reformatting code to avoid mixing up whitespace and tabulator characters
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@ -14,6 +14,7 @@ import numpy as np
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from pylot.core.pick.Picker import *
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from pylot.core.pick.CharFuns import *
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def run_autopicking(wfstream, pickparam):
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"""
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:param: wfstream
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@ -81,22 +82,22 @@ def run_autopicking(wfstream, pickparam):
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# parameter to check for spuriously picked S onset
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zfac = pickparam.getParam('zfac')
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# initialize output
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Pweight = 4 # weight for P onset
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Sweight = 4 # weight for S onset
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FM = 'N' # first motion (polarity)
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SNRP = None # signal-to-noise ratio of P onset
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SNRPdB = None # signal-to-noise ratio of P onset [dB]
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SNRS = None # signal-to-noise ratio of S onset
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SNRSdB = None # signal-to-noise ratio of S onset [dB]
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mpickP = None # most likely P onset
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lpickP = None # latest possible P onset
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epickP = None # earliest possible P onset
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mpickS = None # most likely S onset
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lpickS = None # latest possible S onset
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epickS = None # earliest possible S onset
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Perror = None # symmetrized picking error P onset
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Serror = None # symmetrized picking error S onset
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# initialize output
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Pweight = 4 # weight for P onset
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Sweight = 4 # weight for S onset
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FM = 'N' # first motion (polarity)
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SNRP = None # signal-to-noise ratio of P onset
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SNRPdB = None # signal-to-noise ratio of P onset [dB]
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SNRS = None # signal-to-noise ratio of S onset
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SNRSdB = None # signal-to-noise ratio of S onset [dB]
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mpickP = None # most likely P onset
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lpickP = None # latest possible P onset
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epickP = None # earliest possible P onset
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mpickS = None # most likely S onset
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lpickS = None # latest possible S onset
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epickS = None # earliest possible S onset
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Perror = None # symmetrized picking error P onset
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Serror = None # symmetrized picking error S onset
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aicSflag = 0
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aicPflag = 0
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@ -161,42 +162,45 @@ def run_autopicking(wfstream, pickparam):
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aicpick = AICPicker(aiccf, tsnrz, pickwinP, iplot, None, tsmoothP)
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##############################################################
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if aicpick.getpick() is not None:
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# check signal length to detect spuriously picked noise peaks
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z_copy[0].data = tr_filt.data
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Pflag = checksignallength(z_copy, aicpick.getpick(), tsnrz, minsiglength, \
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nfacsl, minpercent, iplot)
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if Pflag == 1:
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# check for spuriously picked S onset
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# both horizontal traces needed
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if len(ndat) == 0 or len(edat) == 0:
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print 'One or more horizontal components missing!'
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print 'Skip control function checkZ4S.'
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else:
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# filter and taper horizontal traces
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trH1_filt = edat.copy()
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trH2_filt = ndat.copy()
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trH1_filt.filter('bandpass', freqmin=bph1[0], freqmax=bph1[1], \
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zerophase=False)
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trH2_filt.filter('bandpass', freqmin=bph1[0], freqmax=bph1[1], \
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zerophase=False)
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trH1_filt.taper(max_percentage=0.05, type='hann')
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trH2_filt.taper(max_percentage=0.05, type='hann')
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zne = z_copy
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zne += trH1_filt
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zne += trH2_filt
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Pflag = checkZ4S(zne, aicpick.getpick(), zfac, \
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tsnrz[3], iplot)
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if Pflag == 0:
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Pmarker = 'SinsteadP'
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Pweight = 9
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# check signal length to detect spuriously picked noise peaks
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z_copy[0].data = tr_filt.data
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Pflag = checksignallength(z_copy, aicpick.getpick(), tsnrz,
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minsiglength, \
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nfacsl, minpercent, iplot)
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if Pflag == 1:
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# check for spuriously picked S onset
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# both horizontal traces needed
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if len(ndat) == 0 or len(edat) == 0:
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print 'One or more horizontal components missing!'
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print 'Skip control function checkZ4S.'
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else:
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Pmarker = 'shortsignallength'
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# filter and taper horizontal traces
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trH1_filt = edat.copy()
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trH2_filt = ndat.copy()
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trH1_filt.filter('bandpass', freqmin=bph1[0],
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freqmax=bph1[1], \
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zerophase=False)
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trH2_filt.filter('bandpass', freqmin=bph1[0],
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freqmax=bph1[1], \
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zerophase=False)
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trH1_filt.taper(max_percentage=0.05, type='hann')
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trH2_filt.taper(max_percentage=0.05, type='hann')
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zne = z_copy
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zne += trH1_filt
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zne += trH2_filt
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Pflag = checkZ4S(zne, aicpick.getpick(), zfac, \
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tsnrz[3], iplot)
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if Pflag == 0:
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Pmarker = 'SinsteadP'
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Pweight = 9
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else:
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Pmarker = 'shortsignallength'
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Pweight = 9
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##############################################################
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# go on with processing if AIC onset passes quality control
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if (aicpick.getSlope() >= minAICPslope and
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aicpick.getSNR() >= minAICPSNR and
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Pflag == 1):
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aicpick.getSNR() >= minAICPSNR and
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Pflag == 1):
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aicPflag = 1
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print 'AIC P-pick passes quality control: Slope: %f, SNR: %f' % \
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(aicpick.getSlope(), aicpick.getSNR())
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@ -232,36 +236,37 @@ def run_autopicking(wfstream, pickparam):
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mpickP = refPpick.getpick()
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#############################################################
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if mpickP is not None:
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# quality assessment
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# get earliest and latest possible pick and symmetrized uncertainty
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[lpickP, epickP, Perror] = earllatepicker(z_copy, nfacP, tsnrz, mpickP, iplot)
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# quality assessment
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# get earliest and latest possible pick and symmetrized uncertainty
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[lpickP, epickP, Perror] = earllatepicker(z_copy, nfacP, tsnrz,
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mpickP, iplot)
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# get SNR
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[SNRP, SNRPdB, Pnoiselevel] = getSNR(z_copy, tsnrz, mpickP)
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# get SNR
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[SNRP, SNRPdB, Pnoiselevel] = getSNR(z_copy, tsnrz, mpickP)
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# weight P-onset using symmetric error
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if Perror <= timeerrorsP[0]:
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Pweight = 0
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elif timeerrorsP[0] < Perror <= timeerrorsP[1]:
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Pweight = 1
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elif timeerrorsP[1] < Perror <= timeerrorsP[2]:
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Pweight = 2
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elif timeerrorsP[2] < Perror <= timeerrorsP[3]:
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Pweight = 3
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elif Perror > timeerrorsP[3]:
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Pweight = 4
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# weight P-onset using symmetric error
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if Perror <= timeerrorsP[0]:
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Pweight = 0
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elif timeerrorsP[0] < Perror <= timeerrorsP[1]:
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Pweight = 1
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elif timeerrorsP[1] < Perror <= timeerrorsP[2]:
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Pweight = 2
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elif timeerrorsP[2] < Perror <= timeerrorsP[3]:
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Pweight = 3
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elif Perror > timeerrorsP[3]:
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Pweight = 4
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##############################################################
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# get first motion of P onset
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# certain quality required
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if Pweight <= minfmweight and SNRP >= minFMSNR:
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FM = fmpicker(zdat, z_copy, fmpickwin, mpickP, iplot)
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else:
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FM = 'N'
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##############################################################
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# get first motion of P onset
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# certain quality required
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if Pweight <= minfmweight and SNRP >= minFMSNR:
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FM = fmpicker(zdat, z_copy, fmpickwin, mpickP, iplot)
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else:
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FM = 'N'
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print 'run_autopicking: P-weight: %d, SNR: %f, SNR[dB]: %f, ' \
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'Polarity: %s' % (Pweight, SNRP, SNRPdB, FM)
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Sflag = 1
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print 'run_autopicking: P-weight: %d, SNR: %f, SNR[dB]: %f, ' \
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'Polarity: %s' % (Pweight, SNRP, SNRPdB, FM)
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Sflag = 1
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else:
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print 'Bad initial (AIC) P-pick, skip this onset!'
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@ -340,7 +345,7 @@ def run_autopicking(wfstream, pickparam):
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# class needs stream object => build it
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tr_arhaic = trH1_filt.copy()
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tr_arhaic.data = arhcf1.getCF()
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h_copy[0].data = tr_arhaic.data
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h_copy[0].data = tr_arhaic.data
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# calculate ARH-AIC-CF
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haiccf = AICcf(h_copy, cuttimesh) # instance of AICcf
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##############################################################
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@ -351,8 +356,8 @@ def run_autopicking(wfstream, pickparam):
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###############################################################
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# go on with processing if AIC onset passes quality control
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if (aicarhpick.getSlope() >= minAICSslope and
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aicarhpick.getSNR() >= minAICSSNR and
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aicarhpick.getpick() is not None):
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aicarhpick.getSNR() >= minAICSSNR and
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aicarhpick.getpick() is not None):
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aicSflag = 1
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print 'AIC S-pick passes quality control: Slope: %f, SNR: %f' \
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% (aicarhpick.getSlope(), aicarhpick.getSNR())
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@ -405,71 +410,73 @@ def run_autopicking(wfstream, pickparam):
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mpickS = refSpick.getpick()
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#############################################################
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if mpickS is not None:
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# quality assessment
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# get earliest and latest possible pick and symmetrized uncertainty
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h_copy[0].data = trH1_filt.data
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[lpickS1, epickS1, Serror1] = earllatepicker(h_copy, nfacS, tsnrh,
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mpickS, iplot)
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h_copy[0].data = trH2_filt.data
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[lpickS2, epickS2, Serror2] = earllatepicker(h_copy, nfacS, 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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# quality assessment
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# get earliest and latest possible pick and symmetrized uncertainty
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h_copy[0].data = trH1_filt.data
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[lpickS1, epickS1, Serror1] = 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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h_copy[0].data = trH2_filt.data
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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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# get SNR
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[SNRS, SNRSdB, Snoiselevel] = getSNR(h_copy, tsnrh, mpickS)
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# get SNR
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[SNRS, SNRSdB, Snoiselevel] = getSNR(h_copy, tsnrh, mpickS)
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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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# 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 'run_autopicking: S-weight: %d, SNR: %f, SNR[dB]: %f' % (
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Sweight, SNRS, SNRSdB)
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print 'run_autopicking: S-weight: %d, SNR: %f, SNR[dB]: %f' % (
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Sweight, SNRS, SNRSdB)
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else:
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print 'Bad initial (AIC) S-pick, skip this onset!'
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print 'AIC-SNR=', aicarhpick.getSNR(), \
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'AIC-Slope=', aicarhpick.getSlope()
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'AIC-Slope=', aicarhpick.getSlope()
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else:
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print 'run_autopicking: No horizontal component data available or ' \
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@ -525,7 +532,7 @@ def run_autopicking(wfstream, pickparam):
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plt.ylim([-1.5, 1.5])
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plt.ylabel('Normalized Counts')
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plt.suptitle(tr_filt.stats.starttime)
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if len(edat[0]) > 1 and len(ndat[0]) > 1 and Sflag == 1:
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# plot horizontal traces
