// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2009 Gael Guennebaud // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public // License as published by the Free Software Foundation; either // version 3 of the License, or (at your option) any later version. // // Alternatively, you can redistribute it and/or // modify it under the terms of the GNU General Public License as // published by the Free Software Foundation; either version 2 of // the License, or (at your option) any later version. // // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the // GNU General Public License for more details. // // You should have received a copy of the GNU Lesser General Public // License and a copy of the GNU General Public License along with // Eigen. If not, see . #include "main.h" template struct symm_extra { template static void run(M1& m1, M1& m2, M2& rhs2, M2& rhs22, M2& rhs23, Scalar s1, Scalar s2) { m2 = m1.template triangularView(); VERIFY_IS_APPROX(rhs22 = (rhs2) * (m2).template selfadjointView(), rhs23 = (rhs2) * (m1)); VERIFY_IS_APPROX(rhs22 = (s2*rhs2) * (s1*m2).template selfadjointView(), rhs23 = (s2*rhs2) * (s1*m1)); } }; template<> struct symm_extra<1> { template static void run(M1&, M1&, M2&, M2&, M2&, Scalar, Scalar) {} }; template void symm(int size = Size, int othersize = OtherSize) { typedef typename NumTraits::Real RealScalar; typedef Matrix MatrixType; typedef Matrix Rhs1; typedef Matrix Rhs2; typedef Matrix Rhs3; int rows = size; int cols = size; MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols); m1 = (m1+m1.adjoint()).eval(); Rhs1 rhs1 = Rhs1::Random(cols, othersize), rhs12(cols, othersize), rhs13(cols, othersize); Rhs2 rhs2 = Rhs2::Random(othersize, rows), rhs22(othersize, rows), rhs23(othersize, rows); Rhs3 rhs3 = Rhs3::Random(cols, othersize), rhs32(cols, othersize), rhs33(cols, othersize); Scalar s1 = ei_random(), s2 = ei_random(); m2 = m1.template triangularView(); VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView() * (s2*rhs1), rhs13 = (s1*m1) * (s2*rhs1)); m2 = m1.template triangularView(); rhs12.setRandom(); rhs13 = rhs12; VERIFY_IS_APPROX(rhs12 += (s1*m2).template selfadjointView() * (s2*rhs1), rhs13 += (s1*m1) * (s2*rhs1)); m2 = m1.template triangularView(); VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView() * (s2*rhs2.adjoint()), rhs13 = (s1*m1) * (s2*rhs2.adjoint())); m2 = m1.template triangularView(); VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView() * (s2*rhs2.adjoint()), rhs13 = (s1*m1) * (s2*rhs2.adjoint())); m2 = m1.template triangularView(); VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView() * (s2*rhs2.adjoint()), rhs13 = (s1*m1.adjoint()) * (s2*rhs2.adjoint())); // test row major = <...> m2 = m1.template triangularView(); rhs12.setRandom(); rhs13 = rhs12; VERIFY_IS_APPROX(rhs12 -= (s1*m2).template selfadjointView() * (s2*rhs3), rhs13 -= (s1*m1) * (s2 * rhs3)); m2 = m1.template triangularView(); VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView() * (s2*rhs3).conjugate(), rhs13 = (s1*m1.adjoint()) * (s2*rhs3).conjugate()); m2 = m1.template triangularView(); rhs13 = rhs12; VERIFY_IS_APPROX(rhs12 += (s1 * ((m2.adjoint()).template selfadjointView() * (s2*rhs3).conjugate())).lazy(), rhs13 += (s1*m1.adjoint()) * (s2*rhs3).conjugate()); // test matrix * selfadjoint symm_extra::run(m1,m2,rhs2,rhs22,rhs23,s1,s2); } void test_product_symm() { for(int i = 0; i < g_repeat ; i++) { CALL_SUBTEST(( symm(ei_random(10,320),ei_random(10,320)) )); CALL_SUBTEST(( symm,Dynamic,Dynamic>(ei_random(10,320),ei_random(10,320)) )); CALL_SUBTEST(( symm(ei_random(10,320)) )); CALL_SUBTEST(( symm,Dynamic,1>(ei_random(10,320)) )); } }