examples/example_24_large_scale_brian2_simulation/clusternet.py
def analyse(self, traj, network, current_subrun, subrun_list, network_dict):
        """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

        """
        #Check if we finished all subruns
        if len(subrun_list)==0:
            spikes_e = traj.results.monitors.spikes_e

            time_window = traj.parameters.analysis.statistics.time_window
            start_time = traj.parameters.simulation.durations.initial_run
            end_time = start_time+traj.parameters.simulation.durations.measurement_run
            neuron_ids = traj.parameters.analysis.statistics.neuron_ids

            mean_ff = self._compute_mean_fano_factor(
                neuron_ids, spikes_e, time_window, start_time, end_time)

            traj.f_add_result('statistics.mean_fano_factor', mean_ff, comment='Average Fano '
                                                                      'Factor over all '
                                                                      'exc neurons')

            print('R_ee: %f, Mean FF: %f' % (traj.R_ee, mean_ff))
def analyse(self, traj, network, current_subrun, subrun_list, network_dict):
        """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

        """
        #Check if we finished all subruns
        if len(subrun_list)==0:
            spikes_e = traj.results.monitors.spikes_e

            time_window = traj.parameters.analysis.statistics.time_window
            start_time = traj.parameters.simulation.durations.initial_run
            end_time = start_time+traj.parameters.simulation.durations.measurement_run
            neuron_ids = traj.parameters.analysis.statistics.neuron_ids

            mean_ff = self._compute_mean_fano_factor(
                neuron_ids, spikes_e, time_window, start_time, end_time)

            traj.f_add_result('statistics.mean_fano_factor', mean_ff, comment='Average Fano '
                                                                      'Factor over all '
                                                                      'exc neurons')

            print('R_ee: %f, Mean FF: %f' % (traj.R_ee, mean_ff))
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