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_cell(self, row_category: str, col_category: str, value: int):
        """Logs a cell in the confusion matrix.

        Args:
          row_category: String representing the name of the row category.
          col_category: String representing the name of the column category.
          value: Int value of the cell.

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

        if col_category not in self._categories:
            raise ValueError('Invalid category: {} passed. Expected one of: {}'.\
              format(row_category, self._categories))

        self._matrix[self._categories.index(row_category)][
            self._categories.index(col_category)] = value