'A': 0.05,
'C': 0,
'G': 0.95,
'T': 0
},
'I': {
'A': 0.4,
'C': 0.1,
'G': 0.1,
'T': 0.4
}
}
model = MultinomialHMM(n_components=3)
model.startprob_ = np.array([1, 0, 0])
model.endprob_ = np.array([0, 0, 0.1])
model.transmat_ = np.array([[0.9, 0.1, 0], [0, 0, 1], [0, 0, 1]])
model.emissionprob_ = np.array([[0.25, 0.25, 0.25, 0.25], [0.05, 0, 0.95, 0],
[0.4, 0.1, 0.1, 0.4]])
# In[121]:
#"CTTCATGTGAAAGCAGACGTAAGTCA" A = 0 , C = 1 , G = 2 , T = 3
sequence = [
1, 3, 3, 1, 0, 3, 2, 3, 2, 0, 0, 0, 2, 1, 0, 2, 0, 1, 2, 3, 0, 0, 2, 3, 1,
0
]
logprob, seq = model.decode(np.array([sequence]).transpose())
print(logprob)
