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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob@math.jussieu.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_REDUX_H
#define EIGEN_REDUX_H
template<typename BinaryOp, typename Derived, int Start, int Length>
struct ei_redux_unroller
{
enum {
HalfLength = Length/2
};
typedef typename ei_result_of<BinaryOp(typename Derived::Scalar)>::type Scalar;
static Scalar run(const Derived &mat, const BinaryOp& func)
{
return func(
ei_redux_unroller<BinaryOp, Derived, Start, HalfLength>::run(mat, func),
ei_redux_unroller<BinaryOp, Derived, Start+HalfLength, Length - HalfLength>::run(mat, func));
}
};
template<typename BinaryOp, typename Derived, int Start>
struct ei_redux_unroller<BinaryOp, Derived, Start, 1>
{
enum {
col = Start / Derived::RowsAtCompileTime,
row = Start % Derived::RowsAtCompileTime
};
typedef typename ei_result_of<BinaryOp(typename Derived::Scalar)>::type Scalar;
static Scalar run(const Derived &mat, const BinaryOp &func)
{
return mat.coeff(row, col);
}
};
template<typename BinaryOp, typename Derived, int Start>
struct ei_redux_unroller<BinaryOp, Derived, Start, Dynamic>
{
typedef typename ei_result_of<BinaryOp(typename Derived::Scalar)>::type Scalar;
static Scalar run(const Derived&, const BinaryOp&) { return Scalar(); }
};
/** \class PartialRedux
*
* \brief Generic expression of a partially reduxed matrix
*
* \param Direction indicates the direction of the redux (Vertical or Horizontal)
* \param BinaryOp type of the binary functor implementing the operator (must be associative)
* \param MatrixType the type of the matrix we are applying the redux operation
*
* This class represents an expression of a partial redux operator of a matrix.
* It is the return type of MatrixBase::verticalRedux(), MatrixBase::horizontalRedux(),
* and most of the time this is the only way it is used.
*
* \sa class CwiseBinaryOp
*/
template<int Direction, typename BinaryOp, typename MatrixType>
struct ei_traits<PartialRedux<Direction, BinaryOp, MatrixType> >
{
typedef typename ei_result_of<
BinaryOp(typename MatrixType::Scalar)
>::type Scalar;
enum {
RowsAtCompileTime = Direction==Vertical ? 1 : MatrixType::RowsAtCompileTime,
ColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::ColsAtCompileTime,
MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
Flags = (RowsAtCompileTime == Dynamic || ColsAtCompileTime == Dynamic)
? (unsigned int)MatrixType::Flags
: (unsigned int)MatrixType::Flags & ~LargeBit
};
};
template<int Direction, typename BinaryOp, typename MatrixType>
class PartialRedux : ei_no_assignment_operator,
public MatrixBase<PartialRedux<Direction, BinaryOp, MatrixType> >
{
public:
EIGEN_GENERIC_PUBLIC_INTERFACE(PartialRedux)
PartialRedux(const MatrixType& mat, const BinaryOp& func = BinaryOp())
: m_matrix(mat), m_functor(func) {}
private:
int _rows() const { return (Direction==Vertical ? 1 : m_matrix.rows()); }
int _cols() const { return (Direction==Horizontal ? 1 : m_matrix.cols()); }
const Scalar _coeff(int i, int j) const
{
if (Direction==Vertical)
return this->col(j).redux(m_functor);
else
return this->row(i).redux(m_functor);
}
protected:
const typename MatrixType::XprCopy m_matrix;
const BinaryOp m_functor;
};
/** \returns a row vector expression of *this vertically reduxed by \a func
*
* The template parameter \a BinaryOp is the type of the functor
* of the custom redux operator. Note that func must be an associative operator.
*
* \sa class PartialRedux, MatrixBase::horizontalRedux()
*/
template<typename Derived>
template<typename BinaryOp>
const PartialRedux<Vertical, BinaryOp, Derived>
MatrixBase<Derived>::verticalRedux(const BinaryOp& func) const
{
return PartialRedux<Vertical, BinaryOp, Derived>(derived(), func);
}
/** \returns a row vector expression of *this horizontally reduxed by \a func
*
* The template parameter \a BinaryOp is the type of the functor
* of the custom redux operator. Note that func must be an associative operator.
*
* \sa class PartialRedux, MatrixBase::verticalRedux()
*/
template<typename Derived>
template<typename BinaryOp>
const PartialRedux<Horizontal, BinaryOp, Derived>
MatrixBase<Derived>::horizontalRedux(const BinaryOp& func) const
{
return PartialRedux<Horizontal, BinaryOp, Derived>(derived(), func);
}
/** \returns the result of a full redux operation on the whole matrix or vector using \a func
*
* The template parameter \a BinaryOp is the type of the functor \a func which must be
* an assiociative operator. Both current STL and TR1 functor styles are handled.
*
* \sa MatrixBase::sum(), MatrixBase::minCoeff(), MatrixBase::maxCoeff(), MatrixBase::verticalRedux(), MatrixBase::horizontalRedux()
*/
template<typename Derived>
template<typename BinaryOp>
typename ei_result_of<BinaryOp(typename ei_traits<Derived>::Scalar)>::type
MatrixBase<Derived>::redux(const BinaryOp& func) const
{
if(EIGEN_UNROLLED_LOOPS
&& SizeAtCompileTime != Dynamic
&& SizeAtCompileTime <= EIGEN_UNROLLING_LIMIT)
return ei_redux_unroller<BinaryOp, Derived, 0,
(SizeAtCompileTime>0 && SizeAtCompileTime <= EIGEN_UNROLLING_LIMIT) ?
SizeAtCompileTime : Dynamic>::run(derived(), func);
else
{
Scalar res;
res = coeff(0,0);
for(int i = 1; i < rows(); i++)
res = func(res, coeff(i, 0));
for(int j = 1; j < cols(); j++)
for(int i = 0; i < rows(); i++)
res = func(res, coeff(i, j));
return res;
}
}
/** \returns the sum of all coefficients of *this
*
* \sa trace()
*/
template<typename Derived>
typename ei_traits<Derived>::Scalar
MatrixBase<Derived>::sum() const
{
return this->redux(Eigen::ei_scalar_sum_op());
}
/** \returns the trace of \c *this, i.e. the sum of the coefficients on the main diagonal.
*
* \c *this can be any matrix, not necessarily square.
*
* \sa diagonal(), sum()
*/
template<typename Derived>
typename ei_traits<Derived>::Scalar
MatrixBase<Derived>::trace() const
{
return diagonal().sum();
}
/** \returns the minimum of all coefficients of *this
*/
template<typename Derived>
typename ei_traits<Derived>::Scalar
MatrixBase<Derived>::minCoeff() const
{
return this->redux(Eigen::ei_scalar_min_op());
}
/** \returns the maximum of all coefficients of *this
*/
template<typename Derived>
typename ei_traits<Derived>::Scalar
MatrixBase<Derived>::maxCoeff() const
{
return this->redux(Eigen::ei_scalar_max_op());
}
#endif // EIGEN_REDUX_H
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