w1n5t0n/memlnaut-nisps
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Author SHA1 Message Date
w1n5t0n
aa0ffcfd32 feat(playground/nisps): recency & spatial weighted training in JS ML engine 
Add Dataset.computeWeights() with three modes:
- global: exponential recency decay (newest examples weighted higher)
- local: spatial suppression of older examples near the current input
- combined: both applied together

IML and WasmIML now compute weights on every train() call using the
active mode. Exposes recencyBias, weightingMode, localRadius properties.
WASM worker path passes sampleWeights through to C++ via the new binding.
 2026-04-02 20:35:31 +01:00
w1n5t0n
1f21494dee feat(playground): implement Phases 2-4 of control surface spec 
Phase 2 — Pinning + History:
- snapshot-stack.js: ring buffer (20 max) with auto-snapshot on
  train/randomize/thumbs-down, multi-level undo, tagged entries
- ab-compare.js: A/B weight state comparison with capture/toggle/accept/revert
- region-pin.js: pin rectangular input-space regions (Approach A: example
  pinning), pinned examples always included in training
- param-pin.js: per-output pin flags, pin mask skips pinned nodes in moveWeights
- phase2-ui.js: undo button with history popup, A/B toggle, long-press region
  pin, double-tap param pin
- Modified mlp.js/iml.js/nisps-wasm.js to accept outputPinMask in moveWeights

Phase 3 — Input Refinement + Exploration:
- pressure-feedback.js: touch force + hold duration → intensity multiplier
- auto-explore.js: automated thumbs-down at configurable interval, zoom-scaled
- input-heatmap.js: 16×16 MLP sampling, 3 color modes (luminance/variance/
  divergence), zoom-aware resampling, offscreen canvas rendering
- phase3-ui.js: auto-explore toggle with progress ring, heatmap eye icon,
  pressure indicators, settings drawer section
- joy-map-enhanced.js: added setHeatmap() for background layer rendering

Phase 4 — Output Pipeline + Visualization + Polish:
- output-pipeline.js: global curve → smoothing → slew rate → freeze gate
- weight-health.js: weight magnitude histogram, dead/saturating/healthy status
- gradient-flow.js: per-layer weight-delta analysis, vanishing/exploding detection
- session-presets.js: save/load full state, URL sharing via compact params
- phase4-ui.js: freeze button, network health panel, session preset UI

All phases merged into a-app.js with proper integration: auto-snapshots,
pressure-modulated RL, heatmap triggers, output pipeline in routeOutputs,
gradient capture around training, persistence for all new state.
 2026-03-26 10:48:12 +02:00
w1n5t0n
f8983c4806 feat(playground): replace JS ML engine with WASM nisps-core 
Compile nisps-core C++ MLP to WASM (36KB) and use it as the ML engine
in the playground, replacing the JavaScript port for inference, training,
and weight manipulation.

- Add extern "C" WASM bindings with spread-aware drawWeights/moveWeights
- WasmIML class is a drop-in replacement for the JS IML
- Inference runs on main thread via WASM (fast, synchronous)
- Training runs in a Web Worker with its own WASM instance (non-blocking)
- Interactive training (thumbs-up, train button) no longer freezes UI/audio
- Preset loading and state restore still use sync training
 2026-03-23 23:23:07 +02:00