def test_p_iasp91_geo_fallback_manual(self):
"""
Manual test for P phase in IASP91 given geographical input.
This version of the test checks that things still work when
geographiclib is not installed.
"""
has_geographiclib_real = geodetics.HAS_GEOGRAPHICLIB
geodetics.HAS_GEOGRAPHICLIB = False
m = TauPyModel(model="iasp91")
arrivals = m.get_travel_times_geo(source_depth_in_km=10.0,
source_latitude_in_deg=20.0,
source_longitude_in_deg=33.0,
receiver_latitude_in_deg=55.0,
receiver_longitude_in_deg=33.0,
phase_list=["P"])
geodetics.HAS_GEOGRAPHICLIB = has_geographiclib_real
self.assertEqual(len(arrivals), 1)
p_arrival = arrivals[0]
self.assertEqual(p_arrival.name, "P")
self.assertAlmostEqual(p_arrival.time, 412.43, 2)
self.assertAlmostEqual(p_arrival.ray_param_sec_degree, 8.613, 3)
self.assertAlmostEqual(p_arrival.takeoff_angle, 26.74, 2)
self.assertAlmostEqual(p_arrival.incident_angle, 26.70, 2)
self.assertAlmostEqual(p_arrival.purist_distance, 35.00, 2)
self.assertEqual(p_arrival.purist_name, "P")
def test_pierce_p_iasp91_geo(self):
"""
Test single pierce point against output from TauP using geo data.
This version of the test is used when geographiclib is installed
"""
m = TauPyModel(model="iasp91")
arrivals = m.get_pierce_points_geo(source_depth_in_km=10.0,
source_latitude_in_deg=-45.0,
source_longitude_in_deg=-50.0,
receiver_latitude_in_deg=-80.0,
receiver_longitude_in_deg=-50.0,
phase_list=["P"])
self.assertEqual(len(arrivals), 1)
p_arr = arrivals[0]
# Open test file.
filename = os.path.join(DATA,
"taup_pierce_-mod_isp91_ph_P_-h_10_-evt_" +
"-45_-50_-sta_-80_-50")
expected = np.genfromtxt(filename, skip_header=1)
np.testing.assert_almost_equal(expected[:, 0],
np.degrees(p_arr.pierce['dist']), 2)
np.testing.assert_almost_equal(expected[:, 1],
p_arr.pierce['depth'], 1)
np.testing.assert_almost_equal(expected[:, 2],
p_arr.pierce['time'], 1)
np.testing.assert_almost_equal(expected[:, 3],
p_arr.pierce['lat'], 1)
np.testing.assert_almost_equal(expected[:, 4],
p_arr.pierce['lon'], 1)
def test_regional_models(self):
"""
Tests small regional models as this used to not work.
Note: It looks like too much work to get a 1-layer model working.
The problem is first in finding the moho, and second in coarsely-
sampling slowness. Also, why bother.
"""
model_names = ["2_layer_model", "5_layer_model"]
expected_results = [
[("p", 18.143), ("Pn", 19.202), ("PcP", 19.884), ("sP", 22.054),
("ScP", 23.029), ("PcS", 26.410), ("s", 31.509), ("Sn", 33.395),
("ScS", 34.533)],
[("Pn", 17.358), ("P", 17.666), ("p", 17.804), ("P", 17.869),
("PcP", 18.039), ("ScP", 19.988), ("sP", 22.640), ("sP", 22.716),
("sP", 22.992), ("PcS", 23.051), ("sP", 24.039), ("sP", 24.042),
("Sn", 30.029), ("S", 30.563), ("s", 30.801), ("S", 30.913),
("ScS", 31.208)]]
for model_name, expects in zip(model_names, expected_results):
with TemporaryWorkingDirectory():
folder = os.path.abspath(os.curdir)
build_taup_model(
filename=os.path.join(DATA, os.path.pardir,
model_name + ".tvel"),
output_folder=folder, verbose=False)
model = TauPyModel(os.path.join(folder, model_name + ".npz"))
arrvials = model.get_ray_paths(source_depth_in_km=18.0,
distance_in_degree=1.0)
self.assertEqual(len(arrvials), len(expects))
for arrival, expect in zip(arrvials, expects):
self.assertEqual(arrival.name, expect[0])
self.assertAlmostEqual(arrival.time, expect[1], 3)
def get_first_arrival(st, model='ak135'):
'''
Returns first arrival information for a particular stream and a theoretical velocity model ak135 or iasp91.
Output is phase name, arrival time (in s after origin) and slowness (in s / km).
Parameters
----------
st : ObsPy Stream object
Stream of SAC format seismograms for the seismic array
model : string
Model to use for the travel times, either 'ak135' or 'iasp91'.
Returns
-------
phase : Phase object
Phase object containing the phase name, arrival time, and slowness of the first arrival
'''
# Read event depth and great circle distance from SAC header
depth = st[0].stats.sac.evdp
delta = st[0].stats.sac.gcarc
taup = TauPyModel(model)
first_arrival = taup.get_travel_times(depth, delta)[0]
phase = Phase(first_arrival.name, first_arrival.time, first_arrival.ray_param_sec_degree / G_KM_DEG)
return phase
def get_arrivals(st, model='ak135'):
'''
Returns complete arrival information for a particular stream and a theoretical velocity model ak135 or iasp91.
Output is phase name, arrival time (in s after origin) and slowness (in s / km).
Parameters
----------
st : ObsPy Stream object
Stream of SAC format seismograms for the seismic array
model : string
Model to use for the travel times, either 'ak135' or 'iasp91'.
Returns
-------
phase_list : list
List containing Phase objects containing the phase name, arrival time, and slowness of each arrival
'''
# Read event depth and great circle distance from SAC header
depth = st[0].stats.sac.evdp
delta = st[0].stats.sac.gcarc
tau_model = TauPyModel(model)
arrivals = tau_model.get_travel_times(depth, delta)
phase_list = []
for arrival in arrivals:
phase = Phase(arrival.name, arrival.time, arrival.ray_param_sec_degree / G_KM_DEG)
phase_list.append(phase)
return phase_list
def test_surface_wave_ttimes(self):
"""
Tests the calculation of surface ttimes.
Tested against a reference output from the Java TauP version.
"""
for model, table in [("iasp91", "iasp91_surface_waves_table.txt"),
("ak135", "ak135_surface_waves_table.txt")]:
m = TauPyModel(model=model)
filename = os.path.join(DATA, table)
with open(filename, "rt") as fh:
for line in fh:
_, distance, depth, phase, time, ray_param, _, _ \
= line.split()
distance, depth, time, ray_param = \
map(float, [distance, depth, time, ray_param])
arrivals = m.get_travel_times(
source_depth_in_km=depth, distance_in_degree=distance,
phase_list=[phase])
self.assertTrue(len(arrivals) > 0)
# Potentially multiple arrivals. Get the one closest in
# time and closest in ray parameter.
arrivals = sorted(
arrivals,
key=lambda x: (abs(x.time - time),
abs(x.ray_param_sec_degree -
ray_param)))
arrival = arrivals[0]
self.assertEqual(round(arrival.time, 2), round(time, 2))
self.assertEqual(round(arrival.ray_param_sec_degree, 2),
round(ray_param, 2))
def test_different_models(self):
"""
Open all included models and make sure that they can produce
reasonable travel times.
"""
models = ["1066a", "1066b", "ak135", "herrin", "iasp91", "prem",
"sp6", "jb", "pwdk", "ak135f_no_mud"]
for model in models:
m = TauPyModel(model=model)
# Get a p phase.
arrivals = m.get_travel_times(
source_depth_in_km=10.0, distance_in_degree=50.0,
phase_list=["P"])
# AK135 travel time.
expected = 534.4
self.assertTrue(abs(arrivals[0].time - expected) < 5)
# Get an s phase.
arrivals = m.get_travel_times(
source_depth_in_km=10.0, distance_in_degree=50.0,
phase_list=["S"])
# AK135 travel time.
expected = 965.1
# Some models do produce s-waves but they are very far from the
# AK135 value.
self.assertTrue(abs(arrivals[0].time - expected) < 50)
def main():
# MAIN PROGRAM BODY
OT,stlat,stlon,evlat,evlon,depth = getoptions()
origin_time = UTCDateTime(str(OT))
result = client.distaz(stalat=stlat, stalon=stlon, evtlat=evlat,evtlon=evlon)
model = TauPyModel(model="AK135")
arrivals = model.get_travel_times(source_depth_in_km=depth,distance_in_degree=result['distance'])#,
#phase_list = ['P','PcP','PP','PKiKP','S','SS','ScS','SKiKS'])
print "Distance = {0:.1f} arc degrees.".format(result['distance'])
print "{0:.0f} Km distance.".format(result['distance']*111.25)
print "{0:.0f} deg back Azimuth.".format(result['backazimuth'])
table = client.traveltime(evloc=(evlat,evlon),staloc=[(stlat,stlon)],evdepth=depth)
print "Selected phase list:\n"
print (table.decode())
# Print the phases, travel time and forecasted arrival time.
phasename = []
phasetime = []
arrivaltime = []
print "For origin time {}, ".format(origin_time)
print "TauP big list of phases and arrival times:"
for i in range(0,len(arrivals)):
phasename.append(arrivals[i].name)
phasetime.append(arrivals[i].time)
at = origin_time+(arrivals[i].time)
arrivaltime.append(at)
print 'Phase: {0} \t arrives in {1:.2f} sec. at time {2:02.0f}:{3:02.0f}:{4:02.0f}.{5:02.0f}' \
.format(arrivals[i].name,arrivals[i].time,at.hour,at.minute,at.second,at.microsecond/10000)
arrivalpaths = model.get_ray_paths(source_depth_in_km=depth,distance_in_degree=result['distance'])#,\
# phase_list = ['P','PcP','PP','PKiKP','S','SS','ScS','SKiKS'])
arrivalpaths.plot()
def get_station_delays(station_coords,sources,velmod='PREM',phase_list=['s','S']):
'''
Given an array of station corodiantes and sources calculate the travel time
from each source toe ach site.
velmod is the FULL path to the .npz file used by TauPy
'''
from obspy.taup import TauPyModel
from numpy import zeros
from obspy.geodetics.base import locations2degrees
model = TauPyModel(model=velmod)
#Initalize output variabe
delay_time=zeros((len(sources),len(station_coords)))
#Loop over sources
for ksource in range(len(sources)):
print('Working on source %d of %d ' % (ksource,len(sources)))
#loop over sites
for ksite in range(len(station_coords)):
distance_in_degrees=locations2degrees(station_coords[ksite,1],station_coords[ksite,0],
sources[ksource,2],sources[ksource,1])
arrivals = model.get_travel_times(source_depth_in_km=sources[ksource,3],
distance_in_degree=distance_in_degrees,phase_list=phase_list)
delay_time[ksource,ksite]=arrivals[0].time
return delay_time
def test_single_path_ak135(self):
"""
Test the raypath for a single phase. This time for model AK135.
"""
filename = os.path.join(
DATA, "taup_path_-o_stdout_-h_10_-ph_P_-deg_35_-mod_ak135")
expected = np.genfromtxt(filename, comments='>')
m = TauPyModel(model="ak135")
arrivals = m.get_ray_paths(source_depth_in_km=10.0,
distance_in_degree=35.0, phase_list=["P"])
self.assertEqual(len(arrivals), 1)
# Interpolate both paths to 100 samples and make sure they are
# approximately equal.
sample_points = np.linspace(0, 35, 100)
interpolated_expected = np.interp(
sample_points,
expected[:, 0],
expected[:, 1])
interpolated_actual = np.interp(
sample_points,
np.round(np.degrees(arrivals[0].path['dist']), 2),
np.round(6371 - arrivals[0].path['depth'], 2))
self.assertTrue(np.allclose(interpolated_actual,
interpolated_expected, rtol=1E-4, atol=0))
def test_single_path_geo_iasp91(self):
"""
Test the raypath for a single phase given geographical input.
This tests the case when geographiclib is installed.
"""
filename = os.path.join(DATA,
"taup_path_-mod_iasp91_-o_stdout_-h_10_" +
"-ph_P_-sta_-45_-60_evt_-80_-60")
expected = np.genfromtxt(filename, comments='>')
m = TauPyModel(model="iasp91")
arrivals = m.get_ray_paths_geo(source_depth_in_km=10.0,
source_latitude_in_deg=-80.0,
source_longitude_in_deg=-60.0,
receiver_latitude_in_deg=-45.0,
receiver_longitude_in_deg=-60.0,
phase_list=["P"])
self.assertEqual(len(arrivals), 1)
# Interpolate both paths to 100 samples and make sure they are
# approximately equal.
sample_points = np.linspace(0, 35, 100)
interpolated_expected_depth = np.interp(
sample_points,
expected[:, 0],
expected[:, 1])
interpolated_expected_lat = np.interp(
sample_points,
expected[:, 0],
expected[:, 2])
interpolated_expected_lon = np.interp(
sample_points,
expected[:, 0],
expected[:, 3])
interpolated_actual_depth = np.interp(
sample_points,
np.round(np.degrees(arrivals[0].path['dist']), 2),
np.round(6371 - arrivals[0].path['depth'], 2))
interpolated_actual_lat = np.interp(
sample_points,
np.round(np.degrees(arrivals[0].path['dist']), 2),
np.round(arrivals[0].path['lat'], 2))
interpolated_actual_lon = np.interp(
sample_points,
np.round(np.degrees(arrivals[0].path['dist']), 2),
np.round(arrivals[0].path['lon'], 2))
np.testing.assert_allclose(interpolated_actual_depth,
interpolated_expected_depth,
rtol=1E-4, atol=0)
np.testing.assert_allclose(interpolated_actual_lat,
interpolated_expected_lat,
rtol=1E-4, atol=0)
np.testing.assert_allclose(interpolated_actual_lon,
interpolated_expected_lon,
rtol=1E-4, atol=0)
def get_taupy_points(
center_lat, center_lon, ev_lat, ev_lon, ev_depth, stime, etime, mini, maxi, ev_otime, phase_shift, sll, slm
):
distance = locations2degrees(center_lat, center_lon, ev_lat, ev_lon)
# print(distance)
model = TauPyModel(model="ak135")
arrivals = model.get_pierce_points(ev_depth, distance)
# arrivals = earthmodel.get_pierce_points(ev_depth,distance,phase_list=('PP','P^410P'))
# compute the vespagram window
start_vespa = stime - mini
end_vespa = etime - maxi
# compare the arrival times with the time window
count = 0
k = 0
phase_name_info = []
phase_slowness_info = []
phase_time_info = []
for i_elem in arrivals:
# print(i_elem)
dummy_phase = arrivals[count]
# print(dummy_phase)
# phase time in seconds
taup_phase_time = dummy_phase.time
# print(taup_phase_time)
# slowness of the phase
taup_phase_slowness = dummy_phase.ray_param_sec_degree
# compute the UTC travel phase time
taup_phase_time2 = ev_otime + taup_phase_time + phase_shift
# print(start_vespa)
# print(end_vespa)
# print(taup_phase_time2)
if start_vespa <= taup_phase_time2 <= end_vespa: # time window
if sll <= taup_phase_slowness <= slm: # slowness window
# seconds inside the vespagram
taup_mark = taup_phase_time2 - start_vespa
# store the information
phase_name_info.append(dummy_phase.name)
phase_slowness_info.append(dummy_phase.ray_param_sec_degree)
phase_time_info.append(taup_mark)
# print(phases_info[k])
k += 1
count += 1
# print(phase_name_info)
phase_slowness_info = np.array(phase_slowness_info)
phase_time_info = np.array(phase_time_info)
return phase_name_info, phase_slowness_info, phase_time_info
def migrate(self,plot=False):
import geopy
from geopy.distance import VincentyDistance
'''
This is a rewritten function that combines the functions find_pierce_coor and
migrate_1d so that it's more efficient. Still in testing stages. RM 2/6/16
'''
depth_range = np.arange(50,800,5) #set range of pierce points
value = np.zeros((len(depth_range)))
#geodetic info
bearing = self.az
lon_s = self.ses3d_seismogram.sy
lat_s = 90.0-self.ses3d_seismogram.sx
lon_r = self.ses3d_seismogram.ry
lat_r = 90.0-self.ses3d_seismogram.rx
origin = geopy.Point(lat_s, lon_s)
#find how far away the pierce point is
model = TauPyModel(model='pyrolite_5km')
for i in range(0,len(depth_range)):
phase = 'P'+str(depth_range[i])+'s'
pierce = model.get_pierce_points(self.eq_depth,self.delta_deg,phase_list=[phase])
tt = model.get_travel_times(self.eq_depth,self.delta_deg,phase_list=['P',phase])
#in case there's duplicate phase arrivals
for j in range(0,len(tt)):
if tt[j].name == 'P':
p_arr = tt[j].time
elif tt[j].name == phase:
phase_arr = tt[j].time
#determine value
Pds_time = phase_arr - p_arr
i_start = int((0.0 - self.window_start)/self.ses3d_seismogram.dt)
i_t = int(Pds_time/self.ses3d_seismogram.dt) + i_start
value[i] = self.prf[i_t]
points = pierce[0].pierce
for j in range(0,len(points)):
if points[j]['depth'] == depth_range[i] and points[j]['dist']*(180.0/np.pi) > 20.0:
prc_dist = points[j]['dist']*(180.0/np.pi)
d_km = prc_dist * ((2*np.pi*6371.0/360.0))
destination = VincentyDistance(kilometers=d_km).destination(origin,bearing)
lat = destination[0]
lon = destination[1]
row = {'depth':depth_range[i],'dist':prc_dist,'lat':lat,'lon':lon,'value':value[i]}
self.pierce_dict.append(row)
if plot == True:
plt.plot(value,depth_range)
plt.gca().invert_yaxis()
plt.show()
return value,depth_range
def test_p_ak135(self):
"""
Test P phase arrival against TauP output in in model AK135.
"""
m = TauPyModel(model="ak135")
arrivals = m.get_travel_times(source_depth_in_km=10.0,
distance_in_degree=35.0,
phase_list=["P"])
self._compare_arrivals_with_file(
arrivals, "taup_time_-h_10_-ph_ttall_-deg_35_-mod_ak135")
def test_buried_receiver(self):
"""
Simple test for a buried receiver.
"""
m = TauPyModel(model="iasp91")
arrivals = m.get_travel_times(
source_depth_in_km=10.0, distance_in_degree=90.0,
receiver_depth_in_km=50,
phase_list=["P", "PP", "S"])
self._compare_arrivals_with_file(arrivals, "buried_receivers.txt")
def test_ak135(self):
"""
Test travel times for lots of phases against output from TauP in model
AK135.
"""
m = TauPyModel(model="ak135")
arrivals = m.get_travel_times(source_depth_in_km=10.0,
distance_in_degree=35.0,
phase_list=["ttall"])
self._compare_arrivals_with_file(
arrivals, "taup_time_-h_10_-ph_ttall_-deg_35_-mod_ak135")
def test_p_pwdk(self):
"""
Test P phase arrival against TauP output in model pwdk
with different cache values to test `TauModel.load_from_depth_cache`
"""
for cache in self.caches:
m = TauPyModel(model="pwdk", cache=cache)
arrivals = m.get_travel_times(source_depth_in_km=10.0,
distance_in_degree=35.0,
phase_list=["P"])
self._compare_arrivals_with_file(
arrivals, "taup_time_-h_10_-ph_P_-deg_35_-mod_pwdk")
def test_ppointvsobspytaup_S2P(self):
slowness = 12.33
evdep = 12.4
evdist = 67.7
pp1 = self.model.ppoint_distance(200, slowness, phase="P")
model = TauPyModel(model="iasp91")
arrivals = model.get_ray_paths(evdep, evdist, ("S250p",))
arrival = arrivals[0]
index = np.searchsorted(arrival.path["depth"][::-1], 200)
pdist = arrival.path["dist"]
pp2 = degrees2kilometers((pdist[-1] - pdist[-index - 1]) * 180 / np.pi)
self.assertLess(abs(pp1 - pp2) / pp2, 0.2)
def zero_phase(tr,phase,rf_window=[-10,120],**kwargs):
##############################################################################
'''
Finds predicted PP arrival and zeros a window centered on the arrival
args--------------------------------------------------------------------------
tr: obspy trace
phase: phase to zero
time_start: starting point of receiver function time window
kwargs---------------------------------------------------------------------
window_half_dur : half duration of zero window (default = 2.5 s)
taup_model
'''
window_half_dur = kwargs.get('window_half_dur',2.5)
taup_model = kwargs.get('taup_model','none')
if taup_model == 'none':
taup_model = TauPyModel('prem')
arrs = taup_model.get_travel_times(source_depth_in_km=tr.stats.evdp,
distance_in_degree=tr.stats.gcarc,
phase_list=['P',phase])
print 'arrs = ', arrs
P_arr = 'none'
phase_arr = 'none'
for arr in arrs:
if arr.name == 'P':
P_arr = arr
elif arr.name == phase:
phase_arr = arr
if P_arr == 'none' or phase_arr == 'none':
raise ValueError('problem occured in function "zero_phase", no matching arrivals found')
else:
P_time = P_arr.time
phase_time = phase_arr.time
delay_time = phase_time - P_time
zero_window_center = -1.0*rf_window[0] + delay_time
zero_window_start = zero_window_center - window_half_dur
zero_window_end = zero_window_center + window_half_dur
zero_window_start_index = int(zero_window_start/tr.stats.delta)
zero_window_end_index = int(zero_window_end/tr.stats.delta)
#case 1: entire window is in range
if zero_window_start_index >= 0 and zero_window_end_index <= len(tr.data):
tr.data[zero_window_start_index:zero_window_end_index] = 0.0
#case 2: end of window is out of range
if zero_window_start_index >= 0 and zero_window_end_index >= len(tr.data):
tr.data[zero_window_start_index:] = 0.0
#case 3: entire window is out of range
if zero_window_start_index >= len(tr.data):
print "PP arrives outside the receiver function window"
def test_ak135(self):
"""
Test travel times for lots of phases against output from TauP in model
AK135 with different cache values to test
`TauModel.load_from_depth_cache`
"""
for cache in self.caches:
m = TauPyModel(model="ak135", cache=cache)
arrivals = m.get_travel_times(source_depth_in_km=10.0,
distance_in_degree=35.0,
phase_list=["ttall"])
self._compare_arrivals_with_file(
arrivals, "taup_time_-h_10_-ph_ttall_-deg_35_-mod_ak135")
def test_ppointvsobspytaup_P2S(self):
slowness = 6.28
evdep = 12.4
evdist = 67.7
depth = 200
pp1 = self.model.ppoint_distance(depth, slowness)
model = TauPyModel(model="iasp91")
arrivals = model.get_ray_paths(evdep, evdist, ("P250s",))
arrival = arrivals[0]
index = np.searchsorted(arrival.path["depth"][::-1], depth)
pdist = arrival.path["dist"]
pp2 = degrees2kilometers((pdist[-1] - pdist[-index - 1]) * 180 / np.pi)
self.assertLess(abs(pp1 - pp2) / pp2, 0.1)
def test_single_path_geo_fallback_iasp91(self):
"""
Test the raypath for a single phase given geographical input.
This version of the test checks that things still work when
geographiclib is not installed.
"""
has_geographiclib_real = geodetics.HAS_GEOGRAPHICLIB
geodetics.HAS_GEOGRAPHICLIB = False
filename = os.path.join(DATA,
"taup_path_-o_stdout_-h_10_-ph_P_-deg_35")
expected = np.genfromtxt(filename, comments='>')
m = TauPyModel(model="iasp91")
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
arrivals = m.get_ray_paths_geo(source_depth_in_km=10.0,
source_latitude_in_deg=-80.0,
source_longitude_in_deg=-60.0,
receiver_latitude_in_deg=-45.0,
receiver_longitude_in_deg=-60.0,
phase_list=["P"])
geodetics.HAS_GEOGRAPHICLIB = has_geographiclib_real
assert issubclass(w[-1].category, UserWarning)
self.assertEqual(len(arrivals), 1)
# Interpolate both paths to 100 samples and make sure they are
# approximately equal.
sample_points = np.linspace(0, 35, 100)
interpolated_expected = np.interp(
sample_points,
expected[:, 0],
expected[:, 1])
interpolated_actual = np.interp(
sample_points,
np.round(np.degrees(arrivals[0].path['dist']), 2),
np.round(6371 - arrivals[0].path['depth'], 2))
np.testing.assert_allclose(interpolated_actual, interpolated_expected,
rtol=1E-4, atol=0)
# NB: we do not check path['lat'] and path['lon'] here, as these
# are not calculated when geographiclib is not installed. We check
# that they are not present.
with self.assertRaises(ValueError):
arrivals[0].path["lat"]
with self.assertRaises(ValueError):
arrivals[0].path["lon"]
def find_pierce_coor(self,plot='False'):
import geopy
from geopy.distance import VincentyDistance
'''
given an instance of the receiver function class this function
returns latitude and longitude of all receiver side pierce points
of Pds in a given depth range (the default range is 50 - 800 km)
NOTE:
be careful that ses3d typically uses colatitude, while
this function returns latitude '''
depth_range = np.arange(50,800,5) #set range of pierce points
#geodetic info
bearing = self.az
lon_s = self.ses3d_seismogram.sy
lat_s = 90.0-self.ses3d_seismogram.sx
lon_r = self.ses3d_seismogram.ry
lat_r = 90.0-self.ses3d_seismogram.rx
origin = geopy.Point(lat_s, lon_s)
#find how far away the pierce point is
model = TauPyModel(model='pyrolite_5km')
for i in range(0,len(depth_range)):
phase = 'P'+str(depth_range[i])+'s'
pierce = model.get_pierce_points(self.eq_depth,self.delta_deg,phase_list=[phase])
points = pierce[0].pierce
for j in range(0,len(points)):
if points[j]['depth'] == depth_range[i] and points[j]['dist']*(180.0/np.pi) > 25.0:
prc_dist = points[j]['dist']*(180.0/np.pi)
d_km = prc_dist * ((2*np.pi*6371.0/360.0))
destination = VincentyDistance(kilometers=d_km).destination(origin,bearing)
lat = destination[0]
lon = destination[1]
value = 0
row = {'depth':depth_range[i],'dist':prc_dist,'lat':lat,'lon':lon,'value':value}
self.pierce_dict.append(row)
if plot=='True':
m = Basemap(projection='hammer',lon_0=0)
m.drawmapboundary()
m.drawcoastlines()
m.drawgreatcircle(lon_s,lat_s,lon_r,lat_r,linewidth=1,color='b',alpha=0.5)
for i in range(len(self.pierce_dict)):
x,y = m(self.pierce_dict[i]['lon'],self.pierce_dict[i]['lat'])
m.scatter(x,y,5,marker='o',color='r')
plt.show()
def test_underside_reflections(self):
"""
Tests the calculation of a couple of underside reflection phases.
