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Merge branch 'develop' of ariadne.geophysik.rub.de:/data/git/pylot into develop

Browse Source 
Conflicts:
	autoPyLoT.py
	pylot/core/analysis/magnitude.py
	pylot/core/pick/utils.py
This commit is contained in:
Ludger Küperkoch 2015-10-27 09:25:29 +01:00
commit c0ca788c5c
35 changed files with 1132 additions and 1331 deletions
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3
QtPyLoT.py
View File

@ -273,8 +273,7 @@ class MainWindow(QMainWindow):
slot=self.autoPick, shortcut='Alt+Ctrl+A',
icon=auto_icon, tip='Automatically pick'
' the entire dataset'
' displayed!',
checkable=False)
' displayed!')
autoPickToolBar = self.addToolBar("autoPyLoT")
autoPickActions = (auto_pick,)

9
autoPyLoT.py
View File

@ -8,12 +8,11 @@ import glob
import matplotlib.pyplot as plt
from obspy.core import read
from pylot.core.util import _getVersionString
from pylot.core.read.data import Data
from pylot.core.read.inputs import AutoPickParameter
from pylot.core.util.structure import DATASTRUCTURE
from pylot.core.pick.autopick import autopickevent
from pylot.core.pick.utils import writephases
from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString()
@ -86,9 +85,6 @@ def autoPyLoT(inputfile):
# !automated picking starts here!
picks = autopickevent(wfdat, parameter)
# write phases to NLLoc-phase file
writephases(wd_checked_onsets, 'NLLoc', phasefile)
print '------------------------------------------'
print '-----Finished event %s!-----' % event
print '------------------------------------------'
@ -104,9 +100,6 @@ def autoPyLoT(inputfile):
# !automated picking starts here!
picks = autopickevent(wfdat, parameter)
# write phases to NLLoc-phase file
writephases(wd_checked_onsets, 'NLLoc', phasefile)
print '------------------------------------------'
print '-------Finished event %s!-------' % parameter.getParam('eventID')
print '------------------------------------------'

8
icons.qrc
View File

@ -1,10 +1,10 @@
<RCC>
<qresource>
<file>icons/pylot.ico</file>
<file>icons/pylot.png</file>
<file>icons/pylot.ico</file>
<file>icons/pylot.png</file>
<file>icons/printer.png</file>
<file>icons/delete.png</file>
<file>icons/key_E.png</file>
<file>icons/key_E.png</file>
<file>icons/key_N.png</file>
<file>icons/key_P.png</file>
<file>icons/key_Q.png</file>
@ -14,7 +14,7 @@
<file>icons/key_U.png</file>
<file>icons/key_V.png</file>
<file>icons/key_W.png</file>
<file>icons/key_Z.png</file>
<file>icons/key_Z.png</file>
<file>icons/filter.png</file>
<file>icons/sync.png</file>
<file>icons/zoom_0.png</file>

1
pylot/core/__init__.py
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@ -0,0 +1 @@
# -*- coding: utf-8 -*-

1
pylot/core/active/__init__.py
View File

@ -1 +1,2 @@
# -*- coding: utf-8 -*-
__author__ = 'sebastianw'

218
pylot/core/active/activeSeismoPick.py
View File

@ -1,3 +1,4 @@
# -*- coding: utf-8 -*-
import sys
import numpy as np
from pylot.core.active import seismicshot
@ -14,11 +15,12 @@ class Survey(object):
self._sourcefile = sourcefile
self._obsdir = path
self._generateSurvey()
if useDefaultParas == True:
if useDefaultParas == True:
self.setParametersForShots()
self._removeAllEmptyTraces()
self._updateShots()
self.setArtificialPick(0, 0)
def _generateSurvey(self):
from obspy.core import read
@ -27,23 +29,28 @@ class Survey(object):
for shotnumber in shotlist: # loop over data files
# generate filenames and read manual picks to a list
obsfile = self._obsdir + str(shotnumber) + '_pickle.dat'
if not obsfile in shot_dict.keys():
if obsfile not in shot_dict.keys():
shot_dict[shotnumber] = []
shot_dict[shotnumber] = seismicshot.SeismicShot(obsfile)
shot_dict[shotnumber].setParameters('shotnumber', shotnumber)
self.setArtificialPick(0, 0) # artificial pick at source origin
self.data = shot_dict
print ("Generated Survey object for %d shots" % len(shotlist))
print ("Total number of traces: %d \n" %self.countAllTraces())
def setArtificialPick(self, traceID, pick):
'''
Sets an artificial pick for a traceID of all shots in the survey object.
(This can be used to create a pick with t = 0 at the source origin)
'''
for shot in self.data.values():
shot.setPick(traceID, pick)
def setParametersForShots(self, cutwindow = (0, 0.2), tmovwind = 0.3, tsignal = 0.03, tgap = 0.0007):
if (cutwindow == (0, 0.2) and tmovwind == 0.3 and
tsignal == 0.03 and tgap == 0.0007):
print ("Warning: Standard values used for "
"setParamters. This may not be clever.")
"setParamters. This might not be clever.")
# CHANGE this later. Parameters only needed for survey, not for each shot.
for shot in self.data.values():
shot.setCut(cutwindow)
@ -65,7 +72,7 @@ class Survey(object):
if removed is not None:
if count == 0: outfile = open(filename, 'w')
count += 1
outfile.writelines('shot: %s, removed empty traces: %s\n'
outfile.writelines('shot: %s, removed empty traces: %s\n'
%(shot.getShotnumber(), removed))
print ("\nremoveEmptyTraces: Finished! Removed %d traces" %count)
if count > 0:
@ -83,7 +90,7 @@ class Survey(object):
count += 1
countTraces += len(del_traceIDs)
outfile.writelines("shot: %s, removed traceID(s) %s because "
"they were not found in the corresponding stream\n"
"they were not found in the corresponding stream\n"
%(shot.getShotnumber(), del_traceIDs))
print ("\nupdateShots: Finished! Updated %d shots and removed "
@ -120,14 +127,13 @@ class Survey(object):
shot.setPickwindow(traceID, pickwin_used)
shot.pickTraces(traceID, windowsize, folm, HosAic) # picker
# ++ TEST: set and check SNR before adding to distance bin ############################
shot.setSNR(traceID)
#if shot.getSNR(traceID)[0] < snrthreshold:
if shot.getSNR(traceID)[0] < shot.getSNRthreshold(traceID):
shot.removePick(traceID)
# -- TEST: set and check SNR before adding to distance bin ############################
if shot.getPick(traceID) is not None:
# set epp and lpp if SNR > 1 (else earllatepicker cant set values)
if shot.getSNR(traceID)[0] > 1:
shot.setEarllatepick(traceID)
tpicksum += (datetime.now() - tstartpick); tpick = tpicksum/count
@ -137,6 +143,22 @@ class Survey(object):
self._update_progress(shot.getShotname(), tend, progress)
print('\npickAllShots: Finished\n')
def recover(self):
'''
Recovers all (accidently) removed picks. Still regards SNR threshold.
'''
print('Recovering survey...')
numpicks = 0
for shot in self.data.values():
for traceID in shot.getTraceIDlist():
if shot.getFlag(traceID) == 0:
shot.setFlag(traceID, 1)
if shot.getSNR(traceID)[0] < shot.getSNRthreshold(traceID):
shot.removePick(traceID)
else:
numpicks += 1
print('Recovered %d picks'%numpicks)
def setArtificialPick(self, traceID, pick):
for shot in self.data.values():
shot.setPick(traceID, pick)
@ -144,8 +166,8 @@ class Survey(object):
def countAllTraces(self):
numtraces = 0
for line in self.getShotlist():
for line in self.getReceiverlist():
for shot in self.getShotlist():
for rec in self.getReceiverlist(): ### shot.getReceiverlist etc.
numtraces += 1
return numtraces
@ -180,7 +202,7 @@ class Survey(object):
def getReceiverfile(self):
return self._recfile
def getPath(self):
return self._obsdir
@ -194,7 +216,7 @@ class Survey(object):
for traceID in shot.getTraceIDlist():
snrlist.append(shot.getSNR(traceID)[0])
dist.append(shot.getDistance(traceID))
if shot.getPick(traceID) is not None:
if shot.getFlag(traceID) is not 0:
pickedTraces += 1
info_dict[shot.getShotnumber()] = {'numtraces': numtraces,
'picked traces': [pickedTraces,
@ -228,14 +250,14 @@ class Survey(object):
(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\n' %1) #
srcfile.writelines('%10s %10s %10s\n' %(1, 1, ttfilename))
ttfile = open(directory + '/' + ttfilename, 'w')
traceIDlist = shot.getTraceIDlist()
traceIDlist.sort()
ttfile.writelines(str(self.countPickedTraces(shot)) + '\n')
for traceID in traceIDlist:
if shot.getPick(traceID) is not None:
if shot.getFlag(traceID) is not 0:
pick = shot.getPick(traceID) * fmtomo_factor
delta = shot.getPickError(traceID) * fmtomo_factor
(x, y, z) = shot.getRecLoc(traceID)
@ -243,7 +265,7 @@ class Survey(object):
LatAll.append(getAngle(y)); LonAll.append(getAngle(x)); DepthAll.append((-1)*z)
count += 1
ttfile.close()
srcfile.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)'%(
@ -252,14 +274,87 @@ class Survey(object):
def countPickedTraces(self, shot):
count = 0
for traceID in shot.getTraceIDlist():
if shot.getPick(traceID) is not None:
if shot.getFlag(traceID) is not 0:
count += 1
return count
def plotAllPicks(self, plotDeleted = False):
def countAllPickedTraces(self):
count = 0
for shot in self.data.values():
for traceID in shot.getTraceIDlist():
if shot.getFlag(traceID) is not 0:
count += 1
return count
def plotAllShots(self, rows = 3, columns = 4):
'''
Plots all picks over the distance between source and receiver. Returns (ax, region)
Plots all shots as Matrices with the color corresponding to the traveltime for each receiver.
IMPORTANT NOTE: Topography (z - coordinate) is not considered in the diagrams!
'''
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
plt.interactive(True)
fig = plt.figure()
ax = fig.add_subplot(111)
figPerSubplot = columns * rows
index = 1
#shotnames = []
#shotnumbers = []
# for shot in self.data.values():
# shotnames.append(shot.getShotname())
# shotnumbers.append(shot.getShotnumber())
# shotnumbers = [shotnumbers for (shotnumbers, shotnames) in sorted(zip(shotnumbers, shotnames))]
for shotnumber in self.getShotlist():
if index <= figPerSubplot:
#ax = fig.add_subplot(3,3,i, projection = '3d', title = 'shot:'
#+str(shot_dict[shotnumber].getShotnumber()), xlabel = 'X', ylabel = 'Y', zlabel = 'traveltime')
#shot_dict[shotnumber].plot3dttc(ax = ax, plotpicks = True)
ax = fig.add_subplot(3, 4, index)
self.getShot(shotnumber).matshow(ax = ax, colorbar = False, annotations = True)
index += 1
if index > figPerSubplot:
fig.subplots_adjust(left = 0, bottom = 0, right = 1, top = 1, wspace = 0, hspace = 0)
fig = plt.figure()
index = 1
fig.subplots_adjust(left = 0, bottom = 0, right = 1, top = 1, wspace = 0, hspace = 0)
def plotAllPicks(self, plotRemoved = False, colorByVal = 'log10SNR', ax = None, cbar = None, refreshPlot = False):
'''
Plots all picks over the distance between source and receiver. Returns (ax, region).
Picks can be checked and removed by using region class (pylot.core.active.surveyPlotTools.regions)
:param: plotRemoved, if True plots traces that were picked but removed from the survey (flag = 0)
:type: logical
:param: colorByVal, can be "log10SNR", "pickerror", or "spe"
:type: str
Examples:
regions.chooseRectangles():
- lets the user choose several rectangular regions in the plot
regions.plotTracesInRegions():
- creates plots (shot.plot_traces) for all traces in the active regions (i.e. chosen by e.g. chooseRectangles)
regions.setActiveRegionsForDeletion():
- highlights all shots in a the active regions for deletion
regions.deleteMarkedPicks():
- deletes the picks (pick flag set to 0) for all shots set for deletion
regions.deselectSelection(number):
- deselects the region of number = number
'''
import matplotlib.pyplot as plt
import math
plt.interactive(True)
@ -267,44 +362,63 @@ class Survey(object):
dist = []
pick = []
snrloglist = []
snrlog = []
pickerror = []
spe = []
for shot in self.data.values():
for traceID in shot.getTraceIDlist():
if plotDeleted == False:
if shot.getPick(traceID) is not None:
if plotRemoved == False:
if shot.getFlag(traceID) is not 0 or plotRemoved == True:
dist.append(shot.getDistance(traceID))
pick.append(shot.getPick(traceID))
snrloglist.append(math.log10(shot.getSNR(traceID)[0]))
elif plotDeleted == True:
dist.append(shot.getDistance(traceID))
pick.append(shot.getPick(traceID))
snrloglist.append(math.log10(shot.getSNR(traceID)[0]))
snrlog.append(math.log10(shot.getSNR(traceID)[0]))
pickerror.append(shot.getPickError(traceID))
spe.append(shot.getSymmetricPickError(traceID))
ax = self.createPlot(dist, pick, snrloglist, label = 'log10(SNR)')
region = regions(ax, self.data)
ax.legend()
color = {'log10SNR': snrlog,
'pickerror': pickerror,
'spe': spe}
self.color = color
if refreshPlot is False:
ax, cbar = self.createPlot(dist, pick, color[colorByVal], label='%s' % colorByVal)
region = regions(ax, cbar, self)
ax.legend()
return (ax, region)
if refreshPlot is True:
ax, cbar = self.createPlot(dist, pick, color[colorByVal], label='%s' % colorByVal, ax=ax, cbar=cbar)
ax.legend()
return ax
return ax, region
def createPlot(self, dist, pick, inkByVal, label):
def createPlot(self, dist, pick, inkByVal, label, ax = None, cbar = None):
import matplotlib.pyplot as plt
plt.interactive(True)
cm = plt.cm.jet
fig = plt.figure()
ax = fig.add_subplot(111)
fig = ax.scatter(dist, pick, cmap = cm, c = inkByVal, s = 5, edgecolors = 'none', label = label)
cbar = plt.colorbar(fig, fraction = 0.05)
cbar.set_label(label)
plt.title('Plot of all Picks')
plt.xlabel('Distance [m]')
plt.ylabel('Time [s]')
return ax
if ax is None:
print('Generating new plot...')
fig = plt.figure()
ax = fig.add_subplot(111)
sc = ax.scatter(dist, pick, cmap=cm, c=inkByVal, s=5, edgecolors='none', label=label)
cbar = plt.colorbar(sc, fraction=0.05)
cbar.set_label(label)
ax.set_xlabel('Distance [m]')
ax.set_ylabel('Time [s]')
ax.text(0.5, 0.95, 'Plot of all picks', transform=ax.transAxes, horizontalalignment='center')
else:
sc = ax.scatter(dist, pick, cmap=cm, c=inkByVal, s=5, edgecolors='none', label=label)
cbar = plt.colorbar(sc, cax=cbar.ax)
cbar.set_label(label)
ax.set_xlabel('Distance [m]')
ax.set_ylabel('Time [s]')
ax.text(0.5, 0.95, 'Plot of all picks', transform=ax.transAxes, horizontalalignment='center')
return (ax, cbar)
def _update_progress(self, shotname, tend, progress):
sys.stdout.write("Working on shot %s. ETC is %02d:%02d:%02d [%2.2f %%]\r"
%(shotname, tend.hour, tend.minute, tend.second, progress))
sys.stdout.write('Working on shot %s. ETC is %02d:%02d:%02d [%2.2f %%]\r' % (shotname,
tend.hour,
tend.minute,
tend.second,
progress))
sys.stdout.flush()
def saveSurvey(self, filename = 'survey.pickle'):
@ -313,8 +427,8 @@ class Survey(object):
cPickle.dump(self, outfile, -1)
print('saved Survey to file %s'%(filename))
@staticmethod
@staticmethod
def from_pickle(filename):
import cPickle
infile = open(filename, 'rb')

12
pylot/core/active/fmtomo2vtk.py
View File

@ -1,3 +1,4 @@
# -*- coding: utf-8 -*-
import numpy as np
def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk'):
@ -73,7 +74,7 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk'):
dX = getDistance(np.rad2deg(dPhi))
dY = getDistance(np.rad2deg(dTheta))
nPoints = nX * nY * nZ
dZ = dR
@ -114,7 +115,7 @@ def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
R = 6371.
distance = angle / 180 * (PI * R)
return distance
infile = open(fnin, 'r')
R = 6371
rays = {}
@ -124,10 +125,15 @@ def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
### NOTE: rays.dat seems to be in km and radians
while True:
raynumber += 1
raynumber += 1
firstline = infile.readline()
if firstline == '': break # break at EOF
raynumber = int(firstline.split()[0])
shotnumber = int(firstline.split()[1])
rayValid = int(firstline.split()[4]) # is zero if the ray is invalid
if rayValid == 0:
print('Invalid ray number %d for shot number %d'%(raynumber, shotnumber))
continue
nRayPoints = int(infile.readline().split()[0])
if not shotnumber in rays.keys():
rays[shotnumber] = {}

106
pylot/core/active/picking_script.py
View File

@ -1,106 +0,0 @@
import sys
from obspy import read
from obspy import Stream
from obspy import Trace
from datetime import datetime
import numpy as np
from pylot.core.active import surveyUtils
from pylot.core.active import seismicshot
import activeSeismoPick
reload(seismicshot)
reload(surveyUtils)
#####################################################################################
# parameter definitions:#############################################################
#traceslist = list(np.arange(1, 49, 1)) # traces (1-48)
#shotlist = list(np.arange(302, 352, 1)) # shot-files(.dat) (Paffrath: 302-352) (Hauburg: 353-401) (arange+1!)
cutwindow = (0, 0.2) # cut out a part of the trace [seconds]
tmovwind = 0.3 # size of the moving window
windowsize = (5, 0) # windowsize for AIC picker (indices around HOS picks!!)
pickwindow = cutwindow # for local max and threshold picker: fraction of the seismogram used (0...1) TO BE DONE: depends on cutwindow!!!!
folm = 0.6
rockeskyll = False
if rockeskyll == True:
receiverfile = "Geophone_interpoliert_rockes"
sourcefile = "Schusspunkte_rockes"
obsdir = "/rscratch/minos22/marcel/flachseismik/rockeskyll_200615_270615/"
filename = 'survey_rockes.pickle'
else:
receiverfile = "Geophone_interpoliert_GZB"
sourcefile = "Schusspunkte_GZB"
obsdir = "/rscratch/minos22/marcel/flachseismik/GZB_26_06_15_01/"
filename = 'survey_GZB.pickle'
# SNR
tsignal = 0.03
tgap = 0.0007
snrthreshold = 1
######################################################################################
vmin = 333
vmax = 5500
distBinSize = 2
###########################################
############# Settings: ###################
thresholdpick=True
localmaxpick=False
if thresholdpick == True: pickmethod = "threshold"
if localmaxpick == True: pickmethod = "localmax"
HosAic = 'hos' # can be 'hos' or 'aic'
###########################################
starttime = datetime.now()
print '\n--------------------Starting Script at %s -------------------\n' %starttime.time()
if thresholdpick == True: print 'Using treshold pickmethod!\n'
elif localmaxpick == True: print 'Using local maximum pick method!\n'
if HosAic == 'aic': print 'picking with AIC\n'
if HosAic == 'hos': print 'picking with HOS\n'
survey = activeSeismoPick.Survey(obsdir, sourcefile, receiverfile, True)
surveyUtils.setFittedSNR(survey.getShotDict())
print '\nDone after %s seconds!\n------------------------------------------------------------------------------\n' % (datetime.now() - starttime).seconds
count = 0; tpicksum = starttime - starttime
for shot in survey.data.values():
tstartpick = datetime.now(); count += 1
for traceID in shot.getTraceIDlist():
distance = shot.getDistance(traceID) # receive distance
pickwin_used = pickwindow # use pickwindow set in the parameter section
# for higher distances use a linear vmin/vmax to cut out late/early regions with high noise
if distance > 5.:
pwleft = distance/vmax ################## TEST
pwright = distance/vmin
if pwright > cutwindow[1]:
pwright = cutwindow[1]
pickwin_used = (pwleft, pwright)
shot.setPickwindow(traceID, pickwin_used)
shot.pickTraces(traceID, windowsize, folm, HosAic) # picker
#shot.setManualPicks(traceID, picklist) # set manual picks if given (yet used on 2D only)
# ++ TEST: set and check SNR before adding to distance bin ############################
shot.setSNR(traceID)
#if shot.getSNR(traceID)[0] < snrthreshold:
if shot.getSNR(traceID)[0] < shot.getSNRthreshold(traceID):
shot.removePick(traceID)
# -- TEST: set and check SNR before adding to distance bin ############################
if shot.getPick(traceID) is not None:
shot.setEarllatepick(traceID)
tpicksum += (datetime.now() - tstartpick); tpick = tpicksum/count
tremain = (tpick * (len(survey.getShotDict()) - count))
tend = datetime.now() + tremain
print 'shot: %s, est. time to be finished is %s:%s:%s' % (shot.getShotname(), tend.hour, tend.minute, tend.second)
survey.saveSurvey(filename)
print '\n--- Finished script ---'
print 'Elapsed time:', datetime.now()-starttime

81
pylot/core/active/seismicArrayPreparation.py
View File

@ -1,3 +1,4 @@
# -*- coding: utf-8 -*-
import sys
import numpy as np
from scipy.interpolate import griddata
@ -28,12 +29,12 @@ class SeisArray(object):
def _generateReceiverlines(self):
'''
Connects the traceIDs to the lineIDs
Connects the traceIDs to the lineIDs
for each receiverline in a dictionary.
'''
for receiver in self._receiverlist:
traceID = int(receiver.split()[0])
lineID = int(receiver.split()[1])
traceID = int(receiver.split()[0])
lineID = int(receiver.split()[1])
if not lineID in self._receiverlines.keys():
self._receiverlines[lineID] = []
self._receiverlines[lineID].append(traceID)
@ -43,16 +44,16 @@ class SeisArray(object):
Fills the three x, y, z dictionaries with measured coordinates
'''
for line in self._getReceiverlist():
traceID = int(line.split()[0])
x = float(line.split()[3])
y = float(line.split()[4])
z = float(line.split()[5])
traceID = int(line.split()[0])
x = float(line.split()[3])
y = float(line.split()[4])
z = float(line.split()[5])
self._receiverCoords[traceID] = (x, y, z)
self._measuredReceivers[traceID] = (x, y, z)
def _setGeophoneNumbers(self):
for line in self._getReceiverlist():
traceID = int(line.split()[0])
traceID = int(line.split()[0])
gphoneNum = float(line.split()[2])
self._geophoneNumbers[traceID] = gphoneNum
@ -93,7 +94,7 @@ class SeisArray(object):
return self._geophoneNumbers[traceID]
def getMeasuredReceivers(self):
return self._measuredReceivers
return self._measuredReceivers
def getMeasuredTopo(self):
return self._measuredTopo
@ -139,11 +140,11 @@ class SeisArray(object):
if self._getReceiverValue(traceID1, coordinate) < self._getReceiverValue(traceID2, coordinate):
direction = +1
return direction
if self._getReceiverValue(traceID1, coordinate) > self._getReceiverValue(traceID2, coordinate):
if self._getReceiverValue(traceID1, coordinate) > self._getReceiverValue(traceID2, coordinate):
direction = -1
return direction
print "Error: Same Value for traceID1 = %s and traceID2 = %s" %(traceID1, traceID2)
def _interpolateMeanDistances(self, traceID1, traceID2, coordinate):
'''
Returns the mean distance between two traceID's depending on the number of geophones in between
@ -186,7 +187,7 @@ class SeisArray(object):
x = float(line[1])
y = float(line[2])
z = float(line[3])
self._measuredTopo[pointID] = (x, y, z)
self._measuredTopo[pointID] = (x, y, z)
def addSourceLocations(self, filename):
'''
@ -202,7 +203,7 @@ class SeisArray(object):
x = float(line[1])
y = float(line[2])
z = float(line[3])
self._sourceLocs[pointID] = (x, y, z)
self._sourceLocs[pointID] = (x, y, z)
def interpZcoords4rec(self, method = 'linear'):
'''
@ -239,9 +240,9 @@ class SeisArray(object):
'''
x = []; y = []; z = []
for traceID in self.getMeasuredReceivers().keys():
x.append(self.getMeasuredReceivers()[traceID][0])
x.append(self.getMeasuredReceivers()[traceID][0])
y.append(self.getMeasuredReceivers()[traceID][1])
z.append(self.getMeasuredReceivers()[traceID][2])
z.append(self.getMeasuredReceivers()[traceID][2])
return x, y, z
def getMeasuredTopoLists(self):
@ -250,9 +251,9 @@ class SeisArray(object):
'''
x = []; y = []; z = []
for pointID in self.getMeasuredTopo().keys():
x.append(self.getMeasuredTopo()[pointID][0])
x.append(self.getMeasuredTopo()[pointID][0])
y.append(self.getMeasuredTopo()[pointID][1])
z.append(self.getMeasuredTopo()[pointID][2])
z.append(self.getMeasuredTopo()[pointID][2])
return x, y, z
def getSourceLocsLists(self):
@ -261,9 +262,9 @@ class SeisArray(object):
'''
x = []; y = []; z = []
for pointID in self.getSourceLocations().keys():
x.append(self.getSourceLocations()[pointID][0])
x.append(self.getSourceLocations()[pointID][0])
y.append(self.getSourceLocations()[pointID][1])
z.append(self.getSourceLocations()[pointID][2])
z.append(self.getSourceLocations()[pointID][2])
return x, y, z
def getAllMeasuredPointsLists(self):
@ -289,7 +290,7 @@ class SeisArray(object):
y.append(self.getReceiverCoordinates()[traceID][1])
z.append(self.getReceiverCoordinates()[traceID][2])
return x, y, z
def _interpolateXY4rec(self):
'''
Interpolates the X and Y coordinates for all receivers.
@ -317,7 +318,7 @@ class SeisArray(object):
:param: phiWE (W, E) extensions of the model in degree
type: tuple
'''
'''
surface = []
elevation = 0.25 # elevate topography so that no source lies above the surface
@ -356,9 +357,9 @@ class SeisArray(object):
progress = float(count) / float(nTotal) * 100
self._update_progress(progress)
if filename is not None:
if filename is not None:
outfile.writelines('%10s\n'%(z + elevation))
return surface
def generateVgrid(self, nTheta = 80, nPhi = 80, nR = 120,
@ -415,7 +416,7 @@ class SeisArray(object):
thetaDelta = abs(thetaN - thetaS) / (nTheta - 1)
phiDelta = abs(phiE - phiW) / (nPhi - 1)
rDelta = abs(rbot - rtop) / (nR - 1)
# create a regular grid including +2 cushion nodes in every direction
thetaGrid = np.linspace(thetaS - thetaDelta, thetaN + thetaDelta, num = nTheta + 2) # +2 cushion nodes
phiGrid = np.linspace(phiW - phiDelta, phiE + phiDelta, num = nPhi + 2) # +2 cushion nodes
@ -455,7 +456,7 @@ class SeisArray(object):
progress = float(count) / float(nTotal) * 100
self._update_progress(progress)
outfile.close()
def exportAll(self, filename = 'interpolated_receivers.out'):
@ -463,7 +464,7 @@ class SeisArray(object):
count = 0
for traceID in self.getReceiverCoordinates().keys():
count += 1
x, y, z = self.getReceiverCoordinates()[traceID]
x, y, z = self.getReceiverCoordinates()[traceID]
recfile_out.writelines('%5s %15s %15s %15s\n' %(traceID, x, y, z))
print "Exported coordinates for %s traces to file > %s" %(count, filename)
recfile_out.close()
@ -472,15 +473,15 @@ class SeisArray(object):
import matplotlib.pyplot as plt
plt.interactive(True)
plt.figure()
xmt, ymt, zmt = self.getMeasuredTopoLists()
xmt, ymt, zmt = self.getMeasuredTopoLists()
xsc, ysc, zsc = self.getSourceLocsLists()
xmr, ymr, zmr = self.getMeasuredReceiverLists()
xrc, yrc, zrc = self.getReceiverLists()
xmr, ymr, zmr = self.getMeasuredReceiverLists()
xrc, yrc, zrc = self.getReceiverLists()
plt.plot(xrc, yrc, 'k.', markersize = 10, label = 'all receivers')
plt.plot(xsc, ysc, 'b*', markersize = 10, label = 'shot locations')
if plot_topo == True:
if plot_topo == True:
plt.plot(xmt, ymt, 'b', markersize = 10, label = 'measured topo points')
if highlight_measured == True:
plt.plot(xmr, ymr, 'ro', label = 'measured receivers')
@ -490,7 +491,11 @@ class SeisArray(object):
plt.legend()
if annotations == True:
for traceID in self.getReceiverCoordinates().keys():
plt.annotate(str(traceID), xy = (self._getXreceiver(traceID), self._getYreceiver(traceID)), fontsize = 'x-small')
plt.annotate((' ' + str(traceID)), xy = (self._getXreceiver(traceID), self._getYreceiver(traceID)), fontsize = 'x-small', color = 'k')
for shotnumber in self.getSourceLocations().keys():
plt.annotate((' ' + str(shotnumber)), xy = (self._getXshot(shotnumber), self._getYshot(shotnumber)), fontsize = 'x-small', color = 'b')
def plotArray3D(self, ax = None):
import matplotlib.pyplot as plt
@ -501,9 +506,9 @@ class SeisArray(object):
fig = plt.figure()
ax = plt.axes(projection = '3d')
xmt, ymt, zmt = self.getMeasuredTopoLists()
xmr, ymr, zmr = self.getMeasuredReceiverLists()
xin, yin, zin = self.getReceiverLists()
xmt, ymt, zmt = self.getMeasuredTopoLists()
xmr, ymr, zmr = self.getMeasuredReceiverLists()
xin, yin, zin = self.getReceiverLists()
ax.plot(xmt, ymt, zmt, 'b*', markersize = 10, label = 'measured topo points')
ax.plot(xin, yin, zin, 'k.', markersize = 10, label = 'interpolated receivers')
@ -512,8 +517,8 @@ class SeisArray(object):
ax.legend()
return ax
def plotSurface3D(self, ax = None, step = 0.5, method = 'linear'):
from matplotlib import cm
import matplotlib.pyplot as plt
@ -657,8 +662,8 @@ class SeisArray(object):
cPickle.dump(self, outfile, -1)
print('saved SeisArray to file %s'%(filename))
@staticmethod
@staticmethod
def from_pickle(filename):
import cPickle
infile = open(filename, 'rb')

