can cope with stations without horizontal components now, removed dangerous try/except construct
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parent
f310afb4c6
commit
146ef7098c
14
PyLoT.py
14
PyLoT.py
@ -2440,12 +2440,14 @@ class MainWindow(QMainWindow):
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canvas.setZoomBorders2content()
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if self.tap.pylot_picks:
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station = self.tap.get_current_station()
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p_pick = self.tap.pylot_picks[station]['P']
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s_pick = self.tap.pylot_picks[station]['S']
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self.tap.pickDlg.autopicks['P_tuning'] = p_pick
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self.tap.pickDlg.autopicks['S_tuning'] = s_pick
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self.tap.pickDlg.drawPicks(phase='P_tuning', picktype='auto', picks=p_pick)
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self.tap.pickDlg.drawPicks(phase='S_tuning', picktype='auto', picks=s_pick)
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p_pick = self.tap.pylot_picks[station].get('P')
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if p_pick:
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self.tap.pickDlg.autopicks['P_tuning'] = p_pick
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self.tap.pickDlg.drawPicks(phase='P_tuning', picktype='auto', picks=p_pick)
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s_pick = self.tap.pylot_picks[station].get('S')
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if s_pick:
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self.tap.pickDlg.autopicks['S_tuning'] = s_pick
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self.tap.pickDlg.drawPicks(phase='S_tuning', picktype='auto', picks=s_pick)
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def autoPick(self):
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autosave = self.get_current_event_path()
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@ -8,6 +8,7 @@ function conglomerate utils.
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:author: MAGS2 EP3 working group / Ludger Kueperkoch
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"""
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import traceback
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import matplotlib.pyplot as plt
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import numpy as np
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@ -975,115 +976,114 @@ def autopickstation(wfstream, pickparam, verbose=False,
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ax1.set_ylim([-1.5, 1.5])
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ax1.set_ylabel('Normalized Counts')
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# fig.suptitle(tr_filt.stats.starttime)
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try:
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len(edat[0])
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except:
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edat = ndat
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try:
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len(ndat[0])
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except:
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ndat = edat
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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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ax2 = fig.add_subplot(3, 1, 2, sharex=ax1)
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th1data = np.arange(0,
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trH1_filt.stats.npts /
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trH1_filt.stats.sampling_rate,
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trH1_filt.stats.delta)
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# check equal length of arrays, sometimes they are different!?
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wfldiff = len(trH1_filt.data) - len(th1data)
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if wfldiff < 0:
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th1data = th1data[0:len(th1data) - abs(wfldiff)]
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ax2.plot(th1data, trH1_filt.data / max(trH1_filt.data), color=linecolor, linewidth=0.7, label='Data')
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if Pweight < 4:
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ax2.plot(arhcf1.getTimeArray(),
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arhcf1.getCF() / max(arhcf1.getCF()), 'b', label='CF1')
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if aicSflag == 1 and Sweight < 4:
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ax2.plot(arhcf2.getTimeArray(),
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arhcf2.getCF() / max(arhcf2.getCF()), 'm', label='CF2')
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ax2.plot(
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[aicarhpick.getpick(), aicarhpick.getpick()],
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[-1, 1], 'g', label='Initial S Onset')
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ax2.plot(
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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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ax2.plot(
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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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ax2.plot([refSpick.getpick(), refSpick.getpick()],
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[-1.3, 1.3], 'g', linewidth=2, label='Final S Pick')
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ax2.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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ax2.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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ax2.plot([lpickS, lpickS], [-1.1, 1.1], 'g--', label='lpp')
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ax2.plot([epickS, epickS], [-1.1, 1.1], 'g--', label='epp')
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ax2.set_title('%s, S Weight=%d, SNR=%7.2f, SNR[dB]=%7.2f' % (
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trH1_filt.stats.channel,
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Sweight, SNRS, SNRSdB))
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else:
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ax2.set_title('%s, S Weight=%d, SNR=None, SNRdB=None' % (
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trH1_filt.stats.channel, Sweight))
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ax2.legend(loc=1)
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ax2.set_yticks([])
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ax2.set_ylim([-1.5, 1.5])
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ax2.set_ylabel('Normalized Counts')
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# fig.suptitle(trH1_filt.stats.starttime)
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# only continue if one horizontal stream exists
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if (ndat or edat) and Sflag == 1:
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# mirror components in case one does not exist
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if not edat:
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edat = ndat
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if not ndat:
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ndat = edat
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if len(edat[0]) > 1 and len(ndat[0]) > 1:
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# plot horizontal traces
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ax2 = fig.add_subplot(3, 1, 2, sharex=ax1)
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th1data = np.arange(0,
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trH1_filt.stats.npts /
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trH1_filt.stats.sampling_rate,
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trH1_filt.stats.delta)
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# check equal length of arrays, sometimes they are different!?
