[Bugfix] Take care that chosen window lengths fit to length of time series.
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@ -215,6 +215,8 @@ class LocalMagnitude(Magnitude):
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th = np.arange(0, len(sqH) * dt, dt)
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th = np.arange(0, len(sqH) * dt, dt)
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# get maximum peak within pick window
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# get maximum peak within pick window
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iwin = getsignalwin(th, t0 - stime, self.calc_win)
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iwin = getsignalwin(th, t0 - stime, self.calc_win)
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ii = min([iwin[len(iwin)-1], len(th)])
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iwin = iwin[0:ii]
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wapp = np.max(sqH[iwin])
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wapp = np.max(sqH[iwin])
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if self.verbose:
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if self.verbose:
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print("Determined Wood-Anderson peak-to-peak amplitude for station {0}: {1} "
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print("Determined Wood-Anderson peak-to-peak amplitude for station {0}: {1} "
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@ -212,6 +212,14 @@ class AICPicker(AutoPicker):
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self.Data[0].data = self.Data[0].data * 1000000
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self.Data[0].data = self.Data[0].data * 1000000
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# get signal window
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# get signal window
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isignal = getsignalwin(self.Tcf, self.Pick, self.TSNR[2])
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isignal = getsignalwin(self.Tcf, self.Pick, self.TSNR[2])
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ii = min([isignal[len(isignal)-1], len(self.Tcf)])
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isignal = isignal[0:ii]
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try:
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aic[isignal]
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except IndexError as e:
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msg = "Time series out of bounds! {}".format(e)
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print(msg)
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return
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# calculate SNR from CF
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# calculate SNR from CF
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self.SNR = max(abs(aic[isignal] - np.mean(aic[isignal]))) / \
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self.SNR = max(abs(aic[isignal] - np.mean(aic[isignal]))) / \
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max(abs(aic[inoise] - np.mean(aic[inoise])))
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max(abs(aic[inoise] - np.mean(aic[inoise])))
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