GeneralProduct.h
1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
5 // Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
6 //
7 // This Source Code Form is subject to the terms of the Mozilla
8 // Public License v. 2.0. If a copy of the MPL was not distributed
9 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
10 
11 #ifndef EIGEN_GENERAL_PRODUCT_H
12 #define EIGEN_GENERAL_PRODUCT_H
13 
14 namespace Eigen {
15 
35 template<typename Lhs, typename Rhs, int ProductType = internal::product_type<Lhs,Rhs>::value>
37 
38 enum {
39  Large = 2,
40  Small = 3
41 };
42 
43 namespace internal {
44 
45 template<int Rows, int Cols, int Depth> struct product_type_selector;
46 
47 template<int Size, int MaxSize> struct product_size_category
48 {
49  enum { is_large = MaxSize == Dynamic ||
50  Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
51  value = is_large ? Large
52  : Size == 1 ? 1
53  : Small
54  };
55 };
56 
57 template<typename Lhs, typename Rhs> struct product_type
58 {
59  typedef typename remove_all<Lhs>::type _Lhs;
60  typedef typename remove_all<Rhs>::type _Rhs;
61  enum {
62  MaxRows = _Lhs::MaxRowsAtCompileTime,
63  Rows = _Lhs::RowsAtCompileTime,
64  MaxCols = _Rhs::MaxColsAtCompileTime,
65  Cols = _Rhs::ColsAtCompileTime,
66  MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime,
67  _Rhs::MaxRowsAtCompileTime),
68  Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime,
69  _Rhs::RowsAtCompileTime),
70  LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
71  };
72 
73  // the splitting into different lines of code here, introducing the _select enums and the typedef below,
74  // is to work around an internal compiler error with gcc 4.1 and 4.2.
75 private:
76  enum {
77  rows_select = product_size_category<Rows,MaxRows>::value,
78  cols_select = product_size_category<Cols,MaxCols>::value,
79  depth_select = product_size_category<Depth,MaxDepth>::value
80  };
81  typedef product_type_selector<rows_select, cols_select, depth_select> selector;
82 
83 public:
84  enum {
85  value = selector::ret
86  };
87 #ifdef EIGEN_DEBUG_PRODUCT
88  static void debug()
89  {
90  EIGEN_DEBUG_VAR(Rows);
91  EIGEN_DEBUG_VAR(Cols);
92  EIGEN_DEBUG_VAR(Depth);
93  EIGEN_DEBUG_VAR(rows_select);
94  EIGEN_DEBUG_VAR(cols_select);
95  EIGEN_DEBUG_VAR(depth_select);
96  EIGEN_DEBUG_VAR(value);
97  }
98 #endif
99 };
100 
101 
102 /* The following allows to select the kind of product at compile time
103  * based on the three dimensions of the product.
104  * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
105 // FIXME I'm not sure the current mapping is the ideal one.
106 template<int M, int N> struct product_type_selector<M,N,1> { enum { ret = OuterProduct }; };
107 template<int Depth> struct product_type_selector<1, 1, Depth> { enum { ret = InnerProduct }; };
108 template<> struct product_type_selector<1, 1, 1> { enum { ret = InnerProduct }; };
109 template<> struct product_type_selector<Small,1, Small> { enum { ret = CoeffBasedProductMode }; };
110 template<> struct product_type_selector<1, Small,Small> { enum { ret = CoeffBasedProductMode }; };
111 template<> struct product_type_selector<Small,Small,Small> { enum { ret = CoeffBasedProductMode }; };
112 template<> struct product_type_selector<Small, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; };
113 template<> struct product_type_selector<Small, Large, 1> { enum { ret = LazyCoeffBasedProductMode }; };
114 template<> struct product_type_selector<Large, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; };
115 template<> struct product_type_selector<1, Large,Small> { enum { ret = CoeffBasedProductMode }; };
116 template<> struct product_type_selector<1, Large,Large> { enum { ret = GemvProduct }; };
117 template<> struct product_type_selector<1, Small,Large> { enum { ret = CoeffBasedProductMode }; };
118 template<> struct product_type_selector<Large,1, Small> { enum { ret = CoeffBasedProductMode }; };
119 template<> struct product_type_selector<Large,1, Large> { enum { ret = GemvProduct }; };
120 template<> struct product_type_selector<Small,1, Large> { enum { ret = CoeffBasedProductMode }; };
121 template<> struct product_type_selector<Small,Small,Large> { enum { ret = GemmProduct }; };
122 template<> struct product_type_selector<Large,Small,Large> { enum { ret = GemmProduct }; };
123 template<> struct product_type_selector<Small,Large,Large> { enum { ret = GemmProduct }; };
124 template<> struct product_type_selector<Large,Large,Large> { enum { ret = GemmProduct }; };
125 template<> struct product_type_selector<Large,Small,Small> { enum { ret = GemmProduct }; };
126 template<> struct product_type_selector<Small,Large,Small> { enum { ret = GemmProduct }; };
127 template<> struct product_type_selector<Large,Large,Small> { enum { ret = GemmProduct }; };
128 
129 } // end namespace internal
130 
148 template<typename Lhs, typename Rhs, int ProductType>
150 {
151  // TODO use the nested type to reduce instanciations ????
