no message

Better list comprehension.

SimPEG/DCIP/DCIPUtils.py

@@ -169,7 +169,7 @@ def readUBC_DC2DModel(fileName):
 
     return model
 
-def plot_pseudoSection(DCsurvey, axs, stype):
+def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", clim=None):
     """
         Read list of 2D tx-rx location and plot a speudo-section of apparent
         resistivity.
@@ -179,7 +179,7 @@ def plot_pseudoSection(DCsurvey, axs, stype):
         Input:
         :param d2D, z0
         :switch stype -> Either 'pdp' (pole-dipole) | 'dpdp' (dipole-dipole)
-
+        :switch dtype=-> Either 'appr' (app. res) | 'appc' (app. con) | 'volt' (potential)
         Output:
         :figure scatter plot overlayed on image
 
@@ -221,20 +221,43 @@ def plot_pseudoSection(DCsurvey, axs, stype):
         Cmid = (Tx[0][0] + Tx[1][0])/2
         Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
 
-        # Compute pant leg of apparent rho
-        if stype == 'pdp':
-            leg =  data * 2*np.pi  * MA * ( MA + MN ) / MN
+        # Change output for dtype
+        if dtype == 'volt':
 
-            leg = np.log10(abs(1/leg))
+            rho = np.hstack([rho,data])
 
-        elif stype == 'dpdp':
-            leg = data * 2*np.pi / ( 1/MA - 1/MB - 1/NB + 1/NA )
+        else:
 
+            # Compute pant leg of apparent rho
+            if stype == 'pdp':
+
+                leg =  data * 2*np.pi  * MA * ( MA + MN ) / MN
+
+            elif stype == 'dpdp':
+
+                leg = data * 2*np.pi / ( 1/MA - 1/MB - 1/NB + 1/NA )
+
+            else:
+                print """dtype must be 'pdp'(pole-dipole) | 'dpdp' (dipole-dipole) """
+                break
+
+
+            if dtype == 'appc':
+
+                leg = np.log10(abs(1./leg))
+                rho = np.hstack([rho,leg])
+
+            elif dtype == 'appr':
+
+                leg = np.log10(abs(leg))
+                rho = np.hstack([rho,leg])
+
+            else:
+                print """dtype must be 'appr' | 'appc' | 'volt' """
+                break
 
         midx = np.hstack([midx, ( Cmid + Pmid )/2 ])
         midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + z0 ])
-        rho = np.hstack([rho,leg])
-
 
     ax = axs
 
@@ -242,26 +265,38 @@ def plot_pseudoSection(DCsurvey, axs, stype):
     grid_x, grid_z = np.mgrid[np.min(midx):np.max(midx), np.min(midz):np.max(midz)]
     grid_rho = griddata(np.c_[midx,midz], rho.T, (grid_x, grid_z), method='linear')
 
+    if clim == None:
+        vmin, vmax = rho.min(), rho.max()
+    else:
+        vmin, vmax = clim[0], clim[1]
 
-    plt.imshow(grid_rho.T, extent = (np.min(midx),np.max(midx),np.min(midz),np.max(midz)), origin='lower', alpha=0.8, vmin = np.min(rho), vmax = np.max(rho))
-    cbar = plt.colorbar(format = '%.2f',fraction=0.04,orientation="horizontal")
+    grid_rho = np.ma.masked_where(np.isnan(grid_rho), grid_rho)
+    ph = plt.pcolormesh(grid_x[:,0],grid_z[0,:],grid_rho.T, clim=(vmin, vmax))
+    cbar = plt.colorbar(format="$10^{%.1f}$",fraction=0.04,orientation="horizontal")
 
     cmin,cmax = cbar.get_clim()
     ticks = np.linspace(cmin,cmax,3)
     cbar.set_ticks(ticks)
+    cbar.ax.tick_params(labelsize=10)
+    
+    if dtype == 'appc':
+        cbar.set_label("App.Cond",size=12)
+    elif dtype == 'appr':
+        cbar.set_label("App.Res.",size=12)
+    elif dtype == 'volt':
+        cbar.set_label("Potential (V)",size=12)
 
     # Plot apparent resistivity
-    plt.scatter(midx,midz,s=50,c=rho.T)
+    ax.scatter(midx,midz,s=10,c=rho.T, vmin =vmin, vmax = vmax, clim=(vmin, vmax))
 
-    ax.set_xticklabels([])
+    #ax.set_xticklabels([])
+    #ax.set_yticklabels([])
 
-    ax.set_ylabel('Z')
-    ax.yaxis.tick_right()
-    ax.yaxis.set_label_position('right')
     plt.gca().set_aspect('equal', adjustable='box')
 
 
-    return ax
+
+    return ph
 
 def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
     """
@@ -361,16 +396,6 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
                 srcClass = DC.SrcDipole([rxClass], M[ii,:],M[ii,:])
             SrcList.append(srcClass)
 
-#==============================================================================
-#     elif re.match(stype,'dpdp'):
-#
-#         for ii in range(0, int(nstn)-2):
-#
-#             indx = np.min([ii+n+1,nstn])
-#             Tx.append(np.c_[M[ii,:],N[ii,:]])
-#             Rx.append(np.c_[M[ii+2:indx,:],N[ii+2:indx,:]])
-#==============================================================================
-
     elif stype == 'gradient':
 
         # Gradient survey only requires Tx at end of line and creates a square
@@ -513,22 +538,22 @@ def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):
 
     fid.close()
 
-def convertObs_DC3D_to_2D(DCsurvey,lineID):
+def convertObs_DC3D_to_2D(DCsurvey,lineID, flag = 'local'):
     """
-        Read DC survey and data and change
-        coordinate system to distance along line assuming
-        all data is acquired along line.
-        First transmitter pole is assumed to be at the origin
+        Read DC survey and projects the coordinate system
+        according to the flag = 'Xloc' | 'Yloc' | 'local' (default)
+        In the 'local' system, station coordinates are referenced
+        to distance from the first srcLoc[0].loc[0]
 
-        Assumes flat topo for now...
+        The Z value is preserved, but Y coordinates zeroed.
 
         Input:
-        :param Tx, Rx
+        :param survey3D
 
         Output:
-        :figure Tx2d, Rx2d
+        :figure survey2D
 
-        Edited Feb 17th, 2016
+        Edited April 6th, 2016
 
         @author: dominiquef
 
@@ -570,25 +595,39 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID):
             Rx = DCsurvey.srcList[indx[ii]].rxList[0].locs
             nrx = Rx[0].shape[0]
 
-            # Find A electrode along line
-            vec, r = r_unit(x0,Tx[ii][0,0:2])
-            A = stn_id(vecTx,vec,r)
+            if flag == 'local':
+                # Find A electrode along line
+                vec, r = r_unit(x0,Tx[ii][0,0:2])
+                A = stn_id(vecTx,vec,r)
 
-            # Find B electrode along line
-            vec, r = r_unit(x0,Tx[ii][1,0:2])
-            B = stn_id(vecTx,vec,r)
+                # Find B electrode along line
+                vec, r = r_unit(x0,Tx[ii][1,0:2])
+                B = stn_id(vecTx,vec,r)
 
-            M = np.zeros(nrx)
-            N = np.zeros(nrx)
-            for kk in range(nrx):
+                M = np.zeros(nrx)
+                N = np.zeros(nrx)
+                for kk in range(nrx):
 
-                # Find all M electrodes along line
-                vec, r = r_unit(x0,Rx[0][kk,0:2])
-                M[kk] = stn_id(vecTx,vec,r)
+                    # Find all M electrodes along line
+                    vec, r = r_unit(x0,Rx[0][kk,0:2])
+                    M[kk] = stn_id(vecTx,vec,r)
 
-                # Find all N electrodes along line
-                vec, r = r_unit(x0,Rx[1][kk,0:2])
-                N[kk] = stn_id(vecTx,vec,r)
+                    # Find all N electrodes along line
+                    vec, r = r_unit(x0,Rx[1][kk,0:2])
+                    N[kk] = stn_id(vecTx,vec,r)
+            elif flag == 'Yloc':
+                """ Flip the XY axis locs"""
+                A = Tx[ii][0,1]
+                B = Tx[ii][1,1]
+                M = Rx[0][:,1]
+                N = Rx[1][:,1]
+
+            elif flag == 'Xloc':
+                """ Copy the rx-tx locs"""
+                A = Tx[ii][0,0]
+                B = Tx[ii][1,0]
+                M = Rx[0][:,0]
+                N = Rx[1][:,0]
 
             Rx = DC.RxDipole(np.c_[M,np.zeros(nrx),Rx[0][:,2]],np.c_[N,np.zeros(nrx),Rx[1][:,2]])
 
@@ -604,16 +643,16 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID):
 
 def readUBC_DC3Dobs(fileName):
     """
-        Read UBC GIF DCIP 3D observation file and generate arrays for tx-rx location
+        Read UBC GIF DCIP 3D observation file and generate survey
 
         Input:
         :param fileName, path to the UBC GIF 3D obs file
 
         Output:
-        :param rx, tx, d, wd
+        :param DCIPsurvey
         :return
 
-        Created on Mon December 7th, 2015
+        Created on Mon April 6th, 2015
 
         @author: dominiquef
 
@@ -688,6 +727,7 @@ def readUBC_DC3Dobs(fileName):
 
 def readUBC_DC2Dobs(fileName):
     """
+        ------- NEEDS TO BE UPDATED ------
         Read UBC GIF 2D observation file and generate arrays for tx-rx location
 
         Input:
@@ -735,6 +775,73 @@ def readUBC_DC2Dobs(fileName):
 
     return tx, rx, d, wd
 
+def readUBC_DC2Dpre(fileName):
+    """
+        Read UBC GIF DCIP 2D observation file and generate arrays for tx-rx location
+
+        Input:
+        :param fileName, path to the UBC GIF 3D obs file
+
+        Output:
+        DCsurvey
+        :return
+
+        Created on Mon March 9th, 2016 << Doug's 70th Birthday !! >>
+
+        @author: dominiquef
+
+    """
+
+    # Load file
+    obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
+
+    # Pre-allocate
+    srcLists = []
+    Rx = []
+    d = []
+    zflag = True # Flag for z value provided
+
+    for ii in range(obsfile.shape[0]):
+
+        if not obsfile[ii]:
+            continue
+
+        # First line is transmitter with number of receivers
+
+
+        temp = (np.fromstring(obsfile[ii], dtype=float,sep=' ').T)
+
+
+        # Check if z value is provided, if False -> nan
+        if len(temp)==5:
+            tx = np.r_[temp[0],np.nan,np.nan,temp[1],np.nan,np.nan]
+            zflag = False
+
+        else:
+            tx = np.r_[temp[0],np.nan,temp[1],temp[2],np.nan,temp[3]]
+
+
+        if zflag:
+            rx = np.c_[temp[4],np.nan,temp[5],temp[6],np.nan,temp[7]]
+
+
+        else:
+            rx = np.c_[temp[2],np.nan,np.nan,temp[3],np.nan,np.nan]
+            # Check if there is data with the location
+
+        d.append(temp[-1])
+
+
+        Rx = DC.RxDipole(rx[:,:3],rx[:,3:])
+        srcLists.append( DC.SrcDipole( [Rx], tx[:3],tx[3:]) )
+
+    # Create survey class
+    survey = DC.SurveyDC(srcLists)
+
+    survey.dobs = np.asarray(d)
+
+    return {'DCsurvey':survey}
+
 def readUBC_DC2DMesh(fileName):
     """
         Read UBC GIF 2DTensor mesh and generate 2D Tensor mesh in simpeg
@@ -928,7 +1035,6 @@ def getSrc_locs(DCsurvey):
 
     srcMat = np.zeros((DCsurvey.nSrc,2,3))
     for ii in range(DCsurvey.nSrc):
-        print np.asarray(DCsurvey.srcList[ii].loc).shape
         srcMat[ii,:,:] =  np.asarray(DCsurvey.srcList[ii].loc)
 
     return srcMat

SimPEG/Directives.py

@@ -216,7 +216,7 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
         # Save the data.
         ms = self.reg.Ws * ( self.reg.mapping * (self.invProb.curModel - self.reg.mref) )
         phi_ms = 0.5*ms.dot(ms)
-        if self.reg.smoothModel == True:
+        if self.reg.mrefInSmooth == True:
             mref = self.reg.mref
         else:
             mref = 0
@@ -249,7 +249,7 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
         # Save the data.
         ms = self.reg.Ws * ( self.reg.mapping * (self.invProb.curModel - self.reg.mref) )
         phi_ms = 0.5*ms.dot(ms)
-        if self.reg.smoothModel == True:
+        if self.reg.mrefInSmooth == True:
             mref = self.reg.mref
         else:
             mref = 0
@@ -271,7 +271,6 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
         np.savez('{:s}-{:03d}'.format(self.fileName,self.opt.iter), iter=self.opt.iter, beta=self.invProb.beta, phi_d=self.invProb.phi_d, phi_m=self.invProb.phi_m, phi_ms=phi_ms, phi_mx=phi_mx, phi_my=phi_my, phi_mz=phi_mz,f=self.opt.f, m=self.invProb.curModel,dpred=self.invProb.dpred)
 
 
-
 # class UpdateReferenceModel(Parameter):
 
 #     mref0 = None
@@ -283,3 +282,63 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
 #             mref = self.mref0
 #         self.m_prev = self.invProb.m_current
 #         return mref
+
+class update_IRLS(InversionDirective):
+
+    eps_min = None
+    factor = None
+    gamma = None
+    phi_m_last = None
+    phi_d_last = None
+    
+    def initialize(self):
+
+        # Scale the regularization for changes in norm
+        if getattr(self, 'phi_m_last', None) is not None:
+            self.reg.gamma = 1.
+            phim_new = self.reg.eval(self.invProb.curModel)
+            self.gamma = self.phi_m_last / phim_new
+
+        self.reg.curModel = self.invProb.curModel
+        self.reg.gamma = self.gamma
+        
+        if getattr(self, 'phi_d_last', None) is None:
+            self.phi_d_last = self.invProb.phi_d
+            
+    def endIter(self):
+        # Cool the threshold parameter
+        if getattr(self, 'factor', None) is not None:
+            eps = self.reg.eps / self.factor
+
+            if getattr(self, 'eps_min', None) is not None:
+                self.reg.eps = np.max([self.eps_min,eps])
+            else:
+                self.reg.eps = eps
+
+        # Get phi_m at the end of current iteration
+        self.phi_m_last = self.invProb.phi_m_last
+        
+         # Update the model used for the IRLS weights
+        self.reg.curModel = self.invProb.curModel
+
+        # Update the pre-conditioner
+        diagA = np.sum(self.prob.G**2.,axis=0) + self.invProb.beta*(self.reg.W.T*self.reg.W).diagonal() * (self.reg.mapping * np.ones(self.reg.curModel.size))**2.
+        PC     = Utils.sdiag(diagA**-1.)
+        self.opt.approxHinv = PC
+         
+        # Temporarely set gamma to 1.
+        self.reg.gamma = 1.
+        
+        # Compute change in model objective function and update scaling
+        phim_new = self.reg.eval(self.invProb.curModel)
+        self.reg.gamma = self.phi_m_last / phim_new
+        
+        # TO DO: Re-scale beta if too much change in misfit
+        self.invProb.beta = self.invProb.beta * self.phi_d_last / self.invProb.phi_d
+        
+#==============================================================================
+#          import pylab as plt
+#          plt.figure()
+#          ax = plt.subplot(221)
+#          self.prob.mesh.plotSlice(self.invProb.curModel, ax = ax, normal = 'Z', ind=-5, clim = (0, 0.005))
+#==============================================================================

