296 lines
11 KiB
C++
296 lines
11 KiB
C++
// 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) 2008-2009 Guillaume Saupin <guillaume.saupin@cea.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_SKYLINEPRODUCT_H
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#define EIGEN_SKYLINEPRODUCT_H
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namespace Eigen {
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template<typename Lhs, typename Rhs, int ProductMode>
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struct SkylineProductReturnType {
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typedef const typename internal::nested<Lhs, Rhs::RowsAtCompileTime>::type LhsNested;
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typedef const typename internal::nested<Rhs, Lhs::RowsAtCompileTime>::type RhsNested;
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typedef SkylineProduct<LhsNested, RhsNested, ProductMode> Type;
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};
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template<typename LhsNested, typename RhsNested, int ProductMode>
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struct internal::traits<SkylineProduct<LhsNested, RhsNested, ProductMode> > {
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// clean the nested types:
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typedef typename internal::remove_all<LhsNested>::type _LhsNested;
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typedef typename internal::remove_all<RhsNested>::type _RhsNested;
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typedef typename _LhsNested::Scalar Scalar;
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enum {
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LhsCoeffReadCost = _LhsNested::CoeffReadCost,
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RhsCoeffReadCost = _RhsNested::CoeffReadCost,
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LhsFlags = _LhsNested::Flags,
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RhsFlags = _RhsNested::Flags,
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RowsAtCompileTime = _LhsNested::RowsAtCompileTime,
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ColsAtCompileTime = _RhsNested::ColsAtCompileTime,
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InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(_LhsNested::ColsAtCompileTime, _RhsNested::RowsAtCompileTime),
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MaxRowsAtCompileTime = _LhsNested::MaxRowsAtCompileTime,
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MaxColsAtCompileTime = _RhsNested::MaxColsAtCompileTime,
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EvalToRowMajor = (RhsFlags & LhsFlags & RowMajorBit),
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ResultIsSkyline = ProductMode == SkylineTimeSkylineProduct,
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RemovedBits = ~((EvalToRowMajor ? 0 : RowMajorBit) | (ResultIsSkyline ? 0 : SkylineBit)),
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Flags = (int(LhsFlags | RhsFlags) & HereditaryBits & RemovedBits)
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| EvalBeforeAssigningBit
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| EvalBeforeNestingBit,
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CoeffReadCost = Dynamic
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};
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typedef typename internal::conditional<ResultIsSkyline,
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SkylineMatrixBase<SkylineProduct<LhsNested, RhsNested, ProductMode> >,
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MatrixBase<SkylineProduct<LhsNested, RhsNested, ProductMode> > >::type Base;
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};
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namespace internal {
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template<typename LhsNested, typename RhsNested, int ProductMode>
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class SkylineProduct : no_assignment_operator,
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public traits<SkylineProduct<LhsNested, RhsNested, ProductMode> >::Base {
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public:
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EIGEN_GENERIC_PUBLIC_INTERFACE(SkylineProduct)
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private:
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typedef typename traits<SkylineProduct>::_LhsNested _LhsNested;
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typedef typename traits<SkylineProduct>::_RhsNested _RhsNested;
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public:
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template<typename Lhs, typename Rhs>
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EIGEN_STRONG_INLINE SkylineProduct(const Lhs& lhs, const Rhs& rhs)
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: m_lhs(lhs), m_rhs(rhs) {
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eigen_assert(lhs.cols() == rhs.rows());
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enum {
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ProductIsValid = _LhsNested::ColsAtCompileTime == Dynamic
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|| _RhsNested::RowsAtCompileTime == Dynamic
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|| int(_LhsNested::ColsAtCompileTime) == int(_RhsNested::RowsAtCompileTime),
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AreVectors = _LhsNested::IsVectorAtCompileTime && _RhsNested::IsVectorAtCompileTime,
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SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(_LhsNested, _RhsNested)
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};
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// note to the lost user:
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// * for a dot product use: v1.dot(v2)
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// * for a coeff-wise product use: v1.cwise()*v2
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EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
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INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
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EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
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INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
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EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
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}
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EIGEN_STRONG_INLINE Index rows() const {
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return m_lhs.rows();
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}
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EIGEN_STRONG_INLINE Index cols() const {
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return m_rhs.cols();
