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_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):
array = MaskValueArray(np.arange(3), 2)
assert_array_equal(array.ndarray(), np.array([0, 1, 2]))
def test_nd_array(self):
orig = np.arange(24)
array = MaskValueArray(orig, 3)
self.assertIs(array.array, orig)