mirror of
https://github.com/wassname/simpeg.git
synced 2026-07-01 01:10:15 +08:00
Rowan Cockett
220 lines
6.4 KiB
Python
220 lines
6.4 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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driver = PF.MagneticsIO.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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beta_in = 1e+5
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eps_p = 1e-4
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eps_q = 1e-4
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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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# Creat reduced identity map
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idenMap = Maps.IdentityMap(nP = nC)
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# Load starting model file
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mstart = driver.m0
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# Load reference file
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mref = driver.mref
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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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# Get distance weighting function
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#==============================================================================
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# wr = PF.Magnetics.get_dist_wgt(mesh,rxLoc,actv,3.,np.min(mesh.hx)/4)
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# #wrMap = PF.BaseMag.WeightMap(nC, wr)
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#==============================================================================
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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.MagneticIntegral(mesh, mapping=idenMap, actInd=actv)
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prob.solverOpts['accuracyTol'] = 1e-4
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survey.pair(prob)
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#survey.makeSyntheticData(data, std=0.01)
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#survey.dobs=d
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#survey.mtrue = model
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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 / mesh.vol[actv]
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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.Simple(mesh, indActive=actv, mapping=idenMap)
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reg.mref = mref
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reg.wght = wr
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#reg.alpha_s = 1.
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# Create pre-conditioner
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diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
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PC = Utils.sdiag(diagA**-1.)
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dmis = DataMisfit.l2_DataMisfit(survey)
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dmis.Wd = 1/wd
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opt = Optimization.ProjectedGNCG(maxIter=10,lower=0.,upper=1., maxIterCG= 20, tolCG=1e-3)
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opt.approxHinv = PC
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# opt = Optimization.InexactGaussNewton(maxIter=6)
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invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=beta_in)
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beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
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#betaest = Directives.BetaEstimate_ByEig()
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target = Directives.TargetMisfit()
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inv = Inversion.BaseInversion(invProb, directiveList=[beta,target])
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m0 = mstart
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# Run inversion
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mrec = inv.run(m0)
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m_out = actvMap*mrec
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# Write result
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Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2.sus',m_out)
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#Utils.meshutils.writeUBCTensorModel(home_dir+dsep+'wr.dat',mesh,wr_out)
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# Plot predicted
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pred = prob.fields(mrec)
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#PF.Magnetics.plot_obs_2D(rxLoc,pred,wd,'Predicted Data')
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#PF.Magnetics.plot_obs_2D(rxLoc,(d-pred),wd,'Residual 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[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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#%% Run one more round for sparsity
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phim = invProb.phi_m_last
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phid = invProb.phi_d
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reg = Regularization.Sparse(mesh, indActive = actv, mapping = idenMap)
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reg.recModel = mrec
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reg.mref = mref
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reg.wght = wr
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reg.eps_p = eps_p
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reg.eps_q = eps_q
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reg.norms = driver.lpnorms
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diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
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PC = Utils.sdiag(diagA**-1.)
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#reg.alpha_s = 1.
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dmis = DataMisfit.l2_DataMisfit(survey)
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dmis.Wd = wd
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opt = Optimization.ProjectedGNCG(maxIter=20 ,lower=0.,upper=1., maxIterCG= 10, tolCG = 1e-4)
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opt.approxHinv = PC
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#opt.phim_last = reg.eval(mrec)
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# opt = Optimization.InexactGaussNewton(maxIter=6)
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invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = invProb.beta)
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beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
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update_beta = Directives.Scale_Beta(tol = 0.05)
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#betaest = Directives.BetaEstimate_ByEig()
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target = Directives.TargetMisfit()
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IRLS =Directives.Update_IRLS( phi_m_last = phim, phi_d_last = phid )
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inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS,update_beta])
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m0 = mrec
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# Run inversion
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mrec = inv.run(m0)
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m_out = actvMap*mrec
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Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l0l2.sus',m_out)
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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[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.show()
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