v0.27.0 Decoder fixes, offset exploration and testing. #34
@@ -8,6 +8,84 @@ All notable changes to seismo-relay are documented here.
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---
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## v0.27.0 — 2026-08-28
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**Per-sample decoder verification at scale, plus the offset investigation.**
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The series-3 codec is now verified sample-by-sample against **14,338** preserved
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Blastware ASCII exports — 1,249 waveform and 13,089 histogram, spanning 45 units
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and files back to 2018. That is 11x the ground truth the production store
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carried, and it found one real codec bug (below).
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### Fixed
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- **Sub-minute histograms with a partial final block decoded to nothing**
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(`histogram_codec.detect_multi_interval_stride`). The stride search confirmed
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itself on a third block header whenever the body was long enough to hold one —
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but a body can exceed two strides and still contain only two real blocks, because
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a *partial* final block leaves trailing padding. BE18193 `T193L0XM.CI0H` (51
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intervals at 2 s = one full 30-interval block plus a 21-interval remainder, in a
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2787-byte body) therefore had its correct stride of 612 discarded and produced an
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empty decode. A missing third header now means end-of-stream rather than
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disqualification; the block-counter check, which is what actually prevents the
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false positives that once mis-dispatched 9,082 files, is unchanged.
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Found by decoding the full DL2 archive against its preserved Blastware ASCII
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exports. Across **63,535 unique** histogram binaries the fix recovers **4 files** —
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`K440HJCN.3C0H` and `K557IF1U.8K0H` (stride 252), `T191HVNP.0S0H` (92) and
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`T193L0XM.CI0H` (612) — with **zero** files regressed. Verification over all
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14,340 archive pairs goes 14,337 → 14,338 exact, the only remainder being two
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series-4 IDF files that belong to a different codec.
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(The DL2 export keeps a byte-identical `Sent/` mirror of its root, so a naive
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walk double-counts every binary — 127,035 paths are 63,535 distinct files. The
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ASCII exports are *not* mirrored, so the 14,340 pair count is already distinct.)
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⚠ Prod stores hold `.h5` files generated before this fix. Those 4 events stay
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empty until `backfill_sidecars.py` is re-run — not worth a two-hour prod backfill
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on its own; fold it into the next one.
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- **Histogram/waveform twin matching is now interval-based** (`find_twins`). A real
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trigger is recorded twice — as a triggered waveform (stamped at the trigger instant)
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and inside the scheduled histogram whose interval contains it (stamped at the 7am/7pm
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interval start) — so the two twins can be **hours apart**. The old ±5-minute window
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silently missed them, which broke review propagation (flagging one twin didn't flag its
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twin). Twins are now matched by same serial + identical `peak_vector_sum` + opposite
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record type + the waveform falling within the histogram's interval (bounded by the next
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same-serial histogram). `window_seconds` is retained but ignored. Fixes terra-view #102
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sub-task 2.
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- **`/health` reported a hard-coded `0.1.0`** instead of the real service version.
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`sfm/server.py` now derives its version from `minimateplus.event_file_io.TOOL_VERSION`,
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making that constant the single source of truth for the service version and the
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sidecar stamp alike — one place to bump at release.
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- **`CLAUDE.md` had 793 NUL bytes appended** after its last line, which made `grep`
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treat the file as binary and silently skip it. Present since at least v0.21.0.
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Stripped.
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### Added
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- **`docs/offset_investigation.md`** — a dated journal of the "offset" hardware
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fault: base rate, detector design, per-unit case files, ruled-out hypotheses
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(each kept with the evidence that killed it), and Instantel's own autozero
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procedure with its 2027–2069 acceptance window.
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- **`scratch/verify_against_ascii.py`** — decodes a corpus of BW binaries and
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diffs every sample against the paired `_ASCII.TXT`. Includes a saturation
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carve-out: BW clamps clipped events to the range maximum and writes `OORANGE`,
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while the decoder faithfully reports counts past nominal full scale.
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- **`scratch/offset_scan3.py`** — offset detector. Measures the resting floor in
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the *pre-trigger* window (definitionally quiet) and requires it to hold across
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pre / middle / end. Result: **5 of 45 units (11%)**, stable across a 2x
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threshold range. Supersedes `offset_scan.py` and `offset_scan2.py`, both kept
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as the reasoning trail.
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### Verified
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- **19,244 healthy channel-events sit at a pre-trigger floor of exactly 0.000
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(62.7%), 94.5% within ±1 quantisation unit, median +0.0000.** No systematic
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zero-point bias in the decoder — an independent confirmation of the
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32000-count geo full scale, arrived at from a different direction than the
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ASCII sample comparisons.
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---
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## v0.26.0 — 2026-08-27
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**Series-3 decode correctness.** Two body-model rewrites, a systematic
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@@ -2,21 +2,24 @@
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Ground-up Python replacement for **Blastware**, Instantel's Windows-only software for
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managing MiniMate Plus seismographs. Connects over direct RS-232 or cellular modem
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(Sierra Wireless RV50 / RV55). Current version: **v0.26.0**.
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(Sierra Wireless RV50 / RV55). Current version: **v0.27.0**.
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---
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## Where things stand (updated 2026-08-27)
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## Where things stand (updated 2026-08-28)
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Read this first when picking the project back up.
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- **Series-3 decode is correct and verified.** All 11,603 series-3 binaries in
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the prod snapshot pass every check (channel lengths, peaks vs the device's
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own reported PPV, nothing above full scale, length vs declared record time).
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Ground truth: 1,211/1,211 histograms exact per-interval and 75/75 waveform
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sample counts exact against preserved Blastware ASCII exports.
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⚠ That is per-sample proof on 11% of files and peak-only consistency on the
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other 89% — see `docs/instantel_protocol_reference.md` §7.6.1.
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- **Series-3 decode is verified per-sample at scale (v0.27.0).** The full DL2
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archive decodes **14,338 / 14,338** paired files exactly against their
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preserved Blastware ASCII exports — 1,249 waveform + 13,089 histogram, 45
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units, files back to 2018. That is 11x the ground truth the prod store
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carried, and it supersedes the old "per-sample on 11%, peak-only on 89%"
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caveat. Harness: `scratch/verify_against_ascii.py` (note its saturation
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carve-out — BW clamps clipped events, the decoder reports true counts).
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Independent corroboration of the 32000-count scale: 19,244 healthy
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channel-events sit at a pre-trigger floor of exactly 0.000 (62.7%), 94.5%
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within ±1 quantisation unit, median +0.0000 — no zero-point bias.
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- **Series-4 (Thor / Micromate) is NOT verified.** UM-series sits at ~48%
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against device peaks with a ~1.7% systematic bias and a near-zero tail.
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Thor IDFW is pinned to `decode_waveform_legacy` deliberately.
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@@ -24,11 +27,23 @@ Read this first when picking the project back up.
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(= 10.0/1.25) units discrepancy; `scripts/backfill_sidecars.py --force` also
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inserts DB rows for store files that have none (one-time per store) and the
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dry-run does not report that count.
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- **After any codec change, regenerate the store** — `backfill_sidecars.py
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--force` then `backfill_event_shape.py`, DB backup first. Stored `.h5` files
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do not update themselves.
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- **Parked:** the "offset" hardware-fault investigation (Appendix E of the
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protocol reference) pending the multi-year BW archive.
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- **After any codec change, regenerate the store** — `backfill_sidecars.py`
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then `backfill_event_shape.py`, DB backup first. Stored `.h5` files do not
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update themselves. No `--force` needed as long as `TOOL_VERSION` was bumped
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(it gates regeneration). ⚠ On the office NAS this takes **~2 hours**
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(~1.5 files/sec vs 85/sec on the dev box — gzip-4 in `sfm/event_hdf5.py`
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against a Synology CPU). Budget it up front.
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**v0.27.0 owes prod a backfill:** the partial-final-block fix recovers 4
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histograms that are still empty in the store.
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- **The "offset" hardware fault has its own journal** --
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`docs/offset_investigation.md`. **5 of 45 units (11%)**, and the fault is
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**persistent** — it stays until the geophone is serviced. Detect it with
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`scratch/offset_scan3.py`: the resting floor in the **pre-trigger** window,
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required to hold across pre/middle/end. Never score only the dominant-peak
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axis and never use the mean — both produce false recoveries (see the
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retraction banner in the journal). Instantel's autozero procedure and its
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2027-2069 acceptance window are recorded there too. Best open lead is
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`SUB 0x0E` (unimplemented), which may carry those very numbers.
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When new information about the protocol is discovered, please update the instantel_protocol_reference.md with the findings in addition to this document
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@@ -1803,4 +1818,4 @@ body) because writing a dial string may require DLE escaping for embedded contro
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To parse BW TX captures: use `bridges/captures/` scripts or adapt the `find_write_frames()` pattern
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in `/tmp/analyze_write_payload.py` — it correctly handles `0x10 0x03` DLE-escaped ETX bytes
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inside write frame data (the naive parser terminates early at the escaped `0x03`).
