@ -1,6 +1,8 @@
// t-SNE.js object and other global variables
var k ; var points = [ ] ; var all _fields ; var pointsbeta = [ ] ; var KNNEnabled = true ;
var k ; var points = [ ] ; var all _fields ; var pointsbeta = [ ] ; var KNNEnabled = true ; var cost = [ ] ; var ParametersSet = [ ] ; var overallCost ;
// form controls
var input ;
// These are the dimensions for the square shape of the main panel\
var dimensions = document . getElementById ( 'modtSNEcanvas' ) . offsetWidth ;
var prevRightClick ; var ColorsCategorical ; var Category ;
@ -12,21 +14,148 @@ var format; var new_file; var opt; var step_counter; var final_dataset; var max_
var points2d = [ ] ; var ArrayContainsDataFeatures = [ ] ; var ArrayContainsDataFeaturesCleared = [ ] ;
var InitialStatePoints = [ ] ;
function FactoryReset ( ) {
lassoEnable ( ) ;
flag = false ;
d3 . selectAll ( "#modtSNEcanvas_svg_Schema > *" ) . remove ( ) ;
d3 . selectAll ( "#SvgAnnotator > *" ) . remove ( ) ;
Arrayx = [ ] ;
Arrayy = [ ] ;
XYDistId = [ ] ;
Arrayxy = [ ] ;
DistanceDrawing1D = [ ] ;
allTransformPoints = [ ] ;
p ;
pFinal = [ ] ;
paths ;
path ;
ArrayLimit = [ ] ;
minimum ;
correlationResults = [ ] ;
ArrayContainsDataFeaturesLimit = [ ] ;
prevRightClick = false ;
for ( var i = 0 ; i < InitialStatePoints . length ; i ++ ) {
InitialStatePoints [ i ] . selected = true ;
InitialStatePoints [ i ] . starplot = false ;
}
redraw ( InitialStatePoints ) ;
d3 . selectAll ( "#correlation > *" ) . remove ( ) ;
d3 . selectAll ( "#modtSNEcanvas_svg > *" ) . remove ( ) ;
d3 . selectAll ( "#modtSNEcanvas_svg_Schema > *" ) . remove ( ) ;
d3 . selectAll ( "#SvgAnnotator > *" ) . remove ( ) ;
d3 . selectAll ( "#sheparheat > *" ) . remove ( ) ;
d3 . selectAll ( "#knnBarChart > *" ) . remove ( ) ;
var oldcanvOver = document . getElementById ( 'tSNEcanvas' ) ;
var contxOver = oldcanvOver . getContext ( 'experimental-webgl' ) ;
contxOver . clear ( contxOver . COLOR _BUFFER _BIT ) ;
scene = new THREE . Scene ( ) ;
scene . background = new THREE . Color ( 0xffffff ) ;
d3 . selectAll ( "#legend1 > *" ) . remove ( ) ;
d3 . selectAll ( "#legend3 > *" ) . remove ( ) ;
d3 . selectAll ( "#legend4 > *" ) . remove ( ) ;
lassoEnable ( ) ;
Arrayx = [ ] ;
Arrayy = [ ] ;
XYDistId = [ ] ;
Arrayxy = [ ] ;
DistanceDrawing1D = [ ] ;
allTransformPoints = [ ] ;
p ;
pFinal = [ ] ;
paths ;
path ;
ArrayLimit = [ ] ;
minimum ;
correlationResults = [ ] ;
ArrayContainsDataFeaturesLimit = [ ] ;
document . getElementById ( "param-dataset" ) . value = "iris.csv" ;
document . getElementById ( 'file-input' ) . value = "" ;
document . getElementById ( "ExecuteBut" ) . innerHTML = "Execute new t-SNE analysis" ;
$ ( "#cost" ) . html ( "" ) ;
$ ( "#datasetDetails" ) . html ( "" ) ;
$ ( "#kNNDetails" ) . html ( "" ) ;
document . getElementById ( "param-perplexity-value" ) . value = 30 ;
document . getElementById ( "param-learningrate-value" ) . value = 10 ;
document . getElementById ( "param-maxiter-value" ) . value = 500 ;
document . getElementById ( "param-lim-value" ) . value = 2 ;
document . getElementById ( "param-corr-value" ) . value = 150 ;
document . getElementById ( "param-neighborHood" ) . value = "color" ;
document . getElementById ( 'selectionLabel' ) . innerHTML = 'Size' ;
document . getElementById ( "param-distance" ) . value = "euclideanDist" ;
document . getElementById ( "param-transform" ) . value = "noTrans" ;
}
function loadAnalysis ( ) {
document . getElementById ( 'file-input' ) . click ( ) ;