665
pylot/core/active/seismicArrayPreperation.py
View File

@ -1,665 +0,0 @@
import sys
import numpy as np
from scipy.interpolate import griddata
class SeisArray(object):
'''
Can be used to interpolate missing values of a receiver grid, if only support points were measured.
Input file should contain in each line: ('traceID' 'receiverLineID' 'number of the geophone on recLine' 'X' 'Y' 'Z')
Can be used to generate a velocity grid file (vgrids.in) for FMTOMO with a topography adapting gradient.
Can be used to generate an interface file for FMTOMO (right now only interface.z used by grid3dg) for the topography.
Supports vtk output for sources and receivers.
Note: Source and Receiver files for FMTOMO will be generated by the Survey object (because traveltimes will be added directly).
'''
def __init__(self, recfile):
self._receiverlines = {}
self._receiverCoords = {}
self._measuredReceivers = {}
self._measuredTopo = {}
self._sourceLocs = {}
self._geophoneNumbers = {}
self._receiverlist = open(recfile, 'r').readlines()
self._generateReceiverlines()
self._setReceiverCoords()
self._setGeophoneNumbers()
def _generateReceiverlines(self):
'''
Connects the traceIDs to the lineIDs
for each receiverline in a dictionary.
'''
for receiver in self._receiverlist:
traceID = int(receiver.split()[0])
lineID = int(receiver.split()[1])
if not lineID in self._receiverlines.keys():
self._receiverlines[lineID] = []
self._receiverlines[lineID].append(traceID)
def _setReceiverCoords(self):
'''
Fills the three x, y, z dictionaries with measured coordinates
'''
for line in self._getReceiverlist():
traceID = int(line.split()[0])
x = float(line.split()[3])
y = float(line.split()[4])
z = float(line.split()[5])
self._receiverCoords[traceID] = (x, y, z)
self._measuredReceivers[traceID] = (x, y, z)
def _setGeophoneNumbers(self):
for line in self._getReceiverlist():
traceID = int(line.split()[0])
gphoneNum = float(line.split()[2])
self._geophoneNumbers[traceID] = gphoneNum
def _getReceiverlines(self):
return self._receiverlines
def _getReceiverlist(self):
return self._receiverlist
def getReceiverCoordinates(self):
return self._receiverCoords
def _getXreceiver(self, traceID):
return self._receiverCoords[traceID][0]
def _getYreceiver(self, traceID):
return self._receiverCoords[traceID][1]
def _getZreceiver(self, traceID):
return self._receiverCoords[traceID][2]
def _getXshot(self, shotnumber):
return self._sourceLocs[shotnumber][0]
def _getYshot(self, shotnumber):
return self._sourceLocs[shotnumber][1]
def _getZshot(self, shotnumber):
return self._sourceLocs[shotnumber][2]
def _getReceiverValue(self, traceID, coordinate):
setCoordinate = {'X': self._getXreceiver,
'Y': self._getYreceiver,
'Z': self._getZreceiver}
return setCoordinate[coordinate](traceID)
def _getGeophoneNumber(self, traceID):
return self._geophoneNumbers[traceID]
def getMeasuredReceivers(self):
return self._measuredReceivers
def getMeasuredTopo(self):
return self._measuredTopo
def getSourceLocations(self):
return self._sourceLocs
def _setXvalue(self, traceID, value):
self._checkKey(traceID)
self._receiverCoords[traceID][0] = value
def _setYvalue(self, traceID, value):
self._checkKey(traceID)
self._receiverCoords[traceID][1] = value
def _setZvalue(self, traceID, value):
self._checkKey(traceID)
self._receiverCoords[traceID][2] = value
def _setValue(self, traceID, coordinate, value):
setCoordinate = {'X': self._setXvalue,
'Y': self._setYvalue,
'Z': self._setZvalue}
setCoordinate[coordinate](traceID, value)
def _checkKey(self, traceID):
if not traceID in self._receiverCoords.keys():
self._receiverCoords[traceID] = [None, None, None]
def _checkTraceIDdirection(self, traceID1, traceID2):
if traceID2 > traceID1:
direction = +1
return direction
if traceID2 < traceID1:
direction = -1
return direction
print "Error: Same Value for traceID1 = %s and traceID2 = %s" %(traceID1, traceID2)
def _checkCoordDirection(self, traceID1, traceID2, coordinate):
'''
Checks whether the interpolation direction is positive or negative
'''
if self._getReceiverValue(traceID1, coordinate) < self._getReceiverValue(traceID2, coordinate):
direction = +1
return direction
if self._getReceiverValue(traceID1, coordinate) > self._getReceiverValue(traceID2, coordinate):
direction = -1
return direction
print "Error: Same Value for traceID1 = %s and traceID2 = %s" %(traceID1, traceID2)
def _interpolateMeanDistances(self, traceID1, traceID2, coordinate):
'''
Returns the mean distance between two traceID's depending on the number of geophones in between
'''
num_spaces = abs(self._getGeophoneNumber(traceID1) - self._getGeophoneNumber(traceID2))
mean_distance = abs(self._getReceiverValue(traceID1, coordinate) - self._getReceiverValue(traceID2, coordinate))/num_spaces
return mean_distance
def interpolateValues(self, coordinate):
'''
Interpolates and sets all values (linear) for coordinate = 'X', 'Y' or 'Z'
'''
for lineID in self._getReceiverlines().keys():
number_measured = len(self._getReceiverlines()[lineID])
for index, traceID1 in enumerate(self._getReceiverlines()[lineID]):
if index + 1 < number_measured:
traceID2 = self._getReceiverlines()[lineID][index + 1]
traceID_dir = self._checkTraceIDdirection(traceID1, traceID2)
traceID_interp = traceID1 + traceID_dir
coord_dir = self._checkCoordDirection(traceID1, traceID2, coordinate)
mean_distance = self._interpolateMeanDistances(traceID1, traceID2, coordinate)
while (traceID_dir * traceID_interp) < (traceID_dir * traceID2):
self._setValue(traceID_interp, coordinate,
(self._getReceiverValue(traceID_interp - traceID_dir, coordinate)
+ coord_dir * (mean_distance)))
traceID_interp += traceID_dir
def addMeasuredTopographyPoints(self, filename):
'''
Use more measured points for a higher precision of height interpolation.
Input file should contain in each line: ('point ID' 'X' 'Y' 'Z')
'''
topolist = open(filename, 'r').readlines()
for line in topolist:
line = line.split()
pointID = int(line[0])
x = float(line[1])
y = float(line[2])
z = float(line[3])
self._measuredTopo[pointID] = (x, y, z)
def addSourceLocations(self, filename):
'''
Use source locations for a higher precision of height interpolation.
Input file should contain in each line: ('point ID' 'X' 'Y' 'Z')
Source locations must be added before they can be written to vtk files.
'''
topolist = open(filename, 'r').readlines()
for line in topolist:
line = line.split()
pointID = int(line[0])
x = float(line[1])
y = float(line[2])
z = float(line[3])
self._sourceLocs[pointID] = (x, y, z)
def interpZcoords4rec(self, method = 'linear'):
'''
Interpolates z values for all receivers.
'''
measured_x, measured_y, measured_z = self.getAllMeasuredPointsLists()
for traceID in self.getReceiverCoordinates().keys():
if type(self.getReceiverCoordinates()[traceID]) is not tuple:
z = griddata((measured_x, measured_y), measured_z, (self._getXreceiver(traceID), self._getYreceiver(traceID)), method = method)
self._setZvalue(traceID, float(z))
def _getAngle(self, distance):
'''
Function returns the angle on a Sphere of the radius R = 6371 [km] for a distance [km].
'''
PI = np.pi
R = 6371.
angle = distance * 180 / (PI * R)
return angle
def _getDistance(self, angle):
'''
Function returns the distance [km] on a Sphere of the radius R = 6371 [km] for an angle.
'''
PI = np.pi
R = 6371.
distance = angle / 180 * (PI * R)
return distance
def getMeasuredReceiverLists(self):
'''
Returns a list of all measured receivers known to SeisArray.
'''
x = []; y = []; z = []
for traceID in self.getMeasuredReceivers().keys():
x.append(self.getMeasuredReceivers()[traceID][0])
y.append(self.getMeasuredReceivers()[traceID][1])
z.append(self.getMeasuredReceivers()[traceID][2])
return x, y, z
def getMeasuredTopoLists(self):
'''
Returns a list of all measured topography points known to the SeisArray.
'''
x = []; y = []; z = []
for pointID in self.getMeasuredTopo().keys():
x.append(self.getMeasuredTopo()[pointID][0])
y.append(self.getMeasuredTopo()[pointID][1])
z.append(self.getMeasuredTopo()[pointID][2])
return x, y, z
def getSourceLocsLists(self):
'''
Returns a list of all measured source locations known to SeisArray.
'''
x = []; y = []; z = []
for pointID in self.getSourceLocations().keys():
x.append(self.getSourceLocations()[pointID][0])
y.append(self.getSourceLocations()[pointID][1])
z.append(self.getSourceLocations()[pointID][2])
return x, y, z
def getAllMeasuredPointsLists(self):
'''
Returns a list of all measured points known to SeisArray.
'''
mtopo_x, mtopo_y, mtopo_z = self.getMeasuredTopoLists()
msource_x, msource_y, msource_z = self.getSourceLocsLists()
mrec_x, mrec_y, mrec_z = self.getMeasuredReceiverLists()
x = mtopo_x + mrec_x + msource_x
y = mtopo_y + mrec_y + msource_y
z = mtopo_z + mrec_z + msource_z
return x, y, z
def getReceiverLists(self):
'''
Returns a list of all receivers (measured and interpolated).
'''
x = []; y =[]; z = []
for traceID in self.getReceiverCoordinates().keys():
x.append(self.getReceiverCoordinates()[traceID][0])
y.append(self.getReceiverCoordinates()[traceID][1])
z.append(self.getReceiverCoordinates()[traceID][2])
return x, y, z
def _interpolateXY4rec(self):
'''
Interpolates the X and Y coordinates for all receivers.
'''
for coordinate in ('X', 'Y'):
self.interpolateValues(coordinate)
def interpolateAll(self):
self._interpolateXY4rec()
self.interpZcoords4rec()
def interpolateTopography(self, nTheta, nPhi, thetaSN, phiWE, method = 'linear', filename = 'interface1.in'):
'''
Interpolate Z values on a regular grid with cushion nodes to use it as FMTOMO topography interface.
Returns a surface in form of a list of points [[x1, y1, z1], [x2, y2, y2], ...] (cartesian).
:param: nTheta, number of points in theta (NS)
type: integer
:param: nPhi, number of points in phi (WE)
type: integer
:param: thetaSN (S, N) extensions of the model in degree
type: tuple
:param: phiWE (W, E) extensions of the model in degree
type: tuple
'''
surface = []
elevation = 0.25 # elevate topography so that no source lies above the surface
if filename is not None:
outfile = open(filename, 'w')
print "Interpolating topography on regular grid with the dimensions:"
print "nTheta = %s, nPhi = %s, thetaSN = %s, phiWE = %s"%(nTheta, nPhi, thetaSN, phiWE)
print "method = %s, filename = %s" %(method, filename)
thetaS, thetaN = thetaSN
phiW, phiE = phiWE
measured_x, measured_y, measured_z = self.getAllMeasuredPointsLists()
# need to determine the delta to add two cushion nodes around the min/max values
thetaDelta = (thetaN - thetaS) / (nTheta - 1)
phiDelta = (phiE - phiW) / (nPhi - 1)
thetaGrid = np.linspace(thetaS - thetaDelta, thetaN + thetaDelta, num = nTheta + 2) # +2 cushion nodes
phiGrid = np.linspace(phiW - phiDelta, phiE + phiDelta, num = nPhi + 2) # +2 cushion nodes
nTotal = len(thetaGrid) * len(phiGrid); count = 0
for theta in thetaGrid:
for phi in phiGrid:
xval = self._getDistance(phi)
yval = self._getDistance(theta)
z = griddata((measured_x, measured_y), measured_z, (xval, yval), method = method)
# in case the point lies outside, nan will be returned. Find nearest:
if np.isnan(z) == True:
z = griddata((measured_x, measured_y), measured_z, (xval, yval), method = 'nearest')
z = float(z)
surface.append((xval, yval, z))
count += 1
progress = float(count) / float(nTotal) * 100
self._update_progress(progress)
if filename is not None:
outfile.writelines('%10s\n'%(z + elevation))
return surface
def generateVgrid(self, nTheta = 80, nPhi = 80, nR = 120,
thetaSN = (-0.2, 1.2), phiWE = (-0.2, 1.2),
Rbt = (-62.0, 6.0), vbot = 5.5, filename = 'vgrids.in',
method = 'linear' ):
'''
Generate a velocity grid for fmtomo regarding topography with a linear gradient starting at the topography with 0.34 [km/s].
:param: nTheta, number of points in theta (NS)
type: integer
:param: nPhi, number of points in phi (WE)
type: integer
:param: nR, number of points in depth
type: integer
:param: thetaSN (S, N) extensions of the model in degree
type: tuple
:param: phiWE (W, E) extensions of the model in degree
type: tuple
:param: Rbt (bot, top) extensions of the model in km
type: tuple
:param: vbot, velocity at the bottom of the model
type: real
'''
def getRad(angle):
PI = np.pi
rad = angle / 180 * PI
return rad
def getZmax(surface):
z = []
for point in surface:
z.append(point[2])
return max(z)
R = 6371
vmin = 0.34
decm = 0.3 # diagonal elements of the covariance matrix (grid3dg's default value is 0.3)
outfile = open(filename, 'w')
thetaS, thetaN = thetaSN
phiW, phiE = phiWE
rbot = Rbt[0] + R
rtop = Rbt[1] + R
# need to determine the delta to add two cushion nodes around the min/max values
thetaDelta = abs(thetaN - thetaS) / (nTheta - 1)
phiDelta = abs(phiE - phiW) / (nPhi - 1)
rDelta = abs(rbot - rtop) / (nR - 1)
# create a regular grid including +2 cushion nodes in every direction
thetaGrid = np.linspace(thetaS - thetaDelta, thetaN + thetaDelta, num = nTheta + 2) # +2 cushion nodes
phiGrid = np.linspace(phiW - phiDelta, phiE + phiDelta, num = nPhi + 2) # +2 cushion nodes
rGrid = np.linspace(rbot - rDelta, rtop + rDelta, num = nR + 2) # +2 cushion nodes
nTotal = len(rGrid) * len(thetaGrid) * len(phiGrid)
print "Total number of grid nodes: %s"%nTotal
# write header for velocity grid file (in RADIANS)
outfile.writelines('%10s %10s \n' %(1, 1))
outfile.writelines('%10s %10s %10s\n' %(nR + 2, nTheta + 2, nPhi + 2))
outfile.writelines('%10s %10s %10s\n' %(rDelta, getRad(thetaDelta), getRad(phiDelta)))
outfile.writelines('%10s %10s %10s\n' %(rbot - rDelta, getRad(thetaS - thetaDelta), getRad(phiW - phiDelta)))
surface = self.interpolateTopography(nTheta, nPhi, thetaSN, phiWE, method = method, filename = None)
zmax = getZmax(surface)
print "\nGenerating velocity grid for FMTOMO. Output filename = %s, interpolation method = %s"%(filename, method)
print "nTheta = %s, nPhi = %s, nR = %s, thetaSN = %s, phiWE = %s, Rbt = %s"%(nTheta, nPhi, nR, thetaSN, phiWE, Rbt)
count = 0
for radius in rGrid:
for theta in thetaGrid:
for phi in phiGrid:
xval = self._getDistance(phi)
yval = self._getDistance(theta)
for point in surface:
if point[0] == xval and point[1] == yval:
z = point[2]
if radius > (R + z + 1):
vel = 0.0
# elif radius > (R + z - 15): ########### TESTING
# vel = (radius - z - R) / (Rbt[0] - rDelta - zmax) * 1.0 + vmin ##########################
else:
vel = (radius - z - R) / (Rbt[0] - rDelta - zmax) * vbot + vmin ##########################
count += 1
outfile.writelines('%10s %10s\n'%(vel, decm))
progress = float(count) / float(nTotal) * 100
self._update_progress(progress)
outfile.close()
def exportAll(self, filename = 'interpolated_receivers.out'):
recfile_out = open(filename, 'w')
count = 0
for traceID in self.getReceiverCoordinates().keys():
count += 1
x, y, z = self.getReceiverCoordinates()[traceID]
recfile_out.writelines('%5s %15s %15s %15s\n' %(traceID, x, y, z))
print "Exported coordinates for %s traces to file > %s" %(count, filename)
recfile_out.close()
def plotArray2D(self, plot_topo = False, highlight_measured = False, annotations = True):
import matplotlib.pyplot as plt
plt.interactive(True)
plt.figure()
xmt, ymt, zmt = self.getMeasuredTopoLists()
xsc, ysc, zsc = self.getSourceLocsLists()
xmr, ymr, zmr = self.getMeasuredReceiverLists()
xrc, yrc, zrc = self.getReceiverLists()
plt.plot(xrc, yrc, 'k.', markersize = 10, label = 'all receivers')
plt.plot(xsc, ysc, 'b*', markersize = 10, label = 'shot locations')
if plot_topo == True:
plt.plot(xmt, ymt, 'b', markersize = 10, label = 'measured topo points')
if highlight_measured == True:
plt.plot(xmr, ymr, 'ro', label = 'measured receivers')
plt.xlabel('X [m]')
plt.ylabel('Y [m]')
plt.legend()
if annotations == True:
for traceID in self.getReceiverCoordinates().keys():
plt.annotate(str(traceID), xy = (self._getXreceiver(traceID), self._getYreceiver(traceID)), fontsize = 'x-small')
def plotArray3D(self, ax = None):
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
plt.interactive(True)
if ax == None:
fig = plt.figure()
ax = plt.axes(projection = '3d')
xmt, ymt, zmt = self.getMeasuredTopoLists()
xmr, ymr, zmr = self.getMeasuredReceiverLists()
xin, yin, zin = self.getReceiverLists()
ax.plot(xmt, ymt, zmt, 'b*', markersize = 10, label = 'measured topo points')
ax.plot(xin, yin, zin, 'k.', markersize = 10, label = 'interpolated receivers')
ax.plot(xmr, ymr, zmr, 'ro', label = 'measured receivers')
ax.set_xlabel('X'); ax.set_ylabel('Y'); ax.set_zlabel('elevation')
ax.legend()
return ax
def plotSurface3D(self, ax = None, step = 0.5, method = 'linear'):
from matplotlib import cm
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
plt.interactive(True)
if ax == None:
fig = plt.figure()
ax = plt.axes(projection = '3d')
xmt, ymt, zmt = self.getMeasuredTopoLists()
xmr, ymr, zmr = self.getMeasuredReceiverLists()
x = xmt + xmr
y = ymt + ymr
z = zmt + zmr
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)
ax.plot_surface(xgrid, ygrid, zgrid, linewidth = 0, cmap = cm.jet, vmin = min(z), vmax = max(z))
ax.set_zlim(-(max(x) - min(x)/2),(max(x) - min(x)/2))
ax.set_aspect('equal')
ax.set_xlabel('X'); ax.set_ylabel('Y'); ax.set_zlabel('elevation')
ax.legend()
return ax
def _update_progress(self, progress):
sys.stdout.write("%d%% done \r" % (progress) )
sys.stdout.flush()
def receivers2VTK(self, filename = 'receivers.vtk'):
'''
Generates vtk files from all receivers of the SeisArray object.
'''
outfile = open(filename, 'w')
traceIDs = []
for traceID in self.getReceiverCoordinates():
traceIDs.append(traceID)
nPoints = len(traceIDs)
# write header
print("Writing header for VTK file...")
outfile.writelines('# vtk DataFile Version 3.1\n')
outfile.writelines('Receivers with traceIDs\n')
outfile.writelines('ASCII\n')
outfile.writelines('DATASET POLYDATA\n')
outfile.writelines('POINTS %15d float\n' %(nPoints))
# write coordinates
print("Writing coordinates to VTK file...")
for traceID in traceIDs:
x = self._getXreceiver(traceID)
y = self._getYreceiver(traceID)
z = self._getZreceiver(traceID)
outfile.writelines('%10f %10f %10f \n' %(x, y, z))
outfile.writelines('VERTICES %15d %15d\n' %(nPoints, 2 * nPoints))
# write indices
print("Writing indices to VTK file...")
for index in range(nPoints):
outfile.writelines('%10d %10d\n' %(1, index))
outfile.writelines('POINT_DATA %15d\n' %(nPoints))
outfile.writelines('SCALARS traceIDs int %d\n' %(1))
outfile.writelines('LOOKUP_TABLE default\n')
# write traceIDs
print("Writing traceIDs to VTK file...")
for traceID in traceIDs:
outfile.writelines('%10d\n' %traceID)
outfile.close()
print("Wrote receiver grid for %d points to file: %s" %(nPoints, filename))
return
def sources2VTK(self, filename = 'sources.vtk'):
'''
Generates vtk-files for all source locations in the SeisArray object.
'''
outfile = open(filename, 'w')
shotnumbers = []
for shotnumber in self.getSourceLocations():
shotnumbers.append(shotnumber)
nPoints = len(shotnumbers)
# write header
print("Writing header for VTK file...")
outfile.writelines('# vtk DataFile Version 3.1\n')
outfile.writelines('Shots with shotnumbers\n')
outfile.writelines('ASCII\n')
outfile.writelines('DATASET POLYDATA\n')
outfile.writelines('POINTS %15d float\n' %(nPoints))
# write coordinates
print("Writing coordinates to VTK file...")
for shotnumber in shotnumbers:
x = self._getXshot(shotnumber)
y = self._getYshot(shotnumber)
z = self._getZshot(shotnumber)
outfile.writelines('%10f %10f %10f \n' %(x, y, z))
outfile.writelines('VERTICES %15d %15d\n' %(nPoints, 2 * nPoints))
# write indices
print("Writing indices to VTK file...")
for index in range(nPoints):
outfile.writelines('%10d %10d\n' %(1, index))
outfile.writelines('POINT_DATA %15d\n' %(nPoints))
outfile.writelines('SCALARS shotnumbers int %d\n' %(1))
outfile.writelines('LOOKUP_TABLE default\n')
# write shotnumber
print("Writing shotnumbers to VTK file...")
for shotnumber in shotnumbers:
outfile.writelines('%10d\n' %shotnumber)
outfile.close()
print("Wrote receiver grid for %d points to file: %s" %(nPoints, filename))
return
def saveSeisArray(self, filename = 'seisArray.pickle'):
import cPickle
outfile = open(filename, 'wb')
cPickle.dump(self, outfile, -1)
print('saved SeisArray to file %s'%(filename))
@staticmethod
def from_pickle(filename):
import cPickle
infile = open(filename, 'rb')
return cPickle.load(infile)