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inside write frame data (the naive parser terminates early at the escaped `0x03`).
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@@ -1,4 +1,4 @@
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# seismo-relay `v0.26.0`
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# seismo-relay `v0.27.0`
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A ground-up replacement for **Blastware** — Instantel's aging Windows-only
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software for managing seismographs. Supports both the **MiniMate Plus
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@@ -3524,6 +3524,11 @@ of them was, for a while.
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### E.1 The "offset" fault
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> **The full investigation now lives in `docs/offset_investigation.md`** --
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> base rate, detector definition, per-unit case files, ruled-out hypotheses,
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> and Instantel's own autozero procedure with its 2027-2069 acceptance
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> window. This appendix is kept as the protocol-side summary.
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**Symptom.** One geophone channel's baseline steps away from zero and
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stays there. The trace still carries the real AC signal, but it rides
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on a DC pedestal of a few tenths of an in/s. Operators call this an
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@@ -0,0 +1,514 @@
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# The "offset" fault — investigation journal
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> ## ⚠ CORRECTED 2026-08-28 (same day) — the v1 detector was wrong
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>
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> Brian pushed back on the finding that offsets "come and go": in the field,
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> once a unit develops one it stays broken until the geophone is replaced.
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> He was right, and the challenge exposed **two real flaws** in the v1 detector:
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>
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> 1. **It scored only the axis with the largest peak.** A real event on one axis
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> hid a persistent pedestal on another. BE12599 on 2026-08-21 read "clean"
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> solely because Long had a 1.065 in/s event — Tran was sitting at
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> **+0.4732 in/s** at that moment and was never examined.
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> 2. **It used the MEAN**, which a real transient perturbs. The **median** is the
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> resting baseline — most samples sit at it, so a blast does not move it.
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> Same event, Long channel: mean **+0.0783** vs median **-0.0050**.
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>
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> Both flaws manufactured false recoveries. The corrected detector
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> (`scratch/offset_scan2.py`, per-channel median) shows the pedestal is
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> **persistent**, exactly as the field experience says. See §2b and §3b.
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>
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> **Then Brian proposed a better detector still** — measure the floor during
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> the *pre-trigger* window, and require it to hold across pre/middle/end.
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> That is now the detector of record (§2c). Final answer: **5 of 45 units
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> (11%)**, stable across a 2x threshold range.
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>
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> Sections below that were written against v1 are marked; v1 numbers are kept
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> for the reasoning trail, not as current fact.
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A running record of the **offset** hardware fault on Instantel Series III
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seismographs: a geophone channel whose trace sits displaced from zero rather
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than centred on it.
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This is a *journal*, not a spec. Findings are dated, dead ends are kept with
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the reason they died, and every number says where it came from. When something
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here is superseded, strike it and say why rather than deleting it — the point
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is that a future session can tell what was actually established from what was
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merely believed at the time.
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Companion material:
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- `scratch/offset_scan.py` — the detector
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- `scratch/verify_against_ascii.py` — decoder verification harness
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- `docs/instantel_protocol_reference.md` — wire protocol, incl. the
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unimplemented `SUB 0x0E` this investigation now wants
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---
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## TL;DR (current state, 2026-08-28)
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- **It is real device data, not a decode bug.** Settled early and confirmed
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against Blastware's own ASCII exports.
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- **Base rate: 5–6 of 45 units (11–13%)** across the full DL2 archive,
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2018–2026. This *confirms* the earlier 2-of-21 (9.5%) estimate from the much
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smaller Terra-View DB — survivorship bias from deleted events had **not**
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concealed a wave of cases.
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- **The fault is bimodal, not a drift continuum.** A unit is either clean or
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grossly off. Loosening the amplitude threshold 11× adds no new units.
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- **The unit's own sensor check cannot see it.** 102 offset events, zero
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sensor-check failures. Do not try to use it as a screen.
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- **Cause is still unsettled.** Instantel's autozero fixes the minority of
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cases; the rest are hardware. We cannot yet tell which is which remotely.
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- **Best open lead:** `SUB 0x0E` (channel sensor data, 8 channels × 10 bytes,
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unimplemented) may carry the very numbers Instantel says to check against
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**2027–2069**. Untested.
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---
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## 1. What the fault looks like
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A healthy geophone trace is centred on zero. An offset channel is parked away
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from zero, so the channel **mean approaches its own peak**. In Blastware the
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signature is "parallel lines above or below the zero line" (Instantel's own
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wording).
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Consequences observed in the field:
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- The unit can **self-trigger on its own offset** when the displacement exceeds
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the geo trigger level, producing streams of junk events with no ground
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motion. Instantel has a separate FAQ for this symptom (13-0-22, *"Unit
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triggers continuously without activity"*).
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- Recorded PPV for that channel is meaningless while the fault persists.
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---
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## 2. The detector
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Implemented in `scratch/offset_scan.py`. Operates on raw BW binaries only — no
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DB, no sidecars.
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```
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for each series-3 waveform binary:
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decode -> per-channel ADC counts
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dominant axis = channel with the largest |peak|
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flag when |mean| / peak > 0.70
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and |mean| >= 0.90 x the unit's geo trigger level
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episodes = per-serial runs of flagged events, split on a >12 h gap
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```
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Why each term:
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| term | purpose |
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|---|---|
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| `\|mean\|/peak > 0.7` | the discriminator. A DC-parked trace has mean ≈ peak. |
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| `\|mean\| >= 0.9 × trigger` | amplitude floor — suppresses quiet traces where mean and peak are both tiny and the ratio is meaningless. |
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| dominant axis only | the fault is per-channel; scoring all three dilutes it. |
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| 12 h episode gap | separates deployments/visits rather than counting events. |
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Trigger level comes from a paired `_ASCII.TXT` when one exists, else the
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per-serial median learned from that unit's ASCII files, else 0.2 in/s.
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**Known limitation.** Event traces contain real ground motion, so this can only
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see offsets large enough to *dominate* the trace. A mild offset on a real blast
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is invisible. Instantel's A/D-mode check (§5) is the only thing that sees the
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mild end. Our base rate is therefore a **gross-offset** rate.
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### 2b. Detector v2 — per-channel median (CURRENT)
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`scratch/offset_scan2.py`. Supersedes the above.
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```
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for each series-3 waveform binary:
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for each geo channel independently:
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pedestal = median(samples) # resting baseline, robust to blasts
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flag the CHANNEL when |pedestal| >= 0.025 in/s (5 A/D counts)
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a unit has a real fault when a channel is flagged on >=3 CONSECUTIVE events
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```
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Why median: a DC pedestal shifts every sample, so it moves the median. A real
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event moves only a minority of samples, so it does not. This removes the need
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for the `m/p` ratio guard entirely — that guard existed only to compensate for
|
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using the mean.
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Why per-channel: the fault is on one geophone axis. Scoring only the dominant
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axis means any event with motion elsewhere hides it.
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Why "3 consecutive": the 0.025 in/s floor is only ~2x a healthy channel's
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resting median (observed 0.010-0.015), so isolated flags are noise. Persistence
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is the discriminator — and it is what the field experience predicts.
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---
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## 3b. Archive results, corrected (v2)
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| | v1 (dominant axis, mean) | **v2 (per-channel median)** |
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|---|---|---|
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| units with any flagged event | 6 of 45 | 19 of 45 |
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| **units with a sustained pedestal (>=3 consecutive)** | — | **8 of 45 (18%)** |
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| runs of >=3 consecutive | — | 29 |
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| runs of 1-2 events (noise) | — | 69 |
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Units with a sustained pedestal: **BE9558, BE10895, BE11007, BE11529, BE12599,
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BE13117, BE18003, BE18438**. BE10895 and BE18003 were invisible to v1.
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**The affected channel is most often Vert**, which v1 got wrong — it named
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whichever axis had the largest peak. BE13117 and BE18438 are both Vert faults.
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Longest / clearest runs:
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| unit | ch | span | events | median in/s |
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|---|---|---|---|---|
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| BE13117 | Vert | 2023-05-03 → 05-04 | 194 | 0.035 → **1.915** |
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| BE18438 | Vert | 2026-02-25 → 02-26 | 75 | 0.180 → 0.370 |
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| BE9558 | Vert | 2020-02-11 (6 h) | 33 | 0.065 → 0.090 |
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| BE12599 | Tran | 2026-08-14 → 08-23 | 8 | 0.030 → **0.565** |
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| BE18003 | Vert | 2021-03-17 → 06-11 | 3 | 0.040 → 0.060 |
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BE12599 began **2026-08-14**, not 08-17 as v1 reported, and was still faulting
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at the last event in the archive.
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### 2c. Detector v3 — PRE-TRIGGER floor + constant-floor test (CURRENT)
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|
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`scratch/offset_scan3.py`. Brian's method, and better than v2 for a reason
|
||||
worth naming: **the pre-trigger window is definitionally quiet** — it is the
|
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buffer captured before the trigger fired — whereas a whole-record median is
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merely *robust* to the event. `pretrig_samples` comes from the STRT record.
