ROL
step/test_01.cpp
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43 
48 #define USE_HESSVEC 0
49 
50 #include "ROL_TestObjectives.hpp"
51 #include "ROL_LineSearchStep.hpp"
52 #include "ROL_Algorithm.hpp"
53 #include "Teuchos_oblackholestream.hpp"
54 #include "Teuchos_GlobalMPISession.hpp"
55 #include "Teuchos_XMLParameterListHelpers.hpp"
56 
57 #include <iostream>
58 
59 typedef double RealT;
60 
61 int main(int argc, char *argv[]) {
62 
63  Teuchos::GlobalMPISession mpiSession(&argc, &argv);
64 
65  // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
66  int iprint = argc - 1;
67  Teuchos::RCP<std::ostream> outStream;
68  Teuchos::oblackholestream bhs; // outputs nothing
69  if (iprint > 0)
70  outStream = Teuchos::rcp(&std::cout, false);
71  else
72  outStream = Teuchos::rcp(&bhs, false);
73 
74  int errorFlag = 0;
75 
76  // *** Test body.
77 
78  try {
79 
80  std::string filename = "input.xml";
81  Teuchos::RCP<Teuchos::ParameterList> parlist = Teuchos::rcp( new Teuchos::ParameterList() );
82  Teuchos::updateParametersFromXmlFile( filename, Teuchos::Ptr<Teuchos::ParameterList>(&*parlist) );
83  parlist->set("Use Inexact Hessian-Times-A-Vector",true);
84 #if USE_HESSVEC
85  parlist->set("Use Inexact Hessian-Times-A-Vector",false);
86 #endif
87 
88  // Define Status Test
89  RealT gtol = parlist->get("Gradient Tolerance",1.e-6);
90  RealT stol = parlist->get("Step Tolerance",1.e-12);
91  int maxit = parlist->get("Maximum Number of Iterations",100);
92  ROL::StatusTest<RealT> status(gtol,stol,maxit);
93 
94  for ( ROL::ETestObjectives objFunc = ROL::TESTOBJECTIVES_ROSENBROCK; objFunc < ROL::TESTOBJECTIVES_LAST; objFunc++ ) {
95  *outStream << "\n\n" << ROL::ETestObjectivesToString(objFunc) << "\n\n";
96 
97  // Initial Guess Vector
98  Teuchos::RCP<std::vector<RealT> > x0_rcp = Teuchos::rcp( new std::vector<RealT> );
99  ROL::StdVector<RealT> x0(x0_rcp);
100 
101  // Exact Solution Vector
102  Teuchos::RCP<std::vector<RealT> > z_rcp = Teuchos::rcp( new std::vector<RealT> );
103  ROL::StdVector<RealT> z(z_rcp);
104 
105  // Get Objective Function
106  Teuchos::RCP<ROL::Objective<RealT> > obj = Teuchos::null;
107  ROL::getTestObjectives<RealT>(obj,x0,z,objFunc);
108 
109  // Get Dimension of Problem
110  int dim =
111  Teuchos::rcp_const_cast<std::vector<RealT> >((Teuchos::dyn_cast<ROL::StdVector<RealT> >(x0)).getVector())->size();
112  parlist->set("Maximum Number of Krylov Iterations", 2*dim);
113 
114  // Iteration Vector
115  Teuchos::RCP<std::vector<RealT> > x_rcp = Teuchos::rcp( new std::vector<RealT> (dim, 0.0) );
116  ROL::StdVector<RealT> x(x_rcp);
117  x.set(x0);
118 
119  // Error Vector
120  Teuchos::RCP<std::vector<RealT> > e_rcp = Teuchos::rcp( new std::vector<RealT> (dim, 0.0) );
121  ROL::StdVector<RealT> e(e_rcp);
122  e.zero();
123 
124  for ( ROL::EDescent desc = ROL::DESCENT_STEEPEST; desc < ROL::DESCENT_LAST; desc++ ) {
125  parlist->set("Descent Type", ROL::EDescentToString(desc));
126  if ( desc == ROL::DESCENT_NEWTON &&
127  ((objFunc == ROL::TESTOBJECTIVES_LEASTSQUARES) ||
128  (objFunc == ROL::TESTOBJECTIVES_POISSONCONTROL) ||
129  (objFunc == ROL::TESTOBJECTIVES_POISSONINVERSION)) ) {
130  parlist->set("Descent Type", ROL::EDescentToString(ROL::DESCENT_NEWTONKRYLOV));
131  }
132  else {
133  *outStream << "\n\n" << ROL::EDescentToString(desc) << "\n\n";
134 
135  // Define Step
136  ROL::LineSearchStep<RealT> step(*parlist);
137 
138  // Define Algorithm
139  ROL::DefaultAlgorithm<RealT> algo(step,status,false);
140 
141  // Run Algorithm
142  x.set(x0);
143  std::vector<std::string> output = algo.run(x, *obj);
144  for ( unsigned i = 0; i < output.size(); i++ ) {
145  std::cout << output[i];
146  }
147 
148  // Compute Error
149  e.set(x);
150  e.axpy(-1.0,z);
151  *outStream << "\nNorm of Error: " << e.norm() << "\n";
152  //errorFlag += (int)(e.norm() < std::sqrt(ROL::ROL_EPSILON));
153  }
154  }
155  }
156  }
157  catch (std::logic_error err) {
158  *outStream << err.what() << "\n";
159  errorFlag = -1000;
160  }; // end try
161 
162  if (errorFlag != 0)
163  std::cout << "End Result: TEST FAILED\n";
164  else
165  std::cout << "End Result: TEST PASSED\n";
166 
167  return 0;
168 
169 }
170 
double RealT
int main(int argc, char *argv[])
virtual void axpy(const Real alpha, const Vector &x)
Compute where .
Definition: ROL_Vector.hpp:141
Contains definitions of test objective functions.
std::string EDescentToString(EDescent tr)
Definition: ROL_Types.hpp:229
virtual void zero()
Set to zero vector.
Definition: ROL_Vector.hpp:155
Provides the interface to compute optimization steps with line search.
Real norm() const
Returns where .
Provides the std::vector implementation of the ROL::Vector interface.
virtual std::vector< std::string > run(Vector< Real > &x, Objective< Real > &obj, bool print=false, std::ostream &outStream=std::cout)
Run algorithm on unconstrained problems (Type-U). This is the primary Type-U interface.
Provides an interface to check status of optimization algorithms.
ETestObjectives
Enumeration of test objective functions.
Definition: ROL_Types.hpp:761
void set(const Vector< Real > &x)
Set where .
std::string ETestObjectivesToString(ETestObjectives to)
Definition: ROL_Types.hpp:774
double RealT
EDescent
Enumeration of descent direction types.
Definition: ROL_Types.hpp:220