move sparse solvers from unsupported/ to main Eigen/ and remove the "not stable yet" warning

1 files changed, 431 insertions, 0 deletions

diff --git a/Eigen/src/SparseCore/SparseVector.h b/Eigen/src/SparseCore/SparseVector.h
new file mode 100644
index 000000000..ce4bb51a2
--- /dev/null
+++ b/Eigen/src/SparseCore/SparseVector.h
@@ -0,0 +1,431 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.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
+  *
+  * \tparam _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.
+  *
+  * This class can be extended with the help of the plugin mechanism described on the page
+  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN.
+  */
+
+namespace internal {
+template<typename _Scalar, int _Options, typename _Index>
+struct traits<SparseVector<_Scalar, _Options, _Index> >
+{
+  typedef _Scalar Scalar;
+  typedef _Index Index;
+  typedef Sparse StorageKind;
+  typedef MatrixXpr XprKind;
+  enum {
+    IsColVector = _Options & RowMajorBit ? 0 : 1,
+
+    RowsAtCompileTime = IsColVector ? Dynamic : 1,
+    ColsAtCompileTime = IsColVector ? 1 : Dynamic,
+    MaxRowsAtCompileTime = RowsAtCompileTime,
+    MaxColsAtCompileTime = ColsAtCompileTime,
+    Flags = _Options | NestByRefBit | LvalueBit,
+    CoeffReadCost = NumTraits<Scalar>::ReadCost,
+    SupportedAccessPatterns = InnerRandomAccessPattern
+  };
+};
+}
+
+template<typename _Scalar, int _Options, typename _Index>
+class SparseVector
+  : public SparseMatrixBase<SparseVector<_Scalar, _Options, _Index> >
+{
+  public:
+    EIGEN_SPARSE_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 = internal::traits<SparseVector>::IsColVector };
+    
+    enum {
+      Options = _Options
+    };
+
+    CompressedStorage<Scalar,Index> m_data;
+    Index m_size;
+
+    CompressedStorage<Scalar,Index>& _data() { return m_data; }
+    CompressedStorage<Scalar,Index>& _data() const { return m_data; }
+
+  public:
+
+    EIGEN_STRONG_INLINE Index rows() const { return IsColVector ? m_size : 1; }
+    EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; }
+    EIGEN_STRONG_INLINE Index innerSize() const { return m_size; }
+    EIGEN_STRONG_INLINE Index outerSize() const { return 1; }
+    EIGEN_STRONG_INLINE Index innerNonZeros(Index j) const { eigen_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 Index* _innerIndexPtr() const { return &m_data.index(0); }
+    EIGEN_STRONG_INLINE Index* _innerIndexPtr() { return &m_data.index(0); }
+
+    inline Scalar coeff(Index row, Index col) const
+    {
+      eigen_assert((IsColVector ? col : row)==0);
+      return coeff(IsColVector ? row : col);
+    }
+    inline Scalar coeff(Index i) const { return m_data.at(i); }
+
+    inline Scalar& coeffRef(Index row, Index col)
+    {
+      eigen_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(Index i)
+    {
+      return m_data.atWithInsertion(i);
+    }
+
+  public:
+
+    class InnerIterator;
+
+    inline void setZero() { m_data.clear(); }
+
+    /** \returns the number of non zero coefficients */
+    inline Index nonZeros() const  { return static_cast<Index>(m_data.size()); }
+
+    inline void startVec(Index outer)
+    {
+      eigen_assert(outer==0);
+    }
+
+    inline Scalar& insertBackByOuterInner(Index outer, Index inner)
+    {
+      eigen_assert(outer==0);
+      return insertBack(inner);
+    }
+    inline Scalar& insertBack(Index i)
+    {
+      m_data.append(0, i);
+      return m_data.value(m_data.size()-1);
+    }
+
+    inline Scalar& insert(Index row, Index col)
+    {
+      Index inner = IsColVector ? row : col;
+      Index outer = IsColVector ? col : row;
+      eigen_assert(outer==0);
+      return insert(inner);
+    }
+    Scalar& insert(Index i)
+    {
+      Index startId = 0;
+      Index p = m_data.size() - 1;
+      // TODO smart realloc
+      m_data.resize(p+2,1);
+
+      while ( (p >= startId) && (m_data.index(p) > i) )
+      {
+        m_data.index(p+1) = m_data.index(p);
+        m_data.value(p+1) = m_data.value(p);
+        --p;
+      }
+      m_data.index(p+1) = i;
+      m_data.value(p+1) = 0;
+      return m_data.value(p+1);
+    }
+
+    /**
+      */
+    inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }
+
+
+    inline void finalize() {}
+
+    void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
+    {
+      m_data.prune(reference,epsilon);
+    }
+
+    void resize(Index rows, Index cols)
+    {
+      eigen_assert(rows==1 || cols==1);
+      resize(IsColVector ? rows : cols);
+    }
+
+    void resize(Index newSize)
+    {
+      m_size = newSize;
+      m_data.clear();
+    }
+
+    void resizeNonZeros(Index size) { m_data.resize(size); }
+
+    inline SparseVector() : m_size(0) { resize(0); }
+
+    inline SparseVector(Index size) : m_size(0) { resize(size); }
+
+    inline SparseVector(Index rows, Index 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)
+    {
+      if (int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime))
+        return Base::operator=(other.transpose());
+      else
+        return Base::operator=(other);
+    }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename Lhs, typename Rhs>
+    inline SparseVector& operator=(const SparseSparseProduct<Lhs,Rhs>& product)
+    {
+      return Base::operator=(product);
+    }
+    #endif
+
+//       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 internal::nested<OtherDerived,2>::type OtherCopy;
+//         OtherCopy otherCopy(other.derived());
+//         typedef typename internal::remove_all<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 (Index 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) * internal::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() {}
+
+    /** Overloaded for performance */
+    Scalar sum() const;
+
+  public:
+
+    /** \deprecated use setZero() and reserve() */
+    EIGEN_DEPRECATED void startFill(Index reserve)
+    {
+      setZero();
+      m_data.reserve(reserve);
+    }
+
+    /** \deprecated use insertBack(Index,Index) */
+    EIGEN_DEPRECATED Scalar& fill(Index r, Index c)
+    {
+      eigen_assert(r==0 || c==0);
+      return fill(IsColVector ? r : c);
+    }
+
+    /** \deprecated use insertBack(Index) */
+    EIGEN_DEPRECATED Scalar& fill(Index i)
+    {
+      m_data.append(0, i);
+      return m_data.value(m_data.size()-1);
+    }
+
+    /** \deprecated use insert(Index,Index) */
+    EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c)
+    {
+      eigen_assert(r==0 || c==0);
+      return fillrand(IsColVector ? r : c);
+    }
+
+    /** \deprecated use insert(Index) */
+    EIGEN_DEPRECATED Scalar& fillrand(Index i)
+    {
+      return insert(i);
+    }
+
+    /** \deprecated use finalize() */
+    EIGEN_DEPRECATED void endFill() {}
+    
+#   ifdef EIGEN_SPARSEVECTOR_PLUGIN
+#     include EIGEN_SPARSEVECTOR_PLUGIN
+#   endif
+};
+
+template<typename Scalar, int _Options, typename _Index>
+class SparseVector<Scalar,_Options,_Index>::InnerIterator
+{
+  public:
+    InnerIterator(const SparseVector& vec, Index outer=0)
+      : m_data(vec.m_data), m_id(0), m_end(static_cast<Index>(m_data.size()))
+    {
+      eigen_assert(outer==0);
+    }
+
+    InnerIterator(const CompressedStorage<Scalar,Index>& data)
+      : m_data(data), m_id(0), m_end(static_cast<Index>(m_data.size()))
+    {}
+
+    template<unsigned int Added, unsigned int Removed>
+    InnerIterator(const Flagged<SparseVector,Added,Removed>& vec, Index )
+      : 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 Index index() const { return m_data.index(m_id); }
+    inline Index row() const { return IsColVector ? index() : 0; }
+    inline Index col() const { return IsColVector ? 0 : index(); }
+
+    inline operator bool() const { return (m_id < m_end); }
+
+  protected:
+    const CompressedStorage<Scalar,Index>& m_data;
+    Index m_id;
+    const Index m_end;
+};
+
+#endif // EIGEN_SPARSEVECTOR_H