diff --git a/CLAUDE.md b/CLAUDE.md index 6e49ad9..c5dd9d3 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -109,6 +109,50 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th gone with the matplotlib render path. If wanted back, it belongs in the renderer, applied uniformly to every metric — not per-metric +#### `web_session.py` +- Server-side equivalent of `AnalysisResultsManager`, without Qt: owns the + per-track metric cache and the overlay set, and mirrors the desktop's + compute-off-the-request-thread behaviour +- **No audio is stored.** Tracks are keyed by `file_id` = SHA-256 of the audio, + and the session keeps only analysis results and metadata. There is no upload + directory and no cache of bytes +- Because the key is a content hash, re-sending the same master for a second + metric reuses the first decode — the client only re-uploads what the server has + never seen (checked via `metrics_cached`) + +#### `webapp.py` +- FastAPI routes + static mount + the `ujm-web` entry point (binds loopback by + default; `--host`/`--port`/`--open` to override) +- Analysis endpoints take the audio as a **raw request body**, not a multipart + upload: spool to a temp file, `SESSION.observe(...)`, unlink in `finally`. The + bytes exist on disk only for the duration of that one request +- `POST /api/analyse` (analyse + plot data), `POST /api/file` (register without + plotting), `DELETE /api/file`, `POST /api/overlay`, `GET /api/plot`, + `GET /api/metadata`, `GET /api/metrics`, `GET /api/session` + +#### `metrics_json.py` +- The renderer seam: `PlotSpec`/metric data → JSON, so a non-pyqtgraph renderer + consumes the identical spec (curves, bands, hlines, heatmap, axis specs) that + the desktop widget draws. `hlines` carry the integrated LUFS reference line — + it is not an annotation + +#### `static/` (web front end) +- `audio-store.js` — OPFS store. Copies each picked/dropped `File` into Origin + Private File System (browser-sandboxed, not the host's filesystem), hashes it + with WebCrypto in chunks while streaming (never loads a whole master into + memory), and re-sends bytes to the server per metric +- `app.js` — the web renderer, an ES module importing the store. Draws the same + `PlotSpec` the desktop does: uPlot for curves/bands, a plain canvas for the + spectrogram heatmap (a canvas can map rows through an arbitrary function, so it + draws native linear rows and maps them, unlike pyqtgraph's affine-only + `ImageItem`). Mirrors the desktop's per-metric colour cycle, lin/log toggles, + absolute/relative time, and draggable reference lines +- `vendor/` — uPlot 1.6.32 (IIFE + CSS), vendored so nothing is fetched from a + CDN at runtime +- Boot rehydrates: the server still has the last session's analysis, so it + re-offers audio only for metric/track combinations the server reports as + uncached, and reports unavailable combinations rather than faking them + #### `master_core.py` - Defines the `AudioFile` class: librosa loading, rolling RMS power. BPM detection was **removed** — `librosa.beat.beat_track` cost ~3.7 s on every load for a @@ -225,6 +269,7 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th - matplotlib: Colormaps only (consumed by pyqtgraph) + librosa dependency - mutagen: Audio metadata extraction - PyQt5: GUI framework +- fastapi / uvicorn: web UI (optional extra; the desktop app does not need them) ### Architecture considerations - Three-stage split: `metrics.compute` (heavy, worker thread, backend-neutral @@ -248,6 +293,21 @@ uv sync # one-time, after cloning uv run ujm # launch the GUI ``` +### Running the web UI +Branch `feature/web-ui`. Same backend, browser front end. + +```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 # reachable from another machine +``` + +Uploaded audio is held in the browser's Origin Private File System and streamed +to the server per request; the server spools each body to a temp file and unlinks +it before responding. Nothing is written to the host beyond that transient spool. +Verify with `python3 scripts/webapi_smoke.py` against a running server (needs +`ffmpeg` for the fixtures). + Optional flags (handled by `logger_setup.parse_log_args`): ```bash uv run ujm --log-level DEBUG # ERROR | WARN | INFO | DEBUG | TRACE diff --git a/README.md b/README.md index ad8d02c..fe0d1c9 100644 --- a/README.md +++ b/README.md @@ -39,7 +39,7 @@ uv sync uv run ujm ``` -`uv run ujm` is the only supported entry point — it boots the GUI. +`uv run ujm` boots the desktop GUI (see *Web UI* for the browser front end). ### Logging flags ```bash @@ -52,10 +52,71 @@ Drop `.ttf` / `.otf` / `.ttc` files into `fonts/` to get them in the font selector. The directory is gitignored to avoid bundling licensed font data. 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. + +```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 +``` + +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). + +**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. + +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. + +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. + +### Verifying it + +With a server running: + +```bash +python3 scripts/webapi_smoke.py # 61 assertions, needs ffmpeg for the fixtures +python3 scripts/webapi_smoke.py http://host:port /path/to/audio +``` + +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. + +### 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 | + ## Dependencies `librosa`, `numpy`, `matplotlib`, `mutagen`, `pyloudnorm`, `PyQt5` — all pinned through `uv.lock`. Python 3.10+. +The web UI additionally needs `fastapi`, `uvicorn` and `python-multipart` +(`uv sync --extra web`). + ## Architecture | Module | Responsibility | @@ -74,6 +135,8 @@ through `uv.lock`. Python 3.10+. ### Adding a metric Subclass `Metric` in `metrics.py`, implement `compute(audio_file) -> data` (the -heavy part, runs on the worker thread) and `render(data, file_path) -> Figure` -(cheap, runs on the GUI thread). Register the instance in the `METRICS` dict at -the bottom of the file — it shows up in the dropdown automatically. +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`. diff --git a/metrics_json.py b/metrics_json.py new file mode 100644 index 0000000..d5a6002 --- /dev/null +++ b/metrics_json.py @@ -0,0 +1,170 @@ +# 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 diff --git a/pyproject.toml b/pyproject.toml index 554a693..74ff9cb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -21,8 +21,20 @@ dependencies = [ license = {text = "Apache-2.0"} +[project.optional-dependencies] +# Web front end (the `feature/web-ui` branch). Installed with: +# uv sync --extra web +# Deliberately separate from the desktop path: a server install of the web UI +# needs no Qt/wheel stack, and a desktop install needs no ASGI stack. +web = [ + "fastapi>=0.110", + "uvicorn[standard]>=0.27", + "python-multipart>=0.0.9", # multipart upload parsing for FastAPI +] + [project.scripts] ujm = "main:main" +ujm-web = "webapp:main" [tool.setuptools] py-modules = [ @@ -37,4 +49,21 @@ py-modules = [ "ref_line_widget", "logger_setup", "setup_fonts", + # web front end + "webapp", + "web_session", + "metrics_json", ] + +[tool.setuptools.package-data] +# Vendored browser assets: uPlot (curves), no CDN at runtime. `webapp.py` +# resolves them relative to `__file__`, so on an installed wheel they must sit +# next to the modules — see `[tool.setuptools.data-files]` for the sdist path. +"*" = ["static/*"] + +[tool.setuptools.data-files] +# The web assets live next to the *modules*, not in site-packages/static, so a +# wheel install needs them copied into the package directory. `MANIFEST.in` +# keeps them in the sdist; running from a checkout (the documented path) needs +# neither. +"lib/python-static" = ["static/*"] diff --git a/scripts/webapi_smoke.py b/scripts/webapi_smoke.py new file mode 100644 index 0000000..d10fa35 --- /dev/null +++ b/scripts/webapi_smoke.py @@ -0,0 +1,348 @@ +#!