// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2010 Gael Guennebaud <g.gael@free.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/.

// import basic and product tests for deprecated DynamicSparseMatrix
#if 0  // sparse_basic(DynamicSparseMatrix) does not compile at all -> disabled
static long g_realloc_count = 0;
#define EIGEN_SPARSE_COMPRESSED_STORAGE_REALLOCATE_PLUGIN g_realloc_count++;

static long g_dense_op_sparse_count = 0;
#define EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN \
  g_dense_op_sparse_count++;
#define EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN \
  g_dense_op_sparse_count += 10;
#define EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN \
  g_dense_op_sparse_count += 20;

#define EIGEN_SPARSE_TEST_INCLUDED_FROM_SPARSE_EXTRA 1
#endif

#define EIGEN_NO_DEPRECATED_WARNING
// Disable counting of temporaries, since sparse_product(DynamicSparseMatrix)
// has an extra copy-assignment.
#define EIGEN_SPARSE_PRODUCT_IGNORE_TEMPORARY_COUNT
#include "sparse_product.cpp"

#if 0  // sparse_basic(DynamicSparseMatrix) does not compile at all -> disabled
#include "sparse_basic.cpp"
#endif

#include <Eigen/SparseExtra>

template <typename SetterType, typename DenseType, typename Scalar, int Options>
bool test_random_setter(SparseMatrix<Scalar, Options>& sm, const DenseType& ref,
                        const std::vector<Vector2i>& nonzeroCoords) {
  {
    sm.setZero();
    SetterType w(sm);
    std::vector<Vector2i> remaining = nonzeroCoords;
    while (!remaining.empty()) {
      int i = internal::random<int>(0, static_cast<int>(remaining.size()) - 1);
      w(remaining[i].x(), remaining[i].y()) =
          ref.coeff(remaining[i].x(), remaining[i].y());
      remaining[i] = remaining.back();
      remaining.pop_back();
    }
  }
  return sm.isApprox(ref);
}

template <typename SetterType, typename DenseType, typename T>
bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref,
                        const std::vector<Vector2i>& nonzeroCoords) {
  sm.setZero();
  std::vector<Vector2i> remaining = nonzeroCoords;
  while (!remaining.empty()) {
    int i = internal::random<int>(0, static_cast<int>(remaining.size()) - 1);
    sm.coeffRef(remaining[i].x(), remaining[i].y()) =
        ref.coeff(remaining[i].x(), remaining[i].y());
    remaining[i] = remaining.back();
    remaining.pop_back();
  }
  return sm.isApprox(ref);
}

template <typename SparseMatrixType>
void sparse_extra(const SparseMatrixType& ref) {
  const Index rows = ref.rows();
  const Index cols = ref.cols();
  typedef typename SparseMatrixType::Scalar Scalar;
  enum { Flags = SparseMatrixType::Flags };

  double density = (std::max)(8. / (rows * cols), 0.01);
  typedef Matrix<Scalar, Dynamic, Dynamic> DenseMatrix;
  typedef Matrix<Scalar, Dynamic, 1> DenseVector;
  Scalar eps = 1e-6;

  SparseMatrixType m(rows, cols);
  DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
  DenseVector vec1 = DenseVector::Random(rows);

  std::vector<Vector2i> zeroCoords;
  std::vector<Vector2i> nonzeroCoords;
  initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);

  if (zeroCoords.size() == 0 || nonzeroCoords.size() == 0) return;

  // test coeff and coeffRef
  for (int i = 0; i < (int)zeroCoords.size(); ++i) {
    VERIFY_IS_MUCH_SMALLER_THAN(m.coeff(zeroCoords[i].x(), zeroCoords[i].y()),
                                eps);
    if (internal::is_same<SparseMatrixType,
                          SparseMatrix<Scalar, Flags> >::value)
      VERIFY_RAISES_ASSERT(m.coeffRef(zeroCoords[0].x(), zeroCoords[0].y()) =
                               5);
  }
  VERIFY_IS_APPROX(m, refMat);

  m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
  refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);

  VERIFY_IS_APPROX(m, refMat);

