new

frontend/src/components/FeatureSpaceDetail.vue

@@ -107,7 +107,7 @@ export default {
       this.graphVizualization()
     },
     computeOnce () {  
-        var numberOfTransformations = 4 // change that
+        var numberOfTransformations = 12 // change that
         
         var listofNodes = this.dataFS[34]
         var dataLocOnce = []
@@ -125,6 +125,7 @@ export default {
         var outcome
         var countLoc
         var pushEachFinalFinal = []
+
         for (let loop=1; loop<=5; loop++) {
           var corrMatrixCombLoc =[]
           var corrMatrixCombTotalLoc = []
@@ -178,7 +179,7 @@ export default {
               newVal = newVal / listofNodes.length
               outcome = oldVal - newVal
               pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+1], valueIns: outcome})
-
+              console.log(pushEach)
               var transf3 = element.transf3
               corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf3[10+quadrantNumberLocal]))[0] * 100)
               MIRemainingLoc.push(JSON.parse(transf3[20+quadrantNumberLocal]))
@@ -222,6 +223,190 @@ export default {
               newVal = newVal / listofNodes.length
               outcome = oldVal - newVal
               pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+3], valueIns: outcome})
+
+              var transf5 = element.transf5
+              corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf5[10+quadrantNumberLocal]))[0] * 100)
+              MIRemainingLoc.push(JSON.parse(transf5[20+quadrantNumberLocal]))
+              transf5 = JSON.parse(transf5[loop-1])
+              oldVal = 0
+              newVal = 0
+              outcome = 0
+              countLoc = 0
+              Object.entries(transf5).forEach(
+              function ([feature, value]) {
+                var key = listofNodes[index]
+                var retrieveData = dataLocOnce[loop-1]
+                var search = Object.values(retrieveData[key])
+                oldVal = Math.abs(search[countLoc]) + oldVal
+                newVal = Math.abs(Object.values(value)[0]) + newVal
+                countLoc++
+              })
+              oldVal = oldVal / listofNodes.length
+              newVal = newVal / listofNodes.length
+              outcome = oldVal - newVal
+              pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+4], valueIns: outcome})
+              
+
+              var transf6 = element.transf6
+              corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf6[10+quadrantNumberLocal]))[0] * 100)
+              MIRemainingLoc.push(JSON.parse(transf6[20+quadrantNumberLocal]))
+              transf6 = JSON.parse(transf6[loop-1])
+              oldVal = 0
+              newVal = 0
+              outcome = 0
+              countLoc = 0
+              Object.entries(transf6).forEach(
+              function ([feature, value]) {
+                var key = listofNodes[index]
+                var retrieveData = dataLocOnce[loop-1]
+                var search = Object.values(retrieveData[key])
+                oldVal = Math.abs(search[countLoc]) + oldVal
+                newVal = Math.abs(Object.values(value)[0]) + newVal
+                countLoc++
+              })
+              oldVal = oldVal / listofNodes.length
+              newVal = newVal / listofNodes.length
+              outcome = oldVal - newVal
+              pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+5], valueIns: outcome})
+              
+
+              var transf7 = element.transf7
+              corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf7[10+quadrantNumberLocal]))[0] * 100)
+              MIRemainingLoc.push(JSON.parse(transf7[20+quadrantNumberLocal]))
+              transf7 = JSON.parse(transf7[loop-1])
+              oldVal = 0
+              newVal = 0
+              outcome = 0
+              countLoc = 0
+              Object.entries(transf7).forEach(
+              function ([feature, value]) {
+                var key = listofNodes[index]
+                var retrieveData = dataLocOnce[loop-1]
+                var search = Object.values(retrieveData[key])
+                oldVal = Math.abs(search[countLoc]) + oldVal
+                newVal = Math.abs(Object.values(value)[0]) + newVal
+                countLoc++
+              })
+              oldVal = oldVal / listofNodes.length
+              newVal = newVal / listofNodes.length
+              outcome = oldVal - newVal
+              pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+6], valueIns: outcome})
+              
+
+              var transf8 = element.transf8
+              corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf8[10+quadrantNumberLocal]))[0] * 100)
+              MIRemainingLoc.push(JSON.parse(transf8[20+quadrantNumberLocal]))
+              transf8 = JSON.parse(transf8[loop-1])
+              oldVal = 0
+              newVal = 0
+              outcome = 0
+              countLoc = 0
+              Object.entries(transf8).forEach(
+              function ([feature, value]) {
+                var key = listofNodes[index]
+                var retrieveData = dataLocOnce[loop-1]
+                var search = Object.values(retrieveData[key])
+                oldVal = Math.abs(search[countLoc]) + oldVal
+                newVal = Math.abs(Object.values(value)[0]) + newVal
+                countLoc++
+              })
+              oldVal = oldVal / listofNodes.length
+              newVal = newVal / listofNodes.length
+              outcome = oldVal - newVal
+              pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+7], valueIns: outcome})
+              
+
+              var transf9 = element.transf9
+              corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf9[10+quadrantNumberLocal]))[0] * 100)
+              MIRemainingLoc.push(JSON.parse(transf9[20+quadrantNumberLocal]))
+              transf9 = JSON.parse(transf9[loop-1])
+              oldVal = 0
+              newVal = 0
+              outcome = 0
+              countLoc = 0
+              Object.entries(transf9).forEach(
+              function ([feature, value]) {
+                var key = listofNodes[index]
+                var retrieveData = dataLocOnce[loop-1]
+                var search = Object.values(retrieveData[key])
+                oldVal = Math.abs(search[countLoc]) + oldVal
+                newVal = Math.abs(Object.values(value)[0]) + newVal
+                countLoc++
+              })
+              oldVal = oldVal / listofNodes.length
+              newVal = newVal / listofNodes.length
+              outcome = oldVal - newVal
+              pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+8], valueIns: outcome})
+              
+
+              var transf10 = element.transf10
+              corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf10[10+quadrantNumberLocal]))[0] * 100)
+              MIRemainingLoc.push(JSON.parse(transf10[20+quadrantNumberLocal]))
+              transf10 = JSON.parse(transf10[loop-1])
+              oldVal = 0
+              newVal = 0
+              outcome = 0
+              countLoc = 0
+              Object.entries(transf10).forEach(
+              function ([feature, value]) {
+                var key = listofNodes[index]
+                var retrieveData = dataLocOnce[loop-1]
+                var search = Object.values(retrieveData[key])
+                oldVal = Math.abs(search[countLoc]) + oldVal
+                newVal = Math.abs(Object.values(value)[0]) + newVal
+                countLoc++
+              })
+              oldVal = oldVal / listofNodes.length
+              newVal = newVal / listofNodes.length
+              outcome = oldVal - newVal
+              pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+9], valueIns: outcome})
+              
+
+              var transf11 = element.transf11
+              corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf11[10+quadrantNumberLocal]))[0] * 100)
+              MIRemainingLoc.push(JSON.parse(transf11[20+quadrantNumberLocal]))
+              transf11 = JSON.parse(transf11[loop-1])
+              oldVal = 0
+              newVal = 0
+              outcome = 0
+              countLoc = 0
+              Object.entries(transf11).forEach(
+              function ([feature, value]) {
+                var key = listofNodes[index]
+                var retrieveData = dataLocOnce[loop-1]
+                var search = Object.values(retrieveData[key])
+                oldVal = Math.abs(search[countLoc]) + oldVal
+                newVal = Math.abs(Object.values(value)[0]) + newVal
+                countLoc++
+              })
+              oldVal = oldVal / listofNodes.length
+              newVal = newVal / listofNodes.length
+              outcome = oldVal - newVal
+              pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+10], valueIns: outcome})
+              
+              
+              var transf12 = element.transf12
+              corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf12[10+quadrantNumberLocal]))[0] * 100)
+              MIRemainingLoc.push(JSON.parse(transf12[20+quadrantNumberLocal]))
+              transf12 = JSON.parse(transf12[loop-1])
+              oldVal = 0
+              newVal = 0
+              outcome = 0
+              countLoc = 0
+              Object.entries(transf12).forEach(
+              function ([feature, value]) {
+                var key = listofNodes[index]
+                var retrieveData = dataLocOnce[loop-1]
+                var search = Object.values(retrieveData[key])
+                oldVal = Math.abs(search[countLoc]) + oldVal
+                newVal = Math.abs(Object.values(value)[0]) + newVal
+                countLoc++
+              })
+              oldVal = oldVal / listofNodes.length
+              newVal = newVal / listofNodes.length
+              outcome = oldVal - newVal
+              pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+11], valueIns: outcome})
+
               pushEachFinal.push({key: listofNodes[index], value: pushEach})
             })
             pushEachFinalFinal.push(pushEachFinal)
@@ -235,7 +420,7 @@ export default {
 