/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) + tagged = next(r for n, r in uploads.items() if r["file"]["song_name"].startswith("Test Artist")) + + 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) + 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()) diff --git a/static/app.css b/static/app.css new file mode 100644 index 0000000..e723ab3 --- /dev/null +++ b/static/app.css @@ -0,0 +1,270 @@ +/* Audio Mastering Analysis Toolkit — web front end. + Dark by default: a spectrogram is read against its surroundings, and the + desktop app's pythonic defaults are what these numbers were tuned against. */ + +:root { + --bg: #12141a; + --panel: #191c24; + --panel-2: #1f232d; + --line: #2b303c; + --text: #e8eaf0; + --muted: #939aa8; + --accent: #4fc3f7; + --accent-dim: #2b7fa3; + --warn: #ffb74d; + --error: #ef5350; + --ok: #81c784; + --radius: 6px; + --mono: ui-monospace, "Cascadia Mono", "Source Code Pro", Menlo, Consolas, monospace; +} + +* { box-sizing: border-box; } + +html, body { + margin: 0; + height: 100%; + background: var(--bg); + color: var(--text); + font: 13px/1.45 system-ui, -apple-system, "Segoe UI", Roboto, "Noto Sans", sans-serif; + overflow: hidden; +} + +/* ---- top bar ---- */ + +.topbar { + display: flex; + align-items: center; + justify-content: space-between; + gap: 16px; + height: 48px; + padding: 0 14px; + background: var(--panel); + border-bottom: 1px solid var(--line); +} + +.brand { display: flex; align-items: baseline; gap: 8px; } +.logo { color: var(--accent); font-size: 16px; } +.brand-name { font-weight: 600; letter-spacing: .2px; } +.brand-sub { + font-size: 10px; + text-transform: uppercase; + letter-spacing: 1px; + color: var(--bg); + background: var(--accent-dim); + border-radius: 3px; + padding: 1px 5px; +} + +.topbar-controls { display: flex; align-items: center; gap: 8px; flex-wrap: wrap; } + +.field { display: flex; align-items: center; gap: 6px; color: var(--muted); font-size: 12px; } + +select, .btn, .toggle { + background: var(--panel-2); + color: var(--text); + border: 1px solid var(--line); + border-radius: var(--radius); + padding: 5px 9px; + font: inherit; + font-size: 12px; + cursor: pointer; +} +select:hover, .btn:hover, .toggle:hover { border-color: var(--accent-dim); } +select:focus-visible, .btn:focus-visible, .toggle:focus-visible { outline: 2px solid var(--accent); outline-offset: 1px; } + +.btn.primary { background: var(--accent-dim); border-color: var(--accent); color: #eaf7ff; } +.btn.primary:hover { background: var(--accent); color: #06202b; } +.btn.small { padding: 3px 7px; font-size: 11px; } +.btn:disabled, .toggle:disabled { opacity: .45; cursor: not-allowed; } + +.toggle.on { border-color: var(--accent); color: var(--accent); } +.toggle.off { color: var(--muted); } + +.separator { width: 1px; height: 22px; background: var(--line); } + +/* ---- layout ---- */ + +.layout { + display: grid; + grid-template-columns: 288px minmax(0, 1fr); + height: calc(100% - 48px); +} + +.sidebar { + background: var(--panel); + border-right: 1px solid var(--line); + overflow-y: auto; + padding: 12px; + display: flex; + flex-direction: column; + gap: 12px; +} + +.panel { + background: var(--panel-2); + border: 1px solid var(--line); + border-radius: var(--radius); + padding: 10px; +} +.panel h2 { + margin: 0 0 8px; + font-size: 11px; + text-transform: uppercase; + letter-spacing: .8px; + color: var(--muted); + display: flex; + align-items: center; + gap: 6px; +} +.badge { + background: var(--line); + color: var(--text); + border-radius: 8px; + padding: 0 6px; + font-size: 10px; + font-variant-numeric: tabular-nums; +} + +/* ---- file list ---- */ + +.file-list { list-style: none; margin: 0; padding: 0; display: flex; flex-direction: column; gap: 2px; } +.file-row { + display: flex; + align-items: center; + gap: 7px; + padding: 5px 6px; + border-radius: 4px; + cursor: pointer; + border: 1px solid transparent; +} +.file-row:hover { background: #252a35; } +.file-row.selected { background: #232a38; border-color: var(--accent-dim); } +.file-row input[type=checkbox] { margin: 0; accent-color: var(--accent-dim); flex: none; } +.file-swatch { width: 9px; height: 9px; border-radius: 2px; flex: none; } +.file-name { + flex: 1; + min-width: 0; + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + font-size: 12px; +} +.file-remove { + flex: none; + border: 0; + background: none; + color: var(--muted); + cursor: pointer; + font-size: 14px; + line-height: 1; + padding: 0 2px; + opacity: 0; +} +.file-row:hover .file-remove { opacity: 1; } +.file-remove:hover { color: var(--error); } + +.empty, .hint { color: var(--muted); font-size: 11.5px; margin: 4px 0 0; } +.hint code { background: #000; padding: 0 3px; border-radius: 3px; } + +/* ---- metadata ---- */ + +.metadata { display: grid; grid-template-columns: auto 1fr; gap: 3px 10px; margin: 0; font-size: 12px; } +.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); } + +/* ---- reference lines ---- */ + +.ref-list { list-style: none; margin: 0 0 8px; padding: 0; display: flex; flex-direction: column; gap: 3px; } +.ref-row { display: flex; align-items: center; gap: 6px; font-size: 12px; } +.ref-row input[type=color] { width: 20px; height: 18px; padding: 0; border: 1px solid var(--line); background: none; } +.ref-row input[type=text] { width: 62px; } +.ref-row input[type=number] { width: 62px; } +.ref-row input { background: var(--bg); color: var(--text); border: 1px solid var(--line); border-radius: 4px; padding: 2px 4px; font: inherit; font-size: 11px; } +.ref-row .ref-remove { border: 0; background: none; color: var(--muted); cursor: pointer; } +.ref-row .ref-remove:hover { color: var(--error); } +.ref-actions { display: flex; gap: 6px; } + +/* ---- plot stage ---- */ + +.stage { display: flex; flex-direction: column; min-width: 0; padding: 10px 12px 0; } + +.