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||||
```
|
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per channel:
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pre = median of the first pretrig_samples samples
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mid = median of the middle third
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end = median of the final third
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spread = max(pre,mid,end) - min(pre,mid,end)
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|
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offset when |pre| >= floor AND spread <= 0.02 in/s
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real fault when a channel is flagged on >=3 CONSECUTIVE events
|
||||
```
|
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|
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A DC offset is a **constant floor** — present before the trigger, during, and
|
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after. The spread test rejects transients (settling, handling, a long event
|
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tail) that move one segment relative to the others, which is what v2's
|
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whole-record median could not do.
|
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|
||||
**The empirical noise floor justifies the threshold.** Across 19,244
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||||
non-flagged channel-events the pre-trigger floor distributes as:
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|
||||
| floor | share |
|
||||
|---|---|
|
||||
| −1 unit (−0.005) | 18.4% |
|
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| **0.000** | **62.7%** |
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| +1 unit (+0.005) | 13.4% |
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|
||||
**94.5% within ±1 quantisation unit; median exactly +0.0000, mean −0.0008.**
|
||||
So there is **no systematic zero-point bias in the decoder** — an independent
|
||||
confirmation of the 32000-count scale. A healthy channel really does read
|
||||
0.000, and "any constant floor that is not 0.000" is the right signal, with
|
||||
±1 unit of slack for quantisation.
|
||||
|
||||
**The result is threshold-insensitive**, which is what distinguishes a real
|
||||
signal from a tuned one:
|
||||
|
||||
| floor | units flagged | sustained units |
|
||||
|---|---|---|
|
||||
| 2 units (0.010) | 34 | 15 ← into the noise |
|
||||
| 3 units (0.015) | 26 | 8 |
|
||||
| **4 units (0.020)** | 17 | **5** |
|
||||
| **5 units (0.025)** — Instantel's | 12 | **5** |
|
||||
| **8 units (0.040)** | 8 | **5** |
|
||||
|
||||
### FINAL RESULT: 5 of 45 units (11%)
|
||||
|
||||
**BE9558, BE11529, BE12599, BE13117, BE18438.**
|
||||
|
||||
Unchanged across a 2x threshold range. BE11007 and BE10895 drop out — the
|
||||
spread test identifies them as transients, not pedestals.
|
||||
|
||||
The 11% headline happens to match v1's, but the reasoning and the unit list
|
||||
differ: v1 included BE11007 and named the wrong *channel* on most units.
|
||||
|
||||
---
|
||||
|
||||
## 3. Archive results (2026-08-28)
|
||||
|
||||
Source: DL2 event export, 6,577 **unique** series-3 waveforms, 45 units.
|
||||
See [`dl2-archive`](#8-data-and-tooling) for the `Sent/` mirror trap.
|
||||
|
||||
**283 suspect events, 15 episodes, 6 of 45 units (13.3%).**
|
||||
Excluding BE11007 (§4, likely not an offset at all): **5 of 45 = 11.1%**.
|
||||
|
||||
### Threshold sensitivity — the bimodality result
|
||||
|
||||
Re-scoring the same corpus at a range of amplitude floors, with two
|
||||
ratio cut-offs (1 A/D count = 0.005 in/s, see §5):
|
||||
|
||||
| \|offset\| floor | m/p > 0.7 | m/p > 0.9 |
|
||||
|---|---|---|
|
||||
| 5 cts (0.025 in/s) — *Instantel's own* | 333 ev / 6 units | 279 ev / **5 units** |
|
||||
| 10 cts (0.050) | 294 / 6 | 274 / 5 |
|
||||
| 20 cts (0.100) | 250 / 5 | 244 / 4 |
|
||||
| 40 cts (0.200) | 209 / 5 | 203 / 4 |
|
||||
| 80 cts (0.400) | 152 / 4 | 148 / 2 |
|
||||
| 160 cts (0.800) | 144 / 2 | 141 / 1 |
|
||||
|
||||
Relaxing the floor by 11× (0.27 → 0.025 in/s) adds ~14% more events and **no
|
||||
new units**. There is no population of mild offsets hiding below our threshold
|
||||
*in event data*. Either a unit is clean or it is grossly off.
|
||||
|
||||
---
|
||||
|
||||
## 4. Per-unit case files
|
||||
|
||||
Ordered by severity. `m/p` medians are on the offending channel.
|
||||
|
||||
### BE13117 — one violent day, never again
|
||||
`145 / 454 events (32%)`, **1 episode**, 2023-05-04, 6.8 h.
|
||||
Offset climbed **0.393 → 1.875 in/s within the episode**. `m/p` median
|
||||
**0.996** — the trace is almost pure DC. No recurrence in the rest of its 454
|
||||
events. No ASCII files in the archive, so no calibration history.
|
||||
|
||||
### BE18438 — recurring, months apart
|
||||
`87 / 293 (30%)`, **2 episodes**: 2025-11-15 (1.2 h, n=12, 0.279 → 0.369) and
|
||||
2026-02-25 (**28.8 h**, n=75, 0.183 → 0.366). `m/p` median 0.967.
|
||||
Clean across all 196 events preceding its 2025-08-12 calibration.
|
||||
|
||||
### BE9558 — six years apart
|
||||
`38 / 196 (19%)`, **4 episodes**: 2020-02-11 (6.3 h, n=33, but only
|
||||
0.068 → 0.086 — very mild), then 2026-04-14, 2026-04-29, 2026-05-04
|
||||
(0.28–0.45). `m/p` median 0.919. Calibrated 2026-06-26; 0/7 events flagged
|
||||
after, but n=7 is far too small to call it fixed.
|
||||
|
||||
### BE12599 — the live case ⚠
|
||||
`6 / 77 (8%)`, **6 single-event episodes, one per day at exactly 05:00**,
|
||||
2026-08-17 → 2026-08-23. Offset rose 0.383 → 0.565 then fell back to 0.345.
|
||||
`m/p` ≈ 0.965, geo trigger 0.3 in/s — **the offset exceeds the trigger level,
|
||||
so the unit is triggering on its own fault**. Last calibrated 2025-08-12.
|
||||
|
||||
This is the most recent and the most useful: a currently-faulting unit is the
|
||||
natural experiment for the re-zero-vs-repair question (§7).
|
||||
|
||||
### BE11529 — marginal
|
||||
`4 / 99 (4%)`, 1 episode 2025-07-08, 0.4 h, offsets only 0.051 → 0.058 in/s.
|
||||
`m/p` median 0.959, so DC-dominated, but the magnitude is near the noise of
|
||||
this method. Treat as unconfirmed.
|
||||
|
||||
### BE11007 — probably NOT an offset
|
||||
`3 / 70 (4%)`, 1 episode 2022-01-17, offsets 5.500 → 6.904 in/s — by far the
|
||||
largest. But `m/p` is only **0.719–0.738** against ≥0.9 for every other unit,
|
||||
and the peaks are 7.6–9.4 in/s on a 10 in/s range. That reads as a **large
|
||||
real blast with asymmetric ground motion**, not a parked trace. Excluded from
|
||||
the headline base rate.
|
||||
|
||||
---
|
||||
|
||||
## 5. Instantel's own procedure and thresholds
|
||||
|
||||
From two Instantel technical-support FAQs supplied 2026-08-28
|
||||
(answers **13-0-21** *"How to determine offsets"* and **12-0-10** *"Removing
|
||||
offsets on an Instantel Series III monitor"*; created 2008/2007, last updated
|
||||
2009-03-06).
|
||||
|
||||
### Identifying (13-0-21)
|
||||
|
||||
1. Create or use an event with the **manual minimum trigger** set for the
|
||||
connected geophone and microphone — i.e. an event that recorded no real data.
|
||||
2. Save it and open in Blastware.
|
||||
3. An offset shows as **parallel lines above or below the zero line**.
|
||||
4. Put the unit in **A/D mode** — on Series III, press and hold `OPTION`, then
|
||||
press `START MONITOR`.
|
||||
5. **Display counts higher than 5**, with no vibration or overpressure present,
|
||||
indicate an offset.
|
||||
|
||||
### Removing — the autozero (12-0-10)
|
||||
|
||||
1. Be in a **quiet area with low vibration**.
|
||||
2. Power on the Blastmate III / Minimate Plus.
|
||||
3. Connect the geophone and microphone — **LINEAR mic only**.
|
||||
⚠ *Do not connect an "A" weight microphone, regardless of what the monitor
|
||||
displays.*
|
||||
4. Press `Test`.
|
||||
5. Wait for the **Sensor Check** results to appear.
|
||||
6. Press `OPTION` and `START MONITOR` **simultaneously**.
|
||||
7. `Performing Autozero` appears; press `Enter`.
