README.md
In Rnanoflann: Extremely Fast Nearest Neighbor Search

Rnanoflann

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 and radius.
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 via C++. Just #include "Rnanoflann.h". The available implemented function are use Rcpp and RcppArmadillo. For custom matrices you need to implement you own adaptor (see above).