def test_tfnoise_day_demo(tmp_path): daynoise = test_daynoise_demo() with pytest.raises(TypeError): assert TFNoise([]) with pytest.raises(Exception): TFNoise(objnoise=daynoise) daynoise.average_daily_spectra() tfnoise_day = TFNoise(daynoise) tfnoise_day.transfer_func() d = tmp_path / "tmp" tfnoise_day.save(d) return tfnoise_day
def main(): # Run Input Parser args = arguments.get_transfer_arguments() # Load Database db = stdb.io.load_db(fname=args.indb) # Construct station key loop allkeys = db.keys() sorted(allkeys) # Extract key subset if len(args.stkeys) > 0: stkeys = [] for skey in args.stkeys: stkeys.extend([s for s in allkeys if skey in s]) else: stkeys = db.keys() sorted(stkeys) # Loop over station keys for stkey in list(stkeys): # Extract station information from dictionary sta = db[stkey] if not args.skip_daily: # Path where spectra are located specpath = Path('SPECTRA') / stkey if not specpath.is_dir(): raise (Exception("Path to " + str(specpath) + " doesn't exist - aborting")) if not args.skip_clean: # Path where average spectra will be saved avstpath = Path('AVG_STA') / stkey if not avstpath.is_dir(): print("Path to " + str(avstpath) + " doesn't exist - skipping cleaned station spectra") args.skip_clean = True if args.skip_daily and args.skip_clean: print("skipping both daily and clean spectra") continue # Path where transfer functions will be located tfpath = Path('TF_STA') / stkey if not tfpath.is_dir(): print("Path to " + str(tfpath) + " doesn't exist - creating it") tfpath.mkdir(parents=True) # Path where plots will be saved if args.saveplot: plotpath = tfpath / 'PLOTS' if not plotpath.is_dir(): plotpath.mkdir(parents=True) else: plotpath = False # Get catalogue search start time if args.startT is None: tstart = sta.startdate else: tstart = args.startT # Get catalogue search end time if args.endT is None: tend = sta.enddate else: tend = args.endT if tstart > sta.enddate or tend < sta.startdate: continue # Temporary print locations tlocs = sta.location if len(tlocs) == 0: tlocs = [''] for il in range(0, len(tlocs)): if len(tlocs[il]) == 0: tlocs[il] = "--" sta.location = tlocs # Update Display print(" ") print(" ") print("|===============================================|") print("|===============================================|") print("| {0:>8s} |".format( sta.station)) print("|===============================================|") print("|===============================================|") print("| Station: {0:>2s}.{1:5s} |".format( sta.network, sta.station)) print("| Channel: {0:2s}; Locations: {1:15s} |".format( sta.channel, ",".join(tlocs))) print("| Lon: {0:7.2f}; Lat: {1:6.2f} |".format( sta.longitude, sta.latitude)) print("| Start time: {0:19s} |".format( sta.startdate.strftime("%Y-%m-%d %H:%M:%S"))) print("| End time: {0:19s} |".format( sta.enddate.strftime("%Y-%m-%d %H:%M:%S"))) print("|-----------------------------------------------|") # Filename for output transfer functions dstart = str(tstart.year).zfill(4) + '.' + str( tstart.julday).zfill(3) + '-' dend = str(tend.year).zfill(4) + '.' + str(tend.julday).zfill(3) + '.' fileavst = avstpath / (dstart + dend + 'avg_sta.pkl') # Find all files in directories p = specpath.glob('*spectra.pkl') spectra_files = [x for x in p if x.is_file()] if not args.skip_clean: p = avstpath.glob('*avg_sta.pkl') average_files = [x for x in p if x.is_file()] if not args.skip_daily: day_transfer_functions = [] # Cycle through available files for filespec in spectra_files: year = filespec.name.split('.')