mirror of
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Add driver for gravity. Adapt example for new Regularization formulation
This commit is contained in:
D Fournier
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@@ -5,72 +5,39 @@ import pylab as plt
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import os
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home_dir = '.'
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inpfile = 'PYGRAV3D_inv.inp'
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#inpfile = 'PYGRAV3D_inv.inp'
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dsep = os.path.sep
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plt.close('all')
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#%% User input
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# Treshold values for compact norm
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eps_p = 1e-3 # Small model values
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eps_q = 1e-3 # Small model gradient
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# Plotting parameter
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vmin = -0.3
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vmax = 0.3
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#%%
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# Read input file
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[mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms] = PF.Gravity.read_GRAVinv_inp(home_dir + dsep + inpfile)
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#[mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms] = PF.Gravity.read_GRAVinv_inp(home_dir + dsep + inpfile)
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driver = PF.GravityDriver.GravityDriver_Inv('PYGRAV3D_inv.inp')
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mesh = driver.mesh
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survey = driver.survey
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# Load mesh file
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mesh = Mesh.TensorMesh.readUBC(mshfile)
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# Load in observation file
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survey = PF.Gravity.readUBCgravObs(obsfile)
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# Get obs location and data
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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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# Load in topofile or create flat surface
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if topofile == 'null':
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# All active
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actv = np.asarray(range(mesh.nC))
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else:
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topo = np.genfromtxt(topofile,skip_header=1)
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# Find the active cells
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actv = PF.Magnetics.getActiveTopo(mesh,topo,'N')
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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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# Create reduced identity map
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idenMap = Maps.IdentityMap(nP=nC)
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# Load starting model file
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if isinstance(mstart, float):
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mstart = np.ones(nC) * mstart
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else:
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mstart = Mesh.TensorMesh.readModelUBC(mesh,mstart)
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mstart = mstart[actv]
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# Load reference file
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if isinstance(mref, float):
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mref = np.ones(nC) * mref
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else:
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mref = Mesh.TensorMesh.readModelUBC(mesh,mref)
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mref = mref[actv]
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# Get index of the center for plotting
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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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@@ -85,60 +52,53 @@ prob.solverOpts['accuracyTol'] = 1e-4
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survey.pair(prob)
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# Write out the predicted file and generate the forward operator
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pred = prob.fields(mstart)
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pred = prob.fields(driver.m0)
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PF.Gravity.writeUBCobs(home_dir + dsep + 'Pred0.dat',survey,pred)
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#
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# Make depth weighting
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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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# Load weighting file
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if wgtfile is None:
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if driver.wgtfile == 'DEFAULT':
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wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, 3., np.min(mesh.hx)/4.)
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wr = wr**2.
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# Make depth weighting
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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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else:
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wr = Mesh.TensorMesh.readModelUBC(mesh, home_dir + dsep + wgtfile)
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wr = wr[actv]
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wr = wr**2.
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#%% Plot depth weighting
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plt.figure()
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ax = plt.subplot()
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mesh.plotSlice(actvMap*wr, ax = ax, normal = 'Y', ind=midx+1 ,clim = (0, 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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#plt.figure()
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#ax = plt.subplot()
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#mesh.plotSlice(actvMap*wr, ax = ax, normal = 'Y', ind=midx+1 ,clim = (0, 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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#%% Create inversion objects
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# First start with an l2 regularization
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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 = Regularization.Sparse(mesh, indActive=actv, mapping=idenMap)
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reg.mref = driver.mref
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reg.cell_weights = wr*mesh.vol[actv]
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# Data misfit function
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opt = Optimization.ProjectedGNCG(maxIter=100 ,lower=-2.,upper=2., maxIterLS = 20, maxIterCG= 10, tolCG = 1e-3)
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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=20,lower=bounds[0],upper=bounds[1], maxIterCG= 50, tolCG = 1e-4)
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invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
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# Add directives to the inversion
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beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
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beta_init = Directives.BetaEstimate_ByEig()
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target = Directives.TargetMisfit()
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update_Jacobi = Directives.Update_lin_PreCond(onlyOnStart=True)
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inv = Inversion.BaseInversion(invProb, directiveList=[beta,target,beta_init,update_Jacobi])
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m0 = mstart
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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_p=driver.eps[0], eps_q=driver.eps[1], f_min_change = 1e-2)
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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(m0)
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mrec = inv.run(driver.m0)
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m_out = actvMap*mrec
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@@ -152,109 +112,73 @@ pred = prob.fields(mrec)
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print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) )
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#%% Plot out sections of the smooth model
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yslice = midx+1
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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 = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
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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 = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
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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 = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
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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 - Smooth')
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ax = plt.subplot(122)
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plt.hist(reg.regmesh.cellDiffxStencil*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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#%% 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 = lpnorms
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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=20 , maxIterLS = 20,lower=bounds[0],upper=bounds[1], maxIterCG= 50, tolCG = 1e-4)
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invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = invProb.beta)
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# Add directives to the inversion
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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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target = Directives.TargetMisfit()
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IRLS =Directives.Update_IRLS( phi_m_last = phim, phi_d_last = phid )
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update_Jacobi = Directives.Update_lin_PreCond(onlyOnStart=False)
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save_log = Directives.SaveOutputEveryIteration()
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save_log.fileName = 'LogName_blabla'
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inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS,update_beta,update_Jacobi,save_log])
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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', vmin = np.min(d), vmax = np.max(d))
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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*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()), pcolorOpts = {'cmap':'bwr'})
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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()), pcolorOpts = {'cmap':'bwr'})
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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*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
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m_out = actvMap*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()), pcolorOpts = {'cmap':'bwr'})
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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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@@ -263,8 +187,10 @@ 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 - Sparse lp:'+str(lpnorms[0]))
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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*mrec,100)
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plt.yscale('log', nonposy='clip')
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plt.title('Histogram of model gradient values - Sparse lqx: ' + str(lpnorms[1]) + ' lqy:'+ str(lpnorms[2]) + ' lqz:' + str(lpnorms[3]))
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plt.title('Histogram of model gradient values - Compact')
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plt.show()
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@@ -5,10 +5,13 @@ import pylab as plt
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import os
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import numpy as np
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#home_dir = 'C:\Egnyte\Private\craigm\PHD\LdM\Gravity\Bouguer\SIMPEG\models'
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home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\SimPEG\simpegpf\simpegPF\Dev\GRAV'
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#inpfile = 'PYGRAV3D_inv_LdM_Craig.inp'
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inpfile = 'PYGRAV3D_inv_checkerboard.inp'
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#home_dir = 'C:\Egnyte\Private\craigm\PHD\LdM\Gravity\Bouguer\SIMPEG\models\\all_models\\density_-1.2_0.3'
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home_dir = '.\\'
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inpfile = 'PYGRAV3D_inv_LdM_Craig.inp'
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#inpfile = 'PYGRAV3D_inv_checkerboard.inp'
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dsep = '\\'
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os.chdir(home_dir)
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plt.close('all')
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@@ -17,66 +20,35 @@ plt.close('all')
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# Initial beta
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beta_in = 1e-2
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# Treshold values for compact norm
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eps_p = 0.01 # Compact model values
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eps_q = 0.01 # ompact model gradient
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# Plotting parameter
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vmin = -0.1
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vmax = 0.2
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vmin = -1.2
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vmax = 1.2
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#weight exponent for default weighting
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wgtexp = 3. #dont forget the "."
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#%%
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# Read input file
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[mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms] = PF.Gravity.read_GRAVinv_inp(home_dir + dsep + inpfile)
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driver = PF.GravityDriver.GravityDriver_Inv(home_dir + dsep + 'PYGRAV3D_inv.inp')
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mesh = driver.mesh
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||||
survey = driver.survey
|
||||
|
||||
# Load mesh file
|
||||
mesh = Mesh.TensorMesh.readUBC(mshfile)
|
||||
|
||||
# Load in observation file
|
||||
survey = PF.Gravity.readUBCgravObs(obsfile)
|
||||
|
||||
# Get obs location and data
|
||||
rxLoc = survey.srcField.rxList[0].locs
|
||||
d = survey.dobs
|
||||
wd = survey.std
|
||||
|
||||
|
||||
ndata = survey.srcField.rxList[0].locs.shape[0]
|
||||
|
||||
# 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')
|
||||
|
||||
actv = driver.activeCells
|
||||
nC = len(actv)
|
||||
|
||||
# Create active map to go from reduce set to full
|
||||
actvMap = Maps.InjectActiveCells(mesh, actv, -100)
|
||||
|
||||
# Creat reduced identity map
|
||||
idenMap = Maps.IdentityMap(nP = nC)
|
||||
# Create reduced identity map
|
||||
idenMap = Maps.IdentityMap(nP=nC)
|
||||
|
||||
# Load starting model file
|
||||
if isinstance(mstart, float):
|
||||
|
||||
mstart = np.ones(nC) * mstart
|
||||
else:
|
||||
mstart = Mesh.TensorMesh.readModelUBC(mesh,mstart)
|
||||
mstart = mstart[actv]
|
||||
|
||||
# Load reference file
|
||||
if isinstance(mref, float):
|
||||
mref = np.ones(nC) * mref
|
||||
else:
|
||||
mref = Mesh.TensorMesh.readModelUBC(mesh,mref)
|
||||
mref = mref[actv]
|
||||
|
||||
# Get index of the center for plotting
|
||||
# Get index of the center
|
||||
midx = int(mesh.nCx/2)
|
||||
midy = int(mesh.nCy/2)
|
||||
|
||||
@@ -91,24 +63,11 @@ prob.solverOpts['accuracyTol'] = 1e-4
|
||||
survey.pair(prob)
|
||||
|
||||
# Write out the predicted file and generate the forward operator
|
||||
pred = prob.fields(mstart)
|
||||
|
||||
PF.Gravity.writeUBCobs(home_dir + dsep + 'Pred0.dat',survey,pred)
|
||||
|
||||
# Make depth weighting
|
||||
#wr = np.sum(prob.G**2.,axis=0)**0.5 / mesh.vol[actv]
|
||||
#wr = ( wr/np.max(wr) )
|
||||
#wr_out = actvMap * wr
|
||||
|
||||
|
||||
#A different weighting function from Dominic
|
||||
#wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, 2., np.min(mesh.hx)/4.)
