def station_to_target(s, quantity, store_id):
if quantity == 'restituted':
quantity = 'displacement'
return Target(codes=s.nsl() + tuple('Z'),
lat=s.lat,
lon=s.lon,
elevation=s.elevation,
quantity=quantity,
store_id=store_id)
class SimilarityMatrix(Object):
''' A container class to store a list of :py:class:`Similarity` instances
and how they have been calculated.'''
events = List.T(model.Event.T())
targets = List.T(Target.T())
similarities = List.T(Similarity.T())
filters = List.T(trace.FrequencyResponse.T())
padding = Float.T()
windowing_method = String.T()
vmin = Float.T()
vmax = Float.T()
def station_to_target(s, quantity, store_id):
if quantity == "restituted":
quantity = "displacement"
return Target(
codes=s.nsl() + tuple("Z"),
lat=s.lat,
lon=s.lon,
elevation=s.elevation,
quantity=quantity,
store_id=store_id,
)
def get_azimuthal_targets(store_id,
source,
radius,
azi_begin=0.,
azi_end=360.,
dazi=1.,
interpolation='multilinear',
components='RTZ',
quantity='displacement'):
assert dazi > 0.
assert azi_begin < azi_end
nstations = int((azi_end - azi_begin) // dazi)
assert nstations > 0
azimuths = num.linspace(azi_begin, azi_end, nstations)
coords = num.zeros((2, nstations))
coords[0, :] = num.cos(azimuths * d2r)
coords[1, :] = num.sin(azimuths * d2r)
coords *= radius
dips = {'R': 0., 'T': 0., 'Z': -90.}
for comp in components:
assert comp in dips.keys()
target_kwargs = dict(quantity='displacement',
interpolation=interpolation,
store_id=store_id)
targets = [
Target(lat=source.lat,
lon=source.lon,
north_shift=coords[0, iazi] + source.north_shift,
east_shift=coords[1, iazi] + source.east_shift,
azimuth={
'R': azi,
'T': azi + 90.,
'Z': 0.
}[channel],
dip=dips[channel],
codes=('', 'S%01d' % iazi, '', channel),
**target_kwargs) for iazi, azi in enumerate(azimuths)
for channel in components
]
for target, azi in zip(targets, azimuths):
target.azimuth = azi
target.dazi = dazi
return targets, azimuths
def make_targets(pile, stations):
targets = []
for nslc_id in pile.nslc_ids.keys():
for s in stations:
if util.match_nslc('%s.*'%(s.nsl_string()), nslc_id):
targets.append(Target(lat=s.lat,
lon=s.lon,
depth=s.depth,
elevation=s.elevation,
codes=nslc_id))
else:
continue
return targets
# We need a pyrocko.gf.Engine object which provides us with the traces
# extracted from the store. In this case we are going to use a local
# engine since we are going to query a local store.
engine = LocalEngine(store_superdirs=['/media/usb/gf_stores'])
# The store we are going extract data from:
store_id = 'crust2_dd'
# Define a list of pyrocko.gf.Target objects, representing the recording
# devices. In this case one station with a three component sensor will
# serve fine for demonstation.
channel_codes = 'ENZ'
targets = [
Target(lat=10.,
lon=10.,
store_id=store_id,
codes=('', 'STA', '', channel_code))
for channel_code in channel_codes
]
# Let's use a double couple source representation.
source_dc = DCSource(lat=11.,
lon=11.,
depth=10000.,
strike=20.,
dip=40.,
rake=60.,
magnitude=4.)
# Processing that data will return a pyrocko.gf.Reponse object.
response = engine.process(source_dc, targets)
def doCalc_syn (flag,Config,WaveformDict,FilterMetaData,Gmint,Gmaxt,TTTGridMap,
Folder,Origin, ntimes, switch, ev,arrayfolder, syn_in, parameter):
'''
method for calculating semblance of one station array
'''
Logfile.add ('PROCESS %d %s' % (flag,' Enters Semblance Calculation') )
Logfile.add ('MINT : %f MAXT: %f Traveltime' % (Gmint,Gmaxt))
cfg = ConfigObj (dict=Config)
dimX = cfg.dimX() # ('dimx')
dimY = cfg.dimY() # ('dimy')
winlen = cfg.winlen () # ('winlen')
step = cfg.step() # ('step')
new_frequence = cfg.newFrequency() #('new_frequence')
forerun= cfg.Int('forerun')
duration= cfg.Int('duration')
gridspacing = cfg.Float('gridspacing')
nostat = len (WaveformDict)
traveltimes = {}
recordstarttime = ''
minSampleCount = 999999999
if cfg.UInt ('forerun')>0:
ntimes = int ((cfg.UInt ('forerun') + cfg.UInt ('duration') ) / cfg.UInt ('step') )
else:
ntimes = int ((cfg.UInt ('duration') ) / cfg.UInt ('step') )
nsamp = int (winlen * new_frequence)
nstep = int (step * new_frequence)
from pyrocko import obspy_compat
from pyrocko import orthodrome, model
obspy_compat.plant()
############################################################################
calcStreamMap = WaveformDict
stations = []
py_trs = []
for trace in calcStreamMap.keys():
py_tr = obspy_compat.to_pyrocko_trace(calcStreamMap[trace])
py_trs.append(py_tr)
for il in FilterMetaData:
if str(il) == str(trace):
szo = model.Station(lat=il.lat, lon=il.lon,
station=il.sta, network=il.net,
channels=py_tr.channel,
elevation=il.ele, location=il.loc)
stations.append(szo) #right number of stations?
