gdstats

gdstats: Advanced Statistical Distributions for Godot

gdstats is a valuable addition to any Godot project requiring nuanced random number generation. This library provides a suite of pseudorandom number generators, each designed to simulate common statistical distributions. Whether you're modeling game mechanics, simulating environmental effects, or creating procedural content, gdstats offers the tools you need.

Discrete Distributions

The library includes several discrete distributions, useful for generating integer-based random numbers:

• randi_bernoulli(p): Simulates a Bernoulli trial, returning 1 or 0 based on the probability p.
• randi_binomial(p, n): Returns the number of successes in n Bernoulli trials, each with probability p.
• randi_geometric(p): Returns the number of trials needed to achieve the first success in a series of Bernoulli trials with probability p.
• randi_poisson(lambda): Approximates a Poisson distribution, modeling the number of events occurring in a fixed interval of time or space.
• randv_histogram(values, probabilities): Generates a random value from a custom distribution defined by a list of values and their corresponding probabilities.
• randi_pseudo(c): Mimics the Warcraft3/Dota style of "fair" number generators, increasing the probability of an event occurring after each failure.

Continuous Distributions

For generating floating-point random numbers, gdstats provides the following continuous distributions:

• randf_uniform(a, b): Returns a uniformly distributed random number between a and b.
• randf_exponential(lambda): Simulates an exponential distribution, modeling the time between events in a Poisson process.
• randf_erlang(k, lambda): Represents the sum of k exponential distributions, often used to model the time until k events occur in a Poisson process.
• randf_gaussian()/randf_normal(): Generates random numbers from a normal (Gaussian) distribution.

gdstats aims to provide fast and efficient implementations of these distributions, making it a practical choice for game developers seeking realistic and varied random number generation.