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-host { + position: relative; + flex: 1; + min-height: 200px; + margin-top: 6px; + background: #0d0f14; + border: 1px solid var(--line); + border-radius: var(--radius); + 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; } + +.placeholder { + position: absolute; + inset: 0; + display: flex; + flex-direction: column; + align-items: center; + justify-content: center; + text-align: center; + color: var(--muted); + gap: 6px; + padding: 20px; +} +.ph-title { font-size: 15px; color: var(--text); margin: 0; } +.ph-body { margin: 0; max-width: 44ch; font-size: 12px; } +.ph-body code { background: #000; padding: 0 3px; border-radius: 3px; } + +.statusbar { + display: flex; + justify-content: space-between; + gap: 12px; + padding: 6px 2px; + font-size: 11.5px; + color: var(--muted); + min-height: 24px; +} +.status.working { color: var(--accent); } +.status.error { color: var(--error); } +.status.warn { color: var(--warn); } +.timing { font-family: var(--mono); } + +/* ---- drag & drop ---- */ + +.drop-overlay { + position: fixed; + inset: 0; + background: rgba(10, 20, 30, .82); + border: 3px dashed var(--accent); + display: flex; + align-items: center; + justify-content: center; + font-size: 20px; + color: var(--accent); + z-index: 40; +} + +/* ---- tooltip ---- */ + +.tooltip { + position: fixed; + background: #05070b; + border: 1px solid var(--line); + border-radius: 4px; + padding: 5px 7px; + font: 11px/1.4 var(--mono); + color: var(--text); + pointer-events: none; + z-index: 30; + white-space: nowrap; +} diff --git a/static/app.js b/static/app.js new file mode 100644 index 0000000..bc2efcb --- /dev/null +++ b/static/app.js @@ -0,0 +1,1157 @@ +/* Audio Mastering Analysis Toolkit — web front end. + * + * The desktop renderer (`audio_visualization_widget.AudioVisualizationWidget`) + * draws a `PlotSpec` with pyqtgraph. This draws the same `PlotSpec` payload with + * uPlot (curves/bands) and a plain canvas (spectrogram heatmap). It owns the + * things the desktop widget owns: the dataset colour cycle, lin/log handling, + * reference-line dragging, and overlay. + * + * Two renderers exist only because pyqtgraph's ImageItem is affine-only, so the + * desktop app has to resample the STFT onto a log-spaced grid before drawing it. + * A canvas can map rows to pixels through an arbitrary function, so this side + * draws the native linear rows and maps them, which is both faster and sharper. + */ + +import * as store from './audio-store.js'; + +'use strict'; + +// ---- palette --------------------------------------------------------------- +// Same job as `dataset_color` on the desktop: a song keeps one colour wherever +// it appears, and overlaid tracks stay distinguishable. Tuned for a dark plot. +const PALETTE = [ + '#4fc3f7', '#ffb74d', '#81c784', '#ba68c8', + '#f06292', '#4db6ac', '#ffd54f', '#9575cd', + '#a1887f', '#e57373', '#64b5f6', '#aed581', +]; + +const state = { + metrics: [], + metric: null, + files: [], // [{file_id, name, song_name, ...}] — analysis metadata only + overlay: [], // file_id list currently drawn + selected: null, // file_id highlighted in the list + xMode: 'absolute', + yLog: null, // null = use the metric's default + yLogAllowed: false, + xLog: null, + xLogAllowed: false, + // Reference lines are kept per metric, as on the desktop: -14 LUFS means + // nothing on a spectrogram, so switching away and back must not lose them. + refsByMetric: {}, + refs: [], + payload: null, // last /api/plot response + uplot: null, + lastAxes: null, + busy: false, + // Which metrics the server has already computed for which track. Tracked + // client-side because the server holds no audio: after a reload we know what + // still needs re-sending. + analysed: {}, // file_id -> Set(metric_id) + objectUrls: {}, // file_id -> blob URL for playback +}; + +const el = (id) => document.getElementById(id); + +// ---- small helpers --------------------------------------------------------- + +function setStatus(text, kind) { + const node = el('status'); + node.textContent = text; + node.className = 'status' + (kind ? ' ' + kind : ''); +} + +function setTiming(text) { + el('timing').textContent = text || ''; +} + +function fmt(value, digits = 2) { + if (value === null || value === undefined || Number.isNaN(value)) return '—'; + return Number(value).toFixed(digits); +} + +function fmtDuration(seconds) { + if (!isFinite(seconds)) return '—'; + const m = Math.floor(seconds / 60); + const s = seconds - m * 60; + return `${m}:${s.toFixed(2).padStart(5, '0')}`; +} + +function paletteFor(fileId) { + const i = state.files.findIndex((f) => f.file_id === fileId); + return PALETTE[(i < 0 ? 0 : i) % PALETTE.length]; +} + +function currentRefs() { + return state.refs; +} + +// ---- API ------------------------------------------------------------------- + +async function api(path, options) { + const res = await fetch(path, options); + let body = null; + try { body = await res.json(); } catch (_) { /* non-JSON error page */ } + if (!res.ok) { + const detail = body && body.detail ? body.detail : `HTTP ${res.status}`; + throw new Error(detail); + } + return body; +} + +async function loadMetrics() { + const data = await api('/api/metrics'); + state.metrics = data.metrics; + state.metric = data.default; + const select = el('metric-select'); + select.innerHTML = ''; + data.metrics.forEach((m) => { + const opt = document.createElement('option'); + opt.value = m.id; + opt.textContent = m.display_name; + if (m.id === data.default) opt.selected = true; + select.appendChild(opt); + }); +} + +// ---- file list ------------------------------------------------------------- + +function renderFileList() { + const list = el('file-list'); + list.innerHTML = ''; + el('file-count').textContent = String(state.files.length); + el('file-empty').hidden = state.files.length > 0; + + state.files.forEach((f) => { + const li = document.createElement('li'); + li.className = 'file-row' + (f.file_id === state.selected ? ' selected' : ''); + li.dataset.id = f.file_id; + + const check = document.createElement('input'); + check.type = 'checkbox'; + check.checked = state.overlay.includes(f.file_id); + check.title = 'Include in the overlay'; + check.addEventListener('click', (ev) => ev.stopPropagation()); + check.addEventListener('change', async () => { + const ids = collectOverlayFromDOM(); + await api('/api/overlay', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ file_ids: ids }), + }); + state.overlay = ids; + await refreshPlot(); + }); + + const swatch = document.createElement('span'); + swatch.className = 'file-swatch'; + swatch.style.background = paletteFor(f.file_id); + + const name = document.createElement('span'); + name.className = 'file-name'; + name.textContent = f.name; + name.title = `${f.song_name}\nSHA-256 ${f.file_id}… · held in browser storage`; + + const remove = document.createElement('button'); + remove.className = 'file-remove'; + remove.type = 'button'; + remove.textContent = '×'; + remove.title = 'Forget this track (drops the analysis and removes it from browser storage)'; + remove.addEventListener('click', async (ev) => { + ev.stopPropagation(); + await api(`/api/file?file_id=${encodeURIComponent(f.file_id)}`, { method: 'DELETE' }); + // The server only ever held numbers; the audio is ours to delete. + await store.remove(f.file_id); + releaseObjectUrl(f.file_id); + delete state.analysed[f.file_id]; + state.files = state.files.filter((x) => x.file_id !== f.file_id); + state.overlay = state.overlay.filter((p) => p !== f.file_id); + if (state.selected === f.file_id) state.selected = null; + renderFileList(); + renderMetadata(); + await refreshPlot(); + }); + + li.append(check, swatch, name, remove); + li.addEventListener('click', () => { + state.selected = f.file_id; + renderFileList(); + renderMetadata(); + }); + list.appendChild(li); + }); +} + +function collectOverlayFromDOM() { + return Array.from(document.querySelectorAll('#file-list .file-row')) + .filter((row) => row.querySelector('input[type=checkbox]').checked) + .map((row) => row.dataset.id); +} + +function renderMetadata() { + const dl = el('metadata'); + dl.innerHTML = ''; + const file = state.files.find((f) => f.file_id === state.selected); + const held = file ? !!(state.analysed[file.file_id]) : false; + const rows = file ? [ + ['Track', file.song_name], + ['Length', fmtDuration(file.duration)], + ['Sample rate', `${(file.sample_rate / 1000).toFixed(1)} kHz`], + ['Channels', file.channels === 1 ? 'mono' : `${file.channels}`], + ['Max amplitude', fmt(file.max_amplitude, 3)], + ['Avg amplitude', fmt(file.avg_amplitude, 3)], + ['Content hash', `${file.file_id.slice(0, 16)}…`], + ['Audio held by', 'this browser (OPFS)'], + ['Metrics cached', analysedFor(file.file_id).length + ? analysedFor(file.file_id).join(', ') : '—'], + ] : [['Track', 'nothing selected']]; + + rows.forEach(([k, v]) => { + const dt = document.createElement('dt'); + dt.textContent = k; + const dd = document.createElement('dd'); + dd.textContent = v; + if (!file) dd.className = 'muted'; + dl.append(dt, dd); + }); +} + +// ---- reference lines ------------------------------------------------------- + +function refsFor(metric) { + if (!state.refsByMetric[metric]) state.refsByMetric[metric] = []; + return state.refsByMetric[metric]; +} + +function renderRefList() { + const list = el('ref-list'); + list.innerHTML = ''; + const refs = currentRefs(); + el('ref-count').textContent = String(refs.length); + + refs.forEach((ref, index) => { + const li = document.createElement('li'); + li.className = 'ref-row'; + + const color = document.createElement('input'); + color.type = 'color'; + color.value = /^#[0-9a-f]{6}$/i.test(ref.color) ? ref.color : '#ffb74d'; + color.addEventListener('input', () => { ref.color = color.value; redrawRefs(); }); + + const value = document.createElement('input'); + value.type = 'number'; + value.step = '0.1'; + value.value = ref.value; + value.title = 'Position on the value axis'; + value.addEventListener('change', () => { ref.value = parseFloat(value.value) || 0; redrawRefs(); }); + + const label = document.createElement('input'); + label.type = 'text'; + label.value = ref.label || ''; + label.placeholder = 'tag'; + label.addEventListener('change', () => { ref.label = label.value; redrawRefs(); }); + + const remove = document.createElement('button'); + remove.className = 'ref-remove'; + remove.type = 'button'; + remove.textContent = '×'; + remove.addEventListener('click', () => { + currentRefs().splice(index, 1); + renderRefList(); + redrawRefs(); + }); + + li.append(color, value, label, remove); + list.appendChild(li); + }); +} + +// ---- plotting -------------------------------------------------------------- + +function yLogActive() { + if (state.payload && state.payload.axes) { + const axis = state.payload.axes; + if (!axis.y_log_allowed) return false; + return state.yLog === null ? axis.y_log : state.yLog; + } + return state.yLog === true; +} + +function refreshYLogButton() { + const btn = el('toggle-y-log'); + const axis = state.payload && state.payload.axes; + const allowed = !!(axis && axis.y_log_allowed); + btn.disabled = !allowed; + const on = allowed && yLogActive(); + btn.textContent = `Y: ${on ? 'log' : 'lin'}`; + btn.className = 'toggle ' + (on ? 'on' : 'off'); +} + +/** log10 with a floor, for log axes over data that may reach zero. */ +function log10f(v, floor) { + return Math.log10(Math.max(v, floor)); +} + +function buildUplotData(payload, colorFor) { + // uPlot needs one shared x array and one column per series. Series may have + // different x arrays (overlaid tracks of different lengths), so they are all + // resampled onto the union of their own x values. For absolute time that is + // exact (every series has a value at every sample it drew anyway); for + // relative mode the x arrays are already normalised to 0–100 %. + const datasets = payload.datasets; + const xsSet = []; + datasets.forEach((d) => { + const series = d.payload.series.concat(d.payload.segments); + series.forEach((s) => xsSet.push(...s.x)); + }); + if (!xsSet.length) return null; + + let x = Array.from(new Set(xsSet)).sort((a, b) => a - b); + + // Guard against a pathological x axis (a single-sample file yields one point). + if (x.length === 1) x = [x[0], x[0] + 1e-3]; + + function resample(srcX, srcY) { + const out = new Array(x.length).fill(null); + if (!srcX.length) return out; + let j = 0; + for (let i = 0; i < x.length; i++) { + while (j < srcX.length - 1 && srcX[j + 1] <= x[i]) j++; + const x0 = srcX[j]; + const x1 = j + 1 < srcX.length ? srcX[j + 1] : x0; + if (x[i] < srcX[0] || x[i] > srcX[srcX.length - 1]) { out[i] = null; continue; } + const y0 = srcY[j]; + const y1 = j + 1 < srcY.length ? srcY[j + 1] : y0; + if (y0 === null || (x1 > x0 && y0 !== null && y1 !== null)) { + const t = x1 > x0 ? (x[i] - x0) / (x1 - x0) : 0; + out[i] = (y0 === null || y1 === null) ? (y0 === null ? y1 : y0) : y0 + (y1 - y0) * t; + } else { + out[i] = y0 === null ? y1 : y0; + } + } + return out; + } + + const data = [x]; + const series = []; + + datasets.forEach((d) => { + const colour = colorFor(d); + + d.payload.segments.forEach((seg, si) => { + const single = datasets.length === 1; + const tag = seg.label || 'band'; + data.push(resample(seg.x, seg.lo)); + data.push(resample(seg.x, seg.hi)); + // Bands draw as two lines; only the second gets a legend entry so the + // pair reads as one dataset. Styling differs by type: an RMS power fill + // is a solid area from zero, a waveform envelope is a bright line pair. + const isEnvelope = Math.min(...seg.lo.filter((v) => v !== null), 0) < 0; + series.push({ + label: single ? (si === 0 ? tag : '') : (si === 0 ? `${d.label}: ${tag}` : ''), + stroke: colour, width: isEnvelope ? 1 : 1.4, + fill: isEnvelope ? null : hexToRgba(colour, 0.22), + points: { show: false }, + _ref: null, + }); + series.push({ + label: '', + stroke: colour, width: isEnvelope ? 1 : 1.4, + fill: isEnvelope ? hexToRgba(colour, 0.28) : null, + points: { show: false }, + _ref: null, + }); + }); + + d.payload.series.forEach((line) => { + const single = datasets.length === 1; + data.push(resample(line.x, line.y)); + series.push({ + label: single ? line.label : `${d.label}: ${line.label}`, + stroke: line.color || colour, + width: line.width || 1.4, + fill: null, + points: { show: false }, + _ref: null, + }); + }); + }); + + // Reference lines become extra series with filled values, so uPlot draws them + // as part of the same resampled grid instead of needing an annotation overlay. + const refs = currentRefs(); + if (refs.length) { + const axis = payload.axes || {}; + refs.forEach((ref) => { + let v = ref.value; + data.push(new Array(x.length).fill(v).map((value, i) => { + const lo = axis.y_range ? axis.y_range[0] : 0; + const hi = axis.y_range ? axis.y_range[1] : 1; + return axis.y_log ? Math.max(value, lo) : value; + })); + series.push({ + label: ref.label || `${ref.value}`, + stroke: ref.color || '#ffb74d', + width: 1, + dash: dashFor(ref.style), + fill: null, + points: { show: false }, + _ref: ref, + }); + }); + } + + return { x, data, series }; +} + +function dashFor(style) { + if (style === 'solid') return null; + if (style === 'dot') return [2, 3]; + return [6, 4]; +} + +function hexToRgba(hex, alpha) { + const h = hex.replace('#', ''); + const full = h.length === 3 ? h.split('').map((c) => c + c).join('') : h; + const n = parseInt(full, 16); + const r = (n >> 16) & 255, g = (n >> 8) & 255, b = n & 255; + return `rgba(${r},${g},${b},${alpha})`; +} + +function renderLegend(payload) { + const box = el('legend'); + box.innerHTML = ''; + payload.datasets.forEach((d) => { + const item = document.createElement('span'); + item.className = 'item'; + const sw = document.createElement('span'); + sw.className = 'swatch'; + sw.style.background = d.palette || paletteFor(d.file_id); + const text = document.createElement('span'); + text.textContent = d.label; + item.append(sw, text); + box.appendChild(item); + }); + + const notes = new Set(); + payload.datasets.forEach((d) => (d.payload.annotations || []).forEach((n) => notes.add( + payload.datasets.length > 1 ? `${d.label}: ${n}` : n))); + notes.forEach((n) => { + const item = document.createElement('span'); + item.className = 'item annotation'; + item.textContent = n; + box.appendChild(item); + }); +} + +function destroyPlot() { + if (state.uplot) { state.uplot.destroy(); state.uplot = null; } + el('heatmap').hidden = true; + const host = el('plot-host'); + Array.from(host.querySelectorAll('.uplot')).forEach((n) => n.remove()); +} + +function plotSize() { + const host = el('plot-host'); + const rect = host.getBoundingClientRect(); + return [Math.max(320, Math.floor(rect.width)), Math.max(180, Math.floor(rect.height))]; +} + +function buildAxes(axes) { + if (!axes) return { scales: {}, axes: [] }; + const yLog = yLogActive(); + const xLog = state.xLog === null ? !!axes.x_log : state.xLog; + + const scales = { + x: { time: false, log: xLog ? 10 : false }, + y: { log: yLog ? 10 : false }, + }; + + // Explicit ranges: the metric's own defaults, but only for the axes it frames. + // Letting uPlot auto-range a log axis over a series whose values start at 0 + // produces an unreadable scale, so ranged axes are applied as given. + if (axes.x_range) scales.x.range = [axes.x_range[0], axes.x_range[1]]; + if (axes.y_range) { + scales.y.range = (u, min, max) => (axes.y_range ? axes.y_range : [min, max]); + } else if (yLog) { + const bounds = state.payload.datasets + .map((d) => d.payload.y_bounds) + .filter(Boolean); + if (bounds.length) { + const lo = Math.min(...bounds.map((b) => Math.abs(b[0]) || 1e-3)); + const hi = Math.max(...bounds.map((b) => b[1])); + scales.y.range = (u, min, max) => [Math.max(lo, 1e-9), hi]; + } + } + + const yAxis = { + stroke: '#8b93a3', + grid: { stroke: 'rgba(255,255,255,.07)', width: 1 }, + ticks: { stroke: 'rgba(255,255,255,.12)' }, + font: '11px system-ui, sans-serif', + label: axes.y_label, + labelFont: '11px system-ui, sans-serif', + labelSize: 16, + size: 58, + values: (u, vals, space) => formatTicks(vals, space, yLog), + }; + const xAxis = { + stroke: '#8b93a3', + grid: { stroke: 'rgba(255,255,255,.07)', width: 1 }, + ticks: { stroke: 'rgba(255,255,255,.12)' }, + font: '11px system-ui, sans-serif', + label: axes.x_label, + labelFont: '11px system-ui, sans-serif', + labelSize: 16, + size: 40, + values: (u, vals, space) => formatTicks(vals, space, xLog), + }; + + return { scales, axes: [xAxis, yAxis] }; +} + +function formatTicks(vals, space, isLog) { + return vals.map((v) => { + if (v === null || v === undefined) return ''; + if (isLog) { + if (v >= 1000) return `${(v / 1000).toFixed(v >= 10000 ? 0 : 1)}k`; + if (v >= 1) return `${Math.round(v)}`; + return v.toPrecision(1); + } + const abs = Math.abs(v); + if (abs >= 1000) return `${(v / 1000).toFixed(1)}k`; + if (abs >= 100) return v.toFixed(0); + if (abs >= 1) return v.toFixed(1); + if (abs === 0) return '0'; + return v.toFixed(2); + }); +} + +/** Draw the linear-row STFT onto a canvas, mapping rows to pixels in y. */ +function renderHeatmap(payload) { + const hm = payload.datasets[0].payload.heatmap; + const canvas = el('heatmap'); + const host = el('plot-host'); + const [w, h] = plotSize(); + const dpr = window.devicePixelRatio || 1; + canvas.hidden = false; + canvas.width = Math.floor(w * dpr); + canvas.height = Math.floor(h * dpr); + canvas.style.width = `${w}px`; + canvas.style.height = `${h}px`; + const ctx = canvas.getContext('2d'); + + const padLeft = 58, padBottom = 40, padTop = 8, padRight = 10; + const plotW = Math.max(1, w - padLeft - padRight); + const plotH = Math.max(1, h - padTop - padBottom); + + const axes = payload.axes || {}; + const xRange = axes.x_range || [hm.x[0], hm.x[hm.x.length - 1]]; + const yRange = axes.y_range || [Math.max(hm.y[hm.y.length - 1], 1e-6), hm.y[0]]; + const yLog = yLogActive(); + + const rows = hm.z.length; + const cols = hm.x.length; + const lut = buildMagmaLut(256); + + // One offscreen pixel per STFT cell, then one scaled drawImage: the browser's + // bilinear scale is the interpolation, which keeps this O(cells) in JS and + // lets the GPU do the resampling for the display size. + const src = document.createElement('canvas'); + src.width = cols; + src.height = rows; + const sctx = src.getContext('2d'); + const img = sctx.createImageData(cols, rows); + const span = (hm.z_max - hm.z_min) || 1; + for (let r = 0; r < rows; r++) { + const row = hm.z[r]; + for (let c = 0; c < cols; c++) { + const t = (row[c] - hm.z_min) / span; + const idx = Math.max(0, Math.min(255, Math.round(t * 255))); + const [cr, cg, cb] = lut[idx]; + const p = (r * cols + c) * 4; + img.data[p] = cr; img.data[p + 1] = cg; img.data[p + 2] = cb; img.data[p + 3] = 255; + } + } + sctx.putImageData(img, 0, 0); + + // Rows are linear in frequency, so a linear y axis is a single stretch. A log + // axis needs row-by-row drawing: for each destination scanline work out which + // source row's frequency band it covers and blit that single row, expanded. + ctx.clearRect(0, 0, canvas.width, canvas.height); + ctx.save(); + ctx.scale(dpr, dpr); + + if (!yLog) { + // z row 0 is the lowest frequency; canvas y=0 is the top, so flip by scaling. + const destTop = padTop; + ctx.save(); + ctx.translate(padLeft, destTop + plotH); + ctx.scale(1, -1); + ctx.imageSmoothingEnabled = true; + ctx.drawImage(src, 0, 0, cols, rows, 0, 0, plotW, plotH); + ctx.restore(); + } else { + const yLo = Math.max(yRange[0], hm.y0); + const yHi = yRange[1]; + const logLo = Math.log10(yLo); + const logHi = Math.log10(yHi); + const dy = hm.dy; + for (let py = 0; py < plotH; py++) { + // canvas top = high frequency + const freqHi = Math.pow(10, logHi - (py / plotH) * (logHi - logLo)); + const freqLo = Math.pow(10, logHi - ((py + 1) / plotH) * (logHi - logLo)); + let rHi = Math.round((freqHi - hm.y0) / dy) - 1; + let rLo = Math.round((freqLo - hm.y0) / dy); + rHi = Math.max(0, Math.min(rows - 1, rHi)); + rLo = Math.max(0, Math.min(rows - 1, rLo)); + const srcRow = Math.max(0, Math.min(rows - 1, Math.floor((rHi + rLo) / 2))); + ctx.drawImage(src, 0, srcRow, cols, 1, padLeft, padTop + py, plotW, 1); + } + } + + drawHeatmapAxes(ctx, { padLeft, padTop, plotW, plotH, xRange, yRange, yLog, hm, axes }); + ctx.restore(); +} + +function drawHeatmapAxes(ctx, o) { + const { padLeft, padTop, plotW, plotH, xRange, yRange, yLog, hm, axes } = o; + ctx.font = '11px system-ui, sans-serif'; + ctx.strokeStyle = 'rgba(255,255,255,.12)'; + ctx.fillStyle = '#8b93a3'; + + // y ticks: decade lines on a log axis, ~6 even steps on a linear one. + const yTicks = []; + if (yLog) { + for (let e = Math.ceil(Math.log10(Math.max(yRange[0], 1))); e <= Math.log10(yRange[1]); e++) { + const f = Math.pow(10, e); + for (const m of [1, 2, 5]) { + const v = m * f; + if (v >= yRange[0] && v <= yRange[1]) yTicks.push(v); + } + } + } else { + const n = 5; + for (let i = 0; i <= n; i++) yTicks.push(yRange[0] + (yRange[1] - yRange[0]) * i / n); + } + const yPos = (v) => { + if (yLog) { + const t = (Math.log10(v) - Math.log10(Math.max(yRange[0], 1e-6))) / + (Math.log10(yRange[1]) - Math.log10(Math.max(yRange[0], 1e-6))); + return padTop + plotH * (1 - t); + } + const t = (v - yRange[0]) / ((yRange[1] - yRange[0]) || 1); + return padTop + plotH * (1 - t); + }; + ctx.textAlign = 'right'; + ctx.textBaseline = 'middle'; + yTicks.forEach((v) => { + const y = yPos(v); + if (y < padTop - 1 || y > padTop + plotH + 1) return; + ctx.beginPath(); ctx.moveTo(padLeft - 4, y); ctx.lineTo(padLeft, y); ctx.stroke(); + ctx.fillText(v >= 1000 ? `${(v / 1000).toFixed(1)}k` : `${Math.round(v)}`, padLeft - 7, y); + }); + + ctx.textAlign = 'center'; + ctx.textBaseline = 'top'; + const n = 6; + for (let i = 0; i <= n; i++) { + const t = i / n; + const x = padLeft + plotW * t; + const v = xRange[0] + (xRange[1] - xRange[0]) * t; + ctx.beginPath(); ctx.moveTo(x, padTop + plotH); ctx.lineTo(x, padTop + plotH + 4); ctx.stroke(); + ctx.fillText(v.toFixed(1), x, padTop + plotH + 7); + } + + ctx.fillStyle = '#8b93a3'; + ctx.textAlign = 'center'; + ctx.fillText(axes.x_label || 'Time (seconds)', padLeft + plotW / 2, padTop + plotH + 22); + ctx.save(); + ctx.translate(13, padTop + plotH / 2); + ctx.rotate(-Math.PI / 2); + ctx.textBaseline = 'middle'; + ctx.fillText(axes.y_label || 'Frequency (Hz)', 0, 0); + ctx.restore(); + + drawColorbar(ctx, hm); +} + +function drawColorbar(ctx, hm) { + // A compact colourbar in the top-right of the plot area — the desktop app + // gets this free from pyqtgraph; here it is drawn as a 14 px strip. + const x = el('plot-host').clientWidth - 74; + const y = 14, w = 12, h = 96; + const lut = buildMagmaLut(64); + for (let i = 0; i < h; i++) { + const t = 1 - i / (h - 1); + const [r, g, b] = lut[Math.round(t * 63)]; + ctx.fillStyle = `rgb(${r},${g},${b})`; + ctx.fillRect(x, y + i, w, 1); + } + ctx.strokeStyle = 'rgba(255,255,255,.25)'; + ctx.strokeRect(x, y, w, h); + ctx.fillStyle = '#8b93a3'; + ctx.font = '10px system-ui, sans-serif'; + ctx.textAlign = 'left'; + ctx.textBaseline = 'middle'; + ctx.fillText(`${hm.z_max.toFixed(0)} dB`, x + w + 4, y + 4); + ctx.fillText(`${hm.z_min.toFixed(0)} dB`, x + w + 4, y + h - 4); +} + +let _magma = null; +function buildMagmaLut(n) { + if (_magma && _magma.length === n) return _magma; + // matplotlib's 'magma' control points (256-entry table, sampled). + const stops = [ + [0.000, 0, 0, 4], [0.125, 28, 16, 68], [0.250, 79, 18, 123], [0.375, 129, 37, 129], + [0.500, 181, 54, 122], [0.625, 229, 80, 100], [0.750, 251, 135, 97], [0.875, 254, 194, 135], + [1.000, 252, 253, 191], + ]; + const lut = new Array(n); + for (let i = 0; i < n; i++) { + const t = i / (n - 1); + let a = stops[0], b = stops[stops.length - 1]; + for (let s = 0; s < stops.length - 1; s++) { + if (t >= stops[s][0] && t <= stops[s + 1][0]) { a = stops[s]; b = stops[s + 1]; break; } + } + const span = (b[0] - a[0]) || 1; + const u = (t - a[0]) / span; + lut[i] = [ + Math.round(a[1] + (b[1] - a[1]) * u), + Math.round(a[2] + (b[2] - a[2]) * u), + Math.round(a[3] + (b[3] - a[3]) * u), + ]; + } + _magma = lut; + return lut; +} + +function redrawRefs() { + if (state.payload) drawPayload(state.payload); +} + +function drawPayload(payload) { + destroyPlot(); + el('placeholder').hidden = payload.datasets.length > 0; + refreshYLogButton(); + + const dataset = payload.datasets[0]; + const heatmap = dataset && dataset.payload.heatmap; + if (heatmap) { + renderHeatmap(payload); + return; + } + + const colorFor = (d) => d.payload.series[0]?.color || d.payload.segments[0]?.color || d.palette || paletteFor(d.file_id); + const built = buildUplotData(payload, colorFor); + if (!built) return; + + const { scales, axes } = buildAxes(payload.axes || (dataset && dataset.payload.axes)); + const [w, h] = plotSize(); + const host = el('plot-host'); + + const seriesSpec = [{ label: 'x', value: (u, v) => (v == null ? '--' : v.toFixed(2)) }]; + built.series.forEach((s) => { + seriesSpec.push({ + label: s.label, + stroke: s.stroke, + width: s.width, + fill: s.fill || undefined, + dash: s.dash || undefined, + points: { show: false }, + value: (u, v) => (v == null ? '--' : v.toFixed(3)), + }); + }); + + state.uplot = new uPlot({ + width: w, + height: h, + padding: [8, 10, 8, 0], + cursor: { + drag: { x: true, y: false, setScale: false }, + sync: { key: 'ujm' }, + points: { size: 6 }, + }, + legend: { show: true, live: true }, + scales, + axes, + series: seriesSpec, + plugins: [refLineDragPlugin(built.series)], + }, built.data, host); + + el('placeholder').hidden = true; +} + +/** Drag a reference line vertically: the desktop app's draggable HLine. */ +function refLineDragPlugin(seriesList) { + return { + hooks: { + ready: (u) => { + const over = u.over; + let dragging = null; + over.addEventListener('mousedown', (e) => { + if (e.button !== 0) return; + const { top, height } = over.getBoundingClientRect(); + const yFrac = (e.clientY - top) / height; + // Convert pixel y to a value using the live scale, then find the + // nearest reference series and start moving it. + const yMin = u.scales.y.min, yMax = u.scales.y.max; + const yLog = !!u.scales.y.log; + const valueAt = (frac) => (yLog + ? Math.pow(10, Math.log10(yMax) - frac * (Math.log10(yMax) - Math.log10(yMin))) + : yMax - frac * (yMax - yMin)); + const target = valueAt(yFrac); + + let best = null, bestDist = Infinity; + seriesList.forEach((s, i) => { + if (!s._ref) return; + const dist = Math.abs(s._ref.value - target) / ((yMax - yMin) || 1); + if (dist < bestDist) { bestDist = dist; best = s._ref; } + }); + // Only grab a line you actually clicked near (6 % of the axis). + if (!best || bestDist > 0.06) return; + dragging = { ref: best, yLog }; + over.style.cursor = 'ns-resize'; + e.preventDefault(); + }); + + window.addEventListener('mousemove', (e) => { + if (!dragging) return; + const { top, height } = over.getBoundingClientRect(); + const frac = Math.min(1, Math.max(0, (e.clientY - top) / height)); + const yMin = u.scales.y.min, yMax = u.scales.y.max; + dragging.ref.value = dragging.yLog + ? Math.pow(10, Math.log10(yMax) - frac * (Math.log10(yMax) - Math.log10(yMin))) + : yMax - frac * (yMax - yMin); + syncRefInputs(); + redrawRefLine(u, dragging.ref); + }); + + window.addEventListener('mouseup', () => { + if (!dragging) return; + dragging = null; + over.style.cursor = ''; + }); + }, + }, + }; +} + +function syncRefInputs() { + const rows = document.querySelectorAll('#ref-list .ref-row'); + currentRefs().forEach((ref, i) => { + const input = rows[i] && rows[i].querySelector('input[type=number]'); + if (input && document.activeElement !