def produceStream(self, filepath):
time, data = numpy.loadtxt(filepath, unpack=True)
head, tail = os.path.split(filepath)
tr = trace.Trace(data)
try:
#assuming that the information are in the filename following the usual convention
tr.stats['network'] = tail.split('.')[1]
tr.stats['station'] = tail.split('.')[0]
tr.stats['channel'] = tail.split('.')[2]
try:
doc = etree.parse(StringIO(open(self.stationsFile).read()))
ns = {"ns": "http://www.fdsn.org/xml/station/1"}
tr.stats['latitude'] = self.num(
doc.xpath("//ns:Station[@code='" + tr.stats['station'] +
"']/ns:Latitude/text()",
namespaces=ns)[0])
tr.stats['longitude'] = self.num(
doc.xpath("//ns:Station[@code='" + tr.stats['station'] +
"']/ns:Longitude/text()",
namespaces=ns)[0])
except:
with open(self.stationsFile) as f:
k = False
for line in f:
if (k == False):
k = True
else:
station = {}
l = line.strip().split(" ")
if (tr.stats['station'] == l[0]):
tr.stats['latitude'] = float(l[3])
tr.stats['longitude'] = float(l[2])
except:
print traceback.format_exc()
# tr.stats['network']=self.parameters["network"]
# tr.stats['station']=self.parameters["station"]
# tr.stats['channel']=self.parameters["channel"]
tr.stats['starttime'] = time[0]
delta = time[1] - time[0]
tr.stats['delta'] = delta #maybe decimal here
tr.stats['sampling_rate'] = round(1. / delta, 1) #maybe decimal here
if filepath.endswith('.semv'):
tr.stats['type'] = "velocity"
if filepath.endswith('.sema'):
tr.stats['type'] = 'acceleration'
if filepath.endswith('.semd'):
tr.stats['type'] = 'displacement'
st = stream.Stream()
st += stream.Stream(tr)
return st
def acorr(seismic_signal, **kwargs):
"""
Calculate phase auto-correlation for each signal in seismic_stream
:param seismic_signal:
:param kwargs:
:return:
"""
# if seismic signal is a trace object, we pack it to a stream
if isinstance(seismic_signal, _tr.Trace):
sources = _st.Stream([seismic_signal])
else:
sources = seismic_signal
if not isinstance(sources, _st.Stream):
raise TypeError('seismic_stream is not a Stream nor Trace object')
return _st.Stream([_acorr_trace(tr, **kwargs) for tr in sources])
def array2stream(array, sampling_rate, stream_info):
nchans = array.shape[0]
npts = array.shape[1]
traces = []
for c in range(nchans):
traces.append(trace.Trace(data=array[c, :],
header={'sampling_rate': sampling_rate,
'station': stream_info['station'],
'network': stream_info['network'],
'channel': stream_info['channels'][c]}))
return stream.Stream(traces)
def reFormatSAC(self, paths, year, jday, newRate=5.0, channel='Z'):
newSAC = stream.Stream()
try:
oldSAC = read(paths)
except:
oldSAC = stream.Stream()
for nm in paths:
try:
aSAC = read(nm)
except:
print('Error reading ' + nm)
else:
for tr in aSAC:
if channel in tr.stats.channel:
oldSAC.append(tr)
for tr in oldSAC:
oldRate = tr.stats.sampling_rate
mul = int(oldRate / newRate)
if mul > 0:
tr.decimate(mul, strict_length=False, no_filter=True)
tr.stats.sampling_rate = newRate
newSAC.append(tr)
if newSAC.count() > 0:
newSAC.merge(method=0, fill_value="interpolate")
newSAC.detrend()
tB = UTCDateTime(year=year,
julday=jday,
hour=0,
minute=0,
second=0,
microsecond=0)
tE = tB + 3600 * 24
new = newSAC.trim(starttime=tB,
endtime=tE,
pad=True,
fill_value=0,
nearest_sample=False)
return new
else:
return newSAC
def xcorr(seismic_signal, wavelet, **kwargs):
"""
Calculate phase cross correlation (pcc)
between signal and wavelet
foreach signal in seismic
For this purpose wavelet is shifted in time and compared to
corresponding portion in each signals
:param seismic_signal: seismic stream, may contain multiple traces
:param wavelet: seismic trace, or stream containing single trace
:param kwargs:
:return: cross-correlation as stream
"""
# if seismic signal is a trace object, we pack it to a stream
if isinstance(seismic_signal, _tr.Trace):
sources = _st.Stream([seismic_signal])
else:
sources = seismic_signal
if not isinstance(sources, _st.Stream):
raise TypeError('seismic signal is not a Stream nor Trace object')
# if wavelet is a stream, we take the first trace
if isinstance(wavelet, _st.Stream):
ref = wavelet[0]
if wavelet.count() > 1:
_warning.warn(
'wavelet contains multiple traces. Using the first trace as wavelet'
)
else:
ref = wavelet
if not isinstance(ref, _tr.Trace):
raise TypeError('wavelet is not a Stream nor Trace object')
return _st.Stream([_xcorr_trace(tr, ref, **kwargs) for tr in sources])
def getDataByFileName(sacFileNamesL, delta0=0.02, freq=[-1, -1], \
filterName='bandpass', corners=4, zerophase=True,maxA=1e5):
if not checkSacFile(sacFileNamesL):
return Data(np.zeros(0), -999, -999, 0, [-1 - 1])
sacs = stream.Stream()
#time0=time.time()
for sacFileNames in sacFileNamesL:
tmp=mergeSacByName(sacFileNames, delta0=delta0,freq=freq,\
filterName=filterName,corners=corners,zerophase=zerophase,maxA=maxA)
if tmp == None:
print('False')
return Data(np.zeros(0), -999, -999, 0, [-1 - 1])
else:
sacs.append(tmp)
time1 = time.time()
dataL = sac2data(sacs, delta0=delta0)
time2 = time.time()
#print('read',time1-time0,'dec',time2-time1)
return Data(dataL[0], dataL[1], dataL[2], dataL[3], freq)
def removeGapped(station_list):
"""
Remove data with gaps
"""
for station in station_list:
# temp copy of station's stream list
_stream_list = list(station.stream_list)
for stream in station.stream_list:
try:
_st = obspy_stream.Stream()
_st.append(stream.data)
_gaps = _st.getGaps()
if _gaps:
_stream_list.remove(stream)
except:
_stream_list.remove(stream)
# make new stream list as station's stream list
station.stream_list = list(_stream_list)
return removeEmptyStations(station_list)
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 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)
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?
#==================================synthetic BeamForming=======================================
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
# ==================================semblance calculation=======
t1 = time.time()
traces = traces.reshape(1, nostat*minSampleCount)
traveltimes = traveltime.reshape(1, nostat*dimX*dimY)
TTTGrid = True
manual_shift = False
if manual_shift:
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
backSemb = num.ndarray(shape=(ntimes, dimX*dimY), dtype=float)
bf = BeamForming(stations, traces, normalize=True)
for i in range(ntimes):
sembmax = 0
sembmaxX = 0
sembmaxY = 0
for j in range(dimX * dimY):
event = model.Event(lat=float(latv[j]), lon=float(lonv[j]),
depth=ev.depth*1000., time=timeev)
directory = arrayfolder
shifted_traces, stack = bf.process(event=event,
timing=timing,
fn_dump_center=pjoin(
directory,
'array_center.pf'),
fn_beam=pjoin(directory,
'beam.mseed'))
tmin = stack.tmin+(i*nstep)+20
tmax = stack.tmin+(i*nstep)+60
stack.chop(tmin, tmax)
backSemb[i][j] = abs(sum(stack.ydata))
k = backSemb
TTTGrid = False
if TTTGrid:
start_time = time.time()
if cfg.UInt('forerun') > 0:
ntimes = int((cfg.UInt('forerun') + cfg.UInt('duration'))/step)
else:
ntimes = int((cfg.UInt('duration')) / step)
nsamp = int(winlen)
nstep = int(step)
Gmint = cfg.Int('forerun')
k = semblance(maxp, nostat, nsamp, ntimes, nstep, dimX, dimY, Gmint,
new_frequence, minSampleCount, latv, lonv, traveltimes,
traces, calcStreamMap, timeev, Config, Origin)
print("--- %s seconds ---" % (time.time() - start_time))
t2 = time.time()
Logfile.add('%s took %0.3f s' % ('CALC:',(t2-t1)))
partSemb = k
partSemb = partSemb.reshape(ntimes, migpoints)
return partSemb
def _rotate_corr_stream(st):
""" Rotate traces in stream from the EE-EN-EZ-NE-NN-NZ-ZE-ZN-ZZ system to
the RR-RT-RZ-TR-TT-TZ-ZR-ZT-ZZ system. The letters give the component order
in the input and output streams. Input traces are assumed to be of same length
and simultaneously sampled.
