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Diffstat (limited to 'extern/Eigen2/Eigen/src/Sparse/SparseMatrix.h')
-rw-r--r-- | extern/Eigen2/Eigen/src/Sparse/SparseMatrix.h | 447 |
1 files changed, 447 insertions, 0 deletions
diff --git a/extern/Eigen2/Eigen/src/Sparse/SparseMatrix.h b/extern/Eigen2/Eigen/src/Sparse/SparseMatrix.h new file mode 100644 index 00000000000..3f09596bc64 --- /dev/null +++ b/extern/Eigen2/Eigen/src/Sparse/SparseMatrix.h @@ -0,0 +1,447 @@ +// 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_SPARSEMATRIX_H +#define EIGEN_SPARSEMATRIX_H + +/** \class SparseMatrix + * + * \brief Sparse matrix + * + * \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<SparseMatrix<_Scalar, _Flags> > +{ + typedef _Scalar Scalar; + enum { + RowsAtCompileTime = Dynamic, + ColsAtCompileTime = Dynamic, + MaxRowsAtCompileTime = Dynamic, + MaxColsAtCompileTime = Dynamic, + Flags = SparseBit | _Flags, + CoeffReadCost = NumTraits<Scalar>::ReadCost, + SupportedAccessPatterns = InnerRandomAccessPattern + }; +}; + + + +template<typename _Scalar, int _Flags> +class SparseMatrix + : public SparseMatrixBase<SparseMatrix<_Scalar, _Flags> > +{ + public: + EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseMatrix) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, +=) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, -=) + // FIXME: why are these operator already alvailable ??? + // EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(SparseMatrix, *=) + // EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(SparseMatrix, /=) + + typedef MappedSparseMatrix<Scalar,Flags> Map; + + protected: + + enum { IsRowMajor = Base::IsRowMajor }; + typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix; + + int m_outerSize; + int m_innerSize; + int* m_outerIndex; + CompressedStorage<Scalar> m_data; + + public: + + inline int rows() const { return IsRowMajor ? m_outerSize : m_innerSize; } + inline int cols() const { return IsRowMajor ? m_innerSize : m_outerSize; } + + inline int innerSize() const { return m_innerSize; } + inline int outerSize() const { return m_outerSize; } + inline int innerNonZeros(int j) const { return m_outerIndex[j+1]-m_outerIndex[j]; } + + inline const Scalar* _valuePtr() const { return &m_data.value(0); } + inline Scalar* _valuePtr() { return &m_data.value(0); } + + inline const int* _innerIndexPtr() const { return &m_data.index(0); } + inline int* _innerIndexPtr() { return &m_data.index(0); } + + inline const int* _outerIndexPtr() const { return m_outerIndex; } + inline int* _outerIndexPtr() { return m_outerIndex; } + + inline Scalar coeff(int row, int col) const + { + const int outer = IsRowMajor ? row : col; + const int inner = IsRowMajor ? col : row; + return m_data.atInRange(m_outerIndex[outer], m_outerIndex[outer+1], inner); + } + + inline Scalar& coeffRef(int row, int col) + { + const int outer = IsRowMajor ? row : col; + const int inner = IsRowMajor ? col : row; + + int start = m_outerIndex[outer]; + int end = m_outerIndex[outer+1]; + ei_assert(end>=start && "you probably called coeffRef on a non finalized matrix"); + ei_assert(end>start && "coeffRef cannot be called on a zero coefficient"); + const int id = m_data.searchLowerIndex(start,end-1,inner); + ei_assert((id<end) && (m_data.index(id)==inner) && "coeffRef cannot be called on a zero coefficient"); + return m_data.value(id); + } + + public: + + class InnerIterator; + + inline void setZero() + { + m_data.clear(); + //if (m_outerSize) + memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(int)); +// for (int i=0; i<m_outerSize; ++i) +// m_outerIndex[i] = 0; +// if (m_outerSize) +// m_outerIndex[i] = 0; + } + + /** \returns the