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126 lines
4.7 KiB
126 lines
4.7 KiB
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2023 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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#ifndef CERES_PUBLIC_GRADIENT_PROBLEM_H_
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#define CERES_PUBLIC_GRADIENT_PROBLEM_H_
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#include <memory>
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#include "ceres/first_order_function.h"
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#include "ceres/internal/disable_warnings.h"
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#include "ceres/internal/export.h"
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#include "ceres/manifold.h"
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namespace ceres {
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class FirstOrderFunction;
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// Instances of GradientProblem represent general non-linear
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// optimization problems that must be solved using just the value of
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// the objective function and its gradient.
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// Unlike the Problem class, which can only be used to model non-linear least
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// squares problems, instances of GradientProblem are not restricted in the form
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// of the objective function.
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//
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// Structurally GradientProblem is a composition of a FirstOrderFunction and
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// optionally a Manifold.
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//
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// The FirstOrderFunction is responsible for evaluating the cost and gradient of
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// the objective function.
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//
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// The Manifold is responsible for going back and forth between the ambient
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// space and the local tangent space. (See manifold.h for more details). When a
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// Manifold is not provided, then the tangent space is assumed to coincide with
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// the ambient Euclidean space that the gradient vector lives in.
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//
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// Example usage:
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//
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// The following demonstrate the problem construction for Rosenbrock's function
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//
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// f(x,y) = (1-x)^2 + 100(y - x^2)^2;
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//
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// class Rosenbrock : public ceres::FirstOrderFunction {
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// public:
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// virtual ~Rosenbrock() {}
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//
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// virtual bool Evaluate(const double* parameters,
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// double* cost,
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// double* gradient) const {
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// const double x = parameters[0];
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// const double y = parameters[1];
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//
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// cost[0] = (1.0 - x) * (1.0 - x) + 100.0 * (y - x * x) * (y - x * x);
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// if (gradient != nullptr) {
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// gradient[0] = -2.0 * (1.0 - x) - 200.0 * (y - x * x) * 2.0 * x;
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// gradient[1] = 200.0 * (y - x * x);
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// }
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// return true;
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// };
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//
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// virtual int NumParameters() const { return 2; };
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// };
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//
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// ceres::GradientProblem problem(new Rosenbrock());
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class CERES_EXPORT GradientProblem {
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public:
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// Takes ownership of the function.
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explicit GradientProblem(FirstOrderFunction* function);
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// Takes ownership of the function and the manifold.
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GradientProblem(FirstOrderFunction* function, Manifold* manifold);
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int NumParameters() const;
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// Dimension of the manifold (and its tangent space).
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int NumTangentParameters() const;
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// This call is not thread safe.
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bool Evaluate(const double* parameters, double* cost, double* gradient) const;
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bool Plus(const double* x, const double* delta, double* x_plus_delta) const;
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const FirstOrderFunction* function() const { return function_.get(); }
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FirstOrderFunction* mutable_function() { return function_.get(); }
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const Manifold* manifold() const { return manifold_.get(); }
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Manifold* mutable_manifold() { return manifold_.get(); }
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private:
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std::unique_ptr<FirstOrderFunction> function_;
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std::unique_ptr<Manifold> manifold_;
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std::unique_ptr<double[]> scratch_;
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};
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} // namespace ceres
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#include "ceres/internal/reenable_warnings.h"
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#endif // CERES_PUBLIC_GRADIENT_PROBLEM_H_
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