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Open Source Computer Vision Library
https://opencv.org/
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101 lines
2.8 KiB
101 lines
2.8 KiB
#include "test_precomp.hpp" |
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#include <iostream> |
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TEST(Optim_LpSolver, regression_basic){ |
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cv::Mat A,B,z,etalon_z; |
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#if 1 |
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//cormen's example #1 |
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A=(cv::Mat_<double>(3,1)<<3,1,2); |
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B=(cv::Mat_<double>(3,4)<<1,1,3,30,2,2,5,24,4,1,2,36); |
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std::cout<<"here A goes\n"<<A<<"\n"; |
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cv::optim::solveLP(A,B,z); |
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std::cout<<"here z goes\n"<<z<<"\n"; |
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etalon_z=(cv::Mat_<double>(3,1)<<8,4,0); |
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ASSERT_EQ(cv::countNonZero(z!=etalon_z),0); |
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#endif |
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#if 1 |
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//cormen's example #2 |
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A=(cv::Mat_<double>(1,2)<<18,12.5); |
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B=(cv::Mat_<double>(3,3)<<1,1,20,1,0,20,0,1,16); |
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std::cout<<"here A goes\n"<<A<<"\n"; |
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cv::optim::solveLP(A,B,z); |
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std::cout<<"here z goes\n"<<z<<"\n"; |
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etalon_z=(cv::Mat_<double>(2,1)<<20,0); |
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ASSERT_EQ(cv::countNonZero(z!=etalon_z),0); |
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#endif |
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#if 1 |
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//cormen's example #3 |
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A=(cv::Mat_<double>(1,2)<<5,-3); |
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B=(cv::Mat_<double>(2,3)<<1,-1,1,2,1,2); |
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std::cout<<"here A goes\n"<<A<<"\n"; |
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cv::optim::solveLP(A,B,z); |
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std::cout<<"here z goes\n"<<z<<"\n"; |
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etalon_z=(cv::Mat_<double>(2,1)<<1,0); |
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ASSERT_EQ(cv::countNonZero(z!=etalon_z),0); |
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#endif |
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} |
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TEST(Optim_LpSolver, regression_init_unfeasible){ |
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cv::Mat A,B,z,etalon_z; |
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#if 1 |
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//cormen's example #4 - unfeasible |
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A=(cv::Mat_<double>(1,3)<<-1,-1,-1); |
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B=(cv::Mat_<double>(2,4)<<-2,-7.5,-3,-10000,-20,-5,-10,-30000); |
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std::cout<<"here A goes\n"<<A<<"\n"; |
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cv::optim::solveLP(A,B,z); |
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std::cout<<"here z goes\n"<<z<<"\n"; |
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etalon_z=(cv::Mat_<double>(3,1)<<1250,1000,0); |
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ASSERT_EQ(cv::countNonZero(z!=etalon_z),0); |
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#endif |
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} |
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TEST(Optim_LpSolver, regression_absolutely_unfeasible){ |
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cv::Mat A,B,z,etalon_z; |
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#if 1 |
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//trivial absolutely unfeasible example |
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A=(cv::Mat_<double>(1,1)<<1); |
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B=(cv::Mat_<double>(2,2)<<1,-1); |
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std::cout<<"here A goes\n"<<A<<"\n"; |
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int res=cv::optim::solveLP(A,B,z); |
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ASSERT_EQ(res,-1); |
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#endif |
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} |
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TEST(Optim_LpSolver, regression_multiple_solutions){ |
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cv::Mat A,B,z,etalon_z; |
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#if 1 |
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//trivial example with multiple solutions |
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A=(cv::Mat_<double>(2,1)<<1,1); |
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B=(cv::Mat_<double>(1,3)<<1,1,1); |
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std::cout<<"here A goes\n"<<A<<"\n"; |
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int res=cv::optim::solveLP(A,B,z); |
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printf("res=%d\n",res); |
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printf("scalar %g\n",z.dot(A)); |
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std::cout<<"here z goes\n"<<z<<"\n"; |
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ASSERT_EQ(res,1); |
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ASSERT_EQ(z.dot(A),1); |
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#endif |
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} |
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TEST(Optim_LpSolver, regression_cycling){ |
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cv::Mat A,B,z,etalon_z; |
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#if 1 |
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//example with cycling from http://people.orie.cornell.edu/miketodd/or630/SimplexCyclingExample.pdf |
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A=(cv::Mat_<double>(4,1)<<10,-57,-9,-24); |
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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); |
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std::cout<<"here A goes\n"<<A<<"\n"; |
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int res=cv::optim::solveLP(A,B,z); |
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printf("res=%d\n",res); |
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printf("scalar %g\n",z.dot(A)); |
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std::cout<<"here z goes\n"<<z<<"\n"; |
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ASSERT_EQ(z.dot(A),1); |
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//ASSERT_EQ(res,1); |
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#endif |
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}
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