// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 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/.

#ifndef EIGEN_VISITOR_H
#define EIGEN_VISITOR_H

#include "./InternalHeaderCheck.h"

namespace Eigen {

namespace internal {

template<typename Visitor, typename Derived, int UnrollCount, bool Vectorize=((Derived::PacketAccess!=0) && functor_traits<Visitor>::PacketAccess)>
struct visitor_impl;

template<typename Visitor, typename Derived, int UnrollCount>
struct visitor_impl<Visitor, Derived, UnrollCount, false>
{
  enum {
    col = Derived::IsRowMajor ? (UnrollCount-1) % Derived::ColsAtCompileTime
                              : (UnrollCount-1) / Derived::RowsAtCompileTime,
    row = Derived::IsRowMajor ? (UnrollCount-1) / Derived::ColsAtCompileTime
                              : (UnrollCount-1) % Derived::RowsAtCompileTime
  };

  EIGEN_DEVICE_FUNC
  static inline void run(const Derived &mat, Visitor& visitor)
  {
    visitor_impl<Visitor, Derived, UnrollCount-1>::run(mat, visitor);
    visitor(mat.coeff(row, col), row, col);
  }
};

template<typename Visitor, typename Derived>
struct visitor_impl<Visitor, Derived, 1, false>
{
  EIGEN_DEVICE_FUNC
  static inline void run(const Derived &mat, Visitor& visitor)
  {
    return visitor.init(mat.coeff(0, 0), 0, 0);
  }
};

// This specialization enables visitors on empty matrices at compile-time
template<typename Visitor, typename Derived>
struct visitor_impl<Visitor, Derived, 0, false> {
  EIGEN_DEVICE_FUNC
  static inline void run(const Derived &/*mat*/, Visitor& /*visitor*/)
  {}
};

template<typename Visitor, typename Derived>
struct visitor_impl<Visitor, Derived, Dynamic, /*Vectorize=*/false>
{
  EIGEN_DEVICE_FUNC
  static inline void run(const Derived& mat, Visitor& visitor)
  {
    visitor.init(mat.coeff(0,0), 0, 0);
    if (Derived::IsRowMajor) {
      for(Index i = 1; i < mat.cols(); ++i) {
          visitor(mat.coeff(0, i), 0, i);
      }
      for(Index j = 1; j < mat.rows(); ++j) {
        for(Index i = 0; i < mat.cols(); ++i) {
          visitor(mat.coeff(j, i), j, i);
        }
      }
    } else {
      for(Index i = 1; i < mat.rows(); ++i) {
          visitor(mat.coeff(i, 0), i, 0);
      }
      for(Index j = 1; j < mat.cols(); ++j) {
        for(Index i = 0; i < mat.rows(); ++i) {
          visitor(mat.coeff(i, j), i, j);
        }
      }
    }
  }
};

template<typename Visitor, typename Derived, int UnrollSize>
struct visitor_impl<Visitor, Derived, UnrollSize, /*Vectorize=*/true>
{
  typedef typename Derived::Scalar Scalar;
  typedef typename packet_traits<Scalar>::type Packet;

  EIGEN_DEVICE_FUNC
  static inline void run(const Derived& mat, Visitor& visitor)
  {
    const Index PacketSize = packet_traits<Scalar>::size;
    visitor.init(mat.coeff(0,0), 0, 0);
    if (Derived::IsRowMajor) {
      for(Index i = 0; i < mat.rows(); ++i) {
        Index j = i == 0 ? 1 : 0;
        for(; j+PacketSize-1 < mat.cols(); j += PacketSize) {
          Packet p = mat.packet(i, j);
          visitor.packet(p, i, j);
        }
        for(; j < mat.cols(); ++j)
          visitor(mat.coeff(i, j), i, j);
      }
    } else {
      for(Index j = 0; j < mat.cols(); ++j) {
        Index i = j == 0 ? 1 : 0;
        for(; i+PacketSize-1 < mat.rows(); i += PacketSize) {
          Packet p = mat.packet(i, j);
          visitor.packet(p, i, j);
        }
        for(; i < mat.rows(); ++i)
          visitor(mat.coeff(i, j), i, j);
      }
    }
  }
};

