try using list for Jv instead of datapair - has been seen to cause memory leaks

don't use Zero() in mapping derivs)
naming update
2026-09-13 13:03:14 +08:00 · 2016-06-29 15:55:34 -07:00 · 2016-06-29 08:45:45 -07:00 · 2016-06-28 08:15:19 -07:00 · 2016-06-26 15:24:33 -07:00 · 2016-06-25 16:51:18 -07:00
82 changed files with 6414 additions and 868 deletions
@@ -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:
@@ -1,12 +1,16 @@
-from SimPEG import np
+from SimPEG import np, Utils
 import BaseDC as DC
 import BaseDC as IP
+import warnings

 def getActiveindfromTopo(mesh, topo):
 # def genActiveindfromTopo(mesh, topo):
    """
        Get active indices from topography
    """
+    warnings.warn(
+            "`getActiveindfromTopo` is deprecated and will be removed in future versions. Use `SimPEG.Utils.surface2ind_topo` instead",
+            FutureWarning)
    from scipy.interpolate import NearestNDInterpolator
    if mesh.dim==3:
        nCxy = mesh.nCx*mesh.nCy
@@ -28,6 +32,9 @@ def gettopoCC(mesh, airind):
    """
        Get topography from active indices of mesh.
    """
+    warnings.warn(
+            "`gettopoCC` is deprecated and will be removed in future versions. Use `SimPEG.Utils.surface2ind_topo` instead",
+            FutureWarning)
    mesh2D = Mesh.TensorMesh([mesh.hx, mesh.hy], mesh.x0[:2])
    zc = mesh.gridCC[:,2]
    AIRIND = airind.reshape((mesh.vnC[0]*mesh.vnC[1],mesh.vnC[2]), order='F')
@@ -118,34 +125,27 @@ def readUBC_DC3Dobstopo(filename,mesh,topo,probType="CC"):

 def readUBC_DC2DModel(fileName):
    """
-        Read UBC GIF 2DTensor model and generate 2D Tensor model in simpeg
+    Read UBC GIF 2DTensor model and generate 2D Tensor model in simpeg

-        Input:
-        :param fileName, path to the UBC GIF 2D model file
-
-        Output:
-        :param SimPEG TensorMesh 2D object
-        :return
-
-        Created on Thu Nov 12 13:14:10 2015
-
-        @author: dominiquef
+    :param string fileName: path to the UBC GIF 2D model file
+    :rtype: TensorMesh
+    :return: SimPEG TensorMesh 2D object

    """
    from SimPEG import np, mkvc

    # Open fileand skip header... assume that we know the mesh already
-    obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
+    obsfile = np.genfromtxt(fileName, delimiter=' \n', dtype=np.str, comments='!')

-    dim = np.array(obsfile[0].split(),dtype=float)
+    dim = np.array(obsfile[0].split(), dtype=float)

-    temp = np.array(obsfile[1].split(),dtype=float)
+    temp = np.array(obsfile[1].split(), dtype=float)

    if len(temp) > 1:
        model = np.zeros(dim)

        for ii in range(len(obsfile)-1):
-            mm = np.array(obsfile[ii+1].split(),dtype=float)
+            mm = np.array(obsfile[ii+1].split(), dtype=float)
            model[:,ii] = mm

        model = model[:,::-1]
@@ -153,10 +153,10 @@ def readUBC_DC2DModel(fileName):
    else:

        if len(obsfile[1:])==1:
-            mm = np.array(obsfile[1:].split(),dtype=float)
+            mm = np.array(obsfile[1:].split(), dtype=float)

        else:
-            mm = np.array(obsfile[1:],dtype=float)
+            mm = np.array(obsfile[1:], dtype=float)

        # Permute the second dimension to flip the order
        model = mm.reshape(dim[1],dim[0])
@@ -169,32 +169,25 @@ def readUBC_DC2DModel(fileName):

    return model

-def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", clim=None):
+
+def plot_pseudoSection(DCsurvey, axs, surveyType='dipole-dipole', unitType='volt', clim=None, cblabel=True, axlabel = True, colorbar = True, contour = None):
    """
-        Read list of 2D tx-rx location and plot a speudo-section of apparent
-        resistivity.
+    Read list of 2D tx-rx location and plot a speudo-section of apparent
+    resistivity.

-        Assumes flat topo for now...
+    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
+    :param SurveyDC DCsurvey:
+    :param string surveyType: Either 'pole-dipole'  | 'dipole-dipole'
+    :param string unitType: Either 'appResistivity' | 'appConductivity'  | 'volt'
+    :rtype: matplotlib.plt
+    :return: figure scatter plot overlayed on image

    """
    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 = []
@@ -221,76 +214,92 @@ def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", clim=None):
        Cmid = (Tx[0][0] + Tx[1][0])/2
        Pmid = (Rx[0][:,0] + Rx[1][:,0])/2

-        # Change output for dtype
-        if dtype == 'volt':
+        # Change output for unitType
+        if unitType == 'volt':

            rho = np.hstack([rho,data])

        else:

            # Compute pant leg of apparent rho
-            if stype == 'pdp':
+            if surveyType == 'pole-dipole':

                leg =  data * 2*np.pi  * MA * ( MA + MN ) / MN

-            elif stype == 'dpdp':
+            elif surveyType == 'dipole-dipole':

                leg = data * 2*np.pi / ( 1/MA - 1/MB - 1/NB + 1/NA )

            else:
-                print """dtype must be 'pdp'(pole-dipole) | 'dpdp' (dipole-dipole) """
+                print """unitType must be 'pole-dipole' | 'dipole-dipole' """
                break


-            if dtype == 'appc':
+            if unitType == 'appConductivity':

                leg = np.log10(abs(1./leg))
                rho = np.hstack([rho,leg])

-            elif dtype == 'appr':
+            elif unitType == 'appResistivity':

                leg = np.log10(abs(leg))
                rho = np.hstack([rho,leg])

            else:
-                print """dtype must be 'appr' | 'appc' | 'volt' """
+                print """unitType must be 'appResistivity' | 'appConductivity' | 'volt' """
                break

        midx = np.hstack([midx, ( Cmid + Pmid )/2 ])
-        midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + z0 ])
-
-    ax = axs
+        midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + (Tx[0][2] + Tx[1][2])/2 ])

    # 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')

+    # Scale the color scheme
    if clim == None:
        vmin, vmax = rho.min(), rho.max()
    else:
        vmin, vmax = clim[0], clim[1]

+    # Plot data
    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
-    ax.scatter(midx,midz,s=10,c=rho.T, vmin =vmin, vmax = vmax, clim=(vmin, vmax))

-    #ax.set_xticklabels([])
-    #ax.set_yticklabels([])
+    ph = plt.pcolormesh(grid_x[:,0],grid_z[0,:],grid_rho.T, vmin = vmin, vmax = vmax)
+    plt.gca().tick_params(axis='both', which='major', labelsize=8)
+
+    if contour is not None:
+        plt.contour(grid_x,grid_z,grid_rho,levels = contour,colors = 'r', vmin = vmin, vmax = vmax)
+
+    # Add scatter points
+    axs.scatter(midx,midz,s=10,c=rho.T, vmin = vmin, vmax = vmax)
+
+    if colorbar:
+
+        if unitType == 'volt':
+            cbar = plt.colorbar(ph, ax = axs, format="%4.1f",fraction=0.04,orientation="horizontal")
+
+        else:
+            cbar = plt.colorbar(ph, ax = axs, 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 unitType == 'appConductivity':
+                cbar.set_label("App.Cond",size=12)
+            elif unitType == 'appResistivity':
+                cbar.set_label("App.Res.",size=12)
+            elif unitType == 'volt':
+                cbar.set_label("Potential (V)",size=12)
+
+
+    if not axlabel:
+        axs.set_xticklabels([])
+        axs.set_yticklabels([])

    plt.gca().set_aspect('equal', adjustable='box')

@@ -298,27 +307,24 @@ def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", clim=None):

    return ph

-def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
+def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
    """
-        Load in endpoints and survey specifications to generate Tx, Rx location
-        stations.
+    Load in endpoints and survey specifications to generate Tx, Rx location
+    stations.

-        Assumes flat topo for now...
+    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
+    :param numpy.array endl: input endpoints [[x1, y1] , [x2, y2]]
+    :param Mesh mesh: SimPEG mesh object
+    :param string surveyType: 'dipole-dipole' | 'pole-dipole' | 'gradient'
+    :param float AM_sep: transmitter (A) - receiver (M) seperation
+    :param float b: receiver dipole seperation
+    :param float nrx: 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
+    :rtype: DC.Survey, Src, Rx
+    :returns: DC survey, Source

-        Created on Wed December 9th, 2015
-
-        @author: dominiquef
-        !! Require clean up to deal with DCsurvey
+    !! Require clean up to deal with DCsurvey
    """

    from SimPEG import np
@@ -334,17 +340,17 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
    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 )
+    nstn = np.floor( dl_len / AM_sep )

    # 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
+    stn_x = endl[0,0] + np.array(range(int(nstn)))*dl_x*AM_sep
+    stn_y = endl[0,1] + np.array(range(int(nstn)))*dl_y*AM_sep

    # Create line of P1 locations
    M = np.c_[stn_x, stn_y, np.ones(nstn).T*mesh.vectorNz[-1]]

    # Create line of P2 locations
-    N = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+    N = np.c_[stn_x+AM_sep*dl_x, stn_y+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]

    ## Build list of Tx-Rx locations depending on survey type
    # Dipole-dipole: Moving tx with [a] spacing -> [AB a MN1 a MN2 ... a MNn]
@@ -354,14 +360,14 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
    SrcList = []


-    if stype != 'gradient':
+    if surveyType != 'gradient':

        for ii in range(0, int(nstn)-1):


-            if stype == 'dpdp':
+            if surveyType == 'dipole-dipole':
                tx = np.c_[M[ii,:],N[ii,:]]
-            elif stype == 'pdp':
+            elif surveyType == 'pole-dipole':
                tx = np.c_[M[ii,:],M[ii,:]]

            # Rx.append(np.c_[M[ii+1:indx,:],N[ii+1:indx,:]])
@@ -370,33 +376,33 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
            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])
+            nstn = np.min([np.floor( (AB - MN_sep) / AM_sep ) , nrx])

            # 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
+            stn_x = N[ii,0] + dl_x*MN_sep + np.array(range(int(nstn)))*dl_x*AM_sep
+            stn_y = N[ii,1] + dl_y*MN_sep + np.array(range(int(nstn)))*dl_y*AM_sep

            # Create receiver poles
            # Create line of P1 locations
            P1 = np.c_[stn_x, stn_y, np.ones(nstn).T*mesh.vectorNz[-1]]

            # Create line of P2 locations
-            P2 = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+            P2 = np.c_[stn_x+AM_sep*dl_x, stn_y+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]

            Rx.append(np.c_[P1,P2])
            rxClass = DC.RxDipole(P1, P2)
            Tx.append(tx)
-            if stype == 'dpdp':
+            if surveyType == 'dipole-dipole':
                srcClass = DC.SrcDipole([rxClass], M[ii,:],N[ii,:])
-            elif stype == 'pdp':
+            elif surveyType == 'pole-dipole':
                srcClass = DC.SrcDipole([rxClass], M[ii,:],M[ii,:])
            SrcList.append(srcClass)

-    elif stype == 'gradient':
+    elif surveyType == '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
@@ -404,23 +410,23 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
        Tx.append(np.c_[M[0,:],N[-1,:]])

        # Get the edge limit of survey area
-        min_x = endl[0,0] + dl_x * b
-        min_y = endl[0,1] + dl_y * b
+        min_x = endl[0,0] + dl_x * MN_sep
+        min_y = endl[0,1] + dl_y * MN_sep

-        max_x = endl[1,0] - dl_x * b
-        max_y = endl[1,1] - dl_y * b
+        max_x = endl[1,0] - dl_x * MN_sep
+        max_y = endl[1,1] - dl_y * MN_sep

        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 )
+        nstn = np.floor( box_l / AM_sep )

        # 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
+        stn_x = min_x + np.array(range(int(nstn)))*dl_x*AM_sep
+        stn_y = min_y + np.array(range(int(nstn)))*dl_y*AM_sep

        # Define number of cross lines
-        nlin = int(np.floor( box_w / a ))
+        nlin = int(np.floor( box_w / AM_sep ))
        lind = range(-nlin,nlin+1)

        ngrad = nstn * len(lind)
@@ -429,12 +435,12 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
        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
+            lxx = stn_x - lind[ii]*AM_sep*dl_y
+            lyy = stn_y + lind[ii]*AM_sep*dl_x


            M = np.c_[ lxx, lyy , np.ones(nstn).T*mesh.vectorNz[-1]]
-            N = np.c_[ lxx+a*dl_x, lyy+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+            N = np.c_[ lxx+AM_sep*dl_x, lyy+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]

            rx[(ii*nstn):((ii+1)*nstn),:] = np.c_[M,N]

@@ -443,37 +449,37 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
        srcClass = DC.SrcDipole([rxClass], M[0,:], N[-1,:])
        SrcList.append(srcClass)
    else:
-        print """stype must be either 'pdp', 'dpdp' or 'gradient'. """
+        print """surveyType must be either 'pole-dipole', 'dipole-dipole' or 'gradient'. """

    survey = DC.SurveyDC(SrcList)
    return survey, Tx, Rx

-def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):
+
+def writeUBC_DCobs(fileName, DCsurvey, dim, surveyType, iptype = 0):
    """
        Write UBC GIF DCIP 2D or 3D observation file

-        Input:
-        :string fileName -> including path where the file is written out
-        :DCsurvey -> DC survey class object
-        :string dtype ->  either '2D' | '3D'
-        :string  stype ->  either 'SURFACE' | 'GENERAL'
-
-        Output:
-        :param UBC2D-Data file
-        :return
-
-        Last edit: February 16th, 2016
-
-        @author: dominiquef
-
+        :param string fileName: including path where the file is written out
+        :param Survey DCsurvey: DC survey class object
+        :param string dim:  either '2D' | '3D'
+        :param string surveyType:  either 'SURFACE' | 'GENERAL'
+        :rtype: file
+        :return: UBC2D-Data file
    """
+
    from SimPEG import mkvc

-    assert (dtype=='2D') | (dtype=='3D'), "Data must be either '2D' | '3D'"
-    assert (stype=='SURFACE') | (stype=='GENERAL') | (stype=='SIMPLE'), "Data must be either 'SURFACE' | 'GENERAL' | 'SIMPLE'"
+    assert (dim=='2D') | (dim=='3D'), "Data must be either '2D' | '3D'"
+    assert (surveyType=='SURFACE') | (surveyType=='GENERAL') | (surveyType=='SIMPLE'), "Data must be either 'SURFACE' | 'GENERAL' | 'SIMPLE'"

    fid = open(fileName,'w')
-    fid.write('! ' + stype + ' FORMAT\n')
+    fid.write('! ' + surveyType + ' FORMAT\n')
+
+    if iptype!=0:
+        fid.write('IPTYPE=%i\n'%iptype)
+
+    else:
+        fid.write('! ' + stype + ' FORMAT\n')

    count = 0

@@ -488,10 +494,10 @@ def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):
        M = rx[0]
        N = rx[1]

