ROL
step/test_05.cpp
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43
48#define USE_HESSVEC 1
49
52#include "ROL_Stream.hpp"
53#include "Teuchos_GlobalMPISession.hpp"
54
55
56#include <iostream>
57
58typedef double RealT;
59
60int main(int argc, char *argv[]) {
61
62 Teuchos::GlobalMPISession mpiSession(&argc, &argv);
63
64 // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
65 int iprint = argc - 1;
66 ROL::Ptr<std::ostream> outStream;
67 ROL::nullstream bhs; // outputs nothing
68 if (iprint > 0)
69 outStream = ROL::makePtrFromRef(std::cout);
70 else
71 outStream = ROL::makePtrFromRef(bhs);
72
73 int errorFlag = 0;
74
75 // *** Test body.
76
77 try {
78
79 std::string filename = "input.xml";
80
81 auto parlist = ROL::getParametersFromXmlFile( filename );
82 parlist->sublist("General").set("Inexact Hessian-Times-A-Vector",true);
83#if USE_HESSVEC
84 parlist->sublist("General").set("Inexact Hessian-Times-A-Vector",false);
85#endif
86
87 // Krylov parameters.
88 parlist->sublist("General").sublist("Krylov").set("Type", "Conjugate Residuals");
89 parlist->sublist("General").sublist("Krylov").set("Absolute Tolerance", 1.e-8);
90 parlist->sublist("General").sublist("Krylov").set("Relative Tolerance", 1.e-4);
91 parlist->sublist("General").sublist("Krylov").set("Iteration Limit", 50);
92 parlist->sublist("Step").set("Type","Primal Dual Active Set");
93
95 // Get Objective Function
96 ROL::Ptr<ROL::Vector<RealT> > x0;
97 std::vector<ROL::Ptr<ROL::Vector<RealT> > > z;
98 ROL::Ptr<ROL::OptimizationProblem<RealT> > problem;
99 ROL::GetTestProblem<RealT>(problem,x0,z,prob);
100
101 if (problem->getProblemType() == ROL::TYPE_B) {
102 if ( prob != ROL::TESTOPTPROBLEM_HS5 ) {
103 // PDAS parameters.
104 if (prob == ROL::TESTOPTPROBLEM_HS1 ||
105 prob == ROL::TESTOPTPROBLEM_HS2 ||
106 prob == ROL::TESTOPTPROBLEM_HS3 ||
107 prob == ROL::TESTOPTPROBLEM_HS4 ||
108 prob == ROL::TESTOPTPROBLEM_HS45) {
109 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Step Tolerance",1.e-10);
110 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Gradient Tolerance",1.e-8);
111 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Iteration Limit",1);
112 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Dual Scaling",1.e8);
113 }
114 else if (prob == ROL::TESTOPTPROBLEM_HS5) {
115 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Step Tolerance",1.e-10);
116 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Gradient Tolerance",1.e-8);
117 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Iteration Limit",10);
118 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Dual Scaling",1.e-2);
119 }
120 else if (prob == ROL::TESTOPTPROBLEM_HS25) {
121 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Step Tolerance",1.e-10);
122 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Gradient Tolerance",1.e-8);
123 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Iteration Limit",10);
124 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Dual Scaling",1.e10);
125 }
126 else if (prob == ROL::TESTOPTPROBLEM_HS38) {
127 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Step Tolerance",1.e-10);
128 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Gradient Tolerance",1.e-8);
129 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Iteration Limit",1);
130 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Dual Scaling",1.e-3);
131 }
132 else if (prob == ROL::TESTOPTPROBLEM_BVP) {
133 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Step Tolerance",1.e-10);
134 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Relative Gradient Tolerance",1.e-8);
135 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Iteration Limit",1);
136 parlist->sublist("Step").sublist("Primal Dual Active Set").set("Dual Scaling",1.e0);
137 }
138 *outStream << std::endl << std::endl << ROL:: ETestOptProblemToString(prob) << std::endl << std::endl;
139
140 // Get Dimension of Problem
141 int dim = x0->dimension();
142 parlist->sublist("General").sublist("Krylov").set("Iteration Limit", 2*dim);
143
144 // Error Vector
145 ROL::Ptr<ROL::Vector<RealT> > e = x0->clone();
146 e->zero();
147
148 // Define Solver
149 ROL::OptimizationSolver<RealT> solver(*problem,*parlist);
150
151 // Run Solver
152 solver.solve(*outStream);
153
154 // Compute Error
155 RealT err(0);
156 for (int i = 0; i < static_cast<int>(z.size()); ++i) {
157 e->set(*x0);
158 e->axpy(-1.0,*z[i]);
159 if (i == 0) {
160 err = e->norm();
161 }
162 else {
163 err = std::min(err,e->norm());
164 }
165 }
166 *outStream << std::endl << "Norm of Error: " << err << std::endl;
167
168 // Update error flag
169 ROL::Ptr<const ROL::AlgorithmState<RealT> > state = solver.getAlgorithmState();
170 errorFlag += ((err < std::max(1.e-6*z[0]->norm(),1.e-8) || (state->gnorm < 1.e-6)) ? 0 : 1);
171 }
172 }
173 }
174 }
175 catch (std::logic_error& err) {
176 *outStream << err.what() << std::endl;
177 errorFlag = -1000;
178 }; // end try
179
180 if (errorFlag != 0)
181 std::cout << "End Result: TEST FAILED" << std::endl;
182 else
183 std::cout << "End Result: TEST PASSED" << std::endl;
184
185 return 0;
186
187}
Contains definitions of test objective functions.
Defines a no-output stream class ROL::NullStream and a function makeStreamPtr which either wraps a re...
Provides a simplified interface for solving a wide range of optimization problems.
ROL::Ptr< const AlgorithmState< Real > > getAlgorithmState(void) const
Return the AlgorithmState.
int solve(const ROL::Ptr< StatusTest< Real > > &status=ROL::nullPtr, const bool combineStatus=true)
Solve optimization problem with no iteration output.
std::string ETestOptProblemToString(ETestOptProblem to)
@ TESTOPTPROBLEM_ROSENBROCK
@ TYPE_B
int main(int argc, char *argv[])
double RealT
constexpr auto dim