/**
 * The brain's force layout, off the render thread.
 *
 * Run to rest in one go, it took several frames on the main thread: about
 * 75 ms on a page's first layout and 30 ms after for the Demo's 29 neurons,
 * and 250 ms at five times that. Answers with where each neuron settled, in
 * the order they came.
 *
 * `forceX`/`forceY` rather than `forceCenter`: centering only translates the
 * whole thing, so unconnected flows — which is most of them — would push each
 * other apart forever with nothing pulling back.
 */
import {
  forceCollide,
  forceLink,
  forceManyBody,
  forceSimulation,
  forceX,
  forceY,
  type SimulationNodeDatum,
} from "d3-force"

export type Seed = SimulationNodeDatum & { id: string; room: number }

export type LayoutRequest = {
  placed: Seed[]
  links: { source: string; target: string }[]
}

self.onmessage = ({ data }: MessageEvent<LayoutRequest>) => {
  const { placed, links } = data
  forceSimulation(placed)
    .force(
      "link",
      forceLink(links)
        .id((node) => (node as Seed).id)
        .distance(130),
    )
    .force("charge", forceManyBody().strength(-320).distanceMax(500))
    .force(
      "collide",
      forceCollide<Seed>((node) => node.room),
    )
    // Centring pulls nearly three times as hard vertically as horizontally, so
    // the graph compresses into a band roughly twice as wide as it is tall
    // instead of the square an even pull settles into. Coming out of the
    // simulation rather than out of a transform keeps the circles round and the
    // edges the length the link force asked for.
    .force("x", forceX(0).strength(0.05))
    .force("y", forceY(0).strength(0.14))
    .stop()
    .tick(300)
  self.postMessage(placed.map((node) => [node.x ?? 0, node.y ?? 0]))
}