|  | // Ceres Solver - A fast non-linear least squares minimizer | 
|  | // Copyright 2021 Google Inc. All rights reserved. | 
|  | // http://ceres-solver.org/ | 
|  | // | 
|  | // 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 | 
|  | // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR | 
|  | // 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 | 
|  | // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) | 
|  | // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | 
|  | // POSSIBILITY OF SUCH DAMAGE. | 
|  | // | 
|  | // Author: sameeragarwal@google.com (Sameer Agarwal) | 
|  |  | 
|  | #include "ceres/ceres.h" | 
|  | #include "glog/logging.h" | 
|  |  | 
|  | // f(x,y) = (1-x)^2 + 100(y - x^2)^2; | 
|  | struct Rosenbrock { | 
|  | template <typename T> | 
|  | bool operator()(const T* parameters, T* cost) const { | 
|  | const T x = parameters[0]; | 
|  | const T y = parameters[1]; | 
|  | cost[0] = (1.0 - x) * (1.0 - x) + 100.0 * (y - x * x) * (y - x * x); | 
|  | return true; | 
|  | } | 
|  |  | 
|  | static ceres::FirstOrderFunction* Create() { | 
|  | constexpr int kNumParameters = 2; | 
|  | return new ceres::AutoDiffFirstOrderFunction<Rosenbrock, kNumParameters>( | 
|  | new Rosenbrock); | 
|  | } | 
|  | }; | 
|  |  | 
|  | int main(int argc, char** argv) { | 
|  | google::InitGoogleLogging(argv[0]); | 
|  |  | 
|  | double parameters[2] = {-1.2, 1.0}; | 
|  |  | 
|  | ceres::GradientProblemSolver::Options options; | 
|  | options.minimizer_progress_to_stdout = true; | 
|  |  | 
|  | ceres::GradientProblemSolver::Summary summary; | 
|  | ceres::GradientProblem problem(Rosenbrock::Create()); | 
|  | ceres::Solve(options, problem, parameters, &summary); | 
|  |  | 
|  | std::cout << summary.FullReport() << "\n"; | 
|  | std::cout << "Initial x: " << -1.2 << " y: " << 1.0 << "\n"; | 
|  | std::cout << "Final   x: " << parameters[0] << " y: " << parameters[1] | 
|  | << "\n"; | 
|  | return 0; | 
|  | } |