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Tobias Wood
2023-11-29 11:12:48 +00:00
parent 9ea520fc45
commit f38e16c193
534 changed files with 103368 additions and 116934 deletions
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740
Eigen/src/SparseCore/SparseVector.h
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@@ -13,25 +13,24 @@
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace Eigen {
/** \ingroup SparseCore_Module
* \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 TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN.
*/
* \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 TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN.
*/
namespace internal {
template<typename Scalar_, int Options_, typename StorageIndex_>
struct traits<SparseVector<Scalar_, Options_, StorageIndex_> >
{
template <typename Scalar_, int Options_, typename StorageIndex_>
struct traits<SparseVector<Scalar_, Options_, StorageIndex_> > {
typedef Scalar_ Scalar;
typedef StorageIndex_ StorageIndex;
typedef Sparse StorageKind;
@@ -49,452 +48,389 @@ struct traits<SparseVector<Scalar_, Options_, StorageIndex_> >
};
// Sparse-Vector-Assignment kinds:
enum {
SVA_RuntimeSwitch,
SVA_Inner,
SVA_Outer
};
enum { SVA_RuntimeSwitch, SVA_Inner, SVA_Outer };
template< typename Dest, typename Src,
int AssignmentKind = !bool(Src::IsVectorAtCompileTime) ? SVA_RuntimeSwitch
: Src::InnerSizeAtCompileTime==1 ? SVA_Outer
: SVA_Inner>
template <typename Dest, typename Src,
int AssignmentKind = !bool(Src::IsVectorAtCompileTime) ? SVA_RuntimeSwitch
: Src::InnerSizeAtCompileTime == 1 ? SVA_Outer
: SVA_Inner>
struct sparse_vector_assign_selector;
}
} // namespace internal
template<typename Scalar_, int Options_, typename StorageIndex_>
class SparseVector
: public SparseCompressedBase<SparseVector<Scalar_, Options_, StorageIndex_> >
{
typedef SparseCompressedBase<SparseVector> Base;
using Base::convert_index;
public:
EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector)
EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=)
EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=)
typedef internal::CompressedStorage<Scalar,StorageIndex> Storage;
enum { IsColVector = internal::traits<SparseVector>::IsColVector };
enum {
Options = Options_
};
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; }
template <typename Scalar_, int Options_, typename StorageIndex_>
class SparseVector : public SparseCompressedBase<SparseVector<Scalar_, Options_, StorageIndex_> > {
typedef SparseCompressedBase<SparseVector> Base;
using Base::convert_index;
EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return m_data.valuePtr(); }
EIGEN_STRONG_INLINE Scalar* valuePtr() { return m_data.valuePtr(); }
public:
EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector)
EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=)
EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=)
EIGEN_STRONG_INLINE const StorageIndex* innerIndexPtr() const { return m_data.indexPtr(); }
EIGEN_STRONG_INLINE StorageIndex* innerIndexPtr() { return m_data.indexPtr(); }
typedef internal::CompressedStorage<Scalar, StorageIndex> Storage;
enum { IsColVector = internal::traits<SparseVector>::IsColVector };
inline const StorageIndex* outerIndexPtr() const { return 0; }
inline StorageIndex* outerIndexPtr() { return 0; }
inline const StorageIndex* innerNonZeroPtr() const { return 0; }
inline StorageIndex* innerNonZeroPtr() { return 0; }
/** \internal */
inline Storage& data() { return m_data; }
/** \internal */
inline const Storage& data() const { return m_data; }
enum { Options = Options_ };
inline Scalar coeff(Index row, Index col) const
{
eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
return coeff(IsColVector ? row : col);
}
inline Scalar coeff(Index i) const
{
eigen_assert(i>=0 && i<m_size);
return m_data.at(StorageIndex(i));
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 const Scalar* valuePtr() const { return m_data.valuePtr(); }
EIGEN_STRONG_INLINE Scalar* valuePtr() { return m_data.valuePtr(); }
EIGEN_STRONG_INLINE const StorageIndex* innerIndexPtr() const { return m_data.indexPtr(); }
EIGEN_STRONG_INLINE StorageIndex* innerIndexPtr() { return m_data.indexPtr(); }
