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)
