Point Cloud Library (PCL)  1.14.1-dev
kdtree.hpp
1 /*
2  * Software License Agreement (BSD License)
3  *
4  * Point Cloud Library (PCL) - www.pointclouds.org
5  * Copyright (c) 2012-, Open Perception, Inc.
6  *
7  * All rights reserved.
8  *
9  * Redistribution and use in source and binary forms, with or without
10  * modification, are permitted provided that the following conditions
11  * are met:
12  *
13  * * Redistributions of source code must retain the above copyright
14  * notice, this list of conditions and the following disclaimer.
15  * * Redistributions in binary form must reproduce the above
16  * copyright notice, this list of conditions and the following
17  * disclaimer in the documentation and/or other materials provided
18  * with the distribution.
19  * * Neither the name of the copyright holder(s) nor the names of its
20  * contributors may be used to endorse or promote products derived
21  * from this software without specific prior written permission.
22  *
23  * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
24  * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
25  * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
26  * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
27  * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
28  * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
29  * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
30  * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
31  * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
32  * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
33  * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
34  * POSSIBILITY OF SUCH DAMAGE.
35  *
36  */
37 
38 #ifndef PCL_SEARCH_KDTREE_IMPL_HPP_
39 #define PCL_SEARCH_KDTREE_IMPL_HPP_
40 
41 #include <pcl/search/kdtree.h>
42 
43 ///////////////////////////////////////////////////////////////////////////////////////////
44 template <typename PointT, class Tree>
46  : pcl::search::Search<PointT> ("KdTree", sorted)
47  , tree_ (new Tree (sorted))
48 {
49 }
50 
51 ///////////////////////////////////////////////////////////////////////////////////////////
52 template <typename PointT, class Tree> void
54  const PointRepresentationConstPtr &point_representation)
55 {
56  tree_->setPointRepresentation (point_representation);
57 }
58 
59 ///////////////////////////////////////////////////////////////////////////////////////////
60 template <typename PointT, class Tree> void
62 {
63  sorted_results_ = sorted_results;
64  tree_->setSortedResults (sorted_results);
65 }
66 
67 ///////////////////////////////////////////////////////////////////////////////////////////
68 template <typename PointT, class Tree> void
70 {
71  tree_->setEpsilon (eps);
72 }
73 
74 ///////////////////////////////////////////////////////////////////////////////////////////
75 template <typename PointT, class Tree> bool
77  const PointCloudConstPtr& cloud,
78  const IndicesConstPtr& indices)
79 {
80  tree_->setInputCloud (cloud, indices);
81  input_ = cloud;
82  indices_ = indices;
83  return true;
84 }
85 
86 ///////////////////////////////////////////////////////////////////////////////////////////
87 template <typename PointT, class Tree> int
89  const PointT &point, int k, Indices &k_indices,
90  std::vector<float> &k_sqr_distances) const
91 {
92  return (tree_->nearestKSearch (point, k, k_indices, k_sqr_distances));
93 }
94 
95 ///////////////////////////////////////////////////////////////////////////////////////////
96 template <typename PointT, class Tree> int
98  const PointT& point, double radius,
99  Indices &k_indices, std::vector<float> &k_sqr_distances,
100  unsigned int max_nn) const
101 {
102  return (tree_->radiusSearch (point, radius, k_indices, k_sqr_distances, max_nn));
103 }
104 
105 #define PCL_INSTANTIATE_KdTree(T) template class PCL_EXPORTS pcl::search::KdTree<T>;
106 
107 #endif //#ifndef _PCL_SEARCH_KDTREE_IMPL_HPP_
108 
109 
int nearestKSearch(const PointT &point, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const override
Search for the k-nearest neighbors for the given query point.
Definition: kdtree.hpp:88
void setEpsilon(float eps)
Set the search epsilon precision (error bound) for nearest neighbors searches.
Definition: kdtree.hpp:69
void setSortedResults(bool sorted_results) override
Sets whether the results have to be sorted or not.
Definition: kdtree.hpp:61
typename Search< PointT >::PointCloudConstPtr PointCloudConstPtr
Definition: kdtree.h:65
typename PointRepresentation< PointT >::ConstPtr PointRepresentationConstPtr
Definition: kdtree.h:80
void setPointRepresentation(const PointRepresentationConstPtr &point_representation)
Provide a pointer to the point representation to use to convert points into k-D vectors.
Definition: kdtree.hpp:53
bool setInputCloud(const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr()) override
Provide a pointer to the input dataset.
Definition: kdtree.hpp:76
KdTree(bool sorted=true)
Constructor for KdTree.
Definition: kdtree.hpp:45
int radiusSearch(const PointT &point, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const override
Search for all the nearest neighbors of the query point in a given radius.
Definition: kdtree.hpp:97
Generic search class.
Definition: search.h:75
pcl::IndicesConstPtr IndicesConstPtr
Definition: search.h:85
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
A point structure representing Euclidean xyz coordinates, and the RGB color.