ROL
function/test_01.cpp
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43
48//#define USE_HESSVEC 0
49
50#include "ROL_StdVector.hpp"
53#include "ROL_Stream.hpp"
54#include "Teuchos_GlobalMPISession.hpp"
55
56#include <iostream>
57
58typedef double RealT;
59
60int main(int argc, char *argv[]) {
61
62 Teuchos::GlobalMPISession mpiSession(&argc, &argv);
63
64 // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
65 int iprint = argc - 1;
66 ROL::Ptr<std::ostream> outStream;
67 ROL::nullstream bhs; // outputs nothing
68 if (iprint > 0)
69 outStream = ROL::makePtrFromRef(std::cout);
70 else
71 outStream = ROL::makePtrFromRef(bhs);
72
73 // Save the format state of the original std::cout.
74 ROL::nullstream oldFormatState;
75 oldFormatState.copyfmt(std::cout);
76
77 int errorFlag = 0;
78
79 // Specify interval on which to generate uniform random numbers.
80 RealT left = -1.0, right = 1.0;
81
82 // *** Test body.
83
84 try {
85
86 int dim = 128;
87 ROL::Ptr<std::vector<RealT> > x_ptr = ROL::makePtr<std::vector<RealT>>(dim, 0.0);
88 ROL::Ptr<std::vector<RealT> > y_ptr = ROL::makePtr<std::vector<RealT>>(dim, 0.0);
89 ROL::Ptr<std::vector<RealT> > z_ptr = ROL::makePtr<std::vector<RealT>>(dim, 0.0);
90 ROL::StdVector<RealT> x(x_ptr);
91 ROL::StdVector<RealT> y(y_ptr);
92 ROL::StdVector<RealT> z(z_ptr);
93
94 // set x,y
95 for (int i=0; i<dim; i++) {
96 (*x_ptr)[i] = 10.0* (1.0 + (RealT)rand() / (RealT)RAND_MAX);
97 (*y_ptr)[i] = ( (RealT)rand() / (RealT)RAND_MAX ) * (right - left) + left;
98 (*z_ptr)[i] = ( (RealT)rand() / (RealT)RAND_MAX ) * (right - left) + left;
99 }
100
101 //ROL::ZOO::Objective_Rosenbrock<RealT> obj;
103 //ROL::ZOO::Objective_SumOfSquares<RealT> obj;
104 //ROL::ZOO::Objective_LeastSquares<RealT> obj;
105
106 std::vector<std::vector<RealT> > gCheck = obj.checkGradient(x, y);
107
108 for (unsigned i=0; i<gCheck.size(); i++) {
109 if (i==0) {
110 *outStream << std::right
111 << std::setw(20) << "Step size"
112 << std::setw(20) << "grad'*dir"
113 << std::setw(20) << "FD approx"
114 << std::setw(20) << "abs error"
115 << "\n";
116 }
117 *outStream << std::scientific << std::setprecision(8) << std::right
118 << std::setw(20) << gCheck[i][0]
119 << std::setw(20) << gCheck[i][1]
120 << std::setw(20) << gCheck[i][2]
121 << std::setw(20) << gCheck[i][3]
122 << "\n";
123 }
124
125 *outStream << "\n";
126 std::vector<std::vector<RealT> > hvCheck = obj.checkHessVec(x, y);
127
128 for (unsigned i=0; i<hvCheck.size(); i++) {
129 if (i==0) {
130 *outStream << std::right
131 << std::setw(20) << "Step size"
132 << std::setw(20) << "norm(Hess*vec)"
133 << std::setw(20) << "norm(FD approx)"
134 << std::setw(20) << "norm(abs error)"
135 << "\n";
136 }
137 *outStream << std::scientific << std::setprecision(8) << std::right
138 << std::setw(20) << hvCheck[i][0]
139 << std::setw(20) << hvCheck[i][1]
140 << std::setw(20) << hvCheck[i][2]
141 << std::setw(20) << hvCheck[i][3]
142 << "\n";
143 }
144
145 *outStream << "\n";
146 std::vector<RealT> hsymCheck = obj.checkHessSym(x, y, z);
147
148 *outStream << std::right
149 << std::setw(20) << "<w, H(x)v>"
150 << std::setw(20) << "<v, H(x)w>"
151 << std::setw(20) << "abs error"
152 << "\n";
153 *outStream << std::scientific << std::setprecision(8) << std::right
154 << std::setw(20) << hsymCheck[0]
155 << std::setw(20) << hsymCheck[1]
156 << std::setw(20) << hsymCheck[2]
157 << "\n";
158
159 Teuchos::SerialDenseMatrix<int, RealT> H(x.dimension(), x.dimension());
160 H = ROL::computeDenseHessian(obj, x);
161 //H.print(*outStream);
162
163 std::vector<std::vector<RealT> > eigenvals = ROL::computeEigenvalues(H);
164
165 *outStream << "\n";
166 for (unsigned i=0; i<(eigenvals[0]).size(); i++) {
167 if (i==0) {
168 *outStream << std::right
169 << std::setw(20) << "Real"
170 << std::setw(20) << "Imag"
171 << "\n";
172 }
173 *outStream << std::scientific << std::setprecision(8) << std::right
174 << std::setw(20) << (eigenvals[0])[i]
175 << std::setw(20) << (eigenvals[1])[i]
176 << "\n";
177 }
178
179 }
180 catch (std::logic_error& err) {
181 *outStream << err.what() << "\n";
182 errorFlag = -1000;
183 }; // end try
184
185 if (errorFlag != 0)
186 std::cout << "End Result: TEST FAILED\n";
187 else
188 std::cout << "End Result: TEST PASSED\n";
189
190 // reset format state of std::cout
191 std::cout.copyfmt(oldFormatState);
192
193 return 0;
194
195}
196
Contains definitions of test objective functions.
Contains definitions for helper functions in ROL.
Defines a no-output stream class ROL::NullStream and a function makeStreamPtr which either wraps a re...
virtual std::vector< Real > checkHessSym(const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &w, const bool printToStream=true, std::ostream &outStream=std::cout)
Hessian symmetry check.
virtual std::vector< std::vector< Real > > checkGradient(const Vector< Real > &x, const Vector< Real > &d, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
Finite-difference gradient check.
virtual std::vector< std::vector< Real > > checkHessVec(const Vector< Real > &x, const Vector< Real > &v, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
Finite-difference Hessian-applied-to-vector check.
Provides the ROL::Vector interface for scalar values, to be used, for example, with scalar constraint...
int main(int argc, char *argv[])
double RealT
Teuchos::SerialDenseMatrix< int, Real > computeDenseHessian(Objective< Real > &obj, const Vector< Real > &x)
std::vector< std::vector< Real > > computeEigenvalues(const Teuchos::SerialDenseMatrix< int, Real > &mat)
constexpr auto dim