Included AICPicker of class Picker
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@ -10,18 +10,20 @@ 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 CharFuns import *
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from Picker import *
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import glob
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import argparse
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import pdb
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def run_makeCF(project, database, event, iplot, station=None):
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#parameters for CF calculation
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t2 = 7 #length of moving window for HOS calculation [sec]
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p = 4 #order of statistics
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t2 = 7 #length of moving window for HOS calculation [sec]
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p = 4 #order of statistics
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cuttimes = [10, 40] #start and end time vor CF calculation
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bpz = [2, 30] #corner frequencies of bandpass filter, vertical component
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bph = [2, 15] #corner frequencies of bandpass filter, horizontal components
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tdetz= 1.2 #length of AR-determination window [sec], vertical component
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tdeth= 0.8 #length of AR-determination window [sec], horizontal components
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tdetz= 1.2 #length of AR-determination window [sec], vertical component
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tdeth= 0.8 #length of AR-determination window [sec], horizontal components
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tpredz = 0.4 #length of AR-prediction window [sec], vertical component
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tpredh = 0.4 #length of AR-prediction window [sec], horizontal components
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addnoise = 0.001 #add noise to seismogram for stable AR prediction
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@ -29,165 +31,181 @@ def run_makeCF(project, database, event, iplot, station=None):
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arhorder = 4 #chosen order of AR process, horizontal components
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#get waveform data
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if station:
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dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*EHZ.msd' % (project, database, event, station)
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dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*EHE.msd' % (project, database, event, station)
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dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*EHN.msd' % (project, database, event, station)
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dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*EHZ.msd' % (project, database, event, station)
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dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*EHE.msd' % (project, database, event, station)
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dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*EHN.msd' % (project, database, event, station)
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#dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_z.gse' % (project, database, event, station)
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#dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_e.gse' % (project, database, event, station)
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#dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_n.gse' % (project, database, event, station)
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else:
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dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*EHZ.msd' % (project, database, event)
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dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*EHE.msd' % (project, database, event)
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dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*EHN.msd' % (project, database, event)
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dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*EHZ.msd' % (project, database, event)
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dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*EHE.msd' % (project, database, event)
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dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*EHN.msd' % (project, database, event)
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wfzfiles = glob.glob(dpz)
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wfefiles = glob.glob(dpe)
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wfnfiles = glob.glob(dpn)
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if wfzfiles:
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for i in range(len(wfzfiles)):
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print 'Vertical component data found ...'
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print wfzfiles[i]
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st = read('%s' % wfzfiles[i])
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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.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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#calculate HOS-CF using subclass HOScf of class CharacteristicFunction
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hoscf = HOScf(st_copy, cuttimes, t2, p) #instance of HOScf
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##############################################################
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#calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction
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#class needs stream object => build it
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tr_aic = tr_filt.copy()
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tr_aic.data = hoscf.getCF()
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st_copy[0].data = tr_aic.data
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aiccf = AICcf(st_copy, cuttimes, t2, p) #instance of AICcf
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##############################################################
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#calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction
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#get stream object of filtered data
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st_copy[0].data = tr_filt.data
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arzcf = ARZcf(st_copy, cuttimes, tpredz, arzorder, tdetz, addnoise) #instance of ARZcf
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##############################################################
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#calculate AIC-ARZ-CF using subclass AICcf of class CharacteristicFunction
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#class needs stream object => build it
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tr_arzaic = tr_filt.copy()
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tr_arzaic.data = arzcf.getCF()
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st_copy[0].data = tr_arzaic.data
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araiccf = AICcf(st_copy, cuttimes, t2, p) #instance of AICcf
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for i in range(len(wfzfiles)):
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print 'Vertical component data found ...'
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print wfzfiles[i]
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st = read('%s' % wfzfiles[i])
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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.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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#calculate HOS-CF using subclass HOScf of class CharacteristicFunction
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hoscf = HOScf(st_copy, cuttimes, t2, p) #instance of HOScf
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#get corresponding time array
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thoscf = np.arange(0, len(hoscf.getCF()) / tr_filt.stats.sampling_rate, tr_filt.stats.delta) + cuttimes[0]
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##############################################################
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#get onset time from HOS-CF using class Picker
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#hospick = PragPicker(hoscf.getCF(), thoscf, 2, 70, [1, 0.5, 0.2], 2, 0.001, 0.2)
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#pdb.set_trace()
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##############################################################
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#calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction
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#class needs stream object => build it
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tr_aic = tr_filt.copy()
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tr_aic.data = hoscf.getCF()
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st_copy[0].data = tr_aic.data
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aiccf = AICcf(st_copy, cuttimes, t2, p) #instance of AICcf
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#get corresponding time array
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taiccf = np.arange(0, len(aiccf.getCF()) / tr_filt.stats.sampling_rate, tr_filt.stats.delta) + cuttimes[0]
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##############################################################
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#get onset time from AIC-HOS-CF using subclass AICPicker of class AutoPicking
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aicpick = AICPicker(aiccf.getCF(), taiccf, tr_filt.stats.delta, 2, 70, [1, 0.5, 0.2], 2, 0.001, 2.5)
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##############################################################
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#calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction
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#get stream object of filtered data
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st_copy[0].data = tr_filt.data
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arzcf = ARZcf(st_copy, cuttimes, tpredz, arzorder, tdetz, addnoise) #instance of ARZcf
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##############################################################
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#calculate AIC-ARZ-CF using subclass AICcf of class CharacteristicFunction
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#class needs stream object => build it
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tr_arzaic = tr_filt.copy()
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tr_arzaic.data = arzcf.getCF()
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st_copy[0].data = tr_arzaic.data
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araiccf = AICcf(st_copy, cuttimes, t2, p) #instance of AICcf
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elif not wfzfiles:
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print 'No vertical component data found!'
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print 'No vertical component data found!'
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if wfefiles and wfnfiles:
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for i in range(len(wfefiles)):
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print 'Horizontal component data found ...'
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print wfefiles[i]
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print wfnfiles[i]
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#merge streams
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H = read('%s' % wfefiles[i])
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H += read('%s' % wfnfiles[i])
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H_copy = H.copy()
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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.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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H_copy[1].data = trH2_filt.data
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##############################################################
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#calculate ARH-CF using subclass ARHcf of class CharcteristicFunction
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arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) #instance of ARHcf
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##############################################################
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#create stream with 3 traces
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#merge streams
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AllC = read('%s' % wfefiles[i])
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AllC += read('%s' % wfnfiles[i])
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AllC += read('%s' % wfzfiles[i])
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#filter and taper data
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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.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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AllC[0].data = All1_filt.data
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AllC[1].data = All2_filt.data
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AllC[2].data = All3_filt.data
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#calculate AR3C-CF using subclass AR3Ccf of class CharacteristicFunction
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ar3ccf = AR3Ccf(AllC, cuttimes, tpredz, arhorder, tdetz, addnoise) #instance of AR3Ccf
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##############################################################
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if iplot:
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#plot vertical trace
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plt.figure()
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tr = st[0]
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tstepz = tpredz / 16
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tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
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thoscf = np.arange(0, len(hoscf.getCF()) / tr.stats.sampling_rate, tr.stats.delta) + cuttimes[0]
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taiccf = np.arange(0, len(aiccf.getCF()) / tr.stats.sampling_rate, tr.stats.delta) + cuttimes[0]
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tarzcf = np.arange(0, len(arzcf.getCF()) * tstepz, tstepz) + cuttimes[0] + tdetz +tpredz
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taraiccf = np.arange(0, len(araiccf.getCF()) * tstepz, tstepz) + cuttimes[0] +tdetz + tpredz
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p1 = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
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p2 = plt.plot(thoscf, hoscf.getCF()/max(hoscf.getCF()), 'r')
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p3 = plt.plot(taiccf, aiccf.getCF()/max(aiccf.getCF()), 'b')
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p4 = plt.plot(tarzcf, arzcf.getCF()/max(arzcf.getCF()), 'g')
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p5 = plt.plot(taraiccf, araiccf.getCF()/max(araiccf.getCF()), 'y')
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plt.yticks([])
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plt.xlabel('Time [s]')
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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(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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#plot horizontal traces
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plt.figure(2)
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plt.subplot(211)
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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(tarhcf, arhcf.getCF()/max(arhcf.getCF()), 'r')
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plt.yticks([])
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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], ['Data', 'ARH-CF'])
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plt.subplot(212)
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p23 = plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
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p24 = plt.plot(tarhcf, arhcf.getCF()/max(arhcf.getCF()), 'r')
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plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
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plt.yticks([])
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plt.xlabel('Time [s]')
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plt.ylabel('Normalized Counts')
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#plot 3-component window
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plt.figure(3)
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tar3ccf = np.arange(0, len(ar3ccf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdetz +tpredz
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plt.subplot(311)
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p31 = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
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p32 = plt.plot(tar3ccf, ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
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plt.yticks([])
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plt.xticks([])
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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.legend([p31, p32], ['Data', 'AR3C-CF'])
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plt.subplot(312)
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plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
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plt.plot(tar3ccf, ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
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plt.yticks([])
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plt.xticks([])
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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.subplot(313)
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plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
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plt.plot(tar3ccf, ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
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plt.yticks([])
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plt.ylabel('Normalized Counts')
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plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
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plt.xlabel('Time [s]')
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plt.show()
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raw_input()
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plt.close()
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for i in range(len(wfefiles)):
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print 'Horizontal component data found ...'
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print wfefiles[i]
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print wfnfiles[i]
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#merge streams
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H = read('%s' % wfefiles[i])
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H += read('%s' % wfnfiles[i])
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H_copy = H.copy()
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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.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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H_copy[1].data = trH2_filt.data
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##############################################################
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#calculate ARH-CF using subclass ARHcf of class CharcteristicFunction
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arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) #instance of ARHcf
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##############################################################
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#create stream with 3 traces
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#merge streams
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AllC = read('%s' % wfefiles[i])
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AllC += read('%s' % wfnfiles[i])
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AllC += read('%s' % wfzfiles[i])
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#filter and taper data
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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.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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AllC[0].data = All1_filt.data
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AllC[1].data = All2_filt.data
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AllC[2].data = All3_filt.data
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#calculate AR3C-CF using subclass AR3Ccf of class CharacteristicFunction
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ar3ccf = AR3Ccf(AllC, cuttimes, tpredz, arhorder, tdetz, addnoise) #instance of AR3Ccf
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##############################################################
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if iplot:
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#plot vertical trace
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plt.figure()
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tr = st[0]
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tstepz = tpredz / 16
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tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
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tarzcf = np.arange(0, len(arzcf.getCF()) * tstepz, tstepz) + cuttimes[0] + tdetz +tpredz
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taraiccf = np.arange(0, len(araiccf.getCF()) * tstepz, tstepz) + cuttimes[0] +tdetz + tpredz
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p1 = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
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p2 = plt.plot(thoscf, hoscf.getCF()/max(hoscf.getCF()), 'r')
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p3 = plt.plot(taiccf, aiccf.getCF()/max(aiccf.getCF()), 'b')
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p4 = plt.plot(tarzcf, arzcf.getCF()/max(arzcf.getCF()), 'g')
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p5 = plt.plot(taraiccf, araiccf.getCF()/max(araiccf.getCF()), 'y')
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plt.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'b')
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plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [1, 1], 'b')
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plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [-1, -1], 'b')
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plt.yticks([])
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plt.xlabel('Time [s]')
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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(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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#plot horizontal traces
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plt.figure(2)
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plt.subplot(211)
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tsteph = tpredh / 4
|
||||
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
|
||||
p21 = plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
|
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p22 = plt.plot(tarhcf, arhcf.getCF()/max(arhcf.getCF()), 'r')
|
||||
plt.yticks([])
|
||||
plt.ylabel('Normalized Counts')
|
||||
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
|
||||
plt.suptitle(trH1_filt.stats.starttime)
|
||||
plt.legend([p21, p22], ['Data', 'ARH-CF'])
|
||||
plt.subplot(212)
|
||||
p23 = plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
|
||||
p24 = plt.plot(tarhcf, arhcf.getCF()/max(arhcf.getCF()), 'r')
|
||||
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
|
||||
plt.yticks([])
|
||||
plt.xlabel('Time [s]')
|
||||
plt.ylabel('Normalized Counts')
|
||||
#plot 3-component window
|
||||
plt.figure(3)
|
||||
tar3ccf = np.arange(0, len(ar3ccf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdetz +tpredz
|
||||
plt.subplot(311)
|
||||
p31 = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
|
||||
p32 = plt.plot(tar3ccf, ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
|
||||
plt.yticks([])
|
||||
plt.xticks([])
|
||||
plt.ylabel('Normalized Counts')
|
||||
plt.title([tr.stats.station, tr.stats.channel])
|
||||
plt.legend([p31, p32], ['Data', 'AR3C-CF'])
|
||||
plt.subplot(312)
|
||||
plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
|
||||
plt.plot(tar3ccf, ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
|
||||
plt.yticks([])
|
||||
plt.xticks([])
|
||||
plt.ylabel('Normalized Counts')
|
||||
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
|
||||
plt.subplot(313)
|
||||
plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
|
||||
plt.plot(tar3ccf, ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
|
||||
plt.yticks([])
|
||||
plt.ylabel('Normalized Counts')
|
||||
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
|
||||
plt.xlabel('Time [s]')
|
||||
plt.show()
|
||||
raw_input()
|
||||
plt.close()
|
||||
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument('--project', type=str, help='project name (e.g. Insheim)')
|
||||
parser.add_argument('--database', type=str, help='event data base (e.g. 2014.09_Insheim)')
|
||||
|
Loading…
Reference in New Issue
Block a user