clustering.py 文件源码

def compute_similarity_matrix(self, parent=None):

        clusters = list(self._models)
        n_clusters = len(clusters)

        X = np.vstack([self[cluster][0] for cluster in clusters])

        nX = l2_normalize(X)
        similarities = -squareform(pdist(nX, metric=self.distance))

        matrix = ValueSortedDict()
        for i, j in itertools.combinations(range(n_clusters), 2):
            matrix[clusters[i], clusters[j]] = similarities[i, j]
            matrix[clusters[j], clusters[i]] = similarities[j, i]

        return matrix