mirror of
https://github.com/wassname/simpeg.git
synced 2026-07-05 22:37:14 +08:00
Working Spectral IP:
- Fwd - Jvec - Jtvec
This commit is contained in:
seogi_macbook
@@ -5,7 +5,7 @@ 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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from SimPEG.EM.Static.DC import getxBCyBC_CC
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from SurveySIP import Survey
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from SurveySIP import Survey, Data
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class ColeColePropMap(Maps.PropMap):
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"""
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@@ -22,6 +22,7 @@ class BaseSIPProblem(BaseEMProblem):
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surveyPair = Survey
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fieldsPair = Fields
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dataPair = Data
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PropMap = ColeColePropMap
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Ainv = None
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sigma = None
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@@ -29,15 +30,17 @@ class BaseSIPProblem(BaseEMProblem):
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f = None
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Ainv = None
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def DebyeTime(t):
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def DebyeTime(self, t):
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peta = self.curModel.eta*np.exp(-self.curModel.taui*t)
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return peta
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def EtaDeriv(t):
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return np.exp(-self.curModel.taui*t)
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def EtaDeriv(self, t, v):
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v = np.array(v, dtype=float)
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return np.exp(-self.curModel.taui*t) * (self.curModel.etaDeriv*v)
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def TauiDeriv(t):
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return -self.curModel.eta*t*np.exp(-self.curModel.taui*t)
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def TauiDeriv(self, t, v):
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v = np.array(v, dtype=float)
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return -self.curModel.eta*t*np.exp(-self.curModel.taui*t) * (self.curModel.tauiDeriv*v)
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def fields(self, m):
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self.curModel = m
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@@ -63,7 +66,8 @@ class BaseSIPProblem(BaseEMProblem):
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JvAll = []
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for tind in range(len(self.survey.times)):
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#Pseudo-chareability
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v = DebyeTime(self.survey.times[tind])
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t = self.survey.times[tind]
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v = self.DebyeTime(t)
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for src in self.survey.srcList:
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u_src = f[src, self._solutionType] # solution vector
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dA_dm_v = self.getADeriv(u_src, v)
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@@ -74,76 +78,88 @@ class BaseSIPProblem(BaseEMProblem):
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if timeindex[tind]:
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df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
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df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False)
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Jv[src, rx] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
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JvAll.append(Utils.mkvc(Jv))
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Jv[src, rx, t] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
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# Conductivity (d u / d log sigma)
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if self._formulation is 'EB':
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return -np.hstack(JvAll)
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# Conductivity (d u / d log rho)
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return -Utils.mkvc(Jv)
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# Resistivity (d u / d log rho)
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if self._formulation is 'HJ':
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return np.hstack(JvAll)
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return Utils.mkvc(Jv)
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# def Jvec(self, m, v, f=None):
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def Jvec(self, m, v, f=None):
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# if f is None:
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# f = self.fields(m)
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if f is None:
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f = self.fields(m)
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# self.curModel = m
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self.curModel = m
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Jv = self.dataPair(self.survey) #same size as the data
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# A = self.getA()
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JvAll = []
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#Assume only eta and tau (eta first then tau)
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# v = [2*Mx1]
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v = v.reshape((int(v.size/2), 2), order='F')
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# Jv = self.dataPair(self.survey) #same size as the data
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# x1 =
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# x2 =
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# # A = self.getA()
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# for src in self.survey.srcList:
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# u_src = f[src, self._solutionType] # solution vector
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for tind in range(len(self.survey.times)):
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t = self.survey.times[tind]
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v0 = self.EtaDeriv(t, v[:,0])
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v1 = self.TauiDeriv(t, v[:,1])
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for src in self.survey.srcList:
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u_src = f[src, self._solutionType] # solution vector
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dA_dm_v0 = self.getADeriv(u_src, v0)
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dRHS_dm_v0 = self.getRHSDeriv(src, v0)
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du_dm_v0 = self.Ainv * ( - dA_dm_v0 + dRHS_dm_v0 )
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dA_dm_v1 = self.getADeriv(u_src, v1)
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dRHS_dm_v1 = self.getRHSDeriv(src, v1)
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du_dm_v1 = self.Ainv * ( - dA_dm_v1 + dRHS_dm_v1 )
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for rx in src.rxList:
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timeindex = rx.getTimeP(self.survey.times)
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if timeindex[tind]:
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df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
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df_dm_v0 = df_dmFun(src, du_dm_v0, v0, adjoint=False)
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df_dm_v1 = df_dmFun(src, du_dm_v1, v1, adjoint=False)
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Jv[src, rx, t] = rx.evalDeriv(src, self.mesh, f, df_dm_v0)
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Jv[src, rx, t] += rx.evalDeriv(src, self.mesh, f, df_dm_v1)
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# Conductivity (d u / d log sigma)
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if self._formulation is 'EB':
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return -Jv.tovec()
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# Resistivity (d u / d log rho)
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if self._formulation is 'HJ':
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return Jv.tovec()
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# dA_dm_v = self.getADeriv(u_src, v)
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# dRHS_dm_v = self.getRHSDeriv(src, v)
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# du_dm_v = self.Ainv * ( - dA_dm_v + dRHS_dm_v )
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def Jtvec(self, m, v, f=None):
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if f is None:
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f = self.fields(m)
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# for rx in src.rxList:
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self.curModel = m
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# for tind in range(len(self.survey.times)):
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# df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
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# df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False)
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# Jv[src, rx] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
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# # Conductivity (d u / d log sigma)
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# if self._formulation is 'EB':
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# return -Utils.mkvc(Jv)
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# # Conductivity (d u / d log rho)
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# if self._formulation is 'HJ':
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# return Utils.mkvc(Jv)
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# Ensure v is a data object.
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if not isinstance(v, self.dataPair):
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v = self.dataPair(self.survey, v)
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# def Jtvec(self, m, v, f=None):
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# if f is None:
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# f = self.fields(m)
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Jtv= np.zeros(m.size)
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for tind in range(len(self.survey.times)):
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t = self.survey.times[tind]
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for src in self.survey.srcList:
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u_src = f[src, self._solutionType]
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for rx in src.rxList:
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timeindex = rx.getTimeP(self.survey.times)
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if timeindex[tind]:
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PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx, t], adjoint=True) # wrt f, need possibility wrt m
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df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
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df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
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ATinvdf_duT = self.Ainv * df_duT
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dA_dmT = self.getADeriv(u_src, ATinvdf_duT, adjoint=True)
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dRHS_dmT = self.getRHSDeriv(src, ATinvdf_duT, adjoint=True)
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du_dmT = -dA_dmT + dRHS_dmT
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Jtv += np.r_[self.EtaDeriv(self.survey.times[tind], du_dmT), self.TauiDeriv(self.survey.times[tind], du_dmT)]
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# self.curModel = m
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# # Ensure v is a data object.
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# if not isinstance(v, self.dataPair):
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# v = self.dataPair(self.survey, v)
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# Jtv = np.zeros(m.size)
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# # AT = self.getA()
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# for src in self.survey.srcList:
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# u_src = f[src, self._solutionType]
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# for rx in src.rxList:
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# PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx], adjoint=True) # wrt f, need possibility wrt m
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# df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
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# df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
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# ATinvdf_duT = self.Ainv * df_duT
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# dA_dmT = self.getADeriv(u_src, ATinvdf_duT, adjoint=True)
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# dRHS_dmT = self.getRHSDeriv(src, ATinvdf_duT, adjoint=True)
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# du_dmT = -dA_dmT + dRHS_dmT
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# Jtv += df_dmT + du_dmT
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# # Conductivity ((d u / d log sigma).T)
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# if self._formulation is 'EB':
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# return -Utils.mkvc(Jtv)
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# # Conductivity ((d u / d log rho).T)
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# if self._formulation is 'HJ':
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# return Utils.mkvc(Jtv)
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# Conductivity ((d u / d log sigma).T)
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if self._formulation is 'EB':
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return -Jtv
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# Conductivity ((d u / d log rho).T)
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if self._formulation is 'HJ':
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return Jtv
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def getSourceTerm(self):
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"""
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@@ -62,7 +62,13 @@ class Dipole(BaseRx):
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@property
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def nD(self):
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"""Number of data in the receiver."""
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return self.locs[0].shape[0] * len(self.times)
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# return self.locs[0].shape[0] * len(self.times)
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return self.locs[0].shape[0]
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@property
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def nRx(self):
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"""Number of data in the receiver."""
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return self.locs[0].shape[0]
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# Not sure why ...
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# return int(self.locs[0].size / 2)
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@@ -0,0 +1,64 @@
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import SimPEG
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# from SimPEG.EM.Base import BaseEMSurvey
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from SimPEG.Utils import Zero, closestPoints, mkvc
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import numpy as np
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class BaseSrc(SimPEG.Survey.BaseSrc):
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current = 1.0
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loc = None
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def __init__(self, rxList, **kwargs):
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SimPEG.Survey.BaseSrc.__init__(self, rxList, **kwargs)
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def eval(self, prob):
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raise NotImplementedError
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def evalDeriv(self, prob):
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return Zero()
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@property
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def nD(self):
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"""Number of data"""
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return self.vnD.sum()
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@property
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def vnD(self):
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"""Vector number of data"""
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return np.array([rx.nD*len(rx.times) for rx in self.rxList])
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class Dipole(BaseSrc):
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def __init__(self, rxList, locA, locB, **kwargs):
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assert locA.shape == locB.shape, 'Shape of locA and locB should be the same'
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self.loc = [locA, locB]
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BaseSrc.__init__(self, rxList, **kwargs)
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def eval(self, prob):
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if prob._formulation == 'HJ':
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inds = closestPoints(prob.mesh, self.loc, gridLoc='CC')
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q = np.zeros(prob.mesh.nC)
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q[inds] = self.current * np.r_[1., -1.]
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elif prob._formulation == 'EB':
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qa = prob.mesh.getInterpolationMat(self.loc[0], locType='N').todense()
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qb = -prob.mesh.getInterpolationMat(self.loc[1], locType='N').todense()
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q = self.current * mkvc(qa+qb)
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return q
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class Pole(BaseSrc):
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def __init__(self, rxList, loc, **kwargs):
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BaseSrc.__init__(self, rxList, loc=loc, **kwargs)
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def eval(self, prob):
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if prob._formulation == 'HJ':
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inds = closestPoints(prob.mesh, self.loc)
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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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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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@@ -1,9 +1,11 @@
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import SimPEG
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from SimPEG.EM.Base import BaseEMSurvey
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from SimPEG import np, sp, Survey
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from SimPEG import np, sp, Survey, Utils
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from SimPEG.Utils import Zero, Identity
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from SimPEG.EM.Static.DC.SrcDC import BaseSrc
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from SimPEG.EM.Static.SIP.SrcSIP import BaseSrc
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from SimPEG.EM.Static.SIP.RxSIP import BaseRx
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import uuid
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class Survey(BaseEMSurvey):
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rxPair = BaseRx
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@@ -29,4 +31,72 @@ class Survey(BaseEMSurvey):
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.. math::
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d_\\text{pred} = Pf(m)
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"""
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return self.prob.Jvec(m, m, f=f)
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return self.prob.forward(m, f=f)
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class Data(SimPEG.Survey.Data):
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"""Fancy data storage by Src and Rx"""
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def __init__(self, survey, v=None):
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self.uid = str(uuid.uuid4())
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self.survey = survey
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self._dataDict = {}
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for src in self.survey.srcList:
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self._dataDict[src] = {}
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for rx in src.rxList:
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self._dataDict[src][rx] = {}
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if v is not None:
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self.fromvec(v)
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def _ensureCorrectKey(self, key):
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if type(key) is tuple:
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if len(key) is not 3:
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raise KeyError('Key must be [Src, Rx, tInd]')
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if key[0] not in self.survey.srcList:
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raise KeyError('Src Key must be a source in the survey.')
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if key[1] not in key[0].rxList:
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raise KeyError('Rx Key must be a receiver for the source.')
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return key
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elif isinstance(key, self.survey.srcPair):
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if key not in self.survey.srcList:
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raise KeyError('Key must be a source in the survey.')
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return key, None, None
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else:
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raise KeyError('Key must be [Src] or [Src,Rx] or [Src, Rx, tInd]')
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def __setitem__(self, key, value):
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src, rx, t = self._ensureCorrectKey(key)
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assert rx is not None, 'set data using [Src, Rx]'
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assert isinstance(value, np.ndarray), 'value must by ndarray'
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assert value.size == rx.nD, "value must have the same number of data as the source."
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self._dataDict[src][rx][t] = Utils.mkvc(value)
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def __getitem__(self, key):
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src, rx, t = self._ensureCorrectKey(key)
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if rx is not None:
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if rx not in self._dataDict[src]:
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raise Exception('Data for receiver has not yet been set.')
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return self._dataDict[src][rx][t]
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return np.concatenate([self[src,rx, t] for rx in src.rxList])
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def tovec(self):
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val = []
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for src in self.survey.srcList:
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for rx in src.rxList:
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for t in rx.times:
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val.append(self[src, rx, t])
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return np.concatenate(val)
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def fromvec(self, v):
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v = Utils.mkvc(v)
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assert v.size == self.survey.nD, 'v must have the correct number of data.'
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indBot, indTop = 0, 0
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for src in self.survey.srcList:
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for rx in src.rxList:
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for t in rx.times:
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indTop += rx.nRx
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self[src, rx, t] = v[indBot:indTop]
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indBot += rx.nRx
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@@ -1,2 +1,4 @@
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from ProblemSIP import Problem3D_CC, Problem3D_N
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from SurveySIP import Survey
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from SurveySIP import Survey, Data
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import SrcSIP as Src #Pole
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import RxSIP as Rx
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@@ -0,0 +1,154 @@
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import unittest
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from SimPEG import *
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import SimPEG
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from SimPEG import Mesh, Utils, EM, Maps, np, Survey
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from SimPEG.EM.Static import SIP, DC, IP
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from pymatsolver import MumpsSolver
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class IPProblemTestsCC(unittest.TestCase):
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def setUp(self):
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cs = 25.
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hx = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
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hy = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
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hz = [(cs,0, -1.3),(cs,20)]
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mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN")
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blkind0 = Utils.ModelBuilder.getIndicesSphere(np.r_[-100., -100., -200.], 75., mesh.gridCC)
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blkind1 = Utils.ModelBuilder.getIndicesSphere(np.r_[100., 100., -200.], 75., mesh.gridCC)
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sigma = np.ones(mesh.nC)*1e-2
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eta = np.zeros(mesh.nC)
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tau = np.ones_like(sigma)*1.
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eta[blkind0] = 0.1
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eta[blkind1] = 0.1
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tau[blkind0] = 0.1
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tau[blkind1] = 0.01
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x = mesh.vectorCCx[(mesh.vectorCCx>-155.)&(mesh.vectorCCx<155.)]
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y = mesh.vectorCCx[(mesh.vectorCCy>-155.)&(mesh.vectorCCy<155.)]
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Aloc = np.r_[-200., 0., 0.]
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Bloc = np.r_[200., 0., 0.]
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M = Utils.ndgrid(x-25.,y, np.r_[0.])
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N = Utils.ndgrid(x+25.,y, np.r_[0.])
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|
||||
times = np.arange(10)*1e-3 + 1e-3
|
||||
rx = SIP.Rx.Dipole(M, N, times)
|
||||
src = SIP.Src.Dipole([rx], Aloc, Bloc)
|
||||
survey = SIP.Survey([src])
|
||||
colemap = [("eta", Maps.IdentityMap(mesh)), ("taui", Maps.IdentityMap(mesh))]
|
||||
problem = SIP.Problem3D_CC(mesh, rho=1./sigma, mapping=colemap)
|
||||
problem.Solver = MumpsSolver
|
||||
problem.pair(survey)
|
||||
mSynth = np.r_[eta, 1./tau]
|
||||
survey.makeSyntheticData(mSynth)
|
||||
# Now set up the problem to do some minimization
|
||||
dmis = DataMisfit.l2_DataMisfit(survey)
|
||||
reg = Regularization.Tikhonov(mesh)
|
||||
opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
|
||||
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
|
||||
inv = Inversion.BaseInversion(invProb)
|
||||
|
||||
self.inv = inv
|
||||
self.reg = reg
|
||||
self.p = problem
|
||||
self.mesh = mesh
|
||||
self.m0 = mSynth
|
||||
self.survey = survey
|
||||
self.dmis = dmis
|
||||
|
||||
def test_misfit(self):
|
||||
derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
|
||||
passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
|
||||
self.assertTrue(passed)
|
||||
|
||||
def test_adjoint(self):
|
||||
# Adjoint Test
|
||||
u = np.random.rand(self.mesh.nC*self.survey.nSrc)
|
||||
v = np.random.rand(self.mesh.nC*2)
|
||||
w = np.random.rand(self.survey.dobs.shape[0])
|
||||
wtJv = w.dot(self.p.Jvec(self.m0, v))
|
||||
vtJtw = v.dot(self.p.Jtvec(self.m0, w))
|
||||
passed = np.abs(wtJv - vtJtw) < 1e-10
|
||||
print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
|
||||
self.assertTrue(passed)
|
||||
|
||||
def test_dataObj(self):
|
||||
derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
|
||||
passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
|
||||
self.assertTrue(passed)
|
||||
|
||||
class IPProblemTestsN(unittest.TestCase):
|
||||
|
||||
def setUp(self):
|
||||
|
||||
cs = 25.
|
||||
hx = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
|
||||
hy = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
|
||||
hz = [(cs,0, -1.3),(cs,20)]
|
||||
mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN")
|
||||
blkind0 = Utils.ModelBuilder.getIndicesSphere(np.r_[-100., -100., -200.], 75., mesh.gridCC)
|
||||
blkind1 = Utils.ModelBuilder.getIndicesSphere(np.r_[100., 100., -200.], 75., mesh.gridCC)
|
||||
sigma = np.ones(mesh.nC)*1e-2
|
||||
eta = np.zeros(mesh.nC)
|
||||
tau = np.ones_like(sigma)*1.
|
||||
eta[blkind0] = 0.1
|
||||
eta[blkind1] = 0.1
|
||||
tau[blkind0] = 0.1
|
||||
tau[blkind1] = 0.01
|
||||
|
||||
x = mesh.vectorCCx[(mesh.vectorCCx>-155.)&(mesh.vectorCCx<155.)]
|
||||
y = mesh.vectorCCx[(mesh.vectorCCy>-155.)&(mesh.vectorCCy<155.)]
|
||||
Aloc = np.r_[-200., 0., 0.]
|
||||
Bloc = np.r_[200., 0., 0.]
|
||||
M = Utils.ndgrid(x-25.,y, np.r_[0.])
|
||||
N = Utils.ndgrid(x+25.,y, np.r_[0.])
|
||||
|
||||
times = np.arange(10)*1e-3 + 1e-3
|
||||
rx = SIP.Rx.Dipole(M, N, times)
|
||||
src = SIP.Src.Dipole([rx], Aloc, Bloc)
|
||||
survey = SIP.Survey([src])
|
||||
colemap = [("eta", Maps.IdentityMap(mesh)), ("taui", Maps.IdentityMap(mesh))]
|
||||
problem = SIP.Problem3D_N(mesh, sigma=sigma, mapping=colemap)
|
||||
problem.Solver = MumpsSolver
|
||||
problem.pair(survey)
|
||||
mSynth = np.r_[eta, 1./tau]
|
||||
survey.makeSyntheticData(mSynth)
|
||||
# Now set up the problem to do some minimization
|
||||
dmis = DataMisfit.l2_DataMisfit(survey)
|
||||
reg = Regularization.Tikhonov(mesh)
|
||||
opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
|
||||
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
|
||||
inv = Inversion.BaseInversion(invProb)
|
||||
|
||||
self.inv = inv
|
||||
self.reg = reg
|
||||
self.p = problem
|
||||
self.mesh = mesh
|
||||
self.m0 = mSynth
|
||||
self.survey = survey
|
||||
self.dmis = dmis
|
||||
|
||||
def test_misfit(self):
|
||||
derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
|
||||
passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
|
||||
self.assertTrue(passed)
|
||||
|
||||
def test_adjoint(self):
|
||||
# Adjoint Test
|
||||
u = np.random.rand(self.mesh.nC*self.survey.nSrc)
|
||||
v = np.random.rand(self.mesh.nC*2)
|
||||
w = np.random.rand(self.survey.dobs.shape[0])
|
||||
wtJv = w.dot(self.p.Jvec(self.m0, v))
|
||||
vtJtw = v.dot(self.p.Jtvec(self.m0, w))
|
||||
passed = np.abs(wtJv - vtJtw) < 1e-8
|
||||
print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
|
||||
self.assertTrue(passed)
|
||||
|
||||
def test_dataObj(self):
|
||||
derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
|
||||
passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
|
||||
self.assertTrue(passed)
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
Reference in New Issue
Block a user