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')