// evaluator adaptor
template<typename XprType>
class visitor_evaluator
{
public:
  typedef internal::evaluator<XprType> Evaluator;

  enum {
    PacketAccess = Evaluator::Flags & PacketAccessBit,
    IsRowMajor = XprType::IsRowMajor,
    RowsAtCompileTime = XprType::RowsAtCompileTime,
    ColsAtCompileTime = XprType::ColsAtCompileTime,
    CoeffReadCost = Evaluator::CoeffReadCost
  };


  EIGEN_DEVICE_FUNC
  explicit visitor_evaluator(const XprType &xpr) : m_evaluator(xpr), m_xpr(xpr) { }

  typedef typename XprType::Scalar Scalar;
  typedef std::remove_const_t<typename XprType::CoeffReturnType> CoeffReturnType;
  typedef std::remove_const_t<typename XprType::PacketReturnType> PacketReturnType;

  EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT { return m_xpr.rows(); }
  EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT { return m_xpr.cols(); }
  EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index size() const EIGEN_NOEXCEPT { return m_xpr.size(); }

  EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index row, Index col) const
  { return m_evaluator.coeff(row, col); }
  EIGEN_DEVICE_FUNC PacketReturnType packet(Index row, Index col) const
  { return m_evaluator.template packet<Unaligned,PacketReturnType>(row, col); }

protected:
  Evaluator m_evaluator;
  const XprType &m_xpr;
};

} // end namespace internal

/** Applies the visitor \a visitor to the whole coefficients of the matrix or vector.
  *
  * The template parameter \a Visitor is the type of the visitor and provides the following interface:
  * \code
  * struct MyVisitor {
  *   // called for the first coefficient
  *   void init(const Scalar& value, Index i, Index j);
  *   // called for all other coefficients
  *   void operator() (const Scalar& value, Index i, Index j);
  * };
  * \endcode
  *
  * \note compared to one or two \em for \em loops, visitors offer automatic
  * unrolling for small fixed size matrix.
  *
  * \note if the matrix is empty, then the visitor is left unchanged.
  *
  * \sa minCoeff(Index*,Index*), maxCoeff(Index*,Index*), DenseBase::redux()
  */
template<typename Derived>
template<typename Visitor>
EIGEN_DEVICE_FUNC
void DenseBase<Derived>::visit(Visitor& visitor) const
{
  if(size()==0)
    return;

  typedef typename internal::visitor_evaluator<Derived> ThisEvaluator;
  ThisEvaluator thisEval(derived());

  enum {
    unroll =  SizeAtCompileTime != Dynamic
           && SizeAtCompileTime * int(ThisEvaluator::CoeffReadCost) + (SizeAtCompileTime-1) * int(internal::functor_traits<Visitor>::Cost) <= EIGEN_UNROLLING_LIMIT
  };
  return internal::visitor_impl<Visitor, ThisEvaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(thisEval, visitor);
}

namespace internal {

/** \internal
  * \brief Base class to implement min and max visitors
  */
template <typename Derived>
struct coeff_visitor
{
  // default initialization to avoid countless invalid maybe-uninitialized warnings by gcc
  EIGEN_DEVICE_FUNC
  coeff_visitor() : row(-1), col(-1), res(0) {}
  typedef typename Derived::Scalar Scalar;
  Index row, col;
  Scalar res;
  EIGEN_DEVICE_FUNC
  inline void init(const Scalar& value, Index i, Index j)
  {
    res = value;
    row = i;
    col = j;
  }
};


template<typename Scalar, int NaNPropagation, bool is_min=true>
struct minmax_compare {
  typedef typename packet_traits<Scalar>::type Packet;
  static EIGEN_DEVICE_FUNC inline bool compare(Scalar a, Scalar b) { return a < b; }
  static EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& p) { return predux_min<NaNPropagation>(p);}
};

template<typename Scalar, int NaNPropagation>
struct minmax_compare<Scalar, NaNPropagation, false> {
  typedef typename packet_traits<Scalar>::type Packet;
  static EIGEN_DEVICE_FUNC inline bool compare(Scalar a, Scalar b) { return a > b; }
  static EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& p) { return predux_max<NaNPropagation>(p);}
};

template <typename Derived, bool is_min, int NaNPropagation>
struct minmax_coeff_visitor : coeff_visitor<Derived>
{
  using Scalar = typename Derived::Scalar;
  using Packet = typename packet_traits<Scalar>::type;
  using Comparator = minmax_compare<Scalar, NaNPropagation, is_min>;

