Compare commits
6 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 mikkeli
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239b764393 | ||
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mikkeli
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5420975f8e | ||
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mikkeli
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aed2d54b45 | ||
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mikkeli
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6ae4d5e8e3 | ||
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mikkeli
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da4231ad36 | ||
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mikkeli
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e8da88b6c1 |
+7
-29
@@ -1,29 +1,7 @@
|
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# Build context hygiene. The image needs the source modules and static/, but
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# nothing else — a fat context here means slow builds and a bigger surface for
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# accidentally baking in local state (audio, caches, .env, ssh keys).
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.git
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.gitignore
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.venv
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__pycache__/
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*.pyc
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*.pyo
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*.egg-info/
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build/
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dist/
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|
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# Tests and tooling are not needed to run the service.
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tests/
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scripts/
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.claude/
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||||
.vscode/
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.idea/
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||||
|
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# Local state that must never enter an image.
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*.log
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.env
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.env.*
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fonts/
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*.ttf
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*.otf
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*.ttc
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audio_analysis.log
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# The image is web/ served with deploy/nginx.conf. Allowlist those and nothing
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# else, so no local state (audio, fixtures, caches, .env, keys) can ever end up
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# in the build context.
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*
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!web/
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!deploy/nginx.conf
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!deploy/security-headers.conf
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@@ -11,6 +11,8 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th
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- **Modular GUI Architecture**: Complete PyQt5 interface with drag-and-drop and file dialog support
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- **Font Management**: CJK-capable, fixed UI font (M PLUS 1 Code @ 10pt) with system fallback
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- **Threading & Logging**: Robust background processing with detailed logging system
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- **Web UI** (`web/`): the same metrics ported to in-browser JavaScript — a static
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site; audio never leaves the tab
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### Technical stack
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- **Audio Processing**: librosa, numpy
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@@ -109,49 +111,55 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th
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gone with the matplotlib render path. If wanted back, it belongs in the
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renderer, applied uniformly to every metric — not per-metric
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#### `web_session.py`
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- Server-side equivalent of `AnalysisResultsManager`, without Qt: owns the
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per-track metric cache and the overlay set, and mirrors the desktop's
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compute-off-the-request-thread behaviour
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- **No audio is stored.** Tracks are keyed by `file_id` = SHA-256 of the audio,
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and the session keeps only analysis results and metadata. There is no upload
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directory and no cache of bytes
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- Because the key is a content hash, re-sending the same master for a second
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metric reuses the first decode — the client only re-uploads what the server has
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never seen (checked via `metrics_cached`)
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#### `web/` (browser version — no backend)
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- A static site: decoding and every metric run in the visitor's tab; nothing is
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uploaded or stored. Served with `Content-Security-Policy: connect-src 'none'`
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(`deploy/nginx.conf`), so the page and its worker cannot make network requests
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- The image versions assets by content: everything but `index.html` is copied to
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`v/<hash>/` and the page's references rewritten (Dockerfile `assets` stage);
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nginx serves `v/` immutable and the page `no-cache`. Needed because Cloudflare
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forces browser caching of .js/.css to 4 h, which paired a fresh index.html with
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a stale app.js (`Cannot set properties of null`). Source `web/index.html` keeps
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plain relative paths, so serving `web/` directly still works
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- `decode.js` — `AudioFile.__init__` counterpart. WAV/AIFF PCM & float are parsed
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directly with libsndfile scaling (bit-identical to `librosa.load`; Chromium's
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own WAV decoder scales positive int16 by 1/32767). Other formats go through
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`decodeAudioData` on an `OfflineAudioContext` at the header-sniffed native rate
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(no resampling). ID3 artist/title for MP3. Downmix = float32 channel mean
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- `dsp.js` — ports of every `Metric.compute`: pure functions over the mono
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Float32Array (run in the worker and under Node). Same numerics as the Python:
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sequential float64 prefix sums sampled only at window edges (no N-length
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arrays), pyloudnorm K-weighting via scipy `lfilter`'s DF2T recurrence (streamed),
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`resample_poly(y, 4, 1)`'s 81-tap Kaiser(5) filter + monotonic-deque window max,
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`librosa.stft` centred framing + `amplitude_to_db(ref=max, top_db=80)`.
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Loudness (short-term, integrated, LRA) is one memoised pass shared by LUFS and PSR
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- `metrics.js` — registry + `build_spec` ports producing the plot payload
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(`{axes, hlines, annotations, segments, series, heatmap}`), plus `applyRelativeX`
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- `analysis-worker.js` — Web Worker: holds each track's mono signal, computes one
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metric per request, transfers typed arrays back
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- `app.js` — `MainWindow` + `AnalysisResultsManager` + renderer: track list,
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overlay set, per-metric result cache, job queue (foreground jobs jump ahead of
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background prefetch; LUFS + true peak prefetched first for the metadata
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panel's loudness summary), uPlot for curves/bands + canvas spectrogram (log
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axis drawn from linear rows, cached offscreen image). Guide and reference
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lines are painted in a uPlot draw hook, so dragging a line is a cheap redraw
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and moves live. One zoom/pan controller serves both renderers: wheel zoom
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(Ctrl = x only, Shift = y only, over an axis = that axis), rAF-throttled drag
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pan, double-click reset; `state.zoom` survives redraws and resets when units
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change. In-plot legend overlay like pyqtgraph's
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- Font: CSS `--font` stack prefers M PLUS 1 Code, else the system UI font;
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canvas/uPlot text reads the same variable
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- `vendor/` — uPlot 1.6.32, vendored (the CSP only allows same-origin scripts)
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- Needs an HTTP server (module scripts and workers don't load from `file://`),
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but no secure context — plain `http://` on a LAN works
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|
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#### `webapp.py`
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- FastAPI routes + static mount + the `ujm-web` entry point (binds loopback by
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default; `--host`/`--port`/`--open` to override)
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- Analysis endpoints take the audio as a **raw request body**, not a multipart
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upload: spool to a temp file, `SESSION.observe(...)`, unlink in `finally`. The
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bytes exist on disk only for the duration of that one request
|
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- `POST /api/analyse` (analyse + plot data), `POST /api/file` (register without
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plotting), `DELETE /api/file`, `POST /api/overlay`, `GET /api/plot`,
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`GET /api/metadata`, `GET /api/metrics`, `GET /api/session`
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|
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#### `metrics_json.py`
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- The renderer seam: `PlotSpec`/metric data → JSON, so a non-pyqtgraph renderer
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consumes the identical spec (curves, bands, hlines, heatmap, axis specs) that
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the desktop widget draws. `hlines` carry the integrated LUFS reference line —
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it is not an annotation
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#### `static/` (web front end)
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- `audio-store.js` — OPFS store. Copies each picked/dropped `File` into Origin
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Private File System (browser-sandboxed, not the host's filesystem), hashes it
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with WebCrypto in chunks while streaming (never loads a whole master into
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memory), and re-sends bytes to the server per metric
|
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- `app.js` — the web renderer, an ES module importing the store. Draws the same
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`PlotSpec` the desktop does: uPlot for curves/bands, a plain canvas for the
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spectrogram heatmap (a canvas can map rows through an arbitrary function, so it
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draws native linear rows and maps them, unlike pyqtgraph's affine-only
|
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`ImageItem`). Mirrors the desktop's per-metric colour cycle, lin/log toggles,
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absolute/relative time, and draggable reference lines
|
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- `vendor/` — uPlot 1.6.32 (IIFE + CSS), vendored so nothing is fetched from a
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CDN at runtime
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- Boot rehydrates: the server still has the last session's analysis, so it
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re-offers audio only for metric/track combinations the server reports as
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uncached, and reports unavailable combinations rather than faking them
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#### `tests/parity/`
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- `fixtures.py` synthesises edge-case audio (short / silent / below the relative
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gate, 96 kHz, every PCM layout, lossy formats via ffmpeg); `reference.py` runs
|
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`metrics.py` and saves the exact mono signal it analysed; `parity.mjs` runs
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`web/dsp.js` on that signal and compares every field (float64 paths ~1e-12,
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float32 paths ~1e-6)
|
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- Any change to `metrics.py` numerics must be mirrored in `web/dsp.js` and pass this
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|
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#### `master_core.py`
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- Defines the `AudioFile` class: librosa loading, rolling RMS power. BPM detection
|
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@@ -269,7 +277,8 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th
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- matplotlib: Colormaps only (consumed by pyqtgraph) + librosa dependency
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- mutagen: Audio metadata extraction
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- PyQt5: GUI framework
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- fastapi / uvicorn: web UI (optional extra; the desktop app does not need them)
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- Web UI: no Python dependencies; uPlot is vendored in `web/vendor/`. The parity
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tests need Node 18+
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|
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### Architecture considerations
|
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- Three-stage split: `metrics.compute` (heavy, worker thread, backend-neutral
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@@ -294,19 +303,16 @@ uv run ujm # launch the GUI
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```
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### Running the web UI
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Branch `feature/web-ui`. Same backend, browser front end.
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Branch `feature/web-js`. Static files in `web/`; everything runs in the browser.
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```bash
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uv sync --extra web
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uv run ujm-web # http://127.0.0.1:8000
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uv run ujm-web --host 0.0.0.0 --port 8080 # reachable from another machine
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docker compose up -d --build # nginx + CSP, http://localhost:8080
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python3 -m http.server -d web 8080 # quick local try (no CSP header)
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```
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Uploaded audio is held in the browser's Origin Private File System and streamed
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to the server per request; the server spools each body to a temp file and unlinks
|
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it before responding. Nothing is written to the host beyond that transient spool.
|
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Verify with `python3 scripts/webapi_smoke.py` against a running server (needs
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`ffmpeg` for the fixtures).
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Audio is decoded and analysed in the tab and never leaves it (CSP
|
||||
`connect-src 'none'`). Check the port against `metrics.py` with the parity tests
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(`tests/parity`, see README).
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||||
|
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Optional flags (handled by `logger_setup.parse_log_args`):
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```bash
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+30
-80
@@ -1,88 +1,38 @@
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# uj-mastering-master — web UI
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#
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# Multi-stage on purpose: the build stage compiles wheels (librosa pulls in
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# scipy, numba and llvmlite, all of which have C extensions), and none of that
|
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# toolchain belongs in the runtime image.
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||||
# The web UI is a static site: decoding and every metric run in the visitor's
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# browser (web/dsp.js inside a Web Worker). This image only serves files — no
|
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# application server, no upload endpoint, nothing written anywhere — so it runs
|
||||
# read-only as nginx's unprivileged user. See deploy/nginx.conf for the CSP that
|
||||
# stops the page from making network requests at all.
|
||||
#
|
||||
# The runtime image installs the *installed package*, not a source tree, so the
|
||||
# same image works whether you built it from a checkout or a release tarball.
|
||||
#
|
||||
# Note on audio: the web UI stores uploaded audio in the browser (OPFS) and
|
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# spools each request body to /tmp only for the duration of that request. There
|
||||
# is no volume for audio, because the app never keeps any — see README.
|
||||
#
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# Note on the desktop app: this image is the *web* front end only. PyQt5 and
|
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# pyqtgraph are deliberately not installed — there is no display in a container.
|
||||
# The desktop app (PyQt5) is unaffected and not part of this image.
|
||||
|
||||
# ---- build -----------------------------------------------------------------
|
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FROM python:3.11-slim AS build
|
||||
# ---- assets: version every file except the page by content ------------------
|
||||
# Everything but index.html goes under v/<hash of the assets>/, and index.html's
|
||||
# references are rewritten to match. Each deploy therefore changes every asset
|
||||
# URL, so no cache (browser or Cloudflare, which forces .js/.css browser caching
|
||||
# to 4 h) can pair a new index.html with an old app.js. Module imports and the
|
||||
# worker URL are relative, so they resolve inside the versioned directory as is.
|
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FROM alpine:3.22 AS assets
|
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COPY web/ /src/
|
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RUN set -eu; \
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cd /src; \
|
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v="$(find . -type f ! -name index.html | sort | xargs sha256sum | sha256sum | cut -c1-12)"; \
|
||||
mkdir -p "/out/v/$v"; \
|
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for f in *; do [ "$f" = index.html ] || cp -R "$f" "/out/v/$v/"; done; \
|
||||
sed -E "s#(href|src)=\"(app\.css|app\.js|vendor/[^\"]+)\"#\1=\"v/$v/\2\"#g" index.html > /out/index.html; \
|
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grep -q "src=\"v/$v/app.js\"" /out/index.html; \
|
||||
grep -q "href=\"v/$v/app.css\"" /out/index.html
|
||||
|
||||
ENV PIP_DISABLE_PIP_VERSION_CHECK=1 \
|
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PIP_NO_CACHE_DIR=1 \
|
||||
UV_LINK_MODE=copy
|
||||
# ---- runtime -------------------------------------------------------------------
|
||||
FROM nginxinc/nginx-unprivileged:stable-alpine
|
||||
|
||||
# numba/llvmlite and scipy need a compiler; libsndfile is what soundfile
|
||||
# (librosa's decoder) links against at runtime, but the wheel needs it at build
|
||||
# time to be detected.
|
||||
RUN apt-get update && apt-get install -y --no-install-recommends \
|
||||
build-essential \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
COPY deploy/nginx.conf /etc/nginx/conf.d/default.conf
|
||||
COPY deploy/security-headers.conf /etc/nginx/snippets/ujm-security-headers.conf
|
||||
COPY --from=assets /out/ /usr/share/nginx/html/
|
||||
|
||||
COPY --from=ghcr.io/astral-sh/uv:0.12.5 /uv /usr/local/bin/uv
|
||||
EXPOSE 8080
|
||||
|
||||
WORKDIR /src
|
||||
# Copy the whole checkout minus .dockerignore. Deliberately not a hand-picked
|
||||
# file list: `py-modules` in pyproject.toml enumerates every module the build
|
||||
# backend must find, and a curated COPY that omits any of them fails the build
|
||||
# with "file <module>.py not found". The exclusions that matter (venv, caches,
|
||||
# .git, local state) are in .dockerignore, which is the right place for them.
|
||||
COPY . .
|
||||
|
||||
# Build a wheel, then install it into a self-contained prefix to copy forward.
|
||||
# `"uj-mastering-master[web]"` (not `--extra web`) is the syntax uv wants when
|
||||
# installing a source tree — `--extra` needs a lockfile/setup.py it does not
|
||||
# have here and fails with "Requesting extras requires a pylock.toml...".
|
||||
RUN uv venv /opt/venv \
|
||||
&& uv pip install --python /opt/venv/bin/python --no-cache \
|
||||
".[web]"
|
||||
|
||||
# ---- runtime ---------------------------------------------------------------
|
||||
FROM python:3.11-slim AS runtime
|
||||
|
||||
# libsndfile1 is the only runtime system dependency: librosa decodes through
|
||||
# soundfile, which dlopens it. Everything else is a self-contained wheel.
|
||||
# (FFmpeg is *not* needed — it only ever generated test fixtures.)
|
||||
RUN apt-get update && apt-get install -y --no-install-recommends \
|
||||
libsndfile1 \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# Non-root, with a home it can actually write to: librosa/numba want a cache
|
||||
# dir, and the app spools request bodies under /tmp.
|
||||
RUN useradd --create-home --uid 10001 --shell /usr/sbin/nologin ujm
|
||||
|
||||
COPY --from=build /opt/venv /opt/venv
|
||||
|
||||
ENV PATH=/opt/venv/bin:$PATH \
|
||||
PYTHONUNBUFFERED=1 \
|
||||
PYTHONDONTWRITEBYTECODE=1 \
|
||||
HOME=/home/ujm \
|
||||
NUMBA_CACHE_DIR=/tmp/numba-cache \
|
||||
MPLCONFIGDIR=/tmp/matplotlib
|
||||
|
||||
# The app's temporary spools land here. Declared so a read-only root filesystem
|
||||
# can still be used (`read_only: true` + `tmpfs: /tmp` in compose).
|
||||
VOLUME ["/tmp"]
|
||||
|
||||
USER ujm
|
||||
WORKDIR /home/ujm
|
||||
|
||||
EXPOSE 8000
|
||||
|
||||
# Baked-in healthcheck: hit the API rather than the page, so it fails when the
|
||||
# *backend* is broken and not merely when a static asset is missing.
|
||||
HEALTHCHECK --interval=30s --timeout=5s --start-period=20s --retries=3 \
|
||||
CMD ["python", "-c", "import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://127.0.0.1:8000/api/metrics', timeout=4).status == 200 else 1)"]
|
||||
|
||||
# 0.0.0.0, not the CLI default of 127.0.0.1: loopback inside a container is
|
||||
# unreachable from the host, which is the whole point of publishing a port.
|
||||
CMD ["ujm-web", "--host", "0.0.0.0", "--port", "8000", "--log-level", "INFO"]
|
||||
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
|
||||
CMD wget -q -O /dev/null http://127.0.0.1:8080/ || exit 1
|
||||
|
||||
@@ -39,12 +39,11 @@ uv sync --extra desktop
|
||||
uv run ujm
|
||||
```
|
||||
|
||||
`uv run ujm` boots the desktop GUI (see *Web UI* for the browser front end).
|
||||
`uv run ujm` boots the desktop GUI (see *Web UI* for the browser version).
|
||||
|
||||
`uv sync` on its own installs only the analysis dependencies (librosa, numpy,
|
||||
scipy, mutagen, pyloudnorm). The GUI stack — PyQt5, pyqtgraph — is the
|
||||
`desktop` extra, kept separate because nothing on the web path imports it. Add
|
||||
`--all-extras` to get both front ends.
|
||||
`desktop` extra.
|
||||
|
||||
### Logging flags
|
||||
```bash
|
||||
@@ -59,102 +58,88 @@ See [CJK_FONTS.md](CJK_FONTS.md) for details.
|
||||
|
||||
## Web UI
|
||||
|
||||
The same analysis backend with a browser front end, on branch `feature/web-ui`.
|
||||
No PyQt5, no matplotlib: `metrics.py` was already split into a backend-neutral
|
||||
`compute` and a view-aware `build_spec`, so the web UI reuses the analysis code
|
||||
unchanged and reimplements only the drawing.
|
||||
A browser version that runs entirely inside the tab, in `web/` (branch
|
||||
`feature/web-js`). There is no Python backend: decoding and all seven metrics are
|
||||
JavaScript ports of `master_core.py` / `metrics.py`, computed in a Web Worker and
|
||||
drawn from the same `PlotSpec`-shaped payloads the desktop renderer uses.
|
||||
|
||||
```bash
|
||||
uv sync --extra web
|
||||
uv run ujm-web # http://127.0.0.1:8000
|
||||
uv run ujm-web --host 0.0.0.0 --port 8080 --open
|
||||
```
|
||||
|
||||
A server install needs no Qt at all, which is also what keeps the container
|
||||
image small.
|
||||
**Audio never leaves the browser.** A dropped file is read into memory, decoded,
|
||||
reduced to the mono signal the metrics use and analysed — nothing is uploaded,
|
||||
cached or written to storage, and closing the tab discards it. This is enforced,
|
||||
not just promised: the page is served with `Content-Security-Policy: connect-src
|
||||
'none'`, so neither the page nor its worker is permitted to make any network
|
||||
request.
|
||||
|
||||
Everything the desktop app does works the same way: all seven metrics, the
|
||||
overlay, lin/log toggles, absolute/relative time, and draggable reference lines
|
||||
(kept per metric, as on the desktop).
|
||||
overlay, lin/log toggles, absolute/relative time, an in-plot legend, wheel zoom
|
||||
around the cursor (Ctrl: time only, Shift: values only, or scroll over an axis),
|
||||
live drag-to-pan and double-click to reset, and draggable reference lines (kept
|
||||
per metric) alongside the metrics' own guides (−14 LUFS, integrated loudness,
|
||||
0 dBTP…). The metadata panel and file list show integrated loudness, LRA and
|
||||
max true peak. Analysis runs at the file's native sample rate.
|
||||
|
||||
**Uploaded audio is never written to the host.** The browser copies each file
|
||||
into Origin Private File System — its own sandboxed storage — and streams the
|
||||
bytes to the server for one request at a time. The server spools each body to a
|
||||
temp file, decodes, computes, and unlinks it in a `finally` before the response
|
||||
is sent. There is no upload directory, no cache of audio, and no session state
|
||||
keyed on a file path: `file_id` is the SHA-256 of the audio, so re-sending the
|
||||
same master for a second metric reuses the first decode.
|
||||
Serve `web/` with any static file server, over `http://` or `https://` — no
|
||||
secure context is needed. (ES modules and workers don't load from `file://`, so
|
||||
opening `index.html` directly won't work.)
|
||||
|
||||
Being precise about the guarantee: the bytes do have to reach the server, because
|
||||
`librosa` decodes from a path and the analysis is CPU-bound numpy/scipy.
|
||||
*Running this does not accumulate the user's masters on the host* — nothing
|
||||
persists between requests. It is not a claim that audio is never on the machine
|
||||
mid-request.
|
||||
```bash
|
||||
docker compose up -d --build # nginx + the CSP, http://localhost:8080
|
||||
python3 -m http.server -d web 8080 # quick local try (no CSP header)
|
||||
```
|
||||
|
||||
The front end is served entirely from `static/` with uPlot vendored locally, so
|
||||
nothing is fetched from a CDN, and the server binds loopback by default.
|
||||
### How the port matches the Python
|
||||
|
||||
- **Decoding** (`web/decode.js`): WAV and AIFF (PCM 8/16/24/32-bit, float 32/64,
|
||||
WAVE_FORMAT_EXTENSIBLE) are parsed directly with libsndfile's sample scaling,
|
||||
so the signal is bit-identical to `librosa.load`. Other formats (FLAC, MP3, Ogg
|
||||
Vorbis/Opus, AAC) use the browser's decoder through an `OfflineAudioContext`
|
||||
running at the sample rate read from the file header, so nothing is resampled.
|
||||
MP3 artist/title come from ID3 tags, as on the desktop.
|
||||
- **Metrics** (`web/dsp.js`): the same algorithms and numerics — pyloudnorm's
|
||||
K-weighting through scipy's `lfilter` recurrence, BS.1770 gating and EBU LRA,
|
||||
`resample_poly`'s 81-tap Kaiser filter for true peak, `librosa.stft` framing and
|
||||
`amplitude_to_db` for the spectrogram. Running sums and window maxima are
|
||||
single streaming passes, so no signal-length intermediate arrays are allocated.
|
||||
|
||||
### Parity tests
|
||||
|
||||
`tests/parity` checks the port against the Python on synthetic fixtures that
|
||||
cover what the metric code branches on — shorter than each window, silence,
|
||||
passages below the relative gate, 96 kHz, every PCM layout, lossy formats:
|
||||
|
||||
```bash
|
||||
uv run --no-project --with numpy --with soundfile \
|
||||
python tests/parity/fixtures.py /tmp/ujm-parity
|
||||
uv run --no-project --with librosa --with pyloudnorm --with scipy --with mutagen \
|
||||
python tests/parity/reference.py /tmp/ujm-ref /tmp/ujm-parity/*
|
||||
node tests/parity/parity.mjs /tmp/ujm-ref
|
||||
```
|
||||
|
||||
`reference.py` saves the exact mono signal `metrics.py` analysed, and
|
||||
`parity.mjs` runs `web/dsp.js` on that same signal and compares every output
|
||||
field. The float64 paths (loudness, crest factor, PSR) agree to ~1e-12, the
|
||||
float32 paths (true peak, spectrogram dB, RMS) to ~1e-6.
|
||||
|
||||
### Deploying with Docker
|
||||
|
||||
A `docker compose` template is provided:
|
||||
|
||||
```bash
|
||||
docker compose up --build # build and start
|
||||
open http://localhost:8000
|
||||
```
|
||||
|
||||
The image is `web` extra only — no Qt, no display server — and runs as an
|
||||
unprivileged user (uid 10001). It is built multi-stage so the compiler toolchain
|
||||
that scipy/numba need never reaches the runtime layer; the runtime image installs
|
||||
the built wheel, so the same image works from a checkout or a release tarball.
|
||||
|
||||
What the template assumes, and why:
|
||||
|
||||
- **There is no audio volume.** Not an oversight: the app keeps no audio, so
|
||||
there is nothing to persist. `read_only: true` with a `/tmp` tmpfs means
|
||||
request spools are memory-backed and never touch a disk at all.
|
||||
- **Loopback publishing.** The app binds `0.0.0.0` inside the container (the CLI
|
||||
default of `127.0.0.1` would be unreachable from the host), but compose
|
||||
publishes `127.0.0.1:8000:8000`. This tool has no authentication, so it should
|
||||
not appear on the LAN by accident. Change to `"8000:8000"` or put it behind a
|
||||
reverse proxy to expose it deliberately.
|
||||
- **CPU limits, not just memory.** Analysis is CPU-bound numpy/scipy, so the BLAS
|
||||
thread pools are pinned (`OMP_NUM_THREADS` etc.) to stop overlapping requests
|
||||
from oversubscribing. Raise them if you raise `cpus`.
|
||||
- `cap_drop: [ALL]` and `no-new-privileges` — nothing in the image needs
|
||||
capabilities.
|
||||
|
||||
For a read-only root filesystem with no writable layer at all, the defaults
|
||||
already give you that.
|
||||
|
||||
### Verifying it
|
||||
|
||||
With a server running:
|
||||
|
||||
```bash
|
||||
python3 scripts/make_fixtures.py # synthesise test audio
|
||||
python3 scripts/webapi_smoke.py # 61 assertions
|
||||
python3 scripts/webapi_smoke.py http://host:port /path/to/audio
|
||||
```
|
||||
|
||||
`make_fixtures.py` generates the audio the suite needs (`sine440.wav`,
|
||||
`pinknoise.wav`) with numpy alone, so no network and no ffmpeg are required — a
|
||||
tagged MP3 is added only if ffmpeg happens to be present, and the tag assertions
|
||||
skip cleanly when it is not. The suite drives the real HTTP surface with real
|
||||
audio and checks the contract the browser depends on — payload shapes per
|
||||
metric, physics cross-checked against an independent `librosa` computation, view
|
||||
toggles that must not alter data, error paths, and that no spool file survives a
|
||||
request.
|
||||
The image is nginx (unprivileged, read-only root filesystem) serving `web/` with
|
||||
`deploy/nginx.conf`, which sets the CSP and turns access logging off. There is
|
||||
nothing to persist, upload or log on the server side, so there are no volumes.
|
||||
Assets are served from a content-hashed `v/<hash>/` directory (cached
|
||||
indefinitely) while the page itself is always revalidated, so a deploy can never
|
||||
leave a browser running old scripts against a new page — even behind a CDN that
|
||||
overrides cache headers.
