用另一个索引数组正确索引多维Numpy数组 [英] Correctly indexing a multidimensional Numpy array with another array of indices

问题描述

我正在尝试用另一个数组indices为多维数组P编制索引.它指定了我想要的最后一个轴上的哪个元素，如下所示:

I'm trying to index a multidimensional array P with another array indices. which specifies which element along the last axis I want, as follows:

import numpy as np

M, N = 20, 10

P = np.random.rand(M,N,2,9)

# index into the last dimension of P
indices = np.random.randint(0,9,size=(M,N))

# I'm after an array of shape (20,10,2)
# but this has shape (20, 10, 2, 20, 10)
P[...,indices].shape 

如何用indices正确索引P以获得形状为(20,10,2)的数组?

How can I correctly index P with indices to get an array of shape (20,10,2)?

如果不太清楚:对于任何i和j(在边界内)，我希望my_output[i,j,:]等于P[i,j,:,indices[i,j]]

If that's not too clear: For any i and j (in bounds) I want my_output[i,j,:] to be equal to P[i,j,:,indices[i,j]]

推荐答案

我认为这会起作用:

P[np.arange(M)[:, None, None], np.arange(N)[:, None], np.arange(2),
  indices[..., None]]

不漂亮，我知道...

Not pretty, I know...

这可能看起来更好，但也可能不太清晰:

This may look nicer, but it may also be less legible:

P[np.ogrid[0:M, 0:N, 0:2]+[indices[..., None]]]

也许更好:

idx_tuple = tuple(np.ogrid[:M, :N, :2]) + (indices[..., None],)
P[idx_tuple]

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