// Copyright (c) 2013-06  INRIA Sophia-Antipolis (France).
// All rights reserved.
//
// This file is part of CGAL (www.cgal.org).
// You can redistribute it and/or modify it under the terms of the GNU
// General Public License as published by the Free Software Foundation,
// either version 3 of the License, or (at your option) any later version.
//
// Licensees holding a valid commercial license may use this file in
// accordance with the commercial license agreement provided with the software.
//
// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
//
// $URL$
// $Id$
// SPDX-License-Identifier: GPL-3.0+
//
// Author(s) : Shihao Wu, Clement Jamin, Pierre Alliez 

#ifndef CGAL_BILATERAL_SMOOTH_POINT_SET_H
#define CGAL_BILATERAL_SMOOTH_POINT_SET_H

#include <CGAL/license/Point_set_processing_3.h>

#include <CGAL/disable_warnings.h>

#include <CGAL/Search_traits_3.h>
#include <CGAL/Orthogonal_k_neighbor_search.h>
#include <CGAL/property_map.h>
#include <CGAL/point_set_processing_assertions.h>
#include <CGAL/Point_with_normal_3.h>
#include <CGAL/squared_distance_3.h>
#include <CGAL/function.h>

#include <CGAL/boost/graph/named_function_params.h>
#include <CGAL/boost/graph/named_params_helper.h>

#include <iterator>
#include <set>
#include <algorithm>
#include <cmath>
#include <ctime>
#include <CGAL/Real_timer.h>
#include <CGAL/Memory_sizer.h>
#include <CGAL/property_map.h>

#ifdef CGAL_LINKED_WITH_TBB
#include <CGAL/internal/Parallel_callback.h>
#include <tbb/parallel_for.h>
#include <tbb/blocked_range.h>
#include <tbb/scalable_allocator.h>  
#include <tbb/atomic.h>
#endif // CGAL_LINKED_WITH_TBB

// Default allocator: use TBB allocators if available
#ifdef CGAL_LINKED_WITH_TBB
# define CGAL_PSP3_DEFAULT_ALLOCATOR tbb::scalable_allocator
#else // CGAL_LINKED_WITH_TBB
# define CGAL_PSP3_DEFAULT_ALLOCATOR std::allocator
#endif // CGAL_LINKED_WITH_TBB


//#define CGAL_PSP3_VERBOSE 

namespace CGAL {

// ----------------------------------------------------------------------------
// Private section
// ----------------------------------------------------------------------------
/// \cond SKIP_IN_MANUAL

namespace bilateral_smooth_point_set_internal{

// Item in the Kd-tree: position (Point_3) + index
template <typename Kernel>
class Kd_tree_element : public Point_with_normal_3<Kernel>
{
public:
  unsigned int index;

  // basic geometric types
  typedef typename CGAL::Origin Origin;
  typedef CGAL::Point_with_normal_3<Kernel> Base;

  Kd_tree_element(const Origin& o = ORIGIN, unsigned int id=0)
    : Base(o), index(id)
  {}
  Kd_tree_element(const Base& p, unsigned int id=0)
    : Base(p), index(id)
  {}
  Kd_tree_element(const Kd_tree_element& other)
    : Base(other), index(other.index)
  {}
};


// Helper class for the Kd-tree
template <typename Kernel>
class Kd_tree_gt : public Kernel
{
public:
  typedef Kd_tree_element<Kernel> Point_3;
};

template <typename Kernel>
class Kd_tree_traits : public CGAL::Search_traits_3<Kd_tree_gt<Kernel> >
{
public:
  typedef typename Kernel::Point_3 PointType;
};


/// Compute bilateral projection for each point
/// according to their KNN neighborhood points
/// 
/// \pre `k >= 2`, radius > 0 , sharpness_angle > 0 && sharpness_angle < 90
///
/// @tparam Kernel Geometric traits class.
/// @tparam Tree KD-tree.
///
/// @return 

template <typename Kernel>
CGAL::Point_with_normal_3<Kernel>
compute_denoise_projection(
  const CGAL::Point_with_normal_3<Kernel>& query, ///< 3D point to project
  const std::vector<CGAL::Point_with_normal_3<Kernel>,
  CGAL_PSP3_DEFAULT_ALLOCATOR<CGAL::Point_with_normal_3<Kernel> > >& neighbor_pwns,  //
  typename Kernel::FT radius,                   ///< accept neighborhood radius
  typename Kernel::FT sharpness_angle           ///< control sharpness(0-90)
)
{
  CGAL_point_set_processing_precondition(radius > 0);
  CGAL_point_set_processing_precondition(sharpness_angle > 0
                                         && sharpness_angle < 90);

