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Algorithmic Art

We want to generate probabilistic artwork, efficiently. We are going to use random variables to make a picture filled with non-overlapping circles:

Regenerate

In our art, the circles are different sizes. Specifically, each circle's radius is drawn from a Pareto distribution (which is described below). The placement algorithm is greedy: we sample 1000 circle sizes. Sort them by size, largest to smallest. Loop over the circle sizes and place circles one by one.

To place a circle on the canvas, we sample the location of the center of the circle. Both the x and y coordinates are uniformly distributed over the dimensions of the canvas. Once we have selected a prospective location we then check if there would be a collision with a circle that has already been placed. If there is a collision we keep trying new locations until you find one that has no collisions.

The Pareto Distribution

Pareto Random Variable

Notation: $X \sim \text{Pareto}(a)$
Description: A long tail distribution. Large values are rare and small values are common.
Parameters: $a \ge 1$, the shape parameter
Note there are other optional params. See wikipedia
Support: $x \in [0, 1]$
PDF equation: $$f(x) = \frac{1}{x^{a+1}}$$
CDF equation: $$F(x) = 1- \frac{1}{x^a}$$

Sampling from a Pareto Distribution

How can we draw samples from a pareto? In python its simple: stats.pareto.rvs(a) however in JavaScript, or other languages, it might not be made transparent. We can use "inverse transform sampling". The simple idea is to choose a uniform random variable in the range (0, 1) and then select the value $x$ assignment such that $F(x)$ equals the randomly chosen value.

\begin{aligned} y &= 1 - (\frac{1}{x})^\alpha \\ (\frac{1}{x})^\alpha &= 1 - y \\ \frac{1}{x} &= (1-y)^{\frac{1}{\alpha}} \\ x &= \frac{1}{(1-y)^{\frac{1}{\alpha}}} \end{aligned}