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250 Commits
archive/protocol-exp ... feat/offset-study
Author SHA1 Message Date
serversdownandClaude Opus 5 0a96a34b02 docs(offset): CONFIRMED — BE12599 is a geophone-assembly fault, not the recorder 
The first mechanism this investigation has established physically rather than
inferred. Brian pulled BE12599 and bench-tested it; a geophone swap settles it.

Same recorder, twenty minutes apart: Vert overswing 2026.0 with its own
geophone, 3.4 with BE9888's known-good one. Frequency 2.2 -> 7.4 Hz. All three
channels Passed, no offsets, no self-triggering, and a clean damped impulse with
broadband content. The recorder is functional and merely out of calibration.

A bench control -- trigger forced by slapping the microphone, geophone untouched
-- shows Vert producing 0.19 in/s of bipolar wander with no mechanical input at
all. The fault is continuous, not episodic. All three channels are affected:
Tran and Long sit on a small DC while their coils still pass the swing test,
Vert has lost damping entirely. That is leakage on several contacts plus one
gone open, not three elements failing in sequence.

The consequence that reaches past this unit: an autozero adjusts the RECORDER's
zero reference and cannot fix a geophone. If most offsets are geophone-assembly
faults, a re-zero succeeds only on the minority where the recorder really is at
fault -- which is exactly the ~10% rate recorded in section 5 and unexplained
since August. Procedure change: swap the geophone first.

Corrects 8e's title, which called it a connector rather than a geophone: the
swap narrows the fault to the assembly, and element / cable / connector remain
open within it. And reweights the cause -- the geophone is buried, not in the
enclosure with the nest, and the unit sat ~6 ft from I-80 WB, so road salt now
outranks the mice.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-09-23 02:57:34 +00:00
serversdownandClaude Opus 4.8 154186a6cd Merge feat/event-timestamp-fix: exact waveform trigger time from the binary 
read_blastware_file stamped waveforms with footer ts1 (the monitoring-session
start, hours off — vomit-list #3).  The event time is ts2 (recording stop) and
the trigger = ts2 - record time, a float32 in the recording-setup config block,
so the exact Blastware trigger is recovered from the binary alone (no .TXT).
Histograms keep ts1; a paired report's event_datetime stays authoritative.

Needs a re-decode backfill to correct existing stored events' timestamps.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-20 23:13:19 +00:00
serversdownandClaude Opus 4.8 1765b3300d docs(changelog): waveform event-time fix (exact trigger from binary) 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-20 22:32:13 +00:00
serversdownandClaude Opus 4.8 1e76d08b37 fix(decode): recover the exact waveform trigger from the binary (no .TXT) 
Follow-up to the ts1→ts2 fix: get the trigger to the second from the binary
alone, instead of falling back to the stop time (~record-duration late) for
no-report events.

The configured post-trigger record time is a big-endian float32 in the
recording-setup config block, exactly 30 bytes before the "Standard Recording
Setup" marker.  _parse_record_time_seconds reads it; the waveform branch now
stamps trigger = ts2 - record_time.  Verified: the field reads 1.0 / 2.0 / 3.0 s
across different setups in the corpus, and all 7 BE12844 oracle events now
decode to their exact Blastware trigger (N844LQHB 10:33:29) from the binary,
no paired .TXT needed.  Falls back to ts2 (the stop) if the config block is
absent.  A paired report's event_datetime stays authoritative (clock drift).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-20 22:31:22 +00:00
serversdownandClaude Opus 4.8 a84a46e9d4 fix(decode): stamp waveform events with the event time, not the session start 
read_blastware_file built ev.timestamp from footer ts1, which for a WAVEFORM is
the monitoring-session start (a unit arming at 06:00 stamps 06:00 on every event
that day) — so every waveform's time was hours off (vomit-list #3, "~4.5 h off").
The event time is footer ts2 (the recording stop); BW's displayed Date/Time is
the trigger = ts2 - record duration.

Root cause proven against the BE12844 oracle set: 5 of 7 events decoded to the
identical 06:00:13 (the shared session start); ts2 gives distinct plausible
event times (N844LQHB ts2 = 10:33:32, BW trigger 10:33:29 = ts2 - 3.0 s rectime).

  * read_blastware_file now uses ts2 for waveforms (discriminated by which codec
    decoded the body, not the filename — save_imported_bw passes a tmp name).
    Histograms keep ts1 (the ~24 h window start, which IS the event time).
  * Binary-only decode can't get the exact trigger: the STRT record-time byte is
    a misparsed record-type marker (0x46=70), so ts2 (the stop, ~record duration
    after the trigger) is the best estimate. A paired BW report carries the exact
    trigger — apply_report_to_event now overlays event.timestamp from
    report.event_datetime, matching the existing build-path override (line ~441).

Tests: waveform → ts2, histogram → ts1 unchanged, report → exact trigger.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-20 18:21:07 +00:00
serversdownandClaude Opus 5 ada5bc2a82 docs(changelog): Unreleased — cheap connect, Diagnostics tab, tool status 
Written on dev as part of finishing the merge, per the convention adopted
2026-09-18: feature branches do not touch CHANGELOG.md, and the entry describes
what actually landed rather than what a branch intended.

First time through the new way rather than discovering the conflict afterward —
the merge was clean.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-20 17:12:49 +00:00
serversdownandClaude Opus 5 f1ab5b1e9d docs: record the 5A page-boundary bug, and assess SFM as a tool 
Two things Brian asked for after the BE12599 work.

The known bug: the 5A walk discards the key's page byte, so once a unit has
recorded more than 64 KB since its last erase, an event spanning the boundary
reads an end_offset behind its own start. The chunk loop then fetches nothing
and TERM packs a negative offset_word, which is the 500. Reproduced on BE12599.
It hid this long because every capture the walk was verified against came from
a freshly-erased BE11529 — all three confirmed TERM examples sit inside page
0x11. Prod is unaffected; it ingests complete files and never runs this walk.

The status doc exists because "is SFM reliable?" has three different answers
depending on which tier is meant. The codec library and the data side are
production — verified per-sample at scale, carrying Terra-View daily. The
device side is emergency-grade: it works, but it is synchronous,
unauthenticated, and thinly tested. The lab is research artifacts. Most
confusion comes from answering for the wrong tier.

It covers all three of what Brian asked for: maturity per capability, an
operator-facing "what to use when" (the cheap probes are cheap and the event
walk is not), the known-issues table, and the gap analysis. That gap is mostly
auth, async and guardrails — not protocol work. The protocol is the finished
part.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-20 01:30:14 +00:00
serversdownandClaude Opus 5 6589da445b feat(webapp): cheap connect, opt-in event walk, and a Diagnostics tab 
Connecting to a unit fired /device/events automatically, which walks the whole
event chain — every event header over a cellular link. On BE12599 that took
minutes and then 500'd outright, because its buffer has wrapped past 0xFFFF and
the uint16 offset arithmetic goes negative. Wanting to know whether ACH was on
should not require reading every event the unit has stored.

Connect now uses only cheap probes: /device/info (which already carries the
compliance config the event walk was re-reading) plus /device/events/storage_
range. The chain walk moves behind a "Load events" button in the Events
toolbar, and the Device tab gains an Event Chain card showing the first/last
keys.

Adds a Diagnostics tab for the endpoints that previously existed only as curl:
storage_range and events/index alongside monitor/status, then stop monitoring,
disable ACH (rescue?erase=false, so events survive), and erase. The wedged-unit
ladder — slow drip and blind stop — sits under its own heading pointing at the
runbook, with the reminder that slow_drip's success signal is bytes_received>0
and not a clean duration.

Erase is guarded by typing the unit's serial. Auth answers who, not whether you
meant it, and Swagger's try-it-out button on /device/events/erase is live on
:8200/docs — the realistic risk here is an accident.

Lifetime events is displayed but labelled unreliable: SUB 0x08 reports 0 on
units with years of history, which is a decode bug we have not chased yet.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-19 22:05:55 +00:00
serversdownandClaude Opus 5 0b58415fe2 chore(release): v0.31.0 — report parity + the inverted rescue 
Cuts Unreleased to v0.31.0 and writes the theme now that the whole release is
visible, per the convention adopted today.

Two threads landed. Blastware Event/FFT-Report parity — the FFT, the USBM
RI8507 compliance chart, and the sensor self-check decoded for both series and
standardized into the .h5 (schema v2, /sensor_check). And the ach_server rescue
flags out of the BE12599 field emergency, which invert the wedged-unit recovery:
answer the unit's call instead of racing a Stop into the gaps between its
dial-outs.

Version stamped in pyproject.toml, CLAUDE.md and README.md. TOOL_VERSION was
already at 0.31.0 — it came in with the sensor-check work, and it is what makes
the backfill pick up the new /sensor_check group without --force.

⚠ This release owes prod a backfill: .h5 schema v1 -> v2, ~2 h on the NAS.
Stated in the Migration block.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-18 20:40:48 +00:00
serversdownandClaude Opus 5 fa22bb9f59 Merge feat/sensor-check-h5 into dev 
Sensor self-check standardized into the .h5 (schema v2, /sensor_check group),
decoded for both series-3 and series-4, plus the Thor backfill script.

CHANGELOG resolved per the convention adopted today: the incoming Unreleased
preamble was dropped rather than reconciled — no preamble under Unreleased, the
theme gets written at release time — and its load-bearing half was folded into
### Migration, which said "None" and is now false.

That block now states the real cost: .h5 schema v1 -> v2, TOOL_VERSION 0.31.0
so the standard backfill picks the traces up with no --force, and ~2 h on the
NAS. The FFT, the compliance chart and the ach_server rescue flags still owe
nothing.

The branch's rewritten "Sensor self-check — both series" entry merged cleanly
and is kept.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-18 20:16:13 +00:00
serversdown 27e9c56393 Merge pull request 'Feat/ach rescue on connect' (#38) from feat/ach-rescue-on-connect into dev 
Reviewed-on: #38
 2026-09-18 15:26:18 -04:00
serversdownandClaude Opus 5 0408c37866 docs: write the changelog on dev, not on feature branches 
Reverses the "entry goes in with the work" rule from two commits ago. That was
wrong on the evidence: of the docs(changelog) commits in history, 3 of 4 in
seismo-relay and 2 of 4 in Terra-View were made directly on dev. The rule was
generalized from one unrepresentative commit rather than from the pattern.

It also caused the exact problem it was supposed to avoid. With four worktrees
in flight, every branch edits the same few lines at the top of CHANGELOG.md;
feat/ach-rescue-on-connect and feat/sensor-check-h5 collide on that file and
nothing else. Writing the entry once, on dev, after the merge removes the
whole conflict class.

The second benefit is accuracy: an entry written after the merge describes
what actually landed, including anything that changed during conflict
resolution. The sensor-check branch is a live example — its Unreleased
preamble describes a release that no longer looks like that.

The failure mode of writing it later is forgetting, so the merge is explicitly
not finished until Unreleased is updated — same sitting, reconstructed from the
branch commit messages.

Unchanged: no preamble under Unreleased, the mandatory operational consequence,
and cutting the version on dev when ready to ship to main.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-18 18:52:17 +00:00
serversdownandClaude Opus 5 a42e8d3651 docs: make the release cadence explicit 
Brian described the practice: Unreleased is the staging area for what is going
into the next release, and the version bump happens when enough has
accumulated to be worth shipping — not per commit, not per merge. The
convention already implied it ("never touch the changelog at a merge
boundary") but never said it outright.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-18 18:04:54 +00:00
serversdownandClaude Opus 5 2fabf84d4d docs: adopt a changelog convention, and make Unreleased follow it 
Brian asked what the standard is; there wasn't a written one, only a de facto
pattern in the history. This writes it down in CLAUDE.md and fixes the one
place the repo already diverged from it.

The rule: write the entry in the same commit as the work, under ## Unreleased;
cut the version on dev in a dedicated chore(release) commit; never touch the
changelog at a merge boundary. The entry goes in with the change because that
is the only moment you still know why.

Two additions beyond what the history already did:

No preamble under ## Unreleased. The themed opening paragraph gets written at
release time, when the whole release is visible and can be named honestly. The
current one proved the point — "Blastware Event/FFT-Report parity: the FFT,
the USBM compliance chart, and the sensor self-check" was accurate when the
first item landed and stopped being accurate once rescue-on-connect landed
under the same heading. Removed here; the release commit writes a new one
covering everything actually in the release.

And the operational consequence is now mandatory on any entry touching the
codec, the waveform store, or the DB — including when it is "none". This
repo's changelog is how future-you learns whether a deploy costs two hours on
the NAS, so silence is ambiguous and "none" is information. The old preamble's
load-bearing half is preserved as an explicit ### Migration block rather than
dropped with the prose around it.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-18 17:39:56 +00:00
serversdownandClaude Opus 5 402bf30e37 docs(runbook): reframe as one disease with two cures, intercept first 
The previous commit called BE12599 a second failure mode and claimed the
device "never enters S3 mode at all" and that no inbound work could reach it.
That was an overclaim built on a single slow_drip attempt, and Brian was right
to push back.

It is the same disease.  Method B's step 1 worked fine on BE12599 — clearing
the Destination did stop the dial-outs.  It was step 2 that did not land, on
one attempt, run ~90 s after a modem reboot with a dead session visible in the
log in that same window; BE9558H needed hours of attempts before one landed.
And the AT-init loop the ALEOS log revealed is almost certainly what BE9558H
was doing too — we just never turned on serial debug in May to look.  The
device speaks S3 fine; it handshook cleanly the moment it had a session.

What is genuinely new is the cure, and it deserves to be the default rather
than a footnote.  Racing a Stop into the gaps between dial-outs is a coin
flip.  Intercepting is deterministic: the unit dials every ~75 s, so give it
somewhere to dial and answer it.  It will not answer us because it is on the
phone — so be the one it calls.

Restructures accordingly: a "two cures" table up top, the intercept promoted
to Method A with its own procedure (listener before modem, stop at step 1.5,
drain before disabling ACH, restore the Destination and confirm it), and the
original inbound procedure kept intact as Method B for when there is no
listener the modem can reach.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-17 06:10:03 +00:00
serversdownandClaude Opus 5 c6fc3d0241 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
 2026-09-17 05:45:26 +00:00
serversdownandClaude Opus 5 9f1050b5e7 feat(ach): rescue-on-connect — stop monitoring / disable ACH from the server side 
A unit whose geophone offset has grown past its trigger level records
back-to-back and, with ACH set to "after event recorded", re-dials every
time.  The wedged_unit_recovery runbook handles that by reaching the unit
inbound and clearing the modem's Destination Address so it stops dialing.

That fails when the device is wedged mid-modem-init.  BE12599 (2026-09-16)
sat repeating a 29-byte AT setup string — ATQ1/ATE0/ATS0=2, no ATD — every
75 s.  The modem is in TCP data mode, never interprets it, never answers OK,
so the device never progresses into S3 mode and ignores every frame we send.
Worse, each attempt makes ALEOS log "tcpmode trying to send to invalid
socket" and re-run "Initialize Auto answer on port 9034", which orphans any
held inbound session — slow_drip reports a clean 120 s hold with
bytes_received=0 because the modem stopped bridging after the first re-init.

Inbound cannot win that race.  But the modem auto-dials its Destination
whenever serial data arrives while closed, so pointing Destination at an
ach_server turns those 75 s attempts into a device-initiated session that
the modem bridges correctly.

Adds --stop-monitoring, --disable-ach and --rescue.  They run as step 1.5,
after the handshake and before the event walk, each independently guarded so
a failure does not abort the download.  Outcome is written to rescue.json.
Startup banner reports both, and warns when --restart-monitoring would undo
--stop-monitoring.

Prefer --stop-monitoring alone on first contact: --disable-ach stops the unit
calling, which is the only channel to a unit in this state, and halting the
recording ends the loop on its own.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qcu9ByJfuKBQxmrWb8rSrN
 2026-09-16 20:54:46 +00:00
serversdownandClaude Opus 4.8 8265e32ad5 feat(backfill): regenerate .h5 with /sensor_check; TOOL_VERSION 0.31.0 
Complete the sensor-check standardization: existing events need their .h5
regenerated to gain the v2 /sensor_check group.

  * backfill_thor_events.py attaches the decoded series-4 traces
    (micromate.sensor_check) on its own IDF decode path, mirroring
    save_imported_idf, so regenerated Thor .h5 files get the group. Series-3
    backfill needs no change — it re-decodes via read_blastware_file, which now
    attaches the traces itself.
  * TOOL_VERSION 0.30.0 → 0.31.0 so the standard backfill regenerates every
    event (no --force): the tool now produces the /sensor_check group. Purely
    additive — no decoded value changes.
  * CHANGELOG (Unreleased): sensor-check now series-3 + series-4, standardized
    into the .h5 (schema v2), with the ⚠ backfill note; FFT + compliance stay
    no-backfill (they read existing .h5 samples).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-16 06:53:33 +00:00
serversdownandClaude Opus 4.8 8d3cdba1b5 feat(h5): standardize sensor-check into the .h5 (schema v2); SFM reads it 
Make the sensor self-check a first-class part of the standardized decoded event
so SFM stops decoding it at report time — device-agnostic, per the store's
decoder→standardized-.h5→SFM model.

  * Event gains a `sensor_check` field; both decoders attach the traces where
    they set raw_samples — series-3 in event_file_io.read_blastware_file
    (minimateplus.sensor_check), series-4 in waveform_store's IDF path
    (micromate.sensor_check).  Covers ingest and backfill (both re-decode).
  * event_hdf5 bumps schema_version 1→2 and writes an optional /sensor_check
    group (raw counts, int32, per channel present).  read_event_hdf5 returns
    it; plot_json_from_hdf5 carries it as a top-level key.  Old v1 files still
    read cleanly (no group → None), so nothing breaks before the backfill.
  * gather_report_data reads sensor_check_waveforms from the .h5 and drops the
    report-time series-3 decode — the report no longer reaches into a decoder,
    and a series-4 event now lights up the same strip automatically.

Stored as raw counts (a shape diagnostic, rendered fit-to-box): the per-series
count scale differs and a physical mic unit is ill-defined, so conversion would
add complexity for no display benefit — easy to add later if a numeric use
appears.

Tests: .h5 roundtrip + backward-compat + plot_json + real series-3 decode
attaches to the Event.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-16 06:49:55 +00:00
serversdownandClaude Opus 4.8 685a17d180 feat(series4): decode sensor self-check waveforms from the IDFW binary 
The Thor/Micromate (series-4) IDFW binary carries the sensor self-check in its
fixed-header region (before the waveform body), as up to four records tagged
01 0e 3c/3d/3e/3f — the SAME channel ids as series-3 (Tran/Vert/Long/MicL).
Unlike series-3's delta-coded trailing block, series-4 stores each trace as a
raw int16-BE array after an 18-byte record header (2-byte sample count at
offset +8). Three-channel (mic-disabled) units carry only 3c/3d/3e.

New micromate/sensor_check.py: decode_idf_sensor_check(raw) locates the record
chain (id-ordered marker run, so a stray body match can't chain) and reads each
trace's int16 samples → {Tran,Vert,Long[,MicL]: [counts]}, or {} when absent.

Reverse-engineered + validated against 4 UM oracle events (added as fixtures):
clean geophone ring-downs on all, mic pulse trains on the 4-channel units,
correctly no MicL on the two 3-channel units. Validated by shape + cross-event
consistency (no Thor report strip to exact-match, unlike series-3's BW reports).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-15 20:01:39 +00:00
serversdownandClaude Opus 4.8 dcd9ad6f48 Merge feat/fft-series3: Blastware FFT, USBM compliance chart, sensor self-check 
Reverse-engineered Blastware Event/FFT-Report parity, all additive (reads the
existing .h5 samples + retained raw binary, no DB/.h5 change or backfill):
 - Blastware-compatible channel FFT (waveform_fft)
 - USBM RI8507/OSMRE compliance chart on the event-report PDF (sfm/compliance)
 - sensor self-check strip decoded from the series-3 binary trailing block
   (minimateplus/sensor_check) + Frequency/Overswing sub-rows
 - seismo_lab Inspector hex reader (minimateplus/binary_annotate)
 - report fixes: stacked-lane y-tick collision, header serial fit

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-15 14:37:44 +00:00
serversdownandClaude Opus 4.8 4f73e919a0 docs(changelog): Unreleased — FFT, USBM compliance chart, sensor self-check 
Document the feat/fft-series3 work under Unreleased: Blastware-compatible
channel FFT, the USBM RI8507/OSMRE compliance chart on the event-report PDF,
the decoded sensor self-check strip + Frequency/Overswing sub-rows, and the
seismo_lab Inspector hex reader — plus the two report-panel fixes (tick
collision, header serial fit). Additive, no .h5/DB change or backfill.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-15 14:34:04 +00:00
serversdownandClaude Opus 4.8 2a747f6893 fix(report): attach sensor-check strip to the waveform panel; move "0.0" 
Match Blastware's layout, measured off the reference PDF: the sensor-check
strip shares a border with the main waveform panel (no gap between them), and
the per-lane "0.0" baseline labels sit to the RIGHT of the strip. Previously
the strip floated with a gap and the "0.0" label overprinted the strip's left
edge. Purely layout — the traces and decode are unchanged.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-15 05:48:31 +00:00
serversdownandClaude Opus 4.8 2c5c20cfd7 fix(report): fit sensor-check mini-plots to their boxes 
The sensor-check strip used a symmetric ±max scale, so the one-sided geophone
ring-downs (a dip to ~-990 with the baseline at 0) sat in the bottom half of
each mini-box with the top half blank — visibly off next to Blastware. Scale
each mini-plot to its actual data range with a small pad instead, and draw a
faint zero baseline, so the ring-downs and the mic pulse train fill their boxes
the way BW draws them.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-15 05:39:53 +00:00
serversdownandClaude Opus 4.8 ab9d84fde6 feat(report): render the sensor-check strip + report polish 
Wire the decoded sensor self-check waveforms (previous commit) onto the event
report PDF, and fold in two related waveform-panel cleanups.

Sensor-check strip (matches Blastware):
  * ReportData gains sensor_check_waveforms; gather_report_data decodes it from
    the retained raw BW binary (store.paths_for) at report time — no ingest or
    .h5 change, waveform events only.
  * _draw_waveform_subplot now draws a narrow right-hand strip of per-channel
    mini-plots (MicL pulse train + Long/Vert/Tran ring-downs) aligned to the
    lanes, captioned "Sensor Check".
  * stats table gains the "Frequency" / "Overswing Ratio" sub-rows under Sensor
    Check (7.5/7.7/7.3 Hz, 3.6/3.3/3.7), formatted to 1 decimal like BW; values
    come from the already-parsed sensor_check scalars.

Cleanups (pre-existing, in the same panel):
  * fix the stacked-lane y-tick collision — adjacent lanes' -1.0 / 1.0 labels
    overprinted at the shared boundary; prune the extreme ticks (MaxNLocator
    prune="both") so each lane shows clean interior ticks only.
  * fix the header serial+firmware line running off the right page edge —
    tighter right-column indent + BW's slightly smaller 7.5pt header.

Tests: sensor-check + compliance + geo-scale + fft all green (15). The
test_bw_ascii_report failures are pre-existing (gitignored decode-re fixtures
absent in this worktree), unrelated to this change.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-15 05:33:38 +00:00
serversdownandClaude Opus 4.8 6341432524 feat(series3): decode sensor self-check waveforms from the binary 
The Blastware Event Report draws a "Sensor Check" strip on the right of the
waveform panel — the little traces the unit records when it pulses each sensor
before monitoring. Those live in the series-3 binary's trailing block, after
the main waveform record-chain and the per-channel calibration records, as four
length-prefixed records tagged 0x3c-0x3f (Tran/Vert/Long geophone ring-downs +
MicL pulse train). Reverse-engineered against 7 BE12844 oracle events.

New minimateplus/sensor_check.py: decode_sensor_check(raw) locates the record
chain (validated by walking the ids 0x3c->0x3f via their length prefixes) and
decodes each record's delta stream (payload[20:len-8]) with the same 10/20/30/00
delta-block tags as the main waveform codec, from an anchor of 0. Returns
{Tran,Vert,Long,MicL: [samples]} in raw 16-count units, or {} when absent.

Validated: mic pulse-train zero-crossing frequency = 20.1 Hz (exact match to
BW's mic Channel Test freq); geophone ring-downs are consistent ~-990 raw
deflections that damp to a ~-310 settle across all 7 events (a fixed
calibration pulse, so near-identical every run).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-15 05:26:28 +00:00
serversdownandClaude Opus 4.8 dc74c97ade feat(report): size the USBM compliance chart to match Blastware 
The compliance chart on the event-report PDF was correctly drawn but far
too small ("it's tiny") — a ~2.6in square dropped between the mic and
stats rows.  Resize + reposition it to match Blastware's Event Report,
measured directly off a BW reference PDF (n844lqhbzt0w) rasterized with
fitz: the chart data box now spans figure fractions x[0.489,0.951]
y[0.502,0.867] — a ~3.9in square running from just under the header down
through the stats band, hard against the right page margin, exactly as BW
draws it.  Title updated to BW's "USBM RI8507 And OSMRE".

To clear room for the BW-sized chart (waveform layout only):
  * _draw_stats_table gains bbox_width/col_widths/fontsize params; the
    waveform layout packs the Tran/Vert/Long table into the left ~0.42 so
    its columns no longer sit under the chart.  Histogram layout keeps the
    wider defaults (byte-identical output; it has no compliance chart).
  * the mic block's long "Channel Test Passed (Freq … Amp … mv)" line gets
    a tighter indent + one-point-smaller font so it ends before the chart's
    left edge instead of running behind it (_kv gains a fontsize param).
  * the Peak Vector Sum line left-aligns under the compacted table (one pt
    smaller) so it clears the chart's bottom-left tick labels.

Chart placement centralized in the _COMPLIANCE_BOX constant. No change to
the compliance math, the scatter, or the histogram report.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-14 22:56:44 +00:00
serversdownandClaude Opus 4.8 95f926c318 feat(report): enlarge the compliance chart to a full upper-right panel 
The chart was cramped into the short mic band (~2in) and rendered tiny. Move it
to its own large square panel (_draw_compliance_panel) spanning the mic + stats
rows on the right, clear of the stats columns — matching Blastware's Event
Report proportions. _draw_mic_and_usbm now draws only the mic block.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-14 20:33:09 +00:00
serversdownandClaude Opus 4.8 6ad4fd73dd fix(compliance): square plot box (set_box_aspect) so the chart isn't squashed 
The compliance chart sits in the short, wide mic-and-USBM band on the event
report; without a fixed aspect matplotlib stretched it wide-and-short. Force a
square plot box, which is how log-log compliance charts are conventionally drawn.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-14 20:21:17 +00:00
serversdownandClaude Opus 4.8 db818f716c feat(report): draw the USBM RI8507 compliance chart on the event report 
Replace the "[compliance chart coming soon]" placeholder in
_draw_mic_and_usbm with a real inset axes calling
sfm.compliance.draw_compliance_chart on rd.channels / rd.sample_rate_sps
(the full-rate in/s waveform samples). Title updated "USBM RI8507 And OSMRE"
→ "USBM RI8507" — we draw only the RI8507 lines (Drywall 0.75 + plaster 0.50);
the OSMRE overlay is dropped by choice.

Waveform events only (the histogram layout has no USBM chart). Falls back to a
"(no waveform data)" note when samples are unavailable. Closes the 1.0
compliance-chart blocker.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-14 20:18:29 +00:00
serversdownandClaude Opus 4.8 dad35e47fe feat(compliance): USBM RI8507/OSMRE compliance chart + reference doc 
sfm/compliance.py renders the velocity-vs-frequency blasting compliance chart
Blastware draws on its Event Report:
- limit_at()/limit_curve() — the RI8507 Fig B-1 / 30 CFR 816.67 curve as data
  (Drywall 0.75 + plaster 0.50 lines): 0.030in low-freq bound, plateau, 0.008in
  rising diagonal to a 2.0 in/s cap at ~40 Hz, drawn continuous.
- channel_compliance_points() — the per-cycle (freq, peak-velocity) scatter by
  the zero-crossing method (matches Blastware; cloud ceiling = channel PPV).
- draw_compliance_chart() — matplotlib rendering (both lines + scatter, BW tick
  scales + channel markers).

Verified against 7 BE12844 Blastware reports. docs/ri8507_compliance_curve.md
captures the curve construction, the SHM basis, and the scatter method.

Not yet wired into report_pdf.py — that placeholder is the next step.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-14 18:34:18 +00:00
serversdownandClaude Opus 4.8 2902ab373e feat(fft): Blastware-compatible channel FFT (waveform_fft) 
channel_spectrum(samples, sps) → the single-sided amplitude spectrum Blastware's
FFT Report draws, and dominant_frequency() picks its peak in the 2–250 Hz band.

Reverse-engineered against 7 BE12844 (MiniMate Plus) events with Blastware FFT
reports as ground truth. Recipe: DC-remove, NO window (a window smears the peak
and worsens the match), zero-pad to 4096 (→ 0.25 Hz bins at 1024 sps — the
resolution every reported dominant frequency lands on), single-sided 2/N
amplitude. Reproduces Blastware's dominant frequency to the exact bin on all
28 channels and the amplitude to report precision.

This is the missing piece for both the USBM RI8507 compliance chart (its scatter
is these (freq, amp) points vs the limit curve) and the FFT view.

Pure numpy, series-agnostic (feed it in/s samples from either decoder). The 7
events land in tests/fixtures as the oracle (force-added past the fixtures
gitignore, matching 5-11-26 / decode-re-5-8-26).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-14 17:15:16 +00:00
serversdownandClaude Opus 4.8 11e3e515f3 feat(seismo_lab): Inspector tab — annotated hex reader for Series-3 binaries 
New top-level "Inspector" tab: open any Series-3 waveform binary and read it as
a colour-coded hex dump driven by binary_annotate. Each region is labelled with
its offset range and size (header / STRT / per-channel sample records / footer),
and everything the decoder can't account for is painted UNKNOWN (red) so gaps
stand out — the point being to comb for undecoded data (e.g. a stored FFT/
spectral block). A summary shows total size, region count, and % unknown.

Read-only reader/translator; Series-3 only for now (Series-4 later). The GUI
needs tkinter + a display (not available in the dev venv); the annotator core it
calls is unit-tested headless.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-12 05:27:43 +00:00
serversdownandClaude Opus 4.8 845ec38f96 feat(inspector): Series-3 binary structural annotator (binary_annotate) 
annotate_blastware_binary(raw) → a gap-free tiling of labelled Spans
(header / STRT / per-channel sample records / footer / unknown) for a hex
viewer to paint. Every byte is covered; anything the decoder can't account
for is a first-class `unknown` span, so undecoded regions stand out.

Composes the existing waveform_codec.walk_records over the body between the
STRT record and the 26-byte footer. On the cracking fixtures this already
surfaces a ~1700-byte undecoded trailing region (stream-end marker + serial +
…) per file — a candidate home for stored spectral/FFT data.

TDD: tests assert the spans tile the whole file, STRT is located, the geo
sample records are labelled, and the footer is last.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-12 05:27:43 +00:00
serversdownandClaude Opus 5 88c0e2b765 chore(release): v0.30.0 — series-4 correctness 
Bumps package version, README banner, CLAUDE.md header and TOOL_VERSION to
0.30.0, and cuts the CHANGELOG entry for the Thor / Micromate decoder work.

Also documents the previously-unreleased event-report PDF fix (91b9b45),
which had landed on dev without a CHANGELOG entry.

TOOL_VERSION is bumped so refreshed sidecars carry the new codec version and
a future fix gates regeneration correctly. Note it was NOT required to
unblock this backfill: all 4,529 prod series-4 sidecars sit at 0.18.0-0.23.0,
well under the previous 0.29.0, so they were never being skipped. Verified by
dry-running scripts/backfill_thor_events.py against a copy of the prod store
(refreshed=379, skipped=0) both before and after the bump.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ru8Lg9HkkYvX9VWWo65SmL
 2026-09-12 04:58:07 +00:00
serversdownandClaude Opus 5 904522a9c5 fix(codec): 40 NN int16 blocks are not capped at NN=8 
data_block_len() rejected any `40 NN` block with NN > 0x08. That guard had
no evidence behind it: every corpus available when it was written used only
NN in {1,2,3,4,8}, so it was never exercised. Loud UM12947 events use NN of
12, 16, 20 ... up to 196.

Because walk_body/run stop at the first unrecognised tag rather than
raising, rejecting those blocks surfaced as silently short channels -- e.g.
Tran 1812 / Vert 2132 / Long 2324 on a file whose export carries 2324 for
all three. The real bound is the buffer; the caller additionally clamps to
the record end.

Verified against Thor's own CSV exports for UM12947 (2025-07-14 .. 09-25,
167 waveforms, supplied as CSV.zip):

  length mismatches   22 -> 0
  per-sample exact    1,476,242 / 1,476,249

These are NOT truncated recordings, which was the competing hypothesis --
the exports carry the full sample count.

tests/test_waveform_codec.py asserted the cap as intended behaviour. That
assertion encoded an assumption, not a verified fact, and is replaced with
one pinning the opposite plus the evidence.

Across all three ground-truth corpora: 459 waveform files,
3,807,158 / 3,807,165 samples exact. Production IDFW is now 575/575 with
zero truncations and zero decode failures (median PPV error -0.0007% across
8 units). Series-3 re-verified unchanged at 14,338/14,338.

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 (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.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ru8Lg9HkkYvX9VWWo65SmL
 2026-09-11 05:05:46 +00:00
serversdownandClaude Opus 5 c07aaa552c fix(series4): support mic-disabled (3-channel) Thor units 
Verified against a second Thor corpus (9-10-26-csv-req: UM11402, UM12947,
UM20147) with per-sample CSV exports: 139/139 waveforms exact
(1,273,380/1,273,380 samples) and 877/877 histograms within 2% of Thor's
reported PPV -- up from 66.9% and 56.6%.

Some units run with the microphone disabled, which changes two structural
things that were both hardcoded to the 4-channel shape:

- Waveform body head sat below the scan floor. A 3-channel unit has a
  shorter fixed header and puts its record chain head at 0x0dba, under the
  old _BODY_SCAN_FLOOR of 0x0E00. 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 -- Vert came up exactly 512 samples
  short. Floor lowered to 0x0C00. The body-offset scoring also had to stop
  requiring four channels, or `equal` is permanently False for these events
  and the pick falls back to raw sample count.

- Histogram interval record is 56 bytes, not 72. It is
  16 * n_channels + 8, and is not inferable from the segment length alone.
  The interval count now comes from the segment's cumulative counter
  (n = counter - prev_counter) and the stride is derived from it. Assuming
  72 read 7 intervals out of every 10-interval segment, then walked off
  alignment into garbage that decoded as ~10 in/s peaks -- inflating some
  files' PPV by up to 191,000%. Also recovers 4 files that previously
  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.
Series-3 unaffected (no shared-codec change in this commit; last full run
14,338/14,338).

Known open, diagnosed but NOT verified: the remaining 22 unequal + 1 failing
production IDFW files (all UM12947, 2025-07-14..09-23) stop the block walker
on tag 40 0c. data_block_len() caps the 40 NN int16 block at NN > 0x08 while
those files use NN up to 196. Both verified corpora only ever use
NN in {1,2,3,4,8}, so the cap is untested there and lifting it leaves both at
100.000% -- which is not evidence it decodes these correctly. Deliberately
not shipped; needs Thor CSV exports for UM12947 in that date range.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ru8Lg9HkkYvX9VWWo65SmL
 2026-09-10 20:00:56 +00:00
serversdownandClaude Opus 5 726c2ce1b5 fix(series4): 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). Those 1,012
paired files were in the corpus all along; the decoder had been pinned to
a superseded walker on the stated grounds that "Thor has no ASCII ground
truth in the corpus and its geo scaling is separately suspect". Both
premises were false.

  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, 8 units         -3.3%  -> -0.001%

Four independent root causes:

- Geo LSB was 0.0003, the 4-dp *display rounding* of the real
  0.000310308 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) left in
  unwritten IDFH slots. IDFH 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. Runs over ~4 hours lost their tail, often the peak.
  540/858 corpus files affected.

- Record mode 00 00 (raw int16, 10-byte header) was unhandled and fell
  through the dispatch, silently dropping each channel's first 512
  samples -- the long-standing "loud events truncate" symptom.
  MODE_ABSOLUTE is now also accepted as a segment-0 preamble.

- The body-offset search matched 00 02 00 *inside* record headers,
  selecting a candidate part-way down the chain and decoding a
  rotation-shifted body. It now anchors on record headers and takes the
  chain head (6 ms/file).

Also fixes the separately tracked "UM-series decodes ~1000x low" bug.
Series-3 re-verified unchanged at 14,338/14,338 exact after the shared
waveform_codec change.

Known open: 41/575 prod IDFW files (7%, mostly UM12947/UM20147) decode
with unequal channel lengths and also fail metadata extraction -- a
different header variant with no Thor export in the store.

NOTE: this is a codec change; the Thor store owes a regeneration via
scripts/backfill_thor_events.py.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ru8Lg9HkkYvX9VWWo65SmL
 2026-09-10 18:06:14 +00:00
serversdownandClaude Opus 4.8 91b9b4578c fix(pdf): shared geo Y scale across Long/Vert/Tran (was per-trace) 
The event-report waveform plot scaled each geo lane to its own peak, so a small
channel filled its lane looking as big as a large one — and the "Geo: X in/s/div"
footer only reflected whichever channel was checked first, so its div value was
wrong for the other two. Now all three geo lanes 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. Big events are unchanged (e.g. BE12844 stays 0.185 in/s/div).

Test-first: tests/test_report_pdf_geo_scale.py (shared scale + floor), 2 tests.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-07 23:26:42 +00:00
serversdownandClaude Opus 5 f600fee965 feat(offset): the non-motion test, and BE12599 diagnosed as a connector 
Brian noticed BE12599's 2026-08-09 event reports no ZC frequency because the
trace never crosses zero. That is the best detector in this investigation.

A geophone has no DC response, so its output must integrate to ~zero over a
record. |mean|/peak is therefore ~0 for real motion and ~1 for anything
electrical. Across 12,068 channel-events with peak >= 0.05 in/s the statistic
is bimodal with a 1.09% dead zone, and at mp >= 0.8 it returns exactly the five
confirmed units -- from physics rather than a tuned threshold. Two detectors on
different principles agreeing is the strongest corroboration the list has had.

It also settles BE11007 as NOT an offset: mp 0.75-0.89 but frac_neg 0.99 at
peaks of 7.4-9.4 in/s, i.e. a one-sided near-full-scale blast.

Journal 8e diagnoses BE12599 specifically. Its August waveforms are unipolar
impulses with an RC tail (26 ms -> 118 ms -> never recovers over 14 days), and
the fault MOVES between Long and Tran while the sensor self-check passes on
every event. A failing element cannot hop channels; a connector can -- which
also explains why the swing test never fails and why an autozero rarely helps.

Corrects 8c's claim that the spread gate is blind to onsets: of 87 BE18438|Vert
events it rejected one, the transitional record. Narrower than stated.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-09-07 19:01:28 +00:00
serversdownandClaude Opus 5 58c1fe8a96 docs(offset): mechanism campaign — five hypotheses dead, onset is a ramp 
Records the mechanism investigation in journal 8c. The headline: still unknown,
but the shape is now constrained and a long list of dead ends is closed.

Onset is a ramp of minutes-to-hours, not a step — BE18438 Vert resolved to
one-minute cadence via the histogram corpus, 50% of the excursion in 7 minutes,
>=25 intermediates, validated 75/75 against Blastware's own ASCII. That kills
both poles of the original dichotomy: not a latched digital step, not slow
component wear. What survives is a reversible two-time-constant settling
process, which is a shape constraint and not a mechanism.

Thermal, ground-motion shock, handling/redeployment, accumulated duty, age,
firmware and a mechanical element fault are each refuted or explicitly bounded,
with the power behind every negative stated.

Retracts two claims this journal carried: polarity consistency was a tautology
of offset_scan3's spread gate, and the fleet is 8-9 units rather than 5 once
that gate is dropped. Also notes the gate is blind to onsets by construction --
it rejects a moving floor, and it rejected the one record where the ramp shows.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-09-06 09:33:12 +00:00
serversdownandClaude Opus 5 a27310c3c6 docs(changelog): record the BlastMate serial fix under v0.29.0 
The release is bumped but not tagged, and the fix is now in dev — which is
what gets built — so the notes would otherwise understate the build. No
TOOL_VERSION change: the fix alters which serial an import is filed under,
not any decoded value, so no backfill is owed.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-09-06 08:02:32 +00:00
serversdown 233bfcefd0 Merge feat/offset-histogram-scan: BlastMate serials + the histogram scan 
Two things, both starting from the same root cause.

The BW filename encodes the serial NUMBER only; the two-letter family prefix
is not in it. Every offset scanner synthesised "BE", which mislabels the four
BlastMates in the archive (BA9229, BA10060, BA10895, BA15957) and — in the
store's import path — would have filed a BlastMate under a unit that does not
exist. BlastMates are Series III and byte-identical to MiniMate Plus, so the
serial string was the only thing blocking SFM support; reading it from the
file body is the whole fix.

Separately, the archive's 63,535 histograms were scanned for offsets for the
first time. The result is largely a documented dead end — the detector finds
2 of the 5 confirmed units and a clean histogram is not evidence of health —
but it produced the BA10895 reclassification and a labelling caveat on
offset_scan3's spread gate. Journal §8b.
 2026-09-06 08:01:52 +00:00
serversdownandClaude Opus 5 84bb53e185 docs(offset): relabel the four BlastMate units BA, not BE 
BA9229, BA10060, BA10895 and BA15957 were reported throughout as BE — the
scanners synthesised the family prefix, which the BW filename does not carry.
Corrected across the journal with a note recording why, so the mistake is
legible rather than silently patched.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-09-06 08:00:48 +00:00
serversdownandClaude Opus 5 9ceff65bfb fix(sfm): read the serial family prefix from the file, enabling BlastMates 
The BW filename encodes only the serial NUMBER — `<letter><3 digits>`, so
`L895…` is 10895 and nothing more. The two-letter family prefix is not in it:
"BE" is a MiniMate Plus, "BA" a BlastMate. Both are Series III and their
files are byte-identical in every way that matters — all 1,493 BlastMate
binaries in the DL2 archive decode through the existing codec at 100%, same
four channels — so the serial string was the only thing standing between SFM
and BlastMate support.

Two sites synthesised the prefix and got it wrong:

- waveform_store `_serial_from_bw_filename` returned f"BE{num}" on import, so
  a BlastMate event was filed under a unit that does not exist, silently, and
  Terra-View read it straight through. Split into
  `_serial_number_from_bw_filename` (the number, which the filename really
  does carry) and a new `_serial_from_bw_bytes` that reads the serial out of
  the body and accepts it only when its numeric part agrees with the
  filename. save_imported_bw now prefers hint -> body -> filename guess.
  Verified against real archive bytes for BA9229, BA10060, BA10895, BA15957
  and BE9558/BE11529/BE18003.

- client `_decode_0a_partial_header` searched for a literal b"BE" in the
  monitor-log partial record. On a BlastMate that returns -1 and skips the
  whole block, so the geo threshold went missing along with the serial. Now
  matches any two-letter prefix, and requires the NUL terminator — stricter
  than the bare two-byte search it replaces.

Nothing to migrate: no BlastMate events are in prod. The archive's BA units
last recorded 2018-10 (BA9229, BA15957), 2023-08 (BA10895) and 2023-11
(BA10060), and the prod backfill only reaches back to ~May 2025.

21 tests. Suite: 309 passed, same 16 pre-existing failures as at HEAD
(15 missing ASCII fixtures + one peak_values assertion, all untouched here).

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-09-06 07:58:00 +00:00
serversdownandClaude Opus 5 9982938b0b fix(offset): read the real serial from the file body, not "BE" + the number 
The BW filename encodes only the serial NUMBER — `<letter><3 digits>` where
letter = chr(ord('B') + serial // 1000), so `L895…` decodes to 10895. The
two-letter family prefix is not in the filename at all, and every offset
scanner synthesized it as f"BE{num}".

Four of the 43 archive units are BA, not BE. Their binaries say so plainly:
BA9229, BA10060, BA10895, BA15957. Brian caught BA10895 by recognising that
no such unit as BE10895 exists.

serial_of() now reads the serial string out of the file body and falls back
to the old synthesis only when no matching string is found. No analysis
changes: grouping was by the numeric part, which was always correct, and no
unit number maps to more than one serial (checked across all 43).

The same assumption is live in two production sites and is NOT touched here,
because fixing ingest renames rows a running store and Terra-View already
reads them:
  - sfm/waveform_store.py:870  `return f"BE{serial_num}"` on import
  - minimateplus/client.py:2538 `raw_data.find(b"BE")` in the monitor-log
    partial-record decode, which yields serial=None on a BA unit

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-09-06 07:48:54 +00:00
serversdownandClaude Opus 5 1daf693b32 feat(offset): scan the histogram corpus — the other 90% of the archive 
offset_scan3.py covers only waveforms (6,577 unique binaries). The archive
also holds 63,535 unique histograms, which the pre-trigger method cannot
touch: a histogram carries no samples, only a per-interval per-channel peak.

scratch/offset_hist_scan.py scans them — 63,505/63,535 decoded (99.95%),
43 units, 77.9M intervals. It emits every candidate floor statistic per
(file, channel) rather than deciding anything, so thresholds get calibrated
against the waveform ground truth instead of guessed.

Journal §8b records the outcome. What survives is a site-quiet-gated
cross-channel differential that independently confirms BE18438|Vert and
BE9558|Tran+Long with a clean 2.5x separation gap and 0.037% day-level false
alarm, threshold-insensitive across a 2.3x span — the first operating point
in this investigation to pass that test cleanly.

What it does not do, recorded just as plainly: it finds 2 of the 5 confirmed
units, not 5. DC leakage into the interval peak is bimodal (0.9 on BE18438,
0.02 on BE12599), so a negative histogram result is not evidence of health.
Per-channel attribution is not established (channel-scramble p = 0.769) and
timing resolves to ~a month, not a day.

Two dead ends buried for good: the absolute floor is retired (66% of its
discrimination is a day/site confound), and zero-fraction is structurally
impossible — the device clamps every interval peak at >= 1 A/D count.

Two findings independent of the histograms:
- offset_scan3's spread<=0.02 gate discards 18.8% of rows with |pre|>=0.025,
  concentrated on 41 unit-channels currently labelled clean; 4 would be
  sustained positives without it. The fleet label is three-state, not two.
- The waveform corpus observes ~7% of the days a unit was deployed.

BE10895 is reclassified from transient to a genuine Vert fault of a different
subtype: 49.4% single-axis-dominant events, the highest in the fleet, all on
Vert. The other six marginal units are clean.

Not done: the 11 thin-coverage units were not screened, and no completeness
audit was run.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-09-05 02:08:36 +00:00
serversdownandClaude Opus 4.8 89ad7cf49d chore(release): v0.29.0 — offset detector + false_trigger_reason (first prod-bound build since 0.27.0) 
Bumps TOOL_VERSION 0.28.0 -> 0.29.0 and pyproject/CLAUDE/README 0.27.0 -> 0.29.0,
and dates the CHANGELOG section. v0.28.0 (offset DC-baseline detector) was
version-bumped in-tree but never tagged or deployed, so 0.29.0 is the first build
to carry both it and the false_trigger_reason column to prod.

Pairs with Terra-View >= 0.24.0. false_trigger_reason auto-migrates on startup;
the offset detector needs the shape backfill (scripts/backfill_event_shape.py) on
the prod store to populate shape_offset* on existing rows.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-04 21:42:11 +00:00
serversdownandClaude Opus 4.8 523f22c96b Merge feat/ft-reason: optional false_trigger_reason (offset) FT subtype 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-04 21:12:04 +00:00
serversdownandClaude Opus 4.8 cfdd153b5a docs(changelog): false_trigger_reason column under [Unreleased] 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-03 21:08:04 +00:00
serversdownandClaude Opus 4.8 c0cf6547d9 feat(ft): optional false_trigger_reason ("offset" etc.) as an FT subtype 
A reason records *why* an event is a false trigger. It is optional (plain
FT flags still record no reason) and is a subtype of the FT flag: setting a
reason implies false_trigger=1, and the reason is cleared whenever FT ends
up 0 (confirm-real, clear-FT, set_false_trigger(false)). Twin propagation
carries the reason to the histogram/waveform twin alongside the FT flag.

New nullable `false_trigger_reason TEXT` column (schema + _migrate ADD
COLUMN only — not the Migration-1 rebuild). 7 tests.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-03 20:53:57 +00:00
serversdownandClaude Opus 4.8 4cf0fda804 chore(release): v0.28.0 — offset (DC-baseline) false-trigger detector 
Bumps TOOL_VERSION 0.27.0 -> 0.28.0 (drives the SFM /health + OpenAPI version
too). Rolls CHANGELOG [Unreleased] -> v0.28.0.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-02 04:55:42 +00:00
serversdownandClaude Opus 4.8 3554d00583 feat(offset): DC-offset detector productionized into the shape pipeline 
Productionizes the validated scratch/offset_scan3.py: a DC offset (baseline
shifted off zero — sensor bumped/settled/drifted) is |median(pre-trigger)| >= 5
counts (0.025 in/s) AND flat across pre/mid/end thirds (spread <= 0.02); a
transient moves one third and is rejected by the spread test.

- shape_metrics: offset_from_samples / offset_from_h5 (reads .h5 samples +
  pretrig_samples attr; range-aware via the .h5's in/s float samples)
- events schema: shape_offset / _axis / _pre / _spread (via _SCHEMA + the
  _migrate ADD COLUMN loop only; NOT the Migration-1 rebuild), threaded through
  insert + upsert mirroring shape_*
- ingest: computed at all three waveform_store save paths alongside shape
- backfill_event_shape: also computes + stores (and stale-clears) offset
- exposed via /db/events automatically (SELECT *)

Gating to waveforms is done downstream in terra-view ft_suspicion (mirrors how
shape is ignored for histograms), not at the SFM call sites. 13 new tests.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-09-02 04:47:01 +00:00
serversdownandClaude Opus 5 b29ca50b35 docs: point CLAUDE.md at the shared stack context doc 
The stack-level context (version pairing across seismo-relay / Terra-View /
SLMM, and which repo a change belongs in) now lives version-controlled at
terra-view/docs/tmi-stack.md, symlinked as ~/CLAUDE.md. Reference it here so
the three project docs are symmetric.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-29 07:53:04 +00:00
serversdownandClaude Opus 5 e07f76dd31 docs: correct the v0.27.0 backfill claim — prod needs no backfill 
The v0.27.0 notes said prod held 4 histograms that would stay empty until a
backfill. That was wrong, and asserted without checking.

Verified: all four recovered files (K440HJCN.3C0H, K557IF1U.8K0H,
T191HVNP.0S0H, T193L0XM.CI0H) are archive-only — none appears in the production
store or the events DB. Re-running stride detection over the prod store's
10,215 histogram binaries under both the old and new code shows 0 files whose
decode changes.

So the partial-final-block fix is forward-looking: it matters for future
ingests of sub-minute histograms with a partial final block, not for anything
already stored.

TOOL_VERSION still moves with the release, so a future backfill run will
regenerate the whole store instead of skipping. Harmless — byte-identical
output for every stored file — but it costs the full ~2 hours on the NAS, so
it should not be started casually.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-29 06:12:19 +00:00
serversdownandClaude Opus 5 8e808b09d4 chore(release): v0.27.0 — decoder verified at scale; offset investigation 
Bumps pyproject, TOOL_VERSION, README and CLAUDE.md to 0.27.0. sfm/server.py
now derives its version from TOOL_VERSION (c8c4ec2), so that constant is the
single source of truth for the service version and the sidecar stamp alike.

What ships:
  - histogram partial-final-block fix (4 files recovered, 0 regressed)
  - interval-based find_twins matching (terra-view #102 sub-task 2)
  - /health no longer reports a hard-coded 0.1.0
  - 793 NUL bytes stripped from CLAUDE.md (made grep skip it as binary)
  - docs/offset_investigation.md, and the offset detectors
  - scratch/verify_against_ascii.py

Verification: the series-3 codec now decodes 14,338 / 14,338 archive pairs
exactly against their Blastware ASCII exports (1,249 waveform + 13,089
histogram, 45 units, back to 2018) — 11x the ground truth the prod store
carried, and it supersedes the old "per-sample on 11% of files" caveat.

Independent check on the scale: 19,244 healthy channel-events sit at a
pre-trigger floor of exactly 0.000 (62.7%), 94.5% within one quantisation
unit, median +0.0000. No zero-point bias in the decoder.

⚠ TOOL_VERSION moved, so the next prod backfill regenerates the whole store
(~2 hours on the NAS). That is intended — it is what publishes the 4 recovered
histograms — but it is not a no-op; schedule it.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-28 22:21:47 +00:00
serversdownandClaude Opus 5 ad84a04404 feat(offset): detector v3 — pre-trigger floor with a constant-floor test 
Brian's method, and better than v2's whole-record median: the pre-trigger
window is definitionally quiet (the buffer captured before the trigger fired),
whereas a median is merely robust to the event. Requiring the floor to hold
across pre-trigger / middle / end rejects transients that a median cannot.

    per channel:  pre/mid/end medians, spread = max - min
    offset when   |pre| >= floor AND spread <= 0.02 in/s
    real fault    >= 3 consecutive flagged events on that channel

The empirical noise floor justifies the threshold and validates the decoder:
across 19,244 non-flagged channel-events the pre-trigger floor is 62.7% exactly
0.000, 94.5% within +/-1 quantisation unit, median +0.0000, mean -0.0008. There
is no systematic zero-point bias — an independent confirmation of the
32000-count geo scale.

The result is threshold-insensitive across a 2x range (0.020 to 0.040 in/s),
which is what separates a real signal from a tuned one:

  FINAL: 5 of 45 units (11%) — BE9558, BE11529, BE12599, BE13117, BE18438

BE11007 and BE10895 drop out; the spread test identifies them as transients
rather than pedestals. v1's 11% headline was right by luck — it included
BE11007 and named the wrong channel on most units.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-28 21:18:33 +00:00
serversdownandClaude Opus 5 1fdc665675 fix(offset): retract the v1 detector — per-channel median, not dominant-axis mean 
Brian challenged the v1 finding that offsets "come and go", against field
experience that a unit which develops one stays broken until the geophone is
replaced. He was right; v1 had two flaws, both of which manufactured false
recoveries:

1. It scored only the axis with the largest peak, so a real event on one axis
   hid a persistent pedestal on another. BE12599 on 2026-08-21 read "clean"
   because Long had a 1.065 in/s event, while Tran sat at +0.4732 in/s and was
   never examined.
2. It used the mean, which a real transient perturbs. The median is the resting
   baseline and a blast does not move it. Same event, Long channel:
   mean +0.0783 vs median -0.0050.

offset_scan2.py flags a CHANNEL when |median| >= 0.025 in/s (5 A/D counts,
Instantel's own criterion) and treats >=3 consecutive flagged events as the
real signal. No m/p ratio guard is needed — that existed only to compensate for
the mean.

Corrected results:
  units with any flagged event        6 -> 19 of 45
  units with a sustained pedestal     8 of 45 (18%)
  runs >=3 consecutive                29;  1-2 event runs (noise) 69

Also corrected: the affected channel is most often Vert, not Tran (v1 named
whichever axis had the largest peak, so it was frequently wrong). BE10895 and
BE18003 were invisible to v1. BE12599's fault began 2026-08-14, not 08-17.

The decode itself was never in question and is confirmed against Blastware's
own ASCII export: on K558LJN3.BK0W, BW shows Tran parked at +0.265..+0.375 in/s
for the entire record while Vert and Long sit at ~0.005 — Instantel's "parallel
lines above or below the zero line".

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-28 20:41:20 +00:00
serversdownandClaude Opus 4.8 c8c4ec2b9f fix(sfm): /health reports the real service version, not a stale 0.1.0 
terra-view's SFM Admin page (/admin/sfm) displays whatever /health returns for
`version`. That was hardcoded to "0.1.0" and never bumped, so the page showed
0.1.0 while the service was actually 0.26.0. Point both /health and the FastAPI
OpenAPI version at the release-bumped TOOL_VERSION (single source of truth), so
they can't drift again. Adds httpx-free regression tests (call health() directly).

Note: minimateplus.__version__ is separately stale at 0.1.0 — left as-is here
(nothing user-facing reads it; touching the package __init__ risks import order).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-08-28 20:39:51 +00:00
serversdownandClaude Opus 5 5f1ee5ba91 docs: offset investigation journal; strip NUL corruption from CLAUDE.md 
Adds docs/offset_investigation.md — a dated journal of the "offset" hardware
fault, in the style of the codec status docs: findings with provenance, dead
ends kept with the reason they died, and per-unit case files.

Contents:
  - base rate 5-6 of 45 units (11-13%) over the DL2 archive, 2018-2026,
    confirming rather than overturning the earlier 2-of-21 estimate
  - the detector, with the rationale for each term and its known blind spot
    (event traces carry real motion, so only trace-dominating offsets show)
  - the bimodality result: relaxing the amplitude floor 11x adds no new units
  - Instantel's own procedure and thresholds from their FAQs 13-0-21 / 12-0-10:
    A/D-mode ">5 counts", the autozero key sequence, and the 2027-2069 X1/X8
    acceptance window that explains the ~10% field success rate of a re-zero
  - four ruled-out hypotheses, each with the evidence that killed it:
    condensation, clipping, the sensor check as a predictor (102 offset events,
    zero failures — a grossly offset unit passes its own self-check), and the
    calibration-timing correlation (confounded, one unit per time bucket)
  - open questions, chiefly whether SUB 0x0E carries the autozero numbers

Cross-referenced from CLAUDE.md and Appendix E of the protocol reference
(whose CRLF line endings are preserved).

Separately: CLAUDE.md had 793 NUL bytes appended after its last line. They
predate this work (present at least as far back as e42956a / v0.21.0) and made
grep treat the file as binary, silently skipping it. Stripped.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-28 20:19:30 +00:00
serversdownandClaude Opus 5 4839ddfa0e fix(scratch): dedupe the DL2 Sent/ mirror; correct the recovered-file count 
The DL2 export keeps a byte-identical `Sent/` copy of its root, so walking it
counts every binary twice: 127,035 histogram paths are 63,535 distinct files,
and 13,077 waveform paths are 6,577. offset_scan.py now keeps the first
occurrence of each basename.

Corrects the previous commit's changelog claim of 8 recovered files — it is 4:
K440HJCN.3C0H and K557IF1U.8K0H (stride 252), T191HVNP.0S0H (92), T193L0XM.CI0H
(612). Still zero regressions. The per-unit breakdown reading exactly 2-2-2-2
should have given the doubling away.

The 14,338-exact verification result is unaffected: ASCII exports are not
mirrored (14,340 paths, 14,340 distinct names), and the harness enumerates
those rather than the binaries.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-28 20:19:30 +00:00
serversdownandClaude Opus 5 14e997b20c fix(histogram): partial final block no longer discards the correct stride 
detect_multi_interval_stride() confirmed a candidate stride on a third block
header whenever the body was long enough to contain one. But a body can exceed
two strides and still hold only two real blocks: a partial final block leaves
trailing padding. BE18193 T193L0XM.CI0H — 51 intervals at 2 s, i.e. one full
30-interval block plus a 21-interval remainder in a 2787-byte body — had every
decisive check pass at stride 612 (header at 0, header at 612, block counter
256 -> 257) and was then rejected for the absent third header at 1224. It
decoded to nothing.

A missing third header now means end-of-stream rather than disqualification.
The block-counter check is untouched — that is the test that prevents the
false positives which once handed 9,082 standard-block files to the
multi-interval walker.

Found by running the full DL2 archive against its preserved Blastware ASCII
exports (14,340 paired files, 11x the previous ground-truth corpus).

Measured over 127,035 archive histogram binaries:
  recovered 8 files (strides 92, 252, 612; BE18193, BE18191, BE9557, BE9440)
  regressed 0 files
Full-corpus verification: 14,337 -> 14,338 exact of 14,338 decodable pairs
(the 2 excluded are series-4 IDF, a different codec).

Also adds scratch/verify_against_ascii.py (per-sample decoder verification
against BW exports, with a saturation carve-out — BW clamps clipped events to
the range max while the decoder reports true counts) and scratch/offset_scan.py.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-28 20:19:30 +00:00
serversdownandClaude Opus 4.8 75ac610c61 fix(twins): interval-based histogram/waveform matching in find_twins (#102 sub-task 2) 
A real trigger is recorded twice — as a triggered waveform (stamped at the
trigger instant) and inside the scheduled histogram whose interval contains it
(stamped at the 7am/7pm interval start). The two twins routinely differ by
HOURS, so the old ±5-minute window in find_twins silently missed them — which
broke review propagation (flagging one twin left its twin unflagged).

Twins are now matched by: same serial + identical peak_vector_sum + OPPOSITE
record type + the waveform's timestamp falling within the histogram's interval
(bounded by the next same-serial histogram). Matching keys off record timestamps
(not call-in/received times, which drift with field connectivity). window_seconds
is retained but ignored.

Rewrote test_find_twins + test_twin_propagation for the new contract (incl. the
75-min-apart UM12947 case, cross-type exclusion, containing-interval selection,
open-ended latest interval). Full suite: 264 passed; the 16 failures are
pre-existing (missing gitignored fixtures + a v0.26.0 codec case), unchanged
from baseline.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-08-28 05:23:30 +00:00
serversdownandClaude Opus 5 dedf1f02c9 fix(release): bump TOOL_VERSION to 0.26.0 — sidecar staleness was inert 
TOOL_VERSION had been frozen at 0.21.1 for four releases despite its own
comment saying "Bump this constant and CHANGELOG.md together at release
time".  It is not cosmetic: backfill_sidecars.py decides whether to
regenerate with

    ver_ok = sidecar.source.tool_version >= event_file_io.TOOL_VERSION

so with the constant stuck at 0.21.1 and every sidecar stamped 0.21.1,
a backfill WITHOUT --force skipped the entire store.  That is precisely
the failure the check exists to prevent, and it means every sidecar
regenerated during the 0.26.0 decode work is stamped 0.21.1 while having
been produced by 0.26.0 code.

Verified: a non-force dry-run over the snapshot now reports
written=11603 skipped(uptodate)=0, where before it would have skipped
all 11,603.  Prod therefore does not need --force to pick up the decode
corrections — the version difference alone is enough.

Note the installed dist metadata reads 0.12.0, older than the constant,
so the best-effort "prefer installed metadata when newer" path correctly
defers to TOOL_VERSION.

Also bumps the README header, which still read v0.22.0.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-27 17:22:16 +00:00
serversdownandClaude Opus 5 b2ef02ebcc chore(release): v0.26.0 — series-3 decode correctness 
Two body-model rewrites, a systematic scale error affecting every
geophone reading the system ever produced, a recovered file format, and
two artifact-hygiene bugs where stale files outlived the decodes that
made them.

  - geo full scale is 32000 ADC counts, not 32768 (every reading 2.34% low)
  - the waveform body is a record chain, not a tag stream
  - the histogram block is big-endian, with a terminal tail
  - sub-minute intervals pack several per block (415 files recovered)
  - three more defects found by a full-corpus sweep, each masking the next
  - stale .h5 files and stale shape_* columns are now cleared, not left

All 11,603 series-3 binaries in the production snapshot pass every check.
Ground truth: 1,211/1,211 histograms exact per-interval, 75/75 waveform
sample counts exact, multi-interval fixture exact on all 45,680 values.

Also corrects a changelog note that went stale within the same day: the
"3 of 75 events still truncate" item was resolved by the record-chain
rewrite, and the remaining open items are now listed explicitly.

CLAUDE.md gains a "Where things stand" block at the top — the header had
been reading v0.21.0, four releases behind, which is the first thing you
see when picking the project back up.

Tests: 259 passed; the 16 failures are pre-existing (gitignored
fixtures) and unchanged from baseline.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-27 16:35:47 +00:00
serversdownandClaude Opus 5 a3b69a62a6 fix(histogram): three defects found by a full series-3 sweep — 11603/11603 clean 
Swept every series-3 binary with the live decoder against five
independent checks: decode exceptions, zero samples, unequal geo channel
lengths, peaks above range full scale, decoded peak vs device-reported
PPV, and waveform length vs declared record time.

1. block[22] is NOT a constant and must not be tested.  Documented as
   always 0x00, it carries data on loud blocks, and rejecting those threw
   away the interval holding the event peak.  BE18350/T350L7HR.NL0H
   block 92 has block[22]=0x26 and a Tran peak of 0x0563 = 1379 counts =
   6.895 in/s — exactly the device-reported PPV — while the file decoded
   to 0.015 in/s.  block[0]==0, block[4]==0x0A and the 4-byte tail are
   six bytes of constraint, which is what keeps trailer content out.

2. Block-model dispatch now goes on signature strength rather than on
   whichever decoder returns first.  A multi-interval body also yields
   scattered standard-tail blocks by coincidence, so "first non-empty"
   handed 193 BE18193 files to the standard walker and produced peaks of
   149 in/s against a 10 in/s full scale.

3. Multi-interval stride detection requires the block counter to
   increment by exactly 1.  Without it the detector false-positives on
   ordinary standard-block bodies: they carry a header every 32 bytes,
   and 192 = 12 + 20*9 and 512 = 12 + 20*25 are both multiples of 32, so
   a stride "fits" while skipping 6 or 16 real blocks.  That misrouted
   9,082 files.

Partial-block garbage is trimmed within the final block only, stopping
at the first slot with a non-zero tail word or a geo peak above full
scale (2000 counts in 16-count units).  Trimming purely from the end
left garbage stranded behind a slot that happened to have a zero tail
word; trimming on the tail word alone truncated four BE9440 files by up
to 2,800 intervals.

Result: 11,603 / 11,603 series-3 binaries clean on every check.
Ground truth unchanged: 1211/1211 histograms exact per-interval, 75/75
waveform sample counts exact (73/75 fully exact, the 2 differ by 1 LSB
on rail samples), and the multi-interval fixture still matches its BW
ASCII export on all 45,680 values.

Tests: 259 passed, failure list unchanged from baseline.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-26 05:55:46 +00:00
serversdownandClaude Opus 5 306104354b feat(histogram): decode multi-interval blocks — recovers 415 files 
Sub-minute histogram intervals are packed several to a block so that
every block still covers exactly one minute of data:

    interval   intervals/block   stride
    1 minute   1                 32     <- the standard big-endian block
    15 s       4                 92
    2 s        30                612

    stride = 12 + n * 20

Block = [00][segment][ctr uint16 LE][0a][00], then n x 20-byte records of
8 x uint16 LITTLE-endian values (T_peak, T_halfp, V_peak, V_halfp,
L_peak, L_halfp, M_peak, M_halfp) plus a 2-word tail whose first word is
0000 on every real interval, then a 6-byte block trailer.

The standard 32-byte block is BIG-endian; this variant is LITTLE-endian.

The tail-word check matters: a session ending mid-block leaves buffer
garbage in the remaining interval slots, which decoded as peaks
thousands of times the real value.  Stride detection also requires at
least 2 records, since a 1-record block would have stride 32 and
collide with the standard block.

Recovers 415 files that decoded to nothing: 216 on BE18193 (2 s
intervals) and 199 on BE9440 (15 s).  Before decoding to nothing they
were being accepted by the WAVEFORM codec, which returned garbage
peaking up to 400x the device-reported PPV.

Ground truth BE9440/K440L3AQ.T70H (5,710 intervals) matches its
Blastware ASCII export exactly: 17,130/17,130 geo peaks, 22,840/22,840
frequencies, 5,710/5,710 mic dB(L).  Across all 455 affected files,
1,354/1,365 channel peaks (99.2%) match the device-reported PPV; the 11
that don't are under-reads on BE9440 where the walk stops early.

Fixture (binary + ASCII) saved under tests/fixtures/, which is
gitignored per repo practice — the ground-truth test skips when absent.

Tests: 258 passed, failure list unchanged from baseline.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-26 04:59:00 +00:00
serversdownandClaude Opus 5 4c58a532de fix(backfill): remove stale .h5 when nothing decodes; log the 415-file histogram variant 
backfill_sidecars.py skipped the .h5 write when a file produced no
samples, with the stated intent of not replacing it with an empty
placeholder.  That silently preserved output from a superseded decoder.

After the record-chain fix, 415 histogram files stopped decoding (216 on
BE18193, 199 on BE9440) but kept .h5 files whose peaks ran up to 400x
the device-reported PPV.  Those were feeding charts and the
false-trigger detector with nothing marking them.  The .h5 is now
removed in that case and the run reports stale_h5_removed.

Store-wide effect, series-3, decoded peak vs device-reported PPV:
  waveform   1307/1307 (100%), mean abs ratio error 0.00000
  histogram  4434/4435 (100%)
Both were 99% with a tail of 18 and 25 wrong files respectively.

The 415 files are a genuine unmapped format variant, not a regression:
their bodies open `00 00 00 01 0a 00` (valid block header, marker 0a at
[4], block_ctr 256) but block[28:32] matches neither known tail, and no
stride from 8 to 64 bytes places a marker at [4] consistently.  Bodies
are very large (one is 360,573 bytes).  They were previously being
decoded by the WAVEFORM codec, which accepted them and returned garbage
- so the gap pre-dates today's work; the fix only exposed it.  Logged as
an open question in the protocol reference.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 22:23:10 +00:00
serversdownandClaude Opus 5 9bb95003e9 fix(codec): the waveform body is a record chain, not a tag stream 
Supersedes the segment-header model entirely, including the fixes made
earlier today.  Found via multi-agent structural analysis of the 25 files
that stalled the walker, then verified independently.

Records are self-delimiting: off+2 is a uint16 BE length, next_record =
off + 2 + len, and the chain ends on a record whose chan_id is 0x06.
off+8 carries a 3-valued mode enum:
  02 00  14-byte header, 2 anchors, then CUMULATIVE delta blocks
  01 00  10-byte header, no anchors, blocks are ABSOLUTE values
  00 03  10-byte header, NO TAGS AT ALL - raw 12-bit packed absolute

`40 NN` is an ordinary int16 BE data block (2*NN + 2), never a header.
Reading it as a 2*NN + 16 header is what made walks drift — the
"variable-prefix segment descriptors" reported earlier today were not a
format feature, just walker drift of exactly
4 - (old_stop - true_record_start), on all 25 affected files.

Measured on the production snapshot:
  all four channels equal length   156/1388 -> 1388/1388
  ASCII sample-count exact           72/75  ->   75/75
  ASCII fully exact                  70/75  ->   73/75
  device PPV waveform (live)       1288/1306 -> 1306/1306  (mean err 0.00000)
  device PPV histogram (live)      4434/4459 -> 4458/4459

Also eliminates the walker-over-read class: 24 of those 35 files were
histograms that read_blastware_file fed to the waveform codec first; the
old walker accepted them and returned garbage (one yielded 98,923
"intervals"), while the record-chain decoder returns None so they fall
through to histogram_codec.

00 03 records are DECODED, not skipped.  Skipping them silently shifts
the time base of everything after them on that channel — BE9558/
K558LOF2.820W had MicL displaced by exactly 512 samples with nothing
marking the gap.

Footer detection now prefers the 0e 08 candidate whose body yields a
chain terminating on 0x06; the signature can occur inside a sample
stream.  Blast radius 1 file of 1388.

The superseded model survives as decode_waveform_legacy, pinned by
micromate/idf_file.py: its Thor IDFW body-offset search trial-decodes
candidates and keeps whichever yields the most samples, so the new
decoder returning None where the old returned garbage changes that
heuristic's winner.  Deferred until that search uses the record chain.

Tests: 253 passed (+11), failure list unchanged from baseline.  The 9
tests pinning the superseded model are retargeted at
decode_waveform_legacy, which still implements it.

NOTE: stored .h5 files need regenerating — nearly all get longer.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 22:13:29 +00:00
serversdownandClaude Opus 5 260bf0bc67 fix(backfill): clear stale shape_* when the .h5 can no longer yield a shape 
backfill_event_shape.py skipped rows whose .h5 produced no shape and left
the previously stored value in place.  A stale shape outlives the decode
it came from and silently feeds the false-trigger detector.

Found while re-running the backfill after the histogram codec fix: 493
rows in the prod snapshot were carrying shape metrics that no longer
matched their .h5 — e.g. BE17353/S353LDOK.XZ0H held crest_factor from a
223-sample decode while its .h5 holds a single interval.  These predate
today's work (present in the pre-32000 snapshot), so this is pre-existing
behaviour rather than fallout from the codec fixes.

Now NULLs shape_crest_factor / shape_near_peak_count / shape_sample_count
/ shape_axis in that case and reports a `cleared_stale` count.  Verified
on the snapshot: 493 cleared, 0 stale rows remaining, 11570 rows matching
their .h5 exactly.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 19:11:39 +00:00
serversdownandClaude Opus 5 ef1e99b0a0 fix(histogram): block is big-endian + terminal block tail — 1/1196 to 1211/1211 
Two errors in the series-3 histogram block model, both found by diffing
against the per-interval data table in the preserved Blastware ASCII
exports (1211 files in the prod snapshot — far stronger ground truth
than the header PPV used previously).

1. The block is uniformly BIG-ENDIAN.  Peaks and half-periods are uint16
   BE (T_peak [5:7], T_halfperiod [7:9], V_peak [9:11], V_halfperiod
   [11:13], L_peak [13:15], L_halfperiod [15:17], M_peak [17:19],
   M_halfperiod [19:21]); only block_ctr [2:4] is little-endian.

   The old uint8-peak model silently CLIPPED any peak above 1.275 in/s:
   the final interval of BE18193/T193LQ9K.OE0H reads 8.270 in/s in BW's
   export (1654 counts = 0x0676) and decoded as 0x76 = 118 = 0.590.

   The byte documented as a per-channel "annotation" was never an
   annotation — it is the half-period's high byte, which is exactly why
   it was non-zero on the sub-Hz intervals BW renders as "<1.0".

   The marker is block[4] alone.  Testing [4:6] as a uint16 LE marker
   forced block[5] == 0, which is what capped the peak at one byte.

2. The final block of each stream carries tail 9c 06 00 42 instead of
   1e 0a 00 00, and holds arbitrary bytes at [21:23].  Rejecting it
   dropped the last interval of nearly every histogram — frequently the
   interval holding the event peak, so the file's PPV read low.

Verified end to end through the production path: 1211/1211 histograms
decode exactly (interval count + every per-interval peak), plus 842,442
per-interval frequency comparisons with zero mismatches.  Previously
1 of 1196 files was fully correct.

decode_histogram_body_full records expose `is_terminal` in place of the
removed `annotations` tuple.  +6 tests.  No regressions: full-suite
failure list unchanged from baseline.

NOTE: stored histogram .h5 files need regenerating to pick this up.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 18:59:25 +00:00
serversdownandClaude Opus 5 e449ac04af docs: sharpen the series-3 histogram open item — dropped intervals, not wrong values 
Re-measured properly.  The first pass compared h5 max against the ASCII
header PPV and reported "26% of channels miss the peak".  The histogram
ASCII actually carries a full per-interval data table (Tran/Vert/Long
peak + freq + PVS per interval), which is real ground truth, so the
comparison should have been per-interval from the start.

Per-interval result, n=1196 series-3 histograms:
  - decoded VALUES are right: 1031/1196 (86%) match within 1 LSB across
    the overlapping prefix
  - the interval COUNT is short in 1195 of 1196 files: median 1 missing,
    1088 short by 1-2, 65 by 3-10, 39 by 11-100, 3 by >100 (max 205)
  - decoded max falls below the device PPV in 169/1196 files (14%), not
    26% — that happens when a dropped interval held the peak

So it is a termination bug in histogram_codec.decode_histogram_body,
the same family as the waveform-walker truncation fixed earlier today,
rather than mis-decoded interval values.  Series-3 only; there is no
preserved series-4 ASCII in the snapshot to compare against.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 16:23:51 +00:00
serversdownandClaude Opus 5 4f8224a751 docs(appendix-e): offset fault is geophone-side — operator swap test + MicL evidence 
Operator report: attaching a different geophone to an affected unit
makes the offset go away.  That rules out the unit's analog front-end
and any stored per-channel zero constant (a constant lives in the unit
and would survive a sensor swap).

The stored data agrees — MicL, a separate transducer on its own cable,
shows no offset during either episode (|mean|/peak 0.17 and 0.02) while
the geo channels on the same unit at the same moment are pinned.

Two distinct sensor-side patterns recorded:
  BE18438  Vert 0.97, Tran 0.16, Long 0.18  -> one conductor pair
  BE9558   Long 0.99, Tran 0.90, Vert 0.81  -> shared return / ground

Candidate mechanisms narrowed to three, since a geophone coil is passive
and cannot generate sustained DC: galvanic corrosion at a connector or
splice (matches the ~46 mV referred to the ADC input), a leakage path to
shield, or changed coil DC resistance interacting with the amplifier's
input bias current.

Also records the confound: swapping a sensor requires a monitoring
restart, and these units run Sensor Check "Before monitoring", so the
restart re-zeros too.  The swap does not cleanly separate "new sensor"
from "the restart re-zeroed it".  Controls and the single best
measurement (open-circuit DC across the suspect connector) documented.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 15:06:34 +00:00
serversdownandClaude Opus 5 5d3963b545 docs: record the 2026-08-25 body-codec and geo-scale findings 
Brings the protocol reference, CLAUDE.md and the codec RE status doc up
to date with everything confirmed in this pass.

instantel_protocol_reference.md
  - Changelog row for the five findings.
  - S7.6.1: scope table showing the 32000 scale correction applies to
    series-3 waveform, series-3 histogram and series-4 Thor alike, with
    the measured before/after ratios for each.
  - S15: closed "Full channel ID mapping in SUB 5A stream" — resolved by
    the segment-header channel id ([channel][00][00][segment], 0x46=Tran
    0x47=Vert 0x48=Long 0x49=MicL, 1697/1697 verified).  Four new open
    questions: variable-prefix segment descriptors, the histogram codec
    missing peak intervals (26% of channels), UM-series IDF decoding
    ~1000x low, and the Thor per-count LSB residual.
  - NEW Appendix E — Known Device Faults.  Documents the field-observed
    "offset" fault: symptom, why it floods the ACH queue (pedestal
    exceeds the unit's own geo trigger level), the episode table, the
    detection rule that works, what the data rules out (not the
    geophone, not the battery, not environmental, not condensation),
    and the two remaining candidate mechanisms with the test that
    separates them.  Explicitly flags that it is NOT a decode artifact,
    since that mistake has already been made once.

CLAUDE.md
  - Body-codec section: the four framing cases and the channel-id
    finding, with the corpus result.
  - "What's NOT solved": replaced the stale walker-edge-cases bullet
    with the four genuinely open items.

waveform_codec_re_status.md
  - Scale scope table matching the protocol reference.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 14:25:26 +00:00
serversdownandClaude Opus 5 0f6c9d930f data: offset-candidate event list from the 2026-08-25 survey 
274 series-3 waveform events across 6 episodes on 2 units (BE9558,
BE18438) whose dominant geo axis sits pinned at a DC offset above that
unit's own geo trigger level — the "offset" hardware fault that makes a
unit retrigger continuously and flood the ACH queue.

Detection rule: dominant-axis |mean|/peak > 0.7 AND |mean| >= 0.9 x the
unit's geo trigger level.  Bare |mean|/peak is useless on quiet events —
a trace at the 0.010 in/s noise floor clears any ratio threshold.

Not a decode artifact: these reproduce exactly in Blastware's own ASCII
export.  Kept as the starting point for the archive-wide analysis.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 14:21:59 +00:00
serversdownandClaude Opus 5 b6b6ee0331 docs(changelog): record that the 32000 scale fix hit histograms and series-4 too 
The scale lives in _samples_to_float, which every event passes through
regardless of source codec, so waveforms, histograms and Thor IDF events
were all 2.34% low — not just waveforms.  Verified after regeneration:
series-3 histogram peaks vs ASCII reports now median 1.0000 across 1137
comparisons (0.9766 under 32768); series-4 peaks vs device peaks moved
from median 0.960 to 0.983 across 1468.

The four block-framing fixes remain waveform-only; histogram_codec is
untouched.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 09:16:23 +00:00
serversdownandClaude Opus 5 686ab6e7a6 fix(codec): geo full scale is 32000 counts; 4 walker framing cases; channel-id from header 
Two independent bugs, both found by diffing 75 production events against
their preserved Blastware ASCII exports (<store>/<serial>/<file>_ASCII.TXT).

1. Geo full scale was wrong — every geophone reading was 2.34% low.
   The codec emits geo samples in 16-count units with a documented LSB of
   exactly 0.005 in/s, and decoded_to_adc_counts multiplies by 16, so one
   ADC count is 0.005/16 in/s and 10.000 in/s is 10.0/(0.005/16) = 32000
   counts.  sfm/event_hdf5.py and minimateplus/event_file_io.py both
   divided by 32768 (2^15), scaling every sample and derived peak down by
   1 - 32000/32768.  The error scales with amplitude, so it was invisible
   on quiet events and worst on the loud ones that matter for compliance.
   Mic is unaffected (it back-solves its scale from the device peak).

   216 per-channel comparisons: 32768 -> 151/216 exact, worst error 0.238
   in/s on a 10 in/s event; 32000 -> 216/216 exact, worst 0.005 = 1 LSB.

2. walk_body silently truncated channels on four unhandled framing cases.
   An unrecognised tag ends the walk and decode_waveform_v2 returns
   whatever it got, so this surfaced as short channels, never an error:
     - wide-NN RLE `0X NN` (runs longer than 252 samples)
     - `30 NN` with NN > 0x10 (the old cap was arbitrary)
     - variable-width `40 NN` headers: NN counts previous-channel
       continuation deltas, so the header is 2*NN + 16 bytes; `40 01`
       and `40 03` occur alongside `40 02`
     - tagless segment headers: no `40 NN` tag at all, just the 14-byte
       tail [field2:2][len:2][channel_id:4][marker:2][anchors:4]

Also: the header field documented as a "monotonic uint32 LE counter" is
really [channel_id][00][00][segment_index], with 0x46=Tran 0x47=Vert
0x48=Long 0x49=MicL — verified on 1697/1697 segment headers, zero
disagreements.  decode_waveform_v2 now takes the channel from that field
instead of rotation position, which was fragile: one missed header
desynced every channel after it.

parse_segment_header now returns n_prev_deltas/prev_deltas/marker/
anchors/channel/segment_index; the old fixed_pattern (02 00 00 01)
conflated the 2-byte marker with the first anchor.

Ground-truth corpus, end to end through the production path:
  exact 37 -> 72, truncated 23 -> 3, full-length value errors 15 -> 0.
Store-wide, 729 of 1388 series-3 waveform events decode differently and
728 gain samples; the scale fix changes float values on all of them, so
stored .h5 files need regenerating.

Still open: 3 events truncate at a header variant with a variable-width
prefix (2/4/6 bytes) before the channel id and an `01 00` marker.
Documented in docs/instantel_protocol_reference.md with byte offsets.

+20 tests.  No regressions: the byte-exact fixture suite still passes and
the full-suite failure list is unchanged from baseline (16 pre-existing
failures from gitignored fixtures).

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HgTe8CamXAHcAmaQ6QNcog
 2026-08-25 08:11:11 +00:00
serversdown 37043a47e9 fix(review): quick FT path enforces 3-state exclusivity + twin propagation; changelog + twin caveat 
set_false_trigger now clears reviewed_real when flagging false_trigger=True
(mirrors update_event_review's exclusivity), and the quick
PATCH /db/events/{id}/false_trigger endpoint now calls
propagate_review_to_twins after the flag write, matching the sidecar PATCH
path's try/except-with-log.warning pattern. Previously the quick path could
leave both flags set and never touched twins.

Also corrects the v0.25.0 CHANGELOG bullet (exclusivity was not actually
enforced on the quick path until this commit) and adds a caveat comment on
find_twins about rare clamped/saturated-PVS false-positive twin matches.
 2026-08-25 00:55:38 +00:00
serversdown 4a581e0e67 chore(release): v0.25.0 — reviewed_real + twin review-propagation 2026-08-25 00:45:33 +00:00
serversdown 7aae0208f8 feat(review): propagate false_trigger/reviewed_real to twins on sidecar PATCH 2026-08-25 00:42:27 +00:00
serversdown 5ffa92ab87 feat(db): find_twins (serial + identical PVS + time window) 2026-08-25 00:38:49 +00:00
serversdown f73c8eec91 feat(db): update_event_review mirrors reviewed_real + enforces 3-state exclusivity 2026-08-25 00:34:25 +00:00
serversdown 23e4f585a8 fix(db): keep reviewed_real out of the Migration-1 rebuild table (positional SELECT *); regression test 2026-08-25 00:31:39 +00:00
serversdown d9cc5f1780 feat(db): reviewed_real column on events (+ auto-migrate) 2026-08-25 00:26:22 +00:00
serversdownandClaude Opus 4.8 5247e78669 docs(plan): B2-A — reviewed_real + 3-state mirror + twin review-propagation 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-08-25 00:25:02 +00:00
serversdown ac67e83bcf chore(release): v0.24.0 — waveform-shape metrics on events 2026-08-22 06:12:01 +00:00
serversdown c982512e17 feat(scripts): backfill events.shape_* from .h5 samples 2026-08-22 06:06:46 +00:00
serversdown e64e3bcd3e feat(ingest): compute shape from the written .h5 in all save paths 2026-08-22 06:01:43 +00:00
serversdown 54c4182023 feat(db): insert_events persists shape_* from waveform record 2026-08-22 05:55:25 +00:00
serversdown a894b001b1 feat(db): shape_* columns on events (+ auto-migrate) 2026-08-22 05:50:45 +00:00
serversdown cec82038ea test(shape): shape_from_h5 round-trips a real .h5 2026-08-22 05:46:58 +00:00
serversdown 2539f903de feat(shape): crest-factor + points-near-peak waveform metrics 2026-08-22 05:42:36 +00:00
serversdownandClaude Opus 4.8 eb92b13aac docs(plan): waveform-shape FT detection — Phase A (seismo-relay) 
7-task TDD plan: shape DSP module (crest factor + points-near-peak), shape_*
columns + auto-migrate, insert_events persistence, ingest population in the
save paths, backfill script, /db/events exposure + v0.24.0 bump. Phase B
(terra-view scoring/UI/review) gets its own plan once this feed is live.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-08-21 21:32:59 +00:00
serversdownandClaude Opus 4.8 aebb5644bd chore(release): v0.23.0 — per-channel ZC frequency in events store 
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-08-04 21:42:41 +00:00
serversdown ddf6a73292 feat(scripts): backfill event ZC freq columns from sidecars 2026-07-29 17:32:54 +00:00
serversdownandClaude Opus 4.8 1744eb1803 feat(db): persist per-channel ZC freq on insert/upsert 
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
 2026-07-29 17:27:36 +00:00
serversdown 9a71d5b914 feat(parse): carry per-channel ZC freq onto PeakValues (report + dict paths) 2026-07-29 17:20:17 +00:00
serversdown 248276d141 feat(db): add per-channel ZC-freq columns to events (+ migration) 2026-07-29 17:13:59 +00:00
serversdownandClaude Opus 4.8 12401b917c chore(release): v0.22.0 
Full-snapshot bundle (SFM side): document the /db/snapshot,
/db/waveforms/recent.zip and gated /db/restore endpoints. Bump package
version 0.21.1 -> 0.22.0 (pyproject), README version badge + history, and
CHANGELOG. TOOL_VERSION (codec/output provenance) left at 0.21.1 on purpose
— the event codec is unchanged, so existing sidecars must not be flagged
stale for re-backfill.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WyT5m9xppYmoVGmCCVVV6X
 2026-07-03 19:32:15 +00:00
serversdown 6e2994acdd fix(api): threadpool the /db/restore handler (drop async) 2026-07-02 17:50:28 +00:00
serversdown b56eb8c692 feat(api): /db/snapshot, /db/waveforms/recent.zip, gated /db/restore 2026-07-02 06:53:24 +00:00
serversdown 280b3d25ec fix(db): WAL-safe safety backup + tests for validate-first and zip-traversal guard 2026-07-02 06:45:17 +00:00
serversdown 7edd0a1265 feat(db): gated WAL-safe restore of seismo_relay.db + waveforms 2026-07-02 06:35:24 +00:00
serversdown 916e6fcabb feat(db): zip recent events' waveform files 2026-07-02 06:30:11 +00:00
serversdown 31660d24e9 feat(db): WAL-safe seismo_relay.db snapshot helper 2026-07-02 06:22:46 +00:00
serversdown 25386cab8b fix(backfill): regenerate IDFH .h5 + merge binary mic_pspl_psi onto bridge 
Two gaps in backfill_thor_events.py that left old Thor events showing
stale charts after a v0.21.1 backfill pass:
1. IDFH events were skipped from .h5 regeneration (the "have decoded
   samples" gate was IDFW-only).  Histograms kept their pre-v0.21.1
   .h5 — written from raw_samples = None, which the renderer turned
   into a near-empty bar chart, or for older events the dB(L)-as-pseudo-
   psi mic scale that produced "107.7 psi" peaks (atomic-bomb level
   instead of footstep level).  Fix: synthesise the same 1-sample-per-
   interval array save_imported_idf v0.21.1 uses (peak ADC count per
   channel per interval) so the renderer's bar-chart grouping has
   data to work with.
2. The IDFW h5 path didn't merge binary_peaks.mic_pspl_psi onto the
   IdfEvent before to_minimateplus_event().  The live save_imported_idf
   does this merge — without it, IdfEvent.from_report() only sees the
   .txt's dB(L) value, the bridge falls back to the dBL→psi formula
   (instead of the binary-accurate 2.14e-6 psi/count value), and the
   h5 writer's per-count mic factor lands on a less-correct value.
   Fix: same merge the live ingest does (lift res.event.peaks.mic_pspl_psi
   onto idf_event.peaks before the bridge call).
Verified against UM6047_20250804190047.IDFH (250-interval prod
histogram): 250 intervals decode, mic_pspl_psi = 2.78e-5 (was being
treated as dB(L)=107.7 in the old h5).
Operator: re-run after deploy.  `docker compose exec sfm python
scripts/backfill_thor_events.py` is idempotent — the existing version
check still skips events already at the new TOOL_VERSION, and review
state + captured_at are preserved on the second pass.
 2026-06-01 20:02:54 +00:00
serversdown 6cb619ecc4 version bump - 0.21.1 2026-06-01 19:33:44 +00:00
serversdown 1ed86244d0 fix(thor-events): add parallel field for mic psi. Now shows mic in dbl and psi. (psi for charts) 2026-06-01 18:27:24 +00:00
serversdown b2c565f217 fix(idf_waveforms): _find_waveform_body_offset() — scans every 00 02 00 magic past offset 0x0E00, runs decode_waveform_v2 on each candidate, picks the one that returns the most samples. Validated on 483 prod IDFW files: 0 preamble-only events (was ~50%), 355/483 fully decode, 126/483 partial (BW codec walker-stops-early on loud events — known issue). 
IDFH now synthesises a 1-sample-per-interval array from the binary intervals and writes an .h5 so the existing renderer works unchanged. Each "sample" is the per-interval peak ADC count → h5_value = count × geo_fs/32768 yields the right bar height.
 2026-05-31 20:51:09 +00:00
serversdownandClaude Opus 4.7 43f440812a scripts: add backfill_thor_events.py 
Refreshes the bw_report sidecar block + .h5 waveform files for Thor
events ingested before the v0.21.0 adapter wiring + the bee1185 codec
fix.  Those events landed with extensions.idf_report only (no
bw_report, no .h5 for IDFW) — symptom on the UI side: the modal chart
404'd on /waveform.json and the PDF rendered from DB-only fields
without sensor self-check, full per-channel breakdown, or mic dB(L).

Walks <store>/<serial>/<filename>:
  - Reads the existing sidecar (preserves review state + captured_at)
  - Re-runs read_idf_file() on the binary bytes (passes data=
    kwarg so codec doesn't try the broken bare-path Path.read_bytes)
  - Reads extensions.idf_report from the existing sidecar
  - Runs build_bw_report_from_idf adapter
  - Writes refreshed sidecar with bw_report + bumped tool_version,
    preserving review block and original captured_at
  - For IDFW: regenerates .h5 by bridging IdfEvent.from_report ->
    to_minimateplus_event -> write_event_hdf5 (mirrors save_imported_idf
    steps 4-7)
  - IDFH events skip .h5 (histograms have no per-sample data)

Skips events already at current TOOL_VERSION with bw_report present.
--force overrides.  --skip-hdf5 limits to sidecar-only refresh.
--dry-run for preview.

Validated against the prod-snap waveform store: 3,815 Thor sidecars
refreshed cleanly with 0 errors, 462 IDFW .h5 files written, 2 skipped
(binaries with no sidecar — backfill doesn't conjure events from
nothing).  Verified one originally-broken IDFW event now serves
waveform.json (200, 168KB) and a fully populated PDF (119KB vs the
previous 56KB sparse output).

Operator workflow on prod:
  docker exec <sfm-container> python3 /app/scripts/backfill_thor_events.py --dry-run
  # Inspect counts, then for real:
  docker exec <sfm-container> python3 /app/scripts/backfill_thor_events.py

Idempotent — re-running it is a no-op once everything's at the current
TOOL_VERSION.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-30 04:37:43 +00:00
serversdownandClaude Opus 4.7 23e83908c2 report_pdf: fix PVS overlapping stats table, drop NA caption 
Two related fixes to the per-channel stats block:

1. Pin the stats table's position via an explicit bbox= on
   ax.table() so the bottom edge is at a known axes-fraction Y.
   The previous loc="upper left" + tbl.scale(1, 1.4) combo let
   matplotlib choose row heights based on text size, which made the
   table extend further below the axes than the hard-coded PVS line
   at y=-0.08 expected.  Result was the "Peak Vector Sum X in/s"
   string landing horizontally inside the Peak Displacement row.

   With bbox=[0, 1-N*0.12, 0.80, N*0.12] the table is pinned to a
   precise rectangle (12% axes-fraction per row × N rows tall).
   _draw_stats_table now stashes the bottom Y on the axes for the
   PVS helper to reference, so the geometry stays in sync.

2. Center PVS horizontally (ha="center" at x=0.5 instead of ha="left"
   at x=0).  The previous left-edge alignment put PVS at the same
   X as the label column, which read as "off-center" once the rest
   of the stats data was column-aligned further right.

3. Drop the "NA: Not Applicable" caption.  It existed to explain
   "—" placeholder cells, but "—" is universally understood and the
   caption was always visually squished against the PVS line below.
   Less cruft on the page; one fewer position to manage.

Verified against a real BE12599 histogram event (5 data rows) and
a real UM12947 IDFW waveform event (6 data rows) — both layouts
clear the table cleanly with no overlap.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-29 22:17:43 +00:00
serversdownandClaude Opus 4.7 bee118506b fix(idf): decode from in-memory bytes during ingest 
Bug shipped in v0.21.0: save_imported_idf called read_idf_file()
with `source_path` (a bare filename like "UM12947_….IDFW") BEFORE
writing the binary to disk.  The codec did Path(path).read_bytes()
which resolved relative to /app and hit FileNotFoundError.  The
error was caught + logged as a warning, and ingest fell back to
.txt-only — events still landed in the DB but lost the bw_report
block + .h5 waveform that the codec was supposed to produce.

Observed during a full re-forward from thor-watcher on 2026-05-29:
every Thor event logged "binary codec failed for X: [Errno 2] No
such file or directory" and got binary_decoded=False.

Fix:
- read_idf_file() gains a `data: Optional[bytes]` kwarg.  When
  supplied, skips the disk read and decodes the provided bytes
  directly.  `path` stays required (used for filename in error
  messages + .IDFH vs .IDFW suffix detection); only the read is
  conditional.  Backward compatible — existing positional callers
  (CLI scripts, tests) continue to work unchanged.
- save_imported_idf passes `data=idf_bytes` since the bytes are
  already in memory from the multipart upload.  Filesystem write
  still happens at step 5 of the existing flow; codec just no
  longer depends on it.

Verified end-to-end against UM11719_20231219162723.IDFW from the
example-data corpus: ingest endpoint returns inserted=1, log line
shows binary_decoded=True + h5=...IDFW.h5, no warnings.

Re-forward existing Thor events from thor-watcher after deploy to
backfill the bw_report block — UPSERT preserves review state.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-29 20:09:54 +00:00
serversdownandClaude Opus 4.7 defd17d9c2 sfm_webapp: harmonize "Received by server at" → "Time received" 
Matches Terra-View's event-modal relabel from the same iteration.
Wording was already clearer here than in Terra-View's "Captured at",
but using identical text across both surfaces means operators see the
same label whether they're in the native modal or the standalone
webapp.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-29 19:51:58 +00:00
serversdownandClaude Opus 4.7 e42956a20b release: v0.21.0 — Thor / Series IV codec + Thor→BW adapter 
Documents two commits that landed on dev since v0.20.0:

  9b71ead  series 4 codec work, initial decode success
           micromate/idf_file.read_idf_file() decodes both IDFW
           (waveform; 87-99% sample fidelity reusing
           decode_waveform_v2 at offset 0x0f1f) and IDFH (histogram;
           dedicated segment-based decoder, all 859 corpus files
           decode, 181,071 intervals total).

  9fd52dd  feat: add thor report generation, pdf generation
           micromate/idf_to_bw_report.py adapter projects parsed
           Thor data into the bw_report sidecar shape so Thor
           events flow through sfm/report_pdf.py without a
           separate renderer.  Wired into save_imported_idf.

Net effect: a Thor event ingested via /db/import/idf_file now
lands with the same fidelity as a BW event, gets a per-event PDF
on demand, and renders in Terra-View's modal chart using the same
plotting code as a BW event.

Roadmap items closed:
- Binary .IDFW / .IDFH codec (was pending)
- Series IV (Thor IDF) binary codec reverse-engineering

Companion: Terra-View v0.13.0 ships in parallel and closes Phase 1
of the SFM integration.  No API changes in seismo-relay for that
piece — Terra-View just consumes existing endpoints better.

Bumps:
- pyproject.toml 0.20.0 → 0.21.0
- minimateplus.event_file_io.TOOL_VERSION 0.20.0 → 0.21.0
  (any subsequent backfill_sidecars.py --force will re-stamp
  existing sidecars; expected + harmless)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-29 19:25:44 +00:00
serversdown 9fd52ddabb feat: add thor report generation, pdf generation. 2026-05-29 19:03:06 +00:00
serversdown 9b71ead44b series 4 codec work, inital decode success 2026-05-29 06:33:13 +00:00
serversdownandClaude Opus 4.7 1bccc44b88 release: v0.20.0 — PDF + parser polish 
Closes out the Event-Report PDF iteration started in v0.17.x and ships
the parser fixes the real-world events were tripping over.

Today's additions on top of the pre-v0.20 unreleased body:

- Server-wide display TZ via the TZ env var (default America/New_York
  on prod).  Affects server logs, the PDF report's "Created" footer,
  matplotlib datetime axes.  DB columns stay UTC.  Dockerfile now
  installs tzdata.
- ZC Freq "above-range" handling — parser stores 100.0 +
  zc_freq_above_range flag for BW's ">100 Hz" marker.  Renders as
  >100 in the PDF stats table, both modals (inline on webapp Peaks,
  new column on event-browser table).
- scripts/backfill_sidecars.py --reparse-txt — re-runs the current
  parser against the preserved _ASCII.TXT and overwrites the
  sidecar's bw_report block.  Lets parser fixes reach old events
  without re-forwarding.  Validated end-to-end against ~10k prod
  events.

Fixes shipped today:
- histogram_interval_size_s missing from ReportData → every
  histogram PDF render 500'd.
- Histogram PDF geo channels now share a nice-quantized y-axis
  (0.005-LSB-aware 1-2-5 step sequence) instead of auto-scaling
  per channel + inventing sub-LSB "0.003 in/s/div" footer labels.

Roadmap delta: closes the BW ASCII parser "PPV-miss on some TXT
formats", "histogram-specific structural fields", and ">100 Hz value
parsing" items.  Adds a new entry for the byte[5]==0 histogram body
sub-format observed on S353 events.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 21:17:53 +00:00
serversdownandClaude Opus 4.7 a3cc44d30a feat(backfill): --reparse-txt flag to refresh bw_report from preserved .TXT 
The existing backfill_sidecars.py PRESERVES the bw_report block across
regenerations — it's treated as the source of truth from the original
ingest pass (the .TXT isn't reachable from the script's normal data
path, so it can't be re-derived).

That means parser-side fixes (like the 2026-05-28 ">100 Hz" ZC Freq
addition) won't reach old events even with --force.  The new
--reparse-txt flag fixes that: when the sidecar's source.txt_filename
points at a preserved <serial>/<filename>_ASCII.TXT, the script re-runs
the current parser against it and overwrites the bw_report block.

Implies sidecar regeneration on every event (bypasses the
sha-up-to-date / version-up-to-date skip), so that the .h5 cascade-
regenerates alongside.  No-op for events without a preserved .TXT
(legacy ingests pre-2026-05-27).  Idempotent — re-running it produces
the same sidecar bytes when the parser hasn't changed.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 18:56:23 +00:00
serversdownandClaude Opus 4.7 6a73523e4d ui: surface per-channel ZC Freq (and ">100") in event modals 
The PDF report shows per-channel ZC Freq alongside PPV in the stats
block, but neither modal exposed it.  Now that the sidecar projection
carries zc_freq_hz + zc_freq_above_range, plumb them through:

- sfm_webapp.html: inline suffix on existing Peaks cells, e.g.
  "Tran  0.04500 in/s · >100 Hz".  Empty suffix when no ZC is
  available (legacy events without a preserved .TXT).

- event_browser.html: new ZC Freq column on the per-channel stats
  table.  Required adding a parallel sidecar fetch in loadEvent()
  (waveform.json alone doesn't carry bw_report).  Fetch failure is
  non-fatal — falls back to "—" in the new column.

Above-range ZC peaks (BW ">100 Hz") render with a literal ">"
prefix mirroring the PDF, so operators don't have to generate the
PDF to see when a channel hit the zero-crossing ceiling.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 18:47:37 +00:00
serversdownandClaude Opus 4.7 780b45a371 feat: render ">100" for above-range ZC Freq instead of "—" 
BW writes ">100 Hz" for ZC Freq when the zero-crossing algorithm sees a
peak too fast to count — the device's reporting ceiling is 100 Hz on
V10.72.  Our parser fell back to None via _parse_number (which requires
a leading digit), so the PDF rendered "—" where BW shows ">100".

Mirrors the OORANGE/saturated pattern already used for PPV and PSPL:
parser stores the threshold (100.0) on zc_freq_hz + sets a new
zc_freq_above_range flag.  Projection carries the flag through to the
sidecar; PDF renderer prepends ">" when set.

Affects both per-channel stats tables (waveform + histogram variants)
and the mic block's ZC Freq row.

Verified on the real T190LD5Q.LK0W fixture: Tran zc_freq_hz=100.0
above_range=True; Vert/Long (normal values) above_range=False; "N/A"
still produces zc_freq_hz=None which renders as "—" (unchanged).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 18:38:49 +00:00
serversdownandClaude Opus 4.7 f6abe3caa0 fix(report_pdf): histogram geo channels share nice-quantized y-axis 
Two related visual bugs on histogram PDFs:

1. Per-channel auto-scale meant Tran/Vert/Long had different y-axes
   (e.g. 0-0.015, 0-0.025, 0-0.020) — bars looked taller on the
   channel that happened to be quietest.  Not directly comparable.

2. Footer "Amplitude Geo: X in/s/div" was just amax/5 of the FIRST
   geo channel with data, with no LSB quantization — producing
   nonsense like 0.003 in/s/div when the geophone LSB is 0.005.

Fix: compute a single shared geo y-axis range from max(Tran,Vert,Long),
quantize the per-division step to BW's 1-2-5 sequence rounded to the
0.005 LSB (0.005, 0.01, 0.025, 0.05, 0.1, 0.25, ...), apply the same
ylim + ticks to all three geo subplots, and use that same step for the
footer label.  MicL stays on its own auto-scale (different units).

Verified across edge cases including the reported event
(geo max 0.025 → 0.005/div, top 0.025), small PVS events, and large
blast amplitudes.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 18:22:20 +00:00
serversdownandClaude Opus 4.7 ad2702d4bf fix(report_pdf): add missing histogram_interval_size_s field 
The histogram-interval-times derivation block at line 314 references
rd.histogram_interval_size_s, but the field wasn't declared on the
ReportData dataclass — only the string form histogram_interval_size
was.  Result: every PDF render of a histogram event raised
AttributeError → 500 from /db/events/{id}/report.pdf.

Cause: when the histogram aggregation block was inlined into
gather_report_data, the seconds-numeric counterpart that the
projection already carries (bw_report.histogram.interval_size_s) was
never wired into the dataclass.  Waveform PDFs weren't affected
because the offending line is gated on is_histogram.

Fix: add the field, read it from the projection alongside the other
histogram keys.  No-op for waveform events (the field stays None and
the gate skips it).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 18:07:41 +00:00
serversdownandClaude Opus 4.7 86325b9bab docs: roadmap entry for a SECOND undecoded histogram sub-format (S353) 
Observed in fresh ingest logs on 2026-05-28: BE17353 events
(S353L4H2.FZ0H, S353L4H2.P00H, etc.) cause "body codec failed to
decode" warnings.  Different from the byte[5]!=0 case already tracked
(T190 / O121) — these have byte[5]==0x00 with what looks like a
valid block header, but the walker finds zero data blocks anyway.

Operational impact identical to the existing case: ingestion
succeeds, DB peaks come from bw_report overlay, only the chart is
empty.  No data loss.

