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 // 5 // Redistribution and use in source and binary forms, with or without 6 // modification, are permitted provided that the following conditions are met: 7 // 8 // * Redistributions of source code must retain the above copyright notice, 9 // this list of conditions and the following disclaimer. 10 // * Redistributions in binary form must reproduce the above copyright notice, 11 // this list of conditions and the following disclaimer in the documentation 12 // and/or other materials provided with the distribution. 13 // * Neither the name of Google Inc. nor the names of its contributors may be 14 // used to endorse or promote products derived from this software without 15 // specific prior written permission. 16 // 17 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 18 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 19 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 20 // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE 21 // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 22 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 23 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS 24 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN 25 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 26 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 27 // POSSIBILITY OF SUCH DAMAGE. 28 // 29 // Author: keir (at) google.com (Keir Mierle) 30 // 31 // A simple example of using the Ceres minimizer. 32 // 33 // Minimize 0.5 (10 - x)^2 using analytic jacobian matrix. 34 35 #include <vector> 36 #include "ceres/ceres.h" 37 #include "gflags/gflags.h" 38 #include "glog/logging.h" 39 40 using ceres::SizedCostFunction; 41 using ceres::Problem; 42 using ceres::Solver; 43 using ceres::Solve; 44 45 class SimpleCostFunction 46 : public SizedCostFunction<1 /* number of residuals */, 47 1 /* size of first parameter */> { 48 public: 49 virtual ~SimpleCostFunction() {} 50 virtual bool Evaluate(double const* const* parameters, 51 double* residuals, 52 double** jacobians) const { 53 double x = parameters[0][0]; 54 55 // f(x) = 10 - x. 56 residuals[0] = 10 - x; 57 58 // f'(x) = -1. Since there's only 1 parameter and that parameter 59 // has 1 dimension, there is only 1 element to fill in the 60 // jacobians. 61 if (jacobians != NULL && jacobians[0] != NULL) { 62 jacobians[0][0] = -1; 63 } 64 return true; 65 } 66 }; 67 68 int main(int argc, char** argv) { 69 google::ParseCommandLineFlags(&argc, &argv, true); 70 google::InitGoogleLogging(argv[0]); 71 72 // The variable with its initial value that we will be solving for. 73 double x = 5.0; 74 75 // Build the problem. 76 Problem problem; 77 // Set up the only cost function (also known as residual). 78 problem.AddResidualBlock(new SimpleCostFunction, NULL, &x); 79 80 // Run the solver! 81 Solver::Options options; 82 options.max_num_iterations = 10; 83 options.linear_solver_type = ceres::DENSE_QR; 84 options.minimizer_progress_to_stdout = true; 85 Solver::Summary summary; 86 Solve(options, &problem, &summary); 87 std::cout << summary.BriefReport() << "\n"; 88 std::cout << "x : 5.0 -> " << x << "\n"; 89 return 0; 90 } 91
