splearn/rdd.py
def transform(self, fn, dtype=None, *args, **kwargs):
        """Equivalent to map, compatibility purpose only.
        Column parameter ignored.
        """
        rdd = self._rdd.map(fn)

        if dtype is None:
            return self.__class__(rdd, noblock=True, **self.get_params())
        if dtype is np.ndarray:
            return ArrayRDD(rdd, bsize=self.bsize, noblock=True)
        elif dtype is sp.spmatrix:
            return SparseRDD(rdd, bsize=self.bsize, noblock=True)
        else:
            return BlockRDD(rdd, bsize=self.bsize, dtype=dtype, noblock=True)
def transform(self, fn, dtype=None, *args, **kwargs):
        rdd = self._rdd.map(fn)

        if dtype is None:
            return self.__class__(rdd, noblock=True, **self.get_params())
        if dtype is np.ndarray:
            return ArrayRDD(rdd, bsize=self.bsize, noblock=True)
        elif dtype is sp.spmatrix:
            return SparseRDD(rdd, bsize=self.bsize, noblock=True)
        else:
            return BlockRDD(rdd, bsize=self.bsize, dtype=dtype, noblock=True)
def transform ( self , fn , dtype = None , * args , * * kwargs ) : rdd = self . _rdd . map ( fn ) if dtype is None : return self . __class__ ( rdd , noblock = True , * * self . get_params ( ) ) if dtype is np . ndarray : return ArrayRDD ( rdd , bsize = self . bsize , noblock = True ) elif dtype is sp . spmatrix : return SparseRDD ( rdd , bsize = self . bsize , noblock = True ) else : return BlockRDD ( rdd , bsize = self . bsize , dtype = dtype , noblock = True )
Equivalent to map, compatibility purpose only.
        Column parameter ignored.
Equivalent to map compatibility purpose only . Column parameter ignored .