[change] fix legend locations to prevent them from bouncing on zoom
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8e59845558
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@ -330,7 +330,7 @@ def autopickstation(wfstream, pickparam, verbose=False,
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for ax in fig.axes:
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for ax in fig.axes:
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ax.vlines(pstart, ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed', label='P start')
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ax.vlines(pstart, ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed', label='P start')
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ax.vlines(pstop, ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed', label='P stop')
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ax.vlines(pstop, ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed', label='P stop')
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ax.legend()
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ax.legend(loc=1)
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##############################################################
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##############################################################
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if aicpick.getpick() is not None:
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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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# check signal length to detect spuriously picked noise peaks
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@ -872,7 +872,7 @@ def autopickstation(wfstream, pickparam, verbose=False,
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ax1.set_title('%s, %s, P Weight=%d' % (tr_filt.stats.station,
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ax1.set_title('%s, %s, P Weight=%d' % (tr_filt.stats.station,
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tr_filt.stats.channel,
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tr_filt.stats.channel,
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Pweight))
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Pweight))
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ax1.legend()
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ax1.legend(loc=1)
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ax1.set_yticks([])
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ax1.set_yticks([])
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ax1.set_ylim([-1.5, 1.5])
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ax1.set_ylim([-1.5, 1.5])
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ax1.set_ylabel('Normalized Counts')
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ax1.set_ylabel('Normalized Counts')
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@ -930,7 +930,7 @@ def autopickstation(wfstream, pickparam, verbose=False,
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else:
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else:
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ax2.set_title('%s, S Weight=%d, SNR=None, SNRdB=None' % (
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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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trH1_filt.stats.channel, Sweight))
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ax2.legend()
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ax2.legend(loc=1)
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ax2.set_yticks([])
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ax2.set_yticks([])
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ax2.set_ylim([-1.5, 1.5])
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ax2.set_ylim([-1.5, 1.5])
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ax2.set_ylabel('Normalized Counts')
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ax2.set_ylabel('Normalized Counts')
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@ -973,7 +973,7 @@ def autopickstation(wfstream, pickparam, verbose=False,
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[-1.3, -1.3], 'g', linewidth=2)
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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([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.plot([epickS, epickS], [-1.1, 1.1], 'g--', label='epp')
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ax3.legend()
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ax3.legend(loc=1)
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ax3.set_yticks([])
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ax3.set_yticks([])
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ax3.set_ylim([-1.5, 1.5])
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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_xlabel('Time [s] after %s' % tr_filt.stats.starttime)
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@ -272,7 +272,7 @@ class AICPicker(AutoPicker):
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x = self.Data[0].data
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x = self.Data[0].data
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ax.plot(self.Tcf, x / max(x), 'k', label='(HOS-/AR-) Data')
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ax.plot(self.Tcf, x / max(x), 'k', label='(HOS-/AR-) Data')
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ax.plot(self.Tcf, aicsmooth / max(aicsmooth), 'r', label='Smoothed AIC-CF')
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ax.plot(self.Tcf, aicsmooth / max(aicsmooth), 'r', label='Smoothed AIC-CF')
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ax.legend()
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ax.legend(loc=1)
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ax.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
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ax.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
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ax.set_yticks([])
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ax.set_yticks([])
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ax.set_title(self.Data[0].stats.station)
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ax.set_title(self.Data[0].stats.station)
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@ -313,7 +313,7 @@ class AICPicker(AutoPicker):
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ax1.plot([self.Pick, self.Pick], [-0.1, 0.5], 'b', linewidth=2, label='AIC-Pick')
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ax1.plot([self.Pick, self.Pick], [-0.1, 0.5], 'b', linewidth=2, label='AIC-Pick')
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ax1.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
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ax1.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
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ax1.set_yticks([])
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ax1.set_yticks([])
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ax1.legend()
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ax1.legend(loc=1)
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if self.Pick is not None:
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if self.Pick is not None:
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ax2 = fig.add_subplot(2, 1, 2, sharex=ax1)
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ax2 = fig.add_subplot(2, 1, 2, sharex=ax1)
