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 // Minimize 0.5 (10 - x)^2 using jacobian matrix computed using 32 // numeric differentiation. 33 34 #include "ceres/ceres.h" 35 #include "glog/logging.h" 36 37 using ceres::NumericDiffCostFunction; 38 using ceres::CENTRAL; 39 using ceres::CostFunction; 40 using ceres::Problem; 41 using ceres::Solver; 42 using ceres::Solve; 43 44 // A cost functor that implements the residual r = 10 - x. 45 struct CostFunctor { 46 bool operator()(const double* const x, double* residual) const { 47 residual[0] = 10.0 - x[0]; 48 return true; 49 } 50 }; 51 52 int main(int argc, char** argv) { 53 google::InitGoogleLogging(argv[0]); 54 55 // The variable to solve for with its initial value. It will be 56 // mutated in place by the solver. 57 double x = 0.5; 58 const double initial_x = x; 59 60 // Build the problem. 61 Problem problem; 62 63 // Set up the only cost function (also known as residual). This uses 64 // numeric differentiation to obtain the derivative (jacobian). 65 CostFunction* cost_function = 66 new NumericDiffCostFunction<CostFunctor, CENTRAL, 1, 1> (new CostFunctor); 67 problem.AddResidualBlock(cost_function, NULL, &x); 68 69 // Run the solver! 70 Solver::Options options; 71 options.minimizer_progress_to_stdout = true; 72 Solver::Summary summary; 73 Solve(options, &problem, &summary); 74 75 std::cout << summary.BriefReport() << "\n"; 76 std::cout << "x : " << initial_x 77 << " -> " << x << "\n"; 78 return 0; 79 } 80
