def points_on_sphere(dx,xmin=-180.,xmax=180.,ymin=-89.999,ymax=89.999,c_centr=None,\
radius=None):
"""
Calculate a more or less equally spaced grid on spherical Earth's surface.
:param dx: spacing in latitudinal and longitudinal direction in meter
:type c_centr: Tuple
:param c_centr: Specify a central location
:type radius: float
:param radius: Radius around central location in m; no sources beyond this will be included
:returns: np.array(latitude, longitude) of grid points, where -180<=lon<180 and -90 <= lat < 90
"""
if xmax <= xmin or ymax <= ymin:
msg = 'Lower bounds must be lower than upper bounds.'
raise ValueError(msg)
gridx = []
gridy = []
lat = ymin
if ymin == -90.:
ymin = -89.999
warn("Resetting lat_min to -89.999 degree")
while lat <= ymax:
d_lat = dx / len_deg_lat(lat)
d_lon = dx / len_deg_lon(lat)
lon = xmin + np.random.rand(1)[0] * d_lon
while lon <= xmax:
gridx.append(lon)
gridy.append(lat)
if c_centr and radius:
if gps2dist_azimuth(lat, lon, c_centr[0],
c_centr[1])[0] > radius:
print(
lat, lon,
gps2dist_azimuth(lat, lon, c_centr[0], c_centr[1])[0])
if abs(lat) != 90.:
d_lon = dx / len_deg_lon(lat)
lon += d_lon
continue
else:
break
if abs(lat) == 90:
# length of a degree longitude will be 0.
break
else:
d_lon = dx / len_deg_lon(lat)
lon += d_lon
lat += d_lat # do not start at pole or zero division will raise...
# return values sorted by longitude, basemap likes it.
grid = list(zip(*sorted(zip(gridx, gridy), key=lambda it: it[0])))
return list((gridx, gridy)) #grid
def points_on_sphere(dx,xmin=-180.,xmax=180.,ymin=-89.999,ymax=89.999,c_centr=None,\
radius=None):
"""
Calculate a more or less equally spaced grid on spherical Earth's surface.
:param dx: spacing in latitudinal and longitudinal direction in meter
:type c_centr: Tuple
:param c_centr: Specify a central location
:type radius: float
:param radius: Radius around central location in m; no sources beyond this will be included
:returns: np.array(latitude, longitude) of grid points, where -180<=lon<180 and -90 <= lat < 90
"""
if xmax <= xmin or ymax <= ymin:
msg = 'Lower bounds must be lower than upper bounds.'
raise ValueError(msg)
gridx = []
gridy = []
lat = ymin
if ymin == -90.:
ymin = -89.999
warn("Resetting lat_min to -89.999 degree")
while lat <= ymax:
d_lat = dx / len_deg_lat(lat)
d_lon = dx / len_deg_lon(lat)
lon = xmin + np.random.rand(1)[0] * d_lon
while lon <= xmax:
gridx.append(lon)
gridy.append(lat)
if c_centr and radius:
if gps2dist_azimuth(lat,lon,c_centr[0],c_centr[1])[0] > radius:
print(lat,lon,gps2dist_azimuth(lat,lon,c_centr[0],c_centr[1])[0])
if abs(lat) != 90.:
d_lon = dx / len_deg_lon(lat)
lon += d_lon
continue
else:
break
if abs(lat) == 90:
# length of a degree longitude will be 0.
break
else:
d_lon = dx / len_deg_lon(lat)
lon += d_lon
lat += d_lat # do not start at pole or zero division will raise...
# return values sorted by longitude, basemap likes it.
grid = list(zip(*sorted(zip(gridx, gridy), key=lambda it: it[0])))
return list((gridx,gridy))#grid
def test_gps_2_dist_azimuth_bug150(self):
"""
Test case for #150: UserWarning will be only raised if geographiclib is
not installed.
"""
# this raises UserWarning
with warnings.catch_warnings(record=True):
warnings.simplefilter('error', UserWarning)
with pytest.raises(UserWarning):
gps2dist_azimuth(0, 0, 0, 180)
def get_geoinf(x1,y1,x2,y2,inp='coord'):
if inp == 'coord':
try:
dist=gps2DistAzimuth(x1, y1, x2, y2)[0]
az=gps2DistAzimuth(x1, y1, x2, y2)[1]
baz=gps2DistAzimuth(x1, y1, x2, y2)[2]
except NameError:
dist=gps2dist_azimuth(x1, y1, x2, y2)[0]
az=gps2dist_azimuth(x1, y1, x2, y2)[1]
baz=gps2dist_azimuth(x1, y1, x2, y2)[2]
return (x1, y1, x2, y2, dist, az, baz)
def get_geoinf(x1, y1, x2, y2, inp='coord'):
if inp == 'coord':
try:
dist = gps2DistAzimuth(x1, y1, x2, y2)[0]
az = gps2DistAzimuth(x1, y1, x2, y2)[1]
baz = gps2DistAzimuth(x1, y1, x2, y2)[2]
except NameError:
dist = gps2dist_azimuth(x1, y1, x2, y2)[0]
az = gps2dist_azimuth(x1, y1, x2, y2)[1]
baz = gps2dist_azimuth(x1, y1, x2, y2)[2]
return (x1, y1, x2, y2, dist, az, baz)
def initialize(self):
''' Initialize the node.
'''
super(QuarryBlastClassification, self).initialize()
# Compute the neighbor stations.
nearest_station_name = self.pref_manager.get_value('nearest_station')[0]
nearest_station = self.project.geometry_inventory.get_station(name = nearest_station_name)[0]
stations = self.project.geometry_inventory.get_station()
stations = [x for x in stations if x.name != nearest_station.name]
station_dist = []
src_lonlat = nearest_station.get_lon_lat()
for cur_station in stations:
dst_lonlat = cur_station.get_lon_lat()
dist, az1, az2 = geodetics.gps2dist_azimuth(lon1 = src_lonlat[0], lat1 = src_lonlat[1],
lon2 = dst_lonlat[0], lat2 = dst_lonlat[1])
station_dist.append((cur_station, dist))
self.nearest_station = nearest_station
self.neighbor_stations = sorted(station_dist, key = lambda x: x[1])
# Get the desired event type.
event_types = self.load_event_types()
dst_event_type = self.pref_manager.get_value('event_type')[0]
self.event_type = [x for x in event_types if x.name == dst_event_type][0]
def test_issue_375(self):
"""
Test for #375.
"""
_, azim, bazim = gps2dist_azimuth(50, 10, 50 + 1, 10 + 1)
assert round(azim, 0) == 32
assert round(bazim, 0) == 213
_, azim, bazim = gps2dist_azimuth(50, 10, 50 + 1, 10 - 1)
assert round(azim, 0) == 328
assert round(bazim, 0) == 147
_, azim, bazim = gps2dist_azimuth(50, 10, 50 - 1, 10 + 1)
assert round(azim, 0) == 147
assert round(bazim, 0) == 327
_, azim, bazim = gps2dist_azimuth(50, 10, 50 - 1, 10 - 1)
assert round(azim, 0) == 213
assert round(bazim, 0) == 33
def magnitude_coda(self):
Mc = []
# values for california
a = 2.0
b = 0.0035
c = -0.87
#
for key in self.chop['Coda']:
magnitude_dict = self.chop['Coda'][key]
coords = get_coordinates_from_metadata(self.inventory,
magnitude_dict[0])
dist, _, _ = gps2dist_azimuth(coords.Latitude, coords.Longitude,
self.event.latitude,
self.event.longitude)
dist = dist / 1000
#data = np.array(magnitude_dict[2])
pick_time = UTCDateTime(mdt.num2date(magnitude_dict[1][0]))
end_time = UTCDateTime(mdt.num2date(magnitude_dict[1][-1]))
t_coda = end_time - pick_time
Mc_value = a * np.log10(t_coda) + b * dist + c
Mc_value = Mc_value
Mc.append(Mc_value)
Mcs = np.array(Mc)
Mc_mean = Mcs.mean()
Mc_deviation = Mcs.std()
print("Coda Magnitude", Mc_mean, "Variance", Mc_deviation)
label = "Mc"
self.plot_histograms(Mc, label)
self.Mcs = Mcs
self.Mc = Mc_mean
self.Mc_std = Mc_deviation
def test_compute_differential_times(self):
max_sep = 8.
diff_times, mapper = compute_differential_times(catalog=self.catalog,
correlation=False,
event_id_mapper=None,
max_sep=max_sep,
min_link=8)
reverse_mapper = {value: key for key, value in mapper.items()}
self.assertEqual(len(self.catalog), len(diff_times))
for key, links in diff_times.items():
master_id = mapper[key]
master_event = [
e for e in self.catalog if e.resource_id.id == key
][0]
for link in links:
self.assertEqual(master_id, link.event_id_1)
linked_event = [
e for e in self.catalog
if e.resource_id.id == reverse_mapper[link.event_id_2]
][0]
dist, _, _ = gps2dist_azimuth(
lat1=master_event.preferred_origin().latitude,
lon1=master_event.preferred_origin().longitude,
lat2=linked_event.preferred_origin().latitude,
lon2=linked_event.preferred_origin().longitude)
self.assertLess(dist / 1000, max_sep)
def are_duplicates(tr1, tr2, max_dist_tolerance):
"""
Determines whether two StationTraces are duplicates by checking the
station, channel codes, and the distance between them.
