def getMaxSimilarityForNJ(d, seq):
Q = {}
n = len(seq)
for (i, j) in d:
sumI = 0
sumJ = 0
for k in seq:
if i != k:
sumI += d[i, k]
if j != k:
sumJ += d[j, k]
Q[i, j] = (n - 2) * d[i, j] - sumI - sumJ
maxSimilarity = Clustering.getMax(Q)
return maxSimilarity
def getMaxSimilarityForUPGMA(d):
maxSimilarity = Clustering.getMax(d)
return maxSimilarity
