| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> |
| // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| |
| #ifndef EIGEN_XPRHELPER_H |
| #define EIGEN_XPRHELPER_H |
| |
| // just a workaround because GCC seems to not really like empty structs |
| // FIXME: gcc 4.3 generates bad code when strict-aliasing is enabled |
| // so currently we simply disable this optimization for gcc 4.3 |
| #if EIGEN_COMP_GNUC && !EIGEN_GNUC_AT(4,3) |
| #define EIGEN_EMPTY_STRUCT_CTOR(X) \ |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE X() {} \ |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE X(const X& ) {} |
| #else |
| #define EIGEN_EMPTY_STRUCT_CTOR(X) |
| #endif |
| |
| namespace Eigen { |
| |
| typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE DenseIndex; |
| |
| /** |
| * \brief The Index type as used for the API. |
| * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE. |
| * \sa \ref TopicPreprocessorDirectives, StorageIndex. |
| */ |
| |
| typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE Index; |
| |
| namespace internal { |
| |
| template<typename IndexDest, typename IndexSrc> |
| EIGEN_DEVICE_FUNC |
| inline IndexDest convert_index(const IndexSrc& idx) { |
| // for sizeof(IndexDest)>=sizeof(IndexSrc) compilers should be able to optimize this away: |
| eigen_internal_assert(idx <= NumTraits<IndexDest>::highest() && "Index value to big for target type"); |
| return IndexDest(idx); |
| } |
| |
| |
| //classes inheriting no_assignment_operator don't generate a default operator=. |
| class no_assignment_operator |
| { |
| private: |
| no_assignment_operator& operator=(const no_assignment_operator&); |
| }; |
| |
| /** \internal return the index type with the largest number of bits */ |
| template<typename I1, typename I2> |
| struct promote_index_type |
| { |
| typedef typename conditional<(sizeof(I1)<sizeof(I2)), I2, I1>::type type; |
| }; |
| |
| /** \internal If the template parameter Value is Dynamic, this class is just a wrapper around a T variable that |
| * can be accessed using value() and setValue(). |
| * Otherwise, this class is an empty structure and value() just returns the template parameter Value. |
| */ |
| template<typename T, int Value> class variable_if_dynamic |
| { |
| public: |
| EIGEN_EMPTY_STRUCT_CTOR(variable_if_dynamic) |
| EIGEN_DEVICE_FUNC explicit variable_if_dynamic(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); eigen_assert(v == T(Value)); } |
| EIGEN_DEVICE_FUNC static T value() { return T(Value); } |
| EIGEN_DEVICE_FUNC void setValue(T) {} |
| }; |
| |
| template<typename T> class variable_if_dynamic<T, Dynamic> |
| { |
| T m_value; |
| EIGEN_DEVICE_FUNC variable_if_dynamic() { eigen_assert(false); } |
| public: |
| EIGEN_DEVICE_FUNC explicit variable_if_dynamic(T value) : m_value(value) {} |
| EIGEN_DEVICE_FUNC T value() const { return m_value; } |
| EIGEN_DEVICE_FUNC void setValue(T value) { m_value = value; } |
| }; |
| |
| /** \internal like variable_if_dynamic but for DynamicIndex |
| */ |
| template<typename T, int Value> class variable_if_dynamicindex |
| { |
| public: |
| EIGEN_EMPTY_STRUCT_CTOR(variable_if_dynamicindex) |
| EIGEN_DEVICE_FUNC explicit variable_if_dynamicindex(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); eigen_assert(v == T(Value)); } |
| EIGEN_DEVICE_FUNC static T value() { return T(Value); } |
| EIGEN_DEVICE_FUNC void setValue(T) {} |
| }; |
| |
| template<typename T> class variable_if_dynamicindex<T, DynamicIndex> |
| { |
| T m_value; |
| EIGEN_DEVICE_FUNC variable_if_dynamicindex() { eigen_assert(false); } |
| public: |
| EIGEN_DEVICE_FUNC explicit variable_if_dynamicindex(T value) : m_value(value) {} |
| EIGEN_DEVICE_FUNC T value() const { return m_value; } |
| EIGEN_DEVICE_FUNC void setValue(T value) { m_value = value; } |
| }; |
| |
| template<typename T> struct functor_traits |
