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.

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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Slicing Numpy Array by 2 index arrays

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Slicing Numpy Array by 2 index arrays

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