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}
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EIGEN_STRONG_INLINE const _LhsNested& lhs() const {
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return m_lhs;
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}
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EIGEN_STRONG_INLINE const _RhsNested& rhs() const {
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return m_rhs;
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}
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protected:
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LhsNested m_lhs;
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RhsNested m_rhs;
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};
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// dense = skyline * dense
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// Note that here we force no inlining and separate the setZero() because GCC messes up otherwise
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template<typename Lhs, typename Rhs, typename Dest>
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EIGEN_DONT_INLINE void skyline_row_major_time_dense_product(const Lhs& lhs, const Rhs& rhs, Dest& dst) {
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typedef typename remove_all<Lhs>::type _Lhs;
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typedef typename remove_all<Rhs>::type _Rhs;
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typedef typename traits<Lhs>::Scalar Scalar;
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enum {
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LhsIsRowMajor = (_Lhs::Flags & RowMajorBit) == RowMajorBit,
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LhsIsSelfAdjoint = (_Lhs::Flags & SelfAdjointBit) == SelfAdjointBit,
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ProcessFirstHalf = LhsIsSelfAdjoint
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&& (((_Lhs::Flags & (UpperTriangularBit | LowerTriangularBit)) == 0)
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|| ((_Lhs::Flags & UpperTriangularBit) && !LhsIsRowMajor)
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|| ((_Lhs::Flags & LowerTriangularBit) && LhsIsRowMajor)),
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ProcessSecondHalf = LhsIsSelfAdjoint && (!ProcessFirstHalf)
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};
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//Use matrix diagonal part <- Improvement : use inner iterator on dense matrix.
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for (Index col = 0; col < rhs.cols(); col++) {
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for (Index row = 0; row < lhs.rows(); row++) {
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dst(row, col) = lhs.coeffDiag(row) * rhs(row, col);
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}
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}
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//Use matrix lower triangular part
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for (Index row = 0; row < lhs.rows(); row++) {
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typename _Lhs::InnerLowerIterator lIt(lhs, row);
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const Index stop = lIt.col() + lIt.size();
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for (Index col = 0; col < rhs.cols(); col++) {
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Index k = lIt.col();
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Scalar tmp = 0;
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while (k < stop) {
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tmp +=
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lIt.value() *
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rhs(k++, col);
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++lIt;
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}
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dst(row, col) += tmp;
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lIt += -lIt.size();
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}
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}
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//Use matrix upper triangular part
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for (Index lhscol = 0; lhscol < lhs.cols(); lhscol++) {
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typename _Lhs::InnerUpperIterator uIt(lhs, lhscol);
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const Index stop = uIt.size() + uIt.row();
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for (Index rhscol = 0; rhscol < rhs.cols(); rhscol++) {
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const Scalar rhsCoeff = rhs.coeff(lhscol, rhscol);
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Index k = uIt.row();
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while (k < stop) {
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dst(k++, rhscol) +=
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uIt.value() *
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rhsCoeff;
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++uIt;
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}
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uIt += -uIt.size();
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}
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}
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}
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template<typename Lhs, typename Rhs, typename Dest>
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EIGEN_DONT_INLINE void skyline_col_major_time_dense_product(const Lhs& lhs, const Rhs& rhs, Dest& dst) {
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typedef typename remove_all<Lhs>::type _Lhs;
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typedef typename remove_all<Rhs>::type _Rhs;
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typedef typename traits<Lhs>::Scalar Scalar;
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enum {
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LhsIsRowMajor = (_Lhs::Flags & RowMajorBit) == RowMajorBit,
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LhsIsSelfAdjoint = (_Lhs::Flags & SelfAdjointBit) == SelfAdjointBit,
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ProcessFirstHalf = LhsIsSelfAdjoint
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&& (((_Lhs::Flags & (UpperTriangularBit | LowerTriangularBit)) == 0)
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|| ((_Lhs::Flags & UpperTriangularBit) && !LhsIsRowMajor)
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|| ((_Lhs::Flags & LowerTriangularBit) && LhsIsRowMajor)),
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ProcessSecondHalf = LhsIsSelfAdjoint && (!ProcessFirstHalf)
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};
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//Use matrix diagonal part <- Improvement : use inner iterator on dense matrix.
