Book a Demo!
CoCalc Logo Icon
StoreFeaturesDocsShareSupportNewsAboutPoliciesSign UpSign In
Tetragramm
GitHub Repository: Tetragramm/opencv
Path: blob/master/modules/core/test/test_conjugate_gradient.cpp
16337 views
1
/*M///////////////////////////////////////////////////////////////////////////////////////
2
//
3
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
4
//
5
// By downloading, copying, installing or using the software you agree to this license.
6
// If you do not agree to this license, do not download, install,
7
// copy or use the software.
8
//
9
//
10
// License Agreement
11
// For Open Source Computer Vision Library
12
//
13
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
14
// Third party copyrights are property of their respective owners.
15
//
16
// Redistribution and use in source and binary forms, with or without modification,
17
// are permitted provided that the following conditions are met:
18
//
19
// * Redistribution's of source code must retain the above copyright notice,
20
// this list of conditions and the following disclaimer.
21
//
22
// * Redistribution's in binary form must reproduce the above copyright notice,
23
// this list of conditions and the following disclaimer in the documentation
24
// and/or other materials provided with the distribution.
25
//
26
// * The name of the copyright holders may not be used to endorse or promote products
27
// derived from this software without specific prior written permission.
28
//
29
// This software is provided by the copyright holders and contributors "as is" and
30
// any express or implied warranties, including, but not limited to, the implied
31
// warranties of merchantability and fitness for a particular purpose are disclaimed.
32
// In no event shall the OpenCV Foundation or contributors be liable for any direct,
33
// indirect, incidental, special, exemplary, or consequential damages
34
// (including, but not limited to, procurement of substitute goods or services;
35
// loss of use, data, or profits; or business interruption) however caused
36
// and on any theory of liability, whether in contract, strict liability,
37
// or tort (including negligence or otherwise) arising in any way out of
38
// the use of this software, even if advised of the possibility of such damage.
39
//
40
//M*/
41
#include "test_precomp.hpp"
42
43
namespace opencv_test { namespace {
44
45
static void mytest(cv::Ptr<cv::ConjGradSolver> solver,cv::Ptr<cv::MinProblemSolver::Function> ptr_F,cv::Mat& x,
46
cv::Mat& etalon_x,double etalon_res){
47
solver->setFunction(ptr_F);
48
//int ndim=MAX(step.cols,step.rows);
49
double res=solver->minimize(x);
50
std::cout<<"res:\n\t"<<res<<std::endl;
51
std::cout<<"x:\n\t"<<x<<std::endl;
52
std::cout<<"etalon_res:\n\t"<<etalon_res<<std::endl;
53
std::cout<<"etalon_x:\n\t"<<etalon_x<<std::endl;
54
double tol = 1e-2;
55
ASSERT_TRUE(std::abs(res-etalon_res)<tol);
56
/*for(cv::Mat_<double>::iterator it1=x.begin<double>(),it2=etalon_x.begin<double>();it1!=x.end<double>();it1++,it2++){
57
ASSERT_TRUE(std::abs((*it1)-(*it2))<tol);
58
}*/
59
std::cout<<"--------------------------\n";
60
}
61
62
class SphereF_CG:public cv::MinProblemSolver::Function{
63
public:
64
int getDims() const { return 4; }
65
double calc(const double* x)const{
66
return x[0]*x[0]+x[1]*x[1]+x[2]*x[2]+x[3]*x[3];
67
}
68
// use automatically computed gradient
69
/*void getGradient(const double* x,double* grad){
70
for(int i=0;i<4;i++){
71
grad[i]=2*x[i];
72
}
73
}*/
74
};
75
class RosenbrockF_CG:public cv::MinProblemSolver::Function{
76
int getDims() const { return 2; }
77
double calc(const double* x)const{
78
return 100*(x[1]-x[0]*x[0])*(x[1]-x[0]*x[0])+(1-x[0])*(1-x[0]);
79
}
80
void getGradient(const double* x,double* grad){
81
grad[0]=-2*(1-x[0])-400*(x[1]-x[0]*x[0])*x[0];
82
grad[1]=200*(x[1]-x[0]*x[0]);
83
}
84
};
85
86
TEST(Core_ConjGradSolver, regression_basic){
87
cv::Ptr<cv::ConjGradSolver> solver=cv::ConjGradSolver::create();
88
#if 1
89
{
90
cv::Ptr<cv::MinProblemSolver::Function> ptr_F(new SphereF_CG());
91
cv::Mat x=(cv::Mat_<double>(4,1)<<50.0,10.0,1.0,-10.0),
92
etalon_x=(cv::Mat_<double>(1,4)<<0.0,0.0,0.0,0.0);
93
double etalon_res=0.0;
94
mytest(solver,ptr_F,x,etalon_x,etalon_res);
95
}
96
#endif
97
#if 1
98
{
99
cv::Ptr<cv::MinProblemSolver::Function> ptr_F(new RosenbrockF_CG());
100
cv::Mat x=(cv::Mat_<double>(2,1)<<0.0,0.0),
101
etalon_x=(cv::Mat_<double>(2,1)<<1.0,1.0);
102
double etalon_res=0.0;
103
mytest(solver,ptr_F,x,etalon_x,etalon_res);
104
}
105
#endif
106
}
107
108
}} // namespace
109
110