B >?ð[Nã@sDddlmZmZddlmZddlmZeeƒGdd„deƒƒZdS)é)ÚABCMetaÚabstractmethod)Ú add_metaclass)ÚDictionaryProbDistc@sVeZdZdZeddd„ƒZedd„ƒZdd„Zd d „Zed d „ƒZ d d„Z dd„Z dS)ÚClusterIz< Interface covering basic clustering functionality. FcCsdS)zš Assigns the vectors to clusters, learning the clustering parameters from the data. Returns a cluster identifier for each vector. N©)ÚselfZvectorsZassign_clustersrrú/lib/python3.7/site-packages/nltk/cluster/api.pyÚclusterszClusterI.clustercCsdS)z€ Classifies the token into a cluster, setting the token's CLUSTER parameter to that cluster identifier. Nr)rÚtokenrrr ÚclassifyszClusterI.classifycCs| |¡|krdSdSdS)zi Returns the likelihood (a float) of the token having the corresponding cluster. gð?gN)r )rÚvectorZlabelrrr Ú likelihood#szClusterI.likelihoodcCs`i}d}x,| ¡D] }| ||¡||<|||7}qWx | ¡D]}|||<q@Wt|ƒS)z Classifies the token into a cluster, returning a probability distribution over the cluster identifiers. g)Ú cluster_namesrr)rr Z likelihoodsÚsumr rrr Úclassification_probdist-sz ClusterI.classification_probdistcCsdS)z1 Returns the number of clusters. Nr)rrrr Ú num_clusters;szClusterI.num_clusterscCstt| ¡ƒƒS)zI Returns the names of the clusters. :rtype: list )ÚlistÚranger)rrrr rAszClusterI.cluster_namescCs|S)z< Returns the names of the cluster at index. r)rÚindexrrr Ú cluster_nameHszClusterI.cluster_nameN)F) Ú__name__Ú __module__Ú __qualname__Ú__doc__rr r rrrrrrrrr rs    rN) ÚabcrrZsixrZnltk.probabilityrÚobjectrrrrr Ú s