Slicing Numpy Array by 2 index arrays

Question

If I have a set of indices stored in two Numpy arrays, my goal is to slice a given input array based on corresponding indices in those index arrays. For eg.

index_arr1 = np.asarray([2,3,4])
index_arr2 = np.asarray([5,5,6])

input_arr = np.asarray([1,2,3,4,4,5,7,2])

The output to my code should be [[3,4,4],[4,4],[4,5]] which is basically [input_arr[2:5], input_arr[3:5], input_arr[4:6]]

Can anybody suggest a way to solve this problem using numpy functions and avoiding any for loops to be as efficient as possible.

There's no numpy magic to take multiple slices like this (especially with overlapping slices of differing length). — hpaulj
– hpaulj, Commented May 19, 2020 at 15:51

Quang Hoang · Accepted Answer · 2020-05-19 15:37:15Z

2

Do you mean:

[input_arr[x:y] for x,y in zip(index_arr1, index_arr2)]

Output:

[array([3, 4, 4]), array([4, 4]), array([4, 5])]

Or if you really want list of lists:

[[input_arr[x:y].tolist() for x,y in zip(index_arr1, index_arr2)]

Output:

[[3, 4, 4], [4, 4], [4, 5]]

answered May 19, 2020 at 15:37

Quang Hoang

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2 Comments

Ritvik Vij Over a year ago

Thanks for this, I was looking for some 'numpy magic' but I think list comprehensions are faster than for loops as well.

Quang Hoang Over a year ago

Numpy magic would be hard since your output is unlikely a n-D array. I'd be interested in such a solution also.

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