This repository contains code to reproduce figures from the IBL reproducible ephys paper

Installation

Making a new python environment (optional)

Install Anaconda and git, and follow their installer instructions to add each to the system path

Create new python environment

conda create --name ibl_repro_ephys python=3.9

Activate environment

conda activate ibl_repro_ephys

Downloading and Installing repo

Clone the repo

git clone https://github.com/int-brain-lab/paper-reproducible-ephys.git

Navigate to repo

cd paper-reproducible-ephys

Install requirements and repo

pip install -e .

Configuration

Setting up ONE credentials

Open an ipython terminal

from one.api import ONE
pw = 'international'
one = ONE(silent=True, password=pw)

Setting up saving scripts

By default data and figures will be saved into a folder with the figure name e.g figure1. To find this location on you computer (for example for figure 1) you can type the

from reproducible_ephys_functions import save_data_path, save_figure_path
print(save_data_path(figure='figure1'))
print(save_figure_path(figure='figure1'))

If you want to override the location where the data and figures are saved you can create a script in the repo directory, that is called reproducible_ephys_paths.py and add the following following:

FIG_PATH = '/path/where/to/save/your/figures/' DATA_PATH = '/path/where/to/save/your/data/

Getting Started

Download data and compute exclusion criteria

The reproducible_ephys_run.py module will download the data and compute exclusion criteria for the insertions

python reproducible_ephys_run.py

This can also be run from a python terminal or by using the following code snippet in an ipython terminal

from one.api import ONE
from reproducible_ephys_run import run_repro_ephys_metrics
one = ONE()
run_repro_ephys_metrics(one)

Get the list of recordings from the reproducible site

Find insertions used for analysis based on different exclusion levels

Level	Minimum Regions	Minumum trials	Exclude Critical
0	0	0	True
1	2	400	True
2	2	400	True

from one.api import ONE
from reproducible_ephys_functions import get_insertions, traj_list_to_dataframe
LEVEL = 0
one = ONE()
df_trajs = traj_list_to_dataframe(get_insertions(one=one, level=LEVEL))
print(df_trajs.shape[0], 'insertions')
print(df_trajs.columns)

Will return

60 insertions
Index(['subjects', 'dates', 'probes', 'lab', 'eid', 'probe_insertion',
       'institution'],
      dtype='object')

Running figures

For instructions on how to run code for each figure please refer to README file in each figure sub-folder