ROL
function/test_18.cpp
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43 
65 #include "ROL_RandomVector.hpp"
66 #include "ROL_StdVector.hpp"
68 
69 #include "ROL_Stream.hpp"
70 #include "Teuchos_GlobalMPISession.hpp"
71 
73 #include "ROL_Zakharov.hpp"
74 
75 
76 int main(int argc, char *argv[]) {
77 
78  using RealT = double;
80  using ObjectiveT = ROL::ZOO::Objective_Zakharov<RealT>;
82 
83  Teuchos::GlobalMPISession mpiSession(&argc, &argv);
84 
85  // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
86  int iprint = argc - 1;
87  ROL::Ptr<std::ostream> outStream;
88  ROL::nullstream bhs; // outputs nothing
89  if (iprint > 0)
90  outStream = ROL::makePtrFromRef(std::cout);
91  else
92  outStream = ROL::makePtrFromRef(bhs);
93 
94  // Save the format state of the original std::cout.
95  ROL::nullstream oldFormatState;
96  oldFormatState.copyfmt(std::cout);
97 
98 // RealT errtol = std::sqrt(ROL::ROL_THRESHOLD<RealT>());
99 
100  int errorFlag = 0;
101 
102  // *** Test body.
103 
104  try {
105 
106  uint x_dim = 5; // Constraint domain space dimension
107  uint y_dim = 3; // Constraint range space dimension and objective domain space dimension
108 
109 
110  // Make a Zakharov objective function f(y)
111  auto k_ptr = ROL::makePtr<VectorT>(y_dim);
112  auto& k = *k_ptr;
113  k[0] = 1;
114  k[1] = 2;
115  k[2] = 3;
116 
117  auto x = VectorT(x_dim);
118  auto l = VectorT(y_dim);
119 
120  auto obj_ptr = ROL::makePtr<ObjectiveT>(k_ptr);
121  auto con_ptr = ROL::makePtr<ConstraintT>();
122 
123  VectorT v(x_dim), g(x_dim), hv(x_dim), u(x_dim);
124 
125  auto obj = ROL::ChainRuleObjective<RealT>(obj_ptr,con_ptr,x,l);
126 
130 
131  RealT tol = std::sqrt(ROL::ROL_EPSILON<RealT>());
132 
133  auto result_1 = obj.checkGradient(x,v,true,*outStream,7,4);
134 
135  bool gradient_passed = false;
136 
137  for( auto& row : result_1 ) {
138  if(row[3] < tol) {
139  gradient_passed = true;
140  break;
141  }
142  }
143 
144  errorFlag += (!gradient_passed);
145 
146  auto result_2 = obj.checkHessVec(x,hv,v,true,*outStream,7,4);
147 
148  bool hessVec_passed = false;
149 
150  for( auto& row : result_2 ) {
151  if(row[3] < tol) {
152  hessVec_passed = true;
153  break;
154  }
155  }
156 
157  errorFlag += (!hessVec_passed) << 1;
158 
159  auto result_3 = obj.checkHessSym(x,hv,v,u,true,*outStream);
160  auto hessSym_passed = (result_3[2] < tol);
161 
162  errorFlag += (!hessSym_passed) << 2;
163 
164  }
165  catch (std::logic_error& err) {
166  *outStream << err.what() << "\n";
167  errorFlag = -1000;
168  }; // end try
169 
170  if (errorFlag != 0)
171  std::cout << "End Result: TEST FAILED\n";
172  else
173  std::cout << "End Result: TEST PASSED\n";
174 
175  return 0;
176 
177 
178 }
179 
Equality constraints c_i(x) = 0, where: c1(x) = x1^2+x2^2+x3^2+x4^2+x5^2 - 10 c2(x) = x2*x3-5*x4*x5 c...
void RandomizeVector(Vector< Real > &x, const Real &lower=0.0, const Real &upper=1.0)
Fill a ROL::Vector with uniformly-distributed random numbers in the interval [lower,upper].
Defines a no-output stream class ROL::NullStream and a function makeStreamPtr which either wraps a re...
std::vector< RealT > VectorT
Provides the ROL::Vector interface for scalar values, to be used, for example, with scalar constraint...
Contains definitions for the Zakharov function as evaluated using only the ROL::Vector interface...
Contains definitions for the equality constrained NLP from Nocedal/Wright, 2nd edition, page 574, example 18.2; note the typo in reversing the initial guess and the solution.
basic_nullstream< char, char_traits< char >> nullstream
Definition: ROL_Stream.hpp:72
int main(int argc, char *argv[])
Defines an objective of the form f(g(x)) where.