def build_hmm(trans, emis, seed=1):
"""Builds and returns hmm_model given the transition and emission probabilities matrices"""
hmm = MultinomialHMM(n_components=trans.shape[0],
algorithm="viterbi",
random_state=seed)
hmm.__setattr__("n_features", emis.shape[1])
hmm.__setattr__("emissionprob_", emis)
hmm.__setattr__("startprob_", np.array(
[1] + [0] *
(trans.shape[0] - 1))) # We will always start at the first state
hmm.__setattr__("transmat_", trans)
return hmm
