general clean-up 2.0 even more checks made and issues resolved
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parent
0fa701a878
commit
0a7b02c04a
@ -273,8 +273,7 @@ class MainWindow(QMainWindow):
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slot=self.autoPick, shortcut='Alt+Ctrl+A',
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icon=auto_icon, tip='Automatically pick'
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' the entire dataset'
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' displayed!',
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checkable=False)
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' displayed!')
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autoPickToolBar = self.addToolBar("autoPyLoT")
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autoPickActions = (auto_pick,)
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@ -437,7 +437,7 @@ class SeismicShot(object):
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if self.getDistance(traceID) == distance:
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traceID_list.append(traceID)
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if distancebin[0] >= 0 and distancebin[1] > 0:
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if self.getDistance(traceID) > distancebin[0] and self.getDistance(traceID) < distancebin[1]:
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if distancebin[0] < self.getDistance(traceID) < distancebin[1]:
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traceID_list.append(traceID)
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if len(traceID_list) > 0:
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@ -185,7 +185,7 @@ class DCfc(Magnitude):
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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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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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@ -165,12 +165,12 @@ class CharacteristicFunction(object):
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stop = min([len(self.orig_data[0]), len(self.orig_data[1])])
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elif self.cut[0] == 0 and self.cut[1] is not 0:
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start = 0
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stop = min([self.cut[1] / self.dt, len(self.orig_data[0]), \
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len(self.orig_data[1])])
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stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
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len(self.orig_data[1])])
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else:
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start = max([0, self.cut[0] / self.dt])
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stop = min([self.cut[1] / self.dt, len(self.orig_data[0]), \
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len(self.orig_data[1])])
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stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
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len(self.orig_data[1])])
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hh = self.orig_data.copy()
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h1 = hh[0].copy()
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h2 = hh[1].copy()
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@ -181,15 +181,15 @@ class CharacteristicFunction(object):
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elif len(self.orig_data) == 3:
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if self.cut[0] == 0 and self.cut[1] == 0:
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start = 0
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stop = min([self.cut[1] / self.dt, len(self.orig_data[0]), \
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len(self.orig_data[1]), len(self.orig_data[2])])
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stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
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len(self.orig_data[1]), len(self.orig_data[2])])
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elif self.cut[0] == 0 and self.cut[1] is not 0:
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start = 0
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stop = self.cut[1] / self.dt
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else:
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start = max([0, self.cut[0] / self.dt])
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stop = min([self.cut[1] / self.dt, len(self.orig_data[0]), \
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len(self.orig_data[1]), len(self.orig_data[2])])
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stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
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len(self.orig_data[1]), len(self.orig_data[2])])
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hh = self.orig_data.copy()
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h1 = hh[0].copy()
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h2 = hh[1].copy()
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@ -231,7 +231,7 @@ class AICcf(CharacteristicFunction):
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cumsumcf = np.cumsum(np.power(xnp, 2))
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i = np.where(cumsumcf == 0)
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cumsumcf[i] = np.finfo(np.float64).eps
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cf[k] = ((k - 1) * np.log(cumsumcf[k] / k) + (datlen - k + 1) * \
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cf[k] = ((k - 1) * np.log(cumsumcf[k] / k) + (datlen - k + 1) *
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np.log((cumsumcf[datlen - 1] - cumsumcf[k - 1]) / (datlen - k + 1)))
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cf[0] = cf[1]
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inf = np.isinf(cf)
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@ -204,27 +204,27 @@ def autopickstation(wfstream, pickparam):
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if len(ndat) == 0 or len(edat) == 0:
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print ("One or more horizontal components missing!")
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print ("Signal length only checked on vertical component!")
