NumPy: Split array into multiple sub-arrays along the 3rd axis

Last update on March 24 2025 13:39:00 (UTC/GMT +8 hours)

Split Array Along 3rd Axis

Write a NumPy program to split an array into multiple sub-arrays along the 3rd axis.

Sample Solution:

Python Code:

# Importing the NumPy library and aliasing it as 'np'
import numpy as np

# Printing a message indicating the original array will be displayed
print("\nOriginal arrays:")

# Creating a NumPy array 'x' with elements from 0 to 15 and reshaping it into a 3-dimensional array of shape (2, 2, 4)
x = np.arange(16.0).reshape(2, 2, 4)

# Displaying the original 3D array 'x'
print(x)

# Splitting the 3D array 'x' into two sub-arrays along the third axis using np.dsplit()
new_array1 = np.dsplit(x, 2)

# Printing a message indicating the splitting of the array along the 3rd axis and displaying the resulting sub-arrays
print("\nsplit array into multiple sub-arrays along the 3rd axis:")
print(new_array1) 

Sample Output:

Original arrays:
[[[ 0.  1.  2.  3.]
  [ 4.  5.  6.  7.]]

 [[ 8.  9. 10. 11.]
  [12. 13. 14. 15.]]]

split array into multiple sub-arrays along the 3rd axis:
[array([[[ 0.,  1.],
        [ 4.,  5.]],

       [[ 8.,  9.],
        [12., 13.]]]), array([[[ 2.,  3.],
        [ 6.,  7.]],

       [[10., 11.],
        [14., 15.]]])]

Explanation:

In the above code –

x = np.arange(16.0).reshape(2, 2, 4): It creates a 3-dimensional NumPy array x of shape (2, 2, 4) with elements from 0.0 to 15.0.

new_array1 = np.dsplit(x, 2): This line splits the 3-dimensional array x into two equal parts depth-wise (along the third axis). The result is a list of two 3-dimensional arrays, each of shape (2, 2, 2):

Pictorial Presentation:

For more Practice: Solve these Related Problems:

• Write a NumPy program to split a 3D array into multiple sub-arrays along the third axis using np.split.
• Create a function that partitions a 3D array into two parts along the last axis and verifies the shapes.
• Test the split operation on a 3D array and ensure that each resulting sub-array retains the original depth.
• Implement a solution that uses np.array_split to handle cases where the split is uneven.

Python-Numpy Code Editor: