// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2012 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
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//   this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
//   this list of conditions and the following disclaimer in the documentation
//   and/or other materials provided with the distribution.
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//   used to endorse or promote products derived from this software without
//   specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// Author: keir@google.com (Keir Mierle)

#include "ceres/cgnr_solver.h"

#include "ceres/block_jacobi_preconditioner.h"
#include "ceres/cgnr_linear_operator.h"
#include "ceres/conjugate_gradients_solver.h"
#include "ceres/internal/eigen.h"
#include "ceres/linear_solver.h"
#include "ceres/wall_time.h"
#include "glog/logging.h"

namespace ceres {
namespace internal {

CgnrSolver::CgnrSolver(const LinearSolver::Options& options)
  : options_(options),
    preconditioner_(NULL) {
  if (options_.preconditioner_type != JACOBI &&
      options_.preconditioner_type != IDENTITY) {
    LOG(FATAL) << "CGNR only supports IDENTITY and JACOBI preconditioners.";
  }
}

LinearSolver::Summary CgnrSolver::SolveImpl(
    BlockSparseMatrix* A,
    const double* b,
    const LinearSolver::PerSolveOptions& per_solve_options,
    double* x) {
  EventLogger event_logger("CgnrSolver::Solve");

  // Form z = Atb.
  Vector z(A->num_cols());
  z.setZero();
  A->LeftMultiply(b, z.data());

  // Precondition if necessary.
  LinearSolver::PerSolveOptions cg_per_solve_options = per_solve_options;
  if (options_.preconditioner_type == JACOBI) {
    if (preconditioner_.get() == NULL) {
      preconditioner_.reset(new BlockJacobiPreconditioner(*A));
    }
    preconditioner_->Update(*A, per_solve_options.D);
    cg_per_solve_options.preconditioner = preconditioner_.get();
  }

  // Solve (AtA + DtD)x = z (= Atb).
  VectorRef(x, A->num_cols()).setZero();
  CgnrLinearOperator lhs(*A, per_solve_options.D);
  event_logger.AddEvent("Setup");

  ConjugateGradientsSolver conjugate_gradient_solver(options_);
  LinearSolver::Summary summary =
      conjugate_gradient_solver.Solve(&lhs, z.data(), cg_per_solve_options, x);
  event_logger.AddEvent("Solve");
  return summary;
}

}  // namespace internal
}  // namespace ceres