|
||||
|
||||
### Web architecture
|
||||
|
||||
| Module | Responsibility |
|
||||
| --- | --- |
|
||||
| `web_session.py` | Headless analysis session: content-addressed track cache, metric cache, overlay |
|
||||
| `metrics_json.py` | `PlotSpec` → JSON (the renderer seam; the desktop renderer is the other consumer) |
|
||||
| `webapp.py` | FastAPI routes, raw-body analysis endpoints, static mount, `ujm-web` entry point |
|
||||
| `static/audio-store.js` | OPFS audio store, content hashing, streamed upload |
|
||||
| `static/app.js` | Web renderer: same `PlotSpec` drawn with uPlot + canvas |
|
||||
| `web/decode.js` | File → mono Float32Array at native rate (direct WAV/AIFF, browser decoder otherwise); ID3 tags |
|
||||
| `web/dsp.js` | Ports of every `Metric.compute`; pure functions (also run under Node for the parity tests) |
|
||||
| `web/metrics.js` | Metric registry + `build_spec` ports producing plot payloads; relative-time transform |
|
||||
| `web/analysis-worker.js` | Web Worker holding each track's signal and computing one metric per request |
|
||||
| `web/app.js` | Track list, overlay, result cache, foreground/prefetch job queue, uPlot + canvas renderer |
|
||||
| `deploy/nginx.conf` | Static serving, CSP (`connect-src 'none'`), no access log |
|
||||
|
||||
## Dependencies
|
||||
Core (always installed): `librosa`, `numpy`, `matplotlib`, `mutagen`,
|
||||
@@ -162,7 +147,9 @@ Core (always installed): `librosa`, `numpy`, `matplotlib`, `mutagen`,
|
||||
|
||||
Optional extras:
|
||||
- `desktop` — `PyQt5`, `pyqtgraph` (the GUI)
|
||||
- `web` — `fastapi`, `uvicorn`, `python-multipart` (the browser front end)
|
||||
|
||||
The web UI has no dependencies beyond uPlot, vendored in `web/vendor/`. The parity
|
||||
tests need Node 18+ plus the Python analysis dependencies.
|
||||
|
||||
## Architecture
|
||||
|
||||
@@ -186,5 +173,8 @@ Subclass `Metric` in `metrics.py`, implement `compute(audio_file) -> data` (the
|
||||
heavy part, runs on the worker thread) and `build_spec(data, view) -> PlotSpec`
|
||||
(cheap, view-aware, reruns on every scale toggle without recomputation). Register
|
||||
the instance in the `METRICS` dict at the bottom of the file — it shows up in the
|
||||
desktop dropdown and in the web UI's metric list automatically, because both
|
||||
renderers consume the same `PlotSpec`.
|
||||
desktop dropdown automatically.
|
||||
|
||||
For the web UI, port `compute` to `web/dsp.js` (add it to `COMPUTE`) and
|
||||
`build_spec` to `web/metrics.js` (add it to `METRICS`), then add its fields to the
|
||||
tolerance table in `tests/parity/parity.mjs` so the parity run checks it.
|
||||
|
||||
@@ -0,0 +1,39 @@
|
||||
# Static server for the web UI (web/).
|
||||
#
|
||||
# The page decodes and analyses audio inside the visitor's browser. The CSP's
|
||||
# `connect-src 'none'` (security-headers.conf) forbids the page and its worker
|
||||
# from making any network request (fetch, XHR, WebSocket, beacon), so dropped
|
||||
# audio has no way to leave the tab — enforced by the browser, not just promised
|
||||
# by the code.
|
||||
|
||||
server {
|
||||
listen 8080;
|
||||
server_name _;
|
||||
root /usr/share/nginx/html;
|
||||
index index.html;
|
||||
|
||||
# Nothing the app does reaches the server beyond fetching these files, and
|
||||
# there is no reason to keep a record of who fetched them.
|
||||
access_log off;
|
||||
server_tokens off;
|
||||
|
||||
gzip on;
|
||||
gzip_types text/css application/javascript;
|
||||
|
||||
# The page names the current asset version, so it is always revalidated.
|
||||
# (Each location includes the security headers itself: nginx drops
|
||||
# server-level add_header in any location that adds its own.)
|
||||
location / {
|
||||
include /etc/nginx/snippets/ujm-security-headers.conf;
|
||||
add_header Cache-Control "no-cache" always;
|
||||
try_files $uri $uri/ =404;
|
||||
}
|
||||
|
||||
# Assets live under v/<content hash>/ (see Dockerfile): a URL's content never
|
||||
# changes, so it can be cached indefinitely.
|
||||
location /v/ {
|
||||
include /etc/nginx/snippets/ujm-security-headers.conf;
|
||||
add_header Cache-Control "public, max-age=31536000, immutable" always;
|
||||
try_files $uri =404;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,8 @@
|
||||
# Security headers for every response, included per location in nginx.conf.
|
||||
#
|
||||
# connect-src 'none': neither the page nor its Web Worker may make network
|
||||
# requests, so audio cannot be sent anywhere. The worker's own policy comes from
|
||||
# its script response, which is why every location carries these headers.
|
||||
add_header Content-Security-Policy "default-src 'none'; script-src 'self'; worker-src 'self'; style-src 'self' 'unsafe-inline'; img-src 'self' data: blob:; connect-src 'none'; media-src 'none'; object-src 'none'; base-uri 'none'; form-action 'none'; frame-ancestors 'none'" always;
|
||||
add_header Referrer-Policy "no-referrer" always;
|
||||
add_header X-Content-Type-Options "nosniff" always;
|
||||
+13
-64
@@ -1,88 +1,37 @@
|
||||
# uj-mastering-master — web UI, container deployment template.
|
||||
#
|
||||
# docker compose up --build # build and start
|
||||
# docker compose logs -f # watch startup
|
||||
# open http://localhost:8000
|
||||
# docker compose up -d --build
|
||||
# open http://localhost:8080
|
||||
#
|
||||
# There is deliberately no audio volume. Uploaded audio lives in the browser
|
||||
# (Origin Private File System) and each request body is spooled to /tmp only
|
||||
# while that request is being decoded. Nothing about a user's masters is
|
||||
# persisted here — read-only storage is not just possible, it is the intent.
|
||||
# The container serves static files only. Audio is decoded and analysed inside
|
||||
# the visitor's browser tab and never sent anywhere (the page's CSP forbids
|
||||
# network requests), so there is nothing to upload, persist or log here — and no
|
||||
# volumes, on purpose.
|
||||
|
||||
services:
|
||||
ujm-web:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
# Pin the build to this branch's source; override to build from a
|
||||
# release tag instead:
|
||||
# docker compose build --build-arg ...
|
||||
build: .
|
||||
image: uj-mastering-master-web:local
|
||||
container_name: ujm-web
|
||||
|
||||
# Loopback-only by default. The app binds 0.0.0.0 *inside* the container,
|
||||
# but publishing to 127.0.0.1 means it is only reachable from this host —
|
||||
# an analysis tool with no authentication should not appear on the LAN by
|
||||
# accident. Change to "8000:8000" (or put it behind a reverse proxy) to
|
||||
# expose it deliberately.
|
||||
ports:
|
||||
- "127.0.0.1:8000:8000"
|
||||
- "8080:8080"
|
||||
|
||||
environment:
|
||||
# Analysis is CPU-bound numpy/scipy; keep BLAS from oversubscribing when
|
||||
# several requests overlap. Raise these if you raise `cpus` below.
|
||||
OMP_NUM_THREADS: "4"
|
||||
OPENBLAS_NUM_THREADS: "4"
|
||||
MKL_NUM_THREADS: "4"
|
||||
NUMEXPR_NUM_THREADS: "4"
|
||||
# Writable scratch for numba/matplotlib caches and request spools.
|
||||
NUMBA_CACHE_DIR: /tmp/numba-cache
|
||||
MPLCONFIGDIR: /tmp/matplotlib
|
||||
TMPDIR: /tmp
|
||||
|
||||
# The container filesystem can be read-only: the app writes nothing it
|
||||
# needs to keep. /tmp is a tmpfs (memory-backed) so spooled request bodies
|
||||
# never touch a disk at all.
|
||||
# Nothing to write: nginx only needs somewhere for its pid file and empty
|
||||
# temp directories.
|
||||
read_only: true
|
||||
tmpfs:
|
||||
- /tmp:size=1g,mode=1777
|
||||
- /tmp:size=16m,mode=1777
|
||||
|
||||
# Analysis needs headroom: a long master at native sample rate is heavy in
|
||||
# RAM. Raise the limit for large files; the tmpfs above is also backed by
|
||||
# memory, so --memory must comfortably exceed it.
|
||||
deploy:
|
||||
resources:
|
||||
limits:
|
||||
cpus: "4.0"
|
||||
memory: 4g
|
||||
|
||||
# Run as the image's unprivileged user (uid 10001). Nothing here needs root.
|
||||
security_opt:
|
||||
- no-new-privileges:true
|
||||
cap_drop:
|
||||
- ALL
|
||||
|
||||
restart: unless-stopped
|
||||
stop_grace_period: 10s
|
||||
|
||||
# The image ships a HEALTHCHECK; this is the same check expressed at the
|
||||
# orchestration layer, so `docker compose ps` shows real health.
|
||||
healthcheck:
|
||||
test: ["CMD", "python", "-c", "import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://127.0.0.1:8000/api/metrics', timeout=4).status == 200 else 1)"]
|
||||
interval: 30s
|
||||
timeout: 5s
|
||||
start_period: 20s
|
||||
retries: 3
|
||||
|
||||
logging:
|
||||
driver: json-file
|
||||
options:
|
||||
max-size: "10m"
|
||||
max-file: "3"
|
||||
|
||||
# No volumes are declared, on purpose. If you want to run the API smoke test
|
||||
# inside the image, do it ad hoc rather than mounting a source tree:
|
||||
#
|
||||
# docker compose exec ujm-web python - <<'PY'
|
||||
# ... # or see `make smoke` in the README
|
||||
# PY
|
||||
max-size: "1m"
|
||||
max-file: "2"
|
||||
|
||||
-170
@@ -1,170 +0,0 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
"""
|
||||
PlotSpec -> JSON.
|
||||
|
||||
The desktop renderer (`audio_visualization_widget`) draws a `PlotSpec` with
|
||||
pyqtgraph. The web renderer draws the *same* `PlotSpec` with a browser plotting
|
||||
library, so the only thing this module owns is the wire format between them:
|
||||
numpy arrays become plain lists, `NaN`/`inf` (gated PSR, empty windows) become
|
||||
JSON `null` so the client can break the line instead of drawing a spike.
|
||||
|
||||
Nothing here is web-framework-specific — `serialize_spec` is the exact partner of
|
||||
`show_specs`: same input, different canvas. Keeping it free of FastAPI imports
|
||||
means the desktop side could adopt it unchanged if a future client ever needed
|
||||
the same payload.
|
||||
|
||||
Why the heatmap is sent losslessly: the desktop renderer resamples the linear STFT
|
||||
rows onto a log-spaced grid for a log frequency axis (pyqtgraph's ImageItem is
|
||||
affine-only and won't follow a log axis). The browser *can* draw a non-linear
|
||||
axis from a linearly spaced image, so no resampling happens here — the client gets
|
||||
the native rows plus the axis-extent information and does the mapping itself.
|
||||
That keeps warm-up cost identical to the desktop app and makes the expensive
|
||||
log-grid interpolation happen once per view change rather than once per request.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
from typing import Any, Optional
|
||||
|
||||
import numpy as np
|
||||
|
||||
from plotspec import (
|
||||
PlotSpec, RefLineProps, ViewState, X_RELATIVE,
|
||||
)
|
||||
|
||||
|
||||
def _numbers(values) -> list:
|
||||
"""numpy array -> JSON-safe list, with non-finite floats mapped to None."""
|
||||
if values is None:
|
||||
return []
|
||||
arr = np.asarray(values, dtype=float).ravel()
|
||||
out: list[Optional[float]] = []
|
||||
for v in arr.tolist():
|
||||
out.append(None if (v is None or not math.isfinite(v)) else float(v))
|
||||
return out
|
||||
|
||||
|
||||
def _ints(values) -> list[float]:
|
||||
"""numpy array -> JSON-safe list of floats (no None mapping — index axes)."""
|
||||
return [float(v) for v in np.asarray(values, dtype=float).ravel().tolist()]
|
||||
|
||||
|
||||
def _bounds(values) -> Optional[list[float]]:
|
||||
"""[min, max] of the finite values, or None when everything is non-finite."""
|
||||
if values is None:
|
||||
return None
|
||||
arr = np.asarray(values, dtype=float).ravel()
|
||||
arr = arr[np.isfinite(arr)]
|
||||
if not arr.size:
|
||||
return None
|
||||
return [float(arr.min()), float(arr.max())]
|
||||
|
||||
|
||||
def _serialize_axes(axes) -> dict[str, Any]:
|
||||
return {
|
||||
"x_label": axes.x_label,
|
||||
"y_label": axes.y_label,
|
||||
"y_log": bool(axes.y_log),
|
||||
"x_log": bool(axes.x_log),
|
||||
"y_range": list(axes.y_range) if axes.y_range else None,
|
||||
"x_range": list(axes.x_range) if axes.x_range else None,
|
||||
"y_log_allowed": bool(axes.y_log_allowed),
|
||||
"x_log_allowed": bool(axes.x_log_allowed),
|
||||
}
|
||||
|
||||
|
||||
def _serialize_heatmap(hm) -> dict[str, Any]:
|
||||
y = np.asarray(hm.y, dtype=float)
|
||||
z = np.asarray(hm.z, dtype=np.float32)
|
||||
return {
|
||||
"x": _numbers(hm.x),
|
||||
"y": _numbers(y),
|
||||
"z": [[float(v) for v in row] for row in z.tolist()],
|
||||
"z_min": float(hm.z_min),
|
||||
"z_max": float(hm.z_max),
|
||||
"cmap": hm.cmap,
|
||||
"label": hm.label,
|
||||
# Row spacing is uniform in frequency; sending it lets the client address the
|
||||
# image in Hz (draw the raster at y0 + k*dy) instead of in row indices, which
|
||||
# is what makes a log y-axis possible without resampling server-side.
|
||||
"y0": float(y[0]) if y.size else 0.0,
|
||||
"dy": float(y[1] - y[0]) if y.size > 1 else 1.0,
|
||||
"deg": False, # z is already dB or dBFS, never angle
|
||||
}
|
||||
|
||||
|
||||
def serialize_spec(spec: PlotSpec) -> dict[str, Any]:
|
||||
"""One dataset, one metric, ready to draw."""
|
||||
payload = {
|
||||
"title": spec.title,
|
||||
"axes": _serialize_axes(spec.axes),
|
||||
"hlines": [
|
||||
{
|
||||
"y": float(hl.y),
|
||||
"label": hl.label,
|
||||
"color": hl.color,
|
||||
"style": hl.style,
|
||||
"width": float(hl.width),
|
||||
}
|
||||
for hl in spec.hlines
|
||||
],
|
||||
"annotations": list(spec.annotations),
|
||||
"segments": [],
|
||||
"series": [],
|
||||
"heatmap": None,
|
||||
"y_bounds": None,
|
||||
}
|
||||
|
||||
for band in spec.bands:
|
||||
lo = np.broadcast_to(np.asarray(band.lo, dtype=float), np.asarray(band.x).shape)
|
||||
payload["segments"].append({
|
||||
"kind": "band",
|
||||
"x": _numbers(band.x),
|
||||
"lo": _numbers(lo),
|
||||
"hi": _numbers(band.hi),
|
||||
"label": band.label,
|
||||
"color": band.color,
|
||||
})
|
||||
|
||||
for curve in spec.curves:
|
||||
payload["series"].append({
|
||||
"kind": "line",
|
||||
"x": _numbers(curve.x),
|
||||
"y": _numbers(curve.y),
|
||||
"label": curve.label,
|
||||
"width": float(curve.width),
|
||||
"color": curve.color,
|
||||
})
|
||||
|
||||
if spec.heatmap is not None:
|
||||
payload["heatmap"] = _serialize_heatmap(spec.heatmap)
|
||||
|
||||
# Value range the browser should frame to, before any user zoom. For bands the
|
||||
# envelope is lo..hi, not just hi — RMS fills from zero, waveform spans ±peak.
|
||||
values = [np.asarray(c.y, dtype=float) for c in spec.curves]
|
||||
for band in spec.bands:
|
||||
values.append(np.asarray(band.lo, dtype=float))
|
||||
values.append(np.asarray(band.hi, dtype=float))
|
||||
if not spec.axes.y_range:
|
||||
finite = [v[np.isfinite(v)] for v in values]
|
||||
finite = [v for v in finite if v.size]
|
||||
if finite:
|
||||
payload["y_bounds"] = [float(min(v.min() for v in finite)),
|
||||
float(max(v.max() for v in finite))]
|
||||
return payload
|
||||
|
||||
|
||||
def serialize_view(view: ViewState) -> dict[str, Any]:
|
||||
return {"y_log": view.y_log, "x_log": view.x_log, "x_mode": view.x_mode}
|
||||
|
||||
|
||||
def serialize_ref_lines(lines: list[RefLineProps]) -> list[dict[str, Any]]:
|
||||
return [
|
||||
{"value": float(l.value), "color": l.color, "style": l.style, "label": l.label}
|
||||
for l in lines
|
||||
]
|
||||
|
||||
|
||||
def relative_x_mode(view: ViewState) -> bool:
|
||||
return view.x_mode == X_RELATIVE
|
||||
+6
-44
@@ -7,12 +7,10 @@ name = "uj-mastering-master"
|
||||
version = "0.1.0"
|
||||
requires-python = ">=3.10"
|
||||
|
||||
# Only what the *analysis* needs. The GUI stack lives in the `desktop` extra
|
||||
# below, because nothing on the web path touches it: `webapp.py`,
|
||||
# `web_session.py`, `metrics_json.py`, `master_core.py`, `metrics.py` and
|
||||
# `plotspec.py` import no Qt, no pyqtgraph and no matplotlib canvas. Keeping
|
||||
# PyQt5 here would force a `--headless`-style install to drag in a full Qt
|
||||
# stack it never loads.
|
||||
# What the *analysis* needs. The GUI stack lives in the `desktop` extra below.
|
||||
# The web UI (web/) is a static site that analyses audio in the browser and needs
|
||||
# none of these; `tests/parity` uses them to check the browser port against
|
||||
# `metrics.py`.
|
||||
dependencies = [
|
||||
"librosa",
|
||||
"numpy",
|
||||
@@ -34,30 +32,16 @@ desktop = [
|
||||
"pyqtgraph>=0.14.0",
|
||||
]
|
||||
|
||||
# Web front end. Installed with:
|
||||
# uv sync --extra web
|
||||
# Deliberately separate from the desktop path: a server install of the web UI
|
||||
# needs no Qt/wheel stack. Which is what makes the container image small and
|
||||
# lets it run without a display server at all.
|
||||
web = [
|
||||
"fastapi>=0.110",
|
||||
"uvicorn[standard]>=0.27",
|
||||
"python-multipart>=0.0.9", # multipart upload parsing for FastAPI
|
||||
]
|
||||
|
||||
[tool.uv]
|
||||
# Note: `default-groups` cannot name an entry from `[project.optional-dependencies]`
|
||||
# — it only accepts `[dependency-groups]` names, and errors with "Default group
|
||||
# `desktop` ... is not defined in the project's `dependency-groups` table".
|
||||
# Extras must be requested explicitly, which is why the README spells out both:
|
||||
# uv sync # analysis + nothing else
|
||||
# Extras must be requested explicitly:
|
||||
# uv sync # analysis only
|
||||
# uv sync --extra desktop # + Qt/pyqtgraph (the GUI; `uv run ujm`)
|
||||
# uv sync --extra web # + fastapi/uvicorn (`uv run ujm-web`)
|
||||
# uv sync --all-extras # both
|
||||
|
||||
[project.scripts]
|
||||
ujm = "main:main"
|
||||
ujm-web = "webapp:main"
|
||||
|
||||
[tool.setuptools]
|
||||
py-modules = [
|
||||
@@ -72,26 +56,4 @@ py-modules = [
|
||||
"ref_line_widget",
|
||||
"logger_setup",
|
||||
"setup_fonts",
|
||||
# web front end
|
||||
"webapp",
|
||||
"web_session",
|
||||
"metrics_json",
|
||||
]
|
||||
# `static/` is declared a *package* so `package-data` has something to attach
|
||||
# to. `package-data` keys match packages, and top-level `py-modules` are not
|
||||
# packages — so the earlier `"*" = [...]` form silently matched nothing and the
|
||||
# built wheel contained no assets at all (verified: 14 .py files, zero HTML/
|
||||
# JS/CSS). An installed `ujm-web` therefore 404'd every asset. With this entry
|
||||
# the assets install to `site-packages/static/`, which is exactly where
|
||||
# `webapp.py` looks (`Path(__file__).parent / "static"`).
|
||||
packages = ["static"]
|
||||
|
||||
[tool.setuptools.package-data]
|
||||
# Vendored browser assets: uPlot (curves), no CDN at runtime. Keyed on the
|
||||
# `static` package (declared above) rather than `"*"`: a `"*"` key matches
|
||||
# *packages*, and there are none besides `static` — the app modules are
|
||||
# top-level `py-modules`, which is why the original form shipped nothing.
|
||||
#
|
||||
# `**/*` rather than `*` so the glob reaches `static/vendor/`, where the uPlot
|
||||
# bundle lives.
|
||||
static = ["*", "**/*"]
|
||||
|
||||
@@ -1,84 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Generate the audio fixtures `webapi_smoke.py` expects.
|
||||
|
||||
Synthesised rather than downloaded so the smoke test has no network dependency
|
||||
and no external tools — `soundfile` and `numpy` come in with `librosa`, so this
|
||||
runs in the container image as-is (no ffmpeg needed).
|
||||
|
||||
sine440.wav 12 s, 440 Hz, stereo, -12 dBFS — a known-tone reference
|
||||
pinknoise.wav 8 s, pink noise, stereo — broadband, exercises the STFT
|
||||
tagged.mp3 a tagged file — only if ffmpeg is available
|
||||
|
||||
Usage: python3 scripts/make_fixtures.py [output_dir] (default /tmp/ujm-test)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import shutil
|
||||
import subprocess
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
import numpy as np
|
||||
import soundfile as sf
|
||||
|
||||
SR = 44100
|
||||
|
||||
|
||||
def sine(path: Path, seconds: float = 12.0, hz: float = 440.0,
|
||||
dbfs: float = -12.0) -> None:
|
||||
"""A tone at a known level. Peak is exactly 10**(dbfs/20) before encoding."""
|
||||
t = np.arange(int(seconds * SR)) / SR
|
||||
mono = (10 ** (dbfs / 20)) * np.sin(2 * np.pi * hz * t)
|
||||
sf.write(path, np.stack([mono, mono], axis=1), SR, subtype="PCM_16")
|
||||
|
||||
|
||||
def pink(path: Path, seconds: float = 8.0, peak: float = 0.25) -> None:
|
||||
"""Pink noise via 1/sqrt(f) shaping, normalised to a known peak."""
|
||||
rng = np.random.default_rng(7)
|
||||
n = int(seconds * SR)
|
||||
spectrum = np.fft.rfft(rng.standard_normal(n))
|
||||
freqs = np.fft.rfftfreq(n, 1 / SR)
|
||||
freqs[0] = freqs[1] # avoid dividing by zero at DC
|
||||
shaped = np.fft.irfft(spectrum / np.sqrt(freqs), n)
|
||||
mono = peak * shaped / np.max(np.abs(shaped))
|
||||
sf.write(path, np.stack([mono, mono], axis=1), SR, subtype="PCM_16")
|
||||
|
||||
|
||||
def tagged_mp3(path: Path) -> bool:
|
||||
"""An MP3 with ID3 tags, so the tag-reading path is exercised.
|
||||
|
||||
Genuinely optional: MP3 encoding is the one thing numpy cannot do, so this
|
||||
needs ffmpeg and is skipped when it is absent. The suite's tag assertions
|
||||
adapt — see `webapi_smoke.py`.
|
||||
"""
|
||||
if shutil.which("ffmpeg") is None:
|
||||
return False
|
||||
subprocess.run(
|
||||
["ffmpeg", "-y", "-loglevel", "error",
|
||||
"-f", "lavfi", "-i", "sine=frequency=330:duration=6:sample_rate=44100",
|
||||
"-metadata", "artist=Test Artist", "-metadata", "title=Test Title",
|
||||
"-codec:a", "libmp3lame", "-q:a", "2", str(path)],
|
||||
check=True,
|
||||
)
|
||||
return True
|
||||
|
||||
|
||||
def main() -> int:
|
||||
out = Path(sys.argv[1] if len(sys.argv) > 1 else "/tmp/ujm-test")
|
||||
out.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
sine(out / "sine440.wav")
|
||||
pink(out / "pinknoise.wav")
|
||||
mp3 = tagged_mp3(out / "テスト.mp3")
|
||||
|
||||
for f in sorted(out.iterdir()):
|
||||
print(f" {f.name} {f.stat().st_size / 1024:.0f} KiB")
|
||||
if not mp3:
|
||||
print("\nnote: no ffmpeg, so no tagged MP3 fixture was written "
|
||||
"(tag assertions will be skipped)")
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
@@ -1,355 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""End-to-end check of the web API against a running server.
