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Three new standalone ES modules + integration into a-app.js: - input-pipeline.js: 5-stage processing (deadzone → zoom → curve → smoothing → momentum-as-zoom), 3 anchor modes, zoom-at-zero freeze, per-axis overrides - control-surface.js: compound axes (Boldness/Memory/Precision) with interpolation tables, offset-based override resolution (trim-pot model), 6 built-in presets - control-surface-ui.js: floating bar axis sliders, gear icon settings drawer with Input/Training/Exploration/Output sections, log-scale sliders, override dots - joy-map-enhanced.js: zoom minimap with adaptive grid (4×4→32×32), vanishing trail with Catmull-Rom spline + tap-to-return, dual concentric noise rings, frozen overlay Integration fixes from fresh-eyes review: - getCurrentInputs()/setCurrentInputs() use cached pipeline coords (not raw) - CSS noise ring hidden when canvas version active (no doubling) - Input mode switch re-runs through pipeline - Control surface state persisted to localStorage Implements full Phase 1 of SPEC-controls.md plus bonus items from later phases (zoom-aware feedback, control presets with override resolution, input curve/deadzone/ smoothing/momentum all wired). |
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|---|---|---|
| .beads | ||
| .github/workflows | ||
| .vscode | ||
| data | ||
| modes | ||
| nisps-core | ||
| playground | ||
| src | ||
| vcv | ||
| voicespaces | ||
| .gitignore | ||
| .gitmodules | ||
| AGENTS.md | ||
| ChannelStripAudioApp.hpp | ||
| CLAUDE.md | ||
| IMLInterface.hpp | ||
| LICENSE | ||
| MEMLNaut-NISPS.ino | ||
| NISPS_CORE_EXTRACTION_PLAN.md | ||
| NISPS_CORE_TASKS.md | ||
| PAFSynthAudioApp.hpp | ||
| README.md | ||
| ThruAudioApp.hpp | ||
| XiasriAnalysis.cpp | ||
| XiasriAnalysis.hpp | ||
| XIASRIAudioApp.hpp | ||
Neural Interactive Shaping of Parameter Spaces
https://musicallyembodiedml.github.io/memlnaut/approaches/nisps
Web Playground
Try NISPS in your browser — no hardware required:
cd playground
python3 -m http.server
# Open http://localhost:8000
Train a neural network to map joystick positions to generative visuals through interactive machine learning. Two learning modes: direct example mapping and reinforcement learning with thumbs up/down feedback.
The playground UI includes an Expand toggle on the visual surface so you can make the canvas nearly full-screen while compressing parameter/control panels into a minimal strip beneath it.