initial import of new modules working on active seismic data
This commit is contained in:
Marcel Paffrath
parent
61c7e9f417
commit
26c958b421
721
pylot/core/active/seismicshot.py
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721
pylot/core/active/seismicshot.py
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import os
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import numpy as np
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from obspy.core import read
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from obspy import Stream
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from obspy import Trace
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from pylot.core.pick.CharFuns import HOScf
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from pylot.core.pick.CharFuns import AICcf
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from pylot.core.pick.utils import getSNR
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from pylot.core.pick.utils import earllatepicker
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class SeismicShot(object):
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'''
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SuperClass for a seismic shot object.
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'''
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def __init__(self, obsfile):
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'''
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Initialize seismic shot object giving an inputfile.
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:param: obsfile, ((!SEG2/SEGY!)) file readable by obspy
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:type: string
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'''
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self.traces = read(obsfile)
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self.recCoordlist = None
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self.srcCoordlist = None
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self.traceIDs = None
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self.pick = {}
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self.pick_backup = {}
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self.earliest = {}
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self.latest = {}
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self.pickwindow= {}
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self.manualpicks= {}
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self.snr = {}
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self.snrthreshold = {}
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self.timeArray = {}
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self.paras = {}
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self.paras['shotname'] = obsfile
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def removeEmptyTraces(self):
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traceIDs = []
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coordlist = self.getRecCoordlist()
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removed = []
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for i in range(0, len(coordlist)):
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traceIDs.append(int(coordlist[i].split()[0]))
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for trace in self.traces:
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try:
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traceIDs.index(int(trace.stats.channel))
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except:
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self.traces.remove(trace)
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removed.append(int(trace.stats.channel))
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if len(removed) > 0:
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return removed
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def removeTrace(self, traceID):
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for trace in self.traces:
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if traceID == trace.stats.channel:
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self.traces.remove(trace)
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# for traceID in TraceIDs:
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# traces = [trace for trace in self.traces if int(trace.stats.channel) == traceID]
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# if len(traces) is not 1:
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# self.traces.remove(trace)
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def updateTraceList(self):
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'''
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Looks for empty traces, returns a list of deleted traceIDs.
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'''
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traceIDs = []
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for traceID in self.getTraceIDlist():
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if traceID not in self.getStreamTraceIDs():
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self.traceIDs.remove(traceID)
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traceIDs.append(traceID)
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return traceIDs
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def setParameters(self, name, value):
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self.paras[name] = value
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def setCut(self, cut):
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self.setParameters('cut', cut)
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def setTmovwind(self, tmovwind):
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self.setParameters('tmovwind', tmovwind)
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def setOrder(self, order):
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self.setParameters('order', order)
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def setTsignal(self, tsignal):
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self.setParameters('tsignal', tsignal)
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def setTgap(self, tgap):
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self.setParameters('tgap', tgap)
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def setShotnumber(self, shotname):
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self.setParameters('shotname', shotname)
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def setRecfile(self, recfile):
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self.setParameters('recfile', recfile)
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def setSourcefile(self, sourcefile):
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self.setParameters('sourcefile', sourcefile)
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def getParas(self):
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return self.paras
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def getShotname(self):
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return self.paras['shotname']
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def getCut(self):
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return self.paras['cut']
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def getTmovwind(self):
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return self.paras['tmovwind']
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def getOrder(self):
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return self.paras['order']
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def getTsignal(self):
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return self.paras['tsignal']
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def getTgap(self):
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return self.paras['tgap']
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def getShotnumber(self):
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return self.paras['shotnumber']
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def getRecfile(self):
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return self.paras['recfile']
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def getSourcefile(self):
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return self.paras['sourcefile']
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def getPick(self, traceID):
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return self.pick[traceID]
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def getPick_backup(self, traceID):
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return self.pick_backup[traceID]
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def getEarliest(self, traceID):
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return self.earliest[traceID]
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def getLatest(self, traceID):
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return self.latest[traceID]
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def getMistake(self, traceID):
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mistake = abs(self.getEarliest(traceID) - self.getLatest(traceID))
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if np.isnan(mistake) == True:
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print "SPE is NaN for shot %s, traceID %s"%(self.getShotnumber(), traceID)
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return mistake
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def getStreamTraceIDs(self):
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traceIDs = []
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for trace in self.traces:
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traceIDs.append(int(trace.stats.channel))
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return traceIDs
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def getTraceIDlist(self):
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'''
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Returns a list containing the traceIDs read from the receiver inputfile.
