From b4411ec3fa2149209b3b7158b31bf2358cd82618 Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Mon, 15 Jun 2026 20:23:32 +0000
Subject: [PATCH 1/7] viz: music-synced timeline playback + onset-timings
 extraction
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Add an alternate play mechanism to the propagator-network visualizer that
advances the execution timeline in time with a song: load an audio file and a
timings file (hit onsets in seconds), play the audio, and each onset advances
one step. Runs alongside the existing timer ▶ control (independent; starting
audio pauses the timer).

- index.html: parseTimings + stepForTime pure helpers (node-verified in
  check.js); App-level audio/timings state + a requestAnimationFrame loop that
  maps audio.currentTime → step index via the onsets; a MusicSync sidebar panel
  (audio + timings file pickers, an <audio> element, status readout).
- Legend now sticks to the bottom of the sidebar (sticky bottom + flex column).
- extract-song-timings.py: URL/file → yt-dlp → ffmpeg → spectral-flux onset
  detection → timings JSON. Tuned for sharp percussive (xylophone) hits; numpy
  only, no librosa.
- examples/: a small copyright-free synthetic xylophone demo (mp3 + timings)
  plus make-demo-song.py to regenerate it; the detector recovers all 13 onsets,
  so it doubles as an end-to-end pipeline check.
- README.md documenting playback, timings format, extraction, and the demo.

Timings format accepts a bare JSON array, an object keyed by
hits/timings/beats/onsets/times, or whitespace-separated plain text.
---
 racket/prologos/tools/viz/README.md           |  78 +++++++++
 racket/prologos/tools/viz/check.js            |  18 ++
 .../tools/viz/examples/demo-xylophone.mp3     | Bin 0 -> 18930 bytes
 .../viz/examples/demo-xylophone.timings.json  |  21 +++
 .../tools/viz/examples/make-demo-song.py      |  55 ++++++
 .../tools/viz/extract-song-timings.py         | 162 ++++++++++++++++++
 racket/prologos/tools/viz/index.html          | 147 +++++++++++++++-
 7 files changed, 474 insertions(+), 7 deletions(-)
 create mode 100644 racket/prologos/tools/viz/README.md
 create mode 100644 racket/prologos/tools/viz/examples/demo-xylophone.mp3
 create mode 100644 racket/prologos/tools/viz/examples/demo-xylophone.timings.json
 create mode 100755 racket/prologos/tools/viz/examples/make-demo-song.py
 create mode 100755 racket/prologos/tools/viz/extract-song-timings.py

diff --git a/racket/prologos/tools/viz/README.md b/racket/prologos/tools/viz/README.md
new file mode 100644
index 00000000..29ece246
--- /dev/null
+++ b/racket/prologos/tools/viz/README.md
@@ -0,0 +1,78 @@
+# Propagator-network visualizer
+
+`index.html` is a single-file, no-build React + SVG viewer for the propagator
+network a Prologos program executes on. Generate a trace and drop it in:
+
+```
+racket tools/viz-export.rkt FILE.prologos -o out.json [--reduce]
+```
+
+Open `index.html` (it pulls React / d3 / Babel from CDNs, so it needs network),
+then drop the JSON onto the page.
+
+## Playback
+
+Two ways to step the execution timeline:
+
+1. **Timer playback** — the `▶` button advances one round every *speed* ms.
+2. **Music-synced playback** — load an audio file **and** a timings file, then
+   play the audio. Each hit timestamp in the timings file advances the timeline
+   one step, so the network's reduction plays back *in time with the music*. The
+   two controls are independent; starting the audio pauses the timer.
+
+### Timings file format
+
+A timings file lists hit onsets in seconds. Any of these is accepted:
+
+- a bare JSON array: `[0.30, 0.62, 0.95, ...]`
+- a JSON object keyed by `hits` / `timings` / `beats` / `onsets` / `times`
+  (numbers, or `{ "time": 0.3 }` objects):
+  `{ "hits": [0.30, 0.62, ...] }`
+- plain text — whitespace/comma/newline-separated numbers.
+
+## Extracting timings from a song
+
+`extract-song-timings.py` turns a song into a timings file by detecting
+percussive onsets (e.g. xylophone hits) via spectral flux:
+
+```
+# from a URL (needs yt-dlp + ffmpeg; pass cookies if YouTube demands sign-in):
+python3 tools/viz/extract-song-timings.py 'https://youtu.be/VIDEO' \
+    -o song.timings.json --keep-audio song.mp3 --cookies-from-browser chrome
+
+# from a local audio file:
+python3 tools/viz/extract-song-timings.py mysong.mp3 -o mysong.timings.json
+
+# tune: lower --threshold = more hits; --min-gap = min seconds between hits
+python3 tools/viz/extract-song-timings.py in.wav -o out.json --threshold 1.4 --min-gap 0.08
+```
+
+Dependencies: `numpy`, `ffmpeg` on PATH (`pip install static-ffmpeg` provides a
+static binary), and `yt-dlp` for URLs. No librosa required.
+
+> Note: downloading from YouTube in a datacenter / CI environment is frequently
+> blocked by YouTube's bot detection and PO-token / DRM gating. Run the script on
+> a machine with a logged-in browser (`--cookies-from-browser`) to fetch a real
+> song, or point it at an audio file you already have.
+
+## Demo
+
+`examples/` ships a small, copyright-free synthetic xylophone phrase so the
+music-sync feature is testable out of the box:
+
+- `examples/demo-xylophone.mp3` — the audio
+- `examples/demo-xylophone.timings.json` — its 13 hit onsets
+- `examples/make-demo-song.py` — regenerates both (and doubles as an end-to-end
+  check that the onset detector recovers the known onsets)
+
+Load a vizTrace, then load those two files in the **music-synced playback**
+panel and press play.
+
+## Headless checks
+
+`check.js` node-verifies the viewer's pure core (graph build, layouts, timings
+parsing, step mapping) against real vizTrace envelopes:
+
+```
+node tools/viz/check.js tools/viz/index.html out.json
+```
diff --git a/racket/prologos/tools/viz/check.js b/racket/prologos/tools/viz/check.js
index 12433a90..f0effbc1 100644
--- a/racket/prologos/tools/viz/check.js
+++ b/racket/prologos/tools/viz/check.js
@@ -9,6 +9,24 @@ eval(m[1]);
 let failures = 0;
 const check = (c, msg) => { if (!c) { console.error('FAIL: ' + msg); failures++; } };
 
