docs: BE12599 incident — the inverted rescue, plus a rescue-listener plan

The wedged_unit_recovery runbook covered exactly one failure mode. BE12599 turned out to be a second one wearing the same symptoms, and the existing procedure did not work on it. Adds a "TWO failure modes" table up front so the next incident branches correctly, and a full second-incident section covering what the ALEOS serial debug log revealed: the device repeating a 29-byte AT modem-init string (ATQ1/ATE0/ATS0=2, no ATD) every 75 s, never getting an OK because the modem is in TCP data mode, and therefore never entering S3 mode at all. Inbound cannot win against that, no matter how well framed. Also records the two red herrings, since together they cost ~90 minutes: the RV50 trusted-IP whitelist drops non-listed sources silently (presents as a connect timeout, and Brian's dynamic dev IP had rotated off the list), and sfm/server.py returns 502 for BOTH "Protocol error:" and "Connection error:", so a 502 was misread as "TCP connected, device mute" and a theory built on it. And the gotchas worth never re-deriving: slow_drip's send_error=null plus a full duration is not success (only bytes_received > 0 is); stopping monitoring removes the call-in trigger, so it costs you the channel; --events-only skips the device-info step, so the serial is never read and ach_state keys on peer:ephemeral_port, silently breaking dedup and re-downloading the same event every session. The plan doc captures the tool Brian wants built out of this — a rescue listener with a real lifecycle and, critically, a confirmation gate before shutdown, because leaving the modem's Destination pointed at a dead listener is worse than never having started. Open questions are listed rather than guessed at. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
feat(ach): rescue-on-connect — stop monitoring / disable ACH from the server side
2026-09-17 05:45:26 +00:00 · 2026-09-16 20:54:46 +00:00 · 2026-09-15 14:34:04 +00:00 · 2026-09-15 05:48:31 +00:00 · 2026-09-15 05:39:53 +00:00 · 2026-09-15 05:33:38 +00:00
34 changed files with 2949 additions and 128 deletions
@@ -4,6 +4,235 @@ All notable changes to seismo-relay are documented here.
 ---
 ## Unreleased
 **Blastware Event/FFT-Report parity — the FFT, the USBM compliance chart, and
 the sensor self-check.** Three analyses Blastware derives from event data,
 reverse-engineered against BE12844 (MiniMate Plus) reports and reproduced in
 seismo-relay: the compliance chart and the sensor-check strip now render on
 the event-report PDF, and the FFT reproduces Blastware's FFT Report. All three
 are additive and read from data already on disk — the `.h5` samples and the
 retained raw BW binary — so there is **no `.h5`/DB change, no migration, and no
 backfill**: a report regenerated for an existing event simply gains the new
 panels.
 ### Added
 - **Rescue-on-connect for `bridges/ach_server.py`** — `--stop-monitoring`
  (SUB 0x97), `--disable-ach` (SUB 0x2C read → 0x7E write → 0x7F confirm) and
  `--rescue` (both).  They fire immediately after the startup handshake and
  **before** the event walk, so a unit that is recording back-to-back on a
  stuck-triggered geophone is quieted as early in the session as possible.
  Each action is independently guarded — a failure does not abort the download
  — and the outcome is written to `rescue.json` in the session directory.
  This inverts the `docs/runbooks/wedged_unit_recovery.md` approach.  That
  runbook reaches the unit *inbound* and clears the modem's Destination Address
  to stop it dialing.  When the device is instead wedged mid-modem-init — ALEOS
  logs `tcpmode trying to send to invalid socket` and re-runs `Initialize Auto
  answer` every ~75 s, orphaning any held inbound session — inbound cannot win.
  Pointing the modem's Destination at an `ach_server` and letting the unit call
  *us* gives a device-initiated session the modem bridges properly.
  ⚠ Prefer `--stop-monitoring` alone on first contact.  `--disable-ach` stops
  the unit calling, which is the only channel to a unit in this state; stopping
  the recording ends the call-home loop on its own when ACH is
  "after event recorded".
 - **Blastware-compatible channel FFT (`waveform_fft`).** Reproduces Blastware's
  FFT Report: DC-removed, no window, zero-padded to 4096 (0.25 Hz bins at
  1024 sps), single-sided `2/N` amplitude. Matches Blastware's dominant
  frequency to the exact bin and the amplitude to report precision across all
  28 channels of the 7-event BE12844 oracle set. `channel_spectrum()` /
  `dominant_frequency()`; tests in `tests/test_waveform_fft.py`.
 - **USBM RI8507 / OSMRE compliance chart on the event-report PDF
  (`sfm/compliance.py`).** The velocity-vs-frequency blasting-compliance
  scatter Blastware draws in the upper-right of its Event Report: each channel's
  significant cycles as `(frequency, peak velocity)` points (zero-crossing
  method, so each channel's cloud tops out at its PPV) plotted against the
  RI8507 Drywall (0.75 in/s) and plaster (0.50 in/s) limit curves, drawn
  continuous (constant-displacement bounds meeting the plateaus — no vertical
  steps). Sized and positioned to match a Blastware report, measured off the
  reference PDF. A technical breakdown of the curve is in
  `docs/ri8507_compliance_curve.md`.
 - **Sensor self-check waveforms decoded and drawn (`minimateplus.sensor_check`).**
  The "Sensor Check" traces Blastware shows to the right of the waveform panel
  live in the series-3 binary's trailing block as four length-prefixed records
  (`0x3c`–`0x3f`) using the same delta-block codec as the main waveform:
  Tran/Vert/Long geophone ring-downs (the transducer's damped impulse response —
  resonant frequency + overswing/damping) and a MicL pulse train (the mic's
  known-signal gain check). `gather_report_data` decodes them from the retained
  BW binary at report time; the report renders them as a strip flush against the
  waveform panel plus the **Sensor Check → Frequency / Overswing Ratio** sub-rows
  in the stats table. Verified against the reports on all 7 oracle events (mic
  zero-crossing frequency = 20.1 Hz exact; geophone ring-downs consistent
  ~7.5 Hz with overswing ~3.5). Tests in `tests/test_sensor_check.py`.
 - **Inspector tab in `seismo_lab.py` — annotated hex reader for series-3
  binaries (`minimateplus/binary_annotate.py`).** Tiles a raw Blastware file
  into labeled spans (header / STRT / body record-chain / trailing metadata +
  calibration + sensor-check records / footer) so a binary can be combed by eye.
 ### Fixed
 - **Event-report waveform panel — stacked-lane y-tick collision.** The lanes
  touch, so each lane's bottom `-1.0` overprinted the next lane's top `1.0` at
  the shared boundary. Prune the extreme ticks so each lane shows clean interior
  ticks only.
 - **Event-report header — serial+firmware line ran off the page.** The long
  `BE##### V ##.##-#.## MiniMate Plus` string overflowed the right margin;
  tighter right-column indent + BW's slightly smaller header size so it fits.
 ---
 ## v0.30.0 — 2026-09-12
 **The series-4 correctness release** — the Thor / Micromate counterpart to
 v0.26.0's series-3 work.  The decoder is now verified per-sample against
 Thor's own CSV exports: **459 waveform files, 3,807,158 / 3,807,165 samples
 exact** across three independent ground-truth corpora, and production IDFW is
 **575/575** with zero truncations and zero decode failures.  Series-3
 re-verified **unchanged at 14,338/14,338** after every shared-codec change.
 ⚠ **This release owes the prod store a Thor backfill.**  Every stored
 series-4 geophone value is **3.3% low**, and histogram peaks from monitoring
 runs longer than ~4 hours can be far worse (the interval cap discarded the
 tail, frequently the part holding the peak).  Run
 `scripts/backfill_thor_events.py` — `TOOL_VERSION` is bumped to `0.30.0`, so
 regeneration is gated correctly and **no `--force` is needed**.  DB backup
 first.  Series-3 events are untouched by this release and do not need
 re-running.
 ⚠ **Terra-View displays these values.**  Series-4 geophone readings will rise
 ~3.3% after the backfill, and some histogram PPVs will rise a great deal more.
 That is a correction, not a regression.
 ### Fixed — event-report PDF used a per-trace geo Y scale
 The waveform plot scaled each geo lane to its own peak, so a small channel
 filled its lane and looked as large as a big one, and the `Geo: X in/s/div`
 footer reflected only whichever channel was measured first — wrong for the
 other two.  All three geo lanes now share one symmetric scale (max |sample|
 across them, padded, 0.05 in/s floor), matching the event modal and BW's
 single amp/div; the footer reflects that shared scale.  Mic keeps its own psi
 scale.  Large events are unchanged.
 ### Fixed — series-4 (Thor / Micromate) decoder is now per-sample exact
 Verified against **Thor's own CSV exports**, which carry a per-sample
 four-column block beside every binary (`CSV/<name>.IDFW.csv`) — 1,012 paired
 files that had been sitting in the corpus unused.  Previous notes asserted
 "Thor has no ASCII ground truth", which is why the decoder stayed pinned to a
 superseded walker with an unverifiable scale factor.
 | metric | before | after |
 |---|---|---|
 | IDFW per-sample exact | 39.1% | **100.000%** (1,057,536/1,057,536) |
 | IDFW files fully exact | 0/153 | **153/153** |
 | IDFW PPV median error | −3.32% | **−0.002%** |
 | IDFH within 2% of Thor PPV | 51.1% | **100.0%** (858/858) |
 | prod IDFW PPV median error (8 units) | −3.3% | **−0.001%** |
 | decode cost | — | 6 ms/file |
 Four independent root causes:
 - **Geo LSB was `0.0003`, should be `0.000310308`** — the old value was Thor's
  4-decimal *display rounding* of the LSB mistaken for the LSB, so every
  series-4 geophone sample read **3.3% low**.  Pinned to ±6e-11 by
  intersecting 991,415 rounding constraints; corroborated by the ±full-scale
  seed (`±32226`) in unwritten IDFH slots.  Applies to IDFH too, which had a
  separate (also wrong) `10.0/32768`.
 - **IDFH histograms were capped at 250 intervals** — the segment validator
  required the interval counter's high byte to be zero, but the counter is a
  uint16 cumulative index, so every segment past interval 255 was rejected.
  Any run over ~4 hours lost its tail, often the part holding the peak.
  540/858 corpus files affected.
 - **Record mode `00 00` (raw int16, 10-byte header) was unhandled** — the
  record fell through the dispatch, silently dropping each channel's first
  512 samples.  This produced the long-standing "loud events truncate"
  symptom.  `MODE_ABSOLUTE` is now also accepted as a segment-0 preamble.
 - **Body-offset search matched `00 02 00` inside record headers** — picking a
  candidate part-way down the chain, which decodes a rotation-shifted body
  that drops each channel's segment 0.  The search now anchors on record
  headers and takes the chain head.
 Also fixes the separately-tracked "UM-series decodes ~1000× low" bug
 (`UM11402_20260406130113.IDFW` now matches its device report exactly).
 Series-3 re-verified **unchanged at 14,338/14,338 exact** after the shared
 `waveform_codec` change.
 ⚠ **This is a codec change: the Thor store owes a regeneration.**  Run
 `scripts/backfill_thor_events.py` (bump `TOOL_VERSION` first, or pass
 `--force`), DB backup first.  All stored series-4 `.h5`/sidecar peaks are
 currently ~3.3% low, and histogram peaks for runs over ~4 hours may be
 badly low.
 ⚠ **Thor's histogram PPV has a 0.0050 in/s display floor** — 41.4% of prod
 IDFH sidecars report a component PPV larger than their own vector sum.  On
 quiet files the decoder is now *more* accurate than that reference.
 New: `scratch/verify_thor_against_csv.py`, `tests/test_idf_binary_codec.py`
 (10 tests, fixtures under `tests/fixtures/thor-idf/`).
 ### Fixed — mic-disabled (3-channel) units
 Verified on a second corpus (`9-10-26-csv-req`: UM11402, UM12947, UM20147) —
 **139/139 waveforms per-sample exact (1,273,380 samples), 877/877 histograms
 within 2%** (was 66.9% and 56.6%).
 - **Waveform body head sat below the scan floor.** A 3-channel unit's shorter
  header puts the record chain head at `0x0dba`, under the old
  `_BODY_SCAN_FLOOR` of `0x0E00`.  The scan couldn't see it and fell through
  to the Vert segment-0 record, decoding a body shifted one position around
  the channel rotation — Vert came up exactly 512 samples short.  Floor
  lowered to `0x0C00`; body-offset scoring now accepts 3 channels as "equal"
  instead of demanding 4.
 - **Histogram interval record is 56 bytes, not 72.**  It is
  `16 × n_channels + 8`, so mic-disabled units pack 56.  Assuming 72 read 7
  intervals out of every 10-interval segment then walked off alignment into
  garbage decoding as ~10 in/s peaks (errors up to +191,000%).  The interval
  count now comes from the segment's cumulative counter and the stride is
  derived from it; also recovers 4 files that decoded no intervals at all.
 Combined across both corpora: **292/292 waveform files, 2,330,916/2,330,916
 samples exact.**  Production IDFW truncations 41 → 22.
 ### Fixed — `40 NN` int16 blocks with NN > 8
 `data_block_len()` rejected any `40 NN` block with `NN > 0x08`.  The cap had
 no evidence behind it: every corpus available when it was written used only
 NN ∈ {1,2,3,4,8}, so it was never exercised.  Loud UM12947 events use NN of
 12, 16, 20 … up to 196, and because the block walker stops at the first
 unrecognised tag rather than raising, rejecting them surfaced as **silently
 short channels** (e.g. Tran 1812 / Vert 2132 / Long 2324 on a file whose
 export has 2324 for all three).  The bound is the buffer, not a constant.
 Verified against Thor exports for UM12947 (2025-07-14 … 09-25, 167
 waveforms): length mismatches **22 → 0**, **1,476,242/1,476,249** samples
 exact.  These are not truncated recordings — the exports carry full sample
 counts.
 `tests/test_waveform_codec.py` asserted the cap as intended behaviour; that
 assertion was wrong and has been replaced with one pinning the opposite,
 carrying the evidence.
 ### Result across all three ground-truth corpora
 **459 waveform files, 3,807,158 / 3,807,165 samples exact.**  Production
 IDFW: **575/575**, zero truncations, zero decode failures, median PPV error
 −0.0007% across 8 units.  Series-3 re-verified **unchanged at 14,338/14,338**
 after every shared-codec change.
 The 7 residual samples each differ by one 4th-decimal tick and are **Thor's
 own rounding**: intersecting the per-sample rounding constraints over that
 corpus is infeasible (the binding pair contradict by 2.3e-11, 7e-5 relative),
 so no single linear LSB reproduces every printed value.  `_GEO_LSB_IPS` is
 already pinned to ~1e-11 — do not retune it to chase these.
 ---
 ## v0.29.0 — 2026-09-04
 First release to reach prod since **v0.27.0**, so it ships **both** the
@@ -2,7 +2,7 @@
 Ground-up Python replacement for **Blastware**, Instantel's Windows-only software for
 managing MiniMate Plus seismographs. Connects over direct RS-232 or cellular modem
-(Sierra Wireless RV50 / RV55). Current version: **v0.29.0**.
+(Sierra Wireless RV50 / RV55). Current version: **v0.30.0**.
 Stack-level context — which repo owns what, and how the three project versions
 pair — lives in `../terra-view/docs/tmi-stack.md`, which is also loaded as
@@ -24,9 +24,43 @@ Read this first when picking the project back up.
  Independent corroboration of the 32000-count scale: 19,244 healthy
  channel-events sit at a pre-trigger floor of exactly 0.000 (62.7%), 94.5%
  within ±1 quantisation unit, median +0.0000 — no zero-point bias.
- **Series-4 (Thor / Micromate) is NOT verified.** UM-series sits at ~48%
+- **Series-4 (Thor / Micromate) is now verified per-sample (2026-09-10).**
-  against device peaks with a ~1.7% systematic bias and a near-zero tail.
+  **1,057,536 / 1,057,536** geo samples across all 153 genuine Thor waveform
-  Thor IDFW is pinned to `decode_waveform_legacy` deliberately.
+  files reproduce Thor's own CSV export exactly; IDFH peaks are within 2% on
  858/858 (median -0.004%).  The ground truth was in the corpus all along —
  Thor writes `CSV/<name>.IDFW.csv` beside each binary with a **per-sample**
  four-column block.  Harness: `scratch/verify_thor_against_csv.py`.
  Four bugs, all fixed: geo LSB was `0.0003` (display rounding of the real
  `0.000310308`, so every sample read **3.3% low**); the IDFH segment
  validator required a zero counter high byte, **capping every histogram at
  250 intervals**; record mode `00 00` (raw int16) was unhandled, silently
  dropping each channel's first 512 samples; and the body-offset search
  matched `00 02 00` *inside* record headers, decoding a rotation-shifted
  body.  IDFW is no longer pinned to `decode_waveform_legacy`.
  Series-3 re-verified unchanged at 14,338/14,338 after the shared-codec
  change.
 - **Mic-disabled (3-channel) units are a distinct shape (2026-09-10).**
  Verified on a second corpus (`~/thor-csv-req`, UM11402/UM12947/UM20147):
  **139/139** waveforms per-sample exact, **877/877** histograms within 2%.
  Two structural differences: the shorter header puts the waveform record
  chain head at `0x0dba` (below the old `_BODY_SCAN_FLOOR` of `0x0E00`, so it
  was invisible and Vert came up exactly 512 short), and the histogram
  interval record is **56 bytes, not 72** — `16 × n_channels + 8`, derived per
  segment from the cumulative interval counter, never assumed.
 - **`40 NN` blocks are not capped at NN=8 (2026-09-11).**  `data_block_len()`
  rejected `NN > 0x08`, a guard with no evidence behind it — the corpora
  available when it was written only used NN ∈ {1,2,3,4,8}.  Loud UM12947
  events use NN up to 196, and since the walker stops at the first
  unrecognised tag rather than raising, this surfaced as silently short
  channels.  Verified on 167 UM12947 waveforms: length mismatches 22 → 0,
  1,476,242/1,476,249 samples exact.
 - **Production IDFW is now 575/575** — zero truncations, zero decode
  failures, median PPV error −0.0007% across 8 units (was 41 truncated + 1
  failing, −3.3%).  Across all three ground-truth corpora: **459 files,
  3,807,158/3,807,165 samples exact**; the 7 stragglers differ by one
  4th-decimal tick and are Thor's own rounding — no single linear LSB can
  reproduce every printed value (the constraints are infeasible by 7e-5
  relative), so do NOT retune `_GEO_LSB_IPS`.
 - **Open, not blocking:** 14 sensitive-range files show an exact 8x
  (= 10.0/1.25) units discrepancy; `scripts/backfill_sidecars.py --force` also
  inserts DB rows for store files that have none (one-time per store) and the
@@ -120,20 +154,34 @@ should not import from `sfm/`, must not touch a DB, and have no I/O
 beyond reading files passed as arguments.  Keep them pure — both
 tiers can then depend on them without circularity.
-#### Thor IDF binary codec (2026-05-28)
+#### Thor IDF binary codec (updated 2026-09-10)
 `micromate/idf_file.read_idf_file()` decodes both Thor IDFW
-(waveform) and IDFH (histogram) binaries.
+(waveform) and IDFH (histogram) binaries.  **Verified per-sample
 against Thor's own CSV exports** — see
 `scratch/verify_thor_against_csv.py`.
- **IDFW** reuses `decode_waveform_v2()` on the body at fixed file
+- **IDFW** uses the series-3 record-chain `decode_waveform_v2()`.  The
-  offset `0x0f1f`.  Sample fidelity is 87–99% byte-exact on quiet
+  body offset is **not** fixed: it is `<chain-head record> + 7`, found
-  events; loud events hit the BW codec's known walker-stops-early
+  by `_find_waveform_body_offset()` anchoring on record headers.  All
-  limitation.
+  **153/153** genuine Thor waveform files decode per-sample exact
- **IDFH** has its own segment-based decoder: `[len_be][0a 00 00 00]
+  (1,057,536/1,057,536 samples).
-  [00 NN][05 3f]` + N × 72-byte interval records (4 × 16-byte
+- **IDFH** segment header is `[len_be][0a 00 00 00][counter_be][05 3f]`,
-  per-channel min/max/halfp).  All 859 Thor IDFH corpus files
+  where `counter` is a **uint16 cumulative interval index** — it must
-  decode (181,071 intervals); peak matches sidecar within ~1.8%
+  not be constrained to a zero high byte (that capped histograms at 250
-  (ADC quantization).
+  intervals).  Intervals whose `min > max` on all channels are unwritten
  slots carrying a ±full-scale seed and are skipped.  858/858 files land
  within 2% of Thor's PPV (median -0.004%).
 - **Geo LSB is `0.000310308` in/s per count** (full scale 10.0 in/s =
  32226.05 counts).  Series-3's 32000-count scale does NOT apply.
 - **Record modes** are `02 00` deltas (14 B header), `01 00` absolute,
  `00 03` raw 12-bit, and `00 00` **raw int16** (all 10 B headers).
  `01 00` and `00 00` are also valid as the implicit segment-0 preamble.
 ⚠ **Thor's histogram PPV has a 0.0050 in/s display floor.**  41.4% of
 prod IDFH sidecars report a component PPV exceeding their own vector
 sum — impossible.  On quiet files our decode is *more* accurate than
 the reference; do not "fix" the decoder to match it.
 The two outlier `BE9439_*` files in the Thor example corpus are
 actually Series III Blastware binaries that share the `.IDFW`/`.IDFH`
@@ -399,15 +447,19 @@ with zero mismatches.  Before: 1 of 1196.
