Skip to content

InsectRobotics/path-integration-memory

 
 

Repository files navigation

path-integration-memory

Memory modelling for insect path integration.

Getting started

It is recommended to use a virtual Python environment, which can be done by sourcing the env.sh script:

source env.sh

Command-line interface

The quickest way to run an experiment setup is using the command-line interface. The following will run the unmodified Stone model with parameters specified in setups/stone-as-is.json, and output a report:

./cli.py setups/stone-as-is.json --report

Results will also be saved in the results directory.

For documentation of the CLI options, run:

./cli.py --help

Using with Jupyter

The env.sh script also creates an IPython kernel for use with Jupyter; choose the pim kernel under Kernel -> Change Kernel...

Jupyter's saving of cell outputs can be a nice way to share results, but it easily wreaks havoc on repositories if one does not pay attention. It is a good idea to Edit -> Clear All Outputs before committing a notebook, and a Git hook can be used to help with remembering to do so. Install it like so:

cp git-hooks/pre-commit .git/hooks/pre-commit

If the hook stops the commit, but you explicitly want to commit cell output, ignore the hook using --no-verify when committing.

About

Memory modelling for insect path integration.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 93.9%
  • Python 5.4%
  • Other 0.7%