wassname/simpeg
1
0
Fork 0
mirror of https://github.com/wassname/simpeg.git synced 2026-06-27 19:32:36 +08:00
Code Issues Packages Projects Releases Wiki Activity

Problem.Jvec, Problem.Jtvec, Problem.fields, DataMisfit, survey.dpred take a fields object f (not a solution vector, u)

Browse Source
This commit is contained in:
Lindsey Heagy
2016-03-29 22:49:03 -07:00
parent 1d208a8747
commit 0a0caceaca
7 changed files with 98 additions and 104 deletions
Download Patch File Download Diff File Expand all files Collapse all files
SimPEG/DCIP/BaseDC.py
+11 -13
View File
@@ -200,11 +200,11 @@ class ProblemDC_CC(Problem.BaseProblem):
return F
def Jvec(self, m, v, u=None):
def Jvec(self, m, v, f=None):
"""
:param numpy.array m: model
:param numpy.array v: vector to multiply
:param numpy.array u: fields
:param Fields f: fields
:rtype: numpy.array
:return: Jv
@@ -225,11 +225,10 @@ class ProblemDC_CC(Problem.BaseProblem):
# Set current model; clear dependent property $\mathbf{A(m)}$
self.curModel = m
sigma = self.curModel.transform # $\sigma = \mathcal{M}(\m)$
if u is None:
if f is None:
# Run forward simulation if $u$ not provided
u = self.fields(self.curModel)[self.survey.srcList, 'phi_sol']
else:
u = u[self.survey.srcList, 'phi_sol']
f = self.fields(self.curModel)
u = f[self.survey.srcList, 'phi_sol']
D = self.mesh.faceDiv
G = self.mesh.cellGrad
@@ -251,19 +250,18 @@ class ProblemDC_CC(Problem.BaseProblem):
if self.Ainv is None:
self.Ainv = self.Solver(dA_du, **self.solverOpts)
P = self.survey.getP(self.mesh)
P = self.survey.getP(self.mesh)
Jv = - P * mkvc( self.Ainv * dCdm_x_v )
return Jv
def Jtvec(self, m, v, u=None):
def Jtvec(self, m, v, f=None):
self.curModel = m
sigma = self.curModel.transform # $\sigma = \mathcal{M}(\m)$
if u is None:
# Run forward simulation if $u$ not provided
u = self.fields(self.curModel)[self.survey.srcList, 'phi_sol']
else:
u = u[self.survey.srcList, 'phi_sol']
if f is None:
# Run forward simulation if $f$ not provided
f = self.fields(self.curModel)
u = f[self.survey.srcList, 'phi_sol']
shp = u.shape
P = self.survey.getP(self.mesh)
SimPEG/DCIP/BaseIP.py
+4 -4
View File
@@ -14,12 +14,12 @@ class SurveyIP(SurveyDC):
Survey.BaseSurvey.__init__(self, **kwargs)
self._Ps = {}
def dpred(self, m, u=None):
def dpred(self, m, f=None):
"""
Predicted data.
.. math::
d_\\text{pred} = Pu(m)
d_\\text{pred} = Pf(m)
"""
return self.prob.forward(m)
@@ -143,10 +143,10 @@ class ProblemIP(Problem.BaseProblem):
J_x_v = - P * mkvc( self.Ainv * dCdm_x_v )
return -J_x_v
def Jvec(self, m, v, u=None):
def Jvec(self, m, v, f=None):
return self.forward(v)
def Jtvec(self, m, v, u=None):
def Jtvec(self, m, v, f=None):
self.curModel = m
# sigma = self.curModel.transform # $\sigma = \mathcal{M}(\m)$
SimPEG/DataMisfit.py
+21 -25
View File
@@ -22,11 +22,11 @@ class BaseDataMisfit(object):
Utils.setKwargs(self,**kwargs)
@Utils.timeIt
def eval(self, m, u=None):
"""eval(m, u=None)
def eval(self, m, f=None):
"""eval(m, f=None)
:param numpy.array m: geophysical model
:param numpy.array u: fields
:param Fields f: fields
:rtype: float
:return: data misfit
@@ -34,11 +34,11 @@ class BaseDataMisfit(object):
raise NotImplementedError('This method should be overwritten.')
