def test_realization_for_greater_than_check_data(self):
"""
Test to check the behaviour whether the number of percentiles is
greater than the number of realizations. For when the length of the
percentiles is greater than the length of the realizations, check
that the points of the realization coordinate is as expected.
"""
data = np.array([[[[4., 4.625, 5.25],
[5.875, 6.5, 7.125],
[7.75, 8.375, 9.]],
[[6., 6.625, 7.25],
[7.875, 8.5, 9.125],
[9.75, 10.375, 11.]],
[[4., 4.625, 5.25],
[5.875, 6.5, 7.125],
[7.75, 8.375, 9.]]]])
post_processed_forecast_percentiles = self.percentile_cube
raw_forecast_realizations = self.realization_cube
# Slice number of raw forecast realizations, so that there are fewer
# realizations than percentiles.
raw_forecast_realizations = raw_forecast_realizations[:2, :, :, :]
plu = Plugin()
result = plu._recycle_raw_ensemble_realizations(
post_processed_forecast_percentiles, raw_forecast_realizations,
self.perc_coord)
self.assertArrayAlmostEqual(data, result.data)
def test_realization_for_equal_check_data(self):
"""
Test to check the behaviour whether the number of percentiles equals
the number of realizations. For when the length of the percentiles
equals the length of the realizations, check that the points of the
realization coordinate is as expected.
"""
data = [0, 1, 2]
data = np.array([[[[4., 4.625, 5.25],
[5.875, 6.5, 7.125],
[7.75, 8.375, 9.]]],
[[[6., 6.625, 7.25],
[7.875, 8.5, 9.125],
[9.75, 10.375, 11.]]],
[[[8., 8.625, 9.25],
[9.875, 10.5, 11.125],
[11.75, 12.375, 13.]]]])
post_processed_forecast_percentiles = self.percentile_cube
raw_forecast_realizations = self.realization_cube
plu = Plugin()
result = plu._recycle_raw_ensemble_realizations(
post_processed_forecast_percentiles, raw_forecast_realizations,
self.perc_coord)
self.assertArrayAlmostEqual(data, result.data)
def test_realization_for_greater_than_check_data_many_realizations(self):
"""
Test to check the behaviour whether the number of percentiles is
greater than the number of realizations. For when the length of the
percentiles is greater than the length of the realizations, check
that the points of the realization coordinate is as expected.
"""
data = np.tile(np.linspace(5, 10, 9), 9).reshape(9, 1, 3, 3)
data[0] -= 1
data[1] += 1
data[2] += 3
cube = set_up_cube(
data, "air_temperature", "degreesC",
realizations=np.arange(0, 9))
self.realization_cube = (
add_forecast_reference_time_and_forecast_period(cube.copy()))
cube.coord("realization").rename(self.perc_coord)
self.percentile_cube = (
add_forecast_reference_time_and_forecast_period(cube))
expected = np.array([[[[4., 4.625, 5.25],
[5.875, 6.5, 7.125],
[7.75, 8.375, 9.]],
[[6., 6.625, 7.25],
[7.875, 8.5, 9.125],
[9.75, 10.375, 11.]],
[[4., 4.625, 5.25],
[5.875, 6.5, 7.125],
[7.75, 8.375, 9.]],
[[6., 6.625, 7.25],
[7.875, 8.5, 9.125],
[9.75, 10.375, 11.]],
[[4., 4.625, 5.25],
[5.875, 6.5, 7.125],
[7.75, 8.375, 9.]],
[[6., 6.625, 7.25],
[7.875, 8.5, 9.125],
[9.75, 10.375, 11.]],
[[4., 4.625, 5.25],
[5.875, 6.5, 7.125],
[7.75, 8.375, 9.]],
[[6., 6.625, 7.25],
[7.875, 8.5, 9.125],
[9.75, 10.375, 11.]],
[[4., 4.625, 5.25],
[5.875, 6.5, 7.125],
[7.75, 8.375, 9.]]]])
post_processed_forecast_percentiles = self.percentile_cube
raw_forecast_realizations = self.realization_cube
raw_forecast_realizations = raw_forecast_realizations[:2, :, :, :]
plu = Plugin()
result = plu._recycle_raw_ensemble_realizations(
post_processed_forecast_percentiles, raw_forecast_realizations,
self.perc_coord)
self.assertArrayAlmostEqual(expected, result.data)
def test_realization_for_equal(self):
"""
Test to check the behaviour whether the number of percentiles equals
the number of realizations. For when the length of the percentiles
equals the length of the realizations, check that the points of the
realization coordinate is as expected.
"""
data = [0, 1, 2]
post_processed_forecast_percentiles = self.percentile_cube
raw_forecast_realizations = self.realization_cube
plu = Plugin()
result = plu._recycle_raw_ensemble_realizations(
post_processed_forecast_percentiles, raw_forecast_realizations,
self.perc_coord)
self.assertIsInstance(result, Cube)
self.assertArrayAlmostEqual(data, result.coord("realization").points)
