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Fix "routine is both "inline" and "noinline"" warnings
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e5bf4440c0
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3930c9b086
@ -222,7 +222,29 @@ class GeneralProduct<Lhs, Rhs, InnerProduct>
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***********************************************************************/
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namespace internal {
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template<int StorageOrder> struct outer_product_selector;
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// Column major
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template<typename ProductType, typename Dest, typename Func>
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EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const false_type&)
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{
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typedef typename Dest::Index Index;
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// FIXME make sure lhs is sequentially stored
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// FIXME not very good if rhs is real and lhs complex while alpha is real too
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const Index cols = dest.cols();
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for (Index j=0; j<cols; ++j)
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func(dest.col(j), prod.rhs().coeff(j) * prod.lhs());
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}
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// Row major
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template<typename ProductType, typename Dest, typename Func>
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EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const true_type&) {
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typedef typename Dest::Index Index;
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// FIXME make sure rhs is sequentially stored
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// FIXME not very good if lhs is real and rhs complex while alpha is real too
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const Index rows = dest.rows();
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for (Index i=0; i<rows; ++i)
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func(dest.row(i), prod.lhs().coeff(i) * prod.rhs());
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}
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template<typename Lhs, typename Rhs>
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struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
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@ -235,6 +257,8 @@ template<typename Lhs, typename Rhs>
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class GeneralProduct<Lhs, Rhs, OuterProduct>
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: public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
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{
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template<typename T> struct IsRowMajor : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
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public:
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EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
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@ -257,53 +281,25 @@ class GeneralProduct<Lhs, Rhs, OuterProduct>
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template<typename Dest>
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inline void evalTo(Dest& dest) const {
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internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, set());
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internal::outer_product_selector_run(*this, dest, set(), IsRowMajor<Dest>());
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}
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template<typename Dest>
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inline void addTo(Dest& dest) const {
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internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, add());
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internal::outer_product_selector_run(*this, dest, add(), IsRowMajor<Dest>());
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}
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template<typename Dest>
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inline void subTo(Dest& dest) const {
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internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, sub());
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internal::outer_product_selector_run(*this, dest, sub(), IsRowMajor<Dest>());
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}
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template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
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{
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internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, adds(alpha));
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internal::outer_product_selector_run(*this, dest, adds(alpha), IsRowMajor<Dest>());
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}
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};
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namespace internal {
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template<> struct outer_product_selector<ColMajor> {
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template<typename ProductType, typename Dest, typename Func>
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static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, const Func& func) {
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typedef typename Dest::Index Index;
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// FIXME make sure lhs is sequentially stored
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// FIXME not very good if rhs is real and lhs complex while alpha is real too
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const Index cols = dest.cols();
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for (Index j=0; j<cols; ++j)
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func(dest.col(j), prod.rhs().coeff(j) * prod.lhs());
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}
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};
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template<> struct outer_product_selector<RowMajor> {
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template<typename ProductType, typename Dest, typename Func>
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static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, const Func& func) {
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typedef typename Dest::Index Index;
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// FIXME make sure rhs is sequentially stored
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// FIXME not very good if lhs is real and rhs complex while alpha is real too
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const Index rows = dest.rows();
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for (Index i=0; i<rows; ++i)
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func(dest.row(i), prod.lhs().coeff(i) * prod.rhs());
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}
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};
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} // end namespace internal
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/***********************************************************************
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* Implementation of General Matrix Vector Product
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***********************************************************************/
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@ -529,7 +529,14 @@ struct gebp_kernel
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EIGEN_DONT_INLINE
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void operator()(ResScalar* res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index rows, Index depth, Index cols, ResScalar alpha,
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Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0, RhsScalar* unpackedB = 0)
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Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0, RhsScalar* unpackedB=0);
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};
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template<typename LhsScalar, typename RhsScalar, typename Index, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs>
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EIGEN_DONT_INLINE
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void gebp_kernel<LhsScalar,RhsScalar,Index,mr,nr,ConjugateLhs,ConjugateRhs>
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::operator()(ResScalar* res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index rows, Index depth, Index cols, ResScalar alpha,
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Index strideA, Index strideB, Index offsetA, Index offsetB, RhsScalar* unpackedB)
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{
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Traits traits;
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@ -1089,7 +1096,7 @@ EIGEN_ASM_COMMENT("mybegin4");
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}
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}
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}
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};
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#undef CJMADD
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@ -1110,8 +1117,12 @@ EIGEN_ASM_COMMENT("mybegin4");
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template<typename Scalar, typename Index, int Pack1, int Pack2, int StorageOrder, bool Conjugate, bool PanelMode>
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struct gemm_pack_lhs
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{
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EIGEN_DONT_INLINE void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows,
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Index stride=0, Index offset=0)
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EIGEN_DONT_INLINE void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows, Index stride=0, Index offset=0);
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};
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template<typename Scalar, typename Index, int Pack1, int Pack2, int StorageOrder, bool Conjugate, bool PanelMode>
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EIGEN_DONT_INLINE void gemm_pack_lhs<Scalar, Index, Pack1, Pack2, StorageOrder, Conjugate, PanelMode>
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::operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows, Index stride, Index offset)
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{
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typedef typename packet_traits<Scalar>::type Packet;
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enum { PacketSize = packet_traits<Scalar>::size };
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@ -1183,7 +1194,6 @@ struct gemm_pack_lhs
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if(PanelMode) count += (stride-offset-depth);
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}
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}
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};
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// copy a complete panel of the rhs
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// this version is optimized for column major matrices
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@ -1197,8 +1207,12 @@ struct gemm_pack_rhs<Scalar, Index, nr, ColMajor, Conjugate, PanelMode>
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{
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typedef typename packet_traits<Scalar>::type Packet;
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enum { PacketSize = packet_traits<Scalar>::size };
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EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols,
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Index stride=0, Index offset=0)
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EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride=0, Index offset=0);
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};
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template<typename Scalar, typename Index, int nr, bool Conjugate, bool PanelMode>
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EIGEN_DONT_INLINE void gemm_pack_rhs<Scalar, Index, nr, ColMajor, Conjugate, PanelMode>
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::operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride, Index offset)
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{
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EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS COLMAJOR");
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eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
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@ -1238,15 +1252,18 @@ struct gemm_pack_rhs<Scalar, Index, nr, ColMajor, Conjugate, PanelMode>
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if(PanelMode) count += (stride-offset-depth);
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}
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}
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};
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// this version is optimized for row major matrices
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template<typename Scalar, typename Index, int nr, bool Conjugate, bool PanelMode>
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struct gemm_pack_rhs<Scalar, Index, nr, RowMajor, Conjugate, PanelMode>
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{
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enum { PacketSize = packet_traits<Scalar>::size };
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EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols,
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Index stride=0, Index offset=0)
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EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride=0, Index offset=0);
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};
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template<typename Scalar, typename Index, int nr, bool Conjugate, bool PanelMode>
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EIGEN_DONT_INLINE void gemm_pack_rhs<Scalar, Index, nr, RowMajor, Conjugate, PanelMode>
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::operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride, Index offset)
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{
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EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS ROWMAJOR");
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eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
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@ -1282,7 +1299,6 @@ struct gemm_pack_rhs<Scalar, Index, nr, RowMajor, Conjugate, PanelMode>
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if(PanelMode) count += stride-offset-depth;
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}
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}
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};
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} // end namespace internal
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@ -50,6 +50,7 @@ template<
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typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs>
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struct general_matrix_matrix_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,ColMajor>
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{
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typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
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static void run(Index rows, Index cols, Index depth,
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const LhsScalar* _lhs, Index lhsStride,
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@ -169,7 +170,6 @@ static void run(Index rows, Index cols, Index depth,
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// vertical panel which is, in practice, a very low number.
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pack_rhs(blockB, &rhs(k2,0), rhsStride, actual_kc, cols);
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// For each mc x kc block of the lhs's vertical panel...
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// (==GEPP_VAR1)
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for(Index i2=0; i2<rows; i2+=mc)
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@ -183,7 +183,6 @@ static void run(Index rows, Index cols, Index depth,
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// Everything is packed, we can now call the block * panel kernel:
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gebp(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha, -1, -1, 0, 0, blockW);
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}
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}
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}
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@ -49,6 +49,18 @@ typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
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typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
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EIGEN_DONT_INLINE static void run(
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Index rows, Index cols,
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const LhsScalar* lhs, Index lhsStride,
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const RhsScalar* rhs, Index rhsIncr,
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ResScalar* res, Index
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#ifdef EIGEN_INTERNAL_DEBUGGING
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resIncr
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#endif
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, RhsScalar alpha);
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};
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template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version>
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EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>::run(
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Index rows, Index cols,
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const LhsScalar* lhs, Index lhsStride,
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const RhsScalar* rhs, Index rhsIncr,
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@ -274,7 +286,6 @@ EIGEN_DONT_INLINE static void run(
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} while(Vectorizable);
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#undef _EIGEN_ACCUMULATE_PACKETS
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}
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};
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/* Optimized row-major matrix * vector product:
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* This algorithm processes 4 rows at onces that allows to both reduce
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@ -308,6 +319,15 @@ typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
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typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
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EIGEN_DONT_INLINE static void run(
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Index rows, Index cols,
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const LhsScalar* lhs, Index lhsStride,
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const RhsScalar* rhs, Index rhsIncr,
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ResScalar* res, Index resIncr,
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ResScalar alpha);
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};
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template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version>
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EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>::run(
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Index rows, Index cols,
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const LhsScalar* lhs, Index lhsStride,
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const RhsScalar* rhs, Index rhsIncr,
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@ -545,7 +565,6 @@ EIGEN_DONT_INLINE static void run(
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#undef _EIGEN_ACCUMULATE_PACKETS
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}
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};
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} // end namespace internal
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@ -53,7 +53,7 @@ struct general_matrix_vector_product_gemv :
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#define EIGEN_MKL_GEMV_SPECIALIZE(Scalar) \
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template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
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struct general_matrix_vector_product<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs,Specialized> { \
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static EIGEN_DONT_INLINE void run( \
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static void run( \
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Index rows, Index cols, \
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const Scalar* lhs, Index lhsStride, \
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const Scalar* rhs, Index rhsIncr, \
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@ -70,7 +70,7 @@ static EIGEN_DONT_INLINE void run( \
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}; \
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template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
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struct general_matrix_vector_product<Index,Scalar,RowMajor,ConjugateLhs,Scalar,ConjugateRhs,Specialized> { \
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static EIGEN_DONT_INLINE void run( \
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static void run( \
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Index rows, Index cols, \
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const Scalar* lhs, Index lhsStride, \
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const Scalar* rhs, Index rhsIncr, \
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@ -92,7 +92,7 @@ struct general_matrix_vector_product_gemv<Index,EIGTYPE,LhsStorageOrder,Conjugat
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{ \
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typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> GEMVVector;\
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\
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static EIGEN_DONT_INLINE void run( \
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static void run( \
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Index rows, Index cols, \
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const EIGTYPE* lhs, Index lhsStride, \
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const EIGTYPE* rhs, Index rhsIncr, \
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@ -230,6 +230,17 @@ struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs
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{
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static EIGEN_DONT_INLINE void run(
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Index rows, Index cols,
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const Scalar* _lhs, Index lhsStride,
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const Scalar* _rhs, Index rhsStride,
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Scalar* res, Index resStride,
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const Scalar& alpha);
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};
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template <typename Scalar, typename Index,
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int LhsStorageOrder, bool ConjugateLhs,
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int RhsStorageOrder, bool ConjugateRhs>
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EIGEN_DONT_INLINE void product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs, RhsStorageOrder,false,ConjugateRhs,ColMajor>::run(
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Index rows, Index cols,
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const Scalar* _lhs, Index lhsStride,
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const Scalar* _rhs, Index rhsStride,
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@ -301,7 +312,6 @@ struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs
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}
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}
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}
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};
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// matrix * selfadjoint product
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template <typename Scalar, typename Index,
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@ -311,6 +321,17 @@ struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLh
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{
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static EIGEN_DONT_INLINE void run(
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Index rows, Index cols,
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const Scalar* _lhs, Index lhsStride,
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const Scalar* _rhs, Index rhsStride,
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Scalar* res, Index resStride,
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const Scalar& alpha);
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};
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template <typename Scalar, typename Index,
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int LhsStorageOrder, bool ConjugateLhs,
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int RhsStorageOrder, bool ConjugateRhs>
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EIGEN_DONT_INLINE void product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLhs, RhsStorageOrder,true,ConjugateRhs,ColMajor>::run(
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Index rows, Index cols,
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const Scalar* _lhs, Index lhsStride,
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const Scalar* _rhs, Index rhsStride,
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@ -353,7 +374,6 @@ struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLh
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}
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}
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}
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};
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} // end namespace internal
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@ -23,7 +23,7 @@
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ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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//
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********************************************************************************
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* Content : Eigen bindings to Intel(R) MKL
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* Self adjoint matrix * matrix product functionality based on ?SYMM/?HEMM.
