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))