AngoraPy is an open source modeling library for goal-oriented research in neuroscience. It provides a simple interface to train deep neural network models of the human brain on various, customizable, sensorimotor tasks, using reinforcement learning. It thereby empowers goal-driven modeling to surpass the sensory domain and enter that of sensorimotor control, closing the perception-action loop. 

AngoraPy is designed to require no deeper understanding of reinforcement learning. It employs state-of-the-art machine learning techniques, optimized for distributed computation scaling from local workstations to high-performance computing clusters. We aim to hide as much of this under the hood of an intuitive, high-level API but preserve the option for customizing most aspects of the pipeline.

This library is developed as part of the Human Brain Project at CCN Maastricht. It is an effort to build software by neuroscientists, for neuroscientists. If you have suggestions, requests or questions, feel free to open an issue.

Installation

AngoraPy is available on PyPI. 

From source

You can access the source code on Github. After downloading, you may install it by pip.

Docker

Alternatively, you can install AngoraPy and all its dependencies in a docker container using the Dockerfile provided in this repository (/docker/Dockerfile). To this end, download the repository and build the docker image from the /docker directory:

To install different versions, replace #master in the source by the tag/branch of the respective version you want to install.

More Information

For more information consult our Github page.