dust3d/thirdparty/cgal/CGAL-4.13/include/CGAL/estimate_scale.h

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// Copyright (c) 2013 INRIA Sophia-Antipolis (France).
// Copyright (c) 2016 GeometryFactory Sarl (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) : Simon Giraudot
#ifndef CGAL_ESTIMATE_SCALE_H
#define CGAL_ESTIMATE_SCALE_H
#include <CGAL/license/Point_set_processing_3.h>
#include <CGAL/disable_warnings.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 <CGAL/hierarchy_simplify_point_set.h>
#include <CGAL/random_simplify_point_set.h>
#include <CGAL/Point_set_2.h>
#include <CGAL/boost/graph/named_function_params.h>
#include <CGAL/boost/graph/named_params_helper.h>
#include <fstream>
#include <iterator>
#include <list>
namespace CGAL {
// ----------------------------------------------------------------------------
// Private section
// ----------------------------------------------------------------------------
/// \cond SKIP_IN_MANUAL
namespace internal {
template <class Kernel, class PointType>
class Quick_multiscale_approximate_knn_distance
{
};
template <class Kernel>
class Quick_multiscale_approximate_knn_distance<Kernel, typename Kernel::Point_3>
{
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;
typedef typename Neighbor_search::iterator Iterator;
template <typename ValueType, typename PointMap>
struct Pmap_unary_function : public CGAL::cpp98::unary_function<ValueType, typename Kernel::Point_3>
{
PointMap point_map;
Pmap_unary_function (PointMap point_map) : point_map (point_map) { }
typename boost::property_traits<PointMap>::reference
operator() (const ValueType& v) const { return get(point_map, v); }
};
std::size_t m_cluster_size;
std::vector<Tree*> m_trees;
std::vector<FT> m_weights;
std::vector<FT> m_precomputed_factor;
public:
template <typename InputIterator, typename PointMap>
Quick_multiscale_approximate_knn_distance (InputIterator first,
InputIterator beyond,
PointMap point_map,
std::size_t cluster_size = 25)
: m_cluster_size (cluster_size)
{
typedef Pmap_unary_function<typename std::iterator_traits<InputIterator>::value_type,
PointMap> Unary_f;
// Avoid moving points of input as the range is const
std::vector<typename Kernel::Point_3> kd_tree_points;
std::copy (boost::make_transform_iterator (first, Unary_f(point_map)),
boost::make_transform_iterator (beyond, Unary_f(point_map)),
std::back_inserter (kd_tree_points));
m_trees.push_back (new Tree (kd_tree_points.begin(), kd_tree_points.end()));
m_weights.push_back (1.);
std::size_t nb_pts = m_trees[0]->size();
std::size_t nb_trees = 0;
while (nb_pts > m_cluster_size)
{
nb_trees ++;
nb_pts /= m_cluster_size;
}
m_trees.reserve (nb_trees);
m_weights.reserve (nb_trees);
typename std::vector<typename Kernel::Point_3>::iterator first_unused = kd_tree_points.end();
nb_pts = m_trees[0]->size();
for (std::size_t i = 1; i < nb_trees; ++ i)
{
CGAL::Iterator_range<typename std::vector<typename Kernel::Point_3>::iterator> points
(kd_tree_points.begin(), first_unused);
first_unused
= CGAL::hierarchy_simplify_point_set (points,
CGAL::parameters::size(static_cast<unsigned int>(m_cluster_size)).