       },
       initializeNetwork () {   
-        var numberOfTransformations = 4 // change that
+        var numberOfTransformations = 12 // change that
 
         var featureNames = JSON.parse(this.dataFS[35])
 
@@ -356,6 +541,190 @@ export default {
           newVal = newVal / listofNodes.length
           outcome = oldVal - newVal
           pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+3], valueIns: outcome})
+
+          var transf5 = element.transf5
+          corrMatrixCombLoc.push(Object.values(JSON.parse(transf5[5+quadrantNumberLocal])))
+          corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf5[10+quadrantNumberLocal]))[0] * 100)
+          VIFRemainingLoc.push(Object.values(JSON.parse(transf5[15+quadrantNumberLocal]))[0])
+          MIRemainingLoc.push(JSON.parse(transf5[20+quadrantNumberLocal]))
+          transf5 = JSON.parse(transf5[quadrantNumberLocal])
+          oldVal = 0
+          newVal = 0
+          outcome = 0
+          countLoc = 0
+          Object.entries(transf5).forEach(
+          function ([feature, value]) {
+            var key = listofNodes[index]
+            var search = Object.values(dataLoc[key])
+            oldVal = Math.abs(search[countLoc]) + oldVal
+            newVal = Math.abs(Object.values(value)[0]) + newVal
+            countLoc++
+          })
+          oldVal = oldVal / listofNodes.length
+          newVal = newVal / listofNodes.length
+          outcome = oldVal - newVal
+          pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+4], valueIns: outcome}) 
+ 
+          var transf6 = element.transf6
+          corrMatrixCombLoc.push(Object.values(JSON.parse(transf6[5+quadrantNumberLocal])))
+          corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf6[10+quadrantNumberLocal]))[0] * 100)
+          VIFRemainingLoc.push(Object.values(JSON.parse(transf6[15+quadrantNumberLocal]))[0])
+          MIRemainingLoc.push(JSON.parse(transf6[20+quadrantNumberLocal]))
+          transf6 = JSON.parse(transf6[quadrantNumberLocal])
+          oldVal = 0
+          newVal = 0
+          outcome = 0
+          countLoc = 0
+          Object.entries(transf6).forEach(
+          function ([feature, value]) {
+            var key = listofNodes[index]
+            var search = Object.values(dataLoc[key])
+            oldVal = Math.abs(search[countLoc]) + oldVal
+            newVal = Math.abs(Object.values(value)[0]) + newVal
+            countLoc++
+          })
+          oldVal = oldVal / listofNodes.length
+          newVal = newVal / listofNodes.length
+          outcome = oldVal - newVal
+          pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+5], valueIns: outcome})
+
+          var transf7 = element.transf7
+          corrMatrixCombLoc.push(Object.values(JSON.parse(transf7[5+quadrantNumberLocal])))
+          corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf7[10+quadrantNumberLocal]))[0] * 100)
+          VIFRemainingLoc.push(Object.values(JSON.parse(transf7[15+quadrantNumberLocal]))[0])
+          MIRemainingLoc.push(JSON.parse(transf7[20+quadrantNumberLocal]))
+          transf7 = JSON.parse(transf7[quadrantNumberLocal])
+          oldVal = 0
+          newVal = 0
+          outcome = 0
+          countLoc = 0
+          Object.entries(transf7).forEach(
+          function ([feature, value]) {
+            var key = listofNodes[index]
+            var search = Object.values(dataLoc[key])
+            oldVal = Math.abs(search[countLoc]) + oldVal
+            newVal = Math.abs(Object.values(value)[0]) + newVal
+            countLoc++
+          })
+          oldVal = oldVal / listofNodes.length
+          newVal = newVal / listofNodes.length
+          outcome = oldVal - newVal
+          pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+6], valueIns: outcome})
+          
+          var transf8 = element.transf8
+          corrMatrixCombLoc.push(Object.values(JSON.parse(transf8[5+quadrantNumberLocal])))
+          corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf8[10+quadrantNumberLocal]))[0] * 100)
+          VIFRemainingLoc.push(Object.values(JSON.parse(transf8[15+quadrantNumberLocal]))[0])
+          MIRemainingLoc.push(JSON.parse(transf8[20+quadrantNumberLocal]))
+          transf8 = JSON.parse(transf8[quadrantNumberLocal])
+          oldVal = 0
+          newVal = 0
+          outcome = 0
+          countLoc = 0
+          Object.entries(transf8).forEach(
+          function ([feature, value]) {
+            var key = listofNodes[index]
+            var search = Object.values(dataLoc[key])
+            oldVal = Math.abs(search[countLoc]) + oldVal
+            newVal = Math.abs(Object.values(value)[0]) + newVal
+            countLoc++
+          })
+          oldVal = oldVal / listofNodes.length
+          newVal = newVal / listofNodes.length
