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/*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) 2013, OpenCV Foundation, 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 OpenCV Foundation 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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#include "test_precomp.hpp"
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#include <cstdlib>
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static void mytest(cv::Ptr<cv::optim::ConjGradSolver> solver,cv::Ptr<cv::optim::Solver::Function> ptr_F,cv::Mat& x,
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cv::Mat& etalon_x,double etalon_res){
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solver->setFunction(ptr_F);
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//int ndim=MAX(step.cols,step.rows);
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double res=solver->minimize(x);
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std::cout<<"res:\n\t"<<res<<std::endl;
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std::cout<<"x:\n\t"<<x<<std::endl;
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std::cout<<"etalon_res:\n\t"<<etalon_res<<std::endl;
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std::cout<<"etalon_x:\n\t"<<etalon_x<<std::endl;
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double tol=solver->getTermCriteria().epsilon;
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ASSERT_TRUE(std::abs(res-etalon_res)<tol);
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/*for(cv::Mat_<double>::iterator it1=x.begin<double>(),it2=etalon_x.begin<double>();it1!=x.end<double>();it1++,it2++){
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ASSERT_TRUE(std::abs((*it1)-(*it2))<tol);
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}*/
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std::cout<<"--------------------------\n";
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}
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class SphereF:public cv::optim::Solver::Function{
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public:
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double calc(const double* x)const{
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return x[0]*x[0]+x[1]*x[1]+x[2]*x[2]+x[3]*x[3];
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}
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void getGradient(const double* x,double* grad){
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for(int i=0;i<4;i++){
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grad[i]=2*x[i];
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}
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}
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};
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class RosenbrockF:public cv::optim::Solver::Function{
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double calc(const double* x)const{
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return 100*(x[1]-x[0]*x[0])*(x[1]-x[0]*x[0])+(1-x[0])*(1-x[0]);
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}
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void getGradient(const double* x,double* grad){
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grad[0]=-2*(1-x[0])-400*(x[1]-x[0]*x[0])*x[0];
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grad[1]=200*(x[1]-x[0]*x[0]);
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}
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};
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TEST(Optim_ConjGrad, regression_basic){
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cv::Ptr<cv::optim::ConjGradSolver> solver=cv::optim::createConjGradSolver();
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#if 1
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{
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cv::Ptr<cv::optim::Solver::Function> ptr_F(new SphereF());
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cv::Mat x=(cv::Mat_<double>(4,1)<<50.0,10.0,1.0,-10.0),
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etalon_x=(cv::Mat_<double>(1,4)<<0.0,0.0,0.0,0.0);
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double etalon_res=0.0;
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mytest(solver,ptr_F,x,etalon_x,etalon_res);
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}
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#endif
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#if 1
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{
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cv::Ptr<cv::optim::Solver::Function> ptr_F(new RosenbrockF());
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cv::Mat x=(cv::Mat_<double>(2,1)<<0.0,0.0),
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etalon_x=(cv::Mat_<double>(2,1)<<1.0,1.0);
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double etalon_res=0.0;
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mytest(solver,ptr_F,x,etalon_x,etalon_res);
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}
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#endif
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}
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