From 8266eb3ad348986c8c07b4ac1aff335bc5ac29a5 Mon Sep 17 00:00:00 2001
From: Angelos Chatzimparmpas <angelos.chatzimparmpas@gmail.com>
Date: Wed, 1 Jul 2020 13:46:09 +0200
Subject: [PATCH] fixed grid-based

---
 __pycache__/run.cpython-37.pyc                | Bin 26839 -> 27211 bytes
 frontend/src/components/Main.vue              |  39 +-
 frontend/src/components/Predictions.vue       | 439 ++++++++++++++++++
 ...lResultsLinePlot.vue => VotingResults.vue} |   2 +-
 run.py                                        |  13 +-
 5 files changed, 480 insertions(+), 13 deletions(-)
 create mode 100644 frontend/src/components/Predictions.vue
 rename frontend/src/components/{FinalResultsLinePlot.vue => VotingResults.vue} (99%)

diff --git a/__pycache__/run.cpython-37.pyc b/__pycache__/run.cpython-37.pyc
index 8e8bfbb56f751d1f773e460e98a70282b769e13d..404b618e8c0516bc6d8d58b57e4c0a6682f2349c 100644
GIT binary patch
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diff --git a/frontend/src/components/Main.vue b/frontend/src/components/Main.vue
index fe18270..3a49c2c 100755
--- a/frontend/src/components/Main.vue
+++ b/frontend/src/components/Main.vue
@@ -15,24 +15,24 @@
               </mdb-card-body>
           </mdb-card>
         </b-col>
-        <!--
         <b-col cols="6">
           <mdb-card>
-            <mdb-card-header color="primary-color" tag="h5" class="text-center">Hyper-parameters' Space</mdb-card-header>
+            <mdb-card-header color="primary-color" tag="h5" class="text-center">Provenance</mdb-card-header>
             <mdb-card-body>
-                <ScatterPlot/>
+              <mdb-card-text class="text-left" style="font-size: 18.5px; min-height: 230px">
+              </mdb-card-text>
             </mdb-card-body>
           </mdb-card>
         </b-col>
         <b-col cols="3">
-            <mdb-card>
-              <mdb-card-header color="primary-color" tag="h5" class="text-center" style="background-color: #C0C0C0;"><small class="float-left" style="padding-top: 3px;"><font-awesome-icon class="fa-lg" icon="dice-four"/>&nbsp;Metrics Support: [M1, M3-M5 (W)]</small>Metamodel's Performance</mdb-card-header>
+            <mdb-card >
+              <mdb-card-header color="primary-color" tag="h5" class="text-center">Majority Voting Results</mdb-card-header>
               <mdb-card-body>
-                <FinalResultsLinePlot/>
+                <mdb-card-text class="text-left" style="font-size: 18.5px; min-height: 230px">
+                </mdb-card-text>
               </mdb-card-body>
             </mdb-card>
         </b-col>
-      -->
       </b-row>
       <!--
       <hr/>
@@ -122,7 +122,7 @@
                     [Sel: {{OverSelLength}} / All: {{OverAllLength}}]<small class="float-right"><active-scatter/></small>
                     </mdb-card-header>
                     <mdb-card-body>
-                      <mdb-card-text class="text-center"  style="min-height: 822px">
+                      <mdb-card-text class="text-center"  style="min-height: 600px">
                         <HyperParameterSpace/>
                       </mdb-card-text>
                     </mdb-card-body>
@@ -134,13 +134,26 @@
                     [Sel: {{OverSelLengthCM}} / All: {{OverAllLengthCM}}]<small class="float-right"><active-scatter/></small>
                   </mdb-card-header>
                   <mdb-card-body>
-                    <mdb-card-text class="text-center"  style="min-height: 822px">
+                    <mdb-card-text class="text-center"  style="min-height: 600px">
                       <CrossoverMutationSpace/>
                     </mdb-card-text>
                   </mdb-card-body>
                 </mdb-card>
               </b-col>
             </b-row>
+            <b-row class="md-3">
+              <b-col cols="12">
+                <mdb-card style="margin-top: 15px;">
+                  <mdb-card-header color="primary-color" tag="h5" class="text-center">Predictions' Space
+                    </mdb-card-header>
+                    <mdb-card-body>
+                      <mdb-card-text class="text-center"  style="min-height: 270px">
+                        <Predictions/>
+                      </mdb-card-text>
+                    </mdb-card-body>
+                </mdb-card>
+              </b-col>
+            </b-row>
         </div>
       </div>
     </b-container>
@@ -156,8 +169,9 @@ import Algorithms from './Algorithms.vue'
 import AlgorithmHyperParam from './AlgorithmHyperParam.vue'
 import HyperParameterSpace from './HyperParameterSpace.vue'
 import CrossoverMutationSpace from './CrossoverMutationSpace.vue'
-import FinalResultsLinePlot from './FinalResultsLinePlot.vue'
+import VotingResults from './VotingResults.vue'
 import Parameters from './Parameters.vue'
+import Predictions from './Predictions.vue'
 import axios from 'axios'
 import { loadProgressBar } from 'axios-progress-bar'
 import 'axios-progress-bar/dist/nprogress.css'
@@ -182,7 +196,8 @@ export default Vue.extend({
     HyperParameterSpace,
     CrossoverMutationSpace,
     Parameters,
-    FinalResultsLinePlot,
+    Predictions,
+    VotingResults,
     mdbCard,
     mdbCardBody,
     mdbCardHeader,
@@ -289,6 +304,8 @@ export default Vue.extend({
           this.OverviewResults = response.data.OverviewResults
           console.log('Server successfully sent all the data related to visualizations!')
