| // 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: | |
| // | |
| // * 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) | |
| // | |
| // A simple example of optimizing a sampled function by using cubic | |
| // interpolation. | |
| using ceres::AutoDiffCostFunction; | |
| using ceres::CostFunction; | |
| using ceres::CubicInterpolator; | |
| using ceres::Grid1D; | |
| using ceres::Problem; | |
| using ceres::Solve; | |
| using ceres::Solver; | |
| // A simple cost functor that interfaces an interpolated table of | |
| // values with automatic differentiation. | |
| struct InterpolatedCostFunctor { | |
| explicit InterpolatedCostFunctor( | |
| const CubicInterpolator<Grid1D<double>>& interpolator) | |
| : interpolator_(interpolator) {} | |
| template <typename T> | |
| bool operator()(const T* x, T* residuals) const { | |
| interpolator_.Evaluate(*x, residuals); | |
| return true; | |
| } | |
| static CostFunction* Create( | |
| const CubicInterpolator<Grid1D<double>>& interpolator) { | |
| return new AutoDiffCostFunction<InterpolatedCostFunctor, 1, 1>( | |
| new InterpolatedCostFunctor(interpolator)); | |
| } | |
| private: | |
| const CubicInterpolator<Grid1D<double>>& interpolator_; | |
| }; | |
| int main(int argc, char** argv) { | |
| google::InitGoogleLogging(argv[0]); | |
| // Evaluate the function f(x) = (x - 4.5)^2; | |
| const int kNumSamples = 10; | |
| double values[kNumSamples]; | |
| for (int i = 0; i < kNumSamples; ++i) { | |
| values[i] = (i - 4.5) * (i - 4.5); | |
| } | |
| Grid1D<double> array(values, 0, kNumSamples); | |
| CubicInterpolator<Grid1D<double>> interpolator(array); | |
| double x = 1.0; | |
| Problem problem; | |
| CostFunction* cost_function = InterpolatedCostFunctor::Create(interpolator); | |
| problem.AddResidualBlock(cost_function, nullptr, &x); | |
| Solver::Options options; | |
| options.minimizer_progress_to_stdout = true; | |
| Solver::Summary summary; | |
| Solve(options, &problem, &summary); | |
| std::cout << summary.BriefReport() << "\n"; | |
| std::cout << "Expected x: 4.5. Actual x : " << x << std::endl; | |
| return 0; | |
| } | |