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[update] re-implemented code that was lost when corr_pick was integrated in pylot. Use all reference-pick-corrected theoretical picks as correlation reference time instead of using only reference picks

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Marcel Paffrath 2025-03-19 15:43:24 +01:00
parent 2dc27013b2
commit c989b2abc9
2 changed files with 20 additions and 10 deletions
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6
pylot/core/util/dataprocessing.py
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@ -220,9 +220,9 @@ class Metadata(object):
network_name = network.code
if not station_name in self.stations_dict.keys():
st_id = '{}.{}'.format(network_name, station_name)
self.stations_dict[st_id] = {'latitude': station[0].latitude,
'longitude': station[0].longitude,
'elevation': station[0].elevation}
self.stations_dict[st_id] = {'latitude': station.latitude,
'longitude': station.longitude,
'elevation': station.elevation}
read_stat = {'xml': stat_info_from_inventory,
'dless': stat_info_from_parser}

24
pylot/correlation/pick_correlation_correction.py
View File

@ -436,7 +436,7 @@ def correlation_main(database_path_dmt: str, pylot_infile_path: str, params: dic
# iterate over all events in "database_path_dmt"
for eventindex, eventdir in enumerate(eventdirs):
if not istart <= eventindex < istop:
if not istart <= eventindex + 1 < istop:
continue
if select_events and not os.path.split(eventdir)[-1] in select_events:
@ -639,10 +639,19 @@ def correlate_event(eventdir: str, pylot_parameter: PylotParameter, params: dict
if len(picks) < params[phase_type]['min_picks_autopylot']:
logging.info('Not enough automatic picks for correlation. Continue!')
continue
# calculate corrected taupy picks and remove strong outliers
taupypicks_corr_initial, median_diff = get_corrected_taupy_picks(picks, taupypicks_orig)
picks = remove_outliers(picks, taupypicks_corr_initial,
params[phase_type]['initial_pick_outlier_threshold'])
## calculate corrected taupy picks and remove strong outliers - part commented out for now. Maybe make this
## another option but I think it is not worth it
# taupypicks_corr_initial, median_diff = get_corrected_taupy_picks(picks, taupypicks_orig)
# picks = remove_outliers(picks, taupypicks_corr_initial,
# params[phase_type]['initial_pick_outlier_threshold'])
# use mean/median corrected picks from taupy as the new reference picks. This largely increases the yield
# of final picks since every station has a decent reference onset now for a correlation
taupypicks, time_shift = get_corrected_taupy_picks(picks, taupypicks_orig, all_available=True)
picks = copy.deepcopy(taupypicks)
for pick in picks:
pick.method_id.id = 'auto'
if phase_type == 'S':
# check whether rotation to ZNE is possible (to get rid of horizontal channel 1,2,3)
@ -830,7 +839,7 @@ def get_picks_mean(picks: list) -> UTCDateTime:
def get_corrected_taupy_picks(picks: list, taupypicks: list, all_available: bool = False) -> tuple:
""" get mean/median from picks taupy picks, correct latter for the difference """
""" get mean/median from picks relative to taupy picks, correct latter for the difference """
def nwst_id_from_wfid(wfid):
return '{}.{}'.format(wfid.network_code if wfid.network_code else '',
@ -1988,4 +1997,5 @@ if __name__ == "__main__":
# MAIN +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
correlation_main(ARGS.dmt_path, ARGS.pylot_infile, params=CORR_PARAMS, istart=int(ARGS.istart),
istop=int(ARGS.istop),
channel_config=CHANNELS, update=ARGS.update, event_blacklist=ARGS.blacklist)
channel_config=CHANNELS, update=ARGS.update, event_blacklist=ARGS.blacklist,
select_events=['20250107_010516.a'])