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Diffstat (limited to 'eigen/test/eigensolver_complex.cpp')
-rw-r--r-- | eigen/test/eigensolver_complex.cpp | 122 |
1 files changed, 122 insertions, 0 deletions
diff --git a/eigen/test/eigensolver_complex.cpp b/eigen/test/eigensolver_complex.cpp new file mode 100644 index 0000000..c9d8c08 --- /dev/null +++ b/eigen/test/eigensolver_complex.cpp @@ -0,0 +1,122 @@ +// 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) +} |