[0] jday = filespec.name.split('.')[1] print() print("*********************************************" + "***************") print("* Calculating transfer functions for key " + stkey + " and day " + year + "." + jday) tstamp = year + '.' + jday + '.' filename = tfpath / (tstamp + 'transfunc.pkl') # Load file file = open(filespec, 'rb') daynoise = pickle.load(file) file.close() # Load spectra into TFNoise object daytransfer = TFNoise(daynoise) # Calculate the transfer functions daytransfer.transfer_func() # Store the frequency axis f = daytransfer.f # Append to list of transfer functions day_transfer_functions.append(daytransfer.transfunc) # Save daily transfer functions to file daytransfer.save(filename) if not args.skip_clean: # Cycle through available files for fileavst in average_files: name = fileavst.name.split('avg_sta') print() print("*********************************************" + "***************") print("* Calculating transfer functions for key " + stkey + " and range " + name[0]) filename = tfpath / (name[0] + 'transfunc.pkl') # Load file file = open(fileavst, 'rb') stanoise = pickle.load(file) file.close() # Load spectra into TFNoise object - no Rotation object # for station averages rotation = Rotation(None, None, None) statransfer = TFNoise(stanoise) # Calculate the transfer functions statransfer.transfer_func() # Store the frequency axis f = statransfer.f # Extract the transfer functions sta_transfer_functions = statransfer.transfunc # Save average transfer functions to file statransfer.save(filename) if args.fig_TF: fname = stkey + '.' + 'transfer_functions' plot = plotting.fig_TF(f, day_transfer_functions, daynoise.tf_list, sta_transfer_functions, stanoise.tf_list, skey=stkey) if plotpath: plot.savefig(plotpath / (fname + '.' + args.form), dpi=300, bbox_inches='tight', format=args.form) else: plot.show()
def test_tfnoise_sta_demo(tmp_path): stanoise = test_sta_average(tmp_path) tfnoise_sta = TFNoise(stanoise) tfnoise_sta.transfer_func() return tfnoise_sta
def transfer_func(self): """compute daily transfer function """ targetdt = 1. / self.sps oyear = self.otime.year omonth = self.otime.month oday = self.otime.day ohour = self.otime.hour omin = self.otime.minute osec = self.otime.second label = '%d_%s_%d_%d_%d_%d' % (oyear, monthdict[omonth], oday, ohour, omin, osec) self.eventdir = self.datadir + '/' + label self.outeventdir = self.outdir + '/' + label self.label = label chan_type = None # load SAC data for chtype in self.chan_rank: fname1 = self.eventdir + '/%s_%sH1.SAC' % (self.staid, chtype) fname2 = self.eventdir + '/%s_%sH2.SAC' % (self.staid, chtype) fnamez = self.eventdir + '/%s_%sHZ.SAC' % (self.staid, chtype) fnamep = self.eventdir + '/%s_%sDH.SAC' % (self.staid, chtype) if os.path.isfile(fname1) and os.path.isfile(fname1) and \ os.path.isfile(fnamez) and os.path.isfile(fnamep): chan_type = chtype break if chan_type is None: return 0 self.chan_type = chan_type fname1 = self.eventdir + '/%s_%sH1.SAC' % (self.staid, chan_type) fname2 = self.eventdir + '/%s_%sH2.SAC' % (self.staid, chan_type) fnamez = self.eventdir + '/%s_%sHZ.SAC' % (self.staid, chan_type) fnamep = self.eventdir + '/%s_%sDH.SAC' % (self.staid, chan_type) self.sth = obspy.read(fname1) self.sth += obspy.read(fname2) self.sth += obspy.read(fnamez) self.stp = obspy.read(fnamep) # if abs(self.sth[0].stats.delta - targetdt) > 1e-3 or abs(self.sth[1].stats.delta - targetdt) > 1e-3 or \ abs(self.sth[2].stats.delta - targetdt) > 1e-3 or abs(self.stp[0].stats.delta - targetdt) > 1e-3: raise ValueError('!!! CHECK fs :' + self.staid) else: self.sth[0].stats.delta = targetdt self.sth[1].stats.delta = targetdt self.sth[2].stats.delta = targetdt self.stp[0].stats.delta = targetdt stime_event = self.sth[-1].stats.starttime etime_event = self.sth[-1].stats.endtime self.sth.trim(starttime=stime_event, endtime=etime_event, pad=True, nearest_sample=True, fill_value=0.) self.stp.trim(starttime=stime_event, endtime=etime_event, pad=True, nearest_sample=True, fill_value=0.) self.window = self.sth[-1].stats.npts / self.sps # trim data # load daily noise data daystr = '%d.%s.%d.%s' % (self.otime.year, monthdict[self.otime.month], self.otime.day, self.staid) dfname1 = self.daydir + '/ft_%s.%sH1.SAC' % (daystr, chan_type) dfname2 = self.daydir + '/ft_%s.%sH2.SAC' % (daystr, chan_type) dfnamez = self.daydir + '/ft_%s.%sHZ.SAC' % (daystr, chan_type) dfnamep = self.daydir + '/ft_%s.%sDH.SAC' % (daystr, chan_type) if not( os.path.isfile(dfname1) and os.path.isfile(dfname2) and \ os.path.isfile(dfnamez) and os.path.isfile(dfnamep)): return 0 tr1 = obspy.read(dfname1)[0] tr2 = obspy.read(dfname2)[0] trZ = obspy.read(dfnamez)[0] trP = obspy.read(dfnamep)[0] if abs(tr1.stats.delta - targetdt) > 1e-3 or abs(tr2.stats.delta - targetdt) > 1e-3 or \ abs(trZ.stats.delta - targetdt) > 1e-3 or abs(trP.stats.delta - targetdt) > 1e-3: raise ValueError('!!! CHECK fs :' + self.staid) else: tr1.stats.delta = targetdt tr2.stats.delta = targetdt trP.stats.delta = targetdt trZ.stats.delta = targetdt # trim data slidind_wlength = self.window - int( self.overlap * self.window) * tr1.stats.delta stime_noise = tr1.stats.starttime newtime = np.floor((tr1.stats.endtime - stime_noise) / slidind_wlength) * slidind_wlength tr1.trim(starttime=stime_noise, endtime=stime_noise + newtime) tr2.trim(starttime=stime_noise, endtime=stime_noise + newtime) trZ.trim(starttime=stime_noise, endtime=stime_noise + newtime) trP.trim(starttime=stime_noise, endtime=stime_noise + newtime) if np.all(trP.data == 0.) and not (np.all(tr1.data == 0.) or np.all(tr2.data == 0.)): self.daynoise = DayNoise(tr1=tr1, tr2=tr2, trZ=trZ, trP=obspy.Trace(), overlap=self.overlap, window=self.window) self.out_dtype = 'Z2-1' elif (np.all(tr1.data == 0.) or np.all(tr2.data == 0.)) and (not np.all(trP.data == 0.)): self.daynoise = DayNoise(tr1=obspy.Trace(), tr2=obspy.Trace(), trZ=trZ, trP=trP, overlap=self.overlap, window=self.window) self.out_dtype = 'ZP' elif (not (np.all(tr1.data == 0.) or np.all(tr2.data == 0.))) and ( not np.all(trP.data == 0.)): self.daynoise = DayNoise(tr1=tr1, tr2=tr2, trZ=trZ, trP=trP, overlap=self.overlap, window=self.window) self.out_dtype = 'ZP-21' else: return 0 # self.daynoise.QC_daily_spectra() # self.daynoise.average_daily_spectra() # self.tfnoise = TFNoise(self.daynoise) # self.tfnoise.transfer_func() try: self.daynoise.QC_daily_spectra() self.daynoise.average_daily_spectra() self.tfnoise = TFNoise(self.daynoise) self.tfnoise.transfer_func() except: return -1 return 1
