282 lines
9.5 KiB
Python
282 lines
9.5 KiB
Python
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#!/usr/bin/env python3
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# Parse the log files output by the simulator to get the overall average
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# and stddev of total bytes sent+received per epoch for each of:
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# - dirauths
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# - total relays
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# - bootstrapping fallback relays per bw
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# - non-bootstrapping fallback relays per bw
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# - bootstrapping non-fallback relays per bw
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# - non-bootstrapping non-fallback relays per bw
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# - total clients
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# - bootstrapping clients
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# - non-bootstrapping clients
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# - steady-state dirauths (skipping the first epoch in which all clients
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# are bootstrapping)
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# - steady-state relays (as above)
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# - steady-state clients (as above)
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# - steady-state total relay traffic per client (as above)
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# Pass the names of the log files as command-line arguments, or the log
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# files themselves on stdin.
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# The output will be five files named:
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# - vanilla_none.dat
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# - telescoping_merkle.dat
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# - telescoping_threshsig.dat
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# - singlepass_merkle.dat
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# - singlepass_threshsig.dat
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# Each file will contain one line for every network scale seen in the
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# logs. The line will consist of 27 fields:
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# - the network scale (float)
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# - the mean and stddev (two floats) for each of the above 13 classes,
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# in the above order; for the steady states, the stats are computed
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# over the per-epoch averages, while for the others, the stats are
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# computed on a per-entity basis
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import math
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import re
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import os
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import fileinput
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from bwparser import BandwidthParser
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modes = [ "vanilla_none", "telescoping_merkle", "telescoping_threshsig",
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"singlepass_merkle", "singlepass_threshsig" ]
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class StatAccum:
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"""Accumulate (mean, stddev, N) triples to compute an overall (mean,
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stddev, N)."""
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def __init__(self):
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self.sumX = 0
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self.sumXsq = 0
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self.totN = 0
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def accum(self, mean, stddev, N):
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if N == 0:
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# Nothing to change
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return
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if N == 1:
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# stddev will be None
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this_sumX = mean
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this_sumXsq = mean*mean
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else:
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this_sumX = mean * N
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variance = stddev * stddev
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this_sumXsq = variance * (N-1) + this_sumX * this_sumX / N
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self.sumX += this_sumX
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self.sumXsq += this_sumXsq
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self.totN += N
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def stats(self):
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if self.totN == 0:
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return (None, None, 0)
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if self.totN == 1:
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return (self.sumX, None, 1)
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mean = self.sumX / self.totN
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variance = (self.sumXsq - self.sumX * self.sumX / self.totN) \
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/ (self.totN - 1)
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stddev = math.sqrt(variance)
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return (mean, stddev, self.totN)
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def __str__(self):
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mean, stddev, N = self.stats()
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if mean is None:
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mean = 0
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if stddev is None:
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stddev = 0
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return "%f %f" % (mean, stddev)
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class StatBundle:
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"""A bundle of 13 StatAccums, corresponding to the 13 entity classes
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listed above."""
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def __init__(self):
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self.stats = [StatAccum() for i in range(14)]
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def dirauth(self, mean, stddev, N):
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self.stats[0].accum(mean, stddev, N)
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def relay_all(self, mean, stddev, N):
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self.stats[1].accum(mean, stddev, N)
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def relay_fb_boot(self, mean, stddev, N):
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self.stats[2].accum(mean, stddev, N)
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def relay_fb_nboot(self, mean, stddev, N):
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self.stats[3].accum(mean, stddev, N)
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def relay_nfb_boot(self, mean, stddev, N):
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self.stats[4].accum(mean, stddev, N)
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def relay_nfb_nboot(self, mean, stddev, N):
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self.stats[5].accum(mean, stddev, N)
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def client_all(self, mean, stddev, N):
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self.stats[6].accum(mean, stddev, N)
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def client_circuit_build(self, mean, stddev, N):
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self.stats[7].accum(mean, stddev, N)
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def client_boot(self, mean, stddev, N):
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self.stats[8].accum(mean, stddev, N)
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def client_nboot(self, mean, stddev, N):
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self.stats[9].accum(mean, stddev, N)
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def steady_dirauth(self, mean, stddev, N):
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self.stats[10].accum(mean, stddev, N)
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def steady_relay(self, mean, stddev, N):
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self.stats[11].accum(mean, stddev, N)
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def steady_client(self, mean, stddev, N):
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self.stats[12].accum(mean, stddev, N)
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def steady_relay_perclient(self, mean, stddev, N):
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self.stats[13].accum(mean, stddev, N)
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def __str__(self):
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return '%s %s %s %s %s %s %s %s %s %s %s %s %s %s' % (
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self.stats[0], self.stats[1], self.stats[2], self.stats[3],
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self.stats[4], self.stats[5], self.stats[6], self.stats[7],
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self.stats[8], self.stats[9], self.stats[10],
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self.stats[11], self.stats[12], self.stats[13])
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class LogParser:
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"""A class to parse the logfiles output by sim.py."""
