def test_block_median(input_dataarray):
coarsening_factor = 2
block_sizes = {"x": coarsening_factor, "y": coarsening_factor, "z": 1}
expected = _xarray_block_reduce_dataarray(input_dataarray, block_sizes,
np.median)
result = block_median(input_dataarray, coarsening_factor, "x", "y")
assert_identical_including_dtype(result, expected)
def test_xarray_block_reduce_dataarray(reduction_function, use_dask,
input_dataarray, regtest):
if use_dask:
input_dataarray = input_dataarray.chunk({"x": 2, "y": 2, "z": -1})
block_sizes = {"x": 2, "y": 2}
result = _xarray_block_reduce_dataarray(input_dataarray, block_sizes,
reduction_function)
print(vcm.testing.checksum_dataarray(result), file=regtest)
for coord in result.coords:
print(np.asarray(result[coord]), file=regtest)
# This ensures the metadata is correct
result.to_dataset(name="a").info(regtest)
def test_horizontal_block_reduce_dataset(input_dataset):
coarsening_factor = 2
block_sizes = {"x": coarsening_factor, "y": coarsening_factor, "z": 1}
expected_foo = _xarray_block_reduce_dataarray(input_dataset.foo,
block_sizes, np.median)
# No change expected to bar, because it contains no horizontal dimensions.
expected_bar = input_dataset.bar
expected = xr.merge([expected_foo, expected_bar]).assign_attrs(test="a")
result = horizontal_block_reduce(input_dataset, coarsening_factor,
np.median, "x", "y")
assert_identical_including_dtype(result, expected)
def test_block_reduce_dataarray_coordinates(input_dataarray, coord_func):
# Add coordinates to the input_dataarray; make sure coordinate behavior
# matches xarray's default for coarsen. This ensures that the
# coordinate transformation behavior for any function that depends on
# _block_reduce_dataarray matches that for xarray's coarsen.
for dim, size in input_dataarray.sizes.items():
input_dataarray[dim] = np.arange(size)
block_sizes = {"x": 2, "y": 2}
result = _xarray_block_reduce_dataarray(input_dataarray,
block_sizes,
np.median,
coord_func=coord_func)
expected = (input_dataarray.coarsen(
x=2, y=2, coord_func=coord_func).median().rename(
input_dataarray.name).assign_attrs({"units": "m"}))
assert_identical_including_dtype(result, expected)
def test_xarray_block_reduce_dataarray_bad_chunk_size(input_dataarray):
input_dataarray = input_dataarray.chunk({"x": -1, "y": 3, "z": -1})
block_sizes = {"x": 1, "y": 2, "z": 1}
with pytest.raises(ValueError, match="All chunks along dimension"):
_xarray_block_reduce_dataarray(input_dataarray, block_sizes, np.median)