def main(args=None):
if args is None:
# Run Input Parser
args = get_cleanspec_arguments()
# Load Database
# stdb>0.1.3
try:
db, stkeys = stdb.io.load_db(fname=args.indb, keys=args.stkeys)
# stdb=0.1.3
except:
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]
# Path where spectra are located
specpath = Path('SPECTRA') / stkey
if not specpath.is_dir():
raise(Exception("Path to "+str(specpath)+" doesn`t exist - aborting"))
# 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 - creating it")
avstpath.mkdir(parents=True)
# Path where plots will be saved
if args.saveplot:
plotpath = avstpath / '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("| {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 average spectra
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')
if fileavst.exists():
if not args.ovr:
print("* -> file "+str(fileavst)+" exists - continuing")
continue
# Containers for power and cross spectra
coh_all = []
ph_all = []
coh_12_all = []
coh_1Z_all = []
coh_1P_all = []
coh_2Z_all = []
coh_2P_all = []
coh_ZP_all = []
ph_12_all = []
ph_1Z_all = []
ph_1P_all = []
ph_2Z_all = []
ph_2P_all = []
ph_ZP_all = []
ad_12_all = []
ad_1Z_all = []
ad_1P_all = []
ad_2Z_all = []
ad_2P_all = []
ad_ZP_all = []
nwins = []
t1 = tstart
# Initialize StaNoise object
stanoise = StaNoise()
# Loop through each day withing time range
while t1 < tend:
year = str(t1.year).zfill(4)
jday = str(t1.julday).zfill(3)
tstamp = year+'.'+jday+'.'
filespec = specpath / (tstamp + 'spectra.pkl')
# Load file if it exists
if filespec.exists():
print()
print("*"*60)
print('* Calculating noise spectra for key ' +
stkey+' and day '+year+'.'+jday)
print("* -> file "+str(filespec)+" found - loading")
file = open(filespec, 'rb')
daynoise = pickle.load(file)
file.close()
stanoise += daynoise
else:
t1 += 3600.*24.
continue
coh_all.append(daynoise.rotation.coh)
ph_all.append(daynoise.rotation.ph)
# Coherence
coh_12_all.append(
utils.smooth(
utils.coherence(
daynoise.cross.c12,
daynoise.power.c11,
daynoise.power.c22), 50))
coh_1Z_all.append(
utils.smooth(
utils.coherence(
daynoise.cross.c1Z,
daynoise.power.c11,
daynoise.power.cZZ), 50))
coh_1P_all.append(
utils.smooth(
utils.coherence(
daynoise.cross.c1P,
daynoise.power.c11,
daynoise.power.cPP), 50))
coh_2Z_all.append(
utils.smooth(
utils.coherence(
daynoise.cross.c2Z,
daynoise.power.c22,
daynoise.power.cZZ), 50))
coh_2P_all.append(
utils.smooth(
utils.coherence(
daynoise.cross.c2P,
daynoise.power.c22,
daynoise.power.cPP), 50))
coh_ZP_all.append(
utils.smooth(
utils.coherence(
daynoise.cross.cZP,
daynoise.power.cZZ,
daynoise.power.cPP), 50))
# Phase
try:
ph_12_all.append(
180./np.pi*utils.phase(daynoise.cross.c12))
except:
ph_12_all.append(None)
try:
ph_1Z_all.append(
180./np.pi*utils.phase(daynoise.cross.c1Z))
except:
ph_1Z_all.append(None)
try:
ph_1P_all.append(
180./np.pi*utils.phase(daynoise.cross.c1P))
except:
ph_1P_all.append(None)
try:
ph_2Z_all.append(
180./np.pi*utils.phase(daynoise.cross.c2Z))
except:
ph_2Z_all.append(None)
try:
ph_2P_all.append(
180./np.pi*utils.phase(daynoise.cross.c2P))
except:
ph_2P_all.append(None)
try:
ph_ZP_all.append(
180./np.pi*utils.phase(daynoise.cross.cZP))
except:
ph_ZP_all.append(None)
# Admittance
ad_12_all.append(utils.smooth(utils.admittance(
daynoise.cross.c12, daynoise.power.c11), 50))
ad_1Z_all.append(utils.smooth(utils.admittance(
daynoise.cross.c1Z, daynoise.power.c11), 50))
ad_1P_all.append(utils.smooth(utils.admittance(
daynoise.cross.c1P, daynoise.power.c11), 50))
ad_2Z_all.append(utils.smooth(utils.admittance(
daynoise.cross.c2Z, daynoise.power.c22), 50))
ad_2P_all.append(utils.smooth(utils.admittance(
daynoise.cross.c2P, daynoise.power.c22), 50))
ad_ZP_all.append(utils.smooth(utils.admittance(
daynoise.cross.cZP, daynoise.power.cZZ), 50))
t1 += 3600.*24.
