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// 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(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 (T(row,row-1) != Scalar(0)) {
VERIFY(row == size-1 || T(row+1,row) == 0);
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);
}
}
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));
}
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