"""
# rotation angles
# phi1 : counter clockwise angle between E and R(towards second station)
# the leading -1 accounts fact that we rotate the coordinate system, not a vector
phi1 = -np.pi / 180 * (90 - st[0].stats['sac']['az'])
# phi2 : counter clockwise angle between E and R(away from first station)
phi2 = -np.pi / 180 * (90 - st[0].stats['sac']['baz'] + 180)
c1 = np.cos(phi1)
s1 = np.sin(phi1)
c2 = np.cos(phi2)
s2 = np.sin(phi2)
rtz = stream.Stream()
RR = st[0].copy()
RR.data = c1 * c2 * st[0].data - c1 * s2 * st[1].data - s1 * c2 * st[
3].data + s1 * s2 * st[4].data
tcha = list(RR.stats['channel'])
tcha[2] = 'R'
tcha[6] = 'R'
RR.stats['channel'] = ''.join(tcha)
rtz.append(RR)
RT = st[0].copy()
RT.data = c1 * s2 * st[0].data + c1 * c2 * st[1].data - s1 * s2 * st[
3].data - s1 * c2 * st[4].data
tcha = list(RT.stats['channel'])
tcha[2] = 'R'
tcha[6] = 'T'
RT.stats['channel'] = ''.join(tcha)
rtz.append(RT)
RZ = st[0].copy()
RZ.data = c1 * st[2].data - s1 * st[5].data
tcha = list(RZ.stats['channel'])
tcha[2] = 'R'
tcha[6] = 'Z'
RZ.stats['channel'] = ''.join(tcha)
rtz.append(RZ)
TR = st[0].copy()
TR.data = s1 * c2 * st[0].data - s1 * s2 * st[1].data + c1 * c2 * st[
3].data - c1 * s2 * st[4].data
tcha = list(TR.stats['channel'])
tcha[2] = 'T'
tcha[6] = 'R'
TR.stats['channel'] = ''.join(tcha)
rtz.append(TR)
TT = st[0].copy()
TT.data = s1 * s2 * st[0].data + s1 * c2 * st[1].data + c1 * s2 * st[
3].data + c1 * c2 * st[4].data
tcha = list(TT.stats['channel'])
tcha[2] = 'T'
tcha[6] = 'T'
TT.stats['channel'] = ''.join(tcha)
rtz.append(TT)
TZ = st[0].copy()
TZ.data = s1 * st[2].data + c1 * st[5].data
tcha = list(TZ.stats['channel'])
tcha[2] = 'T'
tcha[6] = 'Z'
TZ.stats['channel'] = ''.join(tcha)
rtz.append(TZ)
ZR = st[0].copy()
ZR.data = c2 * st[6].data - s2 * st[7].data
tcha = list(ZR.stats['channel'])
tcha[2] = 'Z'
tcha[6] = 'R'
ZR.stats['channel'] = ''.join(tcha)
rtz.append(ZR)
ZT = st[0].copy()
ZT.data = s2 * st[6].data + c2 * st[7].data
tcha = list(ZT.stats['channel'])
tcha[2] = 'Z'
tcha[6] = 'T'
ZT.stats['channel'] = ''.join(tcha)
rtz.append(ZT)
rtz.append(st[8].copy())
return rtz
def rotate_multi_corr_stream(st):
"""Rotate a stream with full Greens tensor from ENZ to RTZ
Take a stream with numerous correlation traces and rotate the
combinations of ENZ components into combinations of RTZ components in case all
nine components of the Green's tensor are present. If not all nine components
are present no trace for this station combination is returned.
