NumPy: Normalize a 3x3 random matrix

NumPy: Random Exercise-7 with Solution

Write a NumPy program to normalize a 3x3 random matrix.

Sample Solution:

Python Code :

# Importing the NumPy library as np
import numpy as np

# Generating a 3x3 array of random numbers between 0 and 1 using np.random.random()
x = np.random.random((3, 3))

# Printing the original array 'x'
print("Original Array:")
print(x)

# Finding the maximum and minimum values in array 'x' using x.max() and x.min()
xmax, xmin = x.max(), x.min()

# Normalizing the array 'x' using min-max scaling: (x - xmin) / (xmax - xmin)
x = (x - xmin) / (xmax - xmin)

# Printing the array 'x' after normalization
print("After normalization:")
print(x) 

Sample Output:

Original Array:                                                        
[[ 0.89372503  0.99865458  0.77120044]                                 
 [ 0.67632984  0.99990084  0.64110391]                                 
 [ 0.34845794  0.66557903  0.29031742]]                                
After normalization:                                                   
[[ 0.85036881  0.99824367  0.67769765]                                 
 [ 0.54399864  1.          0.49435553]                                 
 [ 0.08193614  0.52884777  0.        ]]

Explanation:

x = np.random.random((3,3)): This line creates a 3x3 array x with random numbers between 0 and 1 using the np.random.random() function. The input tuple (3,3) specifies the output array shape.

xmax, xmin = x.max(), x.min(): This line finds the maximum and minimum values in the array x using the x.max() and x.min() methods, respectively. These values are stored in the variables xmax and xmin.

x = (x - xmin)/(xmax - xmin): This line normalizes the array x by rescaling its elements to the range [0, 1]. This is done by subtracting the minimum value xmin from all elements in the array and then dividing the result by the range (xmax - xmin). The normalized values are stored back into array x.

print(x): Finally print() function prints the normalized 3x3 array x.

Pictorial Presentation:

Python-Numpy Code Editor:

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