.

v5_class.py

     print("F1-Score: ",F1)
 
 anomalyMetric(classes,testRanges,testClasses)
-plotData4()
-exit(0)
 # Compute delay until correct detection for a list of ranges (when transition data exists)
 def computeDelay(l,classes,testRanges,testClasses):
     d=np.zeros(len(l))
     return(d.mean())
 
 d=computeDelay([2,3,4],classes,testRanges,testClasses)
+print("Delay: ",d)
 
-
+plotData4()