// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 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_SPARSEUTIL_H
#define EIGEN_SPARSEUTIL_H

// IWYU pragma: private
#include "./InternalHeaderCheck.h"

namespace Eigen {

#ifdef NDEBUG
#define EIGEN_DBG_SPARSE(X)
#else
#define EIGEN_DBG_SPARSE(X) X
#endif

#define EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, Op)                                    \
  template <typename OtherDerived>                                                               \
  EIGEN_STRONG_INLINE Derived& operator Op(const Eigen::SparseMatrixBase<OtherDerived>& other) { \
    return Base::operator Op(other.derived());                                                   \
  }                                                                                              \
  EIGEN_STRONG_INLINE Derived& operator Op(const Derived & other) { return Base::operator Op(other); }

#define EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, Op) \
  template <typename Other>                                          \
  EIGEN_STRONG_INLINE Derived& operator Op(const Other & scalar) {   \
    return Base::operator Op(scalar);                                \
  }

#define EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATORS(Derived) EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, =)

#define EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) EIGEN_GENERIC_PUBLIC_INTERFACE(Derived)

const int CoherentAccessPattern = 0x1;
const int InnerRandomAccessPattern = 0x2 | CoherentAccessPattern;
const int OuterRandomAccessPattern = 0x4 | CoherentAccessPattern;
const int RandomAccessPattern = 0x8 | OuterRandomAccessPattern | InnerRandomAccessPattern;

template <typename Scalar_, int Flags_ = 0, typename StorageIndex_ = int>
class SparseMatrix;
template <typename Scalar_, int Flags_ = 0, typename StorageIndex_ = int>
class SparseVector;

template <typename MatrixType, unsigned int UpLo>
class SparseSelfAdjointView;
template <typename MatrixType>
class SparseView;

template <typename MatrixType, int UpLo>
class SparseSymmetricPermutationProduct;

namespace internal {

/** \internal
 * Compile-time test for whether a sparse expression exposes its storage directly
 * through outerIndexPtr() / innerIndexPtr() / valuePtr() / innerNonZeroPtr()
 * (the \ref CompressedAccessBit contract: SparseMatrix, SparseVector,
 * Ref<Sparse>, Map<SparseMatrix>, ...). Such expressions can drive raw-pointer
 * fast paths; anything else must be walked via InnerIterator.
 */
template <typename Derived>
struct has_compressed_access : bool_constant<(int(traits<Derived>::Flags) & CompressedAccessBit) != 0> {};

// Defined in SparseApproxComparisons.h; BlockSparseMatrix.h uses it before that.
template <typename Scalar, bool = use_scaled_comparison<Scalar>::value>
struct sparse_approx_comparison;

template <typename T, int Rows, int Cols, int Flags>
struct sparse_eval;

template <typename T>
struct eval<T, Sparse> : sparse_eval<T, traits<T>::RowsAtCompileTime, traits<T>::ColsAtCompileTime, traits<T>::Flags> {
};

template <typename T, int Cols, int Flags>
struct sparse_eval<T, 1, Cols, Flags> {
  using Scalar_ = typename traits<T>::Scalar;
  using StorageIndex_ = typename traits<T>::StorageIndex;

 public:
  using type = SparseVector<Scalar_, RowMajor, StorageIndex_>;
};

template <typename T, int Rows, int Flags>
struct sparse_eval<T, Rows, 1, Flags> {
  using Scalar_ = typename traits<T>::Scalar;
  using StorageIndex_ = typename traits<T>::StorageIndex;

 public:
  using type = SparseVector<Scalar_, ColMajor, StorageIndex_>;
};

// TODO: consider unifying with plain_matrix_type<T, Sparse>.
template <typename T, int Rows, int Cols, int Flags>
struct sparse_eval {
  using Scalar_ = typename traits<T>::Scalar;
  using StorageIndex_ = typename traits<T>::StorageIndex;
  enum { Options_ = ((Flags & RowMajorBit) == RowMajorBit) ? RowMajor : ColMajor };

 public:
  using type = SparseMatrix<Scalar_, Options_, StorageIndex_>;
};

template <typename T, int Flags>
struct sparse_eval<T, 1, 1, Flags> {
  using Scalar_ = typename traits<T>::Scalar;

 public:
  using type = Matrix<Scalar_, 1, 1>;
};

template <typename T>
struct plain_matrix_type<T, Sparse> {
  using Scalar_ = typename traits<T>::Scalar;
  using StorageIndex_ = typename traits<T>::StorageIndex;
  enum { Options_ = ((evaluator<T>::Flags & RowMajorBit) == RowMajorBit) ? RowMajor : ColMajor };

 public:
  using type = SparseMatrix<Scalar_, Options_, StorageIndex_>;
};

template <typename T>
struct plain_object_eval<T, Sparse>
    : sparse_eval<T, traits<T>::RowsAtCompileTime, traits<T>::ColsAtCompileTime, evaluator<T>::Flags> {};

template <typename Decomposition, typename RhsType>
struct solve_traits<Decomposition, RhsType, Sparse> {
  using PlainObject = typename sparse_eval<RhsType, RhsType::RowsAtCompileTime, RhsType::ColsAtCompileTime,
                                           traits<RhsType>::Flags>::type;
};

template <typename Derived>
struct generic_xpr_base<Derived, MatrixXpr, Sparse> {
  using type = SparseMatrixBase<Derived>;
};

struct SparseTriangularShape {
  static std::string debugName() { return "SparseTriangularShape"; }
};
struct SparseSelfAdjointShape {
  static std::string debugName() { return "SparseSelfAdjointShape"; }
};

template <>
struct glue_shapes<SparseShape, SelfAdjointShape> {
  using type = SparseSelfAdjointShape;
};
template <>
struct glue_shapes<SparseShape, TriangularShape> {
  using type = SparseTriangularShape;
};

// return type of SparseCompressedBase::lower_bound;
struct LowerBoundIndex {
  LowerBoundIndex() = default;
  LowerBoundIndex(Index val, bool ok) : value(val), found(ok) {}
  Index value = -1;
  bool found = false;
};

}  // end namespace internal

/** \ingroup SparseCore_Module
 *
 * \class Triplet
 *
 * \brief A small structure to hold a non zero as a triplet (i,j,value).
 *
 * \sa SparseMatrix::setFromTriplets()
 */
template <typename Scalar, typename StorageIndex = typename SparseMatrix<Scalar>::StorageIndex>
class Triplet {
 public:
  Triplet() = default;

  Triplet(const StorageIndex& i, const StorageIndex& j, const Scalar& v = Scalar(0)) : m_row(i), m_col(j), m_value(v) {}

  /** \returns the row index of the element */
  const StorageIndex& row() const { return m_row; }

  /** \returns the column index of the element */
  const StorageIndex& col() const { return m_col; }

  /** \returns the value of the element */
  const Scalar& value() const { return m_value; }

 protected:
  StorageIndex m_row = 0;
  StorageIndex m_col = 0;
  Scalar m_value = Scalar(0);
};

}  // end namespace Eigen

#endif  // EIGEN_SPARSEUTIL_H