fix bug for adjoint problem

Cross gradient?

README.rst

@@ -25,6 +25,10 @@ SimPEG
     :target: https://coveralls.io/r/simpeg/simpeg?branch=master
     :alt: Coverage status
 
+.. image:: http://img.shields.io/badge/GITTER-JOIN_CHAT-brightgreen.svg?style=flat-square
+    :alt: gitter chat room at https://gitter.im/simpeg/simpeg
+    :target: https://gitter.im/simpeg/simpeg
+    
 Simulation and Parameter Estimation in Geophysics  -  A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
 
 The vision is to create a package for finite volume simulation with applications to geophysical imaging and subsurface flow. To enable the understanding of the many different components, this package has the following features:

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])
-
+        midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + (Tx[0][2] + Tx[1][2])/2 ])
 
     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
@@ -237,40 +237,41 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
         # Save the file as a npz
         np.savez('{:03d}-{:s}'.format(self.opt.iter,self.fileName), 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 SaveOutputDictEveryIteration(_SaveEveryIteration):
-    """SaveOutputDictEveryIteration
-    A directive that saves some relevant information from the inversion run to a numpy .npz dictionary file (see numpy.savez function for further info).
-    """
-
-    def initialize(self):
-        print "SimPEG.SaveOutputDictEveryIteration will save your inversion progress as dictionary: '%s-###.npz'"%self.fileName
-
-    def endIter(self):
-        # 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:
-            mref = self.reg.mref
-        else:
-            mref = 0
-        mx = self.reg.Wx * ( self.reg.mapping * (self.invProb.curModel - mref) )
-        phi_mx = 0.5 * mx.dot(mx)
-        if self.prob.mesh.dim==2:
-            my = self.reg.Wy * ( self.reg.mapping * (self.invProb.curModel - mref) )
-            phi_my = 0.5 * my.dot(my)
-        else:
-            phi_my = 'NaN'
-        if self.prob.mesh.dim==3 and 'CYL' not in self.prob.mesh._meshType:
-            mz = self.reg.Wz * ( self.reg.mapping * (self.invProb.curModel - mref) )
-            phi_mz = 0.5 * mz.dot(mz)
-        else:
-            phi_mz = 'NaN'
-
-
-        # Save the file as a npz
-        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 SaveOutputDictEveryIteration(_SaveEveryIteration):
+#     """SaveOutputDictEveryIteration
+#     A directive that saves some relevant information from the inversion run to a numpy .npz dictionary file (see numpy.savez function for further info).
+#     """
+#
+#     def initialize(self):
+#         print "SimPEG.SaveOutputDictEveryIteration will save your inversion progress as dictionary: '%s-###.npz'"%self.fileName
+#
+#     def endIter(self):
+#         # 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.mrefInSmooth == True:
+#             mref = self.reg.mref
+#         else:
+#             mref = 0
+#         mx = self.reg.Wx * ( self.reg.mapping * (self.invProb.curModel - mref) )
+#         phi_mx = 0.5 * mx.dot(mx)
+#         if self.prob.mesh.dim==2:
+#             my = self.reg.Wy * ( self.reg.mapping * (self.invProb.curModel - mref) )
+#             phi_my = 0.5 * my.dot(my)
+#         else:
+#             phi_my = 'NaN'
+#         if self.prob.mesh.dim==3 and 'CYL' not in self.prob.mesh._meshType:
+#             mz = self.reg.Wz * ( self.reg.mapping * (self.invProb.curModel - mref) )
+#             phi_mz = 0.5 * mz.dot(mz)
+#         else:
+#             phi_mz = 'NaN'
+#
+#
+#         # Save the file as a npz
+#         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):
 
@@ -283,3 +284,92 @@ 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.curModel = self.invProb.curModel
+            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
+
+        # 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
+
+        self.invProb.beta = self.invProb.beta * self.survey.nD*0.5 / self.invProb.phi_d
+
+class Update_lin_PreCond(InversionDirective):
+
+
+    def endIter(self):
+        # Cool the threshold parameter
+
+        if getattr(self.opt, 'approxHinv', None) is not None:
+            # 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
+            print 'Updated pre-cond'
+
+class Update_Wj(InversionDirective):
+    """
+        Create approx-sensitivity base weighting using the probing method
+    """
+    k = None # Number of probing cycles
+    itr = None # Iteration number to update Wj, or always update if None
+
+    def endIter(self):
+
+        if self.itr is None or self.itr == self.opt.iter:
+
+            m = self.invProb.curModel
+            if self.k is None:
+                self.k = int(self.survey.nD/10)
+
+            def JtJv(v):
+
+                Jv = self.prob.Jvec(m, v)
+
+                return self.prob.Jtvec(m,Jv)
+
+            JtJdiag = Utils.diagEst(JtJv,len(m),k=self.k)
+            JtJdiag = JtJdiag / max(JtJdiag)
+
+            self.reg.wght = JtJdiag

SimPEG/EM/Analytics/DC.py

@@ -0,0 +1,119 @@
+import numpy as np
+from scipy.constants import mu_0, pi
+from scipy import special
+
+def DCAnalyticHalf(txloc, rxlocs, sigma, flag="wholespace"):
+    """
+        Analytic solution for electric potential from a postive pole
+
+        Input variables:
+
+            txloc =  a xyz location of A (+) electrode (np.r_[xa, ya, za])
+
+            rxlocs = [M, N]
+                M: xyz locations of M (+) electrode (np.c_[xmlocs, ymlocs, zmlocs])
+                N: xyz locations of N (-) electrode (np.c_[xnlocs, ynlocs, znlocs])
+
+            sigma = conductivity (either float or complex)
+            flag = "wholsespace" or "halfspace"
+
+    """
+    M = rxlocs[0]
+    N = rxlocs[1]
+
+    rM = np.sqrt( (M[:,0]-txloc[0])**2 + (M[:,1]-txloc[1])**2 + (M[:,2]-txloc[1])**2 )
+    rN = np.sqrt( (N[:,0]-txloc[0])**2 + (N[:,1]-txloc[1])**2 + (N[:,2]-txloc[1])**2 )
+
+    phiM = 1./(4*np.pi*rM*sigma)
+    phiN = 1./(4*np.pi*rN*sigma)
+    phi = phiM - phiN
+
+    if flag == "halfspace":
+        phi *= 2
+
+    return phi
+
+deg2rad  = lambda deg: deg/180.*np.pi
+rad2deg  = lambda rad: rad*180./np.pi
+
+def DCAnalyticSphere(txloc, rxloc, xc, radius, sigma, sigma1, \
+                 flag = "sec", order=12, halfspace=False):
+# def DCSpherePointCurrent(txloc, rxloc, xc, radius, rho, rho1, \
+#                  flag = "sec", order=12):
+    """
+
+        Parameters:
+
+            txloc (array) : current electrode location (x,y,z)
+            xc (float)    : x center of depressed sphere
+            rxloc (array) : electrode locations
+                              (Nx3 array, # of electrodes)
+            radius (float): radius of the sphere (m)
+            rho (float)   : resistivity of the background (ohm-m)
+            rho1 (float)  : resistivity of the sphere
+            flag (string) : "sec", "total", "prim"
+                              (default="sec")
+                              "sec": secondary potential only due to sphere
+                              "prim": primary potential from the point source
+                              "total": "sec"+"prim"
+            order (float) : maximum order of Legendre polynomial
+                              (default=12)
+
+        Written by Seogi Kang (skang@eos.ubc.ca)
+        Ph.D. Candidate of University of British Columbia, Canada
+
+    """
+
+    Pleg = []
+    # Compute Legendre Polynomial
+    for i in range(order):
+        Pleg.append(special.legendre(i, monic=0))
+
+
+    rho = 1./sigma
+    rho1 = 1./sigma1
+
+    # Center of the sphere should be aligned in txloc in y-direction
+    yc = txloc[1]
+    xyz = np.c_[rxloc[:,0]-xc, rxloc[:,1]-yc, rxloc[:,2]]
+    r = np.sqrt( (xyz**2).sum(axis=1) )
+
+    x0 = abs(txloc[0]-xc)
+
+    costheta = xyz[:,0]/r * (txloc[0]-xc)/x0
+    phi = np.zeros_like(r)
+    R = (r**2+x0**2.-2.*r*x0*costheta)**0.5
+    # primary potential in a whole space
+    prim = rho*1./(4*np.pi*R)
+
+    if flag =="prim":
+        return prim
+
+    sphind = r < radius
+    out = np.zeros_like(r)
+    for n in range(order):
+        An, Bn = AnBnfun(n, radius, x0, rho, rho1)
+        dumout = An*r[~sphind]**(-n-1.)*Pleg[n](costheta[~sphind])
+        out[~sphind] += dumout
+        dumin = Bn*r[sphind]**(n)*Pleg[n](costheta[sphind])
+        out[sphind] += dumin
+
+    out[~sphind] += prim[~sphind]
+
+    if halfspace:
+        scale = 2
+    else:
+        scale = 1
+
+    if flag == "sec":
+        return scale*(out-prim)
+    elif flag == "total":
+        return scale*out
+
+def AnBnfun(n, radius, x0, rho, rho1, I=1.):
+    const = I*rho/(4*np.pi)
+    bunmo = n*rho + (n+1)*rho1
+    An = const * radius**(2*n+1) / x0 ** (n+1.) * n * \
+        (rho1-rho) / bunmo
+    Bn = const * 1. / x0 ** (n+1.) * (2*n+1) * (rho1) / bunmo
+    return An, Bn

SimPEG/EM/Analytics/__init__.py

@@ -1,3 +1,4 @@
 from TDEM import hzAnalyticDipoleT
 from FDEM import hzAnalyticDipoleF
 from FDEMcasing import *
+from DC import DCAnalyticHalf, DCAnalyticSphere

SimPEG/EM/Base.py

@@ -1,13 +1,14 @@
 from SimPEG import Survey, Problem, Utils, Models, Maps, PropMaps, np, sp, Solver as SimpegSolver
 from scipy.constants import mu_0
 
+
 class EMPropMap(Maps.PropMap):
     """
         Property Map for EM Problems. The electrical conductivity (\\(\\sigma\\)) is the default inversion property, and the default value of the magnetic permeability is that of free space (\\(\\mu = 4\\pi\\times 10^{-7} \\) H/m)
     """
 
     sigma = Maps.Property("Electrical Conductivity", defaultInvProp = True, propertyLink=('rho',Maps.ReciprocalMap))
-    mu = Maps.Property("Magnetic Permeability", defaultVal = mu_0, propertyLink=('mui',Maps.ReciprocalMap))
+    mu = Maps.Property("Inverse Magnetic Permeability", defaultVal = mu_0, propertyLink=('mui',Maps.ReciprocalMap))
 
     rho = Maps.Property("Electrical Resistivity", propertyLink=('sigma', Maps.ReciprocalMap))
     mui = Maps.Property("Inverse Magnetic Permeability", defaultVal = 1./mu_0, propertyLink=('mu', Maps.ReciprocalMap))
@@ -70,6 +71,12 @@ class BaseEMProblem(Problem.BaseProblem):
             self._Mf = self.mesh.getFaceInnerProduct()
         return self._Mf
 
+    @property
+    def Vol(self):
+        if getattr(self, '_Vol', None) is None:
+            self._Vol = Utils.sdiag(self.mesh.vol)
+        return self._Vol
+
 
     # ----- Magnetic Permeability ----- #
     @property
@@ -127,7 +134,6 @@ class BaseEMProblem(Problem.BaseProblem):
         """
         return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u) * self.curModel.sigmaDeriv
 
-
     @property
     def MeSigmaI(self):
         """
@@ -150,7 +156,6 @@ class BaseEMProblem(Problem.BaseProblem):
         return dMeSigmaI_dI * ( dMe_dsig * ( dsig_dm))
         # return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma, invMat=True)(u)
 
-
     @property
     def MfRho(self):
         """
@@ -183,7 +188,12 @@ class BaseEMProblem(Problem.BaseProblem):
         """
             Derivative of :code:`MfRhoI` with respect to the model.
         """
-        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho, invMat=True)(u) * self.curModel.rhoDeriv
+
+        dMfRhoI_dI = -self.MfRhoI**2
+        dMf_drho = self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u)
+        return dMfRhoI_dI * ( dMf_drho * (-Utils.sdiag(self.curModel.rho**2) * self.curModel.sigmaDeriv) )
+
+        # return self.mesh.getFaceInnerProductDeriv(self.curModel.rho, invMat=True)(u) * self.curModel.rhoDeriv
 
 class BaseEMSurvey(Survey.BaseSurvey):
 
@@ -192,7 +202,7 @@ class BaseEMSurvey(Survey.BaseSurvey):
         self.srcList = srcList
         Survey.BaseSurvey.__init__(self, **kwargs)
 
-    def eval(self, u):
+    def eval(self, f):
         """
         Project fields to receiver locations
         :param Fields u: fields object
@@ -202,8 +212,8 @@ class BaseEMSurvey(Survey.BaseSurvey):
         data = Survey.Data(self)
         for src in self.srcList:
             for rx in src.rxList:
-                data[src, rx] = rx.eval(src, self.mesh, u)
+                data[src, rx] = rx.eval(src, self.mesh, f)
         return data
 
-    def evalDeriv(self, u):
+    def evalDeriv(self, f):
         raise Exception('Use Receivers to project fields deriv.')

SimPEG/EM/FDEM/FDEM.py

@@ -8,29 +8,29 @@ from SimPEG.EM.Utils import omega
 
 class BaseFDEMProblem(BaseEMProblem):
     """
-    We start by looking at Maxwell's equations in the electric
-    field \\\(\\\mathbf{e}\\\) and the magnetic flux
-    density \\\(\\\mathbf{b}\\\)
+        We start by looking at Maxwell's equations in the electric
+        field \\\(\\\mathbf{e}\\\) and the magnetic flux
+        density \\\(\\\mathbf{b}\\\)
 
-    .. math ::
+        .. math ::
 
-        \mathbf{C} \mathbf{e} + i \omega \mathbf{b} = \mathbf{s_m} \\\\
-        {\mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f} \mathbf{b} - \mathbf{M_{\sigma}^e} \mathbf{e} = \mathbf{s_e}}
+            \mathbf{C} \mathbf{e} + i \omega \mathbf{b} = \mathbf{s_m} \\\\
+            {\mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f} \mathbf{b} - \mathbf{M_{\sigma}^e} \mathbf{e} = \mathbf{s_e}}
 
-    if using the E-B formulation (:code:`Problem_e`
-    or :code:`Problem_b`). Note that in this case, :math:`\mathbf{s_e}` is an integrated quantity.
+        if using the E-B formulation (:code:`Problem_e`
+        or :code:`Problem_b`). Note that in this case, :math:`\mathbf{s_e}` is an integrated quantity.
 
-    If we write Maxwell's equations in terms of
-    \\\(\\\mathbf{h}\\\) and current density \\\(\\\mathbf{j}\\\)
+        If we write Maxwell's equations in terms of
+        \\\(\\\mathbf{h}\\\) and current density \\\(\\\mathbf{j}\\\)
 
-    .. math ::
+        .. math ::
 
-        \mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{j} + i \omega \mathbf{M_{\mu}^e} \mathbf{h} = \mathbf{s_m} \\\\
-        \mathbf{C} \mathbf{h} - \mathbf{j} = \mathbf{s_e}
+            \mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{j} + i \omega \mathbf{M_{\mu}^e} \mathbf{h} = \mathbf{s_m} \\\\
+            \mathbf{C} \mathbf{h} - \mathbf{j} = \mathbf{s_e}
 
-    if using the H-J formulation (:code:`Problem_j` or :code:`Problem_h`). Note that here, :math:`\mathbf{s_m}` is an integrated quantity.
+        if using the H-J formulation (:code:`Problem_j` or :code:`Problem_h`). Note that here, :math:`\mathbf{s_m}` is an integrated quantity.
 
-    The problem performs the elimination so that we are solving the system for \\\(\\\mathbf{e},\\\mathbf{b},\\\mathbf{j} \\\) or \\\(\\\mathbf{h}\\\)
+        The problem performs the elimination so that we are solving the system for \\\(\\\mathbf{e},\\\mathbf{b},\\\mathbf{j} \\\) or \\\(\\\mathbf{h}\\\)
     """
 
     surveyPair = SurveyFDEM
@@ -167,6 +167,7 @@ class BaseFDEMProblem(BaseEMProblem):
 
         for i, src in enumerate(Srcs):
             smi, sei = src.eval(self)
+            #Why are you adding?
             s_m[:,i] = s_m[:,i] + smi
             s_e[:,i] = s_e[:,i] + sei
 
@@ -204,17 +205,6 @@ class Problem_e(BaseFDEMProblem):
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
 
-    def _GLoc(self, fieldType):
-        if fieldType == 'e':
-            return 'E'
-        elif fieldType == 'b':
-            return 'F'
-        elif (fieldType == 'h') or (fieldType == 'j'):
-            return 'CCV'
-        else:
-            raise Exception('Field type must be e, b, h, j')
-
-
     def getA(self, freq):
         """
         System matrix
@@ -294,6 +284,7 @@ class Problem_e(BaseFDEMProblem):
         if adjoint:
             dRHS = MfMui * (C * v)
             return s_mDeriv(dRHS) - 1j * omega(freq) * s_eDeriv(v)
+
         else:
             return C.T * (MfMui * s_mDeriv(v)) -1j * omega(freq) * s_eDeriv(v)
 
@@ -325,16 +316,6 @@ class Problem_b(BaseFDEMProblem):
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
 
-    def _GLoc(self, fieldType):
-        if fieldType == 'e':
-            return 'E'
-        elif fieldType == 'b':
-            return 'F'
-        elif (fieldType == 'h') or (fieldType == 'j'):
-            return'CCV'
-        else:
-            raise Exception('Field type must be e, b, h, j')
-
     def getA(self, freq):
         """
         System matrix
@@ -483,16 +464,6 @@ class Problem_j(BaseFDEMProblem):
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
 
-    def _GLoc(self, fieldType):
-        if fieldType == 'h':
-            return 'E'
-        elif fieldType == 'j':
-            return 'F'
-        elif (fieldType == 'e') or (fieldType == 'b'):
-            return 'CCV'
-        else:
-            raise Exception('Field type must be e, b, h, j')
-
     def getA(self, freq):
         """
         System matrix
@@ -631,17 +602,6 @@ class Problem_h(BaseFDEMProblem):
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
 
-    def _GLoc(self, fieldType):
-        if fieldType == 'h':
-            return 'E'
-        elif fieldType == 'j':
-            return 'F'
-        elif (fieldType == 'e') or (fieldType == 'b'):
-            return 'CCV'
-        else:
-            raise Exception('Field type must be e, b, h, j')
-
-
     def getA(self, freq):
         """
         System matrix

SimPEG/EM/FDEM/FieldsFDEM.py

@@ -181,7 +181,7 @@ class Fields_e(Fields):
                   }
 
     def __init__(self, mesh, survey, **kwargs):
-        Fields.__init__(self,mesh,survey,**kwargs)
+        Fields.__init__(self, mesh, survey, **kwargs)
 
     def startup(self):
         self.prob = self.survey.prob
@@ -193,6 +193,16 @@ class Fields_e(Fields):
         self._MeSigmaDeriv = self.survey.prob.MeSigmaDeriv
         self._MfMui = self.survey.prob.MfMui
 
+    def _GLoc(self, fieldType):
+        if fieldType == 'e':
+            return 'E'
+        elif fieldType == 'b':
+            return 'F'
+        elif (fieldType == 'h') or (fieldType == 'j'):
+            return 'CCV'
+        else:
+            raise Exception('Field type must be e, b, h, j')
+
 
     def _ePrimary(self, eSolution, srcList):
         """
@@ -455,6 +465,17 @@ class Fields_b(Fields):
         self._nC = self.survey.prob.mesh.nC
 
 
+
+    def _GLoc(self,fieldType):
+        if fieldType == 'e':
+            return 'E'
+        elif fieldType == 'b':
+            return 'F'
+        elif (fieldType == 'h') or (fieldType == 'j'):
+            return'CCV'
+        else:
+            raise Exception('Field type must be e, b, h, j')
+
     def _bPrimary(self, bSolution, srcList):
         """
         Primary magnetic flux density from source
@@ -708,6 +729,16 @@ class Fields_j(Fields):
         self._aveE2CCV = self.survey.prob.mesh.aveE2CCV
         self._nC = self.survey.prob.mesh.nC
 
+    def _GLoc(self,fieldType):
+        if fieldType == 'h':
+            return 'E'
+        elif fieldType == 'j':
+            return 'F'
+        elif (fieldType == 'e') or (fieldType == 'b'):
+            return 'CCV'
+        else:
+            raise Exception('Field type must be e, b, h, j')
+
     def _jPrimary(self, jSolution, srcList):
         """
         Primary current density from source
@@ -993,6 +1024,16 @@ class Fields_h(Fields):
         self._aveE2CCV = self.survey.prob.mesh.aveE2CCV
         self._nC = self.survey.prob.mesh.nC
 
+    def _GLoc(self,fieldType):
+        if fieldType == 'h':
+            return 'E'
+        elif fieldType == 'j':
+            return 'F'
+        elif (fieldType == 'e') or (fieldType == 'b'):
+            return 'CCV'
+        else:
+            raise Exception('Field type must be e, b, h, j')
+
     def _hPrimary(self, hSolution, srcList):
         """
         Primary magnetic field from source

SimPEG/EM/FDEM/SrcFDEM.py

@@ -9,14 +9,11 @@ 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):
         """
-        Evaluate the source terms.
         - :math:`s_m` : magnetic source term
         - :math:`s_e` : electric source term
 
@@ -105,7 +102,7 @@ class BaseSrc(Survey.BaseSrc):
         """
         return Zero()
 
-    def s_mDeriv(self, prob, v, adjoint=False):
+    def s_mDeriv(self, prob, v, adjoint = False):
         """
         Derivative of magnetic source term with respect to the inversion model
 
@@ -118,7 +115,7 @@ class BaseSrc(Survey.BaseSrc):
 
         return Zero()
 
-    def s_eDeriv(self, prob, v, adjoint=False):
+    def s_eDeriv(self, prob, v, adjoint = False):
         """
         Derivative of electric source term with respect to the inversion model
 
@@ -138,12 +135,13 @@ 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):
+    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)
+        self.integrate = integrate
 
         BaseSrc.__init__(self, rxList)
 
@@ -167,12 +165,13 @@ 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, integrate=True):  #ePrimary=Zero(), bPrimary=Zero(), hPrimary=Zero(), jPrimary=Zero()):
         self._s_m = np.array(s_m, dtype=complex)
         self.freq = float(freq)
+        self.integrate = integrate
 
         BaseSrc.__init__(self, rxList)
 
@@ -197,13 +196,14 @@ 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):
+    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)
-        BaseSrc.__init__(self, rxList, **kwargs)
+        self.integrate = integrate
+        BaseSrc.__init__(self, rxList)
 
     def s_m(self, prob):
         """
@@ -277,13 +277,14 @@ 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):
@@ -541,10 +542,10 @@ 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 = MagneticLoopVectorPotential
+            srcfct = MagneticDipoleVectorPotential
             ax = srcfct(self.loc, gridX, 'x', self.radius, mu=self.mu)
             ay = srcfct(self.loc, gridY, 'y', self.radius, mu=self.mu)
             az = srcfct(self.loc, gridZ, 'z', self.radius, mu=self.mu)
@@ -603,231 +604,5 @@ class CircularLoop(BaseSrc):
             return -C.T * (MMui_s * self.bPrimary(prob))
 