  `BE12599/N599LPWJ.980W` @849, `BE9558/K558LOF2.820W` @1485.
 (The series-3 histogram codec was fixed 2026-08-25 — see below.)
- **Micromate (UM-series) IDF decode is ~1000× low** — e.g.
+- ~~**Micromate (UM-series) IDF decode is ~1000× low**~~ — FIXED 2026-09-10.
-  `UM11402_20260406130113.IDFW` gives a Tran peak of 0.0009 in/s against
+  `UM11402_20260406130113.IDFW` now decodes Tran 1.1168 / Vert 4.3220 /
-  a device-reported 1.1168.  The Thor IDF path decodes sanely, so this
+  Long 0.9135, matching the device report exactly.  Root cause was the
-  is UM-specific.
+  body-offset search landing inside a record header plus the unhandled
- **Thor IDF per-count LSB** — after the 32000 geo full-scale
+  `00 00` record mode, not anything UM-specific.
-  correction, series-4 Thor peaks sit at a median 0.983 of the
+- ~~**Thor IDF per-count LSB**~~ — RESOLVED 2026-09-10.  The 0.983 ratio was
-  device-reported peak (was 0.960 under 32768).  Closer but not exact;
+  exactly `0.0003 / 0.000310308`.  Thor's geo LSB is **0.000310308 in/s per
-  Thor likely uses its own per-count LSB rather than the BW
+  count** (full scale 10.0 in/s = 32226.05 counts), pinned to ±6e-11 by
-  16-count/0.005 in/s convention.
+  intersecting 991,415 rounding constraints from Thor's own exports and
  corroborated by the ±full-scale seed (`±32226`) left in unwritten IDFH
  interval slots.  Series-3's 32000-count scale does **not** carry over.
  Note `10.0/32226` is very slightly wrong — see
  `docs/idf_protocol_reference.md`.
 ### Decoded sample counts (across the fixture bundle)
@@ -1,4 +1,4 @@
-# seismo-relay  `v0.29.0`
+# seismo-relay  `v0.30.0`
 A ground-up replacement for **Blastware** — Instantel's aging Windows-only
 software for managing seismographs.  Supports both the **MiniMate Plus
@@ -177,6 +177,8 @@ class AchSession:
        store: "WaveformStore",
        clear_after_download: bool = False,
        restart_monitoring: bool = False,
        rescue_stop_monitoring: bool = False,
        rescue_disable_ach: bool = False,
        force_redownload: bool = False,
    ) -> None:
        self.sock                 = sock
@@ -190,6 +192,9 @@ class AchSession:
        self.store                = store
        self.clear_after_download = clear_after_download
        self.restart_monitoring   = restart_monitoring
        # Rescue actions for a runaway unit — fired before the event walk.
        self.rescue_stop_monitoring = rescue_stop_monitoring
        self.rescue_disable_ach     = rescue_disable_ach
        # `force_redownload` tells this session to ignore ach_state and
        # re-download every event currently on the device, regardless of any
        # (key, timestamp) match.  Useful as a manual override when state has
@@ -290,6 +295,41 @@ class AchSession:
        root_logger.addHandler(fh)
        try:
            # ── Step 1.5: rescue actions ──────────────────────────────────────
            # Fired BEFORE the event walk so a runaway unit is quieted as early
            # in the session as possible.  A unit whose geophone sits above the
            # trigger threshold records back-to-back and, with ACH set to "after
            # event recorded", re-dials every time — saturating its own firmware
            # so it never services inbound requests.  See
            # docs/runbooks/wedged_unit_recovery.md.
            #
            # Each action is independently guarded: a failure here must not
            # abort the download that follows.
            if self.rescue_stop_monitoring or self.rescue_disable_ach:
                rescue: dict = {"peer": self.peer, "ts": ts}
                if self.rescue_stop_monitoring:
                    log.info("Step 1.5: RESCUE — stop monitoring (SUB 0x97)")
                    try:
                        client.stop_monitoring()
                        rescue["stop_monitoring"] = "ok"
                        log.info("  stop monitoring OK — device should stop recording")
                    except Exception as exc:
                        rescue["stop_monitoring"] = f"failed: {exc}"
                        log.error("  stop monitoring FAILED: %s", exc)
                if self.rescue_disable_ach:
                    log.info("Step 1.5: RESCUE — disable auto call home (SUB 0x2C/0x7E/0x7F)")
                    try:
                        client.set_call_home_config(auto_call_home_enabled=False)
                        rescue["disable_ach"] = "ok"
                        log.info("  disable ACH OK — unit should stop calling home")
                    except Exception as exc:
                        rescue["disable_ach"] = f"failed: {exc}"
                        log.error("  disable ACH FAILED: %s", exc)
                _save_json(session_dir / "rescue.json", rescue)
            # ── Step 2: device info ───────────────────────────────────────────
            device_info = None
            if not self.events_only:
@@ -747,6 +787,13 @@ def serve(args: argparse.Namespace) -> None:
    print(f"  Max events per session: {max_ev if max_ev else 'unlimited'}")
    print(f"  Clear device after download: {'YES' if args.clear_after_download else 'no'}")
    print(f"  Restart monitoring after download: {'YES' if args.restart_monitoring else 'no'}")
    _stop_mon = args.stop_monitoring or args.rescue
    _dis_ach  = args.disable_ach or args.rescue
    print(f"  RESCUE stop monitoring on connect:  {'YES' if _stop_mon else 'no'}")
    print(f"  RESCUE disable auto call home:      {'YES' if _dis_ach else 'no'}")
    if _stop_mon and args.restart_monitoring:
        print("  !! --restart-monitoring will re-start the unit after download,")
        print("     undoing --stop-monitoring.  Drop one of them.")
    print(f"  Force re-download all (ignore state): {'YES' if args.force_redownload_all else 'no'}")
    print(f"{'='*60}")
    print(f"\n  Point your test unit's ACEmanager call-home settings to:")
@@ -788,6 +835,8 @@ def serve(args: argparse.Namespace) -> None:
                    store=store,
                    clear_after_download=args.clear_after_download,
                    restart_monitoring=args.restart_monitoring,
                    rescue_stop_monitoring=args.stop_monitoring or args.rescue,
                    rescue_disable_ach=args.disable_ach or args.rescue,
                    force_redownload=args.force_redownload_all,
                )
                t = threading.Thread(target=session.run, daemon=True, name=f"ach-{peer}")
@@ -862,6 +911,32 @@ def parse_args() -> argparse.Namespace:
            "DCD on disconnect — without this the unit stays idle after a call-home."
        ),
    )
    p.add_argument(
        "--stop-monitoring",
        action="store_true",
        default=False,
        help=(
            "RESCUE: send SUB 0x97 (stop monitoring) immediately after the "
            "handshake, before any event download. Use on a unit that is "
            "recording back-to-back because of a stuck-triggered geophone."
        ),
    )
    p.add_argument(
        "--disable-ach",
        action="store_true",
        default=False,
        help=(
            "RESCUE: disable Auto Call Home on the device (SUB 0x2C read → "
            "0x7E write → 0x7F confirm) immediately after the handshake. The "
            "unit stops dialing out until ACH is explicitly re-enabled."
        ),
    )
    p.add_argument(
        "--rescue",
        action="store_true",
        default=False,
        help="Shorthand for --stop-monitoring --disable-ach.",
    )
    p.add_argument(
        "--clear-after-download",
        action="store_true",
@@ -6,7 +6,15 @@ Series IV event-file format.  Sibling to
 Series III "Rosetta Stone") — this doc holds what we know so far and
 the open questions still to crack.
-**Status (2026-05-28):** ASCII text sidecar fully decoded (1,014
+> ⚠ **The "Status (2026-05-28)" block below is SUPERSEDED.**  Its geo LSB
 > (0.0003), its IDFH scale (`/32768 × 10`), its fixed body offset (`0x0f1f`)
 > and its "87–99% byte-exact / loud events truncate" caveat were all wrong or
 > incomplete.  See **[Verified against Thor's own exports
 > (2026-09-10)](#verified-against-thors-own-exports-2026-09-10)** — the
 > decoder is now per-sample exact on 1,057,536/1,057,536 samples.  The block
 > is kept only for the reverse-engineering trail.
 **Status (2026-05-28, SUPERSEDED):** ASCII text sidecar fully decoded (1,014
 sample files round-trip).  **Thor IDFW** binary now decodes via
 `micromate.idf_file.read_idf_file()` — reuses the BW segment-rotated
 block codec verbatim at fixed body offset `0x0f1f`; metadata (serial,
@@ -44,6 +52,220 @@ signature and raises `NotImplementedError` pointing callers at
 time-of-peak); the two uint16 fields (probably PVS contributions);
 8-byte interval tail (PVS data); mic dB(L) exact conversion constant.
 ## Verified against Thor's own exports (2026-09-10)
 **The series-4 decoder is now per-sample exact.**  1,057,536 / 1,057,536
 geophone samples across all 153 genuine Thor waveform files reproduce Thor's
 own CSV export exactly; histogram peaks land within 2% on 858/858 files
 (median error −0.004%).
 ### Ground truth — it was there all along
 Thor writes `TXT/`, `CSV/`, `XML/` and `PDF/` exports beside every binary:
 ```
 <serial dir>/UM13981_20220207084555.IDFW
 <serial dir>/CSV/UM13981_20220207084555.IDFW.csv
 ```
 The **CSV carries a per-sample block** — four columns (Tran, Vert, Long, Mic)
 in in/s and psi, after the 2-column report header.  That is the series-4
 equivalent of Blastware's `_ASCII.TXT` exports, and it gives 1,012 paired
 files (152 IDFW + 860 IDFH).  Earlier notes in this file and in
 `micromate/idf_file.py` asserted "Thor has no ASCII ground truth in the
 corpus"; that was wrong, and it is why the decoder sat pinned to a
 superseded walker with a scaling constant nobody could check.
 Harness: `scratch/verify_thor_against_csv.py`.
 ### Geo LSB = 0.000310308 in/s per count (NOT 0.0003)
 The old 0.0003 was read off the smallest non-zero sample in the exports —
 but that is Thor's **4-decimal display rounding of the LSB, not the LSB**.
 It read every series-4 geophone sample **3.3% low**.  The quantisation
 ladder gives it away: counts 1..6 export as 0.0003, 0.0006, 0.0009, 0.0012,
 0.0016, 0.0019 — an LSB of exactly 0.0003 would end 0.0015, 0.0018.
 Each exported sample constrains the LSB to the window that rounds to its
 printed value.  Intersecting 991,415 such constraints gives
 ```
 LSB ∈ [0.000310307933, 0.000310308057]      width 1.2e-10
 ```
 so `_GEO_LSB_IPS = 0.000310308`, i.e. full scale 10.0 in/s = **32226.05
 counts**.  Corroboration: an IDFH interval that never recorded keeps its
 min/max accumulator at its ±full-scale seed, and that seed is
 `(min=+32226, max=-32226)`.  ⚠ The tempting closed form `10.0/32226` is
 very slightly wrong — it lands 4.5e-10 above the feasible window and loses
 78 boundary samples while never winning one.  **Series III uses 32000 counts
 for the same 10.0 in/s, so the two generations do not share a scale.**
 Independently confirmed on 8 production units (UM6047, UM11402, UM11719,
 UM12947, UM13981, UM14133, UM20146, UM20147): every unit's median PPV error
 against its device-reported peak moved from −3.3% to within ±0.03%.  It is a
 global constant, not a per-unit calibration.
 ### IDFH segment header: the counter is a uint16, and it is cumulative
 ```
 [length_be 2B][0a 00 00 00][counter_be 2B][05 3f]
 ```
 `counter` is the **0-based cumulative index of the last interval in the
 segment** — 9, 19, 29, ... for the usual 10-intervals-per-segment layout
 (`length` = 730).
 The validator used to require `counter`'s high byte to be `0x00`.  That
 silently **capped every histogram at 250 intervals**: once the cumulative
 counter passed 255 the high byte went non-zero and every later segment was
 rejected.  Any run longer than ~4 hours lost its tail — frequently the part
 holding the event peak, so the file's PPV read low.  **540 of 858 corpus
 files were affected**; fixing it moved histogram peaks from 48.3% to 93.8%
 within 0.5% of Thor's reported PPV.
 ### Unwritten interval slots carry a ±full-scale seed
 An interval the device reserved but never wrote keeps `min = +32226`,
 `max = -32226` on all four channels — `min > max`, impossible for real data.
 Decoded naively it yields a 10.0 in/s peak on every channel and, being a
 max-over-intervals, poisons the whole file's PPV.  Rare but real: exactly 1
 of 497,611 corpus intervals, and it inflated that file's Long PPV from
 0.0081 to 10.0 in/s.  The inversion is all-or-nothing across channels (0
 partial cases), so requiring every channel to be inverted is a safe test.
 ### Record mode `00 00` — raw int16 absolute (MODE_RAW16)
 The record chain's mode field at `off+8` takes a fourth value:
 | mode | meaning | header |
 |---|---|---|
 | `02 00` | deltas + two int16 anchors | 14 B |
 | `01 00` | absolute, tagged blocks | 10 B |
 | `00 03` | raw 12-bit absolute, untagged | 10 B |
 | **`00 00`** | **raw int16 BE absolute, untagged** | **10 B** |
 A `MODE_RAW16` record with `length = 1032` carries exactly
 `(1032 - 8) / 2 = 512` samples and reproduced Thor's export **512/512
 exactly** on first test.  Thor uses it for segment 0 (the pre-trigger
 window) on some events.  Before this mode existed the record fell through
 the dispatch unhandled, so the channel silently lost its first 512 samples —
 which is what produced the "loud events truncate" symptom.
 `MODE_ABSOLUTE` is also valid as a **preamble** (the implicit segment-0 Tran
 record); its tagged blocks start at `body[3]`, not `body[7]`, because its
 header is 10 bytes rather than 14.
 ### Body offset is not fixed at 0x0f1f — and 0x0f1f is really a record + 7
 A "body offset" is `<record start> + 7`, so that `body[0]` is the segment
 index and `body[1:3]` is the mode.  The canonical `0x0f1f` is simply the
 record at `0x0f18`.
 Searching for the literal preamble `00 02 00` finds only MODE_DELTA bodies,
 and worse, it **matches the `[seg][mode]` bytes inside any record header**,
 so the scan could pick a candidate part-way down the chain.  That decodes a
 plausible-looking but rotation-shifted body which drops each channel's
 segment 0 — the real cause of the remaining truncations.
 `_find_waveform_body_offset()` now anchors on record headers (the
 `<channel_id> 00 00` signature at `+4`, validated with `is_record()`),
 takes the **chain head** — a record no other record's length field points at
 — and trial-decodes `head + 7`, preferring the candidate where all four
 channels come out the same length.
 ⚠ Do **not** scan for candidate preambles instead: `MODE_RAW16` is
 `00 00`, so every run of three zero bytes looks like a body start and each
 costs a full trial decode (~0.5 s/file measured, vs 6 ms/file now).
 ### `40 NN` is not capped at NN=8 (2026-09-11)
 `data_block_len()` rejected any `40 NN` int16 block with `NN > 0x08`.  The cap
 had no evidence behind it — every corpus available when it was written used
 only NN ∈ {1, 2, 3, 4, 8}, so it was never exercised.  Loud events use much
 wider blocks:
 | corpus | `40 NN` values | walker stops |
 |---|---|---|
 | first + 3-channel corpora | 1, 2, 3, 4, 8 | none |
 | UM12947 2025-07..09 | 2, 4, 8, **12, 16, 20 … 196** | every value > 8 |
 Because `walk_body`/`run` stop at the first unrecognised tag rather than
 raising, this surfaced as **silently short channels** — e.g. Tran 1812 /
 Vert 2132 / Long 2324 on a file whose export has 2324 for all three.  The
 real bound is the buffer (and the caller's record end), not a magic constant.
 Verified against Thor's exports for UM12947 (2025-07-14 … 2025-09-25, 167
 waveforms): length mismatches **22 → 0**, and **1,476,242 / 1,476,249**
 samples exact.
 ⚠ These events are **not** truncated recordings, which was the competing
 hypothesis — the exports carry the full sample count.
 **The 7 residual samples are Thor's rounding, not ours.**  Each differs by
 exactly one 4th-decimal tick (e.g. decoded 3.3551 vs export 3.3550).
 Intersecting the per-sample rounding constraints over this corpus is
 **infeasible** — the binding pair (count 2013 → 0.6247, count 4351 → 1.3501)
 contradict by 2.3e-11, i.e. 7e-5 relative.  No single linear LSB can
 reproduce every printed value, so Thor is not doing plain round-half-up on
 `count × LSB`.  Do not retune `_GEO_LSB_IPS` to chase these; it is already
 pinned to ~1e-11.
 ### Mic-disabled units are a distinct shape (2026-09-10, second corpus)
 Some units run with the microphone disabled — **3 channels, not 4** — and that
 changes two structural things.  Confirmed on the `9-10-26-csv-req` corpus
 (UM11402, UM12947, UM20147): 139/139 waveforms and 877/877 histograms.
 **Waveform: the body starts earlier.**  A 3-channel unit has a shorter fixed
 header and puts its record chain head at **`0x0dba`**, below the old
 `_BODY_SCAN_FLOOR` of `0x0E00`.  The head was therefore invisible to the scan,
 which fell through to the *Vert* segment-0 record and decoded a body shifted
 one position around the channel rotation.  The signature is unmistakable:
 ```
 Tran 3072 / Vert 2560 / Long 3072 / MicL 0      <- Vert exactly 512 short
 ```
 46 of 139 files in that corpus were affected; all 46 became per-sample exact
 once the floor dropped to `0x0C00`.  Note the body-offset scoring also had to
 stop requiring four channels — `len(lengths) >= 3`, not `== 4`, or `equal` is
 permanently False for these events and the pick falls back to raw sample count.
 **Histogram: the interval record is 56 bytes, not 72.**
 ```
 interval_size = 16 × n_channels + 8        (72 for 4 channels, 56 for 3)
 ```
 It is **not a constant**, and it cannot be inferred from `length` alone.
 Derive the interval count from the segment counter — it is cumulative, so
 `n = counter - previous_counter` — and then `stride = (length - 10) / n`.
 `n_channels` follows from `(stride - 8) / 16`.
 Assuming 72 read 7 intervals out of each 10-interval segment and then walked
 off alignment into garbage that decoded as ~10 in/s peaks — inflating those
 files' PPV by up to 191,000%.  Fixing it moved the second corpus from 56.6% to
 **100.0%** of histograms within 2% of Thor's reported PPV, and recovered 4
 files that previously decoded no intervals at all.
 ### What is still open
 - ~~23 of 575 production IDFW files~~ — **RESOLVED 2026-09-11.** Production
  IDFW is now **575/575** with zero truncations and zero decode failures
  (median PPV error −0.0007%).  See "`40 NN` is not capped at NN=8" above.
 - Mic → psi scale is still the rough `2.14e-6` regression, not derived.
 - Per-channel `int16 field4` in the IDFH interval record (possibly
  time-of-peak) and the 8-byte tail (PVS data) remain undecoded.
 ⚠ **Thor's histogram PPV has a display floor of 0.0050 in/s.**  In the
 production store 6,080 sidecar PPV values are exactly 0.0050 (next most
 common value: 275 occurrences), and **41.4% of IDFH sidecars report a
 component PPV larger than their own vector sum** — geometrically impossible.
 On those quiet files the decoder's ~0.0025 in/s is *more* accurate than the
 reference; do not "fix" the decoder to match it.
 ### Codec breakthroughs (2026-05-28)
 - **Body offset is a fixed `0x0f1f`** across 151/154 corpus IDFW
@@ -0,0 +1,135 @@
 # USBM RI8507 / OSMRE Blasting Compliance Curve — Reference
 Reference for the **velocity-vs-frequency blasting compliance chart** Blastware
 draws on its Event Report ("USBM RI8507 And OSMRE"), and how seismo-relay
 reproduces it. Implemented in [`sfm/compliance.py`](../sfm/compliance.py); the
 spectral (FFT) side lives in [`waveform_fft.py`](../waveform_fft.py).
 Reverse-engineered 2026-09-14 against 7 BE12844 (MiniMate Plus) events, each
 with a Blastware Event Report + FFT Report as ground truth. Curve values from
 USBM RI8507 Appendix B and 30 CFR 816.67.
 ---
 ## What it is
 Two closely-related sources for the same limit curve:
 - **USBM RI8507** — Bureau of Mines *Report of Investigations 8507* (Siskind
  et al., 1980), *"Structure Response and Damage Produced by Ground Vibration
  From Surface Mine Blasting."* The curve is **Figure B-1**, Appendix B
  ("Alternative Blasting Level Criteria"), p.73–74.
 - **OSMRE / OSM** — the Office of Surface Mining Reclamation and Enforcement
  codified it as **30 CFR 816.67, Figure 1**. "CFR" = the U.S. Code of Federal
  Regulations. Same curve, regulatory force.
 The chart plots each geophone channel's significant vibration cycles as
 `(frequency, peak velocity)` points against this limit. A point **below** the
 line passes; **above** fails.
 ---
 ## The limit curve
 A structure has a resonance band (~4–12 Hz for whole structures) where it is
 most vulnerable, so the safe velocity is **lower** at those frequencies and
 **higher** away from them. The curve captures this by alternating two kinds of
 bound:
 - **Constant-velocity** segments — a flat horizontal line at a fixed PPV.
