#!/usr/bin/env python | |
import unittest | |
import random | |
import time | |
import pickle | |
import warnings | |
from math import log, exp, pi, fsum, sin | |
from functools import reduce | |
from test import test_support | |
class TestBasicOps(unittest.TestCase): | |
# Superclass with tests common to all generators. | |
# Subclasses must arrange for self.gen to retrieve the Random instance | |
# to be tested. | |
def randomlist(self, n): | |
"""Helper function to make a list of random numbers""" | |
return [self.gen.random() for i in xrange(n)] | |
def test_autoseed(self): | |
self.gen.seed() | |
state1 = self.gen.getstate() | |
time.sleep(0.1) | |
self.gen.seed() # diffent seeds at different times | |
state2 = self.gen.getstate() | |
self.assertNotEqual(state1, state2) | |
def test_saverestore(self): | |
N = 1000 | |
self.gen.seed() | |
state = self.gen.getstate() | |
randseq = self.randomlist(N) | |
self.gen.setstate(state) # should regenerate the same sequence | |
self.assertEqual(randseq, self.randomlist(N)) | |
def test_seedargs(self): | |
for arg in [None, 0, 0L, 1, 1L, -1, -1L, 10**20, -(10**20), | |
3.14, 1+2j, 'a', tuple('abc')]: | |
self.gen.seed(arg) | |
for arg in [range(3), dict(one=1)]: | |
self.assertRaises(TypeError, self.gen.seed, arg) | |
self.assertRaises(TypeError, self.gen.seed, 1, 2) | |
self.assertRaises(TypeError, type(self.gen), []) | |
def test_jumpahead(self): | |
self.gen.seed() | |
state1 = self.gen.getstate() | |
self.gen.jumpahead(100) | |
state2 = self.gen.getstate() # s/b distinct from state1 | |
self.assertNotEqual(state1, state2) | |
self.gen.jumpahead(100) | |
state3 = self.gen.getstate() # s/b distinct from state2 | |
self.assertNotEqual(state2, state3) | |
with test_support.check_py3k_warnings(quiet=True): | |
self.assertRaises(TypeError, self.gen.jumpahead) # needs an arg | |
self.assertRaises(TypeError, self.gen.jumpahead, 2, 3) # too many | |
def test_sample(self): | |
# For the entire allowable range of 0 <= k <= N, validate that | |
# the sample is of the correct length and contains only unique items | |
N = 100 | |
population = xrange(N) | |
for k in xrange(N+1): | |
s = self.gen.sample(population, k) | |
self.assertEqual(len(s), k) | |
uniq = set(s) | |
self.assertEqual(len(uniq), k) | |
self.assertTrue(uniq <= set(population)) | |
self.assertEqual(self.gen.sample([], 0), []) # test edge case N==k==0 | |
def test_sample_distribution(self): | |
# For the entire allowable range of 0 <= k <= N, validate that | |
# sample generates all possible permutations | |
n = 5 | |
pop = range(n) | |
trials = 10000 # large num prevents false negatives without slowing normal case | |
def factorial(n): | |
return reduce(int.__mul__, xrange(1, n), 1) | |
for k in xrange(n): | |
expected = factorial(n) // factorial(n-k) | |
perms = {} | |
for i in xrange(trials): | |
perms[tuple(self.gen.sample(pop, k))] = None | |
if len(perms) == expected: | |
break | |
else: | |
self.fail() | |
def test_sample_inputs(self): | |
# SF bug #801342 -- population can be any iterable defining __len__() | |
self.gen.sample(set(range(20)), 2) | |
self.gen.sample(range(20), 2) | |
self.gen.sample(xrange(20), 2) | |
self.gen.sample(str('abcdefghijklmnopqrst'), 2) | |
