Poisson Disc Point Generator
Scattering points uniformly gives clumps and gaps — that is what uniform means. When you want points that look evenly spread, what you actually want is a minimum separation, and Poisson-disc sampling is how to get one without rejection sampling grinding to a halt as the space fills. Every set here is measured after the fact: the closest pair is reported next to the same figure for a uniform scatter of the same size.
What this generator does
Places points across a hundred-unit square such that no two are closer than the spacing you set. The count is not a control — it is however many fit — and the closest pair actually produced is reported so the promise can be checked.
How to use this tool
- Choose the minimum spacing you want between points.
- Generate, and read how many points fitted at that spacing.
- Compare the closest pair against the uniform figure shown.
- Copy the coordinates, or seed the set to reproduce it.
Understanding the controls
- Minimum spacing
- From 4 to 40 units across a hundred-unit field. Smaller spacing fits many more points; the relationship is roughly inverse-square.
- Seed
- Any word reproduces exactly the same point set, which matters when the layout is being used as a fixture.
Common use cases
- Placing markers, trees or objects so they never overlap
- Sampling that looks even to the eye rather than merely being unbiased
- Test coordinates with a guaranteed separation
- Showing why uniform scatter looks clumpy
- Reproducing the same layout from a seed
How this generator works
Bridson's algorithm keeps a list of active points, throws candidates into the ring between one and two radii from a randomly chosen active point, and accepts the first that clears every neighbour. A background grid of cells sized to the radius means only nearby cells need checking, which is what keeps it linear. The check then measures every pair.
Randomness and fairness
The point positions are random; the minimum separation is guaranteed by the algorithm and verified afterwards. Seeded sets reproduce exactly and are therefore explicitly not cryptographically secure. Without a seed the browser's cryptographically secure generator places the points.
For how randomness is produced across the whole site, see how Generate Random works.
Limitations and good to know
- You choose the spacing, not the count — asking for a specific number of points is a different problem.
- The field is a fixed hundred-unit square with no units attached.
- Only two dimensions; the same algorithm generalises but this does not.
- Points are not clipped to a shape other than the square.
- Point sets vanish on leaving; seed a layout you intend to reuse as a fixture.
Privacy and your data
Points are placed and measured entirely in your browser. No coordinates or seed are transmitted or kept.
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