def iter_chunked(self, tinc):
tr_len = self.n_samples * self.deltat_want
nslc_to_index = self.nslc_to_index
tpad = self.config.effective_tpad
tstart = util.stt(self.tstart) if self.tstart else None
tstop = util.stt(self.tstop) if self.tstop else None
logger.debug('START')
for trs in self.data_pile.chopper(
tinc=tinc, tmin=tstart, tmax=tstop, tpad=tpad,
keep_current_files_open=True, want_incomplete=False,
trace_selector=self.reject_blacklisted):
chunk = self.get_raw_data_chunk(self.tensor_shape)
if not trs:
yield chunk, UNLABELED
continue
for tr in trs:
self.preprocess(tr)
indices = [nslc_to_index[tr.nslc_id] for tr in trs]
self.fit_data_into_chunk(trs, chunk=chunk, indices=indices,
tref=trs[0].tmin)
if all_NAN(chunk):
logger.debug('all NAN. skipping...')
continue
yield chunk, UNLABELED
def lessThan(self, left, right):
if left.column() == _column_mapping['Time']:
return util.stt(str(left.data().toString())) > \
util.stt(str(right.data().toString()))
elif left.column() == _column_mapping['Label']:
return left > right
else:
return left.data().toDouble()[0] > right.data().toDouble()[0]
def lessThan(self, left, right):
if left.column() == _column_mapping['Time']:
return util.stt(str(left.data().toString())) > \
util.stt(str(right.data().toString()))
elif left.column() == _column_mapping['Label']:
return left > right
else:
return left.data().toDouble()[0] > right.data().toDouble()[0]
def benchmark_stt_tts(self):
for x in range(2):
if x == 1:
util.util_ext = None
t = util.str_to_time('1999-03-20 20:10:10')
tt1 = time.time()
for i in range(10000):
s = util.tts(t)
util.stt(s)
tt2 = time.time()
print(tt2 - tt1)
def benchmark_stt_tts(self):
for x in xrange(2):
if x == 1:
util.util_ext = None
t = util.str_to_time('1999-03-20 20:10:10')
tt1 = time.time()
for i in xrange(10000):
s = util.tts(t)
util.stt(s)
tt2 = time.time()
print tt2 - tt1
def testISC(self):
cat = catalog.ISC()
tmin = util.stt('2009-02-22 05:00:00')
tmax = util.stt('2009-02-22 19:00:00')
cat.get_events((tmin, tmax), magmin=5)
markers = cat.get_phase_markers(
(tmin, tmax), phases=['XXX'], station_codes=['XXXXX', 'YYYYY'])
self.assertEqual(len(markers), 0)
markers = cat.get_phase_markers(
(tmin, tmax), phases=['P', 'PcP'], station_codes=['WRA'])
self.assertEqual(len(markers), 75)
def testISC(self):
cat = catalog.ISC()
tmin = util.stt('2009-02-22 05:00:00')
tmax = util.stt('2009-02-22 19:00:00')
cat.get_events((tmin, tmax), magmin=5)
markers = cat.get_phase_markers(
(tmin, tmax), phases=['XXX'], station_codes=['XXXXX', 'YYYYY'])
self.assertEqual(len(markers), 0)
markers = cat.get_phase_markers(
(tmin, tmax), phases=['P', 'PcP'], station_codes=['WRA'])
self.assertEqual(len(markers), 76)
def test_leapsecond(self):
fns = map(common.test_data_file, ['leapsecond_dec.cube',
'leapsecond_jan.cube'])
trs = defaultdict(list)
for fn in fns:
for tr in datacube.iload(fn):
trs[tr.channel].append(tr)
for cha in trs.keys():
tra, trb, trc = trs[cha]
assert abs(
tra.tmax - (util.stt('2017-01-01 00:00:01') - tra.deltat)) \
< tra.deltat * 0.001
assert abs(
trb.tmin - util.stt('2017-01-01 00:00:00')) \
< trb.deltat * 0.001
def gen_real_stations(tmin=util.stt('2014-01-01 16:10:00.000'),
tmax=util.stt('2014-01-01 16:39:59.000')):
stations = []
