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  1. // Ceres Solver - A fast non-linear least squares minimizer
  2. // Copyright 2015 Google Inc. All rights reserved.
  3. // http://ceres-solver.org/
  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@google.com (Keir Mierle)
  30. //
  31. // A simple example of using the Ceres minimizer.
  32. //
  33. // Minimize 0.5 (10 - x)^2 using jacobian matrix computed using
  34. // automatic differentiation.
  35. #include "ceres/ceres.h"
  36. #include "glog/logging.h"
  37. using ceres::AutoDiffCostFunction;
  38. using ceres::CostFunction;
  39. using ceres::Problem;
  40. using ceres::Solver;
  41. using ceres::Solve;
  42. // A templated cost functor that implements the residual r = 10 -
  43. // x. The method operator() is templated so that we can then use an
  44. // automatic differentiation wrapper around it to generate its
  45. // derivatives.
  46. struct CostFunctor {
  47. template <typename T> bool operator()(const T* const x, T* residual) const {
  48. residual[0] = T(10.0) - x[0];
  49. return true;
  50. }
  51. };
  52. int main(int argc, char** argv) {
  53. google::InitGoogleLogging(argv[0]);
  54. // The variable to solve for with its initial value. It will be
  55. // mutated in place by the solver.
  56. double x = 0.5;
  57. const double initial_x = x;
  58. // Build the problem.
  59. Problem problem;
  60. // Set up the only cost function (also known as residual). This uses
  61. // auto-differentiation to obtain the derivative (jacobian).
  62. CostFunction* cost_function =
  63. new AutoDiffCostFunction<CostFunctor, 1, 1>(new CostFunctor);
  64. problem.AddResidualBlock(cost_function, NULL, &x);
  65. // Run the solver!
  66. Solver::Options options;
  67. options.minimizer_progress_to_stdout = true;
  68. Solver::Summary summary;
  69. Solve(options, &problem, &summary);
  70. std::cout << summary.BriefReport() << "\n";
  71. std::cout << "x : " << initial_x
  72. << " -> " << x << "\n";
  73. return 0;
  74. }