def sweep_paras(zone, n_iter=1, data_version=None, force=False): #paras_iter = {'sig_V':[0., 0.1]} #paras = Paras({'sig_V':0.}) main_dir = os.path.abspath(__file__) main_dir = os.path.split(os.path.dirname(main_dir))[0] choose_paras('nsim', 1) choose_paras('tmp_from_file', 1) config_file = main_dir + '/abm_tactical/config/config.cfg' #loop(paras_iter, paras_iter.keys(), paras, thing_to_do=do, paras=paras, build_pat=build_pat) input_file = result_dir + '/trajectories/M1/trajs_' + zone + '_real_data.dat' #input_file = main_dir + '/trajectories/M1/trajs_for_testing_10_sectors.dat' produce_M1_trajs_from_data(zone=zone, data_version=data_version, put_fake_sectors=True, save_file=input_file) with open(main_dir + '/libs/All_shapes_334.pic','r') as f: all_shapes = pickle.load(f) boundary = list(all_shapes[zone]['boundary'][0].exterior.coords) assert boundary[0]==boundary[-1] with open(result_dir + '/abm_tactical/config/bound_latlon.dat', 'w') as f: for x, y in boundary: f.write(str(x) + '\t' + str(y) + '\n') compute_temporary_points(50000, boundary) #sig_V_iter = [0.] + [10**(-float(i)) for i in range(5, -1, -1)] sig_V_iter = np.arange(0., 0.26, 0.04) #sig_V_iter = [10**(-float(i)) for i in range(4, -1, -1)] #sig_V_iter = [0., 0.0001] # [0.] + [10**(-float(i)) for i in range(5, -1, -1)] #t_w_iter = [40, 80, 120, 160, 240] # times 8 sec t_w_iter = [40, 60, 80, 100, 120]#, 160, 240] # times 8 sec #t_w_iter = [40, 80] # [40, 80, 120, 160, 240] # times 8 sec print for sig_V in sig_V_iter: print "sig_V=", sig_V choose_paras('sig_V', sig_V) for t_w in t_w_iter: print "t_w=", t_w choose_paras('t_w', t_w) for i in range(n_iter): counter(i, n_iter, message="Doing iterations... ") output_file = result_dir + '/trajectories/M3/trajs_' + zone + '_real_data_sigV' + str(sig_V) + '_t_w' + str(t_w) + '_' + str(i) + '.dat' if not os.path.exists(output_file.split('.dat')[0] + '_0.dat') or force: with stdout_redirected(to=result_dir + '/trajectories/M3/log_trajs_' + zone + '_real_data_sigV' + str(sig_V) + '_t_w' + str(t_w) + '_' + str(i) + '.txt'): do_ABM_tactical(input_file, output_file, config_file, verbose=1) print
db.close() for zone in rr: if not zone in dontdo: print "==============================================" print " Running abm: tactical for zone:", zone print "==============================================" with open('../libs/All_shapes_334.pic','r') as f: all_shapes = pickle.load(f) boundary = list(all_shapes[zone]['boundary'][0].exterior.coords) assert boundary[0]==boundary[-1] with open('../abm_tactical/config/bound_latlon.dat', 'w') as f: for x, y in boundary: f.write(str(x) + '\t' + str(y) + '\n') for i in range(n_M1_trajs): if i==0: # Compute temporary points only for first iteration choose_paras('tmp_from_file', 0) else: choose_paras('tmp_from_file', 1) paras_nav = paras_strategic(zone=zone, mode='navpoints', data_version=data_version) name_G = name_net(paras_nav, data_version) name_results = name_sim(name_G) + '_' + str(i)+ '.dat' #for j in range(n_iter): #print '../trajectories/M3/' + name_results + '_' + str(i) input_name = jn(result_dir, 'trajectories/M1/' + name_results) output_name = jn(result_dir, 'trajectories/M3/' + name_results) do_ABM_tactical(input_name, output_name)# + '_' + str(j))