ph_reaction_diffusion — 2D physics op

• Data kinds: image → image

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

Usage

Gray-Scott reaction-diffusion (no HALCON operator, halcon="").

Two coupled species u,v obeying

u_t = Du*lap(u) - u v^2 + F(1-u)

v_t = Dv*lap(v) + u v^2 - (F+kappa) v

seeded from the input image. `a -> feed F, b` -> kill kappa (both mapped

into the classic pattern-forming regime). Produces spots/stripes/labyrinth

texture; u,v stay bounded so the returned (normalised v) is in [0,1].

Detailed usage guide

• gallery2d_physics_alife_3d family guide

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• gallery2d_physics_alife_3d — py -3.11 examples/gallery2d_physics_alife_3d.py

Ops the type connects to (they accept image as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (physics)

ph_perona_malik · ph_coherence_enhancing_diffusion · ph_heat_flow · ph_mean_curvature_motion · ph_total_variation_flow

*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.