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@ -47,7 +47,7 @@ template <typename Index, \
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struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLhs,RhsStorageOrder,false,ConjugateRhs,ColMajor> \
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{\
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\
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static EIGEN_DONT_INLINE void run( \
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static void run( \
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Index rows, Index cols, \
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const EIGTYPE* _lhs, Index lhsStride, \
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const EIGTYPE* _rhs, Index rhsStride, \
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@ -98,7 +98,7 @@ template <typename Index, \
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int RhsStorageOrder, bool ConjugateRhs> \
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struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLhs,RhsStorageOrder,false,ConjugateRhs,ColMajor> \
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{\
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static EIGEN_DONT_INLINE void run( \
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static void run( \
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Index rows, Index cols, \
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const EIGTYPE* _lhs, Index lhsStride, \
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const EIGTYPE* _rhs, Index rhsStride, \
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@ -174,7 +174,7 @@ template <typename Index, \
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struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateLhs,RhsStorageOrder,true,ConjugateRhs,ColMajor> \
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{\
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\
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static EIGEN_DONT_INLINE void run( \
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static void run( \
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Index rows, Index cols, \
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const EIGTYPE* _lhs, Index lhsStride, \
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const EIGTYPE* _rhs, Index rhsStride, \
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@ -224,7 +224,7 @@ template <typename Index, \
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int RhsStorageOrder, bool ConjugateRhs> \
|
||||
struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateLhs,RhsStorageOrder,true,ConjugateRhs,ColMajor> \
|
||||
{\
|
||||
static EIGEN_DONT_INLINE void run( \
|
||||
static void run( \
|
||||
Index rows, Index cols, \
|
||||
const EIGTYPE* _lhs, Index lhsStride, \
|
||||
const EIGTYPE* _rhs, Index rhsStride, \
|
||||
|
@ -28,6 +28,15 @@ struct selfadjoint_matrix_vector_product
|
||||
|
||||
{
|
||||
static EIGEN_DONT_INLINE void run(
|
||||
Index size,
|
||||
const Scalar* lhs, Index lhsStride,
|
||||
const Scalar* _rhs, Index rhsIncr,
|
||||
Scalar* res,
|
||||
Scalar alpha);
|
||||
};
|
||||
|
||||
template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs, int Version>
|
||||
EIGEN_DONT_INLINE void selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Version>::run(
|
||||
Index size,
|
||||
const Scalar* lhs, Index lhsStride,
|
||||
const Scalar* _rhs, Index rhsIncr,
|
||||
@ -153,7 +162,6 @@ static EIGEN_DONT_INLINE void run(
|
||||
res[j] += alpha * t2;
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
|
@ -50,7 +50,7 @@ struct selfadjoint_matrix_vector_product_symv :
|
||||
#define EIGEN_MKL_SYMV_SPECIALIZE(Scalar) \
|
||||
template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
|
||||
struct selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Specialized> { \
|
||||
static EIGEN_DONT_INLINE void run( \
|
||||
static void run( \
|
||||
Index size, const Scalar* lhs, Index lhsStride, \
|
||||
const Scalar* _rhs, Index rhsIncr, Scalar* res, Scalar alpha) { \
|
||||
enum {\
|
||||
@ -77,7 +77,7 @@ struct selfadjoint_matrix_vector_product_symv<EIGTYPE,Index,StorageOrder,UpLo,Co
|
||||
{ \
|
||||
typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> SYMVVector;\
|
||||
\
|
||||
static EIGEN_DONT_INLINE void run( \
|
||||
static void run( \
|
||||
Index size, const EIGTYPE* lhs, Index lhsStride, \
|
||||
const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* res, EIGTYPE alpha) \
|
||||
{ \
|
||||
|
@ -96,6 +96,19 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
|
||||
const Scalar* _lhs, Index lhsStride,
|
||||
const Scalar* _rhs, Index rhsStride,
|
||||
Scalar* res, Index resStride,
|
||||
const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking);
|
||||
};
|
||||
|
||||
template <typename Scalar, typename Index, int Mode,
|
||||
int LhsStorageOrder, bool ConjugateLhs,
|
||||
int RhsStorageOrder, bool ConjugateRhs, int Version>
|
||||
EIGEN_DONT_INLINE void product_triangular_matrix_matrix<Scalar,Index,Mode,true,
|
||||
LhsStorageOrder,ConjugateLhs,
|
||||
RhsStorageOrder,ConjugateRhs,ColMajor,Version>::run(
|
||||
Index _rows, Index _cols, Index _depth,
|
||||
const Scalar* _lhs, Index lhsStride,
|
||||
const Scalar* _rhs, Index rhsStride,
|
||||
Scalar* res, Index resStride,
|
||||
const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
|
||||
{
|
||||
// strip zeros
|
||||
@ -203,7 +216,6 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// implements col-major += alpha * op(general) * op(triangular)
|
||||
template <typename Scalar, typename Index, int Mode,
|
||||
@ -225,6 +237,19 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,false,
|
||||
const Scalar* _lhs, Index lhsStride,
|
||||
const Scalar* _rhs, Index rhsStride,
|
||||
Scalar* res, Index resStride,
|
||||
const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking);
|
||||
};
|
||||
|
||||
template <typename Scalar, typename Index, int Mode,
|
||||
int LhsStorageOrder, bool ConjugateLhs,
|
||||
int RhsStorageOrder, bool ConjugateRhs, int Version>
|
||||
EIGEN_DONT_INLINE void product_triangular_matrix_matrix<Scalar,Index,Mode,false,
|
