eigen/Eigen/src/Core/Product.h
Benoit Jacob fb3438e609 - expand MathFunctions.h to provide more functions, like exp, log...
- add cwiseExp(), cwiseLog()...
   --> for example, doing a gamma-correction on a bitmap image stored as
       an array of floats is a simple matter of:
         Eigen::Map<VectorXf> m = VectorXf::map(bitmap,size);
         m = m.cwisePow(gamma);
- apidoc improvements, reorganization of the \name's
- remove obsolete examples
- remove EIGEN_ALWAYS_INLINE on lazyProduct(), it seems useless.
2008-03-14 10:38:37 +00:00

175 lines
5.7 KiB
C++

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// 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_PRODUCT_H
#define EIGEN_PRODUCT_H
template<int Index, int Size, typename Lhs, typename Rhs>
struct ei_product_unroller
{
static void run(int row, int col, const Lhs& lhs, const Rhs& rhs,
typename Lhs::Scalar &res)
{
ei_product_unroller<Index-1, Size, Lhs, Rhs>::run(row, col, lhs, rhs, res);
res += lhs.coeff(row, Index) * rhs.coeff(Index, col);
}
};
template<int Size, typename Lhs, typename Rhs>
struct ei_product_unroller<0, Size, Lhs, Rhs>
{
static void run(int row, int col, const Lhs& lhs, const Rhs& rhs,
typename Lhs::Scalar &res)
{
res = lhs.coeff(row, 0) * rhs.coeff(0, col);
}
};
template<int Index, typename Lhs, typename Rhs>
struct ei_product_unroller<Index, Dynamic, Lhs, Rhs>
{
static void run(int, int, const Lhs&, const Rhs&, typename Lhs::Scalar&) {}
};
// prevent buggy user code from causing an infinite recursion
template<int Index, typename Lhs, typename Rhs>
struct ei_product_unroller<Index, 0, Lhs, Rhs>
{
static void run(int, int, const Lhs&, const Rhs&, typename Lhs::Scalar&) {}
};
/** \class Product
*
* \brief Expression of the product of two matrices
*
* \param Lhs the type of the left-hand side
* \param Rhs the type of the right-hand side
*
* This class represents an expression of the product of two matrices.
* It is the return type of MatrixBase::lazyProduct(), which is used internally by
* the operator* between matrices, and most of the time this is the only way it is used.
*
* \sa class Sum, class Difference
*/
template<typename Lhs, typename Rhs>
struct ei_traits<Product<Lhs, Rhs> >
{
typedef typename Lhs::Scalar Scalar;
enum {
RowsAtCompileTime = Lhs::RowsAtCompileTime,
ColsAtCompileTime = Rhs::ColsAtCompileTime,
MaxRowsAtCompileTime = Lhs::MaxRowsAtCompileTime,
MaxColsAtCompileTime = Rhs::MaxColsAtCompileTime
};
};
template<typename Lhs, typename Rhs> class Product : ei_no_assignment_operator,
public MatrixBase<Product<Lhs, Rhs> >
{
public:
EIGEN_GENERIC_PUBLIC_INTERFACE(Product)
Product(const Lhs& lhs, const Rhs& rhs)
: m_lhs(lhs), m_rhs(rhs)
{
assert(lhs.cols() == rhs.rows());
}
private:
int _rows() const { return m_lhs.rows(); }
int _cols() const { return m_rhs.cols(); }
Scalar _coeff(int row, int col) const
{
Scalar res;
if(EIGEN_UNROLLED_LOOPS
&& Lhs::ColsAtCompileTime != Dynamic
&& Lhs::ColsAtCompileTime <= EIGEN_UNROLLING_LIMIT)
ei_product_unroller<Lhs::ColsAtCompileTime-1,
Lhs::ColsAtCompileTime <= EIGEN_UNROLLING_LIMIT
? Lhs::ColsAtCompileTime : Dynamic,
Lhs, Rhs>
::run(row, col, m_lhs, m_rhs, res);
else
{
res = m_lhs.coeff(row, 0) * m_rhs.coeff(0, col);
for(int i = 1; i < m_lhs.cols(); i++)
res += m_lhs.coeff(row, i) * m_rhs.coeff(i, col);
}
return res;
}
protected:
const typename Lhs::XprCopy m_lhs;
const typename Rhs::XprCopy m_rhs;
};
/** \returns an expression of the matrix product of \c this and \a other, in this order.
*
* This function is used internally by the operator* between matrices. The difference between
* lazyProduct() and that operator* is that lazyProduct() only constructs and returns an
* expression without actually computing the matrix product, while the operator* between
* matrices immediately evaluates the product and returns the resulting matrix.
*
* \sa class Product
*/
template<typename Derived>
template<typename OtherDerived>
const Product<Derived, OtherDerived>
MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
{
return Product<Derived, OtherDerived>(derived(), other.derived());
}
/** \returns the matrix product of \c *this and \a other.
*
* \note This function causes an immediate evaluation. If you want to perform a matrix product
* without immediate evaluation, use MatrixBase::lazyProduct() instead.
*
* \sa lazyProduct(), operator*=(const MatrixBase&)
*/
template<typename Derived>
template<typename OtherDerived>
const Eval<Product<Derived, OtherDerived> >
MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
{
return lazyProduct(other).eval();
}
/** replaces \c *this by \c *this * \a other.
*
* \returns a reference to \c *this
*/
template<typename Derived>
template<typename OtherDerived>
Derived &
MatrixBase<Derived>::operator*=(const MatrixBase<OtherDerived> &other)
{
return *this = *this * other;
}
#endif // EIGEN_PRODUCT_H