Pinning so it doesn't get lost — needs a hex dump of one body to
work out what's different about these.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 05:42:18 +00:00
serversdownandClaude Opus 4.7 6381dcb312 tz: server-wide display timezone via TZ env var (default EST/EDT) 
User-reported issue: server logs were timestamped in UTC ("05:36:20"
when local was ~01:36 EDT), and the PDF report's "Created" footer
similarly showed raw UTC.  Inconsistent with the modal which already
converts to browser local via toLocaleString.

Solution: standard Linux TZ env var.  Set once in the container, and:
  - Python's datetime.now() uses local
  - Logging module's timestamps use local
  - matplotlib renderers + report_pdf formatters use local
  - astimezone() conversions resolve to the configured TZ

DB columns stay UTC (created_at uses SQLite's strftime('%Y-...Z', 'now')
which is always UTC, regardless of TZ env var — proper "store UTC,
display local" pattern).

Changes:
  - Dockerfile: install tzdata (python:3.11-slim omits the timezone
    database), set default TZ=America/New_York
  - sfm/report_pdf.py: _fmt_iso_to_bw and _split_iso_to_date_time now
    convert UTC inputs (Z-suffixed) to local via astimezone(); naïve
    inputs (BW recorded-at, already unit-local) returned as-is.
    New _to_display_local helper centralizes the logic.
  - "Created" line in the PDF page footer now uses the converted
    timestamp.

Override per-deployment via the TZ env var in docker-compose
(separate commit on terra-view side).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 05:41:10 +00:00
serversdownandClaude Opus 4.7 53c05d93e2 delete: also clean up preserved _ASCII.TXT file 
_cleanup_event_files() removes the on-disk artifacts when an event is
hard-deleted (binary, a5_pickle, sidecar, h5).  Today's .TXT
preservation feature added a new on-disk file (_ASCII.TXT next to the
binary) but the cleanup didn't know about it — so any event deleted
via /db/events/{id} (single) or /db/events/delete_bulk (or the
Terra-View "SFM Event DB Manager" UI which proxies through to those
endpoints) was leaving orphan .TXT files in the store.

Added "txt" to the cleanup list using the new
WaveformStore.txt_path_for().  Safe for old events without a .TXT —
the exists() check skips the unlink.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 05:31:08 +00:00
serversdownandClaude Opus 4.7 a5888e1b5c report_pdf: PDF histogram aggregation + fix footer/x-axis overlap 
Two issues spotted on a histogram event PDF:

1. Footer scale ("Time — /div  Amplitude Geo: X in/s/div  Mic: Y
   psi(L)/div") was overlapping horizontally with the x-axis tick
   labels (0, 20, 40, 60...).  Both rendered on the same Y row.
   Fix: bumped gridspec bottom margin from 0.06 → 0.12, moved the
   footer text from y=0.045 → y=0.030 (below the tick labels), moved
   the page-bottom Created/Event line from y=0.015 → y=0.005.
   Trigger legend on waveforms moved 0.030 → 0.018.  Everything
   stacks cleanly now without collision.

2. PDF was showing the raw codec output (~150+ bars per histogram)
   instead of BW's per-interval aggregation.  Why: the aggregation
   I'd added to /db/events/{id}/waveform.json wasn't replicated in
   the PDF gather path.  Now: gather_report_data does the same
   max-per-group aggregation when bw_report.histogram.n_intervals is
   populated, AND derives per-interval HH:MM:SS labels from the
   start time + interval_size_s.  Result: histogram PDFs now match
   BW's display (one bar per BW interval, x-axis labeled with actual
   times) — same fix as the modal chart, applied to the PDF.

For events ingested BEFORE the parser extension (no histogram block
in their sidecar), aggregation is a no-op — they still render with
per-block bars + interval-index x-axis (but the overlap fix applies
to them too).  Re-forwarding repopulates the histogram block.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 04:33:53 +00:00
serversdownandClaude Opus 4.7 b9f8bbb220 viewers: enforce minimum Y-range on histogram channels 
Quiet histogram events were filling the chart panel even though the
peak was tiny (0.005 in/s rendered as 90% of chart height because
Chart.js auto-scaled to peak * 1.1).  Made everything look uniformly
loud regardless of actual amplitude.

BW's solution: a near-fixed scale per channel ("Geo: 0.002 in/s/div"
from the footer).  Quiet events render small, loud events render
proportionally tall.

Match the intent without copying BW's "no Y-axis labels at all"
convention.  For histogram channels:

  Geo (in/s):       min Y range 0.05 in/s
  Mic in psi:       min Y range 0.001 psi
  Mic in dBL:       unchanged (the 60 dBL floor + peak+5 top already
                    gives quiet events a sensible baseline)

So a 0.005 in/s geo event renders as ~10% of chart height; a 0.05
event fills it; a 5.0 event still fills it (max(peak*1.1, 0.05) ==
peak*1.1 for any peak > 0.045).

Waveform charts unchanged — they should zoom for shape detail.
Applied to both the modal in sfm_webapp.html and the standalone
/events page in event_browser.html.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 04:23:01 +00:00
serversdownandClaude Opus 4.7 b59f886cb7 docs: roadmap entry for sensor-check waveform extraction 
BW's Event Report PDFs include a per-channel sensor-check response
waveform on the right side of the bottom plot (damped sinusoid for
geo channels, sawtooth-at-test-freq for mic).  Looks like real
per-sample data extracted from the binary, not synthesized.

Our parser captures the test results (freq, ratio, amplitude,
pass/fail) but not the waveform samples — so the report shows text
only for sensor check.  Pinning a roadmap entry to investigate the
binary for the sample data (path a) or fall back to synthesized
visualization (path b).

Current text-only display is operationally sufficient.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-28 04:17:50 +00:00
serversdownandClaude Opus 4.7 87aec3f4d1 viewers: smoother mic dBL chart + restore binary/TXT download links 
Two issues spotted in the modal:

1. Mic dBL chart looked spikey/discontinuous — isolated bars at 80-95
   with gaps in between.  Cause: _psiToDbl() returns null for zero or
   negative samples, and most mic samples on a quiet event sit at the
   digitization noise floor where they're effectively zero.  Result:
   the chart only renders the moments when instantaneous SPL exceeded
   the Y-axis bottom — looks like a sound trigger gate.

   Fix: new _psiToDblForChart() rectifies the AC waveform (abs), then
   converts to dBL, then floors at MIC_DBL_FLOOR=60 dBL.  Chart now
   has a continuous 60 dBL baseline with peaks above it — matches how
   acoustic engineers expect SPL-vs-time.  Y-axis bottom pinned to
   MIC_DBL_FLOOR, top to peak + 5 dB headroom.  Peak label still uses
   the unrectified _psiToDbl so the displayed peak value is exact.

2. Filename in Source/Files block was unlinked.  Endpoint exists
   (/db/events/{id}/blastware_file) — just wasn't wired to the modal.
   Made it a clickable download link.  Same treatment for the
   preserved .TXT — added "(download .TXT)" link next to source kind
   when source.txt_filename is populated (events ingested after the
   .TXT preservation feature landed; older events show no link).

Applied to both the inline modal in sfm_webapp.html and the
standalone /events page in event_browser.html.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 23:08:21 +00:00
serversdownandClaude Opus 4.7 ace542cba5 report_pdf: wire histogram peak date/time + PVS-when + Finish field 
Spotted comparing our PDF to BW's reference for T003LLUB.CE0H:
  - Finish blank
  - Per-channel Date / Time rows all dashes
  - MicL PSPL line missing "on May 27, 2026 at 06:19:14"
  - Peak Vector Sum missing "on May 27, 2026 At 06:06:14"

Root cause: I'd added these fields to the projection (write side) in
_bw_report_to_dict but never wired them into gather_report_data
(read side).  Plus the projection used keys "start"/"stop" while
gather was reading "start_str"/"stop_str" — typo'd lookup.

Fixes:
  - gather_report_data now reads bw_report.histogram.start /
    .stop / .channel_peak_when (correct keys, matching the projection)
  - Per-channel "peak_date" / "peak_time" populated from
    channel_peak_when[<channel>] for the histogram stats table
  - MicL PSPL line formats as "PSPL  125.7 dB(L) on May 27, 2026
    at 06:19:14" (BW style) when channel_peak_when["MicL"] is present;
    falls back to the waveform-relative "at 0.012 sec" otherwise
  - PVS line formats as "Peak Vector Sum  0.091 in/s on May 27, 2026
    At 06:06:14" (BW style) when bw_report.peaks.vector_sum.when is
    populated; falls back to the relative time_s for waveforms
  - New _split_iso_to_date_time() helper splits ISO timestamps into
    BW-formatted ("May 27 /26", "06:06:14") date+time pairs for the
    stats table's separate Date and Time rows

Events ingested BEFORE the parser extension landed (most of the
existing prod corpus) still show dashes — their sidecars lack the
histogram block.  Re-forwarding repopulates.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 22:47:53 +00:00
serversdownandClaude Opus 4.7 8cbda09917 viewers: render timestamps in browser-local time 
Spotted on the SFM webapp event modal — "Received by server at" was
showing the raw ISO string "2026-05-27T21:59:57.213043Z" because we
were assigning ev.timestamp / src.captured_at directly to the
textContent of the modal fields, bypassing the existing _fmtTs()
helper that wraps them in toLocaleString().

Net effect for operators: confusing "21:59 vs it's 6 PM" mismatch
when the displayed UTC timestamp didn't match wall-clock time.  The
values were always correct; the display was just ambiguous.

After this fix:
  - "Recorded at" (naive ISO from BW = unit local time) renders
    cleanly as the unit wrote it: "5/27/2026, 6:00:13 AM"
  - "Received by server at" (UTC with Z suffix) converts to browser
    local: "5/27/2026, 5:59:57 PM"
  - Timestamp column in the history table already used _fmtTs —
    unchanged
  - Same fix applied to the standalone /events page (sidebar event
    list + meta header) via a new _fmtTsLocal helper

Note: did NOT add file-mtime-on-watcher-PC tracking as a separate
"Called in at" column — discussed and decided created_at is close
enough for schedule-compliance monitoring (worst case lag = watcher
poll interval ~60s, indistinguishable from BW write time at the
operationally-relevant resolution).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 22:30:43 +00:00
serversdownandClaude Opus 4.7 3457ed0072 bw_ascii_report: parse OORANGE saturation marker + TimeSum typo 
BW writes "OORANGE" (truncation of "Out Of Range") when a channel
exceeds its full-scale, and uses a typo'd label "Peak Vector Sum
TimeSum" for the PVS time field.  Both confirmed against real ASCII
files pulled from a Windows watcher PC 2026-05-27:

  T190LD5Q.LK0W  Vert PPV = OORANGE  (Normal range, 10 in/s exceeded)
  T438L713.RY0W  All three PPVs OORANGE  (Sensitive range, 1.25 in/s)
  K557L3YM.OE0W  Tran+Vert PPV OORANGE + MicL PSPL OORANGE

Previously our _parse_number() returned None for OORANGE → DB columns
ended up NULL → events vanished from filters / sorts / dashboards
despite being legitimate high-amplitude events.

New behavior — substitute a conservative bound + set a saturation flag:
  - Channel PPV       → geo_range_ips + ChannelStats.ppv_saturated
  - Peak Vector Sum   → sqrt(3) * geo_range_ips + peak_vector_sum_saturated
  - MicL PSPL         → 140 dB(L) + MicStats.pspl_saturated

Flags propagate to the sidecar's bw_report block so the SFM UI can
render "> 10 in/s" / "> 140 dBL" rather than treating the substituted
value as exact.

Same commit also accepts "Peak Vector Sum TimeSum" as an alias for
"Peak Vector Sum Time" (BW always writes the typo on OORANGE PVS
lines — every example file confirms it).

Tests: new test_oorange_marker_treated_as_saturation (synthetic) +
test_real_oorange_event_t190_parses (skips if real fixture absent).
177/177 tests pass; 16 pre-existing missing-fixture skips unchanged.

Five events on prod (T190, T438, K557, plus 2 others matching the
same fault pattern) will pick up correct peaks + saturation flags
once watchers re-forward.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 20:32:56 +00:00
serversdownandClaude Opus 4.7 d21e3b5298 histogram aggregation + parser extension for BW interval fields 
Three layered changes that together make histogram charts visually
match BW's printout (one bar per interval, not per codec block):

1. bw_ascii_report parser captures histogram fields it previously
   dropped:
     - Histogram Start/Stop Time + Date → datetime
     - Number of Intervals + Interval Size (string + parsed seconds)
     - <Channel> Peak Time + Peak Date → datetime (per-channel)
     - Peak Vector Sum Date (combined with PVS Time → datetime;
       clears the bogus seconds parse that interpreted "22:33:52"
       as 22.0)
   New _parse_iso_date() handles BW's ISO format for histograms
   (waveforms use "May 8, 2026" long form).  New _parse_interval_size()
   handles "1 minute" / "5 minutes" / "15 seconds" etc.

2. _bw_report_to_dict() projects the new fields into a new
   bw_report.histogram block in the sidecar.

3. /db/events/{id}/waveform.json wraps the existing path 1 (HDF5)
   output with _maybe_aggregate_histogram(): when the event is a
   histogram AND the sidecar has bw_report.histogram.n_intervals,
   group the codec's per-block samples into N intervals via
   max-per-group and return the aggregated array.  time_axis gains
   histogram_aggregated / n_intervals / interval_size_s / interval_times
   fields.

Frontend (both modal chart in sfm_webapp.html + standalone event
browser) uses interval_times as x-axis labels when provided (BW-style
HH:MM:SS), falls back to interval index.

Defensive: aggregation is no-op when the sidecar lacks the histogram
block (events ingested before this change).  Activates automatically
on prod once a watcher re-forward populates new sidecars.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 20:23:05 +00:00
serversdownandClaude Opus 4.7 ad2b553c7b ingest: preserve raw BW ASCII report (.TXT) alongside the binary 
Previously the .TXT was parsed into the sidecar's bw_report projection
and then discarded at ingest time.  Now save_imported_bw() writes it
to <store>/<serial>/<filename>_ASCII.TXT permanently.

Rationale: with BW Mail / Forwarding Agent being phased out of the
operator workflow, the XML/PDF/WMF those tools produce won't be
available — the binary + .TXT (created by BW ACH itself) are our
only authoritative inputs going forward.  Keeping the raw .TXT
unlocks:

  - Parser bug fixes can be applied RETROACTIVELY by re-parsing the
    stored .TXT, instead of requiring a re-forward from the watcher
    PC (which lost the .TXT after BW ACH cleanup).
  - Audit trail of what BW actually sent us, for debugging.
  - The five known parser-PPV-miss events will be re-parseable once
    the regex fix lands (instead of staying broken indefinitely).

Storage cost: ~15 KB per event × 14k events = ~210 MB on the
existing prod corpus.  Negligible.

Implementation:
  - WaveformStore gains txt_path_for() + open_txt()
  - save_imported_bw() writes the .TXT when bw_report_text is supplied
  - sidecar source block records the txt_filename
  - backfill_sidecars.py preserves txt_filename across regens
  - New GET /db/events/{id}/ascii_report.txt endpoint serves it
  - Returns 404 for events ingested before this change (no .TXT in
    the store yet) — re-forward to populate

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 20:01:12 +00:00
serversdownandClaude Opus 4.7 dfbc8b8520 report_pdf: split waveform vs histogram layouts (BW PDF iteration) 
Reviewed against real Blastware Event Report PDFs (uploaded to
example-events/pdfsnstuff/) for K558LLB7.V20H (histogram) and
K558LLB8.0E0W (waveform).  Each event type has its own layout because
BW's printouts genuinely differ:

  Waveform header:   Date/Time, Trigger Source, Range, Sample Rate
  Histogram header:  Start, Finish, Intervals At Size, Range, Sample Rate
                     (no trigger field — histograms aren't triggered)

  Waveform stats:    PPV, ZC Freq, Time (Rel. to Trig),
                     Peak Acceleration, Peak Displacement, Sensor Check
  Histogram stats:   PPV, ZC Freq, Date, Time (of peak), Sensor Check

  Waveform plot:     4-channel stacked line, x-axis in SECONDS,
                     trigger triangle + window markers, symmetric Y
                     for geo, zero-anchored mic, "0.0" baseline label
                     on right edge per BW convention
  Histogram plot:    4-channel stacked bars, Y-axis 0-to-peak only
                     (never negative — peaks are magnitudes), 0.0
                     baseline at the bottom

  Waveform footer:   USBM chart placeholder upper-right;
                     "Time X sec/div   Amplitude Geo: Y in/s/div   Mic: 0.001 psi(L)/div"
                     "Trigger = ▶━━◀"
  Histogram footer:  No USBM chart; same scale-info footer with
                     interval-size as the time unit

Other fixes from the first-pass screenshot review:
  - Channel labels (MicL/Long/Vert/Tran) no longer cut off (wider
    left margin)
  - Histogram bars rise from zero baseline (abs of any signed values)
  - ISO timestamp "2026-05-16T22:33:50" → "22:33:50 May 16, 2026"
    matching BW's display format

Known gaps (separate work):
  - Histogram codec returns per-block granularity (~200 bars for
    BW's 4-interval display).  XML-driven data source is the planned
    fix; the structured BW XML has the per-interval aggregates.
  - USBM RI8507 / OSMRE compliance chart still placeholder

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 18:22:03 +00:00
serversdownandClaude Opus 4.7 411ef8139e sfm: Event Report PDF generation (v0.20.0 stub layout) 
New endpoint GET /db/events/{id}/report.pdf returns a single-page
letter-portrait PDF for any event with waveform data on disk.

Architecture:
  sfm/report_pdf.py — gather_report_data() assembles fields from
    SeismoDb row + .sfm.json sidecar (bw_report block) + .h5 samples;
    render_event_report_pdf() turns that into PDF bytes via matplotlib.
  sfm/server.py — new endpoint wires them together, streams PDF back
    with Content-Disposition: inline so the browser displays it.
  sfm_webapp.html — new "Download PDF" button in the event modal
    footer that opens the endpoint in a new tab.

Fields surfaced — same coverage as a Blastware Event Report:
  Header metadata (date/time, trigger source, range, sample rate,
                   project, client, operator, location, serial+firmware,
                   battery, calibration, file name)
  Microphone block (PSPL in dB(L) + psi, ZC freq, channel test)
  Per-channel stats (PPV, ZC Freq, Time of Peak, Peak Accel,
                     Peak Disp, Sensor Check) for Tran/Vert/Long
  Peak Vector Sum
  Waveform plot (MicL/Long/Vert/Tran stacked, shared time axis,
                 trigger marker, symmetric Y for geo, zero-anchored
                 mic) — OR per-interval bar chart for histograms.

Rendering pipeline = matplotlib only (vector PDF, no headless-browser
dep).  Adds matplotlib>=3.8 to deps.

Visual layout is approximate until reference PDFs from Instantel land
at docs/reference/instantel/ for iteration.  USBM RI8507 / OSMRE
compliance chart is stubbed (placeholder rectangle) — separate work
item.

Smoke-tested on a K558 waveform event: 77 KB valid PDF, all fields
populated correctly from the snapshot DB.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 02:55:58 +00:00
serversdownandClaude Opus 4.7 ed926de3f4 viewers: default mic to dB(L) + add Mic-unit toggle (dBL ↔ psi) 
The sidecar-modal waveform plot was rendering mic in raw psi, while the
rest of SFM (history table column, peaks block, live-device chart,
event detail modal mic field) had already converted to dB(L) — matching
the BW Event Report convention.  Unifying.

Both viewers now:
  - Default mic chart values + axis title + peak label to dB(L)
  - Provide a header toggle ("Mic: dBL" pill) to flip to psi
  - Persist the preference via localStorage (sfm_mic_unit)
  - Re-render the open chart immediately on toggle

Conversion: dBL = 20 * log10(psi / 2.9e-9), where 2.9e-9 psi is the
20 µPa reference pressure already defined for the rest of the webapp.
Non-positive psi samples (log undefined) render as null; Chart.js
handles them as gaps in line mode and missing bars in histogram mode.

Also fixes event_browser.html's stats table — the MicL row was
hard-coding "<value> psi"; now honors the same toggle.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-27 02:30:56 +00:00
serversdownandClaude Opus 4.7 5d5441604b viewers: symmetric Y-axis on geo waveforms + clarify timestamp labels 
Two fixes from the second screenshot review:

1. Geophone waveform Y-axis now renders SYMMETRIC around zero — zero
   line sits in the middle of the chart, signal goes both above and
   below.  Standard seismograph display convention; matches the
   Instantel printout look.  Previously Chart.js auto-scaled to the
   data range so e.g. Vert showing values from -0.005 to -0.015 had
   the zero line completely off-screen.

   Mic channel (sound pressure, always positive) keeps the default
   auto-scale anchored at zero.  Histograms (per-interval peaks, also
   always positive) likewise keep bars rising from a zero baseline.

2. Modal labels clarified to remove the 'Timestamp' vs 'Captured at'
   ambiguity:
     'Timestamp'   →  'Recorded at'         (when the seismograph
                                              recorded the event —
                                              from BW report's Event
                                              Time field)
     'Captured at' →  'Received by server at' (when our sfm-db
                                              inserted the row)
   Both have tooltips explaining the distinction.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-24 20:26:23 +00:00
serversdownandClaude Opus 4.7 784f2cca36 viewers: decimal peak labels + bar chart for histograms + clean x-axis ticks 
Three polish fixes spotted in the first prod screenshot of the inline
event-modal waveform plot:

1. Peak labels were rendering as "PEAK 2.500E-2 IN/S" because of a
   blanket toExponential(3) call.  New _fmtPeak() formatter picks
   decimal with adaptive precision for normal-range values (0.0001 to
   10000) and falls back to scientific only for truly extreme
   magnitudes.  Same value now reads "peak 0.0250 in/s".

2. Histogram events were being plotted as connected line charts, but
   histograms are per-INTERVAL peaks (one bar per minute, typically),
   not per-sample waveforms.  Now: detect histogram via record_type,
   render as a tight bar graph (bars touch), suppress the trigger line
   + zero baseline overlays (no trigger event on a histogram), and
   label the x-axis with interval number instead of milliseconds.

3. X-axis tick labels were displaying as "11.7187040000000002 ms"
   because the callback used the raw float, not the formatted label.
   Snap to 1 decimal place (or integer for whole-number values like
   histogram intervals).

Applied to both the inline modal plot in sfm_webapp.html and the
standalone /events viewer in event_browser.html — they share the same
data shape and presentation conventions.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-24 19:54:04 +00:00
serversdownandClaude Opus 4.7 6abfadae4f viewers: render pre-trigger samples (time_axis is metadata, not an array) 
The /db/events/{id}/waveform.json endpoint returns `time_axis` as a
metadata object — {sample_rate, pretrig_samples, t0_ms, dt_ms,
n_samples, total_samples, rectime_seconds} — not a per-sample times
array.  Both viewers (sfm_webapp.html sidecar modal + event_browser.html)
were treating it as an array, silently falling back to a derived path
that ignored pretrig entirely and started the time axis at 0.

Symptom: trigger line drawn at the very left edge of every chart, no
visible "leading up to the event" samples even though they're in the
decoded data.

Fix: read time_axis.t0_ms (negative when pretrig samples exist),
time_axis.dt_ms, build per-sample times as `t0_ms + i * dt_ms`.  Trigger
line lands at sample where t crosses 0; pretrig samples render at
negative t to the left of it.

Confirmed on a K558 event with 208 pretrig samples + 2 sec rectime at
1024 sps — time axis now spans -203 ms to +2046 ms, trigger line at
~9% from the left edge as expected.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-23 21:58:20 +00:00
serversdownandClaude Opus 4.7 fd0e28657d sfm_webapp: default to Database view + sortable columns + inline waveform plot 
Three UX upgrades to the main SFM webapp at /, all reinforcing the
'browse stored events' flow as the primary entry point:

1. Default section is now Database, not Live Device.  Most users land
   here to look at stored events; Live Device is opt-in (click the tab
   to talk to a unit).  Initial history + units fetch fires on first
   paint so the table is populated when the page loads.

2. History table columns are sortable.  Click any header to sort:
   timestamp, serial, per-channel PPV (Tran/Vert/Long), PVS, mic dB(L),
   project, client, type, key.  Default direction varies by column type
   (desc for numbers + timestamps, asc for text).  Sort arrows appear
   in the active column header.  Headers are sticky so they stay
   visible while scrolling.

3. Click-event-to-see-waveform.  The existing sidecar review modal now
   renders the 4-channel waveform plot inline at the top, fetched from
   /db/events/{id}/waveform.json in parallel with the sidecar fetch.
   Channels stacked MicL / Long / Vert / Tran (Instantel printout
   order), shared bottom time axis, dashed trigger line + triangle
   markers at t=0, zero baseline with "0.0" label on the right edge,
   peak callouts per channel.  Charts cleaned up on modal close.

Resolves the "where is the viewer" surprise — operators no longer need
to know about the /events route to see waveforms.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-23 19:39:18 +00:00
serversdownandClaude Opus 4.7 c14a8c54db event_browser: Instantel-printout-style polish 
Apply the cheap visual wins from the BW Event Report layout:

  1. Channel order reversed → MicL (top), Long, Vert, Tran (bottom)
     to match the Instantel printout.
  2. Shared bottom time axis — x-axis ticks only render on the
     bottom-most data channel; other channels hide ticks so all four
     visually share one time scale.
  3. Triangle trigger markers above and below the t=0 dashed line.
  4. Horizontal zero-baseline (dotted) per channel with "0.0" label
     on the right edge — Instantel convention.
  5. "Print view" toggle that flips dark→light theme (white panels,
     light grids, dark text) so the viewer can render usefully on
     paper-style output / @media print.
  6. Per-channel PPV stats table in the metadata header, with Peak
     Vector Sum displayed prominently.
  7. Colors adjusted to approximate BW trace colors (magenta MicL,
     blue Long, green Vert, red Tran).

Future PDF-export work will reproduce the same layout server-side
once you upload a real example PDF and we pick a rendering pipeline
(weasyprint / chromium --print-to-pdf / etc.).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-23 07:09:12 +00:00
serversdownandClaude Opus 4.7 460006e5cd sfm: stored-event browser at /events 
New standalone HTML page (sfm/event_browser.html, ~470 lines, Chart.js)
that lets you browse persisted events from the SeismoDb + WaveformStore.
Companion to the existing live-device viewer at /waveform:

  /waveform  — connect to a unit and pull events in real time
  /events    — browse events already stored in the DB

Flow:
  1. Page loads → GET /db/units → populate serial dropdown
  2. Select serial → GET /db/events?serial=X&limit=500 → event list
  3. Click event → GET /db/events/{id}/waveform.json → render

Layout is Instantel-printout-ready: channels stacked vertically in
Tran / Vert / Long / MicL order, trigger line at t=0, peak labels,
clean dark theme.  Frames the future PDF-export feature without
needing extra layout work.

Smoke-tested against the dev prod-snapshot — 4 channels render with
correct peaks for K558 events (L=0.3 in/s = the offset-fault peak
we've been chasing all week).

CHANGELOG entry added under [Unreleased] per the v0.20.0 release plan.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-23 06:53:48 +00:00
serversdownandClaude Opus 4.7 8710b8f327 docs: record three known issues discovered during prod deployment 
1. bw_ascii_report parser misses PPV/vector_sum fields on certain TXT
   formats (5 events in prod).  Parser extracts every OTHER field for
   the same channels — likely a regex / format mismatch specific to
   some firmware-or-event-type combination.

2. NULL-timestamp duplicate rows.  events.timestamp can come back as
   NULL when the codec can't extract a footer timestamp; UNIQUE(serial,
   timestamp) doesn't fire on NULL, so backfills create new rows
   instead of upserting.  2 affected events on prod, easy SQL cleanup.

3. Histogram body sub-format with byte[5] != 0.  ~3 events on prod
   (T190LD5Q, O121L4L1) use a histogram body the walker doesn't
   recognize.  Codec returns 0 valid blocks; DB peaks come from the
   bw_report ASCII overlay so DB columns are correct, only the .h5
   plot is empty.  Cracking the sub-format unlocks the plot.

All three are pre-existing issues that today's deployment surfaced
during validation; none are regressions.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-22 21:02:13 +00:00
serversdown db657bcac9 Merge pull request 'fix: bw_report overlay onto event before DB, prevents data loss docs: three-tier architecture model + strategic roadmap' (#27) from feat/wire-histogram-codec into dev 
Reviewed-on: #27
 2026-05-22 15:46:46 -04:00
serversdownandClaude Opus 4.7 35842ac50a backfill: overlay bw_report onto Event before DB upsert 
Mirror what the ingest path does: BW's reported peaks (and sample_rate
/ record_time) take precedence over codec output where present.

Without this, --force backfill silently overwrites bw_report-overlaid
DB columns with codec-derived peaks.  Wrong for events where the codec
doesn't fully decode (waveform walker edge cases on SP0/SS0/SV0-style
events, histogram byte[5]!=0 sub-format that isn't yet RE'd), producing
PVS=0 on real high-amplitude events.  Bit on prod 2026-05-22 with
three top-10 waveform events ending up at PVS=0 (rolled back same day,
this fix is the proper resolution).

New helper minimateplus.event_file_io.apply_bw_report_dict_to_event
operates on the projected sidecar dict shape (the structure
_bw_report_to_dict produces, which is what gets preserved in the
sidecar).  Mirrors apply_report_to_event's semantics: only writes
fields where bw_report has a non-None value, no-ops cleanly on
empty / None input.

Dev validation against prod snapshot:
  pre  : 1839.7315 pvs_sum   356 events with DB PVS ≠ sidecar bw_report
  post : 2016.4902 pvs_sum     2 events still mismatched (both have NULL
                                timestamp + duplicate rows, edge case)

Both edge-case events DO get the correct value written by the new
backfill — their stale rows from prior backfills remain because
UNIQUE(serial, timestamp) doesn't fire on NULL.  Separate dedup
cleanup needed for those 2 events (0.014% of corpus); not blocking.

Backfill remains idempotent + bw_report preservation still passes
(0 WIPED, 0 CHANGED on the 3rd consecutive run).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-22 18:56:22 +00:00
serversdownandClaude Opus 4.7 49a524d0d4 docs: three-tier architecture model + strategic roadmap 
CLAUDE.md gains an Architecture section near the top describing the
canonical three-tier mental model:

  - SFM: device-side, live connections, /device/* endpoints
  - SDM: data-side, DB + waveform store + /db/* endpoints (currently
    living under sfm/ for historical reasons; rename deferred)
  - Codec library: pure data-interpretation, used by both tiers

Future code should be placed and named according to this model even
though the directory layout doesn't fully reflect it yet.  Decision
rule for where new code goes is documented inline.

README.md's Roadmap section gains two strategic-direction subsections:

  - "Strategic direction" — frames the suite-of-components vision and
    notes that BW ACH + Thor IDF call-home remain the data movers;
    seismo-relay's value is on the receiving and processing side.
  - "Terra-View ↔ SFM device control" — the long-term vision where
    Terra-View can launch into SFM device-control surfaces (operator
    notices missing unit → clicks "Connect to Device" → live view in
    browser).  Includes concrete implementation checklist (auth,
    embedded live-monitor view, action history, series IV live
    support).

The existing tactical roadmap items remain unchanged below.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-22 18:38:00 +00:00
serversdown 9ef424d098 Merge pull request 'Histogram body codec — full RE + peak-count fix that resolves the prod inflation incident' (#26) from feat/wire-histogram-codec into dev 
Reviewed-on: #26
 2026-05-22 13:08:03 -04:00
serversdownandClaude Opus 4.7 ed6982c512 scripts: bw_report preservation check for backfill safety 
Two-step tool to verify that backfill_sidecars doesn't wipe the
bw_report block from existing sidecars.  Workflow:

  1. snapshot --out before.json    (canonical-JSON hash per sidecar)
  2. run backfill
  3. diff --baseline before.json   (classifies every sidecar:
       PRESERVED / CHANGED / WIPED / STILL_MISSING / NEW / ADDED / REMOVED)

Exit code 1 if any WIPED or CHANGED entries found, 0 otherwise — so
it can gate a CI step or a deploy script.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-21 06:13:52 +00:00
serversdownandClaude Opus 4.7 d506ebc103 histogram_codec: peak count is uint8 (not uint16 LE) — properly cracks 
the BE9558 / BE18003 extension-byte case

The bytes at [7]/[11]/[15]/[19] are an annotation field (purpose still
unclear — empirically non-zero on intervals with sub-Hz or unmeasurable
freq), NOT the high byte of the peak count.  The N844 fixture corpus
the original RE was done against had zero values in those bytes for
every block, so uint8 and uint16 LE were equivalent there — but on
real BE9558 Tran-drift events and BE18003 Histogram+Continuous events
the uint16 LE interpretation produced peaks up to 268 in/s and 35×
inflated PVS sums.

Cross-correlated against BW's per-interval ASCII export on:
  - K558LKZU/LL1P/LL3K  → 100% T/V/L/M peak match (1435 blocks each)
  - T003LKZR/LL0O/LL1M  → 100% T/V/L, 99.3% M (0.05 dB rounding only)
  - N599LKZS/LL0L        → 100% all channels
  - N844 fixture corpus  → 100% all channels (unchanged)

Annotations preserved on every record for future RE; the defensive
_MAX_PEAK_COUNT bound is no longer needed (uint8 maxes at 1.275 in/s,
well below any physical limit).

Synthetic regression test added using the verbatim K558LKZU.RE0H
interval-12 block.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-21 06:05:19 +00:00
serversdownandClaude Opus 4.7 e949232875 histogram_codec + backfill: tighter peak ceiling, preserve bw_report 
histogram_codec: drop _MAX_PEAK_COUNT 4096 → 2200. The old ceiling
let extension-byte blocks slip through at up to 20.48 in/s per
channel, producing 35× inflated PVS sums when first deployed to
prod. 2200 covers Normal-range full-scale (10 in/s = 2000 counts)
plus 10% headroom for quantization edge cases.

backfill_sidecars: also preserve the bw_report block alongside
review + extensions when regenerating sidecars. event_to_sidecar_dict
takes a BwAsciiReport dataclass not a dict, so for bw_report we
overlay the existing block after regen rather than passing as a kwarg.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-21 02:50:10 +00:00
serversdownandClaude Opus 4.7 bc5a2d3f19 histogram_codec: defensive bounds-check on peak counts 
Discovered while running the backfill on prod: certain histogram
blocks contain an undocumented extension byte format whose naive
uint16 LE interpretation yields physically impossible peak values
(150+ in/s when the device max is 10).  Concrete example from
K558LKSG.3I0H block at body+7424:

  bytes [6:10] = 05 79 69 00
  current code: T_peak = uint16 LE = 0x7905 = 30981 → 154.9 in/s
  reality:     T_peak = byte[6] = 5 → 0.025 in/s (matches BW display)

The high byte (0x79 here) appears to be an extension field — possibly
"time of peak within interval" or a Histogram+Continuous sub-mode
marker.  Observed across BE9558 and BE18003 units in prod data; never
appeared in the BE12844 fixture corpus the codec was originally
verified against.

Effect on prod: 26 out of 1433 blocks in this one event had inflated
peaks, plus dozens of similar events across the fleet → sum(PVS)
inflated from baseline 988 to 34501 (35x).  Rolled back via the
pre-backfill snapshot before any UI exposure.

Defensive fix: bounds-check peak counts in `_decode_block`.  Any
field exceeding `_MAX_PEAK_COUNT` (4096 = ~20 in/s, well past the
device's 10 in/s Normal-range FS) causes the block to be skipped
entirely.  Other valid blocks in the same event still decode
correctly.

Trade-off: those skipped blocks lose their per-interval data
(peaks + frequencies).  Acceptable until the extension format is
reverse-engineered — better than propagating bogus values into PVS
computations downstream.

The 24 existing tests all still pass — the fixtures used during the
original codec development don't exercise the extension-byte case.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-21 02:17:33 +00:00
serversdownandClaude Opus 4.7 88549bc659 backfill_sidecars: filter out Thor IDF files 
Discovered while dry-running the backfill on prod: the waveform store
contains both BW (.AB0*/.N00) and Thor IDF (.IDFW/.IDFH) event files
side-by-side because both go through the same per-serial directory
layout.  The script's `_looks_like_event_file` heuristic accepted any
3-4 char extension ending in W or H, which matched both BW and IDF.

The script then routes everything through
`event_file_io.read_blastware_file`, which rejects IDF files with
"not a Blastware file (bad header prefix)" — 3807 errors on prod
out of 7201 total events.

Thor IDF events have their own ingest path
(`WaveformStore.save_imported_idf`) and their sidecars are populated
at ingest from the paired `.IDFW.txt` ASCII report.  The backfill
script has no value to add for them — there's no decoder to refresh,
and the sidecar metadata is already correct.  Filter them out.

After this fix, the prod backfill should run clean: ~3392 BW events
get sidecar+h5 regen as expected; the ~3807 Thor IDF events are
silently skipped.

The proper "IDF backfill" (refresh tool_version stamp on IDF
sidecars by re-running event_to_sidecar_dict against the stored
DB row + sidecar extensions block) is a separate, narrower
follow-up — not blocking the BW backfill rollout.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-21 01:20:08 +00:00
serversdown 76bce0b5a3 Merge pull request 'v0.20.0 - prerelease features.' (#25) from feat/wire-histogram-codec into dev 
- dockerfile fix
- histogram body codec FULLY decoded
- backfill scripts fixed.
- docs added for histogram codec
 2026-05-20 21:05:37 -04:00
serversdownandClaude Opus 4.7 7183b953e4 minimateplus: histogram body codec — FULLY DECODED 
The histogram-mode event body is now byte-exact decodable.
Companion to the waveform body codec — together they cover every
event file the watcher forwards.  Cracked in one session via
cross-event correlation against BW's ASCII export.

The §7.6.2 spec in instantel_protocol_reference.md was structurally
correct (32-byte blocks) but the per-sample semantics were
under-documented.  Cross-checking block 130 of N844L6Z8.ZR0H
against its TXT row revealed the layout perfectly:

  slot[0] = 10 (constant marker)
  slot[1] = T_peak_count    (× 0.005 → in/s at Normal range)
  slot[2] = T_halfperiod    (freq_Hz = 512 / halfp)
  slot[3] = V_peak_count
  slot[4] = V_halfperiod
  slot[5] = L_peak_count
  slot[6] = L_halfperiod
  slot[7] = MicL_peak_count (dB via waveform_codec.mic_count_to_db)
  slot[8] = MicL_halfperiod

The `>100 Hz` sentinel is halfperiod ≤ 5 (since 512/5 = 100 Hz).
Mic dB uses the SAME formula as the waveform codec (sign × (81.94
+ 20·log10(|count|))) — they share the mic ADC calibration constant.

Block identification anchor: bytes [22:24] == 0x0000 AND
bytes [28:32] == 1e 0a 00 00.  The tail signature is the most
reliable distinguisher from non-block content in the file.

Files:

  minimateplus/histogram_codec.py (new) — decoder + public API
    matching the waveform codec's shape:
      walk_body(body) -> records
      decode_histogram_body(body) -> {Tran, Vert, Long, MicL}
      decode_histogram_body_full(body) -> [per-interval dicts]
      half_period_to_hz, geo_count_to_ins helpers

  minimateplus/event_file_io.py (modified) — read_blastware_file
    now tries the waveform codec first, falls back to the histogram
    codec on failure.  Same output shape, same downstream pipeline.

  tests/test_histogram_codec.py (new) — 24 regression locks against
    the in-repo fixture corpus, byte-exact against BW ASCII export
    for peaks (all 4 channels), frequencies (all 4 channels,
    including >100 Hz sentinel handling), block framing, and
    segment-ID accounting.

  scripts/backfill_sidecars.py (modified) — the has_samples
    short-circuit added in the histogram-pending era is now a
    pure defensive guard.  Histograms in prod will regen .h5 files
    correctly on the next backfill run.

  docs/histogram_codec_re_status.md (updated) — supersedes the
    earlier "in progress" version with the verified format and
    test-coverage summary.  Notes a few non-essential fields still
    open (4-byte block metadata, Geo PVS, Mic psi(L) — none of
    which are needed for waveform reconstruction).

Total verified coverage: ~3,500 blocks across 5 fixtures, every
field of every block byte-exact against BW.

The watcher-forwarded histogram event corpus on prod (~10,000
events) will now produce correct .h5 sidecars on the next backfill
run.  No additional changes needed to the backfill flow — the
existing tool_version-bump cascade picks them up automatically.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-20 23:05:13 +00:00
serversdownandClaude Opus 4.7 c3c7fe559c docs: histogram body codec RE — starting-point status doc 
Captures everything learned in the 2026-05-20 session before scope
forced a pause:

  - Block framing is solved: 32-byte blocks, one per histogram
    interval, signature byte pattern `[22:24]=0x0000` +
    `[28:32]=0x1e 0x0a 0x00 0x00` reliably identifies data blocks.
  - Block count = interval count (791 blocks in N844L20G.630H for
    a TXT-reported 792 intervals).
  - Sample[0] = Tran peak in 0.0005 in/s/count units (verified on
    one event — needs cross-event confirmation).
  - Samples 1-8 → channel/metric mapping is still open.  None of
    the obvious layouts (peak-then-freq alternating, all-peaks-
    then-all-freqs, per-channel 3-tuples) match the TXT values
    across multiple blocks.  Likely needs a higher-activity
    fixture (current N844 corpus is all noise-floor data) to
    disambiguate.
  - `>100 Hz` sentinel encoding in the binary is unknown.
  - 4-byte variable metadata field at block[24:28] needs
    correlation work against TXT columns.

Doc mirrors the structure of docs/waveform_codec_re_status.md so
a future RE session has a familiar entry point.  Includes the
suggested attack plan + the code seam where the eventual decoder
will land (minimateplus/histogram_codec.py).

The §7.6.2 spec in instantel_protocol_reference.md is structurally
correct but doesn't pin down per-sample semantics — this doc
supersedes it where they conflict on confidence level.

No code shipped on this branch.  When the codec is cracked, the
plan is to land minimateplus/histogram_codec.py + wire into
event_file_io.read_blastware_file() + remove the has_samples
short-circuit from scripts/backfill_sidecars.py.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-20 21:13:26 +00:00
serversdownandClaude Opus 4.7 fa9d3cdef2 read_blastware_file: leave peak_values=None when samples can't be decoded 
Fixes a data-loss bug discovered while dry-running the backfill against
the prod store.

Symptom: every histogram event in the store has its body decoded by
read_blastware_file → codec returns None → samples = empty dict →
``ev.peak_values = _peaks_from_samples(empty)`` returns
``PeakValues(0, 0, 0, 0, 0)`` (NOT None).  The backfill script's
existing "seed from DB row when peak_values is None" branch then
correctly *skips* the seeding, and the all-zeros PeakValues flows into
``db.insert_events()``'s UPSERT path, OVERWRITING the existing good DB
peak values for that event (which were populated from the paired BW
ASCII report at ingest).

Net effect: running the backfill on prod would have wiped the PPV /
mic / vector-sum columns for ~10,000 histogram events.

Fix: only compute peaks-from-samples when there are actually samples.
For events the codec couldn't decode (histogram-mode bodies, until
the §7.6.2 histogram codec is wired in), leave peak_values=None as
the "we don't know" signal.  Downstream consumers:

  - backfill_sidecars.py — its existing ``if ev.peak_values is None:``
    branch (line 243) seeds from the DB row, preserving the real
    BW-report peaks across the regen.
  - WaveformStore.save_imported_bw — apply_report_to_event overlays
    peaks from the paired BW ASCII report when one was uploaded.
    Histogram imports without a paired report end up with NULL peaks
    in the DB, which is correct (better than zeros — clearly says
    "no peak data available" rather than "peaks are exactly zero").

Updated the existing synthetic-event round-trip test to expect
peak_values=None for the no-real-body case, which is the truth now.

The 7 fixture-corpus regression tests for real BW waveforms continue
to pass — those have decodable samples, so peak_values is still
populated from the codec output as before.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-20 20:30:53 +00:00
serversdownandClaude Opus 4.7 c4648c1959 scripts/backfill_sidecars: skip .h5 write when decoder returned no samples 
Discovered while dry-running the backfill on the prod store: ~10,000
of ~10,059 events are histogram-mode (filename extension `*H`), and
the waveform-body codec wired in via the previous commit doesn't
handle histogram-mode bodies — only the waveform-mode codec at
§7.6.1 is implemented; the histogram-mode codec at §7.6.2 of the
protocol reference is documented but no Python implementation
exists yet.

Without this guard, every histogram event's .h5 file would be
*replaced* with an empty one — strictly worse than today's
broken-int16-LE .h5 because any downstream viewer expecting
non-empty sample arrays would now error out instead of just
rendering wrong values.

Fix: after the decoder runs, check whether any channel has samples.
If not, skip the .h5 write entirely.  The sidecar still regenerates
(refreshing the tool_version stamp and any peaks/project info from
the DB row), but the existing .h5 is left untouched.

This is a *temporary* gate.  When the histogram codec lands (next
branch: `feat/wire-histogram-codec`), the has_samples check can be
removed and the backfill will then correctly regenerate all .h5
files, histogram and waveform alike.

Observed effect (dry-run on prod store, 10,059 events):
  - waveform events (~5%): "[DRY ] would write … + .h5 (would (re)write)"
  - histogram events (~95%): "[DRY ] would write … + .h5 (skipped-empty-samples)"
  - sidecar tool_version bump succeeds for both

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-20 20:16:31 +00:00
serversdown 0e89125495 docker: fix dockerfile to include scripts and micromate folders 2026-05-20 19:58:54 +00:00
serversdown fffb363b2b Merge pull request 'minimateplus: wire read_blastware_file to verified body codec' (#24) from feat/wire-codec-to-import-path into dev 
Reviewed-on: #24
 2026-05-20 15:26:15 -04:00
serversdownandClaude Opus 4.7 e8682d49ad scripts/backfill_sidecars: cascade h5 regen when sidecar is stale + bump TOOL_VERSION 
Two coupled changes that close the rollout gap left by the
read_blastware_file codec wiring:

1. minimateplus/event_file_io.py: bump TOOL_VERSION from 0.16.1 to
   0.20.0.  This is the version stamp the backfill script reads from
   each sidecar's source.tool_version field to detect "this sidecar
   was written before the current decoder shipped, regenerate it."
   Bumping past every value baked into existing prod sidecars flags
   them all as stale on the next backfill run — which is exactly what
   we want, since every pre-codec-wiring sidecar was written by the
   retracted int16-LE decoder.

2. scripts/backfill_sidecars.py: when the sidecar is being
   regenerated this iteration (sha mismatch, tool_version too old,
   or --force), also regenerate the .h5.  Previously the .h5 logic
   only rewrote when --force was passed or the file was missing —
   so a tool_version-driven sidecar regen left the broken .h5 in
   place forever.  Added a `sidecar_stale` boolean to track the
   "we're rewriting the sidecar this iteration" state and wired it
   into the h5 need-rewrite check.

   Path coverage (verified by trace):
     - sidecar missing  → both regen
     - --force          → both regen
     - sha mismatch     → both regen
     - tool_ver too old → both regen (THE post-codec-wiring case)
     - everything OK    → skip iteration entirely (h5 untouched)

Operator review state (review.false_trigger, reviewer, notes) and
the sidecar's extensions block are preserved across regen by the
existing read-existing-sidecar / pass-into-event_to_sidecar_dict
path — unchanged from prior behavior.

Deploy procedure (on prod):
  1. Pull this change + the read_blastware_file codec wiring.
  2. `python scripts/backfill_sidecars.py --dry-run` to preview.
     Every sidecar with source.tool_version<0.20.0 will show as
     "would (re)write".
  3. Run for real (drop --dry-run).  Expect every pre-fix event
     to regen.  Big stores may take a while.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-20 18:24:06 +00:00
serversdownandClaude Opus 4.7 31d691b40b minimateplus: wire read_blastware_file to verified body codec 
`read_blastware_file()` was still calling `_decode_samples_4ch_int16_le`
(the retracted int16-LE-interleaved hypothesis) on the body bytes,
producing ±32K noise on every channel of every BW file read from disk.
This was the path watcher-forwarded events take into the system
(via the import endpoint → save_imported_bw → read_blastware_file,
since the watcher doesn't ship A5 frames), so every .h5 sidecar
generated for a forwarded event has been wrong since the feature
shipped.

The fix is mechanical: pass the body bytes straight to
`waveform_codec.decode_waveform_v2()` and run the result through
`decoded_to_adc_counts()` for the 16x geo scaling.  The body already
starts with the codec's exact 7-byte preamble `00 02 00 [Tran[0] BE]
[Tran[1] BE]` — confirmed by `body[:3].hex()` across all 9 fixture
events.  No body-slice adjustment needed.

If the codec returns None (truncated/malformed file, synthetic test
input with no real waveform), fall back to empty channels with a log
warning.  The rest of the event (timestamp, waveform_key, project
strings, sensor_location, peaks-from-samples=0) is still recoverable.

Verified against the bundled fixture corpus:

  V70  Tran/Vert/Long 3328/3328 sample-sets match .TXT ground truth
       within the 0.005 in/s display quantum, every row
  6S0/RG0/AB0/470 (5-8-26)  3328/2304/1280/1280 samples; Vert PPVs
       match BW's own report within 0.02 in/s
  JQ0  3328 samples, Vert PPV 3.384 vs BW 3.465
  SP0/SS0/SV0 (loud events)  3072–3328 samples; known walker
       tail-truncation 1–7 samples per channel, samples reached are
       byte-exact

Existing `test_read_blastware_file_round_trip` (synthetic empty event)
continues to pass thanks to the None-fallback.  Codec verify scripts
(`analysis/verify_quiet_bundle.py`, `analysis/verify_full_decode.py`)
re-run unchanged.

Added two regression-lock tests in tests/test_event_file_io.py:
  - test_read_blastware_file_decodes_via_codec[6 fixtures]
    — verifies sample count + Vert PPV per fixture
  - test_read_blastware_file_v70_samples_match_txt_truth
    — verifies every one of V70's 3328 sample-sets across Tran/Vert/Long
      matches the .TXT ground truth row-by-row within 0.003 in/s

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-05-20 18:13:24 +00:00
serversdown beca5de06e docs: clean up and verify s3 protocol docs 2026-05-20 17:55:02 +00:00
serversdown d85df4c886 Merge pull request 'merge full s3 codec decoded' (#23) from codec-re into main 
Reviewed-on: #23
 2026-05-20 13:45:32 -04:00
Claude 0466bb4f44 codec: crack wide-NN blocks (1X NN / 2X NN); loud events now fully decode 
When NN exceeds 0xFC, the codec extends to 12-bit NN by using the
low nibble of the TYPE byte as the high nibble of NN:

    1X NN  →  nibble-delta block, NN = (X << 8) | NN_byte
    2X NN  →  int8-delta block, same NN encoding

Walker and decode_waveform_v2 now handle both narrow (X=0) and wide
(X != 0) forms uniformly.

Discovered while investigating why SP0/SS0/SV0/event-b walkers stopped
mid-event.  SP0 segment 12 (V continuation, cycle 3) starts with
"11 90" — high nibble of byte 0 = 1 (= nibble-delta block type), low
nibble = 1 plus byte 1 = 0x90 → NN = 0x190 = 400 nibble deltas in
202 bytes.  Walker was rejecting "11" as a non-tag.

Sample count went from 47,364 to 72,972 verified byte-exact:

  event-a:  9984 (full)        was 9984 (full)
  event-b:  6912 (full)        was   738
  event-c:  3840 (full)        was 3840 (full)
  event-d:  3840 (full)        was 3840 (full)
  JQ0:      9984 (full)        was 9984 (full)
  V70:      9984 (full)        was 9984 (full)
  SP0:      9984 (full)        was 5122
  SS0:      9222 (-7 tail)     was 1758
  SV0:      9222 (-7 tail)     was 2114

7 of 9 fixtures now decode end-to-end across all 3 geo channels.
The 2 remaining (SS0, SV0) are missing only 1-7 tail samples per
channel — minor walker edge case at the very end.

74 tests pass (was 71).
 2026-05-20 17:28:54 +00:00
Claude 85f4bcfe86 codec: wire decode_waveform_v2 into production; add MicL dB helper 
Replaces the broken legacy int16 LE decoder in client.py with the
verified multi-channel codec.  Three changes:

1. blastware_file.extract_body_bytes(a5_frames) — new helper that
   factors out the body-reconstruction logic from write_blastware_file
   so both writers (BW binary) and decoders (sample arrays) can use
   the same canonical bytes.

2. waveform_codec.decode_a5_frames(a5_frames) — production entry point.
   Returns the raw_samples dict consumers expect (Tran/Vert/Long as
   int16 ADC counts; MicL as native ADC counts).  Internally:
     A5 frames → extract_body_bytes → decode_waveform_v2
                → decoded_to_adc_counts (geos ×16; mic pass-through)

3. waveform_codec.mic_count_to_db(count) — MicL ADC → dB(L) per BW's
   display formula:
     dB = sign(count) × (81.94 + 20 × log10(|count|))   for |count| ≥ 1
   Verified against V70 fixture: count=813 → 140.14 dB (BW PSPL 140.1).

client.py:_decode_a5_waveform is reduced to a thin wrapper that calls
decode_a5_frames and populates event.raw_samples.  Original implementation
preserved as _decode_a5_waveform_LEGACY (dead code; reference only).

Also fixed a tail-end bug in decode_waveform_v2 where trailer-section
"40 02" markers (containing ASCII serial bytes, NOT real segment headers)
were being mis-interpreted, producing 2 spurious samples per channel at
the end of each event.  Added bytes [12:14] == "02 00" validation to
reject non-header markers.

7 new pytest tests cover the new helpers and dB conversion.  Total:
71 passing (up from 64).

Known limitation (carried over from before): the walker still stops
mid-event on the loudest fixtures (SP0/SS0/SV0/event-b) at some
mid-segment edge cases not yet characterized.  Every sample reached
is decoded correctly; the walker just doesn't reach all of them.
Loud events still yield 5,000–15,000 byte-exact samples each.
 2026-05-20 17:28:54 +00:00
Claude 2ff2762eec codec-re: 30 NN block CRACKED — codec fully decoded 
User intuition (16-bit) + 12-bit packing hypothesis + the int16 ADC
range constraint led to the final piece.

30 NN block format (CONFIRMED across all 14 blocks in the fixture
bundle):

  NN 12-bit signed deltas packed as NN/4 groups of 6 bytes each.
  Within each group:
    bytes [0:2] = 16 bits = 4 × 4-bit high nibbles (MSB-first)
    bytes [2:6] = 4 × int8 low bytes
    delta[k] = sign_extend_12((high_nibble[k] << 8) | low_byte[k])

  Block length = NN × 1.5 + 2 bytes (tag included).  Earlier walker
  used NN × 4 which is only correct in the TRAILER section.

Why 12-bit:  ±2047 in 16-count units ≈ ±10 in/s = the geophone's
full-scale range at Normal sensitivity.  The codec sizes its widest
delta to cover the worst-case sample-to-sample change.

Results: every decoded sample across all fixture events matches truth
byte-exact.  ZERO divergences.

  event-a:  9984 samples (full event, all 3 geos)
  event-c:  3840 (full event)
  event-d:  3840 (full event)
  JQ0:      9984 (full event)
  V70:      9984 (full event)
  SP0:      5122 (walker stops early on edge cases)
  SS0:      1758
  SV0:      2114
  event-b:   738

  TOTAL: 47,364 ADC samples verified, zero errors.

Three full 3-sec events decode end-to-end across all three geo
channels.  The events where fewer samples decode (SP0/SS0/SV0/event-b)
are limited by walker robustness issues past the first few segments,
NOT by decoder correctness.

64 tests pass (up from 55).  Files: minimateplus/waveform_codec.py
(new 30 NN decode + corrected walker length), tests/test_waveform_codec.py
(new full-event regression tests), docs/* (updated status everywhere),
analysis/test_30nn_hybrid.py (new — the analysis script that confirmed
the format).
 2026-05-20 17:28:54 +00:00
Claude d4cdce77fa codec-re: 30 NN partial finding — sum matches but per-sample distribution doesn't 
Tested the 12-bit signed packed delta hypothesis (motivated by the
observation that ±2047 in 16-count units ≈ ±32K raw ADC counts, almost
exactly the int16 ADC range — a strong design hint).

Result: mixed.  For SP0 block @1689 (V seg 4, samples 650..653):
  truth deltas:                47, 297, 384, 61   (sum = 789)
  12-bit BE contiguous pred:   17,  47, 664, 61   (sum = 789)

Positions 1 and 3 of the pred match truth values at positions 0 and 3
exactly, AND the total sum across all 4 positions matches.  But
positions 0 and 2 of pred don't match any truth value.

Hypothesis space narrows to:
- 12-bit deltas WITH a specific re-ordering or interleaving
- 12-bit deltas with one of the positions being a "step size" or
  "checksum-like" repacked value
- A nonlinear / coded format where the underlying total displacement
  is preserved but per-sample distribution is encoded differently

Two analysis scripts committed (test_30nn_12bit.py, test_30nn_v2.py).
The v2 script uses a real-decoder simulation to get the exact channel
+ sample-index for each 30 NN block, eliminating off-by-one errors in
the truth lookup.
 2026-05-20 17:28:54 +00:00
Claude ce5dc640ba codec-re: quiet bundle decodes FULLY (17k samples, zero errors) 
User asked the right question: do events without 30 NN blocks decode
fully?  Answer: YES.

  event-a:  Tran 3328 ✓  Vert 3328 ✓  Long 3328 ✓  (28 segments, 0 '30 NN')
  event-c:  Tran 1280 ✓  Vert 1280 ✓  Long 1280 ✓  (12 segments, 0 '30 NN')
  event-d:  Tran 1280 ✓  Vert 1280 ✓  Long 1280 ✓  (12 segments, 0 '30 NN')

17,664 ADC samples decoded byte-exact against BW's ASCII export.
Zero divergences across event-a, event-c, event-d.

This means the codec is FULLY SOLVED for any event without 30 NN
blocks.  The remaining gap is the 30 NN block format only — used for
high-amplitude regions where deltas exceed int8 range.  For quiet
events (or quiet stretches of loud events), the decoder is complete.

9 new regression tests bring the total to 55, all passing.

Files: tests/test_waveform_codec.py + docs/waveform_codec_re_status.md
+ new analysis/verify_quiet_bundle.py.
 2026-05-20 17:28:54 +00:00
Claude 07675626dc codec-re: channel rotation CONFIRMED — full multi-channel decoder works 
The segment-channel scoring analyzer (from scratch/next_experiment_skeleton.py)
ran and immediately confirmed the rotation hypothesis:

  SP0 seg 0: best fit Vert  508/508  ✓
  SP0 seg 1: best fit Long  508/508  ✓
  SP0 seg 3: best fit Tran  508/508  ✓  (Tran continuation)
  SP0 seg 5: best fit Long  508/508  ✓
  SP0 seg 9: best fit Long  508/508  ✓
  V70 seg 0: best fit Vert  508/508  ✓
  V70 seg 1: best fit Long  508/508  ✓

Channels rotate Tran → Vert → Long → MicL per 40 02 segment header.

Also discovered the segment header has DOUBLE duty: bytes [14:18] anchor
the NEW segment's channel (2 samples as int16 BE in 16-count units), AND
bytes [0:4] extend the PREVIOUS channel by 2 more samples (2 deltas as
int16 BE).  This is the same "2 anchors + delta stream" structure as the
body preamble for Tran.

decode_waveform_v2 now returns full per-channel sample dicts.
Byte-exact verified ranges:
  V70: Tran 512, Vert 512, Long 512   (all first segments)
  JQ0: Tran 512, Vert 258
  SP0: Long 1536 (all 3 L segments)

Still open: the 30 NN block format (high-amplitude packed deltas) —
appears mid-segment when single-byte deltas can't carry the magnitude.

6 new tests bring the count to 46.  All passing.
 2026-05-20 17:28:54 +00:00
Claude ae0e17b5dc codec-re: handoff polish — readmes, skeleton, remove decode-re/ duplicate 
Three things to make pickup smoother:

1. analysis/README.md (NEW): catalogues the ~25 scratch scripts.
   Categorizes them as "still useful" / "superseded — keep for
   archaeology" / "pure exploration".  Tells a fresh engineer which
   files to read first and which to ignore.

2. scratch/next_experiment_skeleton.py (NEW): stub + spec for the
   segment-channel scoring analyzer.  Includes the fixture loader,
   block walker, and decode-segment-as-channel helper — just enough
   scaffolding that the next pass starts from "fill in
   score_segment_against_all_channels()" rather than from scratch.
   Already runs and confirms 13 segments per 3-sec event with sample
   starts going to 6590 (way past the 3328 actual samples) — strong
   evidence that not all segments carry Tran.

3. Removed decode-re/ duplicate.  It was a mirror of tests/fixtures/.
   Analysis scripts that hardcoded decode-re/ paths updated to point
   at tests/fixtures/.  CLAUDE.md note updated: future event uploads
   go directly into a dated subdirectory under tests/fixtures/.

All 40 tests still pass.  Skeleton runs.
 2026-05-20 17:28:54 +00:00
Claude f68ee9f0f9 docs: clean up waveform-codec doc layers per review 
Three "truth layers" had drifted apart between commits.  Fixed:

1. waveform_codec.py docstring rewritten from the 2026-05-08
   "structural framing only" state to the 2026-05-11 "Tran segment 0
   solved + segment-header partially decoded" state.  Killed stale
   "~80 sample-sets per segment" language (real segments are
   flash-page-byte-sized, not sample-count-sized; observed first-segment
   sizes are 42-510 samples depending on signal).  Killed stale
   "preamble is 7 or 9 bytes" language (always 7).

2. docs/instantel_protocol_reference.md §7.6.1: added a clear
   "CURRENT STATUS" box at the top with a status table.  Replaced the
   stale "~80 sample-sets" line with the verified per-event segment
   sizes.  Merged two redundant segment-header field-table sections.

3. docs/waveform_codec_re_status.md (NEW): clean working-status doc.
   Solved / not solved / hypothesis / next experiment / fixtures /
   tests.  The protocol reference remains the historical Rosetta
   Stone; this new file is the current-truth working note that
   shouldn't accumulate fossil layers.

4. CLAUDE.md §"Waveform body codec": prominent warning box at top —
   "DO NOT TRUST decoded sample arrays yet."  BW binary passthrough
   is the only sample-bearing output to trust until the decoder
   lands.  Added a "Next experiment" subsection pointing the next
   pass at the segment-channel scoring analyzer.

40 tests still pass.
 2026-05-20 17:28:54 +00:00
Claude 5bf5329369 codec-re: add Waveform body codec section to CLAUDE.md 
Mirrors the structural findings now documented in
docs/instantel_protocol_reference.md §7.6.1: block framing solved,
Tran segment-0 decode verified across 5 fixture events, multi-segment
continuation still open. Also adds waveform_codec.py to the project
layout map.
 2026-05-20 17:28:54 +00:00
Claude 9ed6f2a8d8 codec-re: add segment 1 block dumper for analysis 
Investigated multi-segment Tran continuation but couldn't crack it.
Each hypothesis tried (segment header consumes 0/1/2 T deltas, blocks
continue Tran with various interpretations) breaks at sample ~512.

Block budget for V70 segment 1: 264 nibbles + 244 RLE zeros = 508
deltas — exactly the segment size. So the block structure CAN encode
508 single-channel samples, but applying segment 1 blocks as Tran
gives wrong values.

Most likely the channel ordering changes in segment 1+ (e.g., segment
0 = Tran, segment 1 = Vert, segment 2 = Long, etc.) but I couldn't
verify cleanly.  Stopping here — segment-0 Tran decode is solid and
multi-segment work needs more fresh thinking.
 2026-05-20 17:28:54 +00:00
Claude a0c9a482c7 codec-re: 00 NN is RLE; full Tran segment-0 decode (4 of 5 events) 
User uploaded a Vert-heavy event (JQ0) and a Mic-heavy event (V70).
Those two were exactly what was needed to crack the next piece:

- 00 NN block = run-length-encoded zero deltas in the current channel.
  Append NN copies of the current cumulative value (no change).
- find_data_start now recognizes 00 NN as a valid first tag (some events
  begin with a leading 00 NN RLE block).
- decode_tran_initial now decodes the FULL segment 0 (not just the first
  data block).

Results across 5 fixture events:
  - M529LL1A.SP0 (loud-all-channels)  : 510 / 510  ✓
  - M529LL1L.JQ0 (Vert-heavy)         : 510 / 510  ✓
  - M529LL1L.V70 (Mic-heavy)          : 510 / 510  ✓
  - M529LL1A.SV0 (loud-from-start)    :  58 /  58  ✓
  - M529LL1A.SS0 (loud-from-start)    :  42 / 502  (stops at first 30 04)

The 30 04 block (only seen in loud-from-start events) hasn't been
decoded yet — likely a channel-switch marker for the high-amplitude
regime.

Also discovered: segment header (40 02) payload bytes [0:2] = T_delta
at first sample of new segment, [6:8] = byte length to next segment.
Multi-segment Tran decoding still diverges after sample 512 because
the per-segment channel ordering after the header is unknown.

Tests: 40 pass (up from 36).

Files:
- minimateplus/waveform_codec.py: find_data_start fix, RLE handling,
  full segment-0 decode in decode_tran_initial
- tests/test_waveform_codec.py: synthetic RLE test, full segment 0
  tests for JQ0 and V70
- tests/fixtures/5-11-26/: M529LL1L.JQ0, M529LL1L.V70 + TXT exports
- docs/instantel_protocol_reference.md §7.6.1: RLE + segment-header docs
 2026-05-20 17:28:54 +00:00
Claude 6ac126e05c codec-re: crack Tran channel codec with high-amplitude May 11 bundle 
User uploaded 3 high-amplitude events (PPV 6-7 in/s — shook the geophone
hard) to decode-re/5-11-26/.  These cracked the Tran codec:

- Preamble bytes [3:5] and [5:7] = Tran[0] and Tran[1] as int16 BE
  in 16-count units (LSB = 0.005 in/s).  Confirmed across all 7
  fixtures.
- First data block carries Tran deltas from sample 2 onward:
  * 10 NN block: NN/2 bytes of payload, each byte = two 4-bit signed
    nibble deltas (high nibble first)
  * 20 NN block: NN int8 signed deltas

Verified 22+42+46 = 110 Tran samples across SP0/SS0/SV0 with 0 errors
against BW's ASCII export.

Why the earlier 96-combination brute force failed: the quiet 5-8
events all had T[0] = T[1] ≈ 0 so the preamble's per-channel encoding
was undetectable.  Loud events made the encoding obvious.

What's solved:
- minimateplus.waveform_codec.decode_tran_initial: returns first
  N Tran samples in 16-count units for any body.
- Walker length formula for in-data 30 NN blocks (NN*2 instead of NN*4).
- Walker now handles bodies that start with 20 NN (in addition to 10 NN).

What's still open:
- Tran past the first data block (multi-block channel switching).
- Vert / Long / MicL channel encodings.
- Walker correctness past offset ~427 in event-b.

Tests: 36 pass.  decode_waveform_v2 still returns None — the full
multi-channel decoder is not wired up.  decode_tran_initial is the
new verified entry point.

Files: minimateplus/waveform_codec.py, tests/test_waveform_codec.py
(adds 5-11-26 fixtures + decode_tran_initial tests), and
docs/instantel_protocol_reference.md §7.6.1 (Tran codec spec).
 2026-05-20 17:28:54 +00:00
Claude d3f77d1d96 codec-re: solve waveform body block framing; per-byte sample mapping still open 
Decoded the structural framing of the Blastware waveform body — the bytes
between the 21-byte STRT record and the 26-byte file footer.  The body is
a sequence of tagged variable-length blocks, NOT raw int16 LE.  Five tag
types (10/20/00/30/40 NN) and their lengths are now confirmed against the
4-event May 2026 fixture bundle.  Body splits cleanly into ~16 segments
(for a 1280-sample event) separated by 40 02 segment headers carrying a
monotonically incrementing uint32 LE counter at bytes [8:12].

What's done:
- minimateplus/waveform_codec.py — block walker, segment splitter, segment
  header parser.  decode_waveform_v2 is a stub returning None until the
  byte-to-sample mapping is solved; client.py is unchanged.
- tests/test_waveform_codec.py — 31 tests covering block detection, lengths,
  contiguous-walk, segment splitting, segment-header parsing, and counter
  monotonicity.  All pass.
- tests/fixtures/decode-re-5-8-26/ — bundled fixtures (4 events, BW binary
  + Blastware ASCII export each).
- docs/instantel_protocol_reference.md §7.6.1 — replaced retraction box
  with the verified structural decoding plus an explicit list of what's
  still open.

What's still open: the per-byte mapping inside 10 NN / 20 NN blocks.  96
channel-permutation × nibble-order × sign-convention combinations were
brute-force tested; none match BW's ASCII export to within ±1 ADC count.
The codec is more elaborate than uniform 4-bit deltas — likely a hybrid
variable-bit-width scheme with segment-anchor resync points.  Next
recommended step: capture an event with a known calibration tone to pin
down magnitude scaling.

Walker also bails out partway through event-b (open issue documented in
both the module and the protocol reference).
 2026-05-20 17:28:54 +00:00
serversdown 7bd0f8badf Pull in v0.18 - Merge branch 'main' into codec-re 2026-05-20 16:50:03 +00:00
Claude 8316a1bbd8 docs(protocol): accuracy sweep across the protocol reference 
Three-pass audit of docs/instantel_protocol_reference.md against
CLAUDE.md and the minimateplus/ implementation. Closes long-standing
discrepancies that had accumulated as the protocol understanding
evolved month over month.

Major corrections:
- §2/§3: S3 frames terminate on bare ETX, not DLE+ETX; payload
  byte[1] is flags / byte[2] is SUB (was wrongly DLE/ADDR).
- §4.2: probe responses do not carry data length; DATA_LENGTH
  is a per-SUB hardcoded constant.
- §5.1: dropped stale duplicate "SUB 1C = TRIGGER CONFIG READ"
  row; SUB 0A lengths corrected from 0x30/0x26 to 0x46/0x2C.
- §5.3: added the missing write-frame mechanics (BW_CMD-only
  doubling, DLE-aware checksum, offset = data[1]+2, ack format,
  SUB 71 chunk parameters).
- §7.6.x: switched compliance-anchor convention from the unstable
  10-byte form to the canonical 6-byte `\xbe\x80\x00\x00\x00\x00`;
  recording_mode confirmed at anchor−8 in both read and write
  (the prior anchor−3/−4 split caused anchor drift on write).
  Sample_rate at anchor−6, histogram_interval at anchor−4 (now ✅),
  record_time at anchor+6. Geo_range row added at channel_label+33.
- §7.5b/§8: added the 10-byte sub_code=0x03 continuous-mode
  timestamp variant; peak vector sum location corrected from
  fixed offset 87 to label-relative tran_pos−12.
- §7.7.2: SUB 1E/1F token byte at params[7], not params[6].
- §7.7.3: SUB 0A length disambiguation rewritten.
- §7.8.4/§7.8.7: fi==9 skip marked FIXED; metadata-page TODO
  replaced with current decoder state.
- §11: POLL example wire bytes corrected; SUB 5A row added to
  checksum table.
- §13/§14: device-under-test updated to BE11529/S338.17; TCP
  Idle Timeout consistency fix (0→2 min); Data Forwarding
  Timeout units clarified.
- §15 (renumbered from second §14): open-question entries
  already resolved in CLAUDE.md closed out.
- Appendix D: extension taxonomy rewritten — extensions encode
  a timestamp (AB0T scheme), not recording mode.

Navigation note added to §7 acknowledging the organic-growth
duplicate section numbers (§7.5/§7.5b, §7.6, §7.7, §7.8, §7.9)
and pointing readers to the canonical sections for each topic.

https://claude.ai/code/session_019tWZybD94YUsBaEGhnM5A2
 2026-05-20 15:41:42 +00:00
serversdown 8f568b809b Merge pull request 'v0.19.0 - minimate compatability + family separation' (#22) from dev into main 
## v0.19.0 — 2026-05-20

The "device-family separation" release.  Tightens the boundary between Series III (MiniMate Plus / Blastware) and Series IV (Micromate / Thor) so the UI and storage layer dispatch deterministically by family instead of sniffing filename extensions or magnitude heuristics.

### Added — Phase 1: `device_family` column on `events`

- **`events.device_family TEXT`** — new column carrying `"series3"` or `"series4"`.  Populated by every import path (`/db/import/blastware_file`, `/db/import/idf_file`, ACH server, BW CLI, sidecar backfill script).  Returned through `/db/events` since `query_events` uses `SELECT *`.
- **Self-applying migration** — on startup, `ALTER TABLE ... ADD COLUMN` lands the new column; a follow-on `UPDATE` backfills existing rows from the binary filename extension (`.IDFH`/`.IDFW` → `series4`, everything else → `series3`).  No manual SQL needed.
- **UPSERT preserves family** — re-imports without an explicit family don't blank existing rows (`COALESCE(?, device_family)`).
- **UI dispatches on the column** — `sfm_webapp.html` events-table mic formatter now branches on `ev.device_family === 'series4'` (Thor stores native dB(L); BW stores psi).  Modal uses `source.kind === 'idf-import'` from the sidecar (sidecars don't carry the DB column).  Source-files section labels changed from "BW filename / BW filesize / BW sha256" to format-neutral "Event file / File size / File sha256".

### Added — Phase 2: `micromate/` package alongside `minimateplus/`

- **`micromate/`** — new sibling package for the Thor / Micromate Series IV device.  Currently scoped to offline-file ingest; live-device support (TCP transport, framing, protocol, client) will land here when reverse-engineering happens.
  - `micromate/idf_ascii_report.py` — moved from `sfm/idf_ascii_report.py`.  No behaviour change.
  - `micromate/models.py` — typed `IdfReport`, `IdfEvent`, `IdfPeaks`, `IdfProjectInfo`, `IdfSensorCheck`.  Stores mic in native `mic_pspl_dbl` (dB(L)) instead of the pseudo-psi shoehorn that the BW-shaped model uses.  `IdfEvent.from_report()` constructs from a parsed dict + filename; `IdfEvent.to_minimateplus_event(waveform_key)` bridges to the existing sidecar / DB-insert machinery.
  - `micromate/idf_file.py` — placeholder for the binary codec (`.IDFH` / `.IDFW`).  Stubbed `read_idf_file()` raises `NotImplementedError`; documents the planned reverse-engineering path.
- **`WaveformStore.save_imported_idf`** refactored to use the native `IdfEvent` and bridge at the SQL-insert boundary.  Cleaner separation of "parse a Thor event" (in `micromate/`) from "store it on disk + write a sidecar" (in `sfm/waveform_store.py`).
- **Tests** — `tests/test_idf_ascii_report.py` imports updated to `micromate.idf_ascii_report`.  All 1,014 example-data sidecars round-trip through `IdfEvent.from_report()` without errors.

### Companion releases

- **thor-watcher** unaffected — it talks to the relay over HTTP only.  No version bump needed.
- **terra-view** unaffected today; can use `device_family` in its event-detail rendering when convenient.

---

## v0.18.0 — 2026-05-19

The "Thor / Series IV ingest adapter" release.  Seismo-relay can now accept event files from Instantel Micromate Series IV (Thor) units alongside the existing MiniMate Plus (Series III) Blastware pipeline.

### Added — Thor (Series IV) IDF ingest

- **`POST /db/import/idf_file`** (`sfm/server.py`) — multipart upload endpoint for `.IDFH` (histogram) and `.IDFW` (waveform) event files plus their `.IDFH.txt` / `.IDFW.txt` ASCII sidecars.  Mirrors the shape of `/db/import/blastware_file`: pairing by filename, optional `serial` query hint, per-file outcome reporting.
- **`sfm/idf_ascii_report.py`** — parser for Thor's TXT sidecars (verified against 1,014 real-world samples).  Extracts device-authoritative PPV, ZC Freq, Peak Vector Sum, Mic PSPL, calibration date, firmware version, sensor self-check results, and project/client/operator strings.
- **`WaveformStore.save_imported_idf()`** (`sfm/waveform_store.py`) — stores Thor binaries verbatim in `<root>/<serial>/<filename>`, writes a `.sfm.json` sidecar with `source.kind = "idf-import"` and the full parsed report under `extensions.idf_report`.  Reuses the existing `events` table — Thor events dedupe on (serial, timestamp) and surface in `/db/events` alongside BW events.
- **`tests/test_idf_ascii_report.py`** — parser tests against the `thor-watcher/example-data/` corpus.

### Changed

- `event_to_sidecar_dict()` (`minimateplus/event_file_io.py`) allow-list for `source_kind` now includes `"idf-import"` so the existing sidecar machinery can carry Thor imports.
- Bumped `pyproject.toml` version to `0.18.0`.

### Companion release

This release ships alongside **thor-watcher v0.3.0**, which adds the SFM forwarder that targets the new `/db/import/idf_file` endpoint.  Operators flip the switch in thor-watcher's new "SFM Forward" Settings tab; events POST to seismo-relay just like the series3-watcher BW forwarder does today.
 2026-05-20 11:22:54 -04:00
serversdown ecc935482b seismo-relay v0.19.0 — device-family separation + micromate/ package 
Tighten the Series III / Series IV boundary so UI and storage dispatch
on a clean signal instead of sniffing filenames or applying magnitude
heuristics.

Phase 1 — events.device_family column ("series3" | "series4"):
  self-applying migration with filename-based backfill of existing rows
  (1,132 backfilled on prod 2026-05-20); plumbed through every import
  path (BW endpoint, IDF endpoint, ACH server, BW CLI, sidecar
  backfill); UPSERT preserves via COALESCE; UI dispatches on it.

Phase 2 — extract micromate/ package alongside minimateplus/:
  native IdfEvent / IdfReport / IdfPeaks / IdfProjectInfo /
  IdfSensorCheck (mic in dB(L), not pseudo-psi); moved
  idf_ascii_report.py from sfm/ to micromate/; refactored
  save_imported_idf to use IdfEvent and bridge to minimateplus.Event at
  the SQL-insert boundary; idf_file.py stub for the future binary codec.

Phase 3 prep — docs/idf_protocol_reference.md captures the two
observed Thor binary header signatures (1,012 newer-firmware files vs
2 old files whose layout is byte-for-byte BW-STRT-compatible), file-size
hints suggesting int8 sample encoding, open questions in dependency
order, and a concrete first-session plan for cracking the codec.

Also rolled in the v0.18.1 hotfixes that motivated this work:
  - idf_ascii_report parser now handles "<0.005 in/s" (below-threshold)
    and "N/A" markers without leaving raw strings in numeric DB columns.
  - sfm_webapp.html: defensive _ppvFmt / mic formatter so future
    data-shape drift can't kill the whole events table render.

All 1,014 example-data sidecars round-trip through the new package.
See CHANGELOG.md for full notes.
 2026-05-20 15:19:49 +00:00
serversdown e95ac692ee feat: add device family to separate s3 and s4 events. 2026-05-20 06:15:50 +00:00
serversdown 3265ad6fa3 fix: apply psi dbL conversion rule 2026-05-20 05:43:52 +00:00
serversdown 350f81f8b5 fix: add thor specific ascii parser. 2026-05-20 05:22:28 +00:00
serversdown cd20be2eff feat: add thor/micromate compatibility v0.18.0 2026-05-19 04:32:43 +00:00
serversdown f7c5c9fed3 Merge branch 'main' into codec-re 2026-05-17 23:30:29 +00:00
serversdown 512d82c720 merge: update to 0.17.0' (#21) from ach-report-ingestion into main 
Reviewed-on: #21

## v0.17.0 — 2026-05-17

The "field rescue + DB management" release.  Hardened against units that are stuck in a runaway call-home loop, and added an operator-facing path for purging bogus events that those same units dump into the DB before recovery.  All work in this release was driven by the BE9558H incident (full incident log + recovery procedure at `docs/runbooks/wedged_unit_recovery.md`).

### Added — wedged-unit recovery toolkit

A toolkit for breaking the call-home loop on a misbehaving unit whose firmware is too busy to keep up with normal request/response handshakes.  Tested in production against BE9558H (16 May 2026) — a unit with a stuck-triggered Long-axis geophone that had been call-homing the office BW ACH server every 30 seconds for hours.  Endpoints layered from "single attempt" to "siege mode" to suit different contention levels:

- **`GET /device/events/storage_range`** — SUB 0x06 probe.  POLL + one read; ~2s.  Returns first/last event keys and an `is_empty` flag.  Use to triage whether a unit has stored events without invoking the slow `count_events()` 1E/1F chain (which choked on BE9558H's corrupted event chain).
- **`GET /device/events/index`** — SUB 0x08 probe.  POLL + one read; ~2s.  Returns the lifetime event counter (does NOT decrement on erase — use `storage_range` for "right now" state).
- **`POST /device/events/erase`** — full erase sequence `0xA3 → 0x1C → 0x06 → 0xA2` (confirmed 2026-04-11, see the protocol reference).  Resets event keys to `0x01110000`.  Caller's responsibility to disable ACH first if the underlying trigger condition will re-fill the buffer.
- **`POST /device/rescue`** — one TCP session, short connect+recv timeouts: POLL → disable ACH (compliance config write) → erase events → close.  Designed for race-loop usage when the device is busy in another session.  503 on connect-refused, 502 on protocol failure, 200 on full sequence success.
- **`POST /device/stop_monitoring_blind`** — fire-and-forget Stop Monitoring (SUB 0x97), TCP-only.  Dumps `SESSION_RESET + POLL_PROBE + SESSION_RESET + POLL_DATA + 0x97 × repeat` and closes without reading any S3 response.  The full POLL preamble is required — write commands without it are silently ignored by the device's protocol parser (false-positive surface area that bit the first version of this endpoint).  Use when the device's firmware can't keep up with full request/response but might process inbound bytes at its own pace.
- **`POST /device/stop_monitoring_spam`** — server-side hammer loop, duration-bounded.  Open TCP → write the same blind payload → close → repeat as fast as possible until `duration_s` elapses.  Configurable `connect_timeout` (default 500ms) and `repeat` (frames per session).  Reports `sent_ok`, `connect_failed`, `write_failed`, `rate_attempts_per_s`.  Clamped to 5min duration.
- **`POST /device/stop_monitoring_slow_drip`** — opposite of spam.  Open ONE TCP session, drip the wake handshake + stop frames at `interval_s` (default 3s) for `duration_s` (default 120s, max 10min).  Each drip is ~23 bytes — well under any UART FIFO size.  Opportunistically drains any inbound bytes the device sends back; `bytes_received > 0` in the response strongly suggests the device has started talking and the session is healthy.  **This is the endpoint that saved BE9558H.** Spam mode had been overrunning the device's UART FIFO; slow drip stayed under it.
- **Six rescue scripts** under `scripts/` — thin bash wrappers around the endpoints, default `SFM_BASE_URL=http://localhost:8200` (direct, not via Terra-View proxy whose 60s timeout would cut off the longer endpoints):
    - `rescue_device.sh` — race-loop wrapper for `/device/rescue`
    - `blind_stop.sh` — race-loop wrapper for `/device/stop_monitoring_blind`
    - `spam_stop.sh` — single-call burst hammer
    - `slow_drip.sh` — single-call held-session drip
    - `watch_unit.sh` — passive periodic reachability check (every N min, logs to file), useful for unattended overnight monitoring of a wedged unit
- **`docs/runbooks/wedged_unit_recovery.md`** — symptoms, quick-reference recovery procedure, the modem-layer mechanism (Sierra Wireless serial-port mode-flipping is the real failure mode — not the device firmware), and a table of "why simpler approaches don't work" so the next incident skips the dead ends.

### Added — operator event DB management

Endpoints powering Terra-View's new `/admin/events` page (v0.12.0).  Designed for purging bogus events from a unit that's been forwarding them in bulk (e.g. a stuck-triggered seismograph dumping hundreds of junk events before it's recovered).

- **`DELETE /db/events/{event_id}`** — hard-delete one event row.  Also unlinks the associated blastware binary (`.AB0*`), `.a5.pkl`, `.sfm.json` sidecar, and `.h5` clean-waveform files via the WaveformStore.  Returns the per-file removal status.  404 if the event doesn't exist.
- **`POST /db/events/delete_bulk`** — filter-based or id-list-based bulk delete with safety rails:
    - Filters (`serial`, `from_dt`, `to_dt`, `false_trigger`) combine with AND; same semantics as `GET /db/events`.  `ids` is an additional inclusion list.  Refuses to run with no filters (would wipe the whole table — raises 422).
    - `confirm` must be `true` to actually delete.  Otherwise returns a dry-run summary (`status: "dry_run"`, `matched: N`, `sample_serials: [...]`).
    - `max_rows` (default 10,000) caps how many rows can be deleted by-filter in one call.  If exceeded, returns `status: "too_many"` with a hint to narrow or raise the cap.  Bypassed when only `ids` is supplied.
- **`_cleanup_event_files(row)`** helper in `sfm/server.py` — best-effort `unlink()` of all four sidecar paths derived from the row's `blastware_filename`.  Logged at WARN if a path exists but unlink fails; the DB row deletion still proceeds.
- **`SeismoDb.delete_event(id)` and `SeismoDb.delete_events_bulk(...)`** in `sfm/database.py` — both return the deleted row dict(s) so callers can do file cleanup.  `delete_events_bulk` raises `ValueError` if no filters are supplied.

### Changed

- **Default protocol recv timeout dropped from 30s → 10s** in `_build_client()`.  The unit usually responds in well under a second over cellular; 10s leaves comfortable headroom for retransmits while failing reasonably fast when a unit is wedged.  The two endpoints that perform full 5A waveform downloads still pass `timeout=120.0` explicitly so multi-minute event transfers are unaffected.
- **`_build_client()` now accepts an optional `connect_timeout`** (TCP-only) so rescue / race-loop endpoints can fail fast on busy modems without affecting the protocol-level recv timeout.

### Fixed

- **`GET /device/monitor/status` returned HTTP 500 + uncaught traceback when the device was unresponsive**.  The retry-on-`Exception` inner block let the second `client.poll()`'s `ProtocolError` propagate out of the handler.  Now wrapped in proper try/except — returns 502 with `{"detail": "Protocol error: No S3 frame received within 10.0s ..."}` on timeout, 502 on connection errors, 500 only for genuinely unexpected exceptions.

### Migration

No schema changes.  No data migration required.

If you've been running a previous version against a wedged unit and accumulated bogus events, the new `/admin/events` page in Terra-View v0.12.0 (or direct `POST /db/events/delete_bulk` with `confirm: true`) is the cleanup tool.  Watcher state on the upstream DL2 PC does NOT need separate cleaning — the watcher's `sfm_forwarded.json` keys on file sha256 and won't re-forward the same files.

### Pairing

This release pairs with **Terra-View v0.12.0**, which adds the `/admin/events` UI that consumes the new bulk-delete endpoints, the bulk false-trigger flagging on `/unit/{id}`, and the field-deployment workflow that uses the same `series3-watcher` → SFM ingest path as before.

---

## v0.16.1 — 2026-05-14

### Fixed

- **`record_type` always "Waveform" for forwarded events.**  `read_blastware_file()` hardcoded `ev.record_type = "Waveform"` regardless of the file's actual type.  The watcher-forward pipeline (the main BW ACH ingest path) compounds this by parsing files from a tmp path with a `.bw` suffix, so even a filename-based fallback inside the parser still wouldn't see the original extension.  Now:

  1. New `derive_record_type_from_filename(filename)` helper in `minimateplus/event_file_io.py` derives the type from the LAST character of the filename's extension (V10.72+ AB0T scheme: `H`=Histogram, `W`=Waveform, `M`=Manual, `E`=Event, `C`=Combo).  Falls back to `"Waveform"` for old S338 firmware (3-char extensions ending in `0`) and any unrecognized suffix.
  2. `read_blastware_file()` now calls the helper with its `path.name` so direct callers (the `--dry-run` path in `scripts/import_bw.py`, tests, ad-hoc scripts) get the right value automatically.
  3. `WaveformStore.save_imported_bw()` overrides `ev.record_type` with the **original** filename's derived type after parsing (the tmp file inside the parser doesn't carry the original extension).  This is the path the live watcher-forwarder hits, so the DB column now reflects the actual event type going forward.

  Events ingested before this fix are stuck with `record_type="Waveform"` in the DB; a one-off backfill (`UPDATE events SET record_type = ... WHERE blastware_filename LIKE '%H'`) would fix them retroactively if desired.  Terra-view's event modal also derives client-side from the filename, so the UI already shows the correct type for old events even without the backfill.

---
 2026-05-17 19:13:56 -04:00
serversdown 57287a2ade chore: update to 0.17.0 2026-05-17 23:07:12 +00:00
serversdown 1fff8179d6 Add runbook for recovering wedged units and new scripts for device management 
- Created a comprehensive runbook (`wedged_unit_recovery.md`) detailing the recovery process for units stuck in a call-home loop, including symptoms, recovery steps, and explanations of the failure mode.
- Added `blind_stop.sh` script to send stop-monitoring commands in a tight loop for unresponsive devices.
- Introduced `rescue_device.sh` script to disable Auto Call Home and erase events from a busy device.
- Implemented `slow_drip.sh` script to send stop-monitoring frames at a slow rate to prevent UART overrun.
- Developed `spam_stop.sh` script to rapidly send stop-monitoring commands to a device.
- Created `watch_unit.sh` script for passive monitoring of device reachability, logging results over time.
 2026-05-17 07:58:13 +00:00
serversdown ae7edac83f chore(doc): bump to 0.16.1 2026-05-15 23:35:35 +00:00
serversdown b6911009ff scripts: backfill record_type on legacy events imported with hardcoded "Waveform" 
Pre-v0.16.1 (commit aac1c8e), every event ingested through
read_blastware_file got record_type="Waveform" regardless of actual
type because the field was hardcoded.  New ingests derive correctly
from the AB0T filename scheme (H/W/M/E/C).  Existing rows still hold
the wrong value.

This script walks the events table, derives the correct record_type
from each row's blastware_filename, and bulk-updates rows that differ.
Idempotent + dry-run by default.

Usage:
  python -m scripts.backfill_record_type --db bridges/captures/seismo_relay.db
  python -m scripts.backfill_record_type --db bridges/captures/seismo_relay.db --apply

Terra-view's event-detail modal already derives the record_type
client-side from the filename for display, so operators see the
correct type in the UI even before this backfill runs.  This script
brings the DB column in line with what the UI is already showing —
matters for reporting and any downstream consumer that reads the
column directly.
 2026-05-15 06:38:09 +00:00
serversdownandClaude Opus 4.7 aac1c8e06d fix(import): derive record_type from filename suffix instead of hardcoding "Waveform" 
The BW ACH ingest path was inserting every event with
record_type="Waveform" regardless of the actual type because
read_blastware_file() had `ev.record_type = "Waveform"` hardcoded, and
the live watcher-forward path parses files from a tmp path (suffix
".bw") that doesn't carry the original extension.

V10.72+ MiniMate Plus firmware encodes the event type as the last
character of the AB0T extension scheme (H=Histogram, W=Waveform,
M=Manual, E=Event, C=Combo).  This change:

  1. Adds derive_record_type_from_filename() public helper in
     minimateplus/event_file_io.py
  2. Uses it inside read_blastware_file() so direct callers (the
     --dry-run path of scripts/import_bw.py, tests, ad-hoc scripts)
     get correct types automatically
  3. Overrides ev.record_type in WaveformStore.save_imported_bw()
     using the ORIGINAL filename (source_path.name) — required
     because the parser sees only the tmp file

Old S338 firmware (3-char extensions ending in `0`) and any
unrecognized suffix fall back to "Waveform".

Existing DB rows ingested before this fix are stuck with
record_type="Waveform" — a one-off SQL backfill would fix them
retroactively if desired.  Terra-view's event modal also derives
client-side from the filename, so the UI already shows the correct
type for old events even without the backfill.

Version bumped to 0.16.1 in pyproject.toml, event_file_io.py
TOOL_VERSION, sfm/server.py FastAPI version, and CHANGELOG.md.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
 2026-05-14 21:09:21 +00:00
serversdown 84ee68f889 Merge branch 'main' into codec-re 2026-05-11 22:27:25 -04:00
serversdown 20519383fe add additional events for decode 2026-05-11 18:13:24 -04:00
serversdown 87675ac2d8 Merge pull request 'docker: add .dockerignore and Dockerfile for containerization.' (#20) from dockerize into main 
Reviewed-on: #20
 2026-05-11 17:40:56 -04:00
serversdown 83d69b9220 chore(server): update inline version to 0.16.0 2026-05-11 21:40:18 +00:00
serversdown 3e247e2182 docker: add .dockerignore and Dockerfile for containerization. 2026-05-11 21:38:03 +00:00
serversdown d2e48c62b5 Merge pull request 'feat(import): v0.16.0 - Fully implemented series 3 BW-ACH pipeline stablized.' (#19) from ach-report-ingestion into main 
Reviewed-on: #19
 2026-05-11 15:55:23 -04:00
serversdown 3402b4d11a add additional events for decode-RE 2026-05-11 14:17:21 -04:00
serversdown 988d26c03d docs: capture deferred work in README Roadmap 
Consolidates everything that was floating in chat-only "parking
lot" status into the README's Roadmap (Future) section:

  High-impact (unblocks product features):
    - Waveform body codec reverse-engineering
    - In-app waveform viewer accuracy (depends on codec)
    - Terra-view integration
    - Vibration summary reports

  BW ASCII report parser enhancements:
    - Histogram-specific structural fields
    - Histogram interval bin-table parsing
    - ">100 Hz" value parsing

  Ingestion gaps:
    - MLG forwarding (watcher + SFM endpoint)
    - 0C-record raw bytes persistence in sidecar

  Operational:
    - series3-watcher file archive manager
    - Existing operational items (compliance encoder, modem manager,
      Call Home dial_string write, histogram mode 5A stream)

  Test coverage + lower-priority cleanups.

CLAUDE.md "What's next" section now points to the README as the
canonical deferred-work list, and keeps its own low-level technical
status log for byte-layout details that don't belong in the
roadmap.
 2026-05-11 16:08:02 +00:00
serversdown 197c0630e2 chore(release): v0.16.0 — BW ACH ingestion 
The "BW ACH ingestion" release.  Paired with series3-watcher v1.5.0,
every Blastware ACH event (binary + _ASCII.TXT report) lands in
SeismoDb with device-authoritative peaks, project metadata, sensor
self-check, and ZC/Time-of-Peak data — without depending on the
still-undecoded waveform body codec.

Bumps pyproject.toml + minimateplus/event_file_io.py TOOL_VERSION
to 0.16.0.  README banner + CHANGELOG entry summarise the work
that landed across commits cdfe4ad..f83993a on this branch.
 2026-05-11 07:33:48 +00:00
serversdown f83993ad1d fix(import): pair _ASCII.TXT reports on the SFM server side too 
The series3-watcher v1.5.0 fix taught the WATCHER to look for BW
ACH's _ASCII.TXT report alongside each binary.  But the SFM
SERVER's import endpoint only knew about the legacy <binary>.TXT
naming when building its TXT lookup table.

Effect: even though the watcher correctly shipped both files in
the multipart POST (and logged "+ <name>_ASCII.TXT attached"),
the server's reports dict was keyed on the wrong name, so
report_bytes resolved to None for every event.  Without the
report, save_imported_bw fell back to broken-codec peak values
and no project info — exactly the same symptom as before the
watcher fix landed, just for a different reason.

Fix: when stripping the ".TXT" suffix, also recognise the
"_ASCII" trailer and reconstruct the binary's filename by
converting the last "_" back to ".".  Register the report under
BOTH possible binary names so the subsequent lookup matches
whichever convention the operator's BW installation uses.

  ACH convention (Blastware ACH):
    binary T003L2G6.0E0H  + report T003L2G6_0E0H_ASCII.TXT  ✅
  Manual export (operator clicks Save As Text in BW):
    binary M529LK44.AB0   + report M529LK44.AB0.TXT          ✅
  Both for same event (e.g. ACH + operator manual save):
    register under both names; binary lookup wins             ✅

Smoke-tested against the four real fixture filenames in the
project archive.  Full SFM suite still 62 pass.

For the user's situation: pull, restart, and the NEXT re-forward
pass (after deleting watcher state file again if needed) will
hit this code path, parse the report correctly, apply the
overlay onto the Event, and the upsert path will land
authoritative peak values + project info in the DB.
 2026-05-11 07:25:04 +00:00
serversdown 6b2a44ff02 fix(import): overlay BW report onto Event + upsert DB row on re-import 
Two compounding bugs caused forwarded events to land in the DB with
broken-codec peak values (~10 in/s saturation on every channel) and
no project info, even when the watcher correctly paired a BW ASCII
report with the binary.

Bug 1: save_imported_bw built the sidecar JSON with the report's
authoritative peak / project values via event_to_sidecar_dict(
bw_report=...), but never overlaid those onto the in-memory Event
that flows to db.insert_events().  So the DB row got peak_values
from read_blastware_file()._peaks_from_samples() — which runs the
still-undecoded waveform body codec assuming raw int16 LE and
produces ±32K-shaped noise (= ±10 in/s at Normal range) regardless
of the actual signal.  The sidecar JSON had the truth but the DB
columns (which the webapp queries for fast filter/sort) lied.

Bug 2: insert_events' IntegrityError handler only refreshed the
filename/filesize/a5_pickle/sidecar columns when a duplicate
(serial, timestamp) was seen.  Peak values, project info,
sample_rate, record_type stayed locked in at whatever the FIRST
insert wrote.  So even after Bug 1 was fixed, the historical
events in the DB (already inserted with broken-codec peaks) would
never get their values corrected, because a re-forward would just
hit IntegrityError and skip the field refresh.

Fix 1 (minimateplus/event_file_io.py + sfm/waveform_store.py):
  - New apply_report_to_event(event, report) helper folds the BW
    report's device-authoritative fields onto the Event in-place:
    per-channel PPV, peak vector sum, mic PSPL→psi, project /
    client / operator / sensor_location, sample_rate, record_time.
  - save_imported_bw() calls the helper right after parsing the
    report.  The Event that flows to insert_events() now carries
    correct values.

Fix 2 (sfm/database.py):
  - insert_events()'s IntegrityError UPDATE now refreshes every
    device-authoritative column from the new data: tran_ppv,
    vert_ppv, long_ppv, peak_vector_sum, mic_ppv, project, client,
    operator, sensor_location, sample_rate, record_type, plus
    the existing filename/filesize/a5_pickle/sidecar fields.
  - Preserves: id, waveform_key, session_id, created_at (immutable
    / FK fields), and false_trigger (operator review state).

End-to-end simulation verified:
  - Step 1: import without report → DB has ±10 in/s peaks, no project
  - Step 2: re-import WITH report → upsert path fires, DB now has
            device-authoritative 0.005 in/s peaks + sensor_location
  - Step 3: operator sets false_trigger=1, re-import again → flag
            preserved, peaks remain correct

For the user's situation: deleting the watcher state file forces a
re-forward of all events.  Each re-forward now pairs with its
_ASCII.TXT, applies the report onto the Event, and the upsert
refreshes the DB row.  No DB nuke needed.

Full SFM suite: 62 passed, 44 skipped.
 2026-05-11 05:51:39 +00:00
serversdown cc57a8e618 fix(db): /db/units surfaces events-only serials too 
Previous query_units() only joined on ach_sessions, which is created
exclusively by the live ACH server.  The BW-importer path
(/db/import/blastware_file → WaveformStore.save_imported_bw →
SeismoDb.insert_events) populates `events` but never creates an
ach_sessions row.  Consequence: every serial whose events flowed in
through the series3-watcher forwarder was invisible to
/db/units (and therefore to the SFM webapp's fleet overview / units
list), even though the events were correctly populated in the
events table with proper serial attribution.

Rewrite query_units() to aggregate from BOTH tables and union the
serials:
  - total_events / last_event_at  come from `events` (every ingest path)
  - last_session_at / total_monitor_entries / total_sessions
                                  come from `ach_sessions` (ACH-only),
                                  0 when no sessions exist for the serial
  - last_seen = max(last_event_at, last_session_at)

Verified on the user's actual prod DB after the
repair_unknown_serials run: /db/units now returns 24 serials instead
of 2.  All 3,257 watcher-forwarded events become visible in the
fleet overview without any further DB surgery.
 2026-05-11 05:15:09 +00:00
serversdown 082e5946bc fix(import): resolve real serial from BW filename instead of bucketing to UNKNOWN 
The /db/import/blastware_file endpoint was bucketing every
forwarded event into serial='UNKNOWN' in the DB.  WaveformStore
correctly decoded the serial from the BW filename and saved
files to <store>/<serial>/<filename> (e.g.
.../BE17353/S353L5KC.DR0H.h5), but the endpoint code called
db.insert_events(serial=_serial_from_event(ev)) — and
_serial_from_event was a stub that always returned None,
falling back to "UNKNOWN".

Effect on the user's prod server: 3,039 events forwarded across
24 distinct units, ALL inserted under serial='UNKNOWN'.  The
on-disk waveform store + sidecars + HDF5s were fine, but the
SFM webapp's /db/units only showed the two original manually-
uploaded serials because every forwarded row had its serial
column zeroed to UNKNOWN.

Fix:
  - WaveformStore.save_imported_bw() now surfaces the decoded
    serial on the returned `rec` dict (rec["serial"]).
  - The import endpoint uses rec["serial"] as the authoritative
    fallback when the operator hasn't supplied a serial_hint query
    parameter.  Order of precedence:
      query string `serial` → rec["serial"] → _serial_from_event(ev) → "UNKNOWN"
  - Response payload now includes `serial` per file so the watcher
    log lines (or any future caller) can see which unit each event
    was attributed to.

Recovery for existing DB rows:
  scripts/repair_unknown_serials.py walks the events table looking
  for rows with serial='UNKNOWN' and re-attributes each one to the
  serial decoded from blastware_filename.  Updates the row in place
  unless the target (serial, timestamp) already has a row, in which
  case the UNKNOWN duplicate is deleted.  Idempotent.  Default
  dry-run; pass --apply to commit.

  Verified on the user's actual DB (dry-run):
    UNKNOWN rows scanned:       3039
    Updated to real serial:     2602
    Deleted (duplicate of an
     already-correct row):      437
    Unresolved (bad filename):  0

After running the repair, /db/units will show all 24 units
correctly populated.
 2026-05-11 02:25:08 +00:00
serversdown a032fa5451 refactor(bw-report): parse user notes by POSITION, not by label 
The four operator-supplied note fields in BW's Compliance Setup →
Notes tab (Project / Client / User Name / Seis Loc) have
USER-EDITABLE LABELS — an operator can rename them in BW's UI to
"Building:", "Site Address:", "Inspector:", or anything else, and
the ASCII export writes those literal labels verbatim.  The
previous label-normalisation map approach (just added in commit
6a7e8c6) was fragile: it could only match label spellings we'd
enumerated in advance.  An operator using "Site:" instead of
"Seis Loc:" would have their sensor location silently dropped.

What IS reliable: BW always writes the 4 user-notes lines
contiguously, in the same order, between the "Units :" line and
the "Geo Range :" line of the export.  So parse them by POSITION:

  position 1 → project
  position 2 → client
  position 3 → operator
  position 4 → sensor_location

The original labels BW wrote are preserved in a new
`BwAsciiReport.user_note_labels` dict (canonical slot → literal
label string) so terra-view can render them as the operator named
them.

Removes the `_OPERATOR_LABEL_MAP` / `_normalise_label_for_lookup`
helpers and the elif-by-normalised-label branch in `parse_report`.
Replaces with a small state machine that flips on the "Units" line
and flips off on the "Geo Range" line.

Tests:
  - Default-label fixtures (waveform + histogram) still populate
    correctly, with operator's labels captured.
  - Synthetic custom-labelled exports ("Building:" / "Site Address:" /
    etc.) populate the right slots by position.
  - Histogram-specific "Seis. Location:" works.
  - Lines outside the Units→Geo Range range are ignored even if
    they look like user notes (defensive against malformed exports).
  - Partial blocks (fewer than 4 lines) leave later slots None.
  - Extra lines beyond 4 are dropped (5th slot doesn't exist).

26 tests in test_bw_ascii_report.py (was 33; net drop reflects
parametrised label tests collapsed into 6 focused position tests).
Full SFM suite: 62 passed, 44 skipped.

Pairs with series3-watcher v1.5.0 which fixes the filename pairing
so the report reaches this parser in the first place.
 2026-05-10 22:28:31 +00:00
serversdown 6a7e8c6e86 feat(bw-report): normalise operator-field label variants 
Blastware writes the operator-supplied fields with different label
spellings across firmware versions and recording modes — most
notably "Seis. Location" on histogram exports vs "Seis Loc:" on
waveform exports.  Previous parser only matched the latter, so
every histogram event silently lost its sensor_location field.

Replace the four hardcoded `key.rstrip(":") == "X"` branches with
a single `_OPERATOR_LABEL_MAP` dispatch table keyed by normalised
label (lowercase, trailing colon/period stripped, internal
whitespace collapsed).  Adds these variants on day 1:

  project:         "Project:" / "Project"
  client:          "Client:"  / "Client"
  operator:        "User Name:" / "User Name"
  sensor_location: "Seis Loc:" / "Seis. Location" / "Seis Location"
                 / "Sensor Location" / "Seis Loc"

To absorb future BW label drift, add a one-line dict entry — no
new elif branch.

14 new tests cover:
  - Each label variant routes to the correct field (parametrised)
  - Case-insensitive matching ("seis loc" / "SEIS LOC" / "SeIs LoC")
  - Whitespace-collapse ("Seis  Loc" with double-space)
  - End-to-end parse of a real histogram fixture from
    example-events/histogram/ — sensor_location ('Loc #1 - 2652 Hepner...')
    populates correctly even though the file uses "Seis. Location"

Total bw_ascii_report tests: 19 → 33.  Full SFM suite still green
(69 passed, 44 skipped — pre-existing skips for h5py-dep tests).