number of non zero coefficients */ + inline int nonZeros() const { return m_data.size(); } + + /** Initializes the filling process of \c *this. + * \param reserveSize approximate number of nonzeros + * Note that the matrix \c *this is zero-ed. + */ + inline void startFill(int reserveSize = 1000) + { + setZero(); + m_data.reserve(reserveSize); + } + + /** + */ + inline Scalar& fill(int row, int col) + { + const int outer = IsRowMajor ? row : col; + const int inner = IsRowMajor ? col : row; + + if (m_outerIndex[outer+1]==0) + { + // we start a new inner vector + int i = outer; + while (i>=0 && m_outerIndex[i]==0) + { + m_outerIndex[i] = m_data.size(); + --i; + } + m_outerIndex[outer+1] = m_outerIndex[outer]; + } + else + { + ei_assert(m_data.index(m_data.size()-1)<inner && "wrong sorted insertion"); + } + assert(size_t(m_outerIndex[outer+1]) == m_data.size()); + int id = m_outerIndex[outer+1]; + ++m_outerIndex[outer+1]; + + m_data.append(0, inner); + return m_data.value(id); + } + + /** Like fill() but with random inner coordinates. + */ + inline Scalar& fillrand(int row, int col) + { + const int outer = IsRowMajor ? row : col; + const int inner = IsRowMajor ? col : row; + if (m_outerIndex[outer+1]==0) + { + // we start a new inner vector + // nothing special to do here + int i = outer; + while (i>=0 && m_outerIndex[i]==0) + { + m_outerIndex[i] = m_data.size(); + --i; + } + m_outerIndex[outer+1] = m_outerIndex[outer]; + } + assert(size_t(m_outerIndex[outer+1]) == m_data.size() && "invalid outer index"); + size_t startId = m_outerIndex[outer]; + // FIXME let's make sure sizeof(long int) == sizeof(size_t) + size_t id = m_outerIndex[outer+1]; + ++m_outerIndex[outer+1]; + + float reallocRatio = 1; + if (m_data.allocatedSize()<id+1) + { + // we need to reallocate the data, to reduce multiple reallocations + // we use a smart resize algorithm based on the current filling ratio + // we use float to avoid overflows + float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer); + reallocRatio = (nnzEstimate-float(m_data.size()))/float(m_data.size()); + // let's bounds the realloc ratio to + // 1) reduce multiple minor realloc when the matrix is almost filled + // 2) avoid to allocate too much memory when the matrix is almost empty + reallocRatio = std::min(std::max(reallocRatio,1.5f),8.f); + } + m_data.resize(id+1,reallocRatio); + + while ( (id > startId) && (m_data.index(id-1) > inner) ) + { + m_data.index(id) = m_data.index(id-1); + m_data.value(id) = m_data.value(id-1); + --id; + } + + m_data.index(id) = inner; + return (m_data.value(id) = 0); + } + + inline void endFill() + { + int size = m_data.size(); + int i = m_outerSize; + // find the last filled column + while (i>=0 && m_outerIndex[i]==0) + --i; + ++i; + while (i<=m_outerSize) + { + m_outerIndex[i] = size; + ++i; + } + } + + void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>()) + { + int k = 0; + for (int j=0; j<m_outerSize; ++j) + { + int previousStart = m_outerIndex[j]; + m_outerIndex[j] = k; + int end = m_outerIndex[j+1]; + for (int i=previousStart; i<end; ++i) + { + if (!ei_isMuchSmallerThan(m_data.value(i), reference, epsilon)) + { + m_data.value(k) = m_data.value(i); + m_data.index(k) = m_data.index(i); + ++k; + } + } + } + m_outerIndex[m_outerSize] = k; + m_data.resize(k,0); + } + + void resize(int rows, int cols) + { +// std::cerr << this << " resize " << rows << "x" << cols << "\n"; + const int outerSize = IsRowMajor ? rows : cols; + m_innerSize = IsRowMajor ? cols : rows; + m_data.clear(); + if (m_outerSize != outerSize) + { + delete[] m_outerIndex; + m_outerIndex = new int [outerSize+1]; + m_outerSize = outerSize; + memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(int)); + } + } + void