perpetual op• Data kinds: none → rgb (an op determined by its arguments alone — it takes no image or data input)
• Call: import fullseye as fs; fs.ledger.perpetual_flow_field(size: 'int' = 520, seed: 'int' = 0, lines: 'int' = 420, steps: 'int' = 150, scale: 'float' = 0.01) -> 'np.ndarray' (to call the implementation directly, import perpetual; perpetual.perpetual_flow_field(size: 'int' = 520, seed: 'int' = 0, lines: 'int' = 420, steps: 'int' = 150, scale: 'float' = 0.01) -> 'np.ndarray'; from the registry, opsgenerative.get("perpetual_flow_field"))
Flow field — keeps advecting particles along the field (it does not end unless stopped).
★The field is built as the curl of a potential ψ. Hence the divergence is identically 0 (incompressible), and particles neither appear nor vanish. This is the difference from a flow field built from "plausible noise",
and perpetual_identities reports it as a number.
★Line colour and width are tied to the flow speed |∇ψ| (if width and darkness were both constant, drawing from the same field would give nothing but "scribbles").
• 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.
• poc_illusions_and_perpetual_drawing — py -3.11 examples/poc_illusions_and_perpetual_drawing.py
rgb as input)—
perpetual)perpetual_ten_print · perpetual_truchet · perpetual_elementary_ca · perpetual_langtons_ant · perpetual_chaos_game · perpetual_apollonian · perpetual_harmonograph · perpetual_ifs_attractor
*Provenance: perpetual.py — GENERATIVE 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.