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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) 2008 Gael Guennebaud <g.gael@free.fr>
// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// 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"
#include <Eigen/LU>
template<typename MatrixType> void inverse(const MatrixType& m)
{
/* this test covers the following files:
Inverse.h
*/
int rows = m.rows();
int cols = m.cols();
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
MatrixType m1 = MatrixType::Random(rows, cols),
m2(rows, cols),
mzero = MatrixType::Zero(rows, cols),
identity = MatrixType::Identity(rows, rows);
if (ei_is_same_type<RealScalar,float>::ret)
{
// let's build a more stable to inverse matrix
MatrixType a = MatrixType::Random(rows,cols);
m1 += m1 * m1.adjoint() + a * a.adjoint();
}
m2 = m1.inverse();
VERIFY_IS_APPROX(m1, m2.inverse() );
m1.computeInverse(&m2);
VERIFY_IS_APPROX(m1, m2.inverse() );
VERIFY_IS_APPROX((Scalar(2)*m2).inverse(), m2.inverse()*Scalar(0.5));
VERIFY_IS_APPROX(identity, m1.inverse() * m1 );
VERIFY_IS_APPROX(identity, m1 * m1.inverse() );
VERIFY_IS_APPROX(m1, m1.inverse().inverse() );
// since for the general case we implement separately row-major and col-major, test that
VERIFY_IS_APPROX(m1.transpose().inverse(), m1.inverse().transpose());
}
void test_inverse()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( inverse(Matrix<double,1,1>()) );
CALL_SUBTEST( inverse(Matrix2d()) );
CALL_SUBTEST( inverse(Matrix3f()) );
CALL_SUBTEST( inverse(Matrix4f()) );
CALL_SUBTEST( inverse(MatrixXf(8,8)) );
CALL_SUBTEST( inverse(MatrixXcd(7,7)) );
}
}
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