In order to calculate DC value and corner frequency of source spectrum a synthetic spectrum is calculated and optimized using scipys curve_fit.
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@ -9,6 +9,7 @@ import matplotlib.pyplot as plt
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import numpy as np
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import numpy as np
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from obspy.core import Stream
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from obspy.core import Stream
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from pylot.core.pick.utils import getsignalwin
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from pylot.core.pick.utils import getsignalwin
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from scipy.optimize import curve_fit
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class Magnitude(object):
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class Magnitude(object):
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'''
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'''
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@ -166,20 +167,73 @@ class DCfc(Magnitude):
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L = (N - 1) / tr.stats.sampling_rate
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L = (N - 1) / tr.stats.sampling_rate
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f = np.arange(0, fny, 1/L)
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f = np.arange(0, fny, 1/L)
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if self.getiplot() > 1:
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# remove zero-frequency and frequencies above
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f1 = plt.figure(1)
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# corner frequency of seismometer (assumed
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# to be 100 Hz)
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fi = np.where((f >= 1) & (f < 100))
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F = f[fi]
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YY = Y[fi]
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# get plateau (DC value) and corner frequency
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# initial guess of plateau
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DCin = np.mean(YY[0:100])
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# initial guess of corner frequency
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# where spectral level reached 50% of flat level
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iin = np.where(YY >= 0.5 * DCin)
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Fcin = F[iin[0][np.size(iin) - 1]]
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fit = synthsourcespec(F, DCin, Fcin)
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[optspecfit, pcov] = curve_fit(synthsourcespec, F, YY.real, [DCin, Fcin])
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self.w0 = optspecfit[0]
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self.fc = optspecfit[1]
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print ("DCfc: Determined DC-value: %f, \n" \
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"Determined corner frequency: %f" % (self.w0, self.fc))
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#if self.getiplot() > 1:
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iplot=2
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if iplot > 1:
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f1 = plt.figure()
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plt.subplot(2,1,1)
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plt.subplot(2,1,1)
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plt.plot(t, np.multiply(tr, 1000), 'k') # show displacement in mm
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# show displacement in mm
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plt.plot(t[iwin], np.multiply(xdat, 1000), 'g') # show displacement in mm
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plt.plot(t, np.multiply(tr, 1000), 'k')
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plt.plot(t[iwin], np.multiply(xdat, 1000), 'g')
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plt.title('Seismogram and P pulse, station %s' % tr.stats.station)
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plt.title('Seismogram and P pulse, station %s' % tr.stats.station)
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plt.xlabel('Time since %s' % tr.stats.starttime)
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plt.xlabel('Time since %s' % tr.stats.starttime)
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plt.ylabel('Displacement [mm]')
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plt.ylabel('Displacement [mm]')
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plt.subplot(2,1,2)
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plt.subplot(2,1,2)
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plt.semilogy(f, Y.real)
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plt.semilogy(f, Y.real, 'k')
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plt.title('Source Spectrum from P Pulse')
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plt.semilogy(F, YY.real)
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plt.semilogy(F, fit, 'g')
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plt.title('Source Spectrum from P Pulse, DC=%f m/Hz, fc=%4.1f Hz' \
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% (self.w0, self.fc))
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plt.xlabel('Frequency [Hz]')
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plt.xlabel('Frequency [Hz]')
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plt.ylabel('Amplitude [m/Hz]')
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plt.ylabel('Amplitude [m/Hz]')
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plt.show()
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plt.show()
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raw_input()
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raw_input()
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plt.close(f1)
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plt.close(f1)
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def synthsourcespec(f, omega0, fcorner):
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'''
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Calculates synthetic source spectrum from given plateau and corner
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frequency assuming Akis omega-square model.
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:param: f, frequencies
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:type: array
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:param: omega0, DC-value (plateau) of source spectrum
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:type: float
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:param: fcorner, corner frequency of source spectrum
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:type: float
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'''
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#ssp = omega0 / (pow(2, (1 + f / fcorner)))
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ssp = omega0 / (1 + pow(2, (f / fcorner)))
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#plt.plot(f, ssp)
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#plt.show()
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#raw_input()
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return ssp
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