ISOVIS
/
t-viSNE
8
0
Fork 0
Code Issues Pull Requests Releases 2 Wiki Activity

SIze legend

Browse Source
Angelos Chatzimparmpas 5 years ago
parent 749399cb9a
commit 7c7ec049f9
3 changed files with 165 additions and 83 deletions
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Show Stats Download Patch File Download Diff File
  1. 13
      css/style.css
  2. 12
      index.html
  3. 223
      js/tsne_vis.js

13
css/style.css
Unescape View File

@ -194,6 +194,9 @@ cursor: default;
z-index: 2;
}
circle.swatch{
opacity: 0.5;
}
/* Legend of the Overview t-SNE canvas */
#legend2 {
@ -213,9 +216,17 @@ cursor: default;
#legend1 {
height: 11vw;
width: 5vw;
margin-left:-8px;
margin-left:-10px;
text-align: left;
}
/* Legend of the Overview t-SNE canvas */
#legend4 {
height: 7vw;
width: 5vw;
margin-top:-80px;
margin-left:-10px;
text-align: left;
}
/* Styling of the ShepardHeatmap */
#sheparheat {

12
index.html
Unescape View File

@ -61,7 +61,7 @@
<div id="control-panel" class="PoinRadius">
<div class="param">
<label for="param-lim" >Points radius scaling factor</label>
<input id="param-lim" type="range" min="1" max="4" value="3", step="0.5" onchange="setReInitialize(true);">
<input id="param-lim" type="range" min="1" max="3" value="3", step="0.5" onchange="setReInitialize(true);">
<output for="param-lim" id="param-lim-value" >3</output>
</div>
</div>
@ -77,6 +77,7 @@
</div>
<div class="col-md-1" style="width: 3.499999995%">
<svg id="legend1"></svg>
<svg id="legend4"></svg>
</div>
<div class="col-md-2" style="width: 21.499999995%">
<div class="panel panel-default">
@ -150,12 +151,9 @@
<option value="breast-cancer-wisconsin.csv">Breast Cancer Wisconsin</option>
<option value="iris.csv">Iris</option>
<option value="winequality-red.csv">Red Wine - Quality</option>
<option value="bank-additional_s.csv">Bank Marketing</option>
<option value="mnist.csv" >Mnist</option>
<option value="Frogs_MFCCs_s.csv" >Frogs</option>
<option value="empty">Upload New File</option>
</select>
<button type="button" class="button" id="FactRes" onclick="FactoryReset()">Factory reset</button>
<button type="button" class="button" id="FactRes" onclick="FactoryReset()">Factory Reset</button>
</div>
<div class="param">
<label for="param-perplexity">Perplexity</label>
@ -277,8 +275,8 @@
<script>
$("#cost").html('(Unknown iteration and cost values.)');
$("#datasetDetails").html('(Unknown number of features and instances.)');
$("#cost").html('(Unknown Iteration and Cost Values.)');
$("#datasetDetails").html('(Unknown Number of Features and Instances.)');
$("#CategoryName").html('No Classification');
$("#knnBarChartDetails").html('(Number of Selected Points: 0/0)');
/* This script is used in order to give functionalities to the different buttons provide through the front-end. */

223
js/tsne_vis.js
Unescape View File

@ -12,7 +12,7 @@ var final_dataset; var points = []; var cost = []; var cost_each; var beta_all =
var ArrayContainsDataFeaturesCleared = []; var ArrayContainsDataFeaturesClearedwithoutNull = []; var ArrayContainsDataFeaturesClearedwithoutNullKeys = []; var flagAnalysis = false;
// The distances in the high dimensional space and in the 2D space. All the labels that were found in the selected data set.
var dists; var dists2d; var all_labels; var dist_list = []; var dist_list2d = []; var InitialFormDists = []; var InitialFormDists2D = [];
var dists; var dists2d; var all_labels; var dist_list = []; var dist_list2d = []; var InitialFormDists = []; var InitialFormDists2D = []; var IterationsList = []; var ArrayWithCostsList = [];
// These are the dimensions for the Overview view and the Main view
var dim = document.getElementById('overviewRect').offsetWidth-2; var dimensions = document.getElementById('modtSNEcanvas').offsetWidth;
@ -113,13 +113,13 @@ var getData = function() {
// Load an analysis and parse the previous points and parameters information.
