def test_log_probability_list(self):
c = dna.DNA(id="ADADAD", seq='ACTTTAAACCC')
c.calculate_signature()
d = dna.DNA(id="ADADAD", seq='ACTTTACGAACCC')
d.calculate_signature()
dna_l = [c,d]
alpha = [3.0]*c.kmer_hash_count
sig_mat = np.zeros((2,c.kmer_hash_count))
for key,cnt in c.signature.iteritems():
sig_mat[0,key] += cnt
for key,cnt in d.signature.iteritems():
sig_mat[1,key] += cnt
p = model.neg_log_probability_l(alpha,sig_mat,2,np.array([10,8]))
assert_almost_equal(p,88.31776,places=4)
def test_log_probability_without_fit(self):
# Example from figure:
# http://en.wikipedia.org/wiki/File:Beta-binomial_distribution_pmf.png
c = dna.DNA(id="ADADAD",seq='ACTTTAAACCC')
signature = np.array([6,4])
alpha = np.array([600,400])
p = model.log_probability_test(signature,alpha)
# 10 choose 6 = 210
assert_almost_equal(p + np.log(210),-1.38799, places=3)
signature_m = np.zeros((1,2))
signature_m[0,:] = np.array([6,4])
p2 = model.neg_log_probability_l(alpha,signature_m,1,10)
assert_almost_equal(-p2+np.log(210),-1.38799, places=3)
