Commit dcd6d9a6 authored by panos's avatar panos

The main script amended

parent 1c358f43
...@@ -29,11 +29,10 @@ from dream.KnowledgeExtraction.DistributionFitting import DistFittest ...@@ -29,11 +29,10 @@ from dream.KnowledgeExtraction.DistributionFitting import DistFittest
from dream.KnowledgeExtraction.ReplaceMissingValues import ReplaceMissingValues from dream.KnowledgeExtraction.ReplaceMissingValues import ReplaceMissingValues
from dream.KnowledgeExtraction.ImportDatabase import ConnectionData from dream.KnowledgeExtraction.ImportDatabase import ConnectionData
from dream.KnowledgeExtraction.DetectOutliers import DetectOutliers from dream.KnowledgeExtraction.DetectOutliers import DetectOutliers
from JSONOutput import JSONOutput from dream.KnowledgeExtraction.JSONOutput import JSONOutput
from dream.KnowledgeExtraction.CMSDOutput import CMSDOutput import dream.simulation.LineGenerationJSON as ManPyMain
from xml.etree import ElementTree as et
# from WIP_Identifier import currentWIP
import xlrd import xlrd
import json
from dateutil.parser import * from dateutil.parser import *
import datetime import datetime
from time import mktime from time import mktime
...@@ -334,25 +333,75 @@ dictProc['PaA']= D.ks_test(PaA_Proc) ...@@ -334,25 +333,75 @@ dictProc['PaA']= D.ks_test(PaA_Proc)
dictProc['Pb']= D.ks_test(Pb_Proc) dictProc['Pb']= D.ks_test(Pb_Proc)
#Call the Distributions object and fit (using the Maximum Likelihood Estimation) the lists with the scrap quantity into a discrete statistical distribution, i.e. Geometric distribution #Call the Distributions object and fit (using the Maximum Likelihood Estimation) the lists with the scrap quantity into a discrete statistical distribution, i.e. Geometric distribution
D=Distributions() E=Distributions()
dictScrap={} #Create a dictionary that holds the Geometric, which is a discrete statistical distribution of the processing times of each station dictScrap={} #Create a dictionary that holds the Geometric, which is a discrete statistical distribution of the processing times of each station
dictScrap['MA']= D.Geometric_distrfit(MA_Scrap) dictScrap['MA']= E.Geometric_distrfit(MA_Scrap)
dictScrap['M1A']= D.Geometric_distrfit(M1A_Scrap) dictScrap['M1A']= E.Geometric_distrfit(M1A_Scrap)
dictScrap['M1B']= D.Geometric_distrfit(M1B_Scrap) dictScrap['M1B']= E.Geometric_distrfit(M1B_Scrap)
dictScrap['M2A']= D.Geometric_distrfit(M2A_Scrap) dictScrap['M2A']= E.Geometric_distrfit(M2A_Scrap)
dictScrap['M2B']= D.Geometric_distrfit(M2B_Scrap) dictScrap['M2B']= E.Geometric_distrfit(M2B_Scrap)
dictScrap['M3A']= D.Geometric_distrfit(M3A_Scrap) dictScrap['M3A']= E.Geometric_distrfit(M3A_Scrap)
dictScrap['M3B']= D.Geometric_distrfit(M3B_Scrap) dictScrap['M3B']= E.Geometric_distrfit(M3B_Scrap)
dictScrap['CB']= D.Geometric_distrfit(CB_Scrap) dictScrap['CB']= E.Geometric_distrfit(CB_Scrap)
dictScrap['MM']= D.Geometric_distrfit(MM_Scrap) dictScrap['MM']= E.Geometric_distrfit(MM_Scrap)
dictScrap['FL']= D.Geometric_distrfit(FL_Scrap) dictScrap['FL']= E.Geometric_distrfit(FL_Scrap)