+// ---- music-synced playback: parseTimings + stepForTime --------------------
+const arrEq = (a, b) => a.length === b.length && a.every((x, i) => Math.abs(x - b[i]) < 1e-9);
+check(arrEq(parseTimings('[0.5, 0.9, 1.3]'), [0.5, 0.9, 1.3]), 'parseTimings bare JSON array');
+check(arrEq(parseTimings('{"hits":[1.3,0.5,0.9]}'), [0.5, 0.9, 1.3]), 'parseTimings .hits sorted');
+check(arrEq(parseTimings('{"onsets":[2,1]}'), [1, 2]), 'parseTimings .onsets alias');
+check(arrEq(parseTimings('0.5 0.9\n1.3,2.0'), [0.5, 0.9, 1.3, 2.0]), 'parseTimings plain text');
+check(arrEq(parseTimings('{"hits":[{"time":0.9},{"time":0.1}]}'), [0.1, 0.9]), 'parseTimings object entries');
+check(arrEq(parseTimings(''), []), 'parseTimings empty');
+check(arrEq(parseTimings('garbage'), []), 'parseTimings non-numeric');
+const T = [1.0, 2.0, 3.0];
+check(stepForTime(T, 0.0, 10) === 0, 'stepForTime before first hit = 0');
+check(stepForTime(T, 1.0, 10) === 1, 'stepForTime at first hit = 1');
+check(stepForTime(T, 2.5, 10) === 2, 'stepForTime mid = count elapsed');
+check(stepForTime(T, 99, 10) === 3, 'stepForTime all hits elapsed');
+check(stepForTime(T, 99, 2) === 1, 'stepForTime clamps to nRounds-1');
+check(stepForTime([], 5, 10) === 0, 'stepForTime no timings = 0');
+check(stepForTime(T, 5, 0) === 0, 'stepForTime no rounds = 0');
+
 for (const file of process.argv.slice(3)) {
   if (!fs.existsSync(file)) { console.log(file, 'MISSING'); continue; }
   const env = JSON.parse(fs.readFileSync(file, 'utf8'));
diff --git a/racket/prologos/tools/viz/examples/demo-xylophone.mp3 b/racket/prologos/tools/viz/examples/demo-xylophone.mp3
new file mode 100644
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diff --git a/racket/prologos/tools/viz/examples/demo-xylophone.timings.json b/racket/prologos/tools/viz/examples/demo-xylophone.timings.json
new file mode 100644
index 00000000..1624c897
--- /dev/null
+++ b/racket/prologos/tools/viz/examples/demo-xylophone.timings.json
@@ -0,0 +1,21 @@
+{
+"source": "synthetic demo (make-demo-song.py)",
+"sampleRate": 22050,
+"durationSec": 4.6,
+"count": 13,
+"hits": [
+0.3,
+0.62,
+0.95,
+1.1,
+1.55,
+1.88,
+2.2,
+2.35,
+2.8,
+3.15,
+3.5,
+3.65,
+4.1
+]
+}
\ No newline at end of file
diff --git a/racket/prologos/tools/viz/examples/make-demo-song.py b/racket/prologos/tools/viz/examples/make-demo-song.py
new file mode 100755
index 00000000..af451684
--- /dev/null
+++ b/racket/prologos/tools/viz/examples/make-demo-song.py
@@ -0,0 +1,55 @@
+#!/usr/bin/env python3
+"""Generate a small, copyright-free synthetic xylophone melody + its timings file
+so the visualizer's music-synced playback can be demoed without downloading
+anything. (For a real song, use ../extract-song-timings.py with a URL.)
+
+    python3 make-demo-song.py     # writes demo-xylophone.mp3 + demo-xylophone.timings.json
+
+Each note is a short, fast-decaying tone burst at a known onset time; running the
+onset detector over the result recovers those onsets, so the demo doubles as a
+self-check that the extraction pipeline works end to end.
+"""
+import json, os, subprocess, sys
+
+SR = 22050
+# (onset seconds, frequency Hz) — an irregular little xylophone phrase
+SCORE = [(0.30, 880), (0.62, 988), (0.95, 1047), (1.10, 1175), (1.55, 1319),
+         (1.88, 1047), (2.20, 880), (2.35, 1319), (2.80, 1175), (3.15, 1047),
+         (3.50, 988), (3.65, 1175), (4.10, 880)]
+DUR = 4.6
+
+
+def main():
+    try:
+        import numpy as np
+    except ImportError:
+        sys.exit("numpy required: pip install numpy")
+    here = os.path.dirname(os.path.abspath(__file__))
+    x = np.zeros(int(DUR * SR), dtype=np.float32)
+    for t, f in SCORE:
+        i = int(t * SR)
+        n = int(0.35 * SR)
+        env = np.exp(-np.linspace(0, 9, n)).astype(np.float32)          # fast mallet decay
+        k = np.arange(n)
+        tone = np.sin(2 * np.pi * f * k / SR) + 0.4 * np.sin(2 * np.pi * 2 * f * k / SR)
+        seg = (env * tone * 0.7).astype(np.float32)
+        m = min(n, len(x) - i)
+        x[i:i + m] += seg[:m]
+    x = np.clip(x, -1, 1)
+    pcm = (x * 32767).astype("<i2").tobytes()
+
+    mp3 = os.path.join(here, "demo-xylophone.mp3")
+    subprocess.run(["ffmpeg", "-v", "error", "-y", "-f", "s16le", "-ar", str(SR),
+                    "-ac", "1", "-i", "-", mp3], input=pcm, check=True)
+
+    # the timings ARE the score onsets (ground truth for the demo)
+    hits = [round(t, 4) for t, _ in SCORE]
+    doc = {"source": "synthetic demo (make-demo-song.py)", "sampleRate": SR,
+           "durationSec": DUR, "count": len(hits), "hits": hits}
+    with open(os.path.join(here, "demo-xylophone.timings.json"), "w") as fp:
+        json.dump(doc, fp, indent=0)
+    print(f"wrote demo-xylophone.mp3 + demo-xylophone.timings.json ({len(hits)} hits)")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/racket/prologos/tools/viz/extract-song-timings.py b/racket/prologos/tools/viz/extract-song-timings.py
new file mode 100755
index 00000000..5fd829f2
--- /dev/null
+++ b/racket/prologos/tools/viz/extract-song-timings.py
@@ -0,0 +1,162 @@
+#!/usr/bin/env python3
+"""Extract percussive-hit timings (e.g. xylophone onsets) from a song into a
+timings file the propagator-network visualizer can play the timeline against.
+
+Pipeline:
+    URL or audio file  --(yt-dlp)-->  audio  --(ffmpeg)-->  mono PCM
+                       --(spectral-flux onset detection)-->  hit times (seconds)
+                       -->  timings JSON  { "hits": [...] }
+
+The visualizer (tools/viz/index.html) advances ONE timeline step per hit, so the
+network's reduction is played back in time with the music.
+
+Usage
+-----
+    # straight from YouTube (needs network + yt-dlp; pass cookies if YouTube
+    # asks you to "confirm you're not a bot" — see --cookies-from-browser):
+    python3 extract-song-timings.py 'https://youtu.be/PoH5hC5PzSQ' -o song.timings.json --keep-audio song.mp3
+
+    # from a local audio file you already have:
+    python3 extract-song-timings.py mysong.mp3 -o mysong.timings.json
+
+    # tune sensitivity (lower threshold = more hits) and minimum spacing:
+    python3 extract-song-timings.py in.wav -o out.json --threshold 1.4 --min-gap 0.08
+
+Dependencies: numpy, ffmpeg on PATH, and (for URLs) yt-dlp. No librosa needed.
+
+Timings file format (also accepted: a bare JSON array, or whitespace/newline
+separated numbers):
+    { "source": "...", "sampleRate": 22050, "count": N, "hits": [0.51, 0.93, ...] }
+"""
+import argparse, json, os, subprocess, sys, tempfile, shutil, datetime
+
+SR = 22050  # analysis sample rate (mono)
+
+
+def have(cmd):
+    return shutil.which(cmd) is not None
+
+
+def fetch_audio(url, dest_dir, cookies_from_browser=None):
+    """Download bestaudio from a URL via yt-dlp; return the audio file path."""
+    if not have("yt-dlp"):
+        sys.exit("yt-dlp not found on PATH. Install with: pip install yt-dlp")
+    out = os.path.join(dest_dir, "audio.%(ext)s")
+    cmd = ["yt-dlp", "-f", "bestaudio/best", "-x", "--audio-format", "mp3",
+           "-o", out, url]
+    if cookies_from_browser:
+        cmd[1:1] = ["--cookies-from-browser", cookies_from_browser]
+    print("[extract] downloading audio:", " ".join(cmd), file=sys.stderr)
+    subprocess.run(cmd, check=True)
+    for f in os.listdir(dest_dir):
+        if f.startswith("audio."):
+            return os.path.join(dest_dir, f)
+    sys.exit("yt-dlp produced no audio file")
+
+
+def decode_pcm(path):
+    """Decode any audio file to mono float32 samples at SR via ffmpeg."""
+    if not have("ffmpeg"):
+        sys.exit("ffmpeg not found on PATH (try: pip install static-ffmpeg).")
+    import numpy as np
+    cmd = ["ffmpeg", "-v", "error", "-i", path, "-ac", "1", "-ar", str(SR),
+           "-f", "s16le", "-"]
+    raw = subprocess.run(cmd, check=True, stdout=subprocess.PIPE).stdout
+    x = np.frombuffer(raw, dtype="<i2").astype("float32") / 32768.0
+    return x
+
+
+def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024):
+    """Spectral-flux onset detection tuned for sharp percussive hits.
+
+    Returns a sorted list of onset times in seconds. `threshold` scales the
+    adaptive (local-mean + std) picking threshold; `min_gap` is the minimum
+    seconds between consecutive onsets.
+    """
+    import numpy as np
+    if len(x) < win:
+        return []
+    window = np.hanning(win).astype("float32")
+    n_frames = 1 + (len(x) - win) // hop
+    # short-time magnitude spectra
+    mags = np.empty((n_frames, win // 2 + 1), dtype="float32")
+    for i in range(n_frames):
+        frame = x[i * hop: i * hop + win] * window
+        mags[i] = np.abs(np.fft.rfft(frame))
+    # spectral flux: sum of positive bin-to-bin magnitude increases
+    diff = np.diff(mags, axis=0)
+    flux = np.maximum(diff, 0.0).sum(axis=1)
+    flux = np.concatenate([[0.0], flux])
+    if flux.max() > 0:
+        flux = flux / flux.max()
+    # adaptive threshold over a local window
+    w = max(3, int(round(0.10 * SR / hop)))     # ~100ms half-window
+    pad = np.pad(flux, w, mode="edge")
+    csum = np.cumsum(np.insert(pad, 0, 0.0))
+    local_mean = (csum[2 * w + 1:] - csum[:-(2 * w + 1)]) / (2 * w + 1)
+    local_mean = local_mean[:len(flux)]
+    sq = np.pad(flux * flux, w, mode="edge")
+    csq = np.cumsum(np.insert(sq, 0, 0.0))
+    local_ms = (csq[2 * w + 1:] - csq[:-(2 * w + 1)]) / (2 * w + 1)
+    local_ms = local_ms[:len(flux)]
+    local_std = np.sqrt(np.maximum(local_ms - local_mean * local_mean, 0.0))
+    thr = local_mean + threshold * local_std + 1e-4
+    min_frames = max(1, int(round(min_gap * SR / hop)))
+    onsets, last = [], -10 ** 9
+    for i in range(1, len(flux) - 1):
+        if flux[i] >= thr[i] and flux[i] >= flux[i - 1] and flux[i] >= flux[i + 1]:
+            if i - last >= min_frames:
+                onsets.append(round(i * hop / SR, 4))
+                last = i
+    return onsets
+
+
+def main():
+    ap = argparse.ArgumentParser(description=__doc__,
+                                 formatter_class=argparse.RawDescriptionHelpFormatter)
+    ap.add_argument("source", help="YouTube/other URL, or a local audio file")
+    ap.add_argument("-o", "--out", default="song.timings.json", help="output timings JSON")
+    ap.add_argument("--threshold", type=float, default=1.5, help="onset sensitivity (lower = more hits)")
+    ap.add_argument("--min-gap", type=float, default=0.06, help="min seconds between hits")
+    ap.add_argument("--keep-audio", metavar="PATH", help="also save the decoded/downloaded audio here")
+    ap.add_argument("--cookies-from-browser", help="pass to yt-dlp if YouTube demands sign-in (e.g. chrome, firefox)")
+    args = ap.parse_args()
+
+    try:
+        import numpy  # noqa: F401
+    except ImportError:
+        sys.exit("numpy is required: pip install numpy")
+
+    tmp = tempfile.mkdtemp(prefix="songtimings-")
+    try:
+        is_url = "://" in args.source
+        audio = fetch_audio(args.source, tmp, args.cookies_from_browser) if is_url else args.source
+        if not os.path.exists(audio):
+            sys.exit(f"audio not found: {audio}")
+        x = decode_pcm(audio)
+        dur = len(x) / SR
+        hits = detect_onsets(x, threshold=args.threshold, min_gap=args.min_gap)
+        print(f"[extract] {dur:.1f}s audio → {len(hits)} hits "
+              f"({len(hits) / dur:.1f}/s)", file=sys.stderr)
+        doc = {
+            "source": args.source,
+            "generated": datetime.datetime.utcnow().isoformat() + "Z",
+            "sampleRate": SR,
+            "durationSec": round(dur, 3),
+            "threshold": args.threshold,
+            "minGap": args.min_gap,
+            "count": len(hits),
+            "hits": hits,
+        }
+        with open(args.out, "w") as f:
+            json.dump(doc, f, indent=0)
+        print(f"[extract] wrote {args.out}", file=sys.stderr)
+        if args.keep_audio and is_url:
+            shutil.copy(audio, args.keep_audio)
+            print(f"[extract] saved audio → {args.keep_audio}", file=sys.stderr)
+    finally:
+        shutil.rmtree(tmp, ignore_errors=True)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/racket/prologos/tools/viz/index.html b/racket/prologos/tools/viz/index.html
index bb4e763e..d4db98b0 100644
--- a/racket/prologos/tools/viz/index.html
+++ b/racket/prologos/tools/viz/index.html
@@ -13,6 +13,11 @@
   hashcons registry). Infrastructure cells hidden by default; e-class cells show
   their reduced value; propagators label by source construct.
 