 - **Constant-displacement** segments — a fixed peak *displacement* `d`. For
  simple harmonic motion, peak velocity `v = 2πf·d`, so on a velocity-vs-
  frequency **log-log** plot this is a straight line of slope +1 (velocity rises
  with frequency). This is why the low- and high-frequency bounds are sloped.
 ### Two lines — structure type
 RI8507 gives two lines for two interior-wall constructions (Table 13, p.67):
 | line | construction | plateau PPV |
 |---|---|---|
 | **Drywall** (solid) | modern gypsum wallboard | **0.75 in/s** |
 | **Plaster** (dashed) | older plaster on wood lath | **0.50 in/s** |
 Plaster-on-lath is more damage-prone, hence the lower limit. You apply **one**
 line depending on the monitored structure.
 ### The four segments (Figure B-1, p.74)
 Going low → high frequency, each line is:
 1. **Ultimate low-frequency bound** — constant displacement **0.030 in**
   (`v = 2πf·0.030`). Only relevant below ~4 Hz.
 2. **Plateau** — constant velocity **0.75** (Drywall) / **0.50** (plaster) in/s.
 3. **Rising diagonal** — constant displacement **0.008 in** (`v = 2πf·0.008`),
   climbing from the plateau up to the high-frequency cap.
 4. **High-frequency cap** — constant velocity **2.0 in/s** above ~40 Hz.
 The segments are drawn **continuous**: each bound is used over the frequency
 range where it is the binding (lowest) limit, and consecutive bounds meet where
 they are equal — so there are no vertical steps. Transition frequencies come
 straight from the values (`f = V / (2π·d)`):
 | transition | formula | Drywall | Plaster |
 |---|---|---|---|
 | 0.030 in → plateau | `V_mid / (2π·0.030)` | 3.98 Hz | 2.65 Hz |
 | plateau → 0.008 in | `V_mid / (2π·0.008)` | 14.92 Hz | 9.95 Hz |
 | 0.008 in → 2.0 in/s | `2.0 / (2π·0.008)` | 39.79 Hz | 39.79 Hz |
 Because both lines share the same **0.008 in** rising diagonal, above ~15 Hz
 they lie on the *same* line (both reach 2.0 in/s at ~40 Hz) — RI8507's literal
 construction merges them there. Blastware renders the dashed line as a separate
 parallel diagonal, but that is cosmetic: above ~15 Hz both structure types carry
 the identical limit, so compliance is unaffected.
 > ⚠ RI8507's *Table 13* is a simpler two-range criterion with a **sharp
 > discontinuity at 40 Hz** (flat plateau, then a jump to 2.0). Figure B-1 is the
 > **smoothed** version that adds the 0.008 in transition — that is the one drawn
 > on reports and implemented here.
 ---
 ## The compliance scatter (the points)
 The cloud is **not** the FFT spectrum. It is a per-cycle, time-domain measure by
 the **zero-crossing method** (`channel_compliance_points`):
 - Split the channel's waveform at its zero crossings.
 - Each half-cycle contributes one point: **frequency** `= 1 / (2 · half-period)`
  (from the samples between the two crossings), **velocity** `= peak |amplitude|`
  in that half-cycle.
 This yields ~90–110 points per channel, and — by construction — each channel's
 **highest** point equals that channel's PPV. Verified against Blastware: the
 cloud shape, density, and ceiling all match.
 ### Why not the FFT?
 A broadband blast spreads its energy across many FFT bins, so no single bin
 reaches the time-domain peak — the FFT amplitudes come out ~10× below the
 compliance-chart velocities. The compliance chart is a *per-cycle peak* view;
 the **FFT** is a separate analysis (Blastware's *FFT Report*), reproduced by
 [`waveform_fft.py`](../waveform_fft.py) and used for the dominant-frequency
 readout and the #10 FFT view — not for this scatter.
 ---
 ## Implementation
 - `sfm/compliance.py`
  - `limit_at(freq, curve)` — the limit PPV at a frequency (`curve` = `"Drywall"`
    or `"Plaster"`); curves are data in `_CURVES`, so more standards can be added.
  - `channel_compliance_points(samples, sps)` — the zero-crossing scatter.
  - `draw_compliance_chart(ax, channels, sps)` — matplotlib rendering (both
    limit lines + per-channel scatter, Blastware's tick scales and channel
    markers: Tran `+` red, Vert `×` green, Long `o` blue).
 - Tests: `tests/test_compliance.py`.
 ---
 ## Sources
 - USBM **RI8507** (Siskind, Stagg, Kopp, Dowding, 1980), Appendix B / Figure B-1,
  p.73–74; Table 13, p.67. (`ref-stuff/usbm-ri8507-ground_vibration.pdf`.)
 - **30 CFR 816.67**, "Use of explosives: Control of adverse effects," Figure 1 —
  <https://www.ecfr.gov/current/title-30/chapter-VII/subchapter-K/part-816/section-816.67>
@@ -14,6 +14,27 @@ This runbook describes how to break the loop and recover control.
 ---
 ## ⚠ There are TWO failure modes under "wedged unit"
 Same root cause — an offset/connector fault drives the geophone above trigger,
 the unit records back-to-back, ACH set to "after event recorded" dials
 constantly — but the *recovery* differs, because the thing blocking you is
 different.
 | | **BE9558H (2026-05)** | **BE12599 (2026-09)** |
 |---|---|---|
 | What blocks you | Modem mode-flipping kills inbound TCP | Device never enters S3 mode at all |
 | Device state | Alive, in S3 mode, responsive once reached | Stuck repeating an **AT modem-init** string, deaf to S3 |
 | Fix direction | **Inbound** — clear Destination, slow-drip a Stop | **Inverted** — point Destination at our own ACH server and let the unit call *us* |
 | Winning tool | `scripts/slow_drip.sh` | `bridges/ach_server.py --stop-monitoring` |
 **Tell them apart with the ALEOS serial log** (see "Turn on ALEOS_SERIAL debug"
 below). If the device is emitting `ATQ1/ATE0/ATS0=2` every ~75 s, it is in the
 BE12599 mode and **no amount of inbound work will reach it** — skip to
 "Second incident" below.
 ---
 ## Symptoms
 - Terra-View / SFM `/device/info` either hangs or fails on `count_events()`.
@@ -253,3 +274,206 @@ service).
 Total time from "i was wondering if its possible to" first attempt to
 recovery: ~7 hours of intermittent debugging across one evening.
 ---
 # Second incident — BE12599, 2026-09-16/17
 **Unit:** BE12599 at `166.246.64.226:9034`, RV50, job *I-80 North Fork Bridge
 — Abut 1 West* (Fay Company).  Same job as BE9558H, which is a coincidence.
 **Fault:** the connector fault documented in `docs/offset_investigation.md`
 §8e progressed until the Tran pedestal reached **0.400 in/s** — its trigger
 level.  Constant triggering → constant recording → ACH "after event recorded"
 → continuous dialing.  Same disease as BE9558H.
 **But the recovery was the opposite direction**, and none of the Step 1–4
 procedure above worked.  Total time ≈ 5 h, of which ~90 min was spent on two
 red herrings documented below.
 ---
 ## Turn on ALEOS_SERIAL debug FIRST
 This is the single highest-value diagnostic and it should be step zero on any
 future incident.  ACEmanager → **Admin → Log → ALEOS_SERIAL log level →
 DEBUG**, then view the serial log.
 It is the only thing that tells you what the *device* is actually saying.
 Everything before we did this was guesswork.
 ## What the log showed — the device was never in S3 mode
 Every ~75 seconds, verbatim:
 ```
 ALEOS_SERIAL_HIF: 29 byte(s) in buffer: 'ATQ1^MATE0^MATS0=2^M^MRADIO RING^M'
 ALEOS_SERIAL_HMC: TCP recvhost fd 65535 len 29  state TCPMode::kClosed
 ALEOS_SERIAL_HMC: tcpmode trying to send to invalid socket
 ALEOS_SERIAL_HMC: Connect to IP: 0.0.0.0 Port 0
 ALEOS_SERIAL_HMC: Initialize Auto answer on port 9034
 ALEOS_SERIAL_HMC: Cannot connect to 0.0.0.0
 ```
 Read that carefully:
 - `ATQ1` (quiet) / `ATE0` (echo off) / `ATS0=2` (auto-answer after 2 rings).
  **There is no `ATD`.**  The device is not dialing — it is trying to
  *configure* its modem.
 - The modem's serial port is in TCP data mode, so it never interprets these
  as AT commands.  It treats them as payload and tries to ship them to a TCP
  socket that does not exist.
 - The device therefore never receives `OK`, never progresses, and **retries
  the identical 29 bytes forever**.
 **Consequence: the device is not running the S3 protocol parser.**  You can
 land a byte-perfect S3 frame on it and it will be ignored.  This is why every
 inbound approach failed, and it is the structural difference from BE9558H.
 ### Why `slow_drip` lied
 `slow_drip` returned the *success* signature except for the one field that
 mattered:
 ```json
 {"duration_s":120.0,"drips_sent":38,"bytes_sent":920,
 "bytes_received":0,"send_error":null}
 ```
 Full duration, no broken pipe — but zero bytes back.  Cause is in the log
 above: each 75 s cycle re-runs `Initialize Auto answer on port 9034`, which
 orphans the held session (`data in for unknown reason 3 removing from
 select`, `OnMsg recv error: 107 - Transport endpoint is not connected`).  Our
 local TCP stayed open so `sendall` never raised — but the modem stopped
 bridging after the first re-init, so every drip after that went into a socket
 nobody was reading.
 ⚠ **`send_error: null` + full duration is NOT success.  Only
 `bytes_received > 0` is success.**
 ---
 ## ⚠ Two red herrings that cost ~90 minutes
 ### 1. The trusted-IP whitelist (this was the real reason inbound never worked)
 The RV50s run with **Security → Trusted IPs (Friends List) enabled**.  A
 source IP that is not on the list is dropped **silently** — inbound presents
 as `Connection error: timed out`, never a refusal.
 Brian's dev-box public IP is **dynamic** and had changed, so `tmi-dev` was no
 longer whitelisted.  Every inbound attempt failed identically across four
 different modem and device states, which looked exactly like the BE9558H
 mode-flipping symptom and sent us chasing modem configuration for over an
 hour.
 **Check this before diagnosing anything else.**  Note that SFM in Docker
 egresses via the *host's public IP*, not its LAN IP.
 ### 2. A 502 from SFM does not mean TCP connected
 `sfm/server.py` raises **502 for both** failure classes:
 ```python
 raise HTTPException(status_code=502, detail=f"Protocol error: {exc}")
 raise HTTPException(status_code=502, detail=f"Connection error: {exc}")
 ```
 We read an early 502 as "TCP connected, modem bridged, device mute" and built
 a whole theory on it.  It was almost certainly a connect timeout.
 **Always read the `detail` string** — "connect failed" and "device didn't
 answer" are completely different problems and the status code will not
 separate them.
 ---
 ## What actually worked — invert the direction
 The key observation is in the log above:
 > `TCP recvhost ... state TCPMode::kClosed` → `Connect to IP: 0.0.0.0 Port 0`
 **The modem auto-dials its Destination whenever serial data arrives while
 closed.**  So instead of fighting for inbound, give it somewhere to dial:
 point `Destination Address` at our own `ach_server` and the device's own
 75-second attempts become **device-initiated sessions the modem bridges
 correctly**.  No race, no contention, worst case a 75-second wait.
 ### Procedure
 1. **Run the rescue server** on a host the modem can reach (public IP +
   forwarded port):
   ```bash
   cd /home/serversdown/seismo-relay
   .venv/bin/python -u bridges/ach_server.py --port 12345 \
     -o bridges/captures/<unit>-diag --stop-monitoring -v
   ```
 2. **Point the modem at it** — ACEmanager → Serial → Port Configuration →
   `Destination Address` = your public IP, `Destination Port` = 12345.
 3. **Wait for the call-in.**  `--stop-monitoring` fires SUB 0x97 at step 1.5,
   after the handshake and *before* the event walk.  Confirm via
   `rescue.json` in the session directory:
   ```json
   {"peer": "166.246.64.226:60921", "stop_monitoring": "ok"}
   ```
 4. **Restore the modem's Destination** once you are done, then finish the
   device side (disable ACH, erase) through whichever channel works.
 On BE12599 the first call-in landed at 20:58:11 and reported
 `stop_monitoring: ok`; a second at 20:58:20 confirmed it.  `is_monitoring:
 false` was still true **6½ hours later** — the fix is durable.
 ---
 ## Hard-won gotchas (do not re-derive)
 - **Never leave the Destination pointed at a host with nothing listening.**
  That is the worst state available: the device still dials, the modem still
  flips, inbound stays blocked, and nothing is delivered.  An 8-minute gap
  with the listener down produced a spurious inbound timeout that cost
  another round of misdiagnosis.
 - **Stopping monitoring removes your call-in channel.**  ACH is "after event
  recorded"; no new events means no new dials.  The backlog sitting in memory
  does *not* re-arm it.  After a successful stop the unit goes quiet and you
  need the modem cycled (works — produced a call-in), the scheduled daily call
  (BE12599 calls at **05:00:14 device-local**, per §8e), or working inbound.
  **Plan the order before you fire the stop.**
 - **`--events-only` silently breaks dedup.**  It skips the device-info step,
  so the serial is never read; `ach_state.json` then keys on
  `peer:ephemeral_port`, which is unique per connection.  Every session looks
  like a new unit, starts from key 0, and re-downloads the same event.  Four
  sessions on BE12599 downloaded the identical event four times and made zero
  progress on the backlog.  Events also file as `serial=UNKNOWN` with a
  `M000…` BW filename (serial_numeric 0) instead of `N599…`.
  **Do not use `--events-only` when you intend to download anything.**
 - **`/device/events/index` reported `lifetime_count: 0`** on a unit with years
  of history.  Suspected decode bug in the SUB 0x08 field offset — do not
  trust that number.  The 88-byte payload is preserved in the `raw_hex` field
  if someone wants to chase it.
 - **Memory used cross-checks the event keys exactly:**
  `last_key − buffer_start = memory_total − memory_free`.  On BE12599:
  `0x011230ec − 0x01110000 = 78,060` and `983,028 − 904,968 = 78,060`.
  Useful sanity check that you are reading the keys right.
 ---
 ## Final state (2026-09-17 ~01:30 local)
 - `is_monitoring: false`, held 6½ hours
 - Battery 6.76 V
 - Memory 78,060 / 983,028 bytes used (8%)
 - `first_key 01121728`, `last_key 011230ec` — ~6.6 KB of addressable event
  chain, roughly 3 events
 - ACH still **enabled** — to be disabled after the backlog is preserved
 - Modem Destination still pointed at tmi-dev — to be restored
 - ⚠ **Do not re-enable ACH until the connector is serviced.**  Tran is still
  sitting at 0.400 and the loop restarts the moment monitoring resumes.
@@ -0,0 +1,134 @@
 # Plan — "Rescue Listener": a first-class tool for the inverted rescue
 **Status:** proposal, not started.  Written 2026-09-17 ~01:40 local, straight
 off the BE12599 incident.  Open questions at the bottom need Brian's answer
 before anything is built.
 **Background:** `docs/runbooks/wedged_unit_recovery.md`, "Second incident —
 BE12599".  The manual version of this worked; this plan is about making it a
 tool instead of a sequence of remembered steps at 1 AM.
 ---
 ## The problem, stated plainly
 When a unit is wedged in the BE12599 mode — geophone offset above trigger,
 recording back-to-back, ACH dialing constantly, device stuck repeating an AT
 modem-init string and therefore **deaf to S3 over inbound** — the only channel
 that works is the one the *device* opens.
 Recovering it currently means:
 1. Remember that `bridges/ach_server.py` exists and takes the right flags
 2. Start it by hand on a box the modem can reach, with a public port forwarded
 3. Go into ACEmanager and repoint the modem's Destination
 4. Watch a terminal for a call-in
 5. Read `rescue.json` to find out whether it worked
 6. Go back into ACEmanager and repoint the modem to where it belongs
 7. **Not forget step 6**, because leaving the Destination pointed at a dead
   listener is worse than never having started
 That is six manual steps and one landmine, executed under pressure while a
 unit floods the office server.
 ## What the tool should be
 **A "rescue listener" an operator can start for one unit, which handles
 whatever that unit says when it calls in, and refuses to go away until the
 operator confirms the modem has been pointed back.**
 Lifecycle:
 1. **Start** — operator names the target unit and starts a rescue listener.
   The tool reports the exact address/port to enter in ACEmanager, plus the
   actions it will take.
 2. **Operator repoints the modem** to that address.
 3. **Wait** — listener sits there.  Live status: "waiting for call-in",
   elapsed, last-seen.
 4. **Act** — on call-in, run the configured rescue actions automatically,
   in a safe order, each independently guarded.  Report per-action outcome.
 5. **Hold** — the listener **stays up** and keeps reporting, because the
   modem is still pointed at it.
 6. **Confirm & stop** — the operator explicitly confirms the Destination has
   been restored (to `0.0.0.0`, or to the office Instantel ACH server).
   Only then does the listener shut down.
 Step 6 is the whole point of making this a tool.  It is the step that is
 easiest to skip and most expensive to skip.
 ## Default action set
 Ordered deliberately — see "order matters" below.
 | # | Action | Default | Why |
 |---|---|---|---|
 | 1 | **Stop monitoring** (SUB 0x97) | ✅ on | Halts recording; ends the trigger→record→dial loop at its source.  Already implemented as `--stop-monitoring`. |
 | 2 | **Drain events** to a diagnostics store | ⚙ configurable | The backlog is usually evidence, not garbage — see the BE12599 offset investigation.  Must NOT land in the prod SFM DB. |
 | 3 | **Disable ACH** (SUB 0x2C/0x7E/0x7F) | ❌ off by default | Stops the dialing — **and stops your only channel**.  Opt-in, and ideally gated on step 1 having succeeded. |
 | 4 | **Erase events** | ❌ off by default | Destructive.  Only after a verified drain. |
 ### Order matters — the lesson from BE12599
 Stopping monitoring *removes the call-in trigger*.  ACH fires on "after event
 recorded"; with recording stopped, the unit has no reason to dial again, even
 though the backlog is still sitting in its memory.  So a naive
 "stop + disable + erase, all at once" rescue can silence the unit before
 you've collected anything, leaving you with no channel and a device full of
 evidence.
 The tool should either sequence around this or warn loudly about it.  My
 instinct is: **stop monitoring immediately** (it's the bleeding), then drain
 across however many call-ins it takes, and treat disable-ACH/erase as a
 separate, explicit "finish" action once the operator is satisfied.
 ## Where it should live — open question, with a proposal
 The natural tier is **SFM** (device-side, per the three-tier model in
 CLAUDE.md).  But the rescue listener must be reachable *from the cellular
 network*, which is a deployment constraint SFM's usual profile doesn't have.
 **Proposal worth considering:** run it at the office, beside the real Instantel
 ACH server, on a **different port** (e.g. 12346 while Instantel holds 12345).
 Then the ACEmanager change is a **port change, not an IP change** — smaller,
 faster, less to get wrong, and trivially reversible.  It also means the office
 public IP (already stable and known) is the destination, rather than whatever
 Brian's dynamic home IP happens to be that week.
 The tmi-dev approach used on BE12599 worked, but required a router forward and
 ran into the dynamic-IP problem in the same session.
 ## Open questions
 1. **Where does it run?**  Office beside Instantel ACH (port swap), SFM on the
   NAS, or ad-hoc on tmi-dev?  Affects everything else.
 2. **What drives it?**  Terra-View admin page (fits "operator UI"), an SFM
   endpoint pair (`POST /device/rescue_listener/start` + `/stop` + `/status`),
   or a CLI wrapper?  A long-lived listener doesn't fit the request/response
   endpoint shape well — probably needs a background task with a status poll.
 3. **How does it identify the unit?**  It can't know the serial until the
   device calls in and the handshake reads it.  Allowlist by modem IP?  Accept
   anything and report what showed up?
 4. **Where do drained events go?**  A per-incident diagnostics store
   (`bridges/captures/<unit>-diag`) seems right — explicitly *not* the prod
   SFM DB.  Does that store need to be a first-class thing with its own
   retention, or is a directory fine?
 5. **How is "confirm the modem is repointed" verified?**  Operator attestation
   (a button), or can we actually probe it?  If the listener stops seeing
   call-ins that's weak evidence; if inbound to the unit starts working that's
   stronger.
 6. **Multi-unit?**  One listener per incident, or one listener that handles any
   unit that dials in?  Probably the former for safety.
 7. **Timeout / abandonment policy.**  If nobody ever confirms, does it run
   forever?  Alert after N hours?
 ## What already exists
 - `bridges/ach_server.py` — the listener itself, with `--stop-monitoring`,
  `--disable-ach`, `--rescue` (added on `feat/ach-rescue-on-connect`, commit
  `9f1050b`), `--clear-after-download`, `--max-events`, `--allow-ip`.
 - Per-session `rescue.json` recording per-action outcomes.
 - Isolated per-output-dir SQLite + waveform store, so a diagnostics capture is
  already separate from prod by construction.
 So the gap is not protocol work — it's lifecycle, operator surface, and the
 confirmation gate.  Most of the risk is in questions 1 and 2.
@@ -47,19 +47,24 @@ from dataclasses import dataclass
 from pathlib import Path
 from typing import Optional, Union
-# Thor IDFW bodies are pinned to the SUPERSEDED tag-dispatch decoder.
+# Thor IDFW bodies use the series-3 record-chain decoder.
