def test_view_mixin_copies_data(adata, array_type: type, attr):
    N = 100
    adata = ad.AnnData(
        obs=pd.DataFrame(index=np.arange(N)), var=pd.DataFrame(index=np.arange(N))
    )

    X = array_type(sparse.eye(N, N).multiply(np.arange(1, N + 1)))
    if attr == "X":
        adata.X = X
    else:
        getattr(adata, attr)["arr"] = X

    view = adata[:50]

    if attr == "X":
        arr_view = view.X
    else:
        arr_view = getattr(view, attr)["arr"]

    arr_view_copy = arr_view.copy()

    if sparse.issparse(X):
        assert not np.shares_memory(arr_view.indices, arr_view_copy.indices)
        assert not np.shares_memory(arr_view.indptr, arr_view_copy.indptr)
        assert not np.shares_memory(arr_view.data, arr_view_copy.data)

        arr_view_copy.data[0] = -5
        assert not np.array_equal(arr_view_copy.data, arr_view.data)
    else:
        assert not np.shares_memory(arr_view, arr_view_copy)

        arr_view_copy[0, 0] = -5
        assert not np.array_equal(arr_view_copy, arr_view)
def intersectmatchers(m1, m2):
    """Composes two matchers by matching if both of them match.

    The second matcher's non-matching-attributes (root, cwd, bad, traversedir)
    are ignored.
    """
    if m1 is None or m2 is None:
        return m1 or m2
    if m1.always():
        m = copy.copy(m2)
        # TODO: Consider encapsulating these things in a class so there's only
        # one thing to copy from m1.
        m.bad = m1.bad
        m.traversedir = m1.traversedir
        m.abs = m1.abs
        m.rel = m1.rel
        m._relativeuipath |= m1._relativeuipath
        return m
    if m2.always():
        m = copy.copy(m1)
        m._relativeuipath |= m2._relativeuipath
        return m
    return intersectionmatcher(m1, m2)