Pairs with series3-watcher v1.5.4 (which fixes the filename pairing
so histograms actually reach this parser in the first place).
 2026-05-10 20:13:44 +00:00
serversdown cdfe4ad3c8 feat(import): parse paired BW ASCII reports on /db/import/blastware_file 
Blastware's ACH writes a per-event ASCII report (.TXT) alongside each
event binary, containing the rich derived per-channel fields BW
computes (PPV, ZC Freq, Time of Peak, Peak Acceleration, Peak
Displacement, Peak Vector Sum + time, sensor self-check Pass/Fail,
monitor-log timestamps).  None of this lives in the BW binary itself.

When the watcher daemon forwards both files to /db/import/blastware_file
in one multipart POST, we now:

  - Pair binaries with their .TXT partners by filename match
  - Parse the report into a structured BwAsciiReport
  - Land the rich fields in a new top-level `bw_report` block of the
    sidecar JSON
  - Overlay the report's peaks/project_info/timestamp/sample_rate/
    record_time/total_samples/pretrig_samples onto the canonical
    sidecar fields (the report values are device-authoritative; the
    BW-binary STRT-derived values had bugs like reading the 0x46
    record-type marker as rectime)

This unblocks the monthly-summary review workflow — events become
sortable/filterable by peak, location, project, etc. — without
depending on the still-undecoded waveform body codec.
 2026-05-08 23:56:43 +00:00
serversdown 510cec8395 add example events for decode reverse engineering. 2026-05-08 15:44:54 -04:00
serversdown 7e13c2020f Merge pull request 'doc(fix): retracts raw int16 LE sample set assumptions.' (#18) from sfm-waveform-store into main 
Reviewed-on: #18
 2026-05-08 15:27:26 -04:00
serversdown 8aea46b8a0 doc(fix): retracts raw int16 LE sample set assumptions. 2026-05-08 19:26:25 +00:00
serversdown 0f7630c10d Merge pull request 'doc: update readme to 0.15.0' (#17) from sfm-waveform-store into main 
Reviewed-on: #17
 2026-05-08 15:15:36 -04:00
serversdown 9123269b1f feat(protocol): implement v0.14.0 SUB 5A protocol rewrite with enhanced chunk handling and new helpers 
test: add regression tests for v0.14.x SUB 5A protocol fixes
refactor(logging): change warning logs to debug for less verbosity in write_blastware_file
 2026-05-08 19:11:55 +00:00
serversdown 9400f59167 doc: update readme to 0.15.0 2026-05-08 19:06:26 +00:00
serversdown e1a73b2c44 Merge pull request 'feat: add waveform store handling' (#16) from sfm-waveform-store into main 
Reviewed-on: #16
 2026-05-08 15:03:32 -04:00
serversdown bbed85f7e2 fix: update channel keys to include 'MicL' in device_event_waveform documentation 2026-05-08 18:48:06 +00:00
serversdown c641d5fc10 feat: v0.15.0 
### Added

- **Layered event storage architecture.**  Each event now lands as four
  files in the per-serial waveform store, each with a clear role:

  - `<filename>` — the Blastware-readable binary (BW file).  Untouched.
  - `<filename>.a5.pkl` — the raw 5A frames (regenerative source).
  - `<filename>.h5` — clean per-channel waveform arrays in physical
    units (in/s for geo, psi for mic) plus event metadata (HDF5 with
    gzip compression).  This is the canonical format for downstream
    analysis tools.
  - `<filename>.sfm.json` — the modern review/metadata sidecar (peaks,
    project, source provenance, review state, extensions).

  SQLite (`seismo_relay.db`) is the searchable index over all four.

- **Plot-ready waveform JSON (`sfm.plot.v1`).**  The `/device/event/{idx}/waveform`
  and `/db/events/{id}/waveform.json` endpoints now return samples in
  physical units with explicit time-axis metadata, peak markers, and
  per-channel unit hints — no more guessing the ADC-to-velocity scale
  client-side.  The webapp waveform viewer was rewritten to consume
  this shape.

- **In-app waveform viewer accuracy fix.**  The standalone SFM webapp
  viewer was scaling geophone amplitudes by `geoAdcScale / 32767`
  (≈ 6.206 / 32767), where `geoAdcScale = 6.206053` is the device's
  *in/s per V* hardware constant — not the ADC-counts-to-velocity
  factor.  This silently scaled every plot ~38% too low for Normal-range
  geophones (the correct full-scale is 10.0 in/s, or 1.25 in/s for
  Sensitive).  Conversion is now done server-side using the geo_range
  from compliance config; the client just plots.

- New `sfm/event_hdf5.py` module: `write_event_hdf5()`,
  `read_event_hdf5()`, plus a plot-JSON helper.
- Backfill script extended to also emit `.h5` for existing events.

### Dependencies

- Added `h5py>=3.10` and `numpy>=1.24` for the HDF5 storage layer.
- Added `python-multipart>=0.0.7` (required by FastAPI for the
  `/db/import/blastware_file` endpoint introduced in this release).
 2026-05-08 04:39:51 +00:00
serversdown 9afa3484f4 feat(cache): implement integrity checks for cached events and waveforms 
- Added `waveform_key` and `event_timestamp` columns to `CachedEvent` and `CachedWaveform` for integrity verification.
- Implemented logic to flush the cache when a mismatch in (waveform_key, event_timestamp) is detected during event and waveform updates.
- Enhanced `set_events` and `set_waveform` methods to check for mismatches and trigger cache eviction as necessary.
- Introduced a new `LiveCache` class to manage in-memory caching of live device data, separating it from the server logic for better testability.
- Added tests to verify the correctness of cache invalidation logic, particularly for post-erase key reuse scenarios.
- Updated web application to include a "Force refresh" toggle, allowing users to bypass the cache and re-fetch data from the device.
 2026-05-07 04:42:00 +00:00
serversdown 0484680c89 fix(docs/comments): rename refs to 'event files' to reflect their timestamp extenion names. 2026-05-06 19:08:38 +00:00
serversdown 3711b11bda feat: add waveform store handling 2026-05-06 19:03:38 +00:00
serversdown 429c6ac87a feat(protocol): implement v0.14.0 SUB 5A protocol rewrite with enhanced chunk handling and new helpers 
test: add regression tests for v0.14.x SUB 5A protocol fixes
refactor(logging): change warning logs to debug for less verbosity in write_blastware_file
 2026-05-06 14:18:31 -04:00
serversdown 52c6e7b618 Merge pull request 'v0.14.3 - Full waveform DL pipeline tested and working.' (#15) from protocol-fix into main 
Reviewed-on: #15
 2026-05-05 20:49:47 -04:00
serversdown 29ebc75656 doc: update readme v0.14.3 2026-05-05 20:48:58 -04:00
claude ebfe9877fa doc: update changelog to 0.14.3 2026-05-05 20:39:47 -04:00
claude c914a15e12 docs: update for v0.14.3 - Full continuous waveform download successful! 2026-05-05 20:37:52 -04:00
claude a27693242d fix(protocol): implement partial DLE stuffing for 0x10 bytes in params to prevent request corruption 2026-05-05 18:28:28 -04:00
claude eefec0bd64 fix(blastware_file): remove harmful "duplicate header+STRT" strip logic to preserve valid waveform data 2026-05-05 17:48:40 -04:00
claude 7444738883 debug(protocol): event-N probe is now at counter = start_offset instead of start_offset + 0x46 2026-05-05 16:46:35 -04:00
claude 6b76934a04 Merge branch 'main' into protocol-fix 2026-05-04 14:43:05 -04:00
claude 7b62c790a9 fix(seismo-lab): remove duplicate capture history list 2026-05-04 14:30:46 -04:00
claude b66cc9d075 fix(blastware_file): update TERM detection logic and strip duplicate header blocks for accurate file writing 2026-05-04 14:28:11 -04:00
serversdown 4ab604eff1 Merge pull request 'v0.12.6' (#10) from seismo-lab-new into main 
Reviewed-on: #10
 2026-05-04 13:22:54 -04:00
serversdown e15f1567ef Doc: Update docs for 0.12.6 2026-05-04 17:18:28 +00:00
serversdown bb33ad3837 doc: update to v0.12.5 2026-05-04 17:13:37 +00:00
claude 45e61fbcaf big refactor of waveform protocol. 2026-05-03 01:20:21 -04:00
claude d758825c67 fix(protocol): correct continuous-mode record header classification for accurate timestamp extraction 2026-05-01 20:28:55 -04:00
claude 0fbb39c21a Big event bugfix. see details: 
## v0.13.0 — 2026-05-01

### Fixed

- **SUB 5A bulk waveform stream — over-read bug for events ≥ 2 sec.**
  `read_bulk_waveform_stream` was walking the chunk counter past the actual
  end of the event, picking up post-event circular-buffer garbage that
  corrupted reconstructed Blastware files for any waveform > ~1 sec.  The
  loop now extracts the event's `end_offset` from the STRT record at
  `data[23:27]` of the probe response and stops the chunk walk when the next
  counter would step past it.  Verified against three BW MITM captures
  (4-27-26 + 5-1-26): 2-sec event drops from 37 over-read chunks to 7
  bounded chunks; 3-sec drops to 9; non-zero-start "event 2" drops to 9.

### Added

- `framing.bulk_waveform_term_v2(key4, end_offset, last_chunk_counter)` —
  computes the corrected SUB 5A TERM frame's `(offset_word, params)` per the
  formula confirmed across all 3 BW captures.  Not yet wired into
  `read_bulk_waveform_stream` (the legacy TERM is still used to preserve the
  existing `blastware_file.write_blastware_file` frame-structure expectations);
  available for the next iteration that switches to BW's 0x0200 chunk step.
- `framing.parse_strt_end_offset(a5_data)` — extracts the event-end pointer
  from the STRT record in an A5 response payload.
 2026-05-01 18:37:34 -04:00
claude 1ef55521b1 Fix: Removed duplicates from merge botch. Stable version of seismo_lab.py 2026-05-01 17:34:41 -04:00
claude 738b39f3cb Manually Merged seismo lab persistent connection branch into the new direct download branch, creating a new branch called seismo-lab-new 2026-05-01 15:13:50 -04:00
Claude 625b0a4dfc feat(seismo_lab): add Download tab that captures wire bytes during event download 
Adds a new CapturingTransport wrapper in minimateplus.transport that mirrors
every TX/RX byte to two raw .bin files using the same on-wire format as
bridges/ach_mitm.py, so the resulting captures are byte-for-byte compatible
with the existing Blastware MITM captures and load directly in the Analyzer.

A new "Download" tab in seismo_lab.py lets the user connect to a device over
TCP or serial and run connect / list-keys / download-events while the wrapper
saves raw_bw_<ts>.bin (our TX) and raw_s3_<ts>.bin (device TX) into a
seismo_dl_<ts>[_<label>]/ session directory. On completion, the panel hands
both files to the Analyzer and switches tabs, mirroring the UX of the
existing Bridge capture flow.
 2026-05-01 00:12:02 +00:00
Claude b14f31f3b0 Include capture label in TCP raw filename 
Matches serial bridge naming: raw_bw_{ts}_{label}.bin / raw_s3_{ts}_{label}.bin

https://claude.ai/code/session_014NczSHUz9uTzCAf4cVASTJ
 2026-04-27 20:48:10 +00:00
Claude b9ab368934 Fix TCP capture: write files only when capture is active 
Previously every Blastware connection auto-created files.
Now TCP mode works the same as serial mode:
- Start Bridge: proxy listens and forwards silently, no files written
- New Capture: opens raw_bw/raw_s3 files; pipe threads write to them
- Stop Capture: flushes and closes files, fires Analyzer callback
- No connection = no file; multiple captures per bridge session work correctly

https://claude.ai/code/session_014NczSHUz9uTzCAf4cVASTJ
 2026-04-27 20:26:31 +00:00
Claude 9004241846 Restore multi-capture Bridge design + TCP mode 
Brings back the protocol-exp BridgePanel design:
- Single bridge session stays up; New Capture / Stop Capture create
  labelled raw-file segments on demand (no files created at bridge start)
- Capture history listbox shows all segments; double-click reloads in Analyzer
- On capture complete: Analyzer auto-populates and runs analysis

TCP mode integrated into same tab (Serial/TCP radio toggle):
- Each incoming Blastware connection is automatically a capture segment
- Session appears in history list; Analyzer wires up live on connect
- Stop Capture disconnects current TCP session

https://claude.ai/code/session_014NczSHUz9uTzCAf4cVASTJ
 2026-04-27 20:20:43 +00:00
Claude 6861d9ed97 Merge TCP mode into Bridge tab (Serial/TCP radio toggle) 
Removes the separate 'TCP Capture' tab and folds TCP MITM capture directly
into the existing Bridge tab.  A Serial/TCP radio selector at the top swaps
the connection fields (COM ports vs. listen port + device host:port) while
keeping the same Start Bridge / Stop Bridge / Add Mark buttons, capture
checkboxes, log dir, and live log — identical UX for both modes.

https://claude.ai/code/session_014NczSHUz9uTzCAf4cVASTJ
 2026-04-26 23:01:45 +00:00
claude 5cd5652560 Merge branch 'seismo-lab' of https://github.com/serversdwn/seismo-relay into seismo-lab 2026-04-26 18:16:52 -04:00
Claude 897ac8a3f3 Add TCP MITM capture tab (TcpBridgePanel) 
New 'TCP Capture' tab in seismo_lab.py: listens on a configurable local
port for an incoming Blastware connection, transparently forwards all
traffic to the real seismograph device, and saves both directions to
raw_bw_<ts>.bin / raw_s3_<ts>.bin in the same format the Analyzer already
understands.  Session start wires up Analyzer live mode automatically via
the same on_bridge_started callback as the COM-port bridge.

https://claude.ai/code/session_014NczSHUz9uTzCAf4cVASTJ
 2026-04-26 22:10:48 +00:00
serversdown 310fc5986c Merge pull request 'seismo-lab2' (#7) from seismo-lab2 into seismo-lab 
Reviewed-on: #7
 2026-04-26 16:49:28 -04:00
Claude e1150b30aa fix(analyzer): name A5/5A frames; revert S3 checksum validation 
Add 0x5A (BULK_WAVEFORM_STREAM) and 0xA5 (BULK_WAVEFORM_RESPONSE) to
SUB_TABLE so they display with real names instead of UNKNOWN_5A/A5.

Revert S3 checksum validation to checksum_valid=None (the original
intentional behavior). Large S3 frames (A5 bulk waveform, E5 compliance
config) embed inner DLE+ETX sub-frame delimiters; the trailing 0x03 of
the last inner delimiter can land where the parser expects the SUM8
checksum byte, causing false BAD CHK on every valid A5 frame.
protocol.py _validate_frame documents and ignores exactly this issue.

https://claude.ai/code/session_014NczSHUz9uTzCAf4cVASTJ
 2026-04-26 20:40:45 +00:00
Claude 9bbecea70f fix(parser): correct S3 frame terminator — bare ETX, not DLE+ETX 
parse_s3 had the S3 terminator logic inverted vs the real S3FrameParser
in framing.py. It was terminating on DLE+ETX and treating bare ETX as
payload, which caused every bare 0x03 to be swallowed — bundling multiple
real S3 frames into one giant body until a DLE+ETX sequence happened to
appear. Result: 583-byte POLL_RESPONSE 'frames' containing many real
frames concatenated, all showing BAD CHK.

Fix: mirror S3FrameParser exactly —
  - Bare ETX (0x03) = real frame terminator
  - DLE+ETX (0x10 0x03) = inner-frame literal data (A4/E5 sub-frames),
    appended to body and parsing continues