  // basic geometric types
  typedef typename Kernel::FT FT;
  typedef CGAL::Point_with_normal_3<Kernel> Pwn;
  typedef typename Kernel::Vector_3 Vector;
  typedef typename Kernel::Point_3 Point;

  FT radius2 = radius * radius;

  FT weight = (FT)0.0;
  FT iradius16 = -(FT)4.0/radius2;
  FT project_dist_sum = FT(0.0);
  FT project_weight_sum = FT(0.0);
  Vector normal_sum = CGAL::NULL_VECTOR; 

  FT cos_sigma = cos(sharpness_angle / 180.0 * 3.1415926);
  FT sharpness_bandwidth = std::pow((CGAL::max)(1e-8, 1 - cos_sigma), 2);

  typename std::vector<Pwn,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwn> >::const_iterator 
    pwn_iter = neighbor_pwns.begin();
  for (; pwn_iter != neighbor_pwns.end(); ++pwn_iter)
  {
    const Point& np = pwn_iter->position();
    const Vector& nn = pwn_iter->normal();

    FT dist2 = CGAL::squared_distance(query.position(), np);
    if (dist2 < radius2)
    {
      FT theta = std::exp(dist2 * iradius16);
      FT psi = std::exp(-std::pow(1 - query.normal() * nn, 2)
        / sharpness_bandwidth);

      weight = theta * psi;

      project_dist_sum += ((query.position() - np) * nn) * weight;
      project_weight_sum += weight;
      normal_sum = normal_sum + nn * weight;
    }
  }

  Vector update_normal = normal_sum / project_weight_sum;
  update_normal = update_normal / sqrt(update_normal.squared_length());

  Point update_point = query.position() - update_normal * 
                      (project_dist_sum / project_weight_sum); 

  return Pwn(update_point, update_normal);
}

/// Computes neighbors from kdtree.
///
/// \pre `k >= 2`.
///
/// @tparam Kernel Geometric traits class.
/// @tparam Tree KD-tree.
///
/// @return neighbors pwn of query point.
template < typename Kernel,
           typename Tree>
std::vector<CGAL::Point_with_normal_3<Kernel>,
            CGAL_PSP3_DEFAULT_ALLOCATOR<CGAL::Point_with_normal_3<Kernel> > >
compute_kdtree_neighbors(
  const CGAL::Point_with_normal_3<Kernel>& query, ///< 3D point
  const Tree& tree,                               ///< KD-tree
  unsigned int k                                  ///< number of neighbors         
)                       
{
  // basic geometric types
  typedef CGAL::Point_with_normal_3<Kernel> Pwn;

  // types for K nearest neighbors search
  typedef bilateral_smooth_point_set_internal::Kd_tree_traits<Kernel> Tree_traits;
  typedef CGAL::Orthogonal_k_neighbor_search<Tree_traits> Neighbor_search;
  typedef typename Neighbor_search::iterator Search_iterator;

  // performs k + 1 queries (if unique the query point is
  // output first). search may be aborted when k is greater
  // than number of input points
  Neighbor_search search(tree, query, k+1);
  Search_iterator search_iterator = search.begin();
  ++search_iterator;
  unsigned int i;
  std::vector<CGAL::Point_with_normal_3<Kernel>
    , CGAL_PSP3_DEFAULT_ALLOCATOR<CGAL::Point_with_normal_3<Kernel> > 
    > neighbor_pwns;

  for(i = 0; i < (k+1); ++i)
  {
    if(search_iterator == search.end())
      break; // premature ending

    Pwn pwn = search_iterator->first;
    neighbor_pwns.push_back(pwn);
    ++search_iterator;
  }