           EventBus.$emit('emittedEventCallingScatterPlot', this.OverviewResults)
+          EventBus.$emit('emittedEventCallingGrid', this.OverviewResults)
+          EventBus.$emit('emittedEventCallingGridSelection', this.OverviewResults)
           //this.getFinalResults()
         })
         .catch(error => {
diff --git a/frontend/src/components/Predictions.vue b/frontend/src/components/Predictions.vue
new file mode 100644
index 0000000..d86556b
--- /dev/null
+++ b/frontend/src/components/Predictions.vue
@@ -0,0 +1,439 @@
+<template>
+  <div>
+    <div id="containerAll"></div>
+    <div id="containerSelection"></div>
+  </div>
+</template>
+
+<script>
+import * as d3Base from 'd3'
+import { EventBus } from '../main.js'
+import $ from 'jquery'
+import * as colorbr from 'colorbrewer'
+
+// attach all d3 plugins to the d3 library
+const d3 = Object.assign(d3Base)
+const colorbrewer = Object.assign(colorbr)
+
+export default {
+  name: "Predictions",
+  data () {
+    return {
+      GetResultsAll: [],
+      GetResultsSelection: [],
+      responsiveWidthHeight: [],
+    }
+  },
+  methods: {
+    reset () {
+      var svg = d3.select("#containerAll");
+      svg.selectAll("*").remove();
+      var svg = d3.select("#containerSelection");
+      svg.selectAll("*").remove();
+    },
+    Grid () {
+
+      Array.prototype.multiIndexOf = function (el) { 
+          var idxs = [];
+          for (var i = this.length - 1; i >= 0; i--) {
+              if (this[i] === el) {
+                  idxs.unshift(i);
+              }
+          }
+          return idxs;
+      };
+      // Clear Heatmap first
+      var svg = d3.select("#GridView");
+      svg.selectAll("*").remove();
+
+      var yValues = JSON.parse(this.GetResultsAll[6])
+      var targetNames = JSON.parse(this.GetResultsAll[7])
+
+      var getIndices = []
+      for (let i = 0; i < targetNames.length; i++) {
+        getIndices.push(yValues.multiIndexOf(targetNames[i]))
+      }
+      getIndices.reverse()
+
+      var predictions = JSON.parse(this.GetResultsAll[12])
+      var KNNPred = predictions[0]
+      var LRPred = predictions[1]
+      var PredAver = predictions[2]
+
+      var dataAver = []
+      var dataAverGetResults = []
+      var dataKNN = []
+      var dataKNNResults = []
+      var dataLR = []
+      var dataLRResults = []
+
+      var max = 0
+      for (let i = 0; i < targetNames.length; i++) {
+        if (getIndices[targetNames[i]].length > max) {
+          max = getIndices[targetNames[i]].length
+        } 
+      }
+
+      var sqrtSize = Math.ceil(Math.sqrt(max))
+      var size = sqrtSize * sqrtSize
+
+      for (let i = 0; i < targetNames.length; i++) {
+        dataAver = [];
+        dataKNN = []
+        dataLR = []
+        getIndices[targetNames[i]].forEach(element => {
+          dataAver.push({ id: element, value: PredAver[element][targetNames[i]] })
+          dataKNN.push({ id: element, value: KNNPred[element][targetNames[i]] })
+          dataLR.push({ id: element, value: LRPred[element][targetNames[i]] })
+        });
+        for (let j = 0; j < size - getIndices[targetNames[i]].length; j++) {
+          dataAver.push({ id: null, value: 0.0 })
+          dataKNN.push({ id: null, value: 0.0 })
+          dataLR.push({ id: null, value: 0.0 })
+        }
+        dataAverGetResults.push(dataAver)
+        dataKNNResults.push(dataKNN)
+        dataLRResults.push(dataLR)
+      }
