def test_basic_circular(self):
"""Test the _calculate_neighbourhood method with a circular neighbourhood."""
expected_array = np.array([
[1.0, 1.0, 1.0, 1.0, 1.0],
[1.0, 1.0, 0.8, 1.0, 1.0],
[1.0, 0.8, 0.8, 0.8, 1.0],
[1.0, 1.0, 0.8, 1.0, 1.0],
[1.0, 1.0, 1.0, 1.0, 1.0],
])
plugin = NeighbourhoodProcessing("circular", self.RADIUS)
plugin.kernel = self.circular_kernel
result = plugin._calculate_neighbourhood(self.data)
self.assertArrayAlmostEqual(result.data, expected_array)
def test_basic_circular_sum(self):
"""Test the _calculate_neighbourhood method calculating a sum in
a circular neighbourhood."""
expected_array = np.array([
[5.0, 5.0, 5.0, 5.0, 5.0],
[5.0, 5.0, 4.0, 5.0, 5.0],
[5.0, 4.0, 4.0, 4.0, 5.0],
[5.0, 5.0, 4.0, 5.0, 5.0],
[5.0, 5.0, 5.0, 5.0, 5.0],
])
plugin = NeighbourhoodProcessing("circular",
self.RADIUS,
sum_only=True)
plugin.kernel = self.circular_kernel
result = plugin._calculate_neighbourhood(self.data)
self.assertArrayAlmostEqual(result.data, expected_array)
def test_masked_array_re_mask_true_circular(self):
"""Test the _calculate_neighbourhood method when masked data is
passed in and re-masking is applied with a circular neighbourhood."""
expected_array = np.array([
[np.nan, 0.5, 0.5, 0.5, 1.0],
[1.0, 1.0, 0.6, 0.5, 0.0],
[np.nan, 1.0, 0.75, 0.4, 0.0],
[np.nan, 1.0, 1.0, 0.5, 0.5],
[np.nan, 1.0, 0.75, 0.5, 0.0],
])
input_data = np.ma.masked_where(self.mask == 0,
self.data_for_masked_tests)
plugin = NeighbourhoodProcessing("circular", self.RADIUS)
plugin.kernel = self.circular_kernel
result = plugin._calculate_neighbourhood(input_data)
self.assertArrayAlmostEqual(result.data, expected_array)
self.assertArrayAlmostEqual(result.mask, self.expected_mask)
