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490 lines
15 KiB
C++
490 lines
15 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_SPARSEVECTOR_H
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#define EIGEN_SPARSEVECTOR_H
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namespace Eigen {
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/** \ingroup SparseCore_Module
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* \class SparseVector
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*
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* \brief a sparse vector class
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*
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* \tparam _Scalar the scalar type, i.e. the type of the coefficients
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*
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* See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
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*
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* This class can be extended with the help of the plugin mechanism described on the page
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* \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN.
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*/
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namespace internal {
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template<typename _Scalar, int _Options, typename _Index>
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struct traits<SparseVector<_Scalar, _Options, _Index> >
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{
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typedef _Scalar Scalar;
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typedef _Index Index;
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typedef Sparse StorageKind;
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typedef MatrixXpr XprKind;
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enum {
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IsColVector = (_Options & RowMajorBit) ? 0 : 1,
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RowsAtCompileTime = IsColVector ? Dynamic : 1,
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ColsAtCompileTime = IsColVector ? 1 : Dynamic,
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MaxRowsAtCompileTime = RowsAtCompileTime,
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MaxColsAtCompileTime = ColsAtCompileTime,
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Flags = _Options | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit),
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CoeffReadCost = NumTraits<Scalar>::ReadCost,
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SupportedAccessPatterns = InnerRandomAccessPattern
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};
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};
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// Sparse-Vector-Assignment kinds:
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enum {
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SVA_RuntimeSwitch,
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SVA_Inner,
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SVA_Outer
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};
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template< typename Dest, typename Src,
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int AssignmentKind = !bool(Src::IsVectorAtCompileTime) ? SVA_RuntimeSwitch
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: Src::InnerSizeAtCompileTime==1 ? SVA_Outer
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: SVA_Inner>
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struct sparse_vector_assign_selector;
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}
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template<typename _Scalar, int _Options, typename _Index>
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class SparseVector
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: public SparseMatrixBase<SparseVector<_Scalar, _Options, _Index> >
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{
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typedef SparseMatrixBase<SparseVector> SparseBase;
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public:
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EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector)
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EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=)
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EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=)
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typedef internal::CompressedStorage<Scalar,Index> Storage;
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enum { IsColVector = internal::traits<SparseVector>::IsColVector };
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enum {
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Options = _Options
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};
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EIGEN_STRONG_INLINE Index rows() const { return IsColVector ? m_size : 1; }
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EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; }
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EIGEN_STRONG_INLINE Index innerSize() const { return m_size; }
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EIGEN_STRONG_INLINE Index outerSize() const { return 1; }
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EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return &m_data.value(0); }
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EIGEN_STRONG_INLINE Scalar* valuePtr() { return &m_data.value(0); }
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EIGEN_STRONG_INLINE const Index* innerIndexPtr() const { return &m_data.index(0); }
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EIGEN_STRONG_INLINE Index* innerIndexPtr() { return &m_data.index(0); }
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/** \internal */
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inline Storage& data() { return m_data; }
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/** \internal */
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inline const Storage& data() const { return m_data; }
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inline Scalar coeff(Index row, Index col) const
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{
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eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
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return coeff(IsColVector ? row : col);
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}
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inline Scalar coeff(Index i) const
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{
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eigen_assert(i>=0 && i<m_size);
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return m_data.at(i);
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}
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inline Scalar& coeffRef(Index row, Index col)
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{
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eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
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return coeffRef(IsColVector ? row : col);
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}
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/** \returns a reference to the coefficient value at given index \a i
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* This operation involes a log(rho*size) binary search. If the coefficient does not
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* exist yet, then a sorted insertion into a sequential buffer is performed.
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*
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* This insertion might be very costly if the number of nonzeros above \a i is large.
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*/
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inline Scalar& coeffRef(Index i)
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{
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eigen_assert(i>=0 && i<m_size);
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return m_data.atWithInsertion(i);
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}
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public:
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class InnerIterator;
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class ReverseInnerIterator;
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inline void setZero() { m_data.clear(); }
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/** \returns the number of non zero coefficients */
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inline Index nonZeros() const { return static_cast<Index>(m_data.size()); }
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inline void startVec(Index outer)
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{
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EIGEN_UNUSED_VARIABLE(outer);
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eigen_assert(outer==0);
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}
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inline Scalar& insertBackByOuterInner(Index outer, Index inner)
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{
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EIGEN_UNUSED_VARIABLE(outer);
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eigen_assert(outer==0);
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return insertBack(inner);
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}
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inline Scalar& insertBack(Index i)
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{
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m_data.append(0, i);
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return m_data.value(m_data.size()-1);
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}
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Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner)
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{
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EIGEN_UNUSED_VARIABLE(outer);
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eigen_assert(outer==0);
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return insertBackUnordered(inner);
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}
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inline Scalar& insertBackUnordered(Index i)
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{
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m_data.append(0, i);
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return m_data.value(m_data.size()-1);
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}
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inline Scalar& insert(Index row, Index col)
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{
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eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
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Index inner = IsColVector ? row : col;
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Index outer = IsColVector ? col : row;
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eigen_assert(outer==0);
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return insert(inner);
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}
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Scalar& insert(Index i)
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{
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eigen_assert(i>=0 && i<m_size);
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Index startId = 0;
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Index p = Index(m_data.size()) - 1;
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// TODO smart realloc
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m_data.resize(p+2,1);
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while ( (p >= startId) && (m_data.index(p) > i) )
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{
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m_data.index(p+1) = m_data.index(p);
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m_data.value(p+1) = m_data.value(p);
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--p;
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}
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m_data.index(p+1) = i;
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m_data.value(p+1) = 0;
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return m_data.value(p+1);
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}
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/**
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*/
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inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }
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inline void finalize() {}
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void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision())
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{
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m_data.prune(reference,epsilon);
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}
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void resize(Index rows, Index cols)
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{
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eigen_assert(rows==1 || cols==1);
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resize(IsColVector ? rows : cols);
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}
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void resize(Index newSize)
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{
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m_size = newSize;
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m_data.clear();
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}
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void resizeNonZeros(Index size) { m_data.resize(size); }
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inline SparseVector() : m_size(0) { check_template_parameters(); resize(0); }
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explicit inline SparseVector(Index size) : m_size(0) { check_template_parameters(); resize(size); }
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inline SparseVector(Index rows, Index cols) : m_size(0) { check_template_parameters(); resize(rows,cols); }
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template<typename OtherDerived>
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inline SparseVector(const SparseMatrixBase<OtherDerived>& other)
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: m_size(0)
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{
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check_template_parameters();
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*this = other.derived();
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}
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inline SparseVector(const SparseVector& other)
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: SparseBase(other), m_size(0)
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{
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check_template_parameters();
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*this = other.derived();
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}
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/** Swaps the values of \c *this and \a other.
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* Overloaded for performance: this version performs a \em shallow swap by swaping pointers and attributes only.
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* \sa SparseMatrixBase::swap()
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*/
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inline void swap(SparseVector& other)
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{
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std::swap(m_size, other.m_size);
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m_data.swap(other.m_data);
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}
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inline SparseVector& operator=(const SparseVector& other)
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{
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if (other.isRValue())
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{
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swap(other.const_cast_derived());
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}
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else
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{
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resize(other.size());
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m_data = other.m_data;
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}
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return *this;
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}
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template<typename OtherDerived>
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inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other)
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{
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SparseVector tmp(other.size());
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internal::sparse_vector_assign_selector<SparseVector,OtherDerived>::run(tmp,other.derived());
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this->swap(tmp);
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return *this;
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}
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#ifndef EIGEN_PARSED_BY_DOXYGEN
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template<typename Lhs, typename Rhs>
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inline SparseVector& operator=(const SparseSparseProduct<Lhs,Rhs>& product)
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{
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return Base::operator=(product);
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}
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#endif
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friend std::ostream & operator << (std::ostream & s, const SparseVector& m)
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{
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for (Index i=0; i<m.nonZeros(); ++i)
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s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
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s << std::endl;
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return s;
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}
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/** Destructor */
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inline ~SparseVector() {}
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/** Overloaded for performance */
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Scalar sum() const;
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public:
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/** \internal \deprecated use setZero() and reserve() */
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EIGEN_DEPRECATED void startFill(Index reserve)
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{
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setZero();
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m_data.reserve(reserve);
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}
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/** \internal \deprecated use insertBack(Index,Index) */
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EIGEN_DEPRECATED Scalar& fill(Index r, Index c)
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{
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eigen_assert(r==0 || c==0);
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return fill(IsColVector ? r : c);
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}
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/** \internal \deprecated use insertBack(Index) */
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EIGEN_DEPRECATED Scalar& fill(Index i)
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{
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m_data.append(0, i);
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return m_data.value(m_data.size()-1);
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}
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/** \internal \deprecated use insert(Index,Index) */
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EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c)
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{
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eigen_assert(r==0 || c==0);
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return fillrand(IsColVector ? r : c);
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}
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/** \internal \deprecated use insert(Index) */
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EIGEN_DEPRECATED Scalar& fillrand(Index i)
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{
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return insert(i);
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}
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/** \internal \deprecated use finalize() */
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EIGEN_DEPRECATED void endFill() {}
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// These two functions were here in the 3.1 release, so let's keep them in case some code rely on them.
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/** \internal \deprecated use data() */
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EIGEN_DEPRECATED Storage& _data() { return m_data; }
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/** \internal \deprecated use data() */
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EIGEN_DEPRECATED const Storage& _data() const { return m_data; }
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# ifdef EIGEN_SPARSEVECTOR_PLUGIN
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# include EIGEN_SPARSEVECTOR_PLUGIN
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# endif
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protected:
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static void check_template_parameters()
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{
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EIGEN_STATIC_ASSERT(NumTraits<Index>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE);
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EIGEN_STATIC_ASSERT((_Options&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS);
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}
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Storage m_data;
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Index m_size;
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};
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template<typename Scalar, int _Options, typename _Index>
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class SparseVector<Scalar,_Options,_Index>::InnerIterator
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{
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public:
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explicit InnerIterator(const SparseVector& vec, Index outer=0)
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: m_data(vec.m_data), m_id(0), m_end(static_cast<Index>(m_data.size()))
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{
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EIGEN_UNUSED_VARIABLE(outer);
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eigen_assert(outer==0);
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}
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explicit InnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
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: m_data(data), m_id(0), m_end(static_cast<Index>(m_data.size()))
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{}
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inline InnerIterator& operator++() { m_id++; return *this; }
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inline Scalar value() const { return m_data.value(m_id); }
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inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id)); }
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inline Index index() const { return m_data.index(m_id); }
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inline Index row() const { return IsColVector ? index() : 0; }
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inline Index col() const { return IsColVector ? 0 : index(); }
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inline operator bool() const { return (m_id < m_end); }
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protected:
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const internal::CompressedStorage<Scalar,Index>& m_data;
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Index m_id;
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const Index m_end;
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private:
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// If you get here, then you're not using the right InnerIterator type, e.g.:
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// SparseMatrix<double,RowMajor> A;
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// SparseMatrix<double>::InnerIterator it(A,0);
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template<typename T> InnerIterator(const SparseMatrixBase<T>&,Index outer=0);
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};
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template<typename Scalar, int _Options, typename _Index>
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class SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator
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{
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public:
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explicit ReverseInnerIterator(const SparseVector& vec, Index outer=0)
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: m_data(vec.m_data), m_id(static_cast<Index>(m_data.size())), m_start(0)
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{
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EIGEN_UNUSED_VARIABLE(outer);
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eigen_assert(outer==0);
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}
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explicit ReverseInnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
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: m_data(data), m_id(static_cast<Index>(m_data.size())), m_start(0)
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{}
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inline ReverseInnerIterator& operator--() { m_id--; return *this; }
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inline Scalar value() const { return m_data.value(m_id-1); }
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inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id-1)); }
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inline Index index() const { return m_data.index(m_id-1); }
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inline Index row() const { return IsColVector ? index() : 0; }
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inline Index col() const { return IsColVector ? 0 : index(); }
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inline operator bool() const { return (m_id > m_start); }
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protected:
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const internal::CompressedStorage<Scalar,Index>& m_data;
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Index m_id;
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const Index m_start;
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};
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namespace internal {
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template<typename _Scalar, int _Options, typename _Index>
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struct evaluator<SparseVector<_Scalar,_Options,_Index> >
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: evaluator_base<SparseVector<_Scalar,_Options,_Index> >
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{
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typedef SparseVector<_Scalar,_Options,_Index> SparseVectorType;
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typedef typename SparseVectorType::InnerIterator InnerIterator;
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typedef typename SparseVectorType::ReverseInnerIterator ReverseInnerIterator;
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enum {
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CoeffReadCost = NumTraits<_Scalar>::ReadCost,
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Flags = SparseVectorType::Flags
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};
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explicit evaluator(const SparseVectorType &mat) : m_matrix(mat) {}
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operator SparseVectorType&() { return m_matrix.const_cast_derived(); }
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operator const SparseVectorType&() const { return m_matrix; }
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const SparseVectorType &m_matrix;
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};
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template< typename Dest, typename Src>
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struct sparse_vector_assign_selector<Dest,Src,SVA_Inner> {
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static void run(Dest& dst, const Src& src) {
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eigen_internal_assert(src.innerSize()==src.size());
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typedef typename internal::evaluator<Src>::type SrcEvaluatorType;
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SrcEvaluatorType srcEval(src);
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for(typename SrcEvaluatorType::InnerIterator it(srcEval, 0); it; ++it)
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dst.insert(it.index()) = it.value();
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}
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};
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template< typename Dest, typename Src>
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struct sparse_vector_assign_selector<Dest,Src,SVA_Outer> {
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static void run(Dest& dst, const Src& src) {
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eigen_internal_assert(src.outerSize()==src.size());
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typedef typename internal::evaluator<Src>::type SrcEvaluatorType;
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SrcEvaluatorType srcEval(src);
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for(typename Dest::Index i=0; i<src.size(); ++i)
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{
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typename SrcEvaluatorType::InnerIterator it(srcEval, i);
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if(it)
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dst.insert(i) = it.value();
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}
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}
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};
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template< typename Dest, typename Src>
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struct sparse_vector_assign_selector<Dest,Src,SVA_RuntimeSwitch> {
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static void run(Dest& dst, const Src& src) {
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if(src.outerSize()==1) sparse_vector_assign_selector<Dest,Src,SVA_Inner>::run(dst, src);
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else sparse_vector_assign_selector<Dest,Src,SVA_Outer>::run(dst, src);
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}
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};
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}
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} // end namespace Eigen
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#endif // EIGEN_SPARSEVECTOR_H
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