inline const StorageIndex* outerIndexPtr() const { return 0; }
inline StorageIndex* outerIndexPtr() { return 0; }
inline const StorageIndex* innerNonZeroPtr() const { return 0; }
inline StorageIndex* innerNonZeroPtr() { return 0; }
/** \internal */
inline Storage& data() { return m_data; }
/** \internal */
inline const Storage& data() const { return m_data; }
inline Scalar coeff(Index row, Index col) const {
eigen_assert(IsColVector ? (col == 0 && row >= 0 && row < m_size) : (row == 0 && col >= 0 && col < m_size));
return coeff(IsColVector ? row : col);
}
inline Scalar coeff(Index i) const {
eigen_assert(i >= 0 && i < m_size);
return m_data.at(StorageIndex(i));
}
inline Scalar& coeffRef(Index row, Index col) {
eigen_assert(IsColVector ? (col == 0 && row >= 0 && row < m_size) : (row == 0 && col >= 0 && col < m_size));
return coeffRef(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) {
eigen_assert(i >= 0 && i < m_size);
return m_data.atWithInsertion(StorageIndex(i));
}
public:
typedef typename Base::InnerIterator InnerIterator;
typedef typename Base::ReverseInnerIterator ReverseInnerIterator;
inline void setZero() { m_data.clear(); }
/** \returns the number of non zero coefficients */
inline Index nonZeros() const { return m_data.size(); }
inline void startVec(Index outer) {
EIGEN_UNUSED_VARIABLE(outer);
eigen_assert(outer == 0);
}
inline Scalar& insertBackByOuterInner(Index outer, Index inner) {
EIGEN_UNUSED_VARIABLE(outer);
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);
}
Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner) {
EIGEN_UNUSED_VARIABLE(outer);
eigen_assert(outer == 0);
return insertBackUnordered(inner);
}
inline Scalar& insertBackUnordered(Index i) {
m_data.append(0, i);
return m_data.value(m_data.size() - 1);
}
inline Scalar& insert(Index row, Index col) {
eigen_assert(IsColVector ? (col == 0 && row >= 0 && row < m_size) : (row == 0 && col >= 0 && col < m_size));
Index inner = IsColVector ? row : col;
Index outer = IsColVector ? col : row;
EIGEN_ONLY_USED_FOR_DEBUG(outer);
eigen_assert(outer == 0);
return insert(inner);
}
Scalar& insert(Index i) {
eigen_assert(i >= 0 && i < m_size);
Index startId = 0;
Index p = Index(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) = convert_index(i);
m_data.value(p + 1) = 0;
return m_data.value(p + 1);
}
inline Scalar& coeffRef(Index row, Index col)
{
eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
return coeffRef(IsColVector ? row : col);
}
/**
*/
inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }
/** \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)
{
eigen_assert(i>=0 && i<m_size);
inline void finalize() {}
return m_data.atWithInsertion(StorageIndex(i));
}
/** \copydoc SparseMatrix::prune(const Scalar&,const RealScalar&) */
Index prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) {
return prune([&](const Scalar& val) { return !internal::isMuchSmallerThan(val, reference, epsilon); });
}
public:
typedef typename Base::InnerIterator InnerIterator;
typedef typename Base::ReverseInnerIterator ReverseInnerIterator;
inline void setZero() { m_data.clear(); }
/** \returns the number of non zero coefficients */
inline Index nonZeros() const { return m_data.size(); }
inline void startVec(Index outer)
{
EIGEN_UNUSED_VARIABLE(outer);
eigen_assert(outer==0);
}
inline Scalar& insertBackByOuterInner(Index outer, Index inner)
{
EIGEN_UNUSED_VARIABLE(outer);
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);
}
Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner)
{
EIGEN_UNUSED_VARIABLE(outer);
eigen_assert(outer==0);
return insertBackUnordered(inner);
}
inline Scalar& insertBackUnordered(Index i)
{
m_data.append(0, i);
return m_data.value(m_data.size()-1);
}
inline Scalar& insert(Index row, Index col)
{
eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
Index inner = IsColVector ? row : col;
Index outer = IsColVector ? col : row;
EIGEN_ONLY_USED_FOR_DEBUG(outer);
eigen_assert(outer==0);
return insert(inner);
}
Scalar& insert(Index i)
{
eigen_assert(i>=0 && i<m_size);
Index startId = 0;
Index p = Index(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;
/**
* \brief Prunes the entries of the vector based on a `predicate`
* \tparam F Type of the predicate.