SimPEG/EM/FDEM/SrcFDEM.py

@@ -9,10 +9,8 @@ class BaseSrc(Survey.BaseSrc):
     """
 
     freq = None
-    integrate = False
-
-    def __init__(self, rxList, **kwargs):
-        Survey.BaseSrc.__init__(self, rxList, **kwargs)
+    # rxPair = RxFDEM
+    integrate = True
 
     def eval(self, prob):
         """
@@ -53,9 +51,6 @@ class BaseSrc(Survey.BaseSrc):
         :rtype: numpy.ndarray
         :return: primary magnetic flux density
         """
-        #TODO : allow hPrimary to be provided and get bPrimary from it
-        if getattr(self, '_bPrimary', None) is not None:
-            return self._bPrimary
         return Zero()
 
     def hPrimary(self, prob):
@@ -66,8 +61,6 @@ class BaseSrc(Survey.BaseSrc):
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
-        if getattr(self, '_hPrimary', None) is not None:
-            return self._hPrimary
         return Zero()
 
     def ePrimary(self, prob):
@@ -78,8 +71,6 @@ class BaseSrc(Survey.BaseSrc):
         :rtype: numpy.ndarray
         :return: primary electric field
         """
-        if getattr(self, '_ePrimary', None) is not None:
-            return self._ePrimary
         return Zero()
 
     def jPrimary(self, prob):
@@ -90,8 +81,6 @@ class BaseSrc(Survey.BaseSrc):
         :rtype: numpy.ndarray
         :return: primary current density
         """
-        if getattr(self, '_jPrimary', None) is not None:
-            return self._jPrimary
         return Zero()
 
     def s_m(self, prob):
@@ -147,13 +136,14 @@ class RawVec_e(BaseSrc):
     :param list rxList: receiver list
     :param float freq: frequency
     :param numpy.array s_e: electric source term
-    :param bool integrate: Integrate the source term (multiply by Me) [False]
+    :param bool integrate: Integrate the source term (multiply by Me) [True]
     """
 
-    def __init__(self, rxList, freq, s_e, **kwargs): #ePrimary=None, jPrimary=None, hPrimary=None, bPrimary=None
+    def __init__(self, rxList, freq, s_e, integrate=True): #, ePrimary=None, bPrimary=None, hPrimary=None, jPrimary=None):
         self._s_e = np.array(s_e, dtype=complex)
         self.freq = float(freq)
-        [setattr(self, '_%s'%primField, kwargs[primField]) for primField in ['ePrimary', 'jPrimary', 'hPrimary', 'bPrimary'] if kwargs.get(primField) is not None]
+        self.integrate = integrate
+
         BaseSrc.__init__(self, rxList)
 
     def s_e(self, prob):
@@ -176,13 +166,14 @@ class RawVec_m(BaseSrc):
     :param float freq: frequency
     :param rxList: receiver list
     :param numpy.array s_m: magnetic source term
-    :param bool integrate: Integrate the source term (multiply by Me) [False]
+    :param bool integrate: Integrate the source term (multiply by Me) [True]
     """
 
-    def __init__(self, rxList, freq, s_m, **kwargs): #ePrimary=None, jPrimary=None, hPrimary=None, bPrimary=None):
+    def __init__(self, rxList, freq, s_m, integrate=True):  #ePrimary=Zero(), bPrimary=Zero(), hPrimary=Zero(), jPrimary=Zero()):
         self._s_m = np.array(s_m, dtype=complex)
         self.freq = float(freq)
-        [setattr(self, '_%s'%primField, kwargs[primField]) for primField in ['ePrimary', 'jPrimary', 'hPrimary', 'bPrimary'] if kwargs.get(primField) is not None]
+        self.integrate = integrate
+
         BaseSrc.__init__(self, rxList)
 
     def s_m(self, prob):
@@ -206,14 +197,14 @@ class RawVec(BaseSrc):
     :param float freq: frequency
     :param numpy.array s_m: magnetic source term
     :param numpy.array s_e: electric source term
-    :param bool integrate: Integrate the source term (multiply by Me) [False]
+    :param bool integrate: Integrate the source term (multiply by Me) [True]
     """
-    def __init__(self, rxList, freq, s_m, s_e, **kwargs): #ePrimary=None, jPrimary=None, hPrimary=None, bPrimary=None, **kwargs):
+    def __init__(self, rxList, freq, s_m, s_e, integrate=True):
         self._s_m = np.array(s_m, dtype=complex)
         self._s_e = np.array(s_e, dtype=complex)
         self.freq = float(freq)
-        [setattr(self, '_%s'%primField, kwargs[primField]) for primField in ['ePrimary', 'jPrimary', 'hPrimary', 'bPrimary'] if kwargs.get(primField) is not None]
-        BaseSrc.__init__(self, rxList, **kwargs)
+        self.integrate = integrate
+        BaseSrc.__init__(self, rxList)
 
     def s_m(self, prob):
         """
@@ -287,13 +278,14 @@ class MagDipole(BaseSrc):
     :param float mu: background magnetic permeability
     """
 
-    def __init__(self, rxList, freq, loc, orientation='Z', moment=1., mu=mu_0, **kwargs):
+    def __init__(self, rxList, freq, loc, orientation='Z', moment=1., mu=mu_0):
         self.freq = float(freq)
         self.loc = loc
         self.orientation = orientation
         assert orientation in ['X','Y','Z'], "Orientation (right now) doesn't actually do anything! The methods in SrcUtils should take care of this..."
         self.moment = moment
         self.mu = mu
+        self.integrate = False
         BaseSrc.__init__(self, rxList)
 
     def bPrimary(self, prob):
@@ -551,7 +543,7 @@ class CircularLoop(BaseSrc):
             if not prob.mesh.isSymmetric:
                 # TODO ?
                 raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-            a = MagneticLoopVectorPotential(self.loc, gridY, 'y', moment=self.radius, mu=self.mu)
+            a = MagneticDipoleVectorPotential(self.loc, gridY, 'y', moment=self.radius, mu=self.mu)
 
         else:
             srcfct = MagneticDipoleVectorPotential

SimPEG/EM/Utils/testingUtils.py

@@ -20,7 +20,7 @@ def getFDEMProblem(fdemType, comp, SrcList, freq, useMu=False, verbose=False):
     mesh = Mesh.TensorMesh([hx,hy,hz],['C','C','C'])
 
     if useMu is True:
-        mapping = [('sigma', Maps.ExpMap(mesh)), ('mu', Maps.IdentityMap(mesh))]
+        mapping = [('sigma', Maps.ExpMap(mesh)), ('mu', Maps.IdentityMap(mesh))] 
     else:
         mapping = Maps.ExpMap(mesh)
 
@@ -43,14 +43,14 @@ def getFDEMProblem(fdemType, comp, SrcList, freq, useMu=False, verbose=False):
                 S_e = np.zeros(mesh.nE)
                 S_m[Utils.closestPoints(mesh,[0.,0.,0.],'Fz') + np.sum(mesh.vnF[:1])] = 1e-3
                 S_e[Utils.closestPoints(mesh,[0.,0.,0.],'Ez') + np.sum(mesh.vnE[:1])] = 1e-3
-                Src.append(EM.FDEM.Src.RawVec([Rx0], freq, S_m, mesh.getEdgeInnerProduct()*S_e))
+                Src.append(EM.FDEM.Src.RawVec([Rx0], freq, S_m, S_e))
 
             elif fdemType is 'h' or fdemType is 'j':
                 S_m = np.zeros(mesh.nE)
                 S_e = np.zeros(mesh.nF)
                 S_m[Utils.closestPoints(mesh,[0.,0.,0.],'Ez') + np.sum(mesh.vnE[:1])] = 1e-3
                 S_e[Utils.closestPoints(mesh,[0.,0.,0.],'Fz') + np.sum(mesh.vnF[:1])] = 1e-3
-                Src.append(EM.FDEM.Src.RawVec([Rx0], freq, mesh.getEdgeInnerProduct()*S_m, S_e))
+                Src.append(EM.FDEM.Src.RawVec([Rx0], freq, S_m, S_e))
 
     if verbose:
         print '  Fetching %s problem' % (fdemType)
@@ -90,7 +90,7 @@ def crossCheckTest(SrcList, fdemType1, fdemType2, comp, addrandoms = False, useM
     prb1 = getFDEMProblem(fdemType1, comp, SrcList, freq, useMu, verbose)
     mesh = prb1.mesh
     print 'Cross Checking Forward: %s, %s formulations - %s' % (fdemType1, fdemType2, comp)
-
+    
     logsig = np.log(np.ones(mesh.nC)*CONDUCTIVITY)
     mu = np.ones(mesh.nC)*MU
 

SimPEG/Examples/DC_Forward_PseudoSection.py

@@ -2,19 +2,27 @@ from SimPEG import Mesh, Utils, np, sp
 import SimPEG.DCIP as DC
 import time
 
-def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
+def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', dtype='appc', plotIt=True):
     """
         DC Forward Simulation
         =====================
 
-        Forward model conductive spheres in a half-space and plot a pseudo-section
-
+        Forward model two conductive spheres in a half-space and plot a 
+        pseudo-section. Assumes an infinite line source and measures along the
+        center of the spheres.
+        
+        INPUT:
+        loc     = Location of spheres [[x1,y1,z1],[x2,y2,z2]]
+        radi    = Radius of spheres [r1,r2]
+        param   = Conductivity of background and two spheres [m0,m1,m2]
+        stype   = survey type "pdp" (pole dipole) or "dpdp" (dipole dipole)
+        dtype   = Data type "appr" (app res) | "appc" (app cond) | "volt" (potential)
         Created by @fourndo on Mon Feb 01 19:28:06 2016
 
     """
 
     assert stype in ['pdp', 'dpdp'], "Source type (stype) must be pdp or dpdp (pole dipole or dipole dipole)"
-
+    assert dtype in ['appr', 'appc', 'volt'], "Data type (dtype) must be appr (app res) or appc (app cond) or volt (potential)"
 
     if loc is None:
         loc = np.c_[[-50.,0.,-50.],[50.,0.,-50.]]
@@ -27,7 +35,6 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
 
 
     # First we need to create a mesh and a model.
-
     # This is our mesh
     dx    = 5.
 
@@ -52,14 +59,10 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
     # Get index of the center
     indy = int(mesh.nCy/2)
 
-
     # Plot the model for reference
     # Define core mesh extent
     xlim = 200
-    zlim = 125
-
-    # Specify the survey type: "pdp" | "dpdp"
-
+    zlim = 100
 
     # Then specify the end points of the survey. Let's keep it simple for now and survey above the anomalies, top of the mesh
     ends = [(-175,0),(175,0)]
@@ -77,12 +80,13 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
     dl_len = np.sqrt( np.sum((locs[0,:] - locs[1,:])**2) )
     dl_x = ( Tx[-1][0,1] - Tx[0][0,0] ) / dl_len
     dl_y = ( Tx[-1][1,1] - Tx[0][1,0]  ) / dl_len
-    azm =  np.arctan(dl_y/dl_x)
+    #azm =  np.arctan(dl_y/dl_x)
 
     #Set boundary conditions
     mesh.setCellGradBC('neumann')
 
-    # Define the differential operators needed for the DC problem
+    # Define the linear system needed for the DC problem. We assume an infitite
+    # line source for simplicity.
     Div = mesh.faceDiv
     Grad = mesh.cellGrad
     Msig = Utils.sdiag(1./(mesh.aveF2CC.T*(1./model)))
@@ -145,16 +149,23 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
     print 'Forward completed'
 
     # Let's just convert the 3D format into 2D (distance along line) and plot
-    # [Tx2d, Rx2d] = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc))
-    survey2D = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc))
+    survey2D = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc) , 'Xloc')
     survey2D.dobs =np.hstack(data)
-    # Here is an example for the first tx-rx array
+
     if plotIt:
         import matplotlib.pyplot as plt
-        fig = plt.figure()
+        fig = plt.figure(figsize=(7,7))
         ax = plt.subplot(2,1,1, aspect='equal')
-        mesh.plotSlice(np.log10(model), ax =ax, normal = 'Y', ind = indy,grid=True)
-        ax.set_title('E-W section at '+str(mesh.vectorCCy[indy])+' m')
+        # Plot the location of the spheres for reference
+        circle1=plt.Circle((loc[0,0],loc[2,0]),radi[0],color='w',fill=False, lw=3)
+        circle2=plt.Circle((loc[0,1],loc[2,1]),radi[1],color='k',fill=False, lw=3)
+        ax.add_artist(circle1)
+        ax.add_artist(circle2)
+
+        dat = mesh.plotSlice(np.log10(model), ax =ax, normal = 'Y',
+                             ind = indy,grid=True, clim = np.log10([sig.min(),sig.max()]))
+
+        ax.set_title('3-D model')
         plt.gca().set_aspect('equal', adjustable='box')
 
         plt.scatter(Tx[0][0,:],Tx[0][2,:],s=40,c='g', marker='v')
@@ -163,22 +174,34 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
         plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
 
 
-        ax = plt.subplot(2,1,2, aspect='equal')
+        pos =  ax.get_position()
+        ax.set_position([pos.x0 , pos.y0 + 0.025 ,  pos.width, pos.height])
+        pos =  ax.get_position()
+        cbarax = fig.add_axes([pos.x0 , pos.y0 + 0.025 ,  pos.width, pos.height * 0.04])  ## the parameters are the specified position you set
+        cb = fig.colorbar(dat[0],cax=cbarax, orientation="horizontal",
+                          ax = ax, ticks=np.linspace(np.log10(sig.min()),
+                         np.log10(sig.max()), 3), format="$10^{%.1f}$")
+        cb.set_label("Conductivity (S/m)",size=12)
+        cb.ax.tick_params(labelsize=12)
+
+        # Second plot for the predicted apparent resistivity data
+        ax2 = plt.subplot(2,1,2, aspect='equal')
 
         # Plot the location of the spheres for reference
-        circle1=plt.Circle((loc[0,0]-Tx[0][0,0],loc[2,0]),radi[0],color='w',fill=False, lw=3)
-        circle2=plt.Circle((loc[0,1]-Tx[0][0,0],loc[2,1]),radi[1],color='k',fill=False, lw=3)
-        ax.add_artist(circle1)
-        ax.add_artist(circle2)
+        circle1=plt.Circle((loc[0,0],loc[2,0]),radi[0],color='w',fill=False, lw=3)
+        circle2=plt.Circle((loc[0,1],loc[2,1]),radi[1],color='k',fill=False, lw=3)
+        ax2.add_artist(circle1)
+        ax2.add_artist(circle2)
 
         # Add the speudo section
-        DC.plot_pseudoSection(survey2D,ax,stype)
+        dat = DC.plot_pseudoSection(survey2D,ax2,stype=stype, dtype = dtype)
 
         # plt.scatter(Tx2d[0][:],Tx[0][2,:],s=40,c='g', marker='v')
         # plt.scatter(Rx2d[0][:],Rx[0][:,2::3],s=40,c='y')
         # plt.plot(np.r_[Tx2d[0][0],Rx2d[-1][-1,-1]],np.ones(2)*mesh.vectorNz[-1], color='k')
-        plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
+        ax2.set_title('Apparent Conductivity data')
 
+        plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
         plt.show()
 
         return fig, ax

SimPEG/Examples/EM_FDEM_1D_Inversion.py

@@ -48,8 +48,7 @@ def run(plotIt=True):
     freqs = np.logspace(1,3,10)
     srcLoc = np.array([0., 0., 10.])
 