document . getElementById ( "ExecuteBut" ) . innerHTML = "Execute previous t-SNE analysis" ;
}
function getfile ( file ) {
new _file = file ; //uploaded file data
}
function fetchVal ( callback ) {
var file , fr ;
file = input . files [ 0 ] ;
fr = new FileReader ( ) ;
fr . onload = function ( e ) {
lines = e . target . result ;
callback ( lines ) ;
} ;
fr . readAsText ( file ) ;
}
// Parse data
var getData = function ( ) {
// form controls
var value = document . getElementById ( "param-dataset" ) . value ;
format = document . getElementById ( "param-dataset" ) . value . split ( "." ) ; //get the actual format
if ( format [ value . split ( "." ) . length - 1 ] == "csv" ) {
parseData ( "./data/" + value ) ;
} else {
parseData ( new _file , init ) ;
}
if ( typeof window . FileReader !== 'function' ) {
alert ( "The file API isn't supported on this browser yet." ) ;
}
var value ;
input = document . getElementById ( "file-input" ) ;
if ( ! input ) {
alert ( "Um, couldn't find the fileinput element." ) ;
}
else if ( ! input . files ) {
alert ( "This browser doesn't seem to support the `files` property of file inputs." ) ;
}
else if ( ! input . files [ 0 ] ) {
value = document . getElementById ( "param-dataset" ) . value ;
format = document . getElementById ( "param-dataset" ) . value . split ( "." ) ; //get the actual format
if ( format [ value . split ( "." ) . length - 1 ] == "csv" ) {
parseData ( "./data/" + value ) ;
} else {
parseData ( new _file , init ) ;
}
}
else {
fetchVal ( function ( lines ) {
AnalaysisResults = JSON . parse ( lines ) ;
length = ( AnalaysisResults . length - 7 ) / 2 ;
ParametersSet = AnalaysisResults . slice ( length * 2 + 1 , length * 2 + 7 ) ;
value = document . getElementById ( "param-dataset" ) . value = ParametersSet [ 0 ] ;
format = document . getElementById ( "param-dataset" ) . value . split ( "." ) ; //get the actual format
if ( format [ value . split ( "." ) . length - 1 ] == "csv" ) {
parseData ( "./data/" + value ) ;
} else {
parseData ( new _file , init ) ;
}
} ) ;
}
} ;
function parseData ( url ) {
@ -65,7 +194,7 @@ function parseData(url) {
}
} ) ;
function doStuff ( results _all ) {
init ( results . data , results _all , results . meta . fields ) ;
init ( results . data , results _all , results . meta . fields ) ;
}
}
} ) ;
@ -110,6 +239,12 @@ function setReset(){
}
function setReInitialize ( ) {
if ( document . getElementById ( 'selectionLabel' ) . innerHTML == 'Size' ) {
document . getElementById ( 'selectionLabel' ) . innerHTML = 'Color' ;
} else {
document . getElementById ( 'selectionLabel' ) . innerHTML = 'Size' ;
}
for ( var i = 0 ; i < InitialStatePoints . length ; i ++ ) {
InitialStatePoints [ i ] . selected = true ;
}
@ -277,6 +412,9 @@ function setAnnotator(){
var correlationResults = [ ] ;
var ArrayContainsDataFeaturesLimit = [ ] ;
// function that executes after data is successfully loaded
function init ( data , results _all , fields ) {
@ -285,6 +423,7 @@ function init(data, results_all, fields) {
d3 . selectAll ( "#modtSNEcanvas_svg_Schema > *" ) . remove ( ) ;
d3 . selectAll ( "#SvgAnnotator > *" ) . remove ( ) ;
d3 . selectAll ( "#sheparheat > *" ) . remove ( ) ;
d3 . selectAll ( "#knnBarChart > *" ) . remove ( ) ;
var oldcanvOver = document . getElementById ( 'tSNEcanvas' ) ;
var contxOver = oldcanvOver . getContext ( 'experimental-webgl' ) ;
@ -328,16 +467,6 @@ function init(data, results_all, fields) {
final _dataset = data ;
dataFeatures = results _all ;
