Generate, manage and analyze anomalous diffusion trajectories.
Project description
Generate, manage and analyze anomalous diffusion trajectories
Get started | Documentation | Tutorials | Cite us | License
This library has been created in the framework of the Anomalous Diffusion (AnDi) Challenge and allows to create trajectories and datasets from various anomalous diffusion models. Learn all the details and discover the available tutorials in the library webpage.
Installation
You can install the package using:
pip install andi-datasets
You can then import the package in a Python3 environment using:
import andi_datasets
Contributing
The AnDi challenge is a community effort, hence any contribution to this library is more than welcome. If you think we should include a new model to the library, you can contact us in this mail: andi.challenge@gmail.com. You can also perform pull-requests and open issues with any feedback or comments you may have.
Requirements
andi-datasets
runs in python>=3.10
. All the requirements are declared in the file setting.ini
and automatically included when installing the package. Further details can be found at the PYPI package webpage.
Cite us
If you found this package useful and used it in your projects, you can use the following to directly cite the package:
Muñoz-Gil, G., Requena B., Volpe G., Garcia-March M.A. and Manzo C.
AnDiChallenge/ANDI_datasets: Challenge 2020 release (v.1.0). Zenodo (2021).
https://doi.org/10.5281/zenodo.4775311
Or you can cite the paper this package was developed for:
Muñoz-Gil, G., Volpe, G., Garcia-March, M.A. et al.
Objective comparison of methods to decode anomalous diffusion.
Nat Commun 12, 6253 (2021).
https://doi.org/10.1038/s41467-021-26320-w
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