| // 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 |
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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: sameeragarwal@google.com (Sameer Agarwal) |
| // |
| // A simple example of optimizing a sampled function by using cubic |
| // interpolation. |
| |
| #include "ceres/ceres.h" |
| #include "ceres/cubic_interpolation.h" |
| #include "glog/logging.h" |
| |
| using ceres::Grid1D; |
| using ceres::CubicInterpolator; |
| using ceres::AutoDiffCostFunction; |
| using ceres::CostFunction; |
| using ceres::Problem; |
| using ceres::Solver; |
| using ceres::Solve; |
| |
| // 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, NULL, &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; |
| } |