Merge branch 'develop' of ariadne.geophysik.ruhr-uni-bochum.de:/data/git/pylot into develop
This commit is contained in:
commit
3cbb6138e0
@ -135,26 +135,45 @@ class Survey(object):
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def plotDiffs(self):
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import matplotlib.pyplot as plt
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diffs = []; dists = []; picks = []
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diffs = []; dists = []; mpicks = []; picks = []
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diffsDic = self.getDiffsFromManual()
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for shot in self.data.values():
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for traceID in shot.getTraceIDlist():
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if shot.getPickFlag(traceID) == 1 and shot.getManualPickFlag(traceID) == 1:
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dists.append(shot.getDistance(traceID))
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picks.append(shot.getManualPick(traceID))
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mpicks.append(shot.getManualPick(traceID))
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picks.append(shot.getPick(traceID))
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diffs.append(diffsDic[shot][traceID])
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label = 'Difference to automatic picks [s]'
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labelm = 'manual picks'
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labela = 'automatic picks'
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fig = plt.figure()
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ax = fig.add_subplot(111)
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sc = ax.scatter(dists, picks, c = diffs, s=5, edgecolors='none', label = label)
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sc_a = ax.scatter(dists, picks, c = '0.5', s=10, edgecolors='none', label = labela, alpha = 0.3)
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sc = ax.scatter(dists, mpicks, c = diffs, s=5, edgecolors='none', label = labelm)
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cbar = plt.colorbar(sc, fraction=0.05)
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cbar.set_label(label)
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cbar.set_label(labelm)
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ax.set_xlabel('Distance [m]')
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ax.set_ylabel('Time [s]')
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ax.text(0.5, 0.95, 'Plot of all MANUAL picks', transform=ax.transAxes, horizontalalignment='center')
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def plotHist(self, nbins = 20, ax = None):
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import matplotlib.pyplot as plt
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plt.interactive(True)
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diffs = []
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if ax == None:
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fig = plt.figure()
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ax = fig.add_subplot(111)
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for shot in self.data.values():
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for traceID in shot.getTraceIDlist():
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if shot.getPickFlag(traceID) == 1 and shot.getManualPickFlag(traceID) == 1:
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diffs.append(self.getDiffsFromManual()[shot][traceID])
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hist = plt.hist(diffs, nbins, histtype = 'step', normed = True, stacked = True)
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plt.title('Histogram of the differences between automatic and manual pick')
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plt.xlabel('Difference in time (auto - manual) [s]')
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return diffs
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def pickAllShots(self, windowsize, HosAic = 'hos', vmin = 333, vmax = 5500, folm = 0.6):
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'''
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@ -403,9 +422,9 @@ class Survey(object):
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#ax = fig.add_subplot(3,3,i, projection = '3d', title = 'shot:'
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#+str(shot_dict[shotnumber].getShotnumber()), xlabel = 'X', ylabel = 'Y', zlabel = 'traveltime')
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#shot_dict[shotnumber].plot3dttc(ax = ax, plotpicks = True)
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ax = fig.add_subplot(3, 4, index)
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ax = fig.add_subplot(rows, columns, index)
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if mode == '3d':
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self.getShot(shotnumber).matshow(ax = ax, colorbar = False, annotations = True)
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self.getShot(shotnumber).matshow(ax = ax, colorbar = False, annotations = True, legend = False)
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elif mode == '2d':
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self.getShot(shotnumber).plot2dttc(ax)
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self.getShot(shotnumber).plotmanual2dttc(ax)
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@ -747,6 +747,9 @@ class SeisArray(object):
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return surface
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def exportAll(self, filename = 'interpolated_receivers.out'):
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'''
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Exports all receivers to an input file for ActiveSeismoPick3D.
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'''
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recfile_out = open(filename, 'w')
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count = 0
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for traceID in self.getReceiverCoordinates().keys():
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@ -803,7 +806,7 @@ class SeisArray(object):
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xrc, yrc, zrc = self.getReceiverLists()
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xsc, ysc, zsc = self.getSourceLocsLists()
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plt.title('3D plot of seismic array %s'%self.recfile)
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plt.title('3D plot of seismic array.')
