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b/cachedir/joblib/tsneGrid/trustworthiness/f9e9cadb5964d72ea2ba86b12db6ea8e/output.pkl @@ -0,0 +1 @@ +G?,;. \ No newline at end of file diff --git a/cachedir/joblib/tsneGrid/trustworthiness/fd3fdf0ab8e387facdaa3c973641932c/metadata.json b/cachedir/joblib/tsneGrid/trustworthiness/fd3fdf0ab8e387facdaa3c973641932c/metadata.json new file mode 100644 index 0000000..fea3acc --- /dev/null +++ b/cachedir/joblib/tsneGrid/trustworthiness/fd3fdf0ab8e387facdaa3c973641932c/metadata.json @@ -0,0 +1 @@ +{"duration": 0.017921924591064453, "input_args": {"D_high": "array([[0. , 0.53851648, 0.50990195, ..., 4.45982062, 4.65080638,\n 4.14004831],\n [0.53851648, 0. , 0.3 , ..., 4.49888875, 4.71805044,\n 4.15331193],\n [0.50990195, 0.3 , 0. , ..., 4.66154481, 4.84871117,\n 4.29883705],\n ...,\n [4.27668096, 4.24970587, 4.43057558, ..., 0.58309519, 1.06770783,\n 0.65574385],\n [4.45982062, 4.49888875, 4.66154481, ..., 0. , 0.6164414 ,\n 0.64031242],\n [4.65080638, 4.71805044, 4.84871117, ..., 0.6164414 , 0. 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index bc3c7f6..1b6aa1f 100755 --- a/js/tsne_vis.js +++ b/js/tsne_vis.js @@ -34,7 +34,7 @@ var sliderTrigger = false; var sliderInsideTrigger = false; var parameters; var var inside = 0; var kValuesLegend = []; var findNearestTable = []; var howManyPoints; var maxKNN = 0 -var mode = 1; var colors = ['#00bbbb','#ff7f00','#b15928','#e31a1c','#1f78b4']; var projections = []; var betas = []; var cost_per_point = []; var cost_overall; var metricsSorting = []; var dataReceivedFromServer = []; var dataReceivedFromServerOptimized = []; var metrics = []; var FocusedIDs = []; +var mode = 1; var colors = ['#00bbbb','#b15928','#ff7f00','#e31a1c','#1f78b4']; var projections = []; var betas = []; var cost_per_point = []; var cost_overall; var metricsSorting = []; var dataReceivedFromServer = []; var dataReceivedFromServerOptimized = []; var metrics = []; var FocusedIDs = []; var Category; var target_names = [] @@ -158,7 +158,6 @@ function ReSort(flagInitialize) { document.getElementById("textToChange").innerHTML = "[Sorting Projections According to Metric for Current Selection:"; } } else { - document.getElementById("textToChange").innerHTML = "[Sorting Projections According to Metric for Current Selection:"; if (!globalFlagCheck) { metricsSorting = metricsSortingCopy metrics = metricsCopy @@ -184,7 +183,6 @@ function ReSort(flagInitialize) { for (let i = 0; i < results_all_global.length; i++){ target_names.push(results_all_global[i][Category]) } - const unique = (value, index, self) => { return self.indexOf(value) === index } @@ -311,10 +309,9 @@ if(k >= 6) { return r; }, {}) var Text = []; - var countPrev = 0; - var count = 0; + for (let i = 0; i < uniqueTarget.length; i++) { - count = 0 + /*count = 0 for (let j = 0; j < target_names.length; j++) { Text.push('Perplexity: '+parameters[SelectedProjections[checkCounter]][0]+'; Learning rate: '+parameters[SelectedProjections[checkCounter]][1]+'; Max iterations: '+parameters[SelectedProjections[checkCounter]][2]) @@ -323,11 +320,20 @@ if(k >= 6) { count = count + 1 } - } + }*/ + + const aux_X = result.Xax.filter((item, index) => target_names[index] == uniqueTarget[i]); + const aux_Y = result.Yax.filter((item, index) => target_names[index] == uniqueTarget[i]); + + Text = aux_X.map(() => { + let popup = 'Perplexity: '+parameters[SelectedProjections[checkCounter]][0]+'; Learning rate: '+parameters[SelectedProjections[checkCounter]][1]+'; Max iterations: '+parameters[SelectedProjections[checkCounter]][2]; + return popup; + }); + traces.push({ - x: result.Xax.slice(countPrev,count+countPrev), - y: result.Yax.slice(countPrev,count+countPrev), + x: aux_X, + y: aux_Y, mode: 'markers', showlegend: false, text: Text, @@ -345,7 +351,7 @@ if(k >= 6) { yaxis: 'y'+parseInt(k+1), }) - countPrev = count + countPrev + //countPrev = count + countPrev } checkCounter++; @@ -1008,22 +1014,23 @@ if (optionMetric == 1) { return r; }, {}) var Text = []; - var countPrev = 0; - var count = 0; + + for (let i = 0; i < uniqueTarget.length; i++) { - count = 0 - for (let j = 0; j < target_names.length; j++) { - Text.push('Perplexity: '+parameters[order[checkCounter]][0]+'; Learning rate: '+parameters[order[checkCounter]][1]+'; Max iterations: '+parameters[order[checkCounter]][2]) + const aux_X = result.Xax.filter((item, index) => target_names[index] == uniqueTarget[i]); + const aux_Y = result.Yax.filter((item, index) => target_names[index] == uniqueTarget[i]); - if (uniqueTarget[i] == target_names[j]) { - count = count + 1 - } - } + + Text = aux_X.map(() => { + let popup = 'Perplexity: '+parameters[order[checkCounter]][0]+'; Learning rate: '+parameters[order[checkCounter]][1]+'; Max iterations: '+parameters[order[checkCounter]][2]; + return popup; + }); + if (k == 0) { traces.push({ - x: result.Xax.slice(countPrev,count+countPrev), - y: result.Yax.slice(countPrev,count+countPrev), + x: aux_X, + y: aux_Y, mode: 'markers', name: labelsTarget[i], text: Text, @@ -1040,8 +1047,8 @@ if (optionMetric == 1) { }) } else { traces.push({ - x: result.Xax.slice(countPrev,count+countPrev), - y: result.Yax.slice(countPrev,count+countPrev), + x: aux_X, + y: aux_Y, mode: 'markers', showlegend: false, text: Text, @@ -1059,7 +1066,6 @@ if (optionMetric == 1) { yaxis: 'y'+parseInt(k+1), }) } - countPrev = count + countPrev } checkCounter++; @@ -2909,7 +2915,7 @@ function updateEmbedding(AnalysisResults) { var y = d3.scaleLinear() // Scale the y points into the canvas width/height .domain(maxExt) - .range([10, +dimensionsY-10]); + .range([+dimensionsY-10, 10]); for(var i = 0; i < betas[activeProjectionNumber].length; i++) { x_position[i] = x(Y[i][0]); // x points position