predicting next observation using HMMLearn.multinomialhmm(discrete hmm) I have implemented a HMM using hmmlearn:

states = ['healthy','sick']
observations = ['sleeping','eating','pooping']
model = HMM(n_components=2)
model.n_features = 3
model.startprob_ = [0.7, 0.3]
model.transmat_ = [
    [0.8, 0.2],
    [0.4, 0.6]
]
model.emissionprob_ = [
    [0.2, 0.6, 0.2],
    [0.4, 0.1, 0.5],
]


Also, I have a sequence of observations:

obs = np.array([0,0,1,0,2,0,1,2,0,1,0,2,0,1,1,2,0])
obs = obs.reshape(-1, 1)


Now, I would like to predict the next observation (at t+1), but don't know how to do this.

(I've read the documentation but haven't found anything)
i found out that there is no function to do this just can use model.predict() to get hidden states probabilities and then find out the next state(and observation) using Viterbi algorithm.