是否存在与numpy.argmax类似的Julia？

Question

在Python中,有numpy.argmax:

In [7]: a = np.random.rand(5,3)

In [8]: a
Out[8]: 
array([[ 0.00108039,  0.16885304,  0.18129883],
       [ 0.42661574,  0.78217538,  0.43942868],
       [ 0.34321459,  0.53835544,  0.72364813],
       [ 0.97914267,  0.40773394,  0.36358753],
       [ 0.59639274,  0.67640815,  0.28126232]])

In [10]: np.argmax(a,axis=1)
Out[10]: array([2, 1, 2, 0, 1])

是否有朱莉娅类似于Numpy的argmax？我只找到了一个indmax,它只接受一个向量,而不是二维数组np.argmax.

Answer 1

最快的实现通常是findmax(如果您愿意,可以一次减少多个维度)以及ind2sub:

julia> a=rand(5,3)
5x3 Array{Float64,2}:
0.283078  0.202384  0.667838 
0.366416  0.671204  0.572707 
0.77384   0.919672  0.127949 
0.873921  0.9334    0.0210074
0.319042  0.200109  0.0944871

julia> mxval, mxindx = findmax(a, 2)
(
5x1 Array{Float64,2}:
0.667838
0.671204
0.919672
0.9334  
0.319042,

5x1 Array{Int64,2}:
11
7
8
9
5)

julia> ind2sub(size(a), vec(mxindx))[2]
5-element Array{Int64,1}:
3
2
2
2
1