Squashed 'third_party/eigen/' content from commit 61d72f6
Change-Id: Iccc90fa0b55ab44037f018046d2fcffd90d9d025
git-subtree-dir: third_party/eigen
git-subtree-split: 61d72f6383cfa842868c53e30e087b0258177257
diff --git a/unsupported/Eigen/src/SparseExtra/BlockOfDynamicSparseMatrix.h b/unsupported/Eigen/src/SparseExtra/BlockOfDynamicSparseMatrix.h
new file mode 100644
index 0000000..e9ec746
--- /dev/null
+++ b/unsupported/Eigen/src/SparseExtra/BlockOfDynamicSparseMatrix.h
@@ -0,0 +1,122 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_BLOCKFORDYNAMICMATRIX_H
+#define EIGEN_SPARSE_BLOCKFORDYNAMICMATRIX_H
+
+namespace Eigen {
+
+#if 0
+
+// NOTE Have to be reimplemented as a specialization of BlockImpl< DynamicSparseMatrix<_Scalar, _Options, _Index>, ... >
+// See SparseBlock.h for an example
+
+
+/***************************************************************************
+* specialisation for DynamicSparseMatrix
+***************************************************************************/
+
+template<typename _Scalar, int _Options, typename _Index, int Size>
+class SparseInnerVectorSet<DynamicSparseMatrix<_Scalar, _Options, _Index>, Size>
+ : public SparseMatrixBase<SparseInnerVectorSet<DynamicSparseMatrix<_Scalar, _Options, _Index>, Size> >
+{
+ typedef DynamicSparseMatrix<_Scalar, _Options, _Index> MatrixType;
+ public:
+
+ enum { IsRowMajor = internal::traits<SparseInnerVectorSet>::IsRowMajor };
+
+ EIGEN_SPARSE_PUBLIC_INTERFACE(SparseInnerVectorSet)
+ class InnerIterator: public MatrixType::InnerIterator
+ {
+ public:
+ inline InnerIterator(const SparseInnerVectorSet& xpr, Index outer)
+ : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
+ {}
+ inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
+ inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
+ protected:
+ Index m_outer;
+ };
+
+ inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize)
+ : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
+ {
+ eigen_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) );
+ }
+
+ inline SparseInnerVectorSet(const MatrixType& matrix, Index outer)
+ : m_matrix(matrix), m_outerStart(outer), m_outerSize(Size)
+ {
+ eigen_assert(Size!=Dynamic);
+ eigen_assert( (outer>=0) && (outer<matrix.outerSize()) );
+ }
+
+ template<typename OtherDerived>
+ inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
+ {
+ if (IsRowMajor != ((OtherDerived::Flags&RowMajorBit)==RowMajorBit))
+ {
+ // need to transpose => perform a block evaluation followed by a big swap
+ DynamicSparseMatrix<Scalar,IsRowMajor?RowMajorBit:0> aux(other);
+ *this = aux.markAsRValue();
+ }
+ else
+ {
+ // evaluate/copy vector per vector
+ for (Index j=0; j<m_outerSize.value(); ++j)
+ {
+ SparseVector<Scalar,IsRowMajor ? RowMajorBit : 0> aux(other.innerVector(j));
+ m_matrix.const_cast_derived()._data()[m_outerStart+j].swap(aux._data());
+ }
+ }
+ return *this;
+ }
+
+ inline SparseInnerVectorSet& operator=(const SparseInnerVectorSet& other)
+ {
+ return operator=<SparseInnerVectorSet>(other);
+ }
+
+ Index nonZeros() const
+ {
+ Index count = 0;
+ for (Index j=0; j<m_outerSize.value(); ++j)
+ count += m_matrix._data()[m_outerStart+j].size();
+ return count;
+ }
+
+ const Scalar& lastCoeff() const
+ {
+ EIGEN_STATIC_ASSERT_VECTOR_ONLY(SparseInnerVectorSet);
+ eigen_assert(m_matrix.data()[m_outerStart].size()>0);
+ return m_matrix.data()[m_outerStart].vale(m_matrix.data()[m_outerStart].size()-1);
+ }
+
+// template<typename Sparse>
+// inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
+// {
+// return *this;
+// }
+
+ EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
+ EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
+
+ protected:
+
+ const typename MatrixType::Nested m_matrix;
+ Index m_outerStart;
+ const internal::variable_if_dynamic<Index, Size> m_outerSize;
+
+};
+
+#endif
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_BLOCKFORDYNAMICMATRIX_H
diff --git a/unsupported/Eigen/src/SparseExtra/CMakeLists.txt b/unsupported/Eigen/src/SparseExtra/CMakeLists.txt
new file mode 100644
index 0000000..7ea32ca
--- /dev/null
+++ b/unsupported/Eigen/src/SparseExtra/CMakeLists.txt
@@ -0,0 +1,6 @@
+FILE(GLOB Eigen_SparseExtra_SRCS "*.h")
+
+INSTALL(FILES
+ ${Eigen_SparseExtra_SRCS}
+ DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/SparseExtra COMPONENT Devel
+ )
diff --git a/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h b/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h
new file mode 100644
index 0000000..dec16df
--- /dev/null
+++ b/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h
@@ -0,0 +1,357 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_DYNAMIC_SPARSEMATRIX_H
+#define EIGEN_DYNAMIC_SPARSEMATRIX_H
+
+namespace Eigen {
+
+/** \deprecated use a SparseMatrix in an uncompressed mode
+ *
+ * \class DynamicSparseMatrix
+ *
+ * \brief A sparse matrix class designed for matrix assembly purpose
+ *
+ * \param _Scalar the scalar type, i.e. the type of the coefficients
+ *
+ * Unlike SparseMatrix, this class provides a much higher degree of flexibility. In particular, it allows
+ * random read/write accesses in log(rho*outer_size) where \c rho is the probability that a coefficient is
+ * nonzero and outer_size is the number of columns if the matrix is column-major and the number of rows
+ * otherwise.
