,u),w=t(e.add(m,d),c,s,u),y=t(h,e.sub(f,g),s,u),b=t(d,e.sub(p,c),s,u),x=t(e.add(h,l),g,s,u),M=t(e.sub(m,h),e.add(c,f),s,u),_=t(e.sub(l,d),e.add(p,g),s,u),$=e.add(v,b);$.sub(x),$.add(_);var S=e.add(y,x),R=e.add(w,b),E=e.sub(v,w);E.add(y),E.add(M);var C=e.zeros(2*$.rows,2*$.columns);return(C=(C=(C=(C=C.setSubMatrix($,0,0)).setSubMatrix(S,$.rows,0)).setSubMatrix(R,0,$.columns)).setSubMatrix(E,$.rows,$.columns)).subMatrix(0,i-1,0,o-1)}(r=a(r,u,h),t=a(t,u,h),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),n=0;n<this.rows;n++){var i=rescale(this.getRow(n),{min:t,max:e});r.setRow(n,i)}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),n=0;n<this.columns;n++){var i=rescale(this.getColumn(n),{min:t,max:e});r.setColumn(n,i)}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){checkRange$4(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 s=r;s<=n;s++)i[o-t][s-r]=this.get(o,s);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){checkRange$4(this,e,e+(t=this.constructor.checkMatrix(t)).rows-1,r,r+t.columns-1);for(var n=0;n<t.rows;n++)for(var i=0;i<t.columns;i++)this[e+n][r+i]=t.get(n,i);return this}selection(t,e){for(var r=checkIndices$4(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],s=0;s<r.column.length;s++){var a=r.column[s];n[i][s]=this.get(o,a)}return n}trace(){for(var t=Math.min(this.rows,this.columns),e=0,r=0;r<t;r++)e+=this.get(r,r);return e}transposeView(){return new MatrixTransposeView$4(this)}rowView(t){return checkRowIndex$4(this,t),new MatrixRowView$4(this,t)}columnView(t){return checkColumnIndex$4(this,t),new MatrixColumnView$4(this,t)}flipRowView(){return new MatrixFlipRowView$4(this)}flipColumnView(){return new MatrixFlipColumnView$4(this)}subMatrixView(t,e,r,n){return new MatrixSubView$4(this,t,e,r,n)}selectionView(t,e){return new MatrixSelectionView$4(this,t,e)}rowSelectionView(t){return new MatrixRowSelectionView$4(this,t)}columnSelectionView(t){return new MatrixColumnSelectionView$4(this,t)}det(){var t,e,r,n,i,o;if(this.isSquare())return 2===this.columns?(t=this.get(0,0),e=this.get(0,1),r=this.get(1,0),t*this.get(1,1)-e*r):3===this.columns?(n=this.selectionView([1,2],[1,2]),i=this.selectionView([1,2],[0,2]),o=this.selectionView([1,2],[0,1]),t=this.get(0,0),e=this.get(0,1),r=this.get(0,2),t*n.det()-e*i.det()+r*o.det()):new LuDecomposition$$1(this).determinant;throw Error("Determinant can only be calculated for a square matrix.")}pseudoInverse(t){void 0===t&&(t=Number.EPSILON);for(var e=new SingularValueDecomposition$$1(this,{autoTranspose:!0}),r=e.leftSingularVectors,n=e.rightSingularVectors,i=e.diagonal,o=0;o<i.length;o++)Math.abs(i[o])>t?i[o]=1/i[o]:i[o]=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 n,i="\n(function %name%(matrix, %args%) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(%args%);\n})\n",o=i,s=eval;for(var a of[["+","add"],["-","sub","subtract"],["*","mul","multiply"],["/","div","divide"],["%","mod","modulus"],["&","and"],["|","or"],["^","xor"],["<<","leftShift"],[">>","signPropagatingRightShift"],[">>>","rightShift","zeroFillRightShift"]]){var u=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",{name:a[1],op:a[0]})),h=s(S("\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, this.get(i, j) %op% value);\n        }\n    }\n    return this;\n})\n",{name:a[1]+"S",op:a[0]})),c=s(S("\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, this.get(i, j) %op% matrix.get(i, j));\n        }\n    }\n    return this;\n})\n",{name:a[1]+"M",op:a[0]})),l=s(S("\n(function %name%(matrix, value) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(value);\n})\n",{name:a[1]}));for(n=1;n<a.length;n++)e.prototype[a[n]]=u,e.prototype[a[n]+"S"]=h,e.prototype[a[n]+"M"]=c,e[a[n]]=l}var f=[["~","not"]];for(var m 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){f.push(["Math."+t,t])})),f)){var p=s(S("\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:m[1],method:m[0]})),d=s(S("\n(function %name%(matrix) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%();\n})\n",{name:m[1]}));for(n=1;n<m.length;n++)e.prototype[m[n]]=p,e[m[n]]=d}for(var g of[["Math.pow",1,"pow"]]){var v="arg0";for(n=1;n<g[1];n++)v+=`, arg${n}`;if(1!