From 655408f595ea50084978f7d62743b4137f121dfa Mon Sep 17 00:00:00 2001 From: Angelos Chatzimparmpas Date: Wed, 22 Jan 2020 14:29:25 +0100 Subject: [PATCH] data space --- __pycache__/run.cpython-37.pyc | Bin 27677 -> 30372 bytes .../metadata.json | 1 - .../output.pkl | Bin 2163893 -> 0 bytes .../metadata.json | 1 - .../output.pkl | Bin 2808020 -> 0 bytes .../run/GridSearchForModels/func_code.py | 2 +- .../src/components/BalancePredictions.vue | 208 ++++++++++++------ frontend/src/components/BarChart.vue | 9 +- frontend/src/components/DataSpace.vue | 108 ++++++++- frontend/src/components/Main.vue | 140 +++++++++++- frontend/src/components/PCPData.vue | 51 +++++ frontend/src/components/Parameters.vue | 66 +++++- frontend/src/components/PredictionsSpace.vue | 4 +- frontend/src/components/ScatterPlot.vue | 2 +- frontend/src/main.js | 4 +- run.py | 132 ++++++++++- 16 files changed, 636 insertions(+), 92 deletions(-) delete mode 100644 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z>G#eK-gJegD?m0)sztSCJfh1a0#cF import { EventBus } from '../main.js' import * as d3Base from 'd3' + import { counter } from '@fortawesome/fontawesome-svg-core' // attach all d3 plugins to the d3 library const d3 = Object.assign(d3Base) @@ -15,19 +16,51 @@ name: 'BalancePredictions', data () { return { - resultsfromOverview: 0, - WH: [] + resultsfromOverview: '', + newResultsFromSelection: '', + responsiveWidthHeight: [] } }, methods: { Balance () { - - // Clear Heatmap first + // erase histogram var svg = d3.select("#my_dataviz"); svg.selectAll("*").remove(); - var widthInitial = this.WH[0]*3 // interactive visualization - var heightInitial = this.WH[1]/1.6 // interactive visualization + // responsive visualizations + var widthInitial = this.responsiveWidthHeight[0]*3 + var heightInitial = this.responsiveWidthHeight[1]/1.6 + + var performancePerModel = JSON.parse(this.resultsfromOverview[0]) + var performancePerModelSelection = [] + if (this.newResultsFromSelection.length != 0) { + var performancePerModelSelection = JSON.parse(this.newResultsFromSelection[0]) + } + var modelId = JSON.parse(this.resultsfromOverview[13]) + var data = [] + + performancePerModel.forEach(element => { + let el = {} + el.type = "variable 1" + el.value = element * 100 + data.push(el) + }) + + if (performancePerModelSelection.length == 0) { + performancePerModel.forEach(element => { + let el = {} + el.type = "variable 2" + el.value = element * 100 + data.push(el) + }) + } else { + performancePerModelSelection.forEach(element => { + let el = {} + el.type = "variable 2" + el.value = element * 100 + data.push(el) + }) + } // set the dimensions and margins of the graph var margin = {top: 10, right: 30, bottom: 50, left: 60}, @@ -43,77 +76,118 @@ .attr("transform", "translate(" + margin.left + "," + margin.top + ")"); - // get the data - d3.csv("https://raw.githubusercontent.com/holtzy/D3-graph-gallery/master/DATA/data_doubleHist.csv").then( function(data) { // add the x Axis var x = d3.scaleLinear() - .domain([-10,15]) + .domain([0,100]) .range([0, width]); svg.append("g") .attr("transform", "translate(0," + height + ")") .call(d3.axisBottom(x)); - // add the first y Axis + // set the parameters for the histogram + var histogram = d3.histogram() + .value(function(d) { return +d.value; }) // I need to give the vector of value + .domain(x.domain()) // then the domain of the graphic + .thresholds(x.ticks(40)); // then the numbers of bins + + // And apply twice this function to data to get the bins. + var bins1 = histogram(data.filter( function(d){return d.type === "variable 1"} )); + var bins2 = histogram(data.filter( function(d){return d.type === "variable 2"} )); + + // Y axis: scale and draw: var y1 = d3.scaleLinear() - .range([height/2, 0]) - .domain([0, 0.12]); + .range([height/2, 0]) + .domain([0, d3.max(bins1, function(d) { return d.length; })]); // d3.hist has to be called before the Y axis obviously svg.append("g") .attr("transform", "translate(-20,0)") - .call(d3.axisLeft(y1).tickValues([0.05, 0.1])); + .call(d3.axisLeft(y1)); - // add the first y Axis + // Y axis: scale and draw: var y2 = d3.scaleLinear() - .range([height/2, height]) - .domain([0, 0.12]); + .range([height/2, height]) + .domain([0, d3.max(bins2, function(d) { return d.length; })]); // d3.hist has to be called before the Y axis obviously svg.append("g") .attr("transform", "translate(-20,0)") - .call(d3.axisLeft(y2).ticks(2).tickSizeOuter(0)); - - // Compute kernel density estimation - var kde = kernelDensityEstimator(kernelEpanechnikov(7), x.ticks(60)) - var density1 = kde( data.filter( function(d){return d.type === "variable 1"} ).map(function(d){ return d.value; }) ) - var density2 = kde( data.filter( function(d){return d.type === "variable 2"} ).map(function(d){ return d.value; }) ) - - // Plot the area - svg.append("path") - .attr("class", "mypath") - .datum(density1) - .attr("fill", "#000") - .attr("opacity", "1") - .attr("stroke", "#000") - .attr("stroke-width", 1) - .attr("stroke-linejoin", "round") - .attr("d", d3.line() - .curve(d3.curveBasis) - .x(function(d) { return x(d[0]); }) - .y(function(d) { return y1(d[1]); }) - ); - - // Plot the area - svg.append("path") - .attr("class", "mypath") - .datum(density2) - .attr("fill", "#D3D3D3") - .attr("opacity", "1") - .attr("stroke", "#000") - .attr("stroke-width", 1) - .attr("stroke-linejoin", "round") - .attr("d", d3.line() - .curve(d3.curveBasis) - .x(function(d) { return x(d[0]); }) - .y(function(d) { return y2(d[1]); }) - ); - - }).catch(function(error){ - // handle error - }) + .call(d3.axisLeft(y2)); + + // Add a tooltip div. Here I define the general feature of the tooltip: stuff that do not depend on the data point. + // Its opacity is set to 0: we don't see it by default. + var tooltip = d3.select("#my_dataviz") + .append("div") + .style("opacity", 0) + .attr("class", "tooltip") + .style("background-color", "black") + .style("color", "white") + .style("border-radius", "5px") + .style("padding", "10px") + + // A function that change this tooltip when the user hover a point. + // Its opacity is set to 1: we can now see it. Plus it set the text and position of tooltip depending on the datapoint (d) + var showTooltip = function(d) { + tooltip + .transition() + .duration(100) + .style("opacity", 1) + tooltip + .html("Range: " + d.x0 + " - " + d.x1) + .style("left", (d3.mouse(this)[0]+20) + "px") + .style("top", (d3.mouse(this)[1]) + "px") + } + var moveTooltip = function(d) { + tooltip + .style("left", (d3.mouse(this)[0]+20) + "px") + .style("top", (d3.mouse(this)[1]) + "px") + } + // A function that change this tooltip when the leaves a point: just need to set opacity to 0 again + var hideTooltip = function(d) { + tooltip + .transition() + .duration(100) + .style("opacity", 0) + } + + // append the bars for series 1 + svg.selectAll("rect") + .data(bins1) + .enter() + .append("rect") + .attr("x", 1) + .attr("transform", function(d) { return "translate(" + x(d.x0) + "," + y1(d.length) + ")"; }) + .attr("width", function(d) { return x(d.x1) - x(d.x0) - 1 ; }) + .attr("height", function(d) { return height/2 - y1(d.length); }) + .attr("stroke-linejoin", "round") + .style("fill", "#000000") + .style("opacity", 1) + .on("mouseover", showTooltip ) + .on("mousemove", moveTooltip ) + .on("mouseleave", hideTooltip ) + + // append the bars for series 2 + svg.selectAll("rect2") + .data(bins2) + .enter() + .append("rect") + .attr("x", 1) + .attr("transform", function(d) { return "translate(" + x(d.x0) + "," + height/2 + ")"; }) + .attr("width", function(d) { return x(d.x1) - x(d.x0) - 1 ; }) + .attr("height", function(d) { return y2(d.length) - height/2; }) + .attr("stroke-linejoin", "round") + .style("fill", "#D3D3D3") + .style("opacity", 1) + // Show tooltip on hover + .on("mouseover", showTooltip ) + .on("mousemove", moveTooltip ) + .on("mouseleave", hideTooltip ) + + // Handmade legend var heightforText = 175 - svg.append("circle").attr("cx",80).attr("cy",heightforText).attr("r", 6).style("fill", "#000") - svg.append("circle").attr("cx",300).attr("cy",heightforText).attr("r", 6).style("fill", "#D3D3D3") - svg.append("text").attr("x", 100).attr("y", heightforText).text("Entire distribution").style("font-size", "15px").attr("alignment-baseline","middle") - svg.append("text").attr("x", 320).attr("y", heightforText).text("Selected points").style("font-size", "15px").attr("alignment-baseline","middle") + svg.append("circle").attr("cx",30).attr("cy",heightforText).attr("r", 6).style("fill", "#000") + svg.append("circle").attr("cx",350).attr("cy",heightforText).attr("r", 6).style("fill", "#D3D3D3") + svg.append("text").attr("x", 50).attr("y", heightforText).text("Entire distribution").style("font-size", "15px").attr("alignment-baseline","middle") + svg.append("text").attr("x", 210).attr("y", heightforText).text("Performance").style("font-size", "15px").attr("alignment-baseline","top") + svg.append("text").attr("x", 370).attr("y", heightforText).text("Selected points").style("font-size", "15px").attr("alignment-baseline","middle") // Function to compute density function kernelDensityEstimator(kernel, X) { @@ -133,10 +207,18 @@ mounted () { EventBus.$on('emittedEventCallingBalanceView', data => { this.resultsfromOverview = data} ) EventBus.$on('emittedEventCallingBalanceView', this.Balance) + EventBus.$on('UpdateBalanceView', data => { this.newResultsFromSelection = data} ) + EventBus.$on('UpdateBalanceView', this.Balance) EventBus.$on('Responsive', data => { - this.WH = data}) + this.responsiveWidthHeight = data}) EventBus.$on('ResponsiveandChange', data => { - this.WH = data}) + this.responsiveWidthHeight = data}) } } - \ No newline at end of file + + + \ No newline at end of file diff --git a/frontend/src/components/BarChart.vue b/frontend/src/components/BarChart.vue index e067532d8..1267d6720 100644 --- a/frontend/src/components/BarChart.vue +++ b/frontend/src/components/BarChart.vue @@ -18,7 +18,8 @@ export default { ClassNamesOverview: '', algorithmsinBar: [], modelsSelectedinBar: [], - KNNModels: 576, //KNN models + KNNModels: 576, //KNN models, + colorsValues: ['#6a3d9a','#b15928','#e31a1c'], WH: [] } }, @@ -136,7 +137,7 @@ export default { var traces = [] var tracesSel = [] var data = [] - var colors = ['#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c','#fdbf6f','#ff7f00','#cab2d6','#6a3d9a'] + for (var i = 0; i < target_names.length; i++) { traces[i] = { x: ['KNN', 'RF'], @@ -145,7 +146,7 @@ export default { opacity: 0.5, marker: { opacity: 0.5, - color: colors[i] + color: this.colorsValues[i] }, type: 'bar' }; @@ -158,7 +159,7 @@ export default { mode: 'markers', marker: { opacity: 1.0, - color: colors[i], + color: this.colorsValues[i], }, width: [0.1, 0.1] }; diff --git a/frontend/src/components/DataSpace.vue b/frontend/src/components/DataSpace.vue index 4bb220eb7..351f199fe 100644 --- a/frontend/src/components/DataSpace.vue +++ b/frontend/src/components/DataSpace.vue @@ -1,5 +1,43 @@ \ No newline at end of file diff --git a/frontend/src/components/Parameters.vue b/frontend/src/components/Parameters.vue index a90beb5cb..9d709dd9d 100644 --- a/frontend/src/components/Parameters.vue +++ b/frontend/src/components/Parameters.vue @@ -1,6 +1,14 @@ @@ -515,7 +523,56 @@ export default { d3.selectAll("text.temporary-text").remove() } - } + }, + drawEncodings () { + // Clear Heatmap first + var svg = d3.select("#encodings"); + svg.selectAll("*").remove(); + + var widthinter = this.WH[0]*0.95 // interactive visualization + var heightinter = this.WH[1]*0.5 // interactive visualization + /* + // Create the SVG element and set its dimensions. + var width = widthinter, + height = heightinter, + padding = 15; + + var div = d3.select('#encodings'), + svg = div.append('svg'); + + svg.attr('width', width).attr('height', height); + + // Create the svg:defs element and the main gradient definition. + var svgDefs = svg.append('defs'); + + var mainGradient = svgDefs.append('linearGradient') + .attr("id", "mainGradient") + .attr("x1", "0%") + .attr("x2", "100%") + .attr("y1", "0%") + .attr("y2", "100%"); + + mainGradient.append("stop") + .attr('class', 'start') + .attr("offset", "0%") + .attr("stop-color", "red") + .attr("stop-opacity", 1); + + mainGradient.append("stop") + .attr('class', 'end') + .attr("offset", "100%") + .attr("stop-color", "blue") + .attr("stop-opacity", 1); + + // Use the gradient to set the shape fill, via CSS. + svg.append('rect') + .classed('filled', true) + .attr('x', padding) + .attr('y', padding) + .attr('width', width - 2 * padding) + .attr('height', height - 2 * padding); + */ + } }, mounted () { EventBus.$on('updateFlagKNN', data => { this.FlagKNN = data }) @@ -525,6 +582,7 @@ export default { EventBus.$on('sendParameters', data => { this.storeParameters = data }) EventBus.$on('updateActiveModels', data => { this.storeActiveModels = data }) EventBus.$on('updateActiveModels', this.draw) + EventBus.$on('updateActiveModels', this.drawEncodings) EventBus.$on('Responsive', data => { this.WH = data}) EventBus.$on('ResponsiveandChange', data => { @@ -602,4 +660,8 @@ export default { font-size: 14px; fill: #fff; } + +.filled { + fill: url(#mainGradient); +} \ No newline at end of file diff --git a/frontend/src/components/PredictionsSpace.vue b/frontend/src/components/PredictionsSpace.vue index 54bca6c68..dfe3aa64f 100644 --- a/frontend/src/components/PredictionsSpace.vue +++ b/frontend/src/components/PredictionsSpace.vue @@ -12,7 +12,7 @@ export default { return { PredictionsData: '', UpdatedData: '', - colorsValues: ['#00bbbb','#b15928','#ff7f00'], + colorsValues: ['#6a3d9a','#b15928','#e31a1c'], responsiveWidthHeight: [] } }, @@ -65,7 +65,7 @@ export default { y: aux_Y, mode: 'markers', name: target_names[i], - marker: { color: this.colorsValues[i], line: { color: 'rgb(0, 0, 0)', width: 2 }, opacity: 1 }, + marker: { color: this.colorsValues[i], line: { color: 'rgb(0, 0, 0)', width: 2 }, opacity: 1, size: 12 }, hovertemplate: "%{text}