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
targets = []
for st in stations:
target = Target(
lat=st.lat,
lon=st.lon,
store_id=store_id,
codes=(st.network, st.station, st.location, 'BHZ'),
tmin=-1900,
tmax=3900,
interpolation='multilinear',
quantity=cfg.quantity())
targets.append(target)
if syn_in.nsources() == 1:
if syn_in.use_specific_stf() is True:
stf = syn_in.stf()
exec(stf)
else:
stf = STF()
if syn_in.source() == 'RectangularSource':
source = RectangularSource(
lat=float(syn_in.lat_0()),
lon=float(syn_in.lon_0()),
depth=syn_in.depth_syn_0()*1000.,
strike=syn_in.strike_0(),
dip=syn_in.dip_0(),
rake=syn_in.rake_0(),
width=syn_in.width_0()*1000.,
length=syn_in.length_0()*1000.,
nucleation_x=syn_in.nucleation_x_0(),
slip=syn_in.slip_0(),
nucleation_y=syn_in.nucleation_y_0(),
stf=stf,
time=util.str_to_time(syn_in.time_0()))
if syn_in.source() == 'DCSource':
source = DCSource(
lat=float(syn_in.lat_0()),
lon=float(syn_in.lon_0()),
depth=syn_in.depth_syn_0()*1000.,
strike=syn_in.strike_0(),
dip=syn_in.dip_0(),
rake=syn_in.rake_0(),
stf=stf,
time=util.str_to_time(syn_in.time_0()),
magnitude=syn_in.magnitude_0())
else:
sources = []
for i in range(syn_in.nsources()):
if syn_in.use_specific_stf() is True:
stf = syn_in.stf()
exec(stf)
else:
stf = STF()
if syn_in.source() == 'RectangularSource':
sources.append(RectangularSource(
lat=float(syn_in.lat_1(i)),
lon=float(syn_in.lon_1(i)),
depth=syn_in.depth_syn_1(i)*1000.,
strike=syn_in.strike_1(i),
dip=syn_in.dip_1(i),
rake=syn_in.rake_1(i),
width=syn_in.width_1(i)*1000.,
length=syn_in.length_1(i)*1000.,
nucleation_x=syn_in.nucleation_x_1(i),
slip=syn_in.slip_1(i),
nucleation_y=syn_in.nucleation_y_1(i),
stf=stf,
time=util.str_to_time(syn_in.time_1(i))))
if syn_in.source() == 'DCSource':
sources.append(DCSource(
lat=float(syn_in.lat_1(i)),
lon=float(syn_in.lon_1(i)),
depth=syn_in.depth_1(i)*1000.,
strike=syn_in.strike_1(i),
dip=syn_in.dip_1(i),
rake=syn_in.rake_1(i),
stf=stf,
time=util.str_to_time(syn_in.time_1(i)),
magnitude=syn_in.magnitude_1(i)))
source = CombiSource(subsources=sources)
response = engine.process(source, targets)
synthetic_traces = response.pyrocko_traces()
if cfg.Bool('synthetic_test_add_noise') is True:
from noise_addition import add_noise
trs_orgs = []
calcStreamMapsyn = calcStreamMap.copy()
#from pyrocko import trace
for tracex in calcStreamMapsyn.keys():
for trl in synthetic_traces:
if str(trl.name()[4:12]) == str(tracex[4:]):
tr_org = obspy_compat.to_pyrocko_trace(calcStreamMapsyn[tracex])
tr_org.downsample_to(2.0)
trs_orgs.append(tr_org)
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
synthetic_traces = add_noise(trs_orgs, engine, source.pyrocko_event(),
stations,
store_id, phase_def='P')
trs_org = []
trs_orgs = []
fobj = os.path.join(arrayfolder, 'shift.dat')
xy = num.loadtxt(fobj, usecols=1, delimiter=',')
calcStreamMapsyn = calcStreamMap.copy()
#from pyrocko import trace
for tracex in calcStreamMapsyn.keys():
for trl in synthetic_traces:
if str(trl.name()[4:12])== str(tracex[4:]):
mod = trl
recordstarttime = calcStreamMapsyn[tracex].stats.starttime.timestamp
recordendtime = calcStreamMapsyn[tracex].stats.endtime.timestamp
tr_org = obspy_compat.to_pyrocko_trace(calcStreamMapsyn[tracex])
trs_orgs.append(tr_org)
tr_org_add = mod.chop(recordstarttime, recordendtime, inplace=False)
synthetic_obs_tr = obspy_compat.to_obspy_trace(tr_org_add)
calcStreamMapsyn[tracex] = synthetic_obs_tr
trs_org.append(tr_org_add)
calcStreamMap = calcStreamMapsyn
if cfg.Bool('shift_by_phase_pws') == True:
calcStreamMapshifted= calcStreamMap.copy()
from obspy.core import stream
stream = stream.Stream()
for trace in calcStreamMapshifted.keys():
stream.append(calcStreamMapshifted[trace])
pws_stack = PWS_stack([stream], weight=2, normalize=True)
for tr in pws_stack:
for trace in calcStreamMapshifted.keys():
calcStreamMapshifted[trace]=tr
calcStreamMap = calcStreamMapshifted
if cfg.Bool('shift_by_phase_onset') == True:
pjoin = os.path.join
timeev = util.str_to_time(ev.time)
trs_orgs= []
calcStreamMapshifted= calcStreamMap.copy()
for trace in calcStreamMapshifted.keys():
tr_org = obspy_compat.to_pyrocko_trace(calcStreamMapshifted[trace])
trs_orgs.append(tr_org)
timing = CakeTiming(
phase_selection='first(p|P|PP|P(cmb)P(icb)P(icb)p(cmb)p)-20',
fallback_time=100.)
traces = trs_orgs
event = model.Event(lat=float(ev.lat), lon=float(ev.lon), depth=ev.depth*1000., time=timeev)
directory = arrayfolder
bf = BeamForming(stations, traces, normalize=True)
shifted_traces = bf.process(event=event,
timing=timing,
fn_dump_center=pjoin(directory, 'array_center.pf'),
fn_beam=pjoin(directory, 'beam.mseed'))
i = 0
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
for trace in calcStreamMapshifted.keys():
recordstarttime = calcStreamMapshifted[trace].stats.starttime.timestamp
recordendtime = calcStreamMapshifted[trace].stats.endtime.timestamp
mod = shifted_traces[i]
extracted = mod.chop(recordstarttime, recordendtime, inplace=False)
shifted_obs_tr = obspy_compat.to_obspy_trace(extracted)
calcStreamMapshifted[trace]=shifted_obs_tr
i = i+1
calcStreamMap = calcStreamMapshifted
weight = 0.
if cfg.Bool('weight_by_noise') == True:
from noise_analyser import analyse
pjoin = os.path.join
timeev = util.str_to_time(ev.time)
trs_orgs= []
calcStreamMapshifted= calcStreamMap.copy()
for trace in calcStreamMapshifted.keys():
tr_org = obspy_compat.to_pyrocko_trace(calcStreamMapshifted[trace])
trs_orgs.append(tr_org)
timing = CakeTiming(
phase_selection='first(p|P|PP|P(cmb)P(icb)P(icb)p(cmb)p)-20',
fallback_time=100.)
