def test_negative_scalar_index(adata, index: int, obs: bool):
    pos_index = index + (adata.n_obs if obs else adata.n_vars)

    if obs:
        adata_pos_subset = adata[pos_index]
        adata_neg_subset = adata[index]
    else:
        adata_pos_subset = adata[:, pos_index]
        adata_neg_subset = adata[:, index]

    np.testing.assert_array_equal(
        adata_pos_subset.obs_names, adata_neg_subset.obs_names
    )
    np.testing.assert_array_equal(
        adata_pos_subset.var_names, adata_neg_subset.var_names
    )
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