def helper(y1,y2):
alphabet = ('A','B','')
toy_alphabet = OrderedDict([('A',0),('B',1)])
profile1= profile(y1,alphabet)
profile2=profile(y2,alphabet)
joint_prof = joint_profile(profile1, profile2)
gamma = decoding.pair_gamma(y1,y2)
self.assertTrue(np.isclose(gamma[0,0], joint_prof.prob_agree))
def helper(y1,y2):
alphabet = ('A','B','')
toy_alphabet = OrderedDict([('A',0),('B',1)])
profile1= profile(y1,alphabet)
profile2=profile(y2,alphabet)
joint_prof = joint_profile(profile1, profile2)
gamma = decoding.decoding_cy.pair_gamma_log(np.log(y1).astype(np.float64),np.log(y2).astype(np.float64))
print('log(Z):',gamma[0,0],np.log(joint_prof.prob_agree))
self.assertTrue(np.isclose(gamma[0,0], np.log(joint_prof.prob_agree)))
def helper(y1,y2):
alphabet = ('A','B','')
toy_alphabet = OrderedDict([('A',0),('B',1)])
profile1= profile(y1,alphabet)
profile2=profile(y2,alphabet)
joint_prof = joint_profile(profile1, profile2)
top_label = joint_prof.top_label()
search_top_label = decoding.pair_prefix_search(y1,y2,alphabet=toy_alphabet)
return((top_label[0] == search_top_label[0]) and np.isclose(top_label[1] / joint_prof.prob_agree, search_top_label[1]))
def helper(y):
alphabet = ('A','B','')
toy_alphabet = OrderedDict([('A',0),('B',1)])
prof = profile(y,alphabet)
top_label = prof.top_label()
search_top_label = decoding.prefix_search(y,alphabet=toy_alphabet)
return((top_label[0] == search_top_label[0]) and np.isclose(top_label[1], search_top_label[1]))
def helper(y,l):
label_int = [alphabet_dict[i] for i in label]
prof = profile(y,alphabet)
alpha = np.log(decoding.forward(label_int, y))
prefix_prob = logsumexp(decoding.forward_vec_no_gap_log(label_int,np.log(y),alpha[-2]))
print(prefix_prob, prof.prefix_prob(label))
self.assertTrue(np.isclose(prefix_prob, np.log(prof.prefix_prob(label))))
def test_label_prob_log(self):
alphabet = ('A','B','')
alphabet_dict = {'A':0,'B':1,'':2}
y = np.array([[0.8,0.1,0.1],[0.1,0.3,0.6],[0.7,0.2,0.1],[0.1,0.1,0.8]])
examples = ['AAAA','ABBA','ABA','AA','BB','A','B']
prof=profile(y,alphabet)
for label in examples:
label_int = [alphabet_dict[i] for i in label]
alpha = decoding.forward(label_int, np.log(y), decoding.forward_vec_log)
self.assertTrue(np.isclose(alpha[-1,-1], np.log(prof.label_prob(label))))
def helper(y,l):
label_int = [alphabet_dict[i] for i in label]
prof = profile(y,alphabet)
alpha = decoding.forward(label_int, y)
prefix_prob = np.sum(decoding.forward_vec_no_gap(label_int,y,alpha[-2]))
self.assertTrue(np.isclose(prefix_prob, prof.prefix_prob(label)))