|
||||
|
||||
Not a unit test — it drives the real HTTP surface with real audio and asserts on
|
||||
the contract the browser depends on:
|
||||
|
||||
* every registered metric returns a drawable payload (curves or a heatmap)
|
||||
* the numbers agree with an independent computation (librosa RMS, sample peak)
|
||||
* view toggles (lin/log, absolute/relative) never change the underlying data
|
||||
* **no audio is written to the host**: uploads are spooled to temp, and neither
|
||||
an application directory nor a temp file survives the request
|
||||
* overlay, metadata, delete and error paths behave
|
||||
|
||||
Usage: python3 scripts/webapi_smoke.py [base_url] [audio_dir]
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import glob
|
||||
import hashlib
|
||||
import json
|
||||
import math
|
||||
import os
|
||||
import sys
|
||||
import tempfile
|
||||
import time
|
||||
import urllib.error
|
||||
import urllib.parse
|
||||
import urllib.request
|
||||
from pathlib import Path
|
||||
|
||||
BASE = sys.argv[1] if len(sys.argv) > 1 else "http://127.0.0.1:8137"
|
||||
AUDIO = Path(sys.argv[2] if len(sys.argv) > 2 else "/tmp/ujm-test")
|
||||
|
||||
PASS, FAIL = [], []
|
||||
|
||||
|
||||
def check(name: str, ok: bool, detail: str = "") -> None:
|
||||
(PASS if ok else FAIL).append(name + (f" — {detail}" if detail else ""))
|
||||
print(f"{'PASS' if ok else 'FAIL'} {name}{' — ' + detail if detail else ''}")
|
||||
|
||||
|
||||
def get(path: str, **params) -> dict:
|
||||
url = BASE + path + (("?" + urllib.parse.urlencode(params)) if params else "")
|
||||
with urllib.request.urlopen(url, timeout=600) as res:
|
||||
return json.loads(res.read())
|
||||
|
||||
|
||||
def post(path: str, payload=None, **params) -> dict:
|
||||
url = BASE + path + (("?" + urllib.parse.urlencode(params)) if params else "")
|
||||
data = json.dumps(payload).encode() if payload is not None else b""
|
||||
req = urllib.request.Request(url, data=data, method="POST",
|
||||
headers={"Content-Type": "application/json"})
|
||||
with urllib.request.urlopen(req, timeout=600) as res:
|
||||
return json.loads(res.read())
|
||||
|
||||
|
||||
def put_audio(path: Path, metric: str = "rms_power", file_id: str | None = None) -> dict:
|
||||
"""Send a raw audio body, the way the browser does."""
|
||||
data = path.read_bytes()
|
||||
qs = {"name": path.name, "metric": metric}
|
||||
if file_id:
|
||||
qs["file_id"] = file_id
|
||||
req = urllib.request.Request(
|
||||
f"{BASE}/api/analyse?" + urllib.parse.urlencode(qs), data=data, method="POST",
|
||||
headers={"Content-Type": "application/octet-stream"})
|
||||
with urllib.request.urlopen(req, timeout=900) as res:
|
||||
return json.loads(res.read())
|
||||
|
||||
|
||||
def expect_http_error(fn, code: int, name: str) -> None:
|
||||
try:
|
||||
fn()
|
||||
except urllib.error.HTTPError as exc:
|
||||
check(name, exc.code == code, f"HTTP {exc.code}")
|
||||
except Exception as exc: # noqa: BLE001
|
||||
check(name, False, f"raised {type(exc).__name__}: {exc}")
|
||||
else:
|
||||
check(name, False, "no error raised")
|
||||
|
||||
|
||||
def temp_leftovers() -> list[str]:
|
||||
"""Any ujm- spools sitting in the temp dir (would mean a leak)."""
|
||||
return glob.glob(os.path.join(tempfile.gettempdir(), "ujm-*"))
|
||||
|
||||
|
||||
def main() -> int:
|
||||
files = sorted(AUDIO.glob("*.wav")) + sorted(AUDIO.glob("*.mp3"))
|
||||
if not files:
|
||||
print(f"no audio in {AUDIO}")
|
||||
return 2
|
||||
|
||||
# ---- catalogue, and the promise that there is no server-side audio store ----
|
||||
cat = get("/api/metrics")
|
||||
ids = [m["id"] for m in cat["metrics"]]
|
||||
check("metric catalogue lists all 7 metrics", len(ids) == 7, ", ".join(ids))
|
||||
check("catalogue marks a default", cat["default"] in ids, cat["default"])
|
||||
sess = get("/api/session")
|
||||
check("session advertises client-side audio storage",
|
||||
"client" in sess.get("audio_storage", ""), sess.get("audio_storage", ""))
|
||||
check("session exposes no upload path", "upload_dir" not in sess)
|
||||
|
||||
before = set(temp_leftovers())
|
||||
|
||||
# ---- analysis, one track per request (the browser's model) ----
|
||||
uploads = {}
|
||||
for f in files:
|
||||
res = put_audio(f)
|
||||
uploads[f.name] = res
|
||||
check(f"analyse {f.name} returns a drawable payload",
|
||||
bool(res["payload"]["series"] or res["payload"]["segments"]
|
||||
or res["payload"]["heatmap"]))
|
||||
check(f"analyse {f.name} returns a content-hash id",
|
||||
res["file"]["file_id"] == hashlib.sha256(f.read_bytes()).hexdigest()[:32],
|
||||
res["file"]["file_id"][:12])
|
||||
|
||||
sine = next(r for n, r in uploads.items() if "sine440" in n)
|
||||
noise = next(r for n, r in uploads.items() if "pinknoise" in n)
|
||||
# The tagged MP3 needs an encoder to create, so it may be absent on a machine
|
||||
# without ffmpeg (e.g. the container image). Skip its assertions rather than
|
||||
# failing the suite on a missing fixture — that would be a false alarm.
|
||||
tagged = next((r for r in uploads.values()
|
||||
if r["file"]["song_name"].startswith("Test Artist")), None)
|
||||
|
||||
check("duration read from container", abs(sine["file"]["duration"] - 12.0) < 0.05,
|
||||
f"{sine['file']['duration']}s")
|
||||
check("native sample rate preserved (sr=None)", sine["file"]["sample_rate"] == 44100)
|
||||
if tagged is None:
|
||||
print("SKIP ID3 tag assertions — no tagged MP3 fixture (needs ffmpeg)")
|
||||
else:
|
||||
check("ID3 tags resolve to a song name",
|
||||
tagged["file"]["song_name"] == "Test Artist - Test Title",
|
||||
tagged["file"]["song_name"])
|
||||
check("CJK-containing filename handled",
|
||||
tagged["file"]["name"].endswith(".mp3"), tagged["file"]["name"])
|
||||
check("analysis starts mono, as documented", sine["file"]["channels"] == 1)
|
||||
check("size is reported back to the client", sine["file"]["size_bytes"] > 0,
|
||||
f"{sine['file']['size_bytes']} bytes")
|
||||
|
||||
# ---- the no-persistence guarantee ----
|
||||
after = set(temp_leftovers())
|
||||
check("no spool file survives a completed analysis",
|
||||
not (after - before), ", ".join(sorted(after - before)) or "clean")
|
||||
|
||||
# re-sending the same bytes must hit the cache, not re-decode
|
||||
t0 = time.perf_counter()
|
||||
again = put_audio(Path(AUDIO / "sine440.wav"), metric="waveform")
|
||||
warm = time.perf_counter() - t0
|
||||
check("re-sent bytes keep the same file_id (content addressed)",
|
||||
again["file"]["file_id"] == sine["file"]["file_id"])
|
||||
check("cached metric is served without re-decoding", warm < 3.0, f"{warm:.2f}s")
|
||||
|
||||
# ---- every metric draws, and the client can request it per track ----
|
||||
for mid in ids:
|
||||
# the plot endpoint only renders what has been analysed; analyse this metric
|
||||
# for the sine first, exactly as the UI does on a dropdown change.
|
||||
put_audio(Path(AUDIO / "sine440.wav"), metric=mid)
|
||||
# restrict to the sine so per-metric shape is unambiguous
|
||||
post("/api/overlay", {"file_ids": [sine["file"]["file_id"]]})
|
||||
plot = get("/api/plot", metric=mid, x_mode="absolute")
|
||||
ds = plot["datasets"]
|
||||
if not ds:
|
||||
check(f"metric {mid} returns a dataset", False, "no datasets")
|
||||
continue
|
||||
payload = ds[0]["payload"]
|
||||
has_drawable = bool(payload["series"] or payload["segments"] or payload["heatmap"])
|
||||
x_len = len(payload["series"][0]["x"]) if payload["series"] else (
|
||||
len(payload["segments"][0]["x"]) if payload["segments"] else
|
||||
(len(payload["heatmap"]["x"]) if payload["heatmap"] else 0))
|
||||
check(f"metric {mid} draws", has_drawable and x_len > 1,
|
||||
f"{len(payload['series'])} curves, {len(payload['segments'])} bands, "
|
||||
f"{'heatmap' if payload['heatmap'] else 'no heatmap'}, x={x_len}")
|
||||
if payload["heatmap"]:
|
||||
hm = payload["heatmap"]
|
||||
# TARGET_COLUMNS is a ceiling, not a floor: the hop is whichever is
|
||||
# larger, N_FFT//4 (1024 samples) or len(y)/TARGET_COLUMNS.
|
||||
check("spectrogram respects the 4000-column ceiling",
|
||||
len(hm["x"]) <= 4000 and len(hm["x"]) > 1, f"{len(hm['x'])} columns")
|
||||
check("spectrogram serialises finite dB",
|
||||
hm["z_max"] == 0.0 and hm["z_min"] == -80.0,
|
||||
f"z range {hm['z_min']}..{hm['z_max']}")
|
||||
check("spectrogram ships frequency extent for the client log axis",
|
||||
hm["dy"] > 0 and hm["y0"] > 0, f"y0={hm['y0']:.2f} dy={hm['dy']:.3f}")
|
||||
|
||||
# ---- physics sanity: independent recomputation ----
|
||||
import librosa
|
||||
import numpy as np
|
||||
|
||||
post("/api/overlay", {"file_ids": [sine["file"]["file_id"]]})
|
||||
put_audio(Path(AUDIO / "sine440.wav"), metric="rms_power")
|
||||
y, sr = librosa.load(str(AUDIO / "sine440.wav"), sr=None)
|
||||
y = librosa.to_mono(y)
|
||||
|
||||
rms_plot = get("/api/plot", metric="rms_power")
|
||||
check("isolation left exactly one dataset on the plot",
|
||||
len(rms_plot["datasets"]) == 1, f"{len(rms_plot['datasets'])} datasets")
|
||||
band = rms_plot["datasets"][0]["payload"]["segments"][0]
|
||||
# Reproduce the metric's own framing: librosa.feature.rms at 10 s / 2 s.
|
||||
expected = librosa.feature.rms(y=y, frame_length=10 * sr, hop_length=2 * sr).ravel()
|
||||
reported = np.array([v for v in band["hi"] if v is not None], dtype=float)
|
||||
check("RMS power matches librosa's own RMS frame-for-frame",
|
||||
len(reported) == len(expected)
|
||||
and float(np.max(np.abs(reported - expected))) < 1e-4,
|
||||
f"{len(reported)} frames, max Δ {float(np.max(np.abs(reported - expected))):.2e}")
|
||||
|
||||
put_audio(Path(AUDIO / "sine440.wav"), metric="waveform")
|
||||
wseg = get("/api/plot", metric="waveform")["datasets"][0]["payload"]["segments"][0]
|
||||
# 529200 samples into ~4000 columns: each column spans ~132 samples of a
|
||||
# constant-amplitude sine, so the envelope must *reach* the true peak exactly.
|
||||
check("waveform envelope reaches the true extremes",
|
||||
abs(max(wseg["hi"]) - float(np.max(y))) < 1e-6
|
||||
and abs(min(wseg["lo"]) - float(np.min(y))) < 1e-6,
|
||||
f"hi {max(wseg['hi']):.6f} vs peak {float(np.max(y)):.6f}")
|
||||
|
||||
put_audio(Path(AUDIO / "sine440.wav"), metric="true_peak")
|
||||
tp = get("/api/plot", metric="true_peak")["datasets"][0]["payload"]
|
||||
note = next(n for n in tp["annotations"] if "dBTP" in n)
|
||||
dbtp = float(note.replace("Max:", "").replace("dBTP", "").strip())
|
||||
expected_dbtp = 20 * math.log10(float(np.max(np.abs(y))) + 1e-12)
|
||||
check("true peak matches the sample peak for a 440 Hz tone (no ISP)",
|
||||
abs(dbtp - expected_dbtp) < 0.5,
|
||||
f"api {dbtp:.2f} dBTP vs {expected_dbtp:.2f} dBFS")
|
||||
|
||||
put_audio(Path(AUDIO / "sine440.wav"), metric="lufs")
|
||||
lp = get("/api/plot", metric="lufs")["datasets"][0]["payload"]
|
||||
integrated_line = next((h for h in lp["hlines"] if h["label"].startswith("Integrated:")), None)
|
||||
check("integrated LUFS is drawn as its own labelled reference line",
|
||||
integrated_line is not None,
|
||||
integrated_line["label"] if integrated_line else "missing")
|
||||
lu = float(integrated_line["label"].split(":")[1].split()[0]) if integrated_line else None
|
||||
check("integrated LUFS is sane for a -12 dBFS sine",
|
||||
lu is not None and -50 < lu < 0, f"{lu} LUFS")
|
||||
check("the -14 LUFS streaming target line is present",
|
||||
any(abs(h["y"] + 14.0) < 1e-9 for h in lp["hlines"]))
|
||||
check("LRA is reported", any("LU" in n for n in lp["annotations"]),
|
||||
"; ".join(lp["annotations"]))
|
||||
|
||||
# ---- view toggles must not touch the data ----
|
||||
put_audio(Path(AUDIO / "sine440.wav"), metric="spectrogram")
|
||||
lin = get("/api/plot", metric="spectrogram", y_log="false")
|
||||
log = get("/api/plot", metric="spectrogram", y_log="true")
|
||||
check("y_log toggle only changes the axis flag",
|
||||
lin["datasets"][0]["payload"]["heatmap"]["z"]
|
||||
== log["datasets"][0]["payload"]["heatmap"]["z"])
|
||||
check("y_log=true is reflected in axes",
|
||||
log["axes"]["y_log"] is True and lin["axes"]["y_log"] is False)
|
||||
|
||||
put_audio(Path(AUDIO / "sine440.wav"), metric="rms_power")
|
||||
abs_x = get("/api/plot", metric="rms_power", x_mode="absolute")["datasets"][0]["payload"]["segments"][0]["x"]
|
||||
rel = get("/api/plot", metric="rms_power", x_mode="relative")
|
||||
rel_x = rel["datasets"][0]["payload"]["segments"][0]["x"]
|
||||
check("relative mode normalises x to 0..100",
|
||||
abs(rel_x[0]) < 1e-6 and abs(rel_x[-1] - 100.0) < 1e-6,
|
||||
f"{rel_x[0]:.4f} .. {rel_x[-1]:.4f}")
|
||||
check("relative mode relabels the x axis",
|
||||
rel["axes"]["x_label"] == "Position (%)", rel["axes"]["x_label"])
|
||||
check("relative mode keeps the same sample count", len(abs_x) == len(rel_x),
|
||||
f"{len(abs_x)} vs {len(rel_x)}")
|
||||
|
||||
# ---- caching: a repeat view render must not recompute ----
|
||||
t0 = time.perf_counter()
|
||||
first = get("/api/plot", metric="spectrogram")
|
||||
t_cold = time.perf_counter() - t0
|
||||
t0 = time.perf_counter()
|
||||
second = get("/api/plot", metric="spectrogram")
|
||||
t_warm = time.perf_counter() - t0
|
||||
check("repeat plot render is cache-served and identical",
|
||||
first["datasets"][0]["payload"]["heatmap"]["z"]
|
||||
== second["datasets"][0]["payload"]["heatmap"]["z"],
|
||||
f"cold {t_cold:.2f}s vs warm {t_warm:.2f}s")
|
||||
|
||||
# ---- overlay ----
|
||||
all_ids = [r["file"]["file_id"] for r in uploads.values()]
|
||||
post("/api/overlay", {"file_ids": all_ids})
|
||||
for f in files:
|
||||
put_audio(f, metric="crest_factor")
|
||||
overlay_all = get("/api/plot", metric="crest_factor")
|
||||
check("overlay draws every selected track", len(overlay_all["datasets"]) == len(files),
|
||||
f"{len(overlay_all['datasets'])} datasets")
|
||||
labels = [d["label"] for d in overlay_all["datasets"]]
|
||||
check("each overlay dataset is labelled with its song", all(labels), ", ".join(labels))
|
||||
check("datasets carry a distinct palette slot",
|
||||
len({d["palette_index"] for d in overlay_all["datasets"]}) == len(files))
|
||||
|
||||
post("/api/overlay", {"file_ids": [sine["file"]["file_id"]]})
|
||||
check("narrowing the overlay removes the others",
|
||||
len(get("/api/plot", metric="crest_factor")["datasets"]) == 1)
|
||||
|
||||
post("/api/overlay", {"file_ids": all_ids})
|
||||
spec = get("/api/plot", metric="crest_factor")
|
||||
check("crest factor overlays all tracks (unlike the heatmap)",
|
||||
len(spec["datasets"]) == len(files), f"{len(spec['datasets'])} datasets")
|
||||
spec = get("/api/plot", metric="spectrogram")
|
||||
check("spectrogram sends one track at a time",
|
||||
len(spec["datasets"]) == 1 and bool(spec["warnings"]),
|
||||
spec["warnings"][0] if spec["warnings"] else "no warning")
|
||||
|
||||
# a metric not yet computed for a track is reported, not silently skipped
|
||||
post("/api/overlay", {"file_ids": all_ids})
|
||||
plot = get("/api/plot", metric="psr")
|
||||
unresolved = [w for w in plot["warnings"] if "not computed yet" in w]
|
||||
check("un-analysed metrics are flagged rather than faked",
|
||||
len(unresolved) >= 1 or len(plot["datasets"]) >= 1,
|
||||
f"{len(unresolved)} pending, {len(plot['datasets'])} ready")
|
||||
|
||||
# ---- reference lines ----
|
||||
refs = json.dumps([{"value": -14, "label": "target", "color": "#ff0000", "style": "dash"}])
|
||||
withrefs = get("/api/plot", metric="rms_power", refs=refs)
|
||||
check("reference lines round-trip",
|
||||
withrefs["refs"][0]["value"] == -14.0 and withrefs["refs"][0]["label"] == "target")
|
||||
badrefs = get("/api/plot", metric="rms_power", refs=json.dumps([{"nope": 1}]))
|
||||
check("malformed reference entries are dropped, not fatal", badrefs["refs"] == [])
|
||||
|
||||
# ---- metadata endpoint ----
|
||||
meta = get("/api/metadata", file_id=sine["file"]["file_id"])
|
||||
check("metadata endpoint returns the snapshot",
|
||||
meta["file_id"] == sine["file"]["file_id"]
|
||||
and meta["name"] == sine["file"]["name"], meta["name"])
|
||||
|
||||
# ---- error paths ----
|
||||
expect_http_error(lambda: get("/api/plot", metric="not_a_metric"), 400,
|
||||
"unknown metric rejected")
|
||||
expect_http_error(lambda: get("/api/metadata", file_id="0" * 32), 404,
|
||||
"unknown track rejected")
|
||||
expect_http_error(lambda: post("/api/overlay", {"file_ids": "nope"}), 400,
|
||||
"overlay requires a list")
|
||||
expect_http_error(
|
||||
lambda: urllib.request.urlopen(urllib.request.Request(
|
||||
f"{BASE}/api/analyse?name=evil.exe&metric=rms_power", data=b"xx", method="POST"),
|
||||
timeout=30), 400, "unsupported extension rejected")
|
||||
|
||||
# ---- delete ----
|
||||
post("/api/overlay", {"file_ids": [noise["file"]["file_id"]]})
|
||||
deleted = json.loads(urllib.request.urlopen(urllib.request.Request(
|
||||
f"{BASE}/api/file?" + urllib.parse.urlencode({"file_id": noise["file"]["file_id"]}),
|
||||
method="DELETE"), timeout=60).read())
|
||||
check("delete forgets the track", noise["file"]["file_id"] not in deleted["overlay"])
|
||||
check("delete explains the audio is still the client's",
|
||||
"browser" in deleted["note"], deleted["note"])
|
||||
check("deleted track is gone from the session",
|
||||
not any(f["file_id"] == noise["file"]["file_id"]
|
||||
for f in get("/api/session")["files"]))
|
||||
|
||||
final = set(temp_leftovers())
|
||||
check("temp dir holds no spool after the whole suite", not (final - before),
|
||||
", ".join(sorted(final - before)) or "clean")
|
||||
|
||||
print(f"\n{len(PASS)} passed, {len(FAIL)} failed")
|
||||
for f in FAIL:
|
||||
print(" FAILED:", f)
|
||||
return 1 if FAIL else 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -1,11 +0,0 @@
|
||||
"""Packaging shim — not an importable Python module.
|
||||
|
||||
`static/` holds the web UI's browser assets (HTML, JS, CSS, vendored uPlot).
|
||||
It is declared as a setuptools *package* purely so `[tool.setuptools.package-data]`
|
||||
has a package to attach the assets to. Without this file the directory is not a
|
||||
package, `package-data` matches nothing, and the built wheel ships without any
|
||||
assets at all — leaving an installed `ujm-web` serving 404s for every file.
|
||||
|
||||
Nothing imports it. `webapp.py` reads the directory from disk via
|
||||
`Path(__file__).parent / "static"`, so the empty module has no runtime role.
|
||||
"""
|
||||
-1157
File diff suppressed because it is too large
Load Diff
@@ -1,187 +0,0 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
// Browser-side audio store.
|
||||
//
|
||||
// Uploaded audio never lives on the server. The File handle from the picker (or
|
||||
// drop) is copied into Origin Private File System — a sandboxed, per-origin
|
||||
// filesystem the browser owns, which no other site can read and which the OS
|
||||
// treats as browser cache, not user data. Everything downstream is driven from
|
||||
// there:
|
||||
//
|
||||
// * playback reads a blob URL minted from OPFS, so scrubbing a 60 MB WAV
|
||||
// never re-reads the original File
|
||||
// * the SHA-256 that identifies a track is computed over OPFS bytes, so the
|
||||
// id is stable across a reload (the File handle doesn't survive one)
|
||||
// * re-analysis after a page reload re-streams from OPFS instead of asking the
|
||||
// user to pick the file again
|
||||
//
|
||||
// The server only ever sees the bytes it needs for one request, spooled to a
|
||||
// temp file and deleted before the response is written.
|
||||
|
||||
const OPFS_DIR = 'ujm-audio';
|
||||
|
||||
/** True when the browser can give us a durable private store. */
|
||||
export function opfsSupported() {
|
||||
return !!(navigator.storage && navigator.storage.getDirectory);
|
||||
}
|
||||
|
||||
async function dir() {
|
||||
const root = await navigator.storage.getDirectory();
|
||||
return root.getDirectoryHandle(OPFS_DIR, { create: true });
|
||||
}
|
||||
|
||||
/** Human-readable reason the store is unusable, or null when it's fine. */
|
||||
export async function storageProblem(estimateBytes) {
|
||||
if (!opfsSupported()) return 'this browser has no OPFS support';
|
||||
try {
|
||||
const est = await navigator.storage.estimate();
|
||||
if (est.quota && estimateBytes && estimateBytes > est.quota * 0.9) {
|
||||
return `need ~${mb(estimateBytes)} but only ${mb(est.quota - (est.usage || 0))} of browser storage is free`;
|
||||
}
|
||||
// Ask to be exempt from eviction: without this the browser may clear the
|
||||
// store under pressure, and the file is the only copy we have.
|
||||
if (navigator.storage.persist) await navigator.storage.persist();
|
||||
} catch {
|
||||
// estimate() is optional and can throw in private windows; not fatal.
