mirror of
https://gitlab.com/libeigen/eigen.git
synced 2024-12-27 07:29:52 +08:00
95db32fcdc
The unsupported module documentation is automatically generated in: build/doc/unsupported/ with bidirectional cross references. I leave a class Foo in AdolcForward module to illustrate the cross-reference behavior. I will remove it in the next commit.
175 lines
6.4 KiB
C++
175 lines
6.4 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>
|
|
//
|
|
// 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/QR>
|
|
|
|
template<typename MatrixType> void qr(const MatrixType& m)
|
|
{
|
|
/* this test covers the following files: QR.h */
|
|
int rows = m.rows();
|
|
int cols = m.cols();
|
|
|
|
typedef typename MatrixType::Scalar Scalar;
|
|
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> SquareMatrixType;
|
|
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
|
|
|
|
MatrixType a = MatrixType::Random(rows,cols);
|
|
QR<MatrixType> qrOfA(a);
|
|
VERIFY_IS_APPROX(a, qrOfA.matrixQ() * qrOfA.matrixR());
|
|
VERIFY_IS_NOT_APPROX(a+MatrixType::Identity(rows, cols), qrOfA.matrixQ() * qrOfA.matrixR());
|
|
|
|
SquareMatrixType b = a.adjoint() * a;
|
|
|
|
// check tridiagonalization
|
|
Tridiagonalization<SquareMatrixType> tridiag(b);
|
|
VERIFY_IS_APPROX(b, tridiag.matrixQ() * tridiag.matrixT() * tridiag.matrixQ().adjoint());
|
|
|
|
// check hessenberg decomposition
|
|
HessenbergDecomposition<SquareMatrixType> hess(b);
|
|
VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint());
|
|
VERIFY_IS_APPROX(tridiag.matrixT(), hess.matrixH());
|
|
b = SquareMatrixType::Random(cols,cols);
|
|
hess.compute(b);
|
|
VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint());
|
|
}
|
|
|
|
template<typename Derived>
|
|
void doSomeRankPreservingOperations(Eigen::MatrixBase<Derived>& m)
|
|
{
|
|
typedef typename Derived::RealScalar RealScalar;
|
|
for(int a = 0; a < 3*(m.rows()+m.cols()); a++)
|
|
{
|
|
RealScalar d = Eigen::ei_random<RealScalar>(-1,1);
|
|
int i = Eigen::ei_random<int>(0,m.rows()-1); // i is a random row number
|
|
int j;
|
|
do {
|
|
j = Eigen::ei_random<int>(0,m.rows()-1);
|
|
} while (i==j); // j is another one (must be different)
|
|
m.row(i) += d * m.row(j);
|
|
|
|
i = Eigen::ei_random<int>(0,m.cols()-1); // i is a random column number
|
|
do {
|
|
j = Eigen::ei_random<int>(0,m.cols()-1);
|
|
} while (i==j); // j is another one (must be different)
|
|
m.col(i) += d * m.col(j);
|
|
}
|
|
}
|
|
|
|
template<typename MatrixType> void qr_non_invertible()
|
|
{
|
|
/* this test covers the following files: QR.h */
|
|
// NOTE there seems to be a problem with too small sizes -- could easily lie in the doSomeRankPreservingOperations function
|
|
int rows = ei_random<int>(20,200), cols = ei_random<int>(20,rows), cols2 = ei_random<int>(20,rows);
|
|
int rank = ei_random<int>(1, std::min(rows, cols)-1);
|
|
|
|
MatrixType m1(rows, cols), m2(cols, cols2), m3(rows, cols2), k(1,1);
|
|
m1 = MatrixType::Random(rows,cols);
|
|
if(rows <= cols)
|
|
for(int i = rank; i < rows; i++) m1.row(i).setZero();
|
|
else
|
|
for(int i = rank; i < cols; i++) m1.col(i).setZero();
|
|
doSomeRankPreservingOperations(m1);
|
|
|
|
QR<MatrixType> lu(m1);
|
|
// typename LU<MatrixType>::KernelResultType m1kernel = lu.kernel();
|
|
// typename LU<MatrixType>::ImageResultType m1image = lu.image();
|
|
std::cerr << rows << "x" << cols << " " << rank << " " << lu.rank() << "\n";
|
|
if (rank != lu.rank())
|
|
std::cerr << lu.matrixR().diagonal().transpose() << "\n";
|
|
VERIFY(rank == lu.rank());
|
|
VERIFY(cols - lu.rank() == lu.dimensionOfKernel());
|
|
VERIFY(!lu.isInjective());
|
|
VERIFY(!lu.isInvertible());
|
|
VERIFY(lu.isSurjective() == (lu.rank() == rows));
|
|
// VERIFY((m1 * m1kernel).isMuchSmallerThan(m1));
|
|
// VERIFY(m1image.lu().rank() == rank);
|
|
// MatrixType sidebyside(m1.rows(), m1.cols() + m1image.cols());
|
|
// sidebyside << m1, m1image;
|
|
// VERIFY(sidebyside.lu().rank() == rank);
|
|
m2 = MatrixType::Random(cols,cols2);
|
|
m3 = m1*m2;
|
|
m2 = MatrixType::Random(cols,cols2);
|
|
lu.solve(m3, &m2);
|
|
VERIFY_IS_APPROX(m3, m1*m2);
|
|
m3 = MatrixType::Random(rows,cols2);
|
|
VERIFY(!lu.solve(m3, &m2));
|
|
}
|
|
|
|
template<typename MatrixType> void qr_invertible()
|
|
{
|
|
/* this test covers the following files: QR.h */
|
|
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
|
|
int size = ei_random<int>(10,200);
|
|
|
|
MatrixType m1(size, size), m2(size, size), m3(size, size);
|
|
m1 = MatrixType::Random(size,size);
|
|
|
|
if (ei_is_same_type<RealScalar,float>::ret)
|
|
{
|
|
// let's build a matrix more stable to inverse
|
|
MatrixType a = MatrixType::Random(size,size*2);
|
|
m1 += a * a.adjoint();
|
|
}
|
|
|
|
QR<MatrixType> lu(m1);
|
|
VERIFY(0 == lu.dimensionOfKernel());
|
|
VERIFY(size == lu.rank());
|
|
VERIFY(lu.isInjective());
|
|
VERIFY(lu.isSurjective());
|
|
VERIFY(lu.isInvertible());
|
|
// VERIFY(lu.image().lu().isInvertible());
|
|
m3 = MatrixType::Random(size,size);
|
|
lu.solve(m3, &m2);
|
|
//std::cerr << m3 - m1*m2 << "\n\n";
|
|
VERIFY_IS_APPROX(m3, m1*m2);
|
|
// VERIFY_IS_APPROX(m2, lu.inverse()*m3);
|
|
m3 = MatrixType::Random(size,size);
|
|
VERIFY(lu.solve(m3, &m2));
|
|
}
|
|
|
|
void test_qr()
|
|
{
|
|
for(int i = 0; i < 1; i++) {
|
|
// CALL_SUBTEST( qr(Matrix2f()) );
|
|
// CALL_SUBTEST( qr(Matrix4d()) );
|
|
// CALL_SUBTEST( qr(MatrixXf(12,8)) );
|
|
// CALL_SUBTEST( qr(MatrixXcd(5,5)) );
|
|
// CALL_SUBTEST( qr(MatrixXcd(7,3)) );
|
|
}
|
|
|
|
for(int i = 0; i < g_repeat; i++) {
|
|
CALL_SUBTEST( qr_non_invertible<MatrixXf>() );
|
|
// CALL_SUBTEST( qr_non_invertible<MatrixXd>() );
|
|
// TODO fix issue with complex
|
|
// CALL_SUBTEST( qr_non_invertible<MatrixXcf>() );
|
|
// CALL_SUBTEST( qr_non_invertible<MatrixXcd>() );
|
|
// CALL_SUBTEST( qr_invertible<MatrixXf>() );
|
|
// CALL_SUBTEST( qr_invertible<MatrixXd>() );
|
|
// TODO fix issue with complex
|
|
// CALL_SUBTEST( qr_invertible<MatrixXcf>() );
|
|
// CALL_SUBTEST( qr_invertible<MatrixXcd>() );
|
|
}
|
|
}
|