==g[1]){var w=s(S("\n(function %name%(%args%) {\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j), %args%));\n        }\n    }\n    return this;\n})\n",{name:g[2],method:g[0],args:v})),y=s(S(i,{name:g[2],args:v}));for(n=2;n<g.length;n++)e.prototype[g[n]]=w,e[g[n]]=y}else{var b={name:g[2],args:v,method:g[0]},x=s(S("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",b)),M=s(S("\n(function %name%S(value) {\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j), value));\n        }\n    }\n    return this;\n})\n",b)),_=s(S("\n(function %name%M(matrix) {\n    matrix = this.constructor.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n        this.columns !== matrix.columns) {\n        throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j), matrix.get(i, j)));\n        }\n    }\n    return this;\n})\n",b)),$=s(S(o,b));for(n=2;n<g.length;n++)e.prototype[g[n]]=x,e.prototype[g[n]+"M"]=_,e.prototype[g[n]+"S"]=M,e[g[n]]=$}}function S(t,e){for(var r in e)t=t.replace(new RegExp("%"+r+"%","g"),e[r]);return t}return e}class Matrix$a extends(AbstractMatrix$4(Array)){constructor(t,e){var r;if(1===arguments.length&&"number"==typeof t)return new Array(t);if(Matrix$a.isMatrix(t))return t.clone();if(Number.isInteger(t)&&t>0){if(super(t),!(Number.isInteger(e)&&e>0))throw new TypeError("nColumns must be a positive integer");for(r=0;r<t;r++)this[r]=new Array(e)}else{if(!Array.isArray(t))throw new TypeError("First argument must be a positive number or an array");{const n=t;if(t=n.length,"number"!=typeof(e=n[0].length)||0===e)throw new TypeError("Data must be a 2D array with at least one element");for(super(t),r=0;r<t;r++){if(n[r].length!==e)throw new RangeError("Inconsistent array dimensions");this[r]=[].concat(n[r])}}}return this.rows=t,this.columns=e,this}set(t,e,r){return this[t][e]=r,this}get(t,e){return this[t][e]}removeRow(t){if(checkRowIndex$4(this,t),1===this.rows)throw new RangeError("A matrix cannot have less than one row");return this.splice(t,1),this.rows-=1,this}addRow(t,e){return void 0===e&&(e=t,t=this.rows),checkRowIndex$4(this,t,!0),e=checkRowVector$4(this,e,!0),this.splice(t,0,e),this.rows+=1,this}removeColumn(t){if(checkColumnIndex$4(this,t),1===this.columns)throw new RangeError("A matrix cannot have less than one column");for(var e=0;e<this.rows;e++)this[e].splice(t,1);return this.columns-=1,this}addColumn(t,e){void 0===e&&(e=t,t=this.columns),checkColumnIndex$4(this,t,!0),e=checkColumnVector$4(this,e);for(var r=0;r<this.rows;r++)this[r].splice(t,0,e[r]);return this.columns+=1,this}}class WrapperMatrix1D$4 extends(AbstractMatrix$4()){constructor(t,e={}){const{rows:r=1}=e;if(t.length%r!=0)throw new Error("the data length is not divisible by the number of rows");super(),this.rows=r,this.columns=t.length/r,this.data=t}set(t,e,r){var n=this._calculateIndex(t,e);return this.data[n]=r,this}get(t,e){var r=this._calculateIndex(t,e);return this.data[r]}_calculateIndex(t,e){return t*this.columns+e}static get[Symbol.species](){return Matrix$a}}class WrapperMatrix2D$4 extends(AbstractMatrix$4()){constructor(t){super(),this.data=t,this.rows=t.length,this.columns=t[0].length}set(t,e,r){return this.data[t][e]=r,this}get(t,e){return this.data[t][e]}static get[Symbol.species](){return Matrix$a}}class LogisticRegressionTwoClasses{constructor(t={}){this.numSteps=t.numSteps||5e5,this.learningRate=t.learningRate||5e-4,this.weights=t.weights?Matrix$a.checkMatrix(t.weights):null}train(t,e){for(var r=Matrix$a.zeros(1,t.columns),n=0;n<this.numSteps;n++){var i=sigmoid(t.mmul(r.transposeView())),o=Matrix$a.columnVector(i).neg().add(e),s=t.transposeView().mmul(o);r=r.add(s.mul(this.learningRate).transposeView())}this.weights=r}testScores(t){var e=sigmoid(t.mmul(this.weights.transposeView()));return(e=Matrix$a.columnVector(e)).to1DArray()}predict(t){var e=sigmoid(t.mmul(this.weights.transposeView()));return(e=Matrix$a.columnVector(e).round()).to1DArray()}static load(t){return new LogisticRegressionTwoClasses(t)}toJSON(){return{numSteps:this.numSteps,learningRate:this.learningRate,weights:this.weights}}}function sigmoid(t){t=t.to1DArray();for(var e=[],r=0;r<t.length;r++)e.push(1/(1+Math.exp(-t[r])));return e}function transformClassesForOneVsAll(t,e){for(var r=t.to1DArray(),n=0;n<r.length;n++)r[n]===e?r[n]=0:r[n]=1;return Matrix$a.columnVector(r)}class LogisticRegression{constructor(t={}){this.numSteps=t.numSteps||5e5,this.learningRate=t.learningRate||5e-4,this.classifiers=t.classifiers||[],this.numberClasses=t.numberClasses||0}train(t,e){this.numberClasses=new Set(e.to1DArray()).size,this.classifiers=new Array(this.numberClasses);for(var r=0;r<this.numberClasses;r++){this.classifiers[r]=new LogisticRegressionTwoClasses({numSteps:this.numSteps,learningRate:this.learningRate});var n=e.clone();n=transformClassesForOneVsAll(n,r),this.classifiers[r].train(t,n)}}predict(t){var e,r=new Array(this.numberClasses).fill(0);for(e=0;e<this.numberClasses;e++)r[e]=this.classifiers[e].testScores(t);var n=new Array(t.rows).fill(0);for(e=0;e<t.rows;e++)for(var i=1e5,o=0;o<this.numberClasses;o++)r[o][e]<i&&(i=r[o][e],n[e]=o);return n}static load(t){if("LogisticRegression"!==t.name)throw new Error("invalid model: "+t.name);const e=new LogisticRegression(t);for(let r=0;r<e.numberClasses;r++)e.classifiers[r]=LogisticRegressionTwoClasses.load(t.classifiers[r]);return e}toJSON(){return{name:"LogisticRegression",numSteps:this.numSteps,learningRate:this.learningRate,numberClasses:this.numberClasses,classifiers:this.classifiers}}}class ReinforcedLearningBase{constructor(t={}){return this.bounds=t.bounds||5,this.getBound=t.getBound||function(t){return t},this.last_selected=[],this.total_reward=0,this.iteration=0,this}learn(){throw new ReferenceError("Missing learn method implementation")}train(){throw new ReferenceError("Missing train method implementation")}predict(){throw new ReferenceError("Missing predict method implementation")}}class UpperConfidenceBound extends ReinforcedLearningBase{constructor(t={}){super(t),this.numbers_of_selections=new Map,this.sums_of_rewards=new Map;for(let t=0;t<this.bounds;t++)this.numbers_of_selections.set(t,0),this.sums_of_rewards.set(t,0);return this}predict(){let t=0,e=0;for(let r=0;r<this.bounds;r++){let n=Infinity;if(this.numbers_of_selections.get(r)>0){n=this.sums_of_rewards.get(r)/this.numbers_of_selections.get(r)+Math.sqrt(1.5*Math.log(this.iteration+1)/this.numbers_of_selections.get(r))}n>e&&(e=n,t=r)}return t}learn(t={}){const{ucbRow:e,getBound:r}=t;let n=this.predict();this.last_selected.push(n),this.numbers_of_selections.set(n,this.numbers_of_selections.get(n)+1);let i=e[r(n)];return this.sums_of_rewards.set(n,this.sums_of_rewards.get(n)+i),this.total_reward=this.total_reward+i,this.iteration++,this}train(t){const{ucbRow:e,getBound:r=this.getBound}=t;if(Array.isArray(e))for(let t in e)this.learn({ucbRow:e[t],getBound:r});else this.learn({ucbRow:e,getBound:r});return this}}class ThompsonSampling extends ReinforcedLearningBase{constructor(t={}){super(t),this.numbers_of_rewards_1=new Map,this.numbers_of_rewards_0=new Map;for(let t=0;t<this.bounds;t++)this.numbers_of_rewards_1.set(t,0),this.numbers_of_rewards_0.set(t,0);return this}predict(){let t=0,e=0;for(let r=0;r<this.bounds;r++){let n=probabilityDistributions.rbeta(1,this.numbers_of_rewards_1.get(r)+1,this.numbers_of_rewards_0.get(r)+1);n>e&&(e=n,t=r)}return t}learn(t={}){const{tsRow:e,getBound:r}=t;let n=this.predict();this.last_selected.push(n);let i=e[r(n)];return 1===i?this.numbers_of_rewards_1.set(n,this.numbers_of_rewards_1.get(n)+1):this.numbers_of_rewards_0.set(n,this.numbers_of_rewards_0.get(n)+1),this.total_reward=this.total_reward+i,this.iteration++,this}train(t){const{tsRow:e,getBound:r=this.getBound}=t;if(Array.isArray(e))for(let t in e)this.learn({tsRow:e[t],getBound:r});else this.learn({tsRow:e,getBound:r});return this}}const