def test_3D_weights_3D_cube_percentile_weighted_mean(self):
"""Test a 3D cube of weights results in a 3D array of weights of the
same shape as the data cube. In this case the cube is a percentile
cube and so has an additional dimension that must be accounted for."""
plugin = WeightedBlendAcrossWholeDimension(self.coord)
perc_coord = self.perc_cube.coord("percentile")
(coord_dim, ) = self.perc_cube.coord_dims(self.coord)
(perc_dim, ) = self.perc_cube.coord_dims(perc_coord)
expected = np.empty_like(self.perc_cube.data)
expected = np.moveaxis(expected, [coord_dim, perc_dim], [0, 1])
result = plugin.percentile_weights(self.perc_cube, self.weights3d,
perc_coord)
self.assertEqual(expected.shape, result.shape)
self.assertArrayEqual(self.weights3d.data, result[:, 0, :, :])
def test_1D_weights_3D_cube_percentile_weighted_mean(self):
"""Test a 1D cube of weights results in a 3D array of weights of an
appropriate shape for a percentile cube. In this case the collapse
coordinate is moved to the leading position and the percentile
coordinate is second."""
plugin = WeightedBlendAcrossWholeDimension(self.coord)
perc_coord = self.perc_cube.coord("percentile")
(coord_dim, ) = self.perc_cube.coord_dims(self.coord)
(perc_dim, ) = self.perc_cube.coord_dims(perc_coord)
expected = np.empty_like(self.perc_cube.data)
expected = np.moveaxis(expected, [coord_dim, perc_dim], [0, 1])
result = plugin.percentile_weights(self.perc_cube, self.weights1d,
perc_coord)
self.assertEqual(expected.shape, result.shape)
self.assertArrayEqual(self.weights1d.data, result[:, 0, 0, 0])
def test_no_weights_cube_provided(self):
"""Test that if a weights cube is not provided, the function generates
a weights array that will equally weight all fields along the blending
coordinate."""
plugin = WeightedBlendAcrossWholeDimension(self.coord)
perc_coord = self.perc_cube.coord("percentile")
(coord_dim, ) = self.perc_cube.coord_dims(self.coord)
(perc_dim, ) = self.perc_cube.coord_dims(perc_coord)
(blending_coord_length, ) = self.perc_cube.coord(self.coord).shape
expected = np.empty_like(self.perc_cube.data)
expected = np.moveaxis(expected, [coord_dim, perc_dim], [0, 1])
expected = np.full_like(expected, 1.0 / blending_coord_length)
result = plugin.percentile_weights(self.perc_cube, None, perc_coord)
self.assertEqual(expected.shape, result.shape)
self.assertArrayEqual(expected, result)
def test_no_weights_cube_provided(self):
"""Test that if a weights cube is not provided, the function generates
a weights array that will equally weight all fields along the blending
coordinate."""
perc_cube = percentile_cube()
coord = "forecast_reference_time"
plugin = WeightedBlendAcrossWholeDimension(coord, 'weighted_mean')
perc_coord = perc_cube.coord('percentile_over_realization')
coord_dim, = perc_cube.coord_dims(coord)
perc_dim, = perc_cube.coord_dims(perc_coord)
blending_coord_length, = perc_cube.coord(coord).shape
expected = np.empty_like(perc_cube.data)
expected = np.moveaxis(expected, [coord_dim, perc_dim], [0, 1])
expected = np.full_like(expected, 1. / blending_coord_length)
result = plugin.percentile_weights(perc_cube, None, perc_coord)
self.assertEqual(expected.shape, result.shape)
self.assertArrayEqual(expected, result)
