def test_global_sum(self):
cdo_sum = cdo_dict['gridarea']['cell_area'].values.sum()
for key, data in data_dict.items():
if key != 'ds_strange':
if key == 'ds_renamed':
area_sum = climapy.xr_area(data_dict[key], lon_name='longitude',
lat_name='latitude').values.sum()
else:
area_sum = climapy.xr_area(data_dict[key]).values.sum()
rel_diff = (area_sum - cdo_sum) / cdo_sum # relative difference
if key in ['ds_irr_lon', 'ds_irr_lat',
'ds_irr_both']: # more leeway allowed for irregular coords
assert abs(rel_diff) < 1e-3, AssertionError(key)
else:
assert abs(rel_diff) < 1e-6, AssertionError(key)
def test_non_monotonic(self):
with pytest.raises(ValueError):
climapy.xr_area(data_dict['ds_strange'])
def test_area_values(self):
cdo_values = cdo_dict['gridarea']['cell_area'].values
area_values = climapy.xr_area(data_dict['data01']).values
rel_diff = (area_values - cdo_values) / cdo_values # relative difference
assert np.abs(rel_diff).max() < 1e-3 # check that diffs are small
def test_incorrect_lat_name(self):
with pytest.raises(KeyError):
climapy.xr_area(data_dict['ds_renamed'])
with pytest.raises(KeyError):
climapy.xr_area(data_dict['data01'], lat_name='latitude')