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 test_ccode_Pow():
    assert ccode(x**3) == "pow(x, 3)"
    assert ccode(x**(y**3)) == "pow(x, pow(y, 3))"
    assert ccode(1/(g(x)*3.5)**(x - y**x)/(x**2 + y)) == \
        "pow(3.5*g(x), -x + pow(y, x))/(pow(x, 2) + y)"
    assert ccode(x**-1.0) == '1.0/x'
    assert ccode(x**Rational(2, 3)) == 'pow(x, 2.0L/3.0L)'
    _cond_cfunc = [(lambda base, exp: exp.is_integer, "dpowi"),
                   (lambda base, exp: not exp.is_integer, "pow")]
    assert ccode(x**3, user_functions={'Pow': _cond_cfunc}) == 'dpowi(x, 3)'
    assert ccode(x**3.2, user_functions={'Pow': _cond_cfunc}) == 'pow(x, 3.2)'