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'''
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traceIDs = []
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if self.traceIDs == None:
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recCoordlist = self.getRecCoordlist()
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for i in range(0, len(recCoordlist)):
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traceIDs.append(int(recCoordlist[i].split()[0]))
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self.traceIDs = traceIDs
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return self.traceIDs
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def getPickwindow(self, traceID):
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try:
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self.pickwindow[traceID]
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except KeyError, e:
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print('no pickwindow for trace %s, set to %s' % (traceID, self.getCut()))
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self.setPickwindow(traceID, self.getCut())
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return self.pickwindow[traceID]
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def getSNR(self, traceID):
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return self.snr[traceID]
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def getSNRthreshold(self, traceID):
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return self.snrthreshold[traceID]
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def getRecCoordlist(self):
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if self.recCoordlist is None:
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coordlist = open(self.getRecfile(),'r').readlines()
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#print 'Reading receiver coordinates from %s' %(self.getRecfile())
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self.recCoordlist = coordlist
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return self.recCoordlist
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def getSrcCoordlist(self):
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if self.srcCoordlist is None:
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coordlist = open(self.getSourcefile(),'r').readlines()
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#print 'Reading shot coordinates from %s' %(self.getSourcefile())
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self.srcCoordlist = coordlist
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return self.srcCoordlist
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def getTimeArray(self, traceID):
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return self.timeArray[traceID]
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def getHOScf(self, traceID):
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'''
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Returns the higher order statistics characteristic function for a trace using pylot.
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:param: traceID
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:type: int
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:param: cut, cut out a part of the trace (t_start, t_end) [s]
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:type: tuple
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:param: t2, size of the moving window [s]
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:type: float
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:param: order, order of the characteristic function
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:type: int
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'''
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return HOScf(self.getSingleStream(traceID), self.getCut(),
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self.getTmovwind(), self.getOrder())
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def getAICcf(self, traceID):
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'''
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Returns the Akaike criterion for a trace using pylot and the higher order statistics characteristic function.
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:param: traceID
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:type: int
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:param: cut, cut out a part of the trace (t_start, t_end) [s]
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:type: tuple
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:param: t2, size of the moving window [s]
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:type: float
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:param: order, order of the characteristic function
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:type: int
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'''
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st_cf = Stream()
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tr_cf = Trace()
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tr_cf.data = self.getHOScf(traceID).getCF()
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st_cf += tr_cf
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return AICcf(st_cf, self.getCut(), self.getTmovwind())
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def getSingleStream(self, traceID): ########## SEG2 / SEGY ? ##########
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'''
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Returns a Stream with only one trace (instead of just one trace) because it is needed for pylot.
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:param: traceID
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:type: int
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'''
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#traces = [trace for trace in self.traces if int(trace.stats.seg2['CHANNEL_NUMBER']) == traceID]
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traces = [trace for trace in self.traces if int(trace.stats.channel) == traceID]
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if len(traces) == 1:
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return Stream(traces)
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else:
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self.setPick(traceID, None)
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print 'Warning: ambigious or empty traceID: %s' % traceID
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#raise ValueError('ambigious or empty traceID: %s' % traceID)
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def pickTraces(self, traceID, pickmethod, windowsize, folm = 0.6, HosAic = 'hos'): ########## input variables ##########
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# LOCALMAX NOT IMPLEMENTED!
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'''
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Intitiate picking for a trace.
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:param: traceID
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:type: int
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:param: pickmethod, use either 'threshold' or 'localmax' method. (localmax not yet implemented 04_08_15)
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:type: string
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:param: cutwindow (equals HOScf 'cut' variable)
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:type: tuple
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:param: t2 (equals HOScf t2 variable)
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:type: float
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:param: order (equals HOScf 'order' variable)
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:type: int
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:param: windowsize, window around the returned HOS picktime, to search for the AIC minumum
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:type: 'tuple'
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:param: folm, fraction of local maximumm (default = 0.6)
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:type: 'real'
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:param: HosAic, get hos or aic pick (can be 'hos'(default) or 'aic')
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:type: 'string'
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'''
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hoscf = self.getHOScf(traceID) ### determination of both, HOS and AIC (need to change threshold-picker) ###
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aiccf = self.getAICcf(traceID)
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self.timeArray[traceID] = hoscf.getTimeArray()
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if pickmethod == 'threshold':
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aiccftime, hoscftime = self.threshold(hoscf, aiccf, windowsize, self.getPickwindow(traceID), folm)
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#setpick = {'threshold':self.threshold,
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# 'localmax':self.localmax}
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#aiccftime, hoscftime = setpick[pickmethod](hoscf, aiccf, windowsize, pickwindow)
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setHosAic = {'hos': hoscftime,
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'aic': aiccftime}
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self.setPick(traceID, setHosAic[HosAic])
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self.pick_backup[traceID] = setHosAic[HosAic] ### verbessern (vor allem weil ueberschrieben bei 2tem mal picken)
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def setEarllatepick(self, traceID, nfac = 1.5):
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tgap = self.getTgap()
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tsignal = self.getTsignal()
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tnoise = self.getPick(traceID) - tgap
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(self.earliest[traceID], self.latest[traceID], tmp) = earllatepicker(self.getSingleStream(traceID),
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nfac, (tnoise, tgap, tsignal),
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self.getPick(traceID))
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def threshold(self, hoscf, aiccf, windowsize, pickwindow, folm = 0.6):
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'''
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Threshold picker, using the local maximum in a pickwindow to find the time at
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which a fraction of the local maximum is reached for the first time.
