new_contents: import numpy as np
  
  from cytokine_settings import build_model, DEFAULT_MODEL, APP_FIELD_STRENGTH, RUNS_SUBDIR_CYTOKINES
  from cytokine_simulate import cytokine_sim
  
  from singlecell_class import Cell
  from singlecell_constants import NUM_STEPS, BETA
  from singlecell_data_io import run_subdir_setup
  from singlecell_functions import state_to_label, label_to_state
  
  
  def state_landscape(model_name=DEFAULT_MODEL, iterations=NUM_STEPS, applied_field_strength=APP_FIELD_STRENGTH, flag_write=False):
  
      spin_labels, intxn_matrix, applied_field_const, init_state = build_model(DEFAULT_MODEL)
      N = len(spin_labels)
  
      labels_to_states = {idx:label_to_state(idx, N) for idx in xrange(2 ** N)}
      states_to_labels = {tuple(v): k for k, v in labels_to_states.iteritems()}
  
      for state_label in range(2**N):
          init_cond = labels_to_states[state_label]
          print "\nSimulating with init state label", state_label, ":", init_cond
          state_array, dirs = cytokine_sim(iterations=iterations, beta=100.0, flag_write=False, applied_field_strength=0.0, init_state_force=init_cond)
          label_timeseries = [states_to_labels[tuple(state_array[:,t])] for t in xrange(iterations)]
          for elem in label_timeseries:
              print elem, "|",
      return
  
  
  if __name__ == '__main__':
      state_landscape(iterations=10)
  
subject: determine label timeseries of state space under noise