self.gen.sample(tuple('abcdefghijklmnopqrst'), 2) | |
def test_sample_on_dicts(self): | |
self.gen.sample(dict.fromkeys('abcdefghijklmnopqrst'), 2) | |
# SF bug #1460340 -- random.sample can raise KeyError | |
a = dict.fromkeys(range(10)+range(10,100,2)+range(100,110)) | |
self.gen.sample(a, 3) | |
# A followup to bug #1460340: sampling from a dict could return | |
# a subset of its keys or of its values, depending on the size of | |
# the subset requested. | |
N = 30 | |
d = dict((i, complex(i, i)) for i in xrange(N)) | |
for k in xrange(N+1): | |
samp = self.gen.sample(d, k) | |
# Verify that we got ints back (keys); the values are complex. | |
for x in samp: | |
self.assertTrue(type(x) is int) | |
samp.sort() | |
self.assertEqual(samp, range(N)) | |
def test_gauss(self): | |
# Ensure that the seed() method initializes all the hidden state. In | |
# particular, through 2.2.1 it failed to reset a piece of state used | |
# by (and only by) the .gauss() method. | |
for seed in 1, 12, 123, 1234, 12345, 123456, 654321: | |
self.gen.seed(seed) | |
x1 = self.gen.random() | |
y1 = self.gen.gauss(0, 1) | |
self.gen.seed(seed) | |
x2 = self.gen.random() | |
y2 = self.gen.gauss(0, 1) | |
self.assertEqual(x1, x2) | |
self.assertEqual(y1, y2) | |
def test_pickling(self): | |
state = pickle.dumps(self.gen) | |
origseq = [self.gen.random() for i in xrange(10)] | |
newgen = pickle.loads(state) | |
restoredseq = [newgen.random() for i in xrange(10)] | |
self.assertEqual(origseq, restoredseq) | |
def test_bug_1727780(self): | |
# verify that version-2-pickles can be loaded | |
# fine, whether they are created on 32-bit or 64-bit | |
# platforms, and that version-3-pickles load fine. | |
files = [("randv2_32.pck", 780), | |
("randv2_64.pck", 866), | |
("randv3.pck", 343)] | |
for file, value in files: | |
f = open(test_support.findfile(file),"rb") | |
r = pickle.load(f) | |
f.close() | |
self.assertEqual(r.randrange(1000), value) | |
class WichmannHill_TestBasicOps(TestBasicOps): | |
gen = random.WichmannHill() | |
def test_setstate_first_arg(self): | |
self.assertRaises(ValueError, self.gen.setstate, (2, None, None)) | |
def test_strong_jumpahead(self): | |
# tests that jumpahead(n) semantics correspond to n calls to random() | |
N = 1000 | |
s = self.gen.getstate() | |
self.gen.jumpahead(N) | |
r1 = self.gen.random() | |
# now do it the slow way | |
self.gen.setstate(s) | |
for i in xrange(N): | |
self.gen.random() | |
r2 = self.gen.random() | |
self.assertEqual(r1, r2) | |
def test_gauss_with_whseed(self): | |
# Ensure that the seed() method initializes all the hidden state. In | |
# particular, through 2.2.1 it failed to reset a piece of state used | |
# by (and only by) the .gauss() method. | |
for seed in 1, 12, 123, 1234, 12345, 123456, 654321: | |
self.gen.whseed(seed) | |
x1 = self.gen.random() | |
y1 = self.gen.gauss(0, 1) | |
self.gen.whseed(seed) | |
x2 = self.gen.random() | |
y2 = self.gen.gauss(0, 1) | |
self.assertEqual(x1, x2) | |
self.assertEqual(y1, y2) | |
def test_bigrand(self): | |
# Verify warnings are raised when randrange is too large for random() | |
with warnings.catch_warnings(): | |
warnings.filterwarnings("error", "Underlying random") | |
self.assertRaises(UserWarning, self.gen.randrange, 2**60) | |
