SparseVector.h

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2015 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/.
// SPDX-License-Identifier: MPL-2.0
 
#ifndef EIGEN_SPARSEVECTOR_H
#define EIGEN_SPARSEVECTOR_H
 
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
 
namespace Eigen {

 
namespace internal {
template <typename Scalar_, int Options_, typename StorageIndex_>
struct traits<SparseVector<Scalar_, Options_, StorageIndex_> > {
  using Scalar = Scalar_;
  using StorageIndex = StorageIndex_;
  using StorageKind = Sparse;
  using XprKind = MatrixXpr;
  enum {
    IsColVector = (Options_ & RowMajorBit) ? 0 : 1,
 
    RowsAtCompileTime = IsColVector ? Dynamic : 1,
    ColsAtCompileTime = IsColVector ? 1 : Dynamic,
    MaxRowsAtCompileTime = RowsAtCompileTime,
    MaxColsAtCompileTime = ColsAtCompileTime,
    Flags = Options_ | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit) | CompressedAccessBit,
    SupportedAccessPatterns = InnerRandomAccessPattern
  };
};
 
// Sparse-Vector-Assignment kinds:
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>
struct sparse_vector_assign_selector;
 
}  // namespace internal
 
template <typename Scalar_, int Options_, typename StorageIndex_>
class SparseVector : public SparseCompressedBase<SparseVector<Scalar_, Options_, StorageIndex_> > {
  using Base = SparseCompressedBase<SparseVector>;
  using Base::convert_index;
 
 public:
  EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector)
  EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=)
  EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=)
 
  using Storage = internal::CompressedStorage<Scalar, StorageIndex>;
  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; }
 
  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; }

  constexpr Storage& data() { return m_data; }
  constexpr 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);
  }

  inline Scalar& coeffRef(Index i) {
    eigen_assert(i >= 0 && i < m_size);
 
    return m_data.atWithInsertion(StorageIndex(i));
  }
 
 public:
  using InnerIterator = typename Base::InnerIterator;
  using ReverseInnerIterator = typename Base::ReverseInnerIterator;
 
  inline void setZero() { m_data.clear(); }

  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(Scalar(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(Scalar(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: implement smart reallocation.
    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) = Scalar(0);
    return m_data.value(p + 1);
  }
 
  inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }
 
  inline void finalize() {}

  Index prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) {
    return prune([&](const Scalar& val) { return !internal::isMuchSmallerThan(val, reference, epsilon); });
  }

  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 resize(Index rows, Index cols) {
    eigen_assert((IsColVector ? cols : rows) == 1 && "Outer dimension must equal 1");
    resize(IsColVector ? rows : cols);
  }

  void resize(NoChange_t, Index cols) { resize(rows(), cols); }

  void resize(Index rows, NoChange_t) { resize(rows, cols()); }

  void resize(Index newSize) {
    m_size = newSize;
    m_data.clear();
  }

  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(); }

  inline void swap(SparseVector& other) {
    std::swap(m_size, other.m_size);
    m_data.swap(other.m_data);
  }
  friend EIGEN_DEVICE_FUNC void swap(SparseVector& a, SparseVector& b) { a.swap(b); }
 
  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);
  }
  template <int OtherOptions>
  friend EIGEN_DEVICE_FUNC void swap(SparseVector& a, SparseMatrix<Scalar, OtherOptions, StorageIndex>& b) {
    a.swap(b);
  }
  template <int OtherOptions>
  friend EIGEN_DEVICE_FUNC void swap(SparseMatrix<Scalar, OtherOptions, StorageIndex>& a, SparseVector& b) {
    b.swap(a);
  }
 
  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;
  }
 
  inline SparseVector(SparseVector&& other) : SparseVector() { this->swap(other); }
 
  template <typename OtherDerived>
  inline SparseVector(SparseCompressedBase<OtherDerived>&& other) : SparseVector() {
    *this = other.derived().markAsRValue();
  }
 
  inline SparseVector& operator=(SparseVector&& other) {
    this->swap(other);
    return *this;
  }
 
  template <typename OtherDerived>
  inline SparseVector& operator=(SparseCompressedBase<OtherDerived>&& other) {
    *this = other.derived().markAsRValue();
    return *this;
  }
 
#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

  Scalar sum() const;
 
 public:
  EIGEN_DEPRECATED_WITH_REASON("Use .setZero() and .reserve() instead.") void startFill(Index reserve) {
    setZero();
    m_data.reserve(reserve);
  }

  EIGEN_DEPRECATED_WITH_REASON("Use .insertBack() instead.") Scalar& fill(Index r, Index c) {
    eigen_assert(r == 0 || c == 0);
    return fill(IsColVector ? r : c);
  }

