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https://github.com/wassname/simpeg.git
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Merge branch 'master' of https://github.com/simpeg/simpegem into em/dev
Conflicts: .coveragerc .gitignore .travis.yml docs/api_Utils.rst docs/conf.py docs/index.rst requirements.txt setup.py
This commit is contained in:
Rowan Cockett
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from SimPEG import Survey, Problem, Utils, np, sp
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from simpegEM.Utils.EMUtils import omega
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class FieldsFDEM(Problem.Fields):
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"""Fancy Field Storage for a FDEM survey."""
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knownFields = {}
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dtype = complex
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class FieldsFDEM_e(FieldsFDEM):
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knownFields = {'eSolution':'E'}
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aliasFields = {
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'e' : ['eSolution','E','_e'],
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'ePrimary' : ['eSolution','E','_ePrimary'],
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'eSecondary' : ['eSolution','E','_eSecondary'],
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'b' : ['eSolution','F','_b'],
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'bPrimary' : ['eSolution','F','_bPrimary'],
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'bSecondary' : ['eSolution','F','_bSecondary']
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}
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def __init__(self,mesh,survey,**kwargs):
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FieldsFDEM.__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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self._edgeCurl = self.survey.prob.mesh.edgeCurl
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def _ePrimary(self, eSolution, srcList):
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ePrimary = np.zeros_like(eSolution)
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for i, src in enumerate(srcList):
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ep = src.ePrimary(self.prob)
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if ep is not None:
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ePrimary[:,i] = ep
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return ePrimary
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def _eSecondary(self, eSolution, srcList):
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return eSolution
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def _e(self, eSolution, srcList):
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return self._ePrimary(eSolution,srcList) + self._eSecondary(eSolution,srcList)
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def _eDeriv_u(self, src, v, adjoint = False):
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return None
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def _eDeriv_m(self, src, v, adjoint = False):
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# assuming primary does not depend on the model
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return None
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def _bPrimary(self, eSolution, srcList):
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bPrimary = np.zeros([self._edgeCurl.shape[0],eSolution.shape[1]],dtype = complex)
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for i, src in enumerate(srcList):
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bp = src.bPrimary(self.prob)
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if bp is not None:
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bPrimary[:,i] += bp
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return bPrimary
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def _bSecondary(self, eSolution, srcList):
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C = self._edgeCurl
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b = (C * eSolution)
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for i, src in enumerate(srcList):
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b[:,i] *= - 1./(1j*omega(src.freq))
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S_m, _ = src.eval(self.prob)
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if S_m is not None:
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b[:,i] += 1./(1j*omega(src.freq)) * S_m
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return b
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def _bSecondaryDeriv_u(self, src, v, adjoint = False):
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C = self._edgeCurl
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if adjoint:
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return - 1./(1j*omega(src.freq)) * (C.T * v)
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return - 1./(1j*omega(src.freq)) * (C * v)
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def _bSecondaryDeriv_m(self, src, v, adjoint = False):
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S_mDeriv, _ = src.evalDeriv(self.prob, adjoint)
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S_mDeriv = S_mDeriv(v)
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if S_mDeriv is not None:
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return 1./(1j * omega(src.freq)) * S_mDeriv
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return None
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def _b(self, eSolution, srcList):
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return self._bPrimary(eSolution, srcList) + self._bSecondary(eSolution, srcList)
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def _bDeriv_u(self, src, v, adjoint=False):
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# Primary does not depend on u
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return self._bSecondaryDeriv_u(src, v, adjoint)
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def _bDeriv_m(self, src, v, adjoint=False):
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# Assuming the primary does not depend on the model
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return self._bSecondaryDeriv_m(src, v, adjoint)
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class FieldsFDEM_b(FieldsFDEM):
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knownFields = {'bSolution':'F'}
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aliasFields = {
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'b' : ['bSolution','F','_b'],
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'bPrimary' : ['bSolution','F','_bPrimary'],
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'bSecondary' : ['bSolution','F','_bSecondary'],
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'e' : ['bSolution','E','_e'],
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'ePrimary' : ['bSolution','E','_ePrimary'],
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'eSecondary' : ['bSolution','E','_eSecondary'],
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}
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def __init__(self,mesh,survey,**kwargs):
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FieldsFDEM.__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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self._edgeCurl = self.survey.prob.mesh.edgeCurl
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self._MeSigmaI = self.survey.prob.MeSigmaI
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self._MfMui = self.survey.prob.MfMui
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self._MeSigmaIDeriv = self.survey.prob.MeSigmaIDeriv
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self._Me = self.survey.prob.Me
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def _bPrimary(self, bSolution, srcList):
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bPrimary = np.zeros_like(bSolution)
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for i, src in enumerate(srcList):
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bp = src.bPrimary(self.prob)
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if bp is not None:
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bPrimary[:,i] = bp
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return bPrimary
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def _bSecondary(self, bSolution, srcList):
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return bSolution
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def _b(self, bSolution, srcList):
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return self._bPrimary(bSolution, srcList) + self._bSecondary(bSolution, srcList)
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def _bDeriv_u(self, src, v, adjoint=False):
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return None
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def _bDeriv_m(self, src, v, adjoint=False):
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# assuming primary does not depend on the model
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return None
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def _ePrimary(self, bSolution, srcList):
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ePrimary = np.zeros([self._edgeCurl.shape[1],bSolution.shape[1]],dtype = complex)
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for i,src in enumerate(srcList):
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ep = src.ePrimary(self.prob)
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if ep is not None:
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ePrimary[:,i] = ep
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return ePrimary
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def _eSecondary(self, bSolution, srcList):
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e = self._MeSigmaI * ( self._edgeCurl.T * ( self._MfMui * bSolution))
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for i,src in enumerate(srcList):
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_,S_e = src.eval(self.prob)
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if S_e is not None:
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e[:,i] += -self._MeSigmaI * S_e
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return e
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def _eSecondaryDeriv_u(self, src, v, adjoint=False):
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if not adjoint:
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return self._MeSigmaI * ( self._edgeCurl.T * ( self._MfMui * v) )
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else:
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return self._MfMui.T * (self._edgeCurl * (self._MeSigmaI.T * v))
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def _eSecondaryDeriv_m(self, src, v, adjoint=False):
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bSolution = self[[src],'bSolution']
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_,S_e = src.eval(self.prob)
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Me = self._Me
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if adjoint:
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Me = Me.T
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w = self._edgeCurl.T * (self._MfMui * bSolution)
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if S_e is not None:
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w += -Utils.mkvc(Me * S_e,2)
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if not adjoint:
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de_dm = self._MeSigmaIDeriv(w) * v
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elif adjoint:
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de_dm = self._MeSigmaIDeriv(w).T * v
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_, S_eDeriv = src.evalDeriv(self.prob, adjoint)
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Se_Deriv = S_eDeriv(v)
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if Se_Deriv is not None:
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de_dm += -self._MeSigmaI * Se_Deriv
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return de_dm
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def _e(self, bSolution, srcList):
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return self._ePrimary(bSolution, srcList) + self._eSecondary(bSolution, srcList)
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def _eDeriv_u(self, src, v, adjoint=False):
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return self._eSecondaryDeriv_u(src, v, adjoint)
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def _eDeriv_m(self, src, v, adjoint=False):
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# assuming primary doesn't depend on model
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return self._eSecondaryDeriv_m(src, v, adjoint)
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class FieldsFDEM_j(FieldsFDEM):
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knownFields = {'jSolution':'F'}
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aliasFields = {
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'j' : ['jSolution','F','_j'],
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'jPrimary' : ['jSolution','F','_jPrimary'],
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'jSecondary' : ['jSolution','F','_jSecondary'],
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'h' : ['jSolution','E','_h'],
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'hPrimary' : ['jSolution','E','_hPrimary'],
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'hSecondary' : ['jSolution','E','_hSecondary'],
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}
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def __init__(self,mesh,survey,**kwargs):
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FieldsFDEM.__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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self._edgeCurl = self.survey.prob.mesh.edgeCurl
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self._MeMuI = self.survey.prob.MeMuI
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self._MfRho = self.survey.prob.MfRho
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self._MfRhoDeriv = self.survey.prob.MfRhoDeriv
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self._Me = self.survey.prob.Me
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def _jPrimary(self, jSolution, srcList):
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jPrimary = np.zeros_like(jSolution,dtype = complex)
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for i, src in enumerate(srcList):
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jp = src.jPrimary(self.prob)
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if jp is not None:
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jPrimary[:,i] += jp
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return jPrimary
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def _jSecondary(self, jSolution, srcList):
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return jSolution
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def _j(self, jSolution, srcList):
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return self._jPrimary(jSolution, srcList) + self._jSecondary(jSolution, srcList)
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def _jDeriv_u(self, src, v, adjoint=False):
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return None
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def _jDeriv_m(self, src, v, adjoint=False):
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# assuming primary does not depend on the model
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return None
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def _hPrimary(self, jSolution, srcList):
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hPrimary = np.zeros([self._edgeCurl.shape[1],jSolution.shape[1]],dtype = complex)
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for i, src in enumerate(srcList):
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hp = src.hPrimary(self.prob)
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if hp is not None:
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hPrimary[:,i] = hp
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return hPrimary
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def _hSecondary(self, jSolution, srcList):
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h = self._MeMuI * (self._edgeCurl.T * (self._MfRho * jSolution) )
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for i, src in enumerate(srcList):
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h[:,i] *= -1./(1j*omega(src.freq))
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S_m,_ = src.eval(self.prob)
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if S_m is not None:
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h[:,i] += 1./(1j*omega(src.freq)) * self._MeMuI * (S_m)
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return h
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def _hSecondaryDeriv_u(self, src, v, adjoint=False):
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if not adjoint:
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return -1./(1j*omega(src.freq)) * self._MeMuI * (self._edgeCurl.T * (self._MfRho * v) )
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elif adjoint:
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return -1./(1j*omega(src.freq)) * self._MfRho.T * (self._edgeCurl * ( self._MeMuI.T * v))
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def _hSecondaryDeriv_m(self, src, v, adjoint=False):
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jSolution = self[[src],'jSolution']
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MeMuI = self._MeMuI
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C = self._edgeCurl
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MfRho = self._MfRho
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MfRhoDeriv = self._MfRhoDeriv
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Me = self._Me
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if not adjoint:
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hDeriv_m = -1./(1j*omega(src.freq)) * MeMuI * (C.T * (MfRhoDeriv(jSolution)*v ) )
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elif adjoint:
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hDeriv_m = -1./(1j*omega(src.freq)) * MfRhoDeriv(jSolution).T * ( C * (MeMuI.T * v ) )
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S_mDeriv,_ = src.evalDeriv(self.prob, adjoint)
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if not adjoint:
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S_mDeriv = S_mDeriv(v)
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if S_mDeriv is not None:
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hDeriv_m += 1./(1j*omega(src.freq)) * MeMuI * (Me * S_mDeriv)
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elif adjoint:
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S_mDeriv = S_mDeriv(Me.T * (MeMuI.T * v))
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if S_mDeriv is not None:
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hDeriv_m += 1./(1j*omega(src.freq)) * S_mDeriv
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return hDeriv_m
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def _h(self, jSolution, srcList):
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return self._hPrimary(jSolution, srcList) + self._hSecondary(jSolution, srcList)
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def _hDeriv_u(self, src, v, adjoint=False):
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return self._hSecondaryDeriv_u(src, v, adjoint)
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def _hDeriv_m(self, src, v, adjoint=False):
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# assuming the primary doesn't depend on the model
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return self._hSecondaryDeriv_m(src, v, adjoint)
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class FieldsFDEM_h(FieldsFDEM):
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knownFields = {'hSolution':'E'}
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aliasFields = {
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'h' : ['hSolution','E','_h'],
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'hPrimary' : ['hSolution','E','_hPrimary'],
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'hSecondary' : ['hSolution','E','_hSecondary'],
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'j' : ['hSolution','F','_j'],
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'jPrimary' : ['hSolution','F','_jPrimary'],
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'jSecondary' : ['hSolution','F','_jSecondary']
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}
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def __init__(self,mesh,survey,**kwargs):
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FieldsFDEM.__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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self._edgeCurl = self.survey.prob.mesh.edgeCurl
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self._MeMuI = self.survey.prob.MeMuI
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self._MfRho = self.survey.prob.MfRho
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def _hPrimary(self, hSolution, srcList):
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hPrimary = np.zeros_like(hSolution,dtype = complex)
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for i, src in enumerate(srcList):
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hp = src.hPrimary(self.prob)
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if hp is not None:
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hPrimary[:,i] += hp
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return hPrimary
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def _hSecondary(self, hSolution, srcList):
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return hSolution
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def _h(self, hSolution, srcList):
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return self._hPrimary(hSolution, srcList) + self._hSecondary(hSolution, srcList)
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def _hDeriv_u(self, src, v, adjoint=False):
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return None
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def _hDeriv_m(self, src, v, adjoint=False):
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# assuming primary does not depend on the model
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return None
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def _jPrimary(self, hSolution, srcList):
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jPrimary = np.zeros([self._edgeCurl.shape[0], hSolution.shape[1]], dtype = complex)
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for i, src in enumerate(srcList):
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jp = src.jPrimary(self.prob)
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if jp is not None:
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jPrimary[:,i] = jp
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return jPrimary
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def _jSecondary(self, hSolution, srcList):
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j = self._edgeCurl*hSolution
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for i, src in enumerate(srcList):
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_,S_e = src.eval(self.prob)
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if S_e is not None:
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j[:,i] += -S_e
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return j
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def _jSecondaryDeriv_u(self, src, v, adjoint=False):
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if not adjoint:
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return self._edgeCurl*v
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elif adjoint:
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return self._edgeCurl.T*v
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def _jSecondaryDeriv_m(self, src, v, adjoint=False):
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_,S_eDeriv = src.evalDeriv(self.prob, adjoint)
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S_eDeriv = S_eDeriv(v)
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if S_eDeriv is not None:
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return -S_eDeriv
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return None
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def _j(self, hSolution, srcList):
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return self._jPrimary(hSolution, srcList) + self._jSecondary(hSolution, srcList)
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def _jDeriv_u(self, src, v, adjoint=False):
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return self._jSecondaryDeriv_u(src,v,adjoint)
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def _jDeriv_m(self, src, v, adjoint=False):
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# assuming the primary does not depend on the model
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return self._jSecondaryDeriv_m(src,v,adjoint)
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