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Started to move the SparseCore module to evaluators: implemented assignment and cwise-unary evaluator

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Gael Guennebaud
2014-06-20 15:42:13 +02:00
parent 78bb808337
commit c415b627a7
6 changed files with 508 additions and 81 deletions
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93
Eigen/src/SparseCore/SparseMatrix.h
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@@ -1053,6 +1053,7 @@ void SparseMatrix<Scalar,_Options,_Index>::sumupDuplicates()
m_data.resize(m_outerIndex[m_outerSize]);
}
#ifndef EIGEN_TEST_EVALUATORS
template<typename Scalar, int _Options, typename _Index>
template<typename OtherDerived>
EIGEN_DONT_INLINE SparseMatrix<Scalar,_Options,_Index>& SparseMatrix<Scalar,_Options,_Index>::operator=(const SparseMatrixBase<OtherDerived>& other)
@@ -1114,6 +1115,71 @@ EIGEN_DONT_INLINE SparseMatrix<Scalar,_Options,_Index>& SparseMatrix<Scalar,_Opt
return Base::operator=(other.derived());
}
}
#else
template<typename Scalar, int _Options, typename _Index>
template<typename OtherDerived>
EIGEN_DONT_INLINE SparseMatrix<Scalar,_Options,_Index>& SparseMatrix<Scalar,_Options,_Index>::operator=(const SparseMatrixBase<OtherDerived>& other)
{
EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
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 evaluate it if needed
typedef typename internal::nested_eval<OtherDerived,2>::type OtherCopy;
typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
typedef internal::evaluator<_OtherCopy> OtherCopyEval;
OtherCopy otherCopy(other.derived());
OtherCopyEval otherCopyEval(otherCopy);
SparseMatrix dest(other.rows(),other.cols());
Eigen::Map<Matrix<Index, Dynamic, 1> > (dest.m_outerIndex,dest.outerSize()).setZero();
// pass 1
// FIXME the above copy could be merged with that pass
for (Index j=0; j<otherCopy.outerSize(); ++j)
for (typename OtherCopyEval::InnerIterator it(otherCopyEval, j); it; ++it)
++dest.m_outerIndex[it.index()];
// prefix sum
Index count = 0;
Matrix<Index,Dynamic,1> positions(dest.outerSize());
for (Index j=0; j<dest.outerSize(); ++j)
{
Index tmp = dest.m_outerIndex[j];
dest.m_outerIndex[j] = count;
positions[j] = count;
count += tmp;
}
dest.m_outerIndex[dest.outerSize()] = count;
// alloc
dest.m_data.resize(count);
// pass 2
for (Index j=0; j<otherCopy.outerSize(); ++j)
{
for (typename OtherCopyEval::InnerIterator it(otherCopyEval, j); it; ++it)
{
Index pos = positions[it.index()]++;
dest.m_data.index(pos) = j;
dest.m_data.value(pos) = it.value();
}
}
this->swap(dest);
return *this;
}
else
{
if(other.isRValue())
initAssignment(other.derived());
// there is no special optimization
return Base::operator=(other.derived());
}
}
#endif
template<typename _Scalar, int _Options, typename _Index>
EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& SparseMatrix<_Scalar,_Options,_Index>::insertUncompressed(Index row, Index col)
@@ -1254,6 +1320,33 @@ EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& Sparse
return (m_data.value(p) = 0);
}
#ifdef EIGEN_ENABLE_EVALUATORS
namespace internal {
template<typename _Scalar, int _Options, typename _Index>
struct evaluator<SparseMatrix<_Scalar,_Options,_Index> >
: evaluator_base<SparseMatrix<_Scalar,_Options,_Index> >
{
typedef SparseMatrix<_Scalar,_Options,_Index> SparseMatrixType;
typedef typename SparseMatrixType::InnerIterator InnerIterator;
typedef typename SparseMatrixType::ReverseInnerIterator ReverseInnerIterator;
enum {
CoeffReadCost = NumTraits<_Scalar>::ReadCost,
Flags = SparseMatrixType::Flags
};
evaluator(const SparseMatrixType &mat) : m_matrix(mat) {}
operator SparseMatrixType&() { return m_matrix.const_cast_derived(); }
operator const SparseMatrixType&() const { return m_matrix; }
const SparseMatrixType &m_matrix;
};
}
#endif
} // end namespace Eigen
#endif // EIGEN_SPARSEMATRIX_H