// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2011 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

#ifndef EIGEN_TESTSPARSE_H
#define EIGEN_TESTSPARSE_H

#include "main.h"

#ifdef min
#undef min
#endif

#ifdef max
#undef max
#endif

#include <unordered_map>

#include <Eigen/Cholesky>
#include <Eigen/LU>
#include <Eigen/Sparse>

enum { ForceNonZeroDiag = 1, MakeLowerTriangular = 2, MakeUpperTriangular = 4, ForceRealDiag = 8 };

/* Initializes both a sparse and dense matrix with same random values,
 * and a ratio of \a density non zero entries.
 * \param flags is a union of ForceNonZeroDiag, MakeLowerTriangular and MakeUpperTriangular
 *        allowing to control the shape of the matrix.
 * \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero,
 *        and zero coefficients respectively.
 */
template <typename Scalar, int Opt1, int Opt2, typename StorageIndex>
void initSparse(double density, Matrix<Scalar, Dynamic, Dynamic, Opt1>& refMat,
                SparseMatrix<Scalar, Opt2, StorageIndex>& sparseMat, int flags = 0,
                std::vector<Matrix<StorageIndex, 2, 1> >* zeroCoords = 0,
                std::vector<Matrix<StorageIndex, 2, 1> >* nonzeroCoords = 0) {
  enum { IsRowMajor = SparseMatrix<Scalar, Opt2, StorageIndex>::IsRowMajor };
  sparseMat.setZero();
  // sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
  int nnz = static_cast<int>((1.5 * density) * static_cast<double>(IsRowMajor ? refMat.cols() : refMat.rows()));
  sparseMat.reserve(VectorXi::Constant(IsRowMajor ? refMat.rows() : refMat.cols(), nnz));

  Index insert_count = 0;
  for (Index j = 0; j < sparseMat.outerSize(); j++) {
    // sparseMat.startVec(j);
    for (Index i = 0; i < sparseMat.innerSize(); i++) {
      Index ai(i), aj(j);
      if (IsRowMajor) std::swap(ai, aj);
      Scalar v = (internal::random<double>(0, 1) < density) ? internal::random<Scalar>() : Scalar(0);
      if ((flags & ForceNonZeroDiag) && (i == j)) {
        // FIXME: the following is too conservative
        v = internal::random<Scalar>() * Scalar(3.);
        v = v * v;
        if (numext::real(v) > 0)
          v += Scalar(5);
        else
          v -= Scalar(5);
      }
      if ((flags & MakeLowerTriangular) && aj > ai)
        v = Scalar(0);
      else if ((flags & MakeUpperTriangular) && aj < ai)
        v = Scalar(0);

      if ((flags & ForceRealDiag) && (i == j)) v = numext::real(v);

      if (!numext::is_exactly_zero(v)) {
        // sparseMat.insertBackByOuterInner(j,i) = v;
        sparseMat.insertByOuterInner(j, i) = v;
        ++insert_count;
        if (nonzeroCoords) nonzeroCoords->push_back(Matrix<StorageIndex, 2, 1>(ai, aj));
      } else if (zeroCoords) {
        zeroCoords->push_back(Matrix<StorageIndex, 2, 1>(ai, aj));
      }
      refMat(ai, aj) = v;

      // make sure we only insert as many as the sparse matrix supports
      if (insert_count == NumTraits<StorageIndex>::highest()) return;
    }
  }
  // sparseMat.finalize();
}

template <typename Scalar, int Options, typename Index>
void initSparse(double density, Matrix<Scalar, Dynamic, 1>& refVec, SparseVector<Scalar, Options, Index>& sparseVec,
                std::vector<int>* zeroCoords = 0, std::vector<int>* nonzeroCoords = 0) {
  sparseVec.reserve(int(refVec.size() * density));
  sparseVec.setZero();
  for (int i = 0; i < refVec.size(); i++) {
    Scalar v = (internal::random<double>(0, 1) < density) ? internal::random<Scalar>() : Scalar(0);
    if (!numext::is_exactly_zero(v)) {
      sparseVec.insertBack(i) = v;
      if (nonzeroCoords) nonzeroCoords->push_back(i);
    } else if (zeroCoords)
      zeroCoords->push_back(i);
    refVec[i] = v;
  }
}

template <typename Scalar, int Options, typename Index>
void initSparse(double density, Matrix<Scalar, 1, Dynamic>& refVec, SparseVector<Scalar, Options, Index>& sparseVec,
                std::vector<int>* zeroCoords = 0, std::vector<int>* nonzeroCoords = 0) {
  sparseVec.reserve(int(refVec.size() * density));
  sparseVec.setZero();
  for (int i = 0; i < refVec.size(); i++) {
    Scalar v = (internal::random<double>(0, 1) < density) ? internal::random<Scalar>() : Scalar(0);
    if (v != Scalar(0)) {
      sparseVec.insertBack(i) = v;
      if (nonzeroCoords) nonzeroCoords->push_back(i);
    } else if (zeroCoords)
      zeroCoords->push_back(i);
    refVec[i] = v;
  }
}

#endif  // EIGEN_TESTSPARSE_H