In this folder we provide numerous "example scripts" or "demos" which will help when learning RatInABox. In approximate order of complexity, these include:
- simple_example.ipynb: a very simple tutorial for importing RiaB, initilising an Environment, Agent and some PlaceCells, running a brief simulation and outputting some data.
- extensive_example.ipynb: a more involved tutorial. More complex enivornment, more complex cell types and more complex plots are used.
- list_of_plotting_functions.md: All the types of plots available for are listed and explained.
- readme_figures.ipynb: (Almost) all plots/animations shown in the root readme are produced from this script (plus some minor formatting done afterwards in powerpoint).
- paper_figures.ipynb: (Almost) all plots/animations shown in the paper are produced from this script (plus some major formatting done afterwards in powerpoint).
- decoding_position_example.ipynb: Postion is decoded from neural data generated with RatInABox using linear regression. Place cells, grid cell and boundary vector cells are compared.
- reinforcement_learning_example.ipynb: RatInABox is use to construct, train and visualise a small two-layer network capable of model free reinforcement learning in order to find a reward hidden behind a wall.
- path_integration_example.ipynb: RatInABox is use to construct, train and visualise a large multi-layer network capable of learning a "ring attractor" capable of path integrating a position estimate using only velocity inputs.