本文整理汇总了Python中simulator.Simulator.out_of_sample方法的典型用法代码示例。如果您正苦于以下问题：Python Simulator.out_of_sample方法的具体用法？Python Simulator.out_of_sample怎么用？Python Simulator.out_of_sample使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类simulator.Simulator的用法示例。
在下文中一共展示了Simulator.out_of_sample方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: run
# 需要导入模块: from simulator import Simulator [as 别名]
# 或者: from simulator.Simulator import out_of_sample [as 别名]
def run(s_option):
"""
Run the agent for a finite number of trials.:
:param s_option: string. The type of the test
"""
i_idx = 15 # 15 # index of the start file to be used in simulations
n_trials = 10 # number of repetitions of the same sessions
n_sessions = 1 # number of different days traded
# Set up environment
s_fname = 'data/data_0725_0926.zip'
e = Environment(s_fname=s_fname, i_idx=i_idx)
# create agent
if s_option in ['train_learner', 'test_learner', 'optimize_k',
'optimize_gamma']:
a = e.create_agent(LearningAgent_k,
f_min_time=2.,
f_k=0.8,
f_gamma=0.5)
elif s_option == 'test_random':
a = e.create_agent(BasicAgent, f_min_time=2.)
else:
l_aux = ['train_learner', 'test_learner', 'test_random', 'optimize_k',
'optimize_gamma']
s_err = 'Select an <OPTION> between: \n{}'.format(l_aux)
raise InvalidOptionException(s_err)
e.set_primary_agent(a) # specify agent to track
# set up the simulation object
sim = Simulator(e, update_delay=1.00, display=False)
if 'train' in s_option:
# ==== IN-SAMPLE TEST ====
# Training the agent
s_print = 'run(): Starting training session ! In-Sample Test.'
if DEBUG:
root.debug(s_print)
else:
print s_print
# run for a specified number of trials
sim.train(n_trials=n_trials, n_sessions=n_sessions)
# test the agent
s_print = 'run(): Starting testing phase ! In-Sample Test.'
if DEBUG:
root.debug(s_print)
else:
print s_print
# run for a specified number of trials. should have the same number of
# trials and session of the training phase
sim.in_sample_test(n_trials=n_trials, n_sessions=n_sessions)
elif s_option in ['test_random', 'test_learner']:
# ==== OUT-OF-SAMPLE TEST ====
# test the agent
s_print = 'run(): Starting testing phase ! Out-of-Sample Test.'
if DEBUG:
root.debug(s_print)
else:
print s_print
# run for a specified number of trials
s_qtable = 'log/qtable/LearningAgent_k_qtable_{}.log'.format(n_trials)
if e.primary_agent.s_agent_name == 'BasicAgent':
# run that if is the basicagent
sim.out_of_sample(s_qtable=s_qtable,
n_start=n_sessions+i_idx,
n_trials=20,
n_sessions=1)
else:
# the learning agent, when the policy is freezed, will always take
# the same actions. So there is no meaning on test multiple times
sim.out_of_sample(s_qtable=s_qtable,
n_start=n_sessions+i_idx,
n_trials=1,
n_sessions=1)
elif s_option == 'optimize_k':
# test the agent
s_print = 'run(): Starting training session ! Optimiza_K Test.'
if DEBUG:
root.debug(s_print)
else:
print s_print
# k tests
for f_k in [0.3, 0.8, 1.3, 2.]:
e = Environment(s_fname=s_fname, i_idx=i_idx)
a = e.create_agent(LearningAgent_k,
f_min_time=2.,
f_k=f_k,
f_gamma=0.5)
e.set_primary_agent(a)
sim = Simulator(e, update_delay=1.00, display=False)
sim.train(n_trials=5, n_sessions=1)
elif s_option == 'optimize_gamma':
# test the agent
s_print = 'run(): Starting training session ! Optimiza_gamma Test.'
if DEBUG:
root.debug(s_print)
else:
print s_print
# gamma test
#.........这里部分代码省略.........