(self, docnums, fieldname, numterms=5,
                  model=classify.Bo1Model, normalize=True)
return expander.expanded_terms(numterms, normalize=normalize)
Returns the 'numterms' most important terms from the documents
        listed (by number) in 'docnums'. You can get document numbers for the
        documents your interested in with the document_number() and
        document_numbers() methods.

        "Most important" is generally defined as terms that occur frequently in
        the top hits but relatively infrequently in the collection as a whole.

        >>> docnum = searcher.document_number(path=u"/a/b")
        >>> keywords_and_scores = searcher.key_terms([docnum], "content")

        This method returns a list of ("term", score) tuples. The score may be
        useful if you want to know the "strength" of the key terms, however to
        just get the terms themselves you can just do this:

        >>> kws = [kw for kw, score in searcher.key_terms([docnum], "content")]

        :param fieldname: Look at the terms in this field. This field must
            store vectors.
        :param docnums: A sequence of document numbers specifying which
            documents to extract key terms from.
        :param numterms: Return this number of important terms.
        :param model: The classify.ExpansionModel to use. See the classify
            module.
        :param normalize: normalize the scores.
        :returns: a list of ("term", score) tuples.
Returns the 'numterms' most important terms from the documents
        listed (by number) in 'docnums'. You can get document numbers for the
        documents your interested in with the document_number() and
        document_numbers() methods.
Returns the numterms most important terms from the documents listed ( by number ) in docnums . You can get document numbers for the documents your interested in with the document_number () and document_numbers () methods .
def key_terms(self, docnums, fieldname, numterms=5,
                  model=classify.Bo1Model, normalize=True):
        """Returns the 'numterms' most important terms from the documents
        listed (by number) in 'docnums'. You can get document numbers for the
        documents your interested in with the document_number() and
        document_numbers() methods.

        "Most important" is generally defined as terms that occur frequently in
        the top hits but relatively infrequently in the collection as a whole.

        >>> docnum = searcher.document_number(path=u"/a/b")
        >>> keywords_and_scores = searcher.key_terms([docnum], "content")

        This method returns a list of ("term", score) tuples. The score may be
        useful if you want to know the "strength" of the key terms, however to
        just get the terms themselves you can just do this:

        >>> kws = [kw for kw, score in searcher.key_terms([docnum], "content")]

        :param fieldname: Look at the terms in this field. This field must
            store vectors.
        :param docnums: A sequence of document numbers specifying which
            documents to extract key terms from.
        :param numterms: Return this number of important terms.
        :param model: The classify.ExpansionModel to use. See the classify
            module.
        :param normalize: normalize the scores.
        :returns: a list of ("term", score) tuples.
        """

        expander = classify.Expander(self.ixreader, fieldname, model=model)
        for docnum in docnums:
            expander.add_document(docnum)
        return expander.expanded_terms(numterms, normalize=normalize)
def key_terms ( self , docnums , fieldname , numterms = 5 , model = classify . Bo1Model , normalize = True ) : expander = classify . Expander ( self . ixreader , fieldname , model = model ) for docnum in docnums : expander . add_document ( docnum ) return expander . expanded_terms ( numterms , normalize = normalize )