#!/usr/bin/env python3 # -*- coding: utf-8 -*- import os import csv import argparse from pathlib import Path from collections import defaultdict from concurrent.futures import ThreadPoolExecutor, wait, FIRST_COMPLETED import h5py import numpy as np from obspy import read, UTCDateTime DEFAULT_LOCATION = "--" def normalize_location(location, default=DEFAULT_LOCATION): if location is None: return default location = str(location).strip() return location if location else default def make_station_id(network, station, location, default_location=DEFAULT_LOCATION): network = str(network or "").strip() station = str(station or "").strip() location = normalize_location(location, default_location) return f"{network}.{station}.{location}" def make_station_key(network, station): network = str(network or "").strip() station = str(station or "").strip() return f"{network}.{station}" def split_station_id(station_id, default_location=DEFAULT_LOCATION): parts = str(station_id).split(".") network = parts[0] if len(parts) > 0 else "" station = parts[1] if len(parts) > 1 else "" location = parts[2] if len(parts) > 2 else default_location return network, station, normalize_location(location, default_location) def parse_utc_or_none(value): value = str(value or "").strip() if not value: return None return UTCDateTime(value) def utc_to_group_id(t: UTCDateTime, level: str) -> str: if level == "year": return f"{t.year:04d}-01-01T00:00:00.000000Z" if level == "day": return f"{t.year:04d}-{t.month:02d}-{t.day:02d}T00:00:00.000000Z" raise ValueError(f"Unsupported level: {level}") def day_file_id(t: UTCDateTime) -> str: return f"{t.year:04d}{t.month:02d}{t.day:02d}" def set_common_attrs(obj, level, node_type, parent_type): obj.attrs["level"] = level obj.attrs["type"] = node_type obj.attrs["parent_type"] = parent_type def load_station_locations_csv(loc_file, default_location=DEFAULT_LOCATION): """ 支持两种格式： 1. 有表头： net,sta,lat,lon,elev_m,start,end 2. 无表头： CI,WBM,35.60839,-117.89049,892.0,1979-09-26T00:00:00.000000Z,3000-01-01T00:00:00.000000Z 注意： 位置匹配只使用 network.station，不使用 location。 """ locations = defaultdict(list) if not loc_file or not os.path.exists(loc_file): print(f"[WARN] Location CSV file not found: {loc_file}") return dict(locations) with open(loc_file, "r", encoding="utf-8-sig", newline="") as f: sample = f.readline() f.seek(0) first_cols = [x.strip().lower() for x in sample.strip().split(",")] has_header = {"net", "sta", "lat", "lon"}.issubset(set(first_cols)) if has_header: reader = csv.DictReader(f) for line_no, row in enumerate(reader, start=2): try: net = row["net"].strip() sta = row["sta"].strip() loc = normalize_location(row.get("location", default_location), default_location) start = parse_utc_or_none(row["start"]) end = parse_utc_or_none(row["end"]) key = make_station_key(net, sta) locations[key].append( { "network": net, "station": sta, "location": loc, "latitude": float(row["lat"]), "longitude": float(row["lon"]), "elevation": float(row["elev_m"]), "start": start, "end": end, "starttime": str(start) if start is not None else "", "endtime": str(end) if end is not None else "", } ) except Exception as e: print(f"[WARN] Failed to parse location CSV line {line_no}: {row}, error={e}") else: reader = csv.reader(f) for line_no, row in enumerate(reader, start=1): if not row or len(row) < 7: continue try: net = row[0].strip() sta = row[1].strip() lat = float(row[2]) lon = float(row[3]) elev = float(row[4]) start = parse_utc_or_none(row[5]) end = parse_utc_or_none(row[6]) key = make_station_key(net, sta) locations[key].append( { "network": net, "station": sta, "location": default_location, "latitude": lat, "longitude": lon, "elevation": elev, "start": start, "end": end, "starttime": str(start) if start is not None else "", "endtime": str(end) if end is not None else "", } ) except Exception as e: print(f"[WARN] Failed to parse location CSV line {line_no}: {row}, error={e}") for key in locations: locations[key].sort( key=lambda x: x["start"] if x["start"] is not None else UTCDateTime(0) ) return dict(locations) def match_station_location( station_locations, station_id, trace_start=None, trace_end=None, allow_fallback=True, ): """ 只按 network.station 匹配台站位置。 