selection = [
('*', '*', '*', 'BH*', tmin, tmax),
]
request_response = ws.station(site='iris',
selection=selection,
level='response')
request_response.dump_xml(filename='stations.xml')
sx = fs.load_xml(filename='stations.xml')
for station in sx.get_pyrocko_stations():
stations.append(station)
return stations
def test_read(self):
fpath = common.test_data_file('test.quakeml')
qml = quakeml.QuakeML.load_xml(filename=fpath)
events = qml.get_pyrocko_events()
assert len(events) == 1
e = events[0]
assert e.lon == -116.9945
assert e.lat == 33.986
assert e.depth == 17300
assert e.time == util.stt("1999-04-02 17:05:10.500")
def supply(watch_folder,
tmin,
tmax,
seiger=True,
selection=None,
duration=3,
package_length=86400,
providers=["bgr", "http://ws.gpi.kit.edu"],
clean=True):
try:
tmin = util.stt(tmin)
tmax = util.stt(tmax)
except:
pass
iter = 0
vorhalten = True
while vorhalten is True:
timemod.sleep(5)
totalDir = 0
for base, dirs, files in os.walk(watch_folder):
for directories in dirs:
totalDir += 1
if totalDir < duration:
twin_start = tmin + iter * package_length
twin_end = tmin + package_length + iter * package_length
download_raw(watch_folder,
twin_start,
twin_end,
seiger=seiger,
selection=selection,
providers=providers,
clean=clean)
iter = iter + 1
if twin_start > tmax:
vorhalten = False
def find_station(name, tmin=None, tmax=None):
if tmin and tmax is None:
tmin = util.stt('2013-10-23 21:06:54.400')
tmax = util.stt('2013-10-23 21:11:59.000')
selection = [('*', name, '*', '*', tmin, tmax)]
sites = [
"bgr", "http://192.168.11.220:8080", "http://gpiseisgate.gpi.kit.edu",
"geofon", "iris", "orfeus", "koeri", "ethz", "lmu", "resif", "geonet",
"ingv"
]
for site in sites:
try:
request_response = fdsn.station(site='%s' % site,
selection=selection,
level='response')
pyrocko_stations = request_response.get_pyrocko_stations()
stations_hyposat.append(pyrocko_stations[0])
stations_inversion.append(pyrocko_stations[0])
st = pyrocko_stations[0]
return st.lat, st.lon
except Exception:
return False
def search_catalog(date, min_magnitude, dayrange=1.):
"""
Search the gcmt catalog for the specified date (+- 1 day), filtering the
events with given magnitude threshold.
Parameters
----------
date : str
'YYYY-MM-DD', date of the event
min_magnitude : float
approximate minimum Mw of the event
dayrange : float
temporal search interval [days] around date
Returns
-------
event : :class:`pyrocko.model.Event`
"""
gcmt = catalog.GlobalCMT()
time_s = util.stt(date + ' ' + seconds_str)
d1 = time_s - (dayrange * (sphr * hrpd))
d2 = time_s + (dayrange * (sphr * hrpd))
logger.info('Getting relevant events from the gCMT catalog for the dates:'
'%s - %s \n' % (util.tts(d1), util.tts(d2)))
events = gcmt.get_events((d1, d2), magmin=min_magnitude)
if len(events) < 1:
logger.warn('Found no event information in the gCMT catalog.')
event = None
if len(events) > 1:
logger.info(
'More than one event from that date with specified magnitude '
'found! Please copy the relevant event information to the '
'configuration file!')
for event in events:
print event
event = events[0]
elif len(events) == 1:
event = events[0]
return event
def tstart_data(self):
'''Returns start point of data returned by generator.'''
