def getCatData(date, opt):
"""
Download data from IRIS or Earthworm waveserver with padding and filter it. This is
a specialized version getData() for catalog events, pulling a smaller amount of time
around a known event.
date: UTCDateTime of known catalog event
opt: Options object describing station/run parameters
Returns ObsPy stream objects, one for cutting and the other for triggering
"""
nets = opt.network.split(',')
stas = opt.station.split(',')
locs = opt.location.split(',')
chas = opt.channel.split(',')
if opt.server == "IRIS":
client = Client("IRIS")
else:
client = EWClient(opt.server, opt.port)
st = Stream()
for n in range(len(stas)):
try:
stmp = client.get_waveforms(nets[n], stas[n], locs[n], chas[n],
date - opt.atrig, date + 3*opt.atrig)
stmp = stmp.filter("bandpass", freqmin=opt.fmin, freqmax=opt.fmax,
corners=2, zerophase=True)
stmp = stmp.merge(method=1, fill_value='interpolate')
except (obspy.fdsn.header.FDSNException):
try: # try again
stmp = client.get_waveforms(nets[n], stas[n], locs[n], chas[n],
date - opt.atrig, date + 3*opt.atrig)
stmp = stmp.filter("bandpass", freqmin=opt.fmin, freqmax=opt.fmax,
corners=2, zerophase=True)
stmp = stmp.merge(method=1, fill_value='interpolate')
except (obspy.fdsn.header.FDSNException):
print('No data found for {0}.{1}'.format(stas[n],nets[n]))
trtmp = Trace()
trtmp.stats.sampling_rate = opt.samprate
trtmp.stats.station = stas[n]
stmp = Stream().extend([trtmp.copy()])
# Resample to ensure all traces are same length
if stmp[0].stats.sampling_rate != opt.samprate:
stmp = stmp.resample(opt.samprate)
st.extend(stmp.copy())
st = st.trim(starttime=date-opt.atrig, endtime=date+3*opt.atrig, pad=True,
fill_value=0)
stC = st.copy()
return st, stC
time_max = 80
dir = '/raid3/zl382/Data/20161225/fk_analysis/az_330.0dist_123.0/'
seislist = glob.glob(dir + '*PICKLE')
#Load data
st = Stream()
for i, seisname in enumerate(seislist):
seis = read(seisname, format='PICKLE')
st += seis.select(channel='BHT')
st[i].stats.coordinates = AttribDict({
'latitude': seis[0].stats['stla'],
'elevation': seis[0].stats['stelv'] / 1000,
'longitude': seis[0].stats['stlo']
})
st.resample(10)
# Execute array_processing
Sdifftime = seis[0].stats.traveltimes['Sdiff'] or seis[0].stats.traveltimes['S']
stime = st[0].stats['eventtime'] + Sdifftime - 40
etime = st[0].stats['eventtime'] + Sdifftime + 80
zerotime = st[0].stats['eventtime'] + Sdifftime
kwargs = dict(
# slowness grid: X min, X max, Y min, Y max, Slow Step
sll_x=-5.0,
slm_x=5.0,
sll_y=-5.0,
slm_y=5.0,
sl_s=0.05,
# sliding window properties
win_len=10.0,
# get list of all days and of unique days
days_all = np.array([
datetime.strptime(a[-8:], '%Y.%j').strftime('%Y.%m.%d') for a in dayfiles
])
days = np.unique(days_all)
for dy in days:
file_list = dayfiles[np.where(
days_all == dy)] # files for this day, all stations
st = Stream()
for fl in file_list:
if fl not in bad_files and os.stat(fl).st_size != 0:
st += read(fl)
if len(st) > 0:
# decimate or resample to 1Hz
if np.all([tr.stats.sampling_rate == 100 for tr in st]):
st.decimate(100, no_filter=True)
else:
st.resample(1.0, no_filter=True)
st.merge(method=1, fill_value=0) # make sure 1 trace per sta/comp
for tr in st: # rename channels to L* to match [edited] dataless
tr.stats.channel = 'L' + tr.stats.channel[1:]
# write miniseed
ofile = os.path.join(mseed_dir_out,'EN-%s.%s.%s.mseed' % \
(dy.split('.')[0],dy.split('.')[1],dy.split('.')[2]))
st.write(ofile, format='MSEED')
tr.data = np.abs(hilbert(tr.data))
tr.normalize()
if np.isnan(tr.data).any():
continue
strmacc1.append(tr.copy())
stalist1.append(tr.id)
reftime = fppdp(70, evdep1)
ctime = fppdp(dis1.delta, evdep1)
ctime = reftime - ctime
data = np.roll(tr.data, int(np.round(ctime * rsample)))
tr.data = data
print('finishing', time.time() - start)
strmacc1.resample(rsample)
if len(strmacc1) < 10:
print('small no. of traces:', len(strmacc1))
continue
refdismax = 70
nsta = len(strmacc1)
npts = strmacc1[0].stats.npts
depstack = np.zeros(npts, )
# print reflat,reflon,refdismax,len(strmacc1)
reftime = fppdp(refdismax, evdep1)
# data = abs(hilbert(strmacc1[0].data.copy()))
data = strmacc1[0].data.copy()
