def make_shakemap_slice(home, project_name, run_name, time_epi, GF_list, dt,
tmax):
'''
Make xyz files with current ground velocity
'''
from numpy import genfromtxt, arange, sqrt, zeros, where, c_, savetxt
from string import rjust
from obspy import read
from mudpy.forward import lowpass
t = arange(0, tmax, dt)
fcorner = 0.5
sta = genfromtxt(home + project_name + '/data/station_info/' + GF_list,
usecols=0,
dtype='S')
lonlat = genfromtxt(home + project_name + '/data/station_info/' + GF_list,
usecols=[1, 2])
for ksta in range(len(sta)):
n = read(home + project_name + '/output/forward_models/' + run_name +
'.' + sta[ksta] + '.vel.n')
e = read(home + project_name + '/output/forward_models/' + run_name +
'.' + sta[ksta] + '.vel.n')
n[0].data = lowpass(n[0].data, fcorner, 1. / n[0].stats.delta, 2)
e[0].data = lowpass(n[0].data, fcorner, 1. / e[0].stats.delta, 2)
if ksta == 0:
h = n.copy()
else:
h += n[0].copy()
h[ksta].data = sqrt(n[0].data**2 + e[0].data**2)
h[ksta].trim(starttime=time_epi)
print h[ksta].stats.starttime
vout = zeros(len(lonlat))
maxv = 0
for kt in range(len(t)):
for ksta in range(len(sta)):
i = where(h[ksta].times() == t[kt])[0]
vout[ksta] = h[ksta].data[i]
if vout.max() > maxv:
maxv = vout.max()
out = c_[lonlat, vout]
num = rjust(str(kt), 4, '0')
print num
savetxt(home + project_name + '/analysis/shake/' + num + '.shake',
out,
fmt='%10.6f\t%10.6f\t%10.4f')
print 'Max velocity was ' + str(maxv) + 'm/s'
def make_shakemap_slice(home,project_name,run_name,time_epi,GF_list,dt,tmax):
'''
Make xyz files with current ground velocity
'''
from numpy import genfromtxt,arange,sqrt,zeros,where,c_,savetxt
from string import rjust
from obspy import read
from mudpy.forward import lowpass
t=arange(0,tmax,dt)
fcorner=0.5
sta=genfromtxt(home+project_name+'/data/station_info/'+GF_list,usecols=0,dtype='S')
lonlat=genfromtxt(home+project_name+'/data/station_info/'+GF_list,usecols=[1,2])
for ksta in range(len(sta)):
n=read(home+project_name+'/output/forward_models/'+run_name+'.'+sta[ksta]+'.vel.n')
e=read(home+project_name+'/output/forward_models/'+run_name+'.'+sta[ksta]+'.vel.n')
n[0].data=lowpass(n[0].data,fcorner,1./n[0].stats.delta,2)
e[0].data=lowpass(n[0].data,fcorner,1./e[0].stats.delta,2)
if ksta==0:
h=n.copy()
else:
h+=n[0].copy()
h[ksta].data=sqrt(n[0].data**2+e[0].data**2)
h[ksta].trim(starttime=time_epi)
print h[ksta].stats.starttime
vout=zeros(len(lonlat))
maxv=0
for kt in range(len(t)):
for ksta in range(len(sta)):
i=where(h[ksta].times()==t[kt])[0]
vout[ksta]=h[ksta].data[i]
if vout.max()>maxv:
maxv=vout.max()
out=c_[lonlat,vout]
num=rjust(str(kt),4,'0')
print num
savetxt(home+project_name+'/analysis/shake/'+num+'.shake',out,fmt='%10.6f\t%10.6f\t%10.4f')
print 'Max velocity was '+str(maxv)+'m/s'
def envelope(n, e, z, fcorner=None, Ncomponents=3):
'''