return util.stt(self.tstart) if self.tstart else self.data_pile.tmin
def download_raw(path,
tmint,
tmaxt,
seiger=True,
selection=None,
providers=["bgr", "http://ws.gpi.kit.edu"],
clean=True,
detector=False,
common_f=80,
tinc=None):
try:
tmin = util.stt(tmint)
tmax = util.stt(tmaxt)
except:
tmin = tmint
tmax = tmaxt
util.ensuredir(path + "/downloads")
for provider in providers:
if clean is True and detector is True:
subprocess.run(['rm -r %s*' % (path + '/downloads/')], shell=True)
if seiger is True:
selection = get_seiger_stations(tmin, tmax)
request_waveform = fdsn.dataselect(site=provider, selection=selection)
# write the incoming data stream to 'traces.mseed'
if provider == "http://ws.gpi.kit.edu":
provider = "kit"
if provider == "http://192.168.11.220:8080":
provider = "bgr"
download_basepath = os.path.join(path, "traces_%s.mseed" % provider)
with open(download_basepath, 'wb') as file:
file.write(request_waveform.read())
traces = io.load(download_basepath)
if common_f is not None:
for tr in traces:
if tr.deltat != common_f:
tr.downsample_to(1 / common_f)
tr.ydata = tr.ydata.astype(num.int32)
if detector is True:
for tr in traces:
tr.chop(tmin, tmax)
date_min = get_time_format_eq(tr.tmin)
date_max = get_time_format_eq(tr.tmax)
io.save(
tr, "%sdownloads/%s/%s.%s..%s__%s__%s.mseed" %
(path, tr.station, tr.network, tr.station, tr.channel,
date_min, date_max))
else:
util.ensuredir("%s/downloads/" % path)
window_start = traces[0].tmin
window_end = traces[0].tmax
timestring = util.time_to_str(window_start, format='%Y-%m')
io.save(
traces, "%s/%s/%s_%s_%s.mseed" %
(path, timestring, provider, tmin, tmax))
if clean is True:
for provider in providers:
if provider == "http://192.168.11.220:8080":
provider = "bgr"
if provider == "http://ws.gpi.kit.edu":
provider = "kit"
subprocess.run(
['rm -r %s*' % (path + '/traces_%s.mseed' % provider)],
shell=True,
stdout=DEVNULL,
stderr=STDOUT)
def load_data_archieve(validation_data,
gf_freq,
duration=4,
wanted_start=None,
wanted_end=None):
folder = validation_data
pathlist = Path(folder).glob('day*')
waveforms = []
stations = []
if wanted_start is not None:
try:
wanted_start = util.stt(wanted_start)
wanted_end = util.stt(wanted_end)
except:
pass
from pyrocko import pile
paths = []
safecon = 0
for path in sorted(pathlist):
path = str(path)
d2 = float(str(path)[-12:])
d1 = float(str(path)[-25:-13])
if wanted_start is not None:
do_safety_files = False
if (d1 >= wanted_start
and d2 <= wanted_end) or (d2 - wanted_end < 86400.
and d2 - wanted_end > 0.
and safecon == 0):
st = model.load_stations(path + "/waveforms/stations.raw.txt")
d_diff = d2 - d1
tr_packages = int(d_diff / duration)
#for tr in traces:
# tr.downsample_to(gf_freq)
# if safecon == 0:
pathlist_waveform_files = Path(path + "/waveforms/rest/").glob(
'*.mseed')
wanted_start_str = util.tts(wanted_start)[14:16]
diff_to_full = float(wanted_start_str)
max_diff = 55.
min_diff = 5.