"""
m = TauPyModel(model="iasp91")
# If an interface that is not in the model is used for a phase name,
# it should snap to the next closest interface. This is reflected in
# the purist name of the arrivals.
arrivals = m.get_travel_times(
source_depth_in_km=10.0, distance_in_degree=90.0,
phase_list=["P", "PP", "P^410P", "P^660P", "P^300P", "P^400P",
"P^500P", "P^600P"])
self._compare_arrivals_with_file(arrivals, "underside_reflections.txt")
def pds_time(evdp,gcarc,depth,model_1d): ################################################################################## ''' Calculates the travel time of a Pds phase based on the spherical travel time equation (e.g., Eager et al. 2010) args-------------------------------------------------------------------------- evdp:event depth gcarc:great circle distance depth:the conversion depth model_1d:velocity model ''' taup_model = TauPyModel(model_1d) p_arrs = taup_model.get_travel_times(evdp,gcarc,['P'])
def plot_expected_arrivals(source_depth, distance, ref_model, phase_list, seislist):
###############################################################################
'''
Plot expected arrival times based on seismic reference model ref_model
ref_model must be a string. source depth in km. distance in degrees.
phase_list is list of phase names you want to plot. seis is a numpy array for
a seismic trace.
See obpy taup manual
'''
model = TauPyModel(model=ref_model)
arrivals = model.get_travel_times(source_depth_in_km=source_depth, \
distance_in_degree=distance)
seis_number = len(seislist)
#seis = seislist
#seis_array = np.loadtxt(seis)
#max_value = seis_array[:,1].max()
arrive_list = str(arrivals).strip().split('\n')
arrive_array = [ii.split() for ii in arrive_list]
phase_dict = dict()
for ii in range(1,len(arrive_array)):
phase_dict[arrive_array[ii][0]] = float(arrive_array[ii][4])
print 'Phases Available: \n'
print phase_dict.keys()
for jj in range(0,len(seislist)):
plt.subplot(seis_number,1,(jj+1))
seis_array = np.loadtxt(seislist[jj])
max_value = seis_array[:,1].max()*0.9
#Remove y lables
ax = plt.gca()
ax.set_yticklabels([])
#Label plot
plt.title(seislist[jj])
plt.xlabel('Seconds')
#change limits
plt.xlim(seis_array[0,0],seis_array[len(seis_array)-1,0])
for ii in phase_list:
plt.axvline(x=phase_dict[ii], ymin=-1.0, ymax = 1.0, \
linewidth=2, color='gold')
plt.text(phase_dict[ii],max_value,ii)
plt.text(0,max_value,'Vel. model '+ref_model)
plt.plot(seis_array[:,0],seis_array[:,1])
plt.show()
def test_many_identically_named_phases(self):
"""
Regression test to make sure obspy.taup works with models that
produce many identically names seismic phases.
"""
with TemporaryWorkingDirectory():
folder = os.path.abspath(os.curdir)
model_name = "smooth_geodynamic_model"
build_taup_model(
filename=os.path.join(DATA, model_name + ".tvel"),
output_folder=folder, verbose=False)
m = TauPyModel(os.path.join(folder, model_name + ".npz"))
arr = m.get_ray_paths(172.8000, 46.762440693494824, ["SS"])
self.assertGreater(len(arr), 10)
def get_travel_times(station, earthquake):
"""
Calculate travel times for phases using obspy.
Return a dictionary with phase name as key and arrival time as the value.
"""
dist = locations2degrees(station[0], station[1],
earthquake[0], earthquake[1])
model = TauPyModel(model='iasp91')
arrivals = model.get_travel_times(source_depth_in_km=earthquake[2],
distance_in_degree=dist)
travel_times = {}
for arrival in arrivals:
travel_times[arrival.name] = arrival.time
return travel_times
def test_arrivals_class(self):
"""
Tests list operations on the Arrivals class.
See #1518.
"""
model = TauPyModel(model='iasp91')
arrivals = model.get_ray_paths(source_depth_in_km=0,
distance_in_degree=1,
phase_list=['Pn', 'PmP'])
self.assertEqual(len(arrivals), 2)
# test copy
self.assertTrue(isinstance(arrivals.copy(), Arrivals))
# test sum
self.assertTrue(isinstance(arrivals + arrivals, Arrivals))
self.assertTrue(isinstance(arrivals + arrivals[0], Arrivals))
# test multiplying
self.assertTrue(isinstance(arrivals * 2, Arrivals))
arrivals *= 3
self.assertEqual(len(arrivals), 6)
self.assertTrue(isinstance(arrivals, Arrivals))
# test slicing
self.assertTrue(isinstance(arrivals[2:5], Arrivals))
# test appending
arrivals.append(arrivals[0])
self.assertEqual(len(arrivals), 7)
self.assertTrue(isinstance(arrivals, Arrivals))
# test assignment
arrivals[0] = arrivals[-1]
self.assertTrue(isinstance(arrivals, Arrivals))
arrivals[2:5] = arrivals[1:4]
self.assertTrue(isinstance(arrivals, Arrivals))
# test assignment with wrong type
with self.assertRaises(TypeError):
arrivals[0] = 10.
with self.assertRaises(TypeError):
arrivals[2:5] = [0, 1, 2]
with self.assertRaises(TypeError):
arrivals.append(arrivals)
# test add and mul with wrong type
with self.assertRaises(TypeError):
arrivals + [2, ]
with self.assertRaises(TypeError):
arrivals += [2, ]
with self.assertRaises(TypeError):
arrivals * [2, ]
with self.assertRaises(TypeError):
arrivals *= [2, ]
def exclude_by_local_catalog(self,catalogue):
model = TauPyModel(model="iasp91")
for tr in self.stream:
tr.detrend('demean')
t_total = 0.0
for trace in self.stream:
t_total += trace.stats.npts
for event in catalogue:
# get origin time
t0 = event.origins[0].time
lon0 = event.origins[0].longitude
lat0 = event.origins[0].latitude
depth0 = event.origins[0].depth/1000.
coords = self.inv.get_coordinates(self.ids[0])
data_start = self.stream[0].stats.starttime
if t0 < data_start-24*60*60.:
continue
data_end = self.stream[-1].stats.endtime
if t0 > data_end:
continue
dist = gps2dist_azimuth(lat0,lon0,
coords["latitude"],coords["longitude"])[0]/1000.
p_arrival = model.get_travel_times(source_depth_in_km=depth0,
distance_in_degree=dist/111.19,phase_list=["P"])
if len(p_arrival)==0:
tcut1 = t0
else:
tcut1 = t0 + p_arrival[0].time - 10.0 #10s before p arrival
if tcut1<t0:
tcut1 = t0
tcut2 = t0 + dist/1.0 + 60. #slowest surface-wave arrival plus one minute
self.stream.cutout(starttime=tcut1,endtime=tcut2)
t_kept = 0.0
for trace in self.stream:
t_kept += trace.stats.npts
print('* Excluded all events in local catalogue.', file=self.ofid)
print('* Lost %g percent of original traces' %((t_total-t_kept)/t_total*100), file=self.ofid)
return()
class Client(object):
def __init__(self, stationinfo, mseeddir, sacdir, model='prem'):
self.mseeddir = mseeddir
self.sacdir = sacdir
self.stations = self._read_stations(stationinfo)
self.model = TauPyModel(model=model)
def _read_stations(self, stationinfo):
"""
Read station information from station metadata file.
Format of station information:
NET.STA latitude longitude elevation
"""
stations = {}
with open(stationinfo, "r") as f:
for line in f:
name, stla, stlo, stel, starttime, endtime = line.split()[0:6]
# handle the time
try:
starttime = UTCDateTime(starttime)
endtime = UTCDateTime(endtime)
except:
starttime = UTCDateTime("20090101")
endtime = UTCDateTime("20500101")
if name not in stations.keys():
station = {
name: [{
"name": name,
"stla": float(stla),
"stlo": float(stlo),
"stel": float(stel) / 1000.0,
"starttime": starttime,
"endtime": endtime
}]
}
stations.update(station)
else:
subdict= {
"name": name,
"stla": float(stla),
"stlo": float(stlo),
"stel": float(stel) / 1000.0,
"starttime": starttime,
"endtime": endtime
}
stations[name].append(subdict)
logger.info("%d stations in database.", len(stations))
return stations
def _get_dirname(self, starttime, endtime):
"""
Get directory names based on starttime and endtime.
"""
# mseed data are stored according to BJT not UTC
starttime_in_bjt = starttime + timedelta(hours=8)
endtime_in_bjt = endtime + timedelta(hours=8)
if starttime_in_bjt.date == endtime_in_bjt.date: # one day
return [starttime_in_bjt.strftime("%Y%m%d")]
else: # two days
return [starttime_in_bjt.strftime("%Y%m%d"),
endtime_in_bjt.strftime("%Y%m%d")]
def _read_mseed(self, station, dirnames, starttime, endtime):
"""
Read waveform in specified time window.
"""
# obtain event waveform
pattern = station['name'] + ".*.*.*.mseed"
if not 1 <= len(dirnames) <= 2: # zero or more than two days
logger.error("Cannot trim waveform duration span %s day(s)",
len(dirnames))
return
# loop over to read all mseed in
st = Stream()
for dirname in dirnames:
mseedname = os.path.join(self.mseeddir, dirname, pattern)
try:
st += read(mseedname)
except FileNotFoundError:
logger.warning("File not exist: %s", mseedname)
except Exception as e:
logger.error("Error in reading: %s", e)
# Merge data
try:
st.merge(fill_value=0)
except Exception:
logger.error("Error in merging %s", station['name'])
return None
# check if st contains data
if not st:
logger.warning("No data for %s", station['name'])
return None
st.trim(starttime, endtime)
return st
def _writesac(self, stream, event, station, outdir):
"""
Write data with SAC format with event and station information.
"""
for trace in stream: # loop over 3-component traces
# transfer obspy trace to sac trace
sac_trace = SACTrace.from_obspy_trace(trace=trace)
# set station related headers
sac_trace.stla = station["stla"]
sac_trace.stlo = station["stlo"]
sac_trace.stel = station["stel"]
if trace.stats.channel[-1] == "E":
sac_trace.cmpaz = 90
sac_trace.cmpinc = 90
elif trace.stats.channel[-1] == "N":
sac_trace.cmpaz = 0
sac_trace.cmpinc = 90
elif trace.stats.channel[-1] == "Z":
sac_trace.cmpaz = 0
sac_trace.cmpinc = 0
else:
logger.warning("Not E|N|Z component")
# set event related headers
sac_trace.evla = event["latitude"]
sac_trace.evlo = event["longitude"]
sac_trace.evdp = event["depth"]
sac_trace.mag = event["magnitude"]