|
||||
#wr = wr**2.
|
||||
|
||||
pred = prob.fields(driver.m0)
|
||||
|
||||
# Load weighting file
|
||||
if wgtfile is None:
|
||||
wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, 2., np.min(mesh.hx)/4.)
|
||||
if driver.wgtfile == 'DEFAULT':
|
||||
wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, wgtexp, np.min(mesh.hx)/4.)
|
||||
wr = wr**2.
|
||||
else:
|
||||
wr = Mesh.TensorMesh.readModelUBC(mesh, home_dir + dsep + wgtfile)
|
||||
@@ -119,205 +78,198 @@ else:
|
||||
|
||||
#%% Plot depth weighting
|
||||
plt.figure()
|
||||
ax = plt.subplot()
|
||||
datwgt=mesh.plotSlice(actvMap*wr, ax = ax, normal = 'Y', ind=midx+1 ,clim = (-1e-1, wr.max()))
|
||||
ax = plt.subplot(211)
|
||||
datwgt=mesh.plotSlice(actvMap*wr, ax = ax, normal = 'Y', ind=midx+1 ,clim = (-1e-1, wr.max()), pcolorOpts={'cmap':'jet'})
|
||||
plt.title('Distance weighting')
|
||||
plt.xlabel('x');plt.ylabel('z')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(datwgt[0],orientation="vertical")
|
||||
cb.set_label('Weighting')
|
||||
plt.savefig(home_dir + dsep + 'Weighting.png', dpi=300)
|
||||
|
||||
ax=plt.subplot(212)
|
||||
plt.hist(wr,bins=100)
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.title('Distribution of weights')
|
||||
plt.tight_layout()
|
||||
plt.savefig(home_dir + dsep + 'Weighting_' +str(wgtexp) +'.png', dpi=300)
|
||||
|
||||
#%% Create inversion objects
|
||||
|
||||
print '\nRun smooth inversion \n'
|
||||
# First start with an l2 (smooth model) regularization
|
||||
reg = Regularization.Simple(mesh, indActive = actv, mapping = idenMap)
|
||||
reg.mref = mref
|
||||
reg.wght = wr
|
||||
reg = Regularization.Sparse(mesh, indActive=actv, mapping=idenMap)
|
||||
reg.mref = driver.mref
|
||||
reg.cell_weights = wr*mesh.vol[actv]
|
||||
eps_p = driver.eps[0]
|
||||
eps_q = driver.eps[1]
|
||||
|
||||
|
||||
|
||||
# Create pre-conditioner
|
||||
diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
|
||||
PC = Utils.sdiag(diagA**-1.)
|
||||
|
||||
# Data misfit function
|
||||
opt = Optimization.ProjectedGNCG(maxIter=100 ,lower=-2.,upper=2., maxIterLS = 20, maxIterCG= 10, tolCG = 1e-3)
|
||||
dmis = DataMisfit.l2_DataMisfit(survey)
|
||||
dmis.Wd = 1./wd
|
||||
opt = Optimization.ProjectedGNCG(maxIter=20,lower=bounds[0],upper=bounds[1], maxIterCG= 20, tolCG = 1e-3)
|
||||
opt.approxHinv = PC
|
||||
|
||||
|
||||
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = beta_in)
|
||||
beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
|
||||
target = Directives.TargetMisfit()
|
||||
|
||||
inv = Inversion.BaseInversion(invProb, directiveList=[beta,target])
|
||||
|
||||
m0 = mstart
|
||||
invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
|
||||
#beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
|
||||
#update_beta = Directives.Scale_Beta(tol = 0.05, coolingRate=5)
|
||||
betaest = Directives.BetaEstimate_ByEig()
|
||||
IRLS = Directives.Update_IRLS( norms=driver.lpnorms, eps_p=eps_p, eps_q=eps_q, f_min_change = 1e-2)
|
||||
update_Jacobi = Directives.Update_lin_PreCond()
|
||||
inv = Inversion.BaseInversion(invProb, directiveList=[IRLS,betaest,update_Jacobi])
|
||||
|
||||
# Run inversion
|
||||
mrec = inv.run(m0)
|
||||
mrec = inv.run(driver.m0)
|
||||
|
||||
m_out = actvMap*reg.l2model
|
||||
|
||||
m_out = actvMap*mrec
|
||||
|
||||
# Write result
|
||||
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2.den',m_out)
|
||||
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2_' +str(wgtexp) + '.den', m_out)
|
||||
#Utils.meshutils.writeUBCTensorModel(home_dir+dsep+'wr.dat',mesh,wr_out)
|
||||
|
||||
# Plot predicted
|
||||
|
||||
|
||||
pred_compact = prob.fields(mrec)
|
||||
PF.Gravity.writeUBCobs(home_dir + dsep + 'Pred_compact' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.dat',survey,pred_compact)
|
||||
|
||||
pred = prob.fields(mrec)
|
||||
# Plot predicted
|
||||
#pred_smooth = prob.fields(mrec)
|
||||
#PF.Gravity.writeUBCobs(home_dir + dsep + 'Pred_smooth' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.dat',survey,pred_smooth)
|
||||
#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. ) )
|
||||
print "Misfit sum(obs-calc)/nobs: %.3f mGal" %np.divide(np.sum(np.abs(d-pred)), len(d))
|
||||
print "RMS misfit: %.3f mGal" %np.sqrt(np.divide(np.sum((d-pred)**2),len(d)))
|
||||
|
||||
#%% Plot out sections of the smooth model
|
||||
|
||||
yslice = midx+1
|
||||
m_out[m_out==-100]=np.nan # set "air" to nan
|
||||
|
||||
print "\nMax density:" + str(np.nanmax(m_out))
|
||||
print "\nMin density:" + str(np.nanmin(m_out))
|
||||
|
||||
plt.figure(figsize=(15,10))
|
||||
plt.suptitle('Smooth Inversion')
|
||||
plt.suptitle('Smooth Inversion: Depth weight = ' + str(wgtexp))
|
||||
ax = plt.subplot(221)
|
||||
dat1=mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (vmin,vmax))
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='w',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
|
||||
dat1=mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-10, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='gray',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='k',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-10]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (kg/m3)')
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
ax = plt.subplot(222)
|
||||
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (vmin,vmax))
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='w',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
|
||||
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-13, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='gray',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='k',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-13]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (kg/m3)')
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
ax = plt.subplot(212)
|
||||
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax))
|
||||
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.title('Cross Section')
|
||||
plt.xlabel('Easting(m)');plt.ylabel('Elevation')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (kg/m3)')
|
||||
plt.savefig(home_dir + str('\Figure1.png'), dpi=300, bb_inches='tight')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4), cmap='bwr')
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
plt.savefig(home_dir + str('\Figure1_' +str(wgtexp) + '.png'), dpi=300, bb_inches='tight')
|
||||
|
||||
#plot histograms
|
||||
plt.figure(figsize=(15,10))
|
||||
ax = plt.subplot(121)
|
||||
plt.hist(reg.l2model,100)
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.xlim(reg.l2model.mean() - 6.*(reg.l2model.std()), reg.l2model.mean() + 6.*(reg.l2model.std()))
|
||||
plt.xlabel('Density (g/cc$^3$)')
|
||||
plt.title('Histogram of model values - Smooth')
|
||||
|
||||
ax = plt.subplot(122)
|
||||
plt.hist(reg.regmesh.cellDiffxStencil*reg.l2model,100)
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.xlim(reg.l2model.mean() - 2.*(reg.l2model.std()), reg.l2model.mean() + 2.*(reg.l2model.std()))
|
||||
plt.xlabel('Density (g/cc$^3$)')
|
||||
plt.title('Histogram of model gradient values - Smooth')
|
||||
plt.savefig(home_dir + str('\Figure2_' +str(wgtexp) + '.png'), dpi=300, bb_inches='tight')
|
||||
|
||||
|
||||
|
||||
#%% Plot obs data
|
||||
PF.Magnetics.plot_obs_2D(rxLoc,pred_compact,'Predicted Data', vmin = np.min(d), vmax = np.max(d))
|
||||
plt.savefig(home_dir + str('\Figure3_' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.png'), dpi=300, bb_inches='tight')
|
||||
PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
|
||||
plt.savefig(home_dir + str('\Figure4.png'), dpi=300, bb_inches='tight')
|
||||
print "\nFinal misfit:" + str(np.sum( ((d-pred_compact)/wd)**2. ) )
|
||||
print "Misfit sum(obs-calc)/nobs: %.3f mGal" %np.divide(np.sum(np.abs(d-pred_compact)), len(d))
|
||||
print "RMS misfit: %.3f mGal" %np.sqrt(np.divide(np.sum((d-pred_compact)**2),len(d)))
|
||||
|
||||
|
||||
|
||||
#%% Plot out a section of the compact model
|
||||
m_out = actvMap*mrec
|
||||
|
||||
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l0l2_' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.den',m_out)
|
||||
|
||||
yslice = midx
|
||||
m_out[m_out==-100]=np.nan # set "air" to nan
|
||||
|
||||
print "\nMax density:" + str(np.nanmax(m_out))
|
||||
print "\nMin density:" + str(np.nanmin(m_out))
|
||||
|
||||
plt.figure(figsize=(15,10))
|
||||
plt.suptitle('Compact Inversion: Depth weight = ' + str(wgtexp) + ': $\epsilon_p$ = ' + str(eps_p) + ': $\epsilon_q$ = ' + str(eps_q))
|
||||
ax = plt.subplot(221)
|
||||
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-10, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='gray',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='k',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-10]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
ax = plt.subplot(222)
|
||||
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-13, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='gray',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='k',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-13]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
ax = plt.subplot(212)
|
||||
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.title('Cross Section')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Elevation (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
plt.savefig(home_dir + str('\Figure5_' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.png'), dpi=300, bb_inches='tight')
|
||||
|
||||
#plot histograms
|
||||
plt.figure(figsize=(15,10))
|
||||
ax = plt.subplot(121)
|
||||
plt.hist(mrec,100)
|
||||
#plt.xlim(mrec.mean() - 6.*(mrec.std()), mrec.mean() + 6.*(mrec.std()))
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
|
||||
plt.title('Histogram of model values - Smooth')
|
||||
plt.xlabel('Density (g/cc$^3$)')
|
||||
plt.title('Histogram of model values - Sparse lp:'+str(driver.lpnorms[0]))
|
||||
|
||||
ax = plt.subplot(122)
|
||||
plt.hist(reg.regmesh.cellDiffxStencil*mrec,100)
|
||||
|
||||
#plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
|
||||
plt.xlabel('Density (g/cc$^3$)')
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
|
||||
plt.title('Histogram of model gradient values - Smooth')
|
||||
plt.savefig(home_dir + str('\Figure2.png'), dpi=300, bb_inches='tight')
|
||||
#%% Run one more round for sparsity (Compact model)
|
||||
print '\nRun compact inversion \n'
|
||||
phim = invProb.phi_m_last
|
||||
phid = invProb.phi_d
|
||||
plt.title('Histogram of model gradient values - Sparse lqx: ' + str(driver.lpnorms[1]) + ' lqy:'+ str(driver.lpnorms[2]) + ' lqz:' + str(driver.lpnorms[3]))
|
||||
plt.savefig(home_dir + str('\Figure6_' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.png'), dpi=300, bb_inches='tight')
|
||||
|
||||
reg = Regularization.Sparse(mesh, indActive = actv, mapping = idenMap)
|
||||
reg.recModel = mrec
|
||||
reg.mref = mref
|
||||
reg.wght = wr
|
||||
reg.eps_p = eps_p
|
||||
reg.eps_q = eps_q
|
||||
reg.norms = lpnorms
|
||||
|
||||
diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
|
||||
PC = Utils.sdiag(diagA**-1.)
