Indexing into the last axis of a 3D array with another 3D array

Question

if i have an array x, which value is as follow with shape (2,3,4):

array([[[ 0.15845319,  0.57808432,  0.05638804,  0.56237656],
        [ 0.73164208,  0.80562342,  0.64561066,  0.15397456],
        [ 0.34734043,  0.88063258,  0.4863103 ,  0.09881028]],

       [[ 0.35823078,  0.71260357,  0.49410944,  0.94909165],
        [ 0.02730397,  0.67890392,  0.74340148,  0.47434223],
        [ 0.02494292,  0.59827256,  0.20550867,  0.30859339]]])

and i have an index array y, which shape is (2, 3, 3), and the value is:

array([[[0, 2, 2],
        [2, 0, 2],
        [0, 0, 2]],

       [[1, 2, 1],
        [1, 1, 1],
        [1, 2, 2]]])

so i could use x[0,0,y[0][0]] to index the array x, and it will generate the output as follow:

array([ 0.15845319,  0.05638804,  0.05638804])

my question is: is there any simple way to do this? i had already tried with x[y], it did not work.

i want to do it in an easy way, not a function, just look like the question i post here (stackoverflow.com/questions/39118401/…). — Lei Hua
– Lei Hua, Commented Aug 29, 2016 at 9:22

Divakar · Accepted Answer · 2016-08-29 09:50:31Z

1

You could use fancy-indexing -

m,n = y.shape[:2]
out = x[np.arange(m)[:,None,None],np.arange(n)[:,None],y]

answered Aug 29, 2016 at 9:50

Divakar

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