int main(int argc, char *argv[]) { // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided. int iprint = argc - 1; Teuchos::RCP<std::ostream> outStream; Teuchos::oblackholestream bhs; // outputs nothing /*** Initialize communicator. ***/ Teuchos::GlobalMPISession mpiSession (&argc, &argv, &bhs); Teuchos::RCP<const Teuchos::Comm<int> > comm = Tpetra::DefaultPlatform::getDefaultPlatform().getComm(); const int myRank = comm->getRank(); if ((iprint > 0) && (myRank == 0)) { outStream = Teuchos::rcp(&std::cout, false); } else { outStream = Teuchos::rcp(&bhs, false); } int errorFlag = 0; // *** Example body. try { /*** Read in XML input ***/ std::string filename = "input.xml"; Teuchos::RCP<Teuchos::ParameterList> parlist = Teuchos::rcp( new Teuchos::ParameterList() ); Teuchos::updateParametersFromXmlFile( filename, parlist.ptr() ); /*** Initialize main data structure. ***/ Teuchos::RCP<PoissonData<RealT> > data = Teuchos::rcp(new PoissonData<RealT>(comm, parlist, outStream)); /*** Build vectors and dress them up as ROL vectors. ***/ Teuchos::RCP<const Tpetra::Map<> > vecmap_u = data->getMatA()->getDomainMap(); Teuchos::RCP<const Tpetra::Map<> > vecmap_z = data->getMatB()->getDomainMap(); Teuchos::RCP<const Tpetra::Map<> > vecmap_c = data->getMatA()->getRangeMap(); Teuchos::RCP<Tpetra::MultiVector<> > u_rcp = Teuchos::rcp(new Tpetra::MultiVector<>(vecmap_u, 1, true)); Teuchos::RCP<Tpetra::MultiVector<> > z_rcp = Teuchos::rcp(new Tpetra::MultiVector<>(vecmap_z, 1, true)); Teuchos::RCP<Tpetra::MultiVector<> > c_rcp = Teuchos::rcp(new Tpetra::MultiVector<>(vecmap_c, 1, true)); Teuchos::RCP<Tpetra::MultiVector<> > du_rcp = Teuchos::rcp(new Tpetra::MultiVector<>(vecmap_u, 1, true)); Teuchos::RCP<Tpetra::MultiVector<> > dz_rcp = Teuchos::rcp(new Tpetra::MultiVector<>(vecmap_z, 1, true)); // Set all values to 1 in u, z and c. u_rcp->putScalar(1.0); z_rcp->putScalar(1.0); c_rcp->putScalar(1.0); // Randomize d vectors. du_rcp->randomize(); dz_rcp->randomize(); // Create ROL::TpetraMultiVectors. Teuchos::RCP<ROL::Vector<RealT> > up = Teuchos::rcp(new ROL::TpetraMultiVector<RealT>(u_rcp)); Teuchos::RCP<ROL::Vector<RealT> > zp = Teuchos::rcp(new ROL::TpetraMultiVector<RealT>(z_rcp)); Teuchos::RCP<ROL::Vector<RealT> > cp = Teuchos::rcp(new ROL::TpetraMultiVector<RealT>(c_rcp)); Teuchos::RCP<ROL::Vector<RealT> > dup = Teuchos::rcp(new ROL::TpetraMultiVector<RealT>(du_rcp)); Teuchos::RCP<ROL::Vector<RealT> > dzp = Teuchos::rcp(new ROL::TpetraMultiVector<RealT>(dz_rcp)); // Create ROL SimOpt vectors. ROL::Vector_SimOpt<RealT> x(up,zp); ROL::Vector_SimOpt<RealT> d(dup,dzp); /*** Build objective function, constraint and reduced objective function. ***/ Teuchos::RCP<Objective_PDEOPT_Poisson<RealT> > obj = Teuchos::rcp(new Objective_PDEOPT_Poisson<RealT>(data, parlist)); Teuchos::RCP<EqualityConstraint_PDEOPT_Poisson<RealT> > con = Teuchos::rcp(new EqualityConstraint_PDEOPT_Poisson<RealT>(data, parlist)); Teuchos::RCP<ROL::Reduced_Objective_SimOpt<RealT> > objReduced = Teuchos::rcp(new ROL::Reduced_Objective_SimOpt<RealT>(obj, con, up, up)); /*** Check functional interface. ***/ obj->checkGradient(x,d,true,*outStream); obj->checkHessVec(x,d,true,*outStream); con->checkApplyJacobian(x,d,*up,true,*outStream); con->checkApplyAdjointHessian(x,*dup,d,x,true,*outStream); con->checkAdjointConsistencyJacobian(*dup,d,x,true,*outStream); con->checkInverseJacobian_1(*up,*up,*up,*zp,true,*outStream); con->checkInverseAdjointJacobian_1(*up,*up,*up,*zp,true,*outStream); //objReduced->checkGradient(*zp,*dzp,true,*outStream); //objReduced->checkHessVec(*zp,*dzp,true,*outStream); /*** Solve optimization problem. ***/ //ROL::Algorithm<RealT> algo_tr("Trust Region",*parlist,false); //algo_tr.run(*zp, *objReduced, true, *outStream); ROL::Algorithm<RealT> algo_cs("Composite Step",*parlist,false); algo_cs.run(x, *cp, *obj, *con, true, *outStream); *outStream << std::endl << "|| u_approx - u_analytic ||_L2 = " << data->computeStateError(u_rcp) << std::endl; data->outputTpetraVector(u_rcp, "state.txt"); } catch (std::logic_error err) { *outStream << err.what() << "\n"; errorFlag = -1000; }; // end try if (errorFlag != 0) std::cout << "End Result: TEST FAILED\n"; else std::cout << "End Result: TEST PASSED\n"; return 0; }
int main(int argc, char *argv[]) { Teuchos::GlobalMPISession mpiSession(&argc, &argv); // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided. int iprint = argc - 1; Teuchos::RCP<std::ostream> outStream; Teuchos::oblackholestream bhs; // outputs nothing if (iprint > 0) outStream = Teuchos::rcp(&std::cout, false); else outStream = Teuchos::rcp(&bhs, false); int errorFlag = 0; // *** Example body. try { std::string filename = "input.xml"; Teuchos::RCP<Teuchos::ParameterList> parlist = Teuchos::rcp( new Teuchos::ParameterList() ); Teuchos::updateParametersFromXmlFile( filename, parlist.ptr() ); RealT V_th = parlist->get("Thermal Voltage", 0.02585); RealT lo_Vsrc = parlist->get("Source Voltage Lower Bound", 0.0); RealT up_Vsrc = parlist->get("Source Voltage Upper Bound", 1.0); RealT step_Vsrc = parlist->get("Source Voltage Step", 1.e-2); RealT true_Is = parlist->get("True Saturation Current", 1.e-12); RealT true_Rs = parlist->get("True Saturation Resistance", 0.25); RealT init_Is = parlist->get("Initial Saturation Current", 1.e-12); RealT init_Rs = parlist->get("Initial Saturation Resistance", 0.25); RealT lo_Is = parlist->get("Saturation Current Lower Bound", 1.e-16); RealT up_Is = parlist->get("Saturation Current Upper Bound", 1.e-1); RealT lo_Rs = parlist->get("Saturation Resistance Lower Bound", 1.e-2); RealT up_Rs = parlist->get("Saturation Resistance Upper Bound", 30.0); // bool use_lambertw = parlist->get("Use Analytical Solution",true); bool use_scale = parlist->get("Use Scaling For Epsilon-Active Sets",true); bool use_sqp = parlist->get("Use SQP", true); // bool use_linesearch = parlist->get("Use Line Search", true); // bool datatype = parlist->get("Get Data From Input File",false); // bool use_adjoint = parlist->get("Use Adjoint Gradient Computation",false); // int