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Merge branch 'develop' of ariadne.geophysik.ruhr-uni-bochum.de:/data/git/pylot into develop

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This commit is contained in:
Sebastian Wehling-Benatelli
2015-11-23 11:41:14 +01:00
parent 851da7eb15 56a89ae386
commit 1f1d0aa118
6 changed files with 161 additions and 26 deletions
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2
pylot/core/active/fmtomoUtils.py
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@@ -341,7 +341,7 @@ def addCheckerboard(spacing = 10., pertubation = 0.1, inputfile = 'vgrids.in',
_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, outputfile))
'Outputfile: %s.'%(inputfile, spacing, pertubation*100, outputfile))
outfile.close()
def addBox(x = (None, None), y = (None, None), z = (None, None),

32
pylot/core/active/seismicArrayPreparation.py
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@@ -381,14 +381,34 @@ class SeisArray(object):
return surface
def generateFMTOMOinputFromArray(self, nRP, nThetaP, nPhiP, nRI, nThetaI, nPhiI,
Rbt, cushionfactor, interpolationMethod = 'linear',
def generateFMTOMOinputFromArray(self, nPointsPropgrid, nPointsInvgrid,
zBotTop, cushionfactor, interpolationMethod = 'linear',
customgrid = 'mygrid.in', writeVTK = True):
'''
Generate FMTOMO input files from the SeisArray dimensions.
Generates: vgrids.in, interfaces.in, propgrid.in
:param: nPointsPropgrid, number of points in each direction of the propagation grid (z, y, x)
:type: tuple
:param: nPointsInvgrid, number of points in each direction of the inversion grid (z, y, x)
:type: tuple
:param: zBotTop, (bottom, top) dimensions of the model
:type: tuple
:param: cushionfactor, adds cushioning around the model (0.1 = 10%)
:type: float
'''
nRP, nThetaP, nPhiP = nPointsPropgrid
nRI, nThetaI, nPhiI = nPointsInvgrid
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)'%(Rbt[0], Rbt[1]))
print('Bottom and Top of model: (%s, %s)'%(zBotTop[0], zBotTop[1]))
print('Method: %s, customgrid = %s'%(interpolationMethod, customgrid))
print('------------------------------------------------------------')
@@ -398,13 +418,13 @@ class SeisArray(object):
z.append(point[2])
return min(z)
self.generatePropgrid(nThetaP, nPhiP, nRP, Rbt, cushionfactor = cushionfactor,
self.generatePropgrid(nThetaP, nPhiP, nRP, zBotTop, cushionfactor = cushionfactor,
cushionpropgrid = 0.05)
surface = self.generateVgrid(nThetaI, nPhiI, nRI, Rbt, method = interpolationMethod,
surface = self.generateVgrid(nThetaI, nPhiI, nRI, zBotTop, method = interpolationMethod,
cushionfactor = cushionfactor, infilename = customgrid,
returnTopo = True)
depthmax = abs(Rbt[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)

82
pylot/core/pick/autopick.py
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@@ -3,7 +3,7 @@
"""
Function to run automated picking algorithms using AIC,
HOS and AR prediction. Uses object CharFuns and Picker and
HOS and AR prediction. Uses objects CharFuns and Picker and
function conglomerate utils.
:author: MAGS2 EP3 working group / Ludger Kueperkoch
@@ -16,6 +16,7 @@ from pylot.core.pick.Picker import AICPicker, PragPicker
from pylot.core.pick.CharFuns import HOScf, AICcf, ARZcf, ARHcf, AR3Ccf
from pylot.core.pick.utils import checksignallength, checkZ4S, earllatepicker,\
getSNR, fmpicker, checkPonsets, wadaticheck, crossings_nonzero_all
from pylot.core.util.utils import getPatternLine
from pylot.core.read.data import Data
from pylot.core.analysis.magnitude import WApp, DCfc
@@ -316,12 +317,11 @@ def autopickstation(wfstream, pickparam):
# from P pulse
# initialize Data object
data = Data()
[corzdat, restflag] = data.restituteWFData(invdir, zdat)
z_copy = zdat.copy()
[corzdat, restflag] = data.restituteWFData(invdir, z_copy)
if restflag == 1:
# integrate to displacement
corintzdat = integrate.cumtrapz(corzdat[0], None, corzdat[0].stats.delta)
# class needs stream object => build it
z_copy = zdat.copy()
z_copy[0].data = corintzdat
# largest detectable period == window length
# after P pulse for calculating source spectrum
@@ -799,3 +799,77 @@ def autopickstation(wfstream, pickparam):
picks[phase]['Ao'] = Ao
return picks
def iteratepicker(wf, NLLocfile, picks, badpicks, pickparameter):
'''
Repicking of bad onsets. Uses theoretical onset times from NLLoc-location file.
:param wf: waveform, obspy stream object
:param NLLocfile: path/name of NLLoc-location file
:param picks: dictionary of available onset times
:param badpicks: picks to be repicked
:param pickparameter: picking parameters from autoPyLoT-input file
'''
print("#######################################################")
print("autoPyLoT: Found bad onsets at station(s) %s, starting re-picking them ...") \
% badpicks
newpicks = {}
for i in range(0, len(badpicks)):
if len(badpicks[i][0]) > 4:
Ppattern = '%s ? ? ? P' % badpicks[i][0]
elif len(badpicks[i][0]) == 4:
Ppattern = '%s ? ? ? P' % badpicks[i][0]
elif len(badpicks[i][0]) < 4:
Ppattern = '%s ? ? ? P' % badpicks[i][0]
nllocline = getPatternLine(NLLocfile, Ppattern)
res = nllocline.split(None)[16]
# get theoretical P-onset time from residuum
badpicks[i][1] = picks[badpicks[i][0]]['P']['mpp'] - float(res)
# get corresponding waveform stream
wf2pick = wf.select(station=badpicks[i][0])
# modify some picking parameters
pstart_old = pickparameter.getParam('pstart')
pstop_old = pickparameter.getParam('pstop')
pickwinP_old = pickparameter.getParam('pickwinP')
Precalcwin_old = pickparameter.getParam('Precalcwin')
pickparameter.setParam(pstart=badpicks[i][1] - wf2pick[0].stats.starttime \
- pickparameter.getParam('tlta'))
pickparameter.setParam(pstop=pickparameter.getParam('pstart') + \
(3 * pickparameter.getParam('tlta')))
pickparameter.setParam(pickwinP=pickparameter.getParam('pickwinP') / 2)
pickparameter.setParam(Precalcwin=pickparameter.getParam('Precalcwin') / 2)
print("iteratepicker: The following picking parameters have been modified for iterative picking:")
print("pstart: %fs => %fs" % (pstart_old, pickparameter.getParam('pstart')))
print("pstop: %fs => %fs" % (pstop_old, pickparameter.getParam('pstop')))
print("pickwinP: %fs => %fs" % (pickwinP_old, pickparameter.getParam('pickwinP')))
print("Precalcwin: %fs => %fs" % (Precalcwin_old, pickparameter.getParam('Precalcwin')))
# repick station
newpicks = autopickstation(wf2pick, pickparameter)
# replace old dictionary with new one
picks[badpicks[i][0]] = newpicks
# reset temporary change of picking parameters
print("iteratepicker: Resetting picking parameters ...")
pickparameter.setParam(pstart=pstart_old)
pickparameter.setParam(pstop=pstop_old)
pickparameter.setParam(pickwinP=pickwinP_old)
pickparameter.setParam(Precalcwin=Precalcwin_old)
return picks

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

@@ -145,7 +145,7 @@ 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):