-        # Adapt source-receiver location for dtype and stype
-        if dtype=='2D':
+        # Adapt source-receiver location for dim and surveyType
+        if dim=='2D':

-            if stype == 'SIMPLE':
+            if surveyType == 'SIMPLE':

                #fid.writelines("%e " % ii for ii in mkvc(tx[0,:]))
                A = np.repeat(tx[0,0],M.shape[0],axis=0)
@@ -504,41 +510,49 @@ def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):

            else:

-                if stype == 'SURFACE':
+                if surveyType == 'SURFACE':

-                    fid.writelines("%e " % ii for ii in mkvc(tx[0,:]))
+                    fid.writelines("%f " % ii for ii in mkvc(tx[0,:]))
                    M = M[:,0]
                    N = N[:,0]

-                if stype == 'GENERAL':
+                if surveyType == 'GENERAL':
+
+                    # Flip sign for z-elevation to depth
+                    tx[2::2,:] = -tx[2::2,:]

                    fid.writelines("%e " % ii for ii in mkvc(tx[::2,:]))
                    M = M[:,0::2]
                    N = N[:,0::2]

+                    # Flip sign for z-elevation to depth
+                    M[:,1::2] = -M[:,1::2]
+                    N[:,1::2] = -N[:,1::2]
+
                fid.write('%i\n'% nD)
-                np.savetxt(fid, np.c_[ M, N , DCsurvey.dobs[count:count+nD], DCsurvey.std[count:count+nD] ], fmt='%e',delimiter=' ',newline='\n')
+                np.savetxt(fid, np.c_[ M, N , DCsurvey.dobs[count:count+nD], DCsurvey.std[count:count+nD] ], fmt='%f',delimiter=' ',newline='\n')

-        if dtype=='3D':
+        if dim=='3D':

-            if stype == 'SURFACE':
+            if surveyType == 'SURFACE':

                fid.writelines("%e " % ii for ii in mkvc(tx[0:2,:]))
                M = M[:,0:2]
                N = N[:,0:2]

-            if stype == 'GENERAL':
+            if surveyType == 'GENERAL':

-                fid.writelines("%e " % ii for ii in mkvc(tx))
+                fid.writelines("%e " % ii for ii in mkvc(tx[0:3,:]))

            fid.write('%i\n'% nD)
            np.savetxt(fid, np.c_[ M, N , DCsurvey.dobs[count:count+nD], DCsurvey.std[count:count+nD] ], fmt='%e',delimiter=' ',newline='\n')
+            fid.write('\n')

        count += nD

    fid.close()

-def convertObs_DC3D_to_2D(DCsurvey,lineID, flag = 'local'):
+def convertObs_DC3D_to_2D(DCsurvey, lineID, flag='local'):
    """
        Read DC survey and projects the coordinate system
        according to the flag = 'Xloc' | 'Yloc' | 'local' (default)
@@ -547,15 +561,9 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID, flag = 'local'):

        The Z value is preserved, but Y coordinates zeroed.

-        Input:
-        :param survey3D
-
-        Output:
-        :figure survey2D
-
-        Edited April 6th, 2016
-
-        @author: dominiquef
+        :param DC.Survey survey3D: 3D simpeg DC survey
+        :rtype: DC.Survey
+        :return: survey2D

    """
    from SimPEG import np
@@ -641,50 +649,53 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID, flag = 'local'):

    return DCsurvey2D

-def readUBC_DC3Dobs(fileName):
+def readUBC_DC3Dobs(fileName, rtype = 'DC'):
    """
-        Read UBC GIF DCIP 3D observation file and generate survey
+        Read UBC GIF IP 3D observation file and generate survey

-        Input:
-        :param fileName, path to the UBC GIF 3D obs file
-
-        Output:
-        :param DCIPsurvey
-        :return
-
-        Created on Mon April 6th, 2015
-
-        @author: dominiquef
+        :param string fileName:, path to the UBC GIF 3D obs file
+        :rtype: Survey
+        :return: DCIPsurvey

    """
+    zflag = True # Flag for z value provided

    # Load file
-    obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
+    if rtype == 'IP':
+        obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='IPTYPE')
+
+    elif rtype == 'DC':
+        obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
+
+    else:
+        print "rtype must be 'DC'(default) | 'IP'"

    # Pre-allocate
    srcLists = []
    Rx = []
    d = []
    wd = []
-    zflag = True # Flag for z value provided
+

    # Countdown for number of obs/tx
    count = 0
    for ii in range(obsfile.shape[0]):

+        # Skip if blank line
        if not obsfile[ii]:
            continue

-        # First line is transmitter with number of receivers
+        # First line or end of a transmitter block, read transmitter info
        if count==0:
-
-            temp = (np.fromstring(obsfile[ii], dtype=float,sep=' ').T)
+            # Read the line
+            temp = (np.fromstring(obsfile[ii], dtype=float, sep=' ').T)
            count = int(temp[-1])

            # Check if z value is provided, if False -> nan
            if len(temp)==5:
-                tx = np.r_[temp[0:2],np.nan,temp[0:2],np.nan]
-                zflag = False
+                tx = np.r_[temp[0:2],np.nan,temp[2:4],np.nan]
+
+                zflag = False # Pass on the flag to the receiver loc

            else:
                tx = temp[:-1]
@@ -692,8 +703,16 @@ def readUBC_DC3Dobs(fileName):
            rx = []
            continue

-        temp = np.fromstring(obsfile[ii], dtype=float,sep=' ')
+        temp = np.fromstring(obsfile[ii], dtype=float,sep=' ') # Get the string

+        # Filter out negative IP
+#        if temp[-2] < 0:
+#            count = count -1
+#            print "Negative!"
+#
+#        else:
+
+        # If the Z-location is provided, otherwise put nan
        if zflag:

            rx.append(temp[:-2])
@@ -703,7 +722,7 @@ def readUBC_DC3Dobs(fileName):
                wd.append(temp[-1])

        else:
-            rx.append(np.r_[temp[0:2],np.nan,temp[0:2],np.nan] )
+            rx.append(np.r_[temp[0:2],np.nan,temp[2:4],np.nan] )
            # Check if there is data with the location
            if len(temp)==6:
                d.append(temp[-2])
@@ -711,7 +730,7 @@ def readUBC_DC3Dobs(fileName):

        count = count -1

-        # Reach the end of transmitter block
+        # Reach the end of transmitter block, append the src, rx and continue
        if count == 0:
            rx = np.asarray(rx)
            Rx = DC.RxDipole(rx[:,:3],rx[:,3:])
@@ -730,17 +749,9 @@ def readUBC_DC2Dobs(fileName):
        ------- NEEDS TO BE UPDATED ------
        Read UBC GIF 2D observation file and generate arrays for tx-rx location

-        Input:
-        :param fileName, path to the UBC GIF 2D model file
-
-        Output:
-        :param rx, tx
-        :return
-
-        Created on Thu Nov 12 13:14:10 2015
-
-        @author: dominiquef
-
+        :param string fileName: path to the UBC GIF 2D model file
+        :rtype: (DC.Src, DC.Rx, ??, ??)
+        :return: source_locs, rx_locs, ??, ??
    """

    from SimPEG import np
@@ -780,11 +791,9 @@ 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
+        :param string fileName: path to the UBC GIF 3D obs file
+        :rtype: DC.Survey
+        :return: DCsurvey

        Created on Mon March 9th, 2016 << Doug's 70th Birthday !! >>

@@ -846,12 +855,9 @@ def readUBC_DC2DMesh(fileName):
    """
        Read UBC GIF 2DTensor mesh and generate 2D Tensor mesh in simpeg

-        Input:
-        :param fileName, path to the UBC GIF mesh file
-
-        Output:
-        :param SimPEG TensorMesh 2D object
-        :return
+        :param string fileName: path to the UBC GIF mesh file
+        :rtype: Mesh.TensorMesh
+        :return: SimPEG TensorMesh 2D object

        Created on Thu Nov 12 13:14:10 2015

@@ -917,12 +923,9 @@ def xy_2_lineID(DCsurvey):
        they were collected. May need to generalize for random
        point locations, but will be more expensive

-        Input:
-        :param DCdict Vectors of station location
-
-        Output:
-        :param LineID Vector of integers
-        :return
+        :param numpy.array DCdict: Vectors of station location
+        :rtype: numpy.array
+        :return: LineID Vector of integers

        Created on Thu Feb 11, 2015

@@ -146,10 +146,15 @@ class BetaSchedule(InversionDirective):

 class TargetMisfit(InversionDirective):

+    chifact = 1.
+    phi_d_star = None
+
    @property
    def target(self):
        if getattr(self, '_target', None) is None:
-            self._target = self.survey.nD*0.5
+            if self.phi_d_star is None:
+                self.phi_d_star = 0.5 * self.survey.nD
+            self._target = self.chifact * self.phi_d_star # the factor of 0.5 is because we do phid = 0.5*|| dpred - dobs||^2
        return self._target
    @target.setter
    def target(self, val):
@@ -222,7 +227,7 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
            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:
+        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:
@@ -237,39 +242,6 @@ 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.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):

@@ -283,30 +255,33 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
 #         self.m_prev = self.invProb.m_current
 #         return mref

-class update_IRLS(InversionDirective):
+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
+        # Cool the threshold parameter if required
        if getattr(self, 'factor', None) is not None:
            eps = self.reg.eps / self.factor

@@ -317,28 +292,87 @@ class update_IRLS(InversionDirective):

        # Get phi_m at the end of current iteration
        self.phi_m_last = self.invProb.phi_m_last
-        
+
         # Update the model used for the IRLS weights
        self.reg.curModel = self.invProb.curModel

-        # Update the pre-conditioner
-        diagA = np.sum(self.prob.G**2.,axis=0) + self.invProb.beta*(self.reg.W.T*self.reg.W).diagonal() * (self.reg.mapping * np.ones(self.reg.curModel.size))**2.
-        PC     = Utils.sdiag(diagA**-1.)
-        self.opt.approxHinv = PC
-         
-        # Temporarely set gamma to 1.
+        # Temporarely set gamma to 1. to get raw phi_m
        self.reg.gamma = 1.
-        
-        # Compute change in model objective function and update scaling
+
+        # Compute new model objective function value
        phim_new = self.reg.eval(self.invProb.curModel)
+
+        # Update gamma to scale the regularization between IRLS iterations
        self.reg.gamma = self.phi_m_last / phim_new
-        
-        # TO DO: Re-scale beta if too much change in misfit
-        self.invProb.beta = self.invProb.beta * self.phi_d_last / self.invProb.phi_d
-        
-#==============================================================================
-#          import pylab as plt
-#          plt.figure()
-#          ax = plt.subplot(221)
-#          self.prob.mesh.plotSlice(self.invProb.curModel, ax = ax, normal = 'Z', ind=-5, clim = (0, 0.005))
-#==============================================================================
+
+        # Set the weighting matrix to None so that it is recomputed next time
+        # it is called in the inversion
+        self.reg._W = None
+
+class Update_lin_PreCond(InversionDirective):
+    """
+    Create a Jacobi preconditioner for the linear problem
+    """
+    onlyOnStart=False
+
+    def initialize(self):
+
+        if getattr(self.opt, 'approxHinv', None) is 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((self.prob.mapping.deriv(None).T *diagA)**-1.)
+            self.opt.approxHinv = PC
+
+    def endIter(self):
+        # Cool the threshold parameter
+        if self.onlyOnStart==True:
+            return
+
+        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((self.prob.mapping.deriv(None).T *diagA)**-1.)
+            self.opt.approxHinv = PC
+
+
+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
+
+class Scale_Beta(InversionDirective):
+    """
+        Instead of a linear cooling schedule, beta is allowed to change based
+        on the ratio between the target misfit and the current data misfit. The
+        update is done only if the misfit is outside some threshold bounds.
+    """
+    tol = 0.05
+
+    def endIter(self):
+
+        # Check if misfit is within the tolerance, otherwise adjust beta
+        val = self.invProb.phi_d / (self.survey.nD*0.5)
+
+        if np.abs(1.-val) > self.tol:
+            self.invProb.beta = self.invProb.beta * self.survey.nD*0.5 / self.invProb.phi_d
@@ -0,0 +1,118 @@
+import numpy as np
+from scipy.constants import mu_0, pi
+from scipy import special
+
+def DCAnalyticHalf(txloc, rxlocs, sigma, earth_type="wholespace"):
+    """
+        Analytic solution for electric potential from a postive pole
+
+        :param array txloc: a xyz location of A (+) electrode (np.r_[xa, ya, za])
+        :param list rxlocs: xyz locations of M (+) and N (-) electrodes [M, N]
+
+            e.g.
+            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])
+
+        :param float or complex sigma: values of conductivity
+        :param string earth_type: values of conductivity ("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 earth_type == "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, \
+                 field_type = "secondary", order=12, halfspace=False):
+# def DCSpherePointCurrent(txloc, rxloc, xc, radius, rho, rho1, \
+#                  field_type = "secondary", order=12):
+    """
+
+        Parameters:
+
+            :param array txloc: A (+) current electrode location (x,y,z)
+            :param array xc: x center of depressed sphere
+            :param array rxloc: M(+) electrode locations / (Nx3 array, # of electrodes)
+
+            :param float radius: radius (float): radius of the sphere (m)
+            :param float rho: resistivity of the background (ohm-m)
+            :param float rho1: resistivity of the sphere
+            :param string field_type: : "secondary", "total", "primary"
+                  (default="secondary")
+                  "secondary": secondary potential only due to sphere
+                  "primary": primary potential from the point source
+                  "total": "secondary"+"primary"
+            :param float order: 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 field_type =="primary":
+        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 field_type == "secondary":
+        return scale*(out-prim)
+    elif field_type == "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
@@ -1,3 +1,4 @@
 from TDEM import hzAnalyticDipoleT
 from FDEM import hzAnalyticDipoleF
 from FDEMcasing import *
+from DC import DCAnalyticHalf, DCAnalyticSphere
@@ -1,6 +1,7 @@
 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)
@@ -61,6 +62,15 @@ class BaseEMProblem(Problem.BaseProblem):
            self._Me = self.mesh.getEdgeInnerProduct()
        return self._Me

+    @property
+    def MeI(self):
+        """
+            Edge inner product matrix
+        """
+        if getattr(self, '_MeI', None) is None:
+            self._MeI = self.mesh.getEdgeInnerProduct(invMat=True)
+        return self._MeI
+
    @property
    def Mf(self):
        """
@@ -70,6 +80,20 @@ class BaseEMProblem(Problem.BaseProblem):
            self._Mf = self.mesh.getFaceInnerProduct()
        return self._Mf

+    @property
+    def MfI(self):
+        """
+            Face inner product matrix
+        """
+        if getattr(self, '_MfI', None) is None:
+            self._MfI = self.mesh.getFaceInnerProduct(invMat=True)
+        return self._MfI
+
+    @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 +151,6 @@ class BaseEMProblem(Problem.BaseProblem):
        """
        return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u) * self.curModel.sigmaDeriv

-
    @property
    def MeSigmaI(self):
        """
@@ -146,10 +169,7 @@ class BaseEMProblem(Problem.BaseProblem):

        dMeSigmaI_dI = -self.MeSigmaI**2
        dMe_dsig = self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u)
-        dsig_dm = self.curModel.sigmaDeriv
-        return dMeSigmaI_dI * ( dMe_dsig * ( dsig_dm))
-        # return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma, invMat=True)(u)
-
+        return dMeSigmaI_dI * ( dMe_dsig * self.curModel.sigmaDeriv )

    @property
    def MfRho(self):
@@ -165,8 +185,7 @@ class BaseEMProblem(Problem.BaseProblem):
        """
            Derivative of :code:`MfRho` with respect to the model.
        """
-        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u) * (-Utils.sdiag(self.curModel.rho**2) * self.curModel.sigmaDeriv)
-        # self.curModel.rhoDeriv
+        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u) * self.curModel.rhoDeriv

    @property
    def MfRhoI(self):
@@ -183,7 +202,10 @@ 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 * self.curModel.rhoDeriv )

 class BaseEMSurvey(Survey.BaseSurvey):

@@ -192,7 +214,7 @@ 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 +224,8 @@ 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.')
@@ -160,9 +160,9 @@ class Fields(SimPEG.Problem.Fields):
            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 = complex)

-class Fields_e(Fields):
+class Fields3D_e(Fields):
    """
-    Fields object for Problem_e.
+    Fields object for Problem3D_e.