if diff_to_full > max_diff or diff_to_full < min_diff:
do_safety_files = True
for path_wave in sorted(pathlist_waveform_files):
path_wave = str(path_wave)
p1 = path_wave[-25:-15]
p2 = path_wave[-14:-12]
p3 = path_wave[-11:-9]
p4 = path_wave[-8:-6]
try:
file_time = util.stt(p1 + " " + p2 + ":" + p3 + ":" +
p4)
tdiff = file_time - wanted_start
if do_safety_files is True:
if float(p2) - float(
util.tts(wanted_start)[11:13]) == 0:
paths.append(str(path_wave))
if diff_to_full > max_diff and float(p2) - float(
util.tts(wanted_start)[11:13]) == 1.:
paths.append(str(path_wave))
if diff_to_full < min_diff and float(p2) - float(
util.tts(wanted_start)[11:13]) == -1.:
paths.append(str(path_wave))
else:
if float(p2) - float(
util.tts(wanted_start)[11:13]) == 0:
paths.append(str(path_wave))
except:
pass
safecon += 1
p = pile.make_pile(paths)
for traces in p.chopper(tmin=wanted_start, tinc=duration):
if traces:
if traces[0].tmax < wanted_end:
# for i in range(0, tr_packages):
# traces = traces
#for tr in traces:
# tr.chop(tr.tmin+i*duration,
# tr.tmin+i*duration+duration)
#tr.downsample_to(gf_freq)
waveforms.append(traces)
stations.append(st)
# else:
# traces = io.load(path+"/waveforms/rest/traces.mseed")
# st = model.load_stations(path+"/waveforms/stations.raw.txt")
# for tr in traces:
# tr.downsample_to(gf_freq)
# waveforms.append(traces)
# stations.append(st)
return waveforms, stations
def locsat2pyrocko(fname):
f = open(fname, "r")
file = f.readlines()
events = []
events_data = []
events_list = []
phase_markers = []
events = []
events_data = []
phase_markers_all_events = []
phase = None
depth = None
component = None
for line in file:
component = None
idx = line.find("Event ID :")
if idx != -1:
idx = line.find(":")
event_id = line[idx + 1:]
if event_id in events:
idx_event = events.index(event_id)
phase_markers = phase_markers_all_events[idx_event]
else:
phase_markers = []
events.append(event_id)
idx = line.find("Station code :")
if idx != -1:
idx = line.find(":")
station = line[idx + 1:]
idx = line.find("Phase name :")
if idx != -1:
idx = line.find(":")
phase = line[idx + 1:]
idx = line.find("Component :")
if idx != -1:
idx = line.find(":")
component = line[idx + 1:]
idx = line.find("Magnitude ml :")
if idx != -1:
idx = line.find(":")
ml = line[idx + 1:]
idx = line.find("Onset time :")
if idx != -1:
idx = line.find(":")
time_full = str(line[idx + 1:])
idx = time_full.find("_")
time = time_full[idx + 1:]
idxs = time_full.find("-")
day = time_full[:idxs]
month = time_full[idxs + 1:idxs + 4]
month = monthToNum(month)
year = time_full[idxs + 5:idxs + 9]
t = year + "-" + str(month) + "-" + str(day) + " " + str(time)
t = stt(t)
idx = line.find("Latitude :")
if idx != -1:
idx = line.find("+")
lat = float(line[idx + 1:])
idx = line.find("Longitude :")
if idx != -1:
idx = line.find("+")
lon = float(line[idx + 1:])
events_data.append([lat, lon])
idx = line.find("Depth (km) :")
if idx != -1:
idx = line.find(":")
depth = float(line[idx + 1:]) * 1000.
if component is not None:
phase_markers.append(
PhaseMarker([("GR", station.strip(), "", component.strip())],
tmin=t,
tmax=t,
phasename=phase.strip()))
if depth is not None:
try:
event = model.event.Event(lat=lat,
lon=lon,
time=t,
depth=depth,
tags=str(event_id))
