//=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; 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.
//
// This program 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 General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
//
#ifndef EIGEN3_INTERFACE_HH
#define EIGEN3_INTERFACE_HH

#include <Eigen/Eigen>
#include <vector>
#include "btl.hh"

using namespace Eigen;

template <class real, int SIZE = Dynamic>
class eigen3_interface {
 public:
  enum { IsFixedSize = (SIZE != Dynamic) };

  typedef real real_type;

  typedef std::vector<real> stl_vector;
  typedef std::vector<stl_vector> stl_matrix;

  typedef Eigen::Matrix<real, SIZE, SIZE> gene_matrix;
  typedef Eigen::Matrix<real, SIZE, 1> gene_vector;

  static inline std::string name(void) { return EIGEN_MAKESTRING(BTL_PREFIX); }

  static void free_matrix(gene_matrix& /*A*/, int /*N*/) {}

  static void free_vector(gene_vector& /*B*/) {}

  static BTL_DONT_INLINE void matrix_from_stl(gene_matrix& A, stl_matrix& A_stl) {
    A.resize(A_stl[0].size(), A_stl.size());

    for (unsigned int j = 0; j < A_stl.size(); j++) {
      for (unsigned int i = 0; i < A_stl[j].size(); i++) {
        A.coeffRef(i, j) = A_stl[j][i];
      }
    }
  }

  static BTL_DONT_INLINE void vector_from_stl(gene_vector& B, stl_vector& B_stl) {
    B.resize(B_stl.size(), 1);

    for (unsigned int i = 0; i < B_stl.size(); i++) {
      B.coeffRef(i) = B_stl[i];
    }
  }

  static BTL_DONT_INLINE void vector_to_stl(gene_vector& B, stl_vector& B_stl) {
    for (unsigned int i = 0; i < B_stl.size(); i++) {
      B_stl[i] = B.coeff(i);
    }
  }

  static BTL_DONT_INLINE void matrix_to_stl(gene_matrix& A, stl_matrix& A_stl) {
    int N = A_stl.size();

    for (int j = 0; j < N; j++) {
      A_stl[j].resize(N);
      for (int i = 0; i < N; i++) {
        A_stl[j][i] = A.coeff(i, j);
      }
    }
  }

  static inline void matrix_matrix_product(const gene_matrix& A, const gene_matrix& B, gene_matrix& X, int /*N*/) {
    X.noalias() = A * B;
  }

  static inline void transposed_matrix_matrix_product(const gene_matrix& A, const gene_matrix& B, gene_matrix& X,
                                                      int /*N*/) {
    X.noalias() = A.transpose() * B.transpose();
  }

  static inline void ata_product(const gene_matrix& A, gene_matrix& X, int /*N*/) {
    // X.noalias() = A.transpose()*A;
    X.template triangularView<Lower>().setZero();
    X.template selfadjointView<Lower>().rankUpdate(A.transpose());
  }

  static inline void aat_product(const gene_matrix& A, gene_matrix& X, int /*N*/) {
    X.template triangularView<Lower>().setZero();
    X.template selfadjointView<Lower>().rankUpdate(A);
  }

  static inline void matrix_vector_product(const gene_matrix& A, const gene_vector& B, gene_vector& X, int /*N*/) {
    X.noalias() = A * B;
  }

  static inline void symv(const gene_matrix& A, const gene_vector& B, gene_vector& X, int /*N*/) {
    X.noalias() = (A.template selfadjointView<Lower>() * B);
    //     internal::product_selfadjoint_vector<real,0,LowerTriangularBit,false,false>(N,A.data(),N, B.data(), 1,
    //     X.data(), 1);
  }

  template <typename Dest, typename Src>
  static void triassign(Dest& dst, const Src& src) {
    typedef typename Dest::Scalar Scalar;
    typedef typename internal::packet_traits<Scalar>::type Packet;
    const int PacketSize = sizeof(Packet) / sizeof(Scalar);
    int size = dst.cols();
    for (int j = 0; j < size; j += 1) {
      //       const int alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
      Scalar* A0 = dst.data() + j * dst.stride();
      int starti = j;
      int alignedEnd = starti;
      int alignedStart = (starti) + internal::first_aligned(&A0[starti], size - starti);
      alignedEnd = alignedStart + ((size - alignedStart) / (2 * PacketSize)) * (PacketSize * 2);

