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Edit in Sources/backgroundModelSources.py such that the

Browse Source 
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
View File
@@ -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)
simpegMT/ProblemMT.py
+1 -1
View File
@@ -108,7 +108,7 @@ class MTProblem(Problem.BaseProblem):
# RHS, CalcFields = self.getRHS(freq,m_back), self.calcFields
F = FieldsMT(self.mesh, self.survey)
#NOTE: add print status statements.
for freq in self.survey.freqs:
A = self.getA(freq)
rhs = self.getRHS(freq,m_back)
simpegMT/Sources/backgroundModelSources.py
+2 -2
View File
@@ -1,5 +1,4 @@
import SimPEG as simpeg, numpy as np
from simpegMT.Utils import get1DEfields
def homo1DModelSource(mesh,freq,m_back):
'''
@@ -14,7 +13,6 @@ def homo1DModelSource(mesh,freq,m_back):
'''
# import
import SimPEG as simpeg
from simpegMT.Utils import get1DEfields
# Get a 1d solution for a halfspace background
mesh1d = simpeg.Mesh.TensorMesh([mesh.hz],np.array([mesh.x0[2]]))
@@ -27,6 +25,7 @@ def homo1DModelSource(mesh,freq,m_back):
for i in np.arange(mesh.vnEx[0]):
for j in np.arange(mesh.vnEx[1]):
ex_px[i,j,:] = e0_1d
ex_px[1:-1,1:-1,1:-1] = 0
eBG_px = np.vstack((simpeg.Utils.mkvc(mesh.r(ex_px,'Ex','Ex','V'),2),ey_px,ez_px))
# Setup y (north) polarization (_py)
ex_py = np.zeros((mesh.nEx,1), dtype='complex128')
@@ -36,6 +35,7 @@ def homo1DModelSource(mesh,freq,m_back):
for i in np.arange(mesh.vnEy[0]):
for j in np.arange(mesh.vnEy[1]):
ey_py[i,j,:] = e0_1d
ex_py[1:-1,1:-1,1:-1] = 0
eBG_py = np.vstack((ex_py,simpeg.Utils.mkvc(ey_py,2),ez_py))
# Return the electric fields
simpegMT/SurveyMT.py
+67 -1
View File
@@ -208,7 +208,7 @@ class SurveyMT(Survey.BaseSurvey):
return self._freqDict[freq]
def projectFields(self, u):
data = Survey.Data(self)
data = DataMT(self)
for src in self.srcList:
for rx in src.rxList:
data[src, rx] = rx.projectFields(src, self.mesh, u)
@@ -216,3 +216,69 @@ class SurveyMT(Survey.BaseSurvey):
def projectFieldsDeriv(self, u):
raise Exception('Use Transmitters to project fields deriv.')
class DataMT(Survey.Data):
'''
Data class for MTdata
:param SimPEG survey object survey:
:param v vector with data
'''
def __init__(self, survey, v=None):
# Pass the variables to the "parent" method
Survey.Data.__init__(self, survey, v)
def toRecArray(self,returnType='RealImag'):
'''
Function that returns a numpy.recarray for a SimpegMT impedance data object.
:param str returnType: Switches between returning a rec array where the impedance is split to real and imaginary ('RealImag') or is a complex ('Complex')
'''
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 self.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 DataMT object as a list
typeList = [[rx.rxType,self[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)
dataBlock = simpeg.mkvc(np.concatenate((rec2ndarr(uniFL),mTemp.data)),2).T
try:
outArr = np.concatenate((outArr,dataBlock),axis=0)
except NameError as e:
outArr = dataBlock
elif 'Complex' in returnType:
# Add the real and imaginary to a complex number
from numpy.lib import recfunctions as recFunc
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
compBlock = np.sum(mTemp.data.reshape((4,2))*np.array([[1,1j],[1,1j],[1,1j],[1,1j]]),axis=1).copy().view(dt[4::])
dataBlock = simpeg.mkvc(recFunc.merge_arrays((np.array(uniFL),compBlock),flatten=True),2).T
try:
outArr = recFunc.stack_arrays((outArr,dataBlock),usemask=False)
except NameError as e:
outArr = dataBlock
# Return
if 'RealImag' in returnType:
return outArr.view(dt)
elif 'Complex' in returnType:
return outArr