class atacr_event_sta(object): def __init__(self, inv, datadir, outdir, noisedir, otime, overlap=0.3, chan_rank=['L', 'H', 'B'], sps=1.): network = inv.networks[0] station = network[0] channel = station[0] self.stdb_inv = stdb.StDbElement(network = network.code, station = station.code, channel = channel.code[:2],\ location = channel.location_code, latitude = station.latitude, longitude = station.longitude,\ elevation = station.elevation, polarity=1., azcorr=0., startdate = station.start_date,\ enddate = station.end_date, restricted_status = station.restricted_status) self.datadir = datadir self.outdir = outdir self.noisedir = noisedir self.otime = otime self.overlap = overlap self.staid = network.code + '.' + station.code self.chan_rank = chan_rank self.stlo = station.longitude self.stla = station.latitude self.monthdir = self.noisedir + '/%04d.%s' % ( self.otime.year, monthdict[self.otime.month]) self.daydir = self.monthdir + '/%d.%s.%d' % ( self.otime.year, monthdict[self.otime.month], self.otime.day) self.sps = sps return def transfer_func(self): """compute daily transfer function """ targetdt = 1. / self.sps oyear = self.otime.year omonth = self.otime.month oday = self.otime.day ohour = self.otime.hour omin = self.otime.minute osec = self.otime.second label = '%d_%s_%d_%d_%d_%d' % (oyear, monthdict[omonth], oday, ohour, omin, osec) self.eventdir = self.datadir + '/' + label self.outeventdir = self.outdir + '/' + label self.label = label chan_type = None # load SAC data for chtype in self.chan_rank: fname1 = self.eventdir + '/%s_%sH1.SAC' % (self.staid, chtype) fname2 = self.eventdir + '/%s_%sH2.SAC' % (self.staid, chtype) fnamez = self.eventdir + '/%s_%sHZ.SAC' % (self.staid, chtype) fnamep = self.eventdir + '/%s_%sDH.SAC' % (self.staid, chtype) if os.path.isfile(fname1) and os.path.isfile(fname1) and \ os.path.isfile(fnamez) and os.path.isfile(fnamep): chan_type = chtype break if chan_type is None: return 0 self.chan_type = chan_type fname1 = self.eventdir + '/%s_%sH1.SAC' % (self.staid, chan_type) fname2 = self.eventdir + '/%s_%sH2.SAC' % (self.staid, chan_type) fnamez = self.eventdir + '/%s_%sHZ.SAC' % (self.staid, chan_type) fnamep = self.eventdir + '/%s_%sDH.SAC' % (self.staid, chan_type) self.sth = obspy.read(fname1) self.sth += obspy.read(fname2) self.sth += obspy.read(fnamez) self.stp = obspy.read(fnamep) # if abs(self.sth[0].stats.delta - targetdt) > 1e-3 or abs(self.sth[1].stats.delta - targetdt) > 1e-3 or \ abs(self.sth[2].stats.delta - targetdt) > 1e-3 or abs(self.stp[0].stats.delta - targetdt) > 1e-3: raise ValueError('!!! CHECK fs :' + self.staid) else: self.sth[0].stats.delta = targetdt self.sth[1].stats.delta = targetdt self.sth[2].stats.delta = targetdt self.stp[0].stats.delta = targetdt stime_event = self.sth[-1].stats.starttime etime_event = self.sth[-1].stats.endtime self.sth.trim(starttime=stime_event, endtime=etime_event, pad=True, nearest_sample=True, fill_value=0.) self.stp.trim(starttime=stime_event, endtime=etime_event, pad=True, nearest_sample=True, fill_value=0.) self.window = self.sth[-1].stats.npts / self.sps # trim data # load daily noise data daystr = '%d.%s.%d.%s' % (self.otime.year, monthdict[self.otime.month], self.otime.day, self.staid) dfname1 = self.daydir + '/ft_%s.%sH1.SAC' % (daystr, chan_type) dfname2 = self.daydir + '/ft_%s.%sH2.SAC' % (daystr, chan_type) dfnamez = self.daydir + '/ft_%s.%sHZ.SAC' % (daystr, chan_type) dfnamep = self.daydir + '/ft_%s.