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Spherical padding and faster tests #45

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merged 8 commits into from
Sep 20, 2024
Merged

Spherical padding and faster tests #45

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ce16f74
initial pass at spherical padding, faster tests, full nan tracking
slevang Sep 6, 2024
ba27714
fix netcdf bug
slevang Sep 6, 2024
6446048
revert to keeping all test slices
slevang Sep 6, 2024
283c310
refactor to separate coord handling functions, appease mypy
slevang Sep 13, 2024
7b44358
add examples to docstrings
slevang Sep 13, 2024
a5788bf
fix modifying coordinates
slevang Sep 19, 2024
52e71c5
fix typing
slevang Sep 19, 2024
1f2e999
review suggestions
slevang Sep 20, 2024
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10 changes: 6 additions & 4 deletions tests/test_regrid.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,20 +27,22 @@
@pytest.fixture(scope="session")
def sample_input_data() -> xr.Dataset:
ds = xr.open_dataset(DATA_PATH / "era5_2m_dewpoint_temperature_2000_monthly.nc")
return ds.isel(time=slice(0, N_TIMESTAMPS)).persist()
# slice after compute due to current xarray bug: https://github.com/pydata/xarray/issues/8909
# then convert to dask so regridding is lazy on attribute tests
return ds.compute().isel(time=slice(0, N_TIMESTAMPS)).chunk()
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@pytest.fixture(scope="session")
def conservative_input_data() -> xr.Dataset:
ds = xr.open_dataset(DATA_PATH / "era5_total_precipitation_2020_monthly.nc")
return ds.isel(time=slice(0, N_TIMESTAMPS)).persist()
return ds.compute().isel(time=slice(0, N_TIMESTAMPS)).chunk()


@pytest.fixture(scope="session")
def cdo_comparison_data() -> dict[str, xr.Dataset]:
data = {}
for method, path in CDO_FILES.items():
data[method] = xr.open_dataset(path).isel(time=slice(0, N_TIMESTAMPS)).persist()
data[method] = xr.open_dataset(path).compute().isel(time=slice(0, N_TIMESTAMPS))
return data


Expand Down Expand Up @@ -203,7 +205,7 @@ def test_conservative_nan_thresholds_against_coarsen(nan_threshold):

@pytest.mark.skipif(xesmf is None, reason="xesmf required")
def test_conservative_nan_thresholds_against_xesmf():
ds = xr.tutorial.open_dataset("ersstv5").sst.isel(time=[0]).persist()
ds = xr.tutorial.open_dataset("ersstv5").sst.compute().isel(time=[0])
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ds = ds.rename(lon="longitude", lat="latitude")
new_grid = xarray_regrid.Grid(
north=90,
Expand Down
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