    :param Mesh mesh: mesh
    :param Survey survey: survey
@@ -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
@@ -257,7 +257,7 @@ class Fields_e(Fields):
        """

        # assuming primary does not depend on the model
-        return Zero()
+        return src.ePrimaryDeriv(self.prob, v, adjoint) #Zero()

    def _bPrimary(self, eSolution, srcList):
        """
@@ -426,9 +426,9 @@ class Fields_e(Fields):



-class Fields_b(Fields):
+class Fields3D_b(Fields):
    """
-    Fields object for Problem_b.
+    Fields object for Problem3D_b.

    :param Mesh mesh: mesh
    :param Survey survey: survey
@@ -600,8 +600,8 @@ class Fields_b(Fields):


        if adjoint:
-            return self._MeSigmaIDeriv(w).T * v - self._MeSigmaI.T * s_eDeriv
-        return  self._MeSigmaIDeriv(w) * v - self._MeSigmaI * s_eDeriv
+            return self._MeSigmaIDeriv(w).T * v - self._MeSigmaI.T * s_eDeriv + src.ePrimaryDeriv(self.prob, v, adjoint)
+        return  self._MeSigmaIDeriv(w) * v - self._MeSigmaI * s_eDeriv + src.ePrimaryDeriv(self.prob, v, adjoint)

    def _j(self, bSolution, srcList):
        """
@@ -693,9 +693,9 @@ class Fields_b(Fields):
        return Zero()


-class Fields_j(Fields):
+class Fields3D_j(Fields):
    """
-    Fields object for Problem_j.
+    Fields object for Problem3D_j.

    :param Mesh mesh: mesh
    :param Survey survey: survey
@@ -988,9 +988,9 @@ class Fields_j(Fields):
        return 1./(1j * omega(src.freq)) * VI * (self._aveE2CCV * ( s_mDeriv(v) - self._edgeCurl.T * ( self._MfRhoDeriv(jSolution) * v ) ) )


-class Fields_h(Fields):
+class Fields3D_h(Fields):
    """
-    Fields object for Problem_h.
+    Fields object for Problem3D_h.

    :param Mesh mesh: mesh
    :param Survey survey: survey
@@ -1,7 +1,7 @@
 from SimPEG import Problem, Utils, np, sp, Solver as SimpegSolver
 from scipy.constants import mu_0
 from SurveyFDEM import Survey as SurveyFDEM
-from FieldsFDEM import Fields, Fields_e, Fields_b, Fields_h, Fields_j
+from FieldsFDEM import Fields, Fields3D_e, Fields3D_b, Fields3D_h, Fields3D_j
 from SimPEG.EM.Base import BaseEMProblem
 from SimPEG.EM.Utils import omega

@@ -17,8 +17,8 @@ class BaseFDEMProblem(BaseEMProblem):
            \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:`Problem3D_e`
+        or :code:`Problem3D_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}\\\)
@@ -28,7 +28,7 @@ class BaseFDEMProblem(BaseEMProblem):
            \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:`Problem3D_j` or :code:`Problem3D_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}\\\)
    """
@@ -74,7 +74,8 @@ class BaseFDEMProblem(BaseEMProblem):

        self.curModel = m

-        Jv = self.dataPair(self.survey)
+        # Jv = self.dataPair(self.survey)
+        Jv = []

        for freq in self.survey.freqs:
            A = self.getA(freq)
@@ -87,11 +88,11 @@ class BaseFDEMProblem(BaseEMProblem):
                du_dm_v = Ainv * ( - dA_dm_v + dRHS_dm_v )

                for rx in src.rxList:
-                    df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                    df_dmFun = getattr(f, '_{0}Deriv'.format(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)
+                    Jv.append(rx.evalDeriv(src, self.mesh, f, df_dm_v))
            Ainv.clean()
-        return Utils.mkvc(Jv)
+        return np.hstack(Jv)

    def Jtvec(self, m, v, f=None):
        """
@@ -125,7 +126,7 @@ class BaseFDEMProblem(BaseEMProblem):
                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_duTFun = getattr(f, '_{0}Deriv'.format(rx.projField), None)
                    df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)

                    ATinvdf_duT = ATinv * df_duT
@@ -137,10 +138,9 @@ class BaseFDEMProblem(BaseEMProblem):
                    df_dmT = df_dmT + du_dmT

                    # TODO: this should be taken care of by the reciever?
-                    real_or_imag = rx.projComp
-                    if real_or_imag is 'real':
+                    if rx.component is 'real':
                        Jtv +=   np.array(df_dmT, dtype=complex).real
-                    elif real_or_imag is 'imag':
+                    elif rx.component is 'imag':
                        Jtv += - np.array(df_dmT, dtype=complex).real
                    else:
                        raise Exception('Must be real or imag')
@@ -177,7 +177,7 @@ class BaseFDEMProblem(BaseEMProblem):
 ################################ E-B Formulation #########################################
 ##########################################################################################

-class Problem_e(BaseFDEMProblem):
+class Problem3D_e(BaseFDEMProblem):
    """
    By eliminating the magnetic flux density using

@@ -199,7 +199,7 @@ class Problem_e(BaseFDEMProblem):

    _solutionType = 'eSolution'
    _formulation  = 'EB'
-    fieldsPair    = Fields_e
+    fieldsPair    = Fields3D_e

    def __init__(self, mesh, **kwargs):
        BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -288,7 +288,7 @@ class Problem_e(BaseFDEMProblem):
            return C.T * (MfMui * s_mDeriv(v)) -1j * omega(freq) * s_eDeriv(v)


-class Problem_b(BaseFDEMProblem):
+class Problem3D_b(BaseFDEMProblem):
    """
    We eliminate :math:`\mathbf{e}` using

@@ -310,7 +310,7 @@ class Problem_b(BaseFDEMProblem):

    _solutionType = 'bSolution'
    _formulation  = 'EB'
-    fieldsPair    = Fields_b
+    fieldsPair    = Fields3D_b

    def __init__(self, mesh, **kwargs):
        BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -436,7 +436,7 @@ class Problem_b(BaseFDEMProblem):
 ##########################################################################################


-class Problem_j(BaseFDEMProblem):
+class Problem3D_j(BaseFDEMProblem):
    """
    We eliminate \\\(\\\mathbf{h}\\\) using

@@ -458,7 +458,7 @@ class Problem_j(BaseFDEMProblem):

    _solutionType = 'jSolution'
    _formulation  = 'HJ'
-    fieldsPair    = Fields_j
+    fieldsPair    = Fields3D_j

    def __init__(self, mesh, **kwargs):
        BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -577,7 +577,7 @@ class Problem_j(BaseFDEMProblem):



-class Problem_h(BaseFDEMProblem):
+class Problem3D_h(BaseFDEMProblem):
    """
    We eliminate \\\(\\\mathbf{j}\\\) using

@@ -596,7 +596,7 @@ class Problem_h(BaseFDEMProblem):

    _solutionType = 'hSolution'
    _formulation  = 'HJ'
-    fieldsPair    = Fields_h
+    fieldsPair    = Fields3D_h

    def __init__(self, mesh, **kwargs):
        BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -0,0 +1,126 @@
+import SimPEG
+from SimPEG import sp
+
+class BaseRx(SimPEG.Survey.BaseRx):
+    """
+    Frequency domain receiver base class
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        assert(orientation in ['x','y','z']), "Orientation %s not known. Orientation must be in 'x', 'y', 'z'. Arbitrary orientations have not yet been implemented."%orientation
+        assert(component in ['real', 'imag']), "'component' must be 'real' or 'imag', not %s"%component
+
+        self.projComp = orientation
+        self.component = component
+
+        SimPEG.Survey.BaseRx.__init__(self, locs, rxType=None) #TODO: remove rxType from baseRx
+
+    def projGLoc(self, u):
+        """Grid Location projection (e.g. Ex Fy ...)"""
+        return u._GLoc(self.projField) + self.projComp
+
+    def eval(self, src, mesh, f):
+        """
+        Project fields to recievers to get data.
+
+        :param Source src: FDEM source
+        :param Mesh mesh: mesh used
+        :param Fields f: fields object
+        :rtype: numpy.ndarray
+        :return: fields projected to recievers
+        """
+
+        P = self.getP(mesh, self.projGLoc(f))
+        f_part_complex = f[src, self.projField]
+        f_part = getattr(f_part_complex, self.component) # get the real or imag component
+
+        return P*f_part
+
+    def evalDeriv(self, src, mesh, f, v, adjoint=False):
+        """
+        Derivative of projected fields with respect to the inversion model times a vector.
+
+        :param Source src: FDEM source
+        :param Mesh mesh: mesh used
+        :param Fields f: fields object
+        :param numpy.ndarray v: vector to multiply
+        :rtype: numpy.ndarray
+        :return: fields projected to recievers
+        """
+
+        P = self.getP(mesh, self.projGLoc(f))
+
+        if not adjoint:
+            Pv_complex = P * v
+            Pv = getattr(Pv_complex, self.component)
+        elif adjoint:
+            Pv_real = P.T * v
+
+            if self.component == 'imag':
+                Pv = 1j*Pv_real
+            elif self.component == 'real':
+                Pv = Pv_real.astype(complex)
+            else:
+                raise NotImplementedError('must be real or imag')
+
+        return Pv
+
+
+class Point_e(BaseRx):
+    """
+    Electric field FDEM receiver
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        self.projField = 'e'
+        super(Point_e, self).__init__(locs, orientation, component)
+
+
+class Point_b(BaseRx):
+    """
+    Magnetic flux FDEM receiver
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        self.projField = 'b'
+        super(Point_b, self).__init__(locs, orientation, component)
+
+
+class Point_h(BaseRx):
+    """
+    Magnetic field FDEM receiver
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        self.projField = 'h'
+        super(Point_h, self).__init__(locs, orientation, component)
+
+
+class Point_j(BaseRx):
+    """
+    Current density FDEM receiver
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        self.projField = 'j'
+        super(Point_j, self).__init__(locs, orientation, component)
@@ -9,12 +9,17 @@ class BaseSrc(Survey.BaseSrc):
    """

    freq = None
-    # rxPair = RxFDEM
-    integrate = True
+    integrate = False
+    _ePrimary = None
+    _bPrimary = None
+    _hPrimary = None
+    _jPrimary = None
+
+    def __init__(self, rxList, **kwargs):
+        Survey.BaseSrc.__init__(self, rxList, **kwargs)

    def eval(self, prob):
        """
-        Evaluate the source terms.
        - :math:`s_m` : magnetic source term
        - :math:`s_e` : electric source term

@@ -51,6 +56,20 @@ class BaseSrc(Survey.BaseSrc):
        :rtype: numpy.ndarray
        :return: primary magnetic flux density
        """
+        if self._bPrimary is None:
+            return Zero()
+        return self._bPrimary
+
+    def bPrimaryDeriv(self, prob, v, adjoint=False):
+        """
+        Derivative of the primary magnetic flux density
+
+        :param Problem prob: FDEM Problem
+        :param numpy.ndarray v: vector
+        :param bool adjoint: adjoint?
+        :rtype: numpy.ndarray
+        :return: primary magnetic flux density
+        """
        return Zero()

    def hPrimary(self, prob):
@@ -61,6 +80,20 @@ class BaseSrc(Survey.BaseSrc):
        :rtype: numpy.ndarray
        :return: primary magnetic field
        """
+        if self._hPrimary is None:
+            return Zero()
+        return self._hPrimary
+
+    def hPrimaryDeriv(self, prob, v, adjoint=False):
+        """
+        Derivative of the primary magnetic field
+
+        :param Problem prob: FDEM Problem
+        :param numpy.ndarray v: vector
+        :param bool adjoint: adjoint?
+        :rtype: numpy.ndarray
+        :return: primary magnetic flux density
+        """
        return Zero()

    def ePrimary(self, prob):
@@ -71,6 +104,20 @@ class BaseSrc(Survey.BaseSrc):
        :rtype: numpy.ndarray
        :return: primary electric field
        """
+        if self._ePrimary is None:
+            return Zero()
+        return self._ePrimary
+
+    def ePrimaryDeriv(self, prob, v, adjoint=False):
+        """
+        Derivative of the primary electric field
+
+        :param Problem prob: FDEM Problem
+        :param numpy.ndarray v: vector
+        :param bool adjoint: adjoint?
+        :rtype: numpy.ndarray
+        :return: primary magnetic flux density
+        """
        return Zero()

    def jPrimary(self, prob):
@@ -81,6 +128,20 @@ class BaseSrc(Survey.BaseSrc):
        :rtype: numpy.ndarray
        :return: primary current density
        """
+        if self._jPrimary is None:
+            return Zero()
+        return self._jPrimary
+
+    def jPrimaryDeriv(self, prob, v, adjoint=False):
+        """
+        Derivative of the primary current density
+
+        :param Problem prob: FDEM Problem
+        :param numpy.ndarray v: vector
+        :param bool adjoint: adjoint?
+        :rtype: numpy.ndarray
+        :return: primary magnetic flux density
+        """
        return Zero()

    def s_m(self, prob):
@@ -136,15 +197,14 @@ class RawVec_e(BaseSrc):
    :param list rxList: receiver list
    :param float freq: frequency
    :param numpy.array s_e: electric source term
-    :param bool integrate: Integrate the source term (multiply by Me) [True]
+    :param bool integrate: Integrate the source term (multiply by Me) [False]
    """

