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A library that defines AIND data schema for the Aind Behavior VR Foraging experiment.

Project description

aind-vr-foraging

CI PyPI - Version License ruff uv

A repository for the VR Foraging task.


📋 General instructions

This repository follows the project structure laid out in the Aind.Behavior.Services repository.


⚙️ Generating settings files

The VR Foraging tasks is instantiated by a set of three settings files that strictly follow a DSL schema. These files are:

  • task.json
  • rig.json
  • session.json

Examples on how to generate these files can be found in the ./Examples directory of the repository. Once generated, these are the the only required inputs to run the Bonsai workflow in ./src/main.bonsai.

The workflow can thus be executed using the Bonsai CLI:

"./.bonsai/bonsai.exe" "./src/main.bonsai" -p SessionPath=<path-to-session.json> -p RigPath=<path-to-rig.json> -p TaskPath=<path-to-task.json>

[> ] CLI tools

The platform exposes a few CLI tools to facilitate various tasks. Tools are available via:

uv run vr-foraging <subcommand>

for a list of all sub commands available:

uv run vr-foraging -h

You may need to install optional dependencies depending on the sub-commands you run.

🔍 Primary data quality-control

Once an experiment is collected, the primary data quality-control script can be run to check the data for issues. This script can be launcher using:

uv run vr-foraging data-qc <path-to-data-dir>

🌉 Mapping to aind-data-schema

Once an experiment is collected, data can be mapped to aind-data-schema using the data-mapper sub-command:

uv run vr-foraging data-mapper

🔄 Regenerating schemas

DSL schemas can be modified in ./src/aind_behavior_vr_foraging/rig.py (or (...)/task_logic.py`).

Once modified, changes to the DSL must be propagated to json-schema and csharp API. This can be done by running:

uv run vr-foraging regenerate

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