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\u003cimg alt=\"rdfpy\" src=\"./logo.png\" height=\"100\"\u003e\n\n[![Build Status](https://travis-ci.org/by256/rdfpy.svg?branch=master)](https://travis-ci.org/by256/rdfpy)\n[![Documentation Status](https://readthedocs.org/projects/rdfpy/badge/?version=latest)](https://rdfpy.readthedocs.io/en/latest/?badge=latest)\n[![PyPI version](https://badge.fury.io/py/rdfpy.svg)](https://pypi.org/project/rdfpy/)\n[![License](http://img.shields.io/:license-mit-blue.svg?style=flat-square)](https://github.com/by256/rdfpy/blob/master/LICENSE)\n\n\n**rdfpy** is a Python module for fast computation of 2D and 3D radial distribution functions (RDFs).\n\n## Installation\n\n```shell\n$ pip install rdfpy\n```\n\n## Usage\n\n```python\nimport numpy as np\nfrom rdfpy import rdf\n\n# create random particle coordinates in a 20x20x20 box\ncoords = np.random.uniform(0.0, 20.0, size=(2500, 3))  \n\n# compute radial distribution function with step size = 0.1\ng_r, radii = rdf(coords, dr=0.1)\n```\n\nYou can find a more detailed example in the [Documentation](https://rdfpy.readthedocs.io/).\n\n**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.\n\n## How does it work?\n\n**rdfpy** achieves significant speed-up due to:\n\n- **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.\n- **Multiprocessing**: computation of the particle count histogram is parallelized across multiple cores, with each core sharing the aforementioned k-d tree.\n\n## Authors\n\n**rdfpy** was developed by [Batuhan Yildirim](https://by256.github.io/) under the supervision of [Prof. Jacqueline M. Cole](https://www.phy.cam.ac.uk/directory/colej).\n\n## Citation\n\nIf you use **rdfpy** in your work, please cite:\n\n```\n@software{rdfpy,\n  author       = {Batuhan Yildirim and\n                  Hamish Galloway Brown},\n  title        = {by256/rdfpy: rdfpy-v1.0.0},\n  month        = mar,\n  year         = 2021,\n  publisher    = {Zenodo},\n  version      = {v1.0.0},\n  doi          = {10.5281/zenodo.4625675},\n  url          = {https://doi.org/10.5281/zenodo.4625675}\n}\n```\n\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4625675.svg)](https://doi.org/10.5281/zenodo.4625675)\n\n## Funding\n\nThis project was financially supported by the [Science and Technology Facilities Council (STFC)](https://stfc.ukri.org/) and the [Royal Academy of Engineering](https://www.raeng.org.uk/) (RCSRF1819\\7\\10).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fby256%2Frdfpy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fby256%2Frdfpy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fby256%2Frdfpy/lists"}