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Edit in Sources/backgroundModelSources.py such that the

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souce is only on the outer shell of the model.

Fixed bug is problem and survey classes.
This commit is contained in:
Gudni Karl
2015-02-19 18:24:34 -08:00
parent 36cde4fe4f
commit f25681ce80
4 changed files with 71 additions and 50 deletions
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simpegMT/Examples/simple3DfowardProblem.py
+1 -46
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@@ -35,51 +35,6 @@ survey = simpegmt.SurveyMT.SurveyMT(srcList)
problem = simpegmt.ProblemMT.MTProblem(M)
problem.pair(survey)
problem.fields(sig,sigBG)
fields = problem.fields(sig,sigBG)
mtData = survey.projectFields(fields)
def torecarray(MTdata,returnType='RealImag'):
'''
Function that returns a numpy.recarray for a SimpegMT data object.
'''
def rec2ndarr(x,dt=float):
return x.view((dt, len(x.dtype.names)))
# Define the record fields
dtRI = [('freq',float),('x',float),('y',float),('z',float),('zxxr',float),('zxxi',float),('zxyr',float),('zxyi',float),('zyxr',float),('zyxi',float),('zyyr',float),('zyyi',float)]
dtCP = [('freq',float),('x',float),('y',float),('z',float),('zxx',complex),('zxy',complex),('zyx',complex),('zyy',complex)]
impList = ['zxxr','zxxi','zxyr','zxyi','zyxr','zyxi','zyyr','zyyi']
for src in MTdata.survey.srcList:
# Temp array for all the receivers of the source.
tArrRec = np.array([(src.freq,rx.locs[0,0],rx.locs[0,1],rx.locs[0,2],np.nan ,np.nan ,np.nan ,np.nan ,np.nan ,np.nan ,np.nan ,np.nan ) for rx in src.rxList],dtype=dtRI)
# Get the type and the value for the mtdata object as a list
typeList = [[rx.rxType,MTdata[src,rx][0]] for rx in src.rxList]
# Insert the values to the temp array
for nr,(key,val) in enumerate(typeList):
tArrRec[key][nr] = val
# Masked array
mArrRec = np.ma.MaskedArray(rec2ndarr(tArrRec),mask=np.isnan(rec2ndarr(tArrRec))).view(dtype=tArrRec.dtype)
# Unique freq and loc of the masked array
uniFLmarr = np.unique(mArrRec[['freq','x','y','z']])
if 'RealImag' in returnType:
dt = dtRI
for uniFL in uniFLmarr:
mTemp = rec2ndarr(mArrRec[np.ma.where(mArrRec[['freq','x','y','z']].data == np.array(uniFL))][impList]).sum(axis=0)
try:
outArr = np.concatenate((outArr,simpeg.mkvc(np.concatenate((rec2ndarr(uniFL),mTemp.data)),2).T),axis=0)
except NameError as e:
outArr = simpeg.mkvc(np.concatenate((rec2ndarr(uniFL),mTemp.data)),2).T
elif 'Complex' in returnType:
# Add the real and imaginary to a complex number
dt = dtCP
for uniFL in uniFLmarr:
mTemp = simpeg.mkvc(rec2ndarr(mArrRec[np.ma.where(mArrRec[['freq','x','y','z']].data == np.array(uniFL))][impList]).sum(axis=0),2).T
dataBlock = np.sum(mTemp.data.reshape((mTemp.shape[0],4,2))*np.array([[[1,1j],[1,1j],[1,1j],[1,1j]]]),axis=2)
try:
outArr = np.concatenate((outArr,simpeg.mkvc(np.concatenate((rec2ndarr(uniFL),dataBlock)),2).T),axis=0)
except NameError as e:
outArr = simpeg.mkvc(np.concatenate((rec2ndarr(uniFL),dataBlock)),2).T
# Return
return outArr.view(dt)