* \param keep_predicate The predicate that is used to test whether a value should be kept. A callable that
* gets passed om a `Scalar` value and returns a boolean. If the predicate returns true, the value is kept.
* \return The new number of structural non-zeros.
*/
template <class F>
Index prune(F&& keep_predicate) {
Index k = 0;
Index n = m_data.size();
for (Index i = 0; i < n; ++i) {
if (keep_predicate(m_data.value(i))) {
m_data.value(k) = std::move(m_data.value(i));
m_data.index(k) = m_data.index(i);
++k;
}
m_data.index(p+1) = convert_index(i);
m_data.value(p+1) = 0;
return m_data.value(p+1);
}
m_data.resize(k);
return k;
}
/**
*/
inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }
/** Resizes the sparse vector to \a rows x \a cols
*
* This method is provided for compatibility with matrices.
* For a column vector, \a cols must be equal to 1.
* For a row vector, \a rows must be equal to 1.
*
* \sa resize(Index)
*/
void resize(Index rows, Index cols) {
eigen_assert((IsColVector ? cols : rows) == 1 && "Outer dimension must equal 1");
resize(IsColVector ? rows : cols);
}
/** Resizes the sparse vector to \a newSize
* This method deletes all entries, thus leaving an empty sparse vector
*
* \sa conservativeResize(), setZero() */
void resize(Index newSize) {
m_size = newSize;
m_data.clear();
}
inline void finalize() {}
/** \copydoc SparseMatrix::prune(const Scalar&,const RealScalar&) */
Index prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) {
return prune([&](const Scalar& val){ return !internal::isMuchSmallerThan(val, reference, epsilon); });
/** Resizes the sparse vector to \a newSize, while leaving old values untouched.
*
* If the size of the vector is decreased, then the storage of the out-of bounds coefficients is kept and reserved.
* Call .data().squeeze() to free extra memory.
*
* \sa reserve(), setZero()
*/
void conservativeResize(Index newSize) {
if (newSize < m_size) {
Index i = 0;
while (i < m_data.size() && m_data.index(i) < newSize) ++i;
m_data.resize(i);
}
m_size = newSize;
}
/**
* \brief Prunes the entries of the vector based on a `predicate`
* \tparam F Type of the predicate.
* \param keep_predicate The predicate that is used to test whether a value should be kept. A callable that
* gets passed om a `Scalar` value and returns a boolean. If the predicate returns true, the value is kept.
* \return The new number of structural non-zeros.
*/
template<class F>
Index prune(F&& keep_predicate)
{
Index k = 0;
Index n = m_data.size();
for (Index i = 0; i < n; ++i)
{
if (keep_predicate(m_data.value(i)))
{
m_data.value(k) = std::move(m_data.value(i));
m_data.index(k) = m_data.index(i);
++k;
}
}
m_data.resize(k);
return k;
void resizeNonZeros(Index size) { m_data.resize(size); }
inline SparseVector() : m_size(0) { resize(0); }
explicit 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 SparseMatrixBase<OtherDerived>& other) : m_size(0) {
#ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
#endif
*this = other.derived();
}
inline SparseVector(const SparseVector& other) : Base(other), m_size(0) { *this = other.derived(); }
/** Swaps the values of \c *this and \a other.
* Overloaded for performance: this version performs a \em shallow swap by swapping pointers and attributes only.
* \sa SparseMatrixBase::swap()
*/
inline void swap(SparseVector& other) {
std::swap(m_size, other.m_size);
m_data.swap(other.m_data);
}
template <int OtherOptions>
inline void swap(SparseMatrix<Scalar, OtherOptions, StorageIndex>& other) {
eigen_assert(other.outerSize() == 1);
std::swap(m_size, other.m_innerSize);
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;
}
/** Resizes the sparse vector to \a rows x \a cols
*
* This method is provided for compatibility with matrices.