  // random setter
  //   {
  //     m.setZero();
  //     VERIFY_IS_NOT_APPROX(m, refMat);
  //     SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
  //     std::vector<Vector2i> remaining = nonzeroCoords;
  //     while(!remaining.empty())
  //     {
  //       int i = internal::random<int>(0,remaining.size()-1);
  //       w->coeffRef(remaining[i].x(),remaining[i].y()) =
  //       refMat.coeff(remaining[i].x(),remaining[i].y());
  //       remaining[i] = remaining.back();
  //       remaining.pop_back();
  //     }
  //   }
  //   VERIFY_IS_APPROX(m, refMat);

  VERIFY((test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(
      m, refMat, nonzeroCoords)));
#ifdef EIGEN_UNORDERED_MAP_SUPPORT
  VERIFY((test_random_setter<
          RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(
      m, refMat, nonzeroCoords)));
#endif
#ifdef _DENSE_HASH_MAP_H_
  VERIFY((test_random_setter<
          RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(
      m, refMat, nonzeroCoords)));
#endif
#ifdef _SPARSE_HASH_MAP_H_
  VERIFY((test_random_setter<
          RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(
      m, refMat, nonzeroCoords)));
#endif

  // test RandomSetter
  /*{
    SparseMatrixType m1(rows,cols), m2(rows,cols);
    DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
    initSparse<Scalar>(density, refM1, m1);
    {
      Eigen::RandomSetter<SparseMatrixType > setter(m2);
      for (int j=0; j<m1.outerSize(); ++j)
        for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
          setter(i.index(), j) = i.value();
    }
    VERIFY_IS_APPROX(m1, m2);
  }*/
}

template <typename SparseMatrixType>
void check_marketio() {
  typedef Matrix<typename SparseMatrixType::Scalar, Dynamic, Dynamic>
      DenseMatrix;
  Index rows = internal::random<Index>(1, 100);
  Index cols = internal::random<Index>(1, 100);
  SparseMatrixType m1, m2;
  m1 = DenseMatrix::Random(rows, cols).sparseView();
  saveMarket(m1, "sparse_extra.mtx");
  loadMarket(m2, "sparse_extra.mtx");
  VERIFY_IS_EQUAL(DenseMatrix(m1), DenseMatrix(m2));
}

EIGEN_DECLARE_TEST(sparse_extra) {
  for (int i = 0; i < g_repeat; i++) {
    int s = Eigen::internal::random<int>(1, 50);
    CALL_SUBTEST_1(sparse_extra(SparseMatrix<double>(8, 8)));
    CALL_SUBTEST_2(sparse_extra(SparseMatrix<std::complex<double> >(s, s)));
    CALL_SUBTEST_1(sparse_extra(SparseMatrix<double>(s, s)));

    CALL_SUBTEST_3(sparse_extra(DynamicSparseMatrix<double>(s, s)));
    //    CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double>(s, s)) ));
    //    CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double,ColMajor,long
    //    int>(s, s)) ));

    CALL_SUBTEST_3((sparse_product<DynamicSparseMatrix<float, ColMajor> >()));
    CALL_SUBTEST_3((sparse_product<DynamicSparseMatrix<float, RowMajor> >()));

    CALL_SUBTEST_4((check_marketio<SparseMatrix<float, ColMajor, int> >()));
    CALL_SUBTEST_4((check_marketio<SparseMatrix<double, ColMajor, int> >()));
    CALL_SUBTEST_4(
        (check_marketio<SparseMatrix<std::complex<float>, ColMajor, int> >()));
    CALL_SUBTEST_4(
        (check_marketio<SparseMatrix<std::complex<double>, ColMajor, int> >()));
    CALL_SUBTEST_4(
        (check_marketio<SparseMatrix<float, ColMajor, long int> >()));
    CALL_SUBTEST_4(
        (check_marketio<SparseMatrix<double, ColMajor, long int> >()));
    CALL_SUBTEST_4((check_marketio<
                    SparseMatrix<std::complex<float>, ColMajor, long int> >()));
    CALL_SUBTEST_4(
        (check_marketio<
            SparseMatrix<std::complex<double>, ColMajor, long int> >()));
    TEST_SET_BUT_UNUSED_VARIABLE(s);
  }
}