`Vg@ddlmZddlZddlmZddlmZddZddZ y) ) annotationsN) NumpyIndexT) is_list_likec d}t|s t||D]}t|rt|t|dk(rgStjd|Dtj }tj |}tj|dkr tdtj|d}d|d<|ddk7r |d|z }ntj|}t|Dcgc]>\}}ttj|||tj||@c}}Scc}}w)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='z$cartesian_product..+s*1A*s)dtypez+Product space too large to allocate arrays!)r TypeErrorrnpfromiterintp cumproductany ValueErrorroll zeros_like enumerate tile_compatrepeatproduct)Xmsgr lenXcumprodXabis r cartesian_productr$ s&. 4C ?n !AC. ! 1v{ ;;**"'' :D}}T"H vvhlFGG !A AaD|q RL8 # MM( #aL   Aq  IIa1  JJqt    s9AEct|tjrtj||Stjtjt ||}|j |S)zf Index compat for np.tile. Notes ----- Does not support multi-dimensional `num`. ) isinstancerndarraytilearangertake)arrnumtakers r rrEsP#rzz"wwsC   GGBIIc#h' -E 88E?)returnzlist[np.ndarray])r+rr,intr/r) __future__rnumpyrpandas._typingrpandas.core.dtypes.commonrr$rr.r r6s"&28v r.