from SimPEG import Problem, Utils, Maps, Mesh from SimPEG.EM.Base import BaseEMProblem from SimPEG.EM.Static.DC.FieldsDC import Fields, Fields_CC, Fields_N from SimPEG.Utils import sdiag import numpy as np from SimPEG.Utils import Zero from SimPEG.EM.Static.DC import getxBCyBC_CC from SurveyIP import Survey class IPPropMap(Maps.PropMap): """ Property Map for IP Problems. The electrical chargeability, (\\(\\eta\\)) is the default inversion property """ eta = Maps.Property("Electrical Chargeability", defaultInvProp = True) class BaseIPProblem(BaseEMProblem): surveyPair = Survey fieldsPair = Fields PropMap = IPPropMap Ainv = None sigma = None rho = None f = None Ainv = None def fields(self, m): self.curModel = m if self.f is None: self.f = self.fieldsPair(self.mesh, self.survey) if self.Ainv == None: A = self.getA() self.Ainv = self.Solver(A, **self.solverOpts) RHS = self.getRHS() u = self.Ainv * RHS Srcs = self.survey.srcList self.f[Srcs, self._solutionType] = u return self.f def Jvec(self, m, v, f=None): if f is None: f = self.fields(m) self.curModel = m Jv = self.dataPair(self.survey) #same size as the data A = self.getA() for src in self.survey.srcList: u_src = f[src, self._solutionType] # solution vector dA_dm_v = self.getADeriv(u_src, v) dRHS_dm_v = self.getRHSDeriv(src, v) du_dm_v = self.Ainv * ( - dA_dm_v + dRHS_dm_v ) for rx in src.rxList: df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None) df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False) Jv[src, rx] = rx.evalDeriv(src, self.mesh, f, df_dm_v) # Conductivity (d u / d log sigma) if self._formulation is 'EB': return -Utils.mkvc(Jv) # Conductivity (d u / d log rho) if self._formulation is 'HJ': return Utils.mkvc(Jv) def Jtvec(self, m, v, f=None): if f is None: f = self.fields(m) self.curModel = m # Ensure v is a data object. if not isinstance(v, self.dataPair): v = self.dataPair(self.survey, v) Jtv = np.zeros(m.size) AT = self.getA() for src in self.survey.srcList: u_src = f[src, self._solutionType] for rx in src.rxList: PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx], adjoint=True) # wrt f, need possibility wrt m df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None) df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True) ATinvdf_duT = self.Ainv * df_duT dA_dmT = self.getADeriv(u_src, ATinvdf_duT, adjoint=True) dRHS_dmT = self.getRHSDeriv(src, ATinvdf_duT, adjoint=True) du_dmT = -dA_dmT + dRHS_dmT Jtv += (df_dmT + du_dmT).astype(float) # Conductivity ((d u / d log sigma).T) if self._formulation is 'EB': return -Utils.mkvc(Jtv) # Conductivity ((d u / d log rho).T) if self._formulation is 'HJ': return Utils.mkvc(Jtv) def getSourceTerm(self): """ takes concept of source and turns it into a matrix """ """ Evaluates the sources, and puts them in matrix form :rtype: (numpy.ndarray, numpy.ndarray) :return: q (nC or nN, nSrc) """ Srcs = self.survey.srcList if self._formulation is 'EB': n = self.mesh.nN # return NotImplementedError elif self._formulation is 'HJ': n = self.mesh.nC q = np.zeros((n, len(Srcs))) for i, src in enumerate(Srcs): q[:,i] = src.eval(self) return q @property def deleteTheseOnModelUpdate(self): toDelete = [] return toDelete # assume log rho or log cond @property def MeSigma(self): """ Edge inner product matrix for \\(\\sigma\\). Used in the E-B formulation """ if getattr(self, '_MeSigma', None) is None: self._MeSigma = self.mesh.getEdgeInnerProduct(self.sigma) return self._MeSigma @property def MfRhoI(self): """ Inverse of :code:`MfRho` """ if getattr(self, '_MfRhoI', None) is None: self._MfRhoI = self.mesh.getFaceInnerProduct(self.rho, invMat=True) return self._MfRhoI def MfRhoIDeriv(self,u): """ Derivative of :code:`MfRhoI` with respect to the model. """ dMfRhoI_dI = -self.MfRhoI**2 dMf_drho = self.mesh.getFaceInnerProductDeriv(self.rho)(u) drho_dlogrho = Utils.sdiag(self.rho)*self.curModel.etaDeriv return dMfRhoI_dI * ( dMf_drho * ( drho_dlogrho)) # TODO: This should take a vector def MeSigmaDeriv(self, u): """ Derivative of MeSigma with respect to the model """ dsigma_dlogsigma = Utils.sdiag(self.sigma)*self.curModel.etaDeriv return self.mesh.getEdgeInnerProductDeriv(self.sigma)(u) * dsigma_dlogsigma class Problem3D_CC(BaseIPProblem): _solutionType = 'phiSolution' _formulation = 'HJ' # CC potentials means J is on faces fieldsPair = Fields_CC def __init__(self, mesh, **kwargs): BaseIPProblem.__init__(self, mesh, **kwargs) self.setBC() def getA(self): """ Make the A matrix for the cell centered DC resistivity problem A = D MfRhoI G """ D = self.Div G = self.Grad MfRhoI = self.MfRhoI A = D * MfRhoI * G # I think we should deprecate this for DC problem. # if self._makeASymmetric is True: # return V.T * A return A def getADeriv(self, u, v, adjoint= False): D = self.Div G = self.Grad MfRhoIDeriv = self.MfRhoIDeriv if adjoint: # if self._makeASymmetric is True: # v = V * v return(MfRhoIDeriv( G * u ).T) * ( D.T * v) # I think we should deprecate this for DC problem. # if self._makeASymmetric is True: # return V.T * ( D * ( MfRhoIDeriv( D.T * ( V * u ) ) * v ) ) return D * (MfRhoIDeriv( G * u ) * v) def getRHS(self): """ RHS for the DC problem q """ RHS = self.getSourceTerm() # I think we should deprecate this for DC problem. # if self._makeASymmetric is True: # return self.Vol.T * RHS return RHS def getRHSDeriv(self, src, v, adjoint=False): """ Derivative of the right hand side with respect to the model """ # TODO: add qDeriv for RHS depending on m # qDeriv = src.evalDeriv(self, adjoint=adjoint) # return qDeriv return Zero() def setBC(self): if self.mesh.dim==3: fxm,fxp,fym,fyp,fzm,fzp = self.mesh.faceBoundaryInd gBFxm = self.mesh.gridFx[fxm,:] gBFxp = self.mesh.gridFx[fxp,:] gBFym = self.mesh.gridFy[fym,:] gBFyp = self.mesh.gridFy[fyp,:] gBFzm = self.mesh.gridFz[fzm,:] gBFzp = self.mesh.gridFz[fzp,:] # Setup Mixed B.C (alpha, beta, gamma) temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0]) temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1]) temp_zm, temp_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2]) alpha_xm, alpha_xp = temp_xm*0., temp_xp*0. alpha_ym, alpha_yp = temp_ym*0., temp_yp*0. alpha_zm, alpha_zp = temp_zm*0., temp_zp*0. beta_xm, beta_xp = temp_xm, temp_xp beta_ym, beta_yp = temp_ym, temp_yp beta_zm, beta_zp = temp_zm, temp_zp gamma_xm, gamma_xp = temp_xm*0., temp_xp*0. gamma_ym, gamma_yp = temp_ym*0., temp_yp*0. gamma_zm, gamma_zp = temp_zm*0., temp_zp*0. alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp, alpha_zm, alpha_zp] beta = [beta_xm, beta_xp, beta_ym, beta_yp, beta_zm, beta_zp] gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp, gamma_zm, gamma_zp] elif self.mesh.dim==2: fxm,fxp,fym,fyp = self.mesh.faceBoundaryInd gBFxm = self.mesh.gridFx[fxm,:] gBFxp = self.mesh.gridFx[fxp,:] gBFym = self.mesh.gridFy[fym,:] gBFyp = self.mesh.gridFy[fyp,:] # Setup Mixed B.C (alpha, beta, gamma) temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0]) temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1]) alpha_xm, alpha_xp = temp_xm*0., temp_xp*0. alpha_ym, alpha_yp = temp_ym*0., temp_yp*0. beta_xm, beta_xp = temp_xm, temp_xp beta_ym, beta_yp = temp_ym, temp_yp gamma_xm, gamma_xp = temp_xm*0., temp_xp*0. gamma_ym, gamma_yp = temp_ym*0., temp_yp*0. alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp] beta = [beta_xm, beta_xp, beta_ym, beta_yp] gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp] x_BC, y_BC = getxBCyBC_CC(self.mesh, alpha, beta, gamma) V = self.Vol self.Div = V * self.mesh.faceDiv P_BC, B = self.mesh.getBCProjWF_simple() M = B*self.mesh.aveCC2F self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M class Problem3D_N(BaseIPProblem): _solutionType = 'phiSolution' _formulation = 'EB' # N potentials means B is on faces fieldsPair = Fields_N def __init__(self, mesh, **kwargs): BaseIPProblem.__init__(self, mesh, **kwargs) def getA(self): """ Make the A matrix for the cell centered DC resistivity problem A = G.T MeSigma G """ MeSigma = self.MeSigma Grad = self.mesh.nodalGrad A = Grad.T * MeSigma * Grad # Handling Null space of A A[0,0] = A[0,0] + 1. return A def getADeriv(self, u, v, adjoint=False): """ Product of the derivative of our system matrix with respect to the model and a vector """ MeSigma = self.MeSigma Grad = self.mesh.nodalGrad if not adjoint: return Grad.T*(self.MeSigmaDeriv(Grad*u)*v) elif adjoint: return self.MeSigmaDeriv(Grad*u).T * (Grad*v) def getRHS(self): """ RHS for the DC problem q """ RHS = self.getSourceTerm() return RHS def getRHSDeriv(self, src, v, adjoint=False): """ Derivative of the right hand side with respect to the model """ # TODO: add qDeriv for RHS depending on m # qDeriv = src.evalDeriv(self, adjoint=adjoint) # return qDeriv return Zero() if __name__ == '__main__': cs = 12.5 hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)] hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)] hz = [(cs,7, -1.3),(cs,20)] mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN") sigma = np.ones(mesh.nC) prob = BaseIPProblem(mesh, sigma=sigma)