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)