|
||||
|
||||
#reg.alpha_s = 1.
|
||||
|
||||
dmis = DataMisfit.l2_DataMisfit(survey)
|
||||
dmis.Wd = 1./wd
|
||||
opt = Optimization.ProjectedGNCG(maxIter=10 ,lower=bounds[0],upper=bounds[1], maxIterCG= 25, 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.den',m_out)
|
||||
|
||||
pred = prob.fields(mrec)
|
||||
|
||||
#%% Plot obs data
|
||||
PF.Magnetics.plot_obs_2D(rxLoc,pred,'Predicted Data', vmin = np.min(d), vmax = np.max(d))
|
||||
plt.savefig(home_dir + str('\Figure3.png'), dpi=300, bb_inches='tight')
|
||||
PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
|
||||
plt.savefig(home_dir + str('\Figure4.png'), dpi=300, bb_inches='tight')
|
||||
print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) )
|
||||
#%% Plot out a section of the compact model
|
||||
|
||||
yslice = midx
|
||||
plt.figure(figsize=(15,10))
|
||||
plt.suptitle('Compact Inversion')
|
||||
ax = plt.subplot(221)
|
||||
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (vmin,vmax))
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='w',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (kg/m3)')
|
||||
|
||||
ax = plt.subplot(222)
|
||||
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (vmin,vmax))
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='w',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (kg/m3)')
|
||||
|
||||
ax = plt.subplot(212)
|
||||
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax))
|
||||
plt.title('Cross Section')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Elevation (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (kg/m3)')
|
||||
|
||||
plt.savefig(home_dir + str('\Figure5.png'), dpi=300, bb_inches='tight')
|
||||
|
||||
|
||||
plt.figure(figsize=(15,10))
|
||||
ax = plt.subplot(121)
|
||||
plt.hist(mrec,100)
|
||||
plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.title('Histogram of model values - Sparse lp:'+str(lpnorms[0]))
|
||||
|
||||
ax = plt.subplot(122)
|
||||
plt.hist(reg.regmesh.cellDiffxStencil*mrec,100)
|
||||
plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.title('Histogram of model gradient values - Sparse lqx: ' + str(lpnorms[1]) + ' lqy:'+ str(lpnorms[2]) + ' lqz:' + str(lpnorms[3]))
|
||||
plt.savefig(home_dir + str('\Figure6.png'), dpi=300, bb_inches='tight')
|
||||
#make a plot of the obs -calc, ie residual
|
||||
plt.figure(figsize=(10,8))
|
||||
residual = d - pred_compact
|
||||
plt.hist(residual, 100)
|
||||
plt.savefig(home_dir + str('\Figure7_residuals.png'), dpi=300, bb_inches='tight')
|
||||
@@ -0,0 +1,395 @@
|
||||
#%%
|
||||
from SimPEG import *
|
||||
import simpegPF as PF
|
||||
import pylab as plt
|
||||
import os
|
||||
import numpy as np
|
||||
|
||||
|
||||
|
||||
home_dir = 'C:\Egnyte\Private\craigm\PHD\LdM\Gravity\Bouguer\SIMPEG\models\surface_layer_model_-500'
|
||||
|
||||
inpfile = 'PYGRAV3D_inv_LdM_surface_layer_fixed.inp'
|
||||
|
||||
dsep = '\\'
|
||||
os.chdir(home_dir)
|
||||
plt.close('all')
|
||||
|
||||
#%% User input
|
||||
# Initial beta
|
||||
beta_in = 1e-2
|
||||
|
||||
# Treshold values for compact norm
|
||||
eps_p = 0.2# Compact model values #refer to histograms to choose appropriate value
|
||||
eps_q = 0.1 # Compact model gradient
|
||||
|
||||
# Plotting parameter
|
||||
vmin = -0.5
|
||||
vmax = 0.5
|
||||
|
||||
#weight exponent for default weighting
|
||||
wgtexp = 3. #dont forget the "."
|
||||
|
||||
#value of fixed cells
|
||||
|
||||
fixedcell = -0.5
|
||||
|
||||
#%%
|
||||
# Read input file
|
||||
[mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms] = PF.Gravity.read_GRAVinv_inp(home_dir + dsep + inpfile)
|
||||
|
||||
# Load mesh file
|
||||
mesh = Mesh.TensorMesh.readUBC(mshfile)
|
||||
|
||||
# Load in observation file
|
||||
survey = PF.Gravity.readUBCgravObs(obsfile)
|
||||
|
||||
# Get obs location and data
|
||||
rxLoc = survey.srcField.rxList[0].locs
|
||||
d = survey.dobs
|
||||
wd = survey.std
|
||||
|
||||
ndata = survey.srcField.rxList[0].locs.shape[0]
|
||||
|
||||
# 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.InjectActiveCells(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 = Mesh.TensorMesh.readModelUBC(mesh,mstart)
|
||||
mstart = mstart[actv]
|
||||
|
||||
# Extract cells under topography and create new index for inactive
|
||||
#m0 = Mesh.TensorMesh.readModelUBC(mesh, mstart)
|
||||
#m0 = m0[actv]
|
||||
ind_act = mstart!= fixedcell
|
||||
|
||||
actvCells = Maps.InjectActiveCells(None, ind_act, fixedcell, nC=nC)
|
||||
mstart = mstart[ind_act]
|
||||
|
||||
|
||||
# Load reference file
|
||||
if isinstance(mref, float):
|
||||
mref = np.ones(nC) * mref
|
||||
else:
|
||||
mref = Mesh.TensorMesh.readModelUBC(mesh,mref)
|
||||
mref = mref[actv]
|
||||
|
||||
mref = mref[ind_act]
|
||||
# Get index of the center for plotting
|
||||
midx = int(mesh.nCx/2)
|
||||
midy = int(mesh.nCy/2)
|
||||
|
||||
|
||||
#%% Plot obs data
|
||||
#PF.Gravity.plot_obs_2D(survey,'Observed Data')
|
||||
|
||||
#%% Run inversion
|
||||
prob = PF.Gravity.GravityIntegral(mesh, mapping = actvCells, actInd = actv)
|
||||
prob.solverOpts['accuracyTol'] = 1e-4
|
||||
|
||||
survey.pair(prob)
|
||||
|
||||
# Write out the predicted file and generate the forward operator
|
||||
pred_start = prob.fields(mstart)
|
||||
|
||||
#PF.Gravity.writeUBCobs(home_dir + dsep + 'Pred_start' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.dat',survey,pred_start)
|
||||
|
||||
# Make depth weighting
|
||||
#wr = np.sum(prob.G**2.,axis=0)**0.5 / mesh.vol[actv]
|
||||
#wr = ( wr/np.max(wr) )
|
||||
#wr_out = actvMap * wr
|
||||
|
||||
|
||||
#A different weighting function from Dominic
|
||||
#wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, 2., np.min(mesh.hx)/4.)
|
||||
#wr = wr**2.
|
||||
|
||||
|
||||
# Load weighting file
|
||||
if wgtfile is None:
|
||||
wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, wgtexp, np.min(mesh.hx)/4.)
|
||||
wr = wr**2.
|
||||
else:
|
||||
wr = Mesh.TensorMesh.readModelUBC(mesh, home_dir + dsep + wgtfile)
|
||||
wr = wr[actv]
|
||||
wr = wr**2.
