modules/core/test/test_conjugate_gradient.cpp - 4.x - Alx89/OpenCV

modules/core/test/test_conjugate_gradient.cpp
108 строк4 KB
Alexander Alekhin
ts: refactor OpenCV tests
03 фев 2018, 22:39
03 фев 2018, 22:394a297a2
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#include "test_precomp.hpp"

namespace opencv_test { namespace {

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
}

}} // namespace