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103 lines
3.9 KiB
C++
103 lines
3.9 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2006-2008 Benoit Jacob <jacob@math.jussieu.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "main.h"
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namespace Eigen {
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template<typename MatrixType> void product(const MatrixType& m)
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{
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/* this test covers the following files:
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Identity.h Product.h
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*/
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typedef typename MatrixType::Scalar Scalar;
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typedef Matrix<Scalar, MatrixType::Traits::RowsAtCompileTime, 1> VectorType;
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int rows = m.rows();
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int cols = m.cols();
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// this test relies a lot on Random.h, and there's not much more that we can do
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// to test it, hence I consider that we will have tested Random.h
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MatrixType m1 = MatrixType::random(rows, cols),
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m2 = MatrixType::random(rows, cols),
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m3(rows, cols),
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mzero = MatrixType::zero(rows, cols),
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identity = Matrix<Scalar, MatrixType::Traits::RowsAtCompileTime, MatrixType::Traits::RowsAtCompileTime>
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::identity(rows, rows),
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square = Matrix<Scalar, MatrixType::Traits::RowsAtCompileTime, MatrixType::Traits::RowsAtCompileTime>
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::random(rows, rows);
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VectorType v1 = VectorType::random(rows),
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v2 = VectorType::random(rows),
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vzero = VectorType::zero(rows);
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Scalar s1 = ei_random<Scalar>();
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int r = ei_random<int>(0, rows-1),
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c = ei_random<int>(0, cols-1);
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// begin testing Product.h: only associativity for now
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// (we use Transpose.h but this doesn't count as a test for it)
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VERIFY_IS_APPROX((m1*m1.transpose())*m2, m1*(m1.transpose()*m2));
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m3 = m1;
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m3 *= (m1.transpose() * m2);
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VERIFY_IS_APPROX(m3, m1*(m1.transpose()*m2));
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VERIFY_IS_APPROX(m3, m1.lazyProduct(m1.transpose()*m2));
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// continue testing Product.h: distributivity
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VERIFY_IS_APPROX(square*(m1 + m2), square*m1+square*m2);
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VERIFY_IS_APPROX(square*(m1 - m2), square*m1-square*m2);
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// continue testing Product.h: compatibility with ScalarMultiple.h
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VERIFY_IS_APPROX(s1*(square*m1), (s1*square)*m1);
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VERIFY_IS_APPROX(s1*(square*m1), square*(m1*s1));
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// continue testing Product.h: lazyProduct
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VERIFY_IS_APPROX(square.lazyProduct(m1), square*m1);
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// again, test operator() to check const-qualification
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s1 += square.lazyProduct(m1)(r,c);
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// test Product.h together with Identity.h
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VERIFY_IS_APPROX(m1, identity*m1);
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VERIFY_IS_APPROX(v1, identity*v1);
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// again, test operator() to check const-qualification
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VERIFY_IS_APPROX(MatrixType::identity(rows, cols)(r,c), static_cast<Scalar>(r==c));
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}
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void EigenTest::testProduct()
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{
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for(int i = 0; i < m_repeat; i++) {
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product(Matrix<float, 1, 1>());
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product(Matrix4d());
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product(MatrixXcf(3, 3));
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product(MatrixXi(8, 12));
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product(MatrixXcd(20, 20));
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}
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// test a large matrix only once
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product(Matrix<float, 100, 100>());
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}
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} // namespace Eigen
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