class SystemRandom_TestBasicOps(TestBasicOps): | |
gen = random.SystemRandom() | |
def test_autoseed(self): | |
# Doesn't need to do anything except not fail | |
self.gen.seed() | |
def test_saverestore(self): | |
self.assertRaises(NotImplementedError, self.gen.getstate) | |
self.assertRaises(NotImplementedError, self.gen.setstate, None) | |
def test_seedargs(self): | |
# Doesn't need to do anything except not fail | |
self.gen.seed(100) | |
def test_jumpahead(self): | |
# Doesn't need to do anything except not fail | |
self.gen.jumpahead(100) | |
def test_gauss(self): | |
self.gen.gauss_next = None | |
self.gen.seed(100) | |
self.assertEqual(self.gen.gauss_next, None) | |
def test_pickling(self): | |
self.assertRaises(NotImplementedError, pickle.dumps, self.gen) | |
def test_53_bits_per_float(self): | |
# This should pass whenever a C double has 53 bit precision. | |
span = 2 ** 53 | |
cum = 0 | |
for i in xrange(100): | |
cum |= int(self.gen.random() * span) | |
self.assertEqual(cum, span-1) | |
def test_bigrand(self): | |
# The randrange routine should build-up the required number of bits | |
# in stages so that all bit positions are active. | |
span = 2 ** 500 | |
cum = 0 | |
for i in xrange(100): | |
r = self.gen.randrange(span) | |
self.assertTrue(0 <= r < span) | |
cum |= r | |
self.assertEqual(cum, span-1) | |
def test_bigrand_ranges(self): | |
for i in [40,80, 160, 200, 211, 250, 375, 512, 550]: | |
start = self.gen.randrange(2 ** i) | |
stop = self.gen.randrange(2 ** (i-2)) | |
if stop <= start: | |
return | |
self.assertTrue(start <= self.gen.randrange(start, stop) < stop) | |
def test_rangelimits(self): | |
for start, stop in [(-2,0), (-(2**60)-2,-(2**60)), (2**60,2**60+2)]: | |
self.assertEqual(set(range(start,stop)), | |
set([self.gen.randrange(start,stop) for i in xrange(100)])) | |
def test_genrandbits(self): | |
# Verify ranges | |
for k in xrange(1, 1000): | |
self.assertTrue(0 <= self.gen.getrandbits(k) < 2**k) | |
# Verify all bits active | |
getbits = self.gen.getrandbits | |
for span in [1, 2, 3, 4, 31, 32, 32, 52, 53, 54, 119, 127, 128, 129]: | |
cum = 0 | |
for i in xrange(100): | |
cum |= getbits(span) | |
self.assertEqual(cum, 2**span-1) | |
# Verify argument checking | |
self.assertRaises(TypeError, self.gen.getrandbits) | |
self.assertRaises(TypeError, self.gen.getrandbits, 1, 2) | |
self.assertRaises(ValueError, self.gen.getrandbits, 0) | |
self.assertRaises(ValueError, self.gen.getrandbits, -1) | |
self.assertRaises(TypeError, self.gen.getrandbits, 10.1) | |
def test_randbelow_logic(self, _log=log, int=int): | |
# check bitcount transition points: 2**i and 2**(i+1)-1 | |
# show that: k = int(1.001 + _log(n, 2)) | |
# is equal to or one greater than the number of bits in n | |
for i in xrange(1, 1000): | |
n = 1L << i # check an exact power of two | |
numbits = i+1 | |
k = int(1.00001 + _log(n, 2)) | |
self.assertEqual(k, numbits) | |
self.assertTrue(n == 2**(k-1)) | |
n += n - 1 # check 1 below the next power of two | |
k = int(1.00001 + _log(n, 2)) | |
self.assertIn(k, [numbits, numbits+1]) | |
self.assertTrue(2**k > n > 2**(k-2)) | |
n -= n >> 15 # check a little farther below the next power of two | |
k = int(1.00001 + _log(n, 2)) | |
