PyNEST EI-clustered network: Run Simulation

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This is an example script for running the EI-clustered model with two stimulations and generating a raster plot.

import matplotlib.pyplot as plt
import network
from helper import raster_plot
from network_params import net_dict
from sim_params import sim_dict
from stimulus_params import stim_dict

if __name__ == "__main__":
    # Creates object which creates the EI clustered network in NEST
    ei_network = network.ClusteredNetwork(sim_dict, net_dict, stim_dict)

    # Runs the simulation and returns the spiketimes
    # get simulation initializes the network in NEST
    # and runs the simulation
    # it returns a dict with the average rates,
    # the spiketimes and the used parameters
    result = ei_network.get_simulation()
    ax = raster_plot(
        result["spiketimes"],
        tlim=(0, sim_dict["simtime"]),
        colorgroups=[
            ("k", 0, net_dict["N_E"]),
            ("darkred", net_dict["N_E"], net_dict["N_E"] + net_dict["N_I"]),
        ],
    )
    plt.savefig("clustered_ei_raster.png")
    print(f"Firing rate of excitatory neurons: {result['e_rate']:6.2f} spikes/s")
    print(f"Firing rate of inhibitory neurons: {result['i_rate']:6.2f} spikes/s")