def _qc_event(
event: Event,
min_stations: int = None,
auto_picks: bool = True,
auto_event: bool = True,
event_type: Union[list, str] = None,
) -> tuple:
"""
QC an individual event - removes picks in place.
Returns
-------
tuple of (event: Event, keep: bool)
"""
if event_type is not None and isinstance(event_type, str):
event_type = [event_type]
if event_type is not None and event.event_type not in event_type:
return event, False
elif not auto_event:
if "manual" not in [ori.evaluation_mode for ori in event.origins]:
return event, False
if not auto_picks:
pick_ids_to_remove = [
p.resource_id for p in event.picks
if p.evaluation_mode == "automatic"
]
# remove arrivals and amplitudes and station_magnitudes
event.picks = [
p for p in event.picks if p.resource_id not in pick_ids_to_remove
]
event = remove_unreferenced(event)[0]
stations = {p.waveform_id.station_code for p in event.picks}
if len(stations) < min_stations:
return event, False
return event, True
def __init__(self, parent=None, evtdata=None):
self._parent = parent
if self.getParent():
self.comp = parent.getComponent()
else:
self.comp = 'Z'
self.wfdata = Stream()
self._new = False
if isinstance(evtdata, ObsPyEvent) or isinstance(evtdata, Event):
pass
elif isinstance(evtdata, dict):
evt = readPILOTEvent(**evtdata)
evtdata = evt
elif isinstance(evtdata, str):
try:
cat = read_events(evtdata)
if len(cat) is not 1:
raise ValueError('ambiguous event information for file: '
'{file}'.format(file=evtdata))
evtdata = cat[0]
except TypeError as e:
if 'Unknown format for file' in e.message:
if 'PHASES' in evtdata:
picks = picksdict_from_pilot(evtdata)
evtdata = ObsPyEvent()
evtdata.picks = picks_from_picksdict(picks)
elif 'LOC' in evtdata:
raise NotImplementedError('PILOT location information '
'read support not yet '
'implemeted.')
else:
raise e
else:
raise e
else: # create an empty Event object
self.setNew()
evtdata = ObsPyEvent()
evtdata.picks = []
self.evtdata = evtdata
self.wforiginal = None
self.cuttimes = None
self.dirty = False
latitude=str(lat[x]),
depth=str(dep[x]))
magnitude = Magnitude(mag = ml[x], magnitude_type = "M", origin_id = (str(orid[x])))
arrival = Arrival(pick_id = rd, phase = str(phase[x]))
event.picks.append(picks)
event.origins.append(origin)
origin.arrivals.append(arrival)
event.magnitudes.append(magnitude)
db_catalog.append(event)
#Only include picks for stations used
all_picks=[]
for event in db_catalog:
stations = ['KCT', 'KMPB', 'KCR', 'KHMB', 'KCS', 'KCO', 'KMR', 'KPP']
event.picks = [pick for pick in event.picks if pick.waveform_id.station_code in stations]
all_picks+= [(pick.waveform_id.station_code, pick.waveform_id.channel_code) for pick in event.picks]
new_catalog=Catalog()
for event in db_catalog:
event.picks = [pick for pick in event.picks if (pick.waveform_id.station_code, pick.waveform_id.channel_code) in all_picks]
new_catalog.append(event)
# count number of picks for each event in catalog
n_picks = [len(event.picks) for event in new_catalog]
#Save catalog
new_catalog.write("DB_Event_Catalog" + '.xml', "QUAKEML")
# =============================================================================
# ## 2. LOAD CATALOG IF AVAILABLE
def stalta_pick(stream,
stalen,
ltalen,
trig_on,
trig_off,
freqmin=False,
freqmax=False,
show=False):
"""
Basic sta/lta picker, suggest using alternative in obspy.
Simple sta/lta (short-term average/long-term average) picker, using
obspy's :func:`obspy.signal.trigger.classic_sta_lta` routine to generate
the characteristic function.
Currently very basic quick wrapper, there are many other (better) options
in obspy in the :mod:`obspy.signal.trigger` module.
:type stream: obspy.core.stream.Stream
:param stream: The stream to pick on, can be any number of channels.
:type stalen: float
:param stalen: Length of the short-term average window in seconds.
:type ltalen: float
:param ltalen: Length of the long-term average window in seconds.
:type trig_on: float
:param trig_on: sta/lta ratio to trigger a detection/pick
:type trig_off: float
:param trig_off: sta/lta ratio to turn the trigger off - no further picks\
will be made between exceeding trig_on until trig_off is reached.
:type freqmin: float
:param freqmin: Low-cut frequency in Hz for bandpass filter
:type freqmax: float
:param freqmax: High-cut frequency in Hz for bandpass filter
:type show: bool
:param show: Show picks on waveform.
:returns: :class:`obspy.core.event.event.Event`
.. rubric:: Example
>>> from obspy import read
>>> from eqcorrscan.utils.picker import stalta_pick
>>> st = read()
>>> event = stalta_pick(st, stalen=0.2, ltalen=4, trig_on=10,
... trig_off=1, freqmin=3.0, freqmax=20.0)
>>> print(event.creation_info.author)
EQcorrscan
.. warning::
This function is not designed for accurate picking, rather it can give
a first idea of whether picks may be possible. Proceed with caution.
"""
event = Event()
event.origins.append(Origin())
event.creation_info = CreationInfo(author='EQcorrscan',
creation_time=UTCDateTime())
event.comments.append(Comment(text='stalta'))
picks = []
for tr in stream:
# We are going to assume, for now, that if the pick is made on the
# horizontal channel then it is an S, otherwise we will assume it is
# a P-phase: obviously a bad assumption...
if tr.stats.channel[-1] == 'Z':
phase = 'P'
else:
phase = 'S'
if freqmin and freqmax:
tr.detrend('simple')
tr.filter('bandpass',
freqmin=freqmin,
freqmax=freqmax,
corners=3,
zerophase=True)
df = tr.stats.sampling_rate
cft = classic_sta_lta(tr.data, int(stalen * df), int(ltalen * df))
triggers = trigger_onset(cft, trig_on, trig_off)
for trigger in triggers:
on = tr.stats.starttime + (trigger[0] / df)
# off = tr.stats.starttime + (trigger[1] / df)
wav_id = WaveformStreamID(station_code=tr.stats.station,
channel_code=tr.stats.channel,
network_code=tr.stats.network)
p = Pick(waveform_id=wav_id, phase_hint=phase, time=on)
Logger.info('Pick made: {0}'.format(p))
picks.append(p)
# QC picks
pick_stations = list(set([pick.waveform_id.station_code
for pick in picks]))
for pick_station in pick_stations:
station_picks = [
pick for pick in picks
if pick.waveform_id.station_code == pick_station
]
