Using the Dataset

# /// script
# requires-python = ">=3.11"
# dependencies = [
#   "livn",
#   "datasets",
# ]
# ///
from datasets import load_dataset
import numpy as np

from livn.io import MEA
from livn.system import make

system_name = "S1"

dataset = load_dataset("livn-org/livn", name=system_name)

sample = dataset["train_with_noise"][0]
it = sample["trial_it"][0]
t = sample["trial_t"][0]

# use a multi-electrode array to 'observe' the data
system = make(system_name)
mea = MEA.from_directory(system.uri)

features = sample["features"]

duration = 1000
channel = int(np.round(features[0]))
t_stim = int(features[1])
amplitude = features[2]

inputs = np.zeros([duration, mea.num_channels], dtype=np.float32)
inputs[t_stim : t_stim + 20, channel] = amplitude

cit, ct = mea.channel_recording(system.neuron_coordinates, it, t)

print("Spikes in channel 0:")
print(ct[0])