devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity

Add a preliminary GeneralizedEigenSolver computing the eigenvalues of Av=lBv with A and B general real matrices.

Browse Source 
Currently only the eigenvalues are reported.
This commit is contained in:
Gael Guennebaud
2012-07-26 20:15:17 +02:00
parent cfb76b242f
commit 9e8d2dea80
4 changed files with 416 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
test/CMakeLists.txt
View File

@@ -155,7 +155,6 @@ ei_add_test(inverse)
ei_add_test(qr)
ei_add_test(qr_colpivoting)
ei_add_test(qr_fullpivoting)
ei_add_test(real_qz)
ei_add_test(upperbidiagonalization)
ei_add_test(hessenberg)
ei_add_test(schur_real)
@@ -163,6 +162,8 @@ ei_add_test(schur_complex)
ei_add_test(eigensolver_selfadjoint)
ei_add_test(eigensolver_generic)
ei_add_test(eigensolver_complex)
ei_add_test(real_qz)
ei_add_test(eigensolver_generalized_real)
ei_add_test(jacobi)
ei_add_test(jacobisvd)
ei_add_test(geo_orthomethods)

63
test/eigensolver_generalized_real.cpp Normal file
View File

@@ -0,0 +1,63 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#include "main.h"
#include <limits>
#include <Eigen/Eigenvalues>
template<typename MatrixType> void generalized_eigensolver_real(const MatrixType& m)
{
typedef typename MatrixType::Index Index;
/* this test covers the following files:
GeneralizedEigenSolver.h
*/
Index rows = m.rows();
Index cols = m.cols();
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
MatrixType a = MatrixType::Random(rows,cols);
MatrixType b = MatrixType::Random(rows,cols);
MatrixType a1 = MatrixType::Random(rows,cols);
MatrixType b1 = MatrixType::Random(rows,cols);
MatrixType spdA = a.adjoint() * a + a1.adjoint() * a1;
MatrixType spdB = b.adjoint() * b + b1.adjoint() * b1;
// lets compare to GeneralizedSelfAdjointEigenSolver
GeneralizedSelfAdjointEigenSolver<MatrixType> symmEig(spdA, spdB);
GeneralizedEigenSolver<MatrixType> eig(spdA, spdB);
VERIFY_IS_EQUAL(eig.eigenvalues().imag().cwiseAbs().maxCoeff(), 0);
VectorType realEigenvalues = eig.eigenvalues().real();
std::sort(realEigenvalues.data(), realEigenvalues.data()+realEigenvalues.size());
VERIFY_IS_APPROX(realEigenvalues, symmEig.eigenvalues());
}
void test_eigensolver_generalized_real()
{
int s;
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( generalized_eigensolver_real(Matrix4f()) );
s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(s,s)) );
// some trivial but implementation-wise tricky cases
CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(1,1)) );
CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(2,2)) );
CALL_SUBTEST_3( generalized_eigensolver_real(Matrix<double,1,1>()) );
CALL_SUBTEST_4( generalized_eigensolver_real(Matrix2d()) );
}
EIGEN_UNUSED_VARIABLE(s)
}