| { |
| enum |
| { |
| Cost = 10, |
| PacketAccess = false, |
| IsRepeatable = false |
| }; |
| }; |
| |
| template<typename T> struct packet_traits; |
| |
| template<typename T> struct unpacket_traits |
| { |
| typedef T type; |
| typedef T half; |
| enum |
| { |
| size = 1, |
| alignment = 1 |
| }; |
| }; |
| |
| template<int Size, typename PacketType, |
| bool Stop = (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value> |
| struct find_best_packet_helper; |
| |
| template< int Size, typename PacketType> |
| struct find_best_packet_helper<Size,PacketType,true> |
| { |
| typedef PacketType type; |
| }; |
| |
| template<int Size, typename PacketType> |
| struct find_best_packet_helper<Size,PacketType,false> |
| { |
| typedef typename find_best_packet_helper<Size,typename unpacket_traits<PacketType>::half>::type type; |
| }; |
| |
| template<typename T, int Size> |
| struct find_best_packet |
| { |
| typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type; |
| }; |
| |
| #if EIGEN_MAX_STATIC_ALIGN_BYTES>0 |
| template<int ArrayBytes, int AlignmentBytes, |
| bool Match = bool((ArrayBytes%AlignmentBytes)==0), |
| bool TryHalf = bool(AlignmentBytes>EIGEN_MIN_ALIGN_BYTES) > |
| struct compute_default_alignment_helper |
| { |
| enum { value = 0 }; |
| }; |
| |
| template<int ArrayBytes, int AlignmentBytes, bool TryHalf> |
| struct compute_default_alignment_helper<ArrayBytes, AlignmentBytes, true, TryHalf> // Match |
| { |
| enum { value = AlignmentBytes }; |
| }; |
| |
| template<int ArrayBytes, int AlignmentBytes> |
| struct compute_default_alignment_helper<ArrayBytes, AlignmentBytes, false, true> // Try-half |
| { |
| // current packet too large, try with an half-packet |
| enum { value = compute_default_alignment_helper<ArrayBytes, AlignmentBytes/2>::value }; |
| }; |
| #else |
| // If static alignment is disabled, no need to bother. |
| // This also avoids a division by zero in "bool Match = bool((ArrayBytes%AlignmentBytes)==0)" |
| template<int ArrayBytes, int AlignmentBytes> |
| struct compute_default_alignment_helper |
| { |
| enum { value = 0 }; |
| }; |
| #endif |
| |
| template<typename T, int Size> struct compute_default_alignment { |
| enum { value = compute_default_alignment_helper<Size*sizeof(T),EIGEN_MAX_STATIC_ALIGN_BYTES>::value }; |
| }; |
| |
| template<typename T> struct compute_default_alignment<T,Dynamic> { |
| enum { value = EIGEN_MAX_ALIGN_BYTES }; |
| }; |
| |
| template<typename _Scalar, int _Rows, int _Cols, |
| int _Options = AutoAlign | |
| ( (_Rows==1 && _Cols!=1) ? RowMajor |
| : (_Cols==1 && _Rows!=1) ? ColMajor |
| : EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION ), |
| int _MaxRows = _Rows, |
| int _MaxCols = _Cols |
| > class make_proper_matrix_type |
| { |
| enum { |
| IsColVector = _Cols==1 && _Rows!=1, |
| IsRowVector = _Rows==1 && _Cols!=1, |
| Options = IsColVector ? (_Options | ColMajor) & ~RowMajor |
| : IsRowVector ? (_Options | RowMajor) & ~ColMajor |
| : _Options |
| }; |
| public: |
| typedef Matrix<_Scalar, _Rows, _Cols, Options, _MaxRows, _MaxCols> type; |
| }; |
| |
| template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols> |
| class compute_matrix_flags |
| { |
| enum { row_major_bit = Options&RowMajor ? RowMajorBit : 0 }; |
| public: |
| // FIXME currently we still have to handle DirectAccessBit at the expression level to handle DenseCoeffsBase<> |
| // and then propagate this information to the evaluator's flags. |
| // However, I (Gael) think that DirectAccessBit should only matter at the evaluation stage. |
| enum { ret = DirectAccessBit | LvalueBit | NestByRefBit | row_major_bit }; |
| }; |
| |
| template<int _Rows, int _Cols> struct size_at_compile_time |
| { |
| enum { ret = (_Rows==Dynamic || _Cols==Dynamic) ? Dynamic : _Rows * _Cols }; |
| }; |
| |
| template<typename XprType> struct size_of_xpr_at_compile_time |
| { |
