diff options
Diffstat (limited to 'numpy/lib/tests/test_function_base.py')
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 33 |
1 files changed, 14 insertions, 19 deletions
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index 0d7b11c44..4535c1e7f 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -8,7 +8,7 @@ from numpy.testing import ( run_module_suite, TestCase, assert_, assert_equal, assert_array_equal, assert_almost_equal, assert_array_almost_equal, assert_raises, assert_allclose, assert_array_max_ulp, assert_warns, - assert_raises_regex, dec, clear_and_catch_warnings + assert_raises_regex, dec, suppress_warnings ) from numpy.testing.utils import HAS_REFCOUNT import numpy.lib.function_base as nfb @@ -320,7 +320,11 @@ class TestAverage(TestCase): a = np.array([[1,2],[3,4]]).view(subclass) w = np.array([[1,2],[3,4]]).view(subclass) - assert_equal(type(np.average(a, weights=w)), subclass) + with suppress_warnings() as sup: + # Note that the warning is spurious, because the test checks + # for weights while a is ignored. + sup.filter(FutureWarning, "np.average currently does not preserve") + assert_equal(type(np.average(a, weights=w)), subclass) # also test matrices a = np.matrix([[1,2],[3,4]]) @@ -1457,12 +1461,12 @@ class TestHistogram(TestCase): a, b = histogram([], bins=([0, 1])) assert_array_equal(a, np.array([0])) assert_array_equal(b, np.array([0, 1])) - + def test_error_binnum_type (self): # Tests if right Error is raised if bins argument is float vals = np.linspace(0.0, 1.0, num=100) histogram(vals, 5) - assert_raises(TypeError, histogram, vals, 2.4) + assert_raises(TypeError, histogram, vals, 2.4) def test_finite_range(self): # Normal ranges should be fine @@ -1792,15 +1796,6 @@ class TestCheckFinite(TestCase): assert_(a.dtype == np.float64) -class catch_warn_nfb(clear_and_catch_warnings): - - """ - Context manager to catch, reset warnings in function_base module - - """ - class_modules = (nfb,) - - class TestCorrCoef(TestCase): A = np.array( [[0.15391142, 0.18045767, 0.14197213], @@ -1837,10 +1832,10 @@ class TestCorrCoef(TestCase): def test_ddof(self): # ddof raises DeprecationWarning - with catch_warn_nfb(): + with suppress_warnings() as sup: warnings.simplefilter("always") assert_warns(DeprecationWarning, corrcoef, self.A, ddof=-1) - warnings.simplefilter("ignore") + sup.filter(DeprecationWarning) # ddof has no or negligible effect on the function assert_almost_equal(corrcoef(self.A, ddof=-1), self.res1) assert_almost_equal(corrcoef(self.A, self.B, ddof=-1), self.res2) @@ -1849,11 +1844,11 @@ class TestCorrCoef(TestCase): def test_bias(self): # bias raises DeprecationWarning - with catch_warn_nfb(): + with suppress_warnings() as sup: warnings.simplefilter("always") assert_warns(DeprecationWarning, corrcoef, self.A, self.B, 1, 0) assert_warns(DeprecationWarning, corrcoef, self.A, bias=0) - warnings.simplefilter("ignore") + sup.filter(DeprecationWarning) # bias has no or negligible effect on the function assert_almost_equal(corrcoef(self.A, bias=1), self.res1) @@ -2316,7 +2311,7 @@ class TestInterp(TestCase): assert_almost_equal(np.interp(x0, x, y), x0) x0 = np.nan assert_almost_equal(np.interp(x0, x, y), x0) - + def test_complex_interp(self): # test complex interpolation x = np.linspace(0, 1, 5) @@ -2335,7 +2330,7 @@ class TestInterp(TestCase): x = [-180, -170, -185, 185, -10, -5, 0, 365] xp = [190, -190, 350, -350] fp = [5+1.0j, 10+2j, 3+3j, 4+4j] - y = [7.5+1.5j, 5.+1.0j, 8.75+1.75j, 6.25+1.25j, 3.+3j, 3.25+3.25j, + y = [7.5+1.5j, 5.+1.0j, 8.75+1.75j, 6.25+1.25j, 3.+3j, 3.25+3.25j, 3.5+3.5j, 3.75+3.75j] assert_almost_equal(np.interp(x, xp, fp, period=360), y) |