Rnanoflann is a wrapper for C++'s library nanoflan which performs nearest neighbors search using kd-trees.
You can use the exported Rnanoflann::nn
function or directly nanoflan via LinkignTo mechanism.
Rnanoflann export the function nn
that performs nearest neighbors search with options:
- data - An
M x d
matrix
where each of the M rows is a point. - points - An
N x d
matrix
that will be queried against data. d, the number of columns, must be the same as data. If missing, defaults to data. - parallel - uses omp library to perform parallel search for each point. Default is
FALSE
- cores - the cores that omp will use. Default is zero and it means to automatically compute the numbers of threads.
- search - the supported types are
standard
andradius
. - eps - Error bound. Default is
0.0
. - k - The maximum number of nearest neighbors to compute. The default value is set to the number of rows in data
Add in Description in LinkingTo section the Rnanoflann and then:
- use nanoflann directly. Just
#include "nanoflann.hpp"
. Refer to nanoflan for more details. - use the
Rnanoflann::nn
viaC++
. Just#include "Rnanoflann.h"
. The available implemented function are useRcpp
andRcppArmadillo
. For custom matrices you need to implement you own adaptor (see above).