||||
LhsStorageOrder,ConjugateLhs,
|
||||
RhsStorageOrder,ConjugateRhs,ColMajor,Version>::run(
|
||||
Index _rows, Index _cols, Index _depth,
|
||||
const Scalar* _lhs, Index lhsStride,
|
||||
const Scalar* _rhs, Index rhsStride,
|
||||
Scalar* res, Index resStride,
|
||||
const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
|
||||
{
|
||||
// strip zeros
|
||||
@ -343,7 +368,6 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,false,
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
/***************************************************************************
|
||||
* Wrapper to product_triangular_matrix_matrix
|
||||
|
@ -91,7 +91,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
|
||||
conjA = ((LhsStorageOrder==ColMajor) && ConjugateLhs) ? 1 : 0 \
|
||||
}; \
|
||||
\
|
||||
static EIGEN_DONT_INLINE void run( \
|
||||
static void run( \
|
||||
Index _rows, Index _cols, Index _depth, \
|
||||
const EIGTYPE* _lhs, Index lhsStride, \
|
||||
const EIGTYPE* _rhs, Index rhsStride, \
|
||||
@ -205,7 +205,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
|
||||
conjA = ((RhsStorageOrder==ColMajor) && ConjugateRhs) ? 1 : 0 \
|
||||
}; \
|
||||
\
|
||||
static EIGEN_DONT_INLINE void run( \
|
||||
static void run( \
|
||||
Index _rows, Index _cols, Index _depth, \
|
||||
const EIGTYPE* _lhs, Index lhsStride, \
|
||||
const EIGTYPE* _rhs, Index rhsStride, \
|
||||
|
@ -27,6 +27,12 @@ struct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,C
|
||||
HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
|
||||
};
|
||||
static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
|
||||
const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const ResScalar& alpha);
|
||||
};
|
||||
|
||||
template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int Version>
|
||||
EIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor,Version>
|
||||
::run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
|
||||
const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const ResScalar& alpha)
|
||||
{
|
||||
static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
|
||||
@ -78,7 +84,6 @@ struct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,C
|
||||
_res, resIncr, alpha);
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs,int Version>
|
||||
struct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor,Version>
|
||||
@ -89,7 +94,13 @@ struct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,C
|
||||
HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
|
||||
HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
|
||||
};
|
||||
static void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
|
||||
static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
|
||||
const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const ResScalar& alpha);
|
||||
};
|
||||
|
||||
template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs,int Version>
|
||||
EIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor,Version>
|
||||
::run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
|
||||
const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const ResScalar& alpha)
|
||||
{
|
||||
static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
|
||||
@ -141,7 +152,6 @@ struct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,C
|
||||
&res.coeffRef(diagSize), resIncr, alpha);
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
/***************************************************************************
|
||||
* Wrapper to product_triangular_vector
|
||||
|
@ -50,7 +50,7 @@ struct triangular_matrix_vector_product_trmv :
|
||||
#define EIGEN_MKL_TRMV_SPECIALIZE(Scalar) \
|
||||
template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
|
||||
struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor,Specialized> { \
|
||||
static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
|
||||
static void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
|
||||
const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
|
||||
triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor>::run( \
|
||||
_rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
|
||||
@ -58,7 +58,7 @@ struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs
|
||||
}; \
|
||||
template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
|
||||
struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor,Specialized> { \
|
||||
static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
|
||||
static void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
|
||||
const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
|
||||
triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor>::run( \
|
||||
_rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
|
||||
@ -81,7 +81,7 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
|
||||
IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \
|
||||
LowUp = IsLower ? Lower : Upper \
|
||||
}; \
|
||||
static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
|
||||
static void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
|
||||
const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
|
||||
{ \
|
||||
if (ConjLhs || IsZeroDiag) { \
|
||||
@ -166,7 +166,7 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
|
||||
IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \
|
||||
LowUp = IsLower ? Lower : Upper \
|
||||
}; \
|
||||
static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
|
||||
static void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
|
||||
const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
|
||||
{ \
|
||||
if (IsZeroDiag) { \
|
||||
|
@ -18,7 +18,7 @@ namespace internal {
|
||||
template <typename Scalar, typename Index, int Side, int Mode, bool Conjugate, int TriStorageOrder>
|
||||
struct triangular_solve_matrix<Scalar,Index,Side,Mode,Conjugate,TriStorageOrder,RowMajor>
|
||||
{
|
||||
static EIGEN_DONT_INLINE void run(
|
||||
static void run(
|
||||
Index size, Index cols,
|
||||
const Scalar* tri, Index triStride,
|
||||
Scalar* _other, Index otherStride,
|
||||
@ -39,6 +39,13 @@ template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStor
|
||||
struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor>
|
||||
{
|
||||