+ *
+ * Internally, the data are stored as a std::vector of compressed vector. The performances of random writes might
+ * decrease as the number of nonzeros per inner-vector increase. In practice, we observed very good performance
+ * till about 100 nonzeros/vector, and the performance remains relatively good till 500 nonzeros/vectors.
+ *
+ * \see SparseMatrix
+ */
+
+namespace internal {
+template<typename _Scalar, int _Options, typename _Index>
+struct traits<DynamicSparseMatrix<_Scalar, _Options, _Index> >
+{
+ typedef _Scalar Scalar;
+ typedef _Index Index;
+ typedef Sparse StorageKind;
+ typedef MatrixXpr XprKind;
+ enum {
+ RowsAtCompileTime = Dynamic,
+ ColsAtCompileTime = Dynamic,
+ MaxRowsAtCompileTime = Dynamic,
+ MaxColsAtCompileTime = Dynamic,
+ Flags = _Options | NestByRefBit | LvalueBit,
+ CoeffReadCost = NumTraits<Scalar>::ReadCost,
+ SupportedAccessPatterns = OuterRandomAccessPattern
+ };
+};
+}
+
+template<typename _Scalar, int _Options, typename _Index>
+ class DynamicSparseMatrix
+ : public SparseMatrixBase<DynamicSparseMatrix<_Scalar, _Options, _Index> >
+{
+ public:
+ EIGEN_SPARSE_PUBLIC_INTERFACE(DynamicSparseMatrix)
+ // FIXME: why are these operator already alvailable ???
+ // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, +=)
+ // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, -=)
+ typedef MappedSparseMatrix<Scalar,Flags> Map;
+ using Base::IsRowMajor;
+ using Base::operator=;
+ enum {
+ Options = _Options
+ };
+
+ protected:
+
+ typedef DynamicSparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
+
+ Index m_innerSize;
+ std::vector<internal::CompressedStorage<Scalar,Index> > m_data;
+
+ public:
+
+ inline Index rows() const { return IsRowMajor ? outerSize() : m_innerSize; }
+ inline Index cols() const { return IsRowMajor ? m_innerSize : outerSize(); }
+ inline Index innerSize() const { return m_innerSize; }
+ inline Index outerSize() const { return static_cast<Index>(m_data.size()); }
+ inline Index innerNonZeros(Index j) const { return m_data[j].size(); }
+
+ std::vector<internal::CompressedStorage<Scalar,Index> >& _data() { return m_data; }
+ const std::vector<internal::CompressedStorage<Scalar,Index> >& _data() const { return m_data; }
+
+ /** \returns the coefficient value at given position \a row, \a col
+ * This operation involes a log(rho*outer_size) binary search.
+ */
+ inline Scalar coeff(Index row, Index col) const
+ {
+ const Index outer = IsRowMajor ? row : col;
+ const Index inner = IsRowMajor ? col : row;
+ return m_data[outer].at(inner);
+ }
+
+ /** \returns a reference to the coefficient value at given position \a row, \a col
+ * This operation involes a log(rho*outer_size) binary search. If the coefficient does not
+ * exist yet, then a sorted insertion into a sequential buffer is performed.
+ */
+ inline Scalar& coeffRef(Index row, Index col)
+ {
+ const Index outer = IsRowMajor ? row : col;
+ const Index inner = IsRowMajor ? col : row;
+ return m_data[outer].atWithInsertion(inner);
+ }
+
+ class InnerIterator;
+ class ReverseInnerIterator;
+
+ void setZero()
+ {
+ for (Index j=0; j<outerSize(); ++j)
+ m_data[j].clear();
+ }
+
+ /** \returns the number of non zero coefficients */
+ Index nonZeros() const
+ {
+ Index res = 0;
+ for (Index j=0; j<outerSize(); ++j)
+ res += static_cast<Index>(m_data[j].size());
+ return res;
+ }
+
+
+
+ void reserve(Index reserveSize = 1000)
+ {
+ if (outerSize()>0)
+ {
+ Index reserveSizePerVector = (std::max)(reserveSize/outerSize(),Index(4));
+ for (Index j=0; j<outerSize(); ++j)
+ {
+ m_data[j].reserve(reserveSizePerVector);
+ }
+ }
+ }
+
+ /** Does nothing: provided for compatibility with SparseMatrix */
+ inline void startVec(Index /*outer*/) {}
+
+ /** \returns a reference to the non zero coefficient at position \a row, \a col assuming that:
+ * - the nonzero does not already exist
+ * - the new coefficient is the last one of the given inner vector.
