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100 KiB
In [22]:
import SimPEG as simpeg
import simpegMT as simpegmt
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inlineIn [2]:
## Setup the problem
# Frequency
nFreq = 33
freqs = np.logspace(3,-3,nFreq)
# freqs = np.array([100,10,1,0.1,0.01])
# Make the mesh
ct = 10
air = simpeg.Utils.meshTensor([(ct,15,1.3)])
core = np.concatenate( ( np.kron(simpeg.Utils.meshTensor([(ct,15,-1.2)]),np.ones((5,))) , simpeg.Utils.meshTensor([(ct,5)]) ) )
bot = simpeg.Utils.meshTensor([(core[0],10,-1.3)])
x0 = -np.array([np.sum(np.concatenate((core,bot)))])
# Change to use no air
m1d = simpeg.Mesh.TensorMesh([np.concatenate((bot,core,air))], x0=x0)
## Setup model varibles
active = m1d.vectorCCx<0.
layer1 = (m1d.vectorCCx<-200.) & (m1d.vectorCCx>=-600.)
layer2 = (m1d.vectorCCx<-2000.) & (m1d.vectorCCx>=-4000.)
actMap = simpeg.Maps.ActiveCells(m1d, active, np.log(1e-8), nC=m1d.nCx)
mappingExpAct = simpeg.Maps.ExpMap(m1d) * actMap
sig_half = 2e-3
sig_air = 1e-8
sig_layer1 = 1
sig_layer2 = .1
# Make the true model
sigma_true = np.ones(m1d.nCx)*sig_air
sigma_true[active] = sig_half
sigma_true[layer1] = sig_layer1
sigma_true[layer2] = sig_layer2
m_true = np.log(sigma_true[active])
# Make the background model
sigma_0 = np.ones(m1d.nCx)*sig_air
sigma_0[active] = sig_half
m_0 = np.log(sigma_0[active])
# Receivers
# 1D impedance at the surface (elevation 0)
rxList = []
for rxType in ['z1dr','z1di']:
rxList.append(simpegmt.SurveyMT.RxMT(simpeg.mkvc(np.array([0.0]),2).T,rxType))
# Source list
srcList =[]
for freq in freqs:
srcList.append(simpegmt.SurveyMT.srcMT_polxy_1Dprimary(rxList,freq,sigma_0))
# Make the survey
survey = simpegmt.SurveyMT.SurveyMT(srcList)
survey.mtrue = m_true
# Set the problem
problem = simpegmt.ProblemMT1D.eForm_psField(m1d,mapping=mappingExpAct)
from pymatsolver import MumpsSolver
problem.solver = MumpsSolver
problem.pair(survey)In [3]:
# problem.mapping.sigmaMap._transform(m_0)In [4]:
sig_halfOut [4]:
0.002
In [5]:
## Make the observed data
# Project the data
d_true = survey.dpred(m_true)
survey.dtrue = d_true
# Add noise
std = 0.05 # 5% std
noise = std*abs(survey.dtrue)*np.random.randn(*survey.dtrue.shape)
# Assign the dobs
survey.dobs = survey.dtrue + noise
survey.std = survey.dobs*0 + std
# Assign the data weight
survey.Wd = 1/(abs(survey.dobs)*std)In [ ]:
In [6]:
## Setup the inversion proceedure
C = simpeg.Utils.Counter()
# Set the optimization
opt = simpeg.Optimization.InexactGaussNewton(maxIter = 50)
opt.counter = C
opt.LSshorten = 0.5
opt.remember('xc')
# Data misfit
dmis = simpeg.DataMisfit.l2_DataMisfit(survey)
# Regularization
# regMesh = simpeg.Mesh.TensorMesh([m1d.hx[problem.mapping.sigmaMap.maps[-1].indActive]])
# reg = simpeg.Regularization.Tikhonov(regMesh)
reg = simpeg.Regularization.Tikhonov(m1d,mapping=mappingExpAct)
reg.alpha_s = 1e-5
reg.alpha_x = 1.