-    srcList = []
-    [srcList.append(EM.FDEM.Src.MagDipole([bzi],freq, srcLoc,orientation='Z')) for freq in freqs]
+    srcList = [EM.FDEM.Src.MagDipole([bzi],freq, srcLoc,orientation='Z') for freq in freqs]
 
     survey = EM.FDEM.Survey(srcList)
     prb = EM.FDEM.Problem_b(mesh, mapping=mapping)

SimPEG/Examples/EM_Schenkel_Morrison_Casing.py

@@ -0,0 +1,275 @@
+from SimPEG import *
+from SimPEG.EM import FDEM, Analytics, mu_0
+import time
+
+try:
+    from pymatsolver import MumpsSolver
+    solver = MumpsSolver
+except Exception:
+    solver = SolverLU
+    pass
+
+def run(plotIt=True):
+    """
+        EM: Schenkel and Morrison Casing Model
+        ======================================
+
+        Here we create and run a FDEM forward simulation to calculate the vertical
+        current inside a steel-cased. The model is based on the Schenkel and
+        Morrison Casing Model, and the results are used in a 2016 SEG abstract by
+        Yang et al.
+
+        - Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
+
+
+        The model consists of:
+        - Air: Conductivity 1e-8 S/m, above z = 0
+        - Background: conductivity 1e-2 S/m, below z = 0
+        - Casing: conductivity 1e6 S/m
+            - 300m long
+            - radius of 0.1m
+            - thickness of 6e-3m
+
+        Inside the casing, we take the same conductivity as the background.
+
+        We are using an EM code to simulate DC, so we use frequency low enough
+        that the skin depth inside the casing is longer than the casing length (f
+        = 1e-6 Hz). The plot produced is of the current inside the casing.
+
+        These results are shown in the SEG abstract by Yang et al., 2016: 3D DC
+        resistivity modeling of steel casing for reservoir monitoring using
+        equivalent resistor network. The solver used to produce these results and
+        achieve the CPU time of ~30s is Mumps, which was installed using pymatsolver_
+
+        .. _pymatsolver: https://github.com/rowanc1/pymatsolver
+
+        This example is on figshare: https://dx.doi.org/10.6084/m9.figshare.3126961.v1
+
+        If you would use this example for a code comparison, or build upon it, a
+        citation would be much appreciated!
+
+    """
+
+    if plotIt:
+        import matplotlib.pylab as plt
+
+    # ------------------ MODEL ------------------
+    sigmaair = 1e-8 # air
+    sigmaback = 1e-2 # background
+    sigmacasing = 1e6 # casing
+    sigmainside = sigmaback # inside the casing
+
+
+    casing_t = 0.006  # 1cm thickness
+    casing_l = 300   # length of the casing
+
+    casing_r = 0.1
+    casing_a = casing_r - casing_t/2. # inner radius
+    casing_b = casing_r + casing_t/2. # outer radius
+    casing_z = np.r_[-casing_l,0.]
+
+
+    # ------------------ SURVEY PARAMETERS ------------------
+    freqs = np.r_[1e-6] #[1e-1, 1, 5] # frequencies
+    dsz = -300 # down-hole z source location
+    src_loc = np.r_[0.,0.,dsz]
+    inf_loc = np.r_[0.,0.,1e4]
+
+    print 'Skin Depth: ', [(500./np.sqrt(sigmaback*_)) for _ in freqs]
+
+
+    # ------------------ MESH ------------------
+    # fine cells near well bore
+    csx1, csx2 = 2e-3, 60.
+    pfx1, pfx2 = 1.3, 1.3
+    ncx1 = np.ceil(casing_b/csx1+2)
+
+    # pad nicely to second cell size
+    npadx1 = np.floor(np.log(csx2/csx1) / np.log(pfx1))
+    hx1a,hx1b = Utils.meshTensor([(csx1,ncx1)]),Utils.meshTensor([(csx1,npadx1,pfx1)])
+    dx1 = sum(hx1a)+sum(hx1b)
+    dx1 = np.floor(dx1/csx2)
+    hx1b *= (dx1*csx2 - sum(hx1a))/sum(hx1b)
+
+    # second chunk of mesh
+    dx2 = 300. # uniform mesh out to here
+    ncx2 = np.ceil((dx2 - dx1)/csx2)
+    npadx2 = 45
+    hx2a, hx2b = Utils.meshTensor([(csx2,ncx2)]), Utils.meshTensor([(csx2,npadx2,pfx2)])
+    hx = np.hstack([hx1a,hx1b,hx2a,hx2b])
+
+    # z-direction
+    csz = 0.05
+    nza = 10
+    ncz, npadzu, npadzd = np.int(np.ceil(np.diff(casing_z)[0]/csz))+10, 68, 68 # cell size, number of core cells, number of padding cells in the x- direction
+    hz = Utils.meshTensor([(csz,npadzd,-1.3), (csz,ncz), (csz,npadzu,1.3)]) # vector of cell widths in the z-direction
+
+    # Mesh
+    mesh = Mesh.CylMesh([hx,1.,hz], [0.,0.,-np.sum(hz[:npadzu+ncz-nza])])
+
+    print 'Mesh Extent xmax: %f,: zmin: %f, zmax: %f'%(mesh.vectorCCx.max(), mesh.vectorCCz.min(), mesh.vectorCCz.max())
+    print 'Number of cells', mesh.nC
+
+    if plotIt is True:
+        fig, ax = plt.subplots(1, 1, figsize=(6, 4))
+        ax.set_title('Simulation Mesh')
+        mesh.plotGrid(ax=ax)
+        plt.show()
+
+    # Put the model on the mesh
+    sigWholespace = sigmaback*np.ones((mesh.nC))
+
+    sigBack = sigWholespace.copy()
+    sigBack[mesh.gridCC[:,2] > 0.] = sigmaair
+
+    sigCasing = sigBack.copy()
+    iCasingZ = (mesh.gridCC[:,2] <= casing_z[1]) & (mesh.gridCC[:,2] >= casing_z[0])
+    iCasingX = (mesh.gridCC[:,0] >= casing_a) & (mesh.gridCC[:,0] <= casing_b)
+    iCasing = iCasingX & iCasingZ
+    sigCasing[iCasing] = sigmacasing
+
+
+    if plotIt is True:
+
+        # plotting parameters
+        xlim = np.r_[0., 0.2]
+        zlim = np.r_[-350., 10.]
+        clim_sig = np.r_[-8,6]
+
+        # plot models
+        fig, ax = plt.subplots(1,1,figsize=(4,4))
+
+        f = plt.colorbar(mesh.plotImage(np.log10(sigCasing),ax=ax)[0], ax=ax)
+        ax.grid(which='both')
+        ax.set_title('Log_10 (Sigma)')
+        ax.set_xlim(xlim)
+        ax.set_ylim(zlim)
+        f.set_clim(clim_sig)
+
+        plt.show()
+
+
+    # -------------- Sources --------------------
+    # Define Custom Current Sources
+
+    # surface source
+    sg_x = np.zeros(mesh.vnF[0],dtype=complex)
+    sg_y = np.zeros(mesh.vnF[1],dtype=complex)
+    sg_z = np.zeros(mesh.vnF[2],dtype=complex)
+
+    nza = 2 # put the wire two cells above the surface
+    ncin = 2
+
+    # vertically directed wire
+    sgv_indx = (mesh.gridFz[:,0] > casing_a) & (mesh.gridFz[:,0] < casing_a + csx1)  # hook it up to casing at the surface
+    sgv_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] >= -csz*2)
+    sgv_ind = sgv_indx & sgv_indz
+    sg_z[sgv_ind] = -1.
+
+    # horizontally directed wire
+    sgh_indx = (mesh.gridFx[:,0] > casing_a)    & (mesh.gridFx[:,0] <= inf_loc[2])
+    sgh_indz = (mesh.gridFx[:,2] > csz*(nza-0.5)) & (mesh.gridFx[:,2] < csz*(nza+0.5))
+    sgh_ind = sgh_indx & sgh_indz
+    sg_x[sgh_ind] = -1.
+
+    sgv2_indx = (mesh.gridFz[:,0] >= mesh.gridFx[sgh_ind,0].max()) & (mesh.gridFz[:,0] <= inf_loc[2]*1.2)  # hook it up to casing at the surface
+    sgv2_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] >= -csz*2)
+    sgv2_ind = sgv2_indx & sgv2_indz
+    sg_z[sgv2_ind] = 1.
+
+    # assemble the source
+    sg = np.hstack([sg_x,sg_y,sg_z])
+    sg_p = [FDEM.Src.RawVec_e([],_,sg/mesh.area) for _ in freqs]
+
+    # downhole source
+    dg_x = np.zeros(mesh.vnF[0],dtype=complex)
+    dg_y = np.zeros(mesh.vnF[1],dtype=complex)
+    dg_z = np.zeros(mesh.vnF[2],dtype=complex)
+
+    # vertically directed wire
+    dgv_indx = (mesh.gridFz[:,0] < csx1)  # go through the center of the well
+    dgv_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] > dsz + csz/2.)
+    dgv_ind = dgv_indx & dgv_indz
+    dg_z[dgv_ind] = -1.
+
+    # couple to the casing downhole
+    dgh_indx = mesh.gridFx[:,0] < casing_a + csx1
+    dgh_indz = (mesh.gridFx[:,2] < dsz + csz)  & (mesh.gridFx[:,2] >= dsz)
+    dgh_ind = dgh_indx & dgh_indz
+    dg_x[dgh_ind] = 1.
+
+    # horizontal part at surface
+    dgh2_indx = mesh.gridFx[:,0] <= inf_loc[2]*1.2
+    dgh2_indz = sgh_indz.copy()
+    dgh2_ind = dgh2_indx & dgh2_indz
+    dg_x[dgh2_ind] = -1.
+
+    # vertical part at surface
+    dgv2_ind = sgv2_ind.copy()
+    dg_z[dgv2_ind] = 1.
+
+    # assemble the source
+    dg = np.hstack([dg_x,dg_y,dg_z])
+    dg_p = [FDEM.Src.RawVec_e([],_,dg/mesh.area) for _ in freqs]
+
+    # ------------ Problem and Survey ---------------
+    survey = FDEM.Survey(sg_p + dg_p)
+    mapping = [('sigma', Maps.IdentityMap(mesh))]
+    problem = FDEM.Problem_h(mesh, mapping=mapping)
+    problem.pair(survey)
+
+    # ------------- Solve ---------------------------
+    t0 = time.time()
+    fieldsCasing = problem.fields(sigCasing)
+    print 'Time to solve 2 sources', time.time() - t0
+
+    # Plot current
+
+    # current density
+    jn0 = fieldsCasing[dg_p,'j']
+    jn1 = fieldsCasing[sg_p,'j']
+
+    # current
+    in0 = [mesh.area*fieldsCasing[dg_p,'j'][:,i] for i in range(len(freqs))]
+    in1 = [mesh.area*fieldsCasing[sg_p,'j'][:,i] for i in range(len(freqs))]
+
+    in0 = np.vstack(in0).T
+    in1 = np.vstack(in1).T
+
+    # integrate to get z-current inside casing
+    inds_inx = (mesh.gridFz[:,0] >= casing_a) & (mesh.gridFz[:,0] <= casing_b)
+    inds_inz = (mesh.gridFz[:,2] >= dsz )     & (mesh.gridFz[:,2] <= 0)
+    inds_fz = inds_inx & inds_inz
+
+    indsx = [False]*mesh.nFx
+    inds = list(indsx) + list(inds_fz)
+
+    in0_in = in0[np.r_[inds]]
+    in1_in = in1[np.r_[inds]]
+    z_in = mesh.gridFz[inds_fz,2]
+
+    in0_in = in0_in.reshape([in0_in.shape[0]/3,3])
+    in1_in = in1_in.reshape([in1_in.shape[0]/3,3])
+    z_in = z_in.reshape([z_in.shape[0]/3,3])
+
+    I0 = in0_in.sum(1).real
+    I1 = in1_in.sum(1).real
+    z_in = z_in[:,0]
+
+    if plotIt is True:
+        fig, ax = plt.subplots(1,2,figsize=(12,4))
+
+        ax[0].plot(z_in,np.absolute(I0), z_in,np.absolute(I1))
+        ax[0].legend(['top casing', 'bottom casing'],loc='best')
+        ax[0].set_title('Magnitude of Vertical Current in Casing')
+
+        ax[1].semilogy(z_in,np.absolute(I0), z_in,np.absolute(I1))
+        ax[1].legend(['top casing', 'bottom casing'],loc='best')
+        ax[1].set_title('Magnitude of Vertical Current in Casing')
+        ax[1].set_ylim([1e-2, 1.])
+
+        plt.show()
+
+if __name__ == '__main__':
+    run()
+

SimPEG/Examples/MT_1D_ForwardAndInversion.py

@@ -100,7 +100,7 @@ def run(plotIt=True):
     # Regularization - with a regularization mesh
     regMesh = simpeg.Mesh.TensorMesh([m1d.hx[problem.mapping.sigmaMap.maps[-1].indActive]],m1d.x0)
     reg = simpeg.Regularization.Tikhonov(regMesh)
-    reg.smoothModel = True
+    reg.mrefInSmooth = True
     reg.alpha_s = 1e-7
     reg.alpha_x = 1.
     # Inversion problem

SimPEG/Examples/__init__.py

@@ -5,6 +5,7 @@ import DC_Analytic_Dipole
 import DC_Forward_PseudoSection
 import EM_FDEM_1D_Inversion
 import EM_FDEM_Analytic_MagDipoleWholespace
+import EM_Schenkel_Morrison_Casing
 import EM_TDEM_1D_Inversion
 import FLOW_Richards_1D_Celia1990
 import Forward_BasicDirectCurrent
@@ -19,7 +20,7 @@ import Mesh_Tensor_Creation
 import MT_1D_ForwardAndInversion
 import MT_3D_Foward
 
-__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Forward_BasicDirectCurrent", "Inversion_Linear", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward"]
+__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_Schenkel_Morrison_Casing", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Forward_BasicDirectCurrent", "Inversion_Linear", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward"]
 