+ *
+ * \sa insert, insertBackByOuterInner */
+ inline Scalar& insertBack(Index row, Index col)
+ {
+ return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row);
+ }
+
+ /** \sa insertBack */
+ inline Scalar& insertBackByOuterInner(Index outer, Index inner)
+ {
+ eigen_assert(outer<Index(m_data.size()) && inner<m_innerSize && "out of range");
+ eigen_assert(((m_data[outer].size()==0) || (m_data[outer].index(m_data[outer].size()-1)<inner))
+ && "wrong sorted insertion");
+ m_data[outer].append(0, inner);
+ return m_data[outer].value(m_data[outer].size()-1);
+ }
+
+ inline Scalar& insert(Index row, Index col)
+ {
+ const Index outer = IsRowMajor ? row : col;
+ const Index inner = IsRowMajor ? col : row;
+
+ Index startId = 0;
+ Index id = static_cast<Index>(m_data[outer].size()) - 1;
+ m_data[outer].resize(id+2,1);
+
+ while ( (id >= startId) && (m_data[outer].index(id) > inner) )
+ {
+ m_data[outer].index(id+1) = m_data[outer].index(id);
+ m_data[outer].value(id+1) = m_data[outer].value(id);
+ --id;
+ }
+ m_data[outer].index(id+1) = inner;
+ m_data[outer].value(id+1) = 0;
+ return m_data[outer].value(id+1);
+ }
+
+ /** Does nothing: provided for compatibility with SparseMatrix */
+ inline void finalize() {}
+
+ /** Suppress all nonzeros which are smaller than \a reference under the tolerence \a epsilon */
+ void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
+ {
+ for (Index j=0; j<outerSize(); ++j)
+ m_data[j].prune(reference,epsilon);
+ }
+
+ /** Resize the matrix without preserving the data (the matrix is set to zero)
+ */
+ void resize(Index rows, Index cols)
+ {
+ const Index outerSize = IsRowMajor ? rows : cols;
+ m_innerSize = IsRowMajor ? cols : rows;
+ setZero();
+ if (Index(m_data.size()) != outerSize)
+ {
+ m_data.resize(outerSize);
+ }
+ }
+
+ void resizeAndKeepData(Index rows, Index cols)
+ {
+ const Index outerSize = IsRowMajor ? rows : cols;
+ const Index innerSize = IsRowMajor ? cols : rows;
+ if (m_innerSize>innerSize)
+ {
+ // remove all coefficients with innerCoord>=innerSize
+ // TODO
+ //std::cerr << "not implemented yet\n";
+ exit(2);
+ }
+ if (m_data.size() != outerSize)
+ {
+ m_data.resize(outerSize);
+ }
+ }
+
+ /** The class DynamicSparseMatrix is deprectaed */
+ EIGEN_DEPRECATED inline DynamicSparseMatrix()
+ : m_innerSize(0), m_data(0)
+ {
+ eigen_assert(innerSize()==0 && outerSize()==0);
+ }
+
+ /** The class DynamicSparseMatrix is deprectaed */
+ EIGEN_DEPRECATED inline DynamicSparseMatrix(Index rows, Index cols)
+ : m_innerSize(0)
+ {
+ resize(rows, cols);
+ }
+
+ /** The class DynamicSparseMatrix is deprectaed */
+ template<typename OtherDerived>
+ EIGEN_DEPRECATED explicit inline DynamicSparseMatrix(const SparseMatrixBase<OtherDerived>& other)
+ : m_innerSize(0)
+ {
+ Base::operator=(other.derived());
+ }
+
+ inline DynamicSparseMatrix(const DynamicSparseMatrix& other)
+ : Base(), m_innerSize(0)
+ {
+ *this = other.derived();
+ }
+
+ inline void swap(DynamicSparseMatrix& other)
+ {
+ //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n");
+ std::swap(m_innerSize, other.m_innerSize);
+ //std::swap(m_outerSize, other.m_outerSize);
+ m_data.swap(other.m_data);
+ }
+
+ inline DynamicSparseMatrix& operator=(const DynamicSparseMatrix& other)
+ {
+ if (other.isRValue())
+ {
+ swap(other.const_cast_derived());
+ }
+ else
+ {
+ resize(other.rows(), other.cols());
+ m_data = other.m_data;
+ }
+ return *this;
+ }
+
+ /** Destructor */
+ inline ~DynamicSparseMatrix() {}
+
+ public:
+
+ /** \deprecated
+ * Set the matrix to zero and reserve the memory for \a reserveSize nonzero coefficients. */
+ EIGEN_DEPRECATED void startFill(Index reserveSize = 1000)
+ {
+ setZero();
+ reserve(reserveSize);
+ }
+
+ /** \deprecated use insert()
+ * inserts a nonzero coefficient at given coordinates \a row, \a col and returns its reference assuming that:
+ * 1 - the coefficient does not exist yet
+ * 2 - this the coefficient with greater inner coordinate for the given outer coordinate.
+ * In other words, assuming \c *this is column-major, then there must not exists any nonzero coefficient of coordinates
+ * \c i \c x \a col such that \c i >= \a row. Otherwise the matrix is invalid.
+ *
+ * \see fillrand(), coeffRef()
+ */
+ EIGEN_DEPRECATED Scalar& fill(Index row, Index col)
+ {
+ const Index outer = IsRowMajor ? row : col;
+ const Index inner = IsRowMajor ? col : row;
+ return insertBack(outer,inner);
+ }
+
+ /** \deprecated use insert()
+ * Like fill() but with random inner coordinates.
+ * Compared to the generic coeffRef(), the unique limitation is that we assume
+ * the coefficient does not exist yet.
