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WALL-E: Einmal aufräumen und zurück!

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This commit is contained in:
Sebastian Wehling-Benatelli 2016-03-30 08:14:58 +02:00
parent a2640e3126
commit d7cfd0d176
29 changed files with 1285 additions and 1105 deletions
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77
autoPyLoT.py
View File

@ -1,6 +1,7 @@
#!/usr/bin/python
# -*- coding: utf-8 -*-
from __future__ import print_function
import os
import argparse
import glob
@ -55,9 +56,9 @@ def autoPyLoT(inputfile):
if parameter.hasParam('datastructure'):
datastructure = DATASTRUCTURE[parameter.getParam('datastructure')]()
dsfields = {'root' :parameter.getParam('rootpath'),
'dpath' :parameter.getParam('datapath'),
'dbase' :parameter.getParam('database')}
dsfields = {'root': parameter.getParam('rootpath'),
'dpath': parameter.getParam('datapath'),
'dbase': parameter.getParam('database')}
exf = ['root', 'dpath', 'dbase']
@ -86,7 +87,7 @@ def autoPyLoT(inputfile):
ttpat = parameter.getParam('ttpatter')
# pattern of NLLoc-output file
nllocoutpatter = parameter.getParam('outpatter')
maxnumit = 3 # maximum number of iterations for re-picking
maxnumit = 3 # maximum number of iterations for re-picking
else:
locflag = 0
print(" !!! ")
@ -94,7 +95,6 @@ def autoPyLoT(inputfile):
print("!!No source parameter estimation possible!!")
print(" !!! ")
# multiple event processing
# read each event in database
datapath = datastructure.expandDataPath()
@ -115,7 +115,7 @@ def autoPyLoT(inputfile):
picksExport(picks, 'NLLoc', phasefile)
# For locating the event the NLLoc-control file has to be modified!
evID = event[string.rfind(event, "/") + 1 : len(events) - 1]
evID = event[string.rfind(event, "/") + 1: len(events) - 1]
nllocout = '%s_%s' % (evID, nllocoutpatter)
# create comment line for NLLoc-control file
modifyInputFile(ctrf, nllocroot, nllocout, phasef, ttpat)
@ -129,8 +129,8 @@ def autoPyLoT(inputfile):
# get stations with bad onsets
badpicks = []
for key in picks:
if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
badpicks.append([key, picks[key]['P']['mpp']])
if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
badpicks.append([key, picks[key]['P']['mpp']])
if len(badpicks) == 0:
print("autoPyLoT: No bad onsets found, thus no iterative picking necessary!")
@ -140,10 +140,10 @@ def autoPyLoT(inputfile):
# get latest NLLoc-location file if several are available
nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
# calculating seismic moment Mo and moment magnitude Mw
finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
nllocfile, picks, parameter.getParam('rho'), \
parameter.getParam('vp'), parameter.getParam('Qp'), \
parameter.getParam('invdir'))
finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
nllocfile, picks, parameter.getParam('rho'), \
parameter.getParam('vp'), parameter.getParam('Qp'), \
parameter.getParam('invdir'))
else:
print("autoPyLoT: No NLLoc-location file available!")
print("No source parameter estimation possible!")
@ -173,24 +173,24 @@ def autoPyLoT(inputfile):
# check for bad picks
badpicks = []
for key in picks:
if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
badpicks.append([key, picks[key]['P']['mpp']])
if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
badpicks.append([key, picks[key]['P']['mpp']])
print("autoPyLoT: After iteration No. %d: %d bad onsets found ..." % (nlloccounter, \
len(badpicks)))
len(badpicks)))
if len(badpicks) == 0:
print("autoPyLoT: No more bad onsets found, stop iterative picking!")
nlloccounter = maxnumit
# calculating seismic moment Mo and moment magnitude Mw
finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
nllocfile, picks, parameter.getParam('rho'), \
parameter.getParam('vp'), parameter.getParam('Qp'), \
parameter.getParam('invdir'))
finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
nllocfile, picks, parameter.getParam('rho'), \
parameter.getParam('vp'), parameter.getParam('Qp'), \
parameter.getParam('invdir'))
# get network moment magntiude
netMw = []
for key in finalpicks.getpicdic():
if finalpicks.getpicdic()[key]['P']['Mw'] is not None:
netMw.append(finalpicks.getpicdic()[key]['P']['Mw'])
if finalpicks.getpicdic()[key]['P']['Mw'] is not None:
netMw.append(finalpicks.getpicdic()[key]['P']['Mw'])
netMw = np.median(netMw)
print("Network moment magnitude: %4.1f" % netMw)
else:
@ -218,8 +218,8 @@ def autoPyLoT(inputfile):
# single event processing
else:
data.setWFData(glob.glob(os.path.join(datapath, parameter.getParam('eventID'), '*')))
print("Working on event "), parameter.getParam('eventID')
print data
print("Working on event {0}".format(parameter.getParam('eventID')))
print(data)
wfdat = data.getWFData() # all available streams
##########################################################
@ -245,8 +245,8 @@ def autoPyLoT(inputfile):
# get stations with bad onsets
badpicks = []
for key in picks:
if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
badpicks.append([key, picks[key]['P']['mpp']])
if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
badpicks.append([key, picks[key]['P']['mpp']])
if len(badpicks) == 0:
print("autoPyLoT: No bad onsets found, thus no iterative picking necessary!")
@ -256,10 +256,10 @@ def autoPyLoT(inputfile):
# get latest NLLOc-location file if several are available
nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
# calculating seismic moment Mo and moment magnitude Mw
finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
nllocfile, picks, parameter.getParam('rho'), \
parameter.getParam('vp'), parameter.getParam('Qp'), \
parameter.getParam('invdir'))
finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
nllocfile, picks, parameter.getParam('rho'), \
parameter.getParam('vp'), parameter.getParam('Qp'), \
parameter.getParam('invdir'))
else:
print("autoPyLoT: No NLLoc-location file available!")
print("No source parameter estimation possible!")
@ -289,24 +289,24 @@ def autoPyLoT(inputfile):
# check for bad picks
badpicks = []
for key in picks:
if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
badpicks.append([key, picks[key]['P']['mpp']])
if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
badpicks.append([key, picks[key]['P']['mpp']])
print("autoPyLoT: After iteration No. %d: %d bad onsets found ..." % (nlloccounter, \
len(badpicks)))
len(badpicks)))
if len(badpicks) == 0:
print("autoPyLoT: No more bad onsets found, stop iterative picking!")
nlloccounter = maxnumit
# calculating seismic moment Mo and moment magnitude Mw
finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
nllocfile, picks, parameter.getParam('rho'), \
parameter.getParam('vp'), parameter.getParam('Qp'), \
parameter.getParam('invdir'))
finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
nllocfile, picks, parameter.getParam('rho'), \
parameter.getParam('vp'), parameter.getParam('Qp'), \
parameter.getParam('invdir'))
# get network moment magntiude
netMw = []
for key in finalpicks.getpicdic():
if finalpicks.getpicdic()[key]['P']['Mw'] is not None:
netMw.append(finalpicks.getpicdic()[key]['P']['Mw'])
if finalpicks.getpicdic()[key]['P']['Mw'] is not None:
netMw.append(finalpicks.getpicdic()[key]['P']['Mw'])
netMw = np.median(netMw)
print("Network moment magnitude: %4.1f" % netMw)
else:
@ -338,6 +338,7 @@ def autoPyLoT(inputfile):
************************************'''.format(version=_getVersionString())
print(endsp)
if __name__ == "__main__":
# parse arguments
parser = argparse.ArgumentParser(

6
makePyLoT.py
View File

@ -1,5 +1,7 @@
#!/usr/bin/env python
# encoding: utf-8
from __future__ import print_function
"""
makePyLoT -- build and install PyLoT
@ -123,7 +125,7 @@ USAGE
except KeyboardInterrupt:
cleanUp(verbose)
return 0
except Exception, e:
except Exception as e:
if DEBUG or TESTRUN:
raise e
indent = len(program_name) * " "
@ -139,7 +141,7 @@ def buildPyLoT(verbosity=None):
"\n"
" Current working directory: {1}\n"
).format(system, os.getcwd())
print msg
print(msg)
if system.startswith(('win', 'microsoft')):
raise CLIError(
"building on Windows system not tested yet; implementation pending")

150
pylot/core/active/activeSeismoPick.py
View File

@ -4,8 +4,9 @@ import numpy as np
from pylot.core.active import seismicshot
from pylot.core.active.surveyUtils import cleanUp
class Survey(object):
def __init__(self, path, sourcefile, receiverfile, useDefaultParas = False):
def __init__(self, path, sourcefile, receiverfile, useDefaultParas=False):
'''
The Survey Class contains all shots [type: seismicshot] of a survey
as well as the aquisition geometry and the topography.
@ -37,7 +38,7 @@ class Survey(object):
shot_dict = {}
shotlist = self.getShotlist()
for shotnumber in shotlist: # loop over data files
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 obsfile not in shot_dict.keys():
@ -47,7 +48,7 @@ class Survey(object):
self.data = shot_dict
print ("Generated Survey object for %d shots" % len(shotlist))
print ("Total number of traces: %d \n" %self.countAllTraces())
print ("Total number of traces: %d \n" % self.countAllTraces())
def _removeAllEmptyTraces(self):
filename = 'removeEmptyTraces.out'
@ -58,11 +59,11 @@ class Survey(object):
if count == 0: outfile = open(filename, 'w')
count += 1
outfile.writelines('shot: %s, removed empty traces: %s\n'
%(shot.getShotnumber(), removed))
print ("\nremoveEmptyTraces: Finished! Removed %d traces" %count)
% (shot.getShotnumber(), removed))
print ("\nremoveEmptyTraces: Finished! Removed %d traces" % count)
if count > 0:
print ("See %s for more information "
"on removed traces."%(filename))
"on removed traces." % (filename))
outfile.close()
def _updateShots(self):
@ -70,7 +71,8 @@ class Survey(object):
Removes traces that do not exist in the dataset for any reason.
'''
filename = 'updateShots.out'
count = 0; countTraces = 0
count = 0;
countTraces = 0
for shot in self.data.values():
del_traceIDs = shot.updateTraceList()
if len(del_traceIDs) > 0:
@ -79,13 +81,13 @@ class Survey(object):
countTraces += len(del_traceIDs)
outfile.writelines("shot: %s, removed traceID(s) %s because "
"they were not found in the corresponding stream\n"
%(shot.getShotnumber(), del_traceIDs))
% (shot.getShotnumber(), del_traceIDs))
print ("\nupdateShots: Finished! Updated %d shots and removed "
"%d traces" %(count, countTraces))
"%d traces" % (count, countTraces))
if count > 0:
print ("See %s for more information "
"on removed traces."%(filename))
"on removed traces." % (filename))
outfile.close()
def setArtificialPick(self, traceID, pick):
@ -96,9 +98,9 @@ class Survey(object):
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):
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):
tsignal == 0.03 and tgap == 0.0007):
print ("Warning: Standard values used for "
"setParamters. This might not be clever.")
# CHANGE this later. Parameters only needed for survey, not for each shot.
@ -107,12 +109,12 @@ class Survey(object):
shot.setTmovwind(tmovwind)
shot.setTsignal(tsignal)
shot.setTgap(tgap)
shot.setOrder(order = 4)
shot.setOrder(order=4)
print ("setParametersForShots: Parameters set to:\n"
"cutwindow = %s, tMovingWindow = %f, tsignal = %f, tgap = %f"
%(cutwindow, tmovwind, tsignal, tgap))
% (cutwindow, tmovwind, tsignal, tgap))
def setManualPicksFromFiles(self, directory = 'picks'):
def setManualPicksFromFiles(self, directory='picks'):
'''
Read manual picks from *.pck files in a directory.
The * must be identical with the shotnumber.
@ -135,7 +137,10 @@ class Survey(object):
def plotDiffs(self):
import matplotlib.pyplot as plt
diffs = []; dists = []; mpicks = []; picks = []
diffs = [];
dists = [];
mpicks = [];
picks = []
diffsDic = self.getDiffsFromManual()
for shot in self.data.values():
for traceID in shot.getTraceIDlist():
@ -151,15 +156,15 @@ class Survey(object):
fig = plt.figure()
ax = fig.add_subplot(111)
sc_a = ax.scatter(dists, picks, c = '0.5', s=10, edgecolors='none', label = labela, alpha = 0.3)
sc = ax.scatter(dists, mpicks, c = diffs, s=5, edgecolors='none', label = labelm)
sc_a = ax.scatter(dists, picks, c='0.5', s=10, edgecolors='none', label=labela, alpha=0.3)
sc = ax.scatter(dists, mpicks, c=diffs, s=5, edgecolors='none', label=labelm)
cbar = plt.colorbar(sc, fraction=0.05)
cbar.set_label(labelm)
ax.set_xlabel('Distance [m]')
ax.set_ylabel('Time [s]')
ax.text(0.5, 0.95, 'Plot of all MANUAL picks', transform=ax.transAxes, horizontalalignment='center')
def plotHist(self, nbins = 20, ax = None):
def plotHist(self, nbins=20, ax=None):
import matplotlib.pyplot as plt
plt.interactive(True)
diffs = []
@ -170,48 +175,51 @@ class Survey(object):
for traceID in shot.getTraceIDlist():
if shot.getPickFlag(traceID) == 1 and shot.getManualPickFlag(traceID) == 1:
diffs.append(self.getDiffsFromManual()[shot][traceID])
hist = plt.hist(diffs, nbins, histtype = 'step', normed = True, stacked = True)
hist = plt.hist(diffs, nbins, histtype='step', normed=True, stacked=True)
plt.title('Histogram of the differences between automatic and manual pick')
plt.xlabel('Difference in time (auto - manual) [s]')
return diffs
def pickAllShots(self, windowsize, HosAic = 'hos', vmin = 333, vmax = 5500, folm = 0.6):
def pickAllShots(self, windowsize, HosAic='hos', vmin=333, vmax=5500, folm=0.6):
'''
Automatically pick all traces of all shots of the survey.
'''
from datetime import datetime
starttime = datetime.now()
count = 0; tpicksum = starttime - starttime
count = 0;
tpicksum = starttime - starttime
for shot in self.data.values():
tstartpick = datetime.now(); count += 1
tstartpick = datetime.now();
count += 1
for traceID in shot.getTraceIDlist():
distance = shot.getDistance(traceID) # receive distance
distance = shot.getDistance(traceID) # receive distance
pickwin_used = shot.getCut()
cutwindow = shot.getCut()
# 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
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.pickTraces(traceID, windowsize, folm, HosAic) # picker
shot.setSNR(traceID)
#if shot.getSNR(traceID)[0] < snrthreshold:
# if shot.getSNR(traceID)[0] < snrthreshold:
if shot.getSNR(traceID)[0] < shot.getSNRthreshold(traceID):
shot.removePick(traceID)
shot.removePick(traceID)
# 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
tpicksum += (datetime.now() - tstartpick);
tpick = tpicksum / count
tremain = (tpick * (len(self.getShotDict()) - count))
tend = datetime.now() + tremain
progress = float(count) / float(len(self.getShotDict())) * 100
@ -220,7 +228,7 @@ class Survey(object):
ntraces = self.countAllTraces()
pickedtraces = self.countAllPickedTraces()
print('Picked %s / %s traces (%d %%)\n'
%(pickedtraces, ntraces, float(pickedtraces)/float(ntraces)*100.))
% (pickedtraces, ntraces, float(pickedtraces) / float(ntraces) * 100.))
def cleanBySPE(self, maxSPE):
for shot in self.data.values():
@ -237,7 +245,7 @@ class Survey(object):
if shot.getPickFlag(traceID) == 1:
spe.append(shot.getSymmetricPickError(traceID))
spe.sort()
plt.plot(spe, label = 'SPE')
plt.plot(spe, label='SPE')
plt.ylabel('Symmetric Pickerror')
plt.legend()
@ -255,7 +263,7 @@ class Survey(object):
shot.removePick(traceID)
else:
numpicks += 1
print('Recovered %d picks'%numpicks)
print('Recovered %d picks' % numpicks)
def setArtificialPick(self, traceID, pick):
for shot in self.data.values():
@ -265,13 +273,13 @@ class Survey(object):
def countAllTraces(self):
numtraces = 0
for shot in self.getShotlist():
for rec in self.getReceiverlist(): ### shot.getReceiverlist etc.
for rec in self.getReceiverlist(): ### shot.getReceiverlist etc.
numtraces += 1
return numtraces
def getShotlist(self):
filename = self.getPath() + self.getSourcefile()
srcfile = open(filename,'r')
srcfile = open(filename, 'r')
shotlist = []
for line in srcfile.readlines():
line = line.split()
@ -281,7 +289,7 @@ class Survey(object):
def getReceiverlist(self):
filename = self.getPath() + self.getReceiverfile()
recfile = open(filename,'r')
recfile = open(filename, 'r')
reclist = []
for line in recfile.readlines():
line = line.split()
@ -318,8 +326,8 @@ class Survey(object):
pickedTraces += 1
info_dict[shot.getShotnumber()] = {'numtraces': numtraces,
'picked traces': [pickedTraces,
'%2.2f %%'%(float(pickedTraces) /
float(numtraces) * 100)],
'%2.2f %%' % (float(pickedTraces) /
float(numtraces) * 100)],
'mean SNR': np.mean(snrlist),
'mean distance': np.mean(dist)}
@ -330,7 +338,7 @@ class Survey(object):
if shot.getShotnumber() == shotnumber:
return shot
def exportFMTOMO(self, directory = 'FMTOMO_export', sourcefile = 'input_sf.in', ttFileExtension = '.tt'):
def exportFMTOMO(self, directory='FMTOMO_export', sourcefile='input_sf.in', ttFileExtension='.tt'):
def getAngle(distance):
PI = np.pi
R = 6371.
@ -338,18 +346,22 @@ class Survey(object):
return angle
count = 0
fmtomo_factor = 1000 # transforming [m/s] -> [km/s]
LatAll = []; LonAll = []; DepthAll = []
fmtomo_factor = 1000 # transforming [m/s] -> [km/s]
LatAll = [];
LonAll = [];
DepthAll = []
srcfile = open(directory + '/' + sourcefile, 'w')
srcfile.writelines('%10s\n' %len(self.data)) # number of sources
srcfile.writelines('%10s\n' % len(self.data)) # number of sources
for shotnumber in self.getShotlist():
shot = self.getShotForShotnumber(shotnumber)
ttfilename = str(shotnumber) + ttFileExtension
(x, y, z) = shot.getSrcLoc() # getSrcLoc returns (x, y, z)
srcfile.writelines('%10s %10s %10s\n' %(getAngle(y), getAngle(x), (-1)*z)) # lat, lon, depth
LatAll.append(getAngle(y)); LonAll.append(getAngle(x)); DepthAll.append((-1)*z)
srcfile.writelines('%10s\n' %1) #
srcfile.writelines('%10s %10s %10s\n' %(1, 1, ttfilename))
(x, y, z) = shot.getSrcLoc() # getSrcLoc returns (x, y, z)
srcfile.writelines('%10s %10s %10s\n' % (getAngle(y), getAngle(x), (-1) * z)) # lat, lon, depth
LatAll.append(getAngle(y));
LonAll.append(getAngle(x));
DepthAll.append((-1) * z)
srcfile.writelines('%10s\n' % 1) #
srcfile.writelines('%10s %10s %10s\n' % (1, 1, ttfilename))
ttfile = open(directory + '/' + ttfilename, 'w')
traceIDlist = shot.getTraceIDlist()
traceIDlist.sort()
@ -359,8 +371,10 @@ class Survey(object):
pick = shot.getPick(traceID) * fmtomo_factor
delta = shot.getSymmetricPickError(traceID) * fmtomo_factor
(x, y, z) = shot.getRecLoc(traceID)
ttfile.writelines('%20s %20s %20s %10s %10s\n' %(getAngle(y), getAngle(x), (-1)*z, pick, delta))
LatAll.append(getAngle(y)); LonAll.append(getAngle(x)); DepthAll.append((-1)*z)
ttfile.writelines('%20s %20s %20s %10s %10s\n' % (getAngle(y), getAngle(x), (-1) * z, pick, delta))
LatAll.append(getAngle(y));
LonAll.append(getAngle(x));
DepthAll.append((-1) * z)
count += 1
ttfile.close()
srcfile.close()
@ -393,7 +407,7 @@ class Survey(object):
count += 1
return count
def plotAllShots(self, rows = 3, columns = 4, mode = '3d'):
def plotAllShots(self, rows=3, columns=4, mode='3d'):
'''
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!
@ -408,8 +422,8 @@ class Survey(object):
figPerSubplot = columns * rows
index = 1
#shotnames = []
#shotnumbers = []
# shotnames = []
# shotnumbers = []
# for shot in self.data.values():
# shotnames.append(shot.getShotname())
@ -419,24 +433,24 @@ class Survey(object):
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(3,3,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(rows, columns, index)
if mode == '3d':
self.getShot(shotnumber).matshow(ax = ax, colorbar = False, annotations = True, legend = False)
self.getShot(shotnumber).matshow(ax=ax, colorbar=False, annotations=True, legend=False)
elif mode == '2d':
self.getShot(shotnumber).plot2dttc(ax)
self.getShot(shotnumber).plotmanual2dttc(ax)
index += 1
if index > figPerSubplot:
fig.subplots_adjust(left = 0, bottom = 0, right = 1, top = 1, wspace = 0, hspace = 0)
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)
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):
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)
@ -488,8 +502,8 @@ class Survey(object):
spe.append(shot.getSymmetricPickError(traceID))
color = {'log10SNR': snrlog,
'pickerror': pickerror,
'spe': spe}
'pickerror': pickerror,
'spe': spe}
self.color = color
if refreshPlot is False:
ax, cbar = self.createPlot(dist, pick, color[colorByVal], label='%s' % colorByVal)
@ -501,7 +515,7 @@ class Survey(object):
ax.legend()
return ax
def createPlot(self, dist, pick, inkByVal, label, ax = None, cbar = None):
def createPlot(self, dist, pick, inkByVal, label, ax=None, cbar=None):
import matplotlib.pyplot as plt
plt.interactive(True)
cm = plt.cm.jet
@ -526,19 +540,19 @@ class Survey(object):
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))
tend.hour,
tend.minute,
tend.second,
progress))
sys.stdout.flush()
def saveSurvey(self, filename = 'survey.pickle'):
def saveSurvey(self, filename='survey.pickle'):
import cPickle
cleanUp(self)
outfile = open(filename, 'wb')
cPickle.dump(self, outfile, -1)
print('saved Survey to file %s'%(filename))
print('saved Survey to file %s' % (filename))
@staticmethod
def from_pickle(filename):

