def test_views():
    X = np.array(X_list)
    adata = ad.AnnData(X, obs=obs_dict, var=var_dict, uns=uns_dict, dtype="int32")

    assert adata[:, 0].is_view
    assert adata[:, 0].X.tolist() == np.reshape([1, 4, 7], (3, 1)).tolist()

    adata[:2, 0].X = [0, 0]

    assert adata[:, 0].X.tolist() == np.reshape([0, 0, 7], (3, 1)).tolist()

    adata_subset = adata[:2, [0, 1]]

    assert adata_subset.is_view
    # now transition to actual object
    adata_subset.obs["foo"] = range(2)
    assert not adata_subset.is_view

    assert adata_subset.obs["foo"].tolist() == list(range(2))
def log_row(self, row_category: str, row: List[int]):
        """Logs a confusion matrix row.

        Args:
          row_category: Category to which the row belongs.
          row: List of integers specifying the values for the row.

        Raises:
          ValueError: If row_category is not in the list of categories set in
            set_categories or size of the row does not match the size of
            categories.
        """
        if row_category not in self._categories:
            raise ValueError('Invalid category: {} passed. Expected one of: {}'.\
              format(row_category, self._categories))

        if len(row) != len(self._categories):
            raise ValueError('Invalid row. Expected size: {} got: {}'.\
              format(len(self._categories), len(row)))

        self._matrix[self._categories.index(row_category)] = row