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authorGravatar Gael Guennebaud <g.gael@free.fr>2013-03-20 21:19:16 +0100
committerGravatar Gael Guennebaud <g.gael@free.fr>2013-03-20 21:19:16 +0100
commitc519be2bac43aa8ccaa8d568c3bfafd311286a9f (patch)
tree8711d8dd2c05ce3f8d31d1e409b917aa639c13e0 /Eigen/src/Core
parentf350f34560d1cc67a8c220d973b003226ff58892 (diff)
Allow multiplication like binary operators to be applied on type couples supported by scalar_product_traits
Diffstat (limited to 'Eigen/src/Core')
-rw-r--r--Eigen/src/Core/CwiseBinaryOp.h4
-rw-r--r--Eigen/src/Core/Functors.h13
-rw-r--r--Eigen/src/Core/products/CoeffBasedProduct.h2
-rw-r--r--Eigen/src/Core/util/Meta.h20
4 files changed, 26 insertions, 13 deletions
diff --git a/Eigen/src/Core/CwiseBinaryOp.h b/Eigen/src/Core/CwiseBinaryOp.h
index 686c2afa3..586f77aaf 100644
--- a/Eigen/src/Core/CwiseBinaryOp.h
+++ b/Eigen/src/Core/CwiseBinaryOp.h
@@ -94,8 +94,8 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
// 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_allows_mixing_real_and_complex<BINOP>::ret \
- ? int(internal::is_same<typename NumTraits<LHS>::Real, typename NumTraits<RHS>::Real>::value) \
+ 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)
diff --git a/Eigen/src/Core/Functors.h b/Eigen/src/Core/Functors.h
index 147df3a50..0ab767f30 100644
--- a/Eigen/src/Core/Functors.h
+++ b/Eigen/src/Core/Functors.h
@@ -648,13 +648,14 @@ template <typename Scalar, bool RandomAccess> struct linspaced_op
template<typename Functor> struct functor_has_linear_access { enum { ret = 1 }; };
template<typename Scalar> struct functor_has_linear_access<scalar_identity_op<Scalar> > { enum { ret = 0 }; };
-// in CwiseBinaryOp, we require the Lhs and Rhs to have the same scalar type, except for multiplication
-// where we only require them to have the same _real_ scalar type so one may multiply, say, float by complex<float>.
+// In Eigen, any binary op (Product, CwiseBinaryOp) require the Lhs and Rhs to have the same scalar type, except for multiplication
+// where the mixing of different types is handled by scalar_product_traits
+// In particular, real * complex<real> is allowed.
// FIXME move this to functor_traits adding a functor_default
-template<typename Functor> struct functor_allows_mixing_real_and_complex { enum { ret = 0 }; };
-template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
-template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_conj_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
-template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_quotient_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
+template<typename Functor> struct functor_is_product_like { enum { ret = 0 }; };
+template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
+template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_conj_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
+template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_quotient_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
/** \internal
diff --git a/Eigen/src/Core/products/CoeffBasedProduct.h b/Eigen/src/Core/products/CoeffBasedProduct.h
index 403d25fa9..c06a0df1c 100644
--- a/Eigen/src/Core/products/CoeffBasedProduct.h
+++ b/Eigen/src/Core/products/CoeffBasedProduct.h
@@ -150,7 +150,7 @@ class CoeffBasedProduct
{
// we don't allow taking products of matrices of different real types, as that wouldn't be vectorizable.
// We still allow to mix T and complex<T>.
- EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
+ EIGEN_STATIC_ASSERT((internal::scalar_product_traits<typename Lhs::RealScalar, typename Rhs::RealScalar>::Defined),
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
eigen_assert(lhs.cols() == rhs.rows()
&& "invalid matrix product"
diff --git a/Eigen/src/Core/util/Meta.h b/Eigen/src/Core/util/Meta.h
index a5f31164d..71d587108 100644
--- a/Eigen/src/Core/util/Meta.h
+++ b/Eigen/src/Core/util/Meta.h
@@ -186,23 +186,35 @@ template<int Y, int InfX, int SupX>
class meta_sqrt<Y, InfX, SupX, true> { public: enum { ret = (SupX*SupX <= Y) ? SupX : InfX }; };
/** \internal determines whether the product of two numeric types is allowed and what the return type is */
-template<typename T, typename U> struct scalar_product_traits;
+template<typename T, typename U> struct scalar_product_traits
+{
+ enum { Defined = 0 };
+};
template<typename T> struct scalar_product_traits<T,T>
{
- //enum { Cost = NumTraits<T>::MulCost };
+ enum {
+ // Cost = NumTraits<T>::MulCost,
+ Defined = 1
+ };
typedef T ReturnType;
};
template<typename T> struct scalar_product_traits<T,std::complex<T> >
{
- //enum { Cost = 2*NumTraits<T>::MulCost };
+ enum {
+ // Cost = 2*NumTraits<T>::MulCost,
+ Defined = 1
+ };
typedef std::complex<T> ReturnType;
};
template<typename T> struct scalar_product_traits<std::complex<T>, T>
{
- //enum { Cost = 2*NumTraits<T>::MulCost };
+ enum {
+ // Cost = 2*NumTraits<T>::MulCost,
+ Defined = 1
+ };
typedef std::complex<T> ReturnType;
};