CODEWITHSUNDEEP
pythonnumpy
Alexander Soare
Alexander Soare

Reputation: 3257

How to slice numpy array with rows of varying length

I have a numpy array arr of numpy arrays each with varying length. I can get the shape of arr:

arr.shape

>>> (9,)

I can get the shape of one of the elements of arr:

arr[0].shape

>>> (6, 1, 2)

And I know that all such elements have shape (n, 1, 2).

I want to slice arr to get a 1 dimensional result as follows:

arr[:,:,:,0]

But I get the following error:

IndexError: too many indices for array

EDIT: My original question was misleading. I want to do this slice so that I can assign values to the slice. So getting the slice in a new variable is not useful for my case. Essentially I want to do something like this in a simple one liner:

arr[:,:,:,0] = arr[:,:,:,0] - np.min(arr[:,:,:,0])

Upvotes: 1

Views: 392

Answers (2)

Georgina Skibinski
Georgina Skibinski

Reputation: 13387

You can fix your first (in fact all varying ones) dimension, and apply your transformation per static-shaped elements of arr

import numpy as np
from random import randint

arr=np.array([np.random.randint(3,15, size=(randint(3,9),randint(3,7),randint(6,19))) for el in range(9)])

print(arr.shape)
print(arr[0].shape)
for i in range(arr.shape[0]):
    arr[i][:,:,0]-=arr[i][:,:,0].min()
    print(arr[i][:,:,0])

Upvotes: 1

Mihai Alexandru-Ionut
Mihai Alexandru-Ionut

Reputation: 48367

You could use list comprehension version of your solution.

desired_result = np.array([el[:,:,0] for el in arr])

Upvotes: 1

Related Questions