def filterWaveform(Config, wafeform, station):
cfg = FilterCfg(self.Config)
switch = cfg.filterswitch() # 'filterswitch'
if switch == 1:
which = 'bandpass'
waveform.filter(
which,
freqmin=cfg.flo(), # ['flo']
freqmax=cfg.fhi(), # ['fhi']
corners=cfg.ns(), # ['ns']
zerophase=bool(Config['zph']))
elif switch == 2:
which = "lowpass"
waveform.filter(
which,
freq=cfg.l_fc(), # ['l_fc']
corners=cfg.l_ns(), # ['l_ns']
zerophase=bool(Config['l_zph']))
elif switch == 3:
which = 'highpass'
waveform.filter(
which,
freq=cfg.h_fc(), # ['h_fc']
corners=cfg.h_ns(), # ['h_ns']
zerophase=bool(Config['h_zph']))
else:
return None
Logfile.add('%s filtered stream for station %s ' % (which, i))
return wafeform
def filterpyrockoWaveform(self, Waveform):
obspy_compat.plant()
Logfile.red('Filter Waveform: ')
cfg = FilterCfg(self.Config)
new_frequence = (cfg.newFrequency())
st = Stream()
for i in Waveform:
tr = obspy_compat.to_pyrocko_trace(i)
tr.downsample_to(new_frequence)
Logfile.red('Downsampling to %d: from %d' %
(new_frequence, i.stats.sampling_rate))
if switch == 0:
Logfile.add('bandpass filtered stream for station %s ' % (i))
tr.bandpass(4, cfg.flo, cfg.fhi)
elif switch == 1:
Logfile.add('bandpass filtered stream for station %s ' % (i))
j = obspy_compat.to_obspy_trace(tr)
st.append(j)
return st
def processpyrockoWaveforms(WaveformDict, Config, Folder, network, MetaDict,
Event, switch, Xcorr):
WaveformDict_obs = []
obspy_compat.plant()
Logfile.red('Start Processing')
cfg = FilterCfg(Config)
new_frequence = cfg.newFrequency() # ['new_frequence']
traces = []
for tr in WaveformDict:
Logfile.add(
'%s:%s -------------------------------------------------------------'
% (index, i))
if Config['export_unfiltered'].capitalize() == 'True':
tr = obspy_compat.to_obspy_trace(tr)
writeWaveform(Folder, i, tr, 'U', network)
if switch == 0:
Logfile.add('bandpass filtered stream for station %s ' % (i))
tr.bandpass(4, cfg.flo, cfg.fhi)
elif switch == 1:
Logfile.add('bandpass filtered stream for station %s ' % (i))
tr.bandpass(4, cfg.flo2, cfg.fhi2)
tr.downsample_to(new_frequence)
tr = obspy_compat.to_obspy_trace(tr)
traces.append(tr)
stream = obspy.Stream()
Wdict = stream.extend([tr])
WaveformDict_obs.append(Wdict)
return WaveformDict_obs
def filterWaveform(self, Waveform):
Logfile.red('Filter Waveform: ')
cfg = FilterCfg(self.Config)
new_frequence = (cfg.newFrequency())
st = Stream()
for i in Waveform:
Logfile.red('Downsampling to %s: from %d' %
(new_frequence, i.stats.sampling_rate))
j = i.resample(new_frequence)
switch = cfg.filterswitch()
if switch == 1:
Logfile.add('bandpass filtered \
stream for station %s ' % (i))
j.filter('bandpass',
freqmin=cfg.flo(),
freqmax=cfg.fhi(),
corners=cfg.ns(),
zerophase=bool(self.Config['zph']))
elif switch == 2:
Logfile.add('bandpass filtered \
stream for station %s ' % (i))
j.filter('bandpass',
freqmin=cfg.flo2(),
freqmax=cfg.fhi2(),
corners=cfg.ns2(),
zerophase=bool(self.Config['zph']))
st.append(j)
return st
def processWaveforms(WaveformDict,
Config,
Folder,
network,
MetaDict,
Event,
Xcorr=None):
Logfile.red('Start Processing')
cfg = FilterCfg(Config)
new_frequence = cfg.newFrequency() # ['new_frequence']
vp, vs, rho = ttt.calcak135parameter(Event)
for index, i in enumerate(WaveformDict):
Logfile.add(
'%s:%s -------------------------------------------------------------'
% (index, i))
if Config['export_unfiltered'].capitalize() == 'True':
writeWaveform(Folder, i, WaveformDict[i], 'U', network)
# TODO implement gain multiplication
station = getStation(i, MetaDict)
psign = 1
# print 'MetaDict ',MetaDict,station,station.takeoff
#needs to be implemented correctly
if cfg.Int('fm') == 1:
print 'Event ', Event, Event.strike, Event.dip, Event.rake
azi = ttt.bearing(Event, station)
bazi = ttt.backazi(station, Event)
psign = ttt.dubcup(rho, vp, vs, Event.strike, Event.dip,
Event.rake, azi, station.takeoff)
#print 'Takeoff ',station.takeoff,' Azi ',azi,' Bazi ',bazi,' vp ',vp,' vs ',vs,' rho ',rho,' Psign ',psign
msg = 'Takeoff ' + str(
station.takeoff) + ' Azi ' + str(azi) + ' Bazi ' + str(bazi)
msg += (' vp ' + str(vp) + ' vs ' + str(vs) + ' rho ' + str(rho) +
' Psign ' + str(psign))
Logfile.add(msg)
'''
if int(Config['xcorr']) == 1:
#print Xcorr[i].value
if Xcorr[i].value > 0: psign = 1
else: psign = -1
'''
Logfile.add(station.getName() + ' ' + station.lat + ' ' + station.lon +
' ' + station.gain + ' PSIGN: ' + str(psign))
if psign == -1:
Logfile.add('correcting polarisation for station %s ' % (i))
-1. * WaveformDict[i][0].data
#remove offset
WaveformDict[i].detrend(type='demean')
#gain correctur
gain = float(station.gain)
if gain == 0.0 or gain == -1.0:
gain = 1 #hs : gain missing in metafile
WaveformDict[i][0].data * (1.0 / gain)
#filtering
switch = cfg.filterswitch() # 'filterswitch'
if switch == 1:
Logfile.add('bandpass filtered stream for station %s ' % (i))
WaveformDict[i].filter(
'bandpass',
freqmin=cfg.flo(), # ['flo']
freqmax=cfg.fhi(), # ['fhi']
corners=cfg.ns(), # ['ns']
zerophase=bool(Config['zph']))
elif switch == 2:
Logfile.add('lowpass filtered stream for station %s ' % (i))
WaveformDict[i].filter(
"lowpass",
freq=cfg.l_fc(), # ['l_fc']
corners=cfg.l_ns(), # ['l_ns']
zerophase=bool(Config['l_zph']))
elif switch == 3:
Logfile.add('highpass filtered stream for station %s ' % (i))
WaveformDict[i].filter(
"highpass",
freq=cfg.h_fc(), # ['h_fc']
corners=cfg.h_ns(), # ['h_ns']
zerophase=bool(Config['h_zph']))
else:
Logfile.add('no filter set for station %s ' % (i))
if Config['export_filtered'].capitalize() == 'True':
writeWaveform(Folder, i, WaveformDict[i], 'F', network)
#resampling
j = resampleWaveform(WaveformDict[i][0], new_frequence)
WaveformDict[i] = j
#Logfile.add (WaveformDict[i])
if Config['export_resampled'].capitalize() == 'True':
writeWaveform(Folder, i, WaveformDict[i], 'R', network)
#endfor
return WaveformDict
def processLoop():
#==================================get meta info==========================================
C = config.Config(evpath)
Origin = C.parseConfig('origin')
try:
Syn_in = C.parseConfig('syn')
syn_in = SynthCfg(Syn_in)
except:
pass
Config = C.parseConfig('config')
cfg = ConfigObj(dict=Config)
if cfg.pyrocko_download() == True:
Meta = C.readpyrockostations() #
elif cfg.colesseo_input() == True:
scenario = guts.load(filename=cfg.colosseo_scenario_yml())
scenario_path = cfg.colosseo_scenario_yml()[:-12]
Meta = C.readcolosseostations(scenario_path)
else:
Meta = C.readMetaInfoFile()
#==================================get meta info==========================================
#==================================do prerequiries========================================
Folder = C.createFolder()
#C.cpSkeleton(Folder,Config)
C.writeConfig(Config, Origin, Folder)
filter = FilterCfg(Config)
ntimes = int(
(cfg.UInt('forerun') + cfg.UInt('duration')) / cfg.UInt('step'))
origin = OriginCfg(Origin)
if cfg.colesseo_input() == True:
from pyrocko import util
events = scenario.get_events()
ev = events[0]
origin.strike = str(ev.moment_tensor.strike1)
origin.rake = str(ev.moment_tensor.rake1)
origin.dip = str(ev.moment_tensor.dip1)
strike = ev.moment_tensor.strike1
origin.lat = str(ev.lat)
origin.lon = str(ev.lon)
origin.depth = str(ev.depth / 1000.)
