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