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