In order to calculate DC value and corner frequency of source spectrum a synthetic spectrum is calculated and optimized using scipys curve_fit.

This commit is contained in:
Ludger Küperkoch 2015-09-29 11:17:47 +02:00
parent 8035903fa5
commit ce57f184e7

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