def setUp(self):
"""Set up a cube and plugin for testing."""
self.cube = set_up_variable_cube(np.ones((3, 3), dtype=np.float32))
self.plugin = Threshold(latitude_to_threshold)
self.plugin.threshold_coord_name = self.cube.name()
self.thresholds = np.array(
latitude_to_threshold(self.cube.coord("latitude").points,
midlatitude=1.0,
tropics=3.0))
def test_threshold_negative(self):
"""Repeat the test with negative numbers when the threshold is negative."""
expected_result_array = np.zeros_like(self.cube.data)
expected_result_array[2:-2][:] = 1
self.cube.data = 0 - self.cube.data
plugin = Threshold(lambda lat: latitude_to_threshold(
lat, midlatitude=-1e-6, tropics=-1.0))
result = plugin(self.cube)
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_threshold_le(self):
"""Test equal-to values when we are in le threshold mode."""
expected_result_array = np.ones_like(self.cube.data)
plugin = Threshold(
lambda lat: latitude_to_threshold(lat, midlatitude=0.5, tropics=1.0),
comparison_operator="<=",
)
name = "probability_of_{}_below_threshold"
expected_name = name.format(self.cube.name())
expected_attribute = "less_than_or_equal_to"
result = plugin(self.cube)
self.assertEqual(result.name(), expected_name)
self.assertEqual(
result.coord(var_name="threshold").attributes["spp__relative_to_threshold"],
expected_attribute,
)
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_threshold_gt(self):
"""Test equal-to values when we are in > threshold mode."""
expected_result_array = np.ones_like(self.cube.data)
expected_result_array[3][:] = 0
plugin = Threshold(
lambda lat: latitude_to_threshold(lat, midlatitude=1e-6, tropics=0.5),
comparison_operator=">",
)
name = "probability_of_{}_above_threshold"
expected_name = name.format(self.cube.name())
expected_attribute = "greater_than"
result = plugin(self.cube)
self.assertEqual(result.name(), expected_name)
self.assertEqual(
result.coord(var_name="threshold").attributes["spp__relative_to_threshold"],
expected_attribute,
)
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_threshold_unit_conversion(self):
"""Test data are correctly thresholded when the threshold (mm) is given in
units different from that of the input cube (m)."""
expected_result_array = np.ones_like(self.cube.data)
expected_result_array[3][:] = 0
plugin = Threshold(
lambda lat: latitude_to_threshold(lat, midlatitude=1e-3, tropics=500.0),
threshold_units="mm",
)
result = plugin(self.cube)
self.assertArrayAlmostEqual(result.data, expected_result_array)
expected_points = (
plugin.threshold_function(self.cube.coord("latitude").points) / 1000
)
expected_coord = AuxCoord(
np.array(expected_points, dtype=np.float32),
standard_name=self.cube.name(),
var_name="threshold",
units=self.cube.units,
attributes={"spp__relative_to_threshold": "greater_than"},
)
self.assertEqual(result.coord(self.cube.name()), expected_coord)
def setUp(self):
"""Create a cube with a constant non-zero value spanning latitudes from -60 to +60."""
attributes = {"title": "UKV Model Forecast"}
data = np.full((7, 3), fill_value=0.5, dtype=np.float32)
self.cube = set_up_variable_cube(
data,
name="precipitation_amount",
units="m",
attributes=attributes,
standard_grid_metadata="uk_det",
domain_corner=(-60, 0),
grid_spacing=20,
)
self.masked_cube = self.cube.copy()
data = np.copy(self.cube.data)
mask = np.zeros_like(data)
data[0][0] = -32768.0
mask[0][0] = 1
self.masked_cube.data = np.ma.MaskedArray(data, mask=mask)
self.plugin = Threshold(lambda lat: latitude_to_threshold(
lat, midlatitude=1e-6, tropics=1.0))
