numpy:如何从argmax结果中获得最大值

Question

我有一个任意形状的numpy数组,例如:

a = array([[[ 1,  2],
            [ 3,  4],
            [ 8,  6]],

          [[ 7,  8],
           [ 9,  8],
           [ 3, 12]]])
a.shape = (2, 3, 2)

和argmax在最后一个轴上的结果:

np.argmax(a, axis=-1) = array([[1, 1, 0],
                               [1, 0, 1]])

我想得到最大值:

np.max(a, axis=-1) = array([[ 2,  4,  8],
                            [ 8,  9, 12]])

但没有重新计算一切.我试过了:

a[np.arange(len(a)), np.argmax(a, axis=-1)]

但得到了:

IndexError: shape mismatch: indexing arrays could not be broadcast together with shapes (2,) (2,3) 

怎么做？类似的问题2-d:numpy 2d array max/argmax

Answer 1

你可以用advanced indexing-

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]])

对于任何数量维度的通用ndarray案例,如我所述comments by @hpaulj,我们可以使用np.ix_,如此 -

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]