Merge branch 'develop' of ariadne.geophysik.ruhr-uni-bochum.de:/data/git/pylot into develop
This commit is contained in:
Marcel Paffrath
commit
2308695fa8
@ -9,6 +9,7 @@ import matplotlib.pyplot as plt
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import numpy as np
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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 scipy.optimize import curve_fit
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class Magnitude(object):
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'''
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@ -166,20 +167,68 @@ class DCfc(Magnitude):
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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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# remove zero-frequency and frequencies above
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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: %e m/Hz, \n" \
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"Determined corner frequency: %f Hz" % (self.w0, self.fc))
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if self.getiplot() > 1:
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f1 = plt.figure(1)
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f1 = plt.figure()
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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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plt.plot(t[iwin], np.multiply(xdat, 1000), 'g') # show displacement in mm
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# 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.xlabel('Time since %s' % tr.stats.starttime)
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plt.ylabel('Displacement [mm]')
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plt.subplot(2,1,2)
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plt.semilogy(f, Y.real)
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plt.title('Source Spectrum from P Pulse')
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plt.loglog(f, Y.real, 'k')
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plt.loglog(F, YY.real)
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plt.loglog(F, fit, 'g')
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plt.title('Source Spectrum from P Pulse, DC=%e 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.ylabel('Amplitude [m/Hz]')
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plt.grid()
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plt.show()
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raw_input()
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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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return ssp
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@ -313,7 +313,6 @@ def autopickstation(wfstream, pickparam):
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##############################################################
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# get DC value (w0) and corner frequency (fc) of source spectrum
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# from P pulse
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# restitute streams
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# initialize Data object
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data = Data()
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[corzdat, restflag] = data.restituteWFData(invdir, zdat)
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@ -323,33 +322,45 @@ def autopickstation(wfstream, pickparam):
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# class needs stream object => build it
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z_copy = zdat.copy()
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z_copy[0].data = corintzdat
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# largest detectable period == window length
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# after P pulse for calculating source spectrum
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winzc = (1 / bpz2[0]) * z_copy[0].stats.sampling_rate
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impickP = mpickP * z_copy[0].stats.sampling_rate
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wfzc = z_copy[0].data[impickP : impickP + winzc]
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# calculate spectrum using only first cycles of
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# waveform after P onset!
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zc = crossings_nonzero_all(wfzc)
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if np.size(zc) == 0:
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print ("Something is wrong with the waveform, " \
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"no zero crossings derived!")
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print ("Cannot calculate source spectrum!")
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else:
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calcwin = (zc[3] - zc[0]) * z_copy[0].stats.delta
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# calculate source spectrum and get w0 and fc
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calcwin = 1 / bpz2[0] # largest detectable period == window length
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# around P pulse for calculating source spectrum
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specpara = DCfc(z_copy, mpickP, calcwin, iplot)
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w0 = specpara.getw0()
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fc = specpara.getfc()
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print 'autopickstation: P-weight: %d, SNR: %f, SNR[dB]: %f, ' \
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'Polarity: %s' % (Pweight, SNRP, SNRPdB, FM)
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print ("autopickstation: P-weight: %d, SNR: %f, SNR[dB]: %f, " \
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"Polarity: %s" % (Pweight, SNRP, SNRPdB, FM))
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Sflag = 1
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else:
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print 'Bad initial (AIC) P-pick, skipping this onset!'
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print ("Bad initial (AIC) P-pick, skipping this onset!")
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print 'AIC-SNR=', aicpick.getSNR(), 'AIC-Slope=', aicpick.getSlope(), 'counts/s'
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print '(min. AIC-SNR=', minAICPSNR, ', min. AIC-Slope=', minAICPslope, 'counts/s)'
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Sflag = 0
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else:
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print 'autopickstation: No vertical component data available!, ' \
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'Skipping station!'
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print ("autopickstation: No vertical component data available!, " \
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"Skipping station!")
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if edat is not None and ndat is not None and len(edat) > 0 and len(
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ndat) > 0 and Pweight < 4:
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print 'Go on picking S onset ...'
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print '##################################################'
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print 'Working on S onset of station %s' % edat[0].stats.station
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print 'Filtering horizontal traces ...'
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print ("Go on picking S onset ...")
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print ("##################################################")
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print ("Working on S onset of station %s" % edat[0].stats.station)
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print ("Filtering horizontal traces ...")
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# determine time window for calculating CF after P onset
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cuttimesh = [round(max([mpickP + sstart, 0])),
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