| enum { ret = size_at_compile_time<traits<XprType>::RowsAtCompileTime,traits<XprType>::ColsAtCompileTime>::ret }; |
| }; |
| |
| /* plain_matrix_type : the difference from eval is that plain_matrix_type is always a plain matrix type, |
| * whereas eval is a const reference in the case of a matrix |
| */ |
| |
| template<typename T, typename StorageKind = typename traits<T>::StorageKind> struct plain_matrix_type; |
| template<typename T, typename BaseClassType> struct plain_matrix_type_dense; |
| template<typename T> struct plain_matrix_type<T,Dense> |
| { |
| typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind>::type type; |
| }; |
| template<typename T> struct plain_matrix_type<T,DiagonalShape> |
| { |
| typedef typename T::PlainObject type; |
| }; |
| |
| template<typename T> struct plain_matrix_type_dense<T,MatrixXpr> |
| { |
| typedef Matrix<typename traits<T>::Scalar, |
| traits<T>::RowsAtCompileTime, |
| traits<T>::ColsAtCompileTime, |
| AutoAlign | (traits<T>::Flags&RowMajorBit ? RowMajor : ColMajor), |
| traits<T>::MaxRowsAtCompileTime, |
| traits<T>::MaxColsAtCompileTime |
| > type; |
| }; |
| |
| template<typename T> struct plain_matrix_type_dense<T,ArrayXpr> |
| { |
| typedef Array<typename traits<T>::Scalar, |
| traits<T>::RowsAtCompileTime, |
| traits<T>::ColsAtCompileTime, |
| AutoAlign | (traits<T>::Flags&RowMajorBit ? RowMajor : ColMajor), |
| traits<T>::MaxRowsAtCompileTime, |
| traits<T>::MaxColsAtCompileTime |
| > type; |
| }; |
| |
| /* eval : the return type of eval(). For matrices, this is just a const reference |
| * in order to avoid a useless copy |
| */ |
| |
| template<typename T, typename StorageKind = typename traits<T>::StorageKind> struct eval; |
| |
| template<typename T> struct eval<T,Dense> |
| { |
| typedef typename plain_matrix_type<T>::type type; |
| // typedef typename T::PlainObject type; |
| // typedef T::Matrix<typename traits<T>::Scalar, |
| // traits<T>::RowsAtCompileTime, |
| // traits<T>::ColsAtCompileTime, |
| // AutoAlign | (traits<T>::Flags&RowMajorBit ? RowMajor : ColMajor), |
| // traits<T>::MaxRowsAtCompileTime, |
| // traits<T>::MaxColsAtCompileTime |
| // > type; |
| }; |
| |
| template<typename T> struct eval<T,DiagonalShape> |
| { |
| typedef typename plain_matrix_type<T>::type type; |
| }; |
| |
| // for matrices, no need to evaluate, just use a const reference to avoid a useless copy |
| template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols> |
| struct eval<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>, Dense> |
| { |
| typedef const Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& type; |
| }; |
| |
| template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols> |
| struct eval<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>, Dense> |
| { |
| typedef const Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& type; |
| }; |
| |
| |
| |
| /* plain_matrix_type_column_major : same as plain_matrix_type but guaranteed to be column-major |
| */ |
| template<typename T> struct plain_matrix_type_column_major |
| { |
| enum { Rows = traits<T>::RowsAtCompileTime, |
| Cols = traits<T>::ColsAtCompileTime, |
| MaxRows = traits<T>::MaxRowsAtCompileTime, |
| MaxCols = traits<T>::MaxColsAtCompileTime |
| }; |
| typedef Matrix<typename traits<T>::Scalar, |
| Rows, |
| Cols, |
| (MaxRows==1&&MaxCols!=1) ? RowMajor : ColMajor, |
| MaxRows, |
| MaxCols |
| > type; |
| }; |
| |
| /* plain_matrix_type_row_major : same as plain_matrix_type but guaranteed to be row-major |
| */ |
| template<typename T> struct plain_matrix_type_row_major |
| { |
| enum { Rows = traits<T>::RowsAtCompileTime, |
| Cols = traits<T>::ColsAtCompileTime, |
| MaxRows = traits<T>::MaxRowsAtCompileTime, |
| MaxCols = traits<T>::MaxColsAtCompileTime |
| }; |
| typedef Matrix<typename traits<T>::Scalar, |
| Rows, |
| Cols, |
