def test_inconsistent_input_shapes(self, src_geom, match, call_precompute,
area_def_stere_target,
data_2d_float32_xarray_dask):
"""Test that geometry and data of the same size but different size still error."""
# transpose the source geometries
if isinstance(src_geom, AreaDefinition):
src_geom = AreaDefinition(
src_geom.area_id,
src_geom.description,
src_geom.proj_id,
src_geom.crs,
src_geom.height,
src_geom.width,
src_geom.area_extent,
)
else:
src_geom = SwathDefinition(
src_geom.lons.T.rename({
'y': 'x',
'x': 'y'
}),
src_geom.lats.T.rename({
'y': 'x',
'x': 'y'
}),
)
resampler = KDTreeNearestXarrayResampler(src_geom,
area_def_stere_target)
with pytest.raises(ValueError, match=match):
if call_precompute:
resampler.precompute(
mask=data_2d_float32_xarray_dask.notnull())
else:
resampler.resample(data_2d_float32_xarray_dask)
def swath_def_2d_numpy_antimeridian():
"""Create a SwathDefinition with numpy arrays (200, 1500) over the antimeridian.
Longitude values go from positive values to negative values as they cross -180/180.
"""
lons, lats = _antimeridian_lonlats()
return SwathDefinition(lons, lats)
def swath_def_1d_xarray_dask():
"""Create a 1D SwathDefinition of DataArrays(dask) (3,)."""
chunks = 5
tlons_1d = xr.DataArray(
da.from_array(np.array([11.280789, 12.649354, 12.080402]), chunks=chunks),
dims=('my_dim1',))
tlats_1d = xr.DataArray(
da.from_array(np.array([56.011037, 55.629675, 55.641535]), chunks=chunks),
dims=('my_dim1',))
return SwathDefinition(lons=tlons_1d, lats=tlats_1d)
def swath_def_2d_xarray_dask_antimeridian():
"""Create a SwathDefinition with DataArrays(dask) arrays (200, 1500) over the antimeridian.
Longitude values go from positive values to negative values as they cross -180/180.
"""
lons, lats = _antimeridian_lonlats()
lons = xr.DataArray(lons, dims=("y", "x"))
lats = xr.DataArray(lats, dims=("y", "x"))
return SwathDefinition(lons, lats)
def test_mismatch_geo_data_dims_swath(self, swath_def_2d_xarray_dask,
area_def_stere_target,
data_2d_float32_xarray_dask):
new_swath_def = SwathDefinition(
swath_def_2d_xarray_dask.lons.rename({
'y': 'my_dim_y',
'x': 'my_dim_x'
}),
swath_def_2d_xarray_dask.lats.rename({
'y': 'my_dim_y',
'x': 'my_dim_x'
}))
resampler = KDTreeNearestXarrayResampler(new_swath_def,
area_def_stere_target)
with pytest.raises(ValueError, match='.*dimensions do not match.*'):
resampler.resample(data_2d_float32_xarray_dask)
def swath_def_2d_xarray_dask():
"""Create a SwathDefinition with DataArrays(dask) (200, 1500)."""
lons, lats = _euro_lonlats_dask()
lons = xr.DataArray(lons, dims=("y", "x"))
lats = xr.DataArray(lats, dims=("y", "x"))
return SwathDefinition(lons, lats)
def swath_def_2d_dask():
"""Create a SwathDefinition with dask arrays (200, 1500)."""
lons, lats = _euro_lonlats_dask()
return SwathDefinition(lons, lats)
def swath_def_2d_numpy():
"""Create a SwathDefinition with numpy arrays (200, 1500)."""
lons, lats = _euro_lonlats()
return SwathDefinition(lons, lats)