Generation lab

Run the benchmark's deterministic planner — algorithm A, the same code the benchmark used — in your browser. Pick a typology, a brief variant and a set of priorities; the planner sizes the envelope, enumerates its partis, refines the proportions and returns the design that scores best under your priorities.

A demo, not results. Designs made here are never mixed into the benchmark tables. The first load fetches a Python runtime with numpy and scipy (tens of megabytes) from a CDN; after that each run takes a few seconds to a minute depending on the budget.