b216c0940c
Added LPSolver class together with two nested classes: LPFunction and LPConstraints. These represent function to be maximized and constraints imposed respectively. They are implementations of interfaces Function and Constraints respectively (latter ones are nested classes of Solver interface, which is generic interface for all optimization algorithms to be implemented within this project). The next step is to implement the simplex algorithm! First, we shall implement it for the case of constraints of the form Ax<=b and x>=0. Then, we shall extend the sets of problems that can be handled by the conversion to the one we've handled already. Finally, we shale concentrate on numerical stability and efficiency.
114 lines
4.4 KiB
C++
114 lines
4.4 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2008-2012, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's 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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//
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// * Redistribution's 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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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_OPTIM_HPP__
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#define __OPENCV_OPTIM_HPP__
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#include <iostream>
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#include "opencv2/core.hpp"
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#include "opencv2/core/mat.hpp"
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/*! \namespace cv
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Namespace where all the C++ OpenCV functionality resides
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*/
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namespace cv{namespace optim
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{
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//! generic class for optimization algorithms */
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class CV_EXPORTS Solver : public Algorithm /* Algorithm is the base OpenCV class */
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{
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public:
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class CV_EXPORTS Function
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{
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public:
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virtual ~Function(){}
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virtual double calc(InputArray args) const = 0;
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};
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class CV_EXPORTS Constraints
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{
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public:
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virtual ~Constraints(){}
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};
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//! could be reused for all the generic algorithms like downhill simplex. Return value is the maximum value of a function*/
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virtual double solve(const Function& F,const Constraints& C, OutputArray result) const = 0;
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/*virtual void setTermCriteria(const TermCriteria& criteria) = 0;
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virtual TermCriteria getTermCriteria() = 0;*/
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// more detailed API to be defined later ...
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};
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class CV_EXPORTS LPSolver : public Solver
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{
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public:
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class CV_EXPORTS LPFunction:public Solver::Function
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{
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cv::Mat z;
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public:
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//! Note, that this class is supposed to be immutable, so it's ok to make only a shallow copy of z_in.*/
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LPFunction(cv::Mat z_in):z(z_in){}
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~LPFunction(){};
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const cv::Mat& getz()const{return z;}
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double calc(InputArray args)const;
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};
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//!This class represents constraints for linear problem. There are two matrix stored: m-by-n matrix A and n-by-1 column-vector b.
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//!What this represents is the set of constraints Ax\leq b and x\geq 0. It can be shown that any set of linear constraints can be converted
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//!this form and **we shall create various constructors for this class that will perform these conversions**.
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class CV_EXPORTS LPConstraints:public Solver::Constraints
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{
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cv::Mat A,b;
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public:
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~LPConstraints(){};
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//! Note, that this class is supposed to be immutable, so it's ok to make only a shallow copy of A_in and b_in.*/
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LPConstraints(cv::Mat A_in, cv::Mat b_in):A(A_in),b(b_in){}
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const cv::Mat& getA()const{return A;}
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const cv::Mat& getb()const{return b;}
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};
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LPSolver(){}
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double solve(const Function& F,const Constraints& C, OutputArray result)const;
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};
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}}// cv
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#endif
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