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Open Source Computer Vision Library
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61 lines
2.0 KiB
61 lines
2.0 KiB
#include "test_precomp.hpp" |
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#include "opencv2/optim.hpp" |
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TEST(Optim_LpSolver, regression) |
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{ |
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cv::Mat A,B,z,etalon_z; |
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if(true){ |
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//cormen's example #1 |
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A=(cv::Mat_<double>(1,3)<<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>(1,3)<<8,4,0); |
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ASSERT_EQ(cv::countNonZero(z!=etalon_z),0); |
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} |
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if(true){ |
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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>(1,2)<<20,0); |
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ASSERT_EQ(cv::countNonZero(z!=etalon_z),0); |
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} |
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if(true){ |
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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>(1,2)<<1,0); |
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ASSERT_EQ(cv::countNonZero(z!=etalon_z),0); |
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} |
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if(false){ |
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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>(1,2)<<1,0); |
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ASSERT_EQ(cv::countNonZero(z!=etalon_z),0); |
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} |
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} |
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//TODO |
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// get optimal solution from initial (0,0,...,0) - DONE |
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// milestone: pass first test (wo initial solution) - DONE |
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// learn how to get initial solution |
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// Blands_rule |
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// 1_more_test & make_more_clear |
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// -> **contact_Vadim**: min_l2_norm, init_optional_fsbl_check, error_codes, comment_style-too_many?, copyTo temp headers |
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// ??how to get smallest l2 norm |
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// FUTURE: compress&debug-> more_tests(Cormen) -> readNumRecipes-> fast&stable || hill_climbing
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