%sDH.SAC' % (daystr, chan_type) if not( os.path.isfile(dfname1) and os.path.isfile(dfname2) and \ os.path.isfile(dfnamez) and os.path.isfile(dfnamep)): return 0 tr1 = obspy.read(dfname1)[0] tr2 = obspy.read(dfname2)[0] trZ = obspy.read(dfnamez)[0] trP = obspy.read(dfnamep)[0] if abs(tr1.stats.delta - targetdt) > 1e-3 or abs(tr2.stats.delta - targetdt) > 1e-3 or \ abs(trZ.stats.delta - targetdt) > 1e-3 or abs(trP.stats.delta - targetdt) > 1e-3: raise ValueError('!!! CHECK fs :' + self.staid) else: tr1.stats.delta = targetdt tr2.stats.delta = targetdt trP.stats.delta = targetdt trZ.stats.delta = targetdt # trim data slidind_wlength = self.window - int( self.overlap * self.window) * tr1.stats.delta stime_noise = tr1.stats.starttime newtime = np.floor((tr1.stats.endtime - stime_noise) / slidind_wlength) * slidind_wlength tr1.trim(starttime=stime_noise, endtime=stime_noise + newtime) tr2.trim(starttime=stime_noise, endtime=stime_noise + newtime) trZ.trim(starttime=stime_noise, endtime=stime_noise + newtime) trP.trim(starttime=stime_noise, endtime=stime_noise + newtime) if np.all(trP.data == 0.) and not (np.all(tr1.data == 0.) or np.all(tr2.data == 0.)): self.daynoise = DayNoise(tr1=tr1, tr2=tr2, trZ=trZ, trP=obspy.Trace(), overlap=self.overlap, window=self.window) self.out_dtype = 'Z2-1' elif (np.all(tr1.data == 0.) or np.all(tr2.data == 0.)) and (not np.all(trP.data == 0.)): self.daynoise = DayNoise(tr1=obspy.Trace(), tr2=obspy.Trace(), trZ=trZ, trP=trP, overlap=self.overlap, window=self.window) self.out_dtype = 'ZP' elif (not (np.all(tr1.data == 0.) or np.all(tr2.data == 0.))) and ( not np.all(trP.data == 0.)): self.daynoise = DayNoise(tr1=tr1, tr2=tr2, trZ=trZ, trP=trP, overlap=self.overlap, window=self.window) self.out_dtype = 'ZP-21' else: return 0 # self.daynoise.QC_daily_spectra() # self.daynoise.average_daily_spectra() # self.tfnoise = TFNoise(self.daynoise) # self.tfnoise.transfer_func() try: self.daynoise.QC_daily_spectra() self.daynoise.average_daily_spectra() self.tfnoise = TFNoise(self.daynoise) self.tfnoise.transfer_func() except: return -1 return 1 def correct(self): """compute monthly transfer function """ tmptime = self.sth[-1].stats.starttime tstamp = str(tmptime.year).zfill(4)+'.' + \ str(tmptime.julday).zfill(3)+'.' tstamp = tstamp + str(tmptime.hour).zfill(2) + \ '.'+str(tmptime.minute).zfill(2) eventstream = EventStream( sta = self.stdb_inv, sth = self.sth, stp = self.stp,\ tstamp = tstamp, lat = self.stla, lon = self.stlo, time = tmptime,\ window = self.window, sampling_rate = 1., ncomp = 4) eventstream.correct_data(self.tfnoise) # save data if not os.path.isdir(self.outeventdir): os.makedirs(self.outeventdir) outTrZ = (self.sth.select(channel='??Z')[0]).copy() outTrZ.data = eventstream.correct[self.out_dtype].copy() outfnameZ = self.outeventdir + '/%s_%sHZ.SAC' % (self.staid, self.chan_type) if os.path.isfile(outfnameZ): shutil.copyfile(src=outfnameZ, dst=outfnameZ + '_old') os.remove(outfnameZ) outTrZ.write(outfnameZ, format='SAC')
def test_tfnoise_day_demo(): daynoise = test_day_average() tfnoise_day = TFNoise(daynoise) tfnoise_day.transfer_func() return tfnoise_day
def transfer_func(self): """compute monthly transfer function """ targetdt = 1./self.sps stime = obspy.UTCDateTime('%04d%02d01' %(self.year, self.month)) monthdir = self.monthdir if not os.path.isdir(monthdir): return False chan_type = None Nday = 0 while( (stime.year == self.year) and (stime.month == self.month)): daydir = monthdir+'/%d.%s.%d' %(self.year, monthdict[self.month], stime.day) if not os.path.isdir(daydir): stime += 86400. continue fpattern= daydir+'/ft_%d.%s.%d.%s' %(self.year, monthdict[self.month], stime.day, self.staid) if chan_type is None: for chtype in self.chan_rank: fname1 = fpattern+'.%sH1.SAC' %chtype fname2 = fpattern+'.%sH2.SAC' %chtype fnamez = fpattern+'.