def traveltimes(self, phase): Logfile.red('Enter AUTOMATIC CROSSCORRELATION ') Logfile.red('\n\n+++++++++++++++++++++++++++++++++++++++++++++++\n ') T = [] Wdict = OrderedDict() SNR = OrderedDict() Config = self.Config cfg = ConfigObj(dict=Config) for i in self.StationMeta: Logfile.red('read in %s ' % (i)) de = loc2degrees(self.Origin, i) Phase = cake.PhaseDef(phase) traveltime_model = cfg.Str('traveltime_model') model = cake.load_model('../data/' + traveltime_model) if cfg.colesseo_input() is True: arrivals = model.arrivals([de, de], phases=Phase, zstart=self.Origin.depth, zstop=0.) else: arrivals = model.arrivals([de, de], phases=Phase, zstart=self.Origin.depth * km, zstop=0.) try: ptime = arrivals[0].t except Exception: try: arrivals = model.arrivals([de, de], phases=Phase, zstart=self.Origin.depth * km - 2.1) ptime = arrivals[0].t except Exception: ptime = 0 T.append(ptime) if ptime == 0: Logfile.red('Available phases for station %s in\ range %f deegree' % (i, de)) Logfile.red('you tried phase %s' % (phase)) raise Exception("ILLEGAL: phase definition") else: tw = self.calculateTimeWindows(ptime) if cfg.pyrocko_download() is True: w, snr = self.readWaveformsCross_pyrocko(i, tw, ptime) elif cfg.colesseo_input() is True: w, snr = self.readWaveformsCross_colesseo(i, tw, ptime) else: w, snr = self.readWaveformsCross(i, tw, ptime) Wdict[i.getName()] = w SNR[i.getName()] = snr Logfile.red('\n\n+++++++++++++++++++++++++++++++++++++++++++++++ ') Logfile.red('Exit AUTOMATIC FILTER ') return Wdict, SNR
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 calcTTTAdv(Config, station, Origin, flag, arrayname, Xcorrshift, Refshift, phase): cfg = ConfigObj(dict=Config) if cfg.Bool('correct_shifts_empirical') is True: dimX = cfg.Int('dimx_emp') dimY = cfg.Int('dimy_emp') else: dimX = cfg.Int('dimx') dimY = cfg.Int('dimy') gridspacing = cfg.Float('gridspacing') traveltime_model = cfg.Str('traveltime_model') o_lat = float(Origin['lat']) o_lon = float(Origin['lon']) o_depth = float(Origin['depth']) oLator = o_lat + dimX / 2 oLonor = o_lon + dimY / 2 oLatul = 0 oLonul = 0 o_dip = 80. plane = False TTTGridMap = {} LMINMAX = [] GridArray = {} locStation = Location(station.lat, station.lon) sdelta = loc2degrees(Location(o_lat, o_lon), locStation) Phase = cake.PhaseDef(phase) model = cake.load_model('../data/' + traveltime_model) z = 0 if plane is True: depth = np.linspace(0., 40., num=dimY) for i in xrange(70): oLatul = o_lat - ((dimX - 1) / 2) * gridspacing + i * gridspacing if z == 0 and i == 0: Latul = oLatul o = 0 start_time = time.clock() for j in xrange(40): oLonul = o_lon - ( (dimY - 1) / 2) * gridspacing + j * gridspacing / np.cos(o_dip) if o == 0 and j == 0: Lonul = oLonul de = loc2degrees(Location(oLatul, oLonul), locStation) arrivals = model.arrivals([de, de], phases=Phase, zstart=depth[j] * km, zstop=0.) try: ttime = arrivals[0].t except Exception: try: arrivals = model.arrivals([de, de], phases=Phase, zstart=depth[j] * km - 2.5, zstop=depth[j] * km + 2.5, refine=True) ttime = arrivals[0].t except Exception: tt = obs_TravelTimes(de, o_depth) for k in tt: if k['phase_name'] == 'P' or k['phase_name'] == ( '%sdiff') % (Config[phasename]): ttime = k['time'] print("Something wrong with phase arrival, too large\ distances choosen?") GridArray[(i, j)] = GridElem(oLatul, oLonul, depth[j], ttime, de) LMINMAX.append(ttime) GridArray[(i, j)] = GridElem(oLatul, oLonul, o_depth, ttime, de) LMINMAX.append(ttime) if ttime == 0: raise Exception("\033[31mILLEGAL: phase definition\033[0m") else: for i in xrange(dimX): oLatul = o_lat - ((dimX - 1) / 2) * gridspacing + i * gridspacing if z == 0 and i == 0: Latul = oLatul o = 0 for j in xrange(dimY): oLonul = o_lon - ( (dimY - 1) / 2) * gridspacing + j * gridspacing if o == 0 and j == 0: Lonul = oLonul de = loc2degrees(Location(oLatul, oLonul), locStation) arrivals = model.arrivals([de, de], phases=Phase, zstart=o_depth * km) try: ttime = arrivals[0].t except: try: arrivals = model.arrivals([de, de], phases=Phase, zstart=o_depth * km, zstop=o_depth * km, refine=True) ttime = arrivals[0].t except: arrivals = model.arrivals([de, de], phases=Phase, zstart=o_depth * km - 2.5, zstop=o_depth * km + 2.5, refine=True) ttime = arrivals[0].t GridArray[(i, j)] = GridElem(oLatul, oLonul, o_depth, ttime, de) LMINMAX.append(ttime) GridArray[(i, j)] = GridElem(oLatul, oLonul, o_depth, ttime, de) LMINMAX.append(ttime) if ttime == 0: raise Exception("\033[31mILLEGAL: phase definition\033[0m") mint = min(LMINMAX) maxt = max(LMINMAX) TTTGridMap[station.getName()] = TTTGrid(o_depth, mint, maxt, Latul, Lonul, oLator, oLonor, GridArray) k = MinTMaxT(mint, maxt) Basic.dumpToFile(str(flag) + '-ttt.pkl', TTTGridMap) Basic.dumpToFile('minmax-' + str(flag) + '.pkl', k) Basic.dumpToFile('station-' + str(flag) + '.pkl', station)