# If P-pick is after S-picks, remove it.
p_time = [
pick.time for pick in station_picks if pick.phase_hint == 'P'
]
s_time = [
pick.time for pick in station_picks if pick.phase_hint == 'S'
]
if p_time > s_time:
p_pick = [pick for pick in station_picks if pick.phase_hint == 'P']
for pick in p_pick:
Logger.info('P pick after S pick, removing P pick')
picks.remove(pick)
event.picks = picks
if show:
plotting.pretty_template_plot(stream,
event=event,
title='Autopicks',
size=(8, 9))
if len(event.picks) > 0:
event.origins[0].time = min([pick.time for pick in event.picks]) - 1
# event.origins[0].latitude = float('nan')
# event.origins[0].longitude = float('nan')
# Set arbitrary origin time
return event
def _dbs_associator(start_time,
end_time,
moving_window,
tbl,
pair_n,
save_dir,
station_list,
consider_combination=False):
if consider_combination == True:
if platform.system() == 'Windows':
Y2000_writer = open(save_dir + "\\" + "Y2000.phs", "w")
else:
Y2000_writer = open(save_dir + "/" + "Y2000.phs", "w")
traceNmae_dic = dict()
st = datetime.strptime(start_time, '%Y-%m-%d %H:%M:%S.%f')
et = datetime.strptime(end_time, '%Y-%m-%d %H:%M:%S.%f')
total_t = et - st
evid = 0
tt = st
pbar = tqdm(total=int(np.ceil(total_t.total_seconds() /
moving_window)),
ncols=100)
while tt < et:
detections = tbl[(tbl.event_start_time >= tt) & (
tbl.event_start_time < tt + timedelta(seconds=moving_window))]
pbar.update()
if len(detections) >= pair_n:
evid += 1
yr = "{:>4}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[0])
mo = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[1])
dy = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[2])
hr = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[0])
mi = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[1])
sec = "{:>4}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[2])
st_lat_DMS = _decimalDegrees2DMS(
float(detections.iloc[0]['stlat']), "Latitude")
st_lon_DMS = _decimalDegrees2DMS(
float(detections.iloc[0]['stlon']), "Longitude")
depth = 5.0
mag = 0.0
# QuakeML
print(detections.iloc[0]['event_start_time'])
if len(detections) / pair_n <= 2:
ch = pair_n
else:
ch = int(len(detections) - pair_n)
picks = []
for ns in range(ch, len(detections) + 1):
comb = 0
for ind in list(combinations(detections.index, ns)):
comb += 1
selected_detections = detections.loc[ind, :]
sorted_detections = selected_detections.sort_values(
'p_arrival_time')
Y2000_writer.write(
"%4d%2d%2d%2d%2d%4.2f%2.0f%1s%4.2f%3.0f%1s%4.2f%5.2f%3.2f\n"
% (int(yr), int(mo), int(dy), int(hr), int(mi),
float(sec), float(st_lat_DMS[0]),
str(st_lat_DMS[1]), float(st_lat_DMS[2]),
float(st_lon_DMS[0]), str(st_lon_DMS[1]),
float(st_lon_DMS[2]), float(depth), float(mag)))
station_buffer = []
row_buffer = []
tr_names = []
tr_names2 = []
for _, row in sorted_detections.iterrows():
trace_name = row['traceID'] + '*' + row[
'station'] + '*' + str(row['event_start_time'])
p_unc = row['p_unc']
p_prob = row['p_prob']
s_unc = row['s_unc']
s_prob = row['s_prob']
if p_unc:
Pweihgt = _weighcalculator_prob(p_prob *
(1 - p_unc))
else:
Pweihgt = _weighcalculator_prob(p_prob)
try:
Pweihgt = int(Pweihgt)
except Exception:
Pweihgt = 4
if s_unc:
Sweihgt = _weighcalculator_prob(s_prob *
(1 - s_unc))
else:
Sweihgt = _weighcalculator_prob(s_prob)
try:
Sweihgt = int(Sweihgt)
except Exception:
Sweihgt = 4
station = "{:<5}".format(row['station'])
network = "{:<2}".format(row['network'])
try:
yrp = "{:>4}".format(
str(row['p_arrival_time']).split(' ')
[0].split('-')[0])
mop = "{:>2}".format(
str(row['p_arrival_time']).split(' ')
[0].split('-')[1])
dyp = "{:>2}".format(
str(row['p_arrival_time']).split(' ')
[0].split('-')[2])
hrp = "{:>2}".format(
str(row['p_arrival_time']).split(' ')
[1].split(':')[0])
mip = "{:>2}".format(
str(row['p_arrival_time']).split(' ')
[1].split(':')[1])
sec_p = "{:>4}".format(
str(row['p_arrival_time']).split(' ')
[1].split(':')[2])
p = Pick(time=UTCDateTime(
row['p_arrival_time']),
waveform_id=WaveformStreamID(
network_code=network,
station_code=station.rstrip()),
phase_hint="P")
picks.append(p)
except Exception:
sec_p = None
try:
yrs = "{:>4}".format(
str(row['s_arrival_time']).split(' ')
[0].split('-')[0])
mos = "{:>2}".format(
str(row['s_arrival_time']).split(' ')
[0].split('-')[1])
dys = "{:>2}".format(
str(row['s_arrival_time']).split(' ')
[0].split('-')[2])
hrs = "{:>2}".format(
str(row['s_arrival_time']).split(' ')
[1].split(':')[0])
mis = "{:>2}".format(
str(row['s_arrival_time']).split(' ')
[1].split(':')[1])
sec_s = "{:>4}".format(
str(row['s_arrival_time']).split(' ')
[1].split(':')[2])
p = Pick(time=UTCDateTime(
row['p_arrival_time']),
waveform_id=WaveformStreamID(
network_code=network,
station_code=station.rstrip()),
phase_hint="S")
picks.append(p)
except Exception:
sec_s = None
if row['station'] not in station_buffer:
tr_names.append(trace_name)
station_buffer.append(row['station'])
if sec_s:
Y2000_writer.write(
"%5s%2s HHE %4d%2d%2d%2d%2d%5.2f %5.2fES %1d\n"
%
(station, network, int(yrs), int(mos),
int(dys), int(hrs), int(mis),
float(0.0), float(sec_s), Sweihgt))
if sec_p:
Y2000_writer.write(
"%5s%2s HHZ IP %1d%4d%2d%2d%2d%2d%5.2f %5.2f 0\n"
% (station, network, Pweihgt, int(yrp),
int(mop), int(dyp), int(hrp),
int(mip), float(sec_p), float(0.0)))
else:
tr_names2.append(trace_name)
if sec_s:
row_buffer.append(
"%5s%2s HHE %4d%2d%2d%2d%2d%5.2f %5.2fES %1d\n"
%
(station, network, int(yrs), int(mos),
int(dys), int(hrs), int(mis), 0.0,
float(sec_s), Sweihgt))
if sec_p:
row_buffer.append(
"%5s%2s HHZ IP %1d%4d%2d%2d%2d%2d%5.2f %5.2f 0\n"
% (station, network, Pweihgt, int(yrp),
int(mop), int(dyp), int(hrp),
int(mip), float(sec_p), float(0.0)))
Y2000_writer.write("{:<62}".format(' ') + "%10d" %
(evid) + '\n')
traceNmae_dic[str(evid)] = tr_names
if len(row_buffer) >= 2 * pair_n:
Y2000_writer.write(
"%4d%2d%2d%2d%2d%4.2f%2.0f%1s%4.2f%3.0f%1s%4.2f%5.2f%3.2f\n"
% (int(yr), int(mo), int(dy), int(hr), int(mi),
float(sec), float(st_lat_DMS[0]), str(
st_lat_DMS[1]), float(st_lat_DMS[2]),
float(st_lon_DMS[0]), str(st_lon_DMS[1]),
float(st_lon_DMS[2]), float(depth), float(mag)))
for rr in row_buffer:
Y2000_writer.write(rr)
Y2000_writer.write("{:<62}".format(' ') + "%10d" % (evid) +
'\n')
traceNmae_dic[str(evid)] = tr_names2
tt += timedelta(seconds=moving_window)
# plt.scatter(LTTP, TTP, s=10, marker='o', c='b', alpha=0.4, label='P')
# plt.scatter(LTTS, TTS, s=10, marker='o', c='r', alpha=0.4, label='S')
# plt.legend('upper right')
# plt.show()
print('The Number of Realizations: ' + str(evid) + '\n', flush=True)
jj = json.dumps(traceNmae_dic)
if platform.system() == 'Windows':
f = open(save_dir + "\\" + "traceNmae_dic.json", "w")
else:
f = open(save_dir + "/" + "traceNmae_dic.json", "w")
f.write(jj)
f.close()
else:
if platform.system() == 'Windows':
Y2000_writer = open(save_dir + "\\" + "Y2000.phs", "w")
else:
Y2000_writer = open(save_dir + "/" + "Y2000.phs", "w")
cat = Catalog()
traceNmae_dic = dict()
st = datetime.strptime(start_time, '%Y-%m-%d %H:%M:%S.%f')
et = datetime.strptime(end_time, '%Y-%m-%d %H:%M:%S.%f')
total_t = et - st
evid = 200000
evidd = 100000
tt = st
pbar = tqdm(total=int(np.ceil(total_t.total_seconds() /
moving_window)))