maximum_variation(1./3.));
m_trees.push_back (new Tree(kd_tree_points.begin(), first_unused));
m_weights.push_back (m_trees[0]->size() / (FT)(m_trees.back()->size()));
}
}
~Quick_multiscale_approximate_knn_distance()
{
for (std::size_t i = 0; i < m_trees.size(); ++ i)
delete m_trees[i];
}
template <typename InputIterator, typename PointMap>
std::size_t compute_k_scale (InputIterator query, PointMap point_map)
{
std::size_t out;
FT dummy;
compute_scale (query, point_map, out, dummy);
return out;
}
template <typename InputIterator, typename PointMap>
FT compute_range_scale (InputIterator query, PointMap point_map)
{
std::size_t dummy;
FT out;
compute_scale (query, point_map, dummy, out);
return out;
}
void precompute_factors ()
{
FT nb = 0.;
for (std::size_t t = 0; t < m_trees.size(); ++ t)
{
std::size_t size = (t == (m_trees.size() - 1)
? m_trees[t]->size()
: static_cast<std::size_t>(m_weights[t+1] / m_weights[t]));
for (std::size_t i = (t == 0 ? 0 : 1); i < size; ++ i)
{
nb += m_weights[t];
if (nb < 6.) // do not consider values under 6
continue;
m_precomputed_factor.push_back (0.91666666 * std::log (nb));
}
}
}
template <typename InputIterator, typename PointMap>
void compute_scale (InputIterator query, PointMap point_map,
std::size_t& k, FT& d)
{
if (m_precomputed_factor.empty())
precompute_factors();
k = 0;
d = 0.;
FT dist_min = (std::numeric_limits<FT>::max)();
FT sum_sq_distances = 0.;
FT nb = 0.;
std::size_t index = 0;
for (std::size_t t = 0; t < m_trees.size(); ++ t)
{
Neighbor_search search (*(m_trees[t]), get(point_map, *query),
static_cast<unsigned int>((t == (m_trees.size() - 1)
? m_trees[t]->size()
: m_weights[t+1] / m_weights[t])));
Iterator it = search.begin();
if (t != 0) // Skip first point except on first scale
++ it;
for (; it != search.end(); ++ it)
{
sum_sq_distances += m_weights[t] * it->second;
nb += m_weights[t];
if (nb < 6.) // do not consider values under 6
continue;
// sqrt(sum_sq_distances / nb) / nb^(5/12)
// Computed in log space with precomputed factor for time optimization
FT dist = 0.5 * std::log (sum_sq_distances) - m_precomputed_factor[index ++];
if (dist < dist_min)
{
dist_min = dist;
k = (std::size_t)nb;
d = it->second;
}
}
}
}
};
template <class Kernel>
class Quick_multiscale_approximate_knn_distance<Kernel, typename Kernel::Point_2>
{
typedef typename Kernel::FT FT;
typedef CGAL::Point_set_2<Kernel> Point_set;
typedef typename Point_set::Vertex_handle Vertex_handle;
template <typename ValueType, typename PointMap>
struct Pmap_unary_function : public CGAL::cpp98::unary_function<ValueType, typename Kernel::Point_2>
{
PointMap point_map;
Pmap_unary_function (PointMap point_map) : point_map (point_map) { }
typename boost::property_traits<PointMap>::reference
operator() (const ValueType& v) const { return get(point_map, v); }
};
template <typename PointMap>
struct Pmap_to_3d
{
PointMap point_map;
typedef typename Kernel::Point_3 value_type;
typedef const value_type& reference;
typedef typename Kernel::Point_2 key_type;
typedef boost::lvalue_property_map_tag category;
Pmap_to_3d () { }
Pmap_to_3d (PointMap point_map)
: point_map (point_map) { }
friend inline value_type get (const Pmap_to_3d& pmap, key_type p)
{
typename boost::property_traits<PointMap>::reference
p2 = get(pmap.point_map, p);
return value_type (p2.x(), p2.y(), 0.);
}
};
struct Sort_by_distance_to_point
{
const typename Kernel::Point_2& ref;
Sort_by_distance_to_point (const typename Kernel::Point_2& ref) : ref (ref) { }
bool operator() (const Vertex_handle& a, const Vertex_handle& b)
{
return (CGAL::squared_distance (a->point(), ref)
< CGAL::squared_distance (b->point(), ref));
}
};
std::size_t m_cluster_size;
std::vector<Point_set*> m_point_sets;
std::vector<FT> m_weights;
std::vector<FT> m_precomputed_factor;
public:
template <typename InputIterator, typename PointMap>
Quick_multiscale_approximate_knn_distance (InputIterator first,
InputIterator beyond,
PointMap point_map,
std::size_t cluster_size = 25)
: m_cluster_size (cluster_size)
{
typedef Pmap_unary_function<typename std::iterator_traits<InputIterator>::value_type,
PointMap> Unary_f;
// Avoid moving points of input as the range is const
std::vector<typename Kernel::Point_2> search_points;
std::copy (boost::make_transform_iterator (first, Unary_f(point_map)),
boost::make_transform_iterator (beyond, Unary_f(point_map)),
std::back_inserter (search_points));
m_point_sets.push_back (new Point_set (search_points.begin(), search_points.end()));
m_weights.push_back (1.);
std::size_t nb_pts = m_point_sets[0]->number_of_vertices();
std::size_t nb_trees = 0;
while (nb_pts > m_cluster_size)
{
nb_trees ++;
nb_pts /= m_cluster_size;
}
m_point_sets.reserve (nb_trees);
m_weights.reserve (nb_trees);
typename std::vector<typename Kernel::Point_2>::iterator first_unused = search_points.end();
nb_pts = m_point_sets[0]->number_of_vertices();
for (std::size_t i = 1; i < nb_trees; ++ i)
{
CGAL::Iterator_range<typename std::vector<typename Kernel::Point_2>::iterator> points
(search_points.begin(), first_unused);
first_unused
= CGAL::hierarchy_simplify_point_set (points,
CGAL::parameters::point_map(Pmap_to_3d<PointMap>(point_map)).
