Bug fixed in the objects of the tool

dream/KnowledgeExtraction/ConfidenceIntervals.py

@@ -25,7 +25,7 @@ Created on 16 Nov 2013
 from rpy2 import robjects
 
 #The ConfidenceIntervals object
-class Intervals:
+class Intervals(object):
     #Calculate the p (decimal number) confidence intervals for a sample of data
     def ConfidIntervals(self,data,p): 
   

dream/KnowledgeExtraction/DataManipulation.py

@@ -26,7 +26,7 @@ Created on 16 Apr 2014
 import rpy2.robjects as robjects
 
 #The DataManipulation object
-class DataManagement:
+class DataManagement(object):
     
     def round(self, data):                      #returns the rounded values of the data sample
         data=robjects.FloatVector(data)          ##The given list changes into float vector in order to be handled by RPy2

dream/KnowledgeExtraction/DistributionFitting.py

@@ -35,7 +35,7 @@ MASS= importr('MASS')
 #DistFittest object: for Kolmogorov-Smirnov distribution fitting test in order to find the best distribution fitting for the given data points
 
 #The Distributions object
-class Distributions:
+class Distributions(object):
            
     def Normal_distrfit(self,data):
         data=robjects.FloatVector(data)     #The given data sample changes into float vector in order to be handled by RPy2
@@ -139,7 +139,7 @@ class Distributions:
         return myDict
         
 #The Distribution Fitting test object
-class DistFittest:
+class DistFittest(object):
     
     def Norm_kstest(self,data):             
         data=robjects.FloatVector(data)         #The given data sample changes into float vector in order to be handled by RPy2

dream/KnowledgeExtraction/ImportCSVdata.py

@@ -23,7 +23,7 @@ Created on 13 Jun 2014
 # ===========================================================================
 import csv
 #The Import_CSV object
-class Import_CSV:
+class Import_CSV(object):
 #This object reads data from a CSV document
     def Input_data(self,fileName):         #This method takes as an argument the Name of the CSV file
         #Opens the CSV for the reader to use

dream/KnowledgeExtraction/ImportExceldata.py

@@ -23,7 +23,7 @@ Created on 19 Feb 2014
 @author: Panos
 '''
 #The Import_Excel object
-class Import_Excel:
+class Import_Excel(object):
 #This object reads data from different worksheets of an Excel document
     def Input_data(self,worksheetName,inputbook):         #This method takes as an argument the Name of the preferred worksheet 
             

dream/KnowledgeExtraction/Plots.py

@@ -25,7 +25,7 @@ Created on 16 Dec 2013
 from rpy2 import robjects
 
 #The Graphs object
-class Graphs:
+class Graphs(object):
     #Graphs that can visualize the data samples 
     
     def Plots(self,data, fileName="plotChart.jpg"):

dream/KnowledgeExtraction/Simul8XML.py

@@ -27,7 +27,7 @@ Created on 27 Nov 2014
 # By using this script the KE tool integrates with Simul8 accessing the XML of one model and modifying several info based on the available data
 from xml.etree import ElementTree as et
 # The Distributions object
-class Simul8Output:
+class Simul8Output(object):
     
     def Simul8Dist(self,dist):     #Using this method the statistical distributions from the DistributionFitting objects translated to meaningful info for the Simul8 package
         self.sim8Dist=[]

dream/KnowledgeExtraction/StatisticalMeasures.py

@@ -28,7 +28,7 @@ from rpy2.robjects.packages import importr
 MASS= importr('MASS')
 
 #The BasicStatisticalMeasures object
-class BasicStatisticalMeasures:
+class BasicStatisticalMeasures(object):
 # A variety of statistical measures are calculated in this object
     def length(self, data):                      #Calculate the length of data sample
         data=robjects.FloatVector(data)          ##The given list changes into float vector in order to be handled by RPy2

dream/KnowledgeExtraction/Transformations.py

@@ -26,7 +26,7 @@ Created on 14 Nov 2013
 import rpy2.robjects as robjects
 
 #The BasicTransformations object
-class BasicTransformations:
+class BasicTransformations(object):
 # A variety of transformations are calculated in this object
     def sum(self, data):                      #calculates the sum of data sample
         data=robjects.FloatVector(data)          ##The given list changes into float vector in order to be handled by RPy2