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| author | Sebastian Berg <sebastian@sipsolutions.net> | 2016-08-31 21:16:08 +0200 |
|---|---|---|
| committer | Sebastian Berg <sebastian@sipsolutions.net> | 2016-09-02 10:10:55 +0200 |
| commit | 20ea3a25119834c2224e32caebf4f2fb4966edd3 (patch) | |
| tree | 7d3ccc7506b76b1d72f96c9f097d54a2383080e8 /numpy/lib/tests/test_nanfunctions.py | |
| parent | 61694be14e678ae49f35205d5af0aee4882e1a70 (diff) | |
| download | numpy-20ea3a25119834c2224e32caebf4f2fb4966edd3.tar.gz | |
TST: Replace catch_warnings when recording is not enforced in test_nanfuncs
Diffstat (limited to 'numpy/lib/tests/test_nanfunctions.py')
| -rw-r--r-- | numpy/lib/tests/test_nanfunctions.py | 20 |
1 files changed, 10 insertions, 10 deletions
diff --git a/numpy/lib/tests/test_nanfunctions.py b/numpy/lib/tests/test_nanfunctions.py index e062bc032..e4aea4482 100644 --- a/numpy/lib/tests/test_nanfunctions.py +++ b/numpy/lib/tests/test_nanfunctions.py @@ -167,8 +167,8 @@ class TestNanFunctions_ArgminArgmax(TestCase): def test_result_values(self): for f, fcmp in zip(self.nanfuncs, [np.greater, np.less]): for row in _ndat: - with warnings.catch_warnings(record=True): - warnings.simplefilter('always') + with suppress_warnings() as sup: + sup.filter(RuntimeWarning, "invalid value encountered in") ind = f(row) val = row[ind] # comparing with NaN is tricky as the result @@ -589,8 +589,8 @@ class TestNanFunctions_Median(TestCase): w = np.random.random((4, 200)) * np.array(d.shape)[:, None] w = w.astype(np.intp) d[tuple(w)] = np.nan - with warnings.catch_warnings(record=True) as w: - warnings.simplefilter('always', RuntimeWarning) + with suppress_warnings() as sup: + sup.filter(RuntimeWarning) res = np.nanmedian(d, axis=None, keepdims=True) assert_equal(res.shape, (1, 1, 1, 1)) res = np.nanmedian(d, axis=(0, 1), keepdims=True) @@ -687,8 +687,8 @@ class TestNanFunctions_Median(TestCase): assert_raises(ValueError, np.nanmedian, d, axis=(1, 1)) def test_float_special(self): - with warnings.catch_warnings(record=True): - warnings.simplefilter('always', RuntimeWarning) + with suppress_warnings() as sup: + sup.filter(RuntimeWarning) a = np.array([[np.inf, np.nan], [np.nan, np.nan]]) assert_equal(np.nanmedian(a, axis=0), [np.inf, np.nan]) assert_equal(np.nanmedian(a, axis=1), [np.inf, np.nan]) @@ -725,8 +725,8 @@ class TestNanFunctions_Percentile(TestCase): w = np.random.random((4, 200)) * np.array(d.shape)[:, None] w = w.astype(np.intp) d[tuple(w)] = np.nan - with warnings.catch_warnings(record=True) as w: - warnings.simplefilter('always', RuntimeWarning) + with suppress_warnings() as sup: + sup.filter(RuntimeWarning) res = np.nanpercentile(d, 90, axis=None, keepdims=True) assert_equal(res.shape, (1, 1, 1, 1)) res = np.nanpercentile(d, 90, axis=(0, 1), keepdims=True) @@ -821,8 +821,8 @@ class TestNanFunctions_Percentile(TestCase): large_mat[:, :, 3:] *= 2 for axis in [None, 0, 1]: for keepdim in [False, True]: - with warnings.catch_warnings(record=True) as w: - warnings.simplefilter('always') + with suppress_warnings() as sup: + sup.filter(RuntimeWarning, "All-NaN slice encountered") val = np.percentile(mat, perc, axis=axis, keepdims=keepdim) nan_val = np.nanpercentile(nan_mat, perc, axis=axis, keepdims=keepdim) |