self.assertEqual(k, numbits) # note the stronger assertion | |
self.assertTrue(2**k > n > 2**(k-1)) # note the stronger assertion | |
class MersenneTwister_TestBasicOps(TestBasicOps): | |
gen = random.Random() | |
def test_setstate_first_arg(self): | |
self.assertRaises(ValueError, self.gen.setstate, (1, None, None)) | |
def test_setstate_middle_arg(self): | |
# Wrong type, s/b tuple | |
self.assertRaises(TypeError, self.gen.setstate, (2, None, None)) | |
# Wrong length, s/b 625 | |
self.assertRaises(ValueError, self.gen.setstate, (2, (1,2,3), None)) | |
# Wrong type, s/b tuple of 625 ints | |
self.assertRaises(TypeError, self.gen.setstate, (2, ('a',)*625, None)) | |
# Last element s/b an int also | |
self.assertRaises(TypeError, self.gen.setstate, (2, (0,)*624+('a',), None)) | |
def test_referenceImplementation(self): | |
# Compare the python implementation with results from the original | |
# code. Create 2000 53-bit precision random floats. Compare only | |
# the last ten entries to show that the independent implementations | |
# are tracking. Here is the main() function needed to create the | |
# list of expected random numbers: | |
# void main(void){ | |
# int i; | |
# unsigned long init[4]={61731, 24903, 614, 42143}, length=4; | |
# init_by_array(init, length); | |
# for (i=0; i<2000; i++) { | |
# printf("%.15f ", genrand_res53()); | |
# if (i%5==4) printf("\n"); | |
# } | |
# } | |
expected = [0.45839803073713259, | |
0.86057815201978782, | |
0.92848331726782152, | |
0.35932681119782461, | |
0.081823493762449573, | |
0.14332226470169329, | |
0.084297823823520024, | |
0.53814864671831453, | |
0.089215024911993401, | |
0.78486196105372907] | |
self.gen.seed(61731L + (24903L<<32) + (614L<<64) + (42143L<<96)) | |
actual = self.randomlist(2000)[-10:] | |
for a, e in zip(actual, expected): | |
self.assertAlmostEqual(a,e,places=14) | |
def test_strong_reference_implementation(self): | |
# Like test_referenceImplementation, but checks for exact bit-level | |
# equality. This should pass on any box where C double contains | |
# at least 53 bits of precision (the underlying algorithm suffers | |
# no rounding errors -- all results are exact). | |
from math import ldexp | |
expected = [0x0eab3258d2231fL, | |
0x1b89db315277a5L, | |
0x1db622a5518016L, | |
0x0b7f9af0d575bfL, | |
0x029e4c4db82240L, | |
0x04961892f5d673L, | |
0x02b291598e4589L, | |
0x11388382c15694L, | |
0x02dad977c9e1feL, | |
0x191d96d4d334c6L] | |
self.gen.seed(61731L + (24903L<<32) + (614L<<64) + (42143L<<96)) | |
actual = self.randomlist(2000)[-10:] | |
for a, e in zip(actual, expected): | |
self.assertEqual(long(ldexp(a, 53)), e) | |
def test_long_seed(self): | |
# This is most interesting to run in debug mode, just to make sure | |
# nothing blows up. Under the covers, a dynamically resized array | |
# is allocated, consuming space proportional to the number of bits | |
# in the seed. Unfortunately, that's a quadratic-time algorithm, | |
# so don't make this horribly big. | |
seed = (1L << (10000 * 8)) - 1 # about 10K bytes | |
self.gen.seed(seed) | |
def test_53_bits_per_float(self): | |
# This should pass whenever a C double has 53 bit precision. | |
span = 2 ** 53 | |
cum = 0 | |
for i in xrange(100): | |
cum |= int(self.gen.random() * span) | |