+          outcome = oldVal - newVal
+          pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+7], valueIns: outcome})
+          
+          var transf9 = element.transf9
+          corrMatrixCombLoc.push(Object.values(JSON.parse(transf9[5+quadrantNumberLocal])))
+          corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf9[10+quadrantNumberLocal]))[0] * 100)
+          VIFRemainingLoc.push(Object.values(JSON.parse(transf9[15+quadrantNumberLocal]))[0])
+          MIRemainingLoc.push(JSON.parse(transf9[20+quadrantNumberLocal]))
+          transf9 = JSON.parse(transf9[quadrantNumberLocal])
+          oldVal = 0
+          newVal = 0
+          outcome = 0
+          countLoc = 0
+          Object.entries(transf9).forEach(
+          function ([feature, value]) {
+            var key = listofNodes[index]
+            var search = Object.values(dataLoc[key])
+            oldVal = Math.abs(search[countLoc]) + oldVal
+            newVal = Math.abs(Object.values(value)[0]) + newVal
+            countLoc++
+          })
+          oldVal = oldVal / listofNodes.length
+          newVal = newVal / listofNodes.length
+          outcome = oldVal - newVal
+          pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+8], valueIns: outcome})
+
+          var transf10 = element.transf10
+          corrMatrixCombLoc.push(Object.values(JSON.parse(transf10[5+quadrantNumberLocal])))
+          corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf10[10+quadrantNumberLocal]))[0] * 100)
+          VIFRemainingLoc.push(Object.values(JSON.parse(transf10[15+quadrantNumberLocal]))[0])
+          MIRemainingLoc.push(JSON.parse(transf10[20+quadrantNumberLocal]))
+          transf10 = JSON.parse(transf10[quadrantNumberLocal])
+          oldVal = 0
+          newVal = 0
+          outcome = 0
+          countLoc = 0
+          Object.entries(transf10).forEach(
+          function ([feature, value]) {
+            var key = listofNodes[index]
+            var search = Object.values(dataLoc[key])
+            oldVal = Math.abs(search[countLoc]) + oldVal
+            newVal = Math.abs(Object.values(value)[0]) + newVal
+            countLoc++
+          })
+          oldVal = oldVal / listofNodes.length
+          newVal = newVal / listofNodes.length
+          outcome = oldVal - newVal
+          pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+9], valueIns: outcome})
+
+          var transf11 = element.transf11
+          corrMatrixCombLoc.push(Object.values(JSON.parse(transf11[5+quadrantNumberLocal])))
+          corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf11[10+quadrantNumberLocal]))[0] * 100)
+          VIFRemainingLoc.push(Object.values(JSON.parse(transf11[15+quadrantNumberLocal]))[0])
+          MIRemainingLoc.push(JSON.parse(transf11[20+quadrantNumberLocal]))
+          transf11 = JSON.parse(transf11[quadrantNumberLocal])
+          oldVal = 0
+          newVal = 0
+          outcome = 0
+          countLoc = 0
+          Object.entries(transf11).forEach(
+          function ([feature, value]) {
+            var key = listofNodes[index]
+            var search = Object.values(dataLoc[key])
+            oldVal = Math.abs(search[countLoc]) + oldVal
+            newVal = Math.abs(Object.values(value)[0]) + newVal
+            countLoc++
+          })
+          oldVal = oldVal / listofNodes.length
+          newVal = newVal / listofNodes.length
+          outcome = oldVal - newVal
+          pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+10], valueIns: outcome})
+
+          var transf12 = element.transf12
+          corrMatrixCombLoc.push(Object.values(JSON.parse(transf12[5+quadrantNumberLocal])))
+          corrMatrixCombTotalLoc.push(Object.values(JSON.parse(transf12[10+quadrantNumberLocal]))[0] * 100)
+          VIFRemainingLoc.push(Object.values(JSON.parse(transf12[15+quadrantNumberLocal]))[0])
+          MIRemainingLoc.push(JSON.parse(transf12[20+quadrantNumberLocal]))
+          transf12 = JSON.parse(transf12[quadrantNumberLocal])
+          oldVal = 0
+          newVal = 0
+          outcome = 0
+          countLoc = 0
+          Object.entries(transf12).forEach(
+          function ([feature, value]) {
+            var key = listofNodes[index]
+            var search = Object.values(dataLoc[key])
+            oldVal = Math.abs(search[countLoc]) + oldVal
+            newVal = Math.abs(Object.values(value)[0]) + newVal
+            countLoc++
+          })
+          oldVal = oldVal / listofNodes.length
+          newVal = newVal / listofNodes.length
+          outcome = oldVal - newVal
+          pushEach.push({keyIns: featureNames[(index)*numberOfTransformations+11], valueIns: outcome})
           pushEachFinal.push({key: listofNodes[index], value: pushEach})
         })
 