 
-class PrimSec(BaseSrc):
-    """
-    Primary-Secondary source in the physical properties. A primary problem is
-    first solved, and the fields from this problem are used to construct a
-    source term for the secondary problem. Either a mesh and
-    fields need to be provided or a prob and a survey.
-
-    For the EB formulation, we start the derivation from Maxwell's equations:
-
-    .. math::
-        \\nabla \\times \\vec{E} + i \omega \\vec{B} = \\vec{s_m} \\\\
-        \\nabla \\times \\mu^{-1} \\vec{B} - \sigma \\vec{E} = \\vec{s_e}
-
-    we consider the physical properties, fields, and fluxes to be composed of
-    two parts, a primary and a secondary:
-
-        - :math:`\sigma   = \sigma_p + \sigma_s`
-        - :math:`\mu^{-1} = \mu^{-1}_p + \mu^{-1}_s`
-        - :math:`\\vec{E} = \\vec{E_p} + \\vec{E_s}`
-        - :math:`\\vec{B} = \\vec{B_p} + \\vec{B_s}`
-
-    and choose our primary such that
-
-    .. math::
-        \\nabla \\times \\vec{E}_p + i \omega \\vec{B}_p = \\vec{s_m} \\\\
-        \\nabla \\times \\mu^{-1}_p \\vec{B}_p - \sigma_p \\vec{E}_p = \\vec{s_e}_p
-
-    so the secondary problem is then
-
-    .. math::
-        \\nabla \\times \\vec{E}_s + i \omega \\vec{B}_s = 0 \\\\
-        \\nabla \\times \\mu^{-1} \\vec{B}_s - \sigma \\vec{E}_s = - \\nabla \\times \\mu^{-1}_s \\vec{B}_p + \sigma_s \\vec{E}_p
-
-
-    If instead, HJ formulation is considered, then we start off with
-
-    .. math::
-        \\nabla \\times \\rho \\vec{J} + i \omega \\mu \\vec{H} = \\vec{s_m} \\\\
-        \\nabla \\times \\vec{H} - \\vec{J} = \\vec{s_e}
-
-    and we define the primary secondary problem in terms of
-
-        - :math:`\\rho  = \\rho_p + \\rho_s`
-        - :math:`\mu = \mu_p + \mu_s`
-        - :math:`\\vec{J} = \\vec{J_p} + \\vec{J_s}`
-        - :math:`\\vec{H} = \\vec{H_p} + \\vec{H_s}`
-
-    with the primary being defined by
-
-    .. math::
-        \\nabla \\times \\rho_p \\vec{J}_p + i \omega \\mu_p \\vec{H}_p = \\vec{s_m} \\\\
-        \\nabla \\times \\vec{H}_p - \\vec{J}_p = \\vec{s_e}
-
-    so the secondary problem is given by
-
-    .. math::
-        \\nabla \\times \\rho \\vec{J}_s + i \omega \\mu \\vec{H} = - \\nabla \\times \\rho_s \\vec{J}_p - i \omega \\mu_s \\vec{H}_p \\
-        \\nabla \\times \\vec{H}_p - \\vec{J}_p = 0
-
-    Note: if different meshes are employed for the primary and secondary
-    problems, then we need to interpolate the fields from the primary mesh to
-    the secondary mesh. We do this by always interpolating the field and
-    computing a flux if need be in order to ensure that fluxes remain
-    numerically divergence free.
-
-    :param list rxList: Receiver list
-    :param float freq: frequency
-    :param numpy.array m: primary model
-    :param Problem prob: primary problem
-    :param Survey survey: primary survey
-    """
-
-
-    def __init__(self, rxList, freq, m, prob, survey):
-        self.freq = float(freq)
-        self.m = m
-        self.prob = prob
-        self.survey = survey
-        self.fields = None
-
-        if self.survey.ispaired:
-            if self.survey.prob is not self.prob:
-                raise Exception('The survey object is already paired to a problem. Use survey.unpair()')
-        else:
-            self.prob.pair(self.survey)
-
-        self.mesh = self.prob.mesh
-        self.prob.curModel = self.m
-
-        BaseSrc.__init__(self, rxList)
-
-    def MeSigma(self, prob):
-        if getattr(self, '_MeSigma', None) is None:
-            sigmaprimary = self.prob.curModel.sigma
-            if self.mesh != prob.mesh:
-                P = self.mesh.getInterpolationMatMesh2Mesh(prob.mesh, locType='CC')
-                sigmaprimary = P * sigmaprimary
-            self._MeSigma = prob.mesh.getEdgeInnerProduct(sigmaprimary)
-        return self._MeSigma
-
-    def MfMui(self, prob):
-        if getattr(self, '_MfMui', None) is None:
-            muiprimary = self.prob.curModel.mui
-            if self.mesh != prob.mesh and not isinstance(muiprimary,float): # if different meshes and mu is a vector --> need to interpolate
-                P = self.mesh.getInterpolationMatMesh2Mesh(prob.mesh, locType='CC')
-                muiprimary = P * muiprimary
-            self._MfMui = prob.mesh.getFaceInnerProduct(muiprimary)
-        return self._MfMui
-
-    def MfRho(self, prob):
-        if getattr(self, '_MfRho', None) is None:
-            rhoprimary = self.prob.curModel.rho
-            if self.mesh != prob.mesh:
-                P = self.mesh.getInterpolationMatMesh2Mesh(prob.mesh, locType='CC')
-                rhoprimary = P * rhoprimary
-            self._MfRho = prob.mesh.getFaceInnerProduct(rhoprimary)
-        return self._MfRho
-
-    def MeMu(self, prob):
-        if getattr(self, '_MeMu', None) is None:
-            muprimary = self.prob.curModel.mu
-            if self.mesh != prob.mesh and not isinstance(muiprimary,float): # if different meshes and mu is a vector --> need to interpolate
-                P = self.mesh.getInterpolationMatMesh2Mesh(prob.mesh, locType='CC')
-                muprimary = P * muprimary
-            self._MeMu = prob.mesh.getEdgeInnerProduct(muprimary)
-        return self._MeMu
-
-    # note if you switch from one formulation to another, but are using the same mesh, this will break
-    def ePrimary(self,prob):
-        if getattr(self, '_ePrimary', None) is None:
-            if self.fields is None:
-                self.fields = self.prob.fields(self.m)
-
-            ePrimary = self.fields[:,'e']
-
-            if self.mesh != prob.mesh:
-                if self.prob._formulation == 'HJ':
-                    P = self.mesh.getInterpolationMatMesh2Mesh(prob.mesh, locType=prob._GLoc('e'), locTypeFrom='CCV')
-                else:
-                    P = self.mesh.getInterpolationMatMesh2Mesh(prob.mesh, locType=prob._GLoc('e'))
-                ePrimary = Utils.mkvc(P * ePrimary)
-            self._ePrimary = Utils.mkvc(ePrimary)
-
-        return self._ePrimary
-
-    # note if you switch from one formulation to another, but are using the same mesh, this will break
-    def bPrimary(self, prob):
-        if getattr(self, '_bPrimary', None) is None:
-            if self.fields is None:
-                self.fields = self.prob.fields(self.m)
-
-            if self.mesh == prob.mesh:
-                bPrimary = self.fields[:,'b']
-            else:
-                bPrimary = prob.mesh.edgeCurl * self.ePrimary(prob)
-
-            self._bPrimary = Utils.mkvc(bPrimary)
-
-        return self._bPrimary
-
-    # note if you switch from one formulation to another, but are using the same mesh, this will break
-    def hPrimary(self, prob):
-        if getattr(self, '_hPrimary', None) is None:
-            if self.fields is None:
-                self.fields = self.prob.fields(self.m)
-
-            hPrimary = self.fields[:,'h']
-
-            if self.mesh != prob.mesh:
-                if self.prob._formulation == 'EB':
-                    P = self.mesh.getInterpolationMatMesh2Mesh(prob.mesh, locType=prob._GLoc('h'), locTypeFrom='CCV')
-                else:
-                    P = self.mesh.getInterpolationMatMesh2Mesh(prob.mesh, locType=prob._GLoc('h'))
-                print P.shape, hPrimary.shape, prob._GLoc('h')
-                hPrimary = Utils.mkvc(P * hPrimary)
-            self._hPrimary = Utils.mkvc(hPrimary)
-
-        return self._hPrimary
-
-    # note if you switch from one formulation to another, but are using the same mesh, this will break
-    def jPrimary(self, prob):
-        if getattr(self, '_jPrimary', None) is None:
-            if self.fields is None:
-                self.fields = self.prob.fields(self.m)
-
-            if self.mesh == prob.mesh:
-                jPrimary = self.fields[:,'j']
-            else:
-                jPrimary = prob.mesh.edgeCurl * self.hPrimary(prob)
-
-            self._jPrimary = Utils.mkvc(jPrimary)
-
-        return self._jPrimary
-
-    def s_e(self,prob):
-        if prob._formulation == 'EB':
-            # - \\nabla \\times \\mu^{-1}_s \\vec{B}_p + \sigma_s \\vec{E}_p
-            s_e =  -prob.mesh.edgeCurl.T * ((prob.MfMui - self.MfMui(prob)) * self.bPrimary(prob)) +  (prob.MeSigma - self.MeSigma(prob)) * self.ePrimary(prob)
-            return Utils.mkvc(s_e)
-        else:
-            return Zero()
-
-    def s_eDeriv(self, prob, v, adjoint=False):
-        if prob._formulation == 'EB':
-            if adjoint is True:
-                return prob.MeSigmaDeriv(self.ePrimary(prob)).T * v
-            return prob.MeSigmaDeriv(self.ePrimary(prob)) * v
-        else:
-            return Zero()
-
-    def s_m(self,prob):
-        if prob._formulation == 'HJ':
-            # - \\nabla \\times \\rho_s \\vec{J}_p - i \omega \\mu_s \\vec{H}_p
-            s_m = - prob.mesh.edgeCurl.T * (prob.MfRho - self.MfRho(prob)) * self.jPrimary(prob) - 1j * omega(self.freq) * ((prob.MeMu - self.MeMu(prob)) * self.hPrimary(prob))
-            return s_m
-        else:
-            return Zero()
-
-    def s_mDeriv(self, prob, v, adjoint=False):
-        if prob._formulation == 'HJ':
-            if adjoint is True:
-                return - prob.MfRhoDeriv(self.jPrimary(prob)).T * (prob.mesh.edgeCurl * v)
-            return - prob.mesh.edgeCurl.T * (prob.MfRhoDeriv(self.jPrimary(prob)) * v)
-        else:
-            return Zero()
-
 
 

SimPEG/EM/FDEM/SurveyFDEM.py

@@ -63,9 +63,9 @@ class Rx(SimPEG.Survey.BaseRx):
         """Component projection (real/imag)"""
         return self.knownRxTypes[self.rxType][2]
 
-    def projGLoc(self, u):
+    def projGLoc(self, f):
         """Grid Location projection (e.g. Ex Fy ...)"""
-        return u.prob._GLoc(self.rxType[0]) + self.knownRxTypes[self.rxType][1]
+        return f._GLoc(self.rxType[0]) + self.knownRxTypes[self.rxType][1]
 
     def eval(self, src, mesh, f):
         """
@@ -77,6 +77,8 @@ class Rx(SimPEG.Survey.BaseRx):
         :rtype: numpy.ndarray
         :return: fields projected to recievers
         """
+        # projGLoc = u._GLoc(self.knownRxTypes[self.rxType][0])
+        # projGLoc += self.knownRxTypes[self.rxType][1]
 
         P = self.getP(mesh, self.projGLoc(f))
         f_part_complex = f[src, self.projField]

SimPEG/EM/Static/DC/BoundaryUtils.py

@@ -0,0 +1,160 @@
+import numpy as np
+
+def getxBCyBC_CC(mesh, alpha, beta, gamma):
+# def getxBCyBC(mesh, alpha, beta, gamma):
+    """
+    This is a subfunction generating mixed-boundary condition:
+
+    .. math::
+
+        \nabla \cdot \vec{j} = -\nabla \cdot \vec{j}_s = q
+
+        \rho \vec{j} = -\nabla \phi \phi
+
+        \alpha \phi + \beta \frac{\partial \phi}{\partial r} = \gamma \ at \ r = \partial \Omega
+
+        xBC = f_1(\alpha, \beta, \gamma)
+        yBC = f(\alpha, \beta, \gamma)
+
+    Computes xBC and yBC for cell-centered discretizations
+    """
+    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]
+        h_xm, h_xp = mesh.hx[0], mesh.hx[-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)
+
+        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")
+
+        fxm,fxp,fym,fyp = mesh.faceBoundaryInd
+        nBC = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
+
+        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]
+
+        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
+        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
+
+        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 = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
+
+        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[4], beta[4], gamma[4]
+        alpha_zp, beta_zp, gamma_zp = alpha[5], beta[5], gamma[5]
+
+        # 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]
+
+        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
+        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
+        h_zm, h_zp = mesh.hz[0]*np.ones_like(alpha_zm), mesh.hz[-1]*np.ones_like(alpha_zp)
+
+        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

SimPEG/EM/Static/DC/FieldsDC.py

@@ -0,0 +1,148 @@
+import SimPEG
+from SimPEG.Utils import Identity, Zero
+import numpy as np
+from scipy.constants import epsilon_0
+
+class Fields(SimPEG.Problem.Fields):
+    knownFields = {}
+    dtype = float
+
+    def _phiDeriv(self, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_phiDeriv_u', None) is None or getattr(self, '_phiDeriv_m', None) is None:
+            raise NotImplementedError ('Getting phiDerivs from %s is not implemented' %self.knownFields.keys()[0])
+
+        if adjoint:
+            return self._phiDeriv_u(src, v, adjoint=adjoint), self._phiDeriv_m(src, v, adjoint=adjoint)
+
+        return np.array(self._phiDeriv_u(src, du_dm_v, adjoint) + self._phiDeriv_m(src, v, adjoint), dtype = float)
+
+    def _eDeriv(self, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_eDeriv_u', None) is None or getattr(self, '_eDeriv_m', None) is None:
+            raise NotImplementedError ('Getting eDerivs from %s is not implemented' %self.knownFields.keys()[0])
+
+        if adjoint:
+            return self._eDeriv_u(src, v, adjoint), self._eDeriv_m(src, v, adjoint)
+        return np.array(self._eDeriv_u(src, du_dm_v, adjoint) + self._eDeriv_m(src, v, adjoint), dtype = float)
+
+    def _jDeriv(self, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_jDeriv_u', None) is None or getattr(self, '_jDeriv_m', None) is None:
+            raise NotImplementedError ('Getting jDerivs from %s is not implemented' %self.knownFields.keys()[0])
+
+        if adjoint:
+            return self._jDeriv_u(src, v, adjoint), self._jDeriv_m(src, v, adjoint)
+        return np.array(self._jDeriv_u(src, du_dm_v, adjoint) + self._jDeriv_m(src, v, adjoint), dtype = float)
+
+
+class Fields_CC(Fields):
+    knownFields = {'phiSolution':'CC'}
+    aliasFields = {
+                    'phi': ['phiSolution','CC','_phi'],
+                    'j' : ['phiSolution','F','_j'],
+                    'e' : ['phiSolution','F','_e'],
+                    'charge' : ['phiSolution','CC','_charge'],
+                  }
+                  # primary - secondary
+                  # CC variables
+
+    def __init__(self, mesh, survey, **kwargs):
+        Fields.__init__(self, mesh, survey, **kwargs)
+        mesh.setCellGradBC("neumann")
+        cellGrad = mesh.cellGrad
+    def startup(self):
+        self.prob = self.survey.prob
+
+    def _GLoc(self, fieldType):
+        if fieldType == 'phi':
+            return 'CC'
+        elif fieldType == 'e' or fieldType == 'j':
+            return 'F'
+        else:
+            raise Exception('Field type must be phi, e, j')
+
+    def _phi(self, phiSolution, srcList):
+        return phiSolution
+
+    def _phiDeriv_u(self, src, v, adjoint = False):
+        return Identity()*v
+
+    def _phiDeriv_m(self, src, v, adjoint = False):
+        return Zero()
+
+    def _j(self, phiSolution, srcList):
+        """
+            .. math::
+                \mathbf{j} = \mathbf{M}^{f \ -1}_{\rho} \mathbf{G} \phi
+        """
+        return self.prob.MfRhoI*self.prob.Grad*phiSolution
+
+    def _e(self, phiSolution, srcList):
+        """
+            In HJ formulation e is not well-defined!!
+            .. math::
+                \vec{e} = -\nabla \phi
+        """
+        return -self.mesh.cellGrad*phiSolution
+
+    def _charge(self, phiSolution, srcList):
+        """
+            .. math::
+                \int \nabla \codt \vec{e} =  \int \frac{\rho_v }{\epsillon_0}
+        """
+        return epsilon_0*self.prob.Vol*(self.mesh.faceDiv*self._e(phiSolution, srcList))
+
+class Fields_N(Fields):
+    knownFields = {'phiSolution':'N'}
+    aliasFields = {
+                    'phi': ['phiSolution','N','_phi'],
+                    'j' : ['phiSolution','E','_j'],
+                    'e' : ['phiSolution','E','_e'],
+                    'charge' : ['phiSolution','N','_charge'],
+                  }
+                  # primary - secondary
+                  # N variables
+
+    def __init__(self, mesh, survey, **kwargs):
+        Fields.__init__(self, mesh, survey, **kwargs)
+
+    def startup(self):
+        self.prob = self.survey.prob
+
+    def _GLoc(self, fieldType):
+        if fieldType == 'phi':
+            return 'N'
+        elif fieldType == 'e' or fieldType == 'j':
+            return 'E'
+        else:
+            raise Exception('Field type must be phi, e, j')
+
+    def _phi(self, phiSolution, srcList):
+        return phiSolution
+
+    def _phiDeriv_u(self, src, v, adjoint = False):
+        return Identity()*v
+
+    def _phiDeriv_m(self, src, v, adjoint = False):
+        return Zero()
+
+    def _j(self, phiSolution, srcList):
+        """
+            In EB formulation j is not well-defined!!
+            .. math::
+                \mathbf{j} = - \mathbf{M}^{e}_{\sigma} \mathbf{G} \phi
+        """
+        return self.prob.MeSigma * self._e(phiSolution, srcList)
+
+    def _e(self, phiSolution, srcList):
+        """
+            In HJ formulation e is not well-defined!!
+            .. math::
+                \vec{e} = -\nabla \phi
+        """
+        return -self.mesh.nodalGrad * phiSolution
+
+    def _charge(self, phiSolution, srcList):
+        """
+            .. math::
+                \int \nabla \codt \vec{e} =  \int \frac{\rho_v }{\epsillon_0}
+        """
+        return - epsilon_0*(self.mesh.nodalGrad.T*self.mesh.getEdgeInnerProduct()*self._e(phiSolution, srcList))

SimPEG/EM/Static/DC/FieldsDC_2D.py

@@ -0,0 +1,146 @@
+import SimPEG
+from SimPEG.Utils import Identity, Zero
+import numpy as np
+
+class Fields_ky(SimPEG.Problem.TimeFields):
+
+    """
+
+    Fancy Field Storage for a 2.5D code.
+
+    u[:,'phi', kyInd] = phi
+    print u[src0,'phi']
+
+    Only one field type is stored for
+    each problem, the rest are computed. The fields obejct acts like an array and is indexed by
+    .. code-block:: python
+        f = problem.fields(m)
+        e = f[srcList,'e']
+        j = f[srcList,'j']
+
+    If accessing all sources for a given field, use the :code:`:`
+    .. code-block:: python
+        f = problem.fields(m)
+        phi = f[:,'phi']
+        e = f[:,'e']
+        b = f[:,'b']
+    The array returned will be size (nE or nF, nSrcs :math:`\\times` nFrequencies)
+    """
+
+    knownFields = {}
+    dtype = float
+
+    def _phiDeriv(self,kyInd, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_phiDeriv_u', None) is None or getattr(self, '_phiDeriv_m', None) is None:
+            raise NotImplementedError ('Getting phiDerivs from %s is not implemented' %self.knownFields.keys()[0])
+
+        if adjoint:
+            return self._phiDeriv_u(kyInd, src, v, adjoint=adjoint), self._phiDeriv_m(kyInd, src, v, adjoint=adjoint)
+
+        return np.array(self._phiDeriv_u(kyInd, src, du_dm_v, adjoint) + self._phiDeriv_m(kyInd, src, v, adjoint), dtype = float)
+
+    def _eDeriv(self,kyInd, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_eDeriv_u', None) is None or getattr(self, '_eDeriv_m', None) is None:
+            raise NotImplementedError ('Getting eDerivs from %s is not implemented' %self.knownFields.keys()[0])
+
+        if adjoint:
+            return self._eDeriv_u(kyInd, src, v, adjoint), self._eDeriv_m(kyInd, src, v, adjoint)
+        return np.array(self._eDeriv_u(kyInd, src, du_dm_v, adjoint) + self._eDeriv_m(kyInd, src, v, adjoint), dtype = float)
+
+    def _jDeriv(self,kyInd, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_jDeriv_u', None) is None or getattr(self, '_jDeriv_m', None) is None:
+            raise NotImplementedError ('Getting jDerivs from %s is not implemented' %self.knownFields.keys()[0])
+
+        if adjoint:
+            return self._jDeriv_u(kyInd, src, v, adjoint), self._jDeriv_m(kyInd, src, v, adjoint)
+        return np.array(self._jDeriv_u(kyInd, src, du_dm_v, adjoint) + self._jDeriv_m(kyInd, src, v, adjoint), dtype = float)
+
+
+    # def _eDeriv(self, tInd, src, dun_dm_v, v, adjoint=False):
+    #     if adjoint is True:
+    #         return self._eDeriv_u(tInd, src, v, adjoint), self._eDeriv_m(tInd, src, v, adjoint)
+    #     return self._eDeriv_u(tInd, src, dun_dm_v) + self._eDeriv_m(tInd, src, v)
+
+    # def _bDeriv(self, tInd, src, dun_dm_v, v, adjoint=False):
+    #     if adjoint is True:
+    #         return self._bDeriv_u(tInd, src, v, adjoint), self._bDeriv_m(tInd, src, v, adjoint)
+    #     return self._bDeriv_u(tInd, src, dun_dm_v) + self._bDeriv_m(tInd, src, v)
+
+
+class Fields_ky_CC(Fields_ky):
+    knownFields = {'phiSolution':'CC'}
+    aliasFields = {
+                    'phi': ['phiSolution','CC','_phi'],
+                    'j' : ['phiSolution','F','_j'],
+                    'e' : ['phiSolution','F','_e'],
+                  }
+                  # primary - secondary
+                  # CC variables
+
+    def __init__(self, mesh, survey, **kwargs):
+        Fields_ky.__init__(self, mesh, survey, **kwargs)
+
+    def startup(self):
+        self.prob = self.survey.prob
+
+    def _GLoc(self, fieldType):
+        if fieldType == 'phi':
+            return 'CC'
+        elif fieldType == 'e' or fieldType == 'j':
+            return 'F'
+        else:
+            raise Exception('Field type must be phi, e, j')
+
+    def _phi(self, phiSolution, src, kyInd):
+        return phiSolution
+
+    def _phiDeriv_u(self, kyInd, src, v, adjoint = False):
+        return Identity()*v
+
+    def _phiDeriv_m(self, kyInd, src, v, adjoint = False):
+        return Zero()
+
+    def _j(self, phiSolution, srcList):
+        raise NotImplementedError
+
+    def _e(self, phiSolution, srcList):
+        raise NotImplementedError
+
+class Fields_ky_N(Fields_ky):
+    knownFields = {'phiSolution':'N'}
+    aliasFields = {
+                    'phi': ['phiSolution','N','_phi'],
+                    'j' : ['phiSolution','E','_j'],
+                    'e' : ['phiSolution','E','_e'],
+                  }
+                  # primary - secondary
+                  # CC variables
+
+    def __init__(self, mesh, survey, **kwargs):
+        Fields_ky.__init__(self, mesh, survey, **kwargs)
+
+    def startup(self):
+        self.prob = self.survey.prob
+
+    def _GLoc(self, fieldType):
+        if fieldType == 'phi':
+            return 'N'
+        elif fieldType == 'e' or fieldType == 'j':
+            return 'E'
+        else:
+            raise Exception('Field type must be phi, e, j')
+
+    def _phi(self, phiSolution, src, kyInd):
+        return phiSolution
+
+    def _phiDeriv_u(self, kyInd, src, v, adjoint = False):
+        return Identity()*v
+
+    def _phiDeriv_m(self, kyInd, src, v, adjoint = False):
+        return Zero()
+
+    def _j(self, phiSolution, srcList):
+        raise NotImplementedError
+
+    def _e(self, phiSolution, srcList):
+        raise NotImplementedError

SimPEG/EM/Static/DC/ProblemDC.py

@@ -0,0 +1,307 @@
+from SimPEG import Problem, Utils
+from SimPEG.EM.Base import BaseEMProblem
+from SurveyDC import Survey
+from FieldsDC import Fields, Fields_CC, Fields_N
+from SimPEG.Utils import sdiag
+import numpy as np
+from SimPEG.Utils import Zero
+from BoundaryUtils import getxBCyBC_CC
+
+class BaseDCProblem(BaseEMProblem):
+
+    surveyPair = Survey
+    fieldsPair = Fields
+    Ainv = None
+
+    def fields(self, m):
+        self.curModel = m
+
+        if not self.Ainv == None:
+            self.Ainv.clean()
+
+        f = self.fieldsPair(self.mesh, self.survey)
+        A = self.getA()
+        self.Ainv = self.Solver(A, **self.solverOpts)
+        RHS = self.getRHS()
+        u = self.Ainv * RHS
+        Srcs = self.survey.srcList
+        f[Srcs, self._solutionType] = u
+        return f
+
+    def Jvec(self, m, v, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        Jv = self.dataPair(self.survey) #same size as the data
+
+        A = self.getA()
+
+        for src in self.survey.srcList:
+            u_src = f[src, self._solutionType] # solution vector
+            dA_dm_v = self.getADeriv(u_src, v)
+            dRHS_dm_v = self.getRHSDeriv(src, v)
+            du_dm_v = self.Ainv * ( - dA_dm_v + dRHS_dm_v )
+
+            for rx in src.rxList:
+                df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False)
+                Jv[src, rx] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
+        return Utils.mkvc(Jv)
+
+    def Jtvec(self, m, v, f=None):
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        # Ensure v is a data object.
+        if not isinstance(v, self.dataPair):
+            v = self.dataPair(self.survey, v)
+
+        Jtv = np.zeros(m.size)
+        AT = self.getA()
+
+
+        for src in self.survey.srcList:
+            u_src = f[src, self._solutionType]
+            for rx in src.rxList:
+                PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx], adjoint=True) # wrt f, need possibility wrt m
+                df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
+
+                ATinvdf_duT = self.Ainv * df_duT
+
+                dA_dmT = self.getADeriv(u_src, ATinvdf_duT, adjoint=True)
+                dRHS_dmT = self.getRHSDeriv(src, ATinvdf_duT, adjoint=True)
+                du_dmT = -dA_dmT + dRHS_dmT
+                Jtv += (df_dmT + du_dmT).astype(float)
+
+        return Utils.mkvc(Jtv)
+
+    def getSourceTerm(self):
+        """
+        takes concept of source and turns it into a matrix
+        """
+        """
+        Evaluates the sources, and puts them in matrix form
+
+        :rtype: (numpy.ndarray, numpy.ndarray)
+        :return: q (nC or nN, nSrc)
+        """
+
+        Srcs = self.survey.srcList
+
+        if self._formulation is 'EB':
+            n = self.mesh.nN
+            # return NotImplementedError
+
+        elif self._formulation is 'HJ':
+            n = self.mesh.nC
+
+        q = np.zeros((n, len(Srcs)))
+
+        for i, src in enumerate(Srcs):
+            q[:,i] = src.eval(self)
+        return q
+
+class Problem3D_CC(BaseDCProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'HJ' # CC potentials means J is on faces
+    fieldsPair    = Fields_CC
+
+    def __init__(self, mesh, **kwargs):
+        BaseDCProblem.__init__(self, mesh, **kwargs)
+        self.setBC()
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI D^\\top V
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        # TODO: this won't work for full anisotropy
+        MfRhoI = self.MfRhoI
+        A = D * MfRhoI * G
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * A
+        return A
+
+    def getADeriv(self, u, v, adjoint= False):
+
+        D = self.Div
+        G = self.Grad
+        MfRhoIDeriv = self.MfRhoIDeriv
+
+        if adjoint:
+            # if self._makeASymmetric is True:
+            #     v = V * v
+            return(MfRhoIDeriv( G * u ).T) * ( D.T * v)
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * ( D * ( MfRhoIDeriv( D.T * ( V * u ) ) * v ) )
+        return D * (MfRhoIDeriv( G * u ) * v)
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return self.Vol.T * RHS
+
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+    def setBC(self):
+        if self.mesh.dim==3:
+            fxm,fxp,fym,fyp,fzm,fzp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+            gBFzm = self.mesh.gridFz[fzm,:]
+            gBFzp = self.mesh.gridFz[fzp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+            temp_zm, temp_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+            alpha_zm, alpha_zp = temp_zm*0., temp_zp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+            beta_zm, beta_zp = temp_zm, temp_zp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+            gamma_zm, gamma_zp = temp_zm*0., temp_zp*0.
+
+            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]
+
+        elif self.mesh.dim==2:
+
+            fxm,fxp,fym,fyp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+
+            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_CC(self.mesh, alpha, beta, gamma)
+        V = self.Vol
+        self.Div = V * self.mesh.faceDiv
+        P_BC, B = self.mesh.getBCProjWF_simple()
+        M = B*self.mesh.aveCC2F
+        self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M
+
+
+class Problem3D_N(BaseDCProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'EB' # N potentials means B is on faces
+    fieldsPair    = Fields_N
+
+    def __init__(self, mesh, **kwargs):
+        BaseDCProblem.__init__(self, mesh, **kwargs)
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI D^\\top V
+
+        """
+
+        # TODO: this won't work for full anisotropy
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        A = Grad.T * MeSigma * Grad
+
+        # Handling Null space of A
+        A[0,0] = A[0,0] + 1.
+
+        return A
+
+    def getADeriv(self, u, v, adjoint=False):
+        """
+
+        Product of the derivative of our system matrix with respect to the model and a vector
+
+        """
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        if not adjoint:
+            return Grad.T*(self.MeSigmaDeriv(Grad*u)*v)
+        elif adjoint:
+            return self.MeSigmaDeriv(Grad*u).T * (Grad*v)
+
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+
+
+