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print ("Decreasing minsiglengh from %f to %f" \
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% (minsiglength, minsiglength / 2))
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print ("Decreasing minsiglengh from %f to %f"
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% (minsiglength, minsiglength / 2))
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Pflag = checksignallength(zne, aicpick.getpick(), tsnrz,
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minsiglength / 2, \
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minsiglength / 2,
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nfacsl, minpercent, iplot)
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else:
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# filter and taper horizontal traces
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trH1_filt = edat.copy()
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trH2_filt = ndat.copy()
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trH1_filt.filter('bandpass', freqmin=bph1[0],
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freqmax=bph1[1], \
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zerophase=False)
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freqmax=bph1[1],
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zerophase=False)
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trH2_filt.filter('bandpass', freqmin=bph1[0],
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freqmax=bph1[1], \
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zerophase=False)
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freqmax=bph1[1],
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zerophase=False)
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trH1_filt.taper(max_percentage=0.05, type='hann')
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trH2_filt.taper(max_percentage=0.05, type='hann')
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zne += trH1_filt
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zne += trH2_filt
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Pflag = checksignallength(zne, aicpick.getpick(), tsnrz,
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minsiglength, \
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minsiglength,
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nfacsl, minpercent, iplot)
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if Pflag == 1:
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@ -234,7 +234,7 @@ def autopickstation(wfstream, pickparam):
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print 'One or more horizontal components missing!'
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print 'Skipping control function checkZ4S.'
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else:
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Pflag = checkZ4S(zne, aicpick.getpick(), zfac, \
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Pflag = checkZ4S(zne, aicpick.getpick(), zfac,
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tsnrz[3], iplot)
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if Pflag == 0:
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Pmarker = 'SinsteadP'
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@ -331,7 +331,7 @@ def autopickstation(wfstream, pickparam):
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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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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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@ -341,7 +341,7 @@ def autopickstation(wfstream, pickparam):
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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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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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@ -352,7 +352,7 @@ def autopickstation(wfstream, pickparam):
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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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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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@ -593,8 +593,8 @@ def autopickstation(wfstream, pickparam):
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if restflag == 1:
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# calculate WA-peak-to-peak amplitude
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# using subclass WApp of superclass Magnitude
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wapp = WApp(cordat, mpickP, mpickP + sstop + (0.5 * (mpickP \
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+ sstop)), iplot)
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wapp = WApp(cordat, mpickP, mpickP + sstop + (0.5 * (mpickP
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+ sstop)), iplot)
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Ao = wapp.getwapp()
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else:
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@ -771,14 +771,14 @@ def autopickstation(wfstream, pickparam):
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# create dictionary
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# for P phase
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phase = 'P'
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phasepick = {'lpp': lpickP, 'epp': epickP, 'mpp': mpickP, 'spe': Perror, \
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phasepick = {'lpp': lpickP, 'epp': epickP, 'mpp': mpickP, 'spe': Perror,
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'snr': SNRP, 'snrdb': SNRPdB, 'weight': Pweight, 'fm': FM}
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picks = {phase: phasepick}
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# add P marker
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picks[phase]['marked'] = Pmarker
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# add S phase
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phase = 'S'
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phasepick = {'lpp': lpickS, 'epp': epickS, 'mpp': mpickS, 'spe': Serror, \
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phasepick = {'lpp': lpickS, 'epp': epickS, 'mpp': mpickS, 'spe': Serror,
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'snr': SNRS, 'snrdb': SNRSdB, 'weight': Sweight, 'fm': None}
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picks[phase] = phasepick
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# add Wood-Anderson amplitude
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@ -6,8 +6,8 @@
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Only for test purposes!
