Marginal changes.
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@ -192,7 +192,7 @@ class WApp(Magnitude):
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self.wapp = np.max(sqH[iwin])
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self.wapp = np.max(sqH[iwin])
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print ("Determined Wood-Anderson peak-to-peak amplitude: %f mm") % self.wapp
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print ("Determined Wood-Anderson peak-to-peak amplitude: %f mm") % self.wapp
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if self.getiplot() > 1:
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if self.getiplot() == 0:
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stream.plot()
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stream.plot()
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f = plt.figure(2)
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f = plt.figure(2)
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plt.plot(th, sqH)
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plt.plot(th, sqH)
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@ -468,7 +468,7 @@ def calcsourcespec(wfstream, onset, metadata, vp, delta, azimuth, incidence,
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except TypeError as er:
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except TypeError as er:
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raise TypeError('''{0}'''.format(er))
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raise TypeError('''{0}'''.format(er))
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if iplot > 1:
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if iplot == 0:
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f1 = plt.figure()
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f1 = plt.figure()
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tLdat = np.arange(0, len(Ldat) * zdat[0].stats.delta, \
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tLdat = np.arange(0, len(Ldat) * zdat[0].stats.delta, \
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zdat[0].stats.delta)
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zdat[0].stats.delta)
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@ -589,7 +589,7 @@ def fitSourceModel(f, S, fc0, iplot):
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print("fitSourceModel: best fc: %fHz, best w0: %e m/Hz" \
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print("fitSourceModel: best fc: %fHz, best w0: %e m/Hz" \
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% (fc, w0))
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% (fc, w0))
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if iplot > 1:
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if iplot == 0:
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plt.figure(iplot)
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plt.figure(iplot)
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plt.loglog(f, S, 'k')
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plt.loglog(f, S, 'k')
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plt.loglog([f[0], fc], [w0, w0], 'g')
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plt.loglog([f[0], fc], [w0, w0], 'g')
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