opencv/modules/optim/test/test_lpsolver.cpp
Alex Leontiev ba537a95db Preparation for pull request
Additional cleaning for simplex method, removing the parts that are
currently unused. Removing developer's notes. Trying to reach production
level.
2013-07-11 09:31:10 +03:00

115 lines
3.3 KiB
C++

#include "test_precomp.hpp"
#include "opencv2/optim.hpp"
TEST(Optim_LpSolver, regression_basic){
cv::Mat A,B,z,etalon_z;
if(true){
//cormen's example #1
A=(cv::Mat_<double>(1,3)<<3,1,2);
B=(cv::Mat_<double>(3,4)<<1,1,3,30,2,2,5,24,4,1,2,36);
std::cout<<"here A goes\n"<<A<<"\n";
cv::optim::solveLP(A,B,z);
std::cout<<"here z goes\n"<<z<<"\n";
etalon_z=(cv::Mat_<double>(1,3)<<8,4,0);
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
}
if(true){
//cormen's example #2
A=(cv::Mat_<double>(1,2)<<18,12.5);
B=(cv::Mat_<double>(3,3)<<1,1,20,1,0,20,0,1,16);
std::cout<<"here A goes\n"<<A<<"\n";
cv::optim::solveLP(A,B,z);
std::cout<<"here z goes\n"<<z<<"\n";
etalon_z=(cv::Mat_<double>(1,2)<<20,0);
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
}
if(true){
//cormen's example #3
A=(cv::Mat_<double>(1,2)<<5,-3);
B=(cv::Mat_<double>(2,3)<<1,-1,1,2,1,2);
std::cout<<"here A goes\n"<<A<<"\n";
cv::optim::solveLP(A,B,z);
std::cout<<"here z goes\n"<<z<<"\n";
etalon_z=(cv::Mat_<double>(1,2)<<1,0);
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
}
}
TEST(Optim_LpSolver, regression_init_unfeasible){
cv::Mat A,B,z,etalon_z;
if(true){
//cormen's example #4 - unfeasible
A=(cv::Mat_<double>(1,3)<<-1,-1,-1);
B=(cv::Mat_<double>(2,4)<<-2,-7.5,-3,-10000,-20,-5,-10,-30000);
std::cout<<"here A goes\n"<<A<<"\n";
cv::optim::solveLP(A,B,z);
std::cout<<"here z goes\n"<<z<<"\n";
etalon_z=(cv::Mat_<double>(1,3)<<1250,1000,0);
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
}
}
TEST(Optim_LpSolver, regression_absolutely_unfeasible){
cv::Mat A,B,z,etalon_z;
if(true){
//trivial absolutely unfeasible example
A=(cv::Mat_<double>(1,1)<<1);
B=(cv::Mat_<double>(2,2)<<1,-1);
std::cout<<"here A goes\n"<<A<<"\n";
int res=cv::optim::solveLP(A,B,z);
ASSERT_EQ(res,-1);
}
}
TEST(Optim_LpSolver, regression_multiple_solutions){
cv::Mat A,B,z,etalon_z;
if(true){
//trivial example with multiple solutions
A=(cv::Mat_<double>(1,2)<<1,1);
B=(cv::Mat_<double>(1,3)<<1,1,1);
std::cout<<"here A goes\n"<<A<<"\n";
int res=cv::optim::solveLP(A,B,z);
printf("res=%d\n",res);
printf("scalar %g\n",z.dot(A));
std::cout<<"here z goes\n"<<z<<"\n";
ASSERT_EQ(res,1);
ASSERT_EQ(z.dot(A),1);
}
if(false){
//cormen's example from chapter about initialize_simplex
//online solver told it has inf many solutions, but I'm not sure
A=(cv::Mat_<double>(1,2)<<2,-1);
B=(cv::Mat_<double>(2,3)<<2,-1,2,1,-5,-4);
std::cout<<"here A goes\n"<<A<<"\n";
int res=cv::optim::solveLP(A,B,z);
printf("res=%d\n",res);
printf("scalar %g\n",z.dot(A));
std::cout<<"here z goes\n"<<z<<"\n";
ASSERT_EQ(res,1);
}
}
TEST(Optim_LpSolver, regression_cycling){
cv::Mat A,B,z,etalon_z;
if(true){
//example with cycling from http://people.orie.cornell.edu/miketodd/or630/SimplexCyclingExample.pdf
A=(cv::Mat_<double>(1,4)<<10,-57,-9,-24);
B=(cv::Mat_<double>(3,5)<<0.5,-5.5,-2.5,9,0,0.5,-1.5,-0.5,1,0,1,0,0,0,1);
std::cout<<"here A goes\n"<<A<<"\n";
int res=cv::optim::solveLP(A,B,z);
printf("res=%d\n",res);
printf("scalar %g\n",z.dot(A));
std::cout<<"here z goes\n"<<z<<"\n";
ASSERT_EQ(z.dot(A),1);
//ASSERT_EQ(res,1);
}
}