Compute the Frobenius norm of a 3x3 random array using NumPy

NumPy: Advanced Exercise-24 with Solution

Write a NumPy program to create a 3x3 array with random values and compute the Frobenius norm of the matrix.

Sample Solution:

Python Code:

# Importing the necessary NumPy library
import numpy as np

# Create a 3x3 array with random values
array = np.random.rand(3, 3)

# Compute the Frobenius norm of the matrix
frobenius_norm = np.linalg.norm(array, 'fro')

# Printing the original array and its Frobenius norm
print("3x3 Array:\n", array)
print("Frobenius Norm of the array:\n", frobenius_norm)

Output:

3x3 Array:
 [[0.25748026 0.5277958  0.43826955]
 [0.01836537 0.417873   0.87132102]
 [0.92522201 0.07203685 0.14956437]]
Frobenius Norm of the array:
 1.5345014516959405

Explanation:

• Import NumPy library: This step imports the NumPy library, which is essential for numerical operations.
• Create a 3x3 array: We use np.random.rand(3, 3) to generate a 3x3 matrix with random values between 0 and 1.
• Compute the Frobenius norm of the matrix: The np.linalg.norm function with the 'fro' argument calculates the Frobenius norm of the matrix, which is the square root of the sum of the absolute squares of its elements.
• Print results: This step prints the original 3x3 array and its Frobenius norm.

Python-Numpy Code Editor:

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