+    dataAverGetResults.reverse()
+    dataKNNResults.reverse()
+    dataLRResults.reverse()
+    
+    var classArray = []
+
+    for (let i = 0; i < dataAverGetResults.length; i++) {
+      dataAverGetResults[i].sort((a, b) => (a.value > b.value) ? -1 : 1)
+      var len = dataAverGetResults[i].length
+      var indices = new Array(len)
+      for (let j = 0; j < len; j++) {
+        indices[j] = dataAverGetResults[i][j].id;
+      }
+      
+      dataKNNResults[i].sort(function(a, b){
+        return indices.indexOf(a.id) - indices.indexOf(b.id)
+      });
+
+      dataLRResults[i].sort(function(a, b){
+        return indices.indexOf(a.id) - indices.indexOf(b.id)
+      });
+
+      classArray.push(dataAverGetResults[i].concat(dataKNNResults[i], dataLRResults[i]));
+    }
+    
+    var classStore = [].concat.apply([], classArray);
+
+		// === Set up canvas === //
+
+		var width = 2500,
+				height = 125;
+		var colourScale;
+
+
+		var canvas = d3.select('#containerAll')
+			.append('canvas')
+			.attr('width', width)
+			.attr('height', height);
+
+		var context = canvas.node().getContext('2d');
+
+		// === Bind data to custom elements === //
+
+		var customBase = document.createElement('custom');
+		var custom = d3.select(customBase); // this is our svg replacement
+
+    // settings for a grid with 40 cells in a row and 2x5 cells in a group
+		var groupSpacing = 60;
+		var cellSpacing = 2;
+    var cellSize = Math.floor((width - 11 * groupSpacing) / (15.2*sqrtSize)) - cellSpacing;
+
+		// === First call === //
+		databind(classStore, size, sqrtSize); // ...then update the databind function
+		
+		var t = d3.timer(function(elapsed) {
+			draw();
+			if (elapsed > 300) t.stop();
+		}); // start a timer that runs the draw function for 500 ms (this needs to be higher than the transition in the databind function)
+
+
+		// === Bind and draw functions === //
+
+		function databind(data, size, sqrtSize) {
+
+      
+			colourScale = d3.scaleSequential(d3.interpolateReds).domain(d3.extent(data, function(d) { return d.value; }));
+
+			var join = custom.selectAll('custom.rect')
+        .data(data);
+        
+			var enterSel = join.enter()
+				.append('custom')
+				.attr('class', 'rect')
+	      .attr('x', function(d, i) {
+	        var x0 = Math.floor(i / 169) % 13, x1 = Math.floor(i % 13);
+	        return groupSpacing * x0 + (cellSpacing + cellSize) * (x1 + x0 * 10);
+	      })
+	      .attr('y', function(d, i) {
+	        var y0 = Math.floor(i / 1000), y1 = Math.floor(i % 169 / 13);
+	        return groupSpacing * y0 + (cellSpacing + cellSize) * (y1 + y0 * 10);
+	      })
+				.attr('width', 0)
+				.attr('height', 0);
+
+			join
+				.merge(enterSel)
+				.transition()
+				.attr('width', cellSize)
+				.attr('height', cellSize)
+        .attr('fillStyle', function(d) { return colourScale(d.value); })
+
+			var exitSel = join.exit()
+				.transition()
+				.attr('width', 0)
+				.attr('height', 0)
+				.remove();
+
+		} // databind()
+
+
+		// === Draw canvas === //
+
+		function draw() {
+
+			// clear canvas
+			
+			context.fillStyle = '#fff';
+			context.fillRect(0, 0, width, height);
+
+			
+			// draw each individual custom element with their properties
+			
+			var elements = custom.selectAll('custom.rect') // this is the same as the join variable, but used here to draw
+			
+			elements.each(function(d,i) {
+
+				// for each virtual/custom element...
