def test_extract_region_irregular(irregular_extract_region_cube, case):
"""Test `extract_region` with data on an irregular grid."""
start_lon, end_lon, start_lat, end_lat = case['region']
if 'raises' not in case:
cube = extract_region(
irregular_extract_region_cube,
start_longitude=start_lon,
end_longitude=end_lon,
start_latitude=start_lat,
end_latitude=end_lat,
)
data = np.arange(9, dtype=np.float32).reshape((3, 3))
np.testing.assert_array_equal(cube.data.mask, case['mask'])
np.testing.assert_array_equal(cube.data.data, data)
else:
with pytest.raises(ValueError) as exc:
extract_region(
irregular_extract_region_cube,
start_longitude=start_lon,
end_longitude=end_lon,
start_latitude=start_lat,
end_latitude=end_lat,
)
assert exc.value == case['raises']
def test_extract_region_mean(self):
"""
Test for extracting a region and performing
the area mean of a 2D field.
"""
cube = guess_bounds(self.grid, ['longitude', 'latitude'])
grid_areas = iris.analysis.cartography.area_weights(cube)
measure = iris.coords.CellMeasure(
grid_areas,
standard_name='cell_area',
units='m2',
measure='area')
self.grid.add_cell_measure(measure, range(0, measure.ndim))
region = extract_region(self.grid, 1.5, 2.5, 1.5, 2.5)
# expected outcome
expected = np.ones((2, 2))
self.assert_array_equal(region.data, expected)
result = area_statistics(region, 'mean')
expected_mean = np.array([1.])
self.assert_array_equal(result.data, expected_mean)
def test_extract_region_neg_lon(self):
"""Test for extracting a region with a negative longitude field."""
result = extract_region(self.negative_grid, -0.5, 0.5, -0.5, 0.5)
expected = np.ones((2, 2))
self.assert_array_equal(result.data, expected)
def test_extract_region(self):
"""Test for extracting a region from a 2D field."""
result = extract_region(self.grid, 1.5, 2.5, 1.5, 2.5)
# expected outcome
expected = np.ones((2, 2))
self.assert_array_equal(result.data, expected)