# 1. SACTrace.from_obspy_trace automatically set Trace starttime
# as the reference time of SACTrace, when converting Trace to
# SACTrace. Thus in SACTrace, b = 0.0.
# 2. Set SACTrace.o as the time difference in seconds between
# event origin time and reference time (a.k.a. starttime).
# 3. Set SACTrace.iztype to 'io' change the reference time to
# event origin time (determined by SACTrace.o) and also
# automatically change other time-related headers
# (e.g. SACTrace.b).
# 1.from_obspy_trace
# o
# |
# b----------------------e
# |=> shift <=|
# reftime |
# origin time
#
# 2.sac_trace.o = shift
# o:reset to be zero
# |
# b---------------------e
# | |
# | refer(origin) time
# -shift
sac_trace.o = event["origin"] - sac_trace.reftime
sac_trace.iztype = 'io'
sac_trace.lcalda = True
# SAC file location
sac_flnm = ".".join([event["origin"].strftime("%Y.%j.%H.%M.%S"),
"0000", trace.id, "M", "SAC"])
sac_fullname = os.path.join(outdir, sac_flnm)
sac_trace.write(sac_fullname)
return
def _get_window(self, event, station=None, by_event=None, by_phase=None):
"""
Determin the starttime and endtime
Parameters
----------
event: dict
Contain information of events
station: dict
Contain information of station
"""
if by_event:
starttime = event['origin'] + by_event['start_offset']
endtime = starttime + by_event['duration']
return starttime, endtime
# by phase
dist = locations2degrees(event["latitude"], event["longitude"],
station["stla"], station["stlo"])
start_ref_phase = by_phase['start_ref_phase']
end_ref_phase = by_phase['end_ref_phase']
start_offset = by_phase['start_offset']
end_offset = by_phase['end_offset']
# TauPyModel.get_travel_times always return sorted value
start_arrivals = self.model.get_travel_times(
source_depth_in_km=event['depth'],
distance_in_degree=dist,
phase_list=start_ref_phase)
if not start_arrivals: # no phase avaiable, skip this data
return None, None # starttime and endtime are None
end_arrivals = model.get_travel_times(
source_depth_in_km=event['depth'],
distance_in_degree=dist,
phase_list=end_ref_phase)
# determine starttime and endtime
starttime = event['origin'] + start_arrivals[0].time + start_offset
endtime = event['origin'] + end_arrivals[-1].time + end_offset
return starttime, endtime
def get_waveform(self, event, by_event=None, by_phase=None, epicenter=None):
"""
Trim waveform from dataset of CGRM
Parameters
----------
event: dict
Event information container
by_event: dict
Determine waveform window by event origin time
by_phase: dict
Determine waveform window by phase arrival times
epicenter: dict
Select station location
"""
# check the destination
eventdir = event['origin'].strftime("%Y%m%d%H%M%S")
outdir = os.path.join(self.sacdir, eventdir)
if not os.path.exists(outdir):
os.makedirs(outdir, exist_ok=True)
if by_event:
starttime, endtime = self._get_window(event=event,
by_event=by_event)
dirnames = self._get_dirname(starttime, endtime)
logger.debug("dirnames: %s", dirnames)
# loop over all stations
for key, stationlist in self.stations.items():
station = find_station(stationlist, event['origin'])
logger.debug("station: %s", key)
if not by_event:
starttime, endtime = self._get_window(event=event,
station=station,
by_phase=by_phase)
dirnames = self._get_dirname(starttime, endtime)
logger.debug("dirnames: %s", dirnames)
if epicenter:
dist = locations2degrees(event["latitude"], event["longitude"],
station["stla"], station["stlo"])
if dist < epicenter['minimum'] or dist > epicenter['maximum']:
continue
st = self._read_mseed(station, dirnames, starttime, endtime)
if not st:
continue
self._writesac(st, event, station, outdir)
client = Client("IRIS")
cat = client.get_events(starttime=UTCDateTime(2004, 1, 1, 0, 0, 0),
endtime=UTCDateTime(2016, 4, 30, 23, 59, 59),
latitude=36.80060501882054,
longitude=137.6569971141782,
mindepth=60,
minmagnitude=6,
minradius=30,
maxradius=90)
print(cat)
# Calculate travel time for the accurate picking of onset from teleseismic waveform
p_tttable = []
s_tttable = []
sta_lat, sta_long = 35.5038, 136.7939 # latitude and longitude of specified station (N.TKTH)
model = TauPyModel(model="iasp91")
for i in range(len(cat)):
distance = locations2degrees(sta_lat, sta_long, cat[i].origins[0].latitude,
cat[i].origins[0].longitude)
parrivals = model.get_travel_times(
source_depth_in_km=cat[i].origins[0].depth / 1000,
distance_in_degree=distance,
phase_list=['P'])
sarrivals = model.get_travel_times(
source_depth_in_km=cat[i].origins[0].depth / 1000,
distance_in_degree=distance,
phase_list=['S'])
p_time = parrivals[0].time
s_time = sarrivals[0].time
p_tttable.append(p_time)
s_tttable.append(s_time)
relative_ptimes = [
5.831, 65.7839, 5.4050, 67.8967, 5.3254, 6.5378, 5.7208, 63.1667, 5.8395,
5.9275, 5.8311, 5.825, 5.66964, 5.22, 5.39
]
rootpath = '/Users/dmelgar/Amatrice2016/strong_motion/sac/'
lonlat = genfromtxt(
'/Users/dmelgar/Amatrice2016/strong_motion/stations/latest.sta',
usecols=[1, 2])
station_catalogue = genfromtxt(
'/Users/dmelgar/Amatrice2016/strong_motion/stations/latest.sta',
usecols=[0],
dtype='S')
#velmod = TauPyModel(model="/Users/dmelgar/FakeQuakes/Cascadia/structure/cascadia")
velmod = TauPyModel(model='aci')
predictedP = 9999 * ones(len(stations))
#Get predicted arrivals
for ksta in range(len(stations)):
st = read(rootpath + stations[ksta] + '.HNZ.sac')
#Find coordinates
i = where(station_catalogue == stations[ksta])[0]
lon_sta = lonlat[i, 0]
lat_sta = lonlat[i, 1]
deg = locations2degrees(lon_sta, lat_sta, epicenter[0], epicenter[1])
arrivals = velmod.get_travel_times(source_depth_in_km=epicenter[2],
distance_in_degree=deg,
phase_list=['P', 'Pn', 'p'])
from bqmail.query import Query
from obspy import UTCDateTime
from obspy.taup import TauPyModel
from obspy.clients.iris import Client
import smtplib
from email.mime.text import MIMEText
from email.header import Header
from .distaz import distaz
model = TauPyModel()
cld = Client()
def connectsmtp(server, port, sender, password):
smtpObj = smtplib.SMTP_SSL(server, port)
smtpObj.login(sender, password)
return smtpObj
def loginmail(sender, server='localhost', password='', port=465, test_num=5):
test_it = 1
while test_it <= test_num:
if test_it > 1:
print('Try to link to {} in {} times'.format(server, test_it))
try:
smtpObj = connectsmtp(server, port, sender, password)
except:
test_it += 1
continue
else:
break
if test_it > test_num:
from obspy.taup import TauPyModel
import matplotlib.pyplot as plt
import os.path
import glob
import numpy as np
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
import math
from skimage import measure
from skimage.draw import ellipsoid
from geographiclib.geodesic import Geodesic as geo
from scipy.interpolate import interp1d
from mpl_toolkits.mplot3d.axes3d import Axes3D
from mpl_toolkits.mplot3d import proj3d
taupmodel = TauPyModel(
model='ak135'
) # Could change to AK135 to setup in accordance with BBAFRP19
# from matplotlib import rc
# rc('font',size=28)
# rc('font',family='serif')
# rc('axes',labelsize=32)
sys.path.append(home + '/Google_Drive/GITHUB_AB/3D_corrections/PLOTTING')
import Africa_BBAFRP19
def init_model_BBAFRP19():
# Read crustal and mantle models
global mod
mod = Africa_BBAFRP19.BBAFRP19_model()
#sta='LUTZ'
#lonsta=-121.8652
#latsta= 37.2869
#sta='MILP'
#lonsta=-121.8340
#latsta=37.4491
path = '/Users/dmelgar/FakeQuakes/M6_validation_pwave/output/waveforms/M6.000000/'
#taup
zs = 8.0
g = Geod(ellps='WGS84')
azimuth, baz, dist = g.inv(-121.753508, 37.332028, lonsta, latsta)
dist_in_degs = kilometer2degrees(dist / 1000.)
velmod = TauPyModel(
'/Users/dmelgar/FakeQuakes/M6_validation_pwave/structure/bbp_norcal.npz')
Ppaths = velmod.get_ray_paths(zs, dist_in_degs, phase_list=['P', 'p'])
p = Ppaths[0].time
Spaths = velmod.get_ray_paths(zs, dist_in_degs, phase_list=['S', 's'])
s = Spaths[0].time
nlf = read(path + sta + '.LYN.sac')
elf = read(path + sta + '.LYE.sac')
zlf = read(path + sta + '.LYZ.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')
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = (13, 8) if False else (10, 6)
from obspy.taup.taup import getTravelTimes
from obspy.core.util.geodetics import gps2DistAzimuth
from obspy.taup import TauPyModel
from seismon.eqmon import ampRf, shoot
degrees = np.linspace(1, 180, 180)
distances = degrees * (np.pi / 180) * 6370000
depths = np.linspace(1, 100, 100)
model = TauPyModel(model="iasp91")
#model = TauPyModel(model="1066a")
fwd = 0
back = 0
eqlat, eqlon = 35.6895, 139.6917
GPS = 0
magnitude = 6.0
depth = 20.0
Rf0 = 76.44
Rfs = 1.37
cd = 440.68
rs = 1.57
relative_ptimes = [
5.831, 65.7839, 5.4050, 67.8967, 5.3254, 6.5378, 5.7208, 63.1667, 5.8395,
5.9275, 5.8311, 5.825, 5.66964
]
rootpath = '/Users/dmelgar/Amatrice2016/strong_motion/sac/'
lonlat = genfromtxt(
'/Users/dmelgar/Amatrice2016/strong_motion/stations/latest.sta',
usecols=[1, 2])
station_catalogue = genfromtxt(
'/Users/dmelgar/Amatrice2016/strong_motion/stations/latest.sta',
usecols=[0],
dtype='S')
#velmod = TauPyModel(model="/Users/dmelgar/FakeQuakes/Cascadia/structure/cascadia")
velmod = TauPyModel()
lon_grid = arange(13.17, 13.37, 0.01)
lat_grid = arange(42.68, 42.75, 0.01)
z_grid = arange(2, 10, 0.5)
Npts = len(lon_grid) * len(lat_grid) * len(z_grid) * len(time_offsets) * len(
stations)
predictedP = ones((Nsta, Npts)) * 9999
arrival_times = zeros((Nsta, Npts))
error = zeros((Nsta, Npts))
lon_out = zeros(Npts)
lat_out = zeros(Npts)
z_out = zeros(Npts)
offsets_out = zeros(Npts)
def main(fnam_nd: str,
times: tuple,
phase_list=("P", "S"),
depth=40.,
plot_rays=False):
"""
Compute distance of an event, given S-P time
:param fnam_nd: name of TauP compatible model file
:param times: list of S-P time
:param phase_list: list of phases between which the time difference is measured (usually P and S)
:param depth: assumed depth of event
:param plot_rays: create a plot with the ray paths
"""
fnam_npz = "./taup_tmp/" \
+ psplit(fnam_nd)[-1][:-3] + ".npz"
build_taup_model(fnam_nd, output_folder="./taup_tmp")
cache = OrderedDict()
model = TauPyModel(model=fnam_npz, cache=cache)
if plot_rays:
fig, ax = plt.subplots(1, 1)
for itime, tSmP in enumerate(times):
dist = get_dist(model, tSmP=tSmP, depth=depth, phase_list=phase_list)
if dist is None:
print(f"{fnam_nd}, S-P time: {tSmP:5.1f}: NO SOLUTION FOUND!")
else:
print(f"{fnam_nd}, S-P time: {tSmP:5.1f}, "
f"taup_distance: {dist:5.1f}")
if plot_rays:
if dist is None:
ax.plot((-200), (-200),
label="%4.1f sec, NO SOLUTION" % (tSmP),
c="white",
lw=0.0)
else:
arrivals = model.get_ray_paths(distance_in_degree=dist,
source_depth_in_km=depth,
phase_list=["P", "S"])
RADIUS_MARS = 3389.5
already_plotted = dict(P=False, S=False)
ls = dict(P="solid", S="dashed")
label = dict(P="%4.1f sec, %5.1f°" % (tSmP, dist), S=None)
for arr in arrivals:
if not already_plotted[arr.name]:
already_plotted[arr.name] = True
x = (RADIUS_MARS - arr.path["depth"]) * \
np.sin(arr.path["dist"])
y = (RADIUS_MARS - arr.path["depth"]) * \
np.cos(arr.path["dist"])
ax.plot(x,
y,
c="C%d" % itime,
ls=ls[arr.name],
label=label[arr.name],
lw=1.2)
if plot_rays:
for layer_depth in model.model.get_branch_depths(
): # (0, 10, 50, 1000,
# 1500):
angles = np.linspace(0, 2 * np.pi, 1000)
x_circle = (RADIUS_MARS - layer_depth) * np.sin(angles)
y_circle = (RADIUS_MARS - layer_depth) * np.cos(angles)
ax.plot(x_circle, y_circle, c="k", ls="dashed", lw=0.5, zorder=-1)
for layer_depth in (model.model.cmb_depth, 0.0):
angles = np.linspace(0, 2 * np.pi, 1000)
x_circle = (RADIUS_MARS - layer_depth) * np.sin(angles)
y_circle = (RADIUS_MARS - layer_depth) * np.cos(angles)
ax.plot(x_circle, y_circle, c="k", ls="solid", lw=1.0)
# for layer_depth in [1100.0]:
# angles = np.linspace(0, 2 * np.pi, 1000)
# x_circle = (RADIUS_MARS - layer_depth) * np.sin(angles)
# y_circle = (RADIUS_MARS - layer_depth) * np.cos(angles)
# ax.plot(x_circle, y_circle, c="k", ls="dotted", lw=0.3)
ax.set_xlim(-100, RADIUS_MARS + 100)
ax.set_ylim(1000, RADIUS_MARS + 100)
ax.set_xlabel("radius / km")
ax.set_ylabel("radius / km")
ax.set_title("Ray path for model %s" % fnam_nd)
ax.set_aspect("equal", "box")
ax.legend(loc="lower left")
plt.show()
tempdata = par['tempdata']
#phasesl = phasel.split(',')
#ndep = 96
#ndis = 111
dep = np.linspace(mindep, maxdep, ndep)
dis = np.linspace(mindis, maxdis, ndis)
filetele = './tables/' + firstarrtt
#filepcp = './tables/'+cmbreftt
if os.path.isfile(filetele):
telep = np.load(filetele)
# pcpdp = np.load(filepcp)
else:
print('constructing tt table')
from obspy.taup import TauPyModel
mod = TauPyModel(model='ak135')
telep = np.zeros((ndep, ndis))
# pcpdp = np.zeros((ndep,ndis))
for ii in range(ndep):
for jj in range(ndis):
arr = mod.get_travel_times(source_depth_in_km=dep[ii],
distance_in_degree=dis[jj],
phase_list=phasesl)
#pcpdp[ii,jj] = arr[-1].time-arr[0].time
telep[ii, jj] = arr[0].time
np.save(filetele, telep)
ftelep = interpolate.interp2d(dis, dep, telep, kind='linear')
#fpcpdp = interpolate.interp2d(dis, dep, pcpdp, kind='linear')
#pPdP = np.load('./tables/teleP50to600.npy')
#ndep = 551
def __init__(self, sta, event, gacmin=30., gacmax=90., phase='P'):
from obspy.geodetics.base import gps2dist_azimuth as epi
from obspy.geodetics import kilometer2degrees as k2d
from obspy.taup import TauPyModel
# Extract event 4D parameters
self.time = event.origins[0].time
self.lon = event.origins[0].longitude
self.lat = event.origins[0].latitude
self.dep = event.origins[0].depth
# Check if depth is valid type
if self.dep is not None:
if self.dep > 1000.:
self.dep = self.dep / 1000.
else:
self.dep = 10.
