with open('action_history_backup.pkl', 'wb') as output:
pickle.dump(action_history, output, pickle.HIGHEST_PROTOCOL)
with open('state_history_backup.pkl', 'wb') as output:
pickle.dump(state_history, output, pickle.HIGHEST_PROTOCOL)
with open('mean_error_history_backup.pkl', 'wb') as output:
pickle.dump(mean_error_history, output, pickle.HIGHEST_PROTOCOL)
expert.print()
# find out what are the ids that existed
region_ids = sorted(list(zip(*mean_error_history[-1]))[0])
Viz.plot_expert_tree(expert, region_ids)
#Viz.plot_evolution(state_history, title='State vs Time', y_label='S(t)', fig_num=1, subplot_num=261)
Viz.plot_evolution(action_history, title='Action vs Time', y_label='M(t)[1]', y_dim=1, fig_num=1, subplot_num=261)
Viz.plot_evolution(action_history, title='Action vs Time', y_label='M(t)[0]', y_dim=0, fig_num=1, subplot_num=262)
Viz.plot_model(expert, region_ids, x_idx=1, y_idx=0, fig_num=1, subplot_num=263)
Viz.plot_model(expert, region_ids, x_idx=2, y_idx=0, fig_num=1, subplot_num=269)
Viz.plot_regional_mean_errors(mean_error_history, region_ids, fig_num=1, subplot_num=234)
#Viz.plot_model_3D(expert, region_ids, x_idx=(0, 1), y_idx=0, fig_num=1, subplot_num=122)
Viz.plot_model_3D(expert, region_ids, x_idx=(1, 2), y_idx=0, fig_num=1, subplot_num=122, data_only=False)
plt.ioff()
plt.show()
