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author | Stanislaw Halik <sthalik@misaki.pl> | 2016-09-18 12:42:15 +0200 |
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committer | Stanislaw Halik <sthalik@misaki.pl> | 2016-11-02 15:12:04 +0100 |
commit | 44861dcbfeee041223c4aac1ee075e92fa4daa01 (patch) | |
tree | 6dfdfd9637846a7aedd71ace97d7d2ad366496d7 /eigen/test/householder.cpp | |
parent | f3fe458b9e0a29a99a39d47d9a76dc18964b6fec (diff) |
update
Diffstat (limited to 'eigen/test/householder.cpp')
-rw-r--r-- | eigen/test/householder.cpp | 138 |
1 files changed, 138 insertions, 0 deletions
diff --git a/eigen/test/householder.cpp b/eigen/test/householder.cpp new file mode 100644 index 0000000..c5f6b5e --- /dev/null +++ b/eigen/test/householder.cpp @@ -0,0 +1,138 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com> +// +// 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 <Eigen/QR> + +template<typename MatrixType> void householder(const MatrixType& m) +{ + typedef typename MatrixType::Index Index; + static bool even = true; + even = !even; + /* this test covers the following files: + Householder.h + */ + Index rows = m.rows(); + Index cols = m.cols(); + + typedef typename MatrixType::Scalar Scalar; + typedef typename NumTraits<Scalar>::Real RealScalar; + typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; + typedef Matrix<Scalar, internal::decrement_size<MatrixType::RowsAtCompileTime>::ret, 1> EssentialVectorType; + typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType; + typedef Matrix<Scalar, Dynamic, MatrixType::ColsAtCompileTime> HBlockMatrixType; + typedef Matrix<Scalar, Dynamic, 1> HCoeffsVectorType; + + typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::RowsAtCompileTime> TMatrixType; + + Matrix<Scalar, EIGEN_SIZE_MAX(MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime), 1> _tmp((std::max)(rows,cols)); + Scalar* tmp = &_tmp.coeffRef(0,0); + + Scalar beta; + RealScalar alpha; + EssentialVectorType essential; + + VectorType v1 = VectorType::Random(rows), v2; + v2 = v1; + v1.makeHouseholder(essential, beta, alpha); + v1.applyHouseholderOnTheLeft(essential,beta,tmp); + VERIFY_IS_APPROX(v1.norm(), v2.norm()); + if(rows>=2) VERIFY_IS_MUCH_SMALLER_THAN(v1.tail(rows-1).norm(), v1.norm()); + v1 = VectorType::Random(rows); + v2 = v1; + v1.applyHouseholderOnTheLeft(essential,beta,tmp); + VERIFY_IS_APPROX(v1.norm(), v2.norm()); + + MatrixType m1(rows, cols), + m2(rows, cols); + + v1 = VectorType::Random(rows); + if(even) v1.tail(rows-1).setZero(); + m1.colwise() = v1; + m2 = m1; + m1.col(0).makeHouseholder(essential, beta, alpha); + m1.applyHouseholderOnTheLeft(essential,beta,tmp); + VERIFY_IS_APPROX(m1.norm(), m2.norm()); + if(rows>=2) VERIFY_IS_MUCH_SMALLER_THAN(m1.block(1,0,rows-1,cols).norm(), m1.norm()); + VERIFY_IS_MUCH_SMALLER_THAN(numext::imag(m1(0,0)), numext::real(m1(0,0))); + VERIFY_IS_APPROX(numext::real(m1(0,0)), alpha); + + v1 = VectorType::Random(rows); + if(even) v1.tail(rows-1).setZero(); + SquareMatrixType m3(rows,rows), m4(rows,rows); + m3.rowwise() = v1.transpose(); + m4 = m3; + m3.row(0).makeHouseholder(essential, beta, alpha); + m3.applyHouseholderOnTheRight(essential,beta,tmp); + VERIFY_IS_APPROX(m3.norm(), m4.norm()); + if(rows>=2) VERIFY_IS_MUCH_SMALLER_THAN(m3.block(0,1,rows,rows-1).norm(), m3.norm()); + VERIFY_IS_MUCH_SMALLER_THAN(numext::imag(m3(0,0)), numext::real(m3(0,0))); + VERIFY_IS_APPROX(numext::real(m3(0,0)), alpha); + + // test householder sequence on the left with a shift + + Index shift = internal::random<Index>(0, std::max<Index>(rows-2,0)); + Index brows = rows - shift; + m1.setRandom(rows, cols); + HBlockMatrixType hbm = m1.block(shift,0,brows,cols); + HouseholderQR<HBlockMatrixType> qr(hbm); + m2 = m1; + m2.block(shift,0,brows,cols) = qr.matrixQR(); + HCoeffsVectorType hc = qr.hCoeffs().conjugate(); + HouseholderSequence<MatrixType, HCoeffsVectorType> hseq(m2, hc); + hseq.setLength(hc.size()).setShift(shift); + VERIFY(hseq.length() == hc.size()); + VERIFY(hseq.shift() == shift); + + MatrixType m5 = m2; + m5.block(shift,0,brows,cols).template triangularView<StrictlyLower>().setZero(); + VERIFY_IS_APPROX(hseq * m5, m1); // test applying hseq directly + m3 = hseq; + VERIFY_IS_APPROX(m3 * m5, m1); // test evaluating hseq to a dense matrix, then applying + + SquareMatrixType hseq_mat = hseq; + SquareMatrixType hseq_mat_conj = hseq.conjugate(); + SquareMatrixType hseq_mat_adj = hseq.adjoint(); + SquareMatrixType hseq_mat_trans = hseq.transpose(); + SquareMatrixType m6 = SquareMatrixType::Random(rows, rows); + VERIFY_IS_APPROX(hseq_mat.adjoint(), hseq_mat_adj); + VERIFY_IS_APPROX(hseq_mat.conjugate(), hseq_mat_conj); + VERIFY_IS_APPROX(hseq_mat.transpose(), hseq_mat_trans); + VERIFY_IS_APPROX(hseq_mat * m6, hseq_mat * m6); + VERIFY_IS_APPROX(hseq_mat.adjoint() * m6, hseq_mat_adj * m6); + VERIFY_IS_APPROX(hseq_mat.conjugate() * m6, hseq_mat_conj * m6); + VERIFY_IS_APPROX(hseq_mat.transpose() * m6, hseq_mat_trans * m6); + VERIFY_IS_APPROX(m6 * hseq_mat, m6 * hseq_mat); + VERIFY_IS_APPROX(m6 * hseq_mat.adjoint(), m6 * hseq_mat_adj); + VERIFY_IS_APPROX(m6 * hseq_mat.conjugate(), m6 * hseq_mat_conj); + VERIFY_IS_APPROX(m6 * hseq_mat.transpose(), m6 * hseq_mat_trans); + + // test householder sequence on the right with a shift + + TMatrixType tm2 = m2.transpose(); + HouseholderSequence<TMatrixType, HCoeffsVectorType, OnTheRight> rhseq(tm2, hc); + rhseq.setLength(hc.size()).setShift(shift); + VERIFY_IS_APPROX(rhseq * m5, m1); // test applying rhseq directly + m3 = rhseq; + VERIFY_IS_APPROX(m3 * m5, m1); // test evaluating rhseq to a dense matrix, then applying +} + +void test_householder() +{ + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_1( householder(Matrix<double,2,2>()) ); + CALL_SUBTEST_2( householder(Matrix<float,2,3>()) ); + CALL_SUBTEST_3( householder(Matrix<double,3,5>()) ); + CALL_SUBTEST_4( householder(Matrix<float,4,4>()) ); + CALL_SUBTEST_5( householder(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE),internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( householder(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE),internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_7( householder(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE),internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_8( householder(Matrix<double,1,1>()) ); + } +} |