|
||||
8. Confirm the sensors are properly connected; press `Enter`.
|
||||
9. Wait for the autozero to complete.
|
||||
10. Press `Enter` twice → Main Menu, *Ready To Monitor*, offset corrected.
|
||||
|
||||
### The go/no-go number — 2027 to 2069
|
||||
|
||||
> When you perform an Autozero on any Series III unit, the lists of numbers in
|
||||
> the **X1 and X8 gains should all be between 2027 and 2069**. If not, repeat
|
||||
> the Autozero. **If the numbers are extremely out of the specified range, then
|
||||
> the unit should be sent in for repair.**
|
||||
>
|
||||
> If this process does not remove the offset problem, return the unit **and
|
||||
> sensors** to Instantel for repair.
|
||||
|
||||
This is the documented explanation for the field experience (Brian's dad,
|
||||
2026-08-28) that **a re-zero works maybe 10% of the time** — the autozero only
|
||||
recovers units whose zero reference is still near-correct.
|
||||
|
||||
### Scale derivation (inference, well-supported — not proven)
|
||||
|
||||
2048 is 12-bit midscale. Our codec's geo full scale is 32000 internal counts =
|
||||
10 in/s, with 1 decoder unit = 16 counts = exactly 0.005 in/s
|
||||
(`geo-full-scale-is-32000-counts`). ±2000 A/D counts about 2048 therefore maps
|
||||
to ±10 in/s at **0.005 in/s per A/D count**. That makes:
|
||||
|
||||
- Instantel's ">5 counts" threshold ≈ **0.025 in/s**
|
||||
- the 2027–2069 window = **±21 counts = ±0.105 in/s** of tolerated zero error
|
||||
|
||||
Consistent and mutually corroborating, but we have not confirmed the A/D-count
|
||||
scale directly from a device reading.
|
||||
|
||||
---
|
||||
|
||||
## 6. Ruled out — keep these dead
|
||||
|
||||
### Condensation / humidity — DEAD (2026-08-25)
|
||||
Proposed, then killed by its own controls: BE18438 stayed flat across a 10-hour
|
||||
overnight gap, and only 2 of 21 units showed the fault while 19 sat in the same
|
||||
weather. The apparent "diurnal cycle" was an artifact of binning by hour-of-day
|
||||
across two days. See `waveform-dc-offset-is-real-device-data`.
|
||||
|
||||
### Clipping as a false-positive source — RULED OUT (2026-08-28)
|
||||
A rail-hitting trace would fake an offset (mean → peak). It isn't happening:
|
||||
median suspect peak is only **10% of full scale**, p90 is 18.6%. Only BE11007's
|
||||
3 events exceed 50% FS, and none reach 98%.
|
||||
|
||||
### The sensor check as a predictor — DOES NOT WORK (2026-08-28)
|
||||
Tested on 102 offset events across 4 units:
|
||||
|
||||
| unit | state | n | failed | median ratio | median freq |
|
||||
|---|---|---|---|---|---|
|
||||
| BE11529 | offset | 4 | **0** | 3.90 | 7.6 |
|
||||
| BE11529 | clean | 14 | 0 | 3.80 | 7.5 |
|
||||
| BE12599 | offset | 6 | **0** | 4.00 | 7.4 |
|
||||
| BE12599 | clean | 13 | 0 | 4.00 | 7.6 |
|
||||
| BE18438 | offset | 87 | **0** | 3.70 | 7.6 |
|
||||
| BE18438 | clean | 25 | 0 | 3.80 | 7.5 |
|
||||
| BE9558 | offset | 5 | **0** | 3.90 | 7.8 |
|
||||
| BE9558 | clean | 44 | 0 | 3.80 | 7.5 |
|
||||
|
||||
Zero failures on either side and indistinguishable ratios/frequencies. The
|
||||
swing test measures geophone frequency response and damping — it never examines
|
||||
DC zero. **A grossly offset unit passes its own self-check.** This is why the
|
||||
fault goes unnoticed until somebody looks at waveforms.
|
||||
|
||||
### "Offsets are transient / come and go on their own" — RETRACTED 2026-08-28
|
||||
v1 reported episodes lasting hours that ended spontaneously. **This was an
|
||||
artifact of the v1 detector** (see the banner at the top). With the per-channel
|
||||
median, the pedestal persists. Every clear case reads clean again only after a
|
||||
multi-day-to-multi-month gap consistent with service: BE13117 6 days, BE18438
|
||||
24 days, BE9558 63 days **with a confirmed Instantel calibration inside the
|
||||
gap**. BE12599 never reads clean — it is still faulting at the end of the
|
||||
archive. This matches the operational experience: once a unit develops an
|
||||
offset it stays broken until the geophone is replaced.
|
||||
|
||||
### "Offsets develop N months after calibration" — CONFOUNDED, NOT A FINDING
|
||||
Tempting, and it looked strong:
|
||||
|
||||
| unit | suspect before latest cal | after |
|
||||
|---|---|---|
|
||||
| BE18438 | 0 / 196 | 87 / 97 |
|
||||
| BE12599 | 0 / 62 | 6 / 15 |
|
||||
| BE11529 | 0 / 82 | 4 / 17 |
|
||||
| BE9558 | 38 / 189 | 0 / 7 |
|
||||
|
||||
But bucketing suspects by months-since-calibration gives **one unit per bucket**:
|
||||
`0–3mo={BE11529}`, `3–6 & 6–9mo={BE18438}`, `9–12mo={BE9558}`,
|
||||
`12–15mo={BE12599}`. The apparent "51% failure rate at 6–9 months" is entirely
|
||||
BE18438's single February 2026 episode. Five units with roughly one episode
|
||||
each cannot support a population trend. **Do not re-derive this.**
|
||||
|
||||
Also note: all affected units are calibrated on a **~12–13 month cadence**, so
|
||||
"sent to Instantel" is the routine annual schedule, not evidence of a
|
||||
fault-driven return.
|
||||
|
||||
---
|
||||
|
||||
## 7. Open questions
|
||||
|
||||
### Q1 — Is it a latched bad zero or analog degradation?
|
||||
The question that decides everything. A latched zero is correctable (possibly
|
||||
over the wire); degradation means a repair. Instantel's 2027–2069 rule implies
|
||||
*both* populations exist, with the split roughly 10/90 in the field.
|
||||
|
||||
**BE12599 is the natural experiment** — faulting as of 2026-08-23. Read its
|
||||
values, run the autozero, read them again.
|
||||
|
||||
### Q2 — Can we read the autozero numbers over the wire? (best lead)
|
||||
Instantel says to check *"the lists of numbers in the **X1 and X8 gains**"* —
|
||||
4 sensors × 2 gains = **8 channels**. The protocol reference already documents
|
||||
an unimplemented command with exactly that shape:
|
||||
|
||||
```
|
||||
SUB 0x0E -> RSP 0xF1 "channel sensor data"
|
||||
2-step read; channel selector in params[6:8] = 0x0000..0x0007
|
||||
data length 0x0A (10 bytes) per channel
|
||||
```
|
||||
|
||||
Blastware's *Unit Channel Test* sequence:
|
||||
`POLL×N → 0x15 → 0x01 → 0x08 → 0x01 → 0x0E×8 → 0x98×2 → 0x0E×8`
|
||||
— note the **second `0x0E` pass carries live ADC readings**.
|
||||
|
||||
**Hypothesis (untested):** `0x0E` returns the numbers Instantel wants compared
|
||||
against 2027–2069. If true, SFM could diagnose an offset remotely *and* predict
|
||||
whether a re-zero will succeed — converting a 10%/90% shipping gamble into a
|
||||
decision made before packing a box.
|
||||
|
||||
**How to test.** `bridges/ach_mitm.py` is a generic TCP proxy:
|
||||
|
||||
```bash
|
||||
python bridges/ach_mitm.py --bw-host <MODEM_IP> --bw-port 9034 --listen-port 9999
|
||||
```
|
||||
|
||||
Point Blastware at the proxy and run **Unit Channel Test**.
|
||||
⚠ In this topology the output filenames are reversed — the tool labels the
|
||||
*connecting* side "unit", so `raw_s3_*.bin` holds Blastware's bytes and
|
||||
`raw_bw_*.bin` the unit's.
|
||||
|
||||
Capture priority: (1) BE12599 while faulting, (2) a known-good unit as control,
|
||||
(3) before/after an autozero on the same unit. Eight 10-byte payloads with an
|
||||
expected value near 2048 is a very constrained puzzle.
|
||||
|
||||
### Q3 — What is the mild-offset rate?
|
||||
Unmeasurable from event files (§2). Only the A/D-mode check sees it. Would
|
||||
need a fleet sweep in A/D mode, or Q2 to succeed.
|
||||
|
||||
### Q4 — Does an offset recur on the same unit after service?
|
||||
BE9558 shows episodes in 2020 and 2026; BE18438 twice in four months. Suggestive
|
||||
of recurrence, but service records aren't in the data — only calibration dates.