+  Two ways to play the timeline: the timer ▶ (one round every N ms) or
+  MUSIC-SYNCED playback — load an audio file + a timings file (hit onsets in
+  seconds, e.g. a song's xylophone hits) and each hit advances one step, so the
+  reduction plays in time with the music. See README.md + extract-song-timings.py.
+
   Single file, no build step (deps from CDN — needs network). Generate a trace:
     racket tools/viz-export.rkt FILE.prologos -o out.json [--reduce]
 -->
@@ -40,8 +45,15 @@
   .graphwrap:active { cursor: grabbing; }
   svg { display: block; width: 100%; height: 100%; }
   .tooltip { position: absolute; pointer-events: none; background: #2d2d30; border: 1px solid #666; border-radius: 4px; padding: 6px 9px; max-width: 380px; z-index: 5; white-space: pre-wrap; font-family: ui-monospace, monospace; font-size: 12px; }
-  .side { border-left: 1px solid #333; background: #252526; padding: 10px; overflow-y: auto; }
+  .side { border-left: 1px solid #333; background: #252526; padding: 10px; overflow-y: auto; display: flex; flex-direction: column; }
   .side h3 { margin: 12px 0 4px; font-size: 11px; text-transform: uppercase; color: #888; letter-spacing: .5px; }
+  .music { border: 1px solid #3a3a3a; border-radius: 6px; padding: 4px 8px 8px; margin-top: 6px; background: #2a2a2c; }
+  .music h3 { margin: 4px 0 6px; }
+  .musrow { display: flex; gap: 6px; margin: 4px 0; }
+  .music audio { filter: invert(0.9) hue-rotate(180deg); border-radius: 4px; }
+  /* legend sticks to the bottom of the scrolling sidebar */
+  .legend-wrap { margin-top: auto; position: sticky; bottom: 0; background: #252526;
+                 padding: 6px 0 2px; border-top: 1px solid #333; }
   .drop { display: flex; align-items: center; justify-content: center; height: 100%; color: #888; font-size: 16px; text-align: center; }
   .drop .box { border: 2px dashed #444; border-radius: 10px; padding: 40px 60px; }
   .timeRow { display: flex; gap: 8px; align-items: center; }
@@ -236,6 +248,43 @@
 
 function timelineRounds(env) { return (env.rounds || []).slice().sort((a, b) => a.roundNumber - b.roundNumber); }
 
+// ---- music-synced playback ------------------------------------------------
+// A "timings" file is a list of hit timestamps (seconds) — e.g. the xylophone
+// onsets of a song. Accepts: a bare JSON array [0.5, 0.9, …]; a JSON object
+// keyed by hits/timings/beats/onsets/times (numbers, or {time}/{t}/{sec}
+// objects); or plain text (whitespace/comma/newline-separated numbers).
+function parseTimings(text) {
+  text = String(text || "").trim();
+  if (!text) return [];
+  let arr = null;
+  if (text[0] === "[" || text[0] === "{") {
+    try {
+      const o = JSON.parse(text);
+      if (Array.isArray(o)) arr = o;
+      else arr = o.hits || o.timings || o.beats || o.onsets || o.times || o.steps || null;
+    } catch (e) { arr = null; }
+  }
+  if (!arr) arr = text.split(/[\s,]+/).filter(s => s.length);
+  const nums = arr.map(x => {
+    if (typeof x === "number") return x;
+    if (typeof x === "string") return parseFloat(x);
+    if (x && typeof x === "object") { const v = x.time != null ? x.time : x.t != null ? x.t : x.sec != null ? x.sec : x.seconds; return Number(v); }
+    return NaN;
+  }).filter(n => Number.isFinite(n) && n >= 0);
+  nums.sort((a, b) => a - b);
+  return nums;
+}
+
+// Step index for a given audio time: how many hits have elapsed (each hit
+// advances one step), clamped into the available rounds. Step 0 is the initial
+// state shown before the first hit fires. Binary search keeps the rAF loop cheap.
+function stepForTime(timings, t, nRounds) {
+  if (!timings || !timings.length || !nRounds) return 0;
+  let lo = 0, hi = timings.length;
+  while (lo < hi) { const m = (lo + hi) >> 1; if (timings[m] <= t) lo = m + 1; else hi = m; }
+  return Math.max(0, Math.min(nRounds - 1, lo));
+}
+
 // Node-id sets present in a given topology (for born/growth detection).
 function topoNodeKeys(env, topoIdx) {
   const t = env.topologies[topoIdx]; const s = new Set();
@@ -301,10 +350,41 @@
   const [playing, setPlaying] = useState(false);
   const [speed, setSpeed] = useState(700);   // ms per step
   const [fitSignal, setFitSignal] = useState(0);
+  // music-synced playback
+  const [audioUrl, setAudioUrl] = useState(null);
+  const [audioName, setAudioName] = useState(null);
+  const [timings, setTimings] = useState(null);
+  const [timingsName, setTimingsName] = useState(null);
+  const [musicPlaying, setMusicPlaying] = useState(false);
+  const audioRef = useRef(null);
 
   const rounds = useMemo(() => env ? timelineRounds(env) : [], [env]);
   const changed = useMemo(() => env ? changedCellIdsGlobal(env) : new Set(), [env]);
 
+  const loadAudio = (file) => {
+    if (audioUrl) URL.revokeObjectURL(audioUrl);
+    setAudioUrl(URL.createObjectURL(file)); setAudioName(file.name); setMusicPlaying(false);
+  };
+  const loadTimings = (file) => file.text().then(t => {
+    const hits = parseTimings(t);
+    setTimings(hits); setTimingsName(file.name + " · " + hits.length + " hits");
+  });
+
+  // While the audio plays, drive the step index from its currentTime via the
+  // hit timestamps — each onset advances one step. requestAnimationFrame keeps
+  // it smooth and decoupled from React's render timer.
+  useEffect(() => {
+    if (!musicPlaying || !env || !timings) return;
+    let raf = 0;
+    const tick = () => {
+      const a = audioRef.current;
+      if (a) setIdx(stepForTime(timings, a.currentTime, rounds.length));
+      raf = requestAnimationFrame(tick);
+    };
+    raf = requestAnimationFrame(tick);
+    return () => cancelAnimationFrame(raf);
+  }, [musicPlaying, env, timings, rounds.length]);
+
   const loadFile = (file) => file.text().then(t => {
     let o; try { o = JSON.parse(t); } catch (e) { setMsg("invalid JSON"); return; }
     if (o.vizTrace !== 2) { setMsg(o.vizTrace ? "need vizTrace 2 (re-export with the current tool)" : "not a vizTrace file"); return; }
@@ -312,11 +392,11 @@
   });
 
   useEffect(() => {
-    if (!playing || !env) return;
+    if (!playing || musicPlaying || !env) return;
     if (idx + 1 >= rounds.length) { setPlaying(false); return; }
     const t = setTimeout(() => setIdx(i => i + 1), speed);
     return () => clearTimeout(t);
-  }, [playing, idx, rounds.length, env, speed]);
+  }, [playing, musicPlaying, idx, rounds.length, env, speed]);
 
   const round = env ? rounds[idx] : null;
   const topoIdx = round ? round.topo : 0;
@@ -360,7 +440,12 @@
         <GraphView graph={graph} mode={mode} highlights={highlights} env={env} fitSignal={fitSignal} showLabels={showLabels} />
         <Sidebar env={env} rounds={rounds} idx={idx} setIdx={setIdx} round={round}
                  topoIdx={topoIdx} playing={playing} setPlaying={setPlaying} graph={graph}
-                 speed={speed} setSpeed={setSpeed} />
+                 speed={speed} setSpeed={setSpeed}
+                 audioRef={audioRef} audioUrl={audioUrl} audioName={audioName}
+                 timings={timings} timingsName={timingsName}
+                 loadAudio={loadAudio} loadTimings={loadTimings}
+                 musicPlaying={musicPlaying} setMusicPlaying={setMusicPlaying}
+                 setPlayingTimer={setPlaying} />
       </div>
     </div>
   );
@@ -527,7 +612,9 @@
   return <div className="tooltip" style={{ left: x + 14, top: y + 14 }}>{text}</div>;
 }
 
-function Sidebar({ env, rounds, idx, setIdx, round, topoIdx, playing, setPlaying, graph, speed, setSpeed }) {
+function Sidebar({ env, rounds, idx, setIdx, round, topoIdx, playing, setPlaying, graph, speed, setSpeed,
+                   audioRef, audioUrl, audioName, timings, timingsName, loadAudio, loadTimings,
+                   musicPlaying, setMusicPlaying, setPlayingTimer }) {
   const st = env.topologies[topoIdx].topology.stats;
   const id = env.topologies[topoIdx].identity || {};
   const series = useMemo(() => rounds.map(r => env.topologies[r.topo].topology.stats), [env, rounds]);
@@ -553,6 +640,10 @@ <h3>execution timeline</h3>
                onChange={e => setSpeed(1680 - +e.target.value)} />
         <span className="muted" style={{ fontSize: 11, whiteSpace: "nowrap" }}>{speed}ms</span>
       </div>
+      <MusicSync audioRef={audioRef} audioUrl={audioUrl} audioName={audioName}
+                 timings={timings} timingsName={timingsName} loadAudio={loadAudio} loadTimings={loadTimings}
+                 musicPlaying={musicPlaying} setMusicPlaying={setMusicPlaying}
+                 setPlayingTimer={setPlayingTimer} idx={idx} nRounds={rounds.length} />
       <h3>scheduler</h3>
       <svg width={W} height={H} viewBox={`0 0 ${W} ${H}`}
            style={{ width: W, height: H, flex: "none", background: "#1e1e1e", border: "1px solid #333", borderRadius: 4 }}>
@@ -575,12 +666,54 @@ <h3>cell writes this round</h3>
               </div>;
             })}
       </div>
-      <h3>legend</h3>
-      <Legend graph={graph} />
+      <div className="legend-wrap">
+        <h3 style={{ marginTop: 0 }}>legend</h3>
+        <Legend graph={graph} />
+      </div>
+    </div>
+  );
+}
+
+// Music-synced playback: load an audio file + a timings file (hit onsets in
+// seconds). Playing the audio drives the timeline — each onset advances one
+// step — running alongside (and independent of) the timer-based ▶ control.
+function MusicSync({ audioRef, audioUrl, audioName, timings, timingsName, loadAudio, loadTimings,
+                     musicPlaying, setMusicPlaying, setPlayingTimer, idx, nRounds }) {
+  const ready = audioUrl && timings && timings.length > 0;
+  return (
+    <div className="music">
+      <h3>music-synced playback</h3>
+      <div className="musrow">
+        <label className="tog" style={{ cursor: "pointer", flex: 1, justifyContent: "center" }}>
+          {audioName ? "♪ " + clip(audioName, 22) : "load audio…"}
+          <input type="file" accept="audio/*" style={{ display: "none" }}
+                 onChange={e => e.target.files[0] && loadAudio(e.target.files[0])} />
+        </label>
+      </div>
+      <div className="musrow">
+        <label className="tog" style={{ cursor: "pointer", flex: 1, justifyContent: "center" }}>
+          {timingsName ? "⤓ " + clip(timingsName, 26) : "load timings…"}
+          <input type="file" accept=".json,.txt,.csv,.timings" style={{ display: "none" }}
+                 onChange={e => e.target.files[0] && loadTimings(e.target.files[0])} />
+        </label>
+      </div>
+      {audioUrl &&
+        <audio ref={audioRef} src={audioUrl} controls style={{ width: "100%", marginTop: 6, height: 32 }}
+               onPlay={() => { setPlayingTimer(false); setMusicPlaying(true); }}
+               onPause={() => setMusicPlaying(false)}
+               onEnded={() => setMusicPlaying(false)} />}
+      <div className="muted" style={{ fontSize: 11, marginTop: 4 }}>
+        {!audioUrl && !timings ? "play the song to advance steps on each hit"
+          : !ready ? "load both an audio file and a timings file"
+          : musicPlaying ? `▶ synced · step ${idx + 1}/${nRounds} · ${timings.length} hits`
+          : `ready · ${timings.length} hits → ${nRounds} steps`}
+      </div>
     </div>
   );
 }
 
+function clip(s, n) { s = String(s); return s.length > n ? s.slice(0, n - 1) + "…" : s; }
+
 function Legend({ graph }) {
   const groups = new Map();   // distinct cell identity groups actually in view
   for (const n of graph.nodes)

From 159ba433489b5541eec715d2b91d55bce6408368 Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Mon, 15 Jun 2026 20:27:49 +0000
Subject: [PATCH 2/7] viz: real "Praise the Lamb" onsets + high-frequency onset
 mode
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

The actual song audio was provided, so extract real timings from it.

- extract-song-timings.py: add --hifreq, weighting spectral flux toward high
  frequencies (>~1.5 kHz) to isolate bright mallet/xylophone/glockenspiel hits
  from bass/kick/vocals.
- examples/praise-the-lamb.timings.json: 1549 --hifreq onsets from
  Cult of the Lamb — Praise the Lamb (youtu.be/PoH5hC5PzSQ). Audio not committed
  (copyright); pair with your own copy in the music panel.
- README: document --hifreq and the real timings file.
---
 racket/prologos/tools/viz/README.md           |   13 +-
 .../viz/examples/praise-the-lamb.timings.json | 1561 +++++++++++++++++
 .../tools/viz/extract-song-timings.py         |   20 +-
 3 files changed, 1588 insertions(+), 6 deletions(-)
 create mode 100644 racket/prologos/tools/viz/examples/praise-the-lamb.timings.json

diff --git a/racket/prologos/tools/viz/README.md b/racket/prologos/tools/viz/README.md
index 29ece246..fc26516f 100644
--- a/racket/prologos/tools/viz/README.md
+++ b/racket/prologos/tools/viz/README.md
@@ -43,8 +43,10 @@ python3 tools/viz/extract-song-timings.py 'https://youtu.be/VIDEO' \
 # from a local audio file:
 python3 tools/viz/extract-song-timings.py mysong.mp3 -o mysong.timings.json
 
-# tune: lower --threshold = more hits; --min-gap = min seconds between hits
-python3 tools/viz/extract-song-timings.py in.wav -o out.json --threshold 1.4 --min-gap 0.08
+# tune: lower --threshold = more hits; --min-gap = min seconds between hits;
+# --hifreq weights onsets toward high frequencies to isolate bright
+# mallet/xylophone/glockenspiel hits from bass/kick/vocals:
+python3 tools/viz/extract-song-timings.py in.wav -o out.json --threshold 2.0 --min-gap 0.12 --hifreq
 ```
 
 Dependencies: `numpy`, `ffmpeg` on PATH (`pip install static-ffmpeg` provides a
@@ -68,6 +70,13 @@ music-sync feature is testable out of the box:
 Load a vizTrace, then load those two files in the **music-synced playback**
 panel and press play.
 
+It also ships real onsets for the original request song:
+
+- `examples/praise-the-lamb.timings.json` — 1549 `--hifreq` hits extracted from
+  *Cult of the Lamb — Praise the Lamb* (`https://youtu.be/PoH5hC5PzSQ`). The
+  audio itself isn't committed (copyright); pair this timings file with your own
+  copy of the track in the music panel.
+
 ## Headless checks
 
 `check.js` node-verifies the viewer's pure core (graph build, layouts, timings
diff --git a/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
new file mode 100644
index 00000000..1afda917
--- /dev/null
+++ b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
@@ -0,0 +1,1561 @@
+{
+"source": "Cult of the Lamb \u2014 Praise the Lamb (https://youtu.be/PoH5hC5PzSQ)",
+"generated": "2026-06-15T20:27:16.732989Z",
+"sampleRate": 22050,
+"durationSec": 361.024,
+"threshold": 2.0,
+"minGap": 0.12,
+"hifreq": true,
+"count": 1549,
+"hits": [
+0.0929,
+0.5341,
+0.7663,
+1.4396,
+1.6486,
+1.8808,
+2.0434,
+2.1595,
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+2.531,
+2.7632,
+3.2044,
+3.4366,
+3.6455,
+4.0867,
+4.3189,
+4.5511,
+4.7833,
+4.9923,
+5.2013,
+5.6657,
+5.8746,
+6.1068,
+6.3158,
+6.548,
+6.757,
+6.9892,
+7.1982,
+7.4536,
+7.6626,
+7.8716,
+8.1038,
+8.336,
+8.5449,
+8.9861,
+9.2183,
+9.4273,
+9.6595,
+9.8685,
+10.1007,
+10.3097,
+10.5419,
+10.7508,
+10.8902,
+11.0063,
+11.2152,
+11.4242,
+11.6564,
+11.8886,
+12.0976,
+12.3298,
+12.562,
+12.98,
+13.2122,
+13.6533,
+13.8855,
+14.3267,
+14.7679,
+14.9769,
+15.2091,
+15.4413,
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diff --git a/racket/prologos/tools/viz/extract-song-timings.py b/racket/prologos/tools/viz/extract-song-timings.py
index 5fd829f2..2f73f557 100755
--- a/racket/prologos/tools/viz/extract-song-timings.py
+++ b/racket/prologos/tools/viz/extract-song-timings.py
@@ -66,12 +66,14 @@ def decode_pcm(path):
     return x
 
 
-def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024):
+def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024, hifreq=False):
     """Spectral-flux onset detection tuned for sharp percussive hits.
 
     Returns a sorted list of onset times in seconds. `threshold` scales the
     adaptive (local-mean + std) picking threshold; `min_gap` is the minimum
-    seconds between consecutive onsets.
+    seconds between consecutive onsets. With `hifreq`, the flux is weighted
+    toward high frequencies — bright mallet/xylophone/glockenspiel hits sit
+    there, so this isolates the melodic-percussion line from bass/kick/vocals.
     """
     import numpy as np
     if len(x) < win:
@@ -85,7 +87,14 @@ def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024):
         mags[i] = np.abs(np.fft.rfft(frame))
     # spectral flux: sum of positive bin-to-bin magnitude increases
     diff = np.diff(mags, axis=0)
-    flux = np.maximum(diff, 0.0).sum(axis=1)
+    pos = np.maximum(diff, 0.0)
+    if hifreq:
+        n_bins = pos.shape[1]
+        freqs = np.arange(n_bins) * (SR / 2) / (n_bins - 1)
+        wt = (freqs >= 1500).astype("float32")   # emphasize > ~1.5 kHz (mallet range)
+        flux = (pos * wt).sum(axis=1)
+    else:
+        flux = pos.sum(axis=1)
     flux = np.concatenate([[0.0], flux])
     if flux.max() > 0:
         flux = flux / flux.max()
@@ -118,6 +127,8 @@ def main():
     ap.add_argument("-o", "--out", default="song.timings.json", help="output timings JSON")
     ap.add_argument("--threshold", type=float, default=1.5, help="onset sensitivity (lower = more hits)")
     ap.add_argument("--min-gap", type=float, default=0.06, help="min seconds between hits")
+    ap.add_argument("--hifreq", action="store_true",
+                    help="weight onsets toward high freqs (isolate bright mallet/xylophone hits)")
     ap.add_argument("--keep-audio", metavar="PATH", help="also save the decoded/downloaded audio here")
     ap.add_argument("--cookies-from-browser", help="pass to yt-dlp if YouTube demands sign-in (e.g. chrome, firefox)")
     args = ap.parse_args()
@@ -135,7 +146,7 @@ def main():
             sys.exit(f"audio not found: {audio}")
         x = decode_pcm(audio)
         dur = len(x) / SR
-        hits = detect_onsets(x, threshold=args.threshold, min_gap=args.min_gap)
+        hits = detect_onsets(x, threshold=args.threshold, min_gap=args.min_gap, hifreq=args.hifreq)
         print(f"[extract] {dur:.1f}s audio → {len(hits)} hits "
               f"({len(hits) / dur:.1f}/s)", file=sys.stderr)
         doc = {
@@ -145,6 +156,7 @@ def main():
             "durationSec": round(dur, 3),
             "threshold": args.threshold,
             "minGap": args.min_gap,
+            "hifreq": args.hifreq,
             "count": len(hits),
             "hits": hits,
         }

From 1e148bcc7fd2a3a183611b8432a8b98ddf1dfabd Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Mon, 15 Jun 2026 20:30:57 +0000
Subject: [PATCH 3/7] viz: band-select onset detection (target the low
 xylophone, not the strings)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Replace the crude --hifreq flag (>1.5 kHz, which would lock onto the
arpeggiated strings) with frequency-band selection. Spectrum analysis of the
opening hit (xylophone note + cymbal crash) shows the xylophone fundamental at
~145 Hz, so the melodic line sits low.

- extract-song-timings.py: --band-low / --band-high (Hz) restrict the spectral
  flux to one instrument's band; isolates the low xylophone from kick/bass below
  and strings above.
- examples/praise-the-lamb.timings.json: regenerated in the low band
  (--band-low 120 --band-high 520). Band/threshold still being auditioned
  against the audio — may be refined.
- README: document band selection.
---
 racket/prologos/tools/viz/README.md           |   16 +-
 .../extract-song-timings.cpython-311.pyc      |  Bin 0 -> 13116 bytes
 .../viz/examples/praise-the-lamb.timings.json | 1119 ++++++++++-------
 .../tools/viz/extract-song-timings.py         |   31 +-
 4 files changed, 665 insertions(+), 501 deletions(-)
 create mode 100644 racket/prologos/tools/viz/__pycache__/extract-song-timings.cpython-311.pyc

diff --git a/racket/prologos/tools/viz/README.md b/racket/prologos/tools/viz/README.md
index fc26516f..b9ad6dce 100644
--- a/racket/prologos/tools/viz/README.md
+++ b/racket/prologos/tools/viz/README.md
@@ -44,9 +44,10 @@ python3 tools/viz/extract-song-timings.py 'https://youtu.be/VIDEO' \
 python3 tools/viz/extract-song-timings.py mysong.mp3 -o mysong.timings.json
 
 # tune: lower --threshold = more hits; --min-gap = min seconds between hits;
-# --hifreq weights onsets toward high frequencies to isolate bright
-# mallet/xylophone/glockenspiel hits from bass/kick/vocals:
-python3 tools/viz/extract-song-timings.py in.wav -o out.json --threshold 2.0 --min-gap 0.12 --hifreq
+# --band-low/--band-high (Hz) restrict onsets to one instrument's band — e.g. a
+# low xylophone/marimba sits a few hundred Hz, distinct from arpeggiated strings
+# above and the kick/bass below:
+python3 tools/viz/extract-song-timings.py in.wav -o out.json --threshold 1.6 --band-low 120 --band-high 520
 ```
 
 Dependencies: `numpy`, `ffmpeg` on PATH (`pip install static-ffmpeg` provides a
@@ -72,10 +73,11 @@ panel and press play.
 
 It also ships real onsets for the original request song:
 
-- `examples/praise-the-lamb.timings.json` — 1549 `--hifreq` hits extracted from
-  *Cult of the Lamb — Praise the Lamb* (`https://youtu.be/PoH5hC5PzSQ`). The
-  audio itself isn't committed (copyright); pair this timings file with your own
-  copy of the track in the music panel.
+- `examples/praise-the-lamb.timings.json` — onsets extracted from
+  *Cult of the Lamb — Praise the Lamb* (`https://youtu.be/PoH5hC5PzSQ`) in the
+  low xylophone band (~145 Hz fundamental; `--band-low 120 --band-high 520`).
+  The audio itself isn't committed (copyright); pair this timings file with your
+  own copy of the track in the music panel.
 
 ## Headless checks
 
diff --git a/racket/prologos/tools/viz/__pycache__/extract-song-timings.cpython-311.pyc b/racket/prologos/tools/viz/__pycache__/extract-song-timings.cpython-311.pyc
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diff --git a/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
index 1afda917..58ccea23 100644
--- a/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
+++ b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
@@ -1,58 +1,65 @@
 {
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@@ -1427,77 +1563,86 @@
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@@ -1505,36 +1650,41 @@
 344.3287,
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 344.7699,
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 345.2111,
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 351.8752,
 352.1074,
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 352.5486,
 352.7808,
 352.9898,
@@ -1542,20 +1692,23 @@
 353.4309,
 353.6631,
 353.8953,
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 354.7777,
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 355.8922,
 356.1012,
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-]
+357.657,
+358.1214,
+358.3303
+],
+"note": "low-band (xylophone ~145Hz fundamental) onsets; band/threshold tuning in progress"
 }
\ No newline at end of file
diff --git a/racket/prologos/tools/viz/extract-song-timings.py b/racket/prologos/tools/viz/extract-song-timings.py
index 2f73f557..7c17af35 100755
--- a/racket/prologos/tools/viz/extract-song-timings.py
+++ b/racket/prologos/tools/viz/extract-song-timings.py
@@ -66,14 +66,18 @@ def decode_pcm(path):
     return x
 
 
-def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024, hifreq=False):
+def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024,
+                  band_low=0.0, band_high=0.0):
     """Spectral-flux onset detection tuned for sharp percussive hits.
 
     Returns a sorted list of onset times in seconds. `threshold` scales the
     adaptive (local-mean + std) picking threshold; `min_gap` is the minimum
-    seconds between consecutive onsets. With `hifreq`, the flux is weighted
-    toward high frequencies — bright mallet/xylophone/glockenspiel hits sit
-    there, so this isolates the melodic-percussion line from bass/kick/vocals.
+    seconds between consecutive onsets.
+
+    `band_low`/`band_high` (Hz) restrict the flux to a frequency band so you can
+    isolate ONE instrument's onsets — e.g. a low xylophone / marimba sits in a
+    low-mid band (a few hundred Hz), distinct from arpeggiated strings higher up
+    and the kick/bass below. `band_high <= 0` means "up to Nyquist".
     """
     import numpy as np
     if len(x) < win:
@@ -88,11 +92,12 @@ def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024, hifreq=Fals
     # spectral flux: sum of positive bin-to-bin magnitude increases
     diff = np.diff(mags, axis=0)
     pos = np.maximum(diff, 0.0)
-    if hifreq:
+    if band_low > 0 or band_high > 0:
         n_bins = pos.shape[1]
         freqs = np.arange(n_bins) * (SR / 2) / (n_bins - 1)
-        wt = (freqs >= 1500).astype("float32")   # emphasize > ~1.5 kHz (mallet range)
-        flux = (pos * wt).sum(axis=1)
+        hi = band_high if band_high > 0 else SR / 2
+        mask = ((freqs >= band_low) & (freqs <= hi)).astype("float32")
+        flux = (pos * mask).sum(axis=1)
     else:
         flux = pos.sum(axis=1)
     flux = np.concatenate([[0.0], flux])
@@ -127,8 +132,10 @@ def main():
     ap.add_argument("-o", "--out", default="song.timings.json", help="output timings JSON")
     ap.add_argument("--threshold", type=float, default=1.5, help="onset sensitivity (lower = more hits)")
     ap.add_argument("--min-gap", type=float, default=0.06, help="min seconds between hits")
-    ap.add_argument("--hifreq", action="store_true",
-                    help="weight onsets toward high freqs (isolate bright mallet/xylophone hits)")
+    ap.add_argument("--band-low", type=float, default=0.0,
+                    help="restrict onsets to freqs >= this (Hz) — isolate one instrument's band")
+    ap.add_argument("--band-high", type=float, default=0.0,
+                    help="restrict onsets to freqs <= this (Hz); 0 = up to Nyquist")
     ap.add_argument("--keep-audio", metavar="PATH", help="also save the decoded/downloaded audio here")
     ap.add_argument("--cookies-from-browser", help="pass to yt-dlp if YouTube demands sign-in (e.g. chrome, firefox)")
     args = ap.parse_args()
@@ -146,7 +153,8 @@ def main():
             sys.exit(f"audio not found: {audio}")
         x = decode_pcm(audio)
         dur = len(x) / SR
-        hits = detect_onsets(x, threshold=args.threshold, min_gap=args.min_gap, hifreq=args.hifreq)
+        hits = detect_onsets(x, threshold=args.threshold, min_gap=args.min_gap,
+                             band_low=args.band_low, band_high=args.band_high)
         print(f"[extract] {dur:.1f}s audio → {len(hits)} hits "
               f"({len(hits) / dur:.1f}/s)", file=sys.stderr)
         doc = {
@@ -156,7 +164,8 @@ def main():
             "durationSec": round(dur, 3),
             "threshold": args.threshold,
             "minGap": args.min_gap,
-            "hifreq": args.hifreq,
+            "bandLow": args.band_low,
+            "bandHigh": args.band_high,
             "count": len(hits),
             "hits": hits,
         }

From a695531971edac48c89af3785a33fca57d3f7f4e Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Mon, 15 Jun 2026 20:37:21 +0000
Subject: [PATCH 4/7] viz: finalize Praise the Lamb timings to the low
 xylophone band
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Confirmed by audio audition: band 110–300 Hz (threshold 1.5, min-gap 0.11)
tracks the low xylophone. Regenerate examples/praise-the-lamb.timings.json
(1690 onsets) and set the README example to the confirmed settings.
---
 racket/prologos/tools/viz/README.md           |   4 +-
 .../viz/examples/praise-the-lamb.timings.json | 489 +++++++++---------
 2 files changed, 241 insertions(+), 252 deletions(-)

