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Refactor IRLS iterations, full solves from l2->lp

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Adapt Example
This commit is contained in:
D Fournier
2016-05-28 11:27:09 -07:00
parent 022e1f7660
commit 3b4bec9c0b
3 changed files with 158 additions and 115 deletions
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SimPEG/Examples/Inversion_IRLS.py
+32 -34
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@@ -52,51 +52,49 @@ def run(N=200, plotIt=True):
wr = np.sum(prob.G**2.,axis=0)**0.5
wr = ( wr/np.max(wr) )
reg = Regularization.Simple(mesh)
reg.mref = mref
reg.cell_weights = wr
# reg = Regularization.Simple(mesh)
# reg.mref = mref
# reg.cell_weights = wr
#
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = 1./wd
opt = Optimization.ProjectedGNCG(maxIter=20,lower=-2.,upper=2., maxIterCG= 10, tolCG = 1e-4)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
invProb.curModel = m0
beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
target = Directives.TargetMisfit()
#
# opt = Optimization.ProjectedGNCG(maxIter=20,lower=-2.,upper=2., maxIterCG= 10, tolCG = 1e-4)
# invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
# invProb.curModel = m0
#
# beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
# target = Directives.TargetMisfit()
#
betaest = Directives.BetaEstimate_ByEig()
inv = Inversion.BaseInversion(invProb, directiveList=[beta, betaest, target])
mrec = inv.run(m0)
ml2 = mrec
print "Final misfit:" + str(invProb.dmisfit.eval(mrec))
# Switch regularization to sparse
phim = invProb.phi_m_last
phid = invProb.phi_d
# inv = Inversion.BaseInversion(invProb, directiveList=[beta, betaest, target])
#
#
# mrec = inv.run(m0)
# ml2 = mrec
# print "Final misfit:" + str(invProb.dmisfit.eval(mrec))
#
# # Switch regularization to sparse
# phim = invProb.phi_m_last
# phid = invProb.phi_d
reg = Regularization.Sparse(mesh)
reg.mref = mref
reg.cell_weights = wr
reg.mref = np.zeros(mesh.nC)
reg.eps_p = 1e-3
reg.eps_q = 1e-2
reg.norms = [0., 0., 2., 2.]
eps_p = 1e-3
eps_q = 1e-2
norms = [0., 0., 2., 2.]
opt = Optimization.ProjectedGNCG(maxIter=100 ,lower=-2.,upper=2., maxIterLS = 20, maxIterCG= 10, tolCG = 1e-3)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = invProb.beta*2.)
beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
update_beta = Directives.Scale_Beta(tol = 0.05, coolingRate=5)
target = Directives.TargetMisfit()
IRLS = Directives.Update_IRLS( phi_m_last = phim, phi_d_last = phid, coolingRate=5 )
invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
#beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
#update_beta = Directives.Scale_Beta(tol = 0.05, coolingRate=5)
# target = Directives.TargetMisfit()
IRLS = Directives.Update_IRLS( norms=norms, eps_p=eps_p, eps_q=eps_q)
inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS,update_beta])
m0 = mrec
inv = Inversion.BaseInversion(invProb, directiveList=[IRLS,betaest])
# Run inversion
mrec = inv.run(m0)
@@ -113,7 +111,7 @@ def run(N=200, plotIt=True):
axes[0].set_title('Columns of matrix G')
axes[1].plot(mesh.vectorCCx, mtrue, 'b-')
axes[1].plot(mesh.vectorCCx, ml2, 'r-')
axes[1].plot(mesh.vectorCCx, reg.l2model, 'r-')
#axes[1].legend(('True Model', 'Recovered Model'))
axes[1].set_ylim(-1.0,1.25)