while tt < et:
detections = tbl[(tbl.event_start_time >= tt) & (
tbl.event_start_time < tt + timedelta(seconds=moving_window))]
pbar.update()
if len(detections) >= pair_n:
yr = "{:>4}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[0])
mo = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[1])
dy = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[2])
hr = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[0])
mi = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[1])
sec = "{:>4}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[2])
st_lat_DMS = _decimalDegrees2DMS(
float(detections.iloc[0]['stlat']), "Latitude")
st_lon_DMS = _decimalDegrees2DMS(
float(detections.iloc[0]['stlon']), "Longitude")
depth = 5.0
mag = 0.0
Y2000_writer.write(
"%4d%2d%2d%2d%2d%4.2f%2.0f%1s%4.2f%3.0f%1s%4.2f%5.2f%3.2f\n"
% (int(yr), int(mo), int(dy), int(hr), int(mi), float(sec),
float(st_lat_DMS[0]), str(st_lat_DMS[1]),
float(st_lat_DMS[2]), float(st_lon_DMS[0]),
str(st_lon_DMS[1]), float(
st_lon_DMS[2]), float(depth), float(mag)))
event = Event()
origin = Origin(time=UTCDateTime(
detections.iloc[0]['event_start_time']),
longitude=detections.iloc[0]['stlon'],
latitude=detections.iloc[0]['stlat'],
method="EqTransformer")
event.origins.append(origin)
station_buffer = []
row_buffer = []
sorted_detections = detections.sort_values('p_arrival_time')
tr_names = []
tr_names2 = []
picks = []
for _, row in sorted_detections.iterrows():
trace_name = row['traceID'] + '*' + row[
'station'] + '*' + str(row['event_start_time'])
p_unc = row['p_unc']
p_prob = row['p_prob']
s_unc = row['s_unc']
s_prob = row['s_prob']
if p_unc:
Pweihgt = _weighcalculator_prob(p_prob * (1 - p_unc))
else:
Pweihgt = _weighcalculator_prob(p_prob)
try:
Pweihgt = int(Pweihgt)
except Exception:
Pweihgt = 4
if s_unc:
Sweihgt = _weighcalculator_prob(s_prob * (1 - s_unc))
else:
Sweihgt = _weighcalculator_prob(s_prob)
try:
Sweihgt = int(Sweihgt)
except Exception:
Sweihgt = 4
station = "{:<5}".format(row['station'])
network = "{:<2}".format(row['network'])
try:
yrp = "{:>4}".format(
str(row['p_arrival_time']).split(' ')[0].split('-')
[0])
mop = "{:>2}".format(
str(row['p_arrival_time']).split(' ')[0].split('-')
[1])
dyp = "{:>2}".format(
str(row['p_arrival_time']).split(' ')[0].split('-')
[2])
hrp = "{:>2}".format(
str(row['p_arrival_time']).split(' ')[1].split(':')
[0])
mip = "{:>2}".format(
str(row['p_arrival_time']).split(' ')[1].split(':')
[1])
sec_p = "{:>4}".format(
str(row['p_arrival_time']).split(' ')[1].split(':')
[2])
p = Pick(time=UTCDateTime(row['p_arrival_time']),
waveform_id=WaveformStreamID(
network_code=network,
station_code=station.rstrip()),
phase_hint="P",
method_id="EqTransformer")
picks.append(p)
except Exception:
sec_p = None
try:
yrs = "{:>4}".format(
str(row['s_arrival_time']).split(' ')[0].split('-')
[0])
mos = "{:>2}".format(
str(row['s_arrival_time']).split(' ')[0].split('-')
[1])
dys = "{:>2}".format(
str(row['s_arrival_time']).split(' ')[0].split('-')
[2])
hrs = "{:>2}".format(
str(row['s_arrival_time']).split(' ')[1].split(':')
[0])
mis = "{:>2}".format(
str(row['s_arrival_time']).split(' ')[1].split(':')
[1])
sec_s = "{:>4}".format(
str(row['s_arrival_time']).split(' ')[1].split(':')
[2])
p = Pick(time=UTCDateTime(row['s_arrival_time']),
waveform_id=WaveformStreamID(
network_code=network,
station_code=station.rstrip()),
phase_hint="S",
method_id="EqTransformer")
picks.append(p)
except Exception:
sec_s = None
if row['station'] not in station_buffer:
tr_names.append(trace_name)
station_buffer.append(row['station'])
if sec_s:
Y2000_writer.write(
"%5s%2s HHE %4d%2d%2d%2d%2d%5.2f %5.2fES %1d\n"
% (station, network, int(yrs), int(mos),
int(dys), int(hrs), int(mis), float(0.0),
float(sec_s), Sweihgt))
if sec_p:
Y2000_writer.write(
"%5s%2s HHZ IP %1d%4d%2d%2d%2d%2d%5.2f %5.2f 0\n"
% (station, network, Pweihgt, int(yrp),
int(mop), int(dyp), int(hrp), int(mip),
float(sec_p), float(0.0)))
else:
tr_names2.append(trace_name)
if sec_s:
row_buffer.append(
"%5s%2s HHE %4d%2d%2d%2d%2d%5.2f %5.2fES %1d\n"
% (station, network, int(yrs), int(mos),
int(dys), int(hrs), int(mis), 0.0,
float(sec_s), Sweihgt))
if sec_p:
row_buffer.append(
"%5s%2s HHZ IP %1d%4d%2d%2d%2d%2d%5.2f %5.2f 0\n"
% (station, network, Pweihgt, int(yrp),
int(mop), int(dyp), int(hrp), int(mip),
float(sec_p), float(0.0)))
event.picks = picks
event.preferred_origin_id = event.origins[0].resource_id
cat.append(event)
evid += 1
Y2000_writer.write("{:<62}".format(' ') + "%10d" % (evid) +
'\n')
traceNmae_dic[str(evid)] = tr_names
if len(row_buffer) >= 2 * pair_n:
Y2000_writer.write(
"%4d%2d%2d%2d%2d%4.2f%2.0f%1s%4.2f%3.0f%1s%4.2f%5.2f%3.2f\n"
% (int(yr), int(mo), int(dy), int(hr), int(mi),
float(sec), float(st_lat_DMS[0]), str(
st_lat_DMS[1]), float(st_lat_DMS[2]),
float(st_lon_DMS[0]), str(st_lon_DMS[1]),
float(st_lon_DMS[2]), float(depth), float(mag)))
for rr in row_buffer:
Y2000_writer.write(rr)
evid += 1
Y2000_writer.write("{:<62}".format(' ') + "%10d" % (evid) +
'\n')
traceNmae_dic[str(evid)] = tr_names2
elif len(row_buffer) < pair_n and len(row_buffer) != 0:
evidd += 1
traceNmae_dic[str(evidd)] = tr_names2
elif len(detections) < pair_n and len(detections) != 0:
tr_names = []
for _, row in detections.iterrows():
trace_name = row['traceID']
tr_names.append(trace_name)
evidd += 1
traceNmae_dic[str(evidd)] = tr_names
tt += timedelta(seconds=moving_window)
print('The Number of Associated Events: ' + str(evid - 200000) + '\n',
flush=True)
jj = json.dumps(traceNmae_dic)
if platform.system() == 'Windows':
f = open(save_dir + "\\" + "traceNmae_dic.json", "w")
else:
f = open(save_dir + "/" + "traceNmae_dic.json", "w")
f.write(jj)
f.close()
print(cat.__str__(print_all=True))
cat.write(save_dir + "/associations.xml", format="QUAKEML")
def full_test_event():
"""
Function to generate a basic, full test event
"""
test_event = Event()
test_event.origins.append(Origin())
test_event.origins[0].time = UTCDateTime("2012-03-26") + 1.2
test_event.event_descriptions.append(EventDescription())
test_event.event_descriptions[0].text = 'LE'
test_event.origins[0].latitude = 45.0
test_event.origins[0].longitude = 25.0
test_event.origins[0].depth = 15000
test_event.creation_info = CreationInfo(agency_id='TES')
test_event.origins[0].quality = OriginQuality(standard_error=0.01)
test_event.magnitudes.append(Magnitude())
test_event.magnitudes[0].mag = 0.1
test_event.magnitudes[0].magnitude_type = 'ML'
test_event.magnitudes[0].creation_info = CreationInfo('TES')
test_event.magnitudes[0].origin_id = test_event.origins[0].resource_id
test_event.magnitudes.append(Magnitude())
test_event.magnitudes[1].mag = 0.5
test_event.magnitudes[1].magnitude_type = 'Mc'
test_event.magnitudes[1].creation_info = CreationInfo('TES')
test_event.magnitudes[1].origin_id = test_event.origins[0].resource_id
test_event.magnitudes.append(Magnitude())
test_event.magnitudes[2].mag = 1.3
test_event.magnitudes[2].magnitude_type = 'Ms'
test_event.magnitudes[2].creation_info = CreationInfo('TES')
test_event.magnitudes[2].origin_id = test_event.origins[0].resource_id
# Define the test pick
_waveform_id_1 = WaveformStreamID(station_code='FOZ', channel_code='SHZ',