depth = ev.depth
origin.time = util.time_to_str(ev.time)
time_ev = util.time_to_str(ev.time)
lat = ev.lat
lon = ev.lon
rake = ev.moment_tensor.rake1
dip = ev.moment_tensor.dip1
Origin['strike'] = str(ev.moment_tensor.strike1)
Origin['rake'] = str(ev.moment_tensor.rake1)
Origin['dip'] = str(ev.moment_tensor.dip1)
Origin['lat'] = str(ev.lat)
Origin['lon'] = str(ev.lon)
Origin['time'] = util.time_to_str(ev.time)
Origin['depth'] = str(ev.depth / 1000.)
ev = Event(lat, lon, depth, time_ev, strike=strike, dip=dip, rake=rake)
else:
default = 0
strike = origin.strike(default) # Origin.get ('strike', default)
dip = origin.dip(default) # Origin.get ('dip', default)
rake = origin.rake(default) # Origin.get ('rake', default)
ev = Event(origin.lat(),
origin.lon(),
origin.depth(),
origin.time(),
strike=strike,
dip=dip,
rake=rake)
filtername = filter.filterName()
Logfile.add('filtername = ' + filtername)
#todo crosscorrelation for all arrays before processing
XDict = {}
RefDict = {}
SL = {}
if cfg.Int('xcorr') == 1:
newFreq = str(filter.newFrequency())
fobjreferenceshiftname = newFreq + '_' + filtername + '.refpkl'
rp = os.path.join(Folder['semb'], fobjreferenceshiftname)
fobjpickleshiftname = newFreq + '_' + filtername + '.xcorrpkl'
ps = os.path.join(Folder['semb'], fobjpickleshiftname)
if (os.path.isfile(rp) and os.path.getsize(rp) != 0
and os.path.isfile(ps) and os.path.getsize(ps) != 0):
Logfile.add('file exits : ' + rp)
Logfile.add('load refshifts')
f = open(rp)
RefDict = pickle.load(f)
x = open(ps)
XDict = pickle.load(x)
xcorrnetworks = cfg.String('networks').split(',')
for i in xcorrnetworks:
SL[i] = len(Config[i].split('|'))
else:
SL = {}
xcorrnetworks = cfg.String('networks').split(',')
for i in xcorrnetworks:
W = {}
refshift = 0
network = cfg.String(i).split('|')
FilterMeta = ttt.filterStations(Meta, Config, Origin, network)
arrayfolder = os.path.join(Folder['semb'], i)
if os.access(arrayfolder, os.F_OK) == False:
os.makedirs(arrayfolder)
if cfg.pyrocko_download() == True:
A = Xcorr(ev, FilterMeta, evpath, Config, Syn_in,
arrayfolder)
else:
A = Xcorr(ev, FilterMeta, evpath, Config, Syn_in,
arrayfolder)
print "run Xcorr"
W, triggerobject = A.runXcorr()
XDict[i] = W
RefDict[i] = triggerobject.tdiff
SL[i] = len(network)
#endfor
fobjrefshift = open(rp, 'w')
pickle.dump(RefDict, fobjrefshift)
fobjrefshift.close()
output = open(ps, 'w')
pickle.dump(XDict, output)
output.close()
for i in sorted(XDict.iterkeys()):
Logfile.red('Array %s has %3d of %3d Stations left' %
(i, len(XDict[i]), SL[i]))
logger.info(
'\033[31mFor proceeding without changes press enter or give new comma seperatet network list or quit for exit\033[0m'
)
while True:
nnl = raw_input("please enter your choice: ")
#Logfile.add ('Choise = ' + nnl)
if len(nnl) == 0:
if not Basic.question('Process all networks ?'): continue
Logfile.red('This networks will be used for processing: %s' %
(Config['networks']))
break
elif str(nnl) == 'quit':
sys.exit()
elif str(nnl) == 'rerun':
event = os.path.join(*evpath.split('/')[-1:])
try:
os.remove(rp)
os.remove(ps)
except:
pass
mainfolder = os.path.join(os.path.sep, *evpath.split('/')[:-2])
os.chdir(mainfolder)
cmd = ('%s arraytool.py process %s') % (sys.executable, event)
Logfile.add('cmd = ' + cmd)
os.system(cmd)
sys.exit()
else:
# Check if selected array(s) exists
names = nnl.split(',')
isOk = True
for array in names:
arrayfolder = os.path.join(Folder['semb'], array)
if not os.path.isdir(arrayfolder):
Logfile.error('Illegal network name ' + str(array))
isOk = False
break
#endfor
if not isOk: continue # Illegal network : input again
# use these networks
Logfile.add('This networks will be used for processing: %s' %
(nnl))
Config['networks'] = nnl
break
for i in range(3, 0, -1):
time.sleep(1)
Logfile.red('Start processing in %d seconds ' % (i))
wd = Origin['depth']
start, stop, step = cfg.String('depths').split(',')
start = int(start)
stop = int(stop) + 1
step = int(step)
filters = cfg.String('filters')
filters = int(filters)
Logfile.add('working on ' + Config['networks'])
#==================================loop over depth======================
for filterindex in xrange(0, filters):
for depthindex in xrange(start, stop, step):
workdepth = float(wd) + depthindex
Origin['depth'] = workdepth
ev = Event(Origin['lat'],
Origin['lon'],
Origin['depth'],
Origin['time'],
strike=strike,
dip=dip,
rake=rake)
Logfile.add('WORKDEPTH: ' + str(Origin['depth']))
#==================================do prerequiries===============
#==================================loop over arrays================
ASL = []
weights = []
array_centers = []
networks = Config['networks'].split(',')
counter = 1
TriggerOnset = []
Wdfs = []
for i in networks:
arrayname = i
arrayfolder = os.path.join(Folder['semb'], arrayname)
network = Config[i].split('|')
Logfile.add('network: ' + str(network))
FilterMeta = ttt.filterStations(Meta, Config, Origin, network)
#if len(FilterMeta) < 3: continue #hs : wieder rein
if len(FilterMeta) < 3: continue
W = XDict[i]
refshift = RefDict[i]
FilterMeta = cmpFilterMetavsXCORR(W, FilterMeta)
Logfile.add(
'BOUNDING BOX DIMX: %s DIMY: %s GRIDSPACING: %s \n' %
(Config['dimx'], Config['dimy'], Config['gridspacing']))
##############=======================PARALLEL===========================================
Logfile.red('Calculating Traveltime Grid')
t1 = time.time()
isParallel = False #10.12.2015
TTTGridMap = []
mint = []
maxt = []
try:
f = open(
'../tttgrid/tttgrid_%s_%s_%s.pkl' %
(ev.time, arrayname, workdepth), 'rb')
print "loading travel time grid_%s_%s_%s.pkl" % (
ev.time, arrayname, workdepth)
TTTGridMap, mint, maxt = pickle.load(f)
f.close()
print "loading of travel time grid sucessful"
except:
print "loading of travel time grid unsucessful, will now calculate the grid:"
if isParallel: #hs
# maxp = int (Config['ncore'])
maxp = 6 #hs
po = multiprocessing.Pool(maxp)
for i in xrange(len(FilterMeta)):
po.apply_async(ttt.calcTTTAdv,
(Config, FilterMeta[i], Origin, i,
arrayname, W, refshift))
po.close()
po.join()
else: #hs+
for i in xrange(len(FilterMeta)):
t1 = time.time()
ttt.calcTTTAdv(Config, FilterMeta[i], Origin, i,
arrayname, W, refshift)
Logfile.add('ttt.calcTTTAdv : ' +
str(time.time() - t1) + ' sec.')