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
function mb(bytes) {
|
||||
return `${(bytes / 1024 / 1024).toFixed(0)} MB`;
|
||||
}
|
||||
|
||||
/**
|
||||
* Copy a File into OPFS under its content hash.
|
||||
*
|
||||
* Returns {fileId, size}. Uses `createWritable` in a single streamed pass so a
|
||||
* large file is never held in memory in full.
|
||||
*/
|
||||
export async function put(file, onProgress) {
|
||||
const d = await dir();
|
||||
const tmpName = `.incoming-${Date.now()}-${Math.random().toString(16).slice(2)}`;
|
||||
const handle = await d.getFileHandle(tmpName, { create: true });
|
||||
|
||||
let written = 0;
|
||||
const writable = await handle.createWritable();
|
||||
try {
|
||||
const reader = file.stream().getReader();
|
||||
for (;;) {
|
||||
const {done, value} = await reader.read();
|
||||
if (done) break;
|
||||
await writable.write(value);
|
||||
written += value.byteLength;
|
||||
if (onProgress) onProgress(written, file.size);
|
||||
}
|
||||
await writable.close();
|
||||
} catch (err) {
|
||||
await writable.abort().catch(() => {});
|
||||
await d.removeEntry(tmpName).catch(() => {});
|
||||
throw err;
|
||||
}
|
||||
|
||||
const hash = await sha256(handle);
|
||||
// Content-addressed: the same audio dropped twice costs one copy, and the id
|
||||
// the server keys its analysis on is reproducible.
|
||||
try {
|
||||
await d.removeEntry(hash);
|
||||
} catch {
|
||||
// first time we've seen these bytes
|
||||
}
|
||||
const named = await rename(d, tmpName, hash);
|
||||
const blob = await named.getFile();
|
||||
return {fileId: hash, size: blob.size, sha256: hash};
|
||||
}
|
||||
|
||||
async function rename(d, from, to) {
|
||||
const fromHandle = await d.getFileHandle(from);
|
||||
const src = await fromHandle.getFile();
|
||||
const toHandle = await d.getFileHandle(to, {create: true});
|
||||
const w = await toHandle.createWritable();
|
||||
await src.stream().pipeTo(w);
|
||||
await d.removeEntry(from);
|
||||
return toHandle;
|
||||
}
|
||||
|
||||
/** SHA-256 of the stored file, read in chunks so memory stays flat. */
|
||||
async function sha256(handle) {
|
||||
const blob = await handle.getFile();
|
||||
const digest = await crypto.subtle.digest('SHA-256', await blob.arrayBuffer());
|
||||
return [...new Uint8Array(digest)]
|
||||
.map((b) => b.toString(16).padStart(2, '0'))
|
||||
.join('')
|
||||
.slice(0, 32);
|
||||
}
|
||||
|
||||
/** The stored File for an id, or null when it isn't here. */
|
||||
export async function get(fileId) {
|
||||
if (!opfsSupported()) return null;
|
||||
try {
|
||||
const d = await dir();
|
||||
const handle = await d.getFileHandle(fileId);
|
||||
return await handle.getFile();
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
export async function has(fileId) {
|
||||
return (await get(fileId)) !== null;
|
||||
}
|
||||
|
||||
export async function remove(fileId) {
|
||||
if (!opfsSupported()) return;
|
||||
try {
|
||||
const d = await dir();
|
||||
await d.removeEntry(fileId);
|
||||
} catch {
|
||||
// already gone
|
||||
}
|
||||
}
|
||||
|
||||
/** Ids currently held, newest touched last — used to prune orphans. */
|
||||
export async function list() {
|
||||
if (!opfsSupported()) return [];
|
||||
const out = [];
|
||||
const d = await dir();
|
||||
for await (const [name] of d.entries()) {
|
||||
if (!name.startsWith('.incoming-')) out.push(name);
|
||||
}
|
||||
return out;
|
||||
}
|
||||
|
||||
/** Drop anything `.incoming-*`, i.e. an upload that died mid-write. */
|
||||
export async function sweepIncomplete() {
|
||||
if (!opfsSupported()) return 0;
|
||||
const d = await dir();
|
||||
let n = 0;
|
||||
for await (const [name] of d.entries()) {
|
||||
if (name.startsWith('.incoming-')) {
|
||||
await d.removeEntry(name).catch(() => {});
|
||||
n += 1;
|
||||
}
|
||||
}
|
||||
return n;
|
||||
}
|
||||
|
||||
/**
|
||||
* Send stored audio to an endpoint as a raw body.
|
||||
*
|
||||
* The OPFS File is passed to fetch as-is: the browser reads a Blob body lazily
|
||||
* from its backing store, so a 200 MB master is never materialised in memory.
|
||||
* (A ReadableStream body with duplex: 'half' was used before, but Chrome only
|
||||
* allows streaming uploads over HTTP/2+, so any file past the old 8 MB cutoff
|
||||
* failed with "Failed to fetch" on HTTP/1.1 — e.g. http://localhost.)
|
||||
*/
|
||||
export async function send(fileId, url, {method = 'POST', onProgress} = {}) {
|
||||
const blob = await get(fileId);
|
||||
if (!blob) throw new Error('audio is no longer in browser storage — re-add the file');
|
||||
|
||||
const res = await fetch(url, {
|
||||
method,
|
||||
headers: {'Content-Type': 'application/octet-stream'},
|
||||
body: blob,
|
||||
});
|
||||
if (onProgress) onProgress(blob.size, blob.size);
|
||||
return res;
|
||||
}
|
||||
@@ -0,0 +1,86 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
"""Synthesise the audio the web-port parity tests run on.
|
||||
|
||||
Aimed at the branches in the metric code rather than at sounding like a song:
|
||||
shorter than each metric's window, digital silence (gated loudness -> -inf /
|
||||
NaN), a passage below the relative gate, int16 / int24 / float WAV, 96 kHz FLAC
|
||||
and stereo downmix. When ffmpeg is on PATH it also writes an ID3-tagged MP3 and
|
||||
Ogg Vorbis / Opus / AAC files for the in-browser decoder checks.
|
||||
|
||||
uv run --no-project --with numpy --with soundfile \
|
||||
python tests/parity/fixtures.py OUT_DIR
|
||||
"""
|
||||
|
||||
import shutil
|
||||
import subprocess
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
import numpy as np
|
||||
import soundfile as sf
|
||||
|
||||
|
||||
def tone_mix(sr: int, seconds: float, seed: int) -> np.ndarray:
|
||||
rng = np.random.default_rng(seed)
|
||||
t = np.arange(int(sr * seconds)) / sr
|
||||
y = (0.3 * np.sin(2 * np.pi * 110 * t)
|
||||
+ 0.15 * np.sin(2 * np.pi * 1760 * t + 0.3)
|
||||
+ 0.05 * rng.standard_normal(len(t)))
|
||||
# Slow level movement so short-term loudness and LRA have something to show.
|
||||
return (y * (0.6 + 0.4 * np.sin(2 * np.pi * 0.07 * t))).astype(np.float32)
|
||||
|
||||
|
||||
def main() -> None:
|
||||
out = Path(sys.argv[1] if len(sys.argv) > 1 else "/tmp/ujm-parity")
|
||||
out.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
sr = 44100
|
||||
left, right = tone_mix(sr, 40, 1), tone_mix(sr, 40, 2) * 0.8
|
||||
for ch in (left, right):
|
||||
ch[10 * sr:15 * sr] = 0.0 # below the absolute gate
|
||||
ch[20 * sr:25 * sr] *= 10 ** (-45 / 20) # below the relative gate
|
||||
left[30 * sr:30 * sr + 2000] = 0.99 # near-full-scale burst for true peak
|
||||
music = out / "music_44k1_s16_stereo.wav"
|
||||
sf.write(music, np.stack([left, right], 1), sr, subtype="PCM_16")
|
||||
|
||||
y = tone_mix(48000, 120, 3)
|
||||
sf.write(out / "long_48k_s24_stereo.wav", np.stack([y, np.roll(y, 480)], 1), 48000, subtype="PCM_24")
|
||||
y = tone_mix(96000, 20, 4)
|
||||
sf.write(out / "hires_96k_s24.flac", np.stack([y, -0.5 * y], 1), 96000, subtype="PCM_24")
|
||||
sf.write(out / "short_1500ms_48k_float.wav", tone_mix(48000, 1.5, 5), 48000, subtype="FLOAT")
|
||||
sf.write(out / "tiny_200ms_44k1_s16.wav", tone_mix(44100, 0.2, 6), 44100, subtype="PCM_16")
|
||||
sf.write(out / "silence_5s_48k_s16.wav", np.zeros(5 * 48000, dtype=np.float32), 48000, subtype="PCM_16")
|
||||
|
||||
# Every PCM layout the browser's direct WAV/AIFF reader handles.
|
||||
y = tone_mix(48000, 4, 7)
|
||||
stereo = np.stack([y, -0.7 * y], 1)
|
||||
sf.write(out / "fmt_s24_48k.wav", stereo, 48000, subtype="PCM_24")
|
||||
sf.write(out / "fmt_s32_48k.wav", stereo, 48000, subtype="PCM_32")
|
||||
sf.write(out / "fmt_f64_48k_mono.wav", y, 48000, subtype="DOUBLE")
|
||||
sf.write(out / "fmt_u8_22k05_mono.wav", tone_mix(22050, 4, 8), 22050, subtype="PCM_U8")
|
||||
sf.write(out / "fmt_wavex_s24_96k.wav", np.stack([tone_mix(96000, 3, 9)] * 3, 1), 96000,
|
||||
format="WAVEX", subtype="PCM_24")
|
||||
sf.write(out / "fmt_s16_44k1.aiff", stereo[: 44100 * 4], 44100, format="AIFF", subtype="PCM_16")
|
||||
sf.write(out / "fmt_f32_48k.aifc", stereo, 48000, format="AIFF", subtype="FLOAT")
|
||||
|
||||
if shutil.which("ffmpeg"):
|
||||
encodes = {
|
||||
"tagged_44k1.mp3": ["-codec:a", "libmp3lame", "-b:a", "192k", "-id3v2_version", "3",
|
||||
"-metadata", "artist=ウジ", "-metadata", "title=テスト曲"],
|
||||
"vorbis_44k1.ogg": ["-codec:a", "libvorbis", "-q:a", "5"],
|
||||
"opus_48k.opus": ["-codec:a", "libopus", "-b:a", "128k"],
|
||||
"aac_44k1.m4a": ["-codec:a", "aac", "-b:a", "192k"],
|
||||
}
|
||||
for name, args in encodes.items():
|
||||
try:
|
||||
subprocess.run(["ffmpeg", "-loglevel", "error", "-y", "-i", str(music), *args, str(out / name)],
|
||||
check=True)
|
||||
except subprocess.CalledProcessError as exc:
|
||||
print(f"skipped {name}: ffmpeg failed ({exc.returncode})")
|
||||
|
||||
for f in sorted(out.iterdir()):
|
||||
print(f" {f.name:32s} {f.stat().st_size / 1024:8.0f} KiB")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,103 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
// Parity check: web/dsp.js against the Python metrics.
|
||||
//
|
||||
// reference.py runs metrics.py on each fixture and saves the exact mono signal
|
||||
// it analysed. This feeds that same signal to dsp.js and compares every output
|
||||
// field, so decoder differences are out of the picture.
|
||||
//
|
||||
// node tests/parity/parity.mjs REF_DIR
|
||||
|
||||
import { existsSync, readdirSync, readFileSync } from 'node:fs';
|
||||
import { join } from 'node:path';
|
||||
|
||||
import { COMPUTE } from '../../web/dsp.js';
|
||||
|
||||
// Largest acceptable |js - python| per field. The float64 paths (loudness,
|
||||
// crest, PSR) should agree to ~1e-12; float32 paths (RMS mean, 4x resampling,
|
||||
// spectrogram dB) to ~1e-6. Waveform min/max are exact sample values.
|
||||
const TOLERANCE = {
|
||||
rms_power: { times: 1e-9, rms: 1e-6 },
|
||||
waveform: { times: 1e-9, lo: 0, hi: 0 },
|
||||
lufs: { times: 1e-9, lufs: 1e-6, integrated: 1e-6, lra: 1e-6 },
|
||||
crest_factor: { times: 1e-9, crest_db: 1e-6 },
|
||||
psr: { times: 1e-9, psr: 1e-6 },
|
||||
true_peak: { times: 1e-9, tp_db: 1e-4, integrated_tp_db: 1e-4 },
|
||||
spectrogram: { times: 1e-9, freqs: 1e-6, s_db: 1e-3 },
|
||||
};
|
||||
|
||||
function readF32(path) {
|
||||
const buf = readFileSync(path);
|
||||
return new Float32Array(buf.buffer.slice(buf.byteOffset, buf.byteOffset + buf.byteLength));
|
||||
}
|
||||
|
||||
const isNum = (v) => typeof v === 'number' && Number.isFinite(v);
|
||||
|
||||
function compare(js, py) {
|
||||
const a = ArrayBuffer.isView(js) || Array.isArray(js) ? js : [js];
|
||||
const b = ArrayBuffer.isView(py) || Array.isArray(py) ? py : [py];
|
||||
if (a.length !== b.length) return { error: `length ${a.length} vs ${b.length}` };
|
||||
let max = 0;
|
||||
let at = -1;
|
||||
let nonFinite = 0;
|
||||
for (let i = 0; i < a.length; i++) {
|
||||
const fx = isNum(a[i]);
|
||||
const fy = isNum(b[i]);
|
||||
if (!fx || !fy) {
|
||||
if (fx !== fy) nonFinite++;
|
||||
continue;
|
||||
}
|
||||
const d = Math.abs(a[i] - b[i]);
|
||||
if (d > max) { max = d; at = i; }
|
||||
}
|
||||
return { max, at, nonFinite };
|
||||
}
|
||||
|
||||
const refDir = process.argv[2];
|
||||
if (!refDir) {
|
||||
console.error('usage: node tests/parity/parity.mjs REF_DIR');
|
||||
process.exit(2);
|
||||
}
|
||||
|
||||
let failures = 0;
|
||||
let checked = 0;
|
||||
for (const name of readdirSync(refDir).sort()) {
|
||||
const dir = join(refDir, name);
|
||||
if (!existsSync(join(dir, 'reference.json'))) continue;
|
||||
const ref = JSON.parse(readFileSync(join(dir, 'reference.json'), 'utf8'));
|
||||
const mono = readF32(join(dir, 'mono.f32'));
|
||||
const sr = ref.meta.sr;
|
||||
const memo = {};
|
||||
console.log(`\n${name} (${sr} Hz, ${(mono.length / sr).toFixed(2)} s)`);
|
||||
|
||||
for (const [metricId, expected] of Object.entries(ref.metrics)) {
|
||||
const t0 = performance.now();
|
||||
const got = COMPUTE[metricId](mono, sr, memo);
|
||||
const ms = performance.now() - t0;
|
||||
|
||||
const fields = metricId === 'spectrogram'
|
||||
? { times: expected.times, freqs: expected.freqs, s_db: readF32(join(dir, 'spectrogram.f32')) }
|
||||
: expected;
|
||||
if (metricId === 'spectrogram' && (got.rows !== expected.rows || got.cols !== expected.cols)) {
|
||||
failures++;
|
||||
console.log(` FAIL spectrogram shape ${got.rows}x${got.cols} vs ${expected.rows}x${expected.cols}`);
|
||||
}
|
||||
|
||||
let first = true;
|
||||
for (const [field, py] of Object.entries(fields)) {
|
||||
const tol = TOLERANCE[metricId][field];
|
||||
if (tol === undefined) continue;
|
||||
const r = compare(got[field], py);
|
||||
const ok = !r.error && r.nonFinite === 0 && r.max <= tol;
|
||||
checked++;
|
||||
if (!ok) failures++;
|
||||
const diff = r.error || `max|d| ${r.max.toExponential(2)}${r.nonFinite ? `, ${r.nonFinite} non-finite mismatches` : ''}`;
|
||||
console.log(` ${ok ? 'ok ' : 'FAIL'} ${metricId.padEnd(13)} ${field.padEnd(17)} ${diff.padEnd(24)} tol ${tol}`
|
||||
+ (first ? ` ${ms.toFixed(0)} ms` : ''));
|
||||
first = false;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
console.log(failures ? `\n${failures} of ${checked} fields out of tolerance` : `\nall ${checked} fields within tolerance`);
|
||||
process.exit(failures ? 1 : 0);
|
||||
@@ -0,0 +1,74 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
"""Dump the Python metrics as the reference for the browser port (web/dsp.js).
|
||||
|
||||
Each audio file is loaded exactly as the desktop app loads it
|
||||
(`master_core.AudioFile`); the mono signal the metrics see is written out next
|
||||
to every metric's `compute()` result. `parity.mjs` feeds that same signal to
|
||||
dsp.js, so the comparison isolates the DSP port from decoder differences.
|
||||
|
||||
uv run --no-project --with librosa --with pyloudnorm --with scipy --with mutagen \
|
||||
python tests/parity/reference.py OUT_DIR AUDIO...
|
||||
|
||||
Writes OUT_DIR/<file name>/{mono.f32, reference.json, spectrogram.f32}.
|
||||
"""
|
||||
|
||||
import json
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
import numpy as np
|
||||
|
||||
sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
|
||||
|
||||
from master_core import AudioFile # noqa: E402
|
||||
from metrics import METRICS # noqa: E402
|
||||
|
||||
|
||||
def _jsonable(value):
|
||||
if isinstance(value, np.ndarray):
|
||||
return [float(v) if np.isfinite(v) else None for v in value.astype(np.float64).ravel()]
|
||||
if isinstance(value, (float, np.floating)):
|
||||
return float(value) if np.isfinite(value) else None
|
||||
return value
|
||||
|
||||
|
||||
def main() -> None:
|
||||
out = Path(sys.argv[1])
|
||||
out.mkdir(parents=True, exist_ok=True)
|
||||
for path in sys.argv[2:]:
|
||||
name = Path(path).name
|
||||
try:
|
||||
audio = AudioFile(path)
|
||||
except Exception as exc: # librosa can't read every container the browser can
|
||||
print(f"{name}: skipped ({exc})")
|
||||
continue
|
||||
|
||||
target = out / name
|
||||
target.mkdir(exist_ok=True)
|
||||
audio.y_mono.astype(np.float32).tofile(target / "mono.f32")
|
||||
|
||||
results = {}
|
||||
for metric_id, metric in METRICS.items():
|
||||
data = metric.compute(audio)
|
||||
if metric_id == "spectrogram":
|
||||
s_db = np.ascontiguousarray(data["s_db"], dtype=np.float32)
|
||||
s_db.tofile(target / "spectrogram.f32")
|
||||
results[metric_id] = {
|
||||
"rows": int(s_db.shape[0]), "cols": int(s_db.shape[1]),
|
||||
"times": _jsonable(data["times"]), "freqs": _jsonable(data["freqs"]),
|
||||
"nyquist": float(data["nyquist"]),
|
||||
}
|
||||
else:
|
||||
results[metric_id] = {key: _jsonable(val) for key, val in data.items()}
|
||||
|
||||
meta = {
|
||||
"file": name, "sr": int(audio.sr), "n": int(len(audio.y_mono)),
|
||||
"song_name": audio.song_name,
|
||||
"max_amplitude": float(audio.max_amplitude), "avg_amplitude": float(audio.avg_amplitude),
|
||||
}
|
||||
(target / "reference.json").write_text(json.dumps({"meta": meta, "metrics": results}))
|
||||
print(f"{name}: {audio.sr} Hz, {len(audio.y_mono) / audio.sr:.2f} s, song_name={audio.song_name!r}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -7,38 +7,6 @@ resolution-markers = [
|
||||
"python_full_version < '3.11'",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "annotated-doc"
|
||||
version = "0.0.5"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/5a/8e/38aa427ed5402449e226975b649c5dc73ccadfefeb95e6aecb8f8ea4b6b6/annotated_doc-0.0.5.tar.gz", hash = "sha256:c7e58ce09192557605d8bbd92836d7e1d520ac9580096042c0bfd197efacf1bb", size = 10758, upload-time = "2026-07-28T13:50:58.129Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/3e/30/e900b21425a860e195f32e37657aa1f7c7f2b1bfb26f03ca209b90933c06/annotated_doc-0.0.5-py3-none-any.whl", hash = "sha256:117bac03a25ede5df5440e855b32d556049ca169ead221505badf432fed4b101", size = 5302, upload-time = "2026-07-28T13:50:57.239Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "annotated-types"
|
||||
version = "0.8.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/5f/56/a8120250d128bed162cd73c76d45f6ef9991f3e068f62a8ee060afa3104a/annotated_types-0.8.0.tar.gz", hash = "sha256:13b2beaad985e05e2d6407ee4c4f35590b11f8d693a258a561055cac8f64cab7", size = 15893, upload-time = "2026-07-23T20:16:13.995Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/99/91/8acff4f5e50511b911bbccb72b8628a49c68ce14148cd9f6431094859a90/annotated_types-0.8.0-py3-none-any.whl", hash = "sha256:f072f4d804ea359e4eaf198b1af7a8b0943881a87f31bb764f8bf219bb9419e0", size = 13427, upload-time = "2026-07-23T20:16:12.938Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "4.14.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "exceptiongroup", marker = "python_full_version < '3.11'" },
|
||||
{ name = "idna" },
|
||||
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/61/cc/a381afa6efea9f496eff839d4a6a1aed3bfafc7b3ab4b0d1b243a12573dd/anyio-4.14.2.tar.gz", hash = "sha256:cfa139f3ed1a23ee8f88a145ddb5ac7605b8bbfd8592baacd7ce3d8bb4313c7f", size = 260176, upload-time = "2026-07-12T20:29:07.082Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/da/35/f2287558c17e29fafc8ef3daf819bb9834061cfa43bff8014f7df7f63bdc/anyio-4.14.2-py3-none-any.whl", hash = "sha256:9f505dda5ac9f0c8309b5e8bd445a8c2bf7246f3ce950121e45ea15bc41d1494", size = 125813, upload-time = "2026-07-12T20:29:05.763Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "audioop-lts"
|
||||
version = "0.2.2"
|
||||
@@ -304,15 +272,6 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/db/8f/61959034484a4a7c527811f4721e75d02d653a35afb0b6054474d8185d4c/charset_normalizer-3.4.7-py3-none-any.whl", hash = "sha256:3dce51d0f5e7951f8bb4900c257dad282f49190fdbebecd4ba99bcc41fef404d", size = 61958, upload-time = "2026-04-02T09:28:37.794Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "click"
|
||||
version = "8.5.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/c7/0e/7fa0ef50764b67090eca4114772a2abf8b6148198475e54c660b97caeee6/click-8.5.0.tar.gz", hash = "sha256:ba0d2089de75ea0310e2dde03160e6ca10009947fb95a182f9b54021bb272e34", size = 382235, upload-time = "2026-08-26T13:33:14.56Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/58/50/6c0d534c5f134586a8e1ba4e330569e32f057e33372ae556463212fb4cd3/click-8.5.0-py3-none-any.whl", hash = "sha256:255bc9599cf7748b4b1a446ccc735421bd08a2ae529a8b88597d3de5664ee360", size = 125251, upload-time = "2026-08-26T13:33:12.928Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "colorama"
|
||||
version = "0.4.6"
|
||||
@@ -330,7 +289,7 @@ resolution-markers = [
|
||||
"python_full_version < '3.11'",
|
||||
]
|
||||
dependencies = [
|
||||
{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" } },
|
||||
{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/66/54/eb9bfc647b19f2009dd5c7f5ec51c4e6ca831725f1aea7a993034f483147/contourpy-1.3.2.tar.gz", hash = "sha256:b6945942715a034c671b7fc54f9588126b0b8bf23db2696e3ca8328f3ff0ab54", size = 13466130, upload-time = "2025-04-15T17:47:53.79Z" }
|
||||
wheels = [
|
||||
@@ -401,7 +360,7 @@ resolution-markers = [
|
||||
"python_full_version >= '3.11' and python_full_version < '3.13'",
|
||||
]
|
||||
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{ url = "https://files.pythonhosted.org/packages/41/63/23572870e01836a98346075b9e17a8bc24a6ddd9800a3204ceee58677f3c/websockets-17.1-py3-none-any.whl", hash = "sha256:f221081107b8c48184d99f7019604486376e7ef826037e70aad6b02540732c23", size = 211134, upload-time = "2026-08-26T17:25:31.397Z" },
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]
|
||||
|
||||
@@ -0,0 +1,49 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
// Analysis worker: the browser's AnalysisResultsManager worker thread.
|
||||
//
|
||||
// Holds each loaded track's mono signal (transferred in, never copied) and runs
|
||||
// one metric at a time on request, so a 10-minute spectrogram never blocks the
|
||||
// page. Everything stays in this tab's memory; closing the tab frees it.
|
||||
//
|
||||
// Messages in: {type: 'load', trackId, mono, sampleRate}
|
||||
// {type: 'compute', reqId, trackId, metricId}
|
||||
// {type: 'drop', trackId}
|
||||
// Messages out: {type: 'result', reqId, trackId, metricId, data, ms}
|
||||
// {type: 'error', reqId, trackId, metricId, message}
|
||||
|
||||
import { COMPUTE, transferables } from './dsp.js';
|
||||
|
||||
const tracks = new Map(); // trackId -> {mono, sampleRate, memo}
|
||||
|
||||
self.onmessage = (event) => {
|
||||
const msg = event.data;
|
||||
if (msg.type === 'load') {
|
||||
tracks.set(msg.trackId, { mono: msg.mono, sampleRate: msg.sampleRate, memo: {} });
|
||||
return;
|
||||
}
|
||||
if (msg.type === 'drop') {
|
||||
tracks.delete(msg.trackId);
|
||||
return;
|
||||
}
|
||||
if (msg.type !== 'compute') return;
|
||||
|
||||
const { reqId, trackId, metricId } = msg;
|
||||
const track = tracks.get(trackId);
|
||||
const compute = COMPUTE[metricId];
|
||||
if (!track || !compute) {
|
||||
self.postMessage({
|
||||
type: 'error', reqId, trackId, metricId,
|
||||
message: track ? `unknown metric ${metricId}` : 'track is no longer loaded',
|
||||
});
|
||||
return;
|
||||
}
|
||||
try {
|
||||
const t0 = performance.now();
|
||||
const data = compute(track.mono, track.sampleRate, track.memo);
|
||||
const ms = performance.now() - t0;
|
||||
self.postMessage({ type: 'result', reqId, trackId, metricId, data, ms }, transferables(data));
|
||||
} catch (err) {
|
||||
self.postMessage({ type: 'error', reqId, trackId, metricId, message: String((err && err.message) || err) });
|
||||
}
|
||||
};
|
||||
@@ -15,7 +15,9 @@
|
||||
--error: #ef5350;
|
||||
--ok: #81c784;
|
||||
--radius: 6px;
|
||||
--mono: ui-monospace, "Cascadia Mono", "Source Code Pro", Menlo, Consolas, monospace;
|
||||
/* M PLUS 1 Code (the desktop app's font) where installed, else the system UI font. */
|
||||
--font: "M PLUS 1 Code", system-ui, -apple-system, "Segoe UI", Roboto, "Noto Sans", sans-serif;
|
||||
--mono: "M PLUS 1 Code", ui-monospace, "Cascadia Mono", "Source Code Pro", Menlo, Consolas, monospace;
|
||||
}
|
||||
|
||||
* { box-sizing: border-box; }
|
||||
@@ -30,7 +32,7 @@ html, body {
|
||||
height: 100%;
|
||||
background: var(--bg);
|
||||
color: var(--text);
|
||||
font: 13px/1.45 system-ui, -apple-system, "Segoe UI", Roboto, "Noto Sans", sans-serif;
|
||||
font: 13px/1.45 var(--font);
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
@@ -154,6 +156,7 @@ select:focus-visible, .btn:focus-visible, .toggle:focus-visible { outline: 2px s
|
||||
text-overflow: ellipsis;
|
||||
font-size: 12px;
|
||||
}
|
||||
.file-lufs { flex: none; font-size: 11px; color: var(--muted); font-variant-numeric: tabular-nums; }
|
||||
.file-remove {
|
||||
flex: none;
|
||||
border: 0;
|
||||
@@ -177,6 +180,8 @@ select:focus-visible, .btn:focus-visible, .toggle:focus-visible { outline: 2px s
|
||||
.metadata dt { color: var(--muted); }
|
||||
.metadata dd { margin: 0; text-align: right; font-variant-numeric: tabular-nums; overflow-wrap: anywhere; }
|
||||
.metadata dd.muted { color: var(--muted); }
|
||||
.metadata .group { margin-top: 7px; }
|
||||
.metadata dd.strong { font-weight: 600; }
|
||||
|
||||
/* ---- reference lines ---- */
|
||||
|
||||
@@ -196,10 +201,7 @@ select:focus-visible, .btn:focus-visible, .toggle:focus-visible { outline: 2px s
|
||||
|
||||
.plot-head { display: flex; align-items: center; justify-content: space-between; gap: 10px; min-height: 24px; }
|
||||
.plot-head h1 { margin: 0; font-size: 13px; font-weight: 600; color: var(--text); }
|
||||
.legend { display: flex; flex-wrap: wrap; gap: 10px; font-size: 11.5px; color: var(--muted); }
|
||||
.legend .item { display: flex; align-items: center; gap: 5px; }
|
||||
.legend .swatch { width: 9px; height: 9px; border-radius: 2px; }
|
||||
.legend .annotation { font-family: var(--mono); color: var(--text); }
|
||||
.plot-hint { font-size: 11px; color: var(--muted); white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
|
||||
|
||||
.plot-host {
|
||||
position: relative;
|
||||
@@ -212,7 +214,30 @@ select:focus-visible, .btn:focus-visible, .toggle:focus-visible { outline: 2px s
|
||||
overflow: hidden;
|
||||
}
|
||||
.plot-host .uplot { position: absolute; inset: 0; width: 100% !important; height: 100% !important; }
|
||||
.plot-host canvas.heatmap { position: absolute; inset: 0; width: 100%; height: 100%; cursor: crosshair; }
|
||||
.plot-host canvas.heatmap { position: absolute; inset: 0; width: 100%; height: 100%; }
|
||||
|
||||
/* In-plot legend, like pyqtgraph's: swatches per track plus scalar readouts.
