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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.

#ifndef EIGEN_TRIANGULAR_MATRIX_MATRIX_H
#define EIGEN_TRIANGULAR_MATRIX_MATRIX_H

namespace internal {

// template<typename Scalar, int mr, int StorageOrder, bool Conjugate, int Mode>
// struct gemm_pack_lhs_triangular
// {
//   Matrix<Scalar,mr,mr,
//   void operator()(Scalar* blockA, const EIGEN_RESTRICT Scalar* _lhs, int lhsStride, int depth, int rows)
//   {
//     conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
//     const_blas_data_mapper<Scalar, StorageOrder> lhs(_lhs,lhsStride);
//     int count = 0;
//     const int peeled_mc = (rows/mr)*mr;
//     for(int i=0; i<peeled_mc; i+=mr)
//     {
//       for(int k=0; k<depth; k++)
//         for(int w=0; w<mr; w++)
//           blockA[count++] = cj(lhs(i+w, k));
//     }
//     for(int i=peeled_mc; i<rows; i++)
//     {
//       for(int k=0; k<depth; k++)
//         blockA[count++] = cj(lhs(i, k));
//     }
//   }
// };

/* Optimized triangular matrix * matrix (_TRMM++) product built on top of
 * the general matrix matrix product.
 */
template <typename Scalar, typename Index,
          int Mode, bool LhsIsTriangular,
          int LhsStorageOrder, bool ConjugateLhs,
          int RhsStorageOrder, bool ConjugateRhs,
          int ResStorageOrder>
struct product_triangular_matrix_matrix;

template <typename Scalar, typename Index,
          int Mode, bool LhsIsTriangular,
          int LhsStorageOrder, bool ConjugateLhs,
          int RhsStorageOrder, bool ConjugateRhs>
struct product_triangular_matrix_matrix<Scalar,Index,Mode,LhsIsTriangular,
                                           LhsStorageOrder,ConjugateLhs,
                                           RhsStorageOrder,ConjugateRhs,RowMajor>
{
  static EIGEN_STRONG_INLINE void run(
    Index rows, Index cols, Index depth,
    const Scalar* lhs, Index lhsStride,
    const Scalar* rhs, Index rhsStride,
    Scalar* res,       Index resStride,
    Scalar alpha)
  {
    product_triangular_matrix_matrix<Scalar, Index,
      (Mode&(UnitDiag|ZeroDiag)) | ((Mode&Upper) ? Lower : Upper),
      (!LhsIsTriangular),
      RhsStorageOrder==RowMajor ? ColMajor : RowMajor,
      ConjugateRhs,
      LhsStorageOrder==RowMajor ? ColMajor : RowMajor,
      ConjugateLhs,
      ColMajor>
      ::run(cols, rows, depth, rhs, rhsStride, lhs, lhsStride, res, resStride, alpha);
  }
};

// implements col-major += alpha * op(triangular) * op(general)
template <typename Scalar, typename Index, int Mode,
          int LhsStorageOrder, bool ConjugateLhs,
          int RhsStorageOrder, bool ConjugateRhs>
struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
                                           LhsStorageOrder,ConjugateLhs,
                                           RhsStorageOrder,ConjugateRhs,ColMajor>
{

  static EIGEN_DONT_INLINE void run(
    Index rows, Index cols, Index depth,
    const Scalar* _lhs, Index lhsStride,
    const Scalar* _rhs, Index rhsStride,
    Scalar* res,        Index resStride,
    Scalar alpha)
  {
    const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
    const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);

    typedef gebp_traits<Scalar,Scalar> Traits;
    enum {
      SmallPanelWidth   = EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr),
      IsLower = (Mode&Lower) == Lower,
      SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1
    };

    Index kc = depth; // cache block size along the K direction
    Index mc = rows;  // cache block size along the M direction
    Index nc = cols;  // cache block size along the N direction
    computeProductBlockingSizes<Scalar,Scalar,4>(kc, mc, nc);

    Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
    std::size_t sizeB = sizeW + kc*cols;
    Scalar* allocatedBlockB = ei_aligned_stack_new(Scalar, sizeB);
    Scalar* blockB = allocatedBlockB + sizeW;

    Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer;
    triangularBuffer.setZero();
    if((Mode&ZeroDiag)==ZeroDiag)
      triangularBuffer.diagonal().setZero();
    else
      triangularBuffer.diagonal().setOnes();

    gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;

    for(Index k2=IsLower ? depth : 0;
        IsLower ? k2>0 : k2<depth;
        IsLower ? k2-=kc : k2+=kc)
    {
      Index actual_kc = std::min(IsLower ? k2 : depth-k2, kc);
      Index actual_k2 = IsLower ? k2-actual_kc : k2;

      // align blocks with the end of the triangular part for trapezoidal lhs
      if((!IsLower)&&(k2<rows)&&(k2+actual_kc>rows))
      {
        actual_kc = rows-k2;
        k2 = k2+actual_kc-kc;
      }

      pack_rhs(blockB, &rhs(actual_k2,0), rhsStride, actual_kc, cols);