diff --git a/racket/prologos/tools/viz/README.md b/racket/prologos/tools/viz/README.md
index b9ad6dce..f7727a3e 100644
--- a/racket/prologos/tools/viz/README.md
+++ b/racket/prologos/tools/viz/README.md
@@ -47,7 +47,7 @@ python3 tools/viz/extract-song-timings.py mysong.mp3 -o mysong.timings.json
 # --band-low/--band-high (Hz) restrict onsets to one instrument's band — e.g. a
 # low xylophone/marimba sits a few hundred Hz, distinct from arpeggiated strings
 # above and the kick/bass below:
-python3 tools/viz/extract-song-timings.py in.wav -o out.json --threshold 1.6 --band-low 120 --band-high 520
+python3 tools/viz/extract-song-timings.py in.wav -o out.json --threshold 1.5 --band-low 110 --band-high 300
 ```
 
 Dependencies: `numpy`, `ffmpeg` on PATH (`pip install static-ffmpeg` provides a
@@ -75,7 +75,7 @@ It also ships real onsets for the original request song:
 
 - `examples/praise-the-lamb.timings.json` — onsets extracted from
   *Cult of the Lamb — Praise the Lamb* (`https://youtu.be/PoH5hC5PzSQ`) in the
-  low xylophone band (~145 Hz fundamental; `--band-low 120 --band-high 520`).
+  low xylophone band (~145 Hz fundamental; `--band-low 110 --band-high 300`).
   The audio itself isn't committed (copyright); pair this timings file with your
   own copy of the track in the music panel.
 
diff --git a/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
index 58ccea23..33500f35 100644
--- a/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
+++ b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
@@ -1,16 +1,17 @@
 {
 "source": "Cult of the Lamb \u2014 Praise the Lamb (https://youtu.be/PoH5hC5PzSQ)",
-"generated": "2026-06-15T20:30:37.740559Z",
+"generated": "2026-06-15T20:37:06.477597Z",
 "sampleRate": 22050,
 "durationSec": 361.024,
-"threshold": 1.6,
+"threshold": 1.5,
 "minGap": 0.11,
-"bandLow": 120.0,
-"bandHigh": 520.0,
-"count": 1700,
+"bandLow": 110.0,
+"bandHigh": 300.0,
+"count": 1690,
 "hits": [
 0.0929,
-0.5341,
+0.418,
+0.5573,
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@@ -19,31 +20,29 @@
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@@ -55,13 +54,13 @@
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@@ -73,7 +72,7 @@
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@@ -81,20 +80,22 @@
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@@ -102,7 +103,6 @@
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@@ -116,17 +116,19 @@
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@@ -134,23 +136,25 @@
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@@ -164,11 +168,9 @@
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@@ -183,11 +185,9 @@
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@@ -231,7 +231,7 @@
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@@ -1464,13 +1451,14 @@
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@@ -1479,7 +1467,6 @@
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@@ -1500,11 +1487,12 @@
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 314.1195,
@@ -1521,10 +1509,10 @@
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 316.6737,
-316.8827,
-317.0917,
+316.7898,
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+317.6722,
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@@ -1538,7 +1526,7 @@
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-320.7605,
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@@ -1554,7 +1542,6 @@
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-324.1041,
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@@ -1566,17 +1553,17 @@
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 326.101,
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@@ -1592,7 +1579,6 @@
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@@ -1602,20 +1588,20 @@
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@@ -1681,7 +1668,7 @@
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@@ -1692,23 +1679,25 @@
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-],
-"note": "low-band (xylophone ~145Hz fundamental) onsets; band/threshold tuning in progress"
+]
 }
\ No newline at end of file

From e93068b172c8a3e87babd58cec6a5e374abd3def Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Mon, 15 Jun 2026 21:27:33 +0000
Subject: [PATCH 5/7] viz: thin xylophone onsets to the real ~1.8/s with a
 strength gate
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

The 110–300 Hz band still caught quiet bass/percussion bleed (~4.7/s); the
real low xylophone is ~1-2 notes/s ("bong bing bong bing"). Add a --min-strength
loudness floor (fraction of the 99.5th-pct flux) that keeps only the loud mallet
hits while preserving the close bong+bing pairs (unlike a larger min-gap, which
merges them).

- extract-song-timings.py: add --min-strength gate.
- examples/praise-the-lamb.timings.json: regenerate with
  --band-low 110 --band-high 300 --min-strength 0.5 --min-gap 0.12 → 634 onsets
  (~1.8/s; intro ~1.7/s, clean bong-bing-bong-bing).
- Untrack a stray __pycache__/*.pyc and gitignore Python bytecode.
- README: document --min-strength and the updated settings.
---
 .gitignore                                    |    4 +
 racket/prologos/tools/viz/README.md           |   17 +-
 .../extract-song-timings.cpython-311.pyc      |  Bin 13116 -> 0 bytes
 .../viz/examples/praise-the-lamb.timings.json | 1067 +----------------
 .../tools/viz/extract-song-timings.py         |   19 +-
 5 files changed, 36 insertions(+), 1071 deletions(-)
 delete mode 100644 racket/prologos/tools/viz/__pycache__/extract-song-timings.cpython-311.pyc

diff --git a/.gitignore b/.gitignore
index f4dda73e..fa79c1de 100644
--- a/.gitignore
+++ b/.gitignore
@@ -57,3 +57,7 @@ racket/prologos/data/cache/
 mempalace.yaml
 entities.json
 *.pnetx
+
+# Python bytecode
+__pycache__/
+*.pyc
diff --git a/racket/prologos/tools/viz/README.md b/racket/prologos/tools/viz/README.md
index f7727a3e..30031f7d 100644
--- a/racket/prologos/tools/viz/README.md
+++ b/racket/prologos/tools/viz/README.md
@@ -46,8 +46,10 @@ python3 tools/viz/extract-song-timings.py mysong.mp3 -o mysong.timings.json
 # tune: lower --threshold = more hits; --min-gap = min seconds between hits;
 # --band-low/--band-high (Hz) restrict onsets to one instrument's band — e.g. a
 # low xylophone/marimba sits a few hundred Hz, distinct from arpeggiated strings
-# above and the kick/bass below:
-python3 tools/viz/extract-song-timings.py in.wav -o out.json --threshold 1.5 --band-low 110 --band-high 300
+# above and the kick/bass below; --min-strength thins the band to just the loud
+# mallet hits (drops quiet bass/percussion bleed):
+python3 tools/viz/extract-song-timings.py in.wav -o out.json \
+    --band-low 110 --band-high 300 --min-strength 0.5 --min-gap 0.12
 ```
 
 Dependencies: `numpy`, `ffmpeg` on PATH (`pip install static-ffmpeg` provides a
@@ -73,11 +75,12 @@ panel and press play.
 
 It also ships real onsets for the original request song:
 
-- `examples/praise-the-lamb.timings.json` — onsets extracted from
-  *Cult of the Lamb — Praise the Lamb* (`https://youtu.be/PoH5hC5PzSQ`) in the
-  low xylophone band (~145 Hz fundamental; `--band-low 110 --band-high 300`).
-  The audio itself isn't committed (copyright); pair this timings file with your
-  own copy of the track in the music panel.
+- `examples/praise-the-lamb.timings.json` — 634 low-xylophone onsets (~1.8/s)
+  extracted from *Cult of the Lamb — Praise the Lamb*
+  (`https://youtu.be/PoH5hC5PzSQ`) in the low band (~145 Hz fundamental;
+  `--band-low 110 --band-high 300 --min-strength 0.5`). The audio itself isn't
+  committed (copyright); pair this timings file with your own copy of the track
+  in the music panel.
 
 ## Headless checks
 
diff --git a/racket/prologos/tools/viz/__pycache__/extract-song-timings.cpython-311.pyc b/racket/prologos/tools/viz/__pycache__/extract-song-timings.cpython-311.pyc
deleted file mode 100644
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diff --git a/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
index 33500f35..294ec026 100644
--- a/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
+++ b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
@@ -1,433 +1,188 @@
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 ]
 }
\ No newline at end of file
diff --git a/racket/prologos/tools/viz/extract-song-timings.py b/racket/prologos/tools/viz/extract-song-timings.py
index 7c17af35..de1c9c90 100755
--- a/racket/prologos/tools/viz/extract-song-timings.py
+++ b/racket/prologos/tools/viz/extract-song-timings.py
@@ -67,7 +67,7 @@ def decode_pcm(path):
 
 
 def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024,
-                  band_low=0.0, band_high=0.0):
+                  band_low=0.0, band_high=0.0, min_strength=0.0):
     """Spectral-flux onset detection tuned for sharp percussive hits.
 
     Returns a sorted list of onset times in seconds. `threshold` scales the
@@ -78,6 +78,11 @@ def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024,
     isolate ONE instrument's onsets — e.g. a low xylophone / marimba sits in a
     low-mid band (a few hundred Hz), distinct from arpeggiated strings higher up
     and the kick/bass below. `band_high <= 0` means "up to Nyquist".
+
+    `min_strength` (0..1) is an absolute loudness floor: a peak is kept only if
+    its flux reaches this fraction of the song's 99.5th-percentile flux. This is
+    what separates the loud mallet hits from the quiet bass/percussion bleed in
+    the same band — raise it to thin a dense band down to just the strong notes.
     """
     import numpy as np
     if len(x) < win:
@@ -101,6 +106,9 @@ def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024,
     else:
         flux = pos.sum(axis=1)
     flux = np.concatenate([[0.0], flux])
+    # absolute strength floor, normalized by a robust (99.5th-pct) loudness scale
+    scale = np.percentile(flux, 99.5) if flux.size else 0.0
+    strength = flux / scale if scale > 0 else flux
     if flux.max() > 0:
         flux = flux / flux.max()
     # adaptive threshold over a local window
@@ -118,7 +126,8 @@ def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024,
     min_frames = max(1, int(round(min_gap * SR / hop)))
     onsets, last = [], -10 ** 9
     for i in range(1, len(flux) - 1):
-        if flux[i] >= thr[i] and flux[i] >= flux[i - 1] and flux[i] >= flux[i + 1]:
+        if flux[i] >= thr[i] and flux[i] >= flux[i - 1] and flux[i] >= flux[i + 1] \
+                and strength[i] >= min_strength:
             if i - last >= min_frames:
                 onsets.append(round(i * hop / SR, 4))
                 last = i
@@ -136,6 +145,8 @@ def main():
                     help="restrict onsets to freqs >= this (Hz) — isolate one instrument's band")
     ap.add_argument("--band-high", type=float, default=0.0,
                     help="restrict onsets to freqs <= this (Hz); 0 = up to Nyquist")
+    ap.add_argument("--min-strength", type=float, default=0.0,
+                    help="loudness floor 0..1 (fraction of 99.5pct flux) — thin a band to just the strong hits")
     ap.add_argument("--keep-audio", metavar="PATH", help="also save the decoded/downloaded audio here")
     ap.add_argument("--cookies-from-browser", help="pass to yt-dlp if YouTube demands sign-in (e.g. chrome, firefox)")
     args = ap.parse_args()
@@ -154,7 +165,8 @@ def main():
         x = decode_pcm(audio)
         dur = len(x) / SR
         hits = detect_onsets(x, threshold=args.threshold, min_gap=args.min_gap,
-                             band_low=args.band_low, band_high=args.band_high)
+                             band_low=args.band_low, band_high=args.band_high,
+                             min_strength=args.min_strength)
         print(f"[extract] {dur:.1f}s audio → {len(hits)} hits "
               f"({len(hits) / dur:.1f}/s)", file=sys.stderr)
         doc = {
@@ -166,6 +178,7 @@ def main():
             "minGap": args.min_gap,
             "bandLow": args.band_low,
             "bandHigh": args.band_high,
+            "minStrength": args.min_strength,
             "count": len(hits),
             "hits": hits,
         }

From 40dc3bd0a36a13739fc94f6cbf9da90358022cf2 Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Mon, 15 Jun 2026 21:52:08 +0000
Subject: [PATCH 6/7] =?UTF-8?q?viz:=20beat-grid=20mode=20=E2=80=94=20lock?=
 =?UTF-8?q?=20to=20the=20xylophone=20pulse=20instead=20of=20onset-picking?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

The low xylophone is metronomic but quieter than the kick/snare on the loud
beats, so onset-picking grabbed the loud off-beat transients and missed the
quiet xylophone notes (e.g. detected 1.44/1.67/2.32 where the real notes are
1.90/2.80). Waveform ground truth showed a steady ~0.89s pulse.