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wfldiff = len(trH1_filt.data) - len(th1data)
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if wfldiff < 0:
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th1data = th1data[0:len(th1data) - abs(wfldiff)]
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ax2.plot(th1data, trH1_filt.data / max(trH1_filt.data), color=linecolor, linewidth=0.7, label='Data')
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if Pweight < 4:
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ax2.plot(arhcf1.getTimeArray(),
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arhcf1.getCF() / max(arhcf1.getCF()), 'b', label='CF1')
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if aicSflag == 1 and Sweight < 4:
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ax2.plot(arhcf2.getTimeArray(),
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arhcf2.getCF() / max(arhcf2.getCF()), 'm', label='CF2')
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ax2.plot(
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[aicarhpick.getpick(), aicarhpick.getpick()],
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[-1, 1], 'g', label='Initial S Onset')
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ax2.plot(
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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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ax2.plot(
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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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ax2.plot([refSpick.getpick(), refSpick.getpick()],
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[-1.3, 1.3], 'g', linewidth=2, label='Final S Pick')
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ax2.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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ax2.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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ax2.plot([lpickS, lpickS], [-1.1, 1.1], 'g--', label='lpp')
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ax2.plot([epickS, epickS], [-1.1, 1.1], 'g--', label='epp')
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ax2.set_title('%s, S Weight=%d, SNR=%7.2f, SNR[dB]=%7.2f' % (
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trH1_filt.stats.channel,
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Sweight, SNRS, SNRSdB))
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else:
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ax2.set_title('%s, S Weight=%d, SNR=None, SNRdB=None' % (
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trH1_filt.stats.channel, Sweight))
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ax2.legend(loc=1)
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ax2.set_yticks([])
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ax2.set_ylim([-1.5, 1.5])
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ax2.set_ylabel('Normalized Counts')
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# fig.suptitle(trH1_filt.stats.starttime)
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ax3 = fig.add_subplot(3, 1, 3, sharex=ax1)
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th2data = np.arange(0,
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trH2_filt.stats.npts /
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trH2_filt.stats.sampling_rate,
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trH2_filt.stats.delta)
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# check equal length of arrays, sometimes they are different!?
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wfldiff = len(trH2_filt.data) - len(th2data)
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if wfldiff < 0:
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th2data = th2data[0:len(th2data) - abs(wfldiff)]
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ax3.plot(th2data, trH2_filt.data / max(trH2_filt.data), color=linecolor, linewidth=0.7, label='Data')
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if Pweight < 4:
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p22, = ax3.plot(arhcf1.getTimeArray(),
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arhcf1.getCF() / max(arhcf1.getCF()), 'b', label='CF1')
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if aicSflag == 1:
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ax3.plot(arhcf2.getTimeArray(),
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arhcf2.getCF() / max(arhcf2.getCF()), 'm', label='CF2')
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ax3.plot(
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[aicarhpick.getpick(), aicarhpick.getpick()],
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[-1, 1], 'g', label='Initial S Onset')
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ax3.plot(
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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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ax3.plot(
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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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ax3.plot([refSpick.getpick(), refSpick.getpick()],
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[-1.3, 1.3], 'g', linewidth=2, label='Final S Pick')
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ax3.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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ax3.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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ax3.plot([lpickS, lpickS], [-1.1, 1.1], 'g--', label='lpp')
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ax3.plot([epickS, epickS], [-1.1, 1.1], 'g--', label='epp')
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ax3.legend(loc=1)
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ax3.set_yticks([])
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ax3.set_ylim([-1.5, 1.5])
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ax3.set_xlabel('Time [s] after %s' % tr_filt.stats.starttime)
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ax3.set_ylabel('Normalized Counts')
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ax3.set_title(trH2_filt.stats.channel)
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if plt_flag == 1:
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fig.show()
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try:
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input()
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except SyntaxError:
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pass
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plt.close(fig)
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ax3 = fig.add_subplot(3, 1, 3, sharex=ax1)
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th2data = np.arange(0,
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trH2_filt.stats.npts /
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trH2_filt.stats.sampling_rate,
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trH2_filt.stats.delta)
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# check equal length of arrays, sometimes they are different!?