      // the selected lhs's panel has to be split in three different parts:
      //  1 - the part which is above the diagonal block => skip it
      //  2 - the diagonal block => special kernel
      //  3 - the panel below the diagonal block => GEPP
      // the block diagonal, if any
      if(IsLower || actual_k2<rows)
      {
        // for each small vertical panels of lhs
        for (Index k1=0; k1<actual_kc; k1+=SmallPanelWidth)
        {
          Index actualPanelWidth = std::min<Index>(actual_kc-k1, SmallPanelWidth);
          Index lengthTarget = IsLower ? actual_kc-k1-actualPanelWidth : k1;
          Index startBlock   = actual_k2+k1;
          Index blockBOffset = k1;

          // => GEBP with the micro triangular block
          // The trick is to pack this micro block while filling the opposite triangular part with zeros.
          // To this end we do an extra triangular copy to a small temporary buffer
          for (Index k=0;k<actualPanelWidth;++k)
          {
            if (SetDiag)
              triangularBuffer.coeffRef(k,k) = lhs(startBlock+k,startBlock+k);
            for (Index i=IsLower ? k+1 : 0; IsLower ? i<actualPanelWidth : i<k; ++i)
              triangularBuffer.coeffRef(i,k) = lhs(startBlock+i,startBlock+k);
          }
          pack_lhs(blockA, triangularBuffer.data(), triangularBuffer.outerStride(), actualPanelWidth, actualPanelWidth);

          gebp_kernel(res+startBlock, resStride, blockA, blockB, actualPanelWidth, actualPanelWidth, cols, alpha,
                      actualPanelWidth, actual_kc, 0, blockBOffset);

          // GEBP with remaining micro panel
          if (lengthTarget>0)
          {
            Index startTarget  = IsLower ? actual_k2+k1+actualPanelWidth : actual_k2;

            pack_lhs(blockA, &lhs(startTarget,startBlock), lhsStride, actualPanelWidth, lengthTarget);

            gebp_kernel(res+startTarget, resStride, blockA, blockB, lengthTarget, actualPanelWidth, cols, alpha,
                        actualPanelWidth, actual_kc, 0, blockBOffset);
          }
        }
      }
      // the part below the diagonal => GEPP
      {
        Index start = IsLower ? k2 : 0;
        Index end   = IsLower ? rows : std::min(actual_k2,rows);
        for(Index i2=start; i2<end; i2+=mc)
        {
          const Index actual_mc = std::min(i2+mc,end)-i2;
          gemm_pack_lhs<Scalar, Index, Traits::mr,Traits::LhsProgress, LhsStorageOrder,false>()
            (blockA, &lhs(i2, actual_k2), lhsStride, actual_kc, actual_mc);

          gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
        }
      }
    }

    ei_aligned_stack_delete(Scalar, blockA, kc*mc);
    ei_aligned_stack_delete(Scalar, allocatedBlockB, sizeB);
//     delete[] allocatedBlockB;
  }
};

// implements col-major += alpha * op(general) * op(triangular)
template <typename Scalar, typename Index, int Mode,
          int LhsStorageOrder, bool ConjugateLhs,
          int RhsStorageOrder, bool ConjugateRhs>
struct product_triangular_matrix_matrix<Scalar,Index,Mode,false,
                                           LhsStorageOrder,ConjugateLhs,
                                           RhsStorageOrder,ConjugateRhs,ColMajor>
{

  static EIGEN_DONT_INLINE void run(
    Index rows, Index cols, Index depth,
    const Scalar* _lhs, Index lhsStride,
    const Scalar* _rhs, Index rhsStride,
    Scalar* res,        Index resStride,
    Scalar alpha)
  {
    const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
    const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);

    typedef gebp_traits<Scalar,Scalar> Traits;
    enum {
      SmallPanelWidth   = EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr),
      IsLower = (Mode&Lower) == Lower,
      SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1
    };

    Index kc = depth; // cache block size along the K direction
    Index mc = rows;  // cache block size along the M direction
    Index nc = cols;  // cache block size along the N direction
    computeProductBlockingSizes<Scalar,Scalar,4>(kc, mc, nc);

    Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
    std::size_t sizeB = sizeW + kc*cols;
    Scalar* allocatedBlockB = ei_aligned_stack_new(Scalar,sizeB);
    Scalar* blockB = allocatedBlockB + sizeW;

    Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,RhsStorageOrder> triangularBuffer;
    triangularBuffer.setZero();
    if((Mode&ZeroDiag)==ZeroDiag)
      triangularBuffer.diagonal().setZero();
    else
      triangularBuffer.diagonal().setOnes();

    gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder,false,true> pack_rhs_panel;

    for(Index k2=IsLower ? 0 : depth;
        IsLower ? k2<depth  : k2>0;
        IsLower ? k2+=kc   : k2-=kc)
    {
      Index actual_kc = std::min(IsLower ? depth-k2 : k2, kc);
      Index actual_k2 = IsLower ? k2 : k2-actual_kc;

      // align blocks with the end of the triangular part for trapezoidal rhs
      if(IsLower && (k2<cols) && (actual_k2+actual_kc>cols))
      {
        actual_kc = cols-k2;
        k2 = actual_k2 + actual_kc - kc;
      }

      // remaining size
      Index rs = IsLower ? std::min(cols,actual_k2) : cols - k2;
      // size of the triangular part
      Index ts = (IsLower && actual_k2>=cols) ? 0 : actual_kc;

      Scalar* geb = blockB+ts*ts;

      pack_rhs(geb, &rhs(actual_k2,IsLower ? 0 : k2), rhsStride, actual_kc, rs);

      // pack the triangular part of the rhs padding the unrolled blocks with zeros
      if(ts>0)
      {
        for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth)
        {
          Index actualPanelWidth = std::min<Index>(actual_kc-j2, SmallPanelWidth);
          Index actual_j2 = actual_k2 + j2;
          Index panelOffset = IsLower ? j2+actualPanelWidth : 0;
          Index panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2;
          // general part
          pack_rhs_panel(blockB+j2*actual_kc,
                         &rhs(actual_k2+panelOffset, actual_j2), rhsStride,
                         panelLength, actualPanelWidth,
                         actual_kc, panelOffset);

          // append the triangular part via a temporary buffer
          for (Index j=0;j<actualPanelWidth;++j)
          {
            if (SetDiag)
              triangularBuffer.coeffRef(j,j) = rhs(actual_j2+j,actual_j2+j);
            for (Index k=IsLower ? j+1 : 0; IsLower ? k<actualPanelWidth : k<j; ++k)
              triangularBuffer.coeffRef(k,j) = rhs(actual_j2+k,actual_j2+j);
          }

          pack_rhs_panel(blockB+j2*actual_kc,
                         triangularBuffer.data(), triangularBuffer.outerStride(),
                         actualPanelWidth, actualPanelWidth,
                         actual_kc, j2);
        }
      }

      for (Index i2=0; i2<rows; i2+=mc)
      {
        const Index actual_mc = std::min(mc,rows-i2);
        pack_lhs(blockA, &lhs(i2, actual_k2), lhsStride, actual_kc, actual_mc);

        // triangular kernel
        if(ts>0)
        {
          for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth)
          {
            Index actualPanelWidth = std::min<Index>(actual_kc-j2, SmallPanelWidth);
            Index panelLength = IsLower ? actual_kc-j2 : j2+actualPanelWidth;
            Index blockOffset = IsLower ? j2 : 0;

            gebp_kernel(res+i2+(actual_k2+j2)*resStride, resStride,
                        blockA, blockB+j2*actual_kc,
                        actual_mc, panelLength, actualPanelWidth,
                        alpha,
                        actual_kc, actual_kc,  // strides
                        blockOffset, blockOffset,// offsets
                        allocatedBlockB); // workspace
          }
        }
        gebp_kernel(res+i2+(IsLower ? 0 : k2)*resStride, resStride,
                    blockA, geb, actual_mc, actual_kc, rs,
                    alpha,
                    -1, -1, 0, 0, allocatedBlockB);
      }
    }

    ei_aligned_stack_delete(Scalar, blockA, kc*mc);
    ei_aligned_stack_delete(Scalar, allocatedBlockB, sizeB);
  }
};

/***************************************************************************
* Wrapper to product_triangular_matrix_matrix
***************************************************************************/

template<int Mode, bool LhsIsTriangular, typename Lhs, typename Rhs>
struct traits<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false> >
  : traits<ProductBase<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false>, Lhs, Rhs> >
{};

} // end namespace internal

template<int Mode, bool LhsIsTriangular, typename Lhs, typename Rhs>
struct TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false>
  : public ProductBase<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false>, Lhs, Rhs >
{
  EIGEN_PRODUCT_PUBLIC_INTERFACE(TriangularProduct)

  TriangularProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}

  template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
  {
    const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs);
    const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs);

    Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
                               * RhsBlasTraits::extractScalarFactor(m_rhs);

    internal::product_triangular_matrix_matrix<Scalar, Index,
      Mode, LhsIsTriangular,
      (internal::traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
      (internal::traits<_ActualRhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
      (internal::traits<Dest          >::Flags&RowMajorBit) ? RowMajor : ColMajor>
      ::run(
        lhs.rows(), rhs.cols(), lhs.cols(),// LhsIsTriangular ? rhs.cols() : lhs.rows(),           // sizes
        &lhs.coeffRef(0,0),    lhs.outerStride(), // lhs info
        &rhs.coeffRef(0,0),    rhs.outerStride(), // rhs info
        &dst.coeffRef(0,0), dst.outerStride(), // result info
        actualAlpha                            // alpha
      );
  }
};


#endif // EIGEN_TRIANGULAR_MATRIX_MATRIX_H