reg.alpha_xx = .1
# Inversion problem
invProb = simpeg.InvProblem.BaseInvProblem(dmis, reg, opt)
invProb.counter = C
# Beta cooling
beta = simpeg.Directives.BetaSchedule()
betaest = simpeg.Directives.BetaEstimate_ByEig(beta0_ratio=0.75)
saveModel = simpeg.Directives.SaveModelEveryIteration()
# Create an inversion object
inv = simpeg.Inversion.BaseInversion(invProb, directiveList=[beta,betaest])#,saveModel])
In [7]:
problem.mapping.sigmaMap.maps[-1]Out [7]:
<SimPEG.Maps.ActiveCells at 0x7f38720f2690>
In [8]:
# Runn the inversion
mopt = inv.run(m_0)SimPEG.InvProblem will set Regularization.mref to m0.
SimPEG.InvProblem is setting bfgsH0 to the inverse of the eval2Deriv.
***Done using same solver as the problem***
SimPEG.l2_DataMisfit is creating default weightings for Wd.
============================ Inexact Gauss Newton ============================
# beta phi_d phi_m f |proj(x-g)-x| LS Comment
-----------------------------------------------------------------------------
0 2.01e+05 1.38e+06 6.91e-07 1.38e+06 2.03e+05 0
1 2.01e+05 1.66e+05 6.15e-06 1.66e+05 2.43e+04 0
2 2.01e+05 8.65e+04 1.09e-05 8.65e+04 1.51e+04 0 Skip BFGS
3 2.51e+04 7.32e+04 1.31e-05 7.32e+04 1.32e+04 0 Skip BFGS
4 2.51e+04 3.60e+04 3.07e-05 3.60e+04 7.51e+03 0 Skip BFGS
5 2.51e+04 2.97e+04 3.89e-05 2.97e+04 6.45e+03 0 Skip BFGS
6 3.14e+03 2.60e+04 4.57e-05 2.60e+04 5.81e+03 0 Skip BFGS
7 3.14e+03 1.40e+04 9.70e-05 1.40e+04 3.59e+03 0 Skip BFGS
8 3.14e+03 1.13e+04 1.25e-04 1.13e+04 3.04e+03 0 Skip BFGS
9 3.92e+02 9.74e+03 1.48e-04 9.74e+03 2.72e+03 0 Skip BFGS
10 3.92e+02 5.04e+03 3.06e-04 5.04e+03 1.66e+03 0 Skip BFGS
11 3.92e+02 3.98e+03 3.93e-04 3.98e+03 1.39e+03 0 Skip BFGS
12 4.90e+01 3.40e+03 4.63e-04 3.40e+03 1.23e+03 0 Skip BFGS
13 4.90e+01 1.79e+03 8.93e-04 1.79e+03 7.41e+02 0 Skip BFGS
14 4.90e+01 1.42e+03 1.13e-03 1.42e+03 6.04e+02 0 Skip BFGS
15 6.13e+00 1.23e+03 1.32e-03 1.23e+03 5.26e+02 0 Skip BFGS
16 6.13e+00 7.15e+02 2.19e-03 7.15e+02 3.08e+02 0 Skip BFGS
17 6.13e+00 5.94e+02 2.65e-03 5.94e+02 2.48e+02 0 Skip BFGS
18 7.66e-01 5.31e+02 2.98e-03 5.31e+02 2.16e+02 0 Skip BFGS
19 7.66e-01 3.63e+02 4.30e-03 3.63e+02 1.35e+02 0 Skip BFGS
20 7.66e-01 3.01e+02 4.92e-03 3.01e+02 1.15e+02 0 Skip BFGS
21 9.58e-02 2.61e+02 5.36e-03 2.61e+02 1.03e+02 0 Skip BFGS
22 9.58e-02 1.70e+02 7.17e-03 1.70e+02 7.52e+01 0 Skip BFGS
23 9.58e-02 1.12e+02 8.27e-03 1.12e+02 5.46e+01 0 Skip BFGS
