def fig_average(f, power, bad, gooddays, ncomp, key='',
save=False, fname='', form='png'):
"""
Function to plot the averaged spectra (those qualified as 'good' in the
QC step). This function is used
in both the `obs_daily_spectra.py` or `obs_clean_spectra.py` scripts.
Parameters
----------
f : :mod:`~numpy.ndarray`
Frequency axis (in Hz)
power : :class:`~obstools.classes.Power`
Container for the Power spectra
bad : :class:`~obstools.classes.Power`
Container for the *bad* Power spectra
gooddays : List
List of booleans representing whether a window is good (True) or not (False)
ncomp : int
Number of components used in analysis (can be 2, 3 or 4)
key : str
String corresponding to the station key under analysis
"""
c11 = power.c11
c22 = power.c22
cZZ = power.cZZ
cPP = power.cPP
bc11 = bad.c11
bc22 = bad.c22
bcZZ = bad.cZZ
bcPP = bad.cPP
if ncomp == 2:
ccs = [cZZ, cPP]
bcs = [bcZZ, bcPP]
title = ['Average HZ, Station: '+key,
'Average HP, Station: '+key]
elif ncomp == 3:
ccs = [c11, c22, cZZ]
bcs = [bc11, bc22, bcZZ]
title = ['Average H1, Station: '+key,
'Average H2, Station: '+key,
'Average HZ, Station: '+key]
else:
ccs = [c11, c22, cZZ, cPP]
bcs = [bc11, bc22, bcZZ, bcPP]
title = ['Average H1, Station: '+key,
'Average H2, Station: '+key,
'Average HZ, Station: '+key,
'Average HP, Station: '+key]
plt.figure()
for i, (cc, bc) in enumerate(zip(ccs, bcs)):
ax = plt.subplot(ncomp, 1, i+1)
ax.semilogx(f, utils.smooth(np.log(cc), 50), 'k', lw=0.5)
if np.sum(~gooddays) > 0:
ax.semilogx(f, utils.smooth(np.log(bc), 50), 'r', lw=0.5)
ax.set_title(title[i], fontdict={'fontsize': 8})
if i == len(ccs)-1:
plt.xlabel('Frequency (Hz)', fontdict={'fontsize': 8})
plt.tight_layout()
# Save or show figure
if save:
plt.savefig(save + fname + '.' + form,
dpi=300, bbox_inches='tight', format=form)
else:
plt.show()
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)
def test_StaNoise():
args = test_args.test_get_dailyspec_arguments()
stanoise = test_classes.test_stanoise_demo()
# 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 = []
for dn in stanoise.daylist:
dn.QC_daily_spectra()
dn.average_daily_spectra()
coh_all.append(dn.rotation.coh)
ph_all.append(dn.rotation.ph)
# Coherence
coh_12_all.append(
utils.smooth(
utils.coherence(dn.cross.c12, dn.power.c11, dn.power.c22), 50))
coh_1Z_all.append(
utils.smooth(
utils.coherence(dn.cross.c1Z, dn.power.c11, dn.power.cZZ), 50))
coh_1P_all.append(
utils.smooth(
utils.coherence(dn.cross.c1P, dn.power.c11, dn.power.cPP), 50))
coh_2Z_all.append(
utils.smooth(
utils.coherence(dn.cross.c2Z, dn.power.c22, dn.power.cZZ), 50))
coh_2P_all.append(
utils.smooth(
utils.coherence(dn.cross.c2P, dn.power.c22, dn.power.cPP), 50))
coh_ZP_all.append(
utils.smooth(
utils.coherence(dn.cross.cZP, dn.power.cZZ, dn.power.cPP), 50))
# Phase
try:
ph_12_all.append(180. / np.pi * utils.phase(dn.cross.c12))
except:
ph_12_all.append(None)
try:
ph_1Z_all.append(180. / np.pi * utils.phase(dn.cross.c1Z))
except:
ph_1Z_all.append(None)
try:
ph_1P_all.append(180. / np.pi * utils.phase(dn.cross.c1P))
except:
ph_1P_all.append(None)
try:
ph_2Z_all.append(180. / np.pi * utils.phase(dn.cross.c2Z))
except:
ph_2Z_all.append(None)
try:
ph_2P_all.append(180. / np.pi * utils.phase(dn.cross.c2P))
except:
ph_2P_all.append(None)
try:
ph_ZP_all.append(180. / np.pi * utils.phase(dn.cross.cZP))
except:
ph_ZP_all.append(None)
# Admittance
ad_12_all.append(
utils.smooth(utils.admittance(dn.cross.c12, dn.power.c11), 50))
ad_1Z_all.append(
utils.smooth(utils.admittance(dn.cross.c1Z, dn.power.c11), 50))
ad_1P_all.append(
utils.smooth(utils.admittance(dn.cross.c1P, dn.power.c11), 50))
ad_2Z_all.append(
utils.smooth(utils.admittance(dn.cross.c2Z, dn.power.c22), 50))
ad_2P_all.append(
utils.smooth(utils.admittance(dn.cross.c2P, dn.power.c22), 50))
ad_ZP_all.append(
utils.smooth(utils.admittance(dn.cross.cZP, dn.power.cZZ), 50))
# 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)
stanoise.QC_sta_spectra(pd=args.pd,
tol=args.tol,
alpha=args.alpha,
fig_QC=True,
debug=False,
save='tmp',
form='png')
stanoise.average_sta_spectra(fig_average=True, save='tmp', form='png')
plot = plotting.fig_av_cross(stanoise.f,
coh,
stanoise.gooddays,
'Coherence',
stanoise.ncomp,
key='7D.M08A',
lw=0.5)
plot.close()
plot = plotting.fig_coh_ph(coh_all, ph_all, stanoise.direc)
plot.close()
return stanoise