def test_get_dataset_indexes_for_single_cell(self):
dataset = new_cube(width=360, height=180, drop_bounds=True)
cell = dataset.isel(time=2, lat=20, lon=30)
with self.assertRaises(ValueError) as cm:
get_dataset_indexes(cell, "lon", np.array([-149.5]))
self.assertEqual(
"cannot determine cell boundaries for coordinate variable 'lon' of size 1",
f"{cm.exception}")
def test_write_dataset(self):
dataset = new_cube()
try:
write_dataset(dataset, TEST_NC_FILE_2)
self.assertTrue(os.path.isfile(TEST_NC_FILE_2))
finally:
if os.path.isfile(TEST_NC_FILE_2):
os.remove(TEST_NC_FILE_2)
def _new_test_cube(self):
return new_cube(width=2000,
height=1000,
lon_start=0.0,
lat_start=50.0,
spatial_res=4.0 / 2000,
time_start="2010-01-01",
time_periods=20,
variables=dict(precipitation=0.6, temperature=276.2))
def test_verify_cube(self):
cube = new_cube()
self.assertEqual([], verify_cube(cube))
ds = cube.drop("time")
self.assertEqual(["missing coordinate variable 'time'"],
verify_cube(ds))
ds = ds.drop("lat")
self.assertEqual([
"missing coordinate variable 'time'",
"missing coordinate variable 'lat'"
], verify_cube(ds))
def test_assert_cube_illegal_coord_var(self):
cube = new_cube(variables=dict(precipitation=0.5))
cube = cube.assign_coords(
lat=xr.DataArray(np.outer(cube.lat, np.ones(cube.lon.size)),
dims=("y", "x")),
lon=xr.DataArray(np.outer(np.ones(cube.lat.size), cube.lon),
dims=("y", "x")))
with self.assertRaises(ValueError) as cm:
assert_cube(cube)
self.assertEqual(
"Dataset is not a valid data cube, because:\n"
"- coordinate variable 'lat' must have a single dimension 'lat';\n"
"- coordinate variable 'lon' must have a single dimension 'lon'.",
f"{cm.exception}")
def test_assert_cube_illegal_data_var(self):
cube = new_cube(variables=dict(precipitation=0.5))
shape = cube.dims["lat"], cube.dims["lon"]
cube["chl"] = xr.DataArray(np.random.rand(*shape),
dims=("lat", "lon"),
coords=dict(lat=cube.lat, lon=cube.lon))
with self.assertRaises(ValueError) as cm:
assert_cube(cube)
self.assertEqual(
"Dataset is not a valid data cube, because:\n"
"- dimensions of data variable 'chl' must be"
" ('time', ..., 'lat', 'lon'), but were ('lat', 'lon') for 'chl';\n"
"- dimensions of all data variables must be same,"
" but found ('time', 'lat', 'lon') for 'precipitation'"
" and ('lat', 'lon') for 'chl'.", f"{cm.exception}")
def test_assert_cube_illegal_coord_bounds_var(self):
cube = new_cube(variables=dict(precipitation=0.5))
lat_bnds = np.zeros((cube.time.size, cube.lat.size, 2))
lon_bnds = np.zeros((cube.time.size, cube.lon.size, 2),
dtype=np.float16)
lat_bnds[:, :, :] = cube.lat_bnds
lon_bnds[:, :, :] = cube.lon_bnds
cube = cube.assign_coords(lat_bnds=xr.DataArray(lat_bnds,
dims=("time", "lat",
"bnds")),
lon_bnds=xr.DataArray(lon_bnds,
dims=("time", "lon",
"bnds")))
with self.assertRaises(ValueError) as cm:
assert_cube(cube)
self.assertEqual(
"Dataset is not a valid data cube, because:\n"
"- bounds coordinate variable 'lat_bnds' must have dimensions ('lat', <bounds_dim>);\n"
"- shape of bounds coordinate variable 'lat_bnds' must be (180, 2) but was (5, 180, 2);\n"
"- bounds coordinate variable 'lon_bnds' must have dimensions ('lon', <bounds_dim>);\n"
"- shape of bounds coordinate variable 'lon_bnds' must be (360, 2) but was (5, 360, 2);\n"
"- type of bounds coordinate variable 'lon_bnds' must be dtype('float64')"
" but was dtype('float16').", f"{cm.exception}")
def test_assert_cube_without_bounds(self):
cube = new_cube(variables=dict(precipitation=0.5), drop_bounds=True)
self.assertIs(cube, assert_cube(cube))
def test_assert_cube_ok(self):
cube = new_cube(variables=dict(precipitation=0.5))
self.assertIs(cube, assert_cube(cube))
def setUp(self):
super().setUp()
self.dataset = new_cube(
variables=dict(precipitation=0.2, temperature=279.1))
self.dataset.to_netcdf(TEST_NC_FILE, mode="w")
self.dataset.close()
def test_get_dataset_indexes_without_bounds_inverse_lat(self):
dataset = new_cube(width=360,
height=180,
inverse_lat=True,
drop_bounds=True)
self._assert_get_dataset_indexes_works(dataset, inverse_lat=True)
def test_get_dataset_indexes_with_bounds(self):
dataset = new_cube(width=360, height=180, drop_bounds=False)
self._assert_get_dataset_indexes_works(dataset)
def setUp(self):
self._rm_outputs()
dataset = new_cube(variables=dict(precipitation=0.4, temperature=275.2, soil_moisture=0.5))
dataset.to_netcdf(TEST_NC_FILE, mode="w")
dataset.to_zarr(TEST_ZARR_DIR, mode="w")