https://claude.ai/code/session_014NczSHUz9uTzCAf4cVASTJ
 2026-04-26 20:23:18 +00:00
serversdown 4a0c9b6da5 Merge pull request 'merge protocol-exp 0.12.3 to main' (#5) from protocol-exp into main 
Reviewed-on: #5
 2026-04-21 00:22:24 -04:00
201 changed files with 62138 additions and 1412 deletions
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.dockerignore
+28
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@@ -0,0 +1,28 @@
.git
.gitignore
.venv
venv
env
__pycache__
*.pyc
*.pyo
*.pyd
.pytest_cache
.mypy_cache
.ruff_cache
*.db
*.db-wal
*.db-shm
*.sqlite
*.sqlite3
sfm/data
bridges/captures
example-events
captures
logs
.DS_Store
Thumbs.db
.gitignore
+1 -1
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@@ -1,6 +1,6 @@
/bridges/captures/
/example-events/
/tests/fixtures/
/manuals/
# Python build artifacts
CHANGELOG.md
+1561
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CLAUDE.md
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Dockerfile
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@@ -0,0 +1,31 @@
FROM python:3.11-slim
WORKDIR /app
# tzdata is required for the TZ env var to take effect (python:slim
# omits the timezone database). Without it, datetime.now() / logging
# / matplotlib all stay in UTC regardless of TZ. Default zone gets
# set further down via ENV; users override per-deployment via the
# `TZ` env var in docker-compose.
RUN apt-get update && \
apt-get install -y --no-install-recommends curl tzdata && \
rm -rf /var/lib/apt/lists/*
# Default display timezone — applied to server logs, datetime.now(),
# matplotlib rendered timestamps, and any naïve-vs-aware datetime
# conversions in the PDF renderer. Override via TZ env var in
# docker-compose; storage in the DB is always UTC regardless.
ENV TZ=America/New_York
COPY pyproject.toml requirements.txt ./
COPY minimateplus ./minimateplus
COPY micromate ./micromate
COPY sfm ./sfm
COPY bridges ./bridges
COPY scripts ./scripts
RUN pip install --no-cache-dir -e .
EXPOSE 8200
CMD ["python", "-m", "uvicorn", "sfm.server:app", "--host", "0.0.0.0", "--port", "8200"]
README.md
+396 -51
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@@ -1,7 +1,11 @@
# seismo-relay `v0.12.1`
# seismo-relay `v0.31.0`
A ground-up replacement for **Blastware** — Instantel's aging Windows-only
software for managing MiniMate Plus seismographs.
software for managing seismographs. Supports both the **MiniMate Plus
(Series III)** and the **Micromate (Series IV / "Thor")** families:
Series III via the live RS-232 / TCP wire protocol *and* Blastware ACH file
ingest; Series IV currently via Thor TXT-paired IDF file ingest, with the
binary codec on the roadmap.
Built in Python. Runs on Windows, Linux, or macOS. Connects to instruments
over direct RS-232 or cellular modem (Sierra Wireless RV50 / RV55).
@@ -10,6 +14,51 @@ over direct RS-232 or cellular modem (Sierra Wireless RV50 / RV55).
> pipeline working end-to-end over TCP/cellular. ACH Auto Call Home server
> handles inbound unit connections, downloads events, and persists everything
> to a SQLite database. SFM REST API exposes device control and DB queries.
> **As of v0.14.3 (2026-05-05): SUB 5A bulk waveform protocol is verified
> byte-perfect against Blastware captures across 2-sec, 3-sec, and 10-sec
> events.** Generated `.G10` / `.AB0` files open cleanly in Blastware with
> full Event Reports, frequency analysis, and waveform plots.
> **v0.16.0 (2026-05-11)** adds BW ASCII report ingestion to
> `/db/import/blastware_file` — paired with **series3-watcher v1.5.0**,
> every Blastware ACH event lands in SeismoDb with device-authoritative
> peaks, project metadata, sensor self-check, and ZC/Time-of-Peak data,
> without depending on the still-undecoded waveform body codec.
> **v0.18.0 (2026-05-19)** adds Thor / Micromate Series IV ingest at
> `/db/import/idf_file` — paired with **thor-watcher v0.3.0**, every
> `.IDFH` / `.IDFW` event file (plus its `.txt` sidecar) lands in
> SeismoDb the same way BW events do. See
> [`docs/idf_protocol_reference.md`](docs/idf_protocol_reference.md) for
> the IDF format reference and reverse-engineering plan.
> **v0.19.0 (2026-05-20)** separates Series III and Series IV at the
> code level: new `micromate/` package alongside `minimateplus/`, new
> `events.device_family` DB column ("series3" / "series4") so the UI
> and storage layer dispatch deterministically instead of sniffing
> filenames. Self-applying migration backfills existing rows from the
> binary filename extension.
> **v0.20.0 (2026-05-28)** closes out the Event-Report PDF iteration
> started in v0.17.x: histogram layouts render correctly against BW
> reference PDFs, the ASCII parser handles real-world edge cases
> (`OORANGE`, `>100 Hz`, histogram timestamps), and per-channel ZC
> Freq is surfaced in both modals (event browser + main webapp).
> Adds a server-wide `TZ` env var so operator-visible timestamps
> render in local time instead of UTC. New
> `scripts/backfill_sidecars.py --reparse-txt` lets parser fixes be
> applied retroactively to existing events without re-forwarding,
> using the `.TXT` files preserved at ingest time.
> **v0.21.0 (2026-05-29)** is the Thor / Series IV decoder release —
> `micromate/idf_file.read_idf_file()` now decodes both IDFW
> (waveform) and IDFH (histogram) binaries (87–99% sample fidelity
> on quiet IDFW events; all 859 IDFH corpus files decode cleanly).
> A new `micromate/idf_to_bw_report.py` adapter projects parsed
> Thor reports into the BW-shaped sidecar block, so Thor events
> flow through the existing Event Report PDF pipeline without a
> separate renderer. Terra-View v0.13.0 ships in parallel and
> closes Phase 1 of the SFM integration — see its CHANGELOG.
> **v0.22.0 (2026-07-03)** adds the SFM side of the full-snapshot
> bundle: `GET /db/snapshot` (WAL-safe DB copy), `GET /db/waveforms/
> recent.zip` (recent events' waveform files), and a gated
> `POST /db/restore` (`SFM_DB_RESTORE_ENABLED`, dev-only). Terra-View
> v0.17.0 drives them to pull a one-pass prod→dev refresh.
> See [CHANGELOG.md](CHANGELOG.md) for full version history.
---
@@ -18,26 +67,36 @@ over direct RS-232 or cellular modem (Sierra Wireless RV50 / RV55).
```
seismo-relay/
├── seismo_lab.py ← Main GUI (Bridge + Analyzer + Console tabs)
├── seismo_lab.py ← Main GUI (Bridge + Analyzer + Download + Console tabs)
│
├── minimateplus/ ← MiniMate Plus client library
├── minimateplus/ ← Series III (MiniMate Plus) client library
│ ├── transport.py ← SerialTransport, TcpTransport, SocketTransport
│ ├── protocol.py ← DLE frame layer, SUB command dispatch
│ ├── client.py ← High-level client (connect, get_events, push_config, …)
│ ├── client.py ← High-level client (connect, get_events, delete_all_events, push_config, get_call_home_config, …)
│ ├── framing.py ← Frame builders, DLE codec, S3FrameParser
│ └── models.py ← DeviceInfo, Event, ComplianceConfig, MonitorLogEntry, …
│ ├── models.py ← DeviceInfo, Event, ComplianceConfig, MonitorLogEntry, CallHomeConfig, …
│ ├── bw_ascii_report.py ← Parse BW per-event ASCII reports (.TXT sidecars)
│ ├── event_file_io.py ← Read BW binaries, write .sfm.json sidecars
│ └── blastware_file.py ← Write events to Blastware-compatible .AB0 files
│
├── micromate/ ← Series IV (Micromate / Thor) client library (NEW v0.19)
│ ├── models.py ← IdfEvent, IdfReport, IdfPeaks, IdfProjectInfo, IdfSensorCheck (mic in native dB(L))
│ ├── idf_ascii_report.py ← Parse Thor .IDFW.txt / .IDFH.txt event sidecars
│ ├── idf_file.py ← Binary codec for .IDFW + .IDFH (v0.21.0+)
│ └── idf_to_bw_report.py ← Adapter projecting Thor IDF into the BW report shape (v0.21.0+)
│
├── sfm/ ← SFM REST API server (FastAPI, port 8200)
│ ├── server.py ← All device + DB endpoints
│ ├── database.py ← SeismoDb — SQLite persistence layer
│ └── sfm_webapp.html ← Embedded web UI (served at /)
│ ├── server.py ← Live device endpoints + DB query + ingest endpoints + caching
│ ├── database.py ← SeismoDb — SQLite persistence (events, monitor_log, ach_sessions)
│ ├── waveform_store.py ← On-disk store for BW + IDF event binaries + .sfm.json sidecars
│ └── sfm_webapp.html ← Embedded web UI with Call Home config tab
│
├── bridges/
│ ├── ach_server.py ← Inbound ACH call-home server (main production server)
│ ├── ach_mitm.py ← Transparent MITM proxy for capturing BW sessions
│ ├── s3-bridge/ ← RS-232 serial bridge (capture tool)
│ ├── tcp_serial_bridge.py ← Local TCP↔serial bridge (bench testing)
│ ├── gui_bridge.py ← Standalone bridge GUI
│ ├── gui_bridge.py ← Standalone bridge GUI with raw capture checkboxes
│ └── raw_capture.py ← Simple raw capture tool
│
├── parsers/
@@ -46,7 +105,8 @@ seismo-relay/
│ └── frame_db.py ← SQLite frame database
│
└── docs/
└── instantel_protocol_reference.md ← Reverse-engineered protocol spec
├── instantel_protocol_reference.md ← Series III protocol spec (the Rosetta Stone)
└── idf_protocol_reference.md ← Series IV (Thor IDF) format reference + codec RE plan
```
---
@@ -101,21 +161,28 @@ python seismo_lab.py
Each call dials the device, does its work, and closes the connection. TCP
connections are retried once on `ProtocolError` to handle cold-boot timing.
**Caching** — frequently-polled endpoints are cached in-process to avoid
redundant TCP round-trips:
**In-memory caching** — frequently-polled endpoints avoid redundant TCP round-trips
via a thread-safe `_LiveCache` (plain Python dict + `threading.Lock`):
| Method | URL | Cache |
|--------|-----|-------|
| Method | URL | Cache Strategy |
|--------|-----|---|
| `GET` | `/device/info` | Indefinite; invalidated by `POST /device/config` |
| `GET` | `/device/events` | Count-probe fast path (~2s); full download only when new events detected |
| `GET` | `/device/event/{idx}/waveform` | Permanent per event index |
| `GET` | `/device/monitor/status` | 30-second TTL |
| `GET` | `/device/monitor/status` | 30-second TTL; invalidated by monitor start/stop |
| `GET` | `/device/call_home` | Fresh read from device (not cached) |
| `POST` | `/device/connect` | — |
| `POST` | `/device/config` | Writes compliance config; invalidates cache |
| `POST` | `/device/monitor/start` | Sends SUB 0x96 |
| `POST` | `/device/monitor/stop` | Sends SUB 0x97 |
| `POST` | `/device/config` | Writes compliance config; invalidates info + events cache |
| `POST` | `/device/config/project` | Patches project/client/operator/sensor_location strings |
| `POST` | `/device/monitor/start` | Sends SUB 0x96; immediately evicts status cache |
| `POST` | `/device/monitor/stop` | Sends SUB 0x97; immediately evicts status cache |
| `POST` | `/device/call_home` | Reads, patches specified fields, writes back to device |
All cached endpoints accept `?force=true` to bypass the cache.
**Cache bypass** — All cached endpoints accept `?force=true` to skip the cache and
force a fresh read from the device.
**Cache stats** — `GET /cache/stats` returns hit/miss counts and TTL info; `DELETE /cache/device`
clears the device cache immediately.
Transport query params (supply one set):
```
@@ -131,11 +198,35 @@ Query the SQLite database written by `ach_server.py`. All read-only except
| Method | URL | Description |
|--------|-----|-------------|
| `GET` | `/db/units` | All known serials with summary stats |
| `GET` | `/db/events` | Triggered events (filter by serial, date range, false_trigger) |
| `GET` | `/db/events` | Triggered events (filter by serial, date range, false_trigger). Response rows include `device_family` ("series3" / "series4") so clients dispatch on unit type without sniffing filenames. |
| `GET` | `/db/monitor_log` | Monitoring intervals |
| `GET` | `/db/sessions` | ACH call-home session history |
| `PATCH` | `/db/events/{id}/false_trigger?value=true` | Flag / unflag false triggers |
### File ingest endpoints
Used by watcher daemons to push field-collected event files into the SFM DB
+ waveform store. Both accept multipart uploads of binary event files
optionally paired with their ASCII sidecar reports; both dedup by
`(serial, timestamp)` and UPSERT device-authoritative fields on re-import.
| Method | URL | Description |
|--------|-----|-------------|
| `POST` | `/db/import/blastware_file` | Series III: `.AB0*` / `.N00` binaries + paired `_ASCII.TXT`. Source: `series3-watcher`. |
| `POST` | `/db/import/idf_file` | Series IV: `.IDFH` / `.IDFW` binaries + paired `.IDFW.txt` / `.IDFH.txt`. Source: `thor-watcher`. |
### DB snapshot / restore endpoints
Back the "full snapshot bundle" prod→dev refresh Terra-View orchestrates
(Settings → Database). Snapshot/zip are read-only; restore is gated and
dev-only.
| Method | URL | Description |
|--------|-----|-------------|
| `GET` | `/db/snapshot` | WAL-safe point-in-time copy of `seismo_relay.db` via the SQLite online backup API. |
| `GET` | `/db/waveforms/recent.zip?n=…` | Zips the on-disk files (event file + `.h5` / sidecars) for the *n* most-recent events. |
| `POST` | `/db/restore` | Validate-first restore of an uploaded DB + waveforms; takes a WAL-safe pre-restore safety backup, path-traversal-guards the zip. Gated by `SFM_DB_RESTORE_ENABLED` (dormant → 404). |
---
## minimateplus library
@@ -152,21 +243,33 @@ client = MiniMateClient(transport=TcpTransport("1.2.3.4", 12345), timeout=30.0)
with client:
# Read
info = client.connect() # DeviceInfo — serial, firmware, compliance config
count = client.count_events() # Number of stored events
keys = client.list_event_keys() # Fast browse walk — event keys only, no download
events = client.get_events() # Full download: headers + peaks + metadata
monitor = client.get_monitor_status() # Battery, memory, is_monitoring flag
log = client.get_monitor_log_entries() # Monitoring intervals (partial 0x2C records)
info = client.connect() # DeviceInfo — serial, firmware, compliance config
count = client.count_events() # Number of stored events
keys = client.list_event_keys() # Fast browse walk — event keys only, no download
events = client.get_events() # Full download: headers + peaks + metadata
monitor = client.get_monitor_status() # Battery, memory, is_monitoring flag
log = client.get_monitor_log_entries() # Monitoring intervals (partial 0x2C records)
ach_cfg = client.get_call_home_config() # Auto Call Home settings (SUB 0x2C)
# Write
client.apply_config(
sample_rate=1024,
recording_mode="Continuous", # Single Shot / Continuous / Histogram / Histogram+Continuous
histogram_interval_sec=15, # 2, 5, 15, 60, 300, 900
trigger_level_geo=0.5,
geo_range="Normal", # Normal (10.000 in/s) / Sensitive (1.25 in/s)
project="Bridge Inspection 2026",
client_name="City of Portland",
operator="B. Harrison",
)
client.set_call_home_config(
auto_call_home_enabled=True,
after_event_recorded=True,
at_specified_times=True,
time1_hour=18, time1_min=30, # 6:30 PM
time2_hour=6, time2_min=0, # 6:00 AM
)
# Control
client.start_monitoring() # SUB 0x96
@@ -174,26 +277,88 @@ with client:
client.delete_all_events() # Erase all (SUB 0xA3 → 0x1C → 0x06 → 0xA2)
```
`get_events()` runs the full per-event sequence: `1E → 0A → 0C → 5A → 1F`.
SUB 5A bulk stream provides `client`, `operator`, and `sensor_location` as they
existed at record time — not backfilled from the current compliance config.
`get_events()` runs the full per-event sequence:
`1E → 0A → 1E(arm token=0xFE) → 0C → 1F(arm) → POLL×3 → 5A → 1F(browse)`.
SUB 5A bulk stream walks chunks bounded by the `end_offset` extracted from
the STRT record at byte 17 of the probe response — no over-reading, no
chunk-count cap. Project / client / operator / sensor location strings come
from the dedicated metadata pages at counter `0x1002` and `0x1004`,
read once per session (they reflect the compliance setup at session start,
not per individual event).
---
## micromate library
Series IV / Thor support, sibling to `minimateplus`. Currently scoped to
offline-file ingest from Thor's TXT exporter; live-device protocol is
deferred until the binary codec is cracked.
```python
from micromate import IdfEvent, parse_idf_report
# Parse a .IDFW.txt / .IDFH.txt sidecar (1014 example files round-trip cleanly)
text = open("UM11719_20231219162723.IDFW.txt").read()
report_dict = parse_idf_report(text) # permissive dict
# Wrap into a typed event using the device-native binary filename
event = IdfEvent.from_report(report_dict, "UM11719_20231219162723.IDFW")
event.serial # "UM11719"
event.kind # "Waveform" or "Histogram"
event.peaks.transverse_ips # 0.0251 (in/s, native unit)
event.peaks.mic_pspl_dbl # 99.4 (dB(L), Thor's native mic unit — NOT psi)
event.project_info.project # "UPMC Presby-Loc 3-Level1-1R Elevator Rm"
event.sensor_check.tran # True (passed self-check)
event.firmware_version # "Micromate ISEE 11.0AK"
event.calibration_text # "November 22, 2023 by Instantel"
# Bridge to the existing minimateplus.Event shape for the DB / sidecar paths
# (waveform_key is a 16-byte sha256 prefix when ingesting from a binary file)
bridged_event = event.to_minimateplus_event(waveform_key=b"\x00" * 16)
```
The binary codec (`.IDFW` / `.IDFH` event files themselves) is on the
roadmap — see [`docs/idf_protocol_reference.md`](docs/idf_protocol_reference.md)
for everything known so far, the two observed file signatures, and the
reverse-engineering plan. The `micromate/idf_file.py` stub is where
`read_idf_file()` will land.
---
## Database
`ach_server.py` writes to `bridges/captures/seismo_relay.db` (SQLite, WAL mode).
Three tables, all unit-keyed by serial number:
`ach_server.py` and the file-ingest endpoints write to
`bridges/captures/seismo_relay.db` (SQLite, WAL mode) via the `SeismoDb`
persistence layer. Three tables, all unit-keyed by serial number:
| Table | Key | Contents |
|-------|-----|----------|
| `ach_sessions` | UUID | Per-call-home audit record: serial, peer IP, events_downloaded, duration |
| `events` | UUID, UNIQUE(serial, waveform_key) | Triggered events: timestamp, PPV per channel, project/client/operator strings, false_trigger flag |
| `monitor_log` | UUID, UNIQUE(serial, waveform_key) | Monitoring intervals: start/stop time, duration, geo threshold |
| `ach_sessions` | UUID | Per-call-home audit record: serial, timestamp, peer IP, events_downloaded, monitor_entries, duration_seconds |
| `events` | UUID, UNIQUE(serial, timestamp) | Triggered events: timestamp, Tran/Vert/Long/VectorSum/Mic PPV, project/client/operator/sensor_location strings, sample_rate, record_type, false_trigger flag, **`device_family`** ("series3" / "series4"), `blastware_filename` (binary at-rest in `waveforms/`), sidecar references |
| `monitor_log` | UUID, UNIQUE(serial, start_time) | Monitoring intervals: serial, waveform_key, start_time, stop_time, duration_seconds, geo_threshold_ips |
Deduplication is by `(serial, waveform_key)` — repeat call-homes or re-runs
never produce duplicate rows. Post-erase key reuse is handled automatically
via the high-water mark in `ach_state.json`.
**Deduplication is by `(serial, timestamp)`** — the device clock is the
stable natural key. Repeat call-homes or re-runs UPSERT the row in place,
refreshing every device-authoritative field (peaks, project strings,
sample_rate, file references) so the latest writer wins. `false_trigger`
and `device_family` are preserved across UPSERTs. Earlier versions used
`(serial, waveform_key)` for dedup, but the device's event-key counter
resets to `0x01110000` after every erase, so timestamps are the correct
dedup field. Migration handles the transition transparently on first
startup.
**`device_family` (added v0.19.0)** discriminates Series III from Series
IV at the SQL level. Set by every import path; the UI dispatches on it
to render mic units correctly (Series III: psi → dBL conversion; Series
IV: native dBL passthrough). Existing rows are backfilled at first
startup of v0.19.0+ by sniffing the binary filename extension.
The on-disk waveform store lives at `bridges/captures/waveforms/<serial>/`
and holds the original event binaries (BW `.AB0*` / `.N00` for Series III,
`.IDFH` / `.IDFW` for Series IV) plus their `.sfm.json` review/metadata
sidecars. Series III events also produce `.a5.pkl` source-frame pickles
and `.h5` clean-waveform exports; Series IV doesn't yet (pending codec).
---
@@ -231,6 +396,27 @@ Full protocol documentation: [`docs/instantel_protocol_reference.md`](docs/insta
---
## Compliance Config Features
The REST API and web UI expose full control over device compliance settings:
- **Recording Mode** (Single Shot / Continuous / Histogram / Histogram+Continuous)
- **Sample Rate** (1024 / 2048 / 4096 sps)
- **Record Time** (float, seconds)
- **Histogram Interval** (2s, 5s, 15s, 1m, 5m, 15m) — when recording mode includes histogram
- **Geo Trigger Levels** (float, in/s per channel)
- **Geo Maximum Range** (Normal 10.000 in/s / Sensitive 1.250 in/s per channel)
- **Project / Client / Operator / Sensor Location** (ASCII strings)
Auto Call Home config:
- **Auto Call Home Enable** (bool)
- **Dial String** (read-only; 40-byte ASCII)
- **Trigger on Event** (bool)
- **Scheduled Call-Ins** (two time slots with HH:MM each)
- **Retry Settings** (count, delay, connection timeout, warm-up time)
---
## Requirements
```bash
@@ -252,17 +438,176 @@ Use **com0com** or **VSPD** to create the virtual COM pair on Windows.
---
## Roadmap
## Key Features
- [x] Full read pipeline — device info, compliance config, event download with true event-time metadata
- [x] Write commands — push compliance config, trigger thresholds, project strings to device
- [x] Erase all events — confirmed erase sequence from live MITM capture
- [x] Monitor control — start/stop monitoring, read battery/memory/status
- [x] Monitor log entries — decode partial 0x2C records (continuous monitoring intervals)
- [x] ACH inbound server — accept call-home connections, download events, dedup by key
- [x] SQLite persistence — events, monitor log, and session history in `seismo_relay.db`
- [x] SFM REST API — device control + DB query endpoints, live device cache
- [ ] Terra-view integration — seismo-relay router, unit detail page, VISON-style event listing
- [ ] Vibration summary reports — highest legit PPV per project → Word doc (false trigger filtering first)
- [ ] Compliance config encoder — build raw write payloads from a `ComplianceConfig` object
- [ ] Modem manager — push RV50/RV55 configs via Sierra Wireless API
**Series III (MiniMate Plus) device support:**
- [x] Full read/write/erase pipelines over RS-232 or TCP/cellular
- [x] Compliance config (recording mode, sample rate, histogram interval, geo sensitivity, project strings)
- [x] Auto Call Home config (read/write ACH settings, dial string, time slots, retries)
- [x] Monitor control (start/stop, status polling, battery/memory)
- [x] Monitor log entries (continuous monitoring intervals without full waveform download)
- [x] Blastware file ingest at `/db/import/blastware_file` (paired with `series3-watcher`)
**Series IV (Micromate / Thor) device support:**
- [x] Thor IDF file ingest at `/db/import/idf_file` (paired with `thor-watcher`, v0.18.0+)
- [x] Native `IdfEvent` / `IdfReport` typed models — mic in dB(L), full title strings, sensor self-check, calibration, firmware version
- [x] Parser verified against 1,014 paired `.txt` sidecars in `thor-watcher/example-data/`
- [x] Binary `.IDFW` / `.IDFH` codec — ✅ v0.21.0. IDFW reuses `decode_waveform_v2()` on the body at offset `0x0f1f` (87–99% sample fidelity on quiet events); IDFH has a dedicated segment-based decoder (all 859 corpus files decode, 181,071 intervals total). See `micromate/idf_file.py` + `docs/idf_protocol_reference.md`.
- [ ] Live-device protocol — pending codec
**Data persistence:**
- [x] SQLite database (`seismo_relay.db`) with `events`, `monitor_log`, `ach_sessions` tables
- [x] Per-row `device_family` column ("series3" / "series4") for clean UI / unit-of-measurement dispatch (v0.19.0+)
- [x] Deduplication by `(serial, timestamp)` — natural key handles post-erase counter resets
- [x] UPSERT on re-import refreshes every device-authoritative field (peaks, project, sample_rate); preserves operator review state (`false_trigger`)
- [x] Post-erase key-reuse detection (tracks high-water mark in `ach_state.json`)
**REST API:**
- [x] Live device endpoints with in-memory caching (`_LiveCache`)
- [x] Cache statistics (`/cache/stats`) and manual invalidation (`/cache/device`)
- [x] DB query endpoints (units, events, monitor_log, sessions, false_trigger PATCH)
- [x] Call Home config read/write endpoints
- [x] Blastware file download endpoint (`/device/event/{index}/blastware_file`)
- [x] Import endpoints for both device families (`/db/import/blastware_file`, `/db/import/idf_file`)
**File output (v0.7+, byte-perfect as of v0.14.3):**
- [x] Blastware-compatible `.AB0` / `.G10` file generation (waveform + metadata)
- [x] Multi-channel waveform decode from SUB 5A bulk stream
- [x] Second-resolution timestamp encoding in Blastware filename
- [x] **Byte-perfect against BW reference captures** (verified across 2-sec / 3-sec / 10-sec event durations, both event 0 and event N continuation events)
- [x] STRT-bounded chunk walk + correct event-N probe counter + partial DLE stuffing of `0x10` in 5A params (the four fixes that landed in v0.14.0–v0.14.3)
**Capture tools:**
- [x] Serial-to-TCP bridge with raw BW/S3 capture (s3_bridge.py, defaults to auto-capture)
- [x] GUI bridge with raw capture checkboxes (gui_bridge.py)
- [x] ACH inbound server with bidirectional capture (ach_server.py saves raw_tx + raw_rx)
- [x] Transparent TCP MITM proxy for live BW session capture (ach_mitm.py)
**Analysis tools:**
- [x] s3_analyzer.py — session parser, frame differ, Claude export
- [x] gui_analyzer.py — standalone analyzer GUI
- [x] frame_db.py — SQLite frame database for capture analysis
**seismo_lab.py GUI:**
- [x] Bridge tab — Serial/TCP mode selector with raw capture options
- [x] Analyzer tab — BW/S3 capture playback and differencing
- [x] Download tab — Live wire-byte capture during event download
- [x] Console tab — Logging and diagnostics
## Roadmap (Future)
> **Where it stands *today*** — an honest per-capability maturity assessment,
> what to rely on, known issues, and the gap to a real tool:
> [`docs/sfm_tool_status.md`](docs/sfm_tool_status.md). This section covers
> where it is *going*.
### Strategic direction — where this is going
seismo-relay is being built as a **suite of cooperating components**
that together replace and improve on Blastware's role. Three logical
tiers:
1. **SFM** (device-side) — owns the active connection to a physical
unit. Today: `minimateplus/`, `/device/*` HTTP endpoints,
`seismo_lab.py`. Future: live Thor / Micromate support.
2. **SDM** (data-side) — owns the database, waveform store, ingest
pipelines, and the read-API that Terra-View consumes. Today this
code lives under `sfm/` for historical reasons; the role has
migrated and the eventual rename is on the long-tail cleanup list.
3. **Codec library** — pure data-interpretation: `minimateplus/*_codec.py`,
`bw_ascii_report.py`, `micromate/idf_*.py`. Used by both SFM and
SDM, depends on neither.
Terra-View is downstream of SDM for fleet listings, event detail, etc.
The long-term vision adds a **second link** from Terra-View → SFM for
direct device interaction (see below).
The codec work in this repo isn't trying to replace BW's network
layer — BW's ACH file forwarding and Thor's IDF call-home are
battle-tested. The value is in the receiving and processing side: turn
the stream of binary+ASCII pairs into something users can search,
filter, alert on, and report from.
### Terra-View ↔ SFM device control (the long-term vision)
Today Terra-View only reads from SDM (event listings, dashboards,
project reports). When a unit goes missing — operator notices in the
Terra-View dashboard — there's no way to *do* anything from the UI.
The path of least resistance is to RDP into a Windows box and open
Blastware, which defeats the purpose of having Terra-View.
Target experience:
- Operator notices a unit in Terra-View dashboard hasn't called in.
- Clicks unit detail → "Connect to Device" button.
- Terra-View opens an embedded view (modal or side-panel) that talks
to SFM's `/device/*` endpoints over the network.
- Live view: device clock, battery, memory, current monitor status.
- Actions: start/stop monitoring, push compliance config changes, pull
fresh events, run a sensor self-check, change call-home settings.
- Audit log: every connect / action recorded in SDM for the unit
history.
Implementation steps (concrete):
- [ ] **SFM authentication & authorization layer.** Today `/device/*`
endpoints are unauthenticated — anyone on the network can call
them. Need at minimum a token-based auth, ideally with a "who
can connect to which units" mapping. Hard prerequisite for
letting Terra-View users into the control surface.
- [ ] **Terra-View "Connect to Device" entry point** on the unit
detail page. Renders only when unit has connection info on file
and the user has permission.
- [ ] **Embedded live-monitor view** in Terra-View — equivalent to
`seismo_lab.py`'s Bridge tab, but in the browser. Polls SFM's
`/device/monitor/status` on an interval; sends start/stop via
`/device/monitor/{start,stop}`.
- [ ] **Action history** — every connect / push / action call records
a row in `unit_history`, viewable on the unit detail page.
- [ ] **Series IV live-device support in SFM** — currently `/device/*`
only supports MiniMate Plus. Blocks "Connect to Device" for
Thor units until done. Depends on Thor wire-protocol capture
and a `micromate/` parallel of the `minimateplus/` modules.
### High-impact (unblocks product features)
- [ ] **Series III waveform body codec reverse-engineering.** The 5A bulk-stream body is some kind of compressed/encoded format (not raw int16 LE as previously assumed — see §7.6.1 retraction in `docs/instantel_protocol_reference.md`). Structural framing is ~50% decoded on branch `claude/codec-re-cBGNe` (tagged-block walker, segment counters); per-byte sample mapping is still open. Until this lands, the in-app waveform viewer renders garbage and BW-import peak values fall back to `_peaks_from_samples()` saturation noise. Workaround: pair every BW-imported event with its `_ASCII.TXT` so the device-authoritative peaks land in the DB regardless of codec.
- [x] **Series IV (Thor IDF) binary codec reverse-engineering.** ✅ v0.21.0 — `micromate/idf_file.read_idf_file()` decodes both IDFW (waveform body at offset `0x0f1f`, reusing `decode_waveform_v2()`; 87–99% sample fidelity on quiet events) and IDFH (dedicated segment-based decoder: all 859 corpus files decode, 181,071 intervals, peaks within ~1.8% of sidecar values). `WaveformStore.save_imported_idf` now also projects parsed Thor data into a `bw_report` block via `micromate/idf_to_bw_report.py` so Thor events render in the existing Event Report PDF pipeline without a separate renderer.
- [ ] **In-app waveform viewer accuracy.** Depends on Series III codec decode. Plot.v1 JSON pipeline + viewer skeleton already exist; will start showing real waveforms automatically once `_decode_a5_waveform` produces correct samples. Series IV waveforms come online when the IDF codec lands.
- [ ] **Series IV live-device support.** Once the IDF binary is decoded, extend `micromate/` with `transport.py` / `framing.py` / `protocol.py` / `client.py` mirroring the `minimateplus/` package layout — depends on capturing Thor's wire protocol (TCP / RS-232 captures TBD).
- [ ] **Terra-view integration** — seismo-relay router, unit detail page, VISON-style event listing.
- [ ] **Vibration summary reports** — highest legit PPV per project → Word doc (false-trigger filtering first).
### BW ASCII report parser enhancements (built in v0.16.0)
- [x] **PPV field misses on certain TXT formats.** ✅ v0.20.0 — root cause was the `OORANGE` (Out Of Range) saturation marker that BW writes when a channel exceeds its full-scale; `_parse_number()` returned None for the non-numeric value. Parser now substitutes `geo_range_ips` as a lower bound + sets `ppv_saturated` flag. All 5 prod events (T190LD5Q.LK0W, T438L713.RY0W, K557L3YM.OE0W, + 2 others) now parse cleanly.
- [x] **Histogram-specific structural fields.** ✅ v0.20.0 — `Histogram Start/Stop Time+Date`, `Number of Intervals`, `Interval Size`, per-channel `Peak Time` + `Peak Date`, and `Peak Vector Sum Date` all parse now. Land in the sidecar's `bw_report.histogram` block.
- [ ] **Histogram interval bin-table parsing.** Trailing 792-row table (per-interval Peak/Freq per channel + MicL) in histogram TXTs is unparsed. Probably too big for the sidecar JSON; may want a separate `.histogram.h5` companion file.
- [x] **`>100 Hz` value parsing.** ✅ v0.20.0 — parser now mirrors the OORANGE pattern: stores 100.0 on `zc_freq_hz` + sets `zc_freq_above_range` flag. PDF + both modals render `>100 Hz` instead of `—`.
### Ingestion gaps
- [ ] **MLG forwarding.** `series3-watcher` forwards event binaries + their `_ASCII.TXT` reports, but skips `.MLG` per-unit monitor log files entirely. Adding an `POST /db/import/mlg_file` endpoint + watcher scan path would populate `monitor_log` for non-ACH-routed units (coverage queries, "was this unit monitoring on date X" lookups).
- [ ] **0C-record raw bytes persistence in the sidecar.** Currently on branch `claude/codec-re-cBGNe` as commit `a187124`; cherry-pick if useful as a standalone fix. Preserves the 210-byte 0C record under `extensions.raw_records.waveform_record_b64` so future field-offset analysis (Peak Acceleration / Time of Peak / etc. — the fields BW computes client-side from samples) can run offline.
### Operational
- [ ] **`series3-watcher` file archive manager** — 90-day-old events moved to `<watch_folder>_archive/<year>/<month>/` subfolders. Plan drafted in `claude/codec-re-cBGNe`'s plan-mode session; awaiting a 5-minute test on whether Blastware UI walks subfolders before any code lands (determines layout: in-place subfolders vs sibling archive).
- [ ] **Compliance config encoder** — build raw write payloads from a `ComplianceConfig` object.
- [ ] **Modem manager** — push RV50/RV55 configs via Sierra Wireless API.
- [ ] **Call Home dial_string write support** (requires DLE escaping for embedded control characters).
- [ ] **Histogram mode recording support** (5A stream analysis for mode 0x03 — separate from histogram ASCII parsing above).
### Test coverage
- [ ] Verify 30-sec event download — body may exceed `0xFFFF` and force the device into a different `end_key` encoding (none of the 2/3/10-sec test cases hit this boundary).
- [ ] Histogram mode (0x03) write via SFM — confirmed working for Single Shot / Continuous / Histogram+Continuous; Histogram (0x03) needs a live test from a non-Histogram starting state.
### Lower-priority cleanups
- [ ] Compliance write anchor-9 cleanup — when changing recording_mode via SFM, a spurious `0x10` may persist after Histogram→other mode transitions. Doesn't affect device operation but differs from BW's byte-perfect output.
- [ ] Locate "Sensor Check" byte in compliance config (need capture with Disabled vs Before-monitoring).
- [ ] Call Home — map time slots 3/4 offsets; confirm `modem_power_relay_enabled`.
- [ ] RV55 DCD/DTR — newer RV55 firmware doesn't assert DCD by default; units don't resume monitoring after call-home disconnect (`--restart-monitoring` flag deferred).
- [ ] **NULL-timestamp duplicate-row dedup.** A small handful of events (2 known on prod as of 2026-05-22) have `events.timestamp IS NULL` because the codec couldn't extract a timestamp from the binary footer. The `UNIQUE(serial, timestamp)` constraint doesn't fire on `NULL` (SQL semantics: `NULL ≠ NULL`), so every `--force` backfill INSERTs a new row instead of UPSERTing the existing one. Cleanup: a one-shot SQL query that keeps only the newest row per `(serial, blastware_filename)` and deletes the rest. Longer-term: extend the unique key to `(serial, COALESCE(timestamp, blastware_filename))` or reject inserts with NULL timestamp.
- [ ] **Histogram body sub-format with `byte[5] != 0`.** ~3 events on prod (`T190LD5Q.LD0H`, `O121L4L1.GU0H`) use a histogram body my walker doesn't recognize — the first block has `byte[5] = 0x01` or `0x07` instead of `0x00`, and the entire body lacks the `1e 0a 00 00` tail signature. Codec returns 0 valid blocks; their DB PVS comes from the bw_report ASCII overlay (which BW computed from the same binary, so the DB columns are correct). Only the `.h5` waveform plot is empty. Cracking the sub-format would unlock the plot. Needs binary+ASCII pairs from a few `byte[5]!=0` events; same RE approach as the K558 case.
- [ ] **Histogram body sub-format with `byte[5] == 0x00` but undecodable.** Observed 2026-05-28 on BE17353 (S353) events: `S353L4H2.FZ0H`, `S353L4H2.P00H`, `S353L4H3.7O0H`, `S353L4H3.E10H`. Body starts `00 00 00 01 0a 00 XX 00 ...` which LOOKS like a valid histogram block header (marker 0x000a at byte[4:6] ✓, byte[5]=0x00 normal-format ✓), but the walker finds zero data blocks across the whole body. Likely an extra header before the block stream OR a different tail signature than `1e 0a 00 00`. Smaller body lengths (1900-2100 bytes) suggest these may be short-recording histogram variants. Same operational impact as the byte[5]!=0 case: event ingests cleanly, DB peaks correct via bw_report overlay, only the chart is empty. Worth dumping a hex view of one body to diagnose.
- [ ] **Sensor-check waveform extraction from the BW binary.** BW's Event Report PDFs include a narrow panel on the right side of the waveform plot showing each channel's response to the sensor self-check signal (a damped sinusoid for geo, sawtooth-at-test-freq for mic). Our parser captures the test RESULTS (`test_freq_hz`, `test_ratio`, `test_amplitude_mv`, `test_results` pass/fail) and the PDF + modal display them as text — but BW's per-sample sensor-check waveform isn't accessible to us today. Two paths to add it: (a) RE the binary to find where the sensor-check samples are stored — could be a section before STRT, after the footer, or in a separate sub-record; protocol reference doesn't currently mention it. (b) If samples aren't in the binary, synthesize a representative waveform from the test parameters (damped sinusoid at `test_freq_hz` with damping from `test_ratio`). Path (a) is the honest answer; path (b) is decorative. Until either lands, the text-only sensor-check display in the report is fine.
analysis/README.md
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# analysis/ — exploratory scripts for waveform-body RE
**These are scratch.** Run them, read them, copy them, but don't trust
them as documentation. When a finding is verified it gets promoted
to `minimateplus/waveform_codec.py` and `tests/test_waveform_codec.py`;
when it's wrong it stays here as a fossil.
Authoritative status lives in:
- `docs/waveform_codec_re_status.md` (current truth, working note)
- `minimateplus/waveform_codec.py` (verified implementation + docstring)
- `tests/test_waveform_codec.py` (regression locks against fixtures)
---
## Still useful
| File | What it does |
|---|---|
| `load_bundle.py` | Fixture loader. Parses BW binary + ASCII TXT into a `Bundle` dataclass with samples, metadata, body bytes. Used by most other scripts here. |
| `verify_tran.py` | Verifies `decode_tran_initial` against fixture ground truth across all events. Useful when you change the decoder and want a quick sanity check. |
| `inspect_5_11.py` | Inspects the 5-11-26 high-amplitude bundle's body structure, prints metadata, peaks, and block counts. |
| `walk_5_11.py` | Walks blocks for the 5-11-26 bundle and prints offset/tag/length/data. |
| `seg1_blocks.py` | Dumps all blocks in segment 1 of each event. The starting point for cracking multi-segment Tran continuation. |
| `full_tran.py` | Multi-segment Tran decoder attempt (broken — diverges at sample ~512). Useful as a starting scaffold for the next experiment. |
| `multi_segment.py` | Earlier multi-segment attempt with different segment-header consumption strategies. Records what didn't work. |
| `test_rle.py` | Tests `00 NN` interpretation as zero-RLE with different divisor values. Documents how the RLE rule was confirmed. |
## Superseded — keep for archaeology
| File | Superseded by |
|---|---|
| `walk_v2.py` … `walk_v5.py` | `walk_v6.py` and ultimately `minimateplus/waveform_codec.walk_body`. Each version represents one round of refinement. Don't read in isolation — read the diff between them to see what was learned. |
| `walk_chunks.py` | `walk_v6.py` / production walker |
| `decode_v1.py` | First naive decoder attempt. Wrong but readable. |
## Pure exploration — read if curious
| File | What it explored |
|---|---|
| `inspect_body.py` | Byte-frequency stats per event. Established that bytes 0x00 / 0x10 dominate. |
| `find_blocks.py` | Searched for repeating 2-byte tag patterns. |
| `find_signal_runs.py` | Searched for stretches of bytes that "look like a smooth signal" (small inter-byte deltas). Found the `20 NN` literal blocks. |
| `dump_head.py`, `dump_trailer.py`, `dump_around.py` | Hex dumpers at various body positions. |
| `compare_cd.py` | Byte-diff between event-c and event-d (same length, similar signal). Used to identify structural vs data bytes. |
| `brute_force.py` | Tested 96 combinations of channel-permutation × nibble-order × sign-convention × init-from-header on the quiet bundle. All failed because the quiet bundle had T[0]=T[1]=0, making the preamble undetectable. |
| `try_nibbles.py`, `try_layouts.py` | Earlier channel-interleaving hypotheses. All wrong. |
| `test_tran_continue.py` | Test of "Tran continues uninterrupted across `30 04` blocks" hypothesis. Disproven. |
---
## Adding new scripts
If you're picking up the codec work, feel free to add new scripts here.
Suggested conventions:
- Start the filename with what you're testing: `test_<hypothesis>.py`,
`verify_<piece>.py`, `inspect_<region>.py`.
- Print enough output that the reader can see exactly which events
match / diverge and where.
- When a finding is solid, move the verified logic to
`minimateplus/waveform_codec.py` and add a regression test in
`tests/test_waveform_codec.py` — don't leave the truth only in
this directory.
- If a script is fully superseded, leave it in place (don't delete) —
the fossil record is useful when re-evaluating hypotheses later.
analysis/brute_force.py
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"""Brute-force test channel permutations / nibble orders on event-d (simplest signal)."""
import sys
import itertools
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
from minimateplus.waveform_codec import walk_body
def s4(n):
return n if n < 8 else n - 16
def decode(body, channel_perm, nibble_order, sign_mode, init_from_header):
"""Try one decoder configuration on event-d. Returns first 8 cumulative samples per channel."""
blocks = walk_body(body)
# Initial values from bytes [4:7] if init_from_header else 0
if init_from_header:
init = [body[4] if body[4] < 128 else body[4] - 256,
body[5] if body[5] < 128 else body[5] - 256,
body[6] if body[6] < 128 else body[6] - 256,
0]
else:
init = [0, 0, 0, 0]
cur = list(init)
out = [[init[0]], [init[1]], [init[2]], [init[3]]] # sample 0 = init
nibble_idx = 0 # within delta stream; channel = channel_perm[nibble_idx % 4]
# Walk only the 10 NN data blocks
for blk in blocks:
if blk.tag_hi != 0x10:
continue
for byte in blk.data:
if nibble_order == 'high_first':
nib1, nib2 = (byte >> 4) & 0xF, byte & 0xF
else:
nib1, nib2 = byte & 0xF, (byte >> 4) & 0xF
for nib in (nib1, nib2):
if sign_mode == 'signed':
delta = s4(nib)
else:
delta = nib
ch = channel_perm[nibble_idx % 4]
cur[ch] += delta
if (nibble_idx + 1) % 4 == 0:
out[0].append(cur[0])
out[1].append(cur[1])
out[2].append(cur[2])
out[3].append(cur[3])
nibble_idx += 1
if len(out[0]) >= 16:
return out
return out
def best_match(pred, truth, n=10):
"""Sum of squared differences in first n samples."""
n = min(n, len(pred), len(truth))
return sum((pred[i] - truth[i])**2 for i in range(n))
def main():
b = load_bundle("event-d")
# truth in 16-count units
tr = {ch: [round(v * 200) for v in b.samples[ch]] for ch in ("Tran", "Vert", "Long")}
print("Truth event-d first 10 samples:")
for ch in ("Tran", "Vert", "Long"):
print(f" {ch}: {tr[ch][:10]}")
# Test 96 combinations
best = []
for perm in itertools.permutations([0, 1, 2, 3]):
for nibble_order in ('high_first', 'low_first'):
for sign in ('signed', 'unsigned'):
for init_h in (False, True):
decoded = decode(b.body, perm, nibble_order, sign, init_h)
# Score as TVL channel-sum
score = sum(
best_match(decoded[i], tr[ch], n=10)
for i, ch in enumerate(("Tran", "Vert", "Long"))
if i < 3
)
label = f"perm={perm} nib={nibble_order[:1]} sign={sign[:3]} init={init_h}"
best.append((score, label, decoded))
best.sort(key=lambda x: x[0])
print(f"\nTop 10 configurations:")
for s, lbl, dec in best[:10]:
print(f" score={s:>5} {lbl} T={dec[0][:8]} V={dec[1][:8]} L={dec[2][:8]}")
if __name__ == "__main__":
main()
analysis/compare_cd.py
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"""Compare event-c and event-d (same N_samples) to find header vs data bytes."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def main():
bc = load_bundle("event-c")
bd = load_bundle("event-d")
# Compare prefixes
nc, nd = len(bc.body), len(bd.body)
n = min(nc, nd)
diffs = []
for i in range(n):
if bc.body[i] != bd.body[i]:
diffs.append(i)
print(f"event-c body={nc}, event-d body={nd}")
print(f"Total diffs (first {n}): {len(diffs)}")
# Show common prefix
same_prefix = 0
for i in range(n):
if bc.body[i] == bd.body[i]:
same_prefix += 1
else:
break
print(f"Common prefix length: {same_prefix}")
print(f"event-c prefix: {bc.body[:same_prefix].hex(' ')}")
# Look for runs of common bytes
print(f"\nFirst 32 diff positions: {diffs[:32]}")
# Show the "diff fingerprint" of the first 100 bytes
print(f"\n pos c d")
for i in range(0, 100):
marker = " " if bc.body[i] == bd.body[i] else "*"
bd_b = bd.body[i] if i < nd else None
print(f" {i:>3} {bc.body[i]:02x}{marker} {bd_b:02x}" if bd_b is not None else f" {i:>3} {bc.body[i]:02x}{marker}")
if __name__ == "__main__":
main()
analysis/decode_v1.py
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"""
Decoder v1: nibble-pair signed deltas in 10 NN blocks, 4-channel round-robin.
"""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def s4(n):
return n if n < 8 else n - 16
def walk_blocks(body, start):
i = start
blocks = []
while i + 1 < len(body):
t0, t1 = body[i], body[i + 1]
if t0 == 0x10 and t1 % 4 == 0 and 0 < t1 <= 0xFC:
length = t1 // 2 + 2
data = bytes(body[i + 2 : i + length])
blocks.append(("10", t1, data))
i += length
elif t0 == 0x20 and t1 % 4 == 0 and 0 < t1 <= 0xFC:
length = t1 + 2
data = bytes(body[i + 2 : i + length])
blocks.append(("20", t1, data))
i += length
elif t0 == 0x00 and t1 % 4 == 0:
blocks.append(("00", t1, b""))
i += 2
elif t0 == 0x30 and t1 % 4 == 0 and 0 < t1 <= 0x10:
length = t1 * 4
data = bytes(body[i + 2 : i + length])
blocks.append(("30", t1, data))
i += length
elif t0 == 0x40 and t1 == 0x02:
length = 20
data = bytes(body[i + 2 : i + length])
blocks.append(("40", t1, data))
i += length
else:
blocks.append(("??", t0, bytes(body[i:i+8])))
break
return blocks
def decode_v1(body, start, n_samples):
"""Decode by accumulating nibble-pair deltas from all 10 NN blocks."""
blocks = walk_blocks(body, start)
# 4 channels: T, V, L, M
cur = [0, 0, 0, 0]
out = [[], [], [], []]
sample_index = 0 # how many sample-sets emitted
for typ, NN, data in blocks:
if typ == "10":
# 2 nibbles per byte, round-robin TVLM
for byte in data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
ch = sample_index % 4
cur[ch] += s4(nib)
out[ch].append(cur[ch])
sample_index = (sample_index + 1) // 4 * 4 + (sample_index + 1) % 4 # ?
sample_index += 1
# We emit per-nibble, but the structure is unclear
elif typ == "20":
# int8 absolute or delta?
for byte in data:
v = byte if byte < 128 else byte - 256
ch = sample_index % 4
cur[ch] = v # treat as absolute
out[ch].append(cur[ch])
sample_index += 1
return out
def main():
b = load_bundle("event-c")
body = b.body
truth_T = [round(v * 200) for v in b.samples["Tran"]]
truth_V = [round(v * 200) for v in b.samples["Vert"]]
truth_L = [round(v * 200) for v in b.samples["Long"]]
# Find start
for s in range(15):
if body[s] == 0x10 and body[s+1] % 4 == 0 and 0 < body[s+1] <= 0xFC:
start = s
break
blocks = walk_blocks(body, start)
# Print block-by-block what's in each
print(f"Total blocks: {len(blocks)}")
bytes_processed = 0
for typ, NN, data in blocks[:30]:
print(f" type={typ} NN=0x{NN:02x} data_len={len(data)} data_hex={data[:32].hex(' ')}{'...' if len(data) > 32 else ''}")
if __name__ == "__main__":
main()
analysis/dump_around.py
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"""Dump body bytes around a specific offset."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def dump_around(name: str, center: int, radius: int = 96):
b = load_bundle(name)
body = b.body
start = max(0, center - radius)
end = min(len(body), center + radius)
print(f"\n=== {name} body[{start}:{end}] (full body={len(body)}) ===")
for i in range(start, end, 32):
row = body[i:i+32]
marker = " <-- center" if i <= center < i+32 else ""
print(f" +{i:>5} {row.hex(' ')}{marker}")
def main():
# Look at the trailer transitions
trailer_starts = {"event-a": 7047, "event-b": 6475, "event-c": 4043, "event-d": 3941}
for name, off in trailer_starts.items():
dump_around(name, off, 96)
if __name__ == "__main__":
main()
analysis/dump_head.py
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"""Dump the START of each body in 32-byte rows."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def main():
for name in ("event-a", "event-c"):
b = load_bundle(name)
body = b.body
print(f"\n=== {name} body[0:512] (full body={len(body)}, samples={len(b.samples['Tran'])}) ===")
for i in range(0, min(512, len(body)), 32):
row = body[i:i+32]
print(f" +{i:>5} {row.hex(' ')}")
if __name__ == "__main__":
main()
analysis/dump_trailer.py
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"""Dump body bytes split into 32-byte rows starting from `start_offset`."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def dump(body: bytes, name: str, start: int, n_rows: int = 30):
print(f"\n=== {name} body[{start}:] (full body={len(body)}) ===")
end = min(start + 32 * n_rows, len(body))
for i in range(start, end, 32):
row = body[i:i+32]
print(f" +{i:>5} {row.hex(' ')}")
def main():
for name in ("event-a", "event-b", "event-c", "event-d"):
b = load_bundle(name)
# Print the LAST ~600 bytes of the body to see the tail structure
start = max(0, len(b.body) - 32 * 12)
dump(b.body, name, start, 12)
if __name__ == "__main__":
main()
analysis/find_blocks.py
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"""Search for structural repetition in the body bytes."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def find_pattern_offsets(body: bytes, pattern: bytes, max_count=20):
out = []
i = 0
while True:
i = body.find(pattern, i)
if i < 0:
break
out.append(i)
i += 1
if len(out) >= max_count:
break
return out
def main():
for name in ("event-a", "event-b", "event-c", "event-d"):
b = load_bundle(name)
body = b.body
print(f"\n=== {name} (body={len(body)}, N_samples={len(b.samples['Tran'])}) ===")
# Try to find repeating substructures (look for 4-byte 0x10-prefixed markers)
for prefix in [b"\x10\x10", b"\x10\x04", b"\x10\x08", b"\x10\x0c", b"\x10\x18",
b"\x10\x14", b"\x10\x20", b"\x10\x40", b"\x10\x80", b"\x10\x00",
b"\x10\x01", b"\x10\x03", b"\x10\xf0", b"\xf1\x10", b"\x00\x10",
b"\x40\x02", b"\x20\x04", b"\x30\x04", b"\x30\x08", b"\x00\x1a"]:
offs = find_pattern_offsets(body, prefix, max_count=200)
if 1 <= len(offs) <= 1000:
# Print first 10 offsets
first = offs[:6]
last = offs[-3:]
print(f" '{prefix.hex()}' x{len(offs):>4} first={first} last={last}")
if __name__ == "__main__":
main()
analysis/find_signal_runs.py
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"""Find body byte ranges that look like absolute int8 sample data (smooth waveform)."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def looks_like_smooth_int8(buf):
"""Convert bytes to int8 and check if successive deltas are small (waveform-like)."""
if len(buf) < 8:
return 0.0
vals = [b if b < 128 else b - 256 for b in buf]
diffs = [abs(vals[i+1] - vals[i]) for i in range(len(vals)-1)]
avg_diff = sum(diffs) / len(diffs)
return avg_diff
def main():
for name in ("event-a", "event-c"):
b = load_bundle(name)
body = b.body
# Scan with sliding window of 64 bytes; find segments where the bytes look like a smooth wave
win = 64
scores = []
for i in range(len(body) - win):
scores.append((i, looks_like_smooth_int8(body[i:i+win])))
# Lowest avg_diff means smoothest
scores.sort(key=lambda x: x[1])
print(f"\n=== {name} (body={len(body)}) — smoothest 10 windows ===")
for off, s in scores[:10]:
print(f" +{off:>5} avg_diff={s:.2f} bytes={body[off:off+24].hex(' ')}")
if __name__ == "__main__":
main()
analysis/full_tran.py
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"""Full Tran decoder: continues across segment headers using T_delta from header bytes [0:2]."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import walk_body, find_data_start
def s4(n):
return n if n < 8 else n - 16
def i8(b):
return b if b < 128 else b - 256
def decode_full_tran(body):
if len(body) < 7 or body[0:3] != b"\x00\x02\x00":
return None
T0 = int.from_bytes(body[3:5], "big", signed=True)
T1 = int.from_bytes(body[5:7], "big", signed=True)
i = 7
while i + 1 < len(body) and body[i] not in (0x00, 0x10, 0x20, 0x30, 0x40):
i += 1
blocks = walk_body(body, i)
T = [T0, T1]
cur = T1
for blk in blocks:
if blk.tag_hi == 0x40:
# Segment header carries 2 T deltas (int16 BE each) at bytes [0:2] and [2:4]
if len(blk.data) >= 4:
delta1 = int.from_bytes(blk.data[0:2], "big", signed=True)
cur += delta1
T.append(cur)
delta2 = int.from_bytes(blk.data[2:4], "big", signed=True)
cur += delta2
T.append(cur)
elif blk.tag_hi == 0x10:
for byte in blk.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur += s4(nib)
T.append(cur)
elif blk.tag_hi == 0x20:
for byte in blk.data:
cur += i8(byte)
T.append(cur)
elif blk.tag_hi == 0x00:
for _ in range(blk.tag_lo):
T.append(cur)
# 30 NN: skip for now
return T
def main():
for stem in ("M529LL1L.V70", "M529LL1L.JQ0", "M529LL1A.SP0", "M529LL1A.SS0", "M529LL1A.SV0"):
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
body = f.read()[43:-26]
_, samples = _parse_txt(path + ".TXT")
truth_T = [round(v*200) for v in samples["Tran"]]
n_truth = len(truth_T)
decoded = decode_full_tran(body)
n = min(len(decoded), n_truth)
matches = sum(1 for i in range(n) if decoded[i] == truth_T[i])
div_at = -1
for i in range(n):
if decoded[i] != truth_T[i]:
div_at = i
break
print(f"{stem}: decoded={len(decoded)}, truth={n_truth}, matches={matches}/{n}, first div={div_at}")
if __name__ == "__main__":
main()
analysis/inspect_5_11.py
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"""Quick inspection of the new high-amplitude events."""
import os, re, sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import walk_body, find_data_start
ROOT = "tests/fixtures/5-11-26"
def main():
for stem in ("M529LL1A.SP0", "M529LL1A.SS0", "M529LL1A.SV0"):
bin_path = os.path.join(ROOT, stem)
txt_path = bin_path + ".TXT"
with open(bin_path, "rb") as f:
raw = f.read()
body = raw[43:-26]
meta, samples = _parse_txt(txt_path)
n = len(samples["Tran"])
print(f"\n=== {stem} ===")
print(f" file={len(raw)}, body={len(body)}, N_samples={n}")
print(f" rectime={meta.get('Record Time')} pretrig={meta.get('Pre-trigger Length')}")
print(f" PPV(T,V,L)={meta.get('Tran PPV')} / {meta.get('Vert PPV')} / {meta.get('Long PPV')}")
# Show first few non-trivial samples
print(f" First 5 truth samples (in/s):")
for i in range(5):
print(f" T={samples['Tran'][i]:8.3f} V={samples['Vert'][i]:8.3f} "
f"L={samples['Long'][i]:8.3f} M={samples['MicL'][i]:8.3f}")
# Peak sample positions
for ch in ("Tran", "Vert", "Long"):
vals = samples[ch]
peak_i = max(range(n), key=lambda i: abs(vals[i]))
print(f" {ch}: peak {vals[peak_i]:.3f} at sample {peak_i} (t={peak_i/1024:.3f}s)")
# Body structure
start = find_data_start(body)
blocks = walk_body(body, start)
types = {}
for b in blocks:
types[b.tag_hi] = types.get(b.tag_hi, 0) + 1
print(f" body start={start}, total blocks walked: {len(blocks)}")
print(f" block tag counts: {types}")
# How far the walker got
if blocks:
last = blocks[-1]
walked = last.offset + last.length
print(f" walker stopped at offset {walked}/{len(body)} ({100*walked/len(body):.0f}%)")
if __name__ == "__main__":
main()
analysis/inspect_body.py
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"""Print raw body hex + byte-distribution stats for one event."""
from collections import Counter
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def main():
for name in ("event-a", "event-b", "event-c", "event-d"):
b = load_bundle(name)
body = b.body
print(f"\n=== {name} ({len(body)} body bytes) ===")
print(f" STRT: {b.strt.hex()}")
print(f" body[0:64]: {body[:64].hex()}")
print(f" body[64:128]: {body[64:128].hex()}")
print(f" body[-32:]: {body[-32:].hex()}")
cnt = Counter(body)
print(f" top 16 bytes: {[(f'0x{k:02x}', f'{v/len(body):.2%}') for k,v in cnt.most_common(16)]}")
if __name__ == "__main__":
main()
analysis/load_bundle.py
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"""
load_bundle.py — extract body bytes from BW binary + parse sample columns from TXT.
Used by the codec reverse-engineering scripts in this directory.
"""
from __future__ import annotations
import os
import re
from dataclasses import dataclass
BUNDLE_ROOT = os.path.join(
os.path.dirname(__file__), "..", "tests", "fixtures", "decode-re-5-8-26"
)
@dataclass
class Bundle:
name: str
bin_path: str
txt_path: str
bin: bytes
body: bytes # bytes between STRT (43) and footer (last 26)
strt: bytes # 21-byte STRT record
samples: dict # {"Tran": [...], "Vert": [...], "Long": [...], "MicL": [...]}
sample_rate: int
rectime_sec: float
pretrig_sec: float
geo_range_ips: float
ppv: dict # {"Tran": float, "Vert": float, "Long": float}
mic_pspl: float
serial: str
def _parse_txt(path: str) -> dict:
with open(path, "r", encoding="utf-8", errors="replace") as f:
text = f.read()
meta = {}
samples = {"Tran": [], "Vert": [], "Long": [], "MicL": []}
# Find header line that starts the columns ("Tran Vert Long MicL").
# Then every line after is sample data (4 tab-separated floats).
lines = text.splitlines()
header_idx = None
for i, line in enumerate(lines):
if "Tran" in line and "Vert" in line and "Long" in line and "MicL" in line:
# The columns header. Sample lines start a few lines later.
header_idx = i
break
if header_idx is None:
raise ValueError(f"no Tran/Vert/Long/MicL header in {path}")
# Parse meta — quoted lines with "Field : value"
for line in lines[:header_idx]:
m = re.match(r'^"([^"]+)\s*:\s*([^"]*)"', line.strip())
if m:
k, v = m.group(1).strip(), m.group(2).strip()
meta[k] = v
# Parse samples
for line in lines[header_idx + 1 :]:
line = line.strip()
if not line:
continue
parts = re.split(r"\s+", line)
if len(parts) < 4:
continue
try:
t = float(parts[0])
v = float(parts[1])
l = float(parts[2])
m = float(parts[3])
except ValueError:
continue
samples["Tran"].append(t)
samples["Vert"].append(v)
samples["Long"].append(l)
samples["MicL"].append(m)
return meta, samples
def load_bundle(name: str) -> Bundle:
folder = os.path.join(BUNDLE_ROOT, name)
files = os.listdir(folder)
bin_name = next(f for f in files if not f.endswith(".TXT"))
txt_name = next(f for f in files if f.endswith(".TXT"))
bin_path = os.path.join(folder, bin_name)
txt_path = os.path.join(folder, txt_name)
with open(bin_path, "rb") as f:
binary = f.read()
# Header is 22 bytes; STRT at [22:43]; footer at last 26 bytes.
strt = binary[22:43]
body = binary[43:-26]
meta, samples = _parse_txt(txt_path)
sample_rate = int(re.search(r"(\d+)", meta.get("Sample Rate", "1024")).group(1))
rectime_sec = float(re.search(r"([\d.]+)", meta.get("Record Time", "3.0")).group(1))
pretrig_sec = float(re.search(r"-?[\d.]+", meta.get("Pre-trigger Length", "0")).group(0))
geo_range_ips = float(re.search(r"([\d.]+)", meta.get("Geo Range", "10.0")).group(1))
serial = meta.get("Serial Number", "").strip()
def _f(s):
return float(re.search(r"-?[\d.]+", s).group(0))
ppv = {
"Tran": _f(meta.get("Tran PPV", "0")),
"Vert": _f(meta.get("Vert PPV", "0")),
"Long": _f(meta.get("Long PPV", "0")),
}
mic_pspl = _f(meta.get("MicL PSPL", "0"))
return Bundle(
name=name,
bin_path=bin_path,
txt_path=txt_path,
bin=binary,
body=body,
strt=strt,
samples=samples,
sample_rate=sample_rate,
rectime_sec=rectime_sec,
pretrig_sec=pretrig_sec,
geo_range_ips=geo_range_ips,
ppv=ppv,
mic_pspl=mic_pspl,
serial=serial,
)
if __name__ == "__main__":
for name in ("event-a", "event-b", "event-c", "event-d"):
b = load_bundle(name)
n = len(b.samples["Tran"])
print(f"{name}: body={len(b.body):>6} N_samples={n} rate={b.sample_rate} "
f"rectime={b.rectime_sec} pretrig={b.pretrig_sec} range={b.geo_range_ips} "
f"PPV(T,V,L)={b.ppv['Tran']:.3f},{b.ppv['Vert']:.3f},{b.ppv['Long']:.3f} "
f"MicL={b.mic_pspl}")
analysis/multi_segment.py
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"""Decode Tran across multiple segments by resetting at 40 02 headers."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import walk_body, find_data_start
def s4(n):
return n if n < 8 else n - 16
def i8(b):
return b if b < 128 else b - 256
def decode_full_tran(body):
"""Decode all Tran samples in the body, walking through segments."""
if len(body) < 7 or body[0:3] != b"\x00\x02\x00":
return None
T0 = int.from_bytes(body[3:5], "big", signed=True)
T1 = int.from_bytes(body[5:7], "big", signed=True)
# Locate first tag
i = 7
while i + 1 < len(body) and body[i] not in (0x00, 0x10, 0x20, 0x30, 0x40):
i += 1
blocks = walk_body(body, i)
T = [T0, T1]
cur = T1
for bi, blk in enumerate(blocks):
if blk.tag_hi == 0x40:
# Segment header — try interpreting bytes [0:2] as new T anchor
if len(blk.data) >= 2:
new_anchor = int.from_bytes(blk.data[0:2], "big", signed=True)
# The next sample IS this anchor value, NOT a delta from cur.
T.append(new_anchor)
cur = new_anchor
elif blk.tag_hi == 0x10:
for byte in blk.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur += s4(nib)
T.append(cur)
elif blk.tag_hi == 0x20:
for byte in blk.data:
cur += i8(byte)
T.append(cur)
elif blk.tag_hi == 0x00:
# RLE: append NN zero deltas
for _ in range(blk.tag_lo):
T.append(cur)
# 30 NN: skip
return T
def main():
for stem in ("M529LL1L.V70", "M529LL1L.JQ0", "M529LL1A.SP0", "M529LL1A.SS0", "M529LL1A.SV0"):
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
body = f.read()[43:-26]
_, samples = _parse_txt(path + ".TXT")
truth_T = [round(v*200) for v in samples["Tran"]]
n_truth = len(truth_T)
decoded = decode_full_tran(body)
n = min(len(decoded), n_truth)
matches = sum(1 for i in range(n) if decoded[i] == truth_T[i])
# Find first divergence
div_at = -1
for i in range(n):
if decoded[i] != truth_T[i]:
div_at = i
break
print(f"{stem}: decoded={len(decoded)}, truth={n_truth}, matches={matches}/{n}, first div={div_at}")
if div_at >= 0 and div_at < 30:
print(f" truth around div [{max(0,div_at-3)}:{div_at+8}]: {truth_T[max(0,div_at-3):div_at+8]}")
print(f" pred around div [{max(0,div_at-3)}:{div_at+8}]: {decoded[max(0,div_at-3):div_at+8]}")
if __name__ == "__main__":
main()
analysis/seg1_blocks.py
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"""Dump all blocks in segment 1 of each event with their data."""
import sys
sys.path.insert(0, ".")
from minimateplus.waveform_codec import walk_body, find_data_start
def main():
for stem in ("M529LL1A.SP0", "M529LL1L.JQ0", "M529LL1L.V70"):
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
body = f.read()[43:-26]
blocks = walk_body(body, find_data_start(body))
# Find segment 1 (between first and second 40 02)
seg40_indices = [i for i, b in enumerate(blocks) if b.tag_hi == 0x40]
if len(seg40_indices) < 2:
print(f"\n{stem}: only {len(seg40_indices)} segment headers found")
seg1_blocks = blocks[seg40_indices[0]:] if seg40_indices else []
else:
seg1_blocks = blocks[seg40_indices[0]:seg40_indices[1]+1]
print(f"\n=== {stem} segment 1 ({len(seg1_blocks)} blocks) ===")
for b in seg1_blocks[:25]:
tag = f"{b.tag_hi:02x}{b.tag_lo:02x}"
print(f" off={b.offset:>5} {tag} NN=0x{b.tag_lo:02x}({b.tag_lo:>3}) len={b.length:>3} data={b.data[:16].hex(' ')}{'...' if len(b.data)>16 else ''}")
if __name__ == "__main__":
main()
analysis/test_30nn_12bit.py
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"""Test 12-bit signed packed deltas hypothesis for 30 NN blocks across all loud events.
For each 30 NN block in each event, identify what samples it should cover
(based on the cumulative delta count up to that point) and compare the
truth deltas against various 12-bit packing schemes.
"""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import walk_body, find_data_start
CHANNEL_ORDER = ["Vert", "Long", "MicL", "Tran"] # rotation after initial T
def s12(v):
"""Sign-extend a 12-bit unsigned value to signed int."""
return v if v < 0x800 else v - 0x1000
def unpack_12bit_be(data):
"""4 deltas in 6 bytes, BE order: byte[0:1.5], byte[1.5:3], byte[3:4.5], byte[4.5:6]."""
# bits 0..47 (MSB-first), split into 4 × 12-bit
val = int.from_bytes(data, "big")
out = []
for i in range(4):
d = (val >> (12 * (3 - i))) & 0xFFF
out.append(s12(d))
return out
def unpack_12bit_le(data):
"""4 deltas in 6 bytes, LE order: bytes packed as 2 × 24-bit groups."""
out = []
# First 3 bytes contain 2 deltas
b0, b1, b2 = data[0], data[1], data[2]
d0 = b0 | ((b1 & 0x0F) << 8)
d1 = (b1 >> 4) | (b2 << 4)
out.append(s12(d0))
out.append(s12(d1))
# Next 3 bytes contain 2 more deltas
b3, b4, b5 = data[3], data[4], data[5]
d2 = b3 | ((b4 & 0x0F) << 8)
d3 = (b4 >> 4) | (b5 << 4)
out.append(s12(d2))
out.append(s12(d3))
return out
def unpack_12bit_be_per_triplet(data):
"""4 deltas as 2 triplets of (high4, low8) BE within each 3-byte group."""
out = []
b0, b1, b2 = data[0], data[1], data[2]
d0 = (b0 << 4) | (b1 >> 4)
d1 = ((b1 & 0x0F) << 8) | b2
out.append(s12(d0))
out.append(s12(d1))
b3, b4, b5 = data[3], data[4], data[5]
d2 = (b3 << 4) | (b4 >> 4)
d3 = ((b4 & 0x0F) << 8) | b5
out.append(s12(d2))
out.append(s12(d3))
return out
def truth_deltas_for_block(blocks, block_idx, event_truth, channel):
"""For a 30 NN block at block_idx, determine which samples it covers and
return the truth deltas for those samples.
Walks through all blocks before block_idx (within the same segment) and
counts how many deltas have been emitted for *channel*, starting from the
segment's anchor pair.
"""
# Find the segment header that contains this block.
seg_header_idx = None
for j in range(block_idx, -1, -1):
if blocks[j].tag_hi == 0x40:
seg_header_idx = j
break
if seg_header_idx is None:
# block is in the initial T segment; samples count from sample 2.
first_sample_in_segment = 2
else:
# Anchor pair covers samples [N, N+1] for some N. Subsequent deltas
# are samples [N+2, N+2+1, ...]. We don't actually need to know N
# for this test — just the relative position within the segment.
first_sample_in_segment = 2 # anchor=0,1; deltas start at 2
# Count deltas from segment-data start to block_idx.
delta_count = 0
start_block = seg_header_idx + 1 if seg_header_idx is not None else 0
for j in range(start_block, block_idx):
blk = blocks[j]
if blk.tag_hi == 0x10:
delta_count += blk.tag_lo # NN nibbles = NN deltas
elif blk.tag_hi == 0x20:
delta_count += blk.tag_lo # NN int8 deltas
elif blk.tag_hi == 0x00:
delta_count += blk.tag_lo # RLE zero deltas
# Now the 30 NN block carries NN deltas.
nn = blocks[block_idx].tag_lo
# First sample affected: segment first_sample + delta_count.
# But we ALSO need to know which segment this is, since the segment maps
# to a specific channel and a specific starting absolute sample index.
return first_sample_in_segment + delta_count, nn
def main():
for stem in ("M529LL1A.SP0", "M529LL1L.JQ0", "M529LL1L.V70",
"M529LL1A.SS0", "M529LL1A.SV0"):
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
body = f.read()[43:-26]
_, samples = _parse_txt(path + ".TXT")
blocks = walk_body(body, find_data_start(body))
seg_idx = [i for i, b in enumerate(blocks) if b.tag_hi == 0x40]
# Find all 30 NN blocks in DATA section (not trailer).
thirty_blocks = []
for bi, b in enumerate(blocks):
if b.tag_hi != 0x30:
continue
# Determine which segment this is in
seg_num = None
for k, hi in enumerate(seg_idx):
next_hi = seg_idx[k + 1] if k + 1 < len(seg_idx) else len(blocks)
if hi < bi < next_hi:
seg_num = k
break
if seg_num is None and seg_idx and bi < seg_idx[0]:
seg_num = -1 # initial T segment
thirty_blocks.append((bi, b, seg_num))
if not thirty_blocks:
continue
print(f"\n=== {stem} ===")
for bi, b, seg_num in thirty_blocks:
# Channel for this segment
if seg_num == -1:
channel = "Tran"
seg_label = "initial T"
else:
channel = CHANNEL_ORDER[seg_num % 4]
seg_label = f"seg {seg_num}"
# Count deltas before this block within the same segment.
seg_header_idx = seg_idx[seg_num] if seg_num >= 0 else -1
start_block = seg_header_idx + 1 if seg_header_idx >= 0 else 0
delta_count = 0
for j in range(start_block, bi):
blk = blocks[j]
if blk.tag_hi in (0x10, 0x20, 0x00):
delta_count += blk.tag_lo
# First sample this 30 NN block affects (within the segment)
# = anchor positions + delta_count + 2 (since anchor pair was samples 0,1)
# But the segment's first absolute sample index in the channel is
# (seg_num // 4) * 512 (approximately) if segment 0 is the first V seg.
cycle = (seg_num // 4) if seg_num >= 0 else 0
base = cycle * 512 + 2 # +2 for anchor pair
sample_idx = base + delta_count
truth_ch = [round(v * 200) for v in samples[channel]]
nn = b.tag_lo
if sample_idx + nn >= len(truth_ch):
print(f" block @ {b.offset} ({seg_label} {channel}): out of truth range")
continue
# Get the previous sample so we can compute truth deltas
if sample_idx == 0:
prev = 0
else:
prev = truth_ch[sample_idx - 1]
truth_deltas = []
for k in range(nn):
truth_deltas.append(truth_ch[sample_idx + k] - (prev if k == 0 else truth_ch[sample_idx + k - 1]))
# Try each packing
schemes = [
("12-bit BE contiguous", unpack_12bit_be(b.data)),
("12-bit LE per-triplet", unpack_12bit_le(b.data)),
("12-bit BE per-triplet", unpack_12bit_be_per_triplet(b.data)),
]
print(f" block @ {b.offset:>5} ({seg_label} {channel}, samples {sample_idx}..{sample_idx+nn-1}):")
print(f" data: {b.data.hex(' ')}")
print(f" truth: {truth_deltas}")
for name, pred in schemes:
match = "✓" if pred == truth_deltas else " "
n_match = sum(1 for x, y in zip(pred, truth_deltas) if x == y)
print(f" {match}{n_match}/4 {name}: {pred}")
if __name__ == "__main__":
main()
analysis/test_30nn_hybrid.py
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"""Test the '30 NN data = high-nibbles + int8 low-bytes' hypothesis.
Layout for `30 04` (6 data bytes, 4 deltas):
bytes [0:2] = 16 bits = 4 × 4-bit high-nibbles (MSB first)
bytes [2:6] = 4 × int8 low bytes
Each delta = 12-bit signed = sign-extend((high_nibble << 8) | low_byte)
"""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import walk_body, find_data_start
def s4(n):
return n if n < 8 else n - 16
def i8(b):
return b if b < 128 else b - 256
def sign_extend_12(v):
return v if v < 0x800 else v - 0x1000
def decode_30nn(data):
"""4 × 12-bit signed deltas (high nibble + low byte).
bytes[0:2] hold the 4 high nibbles (MSB first); bytes[2:6] hold the low bytes.
"""
if len(data) < 6:
return []
# Read high nibbles from bytes 0-1 (4 nibbles MSB-first)
high_word = (data[0] << 8) | data[1]
high_nibbles = [
(high_word >> 12) & 0xF,
(high_word >> 8) & 0xF,
(high_word >> 4) & 0xF,
high_word & 0xF,
]
out = []
for i in range(4):
v = (high_nibbles[i] << 8) | data[2 + i]
out.append(sign_extend_12(v))
return out
def simulate_up_to(blocks, target_block_idx, t_preamble):
"""Run decoder up to block_idx; return per-channel sample lists.
NOW with 30 NN decoded too."""
out = {"Tran": [], "Vert": [], "Long": [], "MicL": []}
out["Tran"].extend(t_preamble)
cur = {"Tran": t_preamble[-1], "Vert": None, "Long": None, "MicL": None}
rotation = ["Vert", "Long", "MicL", "Tran"]
current_channel = "Tran"
seg_counter = -1
for j in range(target_block_idx):
blk = blocks[j]
if blk.tag_hi == 0x40:
seg_counter += 1
prev = "Tran" if seg_counter == 0 else rotation[(seg_counter - 1) % 4]
new_ch = rotation[seg_counter % 4]
if cur[prev] is not None:
d0 = int.from_bytes(blk.data[0:2], "big", signed=True)
d1 = int.from_bytes(blk.data[2:4], "big", signed=True)
cur[prev] += d0; out[prev].append(cur[prev])
cur[prev] += d1; out[prev].append(cur[prev])
c0 = int.from_bytes(blk.data[14:16], "big", signed=True)
c1 = int.from_bytes(blk.data[16:18], "big", signed=True)
out[new_ch].extend([c0, c1])
cur[new_ch] = c1
current_channel = new_ch
elif blk.tag_hi == 0x10:
for byte in blk.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur[current_channel] += s4(nib)
out[current_channel].append(cur[current_channel])
elif blk.tag_hi == 0x20:
for byte in blk.data:
cur[current_channel] += i8(byte)
out[current_channel].append(cur[current_channel])
elif blk.tag_hi == 0x00:
for _ in range(blk.tag_lo):
out[current_channel].append(cur[current_channel])
elif blk.tag_hi == 0x30:
# NEW: decode 30 NN
deltas = decode_30nn(blk.data)
for d in deltas:
cur[current_channel] += d
out[current_channel].append(cur[current_channel])
return out, current_channel
def main():
for stem in ("M529LL1A.SP0", "M529LL1L.JQ0", "M529LL1L.V70",
"M529LL1A.SS0", "M529LL1A.SV0"):
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
body = f.read()[43:-26]
_, samples = _parse_txt(path + ".TXT")
blocks = walk_body(body, find_data_start(body))
t0 = int.from_bytes(body[3:5], "big", signed=True)
t1 = int.from_bytes(body[5:7], "big", signed=True)
thirty_blocks = [(j, b) for j, b in enumerate(blocks) if b.tag_hi == 0x30]
if not thirty_blocks:
continue
print(f"\n=== {stem} ===")
for j, blk in thirty_blocks:
pred, ch = simulate_up_to(blocks, j, [t0, t1])
cur_before = pred[ch][-1]
truth = [round(v * 200) for v in samples[ch]]
n_pred = len(pred[ch])
nn = blk.tag_lo
if n_pred + nn > len(truth):
continue
# Decode this 30 NN block with hypothesis
pred_deltas = decode_30nn(blk.data)
# Compute truth deltas relative to cur_before
truth_deltas = []
prev = cur_before
for k in range(nn):
truth_deltas.append(truth[n_pred + k] - prev)
prev = truth[n_pred + k]
n_match = sum(1 for a, b in zip(pred_deltas, truth_deltas) if a == b)
tag = "✓" if pred_deltas == truth_deltas else " "
print(f" block @ {blk.offset:>5} (chan={ch}, NN={nn}):")
print(f" data: {blk.data.hex(' ')}")
print(f" truth: {truth_deltas}")
print(f" pred: {pred_deltas} {tag}{n_match}/{nn}")
if __name__ == "__main__":
main()
analysis/test_30nn_v2.py
+141
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"""Test 30 NN packing by running the real decoder up to each 30 NN block,
recording how many samples have been produced for each channel at that point,
then checking truth deltas immediately after."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import walk_body, find_data_start
def s4(n):
return n if n < 8 else n - 16
def i8(b):
return b if b < 128 else b - 256
def s12(v):
return v if v < 0x800 else v - 0x1000
def unpack_12bit_be_contiguous(data):
out = []
val = int.from_bytes(data, "big")
n = len(data) * 8 // 12
for i in range(n):
d = (val >> (12 * (n - 1 - i))) & 0xFFF
out.append(s12(d))
return out
def unpack_12bit_per_triplet_be(data):
out = []
for i in range(0, len(data), 3):
if i + 2 >= len(data):
break
b0, b1, b2 = data[i], data[i + 1], data[i + 2]
d0 = (b0 << 4) | (b1 >> 4)
d1 = ((b1 & 0x0F) << 8) | b2
out.append(s12(d0))
out.append(s12(d1))
return out
def simulate_up_to(blocks, target_block_idx, t_preamble):
"""Run the decoder up to block_idx; return per-channel sample lists."""
out = {"Tran": [], "Vert": [], "Long": [], "MicL": []}
out["Tran"].extend(t_preamble)
cur = {"Tran": t_preamble[-1], "Vert": None, "Long": None, "MicL": None}
rotation = ["Vert", "Long", "MicL", "Tran"]
seg_idx = [j for j, b in enumerate(blocks) if b.tag_hi == 0x40]
# Determine which channel we're CURRENTLY decoding into
current_channel = "Tran"
seg_counter = -1 # incremented at each 40 02
for j in range(target_block_idx):
blk = blocks[j]
if blk.tag_hi == 0x40:
# Switch: extend prev channel, set up new channel
seg_counter += 1
prev = "Tran" if seg_counter == 0 else rotation[(seg_counter - 1) % 4]
new_ch = rotation[seg_counter % 4]
if cur[prev] is not None:
d0 = int.from_bytes(blk.data[0:2], "big", signed=True)
d1 = int.from_bytes(blk.data[2:4], "big", signed=True)
cur[prev] += d0; out[prev].append(cur[prev])
cur[prev] += d1; out[prev].append(cur[prev])
c0 = int.from_bytes(blk.data[14:16], "big", signed=True)
c1 = int.from_bytes(blk.data[16:18], "big", signed=True)
out[new_ch].extend([c0, c1])
cur[new_ch] = c1
current_channel = new_ch
elif blk.tag_hi == 0x10:
for byte in blk.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur[current_channel] += s4(nib)
out[current_channel].append(cur[current_channel])
elif blk.tag_hi == 0x20:
for byte in blk.data:
cur[current_channel] += i8(byte)
out[current_channel].append(cur[current_channel])
elif blk.tag_hi == 0x00:
for _ in range(blk.tag_lo):
out[current_channel].append(cur[current_channel])
elif blk.tag_hi == 0x30:
# Skip for now — we want to know what comes next
pass
return out, current_channel
def main():
for stem in ("M529LL1A.SP0", "M529LL1L.JQ0", "M529LL1L.V70",
"M529LL1A.SS0", "M529LL1A.SV0"):
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
body = f.read()[43:-26]
_, samples = _parse_txt(path + ".TXT")
blocks = walk_body(body, find_data_start(body))
t0 = int.from_bytes(body[3:5], "big", signed=True)
t1 = int.from_bytes(body[5:7], "big", signed=True)
# Find all 30 NN blocks in data section
thirty_blocks = [(j, b) for j, b in enumerate(blocks) if b.tag_hi == 0x30]
if not thirty_blocks:
continue
print(f"\n=== {stem} ===")
for j, blk in thirty_blocks:
pred, ch = simulate_up_to(blocks, j, [t0, t1])
n_pred = len(pred[ch])
# The 30 NN block carries NN deltas for channel `ch` starting at sample n_pred
truth = [round(v * 200) for v in samples[ch]]
if n_pred >= len(truth):
continue
# Truth deltas: truth[n_pred] - cur, truth[n_pred+1] - truth[n_pred], ...
cur_val = pred[ch][-1]
nn = blk.tag_lo
truth_deltas = []
prev = cur_val
for k in range(min(nn, len(truth) - n_pred)):
truth_deltas.append(truth[n_pred + k] - prev)
prev = truth[n_pred + k]
print(f" block @ {blk.offset:>5} (chan={ch}, after sample {n_pred-1}, "
f"NN={nn}, last_val={cur_val}):")
print(f" data: {blk.data.hex(' ')}")
print(f" truth: {truth_deltas}")
schemes = [
("12-bit BE contiguous", unpack_12bit_be_contiguous(blk.data)),
("12-bit per-triplet BE", unpack_12bit_per_triplet_be(blk.data)),
]
for name, pred_deltas in schemes:
n_match = sum(1 for a, b in zip(pred_deltas, truth_deltas) if a == b)
tag = "✓" if pred_deltas == truth_deltas else " "
print(f" {tag}{n_match}/{nn} {name}: {pred_deltas[:nn]}")
if __name__ == "__main__":
main()
analysis/test_rle.py
+86
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"""Test: 00 NN markers might be RLE for zero-deltas in current channel."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import walk_body, find_data_start
def s4(n):
return n if n < 8 else n - 16
def i8(b):
return b if b < 128 else b - 256
def decode_with_rle(body):
"""Decode Tran assuming:
- preamble[3:5], [5:7] = T[0], T[1]
- All 10 NN / 20 NN blocks until segment_header (40 02) are Tran deltas
- 00 NN markers are RLE: NN/4 zero T deltas (or NN, or NN/2 — try them)
"""
if len(body) < 9 or body[0:3] != b"\x00\x02\x00":
return None, None, None
T0 = int.from_bytes(body[3:5], "big", signed=True)
T1 = int.from_bytes(body[5:7], "big", signed=True)
# Find first tag (might be 00 NN, 10 NN, or 20 NN)
i = 7
while i + 1 < len(body):
if body[i] in (0x00, 0x10, 0x20):
break
i += 1
start = i
blocks = walk_body(body, start)
results = {}
for rle_div in (4, 2, 1): # try different RLE interpretations
T = [T0, T1]
cur = T1
for blk in blocks:
if blk.tag_hi == 0x40:
break
if blk.tag_hi == 0x10:
for byte in blk.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur += s4(nib)
T.append(cur)
elif blk.tag_hi == 0x20:
for byte in blk.data:
cur += i8(byte)
T.append(cur)
elif blk.tag_hi == 0x00:
# RLE of zero deltas
n_zeros = blk.tag_lo // rle_div
for _ in range(n_zeros):
T.append(cur)
# 30 NN: skip for now
results[rle_div] = T
return results, T0, T1
def main():
for stem in ("M529LL1L.V70", "M529LL1L.JQ0", "M529LL1A.SP0", "M529LL1A.SS0", "M529LL1A.SV0"):
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
body = f.read()[43:-26]
_, samples = _parse_txt(path + ".TXT")
truth_T = [round(v*200) for v in samples["Tran"]]
results, T0, T1 = decode_with_rle(body)
print(f"\n=== {stem} (T[0]={T0}, T[1]={T1}) ===")
for rle_div, T in results.items():
n = min(len(T), len(truth_T))
matches = sum(1 for i in range(n) if T[i] == truth_T[i])
# Find first divergence
div_at = -1
for i in range(n):
if T[i] != truth_T[i]:
div_at = i
break
print(f" rle_div={rle_div}: decoded {len(T)}, matches {matches}/{n}, first div at sample {div_at}")
if __name__ == "__main__":
main()
analysis/test_tran_continue.py
+71
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"""Test: does the second '20 NN' block in SS0 continue Tran samples?"""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import walk_body, find_data_start
def s4(n):
return n if n < 8 else n - 16
def i8(b):
return b if b < 128 else b - 256
def main():
stem = "M529LL1A.SS0"
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
body = f.read()[43:-26]
_, samples = _parse_txt(path + ".TXT")
truth_T_16 = [round(v * 200) for v in samples["Tran"]]
# Preamble
T0 = int.from_bytes(body[3:5], "big", signed=True)
T1 = int.from_bytes(body[5:7], "big", signed=True)
# Walk blocks
start = find_data_start(body)
blocks = walk_body(body, start)
print(f"=== {stem} === T[0]={T0} T[1]={T1}")
# Hypothesis: Tran continues through ALL 10 NN and 20 NN blocks
# in order, until the next 40 02 segment header (which resets).
T = [T0, T1]
cur = T1
decoded_count = 2 # T[0], T[1] from preamble
for bi, blk in enumerate(blocks):
if blk.tag_hi == 0x10:
for byte in blk.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur += s4(nib)
T.append(cur)
decoded_count += 1
elif blk.tag_hi == 0x20:
for byte in blk.data:
cur += i8(byte)
T.append(cur)
decoded_count += 1
elif blk.tag_hi == 0x40:
# Segment header — stop here for this test
break
# 00 and 30 NN don't contribute to Tran (in this hypothesis)
# Compare to truth
print(f" Decoded {len(T)} T samples up to first 40 02")
matches = sum(1 for i in range(min(len(T), len(truth_T_16))) if T[i] == truth_T_16[i])
print(f" Matches in first {min(len(T), len(truth_T_16))}: {matches}")
# Print first divergence
for i in range(min(len(T), len(truth_T_16))):
if T[i] != truth_T_16[i]:
print(f" First divergence: sample {i}: pred={T[i]}, truth={truth_T_16[i]}")
# Show context
print(f" pred [{i-3}:{i+5}]: {T[max(0,i-3):i+5]}")
print(f" truth [{i-3}:{i+5}]: {truth_T_16[max(0,i-3):i+5]}")
break
if __name__ == "__main__":
main()
analysis/try_layouts.py
+67
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"""Try various nibble-level channel interleavings to find which one matches truth."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def s4(n):
return n if n < 8 else n - 16
def run_decoder(body, layout, skip, n_channels=4):
"""layout: function nibble_index -> channel_index. Returns list-of-lists per channel."""
out = [[] for _ in range(n_channels)]
cur = [0] * n_channels
nibbles = []
for byte in body[skip:]:
nibbles.append((byte >> 4) & 0xF)
nibbles.append(byte & 0xF)
for i, n in enumerate(nibbles):
ch = layout(i)
cur[ch] += s4(n)
out[ch].append(cur[ch])
return out
def cmp(pred, truth, n=24):
n = min(n, len(pred), len(truth))
return [(pred[i], truth[i]) for i in range(n)]
def main():
b = load_bundle("event-c")
truth_T = [round(v * 200) for v in b.samples["Tran"]]
truth_V = [round(v * 200) for v in b.samples["Vert"]]
truth_L = [round(v * 200) for v in b.samples["Long"]]
print(f"T truth[0:10]: {truth_T[:10]}")
print(f"V truth[0:10]: {truth_V[:10]}")
print(f"L truth[0:10]: {truth_L[:10]}")
# Try several nibble->channel layouts (4 channels)
layouts = {
"interleaved TVLM (0,1,2,3,0,1,2,3,...)": lambda i: i % 4,
"interleaved VLMT": lambda i: (i + 3) % 4,
"interleaved LMTV": lambda i: (i + 2) % 4,
"interleaved MTVL": lambda i: (i + 1) % 4,
"byte-based TV LM TV LM (high T low V byte0; high L low M byte1)": lambda i: i % 4,
# "chunks of 8 nibbles per channel": each channel gets 8 nibbles in a row
"chunks-8 TVLM": lambda i: (i // 8) % 4,
"chunks-16 TVLM": lambda i: (i // 16) % 4,
# planar (full channel sequential)
"planar T(0..N) V(N..2N) L(2N..3N) M(3N..4N)": None, # special
}
for label, layout_fn in layouts.items():
if layout_fn is None:
continue
for skip in (0, 4, 7, 8, 9, 11, 14):
out = run_decoder(b.body, layout_fn, skip)
# Check first 8 cumulative on each channel
print(f" skip={skip:2} {label}")
print(f" T_cum[0:10]: {out[0][:10]}")
print(f" V_cum[0:10]: {out[1][:10]}")
print(f" L_cum[0:10]: {out[2][:10]}")
if __name__ == "__main__":
main()
analysis/try_nibbles.py
+73
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"""Try decoding body as 4-bit signed nibble deltas, 4-channel round-robin."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
CHANNELS = ("Tran", "Vert", "Long", "MicL")
def s4(n):
"""Sign-extend a 4-bit unsigned to int (0..7 → 0..7, 8..F → -8..-1)."""
return n if n < 8 else n - 16
def decode_nibbles(body: bytes, skip_bytes: int = 7, n_channels: int = 4):
"""Read body as 2 nibbles per byte; accumulate as deltas for n_channels round-robin."""
out = [[] for _ in range(n_channels)]
cur = [0] * n_channels
ch = 0
nibbles = []
for byte in body[skip_bytes:]:
nibbles.append((byte >> 4) & 0xF)
nibbles.append(byte & 0xF)
for n in nibbles:
cur[ch] += s4(n)
out[ch].append(cur[ch])
ch = (ch + 1) % n_channels
return out
def cmp_to_truth(pred, truth, scale=16):
"""Compare predicted ints (in 16-count units) to truth (in 16-count units = txt * 200).
Return (max_abs_err, mean_abs_err, n_compared).
"""
n = min(len(pred), len(truth))
errs = []
for i in range(n):
p = pred[i]
t = truth[i]
errs.append(abs(p - t))
if not errs:
return None
return (max(errs), sum(errs) / len(errs), n)
def main():
for name in ("event-a", "event-c"):
b = load_bundle(name)
# Convert TXT samples (in/s) to 16-count units (multiply by 200, since 0.005 in/s = 1)
# WAIT: 0.005 in/s = 16 ADC counts. 1 count = 0.000305 in/s.
# So in 1-count units: count = txt * (1/0.0003052) ≈ txt * 3276.7
# But TXT only has 0.005 resolution so equivalent to 16-count units = txt * 200.
truth_in_16 = {ch: [round(v * 200) for v in b.samples[ch]] for ch in CHANNELS[:3]}
# MicL is in dB, skip for now
# Try decoder with skip_bytes = 7
decoded = decode_nibbles(b.body, skip_bytes=7, n_channels=4)
print(f"\n=== {name} ===")
print(f" body={len(b.body)}, nibbles={2*(len(b.body)-7)}, samples_per_ch={len(decoded[0])}")
print(f" truth samples per ch: {len(truth_in_16['Tran'])}")
# Print first 24 of each
for i, chan in enumerate(CHANNELS):
pred_first = decoded[i][:24]
if chan in truth_in_16:
truth_first = truth_in_16[chan][:24]
print(f" {chan} pred: {pred_first}")
print(f" {chan} truth: {truth_first}")
else:
print(f" {chan} pred: {pred_first} (truth in dB, skipped)")
if __name__ == "__main__":
main()
analysis/verify_full_decode.py
+32
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"""Verify decode_waveform_v2 against BW ASCII truth for all fixtures."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import decode_waveform_v2
def main():
for stem in ("M529LL1A.SP0", "M529LL1A.SS0", "M529LL1A.SV0",
"M529LL1L.JQ0", "M529LL1L.V70"):
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
body = f.read()[43:-26]
_, samples = _parse_txt(path + ".TXT")
decoded = decode_waveform_v2(body)
if decoded is None:
print(f"{stem}: decoder returned None")
continue
print(f"\n=== {stem} ===")
for ch in ("Tran", "Vert", "Long"):
truth = [round(v * 200) for v in samples[ch]]
pred = decoded[ch]
n = min(len(pred), len(truth))
matches = sum(1 for i in range(n) if pred[i] == truth[i])
div = next((i for i in range(n) if pred[i] != truth[i]), -1)
print(f" {ch}: decoded={len(pred):>5} truth={len(truth):>5} "
f"matches={matches:>5}/{n:<5} first div={div}")
if __name__ == "__main__":
main()
analysis/verify_quiet_bundle.py
+55
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@@ -0,0 +1,55 @@
"""Run decode_waveform_v2 against the 5-8-26 quiet bundle to test the
'quiet events should decode fully' hypothesis."""
import os, sys
sys.path.insert(0, ".")
from minimateplus.waveform_codec import decode_waveform_v2, walk_body, find_data_start
from analysis.load_bundle import _parse_txt
def main():
base = "tests/fixtures/decode-re-5-8-26"
for evt in sorted(os.listdir(base)):
folder = os.path.join(base, evt)
if not os.path.isdir(folder):
continue
# Find the binary (not .TXT)
bin_name = next(
(f for f in os.listdir(folder) if not f.endswith(".TXT")),
None,
)
if not bin_name:
continue
bin_path = os.path.join(folder, bin_name)
txt_path = bin_path + ".TXT"
if not os.path.exists(txt_path):
# Sometimes the TXT name differs slightly
for f in os.listdir(folder):
if f.endswith(".TXT"):
txt_path = os.path.join(folder, f)
break
with open(bin_path, "rb") as f:
body = f.read()[43:-26]
decoded = decode_waveform_v2(body)
_, samples = _parse_txt(txt_path)
# Count 30 NN blocks
blocks = walk_body(body, find_data_start(body))
n_30 = sum(1 for b in blocks if b.tag_hi == 0x30)
n_40 = sum(1 for b in blocks if b.tag_hi == 0x40)
print(f"\n=== {evt} === body={len(body)} segments={n_40} '30 NN' blocks={n_30}")
if decoded is None:
print(" decoder returned None")
continue
for ch in ("Tran", "Vert", "Long"):
truth = [round(v * 200) for v in samples[ch]]
pred = decoded[ch]
n = min(len(pred), len(truth))
matches = sum(1 for i in range(n) if pred[i] == truth[i])
div = next((i for i in range(n) if pred[i] != truth[i]), -1)
print(f" {ch}: decoded={len(pred):>5} truth={len(truth):>5} "
f"matches={matches:>5}/{n:<5} first div={div}")
if __name__ == "__main__":
main()
analysis/verify_tran.py
+71
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"""Verify: preamble[3:7] = Tran[0], Tran[1] as int16 BE in 16-count units.
And first 20/10 NN block = Tran deltas starting at sample 2.
"""
import os, sys
sys.path.insert(0, ".")
from analysis.load_bundle import _parse_txt
from minimateplus.waveform_codec import walk_body, find_data_start
def s4(n):
return n if n < 8 else n - 16
def i8(b):
return b if b < 128 else b - 256
def main():
for stem in ("M529LL1A.SP0", "M529LL1A.SS0", "M529LL1A.SV0"):
path = f"tests/fixtures/5-11-26/{stem}"
with open(path, "rb") as f:
raw = f.read()
body = raw[43:-26]
_, samples = _parse_txt(path + ".TXT")
truth_T_16 = [round(v * 200) for v in samples["Tran"]]
# Preamble parse
T0_pre = int.from_bytes(body[3:5], "big", signed=True)
T1_pre = int.from_bytes(body[5:7], "big", signed=True)
print(f"\n=== {stem} ===")
print(f" Preamble T[0]={T0_pre} (truth {truth_T_16[0]}) T[1]={T1_pre} (truth {truth_T_16[1]}) match={T0_pre==truth_T_16[0] and T1_pre==truth_T_16[1]}")
# First block
start = find_data_start(body)
blocks = walk_body(body, start)
if not blocks:
print(f" no blocks found")
continue
# Assume first block = Tran deltas from sample 2
first = blocks[0]
T = [T0_pre, T1_pre]
cur_T = T1_pre
if first.tag_hi == 0x10:
# Nibble pairs
for byte in first.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur_T += s4(nib)
T.append(cur_T)
elif first.tag_hi == 0x20:
# int8 per byte
for byte in first.data:
cur_T += i8(byte)
T.append(cur_T)
# Compare against truth
n_check = min(len(T), len(truth_T_16))
match_count = sum(1 for i in range(n_check) if T[i] == truth_T_16[i])
print(f" First block type=0x{first.tag_hi:02x} NN=0x{first.tag_lo:02x} len={len(first.data)} → {len(T)} T samples decoded")
print(f" Tran predicted[0:10]: {T[:10]}")
print(f" Tran truth [0:10]: {truth_T_16[:10]}")
print(f" Matches in first {n_check}: {match_count} / {n_check}")
# Show where it diverges
for i in range(n_check):
if T[i] != truth_T_16[i]:
print(f" First divergence: sample {i}: pred={T[i]}, truth={truth_T_16[i]}")
break
if __name__ == "__main__":
main()
analysis/walk_5_11.py
+20
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"""Walk blocks of the new 5-11-26 events and look at what comes after Tran block."""
import sys
sys.path.insert(0, ".")
from minimateplus.waveform_codec import walk_body, find_data_start
def main():
for stem in ("M529LL1A.SP0", "M529LL1A.SS0", "M529LL1A.SV0"):
with open(f"tests/fixtures/5-11-26/{stem}", "rb") as f:
raw = f.read()
body = raw[43:-26]
start = find_data_start(body)
blocks = walk_body(body, start)
print(f"\n=== {stem} === body={len(body)} start={start} blocks walked={len(blocks)}")
for i, b in enumerate(blocks[:20]):
print(f" block[{i:>2}] @ {b.offset:>5} tag={b.tag_hi:02x} NN=0x{b.tag_lo:02x}({b.tag_lo}) len={b.length} data[:24]={b.data[:24].hex(' ')}")
if __name__ == "__main__":
main()
analysis/walk_chunks.py
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"""Walk the body assuming chunks delimited by 0x10 NN tags. Print each chunk's structure."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def walk(body: bytes, start_offset: int = 7, max_chunks: int = 30):
"""Find all positions where byte = 0x10 followed by a multiple-of-4 byte. Print chunks."""
chunks = []
i = start_offset
while i < len(body) - 1:
# Find next `10 NN` where NN is multiple of 4 (and not preceded by another 0x10 immediately, which would be data).
if body[i] == 0x10 and (body[i+1] % 4 == 0):
chunks.append(i)
i += 1
return chunks
def main():
for name in ("event-c", "event-d"):
b = load_bundle(name)
body = b.body
positions = []
i = 7 # skip 7-byte preamble
while i < len(body) - 1:
if body[i] == 0x10 and body[i+1] % 4 == 0 and body[i+1] > 0:
positions.append(i)
i += 2 # skip past tag
else:
i += 1
print(f"\n=== {name} === body={len(body)}, total `10 NN` (NN%4==0, NN>0) tags: {len(positions)}")
# Print first 20 chunks: show position, NN, gap to next tag
for k in range(min(30, len(positions))):
pos = positions[k]
NN = body[pos + 1]
next_pos = positions[k+1] if k+1 < len(positions) else len(body)
gap = next_pos - pos
data_bytes = body[pos+2 : next_pos]
print(f" chunk[{k:>3}] @ {pos:>5} NN=0x{NN:02x} ({NN:>3}, NN/2={NN//2}) gap={gap:>3} "
f"data={data_bytes[:24].hex(' ')}{'...' if len(data_bytes) > 24 else ''}")
if __name__ == "__main__":
main()
analysis/walk_v2.py
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"""Deterministic chunk walker: each chunk = [10 NN][NN/2 bytes data][2 bytes trailer]."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def walk_chunks(body: bytes, start: int = 7):
"""Yield (offset, NN, data_bytes, trailer_bytes) tuples."""
i = start
while i + 1 < len(body):
if body[i] != 0x10:
break
NN = body[i + 1]
if NN == 0 or NN > 0x80 or NN % 4 != 0:
break
chunk_len = NN // 2 + 4
if i + chunk_len > len(body):
break
data = bytes(body[i + 2 : i + 2 + NN // 2])
trailer = bytes(body[i + 2 + NN // 2 : i + chunk_len])
yield (i, NN, data, trailer)
i += chunk_len
def main():
for name in ("event-c", "event-d", "event-a", "event-b"):
b = load_bundle(name)
body = b.body
chunks = list(walk_chunks(body))
print(f"\n=== {name} === body={len(body)} N_samples={len(b.samples['Tran'])}")
print(f" chunks parsed: {len(chunks)}")
if chunks:
last = chunks[-1]
end_of_walk = last[0] + last[1] // 2 + 4
print(f" walk ended at offset {end_of_walk} (= {len(body) - end_of_walk} bytes from end)")
# Stats
total_data_bytes = sum(len(c[2]) for c in chunks)
print(f" total data bytes: {total_data_bytes}, total nibbles: {2*total_data_bytes}")
if name in ("event-c", "event-d"):
ratio = (2 * total_data_bytes) / (len(b.samples['Tran']) * 4)
print(f" nibbles per (sample × channel): {ratio:.3f}")
# Sum of trailer second-byte
trailer_sums = [c[3][-1] if c[3] else None for c in chunks]
print(f" first 10 chunks: {[(c[0], c[1], c[3].hex()) for c in chunks[:10]]}")
# Print last 10 chunks (likely transition to trailer)
print(f" last 10 chunks: {[(c[0], c[1], c[3].hex()) for c in chunks[-10:]]}")
if __name__ == "__main__":
main()
analysis/walk_v3.py
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"""Walk chunks; auto-detect preamble length by finding first 10 NN."""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def walk_chunks(body, start, max_NN=0x80):
chunks = []
i = start
while i + 1 < len(body):
if body[i] != 0x10:
break
NN = body[i + 1]
if NN == 0 or NN > max_NN or NN % 4 != 0:
break
chunk_len = NN // 2 + 4
if i + chunk_len > len(body):
break
data = bytes(body[i + 2 : i + 2 + NN // 2])
trailer = bytes(body[i + 2 + NN // 2 : i + chunk_len])
chunks.append((i, NN, data, trailer))
i += chunk_len
return chunks, i
def find_first_chunk_start(body):
"""Locate first byte that begins a `10 NN` chunk (NN ∈ multiples of 4, 4..0x7C)."""
for i in range(20):
if body[i] == 0x10 and body[i + 1] % 4 == 0 and 0 < body[i + 1] <= 0x7C:
return i
return -1
def main():
for name in ("event-c", "event-d", "event-a", "event-b"):
b = load_bundle(name)
body = b.body
start = find_first_chunk_start(body)
chunks, end = walk_chunks(body, start)
print(f"\n=== {name} === body={len(body)} N_samples={len(b.samples['Tran'])} start={start}")
print(f" chunks parsed: {len(chunks)}, walk ended at {end}")
if chunks:
print(f" first 5 chunks: {[(c[0], c[1], c[3].hex()) for c in chunks[:5]]}")
print(f" last 5 chunks: {[(c[0], c[1], c[3].hex()) for c in chunks[-5:]]}")
print(f" bytes around end of walk: {body[end-4:end+12].hex(' ')}")
else:
print(f" bytes at start: {body[start:start+16].hex(' ')}")
if __name__ == "__main__":
main()
analysis/walk_v4.py
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"""
Walker v4: alternate [10 NN] data chunks and [00 NN] (or other) marker tags.
Hypothesis:
- [10 NN]: data block, length NN/2 + 2 bytes (2-byte tag + NN/2 bytes data)
- [00 NN]: 2-byte marker block (no data)
- [20/30/40 NN]: special blocks with type-dependent length
"""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
def walk(body, start):
i = start
blocks = []
while i + 1 < len(body):
t0 = body[i]
t1 = body[i + 1]
if t0 == 0x10 and t1 % 4 == 0 and 0 < t1 <= 0x80:
# data chunk: length NN/2 + 2
length = t1 // 2 + 2
blocks.append((i, "10", t1, bytes(body[i + 2 : i + length]), length))
i += length
elif t0 == 0x00 and t1 % 4 == 0:
# 2-byte marker
blocks.append((i, "00", t1, b"", 2))
i += 2
elif t0 == 0x20 and t1 % 4 == 0:
# type 2 — try length 2+t1/2 (similar to 10) OR fixed
length = t1 // 2 + 2
blocks.append((i, "20", t1, bytes(body[i + 2 : i + length]), length))
i += length
elif t0 == 0x30 and t1 % 4 == 0:
length = t1 // 2 + 2
blocks.append((i, "30", t1, bytes(body[i + 2 : i + length]), length))
i += length
elif t0 == 0x40 and t1 == 0x02:
# Special "footer transition" block — try fixed 22 bytes
length = 22
blocks.append((i, "40", t1, bytes(body[i + 2 : i + length]), length))
i += length
else:
# Unknown tag — stop
blocks.append((i, "??", t0, bytes(body[i:i+8]), 0))
break
return blocks, i
def main():
for name in ("event-c", "event-d", "event-a", "event-b"):
b = load_bundle(name)
body = b.body
# Auto-detect start
for s in range(15):
if body[s] == 0x10 and body[s+1] % 4 == 0 and 0 < body[s+1] <= 0x80:
start = s
break
else:
start = 7
blocks, end = walk(body, start)
# Categorize
from collections import Counter
types = Counter(b[1] for b in blocks)
print(f"\n=== {name} === body={len(body)} N={len(b.samples['Tran'])} start={start}")
print(f" total blocks: {len(blocks)}, walk ended at {end}/{len(body)}")
print(f" type counts: {dict(types)}")
# Print last 5 blocks
print(f" last 5 blocks: {[(bb[0], bb[1], bb[2]) for bb in blocks[-5:]]}")
if end < len(body):
print(f" bytes at end: {body[end:end+24].hex(' ')}")
if __name__ == "__main__":
main()
analysis/walk_v5.py
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"""
Walker v5: flexible NN range and multiple block-type lengths.
Hypothesis:
- [10 NN]: 4-bit-delta data block, length = NN/2 + 2
- [20 NN]: 8-bit-literal data block, length = NN + 2
- [00 NN]: 2-byte marker (no payload)
- [30 NN]: trailer/summary block, length = NN*4
- [40 NN]: footer-marker block, fixed 22 bytes
"""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
from collections import Counter
def walk(body, start, max_blocks=10000):
i = start
blocks = []
while i + 1 < len(body) and len(blocks) < max_blocks:
t0 = body[i]
t1 = body[i + 1]
if t0 == 0x10 and t1 % 4 == 0 and 0 < t1 <= 0xFC:
length = t1 // 2 + 2
if i + length > len(body):
break
data = bytes(body[i + 2 : i + length])
blocks.append((i, "10", t1, data, length))
i += length
elif t0 == 0x20 and t1 % 4 == 0 and 0 < t1 <= 0xFC:
length = t1 + 2
if i + length > len(body):
break
data = bytes(body[i + 2 : i + length])
blocks.append((i, "20", t1, data, length))
i += length
elif t0 == 0x00 and t1 % 4 == 0:
# 2-byte marker
blocks.append((i, "00", t1, b"", 2))
i += 2
elif t0 == 0x30 and t1 % 4 == 0:
length = t1 * 4
if i + length > len(body):
break
data = bytes(body[i + 2 : i + length])
blocks.append((i, "30", t1, data, length))
i += length
elif t0 == 0x40 and t1 == 0x02:
length = 22
if i + length > len(body):
break
data = bytes(body[i + 2 : i + length])
blocks.append((i, "40", t1, data, length))
i += length
else:
blocks.append((i, "??", t0, bytes(body[i:i+8]), 0))
break
return blocks, i
def main():
for name in ("event-c", "event-d", "event-a", "event-b"):
b = load_bundle(name)
body = b.body
for s in range(15):
if body[s] == 0x10 and body[s+1] % 4 == 0 and 0 < body[s+1] <= 0xFC:
start = s; break
else:
start = 7
blocks, end = walk(body, start)
types = Counter(bb[1] for bb in blocks)
print(f"\n=== {name} === body={len(body)} N={len(b.samples['Tran'])} start={start}")
print(f" total blocks: {len(blocks)}, walk ended at {end}/{len(body)}")
print(f" type counts: {dict(types)}")
if blocks and blocks[-1][1] == "??":
print(f" stopped at byte: 0x{blocks[-1][2]:02x}, prev 5 blocks: {[(bb[0], bb[1], bb[2]) for bb in blocks[-6:-1]]}")
# Sum payload sizes by type
payload_sizes = {t: sum(len(bb[3]) for bb in blocks if bb[1] == t) for t in types}
print(f" payload bytes by type: {payload_sizes}")
if __name__ == "__main__":
main()
analysis/walk_v6.py
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"""
Walker v6: handle 40 02 blocks correctly (length 20).
Block formats:
- [10 NN]: 4-bit nibble delta data, length = NN/2 + 2
- [20 NN]: int8 literal data, length = NN + 2
- [00 NN]: 2-byte marker
- [30 NN]: trailer/summary block, length = NN*4
- [40 02]: segment header, fixed length 20
"""
import sys
sys.path.insert(0, ".")
from analysis.load_bundle import load_bundle
from collections import Counter
def walk(body, start, max_blocks=10000):
i = start
blocks = []
while i + 1 < len(body) and len(blocks) < max_blocks:
t0 = body[i]
t1 = body[i + 1]
if t0 == 0x10 and t1 % 4 == 0 and 0 < t1 <= 0xFC:
length = t1 // 2 + 2
elif t0 == 0x20 and t1 % 4 == 0 and 0 < t1 <= 0xFC:
length = t1 + 2
elif t0 == 0x00 and t1 % 4 == 0:
length = 2
elif t0 == 0x30 and t1 % 4 == 0 and 0 < t1 <= 0x10:
length = t1 * 4
elif t0 == 0x40 and t1 == 0x02:
length = 20
else:
blocks.append((i, "??", t0, bytes(body[i:i+8]), 0))
break
if i + length > len(body):
break
data = bytes(body[i + 2 : i + length])
blocks.append((i, f"{t0:02x}", t1, data, length))
i += length
return blocks, i
def main():
for name in ("event-c", "event-d", "event-a", "event-b"):
b = load_bundle(name)
body = b.body
for s in range(15):
if body[s] == 0x10 and body[s+1] % 4 == 0 and 0 < body[s+1] <= 0xFC:
start = s; break
else:
start = 7
blocks, end = walk(body, start)
types = Counter(bb[1] for bb in blocks)
print(f"\n=== {name} === body={len(body)} N={len(b.samples['Tran'])} start={start}")
print(f" total blocks: {len(blocks)}, walk ended at {end}/{len(body)}")
print(f" type counts: {dict(types)}")
if blocks and blocks[-1][1] == "??":
print(f" stopped at byte: 0x{blocks[-1][2]:02x} at offset {blocks[-1][0]}")
print(f" prev 5 blocks: {[(bb[0], bb[1], bb[2]) for bb in blocks[-6:-1]]}")
print(f" bytes around stop: {body[end-4:end+24].hex(' ')}")
# Sum
payload_sizes = {t: sum(len(bb[3]) for bb in blocks if bb[1] == t) for t in types}
print(f" payload bytes by type: {payload_sizes}")
if __name__ == "__main__":
main()
analysis_idf/corpus_accuracy.py
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"""Run read_idf_file across the corpus and report per-channel accuracy vs sidecars."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from micromate.idf_file import read_idf_file
from analysis_idf.recon import load_sidecar_samples
def sidecar_path(idfw: Path) -> Path:
return idfw.parent / "TXT" / f"{idfw.name}.txt"
def main():
root = REPO / "tests/fixtures/THORDATA_example"
files = [f for f in root.rglob("*.IDFW") if not str(f).endswith(".CDB")]
files.sort()
GEO_LSB = 0.0003
n_ok = n_skip = 0
overall = {"Tran": [], "Vert": [], "Long": []}
for f in files:
try:
res = read_idf_file(f)
except Exception:
n_skip += 1
continue
sc_path = sidecar_path(f)
if not sc_path.exists():
n_skip += 1
continue
try:
sc = load_sidecar_samples(sc_path)
except Exception:
n_skip += 1
continue
per_file = {}
for ch in ("Tran", "Vert", "Long"):
sc_counts = [int(round(v / GEO_LSB)) for v in sc[ch]]
dec = res.samples.get(ch, [])
n = min(len(sc_counts), len(dec))
if n == 0:
per_file[ch] = 0.0
continue
exact = sum(1 for i in range(n) if sc_counts[i] == dec[i])
pct = 100.0 * exact / n
per_file[ch] = pct
overall[ch].append(pct)
n_ok += 1
print(f"Processed {n_ok} files (skipped {n_skip})")
print("Per-channel exact-match % (mean / min / max):")
for ch, vals in overall.items():
if vals:
avg = sum(vals) / len(vals)
print(f" {ch}: mean={avg:.2f}% min={min(vals):.2f}% max={max(vals):.2f}% n={len(vals)}")
if __name__ == "__main__":
main()
analysis_idf/diff_trail.py
+49
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"""Find where decoded-vs-sidecar diverges for each channel."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from minimateplus.waveform_codec import decode_waveform_v2
from analysis_idf.recon import TARGET, TXT, load_sidecar_samples
def main():
buf = TARGET.read_bytes()
sc = load_sidecar_samples(TXT)
decoded = decode_waveform_v2(buf[0x0f1f:])
GEO_LSB = 0.0003
for ch in ("Tran", "Vert", "Long"):
sc_counts = [int(round(v / GEO_LSB)) for v in sc[ch]]
dec = decoded[ch]
# Find ALL transitions where mismatches start/stop
first_diff = next((i for i in range(len(dec)) if dec[i] != sc_counts[i]), None)
if first_diff is None:
print(f"{ch}: NO MISMATCHES")
continue
print(f"{ch}: first diff at idx {first_diff}")
# Show 5 before, 5 after
for i in range(max(0, first_diff - 3), min(len(dec), first_diff + 8)):
mark = " " if dec[i] == sc_counts[i] else "**"
print(f" {mark} idx {i:4d}: sc={sc_counts[i]:6d} dec={dec[i]:6d} diff={dec[i]-sc_counts[i]:+d}")
# Where does cumulative diff exceed 100?
cum_match_run = 0
max_match_run = 0
match_run_start = 0
diff_count = 0
for i in range(len(dec)):
if dec[i] == sc_counts[i]:
cum_match_run += 1
max_match_run = max(max_match_run, cum_match_run)
else:
cum_match_run = 0
diff_count += 1
print(f" total mismatches: {diff_count}/{len(dec)}, longest run of matches: {max_match_run}")
print()
if __name__ == "__main__":
main()
analysis_idf/e2e_idfh.py
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"""End-to-end IDFH ingest verification."""
from __future__ import annotations
import sys
import tempfile
import json
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from sfm.waveform_store import WaveformStore
def main():
idfh = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM13981/UM13981_20220805075441.IDFH"
txt = idfh.parent / "TXT" / f"{idfh.name}.txt"
with tempfile.TemporaryDirectory() as td:
store = WaveformStore(Path(td))
ev, rec = store.save_imported_idf(
idfh.read_bytes(),
idfh,
idf_report_text=txt.read_text(errors="replace"),
)
print("=== save_imported_idf (IDFH) ===")
print(f" serial: {rec['serial']}")
print(f" filename: {rec['filename']}")
print(f" filesize: {rec['filesize']}")
print(f" h5: {rec['hdf5_filename']}") # expect None for histogram
print(f" sidecar: {rec['sidecar_filename']}")
print()
print("=== Event ===")
print(f" timestamp: {ev.timestamp}")
print(f" record_type: {ev.record_type}")
print(f" sample_rate: {ev.sample_rate}")
print()
# Inspect sidecar to confirm intervals were stashed
sc_path = Path(td) / "UM13981" / f"{idfh.name}.sfm.json"
sc = json.loads(sc_path.read_text())
intervals = sc.get("extensions", {}).get("idf_intervals", [])
print(f" sidecar intervals: {len(intervals)}")
if intervals:
print(f" first interval: {intervals[0]}")
print(f" last interval: {intervals[-1]}")
if __name__ == "__main__":
main()
analysis_idf/e2e_no_txt.py
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"""Verify the had_report=False path: ingest IDFW with no .txt."""
from __future__ import annotations
import sys
from pathlib import Path
import tempfile
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from sfm.waveform_store import WaveformStore
def main():
idfw = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM11719/UM11719_20231219162723.IDFW"
with tempfile.TemporaryDirectory() as td:
store = WaveformStore(Path(td))
ev, rec = store.save_imported_idf(
idfw.read_bytes(),
idfw,
serial_hint=None,
idf_report_text=None, # ← no .txt!
)
print("=== IDFW without .txt ingest ===")
print(f" serial: {rec['serial']}")
print(f" timestamp: {ev.timestamp}")
print(f" sample_rate: {ev.sample_rate}")
print(f" record_type: {ev.record_type}")
print(f" rectime_sec: {ev.rectime_seconds}")
nT = len(ev.raw_samples.get('Tran', [])) if ev.raw_samples else 0
nV = len(ev.raw_samples.get('Vert', [])) if ev.raw_samples else 0
nL = len(ev.raw_samples.get('Long', [])) if ev.raw_samples else 0
nM = len(ev.raw_samples.get('MicL', [])) if ev.raw_samples else 0
print(f" raw_samples: Tran={nT} Vert={nV} Long={nL} MicL={nM}")
if ev.peak_values:
print(f" peak_values: tran={ev.peak_values.tran} vert={ev.peak_values.vert} long={ev.peak_values.long}")
print(f" h5 written: {rec['hdf5_filename']}")
if __name__ == "__main__":
main()
analysis_idf/e2e_report.py
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"""End-to-end Thor report PDF rendering.
Ingests an IDFW + .txt via save_imported_idf, runs gather_report_data
(faking a minimal DB row), and renders the PDF to disk.
"""
from __future__ import annotations
import sys
import tempfile
import json
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from sfm.waveform_store import WaveformStore
from sfm import report_pdf
class FakeDb:
"""Stand-in for SeismoDb.get_event(); the renderer only needs a few cols."""
def __init__(self, event):
self.event = event
def get_event(self, _id):
return self.event
def main():
base = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM11719"
idfw = base / "UM11719_20231219162723.IDFW"
txt = base / "TXT" / f"{idfw.name}.txt"
with tempfile.TemporaryDirectory() as td:
store = WaveformStore(Path(td))
ev, rec = store.save_imported_idf(
idfw.read_bytes(),
idfw,
idf_report_text=txt.read_text(errors="replace"),
)
print(f"save_imported_idf: h5={rec['hdf5_filename']}, sidecar={rec['sidecar_filename']}")
# Verify sidecar has bw_report block
sc_path = Path(td) / "UM11719" / f"{idfw.name}.sfm.json"
sc = json.loads(sc_path.read_text())
bw = sc.get("bw_report", {})
print(f" bw_report.available: {bw.get('available')}")
print(f" bw_report.peaks.tran.ppv_ips: {bw.get('peaks', {}).get('tran', {}).get('ppv_ips')}")
print(f" bw_report.mic.pspl_dbl: {bw.get('mic', {}).get('pspl_dbl')}")
print(f" bw_report.histogram.n_intervals: {bw.get('histogram', {}).get('n_intervals')}")
# Build a DB-row-shaped dict from the Event for gather_report_data
import datetime
ts = ev.timestamp
ts_iso = None
if ts is not None:
try:
ts_iso = datetime.datetime(ts.year, ts.month, ts.day, ts.hour, ts.minute, ts.second).isoformat()
except Exception:
pass
fake_row = {
"serial": "UM11719",
"blastware_filename": rec["filename"],
"record_type": "Waveform",
"timestamp": ts_iso,
"sample_rate": ev.sample_rate,
"project": ev.project_info.project if ev.project_info else None,
"client": ev.project_info.client if ev.project_info else None,
"operator": ev.project_info.operator if ev.project_info else None,
"sensor_location": ev.project_info.sensor_location if ev.project_info else None,
"created_at": None,
}
rd = report_pdf.gather_report_data(FakeDb(fake_row), store, event_id="test-1")
print()
print(f"=== ReportData ===")
print(f" event_id: {rd.event_id}")
print(f" serial: {rd.serial}")
print(f" record_type: {rd.record_type}")
print(f" event_datetime: {rd.event_datetime_str}")
print(f" trigger: {rd.trigger_source}")
print(f" geo_range: {rd.geo_range_str}")
print(f" sample_rate: {rd.sample_rate_str}")
print(f" firmware: {rd.firmware}")
print(f" calibration: {rd.calibration_date} by {rd.calibration_by}")
print(f" battery: {rd.battery_volts}")
print(f" PVS: {rd.peak_vector_sum_ips} in/s at {rd.peak_vector_sum_time_s} sec")
print(f" mic_pspl_dbl: {rd.mic_pspl_dbl}")
print(f" mic_zc_freq_hz: {rd.mic_zc_freq_hz}")
print(f" channel_stats: {len(rd.channel_stats)} rows")
for cs in rd.channel_stats:
print(f" {cs['name']}: PPV={cs['ppv_ips']} ZC={cs['zc_freq_hz']} ToP={cs['time_of_peak_s']} Acc={cs['peak_accel_g']} Disp={cs['peak_disp_in']} Test={cs['sensor_check']}")
# Render the PDF
out_path = REPO / "analysis_idf" / "thor_report.pdf"
pdf_bytes = report_pdf.render_event_report_pdf(rd)
out_path.write_bytes(pdf_bytes)
print()
print(f" PDF written: {out_path} ({len(pdf_bytes)} bytes)")
if __name__ == "__main__":
main()
analysis_idf/e2e_report_idfh.py
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"""End-to-end Thor IDFH histogram report PDF rendering."""
from __future__ import annotations
import sys
import tempfile
import json
import datetime
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from sfm.waveform_store import WaveformStore
from sfm import report_pdf
class FakeDb:
def __init__(self, event):
self.event = event
def get_event(self, _id):
return self.event
def main():
# Use the multi-interval IDFH (81 + trigger row)
idfh = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM13981/UM13981_20220805075441.IDFH"
txt = idfh.parent / "TXT" / f"{idfh.name}.txt"
with tempfile.TemporaryDirectory() as td:
store = WaveformStore(Path(td))
ev, rec = store.save_imported_idf(
idfh.read_bytes(),
idfh,
idf_report_text=txt.read_text(errors="replace"),
)
print(f"save_imported_idf: h5={rec['hdf5_filename']}, sidecar={rec['sidecar_filename']}")
sc_path = Path(td) / "UM13981" / f"{idfh.name}.sfm.json"
sc = json.loads(sc_path.read_text())
bw = sc.get("bw_report", {})
hist = bw.get("histogram", {})
print(f" bw_report.histogram.start: {hist.get('start')}")
print(f" bw_report.histogram.stop: {hist.get('stop')}")
print(f" bw_report.histogram.n_intervals: {hist.get('n_intervals')}")
print(f" bw_report.histogram.interval_size: {hist.get('interval_size')}")
print(f" bw_report.histogram.interval_size_s: {hist.get('interval_size_s')}")
print(f" bw_report.peaks.tran.ppv_ips: {bw.get('peaks', {}).get('tran', {}).get('ppv_ips')}")
ts = ev.timestamp
ts_iso = None
if ts is not None:
try:
ts_iso = datetime.datetime(ts.year, ts.month, ts.day, ts.hour, ts.minute, ts.second).isoformat()
except Exception:
pass
fake_row = {
"serial": "UM13981",
"blastware_filename": rec["filename"],
"record_type": "Histogram",
"timestamp": ts_iso,
"sample_rate": ev.sample_rate,
"project": ev.project_info.project if ev.project_info else None,
"client": ev.project_info.client if ev.project_info else None,
"operator": ev.project_info.operator if ev.project_info else None,
"sensor_location": ev.project_info.sensor_location if ev.project_info else None,
"created_at": None,
}
rd = report_pdf.gather_report_data(FakeDb(fake_row), store, event_id="hist-1")
print()
print("=== ReportData (histogram) ===")
print(f" is_histogram: {rd.is_histogram}")
print(f" histogram_start: {rd.histogram_start_str}")
print(f" histogram_stop: {rd.histogram_stop_str}")
print(f" histogram_n_intervals: {rd.histogram_n_intervals}")
print(f" histogram_interval_size:{rd.histogram_interval_size}")
print(f" histogram_interval_times[:3]: {rd.histogram_interval_times[:3]}")
print(f" histogram_interval_times[-2:]: {rd.histogram_interval_times[-2:]}")
print(f" channel_stats: {len(rd.channel_stats)} rows")
for cs in rd.channel_stats:
print(f" {cs['name']}: PPV={cs['ppv_ips']} ZC={cs['zc_freq_hz']} peak_date={cs['peak_date']} peak_time={cs['peak_time']}")
pdf_bytes = report_pdf.render_event_report_pdf(rd)
out_path = REPO / "analysis_idf" / "thor_report_idfh.pdf"
out_path.write_bytes(pdf_bytes)
print()
print(f" PDF written: {out_path} ({len(pdf_bytes)} bytes)")
if __name__ == "__main__":
main()
analysis_idf/e2e_save_idf.py
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"""End-to-end ingest test: feed an IDFW + .txt to save_imported_idf in a tmp store."""
from __future__ import annotations
import sys
from pathlib import Path
import tempfile
import shutil
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from sfm.waveform_store import WaveformStore
def main():
idfw = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM11719/UM11719_20231219162723.IDFW"
txt = idfw.parent / "TXT" / f"{idfw.name}.txt"
with tempfile.TemporaryDirectory() as td:
store = WaveformStore(Path(td))
ev, rec = store.save_imported_idf(
idfw.read_bytes(),
idfw,
serial_hint=None,
idf_report_text=txt.read_text(errors="replace"),
)
print("=== Save result ===")
print(f" serial: {rec['serial']}")
print(f" filename: {rec['filename']}")
print(f" filesize: {rec['filesize']}")
print(f" h5: {rec['hdf5_filename']}")
print(f" sidecar: {rec['sidecar_filename']}")
print()
print("=== Event ===")
print(f" serial: {ev.serial if hasattr(ev,'serial') else '(n/a)'}")
print(f" timestamp: {ev.timestamp}")
print(f" sample_rate: {ev.sample_rate}")
print(f" record_type: {ev.record_type}")
print(f" rectime_sec: {ev.rectime_seconds}")
print(f" raw_samples: Tran={len(ev.raw_samples.get('Tran', [])) if ev.raw_samples else 0}, Vert={len(ev.raw_samples.get('Vert', [])) if ev.raw_samples else 0}, Long={len(ev.raw_samples.get('Long', [])) if ev.raw_samples else 0}, MicL={len(ev.raw_samples.get('MicL', [])) if ev.raw_samples else 0}")
if ev.peak_values:
print(f" peaks (txt): Tran={ev.peak_values.tran} Vert={ev.peak_values.vert} Long={ev.peak_values.long}")
print()
# Verify the h5 file actually got written
h5path = Path(td) / "UM11719" / f"{idfw.name}.h5"
print(f" h5 exists: {h5path.exists()} size={h5path.stat().st_size if h5path.exists() else 0}")
sidecar = Path(td) / "UM11719" / f"{idfw.name}.sfm.json"
print(f" sidecar exists:{sidecar.exists()} size={sidecar.stat().st_size if sidecar.exists() else 0}")
if __name__ == "__main__":
main()
analysis_idf/idfh_decode.py
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"""Decode IDFH histogram intervals + verify against sidecar."""
from __future__ import annotations
import sys
import struct
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
SEGMENT_MAGIC = b"\x02\xda\x0a\x00\x00\x00"
SEGMENT_SIZE = 732 # = 10-byte header + 10 × 72-byte intervals + 2-byte tail
INTERVAL_SIZE = 72
CHANNELS = ("Tran", "Vert", "Long", "MicL")
def decode_interval(buf72: bytes) -> dict:
"""Decode one 72-byte interval into per-channel min/max/halfp."""
out = {}
for i, ch in enumerate(CHANNELS):
block = buf72[i*16 : (i+1)*16]
mn = struct.unpack_from(">h", block, 0)[0]
mx = struct.unpack_from(">h", block, 2)[0]
sb = struct.unpack_from(">h", block, 4)[0]
halfp = struct.unpack_from(">H", block, 6)[0]
f10 = struct.unpack_from(">H", block, 10)[0]
f14 = struct.unpack_from(">H", block, 14)[0]
peak_count = max(abs(mn), abs(mx))
out[ch] = {
"min": mn,
"max": mx,
"field4": sb,
"halfp": halfp,
"field10": f10,
"field14": f14,
"peak": peak_count,
"freq_hz": (512.0 / halfp) if halfp > 5 else None,
}
out["_tail"] = buf72[64:].hex(" ")
return out
def walk_idfh(buf: bytes) -> list:
"""Walk all interval records in an IDFH file."""
intervals = []
# Multi-segment file: every 02 da 0a 00 00 00 marker introduces a segment.
# Single-interval file: just one body header at 0xf96 of form ?? ?? 0a 00 00 00.
# Find them all.
i = 0
while True:
j = buf.find(b"\x0a\x00\x00\x00", i)
if j < 0:
break
# Validate: the 2 bytes before must form a length, and we want bytes
# [j-2 : j+6] to have a recognisable shape. Actually the cleanest
# filter is "preceded by a length and followed by 00 NN 05 3f".
if j < 2:
i = j + 1
continue
# Body header form: [length_be_2][0a 00 00 00][00 NN][05 3f]
if j + 10 > len(buf):
break
length = int.from_bytes(buf[j-2:j], "big")
# Verify the segment-marker shape: [length_be][0a 00 00 00][00 NN][05 3f]
if buf[j+4] != 0x00:
i = j + 1
continue
if buf[j+6:j+8] != b"\x05\x3f":
i = j + 1
continue
# Header layout (10 bytes): [length_be 2B][0a 00 00 00 4B][00 NN 2B][05 3f 2B]
# Followed by N interval records of 72 bytes each, then 2 tail bytes.
# length value = (N × 72) + 10 (counts bytes from 0x0a... through interval data).
header_start = j - 2
n_intervals = (length - 10) // INTERVAL_SIZE
interval_start = header_start + 10
for k in range(n_intervals):
off = interval_start + k * INTERVAL_SIZE
if off + INTERVAL_SIZE > len(buf):
break
chunk = buf[off:off + INTERVAL_SIZE]
intervals.append({"offset": off, **decode_interval(chunk)})
i = header_start + length + 2
return intervals
def main():
# Test against multi-segment IDFH
target = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM13981/UM13981_20220805075441.IDFH"
sc_path = target.parent / "TXT" / f"{target.name}.txt"
buf = target.read_bytes()
intervals = walk_idfh(buf)
print(f"=== {target.name} ===")
print(f" file size: {len(buf)}")
print(f" decoded intervals: {len(intervals)}")
# Show first 2 + last 2
sc_rows = []
for line in sc_path.read_text(errors="replace").splitlines():
if line.startswith("2022-") or line.startswith("2023-"):
sc_rows.append(line)
print(f" sidecar rows: {len(sc_rows)}")
print()
for k in [0, 1, 78, 79, 80]:
if k >= len(intervals):
continue
iv = intervals[k]
print(f"--- interval {k} @0x{iv['offset']:04x} ---")
for ch in CHANNELS:
d = iv[ch]
peak_ips = d["peak"] / 32768 * 10.0
print(f" {ch}: peak={d['peak']:5d} ({peak_ips:.4f} in/s) halfp={d['halfp']:5d} freq={d['freq_hz']}")
# sidecar row
if k < len(sc_rows):
print(f" SC: {sc_rows[k]}")
# Test single-interval IDFH
print()
target2 = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM11719/UM11719_20231219162648.IDFH"
sc2 = target2.parent / "TXT" / f"{target2.name}.txt"
buf2 = target2.read_bytes()
intervals2 = walk_idfh(buf2)
print(f"=== {target2.name} ===")
print(f" file size: {len(buf2)}, decoded intervals: {len(intervals2)}")
if intervals2:
iv = intervals2[0]
for ch in CHANNELS:
d = iv[ch]
peak_ips = d["peak"] / 32768 * 10.0
print(f" {ch}: peak={d['peak']:5d} ({peak_ips:.4f} in/s) halfp={d['halfp']:5d} freq={d['freq_hz']}")
sc_rows2 = [l for l in sc2.read_text(errors='replace').splitlines() if l.startswith("2023-")]
if sc_rows2:
print(f" SC: {sc_rows2[0]}")
if __name__ == "__main__":
main()
analysis_idf/idfh_period.py
+41
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"""Find IDFH interval period via auto-correlation of structural patterns."""
from __future__ import annotations
import sys
from pathlib import Path
from collections import Counter
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
def main():
target = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM13981/UM13981_20220805075441.IDFH"
buf = target.read_bytes()
body_start = 0xF96
body_end = 0x270C
body = buf[body_start:body_end]
print(f"body size: {len(body)} bytes (file {len(buf)} bytes)")
# For each candidate interval size, count how many bytes at fixed offsets within
# each interval are zero (consistent column-zero pattern indicates correct size).
print()
print("=== zero-column score by interval size (higher = more likely) ===")
best = []
for sz in range(16, 100):
n = len(body) // sz
if n < 30:
continue
# For each column position within an interval, count how many of n intervals have zero
score = 0
for col in range(sz):
zeros = sum(1 for i in range(n) if body[i*sz + col] == 0)
if zeros >= n * 0.9:
score += 1
best.append((score, sz, n))
best.sort(reverse=True)
for score, sz, n in best[:10]:
print(f" size={sz:3d} n_intervals={n} consistently-zero-cols={score}")
if __name__ == "__main__":
main()
analysis_idf/per_file_detail.py
+40
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"""Per-file accuracy + sample-count details."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from micromate.idf_file import read_idf_file
from analysis_idf.recon import load_sidecar_samples
def main():
root = REPO / "tests/fixtures/THORDATA_example"
files = sorted([f for f in root.rglob("*.IDFW") if not str(f).endswith(".CDB")])
GEO_LSB = 0.0003
# Limit to first 15 successful files for detail.
shown = 0
for f in files:
try:
res = read_idf_file(f)
except Exception:
continue
sc_path = f.parent / "TXT" / f"{f.name}.txt"
if not sc_path.exists():
continue
sc = load_sidecar_samples(sc_path)
sc_tran = [int(round(v / GEO_LSB)) for v in sc["Tran"]]
dec = res.samples.get("Tran", [])
n = min(len(sc_tran), len(dec))
exact = sum(1 for i in range(n) if sc_tran[i] == dec[i]) if n else 0
pct = 100.0 * exact / n if n else 0.0
print(f"{f.name:40s} size={f.stat().st_size:6d} sc_n={len(sc_tran):4d} dec_n={len(dec):4d} exact={pct:.1f}%")
shown += 1
if shown >= 20:
break
if __name__ == "__main__":
main()
analysis_idf/probe_boundary.py
+64
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"""Look at what's at the divergence boundary."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from minimateplus.waveform_codec import walk_body, find_data_start, parse_segment_header
from analysis_idf.recon import TARGET, TXT, load_sidecar_samples
def main():
buf = TARGET.read_bytes()
body = buf[0x0f1f:]
start = find_data_start(body)
print(f"data_start: {start} (= file offset 0x{0x0f1f + start:04x})")
blocks = walk_body(body, start)
print(f"{len(blocks)} blocks total")
print()
# First 25 blocks
print("=== first 30 blocks ===")
for i, b in enumerate(blocks[:30]):
body_off = 0x0f1f + b.offset
if b.tag_hi == 0x40:
hdr = parse_segment_header(b)
print(f" [{i:3d}] @0x{body_off:04x} {b.kind} (segment header) counter={hdr['counter'] if hdr else '?'} field2={hdr['field2'].hex() if hdr else '?'} anchor={hdr['anchor_bytes'].hex() if hdr else '?'} tail={hdr['tail'].hex() if hdr else '?'}")
else:
print(f" [{i:3d}] @0x{body_off:04x} {b.kind} len={b.length} data={b.data[:16].hex()}")
print()
# Cumulative sample counts per block to find which block contains sample 254
print("=== cumulative samples through blocks ===")
cur_ch = "Tran"
rotation = ["Vert", "Long", "MicL", "Tran"]
seg_count = 0
samples_in_curseg = 2 # preamble Tran[0], Tran[1]
for i, b in enumerate(blocks[:30]):
if b.tag_hi == 0x40:
seg_count += 1
prev_ch = cur_ch
cur_ch = rotation[(seg_count - 1) % 4]
print(f" [{i:3d}] 40 02 -> end of {prev_ch} segment, start {cur_ch} (segment {seg_count})")
samples_in_curseg = 2 # anchors
elif (b.tag_hi & 0xF0) == 0x10:
nn = ((b.tag_hi & 0x0F) << 8) | b.tag_lo
samples_in_curseg += nn
print(f" [{i:3d}] {b.kind} nibble: +{nn} samples, ch={cur_ch}, ch_total~{samples_in_curseg}")
elif (b.tag_hi & 0xF0) == 0x20:
nn = ((b.tag_hi & 0x0F) << 8) | b.tag_lo
samples_in_curseg += nn
print(f" [{i:3d}] {b.kind} int8: +{nn} samples, ch={cur_ch}, ch_total~{samples_in_curseg}")
elif b.tag_hi == 0x00:
samples_in_curseg += b.tag_lo
print(f" [{i:3d}] {b.kind} RLE: +{b.tag_lo}, ch={cur_ch}, ch_total~{samples_in_curseg}")
elif b.tag_hi == 0x30:
samples_in_curseg += b.tag_lo
print(f" [{i:3d}] {b.kind} packed12: +{b.tag_lo} samples, ch={cur_ch}, ch_total~{samples_in_curseg}")
if __name__ == "__main__":
main()
analysis_idf/recon.py
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"""Reconnaissance helpers for cracking the Thor IDFW binary."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
TARGET = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM11719/UM11719_20231219162723.IDFW"
TXT = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM11719/TXT/UM11719_20231219162723.IDFW.txt"
def hex_at(buf: bytes, off: int, n: int = 32) -> str:
chunk = buf[off : off + n]
hexs = " ".join(f"{b:02x}" for b in chunk)
asc = "".join(chr(b) if 32 <= b < 127 else "." for b in chunk)
return f"{off:04x}: {hexs} {asc}"
def find_all(buf: bytes, needle: bytes) -> list[int]:
out: list[int] = []
i = 0
while True:
j = buf.find(needle, i)
if j < 0:
break
out.append(j)
i = j + 1
return out
def load_sidecar_samples(path: Path) -> dict[str, list[float]]:
"""Parse the txt sample table — Tran/Vert/Long/MicL."""
out = {"Tran": [], "Vert": [], "Long": [], "MicL": []}
in_block = False
for line in path.read_text(errors="replace").splitlines():
if not in_block:
if line.strip() == "Waveform Data Channels":
in_block = True
continue
if line.startswith("Waveform Data USB Channels"):
break
parts = line.split("\t")
# First row is the header "\tTran\tVert\tLong\tMicL"
if len(parts) >= 5 and parts[1] == "Tran":
continue
if len(parts) < 5:
continue
try:
out["Tran"].append(float(parts[1]))
out["Vert"].append(float(parts[2]))
out["Long"].append(float(parts[3]))
out["MicL"].append(float(parts[4]))
except ValueError:
continue
return out
def main():
buf = TARGET.read_bytes()
samples = load_sidecar_samples(TXT)
print(f"file size: {len(buf)} bytes")
print(f"sample rows: Tran={len(samples['Tran'])} Vert={len(samples['Vert'])} Long={len(samples['Long'])} MicL={len(samples['MicL'])}")
print(f"first 6 Tran samples: {samples['Tran'][:6]}")
print(f"first 6 Vert samples: {samples['Vert'][:6]}")
print(f"first 6 Long samples: {samples['Long'][:6]}")
print(f"first 6 MicL samples: {samples['MicL'][:6]}")
print()
print("=== BW magic '00 02 00' positions ===")
hits = find_all(buf, b"\x00\x02\x00")
print(f"{len(hits)} hits")
for h in hits[:20]:
print(hex_at(buf, h, 24))
print()
print("=== '40 02' segment-header positions ===")
hits = find_all(buf, b"\x40\x02")
print(f"{len(hits)} hits")
for h in hits:
ctx_pre = buf[max(0, h - 4): h].hex()
ctx_post = buf[h: h + 20].hex()
# Show byte preceding to help identify real headers vs casual occurrences
print(f" 0x{h:04x} pre={ctx_pre} post={ctx_post}")
if __name__ == "__main__":
main()
analysis_idf/seg_resync.py
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"""Find each segment boundary in the channel and check if errors reset there."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from minimateplus.waveform_codec import decode_waveform_v2
from analysis_idf.recon import TARGET, TXT, load_sidecar_samples
def main():
buf = TARGET.read_bytes()
sc = load_sidecar_samples(TXT)
decoded = decode_waveform_v2(buf[0x0f1f:])
GEO_LSB = 0.0003
for ch in ("Tran", "Vert", "Long"):
sc_counts = [int(round(v / GEO_LSB)) for v in sc[ch]]
dec = decoded[ch]
# Find every transition where error becomes zero from nonzero (or grows from zero)
# Print indices where dec resyncs back to exact match.
n = min(len(sc_counts), len(dec))
events = []
prev_match = True
for i in range(n):
match = sc_counts[i] == dec[i]
if match != prev_match:
kind = "RESYNC" if match else "DIVERGE"
events.append((i, kind, sc_counts[i], dec[i]))
prev_match = match
print(f"{ch}: {len(events)} transitions")
for i, kind, sc_v, dec_v in events[:20]:
print(f" idx {i:4d} {kind:8s} sc={sc_v:6d} dec={dec_v:6d} diff={dec_v-sc_v:+d}")
print()
if __name__ == "__main__":
main()
analysis_idf/smoke_idfh.py
+46
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@@ -0,0 +1,46 @@
"""Smoke-test read_idf_file on IDFH across the corpus."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from micromate.idf_file import read_idf_file
def main():
target = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM11719/UM11719_20231219162648.IDFH"
result = read_idf_file(target)
ev = result.event
print(f"=== {target.name} ===")
print(f" signature: {result.signature}")
print(f" serial: {ev.serial}")
print(f" timestamp: {ev.timestamp}")
print(f" sample_rate: {ev.sample_rate}")
print(f" kind: {ev.kind}")
print(f" intervals: {len(result.intervals or [])}")
print(f" peaks: T={ev.peaks.transverse_ips:.4f} V={ev.peaks.vertical_ips:.4f} L={ev.peaks.longitudinal_ips:.4f}")
print()
root = REPO / "tests/fixtures/THORDATA_example"
files = list(root.rglob("*.IDFH"))
ok = fail = nyi = 0
total_intervals = 0
for f in files:
try:
r = read_idf_file(f)
ok += 1
total_intervals += len(r.intervals or [])
except NotImplementedError:
nyi += 1
except Exception as exc:
fail += 1
if fail <= 3:
print(f" FAIL: {f.name}: {type(exc).__name__}: {exc}")
print(f"Corpus: {len(files)} IDFH files | ok={ok} fail={fail} nyi={nyi}")
print(f"Total intervals decoded: {total_intervals}")
if __name__ == "__main__":
main()
analysis_idf/smoke_test.py
+48
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@@ -0,0 +1,48 @@
"""Smoke-test read_idf_file across the sample corpus."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from micromate.idf_file import read_idf_file, geo_count_to_ips, mic_count_to_psi
def main():
target = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM11719/UM11719_20231219162723.IDFW"
result = read_idf_file(target)
ev = result.event
print(f"=== {target.name} ===")
print(f" signature: {result.signature}")
print(f" serial: {ev.serial}")
print(f" timestamp: {ev.timestamp}")
print(f" sample_rate: {ev.sample_rate}")
print(f" record_time: {ev.record_time_sec}")
print(f" calibration: {result.binary_metadata.calibration_date}")
print(f" Tran samples: {len(result.samples['Tran'])}, peak_ips={ev.peaks.transverse_ips:.4f}")
print(f" Vert samples: {len(result.samples['Vert'])}, peak_ips={ev.peaks.vertical_ips:.4f}")
print(f" Long samples: {len(result.samples['Long'])}, peak_ips={ev.peaks.longitudinal_ips:.4f}")
print(f" MicL samples: {len(result.samples['MicL'])}")
print()
# Corpus sweep
root = REPO / "tests/fixtures/THORDATA_example"
files = [f for f in root.rglob("*.IDFW") if not str(f).endswith(".CDB")]
ok = fail = nyi = 0
for f in files:
try:
r = read_idf_file(f)
ok += 1
except NotImplementedError:
nyi += 1
except Exception as exc:
fail += 1
if fail <= 5:
print(f" FAIL: {f.name}: {type(exc).__name__}: {exc}")
print()
print(f"Corpus: {len(files)} IDFW files | ok={ok} fail={fail} not-implemented={nyi}")
if __name__ == "__main__":
main()
analysis_idf/test_adapter.py
+47
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@@ -0,0 +1,47 @@
"""Verify build_bw_report_from_idf against a known sidecar."""
from __future__ import annotations
import json
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from micromate.idf_ascii_report import parse_idf_report
from micromate.idf_to_bw_report import build_bw_report_from_idf
from micromate.idf_file import read_idf_file
def show(prefix: str, d: dict, indent: int = 0):
for k, v in d.items():
if isinstance(v, dict):
print(f"{' '*indent}{prefix}{k}:")
show("", v, indent + 1)
else:
print(f"{' '*indent}{prefix}{k}: {v!r}")
def main():
base = REPO / "tests/fixtures/THORDATA_example/THORDATA_example/UPMC Presby/UM11719"
idfw = base / "UM11719_20231219162723.IDFW"
txt = base / "TXT" / f"{idfw.name}.txt"
report_dict = parse_idf_report(txt.read_text(errors="replace"))
res = read_idf_file(idfw)
bw = build_bw_report_from_idf(report_dict, binary_md=res.binary_metadata)
print("=== IDFW → bw_report ===")
show("", bw)
print()
print("=== IDFH (single trigger row) ===")
idfh = base / "UM11719_20231219162648.IDFH"
txt_h = base / "TXT" / f"{idfh.name}.txt"
rh = parse_idf_report(txt_h.read_text(errors="replace"))
res_h = read_idf_file(idfh)
bw_h = build_bw_report_from_idf(rh, binary_md=res_h.binary_metadata, intervals=res_h.intervals)
show("", bw_h)
if __name__ == "__main__":
main()
analysis_idf/thor_report.pdf
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analysis_idf/trace_path.py
+73
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@@ -0,0 +1,73 @@
"""Trace Tran sample-by-sample to find exactly where the codec drifts."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from analysis_idf.recon import TARGET, TXT, load_sidecar_samples
def s4(n: int) -> int:
return n if n < 8 else n - 16
def i8(b: int) -> int:
return b if b < 128 else b - 256
def main():
buf = TARGET.read_bytes()
sc = load_sidecar_samples(TXT)
GEO_LSB = 0.0003
sc_tran = [int(round(v / GEO_LSB)) for v in sc["Tran"]]
body = buf[0x0f1f:]
# Tran[0], Tran[1] from preamble
t0 = int.from_bytes(body[3:5], "big", signed=True)
t1 = int.from_bytes(body[5:7], "big", signed=True)
print(f"preamble Tran[0]={t0} Tran[1]={t1} (sidecar: {sc_tran[0]}, {sc_tran[1]})")
# Block 0: 10 f8 at body[7:9]
print(f"block 0: tag {body[7]:02x} {body[8]:02x}")
print(f" block 0 first 10 data bytes: {body[9:19].hex()}")
# Walk block 0 manually, comparing each sample
cur = t1
samples = [t0, t1]
block_off = 7
nn = body[8]
print(f" NN = {nn}")
data = body[9 : 9 + nn // 2]
for byi, byte in enumerate(data):
for nib_idx, nib in enumerate(((byte >> 4) & 0xF, byte & 0xF)):
cur += s4(nib)
samples.append(cur)
idx = len(samples) - 1
if 0 <= idx < len(sc_tran):
sc_v = sc_tran[idx]
match = "✓" if sc_v == cur else "✗"
if idx < 12 or 240 <= idx <= 260:
print(f" idx {idx:3d}: nibble byte={byte:02x} nib={nib:x} delta={s4(nib):+d} cur={cur:+d} sc={sc_v:+d} {match}")
print(f"end of block 0: cur={cur}, len(samples)={len(samples)}, decoder expected 250 here")
# Block 1: 20 28 starts at offset 9 + 124 = 133 from block_off=7
block1_off = 9 + nn // 2
print(f"block 1: tag {body[block1_off]:02x} {body[block1_off+1]:02x} (expecting 20 28)")
nn1 = body[block1_off + 1]
print(f" block 1 NN = {nn1}")
data1 = body[block1_off + 2 : block1_off + 2 + nn1]
for byi, byte in enumerate(data1):
cur += i8(byte)
samples.append(cur)
idx = len(samples) - 1
if idx < len(sc_tran):
sc_v = sc_tran[idx]
match = "✓" if sc_v == cur else "✗"
if 248 <= idx <= 295:
print(f" idx {idx:3d}: int8 byte={byte:02x} delta={i8(byte):+d} cur={cur:+d} sc={sc_v:+d} {match}")
if __name__ == "__main__":
main()
analysis_idf/try_codec.py
+42
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@@ -0,0 +1,42 @@
"""Feed candidate body offsets to the BW codec and compare with sidecar."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from minimateplus.waveform_codec import decode_waveform_v2, walk_body, find_data_start
from analysis_idf.recon import TARGET, TXT, load_sidecar_samples
def main():
buf = TARGET.read_bytes()
sc = load_sidecar_samples(TXT)
# Sidecar samples in 0.0003 counts (Thor geo LSB).
sc_tran = [int(round(v / 0.0003)) for v in sc["Tran"][:30]]
sc_vert = [int(round(v / 0.0003)) for v in sc["Vert"][:30]]
sc_long = [int(round(v / 0.0003)) for v in sc["Long"][:30]]
sc_micl = [int(round(v / 1e-6)) for v in sc["MicL"][:30]] # 1 µ unit for mic? Will iterate.
print(f"sidecar Tran (counts): {sc_tran}")
print(f"sidecar Vert (counts): {sc_vert}")
print(f"sidecar Long (counts): {sc_long}")
print(f"sidecar MicL (×1e-6): {sc_micl}")
print()
# Try candidate body start offsets.
for off in (0x0f1f, 0x1057, 0x11f1, 0x1333, 0x1bde, 0x0d30):
print(f"=== body @ 0x{off:04x} ===")
body = buf[off:]
decoded = decode_waveform_v2(body)
if not decoded:
print(" decode_waveform_v2 returned None")
continue
for ch in ("Tran", "Vert", "Long", "MicL"):
arr = decoded.get(ch, [])
print(f" {ch}[{len(arr)}]: {arr[:20]}")
print()
if __name__ == "__main__":
main()
analysis_idf/verify_full.py
+51
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@@ -0,0 +1,51 @@
"""Verify decode_waveform_v2 against sidecar across all 2304 samples per channel."""
from __future__ import annotations
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))
from minimateplus.waveform_codec import decode_waveform_v2
from analysis_idf.recon import TARGET, TXT, load_sidecar_samples
def main():
buf = TARGET.read_bytes()
sc = load_sidecar_samples(TXT)
body = buf[0x0f1f:]
decoded = decode_waveform_v2(body)
print(f"Sidecar lengths: Tran={len(sc['Tran'])} Vert={len(sc['Vert'])} Long={len(sc['Long'])} MicL={len(sc['MicL'])}")
print(f"Decoded lengths: Tran={len(decoded['Tran'])} Vert={len(decoded['Vert'])} Long={len(decoded['Long'])} MicL={len(decoded['MicL'])}")
print()
GEO_LSB = 0.0003 # in/s per count
for ch in ("Tran", "Vert", "Long"):
sc_counts = [int(round(v / GEO_LSB)) for v in sc[ch]]
dec = decoded[ch]
n = min(len(sc_counts), len(dec))
matches = sum(1 for i in range(n) if sc_counts[i] == dec[i])
first_mismatch = next((i for i in range(n) if sc_counts[i] != dec[i]), None)
print(f"{ch}: compared {n}, exact matches {matches} ({100*matches/n:.2f}%)")
if first_mismatch is not None:
i = first_mismatch
print(f" first mismatch at idx {i}: sidecar={sc_counts[i]} ({sc[ch][i]}), decoded={dec[i]}")
print(f" context sidecar[{i-2}..{i+5}]: {sc_counts[max(0,i-2):i+5]}")
print(f" context decoded[{i-2}..{i+5}]: {dec[max(0,i-2):i+5]}")
# MicL: find the multiplicative factor that fits
print()
print("=== MicL scale analysis ===")
sc_micl = sc["MicL"]
dec_micl = decoded["MicL"]
# Skip zero values when computing ratio
ratios = [sc_micl[i] / dec_micl[i] for i in range(min(50, len(sc_micl), len(dec_micl))) if dec_micl[i] != 0]
if ratios:
avg = sum(ratios) / len(ratios)
print(f" avg ratio sidecar/decoded over first 50 nonzero: {avg:.4e} (n={len(ratios)})")
print(f" ratios sample: {[f'{r:.4e}' for r in ratios[:6]]}")
if __name__ == "__main__":
main()
bridges/ach_server.py
+296 -117
View File
@@ -70,42 +70,77 @@ from minimateplus.transport import SocketTransport
from minimateplus.client import MiniMateClient
from minimateplus.models import DeviceInfo, Event, MonitorLogEntry
from sfm.database import SeismoDb
from sfm.waveform_store import WaveformStore
log = logging.getLogger("ach_server")
# ── Per-unit state (downloaded-key set) ───────────────────────────────────────
# ── Per-unit state (downloaded events index) ──────────────────────────────────
# Persisted as <output_dir>/ach_state.json
# Format:
# Format (current — v2):
# {
# "BE11529": {
# "downloaded_keys": ["01110000", "0111245a"], # hex keys already on disk
# "max_downloaded_key": "0111245a", # highest key ever seen
# "last_seen": "2026-04-11T01:04:36"
# "downloaded_events": { # key_hex → ISO timestamp string
# "01110000": "2026-04-11T00:42:17",
# "0111245a": "2026-04-11T01:04:30"
# },
# "max_downloaded_key": "0111245a",
# "last_seen": "2026-04-11T01:04:36",
# "serial": "BE11529",
# "peer": "63.43.212.232:51920"
# }
# }
#
# Key-based deduplication works well within a single "key generation" (between
# erases). After the device memory is erased the event counter resets to
# 0x01110000, so the first new event has the SAME key as the very first event
# we ever downloaded. We detect this situation with max_downloaded_key:
# Why (key, timestamp) and not key alone:
# The device's event-key counter resets to 0x01110000 after every memory
# erase (internal or external). A bare-key dedup (the v1 format) cannot
# distinguish a re-recorded event with the same key from one we already
# downloaded. The 0C waveform record's timestamp IS unique per physical
# event, so we pair (key, timestamp) and treat a key with a different
# timestamp as a new event regardless of `max_downloaded_key`.
#
# if max(current_device_keys) < max_downloaded_key
# → device was wiped and keys have restarted → treat all device keys as new
#
# After our own erase (--clear-after-download) we also explicitly clear
# downloaded_keys and max_downloaded_key so the next session starts fresh.
# Legacy v1 format (`downloaded_keys: list[str]` only) is auto-migrated on
# read: the keys are kept under a sentinel of "" (empty string) timestamp so
# the (key, timestamp) compare always sees a mismatch and forces a one-time
# re-download. After that pass the state is rewritten in v2 form.
_state_lock = threading.Lock()
def _load_state(state_path: Path) -> dict:
if state_path.exists():
try:
with open(state_path) as f:
return json.load(f)
except Exception:
pass
return {}
"""
Load ach_state.json, transparently migrating any legacy
`downloaded_keys: list` entries into the v2 `downloaded_events: dict`
schema. Returns the migrated state.
"""
if not state_path.exists():
return {}
try:
with open(state_path) as f:
state = json.load(f)
except Exception:
return {}
# Per-unit migration: legacy list → dict-with-empty-timestamps
for unit_key, unit_state in list(state.items()):
if not isinstance(unit_state, dict):
continue
if "downloaded_events" in unit_state:
continue
legacy_keys = unit_state.get("downloaded_keys")
if isinstance(legacy_keys, list):
unit_state["downloaded_events"] = {k: "" for k in legacy_keys}
log.info(
"ach_state: migrated %s from v1 (downloaded_keys list) → v2 "
"(downloaded_events dict, %d keys with empty timestamps; "
"they will re-validate on next session)",
unit_key, len(legacy_keys),
)
else:
unit_state["downloaded_events"] = {}
# keep legacy field for one cycle; cleared on next save
unit_state.pop("downloaded_keys", None)
return state
def _save_state(state_path: Path, state: dict) -> None:
@@ -139,8 +174,12 @@ class AchSession:
max_events: Optional[int],
state_path: Path,
db: "SeismoDb",
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
self.peer = peer
@@ -150,8 +189,17 @@ class AchSession:
self.max_events = max_events
self.state_path = state_path
self.db = db
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
# become inconsistent with what's actually on disk / in the DB.
self.force_redownload = force_redownload
def run(self) -> None:
ts = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
@@ -247,6 +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:
@@ -273,11 +356,20 @@ class AchSession:
state = _load_state(self.state_path)
unit_key = serial or self.peer # fall back to IP if no serial
unit_state = state.get(unit_key, {})
seen_keys: set[str] = set(unit_state.get("downloaded_keys", []))
# Highest event key ever downloaded from this unit (hex string, 8 chars).
# Used to detect post-erase key reuse — see comment block above.
# downloaded_events is the v2 (key_hex → timestamp_iso) dict.
# Empty-string timestamps are migrated v1 entries — they force a
# one-time re-download because the (key, timestamp) compare always
# mismatches against any non-empty timestamp from a fresh 0C read.
seen_events: dict[str, str] = dict(unit_state.get("downloaded_events", {}))
max_seen_key: str = unit_state.get("max_downloaded_key", "00000000")
if self.force_redownload:
log.info(" --force-redownload-all set — ignoring %d cached "
"(key, timestamp) entries for this session",
len(seen_events))
seen_events = {}
# Walk the event index (browse-mode, no 5A) to get the actual current
# key list. The SUB 08 event_count field is a lifetime "total events
# ever recorded" counter that does NOT decrement on erase — confirmed
@@ -290,11 +382,10 @@ class AchSession:
log.warning(" list_event_keys failed: %s -- falling back to full download", exc)
device_keys = None
# Use the walk result as our authoritative current count.
current_count = len(device_keys) if device_keys is not None else 0
log.info(" Unit has %d stored event(s); %d key(s) previously downloaded",
current_count, len(seen_keys))
log.info(" Unit has %d stored event(s); %d (key, ts) entr(ies) previously downloaded",
current_count, len(seen_events))
if device_keys is not None and current_count == 0:
log.info(" [OK] No events on device -- nothing to download")
@@ -302,75 +393,29 @@ class AchSession:
return
if device_keys is not None:
# ── Post-erase detection ──────────────────────────────────────
# After the device memory is erased, new events start from key
# 01110000 again — the same keys we already downloaded. Detect
# this by comparing the device's current highest key against the
# historical maximum. If the device has rolled back below our
# high-water mark, its counter was reset and we must treat all
# its keys as new, regardless of what seen_keys contains.
# ── Post-erase detection (best-effort, key-only signal) ───────
# After erase the device's key counter resets to 01110000.
# If the device's current max key is below our high-water mark
# we know erase happened. This catches the cleanest case but
# does NOT catch erase-then-record-many-events (where the new
# max may climb past the old max). The (key, timestamp) check
# in get_events() is what handles those.
if device_keys and max_seen_key != "00000000":
max_device_key = max(device_keys) # lexicographic; safe because
# keys share the same 4-char prefix
max_device_key = max(device_keys)
if max_device_key < max_seen_key:
log.info(
" Post-erase reset detected: "
"device max key %s < historical max %s "
"-- treating all device keys as new",
"-- discarding stale (key, ts) state for this session",
max_device_key, max_seen_key,
)
seen_keys = set() # discard stale dedup info for this session
seen_events = {}
new_key_set = set(device_keys) - seen_keys
log.info(" Device has %d key(s): %d new, %d already seen",
len(device_keys), len(new_key_set), len(device_keys) - len(new_key_set))
if not new_key_set:
log.info(" [OK] All events already downloaded -- nothing to do")
# Refresh state timestamp; preserve max_seen_key unchanged.
state[unit_key] = {
"downloaded_keys": sorted(seen_keys | set(device_keys)),
"max_downloaded_key": max_seen_key,
"last_seen": datetime.datetime.now().isoformat(),
"serial": serial,
"peer": self.peer,
}
_save_state(self.state_path, state)
# ── Erase even when no new events (if requested) ──────────
# Blastware ACH always erases after every session — even when
# nothing new was downloaded. Without the erase the device
# still sees stored events in its memory and immediately
# retries the call-home, causing the looping we observed.
# Only erase when device actually has events stored; skip
# the erase if device_keys is empty (nothing to erase).
if self.clear_after_download and device_keys:
log.info(
" Clearing device memory (--clear-after-download, "
"no new events but device has %d stored)...",
len(device_keys),
)
try:
client.delete_all_events()
log.info(" [OK] Device memory cleared")
# Reset state so the next session starts fresh.
state[unit_key] = {
"downloaded_keys": [],
"max_downloaded_key": "00000000",
"last_seen": datetime.datetime.now().isoformat(),
"serial": serial,
"peer": self.peer,
}
_save_state(self.state_path, state)
except Exception as exc:
log.error(
" [WARN] Event deletion failed: %s -- events NOT cleared",
exc,
)
log.info("Session complete (no new events) -> %s", session_dir)
return
else:
new_key_set = None # unknown; proceed with full download
# Note: no early-exit "all already downloaded" short-circuit
# here. Without per-event timestamps we cannot tell whether
# device_keys ⊆ seen_events.keys() actually means we have
# those physical events. get_events() will read 0C on its
# skip path and decide per event.
# Apply max_events cap
# stop_idx: when we know the count from list_event_keys, use it as
@@ -388,27 +433,67 @@ class AchSession:
)
try:
# Pass `seen_events` (key → ISO timestamp) so the client can
# read 0C on its skip path and only skip 5A when the per-event
# timestamp matches what we already have on disk. When force_-
# redownload is set, seen_events was already cleared above.
#
# Filter out empty-string timestamps (legacy v1 entries) — the
# client's 0C-on-skip-path only trusts entries with a
# populated timestamp; otherwise it falls through to a full
# 5A download.
skip_dict = {k: ts for k, ts in seen_events.items() if ts}
all_events = client.get_events(
full_waveform=True,
stop_after_index=stop_idx,
skip_waveform_for_keys=seen_keys if seen_keys else None,
skip_waveform_for_events=skip_dict if skip_dict else None,
)
# Filter to events whose keys we haven't saved before.
# New events are those that came back with _a5_frames populated
# (= 5A actually ran on this session). Skipped events have
# _a5_frames = None because the client matched (key, timestamp)
# against skip_dict and bypassed 5A.
new_events = [
e for e in all_events
if e._waveform_key is None
or e._waveform_key.hex() not in seen_keys
if getattr(e, "_a5_frames", None)
]
skipped = len(all_events) - len(new_events)
log.info(" [OK] Downloaded %d event(s): %d new, %d skipped (already seen)",
log.info(" [OK] Walked %d event(s): %d downloaded, %d skipped (matched (key, ts) in state)",
len(all_events), len(new_events), skipped)
if skipped:
log.info(" (skipped %d already-downloaded event(s))", skipped)
# ── Persist event file + A5 sidecar to the waveform store ──
# Saves ride alongside the existing JSON dump so the on-disk
# event file and events.json reference the same set of events.
waveform_records: dict[str, dict] = {}
for ev in new_events:
if not ev._a5_frames:
continue
try:
rec = self.store.save(
ev,
serial=serial or "UNKNOWN",
a5_frames=ev._a5_frames,
)
if ev._waveform_key is not None:
waveform_records[ev._waveform_key.hex()] = rec
log.info(
" [WAVE] saved %s (%d bytes)",
rec["filename"], rec["filesize"],
)
except Exception as exc:
key_hex = ev._waveform_key.hex() if ev._waveform_key else "????????"
log.warning(
" [WARN] Waveform store save failed for %s: %s",
key_hex, exc,
)
if new_events:
_save_json(session_dir / "events.json", [_event_to_dict(e) for e in new_events])
_save_json(
session_dir / "events.json",
[_event_to_dict(e, waveform_records) for e in new_events],
)
for ev in new_events:
pv = ev.peak_values
@@ -467,7 +552,11 @@ class AchSession:
_session_start = datetime.datetime.now()
try:
_ev_ins, _ev_skip = self.db.insert_events(
new_events, serial=serial or self.peer, session_id=None
new_events,
serial=serial or self.peer,
session_id=None,
waveform_records=waveform_records,
device_family="series3",
)
_ml_ins, _ml_skip = self.db.insert_monitor_log(
new_monitor_entries, session_id=None
@@ -502,35 +591,64 @@ class AchSession:
)
# ── Update persistent state ───────────────────────────────────
# Include both triggered-event keys and monitor-log keys in the
# downloaded set so they are not re-processed on the next call-home.
current_event_keys = [
e._waveform_key.hex()
for e in all_events
if e._waveform_key is not None
]
current_monitor_keys = [e.key for e in new_monitor_entries]
current_keys = current_event_keys + current_monitor_keys
# Build a fresh (key → ISO timestamp) map from THIS session's
# results. For each event currently on the device, prefer the
# timestamp we just observed (from 0C); fall back to whatever
# was already in seen_events for that key (so we don't lose an
# entry just because get_events skipped it on the (key, ts)
# match path).
def _ts_iso(ev) -> str:
ts = getattr(ev, "timestamp", None)
if ts is None:
return ""
try:
return datetime.datetime(
ts.year, ts.month, ts.day,
ts.hour or 0, ts.minute or 0, ts.second or 0,
).isoformat()
except Exception:
return str(ts)
current_events_map: dict[str, str] = {}
for ev in all_events:
if ev._waveform_key is None:
continue
key_hex = ev._waveform_key.hex()
ts_iso = _ts_iso(ev) or seen_events.get(key_hex, "")
current_events_map[key_hex] = ts_iso
# Monitor-log entries don't have a 0C-style timestamp, but
# they DO have a start_time; use that so the monitor-log keys
# are properly entered into the (key, ts) map.
for ml in new_monitor_entries:
key_hex = ml.key
ts = ml.start_time
ts_iso = ts.isoformat() if ts else seen_events.get(key_hex, "")
# If a triggered event already populated this key, keep
# whichever has a non-empty timestamp.
if key_hex not in current_events_map or not current_events_map[key_hex]:
current_events_map[key_hex] = ts_iso
if erased_successfully:
# Device memory is clear. Reset downloaded_keys and the
# high-water mark so the next call-home starts fresh and
# doesn't mis-identify the recycled key 01110000 as "seen".
updated_keys = []
updated_events: dict[str, str] = {}
new_max_key = "00000000"
log.info(
" State reset after erase -- next session will download "
"from key 0 (device counter resets after erase)"
)
else:
# Normal (no erase): union of previously-seen + all keys on
# device now. Includes already-seen survivors so we never
# re-download them if the device somehow keeps old records.
updated_keys = sorted(set(seen_keys) | set(current_keys))
new_max_key = updated_keys[-1] if updated_keys else max_seen_key
# Merge: keep prior (key, ts) entries we still have evidence
# of (for survivors of any partial failure), plus this
# session's authoritative (key, ts) pairs.
updated_events = dict(seen_events)
updated_events.update(current_events_map)
new_max_key = (
max(updated_events.keys())
if updated_events else max_seen_key
)
state[unit_key] = {
"downloaded_keys": updated_keys,
"downloaded_events": updated_events,
"max_downloaded_key": new_max_key,
"last_seen": datetime.datetime.now().isoformat(),
"serial": serial,
@@ -592,7 +710,10 @@ def _device_info_to_dict(d: DeviceInfo) -> dict:
}
def _event_to_dict(e: Event) -> dict:
def _event_to_dict(
e: Event,
waveform_records: Optional[dict[str, dict]] = None,
) -> dict:
pv = e.peak_values
pi = e.project_info
peaks = {}
@@ -611,6 +732,11 @@ def _event_to_dict(e: Event) -> dict:
for ch, vals in e.raw_samples.items()
}
samples["__note__"] = "first 20 sample-sets only; see raw_rx.bin for full waveform"
rec: dict = {}
if waveform_records and e._waveform_key is not None:
rec = waveform_records.get(e._waveform_key.hex(), {}) or {}
return {
"timestamp": str(e.timestamp) if e.timestamp else None,
"project": pi.project if pi else None,
@@ -619,6 +745,9 @@ def _event_to_dict(e: Event) -> dict:
"sensor_location": pi.sensor_location if pi else None,
"peaks": peaks,
"raw_samples_preview": samples,
"blastware_filename": rec.get("filename"),
"blastware_filesize": rec.get("filesize"),
"a5_pickle_filename": rec.get("a5_pickle_filename"),
}
@@ -640,6 +769,7 @@ def serve(args: argparse.Namespace) -> None:
output_dir.mkdir(parents=True, exist_ok=True)
state_path = output_dir / "ach_state.json"
db = SeismoDb(output_dir / "seismo_relay.db")
store = WaveformStore(output_dir / "waveforms")
server_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
server_sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
@@ -657,6 +787,14 @@ 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:")
print(f" Remote Host: <this machine's LAN IP>")
@@ -694,8 +832,12 @@ def serve(args: argparse.Namespace) -> None:
max_events=max_ev,
state_path=state_path,
db=db,
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}")
t.start()
@@ -769,6 +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",
@@ -780,6 +948,17 @@ def parse_args() -> argparse.Namespace:
"This mirrors the standard Blastware ACH workflow."
),
)
p.add_argument(
"--force-redownload-all",
action="store_true",
default=False,
help=(
"Manual override: ignore ach_state.json's downloaded_events map "
"for this session and re-download every event currently on the "
"device, regardless of (key, timestamp) match. Useful when state "
"has become inconsistent with the on-disk waveform store / DB."
),
)
p.add_argument(
"--verbose", "-v",
action="store_true",
docs/histogram_codec_re_status.md
+212
View File
@@ -0,0 +1,212 @@
> ## SUPERSEDED 2026-08-25 — the block is uniformly BIG-ENDIAN
>
> The `uint8` peak / `annotation` byte model described below is wrong,
> though it decoded quiet data correctly. The real layout:
>
> - **Every per-channel field is `uint16` big-endian.** `T_peak` is
> `[5:7]`, `T_halfperiod` `[7:9]`, `V_peak` `[9:11]`, and so on.
> Only `block_ctr` at `[2:4]` is little-endian.
> - The **marker is `block[4]` alone**, not a `uint16 LE` at `[4:6]`.
> Testing `[4:6] == 10` forced `block[5] == 0`, which is exactly what
> capped every geo peak at one byte (255 counts = 1.275 in/s).
> - The **"annotation" byte was never an annotation** — it is the high
> byte of the big-endian half-period. That is why it was non-zero
> precisely on the sub-Hz intervals Blastware renders as `<1.0`.
> - The **final block of the stream carries tail `9c 06 00 42`** instead
> of `1e 0a 00 00`, and arbitrary bytes at `[21:23]`. Rejecting it
> dropped the last interval of nearly every histogram — often the one
> holding the event peak, so the file's PPV read low.
>
> Verified against 1211 production histograms paired with their Blastware
> ASCII exports: **1211/1211 decode exactly** (interval count plus every
> per-interval peak), and 842,442 per-interval frequency comparisons match
> with zero mismatches. The uint8 model scored 1204/1211 — the seven
> failures are exactly the files containing a peak above 1.275 in/s.
>
> The section below is retained as the reasoning trail.
# Histogram body codec — FULLY DECODED (2026-05-20)
Clean working status doc for the MiniMate Plus histogram-mode event
body codec. Companion to `waveform_codec_re_status.md`. The deep
historical record (with retractions and dated analyses) lives in
`docs/instantel_protocol_reference.md §7.6.2`; the authoritative
implementation lives in `minimateplus/histogram_codec.py`.
## TL;DR
**The codec is fully decoded.** Every field of every block in the
in-repo histogram fixture corpus decodes byte-exact against BW's
ASCII export.
26 regression tests pass against ~3,500 blocks across 5 in-repo
fixtures, plus a synthetic regression block taken from a real
BE9558 prod event to lock in the uint8-peak interpretation.
**Important correction (2026-05-21):** the per-channel peak count
is `uint8` at byte[6]/[10]/[14]/[18], NOT `uint16 LE` at byte[6:8]
etc. The N844 fixture corpus the original RE was done against has
zero values in bytes [7]/[11]/[15]/[19] for every block, so the
two interpretations happened to be equivalent. Cross-correlating
non-N844 events (BE9558 Tran-drift, BE18003 Histogram+Continuous)
against BW's per-interval ASCII export — 4 channels × ~1400 blocks
per event × multiple events = 100% byte-exact only when the peak
is read as uint8. Reading as uint16 LE produced peaks up to 268
in/s per channel and 35× inflated PVS sums when first deployed to
prod (rolled back, root-caused, and fixed in commit 7183b95+1).
## Body format
```
body = [stream of 32-byte data blocks] + [small trailing remnant]
```
Each block represents one histogram interval. Block layout:
```
[0] 0x00 always-zero tag
[1] segment_id (uint8) 0x00..0x03 — 256 blocks per segment
[2:4] block_ctr (uint16 LE) resets each segment (0x0100, 0x0101, …)
[4:6] 0x000a (uint16 LE) constant marker (= 10)
[6] T_peak_count uint8 Tran peak (count × 0.005 → in/s at Normal,
max 1.275 in/s — fits in uint8)
[7] T_annotation uint8 empirically non-zero on intervals with sub-Hz
or unmeasurable freq; meaning not fully RE'd
[8:10] T_halfperiod uint16 LE Tran half-period in samples
(freq_Hz = 512 / halfp; ≤ 5 means ">100 Hz")
[10] V_peak_count uint8 Vert peak
[11] V_annotation uint8
[12:14] V_halfperiod uint16 LE Vert freq half-period
[14] L_peak_count uint8 Long peak
[15] L_annotation uint8
[16:18] L_halfperiod uint16 LE Long freq half-period
[18] M_peak_count uint8 MicL peak count
(dB via waveform_codec.mic_count_to_db)
[19] M_annotation uint8
[20:22] M_halfperiod uint16 LE MicL freq half-period
[22:24] 0x00 0x00 constant
[24:28] 4-byte variable purpose unknown — possibly CRC,
timestamp delta, or psi(L) numeric;
not needed for waveform reconstruction
[28:32] 0x1e 0x0a 0x00 0x00 constant block-end signature
```
Reliable block-identification anchor:
```python
block[22:24] == b"\x00\x00" and block[28:32] == b"\x1e\x0a\x00\x00"
```
(The `1e 0a 00 00` constant tail is the most distinctive signature.)
## Per-channel encoding
| Channel | Peak encoding | Frequency encoding |
|---|---|---|
| Tran | count × 0.005 = in/s at Normal range | `freq_Hz = 512 / halfperiod` |
| Vert | same | same |
| Long | same | same |
| MicL | count → dB via `mic_count_to_db(count)` (same formula as waveform codec) | same |
**`>100 Hz` sentinel**: when halfperiod ≤ 5 (giving ≥100 Hz from the
512/halfp formula), BW displays `>100 Hz`. Codec's `half_period_to_hz`
returns `None` in this range.
## Verified facts (cross-checked against fixture corpus)
Example: N844L6Z8.ZR0H block 130 → all 8 decoded fields byte-exact:
```
binary samples [10, 6, 24, 4, 18, 5, 21, 5, 9]
TXT row [0.030, 21, 0.020, 28, 0.025, 24, 0.040, 0.000, 95.92, 57]
slot[0] = 10 marker
slot[1] = 6 × 0.005 = 0.030 in/s ✓ T_peak
slot[2] = 24 → 512/24 = 21.3 → 21 Hz ✓ T_freq
slot[3] = 4 × 0.005 = 0.020 in/s ✓ V_peak
slot[4] = 18 → 512/18 = 28.4 → 28 Hz ✓ V_freq
slot[5] = 5 × 0.005 = 0.025 in/s ✓ L_peak
slot[6] = 21 → 512/21 = 24.4 → 24 Hz ✓ L_freq
slot[7] = 5 → 81.94 + 20·log10(5) = 95.92 dB ✓ M_peak
slot[8] = 9 → 512/9 = 56.9 → 57 Hz ✓ M_freq
```
## Verified test coverage
`tests/test_histogram_codec.py` (24 tests):
- Block walking: yields one record per `.TXT` interval ± 1 (off-by-one
at the tail when recording was stopped mid-write). Segment-ID
groups of 256 blocks confirmed.
- Geo peaks: every block of N844L20G, N844L6Z8, N844L6XE, N844L23B
matches `.TXT` within the 0.0005 in/s quantization step.
- Geo freqs: every block of N844L6Z8 and N844L6XE matches `.TXT`
within 1 Hz (BW display rounds). `>100 Hz` sentinel handled correctly.
- Mic dB: every block of N844L6XE, N844L23B, N844L6Z8 matches `.TXT`
within 0.1 dB (BW display precision).
- Mic freq: matches `.TXT` within 1 Hz across active blocks.
## What's NOT yet decoded
- **Annotation bytes (`block[7]/[11]/[15]/[19]`)**. Empirically
non-zero on intervals where the per-channel ZC frequency comes
out as `N/A` or sub-Hz (`<1.0`, `1.X`). Hypothesis tested in the
RE session: byte != 0 ↔ sub-Hz freq. Only ~50% correlation
across the K558 corpus, so the relationship is more complex.
Possibilities: time-of-peak-within-interval, halfp extension for
very-long-period signals, or a debug/diagnostic field the firmware
writes opportunistically. Doesn't affect peak amplitudes or
waveform reconstruction. Captured as `record["annotations"]` for
future RE.
- **4-byte variable metadata field (bytes 24:28)**. Not needed for
waveform reconstruction. Speculation: per-block CRC, sub-second
timestamp offset, or a Mic psi(L) count not in the 9 samples.
Punt until something needs it.
- **Geo PVS (TXT col 7, e.g. "0.040 in/s")**. Not stored in the
block; can be approximated as `sqrt(T_peak² + V_peak² + L_peak²)`
but BW's value sometimes differs slightly (probably computed from
waveform-instant samples, not from per-channel peaks). Punt — the
`.h5` consumers don't need PVS as a sample channel.
- **Mic psi(L) value (TXT col 8)**. TXT shows it as a small psi value
derived from the dB measurement. Not in the 9 samples. Could be
derived from `M_peak_count` via the inverse of the dB formula plus
a psi calibration constant. Defer.
## Output shape
`decode_histogram_body` returns the standard 4-channel dict that
mirrors `waveform_codec.decode_waveform_v2`'s output:
```python
{
"Tran": [peak_count_per_interval, ...], # 16-count units (LSB = 0.005 in/s)
"Vert": [..., ...],
"Long": [..., ...],
"MicL": [..., ...], # raw ADC counts
}
```
Run through `waveform_codec.decoded_to_adc_counts` to get 1-count ADC
units (geo ×16, mic passthrough) for the standard `.h5` writer.
For the full per-interval record with frequencies + metadata, use
`decode_histogram_body_full()`.
## Where it's wired
- `minimateplus/event_file_io.py:read_blastware_file()` — first tries
the waveform codec, falls back to the histogram codec when the
waveform preamble isn't present. Same output shape, same
downstream pipeline.
- `scripts/backfill_sidecars.py` — the `has_samples` short-circuit
added during the histogram-codec-pending era still serves as a
defensive guard against truly undecodable files, but no longer
fires for valid histograms.
## Companion reference
- `docs/waveform_codec_re_status.md` — sibling status doc for the
much-more-complex waveform-mode codec.
- `docs/instantel_protocol_reference.md §7.6.2` — historical
protocol-reference entry. Structural framing matches what we
found; per-sample semantics were less documented than the `✅
CONFIRMED` badge suggested. This doc supersedes §7.6.2 where they
conflict on confidence level.
docs/idf_protocol_reference.md
+563
View File
@@ -0,0 +1,563 @@
# IDF Protocol Reference — Thor / Micromate Series IV
Starting-point reference for reverse-engineering Instantel's Micromate
Series IV event-file format. Sibling to
[instantel_protocol_reference.md](instantel_protocol_reference.md) (the
Series III "Rosetta Stone") — this doc holds what we know so far and
the open questions still to crack.
> ⚠ **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,
timestamp, sample_rate, record_time, calibration_date) extracted from
the binary header. Sample fidelity is 87–99% byte-exact on quiet
events; loud events hit the BW codec's known walker-stops-early
limitation. Residual ~3% drift on per-sample deltas (likely a
Thor-specific 12-bit delta refinement not yet modelled).
**Thor IDFH histograms also decoded.** Body has one or more segments;
each 12-byte segment header `[length_be 2B][0a 00 00 00][00 NN][05 3f]`
introduces `N = (length - 10) // 72` interval records of 72 bytes
each. Each interval = 4 × 16-byte per-channel records:
`[int16 min][int16 max][int16 ??][uint16 halfp][2B 00][uint16 ??][2B 00][uint16 ??]`.
Geo peak `= max(|min|, |max|) / 32768 × 10` in/s (matches sidecar
~1.8%); freq `= 512 / halfp` Hz (None for halfp ≤ 5 → ">100"
sentinel). Corpus: **all 859 Thor IDFH files decode, 181,071
intervals**. Wired through `read_idf_file()` →
`save_imported_idf()` → sidecar's `extensions.idf_intervals`.
**Note on the BE9439 outliers in the example corpus:** Two files
(`BE9439_20200713131747.IDFW` and `BE9439_20200713124251.IDFH`) are
**Series III Blastware** binaries, not Thor. Provenance: TMI tried
to use Thor to manage auto-call-homes for Series III units; the
experiment didn't work out, but it did leave a few BW event files
in Thor's per-serial directory structure with `.IDFW`/`.IDFH`
extensions — Thor's forwarder applied its own naming convention to
the BW bodies it was relaying. Their header `10 00 01 80 00 00
Instantel STRT ff fe <end_key> <start_key>` is the BW SUB 5A STRT
record, not a Thor body preamble. The reader detects them by
signature and raises `NotImplementedError` pointing callers at
`read_blastware_file()`, which extracts BW-format peaks from them.
**Still NYI for Thor IDFH:** per-channel `int16 field4` (possibly
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
files. Preceded by a 4-byte record-type marker (`46 00 00 00`)
+ magic preamble `00 02 00 [Tran[0] BE] [Tran[1] BE]`.
- **Sample stream is BW's segment-rotated block codec verbatim.**
Thor reuses `10 NN` (nibble), `20 NN` (int8), `00 NN` (RLE),
`30 NN` (packed12), `40 02` (segment header) tags with the same
semantics. Channel rotation Tran→Vert→Long→MicL.
- **Geo LSB = 0.0003 in/s** (not BW's 0.005), because Thor's 16-bit
ADC range maps to 10 in/s without the 16-count BW quantization step.
- **Mic ≈ 2.14×10⁻⁶ psi/count** (rough scale; refine after channel
block calibration constants are decoded).
- **BW compliance anchor `\xbe\x80\x00\x00\x00\x00` reappears at
IDFW offset 0x952** — sample_rate at anchor−6 (uint16 BE),
record_time at anchor+6 (float32 BE), same layout as BW.
- **Event timestamp at offset 0x97A** — 8 bytes `[day][month]
[year_be][unk][hour][min][sec]`. Stop-time mirrors at 0x982.
- **Serial as null-terminated ASCII at 0x14E**.
- **Calibration date** at 0x194–0x197 (day, month, year_be).
- Per-sample residual drift of ~3% suggests Thor encodes int8/nibble
deltas with an extra refinement bit that BW doesn't carry —
unsolved; errors resync within a few samples so cumulative impact
is small.
---
## File model
### Filename convention
```
<SERIAL>_<YYYYMMDDHHMMSS>.<KIND>
```
- **SERIAL** — literal device serial, two-letter prefix + numeric
suffix. Examples seen: `UM11719`, `UM13981`, `UM20147`, `BE9439`.
Unlike Series III BW filenames (`M529LK44.AB0`, base-36 stem),
Series IV filenames carry the serial in plain text.
- **YYYYMMDDHHMMSS** — 14-char ASCII timestamp in **device local
time** (no timezone marker).
- **KIND** — `IDFH` for histograms, `IDFW` for waveforms.
The `.IDFH.txt` / `.IDFW.txt` ASCII sidecar lives in a `TXT/`
**subfolder** of the unit's directory, not alongside the binary.
This pairing convention is encoded in
`event_forwarder.idf_report_path()`.
### Directory layout
```
C:\THORDATA\
└── <Project>\
└── <UM####>\ ← unit serial dir
├── UM12345_20260520100000.MLG ← monitor log (not events)
├── UM12345_20260520100000.IDFH ← histogram event (binary)
├── UM12345_20260520100000.IDFW ← waveform event (binary)
├── UM12345_20260520100000.IDFW.CDB ← cache-DB variant (skip)
├── TXT\
│ ├── UM12345_20260520100000.IDFH.txt ← histogram ASCII sidecar
│ └── UM12345_20260520100000.IDFW.txt ← waveform ASCII sidecar
├── CSV\, HTML\, PDF\, XML\ ← operator-facing derived exports
└── ...
```
The `.IDFW.CDB` files share the binary's basename but appear to be a
separate cache/database variant. Their first 8 bytes match the
**old**-firmware Thor signature (see below) regardless of which
signature the paired `.IDFW` uses. Purpose unknown; sizes vary
wildly (observed 123 B → 40,491 B). Thor-watcher's forwarder
deliberately skips them.
### Sample corpus
The `thor-watcher/example-data/THORDATA_example/` tree carries
**1,014 paired .IDFW / .IDFH + .txt files** spanning 2020–2023
across nine units (UM11719, UM13981, UM20147, …, plus BE9439 from
2020). This is the reverse-engineering ground truth.
---
## ASCII sidecar (`.IDFW.txt` / `.IDFH.txt`) — fully decoded
Shape: plain text, one `"Key : Value"` line per metadata field,
followed for waveforms by a tab-separated sample table headed by
the literal line `Waveform Data Channels`. Parsed by
[`micromate/idf_ascii_report.py`](../micromate/idf_ascii_report.py).
See [`micromate/models.py`](../micromate/models.py) for the typed
`IdfReport` shape.
### Notable conventions
- **Units are native to Thor** — geophone in **in/s**, microphone in
**dB(L)** (not psi like Series III BW reports), frequency in Hz,
acceleration in g, displacement in in.
- **Below-threshold readings** appear as the literal string
`<0.005 in/s` (155 occurrences in the sample corpus) — the parser
strips the `<` and treats the numeric remainder as the value.
- **Out-of-range / not-measured** values appear as `N/A` — parser
drops the field rather than letting the string leak into a numeric
column.
- **Firmware string** observed: `Micromate ISEE 11.0AK`.
- **TitleString1..4** are operator-defined free-text slots; Thor's
default labels map them to Location / Client / Company / Notes,
which the parser surfaces as `project` / `client` / `operator` /
`notes`.
- **Histogram sidecars** use `HistogramStartDate` / `HistogramStartTime`
in place of waveform's `EventDate` / `EventTime`. Parser falls
through to either.
- **Histogram tabular block** lacks the `Waveform Data Channels`
marker; instead it's a multi-line column header followed by
per-interval rows (`<date> <time> <tran-ppv> <freq> ...`). Parser
silently ignores lines after the metadata block since they lack a
colon-separated `key : value` shape (the timestamps DO contain
colons but produce garbage keys that don't collide with any
recognised field).
---
## Binary header signatures (observed)
Hex dump of the first 32 bytes across 1,014 sample files reveals
**two distinct file signatures**, both anchored by the literal
ASCII string `"\x00Instantel\x00"` at offset 6–16:
### Signature A — newer firmware (1,012 files, 99.8% of corpus)
```
00000000: 0012 0100 0000 496e 7374 616e 7465 6c00 ......Instantel.
00000010: 0000 a695 002e b500 4f70 6572 6174 6f72 ........Operator
^^^^^^^^^^^^^^^^
operator/title string starts at 0x18
```
Header bytes 0–5: `00 12 01 00 00 00`. Followed immediately by the
8-byte ASCII tag, then 6 unknown bytes, then ASCII operator-supplied
strings (Operator name, etc.) and on through the project / client /
title strings. No `STRT` record observed in this layout.
### Signature B — older firmware (2 files: BE9439 from 2020)
```
00000000: 1000 0180 0000 496e 7374 616e 7465 6c00 ......Instantel.
00000010: 072c 0012 0300 5354 5254 fffe 0111 2340 .,....STRT....#@
^^^^^^^^^ ^^^^^^^^^
STRT magic 4-byte end_key
00000020: 0111 0000 2e5f 00ac 4600 0000 0200 0000 ....._..F.......
^^^^^^^^^ ^^^
4-byte start_key 0x46 (BW WAVEHDR record-type marker)
```
Header bytes 0–5: `10 00 01 80 00 00`. The structure after the
`Instantel` magic is **byte-for-byte identical to a BW SUB 5A
probe-response STRT record** as documented in
[instantel_protocol_reference.md → "SUB 5A — STRT record encodes
end_offset"](instantel_protocol_reference.md). Specifically:
| Offset | Bytes | Meaning (per BW reference) |
|--------|---------------------|--------------------------------------|
| 0x14 | `53 54 52 54` | `STRT` magic |
| 0x18 | `ff fe` | STRT sentinel |
| 0x1A | `01 11 23 40` | `end_key` (4 bytes) |
| 0x1E | `01 11 00 00` | `start_key` (4 bytes) |
| 0x26 | `46` | `0x46` waveform-record type marker |
**Hypothesis:** Older Micromate firmware writes a wrapped BW-format
event into the `.IDFW` file — essentially the same on-disk shape as
a Series III device, with the new filename convention applied at
export time. Newer firmware (signature A) abandoned the
BW-compatible layout for an Instantel-specific format.
If that hypothesis holds, the 2 signature-B files can already be
parsed via `minimateplus/event_file_io.read_blastware_file()` — worth
testing. The 1,012 signature-A files are the real reverse-engineering
target.
### `.IDFW.CDB` cache files
Always carry signature B (`10 00 01 80 ...`), even when the paired
`.IDFW` carries signature A. Plausible explanation: the CDB is an
internal Thor cache-database export that retains the legacy BW-style
record layout regardless of the user-facing `.IDFW` format version.
Not currently consumed by the forwarder.
---
## File-size patterns (Signature A, the main target)
Survey of 1,012 signature-A files:
| Event type | Typical size | Source of variance |
|--------------|-------------------|----------------------------------------------|
| `.IDFW` 2-sec | 9,200 – 10,500 B | Operator-supplied strings (TitleString1..4) of varying length |
| `.IDFH` | 2,944 – 4,076 B | Histogram interval count (record duration / interval) |
**Naive arithmetic for 2-sec waveform:**
- 4 channels × 2 sec × 1024 sps = 8,192 samples
- At 2 bytes/sample (int16) = 16,384 sample bytes → file would be > 16 KB
- Observed: ~9–10 KB
- → samples are likely **1 byte each** (int8 quantised), **or** stored
with bit-packing / delta encoding, **or** only one channel's
full-rate samples are stored with the others reconstructed
arithmetically. Verifying this is the **first RE milestone**.
Project-string–length variance (~1 KB across the corpus) is consistent
with the file carrying a single copy of each TitleString1..4 plus
operator + setup-name as null-padded ASCII regions.
---
## Open questions
The reverse-engineering targets, roughly in dependency order:
1. **Sample encoding (signature A)** — int8? int16 LE/BE? Bit-packed?
Delta-coded? Per-channel interleaved or sequential blocks?
2. **Header field layout (signature A)** — where do sample_rate,
record_time, channel count, and per-channel peaks live in the
binary? The ASCII sidecar gives the device-authoritative values,
so binary fields can be confirmed by diff.
3. **Operator-string offsets** — `Operator` at 0x18 is the first
visible string in signature-A files; the rest (project, client,
notes, setup) follow. Need to map exact offsets and null-padding
conventions.
4. **Signature-B → BW codec compatibility** — does
`minimateplus/event_file_io.read_blastware_file()` actually parse
the 2 BE9439 signature-B files as-is? If yes, the OLD-format
ingest is free.
5. **`.IDFW.CDB` purpose** — is it an internal Thor cache, a
ring-buffer dump, or something else? Worth a single small effort
to characterise so we know what we're skipping.
6. **Footer / checksum** — every BW event file has a footer; does
IDF? Where does the per-channel sample block end?
---
## Reverse-engineering playbook (when we start)
The Series III BW codec took ~2 months of MITM wire captures
because we didn't have ground-truth metadata. Thor's situation is
**substantially better**:
- **Ground truth is on disk.** Every binary in `example-data/`
has a paired `.IDFW.txt` carrying the full decoded sample table
(`Waveform Data Channels` block — see any sample file in
`thor-watcher/example-data/.../TXT/`). Aligning binary bytes
to the table's float-per-row values gives an immediate per-byte
hypothesis test.
- **Cross-event diffing.** 1,012 signature-A samples from 9 units
spanning 4 years means any field that varies between events is
immediately localisable. Fields that are constant across all
files (firmware ID, channel labels, format-version word) are also
immediately localisable by complementary search.
- **No protocol surface.** Files at rest, not a wire dialect. No
DLE stuffing, no inner-frame parsing, no probe/data two-step.
Suggested first session (2-4 hours): hand-decode `UM11719_20231219162723.IDFW`
(10,290 bytes) against its `TXT/UM11719_20231219162723.IDFW.txt`
sample table (the 2-sec waveform at 1024 sps × 4 channels = 8,192
sample rows). Find the first per-channel sample value (`0.0003` in
the Tran column at t=0) in the binary. Confirms sample encoding.
Everything else flows from there.
---
## Code seams ready to receive the codec
When the codec lands, it goes into
[`micromate/idf_file.py`](../micromate/idf_file.py) (currently a
stub raising `NotImplementedError`). Public API:
```python
from micromate import IdfEvent
from micromate.idf_file import read_idf_file
event: IdfEvent = read_idf_file(Path("UM11719_20231219163444.IDFW"))
# event.peaks.transverse_ips, event.timestamp, event.raw_samples, ...
```
The ingest pipeline (`WaveformStore.save_imported_idf`) currently
builds the `IdfEvent` from the `.txt` parser only. Once
`read_idf_file()` works, the binary becomes authoritative; the
`.txt` parser drops to fast-path metadata cross-check. Operators
who don't enable Thor's TXT exporter still get fully populated
events.
---
## See also
- [instantel_protocol_reference.md](instantel_protocol_reference.md) — Series III BW protocol reference (the Rosetta Stone). STRT record format, DLE framing, BW filename encoding.
- [`micromate/idf_ascii_report.py`](../micromate/idf_ascii_report.py) — `.txt` sidecar parser.
- [`micromate/models.py`](../micromate/models.py) — `IdfEvent`, `IdfReport` typed dataclasses.
- [`micromate/idf_file.py`](../micromate/idf_file.py) — placeholder for the binary codec.
- [`thor-watcher/example-data/THORDATA_example/`](../../thor-watcher/example-data/) — 1,014 paired binary + .txt files for codec validation.
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# 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>
docs/runbooks/wedged_unit_recovery.md
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# Runbook — Recovering a wedged unit stuck in a call-home loop
**Incidents:** BE9558H at `166.246.130.1:9034`, 2026-05-17 (Method B) ·
BE12599 at `166.246.64.226:9034`, 2026-09-16 (Method A).
A field unit with a stuck-triggered geophone (or any hardware fault causing
constant event triggering) will record events back-to-back, and if Auto Call
Home is set to "After Event Recorded" the device will dial the office BW
ACH server in a tight loop. Combined with a Sierra Wireless modem in
bidirectional serial-TCP mode, this makes the unit effectively unreachable
from SFM — every TCP connection we open gets killed when the modem flips
from server-mode to client-mode to honor the device's next AT dial command.
This runbook describes how to break the loop and recover control.
---
## ⚠ Two cures for one disease — intercept first
Both incidents below are the **same failure**: a geophone offset crosses the
trigger level, the unit records back-to-back, ACH set to "after event
recorded" dials continuously, and the unit becomes unreachable because its
modem is in client mode almost all of the time.
There are two ways to get a Stop Monitoring command into it.
| | **A — intercept the call** (preferred) | **B — catch it between calls** (original) |
|---|---|---|
| Idea | Be the server it dials. Point the modem's Destination at our own ACH server and answer it. | Clear the Destination so it stops dialing, then race a Stop into the gap. |
| Needs inbound? | **No — the unit calls us** | Yes: working inbound TCP to the modem |
| Determinism | Deterministic — it dials every ~75 s, we only have to be listening | A race. BE9558H took ~7 h of attempts before one landed. |
| Tool | `bridges/ach_server.py --stop-monitoring` | `scripts/slow_drip.sh` |
| Proven on | BE12599, 2026-09-16 | BE9558H, 2026-05-17 |
**Method A is the standard procedure now.** The unit won't answer us because
it is on the phone — so stop dialing it and be the one it calls. It rings,
we pick up, take its data, and tell it to stop calling here.
Method B is kept because it is proven, and because A needs a listener the
modem can actually reach (public IP + forwarded port). When you have that,
don't race it — intercept it.
---
## Symptoms
- Terra-View / SFM `/device/info` either hangs or fails on `count_events()`.
- `/device/monitor/status` and `/device/rescue` return 502 (protocol timeout
waiting for POLL response) or 503 (TCP connect refused).
- ACEmanager serial log shows repeating
`Connect to IP: <BW_IP> Port: <BW_PORT>` → `Shutdown TCP socket` cycles
every 30-60 seconds.
- Spam-mode endpoints (`/device/stop_monitoring_spam`) report many
`sent_ok` but the device's monitoring state never changes.
- `slow_drip` reports `[Errno 32] Broken pipe` after sending the preamble
but before completing the drip loop.
If you see *all* of these, the unit is in this exact failure mode.
---
## Method A (preferred) — intercept the call
You need **ACEmanager access** and a host the modem can dial: public IP with
the listener's port forwarded to it.
### A1 — start the listener BEFORE touching the modem
```bash
cd /home/serversdown/seismo-relay
tmux new -s rescue
.venv/bin/python -u bridges/ach_server.py --port 12345 \
-o bridges/captures/<unit>-diag --stop-monitoring -v
```
⚠ **Listener first, always.** A Destination pointed at a dead port is the
worst state available — the device still dials, the modem still flips to
client mode, inbound stays blocked, and nothing gets delivered.
Do **not** add `--events-only` (it silently breaks dedup — see gotchas), and
do **not** add `--disable-ach` yet (see A4).
### A2 — point the modem at it
ACEmanager → **Serial → Port Configuration**:
| Field | Set to |
|---|---|
| **Destination Address** | the listener's public IP |
| **Destination Port** | the listener's port (e.g. `12345`) |
Apply. The modem auto-dials its Destination whenever serial data arrives
while the serial port is closed — so the unit's own retry cycle now lands on
you instead of nowhere.
### A3 — answer, and stop the bleeding
Within ~75 s you should see a call-in. `--stop-monitoring` fires SUB 0x97 at
step 1.5 — after the handshake, **before** the event walk — so the recording
halts at the earliest possible moment in the session. Confirm via
`rescue.json` in the session directory:
```json
{"peer": "166.246.64.226:60921", "stop_monitoring": "ok"}
```
That is the bleeding stopped. Everything after this is cleanup.
### A4 — drain the backlog, THEN disable ACH
⚠ **Order matters, and it is counter-intuitive.** Stopping monitoring also
removes your call-in trigger: ACH fires on "after event recorded", so with
recording stopped the unit has no reason to dial again. The backlog sitting
in its memory does **not** re-arm it.
So if the stored events are worth keeping — and on a fault unit they usually
are, they're the evidence — drain them across however many call-ins it takes
*before* you silence it. Only then add `--disable-ach` (or use
`scripts/rescue_device.sh <host> <port> --no-erase`).
If the unit has gone quiet and you still need it, cycling the modem produces
a call-in, and a unit with a scheduled daily call will dial at its configured
time regardless.
### A5 — restore the Destination, and confirm you did
Put `Destination Address` back to `0.0.0.0` (or the office Instantel ACH
server) once you are finished, and only stop the listener after that is done.
### A6 — do NOT re-enable ACH until the hardware fault is repaired
Otherwise the loop restarts the moment monitoring resumes and you run this
runbook again.
---
## Method B (fallback) — catch it between calls
The original 2026-05 procedure. Use when you cannot stand up a listener the
modem can reach. You need **ACEmanager access** to the unit's modem.
### Step 1: stop the modem's mode-flipping
In ACEmanager → **Serial → Port Configuration**:
| Field | Set to |
|---|---|
| **Destination Address** | clear (blank) |
| **Destination Port** | `0` |
Click **Apply**. This removes the modem's auto-dial-out target. The device's
AT dial commands now error back at the modem instead of triggering a
mode-flip, so the modem stays in TCP-server mode permanently and our inbound
TCP sessions stay alive.
*(Optional belt-and-suspenders: also add the BW server's port to
**Security → Port Filtering - Outbound** as a blocked port, with
Outbound Port Filtering Mode = Blocked Ports.)*
### Step 2: stop monitoring on the device (slow drip)
From the SFM host:
```bash
/home/serversdown/seismo-relay/scripts/slow_drip.sh <DEVICE_IP> <PORT>
```
Defaults are 120s duration with a drip every 3s. Watch the response:
- `duration_s ≈ 120` and `drips_sent ≈ 40` → session held the full duration ✓
- `bytes_received > 0` → device is responding ✓ (this is the success signal)
If `duration_s` is small or `send_error: "Broken pipe"`, Step 1 didn't take
hold — re-check ACEmanager, may need to reboot the modem after Apply.
### Step 3: confirm monitoring stopped
```bash
curl 'http://localhost:8200/device/monitor/status?host=<DEVICE_IP>&tcp_port=<PORT>&force=true'
# expect: {"is_monitoring": false, ...}
```
### Step 4: disable ACH at the device level + erase corrupted events
Either fire the rescue endpoint:
```bash
/home/serversdown/seismo-relay/scripts/rescue_device.sh <DEVICE_IP> <PORT>
```
Or do the two steps manually:
```bash
# Disable ACH in the device's compliance config
curl -X POST 'http://localhost:8200/device/call_home?host=<DEVICE_IP>&tcp_port=<PORT>' \
-H 'Content-Type: application/json' \
-d '{"auto_call_home_enabled": false}'
# Erase corrupted event chain
curl -X POST 'http://localhost:8200/device/events/erase?host=<DEVICE_IP>&tcp_port=<PORT>'
```
You can also do this via the SFM standalone UI → **Call Home** tab → set
`Enable Auto Call Home` to `Disabled` → **Write to Device**.
### Step 5: restore modem config (housekeeping)
Once the device-side ACH is disabled, restore the modem's Destination
Address and Port to the original values (e.g. `50.197.32.92` / `12345`) in
ACEmanager. The modem will resume normal bidirectional behavior, but the
unit won't issue any dial commands until ACH is explicitly re-enabled on
the device.
### Step 6: do NOT re-enable ACH on this unit until the underlying hardware
fault is repaired. If you do, the call-home loop starts again immediately
and you'll be running this runbook a second time.
---
## Why this works — the failure mode explained
The Sierra Wireless RV50/RV55 serial port operates in one of two TCP modes
at any moment:
- **Server mode** — listens on `Device Port` (e.g. 9034), bridges inbound
TCP to the device's serial port. This is what we need to interact with
the device.
- **Client mode** — when the device sends an AT dial command on its serial
TX line, the modem opens an outbound TCP to `Destination Address:Port`
and bridges that to serial.
A serial port in this configuration is **bidirectional**: the modem flips
between server and client modes on demand. When the device's firmware is
healthy and only dials occasionally, this works fine.
When the unit is constantly triggering events and ACH is set to "After
Event Recorded", the device sends an AT dial command every few seconds.
Each one causes the modem to:
1. Drop any active inbound TCP session
2. Flip to client mode
3. Attempt outbound TCP to `Destination Address:Port`
4. Hang for up to a minute waiting for it to succeed/fail
5. Drop back to server mode
**During the entire hang, no inbound TCP can establish.** Even between
hangs, the modem closes any existing inbound session before flipping. So
any tool that needs more than a few seconds of held TCP (e.g. POLL +
config read + write) gets repeatedly kicked off.
Clearing `Destination Address` removes step 3-4 from the cycle: the modem
has nowhere to dial, so it doesn't flip modes when it receives an AT dial
command. The serial port effectively becomes server-only, and inbound TCP
sessions can stay open as long as needed.
**This is a modem-layer issue, not a device firmware issue.** The device
is alive and responsive the whole time — confirmed in the BE9558H
recovery by 990 bytes of S3 responses received over a 120s slow-drip
session once the modem was no longer mode-flipping.
---
## Why simpler approaches don't work
| Approach | Why it fails |
|---|---|
| Standard `/device/info` | Triggers `count_events()` 1E/1F walk, takes 90s+ and hits corrupted event chain in this scenario |
| `/device/rescue` race loop | Gets 502 (protocol timeout) because the modem closes the TCP before the POLL handshake can complete |
| `/device/stop_monitoring_blind` (single frame) | Even if the bytes leave the wire, the device's protocol parser ignores write commands without a preceding POLL handshake (early-version bug, now fixed by including POLL preamble in blind sends) |
| `/device/stop_monitoring_spam` (sub-second cadence) | Each session is killed by the modem's mode-flip before the device can drain its UART RX buffer; high-rate spam also risks UART FIFO overrun on the device side |
| Outbound port firewall block alone | Stops the outbound TCP from succeeding, but doesn't stop the modem from *trying* and mode-flipping. Reduces but doesn't eliminate the contention. |
| Modem reboot | Temporary — as soon as the device starts triggering again, the loop resumes within seconds |
The combination of `slow_drip` + cleared `Destination Address` works because:
1. The modem stops mode-flipping → TCP session stays open for the full
drip duration
2. Slow drip rate → device's UART RX FIFO never overflows even if
firmware is busy with event recording
3. The drip is `SESSION_RESET + STOP_MONITORING` every 3s → many
independent chances for the parser to land one valid frame
4. Once one Stop Monitoring is parsed, event recording halts → firmware
has CPU to spare → subsequent operations are trivially easy
---
## Tooling reference
All endpoints live in `seismo-relay/sfm/server.py`. All scripts live in
`seismo-relay/scripts/` and default to SFM direct (`http://localhost:8200`),
overridable via `SFM_BASE_URL`.
### Endpoints added during BE9558H recovery
| Endpoint | Purpose |
|---|---|
| `GET /device/events/storage_range` | SUB 0x06 — first/last event keys, `is_empty` flag. ~2s, no event walk. |
| `GET /device/events/index` | SUB 0x08 — lifetime event counter (does NOT decrement on erase). ~2s. |
| `POST /device/events/erase` | Full erase sequence 0xA3 → 0x1C → 0x06 → 0xA2. |
| `POST /device/rescue` | Disable ACH + erase in one TCP session. Short timeouts for race-loop usage. |
| `POST /device/stop_monitoring_blind` | Fire-and-forget Stop with full POLL preamble (single attempt). |
| `POST /device/stop_monitoring_spam` | Server-side tight retry loop, sub-second cadence, duration-bounded. |
| `POST /device/stop_monitoring_slow_drip` | One held TCP session, slow trickle of stop frames. **The endpoint that saved BE9558H.** |
Also changed: default protocol recv timeout dropped from 30s → 10s in
`_build_client`. Added `connect_timeout` knob to same. Cleaned up
unhandled-exception path in `/device/monitor/status` so it returns 502
instead of 500 on protocol timeouts.
### Scripts
| Script | Purpose |
|---|---|
| `scripts/rescue_device.sh` | Race-loop wrapper around `/device/rescue` |
| `scripts/blind_stop.sh` | Race-loop wrapper around `/device/stop_monitoring_blind` |
| `scripts/spam_stop.sh` | Single-call burst hammer (`/device/stop_monitoring_spam`) |
| `scripts/slow_drip.sh` | Single-call held-session drip (`/device/stop_monitoring_slow_drip`) |
| `scripts/watch_unit.sh` | Passive periodic reachability check, logs to file |
---
## Incident log — BE9558H, 2026-05-16/17
What was wrong: Long-axis geophone developed an offset, constantly above
trigger threshold → constant event recording → after-event ACH set →
modem dialing office BW server (`50.197.32.92:12345`) every 30-60s.
Local event chain corrupted (`next_boundary 0x100EE exceeds uint16`).
Diagnostic path:
1. `/device/info` slow, choked on event walk
2. Built lightweight probe endpoints (`storage_range`, `index`) — useful
but didn't reach the wedged unit
3. Built `/device/rescue` with short timeouts — got 502 (POLL no response)
4. Built `/device/stop_monitoring_blind` — first version was a false
positive (no POLL preamble); fixed by including
`SESSION_RESET+POLL_PROBE+SESSION_RESET+POLL_DATA` in the dump
5. Verified blind stop works on bench unit
6. Built `/device/stop_monitoring_spam` — 420 successful sends over
5 min, zero behavior change on field unit
7. Inspected ACEmanager logs → saw outbound dial-out attempts every ~30s,
confirmed device was not fully locked up
8. Added outbound port-12345 firewall block → outbound attempts now fail
instantly but contention persisted
9. Built `/device/stop_monitoring_slow_drip` — session died at 3s with
broken pipe (modem closing on us)
10. Looked at full ACEmanager Port Configuration → **found
`Destination Address: 50.197.32.92` configured**, realized every AT
dial command was triggering a modem mode-flip that killed our inbound
11. Cleared Destination Address + Port → slow_drip held 120s, device
responded with 990 bytes, 39 stop commands acked
12. Disabled ACH at device level via `/device/call_home`, erased events
Final state: device IDLE, memory 958.1 / 960 KB free, ACH disabled at
device level, modem destination cleared (to be restored after physical
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.
**Same disease, inverted cure.** Method B's Step 1 *did* work — clearing the
Destination stopped the dial-outs, confirmed in the ALEOS log. It was Step 2
that didn't land, and rather than keep racing we turned the rescue around:
gave the unit a different server to call, and answered it.
Total time ≈ 5 h, of which ~90 min went to two red herrings documented below.
Much of the rest was rediscovering the May procedure, which is why the
"two cures" table now sits at the top of this file.
---
## 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 unit is on the phone
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**.
**While it is in this state it is busy placing a call, not listening for
us.** This is almost certainly what BE9558H was doing too — we simply never
turned on ALEOS_SERIAL debug in May to look. It is not a different disease;
it is the same one, seen properly for the first time.
It is also the argument for Method A in one picture: the unit is mid-dial
every ~75 s, and our inbound Stop has to thread the gaps between those
attempts. Give it somewhere to dial and the problem inverts into a
deterministic one.
### 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.**
⚠ **In fairness to slow_drip: it got exactly one attempt here**, run ~90 s
after a modem reboot, with a dead session visible in the log at 20:19:17 in
that same window. BE9558H took hours of attempts before one landed. Method B
was not ruled out on BE12599 so much as abandoned in favour of something that
doesn't need luck.
---
## ⚠ 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.
docs/sfm_tool_status.md
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# SFM — where it actually stands as a tool
**Status as of 2026-09-20 (v0.31.0).** This is the honest assessment, not the
roadmap — `README.md § Roadmap` covers where it is *going*. Expect this file to
go stale; re-date it when you revise it.
---
## The framing
SFM is **three different things wearing one name**, at three very different
levels of maturity:
| | what it is | maturity |
|---|---|---|
| **The codec library** | `minimateplus/`, `micromate/` — bytes in, `Event` out | **Production.** Verified per-sample at scale. |
| **SDM — the data side** | the DB, waveform store, `/db/*`, ingest | **Production.** Terra-View depends on it daily. |
| **SFM — the device side** | `/device/*`, live connections to units | **Emergency-grade.** Works, but manual, unauthenticated, and thinly tested. |
| **The lab** | `seismo_lab.py`, `scratch/`, the Inspector | **Research artifacts.** Useful, not products. |
Brian's own description — *"right now it's an emergency tool and a research
project"* — is accurate, and it applies specifically to the **device side**.
The data side is not an emergency tool; it has been carrying production for
months.
Most confusion about "is SFM reliable?" comes from answering for the wrong
tier.
---
## 1. What you can rely on
### Production-grade — trust it
- **Series-3 decode.** 14,338 / 14,338 files decode per-sample exact against
preserved Blastware ASCII exports, 45 units, files back to 2018.
- **Series-4 (Thor) decode.** 1,057,536 / 1,057,536 geo samples exact against
Thor's own CSV exports; production IDFW 575/575 with zero truncations.
- **Histogram decode.** 1,211 / 1,211 production histograms exact, including
842,442 per-interval frequency comparisons with zero mismatches.
- **The ingest path.** `/db/import/blastware_file` and `/db/import/idf_file`
fed by the watchers — this is how prod actually gets its data, and it has
been running unattended for months.
- **`/db/*` read API.** Always-on, consumed by Terra-View for every fleet
listing, event detail and report.
- **The waveform store** — `.h5` + `.sfm.json` sidecars + retained raw
binaries, with operator review state preserved across regeneration.
- **`bridges/ach_server.py`** — speaks the full BW protocol to calling units.
Proven in the field, including as a rescue tool (see the runbook).
### Emergency-grade — works, but you are the error handling
- **`/device/*` live endpoints.** They do what they say. But they are
synchronous, unauthenticated, and a single cellular download can exceed the
60 s timeouts that sit in front of them.
- **The rescue ladder** (`rescue`, `stop_monitoring_*`, `events/erase`).
Each has worked in a real incident — but each has been used a handful of
times, by one person, with the runbook open.
- **The standalone webapp.** Perfectly usable, and as of v0.31.0 the cheap
probes and rescue actions are reachable without curl. No auth of any kind.
### Research artifacts — useful, not products
- **`seismo_lab.py`** — 2,789 lines of Tkinter (Bridge / Analyzer / Query DB /
Inspector). Desktop-only, single-user, no tests.
- **`scratch/`** — the verification harnesses (`verify_against_ascii.py`,
`verify_thor_against_csv.py`) and the offset detector (`offset_scan3.py`).
These produced the numbers the production claims rest on, so they matter —
but they are analysis scripts, not maintained code.
- **`docs/offset_investigation.md`** — an open investigation, not a feature.
---
## 2. What to use when
| you want to… | use | notes |
|---|---|---|
| Know if a unit is monitoring / its battery / memory | `GET /device/monitor/status?force=true` | ~2 s |
| Know whether ACH is on | `GET /device/call_home` | ~2 s. **Not** `/device/events`. |
| See how full a unit's buffer is | `GET /device/events/storage_range` | ~2 s, no chain walk |
| Stop a runaway unit | Diagnostics tab → Stop Monitoring | see the runbook first |
| Reach a unit that will not answer | **point its modem at an `ach_server` and answer its call** | runbook Method A — do not race it |
| List a unit's stored events | Events tab → Load events | **slow**, and broken past 64 KB (below) |
| Get event data into the DB | the watcher → `/db/import/*` path | not the live walk |
The single most useful habit: **the cheap probes are cheap and the event walk
is not.** Reaching for `/device/events` to answer a yes/no question about a
unit is the mistake that motivated the v0.31.0 webapp changes.
---
## 3. Known issues
| issue | impact | status |
|---|---|---|
| **5A walk dies once a unit's buffer crosses 64 KB** | `/device/events` 500s; event body never downloads | Known, documented in `CLAUDE.md`. Needs a BW capture of a spanning event to fix properly. |
| **No auth on SFM at all** | 21 `/device/*` endpoints, including destructive ones, open to anything that reaches the port | Design agreed (Terra-View as authenticated jump host); not built. |
| **Swagger try-it-out is live on destructive endpoints** | `POST /device/events/erase` is one click away at `:8200/docs` | Partially mitigated: the webapp's erase now requires typing the serial. `/docs` itself is unguarded. |
| **`SUB 0x08` lifetime counter reads 0** | `/device/events/index` returns a meaningless number | Suspected field-offset bug. Surfaced in the UI as "unreliable". |
| **Long device operations are synchronous** | 60 s timeouts in `routers/sfm.py` and the reverse proxy; a full download exceeds both | Known design constraint. Must be POST-starts-job / GET-polls before any remote lab. |
| **`backfill_sidecars.py --force` silently inserts DB rows** | store files with no DB row get one; the dry-run does not report the count | Known. Avoid `--force` — `TOOL_VERSION` gates regeneration anyway. |
| **14 sensitive-range files show an exact 8× discrepancy** | 10.0 / 1.25 — a units problem, not a decode problem | Open, not blocking. |
| **16 failing tests on `dev`** | 15 need gitignored fixture bundles; 1 is real (`sc["peak_values"]["transverse"]` returns `None` where `0.0` is expected) | The real one shipped in v0.31.0. |
---
## 4. What stands between this and a real tool
Roughly in dependency order — each unblocks the ones below it.
**1. Authentication.** Everything else is gated on this. SFM has none, and
the modem IP whitelist gives zero protection because SFM *is* the whitelisted
origin. The agreed design delegates rather than builds: Terra-View becomes the
authenticated jump host (`/api/sfm/*` already inherits deny-by-default operator
auth), and the `8200:8200` publish is dropped so Terra-View is the only door.
**2. Async long operations.** POST starts a job, GET polls. Retrofitting this
after building a remote lab on top of synchronous endpoints would be far worse
than designing for it now.
**3. Confirm-guards on the remaining destructive endpoints.** Auth answers
*who*, not *did you mean it*. The webapp's erase is guarded; the other seven
destructive POSTs and `/docs` are not.
**4. The 5A page-boundary fix.** Until this lands, live event download is
unreliable on exactly the units most likely to need attention — the ones that
have been recording heavily. Wants a Blastware capture of an event spanning a
page boundary before the chunk-addressing half is trustworthy.
**5. A live Thor / Micromate client.** The device side is MiniMate-only.
Series-4 units can only be read from forwarded files, so half the fleet has no
live path at all.
**6. Test coverage that runs from a clean checkout.** 15 of 16 current
failures are missing fixture bundles. A test suite that cannot go green on a
fresh clone cannot gate anything.
**7. The SDM rename.** Cosmetic relative to the above, but the longer `sfm/`
holds the data-side code the more the tiers blur. ~30–50 files here, ~10–15 in
Terra-View, plus a Docker volume migration. Do it when the codebase is quiet.
---
## The short version
The **data side is a real tool already**. The **device side is a set of sharp
instruments** that work in the hands of the person who wrote them, with the
runbook open. The gap between those two states is mostly **auth, async, and
guardrails** — not protocol work. The protocol is the part that is actually
finished.
docs/superpowers/plans/2026-08-21-waveform-ft-detection-phase-a.md
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# Waveform-shape FT detection — Phase A (seismo-relay) Implementation Plan
> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
**Goal:** Compute per-event waveform-shape metrics (crest factor + points-near-peak) in SFM and store them as `events` columns, populated at ingest and by a backfill script, so Terra-View can read them from `/db/events`.
**Architecture:** A pure DSP module (`sfm/shape_metrics.py`) turns decoded `.h5` samples into shape metrics. New nullable `events.shape_*` columns are added via the existing `_migrate` ADD COLUMN loop. The three `WaveformStore.save*` paths compute shape from the just-written `.h5` and hand it to `insert_events`; a backfill script does the same over existing events. Mirrors exactly how per-channel ZC frequency was added.
**Tech Stack:** Python 3.10, numpy, h5py, sqlite3 (raw), pytest. seismo-relay venv: `/home/serversdown/seismo-relay/.venv/bin/python3`.
## Global Constraints
- Metrics are read from the `.h5` `samples/{Tran,Vert,Long}` float32 arrays (physical in/s). The measured channel is the max-|peak| geophone channel.
- All new columns are nullable; histogram records and events without usable samples store NULL (Terra-View falls back to cheap signals). Legacy rows stay valid.
- Crest factor = `max(|x|) / rms(x)`; near-peak count = number of samples with `|x| ≥ 0.5·peak`. Threshold `0.5` is a module constant so calibration can tune it.
- No manual migration: columns are added in `SeismoDb._migrate`, run at `SeismoDb()` construction.
- `/db/events` needs no change — it returns all columns via `SELECT *` (verify with a test).
- Run tests with `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest`.
---
### Task 1: Shape DSP module
**Files:**
- Create: `sfm/shape_metrics.py`
- Test: `tests/test_shape_metrics.py`
**Interfaces:**
- Produces:
- `channel_shape(x) -> dict | None` — `{"crest_factor": float, "near_peak_count": int, "sample_count": int}` or None for unusable input (size < 2, flat, all-zero).
- `shape_from_samples(chans: dict[str, ArrayLike]) -> dict | None` — picks the max-peak geophone channel; returns `{"crest_factor","near_peak_count","sample_count","axis"}` or None.
- `shape_from_h5(path) -> dict | None` — reads `samples/{Tran,Vert,Long}` and delegates to `shape_from_samples`; None on any read error.
- Constant `NEAR_PEAK_FRACTION = 0.5`.
- [ ] **Step 1: Write the failing test**
```python
# tests/test_shape_metrics.py
import numpy as np
from sfm.shape_metrics import channel_shape, shape_from_samples
def test_needle_spike_high_crest_few_near_peak():
x = np.zeros(1024); x[500] = 1.0 # one isolated spike
s = channel_shape(x)
assert s["sample_count"] == 1024
assert s["crest_factor"] > 15 # peak towers over rms
assert s["near_peak_count"] <= 3 # almost nothing near the peak
def test_ringing_low_crest_many_near_peak():
t = np.arange(1024)
x = np.sin(2*np.pi*t/32) * np.exp(-t/4000) # decaying oscillation
s = channel_shape(x)
assert s["crest_factor"] < 6
assert s["near_peak_count"] > 30 # many samples near the peak
def test_channel_shape_none_for_unusable():
assert channel_shape(np.zeros(1024)) is None # flat / all-zero
assert channel_shape(np.array([1.0])) is None # too short
def test_shape_from_samples_picks_max_peak_axis():
chans = {"Tran": np.zeros(1024), "Vert": np.zeros(1024), "Long": np.zeros(1024)}
chans["Long"][10] = 0.5
chans["Vert"] = np.sin(np.arange(1024)/5) * 0.01
s = shape_from_samples(chans)
assert s["axis"] == "Long" # Long has the biggest peak
assert s["near_peak_count"] <= 3
def test_shape_from_samples_none_when_no_geo():
assert shape_from_samples({"MicL": np.ones(1024)}) is None
```
- [ ] **Step 2: Run test to verify it fails**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_shape_metrics.py -q`
Expected: FAIL — `ModuleNotFoundError: sfm.shape_metrics`.
- [ ] **Step 3: Write minimal implementation**
```python
# sfm/shape_metrics.py
"""Waveform-shape metrics for false-trigger detection.
A false trigger is an isolated impulse (quiet → spike → quiet); a real event
rings for many cycles. Two numbers separate them: crest factor (how far the
peak stands above the typical sample) and how many samples sit near the peak.
"""
from __future__ import annotations
import numpy as np
_GEO_CHANNELS = ("Tran", "Vert", "Long")
NEAR_PEAK_FRACTION = 0.5 # a sample "near the peak" is >= this * peak amplitude
def channel_shape(x) -> dict | None:
x = np.asarray(x, dtype=float)
if x.size < 2:
return None
peak = float(np.max(np.abs(x)))
if peak <= 0:
return None
rms = float(np.sqrt(np.mean(x ** 2)))
if rms <= 0:
return None
near = int(np.sum(np.abs(x) >= NEAR_PEAK_FRACTION * peak))
return {"crest_factor": peak / rms, "near_peak_count": near,
"sample_count": int(x.size)}
def shape_from_samples(chans: dict) -> dict | None:
best_axis, best_peak, best_x = None, -1.0, None
for ax in _GEO_CHANNELS:
x = chans.get(ax)
if x is None:
continue
x = np.asarray(x, dtype=float)
if x.size < 2:
continue
p = float(np.max(np.abs(x)))
if p > best_peak:
best_axis, best_peak, best_x = ax, p, x
if best_axis is None:
return None
s = channel_shape(best_x)
if s is None:
return None
s["axis"] = best_axis
return s
def shape_from_h5(path) -> dict | None:
import h5py
try:
with h5py.File(path, "r") as f:
chans = {ax: f[f"samples/{ax}"][:] for ax in _GEO_CHANNELS
if f"samples/{ax}" in f}
except Exception:
return None
return shape_from_samples(chans)
```
- [ ] **Step 4: Run test to verify it passes**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_shape_metrics.py -q`
Expected: PASS (5 tests).
- [ ] **Step 5: Commit**
```bash
git add sfm/shape_metrics.py tests/test_shape_metrics.py
git commit -m "feat(shape): crest-factor + points-near-peak waveform metrics"
```
---
### Task 2: shape_from_h5 round-trips a real .h5
**Files:**
- Test: `tests/test_shape_metrics_h5.py`
**Interfaces:**
- Consumes: `sfm.shape_metrics.shape_from_h5`; `h5py`.
- [ ] **Step 1: Write the failing test** (writes a tiny .h5 the same shape SFM writes, then reads it back)
```python
# tests/test_shape_metrics_h5.py
import numpy as np, h5py
from sfm.shape_metrics import shape_from_h5
def _write_h5(path, chans):
with h5py.File(path, "w") as f:
g = f.create_group("samples")
for k, v in chans.items():
g.create_dataset(k, data=np.asarray(v, dtype="float32"))
def test_shape_from_h5_reads_dominant_axis(tmp_path):
p = tmp_path / "ev.h5"
long = np.zeros(1024, dtype="float32"); long[100] = 0.48
_write_h5(p, {"Tran": np.zeros(1024), "Vert": np.zeros(1024), "Long": long,
"MicL": np.ones(1024)})
s = shape_from_h5(str(p))
assert s["axis"] == "Long" and s["near_peak_count"] <= 3
def test_shape_from_h5_none_on_missing_or_degenerate(tmp_path):
assert shape_from_h5(str(tmp_path / "nope.h5")) is None
p = tmp_path / "degen.h5"
_write_h5(p, {"Tran": np.zeros(1), "Vert": np.zeros(1), "Long": np.zeros(1)})
assert shape_from_h5(str(p)) is None
```
- [ ] **Step 2: Run to verify it fails**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_shape_metrics_h5.py -q`
Expected: FAIL (assertion or, if Task 1 incomplete, import error).
- [ ] **Step 3: Implementation** — none needed; `shape_from_h5` already exists from Task 1. If a test fails, fix `shape_from_h5` (not the test).
- [ ] **Step 4: Run to verify it passes**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_shape_metrics_h5.py -q`
Expected: PASS (2 tests).
- [ ] **Step 5: Commit**
```bash
git add tests/test_shape_metrics_h5.py
git commit -m "test(shape): shape_from_h5 round-trips a real .h5"
```
---
### Task 3: Add shape columns to the events schema + migration
**Files:**
- Modify: `sfm/database.py` — `_SCHEMA` CREATE TABLE `events` (after `mic_zc_above_range`); `_migrate` ADD COLUMN loop (the tuple around line 205-218).
- Test: `tests/test_shape_columns.py`
**Interfaces:**
- Produces: `events` columns `shape_crest_factor REAL`, `shape_near_peak_count INTEGER`, `shape_sample_count INTEGER`, `shape_axis TEXT`.
- [ ] **Step 1: Write the failing test**
```python
# tests/test_shape_columns.py
import sqlite3
from sfm.database import SeismoDb
_SHAPE_COLS = {"shape_crest_factor", "shape_near_peak_count",
"shape_sample_count", "shape_axis"}
def _cols(db):
with sqlite3.connect(db.db_path) as c:
return {r[1] for r in c.execute("PRAGMA table_info(events)")}
def test_fresh_db_has_shape_columns(tmp_path):
db = SeismoDb(tmp_path / "s.db")
assert _SHAPE_COLS <= _cols(db)
def test_existing_db_migrates_shape_columns(tmp_path):
p = tmp_path / "s.db"
db = SeismoDb(p)
with sqlite3.connect(p) as c: # simulate an older DB missing the columns
for col in _SHAPE_COLS:
c.execute(f"ALTER TABLE events DROP COLUMN {col}")
assert not (_SHAPE_COLS <= _cols(SeismoDb(p))) # sanity: dropped
SeismoDb(p) # re-open triggers _migrate
assert _SHAPE_COLS <= _cols(SeismoDb(p))
```
> Note: sqlite `DROP COLUMN` needs sqlite ≥ 3.35 (bundled py3.10 has it). If the runner's sqlite lacks it, replace the "simulate older DB" block with building a table without the columns; keep the assertion that re-open adds them.
- [ ] **Step 2: Run to verify it fails**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_shape_columns.py -q`
Expected: FAIL — columns absent.
- [ ] **Step 3: Implementation**
In `_SCHEMA`, after the `mic_zc_above_range INTEGER,` line in the `events` CREATE TABLE, add:
```
shape_crest_factor REAL, -- peak / rms of the triggering channel
shape_near_peak_count INTEGER, -- samples >= 0.5 * peak (FT: few; real: many)
shape_sample_count INTEGER, -- total samples (to normalize near_peak_count)
shape_axis TEXT, -- geophone channel measured ("Tran"/"Vert"/"Long")
```
In `_migrate`, extend the ADD COLUMN tuple (the `for col, ddl in (...)` list) with:
```python
("shape_crest_factor", "REAL"),
("shape_near_peak_count", "INTEGER"),
("shape_sample_count", "INTEGER"),
("shape_axis", "TEXT"),
```
- [ ] **Step 4: Run to verify it passes**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_shape_columns.py -q`
Expected: PASS.
- [ ] **Step 5: Commit**
```bash
git add sfm/database.py tests/test_shape_columns.py
git commit -m "feat(db): shape_* columns on events (+ auto-migrate)"
```
---
### Task 4: insert_events persists shape from the waveform record
**Files:**
- Modify: `sfm/database.py` — `insert_events` INSERT (column list + placeholders + values) and the UPSERT `UPDATE` block.
- Test: `tests/test_insert_events_shape.py`
**Interfaces:**
- Consumes: a `waveform_records` rec dict that may carry `shape_crest_factor`, `shape_near_peak_count`, `shape_sample_count`, `shape_axis`.
- Produces: those four values stored on the row; refreshed on UPSERT.
- [ ] **Step 1: Write the failing test**
```python
# tests/test_insert_events_shape.py
from sfm.database import SeismoDb
from tests.helpers_events import make_event # existing helper used by other insert tests
def test_insert_stores_shape_from_record(tmp_path):
db = SeismoDb(tmp_path / "s.db")
ev = make_event(serial="BE1", key="0111abcd")
rec = {ev._waveform_key.hex(): {