network_code='NZ')
_waveform_id_2 = WaveformStreamID(station_code='WTSZ', channel_code='BH1',
network_code=' ')
# Pick to associate with amplitude - 0
test_event.picks = [
Pick(waveform_id=_waveform_id_1, phase_hint='IAML',
polarity='undecidable', time=UTCDateTime("2012-03-26") + 1.68,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_1, onset='impulsive', phase_hint='PN',
polarity='positive', time=UTCDateTime("2012-03-26") + 1.68,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_1, phase_hint='IAML',
polarity='undecidable', time=UTCDateTime("2012-03-26") + 1.68,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_2, onset='impulsive', phase_hint='SG',
polarity='undecidable', time=UTCDateTime("2012-03-26") + 1.72,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_2, onset='impulsive', phase_hint='PN',
polarity='undecidable', time=UTCDateTime("2012-03-26") + 1.62,
evaluation_mode="automatic")]
# Test a generic local magnitude amplitude pick
test_event.amplitudes = [
Amplitude(generic_amplitude=2.0, period=0.4,
pick_id=test_event.picks[0].resource_id,
waveform_id=test_event.picks[0].waveform_id, unit='m',
magnitude_hint='ML', category='point', type='AML'),
Amplitude(generic_amplitude=10,
pick_id=test_event.picks[1].resource_id,
waveform_id=test_event.picks[1].waveform_id, type='END',
category='duration', unit='s', magnitude_hint='Mc',
snr=2.3),
Amplitude(generic_amplitude=5.0, period=0.6,
pick_id=test_event.picks[2].resource_id,
waveform_id=test_event.picks[0].waveform_id, unit='m',
category='point', type='AML')]
test_event.origins[0].arrivals = [
Arrival(time_weight=0, phase=test_event.picks[1].phase_hint,
pick_id=test_event.picks[1].resource_id),
Arrival(time_weight=2, phase=test_event.picks[3].phase_hint,
pick_id=test_event.picks[3].resource_id,
backazimuth_residual=5, time_residual=0.2, distance=15,
azimuth=25),
Arrival(time_weight=2, phase=test_event.picks[4].phase_hint,
pick_id=test_event.picks[4].resource_id,
backazimuth_residual=5, time_residual=0.2, distance=15,
azimuth=25)]
return test_event
def full_test_event():
"""
Function to generate a basic, full test event
"""
test_event = Event()
test_event.origins.append(Origin(
time=UTCDateTime("2012-03-26") + 1.2, latitude=45.0, longitude=25.0,
depth=15000))
test_event.event_descriptions.append(EventDescription())
test_event.event_descriptions[0].text = 'LE'
test_event.creation_info = CreationInfo(agency_id='TES')
test_event.magnitudes.append(Magnitude(
mag=0.1, magnitude_type='ML', creation_info=CreationInfo('TES'),
origin_id=test_event.origins[0].resource_id))
test_event.magnitudes.append(Magnitude(
mag=0.5, magnitude_type='Mc', creation_info=CreationInfo('TES'),
origin_id=test_event.origins[0].resource_id))
test_event.magnitudes.append(Magnitude(
mag=1.3, magnitude_type='Ms', creation_info=CreationInfo('TES'),
origin_id=test_event.origins[0].resource_id))
# Define the test pick
_waveform_id_1 = WaveformStreamID(station_code='FOZ', channel_code='SHZ',
network_code='NZ')
_waveform_id_2 = WaveformStreamID(station_code='WTSZ', channel_code='BH1',
network_code=' ')
# Pick to associate with amplitude - 0
test_event.picks = [
Pick(waveform_id=_waveform_id_1, phase_hint='IAML',
polarity='undecidable', time=UTCDateTime("2012-03-26") + 1.68,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_1, onset='impulsive', phase_hint='PN',
polarity='positive', time=UTCDateTime("2012-03-26") + 1.68,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_1, phase_hint='IAML',
polarity='undecidable', time=UTCDateTime("2012-03-26") + 1.68,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_2, onset='impulsive', phase_hint='SG',
polarity='undecidable', time=UTCDateTime("2012-03-26") + 1.72,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_2, onset='impulsive', phase_hint='PN',
polarity='undecidable', time=UTCDateTime("2012-03-26") + 1.62,
evaluation_mode="automatic")]
# Test a generic local magnitude amplitude pick
test_event.amplitudes = [
Amplitude(generic_amplitude=2.0, period=0.4,
pick_id=test_event.picks[0].resource_id,
waveform_id=test_event.picks[0].waveform_id, unit='m',
magnitude_hint='ML', category='point', type='AML'),
Amplitude(generic_amplitude=10,
pick_id=test_event.picks[1].resource_id,
waveform_id=test_event.picks[1].waveform_id, type='END',
category='duration', unit='s', magnitude_hint='Mc',
snr=2.3),
Amplitude(generic_amplitude=5.0, period=0.6,
pick_id=test_event.picks[2].resource_id,
waveform_id=test_event.picks[0].waveform_id, unit='m',
category='point', type='AML')]
test_event.origins[0].arrivals = [
Arrival(time_weight=0, phase=test_event.picks[1].phase_hint,
pick_id=test_event.picks[1].resource_id),
Arrival(time_weight=2, phase=test_event.picks[3].phase_hint,
pick_id=test_event.picks[3].resource_id,
backazimuth_residual=5, time_residual=0.2, distance=15,
azimuth=25),
Arrival(time_weight=2, phase=test_event.picks[4].phase_hint,
pick_id=test_event.picks[4].resource_id,
backazimuth_residual=5, time_residual=0.2, distance=15,
azimuth=25)]
# Add in error info (line E)
test_event.origins[0].quality = OriginQuality(
standard_error=0.01, azimuthal_gap=36)
# Origin uncertainty in Seisan is output as long-lat-depth, quakeML has
# semi-major and semi-minor
test_event.origins[0].origin_uncertainty = OriginUncertainty(
confidence_ellipsoid=ConfidenceEllipsoid(
semi_major_axis_length=3000, semi_minor_axis_length=1000,
semi_intermediate_axis_length=2000, major_axis_plunge=20,
major_axis_azimuth=100, major_axis_rotation=4))
test_event.origins[0].time_errors = QuantityError(uncertainty=0.5)
# Add in fault-plane solution info (line F) - Note have to check program
# used to determine which fields are filled....
test_event.focal_mechanisms.append(FocalMechanism(
nodal_planes=NodalPlanes(nodal_plane_1=NodalPlane(
strike=180, dip=20, rake=30, strike_errors=QuantityError(10),
dip_errors=QuantityError(10), rake_errors=QuantityError(20))),
method_id=ResourceIdentifier("smi:nc.anss.org/focalMechanism/FPFIT"),
creation_info=CreationInfo(agency_id="NC"), misfit=0.5,
station_distribution_ratio=0.8))
# Need to test high-precision origin and that it is preferred origin.
# Moment tensor includes another origin
test_event.origins.append(Origin(
time=UTCDateTime("2012-03-26") + 1.2, latitude=45.1, longitude=25.2,
depth=14500))
test_event.magnitudes.append(Magnitude(
mag=0.1, magnitude_type='MW', creation_info=CreationInfo('TES'),
origin_id=test_event.origins[-1].resource_id))
# Moment tensors go with focal-mechanisms
test_event.focal_mechanisms.append(FocalMechanism(
moment_tensor=MomentTensor(
derived_origin_id=test_event.origins[-1].resource_id,
moment_magnitude_id=test_event.magnitudes[-1].resource_id,
scalar_moment=100, tensor=Tensor(
m_rr=100, m_tt=100, m_pp=10, m_rt=1, m_rp=20, m_tp=15),
method_id=ResourceIdentifier(
'smi:nc.anss.org/momentTensor/BLAH'))))
return test_event
def outputOBSPY(hp, event=None, only_fm_picks=False):
"""
Make an Event which includes the current focal mechanism information from HASH
Use the 'only_fm_picks' flag to only include the picks HASH used for the FocalMechanism.
This flag will replace the 'picks' and 'arrivals' lists of existing events with new ones.