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"""
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from obspy.core import read
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import matplotlib.pyplot as plt
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from obspy.core import read
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import matplotlib.pyplot as plt
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import numpy as np
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from pylot.core.pick.CharFuns import CharacteristicFunction
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from pylot.core.pick.Picker import AutoPicking
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@ -56,7 +56,7 @@ def run_makeCF(project, database, event, iplot, station=None):
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st_copy = st.copy()
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#filter and taper data
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tr_filt = st[0].copy()
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tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
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tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
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tr_filt.taper(max_percentage=0.05, type='hann')
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st_copy[0].data = tr_filt.data
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##############################################################
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@ -120,8 +120,8 @@ def run_makeCF(project, database, event, iplot, station=None):
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#filter and taper data
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trH1_filt = H[0].copy()
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trH2_filt = H[1].copy()
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trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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trH1_filt.taper(max_percentage=0.05, type='hann')
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trH2_filt.taper(max_percentage=0.05, type='hann')
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H_copy[0].data = trH1_filt.data
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@ -167,9 +167,9 @@ def run_makeCF(project, database, event, iplot, station=None):
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All1_filt = AllC[0].copy()
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All2_filt = AllC[1].copy()
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All3_filt = AllC[2].copy()
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All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
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All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
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All1_filt.taper(max_percentage=0.05, type='hann')
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All2_filt.taper(max_percentage=0.05, type='hann')
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All3_filt.taper(max_percentage=0.05, type='hann')
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@ -209,19 +209,19 @@ def run_makeCF(project, database, event, iplot, station=None):
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plt.ylim([-1.5, 1.5])
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plt.xlabel('Time [s]')
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plt.ylabel('Normalized Counts')
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plt.title('%s, %s, CF-SNR=%7.2f, CF-Slope=%12.2f' % (tr.stats.station, \
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tr.stats.channel, aicpick.getSNR(), aicpick.getSlope()))
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plt.title('%s, %s, CF-SNR=%7.2f, CF-Slope=%12.2f' % (tr.stats.station,
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tr.stats.channel, aicpick.getSNR(), aicpick.getSlope()))
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plt.suptitle(tr.stats.starttime)
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plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
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plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
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#plot horizontal traces
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plt.figure(2)
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plt.subplot(2,1,1)
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tsteph = tpredh / 4
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tsteph = tpredh / 4
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th1data = np.arange(0, trH1_filt.stats.npts / trH1_filt.stats.sampling_rate, trH1_filt.stats.delta)
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th2data = np.arange(0, trH2_filt.stats.npts / trH2_filt.stats.sampling_rate, trH2_filt.stats.delta)
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tarhcf = np.arange(0, len(arhcf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdeth +tpredh
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p21, = plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
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p22, = plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
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p22, = plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
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p23, = plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
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plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
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plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
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@ -238,10 +238,10 @@ def run_makeCF(project, database, event, iplot, station=None):
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plt.ylabel('Normalized Counts')
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plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
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plt.suptitle(trH1_filt.stats.starttime)
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plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
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plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
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plt.subplot(2,1,2)
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plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
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plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
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plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
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plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
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plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
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plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
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@ -271,7 +271,7 @@ def run_makeCF(project, database, event, iplot, station=None):
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plt.ylabel('Normalized Counts')
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plt.title([tr.stats.station, tr.stats.channel])
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plt.suptitle(trH1_filt.stats.starttime)
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plt.legend([p31, p32], ['Data', 'AR3C-CF'])
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plt.legend([p31, p32], ['Data', 'AR3C-CF'])
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plt.subplot(3,1,2)
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plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
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plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
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@ -110,7 +110,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
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markersize=14)
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plt.legend([p1, p2, p3, p4, p5],
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['Data', 'Noise Window', 'Signal Window', 'Noise Level',
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'Zero Crossings'], \
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'Zero Crossings'],
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loc='best')
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plt.plot([t[0], t[int(len(t)) - 1]], [-nlevel, -nlevel], '--k')
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plt.plot([Pick1, Pick1], [max(x), -max(x)], 'b', linewidth=2)
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@ -183,10 +183,10 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
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i = 0
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for j in range(ipick[0][1], ipick[0][len(t[ipick]) - 1]):
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i = i + 1
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if xraw[j - 1] <= 0 and xraw[j] >= 0:
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if xraw[j - 1] <= 0 <= xraw[j]:
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zc1.append(t[ipick][i])
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index1.append(i)
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elif xraw[j - 1] > 0 and xraw[j] <= 0:
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elif xraw[j - 1] > 0 >= xraw[j]:
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zc1.append(t[ipick][i])
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index1.append(i)
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if len(zc1) == 3:
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@ -225,10 +225,10 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
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i = 0
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for j in range(ipick[0][1], ipick[0][len(t[ipick]) - 1]):
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i = i + 1
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if xfilt[j - 1] <= 0 and xfilt[j] >= 0:
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if xfilt[j - 1] <= 0 <= xfilt[j]:
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zc2.append(t[ipick][i])
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index2.append(i)
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elif xfilt[j - 1] > 0 and xfilt[j] <= 0:
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elif xfilt[j - 1] > 0 >= xfilt[j]:
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zc2.append(t[ipick][i])
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index2.append(i)
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if len(zc2) == 3:
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@ -263,15 +263,15 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
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if P1 is not None and P2 is not None:
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if P1[0] < 0 and P2[0] < 0:
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FM = 'D'
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elif P1[0] >= 0 and P2[0] < 0:
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elif P1[0] >= 0 > P2[0]:
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FM = '-'
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elif P1[0] < 0 and P2[0] >= 0:
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elif P1[0] < 0 <= P2[0]:
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FM = '-'
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elif P1[0] > 0 and P2[0] > 0:
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FM = 'U'
