splearn/feature_extraction/text.py
def transform(self, Z):
        """Transform documents to document-term matrix.

        Extract token counts out of raw text documents using the vocabulary
        fitted with fit or the one provided to the constructor.

        Parameters
        ----------
        raw_documents : iterable
            An iterable which yields either str, unicode or file objects.

        Returns
        -------
        X : sparse matrix, [n_samples, n_features]
            Document-term matrix.
        """
        if not hasattr(self, 'vocabulary_'):
            self._validate_vocabulary()

        self._check_vocabulary()

        analyze = self.build_analyzer()
        mapper = self.broadcast(self._count_vocab, Z.context)

        Z = Z.transform(lambda X: list(map(analyze, X)), column='X') \
             .transform(mapper, column='X', dtype=sp.spmatrix)

        return Z
def transform(self, Z):
        if not hasattr(self, 'vocabulary_'):
            self._validate_vocabulary()

        self._check_vocabulary()

        analyze = self.build_analyzer()
        mapper = self.broadcast(self._count_vocab, Z.context)

        Z = Z.transform(lambda X: list(map(analyze, X)), column='X') \
             .transform(mapper, column='X', dtype=sp.spmatrix)

        return Z
def transform ( self , Z ) : if not hasattr ( self , 'vocabulary_' ) : self . _validate_vocabulary ( ) self . _check_vocabulary ( ) analyze = self . build_analyzer ( ) mapper = self . broadcast ( self . _count_vocab , Z . context ) Z = Z . transform ( lambda X : list ( map ( analyze , X ) ) , column = 'X' ) . transform ( mapper , column = 'X' , dtype = sp . spmatrix ) return Z
Transform documents to document-term matrix.

        Extract token counts out of raw text documents using the vocabulary
        fitted with fit or the one provided to the constructor.

        Parameters
        ----------
        raw_documents : iterable
            An iterable which yields either str, unicode or file objects.

        Returns
        -------
        X : sparse matrix, [n_samples, n_features]
            Document-term matrix.
Transform documents to document - term matrix .