def main():
"""
All the experiments on all the configurations and all the policies have all the same true mean.
The generation of the stochastic processes from this true means is different for each experiment.
"""
#log config
logging.basicConfig(filename=st.LOG_FILENAME,level=logging.INFO)
exe = Executor()
for config in st.configs:
str_info= '\n Executing experiments of configuration ' + config.name + ' with N=' + str(st.N) + ' and num_rep=' + str(st.num_repetitions) + ' ...'
logging.info(str_info)
print(str_info)
start_time = time.clock()
exe.run_configuration(config, st.policies, st.num_repetitions, st.N)
exp_time = time.clock() - start_time
str_info = 'TIME TO PERFORM EXPERIMENTS OF ' + config.name + 'CONFIGURATION: ' + str(exp_time)
logging.info(str_info)
print(str_info)
def main():
#set configuration
N = 2**17
num_repetitions = 5
config = MUUD_Configuration(N)
#set possible values of a parameter
values = np.arange(0.1, 1, 0.1)
#set policy
policies = []
policy_names = []
for value in values:
policy = UCB2_Policy(alpha=value)
policy.name = policy.name + str(value)
policies = policies + [policy]
policy_names = policy_names + [policy.name]
#execute experiments
exe = Executor()
print('Executing experiments for tunining...')
start_time = time.clock()
exe.run_configuration(config, policies, num_repetitions)
exp_time = time.clock() - start_time
print('TIME TO PERFORM EXPERIMENTS: ', exp_time)
#printing the results
print('Printing tuning results...')
start_time = time.clock()
plot_configuration(config.name, policy_names)
exp_time = time.clock() - start_time
print('TIME TO PRINT RESULTS: ', exp_time)