Build the envelope of a 3- or 2-component accelerogram using the Hilbert
transform as implemented in obspy.signal.filter
'''
from obspy.signal.filter import envelope
from mudpy.forward import lowpass
#remove pre-event baseline
n[0].data -= n[0].data[0]
e[0].data -= e[0].data[0]
z[0].data -= z[0].data[0]
#Initalize per-component envelopes
nenv = n.copy()
eenv = e.copy()
zenv = z.copy()
#make envelopes
nenv[0].data = envelope(n[0].data)
eenv[0].data = envelope(e[0].data)
zenv[0].data = envelope(z[0].data)
#combine envelopes into one
aenv = n.copy()
aenvf = n.copy()
#How many components
if Ncomponents == 3:
aenv[0].data = (nenv[0].data**2 + eenv[0].data**2 +
zenv[0].data**2)**0.5
else:
aenv[0].data = (nenv[0].data**2 + eenv[0].data**2)**0.5
#Low pass filter envelope
if fcorner == None:
aenvf = aenv.copy()
else:
aenvf[0].data = lowpass(aenv[0].data, fcorner,
1. / aenv[0].stats.delta, 2)
return aenvf
def envelope(n,e,z,fcorner=None,Ncomponents=3):
'''
Build the envelope of a 3- or 2-component accelerogram using the Hilbert
transform as implemented in obspy.signal.filter
'''
from obspy.signal.filter import envelope
from mudpy.forward import lowpass
#remove pre-event baseline
n[0].data-=n[0].data[0]
e[0].data-=e[0].data[0]
z[0].data-=z[0].data[0]
#Initalize per-component envelopes
nenv=n.copy()
eenv=e.copy()
zenv=z.copy()
#make envelopes
nenv[0].data=envelope(n[0].data)
eenv[0].data=envelope(e[0].data)
zenv[0].data=envelope(z[0].data)
#combine envelopes into one
aenv=n.copy()
aenvf=n.copy()
#How many components
if Ncomponents==3:
aenv[0].data=(nenv[0].data**2+eenv[0].data**2+zenv[0].data**2)**0.5
else:
aenv[0].data=(nenv[0].data**2+eenv[0].data**2)**0.5
#Low pass filter envelope
if fcorner==None:
aenvf=aenv.copy()
else:
aenvf[0].data=lowpass(aenv[0].data,fcorner,1./aenv[0].stats.delta,2)
return aenvf
#Final write
n.write(path+'proc/'+sta+'.LXN.sac',format='SAC')
e.write(path+'proc/'+sta+'.LXE.sac',format='SAC')
u.write(path+'proc/'+sta+'.LXZ.sac',format='SAC')
if cut_filter:
stanames=genfromtxt('/Users/dmelgar/Slip_inv/iquique_sm/data/station_info/gps.gflist',usecols=0,dtype='S')
coords=genfromtxt('/Users/dmelgar/Slip_inv/iquique_sm/data/station_info/gps.gflist',usecols=[1,2])
for k in range(len(stanames)):
sta=stanames[k]
print sta
n=read(path+'proc/'+sta+'.LXN.sac')
e=read(path+'proc/'+sta+'.LXE.sac')
u=read(path+'proc/'+sta+'.LXZ.sac')
#Low pass filter
n[0].data=lowpass(n[0].data,fcorner,1./n[0].stats.delta,10)
e[0].data=lowpass(e[0].data,fcorner,1./e[0].stats.delta,10)
u[0].data=lowpass(u[0].data,fcorner,1./u[0].stats.delta,10)
#Get station to hypocenter delta distance
delta=locations2degrees(coords[k,1],coords[k,0],epicenter[1],epicenter[0])
#Get p-time to site
tt=getTravelTimes(delta,epicenter[2])
tp=timedelta(seconds=float64(tt[0]['time']))
#Trim
n[0].trim(starttime=time_epi+tp-tmin,endtime=time_epi+tp+tmax)
