// 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" template void linearStructure(const MatrixType& m) { /* this test covers the following files: Sum.h Difference.h Opposite.h ScalarMultiple.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); VERIFY_IS_APPROX(-(-m1), m1); VERIFY_IS_APPROX(m1+m1, 2*m1); VERIFY_IS_APPROX(m1+m2-m1, m2); VERIFY_IS_APPROX(-m2+m1+m2, m1); VERIFY_IS_APPROX(m1*s1, s1*m1); VERIFY_IS_APPROX((m1+m2)*s1, s1*m1+s1*m2); VERIFY_IS_APPROX((-m1+m2)*s1, -s1*m1+s1*m2); m3 = m2; m3 += m1; VERIFY_IS_APPROX(m3, m1+m2); m3 = m2; m3 -= m1; VERIFY_IS_APPROX(m3, m2-m1); m3 = m2; m3 *= s1; VERIFY_IS_APPROX(m3, s1*m2); if(NumTraits::HasFloatingPoint) { m3 = m2; m3 /= s1; VERIFY_IS_APPROX(m3, m2/s1); } // again, test operator() to check const-qualification VERIFY_IS_APPROX((-m1)(r,c), -(m1(r,c))); VERIFY_IS_APPROX((m1-m2)(r,c), (m1(r,c))-(m2(r,c))); VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c))); VERIFY_IS_APPROX((s1*m1)(r,c), s1*(m1(r,c))); VERIFY_IS_APPROX((m1*s1)(r,c), (m1(r,c))*s1); if(NumTraits::HasFloatingPoint) VERIFY_IS_APPROX((m1/s1)(r,c), (m1(r,c))/s1); // use .block to disable vectorization and compare to the vectorized version VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1); VERIFY_IS_APPROX(m1.cwiseProduct(m1.block(0,0,rows,cols)), m1.cwiseProduct(m1)); VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1); VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1); } void test_linearstructure() { for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST( linearStructure(Matrix()) ); CALL_SUBTEST( linearStructure(Matrix2f()) ); CALL_SUBTEST( linearStructure(Matrix4d()) ); CALL_SUBTEST( linearStructure(MatrixXcf(3, 3)) ); CALL_SUBTEST( linearStructure(MatrixXf(8, 12)) ); CALL_SUBTEST( linearStructure(MatrixXi(8, 12)) ); CALL_SUBTEST( linearStructure(MatrixXcd(20, 20)) ); } }