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Python random.expovariate() Method

The random.expovariate() method in Python generates random numbers that follows the Exponential distribution. The exponential distribution is a continuous probability distribution commonly used to model the time between events in a Poisson process. It is characterized by a parameter lambda, which is the rate parameter.

The parameter lambda is 1.0 divided by the desired mean of the distribution. If lambda is positive, the function returns values from 0 to positive infinity, representing times between events. If lambda were negative, it would return values from negative infinity to 0.

Following is the syntax of the expovariate() method −

random.expovariate(lambda)

This method accepts a single parameter −

• lambda: This is the rate parameter of the exponential distribution.

This method returns random numbers that follows the exponential distribution with the specified rate.

Let's see a basic example of using the random.expovariate() method for generating a single random number.

import random

# Lambda for the Exponential distribution
lambda_ = 2

# Generate a random number from the Exponential distribution
random_value = random.expovariate(lambda_)

print("Random value from Exponential distribution:", random_value)

Following is the output −

Random value from Exponential distribution: 0.895003194051671

Note: The Output generated will vary each time you run the program due to its random nature.

This example generates 10 interval times with an average rate of 15 arrivals per second using the random.expovariate() method.

import random

# Lambda for the Exponential distribution
rate = 15  # 15 arrivals per second

# Generate a random numbers from the Exponential distribution
for i in range(10):
    interarrival_time = random.expovariate(rate)
    print(interarrival_time)

While executing the above code you will get the similar output like below −

0.05535939722671001
0.0365294773838789
0.0708190008748821
0.11920422853122664
0.014966394641357258
0.05936796131161308
0.09168815851495513
0.18426575850779056
0.03533591768827803
0.08367815594819812

Here is another example that uses the random.expovariate() method to generate and display a histogram showing the frequency distribution of the integer parts of samples from an exponential distribution with a rate parameter of 100.

import random
import numpy as np
import matplotlib.pyplot as plt

# Generate 10000 samples from an exponential distribution with rate parameter of 100
rate = 1 / 100  
num_samples = 10000 

# Generate exponential data and convert to integers
d = [int(random.expovariate(rate)) for _ in range(num_samples)]

# Create a histogram of the data with bins from 0 to the maximum value in d
h, b = np.histogram(d, bins=np.arange(0, max(d)+1))

# Plot the histogram
plt.bar(b[:-1], h, width=1, edgecolor='none')
plt.title('Histogram of Integer Parts of Exponentially Distributed Data')
plt.show()

The output of the above code is as follows −

python_modules.htm

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