24 1.20e-02 7.86e+01 9.19e-03 7.86e+01 4.19e+01 0 Skip BFGS
25 1.20e-02 4.42e+01 1.18e-02 4.42e+01 3.46e+01 0 Skip BFGS
26 1.20e-02 2.82e+01 1.32e-02 2.82e+01 1.50e+01 0 Skip BFGS
27 1.50e-03 2.39e+01 1.40e-02 2.39e+01 1.10e+01 0 Skip BFGS
28 1.50e-03 1.94e+01 1.62e-02 1.94e+01 1.02e+01 0 Skip BFGS
29 1.50e-03 1.82e+01 1.76e-02 1.82e+01 2.73e+00 0 Skip BFGS
30 1.87e-04 1.80e+01 1.87e-02 1.80e+01 8.26e-01 0 Skip BFGS
31 1.87e-04 1.79e+01 1.95e-02 1.79e+01 1.04e+00 0 Skip BFGS
32 1.87e-04 1.79e+01 1.97e-02 1.79e+01 7.23e-01 0
33 2.34e-05 1.77e+01 2.30e-02 1.77e+01 2.97e+00 0 Skip BFGS
34 2.34e-05 1.77e+01 2.85e-02 1.77e+01 1.93e+00 0 Skip BFGS
35 2.34e-05 1.76e+01 2.77e-02 1.76e+01 4.66e-01 0
36 2.92e-06 1.76e+01 2.87e-02 1.76e+01 4.19e-01 0
37 2.92e-06 1.76e+01 3.20e-02 1.76e+01 1.03e+00 0
38 2.92e-06 1.76e+01 3.92e-02 1.76e+01 1.95e+00 0
39 3.65e-07 1.76e+01 4.02e-02 1.76e+01 4.95e-01 0
40 3.65e-07 1.76e+01 3.91e-02 1.76e+01 3.65e-01 0
41 3.65e-07 1.76e+01 3.91e-02 1.76e+01 3.16e-01 0
42 4.57e-08 1.76e+01 3.93e-02 1.76e+01 3.42e-01 0
43 4.57e-08 1.75e+01 4.67e-02 1.75e+01 1.26e+00 0 Skip BFGS
44 4.57e-08 1.75e+01 5.23e-02 1.75e+01 1.70e+00 1
45 5.71e-09 1.75e+01 5.63e-02 1.75e+01 9.87e-01 0
46 5.71e-09 1.75e+01 6.77e-02 1.75e+01 1.55e+00 1 Skip BFGS
47 5.71e-09 1.75e+01 6.29e-02 1.75e+01 9.07e-01 0
48 7.14e-10 1.75e+01 6.29e-02 1.75e+01 8.89e-01 0 Skip BFGS
49 7.14e-10 1.75e+01 6.56e-02 1.75e+01 6.85e-01 0
50 7.14e-10 1.75e+01 6.72e-02 1.75e+01 6.46e-01 0
------------------------- STOP! -------------------------
1 : |fc-fOld| = 8.4462e-04 <= tolF*(1+|f0|) = 1.3818e+05
1 : |xc-x_last| = 1.0965e-01 <= tolX*(1+|x0|) = 5.9957e+00
0 : |proj(x-g)-x| = 6.4640e-01 <= tolG = 1.0000e-01
0 : |proj(x-g)-x| = 6.4640e-01 <= 1e3*eps = 1.0000e-02
1 : maxIter = 50 <= iter = 50
------------------------- DONE! -------------------------
In [ ]:
In [9]:
## Setup the inversion proceedure
C = simpeg.Utils.Counter()
# Set the optimization
optc = simpeg.Optimization.InexactGaussNewton(maxIter = 20)
optc.counter = C
optc.LSshorten = 0.5
optc.remember('xc')
# Data misfit
dmisc = simpeg.DataMisfit.l2_DataMisfit(survey)
# Regularization
# regMesh = simpeg.Mesh.TensorMesh([m1d.hx[problem.mapping.sigmaMap.maps[-1].indActive]])
# reg = simpeg.Regularization.Tikhonov(regMesh)
regc = simpeg.Regularization.Tikhonov(m1d,mapping=mappingExpAct)
regc.alpha_s = 1e-5
regc.alpha_x = 1.
