def test_load_regridder(self, tmp_path):
test_dataset, _, _ = _make_dataset(size=(10, 10))
test_dataset.to_netcdf(tmp_path / 'regridder.nc')
output = BasePreProcessor.load_reference_grid(tmp_path /
'regridder.nc')
assert set(output.variables) == {
'lat', 'lon'
}, f'Got extra variables: {output.variables}'
def test_load_regridder(self, tmp_path):
test_dataset, _, _ = _make_dataset(size=(10, 10))
test_dataset.to_netcdf(tmp_path / "regridder.nc")
output = BasePreProcessor.load_reference_grid(tmp_path /
"regridder.nc")
assert set(output.variables) == {
"lat",
"lon",
}, f"Got extra variables: {output.variables}"
# ------------------------------------------------------------------------------
# Test PREPROCESSING
# ------------------------------------------------------------------------------
from src.preprocess.base import BasePreProcessor
b = BasePreProcessor()
ds1_kenya = b.chop_roi(ds1, inverse_lat=True)
ds2_kenya = b.chop_roi(ds2, inverse_lat=True)
# concat across initialisation dates
ds_kenya = xr.concat([ds1_kenya, ds2_kenya], dim="initialisation_date")
stacked = ds_kenya.stack(time=("initialisation_date", "forecast_horizon"))
# stack each individually
k1 = ds1_kenya.stack(time=("initialisation_date", "forecast_horizon"))
k2 = ds2_kenya.stack(time=("initialisation_date", "forecast_horizon"))
# test selectors
stacked.sel(forecast_horizon=np.timedelta64(28, "D"))
stacked.sel(initialisation_date="1997-01-01")
stacked.swap_dims({"time": "valid_time"}).sel(valid_time="1997-04")
# test regridding
ref_ds = b.load_reference_grid(path_to_grid=Path("data/interim/chirps_preprocessed.nc"))
ds1_kenya_regrid = b.regrid(
ds1_kenya.rename({"latitude": "lat", "longitude": "lon"}), ref_ds
)
# test resampling time
b.resample_time()