95
pylot/core/active/fmtomo2vtk.py
View File

@ -1,13 +1,15 @@
# -*- coding: utf-8 -*-
import numpy as np
def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'abs', inputfileref = 'vgridsref.in'):
def vgrids2VTK(inputfile='vgrids.in', outputfile='vgrids.vtk', absOrRel='abs', inputfileref='vgridsref.in'):
'''
Generate a vtk-file readable by e.g. paraview from FMTOMO output vgrids.in
:param: absOrRel, can be "abs" or "rel" for absolute or relative velocities. if "rel" inputfileref must be given
:type: str
'''
def getDistance(angle):
PI = np.pi
R = 6371.
@ -23,7 +25,7 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'a
nPhi = int(vglines[1].split()[2])
print('readNumberOf Points: Awaiting %d grid points in %s'
%(nR*nTheta*nPhi, filename))
% (nR * nTheta * nPhi, filename))
fin.close()
return nR, nTheta, nPhi
@ -53,7 +55,8 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'a
'''
Reads in velocity from vgrids file and returns a list containing all values in the same order
'''
vel = []; count = 0
vel = [];
count = 0
fin = open(filename, 'r')
vglines = fin.readlines()
@ -62,10 +65,10 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'a
if count > 4:
vel.append(float(line.split()[0]))
print("Read %d points out of file: %s" %(count - 4, filename))
print("Read %d points out of file: %s" % (count - 4, filename))
return vel
R = 6371. # earth radius
R = 6371. # earth radius
outfile = open(outputfile, 'w')
# Theta, Phi in radians, R in km
@ -74,7 +77,9 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'a
sR, sTheta, sPhi = readStartpoints(inputfile)
vel = readVelocity(inputfile)
nX = nPhi; nY = nTheta; nZ = nR
nX = nPhi;
nY = nTheta;
nZ = nR
sZ = sR - R
sX = getDistance(np.rad2deg(sPhi))
@ -94,28 +99,28 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'a
outfile.writelines('ASCII\n')
outfile.writelines('DATASET STRUCTURED_POINTS\n')
outfile.writelines('DIMENSIONS %d %d %d\n' %(nX, nY, nZ))
outfile.writelines('ORIGIN %f %f %f\n' %(sX, sY, sZ))
outfile.writelines('SPACING %f %f %f\n' %(dX, dY, dZ))
outfile.writelines('DIMENSIONS %d %d %d\n' % (nX, nY, nZ))
outfile.writelines('ORIGIN %f %f %f\n' % (sX, sY, sZ))
outfile.writelines('SPACING %f %f %f\n' % (dX, dY, dZ))
outfile.writelines('POINT_DATA %15d\n' %(nPoints))
outfile.writelines('POINT_DATA %15d\n' % (nPoints))
if absOrRel == 'abs':
outfile.writelines('SCALARS velocity float %d\n' %(1))
outfile.writelines('SCALARS velocity float %d\n' % (1))
elif absOrRel == 'rel':
outfile.writelines('SCALARS velChangePercent float %d\n' %(1))
outfile.writelines('SCALARS velChangePercent float %d\n' % (1))
outfile.writelines('LOOKUP_TABLE default\n')
# write velocity
if absOrRel == 'abs':
print("Writing velocity values to VTK file...")
for velocity in vel:
outfile.writelines('%10f\n' %velocity)
outfile.writelines('%10f\n' % velocity)
elif absOrRel == 'rel':
velref = readVelocity(inputfileref)
if not len(velref) == len(vel):
print('ERROR: Number of gridpoints mismatch for %s and %s'%(inputfile, inputfileref))
print('ERROR: Number of gridpoints mismatch for %s and %s' % (inputfile, inputfileref))
return
#velrel = [((vel - velref) / velref * 100) for vel, velref in zip(vel, velref)]
# velrel = [((vel - velref) / velref * 100) for vel, velref in zip(vel, velref)]
velrel = []
for velocities in zip(vel, velref):
v, vref = velocities
@ -126,18 +131,19 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'a
nR_ref, nTheta_ref, nPhi_ref = readNumberOfPoints(inputfileref)
if not nR_ref == nR and nTheta_ref == nTheta and nPhi_ref == nPhi:
print('ERROR: Dimension mismatch of grids %s and %s'%(inputfile, inputfileref))
print('ERROR: Dimension mismatch of grids %s and %s' % (inputfile, inputfileref))
return
print("Writing velocity values to VTK file...")
for velocity in velrel:
outfile.writelines('%10f\n' %velocity)
print('Pertubations: min: %s, max: %s'%(min(velrel), max(velrel)))
outfile.writelines('%10f\n' % velocity)
print('Pertubations: min: %s, max: %s' % (min(velrel), max(velrel)))
outfile.close()
print("Wrote velocity grid for %d points to file: %s" %(nPoints, outputfile))
print("Wrote velocity grid for %d points to file: %s" % (nPoints, outputfile))
return
def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
def rays2VTK(fnin, fdirout='./vtk_files/', nthPoint=50):
'''
Writes VTK file(s) for FMTOMO rays from rays.dat. There is one file created for each ray.
@ -147,6 +153,7 @@ def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
:param: nthPoint, plot every nth point of the ray
:type: integer
'''
def getDistance(angle):
PI = np.pi
R = 6371.
@ -164,12 +171,12 @@ def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
while True:
raynumber += 1
firstline = infile.readline()
if firstline == '': break # break at EOF
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
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))
print('Invalid ray number %d for shot number %d' % (raynumber, shotnumber))
continue
nRayPoints = int(infile.readline().split()[0])
if not shotnumber in rays.keys():
@ -178,14 +185,15 @@ def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
for index in range(nRayPoints):
if index % nthPoint is 0 or index == (nRayPoints - 1):
rad, lat, lon = infile.readline().split()
rays[shotnumber][raynumber].append([getDistance(np.rad2deg(float(lon))), getDistance(np.rad2deg(float(lat))), float(rad) - R])
rays[shotnumber][raynumber].append(
[getDistance(np.rad2deg(float(lon))), getDistance(np.rad2deg(float(lat))), float(rad) - R])
else:
dummy = infile.readline()
infile.close()
for shotnumber in rays.keys():
fnameout = fdirout + 'rays%03d.vtk'%(shotnumber)
fnameout = fdirout + 'rays%03d.vtk' % (shotnumber)
outfile = open(fnameout, 'w')
nPoints = 0
@ -194,43 +202,42 @@ def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
nPoints += 1
# write header
#print("Writing header for VTK file...")
print("Writing shot %d to file %s" %(shotnumber, fnameout))
# print("Writing header for VTK file...")
print("Writing shot %d to file %s" % (shotnumber, fnameout))
outfile.writelines('# vtk DataFile Version 3.1\n')
outfile.writelines('FMTOMO rays\n')
outfile.writelines('ASCII\n')
outfile.writelines('DATASET POLYDATA\n')
outfile.writelines('POINTS %15d float\n' %(nPoints))
outfile.writelines('POINTS %15d float\n' % (nPoints))
# write coordinates
#print("Writing coordinates to VTK file...")
# print("Writing coordinates to VTK file...")
for raynumber in rays[shotnumber].keys():
for raypoint in rays[shotnumber][raynumber]:
outfile.writelines('%10f %10f %10f \n' %(raypoint[0], raypoint[1], raypoint[2]))
outfile.writelines('%10f %10f %10f \n' % (raypoint[0], raypoint[1], raypoint[2]))
outfile.writelines('LINES %15d %15d\n' %(len(rays[shotnumber]), len(rays[shotnumber]) + nPoints))
outfile.writelines('LINES %15d %15d\n' % (len(rays[shotnumber]), len(rays[shotnumber]) + nPoints))
# write indices
#print("Writing indices to VTK file...")
# print("Writing indices to VTK file...")
count = 0
for raynumber in rays[shotnumber].keys():
outfile.writelines('%d ' %(len(rays[shotnumber][raynumber])))
outfile.writelines('%d ' % (len(rays[shotnumber][raynumber])))
for index in range(len(rays[shotnumber][raynumber])):
outfile.writelines('%d ' %(count))
outfile.writelines('%d ' % (count))
count += 1
outfile.writelines('\n')
# outfile.writelines('POINT_DATA %15d\n' %(nPoints))
# outfile.writelines('SCALARS rays float %d\n' %(1))
# outfile.writelines('LOOKUP_TABLE default\n')
# outfile.writelines('POINT_DATA %15d\n' %(nPoints))
# outfile.writelines('SCALARS rays float %d\n' %(1))
# outfile.writelines('LOOKUP_TABLE default\n')
# # write velocity
# print("Writing velocity values to VTK file...")
# for velocity in vel:
# outfile.writelines('%10f\n' %velocity)
# outfile.close()
# print("Wrote velocity grid for %d points to file: %s" %(nPoints, outputfile))
# # write velocity
# print("Writing velocity values to VTK file...")
# for velocity in vel:
# outfile.writelines('%10f\n' %velocity)
# outfile.close()
# print("Wrote velocity grid for %d points to file: %s" %(nPoints, outputfile))

146
pylot/core/active/fmtomoUtils.py
View File

@ -2,11 +2,12 @@
import sys
import numpy as np
def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'abs', inputfileref = 'vgridsref.in'):
def vgrids2VTK(inputfile='vgrids.in', outputfile='vgrids.vtk', absOrRel='abs', inputfileref='vgridsref.in'):
'''
Generate a vtk-file readable by e.g. paraview from FMTOMO output vgrids.in
'''
R = 6371. # earth radius
R = 6371. # earth radius
outfile = open(outputfile, 'w')
number, delta, start, vel = _readVgrid(inputfile)
@ -19,7 +20,9 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'a
nPoints = nR * nTheta * nPhi
nX = nPhi; nY = nTheta; nZ = nR
nX = nPhi;
nY = nTheta;
nZ = nR
sZ = sR - R
sX = _getDistance(sPhi)
@ -36,29 +39,29 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'a
outfile.writelines('ASCII\n')
outfile.writelines('DATASET STRUCTURED_POINTS\n')
outfile.writelines('DIMENSIONS %d %d %d\n' %(nX, nY, nZ))
outfile.writelines('ORIGIN %f %f %f\n' %(sX, sY, sZ))
outfile.writelines('SPACING %f %f %f\n' %(dX, dY, dZ))
outfile.writelines('DIMENSIONS %d %d %d\n' % (nX, nY, nZ))
outfile.writelines('ORIGIN %f %f %f\n' % (sX, sY, sZ))
outfile.writelines('SPACING %f %f %f\n' % (dX, dY, dZ))
outfile.writelines('POINT_DATA %15d\n' %(nPoints))
outfile.writelines('POINT_DATA %15d\n' % (nPoints))
if absOrRel == 'abs':
outfile.writelines('SCALARS velocity float %d\n' %(1))
outfile.writelines('SCALARS velocity float %d\n' % (1))
elif absOrRel == 'rel':
outfile.writelines('SCALARS velChangePercent float %d\n' %(1))
outfile.writelines('SCALARS velChangePercent float %d\n' % (1))
outfile.writelines('LOOKUP_TABLE default\n')
# write velocity
if absOrRel == 'abs':
print("Writing velocity values to VTK file...")
for velocity in vel:
outfile.writelines('%10f\n' %velocity)
outfile.writelines('%10f\n' % velocity)
elif absOrRel == 'rel':
nref, dref, sref, velref = _readVgrid(inputfileref)
nR_ref, nTheta_ref, nPhi_ref = nref
if not len(velref) == len(vel):
print('ERROR: Number of gridpoints mismatch for %s and %s'%(inputfile, inputfileref))
print('ERROR: Number of gridpoints mismatch for %s and %s' % (inputfile, inputfileref))
return
#velrel = [((vel - velref) / velref * 100) for vel, velref in zip(vel, velref)]
# velrel = [((vel - velref) / velref * 100) for vel, velref in zip(vel, velref)]
velrel = []
for velocities in zip(vel, velref):
v, vref = velocities
@ -68,18 +71,19 @@ def vgrids2VTK(inputfile = 'vgrids.in', outputfile = 'vgrids.vtk', absOrRel = 'a
velrel.append(0)
if not nR_ref == nR and nTheta_ref == nTheta and nPhi_ref == nPhi:
print('ERROR: Dimension mismatch of grids %s and %s'%(inputfile, inputfileref))
print('ERROR: Dimension mismatch of grids %s and %s' % (inputfile, inputfileref))
return
print("Writing velocity values to VTK file...")
for velocity in velrel:
outfile.writelines('%10f\n' %velocity)
print('Pertubations: min: %s %%, max: %s %%'%(min(velrel), max(velrel)))
outfile.writelines('%10f\n' % velocity)
print('Pertubations: min: %s %%, max: %s %%' % (min(velrel), max(velrel)))
outfile.close()
print("Wrote velocity grid for %d points to file: %s" %(nPoints, outputfile))
print("Wrote velocity grid for %d points to file: %s" % (nPoints, outputfile))
return
def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
def rays2VTK(fnin, fdirout='./vtk_files/', nthPoint=50):
'''
Writes VTK file(s) for FMTOMO rays from rays.dat
@ -96,12 +100,12 @@ def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
while True:
raynumber += 1
firstline = infile.readline()
if firstline == '': break # break at EOF
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
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))
print('Invalid ray number %d for shot number %d' % (raynumber, shotnumber))
continue
nRayPoints = int(infile.readline().split()[0])
if not shotnumber in rays.keys():
@ -110,14 +114,15 @@ def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
for index in range(nRayPoints):
if index % nthPoint is 0 or index == (nRayPoints - 1):
rad, lat, lon = infile.readline().split()
rays[shotnumber][raynumber].append([_getDistance(np.rad2deg(float(lon))), _getDistance(np.rad2deg(float(lat))), float(rad) - R])
rays[shotnumber][raynumber].append(
[_getDistance(np.rad2deg(float(lon))), _getDistance(np.rad2deg(float(lat))), float(rad) - R])
else:
dummy = infile.readline()
infile.close()
for shotnumber in rays.keys():
fnameout = fdirout + 'rays%03d.vtk'%(shotnumber)
fnameout = fdirout + 'rays%03d.vtk' % (shotnumber)
outfile = open(fnameout, 'w')
nPoints = 0
@ -126,32 +131,33 @@ def rays2VTK(fnin, fdirout = './vtk_files/', nthPoint = 50):
nPoints += 1
# write header
#print("Writing header for VTK file...")
print("Writing shot %d to file %s" %(shotnumber, fnameout))
# print("Writing header for VTK file...")
print("Writing shot %d to file %s" % (shotnumber, fnameout))
outfile.writelines('# vtk DataFile Version 3.1\n')
outfile.writelines('FMTOMO rays\n')
outfile.writelines('ASCII\n')
outfile.writelines('DATASET POLYDATA\n')
outfile.writelines('POINTS %15d float\n' %(nPoints))
outfile.writelines('POINTS %15d float\n' % (nPoints))
# write coordinates
#print("Writing coordinates to VTK file...")
# print("Writing coordinates to VTK file...")
for raynumber in rays[shotnumber].keys():
for raypoint in rays[shotnumber][raynumber]:
outfile.writelines('%10f %10f %10f \n' %(raypoint[0], raypoint[1], raypoint[2]))
outfile.writelines('%10f %10f %10f \n' % (raypoint[0], raypoint[1], raypoint[2]))
outfile.writelines('LINES %15d %15d\n' %(len(rays[shotnumber]), len(rays[shotnumber]) + nPoints))
outfile.writelines('LINES %15d %15d\n' % (len(rays[shotnumber]), len(rays[shotnumber]) + nPoints))
# write indices
#print("Writing indices to VTK file...")
# print("Writing indices to VTK file...")
count = 0
for raynumber in rays[shotnumber].keys():
outfile.writelines('%d ' %(len(rays[shotnumber][raynumber])))
outfile.writelines('%d ' % (len(rays[shotnumber][raynumber])))
for index in range(len(rays[shotnumber][raynumber])):
outfile.writelines('%d ' %(count))
outfile.writelines('%d ' % (count))
count += 1
outfile.writelines('\n')
def _readVgrid(filename):
def readNumberOfPoints(filename):
fin = open(filename, 'r')
@ -162,7 +168,7 @@ def _readVgrid(filename):
nPhi = int(vglines[1].split()[2])
print('readNumberOf Points: Awaiting %d grid points in %s'
%(nR*nTheta*nPhi, filename))
% (nR * nTheta * nPhi, filename))
fin.close()
return nR, nTheta, nPhi
@ -192,7 +198,8 @@ def _readVgrid(filename):
'''
Reads in velocity from vgrids file and returns a list containing all values in the same order
'''
vel = []; count = 0
vel = [];
count = 0
fin = open(filename, 'r')
vglines = fin.readlines()
@ -201,7 +208,7 @@ def _readVgrid(filename):
if count > 4:
vel.append(float(line.split()[0]))
print("Read %d points out of file: %s" %(count - 4, filename))
print("Read %d points out of file: %s" % (count - 4, filename))
return vel
# Theta, Phi in radians, R in km
@ -218,6 +225,7 @@ def _readVgrid(filename):
start = (sR, sTheta, sPhi)
return number, delta, start, vel
def _generateGrids(number, delta, start):
nR, nTheta, nPhi = number
dR, dTheta, dPhi = delta
@ -227,14 +235,15 @@ def _generateGrids(number, delta, start):
ePhi = sPhi + (nPhi - 1) * dPhi
eTheta = sTheta + (nTheta - 1) * dTheta
thetaGrid = np.linspace(sTheta, eTheta, num = nTheta)
phiGrid = np.linspace(sPhi, ePhi, num = nPhi)
rGrid = np.linspace(sR, eR, num = nR)
thetaGrid = np.linspace(sTheta, eTheta, num=nTheta)
phiGrid = np.linspace(sPhi, ePhi, num=nPhi)
rGrid = np.linspace(sR, eR, num=nR)
return (thetaGrid, phiGrid, rGrid)
def addCheckerboard(spacing = 10., pertubation = 0.1, inputfile = 'vgrids.in',
outputfile = 'vgrids_cb.in', ampmethod = 'linear', rect = (None, None)):
def addCheckerboard(spacing=10., pertubation=0.1, inputfile='vgrids.in',
outputfile='vgrids_cb.in', ampmethod='linear', rect=(None, None)):
'''
Add a checkerboard to an existing vgrids.in velocity model.
@ -244,13 +253,14 @@ def addCheckerboard(spacing = 10., pertubation = 0.1, inputfile = 'vgrids.in',
:param: pertubation, pertubation (default: 0.1 = 10%)
type: float
'''
def correctSpacing(spacing, delta, disttype = None):
def correctSpacing(spacing, delta, disttype=None):
if spacing > delta:
spacing_corr = round(spacing / delta) * delta
elif spacing < delta:
spacing_corr = delta
print('The spacing of the checkerboard of %s (%s) was corrected to '
'a value of %s to fit the grid spacing of %s.' %(spacing, disttype, spacing_corr, delta))
'a value of %s to fit the grid spacing of %s.' % (spacing, disttype, spacing_corr, delta))
return spacing_corr
def linearAmp(InCell):
@ -265,7 +275,7 @@ def addCheckerboard(spacing = 10., pertubation = 0.1, inputfile = 'vgrids.in',
else:
return 0
def ampFunc(InCell, method = 'linear', rect = None):
def ampFunc(InCell, method='linear', rect=None):
if method == 'linear':
return linearAmp(InCell)
if method == 'rect' and rect is not None:
@ -273,7 +283,7 @@ def addCheckerboard(spacing = 10., pertubation = 0.1, inputfile = 'vgrids.in',
else:
print('ampFunc: Could not amplify cb pattern')
decm = 0.3 # diagonal elements of the covariance matrix (grid3dg's default value is 0.3)
decm = 0.3 # diagonal elements of the covariance matrix (grid3dg's default value is 0.3)
outfile = open(outputfile, 'w')
number, delta, start, vel = _readVgrid(inputfile)
@ -287,10 +297,10 @@ def addCheckerboard(spacing = 10., pertubation = 0.1, inputfile = 'vgrids.in',
nPoints = nR * nTheta * nPhi
# write header for velocity grid file (in RADIANS)
outfile.writelines('%10s %10s \n' %(1, 1))
outfile.writelines('%10s %10s %10s\n' %(nR, nTheta, nPhi))
outfile.writelines('%10s %10s %10s\n' %(dR, np.deg2rad(dTheta), np.deg2rad(dPhi)))
outfile.writelines('%10s %10s %10s\n' %(sR, np.deg2rad(sTheta), np.deg2rad(sPhi)))
outfile.writelines('%10s %10s \n' % (1, 1))
outfile.writelines('%10s %10s %10s\n' % (nR, nTheta, nPhi))
outfile.writelines('%10s %10s %10s\n' % (dR, np.deg2rad(dTheta), np.deg2rad(dPhi)))
outfile.writelines('%10s %10s %10s\n' % (sR, np.deg2rad(sTheta), np.deg2rad(sPhi)))
spacR = correctSpacing(spacing, dR, '[meter], R')
spacTheta = correctSpacing(_getAngle(spacing), dTheta, '[degree], Theta')
@ -298,7 +308,8 @@ def addCheckerboard(spacing = 10., pertubation = 0.1, inputfile = 'vgrids.in',
count = 0
evenOdd = 1
even = 0; odd = 0
even = 0;
odd = 0
# In the following loop it is checked whether the positive distance from the border of the model
# for a point on the grid divided by the spacing is even or odd and then pertubated.
@ -309,21 +320,21 @@ def addCheckerboard(spacing = 10., pertubation = 0.1, inputfile = 'vgrids.in',
# The amplification factor ampFactor comes from a linear relationship and ranges between 0 (cell border)
# and 1 (cell middle)
for radius in rGrid:
rInCell = (radius - sR - dR/2) / spacR
rInCell = (radius - sR - dR / 2) / spacR
ampR = ampFunc(rInCell, ampmethod, rect)
if np.floor(rInCell) % 2:
evenOddR = 1
else:
evenOddR = -1
for theta in thetaGrid:
thetaInCell = (theta - sTheta - dTheta/2) / spacTheta
thetaInCell = (theta - sTheta - dTheta / 2) / spacTheta
ampTheta = ampFunc(thetaInCell, ampmethod, rect)
if np.floor(thetaInCell) % 2:
evenOddT = 1
else:
evenOddT = -1
for phi in phiGrid:
phiInCell = (phi - sPhi - dPhi/2) / spacPhi
phiInCell = (phi - sPhi - dPhi / 2) / spacPhi
ampPhi = ampFunc(phiInCell, ampmethod, rect)
if np.floor(phiInCell) % 2:
evenOddP = 1
@ -334,19 +345,20 @@ def addCheckerboard(spacing = 10., pertubation = 0.1, inputfile = 'vgrids.in',
evenOdd = evenOddR * evenOddT * evenOddP * ampFactor
velocity += evenOdd * pertubation * velocity
outfile.writelines('%10s %10s\n'%(velocity, decm))
outfile.writelines('%10s %10s\n' % (velocity, decm))
count += 1
progress = float(count) / float(nPoints) * 100
_update_progress(progress)
print('Added checkerboard to the grid in file %s with a spacing of %s and a pertubation of %s %%. '
'Outputfile: %s.'%(inputfile, spacing, pertubation*100, outputfile))
'Outputfile: %s.' % (inputfile, spacing, pertubation * 100, outputfile))
outfile.close()
def addBox(x = (None, None), y = (None, None), z = (None, None),
boxvelocity = 1.0, inputfile = 'vgrids.in',
outputfile = 'vgrids_box.in'):
def addBox(x=(None, None), y=(None, None), z=(None, None),
boxvelocity=1.0, inputfile='vgrids.in',
outputfile='vgrids_box.in'):
'''
Add a box with constant velocity to an existing vgrids.in velocity model.
@ -363,7 +375,7 @@ def addBox(x = (None, None), y = (None, None), z = (None, None),
type: float
'''
R = 6371.
decm = 0.3 # diagonal elements of the covariance matrix (grid3dg's default value is 0.3)
decm = 0.3 # diagonal elements of the covariance matrix (grid3dg's default value is 0.3)
outfile = open(outputfile, 'w')
theta1 = _getAngle(y[0])
@ -375,7 +387,7 @@ def addBox(x = (None, None), y = (None, None), z = (None, None),
print('Adding box to grid with theta = (%s, %s), phi = (%s, %s), '
'r = (%s, %s), velocity = %s [km/s]'
%(theta1, theta2, phi1, phi2, r1, r2, boxvelocity))
% (theta1, theta2, phi1, phi2, r1, r2, boxvelocity))
number, delta, start, vel = _readVgrid(inputfile)
@ -388,10 +400,10 @@ def addBox(x = (None, None), y = (None, None), z = (None, None),
nPoints = nR * nTheta * nPhi
# write header for velocity grid file (in RADIANS)
outfile.writelines('%10s %10s \n' %(1, 1))
outfile.writelines('%10s %10s %10s\n' %(nR, nTheta, nPhi))
outfile.writelines('%10s %10s %10s\n' %(dR, np.deg2rad(dTheta), np.deg2rad(dPhi)))
outfile.writelines('%10s %10s %10s\n' %(sR, np.deg2rad(sTheta), np.deg2rad(sPhi)))
outfile.writelines('%10s %10s \n' % (1, 1))
outfile.writelines('%10s %10s %10s\n' % (nR, nTheta, nPhi))
outfile.writelines('%10s %10s %10s\n' % (dR, np.deg2rad(dTheta), np.deg2rad(dPhi)))
outfile.writelines('%10s %10s %10s\n' % (sR, np.deg2rad(sTheta), np.deg2rad(sPhi)))
count = 0
for radius in rGrid:
@ -413,20 +425,22 @@ def addBox(x = (None, None), y = (None, None), z = (None, None),
if rFlag * thetaFlag * phiFlag is not 0:
velocity = boxvelocity
outfile.writelines('%10s %10s\n'%(velocity, decm))
outfile.writelines('%10s %10s\n' % (velocity, decm))
count += 1
progress = float(count) / float(nPoints) * 100
_update_progress(progress)
print('Added box to the grid in file %s. '
'Outputfile: %s.'%(inputfile, outputfile))
'Outputfile: %s.' % (inputfile, outputfile))
outfile.close()
def _update_progress(progress):
sys.stdout.write("%d%% done \r" % (progress) )
sys.stdout.write("%d%% done \r" % (progress))
sys.stdout.flush()
def _getAngle(distance):
'''
Function returns the angle on a Sphere of the radius R = 6371 [km] for a distance [km].
@ -436,9 +450,9 @@ def _getAngle(distance):
angle = distance * 180. / (PI * R)
return angle
def _getDistance(angle):
PI = np.pi
R = 6371.
distance = angle / 180 * (PI * R)
return distance

