A scikit-learn compatible package for fermentations.
Project description
scikit-ferm
scikit-ferm is a Python package designed to generate synthetic fermentation datasets and model microbial growth dynamics. Whether you're studying food fermentation (like yogurt production) or simulating microbial behavior for research and development, scikit-ferm provides flexible tools to create realistic datasets based on established growth models.
The official documentation is hosted here.
Installation
Install scikit-ferm via pip with:
uv pip install scikit-ferm
Alternatively, to edit and contribute you can fork/clone and run:
git clone https://github.com/Aschwins/scikit-ferm.git
uv sync
Use cases
| Use Case | Modules | Notebook | Documentation |
|---|---|---|---|
| Generate synthetic fermentation datasets | •skferm.datasets.generate_synthetic_growth• skferm.datasets.rheolaser |
📓 Notebook | 📚 Docs |
| Growth modeling | • skferm.growth_models.gompertz• skferm.growth_models.logistic |
📓 Notebook | 📚 Docs |
| Curve smoothing | • skferm.curve_smoothing.smooth |
📓 Notebook | 📚 Docs |
Examples
Jupyter notebooks are used to demonstrate examples. You can find the notebooks in the notebooks directory. Each example describes a use case. To run the examples you need to install scikit-ferm with an additional dependencies and start Jupyter Lab.
uv sync
jupyter lab
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