152 // typedef typename internal::nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
153 // typedef typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
154 
155  typedef GeneralProduct<Lhs/*Nested*/, Rhs/*Nested*/, ProductType> Type;
156 };
157 
158 template<typename Lhs, typename Rhs>
159 struct ProductReturnType<Lhs,Rhs,CoeffBasedProductMode>
160 {
161  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
162  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
163  typedef CoeffBasedProduct<LhsNested, RhsNested, EvalBeforeAssigningBit | EvalBeforeNestingBit> Type;
164 };
165 
166 template<typename Lhs, typename Rhs>
167 struct ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
168 {
169  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
170  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
171  typedef CoeffBasedProduct<LhsNested, RhsNested, NestByRefBit> Type;
172 };
173 
174 // this is a workaround for sun CC
175 template<typename Lhs, typename Rhs>
176 struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
177 {};
178 
179 /***********************************************************************
180 * Implementation of Inner Vector Vector Product
181 ***********************************************************************/
182 
183 // FIXME : maybe the "inner product" could return a Scalar
184 // instead of a 1x1 matrix ??
185 // Pro: more natural for the user
186 // Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
187 // product ends up to a row-vector times col-vector product... To tackle this use
188 // case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
189 
190 namespace internal {
191 
192 template<typename Lhs, typename Rhs>
193 struct traits<GeneralProduct<Lhs,Rhs,InnerProduct> >
194  : traits<Matrix<typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> >
195 {};
196 
197 }
198 
199 template<typename Lhs, typename Rhs>
200 class GeneralProduct<Lhs, Rhs, InnerProduct>
201  : internal::no_assignment_operator,
202  public Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1>
203 {
204  typedef Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> Base;
205  public:
206  GeneralProduct(const Lhs& lhs, const Rhs& rhs)
207  {
208  EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
209  YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
210 
211  Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
212  }
213 
215  operator const typename Base::Scalar() const {
216  return Base::coeff(0,0);
217  }
218 };
219 
220 /***********************************************************************
221 * Implementation of Outer Vector Vector Product
222 ***********************************************************************/
223 
224 namespace internal {
225 template<int StorageOrder> struct outer_product_selector;
226 
227 template<typename Lhs, typename Rhs>
228 struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
229  : traits<ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> >
230 {};
231 
232 }
233 
234 template<typename Lhs, typename Rhs>
235 class GeneralProduct<Lhs, Rhs, OuterProduct>
236  : public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
237 {
238  public:
239  EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
240 
241  GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
242  {
243  EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
244  YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
245  }
246 
247  template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
248  {
249  internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, alpha);
250  }
251 };
252 
253 namespace internal {
254 
255 template<> struct outer_product_selector<ColMajor> {
256  template<typename ProductType, typename Dest>
257  static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
258  typedef typename Dest::Index Index;
259  // FIXME make sure lhs is sequentially stored
260  // FIXME not very good if rhs is real and lhs complex while alpha is real too
261  const Index cols = dest.cols();
262  for (Index j=0; j<cols; ++j)
263  dest.col(j) += (alpha * prod.rhs().coeff(j)) * prod.lhs();
264  }
265 };
266 
267 template<> struct outer_product_selector<RowMajor> {
268  template<typename ProductType, typename Dest>
269  static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
270  typedef typename Dest::Index Index;
271  // FIXME make sure rhs is sequentially stored
272  // FIXME not very good if lhs is real and rhs complex while alpha is real too
273  const Index rows = dest.rows();
274  for (Index i=0; i<rows; ++i)
275  dest.row(i) += (alpha * prod.lhs().coeff(i)) * prod.rhs();
276  }
277 };
278 
279 } // end namespace internal
280 
281 /***********************************************************************
282 * Implementation of General Matrix Vector Product
283 ***********************************************************************/
284 
285 /* According to the shape/flags of the matrix we have to distinghish 3 different cases:
286  * 1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
287  * 2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
288  * 3 - all other cases are handled using a simple loop along the outer-storage direction.