|
||||
|
||||
---
|
||||
|
||||
## 8. Data and tooling
|
||||
|
||||
| what | where |
|
||||
|---|---|
|
||||
| detector | `scratch/offset_scan.py` |
|
||||
| current results | `/home/serversdown/dl2-archive/offset_archive.csv` |
|
||||
| earlier candidate list (Terra-View DB, 274 events) | `scratch/offset_candidates.csv` |
|
||||
| archive working copy | `/home/serversdown/dl2-archive/files/` |
|
||||
| archive source | NAS `DeathStar` 10.0.0.2, `/volume1/Uploads/TMI/DL2-Event-backup-8-25-26/Event/autocall home/` |
|
||||
|
||||
⚠ **The DL2 export keeps a byte-identical `Sent/` mirror of its root.** 13,077
|
||||
waveform paths are 6,577 distinct files. Always dedupe by basename — this
|
||||
doubled two reported figures before it was caught.
|
||||
|
||||
---
|
||||
|
||||
## 9. Chronology
|
||||
|
||||
| date | event |
|
||||
|---|---|
|
||||
| 2026-08-25 | Reported as a *waveform decode bug* — traces with a DC offset. Investigation shows the offset is **real device data**; the decoder is correct. |
|
||||
| 2026-08-25 | Brian relays his dad's description: a known hardware fault called an "offset"; usually sent to Instantel. |
|
||||
| 2026-08-25 | First detection pass over the Terra-View DB: **2 of 21 units**, 274 events, 11 months. Flagged as vulnerable to survivorship bias — flooded events were routinely deleted. |
|
||||
| 2026-08-25 | Condensation hypothesis proposed, then **killed by its own controls**. |
|
||||
| 2026-08-25 | Parked pending the multi-year archive. |
|
||||
| 2026-08-28 | DL2 archive pulled (33 GB, 546k files; 6.6 GB working set). |
|
||||
| 2026-08-28 | Archive scan: **6 of 45 units**, 283 events, 15 episodes. Prior base rate **confirmed**, not overturned. |
|
||||
| 2026-08-28 | Clipping ruled out; `m/p` established as the discriminator; BE11007 reclassified as probably a real blast. |
|
||||
| 2026-08-28 | Calibration-timing correlation attempted and **rejected as confounded**. |
|
||||
| 2026-08-28 | Instantel FAQs supplied: autozero procedure, the **2027–2069** window, the **>5 counts** threshold. Explains the ~10% re-zero success rate. |
|
||||
| 2026-08-28 | Bimodality established; sensor check proven **blind** to offsets; `SUB 0x0E` identified as the best open lead. |
|
||||
| 2026-08-28 | **v1 detector retracted.** Brian challenged the "come and go" finding against field experience. Two flaws found: dominant-axis-only scoring and mean-instead-of-median. Corrected detector shows persistent pedestals on **8 of 45 units**, and the gaps are service windows. |
|
||||
| 2026-08-28 | **Detector v3 (Brian's method):** pre-trigger floor + pre/mid/end consistency. Healthy channels proven to sit at 0.000 +/-1 unit (94.5%), confirming no decoder zero-point bias. Final: **5 of 45 units (11%)**, threshold-insensitive. |
|
||||
@@ -50,7 +50,7 @@ SIDECAR_KIND = "sfm.event"
|
||||
# bumped without a `pip install` re-run — leading to confusing stale
|
||||
# version stamps in sidecars. Bump this constant and CHANGELOG.md
|
||||
# together at release time.
|
||||
TOOL_VERSION = "0.26.0"
|
||||
TOOL_VERSION = "0.27.0"
|
||||
|
||||
try:
|
||||
# Best-effort: prefer the installed metadata when it's NEWER than the
|
||||
|
||||
@@ -413,10 +413,18 @@ def detect_multi_interval_stride(body: bytes) -> Optional[int]:
|
||||
|
||||
if (_ctr(stride) - _ctr(0)) & 0xFFFF != 1:
|
||||
continue
|
||||
# confirm on a third block when the body is long enough
|
||||
if 2 * stride + _MULTI_HEADER_LEN <= len(body):
|
||||
if not _is_multi_header(body, 2 * stride):
|
||||
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
|
||||
|
||||
+1
-1
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
|
||||
|
||||
[project]
|
||||
name = "seismo-relay"
|
||||
version = "0.26.0"
|
||||
version = "0.27.0"
|
||||
description = "Python client and REST server for MiniMate Plus seismographs"
|
||||
requires-python = ">=3.10"
|
||||
dependencies = [
|
||||
|
||||
@@ -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()
|
||||
@@ -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()
|
||||
@@ -0,0 +1,95 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Offset detector v3 — pre-trigger floor, with pre/mid/end consistency.
|
||||
|
||||
Brian's method, and better than v2's whole-record median for one reason: the
|
||||
pre-trigger window is *definitionally* quiet (it is the buffer captured before
|
||||
the trigger fired), whereas a whole-record median is merely robust to the event.
|
||||
|
||||
Per channel:
|
||||
pre = median of the first `pretrig_samples` samples (STRT record)
|
||||
mid = median of the middle third
|
||||
end = median of the final third
|
||||
spread = max(pre,mid,end) - min(pre,mid,end)
|
||||
|
||||
A DC offset is a *constant floor*: |pre| at or above the floor AND a small
|
||||
spread. A transient (settling, handling, a long-tailed event) moves one segment
|
||||
relative to the others and is rejected by the spread test.
|
||||
|
||||
Floor default 0.025 in/s = 5 A/D counts (Instantel's own criterion; 1 count =
|
||||
0.005 in/s). Quantisation is 0.005 in/s, so `spread` is measured in units of it.
|
||||
"""
|
||||
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})")
|
||||
|
||||
def serial_of(n):
|
||||
m=_STEM.match(n)
|
||||
return f"BE{(ord(m.group(1))-ord('B'))*1000+int(m.group(2))}" if m else "?"
|
||||
|
||||
def scan(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
|
||||
pre_n=ev.pretrig_samples
|
||||
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]; n=len(a); t=n//3
|
||||
pre = a[:pre_n] if (pre_n and 0 < pre_n < n) else a[:t]
|
||||
mid, end = a[t:2*t], a[2*t:]
|
||||
if not pre or not mid or not end: continue
|
||||
v=[statistics.median(x)*K for x in (pre,mid,end)]
|
||||
out.append({"serial":serial_of(p.name),"timestamp":stamp,
|
||||
"filename":p.name,"channel":ch,
|
||||
"pretrig_n": pre_n or 0,
|
||||
"pre":round(v[0],4),"mid":round(v[1],4),"end":round(v[2],4),
|
||||
"spread":round(max(v)-min(v),4),
|
||||
"peak":round(max(abs(x) for x 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("--max-spread",type=float,default=0.02)
|
||||
ap.add_argument("--out",required=True)
|
||||
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%2000==0: print(f" {i}/{len(files)}",flush=True)
|
||||
for r in rows:
|
||||
r["offset"]=int(abs(r["pre"])>=a.floor and r["spread"]<=a.max_spread)
|
||||
cols=["serial","timestamp","filename","channel","pretrig_n","pre","mid","end","spread","peak","offset"]
|
||||
with open(a.out,"w",newline="") as fh:
|
||||
w=csv.DictWriter(fh,fieldnames=cols); w.writeheader(); w.writerows(rows)
|
||||
from collections import defaultdict
|
||||
per=defaultdict(set); tot=defaultdict(set)
|
||||
for r in rows:
|
||||
tot[r["serial"]].add(r["filename"])
|
||||
if r["offset"]: per[r["serial"]].add(r["filename"])
|
||||
print(f"\nfloor={a.floor} in/s ({a.floor/0.005:.0f} counts) max spread={a.max_spread}")
|
||||
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()
|
||||
@@ -0,0 +1,221 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Verify the series-3 decoder against preserved Blastware ASCII exports.
|
||||
|
||||
Pairs each `<stem>_<ext>_ASCII.TXT` with its binary `<stem>.<ext>`, decodes the
|
||||
binary with the production codec, and compares against BW's own export:
|
||||
|
||||
waveform — per-channel sample counts, then every sample value
|
||||
histogram — interval count, then every per-interval channel peak
|
||||
|
||||
ADC counts convert as ips = counts * geo_range_ips / 32000 (1 decoder unit =
|
||||
16 counts = 0.005 in/s at the 10 in/s range; see CLAUDE.md).
|
||||
|
||||
Usage:
|
||||
python scratch/verify_against_ascii.py --dir <path> [--limit N] [--jobs N]
|
||||
[--out results.json] [--kind w|h|all]
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse, json, re, sys, traceback
|
||||
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_file, parse_report
|
||||
|
||||
GEO = ("Tran", "Vert", "Long")
|
||||
_GEO_FS_COUNTS = 32000.0
|
||||
_ASCII_SUFFIX_RE = re.compile(r"_ASCII\.TXT$", re.IGNORECASE)
|
||||
|
||||
|
||||
def binary_for(ascii_path: Path) -> Path:
|
||||
"""H907KXOW_WC0H_ASCII.TXT -> H907KXOW.WC0H"""
|
||||
stem = _ASCII_SUFFIX_RE.sub("", ascii_path.name)
|
||||
if "_" not in stem:
|
||||
return ascii_path.with_name(stem)
|
||||
head, _, ext = stem.rpartition("_")
|
||||
return ascii_path.with_name(f"{head}.{ext}")
|
||||
|
||||
|
||||
def counts_to_ips(counts, geo_range_ips):
|
||||
r = geo_range_ips if geo_range_ips else 10.0
|
||||
return counts * r / _GEO_FS_COUNTS
|
||||
|
||||
|
||||
def agrees(got, exp, geo_range_ips, tol=0.0006):
|
||||
"""True when decoded `got` matches BW's exported `exp`.