288
pylot/core/active/seismicshot.py
View File

@ -10,6 +10,8 @@ from pylot.core.pick.CharFuns import HOScf
from pylot.core.pick.CharFuns import AICcf
from pylot.core.pick.utils import getSNR
from pylot.core.pick.utils import earllatepicker
import matplotlib.pyplot as plt
plt.interactive('True')
class SeismicShot(object):
'''
@ -27,9 +29,6 @@ class SeismicShot(object):
self.srcCoordlist = None
self.traceIDs = None
self.pick = {}
self.pick_backup = {}
self.earliest = {}
self.latest = {}
self.pickwindow= {}
self.manualpicks= {}
self.snr = {}
@ -44,14 +43,14 @@ class SeismicShot(object):
removed = []
for i in range(0, len(coordlist)):
traceIDs.append(int(coordlist[i].split()[0]))
for trace in self.traces:
try:
traceIDs.index(int(trace.stats.channel))
except:
self.traces.remove(trace)
self.traces.remove(trace)
removed.append(int(trace.stats.channel))
if len(removed) > 0:
return removed
@ -59,7 +58,7 @@ class SeismicShot(object):
for trace in self.traces:
if traceID == trace.stats.channel:
self.traces.remove(trace)
# for traceID in TraceIDs:
# traces = [trace for trace in self.traces if int(trace.stats.channel) == traceID]
# if len(traces) is not 1:
@ -133,24 +132,34 @@ class SeismicShot(object):
def getSourcefile(self):
return self.paras['sourcefile']
def getPick(self, traceID):
return self.pick[traceID]
def getPick(self, traceID, returnRemoved = False):
if not self.getFlag(traceID) == 0:
return self.pick[traceID]['mpp']
if returnRemoved == True:
#print('getPick: Returned removed pick for shot %d, traceID %d' %(self.getShotnumber(), traceID))
return self.pick[traceID]['mpp']
def getPick_backup(self, traceID):
return self.pick_backup[traceID]
def getPickIncludeRemoved(self, traceID):
return self.getPick(traceID, returnRemoved = True)
def getEarliest(self, traceID):
return self.earliest[traceID]
return self.pick[traceID]['epp']
def getLatest(self, traceID):
return self.latest[traceID]
return self.pick[traceID]['lpp']
def getSymmetricPickError(self, traceID):
pickerror = self.pick[traceID]['spe']
if np.isnan(pickerror) == True:
print "SPE is NaN for shot %s, traceID %s"%(self.getShotnumber(), traceID)
return pickerror
def getPickError(self, traceID):
pickerror = abs(self.getEarliest(traceID) - self.getLatest(traceID))
if np.isnan(pickerror) == True:
if np.isnan(pickerror) == True:
print("SPE is NaN for shot %s, traceID %s"%(self.getShotnumber(), traceID))
return pickerror
return pickerror
def getStreamTraceIDs(self):
traceIDs = []
for trace in self.traces:
@ -172,15 +181,15 @@ class SeismicShot(object):
def getPickwindow(self, traceID):
try:
self.pickwindow[traceID]
self.pickwindow[traceID]
except KeyError as e:
print('no pickwindow for trace %s, set to %s' % (traceID, self.getCut()))
self.setPickwindow(traceID, self.getCut())
return self.pickwindow[traceID]
def getSNR(self, traceID):
return self.snr[traceID]
def getSNRthreshold(self, traceID):
return self.snrthreshold[traceID]
@ -218,7 +227,7 @@ class SeismicShot(object):
:type: int
'''
return HOScf(self.getSingleStream(traceID), self.getCut(),
self.getTmovwind(), self.getOrder())
self.getTmovwind(), self.getOrder(), stealthMode = True)
def getAICcf(self, traceID):
'''
@ -241,7 +250,7 @@ class SeismicShot(object):
tr_cf = Trace()
tr_cf.data = self.getHOScf(traceID).getCF()
st_cf += tr_cf
return AICcf(st_cf, self.getCut(), self.getTmovwind())
return AICcf(st_cf, self.getCut(), self.getTmovwind(), stealthMode = True)
def getSingleStream(self, traceID): ########## SEG2 / SEGY ? ##########
'''
@ -254,19 +263,19 @@ class SeismicShot(object):
traces = [trace for trace in self.traces if int(trace.stats.channel) == traceID]
if len(traces) == 1:
return Stream(traces)
else:
self.setPick(traceID, None)
print('Warning: ambigious or empty traceID: %s' % traceID)
self.setPick(traceID, None)
print 'Warning: ambigious or empty traceID: %s' % traceID
#raise ValueError('ambigious or empty traceID: %s' % traceID)
def pickTraces(self, traceID, windowsize, folm = 0.6, HosAic = 'hos'): ########## input variables ##########
# LOCALMAX NOT IMPLEMENTED!
'''
Intitiate picking for a trace.
:param: traceID
:type: int
:param: cutwindow (equals HOScf 'cut' variable)
:type: tuple
@ -289,29 +298,28 @@ class SeismicShot(object):
aiccf = self.getAICcf(traceID)
self.timeArray[traceID] = hoscf.getTimeArray()
aiccftime, hoscftime = self.threshold(hoscf, aiccf, windowsize, self.getPickwindow(traceID), folm)
setHosAic = {'hos': hoscftime,
'aic': aiccftime}
self.setPick(traceID, setHosAic[HosAic])
self.pick_backup[traceID] = setHosAic[HosAic] ### verbessern (vor allem weil ueberschrieben bei 2tem mal picken)
def setEarllatepick(self, traceID, nfac = 1.5):
tgap = self.getTgap()
tsignal = self.getTsignal()
tnoise = self.getPick(traceID) - tgap
tnoise = self.getPickIncludeRemoved(traceID) - tgap
(self.earliest[traceID], self.latest[traceID], tmp) = earllatepicker(self.getSingleStream(traceID),
nfac, (tnoise, tgap, tsignal),
self.getPick(traceID))
(self.pick[traceID]['epp'], self.pick[traceID]['lpp'],
self.pick[traceID]['spe']) = earllatepicker(self.getSingleStream(traceID),
nfac, (tnoise, tgap, tsignal),
self.getPickIncludeRemoved(traceID),
stealthMode = True)
def threshold(self, hoscf, aiccf, windowsize, pickwindow, folm = 0.6):
'''
Threshold picker, using the local maximum in a pickwindow to find the time at
Threshold picker, using the local maximum in a pickwindow to find the time at
which a fraction of the local maximum is reached for the first time.
:param: hoscf, Higher Order Statistics Characteristic Function
:type: 'Characteristic Function'
@ -337,34 +345,34 @@ class SeismicShot(object):
threshold = folm * max(hoscflist[leftb : rightb]) # combination of local maximum and threshold
m = leftb
while hoscflist[m] < threshold:
m += 1
hoscftime = list(hoscf.getTimeArray())[m]
lb = max(0, m - windowsize[0]) # if window exceeds t = 0
aiccfcut = list(aiccf.getCF())[lb : m + windowsize[1]]
n = aiccfcut.index(min(aiccfcut))
m = lb + n
aiccftime = list(hoscf.getTimeArray())[m]
return aiccftime, hoscftime
def getDistance(self, traceID):
'''
Returns the distance of the receiver with the ID == traceID to the source location (shot location).
Uses getSrcLoc and getRecLoc.
:param: traceID
:type: int
'''
shotX, shotY, shotZ = self.getSrcLoc()
recX, recY, recZ = self.getRecLoc(traceID)
dist = np.sqrt((shotX-recX)**2 + (shotY-recY)**2 + (shotZ-recZ)**2)
if np.isnan(dist) == True:
raise ValueError("Distance is NaN for traceID %s" %traceID)
@ -375,7 +383,7 @@ class SeismicShot(object):
'''
Returns the location (x, y, z) of the receiver with the ID == traceID.
RECEIVEIVER FILE MUST BE SET FIRST, TO BE IMPROVED.
:param: traceID
:type: int
'''
@ -389,7 +397,7 @@ class SeismicShot(object):
y = coordlist[i].split()[2]
z = coordlist[i].split()[3]
return float(x), float(y), float(z)
#print "WARNING: traceID %s not found" % traceID
raise ValueError("traceID %s not found" % traceID)
#return float(self.getSingleStream(traceID)[0].stats.seg2['RECEIVER_LOCATION'])
@ -412,7 +420,7 @@ class SeismicShot(object):
'''
Returns the traceID(s) for a certain distance between source and receiver.
Used for 2D Tomography. TO BE IMPROVED.
:param: distance
:type: real
@ -428,7 +436,7 @@ class SeismicShot(object):
if self.getDistance(traceID) == distance:
traceID_list.append(traceID)
if distancebin[0] >= 0 and distancebin[1] > 0:
if self.getDistance(traceID) > distancebin[0] and self.getDistance(traceID) < distancebin[1]:
if distancebin[0] < self.getDistance(traceID) < distancebin[1]:
traceID_list.append(traceID)
if len(traceID_list) > 0:
@ -437,7 +445,7 @@ class SeismicShot(object):
def setManualPicks(self, traceID, picklist): ########## picklist momentan nicht allgemein, nur testweise benutzt ##########
'''
Sets the manual picks for a receiver with the ID == traceID for comparison.
:param: traceID
:type: int
@ -452,21 +460,31 @@ class SeismicShot(object):
if not self.manualpicks.has_key(traceID):
self.manualpicks[traceID] = (mostlikely, earliest, latest)
#else:
# raise KeyError('MANUAL pick to be set more than once for traceID %s' % traceID)
# raise KeyError('MANUAL pick to be set more than once for traceID %s' % traceID)
def setPick(self, traceID, pick): ########## siehe Kommentar ##########
self.pick[traceID] = pick
if not traceID in self.pick.keys():
self.pick[traceID] = {}
self.pick[traceID]['mpp'] = pick
self.pick[traceID]['flag'] = 1
# ++++++++++++++ Block raus genommen, da Error beim 2ten Mal picken! (Ueberschreiben von erstem Pick!)
# if not self.pick.has_key(traceID):
# self.getPick(traceID) = picks
# else:
# raise KeyError('pick to be set more than once for traceID %s' % traceID)
# raise KeyError('pick to be set more than once for traceID %s' % traceID)
# def readParameter(self, parfile):
# parlist = open(parfile,'r').readlines()
def removePick(self, traceID):
self.setPick(traceID, None)
self.setFlag(traceID, 0)
def setFlag(self, traceID, flag):
'Set flag = 0 if pick is invalid, else flag = 1'
self.pick[traceID]['flag'] = flag
def getFlag(self, traceID):
return self.pick[traceID]['flag']
def setPickwindow(self, traceID, pickwindow):
self.pickwindow[traceID] = pickwindow
@ -474,12 +492,13 @@ class SeismicShot(object):
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()
@ -509,7 +528,7 @@ class SeismicShot(object):
# 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'
# '''
@ -517,7 +536,7 @@ class SeismicShot(object):
# plt.interactive('True')
# aictimearray = []
# hostimearray = []
# if dist_med is not 0:
# if dist_med is not 0:
# dist_medarray = []
# i = 1
@ -570,42 +589,89 @@ class SeismicShot(object):
# 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 matplotlib.widgets import Button
def onclick(event):
self.setPick(traceID, event.xdata)
self._drawStream(traceID, refresh = True)
self._drawCFs(traceID, folm, refresh = True)
fig.canvas.mpl_disconnect(self.traces4plot[traceID]['cid'])
plt.draw()
def connectButton(event = None):
cid = fig.canvas.mpl_connect('button_press_event', onclick)
self.traces4plot[traceID]['cid'] = cid
fig = plt.figure()
ax1 = fig.add_subplot(2,1,1)
ax2 = fig.add_subplot(2,1,2, sharex = ax1)
axb = fig.add_axes([0.15, 0.91, 0.05, 0.03])
button = Button(axb, 'repick', color = 'red', hovercolor = 'grey')
button.on_clicked(connectButton)
self.traces4plot = {}
if traceID not in self.traces4plot.keys():
self.traces4plot[traceID] = {'fig': fig,
'ax1': ax1,
'ax2': ax2,
'axb': axb,
'button': button,
'cid': None}
self._drawStream(traceID)
self._drawCFs(traceID, folm)
def _drawStream(self, traceID, refresh = False):
from pylot.core.util.utils import getGlobalTimes
from pylot.core.util.utils import prepTimeAxis
stream = self.getSingleStream(traceID)
stime = getGlobalTimes(stream)[0]
timeaxis = prepTimeAxis(stime, stream[0])
timeaxis = prepTimeAxis(stime, stream[0])
timeaxis -= stime
plt.interactive('True')
ax = self.traces4plot[traceID]['ax1']
if refresh == True:
xlim, ylim = ax.get_xlim(), ax.get_ylim()
ax.clear()
if refresh == True:
ax.set_xlim(xlim)
ax.set_ylim(ylim)
ax.set_title('Shot: %s, traceID: %s, pick: %s'
%(self.getShotnumber(), traceID, self.getPick(traceID)))
ax.plot(timeaxis, stream[0].data, 'k', label = 'trace')
ax.plot([self.getPick(traceID), self.getPick(traceID)],
[min(stream[0].data),
max(stream[0].data)],
'r', label = 'mostlikely')
ax.legend()
def _drawCFs(self, traceID, folm, refresh = False):
hoscf = self.getHOScf(traceID)
aiccf = self.getAICcf(traceID)
ax = self.traces4plot[traceID]['ax2']
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)],
if refresh == True:
xlim, ylim = ax.get_xlim(), ax.get_ylim()
ax.clear()
if refresh == True:
ax.set_xlim(xlim)
ax.set_ylim(ylim)
ax.plot(hoscf.getTimeArray(), hoscf.getCF(), 'b', label = 'HOS')
ax.plot(hoscf.getTimeArray(), aiccf.getCF(), 'g', label = 'AIC')
ax.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)],
ax.plot([0, self.getPick(traceID)],
[folm * max(hoscf.getCF()), folm * max(hoscf.getCF())],
'm:', label = 'folm = %s' %folm)
plt.xlabel('Time [s]')
plt.legend()
ax.set_xlabel('Time [s]')
ax.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.
@ -622,7 +688,6 @@ class SeismicShot(object):
: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
@ -631,20 +696,20 @@ class SeismicShot(object):
y = []
z = []
for traceID in self.pick.keys():
if self.getPick(traceID) != None:
if self.getFlag(traceID) != 0:
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)
xaxis = np.arange(min(x), max(x), step)
yaxis = np.arange(min(y), 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:
@ -656,13 +721,13 @@ class SeismicShot(object):
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):
def matshow(self, ax = None, step = 0.5, method = 'linear', plotRec = True, annotations = True, colorbar = True):
'''
Plots a 2D matrix of the interpolated traveltimes. This needs less performance than plot3dttc
@ -672,27 +737,32 @@ class SeismicShot(object):
:param: method (optional), interpolation method; can be 'linear' (default) or 'cubic'
:type: 'string'
:param: plotRec (optional), plot the receiver positions
:param: plotRec (optional), plot the receiver positions (colored scatter plot, should not be
deactivated because there might be receivers that are not inside the interpolated area)
: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 = []
x = []; xcut = []
y = []; ycut = []
z = []; zcut = []
tmin, tmax = self.getCut()
for traceID in self.pick.keys():
if self.getPick(traceID) != None:
if self.getFlag(traceID) != 0:
x.append(self.getRecLoc(traceID)[0])
y.append(self.getRecLoc(traceID)[1])
z.append(self.getPick(traceID))
if self.getFlag(traceID) == 0 and self.getPickIncludeRemoved(traceID) is not None:
xcut.append(self.getRecLoc(traceID)[0])
ycut.append(self.getRecLoc(traceID)[1])
zcut.append(self.getPickIncludeRemoved(traceID))
xaxis = np.arange(min(x)+1, max(x), step)
yaxis = np.arange(min(y)+1, max(y), step)
xaxis = np.arange(min(x), max(x), step)
yaxis = np.arange(min(y), max(y), step)
xgrid, ygrid = np.meshgrid(xaxis, yaxis)
zgrid = griddata((x, y), z, (xgrid, ygrid), method='linear')
@ -700,14 +770,28 @@ class SeismicShot(object):
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')
ax.matshow(zgrid, extent = [min(x), max(x), min(y), max(y)], origin = 'lower')
plt.text(0.45, 0.9, 'shot: %s' %self.getShotnumber(), transform = ax.transAxes)
sc = ax.scatter(x, y, c = z, s = 30, label = 'picked shots', vmin = tmin, vmax = tmax, linewidths = 1.5)
sccut = ax.scatter(xcut, ycut, c = zcut, s = 30, edgecolor = 'm', label = 'cut out shots', vmin = tmin, vmax = tmax, linewidths = 1.5)
if colorbar == True:
plt.colorbar(sc)
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.plot(self.getSrcLoc()[0], self.getSrcLoc()[1],'*k', markersize = 15) # plot source location
if plotRec == True:
ax.plot(x, y, 'k.')
ax.scatter(x, y, c = z, s = 30)
if annotations == True:
for traceID in self.getTraceIDlist():
if self.getFlag(traceID) is not 0:
ax.annotate(' %s' %traceID , xy = (self.getRecLoc(traceID)[0], self.getRecLoc(traceID)[1]),
fontsize = 'x-small', color = 'k')
else:
ax.annotate(' %s' %traceID , xy = (self.getRecLoc(traceID)[0], self.getRecLoc(traceID)[1]),
fontsize = 'x-small', color = 'r')
plt.show()

