def test_make_mask_mult_rect(data_for_reg_calcs):
mask_bounds = (region_land_mask.mask_bounds[0], [0, 360, -20, -5])
region = Region(name='mult_rect', mask_bounds=mask_bounds)
result = region._make_mask(data_for_reg_calcs)
expected_values = [[True, True],
[True, False],
[True, False],
[True, False]]
expected = xr.DataArray(expected_values, dims=[LAT_STR, LON_STR],
coords={LAT_STR: data_for_reg_calcs[LAT_STR],
LON_STR: data_for_reg_calcs[LON_STR]})
xr.testing.assert_equal(result.transpose(), expected)
def test_make_mask_mult_rect(data_for_reg_calcs):
mask_bounds = (region_land_mask.mask_bounds[0], [0, 360, -20, -5])
region = Region(name='mult_rect', mask_bounds=mask_bounds)
result = region._make_mask(data_for_reg_calcs)
expected_values = [[True, True], [True, False], [True, False],
[True, False]]
expected = xr.DataArray(expected_values,
dims=[LAT_STR, LON_STR],
coords={
LAT_STR: data_for_reg_calcs[LAT_STR],
LON_STR: data_for_reg_calcs[LON_STR]
})
xr.testing.assert_equal(result.transpose(), expected)
def test_region_init_mult_rect():
bounds_in = [[1, 2, 3, 4], (-12, -30, 2.3, 9)]
region = Region(name='test', mask_bounds=bounds_in)
assert isinstance(region.mask_bounds, tuple)
assert len(region.mask_bounds) == 2
for (w, e, s, n), bounds in zip(bounds_in, region.mask_bounds):
assert isinstance(bounds, tuple)
assert np.all(bounds == (Longitude(w), Longitude(e), s, n))
def test_region_init():
region = Region(name='test',
description='region description',
west_bound=0.,
east_bound=5,
south_bound=0,
north_bound=90.,
do_land_mask=True)
assert region.name == 'test'
assert region.description == 'region description'
assert isinstance(region.mask_bounds, tuple)
assert len(region.mask_bounds) == 1
assert isinstance(region.mask_bounds[0], BoundsRect)
assert np.all(region.mask_bounds[0] == (Longitude(0.), Longitude(5), 0,
90.))
assert region.do_land_mask is True
sfc_area = xr.DataArray(sfc_area, dims=[LAT_STR], coords=[lat])
land_mask = xr.DataArray(land_mask, dims=[LAT_STR], coords=[lat])
sfc_area, _ = xr.broadcast(sfc_area, lon)
land_mask, _ = xr.broadcast(land_mask, lon)
da = xr.DataArray([[2., 2.], [np.nan, 5.], [3., 3.], [4., 4.]],
coords=[lat, lon])
da[SFC_AREA_STR] = sfc_area
da[LAND_MASK_STR] = land_mask
return da
region_no_land_mask = Region(name='test',
description='Test region with no land mask',
lat_bounds=(0., 90.),
lon_bounds=(0., 5.),
do_land_mask=False)
region_land_mask = Region(name='test',
description='Test region with no land mask',
lat_bounds=(0., 90.),
lon_bounds=(0., 5.),
do_land_mask=True)
@pytest.mark.parametrize('region', [region_no_land_mask, region_land_mask],
ids=['no-land-mask', 'land-mask'])
def test_mask_var(data_for_reg_calcs, region):
# Test region masks first row and second column
# of test data. Note that first element of
def_time=True,
func=total_precip,
variables=(precip_largescale, precip_convective),
)
precip_conv_frac = Var(
name='precip_conv_frac',
def_time=True,
func=conv_precip_frac,
variables=(precip_largescale, precip_convective),
)
globe = Region(name='globe',
description='Entire globe',
west_bound=0,
east_bound=360,
south_bound=-90,
north_bound=90,
do_land_mask=False)
tropics = Region(name='tropics',
description='Tropics, defined as 30S-30N',
west_bound=0,
east_bound=360,
south_bound=-30,
north_bound=30,
do_land_mask=False)
example_proj = Proj('example_proj',
direc_out='example-output',
