feat(offset): DC-offset detector productionized into the shape pipeline

Productionizes the validated scratch/offset_scan3.py: a DC offset (baseline
shifted off zero — sensor bumped/settled/drifted) is |median(pre-trigger)| >= 5
counts (0.025 in/s) AND flat across pre/mid/end thirds (spread <= 0.02); a
transient moves one third and is rejected by the spread test.

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

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

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YDXjZCr4RqT2U3QvMDhgzf

scripts/backfill_event_shape.py

@@ -1,12 +1,12 @@
 #!/usr/bin/env python3
-"""Backfill events.shape_* from each event's .h5 waveform samples. Idempotent."""
+"""Backfill events.shape_* and shape_offset_* from each event's .h5 samples. Idempotent."""
 from __future__ import annotations
 import argparse, logging, sys
 from pathlib import Path
 sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
 from sfm.database import SeismoDb
 from sfm.waveform_store import WaveformStore
-from sfm.shape_metrics import shape_from_h5
+from sfm.shape_metrics import shape_from_h5, offset_from_h5
 
 log = logging.getLogger("backfill_event_shape")
 
@@ -21,6 +21,7 @@ def backfill_shape(db: SeismoDb, store: WaveformStore, *, dry_run: bool = False)
         if not h5_path.exists():
             counts["skipped_no_h5"] += 1; continue
         shape = shape_from_h5(h5_path)
+        offset = offset_from_h5(h5_path)
         if shape is None:
             # The .h5 can no longer yield a shape (fewer than 2 samples, or a
             # flat trace).  Clear any previously stored value rather than
@@ -28,22 +29,32 @@ def backfill_shape(db: SeismoDb, store: WaveformStore, *, dry_run: bool = False)
             # from and silently feeds the false-trigger detector.  Seen after
             # a decoder fix shrinks an event: 493 rows in the prod snapshot
             # were carrying metrics from a superseded decode (2026-08-25).
-            if row.get("shape_crest_factor") is not None:
+            if (row.get("shape_crest_factor") is not None
+                    or row.get("shape_offset") is not None):
                 if not dry_run:
                     with db._connect() as conn:
                         conn.execute(
                             "UPDATE events SET shape_crest_factor=NULL, "
                             "shape_near_peak_count=NULL, shape_sample_count=NULL, "
-                            "shape_axis=NULL WHERE id=?", (row["id"],))
+                            "shape_axis=NULL, shape_offset=NULL, shape_offset_axis=NULL, "
+                            "shape_offset_pre=NULL, shape_offset_spread=NULL WHERE id=?",
+                            (row["id"],))
                 counts["cleared_stale"] += 1
             counts["skipped_no_samples"] += 1; continue
         if not dry_run:
             with db._connect() as conn:
                 conn.execute(
                     "UPDATE events SET shape_crest_factor=?, shape_near_peak_count=?, "
-                    "shape_sample_count=?, shape_axis=? WHERE id=?",
+                    "shape_sample_count=?, shape_axis=?, shape_offset=?, "
+                    "shape_offset_axis=?, shape_offset_pre=?, shape_offset_spread=? "
+                    "WHERE id=?",
                     (shape["crest_factor"], shape["near_peak_count"],
-                     shape["sample_count"], shape["axis"], row["id"]))
+                     shape["sample_count"], shape["axis"],
+                     (1 if offset["offset"] else 0) if offset else None,
+                     offset["axis"] if offset else None,
+                     offset["pre"] if offset else None,
+                     offset["spread"] if offset else None,
+                     row["id"]))
         counts["updated"] += 1
     log.info("backfill_shape: %s", counts)
     return counts