|
||||
pointer-events: none so zoom and pan work straight through it. */
|
||||
.plot-legend {
|
||||
position: absolute;
|
||||
z-index: 5;
|
||||
pointer-events: none;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 2px;
|
||||
max-width: 46%;
|
||||
padding: 6px 9px;
|
||||
background: rgba(13, 15, 20, .82);
|
||||
border: 1px solid var(--line);
|
||||
border-radius: 4px;
|
||||
font-size: 11.5px;
|
||||
}
|
||||
.plot-legend .entry { display: flex; align-items: center; gap: 7px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
|
||||
.plot-legend .swatch { width: 14px; height: 3px; border-radius: 1px; flex: none; }
|
||||
.plot-legend .note { color: var(--muted); padding-left: 21px; font-variant-numeric: tabular-nums; }
|
||||
|
||||
body.dragging-pan, body.dragging-pan * { cursor: grabbing !important; user-select: none; }
|
||||
body.dragging-ref, body.dragging-ref * { cursor: ns-resize !important; user-select: none; }
|
||||
|
||||
.placeholder {
|
||||
position: absolute;
|
||||
+1481
File diff suppressed because it is too large
Load Diff
+435
@@ -0,0 +1,435 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
// Decode a dropped audio file entirely inside this tab.
|
||||
//
|
||||
// This is the browser counterpart of `master_core.AudioFile.__init__`: tags ->
|
||||
// song name, `librosa.load(sr=None)` -> native-rate samples, `librosa.to_mono`
|
||||
// -> the mono signal every metric reads. Nothing is uploaded or stored: the File
|
||||
// is read into memory, decoded, downmixed, and the compressed bytes and
|
||||
// per-channel buffers are dropped as soon as the mono signal exists.
|
||||
//
|
||||
// Two decode paths:
|
||||
// * WAV and AIFF PCM/float are read directly with libsndfile's sample scaling,
|
||||
// so the signal is bit-identical to what librosa hands the desktop metrics
|
||||
// (Chromium's WAV decoder scales positive int16 by 1/32767, a small but
|
||||
// systematic gain skew; browsers don't decode AIFF at all).
|
||||
// * Everything else goes through decodeAudioData on an OfflineAudioContext
|
||||
// running at the rate sniffed from the container header, so nothing is
|
||||
// resampled — the same "analyse the full band" guarantee as `sr=None`.
|
||||
|
||||
const MIN_CONTEXT_RATE = 3000; // OfflineAudioContext's legal range
|
||||
const MAX_CONTEXT_RATE = 768000;
|
||||
const FALLBACK_RATE = 48000;
|
||||
|
||||
/**
|
||||
* Decode `file` to a mono Float32Array at its native sample rate.
|
||||
*
|
||||
* Returns {name, songName, format, sampleRate, nativeRateKnown, channels,
|
||||
* duration, mono, maxAmplitude, avgAmplitude, size}.
|
||||
*/
|
||||
export async function decodeFile(file) {
|
||||
const bytes = await file.arrayBuffer();
|
||||
const view = new DataView(bytes);
|
||||
|
||||
// Everything that reads the raw bytes must run before decodeAudioData, which
|
||||
// detaches the ArrayBuffer.
|
||||
const format = sniffFormat(view);
|
||||
const tags = format === 'mp3' ? readId3(view) : null;
|
||||
|
||||
let decoded = format === 'wav' || format === 'aiff' ? readPcm(view, format) : null;
|
||||
let nativeRateKnown = true;
|
||||
if (!decoded) {
|
||||
const sniffed = sniffSampleRate(view, format);
|
||||
nativeRateKnown = sniffed !== null && sniffed >= MIN_CONTEXT_RATE && sniffed <= MAX_CONTEXT_RATE;
|
||||
const sampleRate = nativeRateKnown ? sniffed : FALLBACK_RATE;
|
||||
const ctx = new OfflineAudioContext({ numberOfChannels: 1, length: 1, sampleRate });
|
||||
let buffer;
|
||||
try {
|
||||
buffer = await ctx.decodeAudioData(bytes);
|
||||
} catch (err) {
|
||||
throw new Error(`this browser cannot decode ${format || 'this file'} (${err.message || err})`);
|
||||
}
|
||||
decoded = { sampleRate: buffer.sampleRate, channels: buffer.numberOfChannels, mono: bufferToMono(buffer) };
|
||||
}
|
||||
|
||||
const { mono, sampleRate, channels } = decoded;
|
||||
let maxAmplitude = 0;
|
||||
let absSum = 0;
|
||||
for (let i = 0; i < mono.length; i++) {
|
||||
const a = Math.abs(mono[i]);
|
||||
if (a > maxAmplitude) maxAmplitude = a;
|
||||
absSum += a;
|
||||
}
|
||||
|
||||
// Same naming rule as AudioFile: "artist - title" when both tags exist.
|
||||
const songName = tags && tags.artist && tags.title
|
||||
? `${tags.artist} - ${tags.title}`
|
||||
: file.name;
|
||||
|
||||
return {
|
||||
name: file.name,
|
||||
songName,
|
||||
format,
|
||||
sampleRate,
|
||||
nativeRateKnown,
|
||||
channels,
|
||||
duration: mono.length / sampleRate,
|
||||
mono,
|
||||
maxAmplitude,
|
||||
avgAmplitude: mono.length ? absSum / mono.length : 0,
|
||||
size: file.size,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* `librosa.to_mono`: the float32 mean across channels.
|
||||
*
|
||||
* Accumulating in a Float32Array rounds each partial sum to float32 exactly as
|
||||
* numpy's float32 `mean(axis=0)` does, so downmixes match bit for bit.
|
||||
*/
|
||||
function bufferToMono(buffer) {
|
||||
const channels = buffer.numberOfChannels;
|
||||
if (channels === 1) return new Float32Array(buffer.getChannelData(0));
|
||||
const n = buffer.length;
|
||||
const mono = new Float32Array(n);
|
||||
for (let c = 0; c < channels; c++) {
|
||||
const data = buffer.getChannelData(c);
|
||||
for (let i = 0; i < n; i++) mono[i] += data[i];
|
||||
}
|
||||
for (let i = 0; i < n; i++) mono[i] /= channels;
|
||||
return mono;
|
||||
}
|
||||
|
||||
// ---- direct PCM (WAV / AIFF) ------------------------------------------------
|
||||
|
||||
function ascii(view, offset, length) {
|
||||
if (offset < 0 || offset + length > view.byteLength) return '';
|
||||
let s = '';
|
||||
for (let i = 0; i < length; i++) s += String.fromCharCode(view.getUint8(offset + i));
|
||||
return s;
|
||||
}
|
||||
|
||||
/**
|
||||
* A reader for one sample as libsndfile's sf_read_float returns it, or null
|
||||
* for encodings left to the browser decoder.
|
||||
*/
|
||||
function sampleReader(view, encoding, bytesPerSample, littleEndian) {
|
||||
if (encoding === 'int') {
|
||||
switch (bytesPerSample) {
|
||||
case 1: return null; // handled by the caller: WAV is unsigned, AIFF signed
|
||||
case 2: return (p) => view.getInt16(p, littleEndian) / 0x8000;
|
||||
case 3: return littleEndian
|
||||
? (p) => (((view.getUint8(p) | (view.getUint8(p + 1) << 8) | (view.getUint8(p + 2) << 16)) << 8) >> 8) / 0x800000
|
||||
: (p) => (((view.getUint8(p + 2) | (view.getUint8(p + 1) << 8) | (view.getUint8(p) << 16)) << 8) >> 8) / 0x800000;
|
||||
case 4: return (p) => Math.fround(view.getInt32(p, littleEndian)) / 0x80000000;
|
||||
default: return null;
|
||||
}
|
||||
}
|
||||
if (encoding === 'float') {
|
||||
if (bytesPerSample === 4) return (p) => view.getFloat32(p, littleEndian);
|
||||
if (bytesPerSample === 8) return (p) => Math.fround(view.getFloat64(p, littleEndian));
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
/** Interleaved frames -> float32 mono, channel sums in channel order. */
|
||||
function interleavedToMono(view, dataOffset, frames, channels, bytesPerSample, read) {
|
||||
const mono = new Float32Array(frames);
|
||||
const scratch = new Float32Array(1);
|
||||
for (let f = 0; f < frames; f++) {
|
||||
const base = dataOffset + f * channels * bytesPerSample;
|
||||
scratch[0] = 0;
|
||||
for (let c = 0; c < channels; c++) scratch[0] += read(base + c * bytesPerSample);
|
||||
mono[f] = channels === 1 ? scratch[0] : scratch[0] / channels;
|
||||
}
|
||||
return mono;
|
||||
}
|
||||
|
||||
function readPcm(view, format) {
|
||||
return format === 'wav' ? readWav(view) : readAiff(view);
|
||||
}
|
||||
|
||||
function readWav(view) {
|
||||
let fmt = null;
|
||||
let dataOffset = -1;
|
||||
let dataSize = 0;
|
||||
let p = 12;
|
||||
while (p + 8 <= view.byteLength) {
|
||||
const id = ascii(view, p, 4);
|
||||
const size = view.getUint32(p + 4, true);
|
||||
if (id === 'fmt ' && p + 24 <= view.byteLength) {
|
||||
let code = view.getUint16(p + 8, true);
|
||||
// WAVE_FORMAT_EXTENSIBLE: the real format code leads the SubFormat GUID.
|
||||
if (code === 0xfffe && size >= 40 && p + 34 <= view.byteLength) code = view.getUint16(p + 32, true);
|
||||
fmt = {
|
||||
code,
|
||||
channels: view.getUint16(p + 10, true),
|
||||
sampleRate: view.getUint32(p + 12, true),
|
||||
blockAlign: view.getUint16(p + 20, true),
|
||||
};
|
||||
} else if (id === 'data') {
|
||||
dataOffset = p + 8;
|
||||
// Streamed/RF64 files may carry a placeholder size; trust the file length.
|
||||
dataSize = size === 0xffffffff || dataOffset + size > view.byteLength ? view.byteLength - dataOffset : size;
|
||||
break;
|
||||
}
|
||||
p += 8 + size + (size & 1);
|
||||
}
|
||||
if (!fmt || dataOffset < 0 || !fmt.channels || !fmt.blockAlign) return null;
|
||||
|
||||
const bytesPerSample = fmt.blockAlign / fmt.channels;
|
||||
const frames = Math.floor(dataSize / fmt.blockAlign);
|
||||
let read;
|
||||
if (fmt.code === 1 && bytesPerSample === 1) read = (q) => (view.getUint8(q) - 128) / 0x80;
|
||||
else if (fmt.code === 1) read = sampleReader(view, 'int', bytesPerSample, true);
|
||||
else if (fmt.code === 3) read = sampleReader(view, 'float', bytesPerSample, true);
|
||||
if (!read) return null;
|
||||
return {
|
||||
sampleRate: fmt.sampleRate,
|
||||
channels: fmt.channels,
|
||||
mono: interleavedToMono(view, dataOffset, frames, fmt.channels, bytesPerSample, read),
|
||||
};
|
||||
}
|
||||
|
||||
function readAiff(view) {
|
||||
const aifc = ascii(view, 8, 4) === 'AIFC';
|
||||
let comm = null;
|
||||
let dataOffset = -1;
|
||||
let dataSize = 0;
|
||||
let p = 12;
|
||||
while (p + 8 <= view.byteLength) {
|
||||
const id = ascii(view, p, 4);
|
||||
const size = view.getUint32(p + 4, false);
|
||||
if (id === 'COMM' && p + 26 <= view.byteLength) {
|
||||
comm = {
|
||||
channels: view.getUint16(p + 8, false),
|
||||
frames: view.getUint32(p + 10, false),
|
||||
bits: view.getUint16(p + 14, false),
|
||||
sampleRate: aiffRate(view, p + 16),
|
||||
compression: aifc && p + 30 <= view.byteLength ? ascii(view, p + 26, 4) : 'NONE',
|
||||
};
|
||||
} else if (id === 'SSND' && p + 16 <= view.byteLength) {
|
||||
dataOffset = p + 16 + view.getUint32(p + 8, false);
|
||||
dataSize = Math.min(size - 8, view.byteLength - dataOffset);
|
||||
}
|
||||
p += 8 + size + (size & 1);
|
||||
}
|
||||
if (!comm || dataOffset < 0 || !comm.channels) return null;
|
||||
|
||||
const bytesPerSample = Math.ceil(comm.bits / 8);
|
||||
let read = null;
|
||||
const c = comm.compression;
|
||||
if ((c === 'NONE' || c === 'twos') && bytesPerSample === 1) read = (q) => view.getInt8(q) / 0x80;
|
||||
else if (c === 'NONE' || c === 'twos') read = sampleReader(view, 'int', bytesPerSample, false);
|
||||
else if (c === 'sowt') read = sampleReader(view, 'int', bytesPerSample, true);
|
||||
else if (c === 'fl32' || c === 'FL32') read = sampleReader(view, 'float', 4, false);
|
||||
else if (c === 'fl64' || c === 'FL64') read = sampleReader(view, 'float', 8, false);
|
||||
if (!read) return null;
|
||||
|
||||
const width = c.toLowerCase() === 'fl32' ? 4 : c.toLowerCase() === 'fl64' ? 8 : bytesPerSample;
|
||||
const frames = Math.min(comm.frames, Math.floor(dataSize / (width * comm.channels)));
|
||||
return {
|
||||
sampleRate: comm.sampleRate,
|
||||
channels: comm.channels,
|
||||
mono: interleavedToMono(view, dataOffset, frames, comm.channels, width, read),
|
||||
};
|
||||
}
|
||||
|
||||
/** 80-bit IEEE 754 extended float (AIFF COMM sample rate). */
|
||||
function aiffRate(view, q) {
|
||||
const exponent = view.getUint16(q, false) & 0x7fff;
|
||||
const mantissa = view.getUint32(q + 2, false) * 2 ** 32 + view.getUint32(q + 6, false);
|
||||
return Math.round(mantissa * 2 ** (exponent - 16383 - 63));
|
||||
}
|
||||
|
||||
// ---- container sniffing (browser-decoded formats) ---------------------------
|
||||
|
||||
function syncsafe(view, offset) {
|
||||
return ((view.getUint8(offset) & 0x7f) << 21) | ((view.getUint8(offset + 1) & 0x7f) << 14)
|
||||
| ((view.getUint8(offset + 2) & 0x7f) << 7) | (view.getUint8(offset + 3) & 0x7f);
|
||||
}
|
||||
|
||||
/** Byte offset just past a leading ID3v2 tag (0 when there is none). */
|
||||
function skipId3(view) {
|
||||
if (ascii(view, 0, 3) !== 'ID3' || view.byteLength < 10) return 0;
|
||||
const footer = (view.getUint8(5) & 0x10) ? 10 : 0;
|
||||
return 10 + syncsafe(view, 6) + footer;
|
||||
}
|
||||
|
||||
export function sniffFormat(view) {
|
||||
const riff = ascii(view, 0, 4);
|
||||
if ((riff === 'RIFF' || riff === 'RF64') && ascii(view, 8, 4) === 'WAVE') return 'wav';
|
||||
if (riff === 'FORM' && /^AIF[FC]$/.test(ascii(view, 8, 4))) return 'aiff';
|
||||
if (riff === 'OggS') return 'ogg';
|
||||
if (ascii(view, 4, 4) === 'ftyp') return 'mp4';
|
||||
const start = skipId3(view);
|
||||
if (ascii(view, start, 4) === 'fLaC') return 'flac';
|
||||
if (findMpegFrame(view, start) !== null) return 'mp3';
|
||||
return null;
|
||||
}
|
||||
|
||||
export function sniffSampleRate(view, format) {
|
||||
switch (format) {
|
||||
case 'wav': return wavRate(view);
|
||||
case 'aiff': return aiffCommRate(view);
|
||||
case 'flac': return flacRate(view, skipId3(view));
|
||||
case 'mp3': {
|
||||
const frame = findMpegFrame(view, skipId3(view));
|
||||
return frame ? frame.sampleRate : null;
|
||||
}
|
||||
case 'ogg': return oggRate(view);
|
||||
case 'mp4': return mp4Rate(view);
|
||||
default: return null;
|
||||
}
|
||||
}
|
||||
|
||||
function wavRate(view) {
|
||||
let p = 12;
|
||||
while (p + 8 <= view.byteLength) {
|
||||
const id = ascii(view, p, 4);
|
||||
const size = view.getUint32(p + 4, true);
|
||||
if (id === 'fmt ' && p + 16 <= view.byteLength) return view.getUint32(p + 12, true);
|
||||
p += 8 + size + (size & 1);
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
function aiffCommRate(view) {
|
||||
let p = 12;
|
||||
while (p + 8 <= view.byteLength) {
|
||||
const size = view.getUint32(p + 4, false);
|
||||
if (ascii(view, p, 4) === 'COMM' && p + 26 <= view.byteLength) return aiffRate(view, p + 16);
|
||||
p += 8 + size + (size & 1);
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
function flacRate(view, start) {
|
||||
// STREAMINFO is always the first metadata block: 4-byte marker, 4-byte block
|
||||
// header, then 10 bytes of block/frame sizes before the 20-bit sample rate.
|
||||
const q = start + 8 + 10;
|
||||
if (q + 3 > view.byteLength) return null;
|
||||
return (view.getUint8(q) << 12) | (view.getUint8(q + 1) << 4) | (view.getUint8(q + 2) >> 4);
|
||||
}
|
||||
|
||||
const MPEG_RATES = { 3: [44100, 48000, 32000], 2: [22050, 24000, 16000], 0: [11025, 12000, 8000] };
|
||||
const L3_KBPS = {
|
||||
v1: [0, 32, 40, 48, 56, 64, 80, 96, 112, 128, 160, 192, 224, 256, 320],
|
||||
v2: [0, 8, 16, 24, 32, 40, 48, 56, 64, 80, 96, 112, 128, 144, 160],
|
||||
};
|
||||
|
||||
function parseMpegHeader(view, p) {
|
||||
if (p + 4 > view.byteLength) return null;
|
||||
const b1 = view.getUint8(p + 1), b2 = view.getUint8(p + 2);
|
||||
if (view.getUint8(p) !== 0xff || (b1 & 0xe0) !== 0xe0) return null;
|
||||
const version = (b1 >> 3) & 3;
|
||||
const layer = (b1 >> 1) & 3;
|
||||
const bitrateIndex = (b2 >> 4) & 15;
|
||||
const rateIndex = (b2 >> 2) & 3;
|
||||
if (version === 1 || layer === 0 || bitrateIndex === 15 || rateIndex === 3) return null;
|
||||
const sampleRate = MPEG_RATES[version][rateIndex];
|
||||
let frameLength = null;
|
||||
if (layer === 1 && bitrateIndex !== 0) { // Layer III
|
||||
const kbps = (version === 3 ? L3_KBPS.v1 : L3_KBPS.v2)[bitrateIndex];
|
||||
const coeff = version === 3 ? 144 : 72;
|
||||
frameLength = Math.floor((coeff * kbps * 1000) / sampleRate) + ((b2 >> 1) & 1);
|
||||
}
|
||||
return { sampleRate, frameLength };
|
||||
}
|
||||
|
||||
/**
|
||||
* First plausible MPEG audio frame at or after `start`.
|
||||
*
|
||||
* A lone 0xFFE sync pattern is common in arbitrary bytes, so a Layer III frame
|
||||
* is only accepted when another header with the same rate follows at its
|
||||
* computed length.
|
||||
*/
|
||||
function findMpegFrame(view, start) {
|
||||
const limit = Math.min(view.byteLength - 4, start + 64 * 1024);
|
||||
for (let p = start; p < limit; p++) {
|
||||
const head = parseMpegHeader(view, p);
|
||||
if (!head) continue;
|
||||
if (head.frameLength === null) return head;
|
||||
const next = parseMpegHeader(view, p + head.frameLength);
|
||||
if (next && next.sampleRate === head.sampleRate) return head;
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
function oggRate(view) {
|
||||
const segments = view.byteLength > 26 ? view.getUint8(26) : 0;
|
||||
const packet = 27 + segments;
|
||||
if (ascii(view, packet, 7) === '\x01vorbis' && packet + 16 <= view.byteLength) {
|
||||
return view.getUint32(packet + 12, true);
|
||||
}
|
||||
// Opus always decodes at 48 kHz; its header's "input rate" is informational.
|
||||
if (ascii(view, packet, 8) === 'OpusHead') return 48000;
|
||||
return null;
|
||||
}
|
||||
|
||||
function mp4Rate(view) {
|
||||
// Audio sample entries (mp4a/alac/Opus/fLaC) carry a 16.16 fixed-point rate
|
||||
// 32 bytes into the box. moov may sit at the end of the file, so scan it all.
|
||||
const bytes = new Uint8Array(view.buffer, view.byteOffset, view.byteLength);
|
||||
const types = ['mp4a', 'alac', 'Opus', 'fLaC'].map((t) => [...t].map((c) => c.charCodeAt(0)));
|
||||
for (let i = 4; i + 30 < bytes.length; i++) {
|
||||
for (const t of types) {
|
||||
if (bytes[i] === t[0] && bytes[i + 1] === t[1] && bytes[i + 2] === t[2] && bytes[i + 3] === t[3]) {
|
||||
const rate = view.getUint16(i - 4 + 32, false);
|
||||
if (rate >= MIN_CONTEXT_RATE) return rate;
|
||||
}
|
||||
}
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
// ---- ID3 tags ---------------------------------------------------------------
|
||||
|
||||
/** {artist, title} from an ID3v2.2/2.3/2.4 tag (EasyID3's TPE1/TIT2), or null. */
|
||||
export function readId3(view) {
|
||||
if (ascii(view, 0, 3) !== 'ID3' || view.byteLength < 10) return null;
|
||||
const major = view.getUint8(3);
|
||||
const flags = view.getUint8(5);
|
||||
const end = Math.min(10 + syncsafe(view, 6), view.byteLength);
|
||||
let p = 10;
|
||||
if (flags & 0x40) p += major === 4 ? syncsafe(view, 10) : view.getUint32(10, false) + 4;
|
||||
|
||||
const v22 = major === 2;
|
||||
const idLen = v22 ? 3 : 4;
|
||||
const headerLen = v22 ? 6 : 10;
|
||||
const wanted = v22 ? { TT2: 'title', TP1: 'artist' } : { TIT2: 'title', TPE1: 'artist' };
|
||||
const out = {};
|
||||
|
||||
while (p + headerLen <= end) {
|
||||
const id = ascii(view, p, idLen);
|
||||
if (!/^[A-Z0-9]+$/.test(id)) break; // reached padding
|
||||
let size;
|
||||
if (v22) size = (view.getUint8(p + 3) << 16) | (view.getUint8(p + 4) << 8) | view.getUint8(p + 5);
|
||||
else if (major === 4) size = syncsafe(view, p + 4);
|
||||
else size = view.getUint32(p + 4, false);
|
||||
const body = p + headerLen;
|
||||
if (size < 0 || body + size > end) break;
|
||||
if (wanted[id] && size > 1) {
|
||||
const text = decodeId3Text(new Uint8Array(view.buffer, view.byteOffset + body, size));
|
||||
if (text) out[wanted[id]] = text;
|
||||
}
|
||||
p = body + size;
|
||||
}
|
||||
return out;
|
||||
}
|
||||
|
||||
function decodeId3Text(bytes) {
|
||||
const encoding = bytes[0];
|
||||
let data = bytes.subarray(1);
|
||||
let label = 'latin1';
|
||||
if (encoding === 1) {
|
||||
if (data[0] === 0xfe && data[1] === 0xff) { label = 'utf-16be'; data = data.subarray(2); }
|
||||
else { label = 'utf-16le'; if (data[0] === 0xff && data[1] === 0xfe) data = data.subarray(2); }
|
||||
} else if (encoding === 2) {
|
||||
label = 'utf-16be';
|
||||
} else if (encoding === 3) {
|
||||
label = 'utf-8';
|
||||
}
|
||||
// v2.4 separates multiple values with NUL; EasyID3 reports the first.
|
||||
return new TextDecoder(label).decode(data).split('\0')[0].trim();
|
||||
}
|
||||
+694
@@ -0,0 +1,694 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
// Metric computation, ported from `metrics.py` / `master_core.py` to run in the
|
||||
// browser.
|
||||
//
|
||||
// Pure functions over a mono Float32Array at the file's native sample rate — no
|
||||
// DOM, no Web Audio — so the same module runs inside the analysis Web Worker and
|
||||
// under Node for the parity tests (tests/parity), which check every metric
|
||||
// against the Python implementation on identical samples.
|
||||
//
|
||||
// The numerics follow the Python where it matters:
|
||||
// * running sums of squares are sequential float64 sums, like np.cumsum, but
|
||||
// sampled only at the window/block edges that are read — the same values
|
||||
// without an N-length array;
|
||||
// * K-weighting is pyloudnorm's biquad pair run through scipy.signal.lfilter's
|
||||
// direct-form-II-transposed recurrence in float64, streamed sample by sample;
|
||||
// * true peak reproduces scipy.signal.resample_poly(y, 4, 1) — the same 81-tap
|
||||
// Kaiser(beta=5) firwin filter and zero-padded alignment — then an exact
|
||||
// sliding maximum (what maximum_filter1d sampled at window centres yields);
|
||||
// * the spectrogram follows librosa.stft (centred, zero padded, periodic Hann)
|
||||
// and amplitude_to_db(ref=np.max, top_db=80), dropping the DC row.
|
||||
// What remains is float32 rounding where numpy works in float32 (resampling,
|
||||
// RMS, spectrogram dB): far below anything a plot or readout can show.
|
||||
|
||||
const EPS = 1e-12; // keeps 20*log10 finite on perfect silence
|
||||
const LUFS_OFFSET = -0.691; // BS.1770
|
||||
const ABS_GATE = -70.0; // BS.1770 absolute gate
|
||||
const SILENCE_FLOOR = -70.0;
|
||||
|
||||
const toDbfs = (v) => 20 * Math.log10(Math.max(v, EPS));
|
||||
|
||||
/** Number of full windows of `windowN` stepped by `hopN` over `n` samples. */
|
||||
function windowCount(n, windowN, hopN) {
|
||||
return 1 + Math.floor((n - windowN) / hopN);
|
||||
}
|
||||
|
||||
function sampleStream(x) {
|
||||
let i = 0;
|
||||
return () => x[i++];
|
||||
}
|
||||
|
||||
function absStream(x) {
|
||||
let i = 0;
|
||||
return () => Math.abs(x[i++]);
|
||||
}
|
||||
|
||||
function lowerBound(sorted, value) {
|
||||
let lo = 0;
|
||||
let hi = sorted.length;
|
||||
while (lo < hi) {
|
||||
const mid = (lo + hi) >>> 1;
|
||||
if (sorted[mid] < value) lo = mid + 1;
|
||||
else hi = mid;
|
||||
}
|
||||
return lo;
|
||||
}
|
||||
|
||||
/**
|
||||
* csq(i) = sum of x[k]^2 for k < i — np.concatenate(([0], np.cumsum(x * x))) —
|
||||
* at the requested indices only.
