mirror of
https://github.com/wassname/simpeg.git
synced 2026-07-23 13:10:51 +08:00
Working 2.5D fwd (nodal discretization)
On going Jvec and Jtvec
This commit is contained in:
seogi_macbook
@@ -134,7 +134,6 @@ class BaseEMProblem(Problem.BaseProblem):
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"""
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return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u) * self.curModel.sigmaDeriv
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@property
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def MeSigmaI(self):
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"""
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@@ -157,7 +156,6 @@ class BaseEMProblem(Problem.BaseProblem):
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return dMeSigmaI_dI * ( dMe_dsig * ( dsig_dm))
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# return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma, invMat=True)(u)
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@property
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def MfRho(self):
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"""
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@@ -105,3 +105,42 @@ class Fields_ky_CC(Fields_ky):
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def _e(self, phiSolution, srcList):
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raise NotImplementedError
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class Fields_ky_N(Fields_ky):
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knownFields = {'phiSolution':'N'}
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aliasFields = {
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'phi': ['phiSolution','N','_phi'],
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'j' : ['phiSolution','E','_j'],
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'e' : ['phiSolution','E','_e'],
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}
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# primary - secondary
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# CC variables
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def __init__(self, mesh, survey, **kwargs):
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Fields_ky.__init__(self, mesh, survey, **kwargs)
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def startup(self):
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self.prob = self.survey.prob
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def _GLoc(self, fieldType):
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if fieldType == 'phi':
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return 'N'
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elif fieldType == 'e' or fieldType == 'j':
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return 'E'
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else:
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raise Exception('Field type must be phi, e, j')
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def _phi(self, phiSolution, src, kyInd):
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return phiSolution
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def _phiDeriv_u(self, kyInd, src, v, adjoint = False):
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return Identity()*v
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def _phiDeriv_m(self, kyInd, src, v, adjoint = False):
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return Zero()
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def _j(self, phiSolution, srcList):
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raise NotImplementedError
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def _e(self, phiSolution, srcList):
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raise NotImplementedError
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@@ -267,8 +267,6 @@ class Problem3D_N(BaseDCProblem):
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# Handling Null space of A
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A[0,0] = A[0,0] + 1.
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# if self._makeASymmetric is True:
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# return V.T * A
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return A
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def getADeriv(self, u, v, adjoint=False):
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@@ -293,8 +291,6 @@ class Problem3D_N(BaseDCProblem):
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"""
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RHS = self.getSourceTerm()
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# if self._makeASymmetric is True:
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# return self.Vol.T * RHS
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return RHS
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def getRHSDeriv(self, src, v, adjoint=False):
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@@ -1,7 +1,7 @@
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from SimPEG import Problem, Utils
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from SimPEG.EM.Base import BaseEMProblem
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from SurveyDC import Survey, Survey_ky
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from FieldsDC_2D import Fields_ky, Fields_ky_CC
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from FieldsDC_2D import Fields_ky, Fields_ky_CC, Fields_ky_N
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from SimPEG.Utils import sdiag
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import numpy as np
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from SimPEG.Utils import Zero
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@@ -90,14 +90,10 @@ class BaseDCProblem_2D(BaseEMProblem):
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dky = np.r_[dky[0], dky]
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y = 0.
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for src in self.survey.srcList:
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for rx in src.rxList:
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Jtv_temp1 = np.zeros(m.size)
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Jtv_temp0 = np.zeros(m.size)
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for iky in range(self.nky):
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u_src = f[src, self._solutionType, iky]
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ky = self.kys[iky]
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@@ -152,7 +148,7 @@ class Problem2D_CC(BaseDCProblem_2D):
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_solutionType = 'phiSolution'
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_formulation = 'HJ' # CC potentials means J is on faces
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fieldsPair = Fields_ky_CC
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fieldsPair = Fields_ky_N
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def __init__(self, mesh, **kwargs):
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BaseDCProblem_2D.__init__(self, mesh, **kwargs)
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@@ -269,3 +265,85 @@ class Problem2D_CC(BaseDCProblem_2D):
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P_BC, B = self.mesh.getBCProjWF_simple()
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M = B*self.mesh.aveCC2F
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self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M
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class Problem2D_N(BaseDCProblem_2D):
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_solutionType = 'phiSolution'
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_formulation = 'EB' # CC potentials means J is on faces
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fieldsPair = Fields_ky_N
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def __init__(self, mesh, **kwargs):
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BaseDCProblem_2D.__init__(self, mesh, **kwargs)
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# self.setBC()
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@property
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def MnSigma(self):
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"""
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Node inner product matrix for \\(\\sigma\\). Used in the E-B formulation
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"""
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# TODO: only works isotropic sigma
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sigma = self.curModel.sigma
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vol = self.mesh.vol
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MnSigma = Utils.sdiag(self.mesh.aveN2CC.T*(Utils.sdiag(vol)*sigma))
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return MnSigma
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def MnSigmaDeriv(self, u):
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"""
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Derivative of MnSigma with respect to the model
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"""
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sigma = self.curModel.sigma
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sigmaderiv = self.curModel.sigmaDeriv
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vol = self.mesh.vol
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return Utils.sdiag(u)*self.mesh.aveN2CC.T*Utils.sdiag(vol) * self.curModel.sigmaDeriv
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def getA(self, ky):
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"""
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Make the A matrix for the cell centered DC resistivity problem
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A = D MfRhoI D^\\top V
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"""
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# TODO: this won't work for full anisotropy
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MeSigma = self.MeSigma
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MnSigma = self.MnSigma
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Grad = self.mesh.nodalGrad
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# Get conductivity sigma
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sigma = self.curModel.sigma
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A = Grad.T * MeSigma * Grad + ky**2*MnSigma
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# Handling Null space of A
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A[0,0] = A[0,0] + 1.