      // do the non-vectorizable part of the assignment
      for (int index = starti; index < alignedStart; ++index) {
        if (Dest::Flags & RowMajorBit)
          dst.copyCoeff(j, index, src);
        else
          dst.copyCoeff(index, j, src);
      }

      // do the vectorizable part of the assignment
      for (int index = alignedStart; index < alignedEnd; index += PacketSize) {
        if (Dest::Flags & RowMajorBit)
          dst.template copyPacket<Src, Aligned, Unaligned>(j, index, src);
        else
          dst.template copyPacket<Src, Aligned, Unaligned>(index, j, src);
      }

      // do the non-vectorizable part of the assignment
      for (int index = alignedEnd; index < size; ++index) {
        if (Dest::Flags & RowMajorBit)
          dst.copyCoeff(j, index, src);
        else
          dst.copyCoeff(index, j, src);
      }
      // dst.col(j).tail(N-j) = src.col(j).tail(N-j);
    }
  }

  static EIGEN_DONT_INLINE void syr2(gene_matrix& A, gene_vector& X, gene_vector& Y, int N) {
    // internal::product_selfadjoint_rank2_update<real,0,LowerTriangularBit>(N,A.data(),N, X.data(), 1, Y.data(), 1,
    // -1);
    for (int j = 0; j < N; ++j) A.col(j).tail(N - j) += X[j] * Y.tail(N - j) + Y[j] * X.tail(N - j);
  }

  static EIGEN_DONT_INLINE void ger(gene_matrix& A, gene_vector& X, gene_vector& Y, int N) {
    for (int j = 0; j < N; ++j) A.col(j) += X * Y[j];
  }

  static EIGEN_DONT_INLINE void rot(gene_vector& A, gene_vector& B, real c, real s, int /*N*/) {
    internal::apply_rotation_in_the_plane(A, B, JacobiRotation<real>(c, s));
  }

  static inline void atv_product(gene_matrix& A, gene_vector& B, gene_vector& X, int /*N*/) {
    X.noalias() = (A.transpose() * B);
  }

  static inline void axpy(real coef, const gene_vector& X, gene_vector& Y, int /*N*/) { Y += coef * X; }

  static inline void axpby(real a, const gene_vector& X, real b, gene_vector& Y, int /*N*/) { Y = a * X + b * Y; }

  static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix& source, gene_matrix& cible, int /*N*/) {
    cible = source;
  }

  static EIGEN_DONT_INLINE void copy_vector(const gene_vector& source, gene_vector& cible, int /*N*/) {
    cible = source;
  }

  static inline void trisolve_lower(const gene_matrix& L, const gene_vector& B, gene_vector& X, int /*N*/) {
    X = L.template triangularView<Lower>().solve(B);
  }

  static inline void trisolve_lower_matrix(const gene_matrix& L, const gene_matrix& B, gene_matrix& X, int /*N*/) {
    X = L.template triangularView<Upper>().solve(B);
  }

  static inline void trmm(const gene_matrix& L, const gene_matrix& B, gene_matrix& X, int /*N*/) {
    X.noalias() = L.template triangularView<Lower>() * B;
  }

  static inline void cholesky(const gene_matrix& X, gene_matrix& C, int /*N*/) {
    C = X;
    internal::llt_inplace<real, Lower>::blocked(C);
    // C = X.llt().matrixL();
    //     C = X;
    //     Cholesky<gene_matrix>::computeInPlace(C);
    //     Cholesky<gene_matrix>::computeInPlaceBlock(C);
  }

  static inline void lu_decomp(const gene_matrix& X, gene_matrix& C, int /*N*/) { C = X.fullPivLu().matrixLU(); }

  static inline void partial_lu_decomp(const gene_matrix& X, gene_matrix& C, int N) {
    Matrix<DenseIndex, 1, Dynamic> piv(N);
    DenseIndex nb;
    C = X;
    internal::partial_lu_inplace(C, piv, nb);
    //     C = X.partialPivLu().matrixLU();
  }

  static inline void tridiagonalization(const gene_matrix& X, gene_matrix& C, int N) {
    typename Tridiagonalization<gene_matrix>::CoeffVectorType aux(N - 1);
    C = X;
    internal::tridiagonalization_inplace(C, aux);
  }

  static inline void hessenberg(const gene_matrix& X, gene_matrix& C, int /*N*/) {
    C = HessenbergDecomposition<gene_matrix>(X).packedMatrix();
  }
};

#endif