| (MaxCols==1&&MaxRows!=1) ? RowMajor : ColMajor, |
| MaxRows, |
| MaxCols |
| > type; |
| }; |
| |
| /** \internal The reference selector for template expressions. The idea is that we don't |
| * need to use references for expressions since they are light weight proxy |
| * objects which should generate no copying overhead. */ |
| template <typename T> |
| struct ref_selector |
| { |
| typedef typename conditional< |
| bool(traits<T>::Flags & NestByRefBit), |
| T const&, |
| const T |
| >::type type; |
| |
| typedef typename conditional< |
| bool(traits<T>::Flags & NestByRefBit), |
| T &, |
| T |
| >::type non_const_type; |
| }; |
| |
| /** \internal Adds the const qualifier on the value-type of T2 if and only if T1 is a const type */ |
| template<typename T1, typename T2> |
| struct transfer_constness |
| { |
| typedef typename conditional< |
| bool(internal::is_const<T1>::value), |
| typename internal::add_const_on_value_type<T2>::type, |
| T2 |
| >::type type; |
| }; |
| |
| |
| // However, we still need a mechanism to detect whether an expression which is evaluated multiple time |
| // has to be evaluated into a temporary. |
| // That's the purpose of this new nested_eval helper: |
| /** \internal Determines how a given expression should be nested when evaluated multiple times. |
| * For example, when you do a * (b+c), Eigen will determine how the expression b+c should be |
| * evaluated into the bigger product expression. The choice is between nesting the expression b+c as-is, or |
| * evaluating that expression b+c into a temporary variable d, and nest d so that the resulting expression is |
| * a*d. Evaluating can be beneficial for example if every coefficient access in the resulting expression causes |
| * many coefficient accesses in the nested expressions -- as is the case with matrix product for example. |
| * |
| * \param T the type of the expression being nested. |
| * \param n the number of coefficient accesses in the nested expression for each coefficient access in the bigger expression. |
| * \param PlainObject the type of the temporary if needed. |
| */ |
| template<typename T, int n, typename PlainObject = typename eval<T>::type> struct nested_eval |
| { |
| enum { |
| // For the purpose of this test, to keep it reasonably simple, we arbitrarily choose a value of Dynamic values. |
| // the choice of 10000 makes it larger than any practical fixed value and even most dynamic values. |
| // in extreme cases where these assumptions would be wrong, we would still at worst suffer performance issues |
| // (poor choice of temporaries). |
| // It's important that this value can still be squared without integer overflowing. |
| DynamicAsInteger = 10000, |
| ScalarReadCost = NumTraits<typename traits<T>::Scalar>::ReadCost, |
| ScalarReadCostAsInteger = ScalarReadCost == Dynamic ? int(DynamicAsInteger) : int(ScalarReadCost), |
| CoeffReadCost = evaluator<T>::CoeffReadCost, // TODO What if an evaluator evaluate itself into a tempory? |
| // Then CoeffReadCost will be small but we still have to evaluate if n>1... |
| // The solution might be to ask the evaluator if it creates a temp. Perhaps we could even ask the number of temps? |
| CoeffReadCostAsInteger = CoeffReadCost == Dynamic ? int(DynamicAsInteger) : int(CoeffReadCost), |
| NAsInteger = n == Dynamic ? int(DynamicAsInteger) : n, |
| CostEvalAsInteger = (NAsInteger+1) * ScalarReadCostAsInteger + CoeffReadCostAsInteger, |
| CostNoEvalAsInteger = NAsInteger * CoeffReadCostAsInteger |
| }; |
| |
| typedef typename conditional< |
| ( (int(evaluator<T>::Flags) & EvalBeforeNestingBit) || |
| (int(CostEvalAsInteger) < int(CostNoEvalAsInteger)) ), |
| PlainObject, |
| typename ref_selector<T>::type |
| >::type type; |
| }; |
| |
| template<typename T> |
| EIGEN_DEVICE_FUNC |
| inline T* const_cast_ptr(const T* ptr) |
| { |
| return const_cast<T*>(ptr); |
| } |
| |
