def test_rolling_window_exception_too_many_dims(array_size_5):
"""Test an exception is raised if shape has too many dimensions."""
msg = ("Number of dimensions of the input array must be greater than or "
"equal to the length of the neighbourhood shape used for "
"constructing rolling window neighbourhoods.")
with pytest.raises(ValueError) as exc_info:
rolling_window(array_size_5, (2, 2, 2))
assert msg in str(exc_info.value)
def test_rolling_window_writable(array_size_5):
"""Test that result is writable if and only if `writable` is True."""
windows = rolling_window(array_size_5, (2, 2))
msg = "assignment destination is read-only"
with pytest.raises(ValueError) as exc_info:
windows[0, 0, 0, 0] = -1
assert msg in str(exc_info.value)
windows = rolling_window(array_size_5, (2, 2), writeable=True)
windows[0, 0, 0, 0] = -1
assert windows[0, 0, 0, 0] == -1
def test_rolling_window_exception_dims_too_large(array_size_5):
"""Test an exception is raised if dimensions of shape are larger than
corresponding dimensions of input array."""
msg = ("The calculated shape of the output array view contains a "
"dimension that is negative or zero. Each dimension of the "
"neighbourhood shape must be less than or equal to the "
"corresponding dimension of the input array.")
with pytest.raises(RuntimeError) as exc_info:
rolling_window(array_size_5, (2, 6))
assert msg in str(exc_info.value)
def test_rolling_window_neighbourhood_size_2(array_size_5):
"""Test producing a 2 * 2 neighbourhood."""
windows = rolling_window(array_size_5, (2, 2))
expected = np.zeros((4, 4, 2, 2), dtype=np.int32)
for i in range(4):
for j in range(4):
expected[i, j] = array_size_5[i:i + 2, j:j + 2]
np.testing.assert_array_equal(windows, expected)
def test_padding_neighbourhood_size_2(array_size_5):
"""Test that result is same as result of rolling_window with a border of zeros."""
padded = pad_and_roll(array_size_5, (2, 2), mode="constant")
window = rolling_window(array_size_5, (2, 2))
inner_part = padded[1:-1, 1:-1, ::]
np.testing.assert_array_equal(inner_part, window)
border_index = ([[0, i, 0, j] for i in range(5) for j in [0, 1]] +
[[5, i, 1, j] for i in range(5)
for j in [0, 1]] + [[i, 0, j, 0] for i in range(5)
for j in [0, 1]] + [[i, 5, j, 1]
for i in range(5)
for j in [0, 1]])
outer_part = padded[list(zip(*border_index))]
np.testing.assert_array_equal(outer_part, np.zeros(40, dtype=np.int32))