342
pylot/core/active/seismicArrayPreparation.py
View File

@ -3,6 +3,7 @@ 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.
@ -15,6 +16,7 @@ class SeisArray(object):
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.recfile = recfile
self._receiverlines = {}
@ -35,7 +37,7 @@ class SeisArray(object):
'''
for receiver in self._receiverlist:
traceID = int(receiver.split()[0])
lineID = int(receiver.split()[1])
lineID = int(receiver.split()[1])
if not lineID in self._receiverlines.keys():
self._receiverlines[lineID] = []
self._receiverlines[lineID].append(traceID)
@ -132,7 +134,7 @@ class SeisArray(object):
if traceID2 < traceID1:
direction = -1
return direction
print "Error: Same Value for traceID1 = %s and traceID2 = %s" %(traceID1, traceID2)
print "Error: Same Value for traceID1 = %s and traceID2 = %s" % (traceID1, traceID2)
def _checkCoordDirection(self, traceID1, traceID2, coordinate):
'''
@ -144,14 +146,15 @@ class SeisArray(object):
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)
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
mean_distance = abs(
self._getReceiverValue(traceID1, coordinate) - self._getReceiverValue(traceID2, coordinate)) / num_spaces
return mean_distance
def interpolateValues(self, coordinate):
@ -159,22 +162,22 @@ class SeisArray(object):
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]
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
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)
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
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):
'''
@ -206,7 +209,7 @@ class SeisArray(object):
z = float(line[3])
self._sourceLocs[pointID] = (x, y, z)
def interpZcoords4rec(self, method = 'linear'):
def interpZcoords4rec(self, method='linear'):
'''
Interpolates z values for all receivers.
'''
@ -214,7 +217,8 @@ class SeisArray(object):
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)
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):
@ -239,7 +243,9 @@ class SeisArray(object):
'''
Returns a list of all measured receivers known to SeisArray.
'''
x = []; y = []; z = []
x = [];
y = [];
z = []
for traceID in self.getMeasuredReceivers().keys():
x.append(self.getMeasuredReceivers()[traceID][0])
y.append(self.getMeasuredReceivers()[traceID][1])
@ -250,7 +256,9 @@ class SeisArray(object):
'''
Returns a list of all measured topography points known to the SeisArray.
'''
x = []; y = []; z = []
x = [];
y = [];
z = []
for pointID in self.getMeasuredTopo().keys():
x.append(self.getMeasuredTopo()[pointID][0])
y.append(self.getMeasuredTopo()[pointID][1])
@ -261,7 +269,9 @@ class SeisArray(object):
'''
Returns a list of all measured source locations known to SeisArray.
'''
x = []; y = []; z = []
x = [];
y = [];
z = []
for pointID in self.getSourceLocations().keys():
x.append(self.getSourceLocations()[pointID][0])
y.append(self.getSourceLocations()[pointID][1])
@ -285,7 +295,9 @@ class SeisArray(object):
'''
Returns a list of all receivers (measured and interpolated).
'''
x = []; y =[]; z = []
x = [];
y = [];
z = []
for traceID in self.getReceiverCoordinates().keys():
x.append(self.getReceiverCoordinates()[traceID][0])
y.append(self.getReceiverCoordinates()[traceID][1])
@ -303,7 +315,7 @@ class SeisArray(object):
self._interpolateXY4rec()
self.interpZcoords4rec()
def interpolateTopography(self, nTheta, nPhi, thetaSN, phiWE, elevation = 0.25, method = 'linear'):
def interpolateTopography(self, nTheta, nPhi, thetaSN, phiWE, elevation=0.25, method='linear'):
'''
Interpolate Z values on a regular grid with cushion nodes e.g. to use it as FMTOMO topography interface.
Returns a surface in form of a list of points [[x1, y1, z1], [x2, y2, y2], ...] (cartesian).
@ -325,7 +337,7 @@ class SeisArray(object):
'''
return self.interpolateOnRegularGrid(nTheta, nPhi, thetaSN, phiWE, elevation, method)
def interpolateOnRegularGrid(self, nTheta, nPhi, thetaSN, phiWE, elevation, method = 'linear'):
def interpolateOnRegularGrid(self, nTheta, nPhi, thetaSN, phiWE, elevation, method='linear'):
'''
Interpolate Z values on a regular grid with cushion nodes e.g. to use it as FMTOMO topography interface.
Returns a surface in form of a list of points [[x1, y1, z1], [x2, y2, y2], ...] (cartesian).
@ -349,8 +361,8 @@ class SeisArray(object):
surface = []
print "Interpolating interface on regular grid with the dimensions:"
print "nTheta = %s, nPhi = %s, thetaSN = %s, phiWE = %s"%(nTheta, nPhi, thetaSN, phiWE)
print "method = %s, elevation = %s" %(method, elevation)
print "nTheta = %s, nPhi = %s, thetaSN = %s, phiWE = %s" % (nTheta, nPhi, thetaSN, phiWE)
print "method = %s, elevation = %s" % (method, elevation)
thetaS, thetaN = thetaSN
phiW, phiE = phiWE
@ -361,18 +373,19 @@ class SeisArray(object):
deltaTheta = (thetaN - thetaS) / (nTheta - 1)
deltaPhi = (phiE - phiW) / (nPhi - 1)
thetaGrid = np.linspace(thetaS - deltaTheta, thetaN + deltaTheta, num = nTheta + 2) # +2 cushion nodes
phiGrid = np.linspace(phiW - deltaPhi, phiE + deltaPhi, num = nPhi + 2) # +2 cushion nodes
thetaGrid = np.linspace(thetaS - deltaTheta, thetaN + deltaTheta, num=nTheta + 2) # +2 cushion nodes
phiGrid = np.linspace(phiW - deltaPhi, phiE + deltaPhi, num=nPhi + 2) # +2 cushion nodes
nTotal = len(thetaGrid) * len(phiGrid); count = 0
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)
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 = griddata((measured_x, measured_y), measured_z, (xval, yval), method='nearest')
z = float(z) + elevation
surface.append((xval, yval, z))
count += 1
@ -382,8 +395,8 @@ class SeisArray(object):
return surface
def generateFMTOMOinputFromArray(self, nPointsPropgrid, nPointsInvgrid,
zBotTop, cushionfactor, interpolationMethod = 'linear',
customgrid = 'mygrid.in', writeVTK = True):
zBotTop, cushionfactor, interpolationMethod='linear',
customgrid='mygrid.in', writeVTK=True):
'''
Generate FMTOMO input files from the SeisArray dimensions.
Generates: vgrids.in, interfaces.in, propgrid.in
@ -406,10 +419,10 @@ class SeisArray(object):
print('\n------------------------------------------------------------')
print('Automatically generating input for FMTOMO from array size.')
print('Propgrid: nR = %s, nTheta = %s, nPhi = %s'%(nRP, nThetaP, nPhiP))
print('Interpolation Grid and Interfaces Grid: nR = %s, nTheta = %s, nPhi = %s'%(nRI, nThetaI, nPhiI))
print('Bottom and Top of model: (%s, %s)'%(zBotTop[0], zBotTop[1]))
print('Method: %s, customgrid = %s'%(interpolationMethod, customgrid))
print('Propgrid: nR = %s, nTheta = %s, nPhi = %s' % (nRP, nThetaP, nPhiP))
print('Interpolation Grid and Interfaces Grid: nR = %s, nTheta = %s, nPhi = %s' % (nRI, nThetaI, nPhiI))
print('Bottom and Top of model: (%s, %s)' % (zBotTop[0], zBotTop[1]))
print('Method: %s, customgrid = %s' % (interpolationMethod, customgrid))
print('------------------------------------------------------------')
def getZmin(surface):
@ -418,31 +431,31 @@ class SeisArray(object):
z.append(point[2])
return min(z)
self.generatePropgrid(nThetaP, nPhiP, nRP, zBotTop, cushionfactor = cushionfactor,
cushionpropgrid = 0.05)
surface = self.generateVgrid(nThetaI, nPhiI, nRI, zBotTop, method = interpolationMethod,
cushionfactor = cushionfactor, infilename = customgrid,
returnTopo = True)
self.generatePropgrid(nThetaP, nPhiP, nRP, zBotTop, cushionfactor=cushionfactor,
cushionpropgrid=0.05)
surface = self.generateVgrid(nThetaI, nPhiI, nRI, zBotTop, method=interpolationMethod,
cushionfactor=cushionfactor, infilename=customgrid,
returnTopo=True)
depthmax = abs(zBotTop[0] - getZmin(surface)) - 1.0 # cushioning for the bottom interface
depthmax = abs(zBotTop[0] - getZmin(surface)) - 1.0 # cushioning for the bottom interface
interf1, interf2 = self.generateInterfaces(nThetaI, nPhiI, depthmax, cushionfactor = cushionfactor,
returnInterfaces = True, method = interpolationMethod)
interf1, interf2 = self.generateInterfaces(nThetaI, nPhiI, depthmax, cushionfactor=cushionfactor,
returnInterfaces=True, method=interpolationMethod)
if writeVTK == True:
from pylot.core.active import fmtomoUtils
self.surface2VTK(interf1, filename = 'interface1.vtk')
self.surface2VTK(interf2, filename = 'interface2.vtk')
self.surface2VTK(interf1, filename='interface1.vtk')
self.surface2VTK(interf2, filename='interface2.vtk')
self.receivers2VTK()
self.sources2VTK()
fmtomoUtils.vgrids2VTK()
def generateReceiversIn(self, outfilename = 'receivers.in'):
def generateReceiversIn(self, outfilename='receivers.in'):
outfile = open(outfilename, 'w')
recx, recy, recz = self.getReceiverLists()
nsrc = len(self.getSourceLocations())
outfile.writelines('%s\n'%(len(zip(recx, recy, recz)) * nsrc))
outfile.writelines('%s\n' % (len(zip(recx, recy, recz)) * nsrc))
for index in range(nsrc):
for point in zip(recx, recy, recz):
@ -450,17 +463,16 @@ class SeisArray(object):
rad = - rz
lat = self._getAngle(ry)
lon = self._getAngle(rx)
outfile.writelines('%15s %15s %15s\n'%(rad, lat, lon))
outfile.writelines('%15s\n'%(1))
outfile.writelines('%15s\n'%(index + 1))
outfile.writelines('%15s\n'%(1))
outfile.writelines('%15s %15s %15s\n' % (rad, lat, lon))
outfile.writelines('%15s\n' % (1))
outfile.writelines('%15s\n' % (index + 1))
outfile.writelines('%15s\n' % (1))
outfile.close()
def generateInterfaces(self, nTheta, nPhi, depthmax, cushionfactor = 0.1,
outfilename = 'interfaces.in', method = 'linear',
returnInterfaces = False):
def generateInterfaces(self, nTheta, nPhi, depthmax, cushionfactor=0.1,
outfilename='interfaces.in', method='linear',
returnInterfaces=False):
'''
Create an interfaces.in file for FMTOMO from the SeisArray boundaries.
:param: nTheta, number of points in Theta
@ -494,22 +506,22 @@ class SeisArray(object):
deltaPhi = abs(phiE - phiW) / float((nPhi - 1))
# write header for interfaces grid file (in RADIANS)
outfile.writelines('%10s\n' %(nInterfaces))
outfile.writelines('%10s %10s\n' %(nTheta + 2, nPhi + 2)) # +2 cushion nodes
outfile.writelines('%10s %10s\n' %(np.deg2rad(deltaTheta), np.deg2rad(deltaPhi)))
outfile.writelines('%10s %10s\n' %(np.deg2rad(thetaS - deltaTheta), np.deg2rad(phiW - deltaPhi)))
outfile.writelines('%10s\n' % (nInterfaces))
outfile.writelines('%10s %10s\n' % (nTheta + 2, nPhi + 2)) # +2 cushion nodes
outfile.writelines('%10s %10s\n' % (np.deg2rad(deltaTheta), np.deg2rad(deltaPhi)))
outfile.writelines('%10s %10s\n' % (np.deg2rad(thetaS - deltaTheta), np.deg2rad(phiW - deltaPhi)))
interface1 = self.interpolateTopography(nTheta, nPhi, thetaSN, phiWE, method = method)
interface2 = self.interpolateOnRegularGrid(nTheta, nPhi, thetaSN, phiWE, -depthmax, method = method)
interface1 = self.interpolateTopography(nTheta, nPhi, thetaSN, phiWE, method=method)
interface2 = self.interpolateOnRegularGrid(nTheta, nPhi, thetaSN, phiWE, -depthmax, method=method)
for point in interface1:
z = point[2]
outfile.writelines('%10s\n'%(z + R))
outfile.writelines('%10s\n' % (z + R))
outfile.writelines('\n')
for point in interface2:
z = point[2]
outfile.writelines('%10s\n'%(z + R))
outfile.writelines('%10s\n' % (z + R))
outfile.close()
@ -519,7 +531,7 @@ class SeisArray(object):
print('Finished generating interfaces.')
print('------------------------------------------------------------')
def getThetaPhiFromArray(self, cushionfactor = 0.1):
def getThetaPhiFromArray(self, cushionfactor=0.1):
'''
Determine and returns PhiWE (tuple: (West, East)) and thetaSN (tuple (South, North)) from the SeisArray boundaries.
@ -535,8 +547,8 @@ class SeisArray(object):
thetaSN = (theta_min - cushionTheta, theta_max + cushionTheta)
return thetaSN, phiWE
def generatePropgrid(self, nTheta, nPhi, nR, Rbt, cushionfactor, cushionpropgrid = 0.05,
refinement = (5, 5), outfilename = 'propgrid.in'):
def generatePropgrid(self, nTheta, nPhi, nR, Rbt, cushionfactor, cushionpropgrid=0.05,
refinement=(5, 5), outfilename='propgrid.in'):
'''
Create a propergation grid file for FMTOMO using SeisArray boundaries
@ -567,9 +579,9 @@ class SeisArray(object):
print('\n------------------------------------------------------------')
print('Generating Propagation Grid for nTheta = %s, nPhi'
' = %s, nR = %s and a cushioning of %s'
%(nTheta, nPhi, nR, cushionpropgrid))
% (nTheta, nPhi, nR, cushionpropgrid))
print('Bottom of the grid: %s, top of the grid %s'
%(Rbt[0], Rbt[1]))
% (Rbt[0], Rbt[1]))
thetaSN, phiWE = self.getThetaPhiFromArray(cushionfactor)
@ -584,20 +596,20 @@ class SeisArray(object):
deltaPhi = abs(phiE - phiW) / float(nPhi - 1)
deltaR = abs(rbot - rtop) / float(nR - 1)
outfile.writelines('%10s %10s %10s\n' %(nR, nTheta, nPhi))
outfile.writelines('%10s %10s %10s\n' %(deltaR, deltaTheta, deltaPhi))
outfile.writelines('%10s %10s %10s\n' %(rtop, thetaS, phiW))
outfile.writelines('%10s %10s\n' %refinement)
outfile.writelines('%10s %10s %10s\n' % (nR, nTheta, nPhi))
outfile.writelines('%10s %10s %10s\n' % (deltaR, deltaTheta, deltaPhi))
outfile.writelines('%10s %10s %10s\n' % (rtop, thetaS, phiW))
outfile.writelines('%10s %10s\n' % refinement)
outfile.close()
print('Created Propagation Grid and saved it to %s' %outfilename)
print('Created Propagation Grid and saved it to %s' % outfilename)
print('------------------------------------------------------------')
def generateVgrid(self, nTheta, nPhi, nR, Rbt, thetaSN = None,
phiWE = None, cushionfactor = 0.1,
outfilename = 'vgrids.in', method = 'linear',
infilename = 'mygrid.in', returnTopo = False):
def generateVgrid(self, nTheta, nPhi, nR, Rbt, thetaSN=None,
phiWE=None, cushionfactor=0.1,
outfilename='vgrids.in', method='linear',
infilename='mygrid.in', returnTopo=False):
'''
Generate a velocity grid for fmtomo regarding topography with a linear gradient starting at the topography with 0.34 [km/s].
@ -641,11 +653,14 @@ class SeisArray(object):
return nlayers
def readMygrid(filename):
ztop = []; zbot = []; vtop = []; vbot = []
ztop = [];
zbot = [];
vtop = [];
vbot = []
infile = open(filename, 'r')
nlayers = readMygridNlayers(filename)
print('\nreadMygrid: Reading file %s.'%filename)
print('\nreadMygrid: Reading file %s.' % filename)
for index in range(nlayers):
line1 = infile.readline()
line2 = infile.readline()
@ -655,11 +670,11 @@ class SeisArray(object):
vbot.append(float(line2.split()[1]))
print('Layer %s:\n[Top: v = %s [km/s], z = %s [m]]'
'\n[Bot: v = %s [km/s], z = %s [m]]'
%(index + 1, vtop[index], ztop[index],
vbot[index], zbot[index]))
% (index + 1, vtop[index], ztop[index],
vbot[index], zbot[index]))
if not ztop[0] == 0:
print('ERROR: there must be a velocity set for z = 0 in the file %s'%filename)
print('ERROR: there must be a velocity set for z = 0 in the file %s' % filename)
print('e.g.:\n0 0.33\n-5 1.0\netc.')
infile.close()
@ -667,7 +682,7 @@ class SeisArray(object):
R = 6371.
vmin = 0.34
decm = 0.3 # diagonal elements of the covariance matrix (grid3dg's default value is 0.3)
decm = 0.3 # diagonal elements of the covariance matrix (grid3dg's default value is 0.3)
outfile = open(outfilename, 'w')
# generate dimensions of the grid from array
@ -685,28 +700,29 @@ class SeisArray(object):
deltaR = abs(rbot - rtop) / float((nR - 1))
# create a regular grid including +2 cushion nodes in every direction
thetaGrid = np.linspace(thetaS - deltaTheta, thetaN + deltaTheta, num = nTheta + 2) # +2 cushion nodes
phiGrid = np.linspace(phiW - deltaPhi, phiE + deltaPhi, num = nPhi + 2) # +2 cushion nodes
rGrid = np.linspace(rbot - deltaR, rtop + deltaR, num = nR + 2) # +2 cushion nodes
thetaGrid = np.linspace(thetaS - deltaTheta, thetaN + deltaTheta, num=nTheta + 2) # +2 cushion nodes
phiGrid = np.linspace(phiW - deltaPhi, phiE + deltaPhi, num=nPhi + 2) # +2 cushion nodes
rGrid = np.linspace(rbot - deltaR, rtop + deltaR, num=nR + 2) # +2 cushion nodes
nTotal = len(rGrid) * len(thetaGrid) * len(phiGrid)
print("Total number of grid nodes: %s"%nTotal)
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' %(deltaR, np.deg2rad(deltaTheta), np.deg2rad(deltaPhi)))
outfile.writelines('%10s %10s %10s\n' %(rbot - deltaR, np.deg2rad(thetaS - deltaTheta), np.deg2rad(phiW - deltaPhi)))
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' % (deltaR, np.deg2rad(deltaTheta), np.deg2rad(deltaPhi)))
outfile.writelines(
'%10s %10s %10s\n' % (rbot - deltaR, np.deg2rad(thetaS - deltaTheta), np.deg2rad(phiW - deltaPhi)))
surface = self.interpolateTopography(nTheta, nPhi, thetaSN, phiWE, method = method)
surface = self.interpolateTopography(nTheta, nPhi, thetaSN, phiWE, method=method)
nlayers = readMygridNlayers(infilename)
ztop, zbot, vtop, vbot = readMygrid(infilename)
print("\nGenerating velocity grid for FMTOMO. "
"Output filename = %s, interpolation method = %s"%(outfilename, method))
"Output filename = %s, interpolation method = %s" % (outfilename, method))
print("nTheta = %s, nPhi = %s, nR = %s, "
"thetaSN = %s, phiWE = %s, Rbt = %s"%(nTheta, nPhi, nR, thetaSN, phiWE, Rbt))
"thetaSN = %s, phiWE = %s, Rbt = %s" % (nTheta, nPhi, nR, thetaSN, phiWE, Rbt))
count = 0
for radius in rGrid:
@ -721,32 +737,36 @@ class SeisArray(object):
depth = -(R + topo - radius)
if depth > 1:
vel = 0.0
elif 1 >= depth > 0: # cushioning around topography
elif 1 >= depth > 0: # cushioning around topography
vel = vtop[0]
else:
for index in range(nlayers):
if (ztop[index]) >= depth > (zbot[index]):
vel = (depth - ztop[index]) / (zbot[index] - ztop[index]) * (vbot[index] - vtop[index]) + vtop[index]
vel = (depth - ztop[index]) / (zbot[index] - ztop[index]) * (
vbot[index] - vtop[index]) + vtop[index]
break
if not (ztop[index]) >= depth > (zbot[index]):
print('ERROR in grid inputfile, could not find velocity for a z-value of %s in the inputfile'%(depth-topo))
print(
'ERROR in grid inputfile, could not find velocity for a z-value of %s in the inputfile' % (
depth - topo))
return
count += 1
if vel < 0:
print('ERROR, vel <0; z, topo, zbot, vbot, vtop:', depth, topo, zbot[index], vbot[index], vtop[index])
outfile.writelines('%10s %10s\n'%(vel, decm))
print(
'ERROR, vel <0; z, topo, zbot, vbot, vtop:', depth, topo, zbot[index], vbot[index], vtop[index])
outfile.writelines('%10s %10s\n' % (vel, decm))
progress = float(count) / float(nTotal) * 100
self._update_progress(progress)
print('\nWrote %d points to file %s for %d layers'%(count, outfilename, nlayers))
print('\nWrote %d points to file %s for %d layers' % (count, outfilename, nlayers))
print('------------------------------------------------------------')
outfile.close()
if returnTopo == True:
return surface
def exportAll(self, filename = 'interpolated_receivers.out'):
def exportAll(self, filename='interpolated_receivers.out'):
'''
Exports all receivers to an input file for ActiveSeismoPick3D.
'''
@ -755,11 +775,11 @@ class SeisArray(object):
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.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, pointsize = 10):
def plotArray2D(self, plot_topo=False, highlight_measured=False, annotations=True, pointsize=10):
import matplotlib.pyplot as plt
plt.interactive(True)
fig = plt.figure()
@ -770,36 +790,36 @@ class SeisArray(object):
xrc, yrc, zrc = self.getReceiverLists()
if len(xrc) > 0:
ax.plot(xrc, yrc, 'k.', markersize = pointsize, label = 'all receivers')
ax.plot(xrc, yrc, 'k.', markersize=pointsize, label='all receivers')
if len(xsc) > 0:
ax.plot(xsc, ysc, 'b*', markersize = pointsize, label = 'shot locations')
ax.plot(xsc, ysc, 'b*', markersize=pointsize, label='shot locations')
if plot_topo == True:
ax.plot(xmt, ymt, 'b.', markersize = pointsize, label = 'measured topo points')
ax.plot(xmt, ymt, 'b.', markersize=pointsize, label='measured topo points')
if highlight_measured == True:
ax.plot(xmr, ymr, 'r.', markersize = pointsize, label = 'measured receivers')
ax.plot(xmr, ymr, 'r.', markersize=pointsize, label='measured receivers')
plt.title('2D plot of seismic array %s'%self.recfile)
plt.title('2D plot of seismic array %s' % self.recfile)
ax.set_xlabel('X [m]')
ax.set_ylabel('Y [m]')
ax.set_aspect('equal')
plt.legend()
if annotations == True:
for traceID in self.getReceiverCoordinates().keys():
ax.annotate((' ' + str(traceID)), xy = (self._getXreceiver(traceID), self._getYreceiver(traceID)), fontsize = 'x-small', color = 'k')
ax.annotate((' ' + str(traceID)), xy=(self._getXreceiver(traceID), self._getYreceiver(traceID)),
fontsize='x-small', color='k')
for shotnumber in self.getSourceLocations().keys():
ax.annotate((' ' + str(shotnumber)), xy = (self._getXshot(shotnumber), self._getYshot(shotnumber)), fontsize = 'x-small', color = 'b')
ax.annotate((' ' + str(shotnumber)), xy=(self._getXshot(shotnumber), self._getYshot(shotnumber)),
fontsize='x-small', color='b')
def plotArray3D(self, ax = None):
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')
ax = plt.axes(projection='3d')
xmt, ymt, zmt = self.getMeasuredTopoLists()
xmr, ymr, zmr = self.getMeasuredReceiverLists()
@ -808,20 +828,21 @@ class SeisArray(object):
plt.title('3D plot of seismic array.')
if len(xmt) > 0:
ax.plot(xmt, ymt, zmt, 'b.', markersize = 10, label = 'measured topo points')
ax.plot(xmt, ymt, zmt, 'b.', markersize=10, label='measured topo points')
if len(xrc) > 0:
ax.plot(xrc, yrc, zrc, 'k.', markersize = 10, label = 'all receivers')
ax.plot(xrc, yrc, zrc, 'k.', markersize=10, label='all receivers')
if len(xmr) > 0:
ax.plot(xmr, ymr, zmr, 'ro', label = 'measured receivers')
ax.plot(xmr, ymr, zmr, 'ro', label='measured receivers')
if len(xsc) > 0:
ax.plot(xsc, ysc, zsc, 'b*', label = 'shot locations')
ax.set_xlabel('X [m]'); ax.set_ylabel('Y [m]'); ax.set_zlabel('Z [m]')
ax.plot(xsc, ysc, zsc, 'b*', label='shot locations')
ax.set_xlabel('X [m]');
ax.set_ylabel('Y [m]');
ax.set_zlabel('Z [m]')
ax.legend()
return ax
def plotSurface3D(self, ax = None, step = 0.5, method = 'linear', exag = False):
def plotSurface3D(self, ax=None, step=0.5, method='linear', exag=False):
from matplotlib import cm
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
@ -829,7 +850,7 @@ class SeisArray(object):
if ax == None:
fig = plt.figure()
ax = plt.axes(projection = '3d')
ax = plt.axes(projection='3d')
xmt, ymt, zmt = self.getMeasuredTopoLists()
xmr, ymr, zmr = self.getMeasuredReceiverLists()
@ -838,31 +859,33 @@ class SeisArray(object):
y = ymt + ymr
z = zmt + zmr
xaxis = np.arange(min(x)+1, max(x), step)
yaxis = np.arange(min(y)+1, max(y), step)
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)
zgrid = griddata((x, y), z, (xgrid, ygrid), method=method)
surf = ax.plot_surface(xgrid, ygrid, zgrid, linewidth = 0, cmap = cm.jet, vmin = min(z), vmax = max(z))
surf = ax.plot_surface(xgrid, ygrid, zgrid, linewidth=0, cmap=cm.jet, vmin=min(z), vmax=max(z))
cbar = plt.colorbar(surf)
cbar.set_label('Elevation [m]')
if exag == False:
ax.set_zlim(-(max(x) - min(x)/2),(max(x) - min(x)/2))
ax.set_zlim(-(max(x) - min(x) / 2), (max(x) - min(x) / 2))
ax.set_aspect('equal')
ax.set_xlabel('X [m]'); ax.set_ylabel('Y [m]'); ax.set_zlabel('Z [m]')
ax.set_xlabel('X [m]');
ax.set_ylabel('Y [m]');
ax.set_zlabel('Z [m]')
ax.legend()
return ax
def _update_progress(self, progress):
sys.stdout.write("%d%% done \r" % (progress) )
sys.stdout.write("%d%% done \r" % (progress))
sys.stdout.flush()
def surface2VTK(self, surface, filename = 'surface.vtk'):
def surface2VTK(self, surface, filename='surface.vtk'):
'''
Generates a vtk file from all points of a surface as generated by interpolateTopography.
'''
@ -876,7 +899,7 @@ class SeisArray(object):
outfile.writelines('Surface Points\n')
outfile.writelines('ASCII\n')
outfile.writelines('DATASET POLYDATA\n')
outfile.writelines('POINTS %15d float\n' %(nPoints))
outfile.writelines('POINTS %15d float\n' % (nPoints))
# write coordinates
print("Writing coordinates to VTK file...")
@ -885,14 +908,14 @@ class SeisArray(object):
y = point[1]
z = point[2]
outfile.writelines('%10f %10f %10f \n' %(x, y, z))
outfile.writelines('%10f %10f %10f \n' % (x, y, z))
outfile.writelines('VERTICES %15d %15d\n' %(nPoints, 2 * nPoints))
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('%10d %10d\n' % (1, index))
# outfile.writelines('POINT_DATA %15d\n' %(nPoints))
# outfile.writelines('SCALARS traceIDs int %d\n' %(1))
@ -904,10 +927,10 @@ class SeisArray(object):
# outfile.writelines('%10d\n' %traceID)
outfile.close()
print("Wrote %d points to file: %s" %(nPoints, filename))
print("Wrote %d points to file: %s" % (nPoints, filename))
return
def receivers2VTK(self, filename = 'receivers.vtk'):
def receivers2VTK(self, filename='receivers.vtk'):
'''
Generates a vtk file from all receivers of the SeisArray object.
'''
@ -925,7 +948,7 @@ class SeisArray(object):
outfile.writelines('Receivers with traceIDs\n')
outfile.writelines('ASCII\n')
outfile.writelines('DATASET POLYDATA\n')
outfile.writelines('POINTS %15d float\n' %(nPoints))
outfile.writelines('POINTS %15d float\n' % (nPoints))
# write coordinates
print("Writing coordinates to VTK file...")
@ -934,29 +957,29 @@ class SeisArray(object):
y = self._getYreceiver(traceID)
z = self._getZreceiver(traceID)
outfile.writelines('%10f %10f %10f \n' %(x, y, z))
outfile.writelines('%10f %10f %10f \n' % (x, y, z))
outfile.writelines('VERTICES %15d %15d\n' %(nPoints, 2 * nPoints))
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('%10d %10d\n' % (1, index))
outfile.writelines('POINT_DATA %15d\n' %(nPoints))
outfile.writelines('SCALARS traceIDs int %d\n' %(1))
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.writelines('%10d\n' % traceID)
outfile.close()
print("Wrote %d receiver for to file: %s" %(nPoints, filename))
print("Wrote %d receiver for to file: %s" % (nPoints, filename))
return
def sources2VTK(self, filename = 'sources.vtk'):
def sources2VTK(self, filename='sources.vtk'):
'''
Generates a vtk-file for all source locations in the SeisArray object.
'''
@ -974,7 +997,7 @@ class SeisArray(object):
outfile.writelines('Shots with shotnumbers\n')
outfile.writelines('ASCII\n')
outfile.writelines('DATASET POLYDATA\n')
outfile.writelines('POINTS %15d float\n' %(nPoints))
outfile.writelines('POINTS %15d float\n' % (nPoints))
# write coordinates
print("Writing coordinates to VTK file...")
@ -983,35 +1006,34 @@ class SeisArray(object):
y = self._getYshot(shotnumber)
z = self._getZshot(shotnumber)
outfile.writelines('%10f %10f %10f \n' %(x, y, z))
outfile.writelines('%10f %10f %10f \n' % (x, y, z))
outfile.writelines('VERTICES %15d %15d\n' %(nPoints, 2 * nPoints))
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('%10d %10d\n' % (1, index))
outfile.writelines('POINT_DATA %15d\n' %(nPoints))
outfile.writelines('SCALARS shotnumbers int %d\n' %(1))
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.writelines('%10d\n' % shotnumber)
outfile.close()
print("Wrote %d sources to file: %s" %(nPoints, filename))
print("Wrote %d sources to file: %s" % (nPoints, filename))
return
def saveSeisArray(self, filename = 'seisArray.pickle'):
def saveSeisArray(self, filename='seisArray.pickle'):
import cPickle
outfile = open(filename, 'wb')
cPickle.dump(self, outfile, -1)
print('saved SeisArray to file %s'%(filename))
print('saved SeisArray to file %s' % (filename))
@staticmethod
def from_pickle(filename):

