def mleks(_seqa, _seqb):
seqa, seqb = clean_seqs(_seqa, _seqb)
D = calc_difference(seqa, seqb)
seqab = seqa + seqb
slen = len(seqab)/2
scores = {}
# give the optimizer the best guess from this range.
for guess in (0.3, 0.5, 0.75, 1.1, 1.5):
scores[guess] = score_guess(guess, seqab, D, slen)
best_guess = sorted(scores.items(), key=lambda a: (a[1], a[0]))[0][0]
def fnopt(ks_guess):
return score_guess(ks_guess[0], seqab, D, slen)
r = so.fmin(fnopt, best_guess, args=(), disp=False,
xtol=0.1, maxfun=20)
return r[0]
def mleks(_seqa, _seqb):
seqa, seqb = clean_seqs(_seqa, _seqb)
D = calc_difference(seqa, seqb)
seqab = seqa + seqb
slen = len(seqab) / 2
scores = {}
# give the optimizer the best guess from this range.
for guess in (0.3, 0.5, 0.75, 1.1, 1.5):
scores[guess] = score_guess(guess, seqab, D, slen)
best_guess = sorted(scores.items(), key=lambda a: (a[1], a[0]))[0][0]
def fnopt(ks_guess):
return score_guess(ks_guess[0], seqab, D, slen)
r = so.fmin(fnopt, best_guess, args=(), disp=False, xtol=0.1, maxfun=20)
return r[0]
def fnopt(ks_guess):
return score_guess(ks_guess[0], seqab, D, slen)
def fnopt(ks_guess):
return score_guess(ks_guess[0], seqab, D, slen)
