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https://github.com/wassname/simpeg.git
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GudniRos
135 lines
4.6 KiB
Python
135 lines
4.6 KiB
Python
from SimPEG import Survey, Utils, Problem, np, sp, mkvc
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from scipy.constants import mu_0
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import sys
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from numpy.lib import recfunctions as recFunc
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from simpegEM.Utils.EMUtils import omega
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##############
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### Fields ###
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##############
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class FieldsMT(Problem.Fields):
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"""Field Storage for a MT survey."""
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knownFields = {}
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dtype = complex
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class FieldsMT_1D(FieldsMT):
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"""
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Fields storage for the 1D MT solution.
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"""
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knownFields = {'e_1dSolution':'F'}
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aliasFields = {
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'e_1d' : ['e_1dSolution','F','_e'],
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'e_1dPrimary' : ['e_1dSolution','F','_ePrimary'],
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'e_1dSecondary' : ['e_1dSolution','F','_eSecondary'],
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'b_1d' : ['e_1dSolution','E','_b'],
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'b_1dPrimary' : ['e_1dSolution','E','_bPrimary'],
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'b_1dSecondary' : ['e_1dSolution','E','_bSecondary']
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}
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def __init__(self,mesh,survey,**kwargs):
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FieldsMT.__init__(self,mesh,survey,**kwargs)
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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.survey.prob)
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if ep is not None:
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ePrimary[:,i] = ep[:,-1]
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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.survey.mesh.nE,eSolution.shape[1]], dtype = complex)
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for i, src in enumerate(srcList):
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bp = src.bPrimary(self.survey.prob)
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if bp is not None:
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bPrimary[:,i] += bp[:,-1]
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return bPrimary
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def _bSecondary(self, eSolution, srcList):
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C = self.mesh.nodalGrad
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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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# There is no magnetic source in the MT problem
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# S_m, _ = src.eval(self.survey.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 _b(self, eSolution, srcList):
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return self._bPrimary(eSolution, srcList) + self._bSecondary(eSolution, srcList)
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def _bSecondaryDeriv_u(self, src, v, adjoint = False):
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C = self.mesh.nodalGrad
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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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# Doesn't depend on m
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# _, S_eDeriv = src.evalDeriv(self.survey.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 1./(1j * omega(src.freq)) * S_eDeriv
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return None
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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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def _fDeriv_u(self, src, v, adjoint=False):
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"""
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Derivative of the fields object wrt u.
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:param MTsrc src: MT source
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:param numpy.ndarray v: random vector of f_sol.size
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This function stacks the fields derivatives appropriately
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return a vector of size (nreEle+nrbEle)
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"""
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de_du = v #Utils.spdiag(np.ones((self.nF,)))
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db_du = self._bDeriv_u(src, v, adjoint)
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# Return the stack
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# This doesn't work...
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return np.vstack((de_du,db_du))
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def _fDeriv_m(self, src, v, adjoint=False):
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"""
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Derivative of the fields object wrt m.
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This function stacks the fields derivatives appropriately
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"""
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return None
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class FieldsMT_3D(FieldsMT):
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"""
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Fields storage for the 3D MT solution.
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"""
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knownFields = {'e_px':'E','e_py':'E','b_px':'F','b_py':'F'}
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aliasFields = { }
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# 'e_1d' : ['e_1dSolution','F','_e'],
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# 'e_1dPrimary' : ['e_1dSolution','F','_ePrimary'],
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# 'e_1dSecondary' : ['e_1dSolution','F','_eSecondary'],
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# 'b_1d' : ['e_1dSolution','E','_b'],
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# 'b_1dPrimary' : ['e_1dSolution','E','_bPrimary'],
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# 'b_1dSecondary' : ['e_1dSolution','E','_bSecondary']
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# } |