ROL
test_16.cpp
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42 
47 #include "ROL_GetTestProblems.hpp"
49 #include "ROL_Stream.hpp"
50 #include "Teuchos_GlobalMPISession.hpp"
51 #include "Teuchos_XMLParameterListHelpers.hpp"
52 
53 #include <iostream>
54 
55 typedef double RealT;
56 
57 int main(int argc, char *argv[]) {
58 
59  Teuchos::GlobalMPISession mpiSession(&argc, &argv);
60 
61  // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
62  int iprint = argc - 1;
63  ROL::Ptr<std::ostream> outStream;
64  ROL::nullstream bhs; // outputs nothing
65  if (iprint > 0)
66  outStream = ROL::makePtrFromRef(std::cout);
67  else
68  outStream = ROL::makePtrFromRef(bhs);
69 
70  int errorFlag = 0;
71 
72  // *** Test body.
73 
74  try {
75  std::string filename = "input.xml";
76  auto parlist = ROL::getParametersFromXmlFile( filename );
77 
78  // Setup optimization problem
79  ROL::Ptr<ROL::Vector<RealT>> x0;
80  std::vector<ROL::Ptr<ROL::Vector<RealT>>> z;
81  ROL::Ptr<ROL::OptimizationProblem<RealT>> optProblem;
82  //ROL::GetTestProblem<RealT>(optProblem,x0,z,ROL::TESTOPTPROBLEM_CANTILEVERBEAM);
83  //ROL::GetTestProblem<RealT>(optProblem,x0,z,ROL::TESTOPTPROBLEM_CYLINDERHEAD);
84  //ROL::GetTestProblem<RealT>(optProblem,x0,z,ROL::TESTOPTPROBLEM_QUARTIC);
85  ROL::GetTestProblem<RealT>(optProblem,x0,z,ROL::TESTOPTPROBLEM_CANTILEVER);
86 
87  // Get Dimension of Problem
88  int dim = x0->dimension();
89  parlist->sublist("General").sublist("Krylov").set("Iteration Limit", 2*dim);
90 
91  // Check Derivatives
92  optProblem->check(*outStream);
93 
94  // Error Vector
95 // ROL::Ptr<ROL::Vector<RealT>> e = x0->clone();
96 // e->zero();
97 
98  // Setup optimization solver
99  parlist->sublist("Status Test").set("Gradient Tolerance",static_cast<RealT>(1e-6));
100  parlist->sublist("Step").set("Type", "Augmented Lagrangian");
101  ROL::OptimizationSolver<RealT> optSolver(*optProblem,*parlist);
102  optSolver.solve(*outStream);
103 
104  // Compute Error
105 // RealT err(0);
106 // for (int i = 0; i < static_cast<int>(z.size()); ++i) {
107 // e->set(*x0);
108 // e->axpy(-1.0,*z[i]);
109 // if (i == 0) {
110 // err = e->norm();
111 // }
112 // else {
113 // err = std::min(err,e->norm());
114 // }
115 // }
116 // *outStream << std::endl << "Norm of Error: " << err << std::endl;
117 //
118 // RealT tol = static_cast<RealT>(1e-3)*std::max(z[0]->norm(),static_cast<RealT>(1));
119 // errorFlag += ((err < tol) ? 0 : 1);
120  }
121  catch (std::logic_error err) {
122  *outStream << err.what() << std::endl;
123  errorFlag = -1000;
124  }; // end try
125 
126  if (errorFlag != 0)
127  std::cout << "End Result: TEST FAILED" << std::endl;
128  else
129  std::cout << "End Result: TEST PASSED" << std::endl;
130 
131  return 0;
132 
133 }
134 
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.
basic_nullstream< char, char_traits< char >> nullstream
Definition: ROL_Stream.hpp:72
int main(int argc, char *argv[])
int solve(const ROL::Ptr< StatusTest< Real > > &status=ROL::nullPtr, const bool combineStatus=true)
Solve optimization problem with no iteration output.