Wood-Anderson peak-to-peak amplitude is now calculated even if S weight is 4. At least P pick must be confident, if S weight > 3 a larger window for getting maximum peak-to-peak amplitude is used.
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@ -507,7 +507,6 @@ def autopickstation(wfstream, pickparam):
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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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if Sweight < 4:
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# get Wood-Anderson peak-to-peak amplitude
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print "################################################"
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# initialize Data object
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@ -519,8 +518,15 @@ def autopickstation(wfstream, pickparam):
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cordat = data.restituteWFData(invdir, h_copy)
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# calculate WA-peak-to-peak amplitude
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# using subclass WApp of superclass Magnitude
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if Sweight < 4:
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wapp = WApp(cordat, mpickS, mpickP + sstop, iplot)
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Ao = wapp.getwapp()
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else:
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# use larger window for getting peak-to-peak amplitude
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# as the S pick is quite unsure
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wapp = WApp(cordat, mpickP, mpickP + sstop + \
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(0.5 * (mpickP + sstop)), iplot)
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Ao = wapp.getwapp()
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else:
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print 'Bad initial (AIC) S-pick, skipping this onset!'
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@ -541,7 +547,8 @@ def autopickstation(wfstream, pickparam):
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cordat = data.restituteWFData(invdir, h_copy)
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# calculate WA-peak-to-peak amplitude
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# using subclass WApp of superclass Magnitude
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wapp = WApp(cordat, mpickP, mpickP + sstop, iplot)
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wapp = WApp(cordat, mpickP, mpickP + sstop + (0.5 * (mpickP \
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+ sstop)), iplot)
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Ao = wapp.getwapp()
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else:
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