def mpat(tr, seqs) :
dseqs = dict(seqs)
for n in getPostOrder(tr) :
data = n.data
if not n.succ :
data.seq = (None,dseqs[n.data.taxon])
else :
s1,s2 = [tr.node(x).data.seq for x in n.succ]
if s1[1] :
if s2[1] :
a = calign.globalAlign(s1[1],s2[1])
data.seq = (calign.createProfile(a),None)
else :
p1,p2 = calign.createProfile(s1[1:]), s2[0]
#assert all([sum(x)==sum(p1[0]) for x in p1])
#assert all([sum(x)==sum(p2[0]) for x in p2])
pa = calign.prof2profAlign(p1,p2)
data.seq = (trimp(pa),None)
#print len(pa)
else :
p1 = s1[0]
if s2[1] :
p2 = calign.createProfile(s2[1:])
else :
p2 = s2[0]
#assert all([sum(x)==sum(p1[0]) for x in p1])
#assert all([sum(x)==sum(p2[0]) for x in p2])
pa = calign.prof2profAlign(p1,p2)
data.seq = (trimp(pa),None)
#print len(pa)
#import pdb; pdb.set_trace()
assert n.id == tr.root
return n.data.seq[0]
def mpa(tr, seqs, scores = defaultMatchScores, trimEnd = None) :
dseqs = dict(seqs)
#scores = (None,None,gapPenalty,feg)
for n in getPostOrder(tr) :
data = n.data
if not n.succ :
data.seq = (None,dseqs[n.data.taxon.strip("'")])
else :
s1,s2 = [tr.node(x).data.seq for x in n.succ]
if s1[1] :
if s2[1] :
a = calign.globalAlign(s1[1],s2[1], scores = scores)
data.seq = (calign.createProfile(a),None)
else :
p1,p2 = calign.createProfile(s1[1:]), s2[0]
pa = calign.prof2profAlign(p1,p2, scores = scores)
data.seq = (trimendsp(pa, trimEnd) if trimEnd is not None else pa,None)
#print len(pa)
else :
p1 = s1[0]
if s2[1] :
p2 = calign.createProfile(s2[1:])
else :
p2 = s2[0]
pa = calign.prof2profAlign(p1,p2, scores = scores)
data.seq = (trimendsp(pa, trimEnd) if trimEnd is not None else pa,None)
#print len(pa)
#import pdb; pdb.set_trace()
assert n.id == tr.root
return n.data.seq[0]