AnalysisResults = JSON.parse(lines);
var length = (AnalysisResults.length - 7);
var length = (AnalysisResults.length - 9);
ParametersSet = AnalysisResults.slice(length+1, AnalysisResults.length+7)
value = ParametersSet[0];
if (!isNaN(parseInt(value))){
flagAnalysis = true;
length = (AnalysisResults.length - 9);
length = (AnalysisResults.length - 11);
ParametersSet = AnalysisResults.slice(length+1, length+7);
value = ParametersSet[0];
@ -208,6 +208,7 @@ function setContinue(){ // This function allows the continuation of the analysis
function setReset(){ // Reset only the filters which were applied into the data points.
VisiblePoints = [];
emptyPCP();
// Clear d3 SVGs
d3.selectAll("#correlation > *").remove();
@ -502,11 +503,6 @@ function init(data, results_all, fields) {
d3.select("#hider2").style("z-index", 2);
d3.select("#PlotCost").style("z-index", 1);
// Clear the previous t-SNE overview canvas.
/*var oldcanvOver = document.getElementById('tSNEcanvas');
var contxOver = oldcanvOver.getContext('experimental-webgl');
contxOver.clear(contxOver.COLOR_BUFFER_BIT);*/
// Clear the previously drawn main visualization canvas.
scene = new THREE.Scene();
scene.background = new THREE.Color(0xffffff);
@ -515,8 +511,9 @@ function init(data, results_all, fields) {
d3.selectAll("#legend1 > *").remove();
d3.selectAll("#legend2 > *").remove();
d3.selectAll("#legend3 > *").remove();
d3.selectAll("#legend4 > *").remove();
$("#datasetDetails").html('(Unknown number of features and instances.)');
$("#datasetDetails").html('(Unknown Number of Features and Instances.)');
$("#CategoryName").html('No Classification');
$("#knnBarChartDetails").html('(Number of Selected Points: 0/0)');
@ -844,10 +841,9 @@ function updateEmbedding(AnalysisResults) {
points[i] = extend(points[i], ArrayContainsDataFeaturesCleared[i]);
points[i] = extend(points[i], dataFeatures[i]);
}
OverallCostLineChart();
} else{
if (flagAnalysis){
var length = (AnalysisResults.length - dataFeatures.length*2 - 7 - 2);
var length = (AnalysisResults.length - dataFeatures.length*2 - 9 - 2);
points = AnalysisResults.slice(0, dataFeatures.length); // Load the points from the previous analysis
points2d = AnalysisResults.slice(dataFeatures.length, 2*dataFeatures.length); // Load the 2D points
dist_list = AnalysisResults.slice(2*dataFeatures.length, 2*dataFeatures.length+length/2); // Load the parameters and set the necessary values to the visualization of those parameters.
@ -856,6 +852,10 @@ function updateEmbedding(AnalysisResults) {
ParametersSet = AnalysisResults.slice(2*dataFeatures.length+length+1, 2*dataFeatures.length+length+7); // Load the parameters and set the necessary values to the visualization of those parameters.
dists = AnalysisResults.slice(2*dataFeatures.length+length+7, 2*dataFeatures.length+length+8)[0]; // Load the parameters and set the necessary values to the visualization of those parameters.
dists2d = AnalysisResults.slice(2*dataFeatures.length+length+8, 2*dataFeatures.length+length+9)[0]; // Load the parameters and set the necessary values to the visualization of those parameters.
