def test_not_equal_areas(self):
"""
Check it raises an error when the input is not an equal areas grid.
"""
self.cube.remove_coord("projection_x_coordinate")
self.cube.add_dim_coord(
DimCoord(np.linspace(200.0, 600.0, 3),
'projection_x_coordinate',
units='m'), 0)
with self.assertRaisesRegex(
ValueError, "The size of the intervals along the x and y axis"
" should be equal."):
convert_number_of_grid_cells_into_distance(self.cube, 2)
def test_check_different_input_radius(self):
"""Check it works for different input values."""
result_radius = convert_number_of_grid_cells_into_distance(
self.cube, 5)
expected_result = 10000.0
self.assertAlmostEqual(result_radius, expected_result)
self.assertIs(type(expected_result), float)
def test_basic(self):
"""Test the function does what it's meant to in a simple case."""
result_radius = convert_number_of_grid_cells_into_distance(
self.cube, 2)
expected_result = 4000.0
self.assertAlmostEqual(result_radius, expected_result)
self.assertIs(type(expected_result), float)
def _generate_mask(self):
"""
Generates a boolean mask of areas NOT to calculate orographic
enhancement. Criteria for calculating orographic enhancement are that
all of the following are true:
- 3x3 mean topography height >= threshold (20 m)
- Relative humidity (fraction) >= threshold (0.8)
- v dot grad z (wind x topography gradient) >= threshold (0.0005)
The mask is therefore "True" if any of these conditions are false.
Returns:
mask (numpy.ndarray):
Boolean mask - where True, set orographic enhancement to a
default zero value
"""
# calculate mean 3x3 (square nbhood) orography heights
radius = convert_number_of_grid_cells_into_distance(self.topography, 1)
topo_nbhood = NeighbourhoodProcessing('square',
radius).process(self.topography)
topo_nbhood.convert_units('m')
# create mask
mask = np.full(topo_nbhood.shape, False, dtype=bool)
mask = np.where(topo_nbhood.data < self.orog_thresh_m, True, mask)
mask = np.where(self.humidity.data < self.rh_thresh_ratio, True, mask)
mask = np.where(abs(self.vgradz) < self.vgradz_thresh_ms, True, mask)
return mask
def test_check_input_in_km(self):
"""
Test that the output is still in metres when the input coordinates
are in a different unit.
"""
result_radius = convert_number_of_grid_cells_into_distance(
self.cube, 2)
for coord in self.cube.coords():
coord.convert_units("km")
expected_result = 4000.0
self.assertAlmostEqual(result_radius, expected_result)
self.assertIs(type(expected_result), float)
def find_max_in_nbhood_orography(self, orography_cube):
"""
Find the maximum value of the orography in the region around each grid
point in your orography field by finding the maximum in a neighbourhood
around that point.
Args:
orography_cube (iris.cube.Cube):
The cube containing a single 2 dimensional array of orography
data
Returns:
iris.cube.Cube:
The cube containing the maximum in a neighbourhood of the
orography data.
"""
radius_in_metres = convert_number_of_grid_cells_into_distance(
orography_cube, self.grid_point_radius)
max_in_nbhood_orog = OccurrenceWithinVicinity(
radius_in_metres).process(orography_cube)
return max_in_nbhood_orog
