A class to compute the Generalised Forman-Ricci curvature for a Simplicial Complex from a given point cloud data.
Project description
GeneralisedFormanRicci
This 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.
Many thanks to stephenhky and saibalmars for their packages MoguTDA and GraphRicciCurvature respectively. Partial code was modified from MoguTDA for the computation of the boundary matrices.
Installation via conda-forge
Installing generalisedformanricci
from the conda-forge
channel can be achieved by adding conda-forge
to your channels with:
conda config --add channels conda-forge
Once the conda-forge
channel has been enabled, generalisedformanricci
can be installed with:
conda install generalisedformanricci
It is possible to list all of the versions of generalisedformanricci
available on your platform with:
conda search generalisedformanricci --channel conda-forge
Alternatively, generalisedformanricci
can be installed just by conda install -c conda-forge generalisedformanricci
.
Installation via pip
pip install GeneralisedFormanRicci
Upgrading via pip install --upgrade GeneralisedFormanRicci
Package Requirement
Simple Example
from GeneralisedFormanRicci.frc import GeneralisedFormanRicci
data = [[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]]
for f in [0, 0.5, 1, 2, 3]:
sc = GeneralisedFormanRicci(data, method = "rips", epsilon = f)
sc.compute_forman()
sc.compute_bochner()
References
- MoguTDA: https://github.com/stephenhky/MoguTDA
- GraphRicciCurvature: https://github.com/saibalmars/GraphRicciCurvature
- Forman, R. (2003). Bochner's method for cell complexes and combinatorial Ricci curvature. Discrete and Computational Geometry, 29(3), 323-374.
- Forman, R. (1999). Combinatorial Differential Topology and Geometry. New Perspectives in Algebraic Combinatorics, 38, 177.
Cite
If you use this code in your research, please considering cite our paper:
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file GeneralisedFormanRicci-0.3.tar.gz
.
File metadata
- Download URL: GeneralisedFormanRicci-0.3.tar.gz
- Upload date:
- Size: 5.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.1.0.post20200704 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.7.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | bbb5899beaa6f0cea1f0b859cdc217604cdce57fb662eedcc516bbf59ba25b12 |
|
MD5 | afa5fb7e04410e06eca1e4a9b3f25bb1 |
|
BLAKE2b-256 | 25001f8ce6a6e2732e1050a47310196bb4b5abae08b66a111f16bdbaa29656a3 |
File details
Details for the file GeneralisedFormanRicci-0.3-py3-none-any.whl
.
File metadata
- Download URL: GeneralisedFormanRicci-0.3-py3-none-any.whl
- Upload date:
- Size: 9.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.1.0.post20200704 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.7.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6eadc17bbbcdcf0d8ed1c3719272217f740ba070effb210957c0f053dc7b725a |
|
MD5 | 348c822914a47df884071ce523147136 |
|
BLAKE2b-256 | 17bba2a3fc71f55b25d9ba8ad5d3e7ae19f695db8df21737bdb03df0bded8343 |