@@ -394,6 +763,14 @@ export default {
             {"name": featureNames[(featureNumber)*numberOfTransformations+1], "group": groupID, "active": false},
             {"name": featureNames[(featureNumber)*numberOfTransformations+2], "group": groupID, "active": false},
             {"name": featureNames[(featureNumber)*numberOfTransformations+3], "group": groupID, "active": false},
+            {"name": featureNames[(featureNumber)*numberOfTransformations+4], "group": groupID, "active": false},
+            {"name": featureNames[(featureNumber)*numberOfTransformations+5], "group": groupID, "active": false},
+            {"name": featureNames[(featureNumber)*numberOfTransformations+6], "group": groupID, "active": false},
+            {"name": featureNames[(featureNumber)*numberOfTransformations+7], "group": groupID, "active": false},
+            {"name": featureNames[(featureNumber)*numberOfTransformations+8], "group": groupID, "active": false},
+            {"name": featureNames[(featureNumber)*numberOfTransformations+9], "group": groupID, "active": false},
+            {"name": featureNames[(featureNumber)*numberOfTransformations+10], "group": groupID, "active": false},
+            {"name": featureNames[(featureNumber)*numberOfTransformations+11], "group": groupID, "active": false},
           )
           featureNumber++
         })

frontend/src/components/FeatureSpaceOverview.vue

@@ -96,7 +96,7 @@ export default {
         svg.selectAll("*").remove();   
 
         var features = this.colorsReceive
-
+        console.log(features)
         var activeLeafLoc = this.activeLeaf
         var listofNodes = this.overallData[34]
 
