// This file is part of Eigen, a lightweight C++ template library // for linear algebra. Eigen itself is part of the KDE project. // // Copyright (C) 2006-2008 Benoit Jacob // // 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" namespace Eigen { template void product(const MatrixType& m) { /* this test covers the following files: Identity.h Product.h */ typedef typename MatrixType::Scalar Scalar; typedef Matrix VectorType; int rows = m.rows(); int cols = m.cols(); // this test relies a lot on Random.h, and there's not much more that we can do // to test it, hence I consider that we will have tested Random.h MatrixType m1 = MatrixType::random(rows, cols), m2 = MatrixType::random(rows, cols), m3(rows, cols), mzero = MatrixType::zero(rows, cols), identity = Matrix ::identity(rows, rows), square = Matrix ::random(rows, rows); VectorType v1 = VectorType::random(rows), v2 = VectorType::random(rows), vzero = VectorType::zero(rows); Scalar s1 = ei_random(); int r = ei_random(0, rows-1), c = ei_random(0, cols-1); // begin testing Product.h: only associativity for now // (we use Transpose.h but this doesn't count as a test for it) VERIFY_IS_APPROX((m1*m1.transpose())*m2, m1*(m1.transpose()*m2)); m3 = m1; m3 *= (m1.transpose() * m2); VERIFY_IS_APPROX(m3, m1*(m1.transpose()*m2)); VERIFY_IS_APPROX(m3, m1.lazyProduct(m1.transpose()*m2)); // continue testing Product.h: distributivity VERIFY_IS_APPROX(square*(m1 + m2), square*m1+square*m2); VERIFY_IS_APPROX(square*(m1 - m2), square*m1-square*m2); // continue testing Product.h: compatibility with ScalarMultiple.h VERIFY_IS_APPROX(s1*(square*m1), (s1*square)*m1); VERIFY_IS_APPROX(s1*(square*m1), square*(m1*s1)); // continue testing Product.h: lazyProduct VERIFY_IS_APPROX(square.lazyProduct(m1), square*m1); // again, test operator() to check const-qualification s1 += square.lazyProduct(m1)(r,c); // test Product.h together with Identity.h VERIFY_IS_APPROX(m1, identity*m1); VERIFY_IS_APPROX(v1, identity*v1); // again, test operator() to check const-qualification VERIFY_IS_APPROX(MatrixType::identity(rows, cols)(r,c), static_cast(r==c)); if (rows!=cols) VERIFY_RAISES_ASSERT(m3 = m1*m1); } void EigenTest::testProduct() { for(int i = 0; i < m_repeat; i++) { product(Matrix()); product(Matrix4d()); product(MatrixXcf(3, 3)); product(MatrixXi(8, 12)); product(MatrixXcd(20, 20)); } // test a large matrix only once product(Matrix()); } } // namespace Eigen