def test_not_set_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(asarray(sparse.random(20, 20))))
    init_hash = joblib.hash(adata)
    orig_X_val = adata.X.copy()
    while True:
        subset_idx = slice_subset(adata.obs_names)
        if len(adata[subset_idx, :]) > 2:
            break
    subset = adata[subset_idx, :]

    subset = adata[:, subset_idx]

    internal_idx = _normalize_index(
        subset_func(np.arange(subset.X.shape[1])), subset.var_names
    )
    assert subset.is_view
    subset.X[:, internal_idx] = 1
    assert not subset.is_view
    assert not np.any(asarray(adata.X != orig_X_val))

    assert init_hash == joblib.hash(adata)
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