Product.h
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00001 // This file is part of Eigen, a lightweight C++ template library
00002 // for linear algebra.
00003 //
00004 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
00005 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
00006 //
00007 // Eigen is free software; you can redistribute it and/or
00008 // modify it under the terms of the GNU Lesser General Public
00009 // License as published by the Free Software Foundation; either
00010 // version 3 of the License, or (at your option) any later version.
00011 //
00012 // Alternatively, you can redistribute it and/or
00013 // modify it under the terms of the GNU General Public License as
00014 // published by the Free Software Foundation; either version 2 of
00015 // the License, or (at your option) any later version.
00016 //
00017 // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
00018 // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
00019 // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
00020 // GNU General Public License for more details.
00021 //
00022 // You should have received a copy of the GNU Lesser General Public
00023 // License and a copy of the GNU General Public License along with
00024 // Eigen. If not, see <http://www.gnu.org/licenses/>.
00025 
00026 #ifndef EIGEN_PRODUCT_H
00027 #define EIGEN_PRODUCT_H
00028 
00048 template<typename Lhs, typename Rhs, int ProductType = internal::product_type<Lhs,Rhs>::value>
00049 class GeneralProduct;
00050 
00051 enum {
00052   Large = 2,
00053   Small = 3
00054 };
00055 
00056 namespace internal {
00057 
00058 template<int Rows, int Cols, int Depth> struct product_type_selector;
00059 
00060 template<int Size, int MaxSize> struct product_size_category
00061 {
00062   enum { is_large = MaxSize == Dynamic ||
00063                     Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
00064          value = is_large  ? Large
00065                : Size == 1 ? 1
00066                            : Small
00067   };
00068 };
00069 
00070 template<typename Lhs, typename Rhs> struct product_type
00071 {
00072   typedef typename remove_all<Lhs>::type _Lhs;
00073   typedef typename remove_all<Rhs>::type _Rhs;
00074   enum {
00075     MaxRows  = _Lhs::MaxRowsAtCompileTime,
00076     Rows  = _Lhs::RowsAtCompileTime,
00077     MaxCols  = _Rhs::MaxColsAtCompileTime,
00078     Cols  = _Rhs::ColsAtCompileTime,
00079     MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime,
00080                                            _Rhs::MaxRowsAtCompileTime),
00081     Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime,
00082                                         _Rhs::RowsAtCompileTime),
00083     LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
00084   };
00085 
00086   // the splitting into different lines of code here, introducing the _select enums and the typedef below,
00087   // is to work around an internal compiler error with gcc 4.1 and 4.2.
00088 private:
00089   enum {
00090     rows_select = product_size_category<Rows,MaxRows>::value,
00091     cols_select = product_size_category<Cols,MaxCols>::value,
00092     depth_select = product_size_category<Depth,MaxDepth>::value
00093   };
00094   typedef product_type_selector<rows_select, cols_select, depth_select> selector;
00095 
00096 public:
00097   enum {
00098     value = selector::ret
00099   };
00100 #ifdef EIGEN_DEBUG_PRODUCT
00101   static void debug()
00102   {
00103       EIGEN_DEBUG_VAR(Rows);
00104       EIGEN_DEBUG_VAR(Cols);
00105       EIGEN_DEBUG_VAR(Depth);
00106       EIGEN_DEBUG_VAR(rows_select);
00107       EIGEN_DEBUG_VAR(cols_select);
00108       EIGEN_DEBUG_VAR(depth_select);
00109       EIGEN_DEBUG_VAR(value);
00110   }
00111 #endif
00112 };
00113 
00114 
00115 /* The following allows to select the kind of product at compile time
00116  * based on the three dimensions of the product.
00117  * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
00118 // FIXME I'm not sure the current mapping is the ideal one.
