/usr/lib/python2.7/dist-packages/obfsproxy/transports/scramblesuit/probdist.py is in obfsproxy 0.2.12-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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This module provides code to generate and sample probability distributions.
The class RandProbDist provides an interface to randomly generate probability
distributions. Random samples can then be drawn from these distributions.
"""
import random
import const
import obfsproxy.common.log as logging
log = logging.get_obfslogger()
class RandProbDist:
"""
Provides code to generate, sample and dump probability distributions.
"""
def __init__( self, genSingleton, seed=None ):
"""
Initialise a discrete probability distribution.
The parameter `genSingleton' is expected to be a function which yields
singletons for the probability distribution. The optional `seed' can
be used to seed the PRNG so that the probability distribution is
generated deterministically.
"""
self.prng = random if (seed is None) else random.Random(seed)
self.sampleList = []
self.dist = self.genDistribution(genSingleton)
self.dumpDistribution()
def genDistribution( self, genSingleton ):
"""
Generate a discrete probability distribution.
The parameter `genSingleton' is a function which is used to generate
singletons for the probability distribution.
"""
dist = {}
# Amount of distinct bins, i.e., packet lengths or inter arrival times.
bins = self.prng.randint(const.MIN_BINS, const.MAX_BINS)
# Cumulative probability of all bins.
cumulProb = 0
for _ in xrange(bins):
prob = self.prng.uniform(0, (1 - cumulProb))
cumulProb += prob
singleton = genSingleton()
dist[singleton] = prob
self.sampleList.append((cumulProb, singleton,))
dist[genSingleton()] = (1 - cumulProb)
return dist
def dumpDistribution( self ):
"""
Dump the probability distribution using the logging object.
Only probabilities > 0.01 are dumped.
"""
log.debug("Dumping probability distribution.")
for singleton in self.dist.iterkeys():
# We are not interested in tiny probabilities.
if self.dist[singleton] > 0.01:
log.debug("P(%s) = %.3f" %
(str(singleton), self.dist[singleton]))
def randomSample( self ):
"""
Draw and return a random sample from the probability distribution.
"""
assert len(self.sampleList) > 0
rand = random.random()
for cumulProb, singleton in self.sampleList:
if rand <= cumulProb:
return singleton
return self.sampleList[-1][1]
# Alias class name in order to provide a more intuitive API.
new = RandProbDist
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