mlf=src$1,mlc=src,mln=src$6,{RandomForestRegression:RandomForestRegression$1,RandomForestClassifier:RandomForestClassifier$1}=mlf,{DecisionTreeRegression:DecisionTreeRegression$1,DecisionTreeClassifier:DecisionTreeClassifier$1}=mlc,{GaussianNB:GaussianNB$1}=mln;src$n.Regression=Object.assign({},src$n.Regression),src$n.SL=Object.assign({},src$n.SL),src$n.Stat=Object.assign({},src$n.Stat),src$n.RL=Object.assign({},src$n.RL,{ReinforcedLearningBase:ReinforcedLearningBase,UpperConfidenceBound:UpperConfidenceBound,ThompsonSampling:ThompsonSampling}),src$n.UpperConfidenceBound=UpperConfidenceBound,src$n.ThompsonSampling=ThompsonSampling,src$n.Regression.DecisionTreeRegression=DecisionTreeRegression$1,src$n.Regression.RandomForestRegression=RandomForestRegression$1,src$n.Regression.MultivariateLinearRegression=MultivariateLinearRegression,src$n.SL.GaussianNB=GaussianNB$1,src$n.SL.LogisticRegression=LogisticRegression,src$n.SL.DecisionTreeClassifier=DecisionTreeClassifier$1,src$n.SL.RandomForestClassifier=RandomForestClassifier$1,src$n.Stat.PCA=pca;const ml=src$n,transformConfigMap={scale:"scaleOptions",descale:"descaleOptions",label:"labelOptions",labelEncoder:"labelOptions",labeldecode:"labelOptions",labelDecode:"labelOptions",labelDecoder:"labelOptions",onehot:"oneHotOptions",oneHot:"oneHotOptions",oneHotEncode:"oneHotOptions",oneHotEncoder:"oneHotOptions",reducer:"reducerOptions",reduce:"reducerOptions",merge:"mergeData"};class DataSet{static getTransforms(t={}){return Object.keys(t).reduce(((e,r)=>{const n=t[r],i={name:r,options:{strategy:Array.isArray(n)?n[0]:n}};return Array.isArray(n)&&n.length>1&&(i.options[transformConfigMap[n[0]]]=n[1]),e.push(i),e}),[])}static reverseColumnMatrix(t={}){const{vectors:e,labels:r}=t,n=Array.isArray(r)&&Array.isArray(r[0])?r:r.map((t=>[t]));return e.reduce(((t,e)=>(t.push(e.reduce(((t,r,i)=>(t[n[i][0]]=e[i],t)),{})),t)),[])}static reverseColumnVector(t={}){const{vector:e,labels:r}=t,n=Array.isArray(r)&&Array.isArray(r[0])?r:r.map((t=>[t]));return e.reduce(((t,e)=>(t.push({[n[0][0]]:e}),t)),[])}static encodeObject(t,e){const{labels:r,prefix:n,name:i}=e;return r.reduce(((e,r)=>(e[`${n}${r}`]=r&&t[i]&&t[i].toString()===r.toString()?1:0,e)),{})}static oneHotEncoder(t,e){const r=Object.assign({merge:!0},e),n=r.data||this.columnArray(t,r.columnArrayOptions),i=Array.from(new Set(n).values()),o=r.prefix||`${t}_`,s=n.reduce(((t,e,r,n)=>(i.forEach((r=>{const n=`${o}${r}`,i=e===r?1:0;Array.isArray(t[n])?t[n].push(i):t[n]=[i]})),t)),{});return this.encoders.has(t)&&r.merge?this.encoders.get(t).labels=Array.from(new Set(i.concat(this.encoders.get(t).labels))):this.encoders.set(t,{name:t,labels:i,prefix:o}),s}static oneHotDecoder(t,e){const r=Object.assign({},e),n=r.encoders||this.encoders,i=r.prefix||n.get(t).prefix,o=r.labels||n.get(t).labels;return(r.data||this.oneHotColumnArray(t,r.oneHotColumnArrayOptions)).reduce(((e,r)=>{const n=Object.keys(r).filter((t=>1===r[t]&&(-1!==o.indexOf(t.replace(i,""))||-1!==o.map((t=>String(t))).indexOf(t.replace(i,"")))))[0]||"",s={[t]:n.replace(i,"")};return e.push(s),e}),[])}static selectColumns(t,e={}){return(Object.assign({},e).data||this.data).reduce(((e,r)=>{const n={};return t.forEach((t=>{n[t]=r[t]})),e.push(n),e}),[])}static columnArray(t,e={}){const r=Object.assign({prefilter:()=>!0,filter:()=>!0,replace:{test:void 0,value:void 0},parseInt:!1,parseIntBase:10,parseFloat:!!e.scale,scale:!1},e),n=(r.data||this.data).filter(r.prefilter).reduce(((e,n,i,o)=>{let s=n[t],a="function"==typeof r.replace.test&&r.replace.test(s)?"function"==typeof r.replace.value?r.replace.value(e,n,i,o,t):r.replace.value:s;return r.filter(a)&&(r.parseInt?e.push(parseInt(a,r.parseIntBase)):r.parseFloat?e.push(parseFloat(a)):e.push(a)),e}),[]);if("function"==typeof r.scale)return n.map(r.scale);if(!r.scale)return n;switch(r.scale){case"standard":return util$3.StandardScaler(n);case"log":return util$3.LogScaler(n);case"exp":return util$3.ExpScaler(n);default:return util$3.MinMaxScaler(n)}}static columnMatrix(t=[],e=[]){const r=e.length?{data:e}:{},n=(Array.isArray(t)&&Array.isArray(t[0])?t:t.map((t=>[t,r]))).map((t=>DataSet.columnArray.call(this,...t)));return util$3.pivotArrays(n)}static mapToObject(t=new Map){return Array.from(t.keys()).reduce(((e,r)=>{const n=t.get(r);return n instanceof Map?e[r]=DataSet.mapToObject(n):e[r]="function"==typeof n?