size(static_cast<unsigned int>(m_cluster_size)).
maximum_variation(1./3.));
m_point_sets.push_back (new Point_set (search_points.begin(), first_unused));
m_weights.push_back (nb_pts / (FT)(m_point_sets.back()->number_of_vertices()));
}
m_cluster_size = cluster_size;
}
~Quick_multiscale_approximate_knn_distance()
{
for (std::size_t i = 0; i < m_point_sets.size(); ++ i)
delete m_point_sets[i];
}
template <typename InputIterator, typename PointMap>
std::size_t compute_k_scale (InputIterator query, PointMap point_map)
{
std::size_t out;
FT dummy;
compute_scale (query, point_map, out, dummy);
return out;
}
template <typename InputIterator, typename PointMap>
FT compute_range_scale (InputIterator query, PointMap point_map)
{
std::size_t dummy;
FT out;
compute_scale (query, point_map, dummy, out);
return out;
}
void precompute_factors ()
{
FT nb = 0.;
for (std::size_t t = 0; t < m_point_sets.size(); ++ t)
{
std::size_t size = (t == m_point_sets.size() - 1
? m_point_sets[t]->number_of_vertices()
: static_cast<std::size_t>(m_weights[t+1] / m_weights[t]));
for (std::size_t i = (t == 0 ? 0 : 1); i < size; ++ i)
{
nb += m_weights[t];
if (nb < 6.) // do not consider values under 6
continue;
m_precomputed_factor.push_back (1.25 * std::log (nb));
}
}
}
template <typename InputIterator, typename PointMap>
void compute_scale (InputIterator query, PointMap point_map,
std::size_t& k, FT& d)
{
if (m_precomputed_factor.empty())
precompute_factors();
k = 0;
d = 0.;
FT dist_min = (std::numeric_limits<FT>::max)();
FT sum_sq_distances = 0.;
FT nb = 0.;
std::size_t index = 0;
typename boost::property_traits<PointMap>::reference
pquery = get(point_map, *query);
for (std::size_t t = 0; t < m_point_sets.size(); ++ t)
{
std::size_t size = ((t == m_point_sets.size() - 1)
? m_point_sets[t]->number_of_vertices()
: static_cast<std::size_t>(m_weights[t+1] / m_weights[t]));
std::vector<Vertex_handle> neighbors;
neighbors.reserve (size);
m_point_sets[t]->nearest_neighbors (pquery, size, std::back_inserter (neighbors));
std::sort (neighbors.begin(), neighbors.end(),
Sort_by_distance_to_point (pquery));
for (std::size_t n = (t == 0 ? 0 : 1); n < neighbors.size(); ++ n)
{
FT sq_dist = CGAL::squared_distance (pquery, neighbors[n]->point());
sum_sq_distances += m_weights[t] * sq_dist;
nb += m_weights[t];
if (nb < 6.) // do not consider values under 6
continue;
// sqrt(sum_sq_distances / nb) / nb^(3/4)
// Computed in log space with precomputed factor for time optimization
FT dist = 0.5 * std::log (sum_sq_distances) - m_precomputed_factor[index ++];
if (dist < dist_min)
{
dist_min = dist;
k = (std::size_t)nb;
d = sq_dist;
}
}
}
}
};
} /* namespace internal */
/// \endcond
// ----------------------------------------------------------------------------
// Public section
// ----------------------------------------------------------------------------
/**
\ingroup PkgPointSetProcessingAlgorithms
Estimates the local scale in a K nearest neighbors sense on a set
of user-defined query points. The computed scales correspond to
the smallest scales such that the K subsets of points have the
appearance of a surface in 3D or the appearance of a curve in 2D
(see \ref Point_set_processing_3Scale).
