mirror of
https://gitlab.com/libeigen/eigen.git
synced 2024-12-21 07:19:46 +08:00
2120fed849
* fix all numerical instabilies in the unit tests, now all tests can be run 2000 times with almost zero failures.
81 lines
2.8 KiB
C++
81 lines
2.8 KiB
C++
// 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@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"
|
|
#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 = test_random_matrix<MatrixType>(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 = test_random_matrix<MatrixType>(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)) );
|
|
}
|
|
}
|