| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165 | // 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)#include "ceres/ceres.h"#include "glog/logging.h"// Data generated using the following octave code.//   randn('seed', 23497);//   m = 0.3;//   c = 0.1;//   x=[0:0.075:5];//   y = exp(m * x + c);//   noise = randn(size(x)) * 0.2;//   outlier_noise = rand(size(x)) < 0.05;//   y_observed = y + noise + outlier_noise;//   data = [x', y_observed'];const int kNumObservations = 67;const double data[] = {0.000000e+00, 1.133898e+00,7.500000e-02, 1.334902e+00,1.500000e-01, 1.213546e+00,2.250000e-01, 1.252016e+00,3.000000e-01, 1.392265e+00,3.750000e-01, 1.314458e+00,4.500000e-01, 1.472541e+00,5.250000e-01, 1.536218e+00,6.000000e-01, 1.355679e+00,6.750000e-01, 1.463566e+00,7.500000e-01, 1.490201e+00,8.250000e-01, 1.658699e+00,9.000000e-01, 1.067574e+00,9.750000e-01, 1.464629e+00,1.050000e+00, 1.402653e+00,1.125000e+00, 1.713141e+00,1.200000e+00, 1.527021e+00,1.275000e+00, 1.702632e+00,1.350000e+00, 1.423899e+00,1.425000e+00, 5.543078e+00, // Outlier point1.500000e+00, 5.664015e+00, // Outlier point1.575000e+00, 1.732484e+00,1.650000e+00, 1.543296e+00,1.725000e+00, 1.959523e+00,1.800000e+00, 1.685132e+00,1.875000e+00, 1.951791e+00,1.950000e+00, 2.095346e+00,2.025000e+00, 2.361460e+00,2.100000e+00, 2.169119e+00,2.175000e+00, 2.061745e+00,2.250000e+00, 2.178641e+00,2.325000e+00, 2.104346e+00,2.400000e+00, 2.584470e+00,2.475000e+00, 1.914158e+00,2.550000e+00, 2.368375e+00,2.625000e+00, 2.686125e+00,2.700000e+00, 2.712395e+00,2.775000e+00, 2.499511e+00,2.850000e+00, 2.558897e+00,2.925000e+00, 2.309154e+00,3.000000e+00, 2.869503e+00,3.075000e+00, 3.116645e+00,3.150000e+00, 3.094907e+00,3.225000e+00, 2.471759e+00,3.300000e+00, 3.017131e+00,3.375000e+00, 3.232381e+00,3.450000e+00, 2.944596e+00,3.525000e+00, 3.385343e+00,3.600000e+00, 3.199826e+00,3.675000e+00, 3.423039e+00,3.750000e+00, 3.621552e+00,3.825000e+00, 3.559255e+00,3.900000e+00, 3.530713e+00,3.975000e+00, 3.561766e+00,4.050000e+00, 3.544574e+00,4.125000e+00, 3.867945e+00,4.200000e+00, 4.049776e+00,4.275000e+00, 3.885601e+00,4.350000e+00, 4.110505e+00,4.425000e+00, 4.345320e+00,4.500000e+00, 4.161241e+00,4.575000e+00, 4.363407e+00,4.650000e+00, 4.161576e+00,4.725000e+00, 4.619728e+00,4.800000e+00, 4.737410e+00,4.875000e+00, 4.727863e+00,4.950000e+00, 4.669206e+00};using ceres::AutoDiffCostFunction;using ceres::CostFunction;using ceres::CauchyLoss;using ceres::Problem;using ceres::Solve;using ceres::Solver;struct ExponentialResidual {  ExponentialResidual(double x, double y)      : x_(x), y_(y) {}  template <typename T> bool operator()(const T* const m,                                        const T* const c,                                        T* residual) const {    residual[0] = y_ - exp(m[0] * x_ + c[0]);    return true;  } private:  const double x_;  const double y_;};int main(int argc, char** argv) {  google::InitGoogleLogging(argv[0]);  double m = 0.0;  double c = 0.0;  Problem problem;  for (int i = 0; i < kNumObservations; ++i) {    CostFunction* cost_function =        new AutoDiffCostFunction<ExponentialResidual, 1, 1, 1>(            new ExponentialResidual(data[2 * i], data[2 * i + 1]));    problem.AddResidualBlock(cost_function,                             new CauchyLoss(0.5),                             &m, &c);  }  Solver::Options options;  options.linear_solver_type = ceres::DENSE_QR;  options.minimizer_progress_to_stdout = true;  Solver::Summary summary;  Solve(options, &problem, &summary);  std::cout << summary.BriefReport() << "\n";  std::cout << "Initial m: " << 0.0 << " c: " << 0.0 << "\n";  std::cout << "Final   m: " << m << " c: " << c << "\n";  return 0;}
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