IterationsList = AnalysisResults.slice(2*dataFeatures.length+length+9, 2*dataFeatures.length+length+10);
ArrayWithCostsList = AnalysisResults.slice(2*dataFeatures.length+length+10, 2*dataFeatures.length+length+11);
Iterations = IterationsList[0];
ArrayWithCosts = ArrayWithCostsList[0];
$("#cost").html("(Number of Iteration: " + ParametersSet[3] + ", Overall Cost: " + overallCost + ")");
$('#param-perplexity-value').text(ParametersSet[1]);
$('#param-learningrate-value').text(ParametersSet[2]);
@ -863,11 +863,15 @@ function updateEmbedding(AnalysisResults) {
document.getElementById("param-distance").value = ParametersSet[4];
document.getElementById("param-transform").value = ParametersSet[5];
} else{
var length = (AnalysisResults.length - 7) / 2;
var length = (AnalysisResults.length - 9) / 2;
points = AnalysisResults.slice(0, length); // Load the points from the previous analysis
points2d = AnalysisResults.slice(length, 2*length); // Load the 2D points
overallCost = AnalysisResults.slice(2*length, 2*length+1); // Load the overall cost
ParametersSet = AnalysisResults.slice(2*length+1, 2*length+7); // Load the parameters and set the necessary values to the visualization of those parameters.
IterationsList = AnalysisResults.slice(2*length+7, 2*length+8);
ArrayWithCostsList = AnalysisResults.slice(2*length+8, 2*length+9);
Iterations = IterationsList[0];
ArrayWithCosts = ArrayWithCostsList[0];
$("#cost").html("(Number of Iteration: " + ParametersSet[3] + ", Overall Cost: " + overallCost + ")");
$('#param-perplexity-value').text(ParametersSet[1]);
$('#param-learningrate-value').text(ParametersSet[2]);
@ -878,6 +882,8 @@ function updateEmbedding(AnalysisResults) {
$("#data").html(ParametersSet[0]); // Print on the screen the classification label.
$("#param-dataset").html('-');
}
OverallCostLineChart(); // Cost plot
InitialStatePoints = points; // Initial Points will not be modified!
function extend(obj, src) { // Call this function to add additional information to the points such as dataFeatures and Array which contains the data features without strings.
@ -1101,6 +1107,8 @@ function step() {
clearInterval(runner);
}
if (step_counter == max_counter){
ArrayWithCostsList.push(ArrayWithCosts);
IterationsList.push(Iterations);
updateEmbedding(AnalysisResults);
}
}
@ -1270,7 +1278,6 @@ function CostHistogram(points){
for (var i=0; i<points.length; i++){
frequency2.push((points[i].beta-min2)/(max2-min2));
}
var trace1 = {
x: frequency2,
name: '1/sigma',
@ -1285,7 +1292,7 @@ function CostHistogram(points){
opacity: 0.5,
type: "histogram",
xbins: {
end: 1,
end: 1.01,
size: 0.01,
start: 0
}
@ -1293,11 +1300,9 @@ function CostHistogram(points){
var max = (d3.max(points,function(d){ return d.cost; }));
var min = (d3.min(points,function(d){ return d.cost; }));
for (var i=0; i<points.length; i++){
frequency.push((points[i].cost-min)/(max-min));
}
var trace2 = {
x: frequency,
name: 'KLD(P||Q)',
@ -1313,7 +1318,7 @@ function CostHistogram(points){
opacity: 0.5,
type: "histogram",
xbins: {
end: 1,
end: 1.01,
size: 0.01,
start: 0
}
@ -1333,7 +1338,7 @@ function CostHistogram(points){
t: 10,
pad: 4
},
xaxis:{range: [0,1],title: 'Normalized Bins from Min to Max Values.',
xaxis:{range: [0,1.01],title: 'Normalized Bins from Min to Max Values.',
titlefont: {
size: 14,
color: 'black'
@ -1398,7 +1403,7 @@ function emptyPCP(){
var parcoords = d3v3.parcoords()("#PCP")
.data(wrapData)
.composite("darken")
.margin({ top: 20, left: 0, bottom: 5, right: 0 })
.margin({ top: 20, left: 0, bottom: 10, right: 0 })
.mode("queue")
