NumPy: Create a function cube which cubes all the elements of an array

Last update on March 24 2025 13:39:26 (UTC/GMT +8 hours)

Apply Cube Function to All Elements

Write a NumPy program to create a function cube for all array elements.

Pictorial Presentation:

Sample Solution:

Python Code:

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

# Defining a function 'cube' that takes an input 'e'
def cube(e):
    # Creating an nditer object 'it' to iterate over 'e' along with an uninitialized 'None' array
    it = np.nditer([e, None])
    
    # Iterating through each element 'a' in 'e' and corresponding uninitialized element 'b'
    for a, b in it:
        # Setting 'b' to the cube of 'a' in each iteration
        b[...] = a * a * a
    
    # Returning the resulting array after cube operations from the operands of the iterator
    return it.operands[1]

# Calling the 'cube' function with a list [1, 2, 3] as an argument and printing the result
print(cube([1, 2, 3])) 

Sample Output:

[ 1  8 27]

Explanation:

In the above code -

• def cube(e):: Define a function called cube that takes a single argument e.
• it = np.nditer([e, None]): Create a NumPy iterator called it that iterates over the input array e and an uninitialized output array of the same shape as e. This is done by passing None as the second element in the list.
• for a, b in it:: Iterate over the elements of e and the uninitialized output array using the iterator it. a represents an element from e, and b represents the corresponding element in the output array.
• b[...] = a*a*a: Cube the value of a and assign it to the corresponding element b in the output array.
• return it.operands[1]: After the loop, return the output array, which is stored as the second operand in the iterator it.
• Finally ‘print(cube([1,2,3]))’ prints the result.