不使用 location code。 例如： waveform station_id = BK.BDM.00 location key = BK.BDM """ net, sta, _ = split_station_id(station_id) station_key = make_station_key(net, sta) records = station_locations.get(station_key, []) if not records: return None, "default_nan_no_station_record" if trace_start is None and trace_end is None: if allow_fallback: return records[-1], "fallback_nearest_time_network_station_only" return None, "default_nan_no_time_matched_position" matched = [] for rec in records: rec_start = rec.get("start") rec_end = rec.get("end") left_ok = True if rec_end is None or trace_start is None else trace_start < rec_end right_ok = True if rec_start is None or trace_end is None else trace_end >= rec_start if left_ok and right_ok: matched.append(rec) if matched: def strict_score(rec): rec_start = rec.get("start") if rec_start is None or trace_start is None: return 0 if rec_start <= trace_start: return abs(trace_start - rec_start) return abs(trace_start - rec_start) + 1e12 return sorted(matched, key=strict_score)[0], "strict_time_matched_network_station_only" if not allow_fallback: return None, "default_nan_no_time_matched_position" def fallback_score(rec): if trace_start is None: return 0 candidates = [] if rec.get("start") is not None: candidates.append(abs(trace_start - rec["start"])) if rec.get("end") is not None: candidates.append(abs(trace_start - rec["end"])) return min(candidates) if candidates else 0 return sorted(records, key=fallback_score)[0], "fallback_nearest_time_network_station_only" def find_mseed_files(input_dir): input_dir = Path(input_dir) suffixes = { ".mseed", ".msd", ".miniseed", ".seed", ".MSEED", ".MSD", ".MINISEED", ".SEED", } return sorted( p for p in input_dir.rglob("*") if p.is_file() and p.suffix in suffixes ) def read_one_mseed(mseed_file, default_location=DEFAULT_LOCATION): records = [] try: st = read(str(mseed_file)) except Exception as e: return records, f"[WARN] Failed to read {mseed_file}: {e}" for tr in st: net = tr.stats.network or "" sta = tr.stats.station or "" loc = normalize_location(tr.stats.location, default_location) cha = tr.stats.channel or "" start = tr.stats.starttime end = tr.stats.endtime station_id = make_station_id(net, sta, loc, default_location) records.append( { "year_id": utc_to_group_id(start, "year"), "day_id": utc_to_group_id(start, "day"), "day_file_id": day_file_id(start), "station_id": station_id, "channel": cha, "starttime_obj": start, "endtime_obj": end, "starttime": str(start), "endtime": str(end), "sampling_rate": float(tr.stats.sampling_rate), "delta": float(tr.stats.delta), "npts": int(tr.stats.npts), "network": net, "station": sta, "location": loc, "data": np.asarray(tr.data), "dtype": str(tr.data.dtype), "source_file": str(mseed_file), } ) return records, None def write_position_attrs(obj, matched, match_mode): obj.attrs["position_match_mode"] = match_mode obj.attrs["position_is_fallback"] = "fallback" in str(match_mode) if matched is not None: obj.attrs["longitude"] = matched.get("longitude", np.nan) obj.attrs["latitude"] = matched.get("latitude", np.nan) obj.attrs["elevation"] = matched.get("elevation", np.nan) obj.attrs["location_available"] = True obj.attrs["location_source"] = match_mode obj.attrs["station_position_starttime"] = matched.get("starttime", "") obj.attrs["station_position_endtime"] = matched.get("endtime", "") else: obj.attrs["longitude"] = np.nan obj.attrs["latitude"] = np.nan obj.attrs["elevation"] = np.nan obj.attrs["location_available"] = False obj.attrs["location_source"] = match_mode obj.attrs["station_position_starttime"] = "" obj.attrs["station_position_endtime"] = "" def write_station_position_history(station_grp, station_id, station_locations, default_location): if "position_history" in station_grp: return net, sta, _ = split_station_id(station_id, default_location) station_key = make_station_key(net, sta) pos_grp = station_grp.create_group("position_history") set_common_attrs(pos_grp, "position_history", "position_history_group", "station_group") records = station_locations.get(station_key, []) pos_grp.attrs["record_count"] = len(records) pos_grp.attrs["match_key"] = station_key pos_grp.attrs["match_rule"] = "network.station only; location ignored" for i, rec in enumerate(records): item_grp = pos_grp.create_group(str(i)) set_common_attrs(item_grp, "position_record", "position_record_group", "position_history_group") item_grp.attrs["network"] = rec.get("network", "") item_grp.attrs["station"] = rec.get("station", "") item_grp.attrs["location"] = rec.get("location", default_location) item_grp.attrs["longitude"] = rec.get("longitude", np.nan) item_grp.attrs["latitude"] = rec.get("latitude", np.nan) item_grp.attrs["elevation"] = rec.get("elevation", np.nan) item_grp.attrs["starttime"] = rec.get("starttime", "") item_grp.attrs["endtime"] = rec.get("endtime", "") def init_hdf5_root(h5, default_location, split_by_day=False): set_common_attrs(h5, "root", "hdf5_file", "none") h5.attrs["description"] = "Continuous waveform dataset converted from MiniSEED" h5.attrs["station_id_format"] = "network.station.location" h5.attrs["station_location_match_rule"] = "network.station only; location ignored" h5.attrs["empty_location_value"] = default_location h5.attrs["missing_coordinate_value"] = "NaN" h5.attrs["station_location_format"] = ( "CSV with header: net,sta,lat,lon,elev_m,start,end " "or no-header: net,sta,lat,lon,elev_m,start,end" ) h5.attrs["split_by_day"] = bool(split_by_day) def get_or_create_station_group( h5, year_id, day_id, station_id, station_locations, trace_start, trace_end, default_location, ): year_grp = h5.require_group(year_id) set_common_attrs(year_grp, "year", "year_group", "root") year_grp.attrs["utc_time"] = year_id day_grp = year_grp.require_group(day_id) set_common_attrs(day_grp, "day", "day_group", "year_group") day_grp.attrs["utc_time"] = day_id stations_grp = day_grp.require_group("stations") set_common_attrs(stations_grp, "stations", "stations_group", "day_group") stations_grp.attrs["description"] = "Container group for all stations under this day" station_grp = stations_grp.require_group(station_id) set_common_attrs(station_grp, "station", "station_group", "stations_group") network, station, location = split_station_id(station_id, default_location) station_grp.attrs["station_id"] = station_id station_grp.attrs["station_key"] = make_station_key(network, station) station_grp.attrs["network"] = network station_grp.attrs["station"] = station station_grp.attrs["location"] = location station_grp.attrs["location_default_value"] = default_location station_grp.attrs["location_is_default"] = location == default_location station_grp.attrs["instrument_time_range_start"] = str(trace_start) station_grp.attrs["instrument_time_range_end"] = str(trace_end) matched, match_mode = match_station_location( station_locations=station_locations, station_id=station_id, trace_start=trace_start, trace_end=trace_end, allow_fallback=True, ) write_position_attrs(station_grp, matched, match_mode) write_station_position_history( station_grp=station_grp, station_id=station_id, station_locations=station_locations, default_location=default_location, ) waveform_grp = station_grp.require_group("waveform") set_common_attrs(waveform_grp, "waveform", "waveform_group", "station_group") return station_grp, waveform_grp def next_dataset_index(channel_grp): max_idx = -1 for key in channel_grp.keys(): if str(key).isdigit(): max_idx = max(max_idx, int(key)) return max_idx + 1 def update_channel_summary_attrs(channel_grp, rec): channel_grp.attrs["channel"] = rec["channel"] old_count = int(channel_grp.attrs.get("segment_count", 0)) channel_grp.attrs["segment_count"] = old_count + 1 rec_start = rec["starttime_obj"] rec_end = rec["endtime_obj"] old_start = channel_grp.attrs.get("starttime", "") old_end = channel_grp.attrs.get("endtime", "") if not old_start: channel_grp.attrs["starttime"] = str(rec_start) else: old_start_t = UTCDateTime(str(old_start)) channel_grp.attrs["starttime"] = str(min(old_start_t, rec_start)) if not old_end: channel_grp.attrs["endtime"] = str(rec_end) else: old_end_t = UTCDateTime(str(old_end)) channel_grp.attrs["endtime"] = str(max(old_end_t, rec_end)) def write_one_record( h5, rec, station_locations, default_location, compression, compression_opts, shuffle, ): station_grp, waveform_grp = get_or_create_station_group( h5=h5, year_id=rec["year_id"], day_id=rec["day_id"], station_id=rec["station_id"], station_locations=station_locations, trace_start=rec["starttime_obj"], trace_end=rec["endtime_obj"], default_location=default_location, ) channel_grp = waveform_grp.require_group(rec["channel"]) set_common_attrs(channel_grp, "channel", "channel_group", "waveform_group") update_channel_summary_attrs(channel_grp, rec) matched, match_mode = match_station_location( station_locations=station_locations, station_id=rec["station_id"], trace_start=rec["starttime_obj"], trace_end=rec["endtime_obj"], allow_fallback=True, ) write_position_attrs(channel_grp, matched, match_mode) ds_name = str(next_dataset_index(channel_grp)) create_kwargs = {} if compression and compression.lower() != "none": create_kwargs["compression"] = compression if compression.lower() == "gzip": create_kwargs["compression_opts"] = compression_opts create_kwargs["shuffle"] = shuffle ds = channel_grp.create_dataset( ds_name, data=rec["data"], **create_kwargs, ) set_common_attrs(ds, "segment", "waveform_dataset", "channel_group") write_position_attrs(ds, matched, match_mode) ds.attrs["segment_index"] = int(ds_name) ds.attrs["network"] = rec["network"] ds.attrs["station"] = rec["station"] ds.attrs["station_key"] = make_station_key(rec["network"], rec["station"]) ds.attrs["location"] = rec["location"] ds.attrs["location_is_default"] = rec["location"] == default_location ds.attrs["channel"] = rec["channel"] ds.attrs["sampling_rate"] = rec["sampling_rate"] ds.attrs["delta"] = rec["delta"] ds.attrs["npts"] = rec["npts"] ds.attrs["starttime"] = rec["starttime"] ds.attrs["endtime"] = rec["endtime"] ds.attrs["mseed_source_file"] = rec["source_file"] ds.attrs["dtype"] = rec["dtype"] def output_path_for_day(output, day_id): output = Path(output) if output.suffix.lower() in [".h5", ".hdf5"]: out_dir = output.parent stem = output.stem else: out_dir = output stem = "continuous_waveform" out_dir.mkdir(parents=True, exist_ok=True) return out_dir / f"{stem}_{day_id}.h5" def convert_mseed_to_hdf5_streaming( mseed_files, station_locations, output_file, num_workers=4, max_pending=16, default_location=DEFAULT_LOCATION, compression="gzip", compression_opts=4, shuffle=True, split_by_day=False, ): total = len(mseed_files) submitted = 0 finished = 0 written_records = 0 h5_files = {} def get_h5_for_record(rec): if not split_by_day: key = "__single__" if key not in h5_files: output_path = Path(output_file) output_path.parent.mkdir(parents=True, exist_ok=True) h5 = h5py.File(output_path, "w") init_hdf5_root(h5, default_location, split_by_day=False) h5_files[key] = h5 