  // output 
  return neighbor_pwns;
}


/// Computes max-spacing of one query point from K nearest neighbors.
///
/// \pre `k >= 2`.
///
/// @tparam Kernel Geometric traits class.
/// @tparam Tree KD-tree.
///
/// @return max spacing.
template < typename Kernel,
           typename Tree >
typename Kernel::FT
compute_max_spacing(
  const CGAL::Point_with_normal_3<Kernel>& query, ///< 3D point
  Tree& tree,                                     ///< KD-tree
  unsigned int k)                                 ///< number of neighbors
{
  // basic geometric types
  typedef typename Kernel::FT FT;
  typedef CGAL::Point_with_normal_3<Kernel> Pwn;

  // types for K nearest neighbors search
  typedef bilateral_smooth_point_set_internal::Kd_tree_traits<Kernel> Tree_traits;
  typedef CGAL::Orthogonal_k_neighbor_search<Tree_traits> Neighbor_search;
  typedef typename Neighbor_search::iterator Search_iterator;

  // performs k + 1 queries (if unique the query point is
  // output first). search may be aborted when k is greater
  // than number of input points
  Neighbor_search search(tree,query,k+1);
  Search_iterator search_iterator = search.begin();
  ++search_iterator;
  FT max_distance = (FT)0.0;
  unsigned int i;
  for(i = 0; i < (k+1) ; ++i)
  {
    if(search_iterator == search.end())
      break; // premature ending

    Pwn pwn = search_iterator->first;
    double dist2 = CGAL::squared_distance(query.position(), pwn.position());
    max_distance = (CGAL::max)(dist2, max_distance);
    ++search_iterator;
  }

  // output max spacing
  return std::sqrt(max_distance);
}

} /* namespace internal */

/// \endcond

#ifdef CGAL_LINKED_WITH_TBB
/// \cond SKIP_IN_MANUAL
/// This is for parallelization of function: bilateral_smooth_point_set()
template <typename Kernel, typename Tree>
class Compute_pwns_neighbors
{
  typedef typename CGAL::Point_with_normal_3<Kernel> Pwn;
  typedef typename std::vector<Pwn,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwn> > Pwns;
  typedef typename std::vector<Pwns,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwns> > 
                                                                Pwns_neighbors;
  typedef typename Kernel::FT FT;

  unsigned int                                              m_k;
  const Tree                                              & m_tree;
  const Pwns                                              & m_pwns;
  Pwns_neighbors                                          & m_pwns_neighbors;
  cpp11::atomic<std::size_t>& advancement;
  cpp11::atomic<bool>& interrupted;

public:
  Compute_pwns_neighbors(unsigned int k, const Tree &tree,
                         const Pwns &pwns, Pwns_neighbors &neighbors,
                         cpp11::atomic<std::size_t>& advancement,
                         cpp11::atomic<bool>& interrupted)
    : m_k(k), m_tree(tree), m_pwns(pwns), m_pwns_neighbors(neighbors)
    , advancement (advancement), interrupted (interrupted) {} 

  void operator() ( const tbb::blocked_range<size_t>& r ) const 
  {
    for (size_t i = r.begin(); i!=r.end(); i++)
    {
      if (interrupted)
        break;
      
      m_pwns_neighbors[i] = bilateral_smooth_point_set_internal::
        compute_kdtree_neighbors<Kernel, Tree>(m_pwns[i], m_tree, m_k);
      ++ advancement;
    }
  }
};
/// \endcond  

/// \cond SKIP_IN_MANUAL
/// This is for parallelization of function: compute_denoise_projection()
template <typename Kernel>
class Pwn_updater 
{
  typedef typename CGAL::Point_with_normal_3<Kernel> Pwn;
  typedef typename std::vector<Pwn,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwn> > Pwns;
  typedef typename Kernel::FT FT;

