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move sparse solvers from unsupported/ to main Eigen/ and remove the "not stable yet" warning
This commit is contained in:
Gael Guennebaud
431
Eigen/src/SparseCore/SparseVector.h
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431
Eigen/src/SparseCore/SparseVector.h
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// 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) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.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_SPARSEVECTOR_H
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#define EIGEN_SPARSEVECTOR_H
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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,
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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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}
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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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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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// EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, =)
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protected:
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public:
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typedef SparseMatrixBase<SparseVector> SparseBase;
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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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CompressedStorage<Scalar,Index> m_data;
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Index m_size;
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CompressedStorage<Scalar,Index>& _data() { return m_data; }
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CompressedStorage<Scalar,Index>& _data() const { return m_data; }
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public:
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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 Index innerNonZeros(Index j) const { eigen_assert(j==0); return m_size; }
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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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inline Scalar coeff(Index row, Index col) const
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{
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eigen_assert((IsColVector ? col : row)==0);
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return coeff(IsColVector ? row : col);
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}
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inline Scalar coeff(Index i) const { return m_data.at(i); }
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inline Scalar& coeffRef(Index row, Index col)
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{
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eigen_assert((IsColVector ? col : row)==0);
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return coeff(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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return m_data.atWithInsertion(i);
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}
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public:
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class InnerIterator;
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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_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_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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inline Scalar& insert(Index row, Index col)
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{
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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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Index startId = 0;
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Index p = 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(Scalar reference, 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) { resize(0); }
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inline SparseVector(Index size) : m_size(0) { resize(size); }
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inline SparseVector(Index rows, Index cols) : m_size(0) { resize(rows,cols); }
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template<typename OtherDerived>
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inline SparseVector(const MatrixBase<OtherDerived>& other)
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: m_size(0)
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{
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*this = other.derived();
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}
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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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*this = other.derived();
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}
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inline SparseVector(const SparseVector& other)
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: m_size(0)
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{
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*this = other.derived();
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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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if (int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime))
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return Base::operator=(other.transpose());
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else
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return Base::operator=(other);
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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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// const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
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// if (needToTranspose)
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// {
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// // two passes algorithm:
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// // 1 - compute the number of coeffs per dest inner vector
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// // 2 - do the actual copy/eval
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// // Since each coeff of the rhs has to be evaluated twice, let's evauluate it if needed
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// typedef typename internal::nested<OtherDerived,2>::type OtherCopy;
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// OtherCopy otherCopy(other.derived());
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// typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
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//
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// resize(other.rows(), other.cols());
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// Eigen::Map<VectorXi>(m_outerIndex,outerSize()).setZero();
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// // pass 1
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// // FIXME the above copy could be merged with that pass
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// for (int j=0; j<otherCopy.outerSize(); ++j)
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// for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
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// ++m_outerIndex[it.index()];
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//
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// // prefix sum
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// int count = 0;
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// VectorXi positions(outerSize());
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// for (int j=0; j<outerSize(); ++j)
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// {
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// int tmp = m_outerIndex[j];
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// m_outerIndex[j] = count;
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// positions[j] = count;
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// count += tmp;
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// }
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// m_outerIndex[outerSize()] = count;
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// // alloc
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// m_data.resize(count);
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// // pass 2
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// for (int j=0; j<otherCopy.outerSize(); ++j)
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// for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
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// {
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// int pos = positions[it.index()]++;
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// m_data.index(pos) = j;
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// m_data.value(pos) = it.value();
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// }
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//
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// return *this;
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// }
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// else
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// {
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// // there is no special optimization
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// return SparseMatrixBase<SparseMatrix>::operator=(other.derived());
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// }
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// }
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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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// this specialized version does not seems to be faster
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// Scalar dot(const SparseVector& other) const
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// {
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// int i=0, j=0;
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// Scalar res = 0;
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// asm("#begindot");
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// while (i<nonZeros() && j<other.nonZeros())
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// {
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// if (m_data.index(i)==other.m_data.index(j))
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// {
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// res += m_data.value(i) * internal::conj(other.m_data.value(j));
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// ++i; ++j;
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// }
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// else if (m_data.index(i)<other.m_data.index(j))
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// ++i;
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// else
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// ++j;
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// }
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// asm("#enddot");
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// return res;
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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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/** \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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/** \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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/** \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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/** \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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/** \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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/** \deprecated use finalize() */
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EIGEN_DEPRECATED void endFill() {}
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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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};
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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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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_assert(outer==0);
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}
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InnerIterator(const 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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template<unsigned int Added, unsigned int Removed>
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InnerIterator(const Flagged<SparseVector,Added,Removed>& vec, Index )
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: m_data(vec._expression().m_data), m_id(0), m_end(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 CompressedStorage<Scalar,Index>& m_data;
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Index m_id;
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const Index m_end;
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};
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#endif // EIGEN_SPARSEVECTOR_H
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