 ##### AUTOIMPORTS #####
 

SimPEG/Mesh/DiffOperators.py

@@ -307,24 +307,28 @@ class DiffOperators(object):
         return BC
     _cellGradBC_list = 'neumann'
 
+    def _cellGradStencil(self):
+        BC = self.setCellGradBC(self._cellGradBC_list)
+        n = self.vnC
+        if(self.dim == 1):
+            G = ddxCellGrad(n[0], BC[0])
+        elif(self.dim == 2):
+            G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC[0]))
+            G2 = sp.kron(ddxCellGrad(n[1], BC[1]), speye(n[0]))
+            G = sp.vstack((G1, G2), format="csr")
+        elif(self.dim == 3):
+            G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC[0]))
+            G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC[1]), speye(n[0]))
+            G3 = kron3(ddxCellGrad(n[2], BC[2]), speye(n[1]), speye(n[0]))
+            G = sp.vstack((G1, G2, G3), format="csr")
+        return G
+
     def cellGrad():
         doc = "The cell centered Gradient, takes you to cell faces."
 
         def fget(self):
             if(self._cellGrad is None):
-                BC = self.setCellGradBC(self._cellGradBC_list)
-                n = self.vnC
-                if(self.dim == 1):
-                    G = ddxCellGrad(n[0], BC[0])
-                elif(self.dim == 2):
-                    G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC[0]))
-                    G2 = sp.kron(ddxCellGrad(n[1], BC[1]), speye(n[0]))
-                    G = sp.vstack((G1, G2), format="csr")
-                elif(self.dim == 3):
-                    G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC[0]))
-                    G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC[1]), speye(n[0]))
-                    G3 = kron3(ddxCellGrad(n[2], BC[2]), speye(n[1]), speye(n[0]))
-                    G = sp.vstack((G1, G2, G3), format="csr")
+                G = self._cellGradStencil()
                 # Compute areas of cell faces & volumes
                 S = self.area
                 V = self.aveCC2F*self.vol  # Average volume between adjacent cells
@@ -361,19 +365,24 @@ class DiffOperators(object):
     _cellGradBC = None
     cellGradBC = property(**cellGradBC())
 
+    def _cellGradxStencil(self):
+        BC = ['neumann', 'neumann']
+        n = self.vnC
+        if(self.dim == 1):
+            G1 = ddxCellGrad(n[0], BC)
+        elif(self.dim == 2):
+            G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC))
+        elif(self.dim == 3):
+            G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC))
+        return G1
+
+
     def cellGradx():
         doc = "Cell centered Gradient in the x dimension. Has neumann boundary conditions."
 
         def fget(self):
             if getattr(self, '_cellGradx', None) is None:
-                BC = ['neumann', 'neumann']
-                n = self.vnC
-                if(self.dim == 1):
-                    G1 = ddxCellGrad(n[0], BC)
-                elif(self.dim == 2):
-                    G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC))
-                elif(self.dim == 3):
-                    G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC))
+                G1 = self._cellGradxStencil()
                 # Compute areas of cell faces & volumes
                 V = self.aveCC2F*self.vol
                 L = self.r(self.area/V, 'F','Fx', 'V')
@@ -382,17 +391,22 @@ class DiffOperators(object):
         return locals()
     cellGradx = property(**cellGradx())
 
+    def _cellGradyStencil(self):
+        if self.dim < 2: return None
+        BC = ['neumann', 'neumann']
+        n = self.vnC
+        if(self.dim == 2):
+            G2 = sp.kron(ddxCellGrad(n[1], BC), speye(n[0]))
+        elif(self.dim == 3):
+            G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC), speye(n[0]))
+        return G2
+
     def cellGrady():
         doc = "Cell centered Gradient in the x dimension. Has neumann boundary conditions."
         def fget(self):
             if self.dim < 2: return None
             if getattr(self, '_cellGrady', None) is None:
-                BC = ['neumann', 'neumann']
-                n = self.vnC
-                if(self.dim == 2):
-                    G2 = sp.kron(ddxCellGrad(n[1], BC), speye(n[0]))
-                elif(self.dim == 3):
-                    G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC), speye(n[0]))
+                G2 = self._cellGradyStencil()
                 # Compute areas of cell faces & volumes
                 V = self.aveCC2F*self.vol
                 L = self.r(self.area/V, 'F','Fy', 'V')
@@ -401,14 +415,19 @@ class DiffOperators(object):
         return locals()
     cellGrady = property(**cellGrady())
 
+    def _cellGradzStencil(self):
+        if self.dim < 3: return None
+        BC = ['neumann', 'neumann']
+        n = self.vnC
+        G3 = kron3(ddxCellGrad(n[2], BC), speye(n[1]), speye(n[0]))
+        return G3
+
     def cellGradz():
         doc = "Cell centered Gradient in the x dimension. Has neumann boundary conditions."
         def fget(self):
             if self.dim < 3: return None
             if getattr(self, '_cellGradz', None) is None:
-                BC = ['neumann', 'neumann']
-                n = self.vnC
-                G3 = kron3(ddxCellGrad(n[2], BC), speye(n[1]), speye(n[0]))
+                G3 = self._cellGradzStencil()
                 # Compute areas of cell faces & volumes
                 V = self.aveCC2F*self.vol
                 L = self.r(self.area/V, 'F','Fz', 'V')
@@ -565,7 +584,67 @@ class DiffOperators(object):
 
         return Pbc, Pin, Pout
 
+    def getBCProjWF_simple(self, discretization='CC'):
+        """
 
+        The weak form boundary condition projection matrices
+        when mixed boundary condition is used
+
+
+        """
+
+        if discretization is not 'CC':
+            raise NotImplementedError('Boundary conditions only implemented for CC discretization.')
+
+        def projBC(n):
+            ij = ([0,n], [0,1])
+            vals = [0,0]
+            vals[0] = 1
+            vals[1] = 1
+            return sp.csr_matrix((vals, ij), shape=(n+1,2))
+
+        def projDirichlet(n, bc):
+            bc = checkBC(bc)
+            ij = ([0,n], [0,1])
+            vals = [0,0]
+            if(bc[0] == 'dirichlet'):
+                vals[0] = -1
+            if(bc[1] == 'dirichlet'):
+                vals[1] = 1
+            return sp.csr_matrix((vals, ij), shape=(n+1,2))
+
+        BC = [['dirichlet','dirichlet'],['dirichlet','dirichlet'],['dirichlet','dirichlet']]
+        n = self.vnC
+        indF = self.faceBoundaryInd
+        if(self.dim == 1):
+            Pbc = projDirichlet(n[0], BC[0])
+            B = projBC(n[0])
+            indF = indF[0] | indF[1]
+            Pbc = Pbc*sdiag(self.area[indF])
+
+        elif(self.dim == 2):
+            Pbc1 = sp.kron(speye(n[1]), projDirichlet(n[0], BC[0]))
+            Pbc2 = sp.kron(projDirichlet(n[1], BC[1]), speye(n[0]))
+            Pbc = sp.block_diag((Pbc1, Pbc2), format="csr")
+            B1 = sp.kron(speye(n[1]), projBC(n[0]))
+            B2 = sp.kron(projBC(n[1]), speye(n[0]))
+            B = sp.block_diag((B1, B2), format="csr")
+            indF = np.r_[(indF[0] | indF[1]), (indF[2] | indF[3])]
+            Pbc = Pbc*sdiag(self.area[indF])
+
+        elif(self.dim == 3):
+            Pbc1 = kron3(speye(n[2]), speye(n[1]), projDirichlet(n[0], BC[0]))
+            Pbc2 = kron3(speye(n[2]), projDirichlet(n[1], BC[1]), speye(n[0]))
+            Pbc3 = kron3(projDirichlet(n[2], BC[2]), speye(n[1]), speye(n[0]))
+            Pbc = sp.block_diag((Pbc1, Pbc2, Pbc3), format="csr")
+            B1 = kron3(speye(n[2]), speye(n[1]), projBC(n[0]))
+            B2 = kron3(speye(n[2]), projBC(n[1]), speye(n[0]))
+            B3 = kron3(projBC(n[2]), speye(n[1]), speye(n[0]))
+            B = sp.block_diag((B1, B2, B3), format="csr")
+            indF = np.r_[(indF[0] | indF[1]), (indF[2] | indF[3]), (indF[4] | indF[5])]
+            Pbc = Pbc*sdiag(self.area[indF])
+
+        return Pbc, B.T
     # --------------- Averaging ---------------------
 
     @property

SimPEG/Mesh/MeshIO.py

@@ -21,7 +21,7 @@ class TensorMeshIO(object):
                 if '*' in seg:
                     st = seg
                     sp = seg.split('*')
-                    re = np.array(sp[0],dtype=int)*(' ' + sp[1])
+                    re = int(sp[0])*(' ' + sp[1])
                     line = line.replace(st,re.strip())
             return np.array(line.split(),dtype=float)
 

SimPEG/Optimization.py

@@ -888,6 +888,8 @@ class ProjectedGNCG(BFGS, Minimize, Remember):
     maxIterCG = 5
     tolCG = 1e-1
 
+    stepOffBoundsFact = 0.1 # perturbation of the inactive set off the bounds
+
     lower = -np.inf
     upper = np.inf
 
@@ -990,4 +992,19 @@ class ProjectedGNCG(BFGS, Minimize, Remember):
                     cgFlag = 1
                 # End CG Iterations
 
+            # Take a gradient step on the active cells if exist
+            if temp != self.xc.size:
+
+                rhs_a = (Active) * -self.g
+
+                dm_i = max( abs( delx ) )
+                dm_a = max( abs(rhs_a) )
+
+                # perturb inactive set off of bounds so that they are included in the step
+                delx = delx + self.stepOffBoundsFact * (rhs_a * dm_i / dm_a)
+
+            # Only keep gradients going in the right direction on the active set
+            indx = ((self.xc<=self.lower) & (delx < 0)) | ((self.xc>=self.upper) & (delx > 0))
+            delx[indx] = 0.
+
             return delx

