Merge branch 'develop' of ariadne:/data/git/pylot into develop
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commit
27e425844a
17
autoPyLoT.py
17
autoPyLoT.py
@ -346,7 +346,8 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
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picks[stats]['P'].update(props)
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evt = moment_mag.updated_event()
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net_mw = moment_mag.net_magnitude()
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print("Network moment magnitude: %4.1f" % net_mw.mag)
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if net_mw is not None:
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print("Network moment magnitude: %4.1f" % net_mw.mag)
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# calculate local (Richter) magntiude
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WAscaling = parameter.get('WAscaling')
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magscaling = parameter.get('magscaling')
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@ -363,8 +364,15 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
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evt = local_mag.updated_event(magscaling)
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net_ml = local_mag.net_magnitude(magscaling)
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print("Network local magnitude: %4.1f" % net_ml.mag)
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print("Network local magnitude scaled with:")
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print("%f * Ml + %f" % (magscaling[0], magscaling[1]))
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if magscaling == None:
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scaling = False
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elif magscaling[0] != 0 and magscaling[1] != 0:
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scaling = False
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else:
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scaling = True
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if scaling:
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print("Network local magnitude scaled with:")
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print("%f * Ml + %f" % (magscaling[0], magscaling[1]))
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else:
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print("autoPyLoT: No NLLoc-location file available!")
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print("No source parameter estimation possible!")
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@ -421,7 +429,8 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
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picks[stats]['P'].update(props)
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evt = moment_mag.updated_event()
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net_mw = moment_mag.net_magnitude()
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print("Network moment magnitude: %4.1f" % net_mw.mag)
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if net_mw is not None:
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print("Network moment magnitude: %4.1f" % net_mw.mag)
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# calculate local (Richter) magntiude
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WAscaling = parameter.get('WAscaling')
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magscaling = parameter.get('magscaling')
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@ -4,19 +4,19 @@
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%Parameters are optimized for %extent data sets!
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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#main settings#
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#rootpath# %project path
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#datapath# %data path
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#database# %name of data base
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#eventID# %event ID for single event processing (* for all events found in database)
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#invdir# %full path to inventory or dataless-seed file
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/DATA/Insheim #rootpath# %project path
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EVENT_DATA/LOCAL #datapath# %data path
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2018.02_Insheim #database# %name of data base
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e0006.038.18 #eventID# %event ID for single event processing (* for all events found in database)
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/DATA/Insheim/STAT_INFO #invdir# %full path to inventory or dataless-seed file
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PILOT #datastructure# %choose data structure
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True #apverbose# %choose 'True' or 'False' for terminal output
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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#NLLoc settings#
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None #nllocbin# %path to NLLoc executable
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None #nllocroot# %root of NLLoc-processing directory
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None #phasefile# %name of autoPyLoT-output phase file for NLLoc
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None #ctrfile# %name of autoPyLoT-output control file for NLLoc
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/home/ludger/NLLOC #nllocbin# %path to NLLoc executable
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/home/ludger/NLLOC/Insheim #nllocroot# %root of NLLoc-processing directory
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AUTOPHASES.obs #phasefile# %name of autoPyLoT-output phase file for NLLoc
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Insheim_min1d032016_auto.in #ctrfile# %name of autoPyLoT-output control file for NLLoc
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ttime #ttpatter# %pattern of NLLoc ttimes from grid
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AUTOLOC_nlloc #outpatter# %pattern of NLLoc-output file
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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@ -27,31 +27,31 @@ AUTOLOC_nlloc #outpatter# %pattern of
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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#settings local magnitude#
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1.11 0.0009 -2.0 #WAscaling# %Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm] If zeros are set, original Richter magnitude is calculated!
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1.0382 -0.447 #magscaling# %Scaling relation for derived local magnitude [a*Ml+b]. If zeros are set, no scaling of network magnitude is applied!
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0.0 0.0 #magscaling# %Scaling relation for derived local magnitude [a*Ml+b]. If zeros are set, no scaling of network magnitude is applied!
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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#filter settings#
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1.0 1.0 #minfreq# %Lower filter frequency [P, S]
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10.0 10.0 #maxfreq# %Upper filter frequency [P, S]
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2 2 #filter_order# %filter order [P, S]
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2.0 2.0 #minfreq# %Lower filter frequency [P, S]
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30.0 15.0 #maxfreq# %Upper filter frequency [P, S]
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3 3 #filter_order# %filter order [P, S]
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bandpass bandpass #filter_type# %filter type (bandpass, bandstop, lowpass, highpass) [P, S]
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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#common settings picker#
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local #extent# %extent of array ("local", "regional" or "global")
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15.0 #pstart# %start time [s] for calculating CF for P-picking
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60.0 #pstop# %end time [s] for calculating CF for P-picking
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-1.0 #sstart# %start time [s] relative to P-onset for calculating CF for S-picking
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7.0 #pstart# %start time [s] for calculating CF for P-picking
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16.0 #pstop# %end time [s] for calculating CF for P-picking
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-0.5 #sstart# %start time [s] relative to P-onset for calculating CF for S-picking
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10.0 #sstop# %end time [s] after P-onset for calculating CF for S-picking
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True #use_taup# %use estimated traveltimes from TauPy for calculating windows for CF
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False #use_taup# %use estimated traveltimes from TauPy for calculating windows for CF
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iasp91 #taup_model# %define TauPy model for traveltime estimation
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2.0 10.0 #bpz1# %lower/upper corner freq. of first band pass filter Z-comp. [Hz]
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2.0 12.0 #bpz2# %lower/upper corner freq. of second band pass filter Z-comp. [Hz]
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2.0 8.0 #bph1# %lower/upper corner freq. of first band pass filter H-comp. [Hz]
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2.0 10.0 #bph2# %lower/upper corner freq. of second band pass filter z-comp. [Hz]
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2.0 20.0 #bpz1# %lower/upper corner freq. of first band pass filter Z-comp. [Hz]
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2.0 30.0 #bpz2# %lower/upper corner freq. of second band pass filter Z-comp. [Hz]
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2.0 10.0 #bph1# %lower/upper corner freq. of first band pass filter H-comp. [Hz]
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2.0 15.0 #bph2# %lower/upper corner freq. of second band pass filter z-comp. [Hz]
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#special settings for calculating CF#
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%!!Edit the following only if you know what you are doing!!%
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#Z-component#
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HOS #algoP# %choose algorithm for P-onset determination (HOS, ARZ, or AR3)
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7.0 #tlta# %for HOS-/AR-AIC-picker, length of LTA window [s]
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4.0 #tlta# %for HOS-/AR-AIC-picker, length of LTA window [s]
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4 #hosorder# %for HOS-picker, order of Higher Order Statistics
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2 #Parorder# %for AR-picker, order of AR process of Z-component
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1.2 #tdet1z# %for AR-picker, length of AR determination window [s] for Z-component, 1st pick
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@ -59,12 +59,12 @@ HOS #algoP# %choose algo
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0.6 #tdet2z# %for AR-picker, length of AR determination window [s] for Z-component, 2nd pick
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0.2 #tpred2z# %for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick
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0.001 #addnoise# %add noise to seismogram for stable AR prediction
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3.0 0.1 0.5 1.0 #tsnrz# %for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]
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3.0 0.0 1.0 0.5 #tsnrz# %for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]
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3.0 #pickwinP# %for initial AIC pick, length of P-pick window [s]
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6.0 #Precalcwin# %for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)
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0.2 #aictsmooth# %for HOS/AR, take average of samples for smoothing of AIC-function [s]
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0.4 #aictsmooth# %for HOS/AR, take average of samples for smoothing of AIC-function [s]
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0.1 #tsmoothP# %for HOS/AR, take average of samples for smoothing CF [s]
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0.001 #ausP# %for HOS/AR, artificial uplift of samples (aus) of CF (P)
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0.4 #ausP# %for HOS/AR, artificial uplift of samples (aus) of CF (P)
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1.3 #nfacP# %for HOS/AR, noise factor for noise level determination (P)
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#H-components#
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ARH #algoS# %choose algorithm for S-onset determination (ARH or AR3)