" + "", diff --git a/frontend/src/components/ScatterPlot.vue b/frontend/src/components/ScatterPlot.vue index f6ade3f73..d407f3b5c 100644 --- a/frontend/src/components/ScatterPlot.vue +++ b/frontend/src/components/ScatterPlot.vue @@ -31,7 +31,7 @@ export default { return { ScatterPlotResults: '', representationDef: 'mds', - representationSelection: 'MDS', + representationSelection: 'mds', colorsforOver: [], brushedBox : [], max: 0, diff --git a/frontend/src/main.js b/frontend/src/main.js index f4c109d1f..7777f8b05 100755 --- a/frontend/src/main.js +++ b/frontend/src/main.js @@ -6,10 +6,10 @@ import 'bootstrap-vue/dist/bootstrap-vue.css' import router from './router' import { library } from '@fortawesome/fontawesome-svg-core' import { FontAwesomeIcon } from '@fortawesome/vue-fontawesome' -import { faUpload, faPlay, faCheck, faSave, faTrash, faPlus, faBalanceScale, faMinus} from '@fortawesome/free-solid-svg-icons' +import { faUpload, faPlay, faCheck, faSave, faTrash, faPlus, faBalanceScale, faMinus, faEraser, faClone, faObjectGroup, faUndo } from '@fortawesome/free-solid-svg-icons' import bFormSlider from 'vue-bootstrap-slider' -library.add(faUpload, faPlay, faCheck, faSave, faTrash, faPlus, faBalanceScale, faMinus) +library.add(faUpload, faPlay, faCheck, faSave, faTrash, faPlus, faBalanceScale, faMinus, faEraser, faClone, faObjectGroup, faUndo) Vue.component('font-awesome-icon', FontAwesomeIcon) diff --git a/run.py b/run.py index aed6ea9f7..c5f622ded 100644 --- a/run.py +++ b/run.py @@ -7,6 +7,7 @@ import collections import numpy as np import re from numpy import array +from statistics import mode import pandas as pd import warnings import copy @@ -66,6 +67,12 @@ def Reset(): global yData yData = [] + + global XDataStored + XDataStored = [] + + global yDataStored + yDataStored = [] global detailsParams detailsParams = [] @@ -136,6 +143,15 @@ def RetrieveFileName(): global yData yData = [] + global XDataStored + XDataStored = [] + + global yDataStored + yDataStored = [] + + global filterDataFinal + filterDataFinal = 'mean' + global ClassifierIDsList ClassifierIDsList = '' @@ -223,6 +239,8 @@ def DataSetSelection(): DataResultsRaw.sort(key=lambda x: x[target], reverse=True) DataResults.sort(key=lambda x: x[target], reverse=True) + + dataBefore = copy.deepcopy(DataResults) for dictionary in DataResults: del dictionary['_id'] @@ -251,9 +269,40 @@ def DataSetSelection(): global XData, yData, RANDOM_SEED XData, yData = ArrayDataResults, AllTargetsFloatValues + + global XDataStored, yDataStored + XDataStored = XData.copy() + yDataStored = yData.copy() + + DataSpaceRes = FunTsne(XData) + DataSpaceListRes = DataSpaceRes.tolist() + + XDataJSONEntireSetRes = XData.to_json(orient='records') + + global preResults + preResults = [] + + preResults.append(json.dumps(target_names)) # Position: 0 + preResults.append(json.dumps(DataSpaceListRes)) # Position: 1 + preResults.append(json.dumps(XDataJSONEntireSetRes)) # Position: 2 + preResults.append(json.dumps(yData)) # Position: 3 + preResults.append(json.dumps(AllTargets)) # Position: 4 + preResults.append(json.dumps(dataBefore)) # Position: 