[add] transfer P picking routine to new function
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Darius Arnold
parent
58191e2d8f
commit
a68cb9b0b7
@ -404,6 +404,171 @@ class AutopickStation(object):
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else:
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Lc = self.p_params.pstop - self.p_params.pstop
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Lwf = self.ztrace.stats.endtime - self.ztrace.stats.starttime
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if Lwf < 0:
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print('autopickstation: empty trace! Return!')
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return
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Ldiff = Lwf - abs(Lc)
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if Ldiff < 0 or self.p_params.pstop <= self.p_params.pstart:
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msg = 'autopickstation: Cutting times are too large for actual waveform!\nUsing entire waveform instead!'
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self.vprint(msg)
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self.p_params.pstart = 0
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self.p_params.pstop = len(self.ztrace.data) * self.ztrace.stats.delta
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cuttimes = [self.p_params.pstart, self.p_params.pstop]
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if self.p_params.algoP == 'HOS':
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cf1 = HOScf(z_copy, cuttimes, self.p_params.tlta, self.p_params.hosorder)
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elif self.p_params.algoP == 'ARZ':
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cf1 = ARZcf(z_copy, cuttimes, self.p_params.tpred1z, self.p_params.Parorder, self.p_params.tdet1z,
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self.p_params.addnoise)
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else:
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cf1 = None
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assert isinstance(cf1, CharacteristicFunction), 'cf2 is not set ' \
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'correctly: maybe the algorithm name ({algoP}) is ' \
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'corrupted'.format(algoP=self.p_params.algoP)
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# AICcf needs stream object -> build it
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tr_aic = tr_filt.copy()
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tr_aic.data = cf1.getCF()
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z_copy[0].data = tr_aic.data
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aiccf = AICcf(z_copy, cuttimes)
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# get preliminary onset time from AIC-CF
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'aicFig')
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aicpick = AICPicker(aiccf, self.p_params.tsnrz, self.p_params.pickwinP, self.iplot,
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Tsmooth=self.p_params.aictsmooth, fig=fig, linecolor=linecolor,
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checkwindow=self.p_params.checkwindowP, minfactor=self.p_params.minfactorP)
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# add pstart and pstop to aic plot
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if fig:
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for ax in fig.axes:
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ax.vlines(self.p_params.pstart, ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed', label='P start')
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ax.vlines(self.p_params.pstop, ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed', label='P stop')
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ax.legend(loc=1)
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fig, linecolor = get_fig_from_figdict(self.figdict, 'slength')
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if aicpick.getpick() is not None:
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z_copy[0].data = tr_filt.data
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zne = z_copy
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if len(self.nstream) == 0 or len(self.estream) == 0:
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msg = 'One or more horizontal component(s) missing!\n' \
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'Signal length only checked on vertical component!\n' \
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'Decreasing minsiglengh from {0} to {1}' \
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.format(self.signal_length_params.minsiglength, self.signal_length_params.minsiglength/2)
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self.vprint(msg)
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minsiglength = self.signal_length_params.minsiglength/2
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else:
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trH1_filt, _ = self.prepare_wfstream(self.estream, freqmin=self.s_params.bph1[0], freqmax=self.s_params.bph1[1])
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trH2_filt, _ = self.prepare_wfstream(self.nstream, freqmin=self.s_params.bph1[0], freqmax=self.s_params.bph1[1])
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zne += trH1_filt
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zne += trH2_filt
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minsiglength = self.signal_length_params.minsiglength
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Pflag = checksignallength(zne, aicpick.getpick(), self.p_params.tsnrz,
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minsiglength,
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self.signal_length_params.noisefactor,
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self.signal_length_params.minpercent, self.iplot, fig, linecolor)
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if Pflag == 0:
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Pmarker = 'shortsignallength'
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Pweight = 9
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if Pflag == 1:
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if len(self.nstream) == 0 or len(self.estream) == 0:
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msg = 'One or more horizontal components missing!\n' \
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'Skipping control function checkZ4S.'
