Add S phase picking
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Darius Arnold
parent
d4033eca08
commit
e3f7840d9e
@ -574,6 +574,205 @@ class AutopickStation(object):
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self.p_params.minAICPSNR, self.p_params.minAICPslope)
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self.p_params.minAICPSNR, self.p_params.minAICPslope)
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self.vprint(msg)
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self.vprint(msg)
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Sflag = 0
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Sflag = 0
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def pick_s_phase(self):
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def check_existence_ne_traces():
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"""
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Checks if both N and E stream contain traces and copy over the trace to the missing stream if only
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one trace is missing
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:rtype: None
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:raises:
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MissingTraceException when both traces are missing
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"""
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# check existence of vertical traces #Maybe do this in __init__?
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nstream_exists, estream_exists = bool(len(self.nstream)), bool(len(self.estream))
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if not all((nstream_exists, estream_exists)):
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msg = 'Go on picking S onset ...\n' \
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'##################################################\n' \
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'Only one horizontal component available!\n' \
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'ARH prediction requires at least 2 components!\n' \
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'Copying existing horizontal component ...'
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self.vprint(msg)
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if estream_exists == 0:
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self.estream = self.nstream
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elif nstream_exists == 0:
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self.nstream = self.estream
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else:
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raise MissingTraceException("N and E stream missing, can't pick S phase.")
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#check_existence_ne_traces()
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# determine time window for calculating CF after P onset
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start = round(max(self.p_results.mpickP + self.s_params.sstart, 0))
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stop = round(min([
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self.p_results.mpickP + self.s_params.sstop,
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self.etrace.stats.endtime - self.etrace.stats.starttime,
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self.ntrace.stats.endtime - self.ntrace.stats.starttime
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]))
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cuttimesh = (start, stop)
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if cuttimesh[1] <= cuttimesh[0]:
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pickSonset = False
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raise PickingFailedException('Cut window for horizontal phases too small! Will not pick S onsets.')
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# prepare traces for picking by filtering, taper
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if self.s_params.algoS == 'ARH':
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hdat = self.nstream.copy() + self.estream.copy()
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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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h_copy = hdat.copy()
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h_copy[0].data = trH1_filt.data
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h_copy[1].data = trH2_filt.data
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if self.s_params.algoS == 'AR3':
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hdat = self.zstream.copy() + self.estream.copy() + self.nstream.copy()
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trH1_filt, _ = self.prepare_wfstream(self.zstream, freqmin=self.s_params.bph1[0], freqmax=self.s_params.bph1[1])
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trH2_filt, _ = self.prepare_wfstream(self.estream, freqmin=self.s_params.bph1[0], freqmax=self.s_params.bph1[1])
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trH3_filt, _ = self.prepare_wfstream(self.nstream, freqmin=self.s_params.bph1[0], freqmax=self.s_params.bph1[1])
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h_copy = hdat.copy()
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h_copy[0].data = trH1_filt.data
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h_copy[1].data = trH2_filt.data
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h_copy[2].data = trH3_filt.data
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# calculate inital CF based on autoregression
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if self.s_params.algoS == 'ARH':
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arhcf1 = ARHcf(h_copy, cuttimesh, self.s_params.tpred1h, self.s_params.Sarorder, self.s_params.tdet1h, self.p_params.addnoise)
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elif self.s_params.algoS == 'AR3':
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arhcf1 = AR3Ccf(h_copy, cuttimesh, self.s_params.tpred1h, self.s_params.Sarorder, self.s_params.tdet1h, self.p_params.addnoise)
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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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# calculate AIC cf
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haiccf = AICcf(h_copy, cuttimesh)
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# get preliminary onset time from AIC cf
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'aicARHfig')
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aicarhpick = AICPicker(haiccf, self.s_params.tsnrh, self.s_params.pickwinS, self.iplot, Tsmooth=self.s_params.aictsmoothS, fig=fig, linecolor=linecolor)
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# go on with processing if AIC onset passes quality control
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slope = aicarhpick.getSlope()
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if not slope:
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slope = 0
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if slope >= self.s_params.minAICSslope and aicarhpick.getSNR() >= self.s_params.minAICSSNR and aicarhpick.getpick() is not None:
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aicSflag = 1
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msg = 'AIC S-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 horizontal traces ' \
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'...'.format(aicarhpick.getSlope(), aicarhpick.getSNR())
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self.vprint(msg)
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# recalculate cf from refiltered trace in vicinity of initial onset
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start = round(aicarhpick.getpick() - self.s_params.Srecalcwin)
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stop = round(aicarhpick.getpick() + self.s_params.Srecalcwin)
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cuttimesh2 = (start, stop)
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# refilter waveform with larger bandpass
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if self.s_params.algoS == 'ARH':
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trH1_filt, _ = self.prepare_wfstream(self.estream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
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trH2_filt, _ = self.prepare_wfstream(self.nstream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
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h_copy = hdat.copy()
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h_copy[0].data = trH1_filt.data
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h_copy[1].data = trH2_filt.data
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elif self.s_params.algoS == 'AR3':
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trH1_filt, _ = self.prepare_wfstream(self.zstream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
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trH2_filt, _ = self.prepare_wfstream(self.estream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
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trH3_filt, _ = self.prepare_wfstream(self.nstream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
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h_copy = hdat.copy()
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h_copy[0].data = trH1_filt.data
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h_copy[1].data = trH2_filt.data
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h_copy[2].data = trH3_filt.data
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# calculate second cd
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if self.s_params.algoS == 'ARH':
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arhcf2 = ARHcf(h_copy, cuttimesh2, self.s_params.tpred2h, self.s_params.Sarorder, self.s_params.tdet2h, self.p_params.addnoise)
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elif self.s_params.algoS == 'AR3':
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arhcf2 = AR3Ccf(h_copy, cuttimesh2, self.s_params.tpred2h, self.s_params.Sarorder, self.s_params.tdet2h, self.p_params.addnoise)
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# get refined onset time from CF2
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'refSpick')
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refSpick = PragPicker(arhcf2, self.s_params.tsnrh, self.s_params.pickwinS, self.iplot, self.s_params.ausS, self.s_params.tsmoothS, aicarhpick.getpick(), fig, linecolor)
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self.s_results.mpickS = refSpick.getpick()
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if self.s_results.mpickS is not None:
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# quality assessment
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# get earliest/latest possible pick and symmetrized uncertainty
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h_copy[0].data = trH1_filt.data
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if self.iplot:
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'el_Slpick')
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epickS1, lpickS1, Serror1 = earllatepicker(h_copy, self.s_params.nfacS, self.s_params.tsnrh, self.s_results.mpickS, self.iplot, fig=fig, linecolor=linecolor)
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h_copy[0].data = trH2_filt.data
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if self.iplot:
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'el_S2pick')
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else:
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# why is it set to empty here? DA
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linecolor = ''
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epickS2, lpickS2, Serror2 = earllatepicker(h_copy, self.s_params.nfacS, self.s_params.tsnrh, self.s_results.mpickS, self.iplot, fig=fig, linecolor=linecolor)
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if epickS1 is not None and epickS2 is not None:
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if self.s_params.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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ipick = np.argmin(epick)
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if self.s_params.algoS == 'AR3':
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epickS3, lpickS3, Serror3 = earllatepicker(h_copy, self.s_params.nfacS, self.s_params.tsnrh, self.s_results.mpickS, self.iplot)
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# get earliest 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 epickS3 is not None:
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ipick = np.argmin(epick)
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else:
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ipick = np.argmin([epickS1, epickS2])
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self.s_results.epickS = epick[ipick]
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self.s_results.lpickS = lpick[ipick]
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self.s_results.Serror = pickerr[ipick]
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msg = 'autopickstation: Refined S-Pick: {} s | S-Error: {} s'.format(self.s_results.mpickS, self.s_results.Serror)
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print(msg)
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# get SNR
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self.s_results.SNRS, self.s_results.SNRSdB, self.s_results.Snoiselevel = getSNR(h_copy, self.s_params.tsnrh, self.s_results.mpickS)
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self.s_results.Sweight = get_quality_class(self.s_results.Serror, self.s_params.timeerrorsS)
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print('autopickstation: S-weight: {0}, SNR: {1}, '
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'SNR[dB]: {2}\n'
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'##################################################'
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''.format(self.s_results.Sweight, self.s_results.SNRS, self.s_results.SNRSdB))
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else:
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print('autopickstation: No horizontal component data available or '
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'bad P onset, skipping S picking!')
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### plotting ###
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# TODO finish converting the plotting code
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if self.iplot > 0:
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# plot vertical trace
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if self.fig_dict is None:
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fig = plt.figure()
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plt_flag = 1
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linecolor = 'k'
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else:
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fig, linecolor = get_fig_from_figdict(self.fig_dict, 'mainFig')
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fig._tight = True
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ax1 = fig.add_subplot(311)
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# create time axis
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tdata = np.linspace(start=0., stop=self.ztrace.stats.npts*self.tr_filt_z.stats.delta, num=self.tr_filt_z.stats.npts)
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# plot filtered waveform of z trace
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ax1.plot(tdata, self.tr_filt_z.data / max(self.tr_filt_z.data), color=linecolor, linewidth=0.7, label='Data')
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if self.p_results.Pweight < 4:
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# plot first HOS/ARZ cf of z trace
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ax1.plot(self.cf1.getTimeArray(), self.cf1.getCF / max(self.cf1.getCF()), color='b', label='CF1')
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if self.p_results.aicPflag == 1:
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ax1.plot(self.cf2.getTimeArray(), self.cf2.getCF() / max(self.cf2.getCF()), color='m', label='CF2')
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ax1.plot([self.p_results.aicpick.getpick(), self.p_results.aicpick.getpick()], [-1, 1], 'r', label='Initial P Onset')
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def get_fig_from_figdict(figdict, figkey):
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def get_fig_from_figdict(figdict, figkey):
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