diff options
Diffstat (limited to 'numpy/ma/tests/test_extras.py')
| -rw-r--r-- | numpy/ma/tests/test_extras.py | 82 |
1 files changed, 68 insertions, 14 deletions
diff --git a/numpy/ma/tests/test_extras.py b/numpy/ma/tests/test_extras.py index 9e1e8ba38..ee8e6bc18 100644 --- a/numpy/ma/tests/test_extras.py +++ b/numpy/ma/tests/test_extras.py @@ -14,12 +14,16 @@ __version__ = '1.0' __revision__ = "$Revision: 3473 $" __date__ = '$Date: 2007-10-29 17:18:13 +0200 (Mon, 29 Oct 2007) $' +import warnings + import numpy as np -from numpy.testing import TestCase, run_module_suite +from numpy.testing import (TestCase, run_module_suite, assert_warns, + assert_raises, clear_and_catch_warnings) from numpy.ma.testutils import (rand, assert_, assert_array_equal, assert_equal, assert_almost_equal) from numpy.ma.core import (array, arange, masked, MaskedArray, masked_array, getmaskarray, shape, nomask, ones, zeros, count) +import numpy.ma.extras as mae from numpy.ma.extras import ( atleast_2d, mr_, dot, polyfit, cov, corrcoef, median, average, @@ -629,15 +633,46 @@ 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): self.data = array(np.random.rand(12)) + self.data2 = array(np.random.rand(12)) def test_ddof(self): - # Test ddof keyword - x = self.data - assert_almost_equal(np.corrcoef(x, ddof=0), corrcoef(x, ddof=0)) + # ddof raises DeprecationWarning + x, y = self.data, self.data2 + expected = np.corrcoef(x) + expected2 = np.corrcoef(x, y) + with catch_warn_mae(): + warnings.simplefilter("always") + assert_warns(DeprecationWarning, corrcoef, x, ddof=-1) + warnings.simplefilter("ignore") + # 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) + assert_almost_equal(corrcoef(x, y, ddof=-1), expected2) + assert_almost_equal(corrcoef(x, ddof=3), expected) + assert_almost_equal(corrcoef(x, y, ddof=3), expected2) + + def test_bias(self): + x, y = self.data, self.data2 + expected = np.corrcoef(x) + # bias raises DeprecationWarning + with catch_warn_mae(): + 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") + # bias has no or negligible effect on the function + assert_almost_equal(corrcoef(x, bias=1), expected) def test_1d_wo_missing(self): # Test cov on 1D variable w/o missing values @@ -645,8 +680,10 @@ class TestCorrcoef(TestCase): assert_almost_equal(np.corrcoef(x), corrcoef(x)) assert_almost_equal(np.corrcoef(x, rowvar=False), corrcoef(x, rowvar=False)) - assert_almost_equal(np.corrcoef(x, rowvar=False, bias=True), - corrcoef(x, rowvar=False, bias=True)) + with catch_warn_mae(): + warnings.simplefilter("ignore") + assert_almost_equal(np.corrcoef(x, rowvar=False, bias=True), + corrcoef(x, rowvar=False, bias=True)) def test_2d_wo_missing(self): # Test corrcoef on 1 2D variable w/o missing values @@ -654,8 +691,10 @@ class TestCorrcoef(TestCase): assert_almost_equal(np.corrcoef(x), corrcoef(x)) assert_almost_equal(np.corrcoef(x, rowvar=False), corrcoef(x, rowvar=False)) - assert_almost_equal(np.corrcoef(x, rowvar=False, bias=True), - corrcoef(x, rowvar=False, bias=True)) + with catch_warn_mae(): + warnings.simplefilter("ignore") + assert_almost_equal(np.corrcoef(x, rowvar=False, bias=True), + corrcoef(x, rowvar=False, bias=True)) def test_1d_w_missing(self): # Test corrcoef 1 1D variable w/missing values @@ -666,21 +705,26 @@ class TestCorrcoef(TestCase): assert_almost_equal(np.corrcoef(nx), corrcoef(x)) assert_almost_equal(np.corrcoef(nx, rowvar=False), corrcoef(x, rowvar=False)) - assert_almost_equal(np.corrcoef(nx, rowvar=False, bias=True), - corrcoef(x, rowvar=False, bias=True)) - # + with catch_warn_mae(): + warnings.simplefilter("ignore") + assert_almost_equal(np.corrcoef(nx, rowvar=False, bias=True), + corrcoef(x, rowvar=False, bias=True)) try: corrcoef(x, allow_masked=False) except ValueError: pass - # # 2 1D variables w/ missing values nx = x[1:-1] 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)) - assert_almost_equal(np.corrcoef(nx, nx[::-1], rowvar=False, bias=True), - corrcoef(x, x[::-1], rowvar=False, bias=True)) + with catch_warn_mae(): + warnings.simplefilter("ignore") + # 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): # Test corrcoef on 2D variable w/ missing value @@ -691,6 +735,15 @@ 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") + # ddof and bias have no or negligible effect on the function + assert_almost_equal(corrcoef(x, ddof=-2)[:-1, :-1], + control[:-1, :-1]) + assert_almost_equal(corrcoef(x, ddof=3)[:-1, :-1], + control[:-1, :-1]) + assert_almost_equal(corrcoef(x, bias=1)[:-1, :-1], + control[:-1, :-1]) class TestPolynomial(TestCase): @@ -750,6 +803,7 @@ class TestPolynomial(TestCase): for (a, a_) in zip((C, R, K, S, D), (c, r, k, s, d)): assert_almost_equal(a, a_) + class TestArraySetOps(TestCase): def test_unique_onlist(self): |