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Tobias Wood
@@ -14,64 +14,60 @@
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// IWYU pragma: private
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#include "./InternalHeaderCheck.h"
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namespace Eigen {
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namespace Eigen {
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namespace internal {
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template<typename MatrixType>
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struct traits<SparseView<MatrixType> > : traits<MatrixType>
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{
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template <typename MatrixType>
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struct traits<SparseView<MatrixType> > : traits<MatrixType> {
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typedef typename MatrixType::StorageIndex StorageIndex;
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typedef Sparse StorageKind;
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enum {
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Flags = int(traits<MatrixType>::Flags) & (RowMajorBit)
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};
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enum { Flags = int(traits<MatrixType>::Flags) & (RowMajorBit) };
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};
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} // end namespace internal
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} // end namespace internal
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/** \ingroup SparseCore_Module
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* \class SparseView
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*
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* \brief Expression of a dense or sparse matrix with zero or too small values removed
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*
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* \tparam MatrixType the type of the object of which we are removing the small entries
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*
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* This class represents an expression of a given dense or sparse matrix with
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* entries smaller than \c reference * \c epsilon are removed.
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* It is the return type of MatrixBase::sparseView() and SparseMatrixBase::pruned()
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* and most of the time this is the only way it is used.
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*
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* \sa MatrixBase::sparseView(), SparseMatrixBase::pruned()
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*/
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template<typename MatrixType>
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class SparseView : public SparseMatrixBase<SparseView<MatrixType> >
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{
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* \class SparseView
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*
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* \brief Expression of a dense or sparse matrix with zero or too small values removed
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*
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* \tparam MatrixType the type of the object of which we are removing the small entries
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*
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* This class represents an expression of a given dense or sparse matrix with
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* entries smaller than \c reference * \c epsilon are removed.
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* It is the return type of MatrixBase::sparseView() and SparseMatrixBase::pruned()
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* and most of the time this is the only way it is used.
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*
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* \sa MatrixBase::sparseView(), SparseMatrixBase::pruned()
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*/
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template <typename MatrixType>
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class SparseView : public SparseMatrixBase<SparseView<MatrixType> > {
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typedef typename MatrixType::Nested MatrixTypeNested;
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typedef internal::remove_all_t<MatrixTypeNested> MatrixTypeNested_;
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typedef SparseMatrixBase<SparseView > Base;
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public:
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typedef SparseMatrixBase<SparseView> Base;
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public:
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EIGEN_SPARSE_PUBLIC_INTERFACE(SparseView)
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typedef internal::remove_all_t<MatrixType> NestedExpression;
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explicit SparseView(const MatrixType& mat, const Scalar& reference = Scalar(0),
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const RealScalar &epsilon = NumTraits<Scalar>::dummy_precision())
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: m_matrix(mat), m_reference(reference), m_epsilon(epsilon) {}
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const RealScalar& epsilon = NumTraits<Scalar>::dummy_precision())
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: m_matrix(mat), m_reference(reference), m_epsilon(epsilon) {}
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inline Index rows() const { return m_matrix.rows(); }
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inline Index cols() const { return m_matrix.cols(); }
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inline Index innerSize() const { return m_matrix.innerSize(); }
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inline Index outerSize() const { return m_matrix.outerSize(); }
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/** \returns the nested expression */
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const internal::remove_all_t<MatrixTypeNested>&
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nestedExpression() const { return m_matrix; }
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const internal::remove_all_t<MatrixTypeNested>& nestedExpression() const { return m_matrix; }
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Scalar reference() const { return m_reference; }
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RealScalar epsilon() const { return m_epsilon; }
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protected:
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protected:
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MatrixTypeNested m_matrix;
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Scalar m_reference;
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RealScalar m_epsilon;
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@@ -82,176 +78,148 @@ namespace internal {
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// TODO find a way to unify the two following variants
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// This is tricky because implementing an inner iterator on top of an IndexBased evaluator is
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// not easy because the evaluators do not expose the sizes of the underlying expression.
