def METHOD_NAME(self):
    from pyNN.utility.plotting import Figure, Panel
    spike_times = [50.]
    p = sim.Population(3, sim.SpikeSourceArray(spike_times=spike_times))
    p2 = sim.Population(3, sim.Hardware_IF_cond_exp())
    syn = sim.StaticSynapse(weight=0.012)
    con = sim.Projection(p, p2, connector=sim.OneToOneConnector(),
                         synapse_type=syn, receptor_type='excitatory')
    spike_times_g = p.get('spike_times')
    p2.record('v')
    sim.run(100.0)
    weights = nan_to_num(con.get('weight', format="array"))
    print(weights)
    data = p2.get_data().segments[0]
    vm = data.filter(name="v")[0]
    print(vm)
    Figure(
        Panel(weights, data_labels=[
              "ext->cell"], line_properties=[{'xticks': True, 'yticks': True, 'cmap': 'Greys'}]),
        Panel(vm, ylabel="Membrane potential (mV)", data_labels=[
              "excitatory", "excitatory"], line_properties=[{'xticks': True, 'yticks': True}]),
    ).save("result")