`[Function ${n.name}]`:JSON.parse(JSON.stringify(n)),e}),{})}static getBinaryValue(t=""){if(!t)return 0;switch(t){case!1:case"N":case"n":case"NO":case"No":case"no":case"False":case"F":case"f":return 0;default:return 1}}constructor(t=[],e={}){return this.config=Object.assign({debug:!0},e),this.data=[...t],this.labels=new Map,this.encoders=new Map,this.scalers=new Map,this.selectColumns=DataSet.selectColumns,this.columnArray=DataSet.columnArray,this.encodeObject=DataSet.encodeObject,this.oneHotEncoder=DataSet.oneHotEncoder,this.oneHotDecoder=DataSet.oneHotDecoder,this.columnMatrix=DataSet.columnMatrix,this.reverseColumnMatrix=DataSet.reverseColumnMatrix,this.reverseColumnVector=DataSet.reverseColumnVector,this.getTransforms=DataSet.getTransforms,(this.config.labels||this.config.encoders||this.config.scalers)&&this.importFeatures({labels:this.config.labels,encoders:this.config.encoders,scalers:this.config.scalers}),this}exportFeatures(t={}){Object.assign({},t);return{encoders:DataSet.mapToObject(this.encoders),labels:DataSet.mapToObject(this.labels),scalers:DataSet.mapToObject(this.scalers)}}importFeatures(t={}){Object.keys(t.encoders||{}).forEach((e=>{const r=t.encoders[e];this.encoders.set(e,r)})),Object.keys(t.labels||{}).forEach((e=>{const r=t.labels[e],n=Object.keys(r).map((t=>[t,r[t]]));void 0!==r[0]&&void 0!==r[1]&&n.push([0,!1],[!1,0],[null,0],["no",0],["No",0],["NO",0],["F",0],["f",0],["null",0],["",0],[void 0,0],["undefined",0],[1,!0],[!0,1]),this.labels.set(e,new Map(n))})),Object.keys(t.scalers||{}).forEach((e=>{let r;const n=t.scalers[e],{config:i}=n;switch(i.strategy){case"standard":r=util$3.StandardScalerTransforms(void 0,i.nan_value,i.return_nan,n.components),n.scale=r.scale,n.descale=r.descale;break;case"normalize":case"minmax":r=util$3.MinMaxScalerTransforms(void 0,i.nan_value,i.return_nan,n.components),n.scale=r.scale,n.descale=r.descale;break;default:n.scale=Math.log,n.descale=Math.exp}this.scalers.set(e,n)}))}filterColumn(t=()=>!0){return this.data.filter(t)}columnScale(t,e={}){const r="string"==typeof e?{strategy:e}:e,n=Object.assign({strategy:"log",forced_coercion:!1},r);let i,o,s=n.data||this.columnArray(t,n.columnArrayOptions);switch(s=s.filter((t=>void 0!==t)).map(((e,r)=>{if("number"!=typeof e){this.config.debug&&!1===n.forced_coercion&&console.error(TypeError(`Each value must be a number, error at index [${t}][${r}]: <${typeof e}>${e}`));const i=Number(e);if(isNaN(i)&&n.forced_coercion)return 0;if(isNaN(i))throw TypeError(`Only numerical values in (${t}) can be scaled i: ${r} datum: ${e}`);return i}return e})),n.strategy){case"standard":o=util$3.StandardScalerTransforms(s,n.nan_value,n.return_nan),this.scalers.set(t,{name:t,scale:o.scale,descale:o.descale,components:o.components}),i=o.values;break;case"normalize":case"minmax":o=util$3.MinMaxScalerTransforms(s,n.nan_value,n.return_nan),this.scalers.set(t,{name:t,scale:o.scale,descale:o.descale,components:o.components}),i=o.values;break;default:this.scalers.set(t,{name:t,scale:Math.log,descale:Math.exp,components:{average:util$3.avg(s),standard_dev:util$3.sd(s),maximum:util$3.max(s),minimum:util$3.min(s)}}),i=util$3.LogScaler(s)}return this.scalers.get(t).config=n,i}columnDescale(t,e){const r=Object.assign({},e),n=r.data||this.columnArray(t,r.columnArrayOptions),i=this.scalers.get(t).descale;return n.map(i)}labelEncoder(t,e){const r=Object.assign({binary:!1,merge:!0},e),n=r.data||this.columnArray(t,r.columnArrayOptions);let i=Array.from(new Set(n).values()).sort(r.sortFunction);const o=new Map(i.reduce(((t,e,n)=>(r.binary?(0===n&&t.push([0,!1],["0",!1],[1,!0],["1",!0]),t.push([e,DataSet.getBinaryValue(e)])):(t.push([e,n]),t.push([n,e])),t)),[]));this.labels.has(t)&&r.merge?this.labels.set(t,new Map([...this.labels.get(t),...o])):this.labels.set(t,o);return r.binary?n.map(DataSet.getBinaryValue):n.map((t=>o.get(t)))}labelDecode(t,e){const r=Object.assign({},e);return(r.data||this.columnArray(t,r.columnArrayOptions)).map((e=>this.labels.get(t).get(e)))}oneHotColumnArray(t,e){const r=Object.assign({},e),n=r.labels||this.encoders.get(t).labels,i=r.prefix||this.encoders.get(t).prefix;return this.selectColumns(n.map((t=>`${i}${t}`)))}columnReducer(t,e){return{[t]:this.columnArray(e.columnName,e.columnOptions).reduce(e.reducer,[])}}columnMerge(t,e=[]){if(this.data.length!