def test_reclassify_cpu():
bins = [10, 20, 30]
new_values = [1, 2, 3]
# numpy
# add crs for tests
numpy_agg_crs = _add_EPSG4326_crs_to_da(numpy_agg)
numpy_reclassify = reclassify(numpy_agg_crs,
bins=bins,
new_values=new_values,
name='numpy_reclassify')
unique_elements, counts_elements = np.unique(numpy_reclassify.data,
return_counts=True)
assert len(unique_elements) == 3
# crs tests
assert numpy_reclassify.attrs == numpy_agg_crs.attrs
for coord in numpy_agg_crs.coords:
assert np.all(numpy_reclassify[coord] == numpy_agg_crs[coord])
# dask + numpy
dask_reclassify = reclassify(dask_numpy_agg,
bins=bins,
new_values=new_values,
name='dask_reclassify')
assert isinstance(dask_reclassify.data, da.Array)
dask_reclassify.data = dask_reclassify.data.compute()
assert np.isclose(numpy_reclassify, dask_reclassify, equal_nan=True).all()
def test_reclassify_cpu_equals_gpu():
import cupy
bins = [10, 20, 30]
new_values = [1, 2, 3]
# vanilla numpy version
cpu = reclassify(numpy_agg,
name='numpy_result',
bins=bins,
new_values=new_values)
# cupy
cupy_agg = xr.DataArray(cupy.asarray(elevation),
attrs={'res': (10.0, 10.0)})
gpu = reclassify(cupy_agg,
name='cupy_result',
bins=bins,
new_values=new_values)
assert isinstance(gpu.data, cupy.ndarray)
assert np.isclose(cpu, gpu, equal_nan=True).all()
# dask + cupy
dask_cupy_agg = xr.DataArray(cupy.asarray(elevation),
attrs={'res': (10.0, 10.0)})
dask_cupy_agg.data = da.from_array(dask_cupy_agg.data, chunks=(3, 3))
dask_gpu = reclassify(dask_cupy_agg,
name='dask_cupy_result',
bins=bins,
new_values=new_values)
assert isinstance(dask_gpu.data, da.Array) and is_cupy_backed(dask_gpu)
dask_gpu.data = dask_gpu.data.compute()
assert np.isclose(cpu, dask_gpu, equal_nan=True).all()
def test_reclassify_cpu_equals_gpu():
import cupy
bins = [10, 15, np.inf]
new_values = [1, 2, 3]
# vanilla numpy version
cpu = reclassify(numpy_agg,
name='numpy_result',
bins=bins,
new_values=new_values)
# cupy
cupy_agg = xr.DataArray(cupy.asarray(elevation),
attrs={'res': (10.0, 10.0)})
gpu = reclassify(cupy_agg,
name='cupy_result',
bins=bins,
new_values=new_values)
general_output_checks(cupy_agg, gpu)
np.testing.assert_allclose(cpu.data, gpu.data.get(), equal_nan=True)
# dask + cupy
dask_cupy_agg = xr.DataArray(cupy.asarray(elevation),
attrs={'res': (10.0, 10.0)})
dask_cupy_agg.data = da.from_array(dask_cupy_agg.data, chunks=(3, 3))
dask_gpu = reclassify(dask_cupy_agg,
name='dask_cupy_result',
bins=bins,
new_values=new_values)
general_output_checks(dask_cupy_agg, dask_gpu)
dask_gpu.data = dask_gpu.data.compute()
np.testing.assert_allclose(cpu.data, dask_gpu.data.get(), equal_nan=True)
def test_reclassify_numpy_mismatch_length():
bins = [10]
new_values = [1, 2, 3]
numpy_agg = input_data()
msg = 'bins and new_values mismatch. Should have same length.'
with pytest.raises(ValueError, match=msg):
reclassify(numpy_agg, bins, new_values)
def test_reclassify_cupy(result_reclassify):
bins, new_values, expected_result = result_reclassify
cupy_agg = input_data(backend='cupy')
cupy_result = reclassify(cupy_agg, bins=bins, new_values=new_values)
general_output_checks(cupy_agg,
cupy_result,
expected_result,
verify_dtype=True)
def test_reclassify_dask_numpy(result_reclassify):
bins, new_values, expected_result = result_reclassify
dask_agg = input_data(backend='dask')
dask_result = reclassify(dask_agg, bins=bins, new_values=new_values)
general_output_checks(dask_agg,
dask_result,
expected_result,
verify_dtype=True)
def test_reclassify_numpy(result_reclassify):
bins, new_values, expected_result = result_reclassify
numpy_agg = input_data()
numpy_result = reclassify(numpy_agg, bins=bins, new_values=new_values)
general_output_checks(numpy_agg,
numpy_result,
expected_result,
verify_dtype=True)
def test_reclassify_cpu():
bins = [10, 15, np.inf]
new_values = [1, 2, 3]
expected_results = np.asarray([[1., 1., 1., 1., np.nan],
[1., 1., 1., 1., 1.], [1., 2., 2., 2., 2.],
[2., 3., 3., 3., 3.]])
# numpy
numpy_reclassify = reclassify(numpy_agg,
bins=bins,
new_values=new_values,
name='numpy_reclassify')
general_output_checks(numpy_agg, numpy_reclassify, expected_results)
# dask + numpy
dask_reclassify = reclassify(dask_numpy_agg,
bins=bins,
new_values=new_values,
name='dask_reclassify')
general_output_checks(dask_numpy_agg, dask_reclassify, expected_results)
def test_reclassify_cpu():
bins = [10, 20, 30]
new_values = [1, 2, 3]
# numpy
numpy_reclassify = reclassify(numpy_agg,
bins=bins,
new_values=new_values,
name='numpy_reclassify')
unique_elements, counts_elements = np.unique(numpy_reclassify.data,
return_counts=True)
assert len(unique_elements) == 3
# dask + numpy
dask_reclassify = reclassify(dask_numpy_agg,
bins=bins,
new_values=new_values,
name='dask_reclassify')
assert isinstance(dask_reclassify.data, da.Array)
dask_reclassify.data = dask_reclassify.data.compute()
assert np.isclose(numpy_reclassify, dask_reclassify, equal_nan=True).all()