  FT sharpness_angle;
  FT radius;
  Pwns* pwns;
  Pwns* update_pwns;
  std::vector<Pwns,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwns> >* pwns_neighbors;
  cpp11::atomic<std::size_t>& advancement;
  cpp11::atomic<bool>& interrupted;

public:
  Pwn_updater(FT sharpness, 
    FT r,
    Pwns *in,
    Pwns *out, 
    std::vector<Pwns,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwns> >* neighbors,
    cpp11::atomic<std::size_t>& advancement,
    cpp11::atomic<bool>& interrupted): 
  sharpness_angle(sharpness), 
    radius(r),
    pwns(in),
    update_pwns(out),
    pwns_neighbors(neighbors),
    advancement (advancement),
    interrupted (interrupted) {} 

  void operator() ( const tbb::blocked_range<size_t>& r ) const 
  { 
    for (size_t i = r.begin(); i != r.end(); ++i) 
    {
      if (interrupted)
        break;
      (*update_pwns)[i] = bilateral_smooth_point_set_internal::
        compute_denoise_projection<Kernel>((*pwns)[i], 
        (*pwns_neighbors)[i], 
        radius,
        sharpness_angle);  
      ++ advancement;
    }
  }
};
/// \endcond
#endif // CGAL_LINKED_WITH_TBB


// ----------------------------------------------------------------------------
// Public section
// ----------------------------------------------------------------------------


/**
   \ingroup PkgPointSetProcessingAlgorithms
 
   This function smooths an input point set by iteratively projecting each 
   point onto the implicit surface patch fitted over its k nearest neighbors.
   Bilateral projection preserves sharp features according to the normal
   (gradient) information. Both point positions and normals will be modified.  
   For more details, please see section 4 in \cgalCite{ear-2013}.  

   A parallel version of this function is provided and requires the executable to be 
   linked against the <a href="http://www.threadingbuildingblocks.org">Intel TBB library</a>.
   To control the number of threads used, the user may use the tbb::task_scheduler_init class.
   See the <a href="http://www.threadingbuildingblocks.org/documentation">TBB documentation</a> 
   for more details.

   \pre Normals must be unit vectors
   \pre k >= 2

   \tparam ConcurrencyTag enables sequential versus parallel algorithm.
   Possible values are `Sequential_tag`
   And `Parallel_tag`.
   \tparam PointRange is a model of `Range`. The value type of
   its iterator is the key type of the named parameter `point_map`.

   \param points input point range.
   \param k size of the neighborhood for the implicit surface patch fitting.
   The larger the value is, the smoother the result will be.
   \param np optional sequence of \ref psp_namedparameters "Named Parameters" among the ones listed below.

   \cgalNamedParamsBegin
     \cgalParamBegin{point_map} a model of `ReadWritePropertyMap` with value type `geom_traits::Point_3`.
     If this parameter is omitted, `CGAL::Identity_property_map<geom_traits::Point_3>` is used.\cgalParamEnd
     \cgalParamBegin{normal_map} a model of `ReadWritePropertyMap` with value type
     `geom_traits::Vector_3`.\cgalParamEnd
     \cgalParamBegin{sharpness_angle} controls the sharpness of the result.\cgalParamEnd
     \cgalParamBegin{callback} an instance of
      `cpp11::function<bool(double)>`. It is called regularly when the
      algorithm is running: the current advancement (between 0. and
      1.) is passed as parameter. If it returns `true`, then the
      algorithm continues its execution normally; if it returns
      `false`, the algorithm is stopped, all points are left unchanged
      and the function return `NaN`.\cgalParamEnd
     \cgalParamBegin{geom_traits} an instance of a geometric traits class, model of `Kernel`\cgalParamEnd
   \cgalNamedParamsEnd

   \return Average point movement error. It's a convergence criterium for the algorithm.
   This value can help the user to decide how many iterations are
   sufficient.
*/
template <typename ConcurrencyTag,
          typename PointRange,
          typename NamedParameters>
double
bilateral_smooth_point_set(
  PointRange& points,
  unsigned int k,
  const NamedParameters& np)
{
  using boost::choose_param;
  
  // basic geometric types
  typedef typename Point_set_processing_3::GetPointMap<PointRange, NamedParameters>::type PointMap;
  typedef typename Point_set_processing_3::GetNormalMap<PointRange, NamedParameters>::type NormalMap;
  typedef typename Point_set_processing_3::GetK<PointRange, NamedParameters>::Kernel Kernel;