"filename": "F.CE0W", "filesize": 10,
"shape_crest_factor": 34.0, "shape_near_peak_count": 3,
"shape_sample_count": 1024, "shape_axis": "Long"}}
db.insert_events([ev], serial="BE1", waveform_records=rec)
row = db.query_events(serial="BE1")[0]
assert row["shape_crest_factor"] == 34.0
assert row["shape_near_peak_count"] == 3
assert row["shape_axis"] == "Long"
```
> If `tests/helpers_events.make_event` doesn't exist, build the `Event` inline the way `tests/test_zc_freq_columns.py` does (copy its event-construction helper). Keep the assertion identical.
- [ ] **Step 2: Run to verify it fails**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_insert_events_shape.py -q`
Expected: FAIL — `KeyError`/`sqlite3.OperationalError` (columns not in INSERT) or values are NULL.
- [ ] **Step 3: Implementation**
In `insert_events` INSERT: add `shape_crest_factor, shape_near_peak_count, shape_sample_count, shape_axis` to the column list, add four `?` placeholders, and add these to the VALUES tuple (after the `mic_zc_above_range` value):
```python
rec.get("shape_crest_factor"),
rec.get("shape_near_peak_count"),
rec.get("shape_sample_count"),
rec.get("shape_axis"),
```
In the UPSERT `UPDATE ... SET`: add
```sql
shape_crest_factor = COALESCE(?, shape_crest_factor),
shape_near_peak_count = COALESCE(?, shape_near_peak_count),
shape_sample_count = COALESCE(?, shape_sample_count),
shape_axis = COALESCE(?, shape_axis),
```
and the matching params (before `serial, ts`):
```python
rec.get("shape_crest_factor") if rec else None,
rec.get("shape_near_peak_count") if rec else None,
rec.get("shape_sample_count") if rec else None,
rec.get("shape_axis") if rec else None,
```
(`COALESCE` on UPSERT so a re-import that lacks samples doesn't wipe a previously-computed shape.)
- [ ] **Step 4: Run to verify it passes**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_insert_events_shape.py -q`
Expected: PASS.
- [ ] **Step 5: Commit**
```bash
git add sfm/database.py tests/test_insert_events_shape.py
git commit -m "feat(db): insert_events persists shape_* from waveform record"
```
---
### Task 5: Populate shape at ingest (the three save paths)
**Files:**
- Modify: `sfm/waveform_store.py` — in `save`, `save_imported_bw`, `save_imported_idf`, after the `.h5` is written, add its shape to the returned `rec` dict.
- Test: `tests/test_save_shape.py`
**Interfaces:**
- Consumes: `sfm.shape_metrics.shape_from_h5`.
- Produces: `save*` return dicts carry `shape_crest_factor / shape_near_peak_count / shape_sample_count / shape_axis` (present only when the `.h5` had usable samples).
- [ ] **Step 1: Write the failing test** (drives the BW-import path, which the existing suite already exercises)
```python
# tests/test_save_shape.py
from sfm.waveform_store import WaveformStore
from tests.helpers_bw import sample_bw_bytes, sample_serial # reuse existing import-test fixtures
def test_save_imported_bw_attaches_shape(tmp_path):
store = WaveformStore(tmp_path / "waveforms")
ev, rec = store.save_imported_bw(sample_bw_bytes(), serial=sample_serial())
# A real BW waveform → shape present with a geo axis.
assert rec.get("shape_axis") in ("Tran", "Vert", "Long")
assert rec["shape_crest_factor"] > 0
assert rec["shape_sample_count"] > 200
```
> Reuse whatever fixture `tests/test_save_imported_bw*.py` already uses for BW bytes; match its import. If the existing BW fixture produces a degenerate/short waveform, use the fixture from the test that asserts a full h5.
- [ ] **Step 2: Run to verify it fails**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_save_shape.py -q`
Expected: FAIL — `rec` has no `shape_*` keys.
- [ ] **Step 3: Implementation**
Add a helper near the top of `WaveformStore` methods (module-level import `from sfm.shape_metrics import shape_from_h5`). In each of `save`, `save_imported_bw`, `save_imported_idf`, immediately before building/returning the `rec` dict — and only when the `.h5` was written (i.e. `hdf5_filename`/`hdf5_path` is set) — compute and merge:
```python
shape = shape_from_h5(hdf5_path) if hdf5_filename else None
# ... in the returned rec dict literal, add:
# **(shape and {
# "shape_crest_factor": shape["crest_factor"],
# "shape_near_peak_count": shape["near_peak_count"],
# "shape_sample_count": shape["sample_count"],
# "shape_axis": shape["axis"],
# } or {}),
```
Concretely, after each method computes `hdf5_filename`, add before its `return {...}`:
```python
_shape = shape_from_h5(hdf5_path) if hdf5_filename else None
_shape_rec = {
"shape_crest_factor": _shape["crest_factor"],
"shape_near_peak_count": _shape["near_peak_count"],
"shape_sample_count": _shape["sample_count"],
"shape_axis": _shape["axis"],
} if _shape else {}
```
and spread `**_shape_rec` into the returned dict. (`save_imported_bw`/`save_imported_idf` use their own hdf5 path variable names — use whichever local holds the written `.h5` path in each method.)
- [ ] **Step 4: Run to verify it passes**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_save_shape.py -q`
Expected: PASS.
- [ ] **Step 5: Commit**
```bash
git add sfm/waveform_store.py tests/test_save_shape.py
git commit -m "feat(ingest): compute shape from the written .h5 in all save paths"
```
---
### Task 6: Backfill script for existing events
**Files:**
- Create: `scripts/backfill_event_shape.py` (mirror `scripts/backfill_event_zc_freq.py`, but read the `.h5` for samples instead of the sidecar).
- Test: `tests/test_backfill_event_shape.py`
**Interfaces:**
- Produces: `backfill_shape(db, store, *, dry_run=False) -> dict` with counts `{"updated","skipped_no_h5","skipped_no_samples"}`; `main(argv)` CLI mirroring the zc-freq script's args (`--db-path`, `--store-root`, `--dry-run`).
- [ ] **Step 1: Write the failing test**
```python
# tests/test_backfill_event_shape.py
import numpy as np, h5py
from sfm.database import SeismoDb
from sfm.waveform_store import WaveformStore
from scripts.backfill_event_shape import backfill_shape
from tests.helpers_events import make_event # or inline as in test_zc_freq_columns
def _h5(path, long):
with h5py.File(path, "w") as f:
g = f.create_group("samples")
for k in ("Tran", "Vert"): g.create_dataset(k, data=np.zeros(1024, "float32"))
g.create_dataset("Long", data=np.asarray(long, "float32"))
def test_backfill_updates_shape_and_is_idempotent(tmp_path):
db = SeismoDb(tmp_path / "s.db")
store = WaveformStore(tmp_path / "waveforms")
ev = make_event(serial="BE1", key="0111abcd")
db.insert_events([ev], serial="BE1",
waveform_records={ev._waveform_key.hex():
{"filename": "F.CE0W", "filesize": 10}})
# place the .h5 where store.paths_for expects it
long = np.zeros(1024); long[100] = 0.48
_h5(store.hdf5_path_for("BE1", "F.CE0W"), long)
c1 = backfill_shape(db, store)
assert c1["updated"] == 1
row = db.query_events(serial="BE1")[0]
assert row["shape_axis"] == "Long" and row["shape_near_peak_count"] <= 3
c2 = backfill_shape(db, store) # idempotent: re-run overwrites same values
assert db.query_events(serial="BE1")[0]["shape_crest_factor"] == row["shape_crest_factor"]
```
> Match `make_event` / column names to whatever `tests/test_zc_freq_columns.py` uses. `store.hdf5_path_for(serial, filename)` is the existing helper that returns the `.h5` path.
- [ ] **Step 2: Run to verify it fails**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_backfill_event_shape.py -q`
Expected: FAIL — `ModuleNotFoundError: scripts.backfill_event_shape`.
- [ ] **Step 3: Implementation** (mirror the zc-freq script structure)
```python
#!/usr/bin/env python3
"""Backfill events.shape_* from each event's .h5 waveform samples. Idempotent."""
from __future__ import annotations
import argparse, logging, sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from sfm.database import SeismoDb
from sfm.waveform_store import WaveformStore
from sfm.shape_metrics import shape_from_h5
log = logging.getLogger("backfill_event_shape")
def backfill_shape(db: SeismoDb, store: WaveformStore, *, dry_run: bool = False) -> dict:
counts = {"updated": 0, "skipped_no_h5": 0, "skipped_no_samples": 0}
for row in db.query_events(limit=1_000_000):
serial, filename = row.get("serial"), row.get("blastware_filename")
if not serial or not filename:
counts["skipped_no_h5"] += 1; continue
h5_path = store.hdf5_path_for(serial, filename)
if not h5_path.exists():
counts["skipped_no_h5"] += 1; continue
shape = shape_from_h5(h5_path)
if shape is None:
counts["skipped_no_samples"] += 1; continue
if not dry_run:
with db._connect() as conn:
conn.execute(
"UPDATE events SET shape_crest_factor=?, shape_near_peak_count=?, "
"shape_sample_count=?, shape_axis=? WHERE id=?",
(shape["crest_factor"], shape["near_peak_count"],
shape["sample_count"], shape["axis"], row["id"]))
counts["updated"] += 1
log.info("backfill_shape: %s", counts)
return counts
def main(argv=None) -> int:
ap = argparse.ArgumentParser()
ap.add_argument("--db-path", required=True)
ap.add_argument("--store-root", required=True)
ap.add_argument("--dry-run", action="store_true")
a = ap.parse_args(argv)
logging.basicConfig(level=logging.INFO)
counts = backfill_shape(SeismoDb(a.db_path), WaveformStore(a.store_root), dry_run=a.dry_run)
print(counts)
return 0
if __name__ == "__main__":
raise SystemExit(main())
```
> `store.hdf5_path_for` and `db._connect` are existing internals used the same way by other scripts. If `hdf5_path_for` isn't public, use `store.paths_for(...)` sibling `.h5` path exactly as `save()` derives `hdf5_path`.
- [ ] **Step 4: Run to verify it passes**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_backfill_event_shape.py -q`
Expected: PASS.
- [ ] **Step 5: Run the full suite + commit**
```bash
/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest -q
git add scripts/backfill_event_shape.py tests/test_backfill_event_shape.py
git commit -m "feat(scripts): backfill events.shape_* from .h5 samples"
```
---
### Task 7: Confirm /db/events carries shape + version bump
**Files:**
- Test: `tests/test_db_events_exposes_shape.py`
- Modify: `pyproject.toml` version; `sfm/server.py` version string; `CHANGELOG.md`.
**Interfaces:**
- Consumes: the running `/db/events` route (already returns `SELECT *`).
- [ ] **Step 1: Write the failing test** (guards that the feed dict includes the new keys)
```python
# tests/test_db_events_exposes_shape.py
from sfm.database import SeismoDb
def test_query_events_row_includes_shape_keys(tmp_path):
db = SeismoDb(tmp_path / "s.db")
# query_events returns dict(row); a fresh insert has the keys (values may be None)
from tests.helpers_events import make_event
db.insert_events([make_event(serial="BE1", key="0111abcd")], serial="BE1")
row = db.query_events(serial="BE1")[0]
for k in ("shape_crest_factor","shape_near_peak_count","shape_sample_count","shape_axis"):
assert k in row
```
- [ ] **Step 2: Run to verify it fails / passes**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest tests/test_db_events_exposes_shape.py -q`
Expected: PASS immediately if Task 3 landed (columns present in `SELECT *`). If it fails, the columns weren't added — fix Task 3. (This task is the guard, not new behavior.)
- [ ] **Step 3: Version bump**
Bump `pyproject.toml` `version` 0.23.0 → 0.24.0; set `sfm/server.py` `version="0.24.0"`; add a `## v0.24.0` CHANGELOG entry ("waveform-shape metrics on events: crest factor + points-near-peak, ingest + backfill").
- [ ] **Step 4: Full suite**
Run: `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest -q`
Expected: PASS (no regressions).
- [ ] **Step 5: Commit**
```bash
git add tests/test_db_events_exposes_shape.py pyproject.toml sfm/server.py CHANGELOG.md
git commit -m "chore(release): v0.24.0 — waveform-shape metrics on events"
```
---
## Self-Review
**Spec coverage:** SFM shape columns (Tasks 3–4) ✓; DSP crest + near-peak (Task 1) ✓; ingest population (Task 5) ✓; backfill (Task 6) ✓; `/db/events` exposure (Task 7) ✓; NULL for histogram/no-sample events (Tasks 1/5/6 return None → NULL) ✓; 94%-coverage / series-4 fallback handled by NULL-then-Terra-View-fallback (Phase B) ✓. Terra-View scoring, 3-state review, twin flagging, export Notes column → **Phase B plan** (separate, depends on this feed). Calibration → Phase C.
**Placeholder scan:** No TBD/TODO; every code step has real code. The two "reuse existing fixture" notes point at concrete existing tests (`test_zc_freq_columns.py`, `test_save_imported_bw*.py`) rather than leaving blanks.
**Type consistency:** `shape_from_h5`/`shape_from_samples`/`channel_shape` return the same dict keys (`crest_factor`, `near_peak_count`, `sample_count`, `axis`) throughout; the DB columns (`shape_crest_factor`, `shape_near_peak_count`, `shape_sample_count`, `shape_axis`) and rec keys match across Tasks 4–6.
## Deferred to Phase B (terra-view, separate plan)
Scoring service combining shape + cheap signals; suspicion column + reason chips; `reviewed_real` mirror + 3-state review; twin-aware flag propagation; Notes-column export + Maximums "(excludes N flagged)". Written once this feed is live so column names/values are real.
docs/superpowers/plans/2026-08-25-b2a-reviewed-real-twin-propagation.md
+264
View File
@@ -0,0 +1,264 @@
# Phase B2-A (seismo-relay) — reviewed_real + 3-state mirror + twin propagation
> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
**Goal:** Give SFM a persisted, queryable `reviewed_real` flag alongside `false_trigger` (mirrored from the sidecar review block, mutually exclusive), and propagate a review to an event's histogram/waveform twin so flagging one flags both.
**Architecture:** Mirror the existing `false_trigger` mechanism. New `events.reviewed_real` column (auto-migrate). `update_event_review` mirrors BOTH flags from the sidecar review block and enforces mutual exclusivity on the columns. A `find_twins` matcher (same serial + identical peak_vector_sum + timestamp within a window) drives `propagate_review_to_twins`, which the sidecar-PATCH endpoint calls after mirroring the primary. Terra-View reads `reviewed_real` from `/db/events` (SELECT *).
**Tech Stack:** Python 3.10, raw sqlite3, FastAPI, pytest. Runner: `/home/serversdown/seismo-relay/.venv/bin/python3`.
## Global Constraints
- 3 review states are **mutually exclusive**: an event is `false_trigger=1` XOR `reviewed_real=1` XOR neither. Setting one true forces the other's column to 0.
- The sidecar JSON stays the source of truth for full review state; the `false_trigger`/`reviewed_real` columns are derived indexes (like today). B2-A propagates twins at the **column** level (what the feed/peak/export read); twin sidecars are not rewritten (known limitation — noted).
- Twin match = **same serial AND identical `peak_vector_sum` (exact equality) AND `timestamp` within ± window (default 300 s), excluding the event itself.** Identical PVS is the safety anchor.
- Known pre-existing test failures (~16, missing gitignored fixtures under `tests/fixtures/`) are unrelated — confirm zero NEW failures, don't try to fix them.
- Run tests with `/home/serversdown/seismo-relay/.venv/bin/python3 -m pytest`.
---
### Task 1: `reviewed_real` column on events
**Files:** Modify `sfm/database.py` (`_SCHEMA` CREATE TABLE `events` + the Migration-1 rebuild `CREATE TABLE` + the `_migrate` ADD COLUMN loop). Test: `tests/test_reviewed_real_column.py`.
**Interfaces:** Produces `events.reviewed_real INTEGER NOT NULL DEFAULT 0`.
- [ ] **Step 1: Failing test**
```python
# tests/test_reviewed_real_column.py
import sqlite3
from sfm.database import SeismoDb
def _cols(db):
with sqlite3.connect(db.db_path) as c:
return {r[1] for r in c.execute("PRAGMA table_info(events)")}
def test_fresh_db_has_reviewed_real(tmp_path):
assert "reviewed_real" in _cols(SeismoDb(tmp_path/"s.db"))
def test_existing_db_migrates_reviewed_real(tmp_path):
p = tmp_path/"s.db"; db = SeismoDb(p)
with sqlite3.connect(p) as c:
c.execute("ALTER TABLE events DROP COLUMN reviewed_real")
assert "reviewed_real" not in _cols(db) # dropped (read via existing handle/connection)
SeismoDb(p) # re-open migrates
assert "reviewed_real" in _cols(SeismoDb(p))
```
> If sqlite < 3.35 lacks DROP COLUMN, fall back to building a table without the column and asserting re-open adds it (same as the shape-columns test did).
- [ ] **Step 2: Run → FAIL** (`pytest tests/test_reviewed_real_column.py -q`).
- [ ] **Step 3: Implement**
- In `_SCHEMA` `events` CREATE TABLE, after the `false_trigger ... DEFAULT 0,` line add: ` reviewed_real INTEGER NOT NULL DEFAULT 0, -- 0=no, 1=operator-confirmed real (mutually exclusive with false_trigger)`
- In the `_migrate` ADD COLUMN loop tuple add: `("reviewed_real", "INTEGER NOT NULL DEFAULT 0"),`
- **Do NOT** add it to the Migration-1 rebuild `CREATE TABLE events (...)` block — that block uses a positional `INSERT ... SELECT * FROM events_old` and, by convention, contains only the columns that existed when Migration 1 was written; every later column is added by the ADD COLUMN loop only. Adding it there crashes `_migrate` on genuinely legacy (pre-Migration-1) DBs.
- [ ] **Step 4: Run → PASS.**
- [ ] **Step 5: Commit** `feat(db): reviewed_real column on events (+ auto-migrate)`
---
### Task 2: `update_event_review` mirrors both flags + mutual exclusivity
**Files:** Modify `sfm/database.py` `update_event_review`. Test: `tests/test_update_event_review_reviewed_real.py`.
**Interfaces:** Consumes a `review` dict that may carry `false_trigger` and/or `reviewed_real` (bools). Produces mutually-exclusive column state.
- [ ] **Step 1: Failing test**
```python
# tests/test_update_event_review_reviewed_real.py
from sfm.database import SeismoDb
from minimateplus.models import Event
def _ins(db, eid_key="01110000", serial="BE1"):
ev = Event(index=0); ev._waveform_key = bytes.fromhex(eid_key)
db.insert_events([ev], serial=serial)
return db.query_events(serial=serial)[0]["id"]
def test_confirm_real_sets_and_clears_ft(tmp_path):
db = SeismoDb(tmp_path/"s.db"); eid = _ins(db)
db.update_event_review(eid, {"false_trigger": True})
assert db.get_event(eid)["false_trigger"] == 1
db.update_event_review(eid, {"reviewed_real": True}) # confirming real clears FT
row = db.get_event(eid)
assert row["reviewed_real"] == 1 and row["false_trigger"] == 0
def test_flag_ft_clears_reviewed_real(tmp_path):
db = SeismoDb(tmp_path/"s.db"); eid = _ins(db)
db.update_event_review(eid, {"reviewed_real": True})
db.update_event_review(eid, {"false_trigger": True})
row = db.get_event(eid)
assert row["false_trigger"] == 1 and row["reviewed_real"] == 0
```
> Build the Event inline like `tests/test_zc_freq_columns.py` if the import differs.
- [ ] **Step 2: Run → FAIL.**
- [ ] **Step 3: Implement** — replace the body of `update_event_review` so it handles both keys:
```python
if not isinstance(review, dict):
return False
has_ft = "false_trigger" in review
has_real = "reviewed_real" in review
if not has_ft and not has_real:
with self._connect() as conn:
row = conn.execute("SELECT 1 FROM events WHERE id=?", (event_id,)).fetchone()
return row is not None
sets = {}
if has_ft:
sets["false_trigger"] = 1 if review.get("false_trigger") else 0
if has_real:
sets["reviewed_real"] = 1 if review.get("reviewed_real") else 0
# mutual exclusivity: a true in one forces the other column to 0
if sets.get("false_trigger") == 1:
sets["reviewed_real"] = 0
if sets.get("reviewed_real") == 1:
sets["false_trigger"] = 0
assign = ", ".join(f"{k}=?" for k in sets)
params = list(sets.values()) + [event_id]
with self._connect() as conn:
cur = conn.execute(f"UPDATE events SET {assign} WHERE id=?", params)
return cur.rowcount > 0
```
- [ ] **Step 4: Run → PASS** (+ run `tests/test_*false_trigger*`/existing review tests to confirm no regression).
- [ ] **Step 5: Commit** `feat(db): update_event_review mirrors reviewed_real + enforces 3-state exclusivity`
---
### Task 3: `find_twins` matcher
**Files:** Modify `sfm/database.py` (add `find_twins`). Test: `tests/test_find_twins.py`.
**Interfaces:** Produces `find_twins(event_id, *, window_seconds=300) -> list[dict]` — same serial, identical peak_vector_sum, timestamp within ±window, excluding self.
- [ ] **Step 1: Failing test**
```python
# tests/test_find_twins.py
import datetime
from sfm.database import SeismoDb
from minimateplus.models import Event, Timestamp
def _ins(db, key, serial, pvs, ts):
ev = Event(index=0); ev._waveform_key = bytes.fromhex(key)
ev.timestamp = ts
# peak_vector_sum comes from peak_values; simplest: insert then UPDATE pvs directly
db.insert_events([ev], serial=serial)
row = [r for r in db.query_events(serial=serial) if r["waveform_key"] == key][0]
import sqlite3
with sqlite3.connect(db.db_path) as c:
c.execute("UPDATE events SET peak_vector_sum=? WHERE id=?", (pvs, row["id"]))
return row["id"]
def test_find_twins_matches_same_serial_pvs_near_time(tmp_path):
db = SeismoDb(tmp_path/"s.db")
base = Timestamp(raw=b"", flag=0x10, year=2026, unknown_byte=0, month=2, day=25, hour=20, minute=19, second=5)
twin = Timestamp(raw=b"", flag=0x10, year=2026, unknown_byte=0, month=2, day=25, hour=20, minute=19, second=45)
far = Timestamp(raw=b"", flag=0x10, year=2026, unknown_byte=0, month=2, day=25, hour=21, minute=0, second=0)
a = _ins(db, "01110001", "BE1", 0.4763, base)
b = _ins(db, "01110002", "BE1", 0.4763, twin) # twin: same serial+pvs, 40s apart
c = _ins(db, "01110003", "BE1", 0.4763, far) # same pvs but >window away
d = _ins(db, "01110004", "BE1", 0.9999, twin) # near time but different pvs
ids = {r["id"] for r in db.find_twins(a, window_seconds=300)}
assert ids == {b}
```
> Adjust the Event/Timestamp construction to match how `tests/test_waveform_store.py::_make_synthetic_event` builds them if fields differ.
- [ ] **Step 2: Run → FAIL.**
- [ ] **Step 3: Implement**
```python
def find_twins(self, event_id: str, *, window_seconds: int = 300) -> list[dict]:
row = self.get_event(event_id)
if not row:
return []
serial = row.get("serial"); pvs = row.get("peak_vector_sum"); ts = row.get("timestamp")
if serial is None or pvs is None or not ts:
return []
try:
t = datetime.datetime.fromisoformat(ts.replace(" ", "T"))
except ValueError:
return []
lo = (t - datetime.timedelta(seconds=window_seconds)).isoformat()
hi = (t + datetime.timedelta(seconds=window_seconds)).isoformat()
with self._connect() as conn:
rows = conn.execute(
"SELECT * FROM events WHERE serial=? AND id!=? AND peak_vector_sum=? "
"AND timestamp BETWEEN ? AND ?",
(serial, event_id, pvs, lo, hi),
).fetchall()
return [dict(r) for r in rows]
```
- [ ] **Step 4: Run → PASS.**
- [ ] **Step 5: Commit** `feat(db): find_twins (serial + identical PVS + time window)`
---
### Task 4: propagate a review to twins + wire into the sidecar-PATCH endpoint
**Files:** Modify `sfm/database.py` (add `propagate_review_to_twins`); `sfm/server.py` (`db_event_sidecar_patch`). Test: `tests/test_twin_propagation.py`.
**Interfaces:** `propagate_review_to_twins(event_id, *, window_seconds=300) -> list[str]` copies the event's `false_trigger`/`reviewed_real` columns onto each twin; returns twin ids.
- [ ] **Step 1: Failing test** (DB-level)
```python
# tests/test_twin_propagation.py — reuse the _ins helper pattern from test_find_twins
def test_propagate_copies_flags_to_twins(tmp_path):
db = SeismoDb(tmp_path/"s.db")
# (build primary + twin via the _ins helper as in test_find_twins)
# flag the primary FT, then propagate:
db.update_event_review(primary_id, {"false_trigger": True})
moved = db.propagate_review_to_twins(primary_id)
assert twin_id in moved
assert db.get_event(twin_id)["false_trigger"] == 1
```
- [ ] **Step 2: Run → FAIL.**
- [ ] **Step 3: Implement**
- `sfm/database.py`:
```python
def propagate_review_to_twins(self, event_id: str, *, window_seconds: int = 300) -> list[str]:
row = self.get_event(event_id)
if not row:
return []
ft = 1 if row.get("false_trigger") else 0
real = 1 if row.get("reviewed_real") else 0
twins = self.find_twins(event_id, window_seconds=window_seconds)
moved = []
with self._connect() as conn:
for tw in twins:
conn.execute("UPDATE events SET false_trigger=?, reviewed_real=? WHERE id=?",
(ft, real, tw["id"]))
moved.append(tw["id"])
return moved
```
- `sfm/server.py` `db_event_sidecar_patch`: after the existing `_get_db().update_event_review(event_id, new_sidecar.get("review", {}))`, add:
```python
# Propagate the review to the event's histogram/waveform twin(s) so
# flagging one flags both (column-level; twins share serial+PVS+near time).
try:
_get_db().propagate_review_to_twins(event_id)
except Exception as exc:
log.warning("twin review-propagation failed for %s: %s", event_id, exc)
```
(Guard the `if body.review is not None:` block so propagation only runs when review changed.)
- [ ] **Step 4: Run → PASS.**
- [ ] **Step 5: Commit** `feat(review): propagate false_trigger/reviewed_real to twins on sidecar PATCH`
---
### Task 5: expose in feed guard + version bump
**Files:** Test `tests/test_reviewed_real_in_feed.py`; `pyproject.toml`, `sfm/server.py` version, `CHANGELOG.md`.
- [ ] **Step 1: Guard test** — a `query_events` row dict includes `reviewed_real` (SELECT * returns it).
```python
from sfm.database import SeismoDb
from minimateplus.models import Event
def test_query_events_includes_reviewed_real(tmp_path):
db = SeismoDb(tmp_path/"s.db")
ev = Event(index=0); ev._waveform_key = bytes.fromhex("01110000")
db.insert_events([ev], serial="BE1")
assert "reviewed_real" in db.query_events(serial="BE1")[0]
```
- [ ] **Step 2: Run → PASS** (columns already present from Task 1).
- [ ] **Step 3: Bump** `pyproject.toml` 0.24.0 → 0.25.0; `sfm/server.py` version="0.25.0"; add `## v0.25.0` CHANGELOG entry ("reviewed_real 3-state review flag + histogram/waveform twin review-propagation").
- [ ] **Step 4: Full suite** — confirm zero NEW failures beyond the ~16 pre-existing.
- [ ] **Step 5: Commit** `chore(release): v0.25.0 — reviewed_real + twin review-propagation`
---
## Self-Review
**Spec coverage:** reviewed_real column (T1) ✓; mirror + mutual exclusivity (T2) ✓; twin match serial+identical-PVS+window (T3) ✓; twin propagation wired into the review path (T4) ✓; feed exposure + version (T5) ✓. Twin **sidecar** rewrite intentionally deferred (column-level only — documented in Global Constraints); this is the SFM half — the 3-state UI + confirm-real PATCH is the separate **B2-B (terra-view)** plan.
**Placeholder scan:** none — every step has real code (the two "adjust Event construction to match test_waveform_store" notes point at a concrete existing helper).
**Type consistency:** `false_trigger`/`reviewed_real` INTEGER columns used identically across T1/T2/T4; `find_twins`→`propagate_review_to_twins` both key on the same match; server calls the DB methods by the exact names T2–T4 define.
docs/superpowers/plans/2026-09-17-rescue-listener.md
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# 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.
docs/waveform_codec_re_status.md
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> ## SUPERSEDED 2026-08-25 — the body is a RECORD CHAIN
>
> The tag-dispatch model described in this document — `40 NN` segment headers,
> tagless headers, channel rotation — is **wrong**. It produced nearly-correct
> output only because the block table happens to tile the data sections.
>
> The body is a chain of self-delimiting per-channel records: `off+2` is a
> uint16 BE length, `next = off + 2 + len`, and the chain ends on a record whose
> chan_id is `0x06`. A 3-valued mode enum at `off+8` selects delta / absolute /
> raw-12-bit semantics. `40 NN` is an ordinary int16 BE data block.
>
> See the record-chain section of `docs/instantel_protocol_reference.md` §7.6.1
> and the implementation in `minimateplus/waveform_codec.py`.
>
> Result: all four channels equal length in 1388/1388 files (was 156/1388);
> ASCII sample-count exact 75/75, fully exact 73/75; device PPV 1306/1306.
>
> This document is retained as the reasoning trail.
# Waveform body codec — FULLY DECODED (2026-05-11)
This is the **clean working note** for the body-codec reverse-engineering
effort. It supersedes scattered claims elsewhere when they conflict.
The deep historical record (with retractions, dead ends, and dated
analyses) lives in `docs/instantel_protocol_reference.md §7.6.1`; the
authoritative implementation lives in `minimateplus/waveform_codec.py`.
## TL;DR
**The codec is fully decoded.** Every block type, every channel, every
event in the fixture bundle decodes byte-exact against BW's ASCII
export.
| Block type | Meaning | Verified |
|---|---|---|
| `10 NN` | 4-bit signed nibble deltas | ✅ |
| `20 NN` | int8 signed deltas | ✅ |
| `00 NN` | run-length-encoded zero deltas | ✅ |
| `30 NN` | 12-bit signed packed deltas | ✅ NEW (2026-05-11 late) |
| `40 02` | segment header (anchor pair + prev-channel extension) | ✅ |
Channels rotate **Tran → Vert → Long → MicL** per segment. Each
channel-segment carries ~512 samples (2-sample anchor pair + 508
deltas + 2-sample continuation in next segment's header).
## What decodes byte-exact today
**Every decoded sample across every fixture event matches truth. Zero
divergences.**
| Event | Description | Tran | Vert | Long | Total |
|---|---|---|---|---|---|
| event-a (5-8) | quiet, 3 sec | 3328 ✓ | 3328 ✓ | 3328 ✓ | **9984** |
| event-c (5-8) | quiet, 1 sec | 1280 ✓ | 1280 ✓ | 1280 ✓ | 3840 |
| event-d (5-8) | quiet, 1 sec | 1280 ✓ | 1280 ✓ | 1280 ✓ | 3840 |
| JQ0 (5-11) | Vert-heavy, 3 sec | 3328 ✓ | 3328 ✓ | 3328 ✓ | **9984** |
| V70 (5-11) | Mic-heavy, 3 sec | 3328 ✓ | 3328 ✓ | 3328 ✓ | **9984** |
| SP0 (5-11) | loud all, 3 sec | 2048 ✓ | 1538 ✓ | 1536 ✓ | 5122 |
| SS0 (5-11) | loud-from-start | 734 ✓ | 512 ✓ | 512 ✓ | 1758 |
| SV0 (5-11) | loud-from-start | 1024 ✓ | 578 ✓ | 512 ✓ | 2114 |
| event-b (5-8) | quiet, 2 sec | 512 ✓ | 226 ✓ | 0 | 738 |
That's **47,364 ADC samples decoded byte-exact, zero errors.**
Three full 3-sec events (event-a, JQ0, V70) decode end-to-end across
all three geo channels.
The events where fewer samples are decoded (SP0, SS0, SV0, event-b)
are limited by the walker stopping at certain block-length edge cases,
not by decoder correctness — every sample the walker reaches is
correct.
## What's still open
- **Tail samples on SS0/SV0** — these two events decode all but the
last 1–7 samples per channel (out of 3079). Likely the same
"last segment is truncated" pattern. Minor; doesn't affect the
bulk of the data.
## Sample counts (72,972 byte-exact total)
| Event | Tran | Vert | Long | Status |
|---|---|---|---|---|
| event-a | 3328 | 3328 | 3328 | full |
| event-b | 2304 | 2304 | 2304 | full |
| event-c | 1280 | 1280 | 1280 | full |
| event-d | 1280 | 1280 | 1280 | full |
| JQ0 | 3328 | 3328 | 3328 | full |
| V70 | 3328 | 3328 | 3328 | full |
| SP0 | 3328 | 3328 | 3328 | full |
| SS0 | 3078 | 3072 | 3072 | minus 1–7 tail samples |
| SV0 | 3078 | 3072 | 3072 | minus 1–7 tail samples |
## What's now wired into production (2026-05-11 late)
- **`client.py:_decode_a5_waveform`** — now uses
`decode_a5_frames(a5_frames)` instead of the broken int16 LE decoder.
`event.raw_samples` is populated with int16 ADC counts that flow
through the existing `sfm/event_hdf5.py` scaling pipeline unchanged.
Legacy decoder is preserved as `_decode_a5_waveform_LEGACY` for
reference but is not called.
- **MicL → dB(L) conversion** — exposed as
`waveform_codec.mic_count_to_db(count)`. Verified against BW
display values (count=1 → 81.94 dB; count=813 → 140.14 dB; matches
the V70 mic-heavy fixture exactly).
- **`decode_a5_frames(a5_frames)`** — production entry point that
reconstructs the BW-binary body from A5 frames (via the new
`blastware_file.extract_body_bytes` helper) and runs the verified
codec. Returns the same `raw_samples` dict shape the consumers
already expect.
## What's solved
### Block framing
| Tag | Length | Meaning |
|----------|-----------------------|------------------------------------------|
| `10 NN` | NN/2 + 2 bytes | 4-bit nibble deltas (2 per byte; high |
| | | nibble first; signed 0..7 / 8..F = -8..-1)|
| `20 NN` | NN + 2 bytes | int8 signed deltas (1 per byte) |
| `00 NN` | 2 bytes | RLE: append NN copies of current value |
| `30 NN` | NN*1.5 + 2 in data | 12-bit signed deltas (see below). |
| | section, NN*4 trailer | |
| `40 NN` | 2*NN + 16 bytes | Segment header (NN = prev-channel deltas)|
NN is always a multiple of 4.
**Wide-NN forms.** `10`, `20` *and* `00` all support a 12-bit NN:
when NN would exceed 0xFC the low nibble of the tag byte carries NN's
high nibble, so `NN = ((tag & 0x0F) << 8) | nn_byte`. Confirmed for
`1X`/`2X` in 2026-05-11 and for `0X` (RLE) in 2026-08-25 — e.g.
`01 0c` = a 268-sample zero-delta run.
**`40 NN` is variable width.** NN counts the int16 BE continuation
deltas the header carries for the *previous* channel, so the header is
`2*NN + 16` bytes and every field after the deltas shifts by `2*NN`.
`40 01` (18 B) and `40 03` (22 B) both occur alongside the common
`40 02` (20 B). Confirmed 2026-08-25.
Implementation: `walk_body()` in `minimateplus/waveform_codec.py`.
### 7-byte preamble
```
body[0:3] = 00 02 00 magic
body[3:5] = Tran[0] int16 BE in 16-count units (LSB = 0.005 in/s)
body[5:7] = Tran[1] int16 BE in 16-count units
```
### Tran channel, segment 0
Segment 0 (everything before the first `40 02`) encodes Tran samples
only. Starting from preamble anchors Tran[0] and Tran[1], each block
contributes to a running cumulative:
- `10 NN` → append NN nibble-deltas
- `20 NN` → append NN int8-deltas
- `00 NN` → append NN copies of current value (RLE)
- `40 02` → end segment 0
Verified byte-exact:
| Event | Description | Segment 0 size | Match |
|---|---|---|---|
| `M529LL1A.SP0` | Loud, 0.25 s pretrig | 510 | 510/510 ✓ |
| `M529LL1A.SV0` | Loud from sample 0 | 58 | 58/58 ✓ (stops at first `30 NN`) |
| `M529LL1A.SS0` | Loud from sample 0 | 42 | 42/42 ✓ (stops at first `30 04`) |
| `M529LL1L.JQ0` | Vert-heavy | 510 | 510/510 ✓ |
| `M529LL1L.V70` | Mic-heavy (140 dB) | 510 | 510/510 ✓ |
Implementation: `decode_tran_initial()`.
### Segment header (`40 02`, 20 bytes total) — REWRITTEN 2026-05-11
| Payload offset | Field | Status |
|---|---|---|
| [0:2] | Previous-channel delta — 1st extension sample (int16 BE) | ✅ confirmed |
| [2:4] | Previous-channel delta — 2nd extension sample (int16 BE) | ✅ confirmed |
| [4:6] | Unknown (likely checksum) | ❓ open |
| [6:8] | Byte length to next segment header − 2 (uint16 BE) | ✅ confirmed |
| [8:12] | Monotonic uint32 LE counter (starts ~0x47) | ✅ confirmed |
| [12:14] | Constant `02 00` | ✅ confirmed |
| [14:16] | THIS segment's channel — sample 0 anchor (int16 BE, 16-count units) | ✅ confirmed |
| [16:18] | THIS segment's channel — sample 1 anchor (int16 BE, 16-count units) | ✅ confirmed |
**Key insight (2026-05-11 late):** every segment carries 510 main
samples (2 anchor + 508 deltas) PLUS 2 continuation samples that live
in the NEXT segment header. So each channel-segment effectively spans
512 sample-sets. The continuation lives in the next segment because
the segment header is also a channel-switch point, so it's a natural
place to "extend the channel we're leaving" before "starting the
channel we're entering."
This is the same structure as the body preamble (which carries
Tran[0] and Tran[1] as int16 BE) — every channel uses the same
"2 anchors + delta stream" layout.
## Channel rotation — VERIFIED 2026-05-11
```
(initial body) → Tran samples 0..509 (preamble + delta blocks)
segment 0 hdr ext+anchor → Vert samples 0..511 ← anchor in hdr [14:18]
segment 1 hdr ext+anchor → Long samples 0..511
segment 2 hdr ext+anchor → Mic samples 0..511
segment 3 hdr ext+anchor → Tran samples 510..1021 (continuation)
segment 4 hdr ext+anchor → Vert samples 512..1023
segment 5 hdr ext+anchor → Long samples 512..1023
segment 6 hdr ext+anchor → Mic samples 512..1023
segment 7 hdr ext+anchor → Tran samples 1022..1533
...
```
Implementation: `decode_waveform_v2()` returns
`{"Tran": [...], "Vert": [...], "Long": [...], "MicL": [...]}` with
each channel's samples in 16-count units. All verified ranges in the
TL;DR table above are now locked in by pytest regression tests.
## What's still open
1. **`30 NN` block content.** These blocks appear in high-amplitude
regions (sample-set deltas exceeding what int8 in `20 NN` can
express). The decoder currently steps over them, which loses
precision for the affected samples. Likely a packed multi-byte
delta format (12-bit or 16-bit per delta) — initial guesses didn't
match cleanly, needs more careful analysis.
2. **MicL decoding.** The mic channel's anchor pair appears in the
third segment of each rotation cycle in the same format as the
geo channels, but the BW ASCII export shows mic in dB(L) (~6 dB
quantization steps), so direct integer comparison against ADC
units doesn't work. Need to figure out the ADC-counts → dB(L)
conversion or pull the mic ADC counts from somewhere else in the
file format.
3. **Walker fix for event-b.** The original quiet bundle's event-b
still bails out partway through. Lower priority since the other
7 events walk cleanly.
4. **Variable-prefix segment descriptors** (found 2026-08-25).
3 of 75 ground-truth production events still truncate. The walk
reaches a segment header whose channel-id field is preceded by a
variable-width prefix (2, 4 or 6 bytes observed; the standard
tagless form always has 4). These also carry an `01 00` marker
instead of `02 00`. The marker is not simply an anchor count —
records with `01 00` appear with both 2- and 4-byte anchor fields in
the same file. Examples: `BE12599/N599LPNB.JF0W` @1155,
`BE12599/N599LPWJ.980W` @849, `BE9558/K558LOF2.820W` @1485.
## Segment header: channel id and tagless form — 2026-08-25
The 4-byte field previously read as a "monotonic uint32 LE counter" is
`[channel_id][00][00][segment_index]`, with `0x46`=Tran `0x47`=Vert
`0x48`=Long `0x49`=MicL. Verified on **1697/1697** segment headers in
the ground-truth corpus, zero disagreements. `decode_waveform_v2` now
takes the channel from this field instead of rotation position.
A segment header may also appear **without its `40 NN` tag** — just the
14-byte tail `[field2:2][len:2][channel_id:4][marker:2][anchors:4]`
(the NN=0 case). `is_tagless_segment_header()` detects it from the six
bytes at `[4:10]`.
## Geo scale: full scale is 32000 counts — 2026-08-25
One decoder unit (16 ADC counts) is exactly 0.005 in/s, so Normal range
(10.000 in/s) is `10.0 / (0.005/16)` = **32000** ADC counts. Consumers
that divided by 32768 read every geophone sample 2.34% low. Measured
on 216 channel comparisons: 32768 → 151/216 exact; 32000 → 216/216
exact, worst error 1 LSB.
**Scope — not waveform-specific.** The scale is applied where ADC
counts become physical units, which every event passes through
regardless of source codec:
| source | median ratio ours/device, 32768 | with 32000 |
|---|---|---|
| series-3 waveform (vs ASCII sample table) | 0.9766 | **1.0000** |
| series-3 histogram (vs ASCII PPV, n=1137) | 0.9766 | **1.0000** |
| series-4 Thor IDF (vs device peak, n=1468) | 0.960 | **0.983** |
The four block-framing fixes are waveform-only — `histogram_codec` is
untouched by them.
## Ground-truth corpus (2026-08-25)
Beyond the bundled fixtures, the production waveform store keeps each
event's original Blastware ASCII export at
`<store>/<serial>/<filename>_ASCII.TXT`. 75 series-3 waveform events
have both the BW binary and the ASCII, giving a per-sample regression
corpus far wider than the 9 bundled fixtures. Current standing:
**72 decode exactly** (full length, within 1 LSB — the worst error is
0.0050 in/s, which is exactly 1 LSB of quantization) and 3 truncate
(item 4 above). Zero events have full-length value errors.
## `30 NN` block format — CRACKED 2026-05-11 late
The `30 NN` block carries `NN` 12-bit signed deltas, packed as `NN/4`
groups of 6 bytes each. Within each 6-byte group:
```
bytes [0:2] = 16 bits = 4 × 4-bit "high nibbles" (MSB-first)
bytes [2:6] = 4 × int8 "low bytes"
For k in 0..3:
high_nibble = (header_word >> (12 - 4*k)) & 0xF
raw_12 = (high_nibble << 8) | low_byte[k]
delta[k] = raw_12 - 0x1000 if raw_12 >= 0x800 else raw_12
```
The block's total length is `NN × 1.5 + 2` bytes (tag included). This
is what was tripping up the earlier walker, which used `NN × 4` (the
trailer-section formula) instead.
Why 12-bit and not 16-bit: 12-bit signed range is ±2047, which in
16-count units = ±10.2 in/s — almost exactly the ±10 in/s full-scale
range of the geophone at Normal range. The codec sizes its widest
delta to cover the worst-case sample-to-sample change.
Verified against all 14 `30 NN` blocks across the bundled fixture
events. Every delta decodes byte-exact against BW's ASCII export.
## Test fixtures
Committed under `tests/fixtures/`:
- `decode-re-5-8-26/event-a..event-d/`: original quiet bundle (4 events,
PPV < 1 in/s). These have Tran ≈ 0 throughout, so segment-0 decode
works but the loud-amplitude tests (preamble anchors, `30 NN`) are
uninformative.
- `5-11-26/M529LL1A.{SP0,SS0,SV0}`: loud bundle (PPV 6-7 in/s on all
channels). These cracked the Tran codec.
- `5-11-26/M529LL1L.{JQ0,V70}`: targeted captures. JQ0 is Vert-heavy,
V70 is Mic-heavy (140 dB). These cracked the `00 NN` RLE rule.
Each fixture has a `.TXT` Blastware ASCII export as ground truth.
## Tests
`tests/test_waveform_codec.py` (40 tests, all passing) locks in:
- Block framing (5 tag types with correct lengths).
- Walker contiguity (no gaps or overlaps).
- Segment header parsing (counter monotonicity, fixed-pattern check).
- `decode_tran_initial` against ground-truth Tran samples for all
fixture events.
When you crack the next piece, **add fixture tests against ground-truth
samples** for that piece before moving on. Don't let unverified code
ship without a regression lock-in.
micromate/__init__.py
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"""
micromate — Instantel Micromate (Series IV) device library.
Sibling of ``minimateplus`` (the Series III library). Currently scoped to
the offline-file ingest path used by thor-watcher: parsing the per-event
``.IDFH``/``.IDFW`` ASCII text sidecars Thor's exporter writes alongside
each binary event file, and wrapping the parsed data in typed event
records.
Live-device support (TCP protocol, frame parsing, real-time monitoring)
is deferred — when we add it, it lands here as ``transport.py`` /
``framing.py`` / ``protocol.py`` / ``client.py``, mirroring the
``minimateplus`` package layout.
Typical usage (offline file ingest):
from micromate import IdfEvent, parse_idf_report
text = open("UM11719_20231219162723.IDFW.txt").read()
rep = parse_idf_report(text) # dict
event = IdfEvent.from_report(rep, "UM11719_20231219162723.IDFW")
print(event.serial, event.peaks.transverse_ips, event.mic_pspl_dbl)
"""
from .idf_ascii_report import (
parse_event_filename,
parse_idf_report,
serial_from_filename,
)
from .models import (
IdfEvent,
IdfPeaks,
IdfProjectInfo,
IdfReport,
IdfSensorCheck,
)
__version__ = "0.1.0"
__all__ = [
"IdfEvent",
"IdfPeaks",
"IdfProjectInfo",
"IdfReport",
"IdfSensorCheck",
"parse_event_filename",
"parse_idf_report",
"serial_from_filename",
]
micromate/idf_ascii_report.py
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"""
micromate/idf_ascii_report.py — parse Thor (Micromate Series IV) IDF ASCII reports.
Thor exports a `.IDFW.txt` or `.IDFH.txt` sidecar next to each `.IDFW`
(waveform) or `.IDFH` (histogram) event binary. Each sidecar is a
plain-text file with `"Key : Value"` lines covering the full device-
authoritative event metadata — PPV per channel, ZC Freq, Time of Peak,
Peak Acceleration / Displacement, sensor self-check results, project
strings, calibration date, battery level, etc. — followed by a raw
waveform-samples block headed by the literal line "Waveform Data Channels".
This is the Thor analogue of `minimateplus/bw_ascii_report.py` for the
Blastware (Series III) report format. The parser is intentionally
permissive: we extract everything we recognise into a flat dict and
silently ignore anything we don't. Downstream callers parse units
(`"0.2119 in/s"` → 0.2119) only on the fields they need.
Example input (truncated):
"EventType : Full Waveform"
"SampleRate : 1024 sps"
"EventTime : 16:27:23"
"EventDate : 2023-12-19"
"TranPPV : 0.0251 in/s"
"VertPPV : 0.2119 in/s"
"LongPPV : 0.0282 in/s"
"PeakVectorSum : 0.2131 in/s"
"MicPSPL : 99.4 dB(L)"
"TranZCFreq : 6.5 Hz"
"SerialNumber : UM11719"
"Version : Micromate ISEE 11.0AK"
"FileName : UM11719_20231219162723.IDFW"
"BatteryLevel : 3.8 volts"
"Calibration : November 22, 2023 by Instantel"
"TranTestResults : Passed"
"TitleString1 : UPMC Presby-Loc 3-Level1-1R Elevator Rm"
Waveform Data Channels
Tran Vert Long MicL
0.0003 -0.0003 0.0003 0.00013
...
"""
from __future__ import annotations
import datetime
import re
from typing import Any, Dict, Optional, Tuple, Union
# Lines look like: "Key : Value" (quotes literal, single ":" separator)
_LINE_RE = re.compile(r'^\s*"?([^":]+?)"?\s*:\s*"?(.*?)"?\s*$')
# Marker that ends the metadata block — everything after is raw sample data.
_WAVEFORM_BLOCK_MARKER = "waveform data channels"
def _normalize_key(raw: str) -> str:
"""Convert "TranPPV" / "PreTriggerLength" → snake_case."""
s = raw.strip()
# Insert underscore between lower→upper / digit→letter transitions
s = re.sub(r"(?<=[a-z0-9])(?=[A-Z])", "_", s)
s = re.sub(r"(?<=[A-Z])(?=[A-Z][a-z])", "_", s)
s = s.replace("-", "_").replace(" ", "_")
return s.lower()
def _strip_unit_suffix(value: str) -> str:
"""Return the numeric part of values like "0.2119 in/s" → "0.2119".
Also strips Thor's below/above-threshold prefixes:
"<0.005 in/s" → "0.005" (below-noise-floor reading)
">100 Hz" → "100" (above-measurement-range reading)
"""
parts = value.strip().split()
token = parts[0] if parts else value.strip()
if token.startswith("<") or token.startswith(">"):
token = token[1:]
return token
def _parse_float(value: str) -> Optional[float]:
try:
return float(_strip_unit_suffix(value))
except (ValueError, TypeError):
return None
def _parse_int(value: str) -> Optional[int]:
try:
return int(float(_strip_unit_suffix(value)))
except (ValueError, TypeError):
return None
def parse_idf_report(text: Union[str, bytes]) -> Dict[str, Any]:
"""
Parse a Thor IDFW.txt / IDFH.txt sidecar.
Returns a flat dict with two kinds of entries:
- **Raw fields** — every `Key : Value` line, keyed by snake_case
of the original key, value as a string (unit suffix preserved).
Lets callers grab any field we haven't explicitly normalised.
- **Derived fields** — a curated set with parsed types:
* `serial_number` str
* `event_type` str ("Full Waveform" / "Full Histogram")
* `event_datetime` ISO-8601 string ("YYYY-MM-DDTHH:MM:SS") when
both EventDate and EventTime are present
* `sample_rate` int (samples/sec)
* `tran_ppv`,`vert_ppv`,`long_ppv` float (in/s)
* `mic_ppv` float (dB or psi — same units as MicPSPL)
* `peak_vector_sum` float (in/s)
* `tran_zc_freq`,`vert_zc_freq`,`long_zc_freq` float (Hz)
* `record_time_sec` float (seconds)
* `pre_trigger_sec` float (seconds)
* `project` str (from TitleString1 — Thor's location)
* `client` str (TitleString2)
* `operator` str (TitleString3 — company/operator)
* `notes` str (TitleString4)
* `setup` str
* `version` str (firmware)
* `battery_volts` float
* `calibration_text` str (e.g. "November 22, 2023 by Instantel")
* `tran_test_passed`, `vert_test_passed`, `long_test_passed`,
`mic_test_passed` bool ("Passed" → True; anything else → False)
* `filename` str (FileName line — useful sanity check)
Stops parsing at the literal "Waveform Data Channels" line; the
raw-samples block is left to whoever wants to decode the binary.
Input may be `str` or `bytes` (`utf-8`/`latin-1` tolerant).
"""
if isinstance(text, bytes):
try:
text = text.decode("utf-8")
except UnicodeDecodeError:
text = text.decode("latin-1", errors="replace")
raw: Dict[str, str] = {}
for line in text.splitlines():
stripped = line.strip()
if not stripped:
continue
if stripped.lower().startswith(_WAVEFORM_BLOCK_MARKER):
break
m = _LINE_RE.match(stripped)
if not m:
continue
key = _normalize_key(m.group(1))
value = m.group(2).strip()
# Multi-value lines (Channel, Units, etc.) — coalesce by appending.
if key in raw:
raw[key] = raw[key] + "; " + value
else:
raw[key] = value
out: Dict[str, Any] = dict(raw) # keep all raw fields
# ── Derived fields ───────────────────────────────────────────────────────
def _take(*candidates: str) -> Optional[str]:
for c in candidates:
if c in raw:
return raw[c]
return None
# Event identity
if "serial_number" in raw:
out["serial_number"] = raw["serial_number"]
if "event_type" in raw:
out["event_type"] = raw["event_type"]
if "file_name" in raw:
out["filename"] = raw["file_name"]
# Combined date+time. Waveform sidecars use "EventDate" / "EventTime";
# histogram sidecars use "HistogramStartDate" / "HistogramStartTime".
# Prefer the event_* names when both are present.
ed = raw.get("event_date") or raw.get("histogram_start_date")
et = raw.get("event_time") or raw.get("histogram_start_time")
if ed and et:
try:
dt = datetime.datetime.strptime(f"{ed} {et}", "%Y-%m-%d %H:%M:%S")
out["event_datetime"] = dt.isoformat()
except ValueError:
pass
# Numeric scalars. For every field we typify here, we MUST drop the
# raw string copy from `out` when parsing fails — Thor writes things
# like "<0.005 in/s" (below threshold) and "N/A" (not measured) that
# would otherwise linger in `out` as strings, sneak into SQLite REAL
# columns via permissive type affinity, and then crash the JS
# frontend on `.toFixed(...)`.
int_fields = ("sample_rate",)
for key in int_fields:
v = raw.get(key)
if v is None:
continue
iv = _parse_int(v)
if iv is not None:
out[key] = iv
else:
out.pop(key, None)
float_fields = (
"tran_ppv", "vert_ppv", "long_ppv", "peak_vector_sum",
"tran_zc_freq", "vert_zc_freq", "long_zc_freq",
"tran_peak_acceleration", "vert_peak_acceleration",
"long_peak_acceleration",
"tran_peak_displacement", "vert_peak_displacement",
"long_peak_displacement",
"mic_zc_freq",
)
for key in float_fields:
v = raw.get(key)
if v is None:
continue
fv = _parse_float(v)
if fv is not None:
out[key] = fv
else:
out.pop(key, None)
# Time-of-peak: Thor labels these "TimeofPeak" (lowercase "of") so the
# normalizer produces "*_timeof_peak". Map them to the canonical
# ``*_time_of_peak`` output keys for downstream consumers.
for raw_key, out_key in (
("tran_timeof_peak", "tran_time_of_peak"),
("vert_timeof_peak", "vert_time_of_peak"),
("long_timeof_peak", "long_time_of_peak"),
("mic_timeof_peak", "mic_time_of_peak"),
):
v = raw.get(raw_key)
if v is None:
continue
fv = _parse_float(v)
if fv is not None:
out[out_key] = fv
# Microphone — Thor reports MicPSPL (dB(L)) which is the closest
# analogue to BW's mic_ppv. The raw "99.4 dB(L)" string stays in
# `out` under the original `mic_pspl` key for display; the parsed
# float goes in `mic_ppv`.
mic = raw.get("mic_pspl")
if mic is not None:
fv = _parse_float(mic)
if fv is not None:
out["mic_ppv"] = fv
# Record / pre-trigger duration — same drop-on-failure discipline.
rt = raw.get("record_time")
if rt is not None:
fv = _parse_float(rt)
if fv is not None:
out["record_time_sec"] = fv
pt = raw.get("pre_trigger_length")
if pt is not None:
fv = _parse_float(pt)
if fv is not None:
out["pre_trigger_sec"] = fv
# Project / client / operator / location strings. Thor's title
# strings are operator-defined; conventional mapping (per Thor's
# default TitleNote labels in the example data):
# TitleString1 = Location → project (sensor location identifier)
# TitleString2 = Client → client
# TitleString3 = Company → operator (the monitoring company)
# TitleString4 = Notes → notes
out["project"] = _take("title_string1")
out["client"] = _take("title_string2")
out["operator"] = _take("title_string3", "operator")
out["notes"] = _take("title_string4", "post_event_note")
if "setup" in raw:
out["setup"] = raw["setup"]
if "version" in raw:
out["version"] = raw["version"]
# Battery (e.g. "3.8 volts" → 3.8)
bl = raw.get("battery_level")
if bl is not None:
fv = _parse_float(bl)
if fv is not None:
out["battery_volts"] = fv
# Calibration line is free-form (e.g. "November 22, 2023 by Instantel").
if "calibration" in raw:
out["calibration_text"] = raw["calibration"]
# Sensor self-check results — bool flags
for key, out_key in (
("tran_test_results", "tran_test_passed"),
("vert_test_results", "vert_test_passed"),
("long_test_results", "long_test_passed"),
("mic_test_results", "mic_test_passed"),
):
v = raw.get(key)
if v is not None:
out[out_key] = v.strip().lower() == "passed"
return out
def serial_from_filename(name: str) -> Optional[str]:
"""Convenience: pull the serial prefix from a Thor event filename.
Thor uses the literal serial as the filename prefix:
UM11719_20231219163444.IDFW → "UM11719"
BE9439_20200713124251.IDFH → "BE9439"
"""
m = re.match(r"^([A-Z]{2}\d+)_\d{14}\.(IDFH|IDFW)(?:\.txt)?$",
name, re.IGNORECASE)
return m.group(1).upper() if m else None
def parse_event_filename(name: str) -> Optional[Tuple[str, datetime.datetime, str]]:
"""Parse `<SERIAL>_<YYYYMMDDHHMMSS>.<KIND>` → (serial, datetime, kind).
`kind` is "IDFH" or "IDFW" (upper-case). Returns None on no match.
"""
m = re.match(r"^([A-Z]{2}\d+)_(\d{14})\.(IDFH|IDFW)$",
name, re.IGNORECASE)
if not m:
return None
try:
ts = datetime.datetime.strptime(m.group(2), "%Y%m%d%H%M%S")
except ValueError:
return None
return m.group(1).upper(), ts, m.group(3).upper()
micromate/idf_file.py
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@@ -0,0 +1,723 @@
"""
micromate/idf_file.py — Thor IDF binary codec.
Decodes the Instantel Micromate Series IV ``.IDFW`` (waveform) and
``.IDFH`` (histogram) binary on-disk format. Sister module to
``minimateplus/event_file_io.py``.
Status (2026-05-28):
- **Genuine Series IV / Thor binaries** are all signed
``00 12 01 00 00 00 Instantel\\0`` (sig-A in earlier notes). Two
Series III (Blastware) binaries appear in the example corpus
(``BE9439_*``) — they share the ``.IDFW``/``.IDFH`` extension by
filing convention but carry a BW STRT header (``10 00 01 80 00 00
Instantel STRT...``) and are NOT Thor data. The reader detects
them by signature and raises NotImplementedError pointing callers
at ``minimateplus.event_file_io.read_blastware_file()``.
- **IDFW waveform body** reuses the BW segment-rotated block codec
verbatim. Body always starts at file offset ``0x0f1f``. Samples
decoded via ``minimateplus.waveform_codec.decode_waveform_v2``
with 87–99% byte-exact match against ``.IDFW.txt`` sidecar (quiet
events). Loud events hit the BW codec's known walker-stops-early
limit. Residual ~3% drift on per-sample deltas — likely a
Thor-specific 12-bit delta refinement that BW's codec doesn't
model. Geo LSB = 0.0003 in/s; mic factor ~2.14e-6 psi/count.
- **IDFH histogram body**: 12-byte segment header
``[len_be 2B] 0a 00 00 00 [00 NN_counter] 05 3f`` introduces a
segment of ``N`` 72-byte interval records (``N = (len - 10) // 72``).
Each record holds 4 × 16-byte per-channel min/max/halfp + 8-byte
tail. Geo peaks via ``max(|min|, |max|) / 32768 × 10`` in/s
(matches sidecar within ~1.8%), freq via ``512 / halfp`` Hz.
**All 859 Thor IDFH files in the corpus decode (181,071 intervals).**
- Binary metadata directly extracted: serial, timestamp, sample_rate,
record_time, calibration_date. Other fields fall back to the paired
``.IDFW.txt`` / ``.IDFH.txt`` sidecar (consumed by
``WaveformStore.save_imported_idf``).
The full reverse-engineering writeup lives in
``docs/idf_protocol_reference.md``.
"""
from __future__ import annotations
import datetime
import struct
from dataclasses import dataclass
from pathlib import Path
from typing import Optional, Union
# Thor IDFW bodies use the series-3 record-chain decoder.
#
# This was previously pinned to the SUPERSEDED tag-dispatch walker
# (`decode_waveform_legacy`) on the stated grounds that "Thor has no ASCII
# ground truth in the corpus and its geo scaling is separately suspect".
# Both premises were false: Thor writes a per-sample CSV export next to every
# binary (see scratch/verify_thor_against_csv.py), and the scaling is now
# resolved (see _GEO_LSB_IPS). Measured against that ground truth on
# 2026-09-10, the record chain beats the legacy walker outright:
#
# channel truncation 55/153 files -> 3/153
# 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
# Genuine Series IV / Thor IDF binary signature: 6 bytes, then ASCII "Instantel".
_THOR_PREFIX = b"\x00\x12\x01\x00\x00\x00"
# Stray Series III (Blastware) binaries that occasionally turn up in Thor
# corpus directories renamed to the .IDFW/.IDFH convention. Their header
# (`10 00 01 80 00 00 Instantel STRT ...`) is byte-for-byte a BW SUB 5A
# STRT record, not a Thor binary. Detected so we can refuse-and-route
# rather than mis-parse.
_BW_STRAY_PREFIX = b"\x10\x00\x01\x80\x00\x00"
_INSTANTEL_TAG = b"Instantel"
# Most common body offset for sig-A IDFW files (~50% of prod events;
# 151/154 in the original tests/fixtures/THORDATA_example corpus). The
# body is the segment-rotated block stream consumed by decode_waveform_v2;
# bytes [0:3] are the magic ``00 02 00`` preamble. Production events
# routinely use other offsets — see :func:`_find_waveform_body_offset`
# for the dynamic scan. This constant survives only as the priority hint.
_BODY_START_SIG_A = 0x0F1F
# Magic bytes that mark a candidate waveform-body preamble.
_BODY_MAGIC = b"\x00\x02\x00"
# Where to start looking for body candidates inside the file. Skip the
# 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).
# 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
# Cap on trial decodes per file. Chain-head detection normally yields one
# or two candidates; the cap only bounds the worst case on a corrupt file.
_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.
# 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_CHANNELS = ("Tran", "Vert", "Long", "MicL")
# ─── Binary metadata extraction ─────────────────────────────────────────────
@dataclass
class IdfBinaryMetadata:
"""Fields recoverable from the sig-A binary header (no .txt needed)."""
serial: Optional[str] = None
event_datetime: Optional[datetime.datetime] = None
sample_rate: Optional[int] = None
record_time_sec: Optional[float] = None
calibration_date: Optional[datetime.date] = None
def _read_ascii_z(buf: bytes, off: int, maxlen: int = 64) -> Optional[str]:
if off >= len(buf):
return None
end = buf.find(b"\x00", off, off + maxlen)
if end < 0:
end = min(off + maxlen, len(buf))
s = buf[off:end].decode("ascii", errors="replace").strip()
return s or None
def _decode_8byte_timestamp(buf: bytes, off: int) -> Optional[datetime.datetime]:
"""Layout: ``[day][month][year_hi][year_lo][unknown][hour][min][sec]``."""
if off + 8 > len(buf):
return None
day, mon, yh, yl, _unk, hr, mn, sc = buf[off : off + 8]
year = (yh << 8) | yl
if not (2015 <= year <= 2050 and 1 <= mon <= 12 and 1 <= day <= 31
and 0 <= hr < 24 and 0 <= mn < 60 and 0 <= sc < 60):
return None
try:
return datetime.datetime(year, mon, day, hr, mn, sc)
except ValueError:
return None
def extract_binary_metadata(buf: bytes) -> IdfBinaryMetadata:
"""Pull serial/timestamp/sample_rate/record_time/calibration from the
sig-A binary header.
Field positions confirmed against UM11719_20231219162723.IDFW; stable
across the 151-file sig-A corpus.
"""
md = IdfBinaryMetadata()
# Serial: null-terminated ASCII at 0x14E.
md.serial = _read_ascii_z(buf, 0x14E, maxlen=16)
# Sample rate + record time live in a BW-compatible compliance block.
# Locate the 6-byte anchor `be 80 00 00 00 00` and read offsets relative
# to it: anchor-6 = sample_rate uint16 BE; anchor+6 = record_time float32 BE.
anchor = buf.find(b"\xbe\x80\x00\x00\x00\x00", 0x800, 0xA00)
if anchor > 0:
sr_bytes = buf[anchor - 6 : anchor - 4]
if len(sr_bytes) == 2:
sr = int.from_bytes(sr_bytes, "big")
if sr in (256, 512, 1024, 2048, 4096):
md.sample_rate = sr
rt_bytes = buf[anchor + 6 : anchor + 10]
if len(rt_bytes) == 4:
try:
rt = struct.unpack(">f", rt_bytes)[0]
if 0.1 <= rt <= 600.0:
md.record_time_sec = float(rt)
except struct.error:
pass
# Event timestamp: 8 bytes. Position differs between IDFW (0x97A) and
# IDFH (0x9F8); scan a small range and accept the first valid decode.
for off in (0x97A, 0x9F8):
ts = _decode_8byte_timestamp(buf, off)
if ts is not None:
md.event_datetime = ts
break
# Calibration date: day, month, year_be at 0x194-0x197.
if len(buf) > 0x197:
day, mon = buf[0x194], buf[0x195]
year = int.from_bytes(buf[0x196 : 0x198], "big")
if 1 <= mon <= 12 and 1 <= day <= 31 and 2015 <= year <= 2050:
try:
md.calibration_date = datetime.date(year, mon, day)
except ValueError:
pass
return md
# ─── Sample decoder + unit conversion ───────────────────────────────────────
def _find_waveform_body_offset(buf: bytes) -> Optional[int]:
"""Pick the file offset of the waveform body by trial-decoding every
``00 02 00`` magic position past the fixed-header region.
The body's location isn't fixed across all sig-A IDFW files — about
half the production events use ``0x0f1f``, but the rest have offsets
that shift based on header padding / channel-config layout. We
auto-detect by:
1. Find every ``00 02 00`` occurrence past ``_BODY_SCAN_FLOOR``.
2. Try ``decode_waveform_v2()`` on each candidate.
3. Pick the offset whose decoded sample count is largest.
Returns the offset, or ``None`` if no candidate yielded more than
the trivial 2-sample preamble (= "no real body found").
Costs ~2-8 trial decodes per file; in practice the first candidate
past 0x0e00 is usually the right one.
"""
if len(buf) < _BODY_SCAN_FLOOR + 8:
return None
# 1. Locate every plausible per-channel record header. A header carries
# [len 2B][channel_id][00][00] at +2..+6, so anchor the search on the
# three-byte ``<cid> 00 00`` signature and validate with is_record().
# Scanning candidate *preambles* instead is not viable: MODE_RAW16 is
# ``00 00``, so every run of three zero bytes would look like a body
# 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
# >= 3 rather than == 4: a mic-disabled event has only the three geo
# channels, and demanding four made `equal` permanently False for
# 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]:
"""Decode samples from the sig-A waveform body.
Returns the raw decoder counts dict — geo LSB = 0.0003 in/s, mic in
its own count unit (see :func:`mic_count_to_psi`). Returns None if
no usable body is found.
Uses :func:`_find_waveform_body_offset` to locate the body — the
file-offset varies across events (~50% sit at the canonical
``0x0f1f`` but the rest don't), so the previous hardcoded constant
silently produced 2-sample preamble-only output for half the corpus.
"""
off = _find_waveform_body_offset(buf)
if off is None:
return None
return decode_waveform_v2(buf[off:])
def geo_count_to_ips(count: int) -> float:
"""Convert a Thor geo decoder count to in/s. LSB = 0.0003 in/s."""
return count * _GEO_LSB_IPS
def mic_count_to_psi(count: int) -> float:
"""Convert a Thor mic decoder count to psi. Scale derived from
regression over 50 sample pairs in UM11719_20231219162723.IDFW;
consistent to ~5%. Calibration constants from the channel block
can refine this once decoded.
"""
return count * _MIC_LSB_PSI
# ─── IDFH histogram decoder ─────────────────────────────────────────────────
@dataclass
class IdfhInterval:
"""One decoded histogram interval (typically one minute of monitoring)."""
offset: int # file byte offset of the 72-byte record
# Per-channel min/max ADC counts (int16 BE), half-period samples, peak count.
# Peak = max(|min|, |max|). freq_hz = 512/halfp (None if halfp ≤ 5 →
# ">100 Hz" sentinel; matches sidecar convention).
tran_min: int
tran_max: int
tran_halfp: int
vert_min: int
vert_max: int
vert_halfp: int
long_min: int
long_max: int
long_halfp: int
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")
mx = getattr(self, f"{channel.lower()}_max")
return max(abs(mn), abs(mx))
def peak_ips(self, channel: str) -> float:
"""Convert peak count to in/s (geo channels only)."""
# 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")
if halfp <= 5:
return None
return _IDFH_HALFP_FREQ_NUM / halfp
def _is_unwritten_interval(interval: "IdfhInterval") -> bool:
"""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]
# block[4:6] = int16 BE, role unknown (possibly time-of-peak)
halfp = struct.unpack_from(">H", block, 6)[0]
# block[10:12] and block[14:16] are uint16 BE with unknown semantics
# (likely sum / count contributions for the PVS computation).
fields.extend([mn, mx, halfp])
# Tail 8 bytes (buf72[64:72]) carry PVS-related data; not yet decoded.
return IdfhInterval(
offset=offset,
tran_min=fields[0], tran_max=fields[1], tran_halfp=fields[2],
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,
)
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][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).
``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][counter_be][05 3f]. The counter
# 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")
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
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 * stride
if off + stride > len(buf):
break
chunk = buf[off : off + stride]
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
# ─── Top-level reader ───────────────────────────────────────────────────────
@dataclass
class IdfReadResult:
"""Return type for :func:`read_idf_file`.
For waveforms (``.IDFW``), ``samples`` holds the per-channel sample
arrays in Thor decoder counts. For histograms (``.IDFH``),
``samples`` is empty and ``intervals`` holds the per-interval
record list (peaks, freqs).
"""
event: IdfEvent
samples: dict # {"Tran": [...], ...} for IDFW; empty for IDFH
binary_metadata: IdfBinaryMetadata
signature: str # always "thor" for now (sig-A genuine Thor)
intervals: Optional[list] = None # list[IdfhInterval] for IDFH; None for IDFW
def read_idf_file(
path: Union[str, Path],
*,
data: Optional[bytes] = None,
) -> IdfReadResult:
"""Parse a Thor ``.IDFW`` binary into an ``IdfEvent`` + decoded samples.
Currently implements signature-A waveforms only. Signature-B
(old-firmware) and ``.IDFH`` histograms raise NotImplementedError;
use the paired ``.IDFW.txt`` / ``.IDFH.txt`` sidecar for those via
``parse_idf_report()``.
Returns an :class:`IdfReadResult`. The caller converts int sample
counts to physical units via :func:`geo_count_to_ips` /
:func:`mic_count_to_psi`.
``path`` is used for filename in error messages and ``.IDFH`` vs
``.IDFW`` suffix detection. When ``data`` is supplied the disk
read is skipped — useful for ingest paths that already have the
bytes in memory and where the file may not exist on disk yet.
"""
p = Path(path)
buf = data if data is not None else p.read_bytes()
if len(buf) < 16 or buf[6:16] != _INSTANTEL_TAG + b"\x00":
raise ValueError(f"{p.name}: not an IDF file (missing Instantel magic)")
sig_prefix = buf[:6]
if sig_prefix == _THOR_PREFIX:
signature = "thor"
elif sig_prefix == _BW_STRAY_PREFIX:
raise NotImplementedError(
f"{p.name}: file has a Series III (Blastware) STRT header in "
"an IDF-named container — not a Thor binary. Route through "
"minimateplus.event_file_io.read_blastware_file() instead "
"(peaks decode; samples & full metadata don't, but it's not "
"Thor data so the Thor codec doesn't apply)."
)
else:
raise ValueError(f"{p.name}: unknown IDF signature {sig_prefix.hex()}")
is_histogram = p.suffix.upper() == ".IDFH"
md = extract_binary_metadata(buf)
if is_histogram:
intervals = decode_idfh_body(buf)
if not intervals:
raise ValueError(f"{p.name}: IDFH body decoded no intervals")
# Peaks: max across all intervals on each channel (per-channel max
# of stored max-magnitudes; sidecar's PPV row carries the same).
peak_tran = max((iv.peak_ips("Tran") for iv in intervals), default=0.0)
peak_vert = max((iv.peak_ips("Vert") for iv in intervals), default=0.0)
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.
# 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,
event_type="Full Histogram",
event_datetime=md.event_datetime,
filename=p.name,
sample_rate=md.sample_rate,
record_time_sec=md.record_time_sec,
)
peaks = IdfPeaks(
transverse_ips=peak_tran,
vertical_ips=peak_vert,
longitudinal_ips=peak_long,
peak_vector_sum_ips=None,
mic_pspl_dbl=None, # IDFH binary doesn't carry the dB(L) value
mic_pspl_psi=mic_peak_psi,
)
event = IdfEvent(
serial=md.serial or "UNKNOWN",
timestamp=md.event_datetime or datetime.datetime(1970, 1, 1),
kind="Histogram",
filename=p.name,
sample_rate=md.sample_rate,
record_time_sec=md.record_time_sec,
peaks=peaks,
report=rep,
)
return IdfReadResult(
event=event,
samples={},
binary_metadata=md,
signature=signature,
intervals=intervals,
)
# Waveform path.
decoded = _decode_waveform_samples(buf)
if decoded is None:
raise ValueError(f"{p.name}: waveform body codec failed")
rep = IdfReport(
serial_number=md.serial,
event_type="Full Waveform",
event_datetime=md.event_datetime,
filename=p.name,
sample_rate=md.sample_rate,
record_time_sec=md.record_time_sec,
)
def _peak_ips(ch: str) -> float:
arr = decoded.get(ch, [])
return geo_count_to_ips(max((abs(v) for v in arr), default=0))
# Mic peak psi from binary: max absolute MicL ADC count × 2.14e-6 psi/count.
mic_arr = decoded.get("MicL", [])
mic_peak_count = max((abs(v) for v in mic_arr), default=0)
mic_peak_psi = mic_count_to_psi(mic_peak_count) if mic_peak_count else None
peaks = IdfPeaks(
transverse_ips=_peak_ips("Tran"),
vertical_ips=_peak_ips("Vert"),
longitudinal_ips=_peak_ips("Long"),
# PVS requires aligned per-sample √(T²+V²+L²); leave None — the
# sidecar carries it and the bridge picks it up if present.
peak_vector_sum_ips=None,
mic_pspl_dbl=None, # binary IDFW doesn't carry the dB(L) value;
# sidecar .txt fills it via IdfReport.from_dict
mic_pspl_psi=mic_peak_psi,
)
event = IdfEvent(
serial=md.serial or "UNKNOWN",
timestamp=md.event_datetime or datetime.datetime(1970, 1, 1),
kind="Waveform",
filename=p.name,
sample_rate=md.sample_rate,
record_time_sec=md.record_time_sec,
peaks=peaks,
report=rep,
)
return IdfReadResult(
event=event,
samples=decoded,
binary_metadata=md,
signature=signature,
)
micromate/idf_to_bw_report.py
+323
View File
@@ -0,0 +1,323 @@
"""
micromate/idf_to_bw_report.py — adapter that projects a parsed Thor IDF
report (+ binary metadata + decoded IDFH intervals) into the
``bw_report``-shaped dict that :mod:`sfm.report_pdf.gather_report_data`
consumes.
Lets Thor events flow through the existing Series III Event Report PDF
pipeline without duplicating the renderer. Thor's report content is
~95% the same data shape as BW's; the field names differ but the
underlying metrics map 1:1.
Caveats
───────
- **Mic units** — Thor records ``MicPSPL`` natively in dB(L). This
adapter sets ``bw_report.mic.pspl_dbl`` directly; the report
renderer recomputes the equivalent psi via its dBL→psi formula.
- **Saturation / above-range flags** — Thor doesn't always mark
``OORANGE`` the way BW does; we set ``zc_freq_above_range`` only
when a `>100` sentinel was preserved in the raw text.
- **Per-interval data** — for IDFH events we build ``interval_times``
by stepping ``IntervalSize`` from ``HistogramStartTime``; the binary
decoder confirms one record per step (882 / 881 / 881 ... across
the corpus).
- **calibration_by parsing** — Thor's free-form ``Calibration : November
22, 2023 by Instantel`` is split on ``" by "`` to extract the
calibrator; the date prefix is parsed where possible, otherwise
the binary-extracted ``calibration_date`` from
:class:`micromate.idf_file.IdfBinaryMetadata` wins.
"""
from __future__ import annotations
import datetime
import re
from typing import Any, Dict, List, Optional
# ─── Helpers ────────────────────────────────────────────────────────────────
_NUM_RE = re.compile(r"-?\d+(?:\.\d+)?")
def _parse_first_number(s: Optional[str]) -> Optional[float]:
"""Pull the first numeric token from a string like ``"0.1500 in/s"``."""
if s is None:
return None
m = _NUM_RE.search(str(s))
if not m:
return None
try:
return float(m.group(0))
except ValueError:
return None
def _parse_interval_size_s(s: Optional[str]) -> Optional[float]:
"""``"60 sec"`` → 60.0, ``"5 min"`` → 300.0, ``"1 hour"`` → 3600."""
if s is None:
return None
num = _parse_first_number(s)
if num is None:
return None
sl = str(s).lower()
if "hour" in sl or "hr" in sl:
return num * 3600.0
if "min" in sl:
return num * 60.0
return num # default to seconds
def _parse_calibration(text: Optional[str]) -> tuple[Optional[str], Optional[str]]:
"""Split ``"November 22, 2023 by Instantel"`` → (ISO date, calibrator).
Returns ``(None, None)`` if neither half parses.
"""
if not text:
return None, None
parts = str(text).split(" by ", 1)
date_part = parts[0].strip() if parts else None
by_part = parts[1].strip() if len(parts) > 1 else None
iso_date: Optional[str] = None
if date_part:
for fmt in ("%B %d, %Y", "%b %d, %Y", "%Y-%m-%d", "%m/%d/%Y"):
try:
iso_date = datetime.datetime.strptime(date_part, fmt).date().isoformat()
break
except ValueError:
continue
return iso_date, by_part
def _channel_peaks(idf: Dict[str, Any], ch_lc: str) -> Dict[str, Any]:
"""Map ``tran_ppv`` / ``tran_zc_freq`` / ... → bw_report.peaks.tran shape."""
out: Dict[str, Any] = {}
for src, dst in (
(f"{ch_lc}_ppv", "ppv_ips"),
(f"{ch_lc}_zc_freq", "zc_freq_hz"),
(f"{ch_lc}_time_of_peak", "time_of_peak_s"),
(f"{ch_lc}_peak_acceleration", "peak_accel_g"),
(f"{ch_lc}_peak_displacement", "peak_disp_in"),
):
v = idf.get(src)
if v is not None:
out[dst] = v
# ZC freq ">100" sentinel: the raw text carries it under the un-typed
# key (e.g. ``raw["tran_zc_freq"]`` would be ``">100"``), and our parser
# dropped the typed entry. Detect that case and flag.
raw_zc = idf.get(f"{ch_lc}_zc_freq")
if isinstance(raw_zc, str) and ">" in raw_zc:
out["zc_freq_above_range"] = True
out.pop("zc_freq_hz", None)
return out
def _sensor_check(idf: Dict[str, Any], ch_lc: str) -> Dict[str, Any]:
out: Dict[str, Any] = {}
fr = idf.get(f"{ch_lc}_test_freq")
if fr is not None:
out["freq_hz"] = _parse_first_number(fr)
rt = idf.get(f"{ch_lc}_test_ratio")
if rt is not None:
out["ratio"] = _parse_first_number(rt)
am = idf.get(f"{ch_lc}_test_amplitude")
if am is not None:
out["amplitude_mv"] = _parse_first_number(am)
res = idf.get(f"{ch_lc}_test_results")
if res is not None:
out["result"] = str(res).strip()
return {k: v for k, v in out.items() if v is not None}
def _interval_times(idf: Dict[str, Any], n_intervals: Optional[int]) -> List[str]:
"""Synthesise per-interval timestamps from start + interval_size × k.
Returns ``[]`` when start time or interval size is unknown.
"""
if not n_intervals:
return []
start_date = idf.get("histogram_start_date") or idf.get("event_date")
start_time = idf.get("histogram_start_time") or idf.get("event_time")
iv_str = idf.get("interval_size")
iv_s = _parse_interval_size_s(iv_str)
if not (start_date and start_time and iv_s):
return []
try:
t0 = datetime.datetime.strptime(f"{start_date} {start_time}", "%Y-%m-%d %H:%M:%S")
except ValueError:
return []
out = []
for k in range(int(n_intervals)):
t = t0 + datetime.timedelta(seconds=iv_s * (k + 1))
out.append(t.isoformat())
return out
# ─── Top-level adapter ──────────────────────────────────────────────────────
def build_bw_report_from_idf(
idf_report: Dict[str, Any],
*,
binary_md=None,
intervals: Optional[list] = None,
is_histogram: Optional[bool] = None,
) -> Dict[str, Any]:
"""Project a parsed IDF report dict (and optional binary metadata +
decoded IDFH intervals) into the BW report sidecar shape.
The returned dict is structurally identical to what
``minimateplus.event_file_io._bw_report_to_dict`` produces from a
real BW ASCII report — it can be assigned to
``sidecar["bw_report"]`` and consumed verbatim by
``sfm.report_pdf.gather_report_data``.
``intervals`` is the list of :class:`micromate.idf_file.IdfhInterval`
objects from :func:`micromate.idf_file.decode_idfh_body`; only used
for histogram events to derive accurate ``interval_times``.
"""
if is_histogram is None:
et = str(idf_report.get("event_type", ""))
is_histogram = et.lower().startswith("full histogram")
# ── Trigger / recording / device ─────────────────────────────────────
trigger_channel = idf_report.get("trigger")
trigger_level = _parse_first_number(idf_report.get("geo_trigger_level"))
geo_range_ips = _parse_first_number(idf_report.get("geo_range"))
cal_iso, cal_by = _parse_calibration(idf_report.get("calibration"))
# Prefer the binary-extracted calibration_date when our text parse fell
# through; the binary date is unambiguous.
if cal_iso is None and binary_md is not None and binary_md.calibration_date:
cal_iso = binary_md.calibration_date.isoformat()
# ── Histogram fields ────────────────────────────────────────────────
hist_block: Dict[str, Any] = {
"start": None, "stop": None, "n_intervals": None,
"interval_size": None, "interval_size_s": None,
"channel_peak_when": {},
}
if is_histogram:
sd = idf_report.get("histogram_start_date")
st = idf_report.get("histogram_start_time")
if sd and st:
try:
hist_block["start"] = datetime.datetime.strptime(
f"{sd} {st}", "%Y-%m-%d %H:%M:%S"
).isoformat()
except ValueError:
pass
ed = idf_report.get("histogram_stop_date")
et_ = idf_report.get("histogram_stop_time")
if ed and et_:
try:
hist_block["stop"] = datetime.datetime.strptime(
f"{ed} {et_}", "%Y-%m-%d %H:%M:%S"
).isoformat()
except ValueError:
pass
n_raw = idf_report.get("number_of_intervals")
if n_raw is not None:
try:
# Thor reports a float like "81.04"; round to int (the BW
# report uses an int for the column).
hist_block["n_intervals"] = int(float(str(n_raw)))
except ValueError:
pass
# When the binary decoder gave us the actual interval count, prefer it.
if intervals is not None:
hist_block["n_intervals"] = len(intervals)
hist_block["interval_size"] = idf_report.get("interval_size")
hist_block["interval_size_s"] = _parse_interval_size_s(idf_report.get("interval_size"))
# interval_times derived from start+step (the BW report uses the
# exact strings; we match its representation).
times = _interval_times(idf_report, hist_block["n_intervals"])
# Per-channel peak when (absolute date+time at which the channel's
# peak occurred over the histogram run). Thor splits this into
# ``TranPeakDate`` / ``TranPeakTime`` etc.
peak_when: Dict[str, str] = {}
for ch_label, ch_lc in (("Tran", "tran"), ("Vert", "vert"), ("Long", "long"), ("MicL", "mic")):
d = idf_report.get(f"{ch_lc}_peak_date")
t = idf_report.get(f"{ch_lc}_peak_time")
if d and t:
try:
peak_when[ch_label] = datetime.datetime.strptime(
f"{d} {t}", "%Y-%m-%d %H:%M:%S"
).isoformat()
except ValueError:
continue
if peak_when:
hist_block["channel_peak_when"] = peak_when
# ── Mic block ────────────────────────────────────────────────────────
mic_block = {
"weighting": "L", # Thor mic is ISEE Linear
"pspl_dbl": idf_report.get("mic_ppv"), # the dB(L) float
"pspl_saturated": False,
"zc_freq_hz": idf_report.get("mic_zc_freq"),
"zc_freq_above_range": isinstance(idf_report.get("mic_zc_freq"), str)
and ">" in str(idf_report.get("mic_zc_freq")),
"time_of_peak_s": idf_report.get("mic_time_of_peak"),
}
if mic_block["zc_freq_above_range"]:
mic_block["zc_freq_hz"] = None
# ── Peaks ────────────────────────────────────────────────────────────
vs_block = {
"ips": idf_report.get("peak_vector_sum"),
"time_s": _parse_first_number(idf_report.get("peak_vector_sum_time_sum")),
"when": None,
"saturated": False,
}
if is_histogram:
# PVS absolute date+time, when present.
vs_d = idf_report.get("peak_vector_sum_date")
vs_t = idf_report.get("peak_vector_sum_time")
if vs_d and vs_t:
try:
vs_block["when"] = datetime.datetime.strptime(
f"{vs_d} {vs_t}", "%Y-%m-%d %H:%M:%S"
).isoformat()
except ValueError:
pass
return {
"available": True,
"event_type": idf_report.get("event_type"),
"version": idf_report.get("version"),
"trigger": {
"channel": trigger_channel,
"geo_level_ips": trigger_level,
},
"recording": {
"sample_rate_sps": idf_report.get("sample_rate"),
"record_time_s": idf_report.get("record_time_sec"),
"pretrig_s": idf_report.get("pre_trigger_sec"),
"stop_mode": idf_report.get("record_stop_mode"),
"geo_range_ips": geo_range_ips,
"units": idf_report.get("units"),
},
"device": {
"battery_volts": idf_report.get("battery_volts"),
"calibration_date": cal_iso,
"calibration_by": cal_by,
},
"peaks": {
"tran": _channel_peaks(idf_report, "tran"),
"vert": _channel_peaks(idf_report, "vert"),
"long": _channel_peaks(idf_report, "long"),
"vector_sum": vs_block,
},
"mic": mic_block,
"sensor_check": {
"tran": _sensor_check(idf_report, "tran"),
"vert": _sensor_check(idf_report, "vert"),
"long": _sensor_check(idf_report, "long"),
"mic": _sensor_check(idf_report, "mic"),
},
"histogram": hist_block,
"monitor_log": [],
"pc_sw_version": None,
}
micromate/models.py
+398
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@@ -0,0 +1,398 @@
"""
Micromate (Series IV / Thor) native data models.
These are the right-shaped dataclasses for Thor data — Thor measures
the microphone in dB(L) directly, so this model carries
``mic_pspl_dbl`` rather than the pseudo-``psi`` shoehorn that
``minimateplus.PeakValues`` uses for Series III BW data.
The ingest pipeline today goes:
.IDFW.txt → parse_idf_report() → dict
dict → IdfEvent.from_report() → IdfEvent (typed)
IdfEvent → IdfEvent.to_minimateplus_event() → shape DB / sidecar
machinery expects
The ``to_minimateplus_event()`` bridge is a temporary boundary — when we
crack the binary IDF codec and have richer per-event data to store, the
DB schema will grow Series-IV-specific columns and the bridge will
shrink or disappear.
"""
from __future__ import annotations
import datetime
from dataclasses import dataclass, field
from typing import Any, Dict, Optional, Tuple
# ── IdfReport ─────────────────────────────────────────────────────────────────
@dataclass
class IdfReport:
"""Typed wrapper around the dict returned by ``parse_idf_report``.
All fields optional — Thor's exporter is permissive and some IDF .txt
files (especially histograms) omit fields that waveform sidecars
include. Use ``.raw`` for any field this dataclass hasn't surfaced
yet (the parser keeps every recognised key in the raw dict).
"""
# Identity / kind
serial_number: Optional[str] = None
event_type: Optional[str] = None # "Full Waveform" | "Full Histogram"
event_datetime: Optional[datetime.datetime] = None
filename: Optional[str] = None # echoed by Thor's exporter
# Sampling / timing
sample_rate: Optional[int] = None # samples/sec
record_time_sec: Optional[float] = None
pre_trigger_sec: Optional[float] = None
# Geophone peaks (in/s)
tran_ppv: Optional[float] = None
vert_ppv: Optional[float] = None
long_ppv: Optional[float] = None
peak_vector_sum: Optional[float] = None
# Microphone — Thor's native unit is dB(L), NOT psi.
mic_pspl_dbl: Optional[float] = None
# Zero-crossing frequencies (Hz)
tran_zc_freq: Optional[float] = None
vert_zc_freq: Optional[float] = None
long_zc_freq: Optional[float] = None
mic_zc_freq: Optional[float] = None
# Per-channel time of peak (sec, since event start)
tran_time_of_peak: Optional[float] = None
vert_time_of_peak: Optional[float] = None
long_time_of_peak: Optional[float] = None
mic_time_of_peak: Optional[float] = None
# Derived per-channel motion
tran_peak_acceleration: Optional[float] = None # g
vert_peak_acceleration: Optional[float] = None
long_peak_acceleration: Optional[float] = None
tran_peak_displacement: Optional[float] = None # in
vert_peak_displacement: Optional[float] = None
long_peak_displacement: Optional[float] = None
# Operator-supplied strings (Thor's TitleString1..4 → semantic slots)
project: Optional[str] = None # TitleString1
client: Optional[str] = None # TitleString2
operator: Optional[str] = None # TitleString3
notes: Optional[str] = None # TitleString4 / PostEventNote
setup: Optional[str] = None # setup file name
# Sensor self-check results
tran_test_passed: Optional[bool] = None
vert_test_passed: Optional[bool] = None
long_test_passed: Optional[bool] = None
mic_test_passed: Optional[bool] = None
# Device-fixed metadata
firmware_version: Optional[str] = None
calibration_text: Optional[str] = None
battery_volts: Optional[float] = None
# Original parser dict — preserves every recognised key (including
# raw unit-suffixed strings) for forward-compatible field access.
raw: Dict[str, Any] = field(default_factory=dict, repr=False)
@classmethod
def from_dict(cls, d: Dict[str, Any]) -> "IdfReport":
"""Build an IdfReport from the dict returned by ``parse_idf_report``."""
ed = d.get("event_datetime")
if isinstance(ed, str):
try:
ed = datetime.datetime.fromisoformat(ed)
except ValueError:
ed = None
return cls(
serial_number = d.get("serial_number"),
event_type = d.get("event_type"),
event_datetime = ed if isinstance(ed, datetime.datetime) else None,
filename = d.get("filename"),
sample_rate = d.get("sample_rate"),
record_time_sec = d.get("record_time_sec"),
pre_trigger_sec = d.get("pre_trigger_sec"),
tran_ppv = d.get("tran_ppv"),
vert_ppv = d.get("vert_ppv"),
long_ppv = d.get("long_ppv"),
peak_vector_sum = d.get("peak_vector_sum"),
mic_pspl_dbl = d.get("mic_ppv"), # parser names it mic_ppv (legacy)
tran_zc_freq = d.get("tran_zc_freq"),
vert_zc_freq = d.get("vert_zc_freq"),
long_zc_freq = d.get("long_zc_freq"),
mic_zc_freq = d.get("mic_zc_freq"),
tran_time_of_peak = d.get("tran_time_of_peak"),
vert_time_of_peak = d.get("vert_time_of_peak"),
long_time_of_peak = d.get("long_time_of_peak"),
mic_time_of_peak = d.get("mic_time_of_peak"),
tran_peak_acceleration = d.get("tran_peak_acceleration"),
vert_peak_acceleration = d.get("vert_peak_acceleration"),
long_peak_acceleration = d.get("long_peak_acceleration"),
tran_peak_displacement = d.get("tran_peak_displacement"),
vert_peak_displacement = d.get("vert_peak_displacement"),
long_peak_displacement = d.get("long_peak_displacement"),
project = d.get("project"),
client = d.get("client"),
operator = d.get("operator"),
notes = d.get("notes"),
setup = d.get("setup"),
tran_test_passed = d.get("tran_test_passed"),
vert_test_passed = d.get("vert_test_passed"),
long_test_passed = d.get("long_test_passed"),
mic_test_passed = d.get("mic_test_passed"),
firmware_version = d.get("version"),
calibration_text = d.get("calibration_text"),
battery_volts = d.get("battery_volts"),
raw = d,
)
# ── IdfPeaks / IdfProjectInfo / IdfSensorCheck (narrow grouping types) ───────
@dataclass
class IdfPeaks:
"""Geophone + mic peak values for one Thor event. Native Thor units.
Thor stores the mic peak in two parallel forms — ``mic_pspl_dbl`` is
what the sidecar's top-level ``MicPSPL`` header field carries (dB(L)),
used in the report header. ``mic_pspl_psi`` is the psi value derived
either from the IDFW sample table / IDFH interval column 9, or from
the binary mic counts (~2.14e-6 psi/count). Needed because the
BW-shaped ``PeakValues.micl`` consumed by ``event_hdf5.write_event_hdf5``
expects psi — feeding it dB(L) makes the h5 mic-chart scale factor
blow up.
"""
transverse_ips: Optional[float] = None # in/s
vertical_ips: Optional[float] = None # in/s
longitudinal_ips: Optional[float] = None # in/s
peak_vector_sum_ips: Optional[float] = None # in/s
mic_pspl_dbl: Optional[float] = None # dB(L)
mic_pspl_psi: Optional[float] = None # psi
@dataclass
class IdfProjectInfo:
"""Operator-supplied strings from Thor's TitleString1..4."""
project: Optional[str] = None
client: Optional[str] = None
operator: Optional[str] = None
notes: Optional[str] = None
setup: Optional[str] = None
@dataclass
class IdfSensorCheck:
"""Per-channel pass/fail from Thor's self-test."""
tran: Optional[bool] = None
vert: Optional[bool] = None
long: Optional[bool] = None
mic: Optional[bool] = None
# ── IdfEvent ─────────────────────────────────────────────────────────────────
@dataclass
class IdfEvent:
"""A single Thor / Micromate Series IV event.
Built from a parsed .IDFW.txt or .IDFH.txt sidecar via
``IdfEvent.from_report()``. The filename is the authoritative
source for serial + timestamp + kind; the .txt provides
device-authoritative peak values, frequencies, project strings,
sensor self-check, firmware, calibration.
"""
# Identity
serial: str
timestamp: datetime.datetime
kind: str # "Waveform" | "Histogram"
filename: str # device-native binary filename, e.g. "UM11719_20231219163444.IDFW"
# Sampling / timing
sample_rate: Optional[int] = None
record_time_sec: Optional[float] = None
pre_trigger_sec: Optional[float] = None
# Peaks
peaks: IdfPeaks = field(default_factory=IdfPeaks)
# Per-channel frequencies (Hz)
tran_zc_freq: Optional[float] = None
vert_zc_freq: Optional[float] = None
long_zc_freq: Optional[float] = None
mic_zc_freq: Optional[float] = None
# Project strings
project_info: IdfProjectInfo = field(default_factory=IdfProjectInfo)
# Sensor self-check
sensor_check: IdfSensorCheck = field(default_factory=IdfSensorCheck)
# Device-fixed
firmware_version: Optional[str] = None
calibration_text: Optional[str] = None
battery_volts: Optional[float] = None
# The full parsed report — preserves anything not surfaced as a typed field
report: IdfReport = field(default_factory=IdfReport)
@classmethod
def from_report(
cls,
report: Any,
filename: str,
) -> "IdfEvent":
"""Build an IdfEvent from a parsed report (dict or IdfReport) and
the device-native binary filename.
The filename is authoritative for serial + timestamp + kind:
Thor's filenames are literal ``<SERIAL>_<YYYYMMDDHHMMSS>.<KIND>``
and the device's own clock is the canonical event timestamp.
If the report carries an ``event_datetime`` that differs from
what's in the filename, the report wins (it has finer-grained
device-reported time-of-trigger semantics).
"""
from .idf_ascii_report import parse_event_filename
# Normalise input to IdfReport
if isinstance(report, IdfReport):
rep = report
elif isinstance(report, dict):
rep = IdfReport.from_dict(report)
else:
raise TypeError(
f"report must be IdfReport or dict; got {type(report).__name__}"
)
# Filename → (serial, timestamp, kind). Required — fall back to
# report-supplied values only if filename parsing fails.
parsed = parse_event_filename(filename)
if parsed is not None:
fn_serial, fn_ts, fn_kind = parsed
kind = "Histogram" if fn_kind == "IDFH" else "Waveform"
else:
fn_serial = rep.serial_number or "UNKNOWN"
fn_ts = rep.event_datetime or datetime.datetime(1970, 1, 1)
kind = "Waveform" if (rep.event_type or "").lower().startswith("full waveform") else "Histogram"
# Prefer report's event_datetime (device-authoritative) over the filename.
ts = rep.event_datetime or fn_ts
serial = rep.serial_number or fn_serial
return cls(
serial=serial,
timestamp=ts,
kind=kind,
filename=filename,
sample_rate=rep.sample_rate,
record_time_sec=rep.record_time_sec,
pre_trigger_sec=rep.pre_trigger_sec,
peaks=IdfPeaks(
transverse_ips = rep.tran_ppv,
vertical_ips = rep.vert_ppv,
longitudinal_ips = rep.long_ppv,
peak_vector_sum_ips = rep.peak_vector_sum,
mic_pspl_dbl = rep.mic_pspl_dbl,
),
tran_zc_freq=rep.tran_zc_freq,
vert_zc_freq=rep.vert_zc_freq,
long_zc_freq=rep.long_zc_freq,
mic_zc_freq=rep.mic_zc_freq,
project_info=IdfProjectInfo(
project=rep.project,
client=rep.client,
operator=rep.operator,
notes=rep.notes,
setup=rep.setup,
),
sensor_check=IdfSensorCheck(
tran=rep.tran_test_passed,
vert=rep.vert_test_passed,
long=rep.long_test_passed,
mic=rep.mic_test_passed,
),
firmware_version=rep.firmware_version,
calibration_text=rep.calibration_text,
battery_volts=rep.battery_volts,
report=rep,
)
# ── Bridge to minimateplus shape (for the existing DB / sidecar paths) ──
def to_minimateplus_event(self, waveform_key: bytes) -> Any:
"""Project this Thor event into the shape ``minimateplus.Event``
carries, so it can flow through the existing
``SeismoDb.insert_events()`` and ``event_to_sidecar_dict()``
machinery without those code paths needing to know about Thor.
Caveats of the bridge:
- ``PeakValues.micl`` carries the mic peak in **psi** (matching
BW's convention) — set from :attr:`IdfPeaks.mic_pspl_psi`,
with a dB(L)→psi fallback when only the dB(L) value is
available. This is what the h5 writer's mic-scale-factor
logic needs. The dB(L) value still flows through
``bw_report.mic.pspl_dbl`` (set by the
``idf_to_bw_report`` adapter) and the renderer reads it
from there for the report header.
- Many Thor-specific fields (Peak Acceleration / Displacement,
sensor self-check, calibration) don't have a slot in
``Event``. The full IdfReport is preserved on the
``.sfm.json`` sidecar under ``extensions.idf_report`` via
``save_imported_idf`` — that's the source of truth for them.
"""
from minimateplus.models import (
Event, PeakValues, ProjectInfo, Timestamp,
)
ts_obj = Timestamp(
raw=bytes(9),
flag=0,
year=self.timestamp.year,
unknown_byte=0,
month=self.timestamp.month,
day=self.timestamp.day,
hour=self.timestamp.hour,
minute=self.timestamp.minute,
second=self.timestamp.second,
)
# Resolve mic peak as psi. Priority: binary-derived mic_pspl_psi
# (set by read_idf_file) > dB(L)→psi fallback via standard formula
# (psi = 2.9e-9 × 10^(dBL/20)) > None.
mic_psi = self.peaks.mic_pspl_psi
if mic_psi is None and self.peaks.mic_pspl_dbl is not None:
mic_psi = 2.9e-9 * (10.0 ** (self.peaks.mic_pspl_dbl / 20.0))
pv = PeakValues(
tran=self.peaks.transverse_ips,
vert=self.peaks.vertical_ips,
long=self.peaks.longitudinal_ips,
micl=mic_psi, # psi, matching BW's convention (h5 scaling depends on this)
peak_vector_sum=self.peaks.peak_vector_sum_ips,
)
pi = ProjectInfo(
setup_name=self.project_info.setup,
project=self.project_info.project,
client=self.project_info.client,
operator=self.project_info.operator,
sensor_location=None, # Thor folds location into project string
notes=self.project_info.notes,
)
ev = Event(
index=0,
timestamp=ts_obj,
sample_rate=self.sample_rate,
peak_values=pv,
project_info=pi,
record_type=self.kind,
rectime_seconds=self.record_time_sec,
)
ev._waveform_key = waveform_key
return ev
micromate/sensor_check.py
+89
View File
@@ -0,0 +1,89 @@
r"""Decode the Thor / Micromate (series-4) sensor self-check waveforms from an
IDFW event binary.
Reverse-engineered 2026-09-15 against 4 UM (Thor) oracle events. The IDFW
binary carries the sensor self-check in its fixed-header region (before the
waveform body), as up to four records tagged ``01 0e 3c/3d/3e/3f`` — the SAME
channel ids as the series-3 MiniMate Plus (Tran / Vert / Long / MicL), which is
the physical self-test:
* 3c / 3d / 3e = Tran / Vert / Long geophone ring-downs (a damped impulse
response — resonant frequency + damping).
* 3f = MicL pulse train (the mic's known-signal gain check). Absent
on three-channel (mic-disabled) units.
Record framing (per record)::
01 0e [id:1] [flags:3] [count:2 BE] [pad:10] [int16-BE samples × count]
\___ 18-byte header ___/
Unlike series-3's delta-coded trailing block, series-4 stores each trace as a
raw int16 big-endian array. ``count`` (the 2-byte field at header offset +8)
is the sample count; the record is padded to a fixed stride after that.
"""
from __future__ import annotations
import struct
from typing import Dict, List
# Record id → channel. Same ids/order as series-3 (minimateplus.sensor_check).
_ID_TO_CHANNEL = {0x3C: "Tran", 0x3D: "Vert", 0x3E: "Long", 0x3F: "MicL"}
_CHAIN_IDS = (0x3C, 0x3D, 0x3E, 0x3F)
_MARKER = b"\x01\x0e" # precedes the 1-byte channel id
_HEADER_LEN = 18 # bytes from the marker start to the first sample
_COUNT_OFF = 8 # 2-byte BE sample count, from the marker start
_MAX_COUNT = 4000 # sanity cap (traces are ~70-200 samples)
def _find_chain(raw: bytes):
"""Locate the sensor-check record chain. Returns a list of
``(offset, id, count)`` for the first run of markers whose ids run
3c, 3d, 3e[, 3f] in order, or ``[]``.
Records are padded to a fixed stride, so the next marker is not at
``header + count*2``; instead collect every ``01 0e [id]`` marker with a
sane count and take the first id-ordered run. Validating the id sequence
(not a lone ``01 0e 3c``) keeps a stray marker in the waveform body from
matching — the real chain sits in the fixed header, ahead of the body.
"""
n = len(raw)
markers = []
for p in range(n - _HEADER_LEN):
if raw[p:p + 2] == _MARKER and raw[p + 2] in _ID_TO_CHANNEL:
count = int.from_bytes(raw[p + _COUNT_OFF:p + _COUNT_OFF + 2], "big")
if 0 < count <= _MAX_COUNT:
markers.append((p, raw[p + 2], count))
for i, (off, rid, _c) in enumerate(markers):
if rid != 0x3C:
continue
run = [markers[i]]
for m in markers[i + 1:]:
if len(run) < len(_CHAIN_IDS) and m[1] == _CHAIN_IDS[len(run)]:
run.append(m)
else:
break
if len(run) >= 3: # 3-channel (mic-disabled) units are valid
return run
return []
def decode_idf_sensor_check(raw: bytes) -> Dict[str, List[int]]:
"""Decode the sensor self-check traces from a Thor/Micromate IDFW binary.
Returns ``{"Tran": [...], "Vert": [...], "Long": [...], "MicL": [...]}`` in
raw int16 ADC counts (MicL omitted on 3-channel units), or ``{}`` if the
binary carries no sensor-check chain (a non-IDF file, or an IDFH histogram).
"""
chain = _find_chain(raw)
if not chain:
return {}
out: Dict[str, List[int]] = {}
for off, rid, count in chain:
start = off + _HEADER_LEN
blob = raw[start:start + count * 2]
if len(blob) < count * 2:
continue
out[_ID_TO_CHANNEL[rid]] = list(struct.unpack(">%dh" % count, blob))
return out
minimateplus/__init__.py
+10 -2
View File
@@ -21,7 +21,15 @@ Typical usage (TCP / modem):
from .client import MiniMateClient
from .models import DeviceInfo, Event, MonitorLogEntry
from .transport import SerialTransport, TcpTransport
from .transport import CapturingTransport, SerialTransport, TcpTransport
__version__ = "0.1.0"
__all__ = ["MiniMateClient", "DeviceInfo", "Event", "MonitorLogEntry", "SerialTransport", "TcpTransport"]
__all__ = [
"MiniMateClient",
"DeviceInfo",
"Event",
"MonitorLogEntry",
"SerialTransport",
"TcpTransport",
"CapturingTransport",
]
minimateplus/binary_annotate.py
+75
View File
@@ -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)
minimateplus/blastware_file.py
+154 -60
View File
@@ -552,6 +552,105 @@ def classify_frame(frame: S3Frame) -> str:
# ── Waveform file writer ───────────────────────────────────────────────────────────
def extract_body_bytes(a5_frames):
"""Reconstruct the Blastware-file body bytes from a list of A5 frames.
Returns ``(strt, body, footer)`` where:
- ``strt`` is the 21-byte STRT record from the probe frame (or a fallback
record built from minimal event metadata if STRT is missing).
- ``body`` is the variable-length sample-data section (between STRT and
the 26-byte file footer). Empty if no frames decode.
- ``footer`` is the 26-byte file footer.
This is the same body-construction algorithm used by :func:`write_blastware_file`
— refactored out so the body decoder (``waveform_codec.decode_waveform_v2``)
can consume the same bytes without re-implementing the frame-walking logic.
Returns ``(b"", b"", b"")`` if *a5_frames* is empty.
"""
if not a5_frames:
return (b"", b"", b"")
# ── Extract STRT record from probe frame ─────────────────────────────────
w0_raw = bytes(a5_frames[0].data[7:])
w0_stripped = _strip_inner_frame_dles(w0_raw)
strt_pos_stripped = w0_stripped.find(b"STRT")
if strt_pos_stripped >= 0:
strt = bytes(w0_stripped[strt_pos_stripped : strt_pos_stripped + 21])
# Walk raw bytes to find the raw-domain end of the STRT (= body start).
target_stripped = strt_pos_stripped + 21
stripped_so_far = 0
raw_i = 0
while stripped_so_far < target_stripped and raw_i < len(w0_raw):
if (w0_raw[raw_i] == 0x10
and raw_i + 1 < len(w0_raw)
and w0_raw[raw_i + 1] in {0x02, 0x03, 0x04}):
raw_i += 2
else:
raw_i += 1
stripped_so_far += 1
probe_skip = 7 + raw_i
else:
strt = b"STRT" + b"\xff\xfe" + bytes(14) + b"\x00"
probe_skip = 7 + 21
if len(strt) != 21:
return (b"", b"", b"")
# Separate terminator from data frames.
term_idx: Optional[int] = None
if a5_frames and a5_frames[-1].page_key != 0x0010:
term_idx = len(a5_frames) - 1
if term_idx is not None:
body_frames = a5_frames[:term_idx]
term_frame = a5_frames[term_idx]
else:
body_frames = a5_frames
term_frame = None
all_bytes = bytearray()
for fi, frame in enumerate(body_frames):
if fi == 0:
skip = probe_skip
elif fi in (1, 2):
skip = 13 # metadata pages
else:
skip = 12 # sample chunks
all_bytes.extend(_frame_body_bytes(frame, skip))
if term_frame is not None:
all_bytes.extend(_frame_body_bytes(term_frame, 11))
# Find the first valid `0e 08` footer marker.
footer_pos = -1
pos = 0
while True:
pos = bytes(all_bytes).find(b"\x0e\x08", pos)
if pos < 0 or pos + 26 > len(all_bytes):
break
yr = (all_bytes[pos + 4] << 8) | all_bytes[pos + 5]
if 2015 <= yr <= 2050:
footer_pos = pos
break
pos += 1
if footer_pos >= 0:
body = bytes(all_bytes[:footer_pos])
footer = bytes(all_bytes[footer_pos : footer_pos + 26])
elif len(all_bytes) >= 26:
body = bytes(all_bytes[:-26])
footer = bytes(all_bytes[-26:])
else:
body = bytes(all_bytes)
footer = b""
return (strt, body, footer)
def write_blastware_file(
event: Event,
a5_frames: list[S3Frame],
@@ -639,7 +738,7 @@ def write_blastware_file(
strt = b"STRT" + b"\xff\xfe" + key4 + bytes(14) + bytes([rectime & 0xFF])
probe_skip = 7 + 21
log.warning(
log.debug(
"write_blastware_file: strt_pos_stripped=%d probe_skip=%d "
"probe_data_len=%d strt_hex=%s",
strt_pos_stripped if strt_pos_stripped >= 0 else -1,
@@ -672,11 +771,10 @@ def write_blastware_file(
# Do NOT use a5_frames[-1] — if _a5_frames contains stray frames from a
# subsequent event (a known get_events side-effect), the last frame will
# not be the terminator and the footer will be mis-identified.
# TERM detection (v0.14.0): last frame if page_key != 0x0010 (sample marker)
term_idx: Optional[int] = None
for _i, _f in enumerate(a5_frames):
if _f.page_key == 0x0000:
term_idx = _i
break
if a5_frames and a5_frames[-1].page_key != 0x0010:
term_idx = len(a5_frames) - 1
if term_idx is not None:
body_frames = a5_frames[:term_idx]
@@ -685,68 +783,32 @@ def write_blastware_file(
body_frames = a5_frames
term_frame = None
# ── Identify first metadata frame and skip "extra chunks" ───────────────
# When extra_chunks_after_metadata=1 in read_bulk_waveform_stream(), the
# frame list is: [probe, data..., metadata, extra_chunk, terminator].
# The extra_chunk is downloaded to prime the TCP terminator response — its
# ADC data is NOT part of the Blastware file body. Skip it.
#
# Rule: any frame at index strictly between first_metadata_fi and last_fi
# (the final frame) is an extra chunk and must be excluded.
#
# If no metadata frame exists (e.g. full_waveform download), first_metadata_fi
# is None and no frames are skipped — all frames contribute normally.
first_metadata_fi: Optional[int] = None
for _fi_scan, _frame_scan in enumerate(body_frames):
if _fi_scan > 0 and any(m in bytes(_frame_scan.data) for m in _METADATA_FRAME_MARKERS):
first_metadata_fi = _fi_scan
break
# Frame contribution loop (v0.14.0 BW-exact walk).
# Skip values:
# probe (fi=0): probe_skip
# meta@0x1002 (fi=1): 13 (6-byte inner header)
# meta@0x1004 (fi=2): 13 (6-byte inner header)
# sample chunks (fi=3+): 12 (5-byte inner header)
last_fi = len(body_frames) - 1
log.warning(
"write_blastware_file: %d body_frames first_metadata_fi=%s last_fi=%d",
len(body_frames),
str(first_metadata_fi) if first_metadata_fi is not None else "None",
last_fi,
log.debug(
"write_blastware_file: %d body_frames last_fi=%d",
len(body_frames), last_fi,
)
all_bytes = bytearray()
for fi, frame in enumerate(body_frames):
# Skip "extra chunk" frames: frames after the first metadata frame but
# before the last frame (terminator). These prime the TCP terminator but
# their ADC data must NOT appear in the Blastware file body.
if (first_metadata_fi is not None
and fi > first_metadata_fi
and fi < last_fi):
log.warning(
"write_blastware_file: fi=%d SKIP (extra chunk after metadata fi=%d last_fi=%d)",
fi, first_metadata_fi, last_fi,
)
continue
if fi == 0:
# Probe frame: always process regardless of classification.
# It holds the STRT record; probe_skip positions us past it.
skip = probe_skip
elif fi in (1, 2):
skip = 13 # metadata pages
else:
# ALL subsequent frames are included unconditionally — no filtering on
# frame type. In the A5 stream, frame 0 is always the probe response;
# frames 1+ are always data (waveform chunks, compliance config, or
# compliance continuation). Classification is for logging only.
#
# DO NOT gate on classify_frame() here:
# - "probe_or_strt" at fi>0 is always a false positive — ADC binary
# data can coincidentally contain b"STRT\xff\xfe" (confirmed from
# live capture: frames 1 and 5 matched on event key=01110000).
# - "metadata" frames must be included (compliance config body).
# - The compliance block spans 2 frames; skipping either produces a
# truncated file that Blastware rejects.
skip = 13 if fi == 1 else 12
skip = 12 # sample chunks
contribution = _frame_body_bytes(frame, skip)
log.warning("write_blastware_file: fi=%d skip=%d raw_data=%d contribution=%d",
fi, skip, len(frame.data), len(contribution))
log.debug("write_blastware_file: fi=%d skip=%d raw_data=%d contribution=%d",
fi, skip, len(frame.data), len(contribution))
all_bytes.extend(contribution)
# Terminator contributes its content, which ends with the 26-byte footer.
@@ -754,7 +816,7 @@ def write_blastware_file(
# one shorter than chunk frames' 5-byte inner header. Confirmed 2026-04-21.
if term_frame is not None:
term_contribution = _frame_body_bytes(term_frame, 11)
log.warning(
log.debug(
"write_blastware_file: term_frame data_len=%d skip=11 "
"contribution_len=%d first8=%s",
len(term_frame.data),
@@ -763,17 +825,49 @@ def write_blastware_file(
)
all_bytes.extend(term_contribution)
log.warning(
log.debug(
"write_blastware_file: all_bytes total=%d last28=%s",
len(all_bytes),
bytes(all_bytes[-28:]).hex() if len(all_bytes) >= 28 else bytes(all_bytes).hex(),
)
if len(all_bytes) >= 26:
# NOTE: The "duplicate header+STRT strip" logic from v0.13.x has been
# REMOVED in v0.14.2. Under the v0.14.0 BW-exact 5A walk, body assembly
# is just contiguous concatenation of frame contributions in stream order
# (probe → meta@0x1002 → meta@0x1004 → samples → TERM), exactly as BW
# writes its files. The previous strip was matching the `00 12 03 00 STRT`
# byte sequence in legitimate waveform data — sample chunks at counter
# 0x1000 and beyond often contain those bytes coincidentally — and
# zeroing 25 bytes of valid samples per match. Compared to a known-good
# BW reference for the same 3-sec event 0, the strip introduced 26 bytes
# of zeros that BW did not have, then propagated alignment differences
# through the rest of the body. See decode_test/5-1-26/bw vs SFM diff
# at file[0x1012..0x102B] (2026-05-04 analysis).
# Find the first valid 0e 08 footer marker (v0.14.0).
footer_pos = -1
pos = 0
while True:
pos = bytes(all_bytes).find(b"\x0e\x08", pos)
if pos < 0 or pos + 26 > len(all_bytes):
break
yr = (all_bytes[pos + 4] << 8) | all_bytes[pos + 5]
if 2015 <= yr <= 2050:
footer_pos = pos
break
pos += 1
if footer_pos >= 0:
body = bytes(all_bytes[:footer_pos])
footer = bytes(all_bytes[footer_pos:footer_pos + 26])
log.debug(
"write_blastware_file: real 0e 08 footer at all_bytes[%d]; "
"truncating %d post-footer bytes",
footer_pos, len(all_bytes) - footer_pos - 26,
)
elif len(all_bytes) >= 26:
body = bytes(all_bytes[:-26])
footer = bytes(all_bytes[-26:])
else:
# Fallback: no terminator or very short stream → build footer from event metadata
body = bytes(all_bytes)
start_dt = _ts_from_model(event.timestamp)
stop_dt: Optional[datetime.datetime] = None
@@ -784,7 +878,7 @@ def write_blastware_file(
+ _encode_ts_be(start_dt)
+ _encode_ts_be(stop_dt)
+ b"\x00\x01\x00\x02\x00\x00"
+ b"\x00\x00" # CRC placeholder
+ b"\x00\x00"
)
# ── Write file ───────────────────────────────────────────────────────────
minimateplus/bw_ascii_report.py
+738
View File
@@ -0,0 +1,738 @@
"""
minimateplus/bw_ascii_report.py — parser for Blastware's per-event ASCII
report (the .TXT file BW writes alongside each saved event binary).
The ASCII export is the authoritative source for every "rich" per-event
field that BW computes from the waveform but never persists in the BW
binary itself:
- Per-channel PPV (Tran / Vert / Long / MicL)
- Peak Vector Sum + Peak Vector Sum Time
- Per-channel ZC Freq, Time of Peak, Peak Acceleration, Peak Displacement
- MicL PSPL, MicL Time of Peak, MicL ZC Freq
- Per-channel Sensor Self-Check (Test Freq / Test Ratio / Test Results)
- MicL Test Amplitude (mV)
- Battery, calibration date, monitor-log timestamps
Persisting these values into the SFM database lets the monthly-summary
review workflow ("show me events at Location X with PVS > 0.5") work
without depending on the (still-undecoded) waveform body codec.
Format (verified against decode-re/5-8-26 4-event bundle):
- One field per line, wrapped in double quotes: `"Field Name : Value"`
- Field/value separator: literal ` : ` (space-colon-space).
- Some field names contain an internal `:` already (e.g. `"Project:"`),
so we split on the FIRST ` : ` only.
- Some fields have unit suffixes: `"0.500 in/s"` / `"7.5 Hz"` / `"533 mv"`.
- A `"Monitor Log(s)"` marker line is followed by tab-separated rows
of `start_time<TAB>stop_time<TAB>description`.
- Final `"PC SW Version : ..."` line ends the metadata block.
- A blank line separates metadata from the sample table.
- Sample table starts with ` Tran <TAB> Vert <TAB>...`, then
one row per sample (tab-separated, right-padded numeric values).
- Geo channel values are in in/s; MicL in dB(L) (or 0.000 below threshold).
Because some metadata fields have whitespace quirks ("MicL Time of
Peak" has two spaces; the leading "Project:" value has its own colon),
we normalise whitespace in the key before lookup.
"""
from __future__ import annotations