@Utils.timeIt
def evalDeriv(self, m, u=None):
"""evalDeriv(m, u=None)
def evalDeriv(self, m, f=None):
"""evalDeriv(m, f=None)
:param numpy.array m: geophysical model
:param numpy.array u: fields
:param Fields f: fields
:rtype: numpy.array
:return: data misfit derivative
@@ -47,12 +47,12 @@ class BaseDataMisfit(object):
@Utils.timeIt
def eval2Deriv(self, m, v, u=None):
"""eval2Deriv(m, v, u=None)
def eval2Deriv(self, m, v, f=None):
"""eval2Deriv(m, v, f=None)
:param numpy.array m: geophysical model
:param numpy.array v: vector to multiply
:param numpy.array u: fields
:param Fields f: fields
:rtype: numpy.array
:return: data misfit derivative
@@ -108,24 +108,20 @@ class l2_DataMisfit(BaseDataMisfit):
self._Wd = value
@Utils.timeIt
def eval(self, m, u=None):
"eval(m, u=None)"
prob = self.prob
survey = self.survey
R = self.Wd * survey.residual(m, u)
def eval(self, m, f=None):
"eval(m, f=None)"
if f is None: f = self.prob.fields(m)
R = self.Wd * self.survey.residual(m, f)
return 0.5*np.vdot(R, R)
@Utils.timeIt
def evalDeriv(self, m, u=None):
"evalDeriv(m, u=None)"
prob = self.prob
survey = self.survey
if u is None: u = prob.fields(m)
return prob.Jtvec(m, self.Wd * (self.Wd * survey.residual(m, u)), u)
def evalDeriv(self, m, f=None):
"evalDeriv(m, f=None)"
if f is None: f = self.prob.fields(m)
return self.prob.Jtvec(m, self.Wd * (self.Wd * self.survey.residual(m, f=f)), f=f)
@Utils.timeIt
def eval2Deriv(self, m, v, u=None):
"eval2Deriv(m, v, u=None)"
prob = self.prob
if u is None: u = prob.fields(m)
return prob.Jtvec_approx(m, self.Wd * (self.Wd * prob.Jvec_approx(m, v, u=u)), u)
def eval2Deriv(self, m, v, f=None):
"eval2Deriv(m, v, f=None)"
if f is None: f = prob.fields(m)
return self.prob.Jtvec_approx(m, self.Wd * (self.Wd * prob.Jvec_approx(m, v, f=f)), f=f)
SimPEG/FLOW/Richards/RichardsProblem.py
+29 -29
View File
@@ -45,19 +45,19 @@ class RichardsSurvey(Survey.BaseSurvey):
@Utils.count
@Utils.requires('prob')
def dpred(self, m, u=None):
def dpred(self, m, f=None):
"""
Create the projected data from a model.
The field, u, (if provided) will be used for the predicted data
The field, f, (if provided) will be used for the predicted data
instead of recalculating the fields (which may be expensive!).
.. math::
d_\\text{pred} = P(u(m), m)
d_\\text{pred} = P(f(m), m)
Where P is a projection of the fields onto the data space.
"""
if u is None: u = self.prob.fields(m)
return Utils.mkvc(self.eval(u, m))
if f is None: f = self.prob.fields(m)
return Utils.mkvc(self.eval(f, m))
@Utils.requires('prob')
def eval(self, U, m):
@@ -233,16 +233,16 @@ class RichardsProblem(Problem.BaseTimeProblem):
return r, J
@Utils.timeIt
def Jfull(self, m, u=None):
if u is None:
u = self.fields(m)
def Jfull(self, m, f=None):
if f is None:
f = self.fields(m)
nn = len(u)-1
nn = len(f)-1
Asubs, Adiags, Bs = range(nn), range(nn), range(nn)
for ii in range(nn):
dt = self.timeSteps[ii]
bc = self.getBoundaryConditions(ii, u[ii])
Asubs[ii], Adiags[ii], Bs[ii] = self.diagsJacobian(m, u[ii], u[ii+1], dt, bc)
bc = self.getBoundaryConditions(ii, f[ii])
Asubs[ii], Adiags[ii], Bs[ii] = self.diagsJacobian(m, f[ii], f[ii+1], dt, bc)
Ad = sp.block_diag(Adiags)
zRight = Utils.spzeros((len(Asubs)-1)*Asubs[0].shape[0],Adiags[0].shape[1])
zTop = Utils.spzeros(Adiags[0].shape[0], len(Adiags)*Adiags[0].shape[1])
@@ -251,7 +251,7 @@ class RichardsProblem(Problem.BaseTimeProblem):
B = np.array(sp.vstack(Bs).todense())
Ainv = self.Solver(A, **self.solverOpts)
P = self.survey.evalDeriv(u, m)
P = self.survey.evalDeriv(f, m)
AinvB = Ainv * B
z = np.zeros((self.mesh.nC, B.shape[1]))
zAinvB = np.vstack((z, AinvB))
@@ -259,41 +259,41 @@ class RichardsProblem(Problem.BaseTimeProblem):
return J
@Utils.timeIt
def Jvec(self, m, v, u=None):
if u is None:
u = self.fields(m)
def Jvec(self, m, v, f=None):
if f is None:
f = self.fields(m)
JvC = range(len(u)-1) # Cell to hold each row of the long vector.
JvC = range(len(f)-1) # Cell to hold each row of the long vector.
