def test_defaults(self):
"""Test default arguments produce cube with expected dimensions
and metadata"""
result = set_up_percentile_cube(self.data, self.percentiles)
perc_coord = result.coord("percentile_over_realization")
self.assertArrayEqual(perc_coord.points, self.percentiles)
self.assertEqual(perc_coord.units, "%")
def test_percentile_coord_name(self):
"""Test ability to set a different name"""
result = set_up_percentile_cube(self.data,
self.percentiles,
percentile_dim_name="percentile")
dim_coords = [coord.name() for coord in result.coords(dim_coords=True)]
self.assertIn("percentile", dim_coords)
def test_error_non_probability_cube(self):
"""Test failure if cube doesn't contain probabilities"""
perc_cube = set_up_percentile_cube(
np.ones((3, 3, 3), dtype=np.float32),
np.array((25, 50, 75), dtype=np.float32))
plugin = OccurrenceBetweenThresholds([[25, 50]], 'K')
msg = 'Input is not a probability cube'
with self.assertRaisesRegex(ValueError, msg):
plugin.process(perc_cube)
def test_standard_grid_metadata(self):
"""Test standard grid metadata"""
result = set_up_percentile_cube(self.data, self.percentiles,
standard_grid_metadata='uk_ens')
self.assertEqual(result.attributes['mosg__grid_type'], 'standard')
self.assertEqual(result.attributes['mosg__grid_version'], '1.3.0')
self.assertEqual(
result.attributes['mosg__grid_domain'], 'uk_extended')
self.assertEqual(
result.attributes['mosg__model_configuration'], 'uk_ens')
def test_ordering_for_percentile_coordinate(self):
"""Test that the cube has been reordered, if it is originally in an
undesirable order and the cube contains a "percentile" coordinate."""
data = np.ones((3, 4, 5), dtype=np.float32)
cube = set_up_percentile_cube(data, np.array([10, 50, 90]))
cube.transpose([2, 1, 0])
save_netcdf(cube, self.filepath)
result = load_cube(self.filepath)
self.assertEqual(result.coord_dims("percentile")[0], 0)
self.assertArrayAlmostEqual(result.coord_dims("latitude")[0], 1)
self.assertArrayAlmostEqual(result.coord_dims("longitude")[0], 2)
def setUp(self):
"""Set up some conformant cubes of air_temperature to test"""
data = 275 * np.ones((3, 3), dtype=np.float32)
self.data_cube = set_up_variable_cube(data, spatial_grid='equalarea')
data = np.ones((3, 3, 3), dtype=np.float32)
thresholds = np.array([272, 273, 274], dtype=np.float32)
self.probability_cube = set_up_probability_cube(data, thresholds)
data = np.array([
274 * np.ones((3, 3), dtype=np.float32), 275 * np.ones(
(3, 3), dtype=np.float32), 276 * np.ones(
(3, 3), dtype=np.float32)
])
percentiles = np.array([25, 50, 75], np.float32)
self.percentile_cube = set_up_percentile_cube(data, percentiles)
def setUp(self):
"""Set up some conformant cubes of air_temperature to test"""
data = 275 * np.ones((3, 3), dtype=np.float32)
self.data_cube = set_up_variable_cube(data, spatial_grid='equalarea')
data = np.ones((3, 3, 3), dtype=np.float32)
thresholds = np.array([272, 273, 274], dtype=np.float32)
self.probability_cube = set_up_probability_cube(data, thresholds)
data = np.array([
274 * np.ones((3, 3), dtype=np.float32), 275 * np.ones(
(3, 3), dtype=np.float32), 276 * np.ones(
(3, 3), dtype=np.float32)
])
percentiles = np.array([25, 50, 75], np.float32)
self.percentile_cube = set_up_percentile_cube(data, percentiles)
# set to real source here, to test consistency of setup functions
# with up-to-date metadata standard
cube_units.DEFAULT_UNITS = improver.units.DEFAULT_UNITS