* For a column vector, \a cols must be equal to 1.
* For a row vector, \a rows must be equal to 1.
*
* \sa resize(Index)
*/
void resize(Index rows, Index cols)
{
eigen_assert((IsColVector ? cols : rows)==1 && "Outer dimension must equal 1");
resize(IsColVector ? rows : cols);
}
template <typename OtherDerived>
inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other) {
SparseVector tmp(other.size());
internal::sparse_vector_assign_selector<SparseVector, OtherDerived>::run(tmp, other.derived());
this->swap(tmp);
return *this;
}
/** Resizes the sparse vector to \a newSize
* This method deletes all entries, thus leaving an empty sparse vector
*
* \sa conservativeResize(), setZero() */
void resize(Index newSize)
{
m_size = newSize;
m_data.clear();
}
/** Resizes the sparse vector to \a newSize, while leaving old values untouched.
*
* If the size of the vector is decreased, then the storage of the out-of bounds coefficients is kept and reserved.
* Call .data().squeeze() to free extra memory.
*
* \sa reserve(), setZero()
*/
void conservativeResize(Index newSize)
{
if (newSize < m_size)
{
Index i = 0;
while (i<m_data.size() && m_data.index(i)<newSize) ++i;
m_data.resize(i);
}
m_size = newSize;
}
void resizeNonZeros(Index size) { m_data.resize(size); }
inline SparseVector() : m_size(0) { resize(0); }
explicit 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 SparseMatrixBase<OtherDerived>& other)
: m_size(0)
{
#ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
#endif
*this = other.derived();
}
inline SparseVector(const SparseVector& other)
: Base(other), m_size(0)
{
*this = other.derived();
}
/** Swaps the values of \c *this and \a other.
* Overloaded for performance: this version performs a \em shallow swap by swapping pointers and attributes only.
* \sa SparseMatrixBase::swap()
*/
inline void swap(SparseVector& other)
{
std::swap(m_size, other.m_size);
m_data.swap(other.m_data);
}
template<int OtherOptions>
inline void swap(SparseMatrix<Scalar,OtherOptions,StorageIndex>& other)
{
eigen_assert(other.outerSize()==1);
std::swap(m_size, other.m_innerSize);
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)
{
SparseVector tmp(other.size());
internal::sparse_vector_assign_selector<SparseVector,OtherDerived>::run(tmp,other.derived());
this->swap(tmp);
return *this;
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename Lhs, typename Rhs>
inline SparseVector& operator=(const SparseSparseProduct<Lhs,Rhs>& product)
{
return Base::operator=(product);
}
#endif
#ifndef EIGEN_NO_IO
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;
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
template <typename Lhs, typename Rhs>
inline SparseVector& operator=(const SparseSparseProduct<Lhs, Rhs>& product) {
return Base::operator=(product);
}
#endif
/** Destructor */
inline ~SparseVector() {}
#ifndef EIGEN_NO_IO
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;
}
#endif
/** Overloaded for performance */
Scalar sum() const;
/** Destructor */
inline ~SparseVector() {}
public:
/** Overloaded for performance */
Scalar sum() const;
/** \internal \deprecated use setZero() and reserve() */
EIGEN_DEPRECATED void startFill(Index reserve)
{
setZero();
m_data.reserve(reserve);
}
public:
/** \internal \deprecated use setZero() and reserve() */
EIGEN_DEPRECATED void startFill(Index reserve) {
setZero();
m_data.reserve(reserve);
}
/** \internal \deprecated use insertBack(Index,Index) */
EIGEN_DEPRECATED Scalar& fill(Index r, Index c)
{
eigen_assert(r==0 || c==0);
return fill(IsColVector ? r : c);
}
/** \internal \deprecated use insertBack(Index,Index) */
EIGEN_DEPRECATED Scalar& fill(Index r, Index c) {
eigen_assert(r == 0 || c == 0);
return fill(IsColVector ? r : c);
}
/** \internal \deprecated use insertBack(Index) */
EIGEN_DEPRECATED Scalar& fill(Index i)
{
m_data.append(0, i);
return m_data.value(m_data.size()-1);
}
/** \internal \deprecated use insertBack(Index) */
EIGEN_DEPRECATED Scalar& fill(Index i) {
m_data.append(0, i);
return m_data.value(m_data.size() - 1);
}
/** \internal \deprecated use insert(Index,Index) */
EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c)
{
eigen_assert(r==0 || c==0);
return fillrand(IsColVector ? r : c);
}
/** \internal \deprecated use insert(Index,Index) */
EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c) {
eigen_assert(r == 0 || c == 0);
return fillrand(IsColVector ? r : c);
}
/** \internal \deprecated use insert(Index) */
EIGEN_DEPRECATED Scalar& fillrand(Index i)
{
return insert(i);
}
/** \internal \deprecated use insert(Index) */
EIGEN_DEPRECATED Scalar& fillrand(Index i) { return insert(i); }
/** \internal \deprecated use finalize() */
EIGEN_DEPRECATED void endFill() {}
// These two functions were here in the 3.1 release, so let's keep them in case some code rely on them.