resizeNonZeros(int size) + { + m_data.resize(size); + } + + inline SparseMatrix() + : m_outerSize(-1), m_innerSize(0), m_outerIndex(0) + { + resize(0, 0); + } + + inline SparseMatrix(int rows, int cols) + : m_outerSize(0), m_innerSize(0), m_outerIndex(0) + { + resize(rows, cols); + } + + template<typename OtherDerived> + inline SparseMatrix(const SparseMatrixBase<OtherDerived>& other) + : m_outerSize(0), m_innerSize(0), m_outerIndex(0) + { + *this = other.derived(); + } + + inline SparseMatrix(const SparseMatrix& other) + : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0) + { + *this = other.derived(); + } + + inline void swap(SparseMatrix& other) + { + //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n"); + std::swap(m_outerIndex, other.m_outerIndex); + std::swap(m_innerSize, other.m_innerSize); + std::swap(m_outerSize, other.m_outerSize); + m_data.swap(other.m_data); + } + + inline SparseMatrix& operator=(const SparseMatrix& other) + { +// std::cout << "SparseMatrix& operator=(const SparseMatrix& other)\n"; + if (other.isRValue()) + { + swap(other.const_cast_derived()); + } + else + { + resize(other.rows(), other.cols()); + memcpy(m_outerIndex, other.m_outerIndex, (m_outerSize+1)*sizeof(int)); + m_data = other.m_data; + } + return *this; + } + + template<typename OtherDerived> + inline SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other) + { + const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); + if (needToTranspose) + { + // two passes algorithm: + // 1 - compute the number of coeffs per dest inner vector + // 2 - do the actual copy/eval + // Since each coeff of the rhs has to be evaluated twice, let's evauluate it if needed + //typedef typename ei_nested<OtherDerived,2>::type OtherCopy; + typedef typename ei_eval<OtherDerived>::type OtherCopy; + typedef typename ei_cleantype<OtherCopy>::type _OtherCopy; + OtherCopy otherCopy(other.derived()); + + 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 SparseMatrix& m) + { + EIGEN_DBG_SPARSE( + s << "Nonzero entries:\n"; + for (int i=0; i<m.nonZeros(); ++i) + { + s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") "; + } + s << std::endl; + s << std::endl; + s << "Column pointers:\n"; + for (int i=0; i<m.outerSize(); ++i) + { + s << m.m_outerIndex[i] << " "; + } + s << " $" << std::endl; + s << std::endl; + ); + s << static_cast<const SparseMatrixBase<SparseMatrix>&>(m); + return s; + } + + /** Destructor */ + inline ~SparseMatrix() + { + delete[] m_outerIndex; + } +}; + +template<typename Scalar, int _Flags> +class SparseMatrix<Scalar,_Flags>::InnerIterator +{ + public: + InnerIterator(const SparseMatrix& mat, int outer) + : m_matrix(mat), m_outer(outer), m_id(mat.m_outerIndex[outer]), m_start(m_id), m_end(mat.m_outerIndex[outer+1]) + {} + + template<unsigned int Added, unsigned int Removed> + InnerIterator(const Flagged<SparseMatrix,Added,Removed>& mat, int outer) + : m_matrix(mat._expression()), m_outer(outer), m_id(m_matrix.m_outerIndex[outer]), + m_start(m_id), m_end(m_matrix.m_outerIndex[outer+1]) + {} + + inline InnerIterator& operator++() { m_id++; return *this; } + + inline Scalar value() const { return m_matrix.m_data.value(m_id); } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix.m_data.value(m_id)); } + + inline int index() const { return m_matrix.m_data.index(m_id); } + inline int row() const { return IsRowMajor ? m_outer : index(); } + inline int col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id < m_end) && (m_id>=m_start); } + + protected: + const SparseMatrix& m_matrix; + const int m_outer; + int m_id; + const int m_start; + const int m_end; +}; + +#endif // EIGEN_SPARSEMATRIX_H |