feat(h5): standardize sensor-check into the .h5 (schema v2); SFM reads it
Make the sensor self-check a first-class part of the standardized decoded event
so SFM stops decoding it at report time — device-agnostic, per the store's
decoder→standardized-.h5→SFM model.
* Event gains a `sensor_check` field; both decoders attach the traces where
they set raw_samples — series-3 in event_file_io.read_blastware_file
(minimateplus.sensor_check), series-4 in waveform_store's IDF path
(micromate.sensor_check). Covers ingest and backfill (both re-decode).
* event_hdf5 bumps schema_version 1→2 and writes an optional /sensor_check
group (raw counts, int32, per channel present). read_event_hdf5 returns
it; plot_json_from_hdf5 carries it as a top-level key. Old v1 files still
read cleanly (no group → None), so nothing breaks before the backfill.
* gather_report_data reads sensor_check_waveforms from the .h5 and drops the
report-time series-3 decode — the report no longer reaches into a decoder,
and a series-4 event now lights up the same strip automatically.
Stored as raw counts (a shape diagnostic, rendered fit-to-box): the per-series
count scale differs and a physical mic unit is ill-defined, so conversion would
add complexity for no display benefit — easy to add later if a numeric use
appears.
Tests: .h5 roundtrip + backward-compat + plot_json + real series-3 decode
attaches to the Event.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf
This commit is contained in:
@@ -960,6 +960,11 @@ def read_blastware_file(path: Union[str, Path]) -> Event:
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project=project, client=client, operator=user, sensor_location=seisloc,
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)
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ev.raw_samples = samples
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# Sensor self-check traces from the binary's trailing block (waveform
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# events only; returns {} for histograms / when absent). Carried on the
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# Event so the .h5 writer persists them device-agnostically.
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from minimateplus.sensor_check import decode_sensor_check
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ev.sensor_check = decode_sensor_check(raw) or None
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# Only compute peaks from samples when we actually have samples.
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# For events the codec couldn't decode (histogram-mode bodies, until
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# the §7.6.2 histogram codec is wired in), samples is an empty dict
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@@ -544,6 +544,15 @@ class Event:
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pretrig_samples: Optional[int] = None # from STRT record: pre-trigger sample count
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rectime_seconds: Optional[int] = None # from STRT record: record duration (seconds)
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# Sensor self-check traces keyed by channel label — the short diagnostic
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# waveforms the unit records when it pulses each sensor before monitoring
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# (geophone ring-downs + a mic pulse train). Decoded from the binary by
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# the per-series decoder (minimateplus.sensor_check / micromate.sensor_check)
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# and carried here so the .h5 writer can persist them device-agnostically.
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# Raw ADC counts; the source series' scale differs but the trace is a
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# shape diagnostic (rendered fit-to-box). None when absent.
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sensor_check: Optional[dict] = None # {"Tran": [...], ..., "MicL": [...]}
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# ── Debug / introspection ─────────────────────────────────────────────────
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# Raw 210-byte waveform record bytes, set when debug mode is active.
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# Exposed by the SFM server via ?debug=true so field layouts can be verified.
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+44
-4
@@ -12,8 +12,11 @@ Layout written to `<filename>.h5`:
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├─ samples_int16/ (optional)
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│ ├─ Tran (int16, raw ADC counts) shape: (N,)
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│ └─ ... per channel (only when present in the source)
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├─ sensor_check/ (optional, schema v2+)
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│ ├─ Tran (int32, raw counts) shape: (M,) M ≪ N
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│ └─ ... per channel present in the source (MicL absent on 3-channel units)
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└─ root attrs (event metadata):
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schema_version int = 1
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schema_version int = 2
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kind str = "sfm.event.hdf5"
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serial str
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waveform_key str (8-hex)
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@@ -64,7 +67,7 @@ from minimateplus.models import Event
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log = logging.getLogger(__name__)
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SCHEMA_VERSION = 1
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SCHEMA_VERSION = 2 # v2 adds the optional /sensor_check group
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HDF5_KIND = "sfm.event.hdf5"
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# Geophone full-scale velocity per range (in/s). Confirmed in CLAUDE.md
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@@ -270,6 +273,22 @@ def write_event_hdf5(
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)
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igrp.attrs["mic_psi_per_count"] = float(mic_factor)
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# /sensor_check — optional short diagnostic self-check traces (schema
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# v2+). Raw ADC counts (a shape diagnostic; the per-series count scale
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# differs, and the renderer fits each trace to its box). Only channels
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# the decoder found are written — 3-channel units carry no MicL.