return h5_files[key] key = rec["day_file_id"] if key not in h5_files: output_path = output_path_for_day(output_file, key) h5 = h5py.File(output_path, "w") init_hdf5_root(h5, default_location, split_by_day=True) h5.attrs["day_file_id"] = key h5_files[key] = h5 return h5_files[key] try: with ThreadPoolExecutor(max_workers=num_workers) as executor: pending = set() def submit_more(): nonlocal submitted while submitted < total and len(pending) < max_pending: future = executor.submit( read_one_mseed, mseed_files[submitted], default_location, ) pending.add(future) submitted += 1 submit_more() while pending: done, pending_remaining = wait(pending, return_when=FIRST_COMPLETED) pending = pending_remaining for future in done: finished += 1 records, warning = future.result() if warning: print(warning) records.sort( key=lambda r: ( r["day_file_id"], r["year_id"], r["day_id"], r["station_id"], r["channel"], r["starttime_obj"], ) ) for rec in records: h5 = get_h5_for_record(rec) write_one_record( h5=h5, rec=rec, station_locations=station_locations, default_location=default_location, compression=compression, compression_opts=compression_opts, shuffle=shuffle, ) written_records += 1 if finished % 100 == 0 or finished == total: print( f"[INFO] Progress: files {finished}/{total}, " f"written waveform segments {written_records}, " f"open hdf5 files {len(h5_files)}" ) del records submit_more() finally: for h5 in h5_files.values(): h5.close() print(f"[OK] Written waveform segments: {written_records}") if split_by_day: print(f"[OK] HDF5 files written by day under: {Path(output_file).parent if Path(output_file).suffix else output_file}") else: print(f"[OK] HDF5 written to: {output_file}") def main(): parser = argparse.ArgumentParser( description="Convert MiniSEED files to hierarchical HDF5." ) parser.add_argument( "--input_dir", default="data/continous_usa/data", help="Directory containing MiniSEED files.", ) parser.add_argument( "--loc_file", default="data/continous_usa/stations.csv", help="Station CSV file.", ) parser.add_argument( "--output", default="data/hdf5/continuous_waveform_usa.h5", help=( "Output HDF5 file. If --split_by_day is enabled, this is used as " "a filename prefix, e.g. continuous_waveform_usa_20190701.h5." ), ) parser.add_argument( "--split_by_day", action="store_true", default=True, help="Write one HDF5 file per day.", ) parser.add_argument( "--num_workers", type=int, default=2, help="Number of threads for reading MiniSEED files.", ) parser.add_argument( "--max_pending", type=int, default=4, help="Maximum number of pending read tasks.", ) parser.add_argument( "--default_location", default=DEFAULT_LOCATION, help='Default location code when MiniSEED location is empty. Default: "--".', ) parser.add_argument( "--compression", default="gzip", choices=["gzip", "lzf", "none"], help="Dataset compression method.", ) parser.add_argument( "--compression_opts", type=int, default=4, help="Compression level for gzip.", ) parser.add_argument( "--no_shuffle", action="store_true", help="Disable HDF5 shuffle filter.", ) args = parser.parse_args() station_locations = load_station_locations_csv( args.loc_file, default_location=args.default_location, ) print(f"[INFO] Loaded station location histories for {len(station_locations)} station keys.") mseed_files = find_mseed_files(args.input_dir) print(f"[INFO] Found {len(mseed_files)} MiniSEED files.") convert_mseed_to_hdf5_streaming( mseed_files=mseed_files, station_locations=station_locations, output_file=args.output, num_workers=args.num_workers, max_pending=args.max_pending, default_location=args.default_location, compression=args.compression, compression_opts=args.compression_opts, shuffle=not args.no_shuffle, split_by_day=args.split_by_day, ) if __name__ == "__main__": main()