-    def __init__(self, rxList, freq, s_e, integrate=True): #, ePrimary=None, bPrimary=None, hPrimary=None, jPrimary=None):
+    def __init__(self, rxList, freq, s_e, **kwargs):
        self._s_e = np.array(s_e, dtype=complex)
        self.freq = float(freq)
-        self.integrate = integrate

-        BaseSrc.__init__(self, rxList)
+        BaseSrc.__init__(self, rxList, **kwargs)

    def s_e(self, prob):
        """
@@ -166,15 +226,14 @@ class RawVec_m(BaseSrc):
    :param float freq: frequency
    :param rxList: receiver list
    :param numpy.array s_m: magnetic source term
-    :param bool integrate: Integrate the source term (multiply by Me) [True]
+    :param bool integrate: Integrate the source term (multiply by Me) [False]
    """

-    def __init__(self, rxList, freq, s_m, integrate=True):  #ePrimary=Zero(), bPrimary=Zero(), hPrimary=Zero(), jPrimary=Zero()):
+    def __init__(self, rxList, freq, s_m, **kwargs):  #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)
+        BaseSrc.__init__(self, rxList, **kwargs)

    def s_m(self, prob):
        """
@@ -197,14 +256,13 @@ 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) [True]
+    :param bool integrate: Integrate the source term (multiply by Me) [False]
    """
-    def __init__(self, rxList, freq, s_m, s_e, integrate=True):
+    def __init__(self, rxList, freq, s_m, s_e, **kwargs):
        self._s_m = np.array(s_m, dtype=complex)
        self._s_e = np.array(s_e, dtype=complex)
        self.freq = float(freq)
-        self.integrate = integrate
-        BaseSrc.__init__(self, rxList)
+        BaseSrc.__init__(self, rxList, **kwargs)

    def s_m(self, prob):
        """
@@ -278,14 +336,13 @@ class MagDipole(BaseSrc):
    :param float mu: background magnetic permeability
    """

-    def __init__(self, rxList, freq, loc, orientation='Z', moment=1., mu=mu_0):
+    def __init__(self, rxList, freq, loc, orientation='Z', moment=1., mu=mu_0, **kwargs):
        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):
@@ -543,10 +600,10 @@ class CircularLoop(BaseSrc):
            if not prob.mesh.isSymmetric:
                # TODO ?
                raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-            a = MagneticDipoleVectorPotential(self.loc, gridY, 'y', moment=self.radius, mu=self.mu)
+            a = MagneticLoopVectorPotential(self.loc, gridY, 'y', moment=self.radius, mu=self.mu)

        else:
-            srcfct = MagneticDipoleVectorPotential
+            srcfct = MagneticLoopVectorPotential
            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)
@@ -605,5 +662,155 @@ class CircularLoop(BaseSrc):
            return -C.T * (MMui_s * self.bPrimary(prob))


+class PrimSecSigma(BaseSrc):
+
+    def __init__(self, rxList, freq, sigBack, ePrimary, **kwargs):
+        self.sigBack = sigBack
+
+        BaseSrc.__init__(self, rxList, freq=freq, _ePrimary=ePrimary, **kwargs)
+
+    def s_e(self, prob):
+        return (prob.MeSigma -  prob.mesh.getEdgeInnerProduct(self.sigBack)) * self.ePrimary(prob)
+
+    def s_eDeriv(self, prob, v, adjoint=False):
+        if adjoint:
+            return prob.MeSigmaDeriv(self.ePrimary(prob)).T * v
+        return prob.MeSigmaDeriv(self.ePrimary(prob)) * v
+
+
+class PrimSecMappedSigma(BaseSrc):
+
+    """
+    Primary-Secondary Source in which a mapping is provided to put the current model
+    onto the primary mesh. This is solved on every model update.
+
+    There are a lot of layers to the derivatives here!
+
+    **Required**
+    :param list rxList: Receiver List
+    :param float freq: frequency
+    :param ProblemFDEM primaryProblem: FDEM primary problem
+    :param SurveyFDEM primarySurvey: FDEM primary survey
+
+    **Optional**
+    :param Mapping map2meshSecondary: mapping current model to act as primary model on the secondary mesh
+
+    """
+
+    def __init__(self, rxList, freq, primaryProblem, primarySurvey, map2meshSecondary = None ,**kwargs):
+
+        self.primaryProblem = primaryProblem
+        self.primarySurvey = primarySurvey
+
+        if self.primaryProblem.ispaired is False:
+            self.primaryProblem.pair(self.primarySurvey)
+
+        self.map2meshSecondary = map2meshSecondary
+
+        BaseSrc.__init__(self, rxList, freq=freq, **kwargs)
+
+    def _ProjPrimary(self, prob):
+        # if getattr(self, '__ProjPrimary', None) is None:
+        return self.primaryProblem.mesh.getInterpolationMatCartMesh(prob.mesh, locType='F', locTypeTo='E')
+        # return self.__ProjPrimary
+
+
+    def _primaryFields(self, prob, fieldType=None):
+
+        # TODO: cache and check if prob.curModel has changed
+        fields = self.primaryProblem.fields(prob.curModel.sigmaModel)
+
+        if fieldType is not None:
+            return fields[:,fieldType]
+        return fields
+
+    def _primaryFieldsDeriv(self, prob, v, adjoint=False, f=None):
+        if adjoint:
+            raise NotImplementedError
+
+        # TODO: this should not be hard-coded for j
+        # jp = self._primaryFields(prob)[:,'j']
+
+        # TODO: pull apart Jvec so that don't have to copy paste this code in
+        # A = self.primaryProblem.getA(self.freq)
+        # Ainv = self.primaryProblem.Solver(A, **self.primaryProblem.solverOpts) # create the concept of Ainv (actually a solve)
+
+        if f is None:
+           f = self._primaryFields(prob.curModel.sigmaModel)
+
+        freq = self.freq
+
+        A = self.primaryProblem.getA(freq)
+        Ainv = self.primaryProblem.Solver(A, **self.primaryProblem.solverOpts) # create the concept of Ainv (actually a solve)
+
+        src = self.primarySurvey.srcList[0]
+        # for src in self.survey.getSrcByFreq(freq):
+        u_src = Utils.mkvc(f[src, self.primaryProblem._solutionType])
+        dA_dm_v = self.primaryProblem.getADeriv(freq, u_src, v)
+        dRHS_dm_v = self.primaryProblem.getRHSDeriv(freq, src, v)
+        du_dm_v = Ainv * ( - dA_dm_v + dRHS_dm_v )
+
+        df_dmFun = getattr(f, '_{0}Deriv'.format('j'), 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)
+        Ainv.clean()
+
+        return df_dm_v
+
+        # return self.primaryProblem.Jvec(prob.curModel, v, f=f)
+
+    def ePrimary(self, prob, f=None):
+        if f is None:
+            f = self._primaryFields(prob)
+
+        ep = self._ProjPrimary(prob) * (
+                self.primaryProblem.MfI * (
+                self.primaryProblem.MfRho * f[:,'j'])
+                )
+
+        return Utils.mkvc(ep)
+
+    def ePrimaryDeriv(self, prob, v, adjoint=False, f=None):
+
+        if adjoint is True:
+            raise NotImplementedError
+
+        if f is None:
+            f = self._primaryFields(prob)
+
+        epDeriv = self._ProjPrimary(prob) * (
+                    self.primaryProblem.MfI * (
+                    (self.primaryProblem.MfRhoDeriv(f[:,'j']) * v)
+                    +
+                    (self.primaryProblem.MfRho * self._primaryFieldsDeriv(prob, v, f=f))
+                    )
+                    )
+
+        return Utils.mkvc(epDeriv)
+
+
+    def s_e(self, prob):
+        sigmaPrimary = self.map2meshSecondary * prob.curModel.sigmaModel
+
+        return Utils.mkvc((prob.MeSigma -  prob.mesh.getEdgeInnerProduct(sigmaPrimary)) * self.ePrimary(prob))
+
+
+    def s_eDeriv(self, prob, v, adjoint=False):
+        if adjoint:
+            raise NotImplementedError
+            return prob.MeSigmaDeriv(self.ePrimary(prob)).T * v
+
+        sigmaPrimary = self.map2meshSecondary * prob.curModel.sigmaModel
+        sigmaPrimaryDeriv = self.map2meshSecondary.deriv(prob.curModel.sigmaModel)
+
+        f = self._primaryFields(prob)
+        ePrimary = self.ePrimary(prob,f=f)
+
+        return (prob.MeSigmaDeriv(ePrimary) * v
+                - prob.mesh.getEdgeInnerProductDeriv(sigmaPrimary)(ePrimary) * sigmaPrimaryDeriv * v
+                + (prob.MeSigma -  prob.mesh.getEdgeInnerProduct(sigmaPrimary)) * self.ePrimaryDeriv(prob, v, None, f=f)
+                )
+
+


@@ -4,126 +4,9 @@ from SimPEG.EM.Base import BaseEMSurvey
 from scipy.constants import mu_0
 from SimPEG.Utils import Zero, Identity
 import SrcFDEM as Src
+import RxFDEM as Rx
 from SimPEG import sp

-
-####################################################
-# Receivers
-####################################################
-
-class Rx(SimPEG.Survey.BaseRx):
-    """
-    Frequency domain receivers
-
-    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
-    :param string rxType: reciever type from knownRxTypes
-    """
-
-    knownRxTypes = {
-                    'exr':['e', 'x', 'real'],
-                    'eyr':['e', 'y', 'real'],
-                    'ezr':['e', 'z', 'real'],
-                    'exi':['e', 'x', 'imag'],
-                    'eyi':['e', 'y', 'imag'],
-                    'ezi':['e', 'z', 'imag'],
-
-                    'bxr':['b', 'x', 'real'],
-                    'byr':['b', 'y', 'real'],
-                    'bzr':['b', 'z', 'real'],
-                    'bxi':['b', 'x', 'imag'],
-                    'byi':['b', 'y', 'imag'],
-                    'bzi':['b', 'z', 'imag'],
-
-                    'jxr':['j', 'x', 'real'],
-                    'jyr':['j', 'y', 'real'],
-                    'jzr':['j', 'z', 'real'],
-                    'jxi':['j', 'x', 'imag'],
-                    'jyi':['j', 'y', 'imag'],
-                    'jzi':['j', 'z', 'imag'],
-
-                    'hxr':['h', 'x', 'real'],
-                    'hyr':['h', 'y', 'real'],
-                    'hzr':['h', 'z', 'real'],
-                    'hxi':['h', 'x', 'imag'],
-                    'hyi':['h', 'y', 'imag'],
-                    'hzi':['h', 'z', 'imag'],
-                   }
-    radius = None
-
-    def __init__(self, locs, rxType):
-        SimPEG.Survey.BaseRx.__init__(self, locs, rxType)
-
-    @property
-    def projField(self):
-        """Field Type projection (e.g. e b ...)"""
-        return self.knownRxTypes[self.rxType][0]
-
-    @property
-    def projComp(self):
-        """Component projection (real/imag)"""
-        return self.knownRxTypes[self.rxType][2]
-
-    def projGLoc(self, u):
-        """Grid Location projection (e.g. Ex Fy ...)"""
-        return u._GLoc(self.rxType[0]) + self.knownRxTypes[self.rxType][1]
-
-    def eval(self, src, mesh, f):
-        """
-        Project fields to recievers to get data.
-
-        :param Source src: FDEM source
-        :param Mesh mesh: mesh used
-        :param Fields f: fields object
-        :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]
-        # get the real or imag component
-        real_or_imag = self.projComp
-        f_part = getattr(f_part_complex, real_or_imag)
-
-        return P*f_part
-
-    def evalDeriv(self, src, mesh, f, v, adjoint=False):
-        """
-        Derivative of projected fields with respect to the inversion model times a vector.
-
-        :param Source src: FDEM source
-        :param Mesh mesh: mesh used
-        :param Fields f: fields object
-        :param numpy.ndarray v: vector to multiply
-        :rtype: numpy.ndarray
-        :return: fields projected to recievers
-        """
-
-        P = self.getP(mesh, self.projGLoc(f))
-
-        if not adjoint:
-            Pv_complex = P * v
-            real_or_imag = self.projComp
-            Pv = getattr(Pv_complex, real_or_imag)
-        elif adjoint:
-            Pv_real = P.T * v
-
-            real_or_imag = self.projComp
-            if real_or_imag == 'imag':
-                Pv = 1j*Pv_real
-            elif real_or_imag == 'real':
-                Pv = Pv_real.astype(complex)
-            else:
-                raise NotImplementedError('must be real or imag')
-
-        return Pv
-
-
-####################################################
-# Survey
-####################################################
-
 class Survey(BaseEMSurvey):
    """
    Frequency domain electromagnetic survey
@@ -132,7 +15,7 @@ class Survey(BaseEMSurvey):
    """

    srcPair = Src.BaseSrc
-    rxPair = Rx
+    rxPair = Rx.BaseRx

    def __init__(self, srcList, **kwargs):
        # Sort these by frequency
@@ -1,3 +1,5 @@
-from SurveyFDEM import Rx, Src, Survey
-from FDEM import BaseFDEMProblem, Problem_e, Problem_b, Problem_j, Problem_h
-from FieldsFDEM import *
+from SurveyFDEM import Survey
+import SrcFDEM as Src
+import RxFDEM as Rx
+from ProblemFDEM import Problem3D_e, Problem3D_b, Problem3D_j, Problem3D_h
+from FieldsFDEM import Fields3D_e, Fields3D_b, Fields3D_j, Fields3D_h
@@ -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
@@ -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))
@@ -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
@@ -0,0 +1,296 @@
+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 G
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        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:
+            return(MfRhoIDeriv( G * u ).T) * ( D.T * v)
+
+        return D * (MfRhoIDeriv( G * u ) * 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()
+
+    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 = G.T MeSigma G
+
+        """
+
+        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()
+
+
+
+
@@ -0,0 +1,349 @@
+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 G
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        vol = self.mesh.vol
+        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 G
+
+        """
+
+        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()
@@ -0,0 +1,136 @@
+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.Pole(locs)
+class Pole(BaseRx):
+
+    def __init__(self, locs, rxType = 'phi', **kwargs):
+        BaseRx.__init__(self, locs, rxType)
+
+
+# DC.Rx.Dipole(locsM, locsN)
+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
+
@@ -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
@@ -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
+
+
@@ -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
@@ -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
@@ -0,0 +1,372 @@
+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 G
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        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 = G.T MeSigma G
+
+        """
+
+        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)
+
+
@@ -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)
@@ -0,0 +1,2 @@
+from ProblemIP import Problem3D_CC, Problem3D_N
+from SurveyIP import Survey
@@ -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 G
+
+        """
+
+        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 = G.T MeSigma G
+
+        """
+
+        # 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)
+
+
@@ -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) ) )
+
+
+
@@ -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
@@ -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
+
@@ -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
@@ -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
@@ -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
+
@@ -0,0 +1 @@
+from StaticUtils import *
@@ -0,0 +1,3 @@
+import DC
+import IP
+import SIP
@@ -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