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self.vprint(msg)
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else:
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if self.iplot > 1:
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'checkZ4s')
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Pflag = checkZ4S(zne, aicpick.getpick(), self.s_params.zfac, self.p_params.tsnrz[2], self.iplot, fig, linecolor)
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if Pflag == 0:
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Pmarker = 'SinsteadP'
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Pweight = 9
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# go on with processing if AIC onset passes quality control
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slope = aicpick.getSlope()
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if not slope: slope = 0
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if slope >= self.p_params.minAICPslope and aicpick.getSNR() >= self.p_params.minAICPSNR and Pflag == 1:
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aicPflag = 1
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msg = 'AIC P-pick passes quality control: Slope: {0} counts/s, ' \
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'SNR: {1}\nGo on with refined picking ...\n' \
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'autopickstation: re-filtering vertical trace ' \
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'...'.format(aicpick.getSlope(), aicpick.getSNR())
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self.vprint(msg)
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# refilter waveform with larger bandpass
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z_copy, tr_filt = self.prepare_wfstream(self.zstream, freqmin=self.p_params.bpz2[0])
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cuttimes2 = [round(max([aicpick.getpick() - self.p_params.Precalcwin, 0])),
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round(min([len(self.ztrace.data) * self.ztrace.stats.delta,
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aicpick.getpick() + self.p_params.Precalcwin]))]
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if self.p_params.algoP == 'HOS':
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cf2 = HOScf(z_copy, cuttimes2, self.p_params.tlta, self.p_params.hosorder)
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elif self.p_params.algoP == 'ARZ':
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cf2 = ARZcf(z_copy, cuttimes2, self.p_params.tpred1z, self.p_params.Parorder, self.p_params.tdet1z, self.p_params.addnoise)
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else:
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cf2 = None
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# get refined onset time from CF2
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assert isinstance(cf2, CharacteristicFunction), 'cf2 is not set ' \
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'correctly: maybe the algorithm name ({algoP}) is ' \
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'corrupted'.format(algoP=self.p_params.algoP)
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'refPpick')
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refPpick = PragPicker(cf2, self.p_params.tsnrz, self.p_params.pickwinP, self.iplot, self.p_params.ausP,
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self.p_params.tsmoothP, aicpick.getpick(), fig, linecolor,
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checkwindow=self.p_params.checkWindowP, minfactor=self.p_params.minfactorP)
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mpickP = refPpick.getpick()
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if mpickP is not None:
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# quality assessment, get earliest/latest pick and symmetrized uncertainty
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'el_Ppick')
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epickP, lpickP, Perror = earllatepicker(z_copy, self.p_params.nfacP, self.p_params.tsnrz, mpickP,
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self.iplot, fig=fig, linecolor=linecolor)
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SNRP, SNRPdB, Pnoiselevel = getSNR(z_copy, self.p_params.tsnrz, mpickP)
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# weight P-onset using symmetric error
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#todo shorter expression for this
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if Perror is None:
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Pweight = 4
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else:
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if Perror <= self.p_params.timeerrorsP[0]:
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Pweight = 0
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elif self.p_params.timeerrorsP[0] < Perror <= self.p_params.timeerrorsP[1]:
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Pweight = 1
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elif self.p_params.timeerrorsP[1] < Perror <= self.p_params.timeerrorsP[2]:
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Pweight = 2
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elif self.p_params.timeerrorsP[2] < Perror <= self.p_params.timeerrorsP[3]:
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Pweight = 3
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elif Perror > self.p_params.timeerrorsP[3]:
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Pweight = 4
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if Pweight <= self.first_motion_params.minfmweight and SNRP >= self.first_motion_params.minFMSSNR:
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'fm_picker')
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FM = fmpicker(self.zstream, z_copy, self.first_motion_params.fmpickwin, mpickP, self.iplot,
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fig, linecolor)
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else:
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FM = 'N'
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msg = "autopickstation: P-weight: {0}, " \
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"SNR: {1}, SNR[dB]: {2}, Polarity: {3}".format(Pweight, SNRP, SNRPdB, FM)
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print(msg)
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msg = 'autopickstation: Refined P-Pick: {} s | P-Error: {} s'.format(mpickP, Perror)
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print(msg)
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Sflag = 1
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else:
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msg = 'Bad initial (AIC) P-pick, skipping this onset!\n' \
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'AIC-SNR={0}, AIC-Slope={1}counts/s\n' \
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'(min. AIC-SNR={2}, ' \
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'min. AIC-Slope={3}counts/s)'.format(aicpick.getSNR(), aicpick.getSlope(),
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self.p_params.minAICPSNR, self.p_params.minAICPslope)
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self.vprint(msg)
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Sflag = 0
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def get_fig_from_figdict(figdict, figkey):
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"""
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:param figdict:
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:type figdict: dict
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:param figkey:
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:type figkey: str
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:return:
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:rtype:
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"""
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fig = figdict.get(figkey, None)
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linecolor = figdict.get('plot_style', 'k')
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linecolor = linecolor['linecolor']['rgba_mpl']
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return fig, linecolor
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def autopickstation(wfstream, pickparam, verbose=False,
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