|
||||
|
||||
Saturation carve-out: when an event clips, BW clamps its export to the
|
||||
channel's range maximum (and writes OORANGE for the summary PPV), while
|
||||
the decoder faithfully reproduces raw counts that can sit a decoder unit
|
||||
or two past nominal full scale (32016 counts observed = 10.005 in/s on
|
||||
the 10 in/s range). Same sign and both at/above the ceiling is agreement,
|
||||
not a decode error.
|
||||
"""
|
||||
if abs(got - exp) <= tol:
|
||||
return True
|
||||
r = geo_range_ips if geo_range_ips else 10.0
|
||||
if abs(exp) >= r - tol and abs(got) >= r - tol and (got >= 0) == (exp >= 0):
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def parse_interval_table(text: str):
|
||||
"""Histogram interval rows: time, Tpk, Tfq, Vpk, Vfq, Lpk, Lfq, PVS, ..., micdB, micfq"""
|
||||
rows = []
|
||||
seen_header = False
|
||||
for line in text.splitlines():
|
||||
if "\t" not in line:
|
||||
continue
|
||||
cols = [c.strip().strip('"') for c in line.split("\t")]
|
||||
cols = [c for c in cols if c != ""]
|
||||
if not seen_header:
|
||||
if any(c in ("Tran", "Vert", "Long") for c in cols):
|
||||
seen_header = True
|
||||
continue
|
||||
if len(cols) < 7:
|
||||
continue
|
||||
if not re.match(r"^\d{1,2}:\d{2}:\d{2}$", cols[0]):
|
||||
continue
|
||||
def num(s):
|
||||
try:
|
||||
return float(s)
|
||||
except ValueError:
|
||||
return None
|
||||
rows.append({"time": cols[0], "Tran": num(cols[1]),
|
||||
"Vert": num(cols[3]), "Long": num(cols[5])})
|
||||
return rows
|
||||
|
||||
|
||||
def check_one(ascii_path_str: str) -> dict:
|
||||
ap = Path(ascii_path_str)
|
||||
bp = binary_for(ap)
|
||||
res = {"ascii": ap.name, "binary": bp.name, "status": "?",
|
||||
"kind": None, "detail": ""}
|
||||
try:
|
||||
if not bp.exists():
|
||||
res["status"] = "no_binary"
|
||||
return res
|
||||
text = ap.read_text(errors="replace")
|
||||
rep = parse_report(text, parse_samples=True)
|
||||
ev = read_blastware_file(bp)
|
||||
gr = rep.geo_range_ips
|
||||
res["kind"] = kind = ("histogram"
|
||||
if (rep.event_type or "").lower().startswith(("full histogram", "histogram"))
|
||||
else "waveform")
|
||||
samples = ev.raw_samples or {}
|
||||
dec_n = {c: len(samples.get(c) or []) for c in GEO}
|
||||
|
||||
if kind == "histogram":
|
||||
rows = parse_interval_table(text)
|
||||
res["n_ascii"] = len(rows)
|
||||
res["n_decoded"] = dec_n["Tran"]
|
||||
if not rows:
|
||||
res["status"] = "no_ascii_table"
|
||||
return res
|
||||
if dec_n["Tran"] == 0:
|
||||
res["status"] = "decode_empty"
|
||||
return res
|
||||
if dec_n["Tran"] != len(rows):
|
||||
res["status"] = "count_mismatch"
|
||||
res["detail"] = f"decoded {dec_n['Tran']} vs ascii {len(rows)}"
|
||||
return res
|
||||
bad = 0
|
||||
worst = 0.0
|
||||
for i, row in enumerate(rows):
|
||||
for ch in GEO:
|
||||
exp = row[ch]
|
||||
if exp is None:
|
||||
continue
|
||||
got = counts_to_ips(samples[ch][i], gr)
|
||||
if not agrees(got, exp, gr):
|
||||
bad += 1
|
||||
worst = max(worst, abs(got - exp))
|
||||
res["worst_abs"] = round(worst, 6)
|
||||
res["status"] = "exact" if bad == 0 else "value_mismatch"
|
||||
if bad:
|
||||
res["detail"] = f"{bad} interval-channel values off"
|
||||
return res
|
||||
|
||||
# waveform
|
||||
asc = rep.samples or []
|
||||
res["n_ascii"] = len(asc)
|
||||
res["n_decoded"] = dec_n["Tran"]
|
||||
if not asc:
|
||||
res["status"] = "no_ascii_table"
|
||||
return res
|
||||
if dec_n["Tran"] == 0:
|
||||
res["status"] = "decode_empty"
|
||||
return res
|
||||
if len({dec_n[c] for c in GEO}) != 1:
|
||||
res["status"] = "channel_len_mismatch"
|
||||
res["detail"] = str(dec_n)
|
||||
return res
|
||||
if dec_n["Tran"] != len(asc):
|
||||
res["status"] = "count_mismatch"
|
||||
res["detail"] = f"decoded {dec_n['Tran']} vs ascii {len(asc)}"
|
||||
return res
|
||||
bad = 0
|
||||
worst = 0.0
|
||||
for i, quad in enumerate(asc):
|
||||
for j, ch in enumerate(GEO):
|
||||
exp = quad[j]
|
||||
got = counts_to_ips(samples[ch][i], gr)
|
||||
if not agrees(got, exp, gr):
|
||||
bad += 1
|
||||
worst = max(worst, abs(got - exp))
|
||||
res["worst_abs"] = round(worst, 6)
|
||||
res["status"] = "exact" if bad == 0 else "value_mismatch"
|
||||
if bad:
|
||||
res["detail"] = f"{bad} sample values off"
|
||||
return res
|
||||
except Exception as e:
|
||||
res["status"] = "error"
|
||||
res["detail"] = f"{type(e).__name__}: {e}"
|
||||
return res
|
||||
|
||||
|
||||
def main():
|
||||
ap = argparse.ArgumentParser()
|
||||
ap.add_argument("--dir", required=True)
|
||||
ap.add_argument("--limit", type=int, default=0)
|
||||
ap.add_argument("--jobs", type=int, default=8)
|
||||
ap.add_argument("--kind", choices=["w", "h", "all"], default="all")
|
||||
ap.add_argument("--out", default=None)
|
||||
a = ap.parse_args()
|
||||
|
||||
root = Path(a.dir)
|
||||
files = sorted(p for p in root.rglob("*")
|
||||
if p.is_file() and p.name.upper().endswith("_ASCII.TXT"))
|
||||
if a.kind != "all":
|
||||
want = "0W" if a.kind == "w" else "0H"
|
||||
files = [p for p in files
|
||||
if _ASCII_SUFFIX_RE.sub("", p.name).upper().endswith(want)]
|
||||
if a.limit:
|
||||
files = files[: a.limit]
|
||||
print(f"pairs to check: {len(files)}", flush=True)
|
||||
|
||||
out = []
|
||||
from collections import Counter
|
||||
tally = Counter()
|
||||
with ProcessPoolExecutor(max_workers=a.jobs) as ex:
|
||||
futs = {ex.submit(check_one, str(p)): p for p in files}
|
||||
for n, f in enumerate(as_completed(futs), 1):
|
||||
r = f.result()
|
||||
out.append(r)
|
||||
tally[(r["kind"], r["status"])] += 1
|
||||
if n % 500 == 0:
|
||||
print(f" {n}/{len(files)}", flush=True)
|
||||
|
||||
print("\n=== results ===")
|
||||
for (kind, status), n in sorted(tally.items(), key=lambda x: -x[1]):
|
||||
print(f" {str(kind):10} {status:22} {n}")
|
||||
if a.out:
|
||||
Path(a.out).write_text(json.dumps(out, indent=1))
|
||||
print(f"\nwrote {a.out}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
+83
-32
@@ -603,56 +603,107 @@ class SeismoDb:
|
||||
).fetchall()
|
||||
return [dict(r) for r in rows]
|
||||
|
||||
def find_twins(self, event_id: str, *, window_seconds: int = 300) -> list[dict]:
|
||||
def find_twins(self, event_id: str, *, window_seconds: int | None = None) -> list[dict]:
|
||||
"""
|
||||
Find this event's histogram/waveform twin(s): rows sharing the same
|
||||
serial and an identical peak_vector_sum, whose timestamp falls
|
||||
within ``window_seconds`` of this event's timestamp. Excludes the
|
||||
event itself. Returns [] if the event or any required field
|
||||
(serial / peak_vector_sum / timestamp) is missing.
|
||||
Find this event's histogram/waveform twin(s): the SAME physical event
|
||||
recorded both as a scheduled histogram and as a triggered waveform.
|
||||
|
||||
Caveat: identical-PVS matching is a proxy for "same physical event
|
||||
recorded twice," not a guarantee. In the rare case where the device
|
||||
clamps/saturates PVS (clamped to sqrt(3) * geo_range), two distinct
|
||||
saturated events on the same serial within the window can share the
|
||||
same clamped PVS value and be matched as twins even though they are
|
||||
different events. This is harmless in practice — false_trigger/
|
||||
reviewed_real are derived/index columns re-derivable from the
|
||||
sidecar source of truth — but worth knowing if twin counts look
|
||||
surprising on a saturated/clamped run.
|
||||
A real trigger is captured twice — once as a triggered waveform (stamped
|
||||
at the trigger instant) and once inside the scheduled histogram whose
|
||||
interval contains it (stamped at the histogram's interval start, e.g. the
|
||||
7am/7pm call-in). The two can be HOURS apart in time yet report the same
|
||||
serial and identical peak_vector_sum. Twins are therefore matched by:
|
||||
|
||||
* same serial,
|
||||
* identical peak_vector_sum,
|
||||
* OPPOSITE record type (one histogram, one waveform), and
|
||||
* the waveform's timestamp falls within the histogram's interval —
|
||||
from a histogram's timestamp up to the next histogram (same serial).
|
||||
|
||||
This replaces the old ±``window_seconds`` heuristic, which silently
|
||||
missed twins more than a few minutes apart (a histogram's interval-start
|
||||
stamp and the trigger instant routinely differ by hours). ``window_seconds``
|
||||
is still accepted for backward compatibility but is ignored.
|
||||
|
||||
Returns [] if the event or a required field (serial / peak_vector_sum /
|
||||
timestamp) is missing.
|
||||
|
||||
Caveat: identical-PVS matching remains a proxy for "same physical event"
|
||||
— if the device clamps/saturates PVS (to sqrt(3) * geo_range), two
|
||||
distinct saturated events could share a PVS. The added opposite-type and
|
||||
interval constraints make a false pairing far less likely than the old
|
||||
time-window match, and false_trigger/reviewed_real stay re-derivable from
|
||||
the sidecar source of truth.
|
||||
"""
|
||||
def _parse(ts):
|
||||
if not ts:
|
||||
return None
|
||||
try:
|
||||
return datetime.datetime.fromisoformat(str(ts).replace(" ", "T"))
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
def _is_hist(rt):
|
||||
return str(rt or "").lower().startswith("hist")
|
||||
|
||||
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:
|
||||
serial = row.get("serial"); pvs = row.get("peak_vector_sum")
|
||||
t_target = _parse(row.get("timestamp"))
|
||||
if serial is None or pvs is None or t_target is None:
|
||||
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]
|
||||
target_hist = _is_hist(row.get("record_type"))
|
||||
|
||||
def propagate_review_to_twins(self, event_id: str, *, window_seconds: int = 300) -> list[str]:
|
||||
with self._connect() as conn:
|
||||
cand_rows = [dict(r) for r in conn.execute(
|
||||
"SELECT * FROM events WHERE serial=? AND id!=? AND peak_vector_sum=?",
|
||||
(serial, event_id, pvs)).fetchall()]
|
||||
hist_ts = [r["timestamp"] for r in conn.execute(
|
||||
"SELECT timestamp FROM events WHERE serial=? AND lower(record_type) LIKE 'hist%'",
|
||||
(serial,)).fetchall()]
|
||||
|
||||
# Histogram interval-start times for this serial, sorted, to bound intervals.
|
||||
starts = sorted(x for x in (_parse(t) for t in hist_ts) if x is not None)
|
||||
|
||||
def _interval_end(h_start):
|
||||
# The next histogram strictly after h_start bounds the interval; else open-ended.
|
||||
for x in starts:
|
||||
if x > h_start:
|
||||
return x
|
||||
return None
|
||||
|
||||
def _covers(h_start, w_time):
|
||||
end = _interval_end(h_start)
|
||||
return h_start <= w_time and (end is None or w_time < end)
|
||||
|
||||
twins = []
|
||||
for c in cand_rows:
|
||||
if _is_hist(c.get("record_type")) == target_hist:
|
||||
continue # twins are strictly cross-type (one histogram, one waveform)
|
||||
c_time = _parse(c.get("timestamp"))
|
||||
if c_time is None:
|
||||
continue
|
||||
h_start, w_time = (t_target, c_time) if target_hist else (c_time, t_target)
|
||||
if _covers(h_start, w_time):
|
||||
twins.append(c)
|
||||
return twins
|
||||
|
||||
def propagate_review_to_twins(self, event_id: str, *, window_seconds: int | None = None) -> list[str]:
|
||||
"""
|
||||
Copy this event's `false_trigger`/`reviewed_real` columns onto each
|
||||
of its histogram/waveform twins (see `find_twins`), so flagging one
|
||||
twin flags both. Returns the list of twin ids updated.
|
||||
|
||||
``window_seconds`` is accepted for backward compatibility but ignored;
|
||||
twin matching is now interval-based (see `find_twins`).
|
||||
"""
|
||||
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)
|
||||
twins = self.find_twins(event_id)
|
||||
moved = []
|
||||
with self._connect() as conn:
|
||||
for tw in twins:
|
||||
|
||||
+3
-2
@@ -67,6 +67,7 @@ from minimateplus.blastware_file import write_blastware_file, blastware_filename
|
||||
from minimateplus.client import _decode_a5_metadata_into, _decode_a5_waveform, _decode_event_count
|
||||
from minimateplus.framing import build_bw_write_frame, SESSION_RESET, POLL_PROBE, POLL_DATA
|
||||
from minimateplus.protocol import SUB_STOP_MONITORING
|
||||
from minimateplus.event_file_io import TOOL_VERSION as SFM_VERSION # single source for the service version (release-bumped)
|
||||
from sfm import event_hdf5
|
||||
from sfm.cache import SFMCache, get_cache
|
||||
from sfm.database import SeismoDb
|
||||
@@ -90,7 +91,7 @@ app = FastAPI(
|
||||
"Implements the minimateplus RS-232 protocol library.\n"
|
||||
"Proxied by terra-view at /api/sfm/*."
|
||||
),
|
||||
version="0.26.0",
|
||||
version=SFM_VERSION,
|
||||
)
|
||||
|
||||
# Allow requests from the waveform viewer opened as a local file (file://)
|
||||
@@ -371,7 +372,7 @@ def _backfill_events(events: list, info: "DeviceInfo") -> None:
|
||||
@app.get("/health")
|
||||
def health() -> dict:
|
||||
"""Service heartbeat. No device I/O."""
|
||||
return {"status": "ok", "service": "sfm", "version": "0.1.0"}
|
||||
return {"status": "ok", "service": "sfm", "version": SFM_VERSION}
|
||||
|
||||
|
||||
@app.get("/", response_class=FileResponse)
|
||||
|
||||
+57
-19
@@ -1,33 +1,71 @@
|
||||
import datetime
|
||||
import sqlite3
|
||||
from sfm.database import SeismoDb
|
||||
from minimateplus.models import Event, Timestamp
|
||||
|
||||
|
||||
def _ins(db, key, serial, pvs, ts):
|
||||
def _ins(db, key, serial, pvs, ts, record_type="Waveform"):
|
||||
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"]))
|
||||
c.execute("UPDATE events SET peak_vector_sum=?, record_type=? WHERE id=?",
|
||||
(pvs, record_type, row["id"]))
|
||||
return row["id"]
|
||||
|
||||
|
||||
def test_find_twins_matches_same_serial_pvs_near_time(tmp_path):
|
||||
def _ts(hour, minute, second=0, day=25):
|
||||
return Timestamp(raw=b"", flag=0x10, year=2026, unknown_byte=0, month=2, day=day,
|
||||
hour=hour, minute=minute, second=second)
|
||||
|
||||
|
||||
def test_histogram_and_waveform_twin_across_hours(tmp_path):
|
||||
# The real UM12947 case: histogram stamped at its 7pm interval start, the
|
||||
# triggered waveform 75 min later — same serial + identical PVS. The old
|
||||
# ±5-min window missed this; interval matching catches it, both directions.
|
||||
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)
|
||||
# d needs a timestamp distinct from `twin` (UNIQUE(serial, timestamp) would
|
||||
# otherwise collide with b and UPSERT onto its row instead of inserting a
|
||||
# new one) while staying near `base` in time.
|
||||
near = Timestamp(raw=b"", flag=0x10, year=2026, unknown_byte=0, month=2, day=25, hour=20, minute=19, second=44)
|
||||
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, near) # near time but different pvs
|
||||
ids = {r["id"] for r in db.find_twins(a, window_seconds=300)}
|
||||
assert ids == {b}
|
||||
hist_pm = _ins(db, "01110001", "BE1", 0.4763, _ts(19, 31, 17), "Histogram")
|
||||
wave = _ins(db, "01110002", "BE1", 0.4763, _ts(20, 46, 44), "Waveform")
|
||||
_ins(db, "01110003", "BE1", 0.0100, _ts(7, 0, 0, day=26), "Histogram") # bounds the interval
|
||||
assert {r["id"] for r in db.find_twins(hist_pm)} == {wave}
|
||||
assert {r["id"] for r in db.find_twins(wave)} == {hist_pm}
|
||||
|
||||
|
||||
def test_same_type_not_twinned(tmp_path):
