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https://github.com/wassname/simpeg.git
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D Fournier
174 lines
5.4 KiB
Python
174 lines
5.4 KiB
Python
from SimPEG import *
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import simpegPF as PF
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import pylab as plt
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#import os
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plt.close('all')
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driver = PF.MagneticsDriver.MagneticsDriver_Inv('PYMAG3D_inv.inp')
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mesh = driver.mesh
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survey = driver.survey
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rxLoc = survey.srcField.rxList[0].locs
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d = survey.dobs
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wd = survey.std
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ndata = survey.srcField.rxList[0].locs.shape[0]
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actv = driver.activeCells
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nC = len(actv)
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# Create active map to go from reduce set to full
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actvMap = Maps.InjectActiveCells(mesh, actv, -100)
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# Create static map
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static = driver.staticCells
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dynamic = driver.dynamicCells
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staticCells = Maps.InjectActiveCells(None, dynamic, driver.m0[static], nC=nC)
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mstart = driver.m0[dynamic]
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# Get magnetization vector for MOF
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M_xyz = driver.magnetizationModel
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# Get index of the center
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midx = int(mesh.nCx/2)
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midy = int(mesh.nCy/2)
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#%% Plot obs data
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PF.Magnetics.plot_obs_2D(rxLoc,d, 'Observed Data')
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#%% Run inversion
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prob = PF.Magnetics.Problem3D_Integral(mesh, mapping = staticCells, actInd=actv)
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prob.solverOpts['accuracyTol'] = 1e-4
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survey.pair(prob)
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dmis = DataMisfit.l2_DataMisfit(survey)
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dmis.Wd = 1./wd
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# Write out the predicted
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pred = prob.fields(mstart)
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PF.Magnetics.writeUBCobs('Pred.dat', survey, pred)
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wr = np.sum(prob.G**2.,axis=0)**0.5
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wr = ( wr/np.max(wr) )
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wr_out = actvMap * wr
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plt.figure()
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ax = plt.subplot()
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mesh.plotSlice(wr_out, ax=ax, normal='Y', ind=midx ,clim=(-1e-3, wr.max()))
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plt.title('Distance weighting')
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plt.xlabel('x');plt.ylabel('z')
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plt.gca().set_aspect('equal', adjustable='box')
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reg = Regularization.Sparse(mesh, indActive=actv, mapping = staticCells)
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reg.mref = driver.mref[dynamic]
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reg.cell_weights = wr
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#reg.mref = np.zeros(mesh.nC)
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#eps_p = 5e-5
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#eps_q = 5e-5
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#norms = [0., 1., 1., 1.]
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opt = Optimization.ProjectedGNCG(maxIter=100 ,lower=driver.bounds[0],upper=driver.bounds[1], maxIterLS = 20, maxIterCG= 10, tolCG = 1e-3)
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invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
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#beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
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#update_beta = Directives.Scale_Beta(tol = 0.05, coolingRate=5)
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betaest = Directives.BetaEstimate_ByEig()
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IRLS = Directives.Update_IRLS( norms=driver.lpnorms, eps=driver.eps, f_min_change = 1e-3, minGNiter=6)
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update_Jacobi = Directives.Update_lin_PreCond()
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inv = Inversion.BaseInversion(invProb, directiveList=[IRLS,betaest,update_Jacobi])
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# Run inversion
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mrec = inv.run(mstart)
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pred = prob.fields(mrec)
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#%% Plot obs data
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PF.Magnetics.plot_obs_2D(rxLoc,pred,'Predicted Data')
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PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
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print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) )
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#%% Plot out a section of the model
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yslice = midx
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m_out = actvMap*staticCells*reg.l2model
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m_out[m_out==-100] = np.nan
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# Write result
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Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2.sus',m_out)
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plt.figure()
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ax = plt.subplot(221)
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mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (mrec.min(), mrec.max()))
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plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
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plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
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plt.xlabel('x');plt.ylabel('z')
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plt.gca().set_aspect('equal', adjustable='box')
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ax = plt.subplot(222)
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mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (mrec.min(), mrec.max()))
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plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
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plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
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plt.xlabel('x');plt.ylabel('z')
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plt.gca().set_aspect('equal', adjustable='box')
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ax = plt.subplot(212)
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mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (mrec.min(), mrec.max()))
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plt.title('Cross Section')
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plt.xlabel('x');plt.ylabel('z')
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plt.gca().set_aspect('equal', adjustable='box')
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plt.figure()
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ax = plt.subplot(121)
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plt.hist(reg.l2model,100)
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plt.yscale('log', nonposy='clip')
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plt.title('Histogram of model values - Smooth')
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ax = plt.subplot(122)
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plt.hist(reg.regmesh.cellDiffxStencil*(staticCells*reg.l2model),100)
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plt.yscale('log', nonposy='clip')
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plt.title('Histogram of model gradient values - Smooth')
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#%% Plot out a section of the model
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yslice = midx+1
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m_out = actvMap*staticCells*mrec
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m_out[m_out==-100] = np.nan
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plt.figure()
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ax = plt.subplot(221)
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mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (mrec.min(), mrec.max()))
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plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
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plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
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plt.xlabel('x');plt.ylabel('z')
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plt.gca().set_aspect('equal', adjustable='box')
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ax = plt.subplot(222)
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mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (mrec.min(), mrec.max()))
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plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
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plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
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plt.xlabel('x');plt.ylabel('z')
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plt.gca().set_aspect('equal', adjustable='box')
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ax = plt.subplot(212)
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mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (mrec.min(), mrec.max()))
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plt.title('Cross Section')
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plt.xlabel('x');plt.ylabel('z')
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plt.gca().set_aspect('equal', adjustable='box')
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plt.figure()
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ax = plt.subplot(121)
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plt.hist(mrec,100)
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plt.yscale('log', nonposy='clip')
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plt.title('Histogram of model values - Compact')
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ax = plt.subplot(122)
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plt.hist(reg.regmesh.cellDiffxStencil*(staticCells*mrec),100)
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plt.yscale('log', nonposy='clip')
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plt.title('Histogram of model gradient values - Smooth')
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plt.show()
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