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plt.subplot(3, 1, 2)
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@ -544,20 +551,25 @@ def run_autopicking(wfstream, pickparam):
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if aicSflag == 1:
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p23, = plt.plot(arhcf2.getTimeArray(),
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arhcf2.getCF() / max(arhcf2.getCF()), 'm')
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p24, = plt.plot([aicarhpick.getpick(), aicarhpick.getpick()],
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[-1, 1], 'g')
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p24, = plt.plot(
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[aicarhpick.getpick(), aicarhpick.getpick()],
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[-1, 1], 'g')
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plt.plot(
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[aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5],
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[aicarhpick.getpick() - 0.5,
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aicarhpick.getpick() + 0.5],
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[1, 1], 'g')
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plt.plot(
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[aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5],
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[aicarhpick.getpick() - 0.5,
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aicarhpick.getpick() + 0.5],
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[-1, -1], 'g')
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p25, = plt.plot([refSpick.getpick(), refSpick.getpick()],
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[-1.3, 1.3], 'g', linewidth=2)
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plt.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5],
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[1.3, 1.3], 'g', linewidth=2)
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plt.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5],
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[-1.3, -1.3], 'g', linewidth=2)
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plt.plot(
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[refSpick.getpick() - 0.5, refSpick.getpick() + 0.5],
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[1.3, 1.3], 'g', linewidth=2)
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plt.plot(
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[refSpick.getpick() - 0.5, refSpick.getpick() + 0.5],
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[-1.3, -1.3], 'g', linewidth=2)
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plt.plot([lpickS, lpickS], [-1.1, 1.1], 'g--')
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plt.plot([epickS, epickS], [-1.1, 1.1], 'g--')
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plt.legend([p21, p22, p23, p24, p25],
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@ -591,20 +603,25 @@ def run_autopicking(wfstream, pickparam):
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if aicSflag == 1:
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p23, = plt.plot(arhcf2.getTimeArray(),
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arhcf2.getCF() / max(arhcf2.getCF()), 'm')
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p24, = plt.plot([aicarhpick.getpick(), aicarhpick.getpick()],
|
||||
[-1, 1], 'g')
|
||||
p24, = plt.plot(
|
||||
[aicarhpick.getpick(), aicarhpick.getpick()],
|
||||
[-1, 1], 'g')
|
||||
plt.plot(
|
||||
[aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5],
|
||||
[aicarhpick.getpick() - 0.5,
|
||||
aicarhpick.getpick() + 0.5],
|
||||
[1, 1], 'g')
|
||||
plt.plot(
|
||||
[aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5],
|
||||
[aicarhpick.getpick() - 0.5,
|
||||
aicarhpick.getpick() + 0.5],
|
||||
[-1, -1], 'g')
|
||||
p25, = plt.plot([refSpick.getpick(), refSpick.getpick()],
|
||||
[-1.3, 1.3], 'g', linewidth=2)
|
||||
plt.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5],
|
||||
[1.3, 1.3], 'g', linewidth=2)
|
||||
plt.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5],
|
||||
[-1.3, -1.3], 'g', linewidth=2)
|
||||
[-1.3, 1.3], 'g', linewidth=2)
|
||||
plt.plot(
|
||||
[refSpick.getpick() - 0.5, refSpick.getpick() + 0.5],
|
||||
[1.3, 1.3], 'g', linewidth=2)
|
||||
plt.plot(
|
||||
[refSpick.getpick() - 0.5, refSpick.getpick() + 0.5],
|
||||
[-1.3, -1.3], 'g', linewidth=2)
|
||||
plt.plot([lpickS, lpickS], [-1.1, 1.1], 'g--')
|
||||
plt.plot([epickS, epickS], [-1.1, 1.1], 'g--')
|
||||
plt.legend([p21, p22, p23, p24, p25],
|
||||
@ -623,15 +640,15 @@ def run_autopicking(wfstream, pickparam):
|
||||
##########################################################################
|
||||
# calculate "real" onset times
|
||||
if mpickP is not None:
|
||||
lpickP = zdat[0].stats.starttime + lpickP
|
||||
epickP = zdat[0].stats.starttime + epickP
|
||||
mpickP = zdat[0].stats.starttime + mpickP
|
||||
lpickP = zdat[0].stats.starttime + lpickP
|
||||
epickP = zdat[0].stats.starttime + epickP
|
||||
mpickP = zdat[0].stats.starttime + mpickP
|
||||
|
||||
if mpickS is not None:
|
||||
lpickS = edat[0].stats.starttime + lpickS
|
||||
epickS = edat[0].stats.starttime + epickS
|
||||
mpickS = edat[0].stats.starttime + mpickS
|
||||
|
||||
lpickS = edat[0].stats.starttime + lpickS
|
||||
epickS = edat[0].stats.starttime + epickS
|
||||
mpickS = edat[0].stats.starttime + mpickS
|
||||
|
||||
# create dictionary
|
||||
# for P phase
|
||||
phase = 'P'
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user