ROL
function/test_18.cpp
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1// @HEADER
2// *****************************************************************************
3// Rapid Optimization Library (ROL) Package
4//
5// Copyright 2014 NTESS and the ROL contributors.
6// SPDX-License-Identifier: BSD-3-Clause
7// *****************************************************************************
8// @HEADER
9
31#include "ROL_RandomVector.hpp"
32#include "ROL_StdVector.hpp"
34
35#include "ROL_Stream.hpp"
36#include "Teuchos_GlobalMPISession.hpp"
37
39#include "ROL_Zakharov.hpp"
40
41
42int main(int argc, char *argv[]) {
43
44 using RealT = double;
46 using ObjectiveT = ROL::ZOO::Objective_Zakharov<RealT>;
48
49 Teuchos::GlobalMPISession mpiSession(&argc, &argv);
50
51 // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
52 int iprint = argc - 1;
53 ROL::Ptr<std::ostream> outStream;
54 ROL::nullstream bhs; // outputs nothing
55 if (iprint > 0)
56 outStream = ROL::makePtrFromRef(std::cout);
57 else
58 outStream = ROL::makePtrFromRef(bhs);
59
60 // Save the format state of the original std::cout.
61 ROL::nullstream oldFormatState;
62 oldFormatState.copyfmt(std::cout);
63
64// RealT errtol = std::sqrt(ROL::ROL_THRESHOLD<RealT>());
65
66 int errorFlag = 0;
67
68 // *** Test body.
69
70 try {
71
72 uint x_dim = 5; // Constraint domain space dimension
73 uint y_dim = 3; // Constraint range space dimension and objective domain space dimension
74
75
76 // Make a Zakharov objective function f(y)
77 auto k_ptr = ROL::makePtr<VectorT>(y_dim);
78 auto& k = *k_ptr;
79 k[0] = 1;
80 k[1] = 2;
81 k[2] = 3;
82
83 auto x = VectorT(x_dim);
84 auto l = VectorT(y_dim);
85
86 auto obj_ptr = ROL::makePtr<ObjectiveT>(k_ptr);
87 auto con_ptr = ROL::makePtr<ConstraintT>();
88
89 VectorT v(x_dim), g(x_dim), hv(x_dim), u(x_dim);
90
91 auto obj = ROL::ChainRuleObjective<RealT>(obj_ptr,con_ptr,x,l);
92
96
97 RealT tol = std::sqrt(ROL::ROL_EPSILON<RealT>());
98
99 auto result_1 = obj.checkGradient(x,v,true,*outStream,7,4);
100
101 bool gradient_passed = false;
102
103 for( auto& row : result_1 ) {
104 if(row[3] < tol) {
105 gradient_passed = true;
106 break;
107 }
108 }
109
110 errorFlag += (!gradient_passed);
111
112 auto result_2 = obj.checkHessVec(x,hv,v,true,*outStream,7,4);
113
114 bool hessVec_passed = false;
115
116 for( auto& row : result_2 ) {
117 if(row[3] < tol) {
118 hessVec_passed = true;
119 break;
120 }
121 }
122
123 errorFlag += (!hessVec_passed) << 1;
124
125 auto result_3 = obj.checkHessSym(x,hv,v,u,true,*outStream);
126 auto hessSym_passed = (result_3[2] < tol);
127
128 errorFlag += (!hessSym_passed) << 2;
129
130 }
131 catch (std::logic_error& err) {
132 *outStream << err.what() << "\n";
133 errorFlag = -1000;
134 }; // end try
135
136 if (errorFlag != 0)
137 std::cout << "End Result: TEST FAILED\n";
138 else
139 std::cout << "End Result: TEST PASSED\n";
140
141 return 0;
142
143
144}
145
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...
std::vector< RealT > VectorT
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,...