dictScrap['PrA']= D.Geometric_distrfit(PrA_Scrap) dictScrap['PrA']= E.Geometric_distrfit(PrA_Scrap)
dictScrap['PrB']= D.Geometric_distrfit(PrB_Scrap) dictScrap['PrB']= E.Geometric_distrfit(PrB_Scrap)
dictScrap['PaA']= D.Geometric_distrfit(PaA_Scrap) dictScrap['PaA']= E.Geometric_distrfit(PaA_Scrap)
dictScrap['Pb']= D.Geometric_distrfit(Pb_Scrap) dictScrap['Pb']= E.Geometric_distrfit(Pb_Scrap)
jsonFile = open('JSON_DBBatchModel.json','r') #It opens the JSON file
data = json.load(jsonFile) #It loads the file
jsonFile.close()
exportJSON=JSONOutput()
FL= D.ks_test(FL_Proc)
data=exportJSON.ProcessingTimes(data, "Dream.BatchSource1", dictProc['MA'])
data1=exportJSON.ProcessingTimes(data, "1_RO_E_M_A_A", dictProc['M1A'])
data2=exportJSON.ProcessingTimes(data1, "2_P_B_A_A", dictProc['M2A'])
data3=exportJSON.ProcessingTimes(data2, "3_D_B_A_A", dictProc['M3A'])
data4=exportJSON.ProcessingTimes(data3, "1_RO_E_M_A_B", dictProc['M1B'])
data5=exportJSON.ProcessingTimes(data4, "2_P_B_A_B", dictProc['M2B'])
data6=exportJSON.ProcessingTimes(data5, "3_D_B_A_B", dictProc['M3B'])
data7=exportJSON.ProcessingTimes(data6, "4_Cut & Bend", dictProc['CB'])
data8=exportJSON.ProcessingTimes(data7, "5_Moulding", dictProc['MM'])
data9=exportJSON.ProcessingTimes(data8, "6_Flag Labelling A", dictProc['FL'])
data10=exportJSON.ProcessingTimes(data9, "6_Flag Labelling B", D.ks_test(FL_Proc))
data11=exportJSON.ProcessingTimes(data10, "7_Pressure A", dictProc['PrA'])
data12=exportJSON.ProcessingTimes(data11, "7_Pressure B", dictProc['PrB'])
data13=exportJSON.ProcessingTimes(data12, "8_Carding", dictProc['Pb'])
data14=exportJSON.ProcessingTimes(data13, "9_Packaging A", dictProc['PaA'])
data15=exportJSON.ProcessingTimes(data14, "9_Packaging B", D.ks_test(PaA_Proc))
data16=exportJSON.scrapping(data15, "1_RO_E_M_A_A", dictScrap['M1A'])
data17=exportJSON.scrapping(data16, "2_P_B_A_A", dictScrap['M2A'])
data18=exportJSON.scrapping(data17, "3_D_B_A_A", dictScrap['M3A'])
data19=exportJSON.scrapping(data18, "1_RO_E_M_A_B", dictScrap['M1B'])
data20=exportJSON.scrapping(data19, "2_P_B_A_B", dictScrap['M2B'])
data21=exportJSON.scrapping(data20, "3_D_B_A_B", dictScrap['M3B'])
data22=exportJSON.scrapping(data21, "4_Cut & Bend", dictScrap['CB'])
data23=exportJSON.scrapping(data22, "5_Moulding", dictScrap['MM'])
data24=exportJSON.scrapping(data23, "6_Flag Labelling A", dictScrap['FL'])
data25=exportJSON.scrapping(data24, "6_Flag Labelling B", E.Geometric_distrfit(FL_Scrap))
data26=exportJSON.scrapping(data25, "7_Pressure A", dictScrap['PrA'])
data27=exportJSON.scrapping(data26, "7_Pressure B", dictScrap['PrB'])
data28=exportJSON.scrapping(data27, "8_Carding", dictScrap['Pb'])
data29=exportJSON.scrapping(data28, "9_Packaging A", dictScrap['PaA'])
data30=exportJSON.scrapping(data29, "9_Packaging B", E.Geometric_distrfit(PaA_Scrap))
jsonFile = open('JSON_DBBatchModel_Output.json',"w") #It opens the JSON file
jsonFile.write(json.dumps(data30, indent=True)) #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(data30))
# 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
......
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