|
||||
|
||||
|
||||
|
||||
#%% Plot depth weighting
|
||||
plt.figure()
|
||||
ax = plt.subplot(211)
|
||||
datwgt=mesh.plotSlice(actvMap*wr, ax = ax, normal = 'Y', ind=midx+1 ,clim = (-1e-1, wr.max()), pcolorOpts={'cmap':'jet'})
|
||||
plt.title('Distance weighting')
|
||||
plt.xlabel('x');plt.ylabel('z')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(datwgt[0],orientation="vertical")
|
||||
cb.set_label('Weighting')
|
||||
|
||||
ax=plt.subplot(212)
|
||||
plt.hist(wr,bins=100)
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.title('Distribution of weights')
|
||||
plt.tight_layout()
|
||||
plt.savefig(home_dir + dsep + 'Weighting_' +str(wgtexp) +'.png', dpi=300)
|
||||
|
||||
#%% Create inversion objects
|
||||
|
||||
print '\nRun smooth inversion \n'
|
||||
# First start with an l2 (smooth model) regularization
|
||||
reg = Regularization.Simple(mesh, indActive = actv, mapping = actvCells)
|
||||
reg.mref = mref
|
||||
reg.wght = wr
|
||||
|
||||
|
||||
|
||||
# Create pre-conditioner # should be without the *wr at the end but works better with it
|
||||
#diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
|
||||
#PC = Utils.sdiag(diagA**-1.)
|
||||
|
||||
# Data misfit function
|
||||
dmis = DataMisfit.l2_DataMisfit(survey)
|
||||
dmis.Wd = 1./wd
|
||||
opt = Optimization.ProjectedGNCG(maxIter=20,lower=bounds[0],upper=bounds[1], maxIterCG= 20, tolCG = 1e-3)
|
||||
#opt.approxHinv = PC
|
||||
|
||||
|
||||
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = beta_in)
|
||||
beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
|
||||
update_beta = Directives.Scale_Beta(tol = 0.05)
|
||||
target = Directives.TargetMisfit()
|
||||
update_Jacobi = Directives.Update_lin_PreCond(onlyOnStart=True)
|
||||
|
||||
save_log = Directives.SaveOutputEveryIteration()
|
||||
save_log.fileName = home_dir + dsep + 'SimPEG_inv_l2l2_log_' +str(wgtexp)
|
||||
|
||||
inv = Inversion.BaseInversion(invProb, directiveList=[beta,target,update_beta,update_Jacobi,save_log])
|
||||
#inv = Inversion.BaseInversion(invProb, directiveList=[beta,target])
|
||||
|
||||
m0 = mstart
|
||||
|
||||
# Run inversion
|
||||
mrec = inv.run(m0)
|
||||
|
||||
m_out = actvMap*actvCells*mrec
|
||||
|
||||
# Write result
|
||||
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2_' +str(wgtexp) + '.den', m_out)
|
||||
#Utils.meshutils.writeUBCTensorModel(home_dir+dsep+'wr.dat',mesh,wr_out)
|
||||
|
||||
# Plot predicted
|
||||
pred_smooth = prob.fields(mrec)
|
||||
PF.Gravity.writeUBCobs(home_dir + dsep + 'Pred_smooth' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.dat',survey,pred_smooth)
|
||||
#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_smooth)/wd)**2. ) )
|
||||
print "Misfit sum(obs-calc)/nobs: %.3f mGal" %np.divide(np.sum(np.abs(d-pred_smooth)), len(d))
|
||||
print "RMS misfit: %.3f mGal" %np.sqrt(np.divide(np.sum((d-pred_smooth)**2),len(d)))
|
||||
|
||||
#%% Plot out sections of the smooth model
|
||||
|
||||
yslice = midx+1
|
||||
m_out[m_out==-100]=np.nan # set "air" to nan
|
||||
|
||||
print "\nMax density:" + str(np.nanmax(m_out))
|
||||
print "\nMin density:" + str(np.nanmin(m_out))
|
||||
|
||||
plt.figure(figsize=(15,10))
|
||||
plt.suptitle('Smooth Inversion: Depth weight = ' + str(wgtexp))
|
||||
ax = plt.subplot(221)
|
||||
dat1=mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-10, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='gray',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='k',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-10]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
ax = plt.subplot(222)
|
||||
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-25, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='gray',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='k',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-25]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
ax = plt.subplot(212)
|
||||
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.title('Cross Section')
|
||||
plt.xlabel('Easting(m)');plt.ylabel('Elevation')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4), cmap='bwr')
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
plt.savefig(home_dir + str('\Figure1_' +str(wgtexp) + '.png'), dpi=300, bb_inches='tight')
|
||||
|
||||
#plot histograms
|
||||
plt.figure(figsize=(15,10))
|
||||
ax = plt.subplot(121)
|
||||
plt.hist(mrec,100)
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.xlim(mrec.mean() - 6.*(mrec.std()), mrec.mean() + 6.*(mrec.std()))
|
||||
plt.xlabel('Density (g/cc$^3$)')
|
||||
plt.title('Histogram of model values - Smooth')
|
||||
|
||||
ax = plt.subplot(122)
|
||||
plt.hist(reg.regmesh.cellDiffxStencil*(actvCells*mrec),100)
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.xlim(mrec.mean() - 2.*(mrec.std()), mrec.mean() + 2.*(mrec.std()))
|
||||
plt.xlabel('Density (g/cc$^3$)')
|
||||
plt.title('Histogram of model gradient values - Smooth')
|
||||
plt.savefig(home_dir + str('\Figure2_' +str(wgtexp) + '.png'), dpi=300, bb_inches='tight')
|
||||
|
||||
|
||||
|
||||
#%% Run one more round for sparsity (Compact model)
|
||||
print '\nRun compact inversion \n'
|
||||
phim = invProb.phi_m_last
|
||||
phid = invProb.phi_d
|
||||
|
||||
reg = Regularization.Sparse(mesh, indActive = actv, mapping = actvCells)
|
||||
reg.recModel = mrec
|
||||
reg.mref = mref
|
||||
reg.wght = wr
|
||||
reg.eps_p = eps_p
|
||||
reg.eps_q = eps_q
|
||||
reg.norms = lpnorms
|
||||
|
||||
#diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
|
||||
#PC = Utils.sdiag(diagA**-1.)
|
||||
update_Jacobi = Directives.Update_lin_PreCond()
|
||||
|
||||
#reg.alpha_s = 1.
|
||||
|
||||
dmis = DataMisfit.l2_DataMisfit(survey)
|
||||
dmis.Wd = 1./wd
|
||||
opt = Optimization.ProjectedGNCG(maxIterLS=20, maxIter=20 ,lower=bounds[0],upper=bounds[1], maxIterCG= 50, 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)
|
||||
|
||||
#update beta only if misfit is outside the tolerance
|
||||
update_beta = Directives.Scale_Beta(tol = 0.05) #Tolerance value is in % of the target
|
||||
|
||||
#betaest = Directives.BetaEstimate_ByEig()
|
||||
target = Directives.TargetMisfit()
|
||||
IRLS =Directives.Update_IRLS( phi_m_last = phim, phi_d_last = phid )
|
||||
|
||||
#save output to logfile
|
||||
save_log = Directives.SaveOutputEveryIteration()
|
||||
save_log.fileName = home_dir + dsep + 'SimPEG_inv_l0l2_log_' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q)
|
||||
|
||||
|
||||
inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS,update_beta,update_Jacobi,save_log])
|
||||
|
||||
|
||||
|
||||
m0 = mrec
|
||||
|
||||
# Run inversion
|
||||
mrec = inv.run(m0)
|
||||
|
||||
m_out = actvMap*actvCells*mrec
|
||||
|
||||
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l0l2_' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.den',m_out)
|
||||
|
||||
pred_compact = prob.fields(mrec)
|
||||
PF.Gravity.writeUBCobs(home_dir + dsep + 'Pred_compact' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.dat',survey,pred_compact)
|
||||
|
||||
|
||||
|
||||
#%% Plot obs data
|
||||
PF.Magnetics.plot_obs_2D(rxLoc,pred_compact,'Predicted Data', vmin = np.min(d), vmax = np.max(d))
|
||||