@@ -184,56 +184,96 @@ export default {
         for (let i = 0; i < features[4].length; i++) {
           featuresQuad1.push({"name": features[0][i].key,
             "children": [  
-              {"name": features[0][i].value[0].keyIns, "lin_color": features[0][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*4+0]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+0])},
+              {"name": features[0][i].value[0].keyIns, "lin_color": features[0][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+0]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+0])},
-              {"name": features[0][i].value[1].keyIns, "lin_color": features[0][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*4+1]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+1])},
+              {"name": features[0][i].value[1].keyIns, "lin_color": features[0][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+1]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+1])},
-              {"name": features[0][i].value[2].keyIns, "lin_color": features[0][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*4+2]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+2])},
+              {"name": features[0][i].value[2].keyIns, "lin_color": features[0][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+2]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+2])},
-              {"name": features[0][i].value[3].keyIns, "lin_color": features[0][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*4+3]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+3])},
+              {"name": features[0][i].value[3].keyIns, "lin_color": features[0][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+3]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+3])},
+              {"name": features[0][i].value[4].keyIns, "lin_color": features[0][i].value[4].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+4]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+4])},
+              {"name": features[0][i].value[5].keyIns, "lin_color": features[0][i].value[5].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+5]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+5])},
+              {"name": features[0][i].value[6].keyIns, "lin_color": features[0][i].value[6].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+6]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+6])},
+              {"name": features[0][i].value[7].keyIns, "lin_color": features[0][i].value[7].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+7]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+7])},
+              {"name": features[0][i].value[8].keyIns, "lin_color": features[0][i].value[8].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+8]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+8])},
+              {"name": features[0][i].value[9].keyIns, "lin_color": features[0][i].value[9].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+9]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+9])},
+              {"name": features[0][i].value[10].keyIns, "lin_color": features[0][i].value[10].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+10]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+10])},
+              {"name": features[0][i].value[11].keyIns, "lin_color": features[0][i].value[11].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[0][i*12+11]), "MI_pick":colorsScaleNodes1(MIVar1[i*features[4].length+11])},
             ],
-            "lin_color": features[0][i].value[0].valueIns+features[0][i].value[1].valueIns+features[0][i].value[2].valueIns+features[0][i].value[3].valueIns,
+            "lin_color": features[0][i].value[0].valueIns+features[0][i].value[1].valueIns+features[0][i].value[2].valueIns+features[0][i].value[3].valueIns+features[0][i].value[4].valueIns+features[0][i].value[5].valueIns+features[0][i].value[6].valueIns+features[0][i].value[7].valueIns+features[0][i].value[8].valueIns+features[0][i].value[9].valueIns+features[0][i].value[10].valueIns+features[0][i].value[11].valueIns,
             "Corr_pick": Math.round(Object.values(corrGlob1)[i+1]['0'] * 100),
             "MI_pick": colorsScaleNodes1(MIVar1[i])
             })
           featuresQuad2.push({"name": features[1][i].key,
             "children": [  
-              {"name": features[1][i].value[0].keyIns, "lin_color": features[1][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*4+0]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+0])},
+              {"name": features[1][i].value[0].keyIns, "lin_color": features[1][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+0]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+0])},
-              {"name": features[1][i].value[1].keyIns, "lin_color": features[1][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*4+1]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+1])},
+              {"name": features[1][i].value[1].keyIns, "lin_color": features[1][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+1]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+1])},
-              {"name": features[1][i].value[2].keyIns, "lin_color": features[1][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*4+2]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+2])},
+              {"name": features[1][i].value[2].keyIns, "lin_color": features[1][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+2]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+2])},
-              {"name": features[1][i].value[3].keyIns, "lin_color": features[1][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*4+3]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+3])},
+              {"name": features[1][i].value[3].keyIns, "lin_color": features[1][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+3]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+3])},
+              {"name": features[1][i].value[4].keyIns, "lin_color": features[1][i].value[4].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+4]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+4])},
+              {"name": features[1][i].value[5].keyIns, "lin_color": features[1][i].value[5].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+5]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+5])},
+              {"name": features[1][i].value[6].keyIns, "lin_color": features[1][i].value[6].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+6]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+6])},
+              {"name": features[1][i].value[7].keyIns, "lin_color": features[1][i].value[7].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+7]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+7])},
+              {"name": features[1][i].value[8].keyIns, "lin_color": features[1][i].value[8].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+8]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+8])},
+              {"name": features[1][i].value[9].keyIns, "lin_color": features[1][i].value[9].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+9]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+9])},
+              {"name": features[1][i].value[10].keyIns, "lin_color": features[1][i].value[10].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+10]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+10])},
+              {"name": features[1][i].value[11].keyIns, "lin_color": features[1][i].value[11].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[1][i*12+11]), "MI_pick":colorsScaleNodes2(MIVar2[i*features[4].length+11])},
             ],
-            "lin_color": features[1][i].value[0].valueIns+features[1][i].value[1].valueIns+features[1][i].value[2].valueIns+features[1][i].value[3].valueIns,
+            "lin_color": features[1][i].value[0].valueIns+features[1][i].value[1].valueIns+features[1][i].value[2].valueIns+features[1][i].value[3].valueIns+features[1][i].value[4].valueIns+features[1][i].value[5].valueIns+features[1][i].value[6].valueIns+features[1][i].value[7].valueIns+features[1][i].value[8].valueIns+features[1][i].value[9].valueIns+features[1][i].value[10].valueIns+features[1][i].value[11].valueIns,
             "Corr_pick": Math.round(Object.values(corrGlob2)[i+1]['0'] * 100),
             "MI_pick": colorsScaleNodes2(MIVar2[i])
             })
           featuresQuad3.push({"name": features[2][i].key,
             "children": [  
-              {"name": features[2][i].value[0].keyIns, "lin_color": features[2][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*4+0]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+0])},
+              {"name": features[2][i].value[0].keyIns, "lin_color": features[2][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+0]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+0])},
-              {"name": features[2][i].value[1].keyIns, "lin_color": features[2][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*4+1]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+1])},
+              {"name": features[2][i].value[1].keyIns, "lin_color": features[2][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+1]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+1])},
-              {"name": features[2][i].value[2].keyIns, "lin_color": features[2][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*4+2]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+2])},
+              {"name": features[2][i].value[2].keyIns, "lin_color": features[2][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+2]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+2])},
-              {"name": features[2][i].value[3].keyIns, "lin_color": features[2][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*4+3]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+3])},
+              {"name": features[2][i].value[3].keyIns, "lin_color": features[2][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+3]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+3])},
+              {"name": features[2][i].value[4].keyIns, "lin_color": features[2][i].value[4].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+4]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+4])},
+              {"name": features[2][i].value[5].keyIns, "lin_color": features[2][i].value[5].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+5]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+5])},