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template<typename ArgType>
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struct unary_evaluator<SparseView<ArgType>, IteratorBased>
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: public evaluator_base<SparseView<ArgType> >
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{
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typedef typename evaluator<ArgType>::InnerIterator EvalIterator;
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public:
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typedef SparseView<ArgType> XprType;
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class InnerIterator : public EvalIterator
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{
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protected:
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typedef typename XprType::Scalar Scalar;
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public:
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EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer)
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: EvalIterator(sve.m_argImpl,outer), m_view(sve.m_view)
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{
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incrementToNonZero();
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}
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template <typename ArgType>
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struct unary_evaluator<SparseView<ArgType>, IteratorBased> : public evaluator_base<SparseView<ArgType> > {
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typedef typename evaluator<ArgType>::InnerIterator EvalIterator;
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EIGEN_STRONG_INLINE InnerIterator& operator++()
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{
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EvalIterator::operator++();
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incrementToNonZero();
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return *this;
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}
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public:
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typedef SparseView<ArgType> XprType;
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using EvalIterator::value;
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protected:
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const XprType &m_view;
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private:
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void incrementToNonZero()
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{
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while((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.reference(), m_view.epsilon()))
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{
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EvalIterator::operator++();
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}
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}
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};
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enum {
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CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
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Flags = XprType::Flags
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};
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explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {}
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protected:
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evaluator<ArgType> m_argImpl;
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const XprType &m_view;
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};
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template<typename ArgType>
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struct unary_evaluator<SparseView<ArgType>, IndexBased>
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: public evaluator_base<SparseView<ArgType> >
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{
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public:
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typedef SparseView<ArgType> XprType;
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protected:
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enum { IsRowMajor = (XprType::Flags&RowMajorBit)==RowMajorBit };
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class InnerIterator : public EvalIterator {
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protected:
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typedef typename XprType::Scalar Scalar;
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typedef typename XprType::StorageIndex StorageIndex;
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public:
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class InnerIterator
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{
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public:
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EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer)
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: m_sve(sve), m_inner(0), m_outer(outer), m_end(sve.m_view.innerSize())
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{
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incrementToNonZero();
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}
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public:
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EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer)
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: EvalIterator(sve.m_argImpl, outer), m_view(sve.m_view) {
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incrementToNonZero();
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}
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EIGEN_STRONG_INLINE InnerIterator& operator++()
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{
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m_inner++;
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incrementToNonZero();
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return *this;
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}
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EIGEN_STRONG_INLINE InnerIterator& operator++() {
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EvalIterator::operator++();
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incrementToNonZero();
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return *this;
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}
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EIGEN_STRONG_INLINE Scalar value() const
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{
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return (IsRowMajor) ? m_sve.m_argImpl.coeff(m_outer, m_inner)
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: m_sve.m_argImpl.coeff(m_inner, m_outer);
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}
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using EvalIterator::value;
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EIGEN_STRONG_INLINE StorageIndex index() const { return m_inner; }
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inline Index row() const { return IsRowMajor ? m_outer : index(); }
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inline Index col() const { return IsRowMajor ? index() : m_outer; }
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protected:
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const XprType& m_view;
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EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
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private:
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void incrementToNonZero() {
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while ((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.reference(), m_view.epsilon())) {
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EvalIterator::operator++();
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}
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}
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};
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protected:
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const unary_evaluator &m_sve;
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Index m_inner;
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const Index m_outer;
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const Index m_end;
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enum { CoeffReadCost = evaluator<ArgType>::CoeffReadCost, Flags = XprType::Flags };
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private:
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void incrementToNonZero()
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{
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while((bool(*this)) && internal::isMuchSmallerThan(value(), m_sve.m_view.reference(), m_sve.m_view.epsilon()))
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{
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m_inner++;
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}
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}
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};
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enum {
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CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
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Flags = XprType::Flags
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};
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explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {}
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explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {}
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protected:
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evaluator<ArgType> m_argImpl;
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const XprType &m_view;
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protected:
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evaluator<ArgType> m_argImpl;
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const XprType& m_view;
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};
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} // end namespace internal
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template <typename ArgType>