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@ -336,7 +336,7 @@ class AICPicker(AutoPicker):
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ax2.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
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ax2.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
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ax2.set_ylabel('Counts')
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ax2.set_ylabel('Counts')
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ax2.set_yticks([])
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ax2.set_yticks([])
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ax2.legend()
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ax2.legend(loc=1)
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if plt_flag == 1:
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if plt_flag == 1:
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fig.show()
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fig.show()
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try: input()
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try: input()
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@ -480,7 +480,7 @@ class PragPicker(AutoPicker):
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ax.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
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ax.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
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ax.set_yticks([])
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ax.set_yticks([])
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ax.set_title(self.Data[0].stats.station)
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ax.set_title(self.Data[0].stats.station)
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ax.legend()
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ax.legend(loc=1)
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if plt_flag == 1:
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if plt_flag == 1:
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fig.show()
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fig.show()
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try: input()
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try: input()
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@ -150,7 +150,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
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ax.set_title(
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ax.set_title(
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'Earliest-/Latest Possible/Most Likely Pick & Symmetric Pick Error, %s' %
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'Earliest-/Latest Possible/Most Likely Pick & Symmetric Pick Error, %s' %
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X[0].stats.station)
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X[0].stats.station)
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ax.legend()
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ax.legend(loc=1)
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if plt_flag == 1:
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if plt_flag == 1:
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fig.show()
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fig.show()
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try: input()
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try: input()
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@ -330,7 +330,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
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ax1.plot(t[islope1], xraw[islope1], label='Slope Window')
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ax1.plot(t[islope1], xraw[islope1], label='Slope Window')
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ax1.plot(zc1, np.zeros(len(zc1)), '*g', markersize=14, label='Zero Crossings')
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ax1.plot(zc1, np.zeros(len(zc1)), '*g', markersize=14, label='Zero Crossings')
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ax1.plot(t[islope1], datafit1, '--g', linewidth=2)
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ax1.plot(t[islope1], datafit1, '--g', linewidth=2)
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ax1.legend()
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ax1.legend(loc=1)
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ax1.text(Pick + 0.02, max(xraw) / 2, '%s' % FM, fontsize=14)
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ax1.text(Pick + 0.02, max(xraw) / 2, '%s' % FM, fontsize=14)
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ax1.set_yticks([])
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ax1.set_yticks([])
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ax1.set_title('First-Motion Determination, %s, Unfiltered Data' % Xraw[
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ax1.set_title('First-Motion Determination, %s, Unfiltered Data' % Xraw[
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@ -678,7 +678,7 @@ def wadaticheck(pickdic, dttolerance, iplot=0, fig_dict=None):
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ax.plot(checkedPpicks, wdfit2, 'g', label='Wadati 2')
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ax.plot(checkedPpicks, wdfit2, 'g', label='Wadati 2')
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ax.set_title('Wadati-Diagram, %d S-P Times, Vp/Vs(raw)=%5.2f,' \
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ax.set_title('Wadati-Diagram, %d S-P Times, Vp/Vs(raw)=%5.2f,' \
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'Vp/Vs(checked)=%5.2f' % (len(SPtimes), vpvsr, cvpvsr))
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'Vp/Vs(checked)=%5.2f' % (len(SPtimes), vpvsr, cvpvsr))
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ax.legend()
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ax.legend(loc=1)
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else:
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else:
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ax.set_title('Wadati-Diagram, %d S-P Times' % len(SPtimes))
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ax.set_title('Wadati-Diagram, %d S-P Times' % len(SPtimes))
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@ -789,7 +789,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fi
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ax.plot([t[isignal[0]], t[isignal[len(isignal) - 1]]],
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ax.plot([t[isignal[0]], t[isignal[len(isignal) - 1]]],
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[minsiglevel, minsiglevel], 'g', linewidth=2, label='Minimum Signal Level')
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[minsiglevel, minsiglevel], 'g', linewidth=2, label='Minimum Signal Level')
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ax.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2, label='Onset')
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ax.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2, label='Onset')
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ax.legend()
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ax.legend(loc=1)
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ax.set_xlabel('Time [s] since %s' % X[0].stats.starttime)
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ax.set_xlabel('Time [s] since %s' % X[0].stats.starttime)
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ax.set_ylabel('Counts')
