def semblancestalta(sembmaxvaluevector, sembmaxlatvector, sembmaxlonvector):
data = np.array(sembmaxvaluevector, dtype=np.float64)
tr = Trace(data, header=None)
sta = 0.5
lta = 4
cft = recursive_sta_lta(tr, int(sta * tr.stats.sampling_rate),
int(lta * tr.stats.sampling_rate))
thrOn = 0.5
thrOff = 1.5
plotTrigger(tr, cft, thrOn, thrOff)
def semblancestalta(sembmaxvaluevector, sembmaxlatvector, sembmaxlonvector):
data = np.array(sembmaxvaluevector, dtype=np.float64)
#stats = Stats() #hs
#stats.network = 'BW' #hs
#stats['station'] = 'MANZ' #hs
tr = Trace(data, header=None)
sta = 0.5
lta = 4
cft = recSTALTA(tr, int(sta * tr.stats.sampling_rate),
int(lta * tr.stats.sampling_rate))
#print cft
thrOn = 0.5
thrOff = 1.5
plotTrigger(tr, cft, thrOn, thrOff)
def LTASTAtr(tr,thres1, thres2,STA, LTA,plotSTA):
""" return the cut on and off of the LTA/STA list [[cuton, cutoff], [cuton, cutoff]]
* input :
- tr : type : trace , stream to filnd STA, LTA
- thres1 : type; float : cut on limit of STA/LTA values : after tjis value the cut on is defined
- thres2 : type, float : cut off limit of STA/LTA values : after this value the cut off is defined
- STA : type int : size of the LTA windows in second : STA = the trace average on this time windows
- LTA : type int : size of the LTA windows in second : LTA = the trace average on this time windows
- plotSTA: type, bool; it true, the trace and it's characteristic function are plotted
RQ: AFTER TESTING IT'S SEEEMS GOOD TO HAVE A RATIO WSTA/WLTA > 1/4 AND A CUT OFF HIGHER THAN CUT ON
* outputs
- L_onoff: type np, array : 2D array of cut on and cut_off time in number of sample ie time* df where df is the sampling rate [[cuton,cutoff], [cuton1, cutoff1]]
exemple:
st = Read_event('15','206','15','1', '1', True)
stcorrec = Stream_Correction(st, '1', False)
stfiltered= Stream_PBfilter(stcorrec,0.5, 20,False)
LTASTA(stfiltered,2, 2.5,300,1400,True)
"""
#0. sampling rate ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
df = tr.stats.sampling_rate
#1. characteristic function of the trace following classical LTA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#cft = classicSTALTA(tr.data, int(STA * df), int(LTA* df))
#2. characteristic function of the trace following recursive LTA
cft2 =recursive_sta_lta(tr.data, int(STA * df), int(LTA* df))
#3. list of [cuton, cutoff] time in number of samples~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#max_len = maximum lenght of the triggered event in sample,
#max_len_delete = Do not write events longer than max_len into report file.
L_onoff = trigger_onset(cft2, thres1, thres2, max_len=9e+99, max_len_delete=False)
#4. plot~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if plotSTA==True :
##plotTrigger(tr[0], cft, thres1,thres2)
plotTrigger(tr[0], cft2, thres1,thres2)
plt.title('recursive')
return np.array(L_onoff)
def refTrigger(self, RefWaveform, phase, cfg_yaml):
Config = self.Config
cfg = ConfigObj(dict=Config)
name = ('%s.%s.%s.%s') % (RefWaveform[0].stats.network,
RefWaveform[0].stats.station,
RefWaveform[0].stats.location,
RefWaveform[0].stats.channel)
i = self.searchMeta(name, self.StationMeta)
de = loc2degrees(self.Origin, i)
ptime = 0
Phase = cake.PhaseDef(phase)
model = cake.load_model()
if cfg_yaml.config_data.colesseo_input is True:
arrivals = model.arrivals([de, de], phases=Phase,
zstart=self.Origin.depth, zstop=0.)
else:
arrivals = model.arrivals([de, de], phases=Phase,
zstart=self.Origin.depth*km, zstop=0.)