  CGAL_static_assertion_msg(!(boost::is_same<NormalMap,
                              typename Point_set_processing_3::GetNormalMap<PointRange, NamedParameters>::NoMap>::value),
                            "Error: no normal map");
  
  typedef typename CGAL::Point_with_normal_3<Kernel> Pwn;
  typedef typename std::vector<Pwn,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwn> > Pwns;
  typedef typename Kernel::FT FT;
  
  double sharpness_angle = choose_param(get_param(np, internal_np::sharpness_angle), 30.);
  const cpp11::function<bool(double)>& callback = choose_param(get_param(np, internal_np::callback),
                                                               cpp11::function<bool(double)>());
  
  CGAL_point_set_processing_precondition(points.begin() != points.end());
  CGAL_point_set_processing_precondition(k > 1);

  // types for K nearest neighbors search structure
  typedef bilateral_smooth_point_set_internal::
                                       Kd_tree_element<Kernel> Kd_tree_element;
  typedef bilateral_smooth_point_set_internal::Kd_tree_traits<Kernel> Tree_traits;
  typedef CGAL::Orthogonal_k_neighbor_search<Tree_traits> Neighbor_search;
  typedef typename Neighbor_search::Tree Tree;

  PointMap point_map = choose_param(get_param(np, internal_np::point_map), PointMap());
  NormalMap normal_map = choose_param(get_param(np, internal_np::normal_map), NormalMap());

  // copy points and normals
  Pwns pwns;
  for(typename PointRange::iterator it = points.begin(); it != points.end(); ++it)
  {
    typename boost::property_traits<PointMap>::reference p = get(point_map, *it);
    typename boost::property_traits<NormalMap>::reference n = get(normal_map, *it);
    CGAL_point_set_processing_precondition(n.squared_length() > 1e-10);
    
    pwns.push_back(Pwn(p, n));
  }

  std::size_t nb_points = pwns.size();

#ifdef CGAL_PSP3_VERBOSE
   std::cout << "Initialization and compute max spacing: " << std::endl;
#endif
   // initiate a KD-tree search for points
   std::vector<Kd_tree_element,
     CGAL_PSP3_DEFAULT_ALLOCATOR<Kd_tree_element> > treeElements;
   treeElements.reserve(pwns.size());
   typename std::vector<Pwn,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwn> >::iterator 
     pwn_iter = pwns.begin();
   for (unsigned int i = 0; pwn_iter != pwns.end(); ++pwn_iter)
   {
     treeElements.push_back(Kd_tree_element(*pwn_iter, i));
   }
   Tree tree(treeElements.begin(), treeElements.end());
   // Guess spacing
#ifdef CGAL_PSP3_VERBOSE
   CGAL::Real_timer task_timer;
   task_timer.start();
#endif
   FT guess_neighbor_radius = 0.0; 

   for(pwn_iter = pwns.begin(); pwn_iter != pwns.end(); ++pwn_iter)
   {
     FT max_spacing = bilateral_smooth_point_set_internal::
       compute_max_spacing<Kernel,Tree>(*pwn_iter, tree, k);
     guess_neighbor_radius = (CGAL::max)(max_spacing, guess_neighbor_radius); 
   }
   
#ifdef CGAL_PSP3_VERBOSE
   task_timer.stop();
#endif
   guess_neighbor_radius *= 0.95;

#ifdef CGAL_PSP3_VERBOSE
   CGAL::Memory_sizer::size_type memory = CGAL::Memory_sizer().virtual_size();
   std::cout << "done: " << task_timer.time() << " seconds, "
             << (memory>>20) << " Mb allocated" << std::endl;

   std::cout << "Compute all neighbors: " << std::endl;
   task_timer.reset();
   task_timer.start();
#endif
   // compute all neighbors
   std::vector<Pwns,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwns> > pwns_neighbors;
   pwns_neighbors.resize(nb_points);
 
#ifndef CGAL_LINKED_WITH_TBB
  CGAL_static_assertion_msg (!(boost::is_convertible<ConcurrencyTag, Parallel_tag>::value),
			     "Parallel_tag is enabled but TBB is unavailable.");
#else
   if (boost::is_convertible<ConcurrencyTag,Parallel_tag>::value)
   {
     internal::Point_set_processing_3::Parallel_callback
       parallel_callback (callback, 2 * nb_points);

