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various work on the Sparse module:
* added some glue to Eigen/Core (SparseBit, ei_eval, Matrix)
* add two new sparse matrix types:
HashMatrix: based on std::map (for random writes)
LinkedVectorMatrix: array of linked vectors
(for outer coherent writes, e.g. to transpose a matrix)
* add a SparseSetter class to easily set/update any kind of matrices, e.g.:
{ SparseSetter<MatrixType,RandomAccessPattern> wrapper(mymatrix);
for (...) wrapper->coeffRef(rand(),rand()) = rand(); }
* automatic shallow copy for RValue
* and a lot of mess !
plus:
* remove the remaining ArrayBit related stuff
* don't use alloca in product for very large memory allocation
This commit is contained in:
288
Eigen/src/Sparse/LinkedVectorMatrix.h
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288
Eigen/src/Sparse/LinkedVectorMatrix.h
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_LINKEDVECTORMATRIX_H
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#define EIGEN_LINKEDVECTORMATRIX_H
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template<typename _Scalar, int _Flags>
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struct ei_traits<LinkedVectorMatrix<_Scalar,_Flags> >
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{
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typedef _Scalar Scalar;
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enum {
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RowsAtCompileTime = Dynamic,
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ColsAtCompileTime = Dynamic,
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MaxRowsAtCompileTime = Dynamic,
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MaxColsAtCompileTime = Dynamic,
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Flags = _Flags,
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CoeffReadCost = NumTraits<Scalar>::ReadCost,
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SupportedAccessPatterns = InnerCoherentAccessPattern
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};
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};
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template<typename Element, int BlockSize = 8>
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struct LinkedVector
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{
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LinkedVector() : size(0), next(0), prev(0) {}
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Element data[BlockSize];
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LinkedVector* next;
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LinkedVector* prev;
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int size;
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bool isFull() const { return size==BlockSize; }
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};
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template<typename _Scalar, int _Flags>
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class LinkedVectorMatrix : public SparseMatrixBase<LinkedVectorMatrix<_Scalar,_Flags> >
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{
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public:
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EIGEN_GENERIC_PUBLIC_INTERFACE(LinkedVectorMatrix)
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class InnerIterator;
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protected:
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enum {
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RowMajor = Flags&RowMajorBit ? 1 : 0
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};
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struct ValueIndex
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{
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ValueIndex() : value(0), index(0) {}
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ValueIndex(Scalar v, int i) : value(v), index(i) {}
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Scalar value;
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int index;
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};
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typedef LinkedVector<ValueIndex,8> LinkedVectorBlock;
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inline int find(LinkedVectorBlock** _el, int id)
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{
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LinkedVectorBlock* el = *_el;
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while (el && el->data[el->size-1].index<id)
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el = el->next;
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*_el = el;
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if (el)
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{
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// binary search
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int maxI = el->size-1;
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int minI = 0;
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int i = el->size/2;
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const ValueIndex* data = el->data;
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while (data[i].index!=id)
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{
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if (data[i].index<id)
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{
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minI = i+1;
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i = (maxI + minI)+2;
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}
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else
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{
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maxI = i-1;
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i = (maxI + minI)+2;
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}
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if (minI>=maxI)
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return -1;
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}
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if (data[i].index==id)
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return i;
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}
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return -1;
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}
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public:
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inline int rows() const { return RowMajor ? m_data.size() : m_innerSize; }
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inline int cols() const { return RowMajor ? m_innerSize : m_data.size(); }
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inline const Scalar& coeff(int row, int col) const
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{
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const int outer = RowMajor ? row : col;
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const int inner = RowMajor ? col : row;
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LinkedVectorBlock* el = m_data[outer];
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int id = find(&el, inner);
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if (id<0)
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return Scalar(0);
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return el->data[id].value;
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}
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inline Scalar& coeffRef(int row, int col)
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{
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const int outer = RowMajor ? row : col;
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const int inner = RowMajor ? col : row;
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LinkedVectorBlock* el = m_data[outer];
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int id = find(&el, inner);
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ei_assert(id>=0);
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// if (id<0)
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// return Scalar(0);
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return el->data[id].value;
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}
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public:
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inline void startFill(int reserveSize = 1000)
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{
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clear();
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for (int i=0; i<m_data.size(); ++i)
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m_ends[i] = m_data[i] = 0;
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}
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inline Scalar& fill(int row, int col)
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{
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const int outer = RowMajor ? row : col;
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const int inner = RowMajor ? col : row;
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if (m_ends[outer]==0)
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{
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m_data[outer] = m_ends[outer] = new LinkedVectorBlock();
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}
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else
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{
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ei_assert(m_ends[outer]->data[m_ends[outer]->size-1].index < inner);
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if (m_ends[outer]->isFull())
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{
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LinkedVectorBlock* el = new LinkedVectorBlock();
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m_ends[outer]->next = el;
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el->prev = m_ends[outer];
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m_ends[outer] = el;
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}
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}
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m_ends[outer]->data[m_ends[outer]->size].index = inner;
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return m_ends[outer]->data[m_ends[outer]->size++].value;
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}
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inline void endFill()
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{
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}
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~LinkedVectorMatrix()
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{
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if (this->isNotShared())
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clear();
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}
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void clear()
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{
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for (int i=0; i<m_data.size(); ++i)
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{
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LinkedVectorBlock* el = m_data[i];
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while (el)
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{
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LinkedVectorBlock* tmp = el;
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el = el->next;
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delete tmp;
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}
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}
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}
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void resize(int rows, int cols)
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{
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const int outers = RowMajor ? rows : cols;
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const int inners = RowMajor ? cols : rows;
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if (this->outerSize() != outers)
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{
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clear();
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m_data.resize(outers);
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m_ends.resize(outers);
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for (int i=0; i<m_data.size(); ++i)
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m_ends[i] = m_data[i] = 0;
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}
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m_innerSize = inners;
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}
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inline LinkedVectorMatrix(int rows, int cols)
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: m_innerSize(0)
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{
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resize(rows, cols);
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}
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template<typename OtherDerived>
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inline LinkedVectorMatrix(const MatrixBase<OtherDerived>& other)
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: m_innerSize(0)
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{
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*this = other.derived();
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}
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inline void shallowCopy(const LinkedVectorMatrix& other)
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{
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EIGEN_DBG_SPARSE(std::cout << "LinkedVectorMatrix:: shallowCopy\n");
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resize(other.rows(), other.cols());
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for (int j=0; j<this->outerSize(); ++j)
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{
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m_data[j] = other.m_data[j];
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m_ends[j] = other.m_ends[j];
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}
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other.markAsCopied();
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}
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inline LinkedVectorMatrix& operator=(const LinkedVectorMatrix& other)
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{
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if (other.isRValue())
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{
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shallowCopy(other);
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return *this;
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}
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else
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{
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// TODO implement a specialized deep copy here
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return operator=<LinkedVectorMatrix>(other);
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}
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}
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template<typename OtherDerived>
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inline LinkedVectorMatrix& operator=(const MatrixBase<OtherDerived>& other)
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{
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return SparseMatrixBase<LinkedVectorMatrix>::operator=(other.derived());
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}
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protected:
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std::vector<LinkedVectorBlock*> m_data;
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std::vector<LinkedVectorBlock*> m_ends;
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int m_innerSize;
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};
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template<typename Scalar, int _Flags>
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class LinkedVectorMatrix<Scalar,_Flags>::InnerIterator
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{
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public:
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InnerIterator(const LinkedVectorMatrix& mat, int col)
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: m_matrix(mat), m_el(mat.m_data[col]), m_it(0)
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{}
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InnerIterator& operator++() { if (m_it<m_el->size) m_it++; else {m_el = m_el->next; m_it=0;}; return *this; }
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Scalar value() { return m_el->data[m_it].value; }
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int index() const { return m_el->data[m_it].index; }
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operator bool() const { return m_el && (m_el->next || m_it<m_el->size); }
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protected:
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const LinkedVectorMatrix& m_matrix;
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LinkedVectorBlock* m_el;
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int m_it;
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};
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#endif // EIGEN_LINKEDVECTORMATRIX_H
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