events_list.append(event)
except:
pass
if event_id in events:
idx_event = events.index(event_id)
if len(phase_markers_all_events) > 0:
phase_markers_all_events[idx_event] = phase_markers
else:
phase_markers_all_events.append(phase_markers)
else:
phase_markers_all_events.append(phase_markers)
for phase_markers in phase_markers_all_events:
PhaseMarker.save_markers(phase_markers, "%s.pym" % (str(t)), fdigits=3)
return events, phase_markers_all_events
from pyrocko.client import fdsn
from pyrocko import util, io, trace
tmin = util.stt('2014-01-01 16:10:00.000')
tmax = util.stt('2014-01-01 16:39:59.000')
# select stations by their NSLC id and wildcards (asterisk)
selection = [
('*', 'HMDT', '*', '*', tmin, tmax), # all available components
('GE', 'EIL', '*', '*Z', tmin, tmax), # all vertical components
]
# Restricted access token
# token = open('token.asc', 'rb').read()
# request_waveform = fdsn.dataselect(site='geofon', selection=selection,
# token=token)
# setup a waveform data request
request_waveform = fdsn.dataselect(site='geofon', selection=selection)
# write the incoming data stream to 'traces.mseed'
with open('traces.mseed', 'wb') as file:
file.write(request_waveform.read())
# request meta data
request_response = fdsn.station(
site='geofon', selection=selection, level='response')
# save the response in YAML and StationXML format
request_response.dump(filename='responses_geofon.yaml')
def iter_chunked(tinc,
path,
data_pile,
tmin=None,
tmax=None,
minlat=49.1379,
maxlat=49.1879,
minlon=8.1223,
maxlon=8.1723,
channels=["EH" + "[ZNE]"],
client_list=["BGR"],
download=True,
seiger=True,
selection=None,
path_waveforms=None,
sds=None,
stream=False,
reject_blacklisted=None,
tpad=0,
tstart=None,
tstop=None,
hf=10,
lf=1,
deltat=None,
models=None):
try:
tstart = util.stt(tmin) if tmin else None
tstop = util.stt(tmax) if tmax else None
except:
pass
model_path = os.path.dirname(
os.path.abspath(__file__)) + "/model/EqT_model.h5"
deltat_cf = min(data_pile.deltats.keys())
for i, trs in enumerate(
data_pile.chopper(tinc=tinc,
tmin=tstart,
tmax=tstop,
tpad=tpad,
keep_current_files_open=False,
want_incomplete=True)):
tminc = None
tmaxc = None
for tr in trs:
if tminc is None:
tminc = tr.tmin
tmaxc = tr.tmax
else:
if tminc < tr.tmin:
tminc = tr.tmin
if tmaxc > tr.tmax:
tmaxc = tr.tmax
for tr in trs:
tr.highpass(4, 5)
# try:
try:
tr.chop(tminc, tmaxc)
except:
pass
date_min = download_raw.get_time_format_eq(tminc)
date_max = download_raw.get_time_format_eq(tmaxc)
io.save(
tr, "%s/downloads/%s/%s.%s..%s__%s__%s.mseed" %
(path, tr.station, tr.network, tr.station, tr.channel,
date_min, date_max))
# except:
# pass
process(path,
tmin=tminc,
tmax=tmaxc,
minlat=minlat,
maxlat=maxlat,
minlon=minlon,
maxlon=maxlon,
channels=channels,
client_list=client_list,
download=download,
seiger=seiger,
selection=selection,
path_waveforms=path_waveforms,
stream=stream,
model=None,
iter=i,
models=models,
sds=None)
for tr in trs:
subprocess.run([
"rm -r %s/downloads/%s/%s.%s..%s__%s__%s.mseed" %
(path, tr.station, tr.network, tr.station, tr.channel,
date_min, date_max)
],
shell=True)
cat = Catalog()
files = glob("%s/asociation*/associations.xml" % path)
files.sort(key=os.path.getmtime)
for file in files:
cat_read = read_events(file)