e[0].trim(starttime=time_epi+tp-tmin,endtime=time_epi+tp+tmax)
u[0].trim(starttime=time_epi+tp-tmin,endtime=time_epi+tp+tmax)
#Remove first epoch
n[0].data=n[0].data-n[0].data[0]
e[0].data=e[0].data-e[0].data[0]
u[0].data=u[0].data-u[0].data[0]
dtype='S')
for k in range(len(stations)):
print stations[k]
n = read(path + 'trim/' + stations[k] + '.HNN.sac')
e = read(path + 'trim/' + stations[k] + '.HNE.sac')
z = read(path + 'trim/' + stations[k] + '.HNZ.sac')
#Remove zero baseline
n[0].data = n[0].data - mean(n[0].data[0:500])
e[0].data = e[0].data - mean(e[0].data[0:500])
z[0].data = z[0].data - mean(z[0].data[0:500])
#Integrate
n[0].data = cumtrapz(n[0].data, n[0].times(), initial=0)
e[0].data = cumtrapz(e[0].data, e[0].times(), initial=0)
z[0].data = cumtrapz(z[0].data, z[0].times(), initial=0)
#Lowpass or Bandpass
n[0].data = lowpass(n[0].data, fcorner, 1. / n[0].stats.delta, 2)
e[0].data = lowpass(e[0].data, fcorner, 1. / e[0].stats.delta, 2)
z[0].data = lowpass(z[0].data, fcorner, 1. / z[0].stats.delta, 2)
#Decimate to 4 Hz
if n[0].stats.delta == 0.005:
n = stdecimate(n, 5, 10)
n = stdecimate(n, 5, 10)
n = stdecimate(n, 2, 10)
e = stdecimate(e, 5, 10)
e = stdecimate(e, 5, 10)
e = stdecimate(e, 2, 10)
z = stdecimate(z, 5, 10)
z = stdecimate(z, 5, 10)
z = stdecimate(z, 2, 10)
if n[0].stats.delta == 0.01:
n = stdecimate(n, 5, 10)
dtype='S')
station_coords = genfromtxt(path + 'station_info/michoacan_after.sta',
usecols=[1, 2])
#Now loop over station data at each epoch
for ksta in range(len(stanames)):
print '... fetching PGD for ' + stanames[ksta]
try:
n = read(data_path + '/' + stanames[ksta] + '.LYN.sac')
e = read(data_path + '/' + stanames[ksta] + '.LYE.sac')
u = read(data_path + '/' + stanames[ksta] + '.LYZ.sac')
if n[0].stats.npts > 0:
#Trim to times of interest
n.trim(starttime=hypo_time, endtime=hypo_time + tmax, pad=True)
e.trim(starttime=hypo_time, endtime=hypo_time + tmax, pad=True)
u.trim(starttime=hypo_time, endtime=hypo_time + tmax, pad=True)
n[0].data = lowpass(n[0].data, 0.6, 5.0, 2)
e[0].data = lowpass(n[0].data, 0.6, 5.0, 2)
u[0].data = lowpass(n[0].data, 0.6, 5.0, 2)
n[0].decimate(factor=5, no_filter=True)
e[0].decimate(factor=5, no_filter=True)
u[0].decimate(factor=5, no_filter=True)
#Remove mean of first ten seconds
#Get station-event distance
d, az, baz = gps2DistAzimuth(station_coords[ksta, 1],
station_coords[ksta, 0], hypo[1],
hypo[0])
hypo_dist = ((d / 1000)**2 + hypo[2]**2)**0.5
#Now get PGD at that site
pgd_all_out = 0
pgd_nov_out = 0
time_to_all = 0
files = glob(
'/Users/dmelgar/Slip_inv/Chiapas_hernandez/data/waveforms/*.disp*')
dt = 0.25
fcorner = 0.49
for k in range(len(files)):
print files[k]
st = read(files[k])
dt_data = st[0].stats.delta
tmax = dt_data * st[0].stats.npts - dt_data
t = arange(0, tmax, dt)
#filter
d = lowpass(st[0].data, fcorner, 1. / dt_data, 2, zerophase=True)
#Interpolate
f = interp1d(st[0].times(), d)
dinterp = f(t)
#filter again to be safe about upsampled data
dout = lowpass(dinterp, fcorner, 1. / dt, 2, zerophase=True)
#metadata
st[0].stats.delta = dt
#output
st[0].data = dout
st.write(files[k], format='SAC')
nbb = read(path + sta + '.bb.HNN.sac') ebb = read(path + sta + '.bb.HNE.sac') zbb = read(path + sta + '.bb.HNZ.sac') nhf = read(path + sta + '.HNN.sac') ehf = read(path + sta + '.HNE.sac') zhf = read(path + sta + '.HNZ.sac') #Diff LF to accel dt = nlf[0].stats.delta nlf[0].data = r_[0, diff(r_[0, diff(nlf[0].data) / dt]) / dt] elf[0].data = r_[0, diff(r_[0, diff(elf[0].data) / dt]) / dt] zlf[0].data = r_[0, diff(r_[0, diff(zlf[0].data) / dt]) / dt] #low pass filter nlf[0].data = lowpass(nlf[0].data, 1.0, 1. / dt, 4, zerophase=True) elf[0].data = lowpass(elf[0].data, 1.0, 1. / dt, 4, zerophase=True) zlf[0].data = lowpass(zlf[0].data, 1.0, 1. / dt, 4, zerophase=True) #hig pass filter dt = nhf[0].stats.delta nhf[0].data = highpass(nhf[0].data, 1.0, 1. / dt, 4, zerophase=True) ehf[0].data = highpass(ehf[0].data, 1.0, 1. / dt, 4, zerophase=True) zhf[0].data = highpass(zhf[0].data, 1.0, 1. / dt, 4, zerophase=True) #Plot limits elims = [-max(abs(ebb[0].data)), max(abs(ebb[0].data))] nlims = [-max(abs(nbb[0].data)), max(abs(nbb[0].data))] zlims = [-max(abs(zbb[0].data)), max(abs(zbb[0].data))] xlims = [0, 60]
xl=[0,20] run='7546538' M='M5' lag=0.5 #read in BBP waveforms tlf,lfe=bbptools.read_bbp_seismogram(u'/Users/dmelgar/FakeQuakes/M6_BB/plots/'+M+'/'+run+'.'+sta+'-lf.acc.090') thf,hfe=bbptools.read_bbp_seismogram(u'/Users/dmelgar/FakeQuakes/M6_BB/plots/'+M+'/'+run+'.'+sta+'-hf.acc.090') tlf,lfn=bbptools.read_bbp_seismogram(u'/Users/dmelgar/FakeQuakes/M6_BB/plots/'+M+'/'+run+'.'+sta+'-lf.acc.000') thf,hfn=bbptools.read_bbp_seismogram(u'/Users/dmelgar/FakeQuakes/M6_BB/plots/'+M+'/'+run+'.'+sta+'-hf.acc.000') tlf,lfz=bbptools.read_bbp_seismogram(u'/Users/dmelgar/FakeQuakes/M6_BB/plots/'+M+'/'+run+'.'+sta+'-lf.acc.ver') thf,hfz=bbptools.read_bbp_seismogram(u'/Users/dmelgar/FakeQuakes/M6_BB/plots/'+M+'/'+run+'.'+sta+'-hf.acc.ver') #filter fsample=1/(tlf[1]-tlf[0]) lfe=lowpass(lfe,1.0,fsample,4,zerophase=True) lfn=lowpass(lfn,1.0,fsample,4,zerophase=True) lfz=lowpass(lfz,1.0,fsample,4,zerophase=True) fsample=1/(thf[1]-thf[0]) hfe=highpass(hfe,1.0,fsample,4,zerophase=True) hfn=highpass(hfn,1.0,fsample,4,zerophase=True) hfz=highpass(hfz,1.0,fsample,4,zerophase=True) #rescale lfe=lfe/100 lfn=lfn/100 lfz=lfz/100 hfe=hfe/100 hfn=hfn/100 hfz=hfz/100
time_bandwidth=4,
number_of_tapers=5,
nfft=syn_wf[0].stats.npts,
quadratic=True)
syn_amp = np.sqrt(syn_amp_squared)
############## Low frequency spectra ##############
# Double differentiate disp waveform to get it acc
lf_vel_data = r_[0, diff(lf_wf[0].data) / lf_wf[0].stats.delta]