SimPEG/EM/Static/DC/ProblemDC_2D.py

@@ -0,0 +1,351 @@
+from SimPEG import Problem, Utils
+from SimPEG.EM.Base import BaseEMProblem
+from SurveyDC import Survey, Survey_ky
+from FieldsDC_2D import Fields_ky, Fields_ky_CC, Fields_ky_N
+from SimPEG.Utils import sdiag
+import numpy as np
+from SimPEG.Utils import Zero
+from BoundaryUtils import getxBCyBC_CC
+
+class BaseDCProblem_2D(BaseEMProblem):
+
+    surveyPair = Survey_ky
+    fieldsPair = Fields_ky
+    nky = 15
+    kys = np.logspace(-4, 1, nky)
+    Ainv = [None for i in range(nky)]
+    nT = nky # Only for using TimeFields
+
+    def fields(self, m):
+        self.curModel = m
+
+        if not self.Ainv[0] == None:
+            for i in range(self.nky):
+                self.Ainv[i].clean()
+
+        f = self.fieldsPair(self.mesh, self.survey)
+        Srcs = self.survey.srcList
+        for iky in range(self.nky):
+            ky = self.kys[iky]
+            A = self.getA(ky)
+            self.Ainv[iky] = self.Solver(A, **self.solverOpts)
+            RHS = self.getRHS(ky)
+            u = self.Ainv[iky] * RHS
+            f[Srcs, self._solutionType, iky] = u
+        return f
+
+    def Jvec(self, m, v, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        Jv = self.dataPair(self.survey) #same size as the data
+        Jv0 = self.dataPair(self.survey)
+
+        # Assume y=0.
+        # This needs some thoughts to implement in general when src is dipole
+        dky = np.diff(self.kys)
+        dky = np.r_[dky[0], dky]
+        y = 0.
+
+        #TODO: this loop is pretty slow .. (Parellize)
+        for iky in range(self.nky):
+            ky = self.kys[iky]
+            A = self.getA(ky)
+            for src in self.survey.srcList:
+                u_src = f[src, self._solutionType, iky] # solution vector
+                dA_dm_v = self.getADeriv(ky, u_src, v)
+                dRHS_dm_v = self.getRHSDeriv(ky, src, v)
+                du_dm_v = self.Ainv[iky] * ( - dA_dm_v + dRHS_dm_v )
+                for rx in src.rxList:
+                    df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                    df_dm_v = df_dmFun(iky, src, du_dm_v, v, adjoint=False)
+                    # Trapezoidal intergration
+                    Jv1_temp = 1./np.pi*rx.evalDeriv(ky, src, self.mesh, f, df_dm_v)
+                    if iky==0:
+                        #First assigment
+                        Jv[src, rx] = Jv1_temp*dky[iky]*np.cos(ky*y)
+                    else:
+                        Jv[src, rx] += Jv1_temp*dky[iky]    /2.*np.cos(ky*y)
+                        Jv[src, rx] += Jv0[src, rx]*dky[iky]/2.*np.cos(ky*y)
+                    Jv0[src, rx] = Jv1_temp.copy()
+        return Utils.mkvc(Jv)
+
+    def Jtvec(self, m, v, f=None):
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        # Ensure v is a data object.
+        if not isinstance(v, self.dataPair):
+            v = self.dataPair(self.survey, v)
+
+        Jtv = np.zeros(m.size, dtype=float)
+
+        # Assume y=0.
+        # This needs some thoughts to implement in general when src is dipole
+        dky = np.diff(self.kys)
+        dky = np.r_[dky[0], dky]
+        y = 0.
+
+        for src in self.survey.srcList:
+            for rx in src.rxList:
+                Jtv_temp1 = np.zeros(m.size, dtype=float)
+                Jtv_temp0 = np.zeros(m.size, dtype=float)
+                #TODO: this loop is pretty slow .. (Parellize)
+                for iky in range(self.nky):
+                    u_src = f[src, self._solutionType, iky]
+                    ky = self.kys[iky]
+                    AT = self.getA(ky)
+                    PTv = rx.evalDeriv(ky, src, self.mesh, f, v[src, rx], adjoint=True) # wrt f, need possibility wrt m
+                    df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                    df_duT, df_dmT = df_duTFun(iky, src, None, PTv, adjoint=True)
+
+                    ATinvdf_duT = self.Ainv[iky] * df_duT
+
+                    dA_dmT = self.getADeriv(ky, u_src, ATinvdf_duT, adjoint=True)
+                    dRHS_dmT = self.getRHSDeriv(ky, src, ATinvdf_duT, adjoint=True)
+                    du_dmT = -dA_dmT + dRHS_dmT
+                    Jtv_temp1 = 1./np.pi*(df_dmT + du_dmT).astype(float)
+                    # Trapezoidal intergration
+                    if iky==0:
+                        #First assigment
+                        Jtv += Jtv_temp1*dky[iky]*np.cos(ky*y)
+                    else:
+                        Jtv += Jtv_temp1*dky[iky]/2.*np.cos(ky*y)
+                        Jtv += Jtv_temp0*dky[iky]/2.*np.cos(ky*y)
+                    Jtv_temp0 = Jtv_temp1.copy()
+        return Utils.mkvc(Jtv)
+
+    def getSourceTerm(self, ky):
+        """
+        takes concept of source and turns it into a matrix
+        """
+        """
+        Evaluates the sources, and puts them in matrix form
+
+        :rtype: (numpy.ndarray, numpy.ndarray)
+        :return: q (nC or nN, nSrc)
+        """
+
+        Srcs = self.survey.srcList
+
+        if self._formulation is 'EB':
+            n = self.mesh.nN
+            # return NotImplementedError
+
+        elif self._formulation is 'HJ':
+            n = self.mesh.nC
+
+        q = np.zeros((n, len(Srcs)))
+
+        for i, src in enumerate(Srcs):
+            q[:,i] = src.eval(self)
+        return q
+
+class Problem2D_CC(BaseDCProblem_2D):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'HJ' # CC potentials means J is on faces
+    fieldsPair    = Fields_ky_CC
+
+    def __init__(self, mesh, **kwargs):
+        BaseDCProblem_2D.__init__(self, mesh, **kwargs)
+        self.setBC()
+
+    def getA(self, ky):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI D^\\top V
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        vol = self.mesh.vol
+        # TODO: this won't work for full anisotropy
+        MfRhoI = self.MfRhoI
+        # Get resistivity rho
+        rho = self.curModel.rho
+        A = D * MfRhoI * G + Utils.sdiag(ky**2*vol/rho)
+        return A
+
+    def getADeriv(self, ky, u, v, adjoint= False):
+
+        D = self.Div
+        G = self.Grad
+        vol = self.mesh.vol
+        MfRhoIDeriv = self.MfRhoIDeriv
+        rho = self.curModel.rho
+        if adjoint:
+            return(MfRhoIDeriv( G * u ).T) * ( D.T * v) + ky**2*Utils.sdiag(u.flatten()*vol*(-1./rho**2))*v
+        return D * ((MfRhoIDeriv( G * u )) * v) + ky**2*Utils.sdiag(u.flatten()*vol*(-1./rho**2))*v
+
+    def getRHS(self, ky):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm(ky)
+        return RHS
+
+    def getRHSDeriv(self, ky, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, ky, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+    def setBC(self):
+        if self.mesh.dim==3:
+            fxm,fxp,fym,fyp,fzm,fzp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+            gBFzm = self.mesh.gridFz[fzm,:]
+            gBFzp = self.mesh.gridFz[fzp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+            temp_zm, temp_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+            alpha_zm, alpha_zp = temp_zm*0., temp_zp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+            beta_zm, beta_zp = temp_zm, temp_zp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+            gamma_zm, gamma_zp = temp_zm*0., temp_zp*0.
+
+            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]
+
+        elif self.mesh.dim==2:
+
+            fxm,fxp,fym,fyp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+
+            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_CC(self.mesh, alpha, beta, gamma)
+        V = self.Vol
+        self.Div = V * self.mesh.faceDiv
+        P_BC, B = self.mesh.getBCProjWF_simple()
+        M = B*self.mesh.aveCC2F
+        self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M
+
+class Problem2D_N(BaseDCProblem_2D):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'EB' # CC potentials means J is on faces
+    fieldsPair    = Fields_ky_N
+
+    def __init__(self, mesh, **kwargs):
+        BaseDCProblem_2D.__init__(self, mesh, **kwargs)
+        # self.setBC()
+
+    @property
+    def MnSigma(self):
+        """
+            Node inner product matrix for \\(\\sigma\\). Used in the E-B formulation
+        """
+        # TODO: only works isotropic sigma
+        sigma = self.curModel.sigma
+        vol = self.mesh.vol
+        MnSigma = Utils.sdiag(self.mesh.aveN2CC.T*(Utils.sdiag(vol)*sigma))
+
+        return MnSigma
+
+    def MnSigmaDeriv(self, u):
+        """
+            Derivative of MnSigma with respect to the model
+        """
+        sigma = self.curModel.sigma
+        sigmaderiv = self.curModel.sigmaDeriv
+        vol = self.mesh.vol
+        return Utils.sdiag(u)*self.mesh.aveN2CC.T*Utils.sdiag(vol) * self.curModel.sigmaDeriv
+
+    def getA(self, ky):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI D^\\top V
+
+        """
+
+        # TODO: this won't work for full anisotropy
+        MeSigma = self.MeSigma
+        MnSigma = self.MnSigma
+        Grad = self.mesh.nodalGrad
+        # Get conductivity sigma
+        sigma = self.curModel.sigma
+        A = Grad.T * MeSigma * Grad + ky**2*MnSigma
+
+        # Handling Null space of A
+        A[0,0] = A[0,0] + 1.
+        return A
+
+    def getADeriv(self, ky, u, v, adjoint= False):
+
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        sigma = self.curModel.sigma
+        vol = self.mesh.vol
+
+        if adjoint:
+            return self.MeSigmaDeriv(Grad*u).T * (Grad*v) + ky**2*self.MnSigmaDeriv(u).T*v
+        return Grad.T*(self.MeSigmaDeriv(Grad*u)*v) + ky**2*self.MnSigmaDeriv(u)*v
+
+    def getRHS(self, ky):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm(ky)
+        return RHS
+
+    def getRHSDeriv(self, ky, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, ky, adjoint=adjoint)
+        # return qDeriv
+        return Zero()

SimPEG/EM/Static/DC/RxDC.py

@@ -0,0 +1,129 @@
+import SimPEG
+import numpy as np
+from SimPEG.Utils import Zero, closestPoints
+
+class BaseRx(SimPEG.Survey.BaseRx):
+    locs = None
+    rxType = None
+
+    knownRxTypes = {
+                    'phi':['phi',None],
+                    'ex':['e','x'],
+                    'ey':['e','y'],
+                    'ez':['e','z'],
+                    'jx':['j','x'],
+                    'jy':['j','y'],
+                    'jz':['j','z'],
+                    }
+
+    def __init__(self, locs, rxType, **kwargs):
+        SimPEG.Survey.BaseRx.__init__(self, locs, rxType, **kwargs)
+
+
+    @property
+    def projField(self):
+        """Field Type projection (e.g. e b ...)"""
+        return self.knownRxTypes[self.rxType][0]
+
+    def projGLoc(self, f):
+        """Grid Location projection (e.g. Ex Fy ...)"""
+        comp = self.knownRxTypes[self.rxType][1]
+        if comp is not None:
+            return f._GLoc(self.rxType) + comp
+        return f._GLoc(self.rxType)
+
+    def eval(self, src, mesh, f):
+        P = self.getP(mesh, self.projGLoc(f))
+        return P*f[src, self.projField]
+
+    def evalDeriv(self, src, mesh, f, v, adjoint=False):
+        P = self.getP(mesh, self.projGLoc(f))
+        if not adjoint:
+            return P*v
+        elif adjoint:
+            return P.T*v
+
+# DC.Rx.Dipole(locs)
+class Dipole(BaseRx):
+
+    def __init__(self, locsM, locsN, rxType = 'phi', **kwargs):
+        assert locsM.shape == locsN.shape, 'locsM and locsN need to be the same size'
+        locs = [locsM, locsN]
+        # We may not need this ...
+        BaseRx.__init__(self, locs, rxType)
+
+    @property
+    def nD(self):
+        """Number of data in the receiver."""
+        return self.locs[0].shape[0]
+
+        # Not sure why ...
+        # return int(self.locs[0].size / 2)
+
+
+    def getP(self, mesh, Gloc):
+        if mesh in self._Ps:
+            return self._Ps[mesh]
+
+        P0 = mesh.getInterpolationMat(self.locs[0], Gloc)
+        P1 = mesh.getInterpolationMat(self.locs[1], Gloc)
+        P = P0 - P1
+
+        if self.storeProjections:
+            self._Ps[mesh] = P
+
+        return P
+
+
+class Dipole_ky(BaseRx):
+
+    def __init__(self, locsM, locsN, rxType = 'phi', **kwargs):
+        assert locsM.shape == locsN.shape, 'locsM and locsN need to be the same size'
+        locs = [locsM, locsN]
+        # We may not need this ...
+        BaseRx.__init__(self, locs, rxType)
+
+    @property
+    def nD(self):
+        """Number of data in the receiver."""
+        return self.locs[0].shape[0]
+
+        # Not sure why ...
+        # return int(self.locs[0].size / 2)
+
+    def getP(self, mesh, Gloc):
+        if mesh in self._Ps:
+            return self._Ps[mesh]
+
+        P0 = mesh.getInterpolationMat(self.locs[0], Gloc)
+        P1 = mesh.getInterpolationMat(self.locs[1], Gloc)
+        P = P0 - P1
+        if self.storeProjections:
+            self._Ps[mesh] = P
+        return P
+
+    def eval(self, kys, src, mesh, f):
+        P = self.getP(mesh, self.projGLoc(f))
+        Pf = P*f[src, self.projField,:]
+        return self.IntTrapezoidal(kys, Pf, y=0.)
+
+    def evalDeriv(self, ky, src, mesh, f, v, adjoint=False):
+        P = self.getP(mesh, self.projGLoc(f))
+        if not adjoint:
+            return P*v
+        elif adjoint:
+            return P.T*v
+
+    def IntTrapezoidal(self, kys, Pf, y=0.):
+        phi = np.zeros(Pf.shape[0])
+        nky = kys.size
+        dky = np.diff(kys)
+        dky = np.r_[dky[0], dky]
+        phi0 = 1./np.pi*Pf[:,0]
+        for iky in range(nky):
+            phi1 = 1./np.pi*Pf[:,iky]
+            phi += phi1*dky[iky]/2.*np.cos(kys[iky]*y)
+            phi += phi0*dky[iky]/2.*np.cos(kys[iky]*y)
+            phi0 = phi1.copy()
+        return phi
+

SimPEG/EM/Static/DC/SrcDC.py

@@ -0,0 +1,86 @@
+import SimPEG
+# from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG.Utils import Zero, closestPoints, mkvc
+import numpy as np
+
+class BaseSrc(SimPEG.Survey.BaseSrc):
+
+    current = 1.0
+    loc = None
+
+    def __init__(self, rxList, **kwargs):
+        SimPEG.Survey.BaseSrc.__init__(self, rxList, **kwargs)
+
+    def eval(self, prob):
+        raise NotImplementedError
+
+    def evalDeriv(self, prob):
+        return Zero()
+
+
+class Dipole(BaseSrc):
+
+    def __init__(self, rxList, locA, locB, **kwargs):
+        assert locA.shape == locB.shape, 'Shape of locA and locB should be the same'
+        self.loc = [locA, locB]
+        BaseSrc.__init__(self, rxList, **kwargs)
+
+    def eval(self, prob):
+        if prob._formulation == 'HJ':
+            inds = closestPoints(prob.mesh, self.loc, gridLoc='CC')
+            q = np.zeros(prob.mesh.nC)
+            q[inds] = self.current * np.r_[1., -1.]
+        elif prob._formulation == 'EB':
+            qa = prob.mesh.getInterpolationMat(self.loc[0], locType='N').todense()
+            qb = -prob.mesh.getInterpolationMat(self.loc[1], locType='N').todense()
+            q = self.current * mkvc(qa+qb)
+        return q
+
+class Pole(BaseSrc):
+
+    def __init__(self, rxList, loc, **kwargs):
+        BaseSrc.__init__(self, rxList, loc=loc, **kwargs)
+
+    def eval(self, prob):
+        if prob._formulation == 'HJ':
+            inds = closestPoints(prob.mesh, self.loc)
+            q = np.zeros(prob.mesh.nC)
+            q[inds] = self.current * np.r_[1.]
+        elif prob._formulation == 'EB':
+            q = prob.mesh.getInterpolationMat(self.loc, locType='N').todense()
+            q = self.current * mkvc(q)
+        return q
+
+
+# class Dipole_ky(BaseSrc):
+
+#     def __init__(self, rxList, locA, locB, **kwargs):
+#         assert locA.shape == locB.shape, 'Shape of locA and locB should be the same'
+#         self.loc = [locA[[0,2]], locB[[0,2]]]
+#         BaseSrc.__init__(self, rxList, **kwargs)
+
+#     def eval(self, prob):
+#         if prob._formulation == 'HJ':
+#             inds = closestPoints(prob.mesh, self.loc, gridLoc='CC')
+#             q = np.zeros(prob.mesh.nC)
+#             q[inds] = self.current * np.r_[1., -1.]
+#         elif prob._formulation == 'EB':
+#             qa = prob.mesh.getInterpolationMat(self.loc[0], locType='N').todense()
+#             qb = -prob.mesh.getInterpolationMat(self.loc[1], locType='N').todense()
+#             q = self.current * mkvc(qa+qb)
+#         return q
+
+# class Pole_ky(BaseSrc):
+
+#     def __init__(self, rxList, loc, **kwargs):
+#         BaseSrc.__init__(self, rxList, loc=loc, **kwargs)
+
+#     def eval(self, prob):
+#         if prob._formulation == 'HJ':
+#             inds = closestPoints(prob.mesh, self.loc[[0,2]])
+#             q = np.zeros(prob.mesh.nC)
+#             q[inds] = self.current * np.r_[1.]
+#         elif prob._formulation == 'EB':
+#             q = prob.mesh.getInterpolationMat(self.loc[[0,2]], locType='N').todense()
+#             q = self.current * mkvc(q)
+#         return q

SimPEG/EM/Static/DC/SurveyDC.py

@@ -0,0 +1,38 @@
+import SimPEG
+from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG import sp, Survey
+from SimPEG.Utils import Zero, Identity
+from RxDC import BaseRx
+from SrcDC import BaseSrc
+
+class Survey(BaseEMSurvey):
+    rxPair  = BaseRx
+    srcPair = BaseSrc
+
+    def __init__(self, srcList, **kwargs):
+        self.srcList = srcList
+        BaseEMSurvey.__init__(self, srcList, **kwargs)
+
+class Survey_ky(BaseEMSurvey):
+    rxPair  = BaseRx
+    srcPair = BaseSrc
+
+    def __init__(self, srcList, **kwargs):
+        self.srcList = srcList
+        BaseEMSurvey.__init__(self, srcList, **kwargs)
+
+    def eval(self, f):
+        """
+        Project fields to receiver locations
+        :param Fields u: fields object
+        :rtype: numpy.ndarray
+        :return: data
+        """
+        data = SimPEG.Survey.Data(self)
+        kys = self.prob.kys
+        for src in self.srcList:
+            for rx in src.rxList:
+                data[src, rx] = rx.eval(kys, src, self.mesh, f)
+        return data
+
+

SimPEG/EM/Static/DC/Utils.py

@@ -0,0 +1,38 @@
+import numpy as np
+
+def WennerSrcList(nElecs, aSpacing, in2D=False, plotIt=False):
+
+    import SimPEG.EM.Static.DC as DC
+
+    elocs = np.arange(0,aSpacing*nElecs,aSpacing)
+    elocs -= (nElecs*aSpacing - aSpacing)/2
+    space = 1
+    WENNER = np.zeros((0,),dtype=int)
+    for ii in range(nElecs):
+        for jj in range(nElecs):
+            test = np.r_[jj,jj+space,jj+space*2,jj+space*3]
+            if np.any(test >= nElecs):
+                break
+            WENNER = np.r_[WENNER, test]
+        space += 1
+    WENNER = WENNER.reshape((-1,4))
+
+
+    if plotIt:
+        for i, s in enumerate('rbkg'):
+            plt.plot(elocs[WENNER[:,i]],s+'.')
+        plt.show()
+
+    # Create sources and receivers
+    i = 0
+    if in2D:
+        getLoc = lambda ii, abmn: np.r_[elocs[WENNER[ii,abmn]],0]
+    else:
+        getLoc = lambda ii, abmn: np.r_[elocs[WENNER[ii,abmn]],0, 0]
+    srcList = []
+    for i in range(WENNER.shape[0]):
+        rx = DC.Rx.Dipole(getLoc(i,1).reshape([1,-1]),getLoc(i,2).reshape([1,-1]))
+        src = DC.Src.Dipole([rx], getLoc(i,0),getLoc(i,3))
+        srcList += [src]
+
+    return srcList

SimPEG/EM/Static/DC/__init__.py

@@ -0,0 +1,8 @@
+from ProblemDC import Problem3D_CC, Problem3D_N
+from ProblemDC_2D import Problem2D_CC, Problem2D_N
+from SurveyDC import Survey, Survey_ky
+import SrcDC as Src #Pole
+import RxDC as Rx
+from FieldsDC import Fields_CC
+from BoundaryUtils import getxBCyBC_CC
+import Utils

SimPEG/EM/Static/IP/ProblemIP.py

@@ -0,0 +1,374 @@
+from SimPEG import Problem, Utils, Maps, Mesh
+from SimPEG.EM.Base import BaseEMProblem
+from SimPEG.EM.Static.DC.FieldsDC import Fields, Fields_CC, Fields_N
+from SimPEG.Utils import sdiag
+import numpy as np
+from SimPEG.Utils import Zero
+from SimPEG.EM.Static.DC import getxBCyBC_CC
+from SurveyIP import Survey
+
+class IPPropMap(Maps.PropMap):
+    """
+        Property Map for IP Problems. The electrical chargeability,
+        (\\(\\eta\\)) is the default inversion property
+    """
+    eta = Maps.Property("Electrical Chargeability", defaultInvProp = True)
+
+class BaseIPProblem(BaseEMProblem):
+
+    surveyPair = Survey
+    fieldsPair = Fields
+    PropMap = IPPropMap
+    Ainv = None
+    sigma = None
+    rho = None
+    f = None
+    Ainv = None
+
+    def fields(self, m):
+        self.curModel = m
+        if self.f is None:
+            self.f = self.fieldsPair(self.mesh, self.survey)
+            if self.Ainv == None:
+                A = self.getA()
+                self.Ainv = self.Solver(A, **self.solverOpts)
+            RHS = self.getRHS()
+            u = self.Ainv * RHS
+            Srcs = self.survey.srcList
+            self.f[Srcs, self._solutionType] = u
+        return self.f
+
+    def Jvec(self, m, v, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        Jv = self.dataPair(self.survey) #same size as the data
+
+        A = self.getA()
+
+        for src in self.survey.srcList:
+            u_src = f[src, self._solutionType] # solution vector
+            dA_dm_v = self.getADeriv(u_src, v)
+            dRHS_dm_v = self.getRHSDeriv(src, v)
+            du_dm_v = self.Ainv * ( - dA_dm_v + dRHS_dm_v )
+
+            for rx in src.rxList:
+                df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False)
+                Jv[src, rx] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
+        # Conductivity (d u / d log sigma)
+        if self._formulation is 'EB':
+            return -Utils.mkvc(Jv)
+        # Conductivity (d u / d log rho)
+        if self._formulation is 'HJ':
+            return Utils.mkvc(Jv)
+
+    def Jtvec(self, m, v, f=None):
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        # Ensure v is a data object.
+        if not isinstance(v, self.dataPair):
+            v = self.dataPair(self.survey, v)
+
+        Jtv = np.zeros(m.size)
+        AT = self.getA()
+
+        for src in self.survey.srcList:
+            u_src = f[src, self._solutionType]
+            for rx in src.rxList:
+                PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx], adjoint=True) # wrt f, need possibility wrt m
+                df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
+                ATinvdf_duT = self.Ainv * df_duT
+                dA_dmT = self.getADeriv(u_src, ATinvdf_duT, adjoint=True)
+                dRHS_dmT = self.getRHSDeriv(src, ATinvdf_duT, adjoint=True)
+                du_dmT = -dA_dmT + dRHS_dmT
+                Jtv += (df_dmT + du_dmT).astype(float)
+        # Conductivity ((d u / d log sigma).T)
+        if self._formulation is 'EB':
+            return -Utils.mkvc(Jtv)
+        # Conductivity ((d u / d log rho).T)
+        if self._formulation is 'HJ':
+            return Utils.mkvc(Jtv)
+
+    def getSourceTerm(self):
+        """
+        takes concept of source and turns it into a matrix
+        """
+        """
+        Evaluates the sources, and puts them in matrix form
+
+        :rtype: (numpy.ndarray, numpy.ndarray)
+        :return: q (nC or nN, nSrc)
+        """
+
+        Srcs = self.survey.srcList
+
+        if self._formulation is 'EB':
+            n = self.mesh.nN
+            # return NotImplementedError
+
+        elif self._formulation is 'HJ':
+            n = self.mesh.nC
+
+        q = np.zeros((n, len(Srcs)))
+
+        for i, src in enumerate(Srcs):
+            q[:,i] = src.eval(self)
+        return q
+
+    @property
+    def deleteTheseOnModelUpdate(self):
+        toDelete = []
+        return toDelete
+
+    # assume log rho or log cond
+    @property
+    def MeSigma(self):
+        """
+            Edge inner product matrix for \\(\\sigma\\). Used in the E-B formulation
+        """
+        if getattr(self, '_MeSigma', None) is None:
+            self._MeSigma = self.mesh.getEdgeInnerProduct(self.sigma)
+        return self._MeSigma
+
+    @property
+    def MfRhoI(self):
+        """
+            Inverse of :code:`MfRho`
+        """
+        if getattr(self, '_MfRhoI', None) is None:
+            self._MfRhoI = self.mesh.getFaceInnerProduct(self.rho, invMat=True)
+        return self._MfRhoI
+
+    def MfRhoIDeriv(self,u):
+        """
+            Derivative of :code:`MfRhoI` with respect to the model.
+        """
+
+        dMfRhoI_dI = -self.MfRhoI**2
+        dMf_drho = self.mesh.getFaceInnerProductDeriv(self.rho)(u)
+        drho_dlogrho = Utils.sdiag(self.rho)*self.curModel.etaDeriv
+        return dMfRhoI_dI * ( dMf_drho * ( drho_dlogrho))
+
+    # TODO: This should take a vector
+    def MeSigmaDeriv(self, u):
+        """
+            Derivative of MeSigma with respect to the model
+        """
+        dsigma_dlogsigma = Utils.sdiag(self.sigma)*self.curModel.etaDeriv
+        return self.mesh.getEdgeInnerProductDeriv(self.sigma)(u) * dsigma_dlogsigma
+
+class Problem3D_CC(BaseIPProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'HJ' # CC potentials means J is on faces
+    fieldsPair    = Fields_CC
+
+    def __init__(self, mesh, **kwargs):
+        BaseIPProblem.__init__(self, mesh, **kwargs)
+        self.setBC()
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI D^\\top V
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        # TODO: this won't work for full anisotropy
+        MfRhoI = self.MfRhoI
+        A = D * MfRhoI * G
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * A
+        return A
+
+    def getADeriv(self, u, v, adjoint= False):
+
+        D = self.Div
+        G = self.Grad
+        MfRhoIDeriv = self.MfRhoIDeriv
+
+        if adjoint:
+            # if self._makeASymmetric is True:
+            #     v = V * v
+            return(MfRhoIDeriv( G * u ).T) * ( D.T * v)
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * ( D * ( MfRhoIDeriv( D.T * ( V * u ) ) * v ) )
+        return D * (MfRhoIDeriv( G * u ) * v)
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return self.Vol.T * RHS
+
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+    def setBC(self):
+        if self.mesh.dim==3:
+            fxm,fxp,fym,fyp,fzm,fzp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+            gBFzm = self.mesh.gridFz[fzm,:]
+            gBFzp = self.mesh.gridFz[fzp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+            temp_zm, temp_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+            alpha_zm, alpha_zp = temp_zm*0., temp_zp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+            beta_zm, beta_zp = temp_zm, temp_zp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+            gamma_zm, gamma_zp = temp_zm*0., temp_zp*0.
+
+            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]
+
+        elif self.mesh.dim==2:
+
+            fxm,fxp,fym,fyp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+
+            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_CC(self.mesh, alpha, beta, gamma)
+        V = self.Vol
+        self.Div = V * self.mesh.faceDiv
+        P_BC, B = self.mesh.getBCProjWF_simple()
+        M = B*self.mesh.aveCC2F
+        self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M
+
+
+class Problem3D_N(BaseIPProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'EB' # N potentials means B is on faces
+    fieldsPair    = Fields_N
+
+    def __init__(self, mesh, **kwargs):
+        BaseIPProblem.__init__(self, mesh, **kwargs)
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI D^\\top V
+
+        """
+
+        # TODO: this won't work for full anisotropy
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        A = Grad.T * MeSigma * Grad
+
+        # Handling Null space of A
+        A[0,0] = A[0,0] + 1.
+
+        return A
+
+    def getADeriv(self, u, v, adjoint=False):
+        """
+
+        Product of the derivative of our system matrix with respect to the model and a vector
+
+        """
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        if not adjoint:
+            return Grad.T*(self.MeSigmaDeriv(Grad*u)*v)
+        elif adjoint:
+            return self.MeSigmaDeriv(Grad*u).T * (Grad*v)
+
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+if __name__ == '__main__':
+
+
+    cs = 12.5
+    hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
+    hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
+    hz = [(cs,7, -1.3),(cs,20)]
+    mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN")
+    sigma = np.ones(mesh.nC)
+    prob = BaseIPProblem(mesh, sigma=sigma)
+
+

