// Ceres Solver - A fast non-linear least squares minimizer

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// http://ceres-solver.org/

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// Author: sameeragarwal@google.com (Sameer Agarwal)

#include "ceres/sparse_normal_cholesky_solver.h"

#include <algorithm>

#include <cstring>

#include <ctime>

#include "ceres/block_sparse_matrix.h"

#include "ceres/inner_product_computer.h"

#include "ceres/internal/eigen.h"

#include "ceres/internal/scoped_ptr.h"

#include "ceres/linear_solver.h"

#include "ceres/sparse_cholesky.h"

#include "ceres/triplet_sparse_matrix.h"

#include "ceres/types.h"

#include "ceres/wall_time.h"

namespace ceres {

namespace internal {

SparseNormalCholeskySolver::SparseNormalCholeskySolver(

    const LinearSolver::Options& options)

    : options_(options) {

  sparse_cholesky_.reset(

      SparseCholesky::Create(options_.sparse_linear_algebra_library_type,

                             options_.use_postordering ? AMD : NATURAL));

}

SparseNormalCholeskySolver::~SparseNormalCholeskySolver() {}

LinearSolver::Summary SparseNormalCholeskySolver::SolveImpl(

    BlockSparseMatrix* A,

    const double* b,

    const LinearSolver::PerSolveOptions& per_solve_options,

    double* x) {

  EventLogger event_logger("SparseNormalCholeskySolver::Solve");

  LinearSolver::Summary summary;

  summary.num_iterations = 1;

  summary.termination_type = LINEAR_SOLVER_SUCCESS;

  summary.message = "Success.";

  const int num_cols = A->num_cols();

  VectorRef(x, num_cols).setZero();

  A->LeftMultiply(b, x);

  event_logger.AddEvent("Compute RHS");

  if (per_solve_options.D != NULL) {

    // Temporarily append a diagonal block to the A matrix, but undo

    // it before returning the matrix to the user.

    scoped_ptr<BlockSparseMatrix> regularizer;

    regularizer.reset(BlockSparseMatrix::CreateDiagonalMatrix(

        per_solve_options.D, A->block_structure()->cols));

    event_logger.AddEvent("Diagonal");

    A->AppendRows(*regularizer);

    event_logger.AddEvent("Append");

  }

  event_logger.AddEvent("Append Rows");

  if (inner_product_computer_.get() == NULL) {

    inner_product_computer_.reset(

        InnerProductComputer::Create(*A, sparse_cholesky_->StorageType()));

    event_logger.AddEvent("InnerProductComputer::Create");

  }

  inner_product_computer_->Compute();

  event_logger.AddEvent("InnerProductComputer::Compute");

  // TODO(sameeragarwal):

  if (per_solve_options.D != NULL) {

    A->DeleteRowBlocks(A->block_structure()->cols.size());

  }

  summary.termination_type = sparse_cholesky_->FactorAndSolve(

      inner_product_computer_->mutable_result(), x, x, &summary.message);

  event_logger.AddEvent("Factor & Solve");

  return summary;

}

}  // namespace internal

}  // namespace ceres