| template<typename Derived, typename XprKind = typename traits<Derived>::XprKind> |
| struct dense_xpr_base |
| { |
| /* dense_xpr_base should only ever be used on dense expressions, thus falling either into the MatrixXpr or into the ArrayXpr cases */ |
| }; |
| |
| template<typename Derived> |
| struct dense_xpr_base<Derived, MatrixXpr> |
| { |
| typedef MatrixBase<Derived> type; |
| }; |
| |
| template<typename Derived> |
| struct dense_xpr_base<Derived, ArrayXpr> |
| { |
| typedef ArrayBase<Derived> type; |
| }; |
| |
| template<typename Derived, typename XprKind = typename traits<Derived>::XprKind, typename StorageKind = typename traits<Derived>::StorageKind> |
| struct generic_xpr_base; |
| |
| template<typename Derived, typename XprKind> |
| struct generic_xpr_base<Derived, XprKind, Dense> |
| { |
| typedef typename dense_xpr_base<Derived,XprKind>::type type; |
| }; |
| |
| /** \internal Helper base class to add a scalar multiple operator |
| * overloads for complex types */ |
| template<typename Derived,typename Scalar,typename OtherScalar, |
| bool EnableIt = !is_same<Scalar,OtherScalar>::value > |
| struct special_scalar_op_base : public DenseCoeffsBase<Derived> |
| { |
| // dummy operator* so that the |
| // "using special_scalar_op_base::operator*" compiles |
| struct dummy {}; |
| void operator*(dummy) const; |
| void operator/(dummy) const; |
| }; |
| |
| template<typename Derived,typename Scalar,typename OtherScalar> |
| struct special_scalar_op_base<Derived,Scalar,OtherScalar,true> : public DenseCoeffsBase<Derived> |
| { |
| const CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, Derived> |
| operator*(const OtherScalar& scalar) const |
| { |
| #ifdef EIGEN_SPECIAL_SCALAR_MULTIPLE_PLUGIN |
| EIGEN_SPECIAL_SCALAR_MULTIPLE_PLUGIN |
| #endif |
| return CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, Derived> |
| (*static_cast<const Derived*>(this), scalar_multiple2_op<Scalar,OtherScalar>(scalar)); |
| } |
| |
| inline friend const CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, Derived> |
| operator*(const OtherScalar& scalar, const Derived& matrix) |
| { |
| #ifdef EIGEN_SPECIAL_SCALAR_MULTIPLE_PLUGIN |
| EIGEN_SPECIAL_SCALAR_MULTIPLE_PLUGIN |
| #endif |
| return static_cast<const special_scalar_op_base&>(matrix).operator*(scalar); |
| } |
| |
| const CwiseUnaryOp<scalar_quotient2_op<Scalar,OtherScalar>, Derived> |
| operator/(const OtherScalar& scalar) const |
| { |
| #ifdef EIGEN_SPECIAL_SCALAR_MULTIPLE_PLUGIN |
| EIGEN_SPECIAL_SCALAR_MULTIPLE_PLUGIN |
| #endif |
| return CwiseUnaryOp<scalar_quotient2_op<Scalar,OtherScalar>, Derived> |
| (*static_cast<const Derived*>(this), scalar_quotient2_op<Scalar,OtherScalar>(scalar)); |
| } |
| }; |
| |
| template<typename XprType, typename CastType> struct cast_return_type |
| { |
| typedef typename XprType::Scalar CurrentScalarType; |
| typedef typename remove_all<CastType>::type _CastType; |
| typedef typename _CastType::Scalar NewScalarType; |
| typedef typename conditional<is_same<CurrentScalarType,NewScalarType>::value, |
| const XprType&,CastType>::type type; |
| }; |
| |
| template <typename A, typename B> struct promote_storage_type; |
| |
| template <typename A> struct promote_storage_type<A,A> |
| { |
| typedef A ret; |
| }; |
| template <typename A> struct promote_storage_type<A, const A> |
| { |
| typedef A ret; |
| }; |
| template <typename A> struct promote_storage_type<const A, A> |
| { |
| typedef A ret; |
| }; |
| |
| /** \internal Specify the "storage kind" of applying a coefficient-wise |
| * binary operations between two expressions of kinds A and B respectively. |
| * The template parameter Functor permits to specialize the resulting storage kind wrt to |
| * the functor. |
| * The default rules are as follows: |
| * \code |
| * A op A -> A |
| * A op dense -> dense |
| * dense op B -> dense |