SimPEG/EM/Static/IP/SurveyIP.py

@@ -0,0 +1,23 @@
+import SimPEG
+from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG import sp, Survey
+from SimPEG.Utils import Zero, Identity
+from SimPEG.EM.Static.DC.SrcDC import BaseSrc
+from SimPEG.EM.Static.DC.RxDC import BaseRx
+
+class Survey(BaseEMSurvey):
+    rxPair  = BaseRx
+    srcPair = BaseSrc
+
+    def __init__(self, srcList, **kwargs):
+        self.srcList = srcList
+        BaseEMSurvey.__init__(self, srcList, **kwargs)
+
+    def dpred(self, m, f=None):
+        """
+            Predicted data.
+
+            .. math::
+                d_\\text{pred} = Pf(m)
+        """
+        return self.prob.Jvec(m, m, f=f)

SimPEG/EM/Static/IP/__init__.py

@@ -0,0 +1,2 @@
+from ProblemIP import Problem3D_CC, Problem3D_N
+from SurveyIP import Survey

SimPEG/EM/Static/SIP/ProblemSIP.py

@@ -0,0 +1,445 @@
+from SimPEG import Problem, Utils, Maps, Mesh
+from SimPEG.EM.Base import BaseEMProblem
+from SimPEG.EM.Static.DC.FieldsDC import Fields, Fields_CC, Fields_N
+from SimPEG.Utils import sdiag
+import numpy as np
+from SimPEG.Utils import Zero
+from SimPEG.EM.Static.DC import getxBCyBC_CC
+from SurveySIP import Survey, Data
+
+class ColeColePropMap(Maps.PropMap):
+    """
+        Property Map for EM Problems. The electrical conductivity (\\(\\sigma\\)) is the default inversion property, and the default value of the magnetic permeability is that of free space (\\(\\mu = 4\\pi\\times 10^{-7} \\) H/m)
+    """
+
+    eta = Maps.Property("Electrical Conductivity", defaultInvProp=True)
+    tau = Maps.Property("Electrical Conductivity", defaultVal=0.1, propertyLink=('taui', Maps.ReciprocalMap))
+    taui   = Maps.Property("Electrical Conductivity", defaultVal=1., propertyLink=('tau', Maps.ReciprocalMap))
+    c   = Maps.Property("Electrical Conductivity", defaultVal=1.)
+
+
+class BaseSIPProblem(BaseEMProblem):
+
+    surveyPair = Survey
+    fieldsPair = Fields
+    dataPair = Data
+    PropMap = ColeColePropMap
+    Ainv = None
+    sigma = None
+    rho = None
+    f = None
+    Ainv = None
+
+    def DebyeTime(self, t):
+        peta = self.curModel.eta*np.exp(-self.curModel.taui*t)
+        return peta
+
+    def EtaDeriv(self, t, v, adjoint=False):
+        v = np.array(v, dtype=float)
+        if adjoint:
+            return self.curModel.etaDeriv.T * (np.exp(-self.curModel.taui*t)*v)
+        else:
+            return np.exp(-self.curModel.taui*t) * (self.curModel.etaDeriv*v)
+
+
+    def TauiDeriv(self, t, v, adjoint=False):
+        v = np.array(v, dtype=float)
+        if adjoint:
+            return -self.curModel.tauiDeriv.T * (self.curModel.eta*t*np.exp(-self.curModel.taui*t)*v)
+        else:
+            return -self.curModel.eta*t*np.exp(-self.curModel.taui*t) * (self.curModel.tauiDeriv*v)
+
+    def fields(self, m):
+        self.curModel = m
+        if self.f is None:
+            self.f = self.fieldsPair(self.mesh, self.survey)
+            if self.Ainv == None:
+                A = self.getA()
+                self.Ainv = self.Solver(A, **self.solverOpts)
+            RHS = self.getRHS()
+            u = self.Ainv * RHS
+            Srcs = self.survey.srcList
+            self.f[Srcs, self._solutionType] = u
+        return self.f
+
+    def forward(self, m, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+        Jv = self.dataPair(self.survey) #same size as the data
+        # A = self.getA()
+        JvAll = []
+        for tind in range(len(self.survey.times)):
+            #Pseudo-chareability
+            t = self.survey.times[tind]
+            v = self.DebyeTime(t)
+            for src in self.survey.srcList:
+                u_src = f[src, self._solutionType] # solution vector
+                dA_dm_v = self.getADeriv(u_src, v)
+                dRHS_dm_v = self.getRHSDeriv(src, v)
+                du_dm_v = self.Ainv * ( - dA_dm_v + dRHS_dm_v )
+                for rx in src.rxList:
+                    timeindex = rx.getTimeP(self.survey.times)
+                    if timeindex[tind]:
+                        df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                        df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False)
+                        Jv[src, rx, t] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
+
+        # Conductivity (d u / d log sigma)
+        if self._formulation is 'EB':
+            return -Utils.mkvc(Jv)
+        # Resistivity (d u / d log rho)
+        if self._formulation is 'HJ':
+            return Utils.mkvc(Jv)
+
+    def Jvec(self, m, v, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+        Jv = self.dataPair(self.survey) #same size as the data
+        # A = self.getA()
+        JvAll = []
+        #Assume only eta and tau (eta first then tau)
+        # v = [2*Mx1]
+        v = v.reshape((int(v.size/2), 2), order='F')
+
+        for tind in range(len(self.survey.times)):
+            t = self.survey.times[tind]
+            v0 = self.EtaDeriv(t, v[:,0])
+            v1 = self.TauiDeriv(t, v[:,1])
+            for src in self.survey.srcList:
+                u_src = f[src, self._solutionType] # solution vector
+                dA_dm_v0 = self.getADeriv(u_src, v0)
+                dRHS_dm_v0 = self.getRHSDeriv(src, v0)
+                du_dm_v0 = self.Ainv * ( - dA_dm_v0 + dRHS_dm_v0 )
+                dA_dm_v1 = self.getADeriv(u_src, v1)
+                dRHS_dm_v1 = self.getRHSDeriv(src, v1)
+                du_dm_v1 = self.Ainv * ( - dA_dm_v1 + dRHS_dm_v1 )
+                for rx in src.rxList:
+                    timeindex = rx.getTimeP(self.survey.times)
+                    if timeindex[tind]:
+                        df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                        df_dm_v0 = df_dmFun(src, du_dm_v0, v0, adjoint=False)
+                        df_dm_v1 = df_dmFun(src, du_dm_v1, v1, adjoint=False)
+                        Jv[src, rx, t] = rx.evalDeriv(src, self.mesh, f, df_dm_v0)
+                        Jv[src, rx, t] += rx.evalDeriv(src, self.mesh, f, df_dm_v1)
+        # Conductivity (d u / d log sigma)
+        if self._formulation is 'EB':
+            return -Jv.tovec()
+        # Resistivity (d u / d log rho)
+        if self._formulation is 'HJ':
+            return Jv.tovec()
+
+    def Jtvec(self, m, v, f=None):
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        # Ensure v is a data object.
+        if not isinstance(v, self.dataPair):
+            v = self.dataPair(self.survey, v)
+
+        Jtv= np.zeros(m.size)
+        for tind in range(len(self.survey.times)):
+            t = self.survey.times[tind]
+            for src in self.survey.srcList:
+                u_src = f[src, self._solutionType]
+                for rx in src.rxList:
+                    timeindex = rx.getTimeP(self.survey.times)
+                    if timeindex[tind]:
+                        PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx, t], adjoint=True) # wrt f, need possibility wrt m
+                        df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                        df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
+                        ATinvdf_duT = self.Ainv * df_duT
+                        dA_dmT = self.getADeriv(u_src, ATinvdf_duT, adjoint=True)
+                        dRHS_dmT = self.getRHSDeriv(src, ATinvdf_duT, adjoint=True)
+                        du_dmT = -dA_dmT + dRHS_dmT
+                        Jtv += np.r_[self.EtaDeriv(self.survey.times[tind], du_dmT, adjoint=True), self.TauiDeriv(self.survey.times[tind], du_dmT, adjoint=True)]
+
+        # Conductivity ((d u / d log sigma).T)
+        if self._formulation is 'EB':
+            return -Jtv
+        # Conductivity ((d u / d log rho).T)
+        if self._formulation is 'HJ':
+            return Jtv
+
+    def getSourceTerm(self):
+        """
+        takes concept of source and turns it into a matrix
+        """
+        """
+        Evaluates the sources, and puts them in matrix form
+
+        :rtype: (numpy.ndarray, numpy.ndarray)
+        :return: q (nC or nN, nSrc)
+        """
+
+        Srcs = self.survey.srcList
+
+        if self._formulation is 'EB':
+            n = self.mesh.nN
+            # return NotImplementedError
+
+        elif self._formulation is 'HJ':
+            n = self.mesh.nC
+
+        q = np.zeros((n, len(Srcs)))
+
+        for i, src in enumerate(Srcs):
+            q[:,i] = src.eval(self)
+        return q
+
+    @property
+    def deleteTheseOnModelUpdate(self):
+        toDelete = []
+        return toDelete
+
+    # assume log rho or log cond
+    @property
+    def MeSigma(self):
+        """
+            Edge inner product matrix for \\(\\sigma\\). Used in the E-B formulation
+        """
+        if getattr(self, '_MeSigma', None) is None:
+            self._MeSigma = self.mesh.getEdgeInnerProduct(self.sigma)
+        return self._MeSigma
+
+    @property
+    def MfRhoI(self):
+        """
+            Inverse of :code:`MfRho`
+        """
+        if getattr(self, '_MfRhoI', None) is None:
+            self._MfRhoI = self.mesh.getFaceInnerProduct(self.rho, invMat=True)
+        return self._MfRhoI
+
+    def MfRhoIDeriv(self,u):
+        """
+            Derivative of :code:`MfRhoI` with respect to the model.
+        """
+
+        dMfRhoI_dI = -self.MfRhoI**2
+        dMf_drho = self.mesh.getFaceInnerProductDeriv(self.rho)(u)
+        drho_dlogrho = Utils.sdiag(self.rho)
+        return dMfRhoI_dI * ( dMf_drho * ( drho_dlogrho))
+
+    # TODO: This should take a vector
+    def MeSigmaDeriv(self, u):
+        """
+            Derivative of MeSigma with respect to the model
+        """
+        dsigma_dlogsigma = Utils.sdiag(self.sigma)
+        return self.mesh.getEdgeInnerProductDeriv(self.sigma)(u) * dsigma_dlogsigma
+
+class Problem3D_CC(BaseSIPProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'HJ' # CC potentials means J is on faces
+    fieldsPair    = Fields_CC
+
+    def __init__(self, mesh, **kwargs):
+        BaseSIPProblem.__init__(self, mesh, **kwargs)
+        self.setBC()
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI D^\\top V
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        # TODO: this won't work for full anisotropy
+        MfRhoI = self.MfRhoI
+        A = D * MfRhoI * G
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * A
+        return A
+
+    def getADeriv(self, u, v, adjoint= False):
+
+        D = self.Div
+        G = self.Grad
+        MfRhoIDeriv = self.MfRhoIDeriv
+
+        if adjoint:
+            # if self._makeASymmetric is True:
+            #     v = V * v
+            return(MfRhoIDeriv( G * u ).T) * ( D.T * v)
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * ( D * ( MfRhoIDeriv( D.T * ( V * u ) ) * v ) )
+        return D * (MfRhoIDeriv( G * u ) * v)
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return self.Vol.T * RHS
+
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+    def setBC(self):
+        if self.mesh.dim==3:
+            fxm,fxp,fym,fyp,fzm,fzp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+            gBFzm = self.mesh.gridFz[fzm,:]
+            gBFzp = self.mesh.gridFz[fzp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+            temp_zm, temp_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+            alpha_zm, alpha_zp = temp_zm*0., temp_zp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+            beta_zm, beta_zp = temp_zm, temp_zp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+            gamma_zm, gamma_zp = temp_zm*0., temp_zp*0.
+
+            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]
+
+        elif self.mesh.dim==2:
+
+            fxm,fxp,fym,fyp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+
+            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_CC(self.mesh, alpha, beta, gamma)
+        V = self.Vol
+        self.Div = V * self.mesh.faceDiv
+        P_BC, B = self.mesh.getBCProjWF_simple()
+        M = B*self.mesh.aveCC2F
+        self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M
+
+
+class Problem3D_N(BaseSIPProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'EB' # N potentials means B is on faces
+    fieldsPair    = Fields_N
+
+    def __init__(self, mesh, **kwargs):
+        BaseSIPProblem.__init__(self, mesh, **kwargs)
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI D^\\top V
+
+        """
+
+        # TODO: this won't work for full anisotropy
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        A = Grad.T * MeSigma * Grad
+
+        # Handling Null space of A
+        A[0,0] = A[0,0] + 1.
+
+        return A
+
+    def getADeriv(self, u, v, adjoint=False):
+        """
+
+        Product of the derivative of our system matrix with respect to the model and a vector
+
+        """
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        if not adjoint:
+            return Grad.T*(self.MeSigmaDeriv(Grad*u)*v)
+        elif adjoint:
+            return self.MeSigmaDeriv(Grad*u).T * (Grad*v)
+
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+if __name__ == '__main__':
+
+
+    cs = 12.5
+    hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
+    hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
+    hz = [(cs,7, -1.3),(cs,20)]
+    mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN")
+    sigma = np.ones(mesh.nC)
+    prob = BaseSIPProblem(mesh, sigma=sigma)
+
+

SimPEG/EM/Static/SIP/Regularization.py

@@ -0,0 +1,204 @@
+from SimPEG import Utils, Maps, Mesh, sp, np
+from SimPEG.Regularization import BaseRegularization, Simple
+
+class MultiRegularization(Simple):
+    """
+    **MultiRegularization Class**
+
+    This is used to regularize the model space
+    having multiple models [m1, m2, m3, ...] ::
+
+        reg = Regularization(mesh)
+
+    """
+    nModels = None # Number of models
+    ratios = None  # Ratio for different models
+    crossgrad = False # Use cross gradient or not
+    betacross = 1.
+    wx = []
+    wy = []
+    wz = []
+
+    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
+        BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
+        if self.nModels == None:
+            raise Exception("Put nModels as a initial input!")
+        if self.ratios == None:
+            self.ratios = [1. for imodel in range(self.nModels)]
+
+    @property
+    def Wsmall(self):
+        """Regularization matrix Wsmall"""
+        if getattr(self,'_Wsmall', None) is None:
+            vecs = []
+            for imodel in range(self.nModels):
+                vecs.append((self.regmesh.vol*self.alpha_s*self.wght*self.ratios[imodel])**0.5)
+            self._Wsmall = Utils.sdiag(np.hstack(vecs))
+        return self._Wsmall
+
+    @property
+    def Wx(self):
+        """Regularization matrix Wx"""
+        if getattr(self, '_Wx', None) is None:
+            mats = []
+            for imodel in range(self.nModels):
+                self.wx.append(Utils.sdiag((self.regmesh.aveCC2Fx * self.regmesh.vol*self.alpha_x*self.ratios[imodel]*(self.regmesh.aveCC2Fx*self.wght))**0.5))
+                mats.append(self.wx[imodel]*self.regmesh.cellDiffxStencil)
+            self._Wx = sp.block_diag(mats)
+        return self._Wx
+
+    @property
+    def Wy(self):
+        """Regularization matrix Wy"""
+        if getattr(self, '_Wy', None) is None:
+            mats = []
+            for imodel in range(self.nModels):
+                self.wy.append(Utils.sdiag((self.regmesh.aveCC2Fy * self.regmesh.vol*self.alpha_y*self.ratios[imodel]*(self.regmesh.aveCC2Fy*self.wght))**0.5))
+                mats.append(self.wy[imodel]*self.regmesh.cellDiffyStencil)
+            self._Wy = sp.block_diag(mats)
+        return self._Wy
+
+    @property
+    def Wz(self):
+        """Regularization matrix Wz"""
+        if getattr(self, '_Wz', None) is None:
+            mats = []
+            for imodel in range(self.nModels):
+                self.wz.append(Utils.sdiag((self.regmesh.aveCC2Fz * self.regmesh.vol*self.alpha_z*self.ratios[imodel]*(self.regmesh.aveCC2Fz*self.wght))**0.5))
+                mats.append(self.wz[imodel]*self.regmesh.cellDiffzStencil)
+            self._Wz = sp.block_diag(mats)
+        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.Wsmall, self.Wsmooth)
+            self._W = sp.vstack(wlist)
+        return self._W
+
+
+    @Utils.timeIt
+    def eval(self, m):
+        return self._evalSmall(m) + self._evalSmooth(m)
+
+    @Utils.timeIt
+    def _evalSmall(self, m):
+        r = self.Wsmall * ( self.mapping * (m - self.mref) )
+        return 0.5 * r.dot(r)
+
+    @Utils.timeIt
+    def _evalSmooth(self, m):
+        if self.mrefInSmooth == True:
+            r = self.Wsmooth * ( self.mapping * (m - self.mref) )
+        elif self.mrefInSmooth == False:
+            r = self.Wsmooth * ( self.mapping * m)
+        return 0.5 * r.dot(r)
+
+    def cross(a,b):
+        ax, ay, az = a[0], a[1], a[2]
+        bx, by, bz = b[0], b[1], b[2]
+        cx = ay*bz - az*by
+        cy = az*bx - ax*bz
+        cz = ax*by - ay*bx
+        return [cx, cy, cz]
+
+     # TODO: Implement Cross Gradients..
+    @Utils.timeIt
+    def _evalCross(self, m):
+        if self.crossgrad == False:
+            return 0.
+        elif self.crossgrad == True:
+            M = (self.mapping * m).reshape((self.regmesh.nC, self.nModels), order="F")
+
+            ax = self.regmesh.aveFx2CC*self.regmesh.wx[0]*M[:,0]
+            ay = self.regmesh.aveFy2CC*self.regmesh.wy[0]*M[:,0]
+            az = self.regmesh.aveFz2CC*self.regmesh.wz[0]*M[:,0]
+            bx = self.regmesh.aveFx2CC*self.regmesh.wx[1]*M[:,1]
+            by = self.regmesh.aveFy2CC*self.regmesh.wy[1]*M[:,1]
+            bz = self.regmesh.aveFz2CC*self.regmesh.wz[1]*M[:,1]
+            #ab
+            out_ab = cross([ax, ay, az], [bx, by, bz])
+            r = np.r_[out_ab[0], out_ab[1], out_ab[2]]*np.sqrt(self.betacross)
+
+            if self.nModels == 3:
+                cx = self.regmesh.aveFx2CC*self.regmesh.wx[1]*M[:,1]
+                cy = self.regmesh.aveFy2CC*self.regmesh.wy[1]*M[:,1]
+                cz = self.regmesh.aveFz2CC*self.regmesh.wz[1]*M[:,1]
+                #ac
+                out_ac = cross([ax, ay, az], [cx, cy, cz])
+                #bc
+                out_bc = cross([bx, by, bz], [cx, cy, cz])
+                r = np.r_[r, np.hstack(out_ac)*np.sqrt(self.betacross), np.hstack(out_bc)*np.sqrt(self.betacross)]
+
+            return 0.5 * r.dot(r)
+
+    @Utils.timeIt
+    def evalDeriv(self, m):
+        """
+        The regularization is:
+
+        .. math::
+
+            R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top W(m-m_\\text{ref})}
+
+        So the derivative is straight forward:
+
+        .. math::
+
+            R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}
+
+        """
+        deriv = self._evalSmallDeriv(m) + self._evalSmoothDeriv(m)
+        if self.crossgrad==True:
+            deriv += self._evalCrossDeriv(m)
+        return deriv
+
+    @Utils.timeIt
+    def _evalCrossDeriv(self,m):
+        r = self.Wsmall * ( self.mapping * (m - self.mref) )
+        return r.T * ( self.Wsmall * self.mapping.deriv(m - self.mref) )
+
+    @Utils.timeIt
+    def eval2Deriv(self, m, v=None):
+        """
+        Second derivative
+
+        :param numpy.array m: geophysical model
+        :param numpy.array v: vector to multiply
+        :rtype: scipy.sparse.csr_matrix or numpy.ndarray
+        :return: WtW or WtW*v
+
+        The regularization is:
+
+        .. math::
+
+            R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top W(m-m_\\text{ref})}
+
+        So the second derivative is straight forward:
+
+        .. math::
+
+            R(m) = \mathbf{W^\\top W}
+
+        """
+        mD = self.mapping.deriv(m - self.mref)
+        if v is None:
+            return mD.T * self.W.T * self.W * mD
+
+        return mD.T * ( self.W.T * ( self.W * ( mD * v) ) )
+
+
+

SimPEG/EM/Static/SIP/RxSIP.py

@@ -0,0 +1,88 @@
+import SimPEG
+import numpy as np
+from SimPEG.Utils import Zero, closestPoints
+
+class BaseRx(SimPEG.Survey.BaseTimeRx):
+    locs = None
+    rxType = None
+
+    knownRxTypes = {
+                    'phi':['phi',None],
+                    'ex':['e','x'],
+                    'ey':['e','y'],
+                    'ez':['e','z'],
+                    'jx':['j','x'],
+                    'jy':['j','y'],
+                    'jz':['j','z'],
+                    }
+
+    def __init__(self, locs, times, rxType, **kwargs):
+        SimPEG.Survey.BaseTimeRx.__init__(self, locs, times, rxType, **kwargs)
+
+    @property
+    def projField(self):
+        """Field Type projection (e.g. e b ...)"""
+        return self.knownRxTypes[self.rxType][0]
+
+    def projGLoc(self, f):
+        """Grid Location projection (e.g. Ex Fy ...)"""
+        comp = self.knownRxTypes[self.rxType][1]
+        if comp is not None:
+            return f._GLoc(self.rxType) + comp
+        return f._GLoc(self.rxType)
+
+    def getTimeP(self, timesall):
+        """
+            Returns the time projection matrix.
+
+            .. note::
+
+                This is not stored in memory, but is created on demand.
+        """
+        time_inds = np.in1d(timesall, self.times)
+        return time_inds
+
+    def evalDeriv(self, src, mesh, f, v, adjoint=False):
+        P = self.getP(mesh, self.projGLoc(f))
+        if not adjoint:
+            return P*v
+        elif adjoint:
+            return P.T*v
+
+
+# DC.Rx.Dipole(locs)
+class Dipole(BaseRx):
+
+    def __init__(self, locsM, locsN, times, rxType = 'phi', **kwargs):
+        assert locsM.shape == locsN.shape, 'locsM and locsN need to be the same size'
+        locs = [locsM, locsN]
+        # We may not need this ...
+        BaseRx.__init__(self, locs, times, rxType)
+
+    @property
+    def nD(self):
+        """Number of data in the receiver."""
+        # return self.locs[0].shape[0] * len(self.times)
+        return self.locs[0].shape[0]
+
+    @property
+    def nRx(self):
+        """Number of data in the receiver."""
+        return self.locs[0].shape[0]
+
+        # Not sure why ...
+        # return int(self.locs[0].size / 2)
+
+
+    def getP(self, mesh, Gloc):
+        if mesh in self._Ps:
+            return self._Ps[mesh]
+
+        P0 = mesh.getInterpolationMat(self.locs[0], Gloc)
+        P1 = mesh.getInterpolationMat(self.locs[1], Gloc)
+        P = P0 - P1
+
+        if self.storeProjections:
+            self._Ps[mesh] = P
+
+        return P

SimPEG/EM/Static/SIP/SrcSIP.py

@@ -0,0 +1,64 @@
+import SimPEG
+# from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG.Utils import Zero, closestPoints, mkvc
+import numpy as np
+
+class BaseSrc(SimPEG.Survey.BaseSrc):
+
+    current = 1.0
+    loc = None
+
+    def __init__(self, rxList, **kwargs):
+        SimPEG.Survey.BaseSrc.__init__(self, rxList, **kwargs)
+
+    def eval(self, prob):
+        raise NotImplementedError
+
+    def evalDeriv(self, prob):
+        return Zero()
+
+    @property
+    def nD(self):
+        """Number of data"""
+        return self.vnD.sum()
+
+    @property
+    def vnD(self):
+        """Vector number of data"""
+        return np.array([rx.nD*len(rx.times) for rx in self.rxList])
+
+
+
+class Dipole(BaseSrc):
+
+    def __init__(self, rxList, locA, locB, **kwargs):
+        assert locA.shape == locB.shape, 'Shape of locA and locB should be the same'
+        self.loc = [locA, locB]
+        BaseSrc.__init__(self, rxList, **kwargs)
+
+    def eval(self, prob):
+        if prob._formulation == 'HJ':
+            inds = closestPoints(prob.mesh, self.loc, gridLoc='CC')
+            q = np.zeros(prob.mesh.nC)
+            q[inds] = self.current * np.r_[1., -1.]
+        elif prob._formulation == 'EB':
+            qa = prob.mesh.getInterpolationMat(self.loc[0], locType='N').todense()
+            qb = -prob.mesh.getInterpolationMat(self.loc[1], locType='N').todense()
+            q = self.current * mkvc(qa+qb)
+        return q
+
+class Pole(BaseSrc):
+
+    def __init__(self, rxList, loc, **kwargs):
+        BaseSrc.__init__(self, rxList, loc=loc, **kwargs)
+
+    def eval(self, prob):
+        if prob._formulation == 'HJ':
+            inds = closestPoints(prob.mesh, self.loc)
+            q = np.zeros(prob.mesh.nC)
+            q[inds] = self.current * np.r_[1.]
+        elif prob._formulation == 'EB':
+            q = prob.mesh.getInterpolationMat(self.loc, locType='N').todense()
+            q = self.current * mkvc(q)
+        return q
+

SimPEG/EM/Static/SIP/SurveySIP.py

@@ -0,0 +1,102 @@
+import SimPEG
+from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG import np, sp, Survey, Utils
+from SimPEG.Utils import Zero, Identity
+from SimPEG.EM.Static.SIP.SrcSIP import BaseSrc
+from SimPEG.EM.Static.SIP.RxSIP import BaseRx
+import uuid
+
+
+class Survey(BaseEMSurvey):
+    rxPair  = BaseRx
+    srcPair = BaseSrc
+    times = None
+
+    def __init__(self, srcList, **kwargs):
+        self.srcList = srcList
+        BaseEMSurvey.__init__(self, srcList, **kwargs)
+        self.getUniqueTimes()
+
+    def getUniqueTimes(self):
+        time_rx = []
+        for src in self.srcList:
+            for rx in src.rxList:
+                time_rx.append(rx.times)
+        self.times = np.unique(np.hstack(time_rx))
+
+    def dpred(self, m, f=None):
+        """
+            Predicted data.
+
+            .. math::
+                d_\\text{pred} = Pf(m)
+        """
+        return self.prob.forward(m, f=f)
+
+
+class Data(SimPEG.Survey.Data):
+    """Fancy data storage by Src and Rx"""
+
+    def __init__(self, survey, v=None):
+        self.uid = str(uuid.uuid4())
+        self.survey = survey
+        self._dataDict = {}
+        for src in self.survey.srcList:
+            self._dataDict[src] = {}
+            for rx in src.rxList:
+                self._dataDict[src][rx] = {}
+
+        if v is not None:
+            self.fromvec(v)
+
+    def _ensureCorrectKey(self, key):
+        if type(key) is tuple:
+            if len(key) is not 3:
+                raise KeyError('Key must be [Src, Rx, tInd]')
+            if key[0] not in self.survey.srcList:
+                raise KeyError('Src Key must be a source in the survey.')
+            if key[1] not in key[0].rxList:
+                raise KeyError('Rx Key must be a receiver for the source.')
+            return key
+        elif isinstance(key, self.survey.srcPair):
+            if key not in self.survey.srcList:
+                raise KeyError('Key must be a source in the survey.')
+            return key, None, None
+        else:
+            raise KeyError('Key must be [Src] or [Src,Rx] or [Src, Rx, tInd]')
+
+    def __setitem__(self, key, value):
+        src, rx, t = self._ensureCorrectKey(key)
+        assert rx is not None, 'set data using [Src, Rx]'
+        assert isinstance(value, np.ndarray), 'value must by ndarray'
+        assert value.size == rx.nD, "value must have the same number of data as the source."
+        self._dataDict[src][rx][t] = Utils.mkvc(value)
+
+    def __getitem__(self, key):
+        src, rx, t = self._ensureCorrectKey(key)
+        if rx is not None:
+            if rx not in self._dataDict[src]:
+                raise Exception('Data for receiver has not yet been set.')
+            return self._dataDict[src][rx][t]
+
+        return np.concatenate([self[src,rx, t] for rx in src.rxList])
+
+    def tovec(self):
+        val = []
+        for src in self.survey.srcList:
+            for rx in src.rxList:
+                for t in rx.times:
+                    val.append(self[src, rx, t])
+        return np.concatenate(val)
+
+
+    def fromvec(self, v):
+        v = Utils.mkvc(v)
+        assert v.size == self.survey.nD, 'v must have the correct number of data.'
+        indBot, indTop = 0, 0
+        for src in self.survey.srcList:
+            for rx in src.rxList:
+                for t in rx.times:
+                    indTop += rx.nRx
+                    self[src, rx, t] = v[indBot:indTop]
+                    indBot += rx.nRx

SimPEG/EM/Static/SIP/__init__.py

@@ -0,0 +1,5 @@
+from ProblemSIP import Problem3D_CC, Problem3D_N
+from SurveySIP import Survey, Data
+import SrcSIP as Src #Pole
+import RxSIP as Rx
+from Regularization import MultiRegularization

SimPEG/EM/Static/Utils/StaticUtils.py

@@ -0,0 +1,317 @@
+from SimPEG import np
+from SimPEG.EM.Static import DC, IP
+
+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.
+
+        Assumes flat topo for now...
+
+        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
+
+        Edited Feb 17th, 2016
+
+        @author: dominiquef
+
+    """
+    from SimPEG import np
+    from scipy.interpolate import griddata
+    import pylab as plt
+
+    # Set depth to 0 for now
+    z0 = 0.
+
+    # Pre-allocate
+    midx = []
+    midz = []
+    rho = []
+    LEG = []
+    count = 0 # Counter for data
+    for ii in range(DCsurvey.nSrc):
+
+        Tx = DCsurvey.srcList[ii].loc
+        Rx = DCsurvey.srcList[ii].rxList[0].locs
+
+        nD = DCsurvey.srcList[ii].rxList[0].nD
+
+        data = DCsurvey.dobs[count:count+nD]
+        count += nD
+
+        # Get distances between each poles A-B-M-N
+        if stype == 'pdp':
+            MA = np.abs(Tx[0] - Rx[0][:,0])
+            NA = np.abs(Tx[0] - Rx[1][:,0])
+            MN = np.abs(Rx[1][:,0] - Rx[0][:,0])
+
+            # Create mid-point location
+            Cmid = Tx[0]
+            Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
+            if DCsurvey.mesh.dim == 2:
+                zsrc = Tx[1]
+            elif DCsurvey.mesh.dim ==3:
+                zsrc = Tx[2]
+
+        elif stype == 'dpdp':
+            MA = np.abs(Tx[0][0] - Rx[0][:,0])
+            MB = np.abs(Tx[1][0] - Rx[0][:,0])
+            NA = np.abs(Tx[0][0] - Rx[1][:,0])
+            NB = np.abs(Tx[1][0] - Rx[1][:,0])
+
+            # Create mid-point location
+            Cmid = (Tx[0][0] + Tx[1][0])/2
+            Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
+            if DCsurvey.mesh.dim == 2:
+                zsrc = (Tx[0][1] + Tx[1][1])/2
+            elif DCsurvey.mesh.dim ==3:
+                zsrc = (Tx[0][2] + Tx[1][2])/2
+
+        # Change output for dtype
+        if dtype == 'volt':
+
+            rho = np.hstack([rho,data])
+
+        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 )
+                LEG.append(1./(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 ])
+        if DCsurvey.mesh.dim==3:
+            midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + zsrc ])
+        elif DCsurvey.mesh.dim==2:
+            midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + zsrc ])
+    ax = axs
+
+    # Grid points
+    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]
+
+    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), vmin=vmin, vmax=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
+    ax.scatter(midx,midz,s=10,c=rho.T, vmin =vmin, vmax = vmax, clim=(vmin, vmax))
+
+    #ax.set_xticklabels([])
+    #ax.set_yticklabels([])
+
+    plt.gca().set_aspect('equal', adjustable='box')
+
+
+
+    return ph, LEG
+
+def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
+    """
+        Load in endpoints and survey specifications to generate Tx, Rx location
+        stations.
+
+        Assumes flat topo for now...
+
+        Input:
+        :param endl -> input endpoints [x1, y1, z1, x2, y2, z2]
+        :object mesh -> SimPEG mesh object
+        :switch stype -> "dpdp" (dipole-dipole) | "pdp" (pole-dipole) | 'gradient'
+        : param a, n -> pole seperation, number of rx dipoles per tx
+
+        Output:
+        :param Tx, Rx -> List objects for each tx location
+            Lines: P1x, P1y, P1z, P2x, P2y, P2z
+
+        Created on Wed December 9th, 2015
+
+        @author: dominiquef
+        !! Require clean up to deal with DCsurvey
+    """
+
+    from SimPEG import np
+
+    def xy_2_r(x1,x2,y1,y2):
+        r = np.sqrt( np.sum((x2 - x1)**2 + (y2 - y1)**2) )
+        return r
+
+    ## Evenly distribute electrodes and put on surface
+    # Mesure survey length and direction
+    dl_len = xy_2_r(endl[0,0],endl[1,0],endl[0,1],endl[1,1])
+
+    dl_x = ( endl[1,0] - endl[0,0] ) / dl_len
+    dl_y = ( endl[1,1] - endl[0,1] ) / dl_len
+
+    nstn = np.floor( dl_len / a )
+
+    # Compute discrete pole location along line
+    stn_x = endl[0,0] + np.array(range(int(nstn)))*dl_x*a
+    stn_y = endl[0,1] + np.array(range(int(nstn)))*dl_y*a
+
+    if mesh.dim==2:
+        ztop = mesh.vectorNy[-1]
+        # Create line of P1 locations
+        M = np.c_[stn_x, np.ones(nstn).T*ztop]
+        # Create line of P2 locations
+        N = np.c_[stn_x+a*dl_x, np.ones(nstn).T*ztop]
+
+    elif mesh.dim==3:
+        ztop = mesh.vectorNz[-1]
+        # Create line of P1 locations
+        M = np.c_[stn_x, stn_y, np.ones(nstn).T*ztop]
+        # Create line of P2 locations
+        N = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*ztop]
+
+
+    ## Build list of Tx-Rx locations depending on survey type
+    # Dipole-dipole: Moving tx with [a] spacing -> [AB a MN1 a MN2 ... a MNn]
+    # Pole-dipole: Moving pole on one end -> [A a MN1 a MN2 ... MNn a B]
+    SrcList = []
+
+
+    if stype != 'gradient':
+
+        for ii in range(0, int(nstn)-1):
+
+
+            if stype == 'dpdp':
+                tx = np.c_[M[ii,:],N[ii,:]]
+            elif stype == 'pdp':
+                tx = np.c_[M[ii,:],M[ii,:]]
+
+            # Rx.append(np.c_[M[ii+1:indx,:],N[ii+1:indx,:]])
+
+            # Current elctrode seperation
+            AB = xy_2_r(tx[0,1],endl[1,0],tx[1,1],endl[1,1])
+
+            # Number of receivers to fit
+            nstn = np.min([np.floor( (AB - b) / a ) , n])
+
+            # Check if there is enough space, else break the loop
+            if nstn <= 0:
+                continue
+
+            # Compute discrete pole location along line
+            stn_x = N[ii,0] + dl_x*b + np.array(range(int(nstn)))*dl_x*a
+            stn_y = N[ii,1] + dl_y*b + np.array(range(int(nstn)))*dl_y*a
+
+            # Create receiver poles
+
+            if mesh.dim==3:
+                # Create line of P1 locations
+                P1 = np.c_[stn_x, stn_y, np.ones(nstn).T*ztop]
+                # Create line of P2 locations
+                P2 = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*ztop]
+                rxClass = DC.Rx.Dipole(P1, P2)
+
+            elif mesh.dim==2:
+                # Create line of P1 locations
+                P1 = np.c_[stn_x, np.ones(nstn).T*ztop]
+                # Create line of P2 locations
+                P2 = np.c_[stn_x+a*dl_x, np.ones(nstn).T*ztop]
+                rxClass = DC.Rx.Dipole_ky(P1, P2)
+
+            if stype == 'dpdp':
+                    srcClass = DC.Src.Dipole([rxClass], M[ii,:],N[ii,:])
+            elif stype == 'pdp':
+                    srcClass = DC.Src.Pole([rxClass], M[ii,:])
+            SrcList.append(srcClass)
+
+    elif stype == 'gradient':
+
+        # Gradient survey only requires Tx at end of line and creates a square
+        # grid of receivers at in the middle at a pre-set minimum distance
+
+        # Get the edge limit of survey area
+        min_x = endl[0,0] + dl_x * b
+        min_y = endl[0,1] + dl_y * b
+
+        max_x = endl[1,0] - dl_x * b
+        max_y = endl[1,1] - dl_y * b
+
+        box_l = np.sqrt( (min_x - max_x)**2 + (min_y - max_y)**2 )
+        box_w = box_l/2.
+
+        nstn = np.floor( box_l / a )
+
+        # Compute discrete pole location along line
+        stn_x = min_x + np.array(range(int(nstn)))*dl_x*a
+        stn_y = min_y + np.array(range(int(nstn)))*dl_y*a
+
+        # Define number of cross lines
+        nlin = int(np.floor( box_w / a ))
+        lind = range(-nlin,nlin+1)
+
+        ngrad = nstn * len(lind)
+
+        rx = np.zeros([ngrad,6])
+        for ii in range( len(lind) ):
+
+            # Move line in perpendicular direction by dipole spacing
+            lxx = stn_x - lind[ii]*a*dl_y
+            lyy = stn_y + lind[ii]*a*dl_x
+
+
+            M = np.c_[ lxx, lyy , np.ones(nstn).T*ztop]
+            N = np.c_[ lxx+a*dl_x, lyy+a*dl_y, np.ones(nstn).T*ztop]
+            rx[(ii*nstn):((ii+1)*nstn),:] = np.c_[M,N]
+
+            if mesh.dim==3:
+                rxClass = DC.Rx.Dipole(rx[:,:3], rx[:,3:])
+            elif mesh.dim==2:
+                M = M[:,[0,2]]
+                N = N[:,[0,2]]
+                rxClass = DC.Rx.Dipole_ky(rx[:,[0,2]], rx[:,[3,5]])
+            srcClass = DC.Src.Dipole([rxClass], M[0,:], N[-1,:])
+        SrcList.append(srcClass)
+    else:
+        print """stype must be either 'pdp', 'dpdp' or 'gradient'. """
+
+
+    return SrcList
+

SimPEG/EM/Static/Utils/__init__.py

@@ -0,0 +1 @@
+from StaticUtils import *

SimPEG/EM/Static/__init__.py

@@ -0,0 +1,3 @@
+import DC
+import IP
+import SIP

SimPEG/EM/TDEM/SurveyTDEM.py

@@ -87,7 +87,7 @@ class SrcTDEM_VMD_MVP(SrcTDEM):
     def getInitialFields(self, mesh):
         """Vertical magnetic dipole, magnetic vector potential"""
         if self.waveformType == "STEPOFF":
-            print ">> Step waveform: Non-zero initial condition"        
+            print ">> Step waveform: Non-zero initial condition"
             if mesh._meshType is 'CYL':
                 if mesh.isSymmetric:
                     MVP = MagneticDipoleVectorPotential(self.loc, mesh, 'Ey')
@@ -96,8 +96,8 @@ class SrcTDEM_VMD_MVP(SrcTDEM):
             elif mesh._meshType is 'TENSOR':
                 MVP = MagneticDipoleVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'])
             else:
-                raise Exception('Unknown mesh for VMD') 
-            return {"b": mesh.edgeCurl*MVP}               
+                raise Exception('Unknown mesh for VMD')
+            return {"b": mesh.edgeCurl*MVP}
         elif self.waveformType == "GENERAL":
             print ">> General waveform: Zero initial condition"
             return {"b": np.zeros(mesh.nF)}
@@ -113,7 +113,7 @@ class SrcTDEM_VMD_MVP(SrcTDEM):
         elif mesh._meshType is 'TENSOR':
             MVP = MagneticDipoleVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'])
         else:
-            raise Exception('Unknown mesh for VMD')            
+            raise Exception('Unknown mesh for VMD')
         return mesh.edgeCurl.T*MfMui*mesh.edgeCurl*MVP
 
 
@@ -122,7 +122,7 @@ class SrcTDEM_CircularLoop_MVP(SrcTDEM):
         self.loc = loc
         self.radius = radius
         self.waveformType = waveformType
-        SrcTDEM.__init__(self,rxList)        
+        SrcTDEM.__init__(self,rxList)
 
     def getInitialFields(self, mesh):
         """Circular Loop, magnetic vector potential"""
@@ -153,7 +153,7 @@ class SrcTDEM_CircularLoop_MVP(SrcTDEM):
         elif mesh._meshType is 'TENSOR':
             MVP = MagneticLoopVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'], self.radius)
         else:
-            raise Exception('Unknown mesh for CircularLoop')            
+            raise Exception('Unknown mesh for CircularLoop')
         return mesh.edgeCurl.T*MfMui*mesh.edgeCurl*MVP
 
 

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)
 
@@ -37,39 +37,20 @@ def getFDEMProblem(fdemType, comp, SrcList, freq, useMu=False, verbose=False):
             Src.append(EM.FDEM.Src.MagDipole_Bfield([Rx0], freq=freq, loc=np.r_[0.,0.,0.]))
         elif SrcType is 'CircularLoop':
             Src.append(EM.FDEM.Src.CircularLoop([Rx0], freq=freq, loc=np.r_[0.,0.,0.]))
-
         elif SrcType is 'RawVec':
             if fdemType is 'e' or fdemType is 'b':
                 S_m = np.zeros(mesh.nF)
                 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, S_e, integrate=True))
+                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, S_m, S_e, integrate=True))
-
-        elif SrcType is 'PrimSec':
-                primSrc = EM.FDEM.Src.MagDipole([], freq, np.r_[0.,0.,0.])
-                primarySurvey = EM.FDEM.Survey([primSrc])
-                primaryProblem = EM.FDEM.Problem_e(mesh,mapping=mapping)
-                mPrimary = np.ones(mapping.nP)*np.log(CONDUCTIVITY)
-                Src.append(EM.FDEM.Src.PrimSec([Rx0], freq, mPrimary, prob=primaryProblem, survey=primarySurvey))
-
-        elif SrcType is 'PrimSecCyl':
-                hx = [(cs,ncx + 2), (cs,npad + 2,1.3)]
-                hz = [(cs,npad + 2 ,-1.3), (cs,ncz+2), (cs,npad+2,1.3)]
-                primmesh = Mesh.CylMesh([hx,1,hz], '00C')
-
-                primSrc = EM.FDEM.Src.MagDipole([], freq, np.r_[0.,0.,0.])
-                primarySurvey = EM.FDEM.Survey([primSrc])
-                primaryProblem = EM.FDEM.Problem_e(primmesh)
-                mPrimary = np.ones(primmesh.nC)*CONDUCTIVITY
-                Src.append(EM.FDEM.Src.PrimSec([Rx0], freq, mPrimary, prob=primaryProblem, survey=primarySurvey))
+                Src.append(EM.FDEM.Src.RawVec([Rx0], freq, S_m, S_e))
 
     if verbose:
         print '  Fetching %s problem' % (fdemType)
@@ -109,7 +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/EM/__init__.py

@@ -1,5 +1,6 @@
 import TDEM
 import FDEM
+import Static
 import Base
 import Analytics
 import Utils

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.
 
-        Created by @fourndo on Mon Feb 01 19:28:06 2016
+        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
 
     """
 
     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/Inversion_IRLS.py

@@ -0,0 +1,132 @@
+from SimPEG import *
+
+
+def run(N=200, plotIt=True):
+    """
+        Inversion: Linear Problem
+        =========================
+
+        Here we go over the basics of creating a linear problem and inversion.
+
+    """
+
+
+    np.random.seed(1)
+
+    std_noise = 1e-2
+
+    mesh = Mesh.TensorMesh([N])
+
+    m0 = np.ones(mesh.nC) * 1e-4
+    nk = 10
+    jk = np.linspace(1.,nk,nk)
+    p = -2.
+    q = 1.
+
+    g = lambda k: np.exp(p*jk[k]*mesh.vectorCCx)*np.cos(np.pi*q*jk[k]*mesh.vectorCCx)
+
+    G = np.empty((nk, mesh.nC))
+
+    for i in range(nk):
+        G[i,:] = g(i)
+
+    mtrue = np.zeros(mesh.nC)
+    mtrue[mesh.vectorCCx > 0.3] = 1.
+    mtrue[mesh.vectorCCx > 0.45] = -0.5
+    mtrue[mesh.vectorCCx > 0.6] = 0
+
+
+    prob = Problem.LinearProblem(mesh, G)
+    survey = Survey.LinearSurvey()
+    survey.pair(prob)
+    survey.dobs = prob.fields(mtrue) + std_noise * np.random.randn(nk)
+    #survey.makeSyntheticData(mtrue, std=std_noise)
+
+    wd = np.ones(nk) * std_noise
+
+    #print survey.std[0]
+    #M = prob.mesh
+    # Distance weighting
+    wr = np.sum(prob.G**2.,axis=0)**0.5
+    wr = ( wr/np.max(wr) )
+
+    reg = Regularization.Simple(mesh)
+    reg.wght = wr
+
+    dmis = DataMisfit.l2_DataMisfit(survey)
+    dmis.Wd = 1./wd
+
+    opt = Optimization.ProjectedGNCG(maxIter=30,lower=-2.,upper=2., maxIterCG= 20, tolCG = 1e-4)
+    invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
+    invProb.curModel = m0
+
+    beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
+    target = Directives.TargetMisfit()
+
+    betaest = Directives.BetaEstimate_ByEig()
+    inv = Inversion.BaseInversion(invProb, directiveList=[beta, betaest, target])
+
+
+    mrec = inv.run(m0)
+    ml2 = mrec
+    print "Final misfit:" + str(invProb.dmisfit.eval(mrec))
+
+    # Switch regularization to sparse
+    phim = invProb.phi_m_last
+    phid =  invProb.phi_d
+
+    reg = Regularization.Sparse(mesh)
+
+#==============================================================================
+#     fig, axes = plt.subplots(1,2,figsize=(12*1.2,4*1.2))
+#     dmdx = reg.mesh.cellDiffxStencil * mrec
+#     plt.plot(np.sort(dmdx))
+#==============================================================================
+
+    #reg.recModel = mrec
+    reg.wght = np.ones(mesh.nC)
+    reg.mref = np.zeros(mesh.nC)
+    reg.eps_p = 2e-3
+    reg.eps_q = 2e-3
+    reg.norms   = [0., 0., 2., 2.]
+    reg.wght = wr
+
+    opt = Optimization.ProjectedGNCG(maxIter=5 ,lower=-2.,upper=2., maxIterCG= 100, tolCG = 1e-3)
+    invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = invProb.beta*2.)
+    beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
+    #betaest = Directives.BetaEstimate_ByEig()
+    target = Directives.TargetMisfit()
+    IRLS =Directives.Update_IRLS( phi_m_last = phim, phi_d_last = phid )
+
+    inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS])
+
+    m0 = mrec
+
+    # Run inversion
+    mrec = inv.run(m0)
+
+    print "Final misfit:" + str(invProb.dmisfit.eval(mrec))
+
+
+    if plotIt:
+        import matplotlib.pyplot as plt
+
+        fig, axes = plt.subplots(1,2,figsize=(12*1.2,4*1.2))
+        for i in range(prob.G.shape[0]):
+            axes[0].plot(prob.G[i,:])
+        axes[0].set_title('Columns of matrix G')
+
+        axes[1].plot(mesh.vectorCCx, mtrue, 'b-')
+        axes[1].plot(mesh.vectorCCx, ml2, 'r-')
+        #axes[1].legend(('True Model', 'Recovered Model'))
+        axes[1].set_ylim(-1.0,1.25)
+
+        axes[1].plot(mesh.vectorCCx, mrec, 'k-',lw = 2)
+        axes[1].legend(('True Model', 'Smooth l2-l2',
+        'Sparse lp:' + str(reg.norms[0]) + ', lqx:' + str(reg.norms[1]) ), fontsize = 12)
+        plt.show()
+
+    return prob, survey, mesh, mrec
+
+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

@@ -5,9 +5,11 @@ 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
+import Inversion_IRLS
 import Inversion_Linear
 import Mesh_Basic_PlotImage
 import Mesh_Basic_Types
@@ -19,7 +21,7 @@ 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_IRLS", "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/Inversion.py

@@ -33,7 +33,9 @@ class BaseInversion(object):
         self._directiveList = value
         self._directiveList.inversion = self
 
-    def __init__(self, invProb, directiveList=[], **kwargs):
+    def __init__(self, invProb, directiveList=None, **kwargs):
+        if directiveList is None:
+            directiveList = []
         self.directiveList = directiveList
         Utils.setKwargs(self, **kwargs)
 

SimPEG/Maps.py

@@ -759,15 +759,29 @@ class PolyMap(IdentityMap):
 
             m = [\sigma_1, \sigma_2, c]
 
+        Can take in an actInd vector to account for topography.
+
     """
-    def __init__(self, mesh, order, logSigma=True, normal='X'):
+    def __init__(self, mesh, order, logSigma=True, normal='X', actInd = None):
         IdentityMap.__init__(self, mesh)
         self.logSigma = logSigma
         self.order = order
         self.normal = normal
+        self.actInd = actInd
+
+        if getattr(self, 'actInd', None) is None:
+            self.actInd = range(self.mesh.nC)
+            self.nC = self.mesh.nC
+
+        else:
+            self.nC = len(self.actInd)
 
     slope = 1e4
 
+    @property
+    def shape(self):
+        return (self.nC, self.nP)
+
     @property
     def nP(self):
         if np.isscalar(self.order):
@@ -785,8 +799,8 @@ class PolyMap(IdentityMap):
             sig1, sig2 = np.exp(sig1), np.exp(sig2)
         #2D
         if self.mesh.dim == 2:
-            X = self.mesh.gridCC[:,0]
-            Y = self.mesh.gridCC[:,1]
+            X = self.mesh.gridCC[self.actInd,0]
+            Y = self.mesh.gridCC[self.actInd,1]
             if self.normal =='X':
                 f = polynomial.polyval(Y, c) - X
             elif self.normal =='Y':
@@ -795,9 +809,9 @@ class PolyMap(IdentityMap):
                 raise(Exception("Input for normal = X or Y or Z"))
         #3D
         elif self.mesh.dim == 3:
-            X = self.mesh.gridCC[:,0]
-            Y = self.mesh.gridCC[:,1]
-            Z = self.mesh.gridCC[:,2]
+            X = self.mesh.gridCC[self.actInd,0]
+            Y = self.mesh.gridCC[self.actInd,1]
+            Z = self.mesh.gridCC[self.actInd,2]
             if self.normal =='X':
                 f = polynomial.polyval2d(Y, Z, c.reshape((self.order[0]+1,self.order[1]+1))) - X
             elif self.normal =='Y':
@@ -806,6 +820,7 @@ class PolyMap(IdentityMap):
                 f = polynomial.polyval2d(X, Y, c.reshape((self.order[0]+1,self.order[1]+1))) - Z
             else:
                 raise(Exception("Input for normal = X or Y or Z"))
+
         else:
             raise(Exception("Only supports 2D"))
 