@@ -20,56 +20,61 @@ 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)

    x = np.array([np.linspace(-5.*cs,-2.*cs,3),np.linspace(5.*cs,2.*cs,3)]) + cs/4. #don't sample right by the source, slightly off alignment from either staggered grid
    XYZ = Utils.ndgrid(x,x,np.linspace(-2.*cs,2.*cs,5))
-    Rx0 = EM.FDEM.Rx(XYZ, comp)
+    Rx0 = getattr(EM.FDEM.Rx, 'Point_' + comp[0])
+    if comp[2] == 'r':
+        real_or_imag = 'real'
+    elif comp[2] == 'i':
+        real_or_imag = 'imag'
+    rx0 = Rx0(XYZ, comp[1], 'imag')

    Src = []

    for SrcType in SrcList:
        if SrcType is 'MagDipole':
-            Src.append(EM.FDEM.Src.MagDipole([Rx0], freq=freq, loc=np.r_[0.,0.,0.]))
+            Src.append(EM.FDEM.Src.MagDipole([rx0], freq=freq, loc=np.r_[0.,0.,0.]))
        elif SrcType is 'MagDipole_Bfield':
-            Src.append(EM.FDEM.Src.MagDipole_Bfield([Rx0], freq=freq, loc=np.r_[0.,0.,0.]))
+            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.]))
+            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))
+                Src.append(EM.FDEM.Src.RawVec([rx0], freq, S_m, mesh.getEdgeInnerProduct()*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))
+                Src.append(EM.FDEM.Src.RawVec([rx0], freq, mesh.getEdgeInnerProduct()*S_m, S_e))

    if verbose:
        print '  Fetching %s problem' % (fdemType)

    if fdemType == 'e':
        survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem_e(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem3D_e(mesh, mapping=mapping)

    elif fdemType == 'b':
        survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem_b(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem3D_b(mesh, mapping=mapping)

    elif fdemType == 'j':
        survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem_j(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem3D_j(mesh, mapping=mapping)

    elif fdemType == 'h':
        survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem_h(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem3D_h(mesh, mapping=mapping)

    else:
        raise NotImplementedError()
@@ -90,7 +95,7 @@ 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

@@ -1,5 +1,6 @@
 import TDEM
 import FDEM
+import Static
 import Base
 import Analytics
 import Utils
@@ -2,27 +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', dtype='appc', plotIt=True):
+def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', unitType='appConductivity', plotIt=True):
    """
        DC Forward Simulation
        =====================

-        Forward model two conductive spheres in a half-space and plot a 
+        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
+        surveyType = survey type 'pole-dipole' or 'dipole-dipole'
+        unitType = Data type "appResistivity" | "appConductivity"  | "volt"
+        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)"
+    assert surveyType in ['pole-dipole', 'dipole-dipole'], "Source type (surveyType) must be pdp or dpdp (pole dipole or dipole dipole)"
+    assert unitType in ['appResistivity', 'appConductivity', 'volt'], "Unit type (unitType) must be appResistivity or appConductivity or volt (potential)"

    if loc is None:
        loc = np.c_[[-50.,0.,-50.],[50.,0.,-50.]]
@@ -73,8 +73,8 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', dtype='appc', p
    locs = np.c_[mesh.gridCC[indx,0],mesh.gridCC[indx,1],np.ones(2).T*mesh.vectorNz[-1]]

    # We will handle the geometry of the survey for you and create all the combination of tx-rx along line
-    # [Tx, Rx] = DC.gen_DCIPsurvey(locs, mesh, stype, param[0], param[1], param[2])
-    survey, Tx, Rx = DC.gen_DCIPsurvey(locs, mesh, stype, param[0], param[1], param[2])
+    # [Tx, Rx] = DC.gen_DCIPsurvey(locs, mesh, surveyType, param[0], param[1], param[2])
+    survey, Tx, Rx = DC.gen_DCIPsurvey(locs, mesh, surveyType, param[0], param[1], param[2])

    # Define some global geometry
    dl_len = np.sqrt( np.sum((locs[0,:] - locs[1,:])**2) )
@@ -118,8 +118,8 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', dtype='appc', p
        rxloc_N = np.asarray(Rx[ii][:,3:])


-        # For usual cases "dpdp" or "gradient"
-        if stype == 'pdp':
+        # For usual cases 'dipole-dipole' or "gradient"
+        if surveyType == 'pole-dipole':
            # Create an "inifinity" pole
            tx =  np.squeeze(Tx[ii][:,0:1])
            tinf = tx + np.array([dl_x,dl_y,0])*dl_len*2
@@ -157,12 +157,12 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', dtype='appc', p
        fig = plt.figure(figsize=(7,7))
        ax = plt.subplot(2,1,1, aspect='equal')
        # 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)
+        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',
+        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')
@@ -188,15 +188,13 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', dtype='appc', p
        ax2 = plt.subplot(2,1,2, aspect='equal')

        # 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)
+        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
-        dat = DC.plot_pseudoSection(survey2D,ax2,stype=stype, dtype = dtype)
-
-        # plt.scatter(Tx2d[0][:],Tx[0][2,:],s=40,c='g', marker='v')
+        dat = DC.plot_pseudoSection(survey2D, ax2, surveyType=surveyType, unitType=unitType)        # 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')
        ax2.set_title('Apparent Conductivity data')
@@ -42,8 +42,8 @@ def run(plotIt=True):
        ax.grid(color='k', alpha=0.5, linestyle='dashed', linewidth=0.5)


-    rxOffset=10. 
-    bzi = EM.FDEM.Rx(np.array([[rxOffset, 0., 1e-3]]), 'bzi')
+    rxOffset=10.
+    bzi = EM.FDEM.Rx.Point_b(np.array([[rxOffset, 0., 1e-3]]), orientation='z', component='imag')

    freqs = np.logspace(1,3,10)
    srcLoc = np.array([0., 0., 10.])
@@ -51,7 +51,7 @@ def run(plotIt=True):
    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)
+    prb = EM.FDEM.Problem3D_b(mesh, mapping=mapping)

    try:
        from pymatsolver import MumpsSolver
@@ -215,7 +215,7 @@ def run(plotIt=True):
    # ------------ Problem and Survey ---------------
    survey = FDEM.Survey(sg_p + dg_p)
    mapping = [('sigma', Maps.IdentityMap(mesh))]
-    problem = FDEM.Problem_h(mesh, mapping=mapping)
+    problem = FDEM.Problem3D_h(mesh, mapping=mapping)
    problem.pair(survey)

    # ------------- Solve ---------------------------
@@ -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 = 5e-2
+    reg.eps_q = 1e-2
+    reg.norms   = [0., 0., 2., 2.]
+    reg.wght = wr
+
+    opt = Optimization.ProjectedGNCG(maxIter=10 ,lower=-2.,upper=2., maxIterLS = 20, maxIterCG= 20, 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()
@@ -0,0 +1,41 @@
+from SimPEG import *
+from SimPEG.Utils import surface2ind_topo
+
+
+def run(plotIt=False, nx = 5, ny = 5):
+    """
+        Here we show how to use :code:`Utils.surface2ind_topo` to identify cells below
+        a topographic surface.
+
+    """
+
+    mesh = Mesh.TensorMesh([nx,ny], x0='CC') # 2D mesh
+    xtopo = np.linspace(mesh.gridN[:,0].min(), mesh.gridN[:,0].max())
+    topo = 0.4*np.sin(xtopo*5) # define a topographic surface
+
+    Topo = np.hstack([Utils.mkvc(xtopo,2),Utils.mkvc(topo,2)]) #make it an array
+
+    indcc = surface2ind_topo(mesh, Topo,'CC')
+
+    if plotIt:
+        from matplotlib.pylab import plt
+        from scipy.interpolate import interp1d
+        fig, ax = plt.subplots(1,1,figsize=(6,6))
+        mesh.plotGrid(ax=ax, nodes=True, centers=True)
+        ax.plot(xtopo,topo,'k',linewidth=1)
+        # ax.plot(mesh.vectorNx, interp1d(xtopo,topo)(mesh.vectorNx),'--k',linewidth=3)
+        ax.plot(mesh.vectorCCx, interp1d(xtopo,topo)(mesh.vectorCCx),'--k',linewidth=3)
+
+
+        aveN2CC = Utils.sdiag(mesh.aveN2CC.T.sum(1))*mesh.aveN2CC.T
+        a = aveN2CC * indcc
+        a[a > 0] = 1.
+        a[a < 0.25] = np.nan
+        a = a.reshape(mesh.vnN, order='F')
+        masked_array = np.ma.array(a, mask=np.isnan(a))
+        ax.pcolor(mesh.vectorNx,mesh.vectorNy,masked_array.T, cmap = plt.cm.gray,alpha=0.2)
+        plt.show()
+
+
+if __name__ == '__main__':
+    run(plotIt=True)
@@ -9,6 +9,7 @@ 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
@@ -19,8 +20,9 @@ import Mesh_QuadTree_HangingNodes
 import Mesh_Tensor_Creation
 import MT_1D_ForwardAndInversion
 import MT_3D_Foward
+import Utils_surface2ind_topo

-__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_Schenkel_Morrison_Casing", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Forward_BasicDirectCurrent", "Inversion_Linear", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward"]
+__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", "Utils_surface2ind_topo"]

 ##### AUTOIMPORTS #####

@@ -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)

@@ -1,5 +1,5 @@
 from SimPEG import SolverLU as SimpegSolver, PropMaps, Utils, mkvc, sp, np
-from SimPEG.EM.FDEM.FDEM import BaseFDEMProblem
+from SimPEG.EM.FDEM.ProblemFDEM import BaseFDEMProblem
 from SurveyMT import Survey, Data
 from FieldsMT import BaseMTFields

@@ -7,17 +7,16 @@ from SimPEG.MT.Utils.dataUtils import rec2ndarr
 # Import modules
 import numpy as np
 import os, sys, re
-try:
-    import osr
-except ImportError as e:
-    print 'Could not import osr, missing the gdal package'
-    pass
+

 class EDIimporter:
    """
    A class to import EDIfiles.

    """
+
+
+    # Define data converters
    _impUnitEDI2SI = 4*np.pi*1e-4 # Convert Z[mV/km/nT] (as in EDI)to Z[V/A] SI unit
    _impUnitSI2EDI = 1./_impUnitEDI2SI # ConvertZ[V/A] SI unit to Z[mV/km/nT] (as in EDI)

@@ -26,8 +25,8 @@ class EDIimporter:
    comps = None

    # Hidden properties
-    _outEPSG = None
-    _2out = None
+    _outEPSG = None # Project info
+    _2out = None    # The projection operator


    def __init__(self, EDIfilesList, compList=None, outEPSG=None):
@@ -113,6 +112,12 @@ class EDIimporter:
    # nOutData=length(obj.data);
    # obj.data(nOutData+1:nOutData+length(TEMP.data),:) = TEMP.data;
    def _transfromPoints(self,longD,latD):
+        # Import the coordinate projections
+        try:
+            import osr
+        except ImportError as e:
+            print 'Could not import osr, missing the gdal package\nCan not project coordinates'
+            raise e
        # Coordinates convertor
        if self._2out is None:
            src = osr.SpatialReference()
@@ -330,7 +330,7 @@ class CylMesh(BaseTensorMesh, BaseRectangularMesh, InnerProducts, CylView):
                raise NotImplementedError('wrapping in the averaging is not yet implemented')
        return self._aveF2CCV

-    def getInterpolationMatCartMesh(self, Mrect, locType='CC'):
+    def getInterpolationMatCartMesh(self, Mrect, locType='CC', locTypeTo=None):
        """
            Takes a cartesian mesh and returns a projection to translate onto the cartesian grid.
        """
@@ -338,19 +338,22 @@ class CylMesh(BaseTensorMesh, BaseRectangularMesh, InnerProducts, CylView):
        assert self.isSymmetric, "Currently we have not taken into account other projections for more complicated CylMeshes"


+        if locTypeTo is None:
+            locTypeTo = locType
+
        if locType == 'F':
            # do this three times for each component
-            X = self.getInterpolationMatCartMesh(Mrect, locType='Fx')
-            Y = self.getInterpolationMatCartMesh(Mrect, locType='Fy')
-            Z = self.getInterpolationMatCartMesh(Mrect, locType='Fz')
+            X = self.getInterpolationMatCartMesh(Mrect, locType='Fx', locTypeTo=locTypeTo+'x')
+            Y = self.getInterpolationMatCartMesh(Mrect, locType='Fy', locTypeTo=locTypeTo+'y')
+            Z = self.getInterpolationMatCartMesh(Mrect, locType='Fz', locTypeTo=locTypeTo+'z')
            return sp.vstack((X,Y,Z))
        if locType == 'E':
-            X = self.getInterpolationMatCartMesh(Mrect, locType='Ex')
-            Y = self.getInterpolationMatCartMesh(Mrect, locType='Ey')
-            Z = spzeros(Mrect.nEz, self.nE)
+            X = self.getInterpolationMatCartMesh(Mrect, locType='Ex', locTypeTo=locTypeTo+'x')
+            Y = self.getInterpolationMatCartMesh(Mrect, locType='Ey', locTypeTo=locTypeTo+'y')
+            Z = spzeros(getattr(Mrect, 'n' + locTypeTo + 'z'), self.nE)
            return sp.vstack((X,Y,Z))

-        grid = getattr(Mrect, 'grid' + locType)
+        grid = getattr(Mrect, 'grid' + locTypeTo)
        # This is unit circle stuff, 0 to 2*pi, starting at x-axis, rotating counter clockwise in an x-y slice
        theta = - np.arctan2(grid[:,0] - self.cartesianOrigin[0], grid[:,1] - self.cartesianOrigin[1]) + np.pi/2
        theta[theta < 0] += np.pi*2.0
@@ -366,7 +369,7 @@ class CylMesh(BaseTensorMesh, BaseRectangularMesh, InnerProducts, CylView):
                        'Ex': Mrect.tangents[:Mrect.nEx,:],
                        'Ey': Mrect.tangents[Mrect.nEx:(Mrect.nEx+Mrect.nEy),:],
                        'Ez': Mrect.tangents[-Mrect.nEz:,:],
-                    }[locType]
+                    }[locTypeTo]
            if 'F' in locType:
                normals = np.c_[np.cos(theta), np.sin(theta), np.zeros(theta.size)]
                proj = ( normals * dotMe ).sum(axis=1)
@@ -24,7 +24,6 @@ class TensorMeshIO(object):
                    re = int(sp[0])*(' ' + sp[1])
                    line = line.replace(st,re.strip())
            return np.array(line.split(),dtype=float)
-
        # Read the file as line strings, remove lines with comment = !
        msh = np.genfromtxt(fileName,delimiter='\n',dtype=np.str,comments='!')

