diff options
Diffstat (limited to 'numpy/random/tests/test_generator_mt19937.py')
| -rw-r--r-- | numpy/random/tests/test_generator_mt19937.py | 110 |
1 files changed, 85 insertions, 25 deletions
diff --git a/numpy/random/tests/test_generator_mt19937.py b/numpy/random/tests/test_generator_mt19937.py index 332b63198..b69cd38d4 100644 --- a/numpy/random/tests/test_generator_mt19937.py +++ b/numpy/random/tests/test_generator_mt19937.py @@ -18,20 +18,20 @@ JUMP_TEST_DATA = [ { "seed": 0, "steps": 10, - "initial": {"key_md5": "64eaf265d2203179fb5ffb73380cd589", "pos": 9}, - "jumped": {"key_md5": "8cb7b061136efceef5217a9ce2cc9a5a", "pos": 598}, + "initial": {"key_sha256": "bb1636883c2707b51c5b7fc26c6927af4430f2e0785a8c7bc886337f919f9edf", "pos": 9}, + "jumped": {"key_sha256": "ff682ac12bb140f2d72fba8d3506cf4e46817a0db27aae1683867629031d8d55", "pos": 598}, }, { "seed":384908324, "steps":312, - "initial": {"key_md5": "e99708a47b82ff51a2c7b0625b81afb5", "pos": 311}, - "jumped": {"key_md5": "2ecdbfc47a895b253e6e19ccb2e74b90", "pos": 276}, + "initial": {"key_sha256": "16b791a1e04886ccbbb4d448d6ff791267dc458ae599475d08d5cced29d11614", "pos": 311}, + "jumped": {"key_sha256": "a0110a2cf23b56be0feaed8f787a7fc84bef0cb5623003d75b26bdfa1c18002c", "pos": 276}, }, { "seed": [839438204, 980239840, 859048019, 821], "steps": 511, - "initial": {"key_md5": "9fcd6280df9199785e17e93162ce283c", "pos": 510}, - "jumped": {"key_md5": "433b85229f2ed853cde06cd872818305", "pos": 475}, + "initial": {"key_sha256": "d306cf01314d51bd37892d874308200951a35265ede54d200f1e065004c3e9ea", "pos": 510}, + "jumped": {"key_sha256": "0e00ab449f01a5195a83b4aee0dfbc2ce8d46466a640b92e33977d2e42f777f8", "pos": 475}, }, ] @@ -483,18 +483,18 @@ class TestIntegers: assert_array_equal(scalar, array) def test_repeatability(self, endpoint): - # We use a md5 hash of generated sequences of 1000 samples + # We use a sha256 hash of generated sequences of 1000 samples # in the range [0, 6) for all but bool, where the range # is [0, 2). Hashes are for little endian numbers. - tgt = {'bool': 'b3300e66d2bb59e493d255d47c3a6cbe', - 'int16': '39624ead49ad67e37545744024d2648b', - 'int32': '5c4810373f979336c6c0c999996e47a1', - 'int64': 'ab126c15edff26f55c50d2b7e37391ac', - 'int8': 'ba71ccaffeeeb9eeb1860f8075020b9c', - 'uint16': '39624ead49ad67e37545744024d2648b', - 'uint32': '5c4810373f979336c6c0c999996e47a1', - 'uint64': 'ab126c15edff26f55c50d2b7e37391ac', - 'uint8': 'ba71ccaffeeeb9eeb1860f8075020b9c'} + tgt = {'bool': '053594a9b82d656f967c54869bc6970aa0358cf94ad469c81478459c6a90eee3', + 'int16': '54de9072b6ee9ff7f20b58329556a46a447a8a29d67db51201bf88baa6e4e5d4', + 'int32': 'd3a0d5efb04542b25ac712e50d21f39ac30f312a5052e9bbb1ad3baa791ac84b', + 'int64': '14e224389ac4580bfbdccb5697d6190b496f91227cf67df60989de3d546389b1', + 'int8': '0e203226ff3fbbd1580f15da4621e5f7164d0d8d6b51696dd42d004ece2cbec1', + 'uint16': '54de9072b6ee9ff7f20b58329556a46a447a8a29d67db51201bf88baa6e4e5d4', + 'uint32': 'd3a0d5efb04542b25ac712e50d21f39ac30f312a5052e9bbb1ad3baa791ac84b', + 'uint64': '14e224389ac4580bfbdccb5697d6190b496f91227cf67df60989de3d546389b1', + 'uint8': '0e203226ff3fbbd1580f15da4621e5f7164d0d8d6b51696dd42d004ece2cbec1'} for dt in self.itype[1:]: random = Generator(MT19937(1234)) @@ -507,14 +507,14 @@ class TestIntegers: val = random.integers(0, 6 - endpoint, size=1000, endpoint=endpoint, dtype=dt).byteswap() - res = hashlib.md5(val).hexdigest() + res = hashlib.sha256(val).hexdigest() assert_(tgt[np.dtype(dt).name] == res) # bools do not depend on endianness random = Generator(MT19937(1234)) val = random.integers(0, 2 - endpoint, size=1000, endpoint=endpoint, dtype=bool).view(np.int8) - res = hashlib.md5(val).hexdigest() + res = hashlib.sha256(val).hexdigest() assert_(tgt[np.dtype(bool).name] == res) def test_repeatability_broadcasting(self, endpoint): @@ -905,12 +905,12 @@ class TestRandomDist: assert actual.dtype == np.int64 def test_choice_large_sample(self): - choice_hash = 'd44962a0b1e92f4a3373c23222244e21' + choice_hash = '4266599d12bfcfb815213303432341c06b4349f5455890446578877bb322e222' random = Generator(MT19937(self.seed)) actual = random.choice(10000, 5000, replace=False) if sys.byteorder != 'little': actual = actual.byteswap() - res = hashlib.md5(actual.view(np.int8)).hexdigest() + res = hashlib.sha256(actual.view(np.int8)).hexdigest() assert_(choice_hash == res) def test_bytes(self): @@ -1039,6 +1039,56 @@ class TestRandomDist: assert_raises(np.AxisError, random.permutation, arr, 3) assert_raises(TypeError, random.permutation, arr, slice(1, 2, None)) + @pytest.mark.parametrize("dtype", [int, object]) + @pytest.mark.parametrize("axis, expected", + [(None, np.array([[3, 7, 0, 9, 10, 11], + [8, 4, 2, 5, 1, 6]])), + (0, np.array([[6, 1, 2, 9, 10, 11], + [0, 7, 8, 3, 4, 5]])), + (1, np.array([[ 5, 3, 4, 0, 2, 1], + [11, 9, 10, 6, 8, 7]]))]) + def test_permuted(self, dtype, axis, expected): + random = Generator(MT19937(self.seed)) + x = np.arange(12).reshape(2, 6).astype(dtype) + random.permuted(x, axis=axis, out=x) + assert_array_equal(x, expected) + + random = Generator(MT19937(self.seed)) + x = np.arange(12).reshape(2, 6).astype(dtype) + y = random.permuted(x, axis=axis) + assert y.dtype == dtype + assert_array_equal(y, expected) + + def test_permuted_with_strides(self): + random = Generator(MT19937(self.seed)) + x0 = np.arange(22).reshape(2, 11) + x1 = x0.copy() + x = x0[:, ::3] + y = random.permuted(x, axis=1, out=x) + expected = np.array([[0, 9, 3, 6], + [14, 20, 11, 17]]) + assert_array_equal(y, expected) + x1[:, ::3] = expected + # Verify that the original x0 was modified in-place as expected. + assert_array_equal(x1, x0) + + def test_permuted_empty(self): + y = random.permuted([]) + assert_array_equal(y, []) + + @pytest.mark.parametrize('outshape', [(2, 3), 5]) + def test_permuted_out_with_wrong_shape(self, outshape): + a = np.array([1, 2, 3]) + out = np.zeros(outshape, dtype=a.dtype) + with pytest.raises(ValueError, match='same shape'): + random.permuted(a, out=out) + + def test_permuted_out_with_wrong_type(self): + out = np.zeros((3, 5), dtype=np.int32) + x = np.ones((3, 5)) + with pytest.raises(TypeError, match='Cannot cast'): + random.permuted(x, axis=1, out=out) + def test_beta(self): random = Generator(MT19937(self.seed)) actual = random.beta(.1, .9, size=(3, 2)) @@ -2374,7 +2424,7 @@ class TestSingleEltArrayInput: @pytest.mark.parametrize("config", JUMP_TEST_DATA) def test_jumped(config): # Each config contains the initial seed, a number of raw steps - # the md5 hashes of the initial and the final states' keys and + # the sha256 hashes of the initial and the final states' keys and # the position of of the initial and the final state. # These were produced using the original C implementation. seed = config["seed"] @@ -2386,17 +2436,17 @@ def test_jumped(config): key = mt19937.state["state"]["key"] if sys.byteorder == 'big': key = key.byteswap() - md5 = hashlib.md5(key) + sha256 = hashlib.sha256(key) assert mt19937.state["state"]["pos"] == config["initial"]["pos"] - assert md5.hexdigest() == config["initial"]["key_md5"] + assert sha256.hexdigest() == config["initial"]["key_sha256"] jumped = mt19937.jumped() key = jumped.state["state"]["key"] if sys.byteorder == 'big': key = key.byteswap() - md5 = hashlib.md5(key) + sha256 = hashlib.sha256(key) assert jumped.state["state"]["pos"] == config["jumped"]["pos"] - assert md5.hexdigest() == config["jumped"]["key_md5"] + assert sha256.hexdigest() == config["jumped"]["key_sha256"] def test_broadcast_size_error(): @@ -2423,6 +2473,16 @@ def test_broadcast_size_error(): with pytest.raises(ValueError): random.standard_gamma(shape, out=out) + # 2 arg + with pytest.raises(ValueError): + random.binomial(1, [0.3, 0.7], size=(2, 1)) + with pytest.raises(ValueError): + random.binomial([1, 2], 0.3, size=(2, 1)) + with pytest.raises(ValueError): + random.binomial([1, 2], [0.3, 0.7], size=(2, 1)) + with pytest.raises(ValueError): + random.multinomial([2, 2], [.3, .7], size=(2, 1)) + # 3 arg a = random.chisquare(5, size=3) b = random.chisquare(5, size=(4, 3)) |