Inputs
-------
hp : hashpy.HashPype instance
event : obspy.core.event.Event
only_fm_picks : bool of whether to overwrite the picks/arrivals lists
Returns
-------
obspy.core.event.Event
Event will be new if no event was input, FocalMech added to existing event
"""
# Returns new (or updates existing) Event with HASH solution
n = hp.npol
if event is None:
event = Event(focal_mechanisms=[], picks=[], origins=[])
origin = Origin(arrivals=[])
origin.time = UTCDateTime(hp.tstamp)
origin.latitude = hp.qlat
origin.longitude = hp.qlon
origin.depth = hp.qdep
origin.creation_info = CreationInfo(version=hp.icusp)
origin.resource_id = ResourceIdentifier('smi:hash/Origin/{0}'.format(
hp.icusp))
for _i in range(n):
p = Pick()
p.creation_info = CreationInfo(version=hp.arid[_i])
p.resource_id = ResourceIdentifier('smi:nsl/Pick/{0}'.format(
p.creation_info.version))
p.waveform_id = WaveformStreamID(network_code=hp.snet[_i],
station_code=hp.sname[_i],
channel_code=hp.scomp[_i])
if hp.p_pol[_i] > 0:
p.polarity = 'positive'
else:
p.polarity = 'negative'
a = Arrival()
a.creation_info = CreationInfo(version=hp.arid[_i])
a.resource_id = ResourceIdentifier('smi:nsl/Arrival/{0}'.format(
p.creation_info.version))
a.azimuth = hp.p_azi_mc[_i, 0]
a.takeoff_angle = 180. - hp.p_the_mc[_i, 0]
a.pick_id = p.resource_id
origin.arrivals.append(a)
event.picks.append(p)
event.origins.append(origin)
event.preferred_origin_id = origin.resource_id.resource_id
else: # just update the changes
origin = event.preferred_origin()
picks = []
arrivals = []
for _i in range(n):
ind = hp.p_index[_i]
a = origin.arrivals[ind]
p = a.pick_id.getReferredObject()
a.takeoff_angle = hp.p_the_mc[_i, 0]
picks.append(p)
arrivals.append(a)
if only_fm_picks:
origin.arrivals = arrivals
event.picks = picks
# Use me double couple calculator and populate planes/axes etc
x = hp._best_quality_index
# Put all the mechanisms into the 'focal_mechanisms' list, mark "best" as preferred
for s in range(hp.nmult):
dc = DoubleCouple([hp.str_avg[s], hp.dip_avg[s], hp.rak_avg[s]])
ax = dc.axis
focal_mech = FocalMechanism()
focal_mech.creation_info = CreationInfo(creation_time=UTCDateTime(),
author=hp.author)
focal_mech.triggering_origin_id = origin.resource_id
focal_mech.resource_id = ResourceIdentifier(
'smi:hash/FocalMechanism/{0}/{1}'.format(hp.icusp, s + 1))
focal_mech.method_id = ResourceIdentifier('HASH')
focal_mech.nodal_planes = NodalPlanes()
focal_mech.nodal_planes.nodal_plane_1 = NodalPlane(*dc.plane1)
focal_mech.nodal_planes.nodal_plane_2 = NodalPlane(*dc.plane2)
focal_mech.principal_axes = PrincipalAxes()
focal_mech.principal_axes.t_axis = Axis(azimuth=ax['T']['azimuth'],
plunge=ax['T']['dip'])
focal_mech.principal_axes.p_axis = Axis(azimuth=ax['P']['azimuth'],
plunge=ax['P']['dip'])
focal_mech.station_polarity_count = n
focal_mech.azimuthal_gap = hp.magap
focal_mech.misfit = hp.mfrac[s]
focal_mech.station_distribution_ratio = hp.stdr[s]
focal_mech.comments.append(
Comment(
hp.qual[s],
resource_id=ResourceIdentifier(
focal_mech.resource_id.resource_id + '/comment/quality')))
#----------------------------------------
event.focal_mechanisms.append(focal_mech)
if s == x:
event.preferred_focal_mechanism_id = focal_mech.resource_id.resource_id
return event
def stalta_pick(stream,
stalen,
ltalen,
trig_on,
trig_off,
freqmin=False,
freqmax=False,
debug=0,
show=False):
"""
Basic sta/lta picker, suggest using alternative in obspy.
Simple sta-lta (short-term average/long-term average) picker, using \
obspy's stalta routine to generate the characteristic function.
Currently very basic quick wrapper, there are many other (better) options \
in obspy, found \
`here <http://docs.obspy.org/packages/autogen/obspy.signal.trigger.html>`_.
:type stream: obspy.Stream
:param stream: The stream to pick on, can be any number of channels.
:type stalen: float
:param stalen: Length of the short-term average window in seconds.
:type ltalen: float
:param ltalen: Length of the long-term average window in seconds.
:type trig_on: float
:param trig_on: sta/lta ratio to trigger a detection/pick
:type trig_off: float
:param trig_off: sta/lta ratio to turn the trigger off - no further picks\
will be made between exceeding trig_on until trig_off is reached.
:type freqmin: float
:param freqmin: Low-cut frequency in Hz for bandpass filter
:type freqmax: float
:param freqmax: High-cut frequency in Hz for bandpass filter
:type debug: int
:param debug: Debug output level from 0-5.
:type show: bool
:param show: Show picks on waveform.
:returns: obspy.core.event.Event
.. rubric:: Example
>>> from obspy import read
>>> from eqcorrscan.utils.picker import stalta_pick
>>> st = read()
>>> event = stalta_pick(st, stalen=0.2, ltalen=4, trig_on=10,
... trig_off=1, freqmin=3.0, freqmax=20.0)
>>> event.creation_info.author
'EQcorrscan'
"""
from obspy.signal.trigger import classic_sta_lta, trigger_onset
from obspy.signal.trigger import plot_trigger
from obspy import UTCDateTime
from obspy.core.event import Event, Pick, WaveformStreamID
from obspy.core.event import CreationInfo, Comment, Origin
import eqcorrscan.utils.plotting as plotting
event = Event()
event.origins.append(Origin())
event.creation_info = CreationInfo(author='EQcorrscan',
creation_time=UTCDateTime())
event.comments.append(Comment(text='stalta'))
picks = []
for tr in stream:
# We are going to assume, for now, that if the pick is made on the
# horizontal channel then it is an S, otherwise we will assume it is
# a P-phase: obviously a bad assumption...
if tr.stats.channel[-1] == 'Z':
phase = 'P'
else:
phase = 'S'
if freqmin and freqmax:
tr.detrend('simple')
tr.filter('bandpass',
freqmin=freqmin,
freqmax=freqmax,
corners=3,
zerophase=True)
df = tr.stats.sampling_rate
cft = classic_sta_lta(tr.data, int(stalen * df), int(ltalen * df))
if debug > 3:
plot_trigger(tr, cft, trig_on, trig_off)
triggers = trigger_onset(cft, trig_on, trig_off)
for trigger in triggers:
on = tr.stats.starttime + (trigger[0] / df)
# off = tr.stats.starttime + (trigger[1] / df)
wav_id = WaveformStreamID(station_code=tr.stats.station,
channel_code=tr.stats.channel,
network_code=tr.stats.network)
pick = Pick(waveform_id=wav_id, phase_hint=phase, time=on)
if debug > 2:
print('Pick made:')
print(pick)
picks.append(pick)
# QC picks
del pick
pick_stations = list(set([pick.waveform_id.station_code
for pick in picks]))
for pick_station in pick_stations:
station_picks = [
pick for pick in picks
if pick.waveform_id.station_code == pick_station
]
# If P-pick is after S-picks, remove it.
p_time = [
pick.time for pick in station_picks if pick.phase_hint == 'P'
]
s_time = [
pick.time for pick in station_picks if pick.phase_hint == 'S'
]
if p_time > s_time:
p_pick = [pick for pick in station_picks if pick.phase_hint == 'P']
for pick in p_pick:
print('P pick after S pick, removing P pick')
picks.remove(pick)
if show:
plotting.pretty_template_plot(stream,
picks=picks,
title='Autopicks',
size=(8, 9))
event.picks = picks
event.origins[0].time = min([pick.time for pick in event.picks]) - 1
event.origins[0].latitude = float('nan')
event.origins[0].longitude = float('nan')
# Set arbitrary origin time
return event
def plot_detection(grid,
receivers,
frames,
tmin_frames,
deltat_cf,
imax,
iframe,
xpeak,
ypeak,
zpeak,
tr_stackmax,
tpeaks,
apeaks,
detector_threshold,
wmin,
wmax,
pdata,
trs_raw,
fmin,
fmax,
idetection,
tpeaksearch,
movie=False,
save_filename=None,
show=True,
event=None):
from matplotlib import pyplot as plt
from matplotlib import cm
from matplotlib.animation import FuncAnimation
nsls = set(tr.nslc_id[:3] for tr in trs_raw)
receivers_on = [r for r in receivers if r.codes in nsls]
receivers_off = [r for r in receivers if r.codes not in nsls]
distances = grid.distances(receivers)
plot.mpl_init(fontsize=9)
fig = plt.figure(figsize=plot.mpl_papersize('a4', 'landscape'))
axes = plt.subplot2grid((2, 3), (0, 2), aspect=1.0)
plot.mpl_labelspace(axes)
axes2 = plt.subplot2grid((2, 3), (1, 2))
plot.mpl_labelspace(axes2)
axes3 = plt.subplot2grid((2, 3), (0, 1), rowspan=2)
axes4 = plt.subplot2grid((2, 3), (0, 0), rowspan=2)
if grid.distance_max() > km:
dist_units = km
axes.set_xlabel('Easting [km]')
axes.set_ylabel('Northing [km]')
axes4.set_ylabel('Distance [km]')
else:
dist_units = 1.0
axes.set_xlabel('Easting [m]')
axes.set_ylabel('Northing [m]')
axes4.set_ylabel('Distance [m]')
axes.locator_params(nbins=6, tight=True)
axes2.set_xlabel('Time [s]')
axes2.set_ylabel('Detector level')
axes3.set_xlabel('Time [s]')
for el in axes3.get_yticklabels():
el.set_visible(False)
axes4.set_xlabel('Time [s]')
tpeak_current = tmin_frames + deltat_cf * iframe
t0 = tpeak_current
tduration = 2.0 * tpeaksearch
axes2.axvspan(tr_stackmax.tmin - t0,
wmin - t0,
color=plot.mpl_color('aluminium2'))
axes2.axvspan(wmax - t0,
tr_stackmax.tmax - t0,
color=plot.mpl_color('aluminium2'))
axes2.axvspan(tpeak_current - 0.5 * tduration - t0,
tpeak_current + 0.5 * tduration - t0,
color=plot.mpl_color('scarletred2'),
alpha=0.3,
lw=0.)
