// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk> // // 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> #include <Eigen/LU> /* Check that two column vectors are approximately equal upto permutations, by checking that the k-th power sums are equal for k = 1, ..., vec1.rows() */ template<typename VectorType> void verify_is_approx_upto_permutation(const VectorType& vec1, const VectorType& vec2) { typedef typename NumTraits<typename VectorType::Scalar>::Real RealScalar; VERIFY(vec1.cols() == 1); VERIFY(vec2.cols() == 1); VERIFY(vec1.rows() == vec2.rows()); for (int k = 1; k <= vec1.rows(); ++k) { VERIFY_IS_APPROX(vec1.array().pow(RealScalar(k)).sum(), vec2.array().pow(RealScalar(k)).sum()); } } template<typename MatrixType> void eigensolver(const MatrixType& m) { typedef typename MatrixType::Index Index; /* this test covers the following files: ComplexEigenSolver.h, and indirectly ComplexSchur.h */ Index rows = m.rows(); Index cols = m.cols(); typedef typename MatrixType::Scalar Scalar; typedef typename NumTraits<Scalar>::Real RealScalar; MatrixType a = MatrixType::Random(rows,cols); MatrixType symmA = a.adjoint() * a; ComplexEigenSolver<MatrixType> ei0(symmA); VERIFY_IS_EQUAL(ei0.info(), Success); VERIFY_IS_APPROX(symmA * ei0.eigenvectors(), ei0.eigenvectors() * ei0.eigenvalues().asDiagonal()); ComplexEigenSolver<MatrixType> ei1(a); VERIFY_IS_EQUAL(ei1.info(), Success); VERIFY_IS_APPROX(a * ei1.eigenvectors(), ei1.eigenvectors() * ei1.eigenvalues().asDiagonal()); // Note: If MatrixType is real then a.eigenvalues() uses EigenSolver and thus // another algorithm so results may differ slightly verify_is_approx_upto_permutation(a.eigenvalues(), ei1.eigenvalues()); ComplexEigenSolver<MatrixType> ei2; ei2.setMaxIterations(ComplexSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a); VERIFY_IS_EQUAL(ei2.info(), Success); VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors()); VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues()); if (rows > 2) { ei2.setMaxIterations(1).compute(a); VERIFY_IS_EQUAL(ei2.info(), NoConvergence); VERIFY_IS_EQUAL(ei2.getMaxIterations(), 1); } ComplexEigenSolver<MatrixType> eiNoEivecs(a, false); VERIFY_IS_EQUAL(eiNoEivecs.info(), Success); VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues()); // Regression test for issue #66 MatrixType z = MatrixType::Zero(rows,cols); ComplexEigenSolver<MatrixType> eiz(z); VERIFY((eiz.eigenvalues().cwiseEqual(0)).all()); MatrixType id = MatrixType::Identity(rows, cols); VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1)); if (rows > 1) { // Test matrix with NaN a(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN(); ComplexEigenSolver<MatrixType> eiNaN(a); VERIFY_IS_EQUAL(eiNaN.info(), NoConvergence); } } template<typename MatrixType> void eigensolver_verify_assert(const MatrixType& m) { ComplexEigenSolver<MatrixType> eig; VERIFY_RAISES_ASSERT(eig.eigenvectors()); VERIFY_RAISES_ASSERT(eig.eigenvalues()); MatrixType a = MatrixType::Random(m.rows(),m.cols()); eig.compute(a, false); VERIFY_RAISES_ASSERT(eig.eigenvectors()); } void test_eigensolver_complex() { int s = 0; for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( eigensolver(Matrix4cf()) ); s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4); CALL_SUBTEST_2( eigensolver(MatrixXcd(s,s)) ); CALL_SUBTEST_3( eigensolver(Matrix<std::complex<float>, 1, 1>()) ); CALL_SUBTEST_4( eigensolver(Matrix3f()) ); } CALL_SUBTEST_1( eigensolver_verify_assert(Matrix4cf()) ); s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4); CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXcd(s,s)) ); CALL_SUBTEST_3( eigensolver_verify_assert(Matrix<std::complex<float>, 1, 1>()) ); CALL_SUBTEST_4( eigensolver_verify_assert(Matrix3f()) ); // Test problem size constructors CALL_SUBTEST_5(ComplexEigenSolver<MatrixXf> tmp(s)); TEST_SET_BUT_UNUSED_VARIABLE(s) }