NumPy: Create random vector of size 15 and replace the maximum value by -1
Write a NumPy program to create random vector of size 15 and replace the maximum value by -1.
Sample Solution:
Python Code :
# Importing the NumPy library as np
import numpy as np
# Generating an array 'x' with 15 random floats between 0 and 1 using np.random.random()
x = np.random.random(15)
# Displaying the original array 'x'
print("Original array:")
print(x)
# Finding the index of the maximum value in the array using x.argmax()
# Replacing the maximum value with -1 using the index obtained from x.argmax()
x[x.argmax()] = -1
# Displaying the modified array where the maximum value has been replaced by -1
print("Maximum value replaced by -1:")
print(x)
Sample Output:
Original array: [ 0.04921181 0.83545304 0.4394982 0.81889845 0.8022234 0.46176053 0.95785815 0.86968759 0.35100099 0.00107607 0.4330148 0.56632168 0.57764716 0.09226267 0.01710047] Maximum value replaced by -1: [ 0.04921181 0.83545304 0.4394982 0.81889845 0.8022234 0.46176053 -1. 0.86968759 0.35100099 0.00107607 0.4330148 0.56632168 0.57764716 0.09226267 0.01710047]
Explanation:
In the above exercise –
x = np.random.random(15): This line creates a 1D array x with 15 random floating-point values between 0 and 1 using the np.random.random() function.
x[x.argmax()] = -1: This line first finds the index of the maximum value in the array x using the argmax() method. Then, it replaces the maximum value in the array with -1 using array indexing.
print(x): This line prints the modified array x with the maximum value replaced by -1.
When you run the code, you'll get an output similar to this (note that the actual output will vary since the array is generated randomly):
Original array:
[ 0.04921181 0.83545304 0.4394982 0.81889845 0.8022234 0.46176053
0.95785815 0.86968759 0.35100099 0.00107607 0.4330148 0.56632168
0.57764716 0.09226267 0.01710047]
Maximum value replaced by -1:
[ 0.04921181 0.83545304 0.4394982 0.81889845 0.8022234 0.46176053
-1. 0.86968759 0.35100099 0.00107607 0.4330148 0.56632168
0.57764716 0.09226267 0.01710047]
The output shows the modified array x with the maximum value replaced by -1.
Pictorial Presentation:
Python-Numpy Code Editor:
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