| // 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) | 
 | } |