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