kh(8ddlmZmZddlmZGddeZy))ABCMetaabstractmethod)DictionaryProbDistcZeZdZdZed dZedZdZdZedZ dZ dZ y ) ClusterIz< Interface covering basic clustering functionality. cy)z Assigns the vectors to clusters, learning the clustering parameters from the data. Returns a cluster identifier for each vector. N)selfvectorsassign_clusterss L/opt/mcp/mcp-sentiment/venv/lib/python3.12/site-packages/nltk/cluster/api.pyclusterzClusterI.clustercy)z Classifies the token into a cluster, setting the token's CLUSTER parameter to that cluster identifier. Nr )r tokens r classifyzClusterI.classifyrrc.|j||k(ryy)zi Returns the likelihood (a float) of the token having the corresponding cluster. g?)r)r vectorlabels r likelihoodzClusterI.likelihood!s == E )rci}d}|jD]}|j||||<|||z }!|jD]}||xx|zcc<t|S)z Classifies the token into a cluster, returning a probability distribution over the cluster identifiers. r) cluster_namesrr)r r likelihoodssumrs r classification_probdistz ClusterI.classification_probdist+s  ))+ (G#'??67#CK ;w' 'C ())+ (G  C '  (!+..rcy)z1 Returns the number of clusters. Nr r s r num_clusterszClusterI.num_clusters9rrcFtt|jS)zI Returns the names of the clusters. :rtype: list )listranger rs r rzClusterI.cluster_names?s E$++-.//rc|S)z< Returns the names of the cluster at index. r )r indexs r cluster_namezClusterI.cluster_nameFs  rN)F) __name__ __module__ __qualname____doc__rrrrrr rr&r rr rrsW     /  0rr) metaclassN)abcrrnltk.probabilityrrr rr r.s(/<<r