+              {"name": features[2][i].value[6].keyIns, "lin_color": features[2][i].value[6].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+6]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+6])},
+              {"name": features[2][i].value[7].keyIns, "lin_color": features[2][i].value[7].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+7]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+7])},
+              {"name": features[2][i].value[8].keyIns, "lin_color": features[2][i].value[8].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+8]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+8])},
+              {"name": features[2][i].value[9].keyIns, "lin_color": features[2][i].value[9].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+9]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+9])},
+              {"name": features[2][i].value[10].keyIns, "lin_color": features[2][i].value[10].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+10]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+10])},
+              {"name": features[2][i].value[11].keyIns, "lin_color": features[2][i].value[11].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[2][i*12+11]), "MI_pick":colorsScaleNodes3(MIVar3[i*features[4].length+11])},
             ],
-            "lin_color": features[2][i].value[0].valueIns+features[2][i].value[1].valueIns+features[2][i].value[2].valueIns+features[2][i].value[3].valueIns,
+            "lin_color": features[2][i].value[0].valueIns+features[2][i].value[1].valueIns+features[2][i].value[2].valueIns+features[2][i].value[3].valueIns+features[2][i].value[4].valueIns+features[2][i].value[5].valueIns+features[2][i].value[6].valueIns+features[2][i].value[7].valueIns+features[2][i].value[8].valueIns+features[2][i].value[9].valueIns+features[2][i].value[10].valueIns+features[2][i].value[11].valueIns,
             "Corr_pick": Math.round(Object.values(corrGlob3)[i+1]['0'] * 100),
             "MI_pick": colorsScaleNodes3(MIVar3[i])
             })
           featuresQuad4.push({"name": features[3][i].key,
             "children": [  
-              {"name": features[3][i].value[0].keyIns, "lin_color": features[3][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*4+0]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+0])},
+              {"name": features[3][i].value[0].keyIns, "lin_color": features[3][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+0]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+0])},
-              {"name": features[3][i].value[1].keyIns, "lin_color": features[3][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*4+1]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+1])},
+              {"name": features[3][i].value[1].keyIns, "lin_color": features[3][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+1]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+1])},
-              {"name": features[3][i].value[2].keyIns, "lin_color": features[3][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*4+2]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+2])},
+              {"name": features[3][i].value[2].keyIns, "lin_color": features[3][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+2]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+2])},
-              {"name": features[3][i].value[3].keyIns, "lin_color": features[3][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*4+3]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+3])},
+              {"name": features[3][i].value[3].keyIns, "lin_color": features[3][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+3]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+3])},
+              {"name": features[3][i].value[4].keyIns, "lin_color": features[3][i].value[4].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+4]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+4])},
+              {"name": features[3][i].value[5].keyIns, "lin_color": features[3][i].value[5].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+5]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+5])},
+              {"name": features[3][i].value[6].keyIns, "lin_color": features[3][i].value[6].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+6]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+6])},
+              {"name": features[3][i].value[7].keyIns, "lin_color": features[3][i].value[7].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+7]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+7])},
+              {"name": features[3][i].value[8].keyIns, "lin_color": features[3][i].value[8].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+8]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+8])},
+              {"name": features[3][i].value[9].keyIns, "lin_color": features[3][i].value[9].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+9]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+9])},
+              {"name": features[3][i].value[10].keyIns, "lin_color": features[3][i].value[10].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+10]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+10])},
+              {"name": features[3][i].value[11].keyIns, "lin_color": features[3][i].value[11].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[3][i*12+11]), "MI_pick":colorsScaleNodes4(MIVar4[i*features[4].length+11])},
             ],
-            "lin_color": features[3][i].value[0].valueIns+features[3][i].value[1].valueIns+features[3][i].value[2].valueIns+features[3][i].value[3].valueIns,
+            "lin_color": features[3][i].value[0].valueIns+features[3][i].value[1].valueIns+features[3][i].value[2].valueIns+features[3][i].value[3].valueIns+features[3][i].value[4].valueIns+features[3][i].value[5].valueIns+features[3][i].value[6].valueIns+features[3][i].value[7].valueIns+features[3][i].value[8].valueIns+features[3][i].value[9].valueIns+features[3][i].value[10].valueIns+features[3][i].value[11].valueIns,
             "Corr_pick": Math.round(Object.values(corrGlob4)[i+1]['0'] * 100),
             "MI_pick": colorsScaleNodes4(MIVar4[i])
             })
           featuresQuad5.push({"name": features[4][i].key,
             "children": [  
-              {"name": features[4][i].value[0].keyIns, "lin_color": features[4][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*4+0]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+0])},
+              {"name": features[4][i].value[0].keyIns, "lin_color": features[4][i].value[0].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+0]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+0])},
-              {"name": features[4][i].value[1].keyIns, "lin_color": features[4][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*4+1]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+1])},
+              {"name": features[4][i].value[1].keyIns, "lin_color": features[4][i].value[1].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+1]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+1])},
-              {"name": features[4][i].value[2].keyIns, "lin_color": features[4][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*4+2]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+2])},
+              {"name": features[4][i].value[2].keyIns, "lin_color": features[4][i].value[2].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+2]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+2])},
-              {"name": features[4][i].value[3].keyIns, "lin_color": features[4][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*4+3]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+3])},
+              {"name": features[4][i].value[3].keyIns, "lin_color": features[4][i].value[3].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+3]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+3])},
+              {"name": features[4][i].value[4].keyIns, "lin_color": features[4][i].value[4].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+4]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+4])},
+              {"name": features[4][i].value[5].keyIns, "lin_color": features[4][i].value[5].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+5]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+5])},
+              {"name": features[4][i].value[6].keyIns, "lin_color": features[4][i].value[6].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+6]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+6])},
+              {"name": features[4][i].value[7].keyIns, "lin_color": features[4][i].value[7].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+7]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+7])},
+              {"name": features[4][i].value[8].keyIns, "lin_color": features[4][i].value[8].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+8]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+8])},
+              {"name": features[4][i].value[9].keyIns, "lin_color": features[4][i].value[9].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+9]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+9])},
+              {"name": features[4][i].value[10].keyIns, "lin_color": features[4][i].value[10].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+10]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+10])},
+              {"name": features[4][i].value[11].keyIns, "lin_color": features[4][i].value[11].valueIns, "Corr_pick": Math.round(this.overallDataTransfCorr[4][i*12+11]), "MI_pick":colorsScaleNodes5(MIVar5[i*features[4].length+11])},
             ],
-            "lin_color": features[4][i].value[0].valueIns+features[4][i].value[1].valueIns+features[4][i].value[2].valueIns+features[4][i].value[3].valueIns,
+            "lin_color": features[4][i].value[0].valueIns+features[4][i].value[1].valueIns+features[4][i].value[2].valueIns+features[4][i].value[3].valueIns+features[4][i].value[4].valueIns+features[4][i].value[5].valueIns+features[4][i].value[6].valueIns+features[4][i].value[7].valueIns+features[4][i].value[8].valueIns+features[4][i].value[9].valueIns+features[4][i].value[10].valueIns+features[4][i].value[11].valueIns,
             "Corr_pick": Math.round(Object.values(corrGlob5)[i+1]['0'] * 100),
             "MI_pick": colorsScaleNodes5(MIVar5[i])
             })
@@ -302,7 +342,7 @@ export default {
         // current pan, zoom, and rotation
         var curX = width / 2;
         var curY = height / 2;
-        var curZ = 1.22; // current zoom
+        var curZ = 1.18; // current zoom
         var curR = 270; // current rotation
 
