// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk> // // 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/. #include "main.h" #include <limits> #include <Eigen/Eigenvalues> template <typename MatrixType> void verifyIsQuasiTriangular(const MatrixType& T) { const Index size = T.cols(); typedef typename MatrixType::Scalar Scalar; // Check T is lower Hessenberg for (int row = 2; row < size; ++row) { for (int col = 0; col < row - 1; ++col) { VERIFY_IS_EQUAL(T(row, col), Scalar(0)); } } // Check that any non-zero on the subdiagonal is followed by a zero and is // part of a 2x2 diagonal block with imaginary eigenvalues. for (int row = 1; row < size; ++row) { if (!numext::is_exactly_zero(T(row, row - 1))) { VERIFY(row == size - 1 || numext::is_exactly_zero(T(row + 1, row))); Scalar tr = T(row - 1, row - 1) + T(row, row); Scalar det = T(row - 1, row - 1) * T(row, row) - T(row - 1, row) * T(row, row - 1); VERIFY(4 * det > tr * tr); } } } template <typename MatrixType> void schur(int size = MatrixType::ColsAtCompileTime) { // Test basic functionality: T is quasi-triangular and A = U T U* for (int counter = 0; counter < g_repeat; ++counter) { MatrixType A = MatrixType::Random(size, size); RealSchur<MatrixType> schurOfA(A); VERIFY_IS_EQUAL(schurOfA.info(), Success); MatrixType U = schurOfA.matrixU(); MatrixType T = schurOfA.matrixT(); verifyIsQuasiTriangular(T); VERIFY_IS_APPROX(A, U * T * U.transpose()); } // Test asserts when not initialized RealSchur<MatrixType> rsUninitialized; VERIFY_RAISES_ASSERT(rsUninitialized.matrixT()); VERIFY_RAISES_ASSERT(rsUninitialized.matrixU()); VERIFY_RAISES_ASSERT(rsUninitialized.info()); // Test whether compute() and constructor returns same result MatrixType A = MatrixType::Random(size, size); RealSchur<MatrixType> rs1; rs1.compute(A); RealSchur<MatrixType> rs2(A); VERIFY_IS_EQUAL(rs1.info(), Success); VERIFY_IS_EQUAL(rs2.info(), Success); VERIFY_IS_EQUAL(rs1.matrixT(), rs2.matrixT()); VERIFY_IS_EQUAL(rs1.matrixU(), rs2.matrixU()); // Test maximum number of iterations RealSchur<MatrixType> rs3; rs3.setMaxIterations(RealSchur<MatrixType>::m_maxIterationsPerRow * size).compute(A); VERIFY_IS_EQUAL(rs3.info(), Success); VERIFY_IS_EQUAL(rs3.matrixT(), rs1.matrixT()); VERIFY_IS_EQUAL(rs3.matrixU(), rs1.matrixU()); if (size > 2) { rs3.setMaxIterations(1).compute(A); VERIFY_IS_EQUAL(rs3.info(), NoConvergence); VERIFY_IS_EQUAL(rs3.getMaxIterations(), 1); } MatrixType Atriangular = A; Atriangular.template triangularView<StrictlyLower>().setZero(); rs3.setMaxIterations(1).compute(Atriangular); // triangular matrices do not need any iterations VERIFY_IS_EQUAL(rs3.info(), Success); VERIFY_IS_APPROX(rs3.matrixT(), Atriangular); // approx because of scaling... VERIFY_IS_EQUAL(rs3.matrixU(), MatrixType::Identity(size, size)); // Test computation of only T, not U RealSchur<MatrixType> rsOnlyT(A, false); VERIFY_IS_EQUAL(rsOnlyT.info(), Success); VERIFY_IS_EQUAL(rs1.matrixT(), rsOnlyT.matrixT()); VERIFY_RAISES_ASSERT(rsOnlyT.matrixU()); if (size > 2 && size < 20) { // Test matrix with NaN A(0, 0) = std::numeric_limits<typename MatrixType::Scalar>::quiet_NaN(); RealSchur<MatrixType> rsNaN(A); VERIFY_IS_EQUAL(rsNaN.info(), NoConvergence); } } void test_bug2633() { Eigen::MatrixXd A(4, 4); A << 0, 0, 0, -2, 1, 0, 0, -0, 0, 1, 0, 2, 0, 0, 2, -0; RealSchur<Eigen::MatrixXd> schur(A); VERIFY(schur.info() == Eigen::Success); } EIGEN_DECLARE_TEST(schur_real) { CALL_SUBTEST_1((schur<Matrix4f>())); CALL_SUBTEST_2((schur<MatrixXd>(internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 4)))); CALL_SUBTEST_3((schur<Matrix<float, 1, 1> >())); CALL_SUBTEST_4((schur<Matrix<double, 3, 3, Eigen::RowMajor> >())); // Test problem size constructors CALL_SUBTEST_5(RealSchur<MatrixXf>(10)); CALL_SUBTEST_6((test_bug2633())); }