您可以使用advancedindexing
-
In [17]: a
Out[17]:
array([[[ 1, 2],
[ 3, 4],
[ 8, 6]],
[[ 7, 8],
[ 9, 8],
[ 3, 12]]])
In [18]: idx = a.argmax(axis=-1)
In [19]: m,n = a.shape[:2]
In [20]: a[np.arange(m)[:,None],np.arange(n),idx]
Out[20]:
array([[ 2, 4, 8],
[ 8, 9, 12]])
对于任何数量的维度的通用ndarray情况,如中所述comments by@hpaulj
,我们可以使用np.ix_
,就像这样-
shp = np.array(a.shape)
dim_idx = list(np.ix_(*[np.arange(i) for i in shp[:-1]]))
dim_idx.append(idx)
out = a[dim_idx]