| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2012 Alexey Korepanov <kaikaikai@yandex.ru> | |
| // | |
| // 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/. | |
| #define EIGEN_RUNTIME_NO_MALLOC | |
| #include "main.h" | |
| #include <limits> | |
| #include <Eigen/Eigenvalues> | |
| template<typename MatrixType> void real_qz(const MatrixType& m) | |
| { | |
| /* this test covers the following files: | |
| RealQZ.h | |
| */ | |
| using std::abs; | |
| typedef typename MatrixType::Scalar Scalar; | |
| Index dim = m.cols(); | |
| MatrixType A = MatrixType::Random(dim,dim), | |
| B = MatrixType::Random(dim,dim); | |
| // Regression test for bug 985: Randomly set rows or columns to zero | |
| Index k=internal::random<Index>(0, dim-1); | |
| switch(internal::random<int>(0,10)) { | |
| case 0: | |
| A.row(k).setZero(); break; | |
| case 1: | |
| A.col(k).setZero(); break; | |
| case 2: | |
| B.row(k).setZero(); break; | |
| case 3: | |
| B.col(k).setZero(); break; | |
| default: | |
| break; | |
| } | |
| RealQZ<MatrixType> qz(dim); | |
| // TODO enable full-prealocation of required memory, this probably requires an in-place mode for HessenbergDecomposition | |
| //Eigen::internal::set_is_malloc_allowed(false); | |
| qz.compute(A,B); | |
| //Eigen::internal::set_is_malloc_allowed(true); | |
| VERIFY_IS_EQUAL(qz.info(), Success); | |
| // check for zeros | |
| bool all_zeros = true; | |
| for (Index i=0; i<A.cols(); i++) | |
| for (Index j=0; j<i; j++) { | |
| if (abs(qz.matrixT()(i,j))!=Scalar(0.0)) | |
| { | |
| std::cerr << "Error: T(" << i << "," << j << ") = " << qz.matrixT()(i,j) << std::endl; | |
| all_zeros = false; | |
| } | |
| if (j<i-1 && abs(qz.matrixS()(i,j))!=Scalar(0.0)) | |
| { | |
| std::cerr << "Error: S(" << i << "," << j << ") = " << qz.matrixS()(i,j) << std::endl; | |
| all_zeros = false; | |
| } | |
| if (j==i-1 && j>0 && abs(qz.matrixS()(i,j))!=Scalar(0.0) && abs(qz.matrixS()(i-1,j-1))!=Scalar(0.0)) | |
| { | |
| std::cerr << "Error: S(" << i << "," << j << ") = " << qz.matrixS()(i,j) << " && S(" << i-1 << "," << j-1 << ") = " << qz.matrixS()(i-1,j-1) << std::endl; | |
| all_zeros = false; | |
| } | |
| } | |
| VERIFY_IS_EQUAL(all_zeros, true); | |
| VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixS()*qz.matrixZ(), A); | |
| VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixT()*qz.matrixZ(), B); | |
| VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixQ().adjoint(), MatrixType::Identity(dim,dim)); | |
| VERIFY_IS_APPROX(qz.matrixZ()*qz.matrixZ().adjoint(), MatrixType::Identity(dim,dim)); | |
| } | |
| EIGEN_DECLARE_TEST(real_qz) | |
| { | |
| int s = 0; | |
| for(int i = 0; i < g_repeat; i++) { | |
| CALL_SUBTEST_1( real_qz(Matrix4f()) ); | |
| s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4); | |
| CALL_SUBTEST_2( real_qz(MatrixXd(s,s)) ); | |
| // some trivial but implementation-wise tricky cases | |
| CALL_SUBTEST_2( real_qz(MatrixXd(1,1)) ); | |
| CALL_SUBTEST_2( real_qz(MatrixXd(2,2)) ); | |
| CALL_SUBTEST_3( real_qz(Matrix<double,1,1>()) ); | |
| CALL_SUBTEST_4( real_qz(Matrix2d()) ); | |
| } | |
| TEST_SET_BUT_UNUSED_VARIABLE(s) | |
| } |