def doTheCons(sqs, trh, lengthQuant = 40) :
als = [(lengthQuant*(len(s)//lengthQuant), s) for s in sqs]
als = [x[1] for x in sorted(als, reverse=1)]
scmp = random.sample(sqs, min(5,len(sqs)))
cbest = (None,100000)
for i in range(3) :
al = seqMultiAlign(als)
c = stripseq(cons(calign.createProfile(al)))
# spot check
p = mean(calign.allpairs(c, scmp, report = calign.JCcorrection))/2
if p < cbest[1] :
cbest = (c, p)
if i == 2 or p < trh :
break
if i == 0 :
# try original order
als = sqs
elif i == 1 :
# try random order
als = list(sqs)
random.shuffle(als)
return cbest[0]
def getDist(i,j) :
mi,mj = mhs[i],mhs[j]
anyCons = False
if mi < lowDiversity :
ri = [getCons(i)]
anyCons = True
else :
ri = getReps(i)
if mj < lowDiversity :
rj = [getCons(j)]
anyCons = True
else :
rj = getReps(j)
nhs = len(ri)*len(rj)
if nhs == 1 :
h = calign.globalAlign(ri[0], rj[0], scores = defaultMatchScores,
report = calign.JCcorrection)
else :
ap = calign.allpairs(ri, rj, align=True, scores = defaultMatchScores,
report = calign.JCcorrection)
h = sum([sum(x) for x in ap])/nhs
global acnt
acnt += nhs
lowLim = 2*max(mi,mj)
if anyCons and (h < lowLim or (h < refineUpperLimit and h < lowLim*refineFactor)) :
xri = getReps(i) if len(ri) == 1 else ri
xrj = getReps(j) if len(rj) == 1 else rj
if ri != xri or rj != xrj :
ap1 = calign.allpairs(xri, xrj, align=True, scores = defaultMatchScores,
report = calign.JCcorrection)
h1 = sum([sum(x) for x in ap1])
xnhs = (len(xri)*len(xrj))
acnt += xnhs
h = (h * nhs + h1)/(nhs + xnhs)
return max(h, lowLim)