for event in cat_read:
cat.append(event)
cat.write("%s/events_eqt.qml" % path, format="QUAKEML")
def main(path,
tmin="2021-05-26 06:20:03.800",
tmax="2016-02-12 06:20:03.800",
minlat=49.1379,
maxlat=49.1879,
minlon=8.1223,
maxlon=8.1723,
channels=["EH" + "[ZNE]"],
client_list=["BGR", "http://ws.gpi.kit.edu/"],
download=True,
seiger=True,
selection=None,
clean=False,
stream=False,
path_waveforms=None,
tinc=None,
lf=5,
hf=40,
freq=None,
models=None,
sds=None):
if download is True:
if tinc is None:
download_raw.download_raw(path,
tmin,
tmax,
seiger=seiger,
selection=selection,
providers=client_list,
clean=True,
detector=True,
common_f=freq)
else:
tmin = util.stt(tmin)
tmax = util.stt(tmax)
iter = 0
vorhalten = True
tinc = float(tinc)
if int(int(tmax - tmin) / int(tinc)) == 0:
nwin = 1
else:
nwin = int(int(tmax - tmin) / int(tinc))
for i in range(nwin):
twin_start = tmin + iter * tinc
twin_end = tmin + tinc + iter * tinc
download_raw.download_raw(path,
twin_start,
twin_end,
seiger=seiger,
selection=selection,
providers=client_list,
clean=clean,
detector=True,
common_f=freq)
load_eqt_folder(path,
tinc,
path,
tmin=twin_start,
tmax=twin_end,
minlat=minlat,
maxlat=maxlat,
minlon=minlon,
maxlon=maxlon,
channels=channels,
client_list=client_list,
download=download,
seiger=seiger,
selection=selection,
stream=stream,
hf=hf,
lf=lf,
models=models)
subprocess.run(['rm -r %s*' % (path + '/downloads*')],
shell=True)
iter = +1
if path_waveforms is not None or sds is not None:
load_eqt_folder(path_waveforms,
tinc,
path,
tmin=tmin,
tmax=tmax,
minlat=minlat,
maxlat=maxlat,
minlon=minlon,
maxlon=maxlon,
channels=channels,
client_list=client_list,
download=download,
seiger=seiger,
selection=selection,
stream=stream,
hf=hf,
lf=lf,
models=models,
sds=sds)
else:
process(path,
tmin=tmin,
tmax=tmax,
minlat=minlat,
maxlat=maxlat,
minlon=minlon,
maxlon=maxlon,
channels=channels,
client_list=client_list,
download=download,
seiger=seiger,
selection=selection,
path_waveforms=path_waveforms,
stream=stream,
models=models)
def mts_paper_scedc():
'''
Hardcoded copy of the moment tensors from the scedc website.
Retrieved: 23.12.2020
'''
mts = []
times = []
events = []
#https://service.scedc.caltech.edu/MomentTensor/solutions/web_38460967/ci38460967_MT.html
time = "2019-07-06 09:28:29"
Mo = 2.69e+23
Mxx = -1.803e+23
Mxy = -1.840e+23
Mxz = 2.476e+22
Myy = 2.068e+23
Myz = -1.784e+22
Mzz = -2.650e+22
lat = 35.8978
lon = -117.7250
depth = 3900
M = [Mxx, Myy, Mzz, Mxy, Mxz, Myz]
mt = pmt.MomentTensor(mnn=M[0],
mee=M[1],
mdd=M[2],
mne=M[3],
mnd=M[4],
med=M[5])
mts.append(mt)
times.append(time)
event = model.Event(time=util.stt(time),
moment_tensor=M,
lat=lat,
lon=lon,
depth=depth)
events.append(event)
# https://service.scedc.caltech.edu/MomentTensor/solutions/web_38463551/ci38463551_MT.html
time = "2019-07-06 13:06:55"
Mo = 6.91e+22
Mxx = -4.574e+22
Mxy = 4.274e+21
Mxz = 1.557e+22
Myy = 7.768e+22
Myz = -1.884e+22
Mzz = -3.194e+22
lat = 35.9280
lon = -117.7063
depth = 1500
M = [Mxx, Myy, Mzz, Mxy, Mxz, Myz]
mt = pmt.MomentTensor(mnn=M[0],
mee=M[1],
mdd=M[2],
mne=M[3],
mnd=M[4],
med=M[5])
mts.append(mt)
times.append(time)
event = model.Event(time=util.stt(time),
moment_tensor=M,
lat=lat,
lon=lon,
depth=depth)
events.append(event)