+
+				var node = d3.select(this);
+				context.fillStyle = node.attr('fillStyle');
+				context.fillRect(node.attr('x'), node.attr('y'), node.attr('width'), node.attr('height'))
+
+			});
+
+		} // draw()
+
+  },
+  GridSelection () {
+
+      Array.prototype.multiIndexOf = function (el) { 
+          var idxs = [];
+          for (var i = this.length - 1; i >= 0; i--) {
+              if (this[i] === el) {
+                  idxs.unshift(i);
+              }
+          }
+          return idxs;
+      };
+      // Clear Heatmap first
+      var svg = d3.select("#GridView");
+      svg.selectAll("*").remove();
+
+      var yValues = JSON.parse(this.GetResultsSelection[6])
+      var targetNames = JSON.parse(this.GetResultsSelection[7])
+
+      var getIndices = []
+      for (let i = 0; i < targetNames.length; i++) {
+        getIndices.push(yValues.multiIndexOf(targetNames[i]))
+      }
+      getIndices.reverse()
+
+      var predictions = JSON.parse(this.GetResultsSelection[12])
+      var KNNPred = predictions[0]
+      var LRPred = predictions[1]
+      var PredAver = predictions[2]
+
+      var dataAver = []
+      var dataAverGetResults = []
+      var dataKNN = []
+      var dataKNNResults = []
+      var dataLR = []
+      var dataLRResults = []
+
+      var max = 0
+      for (let i = 0; i < targetNames.length; i++) {
+        if (getIndices[targetNames[i]].length > max) {
+          max = getIndices[targetNames[i]].length
+        } 
+      }
+
+      var sqrtSize = Math.ceil(Math.sqrt(max))
+      var size = sqrtSize * sqrtSize
+
+      for (let i = 0; i < targetNames.length; i++) {
+        dataAver = [];
+        dataKNN = []
+        dataLR = []
+        getIndices[targetNames[i]].forEach(element => {
+          dataAver.push({ id: element, value: PredAver[element][targetNames[i]] })
+          dataKNN.push({ id: element, value: KNNPred[element][targetNames[i]] })
+          dataLR.push({ id: element, value: LRPred[element][targetNames[i]] })
+        });
+        for (let j = 0; j < size - getIndices[targetNames[i]].length; j++) {
+          dataAver.push({ id: null, value: 0.0 })
+          dataKNN.push({ id: null, value: 0.0 })
+          dataLR.push({ id: null, value: 0.0 })
+        }
+        dataAverGetResults.push(dataAver)
+        dataKNNResults.push(dataKNN)
+        dataLRResults.push(dataLR)
+      }
+    dataAverGetResults.reverse()
+    dataKNNResults.reverse()
+    dataLRResults.reverse()
+    
+    var classArray = []
+
+    for (let i = 0; i < dataAverGetResults.length; i++) {
+      dataAverGetResults[i].sort((a, b) => (a.value > b.value) ? -1 : 1)
+      var len = dataAverGetResults[i].length
+      var indices = new Array(len)
+      for (let j = 0; j < len; j++) {
+        indices[j] = dataAverGetResults[i][j].id;
+      }
+      
+      dataKNNResults[i].sort(function(a, b){
+        return indices.indexOf(a.id) - indices.indexOf(b.id)
+      });
+
+      dataLRResults[i].sort(function(a, b){
+        return indices.indexOf(a.id) - indices.indexOf(b.id)
+      });
+
+      classArray.push(dataAverGetResults[i].concat(dataKNNResults[i], dataLRResults[i]));
+    }
+    
+    var classStore = [].concat.apply([], classArray);
+
+		// === Set up canvas === //
+
+		var width = 2500,
+				height = 125;
+		var colourScale;
+
+
+		var canvas = d3.select('#containerSelection')
+			.append('canvas')
+			.attr('width', width)
+			.attr('height', height);
+
+		var context = canvas.node().getContext('2d');
+
+		// === Bind data to custom elements === //
+
+		var customBase = document.createElement('custom');
+		var custom = d3.select(customBase); // this is our svg replacement
+
+    // settings for a grid with 40 cells in a row and 2x5 cells in a group
+		var groupSpacing = 60;
+		var cellSpacing = 2;
+    var cellSize = Math.floor((width - 11 * groupSpacing) / (15.2*sqrtSize)) - cellSpacing;
+
+		// === First call === //
+		databind(classStore, size, sqrtSize); // ...then update the databind function
+		
+		var t = d3.timer(function(elapsed) {
+			draw();
+			if (elapsed > 300) t.stop();
+		}); // start a timer that runs the draw function for 500 ms (this needs to be higher than the transition in the databind function)
+
+
+		// === Bind and draw functions === //
+
+		function databind(data, size, sqrtSize) {
+
+      
+			colourScale = d3.scaleSequential(d3.interpolateReds).domain(d3.extent(data, function(d) { return d.value; }));
+
+			var join = custom.selectAll('custom.rect')
+        .data(data);
+        
+			var enterSel = join.enter()
+				.append('custom')
+				.attr('class', 'rect')
+	      .attr('x', function(d, i) {
+	        var x0 = Math.floor(i / 169) % 13, x1 = Math.floor(i % 13);
+	        return groupSpacing * x0 + (cellSpacing + cellSize) * (x1 + x0 * 10);
+	      })
+	      .attr('y', function(d, i) {
+	        var y0 = Math.floor(i / 1000), y1 = Math.floor(i % 169 / 13);
+	        return groupSpacing * y0 + (cellSpacing + cellSize) * (y1 + y0 * 10);
+	      })
+				.attr('width', 0)
+				.attr('height', 0);
+
+			join
+				.merge(enterSel)
+				.transition()
+				.attr('width', cellSize)
+				.attr('height', cellSize)
+        .attr('fillStyle', function(d) { return colourScale(d.value); })
+
+			var exitSel = join.exit()
+				.transition()
+				.attr('width', 0)
+				.attr('height', 0)
+				.remove();
+
+		} // databind()
+
+
+		// === Draw canvas === //
+
+		function draw() {
+
+			// clear canvas
+			
+			context.fillStyle = '#fff';
+			context.fillRect(0, 0, width, height);
+
+			
+			// draw each individual custom element with their properties
+			
+			var elements = custom.selectAll('custom.rect') // this is the same as the join variable, but used here to draw
+			
+			elements.each(function(d,i) {
+
+				// for each virtual/custom element...
+
+				var node = d3.select(this);
+				context.fillStyle = node.attr('fillStyle');
+				context.fillRect(node.attr('x'), node.attr('y'), node.attr('width'), node.attr('height'))
+
+			});
+
+		} // draw()
+
+  },
+  },
+  mounted () {
+      EventBus.$on('emittedEventCallingGrid', data => { this.GetResultsAll = data; })
+      EventBus.$on('emittedEventCallingGrid', this.Grid)
+
+      EventBus.$on('emittedEventCallingGridSelection', data => { this.GetResultsSelection = data; })
+      EventBus.$on('emittedEventCallingGridSelection', this.GridSelection)
+
+      EventBus.$on('Responsive', data => {
+      this.responsiveWidthHeight = data})
+      EventBus.$on('ResponsiveandChange', data => {
+      this.responsiveWidthHeight = data})
+
+      // reset the views
+      EventBus.$on('resetViews', this.reset)
+    }
+}
+</script>
+
+<style type="text/css">
+		canvas {
+			border:  1px dotted #ccc;
+		}
+</style>
\ No newline at end of file
diff --git a/frontend/src/components/FinalResultsLinePlot.vue b/frontend/src/components/VotingResults.vue
similarity index 99%
rename from frontend/src/components/FinalResultsLinePlot.vue
rename to frontend/src/components/VotingResults.vue
index ae4a723..1c69f28 100644
--- a/frontend/src/components/FinalResultsLinePlot.vue
+++ b/frontend/src/components/VotingResults.vue
@@ -7,7 +7,7 @@ import * as Plotly from 'plotly.js'
 import { EventBus } from '../main.js'
 
 export default {
-  name: 'FinalResultsLinePlot',
+  name: 'VotingResults',
   data () {
     return {
       FinalResultsforLinePlot: 0,
diff --git a/run.py b/run.py
index 6a644a9..1601819 100644
--- a/run.py
+++ b/run.py
@@ -615,12 +615,23 @@ def PreprocessingPred():
     dfLR = pd.DataFrame.from_dict(dicLR)
 
     df_concatProbs = pd.concat([dfKNN, dfLR])
+
+    predictionsKNN = []
+    for column, content in dfKNN.items():
+        el = [sum(x)/len(x) for x in zip(*content)]
+        predictionsKNN.append(el)
+
+    predictionsLR = []
+    for column, content in dfLR.items():
+        el = [sum(x)/len(x) for x in zip(*content)]
+        predictionsLR.append(el)
+    
     predictions = []
     for column, content in df_concatProbs.items():
         el = [sum(x)/len(x) for x in zip(*content)]
         predictions.append(el)
 
-    return predictions
+    return [predictionsKNN, predictionsLR, predictions]
 
 def PreprocessingParam():
     dicKNN = allParametersPerformancePerModel[1]