// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 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/.
// SPDX-License-Identifier: MPL-2.0

#include "lapack_common.h"
#include <Eigen/Eigenvalues>

// computes eigen values and vectors of a general N-by-N matrix A
EIGEN_LAPACK_FUNC(syev)
(const char* jobz, const char* uplo, int* n, RealScalar* ra, int* lda, RealScalar* rw, RealScalar* /*work*/, int* lwork,
 int* info) {
  // TODO exploit the work buffer
  bool query_size = *lwork == -1;

  *info = 0;
  if (*jobz != 'N' && *jobz != 'V')
    *info = -1;
  else if (UPLO(*uplo) == INVALID)
    *info = -2;
  else if (*n < 0)
    *info = -3;
  else if (*lda < std::max(1, *n))
    *info = -5;
  else if ((!query_size) && *lwork < std::max(1, 3 * *n - 1))
    *info = -8;

  if (*info != 0) {
    int e = -*info;
    return xerbla_(SCALAR_SUFFIX_UP "SYEV ", &e, kBlasNameLength);
  }

  if (query_size) {
    *lwork = 0;
    return;
  }

  if (*n == 0) return;

  Scalar* a = reinterpret_cast<Scalar*>(ra);
  Scalar* w = reinterpret_cast<Scalar*>(rw);

  PlainMatrixType mat(*n, *n);
  if (UPLO(*uplo) == UP)
    mat = matrix(a, *n, *n, *lda).adjoint();
  else
    mat = matrix(a, *n, *n, *lda);

  bool computeVectors = *jobz == 'V' || *jobz == 'v';
  Eigen::SelfAdjointEigenSolver<PlainMatrixType> eig(
      mat, computeVectors ? Eigen::ComputeEigenvectors : Eigen::EigenvaluesOnly);

  if (eig.info() == Eigen::NoConvergence) {
    make_vector(w, *n).setZero();
    if (computeVectors) matrix(a, *n, *n, *lda).setIdentity();
    //*info = 1;
    return;
  }

  make_vector(w, *n) = eig.eigenvalues();
  if (computeVectors) matrix(a, *n, *n, *lda) = eig.eigenvectors();
}