| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2010, 2011, 2012 Google Inc. All rights reserved. |
| // http://code.google.com/p/ceres-solver/ |
| // |
| // Redistribution and use in source and binary forms, with or without |
| // modification, are permitted provided that the following conditions are met: |
| // |
| // * Redistributions of source code must retain the above copyright notice, |
| // this list of conditions and the following disclaimer. |
| // * Redistributions in binary form must reproduce the above copyright notice, |
| // this list of conditions and the following disclaimer in the documentation |
| // and/or other materials provided with the distribution. |
| // * Neither the name of Google Inc. nor the names of its contributors may be |
| // used to endorse or promote products derived from this software without |
| // specific prior written permission. |
| // |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
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| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN |
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| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
| // POSSIBILITY OF SUCH DAMAGE. |
| // |
| // Author: keir@google.com (Keir Mierle) |
| // |
| // Minimize 0.5 (10 - x)^2 using jacobian matrix computed using |
| // numeric differentiation. |
| |
| #include "ceres/ceres.h" |
| #include "glog/logging.h" |
| |
| using ceres::NumericDiffCostFunction; |
| using ceres::CENTRAL; |
| using ceres::CostFunction; |
| using ceres::Problem; |
| using ceres::Solver; |
| using ceres::Solve; |
| |
| // A cost functor that implements the residual r = 10 - x. |
| struct CostFunctor { |
| bool operator()(const double* const x, double* residual) const { |
| residual[0] = 10.0 - x[0]; |
| return true; |
| } |
| }; |
| |
| int main(int argc, char** argv) { |
| google::InitGoogleLogging(argv[0]); |
| |
| // The variable to solve for with its initial value. It will be |
| // mutated in place by the solver. |
| double x = 0.5; |
| const double initial_x = x; |
| |
| // Build the problem. |
| Problem problem; |
| |
| // Set up the only cost function (also known as residual). This uses |
| // numeric differentiation to obtain the derivative (jacobian). |
| CostFunction* cost_function = |
| new NumericDiffCostFunction<CostFunctor, CENTRAL, 1, 1> (new CostFunctor); |
| problem.AddResidualBlock(cost_function, NULL, &x); |
| |
| // Run the solver! |
| Solver::Options options; |
| options.minimizer_progress_to_stdout = true; |
| Solver::Summary summary; |
| Solve(options, &problem, &summary); |
| |
| std::cout << summary.BriefReport() << "\n"; |
| std::cout << "x : " << initial_x |
| << " -> " << x << "\n"; |
| return 0; |
| } |