1 // Ceres Solver - A fast non-linear least squares minimizer
2 // Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
3 // http://code.google.com/p/ceres-solver/
4 //
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28 //
29 // Author: sameeragarwal@google.com (Sameer Agarwal)
30 //
31 // An example program that minimizes Powell's singular function.
32 //
33 //   F = 1/2 (f1^2 + f2^2 + f3^2 + f4^2)
34 //
35 //   f1 = x1 + 10*x2;
36 //   f2 = sqrt(5) * (x3 - x4)
37 //   f3 = (x2 - 2*x3)^2
38 //   f4 = sqrt(10) * (x1 - x4)^2
39 //
40 // The starting values are x1 = 3, x2 = -1, x3 = 0, x4 = 1.
41 // The minimum is 0 at (x1, x2, x3, x4) = 0.
42 //
43 // From: Testing Unconstrained Optimization Software by Jorge J. More, Burton S.
44 // Garbow and Kenneth E. Hillstrom in ACM Transactions on Mathematical Software,
45 // Vol 7(1), March 1981.
46 
47 #include <vector>
48 #include "ceres/ceres.h"
49 #include "gflags/gflags.h"
50 #include "glog/logging.h"
51 
52 using ceres::AutoDiffCostFunction;
53 using ceres::CostFunction;
54 using ceres::Problem;
55 using ceres::Solver;
56 using ceres::Solve;
57 
58 struct F1 {
operator ()F159   template <typename T> bool operator()(const T* const x1,
60                                         const T* const x2,
61                                         T* residual) const {
62     // f1 = x1 + 10 * x2;
63     residual[0] = x1[0] + T(10.0) * x2[0];
64     return true;
65   }
66 };
67 
68 struct F2 {
operator ()F269   template <typename T> bool operator()(const T* const x3,
70                                         const T* const x4,
71                                         T* residual) const {
72     // f2 = sqrt(5) (x3 - x4)
73     residual[0] = T(sqrt(5.0)) * (x3[0] - x4[0]);
74     return true;
75   }
76 };
77 
78 struct F3 {
operator ()F379   template <typename T> bool operator()(const T* const x2,
80                                         const T* const x4,
81                                         T* residual) const {
82     // f3 = (x2 - 2 x3)^2
83     residual[0] = (x2[0] - T(2.0) * x4[0]) * (x2[0] - T(2.0) * x4[0]);
84     return true;
85   }
86 };
87 
88 struct F4 {
operator ()F489   template <typename T> bool operator()(const T* const x1,
90                                         const T* const x4,
91                                         T* residual) const {
92     // f4 = sqrt(10) (x1 - x4)^2
93     residual[0] = T(sqrt(10.0)) * (x1[0] - x4[0]) * (x1[0] - x4[0]);
94     return true;
95   }
96 };
97 
98 DEFINE_string(minimizer, "trust_region",
99               "Minimizer type to use, choices are: line_search & trust_region");
100 
main(int argc,char ** argv)101 int main(int argc, char** argv) {
102   google::ParseCommandLineFlags(&argc, &argv, true);
103   google::InitGoogleLogging(argv[0]);
104 
105   double x1 =  3.0;
106   double x2 = -1.0;
107   double x3 =  0.0;
108   double x4 =  1.0;
109 
110   Problem problem;
111   // Add residual terms to the problem using the using the autodiff
112   // wrapper to get the derivatives automatically. The parameters, x1 through
113   // x4, are modified in place.
114   problem.AddResidualBlock(new AutoDiffCostFunction<F1, 1, 1, 1>(new F1),
115                            NULL,
116                            &x1, &x2);
117   problem.AddResidualBlock(new AutoDiffCostFunction<F2, 1, 1, 1>(new F2),
118                            NULL,
119                            &x3, &x4);
120   problem.AddResidualBlock(new AutoDiffCostFunction<F3, 1, 1, 1>(new F3),
121                            NULL,
122                            &x2, &x3);
123   problem.AddResidualBlock(new AutoDiffCostFunction<F4, 1, 1, 1>(new F4),
124                            NULL,
125                            &x1, &x4);
126 
127   Solver::Options options;
128   LOG_IF(FATAL, !ceres::StringToMinimizerType(FLAGS_minimizer,
129                                               &options.minimizer_type))
130       << "Invalid minimizer: " << FLAGS_minimizer
131       << ", valid options are: trust_region and line_search.";
132 
133   options.max_num_iterations = 100;
134   options.linear_solver_type = ceres::DENSE_QR;
135   options.minimizer_progress_to_stdout = true;
136 
137   std::cout << "Initial x1 = " << x1
138             << ", x2 = " << x2
139             << ", x3 = " << x3
140             << ", x4 = " << x4
141             << "\n";
142 
143   // Run the solver!
144   Solver::Summary summary;
145   Solve(options, &problem, &summary);
146 
147   std::cout << summary.FullReport() << "\n";
148   std::cout << "Final x1 = " << x1
149             << ", x2 = " << x2
150             << ", x3 = " << x3
151             << ", x4 = " << x4
152             << "\n";
153   return 0;
154 }
155