# This is done via forward substitution.
bc = self.getBoundaryConditions(0, u[0])
temp, Adiag, B = self.diagsJacobian(m, u[0], u[1], self.timeSteps[0], bc)
bc = self.getBoundaryConditions(0, f[0])
temp, Adiag, B = self.diagsJacobian(m, f[0], f[1], self.timeSteps[0], bc)
Adiaginv = self.Solver(Adiag, **self.solverOpts)
JvC[0] = Adiaginv * (B*v)
for ii in range(1,len(u)-1):
bc = self.getBoundaryConditions(ii, u[ii])
Asub, Adiag, B = self.diagsJacobian(m, u[ii], u[ii+1], self.timeSteps[ii], bc)
for ii in range(1,len(f)-1):
bc = self.getBoundaryConditions(ii, f[ii])
Asub, Adiag, B = self.diagsJacobian(m, f[ii], f[ii+1], self.timeSteps[ii], bc)
Adiaginv = self.Solver(Adiag, **self.solverOpts)
JvC[ii] = Adiaginv * (B*v - Asub*JvC[ii-1])
P = self.survey.evalDeriv(u, m)
P = self.survey.evalDeriv(f, m)
return P * np.concatenate([np.zeros(self.mesh.nC)] + JvC)
@Utils.timeIt
def Jtvec(self, m, v, u=None):
if u is None:
u = self.field(m)
def Jtvec(self, m, v, f=None):
if f is None:
f = self.field(m)
P = self.survey.evalDeriv(u, m)
P = self.survey.evalDeriv(f, m)
PTv = P.T*v
# This is done via backward substitution.
minus = 0
BJtv = 0
for ii in range(len(u)-1,0,-1):
bc = self.getBoundaryConditions(ii-1, u[ii-1])
Asub, Adiag, B = self.diagsJacobian(m, u[ii-1], u[ii], self.timeSteps[ii-1], bc)
for ii in range(len(f)-1,0,-1):
bc = self.getBoundaryConditions(ii-1, f[ii-1])
Asub, Adiag, B = self.diagsJacobian(m, f[ii-1], f[ii], self.timeSteps[ii-1], bc)
#select the correct part of v
vpart = range((ii)*Adiag.shape[0], (ii+1)*Adiag.shape[0])
AdiaginvT = self.Solver(Adiag.T, **self.solverOpts)
SimPEG/Problem.py
+14 -14
View File
@@ -88,28 +88,28 @@ class BaseProblem(object):
return self.survey is not None
@Utils.timeIt
def Jvec(self, m, v, u=None):
"""Jvec(m, v, u=None)
def Jvec(self, m, v, f=None):
"""Jvec(m, v, f=None)
Effect of J(m) on a vector v.
:param numpy.array m: model
:param numpy.array v: vector to multiply
:param numpy.array u: fields
:param Fields f: fields
:rtype: numpy.array
:return: Jv
"""
raise NotImplementedError('J is not yet implemented.')
@Utils.timeIt
def Jtvec(self, m, v, u=None):
"""Jtvec(m, v, u=None)
def Jtvec(self, m, v, f=None):
"""Jtvec(m, v, f=None)
Effect of transpose of J(m) on a vector v.
:param numpy.array m: model
:param numpy.array v: vector to multiply
:param numpy.array u: fields
:param Fields f: fields
:rtype: numpy.array
:return: JTv
"""
@@ -117,28 +117,28 @@ class BaseProblem(object):
@Utils.timeIt
def Jvec_approx(self, m, v, u=None):
"""Jvec_approx(m, v, u=None)
def Jvec_approx(self, m, v, f=None):
"""Jvec_approx(m, v, f=None)
Approximate effect of J(m) on a vector v
:param numpy.array m: model
:param numpy.array v: vector to multiply
:param numpy.array u: fields
:param Fields f: fields
:rtype: numpy.array
:return: approxJv
"""
return self.Jvec(m, v, u)
@Utils.timeIt
def Jtvec_approx(self, m, v, u=None):
"""Jtvec_approx(m, v, u=None)
def Jtvec_approx(self, m, v, f=None):
"""Jtvec_approx(m, v, f=None)
Approximate effect of transpose of J(m) on a vector v.
:param numpy.array m: model
:param numpy.array v: vector to multiply
:param numpy.array u: fields
:param Fields f: fields
:rtype: numpy.array
:return: JTv
"""
@@ -224,9 +224,9 @@ class LinearProblem(BaseProblem):
def fields(self, m):
return self.G.dot(m)
def Jvec(self, m, v, u=None):
def Jvec(self, m, v, f=None):
return self.G.dot(v)
def Jtvec(self, m, v, u=None):
def Jtvec(self, m, v, f=None):
return self.G.T.dot(v)
SimPEG/Survey.py
+13 -13
View File
@@ -295,21 +295,21 @@ class BaseSurvey(object):
@Utils.count
@Utils.requires('prob')
def dpred(self, m, u=None):
"""dpred(m, u=None)
def dpred(self, m, f=None):
"""dpred(m, f=None)
Create the projected data from a model.