     Compute_pwns_neighbors<Kernel, Tree> f(k, tree, pwns, pwns_neighbors,
                                            parallel_callback.advancement(),
                                            parallel_callback.interrupted());
     tbb::parallel_for(tbb::blocked_range<size_t>(0, nb_points), f);

     bool interrupted = parallel_callback.interrupted();
  
     // We interrupt by hand as counter only goes halfway and won't terminate by itself
     parallel_callback.interrupted() = true;
     parallel_callback.join();       

     // If interrupted during this step, nothing is computed, we return NaN
     if (interrupted)
       return std::numeric_limits<double>::quiet_NaN();
   }
   else
#endif
   {
     typename std::vector<Pwns,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwns> >::iterator 
       pwns_iter = pwns_neighbors.begin();

     std::size_t nb = 0;
     for(pwn_iter = pwns.begin(); pwn_iter != pwns.end(); ++pwn_iter, ++pwns_iter, ++ nb)
     {
       *pwns_iter = bilateral_smooth_point_set_internal::
         compute_kdtree_neighbors<Kernel, Tree>(*pwn_iter, tree, k);
       if (callback && !callback ((nb+1) / double(2. * nb_points)))
         return std::numeric_limits<double>::quiet_NaN();
     }
   }
   
#ifdef CGAL_PSP3_VERBOSE
   task_timer.stop();
   memory = CGAL::Memory_sizer().virtual_size();
   std::cout << "done: " << task_timer.time() << " seconds, "
             << (memory>>20) << " Mb allocated" << std::endl;

   std::cout << "Compute update points and normals: " << std::endl;
   task_timer.reset();
   task_timer.start();
#endif
   // update points and normals
   Pwns update_pwns(nb_points);

#ifdef CGAL_LINKED_WITH_TBB
   if(boost::is_convertible<ConcurrencyTag, CGAL::Parallel_tag>::value)
   {
     internal::Point_set_processing_3::Parallel_callback
       parallel_callback (callback, 2 * nb_points, nb_points);
     
     //tbb::task_scheduler_init init(4);
     tbb::blocked_range<size_t> block(0, nb_points);
     Pwn_updater<Kernel> pwn_updater(sharpness_angle,
                                     guess_neighbor_radius,
                                     &pwns,
                                     &update_pwns,
                                     &pwns_neighbors,
                                     parallel_callback.advancement(),
                                     parallel_callback.interrupted());
     tbb::parallel_for(block, pwn_updater);

     parallel_callback.join();

     // If interrupted during this step, nothing is computed, we return NaN
     if (parallel_callback.interrupted())
       return std::numeric_limits<double>::quiet_NaN();
   }
   else
#endif // CGAL_LINKED_WITH_TBB
   {
     std::size_t nb = nb_points;
     
     typename std::vector<Pwn,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwn> >::iterator 
       update_iter = update_pwns.begin();
     typename std::vector<Pwns,CGAL_PSP3_DEFAULT_ALLOCATOR<Pwns> >::iterator 
       neighbor_iter = pwns_neighbors.begin();
     for(pwn_iter = pwns.begin(); pwn_iter != pwns.end(); 
         ++pwn_iter, ++update_iter, ++neighbor_iter, ++ nb)
     {
       *update_iter = bilateral_smooth_point_set_internal::
         compute_denoise_projection<Kernel>
         (*pwn_iter, 
          *neighbor_iter, 
          guess_neighbor_radius, 
          sharpness_angle);
       if (callback && !callback ((nb+1) / double(2. * nb_points)))
         return std::numeric_limits<double>::quiet_NaN();
     }
   }
#ifdef CGAL_PSP3_VERBOSE
   task_timer.stop(); 
   memory = CGAL::Memory_sizer().virtual_size();
   std::cout << "done: " << task_timer.time() << " seconds, "
             << (memory>>20) << " Mb allocated" << std::endl;
#endif
   // save results
   FT sum_move_error = 0;
   typename PointRange::iterator it = points.begin();
   for(unsigned int i = 0 ; it != points.end(); ++it, ++i)
   {
     typename boost::property_traits<PointMap>::reference p = get(point_map, *it);
     sum_move_error += CGAL::squared_distance(p, update_pwns[i].position());
     put (point_map, *it, update_pwns[i].position());
     put (normal_map, *it, update_pwns[i].normal());
   }
     
