def test_masked_array(self): """ Test to make sure that if the original array is masked, its mask is applied by MaskValueArray.masked_array() """ orig = np.ma.MaskedArray(np.arange(3), [True, False, False]) array = MaskValueArray(orig, 2) expected = np.ma.MaskedArray([0, 1, 2], [True, False, True]) self.assertIsInstance(array.masked_array(), np.ma.MaskedArray) assert_array_equal(array.masked_array(), expected)
def test_basic(self): array = MaskValueArray(np.arange(3), 2) expected = np.ma.MaskedArray([0, 1, 2], [False, False, True]) self.assertIsInstance(array.masked_array(), np.ma.MaskedArray) assert_array_equal(array.masked_array(), expected)
def test_nd_array(self): array = MaskValueArray(np.arange(3), 2) assert_array_equal(array.ndarray(), np.array([0, 1, 2]))
def test_mask_preserved(self): sliced = MaskValueArray(np.arange(5), 3)[2:] expected = np.ma.MaskedArray([2, 3, 4], [False, True, False]) assert_array_equal(sliced.masked_array(), expected)
def test_nd_array(self): orig = np.arange(24) array = MaskValueArray(orig, 3) self.assertIs(array.array, orig)