/** \internal \deprecated use data() */
EIGEN_DEPRECATED Storage& _data() { return m_data; }
/** \internal \deprecated use data() */
EIGEN_DEPRECATED const Storage& _data() const { return m_data; }
# ifdef EIGEN_SPARSEVECTOR_PLUGIN
# include EIGEN_SPARSEVECTOR_PLUGIN
# endif
/** \internal \deprecated use finalize() */
EIGEN_DEPRECATED void endFill() {}
protected:
EIGEN_STATIC_ASSERT(NumTraits<StorageIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE)
EIGEN_STATIC_ASSERT((Options_&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS)
// These two functions were here in the 3.1 release, so let's keep them in case some code rely on them.
/** \internal \deprecated use data() */
EIGEN_DEPRECATED Storage& _data() { return m_data; }
/** \internal \deprecated use data() */
EIGEN_DEPRECATED const Storage& _data() const { return m_data; }
Storage m_data;
Index m_size;
#ifdef EIGEN_SPARSEVECTOR_PLUGIN
#include EIGEN_SPARSEVECTOR_PLUGIN
#endif
protected:
EIGEN_STATIC_ASSERT(NumTraits<StorageIndex>::IsSigned, THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE)
EIGEN_STATIC_ASSERT((Options_ & (ColMajor | RowMajor)) == Options, INVALID_MATRIX_TEMPLATE_PARAMETERS)
Storage m_data;
Index m_size;
};
namespace internal {
template<typename Scalar_, int Options_, typename Index_>
struct evaluator<SparseVector<Scalar_,Options_,Index_> >
: evaluator_base<SparseVector<Scalar_,Options_,Index_> >
{
typedef SparseVector<Scalar_,Options_,Index_> SparseVectorType;
template <typename Scalar_, int Options_, typename Index_>
struct evaluator<SparseVector<Scalar_, Options_, Index_> > : evaluator_base<SparseVector<Scalar_, Options_, Index_> > {
typedef SparseVector<Scalar_, Options_, Index_> SparseVectorType;
typedef evaluator_base<SparseVectorType> Base;
typedef typename SparseVectorType::InnerIterator InnerIterator;
typedef typename SparseVectorType::ReverseInnerIterator ReverseInnerIterator;
enum {
CoeffReadCost = NumTraits<Scalar_>::ReadCost,
Flags = SparseVectorType::Flags
};
enum { CoeffReadCost = NumTraits<Scalar_>::ReadCost, Flags = SparseVectorType::Flags };
evaluator() : Base() {}
explicit evaluator(const SparseVectorType &mat) : m_matrix(&mat)
{
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
inline Index nonZerosEstimate() const {
return m_matrix->nonZeros();
}
explicit evaluator(const SparseVectorType& mat) : m_matrix(&mat) { EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); }
inline Index nonZerosEstimate() const { return m_matrix->nonZeros(); }
operator SparseVectorType&() { return m_matrix->const_cast_derived(); }
operator const SparseVectorType&() const { return *m_matrix; }
const SparseVectorType *m_matrix;
const SparseVectorType* m_matrix;
};
template< typename Dest, typename Src>
struct sparse_vector_assign_selector<Dest,Src,SVA_Inner> {
template <typename Dest, typename Src>
struct sparse_vector_assign_selector<Dest, Src, SVA_Inner> {
static void run(Dest& dst, const Src& src) {
eigen_internal_assert(src.innerSize()==src.size());