var object ;
for ( let k = 0 ; k < dataFeatures . length ; k ++ ) {
ArrayContainsDataFeatures . push ( Object . values ( dataFeatures [ k ] ) . concat ( k ) ) ;
object = [ ] ;
Object . values ( dataFeatures [ k ] ) . forEach ( function ( dataFeature ) {
if ( typeof ( dataFeature ) == "number" ) {
object . push ( dataFeature ) ;
}
} ) ;
ArrayContainsDataFeaturesCleared . push ( object ) ;
}
all _labels = [ ] ;
dataFeatures . filter ( function ( obj ) {
@ -352,6 +481,18 @@ function init(data, results_all, fields) {
}
} ) ;
for ( let k = 0 ; k < dataFeatures . length ; k ++ ) {
ArrayContainsDataFeatures . push ( Object . values ( dataFeatures [ k ] ) . concat ( k ) ) ;
object = [ ] ;
Object . values ( dataFeatures [ k ] ) . forEach ( function ( dataFeature ) {
if ( typeof ( dataFeature ) == "number" ) {
object . push ( dataFeature ) ;
}
} ) ;
ArrayContainsDataFeaturesCleared . push ( object ) ;
}
var valCategExists = 0 ;
for ( var i = 0 ; i < Object . keys ( dataFeatures [ 0 ] ) . length ; i ++ ) {
@ -373,7 +514,28 @@ function init(data, results_all, fields) {
}
}
for ( var i = 0 ; i < final _dataset . length ; i ++ ) { final _dataset [ i ] . beta = tsne . beta [ i ] ; beta _all [ i ] = tsne . beta [ i ] ; }
runner = setInterval ( step , 0 ) ;
if ( typeof window . FileReader !== 'function' ) {
alert ( "The file API isn't supported on this browser yet." ) ;
}
input = document . getElementById ( "file-input" ) ;
if ( ! input ) {
alert ( "Um, couldn't find the fileinput element." ) ;
}
else if ( ! input . files ) {
alert ( "This browser doesn't seem to support the `files` property of file inputs." ) ;
}
else if ( ! input . files [ 0 ] ) {
AnalaysisResults = [ ] ;
runner = setInterval ( step , 0 ) ;
}
else {
fetchVal ( function ( lines ) {
AnalaysisResults = JSON . parse ( lines ) ;
updateEmbedding ( AnalaysisResults ) ;
} ) ;
}
}
// initialize distance matrix
@ -493,7 +655,8 @@ function computeDistances(data, distFunc, transFunc) {
}
// function that updates embedding
function updateEmbedding ( ) {
function updateEmbedding ( AnalaysisResults ) {
if ( AnalaysisResults == "" ) {
var Y = tsne . getSolution ( ) ; // here we get the solution from the actual t-sne
var xExt = d3 . extent ( Y , d => d [ 0 ] ) ;
var yExt = d3 . extent ( Y , d => d [ 1 ] ) ;
@ -506,16 +669,27 @@ function updateEmbedding() {
var y = d3 . scaleLinear ( )
. domain ( maxExt )
. range ( [ 10 , + dimensions - 10 ] ) ;
for ( var i = 0 ; i < final _dataset . length ; i ++ ) {
x _position [ i ] = x ( Y [ i ] [ 0 ] ) ;
y _position [ i ] = y ( Y [ i ] [ 1 ] ) ;
points [ i ] = { id : i , x : x _position [ i ] , y : y _position [ i ] , beta : final _dataset [ i ] . beta , cost : final _dataset [ i ] . cost , selected : true , DimON : null , starplot : false } ;
points2d [ i ] = { id : i , x : x _position [ i ] , y : y _position [ i ] , selected : true } ;
points [ i ] = extend ( points [ i ] , ArrayContainsDataFeaturesCleared [ i ] ) ;
points [ i ] = extend ( points [ i ] , dataFeatures [ i ] ) ;
}
for ( var i = 0 ; i < final _dataset . length ; i ++ ) {
x _position [ i ] = x ( Y [ i ] [ 0 ] ) ;
y _position [ i ] = y ( Y [ i ] [ 1 ] ) ;
points [ i ] = { id : i , x : x _position [ i ] , y : y _position [ i ] , beta : final _dataset [ i ] . beta , cost : final _dataset [ i ] . cost , selected : true , DimON : null , starplot : false } ;
points2d [ i ] = { id : i , x : x _position [ i ] , y : y _position [ i ] , selected : true } ;