# Inversion problem
invProbc = simpeg.InvProblem.BaseInvProblem(dmisc, regc, optc)
invProbc.counter = C
# Beta cooling
betac = simpeg.Directives.BetaSchedule()
betaestc = simpeg.Directives.BetaEstimate_ByEig(beta0_ratio=0.75)
saveModel = simpeg.Directives.SaveModelEveryIteration()
# Create an inversion object
invc = simpeg.Inversion.BaseInversion(invProbc, directiveList=[betac,betaestc])In [10]:
mopt2 = invc.run(mopt)SimPEG.InvProblem will set Regularization.mref to m0.
SimPEG.InvProblem is setting bfgsH0 to the inverse of the eval2Deriv.
***Done using same solver as the problem***
SimPEG.l2_DataMisfit is creating default weightings for Wd.
============================ Inexact Gauss Newton ============================
# beta phi_d phi_m f |proj(x-g)-x| LS Comment
-----------------------------------------------------------------------------
0 1.22e+03 1.75e+01 6.95e-02 1.02e+02 1.27e+02 0
1 1.22e+03 2.83e+01 2.63e-02 6.03e+01 6.19e+01 0
2 1.22e+03 2.04e+01 2.86e-02 5.52e+01 6.08e+01 0
3 1.52e+02 1.84e+01 2.72e-02 2.25e+01 8.98e+00 0
4 1.52e+02 1.78e+01 2.46e-02 2.16e+01 3.60e+00 0
5 1.52e+02 1.77e+01 2.44e-02 2.14e+01 2.75e+00 0
6 1.90e+01 1.77e+01 2.39e-02 1.82e+01 2.01e+00 0
7 1.90e+01 1.76e+01 2.46e-02 1.81e+01 9.52e-01 0
8 1.90e+01 1.76e+01 2.45e-02 1.81e+01 6.50e-01 0
9 2.38e+00 1.76e+01 2.44e-02 1.77e+01 7.01e-01 0
10 2.38e+00 1.76e+01 2.44e-02 1.77e+01 1.05e+00 0 Skip BFGS
11 2.38e+00 1.76e+01 2.45e-02 1.77e+01 6.53e-01 0
12 2.97e-01 1.76e+01 2.45e-02 1.76e+01 7.44e-01 0
13 2.97e-01 1.76e+01 2.46e-02 1.76e+01 9.88e-01 0
14 2.97e-01 1.76e+01 2.60e-02 1.76e+01 6.11e-01 0
15 3.71e-02 1.76e+01 2.60e-02 1.76e+01 7.53e-01 0
16 3.71e-02 1.76e+01 2.87e-02 1.76e+01 1.45e+00 1
17 3.71e-02 1.76e+01 2.90e-02 1.76e+01 1.29e+00 0
18 4.64e-03 1.76e+01 2.91e-02 1.76e+01 1.02e+00 0
19 4.64e-03 1.76e+01 2.90e-02 1.76e+01 1.35e+00 0
20 4.64e-03 1.76e+01 3.08e-02 1.76e+01 1.38e+00 0 Skip BFGS
------------------------- STOP! -------------------------
1 : |fc-fOld| = 2.1982e-03 <= tolF*(1+|f0|) = 1.0299e+01
1 : |xc-x_last| = 3.4790e-01 <= tolX*(1+|x0|) = 4.5116e+00
0 : |proj(x-g)-x| = 1.3805e+00 <= tolG = 1.0000e-01
0 : |proj(x-g)-x| = 1.3805e+00 <= 1e3*eps = 1.0000e-02
1 : maxIter = 20 <= iter = 20
------------------------- DONE! -------------------------
In [11]:
moptc=mopt2In [12]:
## Setup the inversion proceedure
C = simpeg.Utils.Counter()
# Set the optimization
optc1 = simpeg.Optimization.InexactGaussNewton(maxIter = 20)
optc1.counter = C
optc1.LSshorten = 0.1
optc1.remember('xc')
# Data misfit
dmisc1 = simpeg.DataMisfit.l2_DataMisfit(survey)
# Regularization
# regMesh = simpeg.Mesh.TensorMesh([m1d.hx[problem.mapping.sigmaMap.maps[-1].indActive]])
# reg = simpeg.Regularization.Tikhonov(regMesh)
regc1 = simpeg.Regularization.Tikhonov(m1d,mapping=mappingExpAct)
regc1.alpha_s = 1e-5
regc1.alpha_x = 1.
