.

v3.py

         nrows=NumFeaturesToPlot, ncols=1, figsize=(15, 10), dpi=80, facecolor="w", edgecolor="k",sharex=True
     )
     for i in range(NumFeaturesToPlot):
+        x=[]
+        y=[]
+        for k in anomalous_data_indices:
+            if (k+TIME_STEPS)<x_test.shape[0]:
+                x.append(k+TIME_STEPS)
+                y.append(x_test[k+TIME_STEPS,0,indexesToPlot[i]]*stdevs[i]+means[i])
+        axes[i].plot(x,y ,color='black',marker='.',linewidth=0,label="Fail detection" )
+
+
         init=0
         end=testRanges[0][1]
         axes[i].plot(range(init,end),x_test[testRanges[0][0]:testRanges[0][1],0,indexesToPlot[i]]*stdevs[i]+means[i],label="No fail")
         init=end
         end+=(testRanges[1][1]-testRanges[1][0])
         for j in range(1,NumberOfFailures+1):
-            axes[i].plot(range(init,end),x_test[testRanges[j][0]:testRanges[j][1],0,indexesToPlot[i]]*stdevs[i]+means[i],label="Fail type "+str(j), color=colorline[j-1])
+            axes[i].plot(range(init,end),x_test[testRanges[j][0]:testRanges[j][1],0,indexesToPlot[i]]*stdevs[i]+means[i],label="Fail type "+str(j), color=colorline[j-1],linewidth=1)
             if j<NumberOfFailures:
                 init=end
                 end+=(testRanges[j+1][1]-testRanges[j+1][0])
-        x=[]
-        y=[]
-        for k in anomalous_data_indices:
-            if (k+TIME_STEPS)<x_test.shape[0]:
-                x.append(k+TIME_STEPS)
-                y.append(x_test[k+TIME_STEPS,0,indexesToPlot[i]]*stdevs[i]+means[i])
-        axes[i].plot(x,y ,color='grey',marker='.',linewidth=0,label="Fail detection" )
+
 
         if i==(NumFeatures-1):
             axes[i].legend(loc='right')
             if (k+TIME_STEPS)<x_test.shape[0]:
                 x.append(k+TIME_STEPS)
                 y.append(x_test[k+TIME_STEPS,0,indexesToPlot[i]]*stdevs[i]+means[i])
-        axes[i].plot(x,y ,color='grey',marker='.',linewidth=0,label="Fail detection" )
+        axes[i].plot(x,y ,color='black',marker='.',linewidth=0,label="Fail detection" )
 
         if i==(NumFeatures-1):
             axes[i].legend(loc='right')
             if (k+TIME_STEPS)<x_test.shape[0]:
                 x.append(k+TIME_STEPS)
                 y.append(x_test[k+TIME_STEPS,0,indexesToPlot[i]]*stdevs[i]+means[i])
-        axes[i+1].plot(x,y ,color='grey',marker='.',linewidth=0,label="Fail detection" )
+        axes[i+1].plot(x,y ,color='black',marker='.',linewidth=0,label="Fail detection" )
         if i==0:
             axes[i+1].legend(loc='right')
         s=''
             if (k+TIME_STEPS)<x_test.shape[0]:
                 x.append(k+TIME_STEPS)
                 y.append(x_test[k+TIME_STEPS,0,indexesToPlot[i]])
-        axes[i].plot(x,y ,color='grey',marker='.',linewidth=0,label="Fail detection" )
+        axes[i].plot(x,y ,color='black',marker='.',linewidth=0,label="Fail detection" )
 
         if i==0:
             axes[i].legend(bbox_to_anchor=(0.9, 0.4))