  EIGEN_DEVICE_FUNC inline
  void operator() (const Scalar& value, Index i, Index j)
  {
    if(Comparator::compare(value, this->res)) {
      this->res = value;
      this->row = i;
      this->col = j;
    }
  }

  EIGEN_DEVICE_FUNC inline
  void packet(const Packet& p, Index i, Index j) {
    const Index PacketSize = packet_traits<Scalar>::size;
    Scalar value = Comparator::predux(p);
    if (Comparator::compare(value, this->res)) {
      const Packet range = preverse(plset<Packet>(Scalar(1)));
      Packet mask = pcmp_eq(pset1<Packet>(value), p);
      Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
      this->res = value;
      this->row = Derived::IsRowMajor ? i : i + max_idx;;
      this->col = Derived::IsRowMajor ? j + max_idx : j;
    }
  }
};

// Suppress NaN. The only case in which we return NaN is if the matrix is all NaN, in which case,
// the row=0, col=0 is returned for the location.
template <typename Derived, bool is_min>
struct minmax_coeff_visitor<Derived, is_min, PropagateNumbers> : coeff_visitor<Derived>
{
  typedef typename Derived::Scalar Scalar;
  using Packet = typename packet_traits<Scalar>::type;
  using Comparator = minmax_compare<Scalar, PropagateNumbers, is_min>;

  EIGEN_DEVICE_FUNC inline
  void operator() (const Scalar& value, Index i, Index j)
  {
    if ((!(numext::isnan)(value) && (numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
      this->res = value;
      this->row = i;
      this->col = j;
    }
  }

  EIGEN_DEVICE_FUNC inline
  void packet(const Packet& p, Index i, Index j) {
    const Index PacketSize = packet_traits<Scalar>::size;
    Scalar value = Comparator::predux(p);
    if ((!(numext::isnan)(value) && (numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
      const Packet range = preverse(plset<Packet>(Scalar(1)));
      /* mask will be zero for NaNs, so they will be ignored. */
      Packet mask = pcmp_eq(pset1<Packet>(value), p);
      Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
      this->res = value;
      this->row = Derived::IsRowMajor ? i : i + max_idx;;
      this->col = Derived::IsRowMajor ? j + max_idx : j;
    }
  }

};

// Propagate NaN. If the matrix contains NaN, the location of the first NaN will be returned in
// row and col.
template <typename Derived, bool is_min>
struct minmax_coeff_visitor<Derived, is_min, PropagateNaN> : coeff_visitor<Derived>
{
  typedef typename Derived::Scalar Scalar;
  using Packet = typename packet_traits<Scalar>::type;
  using Comparator = minmax_compare<Scalar, PropagateNaN, is_min>;

  EIGEN_DEVICE_FUNC inline
  void operator() (const Scalar& value, Index i, Index j)
  {
    const bool value_is_nan = (numext::isnan)(value);
    if ((value_is_nan && !(numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
      this->res = value;
      this->row = i;
      this->col = j;
    }
  }

  EIGEN_DEVICE_FUNC inline
  void packet(const Packet& p, Index i, Index j) {
    const Index PacketSize = packet_traits<Scalar>::size;
    Scalar value = Comparator::predux(p);
    const bool value_is_nan = (numext::isnan)(value);
    if ((value_is_nan && !(numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
      const Packet range = preverse(plset<Packet>(Scalar(1)));
      // If the value is NaN, pick the first position of a NaN, otherwise pick the first extremal value.
      Packet mask = value_is_nan ? pnot(pcmp_eq(p, p)) : pcmp_eq(pset1<Packet>(value), p);
      Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
      this->res = value;
      this->row = Derived::IsRowMajor ? i : i + max_idx;;
      this->col = Derived::IsRowMajor ? j + max_idx : j;
    }
  }
};

template<typename Scalar, bool is_min, int NaNPropagation>
struct functor_traits<minmax_coeff_visitor<Scalar, is_min, NaNPropagation> > {
  enum {
    Cost = NumTraits<Scalar>::AddCost,
    PacketAccess = true
  };
};

} // end namespace internal

/** \fn DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
  * \returns the minimum of all coefficients of *this and puts in *row and *col its location.
  *
  * In case \c *this contains NaN, NaNPropagation determines the behavior:
  *   NaNPropagation == PropagateFast : undefined
  *   NaNPropagation == PropagateNaN : result is NaN
  *   NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
  * \warning the matrix must be not empty, otherwise an assertion is triggered.
  *
  * \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visit(), DenseBase::minCoeff()
  */
template<typename Derived>
template<int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC
typename internal::traits<Derived>::Scalar
DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
{
  eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");

  internal::minmax_coeff_visitor<Derived, true, NaNPropagation> minVisitor;
  this->visit(minVisitor);
  *rowId = minVisitor.row;
  if (colId) *colId = minVisitor.col;
  return minVisitor.res;
}

/** \returns the minimum of all coefficients of *this and puts in *index its location.
  *
  * In case \c *this contains NaN, NaNPropagation determines the behavior:
  *   NaNPropagation == PropagateFast : undefined
  *   NaNPropagation == PropagateNaN : result is NaN
  *   NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
  * \warning the matrix must be not empty, otherwise an assertion is triggered.
  *
  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::minCoeff()
  */
template<typename Derived>
template<int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC
typename internal::traits<Derived>::Scalar
DenseBase<Derived>::minCoeff(IndexType* index) const
{
  eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");

  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
      internal::minmax_coeff_visitor<Derived, true, NaNPropagation> minVisitor;
  this->visit(minVisitor);
  *index = IndexType((RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row);
  return minVisitor.res;
}

/** \fn DenseBase<Derived>::maxCoeff(IndexType* rowId, IndexType* colId) const
  * \returns the maximum of all coefficients of *this and puts in *row and *col its location.
  *
  * In case \c *this contains NaN, NaNPropagation determines the behavior:
  *   NaNPropagation == PropagateFast : undefined
  *   NaNPropagation == PropagateNaN : result is NaN
  *   NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
  * \warning the matrix must be not empty, otherwise an assertion is triggered.
  *
  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::maxCoeff()
  */
template<typename Derived>
template<int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC
typename internal::traits<Derived>::Scalar
DenseBase<Derived>::maxCoeff(IndexType* rowPtr, IndexType* colPtr) const
{
  eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");

  internal::minmax_coeff_visitor<Derived, false, NaNPropagation> maxVisitor;
  this->visit(maxVisitor);
  *rowPtr = maxVisitor.row;
  if (colPtr) *colPtr = maxVisitor.col;
  return maxVisitor.res;
}

/** \returns the maximum of all coefficients of *this and puts in *index its location.
  *
  * In case \c *this contains NaN, NaNPropagation determines the behavior:
  *   NaNPropagation == PropagateFast : undefined
  *   NaNPropagation == PropagateNaN : result is NaN
  *   NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
  * \warning the matrix must be not empty, otherwise an assertion is triggered.
  *
  * \sa DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visitor(), DenseBase::maxCoeff()
  */
template<typename Derived>
template<int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC
typename internal::traits<Derived>::Scalar
DenseBase<Derived>::maxCoeff(IndexType* index) const
{
  eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");

  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
      internal::minmax_coeff_visitor<Derived, false, NaNPropagation> maxVisitor;
  this->visit(maxVisitor);
  *index = (RowsAtCompileTime==1) ? maxVisitor.col : maxVisitor.row;
  return maxVisitor.res;
}

} // end namespace Eigen

#endif // EIGEN_VISITOR_H