def METHOD_NAME(sim_path):
  '''
  Finds spike trains in the SIM_PATH and organizes them by cell,
  returning a dict of dicts of SpikeTrains.
  '''
  all_spike_lists = {}
  spike_file_names = [i for i in get_data_file_names(sim_path) if i.endswith('.spike')]
  for file_name in spike_file_names:
    cell_ref = file_name[:file_name.find('.')] # Cell reference in nC.  
    id = int(cell_ref[cell_ref.find('_')+1:]) # Cell id.  
    pop_name = cell_ref[:cell_ref.rfind('_')] # Cell population name.  
    sig = get_spike_train(file_name) # The spike train.  
    if not all_spike_lists.has_key(pop_name):
        all_spike_lists[pop_name] = {}
    all_spike_lists[pop_name][id] = sig
  for popName in all_spike_lists.keys():
    pass
  return all_spike_lists