def analyse(self, traj, network, current_subrun, subrun_list, network_dict):
<EOL>if len(subrun_list)==<NUM_LIT:0>:<EOL><INDENT>spikes_e = traj.results.monitors.spikes_e<EOL>time_window = traj.parameters.analysis.statistics.time_window<EOL>start_time = traj.parameters.simulation.durations.initial_run<EOL>end_time = start_time+traj.parameters.simulation.durations.measurement_run<EOL>neuron_ids = traj.parameters.analysis.statistics.neuron_ids<EOL>mean_ff = self._compute_mean_fano_factor(<EOL>neuron_ids, spikes_e, time_window, start_time, end_time)<EOL>traj.f_add_result('<STR_LIT>', mean_ff, comment='<STR_LIT>'<EOL>'<STR_LIT>'<EOL>'<STR_LIT>')<EOL>print('<STR_LIT>' % (traj.R_ee, mean_ff))<EOL><DEDENT>
Calculates average Fano Factor of a network.

        :param traj:

            Trajectory container

            Expects:

            `results.monitors.spikes_e`: Data from SpikeMonitor for excitatory neurons

            Adds:

            `results.statistics.mean_fano_factor`: Average Fano Factor

        :param network:

            The BRIAN network

        :param current_subrun:

            BrianParameter

        :param subrun_list:

            Upcoming subruns, analysis is only performed if subruns is empty,
            aka the final subrun has finished.

        :param network_dict:

            Dictionary of items shared among componetns