plt.savefig(home_dir + str('\Figure3_' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.png'), dpi=300, bb_inches='tight')
|
||||
PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
|
||||
plt.savefig(home_dir + str('\Figure4.png'), dpi=300, bb_inches='tight')
|
||||
print "\nFinal misfit:" + str(np.sum( ((d-pred_compact)/wd)**2. ) )
|
||||
print "Misfit sum(obs-calc)/nobs: %.3f mGal" %np.divide(np.sum(np.abs(d-pred_compact)), len(d))
|
||||
print "RMS misfit: %.3f mGal" %np.sqrt(np.divide(np.sum((d-pred_compact)**2),len(d)))
|
||||
|
||||
|
||||
|
||||
#%% Plot out a section of the compact model
|
||||
|
||||
yslice = midx
|
||||
m_out[m_out==-100]=np.nan # set "air" to nan
|
||||
|
||||
print "\nMax density:" + str(np.nanmax(m_out))
|
||||
print "\nMin density:" + str(np.nanmin(m_out))
|
||||
|
||||
plt.figure(figsize=(15,10))
|
||||
plt.suptitle('Compact Inversion: Depth weight = ' + str(wgtexp) + ': $\epsilon_p$ = ' + str(eps_p) + ': $\epsilon_q$ = ' + str(eps_q))
|
||||
ax = plt.subplot(221)
|
||||
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-10, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='gray',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='k',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-10]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
ax = plt.subplot(222)
|
||||
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-25, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='gray',linestyle = '--')
|
||||
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='k',s=1)
|
||||
plt.title('Z: ' + str(mesh.vectorCCz[-25]) + ' m')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
ax = plt.subplot(212)
|
||||
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax), pcolorOpts={'cmap':'bwr'})
|
||||
plt.title('Cross Section')
|
||||
plt.xlabel('Easting (m)');plt.ylabel('Elevation (m)')
|
||||
plt.gca().set_aspect('equal', adjustable='box')
|
||||
cb = plt.colorbar(dat[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
|
||||
cb.set_label('Density (g/cc$^3$)')
|
||||
|
||||
plt.savefig(home_dir + str('\Figure5_' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.png'), dpi=300, bb_inches='tight')
|
||||
|
||||
#plot histograms
|
||||
plt.figure(figsize=(15,10))
|
||||
ax = plt.subplot(121)
|
||||
plt.hist(mrec,100)
|
||||
#plt.xlim(mrec.mean() - 6.*(mrec.std()), mrec.mean() + 6.*(mrec.std()))
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.xlabel('Density (g/cc$^3$)')
|
||||
plt.title('Histogram of model values - Sparse lp:'+str(lpnorms[0]))
|
||||
|
||||
ax = plt.subplot(122)
|
||||
plt.hist(reg.regmesh.cellDiffxStencil*(actvCells*mrec),100)
|
||||
#plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
|
||||
plt.xlabel('Density (g/cc$^3$)')
|
||||
plt.yscale('log', nonposy='clip')
|
||||
plt.title('Histogram of model gradient values - Sparse lqx: ' + str(lpnorms[1]) + ' lqy:'+ str(lpnorms[2]) + ' lqz:' + str(lpnorms[3]))
|
||||
plt.savefig(home_dir + str('\Figure6_' +str(wgtexp) + '_' + str(eps_p) + '_' + str(eps_q) +'.png'), dpi=300, bb_inches='tight')
|
||||
@@ -7,4 +7,5 @@ DEFAULT ! Cell based weight file
|
||||
1 ! target chi factor | DEFAULT=1
|
||||
1 1 1 1 ! alpha s, x ,y ,z
|
||||
VALUE -1 1 ! Lower and Upper Bounds for p-component
|
||||
VALUE 0 1 1 1 1 ! lp-norm for amplitude inversion FILE pqxqyqzr.dat ! Norms VALUE p, qx, qy, qz, r | FILE m-by-5 matrix
|
||||
VALUE 0 1 1 1 2 ! lp-norm for amplitude inversion FILE pqxqyqzr.dat ! Norms VALUE p, qx, qy, qz, r | FILE m-by-5 matrix
|
||||
VALUE 1e-2 1e-3 ! Threshold value for the norm on model and model gradient VALUE eps_p, eps_q | DEFAULT
|
||||
@@ -0,0 +1,617 @@
|
||||
616
|
||||
1.050000e+02 1.550000e+02 2.408312e+02 8.699375e-03 2.000000e-03
|
||||
1.150000e+02 1.550000e+02 2.440469e+02 9.811662e-03 2.000000e-03
|
||||
1.250000e+02 1.550000e+02 2.471986e+02 1.102523e-02 2.000000e-03
|
||||
1.350000e+02 1.550000e+02 2.502569e+02 1.230640e-02 2.000000e-03
|
||||
1.450000e+02 1.550000e+02 2.531923e+02 1.361237e-02 2.000000e-03
|
||||
1.550000e+02 1.550000e+02 2.559753e+02 1.488528e-02 2.000000e-03
|
||||
1.650000e+02 1.550000e+02 2.585770e+02 1.607121e-02 2.000000e-03
|
||||
1.750000e+02 1.550000e+02 2.609695e+02 1.713245e-02 2.000000e-03
|
||||
1.850000e+02 1.550000e+02 2.631267e+02 1.804632e-02 2.000000e-03
|
||||
1.950000e+02 1.550000e+02 2.650244e+02 1.880933e-02 2.000000e-03
|
||||
2.050000e+02 1.550000e+02 2.666411e+02 1.944187e-02 2.000000e-03
|
||||
2.150000e+02 1.550000e+02 2.679578e+02 1.997736e-02 2.000000e-03
|
||||
2.250000e+02 1.550000e+02 2.689593e+02 2.045576e-02 2.000000e-03
|
||||
2.350000e+02 1.550000e+02 2.696337e+02 2.091268e-02 2.000000e-03
|
||||
2.450000e+02 1.550000e+02 2.699729e+02 2.137452e-02 2.000000e-03
|
||||
2.550000e+02 1.550000e+02 2.699729e+02 2.185203e-02 2.000000e-03
|
||||
2.650000e+02 1.550000e+02 2.696337e+02 2.233853e-02 2.000000e-03
|
||||
2.750000e+02 1.550000e+02 2.689593e+02 2.280835e-02 2.000000e-03
|
||||
2.850000e+02 1.550000e+02 2.679578e+02 2.321635e-02 2.000000e-03
|
||||
2.950000e+02 1.550000e+02 2.666411e+02 2.350100e-02 2.000000e-03
|
||||
3.050000e+02 1.550000e+02 2.650244e+02 2.359380e-02 2.000000e-03
|
||||
3.150000e+02 1.550000e+02 2.631267e+02 2.342950e-02 2.000000e-03
|
||||
3.250000e+02 1.550000e+02 2.609695e+02 2.295876e-02 2.000000e-03
|
||||
3.350000e+02 1.550000e+02 2.585770e+02 2.216118e-02 2.000000e-03
|
||||
3.450000e+02 1.550000e+02 2.559753e+02 2.105420e-02 2.000000e-03
|
||||
3.550000e+02 1.550000e+02 2.531923e+02 1.969369e-02 2.000000e-03
|
||||
3.650000e+02 1.550000e+02 2.502569e+02 1.816297e-02 2.000000e-03
|
||||
3.750000e+02 1.550000e+02 2.471986e+02 1.655348e-02 2.000000e-03
|
||||
1.050000e+02 1.650000e+02 2.427601e+02 9.727037e-03 2.000000e-03
|
||||
1.150000e+02 1.650000e+02 2.460869e+02 1.109189e-02 2.000000e-03
|
||||
1.250000e+02 1.650000e+02 2.493475e+02 1.259082e-02 2.000000e-03
|
||||
1.350000e+02 1.650000e+02 2.525115e+02 1.417977e-02 2.000000e-03
|
||||
1.450000e+02 1.650000e+02 2.555483e+02 1.579232e-02 2.000000e-03
|
||||
1.550000e+02 1.650000e+02 2.584275e+02 1.734457e-02 2.000000e-03
|
||||
1.650000e+02 1.650000e+02 2.611190e+02 1.876032e-02 2.000000e-03
|
||||
1.750000e+02 1.650000e+02 2.635942e+02 1.998648e-02 2.000000e-03
|
||||
1.850000e+02 1.650000e+02 2.658260e+02 2.099280e-02 2.000000e-03
|
||||
1.950000e+02 1.650000e+02 2.677892e+02 2.178443e-02 2.000000e-03
|
||||
2.050000e+02 1.650000e+02 2.694617e+02 2.240013e-02 2.000000e-03
|
||||
2.150000e+02 1.650000e+02 2.708240e+02 2.289886e-02 2.000000e-03
|
||||
2.250000e+02 1.650000e+02 2.718600e+02 2.334616e-02 2.000000e-03
|
||||
2.350000e+02 1.650000e+02 2.725577e+02 2.379862e-02 2.000000e-03
|
||||
2.450000e+02 1.650000e+02 2.729086e+02 2.429829e-02 2.000000e-03
|
||||
2.550000e+02 1.650000e+02 2.729086e+02 2.486506e-02 2.000000e-03
|
||||
2.650000e+02 1.650000e+02 2.725577e+02 2.549431e-02 2.000000e-03
|
||||
2.750000e+02 1.650000e+02 2.718600e+02 2.615426e-02 2.000000e-03
|
||||
2.850000e+02 1.650000e+02 2.708240e+02 2.678409e-02 2.000000e-03
|
||||
2.950000e+02 1.650000e+02 2.694617e+02 2.729680e-02 2.000000e-03
|
||||
3.050000e+02 1.650000e+02 2.677892e+02 2.758967e-02 2.000000e-03
|
||||
3.150000e+02 1.650000e+02 2.658260e+02 2.755802e-02 2.000000e-03
|
||||
3.250000e+02 1.650000e+02 2.635942e+02 2.711665e-02 2.000000e-03
|
||||
3.350000e+02 1.650000e+02 2.611190e+02 2.622229e-02 2.000000e-03
|
||||
3.450000e+02 1.650000e+02 2.584275e+02 2.488799e-02 2.000000e-03
|
||||
3.550000e+02 1.650000e+02 2.555483e+02 2.318678e-02 2.000000e-03
|
||||
3.650000e+02 1.650000e+02 2.525115e+02 2.123786e-02 2.000000e-03
|
||||
3.750000e+02 1.650000e+02 2.493475e+02 1.917733e-02 2.000000e-03
|
||||
1.050000e+02 1.750000e+02 2.445174e+02 1.089525e-02 2.000000e-03
|
||||
1.150000e+02 1.750000e+02 2.479454e+02 1.257157e-02 2.000000e-03
|
||||
1.250000e+02 1.750000e+02 2.513052e+02 1.443051e-02 2.000000e-03
|
||||
1.350000e+02 1.750000e+02 2.545655e+02 1.641078e-02 2.000000e-03
|
||||
1.450000e+02 1.750000e+02 2.576947e+02 1.841316e-02 2.000000e-03
|
||||
1.550000e+02 1.750000e+02 2.606614e+02 2.031780e-02 2.000000e-03
|
||||
1.650000e+02 1.750000e+02 2.634348e+02 2.201065e-02 2.000000e-03
|
||||
1.750000e+02 1.750000e+02 2.659854e+02 2.341157e-02 2.000000e-03
|
||||
1.850000e+02 1.750000e+02 2.682850e+02 2.448678e-02 2.000000e-03
|
||||
1.950000e+02 1.750000e+02 2.703080e+02 2.525725e-02 2.000000e-03
|
||||
2.050000e+02 1.750000e+02 2.720313e+02 2.579213e-02 2.000000e-03
|
||||
2.150000e+02 1.750000e+02 2.734350e+02 2.618855e-02 2.000000e-03
|
||||
2.250000e+02 1.750000e+02 2.745027e+02 2.654720e-02 2.000000e-03
|
||||
2.350000e+02 1.750000e+02 2.752216e+02 2.695443e-02 2.000000e-03
|
||||
2.450000e+02 1.750000e+02 2.755831e+02 2.747264e-02 2.000000e-03
|
||||
2.550000e+02 1.750000e+02 2.755831e+02 2.813471e-02 2.000000e-03
|
||||
2.650000e+02 1.750000e+02 2.752216e+02 2.894005e-02 2.000000e-03
|
||||
2.750000e+02 1.750000e+02 2.745027e+02 2.985075e-02 2.000000e-03
|
||||
2.850000e+02 1.750000e+02 2.734350e+02 3.078824e-02 2.000000e-03
|
||||
2.950000e+02 1.750000e+02 2.720313e+02 3.163485e-02 2.000000e-03
|
||||
3.050000e+02 1.750000e+02 2.703080e+02 3.224142e-02 2.000000e-03
|
||||
3.150000e+02 1.750000e+02 2.682850e+02 3.244573e-02 2.000000e-03
|
||||
3.250000e+02 1.750000e+02 2.659854e+02 3.210562e-02 2.000000e-03
|
||||
3.350000e+02 1.750000e+02 2.634348e+02 3.113619e-02 2.000000e-03
|
||||
3.450000e+02 1.750000e+02 2.606614e+02 2.953886e-02 2.000000e-03
|
||||
3.550000e+02 1.750000e+02 2.576947e+02 2.741092e-02 2.000000e-03
|
||||
3.650000e+02 1.750000e+02 2.545655e+02 2.492491e-02 2.000000e-03
|
||||
3.750000e+02 1.750000e+02 2.513052e+02 2.228314e-02 2.000000e-03
|
||||
1.050000e+02 1.850000e+02 2.460835e+02 1.219901e-02 2.000000e-03
|
||||
1.150000e+02 1.850000e+02 2.496018e+02 1.425707e-02 2.000000e-03
|
||||
1.250000e+02 1.850000e+02 2.530500e+02 1.656703e-02 2.000000e-03
|
||||
1.350000e+02 1.850000e+02 2.563960e+02 1.904267e-02 2.000000e-03
|
||||
1.450000e+02 1.850000e+02 2.596076e+02 2.154309e-02 2.000000e-03
|
||||
1.550000e+02 1.850000e+02 2.626524e+02 2.389251e-02 2.000000e-03
|
||||
1.650000e+02 1.850000e+02 2.654988e+02 2.591841e-02 2.000000e-03
|
||||
1.750000e+02 1.850000e+02 2.681164e+02 2.750129e-02 2.000000e-03
|
||||
1.850000e+02 1.850000e+02 2.704766e+02 2.860300e-02 2.000000e-03
|
||||
1.950000e+02 1.850000e+02 2.725528e+02 2.927297e-02 2.000000e-03
|
||||
2.050000e+02 1.850000e+02 2.743215e+02 2.963033e-02 2.000000e-03
|
||||
2.150000e+02 1.850000e+02 2.757621e+02 2.982855e-02 2.000000e-03
|
||||
2.250000e+02 1.850000e+02 2.768578e+02 3.001789e-02 2.000000e-03
|
||||
2.350000e+02 1.850000e+02 2.775956e+02 3.032229e-02 2.000000e-03
|
||||
2.450000e+02 1.850000e+02 2.779668e+02 3.082928e-02 2.000000e-03
|
||||
2.550000e+02 1.850000e+02 2.779668e+02 3.158715e-02 2.000000e-03
|
||||
2.650000e+02 1.850000e+02 2.775956e+02 3.260165e-02 2.000000e-03
|
||||
2.750000e+02 1.850000e+02 2.768578e+02 3.383103e-02 2.000000e-03
|
||||
2.850000e+02 1.850000e+02 2.757621e+02 3.517975e-02 2.000000e-03
|
||||
2.950000e+02 1.850000e+02 2.743215e+02 3.649394e-02 2.000000e-03
|
||||
3.050000e+02 1.850000e+02 2.725528e+02 3.756451e-02 2.000000e-03
|
||||
3.150000e+02 1.850000e+02 2.704766e+02 3.814891e-02 2.000000e-03
|
||||
3.250000e+02 1.850000e+02 2.681164e+02 3.801821e-02 2.000000e-03
|
||||
3.350000e+02 1.850000e+02 2.654988e+02 3.701774e-02 2.000000e-03
|
||||
3.450000e+02 1.850000e+02 2.626524e+02 3.512216e-02 2.000000e-03
|
||||
3.550000e+02 1.850000e+02 2.596076e+02 3.245988e-02 2.000000e-03
|
||||
3.650000e+02 1.850000e+02 2.563960e+02 2.928500e-02 2.000000e-03
|
||||
3.750000e+02 1.850000e+02 2.530500e+02 2.589943e-02 2.000000e-03
|
||||
1.050000e+02 1.950000e+02 2.474409e+02 1.361651e-02 2.000000e-03
|
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1.450000e+02 3.250000e+02 2.555483e+02 2.076366e-02 2.000000e-03
|
||||
1.550000e+02 3.250000e+02 2.584275e+02 2.322337e-02 2.000000e-03
|
||||
1.650000e+02 3.250000e+02 2.611190e+02 2.535788e-02 2.000000e-03
|
||||
1.750000e+02 3.250000e+02 2.635942e+02 2.700472e-02 2.000000e-03
|
||||
1.850000e+02 3.250000e+02 2.658260e+02 2.809600e-02 2.000000e-03
|
||||
1.950000e+02 3.250000e+02 2.677892e+02 2.867004e-02 2.000000e-03
|
||||
2.050000e+02 3.250000e+02 2.694617e+02 2.884924e-02 2.000000e-03
|
||||
2.150000e+02 3.250000e+02 2.708240e+02 2.879968e-02 2.000000e-03
|
||||
2.250000e+02 3.250000e+02 2.718600e+02 2.868793e-02 2.000000e-03
|
||||
2.350000e+02 3.250000e+02 2.725577e+02 2.865140e-02 2.000000e-03
|
||||
2.450000e+02 3.250000e+02 2.729086e+02 2.878238e-02 2.000000e-03
|
||||
2.550000e+02 3.250000e+02 2.729086e+02 2.912579e-02 2.000000e-03
|
||||
2.650000e+02 3.250000e+02 2.725577e+02 2.968094e-02 2.000000e-03
|
||||
2.750000e+02 3.250000e+02 2.718600e+02 3.040166e-02 2.000000e-03
|
||||
2.850000e+02 3.250000e+02 2.708240e+02 3.119605e-02 2.000000e-03
|
||||
2.950000e+02 3.250000e+02 2.694617e+02 3.192918e-02 2.000000e-03
|
||||
3.050000e+02 3.250000e+02 2.677892e+02 3.243227e-02 2.000000e-03
|
||||
3.150000e+02 3.250000e+02 2.658260e+02 3.252519e-02 2.000000e-03
|
||||
3.250000e+02 3.250000e+02 2.635942e+02 3.205254e-02 2.000000e-03
|
||||
3.350000e+02 3.250000e+02 2.611190e+02 3.092642e-02 2.000000e-03
|
||||
3.450000e+02 3.250000e+02 2.584275e+02 2.915945e-02 2.000000e-03
|
||||
3.550000e+02 3.250000e+02 2.555483e+02 2.686725e-02 2.000000e-03
|
||||
3.650000e+02 3.250000e+02 2.525115e+02 2.423840e-02 2.000000e-03
|
||||
3.750000e+02 3.250000e+02 2.493475e+02 2.148640e-02 2.000000e-03
|
||||
1.050000e+02 3.350000e+02 2.408312e+02 9.941922e-03 2.000000e-03
|
||||
1.150000e+02 3.350000e+02 2.440469e+02 1.156254e-02 2.000000e-03
|
||||
1.250000e+02 3.350000e+02 2.471986e+02 1.338630e-02 2.000000e-03
|
||||
1.350000e+02 3.350000e+02 2.502569e+02 1.535354e-02 2.000000e-03
|
||||
1.450000e+02 3.350000e+02 2.531923e+02 1.736823e-02 2.000000e-03
|
||||
1.550000e+02 3.350000e+02 2.559753e+02 1.930648e-02 2.000000e-03
|
||||
1.650000e+02 3.350000e+02 2.585770e+02 2.103686e-02 2.000000e-03
|
||||
1.750000e+02 3.350000e+02 2.609695e+02 2.245160e-02 2.000000e-03
|
||||
1.850000e+02 3.350000e+02 2.631267e+02 2.349602e-02 2.000000e-03
|
||||
1.950000e+02 3.350000e+02 2.650244e+02 2.418070e-02 2.000000e-03
|
||||
2.050000e+02 3.350000e+02 2.666411e+02 2.457191e-02 2.000000e-03
|
||||
2.150000e+02 3.350000e+02 2.679578e+02 2.476979e-02 2.000000e-03
|
||||
2.250000e+02 3.350000e+02 2.689593e+02 2.488188e-02 2.000000e-03