289  * Therefore we need a lower level meta selector.
290  * Furthermore, if the matrix is the rhs, then the product has to be transposed.
291  */
292 namespace internal {
293 
294 template<typename Lhs, typename Rhs>
295 struct traits<GeneralProduct<Lhs,Rhs,GemvProduct> >
296  : traits<ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs> >
297 {};
298 
299 template<int Side, int StorageOrder, bool BlasCompatible>
300 struct gemv_selector;
301 
302 } // end namespace internal
303 
304 template<typename Lhs, typename Rhs>
305 class GeneralProduct<Lhs, Rhs, GemvProduct>
306  : public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
307 {
308  public:
309  EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
310 
311  typedef typename Lhs::Scalar LhsScalar;
312  typedef typename Rhs::Scalar RhsScalar;
313 
314  GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
315  {
316 // EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
317 // YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
318  }
319 
320  enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
321  typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
322 
323  template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
324  {
325  eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
326  internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
327  bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
328  }
329 };
330 
331 namespace internal {
332 
333 // The vector is on the left => transposition
334 template<int StorageOrder, bool BlasCompatible>
335 struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
336 {
337  template<typename ProductType, typename Dest>
338  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
339  {
340  Transpose<Dest> destT(dest);
341  enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
342  gemv_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
343  ::run(GeneralProduct<Transpose<const typename ProductType::_RhsNested>,Transpose<const typename ProductType::_LhsNested>, GemvProduct>
344  (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha);
345  }
346 };
347 
348 template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
349 
350 template<typename Scalar,int Size,int MaxSize>
351 struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
352 {
353  EIGEN_STRONG_INLINE Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; }
354 };
355 
356 template<typename Scalar,int Size>
357 struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
358 {
359  EIGEN_STRONG_INLINE Scalar* data() { return 0; }
360 };
361 
362 template<typename Scalar,int Size,int MaxSize>
363 struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
364 {
365  #if EIGEN_ALIGN_STATICALLY
366  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
367  EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
368  #else
369  // Some architectures cannot align on the stack,
370  // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
371  enum {
372  ForceAlignment = internal::packet_traits<Scalar>::Vectorizable,
373  PacketSize = internal::packet_traits<Scalar>::size
374  };
375  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?PacketSize:0),0> m_data;
376  EIGEN_STRONG_INLINE Scalar* data() {
377  return ForceAlignment
378  ? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(15))) + 16)
379  : m_data.array;
380  }
381  #endif
382 };
383 
384 template<> struct gemv_selector<OnTheRight,ColMajor,true>
385 {
386  template<typename ProductType, typename Dest>
387  static inline void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
388  {
389  typedef typename ProductType::Index Index;
390  typedef typename ProductType::LhsScalar LhsScalar;
391  typedef typename ProductType::RhsScalar RhsScalar;
392  typedef typename ProductType::Scalar ResScalar;
393  typedef typename ProductType::RealScalar RealScalar;
394  typedef typename ProductType::ActualLhsType ActualLhsType;
395  typedef typename ProductType::ActualRhsType ActualRhsType;
396  typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
397  typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
398  typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
399 
400  ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
401  ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
402 
403  ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
404  * RhsBlasTraits::extractScalarFactor(prod.rhs());
405 
406  enum {
407  // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
408  // on, the other hand it is good for the cache to pack the vector anyways...
409  EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
410  ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
411  MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal
412  };
413 
414  gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
415 
416  bool alphaIsCompatible = (!ComplexByReal) || (imag(actualAlpha)==RealScalar(0));
417  bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
418 
419  RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
420 
421  ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
422  evalToDest ? dest.data() : static_dest.data());
423 
424  if(!evalToDest)
425  {
426  #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
427  int size = dest.size();
428  EIGEN_DENSE_STORAGE_CTOR_PLUGIN
429  #endif
430  if(!alphaIsCompatible)
431  {
432  MappedDest(actualDestPtr, dest.size()).setZero();
433  compatibleAlpha = RhsScalar(1);
434  }
435  else
436  MappedDest(actualDestPtr, dest.size()) = dest;
437  }
438 
439  general_matrix_vector_product
440  <Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
441  actualLhs.rows(), actualLhs.cols(),
442  actualLhs.data(), actualLhs.outerStride(),
443  actualRhs.data(), actualRhs.innerStride(),
444  actualDestPtr, 1,
445  compatibleAlpha);
446 
447  if (!evalToDest)
448  {
449  if(!alphaIsCompatible)
450  dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
451  else
452  dest = MappedDest(actualDestPtr, dest.size());
453  }
454  }
455 };
456 
457 template<> struct gemv_selector<OnTheRight,RowMajor,true>
458 {
459  template<typename ProductType, typename Dest>
460  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
461  {
462  typedef typename ProductType::LhsScalar LhsScalar;
463  typedef typename ProductType::RhsScalar RhsScalar;
464  typedef typename ProductType::Scalar ResScalar;
465  typedef typename ProductType::Index Index;
466  typedef typename ProductType::ActualLhsType ActualLhsType;
467  typedef typename ProductType::ActualRhsType ActualRhsType;
468  typedef typename ProductType::_ActualRhsType _ActualRhsType;
469  typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
470  typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
471 
472  typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
473  typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
474 
475  ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
476  * RhsBlasTraits::extractScalarFactor(prod.rhs());
477 
478  enum {
479  // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
480  // on, the other hand it is good for the cache to pack the vector anyways...
481  DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
482  };
483 
484  gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
485 
486  ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
487  DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
488 
489  if(!DirectlyUseRhs)
490  {
491  #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
492  int size = actualRhs.size();
493  EIGEN_DENSE_STORAGE_CTOR_PLUGIN
494  #endif
495  Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
496  }
497 
498  general_matrix_vector_product
499  <Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
500  actualLhs.rows(), actualLhs.cols(),
501  actualLhs.data(), actualLhs.outerStride(),
502  actualRhsPtr, 1,
503  dest.data(), dest.innerStride(),
504  actualAlpha);
505  }
506 };
507 
508 template<> struct gemv_selector<OnTheRight,ColMajor,false>
509 {
510  template<typename ProductType, typename Dest>
511  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
512  {
513  typedef typename Dest::Index Index;
514  // TODO makes sure dest is sequentially stored in memory, otherwise use a temp
515  const Index size = prod.rhs().rows();
516  for(Index k=0; k<size; ++k)
517  dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
518  }
519 };
520 
521 template<> struct gemv_selector<OnTheRight,RowMajor,false>
522 {
523  template<typename ProductType, typename Dest>
524  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
525  {
526  typedef typename Dest::Index Index;
527  // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
528  const Index rows = prod.rows();
529  for(Index i=0; i<rows; ++i)
530  dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
531  }
532 };
533 
534 } // end namespace internal
535 
536 /***************************************************************************
537 * Implementation of matrix base methods
538 ***************************************************************************/
539 
546 template<typename Derived>
547 template<typename OtherDerived>
548 inline const typename ProductReturnType<Derived, OtherDerived>::Type
550 {
551  // A note regarding the function declaration: In MSVC, this function will sometimes
552  // not be inlined since DenseStorage is an unwindable object for dynamic
553  // matrices and product types are holding a member to store the result.
554  // Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
555  enum {
556  ProductIsValid = Derived::ColsAtCompileTime==Dynamic
557  || OtherDerived::RowsAtCompileTime==Dynamic
558  || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
559  AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
560  SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
561  };
562  // note to the lost user:
563  // * for a dot product use: v1.dot(v2)
564  // * for a coeff-wise product use: v1.cwiseProduct(v2)
565  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
566  INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
567  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
568  INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
569  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
570 #ifdef EIGEN_DEBUG_PRODUCT
571  internal::product_type<Derived,OtherDerived>::debug();
572 #endif
573  return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
574 }
575 
587 template<typename Derived>
588 template<typename OtherDerived>
591 {
592  enum {
593  ProductIsValid = Derived::ColsAtCompileTime==Dynamic
594  || OtherDerived::RowsAtCompileTime==Dynamic
595  || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
596  AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
597  SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
598  };
599  // note to the lost user:
600  // * for a dot product use: v1.dot(v2)
601  // * for a coeff-wise product use: v1.cwiseProduct(v2)
602  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
603  INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
604  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
605  INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
606  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
607 
608  return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
609 }
610 
611 } // end namespace Eigen
612 
613 #endif // EIGEN_PRODUCT_H