Introduction to Python Uniform Distribution
Python Uniform Distribution
The uniform distribution, also known as the rectangular distribution, is a continuous probability distribution where all values within a given range are equally likely to occur.
In other words, the probability density function (PDF) of a uniform distribution is constant over a defined interval and zero outside that interval.
The probability density function of a uniform distribution is given by:
f(x) = 1 / (b - a)
Where 'a' and 'b' are the lower and upper bounds of the interval, respectively.
In Python, you can generate random numbers from a uniform distribution using the numpy.random.uniform()
function from the NumPy library.
As an example:
import numpy as np
# Generate random numbers from a uniform distribution
a = 0 # Lower bound
b = 10 # Upper bound
size = 1000 # Number of random numbers to generate
random_numbers = np.random.uniform(a, b, size)
In this example:
np.random.uniform(a, b, size)
generates an array of 1000 random numbers from a uniform distribution between 0 (inclusive) and 10 (exclusive).- You can adjust the values of 'a' and 'b' to define the desired interval for the distribution.
- The resulting array
random_numbers
will contain the generated random numbers.