|
||||
2.350000e+02 3.350000e+02 2.696337e+02 2.500175e-02 2.000000e-03
|
||||
2.450000e+02 3.350000e+02 2.699729e+02 2.519563e-02 2.000000e-03
|
||||
2.550000e+02 3.350000e+02 2.699729e+02 2.549683e-02 2.000000e-03
|
||||
2.650000e+02 3.350000e+02 2.696337e+02 2.590408e-02 2.000000e-03
|
||||
2.750000e+02 3.350000e+02 2.689593e+02 2.638174e-02 2.000000e-03
|
||||
2.850000e+02 3.350000e+02 2.679578e+02 2.686149e-02 2.000000e-03
|
||||
2.950000e+02 3.350000e+02 2.666411e+02 2.724651e-02 2.000000e-03
|
||||
3.050000e+02 3.350000e+02 2.650244e+02 2.742183e-02 2.000000e-03
|
||||
3.150000e+02 3.350000e+02 2.631267e+02 2.727229e-02 2.000000e-03
|
||||
3.250000e+02 3.350000e+02 2.609695e+02 2.670598e-02 2.000000e-03
|
||||
3.350000e+02 3.350000e+02 2.585770e+02 2.567965e-02 2.000000e-03
|
||||
3.450000e+02 3.350000e+02 2.559753e+02 2.421447e-02 2.000000e-03
|
||||
3.550000e+02 3.350000e+02 2.531923e+02 2.239399e-02 2.000000e-03
|
||||
3.650000e+02 3.350000e+02 2.502569e+02 2.034502e-02 2.000000e-03
|
||||
3.750000e+02 3.350000e+02 2.471986e+02 1.821014e-02 2.000000e-03
|
||||
1.050000e+02 3.450000e+02 2.387514e+02 8.700295e-03 2.000000e-03
|
||||
1.150000e+02 3.450000e+02 2.418474e+02 9.994043e-03 2.000000e-03
|
||||
1.250000e+02 3.450000e+02 2.448817e+02 1.143375e-02 2.000000e-03
|
||||
1.350000e+02 3.450000e+02 2.478261e+02 1.297678e-02 2.000000e-03
|
||||
1.450000e+02 3.450000e+02 2.506521e+02 1.455633e-02 2.000000e-03
|
||||
1.550000e+02 3.450000e+02 2.533315e+02 1.609073e-02 2.000000e-03
|
||||
1.650000e+02 3.450000e+02 2.558362e+02 1.749413e-02 2.000000e-03
|
||||
1.750000e+02 3.450000e+02 2.581396e+02 1.869352e-02 2.000000e-03
|
||||
1.850000e+02 3.450000e+02 2.602165e+02 1.964746e-02 2.000000e-03
|
||||
1.950000e+02 3.450000e+02 2.620435e+02 2.035288e-02 2.000000e-03
|
||||
2.050000e+02 3.450000e+02 2.635999e+02 2.084311e-02 2.000000e-03
|
||||
2.150000e+02 3.450000e+02 2.648676e+02 2.117625e-02 2.000000e-03
|
||||
2.250000e+02 3.450000e+02 2.658318e+02 2.141826e-02 2.000000e-03
|
||||
2.350000e+02 3.450000e+02 2.664810e+02 2.162950e-02 2.000000e-03
|
||||
2.450000e+02 3.450000e+02 2.668076e+02 2.185433e-02 2.000000e-03
|
||||
2.550000e+02 3.450000e+02 2.668076e+02 2.211540e-02 2.000000e-03
|
||||
2.650000e+02 3.450000e+02 2.664810e+02 2.241087e-02 2.000000e-03
|
||||
2.750000e+02 3.450000e+02 2.658318e+02 2.271456e-02 2.000000e-03
|
||||
2.850000e+02 3.450000e+02 2.648676e+02 2.297828e-02 2.000000e-03
|
||||
2.950000e+02 3.450000e+02 2.635999e+02 2.313594e-02 2.000000e-03
|
||||
3.050000e+02 3.450000e+02 2.620435e+02 2.311177e-02 2.000000e-03
|
||||
3.150000e+02 3.450000e+02 2.602165e+02 2.283466e-02 2.000000e-03
|
||||
3.250000e+02 3.450000e+02 2.581396e+02 2.225286e-02 2.000000e-03
|
||||
3.350000e+02 3.450000e+02 2.558362e+02 2.134775e-02 2.000000e-03
|
||||
3.450000e+02 3.450000e+02 2.533315e+02 2.014201e-02 2.000000e-03
|
||||
3.550000e+02 3.450000e+02 2.506521e+02 1.869606e-02 2.000000e-03
|
||||
3.650000e+02 3.450000e+02 2.478261e+02 1.709628e-02 2.000000e-03
|
||||
3.750000e+02 3.450000e+02 2.448817e+02 1.543918e-02 2.000000e-03
|
||||
1.050000e+02 3.550000e+02 2.365428e+02 7.613911e-03 2.000000e-03
|
||||
1.150000e+02 3.550000e+02 2.395115e+02 8.647298e-03 2.000000e-03
|
||||
1.250000e+02 3.550000e+02 2.424211e+02 9.786237e-03 2.000000e-03
|
||||
1.350000e+02 3.550000e+02 2.452446e+02 1.100079e-02 2.000000e-03
|
||||
1.450000e+02 3.550000e+02 2.479545e+02 1.224611e-02 2.000000e-03
|
||||
1.550000e+02 3.550000e+02 2.505237e+02 1.346689e-02 2.000000e-03
|
||||
1.650000e+02 3.550000e+02 2.529255e+02 1.460571e-02 2.000000e-03
|
||||
1.750000e+02 3.550000e+02 2.551343e+02 1.561255e-02 2.000000e-03
|
||||
1.850000e+02 3.550000e+02 2.571258e+02 1.645653e-02 2.000000e-03
|
||||
1.950000e+02 3.550000e+02 2.588778e+02 1.712919e-02 2.000000e-03
|
||||
2.050000e+02 3.550000e+02 2.603702e+02 1.764484e-02 2.000000e-03
|
||||
2.150000e+02 3.550000e+02 2.615858e+02 1.803522e-02 2.000000e-03
|
||||
2.250000e+02 3.550000e+02 2.625104e+02 1.833890e-02 2.000000e-03
|
||||
2.350000e+02 3.550000e+02 2.631330e+02 1.859274e-02 2.000000e-03
|
||||
2.450000e+02 3.550000e+02 2.634461e+02 1.882440e-02 2.000000e-03
|
||||
2.550000e+02 3.550000e+02 2.634461e+02 1.904792e-02 2.000000e-03
|
||||
2.650000e+02 3.550000e+02 2.631330e+02 1.926108e-02 2.000000e-03
|
||||
2.750000e+02 3.550000e+02 2.625104e+02 1.944546e-02 2.000000e-03
|
||||
2.850000e+02 3.550000e+02 2.615858e+02 1.956845e-02 2.000000e-03
|
||||
2.950000e+02 3.550000e+02 2.603702e+02 1.958670e-02 2.000000e-03
|
||||
3.050000e+02 3.550000e+02 2.588778e+02 1.945233e-02 2.000000e-03
|
||||
3.150000e+02 3.550000e+02 2.571258e+02 1.912335e-02 2.000000e-03
|
||||
3.250000e+02 3.550000e+02 2.551343e+02 1.857233e-02 2.000000e-03
|
||||
3.350000e+02 3.550000e+02 2.529255e+02 1.779329e-02 2.000000e-03
|
||||
3.450000e+02 3.550000e+02 2.505237e+02 1.680720e-02 2.000000e-03
|
||||
3.550000e+02 3.550000e+02 2.479545e+02 1.565863e-02 2.000000e-03
|
||||
3.650000e+02 3.550000e+02 2.452446e+02 1.440777e-02 2.000000e-03
|
||||
3.750000e+02 3.550000e+02 2.424211e+02 1.311967e-02 2.000000e-03
|
||||
1.050000e+02 3.650000e+02 2.342278e+02 6.675879e-03 2.000000e-03
|
||||
1.150000e+02 3.650000e+02 2.370632e+02 7.501534e-03 2.000000e-03
|
||||
1.250000e+02 3.650000e+02 2.398421e+02 8.406384e-03 2.000000e-03
|
||||
1.350000e+02 3.650000e+02 2.425387e+02 9.366917e-03 2.000000e-03
|
||||
1.450000e+02 3.650000e+02 2.451270e+02 1.035317e-02 2.000000e-03
|
||||
1.550000e+02 3.650000e+02 2.475808e+02 1.132872e-02 2.000000e-03
|
||||
1.650000e+02 3.650000e+02 2.498748e+02 1.225382e-02 2.000000e-03
|
||||
1.750000e+02 3.650000e+02 2.519843e+02 1.309303e-02 2.000000e-03
|
||||
1.850000e+02 3.650000e+02 2.538864e+02 1.382311e-02 2.000000e-03
|
||||
1.950000e+02 3.650000e+02 2.555596e+02 1.443470e-02 2.000000e-03
|
||||
2.050000e+02 3.650000e+02 2.569850e+02 1.493134e-02 2.000000e-03
|
||||
2.150000e+02 3.650000e+02 2.581461e+02 1.532861e-02 2.000000e-03
|
||||
2.250000e+02 3.650000e+02 2.590291e+02 1.564824e-02 2.000000e-03
|
||||
2.350000e+02 3.650000e+02 2.596237e+02 1.591135e-02 2.000000e-03
|
||||
2.450000e+02 3.650000e+02 2.599228e+02 1.613371e-02 2.000000e-03
|
||||
2.550000e+02 3.650000e+02 2.599228e+02 1.632286e-02 2.000000e-03
|
||||
2.650000e+02 3.650000e+02 2.596237e+02 1.647652e-02 2.000000e-03
|
||||
2.750000e+02 3.650000e+02 2.590291e+02 1.658239e-02 2.000000e-03
|
||||
2.850000e+02 3.650000e+02 2.581461e+02 1.661913e-02 2.000000e-03
|
||||
2.950000e+02 3.650000e+02 2.569850e+02 1.655899e-02 2.000000e-03
|
||||
3.050000e+02 3.650000e+02 2.555596e+02 1.637349e-02 2.000000e-03
|
||||
3.150000e+02 3.650000e+02 2.538864e+02 1.603953e-02 2.000000e-03
|
||||
3.250000e+02 3.650000e+02 2.519843e+02 1.554295e-02 2.000000e-03
|
||||
3.350000e+02 3.650000e+02 2.498748e+02 1.488428e-02 2.000000e-03
|
||||
3.450000e+02 3.650000e+02 2.475808e+02 1.408257e-02 2.000000e-03
|
||||
3.550000e+02 3.650000e+02 2.451270e+02 1.317151e-02 2.000000e-03
|
||||
3.650000e+02 3.650000e+02 2.425387e+02 1.219236e-02 2.000000e-03
|
||||
3.750000e+02 3.650000e+02 2.398421e+02 1.118891e-02 2.000000e-03
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
Binary file not shown.
