lab_wiki

This is the lab wiki. For more info about our team, research, blog and publications see https://anneurai.net.

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Working with IBL data

Many projects make use of the large dataset collected by the International Brain Laboratory.

General info

Behavioral data

Working with IBL behavioral data

Neural data

Working with IBL neural data

Accessing data on ALICE

Email the ALICE helpdesk to get access to the shared data folder: data_pi-uraiae.

Then,


# ===================================
# code to load shared (internal) data
# ===================================

import os
import pandas as pd
from one.api import ONE

# change my username to your own
project = 'churchland_learninglifespan'
save_dir = os.path.join(os.path.expanduser('~'), 'data_pi-uraiae/ONE/alyx.internationalbrainlab.org/', project)

# THIS IS THE OFFICIAL WAY - FIND THE RELEVANT SESSIONS FROM THE LOCAL CACHE
# If you want to use this cache without re-downloading data (i.e. keep the download cache the same as the main IBL Alyx), you can use the tags system.
one = ONE(mode='local', cache_dir = save_dir)
one.load_cache()
# one = ONE(mode='local')
# one.load_cache(cache_dir=save_dir)
print('Datasets location: %s;\nCache table location: %s' % (one.cache_dir, save_dir))
eids = one.search(lab='churchlandlab', query_type='local', dataset='spikes.times')
print(len(eids)) # should be 51...

# THIS IS THE HACK WAY - READ IN THOSE EIDS THAT CERTAINLY ARE AVAILABLE LOCALLY
eids = pd.read_csv(os.path.join(save_dir,'eids_on_alice.csv'))
eids = eids.eid.values
print(len(eids)) # should be 51...