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"""Build an independent, coverage-qualified reference-arrival table.
The output is derived only from the annotation JSON, waveform-segment SQLite
index, and optional response JSON. It does not read automatic-picker outputs.
C0 requires an exact NSLC segment and a finite sample at the arrival time.
C1--C3 are configuration-dependent and
their window, gap, component, sample-rate, and response requirements are stored
in the output metadata table.
"""
from __future__ import annotations
import argparse
import json
import sqlite3
import sys
from collections import Counter, defaultdict
from pathlib import Path
from typing import Any, Iterable
ROOT = Path(__file__).resolve().parents[1]
if str(ROOT) not in sys.path:
sys.path.insert(0, str(ROOT))
from scripts.evaluate_picks import WaveformCoverageIndex, parse_utc_to_epoch_seconds
def norm_location(value: Any) -> str:
text = "" if value is None else str(value).strip()
return text if text else "--"
def release_path(path: Path | None) -> str | None:
"""Store release-relative paths when inputs are inside the repository."""
if path is None:
return None
resolved = path.expanduser().resolve()
try:
return resolved.relative_to(ROOT.resolve()).as_posix()
except ValueError:
return str(resolved)
def iter_arrivals(annotation: dict[str, Any]) -> Iterable[dict[str, Any]]:
for year in annotation["years"].values():
for day_key, day in year["days"].items():
period = "2019" if day_key.startswith("2019") else "2021"
for event_id, event in day["events"].items():
for station_id, station in event["stations"].items():
for pick in station.get("picks", []):
yield {
"period": period,
"event_id": str(event_id),
"station_id": str(pick.get("station_id") or station_id),
"phase": str(pick.get("phase", "")).upper(),
"status": str(pick.get("status", "unknown")),
"pick_time": str(pick.get("time")),
"pick_time_epoch": parse_utc_to_epoch_seconds(pick.get("time")),
"distance_km": pick.get("distance_km"),
}
class ResponseIndex:
def __init__(self, path: Path | None) -> None:
self.by_key: dict[tuple[str, str, str, str], list[tuple[float, float]]] = defaultdict(list)
if path is None:
return
with path.open() as f:
payload = json.load(f)
for item in payload.get("responses", []):
key = (
str(item.get("network", "")),
str(item.get("station", "")),
norm_location(item.get("location")),
str(item.get("channel", "")).upper(),
)
start = parse_utc_to_epoch_seconds(item.get("epoch_start"))
end_value = item.get("epoch_end")
end = (
parse_utc_to_epoch_seconds(end_value)
if end_value
else float("inf")
)
self.by_key[key].append((start, end))
def response_match_count(
self,
station_key: str,
location: str,
channel: str,
time_epoch: float,
) -> int:
try:
network, station = station_key.split(".", 1)
except ValueError:
return 0
key = (network, station, norm_location(location), str(channel).upper())
return sum(
1 for start, end in self.by_key.get(key, [])
if start <= time_epoch < end
)
def create_output(path: Path) -> sqlite3.Connection:
if path.exists():
path.unlink()
path.parent.mkdir(parents=True, exist_ok=True)
con = sqlite3.connect(path)
con.executescript(
"""
CREATE TABLE metadata (key TEXT PRIMARY KEY, value_json TEXT NOT NULL);
CREATE TABLE reference_arrivals (
arrival_id INTEGER PRIMARY KEY,
period TEXT NOT NULL,
event_id TEXT NOT NULL,
station_id TEXT NOT NULL,
phase TEXT NOT NULL,
status TEXT NOT NULL,
pick_time TEXT NOT NULL,
pick_time_epoch REAL NOT NULL,
distance_km REAL,
c0_point_covered INTEGER NOT NULL,
c1_window_covered INTEGER NOT NULL,
c2_component_covered INTEGER NOT NULL,
c3_processing_ready INTEGER NOT NULL,
matched_location TEXT,
channel_family TEXT,
component_count INTEGER NOT NULL,
channels_json TEXT NOT NULL,
component_channels_json TEXT NOT NULL,
component_gap_fractions_json TEXT NOT NULL,
window_gap_fraction REAL NOT NULL,
required_component_gap_fraction REAL NOT NULL,
response_available INTEGER NOT NULL,
sample_rate_ready INTEGER NOT NULL,
manual_primary_reference INTEGER NOT NULL
);
CREATE INDEX idx_reference_station_phase_time
ON reference_arrivals(station_id, phase, pick_time_epoch);
CREATE INDEX idx_reference_period_status_coverage
ON reference_arrivals(period, status, c0_point_covered);
CREATE INDEX idx_reference_event ON reference_arrivals(event_id);
"""
)
return con
def build(args: argparse.Namespace) -> Counter:
with args.annotation_json.open() as f:
annotation = json.load(f)
coverage = WaveformCoverageIndex(args.waveform_db, args.channel_families)
responses = ResponseIndex(args.response_json)
con = create_output(args.output)
config = {
"schema": "seismicx-cont-reference-arrivals-v1",
"sources": {
"annotation_json": release_path(args.annotation_json),
"waveform_db": release_path(args.waveform_db),
"hdf5_waveforms": "h5_file and dataset_path fields in waveform_db",
"response_json": release_path(args.response_json),
},
"coverage": {
"C0": "exact NSLC point coverage with finite-sample validation",
"C1": "at least one observed component satisfies the finite-sample window gap threshold",
