def test_volume_statistics_masked_level(self):
"""
Test to take the volume weighted average of a (2,3,2,2) cube
where the last depth level is fully masked.
"""
self.grid_4d.data[:, -1, :, :] = np.ma.masked_all((2, 2, 2))
result = volume_statistics(self.grid_4d, 'mean')
expected = np.ma.array([1., 1.], mask=False)
self.assert_array_equal(result.data, expected)
def test_volume_statistics_masked_timestep(self):
"""
Test to take the volume weighted average of a (2,3,2,2) cube
where the first timestep is fully masked.
"""
self.grid_4d.data[0, :, :, :] = np.ma.masked_all((3, 2, 2))
result = volume_statistics(self.grid_4d, 'mean')
expected = np.ma.array([1., 1], mask=[True, False])
self.assert_array_equal(result.data, expected)
def test_volume_statistics_long(self):
"""
Test to take the volume weighted average of a (4,3,2,2) cube.
This extra time is needed, as the volume average calculation uses
different methods for small and large cubes.
"""
result = volume_statistics(self.grid_4d_2, 'mean')
expected = np.ma.array([1., 1., 1., 1.], mask=False)
self.assert_array_equal(result.data, expected)
def test_volume_statistics_cell_measure(self):
"""
Test to take the volume weighted average of a (2,3,2,2) cube.
The volume measure is pre-loaded in the cube.
"""
grid_volume = calculate_volume(self.grid_4d)
measure = iris.coords.CellMeasure(grid_volume,
standard_name='ocean_volume',
units='m3',
measure='volume')
self.grid_4d.add_cell_measure(measure, range(0, measure.ndim))
result = volume_statistics(self.grid_4d, 'mean')
expected = np.ma.array([1., 1.], mask=False)
self.assert_array_equal(result.data, expected)
def test_extract_volume_mean(self):
"""
Test to extract the top two layers and compute the
weighted average of a cube."""
grid_volume = calculate_volume(self.grid_4d)
measure = iris.coords.CellMeasure(grid_volume,
standard_name='ocean_volume',
units='m3',
measure='volume')
self.grid_4d.add_cell_measure(measure, range(0, measure.ndim))
result = extract_volume(self.grid_4d, 0., 10.)
expected = np.ma.ones((2, 2, 2, 2))
self.assert_array_equal(result.data, expected)
result_mean = volume_statistics(result, 'mean')
expected_mean = np.ma.array([1., 1.], mask=False)
self.assert_array_equal(result_mean.data, expected_mean)
def test_volume_statistics(self):
"""Test to take the volume weighted average of a (2,3,2,2) cube."""
result = volume_statistics(self.grid_4d, 'mean')
expected = np.ma.array([1., 1.], mask=False)
self.assert_array_equal(result.data, expected)