ROL
sacado/example_01.cpp
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43 
57 #include <iostream>
58 
59 #include "ROL_Sacado_Objective.hpp"
60 
61 #include "ROL_LineSearchStep.hpp"
62 #include "ROL_Algorithm.hpp"
63 
64 #include "Teuchos_oblackholestream.hpp"
65 #include "Teuchos_GlobalMPISession.hpp"
66 #include "Teuchos_XMLParameterListHelpers.hpp"
67 
68 #include "example_01.hpp"
69 
70 using namespace ROL;
71 
72 typedef double RealT;
73 
74 int main(int argc, char **argv)
75 {
76  Teuchos::GlobalMPISession mpiSession(&argc, &argv);
77 
78  // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
79  int iprint = argc - 1;
80  Teuchos::RCP<std::ostream> outStream;
81  Teuchos::oblackholestream bhs; // outputs nothing
82  if (iprint > 0)
83  outStream = Teuchos::rcp(&std::cout, false);
84  else
85  outStream = Teuchos::rcp(&bhs, false);
86 
87  int errorFlag = 0;
88 
89  // *** Example body.
90 
91  try {
92 
93  Sacado_Objective<RealT,Zakharov> obj;
94 
95  int dim = 10; // Set problem dimension.
96 
97  // Load optimizer parameters form XML file
98  Teuchos::RCP<Teuchos::ParameterList> parlist = Teuchos::rcp(new Teuchos::ParameterList());
99  std::string paramfile = "parameters.xml";
100  Teuchos::updateParametersFromXmlFile(paramfile,Teuchos::Ptr<Teuchos::ParameterList>(&*parlist));
101 
102  // Define Step
103  LineSearchStep<RealT> step(*parlist);
104 
105  // Define Status Test
106  RealT gtol = 1e-12; // norm of gradient tolerance
107  RealT stol = 1e-14; // norm of step tolerance
108  int maxit = 100; // maximum number of iterations
109  StatusTest<RealT> status(gtol, stol, maxit);
110 
111  // Define Algorithm
112  DefaultAlgorithm<RealT> algo(step,status,false);
113 
114  // Iteration Vector
115  Teuchos::RCP<std::vector<RealT> > x_rcp = Teuchos::rcp( new std::vector<RealT> (dim, 0.0) );
116  // Set Initial Guess
117  for (int i=0; i<dim; i++) {
118  (*x_rcp)[i] = 2;
119  }
120 
121  StdVector<RealT> x(x_rcp);
122 
123  // Run Algorithm
124  std::vector<std::string> output = algo.run(x, obj, false);
125  for ( unsigned i = 0; i < output.size(); i++ ) {
126  std::cout << output[i];
127  }
128 
129  // Get True Solution
130  Teuchos::RCP<std::vector<RealT> > xtrue_rcp = Teuchos::rcp( new std::vector<RealT> (dim, 0.0) );
131  StdVector<RealT> xtrue(xtrue_rcp);
132 
133 
134  // Compute Error
135  x.axpy(-1.0, xtrue);
136  RealT abserr = x.norm();
137  *outStream << std::scientific << "\n Absolute Error: " << abserr;
138  if ( abserr > sqrt(ROL_EPSILON) ) {
139  errorFlag += 1;
140  }
141  }
142  catch (std::logic_error err) {
143  *outStream << err.what() << "\n";
144  errorFlag = -1000;
145  }; // end try
146 
147  if (errorFlag != 0)
148  std::cout << "End Result: TEST FAILED\n";
149  else
150  std::cout << "End Result: TEST PASSED\n";
151 
152  return 0;
153 
154 }
virtual void axpy(const Real alpha, const Vector &x)
Compute where .
Definition: ROL_Vector.hpp:141
int main(int argc, char **argv)
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.
double RealT
static const double ROL_EPSILON
Platform-dependent machine epsilon.
Definition: ROL_Types.hpp:109
double RealT