test

Former-commit-id: cdbdf49b16

tsneGrid.py

@@ -399,9 +399,8 @@ def OptimizeSelection():
         resultContinuity = continuity(D_highSpace[dataSelected, :], D_lowSpaceList[index][dataSelected, :], KeepKs[index])
         resultStress = normalized_stress(D_highSpace[dataSelected, :], D_lowSpaceList[index][dataSelected, :])
         resultShep = shepard_diagram_correlation(D_highSpace[dataSelected][:, dataSelected], D_lowSpaceList[index][dataSelected][:, dataSelected]) 
-        resultAverage = (resultNeigh + resultTrust + resultContinuity + resultStress + resultShep) / 5
-        print(resultAverage)
-        metricsAverage.append(resultAverage)
+
+
         metricNeigh.append(resultNeigh)
         metricTrust.append(resultTrust)
         metricCont.append(resultContinuity)
@@ -430,18 +429,18 @@ def OptimizeSelection():
         valueNeigh = (metricNeigh[index] - min_value_neigh) / (max_value_neigh - min_value_neigh) 
         valueTrust = (metricTrust[index] - min_value_trust) / (max_value_trust - min_value_trust) 
         valueCont = (metricCont[index] - min_value_cont) / (max_value_cont - min_value_cont) 
-        valueStress = (metricStress[index] - min_value_stress) / (max_value_stress - min_value_stress) 
+        valueStress = 1 - ((metricStress[index]*(-1) - max_value_stress*(-1)) / (min_value_stress*(-1) - max_value_stress*(-1))) # we need the opposite
         valueShep = (metricShepCorr[index] - min_value_shep) / (max_value_shep - min_value_shep) 
         average = (valueNeigh + valueTrust + valueCont + valueStress + valueShep) / 5
+        
+        metricsAverage.append(average)
         metricsMatrixEntireSel.append([average,valueNeigh,valueTrust,valueCont,valueStress,valueShep])
 
     sortMetricsAverage = sorted(range(len(metricsAverage)), key=lambda k: metricsAverage[k], reverse=True)
-    print(sortMetricsAverage)
-    print(metricsAverage)
     sortNeigh = sorted(range(len(metricNeigh)), key=lambda k: metricNeigh[k], reverse=True)
     sortTrust = sorted(range(len(metricTrust)), key=lambda k: metricTrust[k], reverse=True)
     sortCont = sorted(range(len(metricCont)), key=lambda k: metricCont[k], reverse=True)
-    sortStress = sorted(range(len(metricStress)), key=lambda k: metricStress[k], reverse=False)
+    sortStress = sorted(range(len(metricStress)), key=lambda k: metricStress[k], reverse=True)
     sortShepCorr = sorted(range(len(metricShepCorr)), key=lambda k: metricShepCorr[k], reverse=True)
 
     global metricsMatrixSel