00119 template<int M, int N>  struct product_type_selector<M,N,1>              { enum { ret = OuterProduct }; };
00120 template<int Depth>     struct product_type_selector<1,    1,    Depth>  { enum { ret = InnerProduct }; };
00121 template<>              struct product_type_selector<1,    1,    1>      { enum { ret = InnerProduct }; };
00122 template<>              struct product_type_selector<Small,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
00123 template<>              struct product_type_selector<1,    Small,Small>  { enum { ret = CoeffBasedProductMode }; };
00124 template<>              struct product_type_selector<Small,Small,Small>  { enum { ret = CoeffBasedProductMode }; };
00125 template<>              struct product_type_selector<Small, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
00126 template<>              struct product_type_selector<Small, Large, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
00127 template<>              struct product_type_selector<Large, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
00128 template<>              struct product_type_selector<1,    Large,Small>  { enum { ret = CoeffBasedProductMode }; };
00129 template<>              struct product_type_selector<1,    Large,Large>  { enum { ret = GemvProduct }; };
00130 template<>              struct product_type_selector<1,    Small,Large>  { enum { ret = CoeffBasedProductMode }; };
00131 template<>              struct product_type_selector<Large,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
00132 template<>              struct product_type_selector<Large,1,    Large>  { enum { ret = GemvProduct }; };
00133 template<>              struct product_type_selector<Small,1,    Large>  { enum { ret = CoeffBasedProductMode }; };
00134 template<>              struct product_type_selector<Small,Small,Large>  { enum { ret = GemmProduct }; };
00135 template<>              struct product_type_selector<Large,Small,Large>  { enum { ret = GemmProduct }; };
00136 template<>              struct product_type_selector<Small,Large,Large>  { enum { ret = GemmProduct }; };
00137 template<>              struct product_type_selector<Large,Large,Large>  { enum { ret = GemmProduct }; };
00138 template<>              struct product_type_selector<Large,Small,Small>  { enum { ret = GemmProduct }; };
00139 template<>              struct product_type_selector<Small,Large,Small>  { enum { ret = GemmProduct }; };
00140 template<>              struct product_type_selector<Large,Large,Small>  { enum { ret = GemmProduct }; };
00141 
00142 } // end namespace internal
00143 
00161 template<typename Lhs, typename Rhs, int ProductType>
00162 struct ProductReturnType
00163 {
00164   // TODO use the nested type to reduce instanciations ????
00165 //   typedef typename internal::nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
00166 //   typedef typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
00167 
00168   typedef GeneralProduct<Lhs/*Nested*/, Rhs/*Nested*/, ProductType> Type;
00169 };
00170 
00171 template<typename Lhs, typename Rhs>
00172 struct ProductReturnType<Lhs,Rhs,CoeffBasedProductMode>
00173 {
00174   typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
00175   typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
00176   typedef CoeffBasedProduct<LhsNested, RhsNested, EvalBeforeAssigningBit | EvalBeforeNestingBit> Type;
00177 };
00178 
00179 template<typename Lhs, typename Rhs>
00180 struct ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
00181 {
00182   typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
00183   typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
00184   typedef CoeffBasedProduct<LhsNested, RhsNested, NestByRefBit> Type;
00185 };
00186 
00187 // this is a workaround for sun CC
00188 template<typename Lhs, typename Rhs>
00189 struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
00190 {};
00191 
00192 /***********************************************************************
00193 *  Implementation of Inner Vector Vector Product
00194 ***********************************************************************/
00195 
00196 // FIXME : maybe the "inner product" could return a Scalar
00197 // instead of a 1x1 matrix ??