@@ -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

@@ -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
@@ -1003,6 +1003,7 @@ class ProjectedGNCG(BFGS, Minimize, Remember):
                # 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.
@@ -74,7 +74,7 @@ class Property(object):
                if linkedMap is None:
                    return None
                linkMap = linkMapClass(None) * linkedMap
-                m = getattr(self, '%s'%linkName)
+                m = getattr(self, '%sModel'%linkName)
                return linkMap.deriv( m )

            m = getattr(self, '%sModel'%prop.name)
@@ -239,7 +239,7 @@ class PropMap(object):
            setattr(self, '%sMap'%name, mapping)
            setattr(self, '%sIndex'%name, slices.get(name, slice(nP, nP + mapping.nP)))
            nP += mapping.nP
-        self.nP = nP 
+        self.nP = nP

    @property
    def defaultInvProp(self):
@@ -39,7 +39,7 @@ class RegularizationMesh(object):
            if self.indActive is None:
                self._nC = self.mesh.nC
            else:
-                self._nC = sum(self.indActive)
+                self._nC = int(sum(self.indActive))
        return self._nC

    @property
@@ -304,18 +304,29 @@ class BaseRegularization(object):
    mesh    = None    #: A SimPEG.Mesh instance.
    mref    = None    #: Reference model.

-    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
+    def __init__(self, mesh=None, nP=None, mapping=None, indActive=None, **kwargs):
        Utils.setKwargs(self, **kwargs)
        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
+        if indActive is not None and mapping is None:
+            mapping = Maps.IdentityMap(nP=indActive.nonzero()[0].size)
+
+        if mesh is None and nP is None:
+            raise Exception, 'either Mesh or number of parameters must be provided to the BaseRegularization'
+
        self.regmesh = RegularizationMesh(mesh,indActive)
-        self.mapping = mapping or self.mapPair(mesh)
-        self.mapping._assertMatchesPair(self.mapPair)
        self.indActive = indActive

+        if mesh is not None and nP is None:
+            nP = self.regmesh.nC
+        self.nP = nP
+
+        self.mapping = mapping or self.mapPair(nP=self.nP)
+        self.mapping._assertMatchesPair(self.mapPair)
+
    @property
    def parent(self):
        """This is the parent of the regularization."""
@@ -343,8 +354,7 @@ class BaseRegularization(object):
    @property
    def W(self):
        """Full regularization weighting matrix W."""
-        return sp.identity(self.regmesh.nC)
-        # self.regmesh._Pac.T * sp.identity(self.regmesh.nC) * self.regmesh._Pac # or do we want sp.identity(self.mesh.nC) or even just Utils.Identity() ?
+        return sp.identity(self.nP)

    @Utils.timeIt
    def eval(self, m):
@@ -375,11 +385,12 @@ 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:

@@ -402,25 +413,48 @@ class BaseRegularization(object):

 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
    """
-    mrefInSmooth = True  #: SMOOTH and SMOOTH_MOD_DIF options
-    alpha_s  = Utils.dependentProperty('_alpha_s', 1e-6, ['_W', '_Ws'], "Smallness weight")
-    alpha_x  = Utils.dependentProperty('_alpha_x', 1.0, ['_W', '_Wx'], "Weight for the first derivative in the x direction")
-    alpha_y  = Utils.dependentProperty('_alpha_y', 1.0, ['_W', '_Wy'], "Weight for the first derivative in the y direction")
-    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, indActive=indActive, **kwargs)

    @property
-    def Ws(self):
-        """Regularization matrix Ws"""
-        if getattr(self,'_Ws', None) is None:
-            self._Ws = Utils.sdiag((self.regmesh.vol*self.alpha_s)**0.5)
-        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):
@@ -483,25 +517,44 @@ 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.mrefInSmooth == True:
-            r1 = self.Wsmooth * ( self.mapping * (m) )
-            r2 = self.Ws * ( self.mapping * (m - self.mref) )
-            return 0.5*(r1.dot(r1)+r2.dot(r2))
-        elif self.mrefInSmooth == False:
-            r = self.W * ( self.mapping * (m - self.mref) )
-            return 0.5*r.dot(r)
+    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::
@@ -515,45 +568,33 @@ class Tikhonov(BaseRegularization):
            R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}

        """
-        if self.mrefInSmooth == True:
-            mD1 = self.mapping.deriv(m)
-            mD2 = self.mapping.deriv(m - self.mref)
-            r1 = self.Wsmooth * ( self.mapping * (m))
-            r2 = self.Ws * ( self.mapping * (m - self.mref) )
-            out1 = mD1.T * ( self.Wsmooth.T * r1 )
-            out2 = mD2.T * ( self.Ws.T * r2 )
-            out = out1+out2
-        elif self.mrefInSmooth == False:
-            mD = self.mapping.deriv(m - self.mref)
-            r = self.W * ( self.mapping * (m - self.mref) )
-            out = mD.T * ( self.W.T * r )
-        return out
+        return self._evalSmallDeriv(m) + self._evalSmoothDeriv(m)


-class Simple(BaseRegularization):
+class Simple(Tikhonov):
    """
-        Only for tensor mesh
+    Simple regularization that does not include length scales in the derivatives.
    """

-    mrefInSmooth = True  #: SMOOTH and SMOOTH_MOD_DIF options
-    alpha_s     = Utils.dependentProperty('_alpha_s', 1.0, ['_W', '_Ws'], "Smallness weight")
+    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.
-    
+
    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
        BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
-        
+
        if isinstance(self.wght,float):
            self.wght = np.ones(self.regmesh.nC) * self.wght

    @property
-    def Ws(self):
-        """Regularization matrix Ws"""
-        if getattr(self,'_Ws', None) is None:
-                self._Ws = Utils.sdiag((self.regmesh.vol*self.alpha_s*self.wght)**0.5)
-        return self._Ws
+    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 Wx(self):
@@ -592,99 +633,65 @@ class Simple(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 _evalSmall(self, m):
+        r = self.Wsmall * ( self.mapping * (m - self.mref) )
+        return 0.5 * r.dot(r)

    @Utils.timeIt
-    def eval(self, m):
+    def _evalSmooth(self, m):
        if self.mrefInSmooth == True:
-            r1 = self.Wsmooth * ( self.mapping * (m) )
-            r2 = self.Ws * ( self.mapping * (m - self.mref) )
-            return 0.5*(r1.dot(r1)+r2.dot(r2))
+            r = self.Wsmooth * ( self.mapping * (m - self.mref) )
        elif self.mrefInSmooth == False:
-            r = self.W * ( self.mapping * (m - self.mref) )
-            return 0.5*r.dot(r)
-        return phim
-
-
-
-    @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})}
-
-        """
-        if self.mrefInSmooth == True:
-            mD1 = self.mapping.deriv(m)
-            mD2 = self.mapping.deriv(m - self.mref)
-            r1 = self.Wsmooth * ( self.mapping * (m))
-            r2 = self.Ws * ( self.mapping * (m - self.mref) )
-            out1 = mD1.T * ( self.Wsmooth.T * r1 )
-            out2 = mD2.T * ( self.Ws.T * r2 )
-            out = out1+out2
-        elif self.mrefInSmooth == False:
-            mD = self.mapping.deriv(m - self.mref)
-            r = self.W * ( self.mapping * (m - self.mref) )
-            out = mD.T * ( self.W.T * r )
-        return out
+            r = self.Wsmooth * ( self.mapping * m)
+        return 0.5 * r.dot(r)


 class Sparse(Simple):

    # set default values
-    eps      = 1e-1
+    eps_p      = 1e-1
+    eps_q      = 1e-1
    curModel = None # use a model to compute the weights
    gamma    = 1.
-    p        = 0.
-    qx       = 2.
-    qy       = 2.
-    qz       = 2.
+    norms    = [0., 2., 2., 2.]
    wght     = 1.

    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
        Simple.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
-        
+
        if isinstance(self.wght,float):
            self.wght = np.ones(self.regmesh.nC) * self.wght

    @property
-    def Ws(self):
-        """Regularization matrix Ws"""
+    def Wsmall(self):
+        """Regularization matrix Wsmall"""
        if getattr(self, 'curModel', None) is None:
            self.Rs = Utils.speye(self.regmesh.nC)

        else:
            f_m = self.curModel - self.reg.mref
-            self.rs = self.R(f_m , self.p)
+            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 )
-            
+
        return Utils.sdiag((self.regmesh.vol*self.alpha_s*self.gamma*self.wght)**0.5)*self.Rs


    @property
    def Wx(self):
        """Regularization matrix Wx"""
-            
+
        if getattr(self, 'curModel', None) is None:
            self.Rx = Utils.speye(self.regmesh.cellDiffxStencil.shape[0])

        else:
            f_m = self.regmesh.cellDiffxStencil * self.curModel
-            self.rx = self.R( f_m , self.qx)
+            self.rx = self.R( f_m , self.eps_q, self.norms[1])
            self.Rx = Utils.sdiag( self.rx )

        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
@@ -698,9 +705,9 @@ class Sparse(Simple):

        else:
            f_m = self.regmesh.cellDiffyStencil * self.curModel
-            self.ry = self.R( f_m , self.qy)
+            self.ry = self.R( f_m , self.eps_q, self.norms[2])
            self.Ry = Utils.sdiag( self.ry )
-            
+
        return Utils.sdiag(((self.regmesh.aveCC2Fy * self.regmesh.vol)*self.alpha_y*self.gamma*(self.regmesh.aveCC2Fy*self.wght))**0.5)*self.Ry*self.regmesh.cellDiffyStencil

    @property
@@ -712,7 +719,7 @@ class Sparse(Simple):

        else:
            f_m = self.regmesh.cellDiffzStencil * self.curModel
-            self.rz = self.R( f_m , self.qz)
+            self.rz = self.R( f_m , self.eps_q, self.norms[3])
            self.Rz = Utils.sdiag( self.rz )

        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
@@ -732,14 +739,14 @@ class Sparse(Simple):
    @property
    def W(self):
        """Full regularization matrix W"""
-        #if getattr(self, '_W', None) is None:
-        wlist = (self.Ws, self.Wsmooth)
-        #self._W = sp.vstack(wlist)
-        return sp.vstack(wlist)
-        
-    def R(self, f_m , exponent):
+        if getattr(self, '_W', None) is None:
+            wlist = (self.Wsmall, self.Wsmooth)
+            self._W = sp.vstack(wlist)
+        return self._W

-        eta = (self.eps**(1-exponent/2.))**0.5
-        r = eta / (f_m**2.+self.eps**2.)**((1-exponent/2.)/2.)
+    def R(self, f_m , eps, exponent):
+
+        eta = (eps**(1.-exponent/2.))**0.5
+        r = eta / (f_m**2.+ eps**2.)**((1.-exponent/2.)/2.)

        return r
@@ -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)
@@ -7,3 +7,4 @@ from CounterUtils import *
 import ModelBuilder
 import SolverUtils
 from coordutils import *
+from modelutils import *
@@ -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
@@ -0,0 +1,137 @@
+from SimPEG import np, Mesh
+import time as tm
+import vtk, vtk.util.numpy_support as npsup
+import re
+
+def read_GOCAD_ts(tsfile):
+    """
+
+    Read GOCAD triangulated surface (*.ts) file
+    INPUT:
+    tsfile: Triangulated surface
+
+    OUTPUT:
+    vrts : Array of vertices in XYZ coordinates [n x 3]
+    trgl : Array of index for triangles [m x 3]. The order of the vertices
+            is important and describes the normal
+            n = cross( (P2 - P1 ) , (P3 - P1) )
+
+    Author: @fourndo
+
+
+    .. note::
+
+        Remove all attributes from the GoCAD surface before exporting it!
+
+    """
+
+
+    fid = open(tsfile,'r')
+    line = fid.readline()
+
+    # Skip all the lines until the vertices
+    while re.match('TFACE',line)==None:
+        line = fid.readline()
+
+    line = fid.readline()
+    vrtx = []
+
+    # Run down all the vertices and save in array
+    while re.match('VRTX',line):
+        l_input  = re.split('[\s*]',line)
+        temp = np.array(l_input[2:5])
+        vrtx.append(temp.astype(np.float))
+
+        # Read next line
+        line = fid.readline()
+
+    vrtx = np.asarray(vrtx)
+
+    # Skip lines to the triangles
+    while re.match('TRGL',line)==None:
+        line = fid.readline()
+
+    # Run down the list of triangles
+    trgl = []
+
+    # Run down all the vertices and save in array
+    while re.match('TRGL',line):
+        l_input  = re.split('[\s*]',line)
+        temp = np.array(l_input[1:4])
+        trgl.append(temp.astype(np.int))
+
+        # Read next line
+        line = fid.readline()
+
+    trgl = np.asarray(trgl)
+
+    return vrtx, trgl
+
+def surface2inds(vrtx, trgl, mesh, boundaries=True, internal=True):
+    """"
+    Function to read gocad polystructure file and output indexes of mesh with in the structure.
+
+    """
+    # Adjust the index
+    trgl = trgl - 1
+
+    # Make vtk pts
+    ptsvtk = vtk.vtkPoints()
+    ptsvtk.SetData(npsup.numpy_to_vtk(vrtx,deep=1))
+
+    # Make the polygon connection
+    polys = vtk.vtkCellArray()
+    for face in trgl:
+        poly = vtk.vtkPolygon()
+        poly.GetPointIds().SetNumberOfIds(len(face))
+        for nrv, vert in enumerate(face):
+            poly.GetPointIds().SetId(nrv,vert)
+        polys.InsertNextCell(poly)
+
+    # Make the polydata, structure of connections and vrtx
+    polyData = vtk.vtkPolyData()
+    polyData.SetPoints(ptsvtk)
+    polyData.SetPolys(polys)
+
+    # Make implicit func
+    ImpDistFunc = vtk.vtkImplicitPolyDataDistance()
+    ImpDistFunc.SetInput(polyData)
+
+    # Convert the mesh
+    vtkMesh = vtk.vtkRectilinearGrid()
+    vtkMesh.SetDimensions(mesh.nNx,mesh.nNy,mesh.nNz)
+    vtkMesh.SetXCoordinates(npsup.numpy_to_vtk(mesh.vectorNx, deep=1))
+    vtkMesh.SetYCoordinates(npsup.numpy_to_vtk(mesh.vectorNy, deep=1))
+    vtkMesh.SetZCoordinates(npsup.numpy_to_vtk(mesh.vectorNz, deep=1))
+    # Add indexes
+    vtkInd = npsup.numpy_to_vtk(np.arange(mesh.nC), deep=1)
+    vtkInd.SetName('Index')
+    vtkMesh.GetCellData().AddArray(vtkInd)
+
+    extractImpDistRectGridFilt = vtk.vtkExtractGeometry() # Object constructor
+    extractImpDistRectGridFilt.SetImplicitFunction(ImpDistFunc) #
+    extractImpDistRectGridFilt.SetInputData(vtkMesh)
+
+    if boundaries is True:
+        extractImpDistRectGridFilt.ExtractBoundaryCellsOn()
+
+    else:
+        extractImpDistRectGridFilt.ExtractBoundaryCellsOff()
+
+    if internal is True:
+        extractImpDistRectGridFilt.ExtractInsideOn()
+
+    else:
+        extractImpDistRectGridFilt.ExtractInsideOff()
+
+    print "Extracting indices from grid..."
+    # Executing the pipe
+    extractImpDistRectGridFilt.Update()
+
+    # Get index inside
+    insideGrid = extractImpDistRectGridFilt.GetOutput()
+    insideGrid = npsup.vtk_to_numpy(insideGrid.GetCellData().GetArray('Index'))
+
+
+    # Return the indexes inside
+    return insideGrid
@@ -0,0 +1,63 @@
+from matutils import mkvc, ndgrid
+import numpy as np
+
+def surface2ind_topo(mesh, topo, gridLoc='CC'):
+# def genActiveindfromTopo(mesh, topo):
+    """
+    Get active indices from topography
+    """
+
+
+    if mesh.dim == 3:
+        from scipy.interpolate import NearestNDInterpolator
+        Ftopo = NearestNDInterpolator(topo[:,:2], topo[:,2])
+
+        if gridLoc == 'CC':
+            XY = ndgrid(mesh.vectorCCx, mesh.vectorCCy)
+            Zcc = mesh.gridCC[:,2].reshape((np.prod(mesh.vnC[:2]), mesh.nCz), order='F')
+
+            gridTopo = Ftopo(XY)
+            actind = [gridTopo[ixy] <= Zcc[ixy,:] for ixy in range(np.prod(mesh.vnC[0]))]
+            actind = np.hstack(actind)
+
+        elif gridLoc == 'N':
+
+            XY = ndgrid(mesh.vectorNx, mesh.vectorNy)
+            gridTopo = Ftopo(XY).reshape(mesh.vnN[:2], order='F')
+
+            if mesh._meshType not in ['TENSOR', 'CYL', 'BASETENSOR']:
+                raise NotImplementedError('Nodal surface2ind_topo not implemented for %s mesh'%mesh._meshType)
+
+            Nz = mesh.vectorNz[1:] # TODO: this will only work for tensor meshes
+            actind = np.array([False]*mesh.nC).reshape(mesh.vnC, order='F')
+
+            for ii in range(mesh.nCx):
+                for jj in range(mesh.nCy):
+                     actind[ii,jj,:] = [np.all(gridTopo[ii:ii+2, jj:jj+2] >= Nz[kk]) for kk in range(len(Nz)) ]
+
+    elif mesh.dim == 2:
+        from scipy.interpolate import interp1d
+        Ftopo = interp1d(topo[:,0], topo[:,1])
+
+        if gridLoc == 'CC':
+            gridTopo = Ftopo(mesh.gridCC[:,0])
+            actind = mesh.gridCC[:,1] <= gridTopo
+
+        elif gridLoc == 'N':
+
+            gridTopo = Ftopo(mesh.vectorNx)
+            if mesh._meshType not in ['TENSOR', 'CYL', 'BASETENSOR']:
+                raise NotImplementedError('Nodal surface2ind_topo not implemented for %s mesh'%mesh._meshType)
+
+            Ny = mesh.vectorNy[1:] # TODO: this will only work for tensor meshes
+            actind = np.array([False]*mesh.nC).reshape(mesh.vnC, order='F')
+
+            for ii in range(mesh.nCx):
+                actind[ii,:] = [np.all(gridTopo[ii:ii+2] > Ny[kk]) for kk in range(len(Ny)) ]
+
+    else:
+        raise NotImplementedError('surface2ind_topo not implemented for 1D mesh')
+
+    return mkvc(actind)
+
+
@@ -122,92 +122,10 @@ When these are used in the inverse problem, this is extremely important!!
 The API
 =======