%sHZ.SAC' %chtype fnamep = fpattern+'.%sDH.SAC' %chtype if os.path.isfile(fname1) and os.path.isfile(fname1) and \ os.path.isfile(fnamez) and os.path.isfile(fnamep): chan_type = chtype break if chan_type is None: stime += 86400. continue fname1 = fpattern+'.%sH1.SAC' %chan_type fname2 = fpattern+'.%sH2.SAC' %chan_type fnamez = fpattern+'.%sHZ.SAC' %chan_type fnamep = fpattern+'.%sDH.SAC' %chan_type if not (os.path.isfile(fname1) and os.path.isfile(fname1) and \ os.path.isfile(fnamez) and os.path.isfile(fnamep)): stime += 86400. continue tr1 = obspy.read(fname1)[0] stimetr = tr1.stats.starttime tr2 = obspy.read(fname2)[0] trZ = obspy.read(fnamez)[0] trP = obspy.read(fnamep)[0] if abs(tr1.stats.delta - targetdt) > 1e-3 or abs(tr2.stats.delta - targetdt) > 1e-3 or \ abs(trZ.stats.delta - targetdt) > 1e-3 or abs(trP.stats.delta - targetdt) > 1e-3: raise ValueError('!!! CHECK fs :'+ self.staid) else: tr1.stats.delta = targetdt tr2.stats.delta = targetdt trP.stats.delta = targetdt trZ.stats.delta = targetdt # # # if np.all(tr1.data == 0.) or np.all(tr2.data == 0.) or np.all(trZ.data == 0.) or np.all(trP.data == 0.): # # # stime += 86400. # # # continue tr1.trim(starttime = stimetr, endtime = stimetr + 8400.*10-1) tr2.trim(starttime = stimetr, endtime = stimetr + 8400.*10-1) trZ.trim(starttime = stimetr, endtime = stimetr + 8400.*10-1) trP.trim(starttime = stimetr, endtime = stimetr + 8400.*10-1) # # # print (self.staid) if np.all(trP.data == 0.) and not (np.all(tr1.data == 0.) or np.all(tr2.data == 0.)): self.stanoise += DayNoise(tr1=tr1, tr2=tr2, trZ=trZ, trP=obspy.Trace(), overlap=self.overlap, window = self.window) self.out_dtype = 'Z2-1' elif (np.all(tr1.data == 0.) or np.all(tr2.data == 0.)) and (not np.all(trP.data == 0.)): self.stanoise += DayNoise(tr1=obspy.Trace(), tr2=obspy.Trace(), trZ=trZ, trP=trP, overlap=self.overlap, window = self.window) self.out_dtype = 'ZP' elif (not (np.all(tr1.data == 0.) or np.all(tr2.data == 0.))) and (not np.all(trP.data == 0.)): self.stanoise += DayNoise(tr1=tr1, tr2=tr2, trZ=trZ, trP=trP, overlap=self.overlap, window = self.window) self.out_dtype = 'ZP-21' else: stime += 86400. continue stime += 86400. Nday += 1 if Nday <= 1: return False self.stanoise.QC_sta_spectra() self.stanoise.average_sta_spectra() self.tfnoise= TFNoise(self.stanoise) self.tfnoise.transfer_func() return True
class atacr_monthly_sta(object): def __init__(self, inv, datadir, outdir, year, month, overlap = 0.5, window = 21000., chan_rank = ['L', 'H', 'B'], sps = 1.): network = inv.networks[0] station = network[0] channel = station[0] self.stdb_inv = stdb.StDbElement(network = network.code, station = station.code, channel = channel.code[:2],\ location = channel.location_code, latitude = station.latitude, longitude = station.longitude,\ elevation = station.elevation, polarity=1., azcorr=0., startdate = station.start_date,\ enddate = station.end_date, restricted_status = station.restricted_status) self.datadir = datadir self.outdir = outdir self.year = year self.month = month self.overlap = overlap self.window = window self.staid = network.code+'.'+station.code self.chan_rank = chan_rank self.stanoise = StaNoise() self.stlo = station.longitude self.stla = station.latitude self.monthdir = self.datadir + '/%04d.