zIfr@ddlmZmZddlmZGddeZdS))ABCMetaabstractmethod)DictionaryProbDistcneZdZdZed dZedZdZdZedZ dZ d Z d S) ClusterIz< Interface covering basic clustering functionality. FcdS)z Assigns the vectors to clusters, learning the clustering parameters from the data. Returns a cluster identifier for each vector. N)selfvectorsassign_clusterss D/var/www/piapp/venv/lib/python3.11/site-packages/nltk/cluster/api.pyclusterzClusterI.clustercdS)z Classifies the token into a cluster, setting the token's CLUSTER parameter to that cluster identifier. Nr )r tokens r classifyzClusterI.classifyrrc<|||krdSdS)zi Returns the likelihood (a float) of the token having the corresponding cluster. g?)r)r vectorlabels r likelihoodzClusterI.likelihood!s% == E ) )33rci}d}|D]&}|||||<|||z }'|D]}||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#C#CK ;w' 'CC))++ ( (G  C ' !+...rcdS)z1 Returns the number of clusters. Nr r s r num_clusterszClusterI.num_clusters9rrc^tt|S)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 rrs   ^   ^  / / /  ^ 000rr) metaclassN)abcrrnltk.probabilityrrr rr r.sj('''''''//////<<<<<<<<<<<r