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