# https://service.scedc.caltech.edu/MomentTensor/solutions/web_38466495/ci38466495_MT.html
time = "2019-07-06 17:59:15"
Mo = 8.70e+21
Mxx = -4.447e+21
Mxy = -6.931e+21
Mxz = -1.326e+21
Myy = 5.598e+21
Myz = 9.049e+20
Mzz = -1.151e+21
lat = 35.8997
lon = -117.7347
depth = 3000
M = [Mxx, Myy, Mzz, Mxy, Mxz, Myz]
mt = pmt.MomentTensor(mnn=M[0],
mee=M[1],
mdd=M[2],
mne=M[3],
mnd=M[4],
med=M[5])
mts.append(mt)
times.append(time)
event = model.Event(time=util.stt(time),
moment_tensor=M,
lat=lat,
lon=lon,
depth=depth)
events.append(event)
# https://service.scedc.caltech.edu/MomentTensor/solutions/web_38517119/ci38517119_MT.html
time = "2019-07-10 12:00:05"
Mo = 6.52e+21
Mxx = -1.755e+21
Mxy = -1.499e+21
Mxz = 3.140e+21
Myy = 6.118e+21
Myz = -8.072e+20
Mzz = -4.363e+21
lat = 35.8765
lon = -117.7068
depth = 4400
M = [Mxx, Myy, Mzz, Mxy, Mxz, Myz]
mt = pmt.MomentTensor(mnn=M[0],
mee=M[1],
mdd=M[2],
mne=M[3],
mnd=M[4],
med=M[5])
mts.append(mt)
times.append(time)
event = model.Event(time=util.stt(time),
moment_tensor=M,
lat=lat,
lon=lon,
depth=depth)
events.append(event)
# https://service.scedc.caltech.edu/MomentTensor/solutions/web_38538991/ci38538991_MT.html
time = "2019-07-11 23:45:19"
Mo = 1.97e+22
Mxx = -8.999e+21
Mxy = -1.598e+22
Mxz = 6.197e+21
Myy = 9.964e+21
Myz = 2.233e+21
Mzz = -9.657e+20
lat = 35.9482
lon = -117.7057
depth = 1500
M = [Mxx, Myy, Mzz, Mxy, Mxz, Myz]
mt = pmt.MomentTensor(mnn=M[0],
mee=M[1],
mdd=M[2],
mne=M[3],
mnd=M[4],
med=M[5])
mts.append(mt)
times.append(time)
event = model.Event(time=util.stt(time),
moment_tensor=M,
lat=lat,
lon=lon,
depth=depth)
events.append(event)
#https://service.scedc.caltech.edu/MomentTensor/solutions/web_38644943/ci38644943_MT.html
time = "2019-07-26 00:42:48"
Mo = 1.62e+23
Mxx = -6.930e+22
Mxy = 9.560e+21
Mxz = 3.263e+22
Myy = 1.860e+23
Myz = -2.825e+22
Mzz = -1.167e+23
lat = 35.9237
lon = -117.7115
depth = 1900
M = [Mxx, Myy, Mzz, Mxy, Mxz, Myz]
mt = pmt.MomentTensor(mnn=M[0],
mee=M[1],
mdd=M[2],
mne=M[3],
mnd=M[4],
med=M[5])
mts.append(mt)
times.append(time)
event = model.Event(time=util.stt(time),
moment_tensor=M,
lat=lat,
lon=lon,
depth=depth)
events.append(event)
# https://service.scedc.caltech.edu/MomentTensor/solutions/web_38996632/ci38996632_MT.html
time = "2019-08-22 20:49:50"
Mo = 2.72e+23
Mxx = -8.042e+22
Mxy = -2.026e+23
Mxz = 1.983e+22
Myy = 2.492e+23
Myz = 1.635e+22
Mzz = -1.688e+23
lat = 35.9077
lon = -117.7092
depth = 4900
M = [Mxx, Myy, Mzz, Mxy, Mxz, Myz]
mt = pmt.MomentTensor(mnn=M[0],
mee=M[1],
mdd=M[2],
mne=M[3],
mnd=M[4],
med=M[5])
mts.append(mt)
times.append(time)
event = model.Event(time=util.stt(time),
moment_tensor=M,
lat=lat,
lon=lon,
depth=depth)
events.append(event)
# https://service.scedc.caltech.edu/MomentTensor/solutions/web_38999296/ci38999296_MT.html
time = "2019-08-23 05:34:10"
Mo = 3.87e+22
Mxx = -1.383e+22
Mxy = -2.949e+22
Mxz = 1.231e+22
Myy = 2.220e+22
Myz = 9.991e+21
Mzz = -8.375e+21
lat = 35.9078
lon = -117.7047
depth = 7200
M = [Mxx, Myy, Mzz, Mxy, Mxz, Myz]
mt = pmt.MomentTensor(mnn=M[0],
mee=M[1],
mdd=M[2],
mne=M[3],
mnd=M[4],
med=M[5])
mts.append(mt)
times.append(time)
event = model.Event(time=util.stt(time),
moment_tensor=M,
lat=lat,
lon=lon,
depth=depth)
events.append(event)
return mts, times, events