.color(function(d, i) { return colorScl(IDS[i]); })
.render()
@ -2273,29 +2278,6 @@ var margin = {top: 40, right: 100, bottom: 40, left: 190}, // Set the margins fo
width = Math.min(vw3, window.innerWidth - 10) - margin.left - margin.right,
height = Math.min(width, window.innerHeight - margin.top - margin.bottom);
/*function pcpInitialize() {
var wrapData = [];
var radarChartOptions = { // pcp options
w: width,
h: height,
margin: margin,
maxValue: 100,
roundStrokes: true
};
var colors;
var IDS = [];
//////////////////////////////////////////////////////////////
//////////////////// Draw the Chart //////////////////////////
//////////////////////////////////////////////////////////////
//Call function to draw the Radar chart (pcp)
RadarChart("#PCP", wrapData, colors, IDS, radarChartOptions);
}*/
//pcpInitialize();
function BetatSNE(points){ // Run the main visualization
inside = inside + 1;
if (points.length) { // If points exist (at least 1 point)
@ -2321,7 +2303,7 @@ if (points.length) { // If points exist (at least 1 point)
var vw = viewport[0] * 0.5;
var vh = viewport[1] * 0.042;
var maxKNN = document.getElementById("param-perplexity-value").value; // Specify the amount of k neighborhoods that we are going to calculate. According to "perplexity."
var maxKNN = Math.round(document.getElementById("param-perplexity-value").value*1.25); // Specify the amount of k neighborhoods that we are going to calculate. According to "perplexity."
//var maxKNN = 3;
selectedPoints.sort(function(a, b) { // Sort the points according to ID.
return parseFloat(a.id) - parseFloat(b.id);
@ -2361,7 +2343,6 @@ if (points.length) { // If points exist (at least 1 point)
}
return 0;
});
indexOrder[i] = indices[i].map(function(value) { return value[0]; });
// Sorting the mapped array containing the reduced values
indices2d[i].sort(function(a, b) {
@ -2373,7 +2354,6 @@ if (points.length) { // If points exist (at least 1 point)
}
return 0;
});
indexOrder2d[i] = indices2d[i].map(function(value) { return value[0]; });
}
indexOrderSliced[i] = indexOrder[i].slice(0,k);
@ -2570,7 +2550,7 @@ if (points.length) { // If points exist (at least 1 point)
.alpha(0.1)
.hideAxis(["ID"])
.composite("darken")
.margin({ top: 20, left: 0, bottom: 5, right: -5 })
.margin({ top: 20, left: 0, bottom: 10, right: -5 })
.mode("default")
.color(color)
.render()
@ -2647,15 +2627,14 @@ if (points.length) { // If points exist (at least 1 point)
}
var colorScaleCat = d3.scaleOrdinal().domain(all_labels).range(ColorsCategorical);
}
console.log(wrapData2);
parcoords
.data(AllPointsWrapData2)
.alpha(0.95)
.composite("darken")
.margin({ top: 20, left: 0, bottom: 5, right: -5 })
.margin({ top: 20, left: 0, bottom: 10, right: -5 })
.mode("default")
.color(function(d){if(format[0] == "diabetes"){if(d[Category] == "Negative"){return colorScaleCat("Positive");}else{return colorScaleCat("Negative");}} else{console.log(d[Category]);return colorScaleCat(d[Category]);}})
.color(function(d){if(format[0] == "diabetes"){if(d[Category] == "Negative"){return colorScaleCat("Positive");}else{return colorScaleCat("Negative");}} else{return colorScaleCat(d[Category]);}})
.render()
.highlight(wrapData2)
.createAxes();
@ -2666,22 +2645,35 @@ if (points.length) { // If points exist (at least 1 point)
var ColSizeSelector = document.getElementById("param-neighborHood").value; // This is the mapping of the color/size in beta/KLD
d3.selectAll("#legend4 > *").remove();
if (ColSizeSelector == "color") { // If we have beta into color then calculate the color scales
