def test_not_delayed(self):
"""Test the method of template_gen without applying delays to
channels."""
cat = get_geonet_events(minlat=-40.98,
maxlat=-40.85,
minlon=175.4,
maxlon=175.5,
startdate=UTCDateTime(2016, 5, 1),
enddate=UTCDateTime(2016, 5, 2))
cat = filter_picks(catalog=cat, top_n_picks=5)
template = from_client(catalog=cat,
client_id='GEONET',
lowcut=None,
highcut=None,
samp_rate=100.0,
filt_order=4,
length=10.0,
prepick=0.5,
swin='all',
process_len=3600,
debug=0,
plot=False,
delayed=False)[0]
for tr in template:
tr.stats.starttime.precision = 6
starttime = template[0].stats.starttime
length = template[0].stats.npts
print(template)
for tr in template:
self.assertTrue(
abs((tr.stats.starttime - starttime)) <= tr.stats.delta)
self.assertEqual(tr.stats.npts, length)
def get_test_data():
"""
Generate a set of waveforms from GeoNet for use in subspace testing
:return: List of cut templates with no filters applied
:rtype: list
"""
from eqcorrscan.tutorials.get_geonet_events import get_geonet_events
from obspy import UTCDateTime
from eqcorrscan.utils.catalog_utils import filter_picks
from eqcorrscan.utils.clustering import space_cluster
from obspy.clients.fdsn import Client
cat = get_geonet_events(minlat=-40.98,
maxlat=-40.85,
minlon=175.4,
maxlon=175.5,
startdate=UTCDateTime(2016, 5, 11),
enddate=UTCDateTime(2016, 5, 13))
cat = filter_picks(catalog=cat, top_n_picks=5)
stachans = list(
set([(pick.waveform_id.station_code, pick.waveform_id.channel_code)
for event in cat for pick in event.picks]))
clusters = space_cluster(catalog=cat, d_thresh=2, show=False)
cluster = sorted(clusters, key=lambda c: len(c))[-1]
client = Client('GEONET')
design_set = []
bulk_info = []
for event in cluster:
t1 = event.origins[0].time + 5
t2 = t1 + 15
for station, channel in stachans:
bulk_info.append(('NZ', station, '*', channel[0:2] + '?', t1, t2))
st = client.get_waveforms_bulk(bulk=bulk_info)
for event in cluster:
t1 = event.origins[0].time + 5
t2 = t1 + 15
design_set.append(st.copy().trim(t1, t2))
t1 = UTCDateTime(2016, 5, 11, 19)
t2 = UTCDateTime(2016, 5, 11, 20)
bulk_info = [('NZ', stachan[0], '*', stachan[1][0:2] + '?', t1, t2)
for stachan in stachans]
st = client.get_waveforms_bulk(bulk_info)
st.merge().detrend('simple').trim(starttime=t1, endtime=t2)
return design_set, st
def setUpClass(cls):
client = Client('GEONET')
t1 = UTCDateTime(2016, 9, 4)
t2 = t1 + 86400
catalog = get_geonet_events(startdate=t1, enddate=t2, minmag=4,
minlat=-49, maxlat=-35, minlon=175.0,
maxlon=185.0)
catalog = catalog_utils.filter_picks(catalog, channels=['EHZ'],
top_n_picks=5)
for event in catalog:
extra_pick = Pick()
extra_pick.phase_hint = 'S'
extra_pick.time = event.picks[0].time + 10
extra_pick.waveform_id = event.picks[0].waveform_id
event.picks.append(extra_pick)
cls.templates = template_gen.from_client(catalog=catalog,
client_id='GEONET',
lowcut=2.0, highcut=9.0,
samp_rate=50.0, filt_order=4,
length=3.0, prepick=0.15,
swin='all', process_len=3600)
# Download and process the day-long data
bulk_info = [(tr.stats.network, tr.stats.station, '*',
tr.stats.channel[0] + 'H' + tr.stats.channel[1],
t1 + (4 * 3600), t1 + (5 * 3600))
for tr in cls.templates[0]]
# Just downloading an hour of data
print('Downloading data')
st = client.get_waveforms_bulk(bulk_info)
st.merge(fill_value='interpolate')
st.trim(t1 + (4 * 3600), t1 + (5 * 3600)).sort()
# This is slow?
print('Processing continuous data')
cls.st = pre_processing.shortproc(st, lowcut=2.0, highcut=9.0,
filt_order=4, samp_rate=50.0,
debug=0, num_cores=1)
cls.st.trim(t1 + (4 * 3600), t1 + (5 * 3600)).sort()
cls.template_names = [str(template[0].stats.starttime)
for template in cls.templates]
def run_tutorial(plot=False, multiplex=True, return_streams=False):
"""
Run the tutorial.
:return: detections
"""
# We are going to use data from the GeoNet (New Zealand) catalogue. GeoNet
# do not implement the full FDSN system yet, so we have a hack to get
# around this. It is not strictly part of EQcorrscan, so we haven't
# included it here, but you can find it in the tutorials directory of the
# github repository
import obspy
if int(obspy.__version__.split('.')[0]) >= 1:
from obspy.clients.fdsn import Client
else:
from obspy.fdsn import Client
from eqcorrscan.tutorials.get_geonet_events import get_geonet_events
from obspy import UTCDateTime
from eqcorrscan.utils.catalog_utils import filter_picks
from eqcorrscan.utils.clustering import space_cluster
from eqcorrscan.core import subspace
cat = get_geonet_events(minlat=-40.98,
maxlat=-40.85,
minlon=175.4,
maxlon=175.5,
startdate=UTCDateTime(2016, 5, 1),
enddate=UTCDateTime(2016, 5, 20))
# This gives us a catalog of events - it takes a while to download all
# the information, so give it a bit!
# We will generate a five station, multi-channel detector.
cat = filter_picks(catalog=cat, top_n_picks=5)
stachans = list(
set([(pick.waveform_id.station_code, pick.waveform_id.channel_code)
for event in cat for pick in event.picks]))
# In this tutorial we will only work on one cluster, defined spatially.
# You can work on multiple clusters, or try to whole set.
clusters = space_cluster(catalog=cat, d_thresh=2, show=False)
# We will work on the largest cluster
cluster = sorted(clusters, key=lambda c: len(c))[-1]
# This cluster contains 32 events, we will now download a trim the
# waveforms. Note that each chanel must start at the same time and be the
# same length for multiplexing. If not multiplexing EQcorrscan will
# maintain the individual differences in time between channels and delay
# the detection statistics by that amount before stacking and detection.
client = Client('GEONET')
design_set = []
bulk_info = []
for event in cluster:
t1 = event.origins[0].time
t2 = t1 + 25
for station, channel in stachans:
bulk_info.append(('NZ', station, '*', channel[0:2] + '?', t1, t2))
st = client.get_waveforms_bulk(bulk=bulk_info)
for event in cluster:
t1 = event.origins[0].time
t2 = t1 + 25
design_set.append(st.copy().trim(t1, t2))
# Construction of the detector will process the traces, then align them,
# before multiplexing.
detector = subspace.Detector()
detector.construct(streams=design_set,
lowcut=2.0,
highcut=9.0,
filt_order=4,
sampling_rate=20,
multiplex=multiplex,
name='Wairarapa1',
align=True,
reject=0.2,
shift_len=6,
plot=plot).partition(9)
if plot:
detector.plot()
# We also want the continuous stream to detect in.
t1 = UTCDateTime(2016, 5, 11, 19)
t2 = UTCDateTime(2016, 5, 11, 20)
# We are going to look in a single hour just to minimize cost, but you can \
# run for much longer.
bulk_info = [('NZ', stachan[0], '*', stachan[1][0] + '?' + stachan[1][-1],
t1, t2) for stachan in detector.stachans]
st = client.get_waveforms_bulk(bulk_info)
st.merge().detrend('simple').trim(starttime=t1, endtime=t2)
# We set a very low threshold because the detector is not that great, we
# haven't aligned it particularly well - however, at this threshold we make
# two real detections.
detections, det_streams = detector.detect(st=st,
threshold=0.005,
trig_int=2,
extract_detections=True)
if return_streams:
return detections, det_streams
else:
return detections
#template creation
#Works with GEONET
import sys
sys.path.insert(0, '/Users/home/taylorte/EQcorrscan')
from obspy import UTCDateTime
from obspy.clients.fdsn import Client
from eqcorrscan.core.template_gen import from_client
from eqcorrscan.tutorials.get_geonet_events import get_geonet_events
from eqcorrscan.utils.catalog_utils import filter_picks
from eqcorrscan.core import template_gen
catalog = get_geonet_events(
startdate = UTCDateTime('2016-11-13T11:00:00'),
enddate = UTCDateTime('2016-11-14T11:00:00'),
maxlat = -42.0, minlat = -43.0, minlon = 173, maxlon = 174)
print catalog
filtered_catalog = filter_picks(catalog, stations=['WEL'], top_n_picks=2)
print filtered_catalog
templates = from_client(
catalog = filtered_catalog, client_id='GEONET', lowcut = 2.0,
highcut = 9.0, samp_rate = 20.0, filt_order = 4, length = 2.0,
prepick = 0.15, swin = 'all', process_len = 86400)
print templates
templates[0].plot()
