1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk> 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h" 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <Eigen/Eigenvalues> 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar,int Size> void hessenberg(int size = Size) 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar,Size,Size> MatrixType; 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // Test basic functionality: A = U H U* and H is Hessenberg 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int counter = 0; counter < g_repeat; ++counter) { 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType m = MatrixType::Random(size,size); 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath HessenbergDecomposition<MatrixType> hess(m); 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType Q = hess.matrixQ(); 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType H = hess.matrixH(); 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m, Q * H * Q.adjoint()); 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int row = 2; row < size; ++row) { 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int col = 0; col < row-1; ++col) { 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY(H(row,col) == (typename MatrixType::Scalar)0); 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // Test whether compute() and constructor returns same result 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType A = MatrixType::Random(size, size); 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath HessenbergDecomposition<MatrixType> cs1; 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath cs1.compute(A); 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath HessenbergDecomposition<MatrixType> cs2(A); 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_EQUAL(cs1.matrixH().eval(), cs2.matrixH().eval()); 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType cs1Q = cs1.matrixQ(); 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType cs2Q = cs2.matrixQ(); 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_EQUAL(cs1Q, cs2Q); 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // Test assertions for when used uninitialized 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath HessenbergDecomposition<MatrixType> hessUninitialized; 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT( hessUninitialized.matrixH() ); 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT( hessUninitialized.matrixQ() ); 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT( hessUninitialized.householderCoefficients() ); 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT( hessUninitialized.packedMatrix() ); 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // TODO: Add tests for packedMatrix() and householderCoefficients() 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_hessenberg() 53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1(( hessenberg<std::complex<double>,1>() )); 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_2(( hessenberg<std::complex<double>,2>() )); 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_3(( hessenberg<std::complex<float>,4>() )); 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_4(( hessenberg<float,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE)) )); 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_5(( hessenberg<std::complex<double>,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE)) )); 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // Test problem size constructors 61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_6(HessenbergDecomposition<MatrixXf>(10)); 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 63