\tparam PointRange is a model of `ConstRange`. The value type of
its iterator is the key type of the named parameter `point_map`.
\tparam QueryPointRange is a model of `ConstRange`. The value type of
its iterator is the key type of the named parameter `query_point_map`.
\tparam OutputIterator is used to store the computed scales. It accepts
values of type `std::size_t`.
\param points input point range.
\param queries range of locations where scale must be estimated
\param output iterator to store the computed scales
\param np optional sequence of \ref psp_namedparameters "Named Parameters" among the ones listed below.
\cgalNamedParamsBegin
\cgalParamBegin{point_map} a model of `ReadablePropertyMap` with
value type `geom_traits::Point_3` (or `geom_traits::Point_2`).
If this parameter is omitted,
`CGAL::Identity_property_map<geom_traits::Point_3>` (or
`CGAL::Identity_property_map<geom_traits::Point_2>`) is
used.\cgalParamEnd
\cgalParamBegin{query_point_map} a model of `ReadablePropertyMap` with
value type `geom_traits::Point_3` (or `geom_traits::Point_2`).
If this parameter is omitted,
`CGAL::Identity_property_map<geom_traits::Point_3>` (or
`CGAL::Identity_property_map<geom_traits::Point_2>`) is
used.\cgalParamEnd
\cgalParamBegin{geom_traits} an instance of a geometric traits class, model of `Kernel`\cgalParamEnd
\cgalNamedParamsEnd
\note This function accepts both 2D and 3D points, but sample
points and query must have the same dimension.
*/
template <typename PointRange,
typename QueryPointRange,
typename OutputIterator,
typename NamedParameters
>
OutputIterator
estimate_local_k_neighbor_scales(
const PointRange& points,
const QueryPointRange& queries,
OutputIterator output,
const NamedParameters& np)
{
using boost::choose_param;
typedef typename Point_set_processing_3::GetPointMap<PointRange, NamedParameters>::const_type PointMap;
typedef typename Point_set_processing_3::GetQueryPointMap<QueryPointRange, NamedParameters>::const_type QueryPointMap;
typedef typename Point_set_processing_3::GetK<PointRange, NamedParameters>::Kernel Kernel;
typedef typename boost::property_traits<PointMap>::value_type Point_d;
PointMap point_map = choose_param(get_param(np, internal_np::point_map), PointMap());
QueryPointMap query_point_map = choose_param(get_param(np, internal_np::query_point_map), QueryPointMap());
// Build multi-scale KD-tree
internal::Quick_multiscale_approximate_knn_distance<Kernel, Point_d> kdtree (points.begin(),
points.end(),
point_map);
// Compute local scales everywhere
for (typename QueryPointRange::const_iterator it = queries.begin();
it != queries.end(); ++ it)
*(output ++) = kdtree.compute_k_scale (it, query_point_map);
return output;
}
/// \cond SKIP_IN_MANUAL
// variant with default NP
template <typename PointRange,
typename QueryPointRange,
typename OutputIterator
>
OutputIterator
estimate_local_k_neighbor_scales(
const PointRange& points,
const QueryPointRange& queries,
OutputIterator output)
{
return estimate_local_k_neighbor_scales
(points, queries, output, CGAL::Point_set_processing_3::parameters::all_default(points));
}
/// \endcond
/**
\ingroup PkgPointSetProcessingAlgorithms
Estimates the global scale in a K nearest neighbors sense. The
computed scale corresponds to the smallest scale such that the K
subsets of points have the appearance of a surface in 3D or the
appearance of a curve in 2D (see \ref Point_set_processing_3Scale).
\tparam PointRange is a model of `ConstRange`. The value type of
its iterator is the key type of the named parameter `point_map`.