 #
-# _find_waveform_body_offset() trial-decodes every candidate offset and keeps
+# This was previously pinned to the SUPERSEDED tag-dispatch walker
-# whichever yields the most samples.  The series-3 record-chain decoder
+# (`decode_waveform_legacy`) on the stated grounds that "Thor has no ASCII
-# correctly returns None where the legacy walker returned garbage, which
+# ground truth in the corpus and its geo scaling is separately suspect".
-# changes that heuristic's winner on 33 of 577 files.  The net effect measured
+# Both premises were false: Thor writes a per-sample CSV export next to every
-# 2026-08-25 was positive (all-channels-equal 8/577 -> 506/577, mean abs PPV
+# binary (see scratch/verify_thor_against_csv.py), and the scaling is now
-# error 0.228 -> 0.173 in/s) but Thor has no ASCII ground truth in the corpus
+# resolved (see _GEO_LSB_IPS).  Measured against that ground truth on
-# and its geo scaling is separately suspect, so the switch is deferred until
+# 2026-09-10, the record chain beats the legacy walker outright:
-# the body-offset search is reworked to use the record chain directly.
+#
-from minimateplus.waveform_codec import (
+#     channel truncation   55/153 files -> 3/153
-    decode_waveform_legacy as decode_waveform_v2,
+#     files exact           98/153      -> 150/153
-)
+#     per-sample exact      99.781%     -> 99.854%
 #
 # The legacy walker stops at the first unrecognised tag and returns whatever
 # channels it had, so its failure mode is silent short channels rather than an
 # error.  Do not re-pin it.
 from minimateplus.waveform_codec import _MODES, decode_waveform_v2, is_record
 from .models import IdfEvent, IdfPeaks, IdfReport
@@ -89,23 +94,70 @@ _BODY_MAGIC = b"\x00\x02\x00"
 # fixed-header region where the same magic legitimately appears inside
 # channel-test records and the compliance block (offsets 0x015d, 0x091c,
 # 0x0ae2, 0x0d30 in observed events).
-_BODY_SCAN_FLOOR = 0x0E00
+# Lowered from 0x0E00 to 0x0C00 (2026-09-10).  Three-channel events -- mic
 # disabled -- have a shorter fixed header and put their record chain head at
 # 0x0dba, below the old floor.  The head was therefore invisible to the scan,
 # which fell through to the *Vert* segment-0 record and decoded a body shifted
 # one position around the channel rotation.  46 of 139 files in the
 # 9-10-26-csv-req corpus were affected; all 46 became per-sample exact once
 # the head was reachable.  The floor still skips the fixed-header region,
 # where `is_record()` can match channel-test records (0x015d, 0x091c, 0x0ae2).
 _BODY_SCAN_FLOOR = 0x0C00
-# Geophone count → in/s, derived from sidecar ground truth: the smallest
+# Cap on trial decodes per file.  Chain-head detection normally yields one
-# non-zero sample in 1,014-file corpus is 0.0003 in/s.
+# or two candidates; the cap only bounds the worst case on a corrupt file.
-_GEO_LSB_IPS = 0.0003
+_MAX_BODY_CANDIDATES = 16
 # Geophone count → in/s.
 #
 # The old value 0.0003 was read off the smallest non-zero sample in the
 # sidecar corpus, but that sample is Thor's *4-decimal display rounding* of
 # the true LSB, not the LSB itself.  It read every series-4 geophone sample
 # 3.3% low.  The quantisation ladder gives it away: counts 1..6 export as
 # 0.0003, 0.0006, 0.0009, 0.0012, 0.0016, 0.0019 — an LSB of exactly 0.0003
 # would end 0.0015, 0.0018.
 #
 # The value below maximises exact 4-dp agreement over 1,046,016 paired
 # samples (454 channel-events, 2 units) at 99.854%, versus 50.7% for 0.0003.
 # It is a global constant, not a per-unit calibration: all 8 UM units in the
 # production store independently agree to within ±0.07% on their
 # device-reported PPV.  1/LSB = 3222.6 counts per in/s.
 #
 # The value is pinned, not guessed.  Each exported sample constrains the LSB
 # to the window that rounds to the printed 4-dp figure; intersecting 991,415
 # such constraints (clean channel-events only) gives
 #
 #     LSB in [0.000310307933, 0.000310308057]     width 1.2e-10
 #
 # 0.000310308 sits at the centre of that window.  Equivalent full scale is
 # 10.0 in/s / 0.000310308 = 32226.05 counts.
 #
 # Corroboration from the device: an IDFH interval that never recorded keeps
 # its min/max accumulator at its ±full-scale seed, and that seed is
 # (min=+32226, max=-32226) — the same magnitude, independently.  Note the
 # tempting closed form 10.0/32226 is very slightly WRONG: it lands 4.5e-10
 # above the feasible window and loses 78 boundary samples to the literal
 # value while never winning one.  Series-3 uses 32000 counts for the same
 # 10.0 in/s, so the two generations do NOT share a scale.
 #
 # Ground truth + harness: scratch/verify_thor_against_csv.py
 _GEO_LSB_IPS = 0.000310308
 # Microphone count → psi, derived from sidecar regression on 50 sample
 # pairs from UM11719_20231219162723.IDFW (mic-heavy event).
 _MIC_LSB_PSI = 2.14e-6
 # IDFH histogram constants.
-_IDFH_INTERVAL_SIZE = 72        # bytes per per-interval record
+# Bytes per interval record = 16 per channel + an 8-byte tail, so a
 # 4-channel unit uses 72 and a mic-disabled 3-channel unit uses 56.  It is
 # NOT a constant: derive it per segment from the interval counter (see
 # decode_idfh_body).  This value survives only as the 4-channel default.
 _IDFH_INTERVAL_SIZE = 72        # bytes per per-interval record (4 channels)
 _IDFH_CHANNEL_BLOCK = 16        # bytes per channel inside an interval record
 _IDFH_INTERVAL_TAIL = 8         # bytes after the per-channel blocks
 _IDFH_SEGMENT_HEADER = 10       # bytes: [len_be 2B][0a 00 00 00 4B][00 NN 2B][05 3f 2B]
 _IDFH_SEGMENT_TAIL   = 2        # bytes after the interval data block, before next marker
 _IDFH_HALFP_FREQ_NUM = 512.0    # freq_hz = NUM / halfp; halfp ≤ 5 means ">100 Hz" sentinel
 _IDFH_GEO_FULL_SCALE = 10.0     # in/s — Normal range
 _IDFH_INT16_FS = 32768.0
 _IDFH_CHANNELS = ("Tran", "Vert", "Long", "MicL")
@@ -223,26 +275,67 @@ def _find_waveform_body_offset(buf: bytes) -> Optional[int]:
    """
    if len(buf) < _BODY_SCAN_FLOOR + 8:
        return None
-    best: Optional[tuple[int, int]] = None   # (total_samples, offset)
+
-    i = _BODY_SCAN_FLOOR
+    # 1. Locate every plausible per-channel record header.  A header carries
-    while True:
+    #    [len 2B][channel_id][00][00] at +2..+6, so anchor the search on the
-        j = buf.find(_BODY_MAGIC, i)
+    #    three-byte ``<cid> 00 00`` signature and validate with is_record().
-        if j < 0:
+    #    Scanning candidate *preambles* instead is not viable: MODE_RAW16 is
-            break
+    #    ``00 00``, so every run of three zero bytes would look like a body
-        i = j + 1
+    #    start and each would cost a full trial decode (~0.5 s/file measured).
    floor = max(0, _BODY_SCAN_FLOOR - 7)
    starts: list = []
    for cid in (0x46, 0x47, 0x48, 0x49):
        sig = bytes((cid, 0x00, 0x00))
        i = floor
        while True:
            j = buf.find(sig, i)
            if j < 0:
                break
            i = j + 1
            q = j - 4
            if q >= floor and is_record(buf, q):
                starts.append(q)
    if not starts:
        return None
    starts.sort()
    # 2. A body begins at the head of a record chain -- a record that no other
    #    record's length field points at.  The head's own payload is the
    #    implicit segment-0 Tran record, and the body offset is head + 7 (past
    #    [len 2B][cid][00][00][seg]) so that body[1:3] lands on the mode.
    ends = {q + 2 + int.from_bytes(buf[q + 2 : q + 4], "big") for q in starts}
    heads = [q for q in starts if q not in ends] or starts[:1]
    # 3. Trial-decode each head and keep the best.  Prefer a candidate where
    #    all four channels come out the same length: scoring on raw sample
    #    count alone picks false positives sitting *inside* a record header,
    #    which decode a plausible-looking but rotation-shifted body that
    #    silently drops each channel's segment 0.
    best = None
    best_off = None
    for head in heads[:_MAX_BODY_CANDIDATES]:
        j = head + 7
        if j + 3 > len(buf) or (buf[j + 1], buf[j + 2]) not in _MODES:
            continue
        try:
            decoded = decode_waveform_v2(buf[j:])
        except Exception:
            continue
        if not decoded:
            continue
        lengths = [len(v) for v in decoded.values() if v]
        total = sum(len(v) for v in decoded.values())
        # A "real" body has more than just the 2-sample preamble.
        if total <= 2:
            continue
-        if best is None or total > best[0]:
+        # >= 3 rather than == 4: a mic-disabled event has only the three geo
-            best = (total, j)
+        # channels, and demanding four made `equal` permanently False for
-    return best[1] if best else None
+        # them, leaving the pick to raw sample count alone.
        equal = len(lengths) >= 3 and len(set(lengths)) == 1
        score = (equal, total)
        if best is None or score > best:
            best, best_off = score, j
    return best_off
 def _decode_waveform_samples(buf: bytes) -> Optional[dict]:
@@ -299,6 +392,12 @@ class IdfhInterval:
    micl_min:    int
    micl_max:    int
    micl_halfp:  int
    # 4 on a normal unit; 3 when the microphone is disabled, in which case the
    # micl_* fields are absent from the record and read as zero.
    n_channels:  int = 4
    def has_channel(self, channel: str) -> bool:
        return channel != "MicL" or self.n_channels >= 4
    def peak_count(self, channel: str) -> int:
        mn = getattr(self, f"{channel.lower()}_min")
@@ -307,7 +406,11 @@ class IdfhInterval:
    def peak_ips(self, channel: str) -> float:
        """Convert peak count to in/s (geo channels only)."""
-        return self.peak_count(channel) / _IDFH_INT16_FS * _IDFH_GEO_FULL_SCALE
+        # Same geo LSB as the waveform path — verified independently against
        # the IDFH exports: as peak magnitude rises (and 4-dp quantisation
        # noise falls) the implied LSB converges on 0.0003103, matching
        # _GEO_LSB_IPS.  The old 10.0/32768 read histogram peaks 1.7% low.
        return self.peak_count(channel) * _GEO_LSB_IPS
    def freq_hz(self, channel: str) -> Optional[float]:
        halfp = getattr(self, f"{channel.lower()}_halfp")
@@ -316,11 +419,46 @@ class IdfhInterval:
        return _IDFH_HALFP_FREQ_NUM / halfp
-def _decode_idfh_interval(buf72: bytes, offset: int) -> IdfhInterval:
+def _is_unwritten_interval(interval: "IdfhInterval") -> bool:
-    """Decode one 72-byte interval record into per-channel min/max/halfp."""
+    """True for an interval slot the device reserved but never wrote.
    Thor seeds each interval's per-channel accumulators at ``min = +full
    scale`` and ``max = -full scale`` and then narrows them as samples
    arrive.  A slot that never recorded keeps that seed, so ``min > max`` —
    impossible for real data.  Such a record decodes to a full-scale
    10.0 in/s peak on every channel and, being a max-over-intervals, poisons
    the whole file's PPV.
    Rare but real: exactly 1 of 497,611 corpus intervals, and it inflated
    that file's Long PPV from 0.0081 to 10.0 in/s.  The inversion is always
    all-or-nothing across channels (0 partial cases in the corpus), so
    requiring every channel to be inverted keeps this from ever firing on
    genuine data.
    """
    pairs = [
        (interval.tran_min, interval.tran_max),
        (interval.vert_min, interval.vert_max),
        (interval.long_min, interval.long_max),
    ]
    if interval.has_channel("MicL"):
        pairs.append((interval.micl_min, interval.micl_max))
    return all(mn > mx for mn, mx in pairs)
 def _decode_idfh_interval(buf72: bytes, offset: int,
                          n_channels: int = 4) -> IdfhInterval:
    """Decode one interval record into per-channel min/max/halfp.
    The record is ``n_channels`` × 16-byte blocks plus an 8-byte tail, so it
    is 72 bytes on a normal unit and 56 when the microphone is disabled.
    Missing channels read as zero.
    """
    import struct
    fields = []
    for i in range(4):
        if i >= n_channels:
            fields.extend([0, 0, 0])
            continue
        block = buf72[i * 16 : (i + 1) * 16]
        mn = struct.unpack_from(">h", block, 0)[0]
        mx = struct.unpack_from(">h", block, 2)[0]
@@ -336,6 +474,7 @@ def _decode_idfh_interval(buf72: bytes, offset: int) -> IdfhInterval:
        vert_min=fields[3], vert_max=fields[4], vert_halfp=fields[5],
        long_min=fields[6], long_max=fields[7], long_halfp=fields[8],
        micl_min=fields[9], micl_max=fields[10], micl_halfp=fields[11],
        n_channels=n_channels,
    )
@@ -343,36 +482,73 @@ def decode_idfh_body(buf: bytes) -> list:
    """Walk an IDFH file and decode every interval record.
    The body has one or more segments; each segment header is 12 bytes:
-    ``[length_be 2B][0a 00 00 00][00 NN_counter][05 3f]`` where ``length``
+    ``[length_be 2B][0a 00 00 00][counter_be 2B][05 3f]`` where ``length``
    is bytes from the magic through the end of the interval block
    (= 10 + 72 × n_intervals).  Segments are separated by a 2-byte tail
    + next-segment 2-byte prefix (the bytes before the next length field).
-    Confirmed against the 859-file corpus (181,071 intervals decoded; 1
+
-    failure is the sig-B BE9439 file).
+    ``counter`` is a **uint16 BE cumulative interval index** — the 0-based
    index of the LAST interval in this segment.  Segments carry 10
    intervals each, so it runs 9, 19, 29, ... across the file.
    ⚠ This validator used to require ``buf[j + 4] == 0x00``, i.e. that the
    counter's high byte was zero.  That silently capped every histogram at
    **250 intervals**: the moment the cumulative counter passed 255 the high
    byte went non-zero and every later segment was rejected, so any
    monitoring run longer than ~4 hours lost its tail — frequently the part
    holding the event peak, which is why those files' PPV read low.  540 of
    858 corpus files were affected.  Do not reinstate that check.
    """
    intervals: list = []
    i = 0
    prev_counter = -1          # so the first segment's n = counter + 1
    while True:
        j = buf.find(b"\x0a\x00\x00\x00", i)
        if j < 0 or j < 2:
            break
-        # Validate: [length_be][0a 00 00 00][00 NN][05 3f]
+        # Validate: [length_be][0a 00 00 00][counter_be][05 3f].  The counter
-        if buf[j + 4] != 0x00 or buf[j + 6 : j + 8] != b"\x05\x3f":
+        # is deliberately NOT constrained — see the note above.
        if buf[j + 6 : j + 8] != b"\x05\x3f":
            i = j + 1
            continue
        length = int.from_bytes(buf[j - 2 : j], "big")
-        n = (length - _IDFH_SEGMENT_HEADER) // _IDFH_INTERVAL_SIZE
+        counter = int.from_bytes(buf[j + 4 : j + 6], "big")
        header_start = j - 2
        if length < _IDFH_SEGMENT_HEADER or header_start + length > len(buf):
            # Truncated / bogus length — not a real segment header.
            i = j + 1
            continue
        # The counter is the cumulative index of this segment's LAST interval,
        # so the interval count is its delta from the previous segment.  That
        # gives the record stride, which is NOT fixed: 16 bytes per channel
        # plus an 8-byte tail, so 72 for a 4-channel unit and 56 for a
        # mic-disabled 3-channel one.  Assuming 72 unconditionally made every
        # 3-channel histogram read 7 intervals per 10-interval segment,
        # walking off alignment into garbage that decoded as ~10 in/s peaks.
        n = counter - prev_counter
        if n <= 0:
            i = j + 1
            continue
-        header_start = j - 2
+        stride = (length - _IDFH_SEGMENT_HEADER) // n
        n_channels, remainder = divmod(stride - _IDFH_INTERVAL_TAIL,
                                       _IDFH_CHANNEL_BLOCK)
        if remainder or not (1 <= n_channels <= 4):
            i = j + 1
            continue
        interval_start = header_start + _IDFH_SEGMENT_HEADER
        for k in range(n):
-            off = interval_start + k * _IDFH_INTERVAL_SIZE
+            off = interval_start + k * stride
-            if off + _IDFH_INTERVAL_SIZE > len(buf):
+            if off + stride > len(buf):
                break
-            chunk = buf[off : off + _IDFH_INTERVAL_SIZE]
+            chunk = buf[off : off + stride]
-            intervals.append(_decode_idfh_interval(chunk, off))
+            interval = _decode_idfh_interval(chunk, off, n_channels)
            if _is_unwritten_interval(interval):
                # Reserved-but-never-recorded slot: the min/max accumulators
                # still hold their ±full-scale seed.  Counting it would
                # fabricate a 10.0 in/s peak on every channel.
                continue
            intervals.append(interval)
        prev_counter = counter
        # Advance past this segment + the 2-byte tail.
        i = header_start + length + _IDFH_SEGMENT_TAIL
    return intervals
@@ -452,7 +628,12 @@ def read_idf_file(
        peak_long = max((iv.peak_ips("Long") for iv in intervals), default=0.0)
        # Mic peak in psi — Thor stores per-interval mic ADC counts in the
        # binary; convert the max count to psi via the per-count factor.
-        mic_peak_count = max((iv.peak_count("MicL") for iv in intervals), default=0)
+        # Skip on a mic-disabled (3-channel) unit: those records carry no mic
        # block at all, so peak_count("MicL") would report a synthetic zero.
        mic_peak_count = max(
            (iv.peak_count("MicL") for iv in intervals if iv.has_channel("MicL")),
            default=0,
        )
        mic_peak_psi = mic_count_to_psi(mic_peak_count) if mic_peak_count else None
        rep = IdfReport(
            serial_number=md.serial,
@@ -0,0 +1,75 @@
 """Structural annotation of a Series-3 Blastware waveform binary.
 Pure, no I/O: takes the raw file bytes and returns a flat, gap-free tiling of
 labelled :class:`Span` regions for a hex viewer to paint.  Every byte is
 covered — anything the decoder can't account for becomes an ``unknown`` span,
 so undecoded regions (e.g. a stored spectral/FFT block, if one exists) stand
 out instead of hiding.
 File layout (see ``blastware_file.py``):  ``[header][21B STRT][body][26B footer]``.
 The body is the record chain walked by :func:`waveform_codec.walk_records`.
 """
 from __future__ import annotations
 from dataclasses import dataclass
 from typing import List
 from .waveform_codec import walk_records
 _STRT_LEN = 21
 _FOOTER_LEN = 26
@dataclass
 class Span:
    start: int          # inclusive byte offset
    end: int            # exclusive byte offset
    label: str          # human-readable description
    kind: str           # 'header' | 'strt' | 'sample' | 'footer' | 'unknown'
 def _tile(known: List[Span], total: int) -> List[Span]:
    """Sort *known* spans and fill every gap with an ``unknown`` span, so the
    result is a contiguous, non-overlapping tiling of ``[0, total)``.  Overlaps
    are resolved by clamping to the running position (first writer wins)."""
    out: List[Span] = []
    pos = 0
    for s in sorted(known, key=lambda x: (x.start, x.end)):
        if s.end <= pos:
            continue                       # fully behind — dropped overlap
        start = max(s.start, pos)
        if start > pos:
            out.append(Span(pos, start, "unknown", "unknown"))
        out.append(s if start == s.start else Span(start, s.end, s.label, s.kind))
        pos = s.end
    if pos < total:
        out.append(Span(pos, total, "unknown", "unknown"))
    return out
 def annotate_blastware_binary(raw: bytes) -> List[Span]:
    """Annotate a Series-3 waveform binary into a gap-free list of spans."""
    total = len(raw)
    strt_pos = raw.find(b"STRT")
    if strt_pos < 0:
        return [Span(0, total, "unrecognized — no STRT record", "unknown")]
    known: List[Span] = []
    if strt_pos > 0:
        known.append(Span(0, strt_pos, "File header", "header"))
    known.append(Span(strt_pos, strt_pos + _STRT_LEN, "STRT record", "strt"))
    body_start = strt_pos + _STRT_LEN
    footer_start = total - _FOOTER_LEN
    if footer_start >= body_start:
        known.append(Span(footer_start, total, "File footer", "footer"))
    else:
        footer_start = total          # file too short for a footer
    body = raw[body_start:footer_start]
    for rec in walk_records(body):
        hi, lo = rec["mode"]
        label = f"{rec['channel']} record (seg {rec['segment_index']}, mode {hi:02x} {lo:02x})"
        known.append(Span(body_start + rec["offset"], body_start + rec["end"], label, "sample"))
    return _tile(known, total)
@@ -50,7 +50,7 @@ SIDECAR_KIND   = "sfm.event"
 # bumped without a `pip install` re-run — leading to confusing stale
 # version stamps in sidecars.  Bump this constant and CHANGELOG.md
 # together at release time.
-TOOL_VERSION = "0.29.0"
+TOOL_VERSION = "0.30.0"
 try:
    # Best-effort: prefer the installed metadata when it's NEWER than the
@@ -0,0 +1,146 @@
 r"""Decode the Blastware sensor self-check waveforms from a series-3 event binary.
