You can read this paper for introduction:
Paul Bourke - Random space filling of the plane (2011).
However, provided search algorithm for the next location is inefficient,
and offers very limited control over the distribution.
In this work, i present a new solver over discrete signed distance field:
Where sdfn are custom signed distance functions. Aggregate minima of which is stored in a bitmap.
cn+1 marks a point with highest value of the field, which then supplied to the next iteration
of the algorithm.
Currently, the solver is fully parallel, and highly generic. Supported:
- Regular (fractal) distributions
- Random distributions
- Any shapes which can be represented with SDF: curves, regular polygons, non-convex polygons, disjoint areas
- Mixed shapes.
Examples
You can run examples with following command:
cargo run --release --features "drawing" --example <example name> -- -C target-cpu=native
examples/fractal_distribution
Each subsequent circle is inserted at the maxima of distance field.
examples/random_distribution
Given (xy, value) of the maxima, a new random circle is inserted within a domain of radius value and center xy.
examples/embedded
A regular distribution embedded in a random one.
- Insert a random distribution of circles;
- Invert the distance field;
- Insert a fractal distribution.
examples/polymorphic
Showcasing:
- Dynamic dispatch interface;
- Random distribution of mixed shapes;
- Random color and texture fill style;
- Parallel generation and drawing.
examples/image_dataset
Display over 100'000 images.
Run with cargo run --release --features "drawing" --example image_dataset -- "<image folder>" -C target-cpu=native
Past work
In src/legacy you can find numeruos algorithms which are worth re-exploring, including quadtree and GPU implementations.
Future work
- Add more sample SDFs, and generic draw trait
- Extend to discretization below 2-16 (gigapixel resolution)
Once above are done, I will use this library for my next project "Gallery of Babel".