eigen_internal_assert(src.innerSize() == src.size());
typedef internal::evaluator<Src> SrcEvaluatorType;
SrcEvaluatorType srcEval(src);
for(typename SrcEvaluatorType::InnerIterator it(srcEval, 0); it; ++it)
dst.insert(it.index()) = it.value();
for (typename SrcEvaluatorType::InnerIterator it(srcEval, 0); it; ++it) dst.insert(it.index()) = it.value();
}
};
template< typename Dest, typename Src>
struct sparse_vector_assign_selector<Dest,Src,SVA_Outer> {
template <typename Dest, typename Src>
struct sparse_vector_assign_selector<Dest, Src, SVA_Outer> {
static void run(Dest& dst, const Src& src) {
eigen_internal_assert(src.outerSize()==src.size());
eigen_internal_assert(src.outerSize() == src.size());
typedef internal::evaluator<Src> SrcEvaluatorType;
SrcEvaluatorType srcEval(src);
for(Index i=0; i<src.size(); ++i)
{
for (Index i = 0; i < src.size(); ++i) {
typename SrcEvaluatorType::InnerIterator it(srcEval, i);
if(it)
dst.insert(i) = it.value();
if (it) dst.insert(i) = it.value();
}
}
};
template< typename Dest, typename Src>
struct sparse_vector_assign_selector<Dest,Src,SVA_RuntimeSwitch> {
template <typename Dest, typename Src>
struct sparse_vector_assign_selector<Dest, Src, SVA_RuntimeSwitch> {
static void run(Dest& dst, const Src& src) {
if(src.outerSize()==1) sparse_vector_assign_selector<Dest,Src,SVA_Inner>::run(dst, src);
else sparse_vector_assign_selector<Dest,Src,SVA_Outer>::run(dst, src);
if (src.outerSize() == 1)
sparse_vector_assign_selector<Dest, Src, SVA_Inner>::run(dst, src);
else
sparse_vector_assign_selector<Dest, Src, SVA_Outer>::run(dst, src);
}
};
}
} // namespace internal
// Specialization for SparseVector.
// Serializes [size, numNonZeros, innerIndices, values].
@@ -509,12 +445,10 @@ class Serializer<SparseVector<Scalar, Options, StorageIndex>, void> {
};
EIGEN_DEVICE_FUNC size_t size(const SparseMat& value) const {
return sizeof(Header) +
(sizeof(Scalar) + sizeof(StorageIndex)) * value.nonZeros();
return sizeof(Header) + (sizeof(Scalar) + sizeof(StorageIndex)) * value.nonZeros();
}
EIGEN_DEVICE_FUNC uint8_t* serialize(uint8_t* dest, uint8_t* end,
const SparseMat& value) {
EIGEN_DEVICE_FUNC uint8_t* serialize(uint8_t* dest, uint8_t* end, const SparseMat& value) {
if (EIGEN_PREDICT_FALSE(dest == nullptr)) return nullptr;
if (EIGEN_PREDICT_FALSE(dest + size(value) > end)) return nullptr;
@@ -537,9 +471,7 @@ class Serializer<SparseVector<Scalar, Options, StorageIndex>, void> {
return dest;
}
EIGEN_DEVICE_FUNC const uint8_t* deserialize(const uint8_t* src,
const uint8_t* end,
SparseMat& value) const {
EIGEN_DEVICE_FUNC const uint8_t* deserialize(const uint8_t* src, const uint8_t* end, SparseMat& value) const {
if (EIGEN_PREDICT_FALSE(src == nullptr)) return nullptr;
if (EIGEN_PREDICT_FALSE(src + sizeof(Header) > end)) return nullptr;
@@ -568,6 +500,6 @@ class Serializer<SparseVector<Scalar, Options, StorageIndex>, void> {
}
};
} // end namespace Eigen
} // end namespace Eigen
#endif // EIGEN_SPARSEVECTOR_H
#endif // EIGEN_SPARSEVECTOR_H