cgal/Point_set_processing_3/include/CGAL/compute_average_spacing.h

259 lines
8.5 KiB
C++

// Copyright (c) 2007-09 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.
//
// $URL$
// $Id$
//
// Author(s) : Pierre Alliez and Laurent Saboret
#ifndef CGAL_AVERAGE_SPACING_3_H
#define CGAL_AVERAGE_SPACING_3_H
#include <CGAL/Search_traits_3.h>
#include <CGAL/squared_distance_3.h>
#include <CGAL/Orthogonal_k_neighbor_search.h>
#include <CGAL/property_map.h>
#include <CGAL/point_set_processing_assertions.h>
#include <CGAL/assertions.h>
#include <iterator>
#include <list>
#ifdef CGAL_LINKED_WITH_TBB
#include <tbb/parallel_for.h>
#include <tbb/blocked_range.h>
#include <tbb/scalable_allocator.h>
#endif // CGAL_LINKED_WITH_TBB
namespace CGAL {
// ----------------------------------------------------------------------------
// Private section
// ----------------------------------------------------------------------------
/// \cond SKIP_IN_MANUAL
namespace internal {
/// Computes average spacing of one query point from K nearest neighbors.
///
/// \pre `k >= 2`.
///
/// @tparam Kernel Geometric traits class.
/// @tparam Tree KD-tree.
///
/// @return average spacing (scalar).
template < typename Kernel,
typename Tree >
typename Kernel::FT
compute_average_spacing(const typename Kernel::Point_3& query, ///< 3D point whose spacing we want to compute
const Tree& tree, ///< KD-tree
unsigned int k) ///< number of neighbors
{
// basic geometric types
typedef typename Kernel::FT FT;
typedef typename Kernel::Point_3 Point;
// types for K nearest neighbors search
typedef Search_traits_3<Kernel> Tree_traits;
typedef 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();
FT sum_distances = (FT)0.0;
unsigned int i;
for(i=0;i<(k+1);i++)
{
if(search_iterator == search.end())
break; // premature ending
Point p = search_iterator->first;
sum_distances += std::sqrt(CGAL::squared_distance(query,p));
search_iterator++;
}
// output average spacing
return sum_distances / (FT)i;
}
#ifdef CGAL_LINKED_WITH_TBB
template <typename Kernel, typename Tree>
class Compute_average_spacings {
typedef typename Kernel::Point_3 Point;
typedef typename Kernel::FT FT;
const Tree& tree;
const unsigned int k;
const std::vector<Point>& input;
std::vector<FT>& output;
public:
Compute_average_spacings(Tree& tree, unsigned int k, std::vector<Point>& points,
std::vector<FT>& output)
: tree(tree), k (k), input (points), output (output)
{ }
void operator()(const tbb::blocked_range<std::size_t>& r) const
{
for( std::size_t i = r.begin(); i != r.end(); ++i)
output[i] = CGAL::internal::compute_average_spacing<Kernel,Tree>(input[i], tree, k);
}
};
#endif // CGAL_LINKED_WITH_TBB
} /* namespace internal */
/// \endcond
// ----------------------------------------------------------------------------
// Public section
// ----------------------------------------------------------------------------
/// \ingroup PkgPointSetProcessing
/// Computes average spacing from k nearest neighbors.
///
/// \pre `k >= 2.`
///
/// @tparam Concurrency_tag enables sequential versus parallel algorithm.
/// Possible values are `Sequential_tag`
/// and `Parallel_tag`.
/// @tparam InputIterator iterator over input points.
/// @tparam PointPMap is a model of `ReadablePropertyMap` with value type `Point_3<Kernel>`.
/// It can be omitted if the value type of `InputIterator` is convertible to `Point_3<Kernel>`.
/// @tparam Kernel Geometric traits class.
/// It can be omitted and deduced automatically from the value type of `PointPMap`.
///
/// @return average spacing (scalar).