regc1.mref = reg.mref
# Inversion problem
invProbc1 = simpeg.InvProblem.BaseInvProblem(dmisc1, regc1, optc1)
invProbc1.counter = C
# Beta cooling
betac1 = simpeg.Directives.BetaSchedule()
betaestc1 = simpeg.Directives.BetaEstimate_ByEig(beta0_ratio=0.75)
betaestc1.beta0 = 3.60e-03
saveModel = simpeg.Directives.SaveModelEveryIteration()
# Create an inversion object
invc1 = simpeg.Inversion.BaseInversion(invProbc1, directiveList=[betac1,betaestc1])In [13]:
moptc1 = invc1.run(mopt2)SimPEG.InvProblem is setting bfgsH0 to the inverse of the eval2Deriv.
***Done using same solver as the problem***
SimPEG.l2_DataMisfit is creating default weightings for Wd.
============================ Inexact Gauss Newton ============================
# beta phi_d phi_m f |proj(x-g)-x| LS Comment
-----------------------------------------------------------------------------
0 1.30e-02 1.76e+01 2.85e-02 1.76e+01 1.38e+00 0
1 1.30e-02 1.75e+01 2.85e-02 1.75e+01 1.17e+00 1
2 1.30e-02 1.75e+01 2.85e-02 1.75e+01 9.35e-01 1 Skip BFGS
3 1.62e-03 1.75e+01 2.85e-02 1.75e+01 7.47e-01 1 Skip BFGS
4 1.62e-03 1.75e+01 2.85e-02 1.75e+01 1.00e+00 2 Skip BFGS
5 1.62e-03 1.75e+01 2.85e-02 1.75e+01 1.00e+00 3 Skip BFGS
6 2.03e-04 1.75e+01 2.85e-02 1.75e+01 1.01e+00 3 Skip BFGS
7 2.03e-04 1.75e+01 2.85e-02 1.75e+01 1.01e+00 3 Skip BFGS
8 2.03e-04 1.75e+01 2.85e-02 1.75e+01 1.02e+00 3 Skip BFGS
9 2.53e-05 1.75e+01 2.85e-02 1.75e+01 1.02e+00 3 Skip BFGS
10 2.53e-05 1.75e+01 2.85e-02 1.75e+01 1.03e+00 3 Skip BFGS
11 2.53e-05 1.75e+01 2.85e-02 1.75e+01 1.04e+00 3 Skip BFGS
12 3.16e-06 1.75e+01 2.85e-02 1.75e+01 1.05e+00 3 Skip BFGS
13 3.16e-06 1.75e+01 2.85e-02 1.75e+01 1.06e+00 3 Skip BFGS
14 3.16e-06 1.75e+01 2.85e-02 1.75e+01 1.07e+00 3 Skip BFGS
15 3.96e-07 1.75e+01 2.85e-02 1.75e+01 1.08e+00 3 Skip BFGS
16 3.96e-07 1.75e+01 2.85e-02 1.75e+01 1.10e+00 3 Skip BFGS
17 3.96e-07 1.75e+01 2.85e-02 1.75e+01 1.11e+00 3 Skip BFGS
18 4.94e-08 1.75e+01 2.85e-02 1.75e+01 1.13e+00 3 Skip BFGS
19 4.94e-08 1.75e+01 2.85e-02 1.75e+01 1.14e+00 3 Skip BFGS
20 4.94e-08 1.75e+01 2.85e-02 1.75e+01 1.16e+00 3 Skip BFGS
------------------------- STOP! -------------------------
1 : |fc-fOld| = 2.2454e-04 <= tolF*(1+|f0|) = 1.8553e+00
1 : |xc-x_last| = 1.9180e-01 <= tolX*(1+|x0|) = 4.4390e+00
0 : |proj(x-g)-x| = 1.1563e+00 <= tolG = 1.0000e-01
0 : |proj(x-g)-x| = 1.1563e+00 <= 1e3*eps = 1.0000e-02
1 : maxIter = 20 <= iter = 20
------------------------- DONE! -------------------------
In [14]:
opt.counter.summary()