static EIGEN_DONT_INLINE void run(
|
||||
Index size, Index otherSize,
|
||||
const Scalar* _tri, Index triStride,
|
||||
Scalar* _other, Index otherStride,
|
||||
level3_blocking<Scalar,Scalar>& blocking);
|
||||
};
|
||||
template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStorageOrder>
|
||||
EIGEN_DONT_INLINE void triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor>::run(
|
||||
Index size, Index otherSize,
|
||||
const Scalar* _tri, Index triStride,
|
||||
Scalar* _other, Index otherStride,
|
||||
@ -173,7 +180,6 @@ struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageO
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
/* Optimized triangular solver with multiple left hand sides and the trinagular matrix on the right
|
||||
*/
|
||||
@ -181,6 +187,13 @@ template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStor
|
||||
struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor>
|
||||
{
|
||||
static EIGEN_DONT_INLINE void run(
|
||||
Index size, Index otherSize,
|
||||
const Scalar* _tri, Index triStride,
|
||||
Scalar* _other, Index otherStride,
|
||||
level3_blocking<Scalar,Scalar>& blocking);
|
||||
};
|
||||
template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStorageOrder>
|
||||
EIGEN_DONT_INLINE void triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor>::run(
|
||||
Index size, Index otherSize,
|
||||
const Scalar* _tri, Index triStride,
|
||||
Scalar* _other, Index otherStride,
|
||||
@ -308,7 +321,6 @@ struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorage
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
|
@ -48,7 +48,7 @@ struct triangular_solve_matrix<EIGTYPE,Index,OnTheLeft,Mode,Conjugate,TriStorage
|
||||
IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \
|
||||
conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
|
||||
}; \
|
||||
static EIGEN_DONT_INLINE void run( \
|
||||
static void run( \
|
||||
Index size, Index otherSize, \
|
||||
const EIGTYPE* _tri, Index triStride, \
|
||||
EIGTYPE* _other, Index otherStride, level3_blocking<EIGTYPE,EIGTYPE>& /*blocking*/) \
|
||||
@ -103,7 +103,7 @@ struct triangular_solve_matrix<EIGTYPE,Index,OnTheRight,Mode,Conjugate,TriStorag
|
||||
IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \
|
||||
conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
|
||||
}; \
|
||||
static EIGEN_DONT_INLINE void run( \
|
||||
static void run( \
|
||||
Index size, Index otherSize, \
|
||||
const EIGTYPE* _tri, Index triStride, \
|
||||
EIGTYPE* _other, Index otherStride, level3_blocking<EIGTYPE,EIGTYPE>& /*blocking*/) \
|
||||
|
@ -213,7 +213,7 @@ class SparseMatrix
|
||||
* inserted in increasing inner index order, and in O(nnz_j) for a random insertion.
|
||||
*
|
||||
*/
|
||||
EIGEN_DONT_INLINE Scalar& insert(Index row, Index col)
|
||||
Scalar& insert(Index row, Index col)
|
||||
{
|
||||
if(isCompressed())
|
||||
{
|
||||
@ -434,7 +434,7 @@ class SparseMatrix
|
||||
|
||||
/** \internal
|
||||
* same as insert(Index,Index) except that the indices are given relative to the storage order */
|
||||
EIGEN_DONT_INLINE Scalar& insertByOuterInner(Index j, Index i)
|
||||
Scalar& insertByOuterInner(Index j, Index i)
|
||||
{
|
||||
return insert(IsRowMajor ? j : i, IsRowMajor ? i : j);
|
||||
}
|
||||
@ -711,62 +711,7 @@ class SparseMatrix
|
||||
#endif
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other)
|
||||
{
|
||||
const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
|
||||
if (needToTranspose)
|
||||
{
|
||||
// two passes algorithm:
|
||||
// 1 - compute the number of coeffs per dest inner vector
|
||||
// 2 - do the actual copy/eval
|
||||
// Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed
|
||||
typedef typename internal::nested<OtherDerived,2>::type OtherCopy;
|
||||
typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
|
||||
OtherCopy otherCopy(other.derived());
|
||||
|
||||
SparseMatrix dest(other.rows(),other.cols());
|
||||
Eigen::Map<Matrix<Index, Dynamic, 1> > (dest.m_outerIndex,dest.outerSize()).setZero();
|
||||
|
||||
// pass 1
|
||||
// FIXME the above copy could be merged with that pass
|
||||
for (Index j=0; j<otherCopy.outerSize(); ++j)
|
||||
for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
|
||||
++dest.m_outerIndex[it.index()];
|
||||
|
||||
// prefix sum
|
||||
Index count = 0;
|
||||
VectorXi positions(dest.outerSize());
|
||||
for (Index j=0; j<dest.outerSize(); ++j)
|
||||
{
|
||||
Index tmp = dest.m_outerIndex[j];
|
||||
dest.m_outerIndex[j] = count;
|
||||
positions[j] = count;
|
||||
count += tmp;
|
||||
}
|
||||
dest.m_outerIndex[dest.outerSize()] = count;
|
||||
// alloc
|
||||
dest.m_data.resize(count);
|
||||
// pass 2
|
||||
for (Index j=0; j<otherCopy.outerSize(); ++j)
|
||||
{
|
||||
for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
|
||||
{
|
||||
Index pos = positions[it.index()]++;
|
||||
dest.m_data.index(pos) = j;
|
||||
dest.m_data.value(pos) = it.value();
|
||||
}
|
||||
}
|
||||
this->swap(dest);
|
||||
return *this;
|
||||
}
|
||||
else
|
||||
{
|
||||
if(other.isRValue())
|
||||
initAssignment(other.derived());
|
||||
// there is no special optimization
|
||||
return Base::operator=(other.derived());
|
||||
}
|
||||
}
|
||||
EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other);
|
||||
|
||||
friend std::ostream & operator << (std::ostream & s, const SparseMatrix& m)
|
||||
{
|
||||
@ -836,111 +781,7 @@ protected:
|
||||
|
||||
/** \internal
|
||||
* \sa insert(Index,Index) */
|
||||
EIGEN_DONT_INLINE Scalar& insertCompressed(Index row, Index col)
|
||||
{
|
||||
eigen_assert(isCompressed());
|
||||
|
||||
const Index outer = IsRowMajor ? row : col;
|
||||
const Index inner = IsRowMajor ? col : row;
|
||||
|
||||
Index previousOuter = outer;
|
||||
if (m_outerIndex[outer+1]==0)
|
||||
{
|
||||
// we start a new inner vector
|
||||
while (previousOuter>=0 && m_outerIndex[previousOuter]==0)
|
||||
{
|
||||
m_outerIndex[previousOuter] = static_cast<Index>(m_data.size());
|
||||
--previousOuter;
|
||||
}
|
||||
m_outerIndex[outer+1] = m_outerIndex[outer];
|
||||
}
|
||||
|
||||
// here we have to handle the tricky case where the outerIndex array
|
||||
// starts with: [ 0 0 0 0 0 1 ...] and we are inserted in, e.g.,
|
||||
// the 2nd inner vector...
