opencv/modules/core/test/test_lpsolver.cpp

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#include "test_precomp.hpp"

namespace opencv_test { namespace {

TEST(Core_LPSolver, regression_basic){
    cv::Mat A,B,z,etalon_z;

#if 1
    //cormen's example #1
    A=(cv::Mat_<double>(3,1)<<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::solveLP(A,B,z);
    std::cout<<"here z goes\n"<<z<<"\n";
    etalon_z=(cv::Mat_<double>(3,1)<<8,4,0);
    ASSERT_LT(cvtest::norm(z, etalon_z, cv::NORM_L1), 1e-12);
#endif

#if 1
    //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::solveLP(A,B,z);
    std::cout<<"here z goes\n"<<z<<"\n";
    etalon_z=(cv::Mat_<double>(2,1)<<20,0);
    ASSERT_LT(cvtest::norm(z, etalon_z, cv::NORM_L1), 1e-12);
#endif

#if 1
    //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::solveLP(A,B,z);
    std::cout<<"here z goes\n"<<z<<"\n";
    etalon_z=(cv::Mat_<double>(2,1)<<1,0);
    ASSERT_LT(cvtest::norm(z, etalon_z, cv::NORM_L1), 1e-12);
#endif
}

TEST(Core_LPSolver, regression_init_unfeasible){
    cv::Mat A,B,z,etalon_z;

#if 1
    //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::solveLP(A,B,z);
    std::cout<<"here z goes\n"<<z<<"\n";
    etalon_z=(cv::Mat_<double>(3,1)<<1250,1000,0);
    ASSERT_LT(cvtest::norm(z, etalon_z, cv::NORM_L1), 1e-12);
#endif
}

TEST(DISABLED_Core_LPSolver, regression_absolutely_unfeasible){
    cv::Mat A,B,z,etalon_z;

#if 1
    //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::solveLP(A,B,z);
    ASSERT_EQ(res,-1);
#endif
}

TEST(Core_LPSolver, regression_multiple_solutions){
    cv::Mat A,B,z,etalon_z;

#if 1
    //trivial example with multiple solutions
    A=(cv::Mat_<double>(2,1)<<1,1);
    B=(cv::Mat_<double>(1,3)<<1,1,1);
    std::cout<<"here A goes\n"<<A<<"\n";
    int res=cv::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_LT(fabs(z.dot(A) - 1), DBL_EPSILON);
#endif
}

TEST(Core_LPSolver, regression_cycling){
    cv::Mat A,B,z,etalon_z;

#if 1
    //example with cycling from http://people.orie.cornell.edu/miketodd/or630/SimplexCyclingExample.pdf
    A=(cv::Mat_<double>(4,1)<<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::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_LT(fabs(z.dot(A) - 1), DBL_EPSILON);
    //ASSERT_EQ(res,1);
#endif
}

TEST(Core_LPSolver, issue_12337)
{
    Mat A=(cv::Mat_<double>(3,1)<<3,1,2);
    Mat B=(cv::Mat_<double>(3,4)<<1,1,3,30,2,2,5,24,4,1,2,36);
    Mat1f z_float; cv::solveLP(A, B, z_float);
    Mat1d z_double; cv::solveLP(A, B, z_double);
    Mat1i z_int; cv::solveLP(A, B, z_int);
    EXPECT_ANY_THROW(Mat1b z_8u; cv::solveLP(A, B, z_8u));
}

// NOTE: Test parameters found experimentally to get numerically inaccurate result.
// The test behaviour may change after algorithm tuning and may removed.
TEST(Core_LPSolver, issue_12343)
{
    Mat A = (cv::Mat_<double>(4, 1) << 3., 3., 3., 4.);
    Mat B = (cv::Mat_<double>(4, 5) << 0., 1., 4., 4., 3.,
                                       3., 1., 2., 2., 3.,
                                       4., 4., 0., 1., 4.,
                                       4., 0., 4., 1., 4.);
    Mat z;
    int result = cv::solveLP(A, B, z);
    EXPECT_EQ(SOLVELP_LOST, result);
}

}} // namespace