573
pylot/core/active/surveyPlotTools.py
View File

@ -1,48 +1,69 @@
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import math
import numpy as np
plt.interactive(True)
class regions(object):
def __init__(self, ax, shot_dict):
'''
A class used for manual inspection and processing of all picks for the user.
Examples:
regions.chooseRectangles():
- lets the user choose several rectangular regions in the plot
regions.plotTracesInActiveRegions():
- creates plots (shot.plot_traces) for all traces in the active regions (i.e. chosen by e.g. chooseRectangles)
regions.setAllActiveRegionsForDeletion():
- highlights all shots in a the active regions for deletion
regions.deleteAllMarkedPicks():
- deletes the picks (pick flag set to 0) for all shots set for deletion
regions.deselectSelection(number):
- deselects the region of number = number
'''
def __init__(self, ax, cbar, survey):
self.ax = ax
self.shot_dict = shot_dict
self.cbar = cbar
self.cbv = 'log10SNR'
self._xlim0 = self.ax.get_xlim()
self._ylim0 = self.ax.get_ylim()
self._xlim = self.ax.get_xlim()
self._ylim = self.ax.get_ylim()
self.survey = survey
self.shot_dict = self.survey.getShotDict()
self._x0 = []
self._y0 = []
self._x1 = []
self._y1 = []
self._polyx = []
self._polyy = []
self.buttons = {}
self._allpicks = None
self.shots_found = {}
self.shots_for_deletion = {}
self._generateList()
self._addButtons()
self.addTextfield()
self.drawFigure()
def _onselect(self, eclick, erelease):
'eclick and erelease are matplotlib events at press and release' #print ' startposition : (%f, %f)' % (eclick.xdata, eclick.ydata)
#print ' endposition : (%f, %f)' % (erelease.xdata, erelease.ydata)
print 'region selected x0, y0 = (%3s, %3s), x1, y1 = (%3s, %3s)'%(eclick.xdata, eclick.ydata, erelease.xdata, erelease.ydata)
x0 = min(eclick.xdata, erelease.xdata)
x1 = max(eclick.xdata, erelease.xdata)
y0 = min(eclick.ydata, erelease.ydata)
y1 = max(eclick.ydata, erelease.ydata)
self._x0.append(x0)
self._x1.append(x1)
self._y0.append(y0)
self._y1.append(y1)
self.markCurrentRegion(x0, x1, y0, y1)
def _generateList(self):
allpicks = []
for shot in self.shot_dict.values():
for traceID in shot.getTraceIDlist():
allpicks.append((shot.getDistance(traceID),
shot.getPickIncludeRemoved(traceID),
shot.getShotnumber(),
traceID,
shot.getFlag(traceID)))
def chooseRectangles(self):
from matplotlib.widgets import RectangleSelector
print 'Select rectangle is active'
return RectangleSelector(self.ax, self._onselect)
def _getx0(self):
return self._x0
def _getx1(self):
return self._x1
def _gety0(self):
return self._y0
def _gety1(self):
return self._y1
allpicks.sort()
self._allpicks = allpicks
def getShotDict(self):
return self.shot_dict
@ -50,119 +71,439 @@ class regions(object):
def getShotsForDeletion(self):
return self.shots_for_deletion
def findTracesInShotDict(self, picks = 'normal'):
'''
Returns traces corresponding to a certain area in a plot with all picks over the distances.
'''
print "findTracesInShotDict: Searching for marked traces in the shot dictionary... "
def _onselect_clicks(self, eclick, erelease):
'''eclick and erelease are matplotlib events at press and release'''
print 'region selected x0, y0 = (%3s, %3s), x1, y1 = (%3s, %3s)' % (eclick.xdata,
eclick.ydata,
erelease.xdata,
erelease.ydata)
x0 = min(eclick.xdata, erelease.xdata)
x1 = max(eclick.xdata, erelease.xdata)
y0 = min(eclick.ydata, erelease.ydata)
y1 = max(eclick.ydata, erelease.ydata)
for shot in self.shot_dict.values():
whichpicks = {'normal': shot.getPick,
'includeCutOut': shot.getPick_backup}
for index in range(len(self._getx1())):
distancebin = (self._getx0()[index], self._getx1()[index])
pickbin = (self._gety0()[index], self._gety1()[index])
if shot.getTraceIDs4Dist(distancebin = distancebin) is not None:
for traceID in shot.getTraceIDs4Dist(distancebin = distancebin):
if pickbin[0] < whichpicks[picks](traceID) < pickbin[1]:
shots, numtraces = self.findTracesInShotDict((x0, x1), (y0, y1))
self.printOutput('Found %d traces in rectangle: %s' % (numtraces, shots))
key = self.getKey()
self.shots_found[key] = {'shots': shots,
'selection': 'rect',
'xvalues': (x0, x1),
'yvalues': (y0, y1)}
self.markRectangle((x0, x1), (y0, y1), key)
self.disconnectRect()
def _onselect_verts(self, verts):
x = verts[0][0]
y = verts[0][1]
self._polyx.append(x)
self._polyy.append(y)
self.drawPolyLine()
def _onpress(self, event):
if event.button == 3:
self.disconnectPoly()
self.printOutput('Disconnected polygon selection')
def addTextfield(self, xpos = 0, ypos = 0.95, width = 1, height = 0.03):
self.axtext = self.ax.figure.add_axes([xpos,
ypos,
width,
height])
self.axtext.xaxis.set_visible(False)
self.axtext.yaxis.set_visible(False)
def writeInTextfield(self, text = None):
self.setXYlim(self.ax.get_xlim(), self.ax.get_ylim())
self.axtext.clear()
self.axtext.text(0.01, 0.5, text, verticalalignment='center', horizontalalignment='left')
self.drawFigure()
def _addButtons(self):
xpos1 = 0.13
xpos2 = 0.6
dx = 0.06
self.addButton('Rect', self.chooseRectangles, xpos=xpos1, color='white')
self.addButton('Poly', self.choosePolygon, xpos=xpos1 + dx, color='white')
self.addButton('Plot', self.plotTracesInActiveRegions, xpos=xpos1 + 2 * dx, color='yellow')
self.addButton('SNR', self.refreshLog10SNR, xpos=xpos1 + 3 * dx, color='cyan')
self.addButton('PE', self.refreshPickerror, xpos=xpos1 + 4 * dx, color='cyan')
self.addButton('SPE', self.refreshSPE, xpos=xpos1 + 5 * dx, color='cyan')
self.addButton('DesLst', self.deselectLastSelection, xpos=xpos2 + dx, color='green')
self.addButton('SelAll', self.setAllActiveRegionsForDeletion, xpos=xpos2 + 2 * dx)
self.addButton('DelAll', self.deleteAllMarkedPicks, xpos=xpos2 + 3 * dx, color='red')
def addButton(self, name, action, xpos, ypos = 0.91, color = None):
from matplotlib.widgets import Button
self.buttons[name] = {'ax': None,
'button': None,
'action': action,
'xpos': xpos}
ax = self.ax.figure.add_axes([xpos,
ypos,
0.05,
0.03])
button = Button(ax, name, color=color, hovercolor='grey')
button.on_clicked(action)
self.buttons[name]['ax'] = ax
self.buttons[name]['button'] = button
self.buttons[name]['xpos'] = xpos
def getKey(self):
if self.shots_found.keys() == []:
key = 1
else:
key = max(self.shots_found.keys()) + 1
return key
def drawPolyLine(self):
self.setXYlim(self.ax.get_xlim(), self.ax.get_ylim())
x = self._polyx
y = self._polyy
if len(x) >= 2 and len(y) >= 2:
self.ax.plot(x[-2:], y[-2:], 'k', alpha=0.1)
self.drawFigure()
def drawLastPolyLine(self):
self.setXYlim(self.ax.get_xlim(), self.ax.get_ylim())
x = self._polyx
y = self._polyy
if len(x) >= 2 and len(y) >= 2:
self.ax.plot((x[-1], x[0]), (y[-1], y[0]), 'k', alpha=0.1)
self.drawFigure()
def finishPolygon(self):
self.drawLastPolyLine()
x = self._polyx
y = self._polyy
self._polyx = []; self._polyy = []
key = self.getKey()
self.markPolygon(x, y, key = key)
shots, numtraces = self.findTracesInPoly(x, y)
self.shots_found[key] = {'shots': shots,
'selection': 'poly',
'xvalues': x,
'yvalues': y}
self.printOutput('Found %d traces in polygon: %s' % (numtraces, shots))
def printOutput(self, text):
print text
self.writeInTextfield(text)
def chooseRectangles(self, event = None):
'''
Activates matplotlib widget RectangleSelector.
'''
from matplotlib.widgets import RectangleSelector
if hasattr(self, '_cidPoly'):
self.disconnectPoly()
self.printOutput('Select rectangle is active. Press and hold left mousebutton.')
self._cidRect = None
self._cidRect = self.ax.figure.canvas.mpl_connect('button_press_event', self._onpress)
self._rectangle = RectangleSelector(self.ax, self._onselect_clicks)
return self._rectangle
def choosePolygon(self, event = None):
'''
Activates matplotlib widget LassoSelector.
'''
from matplotlib.widgets import LassoSelector
if hasattr(self, '_cidRect'):
self.disconnectRect()
self.printOutput('Select polygon is active. Add points with leftclick. Finish with rightclick.')
self._cidPoly = None
self._cidPoly = self.ax.figure.canvas.mpl_connect('button_press_event', self._onpress)
self._lasso = LassoSelector(self.ax, self._onselect_verts)
return self._lasso
def disconnectPoly(self, event = None):
if not hasattr(self, '_cidPoly'):
self.printOutput('no poly selection found')
return
self.ax.figure.canvas.mpl_disconnect(self._cidPoly)
del self._cidPoly
self.finishPolygon()
self._lasso.disconnect_events()
print 'disconnected poly selection\n'
def disconnectRect(self, event = None):
if not hasattr(self, '_cidRect'):
self.printOutput('no rectangle selection found')
return
self.ax.figure.canvas.mpl_disconnect(self._cidRect)
del self._cidRect
self._rectangle.disconnect_events()
print 'disconnected rectangle selection\n'
def deselectLastSelection(self, event = None):
if self.shots_found.keys() == []:
self.printOutput('No selection found.')
return
key = max(self.shots_found.keys())
self.deselectSelection(key)
def deselectSelection(self, key, color = 'green', alpha = 0.1):
if key not in self.shots_found.keys():
self.printOutput('No selection found.')
return
if color is not None:
if self.shots_found[key]['selection'] == 'rect':
self.markRectangle(self.shots_found[key]['xvalues'],
self.shots_found[key]['yvalues'],
key = key, color = color, alpha = alpha,
linewidth = 1)
elif self.shots_found[key]['selection'] == 'poly':
self.markPolygon(self.shots_found[key]['xvalues'],
self.shots_found[key]['yvalues'],
key = key, color = color, alpha = alpha,
linewidth = 1)
value = self.shots_found.pop(key)
self.printOutput('Deselected selection number %d' % key)
def findTracesInPoly(self, x, y, picks = 'normal', highlight = True):
def dotproduct(v1, v2):
return sum((a * b for a, b in zip(v1, v2)))
def getlength(v):
return math.sqrt(dotproduct(v, v))
def getangle(v1, v2):
return np.rad2deg(math.acos(dotproduct(v1, v2) / (getlength(v1) * getlength(v2))))
def insidePoly(x, y, pickX, pickY):
angle = 0
epsilon = 1e-07
for index in range(len(x)):
xval1 = x[index - 1]; yval1 = y[index - 1]
xval2 = x[index]; yval2 = y[index]
angle += getangle([xval1 - pickX, yval1 - pickY], [xval2 - pickX, yval2 - pickY])
if 360 - epsilon <= angle <= 360 + epsilon: ### IMPROVE THAT??
return True
if len(x) == 0 or len(y) == 0:
self.printOutput('No polygon defined.')
return
shots_found = {}; numtraces = 0
x0 = min(x); x1 = max(x)
y0 = min(y); y1 = max(y)
shots, numtracesrect = self.findTracesInShotDict((x0, x1), (y0, y1), highlight = False)
for shotnumber in shots.keys():
shot = self.shot_dict[shotnumber]
for traceID in shots[shotnumber]:
if shot.getFlag(traceID) is not 0:
pickX = shot.getDistance(traceID)
pickY = shot.getPick(traceID)
if insidePoly(x, y, pickX, pickY):
if shotnumber not in shots_found.keys():
shots_found[shotnumber] = []
shots_found[shotnumber].append(traceID)
if highlight == True:
self.highlightPick(shot, traceID)
if shot.getShotnumber() not in self.shots_found.keys():
self.shots_found[shot.getShotnumber()] = []
if traceID not in self.shots_found[shot.getShotnumber()]:
self.shots_found[shot.getShotnumber()].append(traceID)
self.refreshFigure()
print self.shots_found
numtraces += 1
self.drawFigure()
return shots_found, numtraces
def findTracesInShotDict(self, (x0, x1), (y0, y1), picks = 'normal', highlight = True):
'''
Returns traces corresponding to a certain area in the plot with all picks over the distances.
'''
shots_found = {}; numtraces = 0
if picks == 'normal': pickflag = 0
elif picks == 'includeCutOut': pickflag = None
for line in self._allpicks:
dist, pick, shotnumber, traceID, flag = line
if flag == pickflag: continue ### IMPROVE THAT
if (x0 <= dist <= x1 and y0 <= pick <= y1):
if shotnumber not in shots_found.keys():
shots_found[shotnumber] = []
shots_found[shotnumber].append(traceID)
if highlight == True:
self.highlightPick(self.shot_dict[shotnumber], traceID)
numtraces += 1
self.drawFigure()
return shots_found, numtraces
def highlightPick(self, shot, traceID, annotations = True):
'''
Highlights a single pick for a shot(object)/shotnumber and traceID.
If annotations == True: Displays shotnumber and traceID in the plot.
'''
if type(shot) == int:
shot = self.survey.getShotDict()[shot]
self.ax.scatter(shot.getDistance(traceID), shot.getPick(traceID), s = 50, marker = 'o', facecolors = 'none', edgecolors = 'm', alpha = 1)
if annotations == True:
self.ax.annotate(s = 's%s|t%s'%(shot.getShotnumber(), traceID), xy = (shot.getDistance(traceID), shot.getPick(traceID)), fontsize = 'xx-small')
self.ax.set_ylim(shot.getCut())
self.ax.annotate(s='s%s|t%s' % (shot.getShotnumber(), traceID), xy=(shot.getDistance(traceID), shot.getPick(traceID)), fontsize='xx-small')
def plotTracesInRegion(self):
def highlightAllActiveRegions(self):
'''
Highlights all picks in all active regions.
'''
for key in self.shots_found.keys():
for shotnumber in self.shots_found[key]['shots'].keys():
for traceID in self.shots_found[key]['shots'][shotnumber]:
self.highlightPick(self.shot_dict[shotnumber], traceID)
self.drawFigure()
def plotTracesInActiveRegions(self, event = None, keys = 'all', maxfigures = 20):
'''
Plots all traces in the active region or for all specified keys.
:param: keys
:type: int or list
:param: maxfigures, maximum value of figures opened
:type: int
'''
count = 0
maxfigures = 20
# if len(self.shots_found) == 0:
self.findTracesInShotDict()
if keys == 'all':
keys = self.shots_found.keys()
elif type(keys) == int:
keys = [keys]
if len(self.shots_found) > 0:
for shot in self.shot_dict.values():
for shotnumber in self.shots_found:
if shot.getShotnumber() == shotnumber:
for traceID in self.shots_found[shotnumber]:
count += 1
if count > maxfigures:
print 'Maximum number of figures (%s) reached. %sth figure was not opened.' %(maxfigures, count)
break
shot.plot_traces(traceID)
for key in keys:
for shotnumber in self.shots_found[key]['shots']:
if shot.getShotnumber() == shotnumber:
for traceID in self.shots_found[key]['shots'][shotnumber]:
count += 1
if count > maxfigures:
print 'Maximum number of figures (%s) reached. %sth figure was not opened.' %(maxfigures, count)
break
shot.plot_traces(traceID)
else:
print 'No picks yet defined in the regions x = (%s, %s), y = (%s, %s)' %(self._x0, self._x1, self._y0, self._y1)
self.printOutput('No picks defined in that region(s)')
def plotTracesInRegion_withCutOutTraces(self):
count = 0
maxfigures = 20
# if len(self.shots_found) == 0:
self.findTracesInShotDict(picks = 'includeCutOut')
def setAllActiveRegionsForDeletion(self, event = None):
keys = []
for key in self.shots_found.keys():
keys.append(key)
self.setRegionForDeletion(keys)
if len(self.shots_found) > 0:
for shot in self.shot_dict.values():
for shotnumber in self.shots_found:
if shot.getShotnumber() == shotnumber:
for traceID in self.shots_found[shotnumber]:
count += 1
if count > maxfigures:
print 'Maximum number of figures (%s) reached. %sth figure was not opened.' %(maxfigures, count)
break
shot.plot_traces(traceID)
else:
print 'No picks yet defined in the regions x = (%s, %s), y = (%s, %s)' %(self._x0, self._x1, self._y0, self._y1)
def setRegionForDeletion(self, keys):
if type(keys) == int:
keys = [keys]
def setCurrentRegionsForDeletion(self):
# if len(self.shots_found) == 0:
self.findTracesInShotDict()
for key in keys:
for shotnumber in self.shots_found[key]['shots'].keys():
if shotnumber not in self.shots_for_deletion:
self.shots_for_deletion[shotnumber] = []
for traceID in self.shots_found[key]['shots'][shotnumber]:
if traceID not in self.shots_for_deletion[shotnumber]:
self.shots_for_deletion[shotnumber].append(traceID)
self.deselectSelection(key, color = 'red', alpha = 0.2)
for shotnumber in self.shots_found:
if not shotnumber in self.shots_for_deletion:
self.shots_for_deletion[shotnumber] = []
for traceID in self.shots_found[shotnumber]:
if not traceID in self.shots_for_deletion[shotnumber]:
self.shots_for_deletion[shotnumber].append(traceID)
self.markAllRegions(color = 'red')
print 'Marked regions for deletion'
self.deselectSelection(key, color='red', alpha=0.2)
def markAllRegions(self, color = 'grey'):
self.printOutput('Set region(s) %s for deletion' % keys)
def markAllActiveRegions(self):
for key in self.shots_found.keys():
if self.shots_found[key]['selection'] == 'rect':
self.markRectangle(self.shots_found[key]['xvalues'],
self.shots_found[key]['yvalues'], key = key)
if self.shots_found[key]['selection'] == 'poly':
self.markPolygon(self.shots_found[key]['xvalues'],
self.shots_found[key]['yvalues'], key = key)
def markRectangle(self, (x0, x1), (y0, y1), key = None, color = 'grey', alpha = 0.1, linewidth = 1):
'''
Mark a rectangular region on the axes.
'''
from matplotlib.patches import Rectangle
self.ax.add_patch(Rectangle((x0, y0), x1 - x0, y1 - y0, alpha=alpha, facecolor=color, linewidth=linewidth))
if key is not None:
self.ax.text(x0 + (x1 - x0) / 2, y0 + (y1 - y0) / 2, str(key))
self.drawFigure()
for index in range(len(self._getx0())):
x0 = self._getx0()[index]
y0 = self._gety0()[index]
x1 = self._getx1()[index]
y1 = self._gety1()[index]
def markPolygon(self, x, y, key = None, color = 'grey', alpha = 0.1, linewidth = 1):
from matplotlib.patches import Polygon
poly = Polygon(np.array(zip(x, y)), color=color, alpha=alpha, lw=linewidth)
self.ax.add_patch(poly)
if key is not None:
self.ax.text(min(x) + (max(x) - min(x)) / 2, min(y) + (max(y) - min(y)) / 2, str(key))
self.drawFigure()
self.ax.add_patch(Rectangle((x0, y0), (x1 - x0), (y1 - y0), alpha=0.5, facecolor = color))
self.refreshFigure()
def clearShotsForDeletion(self):
'''
Clears the list of shots marked for deletion.
'''
self.shots_for_deletion = {}
print('Cleared all shots that were set for deletion.')
def markCurrentRegion(self, x0, x1, y0, y1, color = 'grey'):
from matplotlib.patches import Rectangle
def getShotsForDeletion(self):
return self.shots_for_deletion
self.ax.add_patch(Rectangle((x0, y0), (x1 - x0), (y1 - y0), alpha=0.1, facecolor = color))
self.refreshFigure()
def deleteAllMarkedPicks(self, event = None):
'''
Deletes all shots set for deletion.
'''
if len(self.getShotsForDeletion()) is 0:
self.printOutput('No shots set for deletion.')
return
def deleteMarkedPicks(self):
for shot in self.getShotDict().values():
for shotnumber in self.getShotsForDeletion():
if shot.getShotnumber() == shotnumber:
for traceID in self.getShotsForDeletion()[shotnumber]:
shot.removePick(traceID)
print "Deleted the pick for traceID %s on shot number %s" %(traceID, shotnumber)
self.shots_for_deletion = {} # clear dictionary
def highlightPicksForShot(self, shot, annotations = False):
for traceID in shot.getTraceIDlist():
if shot.getPick(traceID) is not None:
self.highlightPick(shot, traceID, annotations)
self.clearShotsForDeletion()
self.refreshFigure()
def refreshFigure(self):
def highlightPicksForShot(self, shot, annotations = False):
'''
Highlight all picks for a given shot.
'''
if type(shot) is int:
shot = self.survey.getShotDict()[shotnumber]
for traceID in shot.getTraceIDlist():
if shot.getFlag(traceID) is not 0:
self.highlightPick(shot, traceID, annotations)
self.drawFigure()
def setXYlim(self, xlim, ylim):
self._xlim, self._ylim = xlim, ylim
def refreshLog10SNR(self, event = None):
cbv = 'log10SNR'
self.refreshFigure(self, colorByVal=cbv)
def refreshPickerror(self, event = None):
cbv = 'pickerror'
self.refreshFigure(self, colorByVal=cbv)
def refreshSPE(self, event = None):
cbv = 'spe'
self.refreshFigure(self, colorByVal=cbv)
def refreshFigure(self, event = None, colorByVal = None):
if colorByVal == None:
colorByVal = self.cbv
else:
self.cbv = colorByVal
self.printOutput('Refreshing figure...')
self.ax.clear()
self.ax = self.survey.plotAllPicks(ax=self.ax, cbar=self.cbar, refreshPlot=True, colorByVal=colorByVal)
self.setXYlim(self.ax.get_xlim(), self.ax.get_ylim())
self.markAllActiveRegions()
self.highlightAllActiveRegions()
self.drawFigure()
self.printOutput('Done!')
def drawFigure(self, resetAxes = True):
if resetAxes == True:
self.ax.set_xlim(self._xlim)
self.ax.set_ylim(self._ylim)
plt.draw()