try:
ptime = arrivals[0].t
except Exception:
arrivals = model.arrivals([de, de], phases=Phase,
zstart=self.Origin.depth*km-0.1)
ptime = arrivals[0].t
if ptime == 0:
raise Exception("\033[31mILLEGAL: phase definition\033[0m")
tw = self.calculateTimeWindows(ptime)
if cfg_yaml.config_data.pyrocko_download is True:
stP = self.readWaveformsPicker_pyrocko(i, tw, self.Origin, ptime,
cfg_yaml)
elif cfg_yaml.config_data.colesseo_input is True:
stP = self.readWaveformsPicker_colos(i, tw, self.Origin, ptime,
cfg_yaml)
else:
stP = self.readWaveformsPicker(i, tw, self.Origin, ptime, cfg_yaml)
refuntouchname = os.path.basename(self.AF)+'-refstation-raw.mseed'
stP.write(os.path.join(self.EventPath, refuntouchname), format='MSEED',
byteorder='>')
stP.filter("bandpass",
freqmin=float(cfg_yaml.config_xcorr.refstationfreqmin),
freqmax=float(cfg_yaml.config_xcorr.refstationfreqmax))
stP.trim(tw['xcorrstart'], tw['xcorrend'])
trP = stP[0]
trP.stats.starttime = UTCDateTime(3600)
refname = os.path.basename(self.AF)+'-refstation-filtered.mseed'
trP.write(os.path.join(self.EventPath, refname), format='MSEED',
byteorder='>')
sta = float(cfg_yaml.config_xcorr.refsta)
lta = float(cfg_yaml.config_xcorr.reflta)
cft = recSTALTA(trP.data, int(sta * trP.stats.sampling_rate),
int(lta * trP.stats.sampling_rate))
t = triggerOnset(cft, lta, sta)
try:
onset = t[0][0] / trP.stats.sampling_rate
except Exception:
onset = self.mintforerun
trigger = trP.stats.starttime+onset
tdiff = (trP.stats.starttime + onset)-(UTCDateTime(3600)
+ self.mintforerun)
refp = UTCDateTime(self.Origin.time)+ptime
reftriggeronset = refp+onset-self.mintforerun
if cfg_yaml.config_xcorr.autoxcorrcorrectur is True:
refmarkername = os.path.join(self.EventPath,
('%s-marker') % (os.path.basename(
self.AF)))
fobjrefmarkername = open(refmarkername, 'w')
fobjrefmarkername.write('# Snuffler Markers File Version\
0.2\n')
fobjrefmarkername.write(('phase: %s 0 %s None None None XWStart None False\n') % (tw['xcorrstart'].strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write(('phase: %s 0 %s None None None XWEnd None False\n') % (tw['xcorrend'].strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write(('phase: %s 1 %s None None None TheoP None False\n') % (refp.strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write(('phase: %s 3 %s None None None XTrig None False') % (reftriggeronset.strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.close()
cmd = 'snuffler %s --markers=%s&' % (os.path.join(
self.EventPath,
refuntouchname),
refmarkername)
os.system(cmd)
thrOn = float(self.Config['reflta'])
thrOff = float(self.Config['refsta'])
plotTrigger(trP, cft, thrOn, thrOff)
selection = float(input('Enter self picked phase in seconds: '))
tdiff = selection-self.mintforerun
refname = os.path.basename(self.AF)+'-shift.mseed'
trP.stats.starttime = trP.stats.starttime - selection
trP.write(os.path.join(self.EventPath, refname),
format='MSEED')
'''
tdiff = 0
trigger = trP.stats.starttime
'''
To = Trigger(name, trigger, os.path.basename(self.AF), tdiff)
return tdiff, To
def stalta_pick(stream,
stalen,
ltalen,
trig_on,
trig_off,
freqmin=False,
freqmax=False,
debug=0,
show=False):
r"""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: list of pick class.
