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dc9206cec5
(could come back to redux after it has been vectorized, and could serve as a starting point for that) also make the abs2 functor vectorizable (for real types).
118 lines
4.0 KiB
C++
118 lines
4.0 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
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// Copyright (C) 2006-2008 Benoit Jacob <jacob@math.jussieu.fr>
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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_REDUX_H
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#define EIGEN_REDUX_H
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template<typename BinaryOp, typename Derived, int Start, int Length>
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struct ei_redux_impl
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{
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enum {
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HalfLength = Length/2
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};
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typedef typename ei_result_of<BinaryOp(typename Derived::Scalar)>::type Scalar;
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static Scalar run(const Derived &mat, const BinaryOp& func)
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{
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return func(
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ei_redux_impl<BinaryOp, Derived, Start, HalfLength>::run(mat, func),
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ei_redux_impl<BinaryOp, Derived, Start+HalfLength, Length - HalfLength>::run(mat, func));
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}
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};
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template<typename BinaryOp, typename Derived, int Start>
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struct ei_redux_impl<BinaryOp, Derived, Start, 1>
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{
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enum {
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col = Start / Derived::RowsAtCompileTime,
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row = Start % Derived::RowsAtCompileTime
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};
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typedef typename ei_result_of<BinaryOp(typename Derived::Scalar)>::type Scalar;
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static Scalar run(const Derived &mat, const BinaryOp &)
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{
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return mat.coeff(row, col);
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}
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};
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template<typename BinaryOp, typename Derived, int Start>
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struct ei_redux_impl<BinaryOp, Derived, Start, Dynamic>
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{
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typedef typename ei_result_of<BinaryOp(typename Derived::Scalar)>::type Scalar;
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static Scalar run(const Derived& mat, const BinaryOp& func)
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{
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Scalar res;
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res = mat.coeff(0,0);
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for(int i = 1; i < mat.rows(); i++)
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res = func(res, mat.coeff(i, 0));
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for(int j = 1; j < mat.cols(); j++)
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for(int i = 0; i < mat.rows(); i++)
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res = func(res, mat.coeff(i, j));
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return res;
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}
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};
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/** \returns the result of a full redux operation on the whole matrix or vector using \a func
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*
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* The template parameter \a BinaryOp is the type of the functor \a func which must be
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* an assiociative operator. Both current STL and TR1 functor styles are handled.
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*
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* \sa MatrixBase::sum(), MatrixBase::minCoeff(), MatrixBase::maxCoeff(), MatrixBase::verticalRedux(), MatrixBase::horizontalRedux()
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*/
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template<typename Derived>
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template<typename BinaryOp>
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typename ei_result_of<BinaryOp(typename ei_traits<Derived>::Scalar)>::type
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MatrixBase<Derived>::redux(const BinaryOp& func) const
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{
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const bool unroll = SizeAtCompileTime * CoeffReadCost
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+ (SizeAtCompileTime-1) * ei_functor_traits<BinaryOp>::Cost
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<= EIGEN_UNROLLING_LIMIT;
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return ei_redux_impl<BinaryOp, Derived, 0,
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unroll ? int(SizeAtCompileTime) : Dynamic>
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::run(derived(), func);
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}
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/** \returns the minimum of all coefficients of *this
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*/
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template<typename Derived>
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inline typename ei_traits<Derived>::Scalar
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MatrixBase<Derived>::minCoeff() const
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{
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return this->redux(Eigen::ei_scalar_min_op<Scalar>());
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}
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/** \returns the maximum of all coefficients of *this
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*/
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template<typename Derived>
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inline typename ei_traits<Derived>::Scalar
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MatrixBase<Derived>::maxCoeff() const
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{
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return this->redux(Eigen::ei_scalar_max_op<Scalar>());
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}
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#endif // EIGEN_REDUX_H
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