Args:
tr1 (StationTrace):
1st trace.
tr2 (StationTrace):
2nd trace.
max_dist_tolerance (float):
Maximum distance tolerance for determining whether two streams
are at the same location (in meters).
Returns:
bool. True if traces are duplicates, False otherwise.
"""
# First, check if the ids match (net.sta.loc.cha)
if tr1.id == tr2.id:
return True
# If not matching IDs, check the station, instrument code, and distance
else:
distance = gps2dist_azimuth(
tr1.stats.coordinates.latitude, tr1.stats.coordinates.longitude,
tr2.stats.coordinates.latitude, tr2.stats.coordinates.longitude)[0]
if (tr1.stats.station == tr2.stats.station and
tr1.stats.location == tr2.stats.location and
tr1.stats.channel == tr2.stats.channel and
distance < max_dist_tolerance):
return True
else:
return False
def azimuth(coordinates, x0, y0, x1, y1):
"""
Returns the azimuth between two coordinate sets.
:type coordinates: str
:param coordinates: {'DEG', 'UTM', 'MIX'}
:type x0: float
:param x0: X coordinate of station 1
:type y0: float
:param y0: Y coordinate of station 1
:type x1: float
:param x1: X coordinate of station 2
:type y1: float
:param y1: Y coordinate of station 2
:rtype: float
:returns: The azimuth in degrees
"""
if coordinates == "DEG":
dist, azim, bazim = gps2dist_azimuth(y0, x0, y1, x1)
return azim
elif coordinates == 'UTM':
azim = 90. - np.arctan2((y1 - y0), (x1 - x0)) * 180. / np.pi
return azim
else:
print("Please consider having a single coordinate system for\
all stations")
return 0
def get_interstation_distance(station1, station2, coordinates="DEG"):
"""Returns the distance in km between `station1` and `station2`.
.. warning:: Currently the stations coordinates system have to be the same!
:type station1: :class:`~msnoise.msnoise_table_def.Station`
:param station1: A Station object
:type station2: :class:`~msnoise.msnoise_table_def.Station`
:param station2: A Station object
:type coordinates: str
:param coordinates: The coordinates system. "DEG" is WGS84 latitude/
longitude in degrees. "UTM" is expressed in meters.
:rtype: float
:returns: The interstation distance in km
"""
if coordinates == "DEG":
dist, azim, bazim = gps2dist_azimuth(station1.Y, station1.X,
station2.Y, station2.X)
return dist / 1.e3
else:
dist = np.hypot(float(station1.X - station2.X),
float(station1.Y - station2.Y)) / 1.e3
return dist
def get_interstation_distance(station1, station2, coordinates="DEG"):
"""Returns the distance in km between `station1` and `station2`.
.. warning:: Currently the stations coordinates system have to be the same!
:type station1: :class:`~msnoise.msnoise_table_def.Station`
:param station1: A Station object
:type station2: :class:`~msnoise.msnoise_table_def.Station`
:param station2: A Station object
:type coordinates: str
:param coordinates: The coordinates system. "DEG" is WGS84 latitude/
longitude in degrees. "UTM" is expressed in meters.
:rtype: float
:returns: The interstation distance in km
"""
if coordinates == "DEG":
dist, azim, bazim = gps2dist_azimuth(station1.Y, station1.X,
station2.Y, station2.X)
return dist / 1.e3
else:
dist = np.hypot(float(station1.X - station2.X),
float(station1.Y - station2.Y)) / 1.e3
return dist
def azimuth(coordinates, x0, y0, x1, y1):
"""
Returns the azimuth between two coordinate sets.
:type coordinates: str
:param coordinates: {'DEG', 'UTM', 'MIX'}
:type x0: float
:param x0: X coordinate of station 1
:type y0: float
:param y0: Y coordinate of station 1
:type x1: float
:param x1: X coordinate of station 2
:type y1: float
:param y1: Y coordinate of station 2
:rtype: float
:returns: The azimuth in degrees
"""
if coordinates == "DEG":
dist, azim, bazim = gps2dist_azimuth(y0, x0, y1, x1)
return azim
elif coordinates == 'UTM':
if (np.isclose(y0, y1) & np.isclose(x0, x1)):
return 0
else:
azim = 90. - np.arctan2((y1 - y0), (x1 - x0)) * 180. / np.pi
return azim % 360
else:
logging.warning("Please consider having a single coordinate system for\
all stations")
return 0
def get_geoinf(id1,id2):
inv1 = '{}.{}.xml'.format(*id1.split('.')[0:2])
inv2 = '{}.{}.xml'.format(*id2.split('.')[0:2])
inv1 = read_inventory(os.path.join('meta','stationxml',inv1))
inv2 = read_inventory(os.path.join('meta','stationxml',inv2))
# Replace 'radial' and 'transverse' by 'N' and 'E'
id1 = re.sub('\.??R$','N',id1)
id2 = re.sub('\.??R$','N',id2)
id1 = re.sub('\.??T$','E',id1)
id2 = re.sub('\.??T$','E',id2)
c1 = inv1.get_coordinates(id1)
c2 = inv2.get_coordinates(id2)
lat1, lon1, lat2, lon2 = (
c1['latitude'],
c1['longitude'],
c2['latitude'],
c2['longitude'])
dist, az, baz = gps2dist_azimuth(lat1,lon1,lat2,lon2)
return lat1, lon1, lat2, lon2, dist, az, baz
def hypo_dist(trace):
"""Compute hypocentral and epicentral distance (in km) for a trace."""
try:
coords = trace.stats.coords
hypo = trace.stats.hypo
except (KeyError, AttributeError):
return None
if None in (coords, hypo):
return None
stla = coords.latitude
stlo = coords.longitude
stel = coords.elevation
evla = hypo.latitude
evlo = hypo.longitude
evdp = hypo.depth
if None in (stla, stlo, stel, evla, evlo, evdp):
return None
epi_dist, az, baz = gps2dist_azimuth(
hypo.latitude, hypo.longitude,
trace.stats.coords.latitude, trace.stats.coords.longitude)
epi_dist /= 1e3 # in km
gcarc = kilometers2degrees(epi_dist)
hypo_dist = math.sqrt(epi_dist**2 + (stel+evdp)**2)
trace.stats.azimuth = az
trace.stats.back_azimuth = baz
trace.stats.epi_dist = epi_dist
trace.stats.hypo_dist = hypo_dist
trace.stats.gcarc = gcarc
return hypo_dist
def calc_detection(netset, conf, session, dd=0.2):
""" Calculate the magnitude of detection at a delta degrees of dd"""
stalist = get_stations(netset, session)
stalist2csv(stalist, netset)
fh = open("GIS/%s/%s_mdetect.csv" % (netset['label'], netset['label']),
'w')
fh.write("longitude,latitude,Mdetect\n")
for lat in np.arange(conf['region']['minlatitude'],
conf['region']['maxlatitude'], dd):
for lon in np.arange(conf['region']['minlongitude'],
conf['region']['maxlongitude'], dd):
dv = [] # Store detection values to all stations
for sta in stalist:
d, azm, baz = gps2dist_azimuth(sta.latitude, sta.longitude,
lat, lon)
threshold_db = sta.meanp25 + conf['source'][
'nsigma'] * sta.stdp25 + conf['source']['snr_db']
f = np.array([4, 6, 8])
mw = noise2mw(f,
threshold_db,
Q=conf['source']['Q'],
rho=conf['source']['rho'],
vel=conf['source']['alpha'],
delta=d / 1000.,
depth=conf['source']['depth'],
stressdrop=conf['source']['stressdrop'],
phase='P')
dv.append(mw)
dv = np.sort(dv)
fh.write("%.2f,%.2f,%.2f\n" %
(lon, lat, dv[conf['source']['nstations'] - 1]))
fh.close()
def retrieve_waveform(client,net,stn,t1,t2,stats_dict=None,cha="BHE,BHN,BHZ",attach_response=False,loc="",pharr=None, phasenm = 'P'):
try:
st = client.get_waveforms(net, stn, loc, cha, t1, t2,attach_response=attach_response)
except:
return False
# print("Retrieving")
if phasenm == 'P':
# filter_traces(st,lenphase=int(t2-t1))
filter_traces_rf(st,pharr = pharr)
elif phasenm == 'SKS':
filter_traces_sks(st,pharr = pharr)
if len(st) != 3:
# print(f"All three components not available: {len(st)}")
return False
if stats_dict:
dist, baz, _ = gps2dist_azimuth(stats_dict['station_latitude'],stats_dict['station_longitude'],stats_dict['event_latitude'],stats_dict['event_longitude'])
for tr in st:
for key, value in stats_dict.items():
tr.stats[key] = value
tr.stats['distance'] = dist / 1000 / DEG2KM
tr.stats['back_azimuth'] = baz
st.merge()
# if all 3 components present and no gap or overlap in data
if len(st) == 3 and not any(isinstance(tr.data, np.ma.masked_array) for tr in st):
# print(f"Stream obtained {len(st)}")
return RFStream(st)
elif not any(isinstance(tr.data, np.ma.masked_array) for tr in st):
# print("--------> There's a gap/overlap in the data")
return False
def test_issue_375(self):
"""
Test for #375.
"""
_, azim, bazim = gps2dist_azimuth(50, 10, 50 + 1, 10 + 1)
self.assertEqual(round(azim, 0), 32)
self.assertEqual(round(bazim, 0), 213)
_, azim, bazim = gps2dist_azimuth(50, 10, 50 + 1, 10 - 1)
self.assertEqual(round(azim, 0), 328)
self.assertEqual(round(bazim, 0), 147)
_, azim, bazim = gps2dist_azimuth(50, 10, 50 - 1, 10 + 1)
self.assertEqual(round(azim, 0), 147)
self.assertEqual(round(bazim, 0), 327)
_, azim, bazim = gps2dist_azimuth(50, 10, 50 - 1, 10 - 1)
self.assertEqual(round(azim, 0), 213)
self.assertEqual(round(bazim, 0), 33)
def _azimuth(lat1, lon1, lat2, lon2):
"""
The azimuth(unit:degree) starting from point1 to
point 2 on the sphere
"""
_, azi, _ = gps2dist_azimuth(lat1, lon1, lat2, lon2)
return azi
def compute_ellipticity_corr(arrival_phase, ev_latitude, ev_longitude,
ev_depth_km, sta_latitude, sta_longitude,
degrees_to_source):
"""
Utility function to compute ellipticity correction.
:param arrival_phase: P or S
:param ev_latitude: event lat
:param ev_longitude: event long
:param ev_depth_km: event depth in km
:param sta_latitude: station lat
:param sta_longitude: station long
:param degrees_to_source: degree to source
:return: ellipticity correction float value
"""
myazim = gps2dist_azimuth(ev_latitude, ev_longitude, sta_latitude,
sta_longitude)[1] # [1] shall be taken
# see https://docs.obspy.org/_modules/obspy/geodetics/base.html#gps2dist_azimuth
# this function returns 3 values (Great_circle_distance_in_m, azimuth_A->B_in_degrees, azimuth_B->A_in degrees)
log.debug("Check input params to ellipticity_corr = %s, %s, %s, %s, %s",
arrival_phase, degrees_to_source, ev_depth_km, 90 - ev_latitude,
myazim)
ellipticity_corr = ellipcorr.ellipticity_corr(
phase=arrival_phase,
edist=degrees_to_source,
edepth=ev_depth_km,
ecolat=90 - ev_latitude, # conversion to co-latitude
azim=myazim)
log.debug("ellipticity_corr = %s", ellipticity_corr)
return ellipticity_corr
def test_lcalda(self):
"""
Test that distances are set when geographic information is present and
lcalda is True, and that they're not set when geographic information
is missing or lcalca is false.
"""
stla, stlo, evla, evlo = -35.0, 100, 42.5, -37.5
meters, az, baz = gps2dist_azimuth(evla, evlo, stla, stlo)
km = meters / 1000.0
gcarc = kilometer2degrees(km)
# distances are set when lcalda True and all distance values set
sac = SACTrace(lcalda=True, stla=stla, stlo=stlo, evla=evla, evlo=evlo)
self.assertAlmostEqual(sac.az, az, places=4)
self.assertAlmostEqual(sac.baz, baz, places=4)
self.assertAlmostEqual(sac.dist, km, places=4)
self.assertAlmostEqual(sac.gcarc, gcarc, places=4)
# distances are not set when lcalda False and all distance values set
sac = SACTrace(lcalda=False, stla=stla, stlo=stlo, evla=evla,
evlo=evlo)
self.assertIs(sac.az, None)
self.assertIs(sac.baz, None)
self.assertIs(sac.dist, None)
self.assertIs(sac.gcarc, None)
# distances are not set when lcalda True, not all distance values set
sac = SACTrace(lcalda=True, stla=stla)
self.assertIs(sac.az, None)
self.assertIs(sac.baz, None)
self.assertIs(sac.dist, None)
self.assertIs(sac.gcarc, None)
# exception raised when set_distances is forced but not all distances
# values are set. NOTE: still have a problem when others are "None".
sac = SACTrace(lcalda=True, stla=stla)
self.assertRaises(SacHeaderError, sac._set_distances, force=True)
def calc_steer(slats, slons):
"""
Compute the steering vector
:type slats:
:param slats:
:type slons:
:param slons:
"""
theta = arange(0, 362, 2)
theta = theta.reshape((theta.size, 1))
sta_origin_dist = array([])
sta_origin_bearing = array([])
meanlat = slats.mean()
meanlon = slons.mean()
for lat, lon in zip(slats, slons):
#get dist between each sta and mean xy of array
dist, az, baz = gps2dist_azimuth(meanlat, meanlon, lat, lon)
sta_origin_dist = append(sta_origin_dist, dist)
sta_origin_bearing = append(sta_origin_bearing, az)
# ramener dist sur le cadran en x et y (dist*cos(az)) ou dist*sin(az)
sta_origin_x = sta_origin_dist * cos(sta_origin_bearing * pi / 180.)
sta_origin_y = sta_origin_dist * sin(sta_origin_bearing * pi / 180.)
# On le calcule pr plein de theta different car apres on cherche quel est le meilleur.
zeta_x = -cos(theta * pi / 180.)
zeta_y = -sin(theta * pi / 180.)
# dot product betwen zeta and x: d = -x.cos(theta)-y.sin(theta)
zetax = zeta_x * sta_origin_x + zeta_y * sta_origin_y
return zetax, theta, sta_origin_x, sta_origin_y
def test_issue_375(self):
"""
Test for #375.
"""
_, azim, bazim = gps2dist_azimuth(50, 10, 50 + 1, 10 + 1)
self.assertEqual(round(azim, 0), 32)
self.assertEqual(round(bazim, 0), 213)
_, azim, bazim = gps2dist_azimuth(50, 10, 50 + 1, 10 - 1)
self.assertEqual(round(azim, 0), 328)
self.assertEqual(round(bazim, 0), 147)
_, azim, bazim = gps2dist_azimuth(50, 10, 50 - 1, 10 + 1)
self.assertEqual(round(azim, 0), 147)
self.assertEqual(round(bazim, 0), 327)
_, azim, bazim = gps2dist_azimuth(50, 10, 50 - 1, 10 - 1)
self.assertEqual(round(azim, 0), 213)
self.assertEqual(round(bazim, 0), 33)
def _azimuth(lat1, lon1, lat2, lon2):
"""
The azimuth(unit:degree) starting from point1 to
point 2 on the sphere
"""
_, azi, _ = gps2dist_azimuth(lat1, lon1, lat2, lon2)
return azi
def test_lcalda(self):
"""
Test that distances are set when geographic information is present and
lcalda is True, and that they're not set when geographic information
is missing or lcalca is false.
"""
stla, stlo, evla, evlo = -35.0, 100, 42.5, -37.5
meters, az, baz = gps2dist_azimuth(evla, evlo, stla, stlo)
km = meters / 1000.0
gcarc = kilometer2degrees(km)
# distances are set when lcalda True and all distance values set
sac = SACTrace(lcalda=True, stla=stla, stlo=stlo, evla=evla, evlo=evlo)
self.assertAlmostEqual(sac.az, az, places=4)
self.assertAlmostEqual(sac.baz, baz, places=4)
self.assertAlmostEqual(sac.dist, km, places=4)
self.assertAlmostEqual(sac.gcarc, gcarc, places=4)
# distances are not set when lcalda False and all distance values set
sac = SACTrace(lcalda=False, stla=stla, stlo=stlo, evla=evla,
evlo=evlo)
self.assertIs(sac.az, None)
self.assertIs(sac.baz, None)
self.assertIs(sac.dist, None)
self.assertIs(sac.gcarc, None)
# distances are not set when lcalda True, not all distance values set
sac = SACTrace(lcalda=True, stla=stla)
self.assertIs(sac.az, None)
self.assertIs(sac.baz, None)
self.assertIs(sac.dist, None)
self.assertIs(sac.gcarc, None)
# exception raised when set_distances is forced but not all distances
# values are set. NOTE: still have a problem when others are "None".
sac = SACTrace(lcalda=True, stla=stla)
self.assertRaises(SacHeaderError, sac._set_distances, force=True)
def magnitude_local(self):
ML = []
for key in self.chop['Body waves']:
magnitude_dict = self.chop['Body waves'][key]
coords = get_coordinates_from_metadata(self.inventory,
magnitude_dict[0])
dist, _, _ = gps2dist_azimuth(coords.Latitude, coords.Longitude,
self.event.latitude,
self.event.longitude)
dist = dist / 1000
data = np.array(
magnitude_dict[2]
) # already converted Wood Anderson (Gain in mm 2800 +-60)
max_amplitude = np.max(data) * 1e3 # convert to mm --> nm
ML_value = np.log10(
max_amplitude) + 1.11 * np.log10(dist) + 0.00189 * dist - 2.09
ML.append(ML_value)
MLs = np.array(ML)
ML_mean = MLs.mean()
ML_deviation = MLs.std()
print("Local Magnitude", ML_mean, "Variance", ML_deviation)
label = "ML"
self.MLs = MLs
self.plot_histograms(ML, label)
self.ML = ML_mean
self.ML_std = ML_deviation
def aperture(self):
"""The array aperture is the largest inter-station distance."""
aperture = 0
for ele1, ele2 in combinations(self.elements, 2):
dist = gps2dist_azimuth(ele1.latitude, ele1.longitude,
ele2.latitude, ele2.longitude)[0]
aperture = max(aperture, dist)
return aperture
def kernel(event_pair, stations=None):
"""
kernel: the core function to get the information.
"""
model = TauPyModel(model="ak135")
# for each station, we calculate the travel time
result = {}
evla = event_pair.lat
evlo = event_pair.lon
evdp = event_pair.dep / 1000
event_time = event_pair.time
for row in stations:
result_template = {
"event_time": event_time,
"evla": evla,
"evlo": evlo,
"evdp": evdp,
"gcarc": None,
"az": None,
"baz": None,
"S": None,
"sS": None,
"SS": None,
"P": None,
"pP": None,
"sP": None,
"PP": None,
"3.3kmps": None,
"4.6kmps": None,
"ScS": None
}
station = row[0]
network = row[1]
net_sta = f"{network}.{station}"
stla = float(row[2])
stlo = float(row[3])
arrivals = model.get_travel_times_geo(evdp, evla, evlo, stla, stlo,
PHASE_LIST)
gcarc_m, az, baz = gps2dist_azimuth(evla, evlo, stla, stlo)
gcarc = kilometers2degrees(gcarc_m / 1000)
result_template["gcarc"] = gcarc
result_template["az"] = az
result_template["baz"] = baz
for each_arrival in arrivals:
name = each_arrival.name
time = each_arrival.time
if ((name in PHASE_LIST)):
if (name == "p"):
name = "P"
if (name == "s"):
name = "S"
if (result_template[name] == None):
result_template[name] = time
result[net_sta] = result_template
return result
def calculate_epicentral_distance(event_lat, event_lon, sta_lat, sta_lon):
from obspy.geodetics import gps2dist_azimuth
epi_dist, az, baz = gps2dist_azimuth(event_lat, event_lon, sta_lat,
sta_lon)
epi_dist = epi_dist / 1000 # Convert to km
return epi_dist
def _join_unconnected_areas(areas, max_distance, inventory):
# At the moment, areas are joined by setting the site response of
# the station pair with smallest distance to 1
# Often this works, but sometimes it produces undesired results
coordinates = _collect_station_coordinates(inventory)
station_by_coordinate = {c: sta for sta, c in coordinates.items()}
# reduce number of coordinates in each area
hulls = {}
for name in areas:
points = np.array([coordinates[sta] for sta in areas[name]])
hull = scipy.spatial.ConvexHull(points)
hulls[name] = {
station_by_coordinate[tuple(p)]
for p in points[hull.vertices, :]
}
# calculated distances between unconnected areas
distance = {}
for a1 in areas:
for a2 in areas:
name = frozenset((a1, a2))
if name in distance or a1 == a2:
continue
dists = {}
for sta1 in hulls[a1]:
for sta2 in hulls[a2]:
args = coordinates[sta1] + coordinates[sta2]
dist = gps2dist_azimuth(*args)[0]
dists[(sta1, sta2)] = dist
mink = min(dists, key=dists.get)
distance[name] = (dists[mink] / 1e3, mink)
# join unconnected regions if distance is smaller than max_distance
near_stations = {}
while len(distance) > 0:
nearest_pair = min(distance, key=distance.get)
dist = distance[nearest_pair][0]
if dist > max_distance:
break
s1, s2 = distance[nearest_pair][1]
near_stations[s1] = s2
near_stations[s2] = s1
a1, a2 = tuple(nearest_pair)
msg = 'connect areas %s and %s with distance %.1fkm'
log.debug(msg, a1, a2, dist)
distance.pop(nearest_pair)
areas[a1] |= areas.pop(a2)
hulls[a1] |= hulls.pop(a2)
for a3 in areas:
if a3 in (a1, a2):
continue
pair1 = frozenset((a1, a3))
pair2 = frozenset((a2, a3))
dist1 = distance[pair1]
dist2 = distance.pop(pair2)
if dist2[0] < dist1[0]:
distance[pair1] = dist2
return areas, near_stations
def analyse_earthquake(self, event_obj):
# Get event catalogue
self.event_cat = self.ds.events
comp_list = ['*Z', '*N', '*E']
# Launch the custom station/component selection dialog
sel_dlg = selectionDialog(parent=self, sta_list=self.ds.waveforms.list())
if sel_dlg.exec_():
select_sta, bool_comp = sel_dlg.getSelected()
query_comp = list(itertools.compress(comp_list, bool_comp))
# Open up a new stream object
self.st = Stream()
# use the ifilter functionality to extract desired streams to visualize
for station in self.ds.ifilter(self.ds.q.station == map(lambda el: el.split('.')[1], select_sta),
self.ds.q.channel == query_comp,
self.ds.q.event == event_obj):
for filtered_id in station.list():
if filtered_id == 'StationXML':
continue
self.st += station[filtered_id]
if self.st.__nonzero__():
# Get quake origin info
origin_info = event_obj.preferred_origin() or event_obj.origins[0]
# Iterate through traces
for tr in self.st:
# Run Java Script to highlight all selected stations in station view
js_call = "highlightStation('{station}')".format(station=tr.stats.network + '.' +tr.stats.station)
self.ui.web_view.page().mainFrame().evaluateJavaScript(js_call)
# Get inventory for trace
inv = self.ds.waveforms[tr.stats.network + '.' +tr.stats.station].StationXML
sta_coords = inv.get_coordinates(tr.get_id())
dist, baz, _ = gps2dist_azimuth(sta_coords['latitude'],
sta_coords['longitude'],
origin_info.latitude,
origin_info.longitude)
dist_deg = kilometer2degrees(dist/1000.0)
tt_model = TauPyModel(model='iasp91')
arrivals = tt_model.get_travel_times(origin_info.depth/1000.0, dist_deg, ('P'))
# Write info to trace header
tr.stats.distance = dist
tr.stats.ptt = arrivals[0]
# Sort the st by distance from quake
self.st.sort(keys=['distance'])
self.update_waveform_plot()
def setloc_source_centered(self, dist, azimuth, flattening):
self.dist = dist
self.azimuth = azimuth
xsrc = thetaphi2xyz(dist, azimuth)
xglb = SurfaceStation.src_rmat.dot(xsrc)
theta, phi = xyz2thetaphi(xglb)
self.lat, self.lon = thetaphi2latlon(theta, phi, flattening)
d, az, baz = gps2dist_azimuth(SurfaceStation.src_lat, SurfaceStation.src_lon,
self.lat, self.lon, a=1., f=flattening)
self.baz = np.radians(baz)
def get_event_params(eq_lat,eq_lon): dist_az = gps2dist_azimuth(eq_lat,eq_lon,0,0,a=6371000.0,f=0.0) dist_km = dist_az[0]/1000.0 dist_deg = kilometer2degrees(dist_km) az = dist_az[1] baz = dist_az[2] rotation_angle = -1.0*((baz-180) -90.0) #rotation_angle = -1.0*(az-90.0) return dist_deg,rotation_angle
def setloc_geographic(self, lat, lon, flattening):
self.lat = lat
self.lon = lon
theta, phi = latlon2thetaphi(lat, lon, flattening)
xglb = thetaphi2xyz(theta, phi)
xsrc = SurfaceStation.src_rmat.T.dot(xglb)
self.dist, self.azimuth = xyz2thetaphi(xsrc)
d, az, baz = gps2dist_azimuth(SurfaceStation.src_lat, SurfaceStation.src_lon,
self.lat, self.lon, a=1., f=flattening)
self.baz = np.radians(baz)
def chiapas_BAz():
"""case study of chiapas, return backazimuth values for rotating seismograms
"""
from obspy.geodetics import gps2dist_azimuth
event_latlon = (15.38,-94.66)
wpuk_latlon = (-40.06,176.44)
gcd,BAz,Az = gps2dist_azimuth(lat1=event_latlon[0],lon1=event_latlon[1],
lat2=wpuk_latlon[0],lon2=event_latlon[1])
return BAz
def distance(station, origin):
if hasattr(station, 'latitude') and\
hasattr(station, 'longitude'):
distance_in_m, _, _, = gps2dist_azimuth(station.latitude,
station.longitude,
origin.latitude,
origin.longitude)
return distance_in_m / 1000.
else:
raise Exception
def azimuthal_distribution_coefficient(self):
azimuths = []
for arrival in self.arrivals:
d, abaz, baaz = gps2dist_azimuth(self.lat, self.lon,
arrival.station.lat,
arrival.station.lon)
if abaz not in azimuths:
azimuths += [abaz]
hist = np.histogram(azimuths, bins=18, range=(0., 360.))
return sum([1 for count in hist[0] if count > 0]) /\
float(len(hist[1]) - 1)
def single_phase(self):
events = self.assoc_db.query(Associated).all()
for event in events:
event_id = event.id
ot = event.ot
#print event_id,ot
# Pick phases that are between origintime and origintime+max_tt
sta_assoc = []
for sta, in self.assoc_db.query(PickModified.sta).filter(PickModified.assoc_id==event_id).distinct().all(): # only associated single phase from stations not contribute p and s pairs
sta_assoc.append(sta)
# associate single phase
for sta, in self.assoc_db.query(PickModified.sta).filter(PickModified.assoc_id==None).filter(PickModified.time>ot).filter(PickModified.time<=(ot+timedelta(seconds=self.max_tt))).distinct().all():
station = self.tt_stations_db_1D.query(Station1D).filter(Station1D.sta==sta).first()
#print event.latitude,event.longitude,sta,station.latitude,station.longitude
d_km = gps2dist_azimuth(event.latitude,event.longitude,station.latitude,station.longitude)[0]/1000.
if (d_km < self.max_km) and (sta not in sta_assoc): # only associated single phase from stations not contribute p and s pairs
tt,d_diff = tt_km(self.tt_stations_db_1D,d_km)
picks_p = self.assoc_db.query(PickModified).filter(PickModified.sta==sta).filter(PickModified.time>=(ot+timedelta(seconds=tt.p_tt-0.5*self.aggr_window))).filter(PickModified.time<=(ot+timedelta(seconds=tt.p_tt+0.5*self.aggr_window))).all()
#print 'picks_p: ',picks_p, 'tt.p_tt: ',tt.p_tt
# if there are more than one modified pick in the aggr_window range, only associate the first modified pick
if picks_p:
modi_pick = picks_p[0] # the first modified pick
modi_pick.phase = 'P'
modi_pick.assoc_id = event.id
modi_pick.locate_flag = False
# Associated all the picks contribute to this single modified picks with assoc_id and phase
picks=self.assoc_db.query(Pick).filter(Pick.modified_id==modi_pick.id).all()
for pick in picks:
pick.phase='P'
pick.assoc_id=event.id
pick.locate_flag = False
picks_s = self.assoc_db.query(PickModified).filter(PickModified.sta==sta).filter(PickModified.time>=(ot+timedelta(seconds=tt.s_tt-0.5*self.aggr_window))).filter(PickModified.time<=(ot+timedelta(seconds=tt.s_tt+0.5*self.aggr_window))).all()
# if there are more than one modified pick in the aggr_window range, only associate the first modified pick
if picks_s:
modi_pick = picks_s[0] # the first modified pick
modi_pick.phase = 'S'
modi_pick.assoc_id = event.id
modi_pick.locate_flag = None
# Associated all the picks contribute to this single modified picks with assoc_id and phase
picks=self.assoc_db.query(Pick).filter(Pick.modified_id==modi_pick.id).all()
for pick in picks:
pick.phase='S'
pick.assoc_id=event.id
pick.locate_flag = None
self.assoc_db.commit()
def dist_baz_az2(eve, sta):
global StaDict
global AllEveDict
gcarcinfo = gps2dist_azimuth(StaDict[sta]['stla'], StaDict[sta]['stlo'],
AllEveDict[eve]['EVLA'],
AllEveDict[eve]['EVLO'])
gcarc = kilometers2degrees(gcarcinfo[0] / 1000)
dist = gcarcinfo[0] / 1000
baz = gcarcinfo[1]
az = gcarcinfo[2]
return f"{gcarc:.3f} {dist:.3f} {baz:.3f} {az:.3f}"
def Get_location(la_s, lo_s, la_r, lo_r, radius=3389.5, flattening=0):
"""
Get the epicentral distance, azimuth and backazimuth
"""
dist, az, baz = gps2dist_azimuth(lat1=la_s,
lon1=lo_s,
lat2=la_r,
lon2=lo_r,
a=radius,
f=flattening)
epi = kilometer2degrees(dist, radius=radius)
return epi, az, baz
def residuals_minimum(location,args):
# from obspy.core.util import gps2DistAzimuth
L=len(args)
residuals=0
i=0
while True:
residuals=residuals+(gps2dist_azimuth(location[1],location[0],args[i][2],args[i][1])[0]/1000*180/(np.pi*6371)-args[i][4])**2
if i==L-1:
break
else:
i=i+1
return np.sqrt(residuals/L)
def __init__(self, disp_file):
data, self.lon1, self.lat1, self.lon2, self.lat2 = \
readDisp(disp_file)
self.filename = os.path.basename(disp_file)
self.T = data[:, 0]
self.disp = data[:, 1]
self.err = data[:, 2]
self.valid = data[:, 3]
self.dist = gps2dist_azimuth(self.lat1, self.lon1, self.lat2,
self.lon2)[0] / 1000.0
mask = self.valid == 0
self.masked_disp = np.ma.masked_array(self.disp, mask=mask)
def calculate_baz(elat, elon, slat, slon):
"""
Calculate back azimuth(station to event azimuth)
:param elat: event latitude
:param elon: event longitude
:param slat: station latitude
:param slon: station longitude
:return: back azimuth
"""
_, _, baz = gps2dist_azimuth(elat, elon, slat, slon)
return baz
def horiz_rotate(st,event):
'''This function rotates horizontal components into radial and
transverse. Returns the radial component as a trace.
'''
# Calculate the back azimuth
dist, az, baz = gps2dist_azimuth(st[0].stats.coordinates.latitude,
st[0].stats.coordinates.longitude,event.origins[0].latitude,
event.origins[0].longitude)
# Rotate the stream
st = st.rotate(method='NE->RT',back_azimuth=baz)
return st.select(channel="??R")[0]
def locating(guess,*args):
# from obspy.core.util import gps2DistAzimuth
L=len(args)
residuals=0
i=0
while True:
# gps2DistAzimuth(lat1, lon1, lat2, lon2) Returns: (Great circle distance in m, azimuth A->B in degrees, azimuth B->A in degrees)
residuals=residuals+(gps2dist_azimuth(guess[1],guess[0],args[i][2],args[i][1])[0]/1000*180/(np.pi*6371)-args[i][4])**2
# np.sqrt((guess[0]-args[i][1])**2+(guess[1]-args[i][2])**2)-args[i][4])**2
if i==L-1:
break
else:
i=i+1
return np.sqrt(residuals/L)
def bin_filter(st,bin_lat0,bin_lon0,bin_radius):
'''
Removes traces which lie outside of a circular bin.
bin_radius must be given in degrees.
'''
for tr in st:
dist = gps2dist_azimuth(tr.stats.sac['stla'],tr.stats.sac['stlo'],
bin_lat0, bin_lon0)
dist_m = dist[0]
dist_deg = kilometer2degrees(dist_m/1000.0)
if dist_deg > bin_radius:
st.remove(tr)
def get_station_info(stats):
sta1 = '{}.{}.{}.{}'.format(stats.network,stats.station,stats.location,
stats.channel)
sta2 = '{}.{}.{}.{}'.format(stats.sac.kuser0.strip(),stats.sac.kevnm.strip(),
stats.sac.kuser1.strip(),stats.sac.kuser2.strip())
lat1 = stats.sac.stla
lon1 = stats.sac.stlo
lat2 = stats.sac.evla
lon2 = stats.sac.evlo
dist = stats.sac.dist
az = gps2dist_azimuth(lat1,lon1,lat2,lon2)[2]
return([sta1,sta2,lat1,lon1,lat2,lon2,dist,az])
def test_gps2DistAzimuthWithGeographiclib(self):
"""
Testing gps2dist_azimuth function using the module geographiclib.
"""
# nearly antipodal points
result = gps2dist_azimuth(15.26804251, 2.93007342, -14.80522806,
-177.2299081)
self.assertAlmostEqual(result[0], 19951425.048688546)
self.assertAlmostEqual(result[1], 8.65553241932755)
self.assertAlmostEqual(result[2], 351.36325485132306)
# out of bounds
self.assertRaises(ValueError, gps2dist_azimuth, 91, 0, 0, 0)
self.assertRaises(ValueError, gps2dist_azimuth, -91, 0, 0, 0)
self.assertRaises(ValueError, gps2dist_azimuth, 0, 0, 91, 0)
self.assertRaises(ValueError, gps2dist_azimuth, 0, 0, -91, 0)
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()
def prepare_array(self):
# station
self.sta_lat = [window.latitude for window in self.trwins]
self.sta_lon = [window.longitude for window in self.trwins]
for sta_lat, sta_lon in zip(self.sta_lat, self.sta_lon):
dist, az, baz = gps2dist_azimuth(self.cmtsource.latitude,
self.cmtsource.longitude,
sta_lat, sta_lon)
self.sta_azi.append(az)
self.sta_theta.append(az / 180.0 * np.pi)
if self.mode == "regional":
# if regional, then use original distance(in km)
self.sta_dist.append(dist / 1000.0)
elif self.mode == "global":
# if global, then use degree as unit
self.sta_dist.append(dist/EARTH_HC)
def data_request(client_name, cat_client_name, start, end, minmag, net=None, scode="*", channels="*", minlat=None,
maxlat=None,minlon=None,maxlon=None, station_minlat=None,
station_maxlat=None, station_minlon=None, station_maxlon=None, mindepth=None, maxdepth=None,
radialcenterlat=None, radialcenterlon=None, minrad=None, maxrad=None,
station_radialcenterlat=None, station_radialcenterlon=None, station_minrad=None, station_maxrad=None,
azimuth=None, baz=False, t_before_first_arrival=1, t_after_first_arrival=9, savefile=False, file_format='SAC'):
"""
Searches in a given Database for seismic data. Restrictions in terms of starttime, endtime, network etc can be made.
If data is found it returns a stream variable, with the waveforms, an inventory with all station and network information
and a catalog with the event information.
:param client_name: Name of desired fdsn client, for a list of all clients see:
https://docs.obspy.org/tutorial/code_snippets/retrieving_data_from_datacenters.html
:type client_name: string
:param cat_client_name: Name of Event catalog
:type cat_client_name: string
:param start, end: starttime, endtime
:type : UTCDateTime
:param minmag: Minimum magnitude of event
:type minmag: float
:param net: Network code for which to search data for
:type net: string
:param scode: Station code for which to search data for
:type scode: string
:param channels: Used channels of stations
:type channels: string
:param minlat, maxlat, minlon, maxlon: Coordinate-window of interest
:type : float
:param mindepth, maxdepth: depth information of event in km
:type : float
:param radialcenterlat, radialcenterlon: Centercoordinates of a radialsearch, if radialsearch=True
:type : float
:param minrad, maxrad: Minimum and maximum radii for radialsearch
:type : float
:param azimuth: Desired range of azimuths of event, station couples in deg as a list [minimum azimuth, maximum azimuth]
:type azimuth: list
:param baz: Desired range of back-azimuths of event, station couples in deg as a list [minimum back azimuth, maximum back azimuth]
:type baz: list
:param t_before_first_arrival, t_before_after_arrival: Length of the seismograms, startingpoint, minutes before 1st arrival and
minutes after 1st arrival.
:type t_before_first_arrival, t_before_after_arrival: float, int
:param savefile: if True, Stream, Inventory and Catalog will be saved local, in the current directory.
:type savefile: bool
:param format: File-format of the data, for supported formats see: https://docs.obspy.org/packages/autogen/obspy.core.stream.Stream.write.html#obspy.core.stream.Stream.write
:type format: string
returns
:param: list_of_stream, Inventory, Catalog
:type: list, obspy, obspy
### Example 1 ###
from obspy import UTCDateTime
from sipy.util.data_request import data_request
start = UTCDateTime(2010,1,1,0,0)
end = UTCDateTime(2010,12,31,0,0)
minmag = 8
station = '034A'
list_of_stream, inventory, cat = data_request('IRIS', start, end, minmag, net='TA', scode=station)
st = list_of_stream[0]
st = st.select(channel='BHZ')
st.normalize()
inv = inventory[0]
st.plot()
inv.plot()
cat.plot()
### Example 2 ###
from obspy import UTCDateTime
from sipy.util.data_request import data_request
start = UTCDateTime(2010,1,1,0,0)
end = UTCDateTime(2010,12,31,0,0)
minmag = 8
station = '034A'
client = 'IRIS'
cat_client = 'globalcmt'
list_of_stream, inventory, cat = data_request(client, cat_client, start, end, minmag, net='TA', scode=station)
st = list_of_stream[0]
st = st.select(channel='BHZ')
st.normalize()
inv = inventory[0]
st.plot()
inv.plot()
cat.plot()
"""
data =[]
stream = Stream()
streamall = []
#build in different approach for catalog search, using urllib
if cat_client_name == 'globalcmt':
catalog = request_gcmt(starttime=start, endtime=end, minmagnitude=minmag, mindepth=mindepth, maxdepth=maxdepth, minlatitude=minlat, maxlatitude=maxlat, minlongitude=minlon, maxlongitude=maxlon)
client = Client(client_name)
else:
client = Client(client_name)
try:
catalog = client.get_events(starttime=start, endtime=end, minmagnitude=minmag, mindepth=mindepth, maxdepth=maxdepth, latitude=radialcenterlat, longitude=radialcenterlon, minradius=minrad, maxradius=maxrad,minlatitude=minlat, maxlatitude=maxlat, minlongitude=minlon, maxlongitude=maxlon)
except:
print("No events found for given parameters.")
return
print("Following events found: \n")
print(catalog)
m = TauPyModel(model="ak135")
Plist = ["P", "Pdiff", "p"]
for event in catalog:
print("\n")
print("########################################")
print("Looking for available data for event: \n")
print(event.short_str())
print("\n")
origin_t = event.origins[0].time
station_stime = UTCDateTime(origin_t - 3600*24)
station_etime = UTCDateTime(origin_t + 3600*24)
try:
inventory = client.get_stations(network=net, station=scode, level="station", starttime=station_stime, endtime=station_etime,
minlatitude=station_minlat, maxlatitude=station_maxlat, minlongitude=station_minlon, maxlongitude=station_maxlon,
latitude=station_radialcenterlat, longitude=station_radialcenterlon, minradius=station_minrad, maxradius=station_maxrad)
print("Inventory found.")
except:
print("No Inventory found for given parameters")
return
for network in inventory:
elat = event.origins[0].latitude
elon = event.origins[0].longitude
depth = event.origins[0].depth/1000.
array_fits = True
if azimuth or baz:
cog=center_of_gravity(network)
slat = cog['latitude']
slon = cog['longitude']
epidist = locations2degrees(slat,slon,elat,elon)
arrivaltime = m.get_travel_times(source_depth_in_km=depth, distance_in_degree=epidist,
phase_list=Plist)
P_arrival_time = arrivaltime[0]
Ptime = P_arrival_time.time
tstart = UTCDateTime(event.origins[0].time + Ptime - t_before_first_arrival * 60)
tend = UTCDateTime(event.origins[0].time + Ptime + t_after_first_arrival * 60)
center = geometrical_center(inv)
clat = center['latitude']
clon = center['longitude']
if azimuth:
print("Looking for events in the azimuth range of %f to %f" % (azimuth[0], azimuth[1]) )
center_az = gps2dist_azimuth(clat, clon, elat, elon)[1]
if center_az > azimuth[1] and center_az < azimuth[0]:
print("Geometrical center of Array out of azimuth bounds, \ncheking if single stations fit")
array_fits = False
elif baz:
print("Looking for events in the back azimuth range of %f to %f" %(baz[0], baz[1]))
center_baz = gps2dist_azimuth(clat, clon, elat, elon)[2]
if center_baz > baz[1] and center_baz < baz[0]:
print("Geometrical center of Array out of back azimuth bounds, \ncheking if single stations fit")
array_fits = False
# If array fits to azimuth/back azimuth or no azimuth/back azimuth is given
no_of_stations = 0
if array_fits:
for station in network:
epidist = locations2degrees(station.latitude,station.longitude,elat,elon)
arrivaltime = m.get_travel_times(source_depth_in_km=depth, distance_in_degree=epidist,
phase_list=Plist)
P_arrival_time = arrivaltime[0]
Ptime = P_arrival_time.time
tstart = UTCDateTime(event.origins[0].time + Ptime - t_before_first_arrival * 60)
tend = UTCDateTime(event.origins[0].time + Ptime + t_after_first_arrival * 60)
try:
streamreq = client.get_waveforms(network=network.code, station=station.code, location='*', channel=channels, starttime=tstart, endtime=tend, attach_response=True)
no_of_stations += 1
print("Downloaded data for %i of %i available stations!" % (no_of_stations, network.selected_number_of_stations), end='\r' )
sys.stdout.flush()
stream += streamreq
try:
if inventory_used:
inventory_used += client.get_stations(network=net, station=scode, level="station", starttime=station_stime, endtime=station_etime,
minlatitude=station_minlat, maxlatitude=station_maxlat, minlongitude=station_minlon, maxlongitude=station_maxlon,
latitude=station_radialcenterlat, longitude=station_radialcenterlon, minradius=station_minrad, maxradius=station_maxrad)
except:
inventory_used = client.get_stations(network=net, station=scode, level="station", starttime=station_stime, endtime=station_etime,
minlatitude=station_minlat, maxlatitude=station_maxlat, minlongitude=station_minlon, maxlongitude=station_maxlon,
latitude=station_radialcenterlat, longitude=station_radialcenterlon, minradius=station_minrad, maxradius=station_maxrad)
except:
continue
# If not checking each station individually.
else:
for station in network:
epidist = locations2degrees(station.latitude,station.longitude,elat,elon)
arrivaltime = m.get_travel_times(source_depth_in_km=depth, distance_in_degree=epidist,
phase_list=Plist)
P_arrival_time = arrivaltime[0]
Ptime = P_arrival_time.time
tstart = UTCDateTime(event.origins[0].time + Ptime - t_before_first_arrival * 60)
tend = UTCDateTime(event.origins[0].time + Ptime + t_after_first_arrival * 60)
fit = False
if azimuth:
stat_az = gps2dist_azimuth(station.latitude, station.longitude, elat, elon)[1]
if stat_az > azimuth[1] and stat_az < azimuth[0]: fit = True
elif baz:
stat_baz = gps2dist_azimuth(station.latitude, station.longitude, elat, elon)[2]
if stat_baz > baz[1] and stat_baz < baz[0]: fit = True
if fit:
try:
streamreq = client.get_waveforms(network = network.code, station = station.code, location='*', channel = channels, startime = tstart, endtime = tend, attach_response = True)
no_of_stations += 1
print("Downloaded data for %i of %i available stations!" % (no_of_stations, network.selected_number_of_stations), end='\r' )
sys.stdout.flush()
stream += streamreq
try:
if inventory_used:
inventory_used += client.get_stations(network=net, station=scode, level="station", starttime=station_stime, endtime=station_etime,
minlatitude=station_minlat, maxlatitude=station_maxlat, minlongitude=station_minlon, maxlongitude=station_maxlon,
latitude=station_radialcenterlat, longitude=station_radialcenterlon, minradius=station_minrad, maxradius=station_maxrad)
except:
inventory_used = client.get_stations(network=net, station=scode, level="station", starttime=station_stime, endtime=station_etime,
minlatitude=station_minlat, maxlatitude=station_maxlat, minlongitude=station_minlon, maxlongitude=station_maxlon,
latitude=station_radialcenterlat, longitude=station_radialcenterlon, minradius=station_minrad, maxradius=station_maxrad)
except:
continue
try:
if invall:
invall += inventory
except:
invall = inventory
attach_network_to_traces(stream, inventory)
attach_coordinates_to_traces(stream, inventory, event)
streamall.append(stream)
stream = Stream()
if savefile:
stname = str(origin_t).split('.')[0] + ".MSEED"
invname = stname + "_inv.xml"
catname = stname + "_cat.xml"
stream.write(stname, format=file_format)
inventory.write(invname, format="STATIONXML")
catalog.write(catname, format="QUAKEML")
plt.ion()
#invall.plot()
#catalog.plot()
plt.ioff()
inventory = invall
list_of_stream = streamall
return(list_of_stream, inventory, catalog)
def get_rupture_onset(home,project_name,slip,fault_array,model_name,hypocenter,rise_time_depths,M0):
'''
Using a custom built tvel file ray trace from hypocenter to determine rupture
onset times
'''
from numpy import genfromtxt,zeros,arctan,sin,r_,where,log10,isnan
from obspy.geodetics import gps2dist_azimuth
#Load velocity model
vel=genfromtxt(home+project_name+'/structure/'+model_name)
# Convert from thickness to depth to bottom of layer
depth_to_top=r_[0,vel[:,0].cumsum()[0:-1]]
#Get rupture speed shear-wave multipliers
rupture_multiplier=zeros(len(vel))
# Shallow
i=where(depth_to_top<=rise_time_depths[0])[0]
rupture_multiplier[i]=0.56
# Deep
i=where(depth_to_top>=rise_time_depths[1])[0]
rupture_multiplier[i]=0.8
# Transition
i=where((depth_to_top<rise_time_depths[1]) & (depth_to_top>rise_time_depths[0]))[0]
slope=(0.8-0.56)/(rise_time_depths[1]-rise_time_depths[0])
intercept=0.8-slope*rise_time_depths[1]
rupture_multiplier[i]=slope*depth_to_top[i]+intercept
#Loop over all faults
t_onset=zeros(len(slip))
for kfault in range(len(slip)):
D,az,baz=gps2dist_azimuth(hypocenter[1],hypocenter[0],fault_array[kfault,2],fault_array[kfault,1])
D=D/1000
#Start and stop depths
if fault_array[kfault,3]<hypocenter[2]:
zshallow=fault_array[kfault,3]
zdeep=hypocenter[2]
else:
zdeep=fault_array[kfault,3]
zshallow=hypocenter[2]
#Get angle between depths
theta=arctan((zdeep-zshallow)/D)
# get hypotenuse distance on all layers
delta_ray=vel[:,0]/sin(theta)
# Calculate distance in each layer
depth1=0
depth2=vel[0,0]
length_ray=zeros(len(vel))
for klayer in range(len(vel)):
if zshallow>depth1 and zdeep<depth2: #both points in same layer
length_ray[klayer]=abs(zshallow-zdeep)/sin(theta)
elif zshallow>depth1 and zshallow<depth2: #This is the top
length_ray[klayer]=abs(depth2-zshallow)/sin(theta)
elif zdeep>depth1 and zdeep<depth2: #This is the bottom
length_ray[klayer]=abs(depth1-zdeep)/sin(theta)
elif depth1>zshallow and depth2<zdeep: #Use full layer thickness for ray path length
length_ray[klayer]=delta_ray[klayer]
else: #Some other layer, do nothing
pass
#Update reference depths
if klayer<len(vel)-1: #last layer:
depth1=depth2
depth2=depth2+vel[klayer+1,0]
else:
depth1=depth2
depth2=1e6
#Now multiply ray path length times rupture velocity
ray_times=length_ray/(vel[:,1]*rupture_multiplier)
t_onset[kfault]=ray_times.sum()
#Now perturb onset times according to Graves-Pitarka eq 5 and 6
delta_t=((M0*1e7)**(1./3))*1.8e-9
slip_average=slip.mean()
i=where(slip>0.05*slip_average)[0]
perturbation=(log10(slip)-log10(slip_average))/(log10(slip.max())-log10(slip_average))
t_onset_final=t_onset.copy()
t_onset_final[i]=t_onset[i]-delta_t*perturbation[i]
#Check for negative times
i=where(t_onset_final<0)[0]
t_onset_final[i]=t_onset[i]
#Check for nan times
i=where(isnan(t_onset_final)==True)[0]
t_onset_final[i]=0
return t_onset_final
def f(lat,lon,location):
return abs(gps2dist_azimuth(lat,lon,location[0],location[1])[0])
stats.attrs['ntraces'] = ntraces
stats.attrs['Fs'] = Fs
stats.attrs['nt'] = int(npts)
# DATASET NR 2: Source grid
sources = f_out.create_dataset('sourcegrid',data=srcgrid)
# DATASET Nr 3: Seismograms itself
traces = f_out.create_dataset('data',(ntraces,npts),dtype=np.float32)
for k in range(ntraces):
# for each location, determine the distance
lat = srcgrid[1,k]
lon = srcgrid[0,k]
r = gps2dist_azimuth(lat,lon,lat_sta,lon_sta)[0]
# evaluate the Greens fct.
g1 = green_membrane(r)
# apply the freq. domain taper
taper = np.zeros(freq.shape)
i0 = np.argmin(np.abs(freq-filt[0]))
i1 = np.argmin(np.abs(freq-filt[1]))
taper[i0:i1] = hann(i1-i0)
# transform back to time domain
g1_td = np.fft.irfft(g1)[0:3600]
g1_td_taper = np.fft.irfft(taper*g1)[0:3600]
#if k % 30000 == 0:
def get_rupture_onset(home,project_name,slip,fault_array,model_name,hypocenter,
rise_time_depths,M0,sigma_rise_time=0.2):
'''
Using a custom built tvel file ray trace from hypocenter to determine rupture
onset times
'''
from numpy import genfromtxt,zeros,arctan2,sin,r_,where,log10,isnan,argmin,setxor1d,exp
from numpy .random import rand,randn
from obspy.geodetics import gps2dist_azimuth
#Load velocity model
vel=genfromtxt(home+project_name+'/structure/'+model_name)
# Convert from thickness to depth to bottom of layer
depth_to_top=r_[0,vel[:,0].cumsum()[0:-1]]
# #Get rupture speed shear-wave multipliers
# rupture_multiplier=zeros(len(vel))
# # Shallow
# i=where(depth_to_top<=rise_time_depths[0])[0]
# rupture_multiplier[i]=0.56
# # Deep
# i=where(depth_to_top>=rise_time_depths[1])[0]
# rupture_multiplier[i]=0.8
# # Transition
# i=where((depth_to_top<rise_time_depths[1]) & (depth_to_top>rise_time_depths[0]))[0]
# slope=(0.8-0.56)/(rise_time_depths[1]-rise_time_depths[0])
# intercept=0.8-slope*rise_time_depths[1]
# rupture_multiplier[i]=slope*depth_to_top[i]+intercept
#Get rupture speed shear-wave multipliers
rupture_multiplier=zeros(len(vel))
# Shallow
i=where(depth_to_top<=rise_time_depths[0])[0]
rupture_multiplier[i]=0.49
# Deep
i=where(depth_to_top>=rise_time_depths[1])[0]
rupture_multiplier[i]=0.7
# Transition
i=where((depth_to_top<rise_time_depths[1]) & (depth_to_top>rise_time_depths[0]))[0]
slope=(0.7-0.49)/(rise_time_depths[1]-rise_time_depths[0])
intercept=0.7-slope*rise_time_depths[1]
rupture_multiplier[i]=slope*depth_to_top[i]+intercept
#Perturb depths of the hypocenter so that faults at the same depth are not zero onset
delta=0.00001
i_same_as_hypo=where(fault_array[:,3]==hypocenter[2])[0]
dist=((fault_array[:,1]-hypocenter[0])**2+(fault_array[:,2]-hypocenter[1])**2)**0.5
i_hypo=argmin(dist)
#Get faults at same depth that are NOT the hypo
i_same_as_hypo=setxor1d(i_same_as_hypo,i_hypo)
#perturb
R=rand(1)
fault_array[i_hypo,3]=fault_array[i_hypo,3]-delta*R
hypocenter[2]=hypocenter[2]-delta*R
R=rand(len(i_same_as_hypo))
fault_array[i_same_as_hypo,3]=fault_array[i_same_as_hypo,3]+delta*R
#Loop over all faults
t_onset=zeros(len(slip))
#Perturb all subfault depths a tiny amount by some random number so that they NEVER lie on a layer interface
z_perturb=(rand(len(fault_array))-0.5)*1e-6
fault_array[:,3]=fault_array[:,3]+z_perturb
for kfault in range(len(slip)):
D,az,baz=gps2dist_azimuth(hypocenter[1],hypocenter[0],fault_array[kfault,2],fault_array[kfault,1])
D=D/1000
#Start and stop depths
if fault_array[kfault,3]<=hypocenter[2]:
zshallow=fault_array[kfault,3]
zdeep=hypocenter[2]
else:
zdeep=fault_array[kfault,3]
zshallow=hypocenter[2]
#Get angle between depths
theta=arctan2(zdeep-zshallow,D)
# get hypotenuse distance on all layers
delta_ray=vel[:,0]/sin(theta)
# Calculate distance in each layer
depth1=0
depth2=vel[0,0]
length_ray=zeros(len(vel))
for klayer in range(len(vel)):
if zshallow>depth1 and zdeep<depth2: #both points in same layer
length_ray[klayer]=abs(zshallow-zdeep)/sin(theta)
elif zshallow>depth1 and zshallow<depth2: #This is the top
length_ray[klayer]=abs(depth2-zshallow)/sin(theta)
elif zdeep>depth1 and zdeep<depth2: #This is the bottom
length_ray[klayer]=abs(depth1-zdeep)/sin(theta)
elif depth1>zshallow and depth2<zdeep: #Use full layer thickness for ray path length
length_ray[klayer]=delta_ray[klayer]
else: #Some other layer, do nothing
pass
#Update reference depths
if klayer<len(vel)-1: #last layer:
depth1=depth2
depth2=depth2+vel[klayer+1,0]
else:
depth1=depth2
depth2=1e6
#Now multiply ray path length times rupture velocity
ray_times=length_ray/(vel[:,1]*rupture_multiplier)
t_onset[kfault]=ray_times.sum()
#Now perturb onset times according to Graves-Pitarka eq 5 and 6 (assumes 1:1 corelation with slip)
delta_t0=((M0*1e7)**(1./3))*1.8e-9
#GP 2015 extra perturbation to destroy the 1:1 correlation with slip
rand_numb=randn()
delta_t=delta_t0*exp(sigma_rise_time*rand_numb)
#Now apply total perturbation
slip_average=slip.mean()
i=where(slip>0.05*slip_average)[0] #perturbation is applied only to subfaults with significant slip
perturbation=(log10(slip)-log10(slip_average))/(log10(slip.max())-log10(slip_average))
t_onset_final=t_onset.copy()
t_onset_final[i]=t_onset[i]-delta_t*perturbation[i]
#Check for negative times
i=where(t_onset_final<0)[0]
t_onset_final[i]=t_onset[i]
#Reassign subfaults within the "nucleation zone" to be their original, unperturbed onsets
#nu=some-relation-to-M0
i=where(t_onset<5.5)[0]
t_nucleation_edge=max(t_onset[i])
t_onset_final=t_onset_final+t_nucleation_edge
t_onset_final[i]=t_onset[i]
#Check for nan times
i=where(isnan(t_onset_final)==True)[0]
t_onset_final[i]=0
return t_onset_final
sta2 = os.path.splitext(os.path.basename(t))[0].split('--')[1]
datafile = os.path.join(data_dir,os.path.basename(t))
tr = read(t)[0]
i = tr.stats.npts // 2 + 1
tr.data[0:i] *= amps[cnt]
cnt += 1
tr.data[i+1:] *= amps[cnt]
cnt += 1
tr.stats.network = sta1.split('.')[0]
tr.stats.station = sta1.split('.')[1]
tr.stats.location = ''
tr.stats.channel = sta1.split('.')[3]
tr.stats.sac={}
tr.stats.sac.kuser0 = sta2.split('.')[0]
tr.stats.sac.kevnm = sta2.split('.')[1]
tr.stats.sac.kuser1 = ''
tr.stats.sac.kuser2 = sta2.split('.')[3]
tr.stats.sac.stla = coords[sta1][0]
tr.stats.sac.stlo = coords[sta1][1]
tr.stats.sac.evla = coords[sta2][0]
tr.stats.sac.evlo = coords[sta2][1]
tr.stats.sac.dist = gps2dist_azimuth(coords[sta1][0],coords[sta1][1],coords[sta2][0],coords[sta2][1])[0]
tr.write(datafile,format='SAC')
from collections import defaultdict
import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from mpl_toolkits.basemap import Basemap
from matplotlib.patches import Rectangle
from obspy.geodetics import gps2dist_azimuth
from obspy.imaging.beachball import beach
from . import logger
from .util import get_cmt_par, get_trwin_tag
from .measure import _envelope
# earth half circle
EARTH_HC, _, _ = gps2dist_azimuth(0, 0, 0, 180)
def _plot_new_seismogram_sub(trwin, outputdir, cmtsource, figure_format):
obsd = trwin.datalist['obsd']
synt = trwin.datalist['synt']
new_synt = trwin.datalist['new_synt']
station = obsd.stats.station
network = obsd.stats.network
channel = obsd.stats.channel
location = obsd.stats.location
outputfig = os.path.join(outputdir, "%s.%s.%s.%s.%s" % (
network, station, location, channel, figure_format))
if cmtsource is None:
st.simulate(paz_remove="self", paz_simulate=paz_wa, water_level=10)
st.trim(t, t + 50)
tr_n = st.select(component="N")[0]
ampl_n = max(abs(tr_n.data))
tr_e = st.select(component="E")[0]
ampl_e = max(abs(tr_e.data))
ampl = max(ampl_n, ampl_e)
sta_lat = st[0].stats.coordinates.latitude
sta_lon = st[0].stats.coordinates.longitude
event_lat = 46.218
event_lon = 7.706
epi_dist, az, baz = gps2dist_azimuth(event_lat, event_lon, sta_lat, sta_lon)
epi_dist = epi_dist / 1000
if epi_dist < 60:
a = 0.018
b = 2.17
else:
a = 0.0038
b = 3.02
ml = log10(ampl * 1000) + a * epi_dist + b
print(station, ml)
mags.append(ml)
net_mag = np.median(mags)
print("Network magnitude:", net_mag)
tr[0].stats.sac.kuser0 = meta[meta['sta']==sta2].iloc[0]['net']
tr[0].stats.sac.kevnm = sta2
tr[0].stats.sac.kuser1 = ''
try:
tr[0].stats.sac.kuser2 = os.path.basename(t).split('.')[7] #os.path.basename(t).split('--')[1].split('.')[3]
except IndexError:
sta2 = os.path.basename(t).split('.')[7]
tr[0].stats.sac.user0 = 100.
#print(lat1 > -90.)
#print(lat1 < 90.)
#print(type(lat1))
#print(float(lat1))
#print(lat1,lon1,lat2,lon2)
geoinf = gps2dist_azimuth(lat1,lon1,lat2,lon2)
tr[0].stats.sac.dist = geoinf[0]
tr[0].stats.sac.az = geoinf[1]
tr[0].stats.sac.baz = geoinf[2]
tr[0].stats['distance'] = geoinf[0] # add stats.distance for section plot
#print(tr[0].stats.keys())
tr.write(t,format='SAC')
#tr.plot()
# # Back to my code
# Check the metadata again
ext = '*.sac'