|
||||
bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0))
|
||||
&& (size_t(m_outerIndex[outer+1]) == m_data.size());
|
||||
|
||||
size_t startId = m_outerIndex[outer];
|
||||
// FIXME let's make sure sizeof(long int) == sizeof(size_t)
|
||||
size_t p = m_outerIndex[outer+1];
|
||||
++m_outerIndex[outer+1];
|
||||
|
||||
float reallocRatio = 1;
|
||||
if (m_data.allocatedSize()<=m_data.size())
|
||||
{
|
||||
// if there is no preallocated memory, let's reserve a minimum of 32 elements
|
||||
if (m_data.size()==0)
|
||||
{
|
||||
m_data.reserve(32);
|
||||
}
|
||||
else
|
||||
{
|
||||
// we need to reallocate the data, to reduce multiple reallocations
|
||||
// we use a smart resize algorithm based on the current filling ratio
|
||||
// in addition, we use float to avoid integers overflows
|
||||
float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer+1);
|
||||
reallocRatio = (nnzEstimate-float(m_data.size()))/float(m_data.size());
|
||||
// furthermore we bound the realloc ratio to:
|
||||
// 1) reduce multiple minor realloc when the matrix is almost filled
|
||||
// 2) avoid to allocate too much memory when the matrix is almost empty
|
||||
reallocRatio = (std::min)((std::max)(reallocRatio,1.5f),8.f);
|
||||
}
|
||||
}
|
||||
m_data.resize(m_data.size()+1,reallocRatio);
|
||||
|
||||
if (!isLastVec)
|
||||
{
|
||||
if (previousOuter==-1)
|
||||
{
|
||||
// oops wrong guess.
|
||||
// let's correct the outer offsets
|
||||
for (Index k=0; k<=(outer+1); ++k)
|
||||
m_outerIndex[k] = 0;
|
||||
Index k=outer+1;
|
||||
while(m_outerIndex[k]==0)
|
||||
m_outerIndex[k++] = 1;
|
||||
while (k<=m_outerSize && m_outerIndex[k]!=0)
|
||||
m_outerIndex[k++]++;
|
||||
p = 0;
|
||||
--k;
|
||||
k = m_outerIndex[k]-1;
|
||||
while (k>0)
|
||||
{
|
||||
m_data.index(k) = m_data.index(k-1);
|
||||
m_data.value(k) = m_data.value(k-1);
|
||||
k--;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
// we are not inserting into the last inner vec
|
||||
// update outer indices:
|
||||
Index j = outer+2;
|
||||
while (j<=m_outerSize && m_outerIndex[j]!=0)
|
||||
m_outerIndex[j++]++;
|
||||
--j;
|
||||
// shift data of last vecs:
|
||||
Index k = m_outerIndex[j]-1;
|
||||
while (k>=Index(p))
|
||||
{
|
||||
m_data.index(k) = m_data.index(k-1);
|
||||
m_data.value(k) = m_data.value(k-1);
|
||||
k--;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
while ( (p > startId) && (m_data.index(p-1) > inner) )
|
||||
{
|
||||
m_data.index(p) = m_data.index(p-1);
|
||||
m_data.value(p) = m_data.value(p-1);
|
||||
--p;
|
||||
}
|
||||
|
||||
m_data.index(p) = inner;
|
||||
return (m_data.value(p) = 0);
|
||||
}
|
||||
EIGEN_DONT_INLINE Scalar& insertCompressed(Index row, Index col);
|
||||
|
||||
/** \internal
|
||||
* A vector object that is equal to 0 everywhere but v at the position i */
|
||||
@ -959,36 +800,7 @@ protected:
|
||||
|
||||
/** \internal
|
||||
* \sa insert(Index,Index) */
|
||||
EIGEN_DONT_INLINE Scalar& insertUncompressed(Index row, Index col)
|
||||
{
|
||||
eigen_assert(!isCompressed());
|
||||
|
||||
const Index outer = IsRowMajor ? row : col;
|
||||
const Index inner = IsRowMajor ? col : row;
|
||||
|
||||
std::ptrdiff_t room = m_outerIndex[outer+1] - m_outerIndex[outer];
|
||||
std::ptrdiff_t innerNNZ = m_innerNonZeros[outer];
|
||||
if(innerNNZ>=room)
|
||||
{
|
||||
// this inner vector is full, we need to reallocate the whole buffer :(
|
||||
reserve(SingletonVector(outer,std::max<std::ptrdiff_t>(2,innerNNZ)));
|
||||
}
|
||||
|
||||
Index startId = m_outerIndex[outer];
|
||||
Index p = startId + m_innerNonZeros[outer];
|
||||
while ( (p > startId) && (m_data.index(p-1) > inner) )
|
||||
{
|
||||
m_data.index(p) = m_data.index(p-1);
|
||||
m_data.value(p) = m_data.value(p-1);
|
||||
--p;
|
||||
}
|
||||
eigen_assert((p<=startId || m_data.index(p-1)!=inner) && "you cannot insert an element that already exist, you must call coeffRef to this end");
|
||||
|
||||
m_innerNonZeros[outer]++;
|
||||
|
||||
m_data.index(p) = inner;
|
||||
return (m_data.value(p) = 0);
|
||||
}
|
||||
EIGEN_DONT_INLINE Scalar& insertUncompressed(Index row, Index col);
|
||||
|
||||
public:
|
||||
/** \internal
|
||||
@ -1205,6 +1017,204 @@ void SparseMatrix<Scalar,_Options,_Index>::sumupDuplicates()
|
||||
m_data.resize(m_outerIndex[m_outerSize]);