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:param: hoscf, Higher Order Statistics Characteristic Function
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:type: 'Characteristic Function'
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:param: aiccf, Characteristic Function after Akaike
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:type: 'Characteristic Function'
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:param: windowsize, window around the returned HOS picktime, to search for the AIC minumum
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:type: 'tuple'
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:param: pickwindow [seconds]
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:type: 'tuple'
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:param: cutwindow [seconds], cut a part of the trace as in Characteristic Function
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:type: 'tuple'
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:param: folm, fraction of local maximum (default = 0.6)
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:type: 'real'
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'''
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hoscflist = list(hoscf.getCF())
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leftb = int(pickwindow[0] / self.getCut()[1] * len(hoscflist))
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rightb = int(pickwindow[1] / self.getCut()[1] * len(hoscflist))
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threshold = folm * max(hoscflist[leftb : rightb]) # combination of local maximum and threshold
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m = leftb
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while hoscflist[m] < threshold:
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m += 1
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hoscftime = list(hoscf.getTimeArray())[m]
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lb = max(0, m - windowsize[0]) # if window exceeds t = 0
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aiccfcut = list(aiccf.getCF())[lb : m + windowsize[1]]
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n = aiccfcut.index(min(aiccfcut))
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m = lb + n
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aiccftime = list(hoscf.getTimeArray())[m]
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return aiccftime, hoscftime
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def getDistance(self, traceID):
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'''
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Returns the distance of the receiver with the ID == traceID to the source location (shot location).
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Uses getSrcLoc and getRecLoc.
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:param: traceID
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:type: int
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'''
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shotX, shotY, shotZ = self.getSrcLoc()
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recX, recY, recZ = self.getRecLoc(traceID)
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dist = np.sqrt((shotX-recX)**2 + (shotY-recY)**2 + (shotZ-recZ)**2)
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if np.isnan(dist) == True:
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raise ValueError("Distance is NaN for traceID %s" %traceID)
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return dist
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#return abs(float(self.getSrcLoc(traceID))-float(self.getRecLoc(traceID)))
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def getRecLoc(self, traceID): ########## input FILENAME ##########
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'''
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Returns the location (x, y, z) of the receiver with the ID == traceID.
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RECEIVEIVER FILE MUST BE SET FIRST, TO BE IMPROVED.
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:param: traceID
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:type: int
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'''
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if traceID == 0: # artificial traceID 0 with pick at t = 0
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return self.getSrcLoc()
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coordlist = self.getRecCoordlist()
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for i in range(0, len(coordlist)):
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if int(coordlist[i].split()[0]) == traceID:
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x = coordlist[i].split()[1]
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y = coordlist[i].split()[2]
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z = coordlist[i].split()[3]
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return float(x), float(y), float(z)
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#print "WARNING: traceID %s not found" % traceID
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raise ValueError("traceID %s not found" % traceID)
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#return float(self.getSingleStream(traceID)[0].stats.seg2['RECEIVER_LOCATION'])
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def getSrcLoc(self): ########## input FILENAME ##########
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'''
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Returns the location (x, y, z) of the shot.
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SOURCE FILE MUST BE SET FIRST, TO BE IMPROVED.
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'''
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coordlist = self.getSrcCoordlist()
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for i in range(0, len(coordlist)):
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if int(coordlist[i].split()[0]) == self.paras['shotnumber']:
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x = coordlist[i].split()[1]
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y = coordlist[i].split()[2]
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z = coordlist[i].split()[3]
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return float(x), float(y), float(z)
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#return float(self.getSingleStream(traceID)[0].stats.seg2['SOURCE_LOCATION'])
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def getTraceIDs4Dist(self, distance = 0, distancebin = (0, 0)): ########## nur fuer 2D benutzt, 'distance bins' ##########
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'''
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Returns the traceID(s) for a certain distance between source and receiver.
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Used for 2D Tomography. TO BE IMPROVED.
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:param: distance
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:type: real
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:param: distancebin
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:type: tuple
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'''
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traceID_list = []
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for trace in self.traces:
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#traceID = int(trace.stats.seg2['CHANNEL_NUMBER'])
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traceID = int(trace.stats.channel)
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if distance != 0:
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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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traceID_list.append(traceID)
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if len(traceID_list) > 0:
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return traceID_list
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def setManualPicks(self, traceID, picklist): ########## picklist momentan nicht allgemein, nur testweise benutzt ##########
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'''
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Sets the manual picks for a receiver with the ID == traceID for comparison.
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:param: traceID
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:type: int
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:param: picklist, list containing the manual picks (mostlikely, earliest, latest).