 Reverse-engineered 2026-09-15 against 7 BE12844 (MiniMate Plus) oracle events.
 After the main waveform record-chain and the trailing metadata / per-channel
 calibration records, the binary carries four length-prefixed records tagged
 0x3c-0x3f: the sensor self-check traces the unit records when it pulses each
 sensor before monitoring.  Blastware draws these as the little waveforms in the
 "Sensor Check" strip on the right of the Event Report.
  * 0x3c / 0x3d / 0x3e = Tran / Vert / Long geophone ring-downs (a damped
    oscillation at the geophone's resonance, ~7-8 Hz at 1024 sps).
  * 0x3f            = MicL, a pulse train at the mic self-test frequency
    (~20 Hz), whose zero-crossing frequency is BW's mic "Channel Test" freq.
 Record framing (per record, all four chained by their length prefix)::
    [len:2 BE][id:1][00 00][Nchan:1][12-byte header][delta stream][40 02][6B]
    \_________________ payload (len bytes) _______________________________/
 The delta stream is ``payload[20 : len-8]`` (the ``40 02`` terminator sits at
 ``len-8``, followed by 6 trailing bytes).  It uses the exact same 10/20/30/00
 delta-block tags as the main waveform codec
 (:mod:`minimateplus.waveform_codec`), decoded here from an implicit anchor of 0
 — so the traces come out in the same 16-count raw units as the main waveform
 (LSB = 0.005 in/s at Normal range for the geophones).
 """
 from __future__ import annotations
 from typing import Dict, List
 from minimateplus.waveform_codec import walk_body
 # Record id → channel.  Order mirrors the trailing per-channel calibration
 # records (Tran / Vert / Long / MicL), confirmed against BW's sensor-check
 # frequencies on all 7 oracle events.
 _ID_TO_CHANNEL = {0x3C: "Tran", 0x3D: "Vert", 0x3E: "Long", 0x3F: "MicL"}
 _CHAIN_IDS = (0x3C, 0x3D, 0x3E, 0x3F)
 _HEADER_LEN = 20    # payload bytes before the delta stream
 _TRAILER_LEN = 8    # 40 02 terminator + 6 trailing bytes after the stream
 def _s4(nib: int) -> int:
    """Sign-extend a 4-bit nibble delta."""
    return nib - 16 if nib >= 8 else nib
 def _i8(byte: int) -> int:
    """Sign-extend an 8-bit int delta."""
    return byte - 256 if byte >= 128 else byte
 def _decode_delta_stream(buf: bytes) -> List[int]:
    """Accumulate a 10/20/30/00 delta-block stream from an anchor of 0,
    stopping at the 0x40 terminator.
    Mirrors the block semantics in
    :func:`minimateplus.waveform_codec.decode_waveform_v2` (fully decoded &
    byte-exact as of 2026-05-11); see that module for the format details.
    """
    out: List[int] = []
    cur = 0
    for blk in walk_body(buf, 0):
        fam = blk.tag_hi & 0xF0
        if fam == 0x10:
            # nibble deltas, high nibble first
            for byte in blk.data:
                for nib in ((byte >> 4) & 0xF, byte & 0xF):
                    cur += _s4(nib)
                    out.append(cur)
        elif fam == 0x20:
            # int8 deltas
            for byte in blk.data:
                cur += _i8(byte)
                out.append(cur)
        elif fam == 0x30:
            # 12-bit signed deltas, packed as tag_lo/4 groups of 6 bytes
            for g in range(blk.tag_lo // 4):
                grp = blk.data[g * 6:(g + 1) * 6]
                if len(grp) < 6:
                    break
                high_word = (grp[0] << 8) | grp[1]
                for k in range(4):
                    nib = (high_word >> (12 - 4 * k)) & 0xF
                    v = (nib << 8) | grp[2 + k]
                    if v >= 0x800:
                        v -= 0x1000
                    cur += v
                    out.append(cur)
        elif fam == 0x00:
            # RLE zero-delta run (wide form carries the high nibble in the tag)
            run = ((blk.tag_hi & 0x0F) << 8) | blk.tag_lo
            out.extend([cur] * run)
        elif fam == 0x40:
            # segment / record terminator
            break
    return out
 def _find_chain(body: bytes):
    """Locate the four length-prefixed sensor-check records.
    Returns a list of ``(offset, id, length)`` or ``None``.  The chain is
    validated by walking the ids 0x3c → 0x3d → 0x3e → 0x3f via their own length
    prefixes, so a stray 0x3c byte in the waveform data cannot match.
    """
    for p in range(len(body) - 6):
        if body[p + 2] == 0x3C and body[p + 3] == 0 and body[p + 4] == 0:
            q = p
            recs = []
            ok = True
            for expect in _CHAIN_IDS:
                if q + 3 > len(body) or body[q + 2] != expect:
                    ok = False
                    break
                length = int.from_bytes(body[q:q + 2], "big")
                recs.append((q, expect, length))
                q = q + 2 + length
            if ok and len(recs) == 4:
                return recs
    return None
 def decode_sensor_check(raw: bytes) -> Dict[str, List[int]]:
    """Decode the four sensor self-check traces from a series-3 event binary.
    Returns ``{"Tran": [...], "Vert": [...], "Long": [...], "MicL": [...]}`` in
    raw decode units (same 16-count LSB as the main waveform), or ``{}`` if the
    binary carries no sensor-check block (a histogram event, a non-series-3
    file, or a unit/firmware that doesn't store it).
    """
    strt = raw.find(b"STRT")
    if strt < 0 or len(raw) < strt + 21 + 26:
        return {}
    body = raw[strt + 21: len(raw) - 26]
    chain = _find_chain(body)
    if not chain:
        return {}
    out: Dict[str, List[int]] = {}
    for off, rid, length in chain:
        payload = body[off + 2: off + 2 + length]
        if len(payload) < _HEADER_LEN + _TRAILER_LEN:
            continue
        stream = payload[_HEADER_LEN: length - _TRAILER_LEN]
        out[_ID_TO_CHANNEL[rid]] = _decode_delta_stream(stream)
    return out
@@ -722,7 +722,18 @@ STREAM_END_ID = 0x06
 MODE_DELTA    = (0x02, 0x00)
 MODE_ABSOLUTE = (0x01, 0x00)
 MODE_RAW12    = (0x00, 0x03)
-_MODES = (MODE_DELTA, MODE_ABSOLUTE, MODE_RAW12)
+# Raw int16 BE absolute samples, 10-byte header, no tags — the same shape as
 # MODE_RAW12 but two bytes per sample instead of 1.5.  Found on Thor/Micromate
 # segment-0 records (2026-09-10): a `len=1032` record carries exactly
 # (1032 - 8) / 2 = 512 samples and reproduces Thor's own export 512/512
 # exactly.  Before this mode existed the record fell through the dispatch
 # unhandled, so the channel silently lost its first 512 samples.
 MODE_RAW16    = (0x00, 0x00)
 _MODES = (MODE_DELTA, MODE_ABSOLUTE, MODE_RAW12, MODE_RAW16)
 # Preambles whose leading data is untagged and therefore cannot be
 # block-walked; find_first_record() must scan for the next record instead.
 _UNTAGGED_MODES = (MODE_RAW12, MODE_RAW16)
 def _u16(b: bytes, p: int) -> int:
@@ -747,7 +758,18 @@ def data_block_len(body: bytes, p: int) -> Tuple[Optional[int], Optional[int]]:
    hi = t0 & 0xF0
    nn = ((t0 & 0x0F) << 8) | t1
    if hi == 0x40:                          # int16 BE data block
-        return (None, None) if (nn == 0 or nn > 0x08) else (2 * nn + 2, nn)
+        # NN was capped at 0x08 until 2026-09-11.  That cap had no basis: the
        # two corpora available at the time only ever used NN in {1,2,3,4,8},
        # so it was never exercised.  Loud UM12947 events use NN of 12, 16,
        # 20 ... up to 196, and every value above 8 halted the walk, which
        # surfaced as silently short channels (walk_body/run stop at the first
        # unrecognised tag rather than raising).  Verified against Thor's own
        # exports: 22 length-mismatched files -> 0, and the affected corpus
        # went to 1,476,242/1,476,249 samples exact.  The real bound is the
        # buffer; the caller additionally clamps to the record end.
        if nn == 0 or p + 2 * nn + 2 > len(body):
            return None, None
        return 2 * nn + 2, nn
    if nn == 0 or nn % 4:
        return None, None
    if hi == 0x00:
@@ -761,6 +783,11 @@ def data_block_len(body: bytes, p: int) -> Tuple[Optional[int], Optional[int]]:
    return None, None
 def unpack16(data: bytes) -> List[int]:
    """Raw int16 BE absolute samples (MODE_RAW16)."""
    return [_i16(data, 2 * k) for k in range(len(data) // 2)]
 def unpack12(data: bytes) -> List[int]:
    """Raw 12-bit packed samples: 6 bytes -> 4 signed values."""
    out: List[int] = []
@@ -785,13 +812,17 @@ def find_first_record(body: bytes) -> Optional[int]:
    """Offset of the first record, or None.
    Under the normal ``00 02 00`` preamble the leading bytes are segment-0's
-    Tran blocks, so walk them.  Under the ``00 00 03`` preamble that data is
+    Tran blocks, so walk them.  Under the untagged preambles (``00 00 03``
-    raw 12-bit with no tags at all and cannot be block-walked — scan instead.
+    raw-12 and ``00 00 00`` raw-16) that data has no tags at all and cannot
    be block-walked — scan for the next record header instead.
    """
-    if len(body) >= 3 and (body[1], body[2]) == MODE_RAW12:
+    if len(body) >= 3 and (body[1], body[2]) in _UNTAGGED_MODES:
        scan_from = 3
    else:
-        i = 7
+        # Tagged preamble.  MODE_DELTA carries a 14-byte record header (two
        # int16 anchors), so its blocks start at body[7]; MODE_ABSOLUTE has a
        # 10-byte header and starts at body[3].
        i = 3 if (len(body) >= 3 and (body[1], body[2]) == MODE_ABSOLUTE) else 7
        while i < len(body):
            if is_record(body, i):
                nxt = i + 2 + _u16(body, i + 2)
@@ -850,7 +881,7 @@ def decode_waveform_v2(body: bytes) -> Optional[dict]:
    if len(body) < 8 or body[0] != 0x00:
        return None
    preamble = (body[1], body[2])
-    if preamble not in (MODE_DELTA, MODE_RAW12):
+    if preamble not in (MODE_DELTA, MODE_ABSOLUTE, MODE_RAW12, MODE_RAW16):
        return None
    first = find_first_record(body)
    if first is None:
@@ -895,6 +926,10 @@ def decode_waveform_v2(body: bytes) -> Optional[dict]:
    if preamble == MODE_DELTA:
        out["Tran"].extend([_i16(body, 3), _i16(body, 5)])
        run("Tran", 7, first, absolute=False)
    elif preamble == MODE_ABSOLUTE:
        run("Tran", 3, first, absolute=True)
    elif preamble == MODE_RAW16:
        out["Tran"].extend(unpack16(body[3:first]))
    else:
        out["Tran"].extend(unpack12(body[3:first]))
@@ -908,4 +943,6 @@ def decode_waveform_v2(body: bytes) -> Optional[dict]:
            run(ch, off + 10, end, absolute=True)
        elif mode == MODE_RAW12:
            out[ch].extend(unpack12(body[off + 10:end]))
        elif mode == MODE_RAW16:
            out[ch].extend(unpack16(body[off + 10:end]))
    return out
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 [project]
 name = "seismo-relay"
-version = "0.29.0"
+version = "0.30.0"
 description = "Python client and REST server for MiniMate Plus seismographs"
 requires-python = ">=3.10"
 dependencies = [
@@ -0,0 +1,228 @@
 #!/usr/bin/env python3
 """Verify the Thor / Micromate (series-4) IDF decoder against Thor's own exports.
 Sister harness to ``scratch/verify_against_ascii.py`` (series-3 / Blastware).
 Ground truth is the ``.IDFW.csv`` / ``.IDFH.csv`` file Thor writes next to each
 binary, under a sibling ``CSV/`` directory:
    <dir>/UM13981_20220207084555.IDFW
    <dir>/CSV/UM13981_20220207084555.IDFW.csv
 For waveforms the CSV carries a per-sample block of four columns
 (Tran, Vert, Long, Mic) in in/s and psi -- i.e. true per-sample ground truth,
 exactly what the BW ASCII exports give us for series-3.  The leading 2-column
 rows are the report header (PPV, sample rate, geo range, ...).
 Usage:
    python scratch/verify_thor_against_csv.py [--root DIR] [--lsb FLOAT]
                                              [--limit N] [--kind idfw|idfh|both]
 """
 from __future__ import annotations
 import argparse
 import csv
 import os
 import statistics
 import sys
 from collections import Counter, defaultdict
 sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 from micromate import idf_file as M
 DEFAULT_ROOT = "/home/serversdown/thor-watcher/example-data"
 GEO = ("Tran", "Vert", "Long")
 def parse_export(path):
    """Return (header_dict, sample_rows) from a Thor CSV export."""
    hdr, rows = {}, []
    with open(path, newline="", encoding="utf-8", errors="replace") as fh:
        for rec in csv.reader(fh):
            if len(rec) == 2:
                hdr[rec[0].strip()] = rec[1].strip()
            elif len(rec) >= 3:
                try:
                    rows.append([float(x) for x in rec])
                except ValueError:
                    pass
    return hdr, rows
 def index_corpus(root):
    """Map BASENAME.IDFW -> (binary_path, csv_path) for every paired file."""
    exports, binaries = {}, {}
    for dirpath, _dirs, files in os.walk(root):
        for name in files:
            up = name.upper()
            full = os.path.join(dirpath, name)
            if up.endswith(".IDFW.CSV") or up.endswith(".IDFH.CSV"):
                exports.setdefault(name[:-4].upper(), full)
            elif up.endswith(".IDFW") or up.endswith(".IDFH"):
                binaries.setdefault(up, full)
    return {k: (binaries[k], exports[k]) for k in binaries.keys() & exports.keys()}
 def hdr_float(hdr, key):
    raw = hdr.get(key)
    if not raw:
        return None
    try:
        return float(raw.split()[0])
    except (ValueError, IndexError):
        return None
 def verify_waveform(binpath, csvpath, lsb):
    """Compare one IDFW against its export.  Returns a result dict."""
    out = {"file": os.path.basename(binpath), "status": "ok"}
    try:
        res = M.read_idf_file(binpath)
    except NotImplementedError:
        out["status"] = "not-thor"
        return out
    except Exception as exc:  # noqa: BLE001 - harness reports, never raises
        out["status"] = "decode-error"
        out["detail"] = f"{type(exc).__name__}: {exc}"
        return out
    hdr, rows = parse_export(csvpath)
    if not rows:
        out["status"] = "no-gt-samples"
        return out
    gt = {ch: [r[i] for r in rows] for i, ch in enumerate(GEO)}
    out["gt_len"] = len(rows)
    out["geo_range"] = hdr.get("GeoRange")
    exact = total = 0
    lens, chan_status = {}, {}
    ppv_err = {}
    for ch in GEO:
        arr = res.samples.get(ch, [])
        ref = gt[ch]
        lens[ch] = len(arr)
        if len(arr) != len(ref):
            chan_status[ch] = "length"
            continue
        if not arr:
            chan_status[ch] = "empty"
            continue
        hits = sum(1 for c, v in zip(arr, ref) if abs(c * lsb - v) < 5e-5)
        exact += hits
        total += len(arr)
        chan_status[ch] = "exact" if hits == len(arr) else "value"
        gp = hdr_float(hdr, f"{ch}PPV")
        if gp:
            ppv_err[ch] = (max(abs(c) for c in arr) * lsb - gp) / gp
    out["lens"] = lens
    out["chan_status"] = chan_status
    out["exact"] = exact
    out["total"] = total
    out["ppv_err"] = ppv_err
    if all(v == "exact" for v in chan_status.values()):
        out["status"] = "exact"
    elif any(v == "length" for v in chan_status.values()):
        out["status"] = "length-mismatch"
    else:
        out["status"] = "value-mismatch"
    return out
 def verify_histogram(binpath, csvpath, lsb):
    out = {"file": os.path.basename(binpath), "status": "ok"}
    try:
        res = M.read_idf_file(binpath)
    except NotImplementedError:
        out["status"] = "not-thor"
        return out
    except Exception as exc:  # noqa: BLE001
        out["status"] = "decode-error"
        out["detail"] = f"{type(exc).__name__}: {exc}"
        return out
    hdr, _rows = parse_export(csvpath)
    out["n_intervals"] = len(res.intervals or [])
    errs = {}
    for ch, attr in (("Tran", "transverse_ips"), ("Vert", "vertical_ips"),
                     ("Long", "longitudinal_ips")):
        gp = hdr_float(hdr, f"{ch}PPV")
        dv = getattr(res.event.peaks, attr, None)
        if gp and dv:
            errs[ch] = (dv - gp) / gp
    out["ppv_err"] = errs
    out["status"] = "peaks" if errs else "no-gt-peaks"
    return out
 def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--root", default=DEFAULT_ROOT)
    ap.add_argument("--lsb", type=float, default=M._GEO_LSB_IPS)
    ap.add_argument("--limit", type=int, default=0)
    ap.add_argument("--kind", choices=("idfw", "idfh", "both"), default="both")
    ap.add_argument("--show", type=int, default=15, help="worst-N detail rows")
    args = ap.parse_args()
    pairs = index_corpus(args.root)
    keys = sorted(pairs)
    if args.kind != "both":
        keys = [k for k in keys if k.endswith(args.kind.upper())]
    if args.limit:
        keys = keys[: args.limit]
    print(f"root: {args.root}")
    print(f"geo LSB under test: {args.lsb!r} in/s per count")
    print(f"paired files: {len(keys)}\n")
    wf, hg = [], []
    for k in keys:
        binpath, csvpath = pairs[k]
        if k.endswith(".IDFW"):
            wf.append(verify_waveform(binpath, csvpath, args.lsb))
        else:
            hg.append(verify_histogram(binpath, csvpath, args.lsb))
    if wf:
        st = Counter(r["status"] for r in wf)
        ex = sum(r.get("exact", 0) for r in wf)
        tot = sum(r.get("total", 0) for r in wf)
        print("=" * 68)
        print(f"WAVEFORM (IDFW): {len(wf)} files")
        for s, n in st.most_common():
            print(f"    {s:16} {n:5d}  ({100*n/len(wf):5.1f}%)")
        if tot:
            print(f"  per-sample exact: {ex}/{tot} = {100*ex/tot:.3f}%")
        errs = [e for r in wf for e in r.get("ppv_err", {}).values()]
        if errs:
            print(f"  PPV rel-error: median {statistics.median(errs):+.4%}  "
                  f"mean {statistics.mean(errs):+.4%}  "
                  f"max|.| {max(abs(e) for e in errs):.4%}")
        bad = [r for r in wf if r["status"] not in ("exact",)]
        if bad:
            print(f"\n  worst {min(args.show, len(bad))} of {len(bad)} non-exact:")
            for r in bad[: args.show]:
                print(f"    {r['file']:42} {r['status']:16} "
                      f"lens={r.get('lens')} gt={r.get('gt_len')} "
                      f"{r.get('detail','')}")
    if hg:
        st = Counter(r["status"] for r in hg)
        print("=" * 68)
        print(f"HISTOGRAM (IDFH): {len(hg)} files")
        for s, n in st.most_common():
            print(f"    {s:16} {n:5d}  ({100*n/len(hg):5.1f}%)")
        errs = [e for r in hg for e in r.get("ppv_err", {}).values()]
        if errs:
            print(f"  PPV rel-error: median {statistics.median(errs):+.4%}  "
                  f"mean {statistics.mean(errs):+.4%}  "
                  f"max|.| {max(abs(e) for e in errs):.4%}")
            within = lambda t: 100*sum(1 for e in errs if abs(e) <= t)/len(errs)
            print(f"  within 0.5%: {within(0.005):.1f}%   "
                  f"within 2%: {within(0.02):.1f}%   within 5%: {within(0.05):.1f}%")
    return 0
 if __name__ == "__main__":
    raise SystemExit(main())
@@ -54,6 +54,7 @@ from s3_analyzer import (  # noqa: E402
    write_claude_export,
 )
 from frame_db import FrameDB  # noqa: E402
 from minimateplus.binary_annotate import annotate_blastware_binary  # noqa: E402
 # ── colour palette ────────────────────────────────────────────────────────────
 BG       = "#1e1e1e"
@@ -2675,6 +2676,95 @@ class DownloadPanel(tk.Frame):
        self._on_capture_ready(bw_path, s3_path, label)
 # ─────────────────────────────────────────────────────────────────────────────
 # Inspector panel — annotated hex view of a Series-3 binary
 # ─────────────────────────────────────────────────────────────────────────────
 class InspectorPanel(tk.Frame):
    """Load any Series-3 waveform binary and read it as an annotated hex dump.
    Regions the decoder understands (header, STRT, per-channel sample records,
    footer) are labelled and colour-coded; everything the decoder cannot account
    for is flagged UNKNOWN, so undecoded bytes stand out for hand-inspection.
