Index the middle of a numpy array?

Question

To index the middle points of a numpy array, you can do this:

x = np.arange(10)
middle = x[len(x)/4:len(x)*3/4]

Is there a shorthand for indexing the middle of the array? e.g., the n or 2n elements closes to len(x)/2? Is there a nice n-dimensional version of this?

Solution 1

as cge said, the simplest way is by turning it into a lambda function, like so:

x = np.arange(10)
middle = lambda x: x[len(x)/4:len(x)*3/4]

or the n-dimensional way is:

middle = lambda x: x[[slice(np.floor(d/4.),np.ceil(3*d/4.)) for d in x.shape]]

Solution 2

Late, but for everyone else running into this issue: A much smoother way is to use numpy's take or put.

To address the middle of an array you can use put to index an n-dimensional array with a single index. Same for getting values from an array with take

Assuming your array has an odd number of elements, the middle of the array will be at half of it's size. By using an integer division (// instead of /) you won't get any problems here.

import numpy as np

arr = np.array([[0, 1, 2],
                [3, 4, 5],
                [6, 7, 8]])

# put a value to the center 
np.put(arr, arr.size // 2, 999)
print(arr)

# take a value from the center
center = np.take(arr, arr.size // 2)
print(center)

Comments

[cge]

It seems like just making this a function (eg, mid = lambda x: x[len(x)/4:len(x)*3/4]) would be the simplest solution.

[ali_m]

You can use slice objects for the n-dimensional case: mid = lambda x: x[[slice(np.floor(d/4.),np.ceil(3*d/4.)) for d in x.shape]]

[kabammi]

fast forward 4 years, and this now produces a warning "VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future".