diff options
Diffstat (limited to 'numpy/lib/tests/test_twodim_base.py')
| -rw-r--r-- | numpy/lib/tests/test_twodim_base.py | 69 |
1 files changed, 33 insertions, 36 deletions
diff --git a/numpy/lib/tests/test_twodim_base.py b/numpy/lib/tests/test_twodim_base.py index 8183f7ca6..d3a072af3 100644 --- a/numpy/lib/tests/test_twodim_base.py +++ b/numpy/lib/tests/test_twodim_base.py @@ -4,14 +4,14 @@ from __future__ import division, absolute_import, print_function from numpy.testing import ( - run_module_suite, assert_equal, assert_array_equal, assert_array_max_ulp, + assert_equal, assert_array_equal, assert_array_max_ulp, assert_array_almost_equal, assert_raises, ) from numpy import ( - arange, add, fliplr, flipud, zeros, ones, eye, array, diag, - histogram2d, tri, mask_indices, triu_indices, triu_indices_from, - tril_indices, tril_indices_from, vander, + arange, add, fliplr, flipud, zeros, ones, eye, array, diag, histogram2d, + tri, mask_indices, triu_indices, triu_indices_from, tril_indices, + tril_indices_from, vander, ) import numpy as np @@ -244,32 +244,32 @@ class TestHistogram2d(object): def test_binparameter_combination(self): x = array( - [0, 0.09207008, 0.64575234, 0.12875982, 0.47390599, + [0, 0.09207008, 0.64575234, 0.12875982, 0.47390599, 0.59944483, 1]) y = array( - [0, 0.14344267, 0.48988575, 0.30558665, 0.44700682, + [0, 0.14344267, 0.48988575, 0.30558665, 0.44700682, 0.15886423, 1]) edges = (0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1) H, xe, ye = histogram2d(x, y, (edges, 4)) answer = array( - [[ 2., 0., 0., 0.], - [ 0., 1., 0., 0.], - [ 0., 0., 0., 0.], - [ 0., 0., 0., 0.], - [ 0., 1., 0., 0.], - [ 1., 0., 0., 0.], - [ 0., 1., 0., 0.], - [ 0., 0., 0., 0.], - [ 0., 0., 0., 0.], - [ 0., 0., 0., 1.]]) + [[2., 0., 0., 0.], + [0., 1., 0., 0.], + [0., 0., 0., 0.], + [0., 0., 0., 0.], + [0., 1., 0., 0.], + [1., 0., 0., 0.], + [0., 1., 0., 0.], + [0., 0., 0., 0.], + [0., 0., 0., 0.], + [0., 0., 0., 1.]]) assert_array_equal(H, answer) assert_array_equal(ye, array([0., 0.25, 0.5, 0.75, 1])) H, xe, ye = histogram2d(x, y, (4, edges)) answer = array( - [[ 1., 1., 0., 1., 0., 0., 0., 0., 0., 0.], - [ 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.], - [ 0., 1., 0., 0., 1., 0., 0., 0., 0., 0.], - [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.]]) + [[1., 1., 0., 1., 0., 0., 0., 0., 0., 0.], + [0., 0., 0., 0., 1., 0., 0., 0., 0., 0.], + [0., 1., 0., 0., 1., 0., 0., 0., 0., 0.], + [0., 0., 0., 0., 0., 0., 0., 0., 0., 1.]]) assert_array_equal(H, answer) assert_array_equal(xe, array([0., 0.25, 0.5, 0.75, 1])) @@ -288,11 +288,11 @@ def test_tril_triu_ndim2(): a = np.ones((2, 2), dtype=dtype) b = np.tril(a) c = np.triu(a) - yield assert_array_equal, b, [[1, 0], [1, 1]] - yield assert_array_equal, c, b.T + assert_array_equal(b, [[1, 0], [1, 1]]) + assert_array_equal(c, b.T) # should return the same dtype as the original array - yield assert_equal, b.dtype, a.dtype - yield assert_equal, c.dtype, a.dtype + assert_equal(b.dtype, a.dtype) + assert_equal(c.dtype, a.dtype) def test_tril_triu_ndim3(): @@ -314,10 +314,11 @@ def test_tril_triu_ndim3(): ], dtype=dtype) a_triu_observed = np.triu(a) a_tril_observed = np.tril(a) - yield assert_array_equal, a_triu_observed, a_triu_desired - yield assert_array_equal, a_tril_observed, a_tril_desired - yield assert_equal, a_triu_observed.dtype, a.dtype - yield assert_equal, a_tril_observed.dtype, a.dtype + assert_array_equal(a_triu_observed, a_triu_desired) + assert_array_equal(a_tril_observed, a_tril_desired) + assert_equal(a_triu_observed.dtype, a.dtype) + assert_equal(a_tril_observed.dtype, a.dtype) + def test_tril_triu_with_inf(): # Issue 4859 @@ -484,12 +485,12 @@ class TestVander(object): [16, -8, 4, -2, 1], [81, 27, 9, 3, 1]]) # Check default value of N: - yield (assert_array_equal, v, powers[:, 1:]) + assert_array_equal(v, powers[:, 1:]) # Check a range of N values, including 0 and 5 (greater than default) m = powers.shape[1] for n in range(6): v = vander(c, N=n) - yield (assert_array_equal, v, powers[:, m-n:m]) + assert_array_equal(v, powers[:, m-n:m]) def test_dtypes(self): c = array([11, -12, 13], dtype=np.int8) @@ -497,7 +498,7 @@ class TestVander(object): expected = np.array([[121, 11, 1], [144, -12, 1], [169, 13, 1]]) - yield (assert_array_equal, v, expected) + assert_array_equal(v, expected) c = array([1.0+1j, 1.0-1j]) v = vander(c, N=3) @@ -506,8 +507,4 @@ class TestVander(object): # The data is floating point, but the values are small integers, # so assert_array_equal *should* be safe here (rather than, say, # assert_array_almost_equal). - yield (assert_array_equal, v, expected) - - -if __name__ == "__main__": - run_module_suite() + assert_array_equal(v, expected) |