-.. autoclass:: SimPEG.Maps.IdentityMap
+.. automodule:: SimPEG.Maps
    :members:
    :undoc-members:


-Common Maps
-===========


-Exponential Map
---------------
-
-Electrical conductivity varies over many orders of magnitude, so it is a common
-technique when solving the inverse problem to parameterize and optimize in terms
-of log conductivity. This makes sense not only because it ensures all conductivities
-will be positive, but because this is fundamentally the space where conductivity
-lives (i.e. it varies logarithmically).
-
-.. autoclass:: SimPEG.Maps.ExpMap
-    :members:
-    :undoc-members:
-
-
-Vertical 1D Map
---------------
-
-.. autoclass:: SimPEG.Maps.Vertical1DMap
-    :members:
-    :undoc-members:
-
-
-Map 2D Cross-Section to 3D Model
--------------------------------
-
-.. autoclass:: SimPEG.Maps.Map2Dto3D
-    :members:
-    :undoc-members:
-
-
-Mesh to Mesh Map
----------------
-
-
-.. plot::
-
-    from SimPEG import *
-    import matplotlib.pyplot as plt
-    M = Mesh.TensorMesh([100,100])
-    h1 = Utils.meshTensor([(6,7,-1.5),(6,10),(6,7,1.5)])
-    h1 = h1/h1.sum()
-    M2 = Mesh.TensorMesh([h1,h1])
-    V = Utils.ModelBuilder.randomModel(M.vnC, seed=79, its=50)
-    v = Utils.mkvc(V)
-    modh = Maps.Mesh2Mesh([M,M2])
-    modH = Maps.Mesh2Mesh([M2,M])
-    H = modH * v
-    h = modh * H
-    ax = plt.subplot(131)
-    M.plotImage(v, ax=ax)
-    ax.set_title('Fine Mesh (Original)')
-    ax = plt.subplot(132)
-    M2.plotImage(H,clim=[0,1],ax=ax)
-    ax.set_title('Course Mesh')
-    ax = plt.subplot(133)
-    M.plotImage(h,clim=[0,1],ax=ax)
-    ax.set_title('Fine Mesh (Interpolated)')
-    plt.show()
-
-
-.. autoclass:: SimPEG.Maps.Mesh2Mesh
-    :members:
-    :undoc-members:
-
-
-Some Extras
-===========
-
-Combo Map
---------
-
-The ComboMap holds the information for multiplying and combining
-maps. It also uses the chain rule to create the derivative.
-Remember, any time that you make your own combination of mappings
-be sure to test that the derivative is correct.
-
-.. autoclass:: SimPEG.Maps.ComboMap
-    :members:
-    :undoc-members:
-
@@ -12,9 +12,18 @@
 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]
+surveyType = survey type 'pole-dipole' or 'dipole-dipole'
+unitType = Data type "appResistivity" | "appConductivity"  | "volt"
+
+Created by @fourndo



@@ -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:
@@ -0,0 +1,24 @@
+.. _examples_Utils_surface2ind_topo:
+
+.. --------------------------------- ..
+..                                   ..
+..    THIS FILE IS AUTO GENEREATED   ..
+..                                   ..
+..    SimPEG/Examples/__init__.py    ..
+..                                   ..
+.. --------------------------------- ..
+
+
+Here we show how to use :code:`Utils.surface2ind_topo` to identify cells below
+a topographic surface.
+
+
+
+.. plot::
+
+    from SimPEG import Examples
+    Examples.Utils_surface2ind_topo.run()
+
+.. literalinclude:: ../../SimPEG/Examples/Utils_surface2ind_topo.py
+    :language: python
+    :linenos:
@@ -5,16 +5,17 @@ SimPEG is a python package for simulation and gradient based
 parameter estimation in the context of geophysical applications.
 """

-import numpy as np
-
 import os
 import sys
 import subprocess

 from distutils.core import setup
+from distutils.command.build_ext import build_ext
 from setuptools import find_packages
 from distutils.extension import Extension

+
+
 CLASSIFIERS = [
 'Development Status :: 4 - Beta',
 'Intended Audience :: Developers',
@@ -51,11 +52,16 @@ if args.count("build_ext") > 0 and args.count("--inplace") == 0:
 try:
    from Cython.Build import cythonize
    from Cython.Distutils import build_ext
-    cythonKwargs = dict(cmdclass={'build_ext': build_ext})
    USE_CYTHON = True
 except Exception, e:
    USE_CYTHON = False
-    cythonKwargs = dict()
+
+class NumpyBuild(build_ext):
+    def finalize_options(self):
+        build_ext.finalize_options(self)
+        __builtins__.__NUMPY_SETUP__ = False
+        import numpy
+        self.include_dirs.append(numpy.get_include())

 ext = '.pyx' if USE_CYTHON else '.c'

@@ -94,8 +100,8 @@ setup(
    classifiers=CLASSIFIERS,
    platforms = ["Windows", "Linux", "Solaris", "Mac OS-X", "Unix"],
    use_2to3 = False,
-    include_dirs=[np.get_include()],
+    cmdclass={'build_ext':NumpyBuild},
+    setup_requires=['numpy'],
    ext_modules = extensions,
    scripts=scripts,
-    **cythonKwargs
 )
@@ -1,6 +1,7 @@
 import unittest
 from SimPEG import *
 from scipy.constants import mu_0
+from SimPEG import Tests


 class MyPropMap(Maps.PropMap):
@@ -187,6 +188,34 @@ class TestPropMaps(unittest.TestCase):

        MyReciprocalPropMap([('sigma', iMap), ('mu', iMap)]) # This should be fine

+    def test_linked_derivs_sigma(self):
+        mesh = Mesh.TensorMesh([4,5], x0='CC')
+
+        mapping = Maps.ExpMap(mesh)
+        propmap = MyReciprocalPropMap([('rho', mapping)])
+
+        x0 = np.random.rand(mesh.nC)
+        m  = propmap(x0)
+
+        # test Sigma
+        testme = lambda v: [1./(m.rhoMap*v), m.sigmaDeriv]
+        print 'Testing Rho from Sigma'
+        Tests.checkDerivative(testme, x0, dx=0.01*x0, num=5, plotIt=False)
+
+    def test_linked_derivs_rho(self):
+        mesh = Mesh.TensorMesh([4,5], x0='CC')
+
+        mapping = Maps.ExpMap(mesh)
+        propmap = MyReciprocalPropMap([('sigma', mapping)])
+
+        x0 = np.random.rand(mesh.nC)
+        m  = propmap(x0)
+
+        # test Sigma
+        testme = lambda v: [1./(m.sigmaMap*v), m.rhoDeriv]
+        print 'Testing Rho from Sigma'
+        Tests.checkDerivative(testme, x0, dx=0.01*x0, num=5, plotIt=False)
+
 if __name__ == '__main__':
    unittest.main()

@@ -5,8 +5,10 @@ from scipy.sparse.linalg import dsolve

 TOL = 1e-14

-MAPS_TO_TEST_2D = ["CircleMap", "ComplexMap", "ExpMap", "IdentityMap", "SurjectVertical1D", "Weighting", "SurjectFull","FullMap","Vertical1DMap"]
-MAPS_TO_TEST_3D = [             "ComplexMap", "ExpMap", "IdentityMap", "SurjectVertical1D", "Weighting", "SurjectFull","FullMap","Vertical1DMap"]
+MAPS_TO_TEST_2D = ["CircleMap", "ComplexMap", "ExpMap", "IdentityMap", "SurjectVertical1D", "Weighting", "SurjectFull", "FullMap", "Vertical1DMap", "ParametrizedLayer", "ParametrizedBlockInLayer"]
+MAPS_TO_TEST_3D = [             "ComplexMap", "ExpMap", "IdentityMap", "SurjectVertical1D", "Weighting", "SurjectFull", "FullMap", "Vertical1DMap", "ParametrizedLayer", "ParametrizedBlockInLayer"]
+MAPS_TO_TEST_CYL = [             "ComplexMap", "ExpMap", "IdentityMap", "SurjectVertical1D", "Weighting", "SurjectFull", "FullMap", "Vertical1DMap", "ParametrizedLayer"]
+

 class MapTests(unittest.TestCase):

@@ -17,6 +19,8 @@ class MapTests(unittest.TestCase):
        self.mesh2 = Mesh.TensorMesh([a, b], x0=np.array([3, 5]))
        self.mesh3 = Mesh.TensorMesh([a, b, [3,4]], x0=np.array([3, 5, 2]))
        self.mesh22 = Mesh.TensorMesh([b, a], x0=np.array([3, 5]))
+        self.meshCyl = Mesh.CylMesh([10.,1.,10.], x0='00C')
+        print self.meshCyl._meshType

    def test_transforms2D(self):
        for M in MAPS_TO_TEST_2D:
@@ -28,6 +32,15 @@ class MapTests(unittest.TestCase):
            maps = getattr(Maps, M)(self.mesh3)
            self.assertTrue(maps.test())

+    def test_transformsCyl(self):
+        for M in MAPS_TO_TEST_CYL:
+            maps = getattr(Maps, M)(self.meshCyl)
+            self.assertTrue(maps.test())
+
+    def test_ParametricCasingAndLayer(self):
+        mapping = Maps.ParametrizedCasingAndLayer(self.meshCyl)
+        m = np.r_[-2., 1., 6., 2., -0.1, 0.2, 0.5, 0.2, -0.2, 0.2]
+        self.assertTrue(mapping.test(m))

    def test_transforms_logMap_reciprocalMap(self):
        # Note that log/reciprocal maps can be kinda finicky, so we are being explicit about the random seed.
@@ -65,10 +65,8 @@ class RegularizationTests(unittest.TestCase):
                    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)
+                        reg = r(mesh, indActive=indAct)
                        m = np.random.rand(mesh.nC)[indAct]
                        reg.mref = np.ones_like(m)*np.mean(m)

@@ -28,12 +28,12 @@ class FDEM_analyticTests(unittest.TestCase):

        x = np.linspace(-10,10,5)
        XYZ = Utils.ndgrid(x,np.r_[0],np.r_[0])
-        rxList = EM.FDEM.Rx(XYZ, 'exi')
+        rxList = EM.FDEM.Rx.Point_e(XYZ, orientation='x', component='imag')
        Src0 = EM.FDEM.Src.MagDipole([rxList],loc=np.r_[0.,0.,0.], freq=freq)

        survey = EM.FDEM.Survey([Src0])

-        prb = EM.FDEM.Problem_b(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem3D_b(mesh, mapping=mapping)
        prb.pair(survey)

        try:
@@ -125,8 +125,8 @@ class FDEM_analyticTests(unittest.TestCase):

        mapping = [('sigma', Maps.IdentityMap(mesh)),('mu', Maps.IdentityMap(mesh))]

-        prbe = EM.FDEM.Problem_h(mesh, mapping=mapping)
-        prbm = EM.FDEM.Problem_e(mesh, mapping=mapping)
+        prbe = EM.FDEM.Problem3D_h(mesh, mapping=mapping)
+        prbm = EM.FDEM.Problem3D_e(mesh, mapping=mapping)

        prbe.pair(surveye) # pair problem and survey
        prbm.pair(surveym)
@@ -12,7 +12,7 @@ testBH = True
 verbose = False

 TOLEJHB = 1 # averaging and more sensitive to boundary condition violations (ie. the impact of violating the boundary conditions in each case is different.)
-#TODO: choose better testing parameters to lower this 
+#TODO: choose better testing parameters to lower this

 SrcList = ['RawVec', 'MagDipole_Bfield', 'MagDipole', 'CircularLoop']