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wfldiff = len(trH2_filt.data) - len(th2data)
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if wfldiff < 0:
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th2data = th2data[0:len(th2data) - abs(wfldiff)]
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ax3.plot(th2data, trH2_filt.data / max(trH2_filt.data), color=linecolor, linewidth=0.7, label='Data')
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if Pweight < 4:
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p22, = ax3.plot(arhcf1.getTimeArray(),
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arhcf1.getCF() / max(arhcf1.getCF()), 'b', label='CF1')
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if aicSflag == 1:
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ax3.plot(arhcf2.getTimeArray(),
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arhcf2.getCF() / max(arhcf2.getCF()), 'm', label='CF2')
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ax3.plot(
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[aicarhpick.getpick(), aicarhpick.getpick()],
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[-1, 1], 'g', label='Initial S Onset')
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ax3.plot(
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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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ax3.plot(
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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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ax3.plot([refSpick.getpick(), refSpick.getpick()],
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[-1.3, 1.3], 'g', linewidth=2, label='Final S Pick')
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ax3.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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ax3.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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ax3.plot([lpickS, lpickS], [-1.1, 1.1], 'g--', label='lpp')
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ax3.plot([epickS, epickS], [-1.1, 1.1], 'g--', label='epp')
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ax3.legend(loc=1)
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ax3.set_yticks([])
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ax3.set_ylim([-1.5, 1.5])
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ax3.set_xlabel('Time [s] after %s' % tr_filt.stats.starttime)
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ax3.set_ylabel('Normalized Counts')
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ax3.set_title(trH2_filt.stats.channel)
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if plt_flag == 1:
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fig.show()
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try:
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input()
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except SyntaxError:
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pass
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plt.close(fig)
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##########################################################################
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# calculate "real" onset times
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if lpickP is not None and lpickP == mpickP:
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@ -1101,12 +1101,22 @@ def autopickstation(wfstream, pickparam, verbose=False,
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epickP = zdat[0].stats.starttime - timeerrorsP[3]
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mpickP = zdat[0].stats.starttime
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# create dictionary
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# for P phase
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ccode = zdat[0].stats.channel
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ncode = zdat[0].stats.network
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ppick = dict(channel=ccode, network=ncode, lpp=lpickP, epp=epickP, mpp=mpickP, spe=Perror, snr=SNRP,
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snrdb=SNRPdB, weight=Pweight, fm=FM, w0=None, fc=None, Mo=None,
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Mw=None, picker=picker, marked=Pmarker)
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if edat:
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hdat = edat[0]
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elif ndat:
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hdat = ndat[0]
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else:
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return
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# no horizontal components given
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picks = dict(P=ppick)
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return picks
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if lpickS is not None and lpickS == mpickS:
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lpickS += hdat.stats.delta
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@ -1123,13 +1133,6 @@ def autopickstation(wfstream, pickparam, verbose=False,
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epickS = hdat.stats.starttime - timeerrorsS[3]
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mpickS = hdat.stats.starttime
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# create dictionary
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# for P phase
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ccode = zdat[0].stats.channel
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ncode = zdat[0].stats.network
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ppick = dict(channel=ccode, network=ncode, lpp=lpickP, epp=epickP, mpp=mpickP, spe=Perror, snr=SNRP,
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snrdb=SNRPdB, weight=Pweight, fm=FM, w0=None, fc=None, Mo=None,
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Mw=None, picker=picker, marked=Pmarker)
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# add S phase
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ccode = hdat.stats.channel
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ncode = hdat.stats.network
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Block a user