points [ i ] = extend ( points [ i ] , ArrayContainsDataFeaturesCleared [ i ] ) ;
points [ i ] = extend ( points [ i ] , dataFeatures [ i ] ) ;
}
} else {
points = AnalaysisResults . slice ( 0 , dataFeatures . length ) ;
points2d = AnalaysisResults . slice ( dataFeatures . length , 2 * dataFeatures . length ) ;
overallCost = AnalaysisResults . slice ( dataFeatures . length * 2 , dataFeatures . length * 2 + 1 ) ;
ParametersSet = AnalaysisResults . slice ( dataFeatures . length * 2 + 1 , dataFeatures . length * 2 + 7 ) ;
$ ( "#cost" ) . html ( "Number of Iteration: " + ParametersSet [ 3 ] + ", Overall Cost: " + overallCost ) ;
$ ( '#param-perplexity-value' ) . text ( ParametersSet [ 1 ] ) ;
$ ( '#param-learningrate-value' ) . text ( ParametersSet [ 2 ] ) ;
$ ( '#param-maxiter-value' ) . text ( ParametersSet [ 3 ] ) ;
document . getElementById ( "param-distance" ) . value = ParametersSet [ 4 ] ;
document . getElementById ( "param-transform" ) . value = ParametersSet [ 5 ] ;
}
InitialStatePoints = points ;
function extend ( obj , src ) {
for ( var key in src ) {
@ -523,11 +697,9 @@ function updateEmbedding() {
}
return obj ;
}
if ( step _counter == max _counter ) {
ShepardHeatMap ( ) ;
OverviewtSNE ( points ) ;
BetatSNE ( points ) ;
}
}
function ShepardHeatMap ( ) {
@ -694,7 +866,7 @@ d3.tsv("./modules/heat.tsv").then(function(data) {
heatleg . append ( "g" )
. attr ( "class" , "legendLinear" )
. attr ( "transform" , "translate(0,10 )" ) ;
. attr ( "transform" , "translate(0,14 )" ) ;
var legend = d3 . legendColor ( )
. labelFormat ( d3 . format ( ",.0f" ) )
@ -709,19 +881,19 @@ d3.tsv("./modules/heat.tsv").then(function(data) {
// perform single t-SNE iteration
function step ( ) {
step _counter ++ ;
if ( step _counter <= max _counter ) {
var cost = tsne . step ( ) ;
cost _each = cost [ 1 ] ;
for ( var i = 0 ; i < final _dataset . length ; i ++ ) final _dataset [ i ] . cost = cost _each [ i ] ;
$ ( "#cost" ) . html ( "Number of Iteration: " + tsne . iter + ", Overall Cost: " + cost [ 0 ] . toFixed ( 3 ) ) ;
}
else {
clearInterval ( runner ) ;
}
if ( step _counter == max _counter ) {
updateEmbedding ( ) ;
}
step _counter ++ ;
if ( step _counter <= max _counter ) {
cost = tsne . step ( ) ;
cost _each = cost [ 1 ] ;
for ( var i = 0 ; i < final _dataset . length ; i ++ ) final _dataset [ i ] . cost = cost _each [ i ] ;
$ ( "#cost" ) . html ( "Number of Iteration: " + tsne . iter + ", Overall Cost: " + cost [ 0 ] . toFixed ( 3 ) ) ;
}
else {
clearInterval ( runner ) ;
}
if ( step _counter == max _counter ) {
updateEmbedding ( AnalaysisResults ) ;
}
}
function resize ( canvas ) {
@ -1092,7 +1264,7 @@ function CalculateCorrel(){
if ( flag == false ) {
alert ( "Please, draw a schema first!" ) ;
} else {
var correlLimit = document . getElementById ( "param-corr-value" ) . value ;
var correlLimit = document . getElementById ( "param-corr-value" ) . value ;
correlLimit = parseInt ( correlLimit ) ;
allTransformPoints = [ ] ;
@ -1224,7 +1396,6 @@ function CalculateCorrel(){
var SignStore = [ ] ;
correlationResults = [ ] ;
const arrayColumn = ( arr , n ) => arr . map ( x => x [ n ] ) ;
for ( var temp = 0 ; temp < ArrayContainsDataFeaturesLimit [ 0 ] . length - 2 ; temp ++ ) {
var tempData = new Array (
@ -1577,7 +1748,7 @@ function brushmove() {
//Create a gradient
function createGradient ( idName , endPerc ) {
var colorsBarChart = [ '#7f3b08' , '#b35806' , '#e08214' , '#fdb863' , '#fee0b6' , '#d8daeb' , '#b2abd2' , '#8073ac' , '#542788' , '#2d004b' ]