==e.length)throw new RangeError(`Merged data column must have the same length(${e.length}) as the DataSet's length (${this.data.length})`);return{[t]:e}}inverseTransformObject(t,e){const r=Object.assign({removeValues:!1},e),n=[];let i=Object.assign({},t);const o=Object.keys(this.data[0]),s=o.reduce(((e,r)=>(this.scalers.has(r)&&(e[r]=this.scalers.get(r).descale(t[r])),e)),{}),a=o.reduce(((e,r)=>(this.labels.has(r)&&(e[r]=this.labels.get(r).get(t[r])),e)),{}),u=o.reduce(((e,i)=>{if(this.encoders.has(i)){const o=this.oneHotDecoder(i,{data:[t]});e=Object.assign({},e,o[0]),r.removeValues&&n.push(...this.encoders.get(i).labels.map((t=>`${this.encoders.get(i).prefix}${t}`)))}return e}),{});return i=Object.assign(i,s,a,u),r.removeValues&&n.length&&(i=Object.keys(i).reduce(((t,e)=>(-1===n.indexOf(e)&&(t[e]=i[e]),t)),{})),i}transformObject(t,e){const r=Object.assign({removeValues:!1,checkColumnLength:!0},e),n=[],i=[].concat(...Array.from(this.encoders.keys()).map((t=>this.encoders.get(t).labels.map((e=>`${this.encoders.get(t).prefix}${e}`))))),o=this.data.length?Object.keys(this.data[0]):Object.keys(t),s=Object.keys(t).concat(i),a=s.reduce(((t,e)=>(-1===o.indexOf(e)&&-1===i.indexOf(e)&&t.push(e),t)),[]);let u=Object.assign({},t);if(r.checkColumnLength&&o.length!==s.length&&o.length+i.length!==s.length)throw new RangeError(`Object must have the same number of keys (${s.length}) as data in your dataset(${o.length})`);if(r.checkColumnLength&&a.length)throw new ReferenceError(`Object must have identical keys as data in your DataSet. Invalid keys: ${a.join(",")}`);{const e=s.reduce(((e,r)=>(this.scalers.has(r)&&(e[r]=this.scalers.get(r).scale(t[r])),e)),{}),i=s.reduce(((e,r)=>(this.labels.has(r)&&(e[r]=this.labels.get(r).get(t[r])),e)),{}),o=s.reduce(((e,i)=>(this.encoders.has(i)&&(e=Object.assign({},e,this.encodeObject(t,this.encoders.get(i))),r.removeValues&&n.push(i)),e)),{});u=Object.assign(u,e,i,o),r.removeValues&&n.length&&(u=Object.keys(u).reduce(((t,e)=>(-1===n.indexOf(e)&&(t[e]=u[e]),t)),{}))}return u}columnReplace(t,e={}){const r=Object.assign({strategy:"mean",empty:!0,arrayOptions:{parseFloat:!0,filter:t=>t},labelOptions:{}},e);let n,i={test:t=>!t,value:n};switch(r.strategy){case"scale":n=this.columnScale(t,r.scaleOptions),i={test:t=>!0,value:(t,e,r,i)=>n[r]};break;case"descale":n=this.columnDescale(t,r.descaleOptions),i={test:t=>!0,value:(t,e,r,i)=>n[r]};break;case"label":case"labelEncoder":n=this.labelEncoder(t,r.labelOptions),i={test:t=>!0,value:(t,e,r,i)=>n[r]};break;case"labeldecode":case"labelDecode":case"labelDecoder":n=this.labelDecode(t,r.labelOptions),i={test:t=>!0,value:(t,e,r,i)=>n[r]};break;case"onehot":case"oneHot":case"oneHotEncode":case"oneHotEncoder":return n=this.oneHotEncoder(t,r.oneHotOptions),i={test:t=>!0,value:(t,e,r,i)=>n[r]},n;case"reducer":case"reduce":return n=this.columnReducer(t,r.reducerOptions),n;case"merge":return n=this.columnMerge(t,r.mergeData),n;case"parseNumber":return n=this.columnArray(t).map((t=>Number(t))),n;default:n=ml.ArrayStat[r.strategy](this.columnArray(t,r.arrayOptions)),i.value=n}return this.columnArray(t,Object.assign({},{replace:i,scale:e.scale},e.columnOptions))}fitColumns(t={},e={}){const r=Object.assign({returnData:!0,columns:[]},t);t.columns&&!1!==Array.isArray(t.columns)||(r.columns=t.columns?DataSet.getTransforms(t.columns):DataSet.getTransforms(t));const n=r.columns.reduce(((t,e,r,n)=>{let i=this.columnReplace(e.name,e.options);return Array.isArray(i)?(i=i.map((t=>({[e.name]:t}))),t[e.name]=i):Object.keys(i).forEach((e=>{t[e]=i[e].map((t=>({[e]:t})))})),t}),{});if(Object.keys(n)&&Object.keys(n).length){const t=Object.keys(n),e=n[t[0]].reduce(((e,r,i,o)=>{const s={};return t.forEach((t=>{s[t]=n[t][i][t]})),e.push(s),e}),[]);this.data=this.data.map(((t,r)=>Object.assign({},t,e[r])))}return r.returnData?this.data:this}fitInverseTransforms(t={}){const e=Object.assign({returnData:!0},t);return this.data=this.data.map((e=>t.removeValues?this.inverseTransformObject(e,t):Object.assign({},e,this.inverseTransformObject(e,t)))),e.returnData?this.data:this}fitTransforms(t={}){const e=Object.assign({returnData:!0},t);return