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// 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 Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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());
// regression test for bug 1098
{ GeneralizedSelfAdjointEigenSolver<MatrixType> eig1(a.adjoint() * a,b.adjoint() * b); eig1.compute(a.adjoint() * a,b.adjoint() * b); GeneralizedEigenSolver<MatrixType> eig2(a.adjoint() * a,b.adjoint() * b); eig2.compute(a.adjoint() * a,b.adjoint() * b); } }
void test_eigensolver_generalized_real() { for(int i = 0; i < g_repeat; i++) { int s = 0; 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()) ); TEST_SET_BUT_UNUSED_VARIABLE(s) } }
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