"""
from obspy.signal.trigger import classicSTALTA, triggerOnset, plotTrigger
from sfile_util import PICK
import EQcorrscan_plotting as plotting
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 = classicSTALTA(tr.data, int(stalen * df), int(ltalen * df))
if debug > 3:
plotTrigger(tr, cft, trig_on, trig_off)
triggers = triggerOnset(cft, trig_on, trig_off)
for trigger in triggers:
on = tr.stats.starttime + (trigger[0] / df)
# off = tr.stats.starttime + (trigger[1] / df)
pick = PICK(station=tr.stats.station,
channel=tr.stats.channel,
time=on,
phase=phase)
if debug > 2:
print('Pick made:')
print(pick)
picks.append(pick)
# QC picks
del pick
pick_stations = list(set([pick.station for pick in picks]))
for pick_station in pick_stations:
station_picks = [
pick for pick in picks if pick.station == pick_station
]
# If P-pick is after S-picks, remove it.
p_time = [pick.time for pick in station_picks if pick.phase == 'P']
s_time = [pick.time for pick in station_picks if pick.phase == 'S']
if p_time > s_time:
p_pick = [pick for pick in station_picks if pick.phase == '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))
return picks
def stalta_pick(stream, stalen, ltalen, trig_on, trig_off, freqmin=False,
freqmax=False, debug=0, show=False):
r"""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: list of pick class.
"""
from obspy.signal.trigger import classicSTALTA, triggerOnset, plotTrigger
from Sfile_util import PICK
import EQcorrscan_plotting as plotting
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 = classicSTALTA(tr.data, int(stalen * df), int(ltalen * df))
if debug > 3:
plotTrigger(tr, cft, trig_on, trig_off)
triggers = triggerOnset(cft, trig_on, trig_off)
for trigger in triggers:
on = tr.stats.starttime + (trigger[0] / df)
# off = tr.stats.starttime + (trigger[1] / df)
pick = PICK(station=tr.stats.station, channel=tr.stats.channel,
time=on, phase=phase)
if debug > 2:
print('Pick made:')
print(pick)
picks.append(pick)
# QC picks
del pick
pick_stations = list(set([pick.station for pick in picks]))
for pick_station in pick_stations:
station_picks = [pick for pick in picks if
pick.station == pick_station]
# If P-pick is after S-picks, remove it.
p_time = [pick.time for pick in station_picks if pick.phase == 'P']
s_time = [pick.time for pick in station_picks if pick.phase == 'S']
if p_time > s_time:
p_pick = [pick for pick in station_picks if pick.phase == '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))
return picks
tmp.stats.network = tr.stats.network
tmp.stats.station = tr.stats.station
tmp.stats.channel = 'Z'
tmp.stats.update(adict={'sac':{'evla':tr.stats.sac.evla,
'evlo':tr.stats.sac.evlo,
'evdp':tr.stats.sac.evdp,
'stla':tr.stats.sac.stla,
'stlo':tr.stats.sac.stlo,
'b':ctime[0],
'gcarc':tr.stats.sac.gcarc}})
sacname = tr.stats.network+'.'+tr.stats.station+'.z'
tmp.write(os.path.join(outpath,sacname),format='SAC')
# st += tmp
'''
cft = recSTALTA(data_sum, int(0.5 / dt), int(10 / dt))
trigger = np.where(cft>1.5)[0][0]*dt
tmp = obspy.Trace()
tmp.data = data_sum
tmp.stats.delta = dt
plotTrigger(tmp, cft, 1.5, 0.5)
for tr in st:
# cef =np.sum(template*tr.data)
# print(tr.stats.network,tr.stats.station,cef)
# tr.data = -tr.data
tr.stats.sac.b = -trigger
sacname = tr.stats.network+'.'+tr.stats.station+'.z'
tr.write(os.path.join(outpath,sacname),format='SAC')
'''
from obspy.core import read
from obspy.signal.trigger import carlSTATrig, plotTrigger
trace = read("http://examples.obspy.org/ev0_6.a01.gse2")[0]
df = trace.stats.sampling_rate
cft = carlSTATrig(trace.data, int(5 * df), int(10 * df), 0.8, 0.8)
plotTrigger(trace, cft, 20.0, -20.0)
from obspy.core import read
from obspy.signal.trigger import classicSTALTA, plotTrigger
trace = read("http://examples.obspy.org/ev0_6.a01.gse2")[0]
df = trace.stats.sampling_rate
cft = classicSTALTA(trace.data, int(5. * df), int(10. * df))
plotTrigger(trace, cft, 1.5, 0.5)
def refTrigger(self, RefWaveform):
Config = self.Config
cfg = ConfigObj(dict=Config)
name = ('%s.%s.%s.%s') % (
RefWaveform[0].stats.network, RefWaveform[0].stats.station,
RefWaveform[0].stats.location, RefWaveform[0].stats.channel)
i = self.searchMeta(name, self.StationMeta)
de = loc2degrees(self.Origin, i)
ptime = 0
Phase = cake.PhaseDef('P')
model = cake.load_model()
if cfg.colesseo_input() == True:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth,
zstop=0.)
else:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth * km,
zstop=0.)
try:
ptime = arrivals[0].t
except:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km - 0.1)
ptime = arrivals[0].t
phasename = ('%sphase') % (os.path.basename(self.AF))
if ptime == 0:
print '\033[31mAvailable phases for reference station %s in range %f deegree\033[0m' % (
i, de)
print '\033[31m' + '|'.join(
[str(item['phase_name']) for item in tt]) + '\033[0m'
print '\033[31myou tried phase %s\033[0m' % (
self.Config[phasename])
raise Exception("\033[31mILLEGAL: phase definition\033[0m")
tw = self.calculateTimeWindows(ptime)
if cfg.pyrocko_download() == True:
stP = self.readWaveformsPicker_pyrocko(i, tw, self.Origin, ptime)
elif cfg.colesseo_input() == True:
stP = self.readWaveformsPicker_colos(i, tw, self.Origin, ptime)
else:
stP = self.readWaveformsPicker(i, tw, self.Origin, ptime)
refuntouchname = os.path.basename(self.AF) + '-refstation-raw.mseed'
stP.write(os.path.join(self.EventPath, refuntouchname),
format='MSEED',
byteorder='>')
stP.filter("bandpass",
freqmin=float(self.Config['refstationfreqmin']),
freqmax=float(self.Config['refstationfreqmax']))
stP.trim(tw['xcorrstart'], tw['xcorrend'])
trP = stP[0]
trP.stats.starttime = UTCDateTime(3600)
refname = os.path.basename(self.AF) + '-refstation-filtered.mseed'
trP.write(os.path.join(self.EventPath, refname),
format='MSEED',
byteorder='>')
sta = float(self.Config['refsta'])
lta = float(self.Config['reflta'])
cft = recSTALTA(trP.data, int(sta * trP.stats.sampling_rate),
int(lta * trP.stats.sampling_rate))
t = triggerOnset(cft, lta, sta)
try:
onset = t[0][0] / trP.stats.sampling_rate
print 'ONSET ', onset
except:
onset = self.mintforerun
trigger = trP.stats.starttime + onset
print 'TRIGGER ', trigger
print 'THEORETICAL: ', UTCDateTime(3600) + self.mintforerun
tdiff = (trP.stats.starttime + onset) - (UTCDateTime(3600) +
self.mintforerun)
print 'TDIFF: ', tdiff
refp = UTCDateTime(self.Origin.time) + ptime
reftriggeronset = refp + onset - self.mintforerun
if int(self.Config['autoxcorrcorrectur']) == 1:
try:
refmarkername = os.path.join(self.EventPath, ('%s-marker') %
(os.path.basename(self.AF)))
fobjrefmarkername = open(refmarkername, 'w')
fobjrefmarkername.write(
'# Snuffler Markers File Version 0.2\n')
fobjrefmarkername.write((
'phase: %s 0 %s None None None XWStart None False\n'
) % (tw['xcorrstart'].strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write((
'phase: %s 0 %s None None None XWEnd None False\n'
) % (tw['xcorrend'].strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write((
'phase: %s 1 %s None None None TheoP None False\n'
) % (refp.strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write((
'phase: %s 3 %s None None None XTrig None False'
) % (reftriggeronset.strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.close()
cmd = 'snuffler %s --markers=%s&' % (os.path.join(
self.EventPath, refuntouchname), refmarkername)
os.system(cmd)
thrOn = float(self.Config['reflta']) # 4
thrOff = float(self.Config['refsta']) # 0.7
plotTrigger(trP, cft, thrOn, thrOff)
selection = float(
raw_input('Enter self picked phase in seconds: '))
tdiff = selection - self.mintforerun
refname = os.path.basename(self.AF) + '-shift.mseed'
trP.stats.starttime = trP.stats.starttime - selection
trP.write(os.path.join(self.EventPath, refname),
format='MSEED')
except:
selection = 0.