+ */
+ EIGEN_DEPRECATED Scalar& fillrand(Index row, Index col)
+ {
+ return insert(row,col);
+ }
+
+ /** \deprecated use finalize()
+ * Does nothing. Provided for compatibility with SparseMatrix. */
+ EIGEN_DEPRECATED void endFill() {}
+
+# ifdef EIGEN_DYNAMICSPARSEMATRIX_PLUGIN
+# include EIGEN_DYNAMICSPARSEMATRIX_PLUGIN
+# endif
+ };
+
+template<typename Scalar, int _Options, typename _Index>
+class DynamicSparseMatrix<Scalar,_Options,_Index>::InnerIterator : public SparseVector<Scalar,_Options,_Index>::InnerIterator
+{
+ typedef typename SparseVector<Scalar,_Options,_Index>::InnerIterator Base;
+ public:
+ InnerIterator(const DynamicSparseMatrix& mat, Index outer)
+ : Base(mat.m_data[outer]), m_outer(outer)
+ {}
+
+ inline Index row() const { return IsRowMajor ? m_outer : Base::index(); }
+ inline Index col() const { return IsRowMajor ? Base::index() : m_outer; }
+
+ protected:
+ const Index m_outer;
+};
+
+template<typename Scalar, int _Options, typename _Index>
+class DynamicSparseMatrix<Scalar,_Options,_Index>::ReverseInnerIterator : public SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator
+{
+ typedef typename SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator Base;
+ public:
+ ReverseInnerIterator(const DynamicSparseMatrix& mat, Index outer)
+ : Base(mat.m_data[outer]), m_outer(outer)
+ {}
+
+ inline Index row() const { return IsRowMajor ? m_outer : Base::index(); }
+ inline Index col() const { return IsRowMajor ? Base::index() : m_outer; }
+
+ protected:
+ const Index m_outer;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_DYNAMIC_SPARSEMATRIX_H
diff --git a/unsupported/Eigen/src/SparseExtra/MarketIO.h b/unsupported/Eigen/src/SparseExtra/MarketIO.h
new file mode 100644
index 0000000..7aafce9
--- /dev/null
+++ b/unsupported/Eigen/src/SparseExtra/MarketIO.h
@@ -0,0 +1,273 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2012 Desire NUENTSA WAKAM <desire.nuentsa_wakam@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_MARKET_IO_H
+#define EIGEN_SPARSE_MARKET_IO_H
+
+#include <iostream>
+
+namespace Eigen {
+
+namespace internal
+{
+ template <typename Scalar>
+ inline bool GetMarketLine (std::stringstream& line, int& M, int& N, int& i, int& j, Scalar& value)
+ {
+ line >> i >> j >> value;
+ i--;
+ j--;
+ if(i>=0 && j>=0 && i<M && j<N)
+ {
+ return true;
+ }
+ else
+ return false;
+ }
+ template <typename Scalar>
+ inline bool GetMarketLine (std::stringstream& line, int& M, int& N, int& i, int& j, std::complex<Scalar>& value)
+ {
+ Scalar valR, valI;
+ line >> i >> j >> valR >> valI;
+ i--;
+ j--;
+ if(i>=0 && j>=0 && i<M && j<N)
+ {
+ value = std::complex<Scalar>(valR, valI);
+ return true;
+ }
+ else
+ return false;
+ }
+
+ template <typename RealScalar>
+ inline void GetVectorElt (const std::string& line, RealScalar& val)
+ {
+ std::istringstream newline(line);
+ newline >> val;
+ }
+
+ template <typename RealScalar>
+ inline void GetVectorElt (const std::string& line, std::complex<RealScalar>& val)
+ {
+ RealScalar valR, valI;
+ std::istringstream newline(line);
+ newline >> valR >> valI;
+ val = std::complex<RealScalar>(valR, valI);
+ }
+
+ template<typename Scalar>
+ inline void putMarketHeader(std::string& header,int sym)
+ {
+ header= "%%MatrixMarket matrix coordinate ";
+ if(internal::is_same<Scalar, std::complex<float> >::value || internal::is_same<Scalar, std::complex<double> >::value)
+ {
+ header += " complex";
+ if(sym == Symmetric) header += " symmetric";
+ else if (sym == SelfAdjoint) header += " Hermitian";
+ else header += " general";
+ }
+ else
+ {
+ header += " real";
+ if(sym == Symmetric) header += " symmetric";
+ else header += " general";
+ }
+ }
+
+ template<typename Scalar>
+ inline void PutMatrixElt(Scalar value, int row, int col, std::ofstream& out)
+ {
+ out << row << " "<< col << " " << value << "\n";
+ }
+ template<typename Scalar>
+ inline void PutMatrixElt(std::complex<Scalar> value, int row, int col, std::ofstream& out)
+ {
+ out << row << " " << col << " " << value.real() << " " << value.imag() << "\n";
+ }
+
+
+ template<typename Scalar>
+ inline void putVectorElt(Scalar value, std::ofstream& out)
+ {
+ out << value << "\n";
+ }
+ template<typename Scalar>
+ inline void putVectorElt(std::complex<Scalar> value, std::ofstream& out)
+ {
+ out << value.real << " " << value.imag()<< "\n";
+ }
+
+} // end namepsace internal
+
+inline bool getMarketHeader(const std::string& filename, int& sym, bool& iscomplex, bool& isvector)
+{
+ sym = 0;
+ isvector = false;
+ std::ifstream in(filename.c_str(),std::ios::in);
+ if(!in)
+ return false;
+
+ std::string line;
+ // The matrix header is always the first line in the file
+ std::getline(in, line); eigen_assert(in.good());
+
+ std::stringstream fmtline(line);
+ std::string substr[5];
+ fmtline>> substr[0] >> substr[1] >> substr[2] >> substr[3] >> substr[4];
+ if(substr[2].compare("array") == 0) isvector = true;
+ if(substr[3].compare("complex") == 0) iscomplex = true;
+ if(substr[4].compare("symmetric") == 0) sym = Symmetric;
+ else if (substr[4].compare("Hermitian") == 0) sym = SelfAdjoint;
+
+ return true;
+}
+
+template<typename SparseMatrixType>
+bool loadMarket(SparseMatrixType& mat, const std::string& filename)
+{
+ typedef typename SparseMatrixType::Scalar Scalar;
+ std::ifstream input(filename.c_str(),std::ios::in);
+ if(!input)
+ return false;
+
+ const int maxBuffersize = 2048;
+ char buffer[maxBuffersize];
+
+ bool readsizes = false;
+
+ typedef Triplet<Scalar,int> T;
+ std::vector<T> elements;
+
+ int M(-1), N(-1), NNZ(-1);
+ int count = 0;
+ while(input.getline(buffer, maxBuffersize))
+ {
+ // skip comments