%s' %(self.year, monthdict[self.month]) self.sps = sps return def transfer_func(self): """compute monthly transfer function """ targetdt = 1./self.sps stime = obspy.UTCDateTime('%04d%02d01' %(self.year, self.month)) monthdir = self.monthdir if not os.path.isdir(monthdir): return False chan_type = None Nday = 0 while( (stime.year == self.year) and (stime.month == self.month)): daydir = monthdir+'/%d.%s.%d' %(self.year, monthdict[self.month], stime.day) if not os.path.isdir(daydir): stime += 86400. continue fpattern= daydir+'/ft_%d.%s.%d.%s' %(self.year, monthdict[self.month], stime.day, self.staid) if chan_type is None: for chtype in self.chan_rank: fname1 = fpattern+'.%sH1.SAC' %chtype fname2 = fpattern+'.%sH2.SAC' %chtype fnamez = fpattern+'.%sHZ.SAC' %chtype fnamep = fpattern+'.%sDH.SAC' %chtype if os.path.isfile(fname1) and os.path.isfile(fname1) and \ os.path.isfile(fnamez) and os.path.isfile(fnamep): chan_type = chtype break if chan_type is None: stime += 86400. continue fname1 = fpattern+'.%sH1.SAC' %chan_type fname2 = fpattern+'.%sH2.SAC' %chan_type fnamez = fpattern+'.%sHZ.SAC' %chan_type fnamep = fpattern+'.%sDH.SAC' %chan_type if not (os.path.isfile(fname1) and os.path.isfile(fname1) and \ os.path.isfile(fnamez) and os.path.isfile(fnamep)): stime += 86400. continue tr1 = obspy.read(fname1)[0] stimetr = tr1.stats.starttime tr2 = obspy.read(fname2)[0] trZ = obspy.read(fnamez)[0] trP = obspy.read(fnamep)[0] if abs(tr1.stats.delta - targetdt) > 1e-3 or abs(tr2.stats.delta - targetdt) > 1e-3 or \ abs(trZ.stats.delta - targetdt) > 1e-3 or abs(trP.stats.delta - targetdt) > 1e-3: raise ValueError('!!! CHECK fs :'+ self.staid) else: tr1.stats.delta = targetdt tr2.stats.delta = targetdt trP.stats.delta = targetdt trZ.stats.delta = targetdt # # # if np.all(tr1.data == 0.) or np.all(tr2.data == 0.) or np.all(trZ.data == 0.) or np.all(trP.data == 0.): # # # stime += 86400. # # # continue tr1.trim(starttime = stimetr, endtime = stimetr + 8400.*10-1) tr2.trim(starttime = stimetr, endtime = stimetr + 8400.*10-1) trZ.trim(starttime = stimetr, endtime = stimetr + 8400.*10-1) trP.trim(starttime = stimetr, endtime = stimetr + 8400.*10-1) # # # print (self.staid) if np.all(trP.data == 0.) and not (np.all(tr1.data == 0.) or np.all(tr2.data == 0.)): self.stanoise += DayNoise(tr1=tr1, tr2=tr2, trZ=trZ, trP=obspy.Trace(), overlap=self.overlap, window = self.window) self.out_dtype = 'Z2-1' elif (np.all(tr1.data == 0.) or np.all(tr2.data == 0.)) and (not np.all(trP.data == 0.)): self.stanoise += DayNoise(tr1=obspy.Trace(), tr2=obspy.Trace(), trZ=trZ, trP=trP, overlap=self.overlap, window = self.window) self.out_dtype = 'ZP' elif (not (np.all(tr1.data == 0.) or np.all(tr2.data == 0.))) and (not np.all(trP.data == 0.)): self.stanoise += DayNoise(tr1=tr1, tr2=tr2, trZ=trZ, trP=trP, overlap=self.overlap, window = self.window) self.out_dtype = 'ZP-21' else: stime += 86400. continue stime += 86400. Nday += 1 if Nday <= 1: return False self.stanoise.QC_sta_spectra() self.stanoise.average_sta_spectra() self.tfnoise= TFNoise(self.stanoise) self.tfnoise.transfer_func() return True def correct(self): """compute monthly transfer function """ targetdt = 1./self.sps stime = obspy.UTCDateTime('%04d%02d01' %(self.year, self.month)) monthdir = self.monthdir omonthdir = self.outdir + '/%04d.%s' %(self.year, monthdict[self.month]) if not os.path.isdir(monthdir): return False chan_type = None while( (stime.year == self.year) and (stime.month == self.month)): daydir = monthdir+'/%d.%s.%d' %(self.year, monthdict[self.month], stime.day) fpattern = daydir+'/ft_%d.%s.%d.%s' %(self.year, monthdict[self.month], stime.day, self.staid) odaydir = omonthdir+'/%d.