:type st: obspy.stream
:param st: stream with data in ENZ system
:rtype: obspy.stream
:return: stream in the RTZ system
"""
out_st = stream.Stream()
while st:
tl = range(9)
tst = st.select(network=st[0].stats['network'],
station=st[0].stats['station'])
cnt = 0
for ttr in tst:
if ttr.stats['channel'][2] == 'E':
if ttr.stats['channel'][6] == 'E':
tl[0] = ttr
cnt += 1
elif ttr.stats['channel'][6] == 'N':
tl[1] = ttr
cnt += 2
elif ttr.stats['channel'][6] == 'Z':
tl[2] = ttr
cnt += 4
elif ttr.stats['channel'][2] == 'N':
if ttr.stats['channel'][6] == 'E':
tl[3] = ttr
cnt += 8
elif ttr.stats['channel'][6] == 'N':
tl[4] = ttr
cnt += 16
elif ttr.stats['channel'][6] == 'Z':
tl[5] = ttr
cnt += 32
elif ttr.stats['channel'][2] == 'Z':
if ttr.stats['channel'][6] == 'E':
tl[6] = ttr
cnt += 64
elif ttr.stats['channel'][6] == 'N':
tl[7] = ttr
cnt += 128
elif ttr.stats['channel'][6] == 'Z':
tl[8] = ttr
cnt += 256
if cnt == 2**9 - 1:
st0 = stream.Stream()
for t in tl:
st0.append(t)
st1 = _rotate_corr_stream(st0)
out_st += st1
for ttr in tst:
for ind, tr in enumerate(st):
if ttr.id == tr.id:
st.pop(ind)
return out_st
def stream_pxcorr(st, options, comm=None):
"""
Preprocess and correlate traces in a stream
This is the central function of this module. It takes an obspy.stram input
stream applies and:
- applies time domain preprocesing
- Fourier transforms the data
- applies frequency domain preprocessing
- multiplies the conjugate spectra (correlation)
- transforms back into time domain
- returns a stream with the correlated data
All this can be done in parallel on different CPU communicating via
the `mpi4py` implementation of MPI. Control the different processing steps
are controlled with the dictionary `options`. The following keys are
required in `options`:
- combinations: list of tuples that identify the combinations of the\\
traces in `st` to be correlated
- lengthToSave: length of the correlated traces in s to return
- normalize_correlation: Boolean. If True the correaltion is\\
normalized. If False the pure product of the spectra is returned
- center_correlation: Boolean. If True th location of zero lag time\\
is in the center of the returned trace. If False the position of\\
zero lag time is determined by the start times of the traces. If\\
they are identical it is in the center anyway. If the difference \\
in start times is larger the zero lag time is offset.
- TDpreProcessing: list controlling the time domain preprocessing
- FDpreProcessing: list controlling the frequency domain preprocessing
The item in the list `TDpreProcessing` and `FDpreProcessing` are
dictionaries with two keys: `function` containing the function to apply and
`args` being a dictionary with the arguments for this function. The
functions in `TDpreProcessing` are applied in their order before the
Fourier transformation and those in FDpreProcessing` are applied in their
order Fourier domain.
:Example:
``options = {'TDpreProcessing':[{'function':detrend,
'args':{'type':'linear'}},
{'function':taper,
'args':{'type':'cosTaper',
'p':0.01}},
{'function':TDfilter,
'args':{'type':'bandpass',
'freqmin':1.,
'freqmax':3.}},
{'function':TDnormalization,
'args':{'filter':{'type':'bandpass',
'freqmin':0.5,
'freqmax':2.},
'windowLength':1.}},
{'function':signBitNormalization,
'args':{}}
],
'FDpreProcessing':[{'function':spectralWhitening,
'args':{}},
{'function':FDfilter,
'args':{'flimit':[0.5, 1., 5., 7.]}}],
'lengthToSave':20,
'center_correlation':True,
'normalize_correlation':True,
'combinations':[(0,0),(0,1),(0,2),(1,2)]}``
`comm` is a mpi4py communicator that can be passed if already initialized
otherwise it is created here.
:type st: obspy.stream
:param st: stream with traces to be correlated
:type options: dictionary
:param options: controll dictionary as described above
:type comm: mpi4py communicator
:param comm: communicator if initialized externally
"""
# initialize MPI
if not comm:
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
# get parameters of the data
if rank == 0:
starttime = []
npts = []
for tr in st:
starttime.append(tr.stats['starttime'])
npts.append(tr.stats['npts'])
npts = np.max(np.array(npts))
else:
starttime = None
npts = None
starttime = comm.bcast(starttime, root=0)
npts = comm.bcast(npts, root=0)
# fill matrix with noise data
A = np.zeros([npts, len(st)])
if rank == 0:
for ii in range(len(st)):
A[0:st[ii].stats['npts'], ii] = st[ii].data
comm.Bcast([A, MPI.DOUBLE], root=0)
options.update({
'starttime': starttime,
'sampling_rate': st[0].stats['sampling_rate']
})
# call pxcorr_for correlation
A, starttime = pxcorr(comm, A, **options)
npts = A.shape[0]
# put trace into a stream
cst = stream.Stream()
for ii in range(len(options['combinations'])):
cstats = combine_stats(st[options['combinations'][ii][0]],
st[options['combinations'][ii][1]])
cstats['starttime'] = starttime[ii]
cstats['npts'] = npts
cst.append(trace.Trace(data=A[:, ii], header=cstats))
cst[-1].stats_tr1 = st[options['combinations'][ii][0]].stats
cst[-1].stats_tr2 = st[options['combinations'][ii][1]].stats
return cst
def call(self):
try:
from obspy.core import UTCDateTime, stream
from obspy.signal import array_analysis
from obspy.imaging.cm import obspy_sequential as cmap
except ImportError as _import_error:
self.fail('ImportError:\n%s' % _import_error)
from matplotlib.colorbar import ColorbarBase
from matplotlib.colors import Normalize
import matplotlib.dates as mdates
self.cleanup()
viewer = self.get_viewer()
if viewer.lowpass is None or viewer.highpass is None:
self.fail('highpass and lowpass in viewer must be set!')
traces = []
for trs in self.chopper_selected_traces(fallback=True):
for tr in trs:
tr.lowpass(2, viewer.lowpass)
tr.highpass(2, viewer.highpass)
traces.extend(trs)
if not traces:
self.fail('no traces selected')
if self.downresample == 'resample':
dt_want = min([t.deltat for t in traces])
for t in traces:
t.resample(dt_want)
elif self.downresample == 'downsample':
dt_want = max([t.deltat for t in traces])
for t in traces:
t.downsample_to(dt_want)
elif self.downresample == 'downsample to "target dt"':
for t in traces:
t.downsample_to(float(self.target_dt))
tmin = max([t.tmin for t in traces])
tmax = min([t.tmax for t in traces])
try:
obspy_traces = [
p2o_trace(tr, viewer.get_station(viewer.station_key(tr)))
for tr in traces
]
except KeyError:
self.fail('station information missing')
st = stream.Stream(traces=obspy_traces)
center = array_analysis.get_geometry(st, return_center=True)
center_lon, center_lat, center_ele = center[len(center) - 1]
# Execute sonic
kwargs = dict(sll_x=-self.smax,
slm_x=self.smax,
sll_y=-self.smax,
slm_y=self.smax,
sl_s=self.smax / self.divisor,
win_len=self.window_lenth,
win_frac=self.win_frac,
frqlow=viewer.highpass,
frqhigh=viewer.lowpass,
prewhiten=0,
semb_thres=-1.0e9,
vel_thres=-1.0e9,
verbose=True,
timestamp='mlabday',
stime=UTCDateTime(tmin),
etime=UTCDateTime(tmax))
try:
out = array_analysis.array_processing(st, **kwargs)
except AttributeError:
from obspy.signal.array_analysis import sonic
out = sonic(st, **kwargs)
pi = num.pi
# make output human readable, adjust backazimuth to values between 0
# and 360
t, rel_power, abs_power, baz, slow = out.T
baz[baz < 0.0] += 360.