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if len(xmt) > 0:
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ax.plot(xmt, ymt, zmt, 'b.', markersize = 10, label = 'measured topo points')
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if len(xrc) > 0:
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@ -812,7 +815,7 @@ class SeisArray(object):
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ax.plot(xmr, ymr, zmr, 'ro', label = 'measured receivers')
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if len(xsc) > 0:
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ax.plot(xsc, ysc, zsc, 'b*', label = 'shot locations')
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ax.set_xlabel('X'); ax.set_ylabel('Y'); ax.set_zlabel('elevation')
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ax.set_xlabel('X [m]'); ax.set_ylabel('Y [m]'); ax.set_zlabel('Z [m]')
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ax.legend()
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return ax
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@ -842,13 +845,15 @@ class SeisArray(object):
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zgrid = griddata((x, y), z, (xgrid, ygrid), method = method)
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ax.plot_surface(xgrid, ygrid, zgrid, linewidth = 0, cmap = cm.jet, vmin = min(z), vmax = max(z))
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surf = ax.plot_surface(xgrid, ygrid, zgrid, linewidth = 0, cmap = cm.jet, vmin = min(z), vmax = max(z))
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cbar = plt.colorbar(surf)
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cbar.set_label('Elevation [m]')
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if exag == False:
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ax.set_zlim(-(max(x) - min(x)/2),(max(x) - min(x)/2))
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ax.set_aspect('equal')
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ax.set_xlabel('X'); ax.set_ylabel('Y'); ax.set_zlabel('elevation')
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ax.set_xlabel('X [m]'); ax.set_ylabel('Y [m]'); ax.set_zlabel('Z [m]')
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ax.legend()
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return ax
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@ -37,6 +37,7 @@ class SeismicShot(object):
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self.traces4plot = {}
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self.paras = {}
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self.paras['shotname'] = obsfile
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self.folm = None
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def removeEmptyTraces(self):
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traceIDs = []
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@ -279,7 +280,7 @@ class SeismicShot(object):
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#raise ValueError('ambigious or empty traceID: %s' % traceID)
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def pickTraces(self, traceID, windowsize, folm = 0.6, HosAic = 'hos'): ########## input variables ##########
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def pickTraces(self, traceID, windowsize, folm, 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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@ -299,7 +300,7 @@ class SeismicShot(object):
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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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:param: folm, fraction of local maximumm
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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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@ -308,6 +309,8 @@ class SeismicShot(object):
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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.folm = folm
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self.timeArray[traceID] = hoscf.getTimeArray()
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aiccftime, hoscftime = self.threshold(hoscf, aiccf, windowsize, self.getPickwindow(traceID), folm)
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setHosAic = {'hos': hoscftime,
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@ -335,7 +338,7 @@ class SeismicShot(object):
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# self.picks[traceID]['spe'] *= 0.5
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# TEST OF 1/2 PICKERROR
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def threshold(self, hoscf, aiccf, windowsize, pickwindow, folm = 0.6):
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def threshold(self, hoscf, aiccf, windowsize, pickwindow, folm):
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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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@ -355,14 +358,18 @@ class SeismicShot(object):
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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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:param: folm, fraction of local maximum
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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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#threshold = folm * max(hoscflist[leftb : rightb]) # combination of local maximum and threshold
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### TEST TEST
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threshold = folm * (max(hoscflist[leftb : rightb]) - min(hoscflist[leftb : rightb])) + min(hoscflist[leftb : rightb]) # combination of local maximum and threshold
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### TEST TEST
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m = leftb
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@ -373,7 +380,10 @@ class SeismicShot(object):
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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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if len(aiccfcut) > 0:
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n = aiccfcut.index(min(aiccfcut))
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else:
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n = 0
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m = lb + n
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@ -663,7 +673,7 @@ class SeismicShot(object):
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ax.legend()
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ax.text(0.05, 0.9, 'SNR: %s' %snr, transform = ax.transAxes)
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def plot_traces(self, traceID, folm = 0.6): ########## 2D, muss noch mehr verbessert werden ##########
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def plot_traces(self, traceID): ########## 2D, muss noch mehr verbessert werden ##########
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from matplotlib.widgets import Button
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def onclick(event):
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@ -688,6 +698,8 @@ class SeismicShot(object):
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def cleanup(event):
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self.traces4plot[traceID] = {}
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folm = self.folm
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fig = plt.figure()
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ax1 = fig.add_subplot(2,1,1)
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ax2 = fig.add_subplot(2,1,2, sharex = ax1)
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@ -745,7 +757,7 @@ class SeismicShot(object):
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ax.legend()
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return ax
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def _drawCFs(self, traceID, folm, refresh = False):
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def _drawCFs(self, traceID, folm = None, refresh = False):
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hoscf = self.getHOScf(traceID)
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aiccf = self.getAICcf(traceID)
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ax = self.traces4plot[traceID]['ax2']
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@ -773,6 +785,7 @@ class SeismicShot(object):
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[ax.get_ylim()[0],
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ax.get_ylim()[1]],
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'b:', label = 'latest')
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if folm is not None:
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ax.plot([0, self.getPick(traceID)],
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[folm * max(hoscf.getCF()), folm * max(hoscf.getCF())],
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'm:', label = 'folm = %s' %folm)
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@ -808,8 +821,8 @@ class SeismicShot(object):
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y.append(self.getRecLoc(traceID)[1])
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z.append(self.getPick(traceID))
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xaxis = np.arange(min(x), max(x), step)
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yaxis = np.arange(min(y), max(y), step)
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xaxis = np.arange(min(x) + step, max(x), step)
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yaxis = np.arange(min(y) + step, max(y), step)
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xgrid, ygrid = np.meshgrid(xaxis, yaxis)
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zgrid = griddata((x, y), z, (xgrid, ygrid), method = method)
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@ -834,7 +847,7 @@ class SeismicShot(object):
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plotmethod[method](*args)
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def matshow(self, ax = None, step = 0.5, method = 'linear', plotRec = True, annotations = True, colorbar = True):
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def matshow(self, ax = None, step = 0.5, method = 'linear', plotRec = True, annotations = True, colorbar = True, legend = True):
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'''
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Plots a 2D matrix of the interpolated traveltimes. This needs less performance than plot3dttc
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@ -886,9 +899,9 @@ class SeismicShot(object):
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ax.text(0.5, 0.95, 'shot: %s' %self.getShotnumber(), transform = ax.transAxes
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, horizontalalignment = 'center')
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sc = ax.scatter(x, y, c = z, s = 30, label = 'picked shots', vmin = tmin, vmax = tmax, cmap = cmap, linewidths = 1.5)
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label = None
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for xyz in zip(xcut, ycut, zcut):
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x, y, z = xyz
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label = None
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if z > tmax:
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count += 1
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z = 'w'
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@ -899,6 +912,7 @@ class SeismicShot(object):
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cbar = plt.colorbar(sc)
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cbar.set_label('Time [s]')
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if legend == True:
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ax.legend()
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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@ -16,11 +16,13 @@ def setArtificialPick(shot_dict, traceID, pick):
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def fitSNR4dist(shot_dict, shiftdist = 30, shiftSNR = 100):
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import numpy as np
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import matplotlib.pyplot as plt
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dists = []
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picks = []
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snrs = []
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snr_sqrt_inv = []
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snrthresholds = []
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snrBestFit = []
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for shot in shot_dict.values():
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for traceID in shot.getTraceIDlist():
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if shot.getSNR(traceID)[0] >= 1:
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@ -31,23 +33,28 @@ def fitSNR4dist(shot_dict, shiftdist = 30, shiftSNR = 100):
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fit = np.polyfit(dists, snr_sqrt_inv, 1)
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fit_fn = np.poly1d(fit)
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for dist in dists:
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snrBestFit.append((1/(fit_fn(dist)**2)))
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dist += shiftdist
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snrthresholds.append((1/(fit_fn(dist)**2)) - shiftSNR * np.exp(-0.05 * dist))
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plotFittedSNR(dists, snrthresholds, snrs)
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plotFittedSNR(dists, snrthresholds, snrs, snrBestFit)
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return fit_fn #### ZU VERBESSERN, sollte fertige funktion wiedergeben
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def plotFittedSNR(dists, snrthresholds, snrs):
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def plotFittedSNR(dists, snrthresholds, snrs, snrBestFit):
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import matplotlib.pyplot as plt
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plt.interactive(True)
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fig = plt.figure()
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plt.plot(dists, snrs, '.', markersize = 1.0, label = 'SNR values')
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plt.plot(dists, snrthresholds, 'r.', markersize = 1, label = 'Fitted threshold')
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plt.plot(dists, snrs, 'b.', markersize = 2.0, label = 'SNR values')
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dists.sort()
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snrthresholds.sort(reverse = True)
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snrBestFit.sort(reverse = True)
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plt.plot(dists, snrthresholds, 'r', markersize = 1, label = 'Fitted threshold')
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plt.plot(dists, snrBestFit, 'k', markersize = 1, label = 'Best fitted curve')
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plt.xlabel('Distance[m]')
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plt.ylabel('SNR')
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plt.legend()
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def setFittedSNR(shot_dict, shiftdist = 30, shiftSNR = 100, p1 = 0.004, p2 = -0.0007):
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def setDynamicFittedSNR(shot_dict, shiftdist = 30, shiftSNR = 100, p1 = 0.004, p2 = -0.0007):
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import numpy as np
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minSNR = 2.5
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#fit_fn = fitSNR4dist(shot_dict)
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@ -62,8 +69,14 @@ def setFittedSNR(shot_dict, shiftdist = 30, shiftSNR = 100, p1 = 0.004, p2 = -0.
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shot.setSNRthreshold(traceID, minSNR)
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else:
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shot.setSNRthreshold(traceID, snrthreshold)
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print "setFittedSNR: Finished setting of fitted SNR-threshold"
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print "setDynamicFittedSNR: Finished setting of fitted SNR-threshold"
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def setConstantSNR(shot_dict, snrthreshold = 2.5):
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import numpy as np
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for shot in shot_dict.values():
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for traceID in shot.getTraceIDlist():
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shot.setSNRthreshold(traceID, snrthreshold)
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print "setConstantSNR: Finished setting of SNR threshold to a constant value of %s"%snrthreshold
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def findTracesInRanges(shot_dict, distancebin, pickbin):
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'''
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Block a user