%s.%d' %(self.year, monthdict[self.month], stime.day) if not os.path.isdir(odaydir): os.makedirs(odaydir) if chan_type is None: for chtype in self.chan_rank: fname1 = fpattern+'.%sH1.SAC' %chtype fname2 = fpattern+'.%sH2.SAC' %chtype fnamez = fpattern+'.%sHZ.SAC' %chtype fnamep = fpattern+'.%sDH.SAC' %chtype if os.path.isfile(fname1) and os.path.isfile(fname2) and \ os.path.isfile(fnamez) and os.path.isfile(fnamep): chan_type = chtype break if chan_type is None: stime += 86400. continue fname1 = fpattern+'.%sH1.SAC' %chan_type fname2 = fpattern+'.%sH2.SAC' %chan_type fnamez = fpattern+'.%sHZ.SAC' %chan_type fnamep = fpattern+'.%sDH.SAC' %chan_type if not (os.path.isfile(fname1) and os.path.isfile(fname2) and \ os.path.isfile(fnamez) and os.path.isfile(fnamep)): stime += 86400. continue tr1 = obspy.read(fname1)[0] stimetr = tr1.stats.starttime tr2 = obspy.read(fname2)[0] trZ = obspy.read(fnamez)[0] trP = obspy.read(fnamep)[0] if (np.all(tr1.data == 0.) or np.all(tr2.data == 0.)) and np.all(trP.data == 0.): stime += 86400. continue if abs(tr1.stats.delta - targetdt) > 1e-3 or abs(tr2.stats.delta - targetdt) > 1e-3 or \ abs(trZ.stats.delta - targetdt) > 1e-3 or abs(trP.stats.delta - targetdt) > 1e-3: raise ValueError('!!! CHECK fs :'+ self.staid) else: tr1.stats.delta = targetdt tr2.stats.delta = targetdt trP.stats.delta = targetdt trZ.stats.delta = targetdt outfnameZ = odaydir+'/ft_%d.%s.%d.%s.%sHZ.SAC' %(self.year, monthdict[self.month], stime.day, self.staid, chan_type) # sliding window raw data StreamZ = obspy.Stream() overlap = 0.99 for tmptr in trZ.slide(window_length = self.window-1, step = int((self.window-1)*overlap)): # print (tmptr.stats.npts) StreamZ += tmptr.copy() Stream1 = obspy.Stream() for tmptr in tr1.slide(window_length = self.window-1, step = int((self.window-1)*overlap)): Stream1 += tmptr.copy() Stream2 = obspy.Stream() for tmptr in tr2.slide(window_length = self.window-1, step = int((self.window-1)*overlap)): Stream2 += tmptr.copy() StreamP = obspy.Stream() for tmptr in trP.slide(window_length = self.window-1, step = int((self.window-1)*overlap)): StreamP += tmptr.copy() # remove tilt and compliance outStreamZ = obspy.Stream() Ntraces = len(StreamZ) for itr in range(Ntraces): sth = obspy.Stream() if not (np.all(Stream1[itr].data == 0.) or np.all(Stream1[itr].data == 0.)): sth += Stream1[itr] sth += Stream2[itr] sth += StreamZ[itr] stp = obspy.Stream() if not np.all(StreamP[itr].data == 0.): stp += StreamP[itr] tmptime = StreamZ[itr].stats.starttime tstamp = str(tmptime.year).zfill(4)+'.' + \ str(tmptime.julday).zfill(3)+'.' tstamp = tstamp + str(tmptime.hour).zfill(2) + \ '.'+str(tmptime.minute).zfill(2) if self.out_dtype == 'ZP': ncomp = 2 elif self.out_dtype == 'Z2-1': ncomp = 3 elif self.out_dtype == 'ZP-21': ncomp = 4 eventstream = EventStream( sta = self.stdb_inv, sth = sth, stp = stp,\ tstamp = tstamp, lat = self.stla, lon = self.stlo, time = tmptime,\ window = self.window, sampling_rate = 1., ncomp = ncomp) eventstream.correct_data(self.tfnoise) tmptr = StreamZ[itr].copy() tmptr.data = eventstream.correct[self.out_dtype].copy() outStreamZ += tmptr # outStreamZ.data = # merge data outStreamZ.merge(method = 1, fill_value = 'interpolate', interpolation_samples=2) outTrZ = outStreamZ[0] if os.path.isfile(outfnameZ): shutil.copyfile(src = outfnameZ, dst = outfnameZ+'_old') os.remove(outfnameZ) outTrZ.write(outfnameZ, format = 'SAC') stime += 86400.