def test_pretty_template_plot_sort(self):
fig = pretty_template_plot(self.template,
background=self.st,
event=self.event,
show=False,
return_figure=True,
title="sorted test template")
return fig
def test_pretty_template_plot(self):
fig = pretty_template_plot(self.template,
background=self.st,
picks=self.event.picks,
show=False,
return_figure=True,
title="test template")
return fig
prepick = 0.15, length = 4.6, swin = 'P',
parallel = True)
if len(template[0]) < 3:
print('Skipping template -- %i picks & %i WF in template' % (n_picks[i], len(template[0])))
else:
# stats = trace.Stats()
template[0].sort(['starttime'])
timestamp = template[0][0].stats.starttime
end_template = template[0][0].stats.endtime
# make plots
stplot = std.copy()
stplot = stplot.trim(starttime = timestamp - 5,
endtime= end_template + 5)
# stplot = stplot.detrend()
# stplot = stplot.resample(25)
stplot = stplot.filter('bandpass', freqmin= 3, freqmax = 10, corners = 4, zerophase = True)
pretty_template_plot(template[0], background = stplot,
picks = new_catalog[i].picks,
save = True, savefile=os.path.join(os.getcwd() + "/Template_plots", "template_" + str(timestamp) + '-' + str(events_clust[i]) + ".png"))
template[0].write(os.getcwd() + '/Templates_MSEED/template_' + str(timestamp) + '-'+ str(events_clust[i]) +'.ms', format='MSEED')
template_names.append('template_' + str(timestamp) + '.ms')
st.clear()
std.clear()
st_filter.clear()
stplot.clear()
print('Script took ', time.time() - init_time, ' s to complete.')
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 test_pretty_template_plot_basic(self):
fig = pretty_template_plot(self.template,
show=False,
return_figure=True)
return fig
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
for i, group_ids in enumerate(big_group_ids):
file_names = '/home/chet/data/mrp_data/catalogs/2015/final/clustering/' +\
'spatial/thresh_' + str(corr_thresh) + '_group_' + str(i)
temp_cat = Catalog()
with open(file_names + '.csv', 'wb') as f:
csvwriter = csv.writer(f, delimiter=',')
for event in cat:
ev_name = str(event.resource_id).split('/')[-1:][0]
if ev_name in group_ids:
x = str(event.preferred_origin().longitude)
y = str(event.preferred_origin().latitude)
z = str(event.preferred_origin().depth)
csvwriter.writerow([x, y, z])
temp_cat.append(event)
temp_cat.write(file_names + '.shp', format="SHAPEFILE")
# If clutering using space_cluster(), much simpler for shapefile writing
for i, group_cat in enumerate(non_sing_cats):
file_names = '/home/chet/data/mrp_data/catalogs/2015/final/qml/' +\
'spatial_clusts/thresh_%.02f_group_%03d' % (d_thresh, i)
group_cat.write(file_names + '.xml', format="QUAKEML")
# Below we'll plot picks over templates
for event in rand_cat:
ev_id = str(event.resource_id).split('/').pop()
fig_name = '/home/chet/figures/rand_cat_samp/filtered/filt_' +\
ev_id + '_pick_fig.png'
stream = template_list[ev_id]
pretty_template_plot(stream, save=fig_name, picks=event.picks)
plt.close()
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