o rZh(@s2ddlmZmZddlmZGdddedZdS))ABCMetaabstractmethod)DictionaryProbDistc@sVeZdZdZedddZeddZddZd d Zed d Z d dZ ddZ dS)ClusterIz< Interface covering basic clustering functionality. FcCdS)z Assigns the vectors to clusters, learning the clustering parameters from the data. Returns a cluster identifier for each vector. N)selfZvectorsZassign_clustersrr?/var/www/auris/lib/python3.10/site-packages/nltk/cluster/api.pyclusterzClusterI.clustercCr)z Classifies the token into a cluster, setting the token's CLUSTER parameter to that cluster identifier. Nr)rtokenrrr classifyr zClusterI.classifycCs|||kr dSdS)zi Returns the likelihood (a float) of the token having the corresponding cluster. g?)r )rvectorlabelrrr likelihood!szClusterI.likelihoodcCsXi}d}|D]}|||||<|||7}q|D] }|||<qt|S)z Classifies the token into a cluster, returning a probability distribution over the cluster identifiers. r) cluster_namesrr)rrZ likelihoodssumr rrr classification_probdist+s  z ClusterI.classification_probdistcCr)z1 Returns the number of clusters. Nrrrrr num_clusters9r zClusterI.num_clusterscCstt|S)zI Returns the names of the clusters. :rtype: list )listrangerrrrr r?szClusterI.cluster_namescCs|S)z< Returns the names of the cluster at index. r)rindexrrr cluster_nameFszClusterI.cluster_nameN)F) __name__ __module__ __qualname____doc__rr r rrrrrrrrr rs     r) metaclassN)abcrrZnltk.probabilityrrrrrr s