#endif #hs-
assert len(FilterMeta) > 0
TTTGridMap = deserializer.deserializeTTT(len(FilterMeta))
mint, maxt = deserializer.deserializeMinTMaxT(
len(FilterMeta))
f = open(
'../tttgrid/tttgrid_%s_%s_%s.pkl' %
(ev.time, arrayname, workdepth), 'wb')
print "dumping the traveltime grid for this array"
pickle.dump([TTTGridMap, mint, maxt], f)
f.close()
t2 = time.time()
Logfile.red('%s took %0.3f s' % ('TTT', (t2 - t1)))
switch = filterindex
tw = times.calculateTimeWindows(mint, maxt, Config, ev, switch)
if cfg.pyrocko_download() == True:
if cfg.quantity() == 'displacement':
Wd = waveform.readWaveformsPyrocko_restituted(
FilterMeta, tw, evpath, ev)
else:
Wd = waveform.readWaveformsPyrocko(
FilterMeta, tw, evpath, ev)
# Wdf = waveform.processpyrockoWaveforms(Wd, Config, Folder, arrayname, FilterMeta, ev, switch, W)
elif cfg.colesseo_input() == True:
Wd = waveform.readWaveforms_colesseo(
FilterMeta, tw, evpath, ev, C)
else:
Wd = waveform.readWaveforms(FilterMeta, tw, evpath, ev)
if cfg.Bool('synthetic_test') is True:
Wdf = waveform.processdummyWaveforms(
Wd, Config, Folder, arrayname, FilterMeta, ev, switch,
W)
Wdfs.append(Wdf)
else:
Wdf = waveform.processWaveforms(Wd, Config, Folder,
arrayname, FilterMeta, ev,
switch, W)
Wdfs.append(Wdf)
C.writeStationFile(FilterMeta, Folder, counter)
Logfile.red('%d Streams added for Processing' % (len(Wd)))
t1 = time.time()
f = open(
'../tttgrid/tttgrid_%s_%s_%s.pkl' %
(ev.time, arrayname, workdepth), 'rb')
print "loading travel time grid_%s_%s_%s.pkl" % (
ev.time, arrayname, workdepth)
TTTGridMap, mint, maxt = pickle.load(f)
f.close()
if cfg.optimize() == True:
optim.solve(counter, Config, Wdf, FilterMeta, mint, maxt,
TTTGridMap, Folder, Origin, ntimes, switch, ev,
arrayfolder, syn_in)
else:
arraySemb, weight, array_center = sembCalc.doCalc(
counter, Config, Wdf, FilterMeta, mint, maxt,
TTTGridMap, Folder, Origin, ntimes, switch, ev,
arrayfolder, syn_in)
t2 = time.time()
Logfile.add('CALC took %0.3f sec' % (t2 - t1))
weights.append(weight)
array_centers.append(array_center)
ASL.append(arraySemb)
counter += 1
sembCalc.writeSembMatricesSingleArray(arraySemb, Config,
Origin, arrayfolder,
ntimes, switch)
fileName = os.path.join(arrayfolder, 'stations.txt')
Logfile.add('Write to file ' + fileName)
fobjarraynetwork = open(fileName, 'w')
for i in FilterMeta:
fobjarraynetwork.write(
('%s %s %s\n') % (i.getName(), i.lat, i.lon))
fobjarraynetwork.close()
TTTGridMAP = []
if cfg.optimize_all() == True:
import optim_csemb
from optim_csemb import solve
sembmax = sembCalc.collectSemb(ASL, Config, Origin, Folder,
ntimes, len(networks), switch)
optim_csemb.solve(counter, Config, Wdf, FilterMeta, mint, maxt,
TTTGridMap, Folder, Origin, ntimes, switch,
ev, arrayfolder, syn_in, ASL, sembmax,
evpath, XDict, RefDict, workdepth,
filterindex, Wdfs)
if ASL:
Logfile.red('collect semblance matrices from all arrays')
sembmax = sembCalc.collectSemb(ASL, Config, Origin, Folder,
ntimes, len(networks), switch,
array_centers)
if cfg.Bool('weight_by_noise') == True:
sembCalc.collectSembweighted(ASL, Config, Origin, Folder,
ntimes, len(networks), switch,
weights)
else:
Logfile.red('Nothing to do -> Finish')
print "depth:"
print workdepth
def processWaveforms(WaveformDict, Config, Folder, network, MetaDict, Event,
switch, Xcorr):
Logfile.red('Start Processing')
cfg = FilterCfg(Config)
new_frequence = cfg.newFrequency()
for index, i in enumerate(WaveformDict):
Logfile.add('%s:%s ---------------------' % (index, i))
if Config['export_unfiltered'].capitalize() is 'True':
writeWaveform(Folder, i, WaveformDict[i], 'U', network)
station = getStation(i, MetaDict)
if cfg.Int('fm') == 1:
azi = ttt.bearing(Event, station)
bazi = ttt.backazi(station, Event)
msg = 'Takeoff ' + str(station.takeoff) + ' Azi ' + str(azi) +\
'Bazi ' + str(bazi)
Logfile.add(msg)
gain = float(station.gain)
if gain == 0.0 or gain == -1.0:
gain = 1
WaveformDict[i][0].data * (1.0 / gain)
if switch is 0:
Logfile.add('bandpass filtered stream for station %s ' % (i))
WaveformDict[i].filter('bandpass',
freqmin=cfg.flo(),
freqmax=cfg.fhi(),
corners=cfg.ns(),
zerophase=bool(Config['zph']))
elif switch is 1:
Logfile.add('bandpass filtered stream for station %s ' % (i))
WaveformDict[i].filter('bandpass',
freqmin=cfg.flo2(),
freqmax=cfg.fhi2(),
corners=cfg.ns2(),
zerophase=bool(Config['zph2']))
else:
Logfile.add('no filter set for station %s ' % (i))
if Config['export_filtered'].capitalize() is 'True':
writeWaveform(Folder, i, WaveformDict[i], 'F', network)
j = resampleWaveform(WaveformDict[i][0], new_frequence)
WaveformDict[i] = j
if Config['export_resampled'].capitalize() is 'True':
writeWaveform(Folder, i, WaveformDict[i], 'R', network)
return WaveformDict
parser.read(os.path.join('..', 'global.conf'))
for section_name in parser.sections():
for name, value in parser.items(section_name): cDict[name] = value
return cDict
options,args = main(sys.argv)
Basic.checkExistsDir(options.eventpath, isAbort=True)
Globals.setEventDir(options.eventpath)
C = config.Config(options.eventpath)
Origin = C.parseConfig('origin')
Conf = globalConf()
Config = C.parseConfig('config')
filter = FilterCfg(Config)
cfg = ConfigObj(dict=Config)
minDist, maxDist = cfg.FloatRange('mindist', 'maxdist')
ev = Event(Origin['lat'],Origin['lon'],Origin['depth'],Origin['time'] )
event = model.Event(lat=float(ev.lat), lon=float(ev.lon), depth=float(ev.depth)*1000., time=util.str_to_time(ev.time))
newFreq = float(filter.newFrequency())
options.time = Origin ['time']
options.duration = int(Conf['duration'])
sdspath = os.path.join(options.eventpath,'data')
model.dump_events([event], sdspath+'event.pf')
tmin = util.str_to_time(ev.time)-600.
tmax = util.str_to_time(ev.time)+1800.