refname = os.path.basename(self.AF) + '-shift.mseed'
trP.stats.starttime = trP.stats.starttime - selection - self.mintforerun
trP.write(os.path.join(self.EventPath, refname),
format='MSEED')
'''
tdiff = 0
trigger = trP.stats.starttime
'''
To = Trigger(name, trigger, os.path.basename(self.AF), tdiff)
return tdiff, To
adict={
'sac': {
'evla': tr.stats.sac.evla,
'evlo': tr.stats.sac.evlo,
'evdp': tr.stats.sac.evdp,
'stla': tr.stats.sac.stla,
'stlo': tr.stats.sac.stlo,
'b': ctime[0],
'gcarc': tr.stats.sac.gcarc
}
})
sacname = tr.stats.network + '.' + tr.stats.station + '.z'
tmp.write(os.path.join(outpath, sacname), format='SAC')
# st += tmp
'''
cft = recSTALTA(data_sum, int(0.5 / dt), int(10 / dt))
trigger = np.where(cft>1.5)[0][0]*dt
tmp = obspy.Trace()
tmp.data = data_sum
tmp.stats.delta = dt
plotTrigger(tmp, cft, 1.5, 0.5)
for tr in st:
# cef =np.sum(template*tr.data)
# print(tr.stats.network,tr.stats.station,cef)
# tr.data = -tr.data
tr.stats.sac.b = -trigger
sacname = tr.stats.network+'.'+tr.stats.station+'.z'
tr.write(os.path.join(outpath,sacname),format='SAC')
'''
from obspy.core import read
from obspy.signal.trigger import zDetect, plotTrigger
trace = read("http://examples.obspy.org/ev0_6.a01.gse2")[0]
df = trace.stats.sampling_rate
cft = zDetect(trace.data, int(10. * df))
plotTrigger(trace, cft, -0.4, -0.3)
from obspy.core import read
from obspy.signal.trigger import delayedSTALTA, plotTrigger
trace = read("http://examples.obspy.org/ev0_6.a01.gse2")[0]
df = trace.stats.sampling_rate
cft = delayedSTALTA(trace.data, int(5 * df), int(10 * df))
plotTrigger(trace, cft, 5, 10)
def plot_trigger(trace, cft, thrOn, thrOff, show=True):
"""
DEPRECATED. Use :func:`obspy.signal.trigger.plotTrigger` instead.
"""
from obspy.signal.trigger import plotTrigger
return plotTrigger(trace, cft, thrOn, thrOff, show=show)
# In[33]:
npt = len(trNfil[0].data)
emd = EMD(trNfil[0].data)
imfs = emd.decompose()
time = (np.linspace(1, npt, npt)) * dt
plt.rcParams["figure.figsize"] = (30.0, 50.0)
plot_imfs(trNfil[0].data, time, imfs)
# In[44]:
aa = trNfil[2].copy()
plotTrigger(aa, cft, 2.2, 0.5)
dm = len(cft)
item = [i for i in list(range(dm)) if cft[i] > 2.2]
print(min(item))
ene = [0] * dm
for i in xrange(1, dm):
# ene[i] = ene[i-1] + envel[i] ** 2
ene[i] = ene[i - 1] + trNfil[2].data[i] ** 2
# print(ene[i])
# print(ene/dm)
enen = ene / ene[-1]
enend = np.diff(enen)
item1 = [i for i in list(range(len(ene))) if enen[i] > 0.1]
def plot_trigger(trace, cft, thrOn, thrOff, show=True):
"""
DEPRECATED. Use :func:`obspy.signal.trigger.plotTrigger` instead.
"""
from obspy.signal.trigger import plotTrigger
return plotTrigger(trace, cft, thrOn, thrOff, show=show)
