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add new Householder module
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@ -8,8 +8,7 @@ string(REGEX MATCH "define *EIGEN_MAJOR_VERSION ([0-9]*)" _eigen2_major_version_
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set(EIGEN2_MAJOR_VERSION "${CMAKE_MATCH_1}")
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string(REGEX MATCH "define *EIGEN_MINOR_VERSION ([0-9]*)" _eigen2_minor_version_match "${_eigen2_version_header}")
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set(EIGEN2_MINOR_VERSION "${CMAKE_MATCH_1}")
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# TODO find a way to automatically remove the unstable suffix
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set(EIGEN_VERSION_NUMBER ${EIGEN2_WORLD_VERSION}.${EIGEN2_MAJOR_VERSION}.${EIGEN2_MINOR_VERSION}-unstable)
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set(EIGEN_VERSION_NUMBER ${EIGEN2_WORLD_VERSION}.${EIGEN2_MAJOR_VERSION}.${EIGEN2_MINOR_VERSION})
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# if the mercurial program is absent, this will leave the EIGEN_HG_REVISION string empty,
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# but won't stop CMake.
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24
Eigen/Householder
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24
Eigen/Householder
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@ -0,0 +1,24 @@
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#ifndef EIGEN_HOUSEHOLDER_MODULE_H
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#define EIGEN_HOUSEHOLDER_MODULE_H
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#include "Core"
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#include "src/Core/util/DisableMSVCWarnings.h"
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namespace Eigen {
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/** \defgroup Householder_Module Householder module
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* This module provides householder transformations.
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*
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* \code
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* #include <Eigen/Householder>
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* \endcode
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*/
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#include "src/Householder/Householder.h"
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} // namespace Eigen
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#include "src/Core/util/EnableMSVCWarnings.h"
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#endif // EIGEN_HOUSEHOLDER_MODULE_H
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@ -40,6 +40,7 @@ template<typename Derived> struct AnyMatrixBase
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Derived& derived() { return *static_cast<Derived*>(this); }
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const Derived& derived() const { return *static_cast<const Derived*>(this); }
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};
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/** Common base class for all classes T such that there are overloaded operator* allowing to
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* multiply a MatrixBase by a T on both sides.
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*
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@ -749,6 +750,19 @@ template<typename Derived> class MatrixBase
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template<typename Derived1, typename Derived2>
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Derived& lazyAssign(const SparseProduct<Derived1,Derived2,DenseTimeSparseProduct>& product);
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////////// Householder module ///////////
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template<typename EssentialPart>
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void makeHouseholder(EssentialPart *essential,
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RealScalar *beta) const;
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template<typename EssentialPart>
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void applyHouseholderOnTheLeft(const EssentialPart& essential,
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const RealScalar& beta);
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template<typename EssentialPart>
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void applyHouseholderOnTheRight(const EssentialPart& essential,
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const RealScalar& beta);
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#ifdef EIGEN_MATRIXBASE_PLUGIN
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#include EIGEN_MATRIXBASE_PLUGIN
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#endif
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6
Eigen/src/Householder/CMakeLists.txt
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6
Eigen/src/Householder/CMakeLists.txt
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@ -0,0 +1,6 @@
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FILE(GLOB Eigen_Householder_SRCS "*.h")
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INSTALL(FILES
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${Eigen_Householder_SRCS}
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DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Householder COMPONENT Devel
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)
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88
Eigen/src/Householder/Householder.h
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88
Eigen/src/Householder/Householder.h
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@ -0,0 +1,88 @@
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_HOUSEHOLDER_H
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#define EIGEN_HOUSEHOLDER_H
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template<int n> struct ei_decrement_size
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{
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enum {
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ret = (n==1 || n==Dynamic) ? n : n-1
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};
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};
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template<typename Derived>
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template<typename EssentialPart>
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void MatrixBase<Derived>::makeHouseholder(
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EssentialPart *essential,
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RealScalar *beta) const
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{
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EIGEN_STATIC_ASSERT_VECTOR_ONLY(EssentialPart)
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RealScalar _squaredNorm = squaredNorm();
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Scalar c0;
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if(ei_abs2(coeff(0)) <= ei_abs2(precision<Scalar>()) * _squaredNorm)
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{
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c0 = ei_sqrt(_squaredNorm);
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}
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else
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{
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Scalar sign = coeff(0) / ei_abs(coeff(0));
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c0 = coeff(0) + sign * ei_sqrt(_squaredNorm);
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}
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*essential = end(size()-1) / c0; // FIXME take advantage of fixed size
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const RealScalar c0abs2 = ei_abs2(c0);
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*beta = RealScalar(2) * c0abs2 / (c0abs2 + _squaredNorm - ei_abs2(coeff(0)));
