'emission_state':np.array([1,2,3,4,5]),
'init_prob':np.array([0.5,0.5]),
'trans_prob':np.array([[0.8,0.2],[0.1,0.9]]),
'emission_prob_type':'matrix',
'emission_matrix':np.array([[0.2,0.5,0.2,0.1,0],[0,0.1,0.4,0.4,0.1]])
}
hmm=HMM(init_params=params)
hmm.write_params_to_file('params')
# params read
hmm=HMM(folder_name='params')
# generate
hidden_state_chain,emitted_state_chain=hmm.generate(115)
hidden_state_chain_,emitted_state_chain_=hidden_state_chain,emitted_state_chain
hidden_state_chain,emitted_state_chain=hmm.index2state(hidden_state_chain,'hidden_state'),hmm.index2state(emitted_state_chain,'emission_state')
# plot the generated result
fig, ax = plt.subplots()
x=np.arange(115)
ax.plot(x,emitted_state_chain,label='emitted state')
ax.plot(x,hidden_state_chain,label='hidden state')
ax.set_xlabel('position index')
ax.set_ylabel('state')
ax.legend()
fig.savefig('result/q1.pdf')
fig, ax = plt.subplots()
x=np.arange(115)
ax.plot(x,emitted_state_chain,'.',label='emitted state')
ax.plot(x,hidden_state_chain,'.',label='hidden state')