# Magnitude
self.mag = event.magnitudes[0].mag
if self.mag is None:
self.mag = -9.
# Calculate epicentral distance
self.epi_dist, self.az, self.baz = epi(self.lat, self.lon,
sta.latitude, sta.longitude)
self.epi_dist /= 1000
self.gac = k2d(self.epi_dist)
if self.gac > gacmin and self.gac < gacmax:
# Get travel time info
tpmodel = TauPyModel(model='iasp91')
# Get Travel times (Careful: here dep is in meters)
arrivals = tpmodel.get_travel_times(distance_in_degree=self.gac,
source_depth_in_km=self.dep,
phase_list=[phase])
if len(arrivals) > 1:
print("arrival has many entries: ", len(arrivals))
elif len(arrivals) == 0:
print("no arrival found")
self.accept = False
return
arrival = arrivals[0]
# Attributes from parameters
self.ttime = arrival.time
self.slow = arrival.ray_param_sec_degree / 111.
self.inc = arrival.incident_angle
self.phase = phase
self.accept = True
else:
self.ttime = None
self.slow = None
self.inc = None
self.phase = None
self.accept = False
# Defaults for non - station-event geometry attributes
self.vp = 6.0
self.vs = 3.5
self.align = 'ZRT'
# Attributes that get updated as analysis progresses
self.rotated = False
self.snr = None
self.snrh = None
self.cc = None
transform=transform,
zorder=10,
fontsize=8,
color='red')
# print out the filters that have been used
plt.text(0, DURATION * 1.05, filtertext1)
plt.text(0, DURATION * 1.07, filtertext2)
# Print the coloured phases over the seismic section
textlist = [] # list of text on plot, to avoid over-writing
for j, color in enumerate(COLORS):
phase = PHASES[j]
x = []
y = []
model = TauPyModel(model=MODEL)
for dist in range(
MIN_DIST, MAX_DIST + 1,
1): # calculate and plot one point for each degree from 0-180
arrivals = model.get_travel_times(source_depth_in_km=EVT_Z,
distance_in_degree=dist,
phase_list=[phase])
printed = False
for i in range(len(arrivals)):
instring = str(arrivals[i])
phaseline = instring.split(" ")
if phaseline[0] == phase and printed == False and int(
dist) > 0 and int(dist) < 180 and float(
phaseline[4]) > 0 and float(
phaseline[4]) < DURATION:
x.append(int(dist))
Last Modified : Mon 17 Apr 2017 05:02:10 PM EDT
Created By : Samuel M. Haugland
==============================================================================
'''
import numpy as np
from matplotlib import pyplot as plt
from subprocess import call
from os import listdir
import h5py
import obspy
import seispy
from obspy.taup import TauPyModel
model = TauPyModel(model='prem50')
def main():
homedir = '/home/samhaug/work1/SP_brazil_sims/SVaxi/full_shareseismos/shareseismos/'
prem_st = read_prem(homedir)
fig, ax = setup_figure()
thickness_compare(homedir, prem_st, ax[0][0])
dvs_compare(homedir, prem_st, ax[1][0])
dvp_compare(homedir, prem_st, ax[1][1])
drho_compare(homedir, prem_st, ax[0][1])
angle_compare(homedir, prem_st, ax[0][2])
dist_compare(homedir, prem_st, ax[1][2])
plt.figtext(0.3, 0.93, '(a)', size=10)
#!/usr/bin/env python
import h5py
import numpy as np
import obspy
from geopy.distance import great_circle
from obspy.taup import TauPyModel
model = TauPyModel(model="prem")
from matplotlib import pyplot as plt
import glob
def read_ed_list():
dir_list = glob.glob('*PKIKP')
ed_list = []
for ii in dir_list:
f = h5py.File(ii + '/Processed/env.h5', 'r')
env = f['env'][...]
num = f['num'][...]
ed_list.append([env, num])
f.close()
return ed_list
def sum_env(ed_list):
def matrix_sum(ed_list):
norm = np.zeros(ed_list[0][0].shape)
for ii in ed_list:
num = np.flipud(ii[1][:, 1])
env = ii[0].copy()
for jj in range(0, env.shape[0]):
def pro5stack(eq_file,
plot_scale_fac=0.05,
slowR_lo=-0.1,
slowR_hi=0.1,
slow_delta=0.0005,
start_buff=-50,
end_buff=50,
ref_lat=36.3,
ref_lon=138.5,
envelope=1,
plot_dyn_range=1000,
log_plot=1,
norm=1,
global_norm_plot=1,
color_plot=1,
fig_index=401,
ARRAY=0):
#%% Import functions
import obspy
import obspy.signal
from obspy import UTCDateTime
from obspy import Stream, Trace
from obspy import read
from obspy.geodetics import gps2dist_azimuth
import numpy as np
import os
from obspy.taup import TauPyModel
import obspy.signal as sign
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
model = TauPyModel(model='iasp91')
from scipy.signal import hilbert
import math
import time
# import sys # don't show any warnings
# import warnings
print('Running pro5a_stack')
#%% Get saved event info, also used to name files
start_time_wc = time.time()
if ARRAY == 0:
file = open(eq_file, 'r')
elif ARRAY == 1:
file = open('EvLocs/' + eq_file, 'r')
lines = file.readlines()
split_line = lines[0].split()
# ids.append(split_line[0]) ignore label for now
t = UTCDateTime(split_line[1])
date_label = split_line[1][0:10]
ev_lat = float(split_line[2])
ev_lon = float(split_line[3])
ev_depth = float(split_line[4])
#if not sys.warnoptions:
# warnings.simplefilter("ignore")
#%% Get station location file
if ARRAY == 0: # Hinet set and center
sta_file = '/Users/vidale/Documents/GitHub/Array_codes/Files/hinet_sta.txt'
ref_lat = 36.3
ref_lon = 138.5
elif ARRAY == 1: # LASA set and center
sta_file = '/Users/vidale/Documents/GitHub/Array_codes/Files/LASA_sta.txt'
ref_lat = 46.69
ref_lon = -106.22
else: # NORSAR set and center if 2
sta_file = '/Users/vidale/Documents/GitHub/Array_codes/Files/NORSAR_sta.txt'
ref_lat = 61
ref_lon = 11
with open(sta_file, 'r') as file:
lines = file.readlines()
print(str(len(lines)) + ' stations read from ' + sta_file)
# Load station coords into arrays
station_index = range(len(lines))
st_names = []
st_lats = []
st_lons = []
for ii in station_index:
line = lines[ii]
split_line = line.split()
st_names.append(split_line[0])
st_lats.append(split_line[1])
st_lons.append(split_line[2])
#%% Name file, read data
# date_label = '2018-04-02' # date for filename
if ARRAY == 0:
fname = 'HD' + date_label + 'sel.mseed'
elif ARRAY == 1:
fname = 'Pro_Files/HD' + date_label + 'sel.mseed'
st = Stream()
print('reading ' + fname)
st = read(fname)
print('Read in: ' + str(len(st)) + ' traces')
nt = len(st[0].data)
dt = st[0].stats.delta
print('First trace has : ' + str(nt) + ' time pts, time sampling of ' +
str(dt) + ' and thus duration of ' + str((nt - 1) * dt))
#%% Build Stack arrays
stack = Stream()
tr = Trace()
tr.stats.delta = dt
tr.stats.network = 'stack'
tr.stats.channel = 'BHZ'
slow_n = int(1 +
(slowR_hi - slowR_lo) / slow_delta) # number of slownesses
stack_nt = int(1 + ((end_buff - start_buff) / dt)) # number of time points
# In English, stack_slows = range(slow_n) * slow_delta - slowR_lo
a1 = range(slow_n)
stack_slows = [(x * slow_delta + slowR_lo) for x in a1]
print(str(slow_n) + ' slownesses.')
tr.stats.starttime = t + start_buff
tr.data = np.zeros(stack_nt)
done = 0
for stack_one in stack_slows:
tr1 = tr.copy()
tr1.stats.station = str(int(done))
stack.extend([tr1])
done += 1
# stack.append([tr])
# stack += tr
# Only need to compute ref location to event distance once
ref_distance = gps2dist_azimuth(ev_lat, ev_lon, ref_lat, ref_lon)
#%% Select traces by distance, window and adjust start time to align picked times
done = 0
for tr in st: # traces one by one, find lat-lon by searching entire inventory. Inefficient but cheap
for ii in station_index:
if ARRAY == 0: # for hi-net, have to chop off last letter, always 'h'
this_name = st_names[ii]
this_name_truc = this_name[0:5]
name_truc_cap = this_name_truc.upper()
elif ARRAY == 1:
name_truc_cap = st_names[ii]
if (tr.stats.station == name_truc_cap
): # find station in inventory
if norm == 1:
tr.normalize()
# tr.normalize(norm= -len(st)) # mystery command or error
stalat = float(st_lats[ii])
stalon = float(
st_lons[ii]) # look up lat & lon again to find distance
distance = gps2dist_azimuth(
stalat, stalon, ev_lat,
ev_lon) # Get traveltimes again, hard to store
tr.stats.distance = distance[0] # distance in m
del_dist = (ref_distance[0] - distance[0]) / (1000) # in km
# ALSO NEEDS distance station - hypocenter calculation
#isolate components of distance in radial and transverse directions, ref_distR & ref_distT
# FIX ref_distR = distance*cos(azi-backazi)
# FIX ref_distT = distance*sin(azi-backazi)
# for(k=0;k<nslow;k++){
# slow = 110.*(LOWSLOW + k*DELTASLOW);
for slow_i in range(
slow_n): # for this station, loop over slownesses
time_lag = -del_dist * stack_slows[
slow_i] # time shift due to slowness, flipped to match 2D
# start_offset = tr.stats.starttime - t
# time_correction = (start_buff - (start_offset + time_lag))/dt
time_correction = ((t - tr.stats.starttime) +
(time_lag + start_buff)) / dt
# print('Time lag ' + str(time_lag) + ' for slowness ' + str(stack_slows[slow_i]) + ' and distance ' + str(del_dist) + ' time sample correction is ' + str(time_correction))
for it in range(stack_nt): # check points one at a time
it_in = int(it + time_correction)
if it_in >= 0 and it_in < nt - 1: # does data lie within seismogram?
stack[slow_i].data[it] += tr[it_in]
done += 1
if done % 50 == 0:
print('Done stacking ' + str(done) + ' out of ' +
str(len(st)) + ' stations.')