00198 // Pro: more natural for the user
00199 // Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
00200 // product ends up to a row-vector times col-vector product... To tackle this use
00201 // case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
00202 
00203 namespace internal {
00204 
00205 template<typename Lhs, typename Rhs>
00206 struct traits<GeneralProduct<Lhs,Rhs,InnerProduct> >
00207  : traits<Matrix<typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> >
00208 {};
00209 
00210 }
00211 
00212 template<typename Lhs, typename Rhs>
00213 class GeneralProduct<Lhs, Rhs, InnerProduct>
00214   : internal::no_assignment_operator,
00215     public Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1>
00216 {
00217     typedef Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> Base;
00218   public:
00219     GeneralProduct(const Lhs& lhs, const Rhs& rhs)
00220     {
00221       EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
00222         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
00223 
00224       Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
00225     }
00226 
00228     operator const typename Base::Scalar() const {
00229       return Base::coeff(0,0);
00230     }
00231 };
00232 
00233 /***********************************************************************
00234 *  Implementation of Outer Vector Vector Product
00235 ***********************************************************************/
00236 
00237 namespace internal {
00238 template<int StorageOrder> struct outer_product_selector;
00239 
00240 template<typename Lhs, typename Rhs>
00241 struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
00242  : traits<ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> >
00243 {};
00244 
00245 }
00246 
00247 template<typename Lhs, typename Rhs>
00248 class GeneralProduct<Lhs, Rhs, OuterProduct>
00249   : public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
00250 {
00251   public:
00252     EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
00253 
00254     GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
00255     {
00256       EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
00257         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
00258     }
00259 
00260     template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
00261     {
00262       internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, alpha);
00263     }
00264 };
00265 
00266 namespace internal {
00267 
00268 template<> struct outer_product_selector<ColMajor> {
00269   template<typename ProductType, typename Dest>
00270   static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
00271     typedef typename Dest::Index Index;
00272     // FIXME make sure lhs is sequentially stored
00273     // FIXME not very good if rhs is real and lhs complex while alpha is real too
00274     const Index cols = dest.cols();
00275     for (Index j=0; j<cols; ++j)
00276       dest.col(j) += (alpha * prod.rhs().coeff(j)) * prod.lhs();
00277   }
00278 };
00279 
00280 template<> struct outer_product_selector<RowMajor> {
00281   template<typename ProductType, typename Dest>
00282   static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
00283     typedef typename Dest::Index Index;
00284     // FIXME make sure rhs is sequentially stored
00285     // FIXME not very good if lhs is real and rhs complex while alpha is real too
00286     const Index rows = dest.rows();
00287     for (Index i=0; i<rows; ++i)
00288       dest.row(i) += (alpha * prod.lhs().coeff(i)) * prod.rhs();
00289   }
00290 };
00291 
00292 } // end namespace internal
00293 
00294 /***********************************************************************
00295 *  Implementation of General Matrix Vector Product
00296 ***********************************************************************/
00297 
00298 /*  According to the shape/flags of the matrix we have to distinghish 3 different cases:
00299  *   1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
00300  *   2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
00301  *   3 - all other cases are handled using a simple loop along the outer-storage direction.
00302  *  Therefore we need a lower level meta selector.
00303  *  Furthermore, if the matrix is the rhs, then the product has to be transposed.
00304  */
00305 namespace internal {
00306 
00307 template<typename Lhs, typename Rhs>
00308 struct traits<GeneralProduct<Lhs,Rhs,GemvProduct> >
00309  : traits<ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs> >
00310 {};
00311 
00312 template<int Side, int StorageOrder, bool BlasCompatible>
00313 struct gemv_selector;
00314 
00315 } // end namespace internal
00316 
00317 template<typename Lhs, typename Rhs>
00318 class GeneralProduct<Lhs, Rhs, GemvProduct>
00319   : public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
00320 {
00321   public:
00322     EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
00323 
00324     typedef typename Lhs::Scalar LhsScalar;
00325     typedef typename Rhs::Scalar RhsScalar;
00326 
00327     GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
00328     {
00329 //       EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
00330 //         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
00331     }
00332 
00333     enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
00334     typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
00335 
00336     template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
00337     {
00338       eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
00339       internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
00340                        bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
00341     }
00342 };
00343 
00344 namespace internal {
00345 
00346 // The vector is on the left => transposition
00347 template<int StorageOrder, bool BlasCompatible>
00348 struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
00349 {
00350   template<typename ProductType, typename Dest>
00351   static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
00352   {
00353     Transpose<Dest> destT(dest);
00354     enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
