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DC inversion working again. Almost in the new framework..!

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rowanc1
2014-01-16 14:29:08 -08:00
parent fa8a5cd7cb
commit 687ef0c20a
6 changed files with 73 additions and 52 deletions
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SimPEG/Examples/DC.py
+28 -31
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@@ -10,9 +10,10 @@ class DCData(Data.BaseData):
"""
def __init__(self, mesh, model, **kwargs):
problem.BaseProblem.__init__(self, mesh, model)
self.mesh.setCellGradBC('neumann')
P = None #: projection
def __init__(self, **kwargs):
Data.BaseData.__init__(self, **kwargs)
Utils.setKwargs(self, **kwargs)
def reshapeFields(self, u):
@@ -20,18 +21,14 @@ class DCData(Data.BaseData):
u = u.reshape([-1, self.RHS.shape[1]], order='F')
return u
def dpred(self, m, u=None):
def projectField(self, u):
"""
Predicted data.
.. math::
d_\\text{pred} = Pu(m)
"""
if u is None:
u = self.field(m)
u = self.reshapeFields(u)
return Utils.mkvc(self.P*u)
@@ -47,7 +44,7 @@ class DCProblem(Problem.BaseProblem):
dataPair = DCData
def __init__(self, mesh, model, **kwargs):
problem.BaseProblem.__init__(self, mesh, model)
Problem.BaseProblem.__init__(self, mesh, model)
self.mesh.setCellGradBC('neumann')
Utils.setKwargs(self, **kwargs)
@@ -75,7 +72,7 @@ class DCProblem(Problem.BaseProblem):
def field(self, m):
A = self.createMatrix(m)
solve = Solver(A)
phi = solve.solve(self.RHS)
phi = solve.solve(self.data.RHS)
return Utils.mkvc(phi)
def J(self, m, v, u=None):
@@ -103,9 +100,9 @@ class DCProblem(Problem.BaseProblem):
if u is None:
u = self.field(m)
u = self.reshapeFields(u)
u = self.data.reshapeFields(u)
P = self.P
P = self.data.P
D = self.mesh.faceDiv
G = self.mesh.cellGrad
A = self.createMatrix(m)
@@ -128,10 +125,10 @@ class DCProblem(Problem.BaseProblem):
if u is None:
u = self.field(m)
u = self.reshapeFields(u)
v = self.reshapeFields(v)
u = self.data.reshapeFields(u)
v = self.data.reshapeFields(v)
P = self.P
P = self.data.P
D = self.mesh.faceDiv
G = self.mesh.cellGrad
A = self.createMatrix(m)
@@ -186,7 +183,7 @@ if __name__ == '__main__':
# Create the mesh
h1 = np.ones(20)
h2 = np.ones(100)
M = mesh.TensorMesh([h1,h2])
M = Mesh.TensorMesh([h1,h2])
# Create some parameters for the model
sig1 = np.log(1)
@@ -198,7 +195,7 @@ if __name__ == '__main__':
condVals = [sig1, sig2]
mSynth = Utils.ModelBuilder.defineBlockConductivity(p0,p1,M.gridCC,condVals)
plt.colorbar(M.plotImage(mSynth))
plt.show()
# plt.show()
# Set up the projection
nelec = 50
@@ -211,29 +208,29 @@ if __name__ == '__main__':
q, Q, rxmidloc = genTxRxmat(nelec, spacelec, surfloc, elecini, M)
P = Q.T
# Create some data
problem = DCProblem(M)
problem.P = P
problem.RHS = q
data = problem.createSyntheticData(mSynth, std=0.05)
model = Model.LogModel()
prob = DCProblem(M, model)
u = problem.field(mSynth)
u = problem.reshapeFields(u)
# Create some data
data = prob.createSyntheticData(mSynth, std=0.05, P=P, RHS=q)
u = prob.field(mSynth)
u = data.reshapeFields(u)
M.plotImage(u[:,10])
# plt.show()
# Now set up the problem to do some minimization
# problem.dobs = dobs
# problem.std = dobs*0 + 0.05
# Now set up the prob to do some minimization
# prob.dobs = dobs
# prob.std = dobs*0 + 0.05
m0 = M.gridCC[:,0]*0+sig2
opt = inverse.InexactGaussNewton(maxIterLS=20, maxIter=3, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
reg = inverse.Regularization(M)
inv = inverse.Inversion(problem, reg, opt, data, beta0=1e4)
opt = Inverse.InexactGaussNewton(maxIterLS=20, maxIter=3, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
reg = Inverse.Regularization(M)
inv = Inverse.Inversion(prob, reg, opt, data, beta0=1e4)
# Check Derivative
derChk = lambda m: [inv.dataObj(m), inv.dataObjDeriv(m)]
tests.checkDerivative(derChk, mSynth)
# Tests.checkDerivative(derChk, mSynth)