def save_dummy_seas5(
tmp_path,
date_str,
to_grib=False,
dataset="seasonal-monthly-pressure-levels",
variable="temperature",
) -> Path:
"""
filename structure:
data/raw/seasonal-monthly-pressure-levels/temperature/2017/01.grib
"""
year = pd.to_datetime(date_str).year
month = pd.to_datetime(date_str).month
out_dir = tmp_path / "data" / "raw" / dataset / variable / str(year)
if not out_dir.exists():
out_dir.mkdir(exist_ok=True, parents=True)
ds = make_dummy_seas5_data(date_str)
if to_grib:
cfgrib.to_grib(
ds,
out_dir / f"{month:02}.grib",
grib_keys={"edition": 2, "gridType": "regular_ll"},
)
else:
ds.to_netcdf(out_dir / f"{month:02}.nc")
return out_dir
def dataset_to_fieldset(val, **kwarg):
# we try to import xarray as locally as possible to reduce startup time
# try to write the xarray as a GRIB file, then read into a fieldset
import xarray as xr
import cfgrib
if not isinstance(val, xr.core.dataset.Dataset):
raise TypeError(
'dataset_to_fieldset requires a variable of type xr.core.dataset.Dataset;'
' was supplied with ', builtins.type(val))
f, tmp = tempfile.mkstemp(".grib")
os.close(f)
try:
# could add keys, e.g. grib_keys={'centre': 'ecmf'})
cfgrib.to_grib(val, tmp, **kwarg)
except:
print(
"Error trying to write xarray dataset to GRIB for conversion to Metview Fieldset"
)
raise
# TODO: tell Metview that this is a temporary file that should be deleted when no longer needed
fs = read(tmp)
return fs