def test_with_weights(self):
"""Test function when a data cube and a weights cube are provided."""
coord = "forecast_reference_time"
plugin = WeightedBlendAcrossWholeDimension(coord, 'weighted_maximum')
result = plugin.weighted_maximum(self.cube, self.weights1d)
expected = np.full((2, 2), 0.6)
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."""
coord = "forecast_reference_time"
plugin = WeightedBlendAcrossWholeDimension(coord, 'weighted_maximum')
result = plugin.weighted_maximum(self.cube, None)
expected = np.full((2, 2), 1.)
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."""
coord = "forecast_reference_time"
plugin = WeightedBlendAcrossWholeDimension(coord, 'weighted_maximum')
result = plugin.weighted_maximum(self.cube, self.weights3d)
expected = np.array([[2.4, 1.2], [1.8, 0.8]])
self.assertIsInstance(result, iris.cube.Cube)
self.assertArrayAlmostEqual(result.data, expected)
