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One-core-engine P4.3/P4.4: the input/output pipeline processing and the curve
catalog now live in the C++/WASM core (nisps/pipeline/*, nisps/core/math.hpp).
The TS ports are deleted and the browser drives the WASM chains.
Engine:
- WasmIML owns a nisps_pipeline_create handle + bridge buffers and exposes
setInputConfig (TS InputConfig → 15-float wire), processInput, resetInput,
setOutputConfig (Infinity slew → 0), setOutputFreezeMask, processOutput
(in place), resetOutput, curveApply, curveApplyBatch (chunked). Handle +
buffers created in init_, freed in dispose, output-sized buffers realloc'd
on reshape.
- Spine routes setInputs through iml.processInput/processOutput (state lives
C++-side); config source-of-truth stays TS-side and is pushed on attach /
setInputConfig / setOutputConfig. Preserves ?debug=1 fixed-dt determinism
(same dt fed to the WASM calls). EngineApi gains setInputConfig/
setOutputConfig/curveApply/curveApplyBatch.
- New types-only modules: pipeline-types.ts (InputConfig/OutputConfig +
defaults + wire int mappers) and curve-catalog.ts (CurveName + name→id).
types.ts declares the pipeline/curve C ABI. engine barrel updated.
- DELETED src/engine/{input-pipeline,output-pipeline,curves}.ts.
Tests (P4.4 gate — recorded-gesture regression):
- pipeline-golden.test.ts now loads the built WASM (indirect-eval shim,
tests/wasm-load.ts) and drives the frozen gesture/output fixtures through the
C++ chains, honouring the per-event dt clock contract. Tolerance 1e-5
(non-momentum drift <5e-7). The 3 momentum configs carry 1e-2: proven-inherent
f32 drift (a byte-faithful f32 port of the exact original algorithm matches
the WASM to <6e-8 while both diverge from the f64 capture by ~7-9e-3), NOT a
core bug.
- curves-golden.json: linear/square/sqrt/centered_power kept as the original
f64 captures (C++ matches within <3e-8); exp/log/sigmoid/cubic RE-BASELINED
from the WASM (deliberate switch to firmware-exact k=1 exp/log, slope-6
sigmoid, true cubic x^3). Provenance recorded in-file.
- _generate.ts rebuilt as the WASM curve re-baseline tool; pipeline-golden-lib
trimmed to pure data builders.
Docs: fixtures/README.md + manifold/ONBOARDING.md updated.
Gates: typecheck, bun test (9), vite build, playwright e2e (27) all green.
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|---|---|---|
| .claude/worktrees/agent-ae87fe47/playground/js/shapeseq | ||
| .github/workflows | ||
| .vscode | ||
| assets/media | ||
| codegen | ||
| data | ||
| docs | ||
| firmware | ||
| manifold | ||
| nisps | ||
| playground/dist | ||
| schemas | ||
| scripts | ||
| src | ||
| tests | ||
| vcv | ||
| .envrc | ||
| .gitignore | ||
| .gitmodules | ||
| AGENTS.md | ||
| ALIGNMENT.md | ||
| CLAUDE.md | ||
| LICENSE | ||
| MAP.md | ||
| NISPS_CORE_EXTRACTION_PLAN.md | ||
| NISPS_CORE_TASKS.md | ||
| package-lock.json | ||
| package.json | ||
| playwright.config.js | ||
| README.md | ||
| synth-midi-cc.json | ||
Neural Interactive Shaping of Parameter Spaces
https://musicallyembodiedml.github.io/memlnaut/approaches/nisps
Firmware
The hardware firmware targets the MEMLNaut RP2350 build and uses repo-local helper scripts for the known-good build configuration:
git submodule update --init --recursive
scripts/build-firmware.sh
scripts/flash-firmware.sh
scripts/build-and-flash-firmware.sh
Notes:
- The scripts build for
rp2040:rp2040:solderparty_rp2350_stamp_xlwithOptimize3. - The build forces C++20 because the firmware uses
std::spanand concepts. build-firmware.shaccepts an optional variant name such asMEMLCeliumorBreakOr. Matching remains case-insensitive, somemlceliumstill works. If you omit it in an interactive shell, the script parsesMEMLNaut-NISPS.ino, prompts for a variant, and rewrites the activeMEMLNAUT_MODE_TYPEbefore building.flash-firmware.shaccepts an optional mountpoint argument, or auto-detects common UF2 bootloader mounts such as/run/media/$USER/RP2350and/run/media/$USER/RPI-RP2.
Manifold (browser app)
Try NISPS in your browser — no hardware required. Manifold is the React front-end running the same C++ engines + ML as the firmware, compiled to WASM:
cd manifold
bun install
bun run dev
Staging deployment: https://meml.lnfinitemonkeys.org/next/
Train a neural network to map input gestures to synth parameters through interactive machine learning: place examples, or use verdict-based feedback (explore-and-place, geometric dislike).
(The former SolidJS playground was retired in July 2026 — archived on branch
archive/playground-solidjs, tag playground-solidjs-final.)