def new_simu((psfile, num_file, tot_file, check_repo_is_dirty)):
"""Run a simulation using the specified parameter set file"""
filedir = path.dirname(psfile) + "/"
# Register system state
info = get_sys_state(check_repo_is_dirty)
# Creating simulation run arguments
args = SIM_PARSER.parse_args([psfile, "--no-plot", "--no-brian-output", "--no-summary"])
# Run simulation and get results
paramset, results = multiglom_network.main(args)
# Write the simulation to HDF5
nfilename = filedir + info["time"].replace(":", "-")
nfilename += "_" + info["uuid"] + ".h5"
init_data_h5(nfilename)
write_simu_data(nfilename, info, paramset, results)
# Compute one mean for interconnected neurons and another for the other neurons
mean_pop = np.mean(subpop_memb_pot[~subpop_interco_neurons], axis=0)
mean_pop_interco = np.mean(subpop_memb_pot[subpop_interco_neurons], axis=0)
mean_memb_pot[glom*2] = mean_pop
mean_memb_pot[glom*2 + 1] = mean_pop_interco
results['data'] = {'spikes_it': [array_spikes_it,
"Spikes: one array for the neuron number, another one for the spike times."],
'input': [mean_inputs,
"Mean network input conductance value for each glomerule."],
's_granule': [monit_gr['s'].values,
"Variable 's' of the granules."],
's_syn_self': [monit_gr['s_syn_self'].values,
"Variable 's_syn' for the granule, without integrating the mitral 's' from other subpopulations."],
'mean_memb_pot': [mean_memb_pot,
"Mean membrane potential. For each subpop: one mean for the interconnected neurons and one mean for the non-interconnected neurons."]}
results['indexes'] = {'MPS': mps_indexes, 'STS': sts_indexes, 'FFTMAX': fftmax,
'peak_distances': peak_distances}
return {'set': model.PARAMETERS, 'arrays': ps_arrays}, results
if __name__ == '__main__':
# Argument parsing
from arg_parsers import SIM_PARSER
args = SIM_PARSER.parse_args()
# Run script
ps, res = main(args)
