napf 0.0.1

(unofficial) `nanoflann` bindings for python and fortran.

napf

nanoflann wrappers for python and maybe fortran.

python

As nanoflann offers template classes, separate classes are implemented in napf for each {datatype, data dimension, distance metric}. All the search functions are equipped with multi-thread execution. Uses numpy.ndarray for data input and output.
Currently, the combinations of following options are supported:

• data type: {double, float, int, long} (corresponds to {np.float64, np.float32, np.int32, np.int64})
• data dimension: {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}
• distance metric: {L1, L2}

quick start

install with pip:

pip install --upgrade pip
pip install napf

Note: in case your system requires a dynamic build, you need a c++11 compatible c++ compiler. To make sure a correct compiler is chosen, set export CC=<your-c-compiler> CXX=<your-c++-compiler>

import napf
import numpy as np

data = <data in 2D array>
queries = <query points in 2D array>

kdt = napf.KDT(tree_data=data, metric=1)

indices, distances = kdt.knn_search(
    queries=queries,
    kneighbors=3,
    nthread=4,
)
...

fortran

maybe...