var max = (d3.max(points,function(d){ return d.beta; }));
var min = (d3.min(points,function(d){ return d.beta; }));
// colors
var colorbrewer = ["#fed976","#feb24c","#fd8d3c","#fc4e2a","#e31a1c","#bd0026","#800026"];
var calcStep = (max-min)/5;
var colorbrewer = ["#ffffcc","#ffeda0","#fed976","#feb24c","#fd8d3c","#fc4e2a","#e31a1c","#bd0026","#800026"];
var calcStep = (max)/8;
var colorScale = d3.scaleLinear()
.domain(d3.range(0, max+calcStep, calcStep))
.range(colorbrewer);
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([5,parseInt(12-(1-document.getElementById("param-costlim").value)*7)]);
var calcStepSize1 = (maxSize1-minSize1);
var limitdist = document.getElementById("param-lim-value").value;
limitdist = parseFloat(limitdist).toFixed(1);
var legendScale1 = d3.scaleLinear()
.domain(d3.range(minSize1, maxSize1+calcStepSize1, calcStepSize1))
.range([5*limitdist/2,(parseInt(12-(1-document.getElementById("param-costlim").value)*7))*limitdist/2]);
var colorScale = d3.scaleLinear()
.domain(d3.range(0, max+calcStep, calcStep))
.range(colorbrewer);
@ -2690,8 +2682,9 @@ if (points.length) { // If points exist (at least 1 point)
})
var labels_beta = [];
var abbr_labels_beta = [];
var calcStep = (max)/8;
labels_beta = d3.range(0, max+calcStep, calcStep);
for (var i=0; i<7; i++){
for (var i=0; i<9; i++){
labels_beta[i] = parseInt(labels_beta[i]);
abbr_labels_beta[i] = abbreviateNumber(labels_beta[i]);
}
@ -2703,20 +2696,55 @@ if (points.length) { // If points exist (at least 1 point)
var legend = d3.legendColor()
.labelFormat(d3.format(",.0f"))
.cells(7)
.labels([abbr_labels_beta[0],abbr_labels_beta[1],abbr_labels_beta[2],abbr_labels_beta[3],abbr_labels_beta[4],abbr_labels_beta[5],abbr_labels_beta[6]])
.cells(9)
.labels([abbr_labels_beta[0],abbr_labels_beta[1],abbr_labels_beta[2],abbr_labels_beta[3],abbr_labels_beta[4],abbr_labels_beta[5],abbr_labels_beta[6],abbr_labels_beta[7],abbr_labels_beta[8]])
.title("1/sigma")
.scale(colorScale);
svg.select(".legendLinear")
.call(legend);
var svg = d3.select("#legend4");
svg.append("g")
.attr("class", "legendSize")
.attr("transform", "translate(10,20)");
var SizeRange1 = [];
SizeRange1.push((minSize1).toFixed(3));
SizeRange1.push(((maxSize1-minSize1)/2).toFixed(3));
SizeRange1.push((maxSize1).toFixed(3));
var legendSize1 = d3.legendSize()
.scale(legendScale1)
.labelFormat(d3.format(",.5f"))
.cells(3)
.shape('circle')
.labels([SizeRange1[0],SizeRange1[1],SizeRange1[2]])
.shapePadding(10)
.labelOffset(5)
.title("KLD(P||Q)")
.orient('vertical');
svg.select(".legendSize")
.call(legendSize1);
var circles = document.getElementsByClassName("swatch");
for (var i=0; i<circles.length; i++){
if(circles[i].localName == "circle"){
circles[i].style.fill = "rgb(0,128,0)";
}
}
} else { // If we have cost into color then calculate the color scales
var max = (d3.max(points,function(d){ return d.cost; }));
var min = (d3.min(points,function(d){ return d.cost; }));
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])
.domain([0, maxSize2])
.range([5,12]);
d3.selectAll("#legend1 > *").remove();
@ -2741,10 +2769,11 @@ if (points.length) { // If points exist (at least 1 point)
svg.select(".legendOrdinal")
.call(legendOrdinal);
} else{
var colorbrewer = ['#d9f0a3','#addd8e','#78c679','#41ab5d','#238443','#006837','#004529'];
var calcStep = (max-min)/7;
var calcStep = (max-min)/6;
var colorScale = d3.scaleLinear()
.domain(d3.range(min, max, calcStep))
.domain(d3.range(min, max+calcStep, calcStep))
.range(colorbrewer);
points = points.sort(function(a, b) { // Sort them according to importance (darker color!)