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ax.set_ylabel('Counts')
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ax.set_title('Check for Signal Length, Station %s' % X[0].stats.station)
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ax.set_title('Check for Signal Length, Station %s' % X[0].stats.station)
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@ -901,7 +901,7 @@ def checkPonsets(pickdic, dttolerance, jackfactor=5, iplot=0, fig_dict=None):
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ax.set_xlabel('Number of P Picks')
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ax.set_xlabel('Number of P Picks')
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ax.set_ylabel('Onset Time [s] from 1.1.1970')
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ax.set_ylabel('Onset Time [s] from 1.1.1970')
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ax.legend()
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ax.legend(loc=1)
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ax.set_title('Jackknifing and Median Tests on P Onsets')
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ax.set_title('Jackknifing and Median Tests on P Onsets')
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if plt_flag:
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if plt_flag:
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fig.show()
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fig.show()
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@ -1108,7 +1108,7 @@ def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None):
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ax.set_ylabel('Normalized Counts')
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ax.set_ylabel('Normalized Counts')
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ax.axvspan(pick, pick + checkwin, color='c', alpha=0.2,
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ax.axvspan(pick, pick + checkwin, color='c', alpha=0.2,
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lw=0)
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lw=0)
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ax.legend()
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ax.legend(loc=1)
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ax.set_xlabel('Time [s] since %s' % zdat[0].stats.starttime)
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ax.set_xlabel('Time [s] since %s' % zdat[0].stats.starttime)
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if plt_flag == 1:
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if plt_flag == 1:
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fig.show()
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fig.show()
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@ -272,7 +272,7 @@ class map_projection(QtGui.QWidget):
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for index, name in enumerate(self.station_names):
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for index, name in enumerate(self.station_names):
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self.annotations.append(self.main_ax.annotate(' %s' % name, xy=(self.x[index], self.y[index]),
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self.annotations.append(self.main_ax.annotate(' %s' % name, xy=(self.x[index], self.y[index]),
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fontsize='x-small', color='white', zorder=12))
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fontsize='x-small', color='white', zorder=12))
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self.legend = self.main_ax.legend()
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self.legend = self.main_ax.legend(loc=1)
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def add_cbar(self, label):
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def add_cbar(self, label):
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cbar = self.main_ax.figure.colorbar(self.sc_picked, fraction=0.025)
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cbar = self.main_ax.figure.colorbar(self.sc_picked, fraction=0.025)
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@ -1245,7 +1245,7 @@ class PickDlg(QDialog):
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self.get_arrivals(True)
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self.get_arrivals(True)
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ax = self.phaseplot.ax
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ax = self.phaseplot.ax
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self.arrivals.plot(ax=ax, show=False)
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self.arrivals.plot(ax=ax, show=False)
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ax.legend()
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ax.legend(loc=1)
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self.phaseplot.new = False
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self.phaseplot.new = False
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self.phaseplot.draw()
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self.phaseplot.draw()
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self.phaseplot.show()
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self.phaseplot.show()
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@ -2553,7 +2553,7 @@ class TuneAutopicker(QWidget):
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[y_bot, y_bot], linewidth=2, color='teal')
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[y_bot, y_bot], linewidth=2, color='teal')
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ax.plot([pick - 0.5, pick + 0.5],
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ax.plot([pick - 0.5, pick + 0.5],
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[y_top, y_top], linewidth=2, color='teal')
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[y_top, y_top], linewidth=2, color='teal')
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ax.legend()
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ax.legend(loc=1)
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def plot_manual_Spick_to_ax(self, ax, pick):
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def plot_manual_Spick_to_ax(self, ax, pick):
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y_top = 0.9 * ax.get_ylim()[1]
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y_top = 0.9 * ax.get_ylim()[1]
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@ -2564,7 +2564,7 @@ class TuneAutopicker(QWidget):
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[y_bot, y_bot], linewidth=2, color='magenta')
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[y_bot, y_bot], linewidth=2, color='magenta')
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ax.plot([pick - 0.5, pick + 0.5],
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ax.plot([pick - 0.5, pick + 0.5],
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[y_top, y_top], linewidth=2, color='magenta')
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[y_top, y_top], linewidth=2, color='magenta')
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ax.legend()
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ax.legend(loc=1)
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def fill_tabs(self, event=None, picked=False):
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def fill_tabs(self, event=None, picked=False):
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self.clear_all()
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self.clear_all()
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