def test_collapse_dims_with_weights(self):
"""Test function matches when the blend coordinate is first or second."""
coord = "forecast_reference_time"
# Create a new axis.
new_cube = add_coordinate(self.cube, [0.5], "height", coord_units="m")
new_cube = iris.util.new_axis(new_cube, "height")
plugin = WeightedBlendAcrossWholeDimension(coord)
result_blend_coord_second = plugin.weighted_mean(new_cube, self.weights1d)
# Reorder the axis to move the blending coordinate to the front.
order = np.array([1, 0, 2, 3])
new_cube.transpose(order)
result_blend_coord_first = plugin.weighted_mean(new_cube, self.weights1d)
expected = np.full((2, 2), 1.5)
self.assertIsInstance(result_blend_coord_first, iris.cube.Cube)
self.assertIsInstance(result_blend_coord_second, iris.cube.Cube)
self.assertArrayAlmostEqual(
result_blend_coord_first.data, result_blend_coord_second.data
)
self.assertArrayAlmostEqual(result_blend_coord_first.data, expected)
def test_with_weights(self):
"""Test function when a data cube and a weights cube are provided."""
plugin = WeightedBlendAcrossWholeDimension(self.coord)
result = plugin.weighted_mean(self.cube, self.weights1d)
expected = np.full((2, 2), 1.5)
self.assertIsInstance(result, iris.cube.Cube)
self.assertArrayAlmostEqual(result.data, expected)
def test_without_weights(self):
"""Test function when a data cube is provided, but no weights cube
which should result in equal weightings."""
plugin = WeightedBlendAcrossWholeDimension(self.coord)
result = plugin.weighted_mean(self.cube, None)
expected = np.full((2, 2), 2.0)
self.assertIsInstance(result, iris.cube.Cube)
self.assertArrayAlmostEqual(result.data, expected)
def test_with_spatially_varying_weights(self):
"""Test function when a data cube and a multi dimensional weights cube
are provided. This tests spatially varying weights, where each x-y
position is weighted differently in each slice along the blending
coordinate."""
plugin = WeightedBlendAcrossWholeDimension(self.coord)
result = plugin.weighted_mean(self.cube, self.weights3d)
expected = np.array([[2.7, 2.1], [2.4, 1.8]])
self.assertIsInstance(result, iris.cube.Cube)
self.assertArrayAlmostEqual(result.data, expected)