\param points input point range.
\param np optional sequence of \ref psp_namedparameters "Named Parameters" among the ones listed below.
\cgalNamedParamsBegin
\cgalParamBegin{point_map} a model of `ReadablePropertyMap` with
value type `geom_traits::Point_3` (or `geom_traits::Point_2`).
If this parameter is omitted,
`CGAL::Identity_property_map<geom_traits::Point_3>` (or
`CGAL::Identity_property_map<geom_traits::Point_2>`) is
used.\cgalParamEnd
\cgalParamBegin{geom_traits} an instance of a geometric traits class, model of `Kernel`\cgalParamEnd
\cgalNamedParamsEnd
\note This function accepts both 2D and 3D points.
\return The estimated scale in the K nearest neighbors sense.
*/
template <typename PointRange,
typename NamedParameters
>
std::size_t
estimate_global_k_neighbor_scale(
const PointRange& points,
const NamedParameters& np)
{
using boost::choose_param;
typedef typename Point_set_processing_3::GetPointMap<PointRange, NamedParameters>::const_type PointMap;
PointMap point_map = choose_param(get_param(np, internal_np::point_map), PointMap());
std::vector<std::size_t> scales;
estimate_local_k_neighbor_scales (points, points, std::back_inserter (scales), np.query_point_map(point_map));
std::sort (scales.begin(), scales.end());
return scales[scales.size() / 2];
}
/// \cond SKIP_IN_MANUAL
// variant with default NP
template <typename PointRange>
std::size_t
estimate_global_k_neighbor_scale(const PointRange& points)
{
return estimate_global_k_neighbor_scale
(points, CGAL::Point_set_processing_3::parameters::all_default(points));
}
/// \endcond
/**
\ingroup PkgPointSetProcessingAlgorithms
Estimates the local scale in a range sense on a set of
user-defined query points. The computed scales correspond to the
smallest scales such that the subsets of points included in the
sphere range have the appearance of a surface in 3D or the
appearance of a curve in 2D (see \ref Point_set_processing_3Scale).
\tparam PointRange is a model of `ConstRange`. The value type of
its iterator is the key type of the named parameter `point_map`.
\tparam QueryPointRange is a model of `ConstRange`. The value type of
its iterator is the key type of the named parameter `query_point_map`.
\tparam OutputIterator is used to store the computed scales. It accepts
values of type `geom_traits::FT`.
\param points input point range.
\param queries range of locations where scale must be estimated
\param output iterator to store the computed scales
\param np optional sequence of \ref psp_namedparameters "Named Parameters" among the ones listed below.
\cgalNamedParamsBegin
\cgalParamBegin{point_map} a model of `ReadablePropertyMap` with
value type `geom_traits::Point_3` (or `geom_traits::Point_2`).
If this parameter is omitted,
`CGAL::Identity_property_map<geom_traits::Point_3>` (or
`CGAL::Identity_property_map<geom_traits::Point_2>`) is
used.\cgalParamEnd
\cgalParamBegin{query_point_map} a model of `ReadablePropertyMap` with
value type `geom_traits::Point_3` (or `geom_traits::Point_2`).
If this parameter is omitted,
`CGAL::Identity_property_map<geom_traits::Point_3>` (or
`CGAL::Identity_property_map<geom_traits::Point_2>`) is
used.\cgalParamEnd
\cgalParamBegin{geom_traits} an instance of a geometric traits class, model of `Kernel`\cgalParamEnd
\cgalNamedParamsEnd
\note This function accepts both 2D and 3D points, but sample
points and query must have the same dimension.
*/
template <typename PointRange,
typename QueryPointRange,
typename OutputIterator,
typename NamedParameters
>
OutputIterator
estimate_local_range_scales(
const PointRange& points,
const QueryPointRange& queries,
OutputIterator output,
const NamedParameters& np)
{
using boost::choose_param;
typedef typename Point_set_processing_3::GetPointMap<PointRange, NamedParameters>::const_type PointMap;
typedef typename Point_set_processing_3::GetQueryPointMap<QueryPointRange, NamedParameters>::const_type QueryPointMap;
typedef typename Point_set_processing_3::GetK<PointRange, NamedParameters>::Kernel Kernel;
typedef typename boost::property_traits<PointMap>::value_type Point_d;
PointMap point_map = choose_param(get_param(np, internal_np::point_map), PointMap());
QueryPointMap query_point_map = choose_param(get_param(np, internal_np::query_point_map), QueryPointMap());
// Build multi-scale KD-tree
internal::Quick_multiscale_approximate_knn_distance<Kernel, Point_d> kdtree (points.begin(),
points.end(),
point_map);
// Compute local scales everywhere
for (typename QueryPointRange::const_iterator it = queries.begin(); it != queries.end(); ++ it)
*(output ++) = kdtree.compute_range_scale (it, query_point_map);
return output;
}
/// \cond SKIP_IN_MANUAL
// variant with default NP
template <typename PointRange,
typename QueryPointRange,
typename OutputIterator
>
OutputIterator
estimate_local_range_scales(
const PointRange& points,
const QueryPointRange& queries,
OutputIterator output)
{
return estimate_local_range_scales
(points, queries, output, CGAL::Point_set_processing_3::parameters::all_default(points));
}
/// \endcond
/**
\ingroup PkgPointSetProcessingAlgorithms
Estimates the global scale in a range sense. The computed scale
corresponds to the smallest scale such that the subsets of points
inside the sphere range have the appearance of a surface in 3D or
the appearance of a curve in 2D (see \ref Point_set_processing_3Scale).
\tparam PointRange is a model of `ConstRange`. The value type of
its iterator is the key type of the named parameter `point_map`.
\param points input point range.
\param np optional sequence of \ref psp_namedparameters "Named Parameters" among the ones listed below.
\cgalNamedParamsBegin
\cgalParamBegin{point_map} a model of `ReadablePropertyMap` with
value type `geom_traits::Point_3` (or `geom_traits::Point_2`).
If this parameter is omitted,
`CGAL::Identity_property_map<geom_traits::Point_3>` (or
`CGAL::Identity_property_map<geom_traits::Point_2>`) is
used.\cgalParamEnd
\cgalParamBegin{geom_traits} an instance of a geometric traits class, model of `Kernel`\cgalParamEnd
\cgalNamedParamsEnd
\note This function accepts both 2D and 3D points.
\return The estimated scale in the range sense. The return type `FT` is a number type. It is
either deduced from the `geom_traits` \ref psp_namedparameters "Named Parameters" if provided,
or the geometric traits class deduced from the point property map
of `points`.
*/
template <typename PointRange,
typename NamedParameters
>
#ifdef DOXYGEN_RUNNING
FT
#else
typename Point_set_processing_3::GetK<PointRange, NamedParameters>::Kernel::FT
#endif
estimate_global_range_scale(
const PointRange& points,
const NamedParameters& np)
{
using boost::choose_param;
std::vector<double> scales;
typedef typename Point_set_processing_3::GetPointMap<PointRange, NamedParameters>::const_type PointMap;
PointMap point_map = choose_param(get_param(np, internal_np::point_map), PointMap());
estimate_local_range_scales (points, points, std::back_inserter (scales), np.query_point_map(point_map));
std::sort (scales.begin(), scales.end());
return std::sqrt (scales[scales.size() / 2]);
}
/// \cond SKIP_IN_MANUAL
// variant with default NP
template <typename PointRange>
typename Point_set_processing_3::GetFT<PointRange>::type
estimate_global_range_scale(const PointRange& points)
{
return estimate_global_range_scale
(points, CGAL::Point_set_processing_3::parameters::all_default(points));
}
#ifndef CGAL_NO_DEPRECATED_CODE
// deprecated API
template <typename SamplesInputIterator,
typename SamplesPointMap,
typename QueriesInputIterator,
typename QueriesPointMap,
typename OutputIterator,
typename Kernel
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_local_k_neighbor_scales(), please update your code")
OutputIterator
estimate_local_k_neighbor_scales(
SamplesInputIterator first, ///< iterator over the first input sample.
SamplesInputIterator beyond, ///< past-the-end iterator over the input samples.
SamplesPointMap samples_map, ///< property map: value_type of InputIterator -> Point_3 or Point_2
QueriesInputIterator first_query, ///< iterator over the first point where scale must be estimated
QueriesInputIterator beyond_query, ///< past-the-end iterator over the points where scale must be estimated
QueriesPointMap queries_map, ///< property map: value_type of InputIterator -> Point_3 or Point_2
OutputIterator output, ///< output iterator to store the computed scales
const Kernel& /*kernel*/) ///< geometric traits.