var colorsBarChart = [ '#67001f' , '#b2182b' , '#d6604d' , '#f4a582' , '#fddbc7' , '#d1e5f0' , '#92c5de' , '#4393c3' , '#2166ac' , '#053061' ] ;
colorsBarChart . reverse ( ) ;
@ -2059,8 +2230,8 @@ function BetatSNE(points){
var ColSizeSelector = document . getElementById ( "param-neighborHood" ) . value ;
if ( ColSizeSelector == "color" ) {
var max = ( d3 . max ( final _dataset , function ( d ) { return d . beta ; } ) ) ;
var min = ( d3 . min ( final _dataset , function ( d ) { return d . beta ; } ) ) ;
var max = ( d3 . max ( points , function ( d ) { return d . beta ; } ) ) ;
var min = ( d3 . min ( points , function ( d ) { return d . beta ; } ) ) ;
// colors
var colorbrewer = [ "#ffffcc" , "#ffeda0" , "#fed976" , "#feb24c" , "#fd8d3c" , "#fc4e2a" , "#e31a1c" , "#bd0026" , "#800026" ] ;
var calcStep = ( max - min ) / 7 ;
@ -2068,11 +2239,11 @@ function BetatSNE(points){
. domain ( d3 . range ( 0 , max + calcStep , calcStep ) )
. range ( colorbrewer ) ;
var maxSize1 = ( d3 . max ( final _dataset , function ( d ) { return d . cost ; } ) ) ;
var minSize1 = ( d3 . min ( final _dataset , function ( d ) { return d . cost ; } ) ) ;
var maxSize1 = ( d3 . max ( points , function ( d ) { return d . cost ; } ) ) ;
var minSize1 = ( d3 . min ( points , function ( d ) { return d . cost ; } ) ) ;
var rscale1 = d3 . scaleLinear ( )
. domain ( [ minSize1 , maxSize1 ] )
. range ( [ 3 , 10 ] ) ;
. range ( [ 5 , 12 ] ) ;
var colorScale = d3 . scaleLinear ( )
. domain ( d3 . range ( 0 , max + calcStep , calcStep ) )
@ -2103,14 +2274,14 @@ function BetatSNE(points){
svg . select ( ".legendLinear" )
. call ( legend ) ;
} else {
var max = ( d3 . max ( final _dataset , function ( d ) { return d . cost ; } ) ) ;
var min = ( d3 . min ( final _dataset , function ( d ) { return d . cost ; } ) ) ;
var max = ( d3 . max ( points , function ( d ) { return d . cost ; } ) ) ;
var min = ( d3 . min ( points , function ( d ) { return d . cost ; } ) ) ;
var maxSize2 = ( d3 . max ( final _dataset , function ( d ) { return d . beta ; } ) ) ;
var minSize2 = ( d3 . min ( final _dataset , function ( d ) { return d . beta ; } ) ) ;
var maxSize2 = ( d3 . max ( points , function ( d ) { return d . beta ; } ) ) ;
var minSize2 = ( d3 . min ( points , function ( d ) { return d . beta ; } ) ) ;
var rscale2 = d3 . scaleLinear ( )
. domain ( [ minSize2 , maxSize2 ] )
. range ( [ 3 , 10 ] ) ;
. range ( [ 5 , 12 ] ) ;
var colorbrewer = [ "#ffffe5" , "#f7fcb9" , "#d9f0a3" , "#addd8e" , "#78c679" , "#41ab5d" , "#238443" , "#006837" , "#004529" ] ;
var calcStep = ( max - min ) / 9 ;
@ -2189,13 +2360,14 @@ clearThree(scene);
var limitdist = document . getElementById ( "param-lim-value" ) . value ;
limitdist = parseFloat ( limitdist ) . toFixed ( 1 ) ;
let pointsMaterial = [ ] ;
let pointsMaterial ;
let factorPlusSize ;
let pointsGeometry = [ ] ;
let geometry = new THREE . Geometry ( ) ;
for ( var i = 0 ; i < points . length ; i ++ ) {
pointsGeometry [ i ] = new THREE . Geometry ( ) ;
let pointsGeometry = new THREE . Geometry ( ) ;
let vertex = new THREE . Vector3 ( ( ( ( points [ i ] . x / dimensions ) * 2 ) - 1 ) * dimensions , ( ( ( points [ i ] . y / dimensions ) * 2 ) - 1 ) * dimensions * - 1 , 0 ) ;
pointsGeometry [ i ] . vertices . push ( vertex ) ;
pointsGeometry . vertices . push ( vertex ) ;
geometry . vertices . push ( vertex ) ;
if ( points [ i ] . selected == false ) {
var color = new THREE . Color ( "rgb(211, 211, 211)" ) ;