axes2.set_xlim(tr_stackmax.tmin - t0, tr_stackmax.tmax - t0)
axes2.axhline(detector_threshold,
color=plot.mpl_color('aluminium6'),
lw=2.)
t = tr_stackmax.get_xdata()
amp = tr_stackmax.get_ydata()
axes2.plot(t - t0, amp, color=plot.mpl_color('scarletred2'), lw=1.)
for tpeak, apeak in zip(tpeaks, apeaks):
axes2.plot(tpeak - t0, apeak, '*', ms=20., mfc='white', mec='black')
station_index = dict((rec.codes, i) for (i, rec) in enumerate(receivers))
dists_all = []
amps = []
shifts = []
pdata2 = []
for trs, shift_table, shifter in pdata:
trs = [tr.copy() for tr in trs]
dists = []
for tr in trs:
istation = station_index[tr.nslc_id[:3]]
shift = shift_table[imax, istation]
tr2 = tr.chop(tpeak_current - 0.5 * tduration + shift,
tpeak_current + 0.5 * tduration + shift,
inplace=False)
dists.append(distances[imax, istation])
amp = tr2.get_ydata() * shifter.weight
amps.append(num.max(num.abs(amp)))
shifts.append(shift)
pdata2.append((trs, dists, shift_table, shifter))
dists_all.extend(dists)
dist_min = min(dists_all)
dist_max = max(dists_all)
shift_min = min(shifts)
shift_max = max(shifts)
amp_max = max(amps)
scalefactor = (dist_max - dist_min) / len(trs) * 0.5
axes3.set_xlim(-0.5 * tduration + shift_min, 0.5 * tduration + shift_max)
axes3.set_ylim((dist_min - scalefactor) / dist_units,
(dist_max + scalefactor) / dist_units)
axes4.set_xlim(-0.5 * tduration + shift_min, 0.5 * tduration + shift_max)
axes4.set_ylim((dist_min - scalefactor) / dist_units,
(dist_max + scalefactor) / dist_units)
axes3.axvline(0., color=plot.mpl_color('aluminium3'), lw=2.)
nsl_have = set()
phase_markers = []
picks = []
for ishifter, (trs, dists, shift_table, shifter) in enumerate(pdata2):
color = plot.mpl_graph_color(ishifter)
for tr, dist in zip(trs, dists):
tmint = tr.tmin
tr = tr.chop(tpeak_current - 0.5 * tduration + shift_min,
tpeak_current + 0.5 * tduration + shift_max,
inplace=False)
nsl = tr.nslc_id[:3]
istation = station_index[nsl]
shift = shift_table[imax, istation]
phase_markers.append(
PhaseMarker([(nsl[0], nsl[1], "", nsl[2])],
tmin=tmint + shift,
tmax=tmint + shift,
phasename=shifter.name,
event_time=t0,
event_hash=idetection))
p = Pick(time=UTCDateTime(tmint + shift),
waveform_id=WaveformStreamID(network_code=nsl[0],
station_code=nsl[1]),
phase_hint=shifter.name,
method_id="lassie")
picks.append(p)
axes3.plot(shift,
dist / dist_units,
'|',
mew=2,
mec=color,
ms=10,
zorder=2)
t = tr.get_xdata()
amp = tr.get_ydata() * shifter.weight
amp /= amp_max
axes3.plot(
t - t0,
(dist + scalefactor * amp + ishifter * scalefactor * 0.1) /
dist_units,
color=color,
zorder=1)
if nsl not in nsl_have:
axes3.annotate('.'.join(nsl),
xy=(t[0] - t0, dist / dist_units),
xytext=(10., 0.),
textcoords='offset points',
verticalalignment='top')
nsl_have.add(nsl)
for tr in trs_raw:
istation = station_index[tr.nslc_id[:3]]
dist = distances[imax, istation]
shift = shift_table[imax, istation]
tr = tr.copy()
tr.highpass(4, fmin, demean=True)
tr.lowpass(4, fmax, demean=False)
tr.chop(tpeak_current - 0.5 * tduration + shift_min,
tpeak_current + 0.5 * tduration + shift_max)
t = tr.get_xdata()
amp = tr.get_ydata().astype(num.float)
amp = amp / num.max(num.abs(amp))
axes4.plot(t - t0, (dist + scalefactor * amp) / dist_units,
color='black',
alpha=0.5,
zorder=1)
axes4.plot(shift,
dist / dist_units,
'|',
mew=2,
mec=color,
ms=10,
zorder=2)
PhaseMarker.save_markers(phase_markers,
"%s.pym" % (save_filename[:-4]),
fdigits=3)
event_obspy = Event()
origin = Origin(time=UTCDateTime(t0),
longitude=event.lon,
latitude=event.lat,
method="lassie")
event_obspy.origins.append(origin)
event_obspy.picks = picks
cat = Catalog()
cat.append(event_obspy)
cat.write(save_filename[:-4] + ".qml", format="QUAKEML")
nframes = frames.shape[1]
iframe_min = max(0, int(round(iframe - 0.5 * tduration / deltat_cf)))
iframe_max = min(nframes - 1,
int(round(iframe + 0.5 * tduration / deltat_cf)))
amax = frames[imax, iframe]
axes.set_xlim(grid.ymin / dist_units, grid.ymax / dist_units)
axes.set_ylim(grid.xmin / dist_units, grid.xmax / dist_units)
cmap = cm.YlOrBr
system = ('ne', grid.lat, grid.lon)
static_artists = []
static_artists.extend(
plot_receivers(axes,
receivers_on,
system=system,
units=dist_units,
style=dict(mfc='black', ms=5.0)))
static_artists.extend(
plot_receivers(axes,
receivers_off,
system=system,
units=dist_units,
style=dict(mfc='none', ms=5.0)))
static_artists.extend(
axes.plot(ypeak / dist_units,
xpeak / dist_units,
'*',
ms=20.,
mec='black',
mfc='white'))
static_artists.append(
fig.suptitle('%06i - %s' % (idetection, util.time_to_str(t0))))
frame_artists = []
progress_artists = []
def update(iframe):
if iframe is not None:
frame = frames[:, iframe]
if not progress_artists:
progress_artists[:] = [
axes2.axvline(tmin_frames - t0 + deltat_cf * iframe,
color=plot.mpl_color('scarletred3'),
alpha=0.5,
lw=2.)
]
else:
progress_artists[0].set_xdata(tmin_frames - t0 +
deltat_cf * iframe)
else:
frame = num.max(frames[:, iframe_min:iframe_max + 1], axis=1)
frame_artists[:] = grid.plot(axes,
frame,
amin=0.0,
amax=amax,
cmap=cmap,
system=system,
artists=frame_artists,
units=dist_units,
shading='gouraud')
return frame_artists + progress_artists + static_artists
if movie:
ani = FuncAnimation(
fig,
update,
frames=list(range(iframe_min, iframe_max + 1))[::10] + [None],
interval=20.,
repeat=False,
blit=True)
else:
ani = None
update(None)
if save_filename:
fig.savefig(save_filename)
if show:
plt.show()
else:
plt.close()
del ani
def outputOBSPY(hp, event=None, only_fm_picks=False):
"""
Make an Event which includes the current focal mechanism information from HASH
Use the 'only_fm_picks' flag to only include the picks HASH used for the FocalMechanism.
This flag will replace the 'picks' and 'arrivals' lists of existing events with new ones.
Inputs
-------
hp : hashpy.HashPype instance
event : obspy.core.event.Event
only_fm_picks : bool of whether to overwrite the picks/arrivals lists
Returns
-------
obspy.core.event.Event
Event will be new if no event was input, FocalMech added to existing event
"""
# Returns new (or updates existing) Event with HASH solution
n = hp.npol
if event is None:
event = Event(focal_mechanisms=[], picks=[], origins=[])
origin = Origin(arrivals=[])
origin.time = UTCDateTime(hp.tstamp)
origin.latitude = hp.qlat
origin.longitude = hp.qlon
origin.depth = hp.qdep
origin.creation_info = CreationInfo(version=hp.icusp)
origin.resource_id = ResourceIdentifier('smi:hash/Origin/{0}'.format(hp.icusp))
for _i in range(n):
p = Pick()
p.creation_info = CreationInfo(version=hp.arid[_i])
p.resource_id = ResourceIdentifier('smi:hash/Pick/{0}'.format(p.creation_info.version))
p.waveform_id = WaveformStreamID(network_code=hp.snet[_i], station_code=hp.sname[_i], channel_code=hp.scomp[_i])
if hp.p_pol[_i] > 0:
p.polarity = 'positive'
else:
p.polarity = 'negative'
a = Arrival()
a.creation_info = CreationInfo(version=hp.arid[_i])
a.resource_id = ResourceIdentifier('smi:hash/Arrival/{0}'.format(p.creation_info.version))
a.azimuth = hp.p_azi_mc[_i,0]
a.takeoff_angle = 180. - hp.p_the_mc[_i,0]
a.pick_id = p.resource_id
origin.arrivals.append(a)
event.picks.append(p)
event.origins.append(origin)
event.preferred_origin_id = str(origin.resource_id)
else: # just update the changes
origin = event.preferred_origin()
picks = []
arrivals = []
for _i in range(n):
ind = hp.p_index[_i]
a = origin.arrivals[ind]
p = a.pick_id.getReferredObject()
a.takeoff_angle = hp.p_the_mc[_i,0]
picks.append(p)
arrivals.append(a)
if only_fm_picks:
origin.arrivals = arrivals
event.picks = picks
# Use me double couple calculator and populate planes/axes etc
x = hp._best_quality_index
# Put all the mechanisms into the 'focal_mechanisms' list, mark "best" as preferred
for s in range(hp.nmult):
dc = DoubleCouple([hp.str_avg[s], hp.dip_avg[s], hp.rak_avg[s]])
ax = dc.axis
focal_mech = FocalMechanism()
focal_mech.creation_info = CreationInfo(creation_time=UTCDateTime(), author=hp.author)
focal_mech.triggering_origin_id = origin.resource_id
focal_mech.resource_id = ResourceIdentifier('smi:hash/FocalMechanism/{0}/{1}'.format(hp.icusp, s+1))
focal_mech.method_id = ResourceIdentifier('HASH')
focal_mech.nodal_planes = NodalPlanes()
focal_mech.nodal_planes.nodal_plane_1 = NodalPlane(*dc.plane1)
focal_mech.nodal_planes.nodal_plane_2 = NodalPlane(*dc.plane2)
focal_mech.principal_axes = PrincipalAxes()
focal_mech.principal_axes.t_axis = Axis(azimuth=ax['T']['azimuth'], plunge=ax['T']['dip'])
focal_mech.principal_axes.p_axis = Axis(azimuth=ax['P']['azimuth'], plunge=ax['P']['dip'])
focal_mech.station_polarity_count = n
focal_mech.azimuthal_gap = hp.magap
focal_mech.misfit = hp.mfrac[s]
focal_mech.station_distribution_ratio = hp.stdr[s]
focal_mech.comments.append(
Comment(hp.qual[s], resource_id=ResourceIdentifier(str(focal_mech.resource_id) + '/comment/quality'))
)
#----------------------------------------
event.focal_mechanisms.append(focal_mech)
if s == x:
event.preferred_focal_mechanism_id = str(focal_mech.resource_id)
return event
def stalta_pick(stream, stalen, ltalen, trig_on, trig_off, freqmin=False,
freqmax=False, debug=0, show=False):
"""
Basic sta/lta picker, suggest using alternative in obspy.
Simple sta-lta (short-term average/long-term average) picker, using \
obspy's stalta routine to generate the characteristic function.
Currently very basic quick wrapper, there are many other (better) options \
in obspy, found \
`here <http://docs.obspy.org/packages/autogen/obspy.signal.trigger.html>`_.
:type stream: obspy.Stream
:param stream: The stream to pick on, can be any number of channels.
:type stalen: float
:param stalen: Length of the short-term average window in seconds.
:type ltalen: float
:param ltalen: Length of the long-term average window in seconds.
:type trig_on: float
:param trig_on: sta/lta ratio to trigger a detection/pick
:type trig_off: float
:param trig_off: sta/lta ratio to turn the trigger off - no further picks\
will be made between exceeding trig_on until trig_off is reached.
:type freqmin: float
:param freqmin: Low-cut frequency in Hz for bandpass filter
:type freqmax: float
:param freqmax: High-cut frequency in Hz for bandpass filter
:type debug: int
:param debug: Debug output level from 0-5.
:type show: bool
:param show: Show picks on waveform.
:returns: obspy.core.event.Event
.. rubric:: Example
>>> from obspy import read
>>> from eqcorrscan.utils.picker import stalta_pick
>>> st = read()
>>> event = stalta_pick(st, stalen=0.2, ltalen=4, trig_on=10,
... trig_off=1, freqmin=3.0, freqmax=20.0)
>>> event.creation_info.author
'EQcorrscan'
"""
from obspy.signal.trigger import classic_sta_lta, trigger_onset
from obspy.signal.trigger import plot_trigger
from obspy import UTCDateTime
from obspy.core.event import Event, Pick, WaveformStreamID
from obspy.core.event import CreationInfo, Comment, Origin
import eqcorrscan.utils.plotting as plotting
event = Event()
event.origins.append(Origin())
event.creation_info = CreationInfo(author='EQcorrscan',
creation_time=UTCDateTime())
event.comments.append(Comment(text='stalta'))
picks = []
for tr in stream:
# We are going to assume, for now, that if the pick is made on the
# horizontal channel then it is an S, otherwise we will assume it is
# a P-phase: obviously a bad assumption...
if tr.stats.channel[-1] == 'Z':
phase = 'P'
else:
phase = 'S'
if freqmin and freqmax:
tr.detrend('simple')
tr.filter('bandpass', freqmin=freqmin, freqmax=freqmax,
corners=3, zerophase=True)
df = tr.stats.sampling_rate
cft = classic_sta_lta(tr.data, int(stalen * df), int(ltalen * df))
if debug > 3:
plot_trigger(tr, cft, trig_on, trig_off)
triggers = trigger_onset(cft, trig_on, trig_off)
for trigger in triggers:
on = tr.stats.starttime + (trigger[0] / df)
# off = tr.stats.starttime + (trigger[1] / df)
wav_id = WaveformStreamID(station_code=tr.stats.station,
channel_code=tr.stats.channel,
network_code=tr.stats.network)
pick = Pick(waveform_id=wav_id, phase_hint=phase, time=on)
if debug > 2:
print('Pick made:')
print(pick)
picks.append(pick)
# QC picks
del pick
pick_stations = list(set([pick.waveform_id.station_code for pick in picks]))
for pick_station in pick_stations:
station_picks = [pick for pick in picks if
pick.waveform_id.station_code == pick_station]
# If P-pick is after S-picks, remove it.
p_time = [pick.time for pick in station_picks if pick.phase_hint == 'P']
s_time = [pick.time for pick in station_picks if pick.phase_hint == 'S']
if p_time > s_time:
p_pick = [pick for pick in station_picks if pick.phase_hint == 'P']
for pick in p_pick:
print('P pick after S pick, removing P pick')
picks.remove(pick)
if show:
plotting.pretty_template_plot(stream, picks=picks, title='Autopicks',
size=(8, 9))
event.picks = picks
event.origins[0].time = min([pick.time for pick in event.picks]) - 1
event.origins[0].latitude = float('nan')
event.origins[0].longitude = float('nan')
# Set arbitrary origin time
return event
def full_test_event():
"""
Function to generate a basic, full test event
"""
test_event = Event()
test_event.origins.append(
Origin(time=UTCDateTime("2012-03-26") + 1.2,
latitude=45.0,
longitude=25.0,
depth=15000))
test_event.event_descriptions.append(EventDescription())
test_event.event_descriptions[0].text = 'LE'
test_event.creation_info = CreationInfo(agency_id='TES')
test_event.magnitudes.append(
Magnitude(mag=0.1,
magnitude_type='ML',
creation_info=CreationInfo('TES'),
origin_id=test_event.origins[0].resource_id))
test_event.magnitudes.append(
Magnitude(mag=0.5,
magnitude_type='Mc',
creation_info=CreationInfo('TES'),
origin_id=test_event.origins[0].resource_id))
test_event.magnitudes.append(
Magnitude(mag=1.3,
magnitude_type='Ms',
creation_info=CreationInfo('TES'),
origin_id=test_event.origins[0].resource_id))
# Define the test pick
_waveform_id_1 = WaveformStreamID(station_code='FOZ',
channel_code='SHZ',
network_code='NZ')
_waveform_id_2 = WaveformStreamID(station_code='WTSZ',
channel_code='BH1',
network_code=' ')
# Pick to associate with amplitude - 0
test_event.picks = [
Pick(waveform_id=_waveform_id_1,
phase_hint='IAML',
polarity='undecidable',
time=UTCDateTime("2012-03-26") + 1.68,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_1,
onset='impulsive',
phase_hint='PN',
polarity='positive',
time=UTCDateTime("2012-03-26") + 1.68,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_1,
phase_hint='IAML',
polarity='undecidable',
time=UTCDateTime("2012-03-26") + 1.68,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_2,
onset='impulsive',
phase_hint='SG',
polarity='undecidable',
time=UTCDateTime("2012-03-26") + 1.72,
evaluation_mode="manual"),
Pick(waveform_id=_waveform_id_2,
onset='impulsive',
phase_hint='PN',
polarity='undecidable',
time=UTCDateTime("2012-03-26") + 1.62,
evaluation_mode="automatic")
]
# Test a generic local magnitude amplitude pick
test_event.amplitudes = [
Amplitude(generic_amplitude=2.0,
period=0.4,
pick_id=test_event.picks[0].resource_id,
waveform_id=test_event.picks[0].waveform_id,
unit='m',
magnitude_hint='ML',
category='point',
type='AML'),
Amplitude(generic_amplitude=10,
pick_id=test_event.picks[1].resource_id,
waveform_id=test_event.picks[1].waveform_id,
type='END',
category='duration',
unit='s',
magnitude_hint='Mc',
snr=2.3),
Amplitude(generic_amplitude=5.0,
period=0.6,
pick_id=test_event.picks[2].resource_id,
waveform_id=test_event.picks[0].waveform_id,
unit='m',
category='point',
type='AML')
]
test_event.origins[0].arrivals = [
Arrival(time_weight=0,
phase=test_event.picks[1].phase_hint,
pick_id=test_event.picks[1].resource_id),
Arrival(time_weight=2,
phase=test_event.picks[3].phase_hint,
pick_id=test_event.picks[3].resource_id,
backazimuth_residual=5,
time_residual=0.2,
distance=15,
azimuth=25),
Arrival(time_weight=2,
phase=test_event.picks[4].phase_hint,
pick_id=test_event.picks[4].resource_id,
backazimuth_residual=5,
time_residual=0.2,
distance=15,
azimuth=25)
]
# Add in error info (line E)
test_event.origins[0].quality = OriginQuality(standard_error=0.01,
azimuthal_gap=36)
# Origin uncertainty in Seisan is output as long-lat-depth, quakeML has
# semi-major and semi-minor
test_event.origins[0].origin_uncertainty = OriginUncertainty(
confidence_ellipsoid=ConfidenceEllipsoid(
semi_major_axis_length=3000,
semi_minor_axis_length=1000,
semi_intermediate_axis_length=2000,
major_axis_plunge=20,
major_axis_azimuth=100,
major_axis_rotation=4))
test_event.origins[0].time_errors = QuantityError(uncertainty=0.5)