Add --grid mode: estimate tempo from the band onset-envelope autocorrelation,
anchor the phase to the instrument's first hit (--phase; blind phase-finding
locks onto the louder beat), and emit phase + k·period. Joint period+phase
refinement keeps a constant-tempo track aligned with no drift over its length
(verified to ±15ms at the 5-minute mark).

- extract-song-timings.py: band_onset_envelope + beat_grid; --grid/--bpm/--phase
  /--tempo-min/--tempo-max; record mode/bpm/period/phase in the JSON.
- examples/praise-the-lamb.timings.json: regenerate in --grid mode → 407 beats
  @ 67.5 BPM (~1.1/s), matching the waveform (0.08, 0.97, 1.86, 2.75, 3.64…).
- README: document beat-grid mode and the tradeoff (pulses through rests).
---
 racket/prologos/tools/viz/README.md           |   30 +-
 .../viz/examples/praise-the-lamb.timings.json | 1059 +++++++----------
 .../tools/viz/extract-song-timings.py         |  110 +-
 3 files changed, 547 insertions(+), 652 deletions(-)

diff --git a/racket/prologos/tools/viz/README.md b/racket/prologos/tools/viz/README.md
index 30031f7d..9577f936 100644
--- a/racket/prologos/tools/viz/README.md
+++ b/racket/prologos/tools/viz/README.md
@@ -52,6 +52,24 @@ python3 tools/viz/extract-song-timings.py in.wav -o out.json \
     --band-low 110 --band-high 300 --min-strength 0.5 --min-gap 0.12
 ```
 
+**Beat-grid mode (`--grid`)** — for a quiet, *metronomic* instrument. Per-onset
+picking fails when the target plays a steady pulse but is quieter than the
+kick/snare on the loud beats: the picker grabs the loud off-beat transients and
+misses the quiet ones. `--grid` instead locks a steady beat grid to the band's
+pulse — it estimates the tempo from the band onset-envelope autocorrelation and
+emits `phase + k·period`. Anchor the phase to the instrument's first audible hit
+with `--phase` (blind phase-finding locks onto the louder beat), and bound the
+tempo search with `--tempo-min/max`:
+
+```
+python3 tools/viz/extract-song-timings.py in.wav -o out.json \
+    --grid --band-low 110 --band-high 350 --phase 0.10 --tempo-min 55 --tempo-max 90
+```
+
+A constant-tempo track stays aligned for its whole length (no drift); the
+tradeoff is it pulses through sections where the instrument rests. Pass an
+explicit `--bpm` to skip tempo estimation.
+
 Dependencies: `numpy`, `ffmpeg` on PATH (`pip install static-ffmpeg` provides a
 static binary), and `yt-dlp` for URLs. No librosa required.
 
@@ -75,12 +93,12 @@ panel and press play.
 
 It also ships real onsets for the original request song:
 
-- `examples/praise-the-lamb.timings.json` — 634 low-xylophone onsets (~1.8/s)
-  extracted from *Cult of the Lamb — Praise the Lamb*
-  (`https://youtu.be/PoH5hC5PzSQ`) in the low band (~145 Hz fundamental;
-  `--band-low 110 --band-high 300 --min-strength 0.5`). The audio itself isn't
-  committed (copyright); pair this timings file with your own copy of the track
-  in the music panel.
+- `examples/praise-the-lamb.timings.json` — 407 beats (~1.1/s) of the low
+  xylophone pulse in *Cult of the Lamb — Praise the Lamb*
+  (`https://youtu.be/PoH5hC5PzSQ`), `--grid` mode at 67.5 BPM locked to the
+  xylophone's phase (`--band-low 110 --band-high 350 --phase 0.10`). The audio
+  itself isn't committed (copyright); pair this timings file with your own copy
+  of the track in the music panel.
 
 ## Headless checks
 
diff --git a/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
index 294ec026..3bc84f61 100644
--- a/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
+++ b/racket/prologos/tools/viz/examples/praise-the-lamb.timings.json
@@ -1,648 +1,425 @@
 {
 "source": "Cult of the Lamb \u2014 Praise the Lamb (https://youtu.be/PoH5hC5PzSQ)",
-"generated": "2026-06-15T21:26:59.905766Z",
+"generated": "2026-06-15T21:51:25.113480Z",
+"mode": "grid",
 "sampleRate": 22050,
 "durationSec": 361.024,
-"threshold": 1.2,
-"minGap": 0.12,
+"threshold": 1.5,
+"minGap": 0.06,
 "bandLow": 110.0,
-"bandHigh": 300.0,
-"minStrength": 0.5,
-"count": 634,
+"bandHigh": 350.0,
+"minStrength": 0.0,
+"count": 407,
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+],
+"bpm": 67.5,
+"periodSec": 0.88889,
+"phaseSec": 0.08
 }
\ No newline at end of file
diff --git a/racket/prologos/tools/viz/extract-song-timings.py b/racket/prologos/tools/viz/extract-song-timings.py
index de1c9c90..b6fcd197 100755
--- a/racket/prologos/tools/viz/extract-song-timings.py
+++ b/racket/prologos/tools/viz/extract-song-timings.py
@@ -134,6 +134,82 @@ def detect_onsets(x, threshold=1.5, min_gap=0.06, hop=512, win=1024,
     return onsets
 
 
+def band_onset_envelope(x, band_low=0.0, band_high=0.0, hop=256, win=1024):
+    """Positive spectral-flux envelope (optionally band-limited), + frames/sec."""
+    import numpy as np
+    window = np.hanning(win).astype("float32")
+    n_frames = 1 + (len(x) - win) // hop
+    mags = np.empty((n_frames, win // 2 + 1), dtype="float32")
+    for i in range(n_frames):
+        mags[i] = np.abs(np.fft.rfft(x[i * hop: i * hop + win] * window))
+    pos = np.maximum(np.diff(mags, axis=0), 0.0)
+    if band_low > 0 or band_high > 0:
+        freqs = np.arange(pos.shape[1]) * (SR / 2) / (pos.shape[1] - 1)
+        hi = band_high if band_high > 0 else SR / 2
+        mask = ((freqs >= band_low) & (freqs <= hi)).astype("float32")
+        env = (pos * mask).sum(axis=1)
+    else:
+        env = pos.sum(axis=1)
+    return np.concatenate([[0.0], env]), SR / hop
+
+
+def beat_grid(x, dur, bpm=0.0, phase=-1.0, band_low=0.0, band_high=0.0,
+              tempo_min=50.0, tempo_max=100.0):
+    """Lock a steady beat grid to ONE instrument's metronomic pulse.
+
+    Some instruments (a low xylophone here) play a dead-steady pulse but are
+    quieter than the kick/snare on the loud beats — so per-onset picking grabs
+    the wrong transients and misses the quiet ones. The fix: estimate the tempo
+    (period) from the band onset envelope's autocorrelation, lock the phase to
+    where that band's energy actually lands, and emit a grid `phase + k·period`.
+    Constant-tempo tracks stay aligned for their whole length (no drift).
+
+    `bpm` (0 = auto-estimate within tempo_min..tempo_max); `phase` start seconds
+    (<0 = auto). Returns the grid times in seconds.
+    """
+    import numpy as np
+    env, fps = band_onset_envelope(x, band_low, band_high)
+    e = env - env.mean(); e[e < 0] = 0.0
+    tol = int(round(0.05 * fps))
+
+    def score(P, ph):
+        idx = np.round(np.arange(ph, dur - 0.1, P) * fps).astype(int)
+        return sum(env[max(0, i - tol): i + tol + 1].max()
+                   for i in idx if 0 <= i < len(env)) / max(1, len(idx))
+
+    # candidate period: explicit bpm, else autocorrelation within the tempo range
+    if bpm > 0:
+        cand = 60.0 / bpm
+    else:
+        ac = np.correlate(e, e, mode="full")[len(e) - 1:]
+        lags = np.arange(len(ac)) / fps
+        win = (lags >= 60.0 / tempo_max) & (lags <= 60.0 / tempo_min)
+        idx = np.where(win)[0]
+        cand = lags[idx[np.argmax(ac[idx])]]
+
+    # Phase: when a quiet instrument is the target, blind phase-finding locks onto
+    # the LOUDER beat. So if --phase anchors the pulse (e.g. its first audible
+    # hit), constrain the search near it; otherwise take the globally best-aligned
+    # phase. Refine the period jointly (±3%) — a coarse period drifts over a long
+    # track; the per-beat tolerance-max keeps the grid on the metrical position.
+    if bpm > 0:
+        periods = [cand]
+    else:
+        periods = np.arange(cand * 0.97, cand * 1.03, 0.0002)
+    if phase >= 0:
+        phases = np.arange(max(0.0, phase - 0.12), phase + 0.12, 0.01)
+    else:
+        phases = np.arange(0.0, cand, 0.02)
+    best = (-1.0, cand, phases[0])
+    for P in periods:
+        for ph in phases:
+            s = score(P, ph)
+            if s > best[0]:
+                best = (s, float(P), float(ph))
+    _, period, phase = best
+    return [round(float(t), 4) for t in np.arange(phase, dur - 0.02, period)], period, phase
+
+
 def main():
     ap = argparse.ArgumentParser(description=__doc__,
                                  formatter_class=argparse.RawDescriptionHelpFormatter)
@@ -147,6 +223,13 @@ def main():
                     help="restrict onsets to freqs <= this (Hz); 0 = up to Nyquist")
     ap.add_argument("--min-strength", type=float, default=0.0,
                     help="loudness floor 0..1 (fraction of 99.5pct flux) — thin a band to just the strong hits")
+    ap.add_argument("--grid", action="store_true",
+                    help="emit a steady beat grid locked to the band's pulse (best for a quiet metronomic "
+                         "instrument like a low xylophone) instead of per-onset picking")
+    ap.add_argument("--bpm", type=float, default=0.0, help="grid tempo (0 = auto-estimate)")
+    ap.add_argument("--phase", type=float, default=-1.0, help="grid start offset in seconds (<0 = auto)")
+    ap.add_argument("--tempo-min", type=float, default=50.0, help="auto-tempo lower bound (BPM)")
+    ap.add_argument("--tempo-max", type=float, default=100.0, help="auto-tempo upper bound (BPM)")
     ap.add_argument("--keep-audio", metavar="PATH", help="also save the decoded/downloaded audio here")
     ap.add_argument("--cookies-from-browser", help="pass to yt-dlp if YouTube demands sign-in (e.g. chrome, firefox)")
     args = ap.parse_args()
@@ -164,14 +247,27 @@ def main():
             sys.exit(f"audio not found: {audio}")
         x = decode_pcm(audio)
         dur = len(x) / SR
-        hits = detect_onsets(x, threshold=args.threshold, min_gap=args.min_gap,
-                             band_low=args.band_low, band_high=args.band_high,
-                             min_strength=args.min_strength)
-        print(f"[extract] {dur:.1f}s audio → {len(hits)} hits "
-              f"({len(hits) / dur:.1f}/s)", file=sys.stderr)
+        mode = "onset"
+        grid_period = grid_phase = None
+        if args.grid:
+            mode = "grid"
+            hits, grid_period, grid_phase = beat_grid(
+                x, dur, bpm=args.bpm, phase=args.phase,
+                band_low=args.band_low, band_high=args.band_high,
+                tempo_min=args.tempo_min, tempo_max=args.tempo_max)
+            print(f"[extract] {dur:.1f}s audio → {len(hits)} grid beats "
+                  f"@ {60 / grid_period:.1f} BPM (period {grid_period:.4f}s, phase "
+                  f"{grid_phase:.3f}s, {len(hits) / dur:.1f}/s)", file=sys.stderr)
+        else:
+            hits = detect_onsets(x, threshold=args.threshold, min_gap=args.min_gap,
+                                 band_low=args.band_low, band_high=args.band_high,
+                                 min_strength=args.min_strength)
+            print(f"[extract] {dur:.1f}s audio → {len(hits)} hits "
+                  f"({len(hits) / dur:.1f}/s)", file=sys.stderr)
         doc = {
             "source": args.source,
             "generated": datetime.datetime.utcnow().isoformat() + "Z",
+            "mode": mode,
             "sampleRate": SR,
             "durationSec": round(dur, 3),
             "threshold": args.threshold,
@@ -182,6 +278,10 @@ def main():
             "count": len(hits),
             "hits": hits,
         }
+        if mode == "grid":
+            doc["bpm"] = round(60 / grid_period, 3)
+            doc["periodSec"] = round(grid_period, 5)
+            doc["phaseSec"] = round(grid_phase, 4)
         with open(args.out, "w") as f:
             json.dump(doc, f, indent=0)
         print(f"[extract] wrote {args.out}", file=sys.stderr)

From d511c14c049692764ed651b9e9ba9b9fbe86276c Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Mon, 15 Jun 2026 22:22:28 +0000
Subject: [PATCH 7/7] =?UTF-8?q?viz:=20piecewise=20tempo=20map=20(--segment?=
 =?UTF-8?q?s)=20=E2=80=94=20slow=20intro=20then=2010x=20burst?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Alternate playback take: hold the slow xylophone pulse through the intro, then
rush at the drop. Add --segments 'startSec:bpm,...' for a piecewise-constant beat
grid; a tempo switch lands a beat exactly on the boundary.

- extract-song-timings.py: tempo_map() + --segments; record segments in the JSON.
- examples/praise-the-lamb-tempomap.timings.json: '0:67.5,28.5:675' → slow 67.5
  BPM intro, 10x (675 BPM) burst from 28.5s (3773 beats).
- README: document --segments.
---
 racket/prologos/tools/viz/README.md           |   13 +
 .../praise-the-lamb-tempomap.timings.json     | 3798 +++++++++++++++++
 .../tools/viz/extract-song-timings.py         |   38 +-
 3 files changed, 3848 insertions(+), 1 deletion(-)
 create mode 100644 racket/prologos/tools/viz/examples/praise-the-lamb-tempomap.timings.json

diff --git a/racket/prologos/tools/viz/README.md b/racket/prologos/tools/viz/README.md
index 9577f936..d067c353 100644
--- a/racket/prologos/tools/viz/README.md
+++ b/racket/prologos/tools/viz/README.md
@@ -70,6 +70,15 @@ A constant-tempo track stays aligned for its whole length (no drift); the
 tradeoff is it pulses through sections where the instrument rests. Pass an
 explicit `--bpm` to skip tempo estimation.
 
+**Tempo map (`--segments`)** — a piecewise grid of `startSec:bpm` segments, each
+running at its own tempo until the next. Lets you hold a slow pulse through an
+intro then rush at a drop (a tempo switch lands a beat exactly on the boundary):
+
+```
+python3 tools/viz/extract-song-timings.py in.wav -o out.json \
+    --segments '0:67.5,28.5:675' --phase 0.10
+```
+
 Dependencies: `numpy`, `ffmpeg` on PATH (`pip install static-ffmpeg` provides a
 static binary), and `yt-dlp` for URLs. No librosa required.
 
@@ -99,6 +108,10 @@ It also ships real onsets for the original request song:
   xylophone's phase (`--band-low 110 --band-high 350 --phase 0.10`). The audio
   itself isn't committed (copyright); pair this timings file with your own copy
   of the track in the music panel.
+- `examples/praise-the-lamb-tempomap.timings.json` — alternate take: the slow
+  intro pulse (67.5 BPM) then a 10× burst from 28.5s (`--segments
+  '0:67.5,28.5:675'`), so the timeline crawls through the build then rushes the
+  drop.
 
 ## Headless checks
 
diff --git a/racket/prologos/tools/viz/examples/praise-the-lamb-tempomap.timings.json b/racket/prologos/tools/viz/examples/praise-the-lamb-tempomap.timings.json
new file mode 100644
index 00000000..b7291ece
--- /dev/null
+++ b/racket/prologos/tools/viz/examples/praise-the-lamb-tempomap.timings.json
@@ -0,0 +1,3798 @@
+{
+"source": "Cult of the Lamb \u2014 Praise the Lamb (https://youtu.be/PoH5hC5PzSQ)",
+"generated": "2026-06-15T22:21:39.668357Z",
+"mode": "segments",
+"sampleRate": 22050,
+"durationSec": 361.024,
+"threshold": 1.5,
+"minGap": 0.06,
+"bandLow": 0.0,
+"bandHigh": 0.0,
+"minStrength": 0.0,
+"count": 3773,
+"hits": [
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+],
+"segments": [
+{
+"startSec": 0.0,
+"bpm": 67.5
+},
+{
+"startSec": 28.5,
+"bpm": 675.0
+}
+]
+}
\ No newline at end of file
diff --git a/racket/prologos/tools/viz/extract-song-timings.py b/racket/prologos/tools/viz/extract-song-timings.py
index b6fcd197..f9bf6081 100755
--- a/racket/prologos/tools/viz/extract-song-timings.py
+++ b/racket/prologos/tools/viz/extract-song-timings.py
@@ -210,6 +210,28 @@ def score(P, ph):
     return [round(float(t), 4) for t in np.arange(phase, dur - 0.02, period)], period, phase
 
 
+def tempo_map(dur, segments, phase=-1.0):
+    """Piecewise-constant beat grid: a list of (start_sec, bpm) segments, each
+    emitting beats at its own tempo from its start until the next segment (or the
+    end). The first segment may be anchored with `phase` (else it starts at its
+    own start time); later segments start exactly on their boundary, so a tempo
+    switch lands a beat right on the drop. Lets you e.g. hold a slow intro pulse
+    then rush 10x faster at the chorus.
+    """
+    segs = sorted(segments, key=lambda s: s[0])
+    times = []
+    for i, (start, bpm) in enumerate(segs):
+        end = segs[i + 1][0] if i + 1 < len(segs) else dur
+        period = 60.0 / bpm
+        t = phase if (i == 0 and phase >= 0) else start
+        while t < start:
+            t += period
+        while t < end - 1e-4:
+            times.append(round(t, 4))
+            t += period
+    return sorted(set(times))
+
+
 def main():
     ap = argparse.ArgumentParser(description=__doc__,
                                  formatter_class=argparse.RawDescriptionHelpFormatter)
@@ -230,6 +252,10 @@ def main():
     ap.add_argument("--phase", type=float, default=-1.0, help="grid start offset in seconds (<0 = auto)")
     ap.add_argument("--tempo-min", type=float, default=50.0, help="auto-tempo lower bound (BPM)")
     ap.add_argument("--tempo-max", type=float, default=100.0, help="auto-tempo upper bound (BPM)")
+    ap.add_argument("--segments", default="",
+                    help="piecewise tempo map as 'startSec:bpm,startSec:bpm,...' "
+                         "(e.g. '0:67.5,28.5:675' = slow intro then 10x burst at 28.5s); "
+                         "uses --phase to anchor the first segment")
     ap.add_argument("--keep-audio", metavar="PATH", help="also save the decoded/downloaded audio here")
     ap.add_argument("--cookies-from-browser", help="pass to yt-dlp if YouTube demands sign-in (e.g. chrome, firefox)")
     args = ap.parse_args()
@@ -249,7 +275,15 @@ def main():
         dur = len(x) / SR
         mode = "onset"
         grid_period = grid_phase = None
-        if args.grid:
+        if args.segments:
+            mode = "segments"
+            segs = [(float(a), float(b)) for a, b in
+                    (p.split(":") for p in args.segments.split(","))]
+            hits = tempo_map(dur, segs, phase=args.phase)
+            print(f"[extract] {dur:.1f}s audio → {len(hits)} beats over "
+                  f"{len(segs)} tempo segments {segs} ({len(hits) / dur:.1f}/s avg)",
+                  file=sys.stderr)
+        elif args.grid:
             mode = "grid"
             hits, grid_period, grid_phase = beat_grid(
                 x, dur, bpm=args.bpm, phase=args.phase,
@@ -282,6 +316,8 @@ def main():
             doc["bpm"] = round(60 / grid_period, 3)
             doc["periodSec"] = round(grid_period, 5)
             doc["phaseSec"] = round(grid_phase, 4)
+        elif mode == "segments":
+            doc["segments"] = [{"startSec": s, "bpm": b} for s, b in segs]
         with open(args.out, "w") as f:
             json.dump(doc, f, indent=0)
         print(f"[extract] wrote {args.out}", file=sys.stderr)