1 // @HEADER
2 // ************************************************************************
3 //
4 // Rapid Optimization Library (ROL) Package
5 // Copyright (2014) Sandia Corporation
6 //
7 // Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive
8 // license for use of this work by or on behalf of the U.S. Government.
9 //
10 // Redistribution and use in source and binary forms, with or without
11 // modification, are permitted provided that the following conditions are
12 // met:
13 //
14 // 1. Redistributions of source code must retain the above copyright
15 // notice, this list of conditions and the following disclaimer.
16 //
17 // 2. Redistributions in binary form must reproduce the above copyright
18 // notice, this list of conditions and the following disclaimer in the
19 // documentation and/or other materials provided with the distribution.
20 //
21 // 3. Neither the name of the Corporation nor the names of the
22 // contributors may be used to endorse or promote products derived from
23 // this software without specific prior written permission.
24 //
25 // THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
26 // EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
27 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
28 // PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
29 // CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
30 // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
31 // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
32 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
33 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
34 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
35 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
36 //
37 // Questions? Contact lead developers:
38 // Drew Kouri (dpkouri@sandia.gov) and
39 // Denis Ridzal (dridzal@sandia.gov)
40 //
41 // ************************************************************************
42 // @HEADER
43
44 /*! \file example_01.cpp
45 \brief Shows how to minimize Rosenbrock's function using Newton-Krylov.
46 \addtogroup examples_group
47 */
48
49 #define USE_HESSVEC 1
50
51 #include "ROL_Rosenbrock.hpp"
52 #include "ROL_Algorithm.hpp"
53 #include "ROL_LineSearchStep.hpp"
54 #include "ROL_StatusTest.hpp"
55 #include "ROL_Stream.hpp"
56 #include "Teuchos_GlobalMPISession.hpp"
57
58 #include <iostream>
59
60 typedef double RealT;
61
main(int argc,char * argv[])62 int main(int argc, char *argv[]) {
63
64 Teuchos::GlobalMPISession mpiSession(&argc, &argv);
65
66 // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
67 int iprint = argc - 1;
68 ROL::Ptr<std::ostream> outStream;
69 ROL::nullstream bhs; // outputs nothing
70 if (iprint > 0)
71 outStream = ROL::makePtrFromRef(std::cout);
72 else
73 outStream = ROL::makePtrFromRef(bhs);
74
75 int errorFlag = 0;
76
77 // *** Example body.
78
79 try {
80
81 ROL::ZOO::Objective_Rosenbrock<RealT> obj;
82 int dim = 100; // Set problem dimension. Must be even.
83
84 // Set parameters.
85 ROL::ParameterList parlist;
86 parlist.sublist("Step").sublist("Line Search").sublist("Descent Method").set("Type", "Newton-Krylov");
87 parlist.sublist("Status Test").set("Gradient Tolerance",1.e-12);
88 parlist.sublist("Status Test").set("Step Tolerance",1.e-14);
89 parlist.sublist("Status Test").set("Iteration Limit",100);
90
91 // Define algorithm.
92 ROL::Ptr<ROL::Step<RealT>>
93 step = ROL::makePtr<ROL::LineSearchStep<RealT>>(parlist);
94 ROL::Ptr<ROL::StatusTest<RealT>>
95 status = ROL::makePtr<ROL::StatusTest<RealT>>(parlist);
96 ROL::Algorithm<RealT> algo(step,status,false);
97
98 // Iteration Vector
99 ROL::Ptr<std::vector<RealT> > x_ptr = ROL::makePtr<std::vector<RealT>>(dim, 0.0);
100 // Set Initial Guess
101 for (int i=0; i<dim/2; i++) {
102 (*x_ptr)[2*i] = -1.2;
103 (*x_ptr)[2*i+1] = 1.0;
104 }
105 ROL::StdVector<RealT> x(x_ptr);
106
107 // Run Algorithm
108 algo.run(x, obj, true, *outStream);
109
110 // Get True Solution
111 ROL::Ptr<std::vector<RealT> > xtrue_ptr = ROL::makePtr<std::vector<RealT>>(dim, 1.0);
112 ROL::StdVector<RealT> xtrue(xtrue_ptr);
113
114 // Compute Error
115 x.axpy(-1.0, xtrue);
116 RealT abserr = x.norm();
117 RealT relerr = abserr/xtrue.norm();
118 *outStream << std::scientific << "\n Absolute Error: " << abserr;
119 *outStream << std::scientific << "\n Relative Error: " << relerr << "\n";
120 if ( relerr > sqrt(ROL::ROL_EPSILON<RealT>()) ) {
121 errorFlag += 1;
122 }
123 }
124 catch (std::logic_error& err) {
125 *outStream << err.what() << "\n";
126 errorFlag = -1000;
127 }; // end try
128
129 if (errorFlag != 0)
130 std::cout << "End Result: TEST FAILED\n";
131 else
132 std::cout << "End Result: TEST PASSED\n";
133
134 return 0;
135
136 }
137
138