+ //NOTE An appropriate test should be done on the header to get the symmetry
+ if(buffer[0]=='%')
+ continue;
+
+ std::stringstream line(buffer);
+
+ if(!readsizes)
+ {
+ line >> M >> N >> NNZ;
+ if(M > 0 && N > 0 && NNZ > 0)
+ {
+ readsizes = true;
+ std::cout << "sizes: " << M << "," << N << "," << NNZ << "\n";
+ mat.resize(M,N);
+ mat.reserve(NNZ);
+ }
+ }
+ else
+ {
+ int i(-1), j(-1);
+ Scalar value;
+ if( internal::GetMarketLine(line, M, N, i, j, value) )
+ {
+ ++ count;
+ elements.push_back(T(i,j,value));
+ }
+ else
+ std::cerr << "Invalid read: " << i << "," << j << "\n";
+ }
+ }
+ mat.setFromTriplets(elements.begin(), elements.end());
+ if(count!=NNZ)
+ std::cerr << count << "!=" << NNZ << "\n";
+
+ input.close();
+ return true;
+}
+
+template<typename VectorType>
+bool loadMarketVector(VectorType& vec, const std::string& filename)
+{
+ typedef typename VectorType::Scalar Scalar;
+ std::ifstream in(filename.c_str(), std::ios::in);
+ if(!in)
+ return false;
+
+ std::string line;
+ int n(0), col(0);
+ do
+ { // Skip comments
+ std::getline(in, line); eigen_assert(in.good());
+ } while (line[0] == '%');
+ std::istringstream newline(line);
+ newline >> n >> col;
+ eigen_assert(n>0 && col>0);
+ vec.resize(n);
+ int i = 0;
+ Scalar value;
+ while ( std::getline(in, line) && (i < n) ){
+ internal::GetVectorElt(line, value);
+ vec(i++) = value;
+ }
+ in.close();
+ if (i!=n){
+ std::cerr<< "Unable to read all elements from file " << filename << "\n";
+ return false;
+ }
+ return true;
+}
+
+template<typename SparseMatrixType>
+bool saveMarket(const SparseMatrixType& mat, const std::string& filename, int sym = 0)
+{
+ typedef typename SparseMatrixType::Scalar Scalar;
+ std::ofstream out(filename.c_str(),std::ios::out);
+ if(!out)
+ return false;
+
+ out.flags(std::ios_base::scientific);
+ out.precision(64);
+ std::string header;
+ internal::putMarketHeader<Scalar>(header, sym);
+ out << header << std::endl;
+ out << mat.rows() << " " << mat.cols() << " " << mat.nonZeros() << "\n";
+ int count = 0;
+ for(int j=0; j<mat.outerSize(); ++j)
+ for(typename SparseMatrixType::InnerIterator it(mat,j); it; ++it)
+ {
+ ++ count;
+ internal::PutMatrixElt(it.value(), it.row()+1, it.col()+1, out);
+ // out << it.row()+1 << " " << it.col()+1 << " " << it.value() << "\n";
+ }
+ out.close();
+ return true;
+}
+
+template<typename VectorType>
+bool saveMarketVector (const VectorType& vec, const std::string& filename)
+{
+ typedef typename VectorType::Scalar Scalar;
+ std::ofstream out(filename.c_str(),std::ios::out);
+ if(!out)
+ return false;
+
+ out.flags(std::ios_base::scientific);
+ out.precision(64);
+ if(internal::is_same<Scalar, std::complex<float> >::value || internal::is_same<Scalar, std::complex<double> >::value)
+ out << "%%MatrixMarket matrix array complex general\n";
+ else
+ out << "%%MatrixMarket matrix array real general\n";
+ out << vec.size() << " "<< 1 << "\n";
+ for (int i=0; i < vec.size(); i++){
+ internal::putVectorElt(vec(i), out);
+ }
+ out.close();
+ return true;
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_MARKET_IO_H
diff --git a/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h b/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h
new file mode 100644
index 0000000..bf13cf2
--- /dev/null
+++ b/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h
@@ -0,0 +1,232 @@
+
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Desire NUENTSA WAKAM <desire.nuentsa_wakam@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_BROWSE_MATRICES_H
+#define EIGEN_BROWSE_MATRICES_H
+
+namespace Eigen {
+
+enum {
+ SPD = 0x100,
+ NonSymmetric = 0x0
+};
+
+/**
+ * @brief Iterator to browse matrices from a specified folder
+ *
+ * This is used to load all the matrices from a folder.
+ * The matrices should be in Matrix Market format
+ * It is assumed that the matrices are named as matname.mtx
+ * and matname_SPD.mtx if the matrix is Symmetric and positive definite (or Hermitian)
+ * The right hand side vectors are loaded as well, if they exist.
+ * They should be named as matname_b.mtx.
+ * Note that the right hand side for a SPD matrix is named as matname_SPD_b.mtx
+ *
+ * Sometimes a reference solution is available. In this case, it should be named as matname_x.mtx
+ *
+ * Sample code
+ * \code
+ *
+ * \endcode
+ *
+ * \tparam Scalar The scalar type
+ */
+template <typename Scalar>
+class MatrixMarketIterator
+{
+ public:
+ typedef Matrix<Scalar,Dynamic,1> VectorType;
+ typedef SparseMatrix<Scalar,ColMajor> MatrixType;
+
+ public:
+ MatrixMarketIterator(const std::string folder):m_sym(0),m_isvalid(false),m_matIsLoaded(false),m_hasRhs(false),m_hasrefX(false),m_folder(folder)
+ {
+ m_folder_id = opendir(folder.c_str());
+ if (!m_folder_id){
+ m_isvalid = false;
+ std::cerr << "The provided Matrix folder could not be opened \n\n";
+ abort();
+ }
+ Getnextvalidmatrix();
+ }
+
+ ~MatrixMarketIterator()
+ {
+ if (m_folder_id) closedir(m_folder_id);
+ }
+
+ inline MatrixMarketIterator& operator++()
+ {
+ m_matIsLoaded = false;
+ m_hasrefX = false;
+ m_hasRhs = false;
+ Getnextvalidmatrix();
+ return *this;
+ }
+ inline operator bool() const { return m_isvalid;}
+
+ /** Return the sparse matrix corresponding to the current file */
+ inline MatrixType& matrix()
+ {
+ // Read the matrix
+ if (m_matIsLoaded) return m_mat;
+
+ std::string matrix_file = m_folder + "/" + m_matname + ".mtx";
+ if ( !loadMarket(m_mat, matrix_file))
+ {
+ m_matIsLoaded = false;
+ return m_mat;
+ }
+ m_matIsLoaded = true;
+
+ if (m_sym != NonSymmetric)
+ { // Store the upper part of the matrix. It is needed by the solvers dealing with nonsymmetric matrices ??