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sc = event.sensor_check or {}
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if sc:
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scgrp = f.create_group("sensor_check")
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for ch in ("Tran", "Vert", "Long", "MicL"):
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vals = sc.get(ch)
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if vals:
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scgrp.create_dataset(
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ch, data=np.asarray(vals, dtype=np.int32),
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compression="gzip", compression_opts=4, shuffle=True,
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)
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scgrp.attrs["units"] = "raw_counts"
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import os
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os.replace(tmp, path)
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@@ -334,6 +353,16 @@ def read_event_hdf5(path: Union[str, Path]) -> dict:
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if mic_attr is not None:
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mic_psi = float(mic_attr)
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# /sensor_check — optional (schema v2+); absent on older files.
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sensor_check = None
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scgrp = f.get("sensor_check")
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if scgrp is not None:
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sensor_check = {}
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for ch in ("Tran", "Vert", "Long", "MicL"):
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ds = scgrp.get(ch)
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if ds is not None:
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sensor_check[ch] = np.asarray(ds[()])
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return {
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"schema_version": sv,
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"kind": attrs.get("kind"),
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@@ -341,6 +370,7 @@ def read_event_hdf5(path: Union[str, Path]) -> dict:
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"samples": samples,
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"samples_int16": samples_int16,
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"mic_psi_per_count": mic_psi,
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"sensor_check": sensor_check,
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}
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@@ -431,11 +461,16 @@ def plot_json_from_hdf5(
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event_id: Optional[str] = None,
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index: Optional[int] = None,
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) -> dict:
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"""Build a `sfm.plot.v1` JSON dict from a stored .h5 file."""
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"""Build a `sfm.plot.v1` JSON dict from a stored .h5 file.
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The dict also carries a top-level ``sensor_check`` key (the raw self-check
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traces as ``{ch: [int]}``, or None) beyond the plot schema, so report
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generation can read the traces from the same single .h5 load.
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"""
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data = read_event_hdf5(path)
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a = data["attrs"]
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s = data["samples"]
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return _build_plot_dict(
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out = _build_plot_dict(
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n_samples=len(s["Tran"]) if "Tran" in s else 0,
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sample_rate=int(a.get("sample_rate", 1024) or 1024),
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pretrig_samples=int(a.get("pretrig_samples", 0) or 0),
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@@ -463,6 +498,11 @@ def plot_json_from_hdf5(
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event_id=event_id,
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index=index,
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)
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scd = data.get("sensor_check")
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out["sensor_check"] = (
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{ch: v.tolist() for ch, v in scd.items()} if scd else None
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)
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return out
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def _build_plot_dict(
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+11
-16
@@ -121,9 +121,11 @@ class ReportData:
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t0_ms: Optional[float] = None
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dt_ms: Optional[float] = None
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# Sensor self-check traces — {ch: [samples]} in raw decode units, decoded
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# from the binary's trailing block (see minimateplus.sensor_check). The
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# little waveforms BW draws in its "Sensor Check" strip. Empty when absent.
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# Sensor self-check traces — {ch: [samples]} in raw counts, read from the
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# standardized .h5 (/sensor_check group, schema v2+) where the per-series
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# decoder stored them at ingest. The little diagnostic waveforms BW draws
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# in its "Sensor Check" strip. Empty when absent (pre-v2 .h5, histogram,
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# or 3-channel unit's MicL).
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sensor_check_waveforms: dict = field(default_factory=dict)
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# Record-type discriminator
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@@ -294,22 +296,15 @@ def gather_report_data(
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rd.pretrig_samples = ta.get("pretrig_samples")
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rd.t0_ms = ta.get("t0_ms")
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rd.dt_ms = ta.get("dt_ms")
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# Sensor self-check traces — read from the standardized .h5 (schema
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# v2+). Device-agnostic: whichever decoder produced the event
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# stored them at ingest, so SFM reads them here without knowing or
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# caring about the source instrument series. Empty on pre-v2 files
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# (until backfilled) and on 3-channel / histogram events.
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rd.sensor_check_waveforms = wf.get("sensor_check") or {}
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except Exception as exc:
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log.warning("gather_report_data: hdf5 read failed: %s", exc)
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# ── Sensor self-check traces — decoded from the retained raw binary ──
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# The .h5 holds only the main waveform; the sensor-check traces live in the
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# binary's trailing block, so decode them straight from the kept BW file.
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# Waveform events only (histograms have no sensor-check strip).