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:type: list
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'''
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picks = picklist[traceID - 1].split()
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mostlikely = float(picks[1])
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earliest = float(picks[2])
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latest = float(picks[3])
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if not self.manualpicks.has_key(traceID):
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self.manualpicks[traceID] = (mostlikely, earliest, latest)
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#else:
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# raise KeyError('MANUAL pick to be set more than once for traceID %s' % traceID)
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def setPick(self, traceID, pick): ########## siehe Kommentar ##########
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self.pick[traceID] = pick
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# ++++++++++++++ Block raus genommen, da Error beim 2ten Mal picken! (Ueberschreiben von erstem Pick!)
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# if not self.pick.has_key(traceID):
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# self.getPick(traceID) = picks
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# else:
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# raise KeyError('pick to be set more than once for traceID %s' % traceID)
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# def readParameter(self, parfile):
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# parlist = open(parfile,'r').readlines()
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def removePick(self, traceID):
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||||
self.setPick(traceID, None)
|
||||
|
||||
def setPickwindow(self, traceID, pickwindow):
|
||||
self.pickwindow[traceID] = pickwindow
|
||||
|
||||
def setSNR(self, traceID): ########## FORCED HOS PICK ##########
|
||||
'''
|
||||
Gets the SNR using pylot and then sets the SNR for the traceID.
|
||||
|
||||
:param: traceID
|
||||
:type: int
|
||||
|
||||
:param: (tnoise, tgap, tsignal), as used in pylot SNR
|
||||
'''
|
||||
|
||||
from pylot.core.pick.utils import getSNR
|
||||
|
||||
tgap = self.getTgap()
|
||||
tsignal = self.getTsignal()
|
||||
tnoise = self.getPick(traceID) - tgap
|
||||
|
||||
self.snr[traceID] = getSNR(self.getSingleStream(traceID), (tnoise,tgap,tsignal), self.getPick(traceID))
|
||||
|
||||
def setSNRthreshold(self, traceID, snrthreshold):
|
||||
self.snrthreshold[traceID] = snrthreshold
|
||||
|
||||
def getDistArray4ttcPlot(self): ########## nur fuer 2D benoetigt ##########
|
||||
'''
|
||||
Function to create a distance array for the plots. 2D only!
|
||||
'''
|
||||
distancearray = []
|
||||
|
||||
for traceID in self.pick.keys():
|
||||
if self.getRecLoc(traceID) > self.getSrcLoc(traceID):
|
||||
distancearray.append(self.getDistance(traceID))
|
||||
elif self.getRecLoc(traceID) < self.getSrcLoc(traceID):
|
||||
distancearray.append((-1)*self.getDistance(traceID))
