ROL
function/test_18.cpp
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64
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
76int main(int argc, char *argv[]) {
77
78 using RealT = double;
79 using VectorT = ROL::StdVector<RealT>;
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
Contains definitions for the equality constrained NLP from Nocedal/Wright, 2nd edition,...
Defines a no-output stream class ROL::NullStream and a function makeStreamPtr which either wraps a re...
Contains definitions for the Zakharov function as evaluated using only the ROL::Vector interface.
Defines an objective of the form f(g(x)) where.
Provides the ROL::Vector interface for scalar values, to be used, for example, with scalar constraint...
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...
int main(int argc, char *argv[])
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,...
basic_nullstream< char, char_traits< char > > nullstream
Real ROL_EPSILON(void)
Platform-dependent machine epsilon.
Definition ROL_Types.hpp:91