# Convert to numpy arrays
coh_all = np.array(coh_all)
ph_all = np.array(ph_all)
coh_12_all = np.array(coh_12_all)
coh_1Z_all = np.array(coh_1Z_all)
coh_1P_all = np.array(coh_1P_all)
coh_2Z_all = np.array(coh_2Z_all)
coh_2P_all = np.array(coh_2P_all)
coh_ZP_all = np.array(coh_ZP_all)
ph_12_all = np.array(ph_12_all)
ph_1Z_all = np.array(ph_1Z_all)
ph_1P_all = np.array(ph_1P_all)
ph_2Z_all = np.array(ph_2Z_all)
ph_2P_all = np.array(ph_2P_all)
ph_ZP_all = np.array(ph_ZP_all)
ad_12_all = np.array(ad_12_all)
ad_1Z_all = np.array(ad_1Z_all)
ad_1P_all = np.array(ad_1P_all)
ad_2Z_all = np.array(ad_2Z_all)
ad_2P_all = np.array(ad_2P_all)
ad_ZP_all = np.array(ad_ZP_all)
# Store transfer functions as objects for plotting
coh = Cross(coh_12_all, coh_1Z_all, coh_1P_all,
coh_2Z_all, coh_2P_all, coh_ZP_all)
ph = Cross(ph_12_all, ph_1Z_all, ph_1P_all,
ph_2Z_all, ph_2P_all, ph_ZP_all)
ad = Cross(ad_12_all, ad_1Z_all, ad_1P_all,
ad_2Z_all, ad_2P_all, ad_ZP_all)
# Quality control to identify outliers
stanoise.QC_sta_spectra(pd=args.pd, tol=args.tol, alpha=args.alpha,
fig_QC=args.fig_QC, debug=args.debug,
save=plotpath, form=args.form)
# Average spectra for good days
stanoise.average_sta_spectra(
fig_average=args.fig_average,
save=plotpath, form=args.form)
if args.fig_av_cross:
fname = stkey + '.' + 'av_coherence'
plot = plotting.fig_av_cross(stanoise.f, coh, stanoise.gooddays,
'Coherence', stanoise.ncomp, key=stkey, lw=0.5)
# if plotpath.is_dir():
if plotpath:
plot.savefig(str(plotpath / (fname + '.' + args.form)),
dpi=300, bbox_inches='tight', format=args.form)
else:
plot.show()
fname = stkey + '.' + 'av_admittance'
plot = plotting.fig_av_cross(stanoise.f, ad, stanoise.gooddays,
'Admittance', stanoise.ncomp, key=stkey, lw=0.5)
if plotpath:
plot.savefig(str(plotpath / (fname + '.' + args.form)),
dpi=300, bbox_inches='tight', format=args.form)
else:
plot.show()
fname = stkey + '.' + 'av_phase'
plot = plotting.fig_av_cross(stanoise.f, ph, stanoise.gooddays,
'Phase', stanoise.ncomp, key=stkey, marker=',', lw=0)
if plotpath:
plot.savefig(str(plotpath / (fname + '.' + args.form)),
dpi=300, bbox_inches='tight', format=args.form)
else:
plot.show()
if args.fig_coh_ph and stanoise.direc is not None:
fname = stkey + '.' + 'coh_ph'
plot = plotting.fig_coh_ph(coh_all, ph_all, stanoise.direc)
if plotpath:
plot.savefig(str(plotpath / (fname + '.' + args.form)),
dpi=300, bbox_inches='tight', format=args.form)
else:
plot.show()
# Save to file
stanoise.save(fileavst)
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.