   return sum_move_error / nb_points;
}

/// \cond SKIP_IN_MANUAL
// variant with default NP  
template <typename ConcurrencyTag,
          typename PointRange>
double
bilateral_smooth_point_set(
  PointRange& points,
  unsigned int k)           ///< size of the neighborhood for the implicit surface patch fitting.
                            ///< The larger the value is, the smoother the result will be.
{
  return bilateral_smooth_point_set<ConcurrencyTag>
    (points, k, CGAL::Point_set_processing_3::parameters::all_default(points));
}

#ifndef CGAL_NO_DEPRECATED_CODE
// deprecated API
template <typename ConcurrencyTag,
          typename ForwardIterator,
          typename PointMap,
          typename NormalMap,
          typename Kernel>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::bilateral_smooth_point_set(), please update your code")
double
bilateral_smooth_point_set(
  ForwardIterator first,    ///< forward iterator on the first input point.
  ForwardIterator beyond,   ///< past-the-end iterator.
  PointMap point_map,     ///< point property map.
  NormalMap normal_map,   ///< normal property map.
  unsigned int k,           ///< size of the neighborhood for the implicit surface patch fitting.
                            ///< The larger the value is, the smoother the result will be.
  typename Kernel::FT sharpness_angle,  ///< controls the sharpness of the result.
                            ///< The larger the value is, the smoother the result will be.
                            ///< The range of possible value is [0, 90].
  const Kernel& /*kernel*/) ///< geometric traits.
{
  CGAL::Iterator_range<ForwardIterator> points = CGAL::make_range (first, beyond);
  return bilateral_smooth_point_set<ConcurrencyTag>
    (points,
     k,
     CGAL::parameters::point_map(point_map).normal_map(normal_map)
     .sharpness_angle(sharpness_angle).geom_traits(Kernel()));
}
  
// deprecated API
template <typename ConcurrencyTag,
          typename ForwardIterator,
          typename PointMap,
          typename NormalMap>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::bilateral_smooth_point_set(), please update your code")
double
bilateral_smooth_point_set(
  ForwardIterator first,      ///< forward iterator to the first input point.
  ForwardIterator beyond,     ///< past-the-end iterator.
  PointMap point_map,        ///< property map OutputIterator -> Point_3.
  NormalMap normal_map,    ///< property map ForwardIterator -> Vector_3.
  const unsigned int k,      ///< number of neighbors.
  double sharpness_angle     ///< control sharpness(0-90)
) ///< property map OutputIterator -> Vector_3.
{
  CGAL::Iterator_range<ForwardIterator> points = CGAL::make_range (first, beyond);
  return bilateral_smooth_point_set<ConcurrencyTag>
    (points,
     k,
     CGAL::parameters::point_map(point_map).normal_map(normal_map).sharpness_angle(sharpness_angle));
}

// deprecated API
template <typename ConcurrencyTag,
          typename ForwardIterator,
          typename NormalMap>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::bilateral_smooth_point_set(), please update your code")
double
bilateral_smooth_point_set(
  ForwardIterator first,    ///< forward iterator to the first input point.
  ForwardIterator beyond,   ///< past-the-end iterator.
  const unsigned int k,     ///< number of neighbors.
  double sharpness_angle,   ///< control sharpness(0-90)
  NormalMap normal_map)   ///< property map OutputIterator -> Vector_3.
{
  CGAL::Iterator_range<ForwardIterator> points = CGAL::make_range (first, beyond);
  return bilateral_smooth_point_set<ConcurrencyTag>
    (points,
     k,
     CGAL::parameters::normal_map(normal_map).sharpness_angle(sharpness_angle));
}
#endif // CGAL_NO_DEPRECATED_CODE
/// \endcond


} //namespace CGAL

#include <CGAL/enable_warnings.h>

#endif // CGAL_BILATERAL_SMOOTH_POINT_SET_H