avgQueryTimeProduct = 1.0 avgQueryTimeSum = 0 for j, avgQueryTime in avgQueryTimes.iteritems(): avgQueryTimeProduct*=(avgQueryTime) avgQueryTimeSum+=(avgQueryTime) avgQueryTimes["avg"] = avgQueryTimeSum/22 avgQueryTimes["geo"] = nroot(avgQueryTimeProduct,22) result[key].append(avgQueryTimes) return result parse_arguments() # create data structure for logfilepath in logfilepaths: log = Log(logfilepath) queryTimes[log.get_pattern()+log.get_scale()].append(log.get_query_times()) for key, patternScaleSet in queryTimes.iteritems(): print key csvbody = [] csvbody.append(["Q1","Q2","Q3","Q4","Q5","Q6","Q7","Q8","Q9","Q10","Q11","Q12","Q13","Q14","Q15","Q16","Q17","Q18","Q19","Q20","Q21","Q22","Avg","Geo. mean"]) patternScaleSet.append(calculate_average(queryTimes)[key].pop()) #add avg results for queryTimeSet in patternScaleSet: tempList = [] for i, queryTimeList in queryTimeSet.iteritems(): tempList.append(queryTimeList) if len(tempList) != 24: tempList+=["",""]