Examples updated for testing

dream/KnowledgeExtraction/KEtool_examples/TwoServers/TwoServers_example.py

@@ -29,7 +29,7 @@ from dream.KnowledgeExtraction.JSONOutput import JSONOutput
 from dream.KnowledgeExtraction.ReplaceMissingValues import HandleMissingValues
 import dream.simulation.LineGenerationJSON as ManPyMain #import ManPy main JSON script
 from xml.etree import ElementTree as et
-from CMSDOutput import CMSDOutput
+from dream.KnowledgeExtraction.CMSDOutput import CMSDOutput
 import xlrd
 import json
 
@@ -38,67 +38,86 @@ import json
 #The following is the Main script, that calls two Python objects in order to conduct the three main components of the Knowledge extraction tool
 #In the following example the operation times of the topology's two machines are given in an Excel document. 
 #Import_Excel object imports data from the Excel document to the tool and DistFittest object fits the data to a statistical distribution using Kolmogorov-Smirnov test
-   
-workbook = xlrd.open_workbook('inputsTwoServers.xls')      #Using xlrd library opens the Excel document with the input data 
-worksheets = workbook.sheet_names()
-worksheet_OperationTime = worksheets[0]             #It creates a variable that holds the first Excel worksheet 
- 
-X=Import_Excel()                                    #Call the import_Excel object
-OperationTimes= X.Input_data(worksheet_OperationTime,workbook)      #It defines a Python dictionary, giving as name OpearationTimes and as value the returned dictionary from the import_Excel object 
-Machine1_OpearationTimes = OperationTimes.get('Machine1',[])        #Two lists are defined (Machine1_OpearationTimes, Machine2_OpearationTimes) with the operation times data of each machine
-Machine2_OpearationTimes = OperationTimes.get('Machine2',[])
-
-A=HandleMissingValues()                                     #Call the HandleMissingValues object
-Machine1_OpearationTimes= A.DeleteMissingValue(Machine1_OpearationTimes)        #It deletes the missing values in the lists with the operation times data
-Machine2_OpearationTimes= A.DeleteMissingValue(Machine2_OpearationTimes)
-
-Dict={}
-B=DistFittest()                                     #It calls the DistFittest object
-Dict['M1']=B.ks_test(Machine1_OpearationTimes)                 #It conducts the Kolmogorov-Smirnov test in the list with the operation times data 
-Dict['M2']=B.ks_test(Machine2_OpearationTimes)
-M1=Dict.get('M1')
-M2=Dict.get('M2')
-
-
-#==================================== Output preparation: output the updated values in the CMSD information model ====================================================#
-
-datafile=('CMSD_TwoServers.xml')       #It defines the name or the directory of the XML file that is manually written the CMSD information model
-tree = et.parse(datafile)                                               #This file will be parsed using the XML.ETREE Python library
-
-exportCMSD=CMSDOutput()
-stationId1='A020'
-stationId2='A040'
-procTime1=exportCMSD.ProcessingTimes(tree, stationId1, M1) 
-procTime2=exportCMSD.ProcessingTimes(procTime1, stationId2, M2)
-
-procTime2.write('CMSD_TwoServers_Output.xml',encoding="utf8")                         #It writes the element tree to a specified file, using the 'utf8' output encoding
-#================================= Output preparation: output the updated values in the JSON file of Topology10 =========================================================#
-jsonFile= open('JSON_TwoServers.json','r')      #It opens the Topology10 JSON file 
-data = json.load(jsonFile)                                                              #It loads the file
-jsonFile.close()
-
-exportJSON=JSONOutput()
-stationId1='M1'
-stationId2='M2'
-data=exportJSON.ProcessingTimes(data, stationId1, M1)                           
-data1=exportJSON.ProcessingTimes(data, stationId2, M2)         
-
-jsonFile = open('JSON_TwoServers_Output.json',"w")     #It opens the JSON file
-jsonFile.write(json.dumps(data1, indent=True))                                           #It writes the updated data to the JSON file 
-jsonFile.close()                                                                        #It closes the file
     
