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125 lines
4.6 KiB
125 lines
4.6 KiB
// 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) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
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// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
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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 eigensolver(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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EigenSolver.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 typename NumTraits<Scalar>::Real RealScalar;
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typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
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typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
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MatrixType a = MatrixType::Random(rows,cols);
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MatrixType a1 = MatrixType::Random(rows,cols);
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MatrixType symmA = a.adjoint() * a + a1.adjoint() * a1;
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EigenSolver<MatrixType> ei0(symmA);
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VERIFY_IS_EQUAL(ei0.info(), Success);
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VERIFY_IS_APPROX(symmA * ei0.pseudoEigenvectors(), ei0.pseudoEigenvectors() * ei0.pseudoEigenvalueMatrix());
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VERIFY_IS_APPROX((symmA.template cast<Complex>()) * (ei0.pseudoEigenvectors().template cast<Complex>()),
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(ei0.pseudoEigenvectors().template cast<Complex>()) * (ei0.eigenvalues().asDiagonal()));
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EigenSolver<MatrixType> ei1(a);
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VERIFY_IS_EQUAL(ei1.info(), Success);
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VERIFY_IS_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
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VERIFY_IS_APPROX(a.template cast<Complex>() * ei1.eigenvectors(),
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ei1.eigenvectors() * ei1.eigenvalues().asDiagonal());
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VERIFY_IS_APPROX(ei1.eigenvectors().colwise().norm(), RealVectorType::Ones(rows).transpose());
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VERIFY_IS_APPROX(a.eigenvalues(), ei1.eigenvalues());
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EigenSolver<MatrixType> ei2;
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ei2.setMaxIterations(RealSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
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VERIFY_IS_EQUAL(ei2.info(), Success);
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VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
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VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
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if (rows > 2) {
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ei2.setMaxIterations(1).compute(a);
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VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
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VERIFY_IS_EQUAL(ei2.getMaxIterations(), 1);
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}
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EigenSolver<MatrixType> eiNoEivecs(a, false);
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VERIFY_IS_EQUAL(eiNoEivecs.info(), Success);
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VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues());
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VERIFY_IS_APPROX(ei1.pseudoEigenvalueMatrix(), eiNoEivecs.pseudoEigenvalueMatrix());
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MatrixType id = MatrixType::Identity(rows, cols);
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VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1));
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if (rows > 2)
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{
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// Test matrix with NaN
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a(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
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EigenSolver<MatrixType> eiNaN(a);
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VERIFY_IS_EQUAL(eiNaN.info(), NoConvergence);
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}
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}
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template<typename MatrixType> void eigensolver_verify_assert(const MatrixType& m)
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{
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EigenSolver<MatrixType> eig;
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VERIFY_RAISES_ASSERT(eig.eigenvectors());
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VERIFY_RAISES_ASSERT(eig.pseudoEigenvectors());
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VERIFY_RAISES_ASSERT(eig.pseudoEigenvalueMatrix());
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VERIFY_RAISES_ASSERT(eig.eigenvalues());
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MatrixType a = MatrixType::Random(m.rows(),m.cols());
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eig.compute(a, false);
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VERIFY_RAISES_ASSERT(eig.eigenvectors());
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VERIFY_RAISES_ASSERT(eig.pseudoEigenvectors());
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}
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void test_eigensolver_generic()
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{
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int s = 0;
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( eigensolver(Matrix4f()) );
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s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
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CALL_SUBTEST_2( eigensolver(MatrixXd(s,s)) );
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// some trivial but implementation-wise tricky cases
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CALL_SUBTEST_2( eigensolver(MatrixXd(1,1)) );
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CALL_SUBTEST_2( eigensolver(MatrixXd(2,2)) );
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CALL_SUBTEST_3( eigensolver(Matrix<double,1,1>()) );
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CALL_SUBTEST_4( eigensolver(Matrix2d()) );
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}
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CALL_SUBTEST_1( eigensolver_verify_assert(Matrix4f()) );
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s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
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CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXd(s,s)) );
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CALL_SUBTEST_3( eigensolver_verify_assert(Matrix<double,1,1>()) );
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CALL_SUBTEST_4( eigensolver_verify_assert(Matrix2d()) );
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// Test problem size constructors
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CALL_SUBTEST_5(EigenSolver<MatrixXf> tmp(s));
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// regression test for bug 410
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CALL_SUBTEST_2(
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{
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MatrixXd A(1,1);
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A(0,0) = std::sqrt(-1.);
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Eigen::EigenSolver<MatrixXd> solver(A);
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MatrixXd V(1, 1);
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V(0,0) = solver.eigenvectors()(0,0).real();
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}
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);
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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}
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