== input) input.value = ref.value.toFixed(2); + }); +} + +function redrawRefLine(u, ref) { + // Cheapest correct redraw: re-set the data for the reference series. + const idx = u.series.findIndex((s, i) => i > 0 && u.series[i].label === (ref.label || `${ref.value}`)); + u.setData(u.data.map((col, i) => (i === 0 ? col : col)), false); +} + +// ---- orchestration --------------------------------------------------------- + +async function refreshPlot() { + if (state.busy) return; + state.busy = true; + const t0 = performance.now(); + setStatus('Rendering…', 'working'); + + try { + const refs = currentRefs(); + const params = new URLSearchParams({ + metric: state.metric, + x_mode: state.xMode, + refs: JSON.stringify(refs.map((r) => ({ + value: r.value, color: r.color, style: r.style, label: r.label, + }))), + }); + if (state.yLog !== null) params.set('y_log', String(state.yLog)); + if (state.xLog !== null) params.set('x_log', String(state.xLog)); + + const payload = await api(`/api/plot?${params.toString()}`); + state.payload = payload; + el('plot-title').textContent = payload.datasets.length + ? `${payload.metric_name}${payload.datasets.length > 1 ? ` — ${payload.datasets.length} tracks` : ` — ${payload.datasets[0].label}`}` + : `${payload.metric_name} — nothing selected`; + renderLegend(payload); + drawPayload(payload); + + const ms = performance.now() - t0; + setTiming(`${ms.toFixed(0)} ms round trip`); + if (payload.warnings && payload.warnings.length) { + setStatus(payload.warnings.join(' · '), 'warn'); + } else if (!payload.datasets.length) { + setStatus('Tick a file to draw it', 'warn'); + } else { + setStatus('Ready'); + } + } catch (err) { + setStatus(String(err.message || err), 'error'); + } finally { + state.busy = false; + } +} + +/** + * Ingest files: copy into browser storage, then hand the bytes to the server + * one track at a time for the currently selected metric. + * + * The order matters — the file is durable in OPFS before any request goes out, + * so a network failure leaves the audio re-analysable rather than lost. + */ +async function ingest(fileList) { + const files = Array.from(fileList).filter((f) => /\.(wav|mp3|flac|ogg|oga|m4a|aiff?|opus)$/i.test(f.name)); + if (!files.length) { + if (fileList.length) setStatus('No supported audio in that selection', 'warn'); + return; + } + + const problem = await store.storageProblem(files.reduce((n, f) => n + f.size, 0)); + if (problem) { + setStatus(`Cannot store audio locally: ${problem}`, 'error'); + return; + } + + const failures = []; + for (let i = 0; i < files.length; i += 1) { + const f = files[i]; + const tag = `(${i + 1}/${files.length}) ${f.name}`; + setStatus(`Storing ${tag} in browser…`, 'working'); + try { + const stored = await store.put(f, (done, total) => { + const pct = total ? Math.round((done / total) * 100) : 0; + setStatus(`Storing ${tag} — ${pct}%`, 'working'); + }); + setStatus(`Analysing ${tag}…`, 'working'); + await analyseOne(stored.fileId, f.name); + ensureOverlay(stored.fileId); + } catch (err) { + failures.push(`${f.name}: ${err.message || err}`); + } + } + + const s = await api('/api/session'); + state.files = s.files; + state.overlay = s.overlay; + if (!state.selected && state.files.length) state.selected = state.files[0].file_id; + renderFileList(); + renderMetadata(); + await refreshPlot(); + + if (failures.length) setStatus(failures.join(' · '), 'warn'); + else setStatus(`Ready — ${files.length} file${files.length > 1 ? 's' : ''} stored in this browser`); +} + +/** + * Send one stored track to the server for one metric. + * + * The response carries the metadata (so the file list can be built without a + * second round trip) and is recorded in `state.analysed`. + */ +async function analyseOne(fileId, name, metric = state.metric) { + const url = `/api/analyse?` + new URLSearchParams({ + file_id: fileId, + name, + metric: metric || state.metric || '', + }).toString(); + const res = await store.send(fileId, url, { method: 'POST' }); + if (!res.ok) { + let detail = `HTTP ${res.status}`; + try { detail = (await res.json()).detail || detail; } catch (_) { /* not JSON */ } + throw new Error(detail); + } + const body = await res.json(); + markAnalysed(fileId, metric); + return body; +} + +/** Make sure a track is in the overlay, so a fresh upload is visible at once. */ +function ensureOverlay(fileId) { + if (!state.overlay.includes(fileId)) { + state.overlay = [...state.overlay, fileId]; + api('/api/overlay', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ file_ids: state.overlay }), + }).catch(() => { /* next refreshPlot reconciles */ }); + } +} + +function analysedFor(fileId) { + return Array.from(state.analysed[fileId] || []); +} + +function markAnalysed(fileId, metric) { + if (!metric) return; + if (!state.analysed[fileId]) state.analysed[fileId] = new Set(); + state.analysed[fileId].add(metric); +} + +/** + * After a page reload the server still remembers the analysis but we no longer + * know which metrics we asked for. Ask each track for the current metric: the + * server answers from cache when it can, so this is cheap and re-sends bytes + * only for combinations it has never seen. + */ +/** + * Make sure every track in the overlay has the current metric computed. + * + * Cheap when the server has it cached: the request still carries the bytes, + * because that is the only way to name the track — but no decode happens. + */ +async function ensureMetricForVisible() { + const wanted = state.metric; + for (const fileId of state.overlay) { + if (analysedFor(fileId).includes(wanted)) continue; + const f = state.files.find((x) => x.file_id === fileId); + if (!f) continue; + try { + setStatus(`Analysing ${f.name} — ${wanted}…`, 'working'); + await analyseOne(fileId, f.name, wanted); + } catch (err) { + setStatus(`${f.name}: ${err.message || err}`, 'warn'); + } + } +} + +async function rehydrateAnalysed() { + for (const f of state.files) { + try { + await analyseOne(f.file_id, f.name, state.metric); + } catch (_) { + // The audio may be gone from OPFS (cleared storage); refreshPlot will + // report it as not computed rather than pretending. + } + } +} + +function wireEvents() { + el('metric-select').addEventListener('change', async (e) => { + state.metric = e.target.value; + state.refs = refsFor(state.metric); + state.yLog = null; + state.xLog = null; + renderRefList(); + // The server computes one metric per request and keeps no audio, so a new + // metric means re-offering bytes for the tracks we want to draw. Re-sends + // for anything already computed come back from cache without decoding. + await ensureMetricForVisible(); + await refreshPlot(); + }); + + el('x-mode-select').addEventListener('change', async (e) => { + state.xMode = e.target.value; + await refreshPlot(); + }); + + el('toggle-y-log').addEventListener('click', async () => { + const active = yLogActive(); + state.yLog = !active; + await refreshPlot(); + }); + + el('refresh-plot').addEventListener('click', () => refreshPlot()); + + el('pick-files').addEventListener('click', () => el('file-input').click()); + el('file-input').addEventListener('change', async (e) => { + await ingest(e.target.files); + e.target.value = ''; + e.target.value = ''; + }); + + el('add-ref').addEventListener('click', () => { + const refs = currentRefs(); + const axis = (state.payload && state.payload.axes) || {}; + const range = axis.y_range || state.payload?.datasets?.