28
pylot/core/active/surveyUtils.py
View File

@ -1,19 +1,21 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
def readParameters(parfile, parameter):
from ConfigParser import ConfigParser
parameterConfig = ConfigParser()
parameterConfig.read('parfile')
value = parameterConfig.get('vars', parameter).split('#')[0]
value = value.replace(" ", "")
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 = []
@ -23,7 +25,7 @@ def fitSNR4dist(shot_dict, shiftdist = 5):
for traceID in shot.getTraceIDlist():
if shot.getSNR(traceID)[0] >= 1:
dists.append(shot.getDistance(traceID))
picks.append(shot.getPick_backup(traceID))
picks.append(shot.getPickIncludeRemoved(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)
@ -34,6 +36,7 @@ def fitSNR4dist(shot_dict, shiftdist = 5):
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)
@ -45,25 +48,28 @@ def plotFittedSNR(dists, snrthresholds, snrs):
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 "\nsetFittedSNR: Finished setting of fitted SNR-threshold"
print "setFittedSNR: Finished setting of fitted SNR-threshold"
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():

1
pylot/core/analysis/__init__.py
View File

@ -0,0 +1 @@
# -*- coding: utf-8 -*-

4
pylot/core/analysis/coinctimes.py
View File

@ -6,7 +6,7 @@ from obspy.signal.trigger import coincidenceTrigger
class CoincidenceTimes():
class CoincidenceTimes(object):
def __init__(self, st, comp='Z', coinum=4, sta=1., lta=10., on=5., off=1.):
_type = 'recstalta'
@ -54,4 +54,4 @@ def main():
if __name__ == '__main__':
main()
main()

45
pylot/core/analysis/magnitude.py
View File

@ -1,3 +1,4 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created August/September 2015.
@ -34,7 +35,7 @@ class Magnitude(object):
:type: integer
'''
assert isinstance(wfstream, Stream), "%s is not a stream object" % str(wfstream)
self.setwfstream(wfstream)
@ -62,7 +63,7 @@ class Magnitude(object):
def setpwin(self, pwin):
self.pwin = pwin
def getiplot(self):
return self.iplot
@ -71,7 +72,7 @@ class Magnitude(object):
def getwapp(self):
return self.wapp
def getw0(self):
return self.w0
@ -103,7 +104,7 @@ class WApp(Magnitude):
'poles': [5.6089 - 5.4978j, -5.6089 - 5.4978j],
'zeros': [0j, 0j],
'gain': 2080,
'sensitivity': 1}
'sensitivity': 1}
stream.simulate(paz_remove=None, paz_simulate=paz_wa)
@ -133,19 +134,19 @@ class WApp(Magnitude):
raw_input()
plt.close(f)
class DCfc(Magnitude):
'''
Method to calculate the source spectrum and to derive from that the plateau
(so-called DC-value) and the corner frequency assuming Aki's omega-square
Method to calculate the source spectrum and to derive from that the plateau
(so-called DC-value) and the corner frequency assuming Aki's omega-square
source model. Has to be derived from instrument corrected displacement traces!
'''
def calcsourcespec(self):
print ("Calculating source spectrum ....")
print ("Calculating source spectrum ....")
self.w0 = None # DC-value
self.fc = None # corner frequency
self.fc = None # corner frequency
stream = self.getwfstream()
tr = stream[0]
@ -155,7 +156,7 @@ class DCfc(Magnitude):
iwin = getsignalwin(t, self.getTo(), self.getpwin())
xdat = tr.data[iwin]
# fft
# fft
fny = tr.stats.sampling_rate / 2
l = len(xdat) / tr.stats.sampling_rate
n = tr.stats.sampling_rate * l # number of fft bins after Bath
@ -167,7 +168,7 @@ class DCfc(Magnitude):
L = (N - 1) / tr.stats.sampling_rate
f = np.arange(0, fny, 1/L)
# remove zero-frequency and frequencies above
# remove zero-frequency and frequencies above
# corner frequency of seismometer (assumed
# to be 100 Hz)
fi = np.where((f >= 1) & (f < 100))
@ -184,18 +185,16 @@ class DCfc(Magnitude):
[optspecfit, pcov] = curve_fit(synthsourcespec, F, YY.real, [DCin, Fcin])
self.w0 = optspecfit[0]
self.fc = optspecfit[1]
print ("DCfc: Determined DC-value: %e m/Hz, \n" \
"Determined corner frequency: %f Hz" % (self.w0, self.fc))
#if self.getiplot() > 1:
iplot=2
if iplot > 1:
print ("DCfc: Determined DC-value: %e m/Hz, \n"
"Determined corner frequency: %f Hz" % (self.w0, self.fc))
if self.getiplot() > 1:
f1 = plt.figure()
plt.subplot(2,1,1)
# show displacement in mm
plt.plot(t, np.multiply(tr, 1000), 'k')
plt.plot(t[iwin], np.multiply(xdat, 1000), 'g')
plt.plot(t, np.multiply(tr, 1000), 'k')
plt.plot(t[iwin], np.multiply(xdat, 1000), 'g')
plt.title('Seismogram and P pulse, station %s' % tr.stats.station)
plt.xlabel('Time since %s' % tr.stats.starttime)
plt.ylabel('Displacement [mm]')
@ -216,8 +215,8 @@ class DCfc(Magnitude):
def synthsourcespec(f, omega0, fcorner):
'''
Calculates synthetic source spectrum from given plateau and corner
frequency assuming Akis omega-square model.
Calculates synthetic source spectrum from given plateau and corner
frequency assuming Akis omega-square model.
:param: f, frequencies
:type: array
@ -228,7 +227,7 @@ def synthsourcespec(f, omega0, fcorner):
:param: fcorner, corner frequency of source spectrum
:type: float
'''
#ssp = omega0 / (pow(2, (1 + f / fcorner)))
ssp = omega0 / (1 + pow(2, (f / fcorner)))

72
pylot/core/pick/CharFuns.py
View File

@ -1,3 +1,4 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created Oct/Nov 2014
@ -24,7 +25,7 @@ class CharacteristicFunction(object):
'''
SuperClass for different types of characteristic functions.
'''
def __init__(self, data, cut, t2=None, order=None, t1=None, fnoise=None):
def __init__(self, data, cut, t2=None, order=None, t1=None, fnoise=None, stealthMode=False):
'''
Initialize data type object with information from the original
Seismogram.
@ -61,6 +62,7 @@ class CharacteristicFunction(object):
self.calcCF(self.getDataArray())
self.arpara = np.array([])
self.xpred = np.array([])
self._stealthMode = stealthMode
def __str__(self):
return '''\n\t{name} object:\n
@ -119,7 +121,7 @@ class CharacteristicFunction(object):
def getTimeArray(self):
incr = self.getIncrement()
self.TimeArray = np.arange(0, len(self.getCF()) * incr, incr) + self.getCut()[0]
self.TimeArray = np.arange(0, len(self.getCF()) * incr, incr) + self.getCut()[0]
return self.TimeArray
def getFnoise(self):
@ -134,6 +136,9 @@ class CharacteristicFunction(object):
def getXCF(self):
return self.xcf
def _getStealthMode(self):
return self._stealthMode()
def getDataArray(self, cut=None):
'''
If cut times are given, time series is cut from cut[0] (start time)
@ -164,31 +169,31 @@ class CharacteristicFunction(object):
stop = min([len(self.orig_data[0]), len(self.orig_data[1])])
elif self.cut[0] == 0 and self.cut[1] is not 0:
start = 0
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]), \
len(self.orig_data[1])])
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
len(self.orig_data[1])])
else:
start = max([0, self.cut[0] / self.dt])
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]), \
len(self.orig_data[1])])
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
len(self.orig_data[1])])
hh = self.orig_data.copy()
h1 = hh[0].copy()
h2 = hh[1].copy()
hh[0].data = h1.data[int(start):int(stop)]
hh[1].data = h2.data[int(start):int(stop)]
data = hh
data = hh
return data
elif len(self.orig_data) == 3:
if self.cut[0] == 0 and self.cut[1] == 0:
start = 0
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]), \
len(self.orig_data[1]), len(self.orig_data[2])])
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
len(self.orig_data[1]), len(self.orig_data[2])])
elif self.cut[0] == 0 and self.cut[1] is not 0:
start = 0
stop = self.cut[1] / self.dt
else:
start = max([0, self.cut[0] / self.dt])
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]), \
len(self.orig_data[1]), len(self.orig_data[2])])
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
len(self.orig_data[1]), len(self.orig_data[2])])
hh = self.orig_data.copy()
h1 = hh[0].copy()
h2 = hh[1].copy()
@ -196,12 +201,12 @@ class CharacteristicFunction(object):
hh[0].data = h1.data[int(start):int(stop)]
hh[1].data = h2.data[int(start):int(stop)]
hh[2].data = h3.data[int(start):int(stop)]
data = hh
data = hh
return data
else:
data = self.orig_data.copy()
return data
def calcCF(self, data=None):
self.cf = data
@ -218,7 +223,8 @@ class AICcf(CharacteristicFunction):
def calcCF(self, data):
#print 'Calculating AIC ...' ## MP MP output suppressed
#if self._getStealthMode() is False:
# print 'Calculating AIC ...'
x = self.getDataArray()
xnp = x[0].data
nn = np.isnan(xnp)
@ -230,7 +236,7 @@ class AICcf(CharacteristicFunction):
cumsumcf = np.cumsum(np.power(xnp, 2))
i = np.where(cumsumcf == 0)
cumsumcf[i] = np.finfo(np.float64).eps
cf[k] = ((k - 1) * np.log(cumsumcf[k] / k) + (datlen - k + 1) * \
cf[k] = ((k - 1) * np.log(cumsumcf[k] / k) + (datlen - k + 1) *
np.log((cumsumcf[datlen - 1] - cumsumcf[k - 1]) / (datlen - k + 1)))
cf[0] = cf[1]
inf = np.isinf(cf)
@ -256,11 +262,13 @@ class HOScf(CharacteristicFunction):
if len(nn) > 1:
xnp[nn] = 0
if self.getOrder() == 3: # this is skewness
print 'Calculating skewness ...'
#if self._getStealthMode() is False:
# print 'Calculating skewness ...'
y = np.power(xnp, 3)
y1 = np.power(xnp, 2)
elif self.getOrder() == 4: # this is kurtosis
#print 'Calculating kurtosis ...' ## MP MP output suppressed
#if self._getStealthMode() is False:
# print 'Calculating kurtosis ...'
y = np.power(xnp, 4)
y1 = np.power(xnp, 2)
@ -285,7 +293,7 @@ class HOScf(CharacteristicFunction):
LTA[j] = lta / np.power(lta1, 1.5)
elif self.getOrder() == 4:
LTA[j] = lta / np.power(lta1, 2)
nn = np.isnan(LTA)
if len(nn) > 1:
LTA[nn] = 0
@ -315,7 +323,7 @@ class ARZcf(CharacteristicFunction):
cf = np.zeros(len(xnp))
loopstep = self.getARdetStep()
arcalci = ldet + self.getOrder() #AR-calculation index
for i in range(ldet + self.getOrder(), tend - lpred - 1):
for i in range(ldet + self.getOrder(), tend - lpred - 1):
if i == arcalci:
#determination of AR coefficients
#to speed up calculation, AR-coefficients are calculated only every i+loopstep[1]!
@ -362,7 +370,7 @@ class ARZcf(CharacteristicFunction):
rhs = np.zeros(self.getOrder())
for k in range(0, self.getOrder()):
for i in range(rind, ldet+1):
ki = k + 1
ki = k + 1
rhs[k] = rhs[k] + data[i] * data[i - ki]
#recursive calculation of data array (second sum at left part of eq. 6.5 in Kueperkoch et al. 2012)
@ -382,7 +390,7 @@ class ARZcf(CharacteristicFunction):
def arPredZ(self, data, arpara, rind, lpred):
'''
Function to predict waveform, assuming an autoregressive process of order
p (=size(arpara)), with AR parameters arpara calculated in arDet. After
p (=size(arpara)), with AR parameters arpara calculated in arDet. After
Thomas Meier (CAU), published in Kueperkoch et al. (2012).
:param: data, time series to be predicted
:type: array
@ -400,9 +408,9 @@ class ARZcf(CharacteristicFunction):
'''
#be sure of the summation indeces
if rind < len(arpara):
rind = len(arpara)
rind = len(arpara)
if rind > len(data) - lpred :
rind = len(data) - lpred
rind = len(data) - lpred
if lpred < 1:
lpred = 1
if lpred > len(data) - 2:
@ -422,7 +430,7 @@ class ARHcf(CharacteristicFunction):
def calcCF(self, data):
print 'Calculating AR-prediction error from both horizontal traces ...'
xnp = self.getDataArray(self.getCut())
n0 = np.isnan(xnp[0].data)
if len(n0) > 1:
@ -430,7 +438,7 @@ class ARHcf(CharacteristicFunction):
n1 = np.isnan(xnp[1].data)
if len(n1) > 1:
xnp[1].data[n1] = 0
#some parameters needed
#add noise to time series
xenoise = xnp[0].data + np.random.normal(0.0, 1.0, len(xnp[0].data)) * self.getFnoise() * max(abs(xnp[0].data))
@ -441,7 +449,7 @@ class ARHcf(CharacteristicFunction):
#Time2: length of AR-prediction window [sec]
ldet = int(round(self.getTime1() / self.getIncrement())) #length of AR-determination window [samples]
lpred = int(np.ceil(self.getTime2() / self.getIncrement())) #length of AR-prediction window [samples]
cf = np.zeros(len(xenoise))
loopstep = self.getARdetStep()
arcalci = lpred + self.getOrder() - 1 #AR-calculation index
@ -515,7 +523,7 @@ class ARHcf(CharacteristicFunction):
def arPredH(self, data, arpara, rind, lpred):
'''
Function to predict waveform, assuming an autoregressive process of order
p (=size(arpara)), with AR parameters arpara calculated in arDet. After
p (=size(arpara)), with AR parameters arpara calculated in arDet. After
Thomas Meier (CAU), published in Kueperkoch et al. (2012).
:param: data, horizontal component seismograms to be predicted
:type: structured array
@ -558,7 +566,7 @@ class AR3Ccf(CharacteristicFunction):
def calcCF(self, data):
print 'Calculating AR-prediction error from all 3 components ...'
xnp = self.getDataArray(self.getCut())
n0 = np.isnan(xnp[0].data)
if len(n0) > 1:
@ -569,7 +577,7 @@ class AR3Ccf(CharacteristicFunction):
n2 = np.isnan(xnp[2].data)
if len(n2) > 1:
xnp[2].data[n2] = 0
#some parameters needed
#add noise to time series
xenoise = xnp[0].data + np.random.normal(0.0, 1.0, len(xnp[0].data)) * self.getFnoise() * max(abs(xnp[0].data))
@ -581,7 +589,7 @@ class AR3Ccf(CharacteristicFunction):
#Time2: length of AR-prediction window [sec]
ldet = int(round(self.getTime1() / self.getIncrement())) #length of AR-determination window [samples]
lpred = int(np.ceil(self.getTime2() / self.getIncrement())) #length of AR-prediction window [samples]
cf = np.zeros(len(xenoise))
loopstep = self.getARdetStep()
arcalci = ldet + self.getOrder() - 1 #AR-calculation index
@ -616,7 +624,7 @@ class AR3Ccf(CharacteristicFunction):
Function to calculate AR parameters arpara after Thomas Meier (CAU), published
in Kueperkoch et al. (2012). This function solves SLE using the Moore-
Penrose inverse, i.e. the least-squares approach. "data" is a structured array.
AR parameters are calculated based on both horizontal components and vertical
AR parameters are calculated based on both horizontal components and vertical
componant.
:param: data, horizontal component seismograms to calculate AR parameters from
:type: structured array
@ -658,7 +666,7 @@ class AR3Ccf(CharacteristicFunction):
def arPred3C(self, data, arpara, rind, lpred):
'''
Function to predict waveform, assuming an autoregressive process of order
p (=size(arpara)), with AR parameters arpara calculated in arDet3C. After
p (=size(arpara)), with AR parameters arpara calculated in arDet3C. After
Thomas Meier (CAU), published in Kueperkoch et al. (2012).
:param: data, horizontal and vertical component seismograms to be predicted
:type: structured array

2
pylot/core/pick/Picker.py
View File

@ -312,7 +312,7 @@ class PragPicker(AutoPicking):
else:
for i in range(1, len(self.cf)):
if i > ismooth:
ii1 = i - ismooth;
ii1 = i - ismooth
cfsmooth[i] = cfsmooth[i - 1] + (self.cf[i] - self.cf[ii1]) / ismooth
else:
cfsmooth[i] = np.mean(self.cf[1 : i])

3
pylot/core/pick/__init__.py
View File

@ -1 +1,2 @@
#
# -*- coding: utf-8 -*-
#

80
pylot/core/pick/autopick.py
View File

@ -204,27 +204,27 @@ def autopickstation(wfstream, pickparam):
if len(ndat) == 0 or len(edat) == 0:
print ("One or more horizontal components missing!")
print ("Signal length only checked on vertical component!")
print ("Decreasing minsiglengh from %f to %f" \
% (minsiglength, minsiglength / 2))
print ("Decreasing minsiglengh from %f to %f"
% (minsiglength, minsiglength / 2))
Pflag = checksignallength(zne, aicpick.getpick(), tsnrz,
minsiglength / 2, \
minsiglength / 2,
nfacsl, minpercent, iplot)
else:
# filter and taper horizontal traces
trH1_filt = edat.copy()
trH2_filt = ndat.copy()
trH1_filt.filter('bandpass', freqmin=bph1[0],
freqmax=bph1[1], \
zerophase=False)
freqmax=bph1[1],
zerophase=False)
trH2_filt.filter('bandpass', freqmin=bph1[0],
freqmax=bph1[1], \
zerophase=False)
freqmax=bph1[1],
zerophase=False)
trH1_filt.taper(max_percentage=0.05, type='hann')
trH2_filt.taper(max_percentage=0.05, type='hann')
zne += trH1_filt
zne += trH2_filt
Pflag = checksignallength(zne, aicpick.getpick(), tsnrz,
minsiglength, \
minsiglength,
nfacsl, minpercent, iplot)
if Pflag == 1:
@ -234,7 +234,7 @@ def autopickstation(wfstream, pickparam):
print 'One or more horizontal components missing!'
print 'Skipping control function checkZ4S.'
else:
Pflag = checkZ4S(zne, aicpick.getpick(), zfac, \
Pflag = checkZ4S(zne, aicpick.getpick(), zfac,
tsnrz[3], iplot)
if Pflag == 0:
Pmarker = 'SinsteadP'
@ -317,31 +317,31 @@ def autopickstation(wfstream, pickparam):
data = Data()
[corzdat, restflag] = data.restituteWFData(invdir, zdat)
if restflag == 1:
# integrate to displacement
corintzdat = integrate.cumtrapz(corzdat[0], None, corzdat[0].stats.delta)
# class needs stream object => build it
z_copy = zdat.copy()
z_copy[0].data = corintzdat
# largest detectable period == window length
# after P pulse for calculating source spectrum
winzc = (1 / bpz2[0]) * z_copy[0].stats.sampling_rate
impickP = mpickP * z_copy[0].stats.sampling_rate
wfzc = z_copy[0].data[impickP : impickP + winzc]
# calculate spectrum using only first cycles of
# waveform after P onset!
zc = crossings_nonzero_all(wfzc)
if np.size(zc) == 0:
print ("Something is wrong with the waveform, " \
"no zero crossings derived!")
print ("Cannot calculate source spectrum!")
else:
calcwin = (zc[3] - zc[0]) * z_copy[0].stats.delta
# calculate source spectrum and get w0 and fc
specpara = DCfc(z_copy, mpickP, calcwin, iplot)
w0 = specpara.getw0()
fc = specpara.getfc()
# integrate to displacement
corintzdat = integrate.cumtrapz(corzdat[0], None, corzdat[0].stats.delta)
# class needs stream object => build it
z_copy = zdat.copy()
z_copy[0].data = corintzdat
# largest detectable period == window length
# after P pulse for calculating source spectrum
winzc = (1 / bpz2[0]) * z_copy[0].stats.sampling_rate
impickP = mpickP * z_copy[0].stats.sampling_rate
wfzc = z_copy[0].data[impickP : impickP + winzc]
# calculate spectrum using only first cycles of
# waveform after P onset!
zc = crossings_nonzero_all(wfzc)
if np.size(zc) == 0:
print ("Something is wrong with the waveform, "
"no zero crossings derived!")
print ("Cannot calculate source spectrum!")
else:
calcwin = (zc[3] - zc[0]) * z_copy[0].stats.delta
# calculate source spectrum and get w0 and fc
specpara = DCfc(z_copy, mpickP, calcwin, iplot)
w0 = specpara.getw0()
fc = specpara.getfc()
print ("autopickstation: P-weight: %d, SNR: %f, SNR[dB]: %f, " \
print ("autopickstation: P-weight: %d, SNR: %f, SNR[dB]: %f, "
"Polarity: %s" % (Pweight, SNRP, SNRPdB, FM))
Sflag = 1
@ -352,7 +352,7 @@ def autopickstation(wfstream, pickparam):
Sflag = 0
else:
print ("autopickstation: No vertical component data available!, " \
print ("autopickstation: No vertical component data available!, "
"Skipping station!")
if edat is not None and ndat is not None and len(edat) > 0 and len(
@ -560,7 +560,7 @@ def autopickstation(wfstream, pickparam):
hdat += ndat
h_copy = hdat.copy()
[cordat, restflag] = data.restituteWFData(invdir, h_copy)
# calculate WA-peak-to-peak amplitude
# calculate WA-peak-to-peak amplitude
# using subclass WApp of superclass Magnitude
if restflag == 1:
if Sweight < 4:
@ -591,10 +591,10 @@ def autopickstation(wfstream, pickparam):
h_copy = hdat.copy()
[cordat, restflag] = data.restituteWFData(invdir, h_copy)
if restflag == 1:
# calculate WA-peak-to-peak amplitude
# calculate WA-peak-to-peak amplitude
# using subclass WApp of superclass Magnitude
wapp = WApp(cordat, mpickP, mpickP + sstop + (0.5 * (mpickP \
+ sstop)), iplot)
wapp = WApp(cordat, mpickP, mpickP + sstop + (0.5 * (mpickP
+ sstop)), iplot)
Ao = wapp.getwapp()
else:
@ -771,14 +771,14 @@ def autopickstation(wfstream, pickparam):
# create dictionary
# for P phase
phase = 'P'
phasepick = {'lpp': lpickP, 'epp': epickP, 'mpp': mpickP, 'spe': Perror, \
phasepick = {'lpp': lpickP, 'epp': epickP, 'mpp': mpickP, 'spe': Perror,
'snr': SNRP, 'snrdb': SNRPdB, 'weight': Pweight, 'fm': FM}
picks = {phase: phasepick}
# add P marker
picks[phase]['marked'] = Pmarker
# add S phase
phase = 'S'
phasepick = {'lpp': lpickS, 'epp': epickS, 'mpp': mpickS, 'spe': Serror, \
phasepick = {'lpp': lpickS, 'epp': epickS, 'mpp': mpickS, 'spe': Serror,
'snr': SNRS, 'snrdb': SNRSdB, 'weight': Sweight, 'fm': None}
picks[phase] = phasepick
# add Wood-Anderson amplitude

32
pylot/core/pick/run_makeCF.py
View File

@ -6,8 +6,8 @@
Only for test purposes!
"""
from obspy.core import read
import matplotlib.pyplot as plt
from obspy.core import read
import matplotlib.pyplot as plt
import numpy as np
from pylot.core.pick.CharFuns import CharacteristicFunction
from pylot.core.pick.Picker import AutoPicking
@ -56,7 +56,7 @@ def run_makeCF(project, database, event, iplot, station=None):
st_copy = st.copy()
#filter and taper data
tr_filt = st[0].copy()
tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
tr_filt.taper(max_percentage=0.05, type='hann')
st_copy[0].data = tr_filt.data
##############################################################
@ -120,8 +120,8 @@ def run_makeCF(project, database, event, iplot, station=None):
#filter and taper data
trH1_filt = H[0].copy()
trH2_filt = H[1].copy()
trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
trH1_filt.taper(max_percentage=0.05, type='hann')
trH2_filt.taper(max_percentage=0.05, type='hann')
H_copy[0].data = trH1_filt.data
@ -167,9 +167,9 @@ def run_makeCF(project, database, event, iplot, station=None):
All1_filt = AllC[0].copy()
All2_filt = AllC[1].copy()
All3_filt = AllC[2].copy()
All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
All1_filt.taper(max_percentage=0.05, type='hann')
All2_filt.taper(max_percentage=0.05, type='hann')
All3_filt.taper(max_percentage=0.05, type='hann')
@ -209,19 +209,19 @@ def run_makeCF(project, database, event, iplot, station=None):
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
plt.title('%s, %s, CF-SNR=%7.2f, CF-Slope=%12.2f' % (tr.stats.station, \
tr.stats.channel, aicpick.getSNR(), aicpick.getSlope()))
plt.title('%s, %s, CF-SNR=%7.2f, CF-Slope=%12.2f' % (tr.stats.station,
tr.stats.channel, aicpick.getSNR(), aicpick.getSlope()))
plt.suptitle(tr.stats.starttime)
plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
#plot horizontal traces
plt.figure(2)
plt.subplot(2,1,1)
tsteph = tpredh / 4
tsteph = tpredh / 4
th1data = np.arange(0, trH1_filt.stats.npts / trH1_filt.stats.sampling_rate, trH1_filt.stats.delta)
th2data = np.arange(0, trH2_filt.stats.npts / trH2_filt.stats.sampling_rate, trH2_filt.stats.delta)
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')
p22, = plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
p22, = plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
p23, = plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
@ -238,10 +238,10 @@ def run_makeCF(project, database, event, iplot, station=None):
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
plt.subplot(2,1,2)
plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
@ -271,7 +271,7 @@ def run_makeCF(project, database, event, iplot, station=None):
plt.ylabel('Normalized Counts')
plt.title([tr.stats.station, tr.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p31, p32], ['Data', 'AR3C-CF'])
plt.legend([p31, p32], ['Data', 'AR3C-CF'])
plt.subplot(3,1,2)
plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')

