#include <KDTree.h>

Public Types
using	KdTreeT = nanoflann::KDTreeSingleIndexAdaptor< nanoflann::L2_Simple_Adaptor< Real, PointListAdaptor< Point >, Real, std::size_t >, PointListAdaptor< Point >, LIBMESH_DIM, std::size_t >

Public Member Functions
	KDTree (const std::vector< Point > &master_points, unsigned int max_leaf_size)

virtual	~KDTree ()=default

void	neighborSearch (const Point &query_point, unsigned int patch_size, std::vector< std::size_t > &return_index)

void	neighborSearch (const Point &query_point, unsigned int patch_size, std::vector< std::size_t > &return_index, std::vector< Real > &return_dist_sqr)

void	radiusSearch (const Point &query_point, Real radius, std::vector< nanoflann::ResultItem< std::size_t, Real > > &indices_dist)

std::size_t	numberCandidatePoints ()

Protected Attributes
PointListAdaptor< Point >	_point_list_adaptor

std::unique_ptr< KdTreeT >	_kd_tree

Detailed Description

Definition at line 28 of file KDTree.h.

Member Typedef Documentation

◆ KdTreeT

using KDTree::KdTreeT = nanoflann::KDTreeSingleIndexAdaptor< nanoflann::L2_Simple_Adaptor<Real, PointListAdaptor<Point>, Real, std::size_t>, PointListAdaptor<Point>, LIBMESH_DIM, std::size_t>

Definition at line 50 of file KDTree.h.

Constructor & Destructor Documentation

◆ KDTree()

KDTree::KDTree	(	const std::vector< Point > &	master_points,
		unsigned int	max_leaf_size
	)

Definition at line 27 of file KDTree.C.

  : _point_list_adaptor(master_points.begin(), master_points.end()),
    _kd_tree(std::make_unique<KdTreeT>(
        LIBMESH_DIM, _point_list_adaptor, nanoflann::KDTreeSingleIndexAdaptorParams(max_leaf_size)))
{
  mooseAssert(_kd_tree != nullptr, "KDTree was not properly initialized.");
 
  _kd_tree->buildIndex();
}

◆ ~KDTree()

virtual KDTree::~KDTree ( )

virtualdefault

Member Function Documentation

◆ neighborSearch() [1/2]

void KDTree::neighborSearch	(	const Point &	query_point,
		unsigned int	patch_size,
		std::vector< std::size_t > &	return_index
	)

Definition at line 38 of file KDTree.C.

{
  std::vector<Real> return_dist_sqr(patch_size);
  neighborSearch(query_point, patch_size, return_index, return_dist_sqr);
}

Referenced by neighborSearch(), and SecondaryNeighborhoodThread::operator()().

◆ neighborSearch() [2/2]

void KDTree::neighborSearch	(	const Point &	query_point,
		unsigned int	patch_size,
		std::vector< std::size_t > &	return_index,
		std::vector< Real > &	return_dist_sqr
	)

Definition at line 47 of file KDTree.C.

{
  return_index.resize(patch_size);
 
  std::size_t n_result =
      _kd_tree->knnSearch(&query_point(0), patch_size, return_index.data(), return_dist_sqr.data());
 
  if (n_result == 0)
    mooseError("Unable to find closest node!");
 
  return_index.resize(n_result);
  return_dist_sqr.resize(n_result);
}

◆ numberCandidatePoints()

std::size_t KDTree::numberCandidatePoints ( )

Definition at line 74 of file KDTree.C.

{
  return _point_list_adaptor.kdtree_get_point_count();
}

◆ radiusSearch()

void KDTree::radiusSearch	(	const Point &	query_point,
		Real	radius,
		std::vector< nanoflann::ResultItem< std::size_t, Real > > &	indices_dist
	)

Definition at line 65 of file KDTree.C.

{
  nanoflann::SearchParameters sp;
  _kd_tree->radiusSearch(&query_point(0), radius * radius, indices_dist, sp);
}

Member Data Documentation

◆ _kd_tree

std::unique_ptr<KdTreeT> KDTree::_kd_tree

protected

Definition at line 61 of file KDTree.h.

Referenced by KDTree(), neighborSearch(), and radiusSearch().

◆ _point_list_adaptor

PointListAdaptor<Point> KDTree::_point_list_adaptor