00355     gemv_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
00356       ::run(GeneralProduct<Transpose<const typename ProductType::_RhsNested>,Transpose<const typename ProductType::_LhsNested>, GemvProduct>
00357         (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha);
00358   }
00359 };
00360 
00361 template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
00362 
00363 template<typename Scalar,int Size,int MaxSize>
00364 struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
00365 {
00366   EIGEN_STRONG_INLINE  Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; }
00367 };
00368 
00369 template<typename Scalar,int Size>
00370 struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
00371 {
00372   EIGEN_STRONG_INLINE Scalar* data() { return 0; }
00373 };
00374 
00375 template<typename Scalar,int Size,int MaxSize>
00376 struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
00377 {
00378   #if EIGEN_ALIGN_STATICALLY
00379   internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
00380   EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
00381   #else
00382   // Some architectures cannot align on the stack,
00383   // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
00384   enum {
00385     ForceAlignment  = internal::packet_traits<Scalar>::Vectorizable,
00386     PacketSize      = internal::packet_traits<Scalar>::size
00387   };
00388   internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?PacketSize:0),0> m_data;
00389   EIGEN_STRONG_INLINE Scalar* data() {
00390     return ForceAlignment
00391             ? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(15))) + 16)
00392             : m_data.array;
00393   }
00394   #endif
00395 };
00396 
00397 template<> struct gemv_selector<OnTheRight,ColMajor,true>
00398 {
00399   template<typename ProductType, typename Dest>
00400   static inline void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
00401   {
00402     typedef typename ProductType::Index Index;
00403     typedef typename ProductType::LhsScalar   LhsScalar;
00404     typedef typename ProductType::RhsScalar   RhsScalar;
00405     typedef typename ProductType::Scalar      ResScalar;
00406     typedef typename ProductType::RealScalar  RealScalar;
00407     typedef typename ProductType::ActualLhsType ActualLhsType;
00408     typedef typename ProductType::ActualRhsType ActualRhsType;
00409     typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
00410     typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
00411     typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
00412 
00413     const ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
00414     const ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
00415 
00416     ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
00417                                   * RhsBlasTraits::extractScalarFactor(prod.rhs());
00418 
00419     enum {
00420       // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
00421       // on, the other hand it is good for the cache to pack the vector anyways...
00422       EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
00423       ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
00424       MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal
00425     };
00426 
00427     gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
00428 
00429     // this is written like this (i.e., with a ?:) to workaround an ICE with ICC 12
00430     bool alphaIsCompatible = (!ComplexByReal) ? true : (imag(actualAlpha)==RealScalar(0));
00431     bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
00432     
00433     RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
00434 
00435     ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
00436                                                   evalToDest ? dest.data() : static_dest.data());
00437     
00438     if(!evalToDest)
00439     {
00440       #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
00441       int size = dest.size();
00442       EIGEN_DENSE_STORAGE_CTOR_PLUGIN
00443       #endif
00444       if(!alphaIsCompatible)
00445       {
00446         MappedDest(actualDestPtr, dest.size()).setZero();
00447         compatibleAlpha = RhsScalar(1);
00448       }
00449       else
00450         MappedDest(actualDestPtr, dest.size()) = dest;
00451     }
00452 
00453     general_matrix_vector_product
00454       <Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
00455         actualLhs.rows(), actualLhs.cols(),
00456         &actualLhs.coeffRef(0,0), actualLhs.outerStride(),
00457         actualRhs.data(), actualRhs.innerStride(),
00458         actualDestPtr, 1,
00459         compatibleAlpha);
00460 
00461     if (!evalToDest)
00462     {
00463       if(!alphaIsCompatible)
00464         dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
00465       else
00466         dest = MappedDest(actualDestPtr, dest.size());
00467     }
00468   }
00469 };
00470 
00471 template<> struct gemv_selector<OnTheRight,RowMajor,true>
00472 {
00473   template<typename ProductType, typename Dest>
00474   static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
00475   {
00476     typedef typename ProductType::LhsScalar LhsScalar;
00477     typedef typename ProductType::RhsScalar RhsScalar;
00478     typedef typename ProductType::Scalar    ResScalar;
00479     typedef typename ProductType::Index Index;
00480     typedef typename ProductType::ActualLhsType ActualLhsType;
00481     typedef typename ProductType::ActualRhsType ActualRhsType;
00482     typedef typename ProductType::_ActualRhsType _ActualRhsType;
00483     typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
00484     typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
00485 
00486     typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
00487     typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
00488 
00489     ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
00490                                   * RhsBlasTraits::extractScalarFactor(prod.rhs());
00491 
00492     enum {
00493       // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
00494       // on, the other hand it is good for the cache to pack the vector anyways...