-#================================ Calling the ExcelOutput object, outputs the outcomes of the statistical analysis in Excel files =============================================#
-C=Output()
-C.PrintDistributionFit(Machine1_OpearationTimes,'Machine1_DistFitResults.xls')   
-C.PrintStatisticalMeasures(Machine1_OpearationTimes,'Machine1_StatResults.xls')
-C.PrintDistributionFit(Machine2_OpearationTimes,'Machine2_DistFitResults.xls')   
-C.PrintStatisticalMeasures(Machine2_OpearationTimes,'Machine2_StatResults.xls')
+def main(test=0, ExcelFileName='inputsTwoServers.xls',
+                JSONFileName='JSON_TwoServers.json',
+                CMSDFileName='CMSD_TwoServers.xml',
+                workbook=None,
+                jsonFile=None, cmsdFile=None):
+    if not workbook:
+        workbook = xlrd.open_workbook(ExcelFileName)      #Using xlrd library opens the Excel document with the input data      
+    worksheets = workbook.sheet_names()
+    worksheet_OperationTime = worksheets[0]             #It creates a variable that holds the first Excel worksheet 
+     
+    X=Import_Excel()                                    #Call the import_Excel object
+    OperationTimes= X.Input_data(worksheet_OperationTime,workbook)      #It defines a Python dictionary, giving as name OpearationTimes and as value the returned dictionary from the import_Excel object 
+    Machine1_OpearationTimes = OperationTimes.get('Machine1',[])        #Two lists are defined (Machine1_OpearationTimes, Machine2_OpearationTimes) with the operation times data of each machine
+    Machine2_OpearationTimes = OperationTimes.get('Machine2',[])
+    
+    A=HandleMissingValues()                                     #Call the HandleMissingValues object
+    Machine1_OpearationTimes= A.DeleteMissingValue(Machine1_OpearationTimes)        #It deletes the missing values in the lists with the operation times data
+    Machine2_OpearationTimes= A.DeleteMissingValue(Machine2_OpearationTimes)
+    
+    Dict={}
+    B=DistFittest()                                     #It calls the DistFittest object
+    Dict['M1']=B.ks_test(Machine1_OpearationTimes)                 #It conducts the Kolmogorov-Smirnov test in the list with the operation times data 
+    Dict['M2']=B.ks_test(Machine2_OpearationTimes)
+    M1=Dict.get('M1')
+    M2=Dict.get('M2')
+        
+    #==================================== Output preparation: output the updated values in the CMSD information model ====================================================#
+    if not cmsdFile:
+        datafile=CMSDFileName       #It defines the name or the directory of the XML file that is manually written the CMSD information model
+        tree = et.parse(datafile)                                               #This file will be parsed using the XML.ETREE Python library
+    
+    exportCMSD=CMSDOutput()
+    stationId1='A020'
+    stationId2='A040'
+    procTime1=exportCMSD.ProcessingTimes(tree, stationId1, M1) 
+    procTime2=exportCMSD.ProcessingTimes(procTime1, stationId2, M2)
+    
+    procTime2.write('CMSD_TwoServers_Output.xml',encoding="utf8")                         #It writes the element tree to a specified file, using the 'utf8' output encoding
+    #================================= Output preparation: output the updated values in the JSON file of Topology10 =========================================================#
+    if not jsonFile:
+        jsonFile = open(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'
+    data=exportJSON.ProcessingTimes(data, stationId1, M1)                           
+    data1=exportJSON.ProcessingTimes(data, stationId2, M2)         
+    
+    #================================ Call ManPy and run the simulation model =============================================#
+    #calls ManPy main script with the input
+    simulationOutput=ManPyMain.main(input_data=json.dumps(data1))
+    
+    # if we run from test return the ManPy result
+    if test:
+        return simulationOutput
+    
+    #=================== Ouput the JSON file ==========================#
+    jsonFile = open('JSON_TwoServers_Output.json',"w")     #It opens the JSON file
+    jsonFile.write(json.dumps(data1, indent=True))                                           #It writes the updated data to the JSON file 
+    jsonFile.close()                                                                        #It closes the file
+        
+    #================================ Calling the ExcelOutput object, outputs the outcomes of the statistical analysis in Excel files =============================================#
+    C=Output()
+    C.PrintDistributionFit(Machine1_OpearationTimes,'Machine1_DistFitResults.xls')   
+    C.PrintStatisticalMeasures(Machine1_OpearationTimes,'Machine1_StatResults.xls')
+    C.PrintDistributionFit(Machine2_OpearationTimes,'Machine2_DistFitResults.xls')   
+    C.PrintStatisticalMeasures(Machine2_OpearationTimes,'Machine2_StatResults.xls')
+    
+    #================================ Call ManPy and run the simulation model =============================================#
+    #calls ManPy main script with the input
+    simulationOutput=ManPyMain.main(input_data=json.dumps(data))
+    # save the simulation output
+    jsonFile = open('ManPyOutput.json',"w")     #It opens the JSON file
+    jsonFile.write(simulationOutput)                                           #It writes the updated data to the JSON file 
+    jsonFile.close()                                                                        #It closes the file
 
-#================================ Call ManPy and run the simulation model =============================================#
-#calls ManPy main script with the input
-simulationOutput=ManPyMain.main(input_data=json.dumps(data))
-# save the simulation output
-jsonFile = open('ManPyOutput.json',"w")     #It opens the JSON file
-jsonFile.write(simulationOutput)                                           #It writes the updated data to the JSON file 
-jsonFile.close()                                                                        #It closes the file
-    
\ No newline at end of file
+if __name__ == '__main__':
+    main()    
\ No newline at end of file