@@ -819,8 +834,8 @@ class PolyMap(IdentityMap):
             sig1, sig2 = np.exp(sig1), np.exp(sig2)
         #2D
         if self.mesh.dim == 2:
-            X = self.mesh.gridCC[:,0]
-            Y = self.mesh.gridCC[:,1]
+            X = self.mesh.gridCC[self.actInd,0]
+            Y = self.mesh.gridCC[self.actInd,1]
 
             if self.normal =='X':
                 f = polynomial.polyval(Y, c) - X
@@ -832,9 +847,9 @@ class PolyMap(IdentityMap):
                 raise(Exception("Input for normal = X or Y or Z"))
         #3D
         elif self.mesh.dim == 3:
-            X = self.mesh.gridCC[:,0]
-            Y = self.mesh.gridCC[:,1]
-            Z = self.mesh.gridCC[:,2]
+            X = self.mesh.gridCC[self.actInd,0]
+            Y = self.mesh.gridCC[self.actInd,1]
+            Z = self.mesh.gridCC[self.actInd,2]
 
             if self.normal =='X':
                 f = polynomial.polyval2d(Y, Z, c.reshape((self.order[0]+1,self.order[1]+1))) - X

SimPEG/Mesh/BaseMesh.py

@@ -1,5 +1,4 @@
 import numpy as np
-import scipy.sparse as sp
 from SimPEG import Utils
 
 
@@ -595,63 +594,3 @@ class BaseRectangularMesh(BaseMesh):
             return out
         else:
             return switchKernal(x)
-
-
-    def getInterpolationMatMesh2Mesh(self, mesh2, locType='CC', locTypeFrom=None):
-        """
-        Interpolates variables from the current mesh to a new mesh (mesh2)
-
-        :param Mesh mesh2: SimPEG mesh which we interpolate values to
-        :param string locType: location of variables 'CC', 'E', 'F', 'N'
-        :rtype: scipy.sparse.csr_matrix
-        :return P: interpolation matrix
-        """
-
-        # import warnings
-        # warnings.warn(
-        #      "`getInterpolationMatMesh2Mesh` will be slow. If you want to interpolate a vector from one mesh to another, use `InterpolateVecMesh2Mesh`",
-        #      RuntimeWarning)
-
-        if locTypeFrom is None:
-            locTypeFrom = locType # assume that we are interpolating to and from the same place
-
-        # Error Checking
-        if self._meshType == 'CYL':
-            assert self.isSymmetric, "Currently, we do not support non-symmetric cyl meshes"
-        if mesh2._meshType == 'CYL':
-            assert self._meshType == 'CYL', "Interpolation from 3D mesh to Cyl mesh is not supported"
-
-        # if Cyl to cart call
-        if self._meshType == 'CYL' and mesh2._meshType != 'CYL':
-            return self.getInterpolationMatCartMesh(mesh2, locType)
-
-        # Scalars
-        if locType in ['CC', 'CCVx', 'CCVy', 'CCVz', 'N', 'Fx', 'Fy', 'Fz', 'Ex', 'Ey', 'Ez']:
-            grid = getattr(mesh2, 'grid%s'%locTypeFrom)
-            return self.getInterpolationMat(grid, locType)
-
-        # Vectors
-        else:
-            if self._meshType == 'CYL':
-                if locType == 'F':
-                    X = self.getInterpolationMatMesh2Mesh(mesh2, locType='Fx', locTypeFrom=locTypeFrom+'x')
-                    Z = self.getInterpolationMatMesh2Mesh(mesh2, locType='Fz', locTypeFrom=locTypeFrom+'z')
-                    return sp.block_diag([X, Z])
-                elif locType == 'E':
-                    return self.getInterpolationMatMesh2Mesh(mesh2, locType='Ey', locTypeFrom=locTypeFrom+'y')
-
-            if self.dim == 1:
-                return self.getInterpolationMatMesh2Mesh(mesh2, locType='%sx'%locType, locTypeFrom=locTypeFrom+'x')
-            elif self.dim == 2:
-                X = self.getInterpolationMatMesh2Mesh(mesh2, locType='%sx'%locType, locTypeFrom=locTypeFrom+'x')
-                Y = self.getInterpolationMatMesh2Mesh(mesh2, locType='%sy'%locType, locTypeFrom=locTypeFrom+'y')
-                return sp.block_diag([X, Y])
-            elif self.dim == 3:
-                X = self.getInterpolationMatMesh2Mesh(mesh2, locType='%sx'%locType, locTypeFrom=locTypeFrom+'x')
-                Y = self.getInterpolationMatMesh2Mesh(mesh2, locType='%sy'%locType, locTypeFrom=locTypeFrom+'y')
-                Z = self.getInterpolationMatMesh2Mesh(mesh2, locType='%sz'%locType, locTypeFrom=locTypeFrom+'z')
-                return sp.block_diag([X, Y, Z])
-
-
-
-

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/Mesh/TreeMesh.py

@@ -2131,10 +2131,16 @@ class TreeMesh(BaseTensorMesh, InnerProducts, TreeMeshIO):
     def plotSlice(self, v, vType='CC',
         normal='Z', ind=None, grid=True, view='real',
         ax=None, clim=None, showIt=False,
-        pcolorOpts={},
-        streamOpts={'color':'k'},
-        gridOpts={'color':'k', 'alpha':0.5}):
+        pcolorOpts=None,
+        streamOpts=None,
+        gridOpts=None):
 
+        if pcolorOpts is None:
+            pcolorOpts = {}
+        if streamOpts is None:
+            streamOpts = {'color':'k'}
+        if gridOpts is None:
+            gridOpts = {'color':'k', 'alpha':0.5}
         assert vType in ['CC','F','E']
         assert self.dim == 3
 

SimPEG/Mesh/View.py

@@ -42,9 +42,9 @@ class TensorView(object):
 
     def plotImage(self, v, vType='CC', grid=False, view='real',
               ax=None, clim=None, showIt=False,
-              pcolorOpts={},
-              streamOpts={'color':'k'},
-              gridOpts={'color':'k'},
+              pcolorOpts=None,
+              streamOpts=None,
+              gridOpts=None,
               numbering=True, annotationColor='w'
               ):
         """
@@ -84,6 +84,12 @@ class TensorView(object):
             M.plotImage(v, annotationColor='k', showIt=True)
 
         """
+        if pcolorOpts is None:
+            pcolorOpts = {}
+        if streamOpts is None:
+            streamOpts = {'color':'k'}
+        if gridOpts is None:
+            gridOpts = {'color':'k'}
 
         if ax is None:
             fig = plt.figure()
@@ -174,9 +180,9 @@ class TensorView(object):
     def plotSlice(self, v, vType='CC',
                   normal='Z', ind=None, grid=False, view='real',
                   ax=None, clim=None, showIt=False,
-                  pcolorOpts={},
-                  streamOpts={'color':'k'},
-                  gridOpts={'color':'k', 'alpha':0.5}
+                  pcolorOpts=None,
+                  streamOpts=None,
+                  gridOpts=None
                   ):
 
         """
@@ -197,6 +203,12 @@ class TensorView(object):
             M.plotSlice(M.cellGrad*b, 'F', view='vec', grid=True, showIt=True, pcolorOpts={'alpha':0.8})
 
         """
+        if pcolorOpts is None:
+            pcolorOpts = {}
+        if streamOpts is None:
+            streamOpts = {'color':'k'}
+        if gridOpts is None:
+            gridOpts = {'color':'k', 'alpha':0.5}
         if type(vType) in [list, tuple]:
             assert ax is None, "cannot specify an axis to plot on with this function."
             fig, axs = plt.subplots(1,len(vType))
@@ -206,7 +218,7 @@ class TensorView(object):
             return out
         viewOpts = ['real','imag','abs','vec']
         normalOpts = ['X', 'Y', 'Z']
-        vTypeOpts = ['CC', 'CCv','F','E','Fx','Fy','Fz','E','Ex','Ey','Ez']
+        vTypeOpts = ['CC', 'CCv','N','F','E','Fx','Fy','Fz','E','Ex','Ey','Ez']
 
         # Some user error checking
         assert vType in vTypeOpts, "vType must be in ['%s']" % "','".join(vTypeOpts)
@@ -289,11 +301,17 @@ class TensorView(object):
 
     def _plotImage2D(self, v, vType='CC', grid=False, view='real',
               ax=None, clim=None, showIt=False,
-              pcolorOpts={},
-              streamOpts={'color':'k'},
-              gridOpts={'color':'k'}
+              pcolorOpts=None,
+              streamOpts=None,
+              gridOpts=None
               ):
 
+        if pcolorOpts is None:
+            pcolorOpts = {}
+        if streamOpts is None:
+            streamOpts = {'color':'k'}
+        if gridOpts is None:
+            gridOpts = {'color':'k'}
         vTypeOptsCC = ['N','CC','Fx','Fy','Ex','Ey']
         vTypeOptsV = ['CCv','F','E']
         vTypeOpts = vTypeOptsCC + vTypeOptsV

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 +992,20 @@ 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 +343,7 @@ class BaseRegularization(object):
     @property
     def W(self):
         """Full regularization weighting matrix W."""
-        return sp.identity(self.mapping.nP)
-
+        return sp.identity(self.regmesh.nC)
 
     @Utils.timeIt
     def eval(self, m):
@@ -87,11 +374,12 @@ class BaseRegularization(object):
     @Utils.timeIt
     def eval2Deriv(self, m, v=None):
         """
+        Second derivative
 
-            :param numpy.array m: geophysical model
-            :param numpy.array v: vector to multiply
-            :rtype: scipy.sparse.csr_matrix or numpy.ndarray
-            :return: WtW or WtW*v
+        :param numpy.array m: geophysical model
+        :param numpy.array v: vector to multiply
+        :rtype: scipy.sparse.csr_matrix or numpy.ndarray
+        :return: WtW or WtW*v
 
         The regularization is:
 
@@ -112,112 +400,94 @@ class BaseRegularization(object):
 
         return mD.T * ( self.W.T * ( self.W * ( mD * v) ) )
 
-
 class Tikhonov(BaseRegularization):
     """
+    L2 Tikhonov regularization with both smallness and smoothness (first order
+    derivative) contributions.
+
+    .. math::
+        \phi_m(\mathbf{m}) = \\alpha_s \| W_s (\mathbf{m} - \mathbf{m_{ref}} ) \|^2
+        + \\alpha_x \| W_x \\frac{\partial}{\partial x} (\mathbf{m} - \mathbf{m_{ref}} ) \|^2
+        + \\alpha_y \| W_y \\frac{\partial}{\partial y} (\mathbf{m} - \mathbf{m_{ref}} ) \|^2
+        + \\alpha_z \| W_z \\frac{\partial}{\partial z} (\mathbf{m} - \mathbf{m_{ref}} ) \|^2
+
+    Note if the key word argument `mrefInSmooth` is False, then mref is not
+    included in the smoothness contribution.
+
+    :param Mesh mesh: SimPEG mesh
+    :param Maps mapping: regularization mapping, takes the model from model space to the thing you want to regularize
+    :param numpy.ndarray indActive: active cell indices for reducing the size of differential operators in the definition of a regularization mesh
+    :param bool mrefInSmooth: (default = False) put mref in the smoothness component?
+    :param float alpha_s: (default 1e-6) smallness weight
+    :param float alpha_x: (default 1) smoothness weight for first derivative in the x-direction
+    :param float alpha_y: (default 1) smoothness weight for first derivative in the y-direction
+    :param float alpha_z: (default 1) smoothness weight for first derivative in the z-direction
+    :param float alpha_xx: (default 1) smoothness weight for second derivative in the x-direction
+    :param float alpha_yy: (default 1) smoothness weight for second derivative in the y-direction
+    :param float alpha_zz: (default 1) smoothness weight for second derivative in the z-direction
     """
-    smoothModel = 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")
-    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 = False  # put mref in the smoothness contribution
+    alpha_s      = Utils.dependentProperty('_alpha_s', 1e-6, ['_W', '_Wsmall'], "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")
 
     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
-        return self._Ws
+    def Wsmall(self):
+        """Regularization matrix Wsmall"""
+        if getattr(self,'_Wsmall', None) is None:
+            self._Wsmall = Utils.sdiag((self.regmesh.vol*self.alpha_s)**0.5)
+        return self._Wsmall
 
     @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 +495,9 @@ 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
@@ -236,25 +506,44 @@ class Tikhonov(BaseRegularization):
     def W(self):
         """Full regularization matrix W"""
         if getattr(self, '_W', None) is None:
-            wlist = (self.Ws, self.Wsmooth)
+            wlist = (self.Wsmall, 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)
+    def _evalSmall(self, m):
+        r = self.Wsmall * ( self.mapping * (m - self.mref) )
+        return 0.5 * r.dot(r)
 
+    @Utils.timeIt
+    def _evalSmooth(self, m):
+        if self.mrefInSmooth == True:
+            r = self.Wsmooth * ( self.mapping * (m - self.mref) )
+        elif self.mrefInSmooth == False:
+            r = self.Wsmooth * ( self.mapping * (m) )
+        return 0.5 * r.dot(r)
+
+    @Utils.timeIt
+    def eval(self, m):
+        return self._evalSmall(m) + self._evalSmooth(m)
+
+    @Utils.timeIt
+    def _evalSmallDeriv(self,m):
+        r = self.Wsmall * ( self.mapping * (m - self.mref) )
+        return r.T * ( self.Wsmall * self.mapping.deriv(m - self.mref) )
+
+    @Utils.timeIt
+    def _evalSmoothDeriv(self,m):
+        if self.mrefInSmooth == True:
+            r = self.Wsmooth * ( self.mapping * ( m - self.mref ) )
+            return r.T * ( self.Wsmooth * self.mapping.deriv(m - self.mref) )
+        elif self.mrefInSmooth == False:
+            r = self.Wsmooth * ( self.mapping * m )
+            return r.T * ( self.Wsmooth * self.mapping.deriv(m) )
 
     @Utils.timeIt
     def evalDeriv(self, m):
         """
-
         The regularization is:
 
         .. math::
@@ -268,257 +557,185 @@ class Tikhonov(BaseRegularization):
             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
-
-# <<<<<<< HEAD
-
-# 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")
-
-#     def __init__(self, mesh, mapping=None, **kwargs):
-#         BaseRegularization.__init__(self, mesh, mapping=mapping, **kwargs)
+        return self._evalSmallDeriv(m) + self._evalSmoothDeriv(m)
 
 
+class Simple(Tikhonov):
+    """
+    Simple regularization that does not include length scales in the derivatives.
+    """
 
-#     @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
+    mrefInSmooth = False  #: SMOOTH and SMOOTH_MOD_DIF options
+    alpha_s     = Utils.dependentProperty('_alpha_s', 1.0, ['_W', '_Wsmall'], "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.
 
-#     @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
+    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
+        BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
 
-#     @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
+        if isinstance(self.wght,float):
+            self.wght = np.ones(self.regmesh.nC) * self.wght
 
-#     @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
+    @property
+    def Wsmall(self):
+        """Regularization matrix Wsmall"""
+        if getattr(self,'_Wsmall', None) is None:
+            self._Wsmall = Utils.sdiag((self.regmesh.vol*self.alpha_s*self.wght)**0.5)
+        return self._Wsmall
 
-#     @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
+    @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 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
+    @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 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
+    @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, 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 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
+    @property
+    def W(self):
+        """Full regularization matrix W"""
+        if getattr(self, '_W', None) is None:
+            wlist = (self.Wsmall, 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)
+    @Utils.timeIt
+    def _evalSmall(self, m):
+        r = self.Wsmall * ( self.mapping * (m - self.mref) )
+        return 0.5 * r.dot(r)
+
+    @Utils.timeIt
+    def _evalSmooth(self, m):
+        if self.mrefInSmooth == True:
+            r = self.Wsmooth * ( self.mapping * (m - self.mref) )
+        elif self.mrefInSmooth == False:
+            r = self.Wsmooth * ( self.mapping * m)
+        return 0.5 * r.dot(r)
 
 
-#     @Utils.timeIt
-#     def evalDeriv(self, m):
-#         """
+class Sparse(Simple):
 
-#         The regularization is:
+    # set default values
+    eps_p      = 1e-1
+    eps_q      = 1e-1
+    curModel = None # use a model to compute the weights
+    gamma    = 1.
+    norms    = [0., 2., 2., 2.]
+    wght     = 1.
 
-#         .. math::
+    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
+        Simple.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
 
-#             R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top W(m-m_\\text{ref})}
+        if isinstance(self.wght,float):
+            self.wght = np.ones(self.regmesh.nC) * self.wght
 
-#         So the derivative is straight forward:
+    @property
+    def Wsmall(self):
+        """Regularization matrix Wsmall"""
+        if getattr(self, 'curModel', None) is None:
+            self.Rs = Utils.speye(self.regmesh.nC)
 
-#         .. math::
+        else:
+            f_m = self.curModel - self.reg.mref
+            self.rs = self.R(f_m , self.eps_p, self.norms[0])
+            #print "Min rs: " + str(np.max(self.rs)) + "Max rs: " + str(np.min(self.rs))
+            self.Rs = Utils.sdiag( self.rs )
 
-#             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)
+        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"""
 
-#     @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
+        if getattr(self, 'curModel', None) is None:
+            self.Rx = Utils.speye(self.regmesh.cellDiffxStencil.shape[0])
 
-#     @property
-#     def Ws(self):
-#         """Regularization matrix Ws"""
-#         if getattr(self, 'm', None) is None:
-#             self.Rs = Utils.speye(self.mesh.nC)
+        else:
+            f_m = self.regmesh.cellDiffxStencil * self.curModel
+            self.rx = self.R( f_m , self.eps_q, self.norms[1])
+            self.Rx = Utils.sdiag( self.rx )
 
-#         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 )
+        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
 
-#         self._Ws = Utils.sdiag((self.mesh.vol*self.alpha_s*self.gamma)**0.5)*self.Rs
+    @property
+    def Wy(self):
+        """Regularization matrix Wy"""
 
-#         return self._Ws
+        if getattr(self, 'curModel', None) is None:
+            self.Ry = Utils.speye(self.regmesh.cellDiffyStencil.shape[0])
 
-#     @property
-#     def Wx(self):
-#         """Regularization matrix Wx"""
+        else:
+            f_m = self.regmesh.cellDiffyStencil * self.curModel
+            self.ry = self.R( f_m , self.eps_q, self.norms[2])
+            self.Ry = Utils.sdiag( self.ry )
 
-#         if getattr(self, 'm', None) is None:
-#             self.Rx = Utils.speye(self.mesh.unitCellGradx.shape[0])
+        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
 
-#         else:
-#             f_m = self.mesh.unitCellGradx * self.m
-#             self.rx = self.R( f_m , self.qx, self.eps)
-#             self.Rx = Utils.sdiag( self.rx )
+    @property
+    def Wz(self):
+        """Regularization matrix Wz"""
 
-#         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
+        if getattr(self, 'curModel', None) is None:
+            self.Rz = Utils.speye(self.regmesh.cellDiffzStencil.shape[0])
 
-#     @property
-#     def Wy(self):
-#         """Regularization matrix Wy"""
+        else:
+            f_m = self.regmesh.cellDiffzStencil * self.curModel
+            self.rz = self.R( f_m , self.eps_q, self.norms[3])
+            self.Rz = Utils.sdiag( self.rz )
 
-#         if getattr(self, 'm', None) is None:
-#             self.Ry = Utils.speye(self.mesh.unitCellGrady.shape[0])
+        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
 
-#         else:
-#             f_m = self.mesh.unitCellGrady * self.m
-#             self.ry = self.R( f_m , self.qy, self.eps)
-#             self.Ry = Utils.sdiag( self.ry )
+    @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, '_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 W(self):
+        """Full regularization matrix W"""
+        #if getattr(self, '_W', None) is None:
+        wlist = (self.Wsmall, self.Wsmooth)
+        #self._W = sp.vstack(wlist)
+        return sp.vstack(wlist)
 
-#     @property
-#     def Wz(self):
-#         """Regularization matrix Wz"""
+    def R(self, f_m , eps, exponent):
 
-#         if getattr(self, 'm', None) is None:
-#             self.Rz = Utils.speye(self.mesh.unitCellGradz.shape[0])
+        eta = (eps**(1-exponent/2.))**0.5
+        r = eta / (f_m**2.+ eps**2.)**((1-exponent/2.)/2.)
 
-#         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

SimPEG/Tests.py

@@ -82,14 +82,14 @@ class OrderTest(unittest.TestCase):
     _meshType = meshTypes[0]
     meshDimension = 3
 
-    def makeMesh(self, nc, meshType=_meshType, meshDimension=meshDimension):
+    def setupMesh(self, nc):
         """
         For a given number of cells nc, generate a TensorMesh with uniform cells with edge length h=1/nc.
         """
-        if 'TensorMesh' in meshType:
-            if 'uniform' in meshType:
+        if 'TensorMesh' in self._meshType:
+            if 'uniform' in self._meshType:
                 h = [nc, nc, nc]
-            elif 'random' in meshType:
+            elif 'random' in self._meshType:
                 h1 = np.random.rand(nc)*nc*0.5 + nc*0.5
                 h2 = np.random.rand(nc)*nc*0.5 + nc*0.5
                 h3 = np.random.rand(nc)*nc*0.5 + nc*0.5
@@ -97,46 +97,46 @@ class OrderTest(unittest.TestCase):
             else:
                 raise Exception('Unexpected meshType')
 
-            M = TensorMesh(h[:meshDimension])
-            max_h = max([np.max(hi) for hi in M.h])
-            return M, max_h
+            self.M = TensorMesh(h[:self.meshDimension])
+            max_h = max([np.max(hi) for hi in self.M.h])
+            return max_h
 
-        elif 'CylMesh' in meshType:
-            if 'uniform' in meshType:
+        elif 'CylMesh' in self._meshType:
+            if 'uniform' in self._meshType:
                 h = [nc, nc, nc]
             else:
                 raise Exception('Unexpected meshType')
 
-            if meshDimension == 2:
-                M = CylMesh([h[0], 1, h[2]])
-                max_h = max([np.max(hi) for hi in [M.hx, M.hz]])
-            elif meshDimension == 3:
-                M = CylMesh(h)
-                max_h = max([np.max(hi) for hi in M.h])
-            return M, max_h
+            if self.meshDimension == 2:
+                self.M = CylMesh([h[0], 1, h[2]])
+                max_h = max([np.max(hi) for hi in [self.M.hx, self.M.hz]])
+            elif self.meshDimension == 3:
+                self.M = CylMesh(h)
+                max_h = max([np.max(hi) for hi in self.M.h])
+            return max_h
 
-        elif 'Curv' in meshType:
-            if 'uniform' in meshType:
+        elif 'Curv' in self._meshType:
+            if 'uniform' in self._meshType:
                 kwrd = 'rect'
-            elif 'rotate' in meshType:
+            elif 'rotate' in self._meshType:
                 kwrd = 'rotate'
             else:
                 raise Exception('Unexpected meshType')
-            if meshDimension == 1:
+            if self.meshDimension == 1:
                 raise Exception('Lom not supported for 1D')
-            elif meshDimension == 2:
+            elif self.meshDimension == 2:
                 X, Y = Utils.exampleLrmGrid([nc, nc], kwrd)
-                M = CurvilinearMesh([X, Y])
-            elif meshDimension == 3:
+                self.M = CurvilinearMesh([X, Y])
+            elif self.meshDimension == 3:
                 X, Y, Z = Utils.exampleLrmGrid([nc, nc, nc], kwrd)
-                M = CurvilinearMesh([X, Y, Z])
-            return M, 1./nc
+                self.M = CurvilinearMesh([X, Y, Z])
+            return 1./nc
 
-        elif 'Tree' in meshType:
+        elif 'Tree' in self._meshType:
             nc *= 2
-            if 'uniform' in meshType or 'notatree' in meshType:
+            if 'uniform' in self._meshType or 'notatree' in self._meshType:
                 h = [nc, nc, nc]
-            elif 'random' in meshType:
+            elif 'random' in self._meshType:
                 h1 = np.random.rand(nc)*nc*0.5 + nc*0.5
                 h2 = np.random.rand(nc)*nc*0.5 + nc*0.5
                 h3 = np.random.rand(nc)*nc*0.5 + nc*0.5
@@ -145,29 +145,20 @@ class OrderTest(unittest.TestCase):
                 raise Exception('Unexpected meshType')
 
             levels = int(np.log(nc)/np.log(2))
-            M = Tree(h[:meshDimension], levels=levels)
+            self.M = Tree(h[:self.meshDimension], levels=levels)
             def function(cell):
-                if 'notatree' in meshType:
+                if 'notatree' in self._meshType:
                     return levels - 1
                 r = cell.center - np.array([0.5]*len(cell.center))
                 dist = np.sqrt(r.dot(r))
                 if dist < 0.2:
                     return levels
                 return levels - 1
-            M.refine(function,balance=False)
-            M.number(balance=False)
-            # M.plotGrid(showIt=True)
-            max_h = max([np.max(hi) for hi in M.h])
-            return M, max_h
-
-
-    def setupMesh(self, nc):
-        """
-        For a given number of cells nc, generate a TensorMesh with uniform cells with edge length h=1/nc.
-        """
-        M, h = self.makeMesh(nc, meshType=self._meshType, meshDimension=self.meshDimension)
-        self.M = M
-        return h
+            self.M.refine(function,balance=False)
+            self.M.number(balance=False)
+            # self.M.plotGrid(showIt=True)
+            max_h = max([np.max(hi) for hi in self.M.h])
+            return max_h
 
     def getError(self):
         """For given h, generate A[h], f and A(f) and return norm of error."""

SimPEG/Utils/ModelBuilder.py

@@ -88,12 +88,14 @@ def getIndicesBlock(p0,p1,ccMesh):
     # Return a tuple
     return ind
 
-def defineBlock(ccMesh,p0,p1,vals=[0,1]):
+def defineBlock(ccMesh,p0,p1,vals=None):
     """
         Build a block with the conductivity specified by condVal.  Returns an array.
         vals[0]  conductivity of the block
         vals[1]  conductivity of the ground
     """
+    if vals is None:
+        vals = [0,1]
     sigma = np.zeros(ccMesh.shape[0]) + vals[1]
     ind   = getIndicesBlock(p0,p1,ccMesh)
 
@@ -101,7 +103,11 @@ def defineBlock(ccMesh,p0,p1,vals=[0,1]):
 
     return mkvc(sigma)
 
-def defineElipse(ccMesh, center=[0,0,0], anisotropy=[1,1,1], slope=10., theta=0.):
+def defineElipse(ccMesh, center=None, anisotropy=None, slope=10., theta=0.):
+    if center is None:
+        center = [0,0,0]
+    if anisotropy is None:
+        anisotropy = [1,1,1]
     G = ccMesh.copy()
     dim = ccMesh.shape[1]
     for i in range(dim):
@@ -156,7 +162,7 @@ def getIndicesSphere(center,radius,ccMesh):
     # Return a tuple
     return ind
 
-def defineTwoLayers(ccMesh,depth,vals=[0,1]):
+def defineTwoLayers(ccMesh,depth,vals=None):
     """
     Define a two layered model.  Depth of the first layer must be specified.
     CondVals vector with the conductivity values of the layers.  Eg:
@@ -167,6 +173,8 @@ def defineTwoLayers(ccMesh,depth,vals=[0,1]):
         0                          depth                                 zf
              1st layer                       2nd layer
     """
+    if vals is None:
+        vals = [0,1]
     sigma = np.zeros(ccMesh.shape[0]) + vals[1]
 
     dim = np.size(ccMesh[0,:])
@@ -252,7 +260,7 @@ def layeredModel(ccMesh, layerTops, layerValues):
 
 
 
-def randomModel(shape, seed=None, anisotropy=None, its=100, bounds=[0,1]):
+def randomModel(shape, seed=None, anisotropy=None, its=100, bounds=None):
     """
         Create a random model by convolving a kernel with a
         uniformly distributed model.
@@ -276,6 +284,8 @@ def randomModel(shape, seed=None, anisotropy=None, its=100, bounds=[0,1]):
 
 
     """
+    if bounds is None:
+        bounds = [0,1]
 
     if seed is None:
         seed = np.random.randint(1e3)

SimPEG/Utils/codeutils.py

@@ -55,8 +55,10 @@ def hook(obj, method, name=None, overwrite=False, silent=False):
         print 'Method '+name+' was not overwritten.'
 
 
-def setKwargs(obj, ignore=[],  **kwargs):
+def setKwargs(obj, ignore=None,  **kwargs):
     """Sets key word arguments (kwargs) that are present in the object, throw an error if they don't exist."""
+    if ignore is None:
+        ignore = []
     for attr in kwargs:
         if attr in ignore:
             continue

SimPEG/Utils/matutils.py

@@ -27,7 +27,7 @@ def mkvc(x, numDims=1):
 
     if isinstance(x, Zero):
         return x
-
+    
     assert isinstance(x, np.ndarray), "Vector must be a numpy array"
 
     if numDims == 1:
@@ -422,9 +422,9 @@ class Zero(object):
     def __ge__(self, v):return 0 >= v
     def __gt__(self, v):return 0 > v
 
-    @property
+    @property 
     def transpose(self): return Zero()
-
+    
     @property
     def T(self): return Zero()
 

docs/examples/DC_Forward_PseudoSection.rst

@@ -12,8 +12,16 @@
 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
 
 

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:

docs/examples/Inversion_IRLS.rst

@@ -0,0 +1,26 @@
+.. _examples_Inversion_IRLS:
+
+.. --------------------------------- ..
+..                                   ..
+..    THIS FILE IS AUTO GENEREATED   ..
+..                                   ..
+..    SimPEG/Examples/__init__.py    ..
+..                                   ..
+.. --------------------------------- ..
+
+
+Inversion: Linear Problem
+=========================
+
+Here we go over the basics of creating a linear problem and inversion.
+
+
+
+.. plot::
+
+    from SimPEG import Examples
+    Examples.Inversion_IRLS.run()
+
+.. literalinclude:: ../../SimPEG/Examples/Inversion_IRLS.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/em/fdem/inverse/derivs/test_FDEM_derivs.py

@@ -8,8 +8,8 @@ from SimPEG.EM.Utils.testingUtils import getFDEMProblem
 
 testE = True
 testB = True
-testH = False
-testJ = False
+testH = True
+testJ = True
 
 verbose = False
 
@@ -20,8 +20,8 @@ MU = mu_0
 freq = 1e-1
 addrandoms = True
 
-# SrcType = ['MagDipole', 'RawVec'] #or 'MAgDipole_Bfield', 'CircularLoop', 'RawVec'
-SrcType = ['PrimSecCyl']
+SrcType = ['MagDipole', 'RawVec'] #or 'MAgDipole_Bfield', 'CircularLoop', 'RawVec'
+
 
 def derivTest(fdemType, comp):
 

tests/em/static/__init__.py

@@ -0,0 +1,12 @@
+import os
+import glob
+import unittest
+
+if __name__ == '__main__':
+    test_file_strings = glob.glob('test_*.py')
+    module_strings = [str[0:len(str)-3] for str in test_file_strings]
+    suites = [unittest.defaultTestLoader.loadTestsFromName(str) for str
+              in module_strings]
+    testSuite = unittest.TestSuite(suites)
+
+    unittest.TextTestRunner(verbosity=2).run(testSuite)

tests/em/static/test_DC_2D_analytic.py

@@ -0,0 +1,69 @@
+import unittest
+from SimPEG import Mesh, Utils, EM, Maps, np
+import SimPEG.EM.Static.DC as DC
+
+class DCProblemAnalyticTests(unittest.TestCase):
+
+    def setUp(self):
+
+        cs = 12.5
+        hx = [(cs,7, -1.3),(cs,61),(cs,7, 1.3)]
+        hy = [(cs,7, -1.3),(cs,20)]
+        mesh = Mesh.TensorMesh([hx, hy],x0="CN")
+        sighalf = 1e-2
+        sigma = np.ones(mesh.nC)*sighalf
+        x = np.linspace(-135, 250., 20)
+        M = Utils.ndgrid(x-12.5, np.r_[0.])
+        N = Utils.ndgrid(x+12.5, np.r_[0.])
+        A0loc = np.r_[-150, 0.]
+        A1loc = np.r_[-130, 0.]
+        rxloc = [np.c_[M, np.zeros(20)], np.c_[N, np.zeros(20)]]
+        data_anal = EM.Analytics.DCAnalyticHalf(np.r_[A0loc, 0.], rxloc, sighalf, flag="halfspace")
+
+        rx = DC.Rx.Dipole(M, N)
+        src0 = DC.Src.Pole([rx], A0loc)
+        survey = DC.Survey_ky([src0])
+
+        self.survey = survey
+        self.mesh = mesh
+        self.sigma = sigma
+        self.data_anal = data_anal
+
+        try:
+            from pymatsolver import MumpsSolver
+            self.Solver = MumpsSolver
+        except ImportError, e:
+            self.Solver = SolverLU
+
+    def test_Problem3D_N(self):
+
+        problem = DC.Problem2D_N(self.mesh)
+        problem.Solver = self.Solver
+        problem.pair(self.survey)
+        data = self.survey.dpred(self.sigma)
+        err= np.linalg.norm((data-self.data_anal)/self.data_anal)**2 / self.data_anal.size
+        if err < 0.05:
+            passed = True
+            print ">> DC analytic test for Problem3D_N is passed"
+        else:
+            passed = False
+            print ">> DC analytic test for Problem3D_N is failed"
+        self.assertTrue(passed)
+
+    def test_Problem3D_CC(self):
+        problem = DC.Problem2D_CC(self.mesh)
+        problem.Solver = self.Solver
+        problem.pair(self.survey)
+        data = self.survey.dpred(self.sigma)
+        err= np.linalg.norm((data-self.data_anal)/self.data_anal)**2 / self.data_anal.size
+        if err < 0.05:
+            passed = True
+            print ">> DC analytic test for Problem3D_CC is passed"
+        else:
+            passed = False
+            print ">> DC analytic test for Problem3D_CC is failed"
+        self.assertTrue(passed)
+
+if __name__ == '__main__':
+    unittest.main()
+

tests/em/static/test_DC_2D_jvecjtvecadj.py

@@ -0,0 +1,127 @@
+import unittest
+from SimPEG import *
+import SimPEG.EM.Static.DC as DC
+
+
+class DCProblem_2DTestsCC(unittest.TestCase):
+
+    def setUp(self):
+
+        cs = 12.5
+        hx = [(cs,7, -1.3),(cs,61),(cs,7, 1.3)]
+        hy = [(cs,7, -1.3),(cs,20)]
+        mesh = Mesh.TensorMesh([hx, hy],x0="CN")
+        x = np.linspace(-135, 250., 20)
+        M = Utils.ndgrid(x-12.5, np.r_[0.])
+        N = Utils.ndgrid(x+12.5, np.r_[0.])
+        A0loc = np.r_[-150, 0.]
+        A1loc = np.r_[-130, 0.]
+        rxloc = [np.c_[M, np.zeros(20)], np.c_[N, np.zeros(20)]]
+        rx = DC.Rx.Dipole_ky(M, N)
+        src0 = DC.Src.Pole([rx], A0loc)
+        src1 = DC.Src.Pole([rx], A1loc)
+        survey = DC.Survey_ky([src0, src1])
+        problem = DC.Problem2D_CC(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
+        problem.pair(survey)
+
+        mSynth = np.ones(mesh.nC)*1.
+        survey.makeSyntheticData(mSynth)
+
+        # Now set up the problem to do some minimization
+        dmis = DataMisfit.l2_DataMisfit(survey)
+        reg = Regularization.Tikhonov(mesh)
+        opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+        invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e0)
+        inv = Inversion.BaseInversion(invProb)
+
+        self.inv    = inv
+        self.reg    = reg
+        self.p      = problem
+        self.mesh   = mesh
+        self.m0     = mSynth
+        self.survey = survey
+        self.dmis   = dmis
+
+    def test_misfit(self):
+        derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+    def test_adjoint(self):
+        # Adjoint Test
+        u = np.random.rand(self.mesh.nC*self.survey.nSrc)
+        v = np.random.rand(self.mesh.nC)
+        w = np.random.rand(self.survey.dobs.shape[0])
+        wtJv = w.dot(self.p.Jvec(self.m0, v))
+        vtJtw = v.dot(self.p.Jtvec(self.m0, w))
+        passed = np.abs(wtJv - vtJtw) < 1e-10
+        print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
+        self.assertTrue(passed)
+
+    def test_dataObj(self):
+        derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+class DCProblemTestsN(unittest.TestCase):
+
+    def setUp(self):
+
+        cs = 12.5
+        hx = [(cs,7, -1.3),(cs,61),(cs,7, 1.3)]
+        hy = [(cs,7, -1.3),(cs,20)]
+        mesh = Mesh.TensorMesh([hx, hy],x0="CN")
+        x = np.linspace(-135, 250., 20)
+        M = Utils.ndgrid(x-12.5, np.r_[0.])
+        N = Utils.ndgrid(x+12.5, np.r_[0.])
+        A0loc = np.r_[-150, 0.]
+        A1loc = np.r_[-130, 0.]
+        rxloc = [np.c_[M, np.zeros(20)], np.c_[N, np.zeros(20)]]
+        rx = DC.Rx.Dipole_ky(M, N)
+        src0 = DC.Src.Pole([rx], A0loc)
+        src1 = DC.Src.Pole([rx], A1loc)
+        survey = DC.Survey_ky([src0, src1])
+        problem = DC.Problem2D_N(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
+        problem.pair(survey)
+
+        mSynth = np.ones(mesh.nC)*1.
+        survey.makeSyntheticData(mSynth)
+
+        # Now set up the problem to do some minimization
+        dmis = DataMisfit.l2_DataMisfit(survey)
+        reg = Regularization.Tikhonov(mesh)
+        opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+        invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e0)
+        inv = Inversion.BaseInversion(invProb)
+
+        self.inv = inv
+        self.reg = reg
+        self.p =     problem
+        self.mesh = mesh
+        self.m0 = mSynth
+        self.survey = survey
+        self.dmis = dmis
+
+    def test_misfit(self):
+        derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+    def test_adjoint(self):
+        # Adjoint Test
+        u = np.random.rand(self.mesh.nC*self.survey.nSrc)
+        v = np.random.rand(self.mesh.nC)
+        w = np.random.rand(self.survey.dobs.shape[0])
+        wtJv = w.dot(self.p.Jvec(self.m0, v))
+        vtJtw = v.dot(self.p.Jtvec(self.m0, w))
+        passed = np.abs(wtJv - vtJtw) < 1e-8
+        print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
+        self.assertTrue(passed)
+
+    def test_dataObj(self):
+        derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+if __name__ == '__main__':
+    unittest.main()

tests/em/static/test_DC_analytic.py

@@ -0,0 +1,71 @@
+import unittest
+from SimPEG import Mesh, Utils, EM, Maps, np
+import SimPEG.EM.Static.DC as DC
+
+class DCProblemAnalyticTests(unittest.TestCase):
+
+    def setUp(self):
+
+        cs = 25.
+        hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
+        hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
+        hz = [(cs,7, -1.3),(cs,20)]
+        mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN")
+        sigma = np.ones(mesh.nC)*1e-2
+
+        x = mesh.vectorCCx[(mesh.vectorCCx>-155.)&(mesh.vectorCCx<155.)]
+        y = mesh.vectorCCx[(mesh.vectorCCy>-155.)&(mesh.vectorCCy<155.)]
+        Aloc = np.r_[-200., 0., 0.]
+        Bloc = np.r_[200., 0., 0.]
+        M = Utils.ndgrid(x-25.,y, np.r_[0.])
+        N = Utils.ndgrid(x+25.,y, np.r_[0.])
+        phiA = EM.Analytics.DCAnalyticHalf(Aloc, [M,N], 1e-2, flag="halfspace")
+        phiB = EM.Analytics.DCAnalyticHalf(Bloc, [M,N], 1e-2, flag="halfspace")
+        data_anal = phiA-phiB
+
+        rx = DC.Rx.Dipole(M, N)
+        src = DC.Src.Dipole([rx], Aloc, Bloc)
+        survey = DC.Survey([src])
+
+        self.survey = survey
+        self.mesh = mesh
+        self.sigma = sigma
+        self.data_anal = data_anal
+
+        try:
+            from pymatsolver import MumpsSolver
+            self.Solver = MumpsSolver
+        except ImportError, e:
+            self.Solver = SolverLU
+
+    def test_Problem3D_N(self):
+        problem = DC.Problem3D_N(self.mesh)
+        problem.Solver = self.Solver
+        problem.pair(self.survey)
+        data = self.survey.dpred(self.sigma)
+        err= np.linalg.norm(data-self.data_anal)/np.linalg.norm(self.data_anal)
+        if err < 0.2:
+            passed = True
+            print ">> DC analytic test for Problem3D_N is passed"
+        else:
+            passed = False
+            print ">> DC analytic test for Problem3D_N is failed"
+        self.assertTrue(passed)
+
+    def test_Problem3D_CC(self):
+        problem = DC.Problem3D_CC(self.mesh)
+        problem.Solver = self.Solver
+        problem.pair(self.survey)
+        data = self.survey.dpred(self.sigma)
+        err= np.linalg.norm(data-self.data_anal)/np.linalg.norm(self.data_anal)
+        if err < 0.2:
+            passed = True
+            print ">> DC analytic test for Problem3D_CC is passed"
+        else:
+            passed = False
+            print ">> DC analytic test for Problem3D_CC is failed"
+        self.assertTrue(passed)
+
+if __name__ == '__main__':
+    unittest.main()
+

tests/em/static/test_DC_jvecjtvecadj.py

@@ -0,0 +1,127 @@
+import unittest
+from SimPEG import *
+import SimPEG.EM.Static.DC as DC
+
+
+class DCProblemTestsCC(unittest.TestCase):
+
+    def setUp(self):
+
+        aSpacing=2.5
+        nElecs=5
+
+        surveySize = nElecs*aSpacing - aSpacing
+        cs = surveySize/nElecs/4
+
+        mesh = Mesh.TensorMesh([
+                [(cs,10, -1.3),(cs,surveySize/cs),(cs,10, 1.3)],
+                [(cs,3, -1.3),(cs,3,1.3)],
+                # [(cs,5, -1.3),(cs,10)]
+            ],'CN')
+
+        srcList = DC.Utils.WennerSrcList(nElecs, aSpacing, in2D=True)
+        survey = DC.Survey(srcList)
+        problem = DC.Problem3D_CC(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
+        problem.pair(survey)
+
+        mSynth = np.ones(mesh.nC)
+        survey.makeSyntheticData(mSynth)
+
+        # Now set up the problem to do some minimization
+        dmis = DataMisfit.l2_DataMisfit(survey)
+        reg = Regularization.Tikhonov(mesh)
+        opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+        invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
+        inv = Inversion.BaseInversion(invProb)
+
+        self.inv = inv
+        self.reg = reg
+        self.p =     problem
+        self.mesh = mesh
+        self.m0 = mSynth
+        self.survey = survey
+        self.dmis = dmis
+
+    def test_misfit(self):
+        derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+    def test_adjoint(self):
+        # Adjoint Test
+        u = np.random.rand(self.mesh.nC*self.survey.nSrc)
+        v = np.random.rand(self.mesh.nC)
+        w = np.random.rand(self.survey.dobs.shape[0])
+        wtJv = w.dot(self.p.Jvec(self.m0, v))
+        vtJtw = v.dot(self.p.Jtvec(self.m0, w))
+        passed = np.abs(wtJv - vtJtw) < 1e-10
+        print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
+        self.assertTrue(passed)
+
+    def test_dataObj(self):
+        derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+class DCProblemTestsN(unittest.TestCase):
+
+    def setUp(self):
+
+        aSpacing=2.5
+        nElecs=10
+
+        surveySize = nElecs*aSpacing - aSpacing
+        cs = surveySize/nElecs/4
+
+        mesh = Mesh.TensorMesh([
+                [(cs,10, -1.3),(cs,surveySize/cs),(cs,10, 1.3)],
+                [(cs,3, -1.3),(cs,3,1.3)],
+        #         [(cs,5, -1.3),(cs,10)]
+            ],'CN')
+
+        srcList = DC.Utils.WennerSrcList(nElecs, aSpacing, in2D=True)
+        survey = DC.Survey(srcList)
+        problem = DC.Problem3D_N(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
+        problem.pair(survey)
+
+        mSynth = np.ones(mesh.nC)
+        survey.makeSyntheticData(mSynth)
+
+        # Now set up the problem to do some minimization
+        dmis = DataMisfit.l2_DataMisfit(survey)
+        reg = Regularization.Tikhonov(mesh)
+        opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+        invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
+        inv = Inversion.BaseInversion(invProb)
+
+        self.inv = inv
+        self.reg = reg
+        self.p =     problem
+        self.mesh = mesh
+        self.m0 = mSynth
+        self.survey = survey
+        self.dmis = dmis
+
+    def test_misfit(self):
+        derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False)
+        self.assertTrue(passed)
+
+    def test_adjoint(self):
+        # Adjoint Test
+        u = np.random.rand(self.mesh.nC*self.survey.nSrc)
+        v = np.random.rand(self.mesh.nC)
+        w = np.random.rand(self.survey.dobs.shape[0])
+        wtJv = w.dot(self.p.Jvec(self.m0, v))
+        vtJtw = v.dot(self.p.Jtvec(self.m0, w))
+        passed = np.abs(wtJv - vtJtw) < 1e-8
+        print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
+        self.assertTrue(passed)
+
+    def test_dataObj(self):
+        derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False)
+        self.assertTrue(passed)
+
+if __name__ == '__main__':
+    unittest.main()

tests/em/static/test_IP_fwd.py

@@ -0,0 +1,96 @@
+import unittest
+from SimPEG import Mesh, Utils, EM, Maps, np
+import SimPEG.EM.Static.DC as DC
+import SimPEG.EM.Static.IP as IP
+
+class IPProblemAnalyticTests(unittest.TestCase):
+
+    def setUp(self):
+
+        cs = 12.5
+        npad=2
+        hx = [(cs,npad, -1.3),(cs,21),(cs,npad, 1.3)]
+        hy = [(cs,npad, -1.3),(cs,21),(cs,npad, 1.3)]
+        hz = [(cs,npad, -1.3),(cs,20)]
+        mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN")
+
+        x = mesh.vectorCCx[(mesh.vectorCCx>-80.)&(mesh.vectorCCx<80.)]
+        y = mesh.vectorCCx[(mesh.vectorCCy>-80.)&(mesh.vectorCCy<80.)]
+        Aloc = np.r_[-100., 0., 0.]
+        Bloc = np.r_[100., 0., 0.]
+        M = Utils.ndgrid(x-12.5,y, np.r_[0.])
+        N = Utils.ndgrid(x+12.5,y, np.r_[0.])
+        radius = 50.
+        xc = np.r_[0., 0., -100]
+        blkind = Utils.ModelBuilder.getIndicesSphere(xc, radius, mesh.gridCC)
+        sigmaInf = np.ones(mesh.nC)*1e-2
+        eta = np.zeros(mesh.nC)
+        eta[blkind] = 0.1
+        sigma0 = sigmaInf*(1.-eta)
+
+        rx = DC.Rx.Dipole(M, N)
+        src = DC.Src.Dipole([rx], Aloc, Bloc)
+        surveyDC = DC.Survey([src])
+
+        self.surveyDC = surveyDC
+        self.mesh = mesh
+        self.sigmaInf = sigmaInf
+        self.sigma0 = sigma0
+        self.src = src
+        self.eta = eta
+
+        try:
+            from pymatsolver import MumpsSolver
+            self.Solver = MumpsSolver
+        except ImportError, e:
+            self.Solver = SolverLU
+
+    def test_Problem3D_N(self):
+
+        problemDC = DC.Problem3D_N(self.mesh)
+        problemDC.Solver = self.Solver
+        problemDC.pair(self.surveyDC)
+        data0 = self.surveyDC.dpred(self.sigma0)
+        finf = problemDC.fields(self.sigmaInf)
+        datainf = self.surveyDC.dpred(self.sigmaInf, f=finf)
+        problemIP = IP.Problem3D_N(self.mesh, sigma=self.sigmaInf, Ainv=problemDC.Ainv, f=finf)
+        problemIP.Solver = self.Solver
+        surveyIP = IP.Survey([self.src])
+        problemIP.pair(surveyIP)
+        data_full = data0 - datainf
+        data = surveyIP.dpred(self.eta)
+        err= np.linalg.norm((data-data_full)/data_full)**2 / data_full.size
+        if err < 0.05:
+            passed = True
+            print ">> IP forward test for Problem3D_N is passed"
+        else:
+            passed = False
+            print ">> IP forward test for Problem3D_N is failed"
+        self.assertTrue(passed)
+
+    def test_Problem3D_CC(self):
+
+        problemDC = DC.Problem3D_CC(self.mesh)
+        problemDC.Solver = self.Solver
+        problemDC.pair(self.surveyDC)
+        data0 = self.surveyDC.dpred(self.sigma0)
+        finf = problemDC.fields(self.sigmaInf)
+        datainf = self.surveyDC.dpred(self.sigmaInf, f=finf)
+        problemIP = IP.Problem3D_CC(self.mesh, rho=1./self.sigmaInf, Ainv=problemDC.Ainv, f=finf)
+        problemIP.Solver = self.Solver
+        surveyIP = IP.Survey([self.src])
+        problemIP.pair(surveyIP)
+        data_full = data0 - datainf
+        data = surveyIP.dpred(self.eta)
+        err= np.linalg.norm((data-data_full)/data_full)**2 / data_full.size
+        if err < 0.05:
+            passed = True
+            print ">> IP forward test for Problem3D_CC is passed"
+        else:
+            passed = False
+            print ">> IP forward test for Problem3D_CC is failed"
+        self.assertTrue(passed)
+
+if __name__ == '__main__':
+    unittest.main()
+

tests/em/static/test_IP_jvecjtvecadj.py

@@ -0,0 +1,126 @@
+import unittest
+from SimPEG import *
+import SimPEG.EM.Static.DC as DC
+import SimPEG.EM.Static.IP as IP
+
+
+class IPProblemTestsCC(unittest.TestCase):
+
+    def setUp(self):
+
+        aSpacing=2.5
+        nElecs=5
+
+        surveySize = nElecs*aSpacing - aSpacing
+        cs = surveySize/nElecs/4
+
+        mesh = Mesh.TensorMesh([
+                [(cs,10, -1.3),(cs,surveySize/cs),(cs,10, 1.3)],
+                [(cs,3, -1.3),(cs,3,1.3)],
+                # [(cs,5, -1.3),(cs,10)]
+            ],'CN')
+
+        srcList = DC.Utils.WennerSrcList(nElecs, aSpacing, in2D=True)
+        survey = IP.Survey(srcList)
+        sigma = np.ones(mesh.nC)
+        problem = IP.Problem3D_CC(mesh, rho=1./sigma)
+        problem.pair(survey)
+        mSynth = np.ones(mesh.nC)*0.1
+        survey.makeSyntheticData(mSynth)
+        # Now set up the problem to do some minimization
+        dmis = DataMisfit.l2_DataMisfit(survey)
+        reg = Regularization.Tikhonov(mesh)
+        opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+        invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
+        inv = Inversion.BaseInversion(invProb)
+
+        self.inv = inv
+        self.reg = reg
+        self.p =     problem
+        self.mesh = mesh
+        self.m0 = mSynth
+        self.survey = survey
+        self.dmis = dmis
+
+    def test_misfit(self):
+        derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+    def test_adjoint(self):
+        # Adjoint Test
+        u = np.random.rand(self.mesh.nC*self.survey.nSrc)
+        v = np.random.rand(self.mesh.nC)
+        w = np.random.rand(self.survey.dobs.shape[0])
+        wtJv = w.dot(self.p.Jvec(self.m0, v))
+        vtJtw = v.dot(self.p.Jtvec(self.m0, w))
+        passed = np.abs(wtJv - vtJtw) < 1e-10
+        print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
+        self.assertTrue(passed)
+
+    def test_dataObj(self):
+        derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+class IPProblemTestsN(unittest.TestCase):
+
+    def setUp(self):
+
+        aSpacing=2.5
+        nElecs=5
+
+        surveySize = nElecs*aSpacing - aSpacing
+        cs = surveySize/nElecs/4
+
+        mesh = Mesh.TensorMesh([
+                [(cs,10, -1.3),(cs,surveySize/cs),(cs,10, 1.3)],
+                [(cs,3, -1.3),(cs,3,1.3)],
+                # [(cs,5, -1.3),(cs,10)]
+            ],'CN')
+
+        srcList = DC.Utils.WennerSrcList(nElecs, aSpacing, in2D=True)
+        survey = IP.Survey(srcList)
+        sigma = np.ones(mesh.nC)
+        problem = IP.Problem3D_N(mesh, sigma=sigma)
+        problem.pair(survey)
+        mSynth = np.ones(mesh.nC)*0.1
+        survey.makeSyntheticData(mSynth)
+        # Now set up the problem to do some minimization
+        dmis = DataMisfit.l2_DataMisfit(survey)
+        reg = Regularization.Tikhonov(mesh)
+        opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+        invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
+        inv = Inversion.BaseInversion(invProb)
+
+        self.inv = inv
+        self.reg = reg
+        self.p =     problem
+        self.mesh = mesh
+        self.m0 = mSynth
+        self.survey = survey
+        self.dmis = dmis
+
+    def test_misfit(self):
+        derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+    def test_adjoint(self):
+        # Adjoint Test
+        u = np.random.rand(self.mesh.nC*self.survey.nSrc)
+        v = np.random.rand(self.mesh.nC)
+        w = np.random.rand(self.survey.dobs.shape[0])
+        wtJv = w.dot(self.p.Jvec(self.m0, v))
+        vtJtw = v.dot(self.p.Jtvec(self.m0, w))
+        passed = np.abs(wtJv - vtJtw) < 1e-8
+        print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
+        self.assertTrue(passed)
+
+    def test_dataObj(self):
+        derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+if __name__ == '__main__':
+    unittest.main()