traces = trs_orgs
event = model.Event(lat=float(ev.lat), lon=float(ev.lon), depth=ev.depth*1000., time=timeev)
directory = arrayfolder
bf = BeamForming(stations, traces, normalize=True)
shifted_traces = bf.process(event=event,
timing=timing,
fn_dump_center=pjoin(directory, 'array_center.pf'),
fn_beam=pjoin(directory, 'beam.mseed'))
i = 0
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
weight = analyse(shifted_traces, engine, event, stations,
100., store_id, nwindows=1,
check_events=True, phase_def='P')
for trace in calcStreamMap.keys():
recordstarttime = calcStreamMap[trace].stats.starttime
d = calcStreamMap[trace].stats.starttime
d = d.timestamp
if calcStreamMap[trace].stats.npts < minSampleCount:
minSampleCount = calcStreamMap[trace].stats.npts
############################################################################
traces = num.ndarray (shape=(len(calcStreamMap), minSampleCount), dtype=float)
traveltime = num.ndarray (shape=(len(calcStreamMap), dimX*dimY), dtype=float)
latv = num.ndarray (dimX*dimY, dtype=float)
lonv = num.ndarray (dimX*dimY, dtype=float)
############################################################################
c=0
streamCounter = 0
for key in calcStreamMap.keys():
streamID = key
c2 = 0
for o in calcStreamMap[key]:
if c2 < minSampleCount:
traces[c][c2] = o
c2 += 1
for key in TTTGridMap.keys():
if streamID == key:
traveltimes[streamCounter] = TTTGridMap[key]
else:
"NEIN", streamID, key
if not streamCounter in traveltimes :
continue #hs : thread crashed before
g = traveltimes[streamCounter]
dimZ = g.dimZ
mint = g.mint
maxt = g.maxt
Latul = g.Latul
Lonul = g.Lonul
Lator = g.Lator
Lonor = g.Lonor
gridElem = g.GridArray
for x in range(dimX):
for y in range(dimY):
elem = gridElem[x, y]
traveltime [c][x * dimY + y] = elem.tt
latv [x * dimY + y] = elem.lat
lonv [x * dimY + y] = elem.lon
#endfor
c += 1
streamCounter += 1
#endfor
############################## CALCULATE PARAMETER FOR SEMBLANCE CALCULATION ##################
nsamp = winlen * new_frequence
nstep = int (step*new_frequence)
migpoints = dimX * dimY
dimZ = 0
new_frequence = cfg.newFrequency () # ['new_frequence']
maxp = int (Config['ncore'])
Logfile.add ('PROCESS %d NTIMES: %d' % (flag,ntimes))
if False :
print ('nostat ',nostat,type(nostat))
print ('nsamp ',nsamp,type(nsamp))
print ('ntimes ',ntimes,type(ntimes))
print ('nstep ',nstep,type(nstep))
print ('dimX ',dimX,type(dimX))
print ('dimY ',dimY,type(dimY))
print ('mint ',Gmint,type(mint))
print ('new_freq ',new_frequence,type(new_frequence))
print ('minSampleCount ',minSampleCount,type(minSampleCount))
print ('latv ',latv,type(latv))
print ('traces',traces,type(traces))
print ('traveltime',traveltime,type(traveltime))
#==================================semblance calculation========================================
t1 = time.time()
traces = traces.reshape (1,nostat*minSampleCount)
traveltime = traveltime.reshape (1,nostat*dimX*dimY)
USE_C_CODE = True
try:
if USE_C_CODE :
import Cm
import CTrig
start_time = time.time()
k = Cm.otest (maxp,nostat,nsamp,ntimes,nstep,dimX,dimY,Gmint,new_frequence,
minSampleCount,latv,lonv,traveltime,traces)
print("--- %s seconds ---" % (time.time() - start_time))
else :
start_time = time.time()
k = otest (maxp,nostat,nsamp,ntimes,nstep,dimX,dimY,Gmint,new_frequence,
minSampleCount,latv,lonv,traveltime,traces) #hs
print("--- %s seconds ---" % (time.time() - start_time))
except:
print("loaded tttgrid has probably wrong dimensions or stations, delete\
ttgrid or exchange")
t2 = time.time()
partSemb = k
partSemb_syn = partSemb.reshape (ntimes,migpoints)
return partSemb_syn
def generate_test_data_grid(store_id,
store_dirs,
coordinates,
geometry_params,
pre=0.5,
post=3,
stations_input=None,
batch_loading=256,
paths_disks=None):
engine = LocalEngine(store_superdirs=[store_dirs])
store = engine.get_store(store_id)
mod = store.config.earthmodel_1d
cake_phase = cake.PhaseDef("P")
phase_list = [cake_phase]
waveforms_events = []
waveforms_events_uncut = []
waveforms_noise = []
sources = []
lats = coordinates[0]
lons = coordinates[1]
depths = coordinates[2]
if stations_input is None:
stations_unsorted = model.load_stations("data/stations.pf")
else:
stations_unsorted = model.load_stations(stations_input)
for st in stations_unsorted:
st.dist = orthodrome.distance_accurate50m(st.lat, st.lon, lats[0],
lons[0])
st.azi = orthodrome.azimuth(st.lat, st.lon, lats[0], lons[0])
stations = sorted(stations_unsorted, key=lambda x: x.dist, reverse=True)
targets = []
events = []
mean_lat = []
mean_lon = []
max_rho = 0.
for st in stations:
mean_lat.append(st.lat)
mean_lon.append(st.lon)
for cha in st.channels:
if cha.name is not "R" and cha.name is not "T" and cha.name is not "Z":
target = Target(lat=st.lat,
lon=st.lon,
store_id=store_id,
interpolation='multilinear',
quantity='displacement',
codes=st.nsl() + (cha.name, ))
targets.append(target)
strikes = geometry_params[0]
dips = geometry_params[1]
rakes = geometry_params[2]
vs = geometry_params[3]
ws = geometry_params[4]
grid_points = []
for lat in lats:
for lon in lons:
for depth in depths:
grid_points.append([lat, lon, depth])
ray.init(num_cpus=num_cpus - 1)
npm = len(lats) * len(lons) * len(depths)
npm_geom = len(strikes) * len(dips) * len(rakes)
results = ray.get([
get_parallel_mtqt.remote(i,
targets,
store_id,
post,
pre,
stations,
mod,
grid_points[i],
strikes,
dips,
rakes,
vs,
ws,
store_dirs,
batch_loading=batch_loading,
npm=npm_geom,
paths_disks=paths_disks)
for i in range(len(grid_points))
])
ray.shutdown()
return waveforms_events
