def distanceProfile(firstrec, secrec, cdr3="CDR3"):
return profile_distance_allprop(firstrec[cdr3], secrec[cdr3])
TRBdf = TRBdf.set_index('CDR3')
for (seq1, seq2) in nodePairs:
if computOpt == 'pairwiseAlign':
score = pairwise2.align.localds(seq1,
seq2,
matrix,
gop,
gep,
score_only=True)
elif computOpt == 'distancePT':
score = -weighted_cdr3_distance(seq1, seq2,
default_distance_params)
elif computOpt == 'distanceProfile':
score = -profile_distance_allprop(seq1, seq2)
# elif computOpt == 'compareLength':
# score = -abs(len(seq1) - len(seq2))
elif computOpt == 'distanceTrimer':
score = -compareTrimer(seq1, seq2)
elif computOpt == 'distanceDimer':
score = -compareDimer(seq1, seq2)
# elif computOpt == 'distanceVJ':
# v1, j1 = TRBdf.loc[seq1, ['V', 'J']]
# v2, j2 = TRBdf.loc[seq2, ['V', 'J']]
# score = vdist(v1, v2) + jdist(j1, j2)
elif computOpt == 'distanceLvsh':
score = -levenshteinDistance(seq1, seq2)
elif computOpt == 'distanceKernel':
score = KD_scores.loc[(seq1, seq2), 'score'][0]
scorelist.append(score)