def _align_pairwise(s1,
s2,
mprobs,
psub,
TM,
local,
return_alignment=True,
return_score=False,
**kw):
"""Generic alignment with any substitution model and indel model"""
[p1, p2] = [makeLikelihoodTreeLeaf(seq) for seq in [s1, s2]]
[p1, p2] = [pairwise.AlignableSeq(leaf) for leaf in [p1, p2]]
pair = pairwise.Pair(p1, p2)
EP = pair.makeSimpleEmissionProbs(mprobs, [psub])
hmm = EP.makePairHMM(TM)
vpath = hmm.getViterbiPath(local=local, **kw)
score = vpath.getScore()
if return_alignment:
alignment = vpath.getAlignment()
if return_score:
return (alignment, score)
else:
return alignment
else:
return score
def Edge(seq1, seq2, length, bin_data, switch=1.0, bprobs=None):
# one sequence pair in, potentialy, a tree
bins = len(bin_data)
pair = pairwise.Pair(seq1, seq2)
EP = pair.makeReversibleEmissionProbs([(bin.mprobs, bin.Qd) for bin in bin_data], length)
tms = [bin.indel.calcTransitionMatrix(length) for bin in bin_data]
if bins == 1:
TM = tms[0]
else:
assert bprobs
R = SiteClassTransitionMatrix(switch, bprobs)
TM = R.nestTransitionMatricies(tms)
assert min(TM.Matrix.flat) >=0, bin_data
return EP.makePairHMM(TM)
def _align_pairwise(s1, s2, mprobs, psub, TM, local, return_score=False, **kw):
"""Generic alignment with any substitution model and indel model"""
[p1, p2] = [makeLikelihoodTreeLeaf(seq) for seq in [s1, s2]]
[p1, p2] = [pairwise.AlignableSeq(leaf) for leaf in [p1, p2]]
pair = pairwise.Pair(p1, p2)
EP = pair.makeSimpleEmissionProbs(mprobs, [psub])
hmm = EP.makePairHMM(TM)
if local:
(score, alignment) = hmm.getLocalViterbiScoreAndAlignment(**kw)
else:
(score, alignment) = hmm.getViterbiScoreAndAlignment(**kw)
if return_score:
return alignment, score
else:
return alignment