semvec/pypi-packages huggingface dataset:
STIsim 1.3.0
STI modelling toolbox built on the Starsim platform
Keywords: agent-based model, simulation, disease, epidemiology

STIsim
======

.. |tests| image:: https://github.com/starsimhub/stisim/actions/workflows/tests.yaml/badge.svg

.. |pypi| image:: https://img.shields.io/pypi/v/stisim?label=PyPI
    :target: https://pypi.org/project/stisim/

|tests| |pypi|

**Warning! STIsim is still in the early stages of development. It is being shared solely for transparency and to facilitate collaborative development. It is not ready to be used for real research or policy questions.**

STIsim is an agent-based modeling framework in which users can design and configure simulations of sexually-transmitted diseases. STIsim uses the `Starsim <https://starsim.org>`_ architecture, and belongs to the Starsim model suite which also includes `Covasim <https://covasim.org>`_, `HPVsim <https://hpvsim.org>`_, and `FPsim <https://fpsim.org>`_.


Requirements
------------

Python 3.9-3.13.

We recommend, but do not require, installing STIsim in a virtual environment, such as `Anaconda <https://www.anaconda.com/products>`__.


Installation
------------

STIsim is most easily installed via PyPI: ``pip install stisim``.

STIsim can also be installed locally. To do this, clone first this repository, then run ``pip install -e .`` (don't forget the dot at the end!).


Usage and documentation
-----------------------

Documentation is available at https://docs.idmod.org/projects/stisim. 


Contributing
------------

Questions or comments can be directed to `info@starsim.org <mailto:info@starsim.org>`__ , or on this project’s `GitHub <https://github.com/starsimhub/stisim>`__ page.

See `.github/workflows/README.md` for details on publishing new releases of STIsim.


Disclaimer
----------

The code in this repository was developed by IDM, the Burnet Institute, and other collaborators to support our joint research on flexible agent-based modeling. We've made it publicly available under the MIT License to provide others with a better understanding of our research and an opportunity to build upon it for their own work. We make no representations that the code works as intended or that we will provide support, address issues that are found, or accept pull requests. You are welcome to create your own fork and modify the code to suit your own modeling needs as permitted under the MIT License.