@ -2753,7 +2782,7 @@ if (points.length) { // If points exist (at least 1 point)
var labels_cost = [];
var abbr_labels_cost = [];
labels_cost = d3.range(min, max, calcStep);
labels_cost = d3.range(min, max+calcStep, calcStep);
for (var i=0; i<7; i++){
labels_cost[i] = labels_cost[i].toFixed(5);
abbr_labels_cost[i] = abbreviateNumber(labels_cost[i]);
@ -2774,8 +2803,54 @@ if (points.length) { // If points exist (at least 1 point)
svg.select(".legendLinear")
.call(legend);
}
var calcStepSize2 = parseInt(maxSize2/2);
var limitdist = document.getElementById("param-lim-value").value;
limitdist = parseFloat(limitdist).toFixed(1);
var legendScale2 = d3.scaleLinear()
.domain(d3.range(0, abbreviateNumber(parseInt(maxSize2)), calcStepSize2))
.range([5*limitdist/2,12*limitdist/2]);
var svg = d3.select("#legend4");
svg.append("g")
.attr("class", "legendSize")
.attr("transform", "translate(10,20)");
var SizeRange2 = [];
SizeRange2.push(0);
var temporalvalue = parseInt(maxSize2/2);
SizeRange2.push(abbreviateNumber(temporalvalue));
SizeRange2.push(abbreviateNumber(parseInt(maxSize2)));
var legendSize2 = d3.legendSize()
.scale(legendScale2)
.labelFormat(d3.format(",.0f"))
.cells(3)
.shape('circle')
.labels([SizeRange2[0],SizeRange2[1],SizeRange2[2]])
.shapePadding(10)
.labelOffset(5)
.title("1/sigma")
.orient('vertical');
svg.select(".legendSize")
.call(legendSize2);
var circles = document.getElementsByClassName("swatch");
console.log(circles);
for (var i=0; i<circles.length; i++){
if(circles[i].localName == "circle"){
console.log("test");
circles[i].style.fill = "rgb(128,0,0)";
}
}
}
@ -2860,8 +2935,8 @@ if (points.length) { // If points exist (at least 1 point)
var maxDim = (d3.max(points,function(d){ if(d.schemaInv == true){return d[temp]}; }));
var minDim = (d3.min(points,function(d){ if(d.schemaInv == true){return d[temp]}; }));
let colorsBarChart = ['#efedf5','#dadaeb','#bcbddc','#9e9ac8','#807dba','#6a51a3','#54278f','#3f007d'];
var calcStepDim = (maxDim-minDim)/8;
let colorsBarChart = ['#dadaeb','#bcbddc','#9e9ac8','#807dba','#6a51a3','#54278f','#3f007d'];
var calcStepDim = (maxDim-minDim)/6;
var colorScale = d3.scaleLinear()
.domain(d3.range(minDim, maxDim+calcStepDim, calcStepDim))
.range(colorsBarChart);
@ -2952,8 +3027,8 @@ if (points.length) { // If points exist (at least 1 point)
var legend = d3.legendColor()
.labelFormat(d3.format(",.0f"))
.cells(7)
.labels([abbr_labels_beta[0],abbr_labels_beta[1],abbr_labels_beta[2],abbr_labels_beta[3],abbr_labels_beta[4],abbr_labels_beta[5],abbr_labels_beta[6]])
.cells(9)
.labels([abbr_labels_beta[0],abbr_labels_beta[1],abbr_labels_beta[2],abbr_labels_beta[3],abbr_labels_beta[4],abbr_labels_beta[5],abbr_labels_beta[6],abbr_labels_beta[7],abbr_labels_beta[8]])
.title("1/sigma")
.scale(colorScale);
@ -2963,11 +3038,9 @@ if (points.length) { // If points exist (at least 1 point)
} else {
var max = (d3.max(points,function(d){ return d.cost; }));
var min = (d3.min(points,function(d){ return d.cost; }));
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([5,12]);
d3.selectAll("#legend1 > *").remove();
@ -2991,9 +3064,9 @@ if (points.length) { // If points exist (at least 1 point)
.call(legendOrdinal);
} else{
var colorbrewer = ["#d9f0a3","#addd8e","#78c679","#41ab5d","#238443","#006837","#004529"];
var calcStep = (max-min)/7;
var calcStep = (max-min)/6;
var colorScale = d3.scaleLinear()
.domain(d3.range(min, max, calcStep))
.domain(d3.range(min, max+calcStep, calcStep))
.range(colorbrewer);
points = points.sort(function(a, b) { // Sort them according to importance (darker color!)
