#!/usr/bin/env python """ @file statisticsElements.py @author Yun-Pang.Wang@dlr.de @date 2008-07-10 @version $Id: statisticsElements.py 6569 2009-01-08 09:14:51Z dkrajzew $ This script is to define classes, functions, parse-reader and output files/format for - calculating network performances - conducting significance tests (either t-Test or Kruskal-Wallis-Test) and - writing results into files. Copyright (C) 2008 DLR/TS, Germany All rights reserved """ import string from xml.sax import saxutils, make_parser, handler # This class is for storing vehicle information, such as departure time, route and travel time. class Vehicle: def __init__(self, label): self.label = label self.method = None self.depart = 0. self.arrival = 0. self.speed = 0. self.route = [] self.traveltime = 0. self.travellength = 0. self.departdelay = 0. self.waittime = 0. self.rank = 0. def __repr__(self): return "%s_%s_%s_%s_%s_%s<%s>" % (self.label, self.depart, self.arrival, self.speed, self.traveltime, self.travellength, self.route) # This class is used in the significance test. class Assign: def __init__(self, method, totalVeh, totalTravelTime, totalTravelLength, totalDepartDelay, totalWaitTime, avgTravelTime, avgTravelLength, avgTravelSpeed, avgDepartDelay, avgWaitTime, SDTravelTime, SDLength, SDSpeed, SDWaitTime): self.label = method self.totalVeh = totalVeh self.totalTravelTime = totalTravelTime self.totalTravelLength = totalTravelLength self.totalDepartDelay = totalDepartDelay self.totalWaitTime = totalWaitTime self.avgTravelTime = avgTravelTime self.avgTravelLength = avgTravelLength self.avgTravelSpeed = avgTravelSpeed self.avgDepartDelay = avgDepartDelay self.avgWaitTime = avgWaitTime self.SDTravelTime = SDTravelTime self.SDLength = SDLength self.SDSpeed = SDSpeed self.SDWaitTime = SDWaitTime self.sumrank = 0. def __repr__(self): return "%s_<%s|%s|%s|%s|%s|%s|%s|%s|%s>" % (self.label, self.totalVeh, self.avgTravelTime, self.avgTravelLength, self.avgTravelSpeed, self.avgWaitTime, self.SDTravelTime, self.SDLength, self.SDSpeed, self.SDWaitTime) # This cloass is used for the t test in the significance test. class T_Value: def __init__(self, avgtraveltime, avgtravelspeed, avgtravellength, avgwaittime, lowvalue, highvalue): self.avgtraveltime = avgtraveltime self.avgtravelspeed = avgtravelspeed self.avgtravellength = avgtravellength self.avgwaittime = avgwaittime self.lowtvalue = lowvalue self.hightvalue = highvalue def __repr__(self): return "%<%s|%s|%s|%s>" % (self.avgtraveltime, self.avgtravelspeed, self.avgtravellength, self.avgwaittime) # This class is used for the Kruskal-Wallis test in the significance test. class H_Value: def __init__(self, label, lowvalue, highvalue): self.label = label self.traveltime = 0. self.travelspeed = 0. self.travellength = 0. self.waittime = 0. # 95% confidence interval self.lowchivalue = lowvalue # 99% confidence interval self.highchivalue = highvalue def __repr__(self): return "%<%s|%s|%s|%s|%s|%s>" % (self.traveltime, self.travelspeed, self.travellength, self.waittime, self.lowchivalue, self.highchivalue) # The class is for parsing the XML input file (vehicle information). This class is used in the networkStatistics.py for # calculating the gloabal network performances, e.g. avg. travel time and avg. travel speed. class VehInformationReader(handler.ContentHandler): def __init__(self, vehList): self._vehList = vehList self._Vehicle = None self._routeString = '' def startElement(self, name, attrs): if name == 'tripinfo': self._Vehicle = Vehicle(attrs['id']) self._Vehicle.traveltime = float(attrs['duration']) self._Vehicle.travellength = float(attrs['routeLength']) self._Vehicle.departdelay = float(attrs['departDelay']) self._Vehicle.waittime = float(attrs['departDelay']) + float(attrs['waitSteps']) self._vehList.append(self._Vehicle) # output the network statistics based on the sumo-simulation results def getStatisticsOutput(assignments, outputfile): foutveh = file(outputfile, 'w') foutveh.write('average vehicular travel time(s) = the sum of all vehicular travel times / the number of vehicles\n') foutveh.write('average vehicular travel length(m) = the sum of all vehicular travel lengths / the number of vehicles\n') foutveh.write('average vehicular travel speed(m/s) = the sum of all vehicular travel speeds / the number of vehicles\n') for method in assignments.itervalues(): foutveh.write('\nAssignment Method:%s\n' %method.label) foutveh.write('- total number of vehicles:%s\n' %method.totalVeh) foutveh.write('- total departure delay(s):%s, ' %method.totalDepartDelay) foutveh.write('- average departure delay(s):%s\n' %method.avgDepartDelay) foutveh.write('- total waiting time(s):%s, ' %method.totalWaitTime) foutveh.write('- average vehicular waiting time(s):%s\n' %method.avgWaitTime) foutveh.write('- total travel time(s):%s, ' % method.totalTravelTime) foutveh.write('- average vehicular travel time(s):%s\n' %method.avgTravelTime) foutveh.write('- total travel length(m):%s, ' %method.totalTravelLength) foutveh.write('- average vehicular travel length(m):%s\n' %method.avgTravelLength) foutveh.write('- average vehicular travel speed(m/s):%s\n' %method.avgTravelSpeed) foutveh.close() # output the results of the significance tests according to the sumo-simulation results def getSignificanceTestOutput(assignments, tTest, tValueAvg, hValues, outputfile): foutSGtest = file(outputfile, 'w') if tTest: foutSGtest.write('The significances of the performance averages among the used assignment models are examined with the t test.\n') assignlist = list(assignments.itervalues()) for num, A in enumerate(assignlist): for B in assignlist[num+1: ]: foutSGtest.write('\nmethod:%s' %A.label) foutSGtest.write('\nmethod:%s' %B.label) foutSGtest.write('\n t-value for the avg. travel time:%s' %tValueAvg[A][B].avgtraveltime) foutSGtest.write('\n t-value for the avg. travel length:%s'%tValueAvg[A][B].avgtravellength) foutSGtest.write('\n t-value for the avg.travel speed:%s' %tValueAvg[A][B].avgtravelspeed) foutSGtest.write('\n t-value for the avg. wait time:%s\n' %tValueAvg[A][B].avgwaittime) foutSGtest.write('\n95 t-value:%s' %tValueAvg[A][B].lowtvalue) foutSGtest.write('\n99 t-value:%s\n' %tValueAvg[A][B].hightvalue) foutSGtest.write('The significance test among the different assignment methods is also done with the Kruskal-Wallis test.\n') for h in hValues: foutSGtest.write('\n\nmethods:%s' %h.label) foutSGtest.write('\nH_traveltime:%s' %h.traveltime) foutSGtest.write('\nH_travelspeed:%s' %h.travelspeed) foutSGtest.write('\nH_travellength:%s' %h.travellength) foutSGtest.write('\nH_waittime:%s\n' %h.waittime) foutSGtest.write('\n95 chi-square value:%s' %h.lowchivalue) foutSGtest.write('\n99 chi-square value:%s\n' %h.highchivalue) foutSGtest.close()