chromatic_tda
Tool to compute six-packs of persistence diagrams for chromatic point clouds [packaged on PyPI]
Science Score: 77.0%
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Keywords
Repository
Tool to compute six-packs of persistence diagrams for chromatic point clouds [packaged on PyPI]
Basic Info
- Host: GitHub
- Owner: OnDraganov
- License: agpl-3.0
- Language: Jupyter Notebook
- Default Branch: main
- Homepage: https://pypi.org/project/chromatic-tda/
- Size: 4.69 MB
Statistics
- Stars: 14
- Watchers: 1
- Forks: 2
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
chromatic_tda
chromatic_tda is a package for computing six-packs of persistent diagrams of colored point clouds, such as cells on a tissue slide with an information about their type; or 3D stucture of a material composed of different atoms. The six-pack is a topological summary of capturing many aspects of how the different types of points mingle. It consists of kernel, domain, image, codomain, cokernel and relative persistence diagrams.
The main purpose of the code is to provide implementation to experiment with chromatic topological data analysis. Although not completely naive, many aspects of the code can be optimised, especially if only part of the infomration from the six-packs turns out to be interesting in a given application.
The code gives no restriction on the dimension of points or number of colors, but the complexity quickly grows in both parameters. The expected use is points in 2D or 3D with 2 or 3 colors for hundreds to a few thousand points, but both can be increased for toy examples with small numbers of points.
New in 1.1.8: experimental feature extraction. It is now possible to go from a bar back to a loop in a point cloud (or higher-dimensional equivalents). For details, see the last section in the jupyter notebook manual. For now it is released as "experimental". I will be happy for any feedback on this: is it useful? Is it intuitive to use? Is there something confusing/inconvenient/missing?
Cite
If you use the code, please cite the following paper:
S. Cultrera di Montesano, O. Draganov, H. Edelsbrunner, M. Saghafian: Chromatic alpha complexes, Foundations of Data Science (2025). doi: 10.3934/fods.2025003
Installation
Install with pip
The package is uploaded to PyPI, so it can be installed with pip.
Run pip install chromatic_tda.
Install from a file from github project
From the dist folder of the project, you can download the file chromatic_tda-<version>.tar.gz, and install it using pip as pip install <path to the file>.
Install from github project
The project uses poetry for Python dependecy management, which allows you to easily install all you need to run the package:
- Clone the repository
- Install
poetry - Go to the repository folder in terminal
- Run
poetry shell - Run
poetry install - [optional] Run
poetry run pytestto check that the code runs correctly
How to use
The basic use of the package is as follows:
import chromatic_tda as chro
points, labels = ... # load points, labels
chro_alpha = chro.ChromaticAlphaComplex(points, labels) simplicial_complex = chro_alpha.get_simplicial_complex(
sub_complex=‘bi-chromatic’
full_complex=‘all’
relative=‘mono-chromatic’
) # these options make sense for three colors; for two use, e.g., just sub_complex='mono-chromatic'
six_pack = simplicial_complex.bars_six_pack()
chro.plot_six_pack(six_pack)
For more details check the docstrings of the methods and the jupyter notebook file manual (in github repo). For more background on the theory, check the resources listed below.
Resources
The code is based on research done at Institute of Science and Technology by Ranita Biswas, Sebastiano Cultrera di Montesano, Ondřej Draganov, Herbert Edelsbrunner and Morteza Saghafian. A preprint of the full paper can be found on arXiv: Chromatic Alpha Complexes preprint, published version here: Chromatic Alpha Complexes. A shorter introduction to the main ideas can be found in a preprint Chromatic Topological Data Analysis.
A presentation about the main concepts used in this package can be viewed on YouTube: AATRN Online Seminar: TDA for Chromatic Point Clouds. A recording of a complementary talk focusing more on the motivations of the work and the combinatorial structures underlying it is accessible through google drive.
Contact
If you have any questions to the code, do not hesitate to contat us. We are also eager to hear from you if you try the code out, and happy to chat about how you can use it on your data. Use, e.g., the mail in my github profile.
Timing
For a rough idea on the performance, see the two plots below showing times the code took on my laptop.

License
Copyright ©2023. Institute of Science and Technology Austria (IST Austria). All Rights Reserved.
This file is part of chromatic_tda, which is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License along with this program. If not, see https://www.gnu.org/licenses/.
Contact the Technology Transfer Office, ISTA, Am Campus 1, A-3400 Klosterneuburg, Austria, +43-(0)2243 9000, twist@ist.ac.at, for commercial licensing opportunities.
Owner
- Name: Ondrej Draganov
- Login: OnDraganov
- Kind: user
- Company: Institute of Science and Technology Austria (ISTA)
- Repositories: 1
- Profile: https://github.com/OnDraganov
Citation (CITATION.cff)
cff-version: 1.2.0
title: chromatic-tda
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Ondrej
family-names: Draganov
email: ondra@draganov.cz
orcid: 'https://orcid.org/0000-0003-0464-3823'
affiliation: Institute of Science and Technology Austria (ISTA)
- given-names: Mohammad
family-names: Mahini
email: m.mahini@gmail.com
repository-code: 'https://github.com/OnDraganov/chromatic-tda'
repository-artifact: 'https://pypi.org/project/chromatic-tda/'
abstract: >-
Tool to compute six-packs of persistence diagrams for
chromatic point clouds
keywords:
- python
- tda
- topological data analysis
- persistent homology
- persistence
- chromatic alpha
- delaunay
license: AGPL-3.0-or-later
GitHub Events
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- Watch event: 2
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- Fork event: 2
Last Year
- Watch event: 2
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Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Ondrej DRAGANOV | o****v@i****t | 43 |
| Ondrej Draganov | o****a@d****z | 2 |
Committer Domains (Top 20 + Academic)
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Last synced: 6 months ago
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Past Year
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Packages
- Total packages: 1
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Total downloads:
- pypi 60 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 18
- Total maintainers: 1
pypi.org: chromatic_tda
Tool to compute six-packs of persistence diagrams for chromatic point clouds
- Homepage: https://github.com/OnDraganov/chromatic-tda
- Documentation: https://github.com/OnDraganov/chromatic-tda
- License: AGPL-3.0-or-later
-
Latest release: 1.1.8
published 12 months ago
Rankings
Maintainers (1)
Dependencies
- colorama 0.4.6
- contourpy 1.1.0
- cycler 0.11.0
- exceptiongroup 1.1.3
- fonttools 4.42.0
- importlib-resources 6.0.1
- iniconfig 2.0.0
- kiwisolver 1.4.4
- matplotlib 3.7.2
- mypy 1.5.0
- mypy-extensions 1.0.0
- numpy 1.25.2
- packaging 23.1
- pillow 10.0.0
- pluggy 1.2.0
- pyparsing 3.0.9
- pytest 7.4.0
- python-dateutil 2.8.2
- scipy 1.11.1
- six 1.16.0
- tomli 2.0.1
- typing-extensions 4.7.1
- zipp 3.16.2
- matplotlib ^3.7.0
- mypy ^1.3.0
- numpy ^1.24.2
- pytest ^7.3.1
- python >=3.9,<3.13
- scipy ^1.10.1