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 filterWaveform(self, Waveform):
Logfile.red('Filter Waveform: ')
cfg = FilterCfg(self.Config)
#new_frequence = int (self.Config['new_frequence'])
new_frequence = int(cfg.newFrequency())
st = Stream()
for i in Waveform:
Logfile.red('Downsampling to %d: from %d' %
(new_frequence, i.stats.sampling_rate))
j = self.resampleWaveform(i, new_frequence)
j.detrend(type='demean')
old = True #???
if old:
switch = cfg.filterswitch() # ['filterswitch']
if switch == 1:
Logfile.add('bandpass filtered stream for station %s ' %
(i))
j.filter(
'bandpass',
freqmin=cfg.flo(), # ['flo']
freqmax=cfg.fhi(), # ['fhi']
corners=cfg.ns(), # ['ns']
zerophase=bool(self.Config['zph']))
elif switch == 2:
Logfile.add('lowpass filtered stream for station %s ' %
(i))
j.filter(
"lowpass",
freq=cfg.l_fc(), # ['l_fc']
corners=cfg.l_ns(), # ['l_ns']
zerophase=bool(self.Config['l_zph']))
elif switch == 3:
Logfile.add('highpass filtered stream for station %s ' %
(i))
j.filter(
"highpass",
freq=cfg.h_fc(), # ['h_fc']
corners=cfg.h_ns(), # ['h_ns']
zerophase=bool(self.Config['h_zph']))
else:
dummy = 1
#Logfile.add ('bandpass filtered stream for station %s '% (i))
#j.filter ("bandpass", freqmin=0.4, freqmax=3,
# corners=3, zerophase=False)
st.append(j)
else:
j1 = filterWaveform_2(Config, j, i)
st.append(j1)
#endfor
return st
def processLoop():
C = config.Config(evpath)
Origin = C.parseConfig('origin')
flag_rpe = False
try:
Syn_in = C.parseConfig('syn')
syn_in = SynthCfg(Syn_in)
except TypeError:
pass
Config = C.parseConfig('config')
cfg = ConfigObj(dict=Config)
phases = cfg.Str('ttphases')
phases = phases.split(',')
if cfg.pyrocko_download() is True:
Meta = C.readpyrockostations()
elif cfg.colesseo_input() is True:
scenario = guts.load(filename=cfg.colosseo_scenario_yml())
scenario_path = cfg.colosseo_scenario_yml()[:-12]
Meta = C.readcolosseostations(scenario_path)
else:
Meta = C.readMetaInfoFile()
Folder = C.createFolder()
C.writeConfig(Config, Origin, Folder)
filter = FilterCfg(Config)
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'))
origin = OriginCfg(Origin)
if cfg.colesseo_input() is True:
from pyrocko import util
events = scenario.get_events()
ev = events[0]
origin.strike = str(ev.moment_tensor.strike1)
origin.rake = str(ev.moment_tensor.rake1)
origin.dip = str(ev.moment_tensor.dip1)
strike = ev.moment_tensor.strike1
origin.lat = str(ev.lat)
origin.lon = str(ev.lon)
origin.depth = str(ev.depth / 1000.)
depth = ev.depth
origin.time = util.time_to_str(ev.time)
time_ev = util.time_to_str(ev.time)
lat = ev.lat
lon = ev.lon
rake = ev.moment_tensor.rake1
dip = ev.moment_tensor.dip1
Origin['strike'] = str(ev.moment_tensor.strike1)
Origin['rake'] = str(ev.moment_tensor.rake1)
Origin['dip'] = str(ev.moment_tensor.dip1)
Origin['lat'] = str(ev.lat)
Origin['lon'] = str(ev.lon)
Origin['time'] = util.time_to_str(ev.time)
Origin['depth'] = str(ev.depth / 1000.)
ev = Event(lat, lon, depth, time_ev, strike=strike, dip=dip, rake=rake)
else:
default = 0
strike = origin.strike(default)
dip = origin.dip(default)
rake = origin.rake(default)
ev = Event(origin.lat(),
origin.lon(),
origin.depth(),
origin.time(),
strike=strike,
dip=dip,
rake=rake)
if cfg.Bool('correct_shifts_empirical') is True:
Origin_emp = C.parseConfig('origin_emp')
origin_emp = OriginCfg(Origin_emp)
ev_emp = Event(origin_emp.lat(),
origin_emp.lon(),
origin_emp.depth(),
origin_emp.time(),
strike=strike,
dip=dip,
rake=rake)
filtername = filter.filterName()
Logfile.add('filtername = ' + filtername)
XDict = OrderedDict()
RefDict = OrderedDict()
SL = OrderedDict()
refshifts_global = []
newFreq = str(filter.newFrequency())
xcorrnetworks = cfg.String('networks').split(',')
if cfg.Int('xcorr') is 1:
fobjreferenceshiftname = newFreq + '_' + filtername + '.refpkl'
rp = os.path.join(Folder['semb'], fobjreferenceshiftname)
fobjreferenceshiftnameemp = newFreq + '_' + filtername + 'emp' + '.refpkl'
rpe = os.path.join(Folder['semb'], fobjreferenceshiftnameemp)
fobjpickleshiftname = newFreq + '_' + filtername + '.xcorrpkl'
ps = os.path.join(Folder['semb'], fobjpickleshiftname)
if (os.path.isfile(rp) and os.path.getsize(rp) != 0
and os.path.isfile(ps) and os.path.getsize(ps) != 0):
Logfile.add('xcorr/reference shift file exits : ' + rp)
Logfile.add('loaded reference shift')
if sys.version_info.major >= 3:
f = open(rp, 'rb')
else:
f = open(rp)
RefDict = pickle.load(f)
if sys.version_info.major >= 3:
x = open(ps, 'rb')
else:
x = open(ps)
XDict = pickle.load(x)
for i in xcorrnetworks:
SL[i] = len(Config[i].split('|'))
else:
SL = {}
for i in xcorrnetworks:
W = {}
network = cfg.String(i).split('|')
FilterMeta = ttt.filterStations(Meta, Config, Origin, network)
arrayfolder = os.path.join(Folder['semb'], i)
if os.access(arrayfolder, os.F_OK) is False:
os.makedirs(arrayfolder)
if cfg.pyrocko_download() is True:
# TODO check seperate xcoor nescessity
A = Xcorr(ev, FilterMeta, evpath, Config, Syn_in,
arrayfolder)
print("run Xcorr")
phase = phases[0]
W, triggerobject = A.runXcorr(phase)
XDict[i] = W
RefDict[i] = triggerobject.tdiff
SL[i] = len(network)
for j in range(0, len(FilterMeta)):
refshifts_global.append(triggerobject.tdiff)
if sys.version_info.major >= 3:
fobjrefshift = open(rp, 'wb')
else:
fobjrefshift = open(rp, 'w')
pickle.dump(RefDict, fobjrefshift)
fobjrefshift.close()
if sys.version_info.major >= 3:
output = open(ps, 'wb')
else:
output = open(ps, 'w')
pickle.dump(XDict, output)
output.close()
else:
fobjreferenceshiftname = newFreq + '_' + filtername + '.refpkl'
rp = os.path.join(Folder['semb'], fobjreferenceshiftname)
fobjreferenceshiftnameemp = newFreq + '_' + filtername + 'emp' + '.refpkl'
rpe = os.path.join(Folder['semb'], fobjreferenceshiftnameemp)
fobjpickleshiftname = newFreq + '_' + filtername + '.xcorrpkl'
ps = os.path.join(Folder['semb'], fobjpickleshiftname)
refshift = 0
if (os.path.isfile(rp) and os.path.getsize(rp) != 0
and os.path.isfile(ps) and os.path.getsize(ps) != 0):
Logfile.add('Temporay Memory file exits : ' + rp)
if sys.version_info.major >= 3:
f = open(rp, 'rb')
else:
f = open(rp)
RefDict = pickle.load(f)
if sys.version_info.major >= 3:
x = open(ps, 'rb')
else:
x = open(ps)
XDict = pickle.load(x)
for i in xcorrnetworks:
SL[i] = len(Config[j].split('|'))
network = cfg.String(i).split('|')
FilterMeta = ttt.filterStations(Meta, Config, Origin, network)
RefDict[i] = refshift
for j in range(0, len(FilterMeta)):
refshifts_global.append(refshift)
else:
SL = {}
for i in xcorrnetworks:
W = {}
refshift = 0
network = cfg.String(i).split('|')
FilterMeta = ttt.filterStations(Meta, Config, Origin, network)
arrayfolder = os.path.join(Folder['semb'], i)
if os.access(arrayfolder, os.F_OK) is False:
os.makedirs(arrayfolder)
if cfg.pyrocko_download() is True:
# TODO check seperate xcoor nescessity
A = Xcorr(ev, FilterMeta, evpath, Config, Syn_in,
arrayfolder)
else:
A = Xcorr(ev, FilterMeta, evpath, Config, Syn_in,
arrayfolder)
print("run Xcorr")
phase = phases[0]
W, triggerobject = A.runXcorr_dummy(phase)
XDict[j] = W
RefDict[j] = refshift
SL[j] = len(network)
for j in range(0, len(FilterMeta)):
refshifts_global.append(refshift)
if sys.version_info.major >= 3:
fobjrefshift = open(rp, 'wb')
else:
fobjrefshift = open(rp, 'w')
pickle.dump(RefDict, fobjrefshift)
fobjrefshift.close()
if sys.version_info.major >= 3:
output = open(ps, 'wb')
else:
output = open(ps, 'w')
pickle.dump(XDict, output)
output.close()
if sys.version_info.major >= 3:
for j in sorted(XDict.keys()):
Logfile.red('Array %s has %3d of %3d Stations left' %
(j, len(XDict[j]), SL[j]))
else:
for j in sorted(XDict.keys()):
Logfile.red('Array %s has %3d of %3d Stations left' %
(j, len(XDict[j]), SL[j]))
while True:
if sys.version_info.major >= 3:
nnl = input("please enter your choice: ")
else:
nnl = raw_input("please enter your choice: ")
if len(nnl) == 0:
if not Basic.question('Process all networks ?'):
continue
Logfile.red('This networks will be used for processing: %s' %
(Config['networks']))
break
elif str(nnl) == 'quit':
sys.exit()
elif str(nnl) == 'rerun':
event = os.path.join(*evpath.split('/')[-1:])
try:
os.remove(rp)
os.remove(ps)
except Exception:
pass
mainfolder = os.path.join(os.path.sep, *evpath.split('/')[:-2])
os.chdir(mainfolder)
cmd = ('%s arraytool.py process %s') % (sys.executable, event)
Logfile.add('cmd = ' + cmd)
os.system(cmd)
sys.exit()
else:
names = nnl.split(',')
isOk = True
for array in names:
arrayfolder = os.path.join(Folder['semb'], array)
if not os.path.isdir(arrayfolder):
Logfile.error('Illegal network name ' + str(array))
isOk = False
break
if not isOk:
continue
Logfile.add('This networks will be used for processing: %s' %
(nnl))
Config['networks'] = nnl
break
for j in range(3, 0, -1):
time.sleep(1)
Logfile.red('Start processing in %d seconds ' % (j))
wd = Origin['depth']
start, stop, step = cfg.String('depths').split(',')
start = int(start)
stop = int(stop) + 1
step_depth = int(step)
filters = cfg.String('filters')
filters = int(filters)
Logfile.add('working on ' + Config['networks'])
if cfg.Bool('correct_shifts_empirical') is True:
emp_loop = True
else:
emp_loop = False
# ==================================loop over phases======================
for phase in phases:
if phase is 'P':
desired = 'Z'
if phase is 'S':
desired = 'T'
# ==================================loop over filter setups=====
for filterindex in xrange(0, filters):
# ==================================loop over depth=======
for depthindex in xrange(start, stop, step_depth):
workdepth = float(wd) + depthindex
Origin['depth'] = workdepth
ev = Event(Origin['lat'],
Origin['lon'],
Origin['depth'],
Origin['time'],
strike=strike,
dip=dip,
rake=rake)
Logfile.add('WORKDEPTH: ' + str(Origin['depth']))
networks = Config['networks'].split(',')
ASL = []
weights = []
array_centers = []
counter = 1
stations_per_array = []
Wdfs = []
Wdfs_emp = []
FilterMetas = []
TTTgrids = OrderedDict()
mints = []
maxts = []
refshifts = []
for i in networks:
arrayname = i
arrayfolder = os.path.join(Folder['semb'], arrayname)
network = Config[i].split('|')
Logfile.add('network: ' + str(network))
FilterMeta = ttt.filterStations(Meta, Config, Origin,
network)
W = XDict[i]
refshift = RefDict[i]
for j in range(0, len(FilterMeta)):
if cfg.correct_shifts() is False:
refshift = refshift * 0.
refshifts.append(refshift)
FilterMeta = cmpFilterMetavsXCORR(W, FilterMeta)
Logfile.add('BOUNDING BOX DIMX: %s DIMY: %s GRIDSPACING:\
%s \n' % (Config['dimx'], Config['dimy'],
Config['gridspacing']))
Logfile.red('Calculating Traveltime Grid')
t1 = time.time()
isParallel = False
TTTGridMap = []
mint = []
maxt = []
ttt_model = cfg.Str('traveltime_model')
try:
if cfg.Bool('correct_shifts_empirical') is True:
f = open(
'../tttgrid/tttgrid%s_%s_%s_%s_%s_emp.pkl' %
(phase, ttt_model, ev_emp.time, arrayname,
workdepth), 'rb')
print(
"loading travel time grid%s_%s_%s_%s_%s_emp.pkl"
% (phase, ttt_model, ev_emp.time, arrayname,
workdepth))
TTTGridMap_emp, mint_emp, maxt_emp = pickle.load(f)
f.close()
f = open(
'../tttgrid/tttgrid%s_%s_%s_%s_%s.pkl' %
(phase, ttt_model, ev.time, arrayname, workdepth),
'rb')
print(
"loading travel time grid%s_%s_%s_%s_%s.pkl" %
(phase, ttt_model, ev.time, arrayname, workdepth))
TTTGridMap, mint, maxt = pickle.load(f)
f.close()
print("loading of travel time grid sucessful")
except Exception:
print("loading of travel time grid unsucessful,\n \
will now calculate the grid:")
if isParallel:
maxp = 6
po = multiprocessing.Pool(maxp)
for i in xrange(len(FilterMeta)):
po.apply_async(ttt.calcTTTAdv,
(Config, FilterMeta[i], Origin,
i, arrayname, W, refshift))
po.close()
po.join()
else:
for i in xrange(len(FilterMeta)):
t1 = time.time()
ttt.calcTTTAdv(Config, FilterMeta[i], Origin,
i, arrayname, W, refshift,
phase)
Logfile.add('ttt.calcTTTAdv : ' +
str(time.time() - t1) + ' sec.')
assert len(FilterMeta) > 0
TTTGridMap = deserializer.deserializeTTT(
len(FilterMeta))
mint, maxt = deserializer.deserializeMinTMaxT(
len(FilterMeta))
f = open(
'../tttgrid/tttgrid%s_%s_%s_%s_%s.pkl' %
(phase, ttt_model, ev.time, arrayname, workdepth),
'wb')
print("dumping the traveltime grid for this array")
pickle.dump([TTTGridMap, mint, maxt], f)
f.close()
if cfg.Bool('correct_shifts_empirical') is True:
ttt.calcTTTAdv(Config, FilterMeta[i], Origin_emp,
i, arrayname, W, refshift, phase)
assert len(FilterMeta) > 0
TTTGridMap_emp = deserializer.deserializeTTT(
len(FilterMeta))
mint_emp, maxt_emp = deserializer.deserializeMinTMaxT(
len(FilterMeta))
f = open(
'../tttgrid/tttgrid%s_%s_%s_%s_%s_emp.pkl' %
(phase, ttt_model, ev_emp.time, arrayname,
workdepth), 'wb')
print("dumping the traveltime grid for this array")
pickle.dump([TTTGridMap_emp, mint_emp, maxt_emp],
f)
f.close()
t2 = time.time()
Logfile.red('%s took %0.3f s' % ('TTT', (t2 - t1)))
switch = filterindex
tw = times.calculateTimeWindows(mint, maxt, Config, ev,
switch)
if cfg.Bool('correct_shifts_empirical') is True:
tw_emp = times.calculateTimeWindows(
mint_emp, maxt_emp, Config, ev_emp, switch)
if cfg.pyrocko_download() is True:
if cfg.quantity() == 'displacement':
Wd_emp = waveform.readWaveformsPyrocko_restituted(
FilterMeta, tw, evpath, ev_emp, desired)
elif cfg.Bool('synthetic_test') is True:
Wd_emp = waveform.readWaveformsPyrockodummy(
FilterMeta, tw_emp, evpath_emp, ev_emp)
else:
Wd_emp = waveform.readWaveformsPyrocko(
FilterMeta, tw_emp, evpath_emp, ev_emp,
desired)
elif cfg.colesseo_input() is True:
Wd_emp = waveform.readWaveforms_colesseo(
FilterMeta, tw_emp, evpath_emp, ev_emp, C)
else:
Wd_emp = waveform.readWaveforms(
FilterMeta, tw_emp, evpath_emp, ev_emp)
if cfg.Bool('synthetic_test') is True\
or cfg.Bool('dynamic_filter') is True:
Wdf_emp = waveform.processdummyWaveforms(
Wd_emp, Config, Folder, arrayname, FilterMeta,
ev_emp, switch, W)
Wdfs_emp.extend(Wdf_emp)
else:
Wdf_emp = waveform.processWaveforms(
Wd_emp, Config, Folder, arrayname, FilterMeta,
ev_emp, switch, W)
Wdfs_emp.extend(Wdf_emp)
if cfg.pyrocko_download() is True:
if cfg.quantity() == 'displacement':
Wd = waveform.readWaveformsPyrocko_restituted(
FilterMeta, tw, evpath, ev, desired)
elif cfg.Bool('synthetic_test') is True:
Wd = waveform.readWaveformsPyrockodummy(
FilterMeta, tw, evpath, ev)
else:
Wd = waveform.readWaveformsPyrocko(
FilterMeta, tw, evpath, ev, desired)
elif cfg.colesseo_input() is True:
Wd = waveform.readWaveforms_colesseo(
FilterMeta, tw, evpath, ev, C)
else:
Wd = waveform.readWaveforms(FilterMeta, tw, evpath, ev)
if cfg.Bool('synthetic_test') is True\
or cfg.Bool('dynamic_filter') is True:
Wdf = waveform.processdummyWaveforms(
Wd, Config, Folder, arrayname, FilterMeta, ev,
switch, W)
Wdfs.extend(Wdf)
else:
Wdf = waveform.processWaveforms(
Wd, Config, Folder, arrayname, FilterMeta, ev,
switch, W)
Wdfs.extend(Wdf)
C.writeStationFile(FilterMeta, Folder, counter)
Logfile.red('%d Streams added for Processing' % (len(Wd)))
t1 = time.time()
f = open(
'../tttgrid/tttgrid%s_%s_%s_%s_%s.pkl' %
(phase, ttt_model, ev.time, arrayname, workdepth),
'rb')
TTTGridMap, mint, maxt = pickle.load(f)
f.close()
if switch == 0:
step = cfg.step()
if switch == 1:
step = cfg.step_f2()
if cfg.UInt('forerun') > 0:
ntimes = int(
(cfg.UInt('forerun') + cfg.UInt('duration')) /
step)
else:
ntimes = int((cfg.UInt('duration')) / step)
if cfg.Bool('combine_all') is False:
if cfg.optimize() is True:
optim.solve(counter, Config, Wdf, FilterMeta, mint,
maxt, TTTGridMap, Folder, Origin,
ntimes, switch, ev, arrayfolder,
syn_in, refshifts, phase,
rpe + str(arrayname), flag_rpe)
else:
if cfg.Bool('correct_shifts_empirical') is True:
if cfg.Bool('correct_shifts_empirical_run'
) is True:
f = open(
'../tttgrid/tttgrid%s_%s_%s_%s_%s_emp.pkl'
% (phase, ttt_model, ev_emp.time,
arrayname, workdepth), 'rb')
TTTGridMap_emp, mint_emp, maxt_emp = pickle.load(
f)
f.close()
flag_rpe = True
arraySemb, weight, array_center = sembCalc.doCalc(
counter, Config, Wdf_emp, FilterMeta,
mint, maxt, TTTGridMap_emp, Folder,
Origin, ntimes, switch, ev_emp,
arrayfolder, syn_in, refshifts, phase,
rpe + str(arrayname), flag_rpe)
if sys.version_info.major >= 3:
f = open(rpe + str(arrayname), 'rb')
else:
f = open(rpe + str(arrayname))
RefDict_empirical = pickle.load(f)
refshifts = RefDict_empirical
for j in range(0, len(FilterMeta)):
if cfg.correct_shifts() is False:
refshifts[j] = refshifts[j] * 0.
