def sparse(self, rows: np.ndarray = None, cols: np.ndarray = None, layer: str = None) -> scipy.sparse.coo_matrix:
if layer is None:<EOL><INDENT>return self.layers["<STR_LIT>"].sparse(rows=rows, cols=cols)<EOL><DEDENT>else:<EOL><INDENT>return self.layers[layer].sparse(rows=rows, cols=cols)<EOL><DEDENT>
Return the main matrix or specified layer as a scipy.sparse.coo_matrix, without loading dense matrix in RAM

Args:
        rows:		Rows to include, or None to include all
        cols:		Columns to include, or None to include all
        layer:		Layer to return, or None to return the default layer

Returns:
        Sparse matrix (:class:`scipy.sparse.coo_matrix`)