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Merge pull request #2612 from djhoese/feature-pyr2-resamplers
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Remove tests for removed and deprecated functionality
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@djhoese
djhoese committed Oct 23, 2023
2 parents a497619 + e6261e7 commit 93841e5
Showing 1 changed file with 1 addition and 153 deletions.
154 changes: 1 addition & 153 deletions satpy/tests/test_resample.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,11 +28,6 @@
import xarray as xr
from pyproj import CRS

try:
from pyresample.ewa import LegacyDaskEWAResampler
except ImportError:
LegacyDaskEWAResampler = None

from satpy.resample import NativeResampler


Expand Down Expand Up @@ -137,13 +132,12 @@ def test_type_preserve(self):
class TestKDTreeResampler(unittest.TestCase):
"""Test the kd-tree resampler."""

@mock.patch('satpy.resample.KDTreeResampler._check_numpy_cache')
@mock.patch('satpy.resample.xr.Dataset')
@mock.patch('satpy.resample.zarr.open')
@mock.patch('satpy.resample.KDTreeResampler._create_cache_filename')
@mock.patch('pyresample.kd_tree.XArrayResamplerNN')
def test_kd_resampling(self, xr_resampler, create_filename, zarr_open,
xr_dset, cnc):
xr_dset):
"""Test the kd resampler."""
from satpy.resample import KDTreeResampler
data, source_area, swath_data, source_swath, target_area = get_test_data()
Expand All @@ -157,7 +151,6 @@ def test_kd_resampling(self, xr_resampler, create_filename, zarr_open,
# swath definitions should not be cached
self.assertFalse(len(mock_dset.to_zarr.mock_calls), 0)
resampler.resampler.reset_mock()
cnc.assert_called_once()

resampler = KDTreeResampler(source_area, target_area)
resampler.precompute()
Expand Down Expand Up @@ -216,151 +209,6 @@ def astype(self, dtype):
resampler.compute(data, fill_value=fill_value)
resampler.resampler.get_sample_from_neighbour_info.assert_called_with(data, fill_value)

@mock.patch('satpy.resample.np.load')
@mock.patch('satpy.resample.xr.Dataset')
def test_check_numpy_cache(self, xr_Dataset, np_load):
"""Test that cache stored in .npz is converted to zarr."""
from satpy.resample import KDTreeResampler

data, source_area, swath_data, source_swath, target_area = get_test_data()
resampler = KDTreeResampler(source_area, target_area)

zarr_out = mock.MagicMock()
xr_Dataset.return_value = zarr_out

try:
the_dir = tempfile.mkdtemp()
kwargs = {}
np_path = resampler._create_cache_filename(the_dir,
prefix='resample_lut-',
fmt='.npz',
mask=None,
**kwargs)
zarr_path = resampler._create_cache_filename(the_dir,
prefix='nn_lut-',
fmt='.zarr',
mask=None,
**kwargs)
resampler._check_numpy_cache(the_dir)
np_load.assert_not_called()
zarr_out.to_zarr.assert_not_called()
with open(np_path, 'w') as fid:
fid.write("42")
resampler._check_numpy_cache(the_dir)
np_load.assert_called_once_with(np_path, 'r')
zarr_out.to_zarr.assert_called_once_with(zarr_path)
finally:
shutil.rmtree(the_dir)


@unittest.skipIf(LegacyDaskEWAResampler is not None,
"Deprecated EWA resampler is now in pyresample. "
"No need to test in Satpy.")
class TestEWAResampler(unittest.TestCase):
"""Test EWA resampler class."""

@mock.patch('satpy.resample.fornav')
@mock.patch('satpy.resample.ll2cr')
@mock.patch('satpy.resample.SwathDefinition.get_lonlats')
def test_2d_ewa(self, get_lonlats, ll2cr, fornav):
"""Test EWA with a 2D dataset."""
import numpy as np
import xarray as xr

from satpy.resample import resample_dataset
ll2cr.return_value = (100,
np.zeros((10, 10), dtype=np.float32),
np.zeros((10, 10), dtype=np.float32))
fornav.return_value = (100 * 200,
np.zeros((200, 100), dtype=np.float32))
_, _, swath_data, source_swath, target_area = get_test_data()
get_lonlats.return_value = (source_swath.lons, source_swath.lats)
swath_data.data = swath_data.data.astype(np.float32)
num_chunks = len(source_swath.lons.chunks[0]) * len(source_swath.lons.chunks[1])

new_data = resample_dataset(swath_data, target_area, resampler='ewa')
self.assertTupleEqual(new_data.shape, (200, 100))
self.assertEqual(new_data.dtype, np.float32)
self.assertEqual(new_data.attrs['test'], 'test')
self.assertIs(new_data.attrs['area'], target_area)
# make sure we can actually compute everything
new_data.compute()
lonlat_calls = get_lonlats.call_count
ll2cr_calls = ll2cr.call_count

