mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
Sameer Agarwal
17dccef91b
This has been a long requested feature so that users can minimize functions using numeric differentiation. As part of this, I have also redone rosenbrock.cc, which now has three variants. rosenbrock.cc now uses automatic differentiation. rosenbrock_numeric_diff.cc uses numeric differentiation. rosenbrock_analytic_diff.cc uses analytic derivatives. This is analogus to how the helloworld example code is structured. The tutorial for GradientProblemSolver has also been updated to reflect this. https://github.com/ceres-solver/ceres-solver/issues/691 Change-Id: Ib0fb9e35127fe4c8299d4793bea3558722c70dd7
69 lines
2.8 KiB
C++
69 lines
2.8 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2021 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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#include "ceres/ceres.h"
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#include "glog/logging.h"
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// f(x,y) = (1-x)^2 + 100(y - x^2)^2;
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struct Rosenbrock {
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template <typename T>
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bool operator()(const T* parameters, T* cost) const {
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const T x = parameters[0];
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const T y = parameters[1];
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cost[0] = (1.0 - x) * (1.0 - x) + 100.0 * (y - x * x) * (y - x * x);
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return true;
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}
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static ceres::FirstOrderFunction* Create() {
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constexpr int kNumParameters = 2;
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return new ceres::AutoDiffFirstOrderFunction<Rosenbrock, kNumParameters>(
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new Rosenbrock);
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}
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};
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int main(int argc, char** argv) {
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google::InitGoogleLogging(argv[0]);
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double parameters[2] = {-1.2, 1.0};
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ceres::GradientProblemSolver::Options options;
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options.minimizer_progress_to_stdout = true;
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ceres::GradientProblemSolver::Summary summary;
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ceres::GradientProblem problem(Rosenbrock::Create());
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ceres::Solve(options, problem, parameters, &summary);
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std::cout << summary.FullReport() << "\n";
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std::cout << "Initial x: " << -1.2 << " y: " << 1.0 << "\n";
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std::cout << "Final x: " << parameters[0] << " y: " << parameters[1]
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<< "\n";
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return 0;
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}
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