def test_Dataset():
res = dataset.open_file(TEST_DATA)
assert 'history' in res.attributes
assert res.attributes['GRIB_edition'] == 1
assert tuple(res.dimensions.keys()) == \
('number', 'time', 'isobaricInhPa', 'latitude', 'longitude')
assert len(res.variables) == 9
with pytest.warns(FutureWarning):
dataset.open_file(TEST_DATA, mode='rw')
def test_Dataset_reguler_gg_surface() -> None:
path = os.path.join(SAMPLE_DATA_FOLDER, "regular_gg_sfc.grib")
res = dataset.open_file(path)
assert res.dimensions == {"latitude": 96, "longitude": 192}
assert np.allclose(res.variables["latitude"].data[:2],
[88.57216851, 86.72253095])
def test_Dataset_reguler_gg_surface():
path = os.path.join(SAMPLE_DATA_FOLDER, 'regular_gg_sfc.grib')
res = dataset.open_file(path)
assert res.dimensions == {'latitude': 96, 'longitude': 192}
assert np.allclose(res.variables['latitude'].data[:2],
[88.57216851, 86.72253095])
def test_Dataset_no_encode():
res = dataset.open_file(TEST_DATA, encode_cf=())
assert 'history' in res.attributes
assert res.attributes['GRIB_edition'] == 1
assert tuple(res.dimensions.keys()) == ('number', 'dataDate', 'dataTime',
'level', 'values')
assert len(res.variables) == 9
def test_OnDiskArray():
res = dataset.open_file(TEST_DATA).variables["t"]
assert isinstance(res.data, dataset.OnDiskArray)
assert np.allclose(
res.data[2:4:2, [0, 3], 0, 0, 0], res.data.build_array()[2:4:2, [0, 3], 0, 0, 0]
)
def test_Dataset_no_encode():
res = dataset.open_file(TEST_DATA, encode_cf=())
assert "Conventions" in res.attributes
assert "institution" in res.attributes
assert "history" in res.attributes
assert res.attributes["GRIB_edition"] == 1
assert tuple(res.dimensions.keys()) == ("number", "dataDate", "dataTime", "level", "values")
assert len(res.variables) == 9
def test_Dataset() -> None:
res = dataset.open_file(TEST_DATA)
assert "Conventions" in res.attributes
assert "institution" in res.attributes
assert "history" in res.attributes
assert res.attributes["GRIB_edition"] == 1
assert tuple(res.dimensions.keys()) == (
"number",
"time",
"isobaricInhPa",
"latitude",
"longitude",
)
assert len(res.variables) == 9
res1 = dataset.open_file(pathlib.Path(TEST_DATA))
assert res1 == res
def test_Dataset_encode_cf_time():
res = dataset.open_file(TEST_DATA, encode_cf=('time',))
assert 'history' in res.attributes
assert res.attributes['GRIB_edition'] == 1
assert tuple(res.dimensions.keys()) == ('number', 'time', 'level', 'values')
assert len(res.variables) == 9
# equivalent to not np.isnan without importing numpy
assert res.variables['t'].data[:, :, :, :].mean() > 0.
def test_Dataset_encode_cf_time():
res = dataset.open_file(TEST_DATA, encode_cf=("time",))
assert "history" in res.attributes
assert res.attributes["GRIB_edition"] == 1
assert tuple(res.dimensions.keys()) == ("number", "time", "level", "values")
assert len(res.variables) == 9
# equivalent to not np.isnan without importing numpy
assert res.variables["t"].data[:, :, :, :].mean() > 0.0
def test_Dataset_encode_cf_vertical():
res = dataset.open_file(TEST_DATA, encode_cf=("vertical",))
assert "history" in res.attributes
assert res.attributes["GRIB_edition"] == 1
expected_dimensions = ("number", "dataDate", "dataTime", "isobaricInhPa", "values")
assert tuple(res.dimensions.keys()) == expected_dimensions
assert len(res.variables) == 9
# equivalent to not np.isnan without importing numpy
assert res.variables["t"].data[:, :, :, :, :].mean() > 0.0
def test_Dataset_encode_cf_vertical():
res = dataset.open_file(TEST_DATA, encode_cf=('vertical',))
assert 'history' in res.attributes
assert res.attributes['GRIB_edition'] == 1
expected_dimensions = ('number', 'dataDate', 'dataTime', 'isobaricInhPa', 'values')
assert tuple(res.dimensions.keys()) == expected_dimensions
assert len(res.variables) == 9
# equivalent to not np.isnan without importing numpy
assert res.variables['t'].data[:, :, :, :, :].mean() > 0.
def test_Dataset():
res = dataset.open_file(TEST_DATA)
assert 'Conventions' in res.attributes
assert 'institution' in res.attributes
assert 'history' in res.attributes
assert res.attributes['GRIB_edition'] == 1
assert tuple(res.dimensions.keys()) == (
'number',
'time',
'isobaricInhPa',
'latitude',
'longitude',
)
assert len(res.variables) == 9
def test_Dataset_encode_cf_geography() -> None:
res = dataset.open_file(TEST_DATA, encode_cf=("geography", ))
assert "history" in res.attributes
assert res.attributes["GRIB_edition"] == 1
assert tuple(res.dimensions.keys()) == (
"number",
"dataDate",
"dataTime",
"level",
"latitude",
"longitude",
)
assert len(res.variables) == 9
# equivalent to not np.isnan without importing numpy
assert res.variables["t"].data[:, :, :, :, :, :].mean() > 0.0
def test_Dataset_scalar_extra_coords() -> None:
res = dataset.open_file(TEST_DATA_SCALAR_TIME,
extra_coords={"experimentVersionNumber": "time"})
assert "experimentVersionNumber" in res.variables
assert res.variables["experimentVersionNumber"].dimensions == ()
def test_Dataset_extra_coords_error() -> None:
with pytest.raises(ValueError):
dataset.open_file(TEST_DATA, extra_coords={"validityDate": "number"})
def test_open_file() -> None:
res = dataset.open_file(TEST_DATA, filter_by_keys={"shortName": "t"})
assert "t" in res.variables
assert "z" not in res.variables
def test_Dataset_extra_coords():
res = dataset.open_file(TEST_DATA,
extra_coords={"experimentVersionNumber": "time"})
assert "experimentVersionNumber" in res.variables
assert res.variables["experimentVersionNumber"].dimensions == ("time", )