{
return estimate_local_k_neighbor_scales
(CGAL::make_range (first, beyond),
CGAL::make_range (first_query, beyond_query),
output,
CGAL::parameters::point_map (samples_map).
query_point_map (queries_map).
geom_traits (Kernel()));
}
// deprecated API
template <typename SamplesInputIterator,
typename SamplesPointMap,
typename QueriesInputIterator,
typename QueriesPointMap,
typename OutputIterator
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_local_k_neighbor_scales(), please update your code")
OutputIterator
estimate_local_k_neighbor_scales(
SamplesInputIterator first, ///< iterator over the first input sample.
SamplesInputIterator beyond, ///< past-the-end iterator over the input samples.
SamplesPointMap samples_map, ///< property map: value_type of InputIterator -> Point_3 or Point_2
QueriesInputIterator first_query, ///< iterator over the first point where scale must be estimated
QueriesInputIterator beyond_query, ///< past-the-end iterator over the points where scale must be estimated
QueriesPointMap queries_map, ///< property map: value_type of InputIterator -> Point_3 or Point_2
OutputIterator output) ///< output iterator to store the computed scales
{
return estimate_local_k_neighbor_scales
(CGAL::make_range (first, beyond),
CGAL::make_range (first_query, beyond_query),
output,
CGAL::parameters::point_map (samples_map).
query_point_map (queries_map));
}
// deprecated API
template <typename SamplesInputIterator,
typename QueriesInputIterator,
typename OutputIterator
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_local_k_neighbor_scales(), please update your code")
OutputIterator
estimate_local_k_neighbor_scales(
SamplesInputIterator first, ///< iterator over the first input sample.
SamplesInputIterator beyond, ///< past-the-end iterator over the input samples.
QueriesInputIterator first_query, ///< iterator over the first point where scale must be estimated
QueriesInputIterator beyond_query, ///< past-the-end iterator over the points where scale must be estimated
OutputIterator output) ///< output iterator to store the computed scales
{
return estimate_local_k_neighbor_scales
(CGAL::make_range (first, beyond),
CGAL::make_range (first_query, beyond_query),
output);
}
// deprecated API
template <typename InputIterator,
typename PointMap,
typename Kernel
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_global_k_neighbor_scale(), please update your code")
std::size_t
estimate_global_k_neighbor_scale(
InputIterator first, ///< iterator over the first input point.
InputIterator beyond, ///< past-the-end iterator over the input points.
PointMap point_map, ///< property map: value_type of InputIterator -> Point_3 or Point_2
const Kernel& kernel) ///< geometric traits.
{
return estimate_global_k_neighbor_scale
(CGAL::make_range (first, beyond),
CGAL::parameters::point_map (point_map).
geom_traits (kernel));
}
// deprecated API
template <typename InputIterator,
typename PointMap
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_global_k_neighbor_scale(), please update your code")
std::size_t
estimate_global_k_neighbor_scale(
InputIterator first, ///< iterator over the first input point.
InputIterator beyond, ///< past-the-end iterator over the input points.
PointMap point_map) ///< property map: value_type of InputIterator -> Point_3 or Point_2
{
return estimate_global_k_neighbor_scale
(CGAL::make_range (first, beyond),
CGAL::parameters::point_map (point_map));
}
// deprecated API
template <typename InputIterator
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_global_k_neighbor_scale(), please update your code")
std::size_t
estimate_global_k_neighbor_scale(
InputIterator first, ///< iterator over the first input point.
InputIterator beyond) ///< past-the-end iterator over the input points.
{
return estimate_global_k_neighbor_scale
(CGAL::make_range (first, beyond));
}
// deprecated API
template <typename SamplesInputIterator,
typename SamplesPointMap,
typename QueriesInputIterator,
typename QueriesPointMap,
typename OutputIterator,
typename Kernel
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_local_range_scales(), please update your code")
OutputIterator
estimate_local_range_scales(
SamplesInputIterator first, ///< iterator over the first input sample.
SamplesInputIterator beyond, ///< past-the-end iterator over the input samples.