flag_rpe = False
arraySemb, weight, array_center = sembCalc.doCalc(
counter, Config, Wdf, FilterMeta, mint, maxt,
TTTGridMap, Folder, Origin, ntimes, switch, ev,
arrayfolder, syn_in, refshifts, phase,
rpe + str(arrayname), flag_rpe)
weights.append(weight)
array_centers.append(array_center)
ASL.append(arraySemb)
sembCalc.writeSembMatricesSingleArray(
arraySemb, Config, Origin, arrayfolder, ntimes,
switch, phase)
fileName = os.path.join(arrayfolder, 'stations.txt')
Logfile.add('Write to file ' + fileName)
fobjarraynetwork = open(fileName, 'w')
for i in FilterMeta:
fobjarraynetwork.write(
('%s %s %s\n') % (i.getName(), i.lat, i.lon))
fobjarraynetwork.close()
t2 = time.time()
Logfile.add('CALC took %0.3f sec' % (t2 - t1))
counter += 1
stations_per_array.append(len(FilterMeta))
TTTgrids.update(TTTGridMap)
mints.append(mint)
maxts.append(maxt)
FilterMetas[len(FilterMetas):] = FilterMeta
TTTGridMap = []
if cfg.Bool('combine_all') is True:
if cfg.pyrocko_download() is True:
if cfg.Bool('synthetic_test') is True:
Wd = waveform.readWaveformsPyrockodummy(
FilterMetas, tw, evpath, ev)
else:
if cfg.quantity() == 'displacement':
Wd = waveform.readWaveformsPyrocko_restituted(
FilterMetas, tw, evpath, ev, desired)
else:
Wd = waveform.readWaveformsPyrocko(
FilterMetas, tw, evpath, ev, desired)
elif cfg.colesseo_input() is True:
Wd = waveform.readWaveforms_colesseo(
FilterMetas, tw, evpath, ev, C)
else:
Wd = waveform.readWaveforms(FilterMetas, tw, evpath,
ev)
if cfg.Bool('synthetic_test') is True:
Wdf = waveform.processdummyWaveforms(
Wd, Config, Folder, arrayname, FilterMetas, ev,
switch, W)
else:
Wdf = waveform.processWaveforms(
Wd, Config, Folder, arrayname, FilterMetas, ev,
switch, W)
mint = num.min(mints)
maxt = num.max(maxts)
flag_rpe = False
if cfg.Bool('bootstrap_array_weights') is False:
arraySemb, weight, array_center = sembCalc.doCalc(
counter, Config, Wdf, FilterMetas, mint, maxt,
TTTgrids, Folder, Origin, ntimes, switch, ev,
arrayfolder, syn_in, refshifts_global, phase,
rpe + str(arrayname), flag_rpe)
ASL.append(arraySemb)
weights.append(weight)
array_centers.append(array_center)
sembCalc.writeSembMatricesSingleArray(
arraySemb, Config, Origin, arrayfolder, ntimes,
switch, phase)
else:
nboot = cfg.Int('n_bootstrap')
tmp_general = 1
for ibootstrap in range(nboot):
f = rstate.uniform(0., 1., size=counter + 1)
f = num.sort(f)
g = f[1:] - f[:-1]
k = 0
ws = []
for wss in range(0, counter - 1):
for stats in range(0, stations_per_array[k]):
ws.append(g[k])
k = +1
ws = num.asarray(ws)
arraySemb, weight, array_center = sembCalc.doCalc(
counter,
Config,
Wdf,
FilterMetas,
mint,
maxt,
TTTgrids,
Folder,
Origin,
ntimes,
switch,
ev,
arrayfolder,
syn_in,
refshifts_global,
phase,
rpe + str(arrayname),
flag_rpe,
bs_weights=ws)
ASL.append(arraySemb)
weights.append(weight)
array_centers.append(array_center)
sembCalc.writeSembMatricesSingleArray(
arraySemb,
Config,
Origin,
arrayfolder,
ntimes,
switch,
phase,
bootstrap=ibootstrap)
if ASL:
Logfile.red('collect semblance matrices from\
all arrays')
sembmax, tmp = sembCalc.collectSemb(
ASL,
Config,
Origin,
Folder,
ntimes,
len(networks),
switch,
array_centers,
phase,
cboot=ibootstrap)
tmp_general *= tmp
ASL = []
sembmax, tmp = sembCalc.collectSemb(
ASL,
Config,
Origin,
Folder,
ntimes,
len(networks),
switch,
array_centers,
phase,
cboot=None,
temp_comb=tmp_general)
if cfg.optimize_all() is True:
import optim_csemb
sembmax, tmp = sembCalc.collectSemb(
ASL, Config, Origin, Folder, ntimes, len(networks),
switch)
optim_csemb.solve(counter, Config, Wdf, FilterMeta, mint,
maxt, TTTGridMap, Folder, Origin, ntimes,
switch, ev, arrayfolder, syn_in, ASL,
sembmax, evpath, XDict, RefDict,
workdepth, filterindex, Wdfs)
if ASL and cfg.Bool('bootstrap_array_weights') is False:
Logfile.red('collect semblance matrices from all arrays')
sembmax, tmp = sembCalc.collectSemb(
ASL, Config, Origin, Folder, ntimes, len(networks),
switch, array_centers, phase)
if cfg.Bool('weight_by_noise') is True:
sembCalc.collectSembweighted(ASL, Config, Origin,
Folder, ntimes,
len(networks), switch,
weights)
else:
Logfile.red('Nothing to do -> Finish')
print("last work depth:")
print(workdepth)
def processWaveforms(WaveformDict, Config, Folder, network, MetaDict, Event,
switch, Xcorr):
Logfile.red('Start Processing')
cfg = FilterCfg(Config)
new_frequence = cfg.newFrequency() # ['new_frequence']
vp, vs, rho = ttt.calcak135parameter(Event)
for index, i in enumerate(WaveformDict):
Logfile.add(
'%s:%s -------------------------------------------------------------'
% (index, i))
if Config['export_unfiltered'].capitalize() == 'True':
writeWaveform(Folder, i, WaveformDict[i], 'U', network)
station = getStation(i, MetaDict)
psign = 1
if cfg.Int('fm') == 1:
azi = ttt.bearing(Event, station)
bazi = ttt.backazi(station, Event)
psign = ttt.dubcup(rho, vp, vs, Event.strike, Event.dip,
Event.rake, azi, station.takeoff)
msg = 'Takeoff ' + str(
station.takeoff) + ' Azi ' + str(azi) + ' Bazi ' + str(bazi)
msg += (' vp ' + str(vp) + ' vs ' + str(vs) + ' rho ' + str(rho) +
' Psign ' + str(psign))
Logfile.add(msg)
try:
Logfile.add(station.getName() + ' ' + station.lat + ' ' +
station.lon + ' ' + station.gain + ' PSIGN: ' +
str(psign))
except:
try:
print psign, station.getName(
), station.lat, station.lon, station.gain
except:
pass
if psign == -1:
Logfile.add('correcting polarisation for station %s ' % (i))
-1. * WaveformDict[i][0].data
#gain correctur
gain = float(station.gain)
if gain == 0.0 or gain == -1.0:
gain = 1 #hs : gain missing in metafile
WaveformDict[i][0].data * (1.0 / gain)
if switch == 0:
Logfile.add('bandpass filtered stream for station %s ' % (i))
WaveformDict[i].filter(
'bandpass',
freqmin=cfg.flo(), # ['flo']
freqmax=cfg.fhi(), # ['fhi']
corners=cfg.ns(), # ['ns']
zerophase=bool(Config['zph']))
elif switch == 1:
Logfile.add('bandpass filtered stream for station %s ' % (i))
WaveformDict[i].filter(
'bandpass',
freqmin=cfg.flo2(), # ['flo']
freqmax=cfg.fhi2(), # ['fhi']
corners=cfg.ns2(), # ['ns']
zerophase=bool(Config['zph2']))
else:
Logfile.add('no filter set for station %s ' % (i))
if Config['export_filtered'].capitalize() == 'True':
writeWaveform(Folder, i, WaveformDict[i], 'F', network)
#resampling
j = resampleWaveform(WaveformDict[i][0], new_frequence)
WaveformDict[i] = j
if Config['export_resampled'].capitalize() == 'True':
writeWaveform(Folder, i, WaveformDict[i], 'R', network)
return WaveformDict
def processLoop():
#==================================get meta info==========================================
C = config.Config(evpath)
Origin = C.parseConfig('origin')
Config = C.parseConfig('config')
Meta = C.readMetaInfoFile()
#==================================get meta info==========================================
#==================================do prerequiries========================================
Folder = C.createFolder()
C.cpSkeleton(Folder, Config)
C.writeConfig(Config, Origin, Folder)
cfg = ConfigObj(dict=Config)
filter = FilterCfg(Config)
origin = OriginCfg(Origin)
ntimes = int(
(cfg.UInt('forerun') + cfg.UInt('duration')) / cfg.UInt('step'))
default = 0
strike = origin.strike(default) # Origin.get ('strike', default)
dip = origin.dip(default) # Origin.get ('dip', default)