self.assertEqual(cum, span-1) | |
def test_bigrand(self): | |
# The randrange routine should build-up the required number of bits | |
# in stages so that all bit positions are active. | |
span = 2 ** 500 | |
cum = 0 | |
for i in xrange(100): | |
r = self.gen.randrange(span) | |
self.assertTrue(0 <= r < span) | |
cum |= r | |
self.assertEqual(cum, span-1) | |
def test_bigrand_ranges(self): | |
for i in [40,80, 160, 200, 211, 250, 375, 512, 550]: | |
start = self.gen.randrange(2 ** i) | |
stop = self.gen.randrange(2 ** (i-2)) | |
if stop <= start: | |
return | |
self.assertTrue(start <= self.gen.randrange(start, stop) < stop) | |
def test_rangelimits(self): | |
for start, stop in [(-2,0), (-(2**60)-2,-(2**60)), (2**60,2**60+2)]: | |
self.assertEqual(set(range(start,stop)), | |
set([self.gen.randrange(start,stop) for i in xrange(100)])) | |
def test_genrandbits(self): | |
# Verify cross-platform repeatability | |
self.gen.seed(1234567) | |
self.assertEqual(self.gen.getrandbits(100), | |
97904845777343510404718956115L) | |
# Verify ranges | |
for k in xrange(1, 1000): | |
self.assertTrue(0 <= self.gen.getrandbits(k) < 2**k) | |
# Verify all bits active | |
getbits = self.gen.getrandbits | |
for span in [1, 2, 3, 4, 31, 32, 32, 52, 53, 54, 119, 127, 128, 129]: | |
cum = 0 | |
for i in xrange(100): | |
cum |= getbits(span) | |
self.assertEqual(cum, 2**span-1) | |
# Verify argument checking | |
self.assertRaises(TypeError, self.gen.getrandbits) | |
self.assertRaises(TypeError, self.gen.getrandbits, 'a') | |
self.assertRaises(TypeError, self.gen.getrandbits, 1, 2) | |
self.assertRaises(ValueError, self.gen.getrandbits, 0) | |
self.assertRaises(ValueError, self.gen.getrandbits, -1) | |
def test_randbelow_logic(self, _log=log, int=int): | |
# check bitcount transition points: 2**i and 2**(i+1)-1 | |
# show that: k = int(1.001 + _log(n, 2)) | |
# is equal to or one greater than the number of bits in n | |
for i in xrange(1, 1000): | |
n = 1L << i # check an exact power of two | |
numbits = i+1 | |
k = int(1.00001 + _log(n, 2)) | |
self.assertEqual(k, numbits) | |
self.assertTrue(n == 2**(k-1)) | |
n += n - 1 # check 1 below the next power of two | |
k = int(1.00001 + _log(n, 2)) | |
self.assertIn(k, [numbits, numbits+1]) | |
self.assertTrue(2**k > n > 2**(k-2)) | |
n -= n >> 15 # check a little farther below the next power of two | |
k = int(1.00001 + _log(n, 2)) | |
self.assertEqual(k, numbits) # note the stronger assertion | |
self.assertTrue(2**k > n > 2**(k-1)) # note the stronger assertion | |
def test_randrange_bug_1590891(self): | |
start = 1000000000000 | |
stop = -100000000000000000000 | |
step = -200 | |
x = self.gen.randrange(start, stop, step) | |
self.assertTrue(stop < x <= start) | |
self.assertEqual((x+stop)%step, 0) | |
def gamma(z, sqrt2pi=(2.0*pi)**0.5): | |
# Reflection to right half of complex plane | |
if z < 0.5: | |
return pi / sin(pi*z) / gamma(1.0-z) | |
# Lanczos approximation with g=7 | |
az = z + (7.0 - 0.5) | |
return az ** (z-0.5) / exp(az) * sqrt2pi * fsum([ | |
0.9999999999995183, | |
676.5203681218835 / z, | |
-1259.139216722289 / (z+1.0), | |
771.3234287757674 / (z+2.0), | |
-176.6150291498386 / (z+3.0), | |
12.50734324009056 / (z+4.0), | |
-0.1385710331296526 / (z+5.0), | |
