Multiply 3D array by 1D array using NumPy Broadcasting

Last update on December 21 2024 07:37:02 (UTC/GMT +8 hours)

Write a NumPy program that multiplies a 3D array of shape (2, 3, 4) by a 1D array of shape (4,) using broadcasting.

Sample Solution:

Python Code:

# Import the NumPy library
import numpy as np

# Create a 3D array a with shape (2, 3, 4)
a = np.array([[[1, 2, 3, 4],
               [5, 6, 7, 8],
               [9, 10, 11, 12]],

              [[13, 14, 15, 16],
               [17, 18, 19, 20],
               [21, 22, 23, 24]]])

# Create a 1D array b with shape (4,)
b = np.array([2, 3, 4, 5])

# Multiply the 3D array a by the 1D array b using broadcasting
result = a * b

# Print the original arrays and the result
print("3D Array a:\n", a)
print("1D Array b:\n", b)
print("Result of a * b:\n", result)

Output:

3D Array a:
 [[[ 1  2  3  4]
  [ 5  6  7  8]
  [ 9 10 11 12]]

 [[13 14 15 16]
  [17 18 19 20]
  [21 22 23 24]]]
1D Array b:
 [2 3 4 5]
Result of a * b:
 [[[  2   6  12  20]
  [ 10  18  28  40]
  [ 18  30  44  60]]

 [[ 26  42  60  80]
  [ 34  54  76 100]
  [ 42  66  92 120]]]

Explanation:

• Import the NumPy library: This step imports the NumPy library, essential for numerical operations.
• Create a 3D array a: We use np.array to create a 3D array a with shape (2, 3, 4) and the given elements.
• Create a 1D array b: We use np.array to create a 1D array b with shape (4,) and elements [2, 3, 4, 5].
• Multiply the 3D array a by the 1D array b using broadcasting: NumPy automatically adjusts the shape of b to match the last dimension of a and performs element-wise multiplication.
• Print the original arrays and the result: This step prints the original 3D array a, the 1D array b, and the result of the multiplication.

Python-Numpy Code Editor: