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// 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 <jacob@math.jussieu.fr>
//
// 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 <http://www.gnu.org/licenses/>.
#include "main.h"
template<typename MatrixType> void product(const MatrixType& m)
{
/* this test covers the following files:
Identity.h Product.h
*/
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::FloatingPoint FloatingPoint;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> RowSquareMatrixType;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> ColSquareMatrixType;
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);
RowSquareMatrixType
identity = RowSquareMatrixType::identity(rows, rows),
square = RowSquareMatrixType::random(rows, rows),
res = RowSquareMatrixType::random(rows, rows);
ColSquareMatrixType
square2 = ColSquareMatrixType::random(cols, cols),
res2 = ColSquareMatrixType::random(cols, cols);
VectorType v1 = VectorType::random(rows),
v2 = VectorType::random(rows),
vzero = VectorType::zero(rows);
Scalar s1 = ei_random<Scalar>();
int r = ei_random<int>(0, rows-1),
c = ei_random<int>(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.lazy() * (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));
// again, test operator() to check const-qualification
s1 += (square.lazy() * m1)(r,c);
// test Product.h together with Identity.h
VERIFY_IS_APPROX(v1, identity*v1);
// again, test operator() to check const-qualification
VERIFY_IS_APPROX(MatrixType::identity(rows, cols)(r,c), static_cast<Scalar>(r==c));
if (rows!=cols)
VERIFY_RAISES_ASSERT(m3 = m1*m1);
// test the previous tests were not screwed up because operator* returns 0
VERIFY_IS_NOT_APPROX((m1.transpose()*m2).template cast<FloatingPoint>(), (m2.transpose()*m1).template cast<FloatingPoint>());
// test optimized operator+= path
res = square;
res += (m1 * m2.transpose()).lazy();
VERIFY_IS_APPROX(res, square + m1 * m2.transpose());
VERIFY_IS_NOT_APPROX(res.template cast<FloatingPoint>(), (square + m2 * m1.transpose()).template cast<FloatingPoint>());
res2 = square2;
res2 += (m1.transpose() * m2).lazy();
VERIFY_IS_APPROX(res2, square2 + m1.transpose() * m2);
VERIFY_IS_NOT_APPROX(res2.template cast<FloatingPoint>(), (square2 + m2.transpose() * m1).template cast<FloatingPoint>());
}
void test_product()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( product(Matrix3i()) );
CALL_SUBTEST( product(Matrix<float, 3, 2>()) );
CALL_SUBTEST( product(Matrix4d()) );
CALL_SUBTEST( product(Matrix4f()) );
CALL_SUBTEST( product(MatrixXf(3,5)) );
CALL_SUBTEST( product(MatrixXi(28,39)) );
}
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( product(MatrixXf(ei_random<int>(1,320), ei_random<int>(1,320))) );
CALL_SUBTEST( product(MatrixXd(ei_random<int>(1,320), ei_random<int>(1,320))) );
CALL_SUBTEST( product(MatrixXi(ei_random<int>(1,256), ei_random<int>(1,256))) );
CALL_SUBTEST( product(MatrixXcf(ei_random<int>(1,50), ei_random<int>(1,50))) );
#ifndef EIGEN_DEFAULT_TO_ROW_MAJOR
CALL_SUBTEST( product(Matrix<float,Dynamic,Dynamic,Dynamic,Dynamic,RowMajorBit>(ei_random<int>(1,320), ei_random<int>(1,320))) );
#else
CALL_SUBTEST( product(Matrix<float,Dynamic,Dynamic,Dynamic,Dynamic,0>(ei_random<int>(1,320), ei_random<int>(1,320))) );
#endif
}
}
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