!hRddlmZddlmZddlZddlmZerddlm Z ddZ dd Z dS)) annotations) TYPE_CHECKINGN) is_list_like) NumpyIndexTreturnlist[np.ndarray]cDd}t|st||D] }t|st|!t|dkrgStjd|Dtj}tj|}tj|dkrtdtj |ddd<|ddkr |d|z ntj |fdt|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='z$cartesian_product...s(**1A******)dtypez+Product space too large to allocate arrays!c g|]F\}}ttj||tj|GS) tile_compatnprepeatprod)r ir abs r z%cartesian_product..?s[    Aq  Ia1   GAaDMM     r) r TypeErrorr rfromiterintpcumprodany ValueErrorroll zeros_like enumerate)Xmsgr lenXcumprodXrrs @@rcartesian_productr+ sE. 4C ??nn !!A !C..  ! 1vv{{ ;*****"' : : :Dz$H vhlHFGGG !A AaD|q RL8 # M( # #      aLL    rarrrnumintct|tjrtj||Stjtjt ||}||S)zf Index compat for np.tile. Notes ----- Does not support multi-dimensional `num`. ) isinstancerndarraytilearanger take)r,r-takers rrrHs]#rz""!wsC    GBIc#hh'' - -E 88E??r)rr)r,rr-r.rr) __future__rtypingrnumpyrpandas.core.dtypes.commonrpandas._typingrr+rrrrr;s"""""" 222222+******8888v      r