} else if ( points [ i ] . DimON != null ) {
@ -2223,8 +2395,8 @@ for (var i=0; i<points.length; i++) {
if ( ColSizeSelector == "color" ) {
let sizePoint = rscale1 ( points [ i ] . cost ) ;
factorPlusSize = limitdist * sizePoint ;
pointsGeometry [ i ] . colors . push ( color ) ;
pointsMaterial [ i ] = new THREE . PointsMaterial ( {
pointsGeometry . colors . push ( color ) ;
pointsMaterial = new THREE . PointsMaterial ( {
sizeAttenuation : false ,
size : Number ( factorPlusSize . toFixed ( 1 ) ) ,
vertexColors : THREE . VertexColors ,
@ -2234,8 +2406,8 @@ for (var i=0; i<points.length; i++) {
} else {
let sizePoint = rscale2 ( points [ i ] . beta ) ;
factorPlusSize = limitdist * sizePoint ;
pointsGeometry [ i ] . colors . push ( color ) ;
pointsMaterial [ i ] = new THREE . PointsMaterial ( {
pointsGeometry . colors . push ( color ) ;
pointsMaterial = new THREE . PointsMaterial ( {
sizeAttenuation : false ,
size : Number ( factorPlusSize . toFixed ( 1 ) ) ,
vertexColors : THREE . VertexColors ,
@ -2243,8 +2415,8 @@ for (var i=0; i<points.length; i++) {
transparent : true
} ) ;
}
console . log ( Number ( factorPlusSize . toFixed ( 1 ) ) ) ;
var particles = new THREE . Points ( pointsGeometry [ i ] , pointsMaterial [ i ] ) ;
var particlesDuplic = new THREE . Points ( geometry , pointsMaterial ) ;
var particles = new THREE . Points ( pointsGeometry , pointsMaterial ) ;
scene . add ( particles ) ;
}
@ -2386,7 +2558,7 @@ function mouseToThree(mouseX, mouseY) {
function checkIntersects ( mouse _position ) {
let mouse _vector = mouseToThree ( ... mouse _position ) ;
raycaster . setFromCamera ( mouse _vector , camera ) ;
let intersects = raycaster . intersectObject ( particles ) ;
let intersects = raycaster . intersectObject ( particlesDuplic ) ;
if ( intersects [ 0 ] ) {
if ( ColSizeSelector == "color" ) {
points = points . sort ( function ( a , b ) {
@ -2556,4 +2728,39 @@ function hideTooltip() {
viewPortHeight = document . getElementsByTagName ( 'body' ) [ 0 ] . clientHeight
}
return [ viewPortWidth , viewPortHeight ] ;
}
}
function download ( contentP , Parameters , fileName , contentType ) {
var a = document . createElement ( "a" ) ;
var file = new Blob ( [ contentP ] , { type : contentType } ) ;
a . href = URL . createObjectURL ( file ) ;
a . download = fileName ;
a . click ( ) ;
}
var measureSaves = 0 ;
function SaveAnalysis ( ) {
measureSaves = measureSaves + 1 ;
let dataset = document . getElementById ( "param-dataset" ) . value ;
let perplexity = document . getElementById ( "param-perplexity-value" ) . value ;
let learningRate = document . getElementById ( "param-learningrate-value" ) . value ;
let IterValue = document . getElementById ( "param-maxiter-value" ) . value ;
let parDist = document . getElementById ( "param-distance" ) . value ;
let parTrans = document . getElementById ( "param-transform" ) . value ;
let Parameters = [ ] ;
Parameters . push ( dataset ) ;
Parameters . push ( perplexity ) ;
Parameters . push ( learningRate ) ;
Parameters . push ( IterValue ) ;
Parameters . push ( parDist ) ;
Parameters . push ( parTrans ) ;
AllData = [ ] ;
if ( cost [ 0 ] != undefined ) {
AllData = points . concat ( points2d ) . concat ( cost [ 0 ] . toFixed ( 3 ) ) . concat ( Parameters ) ;
} else {
AllData = points . concat ( points2d ) . concat ( overallCost ) . concat ( Parameters ) ;
}
download ( JSON . stringify ( AllData ) , JSON . stringify ( Parameters ) , 'Analysis' + measureSaves + '.txt' , 'text/plain' ) ;
}
