How to use the sumolib.miscutils.Statistics function in sumolib

restrictions[rID] = int(count)

    routeUsage = defaultdict(int)
    for flow in parse(options.emitters, 'flow'):
        num = int(flow.number)
        if flow.route is None:
            dist = flow.routeDistribution[0]
            probs = map(float, dist.probabilities.split())
            probs = [p / sum(probs) for p in probs]
            for rID, p in zip(dist.routes.split(), probs):
                routeUsage[rID] += p * num
        else:
            routeUsage[flow.route] += num

    usage = Statistics("routeUsage")
    restrictUsage = Statistics("restrictedRouteUsage")
    for rID, count in routeUsage.items():
        usage.add(count, rID)
        if rID in restrictions:
            restrictUsage.add(count, rID)
    print(usage)
    print(restrictUsage, "total:", sum(restrictUsage.values))

    if options.unused_output is not None:
        with open(options.unused_output, 'w') as outf:
            for rID, count in routeUsage.items():
                if count <= options.threshold:
                    outf.write("%s\n" % rID)
                if rID in restrictions and count > restrictions[rID]:
                    outf.write("%s %s %s\n" % (rID, count, restrictions[rID]))

assert(routeAlts[0].edges.split() == routeInfos[vehicle.id].edges)
            routeInfos[vehicle.id].shortest_path_distance = getRouteLength(net, routeAlts[1].edges.split())
            if oldCosts <= newCosts:
                routeInfos[vehicle.id].detour = 0
                routeInfos[vehicle.id].detourRatio = 1
                if oldCosts < newCosts:
                    sys.stderr.write(("Warning: fastest route for '%s' is slower than original route " +
                                      "(old=%s, new=%s). Check vehicle types\n") % (
                        vehicle.id, oldCosts, newCosts))
            else:
                routeInfos[vehicle.id].detour = oldCosts - newCosts
                routeInfos[vehicle.id].detourRatio = oldCosts / newCosts

    implausible = []
    allRoutesStats = Statistics("overal implausiblity")
    implausibleRoutesStats = Statistics("implausiblity above threshold")
    for rID in sorted(routeInfos.keys()):
        ri = routeInfos[rID]
        ri.implausibility = (options.airdist_ratio_factor * ri.airDistRatio +
                             options.detour_factor * ri.detour +
                             options.detour_ratio_factor * ri.detourRatio +
                             max(0, options.min_dist / ri.shortest_path_distance - 1) +
                             max(0, options.min_air_dist / ri.airDist - 1))
        allRoutesStats.add(ri.implausibility, rID)
        if ri.implausibility > options.threshold:
            implausible.append((ri.implausibility, rID, ri))
            implausibleRoutesStats.add(ri.implausibility, rID)

    # generate restrictions
    if options.restrictions_output is not None:
        with open(options.restrictions_output, 'w') as outf:
            for score, rID, ri in sorted(implausible):

newCosts = float(routeAlts[1].cost)
            assert(routeAlts[0].edges.split() == routeInfos[vehicle.id].edges)
            routeInfos[vehicle.id].shortest_path_distance = getRouteLength(net, routeAlts[1].edges.split())
            if oldCosts <= newCosts:
                routeInfos[vehicle.id].detour = 0
                routeInfos[vehicle.id].detourRatio = 1
                if oldCosts < newCosts:
                    sys.stderr.write(("Warning: fastest route for '%s' is slower than original route " +
                                      "(old=%s, new=%s). Check vehicle types\n") % (
                        vehicle.id, oldCosts, newCosts))
            else:
                routeInfos[vehicle.id].detour = oldCosts - newCosts
                routeInfos[vehicle.id].detourRatio = oldCosts / newCosts

    implausible = []
    allRoutesStats = Statistics("overal implausiblity")
    implausibleRoutesStats = Statistics("implausiblity above threshold")
    for rID in sorted(routeInfos.keys()):
        ri = routeInfos[rID]
        ri.implausibility = (options.airdist_ratio_factor * ri.airDistRatio +
                             options.detour_factor * ri.detour +
                             options.detour_ratio_factor * ri.detourRatio +
                             max(0, options.min_dist / ri.shortest_path_distance - 1) +
                             max(0, options.min_air_dist / ri.airDist - 1))
        allRoutesStats.add(ri.implausibility, rID)
        if ri.implausibility > options.threshold:
            implausible.append((ri.implausibility, rID, ri))
            implausibleRoutesStats.add(ri.implausibility, rID)

