diff options
Diffstat (limited to 'numpy/ma/tests/test_extras.py')
| -rw-r--r-- | numpy/ma/tests/test_extras.py | 52 |
1 files changed, 23 insertions, 29 deletions
diff --git a/numpy/ma/tests/test_extras.py b/numpy/ma/tests/test_extras.py index 33c4b1922..6d56d4dc6 100644 --- a/numpy/ma/tests/test_extras.py +++ b/numpy/ma/tests/test_extras.py @@ -13,7 +13,7 @@ import warnings import numpy as np from numpy.testing import ( - TestCase, run_module_suite, assert_warns, clear_and_catch_warnings + TestCase, run_module_suite, assert_warns, suppress_warnings ) from numpy.ma.testutils import ( assert_, assert_array_equal, assert_equal, assert_almost_equal @@ -764,7 +764,7 @@ class TestCov(TestCase): def setUp(self): self.data = array(np.random.rand(12)) - def test_1d_wo_missing(self): + def test_1d_without_missing(self): # Test cov on 1D variable w/o missing values x = self.data assert_almost_equal(np.cov(x), cov(x)) @@ -772,7 +772,7 @@ class TestCov(TestCase): assert_almost_equal(np.cov(x, rowvar=False, bias=True), cov(x, rowvar=False, bias=True)) - def test_2d_wo_missing(self): + def test_2d_without_missing(self): # Test cov on 1 2D variable w/o missing values x = self.data.reshape(3, 4) assert_almost_equal(np.cov(x), cov(x)) @@ -780,7 +780,7 @@ class TestCov(TestCase): assert_almost_equal(np.cov(x, rowvar=False, bias=True), cov(x, rowvar=False, bias=True)) - def test_1d_w_missing(self): + def test_1d_with_missing(self): # Test cov 1 1D variable w/missing values x = self.data x[-1] = masked @@ -804,7 +804,7 @@ class TestCov(TestCase): assert_almost_equal(np.cov(nx, nx[::-1], rowvar=False, bias=True), cov(x, x[::-1], rowvar=False, bias=True)) - def test_2d_w_missing(self): + def test_2d_with_missing(self): # Test cov on 2D variable w/ missing value x = self.data x[-1] = masked @@ -826,12 +826,6 @@ class TestCov(TestCase): x.shape[0] / frac)) -class catch_warn_mae(clear_and_catch_warnings): - """ Context manager to catch, reset warnings in ma.extras module - """ - class_modules = (mae,) - - class TestCorrcoef(TestCase): def setUp(self): @@ -843,10 +837,10 @@ class TestCorrcoef(TestCase): x, y = self.data, self.data2 expected = np.corrcoef(x) expected2 = np.corrcoef(x, y) - with catch_warn_mae(): + with suppress_warnings() as sup: warnings.simplefilter("always") assert_warns(DeprecationWarning, corrcoef, x, ddof=-1) - warnings.simplefilter("ignore") + sup.filter(DeprecationWarning, "bias and ddof have no effect") # ddof has no or negligible effect on the function assert_almost_equal(np.corrcoef(x, ddof=0), corrcoef(x, ddof=0)) assert_almost_equal(corrcoef(x, ddof=-1), expected) @@ -858,38 +852,38 @@ class TestCorrcoef(TestCase): x, y = self.data, self.data2 expected = np.corrcoef(x) # bias raises DeprecationWarning - with catch_warn_mae(): + with suppress_warnings() as sup: warnings.simplefilter("always") assert_warns(DeprecationWarning, corrcoef, x, y, True, False) assert_warns(DeprecationWarning, corrcoef, x, y, True, True) assert_warns(DeprecationWarning, corrcoef, x, bias=False) - warnings.simplefilter("ignore") + sup.filter(DeprecationWarning, "bias and ddof have no effect") # bias has no or negligible effect on the function assert_almost_equal(corrcoef(x, bias=1), expected) - def test_1d_wo_missing(self): + def test_1d_without_missing(self): # Test cov on 1D variable w/o missing values x = self.data assert_almost_equal(np.corrcoef(x), corrcoef(x)) assert_almost_equal(np.corrcoef(x, rowvar=False), corrcoef(x, rowvar=False)) - with catch_warn_mae(): - warnings.simplefilter("ignore") + with suppress_warnings() as sup: + sup.filter(DeprecationWarning, "bias and ddof have no effect") assert_almost_equal(np.corrcoef(x, rowvar=False, bias=True), corrcoef(x, rowvar=False, bias=True)) - def test_2d_wo_missing(self): + def test_2d_without_missing(self): # Test corrcoef on 1 2D variable w/o missing values x = self.data.reshape(3, 4) assert_almost_equal(np.corrcoef(x), corrcoef(x)) assert_almost_equal(np.corrcoef(x, rowvar=False), corrcoef(x, rowvar=False)) - with catch_warn_mae(): - warnings.simplefilter("ignore") + with suppress_warnings() as sup: + sup.filter(DeprecationWarning, "bias and ddof have no effect") assert_almost_equal(np.corrcoef(x, rowvar=False, bias=True), corrcoef(x, rowvar=False, bias=True)) - def test_1d_w_missing(self): + def test_1d_with_missing(self): # Test corrcoef 1 1D variable w/missing values x = self.data x[-1] = masked @@ -898,8 +892,8 @@ class TestCorrcoef(TestCase): assert_almost_equal(np.corrcoef(nx), corrcoef(x)) assert_almost_equal(np.corrcoef(nx, rowvar=False), corrcoef(x, rowvar=False)) - with catch_warn_mae(): - warnings.simplefilter("ignore") + with suppress_warnings() as sup: + sup.filter(DeprecationWarning, "bias and ddof have no effect") assert_almost_equal(np.corrcoef(nx, rowvar=False, bias=True), corrcoef(x, rowvar=False, bias=True)) try: @@ -911,15 +905,15 @@ class TestCorrcoef(TestCase): assert_almost_equal(np.corrcoef(nx, nx[::-1]), corrcoef(x, x[::-1])) assert_almost_equal(np.corrcoef(nx, nx[::-1], rowvar=False), corrcoef(x, x[::-1], rowvar=False)) - with catch_warn_mae(): - warnings.simplefilter("ignore") + with suppress_warnings() as sup: + sup.filter(DeprecationWarning, "bias and ddof have no effect") # ddof and bias have no or negligible effect on the function assert_almost_equal(np.corrcoef(nx, nx[::-1]), corrcoef(x, x[::-1], bias=1)) assert_almost_equal(np.corrcoef(nx, nx[::-1]), corrcoef(x, x[::-1], ddof=2)) - def test_2d_w_missing(self): + def test_2d_with_missing(self): # Test corrcoef on 2D variable w/ missing value x = self.data x[-1] = masked @@ -928,8 +922,8 @@ class TestCorrcoef(TestCase): test = corrcoef(x) control = np.corrcoef(x) assert_almost_equal(test[:-1, :-1], control[:-1, :-1]) - with catch_warn_mae(): - warnings.simplefilter("ignore") + with suppress_warnings() as sup: + sup.filter(DeprecationWarning, "bias and ddof have no effect") # ddof and bias have no or negligible effect on the function assert_almost_equal(corrcoef(x, ddof=-2)[:-1, :-1], control[:-1, :-1]) |