"C2": "all declared observed components satisfy the finite-sample window gap threshold",
"C3": (
"C2 plus declared sample-rate requirements and, when requested, "
"exactly one NSLC-and-epoch response match per required component"
),
"channel_families": list(args.channel_families),
"finite_sample_validation": True,
"window_before_s": args.window_before_s,
"window_after_s": args.window_after_s,
"max_gap_fraction": args.max_gap_fraction,
"required_components": list(args.required_components),
"minimum_sample_rate_hz": args.minimum_sample_rate_hz,
"require_response": args.require_response,
},
"reference_settings": {
"primary": "manual labels satisfying the declared coverage level",
"expanded": "manual plus operational automatic labels satisfying the declared coverage level",
},
}
con.executemany(
"INSERT INTO metadata(key, value_json) VALUES (?, ?)",
[(key, json.dumps(value, sort_keys=True)) for key, value in config.items()],
)
sql = """
INSERT INTO reference_arrivals (
period, event_id, station_id, phase, status, pick_time,
pick_time_epoch, distance_km, c0_point_covered, c1_window_covered,
c2_component_covered, c3_processing_ready, matched_location,
channel_family, component_count, channels_json,
component_channels_json, component_gap_fractions_json,
window_gap_fraction, required_component_gap_fraction,
response_available, sample_rate_ready, manual_primary_reference
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
"""
counts: Counter = Counter()
rows: list[tuple[Any, ...]] = []
for arrival in iter_arrivals(annotation):
details = coverage.coverage_window_details(
arrival["station_id"],
arrival["pick_time_epoch"],
args.window_before_s,
args.window_after_s,
args.max_gap_fraction,
args.required_components,
)
component_channels = details["component_channels"]
required_channels = [
component_channels[item]
for item in args.required_components
if item in component_channels
]
response_available = bool(required_channels) and len(required_channels) == len(
args.required_components
) and all(
responses.response_match_count(
str(details["station_key"]),
str(details["matched_location"]),
channel,
arrival["pick_time_epoch"],
) == 1
for channel in required_channels
)
sample_rates = details["component_sample_rates_hz"]
sample_rate_ready = all(
component in sample_rates
and any(rate >= args.minimum_sample_rate_hz for rate in sample_rates[component])
for component in args.required_components
)
c3 = bool(details["component_covered"] and sample_rate_ready)
if args.require_response:
c3 = c3 and response_available
rows.append(
(
arrival["period"], arrival["event_id"], arrival["station_id"],
arrival["phase"], arrival["status"], arrival["pick_time"],
arrival["pick_time_epoch"], arrival["distance_km"],
int(details["point_covered"]), int(details["window_covered"]),
int(details["component_covered"]), int(c3),
details["matched_location"], details["channel_family"],
int(details["component_count"]), json.dumps(details["channels"]),
json.dumps(component_channels, sort_keys=True),
json.dumps(details["component_gap_fractions"], sort_keys=True),
float(details["window_gap_fraction"]),
float(details["required_component_gap_fraction"]),
int(response_available), int(sample_rate_ready),
int(arrival["status"] == "manual"),
)
)
counts["arrivals"] += 1
for level, field in (
("C0", "point_covered"),
("C1", "window_covered"),
("C2", "component_covered"),
):
if details[field]:
counts[level] += 1
if c3:
counts["C3"] += 1
if len(rows) >= 5000:
con.executemany(sql, rows)
rows.clear()
if rows:
con.executemany(sql, rows)
con.execute(
"INSERT INTO metadata(key, value_json) VALUES (?, ?)",
("summary", json.dumps(dict(counts), sort_keys=True)),
)
con.commit()
con.close()
coverage.close()
return counts
def main() -> None:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--annotation-json",
type=Path,
default=ROOT / "data" / "label" / "annotations_for_continuous_hdf5.json",
)
parser.add_argument(
"--waveform-db",
type=Path,
default=ROOT / "data" / "index" / "waveform_index.sqlite",
)
parser.add_argument(
"--response-json",
type=Path,
default=ROOT / "data" / "response" / "instrument_responses.json",
)
parser.add_argument(
"--output",
type=Path,
default=ROOT / "data" / "label" / "reference_arrivals.sqlite",
)
parser.add_argument("--channel-families", nargs="+", default=["HH", "BH", "EH", "HN"])
parser.add_argument("--window-before-s", type=float, required=True)
parser.add_argument("--window-after-s", type=float, required=True)
parser.add_argument("--max-gap-fraction", type=float, default=0.0)
parser.add_argument(
"--required-components", nargs="+", default=["Z", "H1", "H2"]
)
parser.add_argument("--minimum-sample-rate-hz", type=float, default=0.0)
parser.add_argument("--require-response", action="store_true")
args = parser.parse_args()
counts = build(args)
print(json.dumps({"output": str(args.output), "counts": dict(counts)}, indent=2))
if __name__ == "__main__":
main()
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