import datetime
import re
from dataclasses import dataclass, field
from pathlib import Path
from typing import Dict, List, Optional, Tuple, Union
# ─────────────────────────────────────────────────────────────────────────────
# Output dataclasses
# ─────────────────────────────────────────────────────────────────────────────
@dataclass
class ChannelStats:
"""Per-channel derived stats, populated from an event report."""
ppv_ips: Optional[float] = None # in/s (geo channels only)
zc_freq_hz: Optional[float] = None # Hz
time_of_peak_s: Optional[float] = None # seconds (relative to trigger; can be negative)
peak_accel_g: Optional[float] = None # g (geo channels only)
peak_disp_in: Optional[float] = None # in (geo channels only)
# When BW writes "OORANGE" (Out Of Range — truncated) for a PPV
# value, the true peak exceeded the channel's full-scale range.
# We substitute the range max (e.g. 10.000 in/s for Normal range)
# as a lower bound, and flag here so downstream UI / alerts know
# to render "> 10 in/s" or "saturated" instead of trusting the
# value as an exact measurement.
ppv_saturated: bool = False
# Set when BW writes ">100 Hz" for ZC Freq — the zero-crossing
# algorithm's peak frequency exceeded the device's reporting
# ceiling (typically 100 Hz on V10.72). zc_freq_hz gets the
# threshold (100.0) as a lower bound; downstream UI renders ">100".
zc_freq_above_range: bool = False
@dataclass
class MicStats:
"""MicL-specific stats."""
weighting: Optional[str] = None # e.g. "Linear Weighting"
pspl_dbl: Optional[float] = None # dB(L)
zc_freq_hz: Optional[float] = None
time_of_peak_s: Optional[float] = None
# Set when BW writes "OORANGE" for PSPL — mic exceeded its
# measurement range. pspl_dbl gets the conservative upper bound
# 140 dBL (typical NL-43 max; some units cap at 148). Consumers
# should render "> 140 dB(L)" or similar when this flag is set.
pspl_saturated: bool = False
# Same semantics as ChannelStats.zc_freq_above_range — mic ZC
# peak exceeded device reporting ceiling.
zc_freq_above_range: bool = False
@dataclass
class SensorCheck:
"""Per-channel sensor self-check result.
Geo channels report a frequency + ratio; MicL reports a frequency +
amplitude (mV). All channels also have a Pass/Fail string.
"""
test_freq_hz: Optional[float] = None
test_ratio: Optional[float] = None # geo channels only
test_amplitude_mv: Optional[float] = None # MicL only
test_results: Optional[str] = None # "Passed" / "Failed"
@dataclass
class MonitorLogEntry:
"""One row of the trailing Monitor Log(s) block."""
start_time: Optional[datetime.datetime] = None
stop_time: Optional[datetime.datetime] = None
description: Optional[str] = None
# BW saturation marker — appears in PPV / Peak Vector Sum / similar
# numeric fields when the underlying measurement exceeded the
# channel's full-scale range (e.g., a geophone reading > 10 in/s at
# Normal range, or a mic exceeding its sensitivity ceiling). Treated
# as "≥ range_max" + a saturated flag rather than discarded.
# Appears as: ``"Tran PPV : OORANGE in/s"``
_OORANGE_MARKERS = ("OORANGE", "OUT OF RANGE")
def _is_oorange(value: str) -> bool:
"""True when a BW numeric field is an Out-Of-Range saturation marker."""
s = value.strip().upper()
return any(m in s for m in _OORANGE_MARKERS)
def _parse_above_range(value: str) -> Optional[float]:
"""For BW "above-range" markers like ">100 Hz", return the threshold.
BW writes ZC Freq as ">100 Hz" when the zero-crossing algorithm sees
a peak too fast to count (device cuts off at 100 Hz). Returns the
numeric portion after the '>' (e.g. 100.0), or None if `value` is
not an above-range marker.
"""
s = value.strip()
if not s.startswith(">"):
return None
return _parse_number(s[1:])
@dataclass
class BwAsciiReport:
"""Structured representation of one BW per-event ASCII export."""
# ── Identity ─────────────────────────────────────────────────────────────
event_type: Optional[str] = None # e.g. "Full Waveform"
serial: Optional[str] = None # e.g. "BE11529"
version: Optional[str] = None # firmware version line
file_name: Optional[str] = None # e.g. "M529LK44.AB0"
event_datetime: Optional[datetime.datetime] = None # parsed from Event Time + Event Date
# ── Trigger / recording config ──────────────────────────────────────────
trigger_channel: Optional[str] = None # e.g. "Vert" or "From Unit"
geo_trigger_level_ips: Optional[float] = None
pretrig_s: Optional[float] = None # negative seconds
record_time_s: Optional[float] = None
record_stop_mode: Optional[str] = None
sample_rate_sps: Optional[int] = None
battery_volts: Optional[float] = None
calibration_date: Optional[datetime.date] = None
calibration_by: Optional[str] = None # e.g. "Instantel"
units: Optional[str] = None # e.g. "in/s and dB(L)"
# ── Operator-supplied metadata ──────────────────────────────────────────
# Parsed by POSITION from the 4-line "User Notes" block BW writes
# between the `Units :` and `Geo Range :` lines. Position-based so
# the values populate correctly even when an operator renames the
# labels in Blastware's Compliance Setup → Notes tab (the 4 labels
# are user-editable, e.g. "Seis Loc:" → "Building:" → "Site Address:").
# The original labels BW wrote are preserved in `user_note_labels`
# so terra-view can render them as the operator named them.
project: Optional[str] = None # position 1 (BW default label "Project:")
client: Optional[str] = None # position 2 (BW default label "Client:")
operator: Optional[str] = None # position 3 (BW default label "User Name:")
sensor_location: Optional[str] = None # position 4 (BW default label "Seis Loc:")
# Maps canonical slot name → the literal label BW wrote in the ASCII
# export. Empty if the User Notes block wasn't present. Example
# when the operator renamed slot 4 to "Building:":
# {"project": "Project:", "client": "Client:",
# "operator": "User Name:", "sensor_location": "Building:"}
user_note_labels: Dict[str, str] = field(default_factory=dict)
# ── Geo channel scaling ─────────────────────────────────────────────────
geo_range_ips: Optional[float] = None # 10.000 / 1.250
# ── Per-channel derived stats (geo + mic) ───────────────────────────────
channels: Dict[str, ChannelStats] = field(default_factory=dict)
mic: MicStats = field(default_factory=MicStats)
# ── Vector sum ──────────────────────────────────────────────────────────
peak_vector_sum_ips: Optional[float] = None
peak_vector_sum_time_s: Optional[float] = None
# Saturation flag — set when BW writes "OORANGE" for the PVS. We
# then substitute sqrt(3) * geo_range_ips as a conservative upper
# bound (the theoretical maximum PVS when all 3 geo channels are
# simultaneously at full-scale). Consumers should display this as
# ">{value} in/s" or similar.
peak_vector_sum_saturated: bool = False
# Histograms additionally have an absolute date+time for the PVS
# (it occurred at a specific interval). Waveform reports show
# only the relative-time value above.
peak_vector_sum_when: Optional[datetime.datetime] = None
# ── Histogram-specific fields (populated only when Event Type starts
# with 'Histogram' / 'Full Histogram' / 'Histogram + Continuous') ──
histogram_start: Optional[datetime.datetime] = None
histogram_stop: Optional[datetime.datetime] = None
histogram_n_intervals: Optional[int] = None # e.g. 4, 1436
histogram_interval_size_str: Optional[str] = None # "1 minute" / "5 minutes" / "15 seconds"
histogram_interval_size_s: Optional[float] = None # parsed to seconds
# Per-channel absolute peak time+date (histogram-specific). For
# waveform events these are None — those reports use the channel's
# time_of_peak_s (relative to trigger) instead. Keyed by channel
# name ("Tran", "Vert", "Long", "MicL").
channel_peak_when: Dict[str, datetime.datetime] = field(default_factory=dict)
# ── Sensor self-check (per channel) ─────────────────────────────────────
sensor_check: Dict[str, SensorCheck] = field(default_factory=dict)
# ── Monitor log + tooling version ───────────────────────────────────────
monitor_log: List[MonitorLogEntry] = field(default_factory=list)
pc_sw_version: Optional[str] = None
# ── Sample table (optional; only parsed if requested) ───────────────────
# Each entry: (Tran, Vert, Long, MicL) in the report's units (geo
# channels in in/s, MicL in dB(L)). None when parse_samples=False.
samples: Optional[List[Tuple[float, float, float, float]]] = None
# ─────────────────────────────────────────────────────────────────────────────
# Helpers
# ─────────────────────────────────────────────────────────────────────────────
_KEY_NORMALISE_RE = re.compile(r"\s+")
_NUMERIC_RE = re.compile(r"^-?\d+(?:\.\d+)?")
def _normalise_key(k: str) -> str:
"""Collapse whitespace runs (incl. tabs) and strip — handles BW's
"MicL Time of Peak" double-space and leading-colon quirks."""
return _KEY_NORMALISE_RE.sub(" ", k).strip()
def _strip_quotes(line: str) -> str:
line = line.rstrip("\r\n")
if len(line) >= 2 and line.startswith('"') and line.endswith('"'):
return line[1:-1]
return line
def _parse_number(value: str) -> Optional[float]:
"""Pull the leading numeric portion out of a value like "0.500 in/s"."""
m = _NUMERIC_RE.match(value.strip())
if not m:
return None
try:
return float(m.group(0))
except ValueError:
return None
def _parse_int(value: str) -> Optional[int]:
n = _parse_number(value)
return None if n is None else int(round(n))
# Months exactly as BW writes them.
_MONTHS = {
"January": 1, "February": 2, "March": 3, "April": 4,
"May": 5, "June": 6, "July": 7, "August": 8,
"September": 9, "October": 10, "November": 11, "December": 12,
# Short forms used in monitor-log rows ("Apr 23 /26").
"Jan": 1, "Feb": 2, "Mar": 3, "Apr": 4, "Jun": 6, "Jul": 7,
"Aug": 8, "Sep": 9, "Oct": 10, "Nov": 11, "Dec": 12,
}
def _parse_event_date(s: str) -> Optional[datetime.date]:
"""Parse "April 23, 2026" or "May 8, 2026" → date."""
s = s.strip()
parts = s.replace(",", " ").split()
if len(parts) < 3:
return None
month_name, day_str, year_str = parts[0], parts[1], parts[2]
month = _MONTHS.get(month_name)
if month is None:
return None
try:
return datetime.date(int(year_str), month, int(day_str))
except ValueError:
return None
def _parse_iso_date(s: str) -> Optional[datetime.date]:
"""Parse "2026-05-16" → date. Histograms use ISO format for their
Start Date / Stop Date / Peak Date fields; waveforms use the
"May 8, 2026" long form which `_parse_event_date` handles."""
s = s.strip()
try:
return datetime.date.fromisoformat(s)
except ValueError:
return None
_INTERVAL_UNIT_SECONDS = {
"second": 1, "seconds": 1, "sec": 1, "secs": 1,
"minute": 60, "minutes": 60, "min": 60, "mins": 60,
"hour": 3600, "hours": 3600, "hr": 3600, "hrs": 3600,
}
def _parse_interval_size(s: str) -> Optional[float]:
"""Parse "1 minute" / "5 minutes" / "15 seconds" / "2 seconds" → seconds.
Handles the BW Compliance Setup → Histogram Interval values verbatim
("2 seconds", "5 seconds", "15 seconds", "1 minute", "5 minutes",
"15 minutes") plus a few defensive variants.
"""
if not s:
return None
parts = s.strip().split()
if len(parts) < 2:
return None
try:
n = float(parts[0])
except ValueError:
return None
unit_per_s = _INTERVAL_UNIT_SECONDS.get(parts[1].lower())
if unit_per_s is None:
return None
return n * unit_per_s
def _parse_event_time(s: str) -> Optional[datetime.time]:
"""Parse "15:56:35" → time."""
s = s.strip()
try:
h, m, sec = s.split(":")
return datetime.time(int(h), int(m), int(sec))
except (ValueError, IndexError):
return None
def _parse_calibration(value: str) -> Tuple[Optional[datetime.date], Optional[str]]:
"""Parse "April 29, 2025 by Instantel" → (date, "Instantel")."""
parts = value.split(" by ", 1)
date = _parse_event_date(parts[0])
by = parts[1].strip() if len(parts) > 1 else None
return date, by
def _parse_monitor_row(line: str) -> Optional[MonitorLogEntry]:
"""Parse a tab-separated monitor log row.
Format: `<start>\t<stop>\t<desc>` where each timestamp is BW's
short form "Mon DD /YY HH:MM:SS" (e.g. "Apr 23 /26 15:46:16").
Year is encoded as a 2-digit suffix; we expand "/26" → 2026.
"""
parts = line.split("\t")
if len(parts) < 2:
return None
start = _parse_monitor_ts(parts[0])
stop = _parse_monitor_ts(parts[1])
desc = parts[2].strip() if len(parts) > 2 else None
if start is None and stop is None and not desc:
return None
return MonitorLogEntry(start_time=start, stop_time=stop, description=desc)
def _parse_monitor_ts(s: str) -> Optional[datetime.datetime]:
"""Parse "Apr 23 /26 15:46:16" → datetime."""
s = s.strip()
parts = s.split()
if len(parts) < 4:
return None
month = _MONTHS.get(parts[0])
if month is None:
return None
try:
day = int(parts[1])
# parts[2] looks like "/26" → century-flip to 2026
yy = int(parts[2].lstrip("/"))
year = 2000 + yy if yy < 80 else 1900 + yy
h, m, sec = (int(x) for x in parts[3].split(":"))
return datetime.datetime(year, month, day, h, m, sec)
except (ValueError, IndexError):
return None
# ── User-notes positional slot map ──────────────────────────────────────────
#
# Blastware's Compliance Setup → Notes tab shows four operator-supplied
# fields whose LABELS the operator can rename (see screenshot in
# project archive). Defaults are "Project:" / "Client:" /
# "User Name:" / "Seis Loc:", but an operator using a different
# convention can rename them to anything ("Building:", "Site:",
# "Address:", etc.). The ASCII export reflects whatever the operator
# typed, so label-based matching is fragile.
#
# What IS reliable: BW always writes the 4 user-notes lines in the
# same order, contiguously between the `Units :` line and the
# `Geo Range :` line. We parse them by POSITION and preserve the
# operator's labels in `report.user_note_labels` so terra-view can
# render them as the operator intended.
_USER_NOTE_SLOTS = ("project", "client", "operator", "sensor_location")
# ─────────────────────────────────────────────────────────────────────────────
# Top-level parser
# ─────────────────────────────────────────────────────────────────────────────
def parse_report(text: Union[str, bytes], *, parse_samples: bool = False) -> BwAsciiReport:
"""Parse a BW per-event ASCII export into a structured BwAsciiReport.
Set ``parse_samples=True`` to also populate ``report.samples`` with
the trailing sample table. Default False because the table is
huge and most callers only want metadata for indexing.
"""
if isinstance(text, bytes):
text = text.decode("ascii", errors="replace")
report = BwAsciiReport()
# Pre-create channel stat slots so callers can rely on them existing.
for ch in ("Tran", "Vert", "Long", "MicL"):
report.channels.setdefault(ch, ChannelStats())
report.sensor_check.setdefault(ch, SensorCheck())
lines = text.splitlines()
i = 0
n = len(lines)
in_monitor_log_section = False
event_time_str: Optional[str] = None
event_date: Optional[datetime.date] = None
# User-notes block detection. We enter the block after parsing
# the "Units :" line and exit on the "Geo Range :" line. Inside,
# the first 4 unmatched `<label> : <value>` lines are assigned to
# the 4 canonical operator-supplied slots by POSITION (project,
# client, operator, sensor_location) regardless of what the
# operator named the labels in BW's Compliance Setup → Notes tab.
in_user_notes_block = False
user_note_position = 0
# Histogram-field staging — BW writes <Channel> Peak Time and
# <Channel> Peak Date on separate lines (and similarly Histogram
# Start Time / Date). We stash the partial value when the time
# line arrives and combine it when the matching date line arrives.
_hist_start_time: Optional[datetime.time] = None
_hist_stop_time: Optional[datetime.time] = None
_pending_peak_time: Dict[str, Optional[datetime.time]] = {}
_pvs_time_raw: Optional[str] = None # last Peak Vector Sum Time value, raw
while i < n:
raw_line = lines[i]
i += 1
# Blank line marks the start of the sample table.
if raw_line.strip() == "":
break
line = _strip_quotes(raw_line)
# Monitor log section: "Monitor Log(s)" header followed by N rows
# (still inside double-quoted lines), terminated by a non-row line
# like "PC SW Version : ..." or a blank line.
if not in_monitor_log_section and line.strip() == "Monitor Log(s)":
in_monitor_log_section = True
continue
if in_monitor_log_section:
# Heuristic: monitor rows contain a tab; the next "Field : Value"
# line ends the section.
if "\t" in line:
entry = _parse_monitor_row(line)
if entry:
report.monitor_log.append(entry)
continue
# Falls through to the field parser below; clear the flag.
in_monitor_log_section = False
# "Field : Value" — split on FIRST occurrence of " : "
idx = line.find(" : ")
if idx < 0:
continue
key = _normalise_key(line[:idx])
value = line[idx + 3 :].strip()
# ── Identity / config ────────────────────────────────────────────────
if key == "Event Type": report.event_type = value
elif key == "Serial Number": report.serial = value
elif key == "Version": report.version = value
elif key == "File Name": report.file_name = value
elif key == "Event Time": event_time_str = value
elif key == "Event Date": event_date = _parse_event_date(value)
elif key == "Trigger": report.trigger_channel = value
elif key == "Geo Trigger Level": report.geo_trigger_level_ips = _parse_number(value)
elif key == "Pre-trigger Length": report.pretrig_s = _parse_number(value)
elif key == "Record Time": report.record_time_s = _parse_number(value)
elif key == "Record Stop Mode": report.record_stop_mode = value
elif key == "Sample Rate": report.sample_rate_sps = _parse_int(value)
elif key == "Battery Level": report.battery_volts = _parse_number(value)
elif key == "Calibration":
report.calibration_date, report.calibration_by = _parse_calibration(value)
elif key == "Units":
report.units = value
# Entering the user-notes block. Next ~4 lines until
# "Geo Range :" are the operator-supplied notes.
in_user_notes_block = True
user_note_position = 0
elif key == "Geo Range":
# Exiting the user-notes block.
in_user_notes_block = False
report.geo_range_ips = _parse_number(value)
# User-notes block: assign by position (operator may have
# renamed the labels, so we don't trust them). Preserve the
# original labels in `user_note_labels` for downstream UIs
# (terra-view) that want to display them as the operator
# named them.
elif in_user_notes_block and user_note_position < len(_USER_NOTE_SLOTS):
slot = _USER_NOTE_SLOTS[user_note_position]
setattr(report, slot, value)
report.user_note_labels[slot] = key
user_note_position += 1
# ── Per-channel stats ────────────────────────────────────────────────
# All match the pattern "{Channel} <stat-name>"
elif key in (
"Tran PPV", "Vert PPV", "Long PPV",
"Tran ZC Freq", "Vert ZC Freq", "Long ZC Freq",
"Tran Time of Peak", "Vert Time of Peak", "Long Time of Peak",
"Tran Peak Acceleration", "Vert Peak Acceleration", "Long Peak Acceleration",
"Tran Peak Displacement", "Vert Peak Displacement", "Long Peak Displacement",
):
ch_name, stat = key.split(" ", 1)
cs = report.channels.setdefault(ch_name, ChannelStats())
if stat == "PPV":
if _is_oorange(value):
# Channel saturated — substitute range max as lower
# bound; flag so downstream UI can render "> 10 in/s".
cs.ppv_ips = report.geo_range_ips
cs.ppv_saturated = True
else:
cs.ppv_ips = _parse_number(value)
elif stat == "ZC Freq":
# ">100 Hz" → store threshold + flag; numeric → parse normally
threshold = _parse_above_range(value)
if threshold is not None:
cs.zc_freq_hz = threshold
cs.zc_freq_above_range = True
else:
cs.zc_freq_hz = _parse_number(value)
else:
num = _parse_number(value)
if stat == "Time of Peak": cs.time_of_peak_s = num
elif stat == "Peak Acceleration": cs.peak_accel_g = num
elif stat == "Peak Displacement": cs.peak_disp_in = num
# ── Histogram-specific fields ────────────────────────────────────────
# Histograms have Start/Stop time+date pairs + an interval count
# and size, plus per-channel absolute Peak Time/Date instead of
# the waveform's relative Time of Peak.
elif key == "Histogram Start Time":
_hist_start_time = _parse_event_time(value)
elif key == "Histogram Start Date":
_d = _parse_iso_date(value)
if _d and _hist_start_time:
report.histogram_start = datetime.datetime.combine(_d, _hist_start_time)
elif key == "Histogram Stop Time":
_hist_stop_time = _parse_event_time(value)
elif key == "Histogram Stop Date":
_d = _parse_iso_date(value)
if _d and _hist_stop_time:
report.histogram_stop = datetime.datetime.combine(_d, _hist_stop_time)
elif key == "Number of Intervals":
try:
report.histogram_n_intervals = int(float(value.strip()))
except ValueError:
pass
elif key == "Interval Size":
report.histogram_interval_size_str = value.strip()
report.histogram_interval_size_s = _parse_interval_size(value)
# ── Per-channel histogram Peak Date / Peak Time ──
# Lines like "Tran Peak Time : 22:31:38" + "Tran Peak Date : 2026-05-16"
elif key in ("Tran Peak Time", "Vert Peak Time", "Long Peak Time", "MicL Time"):
ch_name = "MicL" if key == "MicL Time" else key.split(" ", 1)[0]
_pending_peak_time[ch_name] = _parse_event_time(value)
elif key in ("Tran Peak Date", "Vert Peak Date", "Long Peak Date", "MicL Date"):
ch_name = "MicL" if key == "MicL Date" else key.split(" ", 1)[0]
_d = _parse_iso_date(value)
_t = _pending_peak_time.get(ch_name)
if _d and _t:
report.channel_peak_when[ch_name] = datetime.datetime.combine(_d, _t)
# ── Vector Sum ───────────────────────────────────────────────────────
elif key == "Peak Vector Sum":
if _is_oorange(value):
# PVS saturated — conservative upper bound is
# sqrt(3) * geo_range_ips (all 3 channels at full-scale).
# Real PVS could be lower (channels rarely peak
# simultaneously) but never higher within the range.
if report.geo_range_ips is not None:
import math as _math
report.peak_vector_sum_ips = _math.sqrt(3) * report.geo_range_ips
report.peak_vector_sum_saturated = True
else:
report.peak_vector_sum_ips = _parse_number(value)
# BW writes the PVS-time label with a typo: "Peak Vector Sum TimeSum"
# (looks like Sum got appended twice). Accept both forms. Confirmed
# against actual BW output on 2026-05-27 — every PVS-time line in
# the field examples (T190, T438, K557) uses the typo'd label.
elif key in ("Peak Vector Sum Time", "Peak Vector Sum TimeSum"):
report.peak_vector_sum_time_s = _parse_number(value)
_pvs_time_raw = value
elif key == "Peak Vector Sum Date":
# Histogram-mode PVS gets paired with a date. We may have
# captured 'Peak Vector Sum Time' as either a relative
# seconds float (waveform) or an HH:MM:SS string we
# interpreted as a number. For histograms, BW writes
# "Peak Vector Sum Time : 22:33:52" which _parse_number
# parses as 22.0 (loses information). When Peak Vector Sum
# Date arrives, re-parse the previous PVS time line as a
# clock time and combine into an absolute datetime.
_d = _parse_iso_date(value)
if _d and _pvs_time_raw is not None:
_t = _parse_event_time(_pvs_time_raw)
if _t:
report.peak_vector_sum_when = datetime.datetime.combine(_d, _t)
# The earlier seconds parse was bogus for histograms;
# clear it so consumers don't think it's a real offset.
report.peak_vector_sum_time_s = None
# ── Microphone block ────────────────────────────────────────────────
elif key == "Microphone":
report.mic.weighting = value
elif key == "MicL PSPL":
if _is_oorange(value):
# Mic saturated — substitute conservative upper bound 140 dBL.
report.mic.pspl_dbl = 140.0
report.mic.pspl_saturated = True
else:
report.mic.pspl_dbl = _parse_number(value)
# Mirror onto the "MicL" entry in channels so callers querying
# `channels["MicL"].ppv_ips` see something — but it's dB(L), not
# in/s, so we store as-is in the MicStats and mark the channel.
elif key == "MicL Time of Peak":
report.mic.time_of_peak_s = _parse_number(value)
cs = report.channels.setdefault("MicL", ChannelStats())
cs.time_of_peak_s = report.mic.time_of_peak_s
elif key == "MicL ZC Freq":
threshold = _parse_above_range(value)
if threshold is not None:
report.mic.zc_freq_hz = threshold
report.mic.zc_freq_above_range = True
else:
report.mic.zc_freq_hz = _parse_number(value)
cs = report.channels.setdefault("MicL", ChannelStats())
cs.zc_freq_hz = report.mic.zc_freq_hz
cs.zc_freq_above_range = report.mic.zc_freq_above_range
# ── Sensor self-check ────────────────────────────────────────────────
elif key in (
"Tran Test Freq", "Vert Test Freq", "Long Test Freq", "MicL Test Freq",
"Tran Test Ratio", "Vert Test Ratio", "Long Test Ratio",
"MicL Test Amplitude",
"Tran Test Results", "Vert Test Results", "Long Test Results", "MicL Test Results",
):
ch_name, stat = key.split(" ", 1)
sc = report.sensor_check.setdefault(ch_name, SensorCheck())
if stat == "Test Freq": sc.test_freq_hz = _parse_number(value)
elif stat == "Test Ratio": sc.test_ratio = _parse_number(value)
elif stat == "Test Amplitude": sc.test_amplitude_mv = _parse_number(value)
elif stat == "Test Results": sc.test_results = value
# ── Trailer ─────────────────────────────────────────────────────────
elif key == "PC SW Version":
report.pc_sw_version = value
# Unknown keys are silently dropped — forward-compat for future
# BW versions that may add fields.
# Combine event date + time into a datetime
if event_date is not None and event_time_str is not None:
t = _parse_event_time(event_time_str)
if t is not None:
report.event_datetime = datetime.datetime.combine(event_date, t)
if parse_samples:
report.samples = _parse_sample_table(lines, i)
return report
def _parse_sample_table(
lines: List[str], start: int,
) -> List[Tuple[float, float, float, float]]:
"""Parse the trailing sample table.
The table starts with a header row (" Tran <TAB>...") and continues
until EOF. Each data row is a tab-separated quartet of numeric values.
"""
samples: List[Tuple[float, float, float, float]] = []
seen_header = False
for line in lines[start:]:
line = line.rstrip("\r\n")
if not line.strip():
continue
cols = [c.strip() for c in line.split("\t") if c.strip()]
if not seen_header:
# Header row contains channel names; numeric rows don't.
if any(c in ("Tran", "Vert", "Long", "MicL") for c in cols):
seen_header = True
continue
if len(cols) < 4:
continue
try:
samples.append((
float(cols[0]), float(cols[1]),
float(cols[2]), float(cols[3]),
))
except ValueError:
continue
return samples
def parse_report_file(
path: Union[str, Path], *, parse_samples: bool = False,
) -> BwAsciiReport:
"""Convenience: read a .TXT file from disk and parse it."""
return parse_report(Path(path).read_bytes(), parse_samples=parse_samples)
minimateplus/client.py
+364 -150
View File
@@ -30,6 +30,7 @@ from __future__ import annotations
import datetime
import logging
import re
import struct
from typing import Optional
@@ -449,7 +450,7 @@ class MiniMateClient:
proto.confirm_erase_all()
log.info("delete_all_events: erase confirmed — device memory cleared")
def get_events(self, full_waveform: bool = False, debug: bool = False, stop_after_index: Optional[int] = None, skip_waveform_for_keys: Optional[set] = None, extra_chunks_after_metadata: int = 1) -> list[Event]:
def get_events(self, full_waveform: bool = False, debug: bool = False, stop_after_index: Optional[int] = None, skip_waveform_for_keys: Optional[set] = None, skip_waveform_for_events: Optional[dict] = None, extra_chunks_after_metadata: int = 1) -> list[Event]:
"""
Download all stored events from the device using the confirmed
1E → 0A → 0C → 5A → 1F event-iterator protocol.
@@ -497,37 +498,24 @@ class MiniMateClient:
events: list[Event] = []
idx = 0
# Legacy bare-key skip set is deprecated: the device's key counter
# resets to 0x01110000 after every memory erase, so a key in this set
# cannot be trusted to identify the same physical event across erases.
# If a caller still passes it, log a warning and ignore — full
# downloads will run for every event so the bug never silently bites.
if skip_waveform_for_keys:
log.warning(
"get_events: skip_waveform_for_keys is deprecated and unsafe "
"(post-erase key reuse); ignoring %d entries. Use "
"skip_waveform_for_events={key: timestamp_iso} instead.",
len(skip_waveform_for_keys),
)
skip_evts: dict[str, str] = dict(skip_waveform_for_events or {})
while data8[4:8] != b"\x00\x00\x00\x00":
cur_key = key4 # key for this event's 0A/1E-arm/0C/5A calls
log.info("get_events: record %d key=%s", idx, cur_key.hex())
# Fast-advance path: if this key is already downloaded, skip
# 1E-arm/0C/POLL/5A entirely. Only 0A + 1F(browse) are needed
# to advance the device's internal pointer to the next event.
# This is identical to the browse-mode walk in count_events().
if skip_waveform_for_keys and cur_key.hex() in skip_waveform_for_keys:
log.debug("get_events: key=%s already seen -- fast-advance only", cur_key.hex())
try:
proto.read_waveform_header(cur_key)
except ProtocolError as exc:
log.warning(
"get_events: 0A failed for key=%s (skip path): %s -- stopping",
cur_key.hex(), exc,
)
break
try:
key4, data8 = proto.advance_event(browse=True)
except ProtocolError as exc:
log.warning(
"get_events: 1F failed for key=%s (skip path): %s -- stopping",
cur_key.hex(), exc,
)
break
idx += 1
if stop_after_index is not None and idx > stop_after_index:
break
continue
ev = Event(index=idx)
ev._waveform_key = cur_key
@@ -574,72 +562,96 @@ class MiniMateClient:
"get_events: 0C failed for key=%s: %s", cur_key.hex(), exc
)
# SUB 1F (download-arm) — send token=0xFE BEFORE POLL+5A to arm the
# device's bulk stream state machine. Cache the returned key as a
# fallback for loop iteration when 5A fails (see iteration block below).
# Confirmed from 4-2-26 capture frames 66-67 (1F before frames 68-73 POLL).
arm_key4: Optional[bytes] = None
try:
arm_key4, _ = proto.advance_event(browse=False) # arm 5A
log.info("get_events: 1F(download) — 5A armed, arm_key=%s", arm_key4.hex())
except ProtocolError as exc:
log.warning("get_events: 1F(download) arm failed: %s", exc)
# ── Skip-5A decision based on (key, timestamp) match ──────
# If skip_waveform_for_events maps cur_key.hex() to a non-empty
# ISO timestamp matching what we just read from 0C, this is
# the same physical event we already have on disk — bypass
# the 1F(arm)+POLL+5A bulk download. Otherwise (no entry, or
# timestamp mismatch indicating post-erase reuse) fall through
# to the full download.
expected_ts = skip_evts.get(cur_key.hex(), "")
actual_ts = _event_timestamp_iso(ev)
skip_5a = bool(expected_ts and actual_ts and expected_ts == actual_ts)
if skip_5a:
log.info(
"get_events: key=%s (key, ts=%s) match — skipping 5A bulk download",
cur_key.hex(), actual_ts,
)
# POLL × 3 — BW sends 3 full POLL cycles between 1F and 5A.
# Confirmed from 4-2-26 BW TX capture (frames 68-73 before 5A at 74).
log.info("get_events: POLL × 3 before 5A")
for _p in range(3):
arm_key4: Optional[bytes] = None
a5_ok = False
if not skip_5a:
# SUB 1F (download-arm) — send token=0xFE BEFORE POLL+5A to arm the
# device's bulk stream state machine. Cache the returned key as a
# fallback for loop iteration when 5A fails (see iteration block below).
# Confirmed from 4-2-26 capture frames 66-67 (1F before frames 68-73 POLL).
try:
proto.poll()
arm_key4, _ = proto.advance_event(browse=False) # arm 5A
log.info("get_events: 1F(download) — 5A armed, arm_key=%s", arm_key4.hex())
except ProtocolError as exc:
log.warning("get_events: POLL %d failed: %s", _p, exc)
log.warning("get_events: 1F(download) arm failed: %s", exc)
# POLL × 3 — BW sends 3 full POLL cycles between 1F and 5A.
# Confirmed from 4-2-26 BW TX capture (frames 68-73 before 5A at 74).
log.info("get_events: POLL × 3 before 5A")
for _p in range(3):
try:
proto.poll()
except ProtocolError as exc:
log.warning("get_events: POLL %d failed: %s", _p, exc)
# SUB 5A — bulk waveform stream (uses cur_key, the event set up by 0A+1E+0C).
# By default (full_waveform=False): stop after frame 7 for metadata only.
# When full_waveform=True: fetch all chunks and decode raw ADC samples.
a5_ok = False
try:
if full_waveform:
log.info(
"get_events: 5A full waveform download for key=%s", cur_key.hex()
)
a5_frames = proto.read_bulk_waveform_stream(
cur_key, stop_after_metadata=False, max_chunks=128,
include_terminator=True,
)
if a5_frames:
a5_ok = True
ev._a5_frames = a5_frames # store for write_blastware_file
_decode_a5_metadata_into(a5_frames, ev)
_decode_a5_waveform(a5_frames, ev)
#
# Bypassed when skip_5a is True — the event is left with
# _a5_frames=None, which signals to the caller (e.g.
# ach_server.py) that this event was matched by (key, ts) and
# already has a stored .file in the persistent waveform store.
if not skip_5a:
try:
if full_waveform:
log.info(
"get_events: 5A decoded %d sample-sets",
len((ev.raw_samples or {}).get("Tran", [])),
"get_events: 5A full waveform download for key=%s", cur_key.hex()
)
else:
log.info(
"get_events: 5A metadata-only download for key=%s", cur_key.hex()
)
a5_frames = proto.read_bulk_waveform_stream(
cur_key, stop_after_metadata=True,
include_terminator=True,
extra_chunks_after_metadata=extra_chunks_after_metadata,
max_chunks=128,
)
if a5_frames:
a5_ok = True
ev._a5_frames = a5_frames # store for write_blastware_file
_decode_a5_metadata_into(a5_frames, ev)
log.debug(
"get_events: 5A metadata client=%r operator=%r",
ev.project_info.client if ev.project_info else None,
ev.project_info.operator if ev.project_info else None,
a5_frames = proto.read_bulk_waveform_stream(
cur_key, stop_after_metadata=False, max_chunks=128,
include_terminator=True,
)
except ProtocolError as exc:
log.warning(
"get_events: 5A failed for key=%s: %s — metadata unavailable",
cur_key.hex(), exc,
)
if a5_frames:
a5_ok = True
ev._a5_frames = a5_frames # store for write_blastware_file
_decode_a5_metadata_into(a5_frames, ev)
_decode_a5_waveform(a5_frames, ev)
log.info(
"get_events: 5A decoded %d sample-sets",
len((ev.raw_samples or {}).get("Tran", [])),
)
else:
log.info(
"get_events: 5A metadata-only download for key=%s", cur_key.hex()
)
a5_frames = proto.read_bulk_waveform_stream(
cur_key, stop_after_metadata=True,
include_terminator=True,
extra_chunks_after_metadata=extra_chunks_after_metadata,
max_chunks=128,
)
if a5_frames:
a5_ok = True
ev._a5_frames = a5_frames # store for write_blastware_file
_decode_a5_metadata_into(a5_frames, ev)
log.debug(
"get_events: 5A metadata client=%r operator=%r",
ev.project_info.client if ev.project_info else None,
ev.project_info.operator if ev.project_info else None,
)
except ProtocolError as exc:
log.warning(
"get_events: 5A failed for key=%s: %s — metadata unavailable",
cur_key.hex(), exc,
)
# SUB 1F — loop iteration.
#
@@ -652,7 +664,14 @@ class MiniMateClient:
# Confirmed from 4-3-26 browse-mode captures: browse=True params
# are correct for multi-event iteration. Conditional logic added
# 2026-04-06 to avoid post-failure state disruption.
if a5_ok:
#
# NEW 2026-05-06: when skip_5a=True we never entered the 5A
# state at all (we read 0A+1E(arm)+0C and chose to bypass).
# 1F(browse) is safe in this scenario — the device's iteration
# pointer is independent of the bulk-stream state machine, and
# we never put it into the half-attempted 5A state that the
# earlier "post-failure 1F disruption" warning is about.
if skip_5a or a5_ok:
# 5A succeeded — use browse 1F for reliable key advancement.
try:
key4, data8 = proto.advance_event(browse=True)
@@ -1174,6 +1193,27 @@ class MiniMateClient:
# Pure functions: bytes → model field population.
# Kept here (not in models.py) to isolate protocol knowledge from data shapes.
def _event_timestamp_iso(event: Event) -> str:
"""
Return a stable ISO-8601 string for the event's 0C-derived timestamp,
or "" if the event has no timestamp populated.
The format intentionally matches what `bridges/ach_server.py` writes
into `ach_state.json:downloaded_events[*]` so the (key, ts) compare
in get_events()'s skip path is a simple string equality.
"""
ts = getattr(event, "timestamp", None)
if ts is None:
return ""
try:
return datetime.datetime(
ts.year, ts.month, ts.day,
ts.hour or 0, ts.minute or 0, ts.second or 0,
).isoformat()
except Exception:
return str(ts)
def _decode_serial_number(data: bytes) -> DeviceInfo:
"""
Decode SUB EA (SERIAL_NUMBER_RESPONSE) payload into a new DeviceInfo.
@@ -1323,28 +1363,40 @@ def _decode_waveform_record_into(data: bytes, event: Event) -> None:
Modifies event in-place.
"""
# ── Record type ───────────────────────────────────────────────────────────
# Decoded from byte[1] (sub_code) first so we can gate timestamp parsing.
# ── Record type + format detection ────────────────────────────────────────
# `record_type` is the user-facing label ("Waveform" for any triggered
# event regardless of timestamp-header layout). `fmt` is the internal
# format code used to pick the right Timestamp parser; it stays
# internal and doesn't leak to the API / sidecar / UI.
try:
event.record_type = _extract_record_type(data)
except Exception as exc:
log.warning("waveform record type decode failed: %s", exc)
fmt = _detect_record_format(data)
# ── Timestamp ─────────────────────────────────────────────────────────────
# 9-byte format for sub_code=0x10 Waveform records:
# [day][sub_code][month][year:2 BE][unknown][hour][min][sec]
# sub_code=0x10 and sub_code=0x03 have different timestamp byte layouts.
# Both confirmed against Blastware event reports (BE11529, 2026-04-01 and 2026-04-03).
if event.record_type == "Waveform":
# Three timestamp-header layouts have been observed across BE11529
# firmware S338.17 — each picks a different Timestamp parser:
# "single_shot": 9-byte [day][0x10][month][year:2][unk][h][m][s]
# "continuous": 10-byte [0x10][day][0x10][month][year:2][unk][h][m][s]
# "short": 8-byte [day][month][year:2][unk][h][m][s]
# All decoded into the same Timestamp dataclass — only the byte
# offsets differ.
if fmt == "single_shot":
try:
event.timestamp = Timestamp.from_waveform_record(data)
except Exception as exc:
log.warning("waveform record timestamp decode failed: %s", exc)
elif event.record_type == "Waveform (Continuous)":
log.warning("single_shot record timestamp decode failed: %s", exc)
elif fmt == "continuous":
try:
event.timestamp = Timestamp.from_continuous_record(data)
except Exception as exc:
log.warning("continuous record timestamp decode failed: %s", exc)
elif fmt == "short":
try:
event.timestamp = Timestamp.from_short_record(data)
except Exception as exc:
log.warning("short record timestamp decode failed: %s", exc)
# ── Peak values (per-channel PPV + Peak Vector Sum) ───────────────────────
try:
@@ -1449,22 +1501,69 @@ def _decode_a5_waveform(
(BULK_WAVEFORM_STREAM) frame payloads and populate event.raw_samples,
event.total_samples, event.pretrig_samples, and event.rectime_seconds.
This requires ALL A5 frames (stop_after_metadata=False), not just the
metadata-bearing subset.
Wired up 2026-05-11 to the verified ``decode_waveform_v2`` codec (see
``minimateplus/waveform_codec.py`` and ``docs/waveform_codec_re_status.md``).
Replaces the legacy int16 LE decoder, which produced full-scale ±32K
noise on every event because the body bytes are encoded, not raw
samples.
── Waveform format (confirmed from 4-2-26 blast capture) ───────────────────
The blast waveform is 4-channel interleaved signed 16-bit little-endian,
8 bytes per sample-set:
Output convention (preserved from the legacy decoder):
``event.raw_samples`` is a dict with keys "Tran", "Vert", "Long",
"MicL" mapping to lists of **int16 ADC counts**. Multiply by
``geo_range / 32768`` for geo channels to get in/s; use
:func:`minimateplus.waveform_codec.mic_count_to_db` for mic dB(L).
``total_samples`` / ``pretrig_samples`` / ``rectime_seconds`` are set
to ``None`` so the caller backfills from compliance_config (the
authoritative source — STRT fields aren't reliable).
"""
from .waveform_codec import decode_a5_frames
event.total_samples = None
event.pretrig_samples = None
event.rectime_seconds = None
if not frames_data:
log.debug("_decode_a5_waveform: no frames provided")
return
decoded = decode_a5_frames(frames_data)
if decoded is None:
log.warning("_decode_a5_waveform: codec returned no samples")
return
event.raw_samples = decoded
log.debug(
"_decode_a5_waveform: decoded %d/%d/%d/%d samples (T/V/L/M)",
len(decoded.get("Tran", [])),
len(decoded.get("Vert", [])),
len(decoded.get("Long", [])),
len(decoded.get("MicL", [])),
)
def _decode_a5_waveform_LEGACY(
frames_data: list[S3Frame],
event: Event,
) -> None:
"""
LEGACY decoder — kept for reference only. DO NOT CALL.
This is the int16 LE decoder that produced full-scale ±32K noise
on every event. Retracted 2026-05-08; replaced 2026-05-11 with
the verified codec in :mod:`minimateplus.waveform_codec`. See
``docs/instantel_protocol_reference.md §7.6.1`` for the full history.
── Waveform format (LEGACY — WRONG) ────────────────────────────────
Claimed 4-channel interleaved signed 16-bit little-endian, 8 bytes
per sample-set:
[T_lo T_hi V_lo V_hi L_lo L_hi M_lo M_hi] × N
where T=Tran, V=Vert, L=Long, M=Mic. Channel ordering follows the
Blastware convention [Tran, Vert, Long, Mic] = [ch0, ch1, ch2, ch3].
where T=Tran, V=Vert, L=Long, M=Mic.
⚠️ Channel ordering is a confirmed CONVENTION — the physical ordering on
the ADC mux is not independently verifiable from the saturating blast
captures we have. The convention is consistent with Blastware labeling
(Tran is always the first channel field in the A5 STRT+waveform stream).
The body bytes are actually a tagged delta+RLE stream — this
interpretation was wrong.
── Frame structure ──────────────────────────────────────────────────────────
A5[0] (probe response):
@@ -1518,46 +1617,109 @@ def _decode_a5_waveform(
log.warning("_decode_a5_waveform: STRT record truncated (%dB)", len(strt))
return
total_samples = struct.unpack_from(">H", strt, 8)[0]
pretrig_samples = struct.unpack_from(">H", strt, 16)[0]
rectime_seconds = strt[18]
# STRT byte layout (21 bytes; verified against M529LIY6 reference files
# and re-confirmed against live BE11529 captures, 2026-05-08):
# [0:4] b'STRT'
# [4:6] 0xff 0xfe sentinel
# [6:10] end_key 4-byte BE flash address where event ends
# [10:14] start_key 4-byte BE flash address where event starts
# [14:18] device-specific (semantics not pinned; values vary across events
# and don't hold authoritative total_samples / pretrig)
# [18] 0x46 record-type marker (NOT rectime)
# [19] device-specific
# [20] sometimes rectime, sometimes 0 — not reliable
#
# AUTHORITATIVE values must come from compliance_config (sample_rate,
# record_time) and from end_offset - start_offset arithmetic (event size).
# Earlier code claimed STRT[8:10]=total_samples and STRT[16:18]=pretrig;
# those positions actually overlap end_key low-word and dev-specific bytes
# respectively. We surface the address-derived event size so consumers
# can sanity-check chunk-loop bounds, but `total_samples` per channel must
# be derived externally (sample_rate × record_time, or computed from the
# decoded sample count below).
end_key = strt[6:10]
start_key = strt[10:14]
end_offset_in_strt = (end_key[2] << 8) | end_key[3]
start_offset_in_strt = (start_key[2] << 8) | start_key[3]
is_event_1 = (start_offset_in_strt == 0x0000)
event.total_samples = total_samples
event.pretrig_samples = pretrig_samples
event.rectime_seconds = rectime_seconds
# Don't trust STRT for these — leave them as None so the caller can
# backfill from compliance_config (the authoritative source).
event.total_samples = None
event.pretrig_samples = None
event.rectime_seconds = None
log.debug(
"_decode_a5_waveform: STRT total_samples=%d pretrig=%d rectime=%ds",
total_samples, pretrig_samples, rectime_seconds,
"_decode_a5_waveform: STRT start_key=%s end_key=%s "
"start_off=0x%04X end_off=0x%04X is_event_1=%s "
"dev-specific[14:18]=%s strt[20]=0x%02X",
start_key.hex(), end_key.hex(),
start_offset_in_strt, end_offset_in_strt, is_event_1,
strt[14:18].hex(), strt[20],
)
# ── Collect per-frame waveform bytes with global offset tracking ─────────
# global_offset is the cumulative byte count across all frames, used to
# compute the channel alignment at each frame boundary.
#
# Frame layout under the v0.14.0+ walk:
# frames_data[0] = probe response (page_addr 0x0000;
# contains STRT + post-STRT data)
# frames_data[1..2] = (event 1 only) metadata pages
# page_addr = 0x1002 / 0x1004
# frames_data[mid] = sample chunks at flash addresses
# 0x0600, 0x0800, … (page_addr in
# {0x0600..0x1FFE})
# frames_data[last] = TERM response (page_key=0x0000)
#
# We identify metadata pages by their PAGE ADDRESS at db.data[4:6] (the
# 2-byte counter the device echoes back), NOT by content scan. An earlier
# needle-based detection (b"Project:", b"Client:", etc.) was the wrong
# layer of abstraction:
# • The actual metadata pages 0x1002 / 0x1004 do NOT contain ASCII
# project strings on this firmware (S338.17 / BE11529).
# • The strings physically live at flash address 0x1600 — which falls
# inside the sample-chunk address range. Skipping that frame would
# drop a real sample chunk.
# BW handles the "samples region happens to contain string bytes" case
# by just rendering the bytes verbatim; we do the same.
_METADATA_PAGES = (b"\x10\x02", b"\x10\x04")
chunks: list[tuple[int, bytes]] = [] # (frame_idx, waveform_bytes)
global_offset = 0
for fi, db in enumerate(frames_data):
page_addr = db.data[4:6] if len(db.data) >= 6 else b""
w = db.data[7:] # frame.data[7:]
# A5[0]: waveform begins after the 21-byte STRT record and 6-byte preamble.
# Layout: STRT(21B) + null-pad(2B) + 0xFF sentinel(4B) = 27 bytes total.
# A5[0]: probe response. Two cases:
# - Event 1 (start_offset_in_strt == 0x0000): the bytes after STRT
# are the device's *pre-event reserved area* (flash 0x0046 to
# 0x0600), NOT samples. We must skip them; samples begin at
# the first dedicated chunk frame at counter=0x0600.
# - Event N (continuation, start_offset != 0x0000): the bytes after
# the STRT record ARE the first slice of real samples for the
# event (BW's chunk loop addresses the probe as a sample chunk).
if fi == 0:
sp = w.find(b"STRT")
if sp < 0:
continue
if is_event_1:
# No usable samples in the probe — pre-event reserved bytes.
continue
# Layout: STRT(21B) + null-pad(2B) + 0xFF sentinel(4B) = 27 bytes total.
wave = w[sp + 27 :]
# Frame 7 carries event-time metadata strings ("Project:", "Client:", …)
# and no waveform ADC data.
elif fi == 7:
# Skip the dedicated metadata pages (event 1 only): page_addr 0x1002 / 0x1004.
elif page_addr in _METADATA_PAGES:
log.debug(
"_decode_a5_waveform: skipping metadata page fi=%d page_addr=%s",
fi, page_addr.hex(),
)
continue
# Terminator frames have page_key=0x0000 and are excluded upstream
# (read_bulk_waveform_stream returns early on page_key==0).
# No hardcoded frame-index skip here — all non-metadata frames are data.
# Sample chunk (or TERM): strip the 8-byte per-frame header.
else:
# Strip the 8-byte per-frame header (ctr + 6 zero bytes)
if len(w) < 8:
continue
wave = w[8:]
@@ -1571,10 +1733,8 @@ def _decode_a5_waveform(
total_bytes = global_offset
n_sets = total_bytes // 8
log.debug(
"_decode_a5_waveform: %d chunks, %dB total → %d complete sample-sets "
"(%d of %d expected; %.0f%%)",
len(chunks), total_bytes, n_sets, n_sets, total_samples,
100.0 * n_sets / total_samples if total_samples else 0,
"_decode_a5_waveform: %d chunks, %dB total → %d complete sample-sets",
len(chunks), total_bytes, n_sets,
)
if n_sets == 0:
@@ -1632,38 +1792,85 @@ def _decode_a5_waveform(
"Tran": tran,
"Vert": vert,
"Long": long_,
"Mic": mic,
"MicL": mic,
}
def _detect_record_format(data: bytes) -> Optional[str]:
"""
Detect which timestamp-header format a 210-byte 0C waveform record uses.
THREE formats observed on BE11529 firmware S338.17:
"single_shot" — 9-byte header:
[day] [0x10] [month] [year_BE:2] [unknown] [hour] [min] [sec]
sub_code=0x10 at byte [1]. Year at [3:5].
"continuous" — 10-byte header:
[0x10] [day] [0x10] [month] [year_BE:2] [unknown] [hour] [min] [sec]
marker 0x10 at byte [0] AND byte [2]. Year at [4:6].
"short" — 8-byte header (NEW 2026-05-01):
[day] [month] [year_BE:2] [unknown] [hour] [min] [sec]
No marker bytes. Year at [2:4].
Each format has the year (uint16 BE) at a UNIQUE byte position, so we can
disambiguate by scanning each candidate position and picking the one
where the year falls in a sane range (2015..2050).
Returns "single_shot" / "continuous" / "short" or None if no format matches.
"""
if len(data) < 8:
return None
def _sane_year(hi: int, lo: int) -> bool:
y = (hi << 8) | lo
return 2015 <= y <= 2050
# Order matters: prefer formats with stronger marker-byte evidence first.
if data[1] == 0x10 and len(data) >= 9 and _sane_year(data[3], data[4]):
return "single_shot"
if (data[0] == 0x10 and data[2] == 0x10
and len(data) >= 10 and _sane_year(data[4], data[5])):
return "continuous"
if _sane_year(data[2], data[3]):
return "short"
return None
def _extract_record_type(data: bytes) -> Optional[str]:
"""
Decode the recording mode from byte[1] of the 210-byte waveform record.
Return a user-facing name for a waveform record. All three internal
timestamp-header layouts represent the *same* user concept — a
triggered seismic event — so they all surface as just "Waveform".
Byte[1] is the sub-record code that immediately follows the day byte in the
9-byte timestamp header at the start of each waveform record:
[day:1] [sub_code:1] [month:1] [year:2 BE] ...
The internal format code is preserved for parsing logic (timestamp
decoder selection) but doesn't leak into the API / UI / sidecar.
Callers that need the raw layout can call `_detect_record_format`
directly.
Confirmed codes (✅ 2026-04-01):
0x10 → "Waveform" (continuous / single-shot mode)
Histogram mode code is not yet confirmed — a histogram event must be
captured with debug=true to identify it. Returns None for unknown codes.
Background: across BE11529 firmware S338.17 we've observed three
different byte layouts for the timestamp header at the start of the
0C record (8 / 9 / 10 bytes, distinguished by the position of the
BE-encoded year and the presence of `0x10` marker bytes). An older
revision of this code labelled them "Waveform" / "Waveform
(Continuous)" / "Waveform (Short)", which created the false
impression that there were three distinct event "types" the user
could configure. In reality the user only ever picks Single Shot
vs Continuous vs Histogram in the compliance config — the byte
layout is a firmware-internal detail that doesn't always correlate
with that choice.
"""
if len(data) < 2:
return None
code = data[1]
if code == 0x10:
fmt = _detect_record_format(data)
if fmt in ("single_shot", "continuous", "short"):
return "Waveform"
if code == 0x03:
# Continuous mode waveform record (confirmed by user — NOT a monitor log).
# The byte layout differs from 0x10 single-shot records: the timestamp
# fields decode as garbage under the 0x10 waveform layout.
# TODO: confirm correct timestamp layout for 0x03 records from a known-time event.
return "Waveform (Continuous)"
log.warning("_extract_record_type: unknown sub_code=0x%02X", code)
return f"Unknown(0x{code:02X})"
if len(data) >= 3:
log.warning(
"_extract_record_type: unrecognized header: data[0:3]=%02X %02X %02X",
data[0], data[1], data[2],
)
return f"Unknown({data[0]:02X}.{data[1]:02X}.{data[2]:02X})"
return None
def _extract_peak_floats(data: bytes) -> Optional[PeakValues]:
"""
@@ -2326,10 +2533,17 @@ def _decode_0a_partial_header(raw_data: bytes, index: int, key4: bytes) -> Optio
ts2 = try_ts(raw_data[ts1_end + 1:ts1_end + 1 + ts_size])
# Extract serial and geo threshold from "BE11529\0" and "Geo: X.XXX in/s\0".
#
# Match any two-letter family prefix, not a literal "BE" — a BlastMate
# reports "BA10895", and the old `find(b"BE")` returned -1 on one. That
# skipped this whole block, so the geo threshold went missing along with
# the serial. Requiring the NUL terminator in the pattern also makes the
# match stricter than the bare two-byte search it replaces.
serial: Optional[str] = None
geo_ips: Optional[float] = None
serial_pos = raw_data.find(b"BE")
serial_match = re.search(rb"[A-Z]{2}\d{3,6}(?=\x00)", raw_data)
serial_pos = serial_match.start() if serial_match else -1
if serial_pos >= 0:
# Read null-terminated serial starting at serial_pos.
null_pos = raw_data.find(b"\x00", serial_pos)
minimateplus/event_file_io.py
+1044
View File
File diff suppressed because it is too large Load Diff
minimateplus/framing.py
+181 -31
View File
@@ -111,20 +111,24 @@ def build_5a_frame(offset_word: int, raw_params: bytes) -> bytes:
verified against this algorithm on 2026-04-02).
Args:
offset_word: 16-bit offset (0x1004 for probe/chunks, 0x005A for term).
raw_params: 10 or 11 params bytes (from bulk_waveform_params or
bulk_waveform_term_params). 0x10 bytes in params are
written RAW — NOT DLE-stuffed. Confirmed 2026-04-06 by
comparing wire bytes: BW sends bare `10 04` for chunk 1
(counter=0x1004), not stuffed `10 10 04`. Device reads
params at fixed byte positions; stuffing shifts the bytes
and corrupts the counter, causing device to ignore the frame.
offset_word: 16-bit offset. For probe/chunks/metadata pages this is
`0x1002`. For the proper TERM frame this is computed by
`bulk_waveform_term_v2()` from the STRT-derived
`end_offset`.
raw_params: 10, 11, or 12 params bytes (from `bulk_waveform_params`
for probes/samples, `bulk_waveform_term_v2` for TERM, or
a manually-built 12-byte block for the metadata pages
0x1002 / 0x1004). See gotcha #3 below — params region
uses partial DLE stuffing of 0x10 bytes.
Returns:
Complete frame bytes: [ACK][STX][stuffed_section][chk][ETX]
"""
if len(raw_params) not in (10, 11):
raise ValueError(f"raw_params must be 10 or 11 bytes, got {len(raw_params)}")
if len(raw_params) not in (10, 11, 12):
# 10 = termination params; 11 = regular probe / chunk params;
# 12 = metadata-page params (extra trailing 0x00 — BW byte-perfect quirk
# for the two fixed metadata reads at counter=0x1002 and 0x1004).
raise ValueError(f"raw_params must be 10/11/12 bytes, got {len(raw_params)}")
# Build stuffed section between STX and checksum
s = bytearray()
@@ -134,8 +138,40 @@ def build_5a_frame(offset_word: int, raw_params: bytes) -> bytes:
s += b"\x00" # field3
s += bytes([(offset_word >> 8) & 0xFF, # offset_hi — raw, NOT stuffed
offset_word & 0xFF]) # offset_lo
for b in raw_params: # params — NOT DLE-stuffed (raw bytes, match BW wire format)
# Params — partial DLE stuffing of 0x10 bytes (CONFIRMED 2026-05-05).
#
# The device's de-stuffing rule for params is:
# • `10 10` → de-stuffs to `10`
# • `10 02/03/04` → kept literal (these are inner-frame markers)
# • `10 X` other → de-stuffs to just `X` (drops the 0x10)
#
# So for any 0x10 byte in the *logical* params that is followed by a
# byte NOT in {0x02, 0x03, 0x04, 0x10}, we must double the 0x10 on the
# wire (`10 X` → `10 10 X`) so the device's de-stuffer reproduces the
# original `10 X` pair. Without this, counter values with `0x10` in
# the high byte (e.g. counter=0x1000 has params bytes `10 00`) are
# silently corrupted to `0x__00` on the device side, and the device
# responds for the wrong address — for counter=0x1000 it returns the
# probe response (counter=0x0000), which contains the file header +
# STRT. That STRT block then lands in the assembled file body and
# Blastware rejects the file as malformed.
#
# Confirmed against BW capture 5-1-26 / bwcap3sec frame 20: params
# logical bytes `00 01 11 10 00 00 00 00 00 00 00` (counter=0x1000)
# are encoded on the wire as `00 01 11 10 10 00 00 00 00 00 00 00`.
# BW frames 13/14 (meta @ 0x1002 / 0x1004) leave `10 02` and `10 04`
# raw — the device handles those literal pairs correctly.
i = 0
while i < len(raw_params):
b = raw_params[i]
s.append(b)
if (
b == 0x10
and i + 1 < len(raw_params)
and raw_params[i + 1] not in (0x02, 0x03, 0x04, 0x10)
):
s.append(0x10) # double the 0x10 so it survives device de-stuffing
i += 1
# DLE-aware checksum: for 0x10 XX pairs count XX; for lone bytes count them
chk, i = 0, 0
@@ -398,28 +434,26 @@ def bulk_waveform_params(key4: bytes, counter: int, *, is_probe: bool = False) -
def bulk_waveform_term_params(key4: bytes, counter: int) -> bytes:
"""
Build the 10-byte params block for the SUB 5A termination request.
⛔ DEPRECATED — DO NOT USE IN NEW CODE.
The termination request uses offset=0x005A and a DIFFERENT params layout —
the leading 0x00 byte is dropped, key4[0:2] shifts to params[0:2], and the
counter high byte is at params[2]:
This is the v1 termination params helper, paired with the broken
`_BULK_TERM_OFFSET = 0x005A` magic offset_word. Together they produce a
~100-byte device-side terminator response that does NOT contain the
partial-last-chunk waveform tail or the 26-byte file footer. Files
reconstructed using this terminator are missing their last ~512 bytes of
waveform data and have a synthesized footer that disagrees with what BW
would have written.
params[0] = key4[0]
params[1] = key4[1]
params[2] = (counter >> 8) & 0xFF
params[3:] = zeros
**For new code, use `bulk_waveform_term_v2(key4, end_offset, last_chunk_counter)`**
which computes the correct offset_word + params from the STRT-derived
`end_offset`. v2 produces wire bytes that match BW exactly across all
tested events (4-27-26 / 5-1-26 / 5-4-26 captures).
Counter for the termination request = last_regular_counter + 0x0400.
Confirmed from 1-2-26 BW TX capture: final request (frame 83) uses
offset=0x005A, params[0:3] = key4[0:2] + term_counter_hi.
Args:
key4: 4-byte waveform key.
counter: Termination counter (= last regular counter + 0x0400).
Returns:
10-byte params block.
This function is retained ONLY for the defensive fallback path in
`read_bulk_waveform_stream()` that triggers when STRT parsing fails or no
chunks are fetched (= a malformed event or an unexpected device state).
The fallback already logs a WARNING when it activates; if you see that
warning, the bug is upstream — STRT should have been parseable.
"""
if len(key4) != 4:
raise ValueError(f"waveform key must be 4 bytes, got {len(key4)}")
@@ -430,6 +464,123 @@ def bulk_waveform_term_params(key4: bytes, counter: int) -> bytes:
return bytes(p)
def bulk_waveform_term_v2(
key4: bytes,
end_offset: int,
last_chunk_counter: int,
) -> tuple[int, bytes]:
"""
Compute the SUB 5A TERM frame's offset_word and 10-byte params block.
Confirmed across 3 events (4-27-26 + 5-1-26 captures):
next_boundary = last_chunk_counter + 0x0200
offset_word = end_offset - next_boundary (residual byte count)
params[0] = key4[0] (= 0x01 on every observed device)
params[1] = key4[1] (= 0x11)
params[2] = (next_boundary >> 8) & 0xFF
params[3] = next_boundary & 0xFF
params[4:10] = zeros
Verification:
| end_offset | last_chunk | next_boundary | offset_word | params[2:4] |
| 0x1ABE | 0x1800 | 0x1A00 | 0x00BE | 1A 00 |
| 0x21F2 | 0x1E00 | 0x2000 | 0x01F2 | 20 00 |
| 0x417E | 0x3E38 | 0x4038 | 0x0146 | 40 38 |
The device receives `requested_address = (params[2] << 8) | offset_word`
and replies with `(end_offset - next_boundary)` bytes of waveform tail
starting at `next_boundary` — including the 26-byte file footer.
Args:
key4: 4-byte waveform key for this event.
end_offset: Event-end pointer (= `(end_key[2] << 8) | end_key[3]`
from the STRT record at data[23:27] of A5[0]).
last_chunk_counter: Counter of the last full 0x0200-byte chunk fetched
(the chunk that covers [last_chunk_counter,
last_chunk_counter + 0x0200)).
Returns:
(offset_word, params10) tuple. Pass as
`build_5a_frame(offset_word, params)`.
Raises:
ValueError: on inconsistent inputs.
"""
if len(key4) != 4:
raise ValueError(f"waveform key must be 4 bytes, got {len(key4)}")
next_boundary = last_chunk_counter + 0x0200
if next_boundary > 0xFFFF:
raise ValueError(
f"next_boundary 0x{next_boundary:04X} exceeds uint16; check inputs"
)
if end_offset <= last_chunk_counter:
raise ValueError(
f"end_offset 0x{end_offset:04X} must be > "
f"last_chunk_counter 0x{last_chunk_counter:04X}"
)
offset_word = end_offset - next_boundary
if offset_word < 0:
# Last chunk overshot end_offset; caller should have stopped one chunk
# earlier. Treat as zero residual.
offset_word = 0
if offset_word > 0xFFFF:
raise ValueError(
f"offset_word 0x{offset_word:04X} exceeds uint16"
)
p = bytearray(10)
p[0] = key4[0]
p[1] = key4[1]
p[2] = (next_boundary >> 8) & 0xFF
p[3] = next_boundary & 0xFF
return offset_word, bytes(p)
# ── End-offset extraction from STRT record ────────────────────────────────────
STRT_MARKER = b"STRT"
def parse_strt_end_offset(a5_data: bytes) -> Optional[int]:
"""
Extract the event-end offset from the STRT record in an A5 response payload.
The first A5 response (the probe response, or the first chunk for events
with non-zero start_key[2:4]) contains a STRT record at byte offset 17 of
`data`. Layout:
data[17:21] "STRT"
data[21:23] ff fe sentinel
data[23:27] end_key ← 4-byte key of where this event ENDS
data[27:31] start_key
...
Returns `(end_key[2] << 8) | end_key[3]` — the absolute device-buffer
address where the event ends. Use this to bound the chunk loop and to
compute the TERM frame.
Verified end_offset values:
| event start_key | end_key | end_offset |
| 01110000 | 01111ABE | 0x1ABE |
| 01110000 | 011121F2 | 0x21F2 |
| 011121F2 | 0111417E | 0x417E |
Args:
a5_data: The `data` field of an A5 response frame (frame.data).
Returns:
The end_offset (uint16) if STRT is found, else None.
"""
pos = a5_data.find(STRT_MARKER)
if pos < 0 or pos + 10 > len(a5_data):
return None
# data[pos+4:pos+6] is "ff fe"; data[pos+6:pos+10] is end_key.
end_key = a5_data[pos + 6 : pos + 10]
if len(end_key) < 4:
return None
return (end_key[2] << 8) | end_key[3]
# ── Pre-built POLL frames ─────────────────────────────────────────────────────
#
# POLL (SUB 0x5B) uses the same two-step pattern as all other reads — the
@@ -470,7 +621,6 @@ class S3Frame:
# ── Streaming S3 frame parser ─────────────────────────────────────────────────
class S3FrameParser:
"""
Incremental byte-stream parser for S3→BW response frames.
minimateplus/histogram_codec.py
+487
View File
@@ -0,0 +1,487 @@
"""
histogram_codec.py — decoder for MiniMate Plus histogram-mode event bodies.
FULLY DECODED 2026-05-20. Every field in every block, verified
byte-exact against BW's ASCII export across multiple histogram
fixtures.
The histogram-mode body is a stream of 32-byte fixed-length blocks,
one block per histogram interval. Each block carries the per-interval
peak amplitude + zero-crossing frequency for all four channels (Tran,
Vert, Long, MicL).
────────────────────────────────────────────────────────────────────────────
Body layout (CONFIRMED 2026-05-20)
────────────────────────────────────────────────────────────────────────────
[stream of 32-byte blocks]
Body length is approximately ``n_intervals * 32`` bytes plus a small
trailing remnant (1-9 bytes typically) at the very end. Walker should
iterate 32-stride and stop before the tail.
────────────────────────────────────────────────────────────────────────────
32-byte block layout
────────────────────────────────────────────────────────────────────────────
[0] 0x00 always-zero tag
[1] segment_id (uint8) 0x00..0x03 - 256 blocks per segment
[2:4] block_ctr (uint16 LE) resets each segment (0x0100, 0x0101, ...)
[4] 0x0a (uint8) constant marker (= 10)
[5:7] T_peak_count uint16 BE Tran peak (count x 0.005 -> in/s)
[7:9] T_halfperiod uint16 BE Tran half-period in samples (freq = 512 / halfp)
[9:11] V_peak_count uint16 BE
[11:13] V_halfperiod uint16 BE
[13:15] L_peak_count uint16 BE
[15:17] L_halfperiod uint16 BE
[17:19] M_peak_count uint16 BE MicL peak (count -> dB via mic_count_to_db)
[19:21] M_halfperiod uint16 BE MicL half-period in samples
[21:23] 0x00 0x00 constant on standard blocks
[24:28] 4-byte variable purpose unknown (possibly CRC or timestamp delta)
[28:32] block-end signature see "Two block tails" below
**Every per-channel field is uint16 BIG-endian** (confirmed 2026-08-25).
Only ``block_ctr`` at [2:4] is little-endian.
HISTORY - two earlier readings of this block were wrong in ways that
cancelled out on quiet data:
1. *peak as uint16 LE at [6:8]* - produced 268 in/s peaks on any
interval whose next byte was non-zero.
2. *peak as uint8 at [6] with an "annotation" byte at [7]* - correct
for every peak below 256 counts (1.275 in/s), but it silently
**clipped larger peaks**: the final interval of
BE18193/T193LQ9K.OE0H reads 8.270 in/s in BW's export
(1654 counts = 0x0676) and decoded as 0x76 = 118 = 0.590 in/s.
The "annotation" byte was never an annotation - it is the high
byte of the big-endian half-period, which is why it was non-zero
exactly on the sub-Hz intervals BW renders as "<1.0".
Both readings also forced ``block[5] == 0`` via a bogus ``uint16 LE``
marker check at [4:6], which is what capped the peak at one byte.
The marker is ``block[4]`` alone.
Verified 2026-08-25 against 1211 production histograms paired with
their Blastware ASCII exports: **1211/1211 decode exactly** (interval
count plus every per-interval peak), and 842,442 per-interval
frequency comparisons match with **zero** mismatches.
Two block tails
---------------
Standard blocks end with ``1e 0a 00 00``. The **final block of the
stream** ends with ``9c 06 00 42`` instead, and carries arbitrary bytes
at [21:23]. Rejecting it dropped the last interval of nearly every
histogram - and the last interval is frequently the one holding the
event peak, so the file's reported PPV came out low. Observed in 1206
of 1211 production histograms, always positioned after every
standard-tail block.
Block-identification anchor: ``block[0] == 0x00`` AND
``block[4] == 0x0A`` AND the tail is one of the two signatures above;
standard-tail blocks additionally require ``block[22] == 0x00``.
────────────────────────────────────────────────────────────────────────────
Per-channel encoding
────────────────────────────────────────────────────────────────────────────
Geophone channels (Tran, Vert, Long):
- peak_count × 0.005 = peak amplitude in in/s at Normal range
- half-period in samples → freq_Hz = 512 / half-period
Microphone channel (MicL):
- peak_count → dB via the same formula used by the waveform codec:
dB = sign(c) × (81.94 + 20·log10(|c|)) for |c| ≥ 1
dB = 0 for c == 0
- half-period → freq_Hz = 512 / half-period (same as geo)
Frequency `>100 Hz` sentinel: the device emits half-period ≤ 5 when the
measured zero-crossing rate exceeds the geophone's measurement range
(since 512/5 = 102 Hz; the BW display rounds anything > 100 to ">100").
────────────────────────────────────────────────────────────────────────────
Output shape
────────────────────────────────────────────────────────────────────────────
``decode_histogram_body`` returns a per-channel dict matching the
waveform codec's shape so the rest of the pipeline (.h5 writer,
sidecar, viewer) consumes it without special-casing:
{"Tran": [peak_count_i for each interval i],
"Vert": [peak_count_i ...],
"Long": [peak_count_i ...],
"MicL": [peak_count_i ...]}
Values are in **16-count units for geo** (LSB = 0.005 in/s, matching
``decode_waveform_v2``) and **1-count units for mic** (matching the
waveform codec's mic convention). Run through
``waveform_codec.decoded_to_adc_counts`` to scale geo to 1-count ADC.
Per-interval frequencies are NOT returned — they're auxiliary data,
not waveform samples. Consumers needing frequencies can call
``decode_histogram_body_full()`` for the structured per-interval
record list.
"""
from __future__ import annotations
import struct
from typing import List, Optional, Tuple
# Block-end signature: constant `1e 0a 00 00` in bytes [28:32] of every
# real data block. More distinctive than the byte-22 `00 00` (which
# matches many false positives), so we anchor on this.
_BLOCK_TAIL = b"\x1e\x0a\x00\x00"
# The final block of a histogram stream ends with this instead. It is a
# real data block - same layout - and holds the last interval. See the
# module docstring, "Two block tails".
_BLOCK_TAIL_TERMINAL = b"\x9c\x06\x00\x42"
_BLOCK_SIZE = 32
# Marker byte at block[4:6] of every histogram data block. Used as
# additional validation that we're looking at a real block.
_BLOCK_MARKER = 10
# Geo peak scaling: stored as "count × 0.005 in/s" where 1 count = one
# 0.005 in/s display quantum. Equivalent to the waveform codec's
# 16-count-unit output (1 unit = 0.005 in/s = 16 ADC counts).
_GEO_LSB_INS = 0.005
# Frequency formula: freq_Hz = _FREQ_NUMERATOR / half_period_samples.
# Empirically determined to be 512 (= sample_rate / 2, where sample rate
# is 1024 sps for the standard MiniMate Plus configuration).
_FREQ_NUMERATOR = 512
def _is_data_block(block: bytes) -> bool:
"""Tight identification of a histogram data block.
Accepts both tail signatures. ``block[4]`` alone is the marker -
``block[5]`` is the high byte of the Tran peak and is non-zero on any
interval above 1.275 in/s, so it must not be part of the marker test.
The ``block[22] == 0`` constraint is what keeps trailer content out,
but it applies only to standard-tail blocks: terminal blocks carry
arbitrary bytes there.
"""
if len(block) < _BLOCK_SIZE:
return False
if block[0] != 0x00:
return False
if block[4] != _BLOCK_MARKER:
return False
# The 4-byte tail plus block[0]==0 and block[4]==0x0A is already six bytes
# of constraint — enough to keep trailer content out. There is NO extra
# test on block[22]: it was documented as a constant 0x00 but carries data
# on loud blocks, and rejecting those threw away the interval holding the
# event peak. BE18350/T350L7HR.NL0H is the proof: its block 92 has
# block[22]=0x26 and a Tran peak of 0x0563 = 1379 counts = 6.895 in/s,
# exactly the device-reported PPV, while the file decoded to 0.015 in/s.
return block[28:32] in (_BLOCK_TAIL, _BLOCK_TAIL_TERMINAL)
def _decode_block(block: bytes) -> Optional[dict]:
"""Decode one 32-byte histogram block. Caller must have validated
with ``_is_data_block`` first.
Returns a record with per-channel peak counts (uint8) and
half-periods (uint16 LE).
"""
# Every per-channel field is uint16 BIG-endian; only block_ctr is LE.
# See the module docstring for the two superseded readings and why
# each looked correct on quiet data.
def _be16(i: int) -> int:
return (block[i] << 8) | block[i + 1]
t_peak = _be16(5)
t_halfp = _be16(7)
v_peak = _be16(9)
v_halfp = _be16(11)
l_peak = _be16(13)
l_halfp = _be16(15)
m_peak = _be16(17)
m_halfp = _be16(19)
segment_id = block[1]
block_ctr = block[2] | (block[3] << 8)
var_meta = bytes(block[24:28])
return {
"segment_id": segment_id,
"block_ctr": block_ctr,
"t_peak": t_peak,
"t_halfp": t_halfp,
"v_peak": v_peak,
"v_halfp": v_halfp,
"l_peak": l_peak,
"l_halfp": l_halfp,
"m_peak": m_peak,
"m_halfp": m_halfp,
"meta_var": var_meta,
"is_terminal": block[28:32] == _BLOCK_TAIL_TERMINAL,
}
def walk_body(body: bytes) -> List[dict]:
"""Walk the body and return one dict per histogram interval.
Iterates 32-byte strides from offset 0. Yields a decoded record
for every block that passes ``_is_data_block`` validation. Stops
when the remaining bytes are too short to form a complete block.
In Histogram+Continuous mode the body interleaves data blocks with
other 32-byte content (likely continuous-mode waveform blocks) that
fail the data-block validation; the walker naturally skips them
without losing 32-byte alignment. Use ``block_ctr`` from each
returned record to map back to the original interval index — the
record list is sparse when other block types are interleaved.
"""
records: List[dict] = []
for off in range(0, len(body) - _BLOCK_SIZE + 1, _BLOCK_SIZE):
blk = body[off:off + _BLOCK_SIZE]
if not _is_data_block(blk):
# Hit non-block content (likely a sync or stream marker).
# Continue walking — block alignment is fixed at 32-stride
# from offset 0, so we don't lose alignment by skipping.
continue
decoded = _decode_block(blk)
if decoded is None:
# Block validated as a histogram block but had peak fields
# outside the plausible range — undocumented extension.
# Skip rather than propagating bogus PVS contributions.
continue
records.append(decoded)
return records
def _walk_auto(body: bytes) -> List[dict]:
"""Pick the block model by signature strength, not by which returns first.
The multi-interval variant announces itself with consecutive block headers
at an exact ``12 + 20*n`` stride — far stronger evidence than a handful of
scattered standard-tail blocks, which a multi-interval body will also yield
by coincidence. Dispatching on "whichever decoder returns something"
handed 193 BE18193 files to the standard walker and produced peaks of
149 in/s against a 10 in/s full scale.
"""
if detect_multi_interval_stride(body):
recs = walk_multi_interval_blocks(body)
if recs:
return recs
return walk_body(body)
def decode_histogram_body(body: bytes) -> Optional[dict]:
"""Decode a histogram-mode body into per-channel peak-sample arrays.
Returns ``{"Tran": [...], "Vert": [...], "Long": [...], "MicL": [...]}``
where each channel's list contains one peak value per histogram
interval (in the same units the waveform codec uses: 16-count units
for geo, 1-count ADC units for mic). Returns ``None`` if the body
doesn't contain any valid histogram blocks.
To convert to physical units:
- Geo channels: ``count * 0.005`` = peak in in/s at Normal range
(or run through ``waveform_codec.decoded_to_adc_counts`` first
to get 1-count ADC values, then ``count / 32767 * 10.0`` for in/s)
- Mic channel: use ``waveform_codec.mic_count_to_db(count)``
"""
records = _walk_auto(body)
if not records:
return None
return {
"Tran": [r["t_peak"] for r in records],
"Vert": [r["v_peak"] for r in records],
"Long": [r["l_peak"] for r in records],
"MicL": [r["m_peak"] for r in records],
}
def decode_histogram_body_full(body: bytes) -> Optional[List[dict]]:
"""Decode a histogram-mode body into the full per-interval record list.
Same data as ``decode_histogram_body`` but in a structured form that
preserves the half-period (frequency) data for each channel + the
per-block segment_id, block_ctr, and 4-byte variable metadata.
Useful for diagnostic tools, sidecar enrichment, and future-codec
work.
Returns ``None`` if the body has no valid blocks.
"""
records = _walk_auto(body)
return records if records else None
def half_period_to_hz(halfp: int) -> Optional[float]:
"""Convert a half-period in samples to frequency in Hz.
Returns ``None`` for half-period ≤ 5 — the device emits values in
that range when the measured zero-crossing rate exceeds 100 Hz
(the BW display reports `>100 Hz` for such cases). Callers can
treat ``None`` as the `>100 Hz` sentinel.
"""
if halfp <= 5:
return None
return _FREQ_NUMERATOR / halfp
def geo_count_to_ins(count: int) -> float:
"""Convert a histogram geo peak count to in/s at Normal range."""
return count * _GEO_LSB_INS
# ── Multi-interval block variant (CONFIRMED 2026-08-26) ─────────────────────
#
# When the histogram interval is SHORTER than one minute, the device packs
# several intervals into a single block so that every block still covers
# exactly one minute of data:
#
# interval size intervals/block stride
# 1 minute 1 32 <- the standard block above
# 15 seconds 4 92
# 2 seconds 30 612
#
# stride = 12 + n_intervals * 20
#
# Block layout:
# [0] 0x00
# [1] segment_id (256 blocks per segment, same as the standard block)
# [2:4] block_ctr uint16 LE (0x0100.., resets each segment)
# [4] 0x0a marker
# [5] 0x00
# [6 ...] n x 20-byte interval records, each carrying 8 x uint16
# LITTLE-endian values:
# T_peak, T_halfperiod, V_peak, V_halfperiod,
# L_peak, L_halfperiod, M_peak, M_halfperiod
# then 2 more words; the first is 0x0000 on every real interval.
# [-6:] 6-byte block trailer
#
# ⚠ ENDIANNESS: the standard 32-byte block is BIG-endian. This variant is
# LITTLE-endian. Do not share the accessor.
#
# These files previously decoded to nothing at all — 415 of them in the
# production snapshot, 216 on BE18193 (2 s intervals) and 199 on BE9440
# (15 s). Before that they were being accepted by the WAVEFORM codec, which
# returned garbage peaking up to 400x the device-reported PPV.
#
# Ground truth: BE9440/K440L3AQ.T70H (15 s intervals, 5,710 of them) decodes
# against its Blastware ASCII export with 17,130/17,130 geo peak counts,
# 22,840/22,840 frequencies and 5,710/5,710 mic dB(L) values matching exactly.
_MULTI_HEADER_LEN = 6
_MULTI_RECORD_LEN = 20
_MULTI_TRAILER_LEN = 6
# At least 2 records: a 1-record block would have stride 12 + 20 = 32, which
# collides with the standard big-endian block and mis-decodes it.
_MULTI_MIN_RECORDS = 2
_MULTI_MAX_RECORDS = 64
# Geo full scale in 16-count units: 10.000 in/s / 0.005 = 2000. A peak above
# this is physically impossible and marks buffer garbage in a partial block.
_GEO_MAX_COUNTS = 2000
def _is_multi_header(body: bytes, off: int) -> bool:
return (off + _MULTI_HEADER_LEN <= len(body)
and body[off] == 0x00
and body[off + 4] == 0x0A
and body[off + 5] == 0x00)
def detect_multi_interval_stride(body: bytes) -> Optional[int]:
"""Block stride of a multi-interval histogram body, or None.
Found by locating the second block header; validated against
``stride = 12 + n * 20`` and confirmed on a third block where present.
"""
if not _is_multi_header(body, 0):
return None
lo = _MULTI_HEADER_LEN + _MULTI_TRAILER_LEN + _MULTI_RECORD_LEN * _MULTI_MIN_RECORDS
hi = _MULTI_HEADER_LEN + _MULTI_TRAILER_LEN + _MULTI_RECORD_LEN * _MULTI_MAX_RECORDS
for stride in range(lo, min(hi, len(body)) + 1, 2):
if (stride - 12) % _MULTI_RECORD_LEN:
continue
if not _is_multi_header(body, stride):
continue
# DECISIVE CHECK: consecutive blocks differ by exactly 1 in block_ctr.
# Without it this false-positives on ordinary standard-block bodies:
# those carry a header every 32 bytes, and 192 = 12 + 20*9 and
# 512 = 12 + 20*25 are both multiples of 32, so a stride "fits" while
# actually skipping 6 or 16 real blocks. Sampling a standard body at
# stride 192 handed 9,082 files to the wrong decoder and produced peaks
# of 149 in/s against a 10 in/s full scale.
def _ctr(o: int) -> int:
return body[o + 2] | (body[o + 3] << 8)
if (_ctr(stride) - _ctr(0)) & 0xFFFF != 1:
continue
# Confirm on a third block WHEN ONE IS ACTUALLY PRESENT. A body can
# be longer than two strides and still hold only two real blocks: a
# final *partial* block leaves trailing padding. E.g. 51 intervals at
# 2 s = one full 30-interval block + a 21-interval remainder, in a
# 2787-byte body — long enough to demand a third header at 1224 that
# does not exist. Requiring it unconditionally threw away the correct
# stride and the file decoded to nothing (BE18193 T193L0XM.CI0H).
# The block-counter check above is the decisive anti-false-positive
# test; this one is corroboration, so a missing third header means
# end-of-stream, not disqualification.
if (2 * stride + _MULTI_HEADER_LEN <= len(body)
and _is_multi_header(body, 2 * stride)):
if (_ctr(2 * stride) - _ctr(stride)) & 0xFFFF != 1:
continue
return stride
return None
def walk_multi_interval_blocks(body: bytes,
stride: Optional[int] = None) -> List[dict]:
"""Decode a multi-interval histogram body into per-interval records."""
if stride is None:
stride = detect_multi_interval_stride(body)
if not stride:
return []
n_per_block = (stride - _MULTI_HEADER_LEN - _MULTI_TRAILER_LEN) // _MULTI_RECORD_LEN
if n_per_block < 1:
return []
def u16le(p: int) -> int:
return body[p] | (body[p + 1] << 8)
out: List[dict] = []
for off in range(0, len(body) - stride + 1, stride):
if not _is_multi_header(body, off):
break # end of the block run; trailer follows
for k in range(n_per_block):
q = off + _MULTI_HEADER_LEN + _MULTI_RECORD_LEN * k
out.append({
"_tail0": u16le(q + 16),
"segment_id": body[off + 1],
"block_ctr": u16le(off + 2),
"t_peak": u16le(q), "t_halfp": u16le(q + 2),
"v_peak": u16le(q + 4), "v_halfp": u16le(q + 6),
"l_peak": u16le(q + 8), "l_halfp": u16le(q + 10),
"m_peak": u16le(q + 12), "m_halfp": u16le(q + 14),
"meta_var": bytes(body[q + 16:q + 20]),
"is_terminal": False,
})
# A session ending mid-block leaves the remaining slots of the FINAL block
# filled with whatever was in the buffer. Those decoded as peaks thousands
# of times the device-reported PPV, so they have to go — but only from the
# final block: a non-zero tail word occurs mid-file on real intervals, and
# trimming on that alone truncated four BE9440 files by up to 2,800
# intervals, while trimming purely from the end left garbage stranded
# behind one slot that happened to have a zero tail word.
#
# Within the final block, stop at the first slot that is not plausibly
# real: a non-zero tail word, or a geo peak above full scale. 16-count
# units put Normal-range full scale (10.000 in/s) at 2000 counts, so
# anything beyond that is physically impossible.
if out:
last_block_start = ((len(out) - 1) // n_per_block) * n_per_block
for i in range(last_block_start, len(out)):
r = out[i]
if (r["_tail0"] != 0
or max(r["t_peak"], r["v_peak"], r["l_peak"]) > _GEO_MAX_COUNTS):
del out[i:]
break
for r in out:
r.pop("_tail0", None)
return out
minimateplus/models.py
+69
View File
@@ -201,6 +201,58 @@ class Timestamp:
second=second,
)
@classmethod
def from_short_record(cls, data: bytes) -> "Timestamp":
"""
Decode an 8-byte timestamp header from a 210-byte waveform record.
Wire layout (✅ CONFIRMED 2026-05-01 against live SFM run on BE11529 in
Continuous mode, day-of-month = 1 May, raw: 01 05 07 ea 00 0d 15 25):
byte[0]: day (uint8)
byte[1]: month (uint8)
bytes[2-3]: year (big-endian uint16)
byte[4]: unknown (0x00 in observed sample)
byte[5]: hour (uint8)
byte[6]: minute (uint8)
byte[7]: second (uint8)
This is a third format observed in the wild — distinct from the 9-byte
(single-shot, sub_code=0x10 at [1]) and 10-byte (continuous, 0x10 at
[0] AND [2]) layouts. No marker bytes; disambiguated by where the
year lands when scanned at byte 2/3/4.
Args:
data: at least 8 bytes; only the first 8 are consumed.
Returns:
Decoded Timestamp.
Raises:
ValueError: if data is fewer than 8 bytes.
"""
if len(data) < 8:
raise ValueError(
f"Short record timestamp requires at least 8 bytes, got {len(data)}"
)
day = data[0]
month = data[1]
year = struct.unpack_from(">H", data, 2)[0]
unknown_byte = data[4]
hour = data[5]
minute = data[6]
second = data[7]
return cls(
raw=bytes(data[:8]),
flag=0,
year=year,
unknown_byte=unknown_byte,
month=month,
day=day,
hour=hour,
minute=minute,
second=second,
)
@property
def clock_set(self) -> bool:
"""False when year == 1995 (factory default / battery-lost state)."""
@@ -300,6 +352,14 @@ class PeakValues:
long: Optional[float] = None # Longitudinal PPV (in/s) ✅
micl: Optional[float] = None # Air overpressure (psi) 🔶 (units uncertain)
peak_vector_sum: Optional[float] = None # Scalar geo PVS (in/s) ✅
tran_zc_freq: Optional[float] = None
vert_zc_freq: Optional[float] = None
long_zc_freq: Optional[float] = None
mic_zc_freq: Optional[float] = None
tran_zc_above_range: bool = False
vert_zc_above_range: bool = False
long_zc_above_range: bool = False
mic_zc_above_range: bool = False
# ── Project / operator metadata ───────────────────────────────────────────────
@@ -484,6 +544,15 @@ class Event:
pretrig_samples: Optional[int] = None # from STRT record: pre-trigger sample count
rectime_seconds: Optional[int] = None # from STRT record: record duration (seconds)
# Sensor self-check traces keyed by channel label — the short diagnostic
# waveforms the unit records when it pulses each sensor before monitoring
# (geophone ring-downs + a mic pulse train). Decoded from the binary by
# the per-series decoder (minimateplus.sensor_check / micromate.sensor_check)
# and carried here so the .h5 writer can persist them device-agnostically.
# Raw ADC counts; the source series' scale differs but the trace is a
# shape diagnostic (rendered fit-to-box). None when absent.
sensor_check: Optional[dict] = None # {"Tran": [...], ..., "MicL": [...]}
# ── Debug / introspection ─────────────────────────────────────────────────
# Raw 210-byte waveform record bytes, set when debug mode is active.
# Exposed by the SFM server via ?debug=true so field layouts can be verified.
minimateplus/protocol.py
+234 -158
View File
@@ -35,6 +35,8 @@ from .framing import (
token_params,
bulk_waveform_params,
bulk_waveform_term_params,
bulk_waveform_term_v2,
parse_strt_end_offset,
POLL_PROBE,
POLL_DATA,
SESSION_RESET,
@@ -122,16 +124,22 @@ DATA_LENGTHS: dict[int, int] = {
}
# SUB 5A (BULK_WAVEFORM_STREAM) protocol constants.
# Confirmed from 1-2-26 BW TX capture analysis (2026-04-02).
_BULK_CHUNK_OFFSET = 0x1004 # offset field for probe + all regular chunk requests ✅
_BULK_TERM_OFFSET = 0x005A # offset field for termination request ✅
_BULK_COUNTER_STEP = 0x0400 # chunk counter increment per chunk ✅
# Chunk counter formula: key4[2:4] + (chunk_num - 1) * 0x0400
# where key4[2:4] is the event's circular-buffer base offset ((key4[2]<<8)|key4[3]).
# Earlier captures showed 0x1004 for chunk 1 of key 01110000 — that was a Blastware
# artifact. For keys where key4[2:4] != 0x0000 (e.g. key 01111884) the old
# "n * 0x0400" formula sends counters from the wrong buffer region and the device
# returns data from a different event. Confirmed correct 2026-04-24.
#
# 2026-05-01 minimal-fix: the chunk-counter walk is now bounded by the event's
# `end_offset` extracted from the STRT record at data[23:27] of the probe
# response. Without this bound the loop kept asking for chunks past the event
# end and the device responded with post-event circular-buffer garbage,
# corrupting reconstructed Blastware files for events ≥ 2 sec.
#
# We keep the OLD 0x0400 chunk step here (BW actually uses 0x0200 — see §7.8.5
# of the protocol reference for the corrected understanding) because the
# existing blastware_file.py builder relies on the 0x0400-step frame structure
# to produce valid files. Switching to BW's 0x0200 step is a separate task
# that also requires updating the file builder.
# BW-exact protocol values (v0.14.0). Verified against 4-27-26 + 5-1-26 captures.
_BULK_CHUNK_OFFSET = 0x1002 # offset_word for probe + all chunk requests
_BULK_TERM_OFFSET = 0x005A # offset_word for the legacy terminator (fallback only)
_BULK_COUNTER_STEP = 0x0200 # chunk counter increment (matches chunk payload size)
# Default timeout values (seconds).
# MiniMate Plus is a slow device — keep these generous.
@@ -526,203 +534,270 @@ class MiniMateProtocol:
self,
key4: bytes,
*,
stop_after_metadata: bool = True,
max_chunks: int = 32,
stop_after_metadata: bool = True, # DEPRECATED — no-op under BW-exact walk
max_chunks: int = 256, # safety cap only; loop is bounded by end_offset
include_terminator: bool = False,
extra_chunks_after_metadata: int = 1,
extra_chunks_after_metadata: int = 1, # DEPRECATED — no-op
) -> list[S3Frame]:
"""
Download the SUB 5A (BULK_WAVEFORM_STREAM) A5 frames for one event.
Download the SUB 5A (BULK_WAVEFORM_STREAM) A5 frames for one event using
Blastware's exact protocol. REWRITTEN 2026-05-02 (v0.14.0).
The bulk waveform stream carries both raw ADC samples (large) and
event-time metadata strings ("Project:", "Client:", "User Name:",
"Seis Loc:", "Extended Notes") embedded in one of the middle frames
(confirmed: A5[7] of 9 for 1-2-26 capture).
Algorithm (matches BW captures across 2-sec / 3-sec / event-2):
Protocol is request-per-chunk, NOT a continuous stream:
1. Probe (offset=_BULK_CHUNK_OFFSET, is_probe=True, counter=0x0000)
2. Chunks (offset=_BULK_CHUNK_OFFSET, is_probe=False, counter+=0x0400)
3. Loop until metadata found (stop_after_metadata=True) or max_chunks
4. Termination (offset=_BULK_TERM_OFFSET, counter=last+_BULK_COUNTER_STEP)
Device responds with a final A5 frame (page_key=0x0000).
1. Probe
- For events at start_key[2:4] = 0x0000 (first event after erase
/ wrap): probe at counter=0x0000 with full key in params.
- For continuation events (start_key[2:4] != 0): first chunk at
counter = start_key[2:4] + 0x0046; acts as both probe and
first sample chunk; response carries STRT.
By default the termination frame (page_key=0x0000) is NOT included in the
returned list. Pass include_terminator=True to append it; the blastware_file
writer needs the terminator frame's body to reconstruct the waveform file footer.
2. Parse end_offset from STRT record at data[23:27] of the probe response.
Args:
key4: 4-byte waveform key from EVENT_HEADER (1E).
stop_after_metadata: If True (default), send termination as soon as
b"Project:" is found in a frame's data — avoids
downloading the full ADC waveform payload (several
hundred KB). Set False to download everything.
max_chunks: Safety cap on the number of chunk requests sent
(default 32; a typical event uses 9 large frames).
include_terminator: If True, append the terminator A5 frame
(page_key=0x0000) to the returned list. The
terminator carries the waveform file footer bytes.
Default False preserves existing caller behaviour.
3. Read two fixed metadata pages at counter=0x1002 and counter=0x1004
— global session metadata (Project / Client / User Name / Seis Loc
/ Extended Notes ASCII strings). Event 1 only; continuation
events skip these (BW caches them across the session).
4. Walk sample chunks at 0x0200 increments, starting from 0x0600 for
event 1 or `start + 0x0046 + 0x0200` for continuation events.
Stop when `next_chunk + 0x0200 > end_offset`.
5. Send TERM frame with offset_word and params computed by
`bulk_waveform_term_v2(key4, end_offset, last_chunk_counter)`.
The TERM response contains the partial last chunk (residual =
end_offset - next_boundary) including the 26-byte 0e 08 file
footer.
Returns:
List of S3Frame objects from each A5 response frame. Frame indices
match the request sequence: index 0 = probe response, index 1 = first
chunk, etc. If include_terminator=True, the last element is the
terminator frame (page_key=0x0000).
List of S3Frame objects from each A5 response (probe, metadata
pages, sample chunks, optional TERM response). Caller passes
`include_terminator=True` (e.g. write_blastware_file) to keep the
TERM response in the list — it's required to reconstruct the
file footer.
Deprecated kwargs:
stop_after_metadata: legacy "Project:"-string-based stop condition.
No-op under the BW-exact walk; the loop is
deterministically bounded by end_offset from
STRT. Accepted for backward compat.
extra_chunks_after_metadata: same.
Raises:
ProtocolError: on timeout, bad checksum, or unexpected SUB.
Confirmed from 1-2-26 BW TX/RX captures (2026-04-02):
- probe + 8 regular chunks + 1 termination = 10 TX frames
- 9 large A5 responses + 1 terminator A5 = 10 RX frames
- page_key=0x0010 on large frames; page_key=0x0000 on terminator ✅
- "Project:" metadata at A5[7].data[626] ✅
ProtocolError: on timeout / bad checksum / unexpected SUB.
"""
if len(key4) != 4:
raise ValueError(f"waveform key must be 4 bytes, got {len(key4)}")
rsp_sub = _expected_rsp_sub(SUB_BULK_WAVEFORM) # 0xFF - 0x5A = 0xA5
# Quietly accept and warn on deprecated kwargs.
if not stop_after_metadata:
log.debug("5A: stop_after_metadata=False is no-op under BW-exact walk")
if extra_chunks_after_metadata not in (0, 1):
log.debug("5A: extra_chunks_after_metadata=%d is no-op under BW-exact walk",
extra_chunks_after_metadata)
rsp_sub = _expected_rsp_sub(SUB_BULK_WAVEFORM) # 0xA5
frames_data: list[S3Frame] = []
counter = 0
# BW counter formula (confirmed from 4-3-26 capture for key 0111245a,
# and empirical live-device test 2026-04-06 for key 01110000):
# counter for chunk n = max(key4[2:4], 0x0400) + (n - 1) * 0x0400
# key4[2:4] is the event's circular-buffer base offset. The max() guard
# ensures chunk 1 never uses counter=0x0000 (which equals the probe address
# and causes the device to re-return STRT record data for the first chunk).
_key4_offset = (key4[2] << 8) | key4[3]
start_offset = (key4[2] << 8) | key4[3]
is_event_1 = (start_offset == 0)
# ── Step 1: probe ────────────────────────────────────────────────────
log.debug("5A probe key=%s key4_offset=0x%04X", key4.hex(), _key4_offset)
params = bulk_waveform_params(key4, 0, is_probe=True)
self._send(build_5a_frame(_BULK_CHUNK_OFFSET, params))
self._parser.reset() # reset bytes_fed counter before probe recv
# ── Step 1: probe / first chunk ──────────────────────────────────────
if is_event_1:
probe_counter = 0
probe_params = bulk_waveform_params(key4, 0, is_probe=True)
log.debug("5A probe (event-1) key=%s counter=0x0000", key4.hex())
else:
# Continuation events: first 5A request lands at counter = key[2:4]
# (i.e. the address of the off=0x46 WAVEHDR record returned by 1F).
# The probe response carries STRT at byte 17 with end_offset.
#
# Confirmed 2026-05-04 from 5-1-26 "copy 2nd address" capture
# (BW probes counter=0x2238 with key=01112238, STRT@17 end=0x417E)
# and 5-4-26 BW captures (2-sec event probes counter=0x2238).
#
# The earlier "+0x46" formula in the doc came from calling
# start_key the BOUNDARY (off=0x2C) key, but the iteration walk
# uses 1F's off=0x46 key as cur_key, which already incorporates
# the +0x46 offset relative to the boundary. Adding it again
# caused the probe to overshoot, miss STRT, and run uncapped.
probe_counter = start_offset
probe_params = bulk_waveform_params(key4, probe_counter)
log.debug(
"5A probe (event-N) key=%s counter=0x%04X",
key4.hex(), probe_counter,
)
self._send(build_5a_frame(_BULK_CHUNK_OFFSET, probe_params))
self._parser.reset()
try:
rsp = self._recv_one(expected_sub=rsp_sub, reset_parser=False)
except TimeoutError:
log.warning(
"5A probe TIMED OUT for key=%s — "
"%d raw bytes received (no complete A5 frame assembled)",
"5A probe TIMED OUT for key=%s — %d raw bytes received",
key4.hex(), self._parser.bytes_fed,
)
raise
frames_data.append(rsp)
log.debug("5A A5[0] page_key=0x%04X %d bytes", rsp.page_key, len(rsp.data))
# ── Step 2: chunk loop ───────────────────────────────────────────────
# Counter formula: _chunk_base + (chunk_num - 1) * 0x0400
# where _chunk_base = max(key4[2:4], 0x0400).
#
# For events with key4[2:4] != 0 (e.g. key 0111245a, offset 0x245a):
# _chunk_base = 0x245a → chunk 1=0x245a, chunk 2=0x285a, ...
# Confirmed from 4-3-26 capture.
#
# For events with key4[2:4] == 0 (e.g. key 01110000):
# _chunk_base = max(0, 0x0400) = 0x0400
# → chunk 1=0x0400, chunk 2=0x0800, ... (= old chunk_num*0x0400)
# CRITICAL: counter=0x0000 (same as the probe) causes the device to
# re-return the STRT record data for chunk 1, making frame 1 look like
# a second probe response (confirmed from server log: frame 1 len=1097,
# contains STRT\xff\xfe, contributes zero body bytes after DLE-strip).
# counter=0x0400 for chunk 1 confirmed working (empirical test 2026-04-06).
_chunk_base = max(_key4_offset, _BULK_COUNTER_STEP)
for chunk_num in range(1, max_chunks + 1):
counter = _chunk_base + (chunk_num - 1) * _BULK_COUNTER_STEP
params = bulk_waveform_params(key4, counter)
log.debug("5A chunk %d counter=0x%04X", chunk_num, counter)
frames_data.append(rsp)
log.debug("5A A5[0] (probe) page_key=0x%04X %d bytes",
rsp.page_key, len(rsp.data))
# ── Step 2: parse STRT end_offset from probe response ────────────────
end_offset = parse_strt_end_offset(rsp.data)
if end_offset is None:
log.warning(
"5A probe response did not contain a STRT record; "
"cannot bound chunk loop — falling back to max_chunks=%d cap",
max_chunks,
)
end_offset = 0xFFFF # impossible value → loop runs to max_chunks
else:
log.info(
"5A STRT start_offset=0x%04X end_offset=0x%04X size=0x%04X",
start_offset, end_offset, end_offset - start_offset,
)
# ── Step 3: metadata pages 0x1002 + 0x1004 (event 1 only) ────────────
# Confirmed from BW captures: BW reads these two fixed device-buffer
# pages immediately after the probe for events at start_key[2:4]=0.
# Continuation events skip them (BW caches across the session).
# Their content is global compliance-setup metadata: Project, Client,
# User Name, Seis Loc, Extended Notes.
if is_event_1:
for meta_counter in (0x1002, 0x1004):
# Metadata page params have an extra trailing 0x00 byte
# (12-byte params instead of 11) — empirical from BW captures.
# Checksum-neutral but matches BW byte-for-byte.
meta_params = bytes([
0x00,
key4[0], key4[1],
(meta_counter >> 8) & 0xFF,
meta_counter & 0xFF,
0, 0, 0, 0, 0, 0, 0,
])
log.debug("5A metadata page counter=0x%04X", meta_counter)
self._send(build_5a_frame(_BULK_CHUNK_OFFSET, meta_params))
self._parser.reset()
try:
meta_rsp = self._recv_one(
expected_sub=rsp_sub, reset_parser=False, timeout=10.0,
)
except TimeoutError:
log.warning(
"5A metadata page 0x%04X TIMED OUT — continuing",
meta_counter,
)
continue
frames_data.append(meta_rsp)
log.debug(
"5A meta@0x%04X page_key=0x%04X %d bytes",
meta_counter, meta_rsp.page_key, len(meta_rsp.data),
)
# ── Step 4: sample chunk loop, bounded by end_offset ─────────────────
# Sample chunks start at:
# event 1: counter = 0x0600
# event N (>0): counter = probe_counter + 0x0200
# (probe was the first sample chunk)
if is_event_1:
counter = 0x0600
else:
counter = probe_counter + _BULK_COUNTER_STEP
last_chunk_counter: Optional[int] = (
probe_counter if not is_event_1 else None
)
chunks_fetched = 0
while chunks_fetched < max_chunks:
# Stop when next chunk would straddle the event end.
if counter + _BULK_COUNTER_STEP > end_offset:
log.debug(
"5A chunk loop done at counter=0x%04X (end=0x%04X); "
"%d chunks fetched",
counter, end_offset, chunks_fetched,
)
break
params = bulk_waveform_params(key4, counter)
log.debug("5A chunk #%d counter=0x%04X", chunks_fetched + 1, counter)
self._send(build_5a_frame(_BULK_CHUNK_OFFSET, params))
self._parser.reset() # reset bytes_fed for accurate per-chunk count
self._parser.reset()
try:
rsp = self._recv_one(expected_sub=rsp_sub, reset_parser=False, timeout=10.0)
rsp = self._recv_one(
expected_sub=rsp_sub, reset_parser=False, timeout=10.0,
)
except TimeoutError:
raw = self._parser.bytes_fed
log.warning(
"5A TIMEOUT chunk=%d counter=0x%04X raw_bytes=%d",
chunk_num, counter, raw,
chunks_fetched + 1, counter, raw,
)
if raw > 0 and frames_data:
# Device sent a partial byte (likely a bare DLE/ETX end-of-stream
# signal) but never completed a full frame. Treat as graceful
# stream end and fall through to the termination step.
log.warning(
"5A end-of-stream detected at chunk=%d (raw_bytes=%d, "
"frames_collected=%d) — proceeding to termination",
chunk_num, raw, len(frames_data),
"5A unexpected end-of-stream — proceeding to TERM",
)
break
raise
log.warning(
"5A RX chunk=%d page_key=0x%04X data_len=%d contains_Project=%s",
chunk_num, rsp.page_key, len(rsp.data), b"Project:" in rsp.data,
log.debug(
"5A RX chunk=%d page_key=0x%04X data_len=%d",
chunks_fetched + 1, rsp.page_key, len(rsp.data),
)
if rsp.page_key == 0x0000:
# Device unexpectedly terminated mid-stream (no termination needed).
log.debug("5A A5[%d] page_key=0x0000 — device terminated early", chunk_num)
# Device terminated mid-stream unexpectedly.
log.warning(
"5A unexpected page_key=0x0000 mid-stream at counter=0x%04X",
counter,
)
if include_terminator:
frames_data.append(rsp)
return frames_data
frames_data.append(rsp)
if stop_after_metadata and b"Project:" in rsp.data:
# Download exactly one more chunk after finding metadata — this is
# what Blastware does. The extra chunk contains the tail ADC data
# and primes the device to return a valid footer in the termination
# response. Without it, termination returns an empty ack with no
# footer bytes (confirmed 2026-04-23 from HxD comparison).
# Download extra_chunks_after_metadata more chunks past the
# metadata. The caller calculates this from record_time and
# sample_rate so we download exactly the right amount of ADC
# data — no more, no less — before terminating.
# The device returns the footer in the termination response only
# after the right amount of data has been consumed.
log.debug("5A A5[%d] metadata found — fetching %d more chunk(s)",
chunk_num, extra_chunks_after_metadata)
for _extra_n in range(extra_chunks_after_metadata):
chunk_num += 1
counter = _chunk_base + (chunk_num - 1) * _BULK_COUNTER_STEP
params = bulk_waveform_params(key4, counter)
self._send(build_5a_frame(_BULK_CHUNK_OFFSET, params))
try:
extra = self._recv_one(expected_sub=rsp_sub, timeout=10.0)
log.debug("5A A5[%d] extra chunk page_key=0x%04X data_len=%d",
chunk_num, extra.page_key, len(extra.data))
if extra.page_key == 0x0000:
if include_terminator:
frames_data.append(extra)
return frames_data
frames_data.append(extra)
except TimeoutError:
log.debug("5A extra chunk %d timed out — end of stream", _extra_n + 1)
break
break
last_chunk_counter = counter
counter += _BULK_COUNTER_STEP
chunks_fetched += 1
else:
log.warning(
"5A reached max_chunks=%d without end-of-stream; sending termination",
max_chunks,
"5A reached max_chunks=%d at counter=0x%04X (end=0x%04X)",
max_chunks, counter, end_offset,
)
# ── Step 3: termination ──────────────────────────────────────────────
term_counter = counter + _BULK_COUNTER_STEP
term_params = bulk_waveform_term_params(key4, term_counter)
log.debug(
"5A termination term_counter=0x%04X offset=0x%04X",
term_counter, _BULK_TERM_OFFSET,
)
self._send(build_5a_frame(_BULK_TERM_OFFSET, term_params))
try:
term_rsp = self._recv_one(expected_sub=rsp_sub)
# ── Step 5: TERM with proper end_offset-derived formula ──────────────
if last_chunk_counter is None or end_offset == 0xFFFF:
# No STRT or no chunks fetched — fall back to legacy TERM.
log.warning(
"5A using legacy TERM (offset_word=0x005A); "
"end_offset unavailable or no chunks fetched",
)
legacy_counter = (last_chunk_counter or probe_counter) + _BULK_COUNTER_STEP
term_offset_word = _BULK_TERM_OFFSET # 0x005A
term_params = bulk_waveform_term_params(key4, legacy_counter)
else:
term_offset_word, term_params = bulk_waveform_term_v2(
key4, end_offset, last_chunk_counter,
)
log.debug(
"5A termination response page_key=0x%04X %d bytes",
"5A TERM offset_word=0x%04X params[2:4]=%s end=0x%04X "
"last_chunk=0x%04X",
term_offset_word, term_params[2:4].hex(),
end_offset, last_chunk_counter,
)
self._send(build_5a_frame(term_offset_word, term_params))
try:
term_rsp = self._recv_one(expected_sub=rsp_sub, timeout=10.0)
log.info(
"5A TERM response page_key=0x%04X %d bytes",
term_rsp.page_key, len(term_rsp.data),
)
if include_terminator:
frames_data.append(term_rsp)
except TimeoutError:
log.debug("5A no termination response — device may have already closed")
log.warning("5A no TERM response (timeout)")
return frames_data
@@ -862,7 +937,7 @@ class MiniMateProtocol:
continue
chunk = data_rsp.data[11:]
log.warning(
log.debug(
"read_compliance_config: frame %s page=0x%04X data=%d cfg_chunk=%d running_total=%d",
step_name, data_rsp.page_key, len(data_rsp.data),
len(chunk), len(config) + len(chunk),
@@ -882,17 +957,18 @@ class MiniMateProtocol:
except TimeoutError:
pass
log.warning(
log.info(
"read_compliance_config: done — %d cfg bytes total",
len(config),
)
# Hex dump first 128 bytes for field mapping
for row in range(0, min(len(config), 128), 16):
row_bytes = bytes(config[row:row + 16])
hex_part = ' '.join(f'{b:02x}' for b in row_bytes)
asc_part = ''.join(chr(b) if 32 <= b < 127 else '.' for b in row_bytes)
log.warning(" cfg[%04x]: %-48s %s", row, hex_part, asc_part)
# Hex dump first 128 bytes — useful only for field-mapping work, not normal operation.
if log.isEnabledFor(logging.DEBUG):
for row in range(0, min(len(config), 128), 16):
row_bytes = bytes(config[row:row + 16])
hex_part = ' '.join(f'{b:02x}' for b in row_bytes)
asc_part = ''.join(chr(b) if 32 <= b < 127 else '.' for b in row_bytes)
log.debug(" cfg[%04x]: %-48s %s", row, hex_part, asc_part)
return bytes(config)
minimateplus/sensor_check.py
+146
View File
@@ -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
minimateplus/transport.py
+99
View File
@@ -454,3 +454,102 @@ class SocketTransport(TcpTransport):
def __repr__(self) -> str:
return f"SocketTransport(peer={self.host!r})"
# ── Capturing transport (MITM-style raw byte mirror) ──────────────────────────
class CapturingTransport(BaseTransport):
"""
Wraps another BaseTransport and mirrors every byte to two raw capture files:
raw_bw_<...>.bin — bytes WE wrote to the device (BW-side TX)
raw_s3_<...>.bin — bytes the device wrote back (S3-side TX)
The file naming and on-wire byte layout are identical to the captures
produced by `bridges/ach_mitm.py`, so the resulting `.bin` files can be
loaded directly by the Analyzer (File > Open Capture) and parsed by the
same tooling used for genuine Blastware MITM captures.
All BaseTransport methods are forwarded to the inner transport; the only
side-effect is that successful read/write byte streams are appended to the
two open binary files.
Args:
inner: An already-built BaseTransport (SerialTransport / TcpTransport).
bw_path: File path for the "BW TX" stream (bytes we send). Opened "wb".
s3_path: File path for the "S3 TX" stream (bytes the device sends).
Opened "wb".
Example:
with CapturingTransport(TcpTransport("1.2.3.4", 9034),
"raw_bw.bin", "raw_s3.bin") as t:
client = MiniMateClient(transport=t)
client.connect()
client.get_events()
# both .bin files now hold the full bidirectional capture.
"""
def __init__(self, inner: BaseTransport, bw_path: str, s3_path: str) -> None:
self._inner = inner
self._bw_path = bw_path
self._s3_path = s3_path
self._bw_fh = None
self._s3_fh = None
# Forward inner attrs so callers can introspect (e.g. .host, .port).
self.host = getattr(inner, "host", None)
self.port = getattr(inner, "port", None)
# ── BaseTransport interface ───────────────────────────────────────────────
def connect(self) -> None:
if self._bw_fh is None:
self._bw_fh = open(self._bw_path, "wb", buffering=0)
if self._s3_fh is None:
self._s3_fh = open(self._s3_path, "wb", buffering=0)
self._inner.connect()
def disconnect(self) -> None:
try:
self._inner.disconnect()
finally:
for fh_attr in ("_bw_fh", "_s3_fh"):
fh = getattr(self, fh_attr)
if fh is not None:
try:
fh.flush()
fh.close()
except Exception:
pass
setattr(self, fh_attr, None)
@property
def is_connected(self) -> bool:
return self._inner.is_connected
def write(self, data: bytes) -> None:
self._inner.write(data)
if data and self._bw_fh is not None:
try:
self._bw_fh.write(data)
except Exception:
pass
def read(self, n: int) -> bytes:
got = self._inner.read(n)
if got and self._s3_fh is not None:
try:
self._s3_fh.write(got)
except Exception:
pass
return got
@property
def bw_path(self) -> str:
return self._bw_path
@property
def s3_path(self) -> str:
return self._s3_path
def __repr__(self) -> str:
return f"CapturingTransport({self._inner!r}, bw={self._bw_path!r}, s3={self._s3_path!r})"
minimateplus/waveform_codec.py
+948
View File
@@ -0,0 +1,948 @@
"""
waveform_codec.py — block-walker and verified decoder for the MiniMate Plus
waveform-file body.
FULLY DECODED 2026-05-11. Every block type, every channel, and the
channel-rotation rule are verified byte-exact against BW's ASCII export
across the 9-event fixture bundle (47,364 ADC samples, zero errors).
The Blastware waveform-file body — the bytes between the 21-byte STRT
record and the 26-byte file footer — is a tagged variable-length block
stream with a custom delta + RLE codec. (Not raw int16 LE, which was
the historical wrong assumption that produced ±32K noise on every event.)
Current status:
- Block framing: ✅ solved (5 block types and lengths all confirmed)
- Per-channel decode: ✅ solved (Tran / Vert / Long / MicL all byte-exact)
- Channel rotation: ✅ Tran → Vert → Long → MicL per segment
- Segment header: ✅ fully decoded (anchor pair + prev-channel extension)
- 30 NN packed-delta block: ✅ NN × 12-bit signed deltas in NN/4 groups
- MicL → dB(L) conversion: ✅ ``mic_count_to_db`` matches BW display
- Production wiring: ✅ ``client.py:_decode_a5_waveform`` uses the new
codec (via ``decode_a5_frames``). ``.h5`` sidecars now render
correctly.
Known limitations:
- Walker stops early on the loudest events (SP0, SS0, SV0, event-b) at
some mid-segment edge cases not yet fully characterized. Every
sample reached IS correct; the walker just doesn't reach all of
them yet. The cleanly-decoded subset is still ~5000–15000 samples
per loud event.
────────────────────────────────────────────────────────────────────────────
Body layout (CONFIRMED 2026-05-11 against 8 fixture events)
────────────────────────────────────────────────────────────────────────────
[7-byte preamble] [stream of tagged blocks] [trailer]
The preamble is always exactly 7 bytes:
body[0:3] = 00 02 00 magic
body[3:5] = Tran[0] int16 BE in 16-count units (LSB = 0.005 in/s)
body[5:7] = Tran[1] int16 BE in 16-count units
(Earlier drafts of this module described a "7-or-9-byte preamble";
that was wrong — single-shot and continuous events both use 7 bytes.
The "extra 2 bytes" on continuous events were the first ``00 NN`` RLE
marker, not part of the preamble.)
Block types and lengths (all confirmed):
| Tag | Length | Meaning |
|----------|-----------------------|----------------------------------------|
| ``10 NN``| NN/2 + 2 bytes | 4-bit nibble deltas (2 per byte; high |
| | | nibble first; signed 0..7 / 8..F = -8..-1)|
| ``20 NN``| NN + 2 bytes | int8 signed deltas (1 per byte) |
| ``00 NN``| 2 bytes | RLE: append NN copies of current value |
| ``30 NN``| NN*2 in data, NN*4 | Unknown content. Only in loud events. |
| | in trailer | |
| ``40 02``| 20 bytes (fixed) | Segment header |
NN is always a multiple of 4.
────────────────────────────────────────────────────────────────────────────
Tran channel, segment 0 (CONFIRMED 2026-05-11)
────────────────────────────────────────────────────────────────────────────
Segment 0 — everything before the first ``40 02`` segment header — encodes
Tran samples only. Starting from preamble anchors Tran[0] and Tran[1],
each subsequent block contributes to the running Tran value:
10 NN → append NN deltas (4-bit signed nibbles)
20 NN → append NN deltas (int8 signed bytes)
00 NN → append NN copies of the current value (RLE zeros)
40 02 → segment 0 ends; multi-segment continuation is open
This decodes the first 482–510 samples of Tran for each event with zero
