// Copyright (C) 2009 Davis E. King (davis@dlib.net) // License: Boost Software License See LICENSE.txt for the full license. #include #include #include #include #include #include #include "../stl_checked.h" #include "../array.h" #include "../rand.h" #include #include "tester.h" namespace { using namespace test; using namespace dlib; using namespace std; logger dlog("test.matrix_eig"); dlib::rand rnd; // ---------------------------------------------------------------------------------------- template const matrix randm(long r, long c) { matrix m(r,c); for (long row = 0; row < m.nr(); ++row) { for (long col = 0; col < m.nc(); ++col) { m(row,col) = static_cast(rnd.get_random_double()); } } return m; } template const matrix randm() { matrix m; for (long row = 0; row < m.nr(); ++row) { for (long col = 0; col < m.nc(); ++col) { m(row,col) = static_cast(rnd.get_random_double()); } } return m; } // ---------------------------------------------------------------------------------------- template void test_eigenvalue_impl ( const matrix_type& m, const eigenvalue_decomposition& test ) { typedef typename matrix_type::type type; const type eps = 10*max(abs(m))*sqrt(std::numeric_limits::epsilon()); dlog << LDEBUG << "test_eigenvalue(): " << m.nr() << " x " << m.nc() << " eps: " << eps; print_spinner(); DLIB_TEST(test.dim() == m.nr()); // make sure all the various ways of asking for the eigenvalues are actually returning a // consistent set of eigenvalues. DLIB_TEST(equal(real(test.get_eigenvalues()), test.get_real_eigenvalues(), eps)); DLIB_TEST(equal(imag(test.get_eigenvalues()), test.get_imag_eigenvalues(), eps)); DLIB_TEST(equal(real(diag(test.get_d())), test.get_real_eigenvalues(), eps)); DLIB_TEST(equal(imag(diag(test.get_d())), test.get_imag_eigenvalues(), eps)); matrix eig1 ( real_eigenvalues(m)); matrix eig2 ( test.get_real_eigenvalues()); sort(&eig1(0), &eig1(0) + eig1.size()); sort(&eig2(0), &eig2(0) + eig2.size()); DLIB_TEST(max(abs(eig1 - eig2)) < eps); const matrix V = test.get_pseudo_v(); const matrix D = test.get_pseudo_d(); const matrix > CV = test.get_v(); const matrix > CD = test.get_d(); const matrix > CM = complex_matrix(m, uniform_matrix(m.nr(),m.nc(),0)); DLIB_TEST(V.nr() == test.dim()); DLIB_TEST(V.nc() == test.dim()); DLIB_TEST(D.nr() == test.dim()); DLIB_TEST(D.nc() == test.dim()); // CD is a diagonal matrix DLIB_TEST(diagm(diag(CD)) == CD); // verify that these things are actually eigenvalues and eigenvectors of m DLIB_TEST_MSG(max(abs(m*V - V*D)) < eps, max(abs(m*V - V*D)) << " " << eps); DLIB_TEST(max(norm(CM*CV - CV*CD)) < eps); // if m is a symmetric matrix if (max(abs(m-trans(m))) < 1e-5) { dlog << LTRACE << "m is symmetric"; // there aren't any imaginary eigenvalues DLIB_TEST(max(abs(test.get_imag_eigenvalues())) < eps); DLIB_TEST(diagm(diag(D)) == D); // only check the determinant against the eigenvalues for small matrices // because for huge ones the determinant might be so big it overflows a floating point number. if (m.nr() < 50) { const type mdet = det(m); DLIB_TEST_MSG(std::abs(prod(test.get_real_eigenvalues()) - mdet) < std::abs(mdet)*sqrt(std::numeric_limits::epsilon()), std::abs(prod(test.get_real_eigenvalues()) - mdet) <<" eps: " << std::abs(mdet)*sqrt(std::numeric_limits::epsilon()) << " mdet: "<< mdet << " prod(eig): " << prod(test.get_real_eigenvalues()) ); } // V is orthogonal DLIB_TEST(equal(V*trans(V), identity_matrix(test.dim()), eps)); DLIB_TEST(equal(m , V*D*trans(V), eps)); } else { dlog << LTRACE << "m is NOT symmetric"; DLIB_TEST_MSG(equal(m , V*D*inv(V), eps), max(abs(m - V*D*inv(V)))); } } // ---------------------------------------------------------------------------------------- template void test_eigenvalue ( const matrix_type& m ) { typedef typename matrix_type::type type; typedef typename matrix_type::mem_manager_type MM; matrix mr(m); matrix mc(m); { eigenvalue_decomposition test(mr); test_eigenvalue_impl(mr, test); eigenvalue_decomposition test_symm(make_symmetric(mr)); test_eigenvalue_impl(make_symmetric(mr), test_symm); } { eigenvalue_decomposition test(mc); test_eigenvalue_impl(mc, test); eigenvalue_decomposition test_symm(make_symmetric(mc)); test_eigenvalue_impl(make_symmetric(mc), test_symm); } } // ---------------------------------------------------------------------------------------- void matrix_test_double() { test_eigenvalue(10*randm(1,1)); test_eigenvalue(10*randm(2,2)); test_eigenvalue(10*randm(3,3)); test_eigenvalue(10*randm(4,4)); test_eigenvalue(10*randm(15,15)); test_eigenvalue(10*randm(150,150)); test_eigenvalue(10*randm()); test_eigenvalue(10*randm()); test_eigenvalue(10*randm()); } // ---------------------------------------------------------------------------------------- void matrix_test_float() { test_eigenvalue(10*randm(1,1)); test_eigenvalue(10*randm(2,2)); test_eigenvalue(10*randm(3,3)); test_eigenvalue(10*randm(4,4)); test_eigenvalue(10*randm(15,15)); test_eigenvalue(10*randm(50,50)); test_eigenvalue(10*randm()); test_eigenvalue(10*randm()); test_eigenvalue(10*randm()); } template void test_eigenvalue2() { for (int seed = 0; seed < 10; ++seed) { print_spinner(); matrix H = gaussian_randm(dims,dims,seed); H = H*trans(H); eigenvalue_decomposition > eig(H); matrix HH = eig.get_pseudo_v()*diagm(eig.get_real_eigenvalues())*trans(eig.get_pseudo_v()); DLIB_TEST_MSG(max(abs(H - HH))<1e-12, "dims: " << dims << " error: " << max(abs(H - HH))); } } // ---------------------------------------------------------------------------------------- class matrix_tester : public tester { public: matrix_tester ( ) : tester ("test_matrix_eig", "Runs tests on the matrix eigen decomp component.") { //rnd.set_seed(cast_to_string(time(0))); } void perform_test ( ) { dlog << LINFO << "seed string: " << rnd.get_seed(); dlog << LINFO << "begin testing with double"; matrix_test_double(); dlog << LINFO << "begin testing with float"; matrix_test_float(); test_eigenvalue2<10>(); test_eigenvalue2<11>(); test_eigenvalue2<3>(); test_eigenvalue2<2>(); test_eigenvalue2<1>(); } } a; }