// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2015-2016 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/.
// #define EIGEN_DONT_VECTORIZE
// #define EIGEN_MAX_ALIGN_BYTES 0
#include "sparse_solver.h"
#include <Eigen/IterativeLinearSolvers>

template <typename T, typename I_>
void test_incomplete_cholesky_T() {
  typedef SparseMatrix<T, 0, I_> SparseMatrixType;
  ConjugateGradient<SparseMatrixType, Lower, IncompleteCholesky<T, Lower, AMDOrdering<I_> > > cg_illt_lower_amd;
  ConjugateGradient<SparseMatrixType, Lower, IncompleteCholesky<T, Lower, NaturalOrdering<I_> > > cg_illt_lower_nat;
  ConjugateGradient<SparseMatrixType, Upper, IncompleteCholesky<T, Upper, AMDOrdering<I_> > > cg_illt_upper_amd;
  ConjugateGradient<SparseMatrixType, Upper, IncompleteCholesky<T, Upper, NaturalOrdering<I_> > > cg_illt_upper_nat;
  ConjugateGradient<SparseMatrixType, Upper | Lower, IncompleteCholesky<T, Lower, AMDOrdering<I_> > > cg_illt_uplo_amd;

  CALL_SUBTEST(check_sparse_spd_solving(cg_illt_lower_amd));
  CALL_SUBTEST(check_sparse_spd_solving(cg_illt_lower_nat));
  CALL_SUBTEST(check_sparse_spd_solving(cg_illt_upper_amd));
  CALL_SUBTEST(check_sparse_spd_solving(cg_illt_upper_nat));
  CALL_SUBTEST(check_sparse_spd_solving(cg_illt_uplo_amd));
}

template <int>
void bug1150() {
  // regression for bug 1150
  for (int N = 1; N < 20; ++N) {
    Eigen::MatrixXd b(N, N);
    b.setOnes();

    Eigen::SparseMatrix<double> m(N, N);
    m.reserve(Eigen::VectorXi::Constant(N, 4));
    for (int i = 0; i < N; ++i) {
      m.insert(i, i) = 1;
      m.coeffRef(i, i / 2) = 2;
      m.coeffRef(i, i / 3) = 2;
      m.coeffRef(i, i / 4) = 2;
    }

    Eigen::SparseMatrix<double> A;
    A = m * m.transpose();

    Eigen::ConjugateGradient<Eigen::SparseMatrix<double>, Eigen::Lower | Eigen::Upper,
                             Eigen::IncompleteCholesky<double> >
        solver(A);
    VERIFY(solver.preconditioner().info() == Eigen::Success);
    VERIFY(solver.info() == Eigen::Success);
  }
}

void test_non_spd() {
  Eigen::SparseMatrix<double> A(2, 2);
  A.insert(0, 0) = 0;
  A.insert(1, 1) = 3;

  Eigen::IncompleteCholesky<double> solver(A);

  // Recover original matrix.
  Eigen::MatrixXd M = solver.permutationP().transpose() *
                      (solver.scalingS().asDiagonal().inverse() *
                       (solver.matrixL() * solver.matrixL().transpose() -
                        solver.shift() * Eigen::MatrixXd::Identity(A.rows(), A.cols())) *
                       solver.scalingS().asDiagonal().inverse()) *
                      solver.permutationP();
  VERIFY_IS_APPROX(A.toDense(), M);
}

EIGEN_DECLARE_TEST(incomplete_cholesky) {
  CALL_SUBTEST_1((test_incomplete_cholesky_T<double, int>()));
  CALL_SUBTEST_2((test_incomplete_cholesky_T<std::complex<double>, int>()));
  CALL_SUBTEST_3((test_incomplete_cholesky_T<double, long int>()));

  CALL_SUBTEST_4((bug1150<0>()));
  CALL_SUBTEST_4(test_non_spd());
}