|
||||
}
|
||||
|
||||
template<typename Scalar, int _Options, typename _Index>
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DONT_INLINE SparseMatrix<Scalar,_Options,_Index>& SparseMatrix<Scalar,_Options,_Index>::operator=(const SparseMatrixBase<OtherDerived>& other)
|
||||
{
|
||||
const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
|
||||
if (needToTranspose)
|
||||
{
|
||||
// two passes algorithm:
|
||||
// 1 - compute the number of coeffs per dest inner vector
|
||||
// 2 - do the actual copy/eval
|
||||
// Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed
|
||||
typedef typename internal::nested<OtherDerived,2>::type OtherCopy;
|
||||
typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
|
||||
OtherCopy otherCopy(other.derived());
|
||||
|
||||
SparseMatrix dest(other.rows(),other.cols());
|
||||
Eigen::Map<Matrix<Index, Dynamic, 1> > (dest.m_outerIndex,dest.outerSize()).setZero();
|
||||
|
||||
// pass 1
|
||||
// FIXME the above copy could be merged with that pass
|
||||
for (Index j=0; j<otherCopy.outerSize(); ++j)
|
||||
for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
|
||||
++dest.m_outerIndex[it.index()];
|
||||
|
||||
// prefix sum
|
||||
Index count = 0;
|
||||
VectorXi positions(dest.outerSize());
|
||||
for (Index j=0; j<dest.outerSize(); ++j)
|
||||
{
|
||||
Index tmp = dest.m_outerIndex[j];
|
||||
dest.m_outerIndex[j] = count;
|
||||
positions[j] = count;
|
||||
count += tmp;
|
||||
}
|
||||
dest.m_outerIndex[dest.outerSize()] = count;
|
||||
// alloc
|
||||
dest.m_data.resize(count);
|
||||
// pass 2
|
||||
for (Index j=0; j<otherCopy.outerSize(); ++j)
|
||||
{
|
||||
for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
|
||||
{
|
||||
Index pos = positions[it.index()]++;
|
||||
dest.m_data.index(pos) = j;
|
||||
dest.m_data.value(pos) = it.value();
|
||||
}
|
||||
}
|
||||
this->swap(dest);
|
||||
return *this;
|
||||
}
|
||||
else
|
||||
{
|
||||
if(other.isRValue())
|
||||
initAssignment(other.derived());
|
||||
// there is no special optimization
|
||||
return Base::operator=(other.derived());
|
||||
}
|
||||
}
|
||||
|
||||
template<typename _Scalar, int _Options, typename _Index>
|
||||
EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& SparseMatrix<_Scalar,_Options,_Index>::insertUncompressed(Index row, Index col)
|
||||
{
|
||||
eigen_assert(!isCompressed());
|
||||
|
||||
const Index outer = IsRowMajor ? row : col;
|
||||
const Index inner = IsRowMajor ? col : row;
|
||||
|
||||
std::ptrdiff_t room = m_outerIndex[outer+1] - m_outerIndex[outer];
|
||||
std::ptrdiff_t innerNNZ = m_innerNonZeros[outer];
|
||||
if(innerNNZ>=room)
|
||||
{
|
||||
// this inner vector is full, we need to reallocate the whole buffer :(
|
||||
reserve(SingletonVector(outer,std::max<std::ptrdiff_t>(2,innerNNZ)));
|
||||
}
|
||||
|
||||
Index startId = m_outerIndex[outer];
|
||||
Index p = startId + m_innerNonZeros[outer];
|
||||
while ( (p > startId) && (m_data.index(p-1) > inner) )
|
||||
{
|
||||
m_data.index(p) = m_data.index(p-1);
|
||||
m_data.value(p) = m_data.value(p-1);
|
||||
--p;
|
||||
}
|
||||
eigen_assert((p<=startId || m_data.index(p-1)!=inner) && "you cannot insert an element that already exist, you must call coeffRef to this end");
|
||||
|
||||
m_innerNonZeros[outer]++;
|
||||
|
||||
m_data.index(p) = inner;
|
||||
return (m_data.value(p) = 0);
|
||||
}
|
||||
|
||||
template<typename _Scalar, int _Options, typename _Index>
|
||||
EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& SparseMatrix<_Scalar,_Options,_Index>::insertCompressed(Index row, Index col)
|
||||
{
|
||||
eigen_assert(isCompressed());
|
||||
|
||||
const Index outer = IsRowMajor ? row : col;
|
||||
const Index inner = IsRowMajor ? col : row;
|
||||
|
||||
Index previousOuter = outer;
|
||||
if (m_outerIndex[outer+1]==0)
|
||||
{
|
||||
// we start a new inner vector
|
||||
while (previousOuter>=0 && m_outerIndex[previousOuter]==0)
|
||||
{
|
||||
m_outerIndex[previousOuter] = static_cast<Index>(m_data.size());
|
||||
--previousOuter;
|
||||
}
|
||||
m_outerIndex[outer+1] = m_outerIndex[outer];
|
||||
}
|
||||
|
||||
// here we have to handle the tricky case where the outerIndex array
|
||||
// starts with: [ 0 0 0 0 0 1 ...] and we are inserted in, e.g.,
|
||||
// the 2nd inner vector...
