Extremely Fast Nearest Neighbor Search.

Rnanoflann

1. About

Rnanoflann is a wrapper for C++'s library nanoflan which performs nearest neighbors search using kd-trees.

2. Usage

You can use the exported Rnanoflann::nn function or directly nanoflan via LinkignTo mechanism.

2.1. Rnanoflann

Rnanoflann export the function nn that performs nearest neighbors search with options:

• data - An M x dmatrix where each of the M rows is a point.
• points - An N x dmatrix 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

2.2. LinkingTo

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).