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if not rd.is_histogram:
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try:
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from minimateplus.sensor_check import decode_sensor_check
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bw_path, _a5 = store.paths_for(serial, filename)
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if bw_path.exists():
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rd.sensor_check_waveforms = decode_sensor_check(bw_path.read_bytes())
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except Exception as exc:
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log.warning("gather_report_data: sensor-check decode failed: %s", exc)
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# ── Histogram aggregation ──
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# Codec emits ~N per-block samples (typically 1/sec); BW reports
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# one bar per configured interval (1 min / 5 min / etc.). When
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@@ -662,6 +662,11 @@ class WaveformStore:
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ev.raw_samples = idf_samples
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n_samples = max((len(idf_samples.get(ch, [])) for ch in ("Tran", "Vert", "Long", "MicL")), default=0)
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ev.total_samples = ev.total_samples or n_samples
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# Sensor self-check traces from the IDFW fixed header (waveform
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# events only; {} on histograms / when absent). Carried on the
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# bridged Event so the .h5 writer persists them like series-3.
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from micromate.sensor_check import decode_idf_sensor_check
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ev.sensor_check = decode_idf_sensor_check(idf_bytes) or None
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# For IDFH histograms there are no per-sample waveform arrays — the
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# device stores one peak ADC count per interval per channel. Synthesise
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@@ -0,0 +1,71 @@
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"""The event .h5 carries the sensor self-check traces (schema v2).
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The sensor check is decoded by the per-series decoder and attached to the
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standardized Event, so the .h5 writer persists it device-agnostically and SFM
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reads it back without knowing which instrument produced it. Old v1 files (no
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sensor_check group) must still read cleanly.
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"""
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import tempfile
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from pathlib import Path
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import numpy as np
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from minimateplus.models import Event
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from minimateplus.event_file_io import read_blastware_file
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from sfm import event_hdf5
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S3_FIX = Path(__file__).parent / "fixtures" / "fft-oracle-2026-09-14" / "N844LQHB.ZT0W"
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def _write(ev, **kw):
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d = Path(tempfile.mkdtemp())
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p = d / "e.h5"
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event_hdf5.write_event_hdf5(p, ev, serial="BE12844", **kw)
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return p
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def test_sensor_check_roundtrips_through_hdf5():
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ev = Event(index=0)
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ev.raw_samples = {"Tran": [1, 2, -3], "Vert": [0, 1], "Long": [2], "MicL": [5, -5]}
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ev.sample_rate = 1024
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sc = {"Tran": [0, -990, -500, -100], "Vert": [0, -980, -480],
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"Long": [0, -986, -470], "MicL": [0, -1800, 1800, -1800]}
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ev.sensor_check = sc
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r = event_hdf5.read_event_hdf5(_write(ev))
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assert r["schema_version"] == 2
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assert set(r["sensor_check"]) == {"Tran", "Vert", "Long", "MicL"}
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for ch, vals in sc.items():
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assert r["sensor_check"][ch].tolist() == vals
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def test_plot_json_carries_sensor_check():
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ev = Event(index=0)
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ev.raw_samples = {"Tran": [1, 2, 3]}
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ev.sample_rate = 1024
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ev.sensor_check = {"Tran": [0, -990, -500], "Vert": [0, -980],
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"Long": [0, -986]} # 3-channel: no MicL
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pj = event_hdf5.plot_json_from_hdf5(_write(ev))
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assert pj["sensor_check"] is not None
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assert "MicL" not in pj["sensor_check"]
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assert pj["sensor_check"]["Tran"] == [0, -990, -500]
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def test_event_without_sensor_check_still_reads_as_v2():
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ev = Event(index=0)
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ev.raw_samples = {"Tran": [1, 2, 3]}
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ev.sample_rate = 1024
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r = event_hdf5.read_event_hdf5(_write(ev))
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assert r["schema_version"] == 2
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assert r["sensor_check"] is None
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assert event_hdf5.plot_json_from_hdf5(_write(ev))["sensor_check"] is None
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def test_series3_decode_populates_event_sensor_check():
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# The real series-3 decoder attaches the traces to the Event, so the
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# ingest/backfill .h5 write picks them up with no extra plumbing.
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ev = read_blastware_file(S3_FIX)
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assert ev.sensor_check is not None
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assert set(ev.sensor_check) == {"Tran", "Vert", "Long", "MicL"}
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tran = np.asarray(ev.sensor_check["Tran"], dtype=float)
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assert tran.min() < -800 # the geophone ring-down deflection
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