def test_vicinity_names(self):
"""Test plugin names the cube and threshold coordinate correctly for a
vicinity diagnostic"""
input = "lwe_thickness_of_precipitation_amount_in_vicinity"
output = "thickness_of_rainfall_amount_in_vicinity"
self.cube.rename(f"probability_of_{input}_above_threshold")
cubelist = iris.cube.CubeList([self.cube.copy(), self.multiplier])
result = CubeMultiplier(broadcast_to_threshold=True)(cubelist, output)
self.assertEqual(result.name(),
f"probability_of_{output}_above_threshold")
self.assertEqual(
result.coord(var_name="threshold").name(),
"thickness_of_rainfall_amount")
def test_vicinity_names(self):
"""Test plugin names the cube and threshold coordinate correctly for a
vicinity diagnostic"""
input = "lwe_thickness_of_precipitation_amount_in_vicinity"
output = "thickness_of_rainfall_amount_in_vicinity"
self.cube4.rename(f"probability_of_{input}_above_threshold")
cube = self.cube4[:, 0, ...].copy()
cube.data = np.ones_like(cube.data)
cube.remove_coord("lwe_thickness_of_precipitation_amount")
cubelist = iris.cube.CubeList([self.cube4.copy(), cube])
input_copy = deepcopy(cubelist)
result = CubeMultiplier()(cubelist, output, broadcast_to_threshold=True)
self.assertEqual(result.name(), f"probability_of_{output}_above_threshold")
self.assertEqual(
result.coord(var_name="threshold").name(), "thickness_of_rainfall_amount"
)
def test_broadcast_coord(self):
"""Test that plugin broadcasts to threshold coord without changing inputs.
Using the broadcast_to_coords argument including a value of "threshold"
will result in the returned cube maintaining the probabilistic elements
of the name of the first input cube."""
cubelist = iris.cube.CubeList([self.cube.copy(), self.multiplier])
input_copy = deepcopy(cubelist)
result = CubeMultiplier(broadcast_to_threshold=True)(cubelist,
"new_cube_name")
self.assertIsInstance(result, Cube)
self.assertEqual(result.name(),
"probability_of_new_cube_name_above_threshold")
self.assertEqual(
result.coord(var_name="threshold").name(), "new_cube_name")
self.assertArrayAlmostEqual(result.data, self.cube.data)
self.assertCubeListEqual(input_copy, cubelist)
def test_broadcast_coord(self):
"""Test that plugin broadcasts to threshold coord without changing inputs.
Using the broadcast_to_coords argument including a value of "threshold"
will result in the returned cube maintaining the probabilistic elements
of the name of the first input cube."""
cube = self.cube4[:, 0, ...].copy()
cube.data = np.ones_like(cube.data)
cube.remove_coord("lwe_thickness_of_precipitation_amount")
cubelist = iris.cube.CubeList([self.cube4.copy(), cube])
input_copy = deepcopy(cubelist)
result = CubeMultiplier()(
cubelist, "new_cube_name", broadcast_to_threshold=True
)
self.assertIsInstance(result, Cube)
self.assertEqual(result.name(), "probability_of_new_cube_name_above_threshold")
self.assertEqual(result.coord(var_name="threshold").name(), "new_cube_name")
self.assertArrayAlmostEqual(result.data, self.cube4.data)
self.assertCubeListEqual(input_copy, cubelist)