  EIGEN_DEPRECATED_WITH_REASON("Use .insertBack() instead.") Scalar& fill(Index i) {
    m_data.append(Scalar(0), i);
    return m_data.value(m_data.size() - 1);
  }

  EIGEN_DEPRECATED_WITH_REASON("Use .insert() instead.") Scalar& fillrand(Index r, Index c) {
    eigen_assert(r == 0 || c == 0);
    return fillrand(IsColVector ? r : c);
  }

  EIGEN_DEPRECATED_WITH_REASON("Use .insert() instead.") Scalar& fillrand(Index i) { return insert(i); }

  EIGEN_DEPRECATED_WITH_REASON("Use .finalize() instead.") void endFill() {}
 
  // These two functions were here in the 3.1 release, so let's keep them in case some code relies on them.
  EIGEN_DEPRECATED_WITH_REASON("Use .data() instead.") Storage& _data() { return m_data; }
  EIGEN_DEPRECATED_WITH_REASON("Use .data() instead.") const Storage& _data() const { return m_data; }
 
#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_> > {
  using SparseVectorType = SparseVector<Scalar_, Options_, Index_>;
  using Base = evaluator_base<SparseVectorType>;
  using InnerIterator = typename SparseVectorType::InnerIterator;
  using ReverseInnerIterator = typename SparseVectorType::ReverseInnerIterator;
 
  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(); }
 
  operator SparseVectorType&() { return m_matrix->const_cast_derived(); }
  operator const SparseVectorType&() const { return *m_matrix; }
 
  const SparseVectorType* m_matrix;
};
 
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());
    using SrcEvaluatorType = internal::evaluator<Src>;
    SrcEvaluatorType srcEval(src);
    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> {
  static void run(Dest& dst, const Src& src) {
    eigen_internal_assert(src.outerSize() == src.size());
    using SrcEvaluatorType = internal::evaluator<Src>;
    SrcEvaluatorType srcEval(src);
    for (Index i = 0; i < src.size(); ++i) {
      typename SrcEvaluatorType::InnerIterator it(srcEval, i);
      if (it) dst.insert(i) = it.value();
    }
  }
};
 
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);
  }
};
 
}  // namespace internal
 
// Specialization for SparseVector.
// Serializes [size, numNonZeros, innerIndices, values].
template <typename Scalar, int Options, typename StorageIndex>
class Serializer<SparseVector<Scalar, Options, StorageIndex>, void> {
 public:
  using SparseMat = SparseVector<Scalar, Options, StorageIndex>;
 
  struct Header {
    typename SparseMat::Index size;
    Index num_non_zeros;
  };
 
  EIGEN_DEVICE_FUNC size_t size(const SparseMat& value) const {
    return sizeof(Header) + (sizeof(Scalar) + sizeof(StorageIndex)) * value.nonZeros();
  }
 
  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;
 
    const size_t header_bytes = sizeof(Header);
    Header header = {value.innerSize(), value.nonZeros()};
    EIGEN_USING_STD(memcpy)
    memcpy(dest, &header, header_bytes);
    dest += header_bytes;
 
    // Inner indices.
    std::size_t data_bytes = sizeof(StorageIndex) * header.num_non_zeros;
    if (data_bytes != 0) {
      memcpy(dest, value.innerIndexPtr(), data_bytes);
    }
    dest += data_bytes;
 
    // Values.
    data_bytes = sizeof(Scalar) * header.num_non_zeros;
    if (data_bytes != 0) {
      memcpy(dest, value.valuePtr(), data_bytes);
    }
    dest += data_bytes;
 
    return dest;
  }
 
  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;
 
    const size_t header_bytes = sizeof(Header);
    Header header;
    EIGEN_USING_STD(memcpy)
    memcpy(&header, src, header_bytes);
    src += header_bytes;
 
    value.setZero();
    value.resize(header.size);
    value.resizeNonZeros(header.num_non_zeros);
 
    // Inner indices.
    std::size_t data_bytes = sizeof(StorageIndex) * header.num_non_zeros;
    if (EIGEN_PREDICT_FALSE(src + data_bytes > end)) return nullptr;
    if (data_bytes != 0) {
      memcpy(value.innerIndexPtr(), src, data_bytes);
    }
    src += data_bytes;
 
    // Values.
    data_bytes = sizeof(Scalar) * header.num_non_zeros;
    if (EIGEN_PREDICT_FALSE(src + data_bytes > end)) return nullptr;
    if (data_bytes != 0) {
      memcpy(value.valuePtr(), src, data_bytes);
    }
    src += data_bytes;
    return src;
  }
};
 
}  // end namespace Eigen
 
#endif  // EIGEN_SPARSEVECTOR_H