SimPEG/Regularization.py

@@ -1,5 +1,289 @@
 import Utils, Maps, Mesh, numpy as np, scipy.sparse as sp
 
+class RegularizationMesh(object):
+    """
+    **Regularization Mesh**
+
+    This contains the operators used in the regularization. Note that these
+    are not necessarily true differential operators, but are constructed from
+    a SimPEG Mesh.
+
+    :param Mesh mesh: problem mesh
+    :param numpy.array indActive: bool array, size nC, that is True where we have active cells. Used to reduce the operators so we regularize only on active cells
+    """
+
+    def __init__(self, mesh, indActive=None):
+        self.mesh = mesh
+        assert indActive is None or indActive.dtype == 'bool', 'indActive needs to be None or a bool'
+        self.indActive = indActive
+
+    @property
+    def vol(self):
+        """
+        reduced volume vector
+        :rtype: numpy.array
+        :return: reduced cell volume
+        """
+        if getattr(self, '_vol', None) is None:
+            self._vol = self._Pac.T * self.mesh.vol
+        return self._vol
+
+    @property
+    def nC(self):
+        """
+        reduced number of cells
+        :rtype: int
+        :return: number of cells being regularized
+        """
+        if getattr(self, '_nC', None) is None:
+            if self.indActive is None:
+                self._nC = self.mesh.nC
+            else:
+                self._nC = sum(self.indActive)
+        return self._nC
+
+    @property
+    def dim(self):
+        """
+        dimension of regularization mesh (1D, 2D, 3D)
+        :rtype: int
+        :return: dimension
+        """
+        if getattr(self, '_dim', None) is None:
+            self._dim = self.mesh.dim
+        return self._dim
+
+
+    @property
+    def _Pac(self):
+        """
+        projection matrix that takes from the reduced space of active cells to full modelling space (ie. nC x nindActive)
+        :rtype: scipy.sparse.csr_matrix
+        :return: active cell projection matrix
+        """
+        if getattr(self, '__Pac', None) is None:
+            if self.indActive is None:
+                self.__Pac = Utils.speye(self.mesh.nC)
+            else:
+                self.__Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
+        return self.__Pac
+
+    @property
+    def _Pafx(self):
+        """
+        projection matrix that takes from the reduced space of active x-faces to full modelling space (ie. nFx x nindActive_Fx )
+        :rtype: scipy.sparse.csr_matrix
+        :return: active face-x projection matrix
+        """
+        if getattr(self, '__Pafx', None) is None:
+            if self.indActive is None:
+                self.__Pafx = Utils.speye(self.mesh.nFx)
+            else:
+                indActive_Fx = (self.mesh.aveFx2CC.T * self.indActive) == 1
+                self.__Pafx = Utils.speye(self.mesh.nFx)[:,indActive_Fx]
+        return self.__Pafx
+
+    @property
+    def _Pafy(self):
+        """
+        projection matrix that takes from the reduced space of active y-faces to full modelling space (ie. nFy x nindActive_Fy )
+        :rtype: scipy.sparse.csr_matrix
+        :return: active face-y projection matrix
+        """
+        if getattr(self, '__Pafy', None) is None:
+            if self.indActive is None:
+                self.__Pafy = Utils.speye(self.mesh.nFy)
+            else:
+                indActive_Fy = (self.mesh.aveFy2CC.T * self.indActive) == 1
+                self.__Pafy = Utils.speye(self.mesh.nFy)[:,indActive_Fy]
+        return self.__Pafy
+
+    @property
+    def _Pafz(self):
+        """
+        projection matrix that takes from the reduced space of active z-faces to full modelling space (ie. nFz x nindActive_Fz )
+        :rtype: scipy.sparse.csr_matrix
+        :return: active face-z projection matrix
+        """
+        if getattr(self, '__Pafz', None) is None:
+            if self.indActive is None:
+                self.__Pafz = Utils.speye(self.mesh.nFz)
+            else:
+                indActive_Fz = (self.mesh.aveFz2CC.T * self.indActive) == 1
+                self.__Pafz = Utils.speye(self.mesh.nFz)[:,indActive_Fz]
+        return self.__Pafz
+
+    @property
+    def aveFx2CC(self):
+        """
+        averaging from active cell centers to active x-faces
+        :rtype: scipy.sparse.csr_matrix
+        :return: averaging from active cell centers to active x-faces
+        """
+        if getattr(self, '_aveFx2CC', None) is None:
+            self._aveFx2CC =  self._Pac.T * self.mesh.aveFx2CC * self._Pafx
+        return self._aveFx2CC
+
+    @property
+    def aveCC2Fx(self):
+        """
+        averaging from active x-faces to active cell centers
+        :rtype: scipy.sparse.csr_matrix
+        :return: averaging matrix from active x-faces to active cell centers
+        """
+        if getattr(self, '_aveCC2Fx', None) is None:
+            self._aveCC2Fx =  Utils.sdiag(1./(self.aveFx2CC.T).sum(1)) * self.aveFx2CC.T
+        return self._aveCC2Fx
+
+    @property
+    def aveFy2CC(self):
+        """
+        averaging from active cell centers to active y-faces
+        :rtype: scipy.sparse.csr_matrix
+        :return: averaging from active cell centers to active y-faces
+        """
+        if getattr(self, '_aveFy2CC', None) is None:
+            self._aveFy2CC = self._Pac.T * self.mesh.aveFy2CC * self._Pafy
+        return self._aveFy2CC
+
+    @property
+    def aveCC2Fy(self):
+        """
+        averaging from active y-faces to active cell centers
+        :rtype: scipy.sparse.csr_matrix
+        :return: averaging matrix from active y-faces to active cell centers
+        """
+        if getattr(self, '_aveCC2Fy', None) is None:
+            self._aveCC2Fy =  Utils.sdiag(1./(self.aveFy2CC.T).sum(1)) * self.aveFy2CC.T
+        return self._aveCC2Fy
+
+    @property
+    def aveFz2CC(self):
+        """
+        averaging from active cell centers to active z-faces
+        :rtype: scipy.sparse.csr_matrix
+        :return: averaging from active cell centers to active z-faces
+        """
+        if getattr(self, '_aveFz2CC', None) is None:
+            self._aveFz2CC = self._Pac.T * self.mesh.aveFz2CC * self._Pafz
+        return self._aveFz2CC
+
+    @property
+    def aveCC2Fz(self):
+        """
+        averaging from active z-faces to active cell centers
+        :rtype: scipy.sparse.csr_matrix
+        :return: averaging matrix from active z-faces to active cell centers
+        """
+        if getattr(self, '_aveCC2Fz', None) is None:
+            self._aveCC2Fz =  Utils.sdiag(1./(self.aveFz2CC.T).sum(1)) * self.aveFz2CC.T
+        return self._aveCC2Fz
+
+    @property
+    def cellDiffx(self):
+        """
+        cell centered difference in the x-direction
+        :rtype: scipy.sparse.csr_matrix
+        :return: differencing matrix for active cells in the x-direction
+        """
+        if getattr(self, '_cellDiffx', None) is None:
+            self._cellDiffx = self._Pafx.T * self.mesh.cellGradx * self._Pac
+        return self._cellDiffx
+
+    @property
+    def cellDiffy(self):
+        """
+        cell centered difference in the y-direction
+        :rtype: scipy.sparse.csr_matrix
+        :return: differencing matrix for active cells in the y-direction
+        """
+        if getattr(self, '_cellDiffy', None) is None:
+            self._cellDiffy = self._Pafy.T * self.mesh.cellGrady * self._Pac
+        return self._cellDiffy
+
+    @property
+    def cellDiffz(self):
+        """
+        cell centered difference in the z-direction
+        :rtype: scipy.sparse.csr_matrix
+        :return: differencing matrix for active cells in the z-direction
+        """
+        if getattr(self, '_cellDiffz', None) is None:
+            self._cellDiffz = self._Pafz.T * self.mesh.cellGradz * self._Pac
+        return self._cellDiffz
+
+    @property
+    def faceDiffx(self):
+        """
+        x-face differences
+        :rtype: scipy.sparse.csr_matrix
+        :return: differencing matrix for active faces in the x-direction
+        """
+        if getattr(self, '_faceDiffx', None) is None:
+            self._faceDiffx = self._Pac.T * self.mesh.faceDivx * self._Pafx
+        return self._faceDiffx
+
+    @property
+    def faceDiffy(self):
+        """
+        y-face differences
+        :rtype: scipy.sparse.csr_matrix
+        :return: differencing matrix for active faces in the y-direction
+        """
+        if getattr(self, '_faceDiffy', None) is None:
+            self._faceDiffy = self._Pac.T * self.mesh.faceDivy * self._Pafy
+        return self._faceDiffy
+
+    @property
+    def faceDiffz(self):
+        """
+        z-face differences
+        :rtype: scipy.sparse.csr_matrix
+        :return: differencing matrix for active faces in the z-direction
+        """
+        if getattr(self, '_faceDiffz', None) is None:
+            self._faceDiffz = self._Pac.T * self.mesh.faceDivz * self._Pafz
+        return self._faceDiffz
+
+    @property
+    def cellDiffxStencil(self):
+        """
+        cell centered difference stencil (no cell lengths include) in the x-direction
+        :rtype: scipy.sparse.csr_matrix
+        :return: differencing matrix for active cells in the x-direction
+        """
+        if getattr(self, '_cellDiffxStencil', None) is None:
+
+            self._cellDiffxStencil = self._Pafx.T * self.mesh._cellGradxStencil() * self._Pac
+        return self._cellDiffxStencil
+
+    @property
+    def cellDiffyStencil(self):
+        """
+        cell centered difference stencil (no cell lengths include) in the y-direction
+        :rtype: scipy.sparse.csr_matrix
+        :return: differencing matrix for active cells in the y-direction
+        """
+        if self.dim < 2: return None
+        if getattr(self, '_cellDiffyStencil', None) is None:
+
+            self._cellDiffyStencil = self._Pafy.T * self.mesh._cellGradyStencil() * self._Pac
+        return self._cellDiffyStencil
+
+    @property
+    def cellDiffzStencil(self):
+        """
+        cell centered difference stencil (no cell lengths include) in the y-direction
+        :rtype: scipy.sparse.csr_matrix
+        :return: differencing matrix for active cells in the y-direction
+        """
+        if self.dim < 3: return None
+        if getattr(self, '_cellDiffzStencil', None) is None:
+
+            self._cellDiffzStencil = self._Pafz.T * self.mesh._cellGradzStencil() * self._Pac
+        return self._cellDiffzStencil
+
+
 class BaseRegularization(object):
     """
     **Base Regularization Class**
@@ -18,12 +302,16 @@ class BaseRegularization(object):
 
     mapping = None    #: A SimPEG.Map instance.
     mesh    = None    #: A SimPEG.Mesh instance.
-    mref = None       #: Reference model.
+    mref    = None    #: Reference model.
 
     def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
         Utils.setKwargs(self, **kwargs)
-        self.mesh = mesh
         assert isinstance(mesh, Mesh.BaseMesh), "mesh must be a SimPEG.Mesh object."
+        if indActive is not None and indActive.dtype != 'bool':
+            tmp = indActive
+            indActive = np.zeros(mesh.nC, dtype=bool)
+            indActive[tmp] = True
+        self.regmesh = RegularizationMesh(mesh,indActive)
         self.mapping = mapping or self.mapPair(mesh)
         self.mapping._assertMatchesPair(self.mapPair)
         self.indActive = indActive
@@ -55,8 +343,8 @@ class BaseRegularization(object):
     @property
     def W(self):
         """Full regularization weighting matrix W."""
-        return sp.identity(self.mapping.nP)
-
+        return sp.identity(self.regmesh.nC)
+        # self.regmesh._Pac.T * sp.identity(self.regmesh.nC) * self.regmesh._Pac # or do we want sp.identity(self.mesh.nC) or even just Utils.Identity() ?
 
     @Utils.timeIt
     def eval(self, m):
@@ -112,11 +400,10 @@ class BaseRegularization(object):
 
         return mD.T * ( self.W.T * ( self.W * ( mD * v) ) )
 
-
 class Tikhonov(BaseRegularization):
     """
     """
-    smoothModel = True  #: SMOOTH and SMOOTH_MOD_DIF options
+    mrefInSmooth = True  #: SMOOTH and SMOOTH_MOD_DIF options
     alpha_s  = Utils.dependentProperty('_alpha_s', 1e-6, ['_W', '_Ws'], "Smallness weight")
     alpha_x  = Utils.dependentProperty('_alpha_x', 1.0, ['_W', '_Wx'], "Weight for the first derivative in the x direction")
     alpha_y  = Utils.dependentProperty('_alpha_y', 1.0, ['_W', '_Wy'], "Weight for the first derivative in the y direction")
@@ -126,98 +413,58 @@ class Tikhonov(BaseRegularization):
     alpha_zz = Utils.dependentProperty('_alpha_zz', 0.0, ['_W', '_Wzz'], "Weight for the second derivative in the z direction")
 
     def __init__(self, mesh, mapping=None, indActive = None, **kwargs):
-        BaseRegularization.__init__(self, mesh, mapping=mapping, **kwargs)
-        self.indActive = indActive
+        BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
 
     @property
     def Ws(self):
         """Regularization matrix Ws"""
         if getattr(self,'_Ws', None) is None:
-            self._Ws = Utils.sdiag((self.mesh.vol*self.alpha_s)**0.5)
-            if self.indActive is not None:
-                Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
-                self._Ws = Pac.T * self._Ws * Pac
+            self._Ws = Utils.sdiag((self.regmesh.vol*self.alpha_s)**0.5)
         return self._Ws
 
     @property
     def Wx(self):
         """Regularization matrix Wx"""
         if getattr(self, '_Wx', None) is None:
-            Ave_x_vol = self.mesh.aveF2CC[:,:self.mesh.nFx].T*self.mesh.vol
-            self._Wx = Utils.sdiag((Ave_x_vol*self.alpha_x)**0.5)*self.mesh.cellGradx
-
-            if self.indActive is not None:
-                indActive_Fx = (self.mesh.aveFx2CC.T * self.indActive) == 1
-                Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
-                Pafx = Utils.speye(self.mesh.nFx)[:,indActive_Fx]
-                self._Wx = Pafx.T*self._Wx*Pac
-
+            Ave_x_vol = self.regmesh.aveCC2Fx * self.regmesh.vol
+            self._Wx = Utils.sdiag((Ave_x_vol*self.alpha_x)**0.5)*self.regmesh.cellDiffx
         return self._Wx
 
     @property
     def Wy(self):
         """Regularization matrix Wy"""
         if getattr(self, '_Wy', None) is None:
-            Ave_y_vol = self.mesh.aveF2CC[:,self.mesh.nFx:np.sum(self.mesh.vnF[:2])].T*self.mesh.vol
-            self._Wy = Utils.sdiag((Ave_y_vol*self.alpha_y)**0.5)*self.mesh.cellGrady
-
-            if self.indActive is not None:
-                indActive_Fy = (self.mesh.aveFy2CC.T * self.indActive) == 1
-                Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
-                Pafy = Utils.speye(self.mesh.nFy)[:,indActive_Fy]
-                self._Wy = Pafy.T*self._Wy*Pac
-
+            Ave_y_vol = self.regmesh.aveCC2Fy * self.regmesh.vol
+            self._Wy = Utils.sdiag((Ave_y_vol*self.alpha_y)**0.5)*self.regmesh.cellDiffy
         return self._Wy
 
     @property
     def Wz(self):
         """Regularization matrix Wz"""
         if getattr(self, '_Wz', None) is None:
-            Ave_z_vol = self.mesh.aveF2CC[:,np.sum(self.mesh.vnF[:2]):].T*self.mesh.vol
-            self._Wz = Utils.sdiag((Ave_z_vol*self.alpha_z)**0.5)*self.mesh.cellGradz
-
-            if self.indActive is not None:
-                indActive_Fz = (self.mesh.aveFz2CC.T * self.indActive) == 1
-                Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
-                Pafz = Utils.speye(self.mesh.nFz)[:,indActive_Fz]
-                self._Wz = Pafz.T*self._Wz*Pac
-
+            Ave_z_vol = self.regmesh.aveCC2Fz * self.regmesh.vol
+            self._Wz = Utils.sdiag((Ave_z_vol*self.alpha_z)**0.5)*self.regmesh.cellDiffz
         return self._Wz
 
     @property
     def Wxx(self):
         """Regularization matrix Wxx"""
         if getattr(self, '_Wxx', None) is None:
-            self._Wxx = Utils.sdiag((self.mesh.vol*self.alpha_xx)**0.5)*self.mesh.faceDivx*self.mesh.cellGradx
-
-            if self.indActive is not None:
-                Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
-                self._Wxx = Pac.T*self._Wxx*Pac
-
+            self._Wxx = Utils.sdiag((self.regmesh.vol*self.alpha_xx)**0.5)*self.regmesh.faceDiffx*self.regmesh.cellDiffx
         return self._Wxx
 
     @property
     def Wyy(self):
         """Regularization matrix Wyy"""
         if getattr(self, '_Wyy', None) is None:
-            self._Wyy = Utils.sdiag((self.mesh.vol*self.alpha_yy)**0.5)*self.mesh.faceDivy*self.mesh.cellGrady
-
-            if self.indActive is not None:
-                Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
-                self._Wyy = Pac.T*self._Wyy*Pac
-
+            self._Wyy = Utils.sdiag((self.regmesh.vol*self.alpha_yy)**0.5)*self.regmesh.faceDiffy*self.regmesh.cellDiffy
         return self._Wyy
 
     @property
     def Wzz(self):
         """Regularization matrix Wzz"""
         if getattr(self, '_Wzz', None) is None:
-            self._Wzz = Utils.sdiag((self.mesh.vol*self.alpha_zz)**0.5)*self.mesh.faceDivz*self.mesh.cellGradz
-
-            if self.indActive is not None:
-                Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
-                self._Wzz = Pac.T*self._Wzz*Pac
-
+            self._Wzz = Utils.sdiag((self.regmesh.vol*self.alpha_zz)**0.5)*self.regmesh.faceDiffz*self.regmesh.cellDiffz
         return self._Wzz
 
     @property
@@ -225,9 +472,9 @@ class Tikhonov(BaseRegularization):
         """Full smoothness regularization matrix W"""
         if getattr(self, '_Wsmooth', None) is None:
             wlist = (self.Wx, self.Wxx)
-            if self.mesh.dim > 1:
+            if self.regmesh.dim > 1:
                 wlist += (self.Wy, self.Wyy)
-            if self.mesh.dim > 2:
+            if self.regmesh.dim > 2:
                 wlist += (self.Wz, self.Wzz)
             self._Wsmooth = sp.vstack(wlist)
         return self._Wsmooth
@@ -242,11 +489,11 @@ class Tikhonov(BaseRegularization):
 
     @Utils.timeIt
     def eval(self, m):
-        if self.smoothModel == True:
+        if self.mrefInSmooth == True:
             r1 = self.Wsmooth * ( self.mapping * (m) )
             r2 = self.Ws * ( self.mapping * (m - self.mref) )
             return 0.5*(r1.dot(r1)+r2.dot(r2))
-        elif self.smoothModel == False:
+        elif self.mrefInSmooth == False:
             r = self.W * ( self.mapping * (m - self.mref) )
             return 0.5*r.dot(r)
 
@@ -268,7 +515,7 @@ class Tikhonov(BaseRegularization):
             R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}
 
         """
-        if self.smoothModel == True:
+        if self.mrefInSmooth == True:
             mD1 = self.mapping.deriv(m)
             mD2 = self.mapping.deriv(m - self.mref)
             r1 = self.Wsmooth * ( self.mapping * (m))
@@ -276,249 +523,223 @@ class Tikhonov(BaseRegularization):
             out1 = mD1.T * ( self.Wsmooth.T * r1 )
             out2 = mD2.T * ( self.Ws.T * r2 )
             out = out1+out2
-        elif self.smoothModel == False:
+        elif self.mrefInSmooth == False:
             mD = self.mapping.deriv(m - self.mref)
             r = self.W * ( self.mapping * (m - self.mref) )
             out = mD.T * ( self.W.T * r )
         return out
 
-# <<<<<<< HEAD
 
-# class Simple(BaseRegularization):
-#     """
-#         Only for tensor mesh
-#     """
+class Simple(BaseRegularization):
+    """
+        Only for tensor mesh
+    """
 
