Method test_unstack_sparse

xarray/tests/test_dataset.py:4246–4290

(self)

    @requires_sparse
    def test_unstack_sparse(self) -> None:
        ds = xr.Dataset(
            {"var": (("x",), np.arange(6))},
            coords={"x": [0, 1, 2] * 2, "y": (("x",), ["a"] * 3 + ["b"] * 3)},
        )
        # make ds incomplete
        ds = ds.isel(x=[0, 2, 3, 4]).set_index(index=["x", "y"])
        # test fill_value
        actual1 = ds.unstack("index", sparse=True)
        expected1 = ds.unstack("index")
        assert isinstance(actual1["var"].data, sparse_array_type)
        assert actual1["var"].variable._to_dense().equals(expected1["var"].variable)
        assert actual1["var"].data.density < 1.0

        actual2 = ds["var"].unstack("index", sparse=True)
        expected2 = ds["var"].unstack("index")
        assert isinstance(actual2.data, sparse_array_type)
        assert actual2.variable._to_dense().equals(expected2.variable)
        assert actual2.data.density < 1.0

        midx = pd.MultiIndex.from_arrays([np.arange(3), np.arange(3)], names=["a", "b"])
        coords = Coordinates.from_pandas_multiindex(midx, "z")
        coords["foo"] = np.arange(4)
        coords["bar"] = np.arange(5)
        ds_eye = Dataset(
            {"var": (("z", "foo", "bar"), np.ones((3, 4, 5)))}, coords=coords
        )
        actual3 = ds_eye.unstack(sparse=True, fill_value=0)
        assert isinstance(actual3["var"].data, sparse_array_type)
        expected3 = xr.Dataset(
            {
                "var": (
                    ("foo", "bar", "a", "b"),
                    np.broadcast_to(np.eye(3, 3), (4, 5, 3, 3)),
                )
            },
            coords={
                "foo": np.arange(4),
                "bar": np.arange(5),
                "a": np.arange(3),
                "b": np.arange(3),
            },
        )
        actual3["var"].data = actual3["var"].data.todense()
        assert_equal(expected3, actual3)

    def test_stack_unstack_fast(self) -> None:
        ds = Dataset(