5 + preResults.append(json.dumps(target)) # Position: 6 + warnings.simplefilter('ignore') return 'Everything is okay' +# Sending each model's results to frontend +@app.route('/data/requestDataSpaceResults', methods=["GET", "POST"]) +def SendDataSpaceResults(): + global preResults + + response = { + 'preDataResults': preResults, + } + return jsonify(response) + # Main function if __name__ == '__main__': app.run() @@ -1259,4 +1308,85 @@ def SendToPlotFinalResults(): response = { 'FinalResults': scores } - return jsonify(response) \ No newline at end of file + return jsonify(response) + +# Retrieve data from client +@cross_origin(origin='localhost',headers=['Content-Type','Authorization']) +@app.route('/data/UpdateFilter', methods=["GET", "POST"]) +def RetrieveFilter(): + filterData = request.get_data().decode('utf8').replace("'", '"') + filterDataCleared = json.loads(filterData) + global filterDataFinal + filterDataFinal = filterDataCleared['filter'] + return 'Done' + +# Retrieve data from client +@cross_origin(origin='localhost',headers=['Content-Type','Authorization']) +@app.route('/data/SendDataSpacPoints', methods=["GET", "POST"]) +def RetrieveDataSpacePoints(): + dataSpacePoints = request.get_data().decode('utf8').replace("'", '"') + dataSpacePointsCleared = json.loads(dataSpacePoints) + global dataSpacePointsIDs + dataSpacePointsIDs = dataSpacePointsCleared['points'] + return 'Done' + +# Retrieve data from client +@cross_origin(origin='localhost',headers=['Content-Type','Authorization']) +@app.route('/data/UpdateAction', methods=["GET", "POST"]) +def RetrieveAction(): + filterAction = request.get_data().decode('utf8').replace("'", '"') + filterActionCleared = json.loads(filterAction) + + global filterActionFinal + global dataSpacePointsIDs + global filterDataFinal + global XData + global yData + + filterActionFinal = filterActionCleared['action'] + + if (filterActionFinal == 'merge'): # fix merge + if (filterDataFinal == 'mean' or filterDataFinal == ''): + mean = XData.iloc[dataSpacePointsIDs, :].mean() + XData.loc[len(XData)]= mean + else: + median = XData.iloc[dataSpacePointsIDs, :].median() + XData.loc[len(XData)]= median + elif (filterActionFinal == 'compose'): + if (filterDataFinal == 'mean' or filterDataFinal == ''): + mean = XData.iloc[dataSpacePointsIDs, :].mean() + XData.loc[len(XData)]= mean + else: + median = XData.iloc[dataSpacePointsIDs, :].median() + XData.loc[len(XData)]= median + yDataSelected = [yData[i] for i in dataSpacePointsIDs] + storeMode = mode(yDataSelected) + yData.append(storeMode) + else: + XData = XData.drop(dataSpacePointsIDs) + yData = [i for j, i in enumerate(yData) if j not in dataSpacePointsIDs] + + print(XData) + print(yData) + return 'Done' + +# Retrieve data from client +@cross_origin(origin='localhost',headers=['Content-Type','Authorization']) +@app.route('/data/UpdateProvenanceState', methods=["GET", "POST"]) +def RetrieveProvenance(): + filterProvenance = request.get_data().decode('utf8').replace("'", '"') + filterProvenanceCleared = json.loads(filterProvenance) + global filterProvenanceFinal + filterProvenanceFinal = filterProvenanceCleared['provenance'] + + global XDataStored + global XData + global yDataStored + global yData + + # fix save and restore + + if (filterProvenanceFinal == 'restore'): + XData = XDataStored.copy() + yData = yDataStored.copy() + return 'Done' \ No newline at end of file