mirror of
https://github.com/wassname/simpeg.git
synced 2026-07-10 20:53:47 +08:00
f for fields in data misfit, directives etc. Previously, f was used in the InvProblem to be the function value for the objective function --> this has been renamed to phi
This commit is contained in:
Lindsey Heagy
@@ -123,5 +123,5 @@ class l2_DataMisfit(BaseDataMisfit):
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@Utils.timeIt
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def eval2Deriv(self, m, v, f=None):
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"eval2Deriv(m, v, f=None)"
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if f is None: f = prob.fields(m)
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return self.prob.Jtvec_approx(m, self.Wd * (self.Wd * prob.Jvec_approx(m, v, f=f)), f=f)
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if f is None: f = self.prob.fields(m)
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return self.prob.Jtvec_approx(m, self.Wd * (self.Wd * self.prob.Jvec_approx(m, v, f=f)), f=f)
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@@ -123,10 +123,10 @@ class BetaEstimate_ByEig(InversionDirective):
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if self.debug: print 'Calculating the beta0 parameter.'
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m = self.invProb.curModel
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u = self.invProb.getFields(m, store=True, deleteWarmstart=False)
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f = self.invProb.getFields(m, store=True, deleteWarmstart=False)
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x0 = np.random.rand(*m.shape)
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t = x0.dot(self.dmisfit.eval2Deriv(m,x0,u=u))
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t = x0.dot(self.dmisfit.eval2Deriv(m,x0,f=f))
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b = x0.dot(self.reg.eval2Deriv(m, v=x0))
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self.beta0 = self.beta0_ratio*(t/b)
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@@ -67,7 +67,7 @@ class Rx(SimPEG.Survey.BaseRx):
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"""Grid Location projection (e.g. Ex Fy ...)"""
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return u._GLoc(self.rxType[0]) + self.knownRxTypes[self.rxType][1]
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def eval(self, src, mesh, u):
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def eval(self, src, mesh, f):
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"""
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Project fields to recievers to get data.
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@@ -80,27 +80,27 @@ class Rx(SimPEG.Survey.BaseRx):
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# projGLoc = u._GLoc(self.knownRxTypes[self.rxType][0])
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# projGLoc += self.knownRxTypes[self.rxType][1]
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P = self.getP(mesh, self.projGLoc(u))
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u_part_complex = u[src, self.projField]
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P = self.getP(mesh, self.projGLoc(f))
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f_part_complex = f[src, self.projField]
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# get the real or imag component
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real_or_imag = self.projComp
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u_part = getattr(u_part_complex, real_or_imag)
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f_part = getattr(f_part_complex, real_or_imag)
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return P*u_part
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return P*f_part
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def evalDeriv(self, src, mesh, u, v, adjoint=False):
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def evalDeriv(self, src, mesh, f, v, adjoint=False):
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"""
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Derivative of projected fields with respect to the inversion model times a vector.
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:param Source src: FDEM source
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:param Mesh mesh: mesh used
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:param Fields u: fields object
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:param Fields f: fields object
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:param numpy.ndarray v: vector to multiply
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:rtype: numpy.ndarray
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:return: fields projected to recievers
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"""
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P = self.getP(mesh, self.projGLoc(u))
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P = self.getP(mesh, self.projGLoc(f))
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if not adjoint:
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Pv_complex = P * v
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+11
-11
@@ -108,11 +108,11 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
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Ainv.clean()
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return F
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def Jvec(self, m, v, u=None):
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def Jvec(self, m, v, f=None):
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"""
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:param numpy.array m: Conductivity model
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:param numpy.ndarray v: vector (model object)
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:param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
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:param simpegEM.TDEM.FieldsTDEM f: Fields resulting from m
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:rtype: numpy.ndarray
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:return: w (data object)
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@@ -125,15 +125,15 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
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"""
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if self.verbose: print '%s\nCalculating J(v)\n%s'%('*'*50,'*'*50)
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self.curModel = m
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if u is None:
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u = self.fields(m)
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p = self.Gvec(m, v, u)
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if f is None:
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f = self.fields(m)
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p = self.Gvec(m, v, f)
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y = self.solveAh(m, p)
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Jv = self.survey.evalDeriv(u, v=y)
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Jv = self.survey.evalDeriv(f, v=y)
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if self.verbose: print '%s\nDone calculating J(v)\n%s'%('*'*50,'*'*50)
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return - mkvc(Jv)
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def Jtvec(self, m, v, u=None):
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def Jtvec(self, m, v, f=None):
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"""
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:param numpy.array m: Conductivity model
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:param numpy.ndarray,SimPEG.Survey.Data v: vector (data object)
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@@ -150,15 +150,15 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
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"""
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if self.verbose: print '%s\nCalculating J^T(v)\n%s'%('*'*50,'*'*50)
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self.curModel = m
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if u is None:
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u = self.fields(m)
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if f is None:
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f = self.fields(m)
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if not isinstance(v, self.dataPair):
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v = self.dataPair(self.survey, v)
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p = self.survey.evalDeriv(u, v=v, adjoint=True)
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p = self.survey.evalDeriv(f, v=v, adjoint=True)
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y = self.solveAht(m, p)
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w = self.Gtvec(m, y, u)
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w = self.Gtvec(m, y, f)
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if self.verbose: print '%s\nDone calculating J^T(v)\n%s'%('*'*50,'*'*50)
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return - mkvc(w)
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+13
-13
@@ -82,23 +82,23 @@ class BaseInvProblem(object):
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self._warmstart = value
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def getFields(self, m, store=False, deleteWarmstart=True):
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u = None
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f = None
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for mtest, u_ofmtest in self.warmstart:
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if m is mtest:
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u = u_ofmtest
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f = u_ofmtest
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if self.debug: print 'InvProb is Warm Starting!'
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break
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if u is None:
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u = self.prob.fields(m)
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if f is None:
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f = self.prob.fields(m)
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if deleteWarmstart:
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self.warmstart = []
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if store:
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self.warmstart += [(m,u)]
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self.warmstart += [(m,f)]
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return u
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return f
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@Utils.timeIt
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def evalFunction(self, m, return_g=True, return_H=True):
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@@ -109,21 +109,21 @@ class BaseInvProblem(object):
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gc.collect()
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# Store fields if doing a line-search
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u = self.getFields(m, store=(return_g==False and return_H==False))
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f = self.getFields(m, store=(return_g==False and return_H==False))
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phi_d = self.dmisfit.eval(m, u=u)
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phi_d = self.dmisfit.eval(m, f=f)
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phi_m = self.reg.eval(m)
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self.dpred = self.survey.dpred(m, u=u) # This is a cheap matrix vector calculation.
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self.dpred = self.survey.dpred(m, f=f) # This is a cheap matrix vector calculation.
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self.phi_d, self.phi_d_last = phi_d, self.phi_d
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self.phi_m, self.phi_m_last = phi_m, self.phi_m
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f = phi_d + self.beta * phi_m
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phi = phi_d + self.beta * phi_m
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out = (f,)
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out = (phi,)
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if return_g:
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phi_dDeriv = self.dmisfit.evalDeriv(m, u=u)
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phi_dDeriv = self.dmisfit.evalDeriv(m, f=f)
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phi_mDeriv = self.reg.evalDeriv(m)
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g = phi_dDeriv + self.beta * phi_mDeriv
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@@ -131,7 +131,7 @@ class BaseInvProblem(object):
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if return_H:
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def H_fun(v):
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phi_d2Deriv = self.dmisfit.eval2Deriv(m, v, u=u)
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phi_d2Deriv = self.dmisfit.eval2Deriv(m, v, f=f)
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phi_m2Deriv = self.reg.eval2Deriv(m, v=v)
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return phi_d2Deriv + self.beta * phi_m2Deriv
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+13
-13
@@ -27,7 +27,7 @@ class BaseMTProblem(BaseFDEMProblem):
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# Might need to add more stuff here.
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## NEED to clean up the Jvec and Jtvec to use Zero and Identities for None components.
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def Jvec(self, m, v, u=None):
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def Jvec(self, m, v, f=None):
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"""
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Function to calculate the data sensitivities dD/dm times a vector.
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@@ -39,8 +39,8 @@ class BaseMTProblem(BaseFDEMProblem):
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"""
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# Calculate the fields
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if u is None:
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u = self.fields(m)
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if f is None:
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f= self.fields(m)
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# Set current model
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self.curModel = m
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# Initiate the Jv object
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@@ -56,9 +56,9 @@ class BaseMTProblem(BaseFDEMProblem):
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# We need fDeriv_m = df/du*du/dm + df/dm
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# Construct du/dm, it requires a solve
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# NOTE: need to account for the 2 polarizations in the derivatives.
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u_src = u[src,:]
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f_src = f[src,:]
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# dA_dm and dRHS_dm should be of size nE,2, so that we can multiply by dA_duI. The 2 columns are each of the polarizations.
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dA_dm = self.getADeriv_m(freq, u_src, v) # Size: nE,2 (u_px,u_py) in the columns.
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dA_dm = self.getADeriv_m(freq, f_src, v) # Size: nE,2 (u_px,u_py) in the columns.
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dRHS_dm = self.getRHSDeriv_m(freq, v) # Size: nE,2 (u_px,u_py) in the columns.
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if dRHS_dm is None:
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du_dm = dA_duI * ( -dA_dm )
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@@ -68,13 +68,13 @@ class BaseMTProblem(BaseFDEMProblem):
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for rx in src.rxList:
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# Get the projection derivative
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# v should be of size 2*nE (for 2 polarizations)
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PDeriv_u = lambda t: rx.evalDeriv(src, self.mesh, u, t) # wrt u, we don't have have PDeriv wrt m
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PDeriv_u = lambda t: rx.evalDeriv(src, self.mesh, f, t) # wrt u, we don't have have PDeriv wrt m
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Jv[src, rx] = PDeriv_u(mkvc(du_dm))
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dA_duI.clean()
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# Return the vectorized sensitivities
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return mkvc(Jv)
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def Jtvec(self, m, v, u=None):
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def Jtvec(self, m, v, f=None):
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"""
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Function to calculate the transpose of the data sensitivities (dD/dm)^T times a vector.
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@@ -85,8 +85,8 @@ class BaseMTProblem(BaseFDEMProblem):
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:return: Data sensitivities wrt m
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"""
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if u is None:
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u = 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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@@ -103,15 +103,15 @@ class BaseMTProblem(BaseFDEMProblem):
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for src in self.survey.getSrcByFreq(freq):
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ftype = self._fieldType + 'Solution'
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u_src = u[src, :]
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f_src = f[src, :]
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for rx in src.rxList:
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# Get the adjoint evalDeriv
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# PTv needs to be nE,
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PTv = rx.evalDeriv(src, self.mesh, u, mkvc(v[src, rx],2), adjoint=True) # wrt u, need possibility wrt m
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PTv = rx.evalDeriv(src, self.mesh, f, mkvc(v[src, rx],2), adjoint=True) # wrt u, need possibility wrt m
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# Get the
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dA_duIT = ATinv * PTv
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dA_dmT = self.getADeriv_m(freq, u_src, mkvc(dA_duIT), adjoint=True)
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dA_dmT = self.getADeriv_m(freq, f_src, mkvc(dA_duIT), adjoint=True)
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dRHS_dmT = self.getRHSDeriv_m(freq, mkvc(dA_duIT), adjoint=True)
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# Make du_dmT
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if dRHS_dmT is None:
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@@ -129,4 +129,4 @@ class BaseMTProblem(BaseFDEMProblem):
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raise Exception('Must be real or imag')
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# Clean the factorization, clear memory.
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ATinv.clean()
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return Jtv
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return Jtv
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@@ -427,15 +427,15 @@ class Survey(SimPEGsurvey.BaseSurvey):
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assert freq in self._freqDict, "The requested frequency is not in this survey."
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return self._freqDict[freq]
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def eval(self, u):
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def eval(self, f):
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data = Data(self)
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for src in self.srcList:
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sys.stdout.flush()
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for rx in src.rxList:
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data[src, rx] = rx.eval(src, self.mesh, u)
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data[src, rx] = rx.eval(src, self.mesh, f)
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return data
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def evalDeriv(self, u):
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def evalDeriv(self, f):
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raise Exception('Use Transmitters to project fields deriv.')
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#################
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+2
-2
@@ -128,7 +128,7 @@ class BaseProblem(object):
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:rtype: numpy.array
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:return: approxJv
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"""
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return self.Jvec(m, v, u)
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return self.Jvec(m, v, f)
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@Utils.timeIt
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def Jtvec_approx(self, m, v, f=None):
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@@ -142,7 +142,7 @@ class BaseProblem(object):
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:rtype: numpy.array
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:return: JTv
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"""
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return self.Jtvec(m, v, u)
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return self.Jtvec(m, v, f)
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def fields(self, m):
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"""
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+7
-7
@@ -313,20 +313,20 @@ class BaseSurvey(object):
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@Utils.count
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def eval(self, u):
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"""eval(u)
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def eval(self, f):
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"""eval(f)
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This function projects the fields onto the data space.
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.. math::
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d_\\text{pred} = \mathbf{P} u(m)
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d_\\text{pred} = \mathbf{P} f(m)
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"""
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raise NotImplemented('eval is not yet implemented.')
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@Utils.count
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def evalDeriv(self, u):
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"""evalDeriv(u)
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def evalDeriv(self, f):
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"""evalDeriv(f)
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This function s the derivative of projects the fields onto the data space.
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@@ -379,8 +379,8 @@ class BaseSurvey(object):
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return self.dobs
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class LinearSurvey(BaseSurvey):
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def eval(self, u):
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return u
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def eval(self, f):
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return f
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@property
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def nD(self):
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