| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2015 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: |
| // |
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| // 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 |
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| // |
| // Author: keir@google.com (Keir Mierle) |
| // |
| // A simple example of using the Ceres minimizer. |
| // |
| // Minimize 0.5 (10 - x)^2 using analytic jacobian matrix. |
| |
| #include <vector> |
| #include "ceres/ceres.h" |
| #include "glog/logging.h" |
| |
| using ceres::CostFunction; |
| using ceres::SizedCostFunction; |
| using ceres::Problem; |
| using ceres::Solver; |
| using ceres::Solve; |
| |
| // A CostFunction implementing analytically derivatives for the |
| // function f(x) = 10 - x. |
| class QuadraticCostFunction |
| : public SizedCostFunction<1 /* number of residuals */, |
| 1 /* size of first parameter */> { |
| public: |
| virtual ~QuadraticCostFunction() {} |
| |
| virtual bool Evaluate(double const* const* parameters, |
| double* residuals, |
| double** jacobians) const { |
| double x = parameters[0][0]; |
| |
| // f(x) = 10 - x. |
| residuals[0] = 10 - x; |
| |
| // f'(x) = -1. Since there's only 1 parameter and that parameter |
| // has 1 dimension, there is only 1 element to fill in the |
| // jacobians. |
| // |
| // Since the Evaluate function can be called with the jacobians |
| // pointer equal to NULL, the Evaluate function must check to see |
| // if jacobians need to be computed. |
| // |
| // For this simple problem it is overkill to check if jacobians[0] |
| // is NULL, but in general when writing more complex |
| // CostFunctions, it is possible that Ceres may only demand the |
| // derivatives w.r.t. a subset of the parameter blocks. |
| if (jacobians != NULL && jacobians[0] != NULL) { |
| jacobians[0][0] = -1; |
| } |
| |
| 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). |
| CostFunction* cost_function = new QuadraticCostFunction; |
| 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; |
| } |