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struct unary_evaluator<SparseView<ArgType>, IndexBased> : public evaluator_base<SparseView<ArgType> > {
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public:
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typedef SparseView<ArgType> XprType;
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protected:
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enum { IsRowMajor = (XprType::Flags & RowMajorBit) == RowMajorBit };
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typedef typename XprType::Scalar Scalar;
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typedef typename XprType::StorageIndex StorageIndex;
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public:
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class InnerIterator {
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public:
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EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer)
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: m_sve(sve), m_inner(0), m_outer(outer), m_end(sve.m_view.innerSize()) {
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incrementToNonZero();
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}
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EIGEN_STRONG_INLINE InnerIterator& operator++() {
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m_inner++;
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incrementToNonZero();
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return *this;
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}
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EIGEN_STRONG_INLINE Scalar value() const {
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return (IsRowMajor) ? m_sve.m_argImpl.coeff(m_outer, m_inner) : m_sve.m_argImpl.coeff(m_inner, m_outer);
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}
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EIGEN_STRONG_INLINE StorageIndex index() const { return m_inner; }
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inline Index row() const { return IsRowMajor ? m_outer : index(); }
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inline Index col() const { return IsRowMajor ? index() : m_outer; }
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EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner >= 0; }
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protected:
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const unary_evaluator& m_sve;
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Index m_inner;
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const Index m_outer;
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const Index m_end;
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private:
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void incrementToNonZero() {
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while ((bool(*this)) && internal::isMuchSmallerThan(value(), m_sve.m_view.reference(), m_sve.m_view.epsilon())) {
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m_inner++;
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}
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}
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};
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enum { CoeffReadCost = evaluator<ArgType>::CoeffReadCost, Flags = XprType::Flags };
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explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {}
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protected:
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evaluator<ArgType> m_argImpl;
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const XprType& m_view;
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};
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} // end namespace internal
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/** \ingroup SparseCore_Module
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*
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* \returns a sparse expression of the dense expression \c *this with values smaller than
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* \a reference * \a epsilon removed.
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*
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* This method is typically used when prototyping to convert a quickly assembled dense Matrix \c D to a SparseMatrix \c S:
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* \code
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* MatrixXd D(n,m);
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* SparseMatrix<double> S;
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* S = D.sparseView(); // suppress numerical zeros (exact)
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* S = D.sparseView(reference);
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* S = D.sparseView(reference,epsilon);
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* \endcode
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* where \a reference is a meaningful non zero reference value,
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* and \a epsilon is a tolerance factor defaulting to NumTraits<Scalar>::dummy_precision().
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*
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* \sa SparseMatrixBase::pruned(), class SparseView */
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template<typename Derived>
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*
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* \returns a sparse expression of the dense expression \c *this with values smaller than
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* \a reference * \a epsilon removed.
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*
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* This method is typically used when prototyping to convert a quickly assembled dense Matrix \c D to a SparseMatrix \c
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* S: \code MatrixXd D(n,m); SparseMatrix<double> S; S = D.sparseView(); // suppress numerical zeros (exact)
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* S = D.sparseView(reference);
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* S = D.sparseView(reference,epsilon);
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* \endcode
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* where \a reference is a meaningful non zero reference value,
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* and \a epsilon is a tolerance factor defaulting to NumTraits<Scalar>::dummy_precision().
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*
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* \sa SparseMatrixBase::pruned(), class SparseView */
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template <typename Derived>
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const SparseView<Derived> MatrixBase<Derived>::sparseView(const Scalar& reference,
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const typename NumTraits<Scalar>::Real& epsilon) const
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{
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const typename NumTraits<Scalar>::Real& epsilon) const {
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return SparseView<Derived>(derived(), reference, epsilon);
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}
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/** \returns an expression of \c *this with values smaller than
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* \a reference * \a epsilon removed.
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*
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* This method is typically used in conjunction with the product of two sparse matrices
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* to automatically prune the smallest values as follows:
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* \code
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* C = (A*B).pruned(); // suppress numerical zeros (exact)
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* C = (A*B).pruned(ref);
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* C = (A*B).pruned(ref,epsilon);
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* \endcode
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* where \c ref is a meaningful non zero reference value.
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* */
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template<typename Derived>
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const SparseView<Derived>
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SparseMatrixBase<Derived>::pruned(const Scalar& reference,
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const RealScalar& epsilon) const
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{
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* \a reference * \a epsilon removed.
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*
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* This method is typically used in conjunction with the product of two sparse matrices
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* to automatically prune the smallest values as follows:
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* \code
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* C = (A*B).pruned(); // suppress numerical zeros (exact)
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* C = (A*B).pruned(ref);
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* C = (A*B).pruned(ref,epsilon);
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* \endcode
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* where \c ref is a meaningful non zero reference value.
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* */
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template <typename Derived>
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const SparseView<Derived> SparseMatrixBase<Derived>::pruned(const Scalar& reference, const RealScalar& epsilon) const {
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return SparseView<Derived>(derived(), reference, epsilon);
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}
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} // end namespace Eigen
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} // end namespace Eigen
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#endif
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