SamplesPointMap samples_map, ///< property map: value_type of InputIterator -> Point_3 or Point_2
QueriesInputIterator first_query, ///< iterator over the first point where scale must be estimated
QueriesInputIterator beyond_query, ///< past-the-end iterator over the points where scale must be estimated
QueriesPointMap queries_map, ///< property map: value_type of InputIterator -> Point_3 or Point_2
OutputIterator output, ///< output iterator to store the computed scales
const Kernel& /*kernel*/) ///< geometric traits.
{
return estimate_local_range_scales
(CGAL::make_range (first, beyond),
CGAL::make_range (first_query, beyond_query),
output,
CGAL::parameters::point_map (samples_map).
query_point_map (queries_map).
geom_traits (Kernel()));
}
// deprecated API
template <typename SamplesInputIterator,
typename SamplesPointMap,
typename QueriesInputIterator,
typename QueriesPointMap,
typename OutputIterator
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_local_range_scales(), please update your code")
OutputIterator
estimate_local_range_scales(
SamplesInputIterator first, ///< iterator over the first input sample.
SamplesInputIterator beyond, ///< past-the-end iterator over the input samples.
SamplesPointMap samples_map, ///< property map: value_type of InputIterator -> Point_3 or Point_2
QueriesInputIterator first_query, ///< iterator over the first point where scale must be estimated
QueriesInputIterator beyond_query, ///< past-the-end iterator over the points where scale must be estimated
QueriesPointMap queries_map, ///< property map: value_type of InputIterator -> Point_3 or Point_2
OutputIterator output) ///< output iterator to store the computed scales
{
return estimate_local_range_scales
(CGAL::make_range (first, beyond),
CGAL::make_range (first_query, beyond_query),
output,
CGAL::parameters::point_map (samples_map).
query_point_map (queries_map));
}
// deprecated API
template <typename SamplesInputIterator,
typename QueriesInputIterator,
typename OutputIterator
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_local_range_scales(), please update your code")
OutputIterator
estimate_local_range_scales(
SamplesInputIterator first, ///< iterator over the first input sample.
SamplesInputIterator beyond, ///< past-the-end iterator over the input samples.
QueriesInputIterator first_query, ///< iterator over the first point where scale must be estimated
QueriesInputIterator beyond_query, ///< past-the-end iterator over the points where scale must be estimated
OutputIterator output) ///< output iterator to store the computed scales
{
return estimate_local_range_scales
(CGAL::make_range (first, beyond),
CGAL::make_range (first_query, beyond_query),
output);
}
// deprecated API
template <typename InputIterator,
typename PointMap,
typename Kernel
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_global_range_scale(), please update your code")
double
estimate_global_range_scale(
InputIterator first, ///< iterator over the first input point.
InputIterator beyond, ///< past-the-end iterator over the input points.
PointMap point_map, ///< property map: value_type of InputIterator -> Point_3 or Point_3
const Kernel& kernel) ///< geometric traits.
{
return estimate_global_range_scale
(CGAL::make_range (first, beyond),
CGAL::parameters::point_map (point_map).
geom_traits (kernel));
}
// deprecated API
template <typename InputIterator,
typename PointMap
>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_global_range_scale(), please update your code")
double
estimate_global_range_scale(
InputIterator first, ///< iterator over the first input point.
InputIterator beyond, ///< past-the-end iterator over the input points.
PointMap point_map) ///< property map: value_type of InputIterator -> Point_3 or Point_3
{
return estimate_global_range_scale
(CGAL::make_range (first, beyond),
CGAL::parameters::point_map (point_map));
}
// deprecated API
template <typename InputIterator>
CGAL_DEPRECATED_MSG("you are using the deprecated V1 API of CGAL::estimate_global_range_scale(), please update your code")
double
estimate_global_range_scale(
InputIterator first, ///< iterator over the first input point.
InputIterator beyond) ///< past-the-end iterator over the input points.
{
return estimate_global_range_scale
(CGAL::make_range (first, beyond));
}
#endif // CGAL_NO_DEPRECATED_CODE
/// \endcond
} //namespace CGAL
#include <CGAL/enable_warnings.h>
#endif // CGAL_ESTIMATE_SCALE_3_H