00495       DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
00496     };
00497 
00498     gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
00499 
00500     ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
00501         DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
00502 
00503     if(!DirectlyUseRhs)
00504     {
00505       #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
00506       int size = actualRhs.size();
00507       EIGEN_DENSE_STORAGE_CTOR_PLUGIN
00508       #endif
00509       Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
00510     }
00511 
00512     general_matrix_vector_product
00513       <Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
00514         actualLhs.rows(), actualLhs.cols(),
00515         &actualLhs.coeffRef(0,0), actualLhs.outerStride(),
00516         actualRhsPtr, 1,
00517         &dest.coeffRef(0,0), dest.innerStride(),
00518         actualAlpha);
00519   }
00520 };
00521 
00522 template<> struct gemv_selector<OnTheRight,ColMajor,false>
00523 {
00524   template<typename ProductType, typename Dest>
00525   static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
00526   {
00527     typedef typename Dest::Index Index;
00528     // TODO makes sure dest is sequentially stored in memory, otherwise use a temp
00529     const Index size = prod.rhs().rows();
00530     for(Index k=0; k<size; ++k)
00531       dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
00532   }
00533 };
00534 
00535 template<> struct gemv_selector<OnTheRight,RowMajor,false>
00536 {
00537   template<typename ProductType, typename Dest>
00538   static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
00539   {
00540     typedef typename Dest::Index Index;
00541     // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
00542     const Index rows = prod.rows();
00543     for(Index i=0; i<rows; ++i)
00544       dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
00545   }
00546 };
00547 
00548 } // end namespace internal
00549 
00550 /***************************************************************************
00551 * Implementation of matrix base methods
00552 ***************************************************************************/
00553 
00560 template<typename Derived>
00561 template<typename OtherDerived>
00562 inline const typename ProductReturnType<Derived,OtherDerived>::Type
00563 MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
00564 {
00565   // A note regarding the function declaration: In MSVC, this function will sometimes
00566   // not be inlined since DenseStorage is an unwindable object for dynamic
00567   // matrices and product types are holding a member to store the result.
00568   // Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
00569   enum {
00570     ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
00571                    || OtherDerived::RowsAtCompileTime==Dynamic
00572                    || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
00573     AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
00574     SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
00575   };
00576   // note to the lost user:
00577   //    * for a dot product use: v1.dot(v2)
00578   //    * for a coeff-wise product use: v1.cwiseProduct(v2)
00579   EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
00580     INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
00581   EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
00582     INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
00583   EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
00584 #ifdef EIGEN_DEBUG_PRODUCT
00585   internal::product_type<Derived,OtherDerived>::debug();
00586 #endif
00587   return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
00588 }
00589 
00601 template<typename Derived>
00602 template<typename OtherDerived>
00603 const typename LazyProductReturnType<Derived,OtherDerived>::Type
00604 MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
00605 {
00606   enum {
00607     ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
00608                    || OtherDerived::RowsAtCompileTime==Dynamic
00609                    || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
00610     AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
00611     SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
00612   };
00613   // note to the lost user:
00614   //    * for a dot product use: v1.dot(v2)
00615   //    * for a coeff-wise product use: v1.cwiseProduct(v2)
00616   EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
00617     INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
00618   EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
00619     INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
00620   EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
00621 
00622   return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
00623 }
00624 
00625 #endif // EIGEN_PRODUCT_H


libicr
Author(s): Robert Krug
autogenerated on Mon Jan 6 2014 11:33:12