|
After Width: | Height: | Size: 133 KiB |
+32837
-32837
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,235 @@
|
||||
import re, os
|
||||
from SimPEG import Mesh, np
|
||||
import BaseGrav, Gravity
|
||||
|
||||
class GravityDriver_Inv(object):
|
||||
"""docstring for GravityDriver_Inv"""
|
||||
|
||||
def __init__(self, input_file=None):
|
||||
if input_file is not None:
|
||||
self.basePath = os.path.sep.join(input_file.split(os.path.sep)[:-1])
|
||||
if len(self.basePath) > 0:
|
||||
self.basePath += os.path.sep
|
||||
self.readDriverFile(input_file.split(os.path.sep)[-1])
|
||||
|
||||
|
||||
def readDriverFile(self, input_file):
|
||||
"""
|
||||
Read input files for forward modeling GRAV data with integral form
|
||||
INPUT:
|
||||
input_file: File name containing the forward parameter
|
||||
|
||||
OUTPUT:
|
||||
mshfile
|
||||
obsfile
|
||||
topofile
|
||||
start model
|
||||
ref model
|
||||
weightfile
|
||||
chi_target
|
||||
as, ax ,ay, az
|
||||
upper, lower bounds
|
||||
lp, lqx, lqy, lqz
|
||||
eps_p, eps_q
|
||||
# All files should be in the working directory, otherwise the path must
|
||||
# be specified.
|
||||
|
||||
"""
|
||||
|
||||
|
||||
fid = open(self.basePath + input_file,'r')
|
||||
|
||||
# Line 1
|
||||
line = fid.readline()
|
||||
l_input = line.split('!')
|
||||
mshfile = l_input[0].rstrip()
|
||||
|
||||
# Line 2
|
||||
line = fid.readline()
|
||||
l_input = line.split('!')
|
||||
obsfile = l_input[0].rstrip()
|
||||
|
||||
# Line 3
|
||||
line = fid.readline()
|
||||
l_input = re.split('[!\s]',line)
|
||||
if l_input=='null':
|
||||
topofile = []
|
||||
|
||||
else:
|
||||
topofile = l_input[0].rstrip()
|
||||
|
||||
|
||||
# Line 4
|
||||
line = fid.readline()
|
||||
l_input = re.split('[!\s]',line)
|
||||
if l_input[0]=='VALUE':
|
||||
mstart = float(l_input[1])
|
||||
|
||||
else:
|
||||
mstart = l_input[0].rstrip()
|
||||
|
||||
# Line 5
|
||||
line = fid.readline()
|
||||
l_input = re.split('[!\s]',line)
|
||||
if l_input[0]=='VALUE':
|
||||
mref = float(l_input[1])
|
||||
|
||||
else:
|
||||
mref = l_input[0].rstrip()
|
||||
|
||||
|
||||
# Line 6
|
||||
line = fid.readline()
|
||||
l_input = re.split('[!\s]',line)
|
||||
if l_input=='DEFAULT':
|
||||
wgtfile = []
|
||||
|
||||
else:
|
||||
wgtfile = l_input[0].rstrip()
|
||||
|
||||
# Line 7
|
||||
line = fid.readline()
|
||||
l_input = re.split('[!\s]',line)
|
||||
chi = float(l_input[0])
|
||||
|
||||
# Line 8
|
||||
line = fid.readline()
|
||||
l_input = re.split('[!\s]',line)
|
||||
val = np.array(l_input[0:4])
|
||||
alphas = val.astype(np.float)
|
||||
|
||||
# Line 9
|
||||
line = fid.readline()
|
||||
l_input = re.split('[!\s]',line)
|
||||
if l_input[0]=='VALUE':
|
||||
val = np.array(l_input[1:3])
|
||||
bounds = val.astype(np.float)
|
||||
|
||||
else:
|
||||
bounds = l_input[0].rstrip()
|
||||
|
||||
# Line 10
|
||||
line = fid.readline()
|
||||
l_input = re.split('[!\s]',line)
|
||||
if l_input[0]=='VALUE':
|
||||
val = np.array(l_input[1:6])
|
||||
lpnorms = val.astype(np.float)
|
||||
|
||||
else:
|
||||
lpnorms = l_input[0].rstrip()
|
||||
|
||||
# Line 11
|
||||
line = fid.readline()
|
||||
l_input = re.split('[!\s]',line)
|
||||
if l_input[0]=='VALUE':
|
||||
val = np.array(l_input[1:3])
|
||||
eps = val.astype(np.float)
|
||||
|
||||
else:
|
||||
eps = l_input[0].rstrip()
|
||||
|
||||
self.mshfile = mshfile
|
||||
self.obsfile = obsfile
|
||||
self.topofile = topofile
|
||||
self.mstart = mstart
|
||||
self._mrefInput = mref
|
||||
self.wgtfile = wgtfile
|
||||
self.chi = chi
|
||||
self.alphas = alphas
|
||||
self.bounds = bounds
|
||||
self.lpnorms = lpnorms
|
||||
self.eps = eps
|
||||
|
||||
@property
|
||||
def mesh(self):
|
||||
if getattr(self, '_mesh', None) is None:
|
||||
self._mesh = Mesh.TensorMesh.readUBC(self.basePath + self.mshfile)
|
||||
return self._mesh
|
||||
|
||||
@property
|
||||
def survey(self):
|
||||
if getattr(self, '_survey', None) is None:
|
||||
self._survey = self.readGravityObservations(self.obsfile)
|
||||
return self._survey
|
||||
|
||||
@property
|
||||
def activeCells(self):
|
||||
if getattr(self, '_activeCells', None) is None:
|
||||
if self.topofile == 'null':
|
||||
self._activeCells = np.arange(mesh.nC)
|
||||
else:
|
||||
topo = np.genfromtxt(self.basePath + self.topofile, skip_header=1)
|
||||
# Find the active cells
|
||||
self._activeCells = Gravity.getActiveTopo(self.mesh,topo,'N')
|
||||
return self._activeCells
|
||||
|
||||
|
||||
@property
|
||||
def nC(self):
|
||||
if getattr(self, '_nC', None) is None:
|
||||
self._nC = len(self.activeCells)
|
||||
return self._nC
|
||||
|
||||
@property
|
||||
def m0(self):
|
||||
if getattr(self, '_m0', None) is None:
|
||||
if isinstance(self.mstart, float):
|
||||
self._m0 = np.ones(self.nC) * self.mstart
|
||||
else:
|
||||
self._m0 = Utils.meshutils.readUBCTensorModel(self.basePath + self.mstart,self.mesh)
|
||||
self._m0 = self._m0[self.activeCells]
|
||||
|
||||
return self._m0
|
||||
|
||||
@property
|
||||
def mref(self):
|
||||
if getattr(self, '_mref', None) is None:
|
||||
if isinstance(self._mrefInput, float):
|
||||
self._mref = np.ones(self.nC) * self._mrefInput
|
||||
else:
|
||||
self._mref = Utils.meshutils.readUBCTensorModel(self.basePath + self._mrefInput, self.mesh)
|
||||
self._mref = self._mref[self.activeCells]
|
||||
return self._mref
|
||||
|
||||
|
||||
|
||||
def readGravityObservations(self, obs_file):
|
||||
"""
|
||||
Read UBC grav file format
|
||||
|
||||
INPUT:
|
||||
:param fileName, path to the UBC obs grav file
|
||||
|
||||
OUTPUT:
|
||||
:param survey
|
||||
|
||||
"""
|
||||
|
||||
fid = open(obs_file,'r')
|
||||
|
||||
# First line has the number of rows
|
||||
line = fid.readline()
|
||||
ndat = np.array(line.split(),dtype=int)
|
||||
|
||||
# Pre-allocate space for obsx, obsy, obsz, data, uncert
|
||||
line = fid.readline()
|
||||
temp = np.array(line.split(),dtype=float)
|
||||
|
||||
d = np.zeros(ndat, dtype=float)
|
||||
wd = np.zeros(ndat, dtype=float)
|
||||
locXYZ = np.zeros( (ndat,3), dtype=float)
|
||||
|
||||
for ii in range(ndat):
|
||||
|
||||
temp = np.array(line.split(),dtype=float)
|
||||
locXYZ[ii,:] = temp[:3]
|
||||
d[ii] = temp[3]
|
||||
wd[ii] = temp[4]
|
||||
line = fid.readline()
|
||||
|
||||
rxLoc = BaseGrav.RxObs(locXYZ)
|
||||
srcField = BaseGrav.SrcField([rxLoc])
|
||||
survey = BaseGrav.LinearSurvey(srcField)
|
||||
survey.dobs = d
|
||||
survey.std = wd
|
||||
return survey
|
||||
@@ -4,3 +4,4 @@ import Magnetics
|
||||
import BaseGrav
|
||||
import Gravity
|
||||
import MagneticsDriver
|
||||
import GravityDriver
|
||||
|
||||
Reference in New Issue
Block a user