def doCalc(flag, Config, WaveformDict, FilterMetaData, Gmint, Gmaxt,
TTTGridMap, Folder, Origin, ntimes, switch, ev, arrayfolder,
syn_in):
'''
method for calculating semblance of one station array
'''
Logfile.add('PROCESS %d %s' % (flag, ' Enters Semblance Calculation'))
Logfile.add('MINT : %f MAXT: %f Traveltime' % (Gmint, Gmaxt))
cfg = ConfigObj(dict=Config)
cfg_f = FilterCfg(Config)
timeev = util.str_to_time(ev.time)
dimX = cfg.dimX() #('dimx')
dimY = cfg.dimY() #('dimy')
winlen = cfg.winlen() #('winlen')
step = cfg.step() #('step')
new_frequence = cfg.newFrequency() #('new_frequence')
forerun = cfg.Int('forerun')
duration = cfg.Int('duration')
nostat = len(WaveformDict)
traveltimes = {}
recordstarttime = ''
minSampleCount = 999999999
ntimes = int((forerun + duration) / step)
nsamp = int(winlen * new_frequence)
nstep = int(step * new_frequence)
from pyrocko import obspy_compat
from pyrocko import model
obspy_compat.plant()
############################################################################
calcStreamMap = WaveformDict
stations = []
py_trs = []
lats = []
lons = []
for trace in calcStreamMap.iterkeys():
py_tr = obspy_compat.to_pyrocko_trace(calcStreamMap[trace])
py_trs.append(py_tr)
for il in FilterMetaData:
if str(il) == str(trace):
szo = model.Station(lat=float(il.lat),
lon=float(il.lon),
station=il.sta,
network=il.net,
channels=py_tr.channel,
elevation=il.ele,
location=il.loc)
stations.append(szo)
lats.append(float(il.lat))
lons.append(float(il.lon))
array_center = [num.mean(lats), num.mean(lons)]
#==================================synthetic BeamForming======================
if cfg.Bool('synthetic_test') is True:
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
recordstarttimes = []
for tracex in calcStreamMap.iterkeys():
recordstarttimes.append(
calcStreamMap[tracex].stats.starttime.timestamp)
tr_org = obspy_compat.to_pyrocko_trace(calcStreamMap[tracex])
tmin = tr_org.tmin
#tmin= num.min(recordstarttimes)
targets = []
sources = []
for st in stations:
target = Target(lat=st.lat,
lon=st.lon,
store_id=store_id,
codes=(st.network, st.station, st.location, 'BHZ'),
tmin=-6900,
tmax=6900,
interpolation='multilinear',
quantity=cfg.quantity())
targets.append(target)
if syn_in.nsources() == 1:
if syn_in.use_specific_stf() is True:
stf = syn_in.stf()
exec(stf)
else:
stf = STF()
if syn_in.source() == 'RectangularSource':
sources.append(
RectangularSource(
lat=float(syn_in.lat_0()),
lon=float(syn_in.lon_0()),
east_shift=float(syn_in.east_shift_0()) * 1000.,
north_shift=float(syn_in.north_shift_0()) * 1000.,
depth=syn_in.depth_syn_0() * 1000.,
strike=syn_in.strike_0(),
dip=syn_in.dip_0(),
rake=syn_in.rake_0(),
width=syn_in.width_0() * 1000.,
length=syn_in.length_0() * 1000.,
nucleation_x=syn_in.nucleation_x_0(),
slip=syn_in.slip_0(),
nucleation_y=syn_in.nucleation_y_0(),
stf=stf,
time=util.str_to_time(syn_in.time_0())))
if syn_in.source() == 'DCSource':
sources.append(
DCSource(lat=float(syn_in.lat_0()),
lon=float(syn_in.lon_0()),
east_shift=float(syn_in.east_shift_0()) * 1000.,
north_shift=float(syn_in.north_shift_0()) * 1000.,
depth=syn_in.depth_syn_0() * 1000.,
strike=syn_in.strike_0(),
dip=syn_in.dip_0(),
rake=syn_in.rake_0(),
stf=stf,
time=util.str_to_time(syn_in.time_0()),
magnitude=syn_in.magnitude_0()))
else:
for i in range(syn_in.nsources()):
if syn_in.use_specific_stf() is True:
stf = syn_in.stf()
exec(stf)
else:
stf = STF()
if syn_in.source() == 'RectangularSource':
sources.append(
RectangularSource(
lat=float(syn_in.lat_1(i)),
lon=float(syn_in.lon_1(i)),
east_shift=float(syn_in.east_shift_1(i)) * 1000.,
north_shift=float(syn_in.north_shift_1(i)) * 1000.,
depth=syn_in.depth_syn_1(i) * 1000.,
strike=syn_in.strike_1(i),
dip=syn_in.dip_1(i),
rake=syn_in.rake_1(i),
width=syn_in.width_1(i) * 1000.,
length=syn_in.length_1(i) * 1000.,
nucleation_x=syn_in.nucleation_x_1(i),
slip=syn_in.slip_1(i),
nucleation_y=syn_in.nucleation_y_1(i),
stf=stf,
time=util.str_to_time(syn_in.time_1(i))))
if syn_in.source() == 'DCSource':
sources.append(
DCSource(
lat=float(syn_in.lat_1(i)),
lon=float(syn_in.lon_1(i)),
east_shift=float(syn_in.east_shift_1(i)) * 1000.,
north_shift=float(syn_in.north_shift_1(i)) * 1000.,
depth=syn_in.depth_syn_1(i) * 1000.,
strike=syn_in.strike_1(i),
dip=syn_in.dip_1(i),
rake=syn_in.rake_1(i),
stf=stf,
time=util.str_to_time(syn_in.time_1(i)),
magnitude=syn_in.magnitude_1(i)))
#source = CombiSource(subsources=sources)
synthetic_traces = []
for source in sources:
response = engine.process(source, targets)
synthetic_traces_source = response.pyrocko_traces()
if not synthetic_traces:
synthetic_traces = synthetic_traces_source
else:
for trsource, tr in zip(synthetic_traces_source,
synthetic_traces):
tr.add(trsource)
from pyrocko import trace as trld
#trld.snuffle(synthetic_traces)
timeev = util.str_to_time(syn_in.time_0())
if cfg.Bool('synthetic_test_add_noise') is True:
from noise_addition import add_noise
trs_orgs = []
calcStreamMapsyn = calcStreamMap.copy()
#from pyrocko import trace
for tracex in calcStreamMapsyn.iterkeys():
for trl in synthetic_traces:
if str(trl.name()[4:12]) == str(tracex[4:]) or str(
trl.name()[3:13]) == str(tracex[3:]) or str(
trl.name()[3:11]) == str(tracex[3:]) or str(
trl.name()[3:14]) == str(tracex[3:]):
tr_org = obspy_compat.to_pyrocko_trace(
calcStreamMapsyn[tracex])
tr_org.downsample_to(2.0)
trs_orgs.append(tr_org)
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
synthetic_traces = add_noise(trs_orgs,
engine,
source.pyrocko_event(),
stations,
store_id,
phase_def='P')
trs_org = []
trs_orgs = []
from pyrocko import trace