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return A
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def getADeriv(self, ky, u, v, adjoint= False):
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MeSigma = self.MeSigma
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Grad = self.mesh.nodalGrad
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sigma = self.curModel.sigma
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vol = self.mesh.vol
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if adjoint:
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return Grad.T*(self.MeSigmaDeriv(Grad*u)*v) + ky**2*self.MnSigmaDeriv(u)*v
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return self.MeSigmaDeriv(Grad*u).T * (Grad*v) + ky**2*self.MnSigmaDeriv(u)*v
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def getRHS(self, ky):
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"""
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RHS for the DC problem
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q
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"""
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RHS = self.getSourceTerm(ky)
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return RHS
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def getRHSDeriv(self, ky, src, v, adjoint=False):
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"""
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Derivative of the right hand side with respect to the model
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"""
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# TODO: add qDeriv for RHS depending on m
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# qDeriv = src.evalDeriv(self, ky, adjoint=adjoint)
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# return qDeriv
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return Zero()
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@@ -47,8 +47,7 @@ class Pole(BaseSrc):
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q = np.zeros(prob.mesh.nC)
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q[inds] = self.current * np.r_[1.]
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elif prob._formulation == 'EB':
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inds = closestPoints(prob.mesh, self.loc)
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q = np.zeros(prob.mesh.nN)
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q[inds] = self.current * np.r_[1.]
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q = prob.mesh.getInterpolationMat(self.loc, locType='N').todense()
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q = self.current * mkvc(q)
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return q
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@@ -1,5 +1,5 @@
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from ProblemDC import Problem3D_CC, Problem3D_N
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from ProblemDC_2D import Problem2D_CC
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from ProblemDC_2D import Problem2D_CC, Problem2D_N
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from SurveyDC import Survey, Survey_ky
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import SrcDC as Src #Pole
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import RxDC as Rx
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@@ -3,7 +3,67 @@ from SimPEG import *
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import SimPEG.EM.Static.DC as DC
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class DCProblem_2DTestsCC(unittest.TestCase):
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# class DCProblem_2DTestsCC(unittest.TestCase):
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# def setUp(self):
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# cs = 12.5
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# hx = [(cs,7, -1.3),(cs,61),(cs,7, 1.3)]
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# hy = [(cs,7, -1.3),(cs,20)]
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# mesh = Mesh.TensorMesh([hx, hy],x0="CN")
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# x = np.linspace(-135, 250., 20)
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# M = Utils.ndgrid(x-12.5, np.r_[0.])
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# N = Utils.ndgrid(x+12.5, np.r_[0.])
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# A0loc = np.r_[-150, 0.]
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# A1loc = np.r_[-130, 0.]
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# rxloc = [np.c_[M, np.zeros(20)], np.c_[N, np.zeros(20)]]
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# rx = DC.Rx.Dipole_ky(M, N)
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# src0 = DC.Src.Pole([rx], A0loc)
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# src1 = DC.Src.Pole([rx], A1loc)
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# survey = DC.Survey_ky([src0, src1])
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# problem = DC.Problem2D_CC(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
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# problem.pair(survey)
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# mSynth = np.ones(mesh.nC)*1.
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# survey.makeSyntheticData(mSynth)
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# # Now set up the problem to do some minimization
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# dmis = DataMisfit.l2_DataMisfit(survey)
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# reg = Regularization.Tikhonov(mesh)
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# opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
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# invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e0)
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# inv = Inversion.BaseInversion(invProb)
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# self.inv = inv
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# self.reg = reg
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# self.p = problem
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# self.mesh = mesh
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# self.m0 = mSynth
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# self.survey = survey
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# self.dmis = dmis
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# def test_misfit(self):
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# derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
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# passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
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# self.assertTrue(passed)
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# def test_adjoint(self):
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# # Adjoint Test
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# u = np.random.rand(self.mesh.nC*self.survey.nSrc)
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# v = np.random.rand(self.mesh.nC)
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# w = np.random.rand(self.survey.dobs.shape[0])
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# wtJv = w.dot(self.p.Jvec(self.m0, v))
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# vtJtw = v.dot(self.p.Jtvec(self.m0, w))
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# passed = np.abs(wtJv - vtJtw) < 1e-10
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# print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
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# self.assertTrue(passed)
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# def test_dataObj(self):
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# derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
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# passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
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# self.assertTrue(passed)
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class DCProblemTestsN(unittest.TestCase):
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def setUp(self):
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@@ -21,7 +81,7 @@ class DCProblem_2DTestsCC(unittest.TestCase):
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src0 = DC.Src.Pole([rx], A0loc)
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src1 = DC.Src.Pole([rx], A1loc)
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survey = DC.Survey_ky([src0, src1])
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problem = DC.Problem2D_CC(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
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problem = DC.Problem2D_N(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
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problem.pair(survey)
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mSynth = np.ones(mesh.nC)*1.
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@@ -34,94 +94,34 @@ class DCProblem_2DTestsCC(unittest.TestCase):
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invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e0)
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inv = Inversion.BaseInversion(invProb)
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self.inv = inv
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self.reg = reg
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self.p = problem
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self.mesh = mesh
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self.m0 = mSynth
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self.inv = inv
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self.reg = reg
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self.p = problem
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self.mesh = mesh
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self.m0 = mSynth
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self.survey = survey
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self.dmis = dmis
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self.dmis = dmis
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def test_misfit(self):
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derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
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passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
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passed = Tests.checkDerivative(derChk, self.m0, plotIt=False)
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self.assertTrue(passed)
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def test_adjoint(self):
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# Adjoint Test
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u = np.random.rand(self.mesh.nC*self.survey.nSrc)
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v = np.random.rand(self.mesh.nC)
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w = np.random.rand(self.survey.dobs.shape[0])
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wtJv = w.dot(self.p.Jvec(self.m0, v))
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vtJtw = v.dot(self.p.Jtvec(self.m0, w))
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passed = np.abs(wtJv - vtJtw) < 1e-10
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print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
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self.assertTrue(passed)
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# def test_adjoint(self):
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# # Adjoint Test
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# u = np.random.rand(self.mesh.nC*self.survey.nSrc)
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# v = np.random.rand(self.mesh.nC)
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# w = np.random.rand(self.survey.dobs.shape[0])
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# wtJv = w.dot(self.p.Jvec(self.m0, v))
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# vtJtw = v.dot(self.p.Jtvec(self.m0, w))
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# passed = np.abs(wtJv - vtJtw) < 1e-8
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# print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
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# self.assertTrue(passed)
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def test_dataObj(self):
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derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
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passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
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self.assertTrue(passed)
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# class DCProblemTestsN(unittest.TestCase):
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# def setUp(self):
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# aSpacing=2.5
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# nElecs=10
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# surveySize = nElecs*aSpacing - aSpacing
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# cs = surveySize/nElecs/4
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# mesh = Mesh.TensorMesh([
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# [(cs,10, -1.3),(cs,surveySize/cs),(cs,10, 1.3)],
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# [(cs,3, -1.3),(cs,3,1.3)],
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# # [(cs,5, -1.3),(cs,10)]
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# ],'CN')
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# srcList = DC.Utils.WennerSrcList(nElecs, aSpacing, in2D=True)
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# survey = DC.Survey(srcList)
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# problem = DC.Problem3D_N(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
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# problem.pair(survey)
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# mSynth = np.ones(mesh.nC)
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# survey.makeSyntheticData(mSynth)
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# # Now set up the problem to do some minimization
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# dmis = DataMisfit.l2_DataMisfit(survey)
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# reg = Regularization.Tikhonov(mesh)
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# opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
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# invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
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# inv = Inversion.BaseInversion(invProb)
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# self.inv = inv
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# self.reg = reg
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# self.p = problem
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# self.mesh = mesh
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# self.m0 = mSynth
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# self.survey = survey
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# self.dmis = dmis
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# def test_misfit(self):
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# derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
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# passed = Tests.checkDerivative(derChk, self.m0, plotIt=False)
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# self.assertTrue(passed)
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# def test_adjoint(self):
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# # Adjoint Test
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# u = np.random.rand(self.mesh.nC*self.survey.nSrc)
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# v = np.random.rand(self.mesh.nC)
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# w = np.random.rand(self.survey.dobs.shape[0])
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# wtJv = w.dot(self.p.Jvec(self.m0, v))
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# vtJtw = v.dot(self.p.Jtvec(self.m0, w))
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# passed = np.abs(wtJv - vtJtw) < 1e-8
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# print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
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# self.assertTrue(passed)
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# def test_dataObj(self):
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# derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
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# passed = Tests.checkDerivative(derChk, self.m0, plotIt=False)
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# self.assertTrue(passed)
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# def test_dataObj(self):
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# derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
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# passed = Tests.checkDerivative(derChk, self.m0, plotIt=False)
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# self.assertTrue(passed)
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if __name__ == '__main__':
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unittest.main()
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