Merge branch 'develop' of ariadne.geophysik.ruhr-uni-bochum.de:/data/git/pylot into develop
This commit is contained in:
commit
ae21c9a149
@ -84,6 +84,7 @@ def autoPyLoT(inputfile):
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ttpat = parameter.getParam('ttpatter')
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# pattern of NLLoc-output file
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nllocoutpatter = parameter.getParam('outpatter')
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maxnumit = 3 # maximum number of iterations for re-picking
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else:
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locflag = 0
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print (" !!! ")
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@ -133,7 +134,6 @@ def autoPyLoT(inputfile):
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else:
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# get theoretical P-onset times from NLLoc-location file
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locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout)
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maxnumit = 3 # maximum number of iterations
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if len(glob.glob(locsearch)) > 0:
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# get latest file if several are available
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nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
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@ -213,8 +213,6 @@ def autoPyLoT(inputfile):
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else:
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# get theoretical P-onset times from NLLoc-location file
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locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout)
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nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
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maxnumit = 3 # maximum number of iterations
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if len(glob.glob(locsearch)) > 0:
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# get latest file if several are available
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nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
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@ -7,7 +7,7 @@
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/DATA/Insheim #rootpath# %project path
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EVENT_DATA/LOCAL #datapath# %data path
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2015.10_Insheim #database# %name of data base
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e0011.280.15 #eventID# %event ID for single event processing
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#eventID# %event ID for single event processing
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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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0 #iplot# %flag for plotting: 0 none, 1 partly, >1 everything
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@ -42,7 +42,7 @@ AUTOFOCMEC_AIC_HOS4_ARH.in #focmecin# %name of focmec input file co
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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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12.0 #sstop# %end time [s] after 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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2 20 #bpz1# %lower/upper corner freq. of first band pass filter Z-comp. [Hz]
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2 30 #bpz2# %lower/upper corner freq. of second band pass filter Z-comp. [Hz]
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2 15 #bph1# %lower/upper corner freq. of first band pass filter H-comp. [Hz]
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@ -74,13 +74,12 @@ ARH #algoS# %choose algorithm for S-onset
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0.6 #tdet2h# %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick
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0.3 #tpred2h# %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick
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4 #Sarorder# %for AR-picker, order of AR process of H-components
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6.0 #Srecalcwin# %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)
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5.0 #Srecalcwin# %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)
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3.0 #pickwinS# %for initial AIC pick, length of S-pick window [s]
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2 0.2 1.5 0.5 #tsnrh# %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
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0.05 #aictsmoothS# %for AIC-picker, take average of samples for smoothing of AIC-function [s]
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0.02 #tsmoothS# %for AR-picker, take average of samples for smoothing CF [s] (S)
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0.2 #pepsS# %for AR-picker, artificial uplift of samples of CF (S)
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0.4 #ausS# %for HOS/AR, artificial uplift of samples (aus) of CF (S)
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0.5 #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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1.5 #nfacS# %for AR-picker, noise factor for noise level determination (S)
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%first-motion picker%
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1 #minfmweight# %minimum required P weight for first-motion determination
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@ -90,9 +89,9 @@ ARH #algoS# %choose algorithm for S-onset
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#inital AIC onset#
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0.01 0.02 0.04 0.08 #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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10 #minAICPslope# %below this slope [counts/s] the initial P pick is rejected
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4 #minAICPslope# %below this slope [counts/s] the initial P pick is rejected
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1.2 #minAICPSNR# %below this SNR the initial P pick is rejected
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3 #minAICSslope# %below this slope [counts/s] the initial S pick is rejected
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2 #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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#check duration of signal using envelope function#
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4 #minsiglength# %minimum required length of signal [s]
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@ -364,7 +364,7 @@ class PragPicker(AutoPicking):
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break
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# now decide which pick: left or right?
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if flagpick_l > 0 and flagpick_r > 0 and cfpick_l <= cfpick_r:
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if flagpick_l > 0 and flagpick_r > 0 and cfpick_l <= 3 * cfpick_r:
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self.Pick = pick_l
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pickflag = 1
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elif flagpick_l > 0 and flagpick_r > 0 and cfpick_l >= cfpick_r:
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@ -500,58 +500,60 @@ def autopickstation(wfstream, pickparam):
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[lpickS2, epickS2, Serror2] = earllatepicker(h_copy, nfacS,
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tsnrh,
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mpickS, iplot)
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if algoS == 'ARH':
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# get earliest pick of both earliest possible picks
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epick = [epickS1, epickS2]
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lpick = [lpickS1, lpickS2]
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pickerr = [Serror1, Serror2]
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if epickS1 == None and epickS2 is not None:
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ipick = 1
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elif epickS1 is not None and epickS2 == None:
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ipick = 0
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elif epickS1 is not None and epickS2 is not None:
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ipick = np.argmin([epickS1, epickS2])
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elif algoS == 'AR3':
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[lpickS3, epickS3, Serror3] = earllatepicker(h_copy, nfacS,
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tsnrh,
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mpickS, iplot)
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# get earliest pick of all three picks
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epick = [epickS1, epickS2, epickS3]
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lpick = [lpickS1, lpickS2, lpickS3]
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pickerr = [Serror1, Serror2, Serror3]
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if epickS1 == None and epickS2 is not None \
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and epickS3 is not None:
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ipick = np.argmin([epickS2, epickS3])
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elif epickS1 is not None and epickS2 == None \
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and epickS3 is not None:
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ipick = np.argmin([epickS2, epickS3])
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elif epickS1 is not None and epickS2 is not None \
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and epickS3 == None:
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ipick = np.argmin([epickS1, epickS2])
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elif epickS1 is not None and epickS2 is not None \
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and epickS3 is not None:
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ipick = np.argmin([epickS1, epickS2, epickS3])
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epickS = epick[ipick]
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lpickS = lpick[ipick]
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Serror = pickerr[ipick]
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if epickS1 is not None and epickS2 is not None:
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if algoS == 'ARH':
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# get earliest pick of both earliest possible picks
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epick = [epickS1, epickS2]
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lpick = [lpickS1, lpickS2]
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pickerr = [Serror1, Serror2]
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if epickS1 == None and epickS2 is not None:
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ipick = 1
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elif epickS1 is not None and epickS2 == None:
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ipick = 0
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elif epickS1 is not None and epickS2 is not None:
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ipick = np.argmin([epickS1, epickS2])
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elif algoS == 'AR3':
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[lpickS3, epickS3, Serror3] = earllatepicker(h_copy, nfacS,
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tsnrh,
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mpickS, iplot)
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# get earliest pick of all three picks
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epick = [epickS1, epickS2, epickS3]
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lpick = [lpickS1, lpickS2, lpickS3]
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pickerr = [Serror1, Serror2, Serror3]
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if epickS1 == None and epickS2 is not None \
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and epickS3 is not None:
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ipick = np.argmin([epickS2, epickS3])
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elif epickS1 is not None and epickS2 == None \
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and epickS3 is not None:
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ipick = np.argmin([epickS2, epickS3])
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elif epickS1 is not None and epickS2 is not None \
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and epickS3 == None:
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ipick = np.argmin([epickS1, epickS2])
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elif epickS1 is not None and epickS2 is not None \
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and epickS3 is not None:
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ipick = np.argmin([epickS1, epickS2, epickS3])
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# get SNR
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[SNRS, SNRSdB, Snoiselevel] = getSNR(h_copy, tsnrh, mpickS)
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epickS = epick[ipick]
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lpickS = lpick[ipick]
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Serror = pickerr[ipick]
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# weight S-onset using symmetric error
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if Serror <= timeerrorsS[0]:
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Sweight = 0
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elif timeerrorsS[0] < Serror <= timeerrorsS[1]:
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Sweight = 1
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elif Perror > timeerrorsS[1] and Serror <= timeerrorsS[2]:
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Sweight = 2
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elif timeerrorsS[2] < Serror <= timeerrorsS[3]:
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Sweight = 3
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elif Serror > timeerrorsS[3]:
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Sweight = 4
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# get SNR
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[SNRS, SNRSdB, Snoiselevel] = getSNR(h_copy, tsnrh, mpickS)
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print 'autopickstation: S-weight: %d, SNR: %f, SNR[dB]: %f' % (
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Sweight, SNRS, SNRSdB)
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# weight S-onset using symmetric error
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if Serror <= timeerrorsS[0]:
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Sweight = 0
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elif timeerrorsS[0] < Serror <= timeerrorsS[1]:
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Sweight = 1
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elif Perror > timeerrorsS[1] and Serror <= timeerrorsS[2]:
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Sweight = 2
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elif timeerrorsS[2] < Serror <= timeerrorsS[3]:
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Sweight = 3
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elif Serror > timeerrorsS[3]:
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Sweight = 4
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print 'autopickstation: S-weight: %d, SNR: %f, SNR[dB]: %f' % (
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Sweight, SNRS, SNRSdB)
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##################################################################
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# get Wood-Anderson peak-to-peak amplitude
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print "################################################"
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