|
||||
|
||||
return distancearray
|
||||
|
||||
|
||||
# def plot2dttc(self, dist_med = 0): ########## 2D ##########
|
||||
# '''
|
||||
# Function to plot the traveltime curve for automated picks (AIC & HOS) of a shot. 2d only!
|
||||
|
||||
# :param: dist_med (optional)
|
||||
# :type: 'dictionary'
|
||||
# '''
|
||||
# import matplotlib.pyplot as plt
|
||||
# plt.interactive('True')
|
||||
# aictimearray = []
|
||||
# hostimearray = []
|
||||
# if dist_med is not 0:
|
||||
# dist_medarray = []
|
||||
|
||||
# i = 1
|
||||
# for traceID in self.pick.keys():
|
||||
# aictimearray.append(self.getPick(traceID)) ###### HIER NICHT MEHR aic = [0] oder hos = [1]
|
||||
# hostimearray.append(self.getPick(traceID))
|
||||
# if dist_med is not 0: dist_medarray.append(dist_med[self.getDistance(traceID)])
|
||||
# i += 1
|
||||
|
||||
# plt.plot(self.getDistArray4ttcPlot(), aictimearray, 'r', label = "AIC")
|
||||
# plt.plot(self.getDistArray4ttcPlot(), hostimearray, 'y', label = "HOS")
|
||||
# if dist_med is not 0: plt.plot(self.getDistArray4ttcPlot(), dist_medarray, ':b')
|
||||
# plt.title(self.shotname)
|
||||
|
||||
# def plotmanualttc(self): ########## 2D ##########
|
||||
# '''
|
||||
# Function to plot the traveltime curve for manual picks of a shot. 2D only!
|
||||
# '''
|
||||
# import matplotlib.pyplot as plt
|
||||
# plt.interactive('True')
|
||||
# manualpicktimesarray = []
|
||||
# dist_medarray = []
|
||||
|
||||
# i = 1
|
||||
# for traceID in self.manualpicks.keys():
|
||||
# if self.manualpicks[traceID][0] <= 0:
|
||||
# manualpicktimesarray.append(None)
|
||||
# else:
|
||||
# manualpicktimesarray.append(self.manualpicks[traceID][0])
|
||||
# i += 1
|
||||
|
||||
# plt.plot(self.getDistArray4ttcPlot(), manualpicktimesarray, 'b', label = "manual")
|
||||
|
||||
# def plotpickwindow(self): ########## 2D ##########
|
||||
# '''
|
||||
# Plots the pickwindow of a shot for the 2nd iteration step of picking. 2D only!
|
||||
# '''
|
||||
# import matplotlib.pyplot as plt
|
||||
# plt.interactive('True')
|
||||
# pickwindowarray_lowerb = []
|
||||
# pickwindowarray_upperb = []
|
||||
|
||||
# i = 1
|
||||
# for traceID in self.pickwindow.keys():
|
||||
# pickwindowarray_lowerb.append(self.pickwindow[traceID][0])
|
||||
# pickwindowarray_upperb.append(self.pickwindow[traceID][1])
|
||||
# i += 1
|
||||
|
||||
# plt.plot(self.getDistArray4ttcPlot(), pickwindowarray_lowerb, ':k')
|
||||
# plt.plot(self.getDistArray4ttcPlot(), pickwindowarray_upperb, ':k')
|
||||
|
||||
def plot_traces(self, traceID, folm = 0.6): ########## 2D, muss noch mehr verbessert werden ##########
|
||||
import matplotlib.pyplot as plt
|
||||
from pylot.core.util import getGlobalTimes
|
||||
from pylot.core.util import prepTimeAxis
|
||||
|
||||
stream = self.getSingleStream(traceID)
|
||||
stime = getGlobalTimes(stream)[0]
|
||||
timeaxis = prepTimeAxis(stime, stream[0])
|
||||
timeaxis -= stime
|
||||
|
||||
plt.interactive('True')
|
||||
|
||||
hoscf = self.getHOScf(traceID)
|
||||
aiccf = self.getAICcf(traceID)
|
||||
|
||||
fig = plt.figure()
|
||||
ax1 = plt.subplot(2,1,1)
|
||||
plt.title('Shot: %s, traceID: %s, pick: %s' %(self.getShotnumber(), traceID, self.getPick(traceID)))
|
||||
ax1.plot(timeaxis, stream[0].data, 'k', label = 'trace')
|
||||
ax1.plot([self.getPick(traceID), self.getPick(traceID)],
|
||||
[min(stream[0].data),
|
||||
max(stream[0].data)],
|
||||
'r', label = 'mostlikely')
|
||||
plt.legend()
|
||||
ax2 = plt.subplot(2,1,2, sharex = ax1)
|
||||
ax2.plot(hoscf.getTimeArray(), hoscf.getCF(), 'b', label = 'HOS')
|
||||
ax2.plot(hoscf.getTimeArray(), aiccf.getCF(), 'g', label = 'AIC')
|
||||
ax2.plot([self.getPick(traceID), self.getPick(traceID)],
|
||||
[min(np.minimum(hoscf.getCF(), aiccf.getCF())),
|
||||
max(np.maximum(hoscf.getCF(), aiccf.getCF()))],
|
||||
'r', label = 'mostlikely')
|
||||
ax2.plot([0, self.getPick(traceID)],
|
||||
[folm * max(hoscf.getCF()), folm * max(hoscf.getCF())],
|
||||
'm:', label = 'folm = %s' %folm)
|
||||
plt.xlabel('Time [s]')
|
||||
plt.legend()
|
||||
|
||||
def plot3dttc(self, step = 0.5, contour = False, plotpicks = False, method = 'linear', ax = None):
|
||||
'''
|
||||
Plots a 3D 'traveltime cone' as surface plot by interpolating on a regular grid over the traveltimes, not yet regarding the vertical offset of the receivers.
|
||||
|
||||
:param: step (optional), gives the stepsize for the interpolated grid. Default is 0.5
|
||||
:type: 'float'
|
||||
|
||||
:param: contour (optional), plot contour plot instead of surface plot
|
||||
:type: 'logical'
|
||||
|
||||
:param: plotpicks (optional), plot the data points onto the interpolated grid
|
||||
:type: 'logical'
|
||||
|
||||
:param: method (optional), interpolation method; can be 'linear' (default) or 'cubic'
|
||||
:type: 'string'
|
||||
'''
|
||||
import matplotlib.pyplot as plt
|
||||
from scipy.interpolate import griddata
|
||||
from matplotlib import cm
|
||||
from mpl_toolkits.mplot3d import Axes3D
|
||||
|
||||
x = []
|
||||
y = []
|
||||
z = []
|
||||
for traceID in self.pick.keys():
|
||||
if self.getPick(traceID) != None:
|
||||
x.append(self.getRecLoc(traceID)[0])
|
||||
y.append(self.getRecLoc(traceID)[1])
|
||||
z.append(self.getPick(traceID))
|
||||
|
||||
xaxis = np.arange(min(x)+1, max(x), step)
|
||||
yaxis = np.arange(min(y)+1, max(y), step)
|
||||
xgrid, ygrid = np.meshgrid(xaxis, yaxis)
|
||||
zgrid = griddata((x, y), z, (xgrid, ygrid), method = method)
|
||||
|
||||
if ax == None:
|
||||
fig = plt.figure()
|
||||
ax = plt.axes(projection = '3d')
|
||||
|
||||
xsrc, ysrc, zsrc = self.getSrcLoc()
|
||||
|
||||
if contour == True:
|
||||
ax.contour3D(xgrid,ygrid,zgrid,20)
|
||||
else:
|
||||
ax.plot_surface(xgrid, ygrid, zgrid, linewidth = 0, cmap = cm.jet, vmin = min(z), vmax = max(z))
|
||||
ax.plot([xsrc], [ysrc], [self.getPick(0)], 'k*', markersize = 20) # plot source location
|
||||
ax.plot([xsrc], [ysrc], [self.getPick(0)], 'r*', markersize = 15) # plot source location
|
||||
|
||||
if plotpicks == True:
|
||||
ax.plot(x, y, z, 'k.')