xc = opt.recall('xc')Counters: InexactGaussNewton.doEndIteration : 50 InexactGaussNewton.doStartIteration : 51 InexactGaussNewton.scaleSearchDirection : 50 Times: mean sum BaseInvProblem.evalFunction : 3.24e+00, 3.33e+02, 103x InexactGaussNewton.findSearchDirection : 2.07e+01, 1.04e+03, 50x InexactGaussNewton.minimize : 1.37e+03, 1.37e+03, 1x InexactGaussNewton.modifySearchDirection: 1.93e+00, 9.63e+01, 50x InexactGaussNewton.projection : 4.69e-05, 9.75e-03, 208x
In [15]:
# import matplotlib.pyplot as plt
# # plt.figure(1)
# # for i in range(problem.G.shape[0]):
# # plt.plot(problem.G[i,:])
# meshPts = np.concatenate((mesh.gridN[0:1],np.kron(mesh.gridN[1::],np.ones(2))[:-1]))
# modelPts = np.kron(1./model,np.ones(2,))
# axM.semilogx(modelPts,meshPts,color=col)
# plt.figure(2)
# plt.plot(m1d.vectorCCx[active], np.log10(mappingExpAct*survey.mtrue)[active], 'b-')
# plt.plot(m1d.vectorCCx[active], np.log10(mappingExpAct*mopt)[active], 'r-')
# plt.show()
In [ ]:
In [16]:
def plotMT1DModelData(problem,models,symList=None):
# Make the analytic solution
# def makeAnalyticSolution(mesh,model,elev,freqs):
# data1D = []
# for freq in freqs:
# anaEd, anaEu, anaHd, anaHu = simpegmt.Utils.MT1Danalytic.getEHfields(mesh,model,freq,elev)
# anaE = anaEd+anaEu
# anaH = anaHd+anaHu
# # Scale the solution
# # anaE = (anaEtemp/anaEtemp[-1])#.conj()
# # anaH = (anaHtemp/anaEtemp[-1])#.conj()
# anaZ = anaE/anaH
# # Add to the list
# data1D.append((freq,0,0,elev,anaZ[0]))
# dataRec = np.array(data1D,dtype=[('freq',float),('x',float),('y',float),('z',float),('zxx',complex)])
# return dataRec
def appResPhs(freq,z):
fr = simpeg.mkvc(freq,2)*np.ones(z.shape)
app_res = ((1./(8e-7*np.pi**2))/fr)*np.abs(z)**2
app_phs = np.arctan2(z.imag,z.real)*(180/np.pi)
return app_res, app_phs
# Setup the figure
fontSize = 15
fig = plt.figure(figsize=[9,7])
axM = fig.add_axes([0.075,.1,.25,.875])
axM.set_xlabel('Resistivity [Ohm*m]',fontsize=fontSize)
axM.set_xlim(1e-1,1e5)
axM.set_ylim(-10000,5000)
axM.set_ylabel('Depth [km]',fontsize=fontSize)
axR = fig.add_axes([0.42,.575,.5,.4])
axR.set_xscale('log')
axR.set_yscale('log')
axR.invert_xaxis()
# axR.set_xlabel('Frequency [Hz]')
axR.set_ylabel('Apparent resistivity [Ohm m]',fontsize=fontSize)
axP = fig.add_axes([0.42,.1,.5,.4])
axP.set_xscale('log')
axP.invert_xaxis()
axP.set_ylim(0,90)
axP.set_xlabel('Frequency [Hz]',fontsize=fontSize)
axP.set_ylabel('Apparent phase [deg]',fontsize=fontSize)
# if not symList:
# symList = ['x']*len(models)
sys.path.append('/home/gudni/Dropbox/code/python/MTview')
