#%% from SimPEG import * import simpegPF as PF import pylab as plt import os #home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\SimPEG\simpegpf\simpegPF\Dev' #home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\ownCloud\\Research\\Modelling\\Synthetic\\Nut_Cracker\\Induced_MAG3C' home_dir = '.\\' #home_dir = '.\\' inpfile = 'PYMAG3D_inv.inp' dsep = '\\' os.chdir(home_dir) ## New scripts to be added to basecode #from fwr_MAG_data import fwr_MAG_data #from read_MAGfwr_inp import read_MAGfwr_inp #%% # Read input file [mshfile, obsfile, topofile, mstart, mref, magfile, wgtfile, chi, alphas, bounds, lpnorms] = PF.Magnetics.read_MAGinv_inp(home_dir + dsep + inpfile) # Load mesh file mesh = Mesh.TensorMesh.readUBC(mshfile) #mesh = Utils.meshutils.readUBCTensorMesh(mshfile) # Load in observation file survey = PF.Magnetics.readUBCmagObs(obsfile) rxLoc = survey.srcField.rxList[0].locs d = survey.dobs wd = survey.std ndata = survey.srcField.rxList[0].locs.shape[0] beta_in = 1e+5 # Load in topofile or create flat surface if topofile == 'null': # All active actv = np.asarray(range(mesh.nC)) else: topo = np.genfromtxt(topofile,skip_header=1) # Find the active cells actv = PF.Magnetics.getActiveTopo(mesh,topo,'N') nC = len(actv) # Create active map to go from reduce set to full actvMap = Maps.ActiveCells(mesh, actv, -100) # Creat reduced identity map idenMap = Maps.IdentityMap(nP = nC) # Load starting model file if isinstance(mstart, float): mstart = np.ones(nC) * mstart else: mstart = Utils.meshutils.readUBCTensorModel(mstart,mesh) mstart = mstart[actv] # Load reference file if isinstance(mref, float): mref = np.ones(nC) * mref else: mref = Utils.meshutils.readUBCTensorModel(mref,mesh) mref = mref[actv] # Get magnetization vector for MOF if magfile=='DEFAULT': M_xyz = PF.Magnetics.dipazm_2_xyz(np.ones(nC) * survey.srcField.param[1], np.ones(nC) * survey.srcField.param[2]) else: M_xyz = np.genfromtxt(magfile,delimiter=' \n',dtype=np.str,comments='!') # Get index of the center midx = int(mesh.nCx/2) midy = int(mesh.nCy/2) # Get distance weighting function #============================================================================== # wr = PF.Magnetics.get_dist_wgt(mesh,rxLoc,actv,3.,np.min(mesh.hx)/4) # #wrMap = PF.BaseMag.WeightMap(nC, wr) #============================================================================== #%% Plot obs data PF.Magnetics.plot_obs_2D(rxLoc,d,wd,'Observed Data') #%% Run inversion prob = PF.Magnetics.MagneticIntegral(mesh, mapping = idenMap, actInd = actv) prob.solverOpts['accuracyTol'] = 1e-4 #survey = Survey.LinearSurvey() survey.pair(prob) #survey.makeSyntheticData(data, std=0.01) #survey.dobs=d #survey.mtrue = model # Write out the predicted pred = prob.fields(mstart) PF.Magnetics.writeUBCobs(home_dir + dsep + 'Pred.dat',survey,pred) wr = np.sum(prob.G**2.,axis=0)**0.5 wr = ( wr/np.max(wr) ) wr_out = actvMap * wr plt.figure() ax = plt.subplot() mesh.plotSlice(wr_out, ax = ax, normal = 'Y', ind=midx ,clim = (-1e-3, wr.max())) plt.title('Distance weighting') plt.xlabel('x');plt.ylabel('z') plt.gca().set_aspect('equal', adjustable='box') reg = Regularization.Simple(mesh, indActive = actv, mapping = idenMap) reg.mref = mref reg.wght = wr #reg.alpha_s = 1. # Create pre-conditioner diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()*wr PC = Utils.sdiag(diagA**-1.) dmis = DataMisfit.l2_DataMisfit(survey) dmis.Wd = 1/wd opt = Optimization.ProjectedGNCG(maxIter=10,lower=0.,upper=1., maxIterCG= 20, tolCG = 1e-3) opt.approxHinv = PC # opt = Optimization.InexactGaussNewton(maxIter=6) invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = beta_in) beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1) #betaest = Directives.BetaEstimate_ByEig() target = Directives.TargetMisfit() inv = Inversion.BaseInversion(invProb, directiveList=[beta,target]) m0 = mstart # Run inversion mrec = inv.run(m0) m_out = actvMap*mrec # Write result Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2.sus',m_out) #Utils.meshutils.writeUBCTensorModel(home_dir+dsep+'wr.dat',mesh,wr_out) # Plot predicted pred = prob.fields(mrec) #PF.Magnetics.plot_obs_2D(rxLoc,pred,wd,'Predicted Data') #PF.Magnetics.plot_obs_2D(rxLoc,(d-pred),wd,'Residual Data') print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) ) #%% Plot out a section of the model yslice = midx plt.figure() ax = plt.subplot(221) mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (-1e-3, mrec.max())) plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--') plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m') plt.xlabel('x');plt.ylabel('z') plt.gca().set_aspect('equal', adjustable='box') ax = plt.subplot(222) mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (-1e-3, mrec.max())) plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--') plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m') plt.xlabel('x');plt.ylabel('z') plt.gca().set_aspect('equal', adjustable='box') ax = plt.subplot(212) mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (-1e-3, mrec.max())) plt.title('Cross Section') plt.xlabel('x');plt.ylabel('z') plt.gca().set_aspect('equal', adjustable='box') #%% Run one more round for sparsity phim = invProb.phi_m_last phid = invProb.phi_d reg = Regularization.Sparse(mesh, indActive = actv, mapping = idenMap) reg.recModel = mrec reg.mref = mref reg.wght = wr reg.eps = 1e-5 reg.p = lpnorms[0] reg.qx = lpnorms[1] reg.qz = lpnorms[2] reg.qy = lpnorms[3] diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()*(wr) PC = Utils.sdiag(diagA**-1.) #reg.alpha_s = 1. dmis = DataMisfit.l2_DataMisfit(survey) dmis.Wd = wd opt = Optimization.ProjectedGNCG(maxIter=10 ,lower=0.,upper=1., maxIterCG= 10, tolCG = 1e-4) opt.approxHinv = PC #opt.phim_last = reg.eval(mrec) # opt = Optimization.InexactGaussNewton(maxIter=6) invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = invProb.beta) beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1) #betaest = Directives.BetaEstimate_ByEig() target = Directives.TargetMisfit() IRLS =Directives.update_IRLS( phi_m_last = phim, phi_d_last = phid ) inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS]) m0 = mrec # Run inversion mrec = inv.run(m0) m_out = actvMap*mrec Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l0l2.sus',m_out) pred = prob.fields(mrec) #%% Plot obs data PF.Magnetics.plot_obs_2D(rxLoc,pred,wd,'Predicted Data') PF.Magnetics.plot_obs_2D(rxLoc,d,wd,'Observed Data') print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) ) #%% Plot out a section of the model yslice = midx plt.figure() ax = plt.subplot(221) mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (-1e-3, mrec.max())) plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--') plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m') plt.xlabel('x');plt.ylabel('z') plt.gca().set_aspect('equal', adjustable='box') ax = plt.subplot(222) mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (-1e-3, mrec.max())) plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--') plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m') plt.xlabel('x');plt.ylabel('z') plt.gca().set_aspect('equal', adjustable='box') ax = plt.subplot(212) mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (-1e-3, mrec.max())) plt.title('Cross Section') plt.xlabel('x');plt.ylabel('z') plt.gca().set_aspect('equal', adjustable='box')