| * A * dense -> A |
| * dense * B -> B |
| * \endcode |
| */ |
| template <typename A, typename B, typename Functor> struct cwise_promote_storage_type; |
| |
| template <typename A, typename Functor> struct cwise_promote_storage_type<A,A,Functor> { typedef A ret; }; |
| template <typename Functor> struct cwise_promote_storage_type<Dense,Dense,Functor> { typedef Dense ret; }; |
| template <typename ScalarA, typename ScalarB> struct cwise_promote_storage_type<Dense,Dense,scalar_product_op<ScalarA,ScalarB> > { typedef Dense ret; }; |
| template <typename A, typename Functor> struct cwise_promote_storage_type<A,Dense,Functor> { typedef Dense ret; }; |
| template <typename B, typename Functor> struct cwise_promote_storage_type<Dense,B,Functor> { typedef Dense ret; }; |
| template <typename A, typename ScalarA, typename ScalarB> struct cwise_promote_storage_type<A,Dense,scalar_product_op<ScalarA,ScalarB> > { typedef A ret; }; |
| template <typename B, typename ScalarA, typename ScalarB> struct cwise_promote_storage_type<Dense,B,scalar_product_op<ScalarA,ScalarB> > { typedef B ret; }; |
| |
| /** \internal Specify the "storage kind" of multiplying an expression of kind A with kind B. |
| * The template parameter ProductTag permits to specialize the resulting storage kind wrt to |
| * some compile-time properties of the product: GemmProduct, GemvProduct, OuterProduct, InnerProduct. |
| * The default rules are as follows: |
| * \code |
| * K * K -> K |
| * dense * K -> dense |
| * K * dense -> dense |
| * diag * K -> K |
| * K * diag -> K |
| * Perm * K -> K |
| * K * Perm -> K |
| * \endcode |
| */ |
| template <typename A, typename B, int ProductTag> struct product_promote_storage_type; |
| |
| template <typename A, int ProductTag> struct product_promote_storage_type<A, A, ProductTag> { typedef A ret;}; |
| template <int ProductTag> struct product_promote_storage_type<Dense, Dense, ProductTag> { typedef Dense ret;}; |
| template <typename A, int ProductTag> struct product_promote_storage_type<A, Dense, ProductTag> { typedef Dense ret; }; |
| template <typename B, int ProductTag> struct product_promote_storage_type<Dense, B, ProductTag> { typedef Dense ret; }; |
| |
| template <typename A, int ProductTag> struct product_promote_storage_type<A, DiagonalShape, ProductTag> { typedef A ret; }; |
| template <typename B, int ProductTag> struct product_promote_storage_type<DiagonalShape, B, ProductTag> { typedef B ret; }; |
| template <int ProductTag> struct product_promote_storage_type<Dense, DiagonalShape, ProductTag> { typedef Dense ret; }; |
| template <int ProductTag> struct product_promote_storage_type<DiagonalShape, Dense, ProductTag> { typedef Dense ret; }; |
| |
| template <typename A, int ProductTag> struct product_promote_storage_type<A, PermutationStorage, ProductTag> { typedef A ret; }; |
| template <typename B, int ProductTag> struct product_promote_storage_type<PermutationStorage, B, ProductTag> { typedef B ret; }; |
| template <int ProductTag> struct product_promote_storage_type<Dense, PermutationStorage, ProductTag> { typedef Dense ret; }; |
| template <int ProductTag> struct product_promote_storage_type<PermutationStorage, Dense, ProductTag> { typedef Dense ret; }; |
| |
| /** \internal gives the plain matrix or array type to store a row/column/diagonal of a matrix type. |
| * \param Scalar optional parameter allowing to pass a different scalar type than the one of the MatrixType. |
| */ |
| template<typename ExpressionType, typename Scalar = typename ExpressionType::Scalar> |
| struct plain_row_type |
| { |
| typedef Matrix<Scalar, 1, ExpressionType::ColsAtCompileTime, |
| ExpressionType::PlainObject::Options | RowMajor, 1, ExpressionType::MaxColsAtCompileTime> MatrixRowType; |
| typedef Array<Scalar, 1, ExpressionType::ColsAtCompileTime, |
| ExpressionType::PlainObject::Options | RowMajor, 1, ExpressionType::MaxColsAtCompileTime> ArrayRowType; |