@ -3002,7 +3075,7 @@ if (points.length) { // If points exist (at least 1 point)
var labels_cost = [];
var abbr_labels_cost = [];
labels_cost = d3.range(min, max, calcStep);
labels_cost = d3.range(min, max+calcStep, calcStep);
for (var i=0; i<7; i++){
labels_cost[i] = labels_cost[i].toFixed(5);
abbr_labels_cost[i] = abbreviateNumber(labels_cost[i]);
@ -3016,7 +3089,7 @@ if (points.length) { // If points exist (at least 1 point)
var legend = d3.legendColor()
.labelFormat(d3.format(",.5f"))
.cells(7)
.labels([abbr_labels_cost[0],abbr_labels_cost[1],abbr_labels_cost[2],abbr_labels_cost[3],abbr_labels_cost[4],abbr_labels_cost[5],abbr_labels_cost[6],abbr_labels_cost[7],abbr_labels_cost[8]])
.labels([abbr_labels_cost[0],abbr_labels_cost[1],abbr_labels_cost[2],abbr_labels_cost[3],abbr_labels_cost[4],abbr_labels_cost[5],abbr_labels_cost[6]])
.title("KLD(P||Q)")
.scale(colorScale);
@ -3296,16 +3369,16 @@ function SaveAnalysis(){ // Save the analysis into a .txt file
Parameters.push(parTrans);
AllData = [];
if (cost[0] != undefined){
if (!returnVal){
AllData = points.concat(points2d).concat(dist_list).concat(dist_list2d).concat(cost[0].toFixed(3)).concat(Parameters).concat(InitialFormDists).concat(InitialFormDists2D);
if (!returnVal){ // Add here if you want to save more parameters from a previous execution.
AllData = points.concat(points2d).concat(dist_list).concat(dist_list2d).concat(cost[0].toFixed(3)).concat(Parameters).concat(InitialFormDists).concat(InitialFormDists2D).concat(IterationsList).concat(ArrayWithCostsList);
} else {
AllData = points.concat(points2d).concat(cost[0].toFixed(3)).concat(Parameters);
AllData = points.concat(points2d).concat(cost[0].toFixed(3)).concat(Parameters).concat(IterationsList).concat(ArrayWithCostsList);
}
} else{
if (!returnVal){
AllData = points.concat(points2d).concat(dist_list).concat(dist_list2d).concat(overallCost).concat(Parameters).concat(InitialFormDists).concat(InitialFormDists2D);
AllData = points.concat(points2d).concat(dist_list).concat(dist_list2d).concat(overallCost).concat(Parameters).concat(InitialFormDists).concat(InitialFormDists2D).concat(IterationsList).concat(ArrayWithCostsList);
} else {
AllData = points.concat(points2d).concat(overallCost).concat(Parameters);
AllData = points.concat(points2d).concat(overallCost).concat(Parameters).concat(IterationsList).concat(ArrayWithCostsList);
}
}
download(JSON.stringify(AllData),'Analysis'+measureSaves+'.txt', 'text/plain');

Write Preview
Loading…
Cancel
Save