|
||||
|
||||
def plotttc(self, method, *args):
|
||||
plotmethod = {'2d': self.plot2dttc, '3d': self.plot3dttc}
|
||||
|
||||
plotmethod[method](*args)
|
||||
|
||||
def matshow(self, step = 0.5, method = 'linear', ax = None, plotRec = False, annotations = False):
|
||||
'''
|
||||
Plots a 2D matrix of the interpolated traveltimes. This needs less performance than plot3dttc
|
||||
|
||||
:param: step (optional), gives the stepsize for the interpolated grid. Default is 0.5
|
||||
:type: 'float'
|
||||
|
||||
:param: method (optional), interpolation method; can be 'linear' (default) or 'cubic'
|
||||
:type: 'string'
|
||||
|
||||
:param: plotRec (optional), plot the receiver positions
|
||||
:type: 'logical'
|
||||
|
||||
:param: annotations (optional), displays traceIDs as annotations
|
||||
:type: 'logical'
|
||||
'''
|
||||
import matplotlib.pyplot as plt
|
||||
from scipy.interpolate import griddata
|
||||
# plt.interactive('True')
|
||||
|
||||
x = []
|
||||
y = []
|
||||
z = []
|
||||
for traceID in self.pick.keys():
|
||||
if self.getPick(traceID) != None:
|
||||
x.append(self.getRecLoc(traceID)[0])
|
||||
y.append(self.getRecLoc(traceID)[1])
|
||||
z.append(self.getPick(traceID))
|
||||
|
||||
xaxis = np.arange(min(x)+1, max(x), step)
|
||||
yaxis = np.arange(min(y)+1, max(y), step)
|
||||
xgrid, ygrid = np.meshgrid(xaxis, yaxis)
|
||||
zgrid = griddata((x, y), z, (xgrid, ygrid), method='linear')
|
||||
|
||||
if ax == None:
|
||||
fig = plt.figure()
|
||||
ax = plt.axes()
|
||||
|
||||
ax.imshow(zgrid, interpolation = 'none', extent = [min(x), max(x), min(y), max(y)])
|
||||
|
||||
if annotations == True:
|
||||
for i, traceID in enumerate(self.pick.keys()):
|
||||
if shot.picks[traceID] != None:
|
||||
ax.annotate('%s' % traceID, xy=(x[i], y[i]), fontsize = 'x-small')
|
||||
|
||||
if plotRec == True:
|
||||
ax.plot(x, y, 'k.')
