diff options
Diffstat (limited to 'numpy/random/tests/test_random.py')
| -rw-r--r-- | numpy/random/tests/test_random.py | 44 |
1 files changed, 26 insertions, 18 deletions
diff --git a/numpy/random/tests/test_random.py b/numpy/random/tests/test_random.py index 47301a770..dc7d18933 100644 --- a/numpy/random/tests/test_random.py +++ b/numpy/random/tests/test_random.py @@ -1,10 +1,11 @@ from __future__ import division, absolute_import, print_function +import warnings import numpy as np from numpy.testing import ( TestCase, run_module_suite, assert_, assert_raises, assert_equal, - assert_warns, assert_array_equal, assert_array_almost_equal, - suppress_warnings) + assert_warns, assert_no_warnings, assert_array_equal, + assert_array_almost_equal, suppress_warnings) from numpy import random from numpy.compat import asbytes import sys @@ -579,10 +580,6 @@ class TestRandomDist(TestCase): [-0.21682183359214885, 2.63373365386060332]]) assert_array_almost_equal(actual, desired, decimal=15) - def test_laplace_0(self): - assert_(np.random.laplace(scale=0) in [0, 1]) - assert_raises(ValueError, np.random.laplace, scale=-0.) - def test_lognormal(self): np.random.seed(self.seed) actual = np.random.lognormal(mean=.123456789, sigma=2.0, size=(3, 2)) @@ -617,28 +614,37 @@ class TestRandomDist(TestCase): def test_multivariate_normal(self): np.random.seed(self.seed) mean = (.123456789, 10) - # Hmm... not even symmetric. - cov = [[1, 0], [1, 0]] + cov = [[1, 0], [0, 1]] size = (3, 2) actual = np.random.multivariate_normal(mean, cov, size) - desired = np.array([[[-1.47027513018564449, 10.], - [-1.65915081534845532, 10.]], - [[-2.29186329304599745, 10.], - [-1.77505606019580053, 10.]], - [[-0.54970369430044119, 10.], - [0.29768848031692957, 10.]]]) + desired = np.array([[[1.463620246718631, 11.73759122771936 ], + [1.622445133300628, 9.771356667546383]], + [[2.154490787682787, 12.170324946056553], + [1.719909438201865, 9.230548443648306]], + [[0.689515026297799, 9.880729819607714], + [-0.023054015651998, 9.201096623542879]]]) + assert_array_almost_equal(actual, desired, decimal=15) # Check for default size, was raising deprecation warning actual = np.random.multivariate_normal(mean, cov) - desired = np.array([-0.79441224511977482, 10.]) + desired = np.array([0.895289569463708, 9.17180864067987]) assert_array_almost_equal(actual, desired, decimal=15) - # Check that non positive-semidefinite covariance raises warning + # Check that non positive-semidefinite covariance warns with + # RuntimeWarning mean = [0, 0] - cov = [[1, 1 + 1e-10], [1 + 1e-10, 1]] + cov = [[1, 2], [2, 1]] assert_warns(RuntimeWarning, np.random.multivariate_normal, mean, cov) + # and that it doesn't warn with RuntimeWarning check_valid='ignore' + assert_no_warnings(np.random.multivariate_normal, mean, cov, + check_valid='ignore') + + # and that it raises with RuntimeWarning check_valid='raises' + assert_raises(ValueError, np.random.multivariate_normal, mean, cov, + check_valid='raise') + def test_negative_binomial(self): np.random.seed(self.seed) actual = np.random.negative_binomial(n=100, p=.12345, size=(3, 2)) @@ -813,7 +819,9 @@ class TestRandomDist(TestCase): assert_raises(OverflowError, func, [0], [np.inf]) # (fmax / 1e17) - fmin is within range, so this should not throw - np.random.uniform(low=fmin, high=fmax / 1e17) + # account for i386 extended precision DBL_MAX / 1e17 + DBL_MAX > + # DBL_MAX by increasing fmin a bit + np.random.uniform(low=np.nextafter(fmin, 1), high=fmax / 1e17) def test_vonmises(self): np.random.seed(self.seed) |