def test_SKS():
import matplotlib
matplotlib.use('Agg')
import numpy as np
from obspy.core import Stream
from obspy.signal.rotate import rotate_ne_rt
from telewavesim import utils as ut
from telewavesim import wiggle as wg
modfile = resource_filename('telewavesim',
'examples/models/model_SKS.txt')
wvtype = 'SV'
npts = 3000 # Number of samples
dt = 0.05 # Sample distance in seconds
slow = 0.04 # Horizontal slowness (or ray parameter) in s/km
baz = np.arange(0., 360., 10.)
model = ut.read_model(modfile)
t1 = ut.calc_ttime(model, slow, wvtype=wvtype)
assert round(t1, 1) == 21.6
trR = Stream()
trT = Stream()
# Loop over range of data
for bb in baz:
# Calculate the plane wave seismograms
trxyz = ut.run_plane(model, slow, npts, dt, bb, wvtype=wvtype)
# Extract East, North and Vertical
ntr = trxyz[0]
etr = trxyz[1]
ztr = trxyz[2]
# Copy to radial and transverse
rtr = ntr.copy()
ttr = etr.copy()
# Rotate to radial and transverse
rtr.data, ttr.data = rotate_ne_rt(ntr.data, etr.data, bb)
# Append to streams
trR.append(rtr)
trT.append(ttr)
# Set frequency corners in Hz
f1 = 0.01
f2 = 0.2
# Filter to get wave-like traces
trR.filter('bandpass', freqmin=f1, freqmax=f2, corners=2, zerophase=True)
trT.filter('bandpass', freqmin=f1, freqmax=f2, corners=2, zerophase=True)
# Plot as wiggles
with tempfile.TemporaryDirectory() as tempdir:
wg.pw_wiggles_baz(trR, trT, 'test', btyp='baz', scale=0.05,
t1=t1, tmin=0., tmax=40, save=True,
ftitle=join(tempdir, 'sks'),
wvtype='SV')
def _synthone(self, src_lat, src_lon, dt, npts, time_init):
"""
Synthesize single event
"""
event_id_base = 'hiperseis:PRM/evid='
stats = self.compute_event_stats(src_lat, src_lon, event_id_base)
stats.pop('tt_model')
ray_param_sec_per_km = stats['slowness'] / KM_PER_DEG
traces_zne = run_plane(self.model,
ray_param_sec_per_km,
npts,
dt,
baz=stats['back_azimuth'])
# Taper beginning to deal with spectral artefacts
traces_zne.taper(0.05, side='left')
# Synthetics here have been observed to have high noise at Nyquist freq. Filter it out.
kernel = sig.firwin(9, 0.5)
for tr in traces_zne:
tr.data = sig.filtfilt(kernel, 1, tr.data)
# end for
# Extract time location of max Z amplitude and use as the onset time marker.
tr_z = traces_zne.select(component='Z')[0]
onset_marker = tr_z.times()[(tr_z.data == np.max(tr_z.data))][0]
times_rel_mantle = tr_z.times()[0] - onset_marker
for tr in traces_zne:
stats['channel'] = '**' + tr.stats['channel'][-1]
tr.stats.update(stats)
if time_init < times_rel_mantle:
n_leading = int((times_rel_mantle - time_init) / dt)
data_new = np.append(np.zeros(n_leading),
tr.data[:(npts - n_leading)])
assert data_new.shape == tr.data.shape
tr.data = data_new
elif time_init > times_rel_mantle:
n_trailing = int((time_init - times_rel_mantle) / dt)
data_new = np.append(tr.data[(npts - n_trailing):],
np.zeros(n_trailing))
assert data_new.shape == tr.data.shape
tr.data = data_new
# end if
# end for
traces_zne.differentiate()
return traces_zne
def test_Porter2011():
import matplotlib
matplotlib.use('Agg')
import numpy as np
from obspy.core import Stream
from telewavesim import utils as ut
from telewavesim import wiggle as wg
modfile = resource_filename('telewavesim',
'examples/models/model_Porter2011.txt')
wvtype = 'P'
npts = 3000 # Number of samples
dt = 0.01 # Sample distance in seconds
slow = 0.06 # Horizontal slowness (or ray parameter) in s/km
baz = np.arange(0., 360., 10.)
model = ut.read_model(modfile)
trR = Stream()
trT = Stream()
# Loop over range of data
for bb in baz:
# Calculate the plane waves seismograms
trxyz = ut.run_plane(model, slow, npts, dt, bb, wvtype=wvtype,
obs=False)
# Then the transfer functions in Z-R-T coordinate system
tfs = ut.tf_from_xyz(trxyz, pvh=False)
# Append to streams
trR.append(tfs[0])
trT.append(tfs[1])
# Set frequency corners in Hz
f1 = 0.01
f2 = 1.0
# Filter to get wave-like traces
trR.filter('bandpass', freqmin=f1, freqmax=f2, corners=2, zerophase=True)
trT.filter('bandpass', freqmin=f1, freqmax=f2, corners=2, zerophase=True)
# Stack over all traces
trR_stack, trT_stack = ut.stack_all(trR, trT, pws=True)
# Plot as wiggles
with tempfile.TemporaryDirectory() as tempdir:
wg.rf_wiggles_baz(trR, trT, trR_stack, trT_stack, 'test', btyp='baz',
scale=1.e3, tmin=-5., tmax=8., save=True,
ftitle=join(tempdir, 'porter2011.png'),
wvtype='P')
def test_Audet2016():
import matplotlib
matplotlib.use('Agg')
from obspy.core import Stream
from obspy.signal.rotate import rotate_ne_rt
from telewavesim import utils as ut
from telewavesim import wiggle as wg
modfile = resource_filename('telewavesim',
'examples/models/model_Audet2016.txt')
wvtype = 'P'
npts = 3000 # Number of samples
dt = 0.01 # Sample distance in seconds
dp = 2000. # Deployment depth below sea level in meters
c = 1.500 # P-wave velocity in salt water (km/s)
rhof = 1027. # Density of salt water (kg/m^3)
slow = 0.06 # Horizontal slowness (or ray parameter) in s/km
# Back-azimuth direction in degrees
# (has no influence if model is isotropic)
baz = 0.
model = ut.read_model(modfile)
assert list(model.rho) == [2800.0, 2800.0, 3200.0]
t1 = ut.calc_ttime(model, slow, wvtype=wvtype)
assert round(t1, 1) == 1.1
trxyz = ut.run_plane(model, slow, npts, dt, baz=baz, wvtype=wvtype,
obs=True, dp=dp, c=c, rhof=rhof)
tfs = ut.tf_from_xyz(trxyz, pvh=False)
ntr = trxyz[0] # North component
etr = trxyz[1] # East component
ztr = trxyz[2] # Vertical component
rtr = ntr.copy() # Radial component
ttr = etr.copy() # Transverse component
rtr.data, ttr.data = rotate_ne_rt(ntr.data, etr.data, baz)
strf = Stream(traces=[tfs[0], ztr, rtr])
# Set frequency corners in Hz
f1 = 0.1
f2 = 1.0
# Plot as wiggles
with tempfile.TemporaryDirectory() as tempdir:
wg.pw_wiggles_Audet2016(strf, t1=t1, tmax=10., f1=f1, f2=f2,
ftitle=join(tempdir, 'audet2016'),
scale=2.e-7, save=True)
def _residuals(self):
"""
Internal method to obtain residuals between observed and predicted
receiver functions given the Moho depth and Vp/Vs obtained from
the Hk stack.
"""
from telewavesim import utils
# Simple 1-layer model over half-space
model = utils.Model([self.h0, 0.], [2800., 3300.], [self.vp, 8.0],
[self.vp / self.k0, 4.5], ['iso', 'iso'])
# Parameters for run
slow = [tr.stats.slow for tr in self.rfV1]
npts = self.rfV1[0].stats.npts
dt = self.rfV1[0].stats.delta
trR = Stream()
for sl in slow:
trxyz = utils.run_plane(model, sl, npts, dt)
tfs = utils.tf_from_xyz(trxyz,
pvh=True,
vp=self.vp,
vs=self.vp / self.k0)
tfs[0].data = np.fft.fftshift(tfs[0].data)
trR.append(tfs[0])
trR.filter('bandpass',
freqmin=0.05,
freqmax=0.5,
corners=2,
zerophase=True)
# Get stream of residuals
res = trR.copy()
for i in range(len(res)):
res[i].data = self.rfV1[i].data - trR[i].data
return res