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}
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template<typename Derived>
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template<typename EssentialPart>
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void MatrixBase<Derived>::applyHouseholderOnTheLeft(
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const EssentialPart& essential,
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const RealScalar& beta)
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{
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Matrix<Scalar, 1, ColsAtCompileTime, PlainMatrixType::Options, 1, MaxColsAtCompileTime> tmp(cols());
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tmp = row(0) + essential.adjoint() * block(1,0,rows()-1,cols());
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// FIXME take advantage of fixed size
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// FIXME play with lazy()
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// FIXME maybe not a good idea to use matrix product
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row(0) -= beta * tmp;
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block(1,0,rows()-1,cols()) -= beta * essential * tmp;
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}
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template<typename Derived>
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template<typename EssentialPart>
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void MatrixBase<Derived>::applyHouseholderOnTheRight(
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const EssentialPart& essential,
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const RealScalar& beta)
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{
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Matrix<Scalar, RowsAtCompileTime, 1, PlainMatrixType::Options, MaxRowsAtCompileTime, 1> tmp(rows());
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tmp = col(0) + block(0,1,rows(),cols()-1) * essential.conjugate();
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// FIXME take advantage of fixed size
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// FIXME play with lazy()
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// FIXME maybe not a good idea to use matrix product
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col(0) -= beta * tmp;
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block(0,1,rows(),cols()-1) -= beta * tmp * essential.transpose();
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}
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#endif // EIGEN_HOUSEHOLDER_H
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@ -149,7 +149,7 @@ ei_add_test(sparse_basic)
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ei_add_test(sparse_product)
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ei_add_test(sparse_solvers " " "${SPARSE_LIBS}")
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ei_add_test(umeyama)
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ei_add_test(householder)
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ei_add_property(EIGEN_TESTING_SUMMARY "CXX: ${CMAKE_CXX_COMPILER}\n")
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if(CMAKE_COMPILER_IS_GNUCXX)
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89
test/householder.cpp
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89
test/householder.cpp
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@ -0,0 +1,89 @@
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "main.h"
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#include <Eigen/Householder>
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template<typename MatrixType> void householder(const MatrixType& m)
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{
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/* this test covers the following files:
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Householder.h
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*/
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int rows = m.rows();
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int cols = m.cols();
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typedef typename MatrixType::Scalar Scalar;
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typedef typename NumTraits<Scalar>::Real RealScalar;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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typedef Matrix<Scalar, ei_decrement_size<MatrixType::RowsAtCompileTime>::ret, 1> EssentialVectorType;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
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RealScalar beta;
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EssentialVectorType essential;
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VectorType v1 = VectorType::Random(rows), v2;
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v2 = v1;
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v1.makeHouseholder(&essential, &beta);
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v1.applyHouseholderOnTheLeft(essential,beta);
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VERIFY_IS_APPROX(v1.norm(), v2.norm());
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VERIFY_IS_MUCH_SMALLER_THAN(v1.end(rows-1).norm(), v1.norm());
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v1 = VectorType::Random(rows);
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v2 = v1;
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v1.applyHouseholderOnTheLeft(essential,beta);
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VERIFY_IS_APPROX(v1.norm(), v2.norm());
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MatrixType m1(rows, cols),
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m2(rows, cols);
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v1 = VectorType::Random(rows);
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m1.colwise() = v1;
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m2 = m1;
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m1.col(0).makeHouseholder(&essential, &beta);
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m1.applyHouseholderOnTheLeft(essential,beta);
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VERIFY_IS_APPROX(m1.norm(), m2.norm());
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VERIFY_IS_MUCH_SMALLER_THAN(m1.block(1,0,rows-1,cols).norm(), m1.norm());
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v1 = VectorType::Random(rows);
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SquareMatrixType m3(rows,rows), m4(rows,rows);
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m3.rowwise() = v1.transpose();
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m4 = m3;
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m3.row(0).makeHouseholder(&essential, &beta);
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m3.applyHouseholderOnTheRight(essential,beta);
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VERIFY_IS_APPROX(m3.norm(), m4.norm());
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VERIFY_IS_MUCH_SMALLER_THAN(m3.block(0,1,rows,rows-1).norm(), m3.norm());
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}
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void test_householder()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST( householder(Matrix<double,2,2>()) );
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CALL_SUBTEST( householder(Matrix<float,2,3>()) );
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CALL_SUBTEST( householder(Matrix<double,3,5>()) );
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CALL_SUBTEST( householder(Matrix<float,4,4>()) );
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CALL_SUBTEST( householder(MatrixXd(10,12)) );
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CALL_SUBTEST( householder(MatrixXcf(16,17)) );
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}
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}
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