    """
    _KIND_COLOR = {
        "header":  ACCENT,
        "strt":    YELLOW,
        "sample":  COL_S3,
        "footer":  FG_DIM,
        "unknown": RED,
    }
    def __init__(self, parent: tk.Widget, initialdir=None, **kw) -> None:
        super().__init__(parent, bg=BG, **kw)
        self._path = None
        self._initialdir = initialdir
        self._build()
    def _build(self) -> None:
        bar = tk.Frame(self, bg=BG2)
        bar.pack(side=tk.TOP, fill=tk.X)
        tk.Button(bar, text="Open binary…", command=self._open, bg=BG3, fg=FG,
                  relief=tk.FLAT, font=MONO, activebackground=ACCENT).pack(side=tk.LEFT, padx=6, pady=6)
        self._path_var = tk.StringVar(value="(no file loaded)")
        tk.Label(bar, textvariable=self._path_var, bg=BG2, fg=FG_DIM, font=MONO).pack(side=tk.LEFT, padx=6)
        self._summary_var = tk.StringVar(value="")
        tk.Label(bar, textvariable=self._summary_var, bg=BG2, fg=FG, font=MONO).pack(side=tk.RIGHT, padx=10)
        legend = tk.Frame(self, bg=BG2)
        legend.pack(side=tk.TOP, fill=tk.X)
        tk.Label(legend, text="legend:", bg=BG2, fg=FG_DIM, font=MONO).pack(side=tk.LEFT, padx=(8, 2))
        for kind, color in self._KIND_COLOR.items():
            tk.Label(legend, text=f"■ {kind}", bg=BG2, fg=color, font=MONO).pack(side=tk.LEFT, padx=5, pady=2)
        self._text = scrolledtext.ScrolledText(
            self, bg=BG, fg=FG, insertbackground=FG, font=MONO, wrap=tk.NONE, borderwidth=0)
        self._text.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
        for kind, color in self._KIND_COLOR.items():
            self._text.tag_configure(kind, foreground=color)
        self._text.tag_configure("label", foreground="#ffffff", font=("Consolas", 9, "bold"))
        self._text.tag_configure("dim", foreground=FG_DIM)
        self._text.configure(state=tk.DISABLED)
    def _open(self) -> None:
        p = filedialog.askopenfilename(title="Open a Series-3 binary", initialdir=self._initialdir)
        if p:
            self.load(Path(p))
    def load(self, path: Path) -> None:
        try:
            raw = path.read_bytes()
            spans = annotate_blastware_binary(raw)
        except Exception as e:  # noqa: BLE001 — surface any read/annotate failure to the user
            messagebox.showerror("Inspector", f"Failed to read/annotate:\n{path}\n\n{e}")
            return
        self._path = path
        self._path_var.set(str(path))
        self._render(raw, spans)
    def _render(self, raw: bytes, spans) -> None:
        t = self._text
        t.configure(state=tk.NORMAL)
        t.delete("1.0", tk.END)
        unknown = sum(s.end - s.start for s in spans if s.kind == "unknown")
        pct = 100 * unknown / max(1, len(raw))
        self._summary_var.set(f"{len(raw)} B · {len(spans)} regions · {pct:.1f}% unknown")
        for s in spans:
            t.insert(tk.END, f"\n── {s.label}  [0x{s.start:04x}:0x{s.end:04x}]  {s.end - s.start} B ──\n", ("label",))
            self._insert_hex(t, raw, s.start, s.end, s.kind)
        t.configure(state=tk.DISABLED)
    def _insert_hex(self, t: tk.Text, raw: bytes, start: int, end: int, kind: str) -> None:
        for off in range(start, end, 16):
            row = raw[off:min(off + 16, end)]
            hx = " ".join(f"{b:02x}" for b in row).ljust(16 * 3 - 1)
            txt = "".join(chr(b) if 32 <= b < 127 else "." for b in row)
            t.insert(tk.END, f"  0x{off:04x}  ", ("dim",))
            t.insert(tk.END, hx, (kind,))
            t.insert(tk.END, f"  {txt}\n", ("dim",))
 # ─────────────────────────────────────────────────────────────────────────────
 # Main application window
 # ─────────────────────────────────────────────────────────────────────────────
@@ -2730,6 +2820,9 @@ class SeismoLab(tk.Tk):
        )
        nb.add(self._download_panel, text="  Download  ")
        self._inspector_panel = InspectorPanel(nb)
        nb.add(self._inspector_panel, text="  Inspector  ")
        self._nb = nb
        self.protocol("WM_DELETE_WINDOW", self._on_close)
@@ -0,0 +1,133 @@
 """USBM RI8507 / OSMRE blasting compliance chart.
 Renders the velocity-vs-frequency compliance scatter Blastware draws on its Event
 Report: each channel's significant waveform cycles as ``(frequency, peak
 velocity)`` points on log-log axes against the regulatory limit curve(s). A point
 below the curve passes; above fails.
 Two pieces, kept separate so both can be reused/extended:
  * ``limit_at`` / ``limit_curve`` — the regulatory limit curve(s), as data.
  * ``channel_compliance_points`` — the per-cycle (freq, velocity) scatter, by
    the zero-crossing method (matches Blastware: each channel's cloud tops out
    at that channel's PPV).
 Limit curves (USBM RI8507 Figure B-1 / OSM 30 CFR 816.67), drawn CONTINUOUS — a
 constant-displacement bound (sloped, ``v = 2πf·d``) meets a constant-velocity
 plateau at the frequency where they're equal, so there are no vertical steps
 (matching how Blastware draws it). Two lines:
  * **Drywall** (modern gypsum board) — 0.75 in/s plateau (solid).
  * **Plaster** on wood lath (older homes) — 0.50 in/s plateau (dashed).
 Both use a 0.030 in low-frequency displacement bound and rise through a 0.010 in
 displacement bound to a 2.0 in/s high-frequency plateau. Values from USBM RI8507
 (Appendix B) / 30 CFR 816.67; ⚠ confirm the exact shape against a Blastware
 report before trusting for compliance.
 """
 from __future__ import annotations
 import math
 from typing import Dict, Sequence, Tuple
 import numpy as np
 from matplotlib.ticker import FixedLocator, NullLocator
 # curve name → (low-freq "ultimate" displacement in, mid velocity plateau in/s,
 #               high-freq displacement in, high-freq velocity plateau in/s).
 # RI8507 Fig B-1 (p.74): ultimate max displacement 0.030 in (< ~4 Hz), plateau
 # 0.75 (Drywall) / 0.50 (plaster), rising diagonal at 0.008 in displacement up to
 # a 2.0 in/s plateau reached at ~40 Hz.
 _CURVES: Dict[str, Tuple[float, float, float, float]] = {
    "Drywall": (0.030, 0.75, 0.008, 2.00),
    "Plaster": (0.030, 0.50, 0.008, 2.00),
 }
 # how each curve is stroked on the chart
 _CURVE_STYLE = {"Drywall": {"ls": "-", "lw": 1.0}, "Plaster": {"ls": "--", "lw": 0.9}}
 STANDARDS = tuple(_CURVES)
 # Blastware's channel markers/colours on the compliance chart.
 _CHANNEL_STYLE = {
    "Tran": ("+", "#d62728"),   # red +
    "Vert": ("x", "#2ca02c"),   # green x
    "Long": ("o", "#1f77b4"),   # blue o
 }
 def limit_at(freq_hz: float, curve: str = "Drywall") -> float:
    """Max allowed PPV (in/s) at ``freq_hz`` for ``curve`` (continuous)."""
    d_low, v_mid, d_high, v_high = _CURVES[curve]
    f = max(freq_hz, 1.0)
    f_a = v_mid / (2.0 * math.pi * d_low)    # disp_low → vel_mid
    f_b = v_mid / (2.0 * math.pi * d_high)   # vel_mid → disp_high
    f_c = v_high / (2.0 * math.pi * d_high)  # disp_high → vel_high
    if f <= f_a:
        return 2.0 * math.pi * f * d_low
    if f <= f_b:
        return v_mid
    if f <= f_c:
        return 2.0 * math.pi * f * d_high
    return v_high
 def limit_curve(curve: str = "Drywall", fmin: float = 1.0, fmax: float = 100.0, n: int = 400):
    """(freqs, limits) sampled across the band for plotting one curve."""
    freqs = np.logspace(np.log10(fmin), np.log10(fmax), n)
    return freqs, np.array([limit_at(f, curve) for f in freqs])
 def channel_compliance_points(
    samples: Sequence[float], sps: float, fmin: float = 1.0, fmax: float = 100.0,
    vmin: float = 0.0,
 ) -> Tuple[np.ndarray, np.ndarray]:
    """Per-cycle (frequency, peak velocity) scatter for one channel.
    Zero-crossing method: split the trace at sign changes; each half-cycle
    contributes one point at ``(1/(2·half_period), max|amplitude|)``. Matches
    Blastware — the cloud's ceiling is the channel PPV. ``samples`` must be in the
    velocity unit you want plotted (in/s). Points outside ``[fmin, fmax]`` or at
    or below ``vmin`` are dropped.
    """
    x = np.asarray(samples, dtype=float)
    if x.size < 3:
        return np.empty(0), np.empty(0)
    zc = np.where(np.diff(np.signbit(x)))[0]
    freqs, vels = [], []
    for a, b in zip(zc[:-1], zc[1:]):
        half_period = (b - a) / sps
        if half_period <= 0:
            continue
        freqs.append(1.0 / (2.0 * half_period))
        vels.append(float(np.abs(x[a:b + 1]).max()))
    f = np.array(freqs)
    v = np.array(vels)
    keep = (f >= fmin) & (f <= fmax) & (v > vmin)
    return f[keep], v[keep]
 def draw_compliance_chart(ax, channels: Dict[str, Sequence[float]], sps: float) -> None:
    """Draw the compliance chart (both limit curves + per-channel scatter)."""
    for name, style in _CURVE_STYLE.items():
        cf, cv = limit_curve(name)
        ax.plot(cf, cv, color="#333", zorder=3, **style)
    for ch, (marker, color) in _CHANNEL_STYLE.items():
        samples = channels.get(ch)
        if samples is None or len(samples) == 0:
            continue
        f, v = channel_compliance_points(samples, sps)
        ax.scatter(f, v, marker=marker, s=12, c=color, linewidths=0.7, zorder=4, label=ch)
    ax.set_xscale("log")
    ax.set_yscale("log")
    ax.set_xlim(1, 100)
    ax.set_ylim(0.0394, 10)
    ax.set_box_aspect(1)   # square plot box (log-log compliance charts are square)
    xt = [1, 2, 5, 10, 20, 50, 100]
    yt = [0.0394, 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10]
    ax.xaxis.set_major_locator(FixedLocator(xt)); ax.xaxis.set_minor_locator(NullLocator())
    ax.yaxis.set_major_locator(FixedLocator(yt)); ax.yaxis.set_minor_locator(NullLocator())
    ax.set_xticklabels([str(v) for v in xt])
    ax.set_yticklabels([("%g" % v) for v in yt])
    ax.set_xlabel("Frequency (Hz)", fontsize=7)
    ax.set_ylabel("Velocity (in/s)", fontsize=7)
    ax.tick_params(labelsize=6)
    ax.grid(True, which="both", ls=":", lw=0.4, color="#ccc")
@@ -121,6 +121,11 @@ class ReportData:
    t0_ms:                  Optional[float] = None
    dt_ms:                  Optional[float] = None
    # Sensor self-check traces — {ch: [samples]} in raw decode units, decoded
    # from the binary's trailing block (see minimateplus.sensor_check). The
    # little waveforms BW draws in its "Sensor Check" strip. Empty when absent.
    sensor_check_waveforms: dict = field(default_factory=dict)
    # Record-type discriminator
    record_type:            Optional[str] = None
    is_histogram:           bool = False
@@ -246,6 +251,8 @@ def gather_report_data(
                "peak_accel_g":       ch.get("peak_accel_g"),
                "peak_disp_in":       ch.get("peak_disp_in"),
                "sensor_check":       sc_ch.get("result"),
                "sc_freq_hz":         sc_ch.get("freq_hz"),
                "sc_ratio":           sc_ch.get("ratio"),
                "peak_date":          peak_date,
                "peak_time":          peak_time,
            })
@@ -290,6 +297,19 @@ def gather_report_data(
        except Exception as exc:
            log.warning("gather_report_data: hdf5 read failed: %s", exc)
    # ── Sensor self-check traces — decoded from the retained raw binary ──
    # The .h5 holds only the main waveform; the sensor-check traces live in the
    # binary's trailing block, so decode them straight from the kept BW file.
    # Waveform events only (histograms have no sensor-check strip).
    if not rd.is_histogram:
        try:
            from minimateplus.sensor_check import decode_sensor_check
            bw_path, _a5 = store.paths_for(serial, filename)
            if bw_path.exists():
                rd.sensor_check_waveforms = decode_sensor_check(bw_path.read_bytes())
        except Exception as exc:
            log.warning("gather_report_data: sensor-check decode failed: %s", exc)
    # ── Histogram aggregation ──
    # Codec emits ~N per-block samples (typically 1/sec); BW reports
    # one bar per configured interval (1 min / 5 min / etc.).  When
@@ -396,9 +416,34 @@ def _render_waveform_layout(fig, rd: ReportData) -> None:
    ax_stats = fig.add_subplot(gs[2]); ax_stats.axis("off")
    _draw_channel_stats_waveform(ax_stats, rd)
    _draw_compliance_panel(fig, rd)
    _draw_waveform_subplot(fig, gs[3], rd)
 # Compliance-chart placement, in figure fractions.  Measured directly off a
 # Blastware Event Report PDF (ref-stuff/n844lqhbzt0w_bw_pdf.pdf) so the chart
 # matches BW's size and position: it spans from just under the header down
 # through the stats band, hard against the right page margin.  The left edge
 # leaves room for the y-axis tick labels + "Velocity (in/s)" title, which the
 # compacted stats table (see _draw_channel_stats_waveform) is sized to clear.
 _COMPLIANCE_BOX = (0.489, 0.502, 0.951, 0.867)   # x0, y0, x1, y1
 def _draw_compliance_panel(fig, rd: ReportData) -> None:
    """Large USBM RI8507 compliance chart in the upper-right, sized and
    positioned to match Blastware's Event Report (see _COMPLIANCE_BOX)."""
    x0, y0, x1, y1 = _COMPLIANCE_BOX
    fig.text((x0 + x1) / 2, y1 + 0.006, "USBM RI8507 And OSMRE", fontsize=9,
             weight="bold", color="#333", ha="center", va="bottom")
    if rd.channels and rd.sample_rate_sps:
        from sfm.compliance import draw_compliance_chart
        ax = fig.add_axes([x0, y0, x1 - x0, y1 - y0])
        draw_compliance_chart(ax, rd.channels, rd.sample_rate_sps)
    else:
        fig.text((x0 + x1) / 2, (y0 + y1) / 2, "(no waveform data)", fontsize=8,
                 color="#bbb", ha="center", va="center", style="italic")
 def _render_histogram_layout(fig, rd: ReportData) -> None:
    """Histogram layout: header / mic-only / per-channel stats / bar plot.
@@ -477,11 +522,11 @@ def _split_iso_to_date_time(iso: Optional[str]) -> tuple[Optional[str], Optional
        return (None, None)
-def _kv(ax, x, y, label, value, *, label_w=0.18):
+def _kv(ax, x, y, label, value, *, label_w=0.18, fontsize=8):
    """Render a 'Label  Value' row at axes-coordinates (x, y)."""
-    ax.text(x, y, label, fontsize=8, color="#555", ha="left", va="top",
+    ax.text(x, y, label, fontsize=fontsize, color="#555", ha="left", va="top",
            transform=ax.transAxes)
-    ax.text(x + label_w, y, _fmt(value), fontsize=8, ha="left", va="top",
+    ax.text(x + label_w, y, _fmt(value), fontsize=fontsize, ha="left", va="top",
            transform=ax.transAxes, family="monospace")
@@ -544,14 +589,17 @@ def _draw_header_columns(ax, rows_left, rd: ReportData) -> None:
        ("File Name", rd.file_name),
        ("Post Event Notes", rd.post_event_notes),
    ]
    # fontsize 7.5 (BW's header is a touch smaller than our body text) + a
    # tighter right-column value indent so the long serial+firmware line
    # ("BE##### V ##.##-#.## MiniMate Plus") fits without running off the page.
    y = 0.95
    dy = 0.095
    for label, value in rows_left:
-        _kv(ax, 0.0, y, label, value, label_w=0.18)
+        _kv(ax, 0.0, y, label, value, label_w=0.18, fontsize=7.5)
        y -= dy
    y = 0.95
    for label, value in rows_right:
-        _kv(ax, 0.55, y, label, value, label_w=0.20)
+        _kv(ax, 0.55, y, label, value, label_w=0.14, fontsize=7.5)
        y -= dy
@@ -574,19 +622,14 @@ def _draw_mic_and_usbm(ax, rd: ReportData) -> None:
            transform=ax.transAxes, va="top")
    rows = _mic_rows(rd)
    y = 0.80
    # Tighter label indent + slightly smaller font so the long "Channel Test
    # Passed (Freq = … Amp = … mv)" line clears the enlarged compliance chart's
    # left edge (_COMPLIANCE_BOX) instead of running behind it.
    for label, value in rows:
-        _kv(ax, 0.0, y, label, value, label_w=0.18)
+        _kv(ax, 0.0, y, label, value, label_w=0.13, fontsize=7)
        y -= 0.15
-
+    # The USBM compliance chart is drawn as its own large square panel spanning
-    # USBM chart placeholder — upper-right.  Real piecewise compliance
+    # the mic + stats rows on the right — see _draw_compliance_panel().
    # curves are a separate work item; for now this just shows the title
    # + a "see report" message so the layout is correct.
    ax.text(0.72, 0.97, "USBM RI8507 And OSMRE",
            fontsize=9, weight="bold", color="#333", ha="center", va="top",
            transform=ax.transAxes)
    ax.text(0.72, 0.50, "[compliance chart\ncoming soon]",
            fontsize=8, color="#bbb", ha="center", va="center",
            transform=ax.transAxes, style="italic")
 def _mic_rows(rd: ReportData) -> list[tuple[str, Optional[str]]]:
@@ -636,8 +679,18 @@ def _draw_channel_stats_waveform(ax, rd: ReportData) -> None:
        ("Peak Acceleration",    "peak_accel_g",   "g"),
        ("Peak Displacement",    "peak_disp_in",   "in"),
        ("Sensor Check",         "sensor_check",   ""),
        # Sensor-check sub-rows (indented under "Sensor Check", like BW): the
        # geophone ring-down frequency + overswing ratio from the self-check.
        ("  Frequency",          "sc_freq_hz",     "Hz"),
        ("  Overswing Ratio",    "sc_ratio",       ""),
    ]
-    _draw_stats_table(ax, rd, rows_spec)
+    # Compacted to the left half so the enlarged compliance chart (BW-sized,
    # right against the page margin) has room — see _COMPLIANCE_BOX.
    _draw_stats_table(
        ax, rd, rows_spec,
        bbox_width=0.42, fontsize=7.5,
        col_widths=[0.185, 0.065, 0.065, 0.065, 0.040],
    )
    _draw_pvs_summary(ax, rd, n_data_rows=len(rows_spec))
@@ -698,19 +751,39 @@ def _draw_pvs_summary(
    table_bottom_y = getattr(ax, "_stats_table_bottom", -0.10)
    pvs_y = table_bottom_y - 0.04   # small gap below the table border
-    # Centered for visual balance — looks intentional rather than offset.
+    # Centered under the stats table for visual balance — looks intentional
-    # The original BW-replica had a "NA: Not Applicable" caption below
+    # rather than offset.  When the table is compacted (waveform layout), it
-    # this line; dropped because we use "—" for missing values and the
+    # occupies only the left portion of the axes, so center on the table's
-    # legend was always squished against the PVS line.
+    # width rather than the full axes (which would push the line under the
-    ax.text(0.5, pvs_y, line, fontsize=9, weight="bold",
+    # compliance chart).  The original BW-replica had a "NA: Not Applicable"
-            ha="center", va="top", transform=ax.transAxes)
+    # caption below this line; dropped because we use "—" for missing values.
    table_w = getattr(ax, "_stats_table_width", 0.80)
    if table_w < 0.79:
        # Compacted (waveform) layout: left-align under the table, one point
        # smaller, so the line clears the enlarged compliance chart's
        # bottom-left tick labels on the right.
        ax.text(0.0, pvs_y, line, fontsize=8, weight="bold",
                ha="left", va="top", transform=ax.transAxes)
    else:
        ax.text(0.5, pvs_y, line, fontsize=9, weight="bold",
                ha="center", va="top", transform=ax.transAxes)
-def _draw_stats_table(ax, rd: ReportData, rows_spec: list[tuple[str, str, str]]) -> None:
+def _draw_stats_table(
    ax, rd: ReportData, rows_spec: list[tuple[str, str, str]],
    *, bbox_width: float = 0.80, fontsize: float = 8,
    col_widths: Optional[list[float]] = None,
 ) -> None:
    """Render a per-channel stats table (Tran/Vert/Long).
    rows_spec: list of (label, field_name_in_channel_stats, unit_string)
    ``bbox_width`` / ``col_widths`` / ``fontsize`` let a caller compact the
    table (the waveform layout packs it into the left half to clear the
    compliance chart; the histogram layout keeps the wider defaults).
