def test_view_of_view_modification():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata[0, :][:, 5:].X = np.ones(5)
    assert np.all(adata.X[0, 5:] == np.ones(5))
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2))
    assert np.all(adata.X[1:3, 1:3] == np.ones((2, 2)))

    adata.X = sparse.csr_matrix(adata.X)
    adata[0, :][:, 5:].X = np.ones(5) * 2
    assert np.all(asarray(adata.X)[0, 5:] == np.ones(5) * 2)
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2)) * 2
    assert np.all(asarray(adata.X)[1:3, 1:3] == np.ones((2, 2)) * 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