From 7f7ce5e25bda392646b427146ef9fd77dd4c85d9 Mon Sep 17 00:00:00 2001
From: D Fournier <fourndo@gmail.com>
Date: Mon, 30 May 2016 17:35:47 -0700
Subject: [PATCH] Add driver for gravity. Adapt example for new Regularization
 formulation

---
 simpegPF/Dev/GRAV/Figure1_3.0.png             |   Bin 0 -> 264812 bytes
 simpegPF/Dev/GRAV/Figure2_3.0.png             |   Bin 0 -> 143463 bytes
 simpegPF/Dev/GRAV/Figure3_3.0_0.01_0.001.png  |   Bin 0 -> 771362 bytes
 simpegPF/Dev/GRAV/Figure4.png                 |   Bin 0 -> 803982 bytes
 simpegPF/Dev/GRAV/Figure5_3.0_0.01_0.001.png  |   Bin 0 -> 262953 bytes
 simpegPF/Dev/GRAV/Figure6_3.0_0.01_0.001.png  |   Bin 0 -> 155595 bytes
 simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver.py   |   248 +-
 .../GRAV/Intgrl_GRAV_Inv_Driver_LdM_Craig.py  |   378 +-
 ...GRAV_Inv_Driver_LdM_surface_layer_fixed.py |   395 +
 simpegPF/Dev/GRAV/PYGRAV3D_inv.inp            |     3 +-
 .../Dev/GRAV/Pred_compact3.0_0.01_0.001.dat   |   617 +
 .../GRAV/SimPEG_inv_l0l2_3.0_0.01_0.001.den   | 44180 +++++++++++
 simpegPF/Dev/GRAV/SimPEG_inv_l2l2.sus         | 44180 +++++++++++
 simpegPF/Dev/GRAV/SimPEG_inv_l2l2_3.0.den     | 44180 +++++++++++
 simpegPF/Dev/GRAV/Weighting_3.0.png           |   Bin 0 -> 136204 bytes
 simpegPF/Dev/MAG/SimPEG_inv_l2l2.sus          | 65674 ++++++++--------
 simpegPF/GravityDriver.py                     |   235 +
 simpegPF/__init__.py                          |     1 +
 18 files changed, 166879 insertions(+), 33212 deletions(-)
 create mode 100644 simpegPF/Dev/GRAV/Figure1_3.0.png
 create mode 100644 simpegPF/Dev/GRAV/Figure2_3.0.png
 create mode 100644 simpegPF/Dev/GRAV/Figure3_3.0_0.01_0.001.png
 create mode 100644 simpegPF/Dev/GRAV/Figure4.png
 create mode 100644 simpegPF/Dev/GRAV/Figure5_3.0_0.01_0.001.png
 create mode 100644 simpegPF/Dev/GRAV/Figure6_3.0_0.01_0.001.png
 create mode 100644 simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver_LdM_surface_layer_fixed.py
 create mode 100644 simpegPF/Dev/GRAV/Pred_compact3.0_0.01_0.001.dat
 create mode 100644 simpegPF/Dev/GRAV/SimPEG_inv_l0l2_3.0_0.01_0.001.den
 create mode 100644 simpegPF/Dev/GRAV/SimPEG_inv_l2l2.sus
 create mode 100644 simpegPF/Dev/GRAV/SimPEG_inv_l2l2_3.0.den
 create mode 100644 simpegPF/Dev/GRAV/Weighting_3.0.png
 create mode 100644 simpegPF/GravityDriver.py

diff --git a/simpegPF/Dev/GRAV/Figure1_3.0.png b/simpegPF/Dev/GRAV/Figure1_3.0.png
new file mode 100644
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diff --git a/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver.py b/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver.py
index 27fa00bf..8a2df812 100644
--- a/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver.py
+++ b/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver.py
@@ -5,72 +5,39 @@ import pylab as plt
 import os
 home_dir = '.'
 
-inpfile = 'PYGRAV3D_inv.inp'
+#inpfile = 'PYGRAV3D_inv.inp'
 
 dsep = os.path.sep
 plt.close('all')
 
 #%% User input
-# Treshold values for compact norm
-eps_p = 1e-3 # Small model values
-eps_q = 1e-3 # Small model gradient
-
 # Plotting parameter
 vmin = -0.3
 vmax = 0.3
 #%%
 # Read input file
-[mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms] = PF.Gravity.read_GRAVinv_inp(home_dir + dsep + inpfile)
+#[mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms] = PF.Gravity.read_GRAVinv_inp(home_dir + dsep + inpfile)
+driver = PF.GravityDriver.GravityDriver_Inv('PYGRAV3D_inv.inp')
+mesh = driver.mesh
+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)
 
@@ -85,60 +52,53 @@ prob.solverOpts['accuracyTol'] = 1e-4
 survey.pair(prob)
 
 # Write out the predicted file and generate the forward operator
-pred = prob.fields(mstart)
+pred = prob.fields(driver.m0)
 
 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
-
 # Load weighting  file
-if wgtfile is None:  
+if driver.wgtfile == 'DEFAULT':  
     wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, 3., np.min(mesh.hx)/4.)
     wr = wr**2.
+    
+    # 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
+    
 else:
     wr = Mesh.TensorMesh.readModelUBC(mesh, home_dir + dsep + wgtfile)   
     wr = wr[actv]
     wr = wr**2.
 
 #%% Plot depth weighting
-plt.figure()
-ax = plt.subplot()
-mesh.plotSlice(actvMap*wr, ax = ax, normal = 'Y', ind=midx+1 ,clim = (0, wr.max()))
-plt.title('Distance weighting')
-plt.xlabel('x');plt.ylabel('z')
-plt.gca().set_aspect('equal', adjustable='box')
+#plt.figure()
+#ax = plt.subplot()
+#mesh.plotSlice(actvMap*wr, ax = ax, normal = 'Y', ind=midx+1 ,clim = (0, wr.max()))
+#plt.title('Distance weighting')
+#plt.xlabel('x');plt.ylabel('z')
+#plt.gca().set_aspect('equal', adjustable='box')
 
 #%% Create inversion objects
 
-# First start with an l2 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]
+    
 
-
-# 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= 50, tolCG = 1e-4)
-
 invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
-
-# Add directives to the inversion 
-beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
-beta_init = Directives.BetaEstimate_ByEig()
-target = Directives.TargetMisfit()
-update_Jacobi = Directives.Update_lin_PreCond(onlyOnStart=True)
-
-inv = Inversion.BaseInversion(invProb, directiveList=[beta,target,beta_init,update_Jacobi])
-
-m0 = mstart
+#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=driver.eps[0], eps_q=driver.eps[1], 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*mrec
 
@@ -152,109 +112,73 @@ pred = prob.fields(mrec)
 
 print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) ) 
 
-#%% Plot out sections of the smooth model
-
-yslice = midx+1
-m_out[m_out==-100] = np.nan
-
-plt.figure()
-ax = plt.subplot(221)
-mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, 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='w',linestyle = '--')
-plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
-plt.xlabel('x');plt.ylabel('z')
-plt.gca().set_aspect('equal', adjustable='box')
-
-ax = plt.subplot(222)
-mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
-plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
-plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
-plt.xlabel('x');plt.ylabel('z')
-plt.gca().set_aspect('equal', adjustable='box')
-
-ax = plt.subplot(212)
-mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
-plt.title('Cross Section')
-plt.xlabel('x');plt.ylabel('z')
-plt.gca().set_aspect('equal', adjustable='box')
-
-plt.figure()
-ax = plt.subplot(121)
-plt.hist(mrec,100)
-plt.yscale('log', nonposy='clip')
-plt.title('Histogram of model values - Smooth')
-ax = plt.subplot(122)
-plt.hist(reg.regmesh.cellDiffxStencil*mrec,100)
-plt.yscale('log', nonposy='clip')
-plt.title('Histogram of model gradient values - Smooth')
-#%% Run one more round for sparsity
-phim = invProb.phi_m_last
-phid =  invProb.phi_d
-
-reg = Regularization.Sparse(mesh, indActive = actv, mapping = idenMap)
-reg.recModel = mrec
-reg.mref = mref
-reg.wght = wr
-reg.eps_p = eps_p
-reg.eps_q = eps_q
-reg.norms   = lpnorms
-
-dmis = DataMisfit.l2_DataMisfit(survey)
-dmis.Wd = 1./wd
-
-opt = Optimization.ProjectedGNCG(maxIter=20 , maxIterLS = 20,lower=bounds[0],upper=bounds[1], maxIterCG= 50, tolCG = 1e-4)
-
-invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = invProb.beta)
-
-# Add directives to the inversion
-beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
-update_beta = Directives.Scale_Beta(tol = 0.05)
-target = Directives.TargetMisfit()
-IRLS =Directives.Update_IRLS( phi_m_last = phim, phi_d_last = phid )
-update_Jacobi = Directives.Update_lin_PreCond(onlyOnStart=False)
-save_log = Directives.SaveOutputEveryIteration()
-save_log.fileName = 'LogName_blabla'
-
-inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS,update_beta,update_Jacobi,save_log])
-
-m0 = mrec
-
-# Run inversion
-mrec = inv.run(m0)
-
-m_out = actvMap*mrec
-
-Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l0l2.sus',m_out)
-
-pred = prob.fields(mrec)
-
-#%% Plot obs data
-PF.Magnetics.plot_obs_2D(rxLoc,pred,'Predicted Data', vmin = np.min(d), vmax = np.max(d))
-PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
-print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) ) 
 #%% Plot out a section of the model
 
 yslice = midx
 
+
+m_out = actvMap*reg.l2model
 m_out[m_out==-100] = np.nan
 
+# Write result
+Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2.sus',m_out)
+
 plt.figure()
 ax = plt.subplot(221)
-mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (mrec.min(), mrec.max()), pcolorOpts = {'cmap':'bwr'})
+mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (mrec.min(), mrec.max()))
 plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
 plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
 plt.xlabel('x');plt.ylabel('z')
 plt.gca().set_aspect('equal', adjustable='box')
 
 ax = plt.subplot(222)
-mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (mrec.min(), mrec.max()), pcolorOpts = {'cmap':'bwr'})
+mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (mrec.min(), mrec.max()))
+plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
+plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
+plt.xlabel('x');plt.ylabel('z')
+plt.gca().set_aspect('equal', adjustable='box')
+
+
+ax = plt.subplot(212)
+mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (mrec.min(), mrec.max()))
+plt.title('Cross Section')
+plt.xlabel('x');plt.ylabel('z')
+plt.gca().set_aspect('equal', adjustable='box')
+
+plt.figure()
+ax = plt.subplot(121)
+plt.hist(reg.l2model,100)
+plt.yscale('log', nonposy='clip')
+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.title('Histogram of model gradient values - Smooth')
+
+#%% Plot out a section of the model
+
+yslice = midx
+
+m_out = actvMap*mrec
+m_out[m_out==-100] = np.nan
+
+plt.figure()
+ax = plt.subplot(221)
+mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (mrec.min(), mrec.max()))
+plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
+plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
+plt.xlabel('x');plt.ylabel('z')
+plt.gca().set_aspect('equal', adjustable='box')
+
+ax = plt.subplot(222)
+mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (mrec.min(), mrec.max()))
 plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
 plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
 plt.xlabel('x');plt.ylabel('z')
 plt.gca().set_aspect('equal', adjustable='box')
 
 ax = plt.subplot(212)
-mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (mrec.min(), mrec.max()), pcolorOpts = {'cmap':'bwr'})
+mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (mrec.min(), mrec.max()))
 plt.title('Cross Section')
 plt.xlabel('x');plt.ylabel('z')
 plt.gca().set_aspect('equal', adjustable='box')
@@ -263,8 +187,10 @@ plt.figure()
 ax = plt.subplot(121)
 plt.hist(mrec,100)
 plt.yscale('log', nonposy='clip')
-plt.title('Histogram of model values - Sparse lp:'+str(lpnorms[0]))
+plt.title('Histogram of model values - Compact')
 ax = plt.subplot(122)
 plt.hist(reg.regmesh.cellDiffxStencil*mrec,100)
 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]))
\ No newline at end of file
+plt.title('Histogram of model gradient values - Compact')
+
+plt.show()
\ No newline at end of file
diff --git a/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver_LdM_Craig.py b/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver_LdM_Craig.py
index eba9dc4c..7784d070 100644
--- a/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver_LdM_Craig.py
+++ b/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver_LdM_Craig.py
@@ -5,10 +5,13 @@ import pylab as plt
 import os
 import numpy as np
 
-#home_dir = 'C:\Egnyte\Private\craigm\PHD\LdM\Gravity\Bouguer\SIMPEG\models'
-home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\SimPEG\simpegpf\simpegPF\Dev\GRAV'
-#inpfile = 'PYGRAV3D_inv_LdM_Craig.inp'
-inpfile = 'PYGRAV3D_inv_checkerboard.inp'
+
+#home_dir = 'C:\Egnyte\Private\craigm\PHD\LdM\Gravity\Bouguer\SIMPEG\models\\all_models\\density_-1.2_0.3'
+home_dir = '.\\'
+
+inpfile = 'PYGRAV3D_inv_LdM_Craig.inp'
+#inpfile = 'PYGRAV3D_inv_checkerboard.inp'
+
 dsep = '\\'
 os.chdir(home_dir)
 plt.close('all')
@@ -17,66 +20,35 @@ plt.close('all')
 # Initial beta
 beta_in = 1e-2
 
-# Treshold values for compact norm
-eps_p = 0.01 # Compact model values
-eps_q = 0.01 # ompact model gradient
-
 # Plotting parameter
-vmin = -0.1
-vmax = 0.2
+vmin = -1.2
+vmax = 1.2
+
+#weight exponent for default weighting
+wgtexp = 3.  #dont forget the "."
+
 #%%
-# Read input file
-[mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms] = PF.Gravity.read_GRAVinv_inp(home_dir + dsep + inpfile)
+driver = PF.GravityDriver.GravityDriver_Inv(home_dir + dsep + 'PYGRAV3D_inv.inp')
+mesh = driver.mesh
+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')
\ No newline at end of file
+#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')
\ No newline at end of file
diff --git a/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver_LdM_surface_layer_fixed.py b/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver_LdM_surface_layer_fixed.py
new file mode 100644
index 00000000..0326157b
--- /dev/null
+++ b/simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver_LdM_surface_layer_fixed.py
@@ -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')
\ No newline at end of file
diff --git a/simpegPF/Dev/GRAV/PYGRAV3D_inv.inp b/simpegPF/Dev/GRAV/PYGRAV3D_inv.inp
index ba5850d6..f7947918 100644
--- a/simpegPF/Dev/GRAV/PYGRAV3D_inv.inp
+++ b/simpegPF/Dev/GRAV/PYGRAV3D_inv.inp
@@ -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
\ No newline at end of file
+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
\ No newline at end of file
diff --git a/simpegPF/Dev/GRAV/Pred_compact3.0_0.01_0.001.dat b/simpegPF/Dev/GRAV/Pred_compact3.0_0.01_0.001.dat
new file mode 100644
index 00000000..cce15735
--- /dev/null
+++ b/simpegPF/Dev/GRAV/Pred_compact3.0_0.01_0.001.dat
@@ -0,0 +1,617 @@
+616
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diff --git a/simpegPF/Dev/GRAV/SimPEG_inv_l0l2_3.0_0.01_0.001.den b/simpegPF/Dev/GRAV/SimPEG_inv_l0l2_3.0_0.01_0.001.den
new file mode 100644
index 00000000..0172c4ca
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diff --git a/simpegPF/Dev/GRAV/SimPEG_inv_l2l2.sus b/simpegPF/Dev/GRAV/SimPEG_inv_l2l2.sus
new file mode 100644
index 00000000..133ebdf5
--- /dev/null
+++ b/simpegPF/Dev/GRAV/SimPEG_inv_l2l2.sus
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diff --git a/simpegPF/Dev/GRAV/SimPEG_inv_l2l2_3.0.den b/simpegPF/Dev/GRAV/SimPEG_inv_l2l2_3.0.den
new file mode 100644
index 00000000..d65ca623
--- /dev/null
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diff --git a/simpegPF/Dev/MAG/SimPEG_inv_l2l2.sus b/simpegPF/Dev/MAG/SimPEG_inv_l2l2.sus
index 766dc97e..6dd04cd0 100644
--- a/simpegPF/Dev/MAG/SimPEG_inv_l2l2.sus
+++ b/simpegPF/Dev/MAG/SimPEG_inv_l2l2.sus
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 nan
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 nan
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 nan
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 nan
 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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@@ -16026,18 +16026,18 @@ nan
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 nan
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 nan
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@@ -16065,759 +16065,759 @@ nan
 nan
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 nan
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 nan
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 nan
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@@ -16966,18 +16966,18 @@ nan
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 nan
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@@ -17005,759 +17005,759 @@ nan
 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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@@ -17905,19 +17905,19 @@ nan
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 nan
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@@ -17925,799 +17925,799 @@ nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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@@ -18826,18 +18826,18 @@ nan
 nan
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 nan
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@@ -18845,19 +18845,19 @@ nan
 nan
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 nan
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@@ -18865,799 +18865,799 @@ nan
 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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-nan
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 nan
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@@ -19766,18 +19766,18 @@ nan
 nan
 nan
 nan
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 nan
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@@ -19785,19 +19785,19 @@ nan
 nan
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 nan
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@@ -19805,799 +19805,799 @@ nan
 nan
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 nan
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 nan
 nan
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 nan
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 nan
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 nan
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--3.848357350344805037e-05
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 nan
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@@ -20687,17 +20687,17 @@ nan
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 nan
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@@ -20706,18 +20706,18 @@ nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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@@ -21627,17 +21627,17 @@ nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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@@ -27325,19 +27325,19 @@ nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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@@ -28305,719 +28305,719 @@ nan
 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
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 nan
 nan
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 nan
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 nan
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 nan
 nan
 nan
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 nan
 nan
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 nan
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 nan
 nan
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 nan
 nan
 nan
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 nan
 nan
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@@ -43828,16 +43828,16 @@ nan
 nan
 nan
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 nan
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 nan
 nan
 nan
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 nan
 nan
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 nan
 nan
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 nan
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 nan
 nan
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 nan
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 nan
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 nan
 nan
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@@ -44128,16 +44128,16 @@ nan
 nan
 nan
 nan
--2.800712105053947002e-05
--2.974752127857378488e-05
--2.363699509219379733e-05
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 nan
 nan
 nan
@@ -44149,15 +44149,15 @@ nan
 nan
 nan
 nan
--5.654378958740323619e-05
--5.175714523025249237e-05
--4.411473043872935650e-05
--3.492064306811720715e-05
--2.561887679750598281e-05
--2.231266708291691959e-05
--4.599707311861385211e-05
--3.869236929428097492e-05
--6.169692597475806911e-06
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 nan
 nan
 nan
@@ -44169,12 +44169,12 @@ nan
 nan
 nan
 nan
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diff --git a/simpegPF/GravityDriver.py b/simpegPF/GravityDriver.py
new file mode 100644
index 00000000..56151387
--- /dev/null
+++ b/simpegPF/GravityDriver.py
@@ -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
diff --git a/simpegPF/__init__.py b/simpegPF/__init__.py
index 96fafd72..1582feec 100644
--- a/simpegPF/__init__.py
+++ b/simpegPF/__init__.py
@@ -4,3 +4,4 @@ import Magnetics
 import BaseGrav
 import Gravity
 import MagneticsDriver
+import GravityDriver