// This variant requires the kernel.
template <typename Concurrency_tag,
typename InputIterator,
typename PointPMap,
typename Kernel
>
typename Kernel::FT
compute_average_spacing(
InputIterator first, ///< iterator over the first input point.
InputIterator beyond, ///< past-the-end iterator over the input points.
PointPMap point_pmap, ///< property map: value_type of InputIterator -> Point_3
unsigned int k, ///< number of neighbors.
const Kernel& /*kernel*/) ///< geometric traits.
{
// basic geometric types
typedef typename Kernel::Point_3 Point;
// types for K nearest neighbors search structure
typedef typename Kernel::FT FT;
typedef Search_traits_3<Kernel> Tree_traits;
typedef Orthogonal_k_neighbor_search<Tree_traits> Neighbor_search;
typedef typename Neighbor_search::Tree Tree;
// precondition: at least one element in the container.
// to fix: should have at least three distinct points
// but this is costly to check
CGAL_point_set_processing_precondition(first != beyond);
// precondition: at least 2 nearest neighbors
CGAL_point_set_processing_precondition(k >= 2);
// Instanciate a KD-tree search.
// Note: We have to convert each input iterator to Point_3.
std::vector<Point> kd_tree_points;
for(InputIterator it = first; it != beyond; it++)
kd_tree_points.push_back(get(point_pmap, *it));
Tree tree(kd_tree_points.begin(), kd_tree_points.end());
// iterate over input points, compute and output normal
// vectors (already normalized)
FT sum_spacings = (FT)0.0;
#ifndef CGAL_LINKED_WITH_TBB
CGAL_static_assertion_msg (!(boost::is_convertible<Concurrency_tag, Parallel_tag>::value),
"Parallel_tag is enabled but TBB is unavailable.");
#else
if (boost::is_convertible<Concurrency_tag,Parallel_tag>::value)
{
std::vector<FT> spacings (kd_tree_points.size ());
CGAL::internal::Compute_average_spacings<Kernel, Tree>
f (tree, k, kd_tree_points, spacings);
tbb::parallel_for(tbb::blocked_range<size_t>(0, kd_tree_points.size ()), f);
for (unsigned int i = 0; i < spacings.size (); ++ i)
sum_spacings += spacings[i];
}
else
#endif
{
for(InputIterator it = first; it != beyond; it++)
{
sum_spacings += internal::compute_average_spacing<Kernel,Tree>(
get(point_pmap,*it),
tree,k);
}
}
// return average spacing
return sum_spacings / (FT)(kd_tree_points.size ());
}
/// @cond SKIP_IN_MANUAL
// This variant deduces the kernel from the iterator type.
template <typename Concurrency_tag,
typename InputIterator,
typename PointPMap
>
typename Kernel_traits<typename boost::property_traits<PointPMap>::value_type>::Kernel::FT
compute_average_spacing(
InputIterator first, ///< iterator over the first input point.
InputIterator beyond, ///< past-the-end iterator over the input points.
PointPMap point_pmap, ///< property map: value_type of InputIterator -> Point_3
unsigned int k) ///< number of neighbors
{
typedef typename boost::property_traits<PointPMap>::value_type Point;
typedef typename Kernel_traits<Point>::Kernel Kernel;
return compute_average_spacing<Concurrency_tag>(
first,beyond,
point_pmap,
k,
Kernel());
}
/// @endcond
/// @cond SKIP_IN_MANUAL
// This variant creates a default point property map = Identity_property_map.
template < typename Concurrency_tag, typename InputIterator >
typename Kernel_traits<typename std::iterator_traits<InputIterator>::value_type>::Kernel::FT
compute_average_spacing(
InputIterator first, ///< iterator over the first input point.
InputIterator beyond, ///< past-the-end iterator over the input points.
unsigned int k) ///< number of neighbors.
{
return compute_average_spacing<Concurrency_tag>(
first,beyond,
make_identity_property_map(
typename std::iterator_traits<InputIterator>::value_type()),
k);
}
/// @endcond
} //namespace CGAL
#endif // CGAL_AVERAGE_SPACING_3_H