| // 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; | 
 |  | 
 |   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 (!numext::is_exactly_zero(abs(qz.matrixT()(i, j)))) { | 
 |         std::cerr << "Error: T(" << i << "," << j << ") = " << qz.matrixT()(i, j) << std::endl; | 
 |         all_zeros = false; | 
 |       } | 
 |       if (j < i - 1 && !numext::is_exactly_zero(abs(qz.matrixS()(i, j)))) { | 
 |         std::cerr << "Error: S(" << i << "," << j << ") = " << qz.matrixS()(i, j) << std::endl; | 
 |         all_zeros = false; | 
 |       } | 
 |       if (j == i - 1 && j > 0 && !numext::is_exactly_zero(abs(qz.matrixS()(i, j))) && | 
 |           !numext::is_exactly_zero(abs(qz.matrixS()(i - 1, j - 1)))) { | 
 |         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) | 
 | } |