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| author | Raghuveer Devulapalli <raghuveer.devulapalli@intel.com> | 2019-11-07 16:12:04 -0800 |
|---|---|---|
| committer | Raghuveer Devulapalli <raghuveer.devulapalli@intel.com> | 2020-01-28 08:52:42 -0800 |
| commit | b6439313168f6df3f4b1486a53bbe8d772b48ff5 (patch) | |
| tree | 4070ebbfea1adbbd1878dec97dc64c22aecc5a18 /numpy/core/tests | |
| parent | f7f8e621ce4774722968f2f0a77d305cfabf46d5 (diff) | |
| download | numpy-b6439313168f6df3f4b1486a53bbe8d772b48ff5.tar.gz | |
TST: Testing strided arrays for np.maximum and np.minimum
Diffstat (limited to 'numpy/core/tests')
| -rw-r--r-- | numpy/core/tests/test_umath.py | 25 |
1 files changed, 25 insertions, 0 deletions
diff --git a/numpy/core/tests/test_umath.py b/numpy/core/tests/test_umath.py index 10a1c0803..d1d4467d6 100644 --- a/numpy/core/tests/test_umath.py +++ b/numpy/core/tests/test_umath.py @@ -1108,6 +1108,19 @@ class TestMaximum(_FilterInvalids): arg2 = arg1 + 1 assert_equal(np.maximum(arg1, arg2), arg2) + def test_strided_array(self): + arr1 = np.array([-4.0, 1.0, 10.0, 0.0, np.nan, -np.nan, np.inf, -np.inf]) + arr2 = np.array([-2.0,-1.0, np.nan, 1.0, 0.0, np.nan, 1.0, -3.0]) + maxtrue = np.array([-2.0, 1.0, np.nan, 1.0, np.nan, np.nan, np.inf, -3.0]) + out = np.ones(8) + out_maxtrue = np.array([-2.0, 1.0, 1.0, 10.0, 1.0, 1.0, np.nan, 1.0]) + assert_equal(np.maximum(arr1,arr2), maxtrue) + assert_equal(np.maximum(arr1[::2],arr2[::2]), maxtrue[::2]) + assert_equal(np.maximum(arr1[:4:], arr2[::2]), np.array([-2.0, np.nan, 10.0, 1.0])) + assert_equal(np.maximum(arr1[::3], arr2[:3:]), np.array([-2.0, 0.0, np.nan])) + assert_equal(np.maximum(arr1[:6:2], arr2[::3], out=out[::3]), np.array([-2.0, 10., np.nan])) + assert_equal(out, out_maxtrue) + class TestMinimum(_FilterInvalids): def test_reduce(self): @@ -1166,6 +1179,18 @@ class TestMinimum(_FilterInvalids): arg2 = arg1 + 1 assert_equal(np.minimum(arg1, arg2), arg1) + def test_strided_array(self): + arr1 = np.array([-4.0, 1.0, 10.0, 0.0, np.nan, -np.nan, np.inf, -np.inf]) + arr2 = np.array([-2.0,-1.0, np.nan, 1.0, 0.0, np.nan, 1.0, -3.0]) + mintrue = np.array([-4.0, -1.0, np.nan, 0.0, np.nan, np.nan, 1.0, -np.inf]) + out = np.ones(8) + out_mintrue = np.array([-4.0, 1.0, 1.0, 1.0, 1.0, 1.0, np.nan, 1.0]) + assert_equal(np.minimum(arr1,arr2), mintrue) + assert_equal(np.minimum(arr1[::2],arr2[::2]), mintrue[::2]) + assert_equal(np.minimum(arr1[:4:], arr2[::2]), np.array([-4.0, np.nan, 0.0, 0.0])) + assert_equal(np.minimum(arr1[::3], arr2[:3:]), np.array([-4.0, -1.0, np.nan])) + assert_equal(np.minimum(arr1[:6:2], arr2[::3], out=out[::3]), np.array([-4.0, 1.0, np.nan])) + assert_equal(out, out_mintrue) class TestFmax(_FilterInvalids): def test_reduce(self): |