+ MatrixType B;
+ B = m_mat;
+ m_mat = B.template selfadjointView<Lower>();
+ }
+ return m_mat;
+ }
+
+ /** Return the right hand side corresponding to the current matrix.
+ * If the rhs file is not provided, a random rhs is generated
+ */
+ inline VectorType& rhs()
+ {
+ // Get the right hand side
+ if (m_hasRhs) return m_rhs;
+
+ std::string rhs_file;
+ rhs_file = m_folder + "/" + m_matname + "_b.mtx"; // The pattern is matname_b.mtx
+ m_hasRhs = Fileexists(rhs_file);
+ if (m_hasRhs)
+ {
+ m_rhs.resize(m_mat.cols());
+ m_hasRhs = loadMarketVector(m_rhs, rhs_file);
+ }
+ if (!m_hasRhs)
+ {
+ // Generate a random right hand side
+ if (!m_matIsLoaded) this->matrix();
+ m_refX.resize(m_mat.cols());
+ m_refX.setRandom();
+ m_rhs = m_mat * m_refX;
+ m_hasrefX = true;
+ m_hasRhs = true;
+ }
+ return m_rhs;
+ }
+
+ /** Return a reference solution
+ * If it is not provided and if the right hand side is not available
+ * then refX is randomly generated such that A*refX = b
+ * where A and b are the matrix and the rhs.
+ * Note that when a rhs is provided, refX is not available
+ */
+ inline VectorType& refX()
+ {
+ // Check if a reference solution is provided
+ if (m_hasrefX) return m_refX;
+
+ std::string lhs_file;
+ lhs_file = m_folder + "/" + m_matname + "_x.mtx";
+ m_hasrefX = Fileexists(lhs_file);
+ if (m_hasrefX)
+ {
+ m_refX.resize(m_mat.cols());
+ m_hasrefX = loadMarketVector(m_refX, lhs_file);
+ }
+ return m_refX;
+ }
+
+ inline std::string& matname() { return m_matname; }
+
+ inline int sym() { return m_sym; }
+
+ inline bool hasRhs() {return m_hasRhs; }
+ inline bool hasrefX() {return m_hasrefX; }
+
+ protected:
+
+ inline bool Fileexists(std::string file)
+ {
+ std::ifstream file_id(file.c_str());
+ if (!file_id.good() )
+ {
+ return false;
+ }
+ else
+ {
+ file_id.close();
+ return true;
+ }
+ }
+
+ void Getnextvalidmatrix( )
+ {
+ m_isvalid = false;
+ // Here, we return with the next valid matrix in the folder
+ while ( (m_curs_id = readdir(m_folder_id)) != NULL) {
+ m_isvalid = false;
+ std::string curfile;
+ curfile = m_folder + "/" + m_curs_id->d_name;
+ // Discard if it is a folder
+ if (m_curs_id->d_type == DT_DIR) continue; //FIXME This may not be available on non BSD systems
+// struct stat st_buf;
+// stat (curfile.c_str(), &st_buf);
+// if (S_ISDIR(st_buf.st_mode)) continue;
+
+ // Determine from the header if it is a matrix or a right hand side
+ bool isvector,iscomplex=false;
+ if(!getMarketHeader(curfile,m_sym,iscomplex,isvector)) continue;
+ if(isvector) continue;
+ if (!iscomplex)
+ {
+ if(internal::is_same<Scalar, std::complex<float> >::value || internal::is_same<Scalar, std::complex<double> >::value)
+ continue;
+ }
+ if (iscomplex)
+ {
+ if(internal::is_same<Scalar, float>::value || internal::is_same<Scalar, double>::value)
+ continue;
+ }
+
+
+ // Get the matrix name
+ std::string filename = m_curs_id->d_name;
+ m_matname = filename.substr(0, filename.length()-4);
+
+ // Find if the matrix is SPD
+ size_t found = m_matname.find("SPD");
+ if( (found!=std::string::npos) && (m_sym != NonSymmetric) )
+ m_sym = SPD;
+
+ m_isvalid = true;
+ break;
+ }
+ }
+ int m_sym; // Symmetry of the matrix
+ MatrixType m_mat; // Current matrix
+ VectorType m_rhs; // Current vector
+ VectorType m_refX; // The reference solution, if exists
+ std::string m_matname; // Matrix Name
+ bool m_isvalid;
+ bool m_matIsLoaded; // Determine if the matrix has already been loaded from the file
+ bool m_hasRhs; // The right hand side exists
+ bool m_hasrefX; // A reference solution is provided
+ std::string m_folder;
+ DIR * m_folder_id;
+ struct dirent *m_curs_id;
+
+};
+
+} // end namespace Eigen
+
+#endif
diff --git a/unsupported/Eigen/src/SparseExtra/RandomSetter.h b/unsupported/Eigen/src/SparseExtra/RandomSetter.h
new file mode 100644
index 0000000..dee1708
--- /dev/null
+++ b/unsupported/Eigen/src/SparseExtra/RandomSetter.h
@@ -0,0 +1,327 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_RANDOMSETTER_H
+#define EIGEN_RANDOMSETTER_H
+
+namespace Eigen {
+
+/** Represents a std::map
+ *
+ * \see RandomSetter
+ */
+template<typename Scalar> struct StdMapTraits
+{
+ typedef int KeyType;
+ typedef std::map<KeyType,Scalar> Type;
+ enum {
+ IsSorted = 1
+ };
+
+ static void setInvalidKey(Type&, const KeyType&) {}
+};
+
+#ifdef EIGEN_UNORDERED_MAP_SUPPORT
+/** Represents a std::unordered_map
+ *
+ * To use it you need to both define EIGEN_UNORDERED_MAP_SUPPORT and include the unordered_map header file
+ * yourself making sure that unordered_map is defined in the std namespace.