-#     smoothModel = True  #: SMOOTH and SMOOTH_MOD_DIF options
-#     alpha_s  = Utils.dependentProperty('_alpha_s', 1.0, ['_W', '_Ws'], "Smallness weight")
-#     alpha_x  = Utils.dependentProperty('_alpha_x', 1.0, ['_W', '_Wx'], "Weight for the first derivative in the x direction")
-#     alpha_y  = Utils.dependentProperty('_alpha_y', 1.0, ['_W', '_Wy'], "Weight for the first derivative in the y direction")
-#     alpha_z  = Utils.dependentProperty('_alpha_z', 1.0, ['_W', '_Wz'], "Weight for the first derivative in the z direction")
-#     alpha_xx = Utils.dependentProperty('_alpha_xx', 0.0, ['_W', '_Wxx'], "Weight for the second derivative in the x direction")
-#     alpha_yy = Utils.dependentProperty('_alpha_yy', 0.0, ['_W', '_Wyy'], "Weight for the second derivative in the y direction")
-#     alpha_zz = Utils.dependentProperty('_alpha_zz', 0.0, ['_W', '_Wzz'], "Weight for the second derivative in the z direction")
+    mrefInSmooth = True  #: SMOOTH and SMOOTH_MOD_DIF options
+    alpha_s     = Utils.dependentProperty('_alpha_s', 1.0, ['_W', '_Ws'], "Smallness weight")
+    alpha_x     = Utils.dependentProperty('_alpha_x', 1.0, ['_W', '_Wx'], "Weight for the first derivative in the x direction")
+    alpha_y     = Utils.dependentProperty('_alpha_y', 1.0, ['_W', '_Wy'], "Weight for the first derivative in the y direction")
+    alpha_z     = Utils.dependentProperty('_alpha_z', 1.0, ['_W', '_Wz'], "Weight for the first derivative in the z direction")
+    wght        = 1.
+    
+    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
+        BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
+        
+        if isinstance(self.wght,float):
+            self.wght = np.ones(self.regmesh.nC) * self.wght
 
-#     def __init__(self, mesh, mapping=None, **kwargs):
-#         BaseRegularization.__init__(self, mesh, mapping=mapping, **kwargs)
+    @property
+    def Ws(self):
+        """Regularization matrix Ws"""
+        if getattr(self,'_Ws', None) is None:
+                self._Ws = Utils.sdiag((self.regmesh.vol*self.alpha_s*self.wght)**0.5)
+        return self._Ws
+
+    @property
+    def Wx(self):
+        """Regularization matrix Wx"""
+        if getattr(self, '_Wx', None) is None:
+            self._Wx = Utils.sdiag((self.regmesh.aveCC2Fx * self.regmesh.vol*self.alpha_x*(self.regmesh.aveCC2Fx*self.wght))**0.5)*self.regmesh.cellDiffxStencil
+        return self._Wx
+
+    @property
+    def Wy(self):
+        """Regularization matrix Wy"""
+        if getattr(self, '_Wy', None) is None:
+            self._Wy = Utils.sdiag((self.regmesh.aveCC2Fy * self.regmesh.vol * self.alpha_y*(self.regmesh.aveCC2Fy*self.wght))**0.5)*self.regmesh.cellDiffyStencil
+        return self._Wy
+
+    @property
+    def Wz(self):
+        """Regularization matrix Wz"""
+        if getattr(self, '_Wz', None) is None:
+            self._Wz = Utils.sdiag((self.regmesh.aveCC2Fz * self.regmesh.vol*self.alpha_z*(self.regmesh.aveCC2Fz*self.wght))**0.5)*self.regmesh.cellDiffzStencil
+        return self._Wz
+
+    @property
+    def Wsmooth(self):
+        """Full smoothness regularization matrix W"""
+        if getattr(self, '_Wsmooth', None) is None:
+            wlist = (self.Wx,)
+            if self.regmesh.dim > 1:
+                wlist += (self.Wy,)
+            if self.regmesh.dim > 2:
+                wlist += (self.Wz,)
+            self._Wsmooth = sp.vstack(wlist)
+        return self._Wsmooth
+
+    @property
+    def W(self):
+        """Full regularization matrix W"""
+        if getattr(self, '_W', None) is None:
+            wlist = (self.Ws, self.Wsmooth)
+            self._W = sp.vstack(wlist)
+        return self._W
+
+
+    @Utils.timeIt
+    def eval(self, m):
+        if self.mrefInSmooth == True:
+            r1 = self.Wsmooth * ( self.mapping * (m) )
+            r2 = self.Ws * ( self.mapping * (m - self.mref) )
+            return 0.5*(r1.dot(r1)+r2.dot(r2))
+        elif self.mrefInSmooth == False:
+            r = self.W * ( self.mapping * (m - self.mref) )
+            return 0.5*r.dot(r)
+        return phim
 
 
 
-#     @property
-#     def Ws(self):
-#         """Regularization matrix Ws"""
-#         if getattr(self,'_Ws', None) is None:
-#                 self._Ws = Utils.sdiag((self.mesh.vol*self.alpha_s)**0.5)
-#         return self._Ws
+    @Utils.timeIt
+    def evalDeriv(self, m):
+        """
 
-#     @property
-#     def Wx(self):
-#         """Regularization matrix Wx"""
-#         if getattr(self, '_Wx', None) is None:
-#             self._Wx = Utils.sdiag((self.mesh.vol*self.alpha_x)**0.5)*self.mesh.unitCellGradx
-#         return self._Wx
+        The regularization is:
 
-#     @property
-#     def Wy(self):
-#         """Regularization matrix Wy"""
-#         if getattr(self, '_Wy', None) is None:
-#             self._Wy = Utils.sdiag((self.mesh.vol*self.alpha_y)**0.5)*self.mesh.unitCellGrady
-#         return self._Wy
+        .. math::
 
-#     @property
-#     def Wz(self):
-#         """Regularization matrix Wz"""
-#         if getattr(self, '_Wz', None) is None:
-#             self._Wz = Utils.sdiag((self.mesh.vol*self.alpha_z)**0.5)*self.mesh.unitCellGradz
-#         return self._Wz
+            R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top W(m-m_\\text{ref})}
 
-#     @property
-#     def Wxx(self):
-#         """Regularization matrix Wxx"""
-#         if getattr(self, '_Wxx', None) is None:
-#             self._Wxx = Utils.sdiag((self.mesh.vol*self.alpha_xx)**0.5)*self.mesh.faceDivx*self.mesh.cellGradx
-#         return self._Wxx
+        So the derivative is straight forward:
 
-#     @property
-#     def Wyy(self):
-#         """Regularization matrix Wyy"""
-#         if getattr(self, '_Wyy', None) is None:
-#             self._Wyy = Utils.sdiag((self.mesh.vol*self.alpha_yy)**0.5)*self.mesh.faceDivy*self.mesh.cellGrady
-#         return self._Wyy
+        .. math::
 
-#     @property
-#     def Wzz(self):
-#         """Regularization matrix Wzz"""
-#         if getattr(self, '_Wzz', None) is None:
-#             self._Wzz = Utils.sdiag((self.mesh.vol*self.alpha_zz)**0.5)*self.mesh.faceDivz*self.mesh.cellGradz
-#         return self._Wzz
+            R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}
 
-#     @property
-#     def Wsmooth(self):
-#         """Full smoothness regularization matrix W"""
-#         if getattr(self, '_Wsmooth', None) is None:
-#             wlist = (self.Wx, self.Wxx)
-#             if self.mesh.dim > 1:
-#                 wlist += (self.Wy, self.Wyy)
-#             if self.mesh.dim > 2:
-#                 wlist += (self.Wz, self.Wzz)
-#             self._Wsmooth = sp.vstack(wlist)
-#         return self._Wsmooth
-
-#     @property
-#     def W(self):
-#         """Full regularization matrix W"""
-#         if getattr(self, '_W', None) is None:
-#             wlist = (self.Ws, self.Wsmooth)
-#             self._W = sp.vstack(wlist)
-#         return self._W
-
-#     @Utils.timeIt
-#     def eval(self, m):
-#         if self.smoothModel == True:
-#             r1 = self.Wsmooth * ( self.mapping * (m) )
-#             r2 = self.Ws * ( self.mapping * (m - self.mref) )
-#             return 0.5*(r1.dot(r1)+r2.dot(r2))
-#         elif self.smoothModel == False:
-#             r = self.W * ( self.mapping * (m - self.mref) )
-#             return 0.5*r.dot(r)
+        """
+        if self.mrefInSmooth == True:
+            mD1 = self.mapping.deriv(m)
+            mD2 = self.mapping.deriv(m - self.mref)
+            r1 = self.Wsmooth * ( self.mapping * (m))
+            r2 = self.Ws * ( self.mapping * (m - self.mref) )
+            out1 = mD1.T * ( self.Wsmooth.T * r1 )
+            out2 = mD2.T * ( self.Ws.T * r2 )
+            out = out1+out2
+        elif self.mrefInSmooth == False:
+            mD = self.mapping.deriv(m - self.mref)
+            r = self.W * ( self.mapping * (m - self.mref) )
+            out = mD.T * ( self.W.T * r )
+        return out
 
 
-#     @Utils.timeIt
-#     def evalDeriv(self, m):
-#         """
+class Sparse(Simple):
 
-#         The regularization is:
+    # set default values
+    eps      = 1e-1
+    curModel = None # use a model to compute the weights
+    gamma    = 1.
+    p        = 0.
+    qx       = 2.
+    qy       = 2.
+    qz       = 2.
+    wght     = 1.
 
-#         .. math::
+    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
+        Simple.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
+        
+        if isinstance(self.wght,float):
+            self.wght = np.ones(self.regmesh.nC) * self.wght
 
-#             R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top W(m-m_\\text{ref})}
+    @property
+    def Ws(self):
+        """Regularization matrix Ws"""
+        if getattr(self, 'curModel', None) is None:
+            self.Rs = Utils.speye(self.regmesh.nC)
 
-#         So the derivative is straight forward:
-
-#         .. math::
-
-#             R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}
-
-#         """
-#         if self.smoothModel == True:
-#             mD1 = self.mapping.deriv(m)
-#             mD2 = self.mapping.deriv(m - self.mref)
-#             r1 = self.Wsmooth * ( self.mapping * (m))
-#             r2 = self.Ws * ( self.mapping * (m - self.mref) )
-#             out1 = mD1.T * ( self.Wsmooth.T * r1 )
-#             out2 = mD2.T * ( self.Ws.T * r2 )
-#             out = out1+out2
-#         elif self.smoothModel == False:
-#             mD = self.mapping.deriv(m - self.mref)
-#             r = self.W * ( self.mapping * (m - self.mref) )
-#             out = mD.T * ( self.W.T * r )
-#         return out
-
-# class SparseRegularization(Simple):
-
-#     eps = 1e-1
-
-#     m = None
-#     gamma = 1.
-#     p = 0.
-#     qx = 2.
-#     qy = 2.
-#     qz = 2.
-
-#     def __init__(self, mesh, mapping=None, **kwargs):
-#         Simple.__init__(self, mesh, mapping=mapping, **kwargs)
+        else:
+            f_m = self.curModel - self.reg.mref
+            self.rs = self.R(f_m , self.p)
+            #print "Min rs: " + str(np.max(self.rs)) + "Max rs: " + str(np.min(self.rs))
+            self.Rs = Utils.sdiag( self.rs )
+            
+        return Utils.sdiag((self.regmesh.vol*self.alpha_s*self.gamma*self.wght)**0.5)*self.Rs
 
 
-#     @property
-#     def Wsmooth(self):
-#         """Full smoothness regularization matrix W"""
-#         if getattr(self, '_Wsmooth', None) is None:
-#             wlist = (self.Wx, self.Wxx)
-#             if self.mesh.dim > 1:
-#                 wlist += (self.Wy, self.Wyy)
-#             if self.mesh.dim > 2:
-#                 wlist += (self.Wz, self.Wzz)
-#             self._Wsmooth = sp.vstack(wlist)
-#         return self._Wsmooth
+    @property
+    def Wx(self):
+        """Regularization matrix Wx"""
+            
+        if getattr(self, 'curModel', None) is None:
+            self.Rx = Utils.speye(self.regmesh.cellDiffxStencil.shape[0])
 
-#     @property
-#     def W(self):
-#         """Full regularization matrix W"""
-#         if getattr(self, '_W', None) is None:
-#             wlist = (self.Ws, self.Wsmooth)
-#             self._W = sp.vstack(wlist)
-#         return self._W
+        else:
+            f_m = self.regmesh.cellDiffxStencil * self.curModel
+            self.rx = self.R( f_m , self.qx)
+            self.Rx = Utils.sdiag( self.rx )
 
-#     @property
-#     def Ws(self):
-#         """Regularization matrix Ws"""
-#         if getattr(self, 'm', None) is None:
-#             self.Rs = Utils.speye(self.mesh.nC)
+        return Utils.sdiag(( (self.regmesh.aveCC2Fx * self.regmesh.vol) *self.alpha_x*self.gamma*(self.regmesh.aveCC2Fx*self.wght))**0.5)*self.Rx*self.regmesh.cellDiffxStencil
 
-#         else:
-#             f_m = self.m
-#             self.rs = self.R(f_m , self.p, self.eps)
-#             #print "Min rs: " + str(np.max(self.rs)) + "Max rs: " + str(np.min(self.rs))
-#             self.Rs = Utils.sdiag( self.rs )
+    @property
+    def Wy(self):
+        """Regularization matrix Wy"""
 
-#         self._Ws = Utils.sdiag((self.mesh.vol*self.alpha_s*self.gamma)**0.5)*self.Rs
+        if getattr(self, 'curModel', None) is None:
+            self.Ry = Utils.speye(self.regmesh.cellDiffyStencil.shape[0])
 
-#         return self._Ws
+        else:
+            f_m = self.regmesh.cellDiffyStencil * self.curModel
+            self.ry = self.R( f_m , self.qy)
+            self.Ry = Utils.sdiag( self.ry )
+            
+        return Utils.sdiag(((self.regmesh.aveCC2Fy * self.regmesh.vol)*self.alpha_y*self.gamma*(self.regmesh.aveCC2Fy*self.wght))**0.5)*self.Ry*self.regmesh.cellDiffyStencil
 
-#     @property
-#     def Wx(self):
-#         """Regularization matrix Wx"""
+    @property
+    def Wz(self):
+        """Regularization matrix Wz"""
 
-#         if getattr(self, 'm', None) is None:
-#             self.Rx = Utils.speye(self.mesh.unitCellGradx.shape[0])
+        if getattr(self, 'curModel', None) is None:
+            self.Rz = Utils.speye(self.regmesh.cellDiffzStencil.shape[0])
 
-#         else:
-#             f_m = self.mesh.unitCellGradx * self.m
-#             self.rx = self.R( f_m , self.qx, self.eps)
-#             self.Rx = Utils.sdiag( self.rx )
+        else:
+            f_m = self.regmesh.cellDiffzStencil * self.curModel
+            self.rz = self.R( f_m , self.qz)
+            self.Rz = Utils.sdiag( self.rz )
 
-#         if getattr(self, '_Wx', None) is None:
-#             self._Wx = Utils.sdiag((self.mesh.vol*self.alpha_x*self.gamma)**0.5)*self.Rx*self.mesh.unitCellGradx
-#         return self._Wx
+        return Utils.sdiag(((self.regmesh.aveCC2Fz * self.regmesh.vol)*self.alpha_z*self.gamma*(self.regmesh.aveCC2Fz*self.wght))**0.5)*self.Rz*self.regmesh.cellDiffzStencil
 
-#     @property
-#     def Wy(self):
-#         """Regularization matrix Wy"""
+    @property
+    def Wsmooth(self):
+        """Full smoothness regularization matrix W"""
+        #if getattr(self, '_Wsmooth', None) is None:
+        wlist = (self.Wx,)
+        if self.regmesh.dim > 1:
+            wlist += (self.Wy,)
+        if self.regmesh.dim > 2:
+            wlist += (self.Wz,)
+        #self._Wsmooth = sp.vstack(wlist)
+        return sp.vstack(wlist)
 
-#         if getattr(self, 'm', None) is None:
-#             self.Ry = Utils.speye(self.mesh.unitCellGrady.shape[0])
+    @property
+    def W(self):
+        """Full regularization matrix W"""
+        #if getattr(self, '_W', None) is None:
+        wlist = (self.Ws, self.Wsmooth)
+        #self._W = sp.vstack(wlist)
+        return sp.vstack(wlist)
+        
+    def R(self, f_m , exponent):
 
-#         else:
-#             f_m = self.mesh.unitCellGrady * self.m
-#             self.ry = self.R( f_m , self.qy, self.eps)
-#             self.Ry = Utils.sdiag( self.ry )
+        eta = (self.eps**(1-exponent/2.))**0.5
+        r = eta / (f_m**2.+self.eps**2.)**((1-exponent/2.)/2.)
 
