| #!/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) |