# Add in fault-plane solution info (line F) - Note have to check program
# used to determine which fields are filled....
test_event.focal_mechanisms.append(
FocalMechanism(nodal_planes=NodalPlanes(
nodal_plane_1=NodalPlane(strike=180,
dip=20,
rake=30,
strike_errors=QuantityError(10),
dip_errors=QuantityError(10),
rake_errors=QuantityError(20))),
method_id=ResourceIdentifier(
"smi:nc.anss.org/focalMechanism/FPFIT"),
creation_info=CreationInfo(agency_id="NC"),
misfit=0.5,
station_distribution_ratio=0.8))
# Need to test high-precision origin and that it is preferred origin.
# Moment tensor includes another origin
test_event.origins.append(
Origin(time=UTCDateTime("2012-03-26") + 1.2,
latitude=45.1,
longitude=25.2,
depth=14500))
test_event.magnitudes.append(
Magnitude(mag=0.1,
magnitude_type='MW',
creation_info=CreationInfo('TES'),
origin_id=test_event.origins[-1].resource_id))
# Moment tensors go with focal-mechanisms
test_event.focal_mechanisms.append(
FocalMechanism(moment_tensor=MomentTensor(
derived_origin_id=test_event.origins[-1].resource_id,
moment_magnitude_id=test_event.magnitudes[-1].resource_id,
scalar_moment=100,
tensor=Tensor(
m_rr=100, m_tt=100, m_pp=10, m_rt=1, m_rp=20, m_tp=15),
method_id=ResourceIdentifier(
'smi:nc.anss.org/momentTensor/BLAH'))))
return test_event
def setEventData(eventParser, arrivals, count):
global originCount
global eventCount
global pickCount
creation_info = CreationInfo(
author='niket_engdahl_parser',
creation_time=UTCDateTime(),
agency_uri=ResourceIdentifier(id='smi:engdahl.ga.gov.au/ga-engdahl'),
agency_id='ga-engdahl')
# magnitudeSurface = Magnitude(resource_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/'+str(originCount)+'#netMag.Ms'),
# mag=eventParser.ms,
# magnitude_type='Ms',
# origin_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/'+str(originCount)),
# azimuthal_gap=eventParser.openaz2,
# creation_info=creation_info)
origin = Origin(
resource_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/' +
str(originCount)),
time=UTCDateTime(int(str(2000 + int(eventParser.iyr))),
int(eventParser.mon), int(eventParser.iday),
int(eventParser.ihr), int(eventParser.min),
int(eventParser.sec.split('.')[0]),
int(eventParser.sec.split('.')[1] + '0')),
longitude=eventParser.glon,
latitude=eventParser.glat,
depth=float(eventParser.depth) *
1000, # engdahl files report kms, obspy expects m
depth_errors=eventParser.sedep,
method_id=ResourceIdentifier(id='EHB'),
earth_model_id=ResourceIdentifier(id='ak135'),
quality=OriginQuality(associated_phase_count=len(arrivals),
used_phase_count=len(arrivals),
standard_error=eventParser.se,
azimuthal_gap=eventParser.openaz2),
evaluation_mode='automatic',
creation_info=creation_info)
magnitude = Magnitude(
resource_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/' +
str(originCount) + '#netMag.Mb'),
mag=eventParser.mb,
magnitude_type='Mb',
origin_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/' +
str(originCount)),
azimuthal_gap=eventParser.openaz1,
creation_info=creation_info)
originCount += 1
pickList = []
arrivalList = []
pPhaseArrival = None
for arrParser in arrivals:
pickOnset = None
pol = None
if arrParser.year and arrParser.month and arrParser.day and arrParser.station:
pPhaseArrival = arrParser
else:
arrParser.year = pPhaseArrival.year
arrParser.day = pPhaseArrival.day
arrParser.month = pPhaseArrival.month
arrParser.station = pPhaseArrival.station
arrParser.delta = pPhaseArrival.delta
arrParser.dtdd = pPhaseArrival.dtdd
arrParser.backaz = pPhaseArrival.backaz
arrParser.focalDip = pPhaseArrival.focalDip
arrParser.angleAzimuth = pPhaseArrival.angleAzimuth
if arrParser.phase1 == 'LR' or arrParser.phase2 == 'LR' or arrParser.hour == '24':
continue
if arrParser.phase1.startswith('i'):
pickOnset = PickOnset.impulsive
if arrParser.fm == '+':
pol = PickPolarity.positive
elif arrParser.fm == '-':
pol = PickPolarity.negative
elif arrParser.phase1.startswith('e'):
pickOnset = PickOnset.emergent
pick = Pick(
resource_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/pick/' +
str(pickCount)),
time=UTCDateTime(int(str(2000 + int(arrParser.year))),
int(arrParser.month), int(arrParser.day),
int(arrParser.hour), int(arrParser.minute),
int(arrParser.second.split('.')[0]),
int(arrParser.second.split('.')[1] + '0')),
waveform_id=WaveformStreamID(network_code='',
station_code=arrParser.station,
channel_code='BHZ'),
methodID=ResourceIdentifier('STA/LTA'),
backazimuth=arrParser.backaz if arrParser.backaz else None,
onset=pickOnset,
phase_hint=arrParser.phase,
polarity=pol,
evaluation_mode='automatic',
# TO-DO
comment='populate all the remaining fields here as key value',
creation_info=creation_info)
if not arrParser.backaz:
print "arrParser.backaz is empty. printing the arrParser for debugging"
pickCount += 1
pickList.append(pick)
arrival = Arrival(
pick_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/pick/' +
str(pickCount - 1)),
phase=arrParser.phase if arrParser.phase else None,
azimuth=arrParser.backaz if arrParser.backaz else None,
distance=arrParser.delta if arrParser.delta else None,
# if the * has some significance, it should be accounted for. ignoring for now.
time_residual=arrParser.residual.rstrip('*'),
time_weight=arrParser.wgt if arrParser.wgt else None,
backazimuth_weight=arrParser.wgt if arrParser.wgt else None)
arrivalList.append(arrival)
if not arrParser.wgt:
print "arrParser.wgt is empty. printing the arrParser for debugging"
# pprint.pprint(arrParser)
origin.arrivals = arrivalList
event = Event(resource_id=ResourceIdentifier(
id='smi:engdahl.ga.gov.au/event/' + str(eventCount)),
creation_info=creation_info,
event_type='earthquake')
eventCount += 1
event.picks = pickList
event.origins = [
origin,
]
event.magnitudes = [
magnitude,
]
event.preferred_origin_id = origin.resource_id
event.preferred_magnitude_id = magnitude.resource_id
return event