this.data=this.data.map((e=>t.removeValues?this.transformObject(e,t):Object.assign({},e,this.transformObject(e,t)))),e.returnData?this.data:this}}class ColumnVectorizer{constructor(t={}){return this.data=t.data||[],this.tokens=new Set,this.vectors=[],this.wordMap={},this.wordCountMap={},this.maxFeatures=t.maxFeatures,this.sortedWordCount=[],this.limitedFeatures=[],this.matrix=[],this.replacer=(t="")=>{const e=t.toLowerCase().replace(/[^a-zA-Z]/gi," ");return nlp.PorterStemmer.tokenizeAndStem(e).join(" ")},this}get_tokens(){return Array.from(this.tokens)}get_vector_array(){return this.get_tokens().map((t=>[t]))}fit_transform(t={}){(t.data||this.data).forEach((t=>{const e={};this.replacer(t).split(" ").forEach((t=>{const r=t.toLowerCase();e[r]=e[r]?e[r]+1:1,this.wordCountMap[r]=this.wordCountMap[r]?this.wordCountMap[r]+1:1,this.tokens.add(r)})),this.vectors.push(e)})),this.wordMap=Array.from(this.tokens).reduce(((t,e)=>(t[e]=0,t)),{}),this.sortedWordCount=Object.keys(this.wordCountMap).sort(((t,e)=>this.wordCountMap[e]-this.wordCountMap[t])),this.vectors=this.vectors.map((t=>Object.assign({},this.wordMap,t)));const e=new DataSet(this.vectors);return this.limitedFeatures=this.get_limited_features(t),this.matrix=e.columnMatrix(this.limitedFeatures),this.matrix}get_limited_features(t={}){const e=t.maxFeatures||this.maxFeatures||this.tokens.size;return this.sortedWordCount.slice(0,e).map((t=>[t]))}evaluateString(t=""){const e=this.replacer(t).split(" ").reduce(((t,e)=>(this.tokens.has(e)&&(t[e]=void 0!==t[e]?t[e]+1:1),t)),{});return Object.assign({},this.wordMap,e)}evaluate(t="",e){const r=this.evaluateString(t),n=this.get_limited_features(e);return new DataSet([r]).columnMatrix(n)}}const nlp=Object.assign({ColumnVectorizer:ColumnVectorizer});class GridSearch{constructor(t){this._run_callback=t.run_callback,this._params=[],this._shades=[],this._combinations=[],this._results=[],this._prepare(t.params)}save(t){let e={results:this._results,params:this._params,combinations:this._combinations};require$$0$2.writeFileSync(t,JSON.stringify(e),{encoding:"utf8"})}load(t){let e=require$$0$2.readFileSync(t,"utf8"),r=JSON.parse(e);this._results=r.results,this._params=r.params,this._combinations=r.combinations}clone(t){return Object.assign({},t)}_prepare(t){let e=[];for(let r in t)t.hasOwnProperty(r)&&e.push({name:r,values:t[r]});this._combinations=[{}];for(let t=0;t<e.length;t++){let r=[];for(let n of this._combinations)for(let i=0;i<e[t].values.length;i++){let o=this.clone(n);o[e[t].name]=e[t].values[i],r.push(o)}this._combinations=r}this._params=e}run(){for(let t of this._combinations)this._results.push({params:t,results:this._run_callback(t)})}_createDefaultTable(t,e,r){let n=[];for(let i=0;i<t;i++){let t=[];for(let n=0;n<e;n++)t.push(r);n.push(t)}return n}_findMatchForParam(t,e){for(let r=0;r<t.length;r++){let n=!0;for(let i in t[r])t[r].hasOwnProperty(i)&&(n=n&&e[i]==t[r][i]);if(n)return r}return-1}getTableOfResults(t,e,r){let n=[{}],i=[{}],o=this._params.filter((t=>e.indexOf(t.name)>=0)),s=this._params.filter((e=>t.indexOf(e.name)>=0));for(let t=0;t<o.length;t++){let e=[];for(let r of n)for(let n=0;n<o[t].values.length;n++){let i=this.clone(r);i[o[t].name]=o[t].values[n],e.push(i)}n=e}for(let t=0;t<s.length;t++){let e=[];for(let r of i)for(let n=0;n<s[t].values.length;n++){let i=this.clone(r);i[s[t].name]=s[t].values[n],e.push(i)}i=e}let a=this._createDefaultTable(n.length,i.length,-1);for(let t of this._results){let e=this._findMatchForParam(n,t.params),o=this._findMatchForParam(i,t.params);if(e<0||o<0)continue;let s=r(t);a[e][o]<s&&(a[e][o]=s)}return{rows:n,cols:i,results:a}}_createTitle(t){let e="";for(let r in t)t.hasOwnProperty(r)&&(e+=`${r}=${t[r]},`);return e.substr(0,e.length-1)}_padToWidth(t,e,r){for(r=r||" ";t.length<e;)t+=r;return t}_prepareColorShades(t,e){let r=(e-t)/5;this._shades=[];for(let t=0;t<5;t++)this._shades.push(e-t*r)}_outputValue(t,e){return this._padToWidth(""+t,e)}displayTableOfResults(t,e,r){let n=this.getTableOfResults(t,e,r),i=n.cols.map((t=>this._createTitle(t))),o=n.rows.map((t=>this._createTitle(t))),s=i.map((t=>Math.max(t.length+4,8))),a=0;o.forEach((t=>{a=Math.max(a,t.length+4)}));let