diff options
Diffstat (limited to 'Eigen/src/Core/util/XprHelper.h')
| -rw-r--r-- | Eigen/src/Core/util/XprHelper.h | 261 |
1 files changed, 182 insertions, 79 deletions
diff --git a/Eigen/src/Core/util/XprHelper.h b/Eigen/src/Core/util/XprHelper.h index a001c473a..088a65240 100644 --- a/Eigen/src/Core/util/XprHelper.h +++ b/Eigen/src/Core/util/XprHelper.h @@ -24,16 +24,6 @@ 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 \blank \ref TopicPreprocessorDirectives, StorageIndex. - */ - -typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE Index; - namespace internal { template<typename IndexDest, typename IndexSrc> @@ -45,6 +35,56 @@ inline IndexDest convert_index(const IndexSrc& idx) { } +// promote_scalar_arg is an helper used in operation between an expression and a scalar, like: +// expression * scalar +// Its role is to determine how the type T of the scalar operand should be promoted given the scalar type ExprScalar of the given expression. +// The IsSupported template parameter must be provided by the caller as: internal::has_ReturnType<ScalarBinaryOpTraits<ExprScalar,T,op> >::value using the proper order for ExprScalar and T. +// Then the logic is as follows: +// - if the operation is natively supported as defined by IsSupported, then the scalar type is not promoted, and T is returned. +// - otherwise, NumTraits<ExprScalar>::Literal is returned if T is implicitly convertible to NumTraits<ExprScalar>::Literal AND that this does not imply a float to integer conversion. +// - otherwise, ExprScalar is returned if T is implicitly convertible to ExprScalar AND that this does not imply a float to integer conversion. +// - In all other cases, the promoted type is not defined, and the respective operation is thus invalid and not available (SFINAE). +template<typename ExprScalar,typename T, bool IsSupported> +struct promote_scalar_arg; + +template<typename S,typename T> +struct promote_scalar_arg<S,T,true> +{ + typedef T type; +}; + +// Recursively check safe conversion to PromotedType, and then ExprScalar if they are different. +template<typename ExprScalar,typename T,typename PromotedType, + bool ConvertibleToLiteral = internal::is_convertible<T,PromotedType>::value, + bool IsSafe = NumTraits<T>::IsInteger || !NumTraits<PromotedType>::IsInteger> +struct promote_scalar_arg_unsupported; + +// Start recursion with NumTraits<ExprScalar>::Literal +template<typename S,typename T> +struct promote_scalar_arg<S,T,false> : promote_scalar_arg_unsupported<S,T,typename NumTraits<S>::Literal> {}; + +// We found a match! +template<typename S,typename T, typename PromotedType> +struct promote_scalar_arg_unsupported<S,T,PromotedType,true,true> +{ + typedef PromotedType type; +}; + +// No match, but no real-to-integer issues, and ExprScalar and current PromotedType are different, +// so let's try to promote to ExprScalar +template<typename ExprScalar,typename T, typename PromotedType> +struct promote_scalar_arg_unsupported<ExprScalar,T,PromotedType,false,true> + : promote_scalar_arg_unsupported<ExprScalar,T,ExprScalar> +{}; + +// Unsafe real-to-integer, let's stop. +template<typename S,typename T, typename PromotedType, bool ConvertibleToLiteral> +struct promote_scalar_arg_unsupported<S,T,PromotedType,ConvertibleToLiteral,false> {}; + +// T is not even convertible to ExprScalar, let's stop. +template<typename S,typename T> +struct promote_scalar_arg_unsupported<S,T,S,false,true> {}; + //classes inheriting no_assignment_operator don't generate a default operator=. class no_assignment_operator { @@ -67,9 +107,9 @@ 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) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamic(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); eigen_assert(v == T(Value)); } + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE T value() { return T(Value); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void setValue(T) {} }; template<typename T> class variable_if_dynamic<T, Dynamic> @@ -77,9 +117,9 @@ 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; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamic(T value) : m_value(value) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T value() const { return m_value; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void setValue(T value) { m_value = value; } }; /** \internal like variable_if_dynamic but for DynamicIndex @@ -88,9 +128,9 @@ 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) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamicindex(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); eigen_assert(v == T(Value)); } + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE T value() { return T(Value); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void setValue(T) {} }; template<typename T> class variable_if_dynamicindex<T, DynamicIndex> @@ -98,9 +138,9 @@ 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; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamicindex(T value) : m_value(value) {} + EIGEN_DEVICE_FUNC T EIGEN_STRONG_INLINE value() const { return m_value; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void setValue(T value) { m_value = value; } }; template<typename T> struct functor_traits @@ -450,52 +490,6 @@ 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, typename BaseType, - bool EnableIt = !is_same<Scalar,OtherScalar>::value > -struct special_scalar_op_base : public BaseType -{ - // 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, typename BaseType> -struct special_scalar_op_base<Derived,Scalar,OtherScalar,BaseType,true> : public BaseType -{ - const CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, const 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>, const Derived> - (*static_cast<const Derived*>(this), scalar_multiple2_op<Scalar,OtherScalar>(scalar)); - } - - inline friend const CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, const 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>, const 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>, const 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; @@ -622,6 +616,20 @@ struct plain_diag_type >::type type; }; +template<typename Expr,typename Scalar = typename Expr::Scalar> +struct plain_constant_type +{ + enum { Options = (traits<Expr>::Flags&RowMajorBit)?RowMajor:0 }; + + typedef Array<Scalar, traits<Expr>::RowsAtCompileTime, traits<Expr>::ColsAtCompileTime, + Options, traits<Expr>::MaxRowsAtCompileTime,traits<Expr>::MaxColsAtCompileTime> array_type; + + typedef Matrix<Scalar, traits<Expr>::RowsAtCompileTime, traits<Expr>::ColsAtCompileTime, + Options, traits<Expr>::MaxRowsAtCompileTime,traits<Expr>::MaxColsAtCompileTime> matrix_type; + + typedef CwiseNullaryOp<scalar_constant_op<Scalar>, const typename conditional<is_same< typename traits<Expr>::XprKind, MatrixXpr >::value, matrix_type, array_type>::type > type; +}; + template<typename ExpressionType> struct is_lvalue { @@ -656,10 +664,27 @@ bool is_same_dense(const T1 &, const T2 &, typename enable_if<!(has_direct_acces return false; } -template<typename T, typename U> struct is_same_or_void { enum { value = is_same<T,U>::value }; }; -template<typename T> struct is_same_or_void<void,T> { enum { value = 1 }; }; -template<typename T> struct is_same_or_void<T,void> { enum { value = 1 }; }; -template<> struct is_same_or_void<void,void> { enum { value = 1 }; }; +// Internal helper defining the cost of a scalar division for the type T. +// The default heuristic can be specialized for each scalar type and architecture. +template<typename T,bool Vectorized=false,typename EnaleIf = void> +struct scalar_div_cost { + enum { value = 8*NumTraits<T>::MulCost }; +}; + +template<typename T,bool Vectorized> +struct scalar_div_cost<std::complex<T>, Vectorized> { + enum { value = 2*scalar_div_cost<T>::value + + 6*NumTraits<T>::MulCost + + 3*NumTraits<T>::AddCost + }; +}; + + +template<bool