#%% Plot traces
global_max = 0
for slow_i in range(
slow_n): # find global max, and if requested, take envelope
if len(stack[slow_i].data) == 0:
print('%d data has zero length ' % (slow_i))
if envelope == 1 or color_plot == 1:
stack[slow_i].data = np.abs(hilbert(stack[slow_i].data))
local_max = max(abs(stack[slow_i].data))
if local_max > global_max:
global_max = local_max
if global_max <= 0:
print('global_max ' + str(global_max) + ' slow_n ' + str(slow_n))
# create time axis (x-axis), use of slow_i here is arbitrary, oops
ttt = (np.arange(len(stack[slow_i].data)) * stack[slow_i].stats.delta +
(stack[slow_i].stats.starttime - t)) # in units of seconds
# Plotting
if color_plot == 1: # 2D color plot
stack_array = np.zeros((slow_n, stack_nt))
# stack_array = np.random.rand(int(slow_n),int(stack_nt)) # test with random numbers
min_allowed = global_max / plot_dyn_range
if log_plot == 1:
for it in range(stack_nt): # check points one at a time
for slow_i in range(
slow_n): # for this station, loop over slownesses
num_val = stack[slow_i].data[it]
if num_val < min_allowed:
num_val = min_allowed
stack_array[
slow_i,
it] = math.log10(num_val) - math.log10(min_allowed)
else:
for it in range(stack_nt): # check points one at a time
for slow_i in range(
slow_n): # for this station, loop over slownesses
stack_array[slow_i,
it] = stack[slow_i].data[it] / global_max
y, x = np.mgrid[slice(stack_slows[0], stack_slows[-1] + slow_delta,
slow_delta),
slice(ttt[0], ttt[-1] + dt,
dt)] # make underlying x-y grid for plot
# y, x = np.mgrid[ stack_slows , time ] # make underlying x-y grid for plot
plt.close(fig_index)
fig, ax = plt.subplots(1, figsize=(9, 2))
fig.subplots_adjust(bottom=0.3)
# c = ax.pcolormesh(x, y, stack_array, cmap=plt.cm.gist_yarg)
# c = ax.pcolormesh(x, y, stack_array, cmap=plt.cm.gist_rainbow_r)
c = ax.pcolormesh(x, y, stack_array, cmap=plt.cm.binary)
ax.axis([x.min(), x.max(), y.min(), y.max()])
fig.colorbar(c, ax=ax)
plt.figure(fig_index, figsize=(6, 8))
plt.close(fig_index)
else: # line plot
for slow_i in range(slow_n):
dist_offset = stack_slows[slow_i] # in units of slowness
if global_norm_plot != 1:
plt.plot(
ttt,
stack[slow_i].data * plot_scale_fac /
(stack[slow_i].data.max() - stack[slow_i].data.min()) +
dist_offset,
color='black')
else:
plt.plot(ttt,
stack[slow_i].data * plot_scale_fac /
(global_max - stack[slow_i].data.min()) + dist_offset,
color='black')
plt.ylim(slowR_lo, slowR_hi)
plt.xlim(start_buff, end_buff)
plt.xlabel('Time (s)')
plt.ylabel('Slowness (s/km)')
plt.title(date_label)
plt.show()
#%% Save processed files
print('Stack has ' + str(len(stack)) + ' traces')
if ARRAY == 0:
fname = 'HD' + date_label + '_1dstack.mseed'
elif ARRAY == 1:
fname = 'Pro_Files/HD' + date_label + '_1dstack.mseed'
stack.write(fname, format='MSEED')
elapsed_time_wc = time.time() - start_time_wc
print('This job took ' + str(elapsed_time_wc) + ' seconds')
os.system('say "Done"')
import numpy as np
import scipy.signal
import copy
import numexpr as npr
import obspy
import os
import matplotlib.pylab as plb
import matplotlib.pyplot as plt
from obspy.taup import TauPyModel
import warnings
from numba import jit
# from pyproj import Geod
#
# geodist = Geod(ellps='WGS84')
taupmodel = TauPyModel(model="iasp91")
stretchbackdatafname='./strechback.data'
def _gaussFilter( dt, nft, f0 ):
"""
Compute a gaussian filter in the freq domain which is unit area in time domain
private function for IterDeconv
================================================================================
Input:
dt - sampling time interval
nft - number freq points
f0 - width of filter
Output:
gauss - Gaussian filter array (numpy)
filter has the form: exp( - (0.5*w/f0)^2 ) the units of the filter are 1/s
def test_deep_source(self):
# Regression test -- check if deep sources are ok
model = TauPyModel("ak135")
arrivals = model.get_ray_paths(2000.0, 60.0, ["P"])
assert abs(arrivals[0].time - 480.32) < 1e-2
def dump_picks(event_log,vel_model,gf_list,out_file):
'''
Dump P and S picks to a file
'''
from obspy.taup import TauPyModel
from obspy.geodetics.base import gps2dist_azimuth
from obspy.geodetics import locations2degrees
from numpy import genfromtxt,zeros,array,ones
from string import replace
#Read station locations
sta=genfromtxt(gf_list,usecols=0,dtype='S')
lonlat=genfromtxt(gf_list,usecols=[1,2])
#Load velocity model for ray tracing
velmod = TauPyModel(vel_model)
# Get hypocenter
f=open(event_log,'r')
loop_go=True
while loop_go:
line=f.readline()
if 'Hypocenter (lon,lat,z[km])' in line:
s=replace(line.split(':')[-1],'(','')
s=replace(s,')','')
hypo=array(s.split(',')).astype('float')
loop_go=False
#compute station to hypo distances
d=zeros(len(lonlat))
for k in range(len(lonlat)):
d[k],az,baz=gps2dist_azimuth(lonlat[k,1],lonlat[k,0],hypo[1],hypo[0])
d[k]=d[k]/1000
f=open(out_file,'w')
f.write('# sta,lon,lat,ptime(s),stime(s)\n')
for k in range(len(sta)):
# Ray trace
deg=locations2degrees(hypo[1],hypo[0],lonlat[k,1],lonlat[k,0])
try:
arrivals = velmod.get_travel_times(source_depth_in_km=hypo[2],distance_in_degree=deg,phase_list=['P','Pn','S','Sn','p','s'])
except:
arrivals = velmod.get_travel_times(source_depth_in_km=hypo[2]-1.056,distance_in_degree=deg,phase_list=['P','Pn','S','Sn','p','s'])
ptime=1e6
stime=1e6
#Determine P and S arrivals
for kphase in range(len(arrivals)):
if 'P' == arrivals[kphase].name or 'p' == arrivals[kphase].name or 'Pn' == arrivals[kphase].name:
if arrivals[kphase].time<ptime:
ptime=arrivals[kphase].time
if 'S' == arrivals[kphase].name or 's' == arrivals[kphase].name or 'Sn' == arrivals[kphase].name:
if arrivals[kphase].time<stime:
stime=arrivals[kphase].time
lon=lonlat[k,0]
lat=lonlat[k,1]
station=sta[k]
line='%s\t%.4f\t%.4f\t%10.4f\t%10.4f\n' % (station,lon,lat,ptime,stime)
f.write(line)
f.close()
def fetch_rf_data(network, location, channel, data_directory, output_units,
minimum_magnitude, maximum_magnitude, station):
# Track execution time for logging purposes
t1 = time.time()
ntwk = network
stat = station
loc = location
chan = channel
# Define the client that hosts the desired data
client = Client("IRIS")
# Define directory where seismic data will be saved as SAC files
if output_units == 'counts':
sac_dir = data_directory + ntwk + '/' + stat + '/' + loc + '/RFQUAKES_COUNTS/'
elif output_units == 'displacement':
sac_dir = data_directory + ntwk + '/' + stat + '/' + loc + '/RFQUAKES_DISP/'
elif output_units == 'velocity':
sac_dir = data_directory + ntwk + '/' + stat + '/' + loc + '/RFQUAKES_VEL/'
elif output_units == 'acceleration':
sac_dir = data_directory + ntwk + '/' + stat + '/' + loc + '/RFQUAKES_ACC/'
else:
print(
'ERROR: Invalid output units. Acceptable options are \'displacement,\' \'velocity,\' or \'counts\''
)
quit()
# For now: delete the directory if it exists...
if os.path.exists(sac_dir):
print('Directory exists. Terminiating process...')
quit()
# shutil.rmtree(sac_dir)
if not os.path.exists(sac_dir):
os.makedirs(sac_dir)
# Define amount of data desired (minutes)
duration = 60
# Log potential errors to a .log file
logFileName = sac_dir + ntwk + '.' + stat + '.log'
# Fetch station information for data retrieval
if loc == "NULL":
loc = ""
try:
inv = client.get_stations(network=ntwk,
station=stat,
channel=chan,
level="response")
except Exception as error:
with open(logFileName, "a") as log:
log.write(str(error))
log.write(
'Error fetching station information with the IRIS client...'
)
return
else:
try:
inv = client.get_stations(network=ntwk,
station=stat,
loc=loc,
channel=chan,
level="response")
except Exception as error:
with open(logFileName, "a") as log:
log.write(str(error))
log.write(
'Error fetching station information with the IRIS client...'
)
return
# Save the pole zero files
nstats = len(inv.networks[0])
resp_t0 = []
resp_tf = []
pre_filt = []
for i in range(0, nstats):
nresp = len(inv.networks[0].stations[i].channels)
# Tag the PZ files and SAC files with a number indicating the period of operation
for j in range(0, nresp):
fileName = sac_dir + "SAC_PZs_" + ntwk + '_' + stat + '_' + inv.networks[0].stations[i].channels[j].code + \
'.' + str(j)
with open(fileName, "a") as pzFile:
pzFile.write('* **********************************\n')
pzFile.write('* NETWORK (KNETWK): ' + inv.networks[0].code +
'\n')
pzFile.write('* STATION (KSTNM): ' +
inv.networks[0].stations[i].code + '\n')
pzFile.write(
'* LOCATION (KHOLE): ' +
inv.networks[0].stations[i].channels[j].location_code +
'\n')
pzFile.write('* CHANNEL (KCMPNM): ' +
inv.networks[0].stations[i].channels[j].code +
'\n')
pzFile.write('* CREATED : ' +
str(UTCDateTime.now()).split('.')[0] + '\n')
pzFile.write('* START : ' +
str(inv.networks[0].stations[i].channels[j].
start_date).split('.')[0] + '\n')
pzFile.write('* END : ' +
str(inv.networks[0].stations[i].channels[j].
end_date).split('.')[0] + '\n')
pzFile.write('* DESCRIPTION : ' +
inv.networks[0].stations[i].site.name + '\n')
pzFile.write('* LATITUDE : %0.6f\n' %
inv.networks[0].stations[i].latitude)
pzFile.write('* LONGITUDE : %0.6f\n' %
inv.networks[0].stations[i].longitude)
pzFile.write('* ELEVATION : %0.1f\n' %
inv.networks[0].stations[i].channels[j].elevation)
pzFile.write('* DEPTH : %0.1f\n' %
inv.networks[0].stations[i].channels[j].depth)
pzFile.write(
'* DIP : %0.1f\n' %
(90.0 -
np.abs(inv.networks[0].stations[i].channels[j].dip)))
pzFile.write('* AZIMUTH : %0.1f\n' %
inv.networks[0].stations[i].channels[j].azimuth)
pzFile.write(
'* SAMPLE RATE : %0.1f\n' %
inv.networks[0].stations[i].channels[j].sample_rate)
pzFile.write('* INPUT UNIT : M\n')
pzFile.write('* OUTPUT UNIT : COUNTS\n')
pzFile.write('* INSTTYPE : ' + inv.networks[0].
stations[i].channels[j].sensor.description + '\n')
pzFile.write('* INSTGAIN : %e (M/S)\n' %
inv.networks[0].stations[i].channels[j].response.
get_paz().stage_gain)
pzFile.write('* COMMENT : \n')
pzFile.write('* SENSITIVITY : %e (M/S)\n' %
inv.networks[0].stations[i].channels[j].response.
instrument_sensitivity.value)
pzFile.write('* A0 : %e\n' %
inv.networks[0].stations[i].channels[j].response.
get_paz().normalization_factor)
pzFile.write('* **********************************\n')
# Save the poles, zeros, and constant
nzeros = 3
zeros = inv.networks[0].stations[i].channels[
j].response.get_paz().zeros
nz = np.nonzero(zeros)
pzFile.write('ZEROS ' + str(len(nz[0]) + nzeros) + '\n')
pzFile.write(" %+e %+e\n" % (0, 0))
pzFile.write(" %+e %+e\n" % (0, 0))
pzFile.write(" %+e %+e\n" % (0, 0))
if len(nz[0]) != 0:
for k in range(0, len(nz[0])):
pzFile.write(" %+e %+e\n" % (np.real(
zeros[nz[0][k]]), np.imag(zeros[nz[0][k]])))
poles = inv.networks[0].stations[i].channels[
j].response.get_paz().poles
pzFile.write('POLES ' + str(len(poles)) + '\n')
for k in range(0, len(poles)):
pzFile.write(
" %+e %+e\n" %
(np.real(inv.networks[0].stations[i].channels[j].
response.get_paz().poles[k]),
np.imag(inv.networks[0].stations[i].channels[j].
response.get_paz().poles[k])))
pzFile.write(
'CONSTANT %e' %
(inv.networks[0].stations[i].channels[j].response.get_paz(
).normalization_factor * inv.networks[0].stations[i].
channels[j].response.instrument_sensitivity.value))
# pzFile.write(inv.networks[0].stations[i].channels[j].response.get_sacpz())
# Loop over time-periods during which the station was operational and fetch data
for i in range(0, nstats):
for j in range(0, nresp):
if inv.networks[0].stations[i].channels[
j].end_date > UTCDateTime.now():
t0 = inv.networks[0].stations[i].channels[j].start_date
tf = UTCDateTime.now()
else:
t0 = inv.networks[0].stations[i].channels[j].start_date
tf = inv.networks[0].stations[i].channels[j].end_date
# Get station coordinates for event selection
stla = inv.networks[0].stations[i].latitude
stlo = inv.networks[0].stations[i].longitude
# Fetch relevant events in time-window during which station was operational
try:
catalog = client.get_events(starttime=t0,
endtime=tf,
minmagnitude=minimum_magnitude,
maxmagnitude=maximum_magnitude,
latitude=stla,
longitude=stlo,
minradius=30,
maxradius=90)
except Exception as error:
with open(logFileName, "a") as log:
log.write(str(error))
log.write('Error fetching event catalog...')
