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68 lines
2.5 KiB
C++
68 lines
2.5 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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#include <limits>
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#include <Eigen/Eigenvalues>
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template<typename MatrixType> void generalized_eigensolver_real(const MatrixType& m)
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{
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typedef typename MatrixType::Index Index;
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/* this test covers the following files:
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GeneralizedEigenSolver.h
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*/
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Index rows = m.rows();
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Index cols = m.cols();
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typedef typename MatrixType::Scalar Scalar;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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MatrixType a = MatrixType::Random(rows,cols);
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MatrixType b = MatrixType::Random(rows,cols);
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MatrixType a1 = MatrixType::Random(rows,cols);
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MatrixType b1 = MatrixType::Random(rows,cols);
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MatrixType spdA = a.adjoint() * a + a1.adjoint() * a1;
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MatrixType spdB = b.adjoint() * b + b1.adjoint() * b1;
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// lets compare to GeneralizedSelfAdjointEigenSolver
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GeneralizedSelfAdjointEigenSolver<MatrixType> symmEig(spdA, spdB);
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GeneralizedEigenSolver<MatrixType> eig(spdA, spdB);
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VERIFY_IS_EQUAL(eig.eigenvalues().imag().cwiseAbs().maxCoeff(), 0);
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VectorType realEigenvalues = eig.eigenvalues().real();
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std::sort(realEigenvalues.data(), realEigenvalues.data()+realEigenvalues.size());
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VERIFY_IS_APPROX(realEigenvalues, symmEig.eigenvalues());
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// regression test for bug 1098
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{
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GeneralizedSelfAdjointEigenSolver<MatrixType> eig1(a.adjoint() * a,b.adjoint() * b);
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eig1.compute(a.adjoint() * a,b.adjoint() * b);
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GeneralizedEigenSolver<MatrixType> eig2(a.adjoint() * a,b.adjoint() * b);
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eig2.compute(a.adjoint() * a,b.adjoint() * b);
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}
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}
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void test_eigensolver_generalized_real()
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{
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for(int i = 0; i < g_repeat; i++) {
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int s = 0;
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CALL_SUBTEST_1( generalized_eigensolver_real(Matrix4f()) );
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s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
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CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(s,s)) );
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// some trivial but implementation-wise tricky cases
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CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(1,1)) );
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CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(2,2)) );
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CALL_SUBTEST_3( generalized_eigensolver_real(Matrix<double,1,1>()) );
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CALL_SUBTEST_4( generalized_eigensolver_real(Matrix2d()) );
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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}
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}
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