tests/em/static/test_SIP_jvecjtvecadj.py

@@ -0,0 +1,232 @@
+import unittest
+from SimPEG import *
+import SimPEG
+from SimPEG import Mesh, Utils, EM, Maps, np, Survey
+from SimPEG.EM.Static import SIP, DC, IP
+from pymatsolver import MumpsSolver
+
+
+class IPProblemTestsCC(unittest.TestCase):
+
+    def setUp(self):
+
+        cs = 25.
+        hx = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
+        hy = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
+        hz = [(cs,0, -1.3),(cs,20)]
+        mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN")
+        blkind0 = Utils.ModelBuilder.getIndicesSphere(np.r_[-100., -100., -200.], 75., mesh.gridCC)
+        blkind1 = Utils.ModelBuilder.getIndicesSphere(np.r_[100., 100., -200.], 75., mesh.gridCC)
+        sigma = np.ones(mesh.nC)*1e-2
+        eta = np.zeros(mesh.nC)
+        tau = np.ones_like(sigma)*1.
+        eta[blkind0] = 0.1
+        eta[blkind1] = 0.1
+        tau[blkind0] = 0.1
+        tau[blkind1] = 0.01
+
+        x = mesh.vectorCCx[(mesh.vectorCCx>-155.)&(mesh.vectorCCx<155.)]
+        y = mesh.vectorCCx[(mesh.vectorCCy>-155.)&(mesh.vectorCCy<155.)]
+        Aloc = np.r_[-200., 0., 0.]
+        Bloc = np.r_[200., 0., 0.]
+        M = Utils.ndgrid(x-25.,y, np.r_[0.])
+        N = Utils.ndgrid(x+25.,y, np.r_[0.])
+
+        times = np.arange(10)*1e-3 + 1e-3
+        rx = SIP.Rx.Dipole(M, N, times)
+        src = SIP.Src.Dipole([rx], Aloc, Bloc)
+        survey = SIP.Survey([src])
+        colemap = [("eta", Maps.IdentityMap(mesh)), ("taui", Maps.IdentityMap(mesh))]
+        problem = SIP.Problem3D_CC(mesh, rho=1./sigma, mapping=colemap)
+        problem.Solver = MumpsSolver
+        problem.pair(survey)
+        mSynth = np.r_[eta, 1./tau]
+        survey.makeSyntheticData(mSynth)
+        # Now set up the problem to do some minimization
+        dmis = DataMisfit.l2_DataMisfit(survey)
+        reg = Regularization.Tikhonov(mesh)
+        opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+        invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
+        inv = Inversion.BaseInversion(invProb)
+
+        self.inv = inv
+        self.reg = reg
+        self.p =     problem
+        self.mesh = mesh
+        self.m0 = mSynth
+        self.survey = survey
+        self.dmis = dmis
+
+    def test_misfit(self):
+        derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+    def test_adjoint(self):
+        # Adjoint Test
+        u = np.random.rand(self.mesh.nC*self.survey.nSrc)
+        v = np.random.rand(self.mesh.nC*2)
+        w = np.random.rand(self.survey.dobs.shape[0])
+        wtJv = w.dot(self.p.Jvec(self.m0, v))
+        vtJtw = v.dot(self.p.Jtvec(self.m0, w))
+        passed = np.abs(wtJv - vtJtw) < 1e-10
+        print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
+        self.assertTrue(passed)
+
+    def test_dataObj(self):
+        derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+class IPProblemTestsN(unittest.TestCase):
+
+    def setUp(self):
+
+        cs = 25.
+        hx = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
+        hy = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
+        hz = [(cs,0, -1.3),(cs,20)]
+        mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN")
+        blkind0 = Utils.ModelBuilder.getIndicesSphere(np.r_[-100., -100., -200.], 75., mesh.gridCC)
+        blkind1 = Utils.ModelBuilder.getIndicesSphere(np.r_[100., 100., -200.], 75., mesh.gridCC)
+        sigma = np.ones(mesh.nC)*1e-2
+        eta = np.zeros(mesh.nC)
+        tau = np.ones_like(sigma)*1.
+        eta[blkind0] = 0.1
+        eta[blkind1] = 0.1
+        tau[blkind0] = 0.1
+        tau[blkind1] = 0.01
+
+        x = mesh.vectorCCx[(mesh.vectorCCx>-155.)&(mesh.vectorCCx<155.)]
+        y = mesh.vectorCCx[(mesh.vectorCCy>-155.)&(mesh.vectorCCy<155.)]
+        Aloc = np.r_[-200., 0., 0.]
+        Bloc = np.r_[200., 0., 0.]
+        M = Utils.ndgrid(x-25.,y, np.r_[0.])
+        N = Utils.ndgrid(x+25.,y, np.r_[0.])
+
+        times = np.arange(10)*1e-3 + 1e-3
+        rx = SIP.Rx.Dipole(M, N, times)
+        src = SIP.Src.Dipole([rx], Aloc, Bloc)
+        survey = SIP.Survey([src])
+        colemap = [("eta", Maps.IdentityMap(mesh)), ("taui", Maps.IdentityMap(mesh))]
+        problem = SIP.Problem3D_N(mesh, sigma=sigma, mapping=colemap)
+        problem.Solver = MumpsSolver
+        problem.pair(survey)
+        mSynth = np.r_[eta, 1./tau]
+        survey.makeSyntheticData(mSynth)
+        # Now set up the problem to do some minimization
+        dmis = DataMisfit.l2_DataMisfit(survey)
+        reg = Regularization.Tikhonov(mesh)
+        opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+        invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
+        inv = Inversion.BaseInversion(invProb)
+
+        self.inv = inv
+        self.reg = reg
+        self.p =     problem
+        self.mesh = mesh
+        self.m0 = mSynth
+        self.survey = survey
+        self.dmis = dmis
+
+    def test_misfit(self):
+        derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+    def test_adjoint(self):
+        # Adjoint Test
+        u = np.random.rand(self.mesh.nC*self.survey.nSrc)
+        v = np.random.rand(self.mesh.nC*2)
+        w = np.random.rand(self.survey.dobs.shape[0])
+        wtJv = w.dot(self.p.Jvec(self.m0, v))
+        vtJtw = v.dot(self.p.Jtvec(self.m0, w))
+        passed = np.abs(wtJv - vtJtw) < 1e-8
+        print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
+        self.assertTrue(passed)
+
+    def test_dataObj(self):
+        derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+class IPProblemTestsN_air(unittest.TestCase):
+
+    def setUp(self):
+
+        cs = 25.
+        hx = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
+        hy = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
+        hz = [(cs,0, -1.3),(cs,20),(cs,0, 1.3)]
+        mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCC")
+        blkind0 = Utils.ModelBuilder.getIndicesSphere(np.r_[-100., -100., -200.], 75., mesh.gridCC)
+        blkind1 = Utils.ModelBuilder.getIndicesSphere(np.r_[100., 100., -200.], 75., mesh.gridCC)
+        sigma = np.ones(mesh.nC)*1e-2
+        airind = mesh.gridCC[:,2]>0.
+        sigma[airind] = 1e-8
+        eta = np.zeros(mesh.nC)
+        tau = np.ones_like(sigma)*1.
+        eta[blkind0] = 0.1
+        eta[blkind1] = 0.1
+        tau[blkind0] = 0.1
+        tau[blkind1] = 0.01
+
+        actmapeta = Maps.InjectActiveCells(mesh, ~airind, 0.)
+        actmaptau = Maps.InjectActiveCells(mesh, ~airind, 1.)
+
+        x = mesh.vectorCCx[(mesh.vectorCCx>-155.)&(mesh.vectorCCx<155.)]
+        y = mesh.vectorCCx[(mesh.vectorCCy>-155.)&(mesh.vectorCCy<155.)]
+        Aloc = np.r_[-200., 0., 0.]
+        Bloc = np.r_[200., 0., 0.]
+        M = Utils.ndgrid(x-25.,y, np.r_[0.])
+        N = Utils.ndgrid(x+25.,y, np.r_[0.])
+
+        times = np.arange(10)*1e-3 + 1e-3
+        rx = SIP.Rx.Dipole(M, N, times)
+        src = SIP.Src.Dipole([rx], Aloc, Bloc)
+        survey = SIP.Survey([src])
+        colemap = [("eta", Maps.IdentityMap(mesh)*actmapeta), ("taui", Maps.IdentityMap(mesh)*actmaptau)]
+        problem = SIP.Problem3D_N(mesh, sigma=sigma, mapping=colemap)
+        problem.Solver = MumpsSolver
+        problem.pair(survey)
+        mSynth = np.r_[eta[~airind], 1./tau[~airind]]
+        survey.makeSyntheticData(mSynth)
+        # Now set up the problem to do some minimization
+        dmis = DataMisfit.l2_DataMisfit(survey)
+        regmap = Maps.IdentityMap(nP=int(mSynth[~airind].size*2))
+        reg = SIP.MultiRegularization(mesh, mapping=regmap, nModels=2, indActive=~airind)
+        opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+        invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
+        inv = Inversion.BaseInversion(invProb)
+
+        self.inv = inv
+        self.reg = reg
+        self.p =     problem
+        self.mesh = mesh
+        self.m0 = mSynth
+        self.survey = survey
+        self.dmis = dmis
+
+    def test_misfit(self):
+        derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+    def test_adjoint(self):
+        # Adjoint Test
+        u = np.random.rand(self.mesh.nC*self.survey.nSrc)
+        v = np.random.rand(self.mesh.nC)
+        w = np.random.rand(self.survey.dobs.shape[0])
+        wtJv = w.dot(self.p.Jvec(self.m0, v))
+        vtJtw = v.dot(self.p.Jtvec(self.m0, w))
+        passed = np.abs(wtJv - vtJtw) < 1e-8
+        print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
+        self.assertTrue(passed)
+
+    def test_dataObj(self):
+        derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
+        passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
+        self.assertTrue(passed)
+
+if __name__ == '__main__':
+    unittest.main()

tests/em/tdem/test_TDEM_forward_Analytic.py

@@ -10,7 +10,9 @@ except ImportError, e:
     MumpsSolver = SolverLU
 
 
-def halfSpaceProblemAnaDiff(meshType, sig_half=1e-2, rxOffset=50., bounds=[1e-5,1e-3], showIt=False):
+def halfSpaceProblemAnaDiff(meshType, sig_half=1e-2, rxOffset=50., bounds=None, showIt=False):
+    if bounds is None:
+        bounds = [1e-5,1e-3]
     if meshType == 'CYL':
         cs, ncx, ncz, npad = 5., 30, 10, 15
         hx = [(cs,ncx), (cs,npad,1.3)]

tests/mesh/test_InterpolationMesh2Mesh.py

@@ -1,353 +0,0 @@
-import numpy as np
-import unittest
-from SimPEG.Utils import mkvc
-from SimPEG import Mesh, Tests
-import unittest
-
-test1D = True
-test2D = True
-test3D = False
-
-call1 = lambda fun, xyz: fun(xyz)
-call2 = lambda fun, xyz: fun(xyz[:, 0], xyz[:, -1])
-call3 = lambda fun, xyz: fun(xyz[:, 0], xyz[:, 1], xyz[:, 2])
-cart_row2 = lambda g, xfun, yfun: np.c_[call2(xfun, g), call2(yfun, g)]
-cart_row3 = lambda g, xfun, yfun, zfun: np.c_[call3(xfun, g), call3(yfun, g), call3(zfun, g)]
-cartF2 = lambda M, fx, fy: np.vstack((cart_row2(M.gridFx, fx, fy), cart_row2(M.gridFy, fx, fy)))
-cartF2Cyl = lambda M, fx, fy: np.vstack((cart_row2(M.gridFx, fx, fy), cart_row2(M.gridFz, fx, fy)))
-cartE2 = lambda M, ex, ey: np.vstack((cart_row2(M.gridEx, ex, ey), cart_row2(M.gridEy, ex, ey)))
-cartE2Cyl = lambda M, ex, ey: cart_row2(M.gridEy, ex, ey)
-cartF3 = lambda M, fx, fy, fz: np.vstack((cart_row3(M.gridFx, fx, fy, fz), cart_row3(M.gridFy, fx, fy, fz), cart_row3(M.gridFz, fx, fy, fz)))
-cartE3 = lambda M, ex, ey, ez: np.vstack((cart_row3(M.gridEx, ex, ey, ez), cart_row3(M.gridEy, ex, ey, ez), cart_row3(M.gridEz, ex, ey, ez)))
-
-TOL = 1e-7
-
-if test1D:
-    class TestInterpolationMesh2Mesh_Tensor1D(Tests.OrderTest):
-
-        name = 'Mesh2Mesh Tensor1D'
-        meshSizes = [8, 16, 32]
-        meshTypes = ['uniformTensorMesh']
-        meshDimension = 1
-
-        def getError(self):
-            funX = lambda x: np.cos(2*np.pi*x)
-
-            mesh2, _ = self.makeMesh(self.M.nC-1, meshType=self._meshType, meshDimension=self.meshDimension )
-            ana = call1(funX, getattr(mesh2, 'grid%s'%self.type))
-
-            v = call1(funX, getattr(self.M, 'grid%s'%self.type))
-            P = self.M.getInterpolationMatMesh2Mesh(mesh2, locType=self.type)
-            num = P*v
-
-            return np.linalg.norm((num - ana), np.inf)
-
-        def test_orderCC_1D(self):
-            self.type = 'CC'
-            self.name = 'Mesh2Mesh Tensor1D: CC'
-            self.orderTest()
-
-        def test_orderN_1D(self):
-            self.type = 'N'
-            self.name = 'Mesh2Mesh Tensor1D: N'
-            self.orderTest()
-
-        def test_orderEx_1D(self):
-            self.type = 'Ex'
-            self.name = 'Mesh2Mesh Tensor1D: Ex'
-            self.orderTest()
-
-        def test_orderFx_1D(self):
-            self.type = 'Fx'
-            self.name = 'Mesh2Mesh Tensor1D: Fx'
-            self.orderTest()
-
-if test2D:
-    class TestInterpolationMesh2Mesh_Tensor2D(Tests.OrderTest):
-
-        name = 'Mesh2Mesh Tensor2D'
-        meshSizes = [4, 8, 16]
-        meshTypes = ['uniformTensorMesh']
-        meshDimension = 2
-
-        def getError(self):
-            funX = lambda x, y: np.cos(2*np.pi*y)
-            funY = lambda x, y: np.cos(2*np.pi*x)
-
-            mesh2, _ = self.makeMesh(self.M.nC-1, meshType=self._meshType, meshDimension=self.meshDimension )
-
-            if 'x' in self.type:
-                ana = call2(funX, getattr(mesh2, 'grid%s'%self.type))
-            elif 'y' in self.type:
-                ana = call2(funY, getattr(mesh2, 'grid%s'%self.type))
-            elif 'F' in self.type:
-                ana = cartF2(mesh2, funX, funY)
-                ana = mesh2.projectFaceVector(ana)
-            elif 'E' in self.type:
-                ana = cartE2(mesh2, funX, funY)
-                ana = mesh2.projectEdgeVector(ana)
-            else:
-                ana = call2(funX, getattr(mesh2, 'grid%s'%self.type))
-
-
-            if 'F' in self.type:
-                v = cartF2(self.M, funX, funY)
-                if 'x' in self.type or 'y' in self.type:
-                    v = self.M.projectFaceVector(v)
-                else:
-                    v = mkvc(v)
-            elif 'E' in self.type:
-                v = cartE2(self.M, funX, funY)
-                if 'x' in self.type or 'y' in self.type:
-                    v = self.M.projectEdgeVector(v)
-                else:
-                    v = mkvc(v)
-            elif 'CC' == self.type:
-                v = call2(funX, self.M.gridCC)
-            elif 'N' == self.type:
-                v = call2(funX, self.M.gridN)
-
-            P = self.M.getInterpolationMatMesh2Mesh(mesh2, locType=self.type)
-            # print P.shape, v.shape
-            num = P*v
-
-            return np.linalg.norm((num - ana), np.inf)
-
-        def test_orderCC_2D(self):
-            self.type = 'CC'
-            self.name = 'Mesh2Mesh Tensor2D: CC'
-            self.orderTest()
-
-        def test_orderN_2D(self):
-            self.type = 'N'
-            self.name = 'Mesh2Mesh Tensor2D: N'
-            self.orderTest()
-
-        def test_orderE_2D(self):
-            self.type = 'E'
-            self.name = 'Mesh2Mesh Tensor2D: E'
-            self.orderTest()
-
-        def test_orderEx_2D(self):
-            self.type = 'Ex'
-            self.name = 'Mesh2Mesh Tensor2D: Ex'
-            self.orderTest()
-
-        def test_orderEy_2D(self):
-            self.type = 'Ey'
-            self.name = 'Mesh2Mesh Tensor2D: Ey'
-            self.orderTest()
-
-        def test_orderF_2D(self):
-            self.type = 'F'
-            self.name = 'Mesh2Mesh Tensor2D: F'
-            self.orderTest()
-
-        def test_orderFx_2D(self):
-            self.type = 'Fx'
-            self.name = 'Mesh2Mesh Tensor2D: Fx'
-            self.orderTest()
-
-        def test_orderFy_2D(self):
-            self.type = 'Fy'
-            self.name = 'Mesh2Mesh Tensor2D: Fy'
-            self.orderTest()
-
-    class TestInterpolationMesh2Mesh_Cyl(Tests.OrderTest):
-
-        name = 'Mesh2Mesh Cyl'
-        meshSizes = [4, 8, 16]
-        meshTypes = ['uniformCylMesh']
-        meshDimension = 2
-
-        def getError(self):
-            funX = lambda x, y: np.cos(2*np.pi*y)
-            funY = lambda x, y: np.cos(2*np.pi*x)
-
-            mesh2, _ = self.makeMesh(self.M.nC-1, meshType=self._meshType, meshDimension=self.meshDimension )
-
-            if 'x' in self.type:
-                ana = call2(funX, getattr(mesh2, 'grid%s'%self.type))
-            elif 'y' in self.type:
-                ana = call2(funY, getattr(mesh2, 'grid%s'%self.type))
-            elif 'z' in self.type:
-                ana = call2(funY, getattr(mesh2, 'grid%s'%self.type))
-            elif 'F' in self.type:
-                ana = cartF2Cyl(mesh2, funX, funY)
-                ana = np.c_[ana[:,0], np.zeros_like(ana[:,0]), ana[:,1]]
-                ana = mesh2.projectFaceVector(ana)
-            elif 'E' in self.type:
-                ana = cartE2Cyl(mesh2, funX, funY)
-                ana = np.c_[np.zeros_like(ana[:,1]),ana[:,1],np.zeros_like(ana[:,1])]
-                ana = mesh2.projectEdgeVector(ana)
-            else:
-                ana = call2(funX, getattr(mesh2, 'grid%s'%self.type))
-
-
-            if 'F' in self.type:
-                v = cartF2Cyl(self.M, funX, funY)
-                v = np.c_[v[:,0], np.zeros_like(v[:,0]),v[:,1]]
-                if 'x' in self.type or 'z' in self.type:
-                    v = self.M.projectFaceVector(v)
-                else:
-                    v = np.c_[v[:,0], v[:,2]]
-                    v = mkvc(v)
-            elif 'E' in self.type:
-                v = cartE2Cyl(self.M, funX, funY)
-                v = np.c_[np.zeros_like(v[:,1]), v[:,1],np.zeros_like(v[:,1])]
-                v = self.M.projectEdgeVector(v)
-
-            elif 'CC' == self.type:
-                v = call2(funX, self.M.gridCC)
-            elif 'N' == self.type:
-                v = call2(funX, self.M.gridN)
-
-            P = self.M.getInterpolationMatMesh2Mesh(mesh2, locType=self.type)
-            num = P*v
-
-            return np.linalg.norm((num - ana), np.inf)
-
-        def test_orderCC_Cyl(self):
-            self.type = 'CC'
-            self.name = 'Mesh2Mesh Tensor2D: CC'
-            self.orderTest()
-
-        def test_orderN_Cyl(self):
-            self.type = 'N'
-            self.name = 'Mesh2Mesh Tensor2D: N'
-            self.orderTest()
-
-        def test_orderE_Cyl(self):
-            self.type = 'E'
-            self.name = 'Mesh2Mesh Tensor2D: E'
-            self.orderTest()
-
-        def test_orderEy_Cyl(self):
-            self.type = 'Ey'
-            self.name = 'Mesh2Mesh Tensor2D: Ey'
-            self.orderTest()
-
-        def test_orderF_Cyl(self):
-            self.type = 'F'
-            self.name = 'Mesh2Mesh Tensor2D: F'
-            self.orderTest()
-
-        def test_orderFx_Cyl(self):
-            self.type = 'Fx'
-            self.name = 'Mesh2Mesh Tensor2D: Fx'
-            self.orderTest()
-
-        def test_orderFz_Cyl(self):
-            self.type = 'Fz'
-            self.name = 'Mesh2Mesh Tensor2D: Fz'
-            self.orderTest()
-
-if test3D:
-    class TestInterpolationMesh2Mesh_Tensor3D(Tests.OrderTest):
-
-        name = 'Mesh2Mesh Tensor3D'
-        meshSizes = [4, 8, 16]
-        meshTypes = ['uniformTensorMesh']
-        meshDimension = 3
-
-        def getError(self):
-            funX = lambda x, y, z: np.cos(2*np.pi*y)
-            funY = lambda x, y, z: np.cos(2*np.pi*z)
-            funZ = lambda x, y, z: np.cos(2*np.pi*x)
-
-            mesh2, _ = self.makeMesh(self.M.nC-1, meshType=self._meshType, meshDimension=self.meshDimension )
-
-            if 'x' in self.type:
-                ana = call3(funX, getattr(mesh2, 'grid%s'%self.type))
-            elif 'y' in self.type:
-                ana = call3(funY, getattr(mesh2, 'grid%s'%self.type))
-            elif 'z' in self.type:
-                ana = call3(funZ, getattr(mesh2, 'grid%s'%self.type))
-            elif 'F' in self.type:
-                ana = cartF3(mesh2, funX, funY, funZ)
-                ana = mesh2.projectFaceVector(ana)
-            elif 'E' in self.type:
-                ana = cartE3(mesh2, funX, funY, funZ)
-                ana = mesh2.projectFaceVector(ana)
-            else:
-                ana = call3(funX, getattr(mesh2, 'grid%s'%self.type))
-
-
-            if 'F' in self.type:
-                v = cartF3(self.M, funX, funY, funZ)
-                if 'x' in self.type or 'y' in self.type or 'z' in self.type:
-                    v = self.M.projectFaceVector(v)
-                else:
-                    v = mkvc(v)
-            elif 'E' in self.type:
-                v = cartE3(self.M, funX, funY, funZ)
-                if 'x' in self.type or 'y' in self.type or 'z' in self.type:
-                    v = self.M.projectFaceVector(v)
-                else:
-                    v = mkvc(v)
-            elif 'CC' == self.type:
-                v = call3(funX, self.M.gridCC)
-            elif 'N' == self.type:
-                v = call3(funX, self.M.gridN)
-
-            P = self.M.getInterpolationMatMesh2Mesh(mesh2, locType=self.type)
-            # print P.shape, v.shape
-            num = P*v
-
-            return np.linalg.norm((num - ana), np.inf)
-
-        def test_orderCC_3D(self):
-            self.type = 'CC'
-            self.name = 'Mesh2Mesh Tensor3D: CC'
-            self.orderTest()
-
-        def test_orderN_3D(self):
-            self.type = 'N'
-            self.name = 'Mesh2Mesh Tensor3D: N'
-            self.orderTest()
-
-        def test_orderE_3D(self):
-            self.type = 'E'
-            self.name = 'Mesh2Mesh Tensor3D: E'
-            self.orderTest()
-
-        def test_orderEx_3D(self):
-            self.type = 'Ex'
-            self.name = 'Mesh2Mesh Tensor3D: Ex'
-            self.orderTest()
-
-        def test_orderEy_3D(self):
-            self.type = 'Ey'
-            self.name = 'Mesh2Mesh Tensor3D: Ey'
-            self.orderTest()
-
-        def test_orderEz_3D(self):
-            self.type = 'Ez'
-            self.name = 'Mesh2Mesh Tensor3D: Ez'
-            self.orderTest()
-
-        def test_orderF_3D(self):
-            self.type = 'F'
-            self.name = 'Mesh2Mesh Tensor3D: F'
-            self.orderTest()
-
-        def test_orderFx_3D(self):
-            self.type = 'Fx'
-            self.name = 'Mesh2Mesh Tensor3D: Fx'
-            self.orderTest()
-
-        def test_orderFy_3D(self):
-            self.type = 'Fy'
-            self.name = 'Mesh2Mesh Tensor3D: Fy'
-            self.orderTest()
-
-        def test_orderFz_3D(self):
-            self.type = 'Fz'
-            self.name = 'Mesh2Mesh Tensor3D: Fz'
-            self.orderTest()
-
-
-
-
-if __name__ == '__main__':
-    unittest.main()

tests/mesh/test_Mixed_boundaryPoisson.py

@@ -0,0 +1,411 @@
+import numpy as np
+import scipy.sparse as sp
+import unittest
+import matplotlib.pyplot as plt
+from SimPEG import *
+
+MESHTYPES = ['uniformTensorMesh']
+
+def getxBCyBC_CC(mesh, alpha, beta, gamma):
+# def getxBCyBC(mesh, alpha, beta, gamma):
+    """
+    This is a subfunction generating mixed-boundary condition:
+
+    .. math::
+
+        \nabla \cdot \vec{j} = -\nabla \cdot \vec{j}_s = q
+
+        \rho \vec{j} = -\nabla \phi \phi
+
+        \alpha \phi + \beta \frac{\partial \phi}{\partial r} = \gamma \ at \ r = \partial \Omega
+
+        xBC = f_1(\alpha, \beta, \gamma)
+        yBC = f(\alpha, \beta, \gamma)
+
+    Computes xBC and yBC for cell-centered discretizations
+    """
+    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]
+        h_xm, h_xp = mesh.hx[0], mesh.hx[-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)
+
+        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")
+
+        fxm,fxp,fym,fyp = mesh.faceBoundaryInd
+        nBC = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
+
+        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]
+
+        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
+        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
+
+        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 = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
+
+        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[4], beta[4], gamma[4]
+        alpha_zp, beta_zp, gamma_zp = alpha[5], beta[5], gamma[5]
+
+        # 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]
+
+        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
+        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
+        h_zm, h_zp = mesh.hz[0]*np.ones_like(alpha_zm), mesh.hz[-1]*np.ones_like(alpha_zp)
+
+        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_CC(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_CC(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[:,2]), np.ones_like(gBFzp[:,2])
+        beta_zm, beta_zp =  np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
+
+
+        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_funZ(gBFzm), phideriv_funZ(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_CC(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()