Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame^] | 1 | // This file is part of Eigen, a lightweight C++ template library |
| 2 | // for linear algebra. |
| 3 | // |
| 4 | // Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr> |
| 5 | // |
| 6 | // This Source Code Form is subject to the terms of the Mozilla |
| 7 | // Public License v. 2.0. If a copy of the MPL was not distributed |
| 8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| 9 | |
| 10 | #include "main.h" |
| 11 | #include <limits> |
| 12 | #include <Eigen/Eigenvalues> |
| 13 | |
| 14 | template<typename MatrixType> void generalized_eigensolver_real(const MatrixType& m) |
| 15 | { |
| 16 | typedef typename MatrixType::Index Index; |
| 17 | /* this test covers the following files: |
| 18 | GeneralizedEigenSolver.h |
| 19 | */ |
| 20 | Index rows = m.rows(); |
| 21 | Index cols = m.cols(); |
| 22 | |
| 23 | typedef typename MatrixType::Scalar Scalar; |
| 24 | typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; |
| 25 | |
| 26 | MatrixType a = MatrixType::Random(rows,cols); |
| 27 | MatrixType b = MatrixType::Random(rows,cols); |
| 28 | MatrixType a1 = MatrixType::Random(rows,cols); |
| 29 | MatrixType b1 = MatrixType::Random(rows,cols); |
| 30 | MatrixType spdA = a.adjoint() * a + a1.adjoint() * a1; |
| 31 | MatrixType spdB = b.adjoint() * b + b1.adjoint() * b1; |
| 32 | |
| 33 | // lets compare to GeneralizedSelfAdjointEigenSolver |
| 34 | GeneralizedSelfAdjointEigenSolver<MatrixType> symmEig(spdA, spdB); |
| 35 | GeneralizedEigenSolver<MatrixType> eig(spdA, spdB); |
| 36 | |
| 37 | VERIFY_IS_EQUAL(eig.eigenvalues().imag().cwiseAbs().maxCoeff(), 0); |
| 38 | |
| 39 | VectorType realEigenvalues = eig.eigenvalues().real(); |
| 40 | std::sort(realEigenvalues.data(), realEigenvalues.data()+realEigenvalues.size()); |
| 41 | VERIFY_IS_APPROX(realEigenvalues, symmEig.eigenvalues()); |
| 42 | } |
| 43 | |
| 44 | void test_eigensolver_generalized_real() |
| 45 | { |
| 46 | for(int i = 0; i < g_repeat; i++) { |
| 47 | int s = 0; |
| 48 | CALL_SUBTEST_1( generalized_eigensolver_real(Matrix4f()) ); |
| 49 | s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4); |
| 50 | CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(s,s)) ); |
| 51 | |
| 52 | // some trivial but implementation-wise tricky cases |
| 53 | CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(1,1)) ); |
| 54 | CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(2,2)) ); |
| 55 | CALL_SUBTEST_3( generalized_eigensolver_real(Matrix<double,1,1>()) ); |
| 56 | CALL_SUBTEST_4( generalized_eigensolver_real(Matrix2d()) ); |
| 57 | TEST_SET_BUT_UNUSED_VARIABLE(s) |
| 58 | } |
| 59 | } |