[0]?.payload?.y_bounds || [0, 1]; + const centre = axis.y_log + ? Math.pow(10, (Math.log10(Math.max(range[0], 1e-3)) + Math.log10(range[1])) / 2) + : (range[0] + range[1]) / 2; + refs.push({ + value: Number(centre.toFixed(2)), + color: PALETTE[(refs.length + 3) % PALETTE.length], + style: 'dash', + label: '', + }); + renderRefList(); + redrawRefs(); + }); + + el('clear-refs').addEventListener('click', () => { + state.refsByMetric[state.metric] = []; + state.refs = state.refsByMetric[state.metric]; + renderRefList(); + redrawRefs(); + }); + + // Drag & drop onto the window, like the desktop app's setAcceptDrops(True). + const overlay = el('drop-overlay'); + let dragDepth = 0; + window.addEventListener('dragenter', (e) => { + if (!Array.from(e.dataTransfer.types || []).includes('Files')) return; + dragDepth++; + overlay.hidden = false; + }); + window.addEventListener('dragleave', () => { + dragDepth = Math.max(0, dragDepth - 1); + if (!dragDepth) overlay.hidden = true; + }); + window.addEventListener('dragover', (e) => e.preventDefault()); + window.addEventListener('drop', async (e) => { + e.preventDefault(); + dragDepth = 0; + overlay.hidden = true; + if (e.dataTransfer.files && e.dataTransfer.files.length) await ingest(e.dataTransfer.files); + }); + + window.addEventListener('resize', () => { + if (state.payload) drawPayload(state.payload); + }); + + document.addEventListener('keydown', (e) => { + if (e.target.tagName === 'INPUT' || e.target.tagName === 'SELECT') return; + if (e.key === 'r') refreshPlot(); + if (e.key === 'l' && !el('toggle-y-log').disabled) el('toggle-y-log').click(); + }); +} + +async function boot() { + wireEvents(); + try { + if (!store.opfsSupported()) { + setStatus('This browser cannot store audio locally (no OPFS) — the web UI needs it to avoid writing to the host', 'error'); + } else { + // An upload killed mid-write leaves a partial file behind; clear those out. + const swept = await store.sweepIncomplete(); + if (swept) console.info(`cleared ${swept} incomplete upload(s)`); + } + + await loadMetrics(); + const s = await api('/api/session'); + state.files = s.files; + state.overlay = s.overlay; + state.selected = state.files.length ? state.files[0].file_id : null; + state.refs = refsFor(state.metric); + renderFileList(); + renderMetadata(); + renderRefList(); + + if (state.files.length) { + // The server remembers the analysis from the previous page load; the + // audio is in our OPFS. Re-offer bytes only where the server has nothing. + setStatus('Reconnecting to stored audio…', 'working'); + await rehydrateAnalysed(); + await refreshPlot(); + } else { + setStatus(store.opfsSupported() + ? 'Drop audio files to begin — they stay in this browser' + : 'Cannot run without local browser storage'); + } + } catch (err) { + setStatus(`Startup failed: ${err.message}`, 'error'); + } +} + +boot(); diff --git a/static/audio-store.js b/static/audio-store.js new file mode 100644 index 0000000..c2567ca --- /dev/null +++ b/static/audio-store.js @@ -0,0 +1,205 @@ +// SPDX-License-Identifier: Apache-2.0 +// +// Browser-side audio store. +// +// Uploaded audio never lives on the server. The File handle from the picker (or +// drop) is copied into Origin Private File System — a sandboxed, per-origin +// filesystem the browser owns, which no other site can read and which the OS +// treats as browser cache, not user data. Everything downstream is driven from +// there: +// +// * playback reads a blob URL minted from OPFS, so scrubbing a 60 MB WAV +// never re-reads the original File +// * the SHA-256 that identifies a track is computed over OPFS bytes, so the +// id is stable across a reload (the File handle doesn't survive one) +// * re-analysis after a page reload re-streams from OPFS instead of asking the +// user to pick the file again +// +// The server only ever sees the bytes it needs for one request, spooled to a +// temp file and deleted before the response is written. + +const OPFS_DIR = 'ujm-audio'; + +/** True when the browser can give us a durable private store. */ +export function opfsSupported() { + return !!(navigator.storage && navigator.storage.getDirectory); +} + +async function dir() { + const root = await navigator.storage.getDirectory(); + return root.getDirectoryHandle(OPFS_DIR, { create: true }); +} + +/** Human-readable reason the store is unusable, or null when it's fine. */ +export async function storageProblem(estimateBytes) { + if (!opfsSupported()) return 'this browser has no OPFS support'; + try { + const est = await navigator.storage.estimate(); + if (est.quota && estimateBytes && estimateBytes > est.quota * 0.9) { + return `need ~${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; +} + +/** + * Stream stored audio to an endpoint as a raw body. + * + * The body is sent as a stream (duplex: 'half') so a 200 MB file doesn't have to + * be materialised as a second in-memory copy just to be uploaded. + */ +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'); + + // Small files go as a plain body: some proxies mishandle streaming duplex + // requests, and below a few MB there is nothing to gain. + if (blob.size < 8 * 1024 * 1024) { + const buf = await blob.arrayBuffer(); + if (onProgress) onProgress(blob.size, blob.size); + return fetch(url, { + method, + headers: {'Content-Type': 'application/octet-stream'}, + body: buf, + }); + } + + let sent = 0; + const body = blob.stream().pipeThrough( + new TransformStream({ + transform(chunk, controller) { + sent += chunk.byteLength; + if (onProgress) onProgress(sent, blob.size); + controller.enqueue(chunk); + }, + }), + ); + return fetch(url, { + method, + headers: {'Content-Type': 'application/octet-stream'}, + body, + duplex: 'half', + }); +} diff --git a/static/index.html b/static/index.html new file mode 100644 index 0000000..b80fa70 --- /dev/null +++ b/static/index.html @@ -0,0 +1,97 @@ + + + + + +Audio Mastering Analysis Toolkit + + + + + +
+
+ + uj-mastering-master + web +
+
+ + + + +
+ + +
+
+ +
+ + + +
+
+

No track loaded

+
+
+ +
+
+

Audio Mastering Analysis Toolkit

+

Drop .mp3, .wav or .flac 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.

+
+ +
+ +
+ Ready + +
+
+
+ + + + + + + + diff --git a/static/vendor/uPlot.iife.min.js b/static/vendor/uPlot.iife.min.js new file mode 100644 index 0000000..047f29b --- /dev/null +++ b/static/vendor/uPlot.iife.min.js @@ -0,0 +1,2 @@ +/*! https://github.com/leeoniya/uPlot (v1.6.32) */ +var uPlot=function(){"use strict";const l="u-off",e="u-label",t="width",n="height",i="top",o="bottom",s="left",r="right",u="#000",a=u+"0",f="mousemove",c="mousedown",h="mouseup",d="mouseenter",p="mouseleave",m="dblclick",g="change",x="dppxchange",w="--",_="undefined"!=typeof window,b=_?document:null,v=_?window:null,k=_?navigator:null;let y,M;function S(l,e){if(null!=e){let t=l.classList;!t.contains(e)&&t.add(e)}}function T(l,e){let t=l.classList;t.contains(e)&&t.remove(e)}function E(l,e,t){l.style[e]=t+"px"}function z(l,e,t,n){let i=b.createElement(l);return null!=e&&S(i,e),null!=t&&t.insertBefore(i,n),i}function D(l,e){return z("div",l,e)}const P=new WeakMap;function A(e,t,n,i,o){let 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}, +] diff --git a/web_session.py b/web_session.py new file mode 100644 index 0000000..1892bff --- /dev/null +++ b/web_session.py @@ -0,0 +1,309 @@ +# 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 diff --git a/webapp.py b/webapp.py new file mode 100644 index 0000000..7b1874f --- /dev/null +++ b/webapp.py @@ -0,0 +1,451 @@ +# 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()