blob: 7b02d7ae4024ec781f804d8a6c5d137c08613b8b [file] [log] [blame]
// 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;
class Rosenbrock final : public ceres::FirstOrderFunction {
public:
bool Evaluate(const double* parameters,
double* cost,
double* gradient) const override {
const double x = parameters[0];
const double y = parameters[1];
cost[0] = (1.0 - x) * (1.0 - x) + 100.0 * (y - x * x) * (y - x * x);
if (gradient) {
gradient[0] = -2.0 * (1.0 - x) - 200.0 * (y - x * x) * 2.0 * x;
gradient[1] = 200.0 * (y - x * x);
}
return true;
}
int NumParameters() const override { return 2; }
};
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(new Rosenbrock());
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;
}