rake = origin.rake(default) # Origin.get ('rake', default)
# ev = Event (Origin['lat'],Origin['lon'],Origin['depth'],Origin['time'],
# strike = strike,dip=dip,rake=rake)
ev = Event(origin.lat(),
origin.lon(),
origin.depth(),
origin.time(),
strike=strike,
dip=dip,
rake=rake)
filtername = filter.filterName()
Logfile.add('filtername = ' + filtername)
#todo crosscorrelation for all arrays before processing
XDict = {}
RefDict = {}
SL = {}
if cfg.Int('xcorr') == 1:
newFreq = str(filter.newFrequency())
fobjreferenceshiftname = newFreq + '_' + filtername + '.refpkl'
rp = os.path.join(Folder['semb'], fobjreferenceshiftname)
fobjpickleshiftname = newFreq + '_' + filtername + '.xcorrpkl'
ps = os.path.join(Folder['semb'], fobjpickleshiftname)
if (os.path.isfile(rp) and os.path.getsize(rp) != 0
and os.path.isfile(ps) and os.path.getsize(ps) != 0):
Logfile.add('file exits : ' + rp)
Logfile.add('load refshifts')
f = open(rp)
RefDict = pickle.load(f)
x = open(ps)
XDict = pickle.load(x)
#xcorrnetworks = Config['networks'].split(',')
xcorrnetworks = cfg.String('networks').split(',')
for i in xcorrnetworks:
SL[i] = len(Config[i].split('|'))
else:
SL = {}
xcorrnetworks = cfg.String('networks').split(',')
for i in xcorrnetworks:
W = {}
refshift = 0
network = cfg.String(i).split('|')
FilterMeta = ttt.filterStations(Meta, Config, Origin, network)
arrayfolder = os.path.join(Folder['semb'], i)
if os.access(arrayfolder, os.F_OK) == False:
os.makedirs(arrayfolder)
A = Xcorr(ev, FilterMeta, evpath, Config, arrayfolder)
W, triggerobject = A.runXcorr()
XDict[i] = W
RefDict[i] = triggerobject.tdiff
SL[i] = len(network)
#endfor
fobjrefshift = open(rp, 'w')
pickle.dump(RefDict, fobjrefshift)
fobjrefshift.close()
output = open(ps, 'w')
pickle.dump(XDict, output)
output.close()
#endif
for i in sorted(XDict.iterkeys()):
Logfile.red('Array %s has %3d of %3d Stations left' %
(i, len(XDict[i]), SL[i]))
logger.info(
'\033[31mFor proceeding without changes press enter or give new comma seperatet network list or quit for exit\033[0m'
)
while True:
nnl = raw_input("please enter your choice: ")
#Logfile.add ('Choise = ' + nnl)
if len(nnl) == 0:
if not Basic.question('Process all networks ?'): continue
Logfile.red('This networks will be used for processing: %s' %
(Config['networks']))
break
elif str(nnl) == 'quit':
sys.exit()
elif str(nnl) == 'rerun':
event = os.path.join(*evpath.split('/')[-1:])
try:
os.remove(rp)
os.remove(ps)
except:
pass
mainfolder = os.path.join(os.path.sep, *evpath.split('/')[:-2])
os.chdir(mainfolder)
cmd = ('%s arraytool.py process %s') % (sys.executable, event)
Logfile.add('cmd = ' + cmd)
os.system(cmd)
sys.exit()
else:
# Check if selected array(s) exists
names = nnl.split(',')
isOk = True
for array in names:
arrayfolder = os.path.join(Folder['semb'], array)
if not os.path.isdir(arrayfolder):
Logfile.error('Illegal network name ' + str(array))
isOk = False
break
#endfor
if not isOk: continue # Illegal network : input again
# use these networks
Logfile.add('This networks will be used for processing: %s' %
(nnl))
Config['networks'] = nnl
break
#endif
#endwhile True
for i in range(3, 0, -1):
time.sleep(1)
Logfile.red('Start processing in %d seconds ' % (i))
#endfor
#print XDict
#print RefDict
#TriggerOnset.append(triggerobject)
#print 'MAINTDIFF ',triggerobject.tdiff
#sys.exit()
wd = Origin['depth']
start, stop, step = cfg.String('depths').split(',')
start = int(start)
stop = int(stop) + 1
step = int(step)
Logfile.add('working on ' + Config['networks'])
#==================================loop over depth=======================================
for depthindex in xrange(start, stop):
workdepth = float(wd) + depthindex * step
Origin['depth'] = workdepth
ev = Event(Origin['lat'],
Origin['lon'],
Origin['depth'],
Origin['time'],
strike=strike,
dip=dip,
rake=rake)
Logfile.add('WORKDEPTH: ' + str(Origin['depth']))
#==================================do prerequiries========================================
#==================================loop over arrays=======================================
ASL = []
networks = Config['networks'].split(',')
counter = 1
TriggerOnset = []
for i in networks:
arrayname = i
arrayfolder = os.path.join(Folder['semb'], arrayname)
network = Config[i].split('|')
Logfile.add('network: ' + str(network))
FilterMeta = ttt.filterStations(Meta, Config, Origin, network)
#if len(FilterMeta) < 3: continue #hs : wieder rein
if len(FilterMeta) < 3: continue
W = XDict[i]
refshift = RefDict[i]
FilterMeta = cmpFilterMetavsXCORR(W, FilterMeta)
#print 'W: ',W,len(W); print refshift; print 'FM ',FilterMeta,len(FilterMeta)
Logfile.add(
'BOUNDING BOX DIMX: %s DIMY: %s GRIDSPACING: %s \n' %
(Config['dimx'], Config['dimy'], Config['gridspacing']))
##############=======================PARALLEL===========================================
Logfile.red('Calculating Traveltime Grid')
t1 = time.time()
if WINDOWS:
isParallel = False #hs : parallel
#else : isParallel = True #10.12.2015
else:
isParallel = False #10.12.2015
if isParallel: #hs
maxp = int(Config['ncore'])
#maxp = 20 #hs
po = multiprocessing.Pool(maxp)
for i in xrange(len(FilterMeta)):
po.apply_async(ttt.calcTTTAdv,
(Config, FilterMeta[i], Origin, i,
arrayname, W, refshift))
po.close()
po.join()
else: #hs+
for i in xrange(len(FilterMeta)):
t1 = time.time()
ttt.calcTTTAdv(Config, FilterMeta[i], Origin, i, arrayname,
W, refshift)
Logfile.add('ttt.calcTTTAdv : ' + str(time.time() - t1) +
' sec.')
#endif #hs-
assert len(FilterMeta) > 0
TTTGridMap = deserializer.deserializeTTT(len(FilterMeta))
mint, maxt = deserializer.deserializeMinTMaxT(len(FilterMeta))
t2 = time.time()
Logfile.red('%s took %0.3f s' % ('TTT', (t2 - t1)))
#sys.exit()
##############=======================SERIELL===========================================
tw = times.calculateTimeWindows(mint, maxt, Config, ev)
Wd = waveform.readWaveforms(FilterMeta, tw, evpath, ev)
Wdf = waveform.processWaveforms(Wd, Config, Folder, arrayname,
FilterMeta, ev, W)
#sys.exit()
C.writeStationFile(FilterMeta, Folder, counter)
Logfile.red('%d Streams added for Processing' % (len(Wd)))
##############=========================================================================
##############=======================PARALLEL==========================================
t1 = time.time()
arraySemb = sembCalc.doCalc(counter, Config, Wdf, FilterMeta, mint,
maxt, TTTGridMap, Folder, Origin,
ntimes)
t2 = time.time()
Logfile.add('CALC took %0.3f sec' % (t2 - t1))
ASL.append(arraySemb)
counter += 1
sembCalc.writeSembMatricesSingleArray(arraySemb, Config, Origin,
arrayfolder, ntimes)
fileName = os.path.join(arrayfolder, 'stations.txt')
Logfile.add('Write to file ' + fileName)
fobjarraynetwork = open(fileName, 'w')
for i in FilterMeta:
fobjarraynetwork.write(
('%s %s %s\n') % (i.getName(), i.lat, i.lon))
fobjarraynetwork.close()
if ASL:
Logfile.red('collect semblance matrices from all arrays')
sembCalc.collectSemb(ASL, Config, Origin, Folder, ntimes,
len(networks))
#fobjtrigger = open (os.path.join(Folder['semb'],'Trigger.txt'),'w')
#for i in TriggerOnset:
# print i.aname,i.sname,i.ttime
# fobjtrigger.write(('%s %s %s\n')%(i.aname,i.sname,i.ttime))
#fobjtrigger.close()
else:
Logfile.red('Nothing to do -> Finish')