The field, u, (if provided) will be used for the predicted data
The fields, f, (if provided) will be used for the predicted data
instead of recalculating the fields (which may be expensive!).
.. math::
d_\\text{pred} = P(u(m))
d_\\text{pred} = P(f(m))
Where P is a projection of the fields onto the data space.
"""
if u is None: u = self.prob.fields(m)
return Utils.mkvc(self.eval(u))
if f is None: f = self.prob.fields(m)
return Utils.mkvc(self.eval(f))
@Utils.count
@@ -337,11 +337,11 @@ class BaseSurvey(object):
raise NotImplemented('eval is not yet implemented.')
@Utils.count
def residual(self, m, u=None):
"""residual(m, u=None)
def residual(self, m, f=None):
"""residual(m, f=None)
:param numpy.array m: geophysical model
:param numpy.array u: fields
:param numpy.array f: fields
:rtype: numpy.array
:return: data residual
@@ -352,14 +352,14 @@ class BaseSurvey(object):
\mu_\\text{data} = \mathbf{d}_\\text{pred} - \mathbf{d}_\\text{obs}
"""
return Utils.mkvc(self.dpred(m, u=u) - self.dobs)
return Utils.mkvc(self.dpred(m, f=f) - self.dobs)
@property
def isSynthetic(self):
"Check if the data is synthetic."
return self.mtrue is not None
def makeSyntheticData(self, m, std=0.05, u=None, force=False):
def makeSyntheticData(self, m, std=0.05, f=None, force=False):
"""
Make synthetic data given a model, and a standard deviation.
@@ -372,7 +372,7 @@ class BaseSurvey(object):
if getattr(self, 'dobs', None) is not None and not force:
raise Exception('Survey already has dobs. You can use force=True to override this exception.')
self.mtrue = m
self.dtrue = self.dpred(m, u=u)
self.dtrue = self.dpred(m, f=f)
noise = std*abs(self.dtrue)*np.random.randn(*self.dtrue.shape)
self.dobs = self.dtrue+noise
self.std = self.dobs*0 + std
@@ -381,7 +381,7 @@ class BaseSurvey(object):
class LinearSurvey(BaseSurvey):
def eval(self, u):
return u
@property
def nD(self):
return self.prob.G.shape[0]
tests/flow/test_Richards.py
+6 -6
View File
@@ -116,8 +116,8 @@ class RichardsTests1D(unittest.TestCase):
v = np.random.rand(self.survey.nD)
z = np.random.rand(self.M.nC)
Hs = self.prob.fields(self.Ks)
vJz = v.dot(self.prob.Jvec(self.Ks,z,u=Hs))
zJv = z.dot(self.prob.Jtvec(self.Ks,v,u=Hs))
vJz = v.dot(self.prob.Jvec(self.Ks,z,f=Hs))
zJv = z.dot(self.prob.Jtvec(self.Ks,v,f=Hs))
tol = TOL*(10**int(np.log10(np.abs(zJv))))
passed = np.abs(vJz - zJv) < tol
print 'Richards Adjoint Test - PressureHead'
@@ -188,8 +188,8 @@ class RichardsTests2D(unittest.TestCase):
v = np.random.rand(self.survey.nD)
z = np.random.rand(self.M.nC)
Hs = self.prob.fields(self.Ks)
vJz = v.dot(self.prob.Jvec(self.Ks,z,u=Hs))
zJv = z.dot(self.prob.Jtvec(self.Ks,v,u=Hs))
vJz = v.dot(self.prob.Jvec(self.Ks,z,f=Hs))
zJv = z.dot(self.prob.Jtvec(self.Ks,v,f=Hs))
tol = TOL*(10**int(np.log10(np.abs(zJv))))
passed = np.abs(vJz - zJv) < tol
print '2D: Richards Adjoint Test - PressureHead'
@@ -260,8 +260,8 @@ class RichardsTests3D(unittest.TestCase):
v = np.random.rand(self.survey.nD)
z = np.random.rand(self.M.nC)
Hs = self.prob.fields(self.Ks)
vJz = v.dot(self.prob.Jvec(self.Ks,z,u=Hs))
zJv = z.dot(self.prob.Jtvec(self.Ks,v,u=Hs))
vJz = v.dot(self.prob.Jvec(self.Ks,z,f=Hs))
zJv = z.dot(self.prob.Jtvec(self.Ks,v,f=Hs))
tol = TOL*(10**int(np.log10(np.abs(zJv))))
passed = np.abs(vJz - zJv) < tol
print '3D: Richards Adjoint Test - PressureHead'