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_dummy_loops():
    # the following line could also be
    # [Dummy(s, integer=True) for s in 'im']
    # or [Dummy(integer=True) for s in 'im']
    i, m = symbols('i m', integer=True, cls=Dummy)
    x = IndexedBase('x')
    y = IndexedBase('y')
    i = Idx(i, m)

    expected = (
        'for (int i_%(icount)i=0; i_%(icount)i<m_%(mcount)i; i_%(icount)i++){\n'
        '   y[i_%(icount)i] = x[i_%(icount)i];\n'
        '}'
    ) % {'icount': i.label.dummy_index, 'mcount': m.dummy_index}
    code = ccode(x[i], assign_to=y[i])
    assert code == expected