scripts/backfill_event_shape.py

@@ -0,0 +1,48 @@
+#!/usr/bin/env python3
+"""Backfill events.shape_* from each event's .h5 waveform samples. Idempotent."""
+from __future__ import annotations
+import argparse, logging, sys
+from pathlib import Path
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
+from sfm.database import SeismoDb
+from sfm.waveform_store import WaveformStore
+from sfm.shape_metrics import shape_from_h5
+
+log = logging.getLogger("backfill_event_shape")
+
+def backfill_shape(db: SeismoDb, store: WaveformStore, *, dry_run: bool = False) -> dict:
+    counts = {"updated": 0, "skipped_no_h5": 0, "skipped_no_samples": 0}
+    for row in db.query_events(limit=1_000_000):
+        serial, filename = row.get("serial"), row.get("blastware_filename")
+        if not serial or not filename:
+            counts["skipped_no_h5"] += 1; continue
+        h5_path = store.hdf5_path_for(serial, filename)
+        if not h5_path.exists():
+            counts["skipped_no_h5"] += 1; continue
+        shape = shape_from_h5(h5_path)
+        if shape is None:
+            counts["skipped_no_samples"] += 1; continue
+        if not dry_run:
+            with db._connect() as conn:
+                conn.execute(
+                    "UPDATE events SET shape_crest_factor=?, shape_near_peak_count=?, "
+                    "shape_sample_count=?, shape_axis=? WHERE id=?",
+                    (shape["crest_factor"], shape["near_peak_count"],
+                     shape["sample_count"], shape["axis"], row["id"]))
+        counts["updated"] += 1
+    log.info("backfill_shape: %s", counts)
+    return counts
+
+def main(argv=None) -> int:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--db-path", required=True)
+    ap.add_argument("--store-root", required=True)
+    ap.add_argument("--dry-run", action="store_true")
+    a = ap.parse_args(argv)
+    logging.basicConfig(level=logging.INFO)
+    counts = backfill_shape(SeismoDb(a.db_path), WaveformStore(a.store_root), dry_run=a.dry_run)
+    print(counts)
+    return 0
+
+if __name__ == "__main__":
+    raise SystemExit(main())

tests/test_backfill_event_shape.py

@@ -0,0 +1,35 @@
+from __future__ import annotations
+import numpy as np, h5py
+
+from sfm.database import SeismoDb
+from sfm.waveform_store import WaveformStore
+from scripts.backfill_event_shape import backfill_shape
+from minimateplus.models import Event
+
+
+def _h5(path, long):
+    with h5py.File(path, "w") as f:
+        g = f.create_group("samples")
+        for k in ("Tran", "Vert"):
+            g.create_dataset(k, data=np.zeros(1024, "float32"))
+        g.create_dataset("Long", data=np.asarray(long, "float32"))
+
+
+def test_backfill_updates_shape_and_is_idempotent(tmp_path):
+    db = SeismoDb(tmp_path / "s.db")
+    store = WaveformStore(tmp_path / "waveforms")
+    ev = Event(index=0)
+    ev._waveform_key = bytes.fromhex("0111abcd")
+    db.insert_events([ev], serial="BE1",
+                     waveform_records={ev._waveform_key.hex():
+                                       {"filename": "F.CE0W", "filesize": 10}})
+    # place the .h5 where store.paths_for expects it
+    long = np.zeros(1024); long[100] = 0.48
+    _h5(store.hdf5_path_for("BE1", "F.CE0W"), long)
+
+    c1 = backfill_shape(db, store)
+    assert c1["updated"] == 1
+    row = db.query_events(serial="BE1")[0]
+    assert row["shape_axis"] == "Long" and row["shape_near_peak_count"] <= 3
+    c2 = backfill_shape(db, store)                  # idempotent: re-run overwrites same values
+    assert db.query_events(serial="BE1")[0]["shape_crest_factor"] == row["shape_crest_factor"]