|
||||
bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0))
|
||||
&& (size_t(m_outerIndex[outer+1]) == m_data.size());
|
||||
|
||||
size_t startId = m_outerIndex[outer];
|
||||
// FIXME let's make sure sizeof(long int) == sizeof(size_t)
|
||||
size_t p = m_outerIndex[outer+1];
|
||||
++m_outerIndex[outer+1];
|
||||
|
||||
float reallocRatio = 1;
|
||||
if (m_data.allocatedSize()<=m_data.size())
|
||||
{
|
||||
// if there is no preallocated memory, let's reserve a minimum of 32 elements
|
||||
if (m_data.size()==0)
|
||||
{
|
||||
m_data.reserve(32);
|
||||
}
|
||||
else
|
||||
{
|
||||
// we need to reallocate the data, to reduce multiple reallocations
|
||||
// we use a smart resize algorithm based on the current filling ratio
|
||||
// in addition, we use float to avoid integers overflows
|
||||
float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer+1);
|
||||
reallocRatio = (nnzEstimate-float(m_data.size()))/float(m_data.size());
|
||||
// furthermore we bound the realloc ratio to:
|
||||
// 1) reduce multiple minor realloc when the matrix is almost filled
|
||||
// 2) avoid to allocate too much memory when the matrix is almost empty
|
||||
reallocRatio = (std::min)((std::max)(reallocRatio,1.5f),8.f);
|
||||
}
|
||||
}
|
||||
m_data.resize(m_data.size()+1,reallocRatio);
|
||||
|
||||
if (!isLastVec)
|
||||
{
|
||||
if (previousOuter==-1)
|
||||
{
|
||||
// oops wrong guess.
|
||||
// let's correct the outer offsets
|
||||
for (Index k=0; k<=(outer+1); ++k)
|
||||
m_outerIndex[k] = 0;
|
||||
Index k=outer+1;
|
||||
while(m_outerIndex[k]==0)
|
||||
m_outerIndex[k++] = 1;
|
||||
while (k<=m_outerSize && m_outerIndex[k]!=0)
|
||||
m_outerIndex[k++]++;
|
||||
p = 0;
|
||||
--k;
|
||||
k = m_outerIndex[k]-1;
|
||||
while (k>0)
|
||||
{
|
||||
m_data.index(k) = m_data.index(k-1);
|
||||
m_data.value(k) = m_data.value(k-1);
|
||||
k--;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
// we are not inserting into the last inner vec
|
||||
// update outer indices:
|
||||
Index j = outer+2;
|
||||
while (j<=m_outerSize && m_outerIndex[j]!=0)
|
||||
m_outerIndex[j++]++;
|
||||
--j;
|
||||
// shift data of last vecs:
|
||||
Index k = m_outerIndex[j]-1;
|
||||
while (k>=Index(p))
|
||||
{
|
||||
m_data.index(k) = m_data.index(k-1);
|
||||
m_data.value(k) = m_data.value(k-1);
|
||||
k--;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
while ( (p > startId) && (m_data.index(p-1) > inner) )
|
||||
{
|
||||
m_data.index(p) = m_data.index(p-1);
|
||||
m_data.value(p) = m_data.value(p-1);
|
||||
--p;
|
||||
}
|
||||
|
||||
m_data.index(p) = inner;
|
||||
return (m_data.value(p) = 0);
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_SPARSEMATRIX_H
|
||||
|
@ -309,30 +309,7 @@ class SparseVector
|
||||
|
||||
protected:
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DONT_INLINE SparseVector& assign(const SparseMatrixBase<OtherDerived>& _other)
|
||||
{
|
||||
const OtherDerived& other(_other.derived());
|
||||
const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
|
||||
if(needToTranspose)
|
||||
{
|
||||
Index size = other.size();
|
||||
Index nnz = other.nonZeros();
|
||||
resize(size);
|
||||
reserve(nnz);
|
||||
for(Index i=0; i<size; ++i)
|
||||
{
|
||||
typename OtherDerived::InnerIterator it(other, i);
|
||||
if(it)
|
||||
insert(i) = it.value();
|
||||
}
|
||||
return *this;
|
||||
}
|
||||
else
|
||||
{
|
||||
// there is no special optimization
|
||||
return Base::operator=(other);
|
||||
}
|
||||
}
|
||||
EIGEN_DONT_INLINE SparseVector& assign(const SparseMatrixBase<OtherDerived>& _other);
|
||||
|
||||
Storage m_data;
|
||||
Index m_size;
|
||||
@ -402,6 +379,33 @@ class SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator
|
||||
const Index m_start;
|
||||
};
|
||||
|
||||
template<typename Scalar, int _Options, typename _Index>
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DONT_INLINE SparseVector<Scalar,_Options,_Index>& SparseVector<Scalar,_Options,_Index>::assign(const SparseMatrixBase<OtherDerived>& _other)
|
||||
{
|
||||
const OtherDerived& other(_other.derived());
|
||||
const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
|
||||
if(needToTranspose)
|
||||
{
|
||||
Index size = other.size();
|
||||
Index nnz = other.nonZeros();
|
||||
resize(size);
|
||||
reserve(nnz);
|
||||
for(Index i=0; i<size; ++i)
|
||||
{
|
||||
typename OtherDerived::InnerIterator it(other, i);
|
||||
if(it)
|
||||
insert(i) = it.value();
|
||||
}
|
||||
return *this;
|
||||
}
|
||||
else
|
||||
{
|
||||
// there is no special optimization
|
||||
return Base::operator=(other);
|
||||
}
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_SPARSEVECTOR_H
|
||||
|
Loading…
Reference in New Issue
Block a user