rdfpy is a Python module for fast computation of 2D and 3D radial distribution functions (RDFs).
$ pip install rdfpyimport numpy as np
from rdfpy import rdf
# create random particle coordinates in a 20x20x20 box
coords = np.random.uniform(0.0, 20.0, size=(2500, 3))
# compute radial distribution function with step size = 0.1
g_r, radii = rdf(coords, dr=0.1)You can find a more detailed example in the Documentation.
Note: In order for rdfpy to work correctly, your particles should spatially be in a cuboidal box, where the entire box is filled with particles.
rdfpy achieves significant speed-up due to:
- Fast nearest-neighbor look-up: a k-d tree is utilized when counting the number of particles as a function of distance from an origin particle.
- Multiprocessing: computation of the particle count histogram is parallelized across multiple cores, with each core sharing the aforementioned k-d tree.
rdfpy was developed by Batuhan Yildirim under the supervision of Prof. Jacqueline M. Cole.
If you use rdfpy in your work, please cite:
@software{rdfpy,
author = {Batuhan Yildirim and
Hamish Galloway Brown},
title = {by256/rdfpy: rdfpy-v1.0.0},
month = mar,
year = 2021,
publisher = {Zenodo},
version = {v1.0.0},
doi = {10.5281/zenodo.4625675},
url = {https://doi.org/10.5281/zenodo.4625675}
}
This project was financially supported by the Science and Technology Facilities Council (STFC) and the Royal Academy of Engineering (RCSRF1819\7\10).
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent