Recording examplesΒΆ

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This script demonstrates how to select different recording backends and read the result data back in. The simulated network itself is rather boring with only a single poisson generator stimulating a single neuron, so we get some data.

import nest
import numpy as np

def setup(record_to, time_in_steps):
    """Set up the network with the given parameters."""

    nest.overwrite_files = True

    pg_params = {"rate": 1000000.0}
    sr_params = {"record_to": record_to, "time_in_steps": time_in_steps}

    n = nest.Create("iaf_psc_exp")
    pg = nest.Create("poisson_generator", 1, pg_params)
    sr = nest.Create("spike_recorder", 1, sr_params)

    nest.Connect(pg, n, syn_spec={"weight": 10.0})
    nest.Connect(n, sr)

    return sr

def get_data(sr):
    """Get recorded data from the spike_recorder."""

    if sr.record_to == "ascii":
        return np.loadtxt(f"{sr.filenames[0]}", dtype=object)
    if sr.record_to == "memory":
        return sr.get("events")

# Just loop through some recording backends and settings
for time_in_steps in (True, False):
    for record_to in ("ascii", "memory"):
        sr = setup(record_to, time_in_steps)
        data = get_data(sr)
        print(f"simulation resolution in ms: {nest.resolution}")
        print(f"data recorded by recording backend {record_to} (time_in_steps={time_in_steps})")

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