Vectorized> +struct scalar_div_cost<signed long,Vectorized,typename conditional<sizeof(long)==8,void,false_type>::type> { enum { value = 24 }; }; +template<bool Vectorized> +struct scalar_div_cost<unsigned long,Vectorized,typename conditional<sizeof(long)==8,void,false_type>::type> { enum { value = 21 }; }; + #ifdef EIGEN_DEBUG_ASSIGN std::string demangle_traversal(int t) @@ -695,17 +720,95 @@ std::string demangle_flags(int f) } // 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. + +/** \class ScalarBinaryOpTraits + * \ingroup Core_Module + * + * \brief Determines whether the given binary operation of two numeric types is allowed and what the scalar return type is. + * + * This class permits to control the scalar return type of any binary operation performed on two different scalar types through (partial) template specializations. + * + * For instance, let \c U1, \c U2 and \c U3 be three user defined scalar types for which most operations between instances of \c U1 and \c U2 returns an \c U3. + * You can let %Eigen knows that by defining: + \code + template<typename BinaryOp> + struct ScalarBinaryOpTraits<U1,U2,BinaryOp> { typedef U3 ReturnType; }; + template<typename BinaryOp> + struct ScalarBinaryOpTraits<U2,U1,BinaryOp> { typedef U3 ReturnType; }; + \endcode + * You can then explicitly disable some particular operations to get more explicit error messages: + \code + template<> + struct ScalarBinaryOpTraits<U1,U2,internal::scalar_max_op<U1,U2> > {}; + \endcode + * Or customize the return type for individual operation: + \code + template<> + struct ScalarBinaryOpTraits<U1,U2,internal::scalar_sum_op<U1,U2> > { typedef U1 ReturnType; }; + \endcode + * + * By default, the following generic combinations are supported: + <table class="manual"> + <tr><th>ScalarA</th><th>ScalarB</th><th>BinaryOp</th><th>ReturnType</th><th>Note</th></tr> + <tr ><td>\c T </td><td>\c T </td><td>\c * </td><td>\c T </td><td></td></tr> + <tr class="alt"><td>\c NumTraits<T>::Real </td><td>\c T </td><td>\c * </td><td>\c T </td><td>Only if \c NumTraits<T>::IsComplex </td></tr> + <tr ><td>\c T </td><td>\c NumTraits<T>::Real </td><td>\c * </td><td>\c T </td><td>Only if \c NumTraits<T>::IsComplex </td></tr> + </table> + * + * \sa CwiseBinaryOp + */ +template<typename ScalarA, typename ScalarB, typename BinaryOp=internal::scalar_product_op<ScalarA,ScalarB> > +struct ScalarBinaryOpTraits +#ifndef EIGEN_PARSED_BY_DOXYGEN + // for backward compatibility, use the hints given by the (deprecated) internal::scalar_product_traits class. + : internal::scalar_product_traits<ScalarA,ScalarB> +#endif // EIGEN_PARSED_BY_DOXYGEN +{}; + +template<typename T, typename BinaryOp> +struct ScalarBinaryOpTraits<T,T,BinaryOp> +{ + typedef T ReturnType; +}; + +template <typename T, typename BinaryOp> +struct ScalarBinaryOpTraits<T, typename NumTraits<typename internal::enable_if<NumTraits<T>::IsComplex,T>::type>::Real, BinaryOp> +{ + typedef T ReturnType; +}; +template <typename T, typename BinaryOp> +struct ScalarBinaryOpTraits<typename NumTraits<typename internal::enable_if<NumTraits<T>::IsComplex,T>::type>::Real, T, BinaryOp> +{ + typedef T ReturnType; +}; + +// For Matrix * Permutation +template<typename T, typename BinaryOp> +struct ScalarBinaryOpTraits<T,void,BinaryOp> +{ + typedef T ReturnType; +}; + +// For Permutation * Matrix +template<typename T, typename BinaryOp> +struct ScalarBinaryOpTraits<void,T,BinaryOp> +{ + typedef T ReturnType; +}; + +// for Permutation*Permutation +template<typename BinaryOp> +struct ScalarBinaryOpTraits<void,void,BinaryOp> +{ + typedef void ReturnType; +}; + +// We require Lhs and Rhs to have "compatible" scalar types. // 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_or_void<LHS, RHS>::value)), \ + EIGEN_STATIC_ASSERT((Eigen::internal::has_ReturnType<ScalarBinaryOpTraits<LHS, RHS,BINOP> >::value), \ YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) } // end namespace Eigen |