def main(test=0, CSVFileName='DataSet.csv', csvFile=None):
if csvFile:
CSVFileName = csvFile.name
filename = CSVFileName
data = ImportCSVdata(
) #call the Import_CSV module and using its method Input_data import the data set from the CSV file to the tool
Data = data.Input_data(filename)
ProcTime = Data.get(
'ProcessingTimes',
[]) #get from the returned Python dictionary the three data sets
MTTF = Data.get('MTTF', [])
MTTR = Data.get('MTTR', [])
CI = ConfidenceIntervals() #create a Intervals object
DM = DataManipulation()
if test:
return DM.round(CI.ConfidIntervals(
ProcTime, 0.95)), CI.ConfidIntervals(MTTR, 0.95), DM.ceiling(
CI.ConfidIntervals(MTTF, 0.90))
#print the confidence intervals of the data sets applying either 90% or 95% probability
print DM.round(CI.ConfidIntervals(ProcTime, 0.95))
print DM.ceiling(CI.ConfidIntervals(MTTF, 0.90))
print CI.ConfidIntervals(MTTR, 0.95)
def main(test=0, CSVFileName='DataSet.csv',
csvFile=None):
if csvFile:
CSVFileName = csvFile.name
filename = CSVFileName
data=ImportCSVdata() #call the Import_CSV module and using its method Input_data import the data set from the CSV file to the tool
Data = data.Input_data(filename)
ProcTime = Data.get('ProcessingTimes',[]) #get from the returned Python dictionary the three data sets
MTTF = Data.get('MTTF',[])
MTTR = Data.get('MTTR',[])
CI=ConfidenceIntervals() #create a Intervals object
DM=DataManipulation()
if test:
return DM.round(CI.ConfidIntervals(ProcTime, 0.95)), CI.ConfidIntervals(MTTR, 0.95), DM.ceiling(CI.ConfidIntervals(MTTF, 0.90))
#print the confidence intervals of the data sets applying either 90% or 95% probability
print DM.round(CI.ConfidIntervals(ProcTime, 0.95))
print DM.ceiling(CI.ConfidIntervals(MTTF, 0.90))
print CI.ConfidIntervals(MTTR, 0.95)
P3_Scrap= B.ReplaceWithZero(P3_Scrap)
P4_Scrap= B.ReplaceWithZero(P4_Scrap)
P5_Scrap= B.ReplaceWithZero(P5_Scrap)
P6_Scrap= B.ReplaceWithZero(P6_Scrap)
P7_Scrap= B.ReplaceWithZero(P7_Scrap)
P8_Scrap= B.ReplaceWithZero(P8_Scrap)
P9_Scrap= B.ReplaceWithZero(P9_Scrap)
P10_Scrap= B.ReplaceWithZero(P10_Scrap)
P11_Scrap= B.ReplaceWithZero(P11_Scrap)
# #Call the BasicSatatisticalMeasures object
C=StatisticalMeasures()
#Create a list with values the calculated mean value of scrap quantity on the different stations in the line
listScrap=[C.mean(P1_Scrap),C.mean(P2_Scrap),C.mean(P3_Scrap),C.mean(P4_Scrap),C.mean(P5_Scrap),C.mean(P6_Scrap),C.mean(P7_Scrap),C.mean(P8_Scrap),C.mean(P9_Scrap),C.mean(P10_Scrap), C.mean(P11_Scrap)]
D= DataManipulation()
listScrap=D.round(listScrap) #Round the mean values of the list so as to get integers
dictScrap={}
dictScrap['P1']= listScrap[0]
dictScrap['P2']= listScrap[1]
dictScrap['P3']= listScrap[2]
dictScrap['P4']= listScrap[3]
dictScrap['P5']= listScrap[4]
dictScrap['P6']= listScrap[5]
dictScrap['P7']= listScrap[6]
dictScrap['P8']= listScrap[7]
dictScrap['P9']= listScrap[8]
dictScrap['P10']= listScrap[9]
dictScrap['P11']= listScrap[10]