memlnaut-nisps/playground/js/nisps
w1n5t0n 44fc974425 feat(tests): add Playwright e2e suite + debug probe for a-immersive
- Add window.__nisps debug probe (gated on ?debug=1) exposing iml state,
  getOutputs/getLoss/getWeights/getExampleCount, and action triggers
  (thumbsUp/thumbsDown/train/randomise/clearExamples/saveState)
- Fix WasmIML bug: this.dataset was a plain object; import Dataset and
  use new Dataset(100) so computeWeights() is available for training
- Fix WasmIML.addExample/clearDataset to use Dataset API methods
- 44 Playwright e2e tests across 4 spec files:
  - ml-engine.spec.js: WASM inference bounds, training loss, thumbs
    up/down behavior, async training, example capture semantics
  - ui-interactions.spec.js: drawer open/close, mode switching,
    heatmap bar counts, preset chips, keyboard shortcuts (1/2/Z)
  - input-pipeline.spec.js: input→output variation, clamping, joystick
    drag, post-training output bounds across the full input space
  - persistence.spec.js: URL params (?preset, ?spread), localStorage
    round-trip, saveState probe
2026-04-03 16:38:04 +01:00
..
dataset.js feat(playground/nisps): recency & spatial weighted training in JS ML engine 2026-04-02 20:35:31 +01:00
iml.js feat(playground/nisps): recency & spatial weighted training in JS ML engine 2026-04-02 20:35:31 +01:00
layer.js feat(vcv,playground): complete Phases 8, 9, 10 — all phases done 2026-03-28 01:48:44 +02:00
mlp.js feat(playground/nisps): recency & spatial weighted training in JS ML engine 2026-04-02 20:35:31 +01:00
nisps-wasm-worker.js feat(playground/nisps): recency & spatial weighted training in JS ML engine 2026-04-02 20:35:31 +01:00
nisps-wasm.js feat(tests): add Playwright e2e suite + debug probe for a-immersive 2026-04-03 16:38:04 +01:00
node.js feat: add web-based interactive playground for NISPS 2026-02-11 13:17:17 +01:00
osc-client.js feat(vcv,playground): complete Phases 8, 9, 10 — all phases done 2026-03-28 01:48:44 +02:00