    """
    if col_widths is None:
        col_widths = [0.28, 0.14, 0.14, 0.14, 0.10]
    headers = ["", "Tran", "Vert", "Long", ""]
    ch_lookup = {c["name"]: c for c in rd.channel_stats}
@@ -726,6 +799,8 @@ def _draw_stats_table(ax, rd: ReportData, rows_spec: list[tuple[str, str, str]])
            if field == "zc_freq_hz":
                prefix = ">" if ch_rec.get("zc_freq_above_range") else ""
                return f"{prefix}{val:.0f}"
            if field in ("sc_freq_hz", "sc_ratio"):
                return f"{val:.1f}"       # BW shows 1 decimal (7.5 Hz, 3.6)
            return f"{val:.3f}"
        return str(val)
@@ -750,16 +825,17 @@ def _draw_stats_table(ax, rd: ReportData, rows_spec: list[tuple[str, str, str]])
    table_bottom = 1.0 - table_height
    tbl = ax.table(
        cellText=table_data,
-        colWidths=[0.28, 0.14, 0.14, 0.14, 0.10],
+        colWidths=col_widths,
        cellLoc="left", edges="open",
-        bbox=[0.0, table_bottom, 0.80, table_height],
+        bbox=[0.0, table_bottom, bbox_width, table_height],
    )
    tbl.auto_set_font_size(False)
-    tbl.set_fontsize(8)
+    tbl.set_fontsize(fontsize)
    for j in range(5):
        tbl[(0, j)].set_text_props(weight="bold", color="#555")
-    # Stash the bottom Y so _draw_pvs_summary can position itself below.
+    # Stash the bottom Y + width so _draw_pvs_summary can position itself.
    ax._stats_table_bottom = table_bottom
    ax._stats_table_width = bbox_width
 def _channel_axis_color(ch: str) -> str:
@@ -769,27 +845,59 @@ def _channel_axis_color(ch: str) -> str:
 def _draw_waveform_subplot(fig, gridspec_cell, rd: ReportData) -> None:
    """4-channel stacked waveform plot — Instantel printout order
    (MicL on top, Tran on bottom), shared x-axis in SECONDS, trigger
-    triangle markers at t=0, '0.0' baseline label on right of each."""
+    triangle markers at t=0, '0.0' baseline label on right of each.
-    inner = gridspec_cell.subgridspec(4, 1, hspace=0.0)
+
    When sensor self-check traces are present (rd.sensor_check_waveforms), a
    narrow "Sensor Check" strip of per-channel mini-plots is drawn to the right,
    aligned to the lanes — matching Blastware's Event Report.
    """
    from matplotlib.ticker import MaxNLocator
    order = ["MicL", "Long", "Vert", "Tran"]
    has_sc = bool(rd.sensor_check_waveforms)
    if has_sc:
        # main lanes + a narrow sensor-check strip column, flush against the
        # main panel (BW shares the border — no gap), with the "0.0" baseline
        # labels moved to the right of the strip.  Proportions match BW's
        # Event Report (main ~0.75 / strip ~0.10 of the panel width).
        inner = gridspec_cell.subgridspec(4, 2, width_ratios=[1.0, 0.13],
                                          wspace=0.0, hspace=0.0)
    else:
        inner = gridspec_cell.subgridspec(4, 1, hspace=0.0)
    sr = rd.sample_rate_sps or 1024
    # Convert ms-based time axis to seconds for the x-axis
    dt_s = (rd.dt_ms or (1000.0 / sr)) / 1000.0
    t0_s = (rd.t0_ms if rd.t0_ms is not None else 0.0) / 1000.0
    # Shared geo scale across Long/Vert/Tran (matches the event modal + BW's
    # single amp/div): all three geo lanes use ONE Y scale = the max |sample|
    # across them (padded, floored), so relative amplitudes stay honest instead
    # of each lane auto-zooming to its own peak.  Mic keeps its own (psi) scale.
    GEO_FLOOR_INS = 0.05
    _geo_amax = 0.0
    for _gch in ("Long", "Vert", "Tran"):
        for _x in (rd.channels.get(_gch) or []):
            _a = abs(_x)
            if _a > _geo_amax:
                _geo_amax = _a
    geo_shared = max(_geo_amax * 1.10, GEO_FLOOR_INS)
    main_axes = []
    sc_axes = []
    last_idx = len(order) - 1
    for i, ch in enumerate(order):
-        ax = fig.add_subplot(inner[i])
+        ax = fig.add_subplot(inner[i, 0] if has_sc else inner[i])
        main_axes.append(ax)
        values = rd.channels.get(ch) or []
        times = [t0_s + j * dt_s for j in range(len(values))]
        if values:
            color = _channel_axis_color(ch)
            ax.plot(times, values, color=color, linewidth=0.5)
-            # Symmetric y-axis for geo; zero-anchored for mic.
+            # Geo: one shared symmetric scale (honest relative amplitudes).
            # Mic: symmetric on its own psi scale (different unit).
            if ch != "MicL":
-                amax = max((abs(v) for v in values), default=0.001)
+                ax.set_ylim(-geo_shared, geo_shared)
                ax.set_ylim(-amax * 1.10, amax * 1.10)
            else:
                amax = max((abs(v) for v in values), default=0.001)
                ax.set_ylim(-amax * 1.10, amax * 1.10)
@@ -797,9 +905,12 @@ def _draw_waveform_subplot(fig, gridspec_cell, rd: ReportData) -> None:
        # Channel label on the LEFT (matches BW)
        ax.set_ylabel(ch, fontsize=8, rotation=0, ha="right", va="center",
                      color=_channel_axis_color(ch), weight="bold", labelpad=14)
-        # "0.0" on the RIGHT (BW convention)
+        # "0.0" baseline label on the RIGHT (BW convention).  With the sensor-
-        ax.text(1.005, 0.5, "0.0", transform=ax.transAxes,
+        # check strip attached, it goes to the right of the STRIP (drawn below);
-                fontsize=7, color="#555", va="center", ha="left")
+        # otherwise just outside the main lane.
        if not has_sc:
            ax.text(1.005, 0.5, "0.0", transform=ax.transAxes,
                    fontsize=7, color="#555", va="center", ha="left")
        ax.grid(True, linestyle="--", linewidth=0.3, color="#bbb", alpha=0.6)
        # Vertical dashed trigger line at t=0
@@ -814,23 +925,53 @@ def _draw_waveform_subplot(fig, gridspec_cell, rd: ReportData) -> None:
        else:
            ax.tick_params(axis="x", labelsize=7)
        ax.tick_params(axis="y", labelsize=6)
        # Stacked lanes touch, so the top/bottom y-tick labels of adjacent lanes
        # would overprint at the shared boundary.  Prune the extreme ticks so
        # each boundary shows clean interior ticks (0.5 / 0.0 / -0.5) only.
        ax.yaxis.set_major_locator(MaxNLocator(nbins=4, prune="both"))
        # Sensor self-check mini-plot in the right strip (aligned to this lane).
        if has_sc:
            scx = fig.add_subplot(inner[i, 1])
            sc_axes.append(scx)
            sc_vals = rd.sensor_check_waveforms.get(ch) or []
            if sc_vals:
                _col = _channel_axis_color(ch)
                # Faint zero baseline (BW draws the channel baseline through the
                # strip) — reference for the one-sided geophone ring-downs.
                scx.axhline(0.0, color=_col, linewidth=0.3, alpha=0.4)
                scx.plot(range(len(sc_vals)), sc_vals, color=_col, linewidth=0.5)
                # Fit the trace to the box (BW-style) rather than a symmetric
                # scale: the geo self-checks are one-sided dips, so a symmetric
                # scale would strand them in the bottom half with an empty top.
                _lo, _hi = min(sc_vals), max(sc_vals)
                _pad = 0.10 * ((_hi - _lo) or 1.0)
                scx.set_ylim(_lo - _pad, _hi + _pad)
            scx.set_xticks([]); scx.set_yticks([])
            for _s in scx.spines.values():
                _s.set_linewidth(0.4); _s.set_color("#999")
            # "0.0" baseline label to the RIGHT of the strip (BW convention)
            scx.text(1.10, 0.5, "0.0", transform=scx.transAxes,
                     fontsize=7, color="#555", va="center", ha="left")
    # Trigger triangle marker ▼ above the top channel at t=0
-    top_ax = fig.axes[-4]  # MicL is the first added in this gridspec
+    top_ax = main_axes[0]  # MicL
    top_ax.plot([0], [top_ax.get_ylim()[1]], marker="v", color="black",
                markersize=8, clip_on=False, zorder=10)
    # "Sensor Check" caption under the strip (BW convention)
    if has_sc and sc_axes:
        pos = sc_axes[-1].get_position()
        fig.text((pos.x0 + pos.x1) / 2, pos.y0 - 0.012, "Sensor Check",
                 fontsize=7, color="#555", ha="center", va="top")
    # Compute scale-per-division for the footer (10 divs across the chart)
    # and find peak geo amplitude for the geo amp/div setting.
    total_s = times[-1] - times[0] if values else 0
    div_s = total_s / 10 if total_s > 0 else 0
-    geo_amp_div = "—"
+    # Footer div value reflects the SHARED geo scale (so it's correct for all
-    for ch in ("Tran", "Vert", "Long"):
+    # three lanes, not just whichever one happened to be checked first).
-        v = rd.channels.get(ch) or []
+    geo_amp_div = f"{(geo_shared * 2) / 10:.3f}" if _geo_amax > 0 else "—"
        if v:
            amax = max(abs(x) for x in v)
            geo_amp_div = f"{(amax * 1.1 * 2) / 10:.3f}"
            break
    fig.text(
        0.11, 0.030,
        f"Time(Seconds) {div_s:.2f} sec/div   Amplitude Geo: {geo_amp_div} in/s/div   Mic: 0.001 psi(L)/div",
@@ -595,8 +595,19 @@ class WaveformStore:
                )
        # Binary-derived peaks fill in when the .txt didn't supply them.
-        # They're ~3% low vs the device-authoritative .txt values (residual
+        #
-        # codec drift), so .txt always wins when present.
+        # The old justification for this precedence -- "binary peaks are ~3%
        # low vs the .txt" -- was a decoder bug (geo LSB 0.0003 instead of
        # 0.000310308) and was fixed 2026-09-10; the binary now agrees with
        # Thor's own export per-sample.  The .txt still wins when present
        # because it is what the operator sees in Thor's report.
        #
        # ⚠ One case where the .txt is the *less* accurate of the two:
        # Thor floors displayed histogram PPV at 0.0050 in/s, so on quiet
        # IDFH events the .txt reports 0.0050 while the binary decodes the
        # true ~0.0025.  41.4% of prod IDFH sidecars carry a component PPV
        # larger than their own vector sum because of it.  Left as-is
        # deliberately, so stored peaks keep matching Thor's report.
        if binary_peaks is not None:
            if binary_peaks.transverse_ips and not report_dict.get("tran_ppv"):
                report_dict["tran_ppv"] = binary_peaks.transverse_ips
@@ -0,0 +1,50 @@
 """Structural annotation of a Series-3 Blastware binary (for the seismo_lab
 Binary Inspector). The annotator maps byte ranges to labelled spans; anything
 the decoder can't account for is a first-class ``unknown`` span, so the whole
 file is tiled and the gaps (candidate FFT/spectral data) are visible.
 """
 from pathlib import Path
 from minimateplus.binary_annotate import annotate_blastware_binary, Span
 # A known-good full-3-channel Series-3 waveform binary (the V70 cracking fixture).
 FIXTURE = Path(__file__).parent / "fixtures" / "5-11-26" / "M529LL1L.V70"
 def _raw() -> bytes:
    return FIXTURE.read_bytes()
 def test_spans_tile_the_whole_file():
    raw = _raw()
    spans = annotate_blastware_binary(raw)
    assert spans, "expected at least one span"
    assert spans[0].start == 0
    assert spans[-1].end == len(raw)
    for a, b in zip(spans, spans[1:]):
        assert a.end == b.start, f"gap/overlap between {a!r} and {b!r}"
    for s in spans:
        assert s.start < s.end, f"empty/negative span {s!r}"
 def test_strt_record_is_located():
    raw = _raw()
    spans = annotate_blastware_binary(raw)
    strt = [s for s in spans if s.kind == "strt"]
    assert strt, "expected a STRT region"
    assert raw[strt[0].start : strt[0].start + 4] == b"STRT"
 def test_geo_sample_records_annotated():
    raw = _raw()
    spans = annotate_blastware_binary(raw)
    chans = {s.label.split()[0] for s in spans if s.kind == "sample"}
    # V70 is a full three-geo-channel event.
    assert {"Tran", "Vert", "Long"} <= chans, f"expected geo records, got {chans}"
 def test_footer_is_last():
    raw = _raw()
    spans = annotate_blastware_binary(raw)
    assert spans[-1].kind == "footer"
    assert spans[-1].end - spans[-1].start == 26
@@ -0,0 +1,35 @@
 """USBM/OSMRE compliance curve + scatter logic (sfm.compliance).
 Rendering is verified visually against Blastware reports."""
 import math
 import numpy as np
 from sfm.compliance import limit_at, channel_compliance_points
 def test_osmre_velocity_segments():
    assert abs(limit_at(6.0) - 0.75) < 1e-9      # 3.5–12 Hz flat
    assert abs(limit_at(50.0) - 2.00) < 1e-9     # 30–100 Hz flat
 def test_displacement_segments():
    assert abs(limit_at(2.0) - 2 * math.pi * 2.0 * 0.030) < 1e-9    # low-freq 0.030 in
    assert abs(limit_at(20.0) - 2 * math.pi * 20.0 * 0.008) < 1e-9  # rising diagonal 0.008 in
 def test_limit_clamps_below_1hz():
    assert limit_at(0.1) == limit_at(1.0)
 def test_scatter_ceiling_is_ppv_at_dominant_freq():
    # ~27 Hz blast-like trace whose energy peaks mid-record (inside full cycles,
    # as a real event does): the scatter cloud's ceiling is the trace PPV and the
    # top point sits near the dominant frequency.
    sps, n = 1024.0, 3328
    t = np.arange(n) / sps
    env = np.exp(-((t - 1.5) ** 2) / (2 * 0.3 ** 2))
    x = 0.9 * env * np.sin(2 * np.pi * 27.0 * t)
    f, v = channel_compliance_points(x, sps)
    assert len(f) > 20
    assert v.max() >= 0.99 * np.abs(x).max()
    assert 20.0 < f[int(np.argmax(v))] < 35.0
@@ -0,0 +1,322 @@
 """Per-sample verification of the Thor / Micromate (series-4) IDF binary codec.
 Ground truth is Thor's own CSV export, written next to each binary by the
 Thor desktop application.  For waveforms the export carries a per-sample
 block of four columns (Tran, Vert, Long, Mic) in in/s and psi -- the
 series-4 equivalent of Blastware's ``_ASCII.TXT`` exports.
 The full-corpus harness is ``scratch/verify_thor_against_csv.py``; these
 tests pin the two constants that harness established so they cannot
 regress silently.
 """
 from __future__ import annotations
 import csv
 import os
 import sys
 from pathlib import Path
 import pytest
 sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 from micromate.idf_file import (
    _GEO_LSB_IPS,
    geo_count_to_ips,
    read_idf_file,
 )
 FIXTURES = Path(__file__).parent / "fixtures" / "thor-idf"
 IDFW = FIXTURES / "UM11719_20231219162723.IDFW"
 IDFH = FIXTURES / "UM11719_20231219162648.IDFH"
 GEO_CHANNELS = ("Tran", "Vert", "Long")
 # tests/fixtures/ is gitignored, so a fresh checkout has no sample data.
 # Skip rather than fail, matching test_idf_ascii_report.py.  To populate:
 #
 #   B="<thor-watcher>/example-data/THORDATA_example/THORDATA_example/UPMC Presby"
 #   mkdir -p tests/fixtures/thor-idf
 #   for f in UM11719/UM11719_20231219162723.IDFW \
 #            UM11719/UM11719_20231219162648.IDFH \
 #            UM13981/UM13981_20220207084555.IDFW \
 #            UM13981/UM13981_20220207183102.IDFH \
 #            UM13981/UM13981_20221202063059.IDFH; do
 #     cp "$B/$f" tests/fixtures/thor-idf/
 #     cp "$B/$(dirname $f)/CSV/$(basename $f).csv" tests/fixtures/thor-idf/
 #   done
 pytestmark = pytest.mark.skipif(
    not FIXTURES.is_dir() or not any(FIXTURES.glob("*.IDFW")),
    reason=f"Thor IDF fixtures not present under {FIXTURES}",
 )
 def _parse_export(path: Path):
    """Split a Thor CSV export into (header dict, per-sample rows)."""
    header, rows = {}, []
    with path.open(newline="", encoding="utf-8", errors="replace") as fh:
        for rec in csv.reader(fh):
            if len(rec) == 2:
                header[rec[0].strip()] = rec[1].strip()
            elif len(rec) >= 3:
                try:
                    rows.append([float(x) for x in rec])
                except ValueError:
                    pass
    return header, rows
 def _header_float(header, key):
    return float(header[key].split()[0])
@pytest.fixture(scope="module")
 def idfw_export():
    return _parse_export(IDFW.with_suffix(".IDFW.csv"))
 # ─── The geo scale constant ────────────────────────────────────────────────
 def test_geo_lsb_matches_thor_quantisation():
    """Thor's own export quantises geo samples to this LSB.
    Derived by maximising exact-match count over 1,046,016 paired samples
    (454 channel-events, 2 units); independently corroborated on 8
    production units via their device-reported PPV.  The historical value
    0.0003 read every series-4 geophone sample 3.3% low.
    """
    assert _GEO_LSB_IPS == pytest.approx(0.000310308, rel=1e-6)
 def test_geo_lsb_is_not_the_legacy_value():
    # Guards against a revert to the truncated 0.0003 constant.
    assert abs(_GEO_LSB_IPS - 0.0003) > 1e-6
 # ─── Per-sample fidelity ───────────────────────────────────────────────────
 def test_waveform_channel_lengths_match_export(idfw_export):
    _header, rows = idfw_export
    result = read_idf_file(IDFW)
    for channel in GEO_CHANNELS:
        assert len(result.samples[channel]) == len(rows), (
            f"{channel} truncated: decoded {len(result.samples[channel])} "
            f"samples, export has {len(rows)}"
        )
 def test_waveform_samples_match_export_exactly(idfw_export):
    """Every geo sample must reproduce Thor's exported value to 4 dp."""
    _header, rows = idfw_export
    result = read_idf_file(IDFW)
    for index, channel in enumerate(GEO_CHANNELS):
        decoded = result.samples[channel]
        expected = [row[index] for row in rows]
        mismatches = [
            (i, geo_count_to_ips(c), v)
            for i, (c, v) in enumerate(zip(decoded, expected))
            if abs(geo_count_to_ips(c) - v) >= 5e-5
        ]
        assert not mismatches, (
            f"{channel}: {len(mismatches)} of {len(expected)} samples differ; "
            f"first three {mismatches[:3]}"
        )
 def test_waveform_ppv_matches_export(idfw_export):
    header, _rows = idfw_export
    result = read_idf_file(IDFW)
    for channel, attr in (
        ("Tran", "transverse_ips"),
        ("Vert", "vertical_ips"),
        ("Long", "longitudinal_ips"),
    ):
        decoded = getattr(result.event.peaks, attr)
        assert decoded == pytest.approx(
            _header_float(header, f"{channel}PPV"), abs=5e-5
        ), f"{channel} PPV disagrees with Thor's export"
 # ─── Histogram path shares the same scale ──────────────────────────────────
 def test_histogram_peaks_match_export():
    header, _rows = _parse_export(IDFH.with_suffix(".IDFH.csv"))
    result = read_idf_file(IDFH)
    assert result.intervals, "IDFH decoded no intervals"
    for channel, attr in (
        ("Tran", "transverse_ips"),
        ("Vert", "vertical_ips"),
        ("Long", "longitudinal_ips"),
    ):
        decoded = getattr(result.event.peaks, attr)
        expected = _header_float(header, f"{channel}PPV")
        # Histogram peaks are stored per-interval, so the export's PPV is
        # reproduced within one quantisation step rather than exactly.
        assert decoded == pytest.approx(expected, abs=2 * _GEO_LSB_IPS), (
            f"{channel} histogram peak {decoded} vs export {expected}"
        )
 # ─── Regressions found 2026-09-10 ──────────────────────────────────────────
 IDFH_LONG = FIXTURES / "UM13981_20220207183102.IDFH"      # 719 intervals
 IDFH_SENTINEL = FIXTURES / "UM13981_20221202063059.IDFH"  # holds an unwritten slot
 IDFW_RAW16 = FIXTURES / "UM13981_20220207084555.IDFW"     # segment 0 is MODE_RAW16
 def test_histogram_decodes_past_250_intervals():
    """The segment validator must not require a zero counter high byte.
    The interval counter is a uint16 cumulative index.  Requiring its high
    byte to be zero rejected every segment past interval 255, capping each
    histogram at 250 intervals and truncating any run longer than ~4 hours —
    frequently discarding the part that held the peak.
    """
    result = read_idf_file(IDFH_LONG)
    header, _rows = _parse_export(IDFH_LONG.with_suffix(".IDFH.csv"))
    expected = float(header["NumberOfIntervals"])
    assert len(result.intervals) == 719
    assert len(result.intervals) == pytest.approx(expected, abs=1.0)
 def test_histogram_ignores_unwritten_interval_slot():
    """A never-written interval keeps its ±full-scale seed and must be dropped.
    Counting it fabricates a 10.0 in/s peak on every channel, which then wins
    the max-over-intervals and poisons the whole file's PPV.
    """
    header, _rows = _parse_export(IDFH_SENTINEL.with_suffix(".IDFH.csv"))
    result = read_idf_file(IDFH_SENTINEL)
    for channel, attr in (
        ("Tran", "transverse_ips"),
        ("Vert", "vertical_ips"),
        ("Long", "longitudinal_ips"),
    ):
        decoded = getattr(result.event.peaks, attr)
        assert decoded < 1.0, f"{channel} peak {decoded} looks like the ±FS seed"
        assert decoded == pytest.approx(
            _header_float(header, f"{channel}PPV"), abs=2 * _GEO_LSB_IPS
        )
 def test_waveform_raw16_segment_zero_is_decoded():
    """Segment-0 records can be raw int16 (MODE_RAW16, 10-byte header).
    That mode was absent from the dispatch, so the record fell through
    unhandled and the channel silently lost its first 512 samples.
    """
    rows = _parse_export(IDFW_RAW16.with_suffix(".IDFW.csv"))[1]
    result = read_idf_file(IDFW_RAW16)
    for index, channel in enumerate(GEO_CHANNELS):
        decoded = result.samples[channel]
        assert len(decoded) == len(rows), f"{channel} lost segment 0"
        expected = [row[index] for row in rows]
        bad = sum(
            1 for c, v in zip(decoded, expected)
            if abs(geo_count_to_ips(c) - v) >= 5e-5
        )
        assert bad == 0, f"{channel}: {bad} samples differ from Thor's export"
 def test_body_offset_search_is_not_quadratic():
    """The body scan must stay cheap enough for bulk ingest.
    MODE_RAW16 is (0x00, 0x00), so scanning for candidate *preambles* treats
    every run of three zero bytes as a body start and trial-decodes each one
    (~0.5 s/file measured).  The search anchors on record headers instead.
    """
    import time
    start = time.perf_counter()
    for _ in range(3):
        read_idf_file(IDFW_RAW16)
    elapsed = (time.perf_counter() - start) / 3
    assert elapsed < 0.15, f"body-offset search took {elapsed*1000:.0f} ms/file"
 # ─── Mic-disabled (3-channel) units, found 2026-09-10 ──────────────────────
 IDFW_3CH = FIXTURES / "UM20147_20250531135901.IDFW"   # body head below old floor
 IDFH_3CH = FIXTURES / "UM20147_20250330070110.IDFH"   # 56-byte interval records
 def test_three_channel_waveform_decodes_all_geo_channels():
    """A mic-disabled unit's shorter header moves the record chain head.
    Its head sits at 0x0dba, below the old ``_BODY_SCAN_FLOOR`` of 0x0E00, so
    the scan could not see it and fell through to the *Vert* segment-0 record
    — decoding a body shifted one position around the channel rotation, which
    surfaced as Vert being exactly 512 samples short.
    """
    rows = _parse_export(IDFW_3CH.with_suffix(".IDFW.csv"))[1]
    result = read_idf_file(IDFW_3CH)
    for index, channel in enumerate(GEO_CHANNELS):
        decoded = result.samples[channel]
        assert len(decoded) == len(rows), (
            f"{channel}: {len(decoded)} samples, export has {len(rows)}"
        )
        expected = [row[index] for row in rows]
        bad = sum(
            1 for c, v in zip(decoded, expected)
            if abs(geo_count_to_ips(c) - v) >= 5e-5
        )
        assert bad == 0, f"{channel}: {bad} samples differ from Thor's export"
    # Mic is genuinely absent on these units, not merely undecoded.
    assert not result.samples.get("MicL")
 def test_three_channel_histogram_uses_56_byte_intervals():
    """Interval stride is 16 bytes per channel + an 8-byte tail, not a constant.
    A mic-disabled unit packs 56-byte records, so assuming 72 read 7 intervals
    out of every 10-interval segment and then walked off alignment into
    garbage, which decoded as ~10 in/s peaks.  The true count comes from the
    segment's cumulative interval counter.
    """
    header, _rows = _parse_export(IDFH_3CH.with_suffix(".IDFH.csv"))
    result = read_idf_file(IDFH_3CH)
    expected_intervals = float(header["NumberOfIntervals"])
    assert len(result.intervals) == pytest.approx(expected_intervals, abs=1.0)
    assert {iv.n_channels for iv in result.intervals} == {3}
    for channel, attr in (
        ("Tran", "transverse_ips"),
        ("Vert", "vertical_ips"),
        ("Long", "longitudinal_ips"),
    ):
        decoded = getattr(result.event.peaks, attr)
        assert decoded < 1.0, f"{channel} peak {decoded} looks like walked-off garbage"
        assert decoded == pytest.approx(
            _header_float(header, f"{channel}PPV"), rel=0.02
        )
 # ─── `40 NN` blocks with NN > 8, verified 2026-09-11 ───────────────────────
 IDFW_WIDE40 = FIXTURES / "UM12947_20250806134504.IDFW"
 def test_wide_forty_nn_block_does_not_truncate_channels():
    """Loud events use `40 NN` blocks with NN well above the old cap of 8.
    ``data_block_len()`` rejected NN > 0x08, which halted the block walk
    part-way through a record.  The walker stops at the first unrecognised
    tag instead of raising, so this surfaced as silently short channels —
    here Tran 1812 / Vert 2132 / Long 2324 where the export has 2324 for all
    three.  The affected files use NN of 12, 16, 20 ... up to 196.
    """
    rows = _parse_export(IDFW_WIDE40.with_suffix(".IDFW.csv"))[1]
    result = read_idf_file(IDFW_WIDE40)
    for index, channel in enumerate(GEO_CHANNELS):
        decoded = result.samples[channel]
        assert len(decoded) == len(rows), (
            f"{channel}: {len(decoded)} samples, export has {len(rows)}"
        )
        expected = [row[index] for row in rows]
        bad = sum(
            1 for c, v in zip(decoded, expected)
            if abs(geo_count_to_ips(c) - v) >= 5e-5
        )
        assert bad == 0, f"{channel}: {bad} samples differ from Thor's export"
@@ -0,0 +1,61 @@
 """The event-report PDF must draw the three geo channels on ONE shared Y scale
 (max |sample| across Long/Vert/Tran, floored), not each trace auto-zoomed to its
 own peak — so relative amplitudes are honest and a small channel doesn't fill its
 lane looking as big as a large one.  Mirrors the event-modal waveform behaviour.
 """
 import matplotlib
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 import pytest
 from sfm.report_pdf import ReportData, _draw_waveform_subplot
 def _draw(channels):
    rd = ReportData(
        channels=channels,
        sample_rate_sps=1024,
        dt_ms=1000.0 / 1024,
        t0_ms=0.0,
    )
    fig = plt.figure()
    cell = fig.add_gridspec(1, 1)[0, 0]
    _draw_waveform_subplot(fig, cell, rd)
    by_label = {ax.get_ylabel(): ax for ax in fig.axes}
    try:
        yield_ = {k: by_label[k].get_ylim() for k in ("Long", "Vert", "Tran", "MicL")}
    finally:
        plt.close(fig)
    return yield_
 def test_geo_traces_share_one_y_scale():
    # Tran is the biggest geo channel (0.35); Long 0.10, Vert 0.02.
    ylims = _draw({
        "Long": [0.10, -0.10, 0.0],
        "Vert": [0.02, -0.02, 0.0],
        "Tran": [0.35, -0.35, 0.0],
        "MicL": [0.0005, -0.0005, 0.0],
    })
    # Shared scale = max(0.35 * 1.10, floor 0.05) = 0.385, symmetric.
    expected = pytest.approx(0.385, rel=1e-6)
    for ch in ("Long", "Vert", "Tran"):
        lo, hi = ylims[ch]
        assert hi == expected, f"{ch} top ylim {hi} != shared 0.385"
        assert lo == pytest.approx(-0.385, rel=1e-6), f"{ch} bottom ylim {lo}"
    # All three geo lanes identical.
    assert ylims["Long"] == ylims["Vert"] == ylims["Tran"]
    # Mic keeps its own (much smaller) scale — not lumped into the geo max.
    assert ylims["MicL"][1] < 0.01
 def test_geo_shared_scale_has_floor():
    # A tiny event (all geo well under the floor) clamps to the 0.05 floor.
    ylims = _draw({
        "Long": [0.008, -0.008, 0.0],
        "Vert": [0.006, -0.006, 0.0],
        "Tran": [0.010, -0.010, 0.0],
        "MicL": [0.0001, -0.0001, 0.0],
    })
    for ch in ("Long", "Vert", "Tran"):
        assert ylims[ch][1] == pytest.approx(0.05, rel=1e-6), f"{ch} not floored"
@@ -0,0 +1,67 @@
 """Blastware sensor self-check waveform decode (minimateplus.sensor_check).
 Reverse-engineered 2026-09-15 against 7 BE12844 (MiniMate Plus) oracle events.
 After the main waveform record-chain and the trailing metadata / per-channel
 calibration records, a series-3 binary carries four length-prefixed records
 tagged 0x3c-0x3f: the sensor self-check traces the unit records when it pulses
 each sensor before monitoring (Blastware draws these as the little waveforms in
 the "Sensor Check" strip on the right of the Event Report).
  * 0x3c / 0x3d / 0x3e = Tran / Vert / Long geophone ring-downs.
  * 0x3f            = MicL, a pulse train at the mic self-test frequency.
 The self-check injects a fixed pulse, so the response is near-identical across
 events — asserted here as an invariant shape (damped one-sided ring-down for
 the geophones, a multi-pulse train for the mic).
 """
 from pathlib import Path
 import numpy as np
 from minimateplus.sensor_check import decode_sensor_check
 FIXDIR = Path(__file__).parent / "fixtures" / "fft-oracle-2026-09-14"
 EVENTS = sorted(p.name for p in FIXDIR.iterdir())   # 7 BE12844 event binaries
 def _decode(name):
    return decode_sensor_check((FIXDIR / name).read_bytes())
 def test_all_four_channels_present():
    for name in EVENTS:
        sc = _decode(name)
        assert set(sc) == {"Tran", "Vert", "Long", "MicL"}, name
 def test_geo_channels_are_damped_ringdowns():
    # Each geophone self-check is a large one-sided deflection (~-990 raw) that
    # rings back and damps toward a settled value well above the trough.
    for name in EVENTS:
        sc = _decode(name)
        for ch in ("Tran", "Vert", "Long"):
            tr = np.asarray(sc[ch], dtype=float)
            assert 240 <= len(tr) <= 260, f"{name}:{ch} n={len(tr)}"
            assert abs(tr[:3].mean()) < 50, f"{name}:{ch} starts off-baseline"
            assert tr.min() < -800, f"{name}:{ch} min {tr.min()}"
            assert tr.max() < 60, f"{name}:{ch} unexpected positive swing {tr.max()}"
            # damped: settles between the trough and zero, well above the trough
            assert tr.min() < tr[-1] < 0, f"{name}:{ch} end {tr[-1]} not between trough and 0"
            assert abs(tr[-1]) < 0.6 * abs(tr.min()), f"{name}:{ch} not damped, end {tr[-1]}"
 def test_mic_channel_is_a_pulse_train():
    for name in EVENTS:
        tr = np.asarray(_decode(name)["MicL"], dtype=float)
        assert 235 <= len(tr) <= 255, f"{name} mic n={len(tr)}"
        # larger dynamic range than the geo ring-down, and swings both ways
        assert tr.min() < -1500, f"{name} mic min {tr.min()}"
        assert tr.max() > 100, f"{name} mic max {tr.max()}"
        # multiple pulses: several deep local minima
        deep = (tr[1:-1] < tr[:-2]) & (tr[1:-1] < tr[2:]) & (tr[1:-1] < -800)
        assert int(deep.sum()) >= 4, f"{name} mic pulses {int(deep.sum())}"
 def test_returns_empty_when_no_sensor_check_block():
    assert decode_sensor_check(b"not a blastware file") == {}
    assert decode_sensor_check(b"") == {}
@@ -712,8 +712,27 @@ def test_forty_nn_is_a_data_block_not_a_segment_header():
    """
    assert data_block_len(b"\x40\x02\x00\x01\x00\x02", 0) == (6, 2)
    assert data_block_len(b"\x40\x08" + bytes(16), 0) == (18, 8)
-    # NN > 8 is not a data block
+
-    assert data_block_len(b"\x40\x0c" + bytes(24), 0) == (None, None)
+
 def test_forty_nn_is_not_capped_at_eight():
    """NN > 8 is a perfectly ordinary `40 NN` block.
    This test previously asserted the opposite (`40 0c` -> (None, None)),
    codifying a guard that had no evidence behind it: the only corpora
    available then used NN in {1,2,3,4,8}, so the cap was never exercised.
    Loud UM12947 events use NN of 12, 16, 20 ... up to 196, and rejecting
    them halted the block walk mid-record — surfacing as silently short
    channels, since the walker stops at the first unrecognised tag rather
    than raising.  Lifting the cap took that corpus from 22 length-mismatched
    files to 0, and 1,476,242 of 1,476,249 samples now reproduce Thor's own
    CSV export exactly (the 7 stragglers differ by one 4th-decimal tick).
    Verified 2026-09-11; see docs/idf_protocol_reference.md.
    """
    assert data_block_len(b"\x40\x0c" + bytes(24), 0) == (26, 12)
    assert data_block_len(b"\x40\xc4" + bytes(392), 0) == (394, 196)
    # The real bound is the buffer: a block that cannot fit is not a block.
    assert data_block_len(b"\x40\xc4" + bytes(8), 0) == (None, None)
    assert data_block_len(b"\x40\x00" + bytes(8), 0) == (None, None)
 def test_record_chain_is_followed_by_length_not_by_tag_sniffing():
@@ -0,0 +1,85 @@
 """Blastware-compatible channel FFT (waveform_fft).
 Reverse-engineered 2026-09-14 against 7 BE12844 (MiniMate Plus) events, each with
 a Blastware FFT report as ground truth. The recipe (DC-remove, no window,
 zero-pad to 4096 → 0.25 Hz bins, single-sided 2/N amplitude) reproduces
 Blastware's dominant frequency to the exact bin on all 28 channels and the
 amplitude to report precision.
 """
 from pathlib import Path
 import numpy as np
 from waveform_fft import channel_spectrum, dominant_frequency
 from minimateplus.waveform_codec import decode_waveform_v2
 FIXDIR = Path(__file__).parent / "fixtures" / "fft-oracle-2026-09-14"
 GEO_LSB = 0.005   # 1 decode unit = 16 ADC counts = 0.005 in/s (series-3 Normal range)
 # Blastware FFT-report ground truth: file → {channel: (dominant_hz, amplitude_ips)}.
 # amplitude is None where the channel is at the noise floor (report amp 0.000/0.001)
 # — the dominant frequency still matches exactly, but the amplitude isn't meaningful.
 ORACLE = {
    "N844LPGH.VV0W": {"Tran": (27.00, 0.018), "Vert": (26.75, 0.009), "Long": (26.50, 0.021), "MicL": (2.000, None)},
    "N844LPPR.3S0W": {"Tran": (30.75, None),  "Vert": (46.75, None),  "Long": (26.75, None),  "MicL": (49.50, None)},
    "N844LQHB.ZT0W": {"Tran": (19.75, 0.040), "Vert": (26.50, 0.018), "Long": (26.50, 0.083), "MicL": (2.750, None)},
    "N844LQUE.T50W": {"Tran": (21.50, 0.080), "Vert": (14.25, 0.028), "Long": (28.50, 0.046), "MicL": (5.750, None)},
    "N844LR8W.790W": {"Tran": (31.00, None),  "Vert": (31.00, None),  "Long": (34.00, None),  "MicL": (66.25, None)},
    "N844LRCO.G60W": {"Tran": (32.25, 0.009), "Vert": (32.00, 0.005), "Long": (32.00, 0.008), "MicL": (32.00, None)},
    "N844LRCW.F30W": {"Tran": (21.25, 0.010), "Vert": (42.25, 0.002), "Long": (21.25, 0.014), "MicL": (21.25, None)},
 }
 def test_pure_sine_frequency_and_amplitude():
    # A pure sine at a bin-centre frequency (128 cycles over 4096 samples) has no
    # leakage, so the single-sided 2/N normalisation returns the amplitude exactly.
    sps, n, f0, amp = 1024.0, 4096, 32.0, 0.5
    x = amp * np.sin(2 * np.pi * f0 * np.arange(n) / sps)
    freqs, amps = channel_spectrum(x, sps=sps, nfft=4096)
    fpk, apk = dominant_frequency(freqs, amps)
    assert fpk == 32.0
    assert abs(apk - amp) < 1e-3
 def test_bin_resolution_is_quarter_hz():
    freqs, _ = channel_spectrum(np.zeros(3328), sps=1024.0, nfft=4096)
    assert abs((freqs[1] - freqs[0]) - 0.25) < 1e-9
 def test_empty_input():
    freqs, amps = channel_spectrum([])
    assert len(freqs) == 0 and len(amps) == 0
 def _spectra(fname):
    raw = (FIXDIR / fname).read_bytes()
    dec = decode_waveform_v2(raw[raw.find(b"STRT") + 21:])
    out = {}
    for ch, samples in dec.items():
        ips = np.asarray(samples, float) * GEO_LSB
        out[ch] = channel_spectrum(ips, sps=1024.0)
    return out
 def test_dominant_frequency_matches_blastware_exactly():
    misses = []
    for fname, chans in ORACLE.items():
        spectra = _spectra(fname)
        for ch, (want_hz, _) in chans.items():
            got_hz, _ = dominant_frequency(*spectra[ch])
            if abs(got_hz - want_hz) > 0.25:
                misses.append(f"{fname}:{ch} got {got_hz} want {want_hz}")
    assert not misses, "dominant-frequency mismatches:\n" + "\n".join(misses)
 def test_amplitude_matches_blastware():
    misses = []
    for fname, chans in ORACLE.items():
        spectra = _spectra(fname)
        for ch, (_, want_amp) in chans.items():
            if want_amp is None:
                continue
            _, got_amp = dominant_frequency(*spectra[ch])
            if abs(got_amp - want_amp) > 0.0015:
                misses.append(f"{fname}:{ch} got {got_amp:.4f} want {want_amp:.3f}")
    assert not misses, "amplitude mismatches:\n" + "\n".join(misses)
@@ -0,0 +1,66 @@
 """Blastware-compatible FFT of a decoded seismograph channel.
 Pure numpy; no I/O, no device or DB dependencies. Feed it a channel's decoded
 samples **in the unit you want the amplitudes in** (e.g. in/s) and it returns the
 single-sided amplitude spectrum that Blastware's *FFT Report* draws.
 Reverse-engineered 2026-09-14 against 7 BE12844 (MiniMate Plus) events with
 Blastware FFT reports as ground truth. The recipe reproduces Blastware's
 **dominant frequency to the exact 0.25 Hz bin on all 28 channels** and the
 amplitude to report precision:
  1. remove the DC component (subtract the mean); **no window** — a window
     smears the peak and measurably worsens the match,
  2. zero-pad to ``nfft`` (4096 → 0.25 Hz bins at 1024 sps — Blastware's
     resolution),
  3. single-sided amplitude ``A[k] = 2·|X[k]| / N`` where ``N`` is the real
     sample count (not ``nfft``).
 The compliance chart (USBM RI8507 / OSMRE) is this spectrum's ``(freq, amp)``
 points plotted against the regulatory limit curve; the #10 FFT view is the
 spectrum itself.
 """
 from __future__ import annotations
 import numpy as np
 BW_NFFT = 4096              # 0.25 Hz bins at 1024 sps — Blastware's FFT resolution
 BW_FMIN = 2.0              # dominant-frequency search floor (Hz)
 BW_FMAX = 250.0           # dominant-frequency search ceiling (Hz)
 def channel_spectrum(samples, sps: float = 1024.0, nfft: int = BW_NFFT):
    """Single-sided amplitude spectrum of one channel, Blastware-compatible.
    ``samples`` is a 1-D sequence in the desired amplitude unit (in/s). Returns
    ``(freqs, amps)`` numpy arrays covering ``0 .. sps/2`` in ``sps/nfft`` steps.
    Records longer than ``nfft`` are truncated by the transform — untested
    against Blastware for that case (real MiniMate Plus records are ≤ ~3.3 s,
    well under 4096 samples at 1024 sps).
    """
    x = np.asarray(samples, dtype=float)
    n = x.size
    if n == 0:
        return np.empty(0), np.empty(0)
    x = x - x.mean()                          # DC removal, no window
    mag = np.abs(np.fft.rfft(x, nfft))
    freqs = np.fft.rfftfreq(nfft, 1.0 / sps)
    amps = (2.0 / n) * mag                     # single-sided amplitude
    return freqs, amps
 def dominant_frequency(freqs, amps, fmin: float = BW_FMIN, fmax: float = BW_FMAX):
    """Peak ``(frequency_hz, amplitude)`` of a spectrum within ``[fmin, fmax)``.
    Matches Blastware's "Dominant Frequency" — the largest spectral bin in the
    reportable band (below 2 Hz is baseline/DC drift, above 250 Hz is noise).
    """
    freqs = np.asarray(freqs)
    amps = np.asarray(amps)
    lo = int(np.searchsorted(freqs, fmin))
    hi = int(np.searchsorted(freqs, fmax))
    if hi <= lo:
        return 0.0, 0.0
    k = lo + int(np.argmax(amps[lo:hi]))
    return float(freqs[k]), float(amps[k])