import plotDataTypes as pDt
# Loop through the models.
modelList = [problem.survey.mtrue]
modelList.extend(models)
if False:
modelList = [problem.mapping.sigmaMap*mod for mod in modelList]
for nr, model in enumerate(modelList):
# Calculate the data
if nr==0:
data1D = problem.dataPair(problem.survey,problem.survey.dobs).toRecArray('Complex')
else:
data1D = problem.dataPair(problem.survey,problem.survey.dpred(model)).toRecArray('Complex')
# Plot the data and the model
colRat = nr/((len(modelList)-2)*1.)
if colRat > 1.:
col = 'k'
else:
col = plt.cm.seismic(1-colRat)
# The model - make the pts to plot
meshPts = np.concatenate((problem.mesh.gridN[0:1],np.kron(problem.mesh.gridN[1::],np.ones(2))[:-1]))
modelPts = np.kron(1./(problem.mapping.sigmaMap*model),np.ones(2,))
axM.semilogx(modelPts,meshPts,color=col)
## Data
# Appres
pDt.plotIsoStaImpedance(axR,np.array([0,0]),data1D,'zyx','res',pColor=col)
# Appphs
pDt.plotIsoStaImpedance(axP,np.array([0,0]),data1D,'zyx','phs',pColor=col)
try:
allData = np.concatenate((allData,mkvc(data1D['zyx'],2)),1)
except:
allData = simpeg.mkvc(data1D['zyx'],2)
freq = data1D['freq']
res, phs = appResPhs(freq,allData)
stdCol = 'gray'
axRtw = axR.twinx()
axRtw.set_ylabel('Std of log10',color=stdCol)
[(t.set_color(stdCol), t.set_rotation(-45)) for t in axRtw.get_yticklabels()]
axPtw = axP.twinx()
axPtw.set_ylabel('Std ',color=stdCol)
[t.set_color(stdCol) for t in axPtw.get_yticklabels()]
axRtw.plot(freq, np.std(np.log10(res),1),'--',color=stdCol)
axPtw.plot(freq, np.std(phs,1),'--',color=stdCol)
# Fix labels and ticks
yMtick = [l/1000 for l in axM.get_yticks().tolist()]
axM.set_yticklabels(yMtick)
[ l.set_rotation(90) for l in axM.get_yticklabels()]
[ l.set_rotation(90) for l in axR.get_yticklabels()]
[(t.set_color(stdCol), t.set_rotation(-45)) for t in axRtw.get_yticklabels()]
[t.set_color(stdCol) for t in axPtw.get_yticklabels()]
for ax in [axM,axR,axP]:
ax.xaxis.set_tick_params(labelsize=fontSize)
ax.yaxis.set_tick_params(labelsize=fontSize)
return fig
# plotMT1DModelData(problem,[mopt])In [23]:
plotMT1DModelData(problem,[mopt,moptc,moptc1])
plt.show()
In [18]:
modelList = [problem.survey.mtrue]
modelList.extend([mopt])
# problem.mapping.sigmaMap*moptIn [19]:
src = survey.srcList[0]
[[rx.rxType.replace('z1d','zyx')] for rx in src.rxList ]Out [19]:
[['zyxr'], ['zyxi']]
In [20]:
'z1dr'.replace('z1d','zyx')Out [20]:
'zyxr'
In [ ]: