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Diffstat (limited to 'extern/Eigen2/Eigen/src/Sparse/SparseVector.h')
| -rw-r--r-- | extern/Eigen2/Eigen/src/Sparse/SparseVector.h | 365 |
1 files changed, 365 insertions, 0 deletions
diff --git a/extern/Eigen2/Eigen/src/Sparse/SparseVector.h b/extern/Eigen2/Eigen/src/Sparse/SparseVector.h new file mode 100644 index 00000000000..8e5a6efeda8 --- /dev/null +++ b/extern/Eigen2/Eigen/src/Sparse/SparseVector.h @@ -0,0 +1,365 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. Eigen itself is part of the KDE project. +// +// Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.fr> +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see <http://www.gnu.org/licenses/>. + +#ifndef EIGEN_SPARSEVECTOR_H +#define EIGEN_SPARSEVECTOR_H + +/** \class SparseVector + * + * \brief a sparse vector class + * + * \param _Scalar the scalar type, i.e. the type of the coefficients + * + * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme. + * + */ +template<typename _Scalar, int _Flags> +struct ei_traits<SparseVector<_Scalar, _Flags> > +{ + typedef _Scalar Scalar; + enum { + IsColVector = _Flags & RowMajorBit ? 0 : 1, + + RowsAtCompileTime = IsColVector ? Dynamic : 1, + ColsAtCompileTime = IsColVector ? 1 : Dynamic, + MaxRowsAtCompileTime = RowsAtCompileTime, + MaxColsAtCompileTime = ColsAtCompileTime, + Flags = SparseBit | _Flags, + CoeffReadCost = NumTraits<Scalar>::ReadCost, + SupportedAccessPatterns = InnerRandomAccessPattern + }; +}; + +template<typename _Scalar, int _Flags> +class SparseVector + : public SparseMatrixBase<SparseVector<_Scalar, _Flags> > +{ + public: + EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseVector) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=) +// EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, =) + + protected: + public: + + typedef SparseMatrixBase<SparseVector> SparseBase; + enum { IsColVector = ei_traits<SparseVector>::IsColVector }; + + CompressedStorage<Scalar> m_data; + int m_size; + + CompressedStorage<Scalar>& _data() { return m_data; } + CompressedStorage<Scalar>& _data() const { return m_data; } + + public: + + EIGEN_STRONG_INLINE int rows() const { return IsColVector ? m_size : 1; } + EIGEN_STRONG_INLINE int cols() const { return IsColVector ? 1 : m_size; } + EIGEN_STRONG_INLINE int innerSize() const { return m_size; } + EIGEN_STRONG_INLINE int outerSize() const { return 1; } + EIGEN_STRONG_INLINE int innerNonZeros(int j) const { ei_assert(j==0); return m_size; } + + EIGEN_STRONG_INLINE const Scalar* _valuePtr() const { return &m_data.value(0); } + EIGEN_STRONG_INLINE Scalar* _valuePtr() { return &m_data.value(0); } + + EIGEN_STRONG_INLINE const int* _innerIndexPtr() const { return &m_data.index(0); } + EIGEN_STRONG_INLINE int* _innerIndexPtr() { return &m_data.index(0); } + + inline Scalar coeff(int row, int col) const + { + ei_assert((IsColVector ? col : row)==0); + return coeff(IsColVector ? row : col); + } + inline Scalar coeff(int i) const { return m_data.at(i); } + + inline Scalar& coeffRef(int row, int col) + { + ei_assert((IsColVector ? col : row)==0); + return coeff(IsColVector ? row : col); + } + + /** \returns a reference to the coefficient value at given index \a i + * This operation involes a log(rho*size) binary search. If the coefficient does not + * exist yet, then a sorted insertion into a sequential buffer is performed. + * + * This insertion might be very costly if the number of nonzeros above \a i is large. + */ + inline Scalar& coeffRef(int i) + { + return m_data.atWithInsertion(i); + } + + public: + + class InnerIterator; + + inline void setZero() { m_data.clear(); } + + /** \returns the number of non zero coefficients */ + inline int nonZeros() const { return m_data.size(); } + + /** + */ + inline void reserve(int reserveSize) { m_data.reserve(reserveSize); } + + inline void startFill(int reserve) + { + setZero(); + m_data.reserve(reserve); + } + + /** + */ + inline Scalar& fill(int r, int c) + { + ei_assert(r==0 || c==0); + return fill(IsColVector ? r : c); + } + + inline Scalar& fill(int i) + { + m_data.append(0, i); + return m_data.value(m_data.size()-1); + } + + inline Scalar& fillrand(int r, int c) + { + ei_assert(r==0 || c==0); + return fillrand(IsColVector ? r : c); + } + + /** Like fill() but with random coordinates. + */ + inline Scalar& fillrand(int i) + { + int startId = 0; + int id = m_data.size() - 1; + m_data.resize(id+2,1); + + while ( (id >= startId) && (m_data.index(id) > i) ) + { + m_data.index(id+1) = m_data.index(id); + m_data.value(id+1) = m_data.value(id); + --id; + } + m_data.index(id+1) = i; + m_data.value(id+1) = 0; + return m_data.value(id+1); + } + + inline void endFill() {} + + void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>()) + { + m_data.prune(reference,epsilon); + } + + void resize(int rows, int cols) + { + ei_assert(rows==1 || cols==1); + resize(IsColVector ? rows : cols); + } + + void resize(int newSize) + { + m_size = newSize; + m_data.clear(); + } + + void resizeNonZeros(int size) { m_data.resize(size); } + + inline SparseVector() : m_size(0) { resize(0); } + + inline SparseVector(int size) : m_size(0) { resize(size); } + + inline SparseVector(int rows, int cols) : m_size(0) { resize(rows,cols); } + + template<typename OtherDerived> + inline SparseVector(const MatrixBase<OtherDerived>& other) + : m_size(0) + { + *this = other.derived(); + } + + template<typename OtherDerived> + inline SparseVector(const SparseMatrixBase<OtherDerived>& other) + : m_size(0) + { + *this = other.derived(); + } + + inline SparseVector(const SparseVector& other) + : m_size(0) + { + *this = other.derived(); + } + + inline void swap(SparseVector& other) + { + std::swap(m_size, other.m_size); + m_data.swap(other.m_data); + } + + inline SparseVector& operator=(const SparseVector& other) + { + if (other.isRValue()) + { + swap(other.const_cast_derived()); + } + else + { + resize(other.size()); + m_data = other.m_data; + } + return *this; + } + + template<typename OtherDerived> + inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other) + { + return Base::operator=(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 evauluate it if needed +// typedef typename ei_nested<OtherDerived,2>::type OtherCopy; +// OtherCopy otherCopy(other.derived()); +// typedef typename ei_cleantype<OtherCopy>::type _OtherCopy; +// +// resize(other.rows(), other.cols()); +// Eigen::Map<VectorXi>(m_outerIndex,outerSize()).setZero(); +// // pass 1 +// // FIXME the above copy could be merged with that pass +// for (int j=0; j<otherCopy.outerSize(); ++j) +// for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it) +// ++m_outerIndex[it.index()]; +// +// // prefix sum +// int count = 0; +// VectorXi positions(outerSize()); +// for (int j=0; j<outerSize(); ++j) +// { +// int tmp = m_outerIndex[j]; +// m_outerIndex[j] = count; +// positions[j] = count; +// count += tmp; +// } +// m_outerIndex[outerSize()] = count; +// // alloc +// m_data.resize(count); +// // pass 2 +// for (int j=0; j<otherCopy.outerSize(); ++j) +// for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it) +// { +// int pos = positions[it.index()]++; +// m_data.index(pos) = j; +// m_data.value(pos) = it.value(); +// } +// +// return *this; +// } +// else +// { +// // there is no special optimization +// return SparseMatrixBase<SparseMatrix>::operator=(other.derived()); +// } +// } + + friend std::ostream & operator << (std::ostream & s, const SparseVector& m) + { + for (unsigned int i=0; i<m.nonZeros(); ++i) + s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") "; + s << std::endl; + return s; + } + + // this specialized version does not seems to be faster +// Scalar dot(const SparseVector& other) const +// { +// int i=0, j=0; +// Scalar res = 0; +// asm("#begindot"); +// while (i<nonZeros() && j<other.nonZeros()) +// { +// if (m_data.index(i)==other.m_data.index(j)) +// { +// res += m_data.value(i) * ei_conj(other.m_data.value(j)); +// ++i; ++j; +// } +// else if (m_data.index(i)<other.m_data.index(j)) +// ++i; +// else +// ++j; +// } +// asm("#enddot"); +// return res; +// } + + /** Destructor */ + inline ~SparseVector() {} +}; + +template<typename Scalar, int _Flags> +class SparseVector<Scalar,_Flags>::InnerIterator +{ + public: + InnerIterator(const SparseVector& vec, int outer=0) + : m_data(vec.m_data), m_id(0), m_end(m_data.size()) + { + ei_assert(outer==0); + } + + InnerIterator(const CompressedStorage<Scalar>& data) + : m_data(data), m_id(0), m_end(m_data.size()) + {} + + template<unsigned int Added, unsigned int Removed> + InnerIterator(const Flagged<SparseVector,Added,Removed>& vec, int outer) + : m_data(vec._expression().m_data), m_id(0), m_end(m_data.size()) + {} + + inline InnerIterator& operator++() { m_id++; return *this; } + + inline Scalar value() const { return m_data.value(m_id); } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id)); } + + inline int index() const { return m_data.index(m_id); } + inline int row() const { return IsColVector ? index() : 0; } + inline int col() const { return IsColVector ? 0 : index(); } + + inline operator bool() const { return (m_id < m_end); } + + protected: + const CompressedStorage<Scalar>& m_data; + int m_id; + const int m_end; +}; + +#endif // EIGEN_SPARSEVECTOR_H |