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elif P1[0] <= 0 and P2[0] > 0:
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elif P1[0] <= 0 < P2[0]:
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FM = '+'
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elif P1[0] > 0 and P2[0] <= 0:
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elif P1[0] > 0 >= P2[0]:
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FM = '+'
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print ("fmpicker: Found polarity %s" % FM)
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@ -286,7 +286,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
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p3, = plt.plot(zc1, np.zeros(len(zc1)), '*g', markersize=14)
|
||||
p4, = plt.plot(t[islope1], datafit1, '--g', linewidth=2)
|
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plt.legend([p1, p2, p3, p4],
|
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['Pick', 'Slope Window', 'Zero Crossings', 'Slope'], \
|
||||
['Pick', 'Slope Window', 'Zero Crossings', 'Slope'],
|
||||
loc='best')
|
||||
plt.text(Pick + 0.02, max(xraw) / 2, '%s' % FM, fontsize=14)
|
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ax = plt.gca()
|
||||
@ -563,8 +563,8 @@ def wadaticheck(pickdic, dttolerance, iplot):
|
||||
f4, = plt.plot(checkedPpicks, wdfit2, 'g')
|
||||
plt.title('Wadati-Diagram, %d S-P Times, Vp/Vs(raw)=%5.2f,' \
|
||||
'Vp/Vs(checked)=%5.2f' % (len(SPtimes), vpvsr, cvpvsr))
|
||||
plt.legend([f1, f2, f3, f4], ['Skipped S-Picks', 'Wadati 1', \
|
||||
'Reliable S-Picks', 'Wadati 2'], loc='best')
|
||||
plt.legend([f1, f2, f3, f4], ['Skipped S-Picks', 'Wadati 1',
|
||||
'Reliable S-Picks', 'Wadati 2'], loc='best')
|
||||
else:
|
||||
plt.title('Wadati-Diagram, %d S-P Times' % len(SPtimes))
|
||||
|
||||
@ -653,12 +653,12 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
|
||||
p1, = plt.plot(t,rms, 'k')
|
||||
p2, = plt.plot(t[inoise], rms[inoise], 'c')
|
||||
p3, = plt.plot(t[isignal],rms[isignal], 'r')
|
||||
p4, = plt.plot([t[isignal[0]], t[isignal[len(isignal)-1]]], \
|
||||
[minsiglevel, minsiglevel], 'g', linewidth=2)
|
||||
p4, = plt.plot([t[isignal[0]], t[isignal[len(isignal)-1]]],
|
||||
[minsiglevel, minsiglevel], 'g', linewidth=2)
|
||||
p5, = plt.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2)
|
||||
plt.legend([p1, p2, p3, p4, p5], ['RMS Data', 'RMS Noise Window', \
|
||||
'RMS Signal Window', 'Minimum Signal Level', \
|
||||
'Onset'], loc='best')
|
||||
plt.legend([p1, p2, p3, p4, p5], ['RMS Data', 'RMS Noise Window',
|
||||
'RMS Signal Window', 'Minimum Signal Level',
|
||||
'Onset'], loc='best')
|
||||
plt.xlabel('Time [s] since %s' % X[0].stats.starttime)
|
||||
plt.ylabel('Counts')
|
||||
plt.title('Check for Signal Length, Station %s' % X[0].stats.station)
|
||||
@ -747,15 +747,15 @@ def checkPonsets(pickdic, dttolerance, iplot):
|
||||
if iplot > 1:
|
||||
p1, = plt.plot(np.arange(0, len(Ppicks)), Ppicks, 'r+', markersize=14)
|
||||
p2, = plt.plot(igood, np.array(Ppicks)[igood], 'g*', markersize=14)
|
||||
p3, = plt.plot([0, len(Ppicks) - 1], [pmedian, pmedian], 'g', \
|
||||
linewidth=2)
|
||||
p3, = plt.plot([0, len(Ppicks) - 1], [pmedian, pmedian], 'g',
|
||||
linewidth=2)
|
||||
for i in range(0, len(Ppicks)):
|
||||
plt.text(i, Ppicks[i] + 0.2, stations[i])
|
||||
|
||||
plt.xlabel('Number of P Picks')
|
||||
plt.ylabel('Onset Time [s] from 1.1.1970')
|
||||
plt.legend([p1, p2, p3], ['Skipped P Picks', 'Good P Picks', 'Median'], \
|
||||
loc='best')
|
||||
plt.legend([p1, p2, p3], ['Skipped P Picks', 'Good P Picks', 'Median'],
|
||||
loc='best')
|
||||
plt.title('Check P Onsets')
|
||||
plt.show()
|
||||
raw_input()
|
||||
@ -916,13 +916,13 @@ def checkZ4S(X, pick, zfac, checkwin, iplot):
|
||||
plt.plot(te[isignal], edat[0].data[isignal] / max(edat[0].data) + 1, 'r')
|
||||
plt.plot(tn, ndat[0].data / max(ndat[0].data) + 2, 'k')
|
||||
plt.plot(tn[isignal], ndat[0].data[isignal] / max(ndat[0].data) + 2, 'r')
|
||||
plt.plot([tz[isignal[0]], tz[isignal[len(isignal) - 1]]], \
|
||||
[minsiglevel / max(z), minsiglevel / max(z)], 'g', \
|
||||
linewidth=2)
|
||||
plt.plot([tz[isignal[0]], tz[isignal[len(isignal) - 1]]],
|
||||
[minsiglevel / max(z), minsiglevel / max(z)], 'g',
|
||||
linewidth=2)
|
||||
plt.xlabel('Time [s] since %s' % zdat[0].stats.starttime)
|
||||
plt.ylabel('Normalized Counts')
|
||||
plt.yticks([0, 1, 2], [zdat[0].stats.channel, edat[0].stats.channel, \
|
||||
ndat[0].stats.channel])
|
||||
plt.yticks([0, 1, 2], [zdat[0].stats.channel, edat[0].stats.channel,
|
||||
ndat[0].stats.channel])
|
||||
plt.title('CheckZ4S, Station %s' % zdat[0].stats.station)
|
||||
plt.show()
|
||||
raw_input()
|
||||
|
||||
@ -73,8 +73,8 @@ def readPILOTEvent(phasfn=None, locfn=None, authority_id=None, **kwargs):
|
||||
|
||||
stations = [stat for stat in phases['stat'][0:-1:3]]
|
||||
|
||||
event = createEvent(eventDate, loccinfo, None, 'earthquake', eventNum,
|
||||
authority_id)
|
||||
event = createEvent(eventDate, loccinfo, etype='earthquake', resID=eventNum,
|
||||
authority_id=authority_id)
|
||||
|
||||
lat = float(loc['LAT'])
|
||||
lon = float(loc['LON'])
|
||||
@ -130,7 +130,7 @@ def readPILOTEvent(phasfn=None, locfn=None, authority_id=None, **kwargs):
|
||||
event.magnitudes.append(magnitude)
|
||||
return event
|
||||
|
||||
except AttributeError, e:
|
||||
except AttributeError as e:
|
||||
raise AttributeError('{0} - Matlab LOC files {1} and {2} contains \
|
||||
insufficient data!'.format(e, phasfn, locfn))
|
||||
|
||||
|
||||
@ -814,9 +814,10 @@ class PropertiesDlg(QDialog):
|
||||
if values is not None:
|
||||
self.setValues(values)
|
||||
|
||||
def setValues(self, tabValues):
|
||||
@staticmethod
|
||||
def setValues(tabValues):
|
||||
settings = QSettings()
|
||||
for setting, value in tabValues.iteritems():
|
||||
for setting, value in tabValues.items():
|
||||
settings.setValue(setting, value)
|
||||
settings.sync()
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user