def test_quantile_cpu():
k = 5
# numpy
# add crs for tests
numpy_agg_crs = _add_EPSG4326_crs_to_da(numpy_agg)
numpy_quantile = quantile(numpy_agg_crs, k=k)
unique_elements, counts_elements = np.unique(numpy_quantile.data,
return_counts=True)
assert isinstance(numpy_quantile.data, np.ndarray)
assert len(unique_elements) == k
assert len(np.unique(counts_elements)) == 1
assert np.unique(counts_elements)[0] == 5
# crs tests
assert numpy_quantile.attrs == numpy_agg_crs.attrs
for coord in numpy_agg_crs.coords:
assert np.all(numpy_quantile[coord] == numpy_agg_crs[coord])
# dask + numpy
dask_quantile = quantile(dask_numpy_agg, k=k)
assert isinstance(dask_quantile.data, da.Array)
def test_quantile_cpu_equals_gpu():
import cupy
k = 5
# vanilla numpy version
cpu = quantile(numpy_agg, k=k, name='numpy_result')
# cupy
cupy_agg = xr.DataArray(cupy.asarray(elevation),
attrs={'res': (10.0, 10.0)})
gpu = quantile(cupy_agg, k=k, name='cupy_result')
general_output_checks(cupy_agg, gpu)
np.testing.assert_allclose(cpu.data, gpu.data.get(), equal_nan=True)
def test_quantile_cpu():
k = 5
# numpy
numpy_quantile = quantile(numpy_agg, k=k)
unique_elements, counts_elements = np.unique(numpy_quantile.data,
return_counts=True)
assert isinstance(numpy_quantile.data, np.ndarray)
assert len(unique_elements) == k
assert len(np.unique(counts_elements)) == 1
assert np.unique(counts_elements)[0] == 5
# dask + numpy
dask_quantile = quantile(dask_numpy_agg, k=k)
assert isinstance(dask_quantile.data, da.Array)
def test_quantile_cpu_equals_gpu():
import cupy
k = 5
# vanilla numpy version
cpu = quantile(numpy_agg, k=k, name='numpy_result')
# cupy
cupy_agg = xr.DataArray(cupy.asarray(elevation),
attrs={'res': (10.0, 10.0)})
gpu = quantile(cupy_agg, k=k, name='cupy_result')
assert isinstance(gpu.data, cupy.ndarray)
assert np.isclose(cpu, gpu, equal_nan=True).all()
def test_quantile_cpu():
k = 5
expected_results = np.asarray([[0., 0., 0., 0., np.nan],
[1., 1., 1., 2., 2.], [2., 2., 3., 3., 3.],
[4., 4., 4., 4., np.nan]])
# numpy
numpy_quantile = quantile(numpy_agg, k=k)
general_output_checks(numpy_agg, numpy_quantile, expected_results)
# dask + numpy
dask_quantile = quantile(dask_numpy_agg, k=k)
general_output_checks(dask_numpy_agg, dask_quantile)
dask_quantile = dask_quantile.compute()
unique_elements = np.unique(dask_quantile.data[np.isfinite(
dask_quantile.data)])
assert len(unique_elements) == k
def test_quantile_not_enough_unique_values():
agg = input_data()
n_uniques = np.isfinite(agg.data).sum()
k = n_uniques + 1
result_quantile = quantile(agg, k=k)
n_uniques_result = np.isfinite(result_quantile.data).sum()
np.testing.assert_allclose(n_uniques_result, n_uniques)
def test_quantile_numpy(result_quantile):
k, expected_result = result_quantile
numpy_agg = input_data()
numpy_quantile = quantile(numpy_agg, k=k)
general_output_checks(numpy_agg,
numpy_quantile,
expected_result,
verify_dtype=True)
def test_quantile_cupy(result_quantile):
k, expected_result = result_quantile
cupy_agg = input_data('cupy')
cupy_result = quantile(cupy_agg, k=k)
general_output_checks(cupy_agg,
cupy_result,
expected_result,
verify_dtype=True)
def test_quantile():
k = 5
n, m = 5, 5
agg = xr.DataArray(np.arange(n * m).reshape((n, m)), dims=['x', 'y'])
agg['x'] = np.linspace(0, n, n)
agg['y'] = np.linspace(0, m, m)
quantile_agg = quantile(agg, k=5)
assert quantile_agg is not None
unique_elements, counts_elements = np.unique(quantile_agg.data,
return_counts=True)
assert len(unique_elements) == k
assert len(np.unique(counts_elements)) == 1
def test_quantile_dask_numpy(result_quantile):
# Note that dask's percentile algorithm is
# approximate, while numpy's is exact.
# This may cause some differences between
# results of vanilla numpy and
# dask version of the input agg.
# https://github.com/dask/dask/issues/3099
dask_numpy_agg = input_data('dask+numpy')
k, expected_result = result_quantile
dask_quantile = quantile(dask_numpy_agg, k=k)
general_output_checks(dask_numpy_agg, dask_quantile)
dask_quantile = dask_quantile.compute()
unique_elements = np.unique(dask_quantile.data[np.isfinite(
dask_quantile.data)])
assert len(unique_elements) == k