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43
44 /*! \file test_05.cpp
45 \brief Shows how to use the nonlinear least squares interface
46 to find a feasible point for the equality constrained NLP
47 from Nocedal/Wright, 2nd edition, page 574, example 18.2.
48 */
49
50 #include "ROL_SimpleEqConstrained.hpp"
51 #include "ROL_StdVector.hpp"
52 #include "ROL_NonlinearLeastSquaresObjective.hpp"
53 #include "ROL_Algorithm.hpp"
54 #include "ROL_TrustRegionStep.hpp"
55 #include "ROL_Stream.hpp"
56 #include "Teuchos_GlobalMPISession.hpp"
57
58 #include <iostream>
59
60 typedef double RealT;
61
62
main(int argc,char * argv[])63 int main(int argc, char *argv[]) {
64
65 Teuchos::GlobalMPISession mpiSession(&argc, &argv);
66
67 // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
68 int iprint = argc - 1;
69 ROL::Ptr<std::ostream> outStream;
70 ROL::nullstream bhs; // outputs nothing
71 if (iprint > 0)
72 outStream = ROL::makePtrFromRef(std::cout);
73 else
74 outStream = ROL::makePtrFromRef(bhs);
75
76 int errorFlag = 0;
77
78 // *** Example body.
79
80 try {
81
82 ROL::Ptr<ROL::Objective<RealT>> obj;
83 ROL::Ptr<ROL::Constraint<RealT>> constr;
84 ROL::Ptr<ROL::Vector<RealT>> x;
85 ROL::Ptr<ROL::Vector<RealT>> sol;
86
87 // Retrieve objective, constraint, iteration vector, solution vector.
88 ROL::ZOO::getSimpleEqConstrained<RealT> SEC;
89 obj = SEC.getObjective();
90 constr = SEC.getEqualityConstraint();
91 x = SEC.getInitialGuess();
92 sol = SEC.getSolution();
93
94 // Inititalize vectors
95 int dim = 5;
96 int nc = 3;
97 RealT left = -1e0, right = 1e0;
98 ROL::Ptr<std::vector<RealT>> xtest_ptr = ROL::makePtr<std::vector<RealT>>(dim, 0.0);
99 ROL::Ptr<std::vector<RealT>> g_ptr = ROL::makePtr<std::vector<RealT>>(dim, 0.0);
100 ROL::Ptr<std::vector<RealT>> d_ptr = ROL::makePtr<std::vector<RealT>>(dim, 0.0);
101 ROL::Ptr<std::vector<RealT>> v_ptr = ROL::makePtr<std::vector<RealT>>(dim, 0.0);
102 ROL::Ptr<std::vector<RealT>> vc_ptr = ROL::makePtr<std::vector<RealT>>(nc, 0.0);
103 ROL::Ptr<std::vector<RealT>> vl_ptr = ROL::makePtr<std::vector<RealT>>(nc, 0.0);
104 ROL::StdVector<RealT> xtest(xtest_ptr);
105 ROL::StdVector<RealT> g(g_ptr);
106 ROL::StdVector<RealT> d(d_ptr);
107 ROL::StdVector<RealT> v(v_ptr);
108 ROL::StdVector<RealT> vc(vc_ptr);
109 ROL::StdVector<RealT> vl(vl_ptr);
110 // set xtest, d, v
111 for (int i=0; i<dim; i++) {
112 (*xtest_ptr)[i] = ( (RealT)rand() / (RealT)RAND_MAX ) * (right - left) + left;
113 (*d_ptr)[i] = ( (RealT)rand() / (RealT)RAND_MAX ) * (right - left) + left;
114 (*v_ptr)[i] = ( (RealT)rand() / (RealT)RAND_MAX ) * (right - left) + left;
115 }
116 // set vc, vl
117 for (int i=0; i<nc; i++) {
118 (*vc_ptr)[i] = ( (RealT)rand() / (RealT)RAND_MAX ) * (right - left) + left;
119 (*vl_ptr)[i] = ( (RealT)rand() / (RealT)RAND_MAX ) * (right - left) + left;
120 }
121
122 xtest.set(*x);
123
124 // Initialize nonlinear least squares objectives
125 ROL::NonlinearLeastSquaresObjective<RealT> nlls(constr,*x,vc,false);
126 ROL::NonlinearLeastSquaresObjective<RealT> gnnlls(constr,*x,vc,true);
127
128 // Check derivatives
129 constr->checkApplyJacobian(xtest, v, vc, true, *outStream); *outStream << "\n";
130 constr->checkApplyAdjointJacobian(xtest, vl, vc, xtest, true, *outStream); *outStream << "\n";
131 constr->checkApplyAdjointHessian(xtest, vl, d, xtest, true, *outStream); *outStream << "\n";
132 nlls.checkGradient(xtest, d, true, *outStream); *outStream << "\n";
133 nlls.checkHessVec(xtest, v, true, *outStream); *outStream << "\n";
134 nlls.checkHessSym(xtest, d, v, true, *outStream); *outStream << "\n";
135
136 // Define algorithm.
137 ROL::ParameterList parlist;
138 parlist.sublist("Step").sublist("Trust Region").set("Subproblem Solver","Truncated CG");
139 parlist.sublist("Status Test").set("Gradient Tolerance",1.e-10);
140 parlist.sublist("Status Test").set("Constraint Tolerance",1.e-10);
141 parlist.sublist("Status Test").set("Step Tolerance",1.e-18);
142 parlist.sublist("Status Test").set("Iteration Limit",100);
143 ROL::Ptr<ROL::StatusTest<RealT>> status = ROL::makePtr<ROL::StatusTest<RealT>>(parlist);
144 ROL::Ptr<ROL::Step<RealT>> step = ROL::makePtr<ROL::TrustRegionStep<RealT>>(parlist);
145 ROL::Algorithm<RealT> algo(step,status,false);
146
147 // Run Algorithm
148 *outStream << "\nSOLVE USING FULL HESSIAN\n";
149 x->set(xtest);
150 algo.run(*x, nlls, true, *outStream);
151 algo.reset();
152 *outStream << "\nSOLVE USING GAUSS-NEWTON HESSIAN\n";
153 x->set(xtest);
154 algo.run(*x, gnnlls, true, *outStream);
155 }
156 catch (std::logic_error& err) {
157 *outStream << err.what() << "\n";
158 errorFlag = -1000;
159 }; // end try
160
161 if (errorFlag != 0)
162 std::cout << "End Result: TEST FAILED\n";
163 else
164 std::cout << "End Result: TEST PASSED\n";
165
166 return 0;
167
168 }
169
170