/*******************************************************************************
 *
 * TRIQS: a Toolbox for Research in Interacting Quantum Systems
 *
 * Copyright (C) 2011-2014 by O. Parcollet
 *
 * TRIQS 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 3 of the License, or (at your option) any later
 * version.
 *
 * TRIQS 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
 * TRIQS. If not, see <http://www.gnu.org/licenses/>.
 *
 ******************************************************************************/
#pragma once
#include <type_traits>
#include "../array.hpp"
#include "../matrix.hpp"
#include "../vector.hpp"
#include <triqs/utility/exceptions.hpp>

namespace triqs {
namespace arrays {
 namespace linalg {

  extern "C" {
  void TRIQS_FORTRAN_MANGLING(dsyev)(char *, char *, // JOBZ and UPLO
                                     int &,          // Matrix Size
                                     double[],       // matrix
                                     int &,          // LDA of the matrix
                                     double[],       // Eigenvalues array
                                     double[],       // WORK
                                     int &,          // LWORK
                                     int &           // INFO
                                     );


  void TRIQS_FORTRAN_MANGLING(zheev)(char *, char *,          // JOBZ and UPLO
                                     int &,                   // Matrix Size
                                     std::complex<double> [], // matrix
                                     int &,                   // LDA of the matrix
                                     double[],                // Eigenvalues array
                                     std::complex<double> [], // WORK
                                     int &,                   // LWORK
                                     double[],                // WORK2
                                     int &                    // INFO
                                     );
  }

  /**
   * A worker to call lapack routine with the matrices. Handles both real and complex case.
   */
  template <typename T> class eigenelements_worker {
   public:
   eigenelements_worker() = default;

   /// The eigenvalues
   template <typename M> array<double, 1> eigenvalues(M &mat) const {
    _prepare(mat);
    _invoke(is_complex<T>(), 'N', mat);
    return ev;
   }

   /// The eigensystems
   template <typename M> std::pair<array<double, 1>, matrix<T>> eigenelements(M &mat) const {
    _prepare(mat);
    _invoke(is_complex<T>(), 'V', mat);
    return {ev, _conj(mat, is_complex<T>())};
   }

   private:
   mutable array<double, 1> ev, work2; // work2 only used for T complex
   mutable array<T, 1> work;
   mutable int dim, lwork, info;

   // dispatch the implementation of invoke for T = double or complex
   void _invoke(std::false_type, char compz, matrix_view<double> mat) const { // the case double (is_complex = false)
    char uplo = 'U';
    TRIQS_FORTRAN_MANGLING(dsyev)(&compz, &uplo, dim, mat.data_start(), dim, ev.data_start(), work.data_start(), lwork, info);
    if (info) TRIQS_RUNTIME_ERROR << "eigenelements_worker :error code dsyev : " << info << " for matrix " << mat;
   }

   void _invoke(std::true_type, char compz, matrix_view<std::complex<double>> mat) const { // the case complex (is_complex = true)
    char uplo = 'U';
    TRIQS_FORTRAN_MANGLING(zheev)(&compz, &uplo, dim, mat.data_start(), dim, ev.data_start(), work.data_start(), lwork,
                                  work2.data_start(), info);
    if (info) TRIQS_RUNTIME_ERROR << "eigenelements_worker :error code zheev : " << info << " for matrix " << mat;
   }

   template <typename M> void _prepare(M const &mat) const {
    if (mat.is_empty()) TRIQS_RUNTIME_ERROR << "eigenelements_worker : the matrix is empty : matrix =  " << mat << "  ";
    if (!mat.is_square()) TRIQS_RUNTIME_ERROR << "eigenelements_worker : the matrix " << mat << " is not square ";
    if (!mat.indexmap().is_contiguous())
     TRIQS_RUNTIME_ERROR << "eigenelements_worker : the matrix " << mat << " is not contiguous in memory";
    dim = first_dim(mat);
    ev.resize(dim);
    lwork = 64 * dim;
    work.resize(lwork);
    if (is_complex<T>::value) work2.resize(lwork);
   }

   template <typename M> matrix<double> _conj(M const &m, std::false_type) const { return m; }

   // impl : since we call fortran lapack, if the order is C (!), the matrix is transposed, or conjugated, so we obtain
   // the conjugate of the eigenvectors... Fix #119.
   // Do nothing if the order is fortran already...
   template <typename M> matrix<std::complex<double>> _conj(M const &m, std::true_type) const {
    if (m.memory_layout_is_c())
     return conj(m);
    else
     return m.transpose(); // the matrix mat is understood as a fortran matrix. After the lapack, in memory, it contains the
                           // correct answer.
    // but since it is a fortran matrix, the C will see its transpose. We need to compensate this transpose (!).
   }
  };

  //--------------------------------

  /**
   * Simple diagonalization call, return all eigenelements.
   * Handles both real and complex case.
   * @param M : the matrix or view. MUST be contiguous. It is modified by the call.
   *            If you wish not to modify it, call eigenelements(make_clone(A))
   */
  template <typename M>
  std::pair<array<double, 1>, matrix<typename std14::remove_reference_t<M>::value_type>> eigenelements(M &&m) {
   return eigenelements_worker<typename std14::remove_reference_t<M>::value_type>().eigenelements(m);
  }

  //--------------------------------

  /**
   * Simple diagonalization call, returning only the eigenvalues.
   * Handles both real and complex case.
   * @param M : the matrix VIEW : it MUST be contiguous
   * @param take_copy : makes a copy of the matrix before calling lapack, so that the original is preserved.
   *   if false : no copy is made and the content of the matrix M is destroyed.
   *   if true : a copy is made, M is preserved, but of course it is slower...
   */
  template <typename M> array<double, 1> eigenvalues(M &&m) {
   return eigenelements_worker<typename std14::remove_reference_t<M>::value_type>().eigenvalues(m);
  }
 }
}
} // namespace triqs::arrays::linalg