Slicing every second row and column of a 3d numpy array, making a new array

Question

I have a NumPy array of dimension 698x64x64 (64rows, 64columns)

I would like to slice it into a new array of 698x32x32 by taking every second row and column of the original array. How do I do that?

Asked By: Tan Jian Sean

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Source

Answer 1

IIUC, You can use slicing like below. (You can read this : understanding-slicing)

import numpy as np
np.random.seed(123)
# this array is a sample array for showing result
a = np.random.rand(2,4,4)
print(a)

b = a[:, 1::2, 1::2] # <- you can use this for (698, 64, 64)
print(b)

Output:

# a =>
array([[[0.69646919, 0.28613933, 0.22685145, 0.55131477],
        [0.71946897, 0.42310646, 0.9807642 , 0.68482974],
# -------------------^^^^^^^^^^,-----------, ^^^^^^^^^^ <- you want this
        [0.4809319 , 0.39211752, 0.34317802, 0.72904971],
        [0.43857224, 0.0596779 , 0.39804426, 0.73799541]],
# -------------------^^^^^^^^^^,-----------, ^^^^^^^^^^ <- you want this

       [[0.18249173, 0.17545176, 0.53155137, 0.53182759],
        [0.63440096, 0.84943179, 0.72445532, 0.61102351],
# -------------------^^^^^^^^^^,-----------, ^^^^^^^^^^ <- you want this

        [0.72244338, 0.32295891, 0.36178866, 0.22826323],
        [0.29371405, 0.63097612, 0.09210494, 0.43370117]]])
# -------------------^^^^^^^^^^,-----------,, ^^^^^^^^^^ <- you want this


# b =>
array([[[0.42310646, 0.68482974],
        [0.0596779 , 0.73799541]],

       [[0.84943179, 0.61102351],
        [0.63097612, 0.43370117]]])

Answered By: I'mahdi

Slicing every second row and column of a 3d numpy array, making a new array

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