The signal-flow model makes interconnection primary, unlike the canvas-drawing model of Processing

Generative-graphics tools rest on different mental models. The canvas/drawing model (Processing, p5.js) comes from graphic design: you have a canvas, choose a paint colour, draw a shape, and loop to repeat. The signal-flow model (Hydra, analog video synthesizers) treats the image as a signal passing through transforming stages, so interconnecting and reordering stages — not issuing sequential draw commands — is the primary act. Choosing a model shapes what feels easy: the canvas model favours placing discrete shapes; the signal model favours experimenting with how transforms compose and route into each other. Jack traces this to Daniel Sandin’s 1971 design aim to ‘maximise the possibility of interconnection.‘

Examples

Processing: fill(255,0,0); ellipse(50,50,40,40) — imperative canvas-paint. Hydra: osc(4).color(1,0,0).rotate(0.5).out() — a routed chain of signal transforms whose ordering is the composition.

Assessment

Given a visual effect (e.g. a spinning gradient circle that warps over time), sketch how you would approach it in the canvas model vs the signal-flow model, and name which operations change.