-#         if getattr(self, '_Wy', None) is None:
-#             self._Wy = Utils.sdiag((self.mesh.vol*self.alpha_y*self.gamma)**0.5)*self.Ry*self.mesh.unitCellGrady
-#         return self._Wy
-
-#     @property
-#     def Wz(self):
-#         """Regularization matrix Wz"""
-
-#         if getattr(self, 'm', None) is None:
-#             self.Rz = Utils.speye(self.mesh.unitCellGradz.shape[0])
-
-#         else:
-#             f_m = self.mesh.unitCellGradz * self.m
-#             self.rz = self.R( f_m , self.qz, self.eps)
-#             self.Rz = Utils.sdiag( self.rz )
-
-#         if getattr(self, '_Wz', None) is None:
-#             self._Wz = Utils.sdiag((self.mesh.vol*self.alpha_z*self.gamma)**0.5)*self.Rz*self.mesh.unitCellGradz
-#         return self._Wz
-
-
-#     def R(self, f_m , p, dec):
-
-#         eta = (self.eps**(1-p/2.))**0.5
-#         r = eta / (f_m**2.+self.eps**2.)**((1-p/2.)/2.)
-
-#         return r
-# =======
-# >>>>>>> 834de582844e8e1eac95819fbe03eed55dbeb001
+        return r

docs/examples/EM_Schenkel_Morrison_Casing.rst

@@ -0,0 +1,58 @@
+.. _examples_EM_Schenkel_Morrison_Casing:
+
+.. --------------------------------- ..
+..                                   ..
+..    THIS FILE IS AUTO GENEREATED   ..
+..                                   ..
+..    SimPEG/Examples/__init__.py    ..
+..                                   ..
+.. --------------------------------- ..
+
+
+EM: Schenkel and Morrison Casing Model
+======================================
+
+Here we create and run a FDEM forward simulation to calculate the vertical
+current inside a steel-cased. The model is based on the Schenkel and
+Morrison Casing Model, and the results are used in a 2016 SEG abstract by
+Yang et al.
+
+- Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
+
+
+The model consists of:
+- Air: Conductivity 1e-8 S/m, above z = 0
+- Background: conductivity 1e-2 S/m, below z = 0
+- Casing: conductivity 1e6 S/m
+    - 300m long
+    - radius of 0.1m
+    - thickness of 6e-3m
+
+Inside the casing, we take the same conductivity as the background.
+
+We are using an EM code to simulate DC, so we use frequency low enough
+that the skin depth inside the casing is longer than the casing length (f
+= 1e-6 Hz). The plot produced is of the current inside the casing.
+
+These results are shown in the SEG abstract by Yang et al., 2016: 3D DC
+resistivity modeling of steel casing for reservoir monitoring using
+equivalent resistor network. The solver used to produce these results and
+achieve the CPU time of ~30s is Mumps, which was installed using pymatsolver_
+
+.. _pymatsolver: https://github.com/rowanc1/pymatsolver
+
+This example is on figshare: https://dx.doi.org/10.6084/m9.figshare.3126961.v1
+
+If you would use this example for a code comparison, or build upon it, a
+citation would be much appreciated!
+
+
+
+.. plot::
+
+    from SimPEG import Examples
+    Examples.EM_Schenkel_Morrison_Casing.run()
+
+.. literalinclude:: ../../SimPEG/Examples/EM_Schenkel_Morrison_Casing.py
+    :language: python
+    :linenos:

tests/base/test_regularization.py

@@ -5,6 +5,8 @@ from scipy.sparse.linalg import dsolve
 import inspect
 
 TOL = 1e-20
+testReg = True
+testRegMesh = True
 
 class RegularizationTests(unittest.TestCase):
 
@@ -16,44 +18,82 @@ class RegularizationTests(unittest.TestCase):
         mesh3 = Mesh.TensorMesh([hx, hy, hz])
         self.meshlist = [mesh1,mesh2, mesh3]
 
-    def test_regularization(self):
-        for R in dir(Regularization):
-            r = getattr(Regularization, R)
-            if not inspect.isclass(r): continue
-            if not issubclass(r, Regularization.BaseRegularization):
-                continue
+    if testReg:
+        def test_regularization(self):
+            for R in dir(Regularization):
+                r = getattr(Regularization, R)
+                if not inspect.isclass(r): continue
+                if not issubclass(r, Regularization.BaseRegularization):
+                    continue
+
+                for i, mesh in enumerate(self.meshlist):
+
+                    print 'Testing %iD'%mesh.dim
+
+                    mapping = r.mapPair(mesh)
+                    reg = r(mesh, mapping=mapping)
+                    m = np.random.rand(mapping.nP)
+                    reg.mref = np.ones_like(m)*np.mean(m)
+
+                    print 'Check: phi_m (mref) = %f' %reg.eval(reg.mref)
+                    passed = reg.eval(reg.mref) < TOL
+                    self.assertTrue(passed)
+
+                    print 'Check:', R
+                    passed = Tests.checkDerivative(lambda m : [reg.eval(m), reg.evalDeriv(m)], m, plotIt=False)
+                    self.assertTrue(passed)
+
+                    print 'Check 2 Deriv:', R
+                    passed = Tests.checkDerivative(lambda m : [reg.evalDeriv(m), reg.eval2Deriv(m)], m, plotIt=False)
+                    self.assertTrue(passed)
+
+        def test_regularization_ActiveCells(self):
+            for R in dir(Regularization):
+                r = getattr(Regularization, R)
+                if not inspect.isclass(r): continue
+                if not issubclass(r, Regularization.BaseRegularization):
+                    continue
+
+                for i, mesh in enumerate(self.meshlist):
+
+                    print 'Testing Active Cells %iD'%(mesh.dim)
+
+                    if mesh.dim == 1:
+                        indActive = Utils.mkvc(mesh.gridCC <= 0.8)
+                    elif mesh.dim == 2:
+                        indActive = Utils.mkvc(mesh.gridCC[:,-1] <= 2*np.sin(2*np.pi*mesh.gridCC[:,0])+0.5)
+                    elif mesh.dim == 3:
+                        indActive = Utils.mkvc(mesh.gridCC[:,-1] <= 2*np.sin(2*np.pi*mesh.gridCC[:,0])+0.5 * 2*np.sin(2*np.pi*mesh.gridCC[:,1])+0.5)
+
+                    mapping = Maps.IdentityMap(nP=indActive.nonzero()[0].size)
+
+                    for indAct in [indActive, indActive.nonzero()[0]]: # test both bool and integers
+                        reg = r(mesh, mapping=mapping, indActive=indAct)
+                        m = np.random.rand(mesh.nC)[indAct]
+                        reg.mref = np.ones_like(m)*np.mean(m)
+
+                    print 'Check: phi_m (mref) = %f' %reg.eval(reg.mref)
+                    passed = reg.eval(reg.mref) < TOL
+                    self.assertTrue(passed)
+
+                    print 'Check:', R
+                    passed = Tests.checkDerivative(lambda m : [reg.eval(m), reg.evalDeriv(m)], m, plotIt=False)
+                    self.assertTrue(passed)
+
+                    print 'Check 2 Deriv:', R
+                    passed = Tests.checkDerivative(lambda m : [reg.evalDeriv(m), reg.eval2Deriv(m)], m, plotIt=False)
+                    self.assertTrue(passed)
+
+    if testRegMesh:
+        def test_regularizationMesh(self):
 
             for i, mesh in enumerate(self.meshlist):
 
                 print 'Testing %iD'%mesh.dim
 
-                mapping = r.mapPair(mesh)
-                reg = r(mesh, mapping=mapping)
-                m = np.random.rand(mapping.nP)
-                reg.mref = np.ones_like(m)*np.mean(m)
-
-                print 'Check: phi_m (mref) = %f' %reg.eval(reg.mref)
-                passed = reg.eval(reg.mref) < TOL
-                self.assertTrue(passed)
-
-                print 'Check:', R
-                passed = Tests.checkDerivative(lambda m : [reg.eval(m), reg.evalDeriv(m)], m, plotIt=False)
-                self.assertTrue(passed)
-
-                print 'Check 2 Deriv:', R
-                passed = Tests.checkDerivative(lambda m : [reg.evalDeriv(m), reg.eval2Deriv(m)], m, plotIt=False)
-                self.assertTrue(passed)
-
-    def test_regularization_ActiveCells(self):
-        for R in dir(Regularization):
-            r = getattr(Regularization, R)
-            if not inspect.isclass(r): continue
-            if not issubclass(r, Regularization.BaseRegularization):
-                continue
-
-            for i, mesh in enumerate(self.meshlist):
-
-                print 'Testing Active Cells %iD'%(mesh.dim)
+                # mapping = r.mapPair(mesh)
+                # reg = r(mesh, mapping=mapping)
+                # m = np.random.rand(mapping.nP)
 
                 if mesh.dim == 1:
                     indAct = Utils.mkvc(mesh.gridCC <= 0.8)
@@ -62,23 +102,9 @@ class RegularizationTests(unittest.TestCase):
                 elif mesh.dim == 3:
                     indAct = Utils.mkvc(mesh.gridCC[:,-1] <= 2*np.sin(2*np.pi*mesh.gridCC[:,0])+0.5 * 2*np.sin(2*np.pi*mesh.gridCC[:,1])+0.5)
 
-                mapping = Maps.IdentityMap(nP=indAct.nonzero()[0].size)
+                regmesh = Regularization.RegularizationMesh(mesh, indActive=indAct)
 
-                reg = r(mesh, mapping=mapping, indActive=indAct)
-                m = np.random.rand(mesh.nC)[indAct]
-                reg.mref = np.ones_like(m)*np.mean(m)
-
-                print 'Check: phi_m (mref) = %f' %reg.eval(reg.mref)
-                passed = reg.eval(reg.mref) < TOL
-                self.assertTrue(passed)
-
-                print 'Check:', R
-                passed = Tests.checkDerivative(lambda m : [reg.eval(m), reg.evalDeriv(m)], m, plotIt=False)
-                self.assertTrue(passed)
-
-                print 'Check 2 Deriv:', R
-                passed = Tests.checkDerivative(lambda m : [reg.evalDeriv(m), reg.eval2Deriv(m)], m, plotIt=False)
-                self.assertTrue(passed)
+                assert (regmesh.vol == mesh.vol[indAct]).all()
 
 
 if __name__ == '__main__':

tests/mesh/test_Mixed_boundaryPoisson.py

@@ -0,0 +1,396 @@
+import numpy as np
+import scipy.sparse as sp
+import unittest
+import matplotlib.pyplot as plt
+from SimPEG import *
+
+MESHTYPES = ['uniformTensorMesh']
+
+def getxBCyBC(mesh, alpha, beta, gamma):
+# def getxBCyBC(mesh, alpha, beta, gamma):
+    """
+
+    """
+    if mesh.dim == 1: #1D
+        if (len(alpha) != 2 or len(beta) != 2 or len(gamma) != 2):
+            raise Exception("Lenght of list, alpha should be 2")
+        fCCxm,fCCxp = mesh.cellBoundaryInd
+        nBC = fCCxm.sum()+fCCxp.sum()
+        h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
+
+        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
+        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
+
+        h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
+
+        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
+        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
+        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
+        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
+
+        xBC_xm = 0.5*a_xm
+        xBC_xp = 0.5*a_xp/b_xp
+        yBC_xm = 0.5*(1.-b_xm)
+        yBC_xp = 0.5*(1.-1./b_xp)
+
+        xBC = np.r_[xBC_xm, xBC_xp]
+        yBC = np.r_[yBC_xm, yBC_xp]
+
+    elif mesh.dim == 2: #2D
+        if (len(alpha) != 4 or len(beta) != 4 or len(gamma) != 4):
+            raise Exception("Lenght of list, alpha should be 4")
+
+        fCCxm,fCCxp,fCCym,fCCyp = mesh.cellBoundaryInd
+        fxm,fxp,fym,fyp = mesh.faceBoundaryInd
+        nBC = fCCxm.sum()+fCCxp.sum()+fCCxm.sum()+fCCxp.sum()
+        h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
+        h_ym, h_yp = mesh.gridCC[fCCym], mesh.gridCC[fCCyp]
+
+        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
+        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
+        alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
+        alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
+
+        h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
+        h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
+
+        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
+        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
+        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
+        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
+
+        a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
+        b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
+        a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
+        b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
+
+        xBC_xm = 0.5*a_xm
+        xBC_xp = 0.5*a_xp/b_xp
+        yBC_xm = 0.5*(1.-b_xm)
+        yBC_xp = 0.5*(1.-1./b_xp)
+        xBC_ym = 0.5*a_ym
+        xBC_yp = 0.5*a_yp/b_yp
+        yBC_ym = 0.5*(1.-b_ym)
+        yBC_yp = 0.5*(1.-1./b_yp)
+
+        sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
+        sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
+
+        xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
+        xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
+        yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
+        yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
+
+        xBC = np.r_[xBC_x, xBC_y]
+        yBC = np.r_[yBC_x, yBC_y]
+
+    elif mesh.dim == 3: #3D
+        if (len(alpha) != 6 or len(beta) != 6 or len(gamma) != 6):
+            raise Exception("Lenght of list, alpha should be 6")
+        fCCxm,fCCxp,fCCym,fCCyp,fCCzm,fCCzp = mesh.cellBoundaryInd
+        fxm,fxp,fym,fyp,fzm,fzp = mesh.faceBoundaryInd
+        nBC = fCCxm.sum()+fCCxp.sum()+fCCxm.sum()+fCCxp.sum()
+        h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
+        h_ym, h_yp = mesh.gridCC[fCCym], mesh.gridCC[fCCyp]
+        h_zm, h_zp = mesh.gridCC[fCCzm], mesh.gridCC[fCCzp]
+
+        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
+        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
+        alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
+        alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
+        alpha_zm, beta_zm, gamma_zm = alpha[2], beta[2], gamma[2]
+        alpha_zp, beta_zp, gamma_zp = alpha[3], beta[3], gamma[3]
+
+        h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
+        h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
+        h_zm, h_zp = mesh.gridCC[fCCzm,2], mesh.gridCC[fCCzp,2]
+
+        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
+        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
+        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
+        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
+
+        a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
+        b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
+        a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
+        b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
+
+        a_zm = gamma_zm/(0.5*alpha_zm-beta_zm/h_zm)
+        b_zm = (0.5*alpha_zm+beta_zm/h_zm)/(0.5*alpha_zm-beta_zm/h_zm)
+        a_zp = gamma_zp/(0.5*alpha_zp-beta_zp/h_zp)
+        b_zp = (0.5*alpha_zp+beta_zp/h_zp)/(0.5*alpha_zp-beta_zp/h_zp)
+
+        xBC_xm = 0.5*a_xm
+        xBC_xp = 0.5*a_xp/b_xp
+        yBC_xm = 0.5*(1.-b_xm)
+        yBC_xp = 0.5*(1.-1./b_xp)
+        xBC_ym = 0.5*a_ym
+        xBC_yp = 0.5*a_yp/b_yp
+        yBC_ym = 0.5*(1.-b_ym)
+        yBC_yp = 0.5*(1.-1./b_yp)
+        xBC_zm = 0.5*a_zm
+        xBC_zp = 0.5*a_zp/b_zp
+        yBC_zm = 0.5*(1.-b_zm)
+        yBC_zp = 0.5*(1.-1./b_zp)
+
+        sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
+        sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
+        sortindsfz = np.argsort(np.r_[np.arange(mesh.nFz)[fzm], np.arange(mesh.nFz)[fzp]])
+
+        xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
+        xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
+        xBC_z = np.r_[xBC_zm, xBC_zp][sortindsfz]
+
+        yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
+        yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
+        yBC_z = np.r_[yBC_zm, yBC_zp][sortindsfz]
+
+        xBC = np.r_[xBC_x, xBC_y, xBC_z]
+        yBC = np.r_[yBC_x, yBC_y, yBC_z]
+
+    return xBC, yBC
+
+class Test1D_InhomogeneousMixed(Tests.OrderTest):
+    name = "1D - Mixed"
+    meshTypes = MESHTYPES
+    meshDimension = 1
+    expectedOrders = 2
+    meshSizes = [4, 8, 16, 32]
+
+    def getError(self):
+        #Test function
+        phi_fun = lambda x: np.cos(np.pi*x)
+        j_fun = lambda x: np.pi*np.sin(np.pi*x)
+        phi_deriv = lambda x: -j_fun(x)
+        q_fun = lambda x: (np.pi**2)*np.cos(np.pi*x)
+
+        xc_ana = phi_fun(self.M.gridCC)
+        q_ana = q_fun(self.M.gridCC)
+        j_ana = j_fun(self.M.gridFx)
+
+        # Get boundary locations
+        vecN = self.M.vectorNx
+        vecC = self.M.vectorCCx
+
+        # Setup Mixed B.C (alpha, beta, gamma)
+        alpha_xm, alpha_xp = 1., 1.
+        beta_xm, beta_xp =  1., 1.
+        alpha = np.r_[alpha_xm, alpha_xp]
+        beta = np.r_[beta_xm, beta_xp]
+        vecN = self.M.vectorNx
+        vecC = self.M.vectorCCx
+        phi_bc = phi_fun(vecN[[0,-1]])
+        phi_deriv_bc = phi_deriv(vecN[[0,-1]])
+        gamma = alpha*phi_bc + beta*phi_deriv_bc
+        x_BC, y_BC = getxBCyBC(self.M, alpha, beta, gamma)
+
+
+        sigma = np.ones(self.M.nC)
+        Mfrho = self.M.getFaceInnerProduct(1./sigma)
+        MfrhoI = self.M.getFaceInnerProduct(1./sigma, invMat=True)
+        V = Utils.sdiag(self.M.vol)
+        Div = V*self.M.faceDiv
+        P_BC, B = self.M.getBCProjWF_simple()
+        q = q_fun(self.M.gridCC)
+        M = B*self.M.aveCC2F
+        G = Div.T - P_BC*Utils.sdiag(y_BC)*M
+        # Mrhoj = D.T V phi + P_BC*Utils.sdiag(y_BC)*M phi - P_BC*x_BC
+        rhs = V*q + Div*MfrhoI*P_BC*x_BC
+        A = Div*MfrhoI*G
+
+        if self.myTest == 'xc':
+            #TODO: fix the null space
+            Ainv = Solver(A)
+            xc = Ainv*rhs
+            err = np.linalg.norm((xc-xc_ana), np.inf)
+        else:
+            NotImplementedError
+        return err
+
+
+    def test_order(self):
+        print "==== Testing Mixed boudary conduction for CC-problem ===="
+        self.name = "1D"
+        self.myTest = 'xc'
+        self.orderTest()
+
+class Test2D_InhomogeneousMixed(Tests.OrderTest):
+    name = "2D - Mixed"
+    meshTypes = MESHTYPES
+    meshDimension = 2
+    expectedOrders = 2
+    meshSizes = [4, 8, 16, 32]
+
+    def getError(self):
+        #Test function
+        phi_fun = lambda x: np.cos(np.pi*x[:,0])*np.cos(np.pi*x[:,1])
+        j_funX = lambda x: +np.pi*np.sin(np.pi*x[:,0])*np.cos(np.pi*x[:,1])
+        j_funY = lambda x: +np.pi*np.cos(np.pi*x[:,0])*np.sin(np.pi*x[:,1])
+        phideriv_funX = lambda x: -j_funX(x)
+        phideriv_funY = lambda x: -j_funY(x)
+        q_fun = lambda x: +2*(np.pi**2)*phi_fun(x)
+
+        xc_ana = phi_fun(self.M.gridCC)
+        q_ana = q_fun(self.M.gridCC)
+        jX_ana = j_funX(self.M.gridFx)
+        jY_ana = j_funY(self.M.gridFy)
+        j_ana = np.r_[jX_ana,jY_ana]
+
+        # Get boundary locations
+        fxm,fxp,fym,fyp = self.M.faceBoundaryInd
+        gBFxm = self.M.gridFx[fxm,:]
+        gBFxp = self.M.gridFx[fxp,:]
+        gBFym = self.M.gridFy[fym,:]
+        gBFyp = self.M.gridFy[fyp,:]
+
+        # Setup Mixed B.C (alpha, beta, gamma)
+        alpha_xm, alpha_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+        beta_xm, beta_xp =  np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+        alpha_ym, alpha_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+        beta_ym, beta_yp =  np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+
+        phi_bc_xm, phi_bc_xp = phi_fun(gBFxm), phi_fun(gBFxp)
+        phi_bc_ym, phi_bc_yp = phi_fun(gBFym), phi_fun(gBFyp)
+
+        phiderivX_bc_xm, phiderivX_bc_xp = phideriv_funX(gBFxm), phideriv_funX(gBFxp)
+        phiderivY_bc_ym, phiderivY_bc_yp = phideriv_funY(gBFym), phideriv_funY(gBFyp)
+
+        gamma_fun = lambda alpha, beta, phi, phi_deriv: alpha*phi + beta*phi_deriv
+        gamma_xm = gamma_fun(alpha_xm, beta_xm, phi_bc_xm, phiderivX_bc_xm)
+        gamma_xp = gamma_fun(alpha_xp, beta_xp, phi_bc_xp, phiderivX_bc_xp)
+        gamma_ym = gamma_fun(alpha_ym, beta_ym, phi_bc_ym, phiderivY_bc_ym)
+        gamma_yp = gamma_fun(alpha_yp, beta_yp, phi_bc_yp, phiderivY_bc_yp)
+
+        alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp]
+        beta = [beta_xm, beta_xp, beta_ym, beta_yp]
+        gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp]
+
+        x_BC, y_BC = getxBCyBC(self.M, alpha, beta, gamma)
+
+
+        sigma = np.ones(self.M.nC)
+        Mfrho = self.M.getFaceInnerProduct(1./sigma)
+        MfrhoI = self.M.getFaceInnerProduct(1./sigma, invMat=True)
+        V = Utils.sdiag(self.M.vol)
+        Div = V*self.M.faceDiv
+        P_BC, B = self.M.getBCProjWF_simple()
+        q = q_fun(self.M.gridCC)
+        M = B*self.M.aveCC2F
+        G = Div.T - P_BC*Utils.sdiag(y_BC)*M
+        rhs = V*q + Div*MfrhoI*P_BC*x_BC
+        A = Div*MfrhoI*G
+
+        if self.myTest == 'xc':
+            Ainv = Solver(A)
+            xc = Ainv*rhs
+            err = np.linalg.norm((xc-xc_ana), np.inf)
+        else:
+            NotImplementedError
+        return err
+
+
+    def test_order(self):
+        print "==== Testing Mixed boudary conduction for CC-problem ===="
+        self.name = "2D"
+        self.myTest = 'xc'
+        self.orderTest()
+
+class Test3D_InhomogeneousMixed(Tests.OrderTest):
+    name = "3D - Mixed"
+    meshTypes = MESHTYPES
+    meshDimension = 3
+    expectedOrders = 2
+    meshSizes = [4, 8, 16]
+
+    def getError(self):
+        #Test function
+        phi_fun = lambda x: np.cos(np.pi*x[:,0])*np.cos(np.pi*x[:,1])*np.cos(np.pi*x[:,2])
+        j_funX = lambda x: +np.pi*np.sin(np.pi*x[:,0])*np.cos(np.pi*x[:,1])*np.cos(np.pi*x[:,2])
+        j_funY = lambda x: +np.pi*np.cos(np.pi*x[:,0])*np.sin(np.pi*x[:,1])*np.cos(np.pi*x[:,2])
+        j_funZ = lambda x: +np.pi*np.cos(np.pi*x[:,0])*np.cos(np.pi*x[:,1])*np.sin(np.pi*x[:,2])
+
+        phideriv_funX = lambda x: -j_funX(x)
+        phideriv_funY = lambda x: -j_funY(x)
+        phideriv_funZ = lambda x: -j_funZ(x)
+
+        q_fun = lambda x: 3*(np.pi**2)*phi_fun(x)
+
+        xc_ana = phi_fun(self.M.gridCC)
+        q_ana = q_fun(self.M.gridCC)
+        jX_ana = j_funX(self.M.gridFx)
+        jY_ana = j_funY(self.M.gridFy)
+        j_ana = np.r_[jX_ana,jY_ana,jY_ana]
+
+        # Get boundary locations
+        fxm,fxp,fym,fyp,fzm,fzp = self.M.faceBoundaryInd
+        gBFxm = self.M.gridFx[fxm,:]
+        gBFxp = self.M.gridFx[fxp,:]
+        gBFym = self.M.gridFy[fym,:]
+        gBFyp = self.M.gridFy[fyp,:]
+        gBFzm = self.M.gridFz[fzm,:]
+        gBFzp = self.M.gridFz[fzp,:]
+
+        # Setup Mixed B.C (alpha, beta, gamma)
+        alpha_xm, alpha_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+        beta_xm, beta_xp =  np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+        alpha_ym, alpha_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+        beta_ym, beta_yp =  np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+        alpha_zm, alpha_zp = np.ones_like(gBFzm[:,1]), np.ones_like(gBFzp[:,1])
+        beta_zm, beta_zp =  np.ones_like(gBFzm[:,1]), np.ones_like(gBFzp[:,1])
+
+
+        phi_bc_xm, phi_bc_xp = phi_fun(gBFxm), phi_fun(gBFxp)
+        phi_bc_ym, phi_bc_yp = phi_fun(gBFym), phi_fun(gBFyp)
+        phi_bc_zm, phi_bc_zp = phi_fun(gBFzm), phi_fun(gBFzp)
+
+        phiderivX_bc_xm, phiderivX_bc_xp = phideriv_funX(gBFxm), phideriv_funX(gBFxp)
+        phiderivY_bc_ym, phiderivY_bc_yp = phideriv_funY(gBFym), phideriv_funY(gBFyp)
+        phiderivY_bc_zm, phiderivY_bc_zp = phideriv_funY(gBFzm), phideriv_funY(gBFzp)
+
+        gamma_fun = lambda alpha, beta, phi, phi_deriv: alpha*phi + beta*phi_deriv
+        gamma_xm = gamma_fun(alpha_xm, beta_xm, phi_bc_xm, phiderivX_bc_xm)
+        gamma_xp = gamma_fun(alpha_xp, beta_xp, phi_bc_xp, phiderivX_bc_xp)
+        gamma_ym = gamma_fun(alpha_ym, beta_ym, phi_bc_ym, phiderivY_bc_ym)
+        gamma_yp = gamma_fun(alpha_yp, beta_yp, phi_bc_yp, phiderivY_bc_yp)
+        gamma_zm = gamma_fun(alpha_zm, beta_zm, phi_bc_zm, phiderivY_bc_zm)
+        gamma_zp = gamma_fun(alpha_zp, beta_zp, phi_bc_zp, phiderivY_bc_zp)
+
+        alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp, alpha_zm, alpha_zp]
+        beta = [beta_xm, beta_xp, beta_ym, beta_yp, beta_zm, beta_zp]
+        gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp, gamma_zm, gamma_zp]
+
+        x_BC, y_BC = getxBCyBC(self.M, alpha, beta, gamma)
+
+
+        sigma = np.ones(self.M.nC)
+        Mfrho = self.M.getFaceInnerProduct(1./sigma)
+        MfrhoI = self.M.getFaceInnerProduct(1./sigma, invMat=True)
+        V = Utils.sdiag(self.M.vol)
+        Div = V*self.M.faceDiv
+        P_BC, B = self.M.getBCProjWF_simple()
+        q = q_fun(self.M.gridCC)
+        M = B*self.M.aveCC2F
+        G = Div.T - P_BC*Utils.sdiag(y_BC)*M
+        rhs = V*q + Div*MfrhoI*P_BC*x_BC
+        A = Div*MfrhoI*G
+
+        if self.myTest == 'xc':
+            #TODO: fix the null space
+            Ainv = Solver(A)
+            xc = Ainv*rhs
+            err = np.linalg.norm((xc-xc_ana), np.inf)
+        else:
+            NotImplementedError
+        return err
+
+
+    def test_order(self):
+        print "==== Testing Mixed boudary conduction for CC-problem ===="
+        self.name = "3D"
+        self.myTest = 'xc'
+        self.orderTest()
+
+
+
+if __name__ == '__main__':
+    unittest.main()