diff options
Diffstat (limited to 'numpy/ma/tests/test_extras.py')
| -rw-r--r-- | numpy/ma/tests/test_extras.py | 50 |
1 files changed, 26 insertions, 24 deletions
diff --git a/numpy/ma/tests/test_extras.py b/numpy/ma/tests/test_extras.py index ff061d8dd..9fd501aaa 100644 --- a/numpy/ma/tests/test_extras.py +++ b/numpy/ma/tests/test_extras.py @@ -363,18 +363,18 @@ class TestCov(TestCase): def test_1d_wo_missing(self): "Test cov on 1D variable w/o missing values" x = self.data - assert_equal(np.cov(x), cov(x)) - assert_equal(np.cov(x, rowvar=False), cov(x, rowvar=False)) - assert_equal(np.cov(x, rowvar=False, bias=True), - cov(x, rowvar=False, bias=True)) + assert_almost_equal(np.cov(x), cov(x)) + assert_almost_equal(np.cov(x, rowvar=False), cov(x, rowvar=False)) + assert_almost_equal(np.cov(x, rowvar=False, bias=True), + cov(x, rowvar=False, bias=True)) # def test_2d_wo_missing(self): "Test cov on 1 2D variable w/o missing values" x = self.data.reshape(3,4) - assert_equal(np.cov(x), cov(x)) - assert_equal(np.cov(x, rowvar=False), cov(x, rowvar=False)) - assert_equal(np.cov(x, rowvar=False, bias=True), - cov(x, rowvar=False, bias=True)) + assert_almost_equal(np.cov(x), cov(x)) + assert_almost_equal(np.cov(x, rowvar=False), cov(x, rowvar=False)) + assert_almost_equal(np.cov(x, rowvar=False, bias=True), + cov(x, rowvar=False, bias=True)) # def test_1d_w_missing(self): "Test cov 1 1D variable w/missing values" @@ -395,10 +395,10 @@ class TestCov(TestCase): # 2 1D variables w/ missing values nx = x[1:-1] assert_almost_equal(np.cov(nx, nx[::-1]), cov(x, x[::-1])) - assert_equal(np.cov(nx, nx[::-1], rowvar=False), - cov(x, x[::-1], rowvar=False)) - assert_equal(np.cov(nx, nx[::-1], rowvar=False, bias=True), - cov(x, x[::-1], rowvar=False, bias=True)) + assert_almost_equal(np.cov(nx, nx[::-1], rowvar=False), + cov(x, x[::-1], rowvar=False)) + 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): "Test cov on 2D variable w/ missing value" @@ -427,18 +427,20 @@ class TestCorrcoef(TestCase): def test_1d_wo_missing(self): "Test cov on 1D variable w/o missing values" x = self.data - assert_equal(np.corrcoef(x), corrcoef(x)) - assert_equal(np.corrcoef(x, rowvar=False), corrcoef(x, rowvar=False)) - assert_equal(np.corrcoef(x, rowvar=False, bias=True), - corrcoef(x, rowvar=False, bias=True)) + 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)) # def test_2d_wo_missing(self): "Test corrcoef on 1 2D variable w/o missing values" x = self.data.reshape(3,4) - assert_equal(np.corrcoef(x), corrcoef(x)) - assert_equal(np.corrcoef(x, rowvar=False), corrcoef(x, rowvar=False)) - assert_equal(np.corrcoef(x, rowvar=False, bias=True), - corrcoef(x, rowvar=False, bias=True)) + 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)) # def test_1d_w_missing(self): "Test corrcoef 1 1D variable w/missing values" @@ -459,10 +461,10 @@ class TestCorrcoef(TestCase): # 2 1D variables w/ missing values nx = x[1:-1] assert_almost_equal(np.corrcoef(nx, nx[::-1]), corrcoef(x, x[::-1])) - assert_equal(np.corrcoef(nx, nx[::-1], rowvar=False), - corrcoef(x, x[::-1], rowvar=False)) - assert_equal(np.corrcoef(nx, nx[::-1], rowvar=False, bias=True), - corrcoef(x, x[::-1], rowvar=False, bias=True)) + 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)) # def test_2d_w_missing(self): "Test corrcoef on 2D variable w/ missing value" |