(self, X)
return Xt
Transform X separately by each transformer, concatenate results.
        Parameters
        ----------
        X : iterable or array-like, depending on transformers
            Input data to be transformed.
        Returns
        -------
        Xt : list of ndarray
            List of results of transformers.
Transform X separately by each transformer, concatenate results.
        Parameters
        ----------
        X : iterable or array-like, depending on transformers
            Input data to be transformed.
        Returns
        -------
        Xt : list of ndarray
            List of results of transformers.
Transform X separately by each transformer concatenate results . Parameters ---------- X : iterable or array - like depending on transformers Input data to be transformed . Returns ------- Xt : list of ndarray List of results of transformers .
def transform(self, X):
        """Transform X separately by each transformer, concatenate results.
        Parameters
        ----------
        X : iterable or array-like, depending on transformers
            Input data to be transformed.
        Returns
        -------
        Xt : list of ndarray
            List of results of transformers.

        """
        Xt = Parallel(n_jobs=self.n_jobs)(
            delayed(_transform_one)(trans, X, None, weight)
            for name, trans, weight in self._iter())
        if not Xt:
            # All transformers are None
            return np.zeros((X.shape[0], 0))
        Xt = list(Xt)
        return Xt
def transform ( self , X ) : Xt = Parallel ( n_jobs = self . n_jobs ) ( delayed ( _transform_one ) ( trans , X , None , weight ) for name , trans , weight in self . _iter ( ) ) if not Xt : # All transformers are None return np . zeros ( ( X . shape [ 0 ] , 0 ) ) Xt = list ( Xt ) return Xt