|
||||
|
||||
plt.show()
|
||||
204
pylot/core/active/surveyUtils.py
Normal file
204
pylot/core/active/surveyUtils.py
Normal file
@ -0,0 +1,204 @@
|
||||
from pylab import *
|
||||
startpos = []
|
||||
endpos = []
|
||||
|
||||
def generateSurvey(obsdir, shotlist):
|
||||
from obspy.core import read
|
||||
from pylot.core.active import seismicshot
|
||||
|
||||
shot_dict = {}
|
||||
for shotnumber in shotlist: # loop over data files
|
||||
# generate filenames and read manual picks to a list
|
||||
obsfile = obsdir + str(shotnumber) + '_pickle.dat'
|
||||
#obsfile = obsdir + str(shotnumber) + '.dat'
|
||||
|
||||
if not obsfile in shot_dict.keys():
|
||||
shot_dict[shotnumber] = []
|
||||
shot_dict[shotnumber] = seismicshot.SeismicShot(obsfile)
|
||||
shot_dict[shotnumber].setParameters('shotnumber', shotnumber)
|
||||
|
||||
return shot_dict
|
||||
|
||||
def setParametersForShots(cutwindow, tmovwind, tsignal, tgap, receiverfile, sourcefile, shot_dict):
|
||||
for shot in shot_dict.values():
|
||||
shot.setCut(cutwindow)
|
||||
shot.setTmovwind(tmovwind)
|
||||
shot.setTsignal(tsignal)
|
||||
shot.setTgap(tgap)
|
||||
shot.setRecfile(receiverfile)
|
||||
shot.setSourcefile(sourcefile)
|
||||
shot.setOrder(order = 4)
|
||||
|
||||
def removeEmptyTraces(shot_dict):
|
||||
filename = 'removeEmptyTraces.out'
|
||||
filename2 = 'updateTraces.out'
|
||||
outfile = open(filename, 'w')
|
||||
outfile2 = open(filename2, 'w')
|
||||
for shot in shot_dict.values():
|
||||
del_traceIDs = shot.updateTraceList()
|
||||
removed = shot.removeEmptyTraces()
|
||||
if removed is not None:
|
||||
outfile.writelines('shot: %s, removed empty traces: %s\n' %(shot.getShotnumber(), removed))
|
||||
outfile2.writelines('shot: %s, removed traceID(s) %s because they were not found in the corresponding stream\n' %(shot.getShotnumber(), del_traceIDs))
|
||||
print '\nremoveEmptyTraces, updateTraces: Finished! See %s and %s for more information of removed traces.\n' %(filename, filename2)
|
||||
outfile.close()
|
||||
outfile2.close()
|
||||
|
||||
|
||||
def readParameters(parfile, parameter):
|
||||
from ConfigParser import ConfigParser
|
||||
parameterConfig = ConfigParser()
|
||||
parameterConfig.read('parfile')
|
||||
|
||||
value = parameterConfig.get('vars', parameter).split('\t')[0]
|
||||
|
||||
return value
|
||||
|
||||
def setArtificialPick(shot_dict, traceID, pick):
|
||||
for shot in shot_dict.values():
|
||||
shot.setPick(traceID, pick)
|
||||
shot.setPickwindow(traceID, shot.getCut())
|
||||
|
||||
def fitSNR4dist(shot_dict, shiftdist = 5):
|
||||
import numpy as np
|
||||
dists = []
|
||||
picks = []
|
||||
snrs = []
|
||||
snr_sqrt_inv = []
|
||||
snrthresholds = []
|
||||
for shot in shot_dict.values():
|
||||
for traceID in shot.getTraceIDlist():
|
||||
if shot.getSNR(traceID)[0] >= 1:
|
||||
dists.append(shot.getDistance(traceID))
|
||||
picks.append(shot.getPick_backup(traceID))
|
||||
snrs.append(shot.getSNR(traceID)[0])
|
||||
snr_sqrt_inv.append(1/np.sqrt(shot.getSNR(traceID)[0]))
|
||||
fit = np.polyfit(dists, snr_sqrt_inv, 1)
|
||||
fit_fn = np.poly1d(fit)
|
||||
for dist in dists:
|
||||
dist += shiftdist
|
||||
snrthresholds.append(1/(fit_fn(dist)**2))
|
||||
plotFittedSNR(dists, snrthresholds, snrs)
|
||||
return fit_fn #### ZU VERBESSERN, sollte fertige funktion wiedergeben
|
||||
|
||||
|
||||
def plotFittedSNR(dists, snrthresholds, snrs):
|
||||
import matplotlib.pyplot as plt
|
||||
plt.interactive(True)
|
||||
fig = plt.figure()
|
||||
plt.plot(dists, snrs, '.', markersize = 0.5, label = 'SNR values')
|
||||
plt.plot(dists, snrthresholds, 'r.', markersize = 1, label = 'Fitted threshold')
|
||||
plt.xlabel('Distance[m]')
|
||||
plt.ylabel('SNR')
|
||||
plt.legend()
|
||||
|
||||
def setFittedSNR(shot_dict, shiftdist = 5, p1 = 0.004, p2 = -0.004):
|
||||
import numpy as np
|
||||
#fit_fn = fitSNR4dist(shot_dict)
|
||||
fit_fn = np.poly1d([p1, p2])
|
||||
for shot in shot_dict.values():
|
||||
for traceID in shot.getTraceIDlist(): ### IMPROVE
|
||||
shot.setSNRthreshold(traceID, 1/(fit_fn(shot.getDistance(traceID) + shiftdist)**2)) ### s.o.
