def METHOD_NAME(sim):
    """
    Balanced network of integrate-and-fire neurons, built with the "low-level"
    API.
    """
    cell_params = {
        'tau_m': 10.0, 'tau_syn_E': 2.0, 'tau_syn_I': 5.0, 'v_rest': -60.0,
        'v_reset': -65.0, 'v_thresh': -55.0, 'cm': 0.5, 'tau_refrac': 2.5,
        'e_rev_E': 0.0, 'e_rev_I': -75.0
    }
    stimulation_params = {'rate': 80.0, 'duration': 50.0}
    n_exc = 80
    n_inh = 20
    n_input = 20
    rngseed = 87546
    parallel_safe = True
    n_threads = 1
    pconn_recurr = 0.03
    pconn_input = 0.01
    tstop = 1100.0
    delay = 1
    w_exc = 3.0e-3
    w_inh = 45.0e-3
    w_input = 0.12
    dt = 0.1
    sim.setup(timestep=dt, min_delay=dt, threads=n_threads)
    iaf_neuron = sim.IF_cond_alpha(**cell_params)
    excitatory_cells = sim.create(iaf_neuron, n=n_exc)
    inhibitory_cells = sim.create(iaf_neuron, n=n_inh)
    inputs = sim.create(sim.SpikeSourcePoisson(**stimulation_params), n=n_input)
    all_cells = excitatory_cells + inhibitory_cells
    sim.initialize(all_cells, v=cell_params['v_rest'])
    sim.connect(excitatory_cells, all_cells, weight=w_exc, delay=delay,
                receptor_type='excitatory', p=pconn_recurr)
    sim.connect(inhibitory_cells, all_cells, weight=w_exc, delay=delay,
                receptor_type='inhibitory', p=pconn_recurr)
    sim.connect(inputs, all_cells, weight=w_input, delay=delay,
                receptor_type='excitatory', p=pconn_input)
    sim.record('spikes', all_cells, "scenario1a_%s_spikes.pkl" % sim.__name__)
    sim.record('v', excitatory_cells[0:2], "scenario1a_%s_v.pkl" % sim.__name__)
    sim.run(tstop)
    E_count = excitatory_cells.mean_spike_count()
    I_count = inhibitory_cells.mean_spike_count()
    print("Excitatory rate        : %g Hz" % (E_count * 1000.0 / tstop,))
    print("Inhibitory rate        : %g Hz" % (I_count * 1000.0 / tstop,))
    sim.end()
    for filename in glob.glob("scenario1a_*"):
        os.remove(filename)