| |
| typedef typename conditional< |
| is_same< typename traits<ExpressionType>::XprKind, MatrixXpr >::value, |
| MatrixRowType, |
| ArrayRowType |
| >::type type; |
| }; |
| |
| template<typename ExpressionType, typename Scalar = typename ExpressionType::Scalar> |
| struct plain_col_type |
| { |
| typedef Matrix<Scalar, ExpressionType::RowsAtCompileTime, 1, |
| ExpressionType::PlainObject::Options & ~RowMajor, ExpressionType::MaxRowsAtCompileTime, 1> MatrixColType; |
| typedef Array<Scalar, ExpressionType::RowsAtCompileTime, 1, |
| ExpressionType::PlainObject::Options & ~RowMajor, ExpressionType::MaxRowsAtCompileTime, 1> ArrayColType; |
| |
| typedef typename conditional< |
| is_same< typename traits<ExpressionType>::XprKind, MatrixXpr >::value, |
| MatrixColType, |
| ArrayColType |
| >::type type; |
| }; |
| |
| template<typename ExpressionType, typename Scalar = typename ExpressionType::Scalar> |
| struct plain_diag_type |
| { |
| enum { diag_size = EIGEN_SIZE_MIN_PREFER_DYNAMIC(ExpressionType::RowsAtCompileTime, ExpressionType::ColsAtCompileTime), |
| max_diag_size = EIGEN_SIZE_MIN_PREFER_FIXED(ExpressionType::MaxRowsAtCompileTime, ExpressionType::MaxColsAtCompileTime) |
| }; |
| typedef Matrix<Scalar, diag_size, 1, ExpressionType::PlainObject::Options & ~RowMajor, max_diag_size, 1> MatrixDiagType; |
| typedef Array<Scalar, diag_size, 1, ExpressionType::PlainObject::Options & ~RowMajor, max_diag_size, 1> ArrayDiagType; |
| |
| typedef typename conditional< |
| is_same< typename traits<ExpressionType>::XprKind, MatrixXpr >::value, |
| MatrixDiagType, |
| ArrayDiagType |
| >::type type; |
| }; |
| |
| template<typename ExpressionType> |
| struct is_lvalue |
| { |
| enum { value = !bool(is_const<ExpressionType>::value) && |
| bool(traits<ExpressionType>::Flags & LvalueBit) }; |
| }; |
| |
| template<typename T> struct is_diagonal |
| { enum { ret = false }; }; |
| |
| template<typename T> struct is_diagonal<DiagonalBase<T> > |
| { enum { ret = true }; }; |
| |
| template<typename T> struct is_diagonal<DiagonalWrapper<T> > |
| { enum { ret = true }; }; |
| |
| template<typename T, int S> struct is_diagonal<DiagonalMatrix<T,S> > |
| { enum { ret = true }; }; |
| |
| template<typename S1, typename S2> struct glue_shapes; |
| template<> struct glue_shapes<DenseShape,TriangularShape> { typedef TriangularShape type; }; |
| |
| template<typename T1, typename T2> |
| bool is_same_dense(const T1 &mat1, const T2 &mat2, typename enable_if<has_direct_access<T1>::ret&&has_direct_access<T2>::ret, T1>::type * = 0) |
| { |
| return (mat1.data()==mat2.data()) && (mat1.innerStride()==mat2.innerStride()) && (mat1.outerStride()==mat2.outerStride()); |
| } |
| |
| template<typename T1, typename T2> |
| bool is_same_dense(const T1 &, const T2 &, typename enable_if<!(has_direct_access<T1>::ret&&has_direct_access<T2>::ret), T1>::type * = 0) |
| { |
| return false; |
| } |
| |
| } // end namespace internal |
| |
| // we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor |
| // that would take two operands of different types. If there were such an example, then this check should be |
| // moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as |
| // currently they take only one typename Scalar template parameter. |
| // It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths. |
| // So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to |
| // add together a float matrix and a double matrix. |
| #define EIGEN_CHECK_BINARY_COMPATIBILIY(BINOP,LHS,RHS) \ |
| EIGEN_STATIC_ASSERT((internal::functor_is_product_like<BINOP>::ret \ |
| ? int(internal::scalar_product_traits<LHS, RHS>::Defined) \ |
| : int(internal::is_same<LHS, RHS>::value)), \ |
| YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) |
| |
| } // end namespace Eigen |
| |
| #endif // EIGEN_XPRHELPER_H |