fobj = os.path.join(arrayfolder, 'shift.dat')
calcStreamMapsyn = calcStreamMap.copy()
for tracex in calcStreamMapsyn.iterkeys():
for trl in synthetic_traces:
if str(trl.name()[4:12]) == str(tracex[4:]) or str(
trl.name()[3:13]) == str(tracex[3:]) or str(
trl.name()[3:11]) == str(tracex[3:]) or str(
trl.name()[3:14]) == str(tracex[3:]):
mod = trl
recordstarttime = calcStreamMapsyn[
tracex].stats.starttime.timestamp
recordendtime = calcStreamMapsyn[
tracex].stats.endtime.timestamp
tr_org = obspy_compat.to_pyrocko_trace(
calcStreamMapsyn[tracex])
if switch == 0:
tr_org.bandpass(4, cfg_f.flo(), cfg_f.fhi())
elif switch == 1:
tr_org.bandpass(4, cfg_f.flo2(), cfg_f.fhi2())
trs_orgs.append(tr_org)
tr_org_add = mod.chop(recordstarttime,
recordendtime,
inplace=False)
synthetic_obs_tr = obspy_compat.to_obspy_trace(tr_org_add)
calcStreamMapsyn[tracex] = synthetic_obs_tr
trs_org.append(tr_org_add)
calcStreamMap = calcStreamMapsyn
if cfg.Bool('shift_by_phase_pws') == True:
calcStreamMapshifted = calcStreamMap.copy()
from obspy.core import stream
stream = stream.Stream()
for trace in calcStreamMapshifted.iterkeys():
stream.append(calcStreamMapshifted[trace])
pws_stack = PWS_stack([stream], weight=2, normalize=True)
for tr in pws_stack:
for trace in calcStreamMapshifted.iterkeys():
calcStreamMapshifted[trace] = tr
calcStreamMap = calcStreamMapshifted
if cfg.Bool('shift_by_phase_cc') is True:
from stacking import align_traces
calcStreamMapshifted = calcStreamMap.copy()
list_tr = []
for trace in calcStreamMapshifted.iterkeys():
tr_org = calcStreamMapshifted[trace]
list_tr.append(tr_org)
shifts, ccs = align_traces(list_tr, 10, master=False)
for shift in shifts:
for trace in calcStreamMapshifted.iterkeys():
tr_org = obspy_compat.to_pyrocko_trace(
calcStreamMapshifted[trace])
tr_org.shift(shift)
shifted = obspy_compat.to_obspy_trace(tr_org)
calcStreamMapshifted[trace] = shifted
calcStreamMap = calcStreamMapshifted
if cfg.Bool('shift_by_phase_onset') is True:
pjoin = os.path.join
timeev = util.str_to_time(ev.time)
trs_orgs = []
calcStreamMapshifted = calcStreamMap.copy()
for trace in calcStreamMapshifted.iterkeys():
tr_org = obspy_compat.to_pyrocko_trace(calcStreamMapshifted[trace])
trs_orgs.append(tr_org)
timing = CakeTiming(
phase_selection='first(p|P|PP|P(cmb)P(icb)P(icb)p(cmb)p)-20',
fallback_time=100.)
traces = trs_orgs
event = model.Event(lat=float(ev.lat),
lon=float(ev.lon),
depth=ev.depth * 1000.,
time=timeev)
directory = arrayfolder
bf = BeamForming(stations, traces, normalize=True)
shifted_traces = bf.process(event=event,
timing=timing,
fn_dump_center=pjoin(
directory, 'array_center.pf'),
fn_beam=pjoin(directory, 'beam.mseed'))
i = 0
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
for tracex in calcStreamMapshifted.iterkeys():
for trl in shifted_traces:
if str(trl.name()[4:12]) == str(tracex[4:]) or str(
trl.name()[3:13]) == str(tracex[3:]) or str(
trl.name()[3:11]) == str(tracex[3:]) or str(
trl.name()[3:14]) == str(tracex[3:]):
mod = trl
recordstarttime = calcStreamMapshifted[
tracex].stats.starttime.timestamp
recordendtime = calcStreamMapshifted[
tracex].stats.endtime.timestamp
tr_org = obspy_compat.to_pyrocko_trace(
calcStreamMapshifted[tracex])
tr_org_add = mod.chop(recordstarttime,
recordendtime,
inplace=False)
shifted_obs_tr = obspy_compat.to_obspy_trace(tr_org_add)
calcStreamMapshifted[tracex] = shifted_obs_tr
calcStreamMap = calcStreamMapshifted
weight = 1.
if cfg.Bool('weight_by_noise') is True:
from noise_analyser import analyse
pjoin = os.path.join
timeev = util.str_to_time(ev.time)
trs_orgs = []
calcStreamMapshifted = calcStreamMap.copy()
for trace in calcStreamMapshifted.iterkeys():
tr_org = obspy_compat.to_pyrocko_trace(calcStreamMapshifted[trace])
trs_orgs.append(tr_org)
timing = CakeTiming(
phase_selection='first(p|P|PP|P(cmb)P(icb)P(icb)p(cmb)p)-20',
fallback_time=100.)
traces = trs_orgs
event = model.Event(lat=float(ev.lat),
lon=float(ev.lon),
depth=ev.depth * 1000.,
time=timeev)
directory = arrayfolder
bf = BeamForming(stations, traces, normalize=True)
shifted_traces = bf.process(event=event,
timing=timing,
fn_dump_center=pjoin(
directory, 'array_center.pf'),
fn_beam=pjoin(directory, 'beam.mseed'))
i = 0
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
weight = analyse(shifted_traces,
engine,
event,
stations,
100.,
store_id,
nwindows=1,
check_events=True,
phase_def='P')
if cfg.Bool('array_response') is True:
from obspy.signal import array_analysis
from obspy.core import stream
ntimesr = int((forerun + duration) / step)
nsampr = int(winlen)
nstepr = int(step)
sll_x = -3.0
slm_x = 3.0
sll_y = -3.0
slm_y = 3.0
sl_s = 0.03,
# sliding window properties
# frequency properties
frqlow = 1.0,
frqhigh = 8.0
prewhiten = 0
# restrict output
semb_thres = -1e9
vel_thres = -1e9
stime = stime
etime = etime
stream_arr = stream.Stream()
for trace in calcStreamMapshifted.iterkeys():
stream_arr.append(calcStreamMapshifted[trace])
results = array_analysis.array_processing(stream_arr, nsamp, nstep,\
sll_x, slm_x, sll_y, slm_y,\
sl_s, semb_thres, vel_thres, \
frqlow, frqhigh, stime, \
etime, prewhiten)
timestemp = results[0]
relative_relpow = results[1]
absolute_relpow = results[2]
for trace in calcStreamMap.iterkeys():
recordstarttime = calcStreamMap[trace].stats.starttime
d = calcStreamMap[trace].stats.starttime
d = d.timestamp
if calcStreamMap[trace].stats.npts < minSampleCount:
minSampleCount = calcStreamMap[trace].stats.npts
###########################################################################
traces = num.ndarray(shape=(len(calcStreamMap), minSampleCount),
