python - using an numpy array as indices of the 2nd dim of another array?

Question

For example, I have two numpy arrays,

A = np.array(
  [[0,1], 
   [2,3], 
   [4,5]])
B = np.array(
  [[1],
   [0],
   [1]], dtype='int')

and I want to extract one element from each row of A, and that element is indexed by B, so I want the following results:

C = np.array(
  [[1],
   [2],
   [5]])

I tried A[:, B.ravel()], but it'll broadcast B, not what I want. Also looked into np.take, seems not the right solution to my problem.

However, I could use np.choose by transposing A,

np.choose(B.ravel(), A.T)

but any other better solution?

@unutbu Well sort of different here, as we are selecting one element per row as opposed to multiple elements per row in the linked previous question. — Divakar
@Divakar: If the OP wants the 2D array, C, your answer on the linked page gives the desired result exactly. — unutbu
@unutbu, the answer you linked use np.take, and I don't think it could fix my problem? — avocado

Divakar Divakar · Accepted Answer · 2016-06-18T13:56:34

You can use NumPy's purely integer array indexing -

A[np.arange(A.shape[0]),B.ravel()]

Sample run -

In [57]: A
Out[57]: 
array([[0, 1],
       [2, 3],
       [4, 5]])

In [58]: B
Out[58]: 
array([[1],
       [0],
       [1]])

In [59]: A[np.arange(A.shape[0]),B.ravel()]
Out[59]: array([1, 2, 5])

Please note that if B is a 1D array or a list of such column indices, you could simply skip the flattening operation with .ravel().

Sample run -

In [186]: A
Out[186]: 
array([[0, 1],
       [2, 3],
       [4, 5]])

In [187]: B
Out[187]: [1, 0, 1]

In [188]: A[np.arange(A.shape[0]),B]
Out[188]: array([1, 2, 5])

python - using an numpy array as indices of the 2nd dim of another array?

2 Answers