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# RatInABox ![Tests](https://github.com/RatInABox-Lab/RatInABox/actions/workflows/test.yml/badge.svg) [![PyPI version](https://badge.fury.io/py/ratinabox.svg)](https://badge.fury.io/py/ratinabox) [![Downloads](https://static.pepy.tech/badge/ratinabox)](https://pepy.tech/project/ratinabox)<img align="right" src=".images/readme/logo.png" width=150>
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# RatInABox ![Tests](https://github.com/RatInABox-Lab/RatInABox/actions/workflows/test.yml/badge.svg) [![PyPI version](https://badge.fury.io/py/ratinabox.svg)](https://badge.fury.io/py/ratinabox) [![Downloads](https://static.pepy.tech/badge/ratinabox)](https://pepy.tech/project/ratinabox) [![PyPI Downloads](https://static.pepy.tech/badge/ratinabox/week)](https://pepy.tech/projects/ratinabox)<img align="right" src=".images/readme/logo.png" width=150>
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`RatInABox` (see [paper](https://elifesciences.org/articles/85274)) is a toolkit for generating synthetic behaviour and neural data for spatially and/or velocity selective cell types in complex continuous environments.
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