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def __init__(self, network_size):
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# self.stats is a dict indexed by mode name (like
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# "singlepass_merkle") whose value is a dict indexed
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# by network scale whose value is a StatBundle
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self.stats = dict()
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self.network_size = network_size
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self.curbundle = None
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self.fbbootstrapping = None
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self.steadystate = False
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self.startre = re.compile('Starting simulation .*?\/([A-Z]+)_([A-Z]+)_([\d\.]+)_')
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self.statperbwre = re.compile('(Relays\(N?F?B\)).*bytes=([\d\.]+)( .pm ([\d\.]+))?.*bytesperbw=([\d\.]+)( .pm ([\d\.]+))?.*N=(\d+)')
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self.statre = re.compile('(Dirauths|Relays|Clients(\(N?B\))?).*bytes=([\d\.]+)( .pm ([\d\.]+))?.*circuit_building_time=([\d\.]+).*N=(\d+)')
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self.mibre = re.compile('MiB used')
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def parse_line(self, line):
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m = self.startre.search(line)
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if m:
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mode = m.group(1).lower() + "_" + m.group(2).lower()
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scale = m.group(3)
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if mode not in self.stats:
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self.stats[mode] = dict()
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if scale not in self.stats[mode]:
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self.stats[mode][scale] = StatBundle()
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self.curbundle = self.stats[mode][scale]
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self.fbbootstrapping = True
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self.steadystate = False
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return
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m = self.statperbwre.search(line)
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circuit_buildings = 0.0
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if m:
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enttype, means, stddevs, meanperbws, stddevperbws, Ns = \
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m.group(1,2,4,5,7,8)
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else:
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m = self.statre.search(line)
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if m:
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enttype, means, stddevs, circuit_buildings, Ns = \
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m.group(1,3,5,6,7)
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meanperbws, stddevperbws = None, None
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else:
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m = self.mibre.search(line)
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if m:
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# We've reached steady state
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self.steadystate = True
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return
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mean = float(means)
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if stddevs:
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stddev = float(stddevs)
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else:
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stddev = None
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if meanperbws:
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meanperbw = float(meanperbws)
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else:
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meanperbw = None
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if stddevperbws:
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stddevperbw = float(stddevperbws)
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else:
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stddevperbw = None
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if circuit_buildings:
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circuit_buildings = float(circuit_buildings)
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N = int(Ns)
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# print('%s %s %s %s %s %s %s' % (enttype, mean, stddev, meanperbw, stddevperbw, circuit_buildings, N))
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if enttype == 'Dirauths':
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self.curbundle.dirauth(mean, stddev, N)
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if self.steadystate:
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self.curbundle.steady_dirauth(mean, None, 1)
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elif enttype == 'Relays':
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self.curbundle.relay_all(mean, stddev, N)
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if self.steadystate:
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self.curbundle.steady_relay(mean, None, 1)
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self.totrelaybytes = mean * N
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elif enttype == 'Relays(FB)':
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if self.fbbootstrapping:
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self.curbundle.relay_fb_boot(meanperbw, stddevperbw, N)
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self.fbbootstrapping = False
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else:
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self.curbundle.relay_fb_nboot(meanperbw, stddevperbw, N)
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elif enttype == 'Relays(B)':
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self.curbundle.relay_nfb_boot(meanperbw, stddevperbw, N)
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elif enttype == 'Relays(NB)':
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self.curbundle.relay_nfb_nboot(meanperbw, stddevperbw, N)
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elif enttype == 'Clients':
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self.curbundle.client_all(mean, stddev, N)
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self.curbundle.client_circuit_build(circuit_buildings, stddev, N)
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if self.steadystate:
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self.curbundle.steady_client(mean, None, 1)
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self.curbundle.steady_relay_perclient(self.totrelaybytes / N, None, 1)
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elif enttype == 'Clients(B)':
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self.curbundle.client_boot(mean, stddev, N)
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self.curbundle.client_circuit_build(circuit_buildings, stddev, N)
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elif enttype == 'Clients(NB)':
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self.curbundle.client_nboot(mean, stddev, N)
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self.curbundle.client_circuit_build(circuit_buildings, stddev, N)
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else:
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raise ValueError('Unknown entity type "%s"' % enttype)
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def write_output(self):
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for mode in self.stats.keys():
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with open("%s.dat" % mode, "w") as datout:
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for scale in sorted(self.stats[mode].keys()):
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datout.write("%s %s\n" % \
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(self.network_size*float(scale), self.stats[mode][scale]))
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datout.close()
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if __name__ == '__main__':
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# sensible defaults
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bandwidth_file = os.getenv('BW_FILE')
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network_size = 0
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if os.getenv('BW_ALGO') != "komlo":
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bw_parser = BandwidthParser(bw_file=bandwidth_file)
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network_size = bw_parser.get_relay_num()
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else:
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# keep the original assumption
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network_size = 6500
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logparser = LogParser(network_size)
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for line in fileinput.input():
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logparser.parse_line(line)
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logparser.write_output()
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