0.9934937113930748e-05 / (z+6.0), | |
0.1659470187408462e-06 / (z+7.0), | |
]) | |
class TestDistributions(unittest.TestCase): | |
def test_zeroinputs(self): | |
# Verify that distributions can handle a series of zero inputs' | |
g = random.Random() | |
x = [g.random() for i in xrange(50)] + [0.0]*5 | |
g.random = x[:].pop; g.uniform(1,10) | |
g.random = x[:].pop; g.paretovariate(1.0) | |
g.random = x[:].pop; g.expovariate(1.0) | |
g.random = x[:].pop; g.weibullvariate(1.0, 1.0) | |
g.random = x[:].pop; g.normalvariate(0.0, 1.0) | |
g.random = x[:].pop; g.gauss(0.0, 1.0) | |
g.random = x[:].pop; g.lognormvariate(0.0, 1.0) | |
g.random = x[:].pop; g.vonmisesvariate(0.0, 1.0) | |
g.random = x[:].pop; g.gammavariate(0.01, 1.0) | |
g.random = x[:].pop; g.gammavariate(1.0, 1.0) | |
g.random = x[:].pop; g.gammavariate(200.0, 1.0) | |
g.random = x[:].pop; g.betavariate(3.0, 3.0) | |
g.random = x[:].pop; g.triangular(0.0, 1.0, 1.0/3.0) | |
def test_avg_std(self): | |
# Use integration to test distribution average and standard deviation. | |
# Only works for distributions which do not consume variates in pairs | |
g = random.Random() | |
N = 5000 | |
x = [i/float(N) for i in xrange(1,N)] | |
for variate, args, mu, sigmasqrd in [ | |
(g.uniform, (1.0,10.0), (10.0+1.0)/2, (10.0-1.0)**2/12), | |
(g.triangular, (0.0, 1.0, 1.0/3.0), 4.0/9.0, 7.0/9.0/18.0), | |
(g.expovariate, (1.5,), 1/1.5, 1/1.5**2), | |
(g.paretovariate, (5.0,), 5.0/(5.0-1), | |
5.0/((5.0-1)**2*(5.0-2))), | |
(g.weibullvariate, (1.0, 3.0), gamma(1+1/3.0), | |
gamma(1+2/3.0)-gamma(1+1/3.0)**2) ]: | |
g.random = x[:].pop | |
y = [] | |
for i in xrange(len(x)): | |
try: | |
y.append(variate(*args)) | |
except IndexError: | |
pass | |
s1 = s2 = 0 | |
for e in y: | |
s1 += e | |
s2 += (e - mu) ** 2 | |
N = len(y) | |
self.assertAlmostEqual(s1/N, mu, 2) | |
self.assertAlmostEqual(s2/(N-1), sigmasqrd, 2) | |
class TestModule(unittest.TestCase): | |
def testMagicConstants(self): | |
self.assertAlmostEqual(random.NV_MAGICCONST, 1.71552776992141) | |
self.assertAlmostEqual(random.TWOPI, 6.28318530718) | |
self.assertAlmostEqual(random.LOG4, 1.38629436111989) | |
self.assertAlmostEqual(random.SG_MAGICCONST, 2.50407739677627) | |
def test__all__(self): | |
# tests validity but not completeness of the __all__ list | |
self.assertTrue(set(random.__all__) <= set(dir(random))) | |
def test_random_subclass_with_kwargs(self): | |
# SF bug #1486663 -- this used to erroneously raise a TypeError | |
class Subclass(random.Random): | |
def __init__(self, newarg=None): | |
random.Random.__init__(self) | |
Subclass(newarg=1) | |
def test_main(verbose=None): | |
testclasses = [WichmannHill_TestBasicOps, | |
MersenneTwister_TestBasicOps, | |
TestDistributions, | |
TestModule] | |
try: | |
random.SystemRandom().random() | |
except NotImplementedError: | |
pass | |
else: | |
testclasses.append(SystemRandom_TestBasicOps) | |
test_support.run_unittest(*testclasses) | |
# verify reference counting | |
import sys | |
if verbose and hasattr(sys, "gettotalrefcount"): | |
counts = [None] * 5 | |
for i in xrange(len(counts)): | |
test_support.run_unittest(*testclasses) | |
counts[i] = sys.gettotalrefcount() | |
print counts | |
if __name__ == "__main__": | |
test_main(verbose=True) |