lf_acc_data = r_[0, diff(lf_vel_data) / lf_wf[0].stats.delta]
# Low pass filter low frequency data
lf_acc_data = forward.lowpass(lf_acc_data,
0.998,
lf_wf[0].stats.sampling_rate,
4,
zerophase=True)
# Calculate spectra
lf_amp_squared, lf_freq = mtspec(lf_acc_data,
delta=lf_wf[0].stats.delta,
time_bandwidth=4,
number_of_tapers=5,
nfft=lf_wf[0].stats.npts,
quadratic=True)
lf_amp = np.sqrt(lf_amp_squared)
############## High frequency spectra ##############
# High pass filter high frequency data
from scipy.signal import ellip, filtfilt
from numpy import size, array
fnyquist = fsample / 2
b, a = ellip(order, rp, rs, array(fcorner) / (fnyquist), btype='low')
data_filt = filtfilt(b, a, data)
return data_filt
tlf_raw, lf_raw = bbptools.read_bbp_seismogram(
'/Users/dmelgar/code/BBP/bbp/bbp_data/finished/rawdata/fake_nocal/111.' +
sta + '-lf.acc.000.prefilter')
tlf_bbp_proc, lf_bbp_proc = bbptools.read_bbp_seismogram(
'/Users/dmelgar/code/BBP/bbp/bbp_data/finished/rawdata/fake_nocal/111.' +
sta + '-lf-resamp.000')
lf_filt2 = lowpass(lf_raw, 1.2, 10, 2)
lf_filt4 = lowpass(lf_raw, 1.2, 10, 4)
lf_filt8 = lowpass(lf_raw, 1.2, 10, 8)
#lf_filt2=ellip_lowpass(lf_raw,1.2,10,2,rs=0.1)
#lf_filt4=ellip_lowpass(lf_raw,1.2,10,4,rs=0.1)
#lf_filt8=ellip_lowpass(lf_raw,1.2,10,8,rs=0.1)
xyz, slip, tinit, stf_all, rise_time, hypocenter = bbptools.read_srf(
u'/Users/dmelgar/code/BBP/bbp/bbp_data/finished/fake_nocal/large_eew_m5.0_frac0.5.srf'
)
ptime, stime = bbptools.arrivals(hypocenter, lonlat[i, 0], lonlat[i, 1])
#plt.figure()
#plt.plot(tlf_raw,lf_raw,'k')
#plt.plot(tlf_raw,lf_filt,'r',lw=2)
#plt.legend(['unfilt','filt'])
u5 = read(u'/Users/dmelgar/Slip_inv/Nepal_ttests_' + str(tr) +
'/output/forward_models/' + str(tr) + 's_vr3.6.KKN4.vel.u')
u = read(u'/Users/dmelgar/Nepal2015/GPS/PPP/KKN4.LXZ.sac')
#trim
delay = 15
t1 = time_epi + timedelta(seconds=delay)
t2 = t1 + timedelta(seconds=70)
u1[0].trim(starttime=t1, endtime=t2)
u2[0].trim(starttime=t1, endtime=t2)
u3[0].trim(starttime=t1, endtime=t2)
u4[0].trim(starttime=t1, endtime=t2)
u5[0].trim(starttime=t1, endtime=t2)
u[0].trim(starttime=t1 + timedelta(seconds=1), endtime=t2)
u[0].data = u[0].data - u[0].data[0]
u[0].data = lowpass(u[0].data, 1.0, 5.0, 2)
u[0].data = diff(u[0].data / 0.2)
plt.figure(figsize=(6, 5))
plt.plot(u1[0].times() + delay, u1[0].data + dvert)
plt.plot(u2[0].times() + delay, u2[0].data + 2 * dvert)
plt.plot(u3[0].times() + delay, u3[0].data + 3 * dvert)
plt.plot(u4[0].times() + delay, u4[0].data + 4 * dvert)
plt.plot(u5[0].times() + delay, u5[0].data + 5 * dvert)
plt.plot(u[0].times() + delay, u[0].data, 'k', lw=1.5)
plt.xlim([15, 80])
plt.ylim([-0.2, 3.5])
plt.grid()
plt.xlabel('Seconds after OT')
plt.ylabel('Vertical velocity (m/s)')
plt.title(str(tr) + 's rise time')