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@ -75,7 +75,7 @@ ARH #algoS# %choose algo
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4 #Sarorder# %for AR-picker, order of AR process of H-components
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5.0 #Srecalcwin# %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)
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4.0 #pickwinS# %for initial AIC pick, length of S-pick window [s]
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2.0 0.3 1.5 1.0 #tsnrh# %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]
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2.0 0.2 1.5 1.0 #tsnrh# %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]
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1.0 #aictsmoothS# %for AIC-picker, take average of samples for smoothing of AIC-function [s]
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0.7 #tsmoothS# %for AR-picker, take average of samples for smoothing CF [s] (S)
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0.9 #ausS# %for HOS/AR, artificial uplift of samples (aus) of CF (S)
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@ -85,16 +85,16 @@ ARH #algoS# %choose algo
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2.0 #minFMSNR# %miniumum required SNR for first-motion determination
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0.2 #fmpickwin# %pick window around P onset for calculating zero crossings
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#quality assessment#
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0.02 0.04 0.08 0.16 #timeerrorsP# %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P
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0.04 0.08 0.16 0.32 #timeerrorsS# %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S
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0.04 0.08 0.16 0.32 #timeerrorsP# %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P
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0.05 0.10 0.20 0.40 #timeerrorsS# %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S
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0.8 #minAICPslope# %below this slope [counts/s] the initial P pick is rejected
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1.1 #minAICPSNR# %below this SNR the initial P pick is rejected
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1.0 #minAICSslope# %below this slope [counts/s] the initial S pick is rejected
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1.5 #minAICSSNR# %below this SNR the initial S pick is rejected
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1.0 #minsiglength# %length of signal part for which amplitudes must exceed noiselevel [s]
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1.0 #noisefactor# %noiselevel*noisefactor=threshold
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10.0 #minpercent# %required percentage of amplitudes exceeding threshold
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1.5 #zfac# %P-amplitude must exceed at least zfac times RMS-S amplitude
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6.0 #mdttolerance# %maximum allowed deviation of P picks from median [s]
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1.1 #noisefactor# %noiselevel*noisefactor=threshold
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50.0 #minpercent# %required percentage of amplitudes exceeding threshold
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1.1 #zfac# %P-amplitude must exceed at least zfac times RMS-S amplitude
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5.0 #mdttolerance# %maximum allowed deviation of P picks from median [s]
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1.0 #wdttolerance# %maximum allowed deviation from Wadati-diagram
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5.0 #jackfactor# %pick is removed if the variance of the subgroup with the pick removed is larger than the mean variance of all subgroups times safety factor
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2.0 #jackfactor# %pick is removed if the variance of the subgroup with the pick removed is larger than the mean variance of all subgroups times safety factor
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@ -240,12 +240,17 @@ class AICPicker(AutoPicker):
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return
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# calculate SNR from CF
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self.SNR = max(abs(self.Data[0].data[isignal])) / \
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max(abs(self.Data[0].data[inoise] - np.mean(self.Data[0].data[inoise])))
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abs(np.mean(self.Data[0].data[inoise]))
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# calculate slope from CF after initial pick
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# get slope window
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tslope = self.TSNR[3] # slope determination window
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islope = np.where((self.Tcf <= min([self.Pick + tslope, self.Tcf[-1]])) \
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& (self.Tcf >= self.Pick)) # TODO: put this in a seperate function like getsignalwin
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tsafety = self.TSNR[1] # safety gap, AIC is usually a little bit too late
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if tsafety >= 0:
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islope = np.where((self.Tcf <= min([self.Pick + tslope + tsafety, self.Tcf[-1]])) \
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& (self.Tcf >= self.Pick)) # TODO: put this in a seperate function like getsignalwin
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else:
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islope = np.where((self.Tcf <= min([self.Pick + tslope, self.Tcf[-1]])) \
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& (self.Tcf >= self.Pick + tsafety)) # TODO: put this in a seperate function like getsignalwin
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# find maximum within slope determination window
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# 'cause slope should be calculated up to first local minimum only!
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try:
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