1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
|
// Copyright (c) 2018 GeometryFactory Sarl (France).
// All rights reserved.
//
// This file is part of CGAL (www.cgal.org).
//
// $URL: https://github.com/CGAL/cgal/blob/v6.1.1/Classification/include/CGAL/Classification/Feature/Cluster_size.h $
// $Id: include/CGAL/Classification/Feature/Cluster_size.h 08b27d3db14 $
// SPDX-License-Identifier: GPL-3.0-or-later OR LicenseRef-Commercial
//
// Author(s) : Simon Giraudot
#ifndef CGAL_CLASSIFICATION_FEATURE_CLUSTER_SIZE_H
#define CGAL_CLASSIFICATION_FEATURE_CLUSTER_SIZE_H
#include <CGAL/license/Classification.h>
#include <vector>
#include <CGAL/Classification/Feature_base.h>
namespace CGAL {
namespace Classification {
namespace Feature {
/*!
\ingroup PkgClassificationCluster
\brief %Feature that returns the size of each cluster.
Its default name is "cluster_size".
*/
class Cluster_size : public CGAL::Classification::Feature_base
{
std::vector<float> m_values;
public:
/*!
\brief constructs the feature.
\tparam ClusterRange model of `ConstRange`. Its iterator type
is `RandomAccessIterator` and its value type is the key type of
`Cluster`.
\param clusters input range.
*/
template <typename ClusterRange>
Cluster_size (ClusterRange& clusters)
{
this->set_name ("cluster_size");
m_values.reserve (clusters.size());
for (std::size_t i = 0; i < clusters.size(); ++ i)
m_values.push_back (float(clusters[i].size()));
}
/// \cond SKIP_IN_MANUAL
virtual float value (std::size_t cluster_index)
{
return m_values[cluster_index];
}
/// \endcond
};
} // namespace Feature
} // namespace Classification
} // namespace CGAL
#endif // CGAL_CLASSIFICATION_FEATURE_CLUSTER_SIZE_H
|