u=null,h=null;n.results.forEach((t=>{t.forEach((t=>{(null===u||u>t)&&(u=t),(null===h||h<t)&&(h=t)}))})),this._prepareColorShades(u,h);let c="",l="";c+="| "+this._padToWidth("",a),l+="|-"+this._padToWidth("",a,"-");for(let t=0;t<i.length;t++)c+="| "+this._padToWidth(i[t],s[t]),l+="|-"+this._padToWidth("",s[t],"-");console.log(c),console.log(l);for(let t=0;t<o.length;t++){c="| ",c+=this._padToWidth(o[t],a);for(let e=0;e<i.length;e++)c+="| "+this._outputValue(n.results[t][e],s[e]);console.log(c)}}}var GridSearch_1=GridSearch,grid_search={GridSearch:GridSearch_1};const{GridSearch:GridSearch$1}=grid_search,Matrix$b=ml.Matrix,ConfusionMatrix$1=ml.ConfusionMatrix;function train_test_split(t=[],e={test_size:.2,train_size:.8,random_state:0,return_array:!1,parse_int_train_size:!0}){const r=random.engines.mt19937().seed(e.random_state||0),n=[],i="boolean"!=typeof e.parse_int_train_size||e.parse_int_train_size,o=e.train_size?e.train_size*t.length:(1-(e.test_size||.2))*t.length,s=i?parseInt(o,10):o,a=[].concat(t);for(;n.length<s;){const t=random.integer(0,a.length-1)(r);n.push(a.splice(t,1)[0])}return e.return_array?[n,a]:{train:n,test:a}}function cross_validation_split(t=[],e={folds:3,random_state:0}){const r=random.engines.mt19937().seed(e.random_state||0),n=e.folds||3,i=[],o=[].concat(t),s=parseInt(t.length/(n||3),10);for(let t in lodash_range(n)){const t=[];for(;t.length<s;){const e=random.integer(0,o.length-1)(r);t.push(o.splice(e,1)[0])}i.push(t)}return i}function cross_validate_score(t={}){const e=Object.assign({},{dependentFeatures:[["X"]],independentFeatures:[["Y"]],folds:10,accuracy:"standardError",use_train_x_matrix:!0,use_train_y_matrix:!1,use_train_y_vector:!1,use_estimates_y_vector:!1},t),r=e.classifier,n=e.regression,i=cross_validation_split(e.dataset,{folds:e.folds,random_state:e.random_state}),o=new DataSet(e.testingset),s=o.columnMatrix(e.independentFeatures),a=o.columnMatrix(e.dependentFeatures),u=util$3.pivotVector(s)[0];return i.map((t=>{const i=new DataSet(t),o=i.columnMatrix(e.dependentFeatures),s=i.columnMatrix(e.independentFeatures),h=e.use_train_x_matrix?new Matrix$b(o):o,c=e.use_train_y_matrix?new Matrix$b(s):e.use_train_y_vector?util$3.pivotVector(s)[0]:s;if(n){let t,r;"function"==typeof n.train?(t=n.train(h,c,e.modelOptions),r=n.predict(a)):(t=new n(h,c,e.modelOptions),r=t.predict(a));const i=r;return"standardError"===e.accuracy?util$3.standardError(u,i):util$3.rSquared(u,i)}{let t,n;"function"==typeof r.train?(r.train(h,c,e.modelOptions),n=r.predict(a)):(t=new r(h,c,e.modelOptions),n=t.predict(a));const i=e.use_estimates_y_vector?util$3.pivotVector(n)[0]:n;return ConfusionMatrix$1.fromLabels(u,i).getAccuracy()}}))}function grid_search$1(t={}){const e=Object.assign({},{return_parameters:!1,compare_score:"mean",sortAccuracyScore:"desc",parameters:{}},t),r=e.regression,n=e.classifier,i=!t.sortAccuracyScore&&e.regression?"asc":e.sortAccuracyScore,o=new GridSearch$1({params:e.parameters,run_callback:t=>{e.regression?e.regression=new r(t):e.classifier=new n(t);const i=cross_validate_score(e);return e.compare_score?util$3[e.compare_score](i):i}});o.run();const s="desc"===i?(t,e)=>e.results-t.results:(t,e)=>t.results-e.results,a=o._results.sort(s);return e.return_parameters?a:a[0]}const cross_validation={train_test_split:train_test_split,cross_validation_split:cross_validation_split,kfolds:cross_validation_split,cross_validate_score:cross_validate_score,grid_search:grid_search$1,GridSearch:GridSearch$1},loadCSV$1=loadCSV,loadCSVURI$1=loadCSVURI,preprocessing={DataSet:DataSet},util$4=util$3,cross_validation$1=cross_validation,model_selection=cross_validation,calc$1=calc,ml$1=ml,nlp$1=nlp,csv=csvUtils,PD$1=PD;exports.loadCSV=loadCSV$1,exports.loadCSVURI=loadCSVURI$1,exports.preprocessing=preprocessing,exports.util=util$4,exports.cross_validation=cross_validation$1,exports.model_selection=model_selection,exports.calc=calc$1,exports.ml=ml$1,exports.nlp=nlp$1,exports.csv=csv,exports.PD=PD$1,exports.DataSet=DataSet,Object.defineProperty(exports,"__esModule",{value:!0})}));
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