A test created for this example

dream/KnowledgeExtraction/KEtool_examples/ConveyerLine/KEtool_MainScript.py

@@ -29,49 +29,67 @@ from dream.KnowledgeExtraction.JSONOutput import JSONOutput
 from dream.KnowledgeExtraction.DetectOutliers import HandleOutliers
 from dream.KnowledgeExtraction.ReplaceMissingValues import HandleMissingValues
 import json
+import os
 ################### Import data using the ImportCSVdataobject ###################################
-filename1=("DataSet.csv")
-filename2=("InterArrivalData.csv")
-CSV=Import_CSV()   #call the Import_CSV module and using its method Input_data import the data set from the CSV file to the tool
-procData=CSV.Input_data(filename1)
-sourceData=CSV.Input_data(filename2)
-M1=procData.get('M1',[])       #get from the returned Python dictionary the data sets
-M2=procData.get('M2',[])
-S1=sourceData.get('S1',[])
-
-################### Processing of the data sets calling the following objects ###################################
-#Replace missing values calling the corresponding object
-missingValues=HandleMissingValues()
-M1=missingValues.DeleteMissingValue(M1)
-M2=missingValues.DeleteMissingValue(M2)
-S1=missingValues.ReplaceWithMean(S1)
-
-#Detect outliers calling the DetectOutliers object
-outliers=HandleOutliers()
-M1=outliers.DeleteExtremeOutliers(M1)
-M2=outliers.DeleteExtremeOutliers(M2)
-S1=outliers.DeleteOutliers(S1)
-
-#Conduct distribution fitting calling the Distributions object and DistFittest object
-MLE=Distributions()
-KStest=DistFittest()
-M1=KStest.ks_test(M1)
-M2=KStest.ks_test(M2)
-S1=MLE.Exponential_distrfit(S1)
-#================================= Output preparation: output the updated values in the JSON file of this example =========================================================#
-jsonFile = open('JSON_ConveyerLine.json','r')      #It opens the JSON file 
-data = json.load(jsonFile)                         #It loads the file
-jsonFile.close()
-
-exportJSON=JSONOutput()
-stationId1='M1'
-stationId2='M2'
-stationId3='S1'
-
-data=exportJSON.ProcessingTimes(data, stationId1, M1)                           
-data1=exportJSON.ProcessingTimes(data, stationId2, M2)
-data2=exportJSON.InterarrivalTime(data1, stationId3, S1)
-
-jsonFile = open('JSON_ConveyerLine_Output.json',"w")     #It opens the JSON file
-jsonFile.write(json.dumps(data2, indent=True))           #It writes the updated data to the JSON file 
-jsonFile.close()                                         #It closes the file
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+def main(test=0, CSVFileName1='InterArrivalData.csv',
+                CSVFileName2='DataSet.csv',
+                JSONFileName='JSON_ConveyerLine.json',
+                jsonFile=None, csvFile1=None, csvFile2=None):
+    if csvFile2:
+        CSVFileName2 = csvFile2.name
+    if csvFile1:
+        CSVFileName1 = csvFile1.name
+    
+    CSV=Import_CSV()   #call the Import_CSV module and using its method Input_data import the data set from the CSV file to the tool
+    procData=CSV.Input_data(CSVFileName2)
+    sourceData=CSV.Input_data(CSVFileName1)
+    M1=procData.get('M1',[])       #get from the returned Python dictionary the data sets
+    M2=procData.get('M2',[])
+    S1=sourceData.get('S1',[])
+    
+    ################### Processing of the data sets calling the following objects ###################################
+    #Replace missing values calling the corresponding object
+    missingValues=HandleMissingValues()
+    M1=missingValues.DeleteMissingValue(M1)
+    M2=missingValues.DeleteMissingValue(M2)
+    S1=missingValues.ReplaceWithMean(S1)
+    
+    #Detect outliers calling the DetectOutliers object
+    outliers=HandleOutliers()
+    M1=outliers.DeleteExtremeOutliers(M1)
+    M2=outliers.DeleteExtremeOutliers(M2)
+    S1=outliers.DeleteOutliers(S1)
+    
+    #Conduct distribution fitting calling the Distributions object and DistFittest object
+    MLE=Distributions()
+    KStest=DistFittest()
+    M1=KStest.ks_test(M1)
+    M2=KStest.ks_test(M2)
+    S1=MLE.Exponential_distrfit(S1)
+    #================================= Output preparation: output the updated values in the JSON file of this example =========================================================#
+    if not jsonFile:
+        jsonFile = open(os.path.join(os.path.dirname(os.path.realpath(__file__)), JSONFileName),'r')      #It opens the JSON file 
+        data = json.load(jsonFile)             #It loads the file
+        jsonFile.close()
+    else:
+        data = json.load(jsonFile) 
+    
+    exportJSON=JSONOutput()
+    stationId1='M1'
+    stationId2='M2'
+    stationId3='S1'
+    
+    data=exportJSON.ProcessingTimes(data, stationId1, M1)                           
+    data1=exportJSON.ProcessingTimes(data, stationId2, M2)
+    data2=exportJSON.InterarrivalTime(data1, stationId3, S1)
+    
+    # if we run from test return the data2
+    if test:
+        return data2
+    
+    jsonFile = open('JSON_ConveyerLine_Output.json',"w")     #It opens the JSON file
+    jsonFile.write(json.dumps(data2, indent=True))           #It writes the updated data to the JSON file 
+    jsonFile.close()                                         #It closes the file
+    
+if __name__ == '__main__':
+    main()
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