# choose number of fractions in plot (desirably 360 degree/N is an
# integer!)
N = int(self.numberOfFraction)
abins = num.arange(N + 1) * 360. / N
sbins = num.linspace(0., self.smax, N + 1)
# sum rel power in bins given by abins and sbins
hist, baz_edges, sl_edges = num.histogram2d(baz,
slow,
bins=[abins, sbins],
weights=rel_power)
# transform to gradient
baz_edges = baz_edges / 180. * pi
fig = self.pylab(get='figure')
cax = fig.add_axes([0.85, 0.2, 0.05, 0.5])
ax = fig.add_axes([0.10, 0.1, 0.70, 0.7], polar=True)
ax.grid(False)
dh = abs(sl_edges[1] - sl_edges[0])
dw = abs(baz_edges[1] - baz_edges[0])
# circle through backazimuth
for i, row in enumerate(hist):
ax.bar(left=(pi / 2 - (i + 1) * dw) * num.ones(N),
height=dh * num.ones(N),
width=dw,
bottom=dh * num.arange(N),
color=cmap(row / hist.max()))
ax.set_xticks([pi / 2, 0, 3. / 2 * pi, pi])
ax.set_xticklabels(['N', 'E', 'S', 'W'])
ax.set_ylim(0., self.smax)
ColorbarBase(cax,
cmap=cmap,
norm=Normalize(vmin=hist.min(), vmax=hist.max()))
fig2 = self.pylab(get='figure')
labels = ['rel.power', 'abs.power', 'baz', 'slow']
xlocator = mdates.AutoDateLocator()
ax = None
for i, lab in enumerate(labels):
ax = fig2.add_subplot(4, 1, i + 1, sharex=ax)
ax.scatter(out[:, 0],
out[:, i + 1],
c=out[:, 1],
alpha=0.6,
edgecolors='none',
cmap=cmap)
ax.set_ylabel(lab)
ax.set_xlim(out[0, 0], out[-1, 0])
ax.set_ylim(out[:, i + 1].min(), out[:, i + 1].max())
ax.xaxis.set_tick_params(which='both', direction='in')
ax.xaxis.set_major_locator(xlocator)
ax.xaxis.set_major_formatter(mdates.AutoDateFormatter(xlocator))
if i != 3:
ax.set_xticklabels([])
fig2.subplots_adjust(hspace=0.)
fig2.canvas.draw()
fig.canvas.draw()
print('Center of Array at latitude %s and longitude %s' %
(center_lat, center_lon))
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 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)
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?
#==================================synthetic BeamForming=======================================
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_onset') == 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 trace in calcStreamMapshifted.iterkeys():
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.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')
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
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))
t1 = time.time()
traces_org = traces.reshape (1,nostat*minSampleCount)
traveltime_org = 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_org,traces_org)
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_org,traces_org) #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_data = partSemb.reshape (ntimes,migpoints)
return partSemb_data
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.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_onset') == True:
pjoin = os.path.join
timeev = util.str_to_time(ev.time)
trs_orgs= []
calcStreamMapshifted= calcStreamMap.copy()
for trace in calcStreamMapshifted.iterkeys():