tar_direc_out='example-tar-output',
def test_region_init_bad_bounds():
with pytest.raises(ValueError):
Region(mask_bounds=[(1, 2, 3)])
Region(mask_bounds=[(1, 2, 3, 4), (1, 2, 3)])
LON_STR: 'LONS',
LAT_STR: 'LATS',
LAND_MASK_STR: 'lm',
SFC_AREA_STR: 'AREA'
}
@pytest.fixture()
def data_reg_alt_names(data_for_reg_calcs):
return data_for_reg_calcs.rename(_alt_names)
region_no_land_mask = Region(name='test',
description='Test region with no land mask',
west_bound=0.,
east_bound=5,
south_bound=0,
north_bound=90.,
do_land_mask=False)
region_land_mask = Region(name='test',
description='Test region with land mask',
west_bound=0.,
east_bound=5,
south_bound=0,
north_bound=90.,
do_land_mask=True)
_expected_mask = [[False, False], [True, False], [True, False], [True, False]]
variables=(convection_rain, condensation_rain))
ps = Var(name='ps',
def_time=True,
description=('surface pressure'),
def_vert=False)
sphum = Var(name='sphum',
def_time=True,
description=('specific humidity'),
def_vert=True)
globe = Region(name='globe',
description='Entire globe',
west_bound=0,
east_bound=360,
south_bound=-90,
north_bound=90,
do_land_mask=False)
sahel = Region(name='sahel',
description='African Sahel',
mask_bounds=[(0, 40, 10, 20), (342, 360, 10, 20)],
do_land_mask=True)
bk = Var(name='bk',
description=('hybrid coefficients'),
def_time=False,
def_vert=True,
def_lon=False,
def_lat=False)
name='precip_total',
def_time=True,
func=total_precip,
variables=(precip_largescale, precip_convective),
)
precip_conv_frac = Var(
name='precip_conv_frac',
def_time=True,
func=conv_precip_frac,
variables=(precip_largescale, precip_convective),
)
globe = Region(name='globe',
description='Entire globe',
lat_bounds=(-90, 90),
lon_bounds=(0, 360),
do_land_mask=False)
tropics = Region(name='tropics',
description='Tropics, defined as 30S-30N',
lat_bounds=(-30, 30),
lon_bounds=(0, 360),
do_land_mask=False)
example_proj = Proj('example_proj',
direc_out='example-output',
tar_direc_out='example-tar-output',
models=[example_model],
regions=(globe, tropics))
def_time=True,
description=('convection rain'),
)
precip = Var(name='total_precipitation',
def_time=True,
description=('total precipitation rate'),
func=total_precipitation,
variables=(convection_rain, condensation_rain))
ps = Var(name='ps',
def_time=True,
description=('surface pressure'),
def_vert=False)
sphum = Var(name='sphum',
def_time=True,
description=('specific humidity'),
def_vert=True)
globe = Region(name='globe',
description='Entire globe',
lat_bounds=(-90, 90),
lon_bounds=(0, 360),
do_land_mask=False)
sahel = Region(name='sahel',
description='African Sahel',
mask_bounds=[((10, 20), (0, 40)), ((10, 20), (342, 360))],
do_land_mask=True)
base = GFDLDataLoader(
data_direc=rootdir,
data_dur=5,
data_start_date=datetime(1980, 1, 1),
data_end_date=datetime(1999, 12, 31),
)
example_run = Run(
name='relative humidity examination',
description='An examination of relative humidity 1980 => 2000',
data_loader=base)
example_model = Model(name='example_model',
runs=[example_run],
grid_file_paths=(os.path.join(rootdir, 'atmos', 'ts',
'monthly',
'zg_A1.199501-199912.nc')))
example_proj = Proj('example_proj',
direc_out=output_dir,
models=[example_model])
hur = Var(name='hur', def_time=True, description='Relative humidity')
globe = Region(name='globe',
description='Entire globe',
west_bound=0,
east_bound=360,
south_bound=-90,
north_bound=90,
do_land_mask=False)