# resample a different dataset and make sure cache is used
data = xr.DataArray(
swath_data.data,
dims=('y', 'x'), attrs={'area': source_swath, 'test': 'test2',
'name': 'test2'})
new_data = resample_dataset(data, target_area, resampler='ewa')
new_data.compute()
# ll2cr will be called once more because of the computation
self.assertEqual(ll2cr.call_count, ll2cr_calls + num_chunks)
# but we should already have taken the lonlats from the SwathDefinition
self.assertEqual(get_lonlats.call_count, lonlat_calls)
self.assertIn('y', new_data.coords)
self.assertIn('x', new_data.coords)
self.assertIn('crs', new_data.coords)
self.assertIsInstance(new_data.coords['crs'].item(), CRS)
self.assertIn('lambert', new_data.coords['crs'].item().coordinate_operation.method_name.lower())
self.assertEqual(new_data.coords['y'].attrs['units'], 'meter')
self.assertEqual(new_data.coords['x'].attrs['units'], 'meter')
self.assertEqual(target_area.crs, new_data.coords['crs'].item())

@mock.patch('satpy.resample.fornav')
@mock.patch('satpy.resample.ll2cr')
@mock.patch('satpy.resample.SwathDefinition.get_lonlats')
def test_3d_ewa(self, get_lonlats, ll2cr, fornav):
"""Test EWA with a 3D dataset."""
import numpy as np
import xarray as xr

from satpy.resample import resample_dataset
_, _, swath_data, source_swath, target_area = get_test_data(
input_shape=(3, 200, 100), input_dims=('bands', 'y', 'x'))
swath_data.data = swath_data.data.astype(np.float32)
ll2cr.return_value = (100,
np.zeros((10, 10), dtype=np.float32),
np.zeros((10, 10), dtype=np.float32))
fornav.return_value = ([100 * 200] * 3,
[np.zeros((200, 100), dtype=np.float32)] * 3)
get_lonlats.return_value = (source_swath.lons, source_swath.lats)
num_chunks = len(source_swath.lons.chunks[0]) * len(source_swath.lons.chunks[1])

new_data = resample_dataset(swath_data, target_area, resampler='ewa')
self.assertTupleEqual(new_data.shape, (3, 200, 100))
self.assertEqual(new_data.dtype, np.float32)
self.assertEqual(new_data.attrs['test'], 'test')
self.assertIs(new_data.attrs['area'], target_area)
# make sure we can actually compute everything
new_data.compute()
lonlat_calls = get_lonlats.call_count
ll2cr_calls = ll2cr.call_count

# resample a different dataset and make sure cache is used
swath_data = xr.DataArray(
swath_data.data,
dims=('bands', 'y', 'x'), coords={'bands': ['R', 'G', 'B']},
attrs={'area': source_swath, 'test': 'test'})
new_data = resample_dataset(swath_data, target_area, resampler='ewa')
new_data.compute()
# ll2cr will be called once more because of the computation
self.assertEqual(ll2cr.call_count, ll2cr_calls + num_chunks)
# but we should already have taken the lonlats from the SwathDefinition
self.assertEqual(get_lonlats.call_count, lonlat_calls)
self.assertIn('y', new_data.coords)
self.assertIn('x', new_data.coords)
self.assertIn('bands', new_data.coords)
self.assertIn('crs', new_data.coords)
self.assertIsInstance(new_data.coords['crs'].item(), CRS)
self.assertIn('lambert', new_data.coords['crs'].item().coordinate_operation.method_name.lower())
self.assertEqual(new_data.coords['y'].attrs['units'], 'meter')
self.assertEqual(new_data.coords['x'].attrs['units'], 'meter')
np.testing.assert_equal(new_data.coords['bands'].values,
['R', 'G', 'B'])
self.assertEqual(target_area.crs, new_data.coords['crs'].item())


class TestNativeResampler:
"""Tests for the 'native' resampling method."""
Expand Down

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