def METHOD_NAME(self):
    p.setup(timestep=1.0, min_delay=1.0)
    n_neurons = 200  # number of neurons in each population
    p.set_number_of_neurons_per_core(p.IF_curr_exp, n_neurons / 2)
    cell_params_lif = {'cm': 0.25,
                       'i_offset': 0.0,
                       'tau_m': 20.0,
                       'tau_refrac': 2.0,
                       'tau_syn_E': 5.0,
                       'tau_syn_I': 5.0,
                       'v_reset': -70.0,
                       'v_rest': -65.0,
                       'v_thresh': -50.0
                       }
    populations = list()
    projections = list()
    spike_array = {'spike_times': [[0]]}
    populations.append(p.Population(n_neurons, p.IF_curr_exp,
                                    cell_params_lif,
                                    label='pop_1'))
    populations.append(p.Population(1, p.SpikeSourceArray, spike_array,
                                    label='inputSpikes_1'))
    projections.append(p.Projection(populations[1], populations[0],
                                    p.AllToAllConnector()))
    populations[1].record("spikes")
    p.run(5000)
    spike_array_spikes = populations[1].spinnaker_get_data("spikes")
    boxed_array = numpy.zeros(shape=(0, 2))
    boxed_array = numpy.append(boxed_array, [[0, 0]], axis=0)
    numpy.testing.assert_array_equal(spike_array_spikes, boxed_array)
    p.end()