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for (Index col = 0; col < rhs.cols(); col++) {
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for (Index row = 0; row < lhs.rows(); row++) {
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dst(row, col) = lhs.coeffDiag(row) * rhs(row, col);
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}
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}
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//Use matrix upper triangular part
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for (Index row = 0; row < lhs.rows(); row++) {
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typename _Lhs::InnerUpperIterator uIt(lhs, row);
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const Index stop = uIt.col() + uIt.size();
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for (Index col = 0; col < rhs.cols(); col++) {
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Index k = uIt.col();
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Scalar tmp = 0;
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while (k < stop) {
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tmp +=
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uIt.value() *
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rhs(k++, col);
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++uIt;
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}
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dst(row, col) += tmp;
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uIt += -uIt.size();
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}
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}
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//Use matrix lower triangular part
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for (Index lhscol = 0; lhscol < lhs.cols(); lhscol++) {
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typename _Lhs::InnerLowerIterator lIt(lhs, lhscol);
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const Index stop = lIt.size() + lIt.row();
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for (Index rhscol = 0; rhscol < rhs.cols(); rhscol++) {
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const Scalar rhsCoeff = rhs.coeff(lhscol, rhscol);
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Index k = lIt.row();
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while (k < stop) {
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dst(k++, rhscol) +=
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lIt.value() *
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rhsCoeff;
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++lIt;
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}
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lIt += -lIt.size();
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}
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}
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}
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template<typename Lhs, typename Rhs, typename ResultType,
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int LhsStorageOrder = traits<Lhs>::Flags&RowMajorBit>
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struct skyline_product_selector;
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template<typename Lhs, typename Rhs, typename ResultType>
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struct skyline_product_selector<Lhs, Rhs, ResultType, RowMajor> {
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typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
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static void run(const Lhs& lhs, const Rhs& rhs, ResultType & res) {
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skyline_row_major_time_dense_product<Lhs, Rhs, ResultType > (lhs, rhs, res);
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}
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};
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template<typename Lhs, typename Rhs, typename ResultType>
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struct skyline_product_selector<Lhs, Rhs, ResultType, ColMajor> {
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typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
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static void run(const Lhs& lhs, const Rhs& rhs, ResultType & res) {
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skyline_col_major_time_dense_product<Lhs, Rhs, ResultType > (lhs, rhs, res);
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}
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};
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} // end namespace internal
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// template<typename Derived>
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// template<typename Lhs, typename Rhs >
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// Derived & MatrixBase<Derived>::lazyAssign(const SkylineProduct<Lhs, Rhs, SkylineTimeDenseProduct>& product) {
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// typedef typename internal::remove_all<Lhs>::type _Lhs;
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// internal::skyline_product_selector<typename internal::remove_all<Lhs>::type,
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// typename internal::remove_all<Rhs>::type,
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// Derived>::run(product.lhs(), product.rhs(), derived());
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//
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// return derived();
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// }
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// skyline * dense
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template<typename Derived>
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template<typename OtherDerived >
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EIGEN_STRONG_INLINE const typename SkylineProductReturnType<Derived, OtherDerived>::Type
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SkylineMatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const {
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return typename SkylineProductReturnType<Derived, OtherDerived>::Type(derived(), other.derived());
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}
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} // end namespace Eigen
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#endif // EIGEN_SKYLINEPRODUCT_H
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