HomemadeRandom 0.1.5

A random number generator built from scratch for ISYE6644 class project

Random Variate Generator

This package provides access to a few frequently used discrete and continuous distributions.

Installation

Normal Installation

pip install HomemadeRandom

API Details and Examples

Start using the library by running
from HomemadeRandom import Random

Initialize a HomemadeRandom object with two parameters: type of base random number generator and a seed.
Select a base random number generator from the following:

1. "desert" - desert island. A good LCG (linear congruential generator).
   • The seed must be between 1 and 2147483646 (inclusive)
2. "randu" - bad LCG
   • The seed must be between 1 and 2147483647 (inclusive)

Example:
random_object = Random('desert', seed=10)

Discrete Distributions

1. Bernoulli
   HomemadeRandom.bernoulli(p=0.5)
   Parameter: (optional) p: floats. 0 <= p <= 1. Probability of a success event

2. Binomial
   HomemadeRandom.binomial(n, p)
   Parameter: n: int. n > 0. Total number of trials
   Parameter: p: floats. 0 <= p <= 1. Probability of a success event

3. Geometric
   HomemadeRandom.geometric(p, mode=0)
   Parameter: p: floats. 0 <= p <= 1. Probability of a success event
   Parameter: (optional) mode: int. Mode 0 is the fast and direct way. Any other mode will use the other implementation, which was implemented for academic purpose.

4. Poisson
   HomemadeRandom.poisson(lmbda)
   Parameter: lmbda: floats. lmbda >= 0. Number of arrivals in one time unit

Continuous Distributions

1. Uniform
   HomemadeRandom.uniform(a=0, b=1)
   Parameter: (optional) a: floats. lower bound of uniform distribution, inclusive
   Parameter: (optional) b: floats. upper bound of uniform distribution, exclusive

2. Exponential
   HomemadeRandom.exponential(lmbda)
   Parameter: lmbda: mean time between events

3. Normal
   HomemadeRandom.normal(mu=0, sigma=1.0)
   Parameter: (optional) mu: floats. mean of a normal distribution Parameter: (optional) sigma: floats. standard deviation of a normal distribution

4. Gamma
   HomemadeRandom.gamma(alpha, beta)
   Parameter: alpha: floats. shape parameter
   Parameter: beta: floats. rate parameter

5. Weibull
   HomemadeRandom.weibull(alpha, beta)
   Parameter: alpha: floats. shape parameter
   Parameter: beta: floats. scale parameter

6. Triangular
   HomemadeRandom.triangular(low=0.0, high=1.0, mode=None)
   Parameter: low: floats. lower limit
   Parameter: high: floats. upper limit
   Parameter: mode: floats. number with highest probability where a <= c <= b

See tests/test.py for actual usage

[0.0.1] - 2020-11-30