ROL
example_01d.cpp
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43 
57 #include <iostream>
58 
59 #include "example_01d.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 
69 using namespace ROL;
70 
71 typedef double RealT;
72 
73 int main(int argc, char **argv)
74 {
75  Teuchos::GlobalMPISession mpiSession(&argc, &argv);
76 
77  // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
78  int iprint = argc - 1;
79  Teuchos::RCP<std::ostream> outStream;
80  Teuchos::oblackholestream bhs; // outputs nothing
81  if (iprint > 0)
82  outStream = Teuchos::rcp(&std::cout, false);
83  else
84  outStream = Teuchos::rcp(&bhs, false);
85 
86  int errorFlag = 0;
87 
88  // *** Example body.
89 
90  try {
91 
92  typedef Sacado::Fad::SFad<RealT,1> FadType;
93  typedef Sacado::Fad::DFad<FadType> FadFadType;
94 
95  Zakharov<FadFadType> zakharov;
96  auto obj = Teuchos::rcp(new ObjectiveAD<RealT>(zakharov));
97 
98  int dim = 10; // Set problem dimension.
99 
100  // Load optimizer parameters form XML file
101  auto parlist = Teuchos::rcp(new Teuchos::ParameterList());
102 
103  std::string paramfile = "parameters.xml";
104 
105  Teuchos::updateParametersFromXmlFile(paramfile,Teuchos::Ptr<Teuchos::ParameterList>(&*parlist));
106 
107  // Define Step
108  LineSearchStep<RealT> step(*parlist);
109 
110  // Define Status Test
111  RealT gtol = 1e-12; // norm of gradient tolerance
112  RealT stol = 1e-14; // norm of step tolerance
113  int maxit = 100; // maximum number of iterations
114  StatusTest<RealT> status(gtol, stol, maxit);
115 
116  // Define Algorithm
117  DefaultAlgorithm<RealT> algo(step,status,false);
118 
119  // Iteration Vector
120  auto x_rcp = Teuchos::rcp( new std::vector<RealT> (dim, 0.0) );
121  // Set Initial Guess
122  for (int i=0; i<dim; i++) {
123  (*x_rcp)[i] = 2;
124  }
125 
126  StdVector<RealT> x(x_rcp);
127 
128  // Run Algorithm
129  std::vector<std::string> output = algo.run(x, *obj, false);
130  for ( unsigned i = 0; i < output.size(); i++ ) {
131  std::cout << output[i];
132  }
133 
134  // Get True Solution
135  auto xtrue_rcp = Teuchos::rcp( new std::vector<RealT> (dim, 0.0) );
136  StdVector<RealT> xtrue(xtrue_rcp);
137 
138 
139  // Compute Error
140  x.axpy(-1.0, xtrue);
141  RealT abserr = x.norm();
142  *outStream << std::scientific << "\n Absolute Error: " << abserr;
143  if ( abserr > sqrt(ROL_EPSILON) ) {
144  errorFlag += 1;
145  }
146  }
147  catch (std::logic_error err) {
148  *outStream << err.what() << "\n";
149  errorFlag = -1000;
150  }; // end try
151 
152  if (errorFlag != 0)
153  std::cout << "End Result: TEST FAILED\n";
154  else
155  std::cout << "End Result: TEST PASSED\n";
156 
157  return 0;
158 
159 }
int main(int argc, char **argv)
Definition: example_01d.cpp:73
virtual void axpy(const Real alpha, const Vector &x)
Compute where .
Definition: ROL_Vector.hpp:141
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.
double RealT
Definition: example_01d.cpp:71
Provides an interface to check status of optimization algorithms.
double RealT
static const double ROL_EPSILON
Platform-dependent machine epsilon.
Definition: ROL_Types.hpp:115