286
pylot/core/active/seismicshot.py
View File

@ -11,12 +11,15 @@ 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):
'''
SuperClass for a seismic shot object.
'''
def __init__(self, obsfile):
'''
Initialize seismic shot object giving an inputfile.
@ -29,8 +32,8 @@ class SeismicShot(object):
self.srcCoordlist = None
self.traceIDs = None
self.picks = {}
self.pwindow= {}
self.manualpicks= {}
self.pwindow = {}
self.manualpicks = {}
self.snr = {}
self.snrthreshold = {}
self.timeArray = {}
@ -61,10 +64,10 @@ class SeismicShot(object):
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:
# 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:
# self.traces.remove(trace)
def updateTraceList(self):
'''
@ -87,22 +90,22 @@ class SeismicShot(object):
self.setParameters('tmovwind', tmovwind)
def setOrder(self, order):
self.setParameters('order', order)
self.setParameters('order', order)
def setTsignal(self, tsignal):
self.setParameters('tsignal', tsignal)
self.setParameters('tsignal', tsignal)
def setTgap(self, tgap):
self.setParameters('tgap', tgap)
self.setParameters('tgap', tgap)
def setShotnumber(self, shotname):
self.setParameters('shotname', shotname)
self.setParameters('shotname', shotname)
def setRecfile(self, recfile):
self.setParameters('recfile', recfile)
self.setParameters('recfile', recfile)
def setSourcefile(self, sourcefile):
self.setParameters('sourcefile', sourcefile)
self.setParameters('sourcefile', sourcefile)
def getParas(self):
return self.paras
@ -144,15 +147,15 @@ class SeismicShot(object):
def getManualLatest(self, traceID):
return self.manualpicks[traceID]['lpp']
def getPick(self, traceID, returnRemoved = False):
def getPick(self, traceID, returnRemoved=False):
if not self.getPickFlag(traceID) == 0:
return self.picks[traceID]['mpp']
if returnRemoved == True:
#print('getPick: Returned removed pick for shot %d, traceID %d' %(self.getShotnumber(), traceID))
# print('getPick: Returned removed pick for shot %d, traceID %d' %(self.getShotnumber(), traceID))
return self.picks[traceID]['mpp']
def getPickIncludeRemoved(self, traceID):
return self.getPick(traceID, returnRemoved = True)
return self.getPick(traceID, returnRemoved=True)
def getEarliest(self, traceID):
return self.picks[traceID]['epp']
@ -163,13 +166,13 @@ class SeismicShot(object):
def getSymmetricPickError(self, traceID):
pickerror = self.picks[traceID]['spe']
if np.isnan(pickerror) == True:
print "SPE is NaN for shot %s, traceID %s"%(self.getShotnumber(), traceID)
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)) / 2
if np.isnan(pickerror) == True:
print("PE is NaN for shot %s, traceID %s"%(self.getShotnumber(), traceID))
print("PE is NaN for shot %s, traceID %s" % (self.getShotnumber(), traceID))
return pickerror
def getStreamTraceIDs(self):
@ -207,15 +210,15 @@ class SeismicShot(object):
def getRecCoordlist(self):
if self.recCoordlist is None:
coordlist = open(self.getRecfile(),'r').readlines()
#print 'Reading receiver coordinates from %s' %(self.getRecfile())
coordlist = open(self.getRecfile(), 'r').readlines()
# print 'Reading receiver coordinates from %s' %(self.getRecfile())
self.recCoordlist = coordlist
return self.recCoordlist
def getSrcCoordlist(self):
if self.srcCoordlist is None:
coordlist = open(self.getSourcefile(),'r').readlines()
#print 'Reading shot coordinates from %s' %(self.getSourcefile())
coordlist = open(self.getSourcefile(), 'r').readlines()
# print 'Reading shot coordinates from %s' %(self.getSourcefile())
self.srcCoordlist = coordlist
return self.srcCoordlist
@ -239,7 +242,7 @@ class SeismicShot(object):
:type: int
'''
return HOScf(self.getSingleStream(traceID), self.getCut(),
self.getTmovwind(), self.getOrder(), stealthMode = True)
self.getTmovwind(), self.getOrder(), stealthMode=True)
def getAICcf(self, traceID):
'''
@ -262,7 +265,7 @@ 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(), stealthMode = True)
return AICcf(st_cf, self.getCut(), self.getTmovwind(), stealthMode=True)
def getSingleStream(self, traceID): ########## SEG2 / SEGY ? ##########
'''
@ -271,16 +274,16 @@ class SeismicShot(object):
:param: traceID
:type: int
'''
#traces = [trace for trace in self.traces if int(trace.stats.seg2['CHANNEL_NUMBER']) == traceID]
# traces = [trace for trace in self.traces if int(trace.stats.seg2['CHANNEL_NUMBER']) == traceID]
traces = [trace for trace in self.traces if int(trace.stats.channel) == traceID]
if len(traces) == 1:
return Stream(traces)
self.setPick(traceID, None)
print 'Warning: ambigious or empty traceID: %s' % traceID
#raise ValueError('ambigious or empty traceID: %s' % traceID)
# raise ValueError('ambigious or empty traceID: %s' % traceID)
def pickTraces(self, traceID, windowsize, folm, HosAic = 'hos'): ########## input variables ##########
def pickTraces(self, traceID, windowsize, folm, HosAic='hos'): ########## input variables ##########
# LOCALMAX NOT IMPLEMENTED!
'''
Intitiate picking for a trace.
@ -306,7 +309,7 @@ class SeismicShot(object):
:param: HosAic, get hos or aic pick (can be 'hos'(default) or 'aic')
:type: 'string'
'''
hoscf = self.getHOScf(traceID) ### determination of both, HOS and AIC (need to change threshold-picker) ###
hoscf = self.getHOScf(traceID) ### determination of both, HOS and AIC (need to change threshold-picker) ###
aiccf = self.getAICcf(traceID)
self.folm = folm
@ -318,7 +321,7 @@ class SeismicShot(object):
self.setPick(traceID, setHosAic[HosAic])
def setEarllatepick(self, traceID, nfac = 1.5):
def setEarllatepick(self, traceID, nfac=1.5):
tgap = self.getTgap()
tsignal = self.getTsignal()
tnoise = self.getPickIncludeRemoved(traceID) - tgap
@ -326,17 +329,17 @@ class SeismicShot(object):
(self.picks[traceID]['epp'],
self.picks[traceID]['lpp'],
self.picks[traceID]['spe']) = earllatepicker(self.getSingleStream(traceID),
nfac, (tnoise, tgap, tsignal),
self.getPickIncludeRemoved(traceID),
stealthMode = True)
nfac, (tnoise, tgap, tsignal),
self.getPickIncludeRemoved(traceID),
stealthMode=True)
if self.picks[traceID]['epp'] < 0:
self.picks[traceID]['epp']
#print('setEarllatepick: Set epp to 0 because it was < 0')
# print('setEarllatepick: Set epp to 0 because it was < 0')
# TEST OF 1/2 PICKERROR
# self.picks[traceID]['spe'] *= 0.5
# TEST OF 1/2 PICKERROR
# TEST OF 1/2 PICKERROR
# self.picks[traceID]['spe'] *= 0.5
# TEST OF 1/2 PICKERROR
def threshold(self, hoscf, aiccf, windowsize, pickwindow, folm):
'''
@ -365,10 +368,11 @@ class SeismicShot(object):
leftb = int(pickwindow[0] / self.getCut()[1] * len(hoscflist))
rightb = int(pickwindow[1] / self.getCut()[1] * len(hoscflist))
#threshold = folm * max(hoscflist[leftb : rightb]) # combination of local maximum and threshold
# threshold = folm * max(hoscflist[leftb : rightb]) # combination of local maximum and threshold
### TEST TEST
threshold = folm * (max(hoscflist[leftb : rightb]) - min(hoscflist[leftb : rightb])) + min(hoscflist[leftb : rightb]) # combination of local maximum and threshold
threshold = folm * (max(hoscflist[leftb: rightb]) - min(hoscflist[leftb: rightb])) + min(
hoscflist[leftb: rightb]) # combination of local maximum and threshold
### TEST TEST
m = leftb
@ -378,8 +382,8 @@ class SeismicShot(object):
hoscftime = list(hoscf.getTimeArray())[m]
lb = max(0, m - windowsize[0]) # if window exceeds t = 0
aiccfcut = list(aiccf.getCF())[lb : m + windowsize[1]]
lb = max(0, m - windowsize[0]) # if window exceeds t = 0
aiccfcut = list(aiccf.getCF())[lb: m + windowsize[1]]
if len(aiccfcut) > 0:
n = aiccfcut.index(min(aiccfcut))
else:
@ -401,13 +405,13 @@ class SeismicShot(object):
'''
shotX, shotY, shotZ = self.getSrcLoc()
recX, recY, recZ = self.getRecLoc(traceID)
dist = np.sqrt((shotX-recX)**2 + (shotY-recY)**2 + (shotZ-recZ)**2)
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)
raise ValueError("Distance is NaN for traceID %s" % traceID)
return dist
#return abs(float(self.getSrcLoc(traceID))-float(self.getRecLoc(traceID)))
# return abs(float(self.getSrcLoc(traceID))-float(self.getRecLoc(traceID)))
def getRecLoc(self, traceID): ########## input FILENAME ##########
'''
@ -417,7 +421,7 @@ class SeismicShot(object):
:param: traceID
:type: int
'''
if traceID == 0: # artificial traceID 0 with pick at t = 0
if traceID == 0: # artificial traceID 0 with pick at t = 0
return self.getSrcLoc()
coordlist = self.getRecCoordlist()
@ -428,9 +432,9 @@ class SeismicShot(object):
z = coordlist[i].split()[3]
return float(x), float(y), float(z)
#print "WARNING: traceID %s not found" % traceID
# print "WARNING: traceID %s not found" % traceID
raise ValueError("traceID %s not found" % traceID)
#return float(self.getSingleStream(traceID)[0].stats.seg2['RECEIVER_LOCATION'])
# return float(self.getSingleStream(traceID)[0].stats.seg2['RECEIVER_LOCATION'])
def getSrcLoc(self): ########## input FILENAME ##########
'''
@ -444,9 +448,10 @@ class SeismicShot(object):
y = coordlist[i].split()[2]
z = coordlist[i].split()[3]
return float(x), float(y), float(z)
#return float(self.getSingleStream(traceID)[0].stats.seg2['SOURCE_LOCATION'])
# return float(self.getSingleStream(traceID)[0].stats.seg2['SOURCE_LOCATION'])
def getTraceIDs4Dist(self, distance = 0, distancebin = (0, 0)): ########## nur fuer 2D benutzt, 'distance bins' ##########
def getTraceIDs4Dist(self, distance=0,
distancebin=(0, 0)): ########## nur fuer 2D benutzt, 'distance bins' ##########
'''
Returns the traceID(s) for a certain distance between source and receiver.
Used for 2D Tomography. TO BE IMPROVED.
@ -460,39 +465,39 @@ class SeismicShot(object):
traceID_list = []
for trace in self.traces:
#traceID = int(trace.stats.seg2['CHANNEL_NUMBER'])
traceID = int(trace.stats.channel)
if distance != 0:
if self.getDistance(traceID) == distance:
traceID_list.append(traceID)
if distancebin[0] >= 0 and distancebin[1] > 0:
if distancebin[0] < self.getDistance(traceID) < distancebin[1]:
traceID_list.append(traceID)
# traceID = int(trace.stats.seg2['CHANNEL_NUMBER'])
traceID = int(trace.stats.channel)
if distance != 0:
if self.getDistance(traceID) == distance:
traceID_list.append(traceID)
if distancebin[0] >= 0 and distancebin[1] > 0:
if distancebin[0] < self.getDistance(traceID) < distancebin[1]:
traceID_list.append(traceID)
if len(traceID_list) > 0:
return traceID_list
# 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.
# 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
# :param: traceID
# :type: int
# :param: picklist, list containing the manual picks (mostlikely, earliest, latest).
# :type: list
# '''
# picks = picklist[traceID - 1].split()
# mostlikely = float(picks[1])
# earliest = float(picks[2])
# latest = float(picks[3])
# :param: picklist, list containing the manual picks (mostlikely, earliest, latest).
# :type: list
# '''
# picks = picklist[traceID - 1].split()
# mostlikely = float(picks[1])
# earliest = float(picks[2])
# latest = float(picks[3])
# 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)
# 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)
def setManualPicksFromFile(self, directory = 'picks'):
def setManualPicksFromFile(self, directory='picks'):
'''
Read manual picks from *.pck file.
The * must be identical with the shotnumber.
@ -517,8 +522,7 @@ class SeismicShot(object):
else:
self.setManualPickFlag(traceID, 1)
def setPick(self, traceID, pick): ########## siehe Kommentar ##########
def setPick(self, traceID, pick): ########## siehe Kommentar ##########
if not traceID in self.picks.keys():
self.picks[traceID] = {}
self.picks[traceID]['mpp'] = pick
@ -568,7 +572,7 @@ class SeismicShot(object):
tsignal = self.getTsignal()
tnoise = self.getPick(traceID) - tgap
self.snr[traceID] = getSNR(self.getSingleStream(traceID), (tnoise,tgap,tsignal), self.getPick(traceID))
self.snr[traceID] = getSNR(self.getSingleStream(traceID), (tnoise, tgap, tsignal), self.getPick(traceID))
def setSNRthreshold(self, traceID, snrthreshold):
self.snrthreshold[traceID] = snrthreshold
@ -583,12 +587,11 @@ class SeismicShot(object):
if self.getRecLoc(traceID)[0] > self.getSrcLoc()[0]:
distancearray.append(self.getDistance(traceID))
elif self.getRecLoc(traceID)[0] <= self.getSrcLoc()[0]:
distancearray.append((-1)*self.getDistance(traceID))
distancearray.append((-1) * self.getDistance(traceID))
return distancearray
def plot2dttc(self, ax = None): ########## 2D ##########
def plot2dttc(self, ax=None): ########## 2D ##########
'''
Function to plot the traveltime curve for automated picks of a shot. 2d only! ATM: X DIRECTION!!
'''
@ -605,15 +608,16 @@ class SeismicShot(object):
# shotnumbers = [shotnumbers for (shotnumbers, shotnames) in sorted(zip(shotnumbers, shotnames))]
plotarray = sorted(zip(self.getDistArray4ttcPlot(), picks))
x = []; y = []
x = [];
y = []
for point in plotarray:
x.append(point[0])
y.append(point[1])
ax.plot(x, y,'r', label = "Automatic Picks")
ax.text(0.5, 0.9, 'shot: %s' %self.getShotnumber(), transform = ax.transAxes
, horizontalalignment = 'center')
ax.plot(x, y, 'r', label="Automatic Picks")
ax.text(0.5, 0.9, 'shot: %s' % self.getShotnumber(), transform=ax.transAxes
, horizontalalignment='center')
def plotmanual2dttc(self, ax = None): ########## 2D ##########
def plotmanual2dttc(self, ax=None): ########## 2D ##########
'''
Function to plot the traveltime curve for manual picks of a shot. 2D only!
'''
@ -632,11 +636,12 @@ class SeismicShot(object):
ax = fig.add_subplot(111)
plotarray = sorted(zip(self.getDistArray4ttcPlot(), manualpicktimesarray))
x = []; y = []
x = [];
y = []
for point in plotarray:
x.append(point[0])
y.append(point[1])
ax.plot(x, y, 'b', label = "Manual Picks")
ax.plot(x, y, 'b', label="Manual Picks")
# def plotpickwindow(self): ########## 2D ##########
# '''
@ -656,10 +661,10 @@ class SeismicShot(object):
# plt.plot(self.getDistArray4ttcPlot(), pickwindowarray_lowerb, ':k')
# plt.plot(self.getDistArray4ttcPlot(), pickwindowarray_upperb, ':k')
def plotTrace(self, traceID, plotSNR = True, lw = 1):
def plotTrace(self, traceID, plotSNR=True, lw=1):
fig = plt.figure()
ax = fig.add_subplot(111)
ax = self._drawStream(traceID, ax = ax)
ax = self._drawStream(traceID, ax=ax)
tgap = self.getTgap()
tsignal = self.getTsignal()
@ -667,31 +672,32 @@ class SeismicShot(object):
tnoise = pick - tgap
snr, snrdb, noiselevel = self.getSNR(traceID)
ax.plot([0, tnoise], [noiselevel, noiselevel], 'm', linewidth = lw, label = 'noise level')
ax.plot([tnoise, pick], [noiselevel, noiselevel], 'g:', linewidth = lw, label = 'gap')
ax.plot([tnoise + tgap, pick + tsignal], [noiselevel * snr, noiselevel * snr], 'b', linewidth = lw, label = 'signal level')
ax.plot([0, tnoise], [noiselevel, noiselevel], 'm', linewidth=lw, label='noise level')
ax.plot([tnoise, pick], [noiselevel, noiselevel], 'g:', linewidth=lw, label='gap')
ax.plot([tnoise + tgap, pick + tsignal], [noiselevel * snr, noiselevel * snr], 'b', linewidth=lw,
label='signal level')
ax.legend()
ax.text(0.05, 0.9, 'SNR: %s' %snr, transform = ax.transAxes)
ax.text(0.05, 0.9, 'SNR: %s' % snr, transform=ax.transAxes)
def plot_traces(self, traceID): ########## 2D, muss noch mehr verbessert werden ##########
def plot_traces(self, traceID): ########## 2D, muss noch mehr verbessert werden ##########
from matplotlib.widgets import Button
def onclick(event):
self.setPick(traceID, event.xdata)
if self.getSNR(traceID)[0] > 1:
self.setEarllatepick(traceID)
self._drawStream(traceID, refresh = True)
self._drawCFs(traceID, folm, refresh = True)
self._drawStream(traceID, refresh=True)
self._drawCFs(traceID, folm, refresh=True)
fig.canvas.mpl_disconnect(self.traces4plot[traceID]['cid'])
plt.draw()
def rmPick(event = None):
def rmPick(event=None):
self.removePick(traceID)
self._drawStream(traceID, refresh = True)
self._drawCFs(traceID, folm, refresh = True)
self._drawStream(traceID, refresh=True)
self._drawCFs(traceID, folm, refresh=True)
plt.draw()
def connectButton(event = None):
def connectButton(event=None):
cid = fig.canvas.mpl_connect('button_press_event', onclick)
self.traces4plot[traceID]['cid'] = cid
@ -701,13 +707,13 @@ class SeismicShot(object):
folm = self.folm
fig = plt.figure()
ax1 = fig.add_subplot(2,1,1)
ax2 = fig.add_subplot(2,1,2, sharex = ax1)
ax1 = fig.add_subplot(2, 1, 1)
ax2 = fig.add_subplot(2, 1, 2, sharex=ax1)
axb1 = fig.add_axes([0.15, 0.91, 0.05, 0.03])
axb2 = fig.add_axes([0.22, 0.91, 0.05, 0.03])
button1 = Button(axb1, 'repick', color = 'red', hovercolor = 'grey')
button1 = Button(axb1, 'repick', color='red', hovercolor='grey')
button1.on_clicked(connectButton)
button2 = Button(axb2, 'delete', color = 'green', hovercolor = 'grey')
button2 = Button(axb2, 'delete', color='green', hovercolor='grey')
button2.on_clicked(rmPick)
fig.canvas.mpl_connect('close_event', cleanup)
@ -717,7 +723,7 @@ class SeismicShot(object):
self._drawStream(traceID)
self._drawCFs(traceID, folm)
def _drawStream(self, traceID, refresh = False, ax = None):
def _drawStream(self, traceID, refresh=False, ax=None):
from pylot.core.util.utils import getGlobalTimes
from pylot.core.util.utils import prepTimeAxis
@ -737,27 +743,27 @@ class SeismicShot(object):
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')
% (self.getShotnumber(), traceID, self.getPick(traceID)))
ax.plot(timeaxis, stream[0].data, 'k', label='trace')
ax.plot([self.getPick(traceID), self.getPick(traceID)],
[ax.get_ylim()[0],
ax.get_ylim()[1]],
'r', label = 'most likely')
'r', label='most likely')
if self.getEarliest(traceID) is not None:
ax.plot([self.getEarliest(traceID), self.getEarliest(traceID)],
[ax.get_ylim()[0],
ax.get_ylim()[1]],
'g:', label = 'earliest')
'g:', label='earliest')
if self.getLatest(traceID) is not None:
ax.plot([self.getLatest(traceID), self.getLatest(traceID)],
[ax.get_ylim()[0],
ax.get_ylim()[1]],
'b:', label = 'latest')
'b:', label='latest')
ax.legend()
return ax
def _drawCFs(self, traceID, folm = None, refresh = False):
def _drawCFs(self, traceID, folm=None, refresh=False):
hoscf = self.getHOScf(traceID)
aiccf = self.getAICcf(traceID)
ax = self.traces4plot[traceID]['ax2']
@ -769,30 +775,30 @@ class SeismicShot(object):
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(hoscf.getTimeArray(), hoscf.getCF(), 'b', label='HOS')
ax.plot(hoscf.getTimeArray(), aiccf.getCF(), 'g', label='AIC')
ax.plot([self.getPick(traceID), self.getPick(traceID)],
[ax.get_ylim()[0],
ax.get_ylim()[1]],
'r', label = 'most likely')
'r', label='most likely')
if self.getEarliest(traceID) is not None:
ax.plot([self.getEarliest(traceID), self.getEarliest(traceID)],
[ax.get_ylim()[0],
ax.get_ylim()[1]],
'g:', label = 'earliest')
'g:', label='earliest')
if self.getLatest(traceID) is not None:
ax.plot([self.getLatest(traceID), self.getLatest(traceID)],
[ax.get_ylim()[0],
ax.get_ylim()[1]],
'b:', label = 'latest')
'b:', label='latest')
if folm is not None:
ax.plot([0, self.getPick(traceID)],
[folm * max(hoscf.getCF()), folm * max(hoscf.getCF())],
'm:', label = 'folm = %s' %folm)
'm:', label='folm = %s' % folm)
ax.set_xlabel('Time [s]')
ax.legend()
def plot3dttc(self, step = 0.5, contour = False, plotpicks = False, method = 'linear', ax = None):
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.
@ -824,20 +830,20 @@ class SeismicShot(object):
xaxis = np.arange(min(x) + step, max(x), step)
yaxis = np.arange(min(y) + step, max(y), step)
xgrid, ygrid = np.meshgrid(xaxis, yaxis)
zgrid = griddata((x, y), z, (xgrid, ygrid), method = method)
zgrid = griddata((x, y), z, (xgrid, ygrid), method=method)
if ax == None:
fig = plt.figure()
ax = plt.axes(projection = '3d')
ax = plt.axes(projection='3d')
xsrc, ysrc, zsrc = self.getSrcLoc()
if contour == True:
ax.contour3D(xgrid,ygrid,zgrid,20)
ax.contour3D(xgrid, ygrid, zgrid, 20)
else:
ax.plot_surface(xgrid, ygrid, zgrid, linewidth = 0, cmap = cm.jet, vmin = min(z), vmax = max(z))
ax.plot([xsrc], [ysrc], [self.getPick(0)], 'k*', markersize = 20) # plot source location
ax.plot([xsrc], [ysrc], [self.getPick(0)], 'r*', markersize = 15) # plot source location
ax.plot_surface(xgrid, ygrid, zgrid, linewidth=0, cmap=cm.jet, vmin=min(z), vmax=max(z))
ax.plot([xsrc], [ysrc], [self.getPick(0)], 'k*', markersize=20) # plot source location
ax.plot([xsrc], [ysrc], [self.getPick(0)], 'r*', markersize=15) # plot source location
if plotpicks == True:
ax.plot(x, y, z, 'k.')
@ -847,7 +853,7 @@ class SeismicShot(object):
plotmethod[method](*args)
def matshow(self, ax = None, step = 0.5, method = 'linear', plotRec = True, annotations = True, colorbar = True, legend = True):
def matshow(self, ax=None, step=0.5, method='linear', plotRec=True, annotations=True, colorbar=True, legend=True):
'''
Plots a 2D matrix of the interpolated traveltimes. This needs less performance than plot3dttc
@ -868,9 +874,12 @@ class SeismicShot(object):
from matplotlib import cm
cmap = cm.jet
x = []; xcut = []
y = []; ycut = []
z = []; zcut = []
x = [];
xcut = []
y = [];
ycut = []
z = [];
zcut = []
for traceID in self.picks.keys():
if self.getPickFlag(traceID) != 0:
@ -882,7 +891,7 @@ class SeismicShot(object):
ycut.append(self.getRecLoc(traceID)[1])
zcut.append(self.getPickIncludeRemoved(traceID))
tmin = 0.8 * min(z) # 20% cushion for colorbar
tmin = 0.8 * min(z) # 20% cushion for colorbar
tmax = 1.2 * max(z)
xaxis = np.arange(min(x), max(x), step)
@ -895,10 +904,11 @@ class SeismicShot(object):
ax = plt.axes()
count = 0
ax.imshow(zgrid, extent = [min(x), max(x), min(y), max(y)], vmin = tmin, vmax = tmax, cmap = cmap, origin = 'lower', alpha = 0.85)
ax.text(0.5, 0.95, 'shot: %s' %self.getShotnumber(), transform = ax.transAxes
, horizontalalignment = 'center')
sc = ax.scatter(x, y, c = z, s = 30, label = 'picked shots', vmin = tmin, vmax = tmax, cmap = cmap, linewidths = 1.5)
ax.imshow(zgrid, extent=[min(x), max(x), min(y), max(y)], vmin=tmin, vmax=tmax, cmap=cmap, origin='lower',
alpha=0.85)
ax.text(0.5, 0.95, 'shot: %s' % self.getShotnumber(), transform=ax.transAxes
, horizontalalignment='center')
sc = ax.scatter(x, y, c=z, s=30, label='picked shots', vmin=tmin, vmax=tmax, cmap=cmap, linewidths=1.5)
label = None
for xyz in zip(xcut, ycut, zcut):
x, y, z = xyz
@ -907,7 +917,7 @@ class SeismicShot(object):
z = 'w'
if count == 1:
label = 'cut out shots'
ax.scatter(x, y, c = z, s = 30, edgecolor = 'm', label = label, vmin = tmin, vmax = tmax, cmap = cmap, linewidths = 1.5)
ax.scatter(x, y, c=z, s=30, edgecolor='m', label=label, vmin=tmin, vmax=tmax, cmap=cmap, linewidths=1.5)
if colorbar == True:
cbar = plt.colorbar(sc)
cbar.set_label('Time [s]')
@ -916,17 +926,15 @@ class SeismicShot(object):
ax.legend()
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.plot(self.getSrcLoc()[0], self.getSrcLoc()[1],'*k', markersize = 15) # plot source location
ax.plot(self.getSrcLoc()[0], self.getSrcLoc()[1], '*k', markersize=15) # plot source location
if annotations == True:
for traceID in self.getTraceIDlist():
if self.getPickFlag(traceID) is not 0:
ax.annotate(' %s' %traceID , xy = (self.getRecLoc(traceID)[0], self.getRecLoc(traceID)[1]),
fontsize = 'x-small', color = 'k')
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')
ax.annotate(' %s' % traceID, xy=(self.getRecLoc(traceID)[0], self.getRecLoc(traceID)[1]),
fontsize='x-small', color='r')
plt.show()

147
pylot/core/active/surveyPlotTools.py
View File

@ -2,8 +2,10 @@
import matplotlib.pyplot as plt
import math
import numpy as np
plt.interactive(True)
class regions(object):
'''
A class used for manual inspection and processing of all picks for the user.
@ -57,10 +59,10 @@ class regions(object):
for shot in self.shot_dict.values():
for traceID in shot.getTraceIDlist():
allpicks.append((shot.getDistance(traceID),
shot.getPickIncludeRemoved(traceID),
shot.getShotnumber(),
traceID,
shot.getPickFlag(traceID)))
shot.getPickIncludeRemoved(traceID),
shot.getShotnumber(),
traceID,
shot.getPickFlag(traceID)))
allpicks.sort()
self._allpicks = allpicks
@ -74,9 +76,9 @@ class regions(object):
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)
eclick.ydata,
erelease.xdata,
erelease.ydata)
x0 = min(eclick.xdata, erelease.xdata)
x1 = max(eclick.xdata, erelease.xdata)
y0 = min(eclick.ydata, erelease.ydata)
@ -105,18 +107,18 @@ class regions(object):
self.disconnectPoly()
self.printOutput('Disconnected polygon selection')
def addTextfield(self, xpos = 0, ypos = 0.95, width = 1, height = 0.03):
def addTextfield(self, xpos=0, ypos=0.95, width=1, height=0.03):
'''
Adds an ax for text output to the plot.
'''
self.axtext = self.ax.figure.add_axes([xpos,
ypos,
width,
height])
ypos,
width,
height])
self.axtext.xaxis.set_visible(False)
self.axtext.yaxis.set_visible(False)
def writeInTextfield(self, text = None):
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')
@ -136,16 +138,16 @@ class regions(object):
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):
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}
'button': None,
'action': action,
'xpos': xpos}
ax = self.ax.figure.add_axes([xpos,
ypos,
0.05,
0.03])
ypos,
0.05,
0.03])
button = Button(ax, name, color=color, hovercolor='grey')
button.on_clicked(action)
self.buttons[name]['ax'] = ax
@ -179,23 +181,24 @@ class regions(object):
self.drawLastPolyLine()
x = self._polyx
y = self._polyy
self._polyx = []; self._polyy = []
self._polyx = [];
self._polyy = []
key = self.getKey()
self.markPolygon(x, y, key = key)
self.markPolygon(x, y, key=key)
shots, numtraces = self.findTracesInPoly(x, y)
self.shots_found[key] = {'shots': shots,
'selection': 'poly',
'xvalues': x,
'yvalues': y}
'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):
def chooseRectangles(self, event=None):
'''
Activates matplotlib widget RectangleSelector.
'''
@ -208,7 +211,7 @@ class regions(object):
self._rectangle = RectangleSelector(self.ax, self._onselect_clicks)
return self._rectangle
def choosePolygon(self, event = None):
def choosePolygon(self, event=None):
'''
Activates matplotlib widget LassoSelector.
'''
@ -221,7 +224,7 @@ class regions(object):
self._lasso = LassoSelector(self.ax, self._onselect_verts)
return self._lasso
def disconnectPoly(self, event = None):
def disconnectPoly(self, event=None):
if not hasattr(self, '_cidPoly'):
self.printOutput('no poly selection found')
return
@ -231,7 +234,7 @@ class regions(object):
self._lasso.disconnect_events()
print 'disconnected poly selection\n'
def disconnectRect(self, event = None):
def disconnectRect(self, event=None):
if not hasattr(self, '_cidRect'):
self.printOutput('no rectangle selection found')
return
@ -240,14 +243,14 @@ class regions(object):
self._rectangle.disconnect_events()
print 'disconnected rectangle selection\n'
def deselectLastSelection(self, event = None):
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):
def deselectSelection(self, key, color='green', alpha=0.1):
if key not in self.shots_found.keys():
self.printOutput('No selection found.')
return
@ -255,17 +258,17 @@ class regions(object):
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)
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)
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 findTracesInPoly(self, x, y, picks='normal', highlight=True):
def dotproduct(v1, v2):
return sum((a * b for a, b in zip(v1, v2)))
@ -279,21 +282,26 @@ class regions(object):
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]
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??
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_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)
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]:
@ -311,17 +319,20 @@ class regions(object):
self.drawFigure()
return shots_found, numtraces
def findTracesInShotDict(self, (x0, x1), (y0, y1), picks = 'normal', highlight = True):
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
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 flag == pickflag: continue ### IMPROVE THAT
if (x0 <= dist <= x1 and y0 <= pick <= y1):
if shotnumber not in shots_found.keys():
shots_found[shotnumber] = []
@ -333,7 +344,7 @@ class regions(object):
self.drawFigure()
return shots_found, numtraces
def highlightPick(self, shot, traceID, annotations = True):
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.
@ -344,9 +355,11 @@ class regions(object):
if shot.getPickFlag(traceID) is 0:
return
self.ax.scatter(shot.getDistance(traceID), shot.getPick(traceID), s = 50, marker = 'o', facecolors = 'none', edgecolors = 'm', alpha = 1)
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.annotate(s='s%s|t%s' % (shot.getShotnumber(), traceID),
xy=(shot.getDistance(traceID), shot.getPick(traceID)), fontsize='xx-small')
def highlightAllActiveRegions(self):
'''
@ -358,7 +371,7 @@ class regions(object):
self.highlightPick(self.shot_dict[shotnumber], traceID)
self.drawFigure()
def plotTracesInActiveRegions(self, event = None, keys = 'all', maxfigures = 20):
def plotTracesInActiveRegions(self, event=None, keys='all', maxfigures=20):
'''
Plots all traces in the active region or for all specified keys.
@ -382,13 +395,14 @@ class regions(object):
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)
print 'Maximum number of figures (%s) reached. %sth figure was not opened.' % (
maxfigures, count)
break
shot.plot_traces(traceID)
else:
self.printOutput('No picks defined in that region(s)')
def setAllActiveRegionsForDeletion(self, event = None):
def setAllActiveRegionsForDeletion(self, event=None):
keys = []
for key in self.shots_found.keys():
keys.append(key)
@ -405,7 +419,7 @@ class regions(object):
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)
self.deselectSelection(key, color='red', alpha=0.2)
self.deselectSelection(key, color='red', alpha=0.2)
@ -415,13 +429,12 @@ class regions(object):
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)
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)
self.shots_found[key]['yvalues'], key=key)
def markRectangle(self, (x0, x1), (y0, y1), key = None, color = 'grey', alpha = 0.1, linewidth = 1):
def markRectangle(self, (x0, x1), (y0, y1), key=None, color='grey', alpha=0.1, linewidth=1):
'''
Mark a rectangular region on the axes.
'''
@ -431,7 +444,7 @@ class regions(object):
self.ax.text(x0 + (x1 - x0) / 2, y0 + (y1 - y0) / 2, str(key))
self.drawFigure()
def markPolygon(self, x, y, key = None, color = 'grey', alpha = 0.1, linewidth = 1):
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)
@ -449,7 +462,7 @@ class regions(object):
def getShotsForDeletion(self):
return self.shots_for_deletion
def deleteAllMarkedPicks(self, event = None):
def deleteAllMarkedPicks(self, event=None):
'''
Deletes all shots set for deletion.
'''
@ -462,11 +475,11 @@ class regions(object):
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)
print "Deleted the pick for traceID %s on shot number %s" % (traceID, shotnumber)
self.clearShotsForDeletion()
self.refreshFigure()
def highlightPicksForShot(self, shot, annotations = False):
def highlightPicksForShot(self, shot, annotations=False):
'''
Highlight all picks for a given shot.
'''
@ -482,19 +495,19 @@ class regions(object):
def setXYlim(self, xlim, ylim):
self._xlim, self._ylim = xlim, ylim
def refreshLog10SNR(self, event = None):
def refreshLog10SNR(self, event=None):
cbv = 'log10SNR'
self.refreshFigure(self, colorByVal=cbv)
def refreshPickerror(self, event = None):
def refreshPickerror(self, event=None):
cbv = 'pickerror'
self.refreshFigure(self, colorByVal=cbv)
def refreshSPE(self, event = None):
def refreshSPE(self, event=None):
cbv = 'spe'
self.refreshFigure(self, colorByVal=cbv)
def refreshFigure(self, event = None, colorByVal = None):
def refreshFigure(self, event=None, colorByVal=None):
if colorByVal == None:
colorByVal = self.cbv
else:
@ -508,7 +521,7 @@ class regions(object):
self.drawFigure()
self.printOutput('Done!')
def drawFigure(self, resetAxes = True):
def drawFigure(self, resetAxes=True):
if resetAxes == True:
self.ax.set_xlim(self._xlim)
self.ax.set_ylim(self._ylim)

142
pylot/core/active/surveyUtils.py
View File

@ -1,6 +1,13 @@
import numpy as np
from __future__ import print_function
def readParameters(parfile, parameter):
"""
:param parfile:
:param parameter:
:return:
"""
from ConfigParser import ConfigParser
parameterConfig = ConfigParser()
parameterConfig.read('parfile')
@ -9,14 +16,29 @@ def readParameters(parfile, parameter):
return value
def setArtificialPick(shot_dict, traceID, pick):
"""
:param shot_dict:
:param traceID:
:param pick:
:return:
"""
for shot in shot_dict.values():
shot.setPick(traceID, pick)
shot.setPickwindow(traceID, shot.getCut())
def fitSNR4dist(shot_dict, shiftdist = 30, shiftSNR = 100):
def fitSNR4dist(shot_dict, shiftdist=30, shiftSNR=100):
"""
:param shot_dict:
:param shiftdist:
:param shiftSNR:
:return:
"""
import numpy as np
import matplotlib.pyplot as plt
dists = []
picks = []
snrs = []
@ -29,54 +51,84 @@ def fitSNR4dist(shot_dict, shiftdist = 30, shiftSNR = 100):
dists.append(shot.getDistance(traceID))
picks.append(shot.getPickIncludeRemoved(traceID))
snrs.append(shot.getSNR(traceID)[0])
snr_sqrt_inv.append(1/np.sqrt(shot.getSNR(traceID)[0]))
snr_sqrt_inv.append(1 / np.sqrt(shot.getSNR(traceID)[0]))
fit = np.polyfit(dists, snr_sqrt_inv, 1)
fit_fn = np.poly1d(fit)
for dist in dists:
snrBestFit.append((1/(fit_fn(dist)**2)))
snrBestFit.append((1 / (fit_fn(dist) ** 2)))
dist += shiftdist
snrthresholds.append((1/(fit_fn(dist)**2)) - shiftSNR * np.exp(-0.05 * dist))
snrthresholds.append((1 / (fit_fn(dist) ** 2)) - shiftSNR * np.exp(-0.05 * dist))
plotFittedSNR(dists, snrthresholds, snrs, snrBestFit)
return fit_fn #### ZU VERBESSERN, sollte fertige funktion wiedergeben
return fit_fn #### ZU VERBESSERN, sollte fertige funktion wiedergeben
def plotFittedSNR(dists, snrthresholds, snrs, snrBestFit):
"""
:param dists:
:param snrthresholds:
:param snrs:
:param snrBestFit:
:return:
"""
import matplotlib.pyplot as plt
plt.interactive(True)
fig = plt.figure()
plt.plot(dists, snrs, 'b.', markersize = 2.0, label = 'SNR values')
plt.plot(dists, snrs, 'b.', markersize=2.0, label='SNR values')
dists.sort()
snrthresholds.sort(reverse = True)
snrBestFit.sort(reverse = True)
plt.plot(dists, snrthresholds, 'r', markersize = 1, label = 'Fitted threshold')
plt.plot(dists, snrBestFit, 'k', markersize = 1, label = 'Best fitted curve')
snrthresholds.sort(reverse=True)
snrBestFit.sort(reverse=True)
plt.plot(dists, snrthresholds, 'r', markersize=1, label='Fitted threshold')
plt.plot(dists, snrBestFit, 'k', markersize=1, label='Best fitted curve')
plt.xlabel('Distance[m]')
plt.ylabel('SNR')
plt.legend()
def setDynamicFittedSNR(shot_dict, shiftdist = 30, shiftSNR = 100, p1 = 0.004, p2 = -0.0007):
def setDynamicFittedSNR(shot_dict, shiftdist=30, shiftSNR=100, p1=0.004, p2=-0.0007):
"""
:param shot_dict:
:type shot_dict: dict
:param shiftdist:
:type shiftdist: int
:param shiftSNR:
:type shiftSNR: int
:param p1:
:type p1: float
:param p2:
:type p2: float
:return:
"""
import numpy as np
minSNR = 2.5
#fit_fn = fitSNR4dist(shot_dict)
# fit_fn = fitSNR4dist(shot_dict)
fit_fn = np.poly1d([p1, p2])
for shot in shot_dict.values():
for traceID in shot.getTraceIDlist(): ### IMPROVE
for traceID in shot.getTraceIDlist(): ### IMPROVE
dist = shot.getDistance(traceID) + shiftdist
snrthreshold = (1/(fit_fn(dist)**2)) - shiftSNR * np.exp(-0.05 * dist)
snrthreshold = (1 / (fit_fn(dist) ** 2)) - shiftSNR * np.exp(-0.05 * dist)
if snrthreshold < minSNR:
print('WARNING: SNR threshold %s lower %s. Set SNR threshold to %s.'
%(snrthreshold, minSNR, minSNR))
% (snrthreshold, minSNR, minSNR))
shot.setSNRthreshold(traceID, minSNR)
else:
shot.setSNRthreshold(traceID, snrthreshold)
print "setDynamicFittedSNR: Finished setting of fitted SNR-threshold"
print("setDynamicFittedSNR: Finished setting of fitted SNR-threshold")
def setConstantSNR(shot_dict, snrthreshold = 2.5):
import numpy as np
def setConstantSNR(shot_dict, snrthreshold=2.5):
"""
:param shot_dict:
:param snrthreshold:
:return:
"""
for shot in shot_dict.values():
for traceID in shot.getTraceIDlist():
shot.setSNRthreshold(traceID, snrthreshold)
print "setConstantSNR: Finished setting of SNR threshold to a constant value of %s"%snrthreshold
print("setConstantSNR: Finished setting of SNR threshold to a constant value of %s" % snrthreshold)
def findTracesInRanges(shot_dict, distancebin, pickbin):
'''
@ -94,8 +146,8 @@ def findTracesInRanges(shot_dict, distancebin, pickbin):
'''
shots_found = {}
for shot in shot_dict.values():
if shot.getTraceIDs4Dist(distancebin = distancebin) is not None:
for traceID in shot.getTraceIDs4Dist(distancebin = distancebin):
if shot.getTraceIDs4Dist(distancebin=distancebin) is not None:
for traceID in shot.getTraceIDs4Dist(distancebin=distancebin):
if pickbin[0] < shot.getPick(traceID) < pickbin[1]:
if shot.getShotnumber() not in shots_found.keys():
shots_found[shot.getShotnumber()] = []
@ -103,11 +155,17 @@ def findTracesInRanges(shot_dict, distancebin, pickbin):
return shots_found
def cleanUp(survey):
def cleanUp(survey):
"""
:param survey:
:return:
"""
for shot in survey.data.values():
shot.traces4plot = {}
# def plotScatterStats(survey, key, ax = None):
# import matplotlib.pyplot as plt
# x = []; y = []; value = []
@ -131,14 +189,19 @@ def cleanUp(survey):
# cbar.set_label(key)
def plotScatterStats4Shots(survey, key):
'''
"""
Statistics, scatter plot.
key can be 'mean SNR', 'median SNR', 'mean SPE', 'median SPE', or 'picked traces'
'''
:param survey:
:param key:
:return:
"""
import matplotlib.pyplot as plt
import numpy as np
statsShot = {}
x = []; y = []; value = []
x = []
y = []
value = []
for shot in survey.data.values():
for traceID in shot.getTraceIDlist():
if not shot in statsShot.keys():
@ -171,7 +234,7 @@ def plotScatterStats4Shots(survey, key):
for val in value:
size.append(100 * val / max(value))
sc = ax.scatter(x, y, s = size, c = value)
sc = ax.scatter(x, y, s=size, c=value)
plt.title('Plot of all shots')
plt.xlabel('X')
plt.ylabel('Y')
@ -179,18 +242,24 @@ def plotScatterStats4Shots(survey, key):
cbar.set_label(key)
for shot in statsShot.keys():
ax.annotate(' %s' %shot.getShotnumber() , xy = (shot.getSrcLoc()[0], shot.getSrcLoc()[1]),
fontsize = 'x-small', color = 'k')
ax.annotate(' %s' % shot.getShotnumber(), xy=(shot.getSrcLoc()[0], shot.getSrcLoc()[1]),
fontsize='x-small', color='k')
def plotScatterStats4Receivers(survey, key):
'''
"""
Statistics, scatter plot.
key can be 'mean SNR', 'median SNR', 'mean SPE', 'median SPE', or 'picked traces'
'''
:param survey:
:param key:
:return:
"""
import matplotlib.pyplot as plt
import numpy as np
statsRec = {}
x = []; y = []; value = []
x = []
y = []
value = []
for shot in survey.data.values():
for traceID in shot.getTraceIDlist():
if not traceID in statsRec.keys():
@ -205,7 +274,6 @@ def plotScatterStats4Receivers(survey, key):
statsRec[traceID]['picked traces'] += 1
statsRec[traceID]['SPE'].append(shot.getSymmetricPickError(traceID))
for traceID in statsRec.keys():
statsRec[traceID]['mean SNR'] = np.mean(statsRec[traceID]['SNR'])
statsRec[traceID]['median SNR'] = np.median(statsRec[traceID]['SNR'])
@ -224,7 +292,7 @@ def plotScatterStats4Receivers(survey, key):
for val in value:
size.append(100 * val / max(value))
sc = ax.scatter(x, y, s = size, c = value)
sc = ax.scatter(x, y, s=size, c=value)
plt.title('Plot of all receivers')
plt.xlabel('X')
plt.ylabel('Y')
@ -233,5 +301,5 @@ def plotScatterStats4Receivers(survey, key):
shot = survey.data.values()[0]
for traceID in shot.getTraceIDlist():
ax.annotate(' %s' %traceID , xy = (shot.getRecLoc(traceID)[0], shot.getRecLoc(traceID)[1]),
fontsize = 'x-small', color = 'k')
ax.annotate(' %s' % traceID, xy=(shot.getRecLoc(traceID)[0], shot.getRecLoc(traceID)[1]),
fontsize='x-small', color='k')

2
pylot/core/analysis/coinctimes.py
View File

@ -5,9 +5,7 @@ from obspy.core import read
from obspy.signal.trigger import coincidenceTrigger
class CoincidenceTimes(object):
def __init__(self, st, comp='Z', coinum=4, sta=1., lta=10., on=5., off=1.):
_type = 'recstalta'
self.coinclist = self.createCoincTriggerlist(data=st, trigcomp=comp,

172
pylot/core/analysis/magnitude.py
View File

@ -15,6 +15,7 @@ from scipy.optimize import curve_fit
from scipy import integrate, signal
from pylot.core.read.data import Data
class Magnitude(object):
'''
Superclass for calculating Wood-Anderson peak-to-peak
@ -72,7 +73,6 @@ class Magnitude(object):
self.calcsourcespec()
self.run_calcMoMw()
def getwfstream(self):
return self.wfstream
@ -154,6 +154,7 @@ class Magnitude(object):
def run_calcMoMw(self):
self.pickdic = None
class WApp(Magnitude):
'''
Method to derive peak-to-peak amplitude as seen on a Wood-Anderson-
@ -222,44 +223,45 @@ class M0Mw(Magnitude):
self.picdic = None
for key in picks:
if picks[key]['P']['weight'] < 4:
# select waveform
selwf = wfdat.select(station=key)
if len(key) > 4:
Ppattern = '%s ? ? ? P' % key
elif len(key) == 4:
Ppattern = '%s ? ? ? P' % key
elif len(key) < 4:
Ppattern = '%s ? ? ? P' % key
nllocline = getPatternLine(nllocfile, Ppattern)
# get hypocentral distance, station azimuth and
# angle of incidence from NLLoc-location file
delta = float(nllocline.split(None)[21])
az = float(nllocline.split(None)[22])
inc = float(nllocline.split(None)[24])
# call subfunction to estimate source spectrum
# and to derive w0 and fc
[w0, fc] = calcsourcespec(selwf, picks[key]['P']['mpp'], \
self.getinvdir(), self.getvp(), delta, az, \
inc, self.getQp(), self.getiplot())
if picks[key]['P']['weight'] < 4:
# select waveform
selwf = wfdat.select(station=key)
if len(key) > 4:
Ppattern = '%s ? ? ? P' % key
elif len(key) == 4:
Ppattern = '%s ? ? ? P' % key
elif len(key) < 4:
Ppattern = '%s ? ? ? P' % key
nllocline = getPatternLine(nllocfile, Ppattern)
# get hypocentral distance, station azimuth and
# angle of incidence from NLLoc-location file
delta = float(nllocline.split(None)[21])
az = float(nllocline.split(None)[22])
inc = float(nllocline.split(None)[24])
# call subfunction to estimate source spectrum
# and to derive w0 and fc
[w0, fc] = calcsourcespec(selwf, picks[key]['P']['mpp'], \
self.getinvdir(), self.getvp(), delta, az, \
inc, self.getQp(), self.getiplot())
if w0 is not None:
# call subfunction to calculate Mo and Mw
zdat = selwf.select(component="Z")
if len(zdat) == 0: # check for other components
zdat = selwf.select(component="3")
[Mo, Mw] = calcMoMw(zdat, w0, self.getrho(), self.getvp(), \
delta, self.getinvdir())
else:
Mo = None
Mw = None
if w0 is not None:
# call subfunction to calculate Mo and Mw
zdat = selwf.select(component="Z")
if len(zdat) == 0: # check for other components
zdat = selwf.select(component="3")
[Mo, Mw] = calcMoMw(zdat, w0, self.getrho(), self.getvp(), \
delta, self.getinvdir())
else:
Mo = None
Mw = None
# add w0, fc, Mo and Mw to dictionary
picks[key]['P']['w0'] = w0
picks[key]['P']['fc'] = fc
picks[key]['P']['Mo'] = Mo
picks[key]['P']['Mw'] = Mw
self.picdic = picks
# add w0, fc, Mo and Mw to dictionary
picks[key]['P']['w0'] = w0
picks[key]['P']['fc'] = fc
picks[key]['P']['Mo'] = Mo
picks[key]['P']['Mw'] = Mw
self.picdic = picks
def calcMoMw(wfstream, w0, rho, vp, delta, inv):
'''
@ -283,26 +285,25 @@ def calcMoMw(wfstream, w0, rho, vp, delta, inv):
'''
tr = wfstream[0]
delta = delta * 1000 # hypocentral distance in [m]
delta = delta * 1000 # hypocentral distance in [m]
print("calcMoMw: Calculating seismic moment Mo and moment magnitude Mw for station %s ..." \
% tr.stats.station)
% tr.stats.station)
# additional common parameters for calculating Mo
rP = 2 / np.sqrt(15) # average radiation pattern of P waves (Aki & Richards, 1980)
freesurf = 2.0 # free surface correction, assuming vertical incidence
rP = 2 / np.sqrt(15) # average radiation pattern of P waves (Aki & Richards, 1980)
freesurf = 2.0 # free surface correction, assuming vertical incidence
Mo = w0 * 4 * np.pi * rho * np.power(vp, 3) * delta / (rP * freesurf)
#Mw = np.log10(Mo * 1e07) * 2 / 3 - 10.7 # after Hanks & Kanamori (1979), defined for [dyn*cm]!
Mw = np.log10(Mo) * 2 / 3 - 6.7 # for metric units
# Mw = np.log10(Mo * 1e07) * 2 / 3 - 10.7 # after Hanks & Kanamori (1979), defined for [dyn*cm]!
Mw = np.log10(Mo) * 2 / 3 - 6.7 # for metric units
print("calcMoMw: Calculated seismic moment Mo = %e Nm => Mw = %3.1f " % (Mo, Mw))
return Mo, Mw
def calcsourcespec(wfstream, onset, inventory, vp, delta, azimuth, incidence, Qp, iplot):
'''
Subfunction to calculate the source spectrum and to derive from that the plateau
@ -346,7 +347,7 @@ def calcsourcespec(wfstream, onset, inventory, vp, delta, azimuth, incidence, Qp
Q = int(qu[0])
# A, i.e. power of frequency
A = float(qu[1])
delta = delta * 1000 # hypocentral distance in [m]
delta = delta * 1000 # hypocentral distance in [m]
fc = None
w0 = None
@ -385,7 +386,7 @@ def calcsourcespec(wfstream, onset, inventory, vp, delta, azimuth, incidence, Qp
# L: P-wave direction
# Q: SV-wave direction
# T: SH-wave direction
LQT=cordat_copy.rotate('ZNE->LQT',azimuth, incidence)
LQT = cordat_copy.rotate('ZNE->LQT', azimuth, incidence)
ldat = LQT.select(component="L")
if len(ldat) == 0:
# if horizontal channels are 2 and 3
@ -398,30 +399,30 @@ def calcsourcespec(wfstream, onset, inventory, vp, delta, azimuth, incidence, Qp
# integrate to displacement
# unrotated vertical component (for copmarison)
inttrz = signal.detrend(integrate.cumtrapz(zdat[0].data, None, \
zdat[0].stats.delta))
zdat[0].stats.delta))
# rotated component Z => L
Ldat = signal.detrend(integrate.cumtrapz(ldat[0].data, None, \
ldat[0].stats.delta))
ldat[0].stats.delta))
# get window after P pulse for
# calculating source spectrum
if zdat[0].stats.sampling_rate <= 100:
winzc = zdat[0].stats.sampling_rate
elif zdat[0].stats.sampling_rate > 100 and \
zdat[0].stats.sampling_rate <= 200:
winzc = 0.5 * zdat[0].stats.sampling_rate
zdat[0].stats.sampling_rate <= 200:
winzc = 0.5 * zdat[0].stats.sampling_rate
elif zdat[0].stats.sampling_rate > 200 and \
zdat[0].stats.sampling_rate <= 400:
winzc = 0.2 * zdat[0].stats.sampling_rate
zdat[0].stats.sampling_rate <= 400:
winzc = 0.2 * zdat[0].stats.sampling_rate
elif zdat[0].stats.sampling_rate > 400:
winzc = zdat[0].stats.sampling_rate
winzc = zdat[0].stats.sampling_rate
tstart = UTCDateTime(zdat[0].stats.starttime)
tonset = onset.timestamp -tstart.timestamp
tonset = onset.timestamp - tstart.timestamp
impickP = tonset * zdat[0].stats.sampling_rate
wfzc = Ldat[impickP : impickP + winzc]
wfzc = Ldat[impickP: impickP + winzc]
# get time array
t = np.arange(0, len(inttrz) * zdat[0].stats.delta, \
zdat[0].stats.delta)
zdat[0].stats.delta)
# calculate spectrum using only first cycles of
# waveform after P onset!
zc = crossings_nonzero_all(wfzc)
@ -446,9 +447,9 @@ def calcsourcespec(wfstream, onset, inventory, vp, delta, azimuth, incidence, Qp
m = pow(2, np.ceil(np.log(len(xdat)) / np.log(2)))
N = int(np.power(m, 2))
y = zdat[0].stats.delta * np.fft.fft(xdat, N)
Y = abs(y[: N/2])
Y = abs(y[: N / 2])
L = (N - 1) / zdat[0].stats.sampling_rate
f = np.arange(0, fny, 1/L)
f = np.arange(0, fny, 1 / L)
# remove zero-frequency and frequencies above
# corner frequency of seismometer (assumed
@ -458,9 +459,9 @@ def calcsourcespec(wfstream, onset, inventory, vp, delta, azimuth, incidence, Qp
YY = Y[fi]
# correction for attenuation
wa = 2 * np.pi * F #angular frequency
D = np.exp((wa * delta) / (2 * vp * Q*F**A))
YYcor = YY.real*D
wa = 2 * np.pi * F # angular frequency
D = np.exp((wa * delta) / (2 * vp * Q * F ** A))
YYcor = YY.real * D
# get plateau (DC value) and corner frequency
# initial guess of plateau
@ -493,8 +494,8 @@ def calcsourcespec(wfstream, onset, inventory, vp, delta, azimuth, incidence, Qp
if iplot > 1:
f1 = plt.figure()
tLdat = np.arange(0, len(Ldat) * zdat[0].stats.delta, \
zdat[0].stats.delta)
plt.subplot(2,1,1)
zdat[0].stats.delta)
plt.subplot(2, 1, 1)
# show displacement in mm
p1, = plt.plot(t, np.multiply(inttrz, 1000), 'k')
p2, = plt.plot(tLdat, np.multiply(Ldat, 1000))
@ -502,26 +503,26 @@ def calcsourcespec(wfstream, onset, inventory, vp, delta, azimuth, incidence, Qp
if plotflag == 1:
plt.plot(t[iwin], np.multiply(xdat, 1000), 'g')
plt.title('Seismogram and P Pulse, Station %s-%s' \
% (zdat[0].stats.station, zdat[0].stats.channel))
% (zdat[0].stats.station, zdat[0].stats.channel))
else:
plt.title('Seismogram, Station %s-%s' \
% (zdat[0].stats.station, zdat[0].stats.channel))
% (zdat[0].stats.station, zdat[0].stats.channel))
plt.xlabel('Time since %s' % zdat[0].stats.starttime)
plt.ylabel('Displacement [mm]')
if plotflag == 1:
plt.subplot(2,1,2)
plt.subplot(2, 1, 2)
p1, = plt.loglog(f, Y.real, 'k')
p2, = plt.loglog(F, YY.real)
p3, = plt.loglog(F, YYcor, 'r')
p4, = plt.loglog(F, fit, 'g')
plt.loglog([fc, fc], [w0/100, w0], 'g')
plt.loglog([fc, fc], [w0 / 100, w0], 'g')
plt.legend([p1, p2, p3, p4], ['Raw Spectrum', \
'Used Raw Spectrum', \
'Q-Corrected Spectrum', \
'Fit to Spectrum'])
plt.title('Source Spectrum from P Pulse, w0=%e m/Hz, fc=%6.2f Hz' \
% (w0, fc))
% (w0, fc))
plt.xlabel('Frequency [Hz]')
plt.ylabel('Amplitude [m/Hz]')
plt.grid()
@ -547,7 +548,7 @@ def synthsourcespec(f, omega0, fcorner):
:type: float
'''
#ssp = omega0 / (pow(2, (1 + f / fcorner)))
# ssp = omega0 / (pow(2, (1 + f / fcorner)))
ssp = omega0 / (1 + pow(2, (f / fcorner)))
return ssp
@ -569,7 +570,7 @@ def fitSourceModel(f, S, fc0, iplot):
:type: float
'''
w0 = []
w0 = []
stdw0 = []
fc = []
stdfc = []
@ -577,17 +578,17 @@ def fitSourceModel(f, S, fc0, iplot):
# get window around initial corner frequency for trials
fcstopl = fc0 - max(1, len(f) / 10)
il = np.argmin(abs(f-fcstopl))
il = np.argmin(abs(f - fcstopl))
fcstopl = f[il]
fcstopr = fc0 + min(len(f), len(f) /10)
ir = np.argmin(abs(f-fcstopr))
fcstopr = fc0 + min(len(f), len(f) / 10)
ir = np.argmin(abs(f - fcstopr))
fcstopr = f[ir]
iF = np.where((f >= fcstopl) & (f <= fcstopr))
# vary corner frequency around initial point
for i in range(il, ir):
FC = f[i]
indexdc = np.where((f > 0 ) & (f <= FC))
indexdc = np.where((f > 0) & (f <= FC))
dc = np.mean(S[indexdc])
stddc = np.std(dc - S[indexdc])
w0.append(dc)
@ -595,7 +596,7 @@ def fitSourceModel(f, S, fc0, iplot):
fc.append(FC)
# slope
indexfc = np.where((f >= FC) & (f <= fcstopr))
yi = dc/(1+(f[indexfc]/FC)**2)
yi = dc / (1 + (f[indexfc] / FC) ** 2)
stdFC = np.std(yi - S[indexfc])
stdfc.append(stdFC)
STD.append(stddc + stdFC)
@ -609,29 +610,29 @@ def fitSourceModel(f, S, fc0, iplot):
w0 = max(S)
print("fitSourceModel: best fc: %fHz, best w0: %e m/Hz" \
% (fc, w0))
% (fc, w0))
if iplot > 1:
plt.figure(iplot)
plt.loglog(f, S, 'k')
plt.loglog([f[0], fc], [w0, w0], 'g')
plt.loglog([fc, fc], [w0/100, w0], 'g')
plt.loglog([fc, fc], [w0 / 100, w0], 'g')
plt.title('Calculated Source Spectrum, Omega0=%e m/Hz, fc=%6.2f Hz' \
% (w0, fc))
% (w0, fc))
plt.xlabel('Frequency [Hz]')
plt.ylabel('Amplitude [m/Hz]')
plt.grid()
plt.figure(iplot+1)
plt.figure(iplot + 1)
plt.subplot(311)
plt.plot(f[il:ir], STD,'*')
plt.plot(f[il:ir], STD, '*')
plt.title('Common Standard Deviations')
plt.xticks([])
plt.subplot(312)
plt.plot(f[il:ir], stdw0,'*')
plt.plot(f[il:ir], stdw0, '*')
plt.title('Standard Deviations of w0-Values')
plt.xticks([])
plt.subplot(313)
plt.plot(f[il:ir],stdfc,'*')
plt.plot(f[il:ir], stdfc, '*')
plt.title('Standard Deviations of Corner Frequencies')
plt.xlabel('Corner Frequencies [Hz]')
plt.show()
@ -639,10 +640,3 @@ def fitSourceModel(f, S, fc0, iplot):
plt.close()
return w0, fc

6
pylot/core/analysis/trigger.py
View File

@ -1,7 +1,7 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from obspy.signal.trigger import recSTALTA, triggerOnset
from obspy.signal.trigger import recursive_sta_lta, trigger_onset
def createSingleTriggerlist(st, station='ZV01', trigcomp='Z', stalta=(1, 10),
@ -24,8 +24,8 @@ def createSingleTriggerlist(st, station='ZV01', trigcomp='Z', stalta=(1, 10),
tr = st.copy().select(component=trigcomp, station=station)[0]
df = tr.stats.sampling_rate
cft = recSTALTA(tr.data, int(stalta[0] * df), int(stalta[1] * df))
triggers = triggerOnset(cft, trigonoff[0], trigonoff[1])
cft = recursive_sta_lta(tr.data, int(stalta[0] * df), int(stalta[1] * df))
triggers = trigger_onset(cft, trigonoff[0], trigonoff[1])
trigg = []
for time in triggers:
trigg.append(tr.stats.starttime + time[0] / df)

9
pylot/core/loc/nll.py
View File

@ -9,6 +9,7 @@ from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString()
def picksExport(picks, locrt, phasefile):
'''
Take <picks> dictionary and exports picking data to a NLLOC-obs
@ -26,6 +27,7 @@ def picksExport(picks, locrt, phasefile):
# write phases to NLLoc-phase file
writephases(picks, locrt, phasefile)
def modifyInputFile(ctrfn, root, nllocoutn, phasefn, tttn):
'''
:param ctrfn: name of NLLoc-control file
@ -46,7 +48,7 @@ def modifyInputFile(ctrfn, root, nllocoutn, phasefn, tttn):
# For locating the event the NLLoc-control file has to be modified!
# create comment line for NLLoc-control file NLLoc-output file
ctrfile = os.path.join(root, 'run', ctrfn)
nllocout = os.path.join(root,'loc', nllocoutn)
nllocout = os.path.join(root, 'loc', nllocoutn)
phasefile = os.path.join(root, 'obs', phasefn)
tttable = os.path.join(root, 'time', tttn)
locfiles = 'LOCFILES %s NLLOC_OBS %s %s 0\n' % (phasefile, tttable, nllocout)
@ -63,6 +65,7 @@ def modifyInputFile(ctrfn, root, nllocoutn, phasefn, tttn):
nllfile.write(filedata)
nllfile.close()
def locate(call, fnin):
'''
Takes paths to NLLoc executable <call> and input parameter file <fnin>
@ -78,8 +81,10 @@ def locate(call, fnin):
# locate the event
subprocess.call([call, fnin])
def readLocation(fn):
pass
if __name__=='__main__':
if __name__ == '__main__':
pass

16
pylot/core/pick/autopick.py
View File

@ -144,7 +144,7 @@ def autopickstation(wfstream, pickparam, verbose=False):
Sflag = 0
Pmarker = []
Ao = None # Wood-Anderson peak-to-peak amplitude
picker = 'autoPyLoT' # name of the picking programm
picker = 'autoPyLoT' # name of the picking programm
# split components
zdat = wfstream.select(component="Z")
@ -867,19 +867,19 @@ def iteratepicker(wf, NLLocfile, picks, badpicks, pickparameter):
pickparameter.setParam(noisefactor=1.0)
pickparameter.setParam(zfac=1.0)
print(
"iteratepicker: The following picking parameters have been modified for iterative picking:")
"iteratepicker: The following picking parameters have been modified for iterative picking:")
print(
"pstart: %fs => %fs" % (pstart_old, pickparameter.getParam('pstart')))
"pstart: %fs => %fs" % (pstart_old, pickparameter.getParam('pstart')))
print(
"pstop: %fs => %fs" % (pstop_old, pickparameter.getParam('pstop')))
"pstop: %fs => %fs" % (pstop_old, pickparameter.getParam('pstop')))
print(
"sstop: %fs => %fs" % (sstop_old, pickparameter.getParam('sstop')))
"sstop: %fs => %fs" % (sstop_old, pickparameter.getParam('sstop')))
print("pickwinP: %fs => %fs" % (
pickwinP_old, pickparameter.getParam('pickwinP')))
pickwinP_old, pickparameter.getParam('pickwinP')))
print("Precalcwin: %fs => %fs" % (
Precalcwin_old, pickparameter.getParam('Precalcwin')))
Precalcwin_old, pickparameter.getParam('Precalcwin')))
print("noisefactor: %f => %f" % (
noisefactor_old, pickparameter.getParam('noisefactor')))
noisefactor_old, pickparameter.getParam('noisefactor')))
print("zfac: %f => %f" % (zfac_old, pickparameter.getParam('zfac')))
# repick station

255
pylot/core/pick/charfuns.py
View File

@ -21,10 +21,12 @@ import matplotlib.pyplot as plt
import numpy as np
from obspy.core import Stream
class CharacteristicFunction(object):
'''
SuperClass for different types of characteristic functions.
'''
def __init__(self, data, cut, t2=None, order=None, t1=None, fnoise=None, stealthMode=False):
'''
Initialize data type object with information from the original
@ -103,9 +105,9 @@ class CharacteristicFunction(object):
def setARdetStep(self, t1):
if t1:
self.ARdetStep = []
self.ARdetStep.append(t1 / 4)
self.ARdetStep.append(int(np.ceil(self.getTime2() / self.getIncrement()) / 4))
self.ARdetStep = []
self.ARdetStep.append(t1 / 4)
self.ARdetStep.append(int(np.ceil(self.getTime2() / self.getIncrement()) / 4))
def getOrder(self):
return self.order
@ -150,14 +152,14 @@ class CharacteristicFunction(object):
if cut is not None:
if len(self.orig_data) == 1:
if self.cut[0] == 0 and self.cut[1] == 0:
start = 0
stop = len(self.orig_data[0])
start = 0
stop = len(self.orig_data[0])
elif self.cut[0] == 0 and self.cut[1] is not 0:
start = 0
stop = self.cut[1] / self.dt
start = 0
stop = self.cut[1] / self.dt
else:
start = self.cut[0] / self.dt
stop = self.cut[1] / self.dt
start = self.cut[0] / self.dt
stop = self.cut[1] / self.dt
zz = self.orig_data.copy()
z1 = zz[0].copy()
zz[0].data = z1.data[int(start):int(stop)]
@ -165,16 +167,16 @@ class CharacteristicFunction(object):
return data
elif len(self.orig_data) == 2:
if self.cut[0] == 0 and self.cut[1] == 0:
start = 0
stop = min([len(self.orig_data[0]), len(self.orig_data[1])])
start = 0
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])])
start = 0
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])])
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])])
hh = self.orig_data.copy()
h1 = hh[0].copy()
h2 = hh[1].copy()
@ -184,16 +186,16 @@ class CharacteristicFunction(object):
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])])
start = 0
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
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])])
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])])
hh = self.orig_data.copy()
h1 = hh[0].copy()
h2 = hh[1].copy()
@ -223,13 +225,13 @@ class AICcf(CharacteristicFunction):
def calcCF(self, data):
#if self._getStealthMode() is False:
# if self._getStealthMode() is False:
# print 'Calculating AIC ...'
x = self.getDataArray()
xnp = x[0].data
nn = np.isnan(xnp)
if len(nn) > 1:
xnp[nn] = 0
xnp[nn] = 0
datlen = len(xnp)
k = np.arange(1, datlen)
cf = np.zeros(datlen)
@ -247,6 +249,7 @@ class AICcf(CharacteristicFunction):
self.cf = cf - np.mean(cf)
self.xcf = x
class HOScf(CharacteristicFunction):
'''
Function to calculate skewness (statistics of order 3) or kurtosis
@ -257,38 +260,38 @@ class HOScf(CharacteristicFunction):
def calcCF(self, data):
x = self.getDataArray(self.getCut())
xnp =x[0].data
xnp = x[0].data
nn = np.isnan(xnp)
if len(nn) > 1:
xnp[nn] = 0
xnp[nn] = 0
if self.getOrder() == 3: # this is skewness
#if self._getStealthMode() is False:
# 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
#if self._getStealthMode() is False:
# if self._getStealthMode() is False:
# print 'Calculating kurtosis ...'
y = np.power(xnp, 4)
y1 = np.power(xnp, 2)
#Initialisation
#t2: long term moving window
# Initialisation
# t2: long term moving window
ilta = int(round(self.getTime2() / self.getIncrement()))
lta = y[0]
lta1 = y1[0]
#moving windows
# moving windows
LTA = np.zeros(len(xnp))
for j in range(0, len(xnp)):
if j < 4:
LTA[j] = 0
elif j <= ilta:
lta = (y[j] + lta * (j-1)) / j
lta1 = (y1[j] + lta1 * (j-1)) / j
lta = (y[j] + lta * (j - 1)) / j
lta1 = (y1[j] + lta1 * (j - 1)) / j
else:
lta = (y[j] - y[j - ilta]) / ilta + lta
lta1 = (y1[j] - y1[j - ilta]) / ilta + lta1
#define LTA
# define LTA
if self.getOrder() == 3:
LTA[j] = lta / np.power(lta1, 1.5)
elif self.getOrder() == 4:
@ -296,13 +299,12 @@ class HOScf(CharacteristicFunction):
nn = np.isnan(LTA)
if len(nn) > 1:
LTA[nn] = 0
LTA[nn] = 0
self.cf = LTA
self.xcf = x
class ARZcf(CharacteristicFunction):
def calcCF(self, data):
print 'Calculating AR-prediction error from single trace ...'
@ -310,33 +312,33 @@ class ARZcf(CharacteristicFunction):
xnp = x[0].data
nn = np.isnan(xnp)
if len(nn) > 1:
xnp[nn] = 0
#some parameters needed
#add noise to time series
xnp[nn] = 0
# some parameters needed
# add noise to time series
xnoise = xnp + np.random.normal(0.0, 1.0, len(xnp)) * self.getFnoise() * max(abs(xnp))
tend = len(xnp)
#Time1: length of AR-determination window [sec]
#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]
# Time1: length of AR-determination window [sec]
# 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(xnp))
loopstep = self.getARdetStep()
arcalci = ldet + self.getOrder() #AR-calculation index
arcalci = ldet + self.getOrder() # AR-calculation index
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]!
self.arDetZ(xnoise, self.getOrder(), i-ldet, i)
# determination of AR coefficients
# to speed up calculation, AR-coefficients are calculated only every i+loopstep[1]!
self.arDetZ(xnoise, self.getOrder(), i - ldet, i)
arcalci = arcalci + loopstep[1]
#AR prediction of waveform using calculated AR coefficients
# AR prediction of waveform using calculated AR coefficients
self.arPredZ(xnp, self.arpara, i + 1, lpred)
#prediction error = CF
cf[i + lpred-1] = np.sqrt(np.sum(np.power(self.xpred[i:i + lpred-1] - xnp[i:i + lpred-1], 2)) / lpred)
# prediction error = CF
cf[i + lpred - 1] = np.sqrt(np.sum(np.power(self.xpred[i:i + lpred - 1] - xnp[i:i + lpred - 1], 2)) / lpred)
nn = np.isnan(cf)
if len(nn) > 1:
cf[nn] = 0
#remove zeros and artefacts
cf[nn] = 0
# remove zeros and artefacts
tap = np.hanning(len(cf))
cf = tap * cf
io = np.where(cf == 0)
@ -366,25 +368,25 @@ class ARZcf(CharacteristicFunction):
Output: AR parameters arpara
'''
#recursive calculation of data vector (right part of eq. 6.5 in Kueperkoch et al. (2012)
# recursive calculation of data vector (right part of eq. 6.5 in Kueperkoch et al. (2012)
rhs = np.zeros(self.getOrder())
for k in range(0, self.getOrder()):
for i in range(rind, ldet+1):
for i in range(rind, ldet + 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)
A = np.zeros((self.getOrder(),self.getOrder()))
# recursive calculation of data array (second sum at left part of eq. 6.5 in Kueperkoch et al. 2012)
A = np.zeros((self.getOrder(), self.getOrder()))
for k in range(1, self.getOrder() + 1):
for j in range(1, k + 1):
for i in range(rind, ldet+1):
for i in range(rind, ldet + 1):
ki = k - 1
ji = j - 1
A[ki,ji] = A[ki,ji] + data[i - j] * data[i - k]
A[ki, ji] = A[ki, ji] + data[i - j] * data[i - k]
A[ji,ki] = A[ki,ji]
A[ji, ki] = A[ki, ji]
#apply Moore-Penrose inverse for SVD yielding the AR-parameters
# apply Moore-Penrose inverse for SVD yielding the AR-parameters
self.arpara = np.dot(np.linalg.pinv(A), rhs)
def arPredZ(self, data, arpara, rind, lpred):
@ -406,10 +408,10 @@ class ARZcf(CharacteristicFunction):
Output: predicted waveform z
'''
#be sure of the summation indeces
# be sure of the summation indeces
if rind < len(arpara):
rind = len(arpara)
if rind > len(data) - lpred :
if rind > len(data) - lpred:
rind = len(data) - lpred
if lpred < 1:
lpred = 1
@ -426,7 +428,6 @@ class ARZcf(CharacteristicFunction):
class ARHcf(CharacteristicFunction):
def calcCF(self, data):
print 'Calculating AR-prediction error from both horizontal traces ...'
@ -434,41 +435,42 @@ class ARHcf(CharacteristicFunction):
xnp = self.getDataArray(self.getCut())
n0 = np.isnan(xnp[0].data)
if len(n0) > 1:
xnp[0].data[n0] = 0
xnp[0].data[n0] = 0
n1 = np.isnan(xnp[1].data)
if len(n1) > 1:
xnp[1].data[n1] = 0
xnp[1].data[n1] = 0
#some parameters needed
#add noise to time series
# 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))
xnnoise = xnp[1].data + np.random.normal(0.0, 1.0, len(xnp[1].data)) * self.getFnoise() * max(abs(xnp[1].data))
Xnoise = np.array( [xenoise.tolist(), xnnoise.tolist()] )
Xnoise = np.array([xenoise.tolist(), xnnoise.tolist()])
tend = len(xnp[0].data)
#Time1: length of AR-determination window [sec]
#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]
# Time1: length of AR-determination window [sec]
# 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
#arcalci = ldet + self.getOrder() - 1 #AR-calculation index
arcalci = lpred + self.getOrder() - 1 # AR-calculation index
# arcalci = ldet + self.getOrder() - 1 #AR-calculation index
for i in range(lpred + self.getOrder() - 1, tend - 2 * lpred + 1):
if i == arcalci:
#determination of AR coefficients
#to speed up calculation, AR-coefficients are calculated only every i+loopstep[1]!
self.arDetH(Xnoise, self.getOrder(), i-ldet, i)
# determination of AR coefficients
# to speed up calculation, AR-coefficients are calculated only every i+loopstep[1]!
self.arDetH(Xnoise, self.getOrder(), i - ldet, i)
arcalci = arcalci + loopstep[1]
#AR prediction of waveform using calculated AR coefficients
# AR prediction of waveform using calculated AR coefficients
self.arPredH(xnp, self.arpara, i + 1, lpred)
#prediction error = CF
# prediction error = CF
cf[i + lpred] = np.sqrt(np.sum(np.power(self.xpred[0][i:i + lpred] - xnp[0][i:i + lpred], 2) \
+ np.power(self.xpred[1][i:i + lpred] - xnp[1][i:i + lpred], 2)) / (2 * lpred))
+ np.power(self.xpred[1][i:i + lpred] - xnp[1][i:i + lpred], 2)) / (
2 * lpred))
nn = np.isnan(cf)
if len(nn) > 1:
cf[nn] = 0
#remove zeros and artefacts
cf[nn] = 0
# remove zeros and artefacts
tap = np.hanning(len(cf))
cf = tap * cf
io = np.where(cf == 0)
@ -500,24 +502,24 @@ class ARHcf(CharacteristicFunction):
Output: AR parameters arpara
'''
#recursive calculation of data vector (right part of eq. 6.5 in Kueperkoch et al. (2012)
# recursive calculation of data vector (right part of eq. 6.5 in Kueperkoch et al. (2012)
rhs = np.zeros(self.getOrder())
for k in range(0, self.getOrder()):
for i in range(rind, ldet):
rhs[k] = rhs[k] + data[0,i] * data[0,i - k] + data[1,i] * data[1,i - k]
rhs[k] = rhs[k] + data[0, i] * data[0, i - k] + data[1, i] * data[1, i - k]
#recursive calculation of data array (second sum at left part of eq. 6.5 in Kueperkoch et al. 2012)
A = np.zeros((4,4))
# recursive calculation of data array (second sum at left part of eq. 6.5 in Kueperkoch et al. 2012)
A = np.zeros((4, 4))
for k in range(1, self.getOrder() + 1):
for j in range(1, k + 1):
for i in range(rind, ldet):
ki = k - 1
ji = j - 1
A[ki,ji] = A[ki,ji] + data[0,i - ji] * data[0,i - ki] + data[1,i - ji] *data[1,i - ki]
A[ki, ji] = A[ki, ji] + data[0, i - ji] * data[0, i - ki] + data[1, i - ji] * data[1, i - ki]
A[ji,ki] = A[ki,ji]
A[ji, ki] = A[ki, ji]
#apply Moore-Penrose inverse for SVD yielding the AR-parameters
# apply Moore-Penrose inverse for SVD yielding the AR-parameters
self.arpara = np.dot(np.linalg.pinv(A), rhs)
def arPredH(self, data, arpara, rind, lpred):
@ -540,7 +542,7 @@ class ARHcf(CharacteristicFunction):
Output: predicted waveform z
:type: structured array
'''
#be sure of the summation indeces
# be sure of the summation indeces
if rind < len(arpara) + 1:
rind = len(arpara) + 1
if rind > len(data[0]) - lpred + 1:
@ -558,11 +560,11 @@ class ARHcf(CharacteristicFunction):
z1[i] = z1[i] + arpara[ji] * z1[i - ji]
z2[i] = z2[i] + arpara[ji] * z2[i - ji]
z = np.array( [z1.tolist(), z2.tolist()] )
z = np.array([z1.tolist(), z2.tolist()])
self.xpred = z
class AR3Ccf(CharacteristicFunction):
class AR3Ccf(CharacteristicFunction):
def calcCF(self, data):
print 'Calculating AR-prediction error from all 3 components ...'
@ -570,46 +572,47 @@ class AR3Ccf(CharacteristicFunction):
xnp = self.getDataArray(self.getCut())
n0 = np.isnan(xnp[0].data)
if len(n0) > 1:
xnp[0].data[n0] = 0
xnp[0].data[n0] = 0
n1 = np.isnan(xnp[1].data)
if len(n1) > 1:
xnp[1].data[n1] = 0
xnp[1].data[n1] = 0
n2 = np.isnan(xnp[2].data)
if len(n2) > 1:
xnp[2].data[n2] = 0
xnp[2].data[n2] = 0
#some parameters needed
#add noise to time series
# 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))
xnnoise = xnp[1].data + np.random.normal(0.0, 1.0, len(xnp[1].data)) * self.getFnoise() * max(abs(xnp[1].data))
xznoise = xnp[2].data + np.random.normal(0.0, 1.0, len(xnp[2].data)) * self.getFnoise() * max(abs(xnp[2].data))
Xnoise = np.array( [xenoise.tolist(), xnnoise.tolist(), xznoise.tolist()] )
Xnoise = np.array([xenoise.tolist(), xnnoise.tolist(), xznoise.tolist()])
tend = len(xnp[0].data)
#Time1: length of AR-determination window [sec]
#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]
# Time1: length of AR-determination window [sec]
# 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
arcalci = ldet + self.getOrder() - 1 # AR-calculation index
for i in range(ldet + self.getOrder() - 1, tend - 2 * lpred + 1):
if i == arcalci:
#determination of AR coefficients
#to speed up calculation, AR-coefficients are calculated only every i+loopstep[1]!
self.arDet3C(Xnoise, self.getOrder(), i-ldet, i)
# determination of AR coefficients
# to speed up calculation, AR-coefficients are calculated only every i+loopstep[1]!
self.arDet3C(Xnoise, self.getOrder(), i - ldet, i)
arcalci = arcalci + loopstep[1]
#AR prediction of waveform using calculated AR coefficients
# AR prediction of waveform using calculated AR coefficients
self.arPred3C(xnp, self.arpara, i + 1, lpred)
#prediction error = CF
# prediction error = CF
cf[i + lpred] = np.sqrt(np.sum(np.power(self.xpred[0][i:i + lpred] - xnp[0][i:i + lpred], 2) \
+ np.power(self.xpred[1][i:i + lpred] - xnp[1][i:i + lpred], 2) \
+ np.power(self.xpred[2][i:i + lpred] - xnp[2][i:i + lpred], 2)) / (3 * lpred))
+ np.power(self.xpred[1][i:i + lpred] - xnp[1][i:i + lpred], 2) \
+ np.power(self.xpred[2][i:i + lpred] - xnp[2][i:i + lpred], 2)) / (
3 * lpred))
nn = np.isnan(cf)
if len(nn) > 1:
cf[nn] = 0
#remove zeros and artefacts
cf[nn] = 0
# remove zeros and artefacts
tap = np.hanning(len(cf))
cf = tap * cf
io = np.where(cf == 0)
@ -641,26 +644,26 @@ class AR3Ccf(CharacteristicFunction):
Output: AR parameters arpara
'''
#recursive calculation of data vector (right part of eq. 6.5 in Kueperkoch et al. (2012)
# recursive calculation of data vector (right part of eq. 6.5 in Kueperkoch et al. (2012)
rhs = np.zeros(self.getOrder())
for k in range(0, self.getOrder()):
for i in range(rind, ldet):
rhs[k] = rhs[k] + data[0,i] * data[0,i - k] + data[1,i] * data[1,i - k] \
+ data[2,i] * data[2,i - k]
rhs[k] = rhs[k] + data[0, i] * data[0, i - k] + data[1, i] * data[1, i - k] \
+ data[2, i] * data[2, i - k]
#recursive calculation of data array (second sum at left part of eq. 6.5 in Kueperkoch et al. 2012)
A = np.zeros((4,4))
# recursive calculation of data array (second sum at left part of eq. 6.5 in Kueperkoch et al. 2012)
A = np.zeros((4, 4))
for k in range(1, self.getOrder() + 1):
for j in range(1, k + 1):
for i in range(rind, ldet):
ki = k - 1
ji = j - 1
A[ki,ji] = A[ki,ji] + data[0,i - ji] * data[0,i - ki] + data[1,i - ji] *data[1,i - ki] \
+ data[2,i - ji] *data[2,i - ki]
A[ki, ji] = A[ki, ji] + data[0, i - ji] * data[0, i - ki] + data[1, i - ji] * data[1, i - ki] \
+ data[2, i - ji] * data[2, i - ki]
A[ji,ki] = A[ki,ji]
A[ji, ki] = A[ki, ji]
#apply Moore-Penrose inverse for SVD yielding the AR-parameters
# apply Moore-Penrose inverse for SVD yielding the AR-parameters
self.arpara = np.dot(np.linalg.pinv(A), rhs)
def arPred3C(self, data, arpara, rind, lpred):
@ -683,7 +686,7 @@ class AR3Ccf(CharacteristicFunction):
Output: predicted waveform z
:type: structured array
'''
#be sure of the summation indeces
# be sure of the summation indeces
if rind < len(arpara) + 1:
rind = len(arpara) + 1
if rind > len(data[0]) - lpred + 1:
@ -703,5 +706,5 @@ class AR3Ccf(CharacteristicFunction):
z2[i] = z2[i] + arpara[ji] * z2[i - ji]
z3[i] = z3[i] + arpara[ji] * z3[i - ji]
z = np.array( [z1.tolist(), z2.tolist(), z3.tolist()] )
z = np.array([z1.tolist(), z2.tolist(), z3.tolist()])
self.xpred = z

59
pylot/core/pick/picker.py
View File

@ -25,6 +25,7 @@ from pylot.core.pick.utils import getnoisewin, getsignalwin
from pylot.core.pick.charfuns import CharacteristicFunction
import warnings
class AutoPicker(object):
'''
Superclass of different, automated picking algorithms applied on a CF determined
@ -87,7 +88,6 @@ class AutoPicker(object):
Tsmooth=self.getTsmooth(),
Pick1=self.getpick1())
def getTSNR(self):
return self.TSNR
@ -152,14 +152,14 @@ class AICPicker(AutoPicker):
self.Pick = None
self.slope = None
self.SNR = None
#find NaN's
# find NaN's
nn = np.isnan(self.cf)
if len(nn) > 1:
self.cf[nn] = 0
#taper AIC-CF to get rid off side maxima
# taper AIC-CF to get rid off side maxima
tap = np.hanning(len(self.cf))
aic = tap * self.cf + max(abs(self.cf))
#smooth AIC-CF
# smooth AIC-CF
ismooth = int(round(self.Tsmooth / self.dt))
aicsmooth = np.zeros(len(aic))
if len(aic) < ismooth:
@ -171,32 +171,32 @@ class AICPicker(AutoPicker):
ii1 = i - ismooth
aicsmooth[i] = aicsmooth[i - 1] + (aic[i] - aic[ii1]) / ismooth
else:
aicsmooth[i] = np.mean(aic[1 : i])
#remove offset
aicsmooth[i] = np.mean(aic[1: i])
# remove offset
offset = abs(min(aic) - min(aicsmooth))
aicsmooth = aicsmooth - offset
#get maximum of 1st derivative of AIC-CF (more stable!) as starting point
# get maximum of 1st derivative of AIC-CF (more stable!) as starting point
diffcf = np.diff(aicsmooth)
#find NaN's
# find NaN's
nn = np.isnan(diffcf)
if len(nn) > 1:
diffcf[nn] = 0
#taper CF to get rid off side maxima
# taper CF to get rid off side maxima
tap = np.hanning(len(diffcf))
diffcf = tap * diffcf * max(abs(aicsmooth))
icfmax = np.argmax(diffcf)
#find minimum in AIC-CF front of maximum
# find minimum in AIC-CF front of maximum
lpickwindow = int(round(self.PickWindow / self.dt))
for i in range(icfmax - 1, max([icfmax - lpickwindow, 2]), -1):
if aicsmooth[i - 1] >= aicsmooth[i]:
self.Pick = self.Tcf[i]
break
#if no minimum could be found:
#search in 1st derivative of AIC-CF
# if no minimum could be found:
# search in 1st derivative of AIC-CF
if self.Pick is None:
for i in range(icfmax -1, max([icfmax -lpickwindow, 2]), -1):
if diffcf[i -1] >= diffcf[i]:
for i in range(icfmax - 1, max([icfmax - lpickwindow, 2]), -1):
if diffcf[i - 1] >= diffcf[i]:
self.Pick = self.Tcf[i]
break
@ -215,7 +215,7 @@ class AICPicker(AutoPicker):
max(abs(aic[inoise] - np.mean(aic[inoise])))
# calculate slope from CF after initial pick
# get slope window
tslope = self.TSNR[3] #slope determination window
tslope = self.TSNR[3] # slope determination window
islope = np.where((self.Tcf <= min([self.Pick + tslope, len(self.Data[0].data)])) \
& (self.Tcf >= self.Pick))
# find maximum within slope determination window
@ -237,7 +237,7 @@ class AICPicker(AutoPicker):
raw_input()
plt.close(p)
return
islope = islope[0][0 :imax]
islope = islope[0][0:imax]
dataslope = self.Data[0].data[islope]
# calculate slope as polynomal fit of order 1
xslope = np.arange(0, len(dataslope), 1)
@ -258,7 +258,7 @@ class AICPicker(AutoPicker):
p1, = plt.plot(self.Tcf, x / max(x), 'k')
p2, = plt.plot(self.Tcf, aicsmooth / max(aicsmooth), 'r')
if self.Pick is not None:
p3, = plt.plot([self.Pick, self.Pick], [-0.1 , 0.5], 'b', linewidth=2)
p3, = plt.plot([self.Pick, self.Pick], [-0.1, 0.5], 'b', linewidth=2)
plt.legend([p1, p2, p3], ['(HOS-/AR-) Data', 'Smoothed AIC-CF', 'AIC-Pick'])
else:
plt.legend([p1, p2], ['(HOS-/AR-) Data', 'Smoothed AIC-CF'])
@ -273,7 +273,8 @@ class AICPicker(AutoPicker):
p13, = plt.plot(self.Tcf[isignal], self.Data[0].data[isignal], 'r')
p14, = plt.plot(self.Tcf[islope], dataslope, 'g--')
p15, = plt.plot(self.Tcf[islope], datafit, 'g', linewidth=2)
plt.legend([p11, p12, p13, p14, p15], ['Data', 'Noise Window', 'Signal Window', 'Slope Window', 'Slope'],
plt.legend([p11, p12, p13, p14, p15],
['Data', 'Noise Window', 'Signal Window', 'Slope Window', 'Slope'],
loc='best')
plt.title('Station %s, SNR=%7.2f, Slope= %12.2f counts/s' % (self.Data[0].stats.station,
self.SNR, self.slope))
@ -303,7 +304,7 @@ class PragPicker(AutoPicker):
self.SNR = None
self.slope = None
pickflag = 0
#smooth CF
# smooth CF
ismooth = int(round(self.Tsmooth / self.dt))
cfsmooth = np.zeros(len(self.cf))
if len(self.cf) < ismooth:
@ -315,28 +316,28 @@ class PragPicker(AutoPicker):
ii1 = i - ismooth
cfsmooth[i] = cfsmooth[i - 1] + (self.cf[i] - self.cf[ii1]) / ismooth
else:
cfsmooth[i] = np.mean(self.cf[1 : i])
cfsmooth[i] = np.mean(self.cf[1: i])
#select picking window
#which is centered around tpick1
# select picking window
# which is centered around tpick1
ipick = np.where((self.Tcf >= self.getpick1() - self.PickWindow / 2) \
& (self.Tcf <= self.getpick1() + self.PickWindow / 2))
cfipick = self.cf[ipick] - np.mean(self.cf[ipick])
Tcfpick = self.Tcf[ipick]
cfsmoothipick = cfsmooth[ipick]- np.mean(self.cf[ipick])
cfsmoothipick = cfsmooth[ipick] - np.mean(self.cf[ipick])
ipick1 = np.argmin(abs(self.Tcf - self.getpick1()))
cfpick1 = 2 * self.cf[ipick1]
#check trend of CF, i.e. differences of CF and adjust aus regarding this trend
#prominent trend: decrease aus
#flat: use given aus
# check trend of CF, i.e. differences of CF and adjust aus regarding this trend
# prominent trend: decrease aus
# flat: use given aus
cfdiff = np.diff(cfipick)
i0diff = np.where(cfdiff > 0)
cfdiff = cfdiff[i0diff]
minaus = min(cfdiff * (1 + self.aus))
aus1 = max([minaus, self.aus])
#at first we look to the right until the end of the pick window is reached
# at first we look to the right until the end of the pick window is reached
flagpick_r = 0
flagpick_l = 0
cfpick_r = 0
@ -380,8 +381,8 @@ class PragPicker(AutoPicker):
if self.getiplot() > 1:
p = plt.figure(self.getiplot())
p1, = plt.plot(Tcfpick,cfipick, 'k')
p2, = plt.plot(Tcfpick,cfsmoothipick, 'r')
p1, = plt.plot(Tcfpick, cfipick, 'k')
p2, = plt.plot(Tcfpick, cfsmoothipick, 'r')
if pickflag > 0:
p3, = plt.plot([self.Pick, self.Pick], [min(cfipick), max(cfipick)], 'b', linewidth=2)
plt.legend([p1, p2, p3], ['CF', 'Smoothed CF', 'Pick'])

228
pylot/core/pick/utils.py
View File

@ -15,7 +15,7 @@ from obspy.core import Stream, UTCDateTime
import warnings
def earllatepicker(X, nfac, TSNR, Pick1, iplot=None, stealthMode = False):
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,
@ -70,7 +70,8 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None, stealthMode = False):
# get earliest possible pick
EPick = np.nan; count = 0
EPick = np.nan;
count = 0
pis = isignal
# if EPick stays NaN the signal window size will be doubled
@ -78,10 +79,10 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None, stealthMode = False):
if count > 0:
if stealthMode is False:
print("\nearllatepicker: Doubled signal window size %s time(s) "
"because of NaN for earliest pick." %count)
"because of NaN for earliest pick." % count)
isigDoubleWinStart = pis[-1] + 1
isignalDoubleWin = np.arange(isigDoubleWinStart,
isigDoubleWinStart + len(pis))
isigDoubleWinStart + len(pis))
if (isigDoubleWinStart + len(pis)) < X[0].data.size:
pis = np.concatenate((pis, isignalDoubleWin))
else:
@ -92,8 +93,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None, stealthMode = False):
zc = crossings_nonzero_all(x[pis] - x[pis].mean())
# calculate mean half period T0 of signal as the average of the
T0 = np.mean(np.diff(zc)) * X[0].stats.delta # this is half wave length!
EPick = Pick1 - T0 # half wavelength as suggested by Diehl et al.
EPick = Pick1 - T0 # half wavelength as suggested by Diehl et al.
# get symmetric pick error as mean from earliest and latest possible pick
# by weighting latest possible pick two times earliest possible pick
@ -395,7 +395,7 @@ def getnoisewin(t, t1, tnoise, tgap):
# get noise window
inoise, = np.where((t <= max([t1 - tgap, 0])) \
& (t >= max([t1 - tnoise - tgap, 0])))
& (t >= max([t1 - tnoise - tgap, 0])))
if np.size(inoise) < 1:
print ("getnoisewin: Empty array inoise, check noise window!")
@ -419,7 +419,7 @@ def getsignalwin(t, t1, tsignal):
# get signal window
isignal, = np.where((t <= min([t1 + tsignal, len(t)])) \
& (t >= t1))
& (t >= t1))
if np.size(isignal) < 1:
print ("getsignalwin: Empty array isignal, check signal window!")
@ -460,7 +460,7 @@ def getResolutionWindow(snr):
else:
time_resolution = res_wins['HRW']
return time_resolution/2
return time_resolution / 2
def wadaticheck(pickdic, dttolerance, iplot):
@ -488,17 +488,16 @@ def wadaticheck(pickdic, dttolerance, iplot):
SPtimes = []
for key in pickdic:
if pickdic[key]['P']['weight'] < 4 and pickdic[key]['S']['weight'] < 4:
# calculate S-P time
spt = pickdic[key]['S']['mpp'] - pickdic[key]['P']['mpp']
# add S-P time to dictionary
pickdic[key]['SPt'] = spt
# add P onsets and corresponding S-P times to list
UTCPpick = UTCDateTime(pickdic[key]['P']['mpp'])
UTCSpick = UTCDateTime(pickdic[key]['S']['mpp'])
Ppicks.append(UTCPpick.timestamp)
Spicks.append(UTCSpick.timestamp)
SPtimes.append(spt)
# calculate S-P time
spt = pickdic[key]['S']['mpp'] - pickdic[key]['P']['mpp']
# add S-P time to dictionary
pickdic[key]['SPt'] = spt
# add P onsets and corresponding S-P times to list
UTCPpick = UTCDateTime(pickdic[key]['P']['mpp'])
UTCSpick = UTCDateTime(pickdic[key]['S']['mpp'])
Ppicks.append(UTCPpick.timestamp)
Spicks.append(UTCSpick.timestamp)
SPtimes.append(spt)
if len(SPtimes) >= 3:
# calculate slope
@ -530,7 +529,7 @@ def wadaticheck(pickdic, dttolerance, iplot):
ibad += 1
else:
marker = 'goodWadatiCheck'
checkedPpick = UTCDateTime(pickdic[key]['P']['mpp'])
checkedPpick = UTCDateTime(pickdic[key]['P']['mpp'])
checkedPpicks.append(checkedPpick.timestamp)
checkedSpick = UTCDateTime(pickdic[key]['S']['mpp'])
checkedSpicks.append(checkedSpick.timestamp)
@ -642,7 +641,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
# calculate minimum adjusted signal level
minsiglevel = max(rms[inoise]) * nfac
# minimum adjusted number of samples over minimum signal level
minnum = len(isignal) * minpercent/100
minnum = len(isignal) * minpercent / 100
# get number of samples above minimum adjusted signal level
numoverthr = len(np.where(rms[isignal] >= minsiglevel)[0])
@ -657,10 +656,10 @@ 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]]],
p3, = plt.plot(t[isignal], rms[isignal], 'r')
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',
@ -701,15 +700,15 @@ def checkPonsets(pickdic, dttolerance, iplot):
stations = []
for key in pickdic:
if pickdic[key]['P']['weight'] < 4:
# add P onsets to list
UTCPpick = UTCDateTime(pickdic[key]['P']['mpp'])
Ppicks.append(UTCPpick.timestamp)
stations.append(key)
# add P onsets to list
UTCPpick = UTCDateTime(pickdic[key]['P']['mpp'])
Ppicks.append(UTCPpick.timestamp)
stations.append(key)
# apply jackknife bootstrapping on variance of P onsets
print ("###############################################")
print ("checkPonsets: Apply jackknife bootstrapping on P-onset times ...")
[xjack,PHI_pseudo,PHI_sub] = jackknife(Ppicks, 'VAR', 1)
[xjack, PHI_pseudo, PHI_sub] = jackknife(Ppicks, 'VAR', 1)
# get pseudo variances smaller than average variances
# (times safety factor), these picks passed jackknife test
ij = np.where(PHI_pseudo <= 2 * xjack)
@ -730,7 +729,7 @@ def checkPonsets(pickdic, dttolerance, iplot):
print ("checkPonsets: %d pick(s) deviate too much from median!" % len(ibad))
print ("checkPonsets: Skipped %d P pick(s) out of %d" % (len(badstations) \
+ len(badjkstations), len(stations)))
+ len(badjkstations), len(stations)))
goodmarker = 'goodPonsetcheck'
badmarker = 'badPonsetcheck'
@ -881,10 +880,9 @@ def checkZ4S(X, pick, zfac, checkwin, iplot):
if len(ndat) == 0: # check for other components
ndat = X.select(component="1")
z = zdat[0].data
tz = np.arange(0, zdat[0].stats.npts / zdat[0].stats.sampling_rate,
zdat[0].stats.delta)
zdat[0].stats.delta)
# calculate RMS trace from vertical component
absz = np.sqrt(np.power(z, 2))
@ -916,9 +914,9 @@ def checkZ4S(X, pick, zfac, checkwin, iplot):
if iplot > 1:
te = np.arange(0, edat[0].stats.npts / edat[0].stats.sampling_rate,
edat[0].stats.delta)
edat[0].stats.delta)
tn = np.arange(0, ndat[0].stats.npts / ndat[0].stats.sampling_rate,
ndat[0].stats.delta)
ndat[0].stats.delta)
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')
@ -960,65 +958,64 @@ def writephases(arrivals, fformat, filename):
:type: string
'''
if fformat == 'NLLoc':
print ("Writing phases to %s for NLLoc" % filename)
fid = open("%s" % filename, 'w')
# write header
fid.write('# EQEVENT: Label: EQ001 Loc: X 0.00 Y 0.00 Z 10.00 OT 0.00 \n')
for key in arrivals:
# P onsets
if arrivals[key]['P']:
fm = arrivals[key]['P']['fm']
if fm == None:
fm = '?'
onset = arrivals[key]['P']['mpp']
year = onset.year
month = onset.month
day = onset.day
hh = onset.hour
mm = onset.minute
ss = onset.second
ms = onset.microsecond
ss_ms = ss + ms / 1000000.0
if arrivals[key]['P']['weight'] < 4:
pweight = 1 # use pick
else:
pweight = 0 # do not use pick
fid.write('%s ? ? ? P %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 %d \n' % (key,
fm,
year,
month,
day,
hh,
mm,
ss_ms,
pweight))
# S onsets
if arrivals[key]['S']:
fm = '?'
onset = arrivals[key]['S']['mpp']
year = onset.year
month = onset.month
day = onset.day
hh = onset.hour
mm = onset.minute
ss = onset.second
ms = onset.microsecond
ss_ms = ss + ms / 1000000.0
if arrivals[key]['S']['weight'] < 4:
sweight = 1 # use pick
else:
sweight = 0 # do not use pick
fid.write('%s ? ? ? S %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 %d \n' % (key,
fm,
year,
month,
day,
hh,
mm,
ss_ms,
sweight))
# P onsets
if arrivals[key]['P']:
fm = arrivals[key]['P']['fm']
if fm == None:
fm = '?'
onset = arrivals[key]['P']['mpp']
year = onset.year
month = onset.month
day = onset.day
hh = onset.hour
mm = onset.minute
ss = onset.second
ms = onset.microsecond
ss_ms = ss + ms / 1000000.0
if arrivals[key]['P']['weight'] < 4:
pweight = 1 # use pick
else:
pweight = 0 # do not use pick
fid.write('%s ? ? ? P %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 %d \n' % (key,
fm,
year,
month,
day,
hh,
mm,
ss_ms,
pweight))
# S onsets
if arrivals[key]['S']:
fm = '?'
onset = arrivals[key]['S']['mpp']
year = onset.year
month = onset.month
day = onset.day
hh = onset.hour
mm = onset.minute
ss = onset.second
ms = onset.microsecond
ss_ms = ss + ms / 1000000.0
if arrivals[key]['S']['weight'] < 4:
sweight = 1 # use pick
else:
sweight = 0 # do not use pick
fid.write('%s ? ? ? S %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 %d \n' % (key,
fm,
year,
month,
day,
hh,
mm,
ss_ms,
sweight))
fid.close()
@ -1043,9 +1040,9 @@ def writephases(arrivals, fformat, filename):
Ao = str('%7.2f' % Ao)
year = Ponset.year
if year >= 2000:
year = year -2000
year = year - 2000
else:
year = year - 1900
year = year - 1900
month = Ponset.month
day = Ponset.day
hh = Ponset.hour
@ -1054,9 +1051,9 @@ def writephases(arrivals, fformat, filename):
ms = Ponset.microsecond
ss_ms = ss + ms / 1000000.0
if pweight < 2:
pstr = 'I'
pstr = 'I'
elif pweight >= 2:
pstr = 'E'
pstr = 'E'
if arrivals[key]['S']['weight'] < 4:
Sss = Sonset.second
Sms = Sonset.microsecond
@ -1067,35 +1064,36 @@ def writephases(arrivals, fformat, filename):
elif sweight >= 2:
sstr = 'E'
fid.write('%s%sP%s%d %02d%02d%02d%02d%02d%5.2f %s%sS %d %s\n' % (key,
pstr,
fm,
pweight,
year,
month,
day,
hh,
mm,
ss_ms,
Sss_ms,
sstr,
sweight,
Ao))
pstr,
fm,
pweight,
year,
month,
day,
hh,
mm,
ss_ms,
Sss_ms,
sstr,
sweight,
Ao))
else:
fid.write('%s%sP%s%d %02d%02d%02d%02d%02d%5.2f %s\n' % (key,
pstr,
fm,
pweight,
year,
month,
day,
hh,
mm,
ss_ms,
Ao))
pstr,
fm,
pweight,
year,
month,
day,
hh,
mm,
ss_ms,
Ao))
fid.close()
if __name__ == '__main__':
import doctest
doctest.testmod()

1
pylot/core/read/data.py
View File

@ -81,7 +81,6 @@ class Data(object):
picks_str += str(pick) + '\n'
return picks_str
def getParent(self):
"""

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

@ -3,6 +3,7 @@
from pylot.core.util.errors import ParameterError
class AutoPickParameter(object):
'''
AutoPickParameters is a parameter type object capable to read and/or write
@ -50,7 +51,7 @@ class AutoPickParameter(object):
parFileCont[key] = val
if self.__filename is not None:
inputFile = open(self.__filename, 'r')
inputFile = open(self.__filename, 'r')
else:
return
try:
@ -148,7 +149,7 @@ class AutoPickParameter(object):
def setParam(self, **kwargs):
for param, value in kwargs.items():
self.__setitem__(param, value)
#print(self)
# print(self)
@staticmethod
def _printParameterError(errmsg):
@ -193,6 +194,7 @@ class FilterOptions(object):
``'highpass'``
Butterworth-Highpass
'''
def __init__(self, filtertype='bandpass', freq=[2., 5.], order=3,
**kwargs):
self._order = order

5
pylot/core/read/io.py
View File

@ -7,9 +7,10 @@ import scipy.io as sio
import obspy.core.event as ope
from obspy.core import UTCDateTime
from pylot.core.util.utils import getOwner, createPick, createArrival,\
from pylot.core.util.utils import getOwner, createPick, createArrival, \
createEvent, createOrigin, createMagnitude
def readPILOTEvent(phasfn=None, locfn=None, authority_id=None, **kwargs):
"""
readPILOTEvent - function
@ -133,5 +134,3 @@ def readPILOTEvent(phasfn=None, locfn=None, authority_id=None, **kwargs):
except AttributeError as e:
raise AttributeError('{0} - Matlab LOC files {1} and {2} contains \
insufficient data!'.format(e, phasfn, locfn))

7
pylot/core/scripts/pylot-pick-earliest-latest.py
View File

@ -14,11 +14,12 @@ import argparse
import obspy
from pylot.core.pick.utils import earllatepicker
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--X', type=~obspy.core.stream.Stream, help='time series (seismogram) read with obspy module read')
parser.add_argument('--nfac', type=int, help='(noise factor), nfac times noise level to calculate latest possible pick')
parser.add_argument('--X', type=~obspy.core.stream.Stream,
help='time series (seismogram) read with obspy module read')
parser.add_argument('--nfac', type=int,
help='(noise factor), nfac times noise level to calculate latest possible pick')
parser.add_argument('--TSNR', type=tuple, help='length of time windows around pick used to determine SNR \
[s] (Tnoise, Tgap, Tsignal)')
parser.add_argument('--Pick1', type=float, help='Onset time of most likely pick')

7
pylot/core/scripts/pylot-pick-firstmotion.py
View File

@ -13,11 +13,12 @@ from pylot.core.pick.utils import fmpicker
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--Xraw', type=obspy.core.stream.Stream, help='unfiltered time series (seismogram) read with obspy module read')
parser.add_argument('--Xfilt', type=obspy.core.stream.Stream, help='filtered time series (seismogram) read with obspy module read')
parser.add_argument('--Xraw', type=obspy.core.stream.Stream,
help='unfiltered time series (seismogram) read with obspy module read')
parser.add_argument('--Xfilt', type=obspy.core.stream.Stream,
help='filtered time series (seismogram) read with obspy module read')
parser.add_argument('--pickwin', type=float, help='length of pick window [s] for first motion determination')
parser.add_argument('--Pick', type=float, help='Onset time of most likely pick')
parser.add_argument('--iplot', type=int, help='if set, figure no. iplot occurs')
args = parser.parse_args()
fmpicker(args.Xraw, args.Xfilt, args.pickwin, args.Pick, args.iplot)

0
pylot/core/pick/run_makeCF.py → pylot/core/scripts/run_makeCF.py
View File

26
pylot/core/util/defaults.py
View File

@ -11,6 +11,7 @@ from pylot.core.loc import nll
from pylot.core.loc import hsat
from pylot.core.loc import velest
def readFilterInformation(fname):
def convert2FreqRange(*args):
if len(args) > 1:
@ -18,6 +19,7 @@ def readFilterInformation(fname):
elif len(args) == 1:
return float(args[0])
return None
filter_file = open(fname, 'r')
filter_information = dict()
for filter_line in filter_file.readlines():
@ -26,14 +28,14 @@ def readFilterInformation(fname):
if pos == '\n':
filter_line[n] = ''
filter_information[filter_line[0]] = {'filtertype': filter_line[1]
if filter_line[1]
else None,
if filter_line[1]
else None,
'order': int(filter_line[2])
if filter_line[1]
else None,
if filter_line[1]
else None,
'freq': convert2FreqRange(*filter_line[3:])
if filter_line[1]
else None}
if filter_line[1]
else None}
return filter_information
@ -41,15 +43,15 @@ FILTERDEFAULTS = readFilterInformation(os.path.join(os.path.expanduser('~'),
'.pylot',
'filter.in'))
OUTPUTFORMATS = {'.xml':'QUAKEML',
'.cnv':'CNV',
'.obs':'NLLOC_OBS'}
OUTPUTFORMATS = {'.xml': 'QUAKEML',
'.cnv': 'CNV',
'.obs': 'NLLOC_OBS'}
LOCTOOLS = dict(nll = nll, hsat = hsat, velest = velest)
LOCTOOLS = dict(nll=nll, hsat=hsat, velest=velest)
COMPPOSITION_MAP = dict(Z = 2, N = 1, E = 0)
COMPPOSITION_MAP = dict(Z=2, N=1, E=0)
COMPPOSITION_MAP['1'] = 1
COMPPOSITION_MAP['2'] = 0
COMPPOSITION_MAP['3'] = 2
COMPNAME_MAP = dict(Z = '3', N = '1', E = '2')
COMPNAME_MAP = dict(Z='3', N='1', E='2')

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

@ -21,5 +21,6 @@ class DatastructureError(Exception):
class OverwriteError(IOError):
pass
class ParameterError(Exception):
pass

2
pylot/core/util/thread.py
View File

@ -2,6 +2,7 @@
import sys
from PySide.QtCore import QThread, Signal
class AutoPickThread(QThread):
message = Signal(str)
finished = Signal()
@ -28,6 +29,5 @@ class AutoPickThread(QThread):
sys.stdout = sys.__stdout__
self.finished.emit()
def write(self, text):
self.message.emit(text)

27
pylot/core/util/utils.py
View File

@ -10,6 +10,7 @@ import numpy as np
from obspy.core import UTCDateTime
import obspy.core.event as ope
def createAmplitude(pickID, amp, unit, category, cinfo):
'''
@ -28,6 +29,7 @@ def createAmplitude(pickID, amp, unit, category, cinfo):
amplitude.pick_id = pickID
return amplitude
def createArrival(pickresID, cinfo, phase, azimuth=None, dist=None):
'''
createArrival - function to create an Obspy Arrival
@ -56,6 +58,7 @@ def createArrival(pickresID, cinfo, phase, azimuth=None, dist=None):
arrival.distance = dist
return arrival
def createCreationInfo(agency_id=None, creation_time=None, author=None):
'''
@ -71,6 +74,7 @@ def createCreationInfo(agency_id=None, creation_time=None, author=None):
return ope.CreationInfo(agency_id=agency_id, author=author,
creation_time=creation_time)
def createEvent(origintime, cinfo, originloc=None, etype=None, resID=None,
authority_id=None):
'''
@ -115,6 +119,7 @@ def createEvent(origintime, cinfo, originloc=None, etype=None, resID=None,
event.origins = [o]
return event
def createMagnitude(originID, cinfo):
'''
createMagnitude - function to create an ObsPy Magnitude object
@ -129,6 +134,7 @@ def createMagnitude(originID, cinfo):
magnitude.origin_id = originID
return magnitude
def createOrigin(origintime, cinfo, latitude, longitude, depth):
'''
createOrigin - function to create an ObsPy Origin
@ -158,6 +164,7 @@ def createOrigin(origintime, cinfo, latitude, longitude, depth):
origin.depth = depth
return origin
def createPick(origintime, picknum, picktime, eventnum, cinfo, phase, station,
wfseedstr, authority_id):
'''
@ -196,6 +203,7 @@ def createPick(origintime, picknum, picktime, eventnum, cinfo, phase, station,
pick.waveform_id = ope.ResourceIdentifier(id=wfseedstr, prefix='file:/')
return pick
def createResourceID(timetohash, restype, authority_id=None, hrstr=None):
'''
@ -220,6 +228,7 @@ def createResourceID(timetohash, restype, authority_id=None, hrstr=None):
resID.convertIDToQuakeMLURI(authority_id=authority_id)
return resID
def demeanTrace(trace, window):
"""
returns the DATA where each trace is demean by the average value within
@ -234,6 +243,7 @@ def demeanTrace(trace, window):
trace.data -= trace.data[window].mean()
return trace
def findComboBoxIndex(combo_box, val):
"""
Function findComboBoxIndex takes a QComboBox object and a string and
@ -246,6 +256,7 @@ def findComboBoxIndex(combo_box, val):
"""
return combo_box.findText(val) if combo_box.findText(val) is not -1 else 0
def find_nearest(array, value):
'''
Function find_nearest takes an array and a value and returns the
@ -254,7 +265,8 @@ def find_nearest(array, value):
:param value:
:return:
'''
return (np.abs(array-value)).argmin()
return (np.abs(array - value)).argmin()
def fnConstructor(s):
'''
@ -277,6 +289,7 @@ def fnConstructor(s):
fn = '_' + fn
return fn
def getGlobalTimes(stream):
'''
@ -293,6 +306,7 @@ def getGlobalTimes(stream):
max_end = trace.stats.endtime
return min_start, max_end
def getHash(time):
'''
:param time: time object for which a hash should be calculated
@ -303,6 +317,7 @@ def getHash(time):
hg.update(time.strftime('%Y-%m-%d %H:%M:%S.%f'))
return hg.hexdigest()
def getLogin():
'''
@ -310,6 +325,7 @@ def getLogin():
'''
return pwd.getpwuid(os.getuid())[0]
def getOwner(fn):
'''
@ -319,6 +335,7 @@ def getOwner(fn):
'''
return pwd.getpwuid(os.stat(fn).st_uid).pw_name
def getPatternLine(fn, pattern):
"""
Takes a file name and a pattern string to search for in the file and
@ -343,6 +360,7 @@ def getPatternLine(fn, pattern):
return None
def isSorted(iterable):
'''
@ -352,6 +370,7 @@ def isSorted(iterable):
'''
return sorted(iterable) == iterable
def prepTimeAxis(stime, trace):
'''
@ -378,6 +397,7 @@ def prepTimeAxis(stime, trace):
'delta: {2}'.format(nsamp, len(time_ax), tincr))
return time_ax
def scaleWFData(data, factor=None, components='all'):
"""
produce scaled waveforms from given waveform data and a scaling factor,
@ -409,6 +429,7 @@ def scaleWFData(data, factor=None, components='all'):
return data
def runProgram(cmd, parameter=None):
"""
run an external program specified by cmd with parameters input returning the
@ -427,8 +448,10 @@ def runProgram(cmd, parameter=None):
cmd += ' %s 2>&1' % parameter
output = subprocess.check_output('{} | tee /dev/stderr'.format(cmd),
shell = True)
shell=True)
if __name__ == "__main__":
import doctest
doctest.testmod()

7
pylot/core/util/version.py
View File

@ -31,16 +31,19 @@
#
# include RELEASE-VERSION
from __future__ import print_function
__all__ = "get_git_version"
# NO IMPORTS FROM PYLOT IN THIS FILE! (file gets used at installation time)
import os
import inspect
from subprocess import Popen, PIPE
# NO IMPORTS FROM PYLOT IN THIS FILE! (file gets used at installation time)
script_dir = os.path.abspath(os.path.dirname(inspect.getfile(
inspect.currentframe())))
inspect.currentframe())))
PYLOT_ROOT = os.path.abspath(os.path.join(script_dir, os.pardir,
os.pardir, os.pardir))
VERSION_FILE = os.path.join(PYLOT_ROOT, "pylot", "RELEASE-VERSION")
@ -108,4 +111,4 @@ def get_git_version(abbrev=4):
if __name__ == "__main__":
print get_git_version()
print(get_git_version())

23
pylot/core/util/widgets.py
View File

@ -9,6 +9,7 @@ import datetime
import numpy as np
from matplotlib.figure import Figure
try:
from matplotlib.backends.backend_qt4agg import FigureCanvas
except ImportError:
@ -23,9 +24,9 @@ from PySide.QtCore import QSettings, Qt, QUrl, Signal, Slot
from PySide.QtWebKit import QWebView
from obspy import Stream, UTCDateTime
from pylot.core.read.inputs import FilterOptions
from pylot.core.pick.utils import getSNR, earllatepicker, getnoisewin,\
from pylot.core.pick.utils import getSNR, earllatepicker, getnoisewin, \
getResolutionWindow
from pylot.core.util.defaults import OUTPUTFORMATS, FILTERDEFAULTS, LOCTOOLS,\
from pylot.core.util.defaults import OUTPUTFORMATS, FILTERDEFAULTS, LOCTOOLS, \
COMPPOSITION_MAP
from pylot.core.util.utils import prepTimeAxis, getGlobalTimes, scaleWFData, \
demeanTrace, isSorted, findComboBoxIndex
@ -164,9 +165,10 @@ class MPLWidget(FigureCanvas):
def insertLabel(self, pos, text):
pos = pos / max(self.getAxes().ylim)
axann = self.getAxes().annotate(text, xy=(.03, pos),
xycoords='axes fraction')
xycoords='axes fraction')
axann.set_bbox(dict(facecolor='lightgrey', alpha=.6))
class PickDlg(QDialog):
def __init__(self, parent=None, data=None, station=None, picks=None,
rotate=False):
@ -263,8 +265,8 @@ class PickDlg(QDialog):
tip='Zoom into waveform',
checkable=True)
self.resetZoomAction = createAction(parent=self, text='Home',
slot=self.resetZoom, icon=home_icon,
tip='Reset zoom to original limits')
slot=self.resetZoom, icon=home_icon,
tip='Reset zoom to original limits')
self.resetPicksAction = createAction(parent=self, text='Delete Picks',
slot=self.delPicks, icon=del_icon,
tip='Delete current picks.')
@ -516,7 +518,6 @@ class PickDlg(QDialog):
inoise = getnoisewin(t, ini_pick, noise_win, gap_win)
trace = demeanTrace(trace=trace, window=inoise)
self.setXLims([ini_pick - x_res, ini_pick + x_res])
self.setYLims(np.array([-noiselevel * 2.5, noiselevel * 2.5]) +
trace_number)
@ -575,8 +576,8 @@ class PickDlg(QDialog):
traces = self.getTraceID(horiz_comp)
traces.sort()
self.setYLims(tuple(np.array([-0.5, +0.5]) +
np.array(traces)))
noiselevels = [trace + 1 / (2.5 * 2) for trace in traces] +\
np.array(traces)))
noiselevels = [trace + 1 / (2.5 * 2) for trace in traces] + \
[trace - 1 / (2.5 * 2) for trace in traces]
self.getPlotWidget().plotWFData(wfdata=data,
@ -757,7 +758,6 @@ class PickDlg(QDialog):
self.drawPicks()
self.draw()
def setPlotLabels(self):
# get channel labels
@ -1041,7 +1041,7 @@ class LocalisationTab(PropTab):
self.binlabel.setText("{0} bin directory".format(curtool))
def selectDirectory(self, edit):
selected_directory = QFileDialog.getExistingDirectory()
selected_directory = QFileDialog.getExistingDirectory()
edit.setText(selected_directory)
def getValues(self):
@ -1052,7 +1052,6 @@ class LocalisationTab(PropTab):
return values
class NewEventDlg(QDialog):
def __init__(self, parent=None, titleString="Create a new event"):
"""
@ -1293,6 +1292,8 @@ class HelpForm(QDialog):
def updatePageTitle(self):
self.pageLabel.setText(self.webBrowser.documentTitle())
if __name__ == '__main__':
import doctest
doctest.testmod()