U c@sPddlmZddlZddlmZddlmZddddZd d d d d d Z dS)) annotationsN) NumpyIndexT) is_list_likezlist[np.ndarray])returncsd}t|st||D]}t|st|qt|dkr>gStjdd|Dtjd}t|}t|dkrxtdt |ddd<|ddkr|d|n t |fd d t |DS) a Numpy version of itertools.product. Sometimes faster (for large inputs)... Parameters ---------- X : list-like of list-likes Returns ------- product : list of ndarrays Examples -------- >>> cartesian_product([list('ABC'), [1, 2]]) [array(['A', 'A', 'B', 'B', 'C', 'C'], dtype='+sz$cartesian_product..)Zdtypez+Product space too large to allocate arrays!cs0g|](\}}tt||t|qSr ) tile_compatnprepeatproduct)rirabr r <s  z%cartesian_product..) r TypeErrorrrZfromiterZintpZ cumproductany ValueErrorZrollZ zeros_like enumerate)XmsgrZlenXZcumprodXr rr cartesian_product s(       rrint)arrnumrcCs8t|tjrt||Sttt||}||S)zf Index compat for np.tile. Notes ----- Does not support multi-dimensional `num`. ) isinstancerZndarrayZtileZarangerZtake)rr Ztakerr r r rEs  r) __future__rZnumpyrZpandas._typingrZpandas.core.dtypes.commonrrrr r r r s   ;