def _LDL_sparse(self):
        """Algorithm for numeric LDL factization, exploiting sparse structure.
        """
        Lrowstruc = self.row_structure_symbolic_cholesky()
        L = self.eye(self.rows)
        D = self.zeros(self.rows, self.cols)

        for i in range(len(Lrowstruc)):
            for j in Lrowstruc[i]:
                if i != j:
                    L[i, j] = self[i, j]
                    summ = 0
                    for p1 in Lrowstruc[i]:
                        if p1 < j:
                            for p2 in Lrowstruc[j]:
                                if j < p2:
                                    if p1 == p2:
                                        summ += L[i, p1]*L[j, p1]*D[p1, p1]
                                else:
                                    break
                        else:
                            break
                    L[i, j] -= summ
                    L[i, j] /= D[j, j]
                elif i == j:
                    D[i, i] = self[i, i]
                    summ = 0
                    for k in Lrowstruc[i]:
                        if k < i:
                            summ += L[i, k]**2*D[k, k]
                        else:
                            break
                    D[i, i] -= summ

        return L, D
dataset/ETHPy150Open sympy/sympy/sympy/matrices/sparse.py/SparseMatrix._LDL_sparse/swapped operands of `<`