artificial-life op• Data kinds: image → image
• Call: fullseye.apply(img, "alife_dla", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*
Deterministic diffusion-limited-aggregation (DLA) growth proxy.
Witten-Sander DLA grows a cluster by releasing random walkers that stick on
contact; the walker density obeys a Laplace equation, so this op replaces the
random walkers by their *deterministic* mean field: the unclaimed image
brightness is diffused with a Gaussian Green's function to give a
concentration u, and each generation the cluster's Moore boundary attaches
exactly those cells whose concentration clears a stickiness threshold
(with the single strongest boundary cell always attaching, so growth never
stalls). Bright pixels (>= 0.75 of the image maximum, or the single brightest
pixel) are the seed. `a` sets the number of growth generations
1 + int(11a), `b` the stickiness: high b selects only the highest-
concentration tips (dendritic, screened growth), low b attaches nearly the
whole boundary (compact, Eden-like growth). Returns the 0/1 cluster.
• gallery2d_physics_alife_3d family guide
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.
alife_dla 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_physics_alife_3d — py -3.11 examples/gallery2d_physics_alife_3d.py
• sim2real_and_alife — py -3.11 examples/sim2real_and_alife.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
artificial-life)alife_gray_scott · alife_turing · alife_life_step · alife_cyclic_ca · alife_perona_malik · alife_curvature_flow · alife_reaction_bz · alife_wolfram1d
*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.