load_data.py

import numpy as np

from matplotlib import pyplot as plt
%matplotlib inline
import seaborn as sns


sns.set()

import os, requests

fname = []
for j in range(3):
  fname.append('steinmetz_part%d.npz'%j)
url = ["https://osf.io/agvxh/download"]
url.append("https://osf.io/uv3mw/download")
url.append("https://osf.io/ehmw2/download")

for j in range(len(url)):
  if not os.path.isfile(fname[j]):
    try:
      r = requests.get(url[j])
    except requests.ConnectionError:
      print("!!! Failed to download data !!!")
    else:
      if r.status_code != requests.codes.ok:
        print("!!! Failed to download data !!!")
      else:
        with open(fname[j], "wb")


alldat = np.array([])
for j in range(len(fname)):
  alldat = np.hstack((alldat, np.load('steinmetz_part%d.npz'%j, allow_pickle=True)['dat']))

# select just one of the recordings here. 11 is nice because it has some neurons in vis ctx. 
dat = alldat[11]
print(dat.keys())

# From here data can be accessed per brain area. See visualisation code for further details