         // keyboard key codes

run.py

@@ -134,7 +134,7 @@ def reset():
     columnsNames = []
     
     global listofTransformations
-    listofTransformations = ["r","rE","r2","r10"]
+    listofTransformations = ["r","b","zs","mms","l2","l1p","l10","e2","em1","p2","p3","p4"]
 
     return 'The reset was done!'
 
@@ -248,7 +248,7 @@ def retrieveFileName():
     columnsNames = []
 
     global listofTransformations
-    listofTransformations = ["r","rE","r2","r10"]
+    listofTransformations = ["r","b","zs","mms","l2","l1p","l10","e2","em1","p2","p3","p4"]
 
     DataRawLength = -1
     DataRawLengthTest = -1
@@ -531,17 +531,38 @@ def executeModel(exeCall, flagEx, nodeTransfName):
             else:
                 if (splittedCol[1] == 'r'):
                     XData[nodeTransfName] = XData[nodeTransfName].round()
-                elif (splittedCol[1] == 'rE'):
+                elif (splittedCol[1] == 'b'):
-                    XData[nodeTransfName] = np.log(XData[nodeTransfName])
+                    number_of_bins = np.histogram_bin_edges(XData[nodeTransfName], bins='auto')
-                    XData[nodeTransfName] = XData[nodeTransfName].round()
+                    emptyLabels = []
-                elif (splittedCol[1] == 'r2'):
+                    for index, number in enumerate(number_of_bins):
-                    XData[nodeTransfName] = np.log2(XData[nodeTransfName])
+                        if (index == 0):
-                    XData[nodeTransfName] = XData[nodeTransfName].round()
+                            pass
                         else:
+                            emptyLabels.append(index)
+                    XData[nodeTransfName] = pd.cut(XData[nodeTransfName], bins=number_of_bins, labels=emptyLabels, include_lowest=True, right=True)
+                    XData[nodeTransfName] = pd.to_numeric(XData[nodeTransfName], downcast='signed')
+                elif (splittedCol[1] == 'zs'):
+                    XData[nodeTransfName] = (XData[nodeTransfName]-XData[nodeTransfName].mean())/XData[nodeTransfName].std()
+                elif (splittedCol[1] == 'mms'):
+                    XData[nodeTransfName] = (XData[nodeTransfName]-XData[nodeTransfName].min())/(XData[nodeTransfName].max()-XData[nodeTransfName].min())
+                elif (splittedCol[1] == 'l2'):
+                    XData[nodeTransfName] = np.log2(XData[nodeTransfName])
+                elif (splittedCol[1] == 'l1p'):
+                    XData[nodeTransfName] = np.log1p(XData[nodeTransfName])
+                elif (splittedCol[1] == 'l10'):
                     XData[nodeTransfName] = np.log10(XData[nodeTransfName])
-                    XData[nodeTransfName] = XData[nodeTransfName].round()
+                elif (splittedCol[1] == 'e2'):
+                    XData[nodeTransfName] = np.exp2(XData[nodeTransfName])
+                elif (splittedCol[1] == 'em1'):
+                    XData[nodeTransfName] = np.expm1(XData[nodeTransfName])
+                elif (splittedCol[1] == 'p2'):
+                    XData[nodeTransfName] = np.power(XData[nodeTransfName], 2)
+                elif (splittedCol[1] == 'p3'):
+                    XData[nodeTransfName] = np.power(XData[nodeTransfName], 3)
+                else:
+                    XData[nodeTransfName] = np.power(XData[nodeTransfName], 4)
             XDataStored = XData.copy()     
-    print(XData)       
+            
     columnsNamesLoc = XData.columns.values.tolist()
 
     for col in columnsNamesLoc:
@@ -744,7 +765,6 @@ def Transformation(quadrant1, quadrant2, quadrant3, quadrant4, quadrant5):
         
         splittedCol = columnsNames[(count)*len(listofTransformations)+0].split('_')
         if(len(splittedCol) == 1):
-
             d={}
             XDataNumericCopy = XDataNumeric.copy()
             for number in range(1,6):
@@ -773,8 +793,15 @@ def Transformation(quadrant1, quadrant2, quadrant3, quadrant4, quadrant5):
         else:
             d={}
             XDataNumericCopy = XDataNumeric.copy()
-            XDataNumericCopy[i] = np.log(XDataNumericCopy[i])
+            number_of_bins = np.histogram_bin_edges(XDataNumericCopy[i], bins='auto')
-            XDataNumericCopy[i] = XDataNumericCopy[i].round()
+            emptyLabels = []
+            for index, number in enumerate(number_of_bins):
+                if (index == 0):
+                    pass
+                else:
+                    emptyLabels.append(index)
+            XDataNumericCopy[i] = pd.cut(XDataNumericCopy[i], bins=number_of_bins, labels=emptyLabels, include_lowest=True, right=True)
+            XDataNumericCopy[i] = pd.to_numeric(XDataNumericCopy[i], downcast='signed')
             for number in range(1,6):
                 quadrantVariable = str('quadrant%s' % number)
                 illusion = locals()[quadrantVariable]
@@ -792,8 +819,7 @@ def Transformation(quadrant1, quadrant2, quadrant3, quadrant4, quadrant5):
         else:
             d={}
             XDataNumericCopy = XDataNumeric.copy()
-            XDataNumericCopy[i] = np.log2(XDataNumericCopy[i])
+            XDataNumericCopy[i] = (XDataNumericCopy[i]-XDataNumericCopy[i].mean())/XDataNumericCopy[i].std()
-            XDataNumericCopy[i] = XDataNumericCopy[i].round()
             for number in range(1,6):
                 quadrantVariable = str('quadrant%s' % number)
                 illusion = locals()[quadrantVariable]
@@ -811,13 +837,156 @@ def Transformation(quadrant1, quadrant2, quadrant3, quadrant4, quadrant5):
         else:
             d={}
             XDataNumericCopy = XDataNumeric.copy()
-            XDataNumericCopy[i] = np.log10(XDataNumericCopy[i])
+            XDataNumericCopy[i] = (XDataNumericCopy[i]-XDataNumericCopy[i].min())/(XDataNumericCopy[i].max()-XDataNumericCopy[i].min())
-            XDataNumericCopy[i] = XDataNumericCopy[i].round()
             for number in range(1,6):
                 quadrantVariable = str('quadrant%s' % number)
                 illusion = locals()[quadrantVariable]
                 d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
             dicTransf["transf4"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)          
+        splittedCol = columnsNames[(count)*len(listofTransformations)+4].split('_')
+        if(len(splittedCol) == 1):
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf5"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        else:
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            XDataNumericCopy[i] = np.log2(XDataNumericCopy[i])
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf5"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        splittedCol = columnsNames[(count)*len(listofTransformations)+5].split('_')
+        if(len(splittedCol) == 1):
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf6"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        else:
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            XDataNumericCopy[i] = np.log1p(XDataNumericCopy[i])
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf6"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        splittedCol = columnsNames[(count)*len(listofTransformations)+6].split('_')
+        if(len(splittedCol) == 1):
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf7"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        else:
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            XDataNumericCopy[i] = np.log10(XDataNumericCopy[i])
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf7"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        splittedCol = columnsNames[(count)*len(listofTransformations)+7].split('_')   
+        if(len(splittedCol) == 1):
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf8"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        else:
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            XDataNumericCopy[i] = np.exp2(XDataNumericCopy[i])
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf8"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        splittedCol = columnsNames[(count)*len(listofTransformations)+8].split('_')   
+        if(len(splittedCol) == 1):
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf9"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        else:
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            XDataNumericCopy[i] = np.expm1(XDataNumericCopy[i])
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf9"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        splittedCol = columnsNames[(count)*len(listofTransformations)+9].split('_')   
+        if(len(splittedCol) == 1):
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf10"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        else:
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            XDataNumericCopy[i] = np.power(XDataNumericCopy[i], 2)
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf10"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        splittedCol = columnsNames[(count)*len(listofTransformations)+10].split('_')   
+        if(len(splittedCol) == 1):
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf11"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        else:
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            XDataNumericCopy[i] = np.power(XDataNumericCopy[i], 3)
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf11"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        splittedCol = columnsNames[(count)*len(listofTransformations)+11].split('_')   
+        if(len(splittedCol) == 1):
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf12"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
+        else:
+            d={}
+            XDataNumericCopy = XDataNumeric.copy()
+            XDataNumericCopy[i] = np.power(XDataNumericCopy[i], 4)
+            for number in range(1,6):
+                quadrantVariable = str('quadrant%s' % number)
+                illusion = locals()[quadrantVariable]
+                d["DataRows{0}".format(number)] = XDataNumericCopy.iloc[illusion, :]
+            dicTransf["transf12"] = NewComputationTransf(d['DataRows1'], d['DataRows2'], d['DataRows3'], d['DataRows4'], d['DataRows5'], quadrant1, quadrant2, quadrant3, quadrant4, quadrant5, i, count)
         packCorrTransformed.append(dicTransf)
 
     return 'Everything Okay'
@@ -833,7 +1002,6 @@ def NewComputationTransf(DataRows1, DataRows2, DataRows3, DataRows4, DataRows5,
     corrMatrix4 = corrMatrix4.abs()
     corrMatrix5 = DataRows5.corr()
     corrMatrix5 = corrMatrix5.abs()
-
     corrMatrix1 = corrMatrix1.loc[[feature]]
     corrMatrix2 = corrMatrix2.loc[[feature]]
     corrMatrix3  = corrMatrix3.loc[[feature]]