|
||||
*
|
||||
* `next()` yields x[0], x[1], ... in order, so a filtered signal can be streamed
|
||||
* straight in. Indices past `n` read csq(n), i.e. a zero-padded tail.
|
||||
*/
|
||||
function prefixSquares(n, next, indexArrays) {
|
||||
let total = 0;
|
||||
for (const a of indexArrays) total += a.length;
|
||||
const marks = new Float64Array(total);
|
||||
let offset = 0;
|
||||
for (const a of indexArrays) {
|
||||
marks.set(a, offset);
|
||||
offset += a.length;
|
||||
}
|
||||
marks.sort();
|
||||
|
||||
const values = new Float64Array(marks.length);
|
||||
let m = 0;
|
||||
while (m < marks.length && marks[m] <= 0) values[m++] = 0;
|
||||
let acc = 0;
|
||||
for (let k = 0; k < n && m < marks.length; k++) {
|
||||
const v = next();
|
||||
acc += v * v;
|
||||
while (m < marks.length && marks[m] === k + 1) values[m++] = acc;
|
||||
}
|
||||
while (m < marks.length) values[m++] = acc;
|
||||
return (index) => values[lowerBound(marks, index)];
|
||||
}
|
||||
|
||||
/**
|
||||
* max(x[s .. s + windowN)) for s = 0, hopN, 2*hopN, ... (`count` windows).
|
||||
*
|
||||
* A monotonic deque: one O(N) pass, O(windowN + hopN) memory, exact maxima.
|
||||
*/
|
||||
function windowMaxima(count, windowN, hopN, next) {
|
||||
const out = new Float64Array(Math.max(count, 0));
|
||||
if (count <= 0) return out;
|
||||
const cap = windowN + hopN + 1;
|
||||
const idx = new Float64Array(cap);
|
||||
const val = new Float64Array(cap);
|
||||
let head = 0;
|
||||
let size = 0;
|
||||
let w = 0;
|
||||
let end = windowN; // exclusive end of window w
|
||||
const last = (count - 1) * hopN + windowN;
|
||||
|
||||
for (let k = 0; k < last; k++) {
|
||||
const v = next();
|
||||
while (size > 0) {
|
||||
let back = head + size - 1;
|
||||
if (back >= cap) back -= cap;
|
||||
if (val[back] <= v) size--;
|
||||
else break;
|
||||
}
|
||||
let pos = head + size;
|
||||
if (pos >= cap) pos -= cap;
|
||||
idx[pos] = k;
|
||||
val[pos] = v;
|
||||
size++;
|
||||
|
||||
if (k + 1 === end) {
|
||||
const start = end - windowN;
|
||||
while (idx[head] < start) {
|
||||
head++;
|
||||
if (head === cap) head = 0;
|
||||
size--;
|
||||
}
|
||||
out[w++] = val[head];
|
||||
if (w === count) break;
|
||||
end += hopN;
|
||||
}
|
||||
}
|
||||
return out;
|
||||
}
|
||||
|
||||
// ---- K-weighting and loudness ------------------------------------------------
|
||||
|
||||
/** pyloudnorm IIRfilter.generate_coefficients, normalised by a0. */
|
||||
function rbjBiquad(type, G, Q, fc, rate) {
|
||||
const A = 10 ** (G / 40.0);
|
||||
const w0 = 2.0 * Math.PI * (fc / rate);
|
||||
const alpha = Math.sin(w0) / (2.0 * Q);
|
||||
let b0, b1, b2, a0, a1, a2;
|
||||
if (type === 'high_shelf') {
|
||||
b0 = A * (A + 1 + (A - 1) * Math.cos(w0) + 2 * Math.sqrt(A) * alpha);
|
||||
b1 = -2 * A * (A - 1 + (A + 1) * Math.cos(w0));
|
||||
b2 = A * (A + 1 + (A - 1) * Math.cos(w0) - 2 * Math.sqrt(A) * alpha);
|
||||
a0 = A + 1 - (A - 1) * Math.cos(w0) + 2 * Math.sqrt(A) * alpha;
|
||||
a1 = 2 * (A - 1 - (A + 1) * Math.cos(w0));
|
||||
a2 = A + 1 - (A - 1) * Math.cos(w0) - 2 * Math.sqrt(A) * alpha;
|
||||
} else if (type === 'high_pass') {
|
||||
b0 = (1 + Math.cos(w0)) / 2;
|
||||
b1 = -(1 + Math.cos(w0));
|
||||
b2 = (1 + Math.cos(w0)) / 2;
|
||||
a0 = 1 + alpha;
|
||||
a1 = -2 * Math.cos(w0);
|
||||
a2 = 1 - alpha;
|
||||
} else {
|
||||
throw new Error(`unsupported filter type ${type}`);
|
||||
}
|
||||
return { b0: b0 / a0, b1: b1 / a0, b2: b2 / a0, a1: a1 / a0, a2: a2 / a0 };
|
||||
}
|
||||
|
||||
/** pyloudnorm Meter(rate) 'K-weighting': high shelf, then high pass. */
|
||||
export function kWeightingCoefficients(rate) {
|
||||
return [
|
||||
rbjBiquad('high_shelf', 4.0, 1 / Math.sqrt(2), 1500.0, rate),
|
||||
rbjBiquad('high_pass', 0.0, 0.5, 38.0, rate),
|
||||
];
|
||||
}
|
||||
|
||||
/**
|
||||
* The K-weighted signal as a stream (metrics._kweight).
|
||||
*
|
||||
* Each stage is scipy's lfilter recurrence — y = z0 + b0*x;
|
||||
* z0 = z1 + x*b1 - y*a1; z1 = x*b2 - y*a2 — in the same operation order, so the
|
||||
* filtered samples match pyloudnorm's whole-array filtering.
|
||||
*/
|
||||
function kWeightedStream(mono, rate) {
|
||||
const [s, p] = kWeightingCoefficients(rate);
|
||||
let i = 0;
|
||||
let sz0 = 0, sz1 = 0, pz0 = 0, pz1 = 0;
|
||||
return () => {
|
||||
const x = mono[i++];
|
||||
const y1 = sz0 + s.b0 * x;
|
||||
sz0 = sz1 + x * s.b1 - y1 * s.a1;
|
||||
sz1 = x * s.b2 - y1 * s.a2;
|
||||
const y2 = pz0 + p.b0 * y1;
|
||||
pz0 = pz1 + y1 * p.b1 - y2 * p.a1;
|
||||
pz1 = y1 * p.b2 - y2 * p.a2;
|
||||
return y2;
|
||||
};
|
||||
}
|
||||
|
||||
/** np.round: round half to even. */
|
||||
function roundHalfEven(x) {
|
||||
const r = Math.round(x);
|
||||
return Math.abs(x % 1) === 0.5 && r % 2 !== 0 ? r - 1 : r;
|
||||
}
|
||||
|
||||
/** Block edges as metrics._block_loudness lays them out, or null when none fit. */
|
||||
function blockEdges(nSignal, sr, blockS, stepPct) {
|
||||
const T = nSignal / sr;
|
||||
const nBlocks = Math.trunc(roundHalfEven((T - blockS) / (blockS * stepPct)) + 1);
|
||||
if (!(nBlocks >= 1)) return null;
|
||||
const lo = new Float64Array(nBlocks);
|
||||
const up = new Float64Array(nBlocks);
|
||||
for (let j = 0; j < nBlocks; j++) {
|
||||
lo[j] = Math.trunc(blockS * (j * stepPct) * sr);
|
||||
up[j] = Math.min(Math.trunc(blockS * (j * stepPct + 1) * sr), nSignal);
|
||||
}
|
||||
return { lo, up, n: nBlocks, divisor: blockS * sr };
|
||||
}
|
||||
|
||||
function blockLoudness(blocks, csq) {
|
||||
const z = new Float64Array(blocks.n);
|
||||
const l = new Float64Array(blocks.n);
|
||||
for (let j = 0; j < blocks.n; j++) {
|
||||
z[j] = (csq(blocks.up[j]) - csq(blocks.lo[j])) / blocks.divisor;
|
||||
l[j] = LUFS_OFFSET + 10.0 * Math.log10(z[j]);
|
||||
}
|
||||
return { z, l };
|
||||
}
|
||||
|
||||
/** metrics._integrated_lufs: two-stage gated mean of the 400 ms blocks. */
|
||||
function gatedIntegrated(z, l) {
|
||||
let sum = 0;
|
||||
let count = 0;
|
||||
for (let j = 0; j < l.length; j++) {
|
||||
if (l[j] >= ABS_GATE) { sum += z[j]; count++; }
|
||||
}
|
||||
if (!count) return -Infinity;
|
||||
const gammaR = LUFS_OFFSET + 10.0 * Math.log10(sum / count) - 10.0;
|
||||
sum = 0;
|
||||
count = 0;
|
||||
for (let j = 0; j < l.length; j++) {
|
||||
if (l[j] > gammaR && l[j] > ABS_GATE) { sum += z[j]; count++; }
|
||||
}
|
||||
if (!count) return -Infinity;
|
||||
return LUFS_OFFSET + 10.0 * Math.log10(sum / count);
|
||||
}
|
||||
|
||||
/** np.percentile(values, q), default 'linear' method, on a sorted array. */
|
||||
function percentileSorted(sorted, q) {
|
||||
const index = (q / 100) * (sorted.length - 1);
|
||||
const lo = Math.floor(index);
|
||||
const hi = Math.min(lo + 1, sorted.length - 1);
|
||||
const t = index - lo;
|
||||
const a = sorted[lo];
|
||||
const b = sorted[hi];
|
||||
return t >= 0.5 ? b - (b - a) * (1 - t) : a + (b - a) * t;
|
||||
}
|
||||
|
||||
/** metrics._loudness_range: EBU Tech 3342 LRA from 3 s block loudness. */
|
||||
function loudnessRange(l) {
|
||||
const absGated = [];
|
||||
for (let j = 0; j < l.length; j++) if (l[j] >= ABS_GATE) absGated.push(l[j]);
|
||||
if (!absGated.length) return NaN;
|
||||
let energy = 0;
|
||||
for (const v of absGated) energy += 10.0 ** (v / 10.0);
|
||||
const stlIntegrated = 10.0 * Math.log10(energy / absGated.length);
|
||||
const rel = Float64Array.from(absGated.filter((v) => v >= stlIntegrated - 20.0));
|
||||
if (!rel.length) return NaN;
|
||||
rel.sort();
|
||||
return percentileSorted(rel, 95) - percentileSorted(rel, 10);
|
||||
}
|
||||
|
||||
/**
|
||||
* Every loudness quantity from one K-weighting pass: the ungated short-term
|
||||
* (3 s / 0.5 s) series, integrated loudness and LRA.
|
||||
*
|
||||
* Memoised on `memo` (the AudioFile attribute caching in Python) so LUFS and PSR
|
||||
* share it. Returned arrays are owned by the memo — callers copy before handing
|
||||
* them out.
|
||||
*/
|
||||
function loudness(mono, sr, memo) {
|
||||
if (memo && memo.loudness) return memo.loudness;
|
||||
const n = mono.length;
|
||||
const windowN = Math.max(Math.trunc(3.0 * sr), 1);
|
||||
const hopN = Math.max(Math.trunc(0.5 * sr), 1);
|
||||
|
||||
const stCount = n >= windowN ? windowCount(n, windowN, hopN) : 0;
|
||||
const stStarts = new Float64Array(stCount);
|
||||
const stEnds = new Float64Array(stCount);
|
||||
for (let i = 0; i < stCount; i++) {
|
||||
stStarts[i] = i * hopN;
|
||||
stEnds[i] = i * hopN + windowN;
|
||||
}
|
||||
const integ = blockEdges(n, sr, 0.4, 0.25);
|
||||
// LRA appends 1.5 s of silence; indices past n read csq(n), which is exactly that.
|
||||
const lraBlocks = blockEdges(n + Math.trunc(1.5 * sr), sr, 3.0, 0.03);
|
||||
|
||||
const wanted = [stStarts, stEnds, Float64Array.of(0, n)];
|
||||
if (integ) wanted.push(integ.lo, integ.up);
|
||||
if (lraBlocks) wanted.push(lraBlocks.lo, lraBlocks.up);
|
||||
const csq = prefixSquares(n, kWeightedStream(mono, sr), wanted);
|
||||
|
||||
let times;
|
||||
let lufs;
|
||||
if (n < windowN) {
|
||||
const ms = n ? csq(n) / n : 0;
|
||||
times = Float64Array.of(n / (2.0 * sr));
|
||||
lufs = Float64Array.of(LUFS_OFFSET + 10.0 * Math.log10(Math.max(ms, EPS)));
|
||||
} else {
|
||||
times = new Float64Array(stCount);
|
||||
lufs = new Float64Array(stCount);
|
||||
for (let i = 0; i < stCount; i++) {
|
||||
const ms = (csq(stEnds[i]) - csq(stStarts[i])) / windowN;
|
||||
lufs[i] = LUFS_OFFSET + 10.0 * Math.log10(Math.max(ms, EPS));
|
||||
times[i] = (stStarts[i] + windowN / 2.0) / sr;
|
||||
}
|
||||
}
|
||||
|
||||
let integrated = -Infinity;
|
||||
if (integ) {
|
||||
const { z, l } = blockLoudness(integ, csq);
|
||||
integrated = gatedIntegrated(z, l);
|
||||
}
|
||||
|
||||
let lra = NaN;
|
||||
if (n >= Math.trunc(3.0 * sr) && lraBlocks) {
|
||||
lra = loudnessRange(blockLoudness(lraBlocks, csq).l);
|
||||
}
|
||||
|
||||
const result = { times, lufs, integrated, lra };
|
||||
if (memo) memo.loudness = result;
|
||||
return result;
|
||||
}
|
||||
|
||||
// ---- metrics -------------------------------------------------------------------
|
||||
|
||||
/** RMSPowerMetric: librosa.feature.rms, 10 s frames / 2 s hop, centred. */
|
||||
export function computeRmsPower(mono, sr, window = 10, hop = 2) {
|
||||
const n = mono.length;
|
||||
const frameLength = window * sr;
|
||||
const hopLength = hop * sr;
|
||||
const half = Math.floor(frameLength / 2);
|
||||
const padded = n + 2 * half;
|
||||
const count = padded >= frameLength ? 1 + Math.floor((padded - frameLength) / hopLength) : 0;
|
||||
|
||||
// Frame i covers padded[i*hop, i*hop + frameLength): the zero padding adds
|
||||
// nothing to the sum but still counts in the mean, as in librosa.
|
||||
const starts = new Float64Array(count);
|
||||
const ends = new Float64Array(count);
|
||||
for (let i = 0; i < count; i++) {
|
||||
const a = i * hopLength - half;
|
||||
starts[i] = Math.min(Math.max(a, 0), n);
|
||||
ends[i] = Math.min(Math.max(a + frameLength, 0), n);
|
||||
}
|
||||
const csq = prefixSquares(n, sampleStream(mono), [starts, ends]);
|
||||
|
||||
const times = new Float64Array(count);
|
||||
const rms = new Float64Array(count);
|
||||
for (let i = 0; i < count; i++) {
|
||||
times[i] = (i * hopLength) / sr;
|
||||
rms[i] = Math.sqrt((csq(ends[i]) - csq(starts[i])) / frameLength);
|
||||
}
|
||||
return { times, rms };
|
||||
}
|
||||
|
||||
/** WaveformMetric: min/max envelope over ~4000 columns. */
|
||||
export function computeWaveform(mono, sr, targetColumns = 4000) {
|
||||
const n = mono.length;
|
||||
if (n <= targetColumns) {
|
||||
const times = new Float64Array(n);
|
||||
for (let i = 0; i < n; i++) times[i] = i / sr;
|
||||
return { times, lo: Float32Array.from(mono), hi: Float32Array.from(mono) };
|
||||
}
|
||||
const chunk = Math.floor(n / targetColumns);
|
||||
const times = new Float64Array(targetColumns);
|
||||
const lo = new Float32Array(targetColumns);
|
||||
const hi = new Float32Array(targetColumns);
|
||||
for (let c = 0; c < targetColumns; c++) {
|
||||
let mn = Infinity;
|
||||
let mx = -Infinity;
|
||||
const base = c * chunk;
|
||||
for (let k = base; k < base + chunk; k++) {
|
||||
const v = mono[k];
|
||||
if (v < mn) mn = v;
|
||||
if (v > mx) mx = v;
|
||||
}
|
||||
lo[c] = mn;
|
||||
hi[c] = mx;
|
||||
times[c] = (c * chunk + chunk / 2) / sr;
|
||||
}
|
||||
return { times, lo, hi };
|
||||
}
|
||||
|
||||
/** LUFSMetric: short-term series clipped to [-70, 0], plus integrated and LRA. */
|
||||
export function computeLufs(mono, sr, memo) {
|
||||
const L = loudness(mono, sr, memo);
|
||||
const lufs = new Float64Array(L.lufs.length);
|
||||
for (let i = 0; i < lufs.length; i++) {
|
||||
const v = Number.isFinite(L.lufs[i]) ? L.lufs[i] : SILENCE_FLOOR;
|
||||
lufs[i] = Math.min(Math.max(v, SILENCE_FLOOR), 0.0);
|
||||
}
|
||||
return { times: L.times.slice(), lufs, integrated: L.integrated, lra: L.lra };
|
||||
}
|
||||
|
||||
/** CrestFactorMetric: 20*log10(peak / RMS) per 1 s window, 0.25 s hop. */
|
||||
export function computeCrestFactor(mono, sr) {
|
||||
const n = mono.length;
|
||||
const windowN = Math.trunc(1.0 * sr);
|
||||
const hopN = Math.trunc(0.25 * sr);
|
||||
|
||||
if (n < windowN) {
|
||||
let peak = 0;
|
||||
let sumSq = 0;
|
||||
for (let i = 0; i < n; i++) {
|
||||
const v = mono[i];
|
||||
if (Math.abs(v) > peak) peak = Math.abs(v);
|
||||
sumSq += v * v;
|
||||
}
|
||||
const rms = n ? Math.sqrt(sumSq / n) : 0;
|
||||
return {
|
||||
times: Float64Array.of(n / (2.0 * sr)),
|
||||
crest_db: Float64Array.of(20.0 * Math.log10(Math.max(peak, EPS) / Math.max(rms, EPS))),
|
||||
};
|
||||
}
|
||||
|
||||
const count = windowCount(n, windowN, hopN);
|
||||
const starts = new Float64Array(count);
|
||||
const ends = new Float64Array(count);
|
||||
for (let i = 0; i < count; i++) {
|
||||
starts[i] = i * hopN;
|
||||
ends[i] = i * hopN + windowN;
|
||||
}
|
||||
const csq = prefixSquares(n, sampleStream(mono), [starts, ends]);
|
||||
const peaks = windowMaxima(count, windowN, hopN, absStream(mono));
|
||||
|
||||
const times = new Float64Array(count);
|
||||
const crest = new Float64Array(count);
|
||||
for (let i = 0; i < count; i++) {
|
||||
const meanSq = (csq(ends[i]) - csq(starts[i])) / windowN;
|
||||
const rms = Math.sqrt(Math.max(meanSq, EPS));
|
||||
crest[i] = 20.0 * Math.log10(Math.max(peaks[i], EPS) / rms);
|
||||
times[i] = (starts[i] + windowN / 2.0) / sr;
|
||||
}
|
||||
return { times, crest_db: crest };
|
||||
}
|
||||
|
||||
/** PSRMetric: sample peak minus short-term LUFS (3 s), NaN below the gate. */
|
||||
export function computePsr(mono, sr, memo) {
|
||||
const n = mono.length;
|
||||
const windowN = Math.max(Math.trunc(3.0 * sr), 1);
|
||||
const hopN = Math.max(Math.trunc(0.5 * sr), 1);
|
||||
const L = loudness(mono, sr, memo);
|
||||
const count = L.times.length;
|
||||
|
||||
let peaksDb;
|
||||
if (n < windowN) {
|
||||
let peak = 0;
|
||||
for (let i = 0; i < n; i++) peak = Math.max(peak, Math.abs(mono[i]));
|
||||
peaksDb = Float64Array.of(n ? toDbfs(peak) : SILENCE_FLOOR);
|
||||
} else {
|
||||
peaksDb = windowMaxima(count, windowN, hopN, absStream(mono)).map(toDbfs);
|
||||
}
|
||||
|
||||
const psr = new Float64Array(count);
|
||||
for (let i = 0; i < count; i++) {
|
||||
const l = L.lufs[i];
|
||||
psr[i] = Number.isFinite(l) && l > SILENCE_FLOOR ? peaksDb[i] - l : NaN;
|
||||
}
|
||||
return { times: L.times.slice(), psr };
|
||||
}
|
||||
|
||||
// ---- true peak -------------------------------------------------------------------
|
||||
|
||||
const OVERSAMPLE = 4;
|
||||
let truePeakTaps = null;
|
||||
|
||||
function besselI0(x) {
|
||||
const q = (x * x) / 4;
|
||||
let term = 1;
|
||||
let sum = 1;
|
||||
for (let k = 1; k < 500; k++) {
|
||||
term *= q / (k * k);
|
||||
sum += term;
|
||||
if (term < 1e-17 * sum) break;
|
||||
}
|
||||
return sum;
|
||||
}
|
||||
|
||||
/**
|
||||
* The anti-imaging filter resample_poly(x, 4, 1) builds for float32 input:
|
||||
* firwin(81, 1/4, window=('kaiser', 5.0)), cast to float32, times 4.
|
||||
*/
|
||||
function truePeakFilter() {
|
||||
if (truePeakTaps) return truePeakTaps;
|
||||
const numtaps = 2 * 10 * OVERSAMPLE + 1;
|
||||
const cutoff = 1.0 / OVERSAMPLE;
|
||||
const beta = 5.0;
|
||||
const alpha = 0.5 * (numtaps - 1);
|
||||
const i0beta = besselI0(beta);
|
||||
const h = new Float64Array(numtaps);
|
||||
let sum = 0;
|
||||
for (let k = 0; k < numtaps; k++) {
|
||||
const m = k - alpha;
|
||||
const x = Math.PI * (m === 0 ? 1e-20 : cutoff * m);
|
||||
const sinc = Math.sin(x) / x;
|
||||
const r = (k - alpha) / alpha;
|
||||
h[k] = cutoff * sinc * (besselI0(beta * Math.sqrt(1 - r * r)) / i0beta);
|
||||
sum += h[k];
|
||||
}
|
||||
truePeakTaps = new Float32Array(numtaps);
|
||||
for (let k = 0; k < numtaps; k++) truePeakTaps[k] = Math.fround(h[k] / sum) * OVERSAMPLE;
|
||||
return truePeakTaps;
|
||||
}
|
||||
|
||||
/**
|
||||
* |resample_poly(x, 4, 1)| as a stream, one output sample per call.
|
||||
*
|
||||
* resample_poly zero-stuffs x, convolves with the taps and keeps outputs
|
||||
* [41, 41 + 4n); output k therefore sums x[s] * h[40 + k - 4s] over the input
|
||||
* samples within the filter's reach — 20 or 21 taps per output.
|
||||
*/
|
||||
function upsampledAbsStream(x, h) {
|
||||
const n = x.length;
|
||||
const half = 10 * OVERSAMPLE;
|
||||
let k = 0;
|
||||
return () => {
|
||||
const q = Math.floor(k / OVERSAMPLE);
|
||||
const r = k - OVERSAMPLE * q;
|
||||
const sLo = Math.max(0, r === 0 ? q - 10 : q - 9);
|
||||
const sHi = Math.min(n - 1, q + 10);
|
||||
let acc = 0;
|
||||
for (let s = sLo; s <= sHi; s++) acc += x[s] * h[half + r + OVERSAMPLE * (q - s)];
|
||||
k++;
|
||||
return Math.abs(Math.fround(acc));
|
||||
};
|
||||
}
|
||||
|
||||
/** TruePeakMetric: 4x oversampled dBTP per 250 ms window, 100 ms hop. */
|
||||
export function computeTruePeak(mono, sr) {
|
||||
const n = mono.length;
|
||||
const windowN = Math.trunc(0.25 * sr);
|
||||
const hopN = Math.trunc(0.1 * sr);
|
||||
const h = truePeakFilter();
|
||||
|
||||
if (n < windowN) {
|
||||
let peak = 0;
|
||||
const next = upsampledAbsStream(mono, h);
|
||||
for (let k = 0; k < n * OVERSAMPLE; k++) peak = Math.max(peak, next());
|
||||
const db = toDbfs(peak);
|
||||
return { times: Float64Array.of(n / (2.0 * sr)), tp_db: Float64Array.of(db), integrated_tp_db: db };
|
||||
}
|
||||
|
||||
const count = windowCount(n, windowN, hopN);
|
||||
const peaks = windowMaxima(count, windowN * OVERSAMPLE, hopN * OVERSAMPLE, upsampledAbsStream(mono, h));
|
||||
const times = new Float64Array(count);
|
||||
const tpDb = new Float64Array(count);
|
||||
let max = -Infinity;
|
||||
for (let i = 0; i < count; i++) {
|
||||
tpDb[i] = toDbfs(peaks[i]);
|
||||
times[i] = (i * hopN + windowN / 2.0) / sr;
|
||||
if (tpDb[i] > max) max = tpDb[i];
|
||||
}
|
||||
return { times, tp_db: tpDb, integrated_tp_db: max };
|
||||
}
|
||||
|
||||
// ---- spectrogram -----------------------------------------------------------------
|
||||
|
||||
const N_FFT = 4096;
|
||||
const SPEC_TARGET_COLUMNS = 4000;
|
||||
const SPEC_DB_FLOOR = -80.0;
|
||||
const fftPlans = new Map();
|
||||
|
||||
/** In-place radix-2 complex FFT for `size` (a power of two). */
|
||||
function fftPlan(size) {
|
||||
if (fftPlans.has(size)) return fftPlans.get(size);
|
||||
const levels = Math.round(Math.log2(size));
|
||||
const rev = new Uint32Array(size);
|
||||
for (let i = 0; i < size; i++) {
|
||||
let r = 0;
|
||||
for (let b = 0; b < levels; b++) r |= ((i >> b) & 1) << (levels - 1 - b);
|
||||
rev[i] = r;
|
||||
}
|
||||
const cos = new Float64Array(size / 2);
|
||||
const sin = new Float64Array(size / 2);
|
||||
for (let i = 0; i < size / 2; i++) {
|
||||
cos[i] = Math.cos((2 * Math.PI * i) / size);
|
||||
sin[i] = Math.sin((2 * Math.PI * i) / size);
|
||||
}
|
||||
const plan = (re, im) => {
|
||||
for (let i = 0; i < size; i++) {
|
||||
const j = rev[i];
|
||||
if (j > i) {
|
||||
let t = re[i]; re[i] = re[j]; re[j] = t;
|
||||
t = im[i]; im[i] = im[j]; im[j] = t;
|
||||
}
|
||||
}
|
||||
for (let len = 2; len <= size; len <<= 1) {
|
||||
const halfLen = len >> 1;
|
||||
const step = size / len;
|
||||
for (let i = 0; i < size; i += len) {
|
||||
for (let j = 0; j < halfLen; j++) {
|
||||
const c = cos[j * step];
|
||||
const s = sin[j * step];
|
||||
const u = i + j;
|
||||
const v = u + halfLen;
|
||||
const tre = re[v] * c + im[v] * s;
|
||||
const tim = im[v] * c - re[v] * s;
|
||||
re[v] = re[u] - tre;
|
||||
im[v] = im[u] - tim;
|
||||
re[u] += tre;
|
||||
im[u] += tim;
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
fftPlans.set(size, plan);
|
||||
return plan;
|
||||
}
|
||||
|
||||
/**
|
||||
* SpectrogramMetric: |STFT| in dB relative to the loudest bin, floored at -80.
|
||||
*
|
||||
* `s_db` is row-major (rows x cols), row 0 the lowest non-DC bin — the same
|
||||
* layout as the Python `s_db[1:, :]`.
|
||||
*/
|
||||
export function computeSpectrogram(mono, sr) {
|
||||
const n = mono.length;
|
||||
const half = N_FFT / 2;
|
||||
const hop = Math.max(N_FFT / 4, Math.floor(n / SPEC_TARGET_COLUMNS));
|
||||
const cols = 1 + Math.floor(n / hop);
|
||||
const rows = half; // bins 1..N_FFT/2
|
||||
|
||||
const window = new Float64Array(N_FFT); // periodic Hann (fftbins=True)
|
||||
for (let j = 0; j < N_FFT; j++) window[j] = 0.5 - 0.5 * Math.cos((2 * Math.PI * j) / N_FFT);
|
||||
|
||||
const fft = fftPlan(N_FFT);
|
||||
const re = new Float64Array(N_FFT);
|
||||
const im = new Float64Array(N_FFT);
|
||||
const sDb = new Float32Array(rows * cols);
|
||||
let maxPower = 0;
|
||||
|
||||
for (let c = 0; c < cols; c++) {
|
||||
// Centred framing: frame c is padded[c*hop, c*hop + N_FFT) with N_FFT/2
|
||||
// zeros either side of the signal.
|
||||
const offset = c * hop - half;
|
||||
for (let j = 0; j < N_FFT; j++) {
|
||||
const t = offset + j;
|
||||
re[j] = t >= 0 && t < n ? mono[t] * window[j] : 0;
|
||||
im[j] = 0;
|
||||
}
|
||||
fft(re, im);
|
||||
const p0 = re[0] * re[0] + im[0] * im[0];
|
||||
if (p0 > maxPower) maxPower = p0;
|
||||
for (let b = 1; b <= half; b++) {
|
||||
const p = re[b] * re[b] + im[b] * im[b];
|
||||
if (p > maxPower) maxPower = p;
|
||||
sDb[(b - 1) * cols + c] = p;
|
||||
}
|
||||
}
|
||||
|
||||
// amplitude_to_db(ref=np.max, amin=1e-5, top_db=80): in power terms
|
||||
// 10*log10(max(1e-10, p)) - 10*log10(max(1e-10, max p)), then clipped to
|
||||
// (maximum - 80). The maximum of that is 0 at the reference bin, so the clip
|
||||
// is a fixed -80 floor.
|
||||
const amin = 1e-5 ** 2;
|
||||
const refDb = 10.0 * Math.log10(Math.max(amin, maxPower));
|
||||
for (let i = 0; i < sDb.length; i++) {
|
||||
sDb[i] = Math.max(10.0 * Math.log10(Math.max(amin, sDb[i])) - refDb, SPEC_DB_FLOOR);
|
||||
}
|
||||
|
||||
const binHz = 1.0 / (N_FFT * (1.0 / sr)); // np.fft.rfftfreq spacing
|
||||
const freqs = new Float64Array(rows);
|
||||
for (let b = 0; b < rows; b++) freqs[b] = (b + 1) * binHz;
|
||||
const times = new Float64Array(cols);
|
||||
for (let c = 0; c < cols; c++) times[c] = (c * hop + half) / sr;
|
||||
|
||||
return { freqs, times, s_db: sDb, rows, cols, nyquist: sr / 2.0 };
|
||||
}
|
||||
|
||||
// ---- registry ----------------------------------------------------------------------
|
||||
|
||||
/** metric id -> compute(mono, sampleRate, memo). `memo` is per track. */
|
||||
export const COMPUTE = {
|
||||
rms_power: (mono, sr) => computeRmsPower(mono, sr),
|
||||
waveform: (mono, sr) => computeWaveform(mono, sr),
|
||||
lufs: (mono, sr, memo) => computeLufs(mono, sr, memo),
|
||||
crest_factor: (mono, sr) => computeCrestFactor(mono, sr),
|
||||
psr: (mono, sr, memo) => computePsr(mono, sr, memo),
|
||||
true_peak: (mono, sr) => computeTruePeak(mono, sr),
|
||||
spectrogram: (mono, sr) => computeSpectrogram(mono, sr),
|
||||
};
|
||||
|
||||
/** The ArrayBuffers inside a computed result, for a zero-copy postMessage. */
|
||||
export function transferables(data) {
|
||||
const buffers = new Set();
|
||||
for (const value of Object.values(data)) {
|
||||
if (ArrayBuffer.isView(value)) buffers.add(value.buffer);
|
||||
}
|
||||
return [...buffers];
|
||||
}
|
||||
@@ -4,8 +4,9 @@
|
||||
<meta charset="utf-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1">
|
||||
<title>Audio Mastering Analysis Toolkit</title>
|
||||
<link rel="stylesheet" href="static/vendor/uPlot.min.css">
|
||||
<link rel="stylesheet" href="static/app.css">
|
||||
<link rel="icon" href="data:,">
|
||||
<link rel="stylesheet" href="vendor/uPlot.min.css">
|
||||
<link rel="stylesheet" href="app.css">
|
||||
</head>
|
||||
<body>
|
||||
|
||||
@@ -28,10 +29,10 @@
|
||||
</select>
|
||||
</label>
|
||||
<button id="toggle-y-log" class="toggle" type="button">Y: log</button>
|
||||
<button id="refresh-plot" class="btn" type="button" title="Redraw from cached data">Refresh</button>
|
||||
<button id="refresh-plot" class="btn" type="button" title="Redraw from the computed results">Refresh</button>
|
||||
<div class="separator"></div>
|
||||
<button id="pick-files" class="btn primary" type="button">Add audio…</button>
|
||||
<input id="file-input" type="file" accept=".mp3,.wav,.flac,.ogg,.oga,.m4a,.aif,.aiff,.opus" multiple hidden>
|
||||
<input id="file-input" type="file" accept=".mp3,.wav,.flac,.ogg,.oga,.m4a,.aif,.aiff,.aifc,.opus" multiple hidden>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
@@ -42,7 +43,7 @@
|
||||
<h2>Files <span id="file-count" class="badge">0</span></h2>
|
||||
<ul id="file-list" class="file-list"></ul>
|
||||
<p id="file-empty" class="empty">Drop audio files here, or use <em>Add audio…</em>.
|
||||
Files are held in this browser, not on the server.</p>
|
||||
They are analysed in this tab and never uploaded.</p>
|
||||
</section>
|
||||
|
||||
<section class="panel">
|
||||
@@ -66,18 +67,19 @@
|
||||
<section class="stage">
|
||||
<div class="plot-head">
|
||||
<h1 id="plot-title">No track loaded</h1>
|
||||
<div id="legend" class="legend"></div>
|
||||
<div class="plot-hint">Scroll to zoom · Ctrl: time only · Shift: values only · drag to pan · double-click to reset</div>
|
||||
</div>
|
||||
|
||||
<div id="plot-host" class="plot-host">
|
||||
<div id="placeholder" class="placeholder">
|
||||
<p class="ph-title">Audio Mastering Analysis Toolkit</p>
|
||||
<p class="ph-body">Drop <code>.mp3</code>, <code>.wav</code> or <code>.flac</code> files to analyse.
|
||||
Audio stays in this browser's private storage; the server receives it
|
||||
only for the moment it takes to compute a metric, and writes nothing to
|
||||
disk. Analysis runs at the file's native sample rate.</p>
|
||||
<p class="ph-body">Drop <code>.wav</code>, <code>.flac</code> or <code>.mp3</code> files to analyse.
|
||||
Decoding and every metric run inside this tab: the audio is never uploaded
|
||||
or saved anywhere (this page isn't even permitted to make network requests),
|
||||
and closing the tab discards it. Analysis runs at the file's native sample rate.</p>
|
||||
</div>
|
||||
<canvas id="heatmap" class="heatmap" hidden></canvas>
|
||||
<div id="plot-legend" class="plot-legend" hidden></div>
|
||||
</div>
|
||||
|
||||
<div class="statusbar">
|
||||
@@ -89,9 +91,9 @@
|
||||
|
||||
<div id="drop-overlay" class="drop-overlay" hidden><span>Drop to analyse</span></div>
|
||||
|
||||
<script src="static/vendor/uPlot.iife.min.js"></script>
|
||||
<!-- app.js is an ES module: it imports ./audio-store.js, which owns the
|
||||
browser-side copy of every uploaded file. -->
|
||||
<script type="module" src="static/app.js"></script>
|
||||
<script src="vendor/uPlot.iife.min.js"></script>
|
||||
<!-- app.js is an ES module: it decodes with decode.js and runs the metrics
|
||||
from dsp.js in analysis-worker.js. -->
|
||||
<script type="module" src="app.js"></script>
|
||||
</body>
|
||||
</html>
|
||||
+184
@@ -0,0 +1,184 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
// Metric registry for the browser: display names and `build_spec` ports.
|
||||
//
|
||||
// Mirrors `metrics.METRICS`. Computation lives in dsp.js and runs in the
|
||||
// analysis worker; `buildSpec` is cheap and runs on the main thread whenever the
|
||||
// view changes, turning computed data into the plot payload the renderer draws —
|
||||
// the same shape `metrics_json.serialize_spec` used to put on the wire:
|
||||
// {axes, hlines, annotations, segments (bands), series (curves), heatmap}.
|
||||
|
||||
const numbers = (arr) => Array.from(arr, (v) => (Number.isFinite(v) ? v : null));
|
||||
const extent = (times) => (times.length ? [times[0], times[times.length - 1]] : null);
|
||||
|
||||
function payload({ axes, bands = [], curves = [], hlines = [], heatmap = null, annotations = [] }) {
|
||||
return {
|
||||
title: '',
|
||||
axes: {
|
||||
x_label: '', y_label: '', y_log: false, x_log: false,
|
||||
y_range: null, x_range: null, y_log_allowed: false, x_log_allowed: false,
|
||||
...axes,
|
||||
},
|
||||
hlines: hlines.map((h) => ({ label: '', color: '#888888', style: 'dot', width: 0.8, ...h })),
|
||||
annotations,
|
||||
segments: bands.map((b) => ({
|
||||
kind: 'band', x: numbers(b.x), lo: numbers(b.lo), hi: numbers(b.hi),
|
||||
label: b.label || '', color: null,
|
||||
})),
|
||||
series: curves.map((c) => ({
|
||||
kind: 'line', x: numbers(c.x), y: numbers(c.y),
|
||||
label: c.label || '', width: c.width ?? 1.4, color: c.color ?? null,
|
||||
})),
|
||||
heatmap,
|
||||
y_bounds: null,
|
||||
};
|
||||
}
|
||||
|
||||
export const METRICS = [
|
||||
{
|
||||
id: 'rms_power',
|
||||
displayName: 'RMS Power',
|
||||
buildSpec(data) {
|
||||
let peak = 0;
|
||||
for (const v of data.rms) if (v > peak) peak = v;
|
||||
// Adaptive headroom: loud masters get a taller scale.
|
||||
const ymax = data.rms.length && peak > 0.3 ? 0.6 : 0.3;
|
||||
return payload({
|
||||
axes: { x_label: 'Time (seconds)', y_label: 'Power', y_range: [0.0, ymax], x_range: extent(data.times) },
|
||||
bands: [{ x: data.times, lo: new Float64Array(data.rms.length), hi: data.rms, label: 'RMS power' }],
|
||||
});
|
||||
},
|
||||
},
|
||||
{
|
||||
id: 'waveform',
|
||||
displayName: 'Waveform',
|
||||
buildSpec(data) {
|
||||
return payload({
|
||||
axes: { x_label: 'Time (seconds)', y_label: 'Amplitude', y_range: [-1.1, 1.1], x_range: extent(data.times) },
|
||||
bands: [{ x: data.times, lo: data.lo, hi: data.hi, label: 'Waveform' }],
|
||||
});
|
||||
},
|
||||
},
|
||||
{
|
||||
id: 'lufs',
|
||||
displayName: 'LUFS',
|
||||
buildSpec(data) {
|
||||
const hlines = [{ y: -14.0, label: '-14 LUFS (streaming target)', style: 'dot' }];
|
||||
const annotations = [];
|
||||
if (Number.isFinite(data.integrated)) {
|
||||
hlines.push({
|
||||
y: data.integrated, label: `Integrated: ${data.integrated.toFixed(1)} LUFS`,
|
||||
color: '#e76f51', style: 'dash', width: 1.5,
|
||||
perTrack: true, // differs per track: coloured by track when overlaid
|
||||
});
|
||||
}
|
||||
if (Number.isFinite(data.lra)) annotations.push(`LRA: ${data.lra.toFixed(1)} LU`);
|
||||
return payload({
|
||||
axes: { x_label: 'Time (seconds)', y_label: 'LUFS', y_range: [-50.0, 0.0], x_range: extent(data.times) },
|
||||
curves: [{ x: data.times, y: data.lufs, label: 'Short-term (3 s)' }],
|
||||
hlines,
|
||||
annotations,
|
||||
});
|
||||
},
|
||||
},
|
||||
{
|
||||
id: 'crest_factor',
|
||||
displayName: 'Crest Factor',
|
||||
buildSpec(data) {
|
||||
return payload({
|
||||
axes: { x_label: 'Time (seconds)', y_label: 'Crest factor (dB)', y_range: [0.0, 25.0], x_range: extent(data.times) },
|
||||
curves: [{ x: data.times, y: data.crest_db, label: 'Crest factor (1 s)' }],
|
||||
hlines: [
|
||||
{ y: 12.0, label: '12 dB', style: 'dot' },
|
||||
{ y: 6.0, label: '6 dB (squashed)', style: 'dot' },
|
||||
],
|
||||
});
|
||||
},
|
||||
},
|
||||
{
|
||||
id: 'psr',
|
||||
displayName: 'PSR',
|
||||
buildSpec(data) {
|
||||
return payload({
|
||||
axes: { x_label: 'Time (seconds)', y_label: 'PSR (LU)', y_range: [0.0, 25.0], x_range: extent(data.times) },
|
||||
curves: [{ x: data.times, y: data.psr, label: 'PSR (3 s)' }],
|
||||
hlines: [
|
||||
{ y: 10.0, label: '10 LU (good punch)', style: 'dot' },
|
||||
{ y: 4.0, label: '4 LU (squashed)', style: 'dot' },
|
||||
],
|
||||
});
|
||||
},
|
||||
},
|
||||
{
|
||||
id: 'true_peak',
|
||||
displayName: 'True Peak',
|
||||
buildSpec(data) {
|
||||
const annotations = [];
|
||||
if (Number.isFinite(data.integrated_tp_db)) annotations.push(`Max: ${data.integrated_tp_db.toFixed(2)} dBTP`);
|
||||
return payload({
|
||||
axes: { x_label: 'Time (seconds)', y_label: 'dBTP', y_range: [-30.0, 6.0], x_range: extent(data.times) },
|
||||
curves: [{ x: data.times, y: data.tp_db, label: 'True Peak (250 ms)', width: 1.0 }],
|
||||
hlines: [
|
||||
{ y: 0.0, label: '0 dBTP (clip)', color: '#000000', style: 'dash', width: 1.0 },
|
||||
{ y: -1.0, label: '-1 dBTP (typical ceiling)', style: 'dot' },
|
||||
],
|
||||
annotations,
|
||||
});
|
||||
},
|
||||
},
|
||||
{
|
||||
id: 'spectrogram',
|
||||
displayName: 'Spectrogram',
|
||||
buildSpec(data, view) {
|
||||
const yLog = view && view.yLog !== null && view.yLog !== undefined ? view.yLog : true;
|
||||
return payload({
|
||||
axes: {
|
||||
x_label: 'Time (seconds)', y_label: 'Frequency (Hz)',
|
||||
y_log: yLog, y_log_allowed: true,
|
||||
y_range: [20.0, data.nyquist], x_range: extent(data.times),
|
||||
},
|
||||
heatmap: {
|
||||
x: Array.from(data.times),
|
||||
y: data.freqs,
|
||||
z: data.s_db, // Float32Array, row-major rows x cols
|
||||
rows: data.rows,
|
||||
cols: data.cols,
|
||||
z_min: -80.0,
|
||||
z_max: 0.0,
|
||||
cmap: 'magma',
|
||||
label: 'Power (dB)',
|
||||
// Rows are uniform in frequency: the renderer addresses them in Hz,
|
||||
// which is what lets it draw a log axis without resampling.
|
||||
y0: data.freqs.length ? data.freqs[0] : 0,
|
||||
dy: data.freqs.length > 1 ? data.freqs[1] - data.freqs[0] : 1,
|
||||
},
|
||||
});
|
||||
},
|
||||
},
|
||||
];
|
||||
|
||||
export const METRIC_BY_ID = Object.fromEntries(METRICS.map((m) => [m.id, m]));
|
||||
export const DEFAULT_METRIC_ID = 'rms_power';
|
||||
|
||||
/**
|
||||
* plotspec.apply_x_mode: rewrite a payload's x values to 0-100 % of the
|
||||
* dataset's own span. A pure view transform — returns a new payload and leaves
|
||||
* the cached one untouched.
|
||||
*/
|
||||
export function applyRelativeX(p) {
|
||||
const xs = [...p.series.map((s) => s.x), ...p.segments.map((s) => s.x)];
|
||||
if (p.heatmap) xs.push(p.heatmap.x);
|
||||
const nonEmpty = xs.filter((x) => x.length);
|
||||
if (!nonEmpty.length) return p;
|
||||
const lo = Math.min(...nonEmpty.map((x) => x[0]));
|
||||
const hi = Math.max(...nonEmpty.map((x) => x[x.length - 1]));
|
||||
const span = hi - lo || 1.0;
|
||||
const rel = (x) => x.map((v) => (v === null ? null : ((v - lo) / span) * 100.0));
|
||||
return {
|
||||
...p,
|
||||
axes: { ...p.axes, x_label: 'Position (%)', x_range: [0.0, 100.0] },
|
||||
series: p.series.map((s) => ({ ...s, x: rel(s.x) })),
|
||||
segments: p.segments.map((s) => ({ ...s, x: rel(s.x) })),
|
||||
heatmap: p.heatmap ? { ...p.heatmap, x: rel(p.heatmap.x) } : null,
|
||||
};
|
||||
}
|
||||
-309
@@ -1,309 +0,0 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
"""
|
||||
Headless analysis service for the web UI.
|
||||
|
||||
This is the server-side equivalent of `AnalysisResultsManager` + its worker
|
||||
threads: it owns the decode-and-compute lifecycle and the per-file metric cache,
|
||||
but it knows nothing about a GUI toolkit. No PyQt import appears in this file or
|
||||
anything it imports — that property is what lets `webapp.py` run under a plain
|
||||
ASGI server on a box with no display.
|
||||
|
||||
## Where the audio lives
|
||||
|
||||
The browser is the store of record. The client keeps every uploaded file in OPFS
|
||||
(origin-private file system) and re-sends the bytes for each analysis request; the
|
||||
server spools them to a temporary file, analyses it, and deletes it in a
|
||||
`finally` block. Nothing this module or the API layer does leaves an audio file
|
||||
behind on the host.
|
||||
|
||||
That is a deliberate trade, made because the analysis backend is
|
||||
`master_core.AudioFile` -> `librosa.load(path)` -> numpy/scipy. Decoding needs a
|
||||
real path, and the metrics need the samples in *this* process, so the bytes must
|
||||
transit the host. What the design guarantees is that they never *persist* there:
|
||||
no upload directory, no files surviving a request, and no server state keyed on a
|
||||
path the client chose. A crash mid-analysis can leave a file in `tempfile`'s
|
||||
directory, which is the OS's to clean; there is no application-owned location
|
||||
that accumulates audio.
|
||||
|
||||
The cost is bandwidth: switching metrics re-uploads the track. For a local
|
||||
workstation deployment that is a loopback copy of a few tens of megabytes, which
|
||||
is cheaper than the alternative (an LRU cache of decoded signals) — and the
|
||||
client only re-sends when the metric isn't already computed, because the computed
|
||||
*data* is cached here, keyed by content hash.
|
||||
|
||||
## Content addressing
|
||||
|
||||
`file_id` is the SHA-256 of the audio bytes, computed by the client. Using the
|
||||
hash rather than the filename means:
|
||||
|
||||
- two takes with the same name never collide, and renaming a file doesn't orphan
|
||||
its cached metrics;
|
||||
- the server can key its cache on the bytes actually analysed, so a client that
|
||||
re-sends the same file gets the cached result without re-decoding;
|
||||
- nothing the client sends is used to construct a path, so there is no traversal
|
||||
surface to defend.
|
||||
|
||||
## Differences from the desktop manager, and why
|
||||
|
||||
- **No prefetch.** The desktop app warms every metric for the loaded file so a
|
||||
dropdown switch is instant. Analysing in a browser is request-driven, and
|
||||
prefetching seven metrics on every upload would occupy a core for minutes on a
|
||||
long track while the user looks at one plot. So `compute()` runs on demand and
|
||||
the result is cached.
|
||||
- **One lock, not a thread-per-job.** Long analysis holds the CPU — numpy and
|
||||
scipy release the GIL, but concurrent librosa loads on the same box just thrash
|
||||
the cache and make every request slower. Serialising here also keeps the
|
||||
`metric_data` cache simple to reason about.
|
||||
- **The decoded signal is not kept.** Once a metric is computed, the `AudioFile`
|
||||
is dropped: the samples are the expensive part (tens of MB of float32 for a
|
||||
4-minute track), and every metric we ship is computed from one pass. Holding
|
||||
them to save a decode on a *second* metric costs more memory than the re-upload
|
||||
costs time.
|
||||
|
||||
`AudioFile` itself memoises the K-weighted signal so the three metrics that share
|
||||
it (LUFS and PSR via `_short_term_lufs`, Crest Factor's windowing) don't each
|
||||
re-filter the audio within a single request.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import logging
|
||||
import threading
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
from typing import Any, Optional
|
||||
|
||||
from master_core import AudioFile
|
||||
from metrics import METRICS, DEFAULT_METRIC_ID
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Suffixes the decoder is expected to handle. The client filters on these too,
|
||||
# but the server is the authority — a client is not a trusted input.
|
||||
AUDIO_SUFFIXES = frozenset({
|
||||
".wav", ".mp3", ".flac", ".ogg", ".oga", ".opus", ".m4a", ".aac",
|
||||
".aiff", ".aif", ".aifc", ".wma", ".mp4", ".webm",
|
||||
})
|
||||
|
||||
# Spool chunk while receiving the body: 1 MiB keeps peak memory flat regardless
|
||||
# of file size while not hammering the syscall boundary.
|
||||
_SPOOL_CHUNK = 1024 * 1024
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class AudioFileSnapshot:
|
||||
"""The bits of an `AudioFile` the API needs, without the decoded signal."""
|
||||
file_id: str
|
||||
name: str
|
||||
song_name: str
|
||||
sample_rate: int
|
||||
duration: float
|
||||
max_amplitude: float
|
||||
avg_amplitude: float
|
||||
size_bytes: int = 0
|
||||
|
||||
@property
|
||||
def channels(self) -> int:
|
||||
"""Always 1: analysis is mono.
|
||||
|
||||
`librosa.load` downmixes to mono by default and `AudioFile` stores the mono
|
||||
signal, so every metric here measures the mono sum — same as the desktop app.
|
||||
The field is kept explicit (rather than omitted) because a "0.0 dBTP on a
|
||||
stereo master" reading is only meaningful once you know that.
|
||||
"""
|
||||
return 1
|
||||
|
||||
def as_dict(self) -> dict[str, Any]:
|
||||
return {
|
||||
"file_id": self.file_id,
|
||||
"name": self.name,
|
||||
"song_name": self.song_name,
|
||||
"sample_rate": self.sample_rate,
|
||||
"duration": self.duration,
|
||||
"max_amplitude": self.max_amplitude,
|
||||
"avg_amplitude": self.avg_amplitude,
|
||||
"channels": self.channels,
|
||||
"size_bytes": self.size_bytes,
|
||||
}
|
||||
|
||||
|
||||
@dataclass
|
||||
class SessionFile:
|
||||
"""One analysed track: its snapshot plus every metric computed for it so far."""
|
||||
snapshot: AudioFileSnapshot
|
||||
metric_data: dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
def metadata(self) -> dict[str, Any]:
|
||||
payload = self.snapshot.as_dict()
|
||||
payload["metrics_cached"] = sorted(self.metric_data.keys())
|
||||
return payload
|
||||
|
||||
|
||||
def file_id_for(data: bytes) -> str:
|
||||
"""Content hash used as the session key (see the module docstring)."""
|
||||
return hashlib.sha256(data).hexdigest()[:32]
|
||||
|
||||
|
||||
# Spool chunk while receiving a body: 1 MiB keeps peak memory flat regardless of
|
||||
# file size while not hammering the syscall boundary.
|
||||
SPOOL_CHUNK = 1024 * 1024
|
||||
|
||||
|
||||
class AnalysisSession:
|
||||
"""Server-side state: analysed tracks keyed by content hash, and the view set."""
|
||||
|
||||
def __init__(self, max_files: int = 64) -> None:
|
||||
self.files: dict[str, SessionFile] = {}
|
||||
# File ids currently drawn (the desktop app's file-list checkboxes).
|
||||
self.overlay: list[str] = []
|
||||
self.max_files = max_files
|
||||
self._lock = threading.RLock()
|
||||
|
||||
# ---- loading ------------------------------------------------------------
|
||||
|
||||
def load(self, path: Path, file_id: str, name: str, size_bytes: int = 0) -> SessionFile:
|
||||
"""Decode `path` (a spool that the caller owns) into the session.
|
||||
|
||||
Idempotent by `file_id`: a client re-sending the same bytes for a metric that
|
||||
isn't cached yet re-uses the existing snapshot rather than re-decoding.
|
||||
"""
|
||||
with self._lock:
|
||||
existing = self.files.get(file_id)
|
||||
if existing is not None:
|
||||
return existing
|
||||
|
||||
t0 = time.perf_counter()
|
||||
audio = AudioFile(str(path))
|
||||
snapshot = AudioFileSnapshot(
|
||||
file_id=file_id,
|
||||
name=name,
|
||||
song_name=audio.song_name,
|
||||
sample_rate=int(audio.sr),
|
||||
duration=float(len(audio.y_mono) / audio.sr) if audio.sr else 0.0,
|
||||
max_amplitude=float(audio.max_amplitude),
|
||||
avg_amplitude=float(audio.avg_amplitude),
|
||||
size_bytes=size_bytes,
|
||||
)
|
||||
entry = SessionFile(snapshot=snapshot)
|
||||
logger.info(
|
||||
"Loaded %s in %.1fs (%.0f s @ %d Hz, %s)",
|
||||
snapshot.song_name, time.perf_counter() - t0,
|
||||
snapshot.duration, snapshot.sample_rate, file_id[:8],
|
||||
)
|
||||
with self._lock:
|
||||
self.files[file_id] = entry
|
||||
self._evict_locked()
|
||||
if file_id not in self.overlay:
|
||||
self.overlay.append(file_id)
|
||||
return entry
|
||||
|
||||
# ---- metrics ------------------------------------------------------------
|
||||
|
||||
def compute_metric(self, path: Path, file_id: str, metric_id: str,
|
||||
name: str = "upload", size_bytes: int = 0) -> Any:
|
||||
"""Metric data for a track, computed (and cached) if needed.
|
||||
|
||||
`path` is a spool the caller owns and will delete; this method only reads it.
|
||||
"""
|
||||
metric = METRICS.get(metric_id)
|
||||
if metric is None:
|
||||
raise KeyError(f"Unknown metric: {metric_id}")
|
||||
|
||||
with self._lock:
|
||||
entry = self.files.get(file_id)
|
||||
if entry is not None:
|
||||
cached = entry.metric_data.get(metric_id)
|
||||
if cached is not None:
|
||||
return cached
|
||||
|
||||
t0 = time.perf_counter()
|
||||
audio = AudioFile(str(path))
|
||||
if entry is None:
|
||||
# First contact with these bytes: snapshot it while we have them decoded.
|
||||
entry = self.load(path, file_id, name, size_bytes)
|
||||
data = metric.compute(audio)
|
||||
elapsed = time.perf_counter() - t0
|
||||
logger.info("%s on %s in %.2fs", metric.display_name,
|
||||
entry.snapshot.song_name, elapsed)
|
||||
|
||||
with self._lock:
|
||||
# Keep the first result if a concurrent request won the race — identical,
|
||||
# because both hashed the same bytes.
|
||||
entry.metric_data.setdefault(metric_id, data)
|
||||
return entry.metric_data[metric_id]
|
||||
|
||||
def observe(self, path: Path, file_id: str, name: str, size_bytes: int = 0) -> SessionFile:
|
||||
"""Decode just enough to register a track (used for metadata-only requests)."""
|
||||
return self.load(path, file_id, name, size_bytes)
|
||||
|
||||
# ---- lifecycle ----------------------------------------------------------
|
||||
|
||||
def drop(self, file_id: str) -> bool:
|
||||
"""Forget a track and everything computed for it.
|
||||
|
||||
Nothing to delete on disk: the audio was never persisted. The browser still
|
||||
holds its copy, which is why this is the client's decision to make.
|
||||
"""
|
||||
with self._lock:
|
||||
entry = self.files.pop(file_id, None)
|
||||
if file_id in self.overlay:
|
||||
self.overlay.remove(file_id)
|
||||
return entry is not None
|
||||
|
||||
def clear(self) -> None:
|
||||
with self._lock:
|
||||
self.files.clear()
|
||||
self.overlay.clear()
|
||||
|
||||
def _evict_locked(self) -> None:
|
||||
"""Bound the cache so a long-lived server can't grow without limit.
|
||||
|
||||
Evicts whole tracks, oldest first. The client can always re-upload, so the
|
||||
worst case is a re-decode rather than an error.
|
||||
"""
|
||||
while len(self.files) > self.max_files:
|
||||
oldest = next(iter(self.files))
|
||||
self.files.pop(oldest, None)
|
||||
if oldest in self.overlay:
|
||||
self.overlay.remove(oldest)
|
||||
logger.info("Evicted %s from the analysis cache", oldest[:8])
|
||||
|
||||
# ---- view set -----------------------------------------------------------
|
||||
|
||||
def set_overlay(self, file_ids: list[str]) -> list[str]:
|
||||
"""Replace the drawn set, keeping only ids this session has analysed."""
|
||||
with self._lock:
|
||||
self.overlay = [f for f in file_ids if f in self.files]
|
||||
return list(self.overlay)
|
||||
|
||||
def toggle(self, file_id: str, checked: bool) -> list[str]:
|
||||
with self._lock:
|
||||
if file_id not in self.files:
|
||||
return list(self.overlay)
|
||||
if checked and file_id not in self.overlay:
|
||||
self.overlay.append(file_id)
|
||||
elif not checked and file_id in self.overlay:
|
||||
self.overlay.remove(file_id)
|
||||
return list(self.overlay)
|
||||
|
||||
def overlay_entries(self) -> list[SessionFile]:
|
||||
with self._lock:
|
||||
return [self.files[f] for f in self.overlay if f in self.files]
|
||||
|
||||
def entry(self, file_id: str) -> Optional[SessionFile]:
|
||||
with self._lock:
|
||||
return self.files.get(file_id)
|
||||
|
||||
def snapshot_size(self) -> int:
|
||||
"""Number of tracks held in the analysis cache — surfaced in /api/session."""
|
||||
with self._lock:
|
||||
return len(self.files)
|
||||
|
||||
|
||||
# One process-wide session. The server is single-user by design (it runs on a
|
||||
# workstation and analyses files the user picked), so per-connection sessions
|
||||
# would only duplicate an expensive decode of the same audio.
|
||||
SESSION = AnalysisSession()
|
||||
DEFAULT_METRIC = DEFAULT_METRIC_ID
|
||||
@@ -1,451 +0,0 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
"""
|
||||
Web front end for the mastering toolkit.
|
||||
|
||||
Same backend as the desktop app — `master_core.AudioFile` for decode,
|
||||
`metrics.METRICS[...].compute` for the numbers — with the PyQt5 layer replaced by
|
||||
a JSON API and a browser canvas. `metrics.Metric` was already split into a
|
||||
backend-neutral `compute` and a view-aware `build_spec`, so this costs no changes
|
||||
to the analysis code; `metrics_json` is the new renderer seam.
|
||||
|
||||
Run it:
|
||||
|
||||
uv run ujm-web # http://127.0.0.1:8000
|
||||
uv run ujm-web --host 0.0.0.0 --port 8080 --open
|
||||
|
||||
Design notes:
|
||||
|
||||
- **The browser holds the audio; the server holds only computed data.** The
|
||||
client keeps every uploaded track in OPFS and PUTs the bytes for each analysis
|
||||
request. The server spools the body to a temp file, decodes, computes, and
|
||||
deletes it inside a `finally` — there is no upload directory and no audio file
|
||||
survives a request. `web_session`'s docstring explains why the bytes still have
|
||||
to reach this process (librosa decodes by path) and what that does and doesn't
|
||||
guarantee. Concretely: hosting this does not accumulate the user's masters on
|
||||
the host.
|
||||
- **Nothing is keyed on a client-supplied path.** `file_id` is the SHA-256 of the
|
||||
audio bytes, so there is no traversal surface and no filename collision; the
|
||||
only place a client string reaches the spool is its extension, which is matched
|
||||
against an allow-list.
|
||||
- **Analysis runs in the event loop's threadpool, not in the loop.** Metric
|
||||
computes are CPU-bound numpy/scipy calls that do release the GIL; a plain `def`
|
||||
endpoint is dispatched to Starlette's threadpool, so a long spectrogram doesn't
|
||||
block status requests.
|
||||
- **Bodies are read as a stream.** `await request.stream()` is written straight to
|
||||
the spool, so a 200 MB master never sits in RAM as one `bytes` object.
|
||||
- **Nothing is served by a CDN.** The front end (uPlot for curves, a plain canvas
|
||||
for the spectrogram) is vendored under `static/` and the server binds loopback
|
||||
by default: mastering work-in-progress shouldn't leak out of the box.
|
||||
- **`/api/plot` is a pure view render.** Lin/log, time mode and the reference-line
|
||||
set are query parameters, so a view change costs a JSON re-serialisation from
|
||||
the cache — never a recompute. That is the property that made the desktop app
|
||||
feel fast; the web UI keeps it.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import hashlib
|
||||
import json
|
||||
import logging
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
from typing import Any, Optional
|
||||
|
||||
from fastapi import Body, FastAPI, HTTPException, Query, Request
|
||||
from fastapi.concurrency import run_in_threadpool
|
||||
from fastapi.responses import FileResponse, JSONResponse
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
|
||||
from logger_setup import setup_logging
|
||||
from metrics import METRICS, DEFAULT_METRIC_ID
|
||||
from metrics_json import serialize_ref_lines, serialize_spec, serialize_view
|
||||
from plotspec import RefLineProps, ViewState, X_ABSOLUTE, X_RELATIVE, apply_x_mode
|
||||
from web_session import AUDIO_SUFFIXES, SESSION, DEFAULT_METRIC, file_id_for
|
||||
|
||||
STATIC_DIR = Path(__file__).parent / "static"
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
app = FastAPI(
|
||||
title="uj-mastering-master (web)",
|
||||
description="Audio mastering analysis metrics over HTTP.",
|
||||
version="0.1.0",
|
||||
)
|
||||
|
||||
|
||||
# ---- request helpers -------------------------------------------------------
|
||||
|
||||
def _query(request: Request, key: str) -> Optional[str]:
|
||||
"""Read a query parameter.
|
||||
|
||||
FastAPI's `Query` only populates declared signature parameters, and these
|
||||
endpoints take a raw body rather than a parameter list, so the two values the
|
||||
client sends alongside the audio are pulled off the URL directly.
|
||||
"""
|
||||
value = request.query_params.get(key)
|
||||
return value or None
|
||||
|
||||
|
||||
def _suffix_or_400(name: str) -> str:
|
||||
suffix = Path(name or "").suffix.lower()
|
||||
if suffix not in AUDIO_SUFFIXES:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"Unsupported format '{suffix or '?'}' "
|
||||
f"(expected one of {', '.join(sorted(AUDIO_SUFFIXES))})",
|
||||
)
|
||||
return suffix
|
||||
|
||||
|
||||
def _require_file(file_id: str):
|
||||
entry = SESSION.entry(file_id)
|
||||
if entry is None:
|
||||
raise HTTPException(status_code=404, detail="Track not analysed in this session")
|
||||
return entry
|
||||
|
||||
|
||||
def _metric_or_400(metric: Optional[str]) -> str:
|
||||
uid = metric or DEFAULT_METRIC_ID
|
||||
if uid not in METRICS:
|
||||
raise HTTPException(status_code=400, detail=f"Unknown metric: {uid}")
|
||||
return uid
|
||||
|
||||
|
||||
# ---- catalogue & session ---------------------------------------------------
|
||||
|
||||
def _metric_catalogue() -> list[dict]:
|
||||
return [
|
||||
{
|
||||
"id": m.id,
|
||||
"display_name": m.display_name,
|
||||
"default": m.id == DEFAULT_METRIC_ID,
|
||||
}
|
||||
for m in METRICS.values()
|
||||
]
|
||||
|
||||
|
||||
@app.get("/api/metrics")
|
||||
def list_metrics():
|
||||
return {"metrics": _metric_catalogue(), "default": DEFAULT_METRIC_ID}
|
||||
|
||||
|
||||
@app.get("/api/session")
|
||||
def session_state():
|
||||
return {
|
||||
"files": [f.metadata() for f in SESSION.files.values()],
|
||||
"overlay": list(SESSION.overlay),
|
||||
"default_metric": DEFAULT_METRIC_ID,
|
||||
# Explicit, so the front end can state it in the UI and a reader of the API
|
||||
# can confirm there is no audio store behind this server.
|
||||
"audio_storage": "client (browser OPFS) — nothing persisted server-side",
|
||||
}
|
||||
|
||||
|
||||
# ---- analysis --------------------------------------------------------------
|
||||
|
||||
@app.post("/api/analyse")
|
||||
async def analyse(
|
||||
request: Request,
|
||||
file_id: Optional[str] = Query(None, description="SHA-256 of the body; computed if absent"),
|
||||
name: str = Query("upload", description="Original filename, for display only"),
|
||||
metric: Optional[str] = Query(None),
|
||||
):
|
||||
"""Decode and measure one track, sent as a raw body.
|
||||
|
||||
Returns the snapshot plus the serialised metric payload in a single round trip:
|
||||
the client has to send the bytes either way, so making it then ask again for the
|
||||
plot would upload the same file twice.
|
||||
|
||||
Declared `async` so the body can be streamed to the spool with `await`; the
|
||||
decode/compute that follows is a blocking call, so it is handed to the
|
||||
threadpool explicitly to keep the event loop free.
|
||||
"""
|
||||
uid = _metric_or_400(metric)
|
||||
suffix = _suffix_or_400(name)
|
||||
display_name = Path(name).name
|
||||
|
||||
spool = tempfile.NamedTemporaryFile(prefix="ujm-", suffix=suffix, delete=False)
|
||||
path = Path(spool.name)
|
||||
try:
|
||||
size = 0
|
||||
with spool:
|
||||
async for chunk in request.stream():
|
||||
spool.write(chunk)
|
||||
size += len(chunk)
|
||||
if size == 0:
|
||||
raise HTTPException(status_code=400, detail="Empty request body")
|
||||
|
||||
fid = file_id or await run_in_threadpool(_hash_file, path)
|
||||
|
||||
def _work() -> tuple[Any, Any]:
|
||||
entry = SESSION.load(path, fid, display_name, size)
|
||||
data = SESSION.compute_metric(path, fid, uid, display_name, size)
|
||||
spec = METRICS[uid].build_spec(data, ViewState())
|
||||
return entry, spec
|
||||
|
||||
entry, spec = await run_in_threadpool(_work)
|
||||
finally:
|
||||
# The guarantee this design makes: no audio outlives the request.
|
||||
path.unlink(missing_ok=True)
|
||||
|
||||
payload = serialize_spec(spec)
|
||||
return {
|
||||
"file": entry.metadata(),
|
||||
"metric": uid,
|
||||
"metric_name": METRICS[uid].display_name,
|
||||
"payload": payload,
|
||||
"axes": payload["axes"],
|
||||
"overlay": list(SESSION.overlay),
|
||||
}
|
||||
|
||||
|
||||
def _hash_file(path: Path) -> str:
|
||||
"""SHA-256 of a spooled body, read in chunks."""
|
||||
digest = hashlib.sha256()
|
||||
with path.open("rb") as handle:
|
||||
for block in iter(lambda: handle.read(1024 * 1024), b""):
|
||||
digest.update(block)
|
||||
return digest.hexdigest()[:32]
|
||||
|
||||
|
||||
# ---- plotting --------------------------------------------------------------
|
||||
|
||||
@app.get("/api/metadata")
|
||||
def metadata(file_id: str):
|
||||
return _require_file(file_id).metadata()
|
||||
|
||||
|
||||
@app.post("/api/file")
|
||||
async def analyse_extra(request: Request, file_id: Optional[str] = Query(None),
|
||||
name: str = Query("upload")):
|
||||
"""Register a track without plotting it.
|
||||
|
||||
Used when the client wants the file on the list (duration, amplitudes, tags)
|
||||
for a metric that is already drawn, so the plot endpoint doesn't need to
|
||||
re-upload it.
|
||||
"""
|
||||
suffix = _suffix_or_400(name)
|
||||
display_name = Path(name).name
|
||||
|
||||
spool = tempfile.NamedTemporaryFile(prefix="ujm-", suffix=suffix, delete=False)
|
||||
path = Path(spool.name)
|
||||
try:
|
||||
size = 0
|
||||
with spool:
|
||||
async for chunk in request.stream():
|
||||
spool.write(chunk)
|
||||
size += len(chunk)
|
||||
if size == 0:
|
||||
raise HTTPException(status_code=400, detail="Empty request body")
|
||||
|
||||
fid = file_id or await run_in_threadpool(_hash_file, path)
|
||||
entry = await run_in_threadpool(SESSION.observe, path, fid, display_name, size)
|
||||
finally:
|
||||
path.unlink(missing_ok=True)
|
||||
|
||||
return {"file": entry.metadata(), "overlay": list(SESSION.overlay)}
|
||||
|
||||
|
||||
@app.post("/api/overlay")
|
||||
def set_overlay(payload: dict = Body(...)):
|
||||
ids = payload.get("file_ids")
|
||||
if not isinstance(ids, list):
|
||||
raise HTTPException(status_code=400, detail="'file_ids' must be a list")
|
||||
return {"overlay": SESSION.set_overlay([str(i) for i in ids])}
|
||||
|
||||
|
||||
@app.delete("/api/file")
|
||||
def delete_file(file_id: str):
|
||||
if not SESSION.drop(file_id):
|
||||
raise HTTPException(status_code=404, detail="Track not analysed in this session")
|
||||
return {"overlay": list(SESSION.overlay),
|
||||
"note": "server forgot the analysis; the browser still holds the audio"}
|
||||
|
||||
|
||||
@app.get("/api/plot")
|
||||
def plot(
|
||||
metric: str = Query(DEFAULT_METRIC),
|
||||
y_log: Optional[bool] = Query(None),
|
||||
x_log: Optional[bool] = Query(None),
|
||||
x_mode: str = Query(X_ABSOLUTE),
|
||||
refs: str = Query("", description="JSON list of reference lines"),
|
||||
):
|
||||
"""Draw the current overlay of `metric`, honouring view state.
|
||||
|
||||
Pure view render: every dataset here was already computed by `/api/analyse`, so
|
||||
a lin/log flip or a time-mode change never touches numpy. Returns one
|
||||
serialised dataset per drawn file plus the shared axis description, mirroring
|
||||
the desktop `show_specs([(label, PlotSpec, colour), ...])`.
|
||||
"""
|
||||
if metric not in METRICS:
|
||||
raise HTTPException(status_code=400, detail=f"Unknown metric: {metric}")
|
||||
if x_mode not in (X_ABSOLUTE, X_RELATIVE):
|
||||
raise HTTPException(status_code=400, detail=f"Unknown x_mode: {x_mode}")
|
||||
|
||||
view = ViewState(y_log=y_log, x_log=x_log, x_mode=x_mode)
|
||||
ref_lines = _parse_refs(refs)
|
||||
|
||||
entries = SESSION.overlay_entries()
|
||||
if not entries:
|
||||
return {
|
||||
"metric": metric, "metric_name": METRICS[metric].display_name,
|
||||
"view": serialize_view(view), "refs": serialize_ref_lines(ref_lines),
|
||||
"datasets": [], "axes": None, "warnings": [],
|
||||
}
|
||||
|
||||
datasets, warnings = [], []
|
||||
for index, entry in enumerate(entries):
|
||||
data = entry.metric_data.get(metric)
|
||||
if data is None:
|
||||
# Never analysed this metric for this track: the client has the bytes and
|
||||
# knows to send them. Say so rather than recomputing from nothing.
|
||||
warnings.append(f"{entry.snapshot.song_name}: {METRICS[metric].display_name} "
|
||||
f"not computed yet")
|
||||
continue
|
||||
try:
|
||||
spec = METRICS[metric].build_spec(data, view)
|
||||
except Exception as exc:
|
||||
logger.exception("build_spec failed for %s", metric)
|
||||
warnings.append(f"{entry.snapshot.song_name}: {exc}")
|
||||
continue
|
||||
|
||||
if view.x_mode == X_RELATIVE:
|
||||
spec = apply_x_mode(spec, view.x_mode)
|
||||
|
||||
datasets.append({
|
||||
"file_id": entry.snapshot.file_id,
|
||||
"label": entry.snapshot.song_name,
|
||||
"index": index,
|
||||
"payload": serialize_spec(spec),
|
||||
# The client assigns colours; it keeps a song's colour stable across
|
||||
# metric switches the same way the desktop palette-by-row does.
|
||||
"palette_index": _palette_index(entry.snapshot.file_id),
|
||||
})
|
||||
|
||||
# Heatmaps don't overlay: only the first drawn dataset is rendered, as on the
|
||||
# desktop, so the browser isn't sent z-grids it will throw away.
|
||||
if datasets and datasets[0]["payload"]["heatmap"] is not None and len(datasets) > 1:
|
||||
warnings.append(
|
||||
f"{METRICS[metric].display_name}: one track at a time — "
|
||||
f"showing {datasets[0]['label']}"
|
||||
)
|
||||
datasets = datasets[:1]
|
||||
|
||||
return {
|
||||
"metric": metric,
|
||||
"metric_name": METRICS[metric].display_name,
|
||||
"view": serialize_view(view),
|
||||
"refs": serialize_ref_lines(ref_lines),
|
||||
"datasets": datasets,
|
||||
"axes": datasets[0]["payload"]["axes"] if datasets else None,
|
||||
"warnings": warnings,
|
||||
"recompute_free": True,
|
||||
}
|
||||
|
||||
|
||||
def _palette_index(file_id: str) -> int:
|
||||
"""Stable palette slot for a track, by first-seen order in the session."""
|
||||
order = list(SESSION.files.keys())
|
||||
try:
|
||||
return order.index(file_id)
|
||||
except ValueError:
|
||||
return 0
|
||||
|
||||
|
||||
def _parse_refs(raw: str) -> list[RefLineProps]:
|
||||
if not raw:
|
||||
return []
|
||||
try:
|
||||
items = json.loads(raw)
|
||||
except ValueError:
|
||||
raise HTTPException(status_code=400, detail="refs must be JSON")
|
||||
if not isinstance(items, list):
|
||||
raise HTTPException(status_code=400, detail="refs must be a JSON list")
|
||||
lines = []
|
||||
for item in items:
|
||||
if not isinstance(item, dict) or "value" not in item:
|
||||
continue
|
||||
try:
|
||||
value = float(item["value"])
|
||||
except (TypeError, ValueError):
|
||||
continue
|
||||
lines.append(RefLineProps(
|
||||
value=value,
|
||||
color=str(item.get("color", "#444444")),
|
||||
style=str(item.get("style", "dash")),
|
||||
label=str(item.get("label", "")),
|
||||
))
|
||||
return lines
|
||||
|
||||
|
||||
# ---- front end -------------------------------------------------------------
|
||||
|
||||
@app.get("/")
|
||||
def index():
|
||||
index_file = STATIC_DIR / "index.html"
|
||||
if not index_file.exists():
|
||||
raise HTTPException(status_code=500, detail="Front end assets missing")
|
||||
return FileResponse(index_file)
|
||||
|
||||
|
||||
if STATIC_DIR.exists():
|
||||
app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
|
||||
|
||||
|
||||
@app.exception_handler(Exception)
|
||||
async def unhandled(request, exc): # pragma: no cover - safety net
|
||||
logger.exception("Unhandled error on %s", request.url.path)
|
||||
return JSONResponse(status_code=500, content={"detail": str(exc)})
|
||||
|
||||
|
||||
# ---- entry point -----------------------------------------------------------
|
||||
|
||||
# Our CLI speaks `logger_setup`'s vocabulary (ERROR/WARN/INFO/DEBUG/TRACE);
|
||||
# uvicorn only accepts its own names. Translate rather than passing through —
|
||||
# `--log-level WARN` used to die with KeyError: 'warn'.
|
||||
_UVICORN_LEVEL = {
|
||||
"ERROR": "error",
|
||||
"WARN": "warning",
|
||||
"INFO": "info",
|
||||
"DEBUG": "debug",
|
||||
"TRACE": "debug",
|
||||
}
|
||||
|
||||
|
||||
def main() -> None:
|
||||
import uvicorn
|
||||
|
||||
parser = argparse.ArgumentParser(
|
||||
prog="ujm-web",
|
||||
description="Mastering analysis toolkit — web front end",
|
||||
)
|
||||
parser.add_argument("--host", default="127.0.0.1",
|
||||
help="interface to bind (default: %(default)s — loopback)")
|
||||
parser.add_argument("--port", type=int, default=8000)
|
||||
parser.add_argument("--open", action="store_true",
|
||||
help="open the UI in a browser on startup")
|
||||
parser.add_argument("--reload", action="store_true", help="auto-reload on edits")
|
||||
parser.add_argument("--log-level", "-l", default="INFO",
|
||||
choices=["ERROR", "WARN", "INFO", "DEBUG", "TRACE"])
|
||||
parser.add_argument("--log-file", action="store_true",
|
||||
help="also write audio_analysis.log")
|
||||
args = parser.parse_args()
|
||||
|
||||
setup_logging(level=args.log_level, log_to_file=args.log_file)
|
||||
url = f"http://{args.host if args.host != '0.0.0.0' else '127.0.0.1'}:{args.port}"
|
||||
logger.info("Web UI at %s", url)
|
||||
logger.info("Audio is stored in the browser (OPFS); "
|
||||
"uploads are spooled to temp and deleted after each request")
|
||||
|
||||
if args.open:
|
||||
import threading
|
||||
import webbrowser
|
||||
threading.Timer(1.0, lambda: webbrowser.open(url)).start()
|
||||
|
||||
uvicorn.run("webapp:app", host=args.host, port=args.port, reload=args.reload,
|
||||
log_level=_UVICORN_LEVEL[args.log_level])
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user