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Diffstat (limited to 'extern/ceres/include/ceres/gradient_problem.h')
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diff --git a/extern/ceres/include/ceres/gradient_problem.h b/extern/ceres/include/ceres/gradient_problem.h new file mode 100644 index 00000000000..1226a4cd895 --- /dev/null +++ b/extern/ceres/include/ceres/gradient_problem.h @@ -0,0 +1,127 @@ +// 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) + +#ifndef CERES_PUBLIC_GRADIENT_PROBLEM_H_ +#define CERES_PUBLIC_GRADIENT_PROBLEM_H_ + +#include "ceres/internal/macros.h" +#include "ceres/internal/port.h" +#include "ceres/internal/scoped_ptr.h" +#include "ceres/local_parameterization.h" + +namespace ceres { + +class FirstOrderFunction; + +// Instances of GradientProblem represent general non-linear +// optimization problems that must be solved using just the value of +// the objective function and its gradient. Unlike the Problem class, +// which can only be used to model non-linear least squares problems, +// instances of GradientProblem not restricted in the form of the +// objective function. +// +// Structurally GradientProblem is a composition of a +// FirstOrderFunction and optionally a LocalParameterization. +// +// The FirstOrderFunction is responsible for evaluating the cost and +// gradient of the objective function. +// +// The LocalParameterization is responsible for going back and forth +// between the ambient space and the local tangent space. (See +// local_parameterization.h for more details). When a +// LocalParameterization is not provided, then the tangent space is +// assumed to coincide with the ambient Euclidean space that the +// gradient vector lives in. +// +// Example usage: +// +// The following demonstrate the problem construction for Rosenbrock's function +// +// f(x,y) = (1-x)^2 + 100(y - x^2)^2; +// +// class Rosenbrock : public ceres::FirstOrderFunction { +// public: +// virtual ~Rosenbrock() {} +// +// virtual bool Evaluate(const double* parameters, +// double* cost, +// double* gradient) const { +// 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 != NULL) { +// gradient[0] = -2.0 * (1.0 - x) - 200.0 * (y - x * x) * 2.0 * x; +// gradient[1] = 200.0 * (y - x * x); +// } +// return true; +// }; +// +// virtual int NumParameters() const { return 2; }; +// }; +// +// ceres::GradientProblem problem(new Rosenbrock()); +class CERES_EXPORT GradientProblem { + public: + // Takes ownership of the function. + explicit GradientProblem(FirstOrderFunction* function); + + // Takes ownership of the function and the parameterization. + GradientProblem(FirstOrderFunction* function, + LocalParameterization* parameterization); + + int NumParameters() const; + int NumLocalParameters() const; + + // This call is not thread safe. + bool Evaluate(const double* parameters, double* cost, double* gradient) const; + bool Plus(const double* x, const double* delta, double* x_plus_delta) const; + + private: + internal::scoped_ptr<FirstOrderFunction> function_; + internal::scoped_ptr<LocalParameterization> parameterization_; + internal::scoped_array<double> scratch_; +}; + +// A FirstOrderFunction object implements the evaluation of a function +// and its gradient. +class CERES_EXPORT FirstOrderFunction { + public: + virtual ~FirstOrderFunction() {} + // cost is never NULL. gradient may be null. + virtual bool Evaluate(const double* const parameters, + double* cost, + double* gradient) const = 0; + virtual int NumParameters() const = 0; +}; + +} // namespace ceres + +#endif // CERES_PUBLIC_GRADIENT_PROBLEM_H_ |