36 #if EIGEN_VERSION_AT_LEAST(2,92,0)
40 #include "Eigen/Array"
44 #include <boost/any.hpp>
213 #define NABO_VERSION "1.0.4"
214 #define NABO_VERSION_INT 10004
226 Parameters(
const std::string& key,
const boost::any& value){(*this)[key] = value;}
233 T
get(
const std::string& key,
const T& defaultValue)
const
235 const_iterator it(find(key));
237 return boost::any_cast<T>(it->second);
248 typedef typename Eigen::Matrix<T, Eigen::Dynamic, 1>
Vector;
250 typedef typename Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
Matrix;
254 typedef typename Eigen::Matrix<Index, Eigen::Dynamic, 1>
IndexVector;
256 typedef typename Eigen::Matrix<Index, Eigen::Dynamic, Eigen::Dynamic>
IndexMatrix;
305 unsigned long knn(
const Vector& query,
IndexVector& indices,
Vector& dists2,
const Index k = 1,
const T epsilon = 0,
const unsigned optionFlags = 0,
const T maxRadius = std::numeric_limits<T>::infinity())
const;
318 virtual unsigned long knn(
const Matrix& query,
IndexMatrix& indices,
Matrix& dists2,
const Index k = 1,
const T epsilon = 0,
const unsigned optionFlags = 0,
const T maxRadius = std::numeric_limits<T>::infinity())
const = 0;
331 virtual unsigned long knn(
const Matrix& query,
IndexMatrix& indices,
Matrix& dists2,
const Vector& maxRadii,
const Index k = 1,
const T epsilon = 0,
const unsigned optionFlags = 0)
const = 0;
Eigen::Matrix< Index, Eigen::Dynamic, 1 > IndexVector
a vector of indices to data points
Definition: nabo.h:254
static NearestNeighbourSearch * createKDTreeTreeHeap(const Matrix &cloud, const Index dim=std::numeric_limits< Index >::max(), const unsigned creationOptionFlags=0, const Parameters &additionalParameters=Parameters())
Create a nearest-neighbour search, using a kd-tree with tree heap, good for large k (~from 30) ...
Definition: nabo.cpp:155
Parameters()
Create an empty parameter vector.
Definition: nabo.h:221
const Index dim
the dimensionality of the data-point cloud
Definition: nabo.h:261
const Vector minBound
the low bound of the search space (axis-aligned bounding box)
Definition: nabo.h:265
brute-force using openCL, only available if OpenCL enabled, UNSTABLE API
Definition: nabo.h:277
void checkSizesKnn(const Matrix &query, const IndexMatrix &indices, const Matrix &dists2, const Index k, const unsigned optionFlags, const Vector *maxRadii=0) const
Make sure that the output matrices have the right sizes. Throw an exception otherwise.
Definition: nabo.cpp:84
Eigen::Matrix< Index, Eigen::Dynamic, Eigen::Dynamic > IndexMatrix
a matrix of indices to data points
Definition: nabo.h:256
NearestNeighbourSearch(const Matrix &cloud, const Index dim, const unsigned creationOptionFlags)
constructor
Definition: nabo.cpp:50
Nearest neighbour search interface, templatized on scalar type.
Definition: nabo.h:245
SearchType
type of search
Definition: nabo.h:270
static NearestNeighbourSearch * create(const Matrix &cloud, const Index dim=std::numeric_limits< Index >::max(), const SearchType preferedType=KDTREE_LINEAR_HEAP, const unsigned creationOptionFlags=0, const Parameters &additionalParameters=Parameters())
Create a nearest-neighbour search.
Definition: nabo.cpp:116
brute force, check distance to every point in the data
Definition: nabo.h:272
SearchOptionFlags
search option
Definition: nabo.h:288
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > Matrix
a column-major Eigen matrix in which each column is a point; this matrix has dim rows ...
Definition: nabo.h:250
const unsigned creationOptionFlags
creation options
Definition: nabo.h:263
int Index
an index to a Vector or a Matrix, for refering to data points
Definition: nabo.h:252
const Vector maxBound
the high bound of the search space (axis-aligned bounding box)
Definition: nabo.h:267
static NearestNeighbourSearch * createKDTreeLinearHeap(const Matrix &cloud, const Index dim=std::numeric_limits< Index >::max(), const unsigned creationOptionFlags=0, const Parameters &additionalParameters=Parameters())
Create a nearest-neighbour search, using a kd-tree with linear heap, good for small k (~up to 30) ...
Definition: nabo.cpp:147
NearestNeighbourSearch< double > NNSearchD
nearest neighbour search with scalars of type double
Definition: nabo.h:390
kd-tree with tree heap, good for large k (~from 30)
Definition: nabo.h:274
sort points by distances, when k > 1; do not sort by default
Definition: nabo.h:291
CreationOptionFlags
creation option
Definition: nabo.h:282
Parameter vector.
Definition: nabo.h:218
virtual ~NearestNeighbourSearch()
virtual destructor
Definition: nabo.h:369
static NearestNeighbourSearch * createBruteForce(const Matrix &cloud, const Index dim=std::numeric_limits< Index >::max(), const unsigned creationOptionFlags=0)
Create a nearest-neighbour search, using brute-force search, useful for comparison only...
Definition: nabo.cpp:139
perform statistics on the number of points touched
Definition: nabo.h:284
unsigned long knn(const Vector &query, IndexVector &indices, Vector &dists2, const Index k=1, const T epsilon=0, const unsigned optionFlags=0, const T maxRadius=std::numeric_limits< T >::infinity()) const
Find the k nearest neighbours of query.
Definition: nabo.cpp:64
kd-tree using openCL, pt in nodes, only available if OpenCL enabled, UNSTABLE API ...
Definition: nabo.h:275
allows the return of the same point as the query, if this point is in the data cloud; forbidden by de...
Definition: nabo.h:290
kd-tree using openCL, pt in leaves, only available if OpenCL enabled, UNSTABLE API ...
Definition: nabo.h:276
kd-tree with linear heap, good for small k (~up to 30)
Definition: nabo.h:273
Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
an Eigen vector of type T, to hold the coordinates of a point
Definition: nabo.h:248
Parameters(const std::string &key, const boost::any &value)
Create a parameter vector with a single entry.
Definition: nabo.h:226
const Matrix & cloud
the reference to the data-point cloud, which must remain valid during the lifetime of the NearestNeig...
Definition: nabo.h:259
number of search types
Definition: nabo.h:278
NearestNeighbourSearch< float > NNSearchF
nearest neighbour search with scalars of type float
Definition: nabo.h:388