+ *
+ * For instance, with current version of gcc you can either enable C++0x standard (-std=c++0x) or do:
+ * \code
+ * #include <tr1/unordered_map>
+ * #define EIGEN_UNORDERED_MAP_SUPPORT
+ * namespace std {
+ * using std::tr1::unordered_map;
+ * }
+ * \endcode
+ *
+ * \see RandomSetter
+ */
+template<typename Scalar> struct StdUnorderedMapTraits
+{
+ typedef int KeyType;
+ typedef std::unordered_map<KeyType,Scalar> Type;
+ enum {
+ IsSorted = 0
+ };
+
+ static void setInvalidKey(Type&, const KeyType&) {}
+};
+#endif // EIGEN_UNORDERED_MAP_SUPPORT
+
+#ifdef _DENSE_HASH_MAP_H_
+/** Represents a google::dense_hash_map
+ *
+ * \see RandomSetter
+ */
+template<typename Scalar> struct GoogleDenseHashMapTraits
+{
+ typedef int KeyType;
+ typedef google::dense_hash_map<KeyType,Scalar> Type;
+ enum {
+ IsSorted = 0
+ };
+
+ static void setInvalidKey(Type& map, const KeyType& k)
+ { map.set_empty_key(k); }
+};
+#endif
+
+#ifdef _SPARSE_HASH_MAP_H_
+/** Represents a google::sparse_hash_map
+ *
+ * \see RandomSetter
+ */
+template<typename Scalar> struct GoogleSparseHashMapTraits
+{
+ typedef int KeyType;
+ typedef google::sparse_hash_map<KeyType,Scalar> Type;
+ enum {
+ IsSorted = 0
+ };
+
+ static void setInvalidKey(Type&, const KeyType&) {}
+};
+#endif
+
+/** \class RandomSetter
+ *
+ * \brief The RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access
+ *
+ * \param SparseMatrixType the type of the sparse matrix we are updating
+ * \param MapTraits a traits class representing the map implementation used for the temporary sparse storage.
+ * Its default value depends on the system.
+ * \param OuterPacketBits defines the number of rows (or columns) manage by a single map object
+ * as a power of two exponent.
+ *
+ * This class temporarily represents a sparse matrix object using a generic map implementation allowing for
+ * efficient random access. The conversion from the compressed representation to a hash_map object is performed
+ * in the RandomSetter constructor, while the sparse matrix is updated back at destruction time. This strategy
+ * suggest the use of nested blocks as in this example:
+ *
+ * \code
+ * SparseMatrix<double> m(rows,cols);
+ * {
+ * RandomSetter<SparseMatrix<double> > w(m);
+ * // don't use m but w instead with read/write random access to the coefficients:
+ * for(;;)
+ * w(rand(),rand()) = rand;
+ * }
+ * // when w is deleted, the data are copied back to m
+ * // and m is ready to use.
+ * \endcode
+ *
+ * Since hash_map objects are not fully sorted, representing a full matrix as a single hash_map would
+ * involve a big and costly sort to update the compressed matrix back. To overcome this issue, a RandomSetter
+ * use multiple hash_map, each representing 2^OuterPacketBits columns or rows according to the storage order.
+ * To reach optimal performance, this value should be adjusted according to the average number of nonzeros
+ * per rows/columns.
+ *
+ * The possible values for the template parameter MapTraits are:
+ * - \b StdMapTraits: corresponds to std::map. (does not perform very well)
+ * - \b GnuHashMapTraits: corresponds to __gnu_cxx::hash_map (available only with GCC)
+ * - \b GoogleDenseHashMapTraits: corresponds to google::dense_hash_map (best efficiency, reasonable memory consumption)
+ * - \b GoogleSparseHashMapTraits: corresponds to google::sparse_hash_map (best memory consumption, relatively good performance)
+ *
+ * The default map implementation depends on the availability, and the preferred order is:
+ * GoogleSparseHashMapTraits, GnuHashMapTraits, and finally StdMapTraits.
+ *
+ * For performance and memory consumption reasons it is highly recommended to use one of
+ * the Google's hash_map implementation. To enable the support for them, you have two options:
+ * - \#include <google/dense_hash_map> yourself \b before Eigen/Sparse header
+ * - define EIGEN_GOOGLEHASH_SUPPORT
+ * In the later case the inclusion of <google/dense_hash_map> is made for you.
+ *
+ * \see http://code.google.com/p/google-sparsehash/
+ */
+template<typename SparseMatrixType,
+ template <typename T> class MapTraits =
+#if defined _DENSE_HASH_MAP_H_
+ GoogleDenseHashMapTraits
+#elif defined _HASH_MAP
+ GnuHashMapTraits
+#else
+ StdMapTraits
+#endif
+ ,int OuterPacketBits = 6>
+class RandomSetter
+{
+ typedef typename SparseMatrixType::Scalar Scalar;
+ typedef typename SparseMatrixType::Index Index;
+
+ struct ScalarWrapper
+ {
+ ScalarWrapper() : value(0) {}
+ Scalar value;
+ };
+ typedef typename MapTraits<ScalarWrapper>::KeyType KeyType;
+ typedef typename MapTraits<ScalarWrapper>::Type HashMapType;
+ static const int OuterPacketMask = (1 << OuterPacketBits) - 1;
+ enum {
+ SwapStorage = 1 - MapTraits<ScalarWrapper>::IsSorted,
+ TargetRowMajor = (SparseMatrixType::Flags & RowMajorBit) ? 1 : 0,
+ SetterRowMajor = SwapStorage ? 1-TargetRowMajor : TargetRowMajor
+ };
+
+ public:
+
+ /** Constructs a random setter object from the sparse matrix \a target
+ *
+ * Note that the initial value of \a target are imported. If you want to re-set
+ * a sparse matrix from scratch, then you must set it to zero first using the
+ * setZero() function.
+ */
+ inline RandomSetter(SparseMatrixType& target)
+ : mp_target(&target)
+ {
+ const Index outerSize = SwapStorage ? target.innerSize() : target.outerSize();
+ const Index innerSize = SwapStorage ? target.outerSize() : target.innerSize();
+ m_outerPackets = outerSize >> OuterPacketBits;
+ if (outerSize&OuterPacketMask)
+ m_outerPackets += 1;
+ m_hashmaps = new HashMapType[m_outerPackets];
+ // compute number of bits needed to store inner indices
+ Index aux = innerSize - 1;
+ m_keyBitsOffset = 0;
+ while (aux)
+ {
+ ++m_keyBitsOffset;
+ aux = aux >> 1;
+ }
+ KeyType ik = (1<<(OuterPacketBits+m_keyBitsOffset));
+ for (Index k=0; k<m_outerPackets; ++k)
+ MapTraits<ScalarWrapper>::setInvalidKey(m_hashmaps[k],ik);
+
+ // insert current coeffs
+ for (Index j=0; j<mp_target->outerSize(); ++j)
+ for (typename SparseMatrixType::InnerIterator it(*mp_target,j); it; ++it)
+ (*this)(TargetRowMajor?j:it.index(), TargetRowMajor?it.index():j) = it.value();
+ }
+
+ /** Destructor updating back the sparse matrix target */
+ ~RandomSetter()
+ {
+ KeyType keyBitsMask = (1<<m_keyBitsOffset)-1;
+ if (!SwapStorage) // also means the map is sorted
+ {
+ mp_target->setZero();
+ mp_target->makeCompressed();
+ mp_target->reserve(nonZeros());
+ Index prevOuter = -1;
+ for (Index k=0; k<m_outerPackets; ++k)
+ {
+ const Index outerOffset = (1<<OuterPacketBits) * k;
+ typename HashMapType::iterator end = m_hashmaps[k].end();
+ for (typename HashMapType::iterator it = m_hashmaps[k].begin(); it!=end; ++it)
+ {
+ const Index outer = (it->first >> m_keyBitsOffset) + outerOffset;
+ const Index inner = it->first & keyBitsMask;
+ if (prevOuter!=outer)
+ {
+ for (Index j=prevOuter+1;j<=outer;++j)
+ mp_target->startVec(j);
+ prevOuter = outer;
+ }
+ mp_target->insertBackByOuterInner(outer, inner) = it->second.value;
+ }
+ }
+ mp_target->finalize();
+ }
+ else
+ {
+ VectorXi positions(mp_target->outerSize());
+ positions.setZero();
+ // pass 1
+ for (Index k=0; k<m_outerPackets; ++k)
+ {
+ typename HashMapType::iterator end = m_hashmaps[k].end();
+ for (typename HashMapType::iterator it = m_hashmaps[k].begin(); it!=end; ++it)
+ {
+ const Index outer = it->first & keyBitsMask;
+ ++positions[outer];
+ }
+ }
+ // prefix sum
+ Index count = 0;
+ for (Index j=0; j<mp_target->outerSize(); ++j)
+ {
+ Index tmp = positions[j];
+ mp_target->outerIndexPtr()[j] = count;
+ positions[j] = count;
+ count += tmp;
+ }
+ mp_target->makeCompressed();
+ mp_target->outerIndexPtr()[mp_target->outerSize()] = count;
+ mp_target->resizeNonZeros(count);
+ // pass 2
+ for (Index k=0; k<m_outerPackets; ++k)
+ {
+ const Index outerOffset = (1<<OuterPacketBits) * k;
+ typename HashMapType::iterator end = m_hashmaps[k].end();
+ for (typename HashMapType::iterator it = m_hashmaps[k].begin(); it!=end; ++it)
+ {
+ const Index inner = (it->first >> m_keyBitsOffset) + outerOffset;
+ const Index outer = it->first & keyBitsMask;
+ // sorted insertion
+ // Note that we have to deal with at most 2^OuterPacketBits unsorted coefficients,
+ // moreover those 2^OuterPacketBits coeffs are likely to be sparse, an so only a
+ // small fraction of them have to be sorted, whence the following simple procedure:
+ Index posStart = mp_target->outerIndexPtr()[outer];
+ Index i = (positions[outer]++) - 1;
+ while ( (i >= posStart) && (mp_target->innerIndexPtr()[i] > inner) )
+ {
+ mp_target->valuePtr()[i+1] = mp_target->valuePtr()[i];
+ mp_target->innerIndexPtr()[i+1] = mp_target->innerIndexPtr()[i];
+ --i;
+ }
+ mp_target->innerIndexPtr()[i+1] = inner;
+ mp_target->valuePtr()[i+1] = it->second.value;
+ }
+ }
+ }
+ delete[] m_hashmaps;
+ }
+
+ /** \returns a reference to the coefficient at given coordinates \a row, \a col */
+ Scalar& operator() (Index row, Index col)
+ {
+ const Index outer = SetterRowMajor ? row : col;
+ const Index inner = SetterRowMajor ? col : row;
+ const Index outerMajor = outer >> OuterPacketBits; // index of the packet/map
+ const Index outerMinor = outer & OuterPacketMask; // index of the inner vector in the packet
+ const KeyType key = (KeyType(outerMinor)<<m_keyBitsOffset) | inner;
+ return m_hashmaps[outerMajor][key].value;
+ }
+
+ /** \returns the number of non zero coefficients
+ *
+ * \note According to the underlying map/hash_map implementation,
+ * this function might be quite expensive.
+ */
+ Index nonZeros() const
+ {
+ Index nz = 0;
+ for (Index k=0; k<m_outerPackets; ++k)
+ nz += static_cast<Index>(m_hashmaps[k].size());
+ return nz;
+ }
+
+
+ protected:
+
+ HashMapType* m_hashmaps;
+ SparseMatrixType* mp_target;
+ Index m_outerPackets;
+ unsigned char m_keyBitsOffset;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_RANDOMSETTER_H