def single_testing(pt_net, local_net, sample_pax, save_file_name, time_interval, sample_size, seed):
start_time_int = 0
sim_period = round(1*len(pt_net) - start_time_int)
mu_r = _constants.mu_r
mu_d = _constants.mu_d
beta_I = _constants.beta_I
beta_E = _constants.beta_E
theta_l = _constants.theta_l
theta_g = _constants.theta_g
gamma = _constants.gamma
para_dict = {'mu_r': mu_r, 'mu_d':mu_d, 'beta_I': beta_I,'beta_E': beta_E,
'theta_l':theta_l,'theta_g':theta_g,'gamma':gamma,'initial_I':_constants.initial_I}
simulation_seed = 0
sim = sim_eng.simulation(pt_net, sim_period, local_net, para_dict, sample_size,
time_interval, sample_pax, start_time_int, save_file_name,
verbal = False, random_seed = simulation_seed)
tic = time.time()
sim.run()
running_time = round(time.time() - tic,1)
df_test_info = {'test_name': [save_file_name], 'sample_size':[sample_size],'time_interval':[time_interval],
'sample_seed':[seed],'sim_seed':[simulation_seed],'start_time_int':[start_time_int],
'total_sim_period':[sim_period]}
for para in para_dict:
df_test_info[para] = [para_dict[para]]
df_test_info['running_time'] = [running_time]
df_test_info = pd.DataFrame(df_test_info)
df_test_info.to_csv('output/simulation_para_' + save_file_name + '.csv',index=False)
def system_test(para_hyperspace, num_of_test, sample_case_seed, iterate_all,
time_interval, sample_size, seed):
# get all combination
inputdata = []
for key in para_hyperspace:
inputdata.append(para_hyperspace[key])
result = list(itertools.product(*inputdata))
if iterate_all:
test_samples = result
else:
random.seed(sample_case_seed)
test_samples = random.sample(result, num_of_test)
print('Total sim cases', len(test_samples))
count = 0
for test_case in test_samples:
count += 1
save_file_name = 'system_test_' + str(count)
print('==============')
print('Current test number', count)
start_time_int = 0
sim_period = round(1 * len(pt_net) - start_time_int)
mu_r = test_case[0]
mu_d = test_case[1]
beta_I = test_case[2]
beta_E = 0.01 * test_case[2]
theta_l = test_case[3]
theta_g = test_case[4]
gamma = test_case[5]
initial_I = test_case[6]
para_dict = {
'mu_r': mu_r,
'mu_d': mu_d,
'beta_I': beta_I,
'beta_E': beta_E,
'theta_l': theta_l,
'theta_g': theta_g,
'gamma': gamma,
'initial_I': initial_I
}
print(para_dict)
simulation_seed = 0
sim = sim_eng.simulation(pt_net,
sim_period,
local_net,
para_dict,
sample_size,
time_interval,
sample_pax,
start_time_int,
save_file_name,
verbal=False,
random_seed=simulation_seed)
tic = time.time()
sim.run()
running_time = round(time.time() - tic, 1)
df_test_info = {
'test_name': [save_file_name],
'sample_size': [sample_size],
'time_interval': [time_interval],
'sample_seed': [seed],
'sim_seed': [simulation_seed],
'start_time_int': [start_time_int],
'total_sim_period': [sim_period]
}
for para in para_dict:
df_test_info[para] = [para_dict[para]]
df_test_info['running_time'] = [running_time]
df_test_info = pd.DataFrame(df_test_info)
df_test_info.to_csv('output/simulation_para_' + save_file_name +
'.csv',
index=False)
