Epiphyte
This project is a processing pipeline for high-dimensional single-unit neural activity colligated with meta data. We present a toolbox for organizing neural activity alongside meta-data and stimulus information, as well as a processing pipeline which allows ad-hoc importing, exporting, annotating, and visualizing of data. Our toolbox is developed for large sets of continuous single-unit recordings and introduces a set of modules for algorithmically and manually annotating data, defining data irregularities, and designating new layers of meta-data for further analyses.
Installing the package
here.
Note: These installation instructions assume that you have basic fluency in Python and command line interfaces. If you would like to set-up this package from scratch, check out the more robust instructions(1) Install the required packages by running the following command (Note: we highly recommend doing so within a virtual environment with Python==3.7):
If using PyPip:
pip install -r requirements_pip.txt
If using Conda:
conda create --name <env> --file requirements_conda.txt
(2) Go to the top-level folder of Epiphyte and install the package itself
pip install -e .
(3) Set up a DataJoint database
Prerequesites:
- install docker
- install docker compose
Actual setup:
-
follow instructions on DataJoint tutorial page to set up for using a docker container with database.
Note for macOS users: we recommend installing MySQL via Homebrew (as opposed to the direct download via Docker or MySQL). For instructions, check out the Homebrew instructions or step 6 of the install tutorial.
-
navigate to the top-level directory of Epiphyte and run the docker container:
sudo docker-compose up -d
- run database/database_set_up.ipynb notebook to fill the database with the mock data
- now everything should be set up and ready to go!
- for troubleshooting issues, check out here.