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peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["differential-geometry","forman","graph-network","networkx","ricci-curvature","simplicial-complex"],"created_at":"2025-10-21T19:46:48.774Z","updated_at":"2026-02-21T18:03:26.524Z","avatar_url":"https://github.com/ExpectozJJ.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/ExpectozJJ/GeneralisedFormanRicci/master?filepath=tutorial%2FGeneralisedFormanRicci-demo.ipynb)\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ExpectozJJ/GeneralisedFormanRicci/blob/master/tutorial/GeneralisedFormanRicci-demo.ipynb)\n[![Downloads](https://pepy.tech/badge/generalisedformanricci)](https://pepy.tech/project/generalisedformanricci)\n[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) \n![Azure](https://dev.azure.com/conda-forge/feedstock-builds/_apis/build/status/generalisedformanricci-feedstock?branchName=master)\n\n# GeneralisedFormanRicci\nThis code computes the Forman Ricci Curvature for simplicial complex generated from a given point cloud data. The implementation is based on the combinatorial definition of Forman Ricci curvature defined by Robin Forman. This implementation generalises beyond the simplified version implemented in saibalmars/GraphRicciCurvature github.\n\nMany thanks to stephenhky and saibalmars for their packages MoguTDA and GraphRicciCurvature respectively. \nPartial code was modified from MoguTDA for the computation of the boundary matrices. \n\n## Installation via conda-forge\n\n[![Anaconda-Server Badge](https://img.shields.io/badge/install%20with%20-conda--forge-blue)](https://anaconda.org/conda-forge/generalisedformanricci)\n![Conda (channel only)](https://img.shields.io/conda/vn/conda-forge/generalisedformanricci)\n![Conda](https://img.shields.io/conda/dn/conda-forge/generalisedformanricci?color=green)\n![Conda](https://img.shields.io/conda/pn/conda-forge/generalisedformanricci?color=red)\n\nInstalling `generalisedformanricci` from the `conda-forge` channel can be achieved by adding `conda-forge` to your channels with:\n\n```\nconda config --add channels conda-forge\n```\n\nOnce the `conda-forge` channel has been enabled, `generalisedformanricci` can be installed with:\n\n```\nconda install generalisedformanricci\n```\n\nIt is possible to list all of the versions of `generalisedformanricci` available on your platform with:\n\n```\nconda search generalisedformanricci --channel conda-forge\n```\n\nAlternatively, `generalisedformanricci` can be installed just by `conda install -c conda-forge generalisedformanricci`.\n\n## Installation via pip\n\n![PyPI](https://img.shields.io/pypi/v/GeneralisedFormanRicci)\n![PyPI - Downloads](https://img.shields.io/pypi/dw/GeneralisedFormanRicci)\n\n`pip install GeneralisedFormanRicci`\n\nUpgrading via `pip install --upgrade GeneralisedFormanRicci`\n\n## Package Requirement\n\n* [NetworkX](https://github.com/networkx/networkx) \u003e= 2.0 (Based Graph library)\n* [GUDHI](https://github.com/GUDHI) (Simplicial Complex Library)\n* [NumPy](https://github.com/numpy/numpy)\n* [SciPy](https://github.com/scipy/scipy)\n\n## Simple Example\n\n```\nfrom GeneralisedFormanRicci.frc import GeneralisedFormanRicci\n\ndata = [[0.8, 2.6], [0.2, 1.0], [0.9, 0.5], [2.7, 1.8], [1.7, 0.5], [2.5, 2.5], [2.4, 1.0], [0.6, 0.9], [0.4, 2.2]]\nfor f in [0, 0.5, 1, 2, 3]:\n    sc = GeneralisedFormanRicci(data, method = \"rips\", epsilon = f)\n    sc.compute_forman()\n    sc.compute_bochner()\n```\n\n## References\n* MoguTDA: https://github.com/stephenhky/MoguTDA\n* GraphRicciCurvature: https://github.com/saibalmars/GraphRicciCurvature\n* Forman, R. (2003). Bochner's method for cell complexes and combinatorial Ricci curvature. Discrete and Computational Geometry, 29(3), 323-374.\n* Forman, R. (1999). Combinatorial Differential Topology and Geometry. New Perspectives in Algebraic Combinatorics, 38, 177.\n\n## Cite \nIf you use this code in your research, please considering cite our paper:\n* JunJie Wee and Kelin Xia, Ollivier Persistent Ricci Curvature-Based Machine Learning for the Protein–Ligand Binding Affinity Prediction, Journal of Chemical Information and Modeling 2021 61 (4), 1617-1626\n* JunJie Wee, Kelin Xia, Forman persistent Ricci curvature (FPRC)-based machine learning models for protein–ligand binding affinity prediction, Briefings in Bioinformatics, 2021;, bbab136\n* D. Vijay Anand, Qiang Xu, JunJie Wee, Kelin Xia, Tze Chien Sum. Topological Feature Engineering for Machine Learning Based Halide Perovskite Materials Design. npj Computational Materials. 8, 203. 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