dtype=float)
traveltime = num.ndarray(shape=(len(calcStreamMap), dimX * dimY),
dtype=float)
latv = num.ndarray(dimX * dimY, dtype=float)
lonv = num.ndarray(dimX * dimY, dtype=float)
###########################################################################
c = 0
streamCounter = 0
for key in calcStreamMap.iterkeys():
streamID = key
c2 = 0
for o in calcStreamMap[key]:
if c2 < minSampleCount:
traces[c][c2] = o
c2 += 1
for key in TTTGridMap.iterkeys():
if streamID == key:
traveltimes[streamCounter] = TTTGridMap[key]
else:
"NEIN", streamID, key
if not streamCounter in traveltimes:
continue #hs : thread crashed before
g = traveltimes[streamCounter]
dimZ = g.dimZ
mint = g.mint
gridElem = g.GridArray
for x in range(dimX):
for y in range(dimY):
elem = gridElem[x, y]
traveltime[c][x * dimY + y] = elem.tt
latv[x * dimY + y] = elem.lat
lonv[x * dimY + y] = elem.lon
#endfor
c += 1
streamCounter += 1
#endfor
################ CALCULATE PARAMETER FOR SEMBLANCE CALCULATION ########
nsamp = winlen * new_frequence
nstep = step * new_frequence
migpoints = dimX * dimY
dimZ = 0
maxp = int(Config['ncore'])
Logfile.add('PROCESS %d NTIMES: %d' % (flag, ntimes))
if False:
print('nostat ', nostat, type(nostat))
print('nsamp ', nsamp, type(nsamp))
print('ntimes ', ntimes, type(ntimes))
print('nstep ', nstep, type(nstep))
print('dimX ', dimX, type(dimX))
print('dimY ', dimY, type(dimY))
print('mint ', Gmint, type(mint))
print('new_freq ', new_frequence, type(new_frequence))
print('minSampleCount ', minSampleCount, type(minSampleCount))
print('latv ', latv, type(latv))
print('traces', traces, type(traces))
#===================compressed sensing=================================
try:
cs = cfg.cs()
except:
cs = 0
if cs == 1:
csmaxvaluev = num.ndarray(ntimes, dtype=float)
csmaxlatv = num.ndarray(ntimes, dtype=float)
csmaxlonv = num.ndarray(ntimes, dtype=float)
folder = Folder['semb']
fobjcsmax = open(os.path.join(folder, 'csmax_%s.txt' % (switch)), 'w')
traveltimes = traveltime.reshape(1, nostat * dimX * dimY)
traveltime2 = toMatrix(traveltimes, dimX * dimY) # for relstart
traveltime = traveltime.reshape(dimX * dimY, nostat)
import matplotlib as mpl
import scipy.optimize as spopt
import scipy.fftpack as spfft
import scipy.ndimage as spimg
import cvxpy as cvx
import matplotlib.pyplot as plt
A = spfft.idct(traveltime, norm='ortho', axis=0)
n = (nostat * dimX * dimY)
vx = cvx.Variable(dimX * dimY)
res = cvx.Variable(1)
objective = cvx.Minimize(cvx.norm(res, 1))
back2 = num.zeros([dimX, dimY])
l = int(nsamp)
fobj = open(
os.path.join(folder,
'%s-%s_%03d.cs' % (switch, Origin['depth'], l)), 'w')
for i in range(ntimes):
ydata = []
try:
for tr in traces:
relstart = int((dimX * dimY - mint) * new_frequence +
0.5) + i * nstep
tr = spfft.idct(tr[relstart + i:relstart + i +
dimX * dimY],
norm='ortho',
axis=0)
ydata.append(tr)
ydata = num.asarray(ydata)
ydata = ydata.reshape(dimX * dimY, nostat)
constraints = [
res == cvx.sum_entries(0 + num.sum([
ydata[:, x] - A[:, x] * vx for x in range(nostat)
]))
]
prob = cvx.Problem(objective, constraints)
result = prob.solve(verbose=False, max_iters=200)
x = num.array(vx.value)
x = num.squeeze(x)
back1 = x.reshape(dimX, dimY)
sig = spfft.idct(x, norm='ortho', axis=0)
back2 = back2 + back1
xs = num.array(res.value)
xs = num.squeeze(xs)
max_cs = num.max(back1)
idx = num.where(back1 == back1.max())
csmaxvaluev[i] = max_cs
csmaxlatv[i] = latv[idx[0]]
csmaxlonv[i] = lonv[idx[1]]
fobj.write('%.5f %.5f %.20f\n' %
(latv[idx[0]], lonv[idx[1]], max_cs))
fobjcsmax.write('%.5f %.5f %.20f\n' %
(latv[idx[0]], lonv[idx[1]], max_cs))
fobj.close()
fobjcsmax.close()
except:
pass
#==================================semblance calculation========================================
t1 = time.time()
traces = traces.reshape(1, nostat * minSampleCount)
traveltimes = traveltime.reshape(1, nostat * dimX * dimY)
USE_C_CODE = False
#try:
if USE_C_CODE:
import Cm
import CTrig
start_time = time.time()
k = Cm.otest(maxp, nostat, nsamp, ntimes, nstep, dimX, dimY, Gmint,
new_frequence, minSampleCount, latv, lonv, traveltimes,
traces)
print("--- %s seconds ---" % (time.time() - start_time))
else:
start_time = time.time()
ntimes = int((forerun + duration) / step)
nsamp = int(winlen)
nstep = int(step)
Gmint = cfg.Int('forerun')
k = otest(maxp, nostat, nsamp, ntimes, nstep, dimX, dimY, Gmint,
new_frequence, minSampleCount, latv, lonv, traveltimes,
traces, calcStreamMap, timeev)
print("--- %s seconds ---" % (time.time() - start_time))
#except ValueError:
# k = Cm.otest(maxp,nostat,nsamp,ntimes,nstep,dimX,dimY,Gmint,new_frequence,
# minSampleCount,latv,lonv,traveltimes,traces)
# print "loaded tttgrid has probably wrong dimensions or stations,\
# delete ttgrid or exchange is recommended"
t2 = time.time()
Logfile.add('%s took %0.3f s' % ('CALC:', (t2 - t1)))
partSemb = k
partSemb = partSemb.reshape(ntimes, migpoints)
return partSemb, weight, array_center
def load(self, inv):
# load the data as a pyrocko pile and reform them into an array of traces
data = pile.make_pile([self.wdir + self.reduction])
self.traces = data.all()
# load station file
fname = self.wdir + self.network
stations_list = model.load_stations(fname)
for s in stations_list:
s.set_channels_by_name(*self.component.split())
self.targets = []
self.tmin, self.tmax = [], []
self.arrivals = []
self.names = []
for station, tr in zip(stations_list,
self.traces): # iterate over all stations
# print station.lat, station.lon
target = Target(
lat=np.float(station.lat), # station lat.
lon=np.float(station.lon), # station lon.
store_id=inv.store, # The gf-store to be used for this target,
# we can also employ different gf-stores for different targets.
interpolation='multilinear', # interp. method between gf cells
quantity='displacement', # wanted retrieved quantity
codes=station.nsl() +
('BH' + self.component, )) # Station and network code
# Next we extract the expected arrival time for this station from the the store,
# so we can use this later to define a cut-out window for the optimization:
self.targets.append(target)
self.names.append(station.nsl()[1])
# print len(self.traces), len(self.targets)
for station, tr, target in zip(stations_list, self.traces,
self.targets):
engine = LocalEngine(store_superdirs=inv.store_path)
store = engine.get_store(inv.store)
# trace.snuffle(tr, events=self.events)
arrival = store.t(self.phase, self.base_source,
target) # expected P-wave arrival
# print arrival
tmin = self.base_source.time + arrival - 15 # start 15s before theor. arrival
tmax = self.base_source.time + arrival + 15 # end 15s after theor. arrival
# # print self.tmin,self.tmax
tr.chop(tmin=tmin, tmax=tmax)
self.tmin.append(tmin)
self.tmax.append(tmax)
self.arrivals.append(self.base_source.time + arrival)
self.Npoints = len(self.targets)
# data vector
self.d = []
self.d.append(map((lambda x: getattr(x, 'ydata')), self.traces))
self.d = flatten(self.d)
# time vector
t = []
for i in xrange(self.Npoints):
t.append(self.traces[i].get_xdata())
# self.t.append(map((lambda x: getattr(x,'get_xdata()')),self.traces))
# convert time
self.t = time2dec(map(util.time_to_str, flatten(t)))
# print self.t
self.N = len(self.d)
scale = 2e-14
cake_phase = cake.PhaseDef("P")
phase_list = [cake_phase]
waveforms_events = []
waveforms_noise = []
stations = model.load_stations("stations.raw.txt")
nstations = len(stations)*3
noised = True
nevents = 1200
targets = []
for st in stations:
for cha in st.channels:
target = Target(
lat=st.lat,
lon=st.lon,
store_id=store_id,
interpolation='multilinear',
quantity='displacement',
codes=st.nsl() + (cha.name,))
targets.append(target)
import _pickle as pickle
try:
f = open("data_waveforms", 'rb')
waveforms_events, nsamples = pickle.load(f)
f.close()
except:
f = open("data_waveforms", 'wb')
for i in range(0, nevents):
trace_offset = 0.1
store_id = 'qplayground_total_4_mr_full'
store_id = 'crust2_u6'
engine = LocalEngine(store_superdirs=['.'])
ls = num.linspace
dips = ls(0, 360, nframes)
rakes = ls(0., 10., nframes)
strikes = ls(-180., 180, nframes)
depths = ls(10 * km, 10 * km, nframes)
east_shifts = ls(100., 200 * km, ntraces)
nshift = 5 * km
targets = [
Target(store_id=store_id, east_shift=east_shift, north_shift=east_shift)
for east_shift in east_shifts
]
ylim = ntraces * trace_offset
fig = plt.figure()
ax = fig.add_subplot(111, facecolor='#111111')
ax.set_xlim(-20, 190)
ax.set_ylim(-1., ylim + .7)
lines = []
for t in targets:
l, = ax.plot([], [],
color='white',
def doCalc_syn (flag,Config,WaveformDict,FilterMetaData,Gmint,Gmaxt,TTTGridMap,
Folder,Origin, ntimes, switch, ev,arrayfolder, syn_in, parameter):
'''
method for calculating semblance of one station array
'''
Logfile.add ('PROCESS %d %s' % (flag,' Enters Semblance Calculation') )
Logfile.add ('MINT : %f MAXT: %f Traveltime' % (Gmint,Gmaxt))
cfg = ConfigObj (dict=Config)
dimX = cfg.dimX() # ('dimx')
dimY = cfg.dimY() # ('dimy')
winlen = cfg.winlen () # ('winlen')
step = cfg.step() # ('step')
new_frequence = cfg.newFrequency() #('new_frequence')
forerun= cfg.Int('forerun')
duration= cfg.Int('duration')
gridspacing = cfg.Float('gridspacing')
nostat = len (WaveformDict)
traveltimes = {}
recordstarttime = ''
minSampleCount = 999999999
ntimes = int ((forerun + duration)/step)
nsamp = int (winlen * new_frequence)
nstep = int (step * new_frequence)
from pyrocko import obspy_compat
from pyrocko import orthodrome, model
obspy_compat.plant()
############################################################################
calcStreamMap = WaveformDict
stations = []
py_trs = []
for trace in calcStreamMap.iterkeys():
py_tr = obspy_compat.to_pyrocko_trace(calcStreamMap[trace])
py_trs.append(py_tr)
for il in FilterMetaData:
if str(il) == str(trace):
szo = model.Station(lat=il.lat, lon=il.lon,
station=il.sta, network=il.net,
channels=py_tr.channel,
elevation=il.ele, location=il.loc)
stations.append(szo) #right number of stations?
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
targets = []
for st in stations:
target = Target(
lat=st.lat,
lon=st.lon,
store_id=store_id,
codes=(st.network, st.station, st.location, 'BHZ'),
tmin=-1900,
tmax=3900,
interpolation='multilinear',
quantity=cfg.quantity())
targets.append(target)
if syn_in.nsources() == 1:
if syn_in.use_specific_stf() is True:
stf = syn_in.stf()
exec(stf)
else:
stf = STF()
if syn_in.source() == 'RectangularSource':
source = RectangularSource(
lat=float(syn_in.lat_0()),
lon=float(syn_in.lon_0()),
depth=syn_in.depth_syn_0()*1000.,
strike=syn_in.strike_0(),
dip=syn_in.dip_0(),
rake=syn_in.rake_0(),
width=syn_in.width_0()*1000.,
length=syn_in.length_0()*1000.,
nucleation_x=syn_in.nucleation_x_0(),
slip=syn_in.slip_0(),
nucleation_y=syn_in.nucleation_y_0(),
stf=stf,
time=util.str_to_time(syn_in.time_0()))
if syn_in.source() == 'DCSource':
source = DCSource(
lat=float(syn_in.lat_0()),
lon=float(syn_in.lon_0()),
depth=syn_in.depth_syn_0()*1000.,
strike=syn_in.strike_0(),
dip=syn_in.dip_0(),
rake=syn_in.rake_0(),
stf=stf,
time=util.str_to_time(syn_in.time_0()),
magnitude=syn_in.magnitude_0())
else:
sources = []
for i in range(syn_in.nsources()):
if syn_in.use_specific_stf() is True:
stf = syn_in.stf()
exec(stf)
else:
stf = STF()
if syn_in.source() == 'RectangularSource':
sources.append(RectangularSource(
lat=float(syn_in.lat_1(i)),
lon=float(syn_in.lon_1(i)),
depth=syn_in.depth_syn_1(i)*1000.,
strike=syn_in.strike_1(i),
dip=syn_in.dip_1(i),
rake=syn_in.rake_1(i),
width=syn_in.width_1(i)*1000.,
length=syn_in.length_1(i)*1000.,
nucleation_x=syn_in.nucleation_x_1(i),
slip=syn_in.slip_1(i),
nucleation_y=syn_in.nucleation_y_1(i),
stf=stf,
time=util.str_to_time(syn_in.time_1(i))))
if syn_in.source() == 'DCSource':
sources.append(DCSource(
lat=float(syn_in.lat_1(i)),
lon=float(syn_in.lon_1(i)),
depth=syn_in.depth_1(i)*1000.,
strike=syn_in.strike_1(i),
dip=syn_in.dip_1(i),
rake=syn_in.rake_1(i),
stf=stf,
time=util.str_to_time(syn_in.time_1(i)),
magnitude=syn_in.magnitude_1(i)))
source = CombiSource(subsources=sources)
response = engine.process(source, targets)
synthetic_traces = response.pyrocko_traces()
if cfg.Bool('synthetic_test_add_noise') is True:
from noise_addition import add_noise
trs_orgs = []
calcStreamMapsyn = calcStreamMap.copy()
#from pyrocko import trace
for tracex in calcStreamMapsyn.iterkeys():
for trl in synthetic_traces:
if str(trl.name()[4:12])== str(tracex[4:]):
tr_org = obspy_compat.to_pyrocko_trace(calcStreamMapsyn[tracex])
tr_org.downsample_to(2.0)
trs_orgs.append(tr_org)
store_id = syn_in.store()
engine = LocalEngine(store_superdirs=[syn_in.store_superdirs()])
synthetic_traces = add_noise(trs_orgs, engine, source.pyrocko_event(),
stations,
store_id, phase_def='P')
trs_org = []
trs_orgs = []
fobj = os.path.join(arrayfolder, 'shift.dat')
xy = num.loadtxt(fobj, usecols=1, delimiter=',')
calcStreamMapsyn = calcStreamMap.copy()
#from pyrocko import trace
for tracex in calcStreamMapsyn.iterkeys():
for trl in synthetic_traces:
if str(trl.name()[4:12])== str(tracex[4:]):
mod = trl
recordstarttime = calcStreamMapsyn[tracex].stats.starttime.timestamp
recordendtime = calcStreamMapsyn[tracex].stats.endtime.timestamp
tr_org = obspy_compat.to_pyrocko_trace(calcStreamMapsyn[tracex])
trs_orgs.append(tr_org)
tr_org_add = mod.chop(recordstarttime, recordendtime, inplace=False)
synthetic_obs_tr = obspy_compat.to_obspy_trace(tr_org_add)
calcStreamMapsyn[tracex] = synthetic_obs_tr
trs_org.append(tr_org_add)
calcStreamMap = calcStreamMapsyn
def gen_dataset(scenarios,
projdir,
store_id,
modelled_channel_codes,
magmin,
magmax,
depmin,
depmax,
latmin,
latmax,
lonmin,
lonmax,
stations_file,
gf_store_superdirs,
shakemap=True,
add_noise=True,
t_station_dropout=False,
simple_induced=True,
seiger=True,
generate_scenario_type="full",
event_list=None,
respones="responses_bgr.xml"):
# random station dropout
if seiger is True:
times_kuper, pressure_kuper, temp_kuper, rate_kuper = get_kuperkoch_data(
)
mean_pressure = num.mean(pressure_kuper)
mean_temp = num.mean(temp_kuper)
mean_rate = num.mean(rate_kuper)
if gf_store_superdirs is None:
engine = gf.LocalEngine(use_config=True)
else:
engine = gf.LocalEngine(store_superdirs=[gf_store_superdirs])
if t_station_dropout is True:
from pyrocko.io import stationxml
station_xml = stationxml.load_xml(filename=responses)
for scenario in range(scenarios):
generated_scenario = False
while generated_scenario is False:
try:
if seiger is True:
if generate_scenario_type is "catalog":
choice = num.random.choice(len(event_list), 1)
base_event = event_list[choice]
source, event = get_source_seiger(
generate_scenario_type,
magmin,
magmax,
depmin,
depmax,
latmin,
lonmin,
latmax,
lonmax,
simple_induced,
use_pressure=use_pressure,
event=base_event,
store_id=store_id)
else:
source, event = get_source()
savedir = projdir + '/scenario_' + str(scenario) + '/'
if not os.path.exists(savedir):
os.makedirs(savedir)
if stations_file is not None:
stations = model.load_stations(projdir + "/" +
stations_file)
targets = []
for st in stations:
for cha in st.channels:
target = Target(lat=st.lat,
lon=st.lon,
store_id=store_id,
interpolation='multilinear',
quantity='displacement',
codes=st.nsl() + (cha.name, ))
targets.append(target)
else:
targets = []
for st in stations:
channels = modelled_channel_codes
for cha in channels:
target = Target(lat=st.lat,
lon=st.lon,
store_id=store_id,
interpolation='multilinear',
quantity='displacement',
codes=st.nsl() + (cha, ))
targets.append(target)
if shakemap is True:
shakemap_fwd.make_shakemap(engine,
source,
store_id,
savedir,
stations=stations)
gen_loop = True
response = engine.process(source, targets)
synthetic_traces = response.pyrocko_traces()
if t_station_dropout is True:
station_time_dict = load_time_dependent_stations(
event, stations, station_xml)
for tr in synthetic_traces:
for st in station_time_dict:
if tr.station == st.station:
tr.ydata = tr.ydata * 0.
if choice == 2:
synthetic_traces = gen_white_noise(synthetic_traces)
event.tags = ["no_event"]
if add_noise is True and choice != 2:
add_white_noise(synthetic_traces)
noise_events = gen_noise_events(targets, synthetic_traces,
engine)
events = [event]
save(synthetic_traces,
events,
stations,
savedir,
noise_events=noise_events)
generated_scenario = True
except pyrocko.gf.seismosizer.SeismosizerError:
pass
# The store we are going extract data from:
store_id = 'kazeroon'
# We need a pyrocko.gf.Engine object which provides us with the traces
# extracted from the store. In this case we are going to use a local
# engine since we are going to query a local store.
engine = LocalEngine(store_superdirs=['/home/alireza/Kiwi/GFDB'])
# Define a list of pyrocko.gf.Target objects, representing the recording
# devices. In this case one station with a three component sensor will
# serve fine for demonstation.
channel_codes = 'ENZ'
targets = [
Target(
lat=36.21,
lon=48.22,
store_id=store_id,
codes=('', 'CVD', '', channel_code))
for channel_code in channel_codes]
# Let's use a double couple source representation.
source_dc = DCSource(
lat=34.00,
lon=45.00,
depth=10000,
strike=170,
dip=35,
rake=50,
magnitude=5.6)
# Processing that data will return a pyrocko.gf.Reponse object.