Bugs fixed in the DetectOuliers object

dream/KnowledgeExtraction/DetectOutliers.py

@@ -29,10 +29,9 @@ class HandleOutliers(BasicStatisticalMeasures):
 #Two different approaches to handle the outliers are included in this object, 
 #the first one delete both the mild and extreme outliers while the second approach delete only the extreme outliers in the given data set 
     def DeleteOutliers(self,mylist):              #Delete the ouliers (both mild and extreme) in a given data set
-        A= BasicStatisticalMeasures()             #Call the BasicStatisticalMeasures to calculate the quantiles and interquartile range
-        Q1= A.quantile(mylist)[1]
-        Q3= A.quantile(mylist)[3]
-        IQ= A.IQR(mylist)
+        Q1= self.quantile(mylist)[1]
+        Q3= self.quantile(mylist)[3]
+        IQ= self.IQR(mylist)
         LIF= Q1 - 1.5*IQ                        #Calculate the lower inner fence
         UIF= Q3 + 1.5*IQ                        #Calculate the upper inner fence
         LOF= Q1 - 3*IQ                          #Calculate the lower outer fence
@@ -40,22 +39,21 @@ class HandleOutliers(BasicStatisticalMeasures):
         i=0
         listx=[]
         for value in mylist:                       
-            if not ((value<LOF or value>UOF) or (value<LIF or value>UIF)):    #If the value is beyond the inner fence ([LIF,UIF]) on either side (mild outlier) or beyond the outer fence ([LOF,UOF]) on either side (extreme outlier) doesn't pass the control and deleted  
+            if not ((float(value)<float(LOF) or float(value)>float(UOF)) or (float(value)<float(LIF) or float(value)>float(UIF))):    #If the value is beyond the inner fence ([LIF,UIF]) on either side (mild outlier) or beyond the outer fence ([LOF,UOF]) on either side (extreme outlier) doesn't pass the control and deleted  
                 listx.append(value)
             i+=1 
         return listx
     
     def DeleteExtremeOutliers(self,mylist):            #Delete only the  extreme ouliers in a given data set
-        A= BasicStatisticalMeasures()
-        Q1= A.quantile(mylist)[1]
-        Q3= A.quantile(mylist)[3]
-        IQ= A.IQR(mylist)
+        Q1= self.quantile(mylist)[1]
+        Q3= self.quantile(mylist)[3]
+        IQ= self.IQR(mylist)
         LOF= Q1 - 3*IQ 
         UOF= Q3 + 3*IQ
         i=0
         listx=[]
         for value in mylist:
-            if not (value<LOF or value>UOF):           #If the value is  beyond the outer fence ([LOF,UOF]) on either side (extreme outlier) doesn't pass the control and deleted  
+            if not (float(value)<float(LOF) or float(value)>float(UOF)):           #If the value is  beyond the outer fence ([LOF,UOF]) on either side (extreme outlier) doesn't pass the control and deleted  
                 listx.append(value)
             i+=1
         return listx