if __name__ == "__main__":
transition_matrix = [[0.8, 0.19, 0.01], [0.2, 0.7, 0.1], [0.1, 0.2, 0.7]]
weather_chain = MarkovChain(
transition_matrix=transition_matrix,
states=[
'GGG_GGG', 'GGG_BGG', 'GGG_GBG', 'GGG_GGB', 'GGG_GBB', 'GGG_BBG',
'GGG_BGB', 'GGG_BBB', 'GGB_GGG', 'GGB_BGG', 'GGB_GBG', 'GGB_GGB',
'GGB_GBB', 'GGB_BGB', 'GGB_BBG', 'GGB_BBB', 'GBG_GGG', 'GBG_BGG',
'GBG_GBG', 'GBG_GGB', 'GBG_GBB', 'BGG_BBG', 'BGG_BGB', 'BGG_BBB',
'BGG_GGG', 'BGG_BGG', 'BGG_GBG', 'BGG_GGB', 'BGG_GBB', 'BGG_BBG',
'BGG_BGB', 'BGG_BBB', 'GBB_GGG', 'GBB_BGG', 'GBB_GBG', 'GBB_GGB',
'GBB_GBB', 'GBB_BBG', 'GBB_BGB', 'GBB_BBB', 'BBG_GGG', 'BBG_BGG',
'BBG_GBG', 'BBG_GGB', 'BBG_GBB', 'BBG_BBG', 'BBG_BGB', 'BBG_BBB',
'BGB_GGG', 'BGB_BGG', 'BGB_GBG', 'BGB_GGB', 'BGB_GBB', 'BGB_BBG',
'BGB_BGB', 'BGB_BBB', 'BBB_GGG', 'BBB_BGG', 'BBB_GBG', 'BBB_GGB',
'BBB_GBB', 'BBB_BBG', 'BBB_BGB', 'BBB_BBB'
])
print(weather_chain.next_state(current_state='GGG_GGG'))
print(weather_chain.next_state(current_state='Snowy'))
weather_chain.generate_states(current_state='Snowy', no=10)
#env = MarkovChain()
#RL = QLearningTable(actions=list(range(env.n_actions)))
#update()
#env.after(100, update)
#env.mainloop()