use_hessvec = parlist->get("Use Hessian-Vector Implementation",1); // 0 - FD, 1 - exact, 2 - GN // bool plot = parlist->get("Generate Plot Data",false); // RealT noise = parlist->get("Measurement Noise",0.0); EqualityConstraint_DiodeCircuit<RealT> con(V_th,lo_Vsrc,up_Vsrc,step_Vsrc); RealT alpha = 1.e-4; // regularization parameter (unused) int ns = 101; // number of Vsrc components int nz = 2; // number of optimization variables Objective_DiodeCircuit<RealT> obj(alpha,ns,nz); // Initialize iteration vectors. Teuchos::RCP<std::vector<RealT> > z_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) ); Teuchos::RCP<std::vector<RealT> > yz_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) ); Teuchos::RCP<std::vector<RealT> > soln_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) ); (*z_rcp)[0] = init_Is; (*z_rcp)[1] = init_Rs; (*yz_rcp)[0] = init_Is; (*yz_rcp)[1] = init_Rs; (*soln_rcp)[0] = true_Is; (*soln_rcp)[1] = true_Rs; ROL::StdVector<RealT> z(z_rcp); ROL::StdVector<RealT> yz(yz_rcp); ROL::StdVector<RealT> soln(soln_rcp); Teuchos::RCP<ROL::Vector<RealT> > zp = Teuchos::rcp(&z,false); Teuchos::RCP<ROL::Vector<RealT> > yzp = Teuchos::rcp(&yz,false); Teuchos::RCP<std::vector<RealT> > u_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) ); Teuchos::RCP<std::vector<RealT> > yu_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) ); std::ifstream input_file("measurements.dat"); RealT temp, temp_scale; for (int i=0; i<ns; i++) { input_file >> temp; input_file >> temp; temp_scale = pow(10,int(log10(temp))); (*u_rcp)[i] = temp_scale*(RealT)rand()/(RealT)RAND_MAX; (*yu_rcp)[i] = temp_scale*(RealT)rand()/(RealT)RAND_MAX; } input_file.close(); ROL::StdVector<RealT> u(u_rcp); ROL::StdVector<RealT> yu(yu_rcp); Teuchos::RCP<ROL::Vector<RealT> > up = Teuchos::rcp(&u,false); Teuchos::RCP<ROL::Vector<RealT> > yup = Teuchos::rcp(&yu,false); Teuchos::RCP<std::vector<RealT> > jv_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 1.0) ); ROL::StdVector<RealT> jv(jv_rcp); Teuchos::RCP<ROL::Vector<RealT> > jvp = Teuchos::rcp(&jv,false); ROL::Vector_SimOpt<RealT> x(up,zp); ROL::Vector_SimOpt<RealT> y(yup,yzp); // Check derivatives obj.checkGradient(x,x,y,true,*outStream); obj.checkHessVec(x,x,y,true,*outStream); con.checkApplyJacobian(x,y,jv,true,*outStream); con.checkApplyAdjointJacobian(x,yu,jv,x,true,*outStream); con.checkApplyAdjointHessian(x,yu,y,x,true,*outStream); // Check consistency of Jacobians and adjoint Jacobians. con.checkAdjointConsistencyJacobian_1(jv,yu,u,z,true,*outStream); con.checkAdjointConsistencyJacobian_2(jv,yz,u,z,true,*outStream); // Check consistency of solves. con.checkSolve(u,z,jv,true,*outStream); con.checkInverseJacobian_1(jv,yu,u,z,true,*outStream); con.checkInverseAdjointJacobian_1(yu,jv,u,z,true,*outStream); // Initialize reduced objective function. Teuchos::RCP<std::vector<RealT> > p_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) ); ROL::StdVector<RealT> p(p_rcp); Teuchos::RCP<ROL::Vector<RealT> > pp = Teuchos::rcp(&p,false); Teuchos::RCP<ROL::Objective_SimOpt<RealT> > pobj = Teuchos::rcp(&obj,false); Teuchos::RCP<ROL::EqualityConstraint_SimOpt<RealT> > pcon = Teuchos::rcp(&con,false); ROL::Reduced_Objective_SimOpt<RealT> robj(pobj,pcon,up,pp); // Check derivatives. *outStream << "Derivatives of reduced objective" << std::endl; robj.checkGradient(z,z,yz,true,*outStream); robj.checkHessVec(z,z,yz,true,*outStream); // Bound constraints RealT tol = 1.e-12; Teuchos::RCP<std::vector<RealT> > g0_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) );; ROL::StdVector<RealT> g0p(g0_rcp); robj.gradient(g0p,z,tol); *outStream << std::scientific << "Initial gradient = " << (*g0_rcp)[0] << " " << (*g0_rcp)[1] << "\n"; *outStream << std::scientific << "Norm of Gradient = " << g0p.norm() << "\n"; // Define scaling for epsilon-active sets (used in inequality constraints) RealT scale; if(use_scale){ scale = 1.0e-2/g0p.norm();} else{ scale = 1.0;} *outStream << std::scientific << "Scaling: " << scale << "\n"; /// Define constraints on Is and Rs BoundConstraint_DiodeCircuit<RealT> bcon(scale,lo_Is,up_Is,lo_Rs,up_Rs); //bcon.deactivate(); // Optimization *outStream << "\n Initial guess " << (*z_rcp)[0] << " " << (*z_rcp)[1] << std::endl; if (!use_sqp){ // Trust Region ROL::Algorithm<RealT> algo_tr("Trust Region",*parlist); std::clock_t timer_tr = std::clock(); algo_tr.run(z,robj,bcon,true,*outStream); *outStream << "\n Solution " << (*z_rcp)[0] << " " << (*z_rcp)[1] << "\n" << std::endl; *outStream << "Trust-Region required " << (std::clock()-timer_tr)/(RealT)CLOCKS_PER_SEC << " seconds.\n"; } else{ // SQP. //Teuchos::RCP<std::vector<RealT> > gz_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) ); //ROL::StdVector<RealT> gz(gz_rcp); //Teuchos::RCP<ROL::Vector<RealT> > gzp = Teuchos::rcp(&gz,false); Teuchos::RCP<std::vector<RealT> > gu_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) ); ROL::StdVector<RealT> gu(gu_rcp); Teuchos::RCP<ROL::Vector<RealT> > gup = Teuchos::rcp(&gu,false); //ROL::Vector_SimOpt<RealT> g(gup,gzp); ROL::Vector_SimOpt<RealT> g(gup,zp); Teuchos::RCP<std::vector<RealT> > c_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) ); Teuchos::RCP<std::vector<RealT> > l_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) ); ROL::StdVector<RealT> c(c_rcp); ROL::StdVector<RealT> l(l_rcp); ROL::Algorithm<RealT> algo_cs("Composite Step",*parlist); //x.zero(); std::clock_t timer_cs = std::clock(); algo_cs.run(x,g,l,c,obj,con,true,*outStream); *outStream << "\n Solution " << (*z_rcp)[0] << " " << (*z_rcp)[1] << "\n" << std::endl; *outStream << "Composite Step required " << (std::clock()-timer_cs)/(RealT)CLOCKS_PER_SEC << " seconds.\n"; } soln.axpy(-1.0, z); *outStream << "Norm of error: " << soln.norm() << std::endl; if (soln.norm() > 1e4*ROL::ROL_EPSILON) { errorFlag = 1; } } catch (std::logic_error err) { *outStream << err.what() << "\n"; errorFlag = -1000; }; // end try if (errorFlag != 0) std::cout << "End Result: TEST FAILED\n"; else std::cout << "End Result: TEST PASSED\n"; return 0; }