def show_agent_model_error_plot(self):
for a in range(self.agent_model_error_list.shape[0]):
agent_name = self.agents[a].name
for r in range(self.agent_model_error_list.shape[1]):
utils.draw_plot(range(len(self.model_error_samples[a, r])), self.agent_model_error_list[a, r],
xlabel='num_samples', ylabel='agent_model_error', show=True,
label=agent_name, title='run_number ' + str(r + 1))
def show_num_steps_plot(self):
if False:
for a in range(self.num_steps_run_list.shape[0]):
agent_name = self.agents[a].name
for r in range(self.num_steps_run_list.shape[1]):
utils.draw_plot(range(len(self.num_steps_run_list[a, r])),
self.num_steps_run_list[a, r],
xlabel='episode_num',
ylabel='num_steps',
show=True,
label=agent_name,
title='run_number ' + str(r + 1))
if False:
for r in range(self.num_steps_run_list.shape[1]):
for a in range(self.num_steps_run_list.shape[0]):
agent_name = self.agents[a].name
utils.draw_plot(range(len(self.num_steps_run_list[a, r])),
self.num_steps_run_list[a, r],
xlabel='episode_num',
ylabel='num_steps',
show=False,
label=agent_name,
title='run_number ' + str(r + 1))
plt.show()
if False:
color = ['blue', 'orange', 'green']
for a in range(self.num_steps_run_list.shape[0]):
agent_name = self.agents[a].name
average_num_steps_run = np.mean(self.num_steps_run_list[a],
axis=0)
std_err_num_steps_run = np.std(self.num_steps_run_list[a],
axis=0)
AUC = sum(average_num_steps_run)
print("AUC:", AUC, agent_name)
utils.draw_plot(range(len(average_num_steps_run)),
average_num_steps_run,
std_error=std_err_num_steps_run,
xlabel='episode_num',
ylabel='num_steps',
show=False,
label=agent_name + str(a),
title='average over runs',
sub_plot_num='4' + '1' + str(a + 1),
color=color[a])
utils.draw_plot(range(len(average_num_steps_run)),
average_num_steps_run,
std_error=std_err_num_steps_run,
xlabel='episode_num',
ylabel='num_steps',
show=False,
label=agent_name + str(a),
title='average over runs',
sub_plot_num=414)
# plt.savefig('')
plt.show()