Random Num Gen¶

https://user-images.githubusercontent.com/14288520/189126776-794ea0fb-f6c1-4ec0-9965-cdd5009d3fe7.png

Functionality¶

Produces a list of pseudo-random numbers from a seed value.

Inputs & Parameters¶

Parameters	Description
Int / Float	Number type to be created
Size	Amount of numbers you want to create
Seed	Accepts float values, they are hashed into Integers internally.
Int/Float Low	Lower limit of values (included)*
Int/Float High	Higher limit of values (included)*
Weights	On “Int” mode. Can be supplied to create a non-uniform distribution
Unique	On “Int” mode. Outputs non-repeated numbers. The output size will be limited to (Int High - Int Low + 1)
Distribution	On “Float” mode many distribution functions can be selected. Beta, Binomial, Chi_square, Exponential, F Distrib., Gamma, Geometric, Gumbel, Laplace, Logistic, Log Normal, Log Series, Negative Binomial, Noncentered Chi-Square, Normal, Pareto, Poisson, Power, RayLeigh, Standard Cauchy, Standard Gamma, Standard T, Triangular, Uniform, Vonmises, Wald, Weibull, Zipf
Alpha	Distribution parameter. Alpha > 0**
Beta	Secondary distribution parameter. Beta > 0**
t	Normalized distribution parameter. 0 < t < 1

What’s a Seed? Read the Python docs here.

Learn more about the distribution functions on the SciPy random reference.

Outputs¶

A list, or nested lists.

Notes¶

Providing a float values as a Seed parameter may be unconventional, if you are uncomfortable with it you could place a FloatToInt node before the Seed parameter.

(*) Notes on Float Low and Float High

Except on some distributions (Uniform, Beta and Triangular) the output values are mapped to fit the desired range. Due this mapping there will be at least one value which matches the “Float High” and another that matches the “Float Low”

(**)Notes on Alpha and Beta values

On the “F Distribution” the minimum “Beta” is 0.025
On the “Pareto” distribution the minimum valid “Alpha” is 0.01
On the “Standard T” distribution the minimum valid “Alpha” is 0.017
On the “Triangular” distribution the “Alpha” parameter has to be greater than the “Float Low” and smaller than the “Float High”.
On the “Weibull the minimum valid “Alpha” is 0.0028.
On the “Zipf” distribution the minimum valid “Alpha” has to be bigger than 1.0