errors against BW's ASCII export. The exact segment-0 sample count
varies per event (it's bounded by a fixed device-flash byte budget, not
a fixed sample count — quiet events fit more samples because zero
deltas pack into ``00 NN`` markers compactly).
Implementation: :func:`decode_tran_initial`.
────────────────────────────────────────────────────────────────────────────
Segment header (40 02, 20 bytes total)
────────────────────────────────────────────────────────────────────────────
The 18-byte payload of the ``40 02`` block:
| Offset | Field | Status |
|-----------|---------------------------------------------|-------------|
| [0:2] | T_delta at first sample of new segment | ✅ confirmed|
| | (int16 BE, in 16-count units) | |
| [2:4] | Likely T_delta at sample seg_start+1 | 🟡 likely |
| [4:6] | Unknown (varies; possibly checksum) | ❓ open |
| [6:8] | Byte length to next segment header − 2 | ✅ confirmed|
| | (uint16 BE; useful for walker pre-scan) | |
| [8:12] | Monotonic uint32 LE counter | ✅ confirmed|
| | (starts ~0x47, increments by 1 per segment) | |
| [12:14] | Constant ``02 00`` | ✅ confirmed|
| [14:18] | Unknown 4-byte field | ❓ open |
────────────────────────────────────────────────────────────────────────────
What breaks the multi-segment decoder (the main open question)
────────────────────────────────────────────────────────────────────────────
After segment 0 ends and the segment header T_delta is consumed,
applying segment 1's blocks as Tran continuation produces values that
diverge from truth by sample ~512. The block structure inside segment
1 is IDENTICAL to segment 0 (same alternating 10 NN / 00 NN pattern),
and the delta budget matches the segment size exactly (V70 segment 1
has 264 nibble-deltas + 244 RLE zeros = 508 = the segment's sample
count). But the cumulative is wrong.
The strongest unverified hypothesis is that segments rotate channels:
segment 0 → Tran samples 0..509
segment 1 → Vert samples 0..507
segment 2 → Long samples 0..507
segment 3 → Mic samples 0..507
segment 4 → Tran samples 510..N (continuation)
...
This is consistent with the segment-1 block sums net-to-near-zero in
V70 (where all 4 channels are near zero) and with the per-segment delta
budget matching the segment size for a single channel. It is NOT yet
verified because the per-segment channel anchor isn't pinned down in
the segment header — bytes [4:6] and [14:18] of the header are still
open and probably encode V/L/M anchors.
See ``docs/waveform_codec_re_status.md`` for the current working notes
and the suggested next experiment ("segment-channel scoring analyzer").
"""
from __future__ import annotations
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple
@dataclass
class WaveformBlock:
"""One tagged block parsed out of a Blastware waveform-file body."""
offset: int # byte offset into body
tag_hi: int # first tag byte (0x10 / 0x20 / 0x00 / 0x30 / 0x40)
tag_lo: int # second tag byte (NN)
data: bytes # block payload (excludes the 2-byte tag)
length: int # total block length on the wire (includes the tag)
@property
def kind(self) -> str:
return f"{self.tag_hi:02x} {self.tag_lo:02x}"
def find_data_start(body: bytes) -> int:
"""Auto-detect the offset of the first data block.
The body starts with a 7-byte preamble (magic ``00 02 00`` + two int16 BE
Tran anchors). After that, the data section starts with a tag — usually
``10 NN`` or ``20 NN``, but quiet events may begin with a ``00 NN`` RLE
marker. We return the offset of the first recognized tag.
"""
# Try fixed offset 7 first (canonical preamble length).
if len(body) >= 9:
b, nn = body[7], body[8]
# Accept the same tag vocabulary ``walk_body`` accepts, including the
# wide-NN forms (``0X``/``1X``/``2X``) and the variable-width ``40 NN``
# segment header.
if ((b & 0xF0) in (0x00, 0x10, 0x20) and nn % 4 == 0
and ((b & 0x0F) != 0 or 0 < nn <= 0xFC)) \
or (b == 0x30 and nn % 4 == 0 and 0 < nn <= 0xFC) \
or (b == 0x40 and 0 < nn <= 0x08) \
or is_tagless_segment_header(body, 7):
return 7
# Fall back to scanning the first 20 bytes.
for i in range(min(20, len(body) - 1)):
b = body[i]
nn = body[i + 1]
if b in (0x10, 0x20) and nn % 4 == 0 and 0 < nn <= 0xFC:
return i
return -1
# Channel-id byte carried in every segment header. Previously mis-read as a
# "monotonic uint32 LE counter"; it is really ``[channel][00][00][segment]``.
# Verified 2026-08-25 on 1697/1697 segment headers across the ground-truth
# corpus with zero disagreements against the decoded channel rotation.
SEGMENT_CHANNEL_IDS = {0x46: "Tran", 0x47: "Vert", 0x48: "Long", 0x49: "MicL"}
# A tagless segment header: the 14-byte tail of a ``40 NN`` header with no tag
# and no previous-channel continuation deltas (the NN=0 case).
_TAGLESS_HEADER_LEN = 14
def is_tagless_segment_header(body: bytes, i: int) -> bool:
"""True if a bare 14-byte segment header starts at *i*.
Layout ``[field2:2][len_to_next:2][channel_id:4][marker:2][anchors:4]``.
The discriminator is the 6 bytes at ``[4:10]``: a known channel id, two
zero bytes, a small segment index, and the ``01 00`` / ``02 00`` marker.
"""
if i + _TAGLESS_HEADER_LEN > len(body):
return False
return (body[i + 4] in SEGMENT_CHANNEL_IDS
and body[i + 5] == 0x00 and body[i + 6] == 0x00
and body[i + 8] in (0x01, 0x02) and body[i + 9] == 0x00)
def walk_body(body: bytes, start: Optional[int] = None) -> List[WaveformBlock]:
"""Walk the tagged-block sequence starting at *start* (auto-detected by default).
Stops when an unrecognized tag is encountered or end of body is reached.
Returned blocks are in stream order.
"""
if start is None:
start = find_data_start(body)
if start < 0:
return []
blocks: List[WaveformBlock] = []
i = start
while i + 1 < len(body):
t0 = body[i]
t1 = body[i + 1]
if t0 == 0x10 and t1 % 4 == 0 and 0 < t1 <= 0xFC:
length = t1 // 2 + 2
elif (t0 & 0xF0) == 0x10 and (t0 & 0x0F) != 0 and t1 % 4 == 0:
# Wide-NN nibble block: ``1X NN`` where X is the high nibble of a
# 12-bit NN value. NN = ((t0 & 0x0F) << 8) | t1. Block length
# = NN/2 + 2 bytes (NN nibble deltas, same as ``10 NN`` semantics
# but with NN > 0xFC). Confirmed 2026-05-11 in SP0 segment 12
# where V continuation uses ``11 90`` = NN=0x190=400.
wide_nn = ((t0 & 0x0F) << 8) | t1
length = wide_nn // 2 + 2
elif t0 == 0x20 and t1 % 4 == 0 and 0 < t1 <= 0xFC:
length = t1 + 2
elif (t0 & 0xF0) == 0x20 and (t0 & 0x0F) != 0 and t1 % 4 == 0:
# Wide-NN int8 block: ``2X NN`` extends NN to 12 bits the same way.
wide_nn = ((t0 & 0x0F) << 8) | t1
length = wide_nn + 2
elif (t0 & 0xF0) == 0x00 and t1 % 4 == 0:
# ``00 NN`` RLE zero-delta run, plus its wide form ``0X NN``
# (X != 0) which extends NN to 12 bits exactly like ``1X``/``2X``:
# NN = ((t0 & 0x0F) << 8) | t1. A narrow run maxes out at
# NN=0xFC, so quiet stretches longer than 252 samples must use
# the wide form. Confirmed 2026-08-25 against six production
# events (e.g. ``01 0c`` = 268 repeats in K558LKOF.460W).
length = 2
elif t0 == 0x30 and t1 % 4 == 0 and 0 < t1 <= 0xFC:
# Data-section ``30 NN`` blocks carry NN 12-bit signed deltas packed
# as NN/4 groups of (2-byte high-nibble field + 4 × int8 low byte).
# Length = NN/4 × 6 + 2 = NN × 1.5 + 2 (= 8 for NN=4, 14 for NN=8,
# 20 for NN=12, etc.). Confirmed 2026-05-11 by full-decoder
# verification against BW ASCII export.
#
# Trailer-section ``30 NN`` blocks have a different length formula
# (NN × 4 = 32 for NN=8 in trailers). We try the data-section
# length first and fall back to the trailer length if needed.
cand_data = t1 * 3 // 2 + 2
cand_trailer = t1 * 4
if (i + cand_data < len(body) - 1
and body[i + cand_data] in (0x10, 0x20, 0x00, 0x30, 0x40)):
length = cand_data
else:
length = cand_trailer
elif t0 == 0x40 and 0 < t1 <= 0x08:
# ``40 NN`` segment header. NN is the number of int16 BE
# continuation deltas the header carries for the PREVIOUS
# channel, so the header grows with NN:
# length = 2 (tag) + 2*NN (deltas) + 14 (fixed tail)
# ``40 02`` (20 bytes) dominates, but ``40 01`` (18) and
# ``40 03`` (22) both occur in production files. Confirmed
# 2026-08-25; the constant ``02 00`` marker moves with NN too
# (see :func:`parse_segment_header`).
length = 2 * t1 + 16
elif is_tagless_segment_header(body, i):
# Segment header with no ``40 NN`` tag (NN=0 — the previous channel
# needed no continuation deltas). Emit it as a synthetic ``40 00``
# block whose ``data`` is the whole 14-byte record, so the nd=0
# offsets in :func:`decode_waveform_v2` line up unchanged.
blocks.append(WaveformBlock(
offset=i, tag_hi=0x40, tag_lo=0x00,
data=bytes(body[i : i + _TAGLESS_HEADER_LEN]),
length=_TAGLESS_HEADER_LEN,
))
i += _TAGLESS_HEADER_LEN
continue
else:
# Unknown tag; stop. Caller can inspect ``i`` to see where.
break
if i + length > len(body):
break
data = bytes(body[i + 2 : i + length])
blocks.append(WaveformBlock(offset=i, tag_hi=t0, tag_lo=t1, data=data, length=length))
i += length
return blocks
def split_segments(blocks: List[WaveformBlock]) -> List[List[WaveformBlock]]:
"""Group consecutive blocks into segments separated by ``40 02`` headers.
The first segment is whatever runs before the first ``40 02`` header
(typically the "segment 0" preamble data after the body preamble).
Subsequent segments start with a ``40 02`` block, then have their
own data blocks until the next ``40 02``.
"""
segments: List[List[WaveformBlock]] = []
current: List[WaveformBlock] = []
for b in blocks:
if b.tag_hi == 0x40:
if current:
segments.append(current)
current = [b]
else:
current.append(b)
if current:
segments.append(current)
return segments
def parse_segment_header(block: WaveformBlock) -> Optional[dict]:
"""Decode the payload of a ``40 NN`` segment header.
NN (the tag's low byte) is the number of int16 BE continuation deltas
the header carries for the PREVIOUS channel, so every field after
those deltas shifts by ``2 * NN``. The payload is ``2 * NN + 14``
bytes. ``40 02`` is the common case; ``40 01`` and ``40 03`` also
occur in production files (confirmed 2026-08-25).
Returns a dict with the labelled fields, or None if *block* is not a
segment header or is too short.
"""
if block.tag_hi != 0x40 or block.tag_lo > 0x08:
return None
nd = block.tag_lo
if len(block.data) < 2 * nd + 14:
return None
p = block.data
counter = int.from_bytes(p[2 * nd + 4 : 2 * nd + 8], "little", signed=False)
return {
"n_prev_deltas": nd,
# ``nd`` int16 BE deltas extending the previous channel.
"prev_deltas": [
int.from_bytes(p[2 * k : 2 * k + 2], "big", signed=True)
for k in range(nd)
],
"field2": p[2 * nd : 2 * nd + 4], # 4-byte field, role unconfirmed
"counter": counter, # legacy: raw uint32 LE of the id field
"channel": SEGMENT_CHANNEL_IDS.get(p[2 * nd + 4]),
"segment_index": p[2 * nd + 7],
"marker": p[2 * nd + 8 : 2 * nd + 10], # always b"\x02\x00"
"anchors": [
int.from_bytes(p[2 * nd + 10 : 2 * nd + 12], "big", signed=True),
int.from_bytes(p[2 * nd + 12 : 2 * nd + 14], "big", signed=True),
],
}
def _s4(n: int) -> int:
"""Sign-extend a 4-bit value to signed int (0..7 → 0..7; 8..F → -8..-1)."""
return n if n < 8 else n - 16
def _i8(b: int) -> int:
"""Reinterpret an unsigned byte as signed int8."""
return b if b < 128 else b - 256
def decode_tran_initial(body: bytes) -> Optional[List[int]]:
"""
Decode the initial Tran-channel samples — VERIFIED 2026-05-11.
Returns Tran samples in **16-count units** (LSB = 0.005 in/s at Normal
range — the same quantization BW uses for its ASCII export). Returns
``None`` if the body cannot be parsed.
The decoded list extends from sample 0 through the end of segment 0
(= just before the first ``40 02`` segment header; ~510 sample-sets
for the events tested). Multi-segment decoding requires continuing
past the segment header — that's done by :func:`decode_tran_full`
when the per-segment rules are pinned down for all signal types.
Codec for segment 0 (CONFIRMED 2026-05-11 against 7 fixture events):
- Body bytes [0:3] are the magic ``00 02 00``.
- Body bytes [3:5] = ``Tran[0]`` as int16 BE in 16-count units.
- Body bytes [5:7] = ``Tran[1]`` as int16 BE in 16-count units.
- Data blocks (``10 NN`` or ``20 NN``) carry Tran deltas starting
at sample 2:
* ``10 NN``: NN nibbles = NN/2 bytes; each nibble is a 4-bit
signed delta (0..7 → 0..+7; 8..F → -8..-1). High nibble of
each byte comes first.
* ``20 NN``: NN int8 signed deltas (one delta per byte).
- ``00 NN`` blocks are run-length-encoded zero deltas: append NN
copies of the current cumulative Tran value (no change).
- ``30 NN`` blocks have not yet been decoded for content — they
appear in segment 0 of loud-from-start events (SS0, SV0) and
seem to signal a transition or special-case interpretation.
The walker steps over them but their data is ignored.
The walk stops at the first ``40 02`` segment header.
"""
if len(body) < 7 or body[0:3] != b"\x00\x02\x00":
return None
t0 = int.from_bytes(body[3:5], "big", signed=True)
t1 = int.from_bytes(body[5:7], "big", signed=True)
start = find_data_start(body)
if start < 0:
return [t0, t1]
out = [t0, t1]
cur = t1
for blk in walk_body(body, start):
if blk.tag_hi == 0x40:
# Segment boundary — stop. Multi-segment decode is decode_tran_full.
break
if blk.tag_hi == 0x10:
for byte in blk.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur += _s4(nib)
out.append(cur)
elif blk.tag_hi == 0x20:
for byte in blk.data:
cur += _i8(byte)
out.append(cur)
elif blk.tag_hi == 0x00:
# RLE zero deltas: append NN copies of current Tran value.
for _ in range(blk.tag_lo):
out.append(cur)
# 30 NN: unknown content; skip.
return out
def decode_waveform_legacy(body: bytes) -> Optional[dict]:
"""
SUPERSEDED 2026-08-25 — the tag-dispatch / segment-header model.
Retained because ``micromate/idf_file.py`` trial-decodes Thor IDFW bodies
at many candidate offsets and keeps whichever yields the most samples;
the record-chain decoder returns None where this one returned garbage,
which shifts that heuristic's winner. Thor is pinned here until its own
body-offset search is reworked. Do not use for series-3.
Decode the body into per-channel sample arrays.
Status (2026-05-11 evening — channel-rotation hypothesis CONFIRMED):
segments rotate channels in fixed order **Tran → Vert → Long → MicL**.
Each channel-segment carries a 2-sample anchor pair in segment-header
bytes [14:18] (or in the body preamble for the initial Tran segment)
plus a stream of delta blocks for samples 2 onward.
Returns ``{"Tran": [...], "Vert": [...], "Long": [...], "MicL": [...]}``
with each channel's decoded samples in 16-count units (LSB = 0.005
in/s at Normal range). Returns ``None`` if the body cannot be
parsed.
"""
if len(body) < 7 or body[0:3] != b"\x00\x02\x00":
return None
channels = ["Tran", "Vert", "Long", "MicL"]
out: dict = {ch: [] for ch in channels}
# Initial Tran segment: preamble anchor pair + delta blocks before first 40 02.
t0 = int.from_bytes(body[3:5], "big", signed=True)
t1 = int.from_bytes(body[5:7], "big", signed=True)
out["Tran"].extend([t0, t1])
start = find_data_start(body)
if start < 0:
return out
blocks = walk_body(body, start)
seg_idx = [i for i, b in enumerate(blocks) if b.tag_hi == 0x40]
def apply_blocks(channel: str, anchor: int,
block_start: int, block_end: int) -> int:
"""Apply delta blocks [block_start, block_end) to *channel*'s sample
list, starting from *anchor*. Returns the final cumulative value."""
cur = anchor
for bi in range(block_start, block_end):
blk = blocks[bi]
if (blk.tag_hi & 0xF0) == 0x10:
# Both ``10 NN`` (NN ≤ 0xFC) and wide-NN ``1X NN`` (X != 0)
# are nibble-delta streams. The walker has already used the
# right length; here we just iterate the payload bytes.
for byte in blk.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur += _s4(nib)
out[channel].append(cur)
elif (blk.tag_hi & 0xF0) == 0x20:
# ``20 NN`` and wide ``2X NN`` both carry int8 deltas.
for byte in blk.data:
cur += _i8(byte)
out[channel].append(cur)
elif (blk.tag_hi & 0xF0) == 0x00:
# RLE zero-delta run. Wide form ``0X NN`` carries the high
# nibble of a 12-bit NN in the tag byte, same as ``1X``/``2X``.
run = ((blk.tag_hi & 0x0F) << 8) | blk.tag_lo
for _ in range(run):
out[channel].append(cur)
elif blk.tag_hi == 0x30:
# 12-bit signed deltas, packed as NN/4 groups of 6 bytes each:
# bytes [0:2] = 16 bits = 4 × 4-bit high nibbles (MSB first)
# bytes [2:6] = 4 × int8 low bytes
# Each delta = sign_extend_12((high_nibble << 8) | low_byte).
# Confirmed 2026-05-11 against all 14 ``30 NN`` blocks in the
# bundled fixtures.
n_groups = blk.tag_lo // 4
for g in range(n_groups):
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[channel].append(cur)
# 40 02: should not occur in segment data.
return cur
# Initial Tran segment: deltas from start of body up to first 40 02 (or end).
first_seg = seg_idx[0] if seg_idx else len(blocks)
last_tran_value = apply_blocks("Tran", t1, 0, first_seg)
# Subsequent segments rotate channels. Each segment header carries:
# bytes [0:2] and [2:4] = 2 deltas extending the PREVIOUS channel
# bytes [14:16] and [16:18] = anchor pair for THIS segment's channel
#
# Rotation: V, L, M, T, V, L, M, T, ... (initial Tran segment is the
# implicit T in the cycle.)
rotation = ["Vert", "Long", "MicL", "Tran"]
# Track each channel's "running cumulative value" so we can apply the
# previous-channel extension deltas at every segment boundary.
last_value = {"Tran": last_tran_value, "Vert": None, "Long": None, "MicL": None}
prev_channel = "Tran"
for k, hi in enumerate(seg_idx):
header = blocks[hi]
# Channel comes from the header's own id byte, which is authoritative.
# The old rotation-by-position fallback is kept for headers whose id
# byte isn't one of the four known values — but a single missed or
# extra header would desync rotation and corrupt every later channel,
# which is exactly what tagless headers used to cause.
_nd = header.tag_lo
channel = None
if len(header.data) >= 2 * _nd + 8:
channel = SEGMENT_CHANNEL_IDS.get(header.data[2 * _nd + 4])
if channel is None:
channel = rotation[k % 4]
# ``40 NN``: NN int16 BE continuation deltas for the previous channel
# come first, so every later field shifts by 2*NN. NN is usually 2
# but 1 and 3 both occur (confirmed 2026-08-25).
nd = header.tag_lo
if len(header.data) < 2 * nd + 14:
continue
# Validate: real segment headers have the constant `02 00` marker
# right after the counter. Trailer/footer "40 NN" markers contain
# ASCII serial bytes or other non-header data there and would
# otherwise be mis-read as segment headers, adding spurious tail
# samples.
if header.data[2 * nd + 8 : 2 * nd + 10] != b"\x02\x00":
break
# Extend the PREVIOUS channel by NN more samples.
if last_value[prev_channel] is not None:
v = last_value[prev_channel]
for d in range(nd): # NB: not `k` — that's the segment index
v += int.from_bytes(
header.data[2 * d : 2 * d + 2], "big", signed=True
)
out[prev_channel].append(v)
last_value[prev_channel] = v
# Anchor pair for THIS segment's channel.
c0 = int.from_bytes(
header.data[2 * nd + 10 : 2 * nd + 12], "big", signed=True
)
c1 = int.from_bytes(
header.data[2 * nd + 12 : 2 * nd + 14], "big", signed=True
)
out[channel].extend([c0, c1])
# Apply delta blocks for this segment.
next_hi = seg_idx[k + 1] if k + 1 < len(seg_idx) else len(blocks)
last_value[channel] = apply_blocks(channel, c1, hi + 1, next_hi)
prev_channel = channel
return out
# ── ADC-scale conversion helpers ────────────────────────────────────────────
# Scaling factor: decode_waveform_v2 produces geo-channel samples in the BW
# display quantization (16-count units, LSB = 0.005 in/s at Normal range).
# The legacy consumer pipeline (sfm/event_hdf5.py) expects raw_samples in
# 1-count ADC units (× full_scale / 32768 → physical). To plug the new
# decoder in without rewriting consumers, multiply geo values by 16.
#
# Mic samples are already in raw ADC counts (decoded value 1 = 1 mic ADC count
# = -81.94 dB on the BW display). Mic values pass through unchanged.
_GEO_DECODER_TO_ADC = 16
def decoded_to_adc_counts(decoded: dict) -> dict:
"""Convert :func:`decode_waveform_v2` output to int16 ADC counts.
Geo channels are scaled by ×16 (decoder produces 16-count units,
consumer expects 1-count ADC). Mic is passed through as raw counts.
"""
if not decoded:
return {}
return {
"Tran": [v * _GEO_DECODER_TO_ADC for v in decoded.get("Tran", [])],
"Vert": [v * _GEO_DECODER_TO_ADC for v in decoded.get("Vert", [])],
"Long": [v * _GEO_DECODER_TO_ADC for v in decoded.get("Long", [])],
"MicL": list(decoded.get("MicL", [])),
}
def mic_count_to_db(count: int) -> float:
"""Convert a MicL ADC count to dB(L) for BW-display-compatible output.
Empirical formula (confirmed 2026-05-11 against V70 fixture: count=813
→ 140.1 dB; count=±1 → ±81.94 dB; count=±24 → ±109.5 dB):
dB = sign(count) × (81.94 + 20 × log10(|count|)) for |count| ≥ 1
dB = 0.0 for count == 0
The constant 81.94 corresponds to 10^(81.94/20) ≈ 12490 mic ADC counts
being the dB(L) reference level — almost certainly a calibration
constant from the device's mic.
"""
if count == 0:
return 0.0
sign = 1.0 if count > 0 else -1.0
return sign * (81.94 + 20.0 * math.log10(abs(count)))
# ── A5-frame entry point ────────────────────────────────────────────────────
def decode_a5_frames(a5_frames) -> Optional[dict]:
"""Decode a list of A5 (BULK_WAVEFORM_STREAM) frames into per-channel
int16 ADC samples.
Returns ``{"Tran": [...], "Vert": [...], "Long": [...], "MicL": [...]}``
with each channel's samples in **1-count ADC units** (the legacy
``event.raw_samples`` convention — multiply by ``full_scale / 32768``
to convert to physical units; for mic, use :func:`mic_count_to_db` or
a per-count psi factor).
Returns ``None`` if the frames cannot be parsed.
This is the wired-up production entry point. It:
1. Reconstructs the BW-binary body bytes from the A5 frames
(``blastware_file.extract_body_bytes``).
2. Runs the verified codec (``decode_waveform_v2``) on the body.
3. Converts to int16 ADC counts via :func:`decoded_to_adc_counts`.
"""
# Local import to avoid a cycle: blastware_file imports models and
# ultimately client.py imports waveform_codec.
from .blastware_file import extract_body_bytes
if not a5_frames:
return None
_strt, body, _footer = extract_body_bytes(a5_frames)
if not body:
return None
decoded = decode_waveform_v2(body)
if decoded is None:
return None
return decoded_to_adc_counts(decoded)
# ── Record-chain body model (CONFIRMED 2026-08-25) ──────────────────────────
#
# The body is NOT a flat tag-dispatch stream with ``40 NN`` segment headers.
# It is a chain of self-delimiting per-channel RECORDS:
#
# off+0 field2 uint16 purpose unknown (not a length, not a checksum)
# off+2 len uint16 BE next_record = off + 2 + len <- authoritative
# off+4 chan_id 0x46 Tran / 0x47 Vert / 0x48 Long / 0x49 MicL
# 0x06 = end of waveform stream
# off+5 0x00
# off+6 0x00
# off+7 segment index
# off+8 mode 2 bytes, a 3-valued enum (see below)
# off+10 anchors 2 x int16 BE, ABSOLUTE — present only when mode is 02 00
#
# Mode semantics, all ground-truth verified:
# 02 00 14-byte header; emit the 2 anchors, then blocks are CUMULATIVE deltas
# 01 00 10-byte header; no anchors; blocks carry ABSOLUTE sample values
# 00 03 10-byte header; NO TAGS AT ALL — the data section is raw 12-bit
# packed ABSOLUTE samples (6 bytes -> 4 samples)
#
# ``40 NN`` is an ordinary int16 BE DATA block (length 2*NN + 2), never a header.
# The previous model read it as a variable-width segment header of length
# 2*NN + 16, which is why walks drifted and channels came out unequal.
#
# Verified over the 1,388 series-3 waveform binaries in the production
# snapshot: the length chain terminates on a 0x06 record in 1,387 of them (the
# exception has an ambiguous footer, handled by the caller), and all four
# channels come out at identical length in 1,388/1,388 — against 156/1,388
# under the superseded model. Against the 75 events with a preserved
# Blastware ASCII export: sample-count exact 72/75 -> 75/75, fully exact
# 70/75 -> 73/75.
CHANNEL_IDS = {0x46: "Tran", 0x47: "Vert", 0x48: "Long", 0x49: "MicL"}
STREAM_END_ID = 0x06
MODE_DELTA = (0x02, 0x00)
MODE_ABSOLUTE = (0x01, 0x00)
MODE_RAW12 = (0x00, 0x03)
# 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:
return (b[p] << 8) | b[p + 1]
def _i16(b: bytes, p: int) -> int:
v = _u16(b, p)
return v - 0x10000 if v >= 0x8000 else v
def data_block_len(body: bytes, p: int) -> Tuple[Optional[int], Optional[int]]:
"""``(byte_length, n_samples)`` of the data block at *p*, or ``(None, None)``.
Data-section blocks only — there is no segment-header tag in this model.
``30 NN`` has no trailer-length fallback here; that fallback corrupted
records whose ``30 NN`` sat near a record boundary.
"""
if p + 2 > len(body):
return None, None
t0, t1 = body[p], body[p + 1]
hi = t0 & 0xF0
nn = ((t0 & 0x0F) << 8) | t1
if hi == 0x40: # int16 BE data block
# 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:
return 2, nn # RLE hold
if hi == 0x10:
return nn // 2 + 2, nn # 4-bit nibble
if hi == 0x20:
return nn + 2, nn # int8
if hi == 0x30:
return nn * 3 // 2 + 2, nn # 12-bit packed
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] = []
for g in range(len(data) // 6):
hi = (data[6 * g] << 8) | data[6 * g + 1]
for k in range(4):
x = (((hi >> (12 - 4 * k)) & 0xF) << 8) | data[6 * g + 2 + k]
out.append(x - 0x1000 if x >= 0x800 else x)
return out
def is_record(body: bytes, p: int) -> bool:
"""True if a per-channel record header starts at *p*."""
return (p + 10 <= len(body)
and body[p + 4] in CHANNEL_IDS
and body[p + 5] == 0x00 and body[p + 6] == 0x00
and 8 <= _u16(body, p + 2) <= len(body) - p
and (body[p + 8], body[p + 9]) in _MODES)
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 untagged preambles (``00 00 03``
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]) in _UNTAGGED_MODES:
scan_from = 3
else:
# 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)
if nxt + 5 <= len(body) and (is_record(body, nxt)
or body[nxt + 4] == STREAM_END_ID):
return i
length, _ = data_block_len(body, i)
if length is None:
return None
i += length
return None
for i in range(scan_from, max(scan_from, len(body) - 10)):
if is_record(body, i):
nxt = i + 2 + _u16(body, i + 2)
if nxt + 5 <= len(body) and (is_record(body, nxt)
or body[nxt + 4] == STREAM_END_ID):
return i
return None
def walk_records(body: bytes, first: Optional[int] = None) -> List[dict]:
"""Follow the length chain from *first* to the ``0x06`` terminator."""
if first is None:
first = find_first_record(body)
out: List[dict] = []
if first is None:
return out
p, seen = first, set()
while p is not None and p + 10 <= len(body):
if p in seen:
break
seen.add(p)
cid = body[p + 4]
if cid == STREAM_END_ID or cid not in CHANNEL_IDS:
break
length = _u16(body, p + 2)
if length < 8 or p + 2 + length > len(body):
break
out.append({"offset": p, "channel": CHANNEL_IDS[cid],
"segment_index": body[p + 7],
"mode": (body[p + 8], body[p + 9]),
"end": p + 2 + length})
p += 2 + length
return out
def decode_waveform_v2(body: bytes) -> Optional[dict]:
"""Decode a Blastware waveform body into per-channel sample arrays.
Returns ``{"Tran": [...], "Vert": [...], "Long": [...], "MicL": [...]}``
in 16-count units (LSB = 0.005 in/s at Normal range), or None if *body*
is not a decodable waveform body.
Implements the record-chain model documented above.
"""
if len(body) < 8 or body[0] != 0x00:
return None
preamble = (body[1], body[2])
if preamble not in (MODE_DELTA, MODE_ABSOLUTE, MODE_RAW12, MODE_RAW16):
return None
first = find_first_record(body)
if first is None:
return None
out: dict = {c: [] for c in ("Tran", "Vert", "Long", "MicL")}
def run(channel: str, start: int, end: int, absolute: bool) -> None:
cur = out[channel][-1] if out[channel] else 0
i = start
while i < end:
length, nn = data_block_len(body, i)
if length is None or i + length > end:
return # stop this record; the chain resyncs at end
hi = body[i] & 0xF0
if hi == 0x00:
vals = [None] * nn
elif hi == 0x10:
vals = []
for k in range(nn):
byte = body[i + 2 + k // 2]
v = (byte >> 4) if k % 2 == 0 else (byte & 0xF)
vals.append(v - 16 if v >= 8 else v)
elif hi == 0x20:
vals = [v - 256 if v >= 128 else v
for v in body[i + 2:i + 2 + nn]]
elif hi == 0x30:
vals = unpack12(body[i + 2:i + length])
else:
vals = [_i16(body, i + 2 + 2 * k) for k in range(nn)]
for v in vals:
if v is None:
pass # RLE hold, in delta AND absolute modes
elif absolute:
cur = v
else:
cur += v
out[channel].append(cur)
i += length
# Segment 0 is an implicit Tran record carried in the preamble.
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]))
for rec in walk_records(body, first):
ch, off, mode, end = (rec["channel"], rec["offset"],
rec["mode"], rec["end"])
if mode == MODE_DELTA:
out[ch].extend([_i16(body, off + 10), _i16(body, off + 12)])
run(ch, off + 14, end, absolute=False)
elif mode == MODE_ABSOLUTE:
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
parsers/s3_analyzer.py
+2
View File
@@ -53,7 +53,9 @@ SUB_TABLE: dict[int, tuple[str, str, str]] = {
0x82: ("TRIGGER_CONFIG_WRITE", "BW→S3", "0x1C bytes; trigger config block; mirrors SUB 1C"),
0x83: ("TRIGGER_WRITE_CONFIRM", "BW→S3", "Short frame; commit step after 0x82"),
# S3→BW responses
0x5A: ("BULK_WAVEFORM_STREAM", "BW→S3", "Bulk waveform chunk request; response is A5 stream"),
0xA4: ("POLL_RESPONSE", "S3→BW", "Response to SUB 5B poll"),
0xA5: ("BULK_WAVEFORM_RESPONSE", "S3→BW", "Response to SUB 5A; waveform chunks + metadata"),
0xFE: ("FULL_CONFIG_RESPONSE", "S3→BW", "Response to SUB 01"),
0xF9: ("CHANNEL_CONFIG_RESPONSE", "S3→BW", "Response to SUB 06"),
0xF7: ("EVENT_INDEX_RESPONSE", "S3→BW", "Response to SUB 08; contains backlight/power-save"),
parsers/s3_parser.py
+33 -36
View File
@@ -33,7 +33,7 @@ STX = 0x02
ETX = 0x03
ACK = 0x41
__version__ = "0.2.3"
__version__ = "0.2.5"
@dataclass
@@ -184,9 +184,9 @@ def validate_bw_body_auto(body: bytes) -> Optional[Tuple[bytes, bytes, str]]:
def parse_s3(blob: bytes, trailer_len: int) -> List[Frame]:
frames: List[Frame] = []
IDLE = 0
IN_FRAME = 1
AFTER_DLE = 2
IDLE = 0
IN_FRAME = 1
IN_FRAME_DLE = 2 # saw DLE inside frame — waiting for next byte
state = IDLE
body = bytearray()
@@ -206,66 +206,63 @@ def parse_s3(blob: bytes, trailer_len: int) -> List[Frame]:
state = IN_FRAME
i += 2
continue
# ACK bytes, boot strings, garbage — silently ignored
elif state == IN_FRAME:
if b == DLE:
state = AFTER_DLE
state = IN_FRAME_DLE
i += 1
continue
body.append(b)
else: # AFTER_DLE
if b == DLE:
body.append(DLE)
state = IN_FRAME
i += 1
continue
if b == ETX:
# Bare ETX = real S3 frame terminator (confirmed from S3FrameParser)
end_offset = i + 1
trailer_start = i + 1
trailer_end = trailer_start + trailer_len
trailer = blob[trailer_start:trailer_end]
chk_valid = None
chk_type = None
chk_hex = None
payload = bytes(body)
if len(body) >= 1:
received_chk = body[-1]
computed_chk = checksum8_sum(bytes(body[:-1]))
if computed_chk == received_chk:
chk_valid = True
chk_type = "SUM8"
chk_hex = f"{received_chk:02x}"
payload = bytes(body[:-1])
else:
chk_valid = False
# S3 checksums are deliberately not validated here.
# Large S3 responses (A5 bulk waveform, E5 compliance) embed
# inner DLE+ETX sub-frame terminators whose trailing 0x03 byte
# lands where the parser would expect the SUM8 checksum, causing
# false failures. The live protocol (protocol.py _validate_frame)
# also skips S3 checksum enforcement for the same reason.
frames.append(Frame(
index=idx,
start_offset=start_offset,
end_offset=end_offset,
payload_raw=bytes(body),
payload=payload,
payload=bytes(body),
trailer=trailer,
checksum_valid=chk_valid,
checksum_type=chk_type,
checksum_hex=chk_hex
checksum_valid=None,
checksum_type=None,
checksum_hex=None
))
idx += 1
state = IDLE
i = trailer_end
continue
body.append(b)
else: # IN_FRAME_DLE
if b == DLE:
# DLE DLE → literal 0x10 in payload
body.append(DLE)
state = IN_FRAME
i += 1
continue
if b == ETX:
# DLE+ETX inside a frame = inner-frame terminator (A4/E5 sub-frames).
# Treat as literal data, NOT the outer frame end.
body.append(DLE)
body.append(ETX)
state = IN_FRAME
i += 1
continue
# Unexpected DLE + byte → treat as literal data
body.append(DLE)
body.append(b)
state = IN_FRAME
i += 1
continue
i += 1
pyproject.toml
+7 -3
View File
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "seismo-relay"
version = "0.12.0"
version = "0.31.0"
description = "Python client and REST server for MiniMate Plus seismographs"
requires-python = ">=3.10"
dependencies = [
@@ -12,9 +12,13 @@ dependencies = [
"uvicorn[standard]>=0.24",
"pyserial>=3.5",
"sqlalchemy>=2.0",
"python-multipart>=0.0.7",
"h5py>=3.10",
"numpy>=1.24",
"matplotlib>=3.8",
]
[tool.setuptools.packages.find]
# Auto-discovers minimateplus/, sfm/, bridges/ as packages
# Auto-discovers minimateplus/, micromate/, sfm/, bridges/ as packages
where = ["."]
include = ["minimateplus*", "sfm*", "bridges*"]
include = ["minimateplus*", "micromate*", "sfm*", "bridges*"]
requirements.txt
+4
View File
@@ -2,3 +2,7 @@ fastapi
uvicorn
sqlalchemy
pyserial
python-multipart
h5py
numpy
matplotlib
scratch/next_experiment_skeleton.py
+360
View File
@@ -0,0 +1,360 @@
"""
scratch/next_experiment_skeleton.py — segment-channel scoring analyzer.
This is the suggested NEXT EXPERIMENT for cracking the waveform body codec.
The goal is to figure out what segments 1+ contain, since segment 0 = Tran
is solved but multi-segment continuation diverges from truth at sample ~512.
────────────────────────────────────────────────────────────────────────────
The hypothesis to test
────────────────────────────────────────────────────────────────────────────
Segments rotate through channels:
segment 0 → Tran samples 0..509
segment 1 → Vert samples 0..507
segment 2 → Long samples 0..507
segment 3 → Mic samples 0..507
segment 4 → Tran samples 510..N (continuation)
...
This would explain why segment 0 works perfectly (it's pure Tran) and why
applying segment 1's blocks as Tran continuation gives wrong values
(it's actually Vert).
────────────────────────────────────────────────────────────────────────────
What the analyzer should do
────────────────────────────────────────────────────────────────────────────
For each segment in each fixture event:
1. Run the segment-0 block-walker + RLE decode (the same algorithm that
``decode_tran_initial`` uses) over the segment's blocks. Start from
some anchor value and produce a cumulative trajectory of length =
number-of-deltas-in-segment.
2. For each candidate channel C ∈ {Tran, Vert, Long, MicL}:
For each candidate anchor location in the segment-header payload
(try [0:2], [2:4], [4:6], [14:16], [16:18] as int16 BE):
Compare the decoded trajectory against truth[C] starting from
the segment's first sample index.
Score = number of matches (or sum of squared errors).
3. Report the best (channel, anchor-location) combination per segment.
If the rotation hypothesis is correct, you'll see:
segment 0 → best score for (Tran, preamble bytes [3:5]) ✓ already known
segment 1 → best score for (Vert, <some-header-byte>)
segment 2 → best score for (Long, <some-header-byte>)
segment 3 → best score for (MicL, <some-header-byte>)
segment 4 → best score for (Tran, continuing from segment 0's end)
If the rotation hypothesis is NOT correct, the scorer will at least narrow
down what segment 1 actually carries. Maybe channels interleave at finer
granularity, or maybe segments alternate by something other than channel.
────────────────────────────────────────────────────────────────────────────
Why this is a scoring analyzer, not a hand-written decoder
────────────────────────────────────────────────────────────────────────────
Direct hand-coding ("assume segment 1 is Vert with anchor at byte X") gets
stuck when the assumption is wrong because the failure mode is silent —
you get plausible-looking-but-wrong samples and have to manually diff
against truth to debug.
The scorer is brute-force but cheap: every fixture event × every segment ×
4 channels × 5 anchor-byte candidates is only ~hundreds of comparisons.
The winning combination jumps out by score.
────────────────────────────────────────────────────────────────────────────
Skeleton
────────────────────────────────────────────────────────────────────────────
"""
from __future__ import annotations
import os
import re
import sys
from dataclasses import dataclass
from typing import List, Optional, Tuple
sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
from minimateplus.waveform_codec import walk_body, find_data_start, WaveformBlock
# ── Reusable pieces ──────────────────────────────────────────────────────────
CHANNELS = ("Tran", "Vert", "Long", "MicL")
LSB_INV = 200 # 1 in/s / 0.005 in/s/LSB; multiply BW-export floats by this
# to get 16-count units (the body's native quantization).
@dataclass
class FixtureEvent:
name: str # e.g. "M529LL1A.SP0"
bin_path: str
txt_path: str
body: bytes
truth: dict # {channel: list of int16-quantized samples}
blocks: List[WaveformBlock]
segment_starts: List[int] # block indices of each 40 02 segment header
segment_sample_starts: List[int] # for each segment, the truth sample index it starts at
def s4(n: int) -> int:
"""4-bit signed nibble decode."""
return n if n < 8 else n - 16
def i8(b: int) -> int:
"""int8 reinterpret of unsigned byte."""
return b if b < 128 else b - 256
def load_fixture(name: str) -> FixtureEvent:
"""Load a fixture event with its truth values and parsed block stream."""
# Find the fixture (search both subdirs of tests/fixtures/).
base = os.path.join(os.path.dirname(__file__), "..", "tests", "fixtures")
candidates = [
os.path.join(base, "5-11-26", name),
os.path.join(base, "decode-re-5-8-26", "event-a", name), # not used directly
]
bin_path = next((c for c in candidates if os.path.exists(c)), None)
if bin_path is None:
# Try a glob walk for the 5-8 fixtures (they're in subdirs).
for root, _, files in os.walk(base):
if name in files:
bin_path = os.path.join(root, name)
break
if bin_path is None:
raise FileNotFoundError(name)
txt_path = bin_path + ".TXT"
with open(bin_path, "rb") as f:
raw = f.read()
body = raw[43:-26]
truth = _parse_txt(txt_path)
blocks = walk_body(body, find_data_start(body))
seg_idx = [i for i, b in enumerate(blocks) if b.tag_hi == 0x40]
# Segment 0 starts at sample 0; subsequent segments start at the
# cumulative sample count from previous segment(s). Tran's segment 0
# is N samples; if rotation hypothesis is correct, segment 1's data
# starts at sample 0 for a *different* channel. The analyzer should
# try both "continues from previous segment" and "starts at sample 0
# of a different channel."
seg_sample_starts = _compute_segment_sample_starts(blocks, seg_idx)
return FixtureEvent(
name=name, bin_path=bin_path, txt_path=txt_path,
body=body, truth=truth, blocks=blocks,
segment_starts=seg_idx, segment_sample_starts=seg_sample_starts,
)
def _parse_txt(path: str) -> dict:
"""Parse BW ASCII TXT export into {channel: [int_samples_in_16_count_units]}."""
with open(path, "r", encoding="utf-8", errors="replace") as f:
lines = f.read().splitlines()
header_idx = next(
(i for i, l in enumerate(lines)
if all(c in l for c in CHANNELS)),
None,
)
if header_idx is None:
return {ch: [] for ch in CHANNELS}
out = {ch: [] for ch in CHANNELS}
for line in lines[header_idx + 1:]:
parts = re.split(r"\s+", line.strip())
if len(parts) < 4:
continue
try:
vals = [float(p) for p in parts[:4]]
except ValueError:
continue
for ch, v in zip(CHANNELS, vals):
# Multiply by LSB_INV; geo channels are in in/s, MicL is in dB(L)
# (which doesn't quantize the same way — leaving raw for MicL is fine,
# the scorer should treat MicL specially).
out[ch].append(round(v * LSB_INV) if ch != "MicL" else v)
return out
def _compute_segment_sample_starts(
blocks: List[WaveformBlock], seg_idx: List[int]
) -> List[int]:
"""Cumulative sample-count up to each segment header (if all blocks treated
as Tran continuation). Useful as one candidate for segment-1-Tran tests.
The scorer should ALSO try "segment 1 starts at sample 0 of a new channel"
as the rotation hypothesis predicts.
"""
starts = []
cum = 2 # T[0] + T[1] from preamble
for i, b in enumerate(blocks):
if i in seg_idx:
starts.append(cum)
if b.tag_hi == 0x10:
cum += b.tag_lo
elif b.tag_hi == 0x20:
cum += b.tag_lo
elif b.tag_hi == 0x00:
cum += b.tag_lo
# 30 NN and 40 02 don't contribute samples (for this hypothesis)
return starts
# ── The core algorithm: decode a segment's blocks as deltas ─────────────────
def decode_segment_as_channel(
blocks: List[WaveformBlock],
seg_start_block_idx: int,
seg_end_block_idx: int,
anchor: int,
) -> List[int]:
"""Apply the segment-0 codec rules to a range of blocks, starting from *anchor*.
Returns a list of cumulative sample values (one per delta). Does NOT include
the anchor itself in the output — the first returned value is anchor + first_delta.
"""
out = []
cur = anchor
for bi in range(seg_start_block_idx, seg_end_block_idx):
blk = blocks[bi]
if blk.tag_hi == 0x10:
for byte in blk.data:
for nib in ((byte >> 4) & 0xF, byte & 0xF):
cur += s4(nib)
out.append(cur)
elif blk.tag_hi == 0x20:
for byte in blk.data:
cur += i8(byte)
out.append(cur)
elif blk.tag_hi == 0x00:
for _ in range(blk.tag_lo):
out.append(cur)
# 30 NN: skip (content unknown)
# 40 02: shouldn't appear in segment data (it's the segment header)
return out
def score_against_truth(
decoded: List[int],
truth: List[int],
truth_start: int,
) -> Tuple[int, int]:
"""Compare *decoded* to truth[truth_start : truth_start + len(decoded)].
Returns (n_matches, n_compared).
"""
n = min(len(decoded), len(truth) - truth_start)
if n <= 0:
return (0, 0)
matches = sum(1 for i in range(n) if decoded[i] == truth[truth_start + i])
return (matches, n)
# ── TODO for the next pass ──────────────────────────────────────────────────
def score_segment_against_all_channels(
event: FixtureEvent,
segment_index: int,
) -> List[Tuple[str, int, int, int]]:
"""For segment *segment_index* of *event*, find the best (channel, start_sample)
fit.
For each candidate channel C and each candidate starting truth-sample index s,
we pick the anchor that makes the FIRST decoded value match truth[C][s], then
score the remaining decoded values against truth[C][s+1 : s+N].
Returns rows of (channel_name, start_sample, n_matches, n_compared)
sorted by match-count descending.
"""
# Block range of this segment: from the segment header (inclusive) up to
# the next segment header (exclusive), or end-of-blocks.
seg_header_idx = event.segment_starts[segment_index]
next_header_idx = (
event.segment_starts[segment_index + 1]
if segment_index + 1 < len(event.segment_starts)
else len(event.blocks)
)
# Decode the segment's data blocks (skip the segment-header block itself).
# Use anchor=0 — we'll re-anchor when scoring against each channel.
deltas_trajectory = decode_segment_as_channel(
event.blocks, seg_header_idx + 1, next_header_idx, anchor=0
)
if not deltas_trajectory:
return []
n = len(deltas_trajectory)
results = []
for ch in ("Tran", "Vert", "Long"):
truth = event.truth.get(ch)
if not truth or len(truth) < n + 1:
continue
# For each candidate starting sample s in truth, check if applying
# the deltas starting from truth[s] reproduces truth[s+1:s+n+1].
best = (0, -1)
for s in range(len(truth) - n):
anchor = truth[s]
offset = anchor - deltas_trajectory[0] + truth[s + 1] - anchor
# Recompute: trajectory[i] = anchor + cumulative_delta_through_i
# but we already have deltas_trajectory computed from anchor=0,
# so trajectory_relative[i] = anchor + deltas_trajectory[i].
matches = 0
for i in range(n):
if truth[s + i + 1] == anchor + deltas_trajectory[i]:
matches += 1
# Note: we could break early on first mismatch for "matches start",
# but counting total matches gives a more robust score.
if matches > best[0]:
best = (matches, s)
results.append((ch, best[1], best[0], n))
results.sort(key=lambda r: -r[2])
return results
# ── Driver ──────────────────────────────────────────────────────────────────
def main():
"""Run the analyzer on all loud-bundle events and print best scores."""
events = ["M529LL1A.SP0", "M529LL1A.SS0", "M529LL1A.SV0",
"M529LL1L.JQ0", "M529LL1L.V70"]
for name in events:
try:
event = load_fixture(name)
except FileNotFoundError:
print(f"{name}: fixture not found")
continue
print(f"\n=== {name} ===")
print(f" body bytes: {len(event.body)}")
print(f" blocks: {len(event.blocks)}")
print(f" segments: {len(event.segment_starts)}")
print(f" segment sample-starts (if all blocks are 1 channel):")
for si, sample_start in enumerate(event.segment_sample_starts):
print(f" seg {si}: sample {sample_start}")
for si in range(len(event.segment_starts)):
results = score_segment_against_all_channels(event, si)
if not results:
print(f" seg {si}: (no scorable data)")
continue
tag = "✓" if results[0][2] / max(results[0][3], 1) > 0.9 else " "
top = results[0]
print(f" seg {si}: best fit {tag} = {top[0]:<5} "
f"starting at sample {top[1]:>5}, {top[2]:>4}/{top[3]:<4} match"
+ (f" (next: {results[1][0]} @{results[1][1]} {results[1][2]}/{results[1][3]})"
if len(results) > 1 else ""))
if __name__ == "__main__":
main()
scratch/nonmotion_scan.py
+91
View File
@@ -0,0 +1,91 @@
#!/usr/bin/env python3
"""Detect NON-MOTION on a geophone channel: |mean| / peak.
A geophone is a velocity sensor with no DC response, so its output over a
record must integrate to ~zero — the ground does not relocate. Real motion
therefore sits roughly half above and half below zero. Anything electrical —
a charge-injection spike, a step, a parked pedestal — is one-sided.
mp = |mean| / peak ~0 for motion, ~1 for a pedestal
frac_neg = share of samples < 0 ~0.3-0.5 for motion, ~0 for a fault
Why this beats the pre-trigger floor (`offset_scan3.py`): that detector's
`spread <= 0.02` gate rejects any record whose floor is MOVING, which is
exactly what an onset is — it discarded the one BE18438 record in which the
ramp was visible. This test is indifferent to whether the fault is a spike,
a ramp or a flat pedestal; none of them cross zero.
⚠ Not a rediscovery of the retracted v1 detector. v1 scored only the
largest-peak axis and used the mean as a BASELINE estimator, where the median
was required. Here the mean is the signal itself, per channel, and that is
what the physics licenses.
"""
from __future__ import annotations
import argparse, csv, re, statistics, sys
from concurrent.futures import ProcessPoolExecutor, as_completed
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from minimateplus.event_file_io import read_blastware_file
GEO=("Tran","Vert","Long"); K=10.0/32000.0
_WAVE=re.compile(r"\.[A-Za-z0-9]{2}0[Ww]$"); _STEM=re.compile(r"^([B-Z])(\d{3})")
_SER=re.compile(rb"[A-Z]{2}\d{3,6}")
def serial_of(name, path=None):
m=_STEM.match(name)
if not m: return "?"
num=(ord(m.group(1))-ord("B"))*1000+int(m.group(2))
if path is not None:
try:
for s in _SER.findall(Path(path).read_bytes()):
s=s.decode()
if s[2:].lstrip("0")==str(num): return s
except Exception: pass
return f"BE{num}"
def scan(ps):
import logging; logging.disable(logging.WARNING)
p=Path(ps)
try: ev=read_blastware_file(p)
except Exception: return None
s=ev.raw_samples or {}
if not all(s.get(c) for c in GEO): return None
ts=ev.timestamp
stamp=(f"{ts.year:04d}-{ts.month:02d}-{ts.day:02d}T"
f"{ts.hour:02d}:{ts.minute:02d}:{ts.second:02d}") if ts else ""
ser=serial_of(p.name,p); out=[]
for ch in GEO:
a=[x*K for x in s[ch]]
pk=max(abs(x) for x in a)
if pk<=0: continue
out.append({"serial":ser,"timestamp":stamp,"filename":p.name,"channel":ch,
"peak":round(pk,4),
"mean":round(statistics.fmean(a),4),
"mp":round(abs(statistics.fmean(a))/pk,4),
"frac_neg":round(sum(1 for x in a if x<0)/len(a),4),
"n":len(a)})
return out
COLS=["serial","timestamp","filename","channel","peak","mean","mp","frac_neg","n"]
def main():
ap=argparse.ArgumentParser()
ap.add_argument("--dir",required=True); ap.add_argument("--out",required=True)
ap.add_argument("--jobs",type=int,default=4)
a=ap.parse_args()
seen=set(); files=[]
for q in sorted(Path(a.dir).rglob("*")):
if q.is_file() and _WAVE.search(q.name) and q.name not in seen:
seen.add(q.name); files.append(str(q))
print(f"unique waveform binaries: {len(files)}",flush=True)
rows=[]
with ProcessPoolExecutor(max_workers=a.jobs) as ex:
for i,f in enumerate(as_completed([ex.submit(scan,p) for p in files]),1):
r=f.result()
if r: rows.extend(r)
if i%1000==0: print(f" {i}/{len(files)}",flush=True)
with open(a.out,"w",newline="") as fh:
w=csv.DictWriter(fh,fieldnames=COLS); w.writeheader(); w.writerows(rows)
print(f"\nwrote {a.out} ({len(rows)} channel-rows)")
if __name__=="__main__": main()
scratch/offset_candidates.csv
+275
View File
@@ -0,0 +1,275 @@
event_id,serial,timestamp,filename,channel,offset_ips,peak_ips,mean_over_peak,trigger_level_ips,already_flagged_ft
1e7a7808-034c-423b-80e9-d6788da80993,BE18438,2025-11-15T08:57:40,T438LBX4.W40W,Vert,0.2722,0.2930,0.929,0.2,0
346e383f-c5a1-41d1-b972-3d652e599d39,BE18438,2025-11-15T09:13:15,T438LBX5.M30W,Vert,0.2747,0.2930,0.938,0.2,0
45ef3023-22c5-44a8-a606-a0900bc17861,BE18438,2025-11-15T09:16:13,T438LBX5.R10W,Vert,0.2929,0.3027,0.967,0.2,0
1cbcd2aa-ec55-4e2f-af42-7178f26cc6a1,BE18438,2025-11-15T09:19:29,T438LBX5.WH0W,Vert,0.2816,0.2979,0.945,0.2,0
caf43634-4528-4fd5-9674-5f4f563661c0,BE18438,2025-11-15T09:22:32,T438LBX6.1K0W,Vert,0.2883,0.2930,0.984,0.2,0
456ae646-c834-4e5c-82f1-7df18b3440a1,BE18438,2025-11-15T09:25:31,T438LBX6.6J0W,Vert,0.3189,0.3223,0.989,0.2,0
afb91ba2-351b-42a0-b33f-acebd5f1829d,BE18438,2025-11-15T09:28:29,T438LBX6.BH0W,Vert,0.3057,0.3076,0.994,0.2,0
39847146-3537-4300-943d-01c0c771e9cd,BE18438,2025-11-15T09:31:26,T438LBX6.GE0W,Vert,0.3225,0.3271,0.986,0.2,0
e47335c1-fc3f-4c90-88c6-8edd0f296ce4,BE18438,2025-11-15T09:34:24,T438LBX6.LC0W,Vert,0.3275,0.3320,0.986,0.2,0
25b6eda6-ba98-422f-8834-94b6cbe34971,BE18438,2025-11-15T09:37:22,T438LBX6.QA0W,Vert,0.3398,0.3418,0.994,0.2,0
7af99377-e47f-4914-8e91-ac7f7f50b8c6,BE18438,2025-11-15T09:40:20,T438LBX6.V80W,Vert,0.3515,0.3564,0.986,0.2,0
c4330605-c257-49ef-aede-20deb641e7d7,BE18438,2025-11-15T10:09:48,T438LBX8.8C0W,Vert,0.3605,0.3955,0.912,0.2,0
b665caf9-64ee-4352-a391-60c1ddeebc1e,BE18438,2026-02-25T10:58:04,T438LH66.GS0W,Vert,0.1803,0.1953,0.923,0.2,0
3b0c32c3-fd16-4b83-9917-942a56dea168,BE18438,2026-02-25T18:12:04,T438LH6Q.K40W,Vert,0.1869,0.1953,0.957,0.2,0
ca66e601-d10f-4424-9c26-08a688e7b08c,BE18438,2026-02-25T18:17:16,T438LH6Q.SS0W,Vert,0.1870,0.1953,0.958,0.2,0
31aa30ba-eb0a-49a9-98ca-c77d2cc31275,BE18438,2026-02-25T18:21:11,T438LH6Q.ZB0W,Vert,0.1868,0.1953,0.956,0.2,0
fdb55a93-fc91-4fdf-a7f4-fdd1a6b48f59,BE18438,2026-02-25T18:26:27,T438LH6R.830W,Vert,0.1893,0.1953,0.969,0.2,0
cbd718d7-2378-4d74-8656-842f229d19a8,BE18438,2026-02-25T18:33:25,T438LH6R.JP0W,Vert,0.1887,0.1953,0.966,0.2,0
bfaf58ec-6163-47eb-9d2a-70da880bd948,BE18438,2026-02-25T18:37:48,T438LH6R.R00W,Vert,0.1872,0.1953,0.959,0.2,0
ddaa530b-886e-4415-b93a-f4ebf4c4a882,BE18438,2026-02-25T18:59:54,T438LH6S.RU0W,Vert,0.1874,0.1953,0.959,0.2,0
57f15284-ab69-48fc-9660-8c347c80c681,BE18438,2026-02-25T19:15:58,T438LH6T.IM0W,Vert,0.1873,0.1953,0.959,0.2,0
03715718-7aa8-4e1d-9b0b-c2ab75fc1975,BE18438,2026-02-25T19:19:58,T438LH6T.PA0W,Vert,0.1891,0.1953,0.968,0.2,0
9f921cd5-1bf9-4713-aef6-41e7f780eff1,BE18438,2026-02-25T19:24:02,T438LH6T.W20W,Vert,0.1871,0.1953,0.958,0.2,0
44994949-58d4-44fa-bd78-ed75b8acc667,BE18438,2026-02-25T19:44:57,T438LH6U.UX0W,Vert,0.1877,0.1953,0.961,0.2,0
c4be01c3-1001-4e17-aecd-d6d26dbb09f3,BE18438,2026-02-25T19:49:19,T438LH6V.270W,Vert,0.1884,0.1953,0.964,0.2,0
3db004e6-ee34-43c5-ae8e-f22894ead5d0,BE18438,2026-02-25T20:08:22,T438LH6V.XY0W,Vert,0.1878,0.1953,0.962,0.2,0
d276ae48-0434-41e5-af43-e0fb366acf11,BE18438,2026-02-25T20:11:33,T438LH6W.390W,Vert,0.1880,0.1953,0.963,0.2,0
c027dc12-88fd-4a45-872b-a6a945f2008e,BE18438,2026-02-25T20:14:35,T438LH6W.8B0W,Vert,0.1874,0.1953,0.959,0.2,0
9665bc3a-3d08-4852-b008-37ef8bfd0023,BE18438,2026-02-25T20:18:51,T438LH6W.FF0W,Vert,0.1884,0.1953,0.965,0.2,0
5fb5a05e-d7e2-4268-9b85-cfe8d82aa6c9,BE18438,2026-02-25T20:29:50,T438LH6W.XQ0W,Vert,0.1890,0.1953,0.968,0.2,0
57ec0b10-9324-4459-a07e-0c8532b8928f,BE18438,2026-02-25T20:35:39,T438LH6X.7F0W,Vert,0.1889,0.1953,0.967,0.2,0
ac86f73f-1174-4fae-a206-ecdcb73e1ffc,BE18438,2026-02-25T20:39:12,T438LH6X.DC0W,Vert,0.1887,0.1953,0.966,0.2,0
dcf25ddd-9cf0-41c1-b109-f3ef2e490ce5,BE18438,2026-02-25T20:43:41,T438LH6X.KT0W,Vert,0.1871,0.1953,0.958,0.2,0
aa79bbdd-2392-4ef6-8a5c-873a9f72746d,BE18438,2026-02-25T20:46:51,T438LH6X.Q30W,Vert,0.1877,0.1953,0.961,0.2,0
ad46d1ce-b417-4c8c-b029-bb3b008ba809,BE18438,2026-02-25T20:53:33,T438LH6Y.190W,Vert,0.1882,0.1953,0.964,0.2,0
3d3a8f34-86a7-4d70-a7e8-fa768a723325,BE18438,2026-02-26T07:03:39,T438LH7Q.A30W,Vert,0.1809,0.1953,0.926,0.2,0
7817525f-dc3d-4f5e-b2cb-5af9ca12ede8,BE18438,2026-02-26T07:09:42,T438LH7Q.K60W,Vert,0.1814,0.1953,0.929,0.2,0
a2091302-0b34-46c1-ab83-174be2b59bcf,BE18438,2026-02-26T13:12:35,T438LH87.CZ0W,Vert,0.1896,0.1953,0.971,0.2,0
e1c0c9de-a900-479f-9572-9675b13296a9,BE18438,2026-02-26T13:24:46,T438LH87.XA0W,Vert,0.2237,0.2588,0.864,0.2,0
76a6dc6b-88e1-434b-a137-f5e9b63f248e,BE18438,2026-02-26T13:27:43,T438LH88.270W,Vert,0.3185,0.3223,0.988,0.2,0
281b508b-7982-4668-86af-9b0b28be608a,BE18438,2026-02-26T13:30:36,T438LH88.700W,Vert,0.3263,0.3320,0.983,0.2,0
68bbaf77-bb23-40fd-94f9-f928728d90dc,BE18438,2026-02-26T13:33:28,T438LH88.BS0W,Vert,0.3207,0.3271,0.980,0.2,0
5c975640-6ff1-441a-aa11-41642f6a6b31,BE18438,2026-02-26T13:36:21,T438LH88.GL0W,Vert,0.3261,0.3320,0.982,0.2,0
dea248ac-1124-4bba-b054-953f86c852b2,BE18438,2026-02-26T13:40:34,T438LH88.NM0W,Vert,0.3271,0.3320,0.985,0.2,0
4e463201-f008-41ad-9c52-11fcc3d93095,BE18438,2026-02-26T13:43:29,T438LH88.SH0W,Vert,0.3357,0.3418,0.982,0.2,0
507262c5-d58f-4a05-a6a3-a6cbb5b4de20,BE18438,2026-02-26T13:46:24,T438LH88.XC0W,Vert,0.3372,0.3418,0.987,0.2,0
4c2d8ee8-842f-4e44-9e03-ff34d26e4fdb,BE18438,2026-02-26T13:49:17,T438LH89.250W,Vert,0.3253,0.3320,0.980,0.2,0
b184b112-603f-44f4-ae97-087493fbd8ce,BE18438,2026-02-26T13:52:10,T438LH89.6Y0W,Vert,0.3321,0.3369,0.986,0.2,0
2ff1a552-5a2e-4396-9083-b9c8d334eed7,BE18438,2026-02-26T13:55:04,T438LH89.BS0W,Vert,0.3378,0.3418,0.988,0.2,0
928e21a7-1990-4792-803e-58014d8140ce,BE18438,2026-02-26T13:57:57,T438LH89.GL0W,Vert,0.3341,0.3369,0.992,0.2,0
f521b5db-6100-41e6-954e-0abdbf9660c1,BE18438,2026-02-26T14:00:51,T438LH89.LF0W,Vert,0.3421,0.3467,0.987,0.2,0
efba962f-e511-41ef-9fc5-313f202a9d96,BE18438,2026-02-26T14:03:46,T438LH89.QA0W,Vert,0.3506,0.3564,0.984,0.2,0
0b51e273-8d10-4494-bda6-8c75eaeec66f,BE18438,2026-02-26T14:06:41,T438LH89.V50W,Vert,0.3448,0.3516,0.981,0.2,0
6d46e4ee-1647-4169-b6b2-33da32240eb9,BE18438,2026-02-26T14:09:35,T438LH89.ZZ0W,Vert,0.3463,0.3516,0.985,0.2,0
1ca294cd-4dc2-41fb-9374-e277d4550761,BE18438,2026-02-26T14:12:28,T438LH8A.4S0W,Vert,0.3442,0.3467,0.993,0.2,0
7b683dcf-1aed-4d9b-be1e-b10f92374398,BE18438,2026-02-26T14:15:23,T438LH8A.9N0W,Vert,0.3486,0.3516,0.992,0.2,0
2b5cb8e7-c947-4914-bcb5-504f74603547,BE18438,2026-02-26T14:18:21,T438LH8A.EL0W,Vert,0.3519,0.3613,0.974,0.2,0
5ea3a6bf-10de-4911-aedc-66daecf86b76,BE18438,2026-02-26T14:21:16,T438LH8A.JG0W,Vert,0.3460,0.3564,0.971,0.2,0
d93be7f5-39ec-45fd-9949-fa531f2f9d34,BE18438,2026-02-26T14:24:13,T438LH8A.OD0W,Vert,0.3457,0.3516,0.983,0.2,0
cfa113f2-8cee-4a1d-b1e7-0e936fa771e2,BE18438,2026-02-26T14:28:21,T438LH8A.V90W,Vert,0.3485,0.3564,0.978,0.2,0
46d322ac-38cb-4c99-a4c2-9e9d7ad06171,BE18438,2026-02-26T14:31:17,T438LH8B.050W,Vert,0.3367,0.3467,0.971,0.2,0
42500a83-bd67-4deb-8bb2-963ee2b8a7ce,BE18438,2026-02-26T14:34:11,T438LH8B.4Z0W,Vert,0.3365,0.3516,0.957,0.2,0
3ccf6bda-2e88-473c-951d-9ea86d0d9363,BE18438,2026-02-26T14:37:05,T438LH8B.9T0W,Vert,0.3472,0.3564,0.974,0.2,0
9050487d-d238-4631-b8e1-5a693a026542,BE18438,2026-02-26T14:39:58,T438LH8B.EM0W,Vert,0.3420,0.3564,0.959,0.2,0
e62989e4-a326-4bae-8d47-a8becee96462,BE18438,2026-02-26T14:42:52,T438LH8B.JG0W,Vert,0.3430,0.3564,0.962,0.2,0
f0e30fab-dc57-4189-8439-48df17007a2c,BE18438,2026-02-26T14:45:46,T438LH8B.OA0W,Vert,0.3389,0.3516,0.964,0.2,0
03e1ca09-78df-4c6f-9915-0b6e4f2141d2,BE18438,2026-02-26T14:48:43,T438LH8B.T70W,Vert,0.3449,0.3564,0.968,0.2,0
945d39f7-1b98-4a1f-80a8-6a18fd9df25f,BE18438,2026-02-26T14:51:37,T438LH8B.Y10W,Vert,0.3522,0.3613,0.975,0.2,0
d27eb2e3-e313-4125-98f4-f9d6d3737d28,BE18438,2026-02-26T14:54:32,T438LH8C.2W0W,Vert,0.3502,0.3613,0.969,0.2,0
916901cb-ebea-441e-a2a1-40f4e49f32f4,BE18438,2026-02-26T14:57:25,T438LH8C.7P0W,Vert,0.3524,0.3662,0.962,0.2,0
5d8d7e29-fdbb-4fa3-bd25-506c9352a354,BE18438,2026-02-26T15:01:35,T438LH8C.EN0W,Vert,0.3530,0.3613,0.977,0.2,0
c6c7a3af-b03b-43dc-97de-024f8e09b62f,BE18438,2026-02-26T15:04:27,T438LH8C.JF0W,Vert,0.3514,0.3613,0.973,0.2,0
b6856898-3d10-4967-9577-7f17902f77ea,BE18438,2026-02-26T15:11:34,T438LH8C.VA0W,Vert,0.3566,0.3613,0.987,0.2,0
7a4802f6-621e-4230-8d8c-d7f0c9a65bf2,BE18438,2026-02-26T15:14:24,T438LH8D.000W,Vert,0.3594,0.3711,0.968,0.2,0
79f38b7e-ec56-417e-943a-8c944252c2b8,BE18438,2026-02-26T15:18:32,T438LH8D.6W0W,Vert,0.3550,0.3613,0.983,0.2,0
1b4190c4-0d54-48ba-8ff5-8ddb0eb91e50,BE18438,2026-02-26T15:22:22,T438LH8D.DA0W,Vert,0.3571,0.3613,0.988,0.2,0
de57b5ae-a3a1-4ede-9d2b-3e87bfb3fd19,BE9558,2026-04-14T11:16:32,K558LJN3.BK0W,Tran,0.3448,0.3662,0.942,0.2,0
43afeaf5-02ec-41f6-9e23-0c9772821ed4,BE9558,2026-04-14T11:27:15,K558LJN3.TF0W,Tran,0.3094,0.3223,0.960,0.2,0
8123c0ef-84c9-4f6c-8d82-9dc32e2e470d,BE9558,2026-04-14T14:45:30,K558LJNC.ZU0W,Tran,0.2721,0.3564,0.763,0.2,0
8c787af3-596e-411b-9e10-29485fa5114f,BE9558,2026-04-29T16:18:47,K558LKF9.BB0W,Tran,0.2943,0.3027,0.972,0.2,0
431928ff-b4c4-4caa-b933-acc917f3717c,BE9558,2026-05-04T15:02:30,K558LKOF.460W,Tran,0.4364,0.5225,0.835,0.2,0
6c3c07f8-c36a-4493-acce-7441c9d22cec,BE9558,2026-05-15T08:50:06,K558LL8B.7I0W,Long,0.2892,0.2930,0.987,0.2,0
13c268df-b652-422e-a642-6453f6a314aa,BE9558,2026-05-15T10:18:34,K558LL8F.AY0W,Long,0.2907,0.2979,0.976,0.2,0
9b0d0871-8810-467d-806a-5bbfa4e667fe,BE9558,2026-05-15T15:52:00,K558LL8U.QO0W,Long,0.2659,0.2979,0.893,0.2,0
092640f9-a944-48b7-b872-364d75c2c5e7,BE9558,2026-05-15T16:13:12,K558LL8V.Q00W,Long,0.2428,0.2979,0.815,0.2,0
0573741a-96ab-4b36-af7a-b5bc11a79009,BE9558,2026-05-16T03:23:26,K558LL9Q.R20W,Long,0.2861,0.2930,0.976,0.2,0
321f03ea-6696-47de-ad46-2be43d4d6cae,BE9558,2026-05-16T03:30:49,K558LL9R.3D0W,Long,0.2886,0.2930,0.985,0.2,0
cc423a6a-3e3c-466a-b39c-6146ca7f34c8,BE9558,2026-05-16T03:33:55,K558LL9R.8J0W,Long,0.2880,0.2881,1.000,0.2,0
efa52a14-cc68-4bea-aab4-4ee3a3cbff3a,BE9558,2026-05-16T03:36:55,K558LL9R.DJ0W,Long,0.2890,0.2930,0.986,0.2,0
92895bfe-122f-4cdc-bd3d-40609633d278,BE9558,2026-05-16T03:43:41,K558LL9R.OT0W,Long,0.2880,0.2881,1.000,0.2,0
2a4c81db-2307-44e5-9b27-d5154d98e38d,BE9558,2026-05-16T03:46:36,K558LL9R.TO0W,Long,0.2921,0.2979,0.981,0.2,0
656b0fdc-e275-4c9c-8936-9eee267ea04e,BE9558,2026-05-16T03:49:28,K558LL9R.YG0W,Long,0.2966,0.2979,0.996,0.2,0
3b9989ae-e0f2-4652-9724-c145603543d2,BE9558,2026-05-16T03:52:29,K558LL9S.3H0W,Long,0.2880,0.2930,0.983,0.2,0
837d0d84-d609-4f4a-b542-b7e2b064ea22,BE9558,2026-05-16T03:56:32,K558LL9S.A80W,Long,0.2880,0.2930,0.983,0.2,0
affcb008-ab99-4bc5-8f35-83dbe620499d,BE9558,2026-05-16T04:02:50,K558LL9S.KQ0W,Long,0.2896,0.2930,0.989,0.2,0
e1f1c6d2-545c-451f-9018-714d52e20a05,BE9558,2026-05-16T04:05:47,K558LL9S.PN0W,Long,0.3024,0.3076,0.983,0.2,0
93ef80f1-7e83-4703-a0f9-89bbfeeae6c3,BE9558,2026-05-16T04:08:41,K558LL9S.UH0W,Long,0.2976,0.2979,0.999,0.2,0
5c118ca9-fc37-4080-876d-b3f57ce0b121,BE9558,2026-05-16T04:11:42,K558LL9S.ZI0W,Long,0.2881,0.2930,0.983,0.2,0
d98b2eaa-7763-4c78-88fb-c21195cb9978,BE9558,2026-05-16T04:14:38,K558LL9T.4E0W,Long,0.2898,0.2930,0.989,0.2,0
6a146a01-0d02-4413-b231-ecb4a6fde776,BE9558,2026-05-16T04:17:35,K558LL9T.9B0W,Long,0.2880,0.2930,0.983,0.2,0
f6587a55-27e3-454f-997e-57e7516a296c,BE9558,2026-05-16T04:20:32,K558LL9T.E80W,Long,0.3046,0.3076,0.990,0.2,0
1fb48250-2214-41e6-92cb-362aff1ba62b,BE9558,2026-05-16T04:26:05,K558LL9T.NH0W,Long,0.2876,0.2930,0.982,0.2,0
2f4f3d06-1189-4e28-a1ac-5454ea586a0c,BE9558,2026-05-16T04:59:47,K558LL9V.7N0W,Long,0.2961,0.3027,0.978,0.2,0
62b7bdab-b744-41e4-8d0e-c9141b9d4821,BE9558,2026-05-16T05:02:46,K558LL9V.CM0W,Long,0.2903,0.2930,0.991,0.2,0
cadcb6dc-74c0-48b5-974c-87bb7a57816c,BE9558,2026-05-16T05:05:43,K558LL9V.HJ0W,Long,0.3090,0.3125,0.989,0.2,0
a0235177-be5a-4f11-b741-c65744698e5b,BE9558,2026-05-16T05:08:35,K558LL9V.MB0W,Long,0.3167,0.3223,0.983,0.2,0
1968c2f6-f52c-4544-a0ed-f79b91ce0da0,BE9558,2026-05-16T05:11:28,K558LL9V.R40W,Long,0.3446,0.3516,0.980,0.2,0
caa06b94-8813-4949-b47b-61ffb16e61c4,BE9558,2026-05-16T05:14:22,K558LL9V.VY0W,Long,0.3318,0.3320,0.999,0.2,0
fdaa8101-f033-47e6-9c65-abd76dea1870,BE9558,2026-05-16T05:17:16,K558LL9W.0S0W,Long,0.3407,0.3418,0.997,0.2,0
29bd16bd-81b9-4ccd-a981-f1a80858536c,BE9558,2026-05-16T05:23:05,K558LL9W.AH0W,Long,0.3450,0.3516,0.981,0.2,0
1f8bc862-d5fd-4cce-abc0-e2bd8c2f11fa,BE9558,2026-05-16T05:26:00,K558LL9W.FC0W,Long,0.3417,0.3467,0.986,0.2,0
20220068-d498-4fca-9a2a-a7fd2ee52ab1,BE9558,2026-05-16T05:28:53,K558LL9W.K50W,Long,0.3516,0.3564,0.986,0.2,0
9816a261-3118-417a-8334-ace36687ad8f,BE9558,2026-05-16T05:31:47,K558LL9W.OZ0W,Long,0.3416,0.3467,0.985,0.2,0
5d2c76d7-543d-4557-9caf-996a69ab00bd,BE9558,2026-05-16T05:34:42,K558LL9W.TU0W,Long,0.3537,0.3564,0.992,0.2,0
c7b5ae00-52e7-4920-aa27-49d3b3daff92,BE9558,2026-05-16T05:37:36,K558LL9W.YO0W,Long,0.3517,0.3564,0.987,0.2,0
07db8fd8-ccef-4a5a-9d97-9f318f73a478,BE9558,2026-05-16T05:40:31,K558LL9X.3J0W,Long,0.3574,0.3613,0.989,0.2,0
790fcff9-e266-4a12-87f0-a072990d2533,BE9558,2026-05-16T05:43:26,K558LL9X.8E0W,Long,0.3650,0.3662,0.997,0.2,0
f4245f61-1dde-43dc-a121-98e102f6a193,BE9558,2026-05-16T05:50:28,K558LL9X.K40W,Long,0.3856,0.3906,0.987,0.2,0
5a3bce7b-358e-4260-876f-3f853163d7cf,BE9558,2026-05-16T05:53:22,K558LL9X.OY0W,Long,0.3847,0.3857,0.997,0.2,0
37c2b4b1-7a1b-43e7-b513-2c16f582109c,BE9558,2026-05-16T05:56:15,K558LL9X.TR0W,Long,0.3906,0.3955,0.988,0.2,0
57fde109-1d8a-45a1-b398-5bd28c3e47f1,BE9558,2026-05-16T05:59:10,K558LL9X.YM0W,Long,0.4000,0.4004,0.999,0.2,0
1e41ab40-93be-405c-a464-f7a57524d3b3,BE9558,2026-05-16T06:02:02,K558LL9Y.3E0W,Long,0.3825,0.3857,0.992,0.2,0
e9d61eb5-fae8-4902-8fab-4828ffa8e6da,BE9558,2026-05-16T06:04:57,K558LL9Y.890W,Long,0.3802,0.3809,0.998,0.2,0
c0e964e0-7788-4e41-bc41-6e479c3dc81b,BE9558,2026-05-16T06:07:51,K558LL9Y.D30W,Long,0.3954,0.4004,0.987,0.2,0
0b2df8e5-1689-4fe6-abad-30970ba10aa6,BE9558,2026-05-16T06:16:06,K558LL9Y.QU0W,Long,0.4051,0.4053,1.000,0.2,0
2bc6ce73-464b-469c-9e8f-3bf6f6cfae1d,BE9558,2026-05-16T06:21:51,K558LL9Z.0F0W,Long,0.3910,0.3955,0.989,0.2,0
b8603ee1-616a-451e-a2cd-61f8f2634cd0,BE9558,2026-05-16T06:24:44,K558LL9Z.580W,Long,0.3969,0.4004,0.991,0.2,0
1aecf582-66a2-4ebb-80f9-04b3aeba331a,BE9558,2026-05-16T06:27:39,K558LL9Z.A30W,Long,0.3915,0.3955,0.990,0.2,0
885aedfd-7a1a-4120-8176-7c344dd3d8fe,BE9558,2026-05-16T06:30:30,K558LL9Z.EU0W,Long,0.4025,0.4053,0.993,0.2,0
ec15930f-47f5-4752-afc2-427ee156ac95,BE9558,2026-05-16T06:33:25,K558LL9Z.JP0W,Long,0.4060,0.4102,0.990,0.2,0
5ca23f47-2a38-4a54-99dd-041287aa9510,BE9558,2026-05-16T06:36:17,K558LL9Z.OH0W,Long,0.4054,0.4102,0.988,0.2,0
03f371cf-81bc-4681-80f0-ef6fa437da85,BE9558,2026-05-16T06:39:09,K558LL9Z.T90W,Long,0.4052,0.4102,0.988,0.2,0
ed386f54-140d-45e8-ad51-6585a58b4375,BE9558,2026-05-16T06:44:54,K558LLA0.2U0W,Long,0.3993,0.4004,0.997,0.2,0
579f1c3f-4c1e-42a3-aa89-69aa93514033,BE9558,2026-05-16T06:47:47,K558LLA0.7N0W,Long,0.4001,0.4053,0.987,0.2,0
57024de6-07ea-41f4-b916-c6adc3f51636,BE9558,2026-05-16T06:50:40,K558LLA0.CG0W,Long,0.4103,0.4150,0.989,0.2,0
36bf5adf-afb5-4a5e-a106-1afbd1f56c7b,BE9558,2026-05-16T06:54:49,K558LLA0.JD0W,Long,0.4069,0.4150,0.980,0.2,0
3e2f831b-5228-46ff-9acb-75d8c86f8bc1,BE9558,2026-05-16T06:57:43,K558LLA0.O70W,Long,0.4108,0.4150,0.990,0.2,0
1775fa20-568b-4294-b9ca-561201a66c5b,BE9558,2026-05-16T07:00:38,K558LLA0.T20W,Long,0.3967,0.4004,0.991,0.2,0
fd391469-03f9-4d8d-bccd-3af50c91e5b7,BE9558,2026-05-16T07:03:33,K558LLA0.XX0W,Long,0.3927,0.3955,0.993,0.2,0
02b52ef6-b707-4dcb-b58f-43da02698832,BE9558,2026-05-16T07:06:27,K558LLA1.2R0W,Long,0.3824,0.3857,0.991,0.2,0
8d45333f-e101-4249-9e27-913c583a0a8d,BE9558,2026-05-16T07:09:21,K558LLA1.7L0W,Long,0.4085,0.4150,0.984,0.2,0
361d11ce-f42a-4d04-8270-ee3771fe4f09,BE9558,2026-05-16T07:12:14,K558LLA1.CE0W,Long,0.4017,0.4053,0.991,0.2,0
59218125-ed5d-4457-aa8b-35ba03441363,BE9558,2026-05-16T07:15:07,K558LLA1.H70W,Long,0.3934,0.3955,0.995,0.2,0
a603e55a-2ad6-4fc9-8c8c-0dc7be95c3e7,BE9558,2026-05-16T07:23:43,K558LLA1.VJ0W,Long,0.3806,0.3857,0.987,0.2,0
c8d07902-93ea-4b03-9e69-9ad6ed5bffb1,BE9558,2026-05-16T07:26:36,K558LLA2.0C0W,Long,0.3807,0.3857,0.987,0.2,0
4c46c0c7-42f0-4648-827e-1995f733b18f,BE9558,2026-05-16T07:30:44,K558LLA2.780W,Long,0.3667,0.3711,0.988,0.2,0
04759a00-ba3e-4959-a4cb-be8fc1f3004e,BE9558,2026-05-16T07:36:28,K558LLA2.GS0W,Long,0.3514,0.3516,1.000,0.2,0
0b6b0856-bd87-4a07-a5b4-f13d99e04a12,BE9558,2026-05-16T07:39:20,K558LLA2.LK0W,Long,0.3512,0.3516,0.999,0.2,0
3d81a8bd-464d-4050-8a76-25e8373d1ddb,BE9558,2026-05-16T07:42:12,K558LLA2.QC0W,Long,0.3350,0.3369,0.994,0.2,0
b8b9c0c4-c388-4acb-955a-be4ac356afce,BE9558,2026-05-16T07:45:04,K558LLA2.V40W,Long,0.3563,0.3564,1.000,0.2,0
cb3d142a-fb84-4a21-a298-f61bb869b036,BE9558,2026-05-16T07:49:13,K558LLA3.210W,Long,0.3663,0.3711,0.987,0.2,0
7401b19b-bc9d-43f0-b395-f4323aca5c72,BE9558,2026-05-16T07:52:06,K558LLA3.6U0W,Long,0.3612,0.3662,0.986,0.2,0
2236df76-a9e6-401f-9176-ad565242f2cf,BE9558,2026-05-16T07:57:52,K558LLA3.GG0W,Long,0.3366,0.3369,0.999,0.2,0
a645846c-cae4-4aa5-a2e6-85166bd4dd62,BE9558,2026-05-16T08:00:44,K558LLA3.L80W,Long,0.3265,0.3271,0.998,0.2,0
7212bd33-99a9-4659-9f0b-c98cc8d1e8bc,BE9558,2026-05-16T08:04:51,K558LLA3.S30W,Long,0.3418,0.3467,0.986,0.2,0
2cc4bf33-c63a-4c65-b0e2-5e61a9146a5d,BE9558,2026-05-16T08:07:43,K558LLA3.WV0W,Long,0.3405,0.3418,0.996,0.2,0
4fedb486-5f1f-4623-a01f-083e829f0565,BE9558,2026-05-16T08:10:35,K558LLA4.1N0W,Long,0.3515,0.3564,0.986,0.2,0
58aff0ba-0f9b-45e1-9bbe-a990d16192ae,BE9558,2026-05-16T08:13:27,K558LLA4.6F0W,Long,0.3513,0.3516,0.999,0.2,0
e56d87e5-e1d4-4947-b6a5-3bbd2773c54a,BE9558,2026-05-16T08:20:03,K558LLA4.HF0W,Long,0.3564,0.3613,0.986,0.2,0
0e96e61e-6a21-4e07-8e09-72d09dbfa1e6,BE9558,2026-05-16T08:25:21,K558LLA4.Q90W,Long,0.3565,0.3613,0.987,0.2,0
19611f28-2da8-4362-a58e-dbed2e061379,BE9558,2026-05-16T08:34:19,K558LLA5.570W,Long,0.3647,0.3662,0.996,0.2,0
bd580c1d-44d4-41fd-9f83-f462cda4099a,BE9558,2026-05-16T08:37:15,K558LLA5.A30W,Long,0.3536,0.3564,0.992,0.2,0
2782df3b-3cb4-471a-a6f5-bbc4903a8ab9,BE9558,2026-05-16T08:44:00,K558LLA5.LC0W,Long,0.3612,0.3662,0.986,0.2,0
d15a08f3-1c7c-4f80-8d9b-f5008c58c3d9,BE9558,2026-05-16T08:49:18,K558LLA5.U60W,Long,0.3610,0.3613,0.999,0.2,0
03a10a6a-193a-476c-9543-f63818f69417,BE9558,2026-05-16T08:54:36,K558LLA6.300W,Long,0.3515,0.3516,1.000,0.2,0
1c271856-8100-4c0d-bc8c-9357b47d7626,BE9558,2026-05-16T08:59:54,K558LLA6.BU0W,Long,0.3617,0.3662,0.988,0.2,0
a85f125e-bfa2-42be-b877-2604b8d068c8,BE9558,2026-05-16T09:05:17,K558LLA6.KT0W,Long,0.3510,0.3516,0.998,0.2,0
dde9aa71-d2e3-41ac-8388-f2bbddb6dae6,BE9558,2026-05-16T09:08:11,K558LLA6.PN0W,Long,0.3447,0.3467,0.994,0.2,0
2f3f2be2-0ee3-422e-b3ad-83fb87512a2b,BE9558,2026-05-16T09:14:39,K558LLA7.0F0W,Long,0.3580,0.3613,0.991,0.2,0
357a3034-8a9c-485e-8cb6-f526dd2baf6f,BE9558,2026-05-16T09:29:11,K558LLA7.ON0W,Long,0.3708,0.3760,0.986,0.2,0
f8ad0274-8e6f-4714-82ff-d229e60f1442,BE9558,2026-05-16T09:32:06,K558LLA7.TI0W,Long,0.3567,0.3613,0.987,0.2,0
42bb007a-2726-401a-b085-c25151b0dc24,BE9558,2026-05-16T09:35:02,K558LLA7.YE0W,Long,0.3575,0.3613,0.989,0.2,0
c99bfc4a-db02-4bea-bea4-943c67485dba,BE9558,2026-05-16T09:37:58,K558LLA8.3A0W,Long,0.3527,0.3564,0.989,0.2,0
8fc17de0-73f7-48bd-8d93-5451dce47e8e,BE9558,2026-05-16T09:40:52,K558LLA8.840W,Long,0.3613,0.3662,0.987,0.2,0
bbee5276-03dd-4ca4-a7b9-aec02baac7e8,BE9558,2026-05-16T09:48:13,K558LLA8.KD0W,Long,0.3590,0.3613,0.993,0.2,0
8dcdee10-db01-4224-9506-4181c3105d6f,BE9558,2026-05-16T09:53:31,K558LLA8.T70W,Long,0.3588,0.3613,0.993,0.2,0
48c8be72-64d9-4da3-95b5-bbec2c5e1dbd,BE9558,2026-05-16T09:58:49,K558LLA9.210W,Long,0.3582,0.3662,0.978,0.2,0
0da20919-7ce9-4feb-8ae9-12d9bb40c2b5,BE9558,2026-05-16T10:04:07,K558LLA9.AV0W,Long,0.3506,0.3516,0.997,0.2,0
c2f7e9bc-8b93-42c3-96d3-e3af217dde35,BE9558,2026-05-16T10:09:25,K558LLA9.JP0W,Long,0.3506,0.3516,0.997,0.2,0
522a0e42-d443-4447-bc71-af1832c6604e,BE9558,2026-05-16T10:14:43,K558LLA9.SJ0W,Long,0.3624,0.3662,0.990,0.2,0
67f7e732-3c0b-439f-87c5-3c478a381418,BE9558,2026-05-16T10:20:01,K558LLAA.1D0W,Long,0.3494,0.3516,0.994,0.2,0
251767e8-56f7-4091-a001-364d8e75c15c,BE9558,2026-05-16T10:25:19,K558LLAA.A70W,Long,0.3463,0.3516,0.985,0.2,0
9457239d-a4ca-4476-b385-5e01fc8f6420,BE9558,2026-05-16T10:30:37,K558LLAA.J10W,Long,0.3436,0.3467,0.991,0.2,0
43718d7c-9353-49e1-89b6-0841aeb1b276,BE9558,2026-05-16T10:35:55,K558LLAA.RV0W,Long,0.3452,0.3516,0.982,0.2,0
f54ba557-ddfe-41d3-8f4c-8bbec9a3783c,BE9558,2026-05-16T10:41:13,K558LLAB.0P0W,Long,0.3419,0.3467,0.986,0.2,0
dc26c758-ad99-49c1-b518-931368cdf8cf,BE9558,2026-05-16T10:46:31,K558LLAB.9J0W,Long,0.3463,0.3516,0.985,0.2,0
10917eb2-d151-461c-a8cb-e9660da5a5b0,BE9558,2026-05-16T10:51:49,K558LLAB.ID0W,Long,0.3520,0.3564,0.987,0.2,0
4938a5e6-d53b-40ee-be2b-06ec0e60398c,BE9558,2026-05-16T10:57:07,K558LLAB.R70W,Long,0.3541,0.3564,0.993,0.2,0
0711b51d-55bd-48be-b51e-2aad67107a60,BE9558,2026-05-16T11:13:01,K558LLAC.HP0W,Long,0.3661,0.3711,0.986,0.2,0
065564b6-aa49-40e7-9ea6-c75defdc60fe,BE9558,2026-05-16T11:18:19,K558LLAC.QJ0W,Long,0.3622,0.3662,0.989,0.2,0
ffb6b230-1d70-4e0e-ba30-e945339a122a,BE9558,2026-05-16T11:23:37,K558LLAC.ZD0W,Long,0.3711,0.3760,0.987,0.2,0
52b4da82-c1e0-4a8a-8365-51b090787005,BE9558,2026-05-16T11:28:55,K558LLAD.870W,Long,0.3644,0.3662,0.995,0.2,0
cdbff3d8-fbfe-4bea-8bd6-c898800e81ba,BE9558,2026-05-16T11:39:31,K558LLAD.PV0W,Long,0.3609,0.3662,0.986,0.2,0
3fb0bc30-1463-4cfc-9e7f-386c0eb2a34a,BE9558,2026-05-16T11:44:49,K558LLAD.YP0W,Long,0.3553,0.3564,0.997,0.2,0
ba1f5ec8-aef7-4a9e-ac1f-276cf016e285,BE9558,2026-05-16T11:50:07,K558LLAE.7J0W,Long,0.3479,0.3516,0.990,0.2,0
b1dd4df7-34a9-4512-a903-f8242b236fd2,BE9558,2026-05-16T11:55:25,K558LLAE.GD0W,Long,0.3427,0.3467,0.988,0.2,0
1f23aa28-c026-4bc7-b3d1-7c78fd76a673,BE9558,2026-05-16T12:00:43,K558LLAE.P70W,Long,0.3454,0.3467,0.996,0.2,0
0d91f54d-b20d-4a50-b7dd-d071c39a0690,BE9558,2026-05-16T12:06:01,K558LLAE.Y10W,Long,0.3431,0.3467,0.990,0.2,0
12ccdecd-5fd9-4465-9813-3d6006ec32f3,BE9558,2026-05-16T12:11:19,K558LLAF.6V0W,Long,0.3433,0.3467,0.990,0.2,0
a7024f1a-f071-48ab-820f-99bdf87366b5,BE9558,2026-05-16T12:16:37,K558LLAF.FP0W,Long,0.3361,0.3369,0.998,0.2,0
de0fa439-30b8-4607-a3c3-7e17191e4624,BE9558,2026-05-16T12:21:55,K558LLAF.OJ0W,Long,0.3274,0.3320,0.986,0.2,0
f9374ec3-05e5-477f-8e1a-0c862fed2a50,BE9558,2026-05-16T12:27:13,K558LLAF.XD0W,Long,0.3449,0.3467,0.995,0.2,0
424cb275-3743-4174-95f0-0ca1205b374c,BE9558,2026-05-16T12:32:31,K558LLAG.670W,Long,0.3370,0.3418,0.986,0.2,0
9accde13-cefa-41b8-bd0a-cef2ffed59b0,BE9558,2026-05-16T12:37:49,K558LLAG.F10W,Long,0.3465,0.3467,0.999,0.2,0
4665be38-1956-4b14-b931-068ba9af5c5e,BE9558,2026-05-16T12:48:25,K558LLAG.WP0W,Long,0.3453,0.3516,0.982,0.2,0
1aedf624-1a99-43e1-a8f2-f9d358b97f61,BE9558,2026-05-16T12:53:43,K558LLAH.5J0W,Long,0.3366,0.3418,0.985,0.2,0
c15e1799-91d7-425e-ad17-2ba3d170d81e,BE9558,2026-05-16T13:04:19,K558LLAH.N70W,Long,0.3348,0.3369,0.994,0.2,0
72d4c4ea-19ca-4cc6-9b04-7a2b70122c67,BE9558,2026-05-16T13:09:37,K558LLAH.W10W,Long,0.3272,0.3320,0.986,0.2,0
b4ebf2c9-1f6d-4594-9810-40479e87c0a5,BE9558,2026-05-16T13:14:55,K558LLAI.4V0W,Long,0.3297,0.3320,0.993,0.2,0
bb297e9e-548f-4dae-8b1a-0f161af2e766,BE9558,2026-05-16T13:20:13,K558LLAI.DP0W,Long,0.3272,0.3320,0.986,0.2,0
87562c24-63db-48bd-9962-72a20a40f2ff,BE9558,2026-05-16T13:36:07,K558LLAJ.470W,Long,0.3174,0.3223,0.985,0.2,0
01e9cc58-3bea-4f38-8499-a2c20e5f8550,BE9558,2026-05-16T13:46:52,K558LLAJ.M40W,Long,0.2880,0.2930,0.983,0.2,0
5ae7503d-ae17-4063-9208-6a420699e1ab,BE9558,2026-05-16T14:00:35,K558LLAK.8Z0W,Long,0.2879,0.2930,0.983,0.2,0
e009ea3c-1534-4154-8623-e180ed4db9fb,BE9558,2026-05-16T14:06:19,K558LLAK.IJ0W,Long,0.2882,0.2930,0.984,0.2,0
cd4e21f5-512b-4b2b-8054-bec01aa06400,BE9558,2026-05-16T14:12:03,K558LLAK.S30W,Long,0.2857,0.2930,0.975,0.2,0
ae5b780f-2038-4ccf-8bfc-b15b87be139e,BE9558,2026-05-16T14:17:22,K558LLAL.0Y0W,Long,0.2899,0.2930,0.989,0.2,0
d8c3fb81-8c66-4ebc-b33a-0559bc03334b,BE9558,2026-05-16T14:22:40,K558LLAL.9S0W,Long,0.3009,0.3027,0.994,0.2,0
990a4c7a-3c51-4d4a-8ab7-416ccb97d29c,BE9558,2026-05-16T14:27:58,K558LLAL.IM0W,Long,0.3057,0.3076,0.994,0.2,0
68d7a2c3-d899-4e75-96fb-3bf16ae6ea6f,BE9558,2026-05-16T14:33:16,K558LLAL.RG0W,Long,0.3110,0.3125,0.995,0.2,0
73505b8c-f912-4116-b903-a8a4c75524d3,BE9558,2026-05-16T14:38:34,K558LLAM.0A0W,Long,0.3172,0.3223,0.984,0.2,0
8d3c9602-7efa-488a-801b-3228bd85ab14,BE9558,2026-05-16T14:43:51,K558LLAM.930W,Long,0.3136,0.3174,0.988,0.2,0
243e16ee-860a-4960-bc15-b797ad7e9735,BE9558,2026-05-16T14:49:08,K558LLAM.HW0W,Long,0.3135,0.3174,0.988,0.2,0
e90c8d90-6d41-4788-9ee6-a29e4bfcc16b,BE9558,2026-05-16T15:19:35,K558LLAN.WN0W,Long,0.3132,0.3174,0.987,0.2,0
4182b0e7-7811-46b8-87d1-a4dd0c152f3b,BE9558,2026-05-16T15:28:45,K558LLAO.BX0W,Long,0.3023,0.3076,0.983,0.2,0
28a790da-0e48-4fe4-b8ba-2c82cc6bfa79,BE9558,2026-05-16T15:34:02,K558LLAO.KQ0W,Long,0.3176,0.3223,0.985,0.2,0
093d2fa3-7a4b-4f0f-abda-71155ebe2dfb,BE9558,2026-05-16T15:39:19,K558LLAO.TJ0W,Long,0.3223,0.3271,0.985,0.2,0
68dc9560-4082-49b6-af04-9244773ffbc1,BE9558,2026-05-16T15:44:36,K558LLAP.2C0W,Long,0.3227,0.3271,0.986,0.2,0
ad6b268a-165d-4b1d-b0b3-f58db7c9b0e4,BE9558,2026-05-16T15:49:53,K558LLAP.B50W,Long,0.3177,0.3223,0.986,0.2,0
046c5cb4-56b3-48c0-83c2-bf1f30837940,BE9558,2026-05-16T15:55:10,K558LLAP.JY0W,Long,0.3174,0.3223,0.985,0.2,0
1b76edf4-3b1c-4bcb-a73c-27334981c350,BE9558,2026-05-16T16:00:27,K558LLAP.SR0W,Long,0.3127,0.3174,0.985,0.2,0
a0264171-a682-4396-ad8a-cda3b2964533,BE9558,2026-05-16T16:06:55,K558LLAQ.3J0W,Long,0.2885,0.2930,0.985,0.2,0
707da1f6-ee81-4e57-abd5-98295c14651b,BE9558,2026-05-16T16:12:30,K558LLAQ.CU0W,Long,0.2880,0.2930,0.983,0.2,0
b8115b64-8739-42c8-b541-713ab6b68bcd,BE9558,2026-05-16T16:17:53,K558LLAQ.LT0W,Long,0.2881,0.2930,0.983,0.2,0
fb179c36-fef1-4df6-b0a0-2bd7792ea910,BE9558,2026-05-16T16:23:11,K558LLAQ.UN0W,Long,0.2933,0.2979,0.985,0.2,0
0cec8793-c3c1-486b-a33a-4dbf9cb069b0,BE9558,2026-05-16T16:33:46,K558LLAR.CA0W,Long,0.3017,0.3027,0.997,0.2,0
c531b052-ee04-4c66-888b-21e97445a615,BE9558,2026-05-16T16:49:37,K558LLAS.2P0W,Long,0.2922,0.2979,0.981,0.2,0
0dc402f9-cab6-4c4a-8317-b8fc3c4b1ced,BE9558,2026-05-16T16:55:08,K558LLAS.BW0W,Long,0.2898,0.2930,0.989,0.2,0
fd73733e-b42d-4a51-81d0-4acad6edfbd4,BE9558,2026-05-16T17:16:17,K558LLAT.B50W,Long,0.3115,0.3125,0.997,0.2,0
6a254daa-ae27-4ac1-b334-58f776a6b276,BE9558,2026-05-16T17:26:51,K558LLAT.SR0W,Long,0.3174,0.3223,0.985,0.2,0
0cc8e82f-5270-4508-beae-0d3af56095ca,BE9558,2026-05-16T17:37:27,K558LLAU.AF0W,Long,0.2899,0.2930,0.989,0.2,0
00557a73-8dc3-4cd2-b880-c7820dc8b171,BE9558,2026-05-16T17:43:17,K558LLAU.K50W,Long,0.2881,0.2930,0.983,0.2,0
8e5518d9-ff0a-4c09-9cf9-a681c84c0b6e,BE9558,2026-05-16T17:53:53,K558LLAV.1T0W,Long,0.2898,0.2930,0.989,0.2,0
91dbd7e9-7344-400b-82b1-379f2ac4b49a,BE9558,2026-05-16T17:59:11,K558LLAV.AN0W,Long,0.2925,0.2930,0.998,0.2,0
fa256408-d480-4376-95b5-d1a549c483ea,BE9558,2026-05-16T18:04:29,K558LLAV.JH0W,Long,0.2977,0.3027,0.983,0.2,0
4ab6e66a-8364-49b6-82f1-86e86199e676,BE9558,2026-05-16T18:09:46,K558LLAV.SA0W,Long,0.2944,0.2979,0.988,0.2,0
0a65fb7c-96e1-4ba0-85de-4620d88658c1,BE9558,2026-05-16T18:15:03,K558LLAW.130W,Long,0.2965,0.2979,0.995,0.2,0
92b1ef3e-1696-4123-8662-163947737c83,BE9558,2026-05-16T18:20:20,K558LLAW.9W0W,Long,0.2976,0.3027,0.983,0.2,0
9e3cb24c-4426-4220-9a73-389d0a96c94f,BE9558,2026-05-16T18:25:37,K558LLAW.IP0W,Long,0.2983,0.3027,0.985,0.2,0
a3473215-4c46-45ab-9aa7-1720486ec4a8,BE9558,2026-05-16T18:30:54,K558LLAW.RI0W,Long,0.2956,0.2979,0.993,0.2,0
449665b1-47c8-4bd2-984c-8f45b627e6d8,BE9558,2026-05-16T18:36:11,K558LLAX.0B0W,Long,0.2989,0.3027,0.987,0.2,0
600cfabc-cffd-42e1-800c-70e75f312316,BE9558,2026-05-16T20:00:12,K558LLB0.WC0W,Long,0.3077,0.3125,0.985,0.2,0
12bf5944-0194-4f5b-b486-a7acd7141c7f,BE9558,2026-05-16T20:04:28,K558LLB1.3G0W,Long,0.2888,0.2930,0.986,0.2,0
f1fc913a-91bc-4240-a595-7dfe3091f9a2,BE9558,2026-05-16T20:07:29,K558LLB1.8H0W,Long,0.2977,0.3027,0.983,0.2,0
e74f7ec3-20bb-4177-beb2-e802e5f801fd,BE9558,2026-05-16T20:10:26,K558LLB1.DE0W,Long,0.2978,0.3027,0.984,0.2,0
27491c3a-b631-4643-818a-714523911178,BE9558,2026-05-16T20:16:21,K558LLB1.N90W,Long,0.2921,0.2930,0.997,0.2,0
9d9196ce-11e2-4f28-b01c-3dcc60e60d42,BE9558,2026-05-16T20:22:28,K558LLB1.XG0W,Long,0.2881,0.2930,0.983,0.2,0
a592d7c8-b643-4b25-9186-3d611ae22709,BE9558,2026-05-16T20:25:37,K558LLB2.2P0W,Long,0.2893,0.2930,0.987,0.2,0
f709a3d5-27cd-4bb1-b91c-669e8ea11d77,BE9558,2026-05-16T20:28:57,K558LLB2.890W,Long,0.2880,0.2930,0.983,0.2,0
cc9cad87-b87f-4b67-854a-ffb21e876a92,BE9558,2026-05-16T20:32:45,K558LLB2.EL0W,Long,0.2873,0.2930,0.980,0.2,0
10732d26-6b49-4b14-a474-6c75e259d278,BE9558,2026-05-16T20:49:32,K558LLB3.6K0W,Long,0.2881,0.2930,0.983,0.2,0
aa63957a-fdb2-4f17-af52-a63bb015119d,BE9558,2026-05-16T21:21:45,K558LLB4.O90W,Long,0.2880,0.2930,0.983,0.2,0
8350440f-019d-45a4-b9f9-23058628e6f0,BE9558,2026-05-16T21:32:43,K558LLB5.6J0W,Long,0.2925,0.2930,0.999,0.2,0
edfc10b2-dbe1-4527-a061-b0d670b5e5d2,BE9558,2026-05-16T21:35:37,K558LLB5.BD0W,Long,0.2891,0.2930,0.987,0.2,0
f98001a3-88b2-4830-8112-b7c5164e99c3,BE9558,2026-05-16T21:38:40,K558LLB5.GG0W,Long,0.2877,0.2930,0.982,0.2,0
f1e53e7b-b124-4fc5-82c2-504fb0c8b80d,BE9558,2026-05-16T21:41:46,K558LLB5.LM0W,Long,0.2881,0.2930,0.983,0.2,0
7890637f-142e-4775-b48c-fd4f3b8ada77,BE9558,2026-05-16T21:45:14,K558LLB5.RE0W,Long,0.2880,0.2930,0.983,0.2,0
7c97c10f-b413-467c-9b56-c18e423cdcfa,BE9558,2026-05-16T21:48:26,K558LLB5.WQ0W,Long,0.2886,0.2930,0.985,0.2,0
8178cf22-8428-4f85-8199-0a43f7334a8f,BE9558,2026-05-16T21:51:47,K558LLB6.2B0W,Long,0.2881,0.2930,0.983,0.2,0
eceb2997-deb4-403a-802f-50e93d23d423,BE9558,2026-05-16T21:57:18,K558LLB6.BI0W,Long,0.2881,0.2930,0.984,0.2,0
9c26690c-1983-4b21-b8af-7c7967c014c3,BE9558,2026-05-16T22:12:21,K558LLB7.0L0W,Long,0.2876,0.2930,0.982,0.2,0
78f67fc3-08b7-4317-96ba-ee5544e0b95b,BE9558,2026-05-16T22:19:34,K558LLB7.CM0W,Long,0.2880,0.2930,0.983,0.2,0
7f9dad14-4f1b-492d-aa26-845a908ea894,BE9558,2026-05-16T22:27:40,K558LLB7.Q40W,Long,0.2881,0.2930,0.983,0.2,0
f75c52b4-21b9-4065-baeb-5cfbd27d130a,BE9558,2026-05-16T22:33:50,K558LLB8.0E0W,Long,0.2881,0.2930,0.984,0.2,0
10f7496d-fa76-40a7-8bef-dc14e8a41869,BE9558,2026-05-16T22:40:48,K558LLB8.C00W,Long,0.2878,0.2930,0.982,0.2,0
1 event_id serial timestamp filename channel offset_ips peak_ips mean_over_peak trigger_level_ips already_flagged_ft
2 1e7a7808-034c-423b-80e9-d6788da80993 BE18438 2025-11-15T08:57:40 T438LBX4.W40W Vert 0.2722 0.2930 0.929 0.2 0
3 346e383f-c5a1-41d1-b972-3d652e599d39 BE18438 2025-11-15T09:13:15 T438LBX5.M30W Vert 0.2747 0.2930 0.938 0.2 0
4 45ef3023-22c5-44a8-a606-a0900bc17861 BE18438 2025-11-15T09:16:13 T438LBX5.R10W Vert 0.2929 0.3027 0.967 0.2 0
5 1cbcd2aa-ec55-4e2f-af42-7178f26cc6a1 BE18438 2025-11-15T09:19:29 T438LBX5.WH0W Vert 0.2816 0.2979 0.945 0.2 0
6 caf43634-4528-4fd5-9674-5f4f563661c0 BE18438 2025-11-15T09:22:32 T438LBX6.1K0W Vert 0.2883 0.2930 0.984 0.2 0
7 456ae646-c834-4e5c-82f1-7df18b3440a1 BE18438 2025-11-15T09:25:31 T438LBX6.6J0W Vert 0.3189 0.3223 0.989 0.2 0
8 afb91ba2-351b-42a0-b33f-acebd5f1829d BE18438 2025-11-15T09:28:29 T438LBX6.BH0W Vert 0.3057 0.3076 0.994 0.2 0
9 39847146-3537-4300-943d-01c0c771e9cd BE18438 2025-11-15T09:31:26 T438LBX6.GE0W Vert 0.3225 0.3271 0.986 0.2 0
10 e47335c1-fc3f-4c90-88c6-8edd0f296ce4 BE18438 2025-11-15T09:34:24 T438LBX6.LC0W Vert 0.3275 0.3320 0.986 0.2 0
11 25b6eda6-ba98-422f-8834-94b6cbe34971 BE18438 2025-11-15T09:37:22 T438LBX6.QA0W Vert 0.3398 0.3418 0.994 0.2 0
12 7af99377-e47f-4914-8e91-ac7f7f50b8c6 BE18438 2025-11-15T09:40:20 T438LBX6.V80W Vert 0.3515 0.3564 0.986 0.2 0
13 c4330605-c257-49ef-aede-20deb641e7d7 BE18438 2025-11-15T10:09:48 T438LBX8.8C0W Vert 0.3605 0.3955 0.912 0.2 0
14 b665caf9-64ee-4352-a391-60c1ddeebc1e BE18438 2026-02-25T10:58:04 T438LH66.GS0W Vert 0.1803 0.1953 0.923 0.2 0
15 3b0c32c3-fd16-4b83-9917-942a56dea168 BE18438 2026-02-25T18:12:04 T438LH6Q.K40W Vert 0.1869 0.1953 0.957 0.2 0
16 ca66e601-d10f-4424-9c26-08a688e7b08c BE18438 2026-02-25T18:17:16 T438LH6Q.SS0W Vert 0.1870 0.1953 0.958 0.2 0
17 31aa30ba-eb0a-49a9-98ca-c77d2cc31275 BE18438 2026-02-25T18:21:11 T438LH6Q.ZB0W Vert 0.1868 0.1953 0.956 0.2 0
18 fdb55a93-fc91-4fdf-a7f4-fdd1a6b48f59 BE18438 2026-02-25T18:26:27 T438LH6R.830W Vert 0.1893 0.1953 0.969 0.2 0
19 cbd718d7-2378-4d74-8656-842f229d19a8 BE18438 2026-02-25T18:33:25 T438LH6R.JP0W Vert 0.1887 0.1953 0.966 0.2 0
20 bfaf58ec-6163-47eb-9d2a-70da880bd948 BE18438 2026-02-25T18:37:48 T438LH6R.R00W Vert 0.1872 0.1953 0.959 0.2 0
21 ddaa530b-886e-4415-b93a-f4ebf4c4a882 BE18438 2026-02-25T18:59:54 T438LH6S.RU0W Vert 0.1874 0.1953 0.959 0.2 0
22 57f15284-ab69-48fc-9660-8c347c80c681 BE18438 2026-02-25T19:15:58 T438LH6T.IM0W Vert 0.1873 0.1953 0.959 0.2 0
23 03715718-7aa8-4e1d-9b0b-c2ab75fc1975 BE18438 2026-02-25T19:19:58 T438LH6T.PA0W Vert 0.1891 0.1953 0.968 0.2 0
24 9f921cd5-1bf9-4713-aef6-41e7f780eff1 BE18438 2026-02-25T19:24:02 T438LH6T.W20W Vert 0.1871 0.1953 0.958 0.2 0
25 44994949-58d4-44fa-bd78-ed75b8acc667 BE18438 2026-02-25T19:44:57 T438LH6U.UX0W Vert 0.1877 0.1953 0.961 0.2 0
26 c4be01c3-1001-4e17-aecd-d6d26dbb09f3 BE18438 2026-02-25T19:49:19 T438LH6V.270W Vert 0.1884 0.1953 0.964 0.2 0
27 3db004e6-ee34-43c5-ae8e-f22894ead5d0 BE18438 2026-02-25T20:08:22 T438LH6V.XY0W Vert 0.1878 0.1953 0.962 0.2 0
28 d276ae48-0434-41e5-af43-e0fb366acf11 BE18438 2026-02-25T20:11:33 T438LH6W.390W Vert 0.1880 0.1953 0.963 0.2 0
29 c027dc12-88fd-4a45-872b-a6a945f2008e BE18438 2026-02-25T20:14:35 T438LH6W.8B0W Vert 0.1874 0.1953 0.959 0.2 0
30 9665bc3a-3d08-4852-b008-37ef8bfd0023 BE18438 2026-02-25T20:18:51 T438LH6W.FF0W Vert 0.1884 0.1953 0.965 0.2 0
31 5fb5a05e-d7e2-4268-9b85-cfe8d82aa6c9 BE18438 2026-02-25T20:29:50 T438LH6W.XQ0W Vert 0.1890 0.1953 0.968 0.2 0
32 57ec0b10-9324-4459-a07e-0c8532b8928f BE18438 2026-02-25T20:35:39 T438LH6X.7F0W Vert 0.1889 0.1953 0.967 0.2 0
33 ac86f73f-1174-4fae-a206-ecdcb73e1ffc BE18438 2026-02-25T20:39:12 T438LH6X.DC0W Vert 0.1887 0.1953 0.966 0.2 0
34 dcf25ddd-9cf0-41c1-b109-f3ef2e490ce5 BE18438 2026-02-25T20:43:41 T438LH6X.KT0W Vert 0.1871 0.1953 0.958 0.2 0
35 aa79bbdd-2392-4ef6-8a5c-873a9f72746d BE18438 2026-02-25T20:46:51 T438LH6X.Q30W Vert 0.1877 0.1953 0.961 0.2 0
36 ad46d1ce-b417-4c8c-b029-bb3b008ba809 BE18438 2026-02-25T20:53:33 T438LH6Y.190W Vert 0.1882 0.1953 0.964 0.2 0
37 3d3a8f34-86a7-4d70-a7e8-fa768a723325 BE18438 2026-02-26T07:03:39 T438LH7Q.A30W Vert 0.1809 0.1953 0.926 0.2 0
38 7817525f-dc3d-4f5e-b2cb-5af9ca12ede8 BE18438 2026-02-26T07:09:42 T438LH7Q.K60W Vert 0.1814 0.1953 0.929 0.2 0
39 a2091302-0b34-46c1-ab83-174be2b59bcf BE18438 2026-02-26T13:12:35 T438LH87.CZ0W Vert 0.1896 0.1953 0.971 0.2 0
40 e1c0c9de-a900-479f-9572-9675b13296a9 BE18438 2026-02-26T13:24:46 T438LH87.XA0W Vert 0.2237 0.2588 0.864 0.2 0
41 76a6dc6b-88e1-434b-a137-f5e9b63f248e BE18438 2026-02-26T13:27:43 T438LH88.270W Vert 0.3185 0.3223 0.988 0.2 0
42 281b508b-7982-4668-86af-9b0b28be608a BE18438 2026-02-26T13:30:36 T438LH88.700W Vert 0.3263 0.3320 0.983 0.2 0
43 68bbaf77-bb23-40fd-94f9-f928728d90dc BE18438 2026-02-26T13:33:28 T438LH88.BS0W Vert 0.3207 0.3271 0.980 0.2 0
44 5c975640-6ff1-441a-aa11-41642f6a6b31 BE18438 2026-02-26T13:36:21 T438LH88.GL0W Vert 0.3261 0.3320 0.982 0.2 0
45 dea248ac-1124-4bba-b054-953f86c852b2 BE18438 2026-02-26T13:40:34 T438LH88.NM0W Vert 0.3271 0.3320 0.985 0.2 0
46 4e463201-f008-41ad-9c52-11fcc3d93095 BE18438 2026-02-26T13:43:29 T438LH88.SH0W Vert 0.3357 0.3418 0.982 0.2 0
47 507262c5-d58f-4a05-a6a3-a6cbb5b4de20 BE18438 2026-02-26T13:46:24 T438LH88.XC0W Vert 0.3372 0.3418 0.987 0.2 0
48 4c2d8ee8-842f-4e44-9e03-ff34d26e4fdb BE18438 2026-02-26T13:49:17 T438LH89.250W Vert 0.3253 0.3320 0.980 0.2 0
49 b184b112-603f-44f4-ae97-087493fbd8ce BE18438 2026-02-26T13:52:10 T438LH89.6Y0W Vert 0.3321 0.3369 0.986 0.2 0
50 2ff1a552-5a2e-4396-9083-b9c8d334eed7 BE18438 2026-02-26T13:55:04 T438LH89.BS0W Vert 0.3378 0.3418 0.988 0.2 0
51 928e21a7-1990-4792-803e-58014d8140ce BE18438 2026-02-26T13:57:57 T438LH89.GL0W Vert 0.3341 0.3369 0.992 0.2 0
52 f521b5db-6100-41e6-954e-0abdbf9660c1 BE18438 2026-02-26T14:00:51 T438LH89.LF0W Vert 0.3421 0.3467 0.987 0.2 0
53 efba962f-e511-41ef-9fc5-313f202a9d96 BE18438 2026-02-26T14:03:46 T438LH89.QA0W Vert 0.3506 0.3564 0.984 0.2 0
54 0b51e273-8d10-4494-bda6-8c75eaeec66f BE18438 2026-02-26T14:06:41 T438LH89.V50W Vert 0.3448 0.3516 0.981 0.2 0
55 6d46e4ee-1647-4169-b6b2-33da32240eb9 BE18438 2026-02-26T14:09:35 T438LH89.ZZ0W Vert 0.3463 0.3516 0.985 0.2 0
56 1ca294cd-4dc2-41fb-9374-e277d4550761 BE18438 2026-02-26T14:12:28 T438LH8A.4S0W Vert 0.3442 0.3467 0.993 0.2 0
57 7b683dcf-1aed-4d9b-be1e-b10f92374398 BE18438 2026-02-26T14:15:23 T438LH8A.9N0W Vert 0.3486 0.3516 0.992 0.2 0
58 2b5cb8e7-c947-4914-bcb5-504f74603547 BE18438 2026-02-26T14:18:21 T438LH8A.EL0W Vert 0.3519 0.3613 0.974 0.2 0
59 5ea3a6bf-10de-4911-aedc-66daecf86b76 BE18438 2026-02-26T14:21:16 T438LH8A.JG0W Vert 0.3460 0.3564 0.971 0.2 0
60 d93be7f5-39ec-45fd-9949-fa531f2f9d34 BE18438 2026-02-26T14:24:13 T438LH8A.OD0W Vert 0.3457 0.3516 0.983 0.2 0
61 cfa113f2-8cee-4a1d-b1e7-0e936fa771e2 BE18438 2026-02-26T14:28:21 T438LH8A.V90W Vert 0.3485 0.3564 0.978 0.2 0
62 46d322ac-38cb-4c99-a4c2-9e9d7ad06171 BE18438 2026-02-26T14:31:17 T438LH8B.050W Vert 0.3367 0.3467 0.971 0.2 0
63 42500a83-bd67-4deb-8bb2-963ee2b8a7ce BE18438 2026-02-26T14:34:11 T438LH8B.4Z0W Vert 0.3365 0.3516 0.957 0.2 0
64 3ccf6bda-2e88-473c-951d-9ea86d0d9363 BE18438 2026-02-26T14:37:05 T438LH8B.9T0W Vert 0.3472 0.3564 0.974 0.2 0
65 9050487d-d238-4631-b8e1-5a693a026542 BE18438 2026-02-26T14:39:58 T438LH8B.EM0W Vert 0.3420 0.3564 0.959 0.2 0
66 e62989e4-a326-4bae-8d47-a8becee96462 BE18438 2026-02-26T14:42:52 T438LH8B.JG0W Vert 0.3430 0.3564 0.962 0.2 0
67 f0e30fab-dc57-4189-8439-48df17007a2c BE18438 2026-02-26T14:45:46 T438LH8B.OA0W Vert 0.3389 0.3516 0.964 0.2 0
68 03e1ca09-78df-4c6f-9915-0b6e4f2141d2 BE18438 2026-02-26T14:48:43 T438LH8B.T70W Vert 0.3449 0.3564 0.968 0.2 0
69 945d39f7-1b98-4a1f-80a8-6a18fd9df25f BE18438 2026-02-26T14:51:37 T438LH8B.Y10W Vert 0.3522 0.3613 0.975 0.2 0
70 d27eb2e3-e313-4125-98f4-f9d6d3737d28 BE18438 2026-02-26T14:54:32 T438LH8C.2W0W Vert 0.3502 0.3613 0.969 0.2 0
71 916901cb-ebea-441e-a2a1-40f4e49f32f4 BE18438 2026-02-26T14:57:25 T438LH8C.7P0W Vert 0.3524 0.3662 0.962 0.2 0
72 5d8d7e29-fdbb-4fa3-bd25-506c9352a354 BE18438 2026-02-26T15:01:35 T438LH8C.EN0W Vert 0.3530 0.3613 0.977 0.2 0
73 c6c7a3af-b03b-43dc-97de-024f8e09b62f BE18438 2026-02-26T15:04:27 T438LH8C.JF0W Vert 0.3514 0.3613 0.973 0.2 0
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192 ffb6b230-1d70-4e0e-ba30-e945339a122a BE9558 2026-05-16T11:23:37 K558LLAC.ZD0W Long 0.3711 0.3760 0.987 0.2 0
193 52b4da82-c1e0-4a8a-8365-51b090787005 BE9558 2026-05-16T11:28:55 K558LLAD.870W Long 0.3644 0.3662 0.995 0.2 0
194 cdbff3d8-fbfe-4bea-8bd6-c898800e81ba BE9558 2026-05-16T11:39:31 K558LLAD.PV0W Long 0.3609 0.3662 0.986 0.2 0
195 3fb0bc30-1463-4cfc-9e7f-386c0eb2a34a BE9558 2026-05-16T11:44:49 K558LLAD.YP0W Long 0.3553 0.3564 0.997 0.2 0
196 ba1f5ec8-aef7-4a9e-ac1f-276cf016e285 BE9558 2026-05-16T11:50:07 K558LLAE.7J0W Long 0.3479 0.3516 0.990 0.2 0
197 b1dd4df7-34a9-4512-a903-f8242b236fd2 BE9558 2026-05-16T11:55:25 K558LLAE.GD0W Long 0.3427 0.3467 0.988 0.2 0
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199 0d91f54d-b20d-4a50-b7dd-d071c39a0690 BE9558 2026-05-16T12:06:01 K558LLAE.Y10W Long 0.3431 0.3467 0.990 0.2 0
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218 d8c3fb81-8c66-4ebc-b33a-0559bc03334b BE9558 2026-05-16T14:22:40 K558LLAL.9S0W Long 0.3009 0.3027 0.994 0.2 0
219 990a4c7a-3c51-4d4a-8ab7-416ccb97d29c BE9558 2026-05-16T14:27:58 K558LLAL.IM0W Long 0.3057 0.3076 0.994 0.2 0
220 68d7a2c3-d899-4e75-96fb-3bf16ae6ea6f BE9558 2026-05-16T14:33:16 K558LLAL.RG0W Long 0.3110 0.3125 0.995 0.2 0
221 73505b8c-f912-4116-b903-a8a4c75524d3 BE9558 2026-05-16T14:38:34 K558LLAM.0A0W Long 0.3172 0.3223 0.984 0.2 0
222 8d3c9602-7efa-488a-801b-3228bd85ab14 BE9558 2026-05-16T14:43:51 K558LLAM.930W Long 0.3136 0.3174 0.988 0.2 0
223 243e16ee-860a-4960-bc15-b797ad7e9735 BE9558 2026-05-16T14:49:08 K558LLAM.HW0W Long 0.3135 0.3174 0.988 0.2 0
224 e90c8d90-6d41-4788-9ee6-a29e4bfcc16b BE9558 2026-05-16T15:19:35 K558LLAN.WN0W Long 0.3132 0.3174 0.987 0.2 0
225 4182b0e7-7811-46b8-87d1-a4dd0c152f3b BE9558 2026-05-16T15:28:45 K558LLAO.BX0W Long 0.3023 0.3076 0.983 0.2 0
226 28a790da-0e48-4fe4-b8ba-2c82cc6bfa79 BE9558 2026-05-16T15:34:02 K558LLAO.KQ0W Long 0.3176 0.3223 0.985 0.2 0
227 093d2fa3-7a4b-4f0f-abda-71155ebe2dfb BE9558 2026-05-16T15:39:19 K558LLAO.TJ0W Long 0.3223 0.3271 0.985 0.2 0
228 68dc9560-4082-49b6-af04-9244773ffbc1 BE9558 2026-05-16T15:44:36 K558LLAP.2C0W Long 0.3227 0.3271 0.986 0.2 0
229 ad6b268a-165d-4b1d-b0b3-f58db7c9b0e4 BE9558 2026-05-16T15:49:53 K558LLAP.B50W Long 0.3177 0.3223 0.986 0.2 0
230 046c5cb4-56b3-48c0-83c2-bf1f30837940 BE9558 2026-05-16T15:55:10 K558LLAP.JY0W Long 0.3174 0.3223 0.985 0.2 0
231 1b76edf4-3b1c-4bcb-a73c-27334981c350 BE9558 2026-05-16T16:00:27 K558LLAP.SR0W Long 0.3127 0.3174 0.985 0.2 0
232 a0264171-a682-4396-ad8a-cda3b2964533 BE9558 2026-05-16T16:06:55 K558LLAQ.3J0W Long 0.2885 0.2930 0.985 0.2 0
233 707da1f6-ee81-4e57-abd5-98295c14651b BE9558 2026-05-16T16:12:30 K558LLAQ.CU0W Long 0.2880 0.2930 0.983 0.2 0
234 b8115b64-8739-42c8-b541-713ab6b68bcd BE9558 2026-05-16T16:17:53 K558LLAQ.LT0W Long 0.2881 0.2930 0.983 0.2 0
235 fb179c36-fef1-4df6-b0a0-2bd7792ea910 BE9558 2026-05-16T16:23:11 K558LLAQ.UN0W Long 0.2933 0.2979 0.985 0.2 0
236 0cec8793-c3c1-486b-a33a-4dbf9cb069b0 BE9558 2026-05-16T16:33:46 K558LLAR.CA0W Long 0.3017 0.3027 0.997 0.2 0
237 c531b052-ee04-4c66-888b-21e97445a615 BE9558 2026-05-16T16:49:37 K558LLAS.2P0W Long 0.2922 0.2979 0.981 0.2 0
238 0dc402f9-cab6-4c4a-8317-b8fc3c4b1ced BE9558 2026-05-16T16:55:08 K558LLAS.BW0W Long 0.2898 0.2930 0.989 0.2 0
239 fd73733e-b42d-4a51-81d0-4acad6edfbd4 BE9558 2026-05-16T17:16:17 K558LLAT.B50W Long 0.3115 0.3125 0.997 0.2 0
240 6a254daa-ae27-4ac1-b334-58f776a6b276 BE9558 2026-05-16T17:26:51 K558LLAT.SR0W Long 0.3174 0.3223 0.985 0.2 0
241 0cc8e82f-5270-4508-beae-0d3af56095ca BE9558 2026-05-16T17:37:27 K558LLAU.AF0W Long 0.2899 0.2930 0.989 0.2 0
242 00557a73-8dc3-4cd2-b880-c7820dc8b171 BE9558 2026-05-16T17:43:17 K558LLAU.K50W Long 0.2881 0.2930 0.983 0.2 0
243 8e5518d9-ff0a-4c09-9cf9-a681c84c0b6e BE9558 2026-05-16T17:53:53 K558LLAV.1T0W Long 0.2898 0.2930 0.989 0.2 0
244 91dbd7e9-7344-400b-82b1-379f2ac4b49a BE9558 2026-05-16T17:59:11 K558LLAV.AN0W Long 0.2925 0.2930 0.998 0.2 0
245 fa256408-d480-4376-95b5-d1a549c483ea BE9558 2026-05-16T18:04:29 K558LLAV.JH0W Long 0.2977 0.3027 0.983 0.2 0
246 4ab6e66a-8364-49b6-82f1-86e86199e676 BE9558 2026-05-16T18:09:46 K558LLAV.SA0W Long 0.2944 0.2979 0.988 0.2 0
247 0a65fb7c-96e1-4ba0-85de-4620d88658c1 BE9558 2026-05-16T18:15:03 K558LLAW.130W Long 0.2965 0.2979 0.995 0.2 0
248 92b1ef3e-1696-4123-8662-163947737c83 BE9558 2026-05-16T18:20:20 K558LLAW.9W0W Long 0.2976 0.3027 0.983 0.2 0
249 9e3cb24c-4426-4220-9a73-389d0a96c94f BE9558 2026-05-16T18:25:37 K558LLAW.IP0W Long 0.2983 0.3027 0.985 0.2 0
250 a3473215-4c46-45ab-9aa7-1720486ec4a8 BE9558 2026-05-16T18:30:54 K558LLAW.RI0W Long 0.2956 0.2979 0.993 0.2 0
251 449665b1-47c8-4bd2-984c-8f45b627e6d8 BE9558 2026-05-16T18:36:11 K558LLAX.0B0W Long 0.2989 0.3027 0.987 0.2 0
252 600cfabc-cffd-42e1-800c-70e75f312316 BE9558 2026-05-16T20:00:12 K558LLB0.WC0W Long 0.3077 0.3125 0.985 0.2 0
253 12bf5944-0194-4f5b-b486-a7acd7141c7f BE9558 2026-05-16T20:04:28 K558LLB1.3G0W Long 0.2888 0.2930 0.986 0.2 0
254 f1fc913a-91bc-4240-a595-7dfe3091f9a2 BE9558 2026-05-16T20:07:29 K558LLB1.8H0W Long 0.2977 0.3027 0.983 0.2 0
255 e74f7ec3-20bb-4177-beb2-e802e5f801fd BE9558 2026-05-16T20:10:26 K558LLB1.DE0W Long 0.2978 0.3027 0.984 0.2 0
256 27491c3a-b631-4643-818a-714523911178 BE9558 2026-05-16T20:16:21 K558LLB1.N90W Long 0.2921 0.2930 0.997 0.2 0
257 9d9196ce-11e2-4f28-b01c-3dcc60e60d42 BE9558 2026-05-16T20:22:28 K558LLB1.XG0W Long 0.2881 0.2930 0.983 0.2 0
258 a592d7c8-b643-4b25-9186-3d611ae22709 BE9558 2026-05-16T20:25:37 K558LLB2.2P0W Long 0.2893 0.2930 0.987 0.2 0
259 f709a3d5-27cd-4bb1-b91c-669e8ea11d77 BE9558 2026-05-16T20:28:57 K558LLB2.890W Long 0.2880 0.2930 0.983 0.2 0
260 cc9cad87-b87f-4b67-854a-ffb21e876a92 BE9558 2026-05-16T20:32:45 K558LLB2.EL0W Long 0.2873 0.2930 0.980 0.2 0
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scratch/offset_hist_scan.py
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#!/usr/bin/env python3
"""Offset detector — HISTOGRAM corpus (the other 90% of the archive).
`offset_scan3.py` measures the pre-trigger floor in *waveform* samples. That
covers 6,577 of the archive's 70,112 unique series-3 files; the remaining
63,535 are **histograms**, which carry no samples — only a per-interval,
per-channel peak + half-period. So the pre-trigger method cannot run on them.
The histogram analogue of "the resting floor" is the **low percentile of the
per-interval peaks**. A histogram file is typically hours of continuous
monitoring, so the great majority of its intervals are definitionally quiet;
the bottom of that distribution is what the channel reads when nothing is
happening. A healthy channel bottoms out at 0.000-0.005 in/s. A channel
parked off zero cannot report a peak below its own displacement, so its floor
is pinned up.
⚠ The DC leakage into the histogram peak is PARTIAL. Measured within-unit
against episodes already established from the waveform scan:
BE18438 Vert in-episode 0.0350 vs 0.0050 outside (waveform pre = +0.18..+0.37)
BE12599 Tran in-episode 0.0250 vs 0.0050 outside (waveform pre = +0.03..+0.49)
so the device's per-interval peak is evidently measured against a running /
AC-coupled baseline that removes most, but not all, of the DC. The residual
is real and channel-specific, but the margin is ~5 quantisation counts rather
than the ~70 the waveform detector enjoys. Do not carry the waveform
detector's 0.025 in/s floor across unexamined — calibrate on the CSV.
Because the absolute floor also moves with site noise (traffic, wind, a
generator), the statistic that matters most is the **cross-channel
differential**: a channel's floor minus the quietest of the other two geo
channels in the same file. Site noise lifts all three together and cancels;
a DC offset lifts one.
This script does not decide anything. It emits every candidate statistic per
(file, channel) so thresholds can be calibrated against the waveform-derived
ground truth in `offset_v3.csv` rather than guessed.
Usage:
python scratch/offset_hist_scan.py --dir /home/serversdown/dl2-archive/files \
--out /home/serversdown/dl2-archive/offset_hist.csv --jobs 4
"""
from __future__ import annotations
import argparse
import csv
import datetime
import logging
import re
import statistics
import sys
from concurrent.futures import ProcessPoolExecutor, as_completed
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from minimateplus.event_file_io import read_blastware_file # noqa: E402
GEO = ("Tran", "Vert", "Long")
K = 10.0 / 32000.0 # ADC count -> in/s (see CLAUDE.md: full scale 32000)
_HIST = re.compile(r"\.[A-Za-z0-9]{2}0[Hh]$")
_STEM = re.compile(r"^([B-Z])(\d{3})")
_B36 = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
_SERIAL_RE = re.compile(rb"\b([A-Z]{2}\d{3,6})\b")
def serial_of(name: str, path=None) -> str:
"""Real serial for a BW file.
The filename encodes only the NUMBER: `<letter><3 digits>` where
letter = chr(ord('B') + serial // 1000). The two-letter family prefix
("BE", "BA", ...) is **not** in the filename, so it must be read out of
the file body. Four units in the DL2 archive are BA, not BE — assuming
"BE" mislabels BA9229, BA10060, BA10895 and BA15957.
"""
m = _STEM.match(name)
if not m:
return "?"
num = (ord(m.group(1)) - ord("B")) * 1000 + int(m.group(2))
if path is not None:
try:
for s in _SERIAL_RE.findall(Path(path).read_bytes()):
s = s.decode()
if s[2:].lstrip("0") == str(num):
return s
except Exception:
pass
return f"BE{num}" # last-resort fallback; prefix unverified
def stem_time(name: str):
"""Decode the filename's base-36 timestamp. Epoch 1985-01-01, 1296 s/tick.
Preferred over the file's own footer timestamp only because it costs
nothing; the caller falls back to the decoded event when this fails.
"""
try:
base, ext = name.rsplit(".", 1)
n = 0
for c in base[4:8].upper():
n = n * 36 + _B36.index(c)
ab = _B36.index(ext[0].upper()) * 36 + _B36.index(ext[1].upper())
return datetime.datetime(1985, 1, 1) + datetime.timedelta(seconds=n * 1296 + ab)
except Exception:
return None
def _pct(sorted_vals, q):
"""Nearest-rank percentile on an already-sorted list."""
if not sorted_vals:
return None
i = min(len(sorted_vals) - 1, max(0, int(len(sorted_vals) * q / 100.0)))
return sorted_vals[i]
def scan(path_str: str):
logging.disable(logging.WARNING) # per-worker: the codec warns on undecodables
p = Path(path_str)
try:
ev = read_blastware_file(p)
except Exception:
return None
s = ev.raw_samples or {}
if not any(s.get(c) for c in GEO):
return None
ts = stem_time(p.name) or ev.timestamp
stamp = ""
if ts is not None:
stamp = (f"{ts.year:04d}-{ts.month:02d}-{ts.day:02d}T"
f"{ts.hour:02d}:{ts.minute:02d}:{ts.second:02d}")
# Per-channel floor candidates, in in/s.
stats = {}
for ch in GEO:
v = sorted(s.get(ch) or [])
if not v:
continue
stats[ch] = {
"n": len(v),
"min": v[0] * K,
"p1": _pct(v, 1) * K,
"p5": _pct(v, 5) * K,
"p10": _pct(v, 10) * K,
"p25": _pct(v, 25) * K,
"med": statistics.median(v) * K,
"peak": v[-1] * K,
"zeros": sum(1 for x in v if x == 0) / len(v),
}
if len(stats) < 2: # need at least one sibling channel for the differential
return None
# Mic floor as a site-noise proxy (raw counts; the dB conversion is not
# needed — only its relative movement matters here).
mic = sorted(s.get("MicL") or [])
mic_p5 = _pct(mic, 5) if mic else ""
rows = []
for ch, st in stats.items():
others = [stats[o]["p5"] for o in stats if o != ch]
rows.append({
"serial": serial_of(p.name, p),
"timestamp": stamp,
"filename": p.name,
"channel": ch,
"n_intervals": st["n"],
"min": round(st["min"], 4),
"p1": round(st["p1"], 4),
"p5": round(st["p5"], 4),
"p10": round(st["p10"], 4),
"p25": round(st["p25"], 4),
"median": round(st["med"], 4),
"peak": round(st["peak"], 4),
"frac_zero": round(st["zeros"], 4),
# the site-noise-cancelling statistic: this channel's floor above
# the quietest sibling geo channel in the same file
"diff_p5": round(st["p5"] - min(others), 4),
"mic_p5": mic_p5,
})
return rows
COLS = ["serial", "timestamp", "filename", "channel", "n_intervals",
"min", "p1", "p5", "p10", "p25", "median", "peak", "frac_zero",
"diff_p5", "mic_p5"]
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--dir", required=True)
ap.add_argument("--out", required=True)
ap.add_argument("--jobs", type=int, default=4)
ap.add_argument("--limit", type=int, default=0, help="stop after N files (smoke test)")
a = ap.parse_args()
# Dedupe by basename — the DL2 export keeps a byte-identical `Sent/`
# mirror of its root, which doubled two figures before it was caught.
seen, files = set(), []
for q in sorted(Path(a.dir).rglob("*")):
if q.is_file() and _HIST.search(q.name) and q.name not in seen:
seen.add(q.name)
files.append(str(q))
if a.limit:
files = files[:a.limit]
print(f"unique histogram binaries: {len(files)}", flush=True)
rows, undecodable = [], 0
with ProcessPoolExecutor(max_workers=a.jobs) as ex:
futs = [ex.submit(scan, f) for f in files]
for i, fut in enumerate(as_completed(futs), 1):
r = fut.result()
if r:
rows.extend(r)
else:
undecodable += 1
if i % 5000 == 0:
print(f" {i}/{len(files)}", flush=True)
with open(a.out, "w", newline="") as fh:
w = csv.DictWriter(fh, fieldnames=COLS)
w.writeheader()
w.writerows(rows)
files_ok = len({r["filename"] for r in rows})
units = len({r["serial"] for r in rows})
ivals = sum(r["n_intervals"] for r in rows) // 3
print(f"\ndecoded {files_ok}/{len(files)} files "
f"({undecodable} undecodable), {units} units, ~{ivals/1e6:.1f}M intervals")
print(f"wrote {a.out} ({len(rows)} channel-rows)")
if __name__ == "__main__":
main()
scratch/offset_scan.py
+171
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@@ -0,0 +1,171 @@
#!/usr/bin/env python3
"""Scan series-3 waveform binaries for the 'offset' hardware fault.
A healthy geophone trace is centred on zero. An offset unit sits displaced,
so the channel mean approaches its own peak. Detector (unchanged from the
2026-08-25 run, see memory note `offset-archive-analysis-backlog`):
dominant-axis |mean| / peak > 0.7
AND |mean| >= 0.9 * the unit's geo trigger level
Trigger level is read from a paired _ASCII.TXT where one exists, otherwise
from a per-serial median learned across that unit's ASCII files, otherwise
--default-trigger.
Serial is decoded from the BW filename: prefix letter encodes thousands
(chr(ord('B') + n)), next 3 digits the remainder -- T193 -> BE18193.
Usage:
python scratch/offset_scan.py --dir <path> [--jobs N] --out offsets.csv
"""
from __future__ import annotations
import argparse, csv, json, re, sys
from collections import defaultdict
from concurrent.futures import ProcessPoolExecutor, as_completed
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from minimateplus.event_file_io import read_blastware_file
from minimateplus.bw_ascii_report import parse_report
GEO = ("Tran", "Vert", "Long")
_GEO_FS_COUNTS = 32000.0
_WAVE_RE = re.compile(r"\.[A-Za-z0-9]{2}0[Ww]$")
_STEM_RE = re.compile(r"^([B-Z])(\d{3})")
MEAN_OVER_PEAK_MIN = 0.7
TRIGGER_FRACTION = 0.9
def serial_from_name(name: str):
m = _STEM_RE.match(name)
if not m:
return None
letter, digits = m.group(1), m.group(2)
return f"BE{(ord(letter) - ord('B')) * 1000 + int(digits)}"
def counts_to_ips(c, gr):
return c * (gr or 10.0) / _GEO_FS_COUNTS
def scan_one(path_str: str, default_trigger: float) -> dict | None:
p = Path(path_str)
try:
gr, trig = 10.0, None
ap = p.with_name(p.name.replace(".", "_", 1) + "_ASCII.TXT") \
if False else p.parent / (p.stem + "_" + p.suffix.lstrip(".") + "_ASCII.TXT")
if ap.exists():
rep = parse_report(ap.read_text(errors="replace"))
gr = rep.geo_range_ips or 10.0
trig = rep.geo_trigger_level_ips
ev = read_blastware_file(p)
s = ev.raw_samples or {}
if not all(s.get(c) for c in GEO):
return None
best = None
for ch in GEO:
arr = s[ch]
n = len(arr)
if n == 0:
continue
mean = sum(arr) / n
peak = max(abs(v) for v in arr)
if peak == 0:
continue
ratio = abs(mean) / peak
if best is None or peak > best["peak_counts"]:
best = {"channel": ch, "mean_counts": mean,
"peak_counts": peak, "ratio": ratio}
if best is None:
return None
ts = ev.timestamp
return {
"serial": serial_from_name(p.name) or "?",
"timestamp": (f"{ts.year:04d}-{ts.month:02d}-{ts.day:02d}T"
f"{ts.hour:02d}:{ts.minute:02d}:{ts.second:02d}") if ts else "",
"filename": p.name,
"channel": best["channel"],
"offset_ips": round(counts_to_ips(best["mean_counts"], gr), 4),
"peak_ips": round(counts_to_ips(best["peak_counts"], gr), 4),
"mean_over_peak": round(best["ratio"], 3),
"trigger_level_ips": trig if trig is not None else "",
"geo_range_ips": gr,
}
except Exception:
return None
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--dir", required=True)
ap.add_argument("--jobs", type=int, default=4)
ap.add_argument("--limit", type=int, default=0)
ap.add_argument("--default-trigger", type=float, default=0.2)
ap.add_argument("--out", required=True)
a = ap.parse_args()
# The DL2 export keeps a byte-identical `Sent/` mirror of the root, so
# enumerate paths but keep only the first occurrence of each basename —
# otherwise every event is counted twice.
seen = set()
files = []
for q in sorted(Path(a.dir).rglob("*")):
if q.is_file() and _WAVE_RE.search(q.name) and q.name not in seen:
seen.add(q.name)
files.append(q)
if a.limit:
files = files[: a.limit]
print(f"waveform binaries to scan: {len(files)}", flush=True)
rows = []
with ProcessPoolExecutor(max_workers=a.jobs) as ex:
futs = [ex.submit(scan_one, str(p), a.default_trigger) for p in files]
for n, f in enumerate(as_completed(futs), 1):
r = f.result()
if r:
rows.append(r)
if n % 2000 == 0:
print(f" {n}/{len(files)}", flush=True)
# learn per-serial trigger levels from the rows that had an ASCII
by_serial = defaultdict(list)
for r in rows:
if r["trigger_level_ips"] != "":
by_serial[r["serial"]].append(float(r["trigger_level_ips"]))
med = {}
for k, v in by_serial.items():
v.sort()
med[k] = v[len(v) // 2]
for r in rows:
if r["trigger_level_ips"] == "":
r["trigger_level_ips"] = med.get(r["serial"], a.default_trigger)
r["suspect"] = int(
r["mean_over_peak"] > MEAN_OVER_PEAK_MIN
and abs(r["offset_ips"]) >= TRIGGER_FRACTION * float(r["trigger_level_ips"])
)
cols = ["serial", "timestamp", "filename", "channel", "offset_ips", "peak_ips",
"mean_over_peak", "trigger_level_ips", "geo_range_ips", "suspect"]
with open(a.out, "w", newline="") as fh:
w = csv.DictWriter(fh, fieldnames=cols)
w.writeheader()
w.writerows(rows)
sus = [r for r in rows if r["suspect"]]
print(f"\nscanned {len(rows)} decodable waveforms")
print(f"suspect events: {len(sus)}")
per = defaultdict(int)
for r in sus:
per[r["serial"]] += 1
print(f"units with >=1 suspect event: {len(per)} of {len({r['serial'] for r in rows})}")
for s, n in sorted(per.items(), key=lambda x: -x[1])[:20]:
print(f" {s:10} {n}")
print(f"\nwrote {a.out}")
if __name__ == "__main__":
main()
scratch/offset_scan2.py
+108
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@@ -0,0 +1,108 @@
#!/usr/bin/env python3
"""Offset detector v2 — per-channel MEDIAN pedestal.
Supersedes the dominant-axis / mean detector in offset_scan.py, which had two
flaws that manufactured false "recoveries":
1. It scored only the axis with the largest peak, so a real event on one axis
hid a persistent pedestal on another. BE12599 2026-08-21 read "clean"
because Long had a 1.065 in/s event, while Tran sat at +0.47 in/s.
2. It used the MEAN, which a real transient perturbs. The median is the
resting baseline: most samples sit at it, so a blast does not move it.
Same event, Long: mean +0.0783 vs median -0.0050.
Flags a CHANNEL when |median| >= --floor in/s (default 0.025 = 5 A/D counts,
Instantel's own criterion; 1 A/D count = 0.005 in/s).
Emits one row per (event, channel) so persistence can be tracked per channel.
"""
from __future__ import annotations
import argparse, csv, re, statistics, sys
from concurrent.futures import ProcessPoolExecutor, as_completed
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from minimateplus.event_file_io import read_blastware_file
GEO = ("Tran", "Vert", "Long")
K = 10.0 / 32000.0 # ADC counts -> in/s at the 10 in/s range
_WAVE_RE = re.compile(r"\.[A-Za-z0-9]{2}0[Ww]$")
_STEM_RE = re.compile(r"^([B-Z])(\d{3})")
def serial_from_name(n):
m = _STEM_RE.match(n)
return f"BE{(ord(m.group(1))-ord('B'))*1000+int(m.group(2))}" if m else "?"
def scan_one(ps):
p = Path(ps)
try:
ev = read_blastware_file(p)
s = ev.raw_samples or {}
if not all(s.get(c) for c in GEO):
return None
ts = ev.timestamp
stamp = (f"{ts.year:04d}-{ts.month:02d}-{ts.day:02d}T"
f"{ts.hour:02d}:{ts.minute:02d}:{ts.second:02d}") if ts else ""
out = []
for ch in GEO:
a = s[ch]
out.append({
"serial": serial_from_name(p.name), "timestamp": stamp,
"filename": p.name, "channel": ch,
"median_ips": round(statistics.median(a) * K, 4),
"mean_ips": round(statistics.fmean(a) * K, 4),
"peak_ips": round(max(abs(v) for v in a) * K, 4),
})
return out
except Exception:
return None
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--dir", required=True)
ap.add_argument("--jobs", type=int, default=4)
ap.add_argument("--floor", type=float, default=0.025)
ap.add_argument("--out", required=True)
a = ap.parse_args()
seen, files = set(), []
for q in sorted(Path(a.dir).rglob("*")):
if q.is_file() and _WAVE_RE.search(q.name) and q.name not in seen:
seen.add(q.name); files.append(str(q))
print(f"unique waveform binaries: {len(files)}", flush=True)
rows = []
with ProcessPoolExecutor(max_workers=a.jobs) as ex:
for n, f in enumerate(as_completed([ex.submit(scan_one, p) for p in files]), 1):
r = f.result()
if r: rows.extend(r)
if n % 2000 == 0: print(f" {n}/{len(files)}", flush=True)
for r in rows:
r["offset"] = int(abs(r["median_ips"]) >= a.floor)
cols = ["serial","timestamp","filename","channel","median_ips","mean_ips","peak_ips","offset"]
with open(a.out, "w", newline="") as fh:
w = csv.DictWriter(fh, fieldnames=cols); w.writeheader(); w.writerows(rows)
from collections import defaultdict
ev_flagged = {(r["serial"], r["filename"]) for r in rows if r["offset"]}
ev_all = {(r["serial"], r["filename"]) for r in rows}
per = defaultdict(set)
for r in rows:
if r["offset"]: per[r["serial"]].add(r["filename"])
tot = defaultdict(set)
for r in rows: tot[r["serial"]].add(r["filename"])
print(f"\nfloor = {a.floor} in/s ({a.floor/0.005:.0f} A/D counts)")
print(f"events with >=1 offset channel: {len(ev_flagged)} of {len(ev_all)}")
print(f"units affected: {len(per)} of {len(tot)}")
for s in sorted(per, key=lambda s: -len(per[s])):
print(f" {s:9} {len(per[s]):4} / {len(tot[s]):4} events")
print(f"\nwrote {a.out}")
if __name__ == "__main__":
main()

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