def test_stratified_table_cube():
 tab1 = [[[8, 9], [6, 7]], [[4, 9], [5, 5]], [[8, 8], [9, 11]]]
 tab2 = np.asarray(tab1).T
 ct1 = ctab.StratifiedTable(tab1)
 ct2 = ctab.StratifiedTable(tab2)
 assert_allclose(ct1.oddsratio_pooled, ct2.oddsratio_pooled)
 assert_allclose(ct1.logodds_pooled, ct2.logodds_pooled)

def test_stratified_table_cube ( ) : tab1 = [ [ [ 8 , 9 ] , [ 6 , 7 ] ] , [ [ 4 , 9 ] , [ 5 , 5 ] ] , [ [ 8 , 8 ] , [ 9 , 11 ] ] ] tab2 = np . asarray ( tab1 ) . T ct1 = ctab . StratifiedTable ( tab1 ) ct2 = ctab . StratifiedTable ( tab2 ) assert_allclose ( ct1 . oddsratio_pooled , ct2 . oddsratio_pooled ) assert_allclose ( ct1 . logodds_pooled , ct2 . logodds_pooled )
test that we can pass a rank 3 ndarray or a list of rank 2 ndarrays to stratifiedtable and get the same results .