continue
nEvents = len(catalog.events)
# Initialize list of events used for bulk request
bulk = []
# Fill 'bulk' with desired event information
for k in range(0, nEvents):
teq = catalog.events[k].origins[0].time
chan = inv.networks[0].stations[i].channels[j].code
bulk.append((ntwk, stat, loc, chan, teq, teq + duration * 60))
# Fetch the data!
if output_units == 'counts':
try:
st = client.get_waveforms_bulk(bulk)
except Exception as error:
with open(logFileName, "a") as log:
log.write(str(error))
log.write('Unable to complete fetch request for: ' +
stat + '.' + loc + '.' + chan)
continue
else:
try:
st = client.get_waveforms_bulk(bulk, attach_response=True)
except Exception as error:
with open(logFileName, "a") as log:
log.write(str(error))
log.write('Unable to complete fetch request for: ' +
stat + '.' + loc + '.' + chan)
continue
# Do some file-formatting and optional minor pre-processing
for k in range(0, len(st)):
teq = st[k].meta.starttime
# Optional instrument response removal goes here...
# Prepare filename for saving
evchan = st[k].meta.channel
evid = st[k].meta.starttime.isoformat().replace(
'-', '.').replace('T', '.').replace(':',
'.').split('.')[:-1]
evid.extend([ntwk, stat, loc, evchan, str(j), 'SAC'])
evid = ".".join(evid)
# Add station specific metadata to SAC files
st[k].stats.sac = {}
st[k].stats.sac.stla = stla
st[k].stats.sac.stlo = stlo
# Channel orientation (CMPAZ)
azid = [ntwk, stat, loc, evchan]
azid = ".".join(azid)
st[k].stats.sac.cmpaz = inv.get_orientation(azid,
teq)["azimuth"]
# Add event-specific metadata to SAC files (surely there must be a faster way to do this...?)
for l in range(0, nEvents):
if catalog.events[l].origins[0].time - 5 <= st[k].meta.starttime <= \
catalog.events[l].origins[0].time + 5:
st[k].stats.sac.evla = catalog.events[l].origins[
0].latitude
if st[k].stats.sac.evla is None:
with open(logFileName, "a") as log:
log.write('Couldn'
't find event latitude for: ' +
evid + '\n')
st[k].stats.sac.evla = 0.0
st[k].stats.sac.evlo = catalog.events[l].origins[
0].longitude
if st[k].stats.sac.evlo is None:
with open(logFileName, "a") as log:
log.write('Couldn'
't find event longitude for: ' +
evid + '\n')
st[k].stats.sac.evlo = 0.0
st[k].stats.sac.evdp = catalog.events[l].origins[
0].depth
if st[k].stats.sac.evdp is None:
with open(logFileName, "a") as log:
log.write('Couldn'
't find event depth for: ' + evid +
'\n')
st[k].stats.sac.evdp = 0.0
st[k].stats.sac.mag = catalog.events[l].magnitudes[
0].mag
if st[k].stats.sac.mag is None:
with open(logFileName, "a") as log:
log.write('Couldn'
't find event magnitude for: ' +
evid + '\n')
st[k].stats.sac.mag = 0.0
# Calculate great circle distance and back-azimuth
gcarc, baz = su.haversine(stla, stlo,
st[k].stats.sac.evla,
st[k].stats.sac.evlo)
st[k].stats.sac.gcarc = gcarc
st[k].stats.sac.baz = baz
# Get theoretical P arrival time, and assign to header 'T0'
model = TauPyModel(model="iasp91")
phases = ["P"]
arrivals = model.get_travel_times(
source_depth_in_km=st[k].stats.sac.evdp / 1000.0,
distance_in_degree=gcarc,
phase_list=phases)
st[k].stats.sac.t0 = arrivals[0].time
# Save the Pole Zero file index in 'USER0' Header
st[k].stats.sac.user0 = j
# Save the P-wave ray parameter in 'USER9' Header
st[k].stats.sac.user9 = arrivals[0].ray_param * (
np.pi / 180)
# Write the data to a SAC file
st[k].write(sac_dir + evid, format='SAC')
elapsed = time.time() - t1
with open(logFileName, "a") as log:
log.write('Time required to complete fetch request: ' + str(elapsed))
mnt_folder = "/mnt/marshost/"
if not lsdir(mnt_folder):
print(f"{mnt_folder} is still empty, mounting now...")
SS_MTI.DataGetter.mnt_remote_folder(
host_ip="marshost.ethz.ch",
host_usr="******",
remote_folder="/data/",
mnt_folder=mnt_folder,
)
npz_file = "/home/nienke/Documents/Research/Data/npz_files/TAYAK_BKE.npz"
# npz_file = "/home/nienke/Data_2020/npz_files/TAYAK_BKE.npz"
# npz_file = "/home/nienke/Documents/Research/Data/npz_files/TAYAK.npz"
model = TauPyModel(npz_file)
db_path = "/mnt/marshost/instaseis2/databases/TAYAK_15s_BKE"
# db_path = "/opt/databases/TAYAK_15s_BKE"
# db_path = "http://instaseis.ethz.ch/blindtest_1s/TAYAK_1s/"
db = instaseis.open_db(db_path)
# SS_MTI.DataGetter.unmnt_remote_folder(mnt_folder=mnt_folder)
lat_rec = 4.502384
lon_rec = 135.623447
strike = 90
dip = 90 # 45
rake = 0 # -90
focal_mech = [strike, dip, rake]
Last Modified : Mon 30 Apr 2018 03:58:10 PM EDT
Created By : Samuel M. Haugland
==============================================================================
'''
from matplotlib import pyplot as plt
import numpy as np
import h5py
import obspy
from sys import argv
from obspy.taup import TauPyModel
import argparse
from subprocess import call
from scipy.signal import correlate
model = TauPyModel(model='prem')
def main():
parser = argparse.ArgumentParser(description='Clip/write reverb intervals')
parser.add_argument('-s','--synth', metavar='H5_FILE',type=str,
help='h5 obspy stream synth file')
parser.add_argument('-d','--data', metavar='H5_FILE',type=str,
help='h5 obspy stream data file')
args = parser.parse_args()
try:
h5f_d = h5py.File('peg_data_reverb.h5','w',driver='core')
except IOError:
call('rm peg_data_reverb.h5',shell=True)
h5f_d = h5py.File('peg_data_reverb.h5','w',driver='core')
try:
""" from obspy.clients.fdsn import Client from obspy import UTCDateTime, Stream, read, read_inventory from obspy.taup import TauPyModel from obspy.geodetics.base import locations2degrees from matplotlib.transforms import blended_transform_factory from os import path import matplotlib.pyplot as plt from geopy.geocoders import Nominatim import numpy as np from matplotlib.cm import get_cmap from obspy.geodetics import gps2dist_azimuth DATA_PROVIDER = "RASPISHAKE" MODEL = 'iasp91' # Velocity model to predict travel-times through #MODEL = 'ak135' # Velocity model to predict travel-times through model = TauPyModel(model=MODEL) client = Client(DATA_PROVIDER) # Event details URL = 'https://earthquake.usgs.gov/earthquakes/eventpage/us7000c7y0/executive' EQNAME = 'M7 15 km NNE of Néon Karlovásion, Greece' EQLAT = 37.9175 EQLON = 26.7901 EQZ = '2020-10-30 11:51:28' EQTIME = 25.7859016291 FILE_STEM = 'Turkey-2020-10-30' MAGNITUDE = 'M7' RESP = "DISP" # DISP, VEL or ACC WINDOW = 20 # displacement plus/minus window
def input_chen_tele_body(tensor_info, data_prop):
"""We write some text files, which are based on teleseismic body wave data,
as inputs for Chen's scripts.
:param tensor_info: dictionary with moment tensor information
:param data_prop: dictionary with properties of waveform data
:type tensor_info: dict
:type data_prop: dict
.. warning::
Make sure the filters of teleseismic data agree with the values in
sampling_filter.json!
"""
if not os.path.isfile('tele_waves.json'):
return
traces_info = json.load(open('tele_waves.json'))
date_origin = tensor_info['date_origin']
dt = traces_info[0]['dt']
dt = round(dt, 1)
filtro = data_prop['tele_filter']
low_freq = filtro['low_freq']
high_freq = filtro['high_freq']
with open('filtro_tele', 'w') as outfile:
outfile.write('Corners: {} {}\n'.format(low_freq, high_freq))
outfile.write('dt: {}'.format(dt))
nsta = len(traces_info)
model = TauPyModel(model="ak135f_no_mud")
depth = tensor_info['depth']
event_lat = tensor_info['lat']
event_lon = tensor_info['lon']
string = '{0:2d} FAR GDSN {1:>6} {1:>6}BHZ.DAT {2:5.2f} {3:6.2f} '\
'{4:5.2f} {5:6.2f} {6:6.2f} 0 0 {7} {8} {9} 1 0\n'
sin_fun = lambda p: p * 3.6 / 111.12
angle_fun = lambda p:\
np.arctan2(sin_fun(p), np.sqrt(1 - sin_fun(p)**2)) * 180.0 / np.pi
string_fun1 = lambda i, name, dist, az, lat, lon, p_slowness, disp_or_vel:\
string.format(
i, name, dist, az, lat, lon, angle_fun(p_slowness), disp_or_vel, 1.0, 0)
string_fun2 = lambda i, name, dist, az, lat, lon, s_slowness, disp_or_vel:\
string.format(
i, name, dist, az, lat, lon, angle_fun(s_slowness), disp_or_vel, 4.0, 2)
with open('Readlp.das', 'w') as outfile:
outfile.write('30 30 30 0 0 0 0 0 0 1.1e+20\n')
outfile.write('3 10 {}\n{}{}{}{}{}{}.{}\n{}\n'.format(
dt, date_origin.year, date_origin.month, date_origin.day,
date_origin.hour, date_origin.minute, date_origin.second,
date_origin.microsecond, nsta))
i = 0
for file in traces_info: #header in headers:
name = file['name']
channel = file['component']
lat, lon = file['location']
dist, az, back_azimuth = mng._distazbaz(lat, lon, event_lat,
event_lon)
dist = kilometers2degrees(dist)
derivative = False if not 'derivative' in file\
else file['derivative']
derivative = int(derivative)
arrivals = mng.theoretic_arrivals(model, dist, depth)
p_slowness = arrivals['p_slowness']
s_slowness = arrivals['s_slowness']
if channel == 'BHZ':
outfile.write(
string_fun1(i + 1, name, dist, az, lat, lon, p_slowness,
derivative))
else:
outfile.write(
string_fun2(i + 1, name, dist, az, lat, lon, s_slowness,
derivative))
i = i + 1
with open('Wave.tele', 'w') as file1, open('Obser.tele', 'w') as file2:
write_files_wavelet_observed(file1, file2, dt, data_prop, traces_info)
#
# instrumental response common to all body waves
#
string2 = '\n3\n' + '0. 0.\n' * 3 + '4\n-6.17E-03 6.17E-03\n'\
'-6.17E-03 -6.17E-03\n-39.18 49.12\n-39.18 '\
'-49.12\n3948\n'
with open('instrumental_response', 'w') as outfile:
outfile.write('{}\n'.format(nsta))
outfile.write(string2 * len(traces_info))
write_wavelet_freqs(dt, 'Wavelets_tele_body')
with open('Weight', 'w') as outfile:
for info in traces_info:
sta = info['name']
channel = info['component']
weight = info['trace_weight']
outfile.write('{} {} {}\n'.format(weight, sta, channel))
return 'tele_body'
def arrival(ot, depth, distance_in_degree):
model = TauPyModel(model="iasp91")
arrivals = model.get_travel_times(source_depth_in_km=depth,
distance_in_degree=distance_in_degree)
arrival_time = ot + arrivals[0].time
return arrival_time
# #### Step 4: Calculate Theoretical Arrivals
#
# ```python
# from obspy.taup import TauPyModel
# m = TauPyModel(model="ak135")
# arrivals = m.get_ray_paths(...)
# arrivals.plot()
# ```
# + {"tags": ["exercise"]}
# + {"tags": ["solution"]}
from obspy.taup import TauPyModel
m = TauPyModel(model="ak135")
arrivals = m.get_ray_paths(
distance_in_degree=distance,
source_depth_in_km=origin.depth / 1000.0)
arrivals.plot();
# -
# #### Step 5: Calculate absolute time of the first arrivals at the station
# + {"tags": ["exercise"]}
# + {"tags": ["solution"]}
first_arrival = origin.time + arrivals[0].time
def get_sp(self, epi, depth_m):
model = TauPyModel(model=self.veloc_model)
tt = model.get_travel_times(source_depth_in_km=depth_m / 1000,
distance_in_degree=epi,
phase_list=['sP'])
return tt[0].time
def __init__(self, stationinfo, mseeddir, sacdir, model='prem'):
self.mseeddir = mseeddir
self.sacdir = sacdir
self.stations = self._read_stations(stationinfo)
self.model = TauPyModel(model=model)
def run_parallel_generate_ruptures(home,project_name,run_name,fault_name,slab_name,mesh_name,
load_distances,distances_name,UTM_zone,tMw,model_name,hurst,Ldip,Lstrike,
num_modes,Nrealizations,rake,buffer_factor,rise_time_depths0,rise_time_depths1,time_epi,max_slip,
source_time_function,lognormal,slip_standard_deviation,scaling_law,ncpus,force_magnitude,
force_area,mean_slip_name,hypocenter,slip_tol,force_hypocenter,
no_random,shypo,use_hypo_fraction,shear_wave_fraction,rank,size):
'''
Depending on user selected flags parse the work out to different functions
'''
from numpy import load,save,genfromtxt,log10,cos,sin,deg2rad,savetxt,zeros,where
from time import gmtime, strftime
from numpy.random import shuffle
from mudpy import fakequakes
from obspy import UTCDateTime
from obspy.taup import TauPyModel
import warnings
#I don't condone it but this cleans up the warnings
warnings.filterwarnings("ignore")
# Fix input formats
rank=int(rank)
size=int(size)
if time_epi=='None':
time_epi=None
else:
time_epi=UTCDateTime(time_epi)
rise_time_depths=[rise_time_depths0,rise_time_depths1]
#hypocenter=[hypocenter_lon,hypocenter_lat,hypocenter_dep]
tMw=tMw.split(',')
target_Mw=zeros(len(tMw))
for rMw in range(len(tMw)):
target_Mw[rMw]=float(tMw[rMw])
#Should I calculate or load the distances?
