Remove zero rows from A

    def _solve(self):

        import qics

        import scipy

        options = {}

        if self.ext.options.timelimit is not None:

            options["max_time"] = self.ext.options.timelimit

        # Remove zero rows from A, and make sure corresponding b is consistent

        JP = list(set(self.int["A"].tocoo().row))

        IP = range(len(JP))

        VP = [1] * len(JP)

        if any([b for (i, b) in enumerate(self.int["b"]) if i not in JP]):

            return Solution(

                primals=None, duals=None, problem=self.ext, solver="PICOS",

                primalStatus=SS_INFEASIBLE, dualStatus=SS_UNKNOWN,

                problemStatus=PS_INFEASIBLE, vectorizedPrimals=True)

        P = scipy.sparse.csr_matrix((VP, (IP, JP)), shape=(len(IP), self.int["A"].shape[0]))

        self.int["A"] = P @ self.int["A"]

        self.int["b"] = P @ self.int["b"]

        # Attempt to solve the problem.

        with self._header(), self._stopwatch():

            model  = qics.Model(**self.int)

                if isinstance(constraint, AffineConstraint):

                    if constraint.is_equality():

                        dual = -cvxopt.matrix(result["y_opt"][indices, 0])

                        dual = -cvxopt.matrix((P.T @ result["y_opt"])[indices, 0])

                    else:

                        dual = cvxopt.matrix(result["z_opt"][indices][0])

                elif isinstance(constraint, LMIConstraint):