Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: scholar.google -
○Academic email domains
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○Institutional organization owner
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○Scientific vocabulary similarity
Low similarity (11.6%) to scientific vocabulary
Repository
Tools for the inference of compartmental models
Basic Info
- Host: GitHub
- Owner: Priesemann-Group
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://icomo.readthedocs.io/
- Size: 2.78 MB
Statistics
- Stars: 10
- Watchers: 4
- Forks: 1
- Open Issues: 0
- Releases: 11
Metadata Files
README.md
Inference of Compartmental Models toolbox
Leverage the power of JAX libraries for PyMC models
This toolbox aims to simplify the construction of compartmental models and the inference of their parameters.
The aim isn't to provide a complete package that will build models from A to Z, but rather provide different helper functions examples and guidelines to help leverage modern python packages like JAX, Diffrax and PyMC to build, automatically differentiate and fit compartmental models.
A central part of the toolbox is the possibility to wrap JAX functions to be used in PyMC models (see here), which is used tro wrap the Diffrax ODE solvers, but might be also useful for other projects.
- Documentation: https://icomo.readthedocs.io.
Features
- Facilitate the construction of compartmental models by only defining flow between compartments, and automatically generating the corresponding ODEs.
- Plot the graph of the compartmental model to verify the correctness of the model.
- Integrate the ODEs using diffrax, automatically generating the Jacobian of the parameters of the ODE
- Fit the parameters using minimization algorithms or build a Bayesian model using PyMC.
Citation
If you use this toolbox in your research, please find the citation information on the right sidebar.
Credits
Logo by Fabian Mikulasch
Owner
- Name: Priesemann-Group
- Login: Priesemann-Group
- Kind: organization
- Repositories: 13
- Profile: https://github.com/Priesemann-Group
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: Dehning given-names: Jonas orcid: https://orcid.org/0000-0002-1728-2505 doi: 10.5281/zenodo.15641362 title: ICoMo (Inference of Compartmental Models) repository-code: 'https://github.com/Priesemann-Group/icomo' url: 'https://icomo.readthedocs.io/en/latest/' version: 1.0.3 date-released: 2025-03-07
GitHub Events
Total
- Release event: 2
- Watch event: 8
- Issue comment event: 1
- Push event: 26
- Pull request event: 1
- Create event: 3
Last Year
- Release event: 2
- Watch event: 8
- Issue comment event: 1
- Push event: 26
- Pull request event: 1
- Create event: 3
Packages
- Total packages: 1
-
Total downloads:
- pypi 131 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 10
- Total maintainers: 1
pypi.org: icomo
This toolbox aims to simplify the construction of compartmental models and the inference of their parameters
- Homepage: https://github.com/Priesemann-Group/icomo
- Documentation: https://icomo.readthedocs.io/
- License: MIT License
-
Latest release: 1.0.3
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
- actions/checkout v3 composite
- pypa/gh-action-pypi-publish release/v1 composite
- arviz *
- diffrax *
- graphviz *
- ipywidgets *
- jaxopt *
- matplotlib *
- numpy *
- numpyro *
- optax *
- pymc ==5.*
- pytensor *