if load_distances==1:
Dstrike=load(home+project_name+'/data/distances/'+distances_name+'.strike.npy')
Ddip=load(home+project_name+'/data/distances/'+distances_name+'.dip.npy')
else:
Dstrike,Ddip=fakequakes.subfault_distances_3D(home,project_name,fault_name,slab_name,UTM_zone)
save(home+project_name+'/data/distances/'+distances_name+'.strike.npy',Dstrike)
save(home+project_name+'/data/distances/'+distances_name+'.dip.npy',Ddip)
#Read fault and prepare output variable
whole_fault=genfromtxt(home+project_name+'/data/model_info/'+fault_name)
#Get structure model
vel_mod_file=home+project_name+'/structure/'+model_name
#Get TauPyModel
velmod = TauPyModel(model=home+project_name+'/structure/'+model_name.split('.')[0])
#Now loop over the number of realizations
realization=0
if rank==0:
print('Generating rupture scenarios')
for kmag in range(len(target_Mw)):
if rank==0:
print('... Calculating ruptures for target magnitude Mw = '+str(target_Mw[kmag]))
for kfault in range(Nrealizations):
if kfault%1==0 and rank==0:
print('... ... working on ruptures '+str(ncpus*realization)+' to ' + str(ncpus*(realization+1)-1) + ' of '+str(Nrealizations*size*len(target_Mw)))
#print '... ... working on ruptures '+str(ncpus*realization+rank)+' of '+str(Nrealizations*size-1)
#Prepare output
fault_out=zeros((len(whole_fault),14))
fault_out[:,0:8]=whole_fault[:,0:8]
fault_out[:,10:12]=whole_fault[:,8:]
#Sucess criterion
success=False
while success==False:
#Select only a subset of the faults based on magnitude scaling
current_target_Mw=target_Mw[kmag]
ifaults,hypo_fault,Lmax,Wmax,Leff,Weff=fakequakes.select_faults(whole_fault,Dstrike,Ddip,current_target_Mw,buffer_factor,num_modes,scaling_law,force_area,no_shallow_epi=False,no_random=no_random,subfault_hypocenter=shypo)
fault_array=whole_fault[ifaults,:]
Dstrike_selected=Dstrike[ifaults,:][:,ifaults]
Ddip_selected=Ddip[ifaults,:][:,ifaults]
#Determine correlation lengths from effective length.width Leff and Weff
if Lstrike=='auto': #Use scaling
#Ls=10**(-2.43+0.49*target_Mw)
Ls=2.0+(1./3)*Leff
elif Lstrike=='MH2019':
Ls=17.7+0.34*Leff
else:
Ls=Lstrike
if Ldip=='auto': #Use scaling
#Ld=10**(-1.79+0.38*target_Mw)
Ld=1.0+(1./3)*Weff
elif Ldip=='MH2019':
Ld=6.8+0.4*Weff
else:
Ld=Ldip
#Get the mean uniform slip for the target magnitude
if mean_slip_name==None:
mean_slip,mu=fakequakes.get_mean_slip(target_Mw[kmag],fault_array,vel_mod_file)
else:
foo,mu=fakequakes.get_mean_slip(target_Mw[kmag],fault_array,vel_mod_file)
mean_fault=genfromtxt(mean_slip_name)
mean_slip=(mean_fault[:,8]**2+mean_fault[:,9]**2)**0.5
#keep onlt faults that have man slip inside the fault_array seelcted faults
mean_slip=mean_slip[ifaults]
#get the area in those selected faults
area=fault_array[:,-2]*fault_array[:,-1]
#get the moment in those selected faults
moment_on_selected=(area*mu*mean_slip).sum()
#target moment
target_moment=10**(1.5*target_Mw[kmag]+9.1)
#How much do I need to upscale?
scale_factor=target_moment/moment_on_selected
#rescale the slip
mean_slip = mean_slip*scale_factor
#Make sure mean_slip has no zero slip faults
izero=where(mean_slip==0)[0]
mean_slip[izero]=slip_tol
#Get correlation matrix
C=fakequakes.vonKarman_correlation(Dstrike_selected,Ddip_selected,Ls,Ld,hurst)
# Lognormal or not?
if lognormal==False:
#Get covariance matrix
C_nonlog=fakequakes.get_covariance(mean_slip,C,target_Mw[kmag],fault_array,vel_mod_file,slip_standard_deviation)
#Get eigen values and eigenvectors
eigenvals,V=fakequakes.get_eigen(C_nonlog)
#Generate fake slip pattern
rejected=True
while rejected==True:
# slip_unrectified,success=make_KL_slip(fault_array,num_modes,eigenvals,V,mean_slip,max_slip,lognormal=False,seed=kfault)
slip_unrectified,success=fakequakes.make_KL_slip(fault_array,num_modes,eigenvals,V,mean_slip,max_slip,lognormal=False,seed=None)
slip,rejected,percent_negative=fakequakes.rectify_slip(slip_unrectified,percent_reject=13)
if rejected==True:
print('... ... ... negative slip threshold exceeeded with %d%% negative slip. Recomputing...' % (percent_negative))
else:
#Get lognormal values
C_log,mean_slip_log=fakequakes.get_lognormal(mean_slip,C,target_Mw[kmag],fault_array,vel_mod_file,slip_standard_deviation)
#Get eigen values and eigenvectors
eigenvals,V=fakequakes.get_eigen(C_log)
#Generate fake slip pattern
# slip,success=make_KL_slip(fault_array,num_modes,eigenvals,V,mean_slip_log,max_slip,lognormal=True,seed=kfault)
slip,success=fakequakes.make_KL_slip(fault_array,num_modes,eigenvals,V,mean_slip_log,max_slip,lognormal=True,seed=None)
#Slip pattern sucessfully made, moving on.
#Rigidities
foo,mu=fakequakes.get_mean_slip(target_Mw[kmag],whole_fault,vel_mod_file)
fault_out[:,13]=mu
#Calculate moment and magnitude of fake slip pattern
M0=sum(slip*fault_out[ifaults,10]*fault_out[ifaults,11]*mu[ifaults])
Mw=(2./3)*(log10(M0)-9.1)
#Force to target magnitude
if force_magnitude==True:
M0_target=10**(1.5*target_Mw[kmag]+9.1)
M0_ratio=M0_target/M0
#Multiply slip by ratio
slip=slip*M0_ratio
#Recalculate
M0=sum(slip*fault_out[ifaults,10]*fault_out[ifaults,11]*mu[ifaults])
Mw=(2./3)*(log10(M0)-9.1)
#check max_slip again
if slip.max() > max_slip:
success=False
print('... ... ... max slip condition violated due to force_magnitude=True, recalculating...')
#Get stochastic rake vector
stoc_rake=fakequakes.get_stochastic_rake(rake,len(slip))
#Place slip values in output variable
fault_out[ifaults,8]=slip*cos(deg2rad(stoc_rake))
fault_out[ifaults,9]=slip*sin(deg2rad(stoc_rake))
#Move hypocenter to somewhere with a susbtantial fraction of peak slip
# slip_fraction=0.25
# islip=where(slip>slip.max()*slip_fraction)[0]
# shuffle(islip) #randomize
# hypo_fault=ifaults[islip[0]] #select first from randomized vector
#Calculate and scale rise times
rise_times=fakequakes.get_rise_times(M0,slip,fault_array,rise_time_depths,stoc_rake)
#Place rise_times in output variable
fault_out[:,7]=0
fault_out[ifaults,7]=rise_times
#Calculate rupture onset times
if force_hypocenter==False: #Use random hypo, otehrwise force hypo to user specified
hypocenter=whole_fault[hypo_fault,1:4]
t_onset=fakequakes.get_rupture_onset(home,project_name,slip,fault_array,model_name,hypocenter,rise_time_depths,M0,velmod)
fault_out[:,12]=0
fault_out[ifaults,12]=t_onset
#Calculate location of moment centroid
centroid_lon,centroid_lat,centroid_z=fakequakes.get_centroid(fault_out)
#Write to file
run_number=str(ncpus*realization+rank).rjust(6,'0')
outfile=home+project_name+'/output/ruptures/'+run_name+'.'+run_number+'.rupt'
savetxt(outfile,fault_out,fmt='%d\t%10.6f\t%10.6f\t%8.4f\t%7.2f\t%7.2f\t%4.1f\t%5.2f\t%5.2f\t%5.2f\t%10.2f\t%10.2f\t%5.2f\t%.6e',header='No,lon,lat,z(km),strike,dip,rise,dura,ss-slip(m),ds-slip(m),ss_len(m),ds_len(m),rupt_time(s),rigidity(Pa)')
#Write log file
logfile=home+project_name+'/output/ruptures/'+run_name+'.'+run_number+'.log'
f=open(logfile,'w')
f.write('Scenario calculated at '+strftime("%Y-%m-%d %H:%M:%S", gmtime())+' GMT\n')
f.write('Project name: '+project_name+'\n')
f.write('Run name: '+run_name+'\n')
f.write('Run number: '+run_number+'\n')
f.write('Velocity model: '+model_name+'\n')
f.write('No. of KL modes: '+str(num_modes)+'\n')
f.write('Hurst exponent: '+str(hurst)+'\n')
f.write('Corr. length used Lstrike: %.2f km\n' % Ls)
f.write('Corr. length used Ldip: %.2f km\n' % Ld)
f.write('Slip std. dev.: %.3f km\n' % slip_standard_deviation)
f.write('Maximum length Lmax: %.2f km\n' % Lmax)
f.write('Maximum width Wmax: %.2f km\n' % Wmax)
f.write('Effective length Leff: %.2f km\n' % Leff)
f.write('Effective width Weff: %.2f km\n' % Weff)
f.write('Target magnitude: Mw %.4f\n' % target_Mw[kmag])
f.write('Actual magnitude: Mw %.4f\n' % Mw)
f.write('Hypocenter (lon,lat,z[km]): (%.6f,%.6f,%.2f)\n' %(hypocenter[0],hypocenter[1],hypocenter[2]))
f.write('Hypocenter time: %s\n' % time_epi)
f.write('Centroid (lon,lat,z[km]): (%.6f,%.6f,%.2f)\n' %(centroid_lon,centroid_lat,centroid_z))
f.write('Source time function type: %s' % source_time_function)
f.close()
realization+=1
import matplotlib.pyplot as plt
import os.path
import time
import glob
import shutil
import numpy as np
import scipy
from obspy.io.xseed import Parser
from obspy.clients.arclink import Client as ARCLINKClient
from obspy.clients.fdsn import Client as IRISClient
from subprocess import call
import subprocess
from obspy.taup.taup import getTravelTimes
import sys
from obspy.taup import TauPyModel
model=TauPyModel(model="prem")
# Find list of stations directories
stations = glob.glob('DataRF/*')
# Add phase names as additional arguments (these are the TauP phase names)
phase=[]
for i in range(1,len(sys.argv)):
phase.append(sys.argv[i])
count=0
# Loop through stations
for stadir in stations:
print("STATION:", stadir)
stalist=glob.glob(stadir+'/*PICKLE')
# make directory for processed data
direc= stadir+'/Travel_time_added'
:copyright:
2012-2021 Claudio Satriano <*****@*****.**>
:license:
CeCILL Free Software License Agreement, Version 2.1
(http://www.cecill.info/index.en.html)
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
from glob import glob
import logging
import warnings
from sourcespec.ssp_setup import ssp_exit
from obspy.taup import TauPyModel
model = TauPyModel(model='iasp91')
logger = logging.getLogger(__name__.split('.')[-1])
def _wave_arrival_nll(trace, phase, NLL_time_dir):
"""Arrival time using a NLL grid."""
if trace.stats.hypo.origin_time is None:
return
if NLL_time_dir is None:
return
try:
from nllgrid import NLLGrid
except ImportError:
logger.error('Error: the "nllgrid" python module is required '
'for "NLL_time_dir".')
ssp_exit()