StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics https://doi.org/10.1109/TVCG.2020.3030352
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StackGenVis/frontend/src/components/PredictionsSpace.vue

148 lines
4.7 KiB

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<template>
<div id="OverviewPredPlotly" class="OverviewPredPlotly"></div>
</template>
<script>
import * as Plotly from 'plotly.js'
import { EventBus } from '../main.js'
export default {
name: 'PredictionsSpace',
data () {
return {
PredictionsData: '',
UpdatedData: '',
WH: []
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}
},
methods: {
ScatterPlotDataView () {
var target_names = JSON.parse(this.PredictionsData[4])
const XandYCoordinates = JSON.parse(this.PredictionsData[8])
const DataSet = JSON.parse(this.PredictionsData[14])
const DataSetY = JSON.parse(this.PredictionsData[15])
var DataSetParse = JSON.parse(DataSet)
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var result = XandYCoordinates.reduce(function(r, a) {
a.forEach(function(s, i) {
var key = i === 0 ? 'Xax' : 'Yax';
r[key] || (r[key] = []); // if key not found on result object, add the key with empty array as the value
r[key].push(s);
})
return r;
}, {})
var dataPointInfo = []
for (let i = 0; i < XandYCoordinates.length; i++) {
dataPointInfo[i] = 'Data Point ID: ' + i + '; Details: ' + JSON.stringify(DataSetParse[i])
}
var colors = ['#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c','#fdbf6f','#ff7f00','#cab2d6','#6a3d9a']
var traces = []
var countPrev = 0
var count = 0
for (let i = 0; i < target_names.length; i++) {
count = 0
for (let j = 0; j < DataSetY.length; j++) {
if (i == DataSetY[j]) {
count = count + 1
}
}
traces.push({
x: result.Xax.slice(countPrev,count+countPrev),
y: result.Yax.slice(countPrev,count+countPrev),
mode: 'markers',
name: target_names[i],
marker: {
color: colors[i]
},
hovertemplate:
"<b>%{text}</b><br><br>" +
"<extra></extra>",
text: dataPointInfo.slice(countPrev,count+countPrev),
})
countPrev = count + countPrev
}
var width = this.WH[0]*3 // interactive visualization
var height = this.WH[1]*1.48 // interactive visualization
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const layout = {
title: 'Predictions Space Projection (t-SNE)',
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xaxis: {
visible: false
},
yaxis: {
visible: false
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},
dragmode: 'lasso',
hovermode: "closest",
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autosize: true,
width: width,
height: height,
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}
var config = {scrollZoom: true, displaylogo: false, showLink: false, showSendToCloud: false, modeBarButtonsToRemove: ['toImage', 'toggleSpikelines', 'autoScale2d', 'hoverClosestGl2d','hoverCompareCartesian','select2d','hoverClosestCartesian','zoomIn2d','zoomOut2d','zoom2d'], responsive: true}
Plotly.newPlot('OverviewPredPlotly', traces, layout, config)
this.selectedPointsOverview()
},
UpdateScatterPlot () {
const XandYCoordinates = JSON.parse(this.UpdatedData[0])
Plotly.animate('OverviewPredPlotly', {
data: [
{x: XandYCoordinates[0], y: XandYCoordinates[1]}
],
traces: [0],
layout: {}
}, {
transition: {
duration: 1000,
easing: 'cubic-in-out'
},
frame: {
duration: 1000
}
})
this.selectedPointsOverview()
},
selectedPointsOverview () {
const OverviewPlotly = document.getElementById('OverviewPredPlotly')
OverviewPlotly.on('plotly_selected', function (evt) {
if (typeof evt !== 'undefined') {
const DataPoints = []
for (let i = 0; evt.points.length; i++) {
if (evt.points[i] === undefined) {
break
} else {
const OnlyId = evt.points[i].text.split(' ')
DataPoints.push(OnlyId[3])
}
}
if (DataPoints != '') {
EventBus.$emit('SendSelectedDataPointsToServerEvent', DataPoints)
} else {
EventBus.$emit('SendSelectedDataPointsToServerEvent', '')
}
}
})
},
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},
mounted() {
EventBus.$on('updatePredictionsSpace', data => { this.UpdatedData = data })
EventBus.$on('updatePredictionsSpace', this.UpdateScatterPlot)
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EventBus.$on('emittedEventCallingPredictionsSpacePlotView', data => {
this.PredictionsData = data})
EventBus.$on('emittedEventCallingPredictionsSpacePlotView', this.ScatterPlotDataView)
EventBus.$on('Responsive', data => {
this.WH = data})
EventBus.$on('ResponsiveandChange', data => {
this.WH = data})
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}
}
</script>