This toolbox aims to simplify the construction of compartmental models and the inference of their parameters
Project description
Inference of Compartmental Models (ICoMo) Toolbox
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.
- 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.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
icomo-0.2.0.tar.gz
(240.8 kB
view details)
Built Distribution
icomo-0.2.0-py3-none-any.whl
(19.1 kB
view details)
File details
Details for the file icomo-0.2.0.tar.gz
.
File metadata
- Download URL: icomo-0.2.0.tar.gz
- Upload date:
- Size: 240.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 99d6295a60f4bc88a8f720a563f513e884680247d42c7ac207b01e9aa18cabfd |
|
MD5 | fa267238616827144a180b0db3812b96 |
|
BLAKE2b-256 | 95fabcc67ecc5df4dc5d0911adc04b5515dbf2d2e8a1304d75a16517a4a0146d |
File details
Details for the file icomo-0.2.0-py3-none-any.whl
.
File metadata
- Download URL: icomo-0.2.0-py3-none-any.whl
- Upload date:
- Size: 19.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3987477f746a1fc99c9dfe52d81042ecff8ad01813d522cd08e8890e6548c0f2 |
|
MD5 | 2da9ca2b56f38eff21753dabd478ca25 |
|
BLAKE2b-256 | bf9ceaf8d06f7c8c8a878f1b12bf978125f8f4ad8c1224f7b3dda86305aa04b5 |