/*
    Genome-wide Efficient Mixed Model Association (GEMMA)
    Copyright (C) 2011-2017, Xiang Zhou

    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 3 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, see <http://www.gnu.org/licenses/>.
*/

#include <iostream>
#include <cmath>
#include <vector>
#include "gsl/gsl_vector.h"
#include "gsl/gsl_matrix.h"
#include "gsl/gsl_linalg.h"
#include "Eigen/Dense"

using namespace std;
using namespace Eigen;

// On two different clusters, compare eigen vs lapack/gsl:
//
// dgemm, 5x or 0.5x faster or slower than lapack, 5x or 4x faster than gsl
// dgemv, 20x or 4x faster than gsl,
// eigen, 1x or 0.3x slower than lapack
// invert, 20x or 10x faster than lapack
//
void eigenlib_dgemm (const char *TransA, const char *TransB,
		     const double alpha, const gsl_matrix *A,
		     const gsl_matrix *B, const double beta,
		     gsl_matrix *C) {
  Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>  >
    A_mat(A->data, A->size1, A->size2, OuterStride<Dynamic>(A->tda) );
  Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>  >
    B_mat(B->data, B->size1, B->size2, OuterStride<Dynamic>(B->tda) );
  Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>  >
    C_mat(C->data, C->size1, C->size2, OuterStride<Dynamic>(C->tda) );

  if (*TransA=='N' || *TransA=='n') {
    if (*TransB=='N' || *TransB=='n') {
      C_mat=alpha*A_mat*B_mat+beta*C_mat;
    } else {
      C_mat=alpha*A_mat*B_mat.transpose()+beta*C_mat;
    }
  } else {
    if (*TransB=='N' || *TransB=='n') {
      C_mat=alpha*A_mat.transpose()*B_mat+beta*C_mat;
    } else {
      C_mat=alpha*A_mat.transpose()*B_mat.transpose()+beta*C_mat;
    }
  }

  return;
}

void eigenlib_dgemv (const char *TransA, const double alpha,
		     const gsl_matrix *A, const gsl_vector *x,
		     const double beta, gsl_vector *y) {
  Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>  >
    A_mat(A->data, A->size1, A->size2, OuterStride<Dynamic>(A->tda) );
  Map<Matrix<double, Dynamic, 1>, 0, InnerStride<Dynamic> >
    x_vec(x->data, x->size, InnerStride<Dynamic>(x->stride) );
  Map<Matrix<double, Dynamic, 1>, 0, InnerStride<Dynamic> >
    y_vec(y->data, y->size, InnerStride<Dynamic>(y->stride) );

  if (*TransA=='N' || *TransA=='n') {
    y_vec=alpha*A_mat*x_vec+beta*y_vec;
  } else {
    y_vec=alpha*A_mat.transpose()*x_vec+beta*y_vec;
  }

  return;
}

void eigenlib_invert(gsl_matrix *A) {
  Map<Matrix<double, Dynamic, Dynamic, RowMajor> >
    A_mat(A->data, A->size1, A->size2);
  A_mat=A_mat.inverse();
  return;
}

void eigenlib_dsyr (const double alpha, const gsl_vector *b, gsl_matrix *A) {
  Map<Matrix<double, Dynamic, Dynamic, RowMajor> >
    A_mat(A->data, A->size1, A->size2);
  Map<Matrix<double, Dynamic, 1>, 0, OuterStride<Dynamic> >
    b_vec(b->data, b->size, OuterStride<Dynamic>(b->stride) );
  A_mat=alpha*b_vec*b_vec.transpose()+A_mat;
  return;
}

void eigenlib_eigensymm (const gsl_matrix *G, gsl_matrix *U,
			 gsl_vector *eval) {
  Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>  >
    G_mat(G->data, G->size1, G->size2, OuterStride<Dynamic>(G->tda) );
  Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>  >
    U_mat(U->data, U->size1, U->size2, OuterStride<Dynamic>(U->tda) );
  Map<Matrix<double, Dynamic, 1>, 0, OuterStride<Dynamic> >
    eval_vec(eval->data, eval->size, OuterStride<Dynamic>(eval->stride) );

  SelfAdjointEigenSolver<MatrixXd> es(G_mat);
  if (es.info() != Success)
    abort();
  eval_vec=es.eigenvalues();
  U_mat=es.eigenvectors();
  return;
}