    # generate restrictions
    if options.restrictions_output is not None:
        with open(options.restrictions_output, 'w') as outf:

def write_diff(orig, new, out, earliest_out=None):
    earliest_diffs = defaultdict(lambda: (uMax, None))  # diff -> (time, veh)
    vehicles_orig = dict([(v.id, v) for v in parse(orig, 'vehicle')])
    origDurations = Statistics('original durations')
    durations = Statistics('new durations')
    durationDiffs = Statistics('duration differences')
    with open(out, 'w') as f:
        f.write("\n")
        for v in parse(new, 'vehicle'):
            if v.id in vehicles_orig:
                vOrig = vehicles_orig[v.id]
                departDiff = float(v.depart) - float(vOrig.depart)
                arrivalDiff = float(v.arrival) - float(vOrig.arrival)
                if v.route[0].exitTimes is None:
                    sys.exit("Error: Need route input with 'exitTimes'\n")
                exitTimes = map(float, v.route[0].exitTimes.split())
                origExitTimes = map(float, vOrig.route[0].exitTimes.split())
                exitTimesDiff = [
                    e - eOrig for e, eOrig in zip(exitTimes, origExitTimes)]

for rID in routes[edges]:
                restrictions[rID] = int(count)

    routeUsage = defaultdict(int)
    for flow in parse(options.emitters, 'flow'):
        num = int(flow.number)
        if flow.route is None:
            dist = flow.routeDistribution[0]
            probs = map(float, dist.probabilities.split())
            probs = [p / sum(probs) for p in probs]
            for rID, p in zip(dist.routes.split(), probs):
                routeUsage[rID] += p * num
        else:
            routeUsage[flow.route] += num

    usage = Statistics("routeUsage")
    restrictUsage = Statistics("restrictedRouteUsage")
    for rID, count in routeUsage.items():
        usage.add(count, rID)
        if rID in restrictions:
            restrictUsage.add(count, rID)
    print(usage)
    print(restrictUsage, "total:", sum(restrictUsage.values))

    if options.unused_output is not None:
        with open(options.unused_output, 'w') as outf:
            for rID, count in routeUsage.items():
                if count <= options.threshold:
                    outf.write("%s\n" % rID)
                if rID in restrictions and count > restrictions[rID]:
                    outf.write("%s %s %s\n" % (rID, count, restrictions[rID]))

odpairs = {}
    for trip in parse(options.tripinfoFile, 'tripinfo'):
        odpair = id2TAZ.get(trip.id)
        tripID = trip.id
        if odpair is None and '.' in trip.id:
            flowID = trip.id[:trip.id.rfind('.')]
            if flowID in flowIDs:
                tripID = flowID
                odpair = flowIds2TAZ.get(tripID)
        if odpair is None:
            fromEdge = trip.departLane[:trip.departLane.rfind('_')]
            toEdge = trip.arrivalLane[:trip.arrivalLane.rfind('_')]
            odpair = (sourceEdge2TAZ.get(fromEdge, '?'), sinkEdge2TAZ.get(toEdge, '?'))
        if odpair not in odpairs:
            odpairs[odpair] = Statistics(' '.join(odpair))

        odpairs[odpair].add(parseTime(getattr(trip, options.attribute)), tripID)

    if options.output:
        with open(options.output, 'w') as outf:
            outf.write('\n' % options.attribute)
            for (fromTaz, toTaz), stats in sorted(odpairs.items()):
                q1, median, q3 = stats.quartiles()
                outf.write('    \n' %
                           (stats.max, stats.max_label, stats.avg(), q1, median, q3))
            outf.write('\n')
    else:
        for (fromTaz, toTaz), stats in sorted(odpairs.items()):
            print(stats)

def accelStats(netstate):
    lastSpeed = {}
    stats = Statistics(
        "Accelerations", histogram=True, printMin=True, scale=0.2)
    for vehicle in parse_fast(netstate, 'vehicle', ['id', 'speed']):
        speed = float(vehicle.speed)
        prevSpeed = lastSpeed.get(vehicle.id, speed)
        stats.add(speed - prevSpeed, (vehicle.id, vehicle.speed))
        lastSpeed[vehicle.id] = speed
    print(stats)

def parse_dualog(dualog, limit):
    print("Parsing %s" % dualog)
    teleStats = Statistics('Teleports')
    header = ['#Inserted', 'Running', 'Waiting', 'Teleports', 'Loaded']
    step_values = []  # list of lists
    step_counts = []  # list of edge teleport counters
    reInserted = re.compile(r"Inserted: (\d*)")
    reLoaded = re.compile(r"Loaded: (\d*)")
    reRunning = re.compile(r"Running: (\d*)")
    reWaiting = re.compile(r"Waiting: (\d*)")
    reFrom = re.compile("from '([^']*)'")  # mesosim
    teleports = 0
    inserted = None
    loaded = None
    running = None
    waiting = None
    haveMicrosim = None
    counts = defaultdict(lambda: 0)
    for line in open(dualog):

def write_persondiff(options):
    attrs = ["depart", "arrival", "timeLoss", "duration", "routeLength", "waitingTime"]
    attr_conversions = dict([(a, parseTime) for a in attrs])
    persons_orig = OrderedDict([(p.id, p) for p in parse(options.orig, 'personinfo',
                                                         attr_conversions=attr_conversions)])
    origDurations = Statistics('original durations')
    durations = Statistics('new durations')
    durationDiffs = Statistics('duration differences')
    statAttrs = ["duration", "walkTimeLoss", "rideWait", "walks", "accesses", "rides", "stops"]
    with open(options.output, 'w') as f:
        f.write("\n")
        for p in parse(options.new, 'personinfo', attr_conversions=attr_conversions):
            if p.id in persons_orig:
                pOrig = persons_orig[p.id]
                stats = plan_stats(p)
                statsOrig = plan_stats(pOrig)
                diffs = [a - b for a, b in zip(stats, statsOrig)]
                durations.add(stats[0], p.id)
                origDurations.add(statsOrig[0], p.id)
                durationDiffs.add(stats[0] - statsOrig[0], p.id)
                diffAttrs = ''.join([' %sDiff="%s"' % (a, x) for a, x in zip(statAttrs, diffs)])
                f.write('    \n' % (p.id, diffAttrs))
                del persons_orig[p.id]

def write_persondiff(options):
    attrs = ["depart", "arrival", "timeLoss", "duration", "routeLength", "waitingTime"]
    attr_conversions = dict([(a, parseTime) for a in attrs])
    persons_orig = OrderedDict([(p.id, p) for p in parse(options.orig, 'personinfo',
                                                         attr_conversions=attr_conversions)])
    origDurations = Statistics('original durations')
    durations = Statistics('new durations')
    durationDiffs = Statistics('duration differences')
    statAttrs = ["duration", "walkTimeLoss", "rideWait", "walks", "accesses", "rides", "stops"]
    with open(options.output, 'w') as f:
        f.write("\n")
        for p in parse(options.new, 'personinfo', attr_conversions=attr_conversions):
            if p.id in persons_orig:
                pOrig = persons_orig[p.id]
                stats = plan_stats(p)
                statsOrig = plan_stats(pOrig)
                diffs = [a - b for a, b in zip(stats, statsOrig)]
                durations.add(stats[0], p.id)
                origDurations.add(statsOrig[0], p.id)
                durationDiffs.add(stats[0] - statsOrig[0], p.id)
                diffAttrs = ''.join([' %sDiff="%s"' % (a, x) for a, x in zip(statAttrs, diffs)])
                f.write('    \n' % (p.id, diffAttrs))