191
pylot/core/pick/utils.py
View File

@ -1,4 +1,5 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# -*- coding: utf-8 -*-
"""
@ -14,7 +15,7 @@ from obspy.core import Stream, UTCDateTime
import warnings
def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
def earllatepicker(X, nfac, TSNR, Pick1, iplot=None, stealthMode = False):
'''
Function to derive earliest and latest possible pick after Diehl & Kissling (2009)
as reasonable uncertainties. Latest possible pick is based on noise level,
@ -43,7 +44,8 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
LPick = None
EPick = None
PickError = None
#print 'earllatepicker: Get earliest and latest possible pick relative to most likely pick ...'
if stealthMode is False:
print 'earllatepicker: Get earliest and latest possible pick relative to most likely pick ...'
x = X[0].data
t = np.arange(0, X[0].stats.npts / X[0].stats.sampling_rate,
@ -74,8 +76,9 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
# if EPick stays NaN the signal window size will be doubled
while np.isnan(EPick):
if count > 0:
print("earllatepicker: Doubled signal window size %s time(s) "
"because of NaN for earliest pick." %count)
if stealthMode is False:
print("\nearllatepicker: Doubled signal window size %s time(s) "
"because of NaN for earliest pick." %count)
isigDoubleWinStart = pis[-1] + 1
isignalDoubleWin = np.arange(isigDoubleWinStart,
isigDoubleWinStart + len(pis))
@ -91,7 +94,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
T0 = np.mean(np.diff(zc)) * X[0].stats.delta # this is half wave length
# T0/4 is assumed as time difference between most likely and earliest possible pick!
EPick = Pick1 - T0 / 2
# get symmetric pick error as mean from earliest and latest possible pick
# by weighting latest possible pick two times earliest possible pick
@ -109,7 +112,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
markersize=14)
plt.legend([p1, p2, p3, p4, p5],
['Data', 'Noise Window', 'Signal Window', 'Noise Level',
'Zero Crossings'], \
'Zero Crossings'],
loc='best')
plt.plot([t[0], t[int(len(t)) - 1]], [-nlevel, -nlevel], '--k')
plt.plot([Pick1, Pick1], [max(x), -max(x)], 'b', linewidth=2)
@ -182,10 +185,10 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
i = 0
for j in range(ipick[0][1], ipick[0][len(t[ipick]) - 1]):
i = i + 1
if xraw[j - 1] <= 0 and xraw[j] >= 0:
if xraw[j - 1] <= 0 <= xraw[j]:
zc1.append(t[ipick][i])
index1.append(i)
elif xraw[j - 1] > 0 and xraw[j] <= 0:
elif xraw[j - 1] > 0 >= xraw[j]:
zc1.append(t[ipick][i])
index1.append(i)
if len(zc1) == 3:
@ -224,10 +227,10 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
i = 0
for j in range(ipick[0][1], ipick[0][len(t[ipick]) - 1]):
i = i + 1
if xfilt[j - 1] <= 0 and xfilt[j] >= 0:
if xfilt[j - 1] <= 0 <= xfilt[j]:
zc2.append(t[ipick][i])
index2.append(i)
elif xfilt[j - 1] > 0 and xfilt[j] <= 0:
elif xfilt[j - 1] > 0 >= xfilt[j]:
zc2.append(t[ipick][i])
index2.append(i)
if len(zc2) == 3:
@ -262,15 +265,15 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
if P1 is not None and P2 is not None:
if P1[0] < 0 and P2[0] < 0:
FM = 'D'
elif P1[0] >= 0 and P2[0] < 0:
elif P1[0] >= 0 > P2[0]:
FM = '-'
elif P1[0] < 0 and P2[0] >= 0:
elif P1[0] < 0 <= P2[0]:
FM = '-'
elif P1[0] > 0 and P2[0] > 0:
FM = 'U'
elif P1[0] <= 0 and P2[0] > 0:
elif P1[0] <= 0 < P2[0]:
FM = '+'
elif P1[0] > 0 and P2[0] <= 0:
elif P1[0] > 0 >= P2[0]:
FM = '+'
print ("fmpicker: Found polarity %s" % FM)
@ -285,7 +288,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
p3, = plt.plot(zc1, np.zeros(len(zc1)), '*g', markersize=14)
p4, = plt.plot(t[islope1], datafit1, '--g', linewidth=2)
plt.legend([p1, p2, p3, p4],
['Pick', 'Slope Window', 'Zero Crossings', 'Slope'], \
['Pick', 'Slope Window', 'Zero Crossings', 'Slope'],
loc='best')
plt.text(Pick + 0.02, max(xraw) / 2, '%s' % FM, fontsize=14)
ax = plt.gca()
@ -493,9 +496,9 @@ def wadaticheck(pickdic, dttolerance, iplot):
if len(SPtimes) >= 3:
# calculate slope
p1 = np.polyfit(Ppicks, SPtimes, 1)
wdfit = np.polyval(p1, Ppicks)
# calculate slope
p1 = np.polyfit(Ppicks, SPtimes, 1)
wdfit = np.polyval(p1, Ppicks)
wfitflag = 0
# calculate vp/vs ratio before check
@ -532,40 +535,40 @@ def wadaticheck(pickdic, dttolerance, iplot):
pickdic[key]['S']['marked'] = marker
if len(checkedPpicks) >= 3:
# calculate new slope
p2 = np.polyfit(checkedPpicks, checkedSPtimes, 1)
wdfit2 = np.polyval(p2, checkedPpicks)
# calculate new slope
p2 = np.polyfit(checkedPpicks, checkedSPtimes, 1)
wdfit2 = np.polyval(p2, checkedPpicks)
# calculate vp/vs ratio after check
cvpvsr = p2[0] + 1
print ("wadaticheck: Average Vp/Vs ratio after check: %f" % cvpvsr)
print ("wadatacheck: Skipped %d S pick(s)" % ibad)
# calculate vp/vs ratio after check
cvpvsr = p2[0] + 1
print ("wadaticheck: Average Vp/Vs ratio after check: %f" % cvpvsr)
print ("wadatacheck: Skipped %d S pick(s)" % ibad)
else:
print ("###############################################")
print ("wadatacheck: Not enough checked S-P times available!")
print ("Skip Wadati check!")
print ("###############################################")
print ("wadatacheck: Not enough checked S-P times available!")
print ("Skip Wadati check!")
checkedonsets = pickdic
else:
print ("wadaticheck: Not enough S-P times available for reliable regression!")
print ("wadaticheck: Not enough S-P times available for reliable regression!")
print ("Skip wadati check!")
wfitflag = 1
# plot results
if iplot > 1:
plt.figure(iplot)
f1, = plt.plot(Ppicks, SPtimes, 'ro')
plt.figure(iplot)
f1, = plt.plot(Ppicks, SPtimes, 'ro')
if wfitflag == 0:
f2, = plt.plot(Ppicks, wdfit, 'k')
f3, = plt.plot(checkedPpicks, checkedSPtimes, 'ko')
f4, = plt.plot(checkedPpicks, wdfit2, 'g')
plt.title('Wadati-Diagram, %d S-P Times, Vp/Vs(raw)=%5.2f,' \
'Vp/Vs(checked)=%5.2f' % (len(SPtimes), vpvsr, cvpvsr))
plt.legend([f1, f2, f3, f4], ['Skipped S-Picks', 'Wadati 1', \
'Reliable S-Picks', 'Wadati 2'], loc='best')
f2, = plt.plot(Ppicks, wdfit, 'k')
f3, = plt.plot(checkedPpicks, checkedSPtimes, 'ko')
f4, = plt.plot(checkedPpicks, wdfit2, 'g')
plt.title('Wadati-Diagram, %d S-P Times, Vp/Vs(raw)=%5.2f,' \
'Vp/Vs(checked)=%5.2f' % (len(SPtimes), vpvsr, cvpvsr))
plt.legend([f1, f2, f3, f4], ['Skipped S-Picks', 'Wadati 1',
'Reliable S-Picks', 'Wadati 2'], loc='best')
else:
plt.title('Wadati-Diagram, %d S-P Times' % len(SPtimes))
plt.title('Wadati-Diagram, %d S-P Times' % len(SPtimes))
plt.ylabel('S-P Times [s]')
plt.xlabel('P Times [s]')
@ -579,8 +582,8 @@ def wadaticheck(pickdic, dttolerance, iplot):
def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
'''
Function to detect spuriously picked noise peaks.
Uses RMS trace of all 3 components (if available) to determine,
how many samples [per cent] after P onset are below certain
Uses RMS trace of all 3 components (if available) to determine,
how many samples [per cent] after P onset are below certain
threshold, calculated from noise level times noise factor.
: param: X, time series (seismogram)
@ -612,7 +615,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
print ("Checking signal length ...")
if len(X) > 1:
# all three components available
# all three components available
# make sure, all components have equal lengths
ilen = min([len(X[0].data), len(X[1].data), len(X[2].data)])
x1 = X[0][0:ilen]
@ -639,7 +642,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
numoverthr = len(np.where(rms[isignal] >= minsiglevel)[0])
if numoverthr >= minnum:
print ("checksignallength: Signal reached required length.")
print ("checksignallength: Signal reached required length.")
returnflag = 1
else:
print ("checksignallength: Signal shorter than required minimum signal length!")
@ -649,15 +652,15 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
if iplot == 2:
plt.figure(iplot)
p1, = plt.plot(t,rms, 'k')
p1, = plt.plot(t,rms, 'k')
p2, = plt.plot(t[inoise], rms[inoise], 'c')
p3, = plt.plot(t[isignal],rms[isignal], 'r')
p4, = plt.plot([t[isignal[0]], t[isignal[len(isignal)-1]]], \
[minsiglevel, minsiglevel], 'g', linewidth=2)
p4, = plt.plot([t[isignal[0]], t[isignal[len(isignal)-1]]],
[minsiglevel, minsiglevel], 'g', linewidth=2)
p5, = plt.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2)
plt.legend([p1, p2, p3, p4, p5], ['RMS Data', 'RMS Noise Window', \
'RMS Signal Window', 'Minimum Signal Level', \
'Onset'], loc='best')
plt.legend([p1, p2, p3, p4, p5], ['RMS Data', 'RMS Noise Window',
'RMS Signal Window', 'Minimum Signal Level',
'Onset'], loc='best')
plt.xlabel('Time [s] since %s' % X[0].stats.starttime)
plt.ylabel('Counts')
plt.title('Check for Signal Length, Station %s' % X[0].stats.station)
@ -729,32 +732,32 @@ def checkPonsets(pickdic, dttolerance, iplot):
badjkmarker = 'badjkcheck'
for i in range(0, len(goodstations)):
# mark P onset as checked and keep P weight
pickdic[goodstations[i]]['P']['marked'] = goodmarker
pickdic[goodstations[i]]['P']['marked'] = goodmarker
for i in range(0, len(badstations)):
# mark P onset and downgrade P weight to 9
# (not used anymore)
pickdic[badstations[i]]['P']['marked'] = badmarker
pickdic[badstations[i]]['P']['weight'] = 9
# mark P onset and downgrade P weight to 9
# (not used anymore)
pickdic[badstations[i]]['P']['marked'] = badmarker
pickdic[badstations[i]]['P']['weight'] = 9
for i in range(0, len(badjkstations)):
# mark P onset and downgrade P weight to 9
# (not used anymore)
pickdic[badjkstations[i]]['P']['marked'] = badjkmarker
pickdic[badjkstations[i]]['P']['weight'] = 9
# mark P onset and downgrade P weight to 9
# (not used anymore)
pickdic[badjkstations[i]]['P']['marked'] = badjkmarker
pickdic[badjkstations[i]]['P']['weight'] = 9
checkedonsets = pickdic
if iplot > 1:
p1, = plt.plot(np.arange(0, len(Ppicks)), Ppicks, 'r+', markersize=14)
p1, = plt.plot(np.arange(0, len(Ppicks)), Ppicks, 'r+', markersize=14)
p2, = plt.plot(igood, np.array(Ppicks)[igood], 'g*', markersize=14)
p3, = plt.plot([0, len(Ppicks) - 1], [pmedian, pmedian], 'g', \
linewidth=2)
p3, = plt.plot([0, len(Ppicks) - 1], [pmedian, pmedian], 'g',
linewidth=2)
for i in range(0, len(Ppicks)):
plt.text(i, Ppicks[i] + 0.2, stations[i])
plt.text(i, Ppicks[i] + 0.2, stations[i])
plt.xlabel('Number of P Picks')
plt.ylabel('Onset Time [s] from 1.1.1970')
plt.legend([p1, p2, p3], ['Skipped P Picks', 'Good P Picks', 'Median'], \
loc='best')
plt.legend([p1, p2, p3], ['Skipped P Picks', 'Good P Picks', 'Median'],
loc='best')
plt.title('Check P Onsets')
plt.show()
raw_input()
@ -789,37 +792,37 @@ def jackknife(X, phi, h):
g = len(X) / h
if type(g) is not int:
print ("jackknife: Cannot divide quantity X in equal sized subgroups!")
print ("jackknife: Cannot divide quantity X in equal sized subgroups!")
print ("Choose another size for subgroups!")
return PHI_jack, PHI_pseudo, PHI_sub
else:
# estimator of undisturbed spot check
if phi == 'MEA':
phi_sc = np.mean(X)
# estimator of undisturbed spot check
if phi == 'MEA':
phi_sc = np.mean(X)
elif phi == 'VAR':
phi_sc = np.var(X)
phi_sc = np.var(X)
elif phi == 'MED':
phi_sc = np.median(X)
phi_sc = np.median(X)
# estimators of subgroups
# estimators of subgroups
PHI_pseudo = []
PHI_sub = []
for i in range(0, g - 1):
# subgroup i, remove i-th sample
xx = X[:]
del xx[i]
# calculate estimators of disturbed spot check
if phi == 'MEA':
phi_sub = np.mean(xx)
elif phi == 'VAR':
phi_sub = np.var(xx)
elif phi == 'MED':
phi_sub = np.median(xx)
# subgroup i, remove i-th sample
xx = X[:]
del xx[i]
# calculate estimators of disturbed spot check
if phi == 'MEA':
phi_sub = np.mean(xx)
elif phi == 'VAR':
phi_sub = np.var(xx)
elif phi == 'MED':
phi_sub = np.median(xx)
PHI_sub.append(phi_sub)
# pseudo values
phi_pseudo = g * phi_sc - ((g - 1) * phi_sub)
PHI_pseudo.append(phi_pseudo)
PHI_sub.append(phi_sub)
# pseudo values
phi_pseudo = g * phi_sc - ((g - 1) * phi_sub)
PHI_pseudo.append(phi_pseudo)
# jackknife estimator
PHI_jack = np.mean(PHI_pseudo)
@ -899,29 +902,29 @@ def checkZ4S(X, pick, zfac, checkwin, iplot):
# vertical P-coda level must exceed horizontal P-coda level
# zfac times encodalevel
if zcodalevel < minsiglevel:
print ("checkZ4S: Maybe S onset? Skip this P pick!")
print ("checkZ4S: Maybe S onset? Skip this P pick!")
else:
print ("checkZ4S: P onset passes checkZ4S test!")
returnflag = 1
if iplot > 1:
te = np.arange(0, edat[0].stats.npts / edat[0].stats.sampling_rate,
te = np.arange(0, edat[0].stats.npts / edat[0].stats.sampling_rate,
edat[0].stats.delta)
tn = np.arange(0, ndat[0].stats.npts / ndat[0].stats.sampling_rate,
tn = np.arange(0, ndat[0].stats.npts / ndat[0].stats.sampling_rate,
ndat[0].stats.delta)
plt.plot(tz, z / max(z), 'k')
plt.plot(tz, z / max(z), 'k')
plt.plot(tz[isignal], z[isignal] / max(z), 'r')
plt.plot(te, edat[0].data / max(edat[0].data) + 1, 'k')
plt.plot(te[isignal], edat[0].data[isignal] / max(edat[0].data) + 1, 'r')
plt.plot(tn, ndat[0].data / max(ndat[0].data) + 2, 'k')
plt.plot(tn[isignal], ndat[0].data[isignal] / max(ndat[0].data) + 2, 'r')
plt.plot([tz[isignal[0]], tz[isignal[len(isignal) - 1]]], \
[minsiglevel / max(z), minsiglevel / max(z)], 'g', \
linewidth=2)
plt.plot([tz[isignal[0]], tz[isignal[len(isignal) - 1]]],
[minsiglevel / max(z), minsiglevel / max(z)], 'g',
linewidth=2)
plt.xlabel('Time [s] since %s' % zdat[0].stats.starttime)
plt.ylabel('Normalized Counts')
plt.yticks([0, 1, 2], [zdat[0].stats.channel, edat[0].stats.channel, \
ndat[0].stats.channel])
plt.yticks([0, 1, 2], [zdat[0].stats.channel, edat[0].stats.channel,
ndat[0].stats.channel])
plt.title('CheckZ4S, Station %s' % zdat[0].stats.station)
plt.show()
raw_input()

2
pylot/core/read/__init__.py
View File

@ -1 +1 @@
# -*- coding: utf-8 -*-

3
pylot/core/read/inputs.py
View File

@ -208,8 +208,7 @@ class FilterOptions(object):
def parseFilterOptions(self):
if self.getFilterType():
robject = {'type':self.getFilterType()}
robject['corners'] = self.getOrder()
robject = {'type': self.getFilterType(), 'corners': self.getOrder()}
if len(self.getFreq()) > 1:
robject['freqmin'] = self.getFreq()[0]
robject['freqmax'] = self.getFreq()[1]

6
pylot/core/read/io.py
View File

@ -73,8 +73,8 @@ def readPILOTEvent(phasfn=None, locfn=None, authority_id=None, **kwargs):
stations = [stat for stat in phases['stat'][0:-1:3]]
event = createEvent(eventDate, loccinfo, None, 'earthquake', eventNum,
authority_id)
event = createEvent(eventDate, loccinfo, etype='earthquake', resID=eventNum,
authority_id=authority_id)
lat = float(loc['LAT'])
lon = float(loc['LON'])
@ -130,7 +130,7 @@ def readPILOTEvent(phasfn=None, locfn=None, authority_id=None, **kwargs):
event.magnitudes.append(magnitude)
return event
except AttributeError, e:
except AttributeError as e:
raise AttributeError('{0} - Matlab LOC files {1} and {2} contains \
insufficient data!'.format(e, phasfn, locfn))

1
pylot/core/util/__init__.py
View File

@ -1 +1,2 @@
# -*- coding: utf-8 -*-
from pylot.core.util.version import get_git_version as _getVersionString

3
pylot/core/util/testUtils.py
View File

@ -1,3 +1,4 @@
# -*- coding: utf-8 -*-
'''
Created on 10.11.2014
@ -23,4 +24,4 @@ class Test(unittest.TestCase):
if __name__ == "__main__":
#import sys;sys.argv = ['', 'Test.testName']
unittest.main()
unittest.main()

3
pylot/core/util/testWidgets.py
View File

@ -1,3 +1,4 @@
# -*- coding: utf-8 -*-
'''
Created on 10.11.2014
@ -15,4 +16,4 @@ class Test(unittest.TestCase):
if __name__ == "__main__":
#import sys;sys.argv = ['', 'Test.testName']
unittest.main()
unittest.main()

1
pylot/core/util/thread.py
View File

@ -1,3 +1,4 @@
# -*- coding: utf-8 -*-
import sys
from PySide.QtCore import QThread, Signal

1
pylot/core/util/utils.py
View File

@ -1,4 +1,5 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# -*- coding: utf-8 -*-

5
pylot/core/util/widgets.py
View File

@ -814,9 +814,10 @@ class PropertiesDlg(QDialog):
if values is not None:
self.setValues(values)
def setValues(self, tabValues):
@staticmethod
def setValues(tabValues):
settings = QSettings()
for setting, value in tabValues.iteritems():
for setting, value in tabValues.items():
settings.setValue(setting, value)
settings.sync()

1
testHelpForm.py
View File

@ -1,4 +1,5 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys, time
from PySide.QtGui import QApplication

1
testPickDlg.py
View File

@ -1,4 +1,5 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import matplotlib

3
testPropDlg.py
View File

@ -1,4 +1,5 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys, time
from PySide.QtGui import QApplication
@ -8,4 +9,4 @@ app = QApplication(sys.argv)
win = PropertiesDlg()
win.show()
app.exec_()
app.exec_()

10
testUIcomponents.py
View File

@ -1,4 +1,6 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys, time
from PySide.QtGui import QApplication
@ -9,7 +11,7 @@ dialogs = [FilterOptionsDialog, PropertiesDlg, HelpForm]
app = QApplication(sys.argv)
for dlg in dialogs:
win = dlg()
win.show()
time.sleep(1)
win.destroy()
win = dlg()
win.show()
time.sleep(1)
win.destroy()