|
||||
print "setFittedSNR: Finished setting of fitted SNR-threshold"
|
||||
|
||||
#def linearInterp(dist_med, dist_start
|
||||
|
||||
def exportFMTOMO(shot_dict, directory = 'FMTOMO_export', sourcefile = 'input_sf.in', ttFileExtension = '.tt'):
|
||||
count = 0
|
||||
fmtomo_factor = 1000 # transforming [m/s] -> [km/s]
|
||||
LatAll = []; LonAll = []; DepthAll = []
|
||||
srcfile = open(directory + '/' + sourcefile, 'w')
|
||||
srcfile.writelines('%10s\n' %len(shot_dict)) # number of sources
|
||||
for shotnumber in getShotlist(shot_dict):
|
||||
shot = getShotForShotnumber(shot_dict, shotnumber)
|
||||
ttfilename = str(shotnumber) + ttFileExtension
|
||||
(x, y, z) = shot.getSrcLoc() # getSrcLoc returns (x, y, z)
|
||||
srcfile.writelines('%10s %10s %10s\n' %(getAngle(y), getAngle(x), (-1)*z)) # lat, lon, depth
|
||||
LatAll.append(getAngle(y)); LonAll.append(getAngle(x)); DepthAll.append((-1)*z)
|
||||
srcfile.writelines('%10s\n' %1) #
|
||||
srcfile.writelines('%10s %10s %10s\n' %(1, 1, ttfilename))
|
||||
ttfile = open(directory + '/' + ttfilename, 'w')
|
||||
traceIDlist = shot.getTraceIDlist()
|
||||
traceIDlist.sort()
|
||||
ttfile.writelines(str(countPickedTraces(shot)) + '\n')
|
||||
for traceID in traceIDlist:
|
||||
if shot.getPick(traceID) is not None:
|
||||
pick = shot.getPick(traceID) * fmtomo_factor
|
||||
### MP MP + +
|
||||
#delta = shot.getMistake(traceID) * fmtomo_factor
|
||||
delta = 0.2
|
||||
### MP MP - -
|
||||
(x, y, z) = shot.getRecLoc(traceID)
|
||||
ttfile.writelines('%20s %20s %20s %10s %10s\n' %(getAngle(y), getAngle(x), (-1)*z, pick, delta))
|
||||
LatAll.append(getAngle(y)); LonAll.append(getAngle(x)); DepthAll.append((-1)*z)
|
||||
count += 1
|
||||
ttfile.close()
|
||||
srcfile.close()
|
||||
print 'Wrote output for %s traces' %count
|
||||
print 'WARNING: output generated for FMTOMO-obsdata. Obsdata seems to take Lat, Lon, Depth and creates output for FMTOMO as Depth, Lat, Lon'
|
||||
print 'Dimensions of the seismic Array, transformed for FMTOMO, are Depth(%s, %s), Lat(%s, %s), Lon(%s, %s)'%(
|
||||
min(DepthAll), max(DepthAll), min(LatAll), max(LatAll), min(LonAll), max(LonAll))
|
||||
|
||||
def getShotlist(shot_dict):
|
||||
shotlist = []
|
||||
for shot in shot_dict.values():
|
||||
shotlist.append(shot.getShotnumber())
|
||||
shotlist.sort()
|
||||
return shotlist
|
||||
|
||||
def getShotForShotnumber(shot_dict, shotnumber):
|
||||
for shot in shot_dict.values():
|
||||
if shot.getShotnumber() == shotnumber:
|
||||
return shot
|
||||
|
||||
def getAngle(distance):
|
||||
'''
|
||||
Function returns the angle on a Sphere of the radius R = 6371 [km] for a distance [km].
|
||||
'''
|
||||
import numpy as np
|
||||
PI = np.pi
|
||||
R = 6371.
|
||||
angle = distance * 180 / (PI * R)
|
||||
return angle
|
||||
|
||||
def countPickedTraces(shot):
|
||||
numtraces = 0
|
||||
for traceID in shot.getTraceIDlist():
|
||||
if shot.getPick(traceID) is not None:
|
||||
numtraces += 1
|
||||
print "countPickedTraces: Found %s picked traces in shot number %s" %(numtraces, shot.getShotnumber())
|
||||
return numtraces
|
||||
|
||||
def countAllPickedTraces(shot_dict):
|
||||
traces = 0
|
||||
for shot in shot_dict.values():
|
||||
traces += countPickedTraces(shot)
|
||||
return traces
|
||||
|
||||
def findTracesInRanges(shot_dict, distancebin, pickbin):
|
||||
'''
|
||||
Returns traces corresponding to a certain area in a plot with all picks over the distances.
|
||||
|
||||
:param: shot_dict, dictionary containing all shots that are used
|
||||
:type: dictionary
|
||||
|
||||
:param: distancebin
|
||||
:type: tuple, (dist1[m], dist2[m])
|
||||
|
||||
:param: pickbin
|
||||
:type: tuple, (t1[s], t2[s])
|
||||
|
||||
'''
|
||||
shots_found = {}
|
||||
for shot in shot_dict.values():
|
||||
if shot.getTraceIDs4Dist(distancebin = distancebin) is not None:
|
||||
for traceID in shot.getTraceIDs4Dist(distancebin = distancebin):
|
||||
if pickbin[0] < shot.getPick(traceID) < pickbin[1]:
|
||||
if shot.getShotnumber() not in shots_found.keys():
|
||||
shots_found[shot.getShotnumber()] = []
|
||||
shots_found[shot.getShotnumber()].append(traceID)
|
||||
|
||||
return shots_found
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user