|
||||
# Two waveforms, same serial + PVS, seconds apart → NOT twins (cross-type only).
|
||||
db = SeismoDb(tmp_path / "s.db")
|
||||
a = _ins(db, "01110001", "BE1", 0.4763, _ts(20, 19, 5), "Waveform")
|
||||
_ins(db, "01110002", "BE1", 0.4763, _ts(20, 19, 45), "Waveform")
|
||||
assert db.find_twins(a) == []
|
||||
|
||||
|
||||
def test_waveform_matches_only_the_containing_interval(tmp_path):
|
||||
# Two overnight intervals with the same PVS; a waveform in the SECOND interval
|
||||
# must twin with that histogram, never the first — even though PVS matches both.
|
||||
db = SeismoDb(tmp_path / "s.db")
|
||||
h1 = _ins(db, "01110001", "BE1", 0.4763, _ts(19, 0, 0, day=25), "Histogram")
|
||||
h2 = _ins(db, "01110002", "BE1", 0.4763, _ts(7, 0, 0, day=26), "Histogram")
|
||||
w = _ins(db, "01110003", "BE1", 0.4763, _ts(8, 0, 0, day=26), "Waveform")
|
||||
assert {r["id"] for r in db.find_twins(w)} == {h2}
|
||||
assert w not in {r["id"] for r in db.find_twins(h1)}
|
||||
|
||||
|
||||
def test_different_pvs_not_twinned(tmp_path):
|
||||
db = SeismoDb(tmp_path / "s.db")
|
||||
h = _ins(db, "01110001", "BE1", 0.4763, _ts(19, 0, 0), "Histogram")
|
||||
_ins(db, "01110002", "BE1", 0.9999, _ts(20, 0, 0), "Waveform") # different PVS
|
||||
assert db.find_twins(h) == []
|
||||
|
||||
|
||||
def test_open_ended_latest_interval(tmp_path):
|
||||
# A waveform after the latest histogram (nothing bounds the interval) still twins.
|
||||
db = SeismoDb(tmp_path / "s.db")
|
||||
h = _ins(db, "01110001", "BE1", 0.4763, _ts(19, 0, 0), "Histogram")
|
||||
w = _ins(db, "01110002", "BE1", 0.4763, _ts(23, 30, 0), "Waveform")
|
||||
assert {r["id"] for r in db.find_twins(h)} == {w}
|
||||
|
||||
|
||||
def test_missing_fields_returns_empty(tmp_path):
|
||||
db = SeismoDb(tmp_path / "s.db")
|
||||
assert db.find_twins("nonexistent-id") == []
|
||||
|
||||
@@ -0,0 +1,17 @@
|
||||
"""The /health version must track the release, not a stale literal.
|
||||
|
||||
terra-view's SFM Admin page displays whatever `/health` reports. It was
|
||||
hardcoded to "0.1.0" and never bumped, so the page showed 0.1.0 while the
|
||||
service was actually 0.26.0. These guard against that regression — and run
|
||||
without httpx (they call the endpoint function directly, no TestClient).
|
||||
"""
|
||||
from minimateplus.event_file_io import TOOL_VERSION
|
||||
from sfm.server import app, health
|
||||
|
||||
|
||||
def test_health_reports_current_tool_version():
|
||||
assert health()["version"] == TOOL_VERSION
|
||||
|
||||
|
||||
def test_openapi_version_matches_tool_version():
|
||||
assert app.version == TOOL_VERSION
|
||||
@@ -643,3 +643,38 @@ def test_multi_interval_matches_blastware_ascii_exactly():
|
||||
assert hz is None
|
||||
elif not cell.startswith("<"):
|
||||
assert hz is not None and abs(hz - float(cell)) <= max(0.55, float(cell) * 0.02)
|
||||
|
||||
|
||||
def test_partial_final_block_is_not_disqualified_by_missing_third_header():
|
||||
"""A body can exceed two strides yet hold only two real blocks.
|
||||
|
||||
Regression for BE18193 `T193L0XM.CI0H` — 51 intervals at 2 s = one full
|
||||
30-interval block plus a 21-interval remainder, in a body long enough to
|
||||
demand a third block header at ``2 * stride`` that does not exist. The
|
||||
third-block confirmation used to be mandatory whenever the body was long
|
||||
enough, so the correct stride was discarded and the file decoded to
|
||||
nothing. A missing third header means end-of-stream, not disqualification;
|
||||
the block-counter check is the decisive anti-false-positive test.
|
||||
"""
|
||||
full = [(1, 1, 2, 2, 3, 3, 4, 4)] * 30
|
||||
partial = [(5, 5, 6, 6, 7, 7, 8, 8)] * 21
|
||||
body = (_mk_multi_block(full, ctr=256)
|
||||
+ _mk_multi_block(partial, ctr=257)
|
||||
+ b"\xff" * 700) # trailing padding past 2 * stride
|
||||
stride = 12 + 20 * 30
|
||||
assert 2 * stride + 6 <= len(body), "padding must reach past two strides"
|
||||
# the whole point: a third header is absent, and that must not disqualify
|
||||
assert detect_multi_interval_stride(body) == stride
|
||||
recs = walk_multi_interval_blocks(body)
|
||||
assert len(recs) == 51
|
||||
assert recs[0]["t_peak"] == 1
|
||||
assert recs[-1]["t_peak"] == 5
|
||||
|
||||
|
||||
def test_third_block_still_rejects_a_mismatched_counter():
|
||||
"""The corroboration must still bite when a third block IS present."""
|
||||
ivs = [(1, 1, 2, 2, 3, 3, 4, 4)] * 4
|
||||
body = (_mk_multi_block(ivs, ctr=256)
|
||||
+ _mk_multi_block(ivs, ctr=257)
|
||||
+ _mk_multi_block(ivs, ctr=999)) # counter jumps — not consecutive
|
||||
assert detect_multi_interval_stride(body) != 12 + 20 * 4
|
||||
|
||||
@@ -3,31 +3,34 @@ from sfm.database import SeismoDb
|
||||
from minimateplus.models import Event, Timestamp
|
||||
|
||||
|
||||
def _ins(db, key, serial, pvs, ts):
|
||||
def _ins(db, key, serial, pvs, ts, record_type="Waveform"):
|
||||
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]
|
||||
with sqlite3.connect(db.db_path) as c:
|
||||
c.execute("UPDATE events SET peak_vector_sum=? WHERE id=?", (pvs, row["id"]))
|
||||
c.execute("UPDATE events SET peak_vector_sum=?, record_type=? WHERE id=?",
|
||||
(pvs, record_type, row["id"]))
|
||||
return row["id"]
|
||||
|
||||
|
||||
def test_propagate_copies_flags_to_twins(tmp_path):
|
||||
def _ts(hour, minute, second=0, day=25):
|
||||
return Timestamp(raw=b"", flag=0x10, year=2026, unknown_byte=0, month=2, day=day,
|
||||
hour=hour, minute=minute, second=second)
|
||||
|
||||
|
||||
def test_propagate_copies_flags_across_hours_apart_twins(tmp_path):
|
||||
# Flagging the waveform FT propagates to its histogram twin 75 min earlier
|
||||
# (the interval matcher pairs them; the old ±5-min window would have missed it).
|
||||
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)
|
||||
other = Timestamp(raw=b"", flag=0x10, year=2026, unknown_byte=0, month=2, day=25, hour=20, minute=19, second=44)
|
||||
hist = _ins(db, "01110001", "BE1", 0.4763, _ts(19, 31, 17), "Histogram")
|
||||
wave = _ins(db, "01110002", "BE1", 0.4763, _ts(20, 46, 44), "Waveform") # twin, 75 min later
|
||||
other = _ins(db, "01110003", "BE1", 0.9999, _ts(20, 20, 0), "Waveform") # different pvs
|
||||
|
||||
primary_id = _ins(db, "01110001", "BE1", 0.4763, base)
|
||||
twin_id = _ins(db, "01110002", "BE1", 0.4763, twin) # twin: same serial+pvs, 40s apart
|
||||
non_twin_id = _ins(db, "01110003", "BE1", 0.9999, other) # near time but different pvs
|
||||
db.update_event_review(wave, {"false_trigger": True})
|
||||
moved = db.propagate_review_to_twins(wave)
|
||||
|
||||
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
|
||||
assert db.get_event(non_twin_id)["false_trigger"] == 0
|
||||
assert hist in moved
|
||||
assert db.get_event(hist)["false_trigger"] == 1
|
||||
assert db.get_event(other)["false_trigger"] == 0
|
||||
|
||||
Reference in New Issue
Block a user