@@ -125,4 +125,4 @@ class FDEM_CrossCheck(unittest.TestCase):
            self.assertTrue(crossCheckTest(SrcList, 'b', 'h', 'hzi', verbose=verbose, TOL=TOLEJHB))

 if __name__ == '__main__':
-    unittest.main()
+    unittest.main()
@@ -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)
@@ -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, earth_type="halfspace")
+
+        rx = DC.Rx.Dipole_ky(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()
+
@@ -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()
@@ -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, earth_type="halfspace")
+        phiB = EM.Analytics.DCAnalyticHalf(Bloc, [M,N], 1e-2, earth_type="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()
+
@@ -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()
@@ -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()
+
@@ -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()
@@ -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()
@@ -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)]
@@ -6,10 +6,23 @@ from SimPEG import *

 MESHTYPES = ['uniformTensorMesh']

-def getxBCyBC(mesh, alpha, beta, gamma):
+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):
@@ -21,7 +34,8 @@ def getxBCyBC(mesh, alpha, beta, gamma):
        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.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)
@@ -40,19 +54,19 @@ def getxBCyBC(mesh, alpha, beta, gamma):
        if (len(alpha) != 4 or len(beta) != 4 or len(gamma) != 4):
            raise Exception("Lenght of list, alpha should be 4")

-        fCCxm,fCCxp,fCCym,fCCyp = mesh.cellBoundaryInd
        fxm,fxp,fym,fyp = mesh.faceBoundaryInd
-        nBC = fCCxm.sum()+fCCxp.sum()+fCCxm.sum()+fCCxp.sum()
-        h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
-        h_ym, h_yp = mesh.gridCC[fCCym], mesh.gridCC[fCCyp]
+        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.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)
@@ -87,23 +101,24 @@ def getxBCyBC(mesh, alpha, beta, gamma):
    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
+        # fCCxm,fCCxp,fCCym,fCCyp,fCCzm,fCCzp = mesh.cellBoundaryInd
        fxm,fxp,fym,fyp,fzm,fzp = mesh.faceBoundaryInd
-        nBC = fCCxm.sum()+fCCxp.sum()+fCCxm.sum()+fCCxp.sum()
-        h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
-        h_ym, h_yp = mesh.gridCC[fCCym], mesh.gridCC[fCCyp]
-        h_zm, h_zp = mesh.gridCC[fCCzm], mesh.gridCC[fCCzp]
+        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[2], beta[2], gamma[2]
-        alpha_zp, beta_zp, gamma_zp = 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.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)
@@ -182,7 +197,7 @@ class Test1D_InhomogeneousMixed(Tests.OrderTest):
        phi_bc = phi_fun(vecN[[0,-1]])
        phi_deriv_bc = phi_deriv(vecN[[0,-1]])
        gamma = alpha*phi_bc + beta*phi_deriv_bc
-        x_BC, y_BC = getxBCyBC(self.M, alpha, beta, gamma)
+        x_BC, y_BC = getxBCyBC_CC(self.M, alpha, beta, gamma)


        sigma = np.ones(self.M.nC)
@@ -265,7 +280,7 @@ class Test2D_InhomogeneousMixed(Tests.OrderTest):
        beta = [beta_xm, beta_xp, beta_ym, beta_yp]
        gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp]

-        x_BC, y_BC = getxBCyBC(self.M, alpha, beta, gamma)
+        x_BC, y_BC = getxBCyBC_CC(self.M, alpha, beta, gamma)


        sigma = np.ones(self.M.nC)
@@ -335,8 +350,8 @@ class Test3D_InhomogeneousMixed(Tests.OrderTest):
        beta_xm, beta_xp =  np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
        alpha_ym, alpha_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
        beta_ym, beta_yp =  np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
-        alpha_zm, alpha_zp = np.ones_like(gBFzm[:,1]), np.ones_like(gBFzp[:,1])
-        beta_zm, beta_zp =  np.ones_like(gBFzm[:,1]), np.ones_like(gBFzp[:,1])
+        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)
@@ -345,7 +360,7 @@ class Test3D_InhomogeneousMixed(Tests.OrderTest):

        phiderivX_bc_xm, phiderivX_bc_xp = phideriv_funX(gBFxm), phideriv_funX(gBFxp)
        phiderivY_bc_ym, phiderivY_bc_yp = phideriv_funY(gBFym), phideriv_funY(gBFyp)
-        phiderivY_bc_zm, phiderivY_bc_zp = phideriv_funY(gBFzm), phideriv_funY(gBFzp)
+        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)
@@ -359,7 +374,7 @@ class Test3D_InhomogeneousMixed(Tests.OrderTest):
        beta = [beta_xm, beta_xp, beta_ym, beta_yp, beta_zm, beta_zp]
        gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp, gamma_zm, gamma_zp]

-        x_BC, y_BC = getxBCyBC(self.M, alpha, beta, gamma)
+        x_BC, y_BC = getxBCyBC_CC(self.M, alpha, beta, gamma)


        sigma = np.ones(self.M.nC)
@@ -146,6 +146,20 @@ class TestCyl2DMesh(unittest.TestCase):

        assert np.abs(Pr*(Pc2r*mc) - Pc*mc).max() < 1e-3

+    def test_getInterpMatCartMesh_Cells2Nodes(self):
+
+        Mr = Mesh.TensorMesh([100,100,2], x0='CC0')
+        Mc = Mesh.CylMesh([np.ones(10)/5,1,10],x0='0C0',cartesianOrigin=[-0.2,-0.2,0])
+
+        mc = np.arange(Mc.nC)
+        xr = np.linspace(0,0.4,50)
+        xc = np.linspace(0,0.4,50) + 0.2
+        Pr = Mr.getInterpolationMat(np.c_[xr,np.ones(50)*-0.2,np.ones(50)*0.5],'N')
+        Pc = Mc.getInterpolationMat(np.c_[xc,np.zeros(50),np.ones(50)*0.5],'CC')
+        Pc2r = Mc.getInterpolationMatCartMesh(Mr, 'CC', locTypeTo='N')
+
+        assert np.abs(Pr*(Pc2r*mc) - Pc*mc).max() < 1e-3
+
    def test_getInterpMatCartMesh_Faces(self):

        Mr = Mesh.TensorMesh([100,100,2], x0='CC0')
@@ -177,6 +191,37 @@ class TestCyl2DMesh(unittest.TestCase):
        assert np.abs(mag[dist > 0.1].min() - 1) < TOL


+    def test_getInterpMatCartMesh_Faces2Edges(self):
+
+        Mr = Mesh.TensorMesh([100,100,2], x0='CC0')
+        Mc = Mesh.CylMesh([np.ones(10)/5,1,10],x0='0C0',cartesianOrigin=[-0.2,-0.2,0])
+
+        Pf2e = Mc.getInterpolationMatCartMesh(Mr, 'F', locTypeTo='E')
+        mf = np.ones(Mc.nF)
+
+        ecart = Pf2e * mf
+
+        excc = Mr.aveEx2CC*Mr.r(ecart, 'E', 'Ex')
+        eycc = Mr.aveEy2CC*Mr.r(ecart, 'E', 'Ey')
+        ezcc = Mr.r(ecart, 'E', 'Ez')
+
+        indX = Utils.closestPoints(Mr, [0.45, -0.2, 0.5])
+        indY = Utils.closestPoints(Mr, [-0.2, 0.45, 0.5])
+
+        TOL = 1e-2
+        assert np.abs(float(excc[indX]) - 1) < TOL
+        assert np.abs(float(excc[indY]) - 0) < TOL
+        assert np.abs(float(eycc[indX]) - 0) < TOL
+        assert np.abs(float(eycc[indY]) - 1) < TOL
+        assert np.abs((ezcc - 1).sum()) < TOL
+
+        mag = (excc**2 + eycc**2)**0.5
+        dist = ((Mr.gridCC[:,0] + 0.2)**2  + (Mr.gridCC[:,1] + 0.2)**2)**0.5
+
+        assert np.abs(mag[dist > 0.1].max() - 1) < TOL
+        assert np.abs(mag[dist > 0.1].min() - 1) < TOL
+
+
    def test_getInterpMatCartMesh_Edges(self):

        Mr = Mesh.TensorMesh([100,100,2], x0='CC0')
@@ -185,11 +230,42 @@ class TestCyl2DMesh(unittest.TestCase):
        Pe = Mc.getInterpolationMatCartMesh(Mr, 'E')
        me = np.ones(Mc.nE)

-        erect = Pe * me
+        ecart = Pe * me

-        excc = Mr.aveEx2CC*Mr.r(erect, 'E', 'Ex')
-        eycc = Mr.aveEy2CC*Mr.r(erect, 'E', 'Ey')
-        ezcc = Mr.r(erect, 'E', 'Ez')
+        excc = Mr.aveEx2CC*Mr.r(ecart, 'E', 'Ex')
+        eycc = Mr.aveEy2CC*Mr.r(ecart, 'E', 'Ey')
+        ezcc = Mr.aveEz2CC*Mr.r(ecart, 'E', 'Ez')
+
+        indX = Utils.closestPoints(Mr, [0.45, -0.2, 0.5])
+        indY = Utils.closestPoints(Mr, [-0.2, 0.45, 0.5])
+
+        TOL = 1e-2
+        assert np.abs(float(excc[indX]) - 0) < TOL
+        assert np.abs(float(excc[indY]) + 1) < TOL
+        assert np.abs(float(eycc[indX]) - 1) < TOL
+        assert np.abs(float(eycc[indY]) - 0) < TOL
+        assert np.abs(ezcc.sum()) < TOL
+
+        mag = (excc**2 + eycc**2)**0.5
+        dist = ((Mr.gridCC[:,0] + 0.2)**2  + (Mr.gridCC[:,1] + 0.2)**2)**0.5
+
+        assert np.abs(mag[dist > 0.1].max() - 1) < TOL
+        assert np.abs(mag[dist > 0.1].min() - 1) < TOL
+
+
+    def test_getInterpMatCartMesh_Edges2Faces(self):
+
+        Mr = Mesh.TensorMesh([100,100,2], x0='CC0')
+        Mc = Mesh.CylMesh([np.ones(10)/5,1,10],x0='0C0',cartesianOrigin=[-0.2,-0.2,0])
+
+        Pe2f = Mc.getInterpolationMatCartMesh(Mr, 'E', locTypeTo='F')
+        me = np.ones(Mc.nE)
+
+        frect = Pe2f * me
+
+        excc = Mr.aveFx2CC*Mr.r(frect, 'F', 'Fx')
+        eycc = Mr.aveFy2CC*Mr.r(frect, 'F', 'Fy')
+        ezcc = Mr.r(frect, 'F', 'Fz')

        indX = Utils.closestPoints(Mr, [0.45, -0.2, 0.5])
        indY = Utils.closestPoints(Mr, [-0.2, 0.45, 0.5])
@@ -242,9 +242,6 @@ class TestAnalytics(unittest.TestCase):
    def test_appRes1en3(self):self.assertTrue(appResPhsHalfspace_eFrom_ps_Norm(1e-3))
    def test_appPhs1en3(self):self.assertTrue(appResPhsHalfspace_eFrom_ps_Norm(1e-3,False))

-    # Do a derivative test
-    def test_derivProj1(self):self.assertTrue(DerivProjfieldsTest(halfSpace(1e-2)))
-
    # Do a derivative test of Jvec
    # def test_derivJvec_zxxr(self):self.assertTrue(DerivJvecTest(random(1e-2),'zxxr',.1))
    # def test_derivJvec_zxxi(self):self.assertTrue(DerivJvecTest(random(1e-2),'zxxi',.1))
Author	SHA1	Message	Date
Lindsey Heagy	3cbefac3ba	try using list for Jv instead of datapair - has been seen to cause memory leaks	2016-06-29 15:55:34 -07:00
Lindsey Heagy	e7e497a06d	don't use Zero() in mapping derivs)	2016-06-29 08:45:45 -07:00
Lindsey Heagy	3157aa02cf	naming update	2016-06-28 08:15:19 -07:00
Lindsey Heagy	c40d11ef53	- better model for testing Parametric casing map - allow vector containing values in the inactive set to be passed (not just nC in length)	2016-06-26 15:24:33 -07:00
Lindsey Heagy	c75e3d0246	use a dictionary to keep track of parametric model parameters. Test mappings on cyl meshes, parametric casing and layer model	2016-06-25 16:51:18 -07:00
Lindsey Heagy	14f0d90f99	debugging derivs	2016-06-23 13:06:15 -07:00
Lindsey Heagy	425b1e292c	only accept one source for the prim-sec source	2016-06-21 18:00:41 -07:00
Lindsey Heagy	f6cd8696d1	call fields inside of SrcDeriv for primsec	2016-06-21 17:36:53 -07:00
Lindsey Heagy	f788d5f05d	bug hunting a silly memory issue (don't add vectors to column arrays!). return sparse matrices from mapping derivs for multiplying things	2016-06-21 17:20:02 -07:00
Lindsey Heagy	1521b08af6	remove @property from projPrimary	2016-05-31 23:48:04 -07:00
Lindsey Heagy	8c366463e7	call projection with problem	2016-05-31 23:19:02 -07:00
Lindsey Heagy	6d77ae9a12	pass problem to projection matrix in primsecsrc	2016-05-31 23:08:57 -07:00
Lindsey Heagy	ce88c676d4	add a projection map (for re-arranging models) use current sigmaModel in src	2016-05-31 22:44:39 -07:00
Lindsey Heagy	1e6ed86135	- parametrized layer - parameterized block in layer inherits parametrized layer	2016-05-31 21:39:59 -07:00
Lindsey Heagy	9061ef5839	start of including primary fields derivs	2016-05-31 21:04:26 -07:00
Lindsey Heagy	0638fa308c	start of prim sec src with more derivs	2016-05-30 20:30:00 -07:00
Lindsey Heagy	54478ad05e	don't use adjoint when not asking for the adjoint!	2016-05-30 11:40:42 -07:00
Lindsey Heagy	2cf0edb736	bug fix in PrimSec src Deriv	2016-05-30 11:29:24 -07:00
Lindsey Heagy	3b5dfecb46	cleanup imports and class instantiation of prim-sec src in sigma	2016-05-30 10:05:15 -07:00
Lindsey Heagy	93d8ef5921	don't need m on the prim-sec src	2016-05-30 09:37:06 -07:00
Lindsey Heagy	5b0a58b751	typo in src input	2016-05-30 09:26:28 -07:00
Lindsey Heagy	9155a9c474	prim sec src in conductivity	2016-05-30 09:10:53 -07:00
Lindsey Heagy	64510bc606	Merge branch 'dev' into maps/feat-parametrizedBlock	2016-05-29 14:51:11 -07:00
Lindsey	09eb2106ec	Merge pull request #307 from simpeg/ref/dev Ref/dev	2016-05-29 14:50:43 -07:00
Lindsey Heagy	d9f0241da3	typo fix in nC (it is mesh.nC)	2016-05-29 14:21:08 -07:00
Lindsey Heagy	9a7225c9f6	- bug fix in parametrized block when active cells are used - need a shape - add a pole receiver for DC	2016-05-29 13:40:21 -07:00
Lindsey Heagy	e8e022fcc6	return a scipy sparse matrix for the deriv (a bit silly - it is dense, but nicer for multiplication). Init Regularization with a nP	2016-05-28 15:40:28 -07:00
Lindsey Heagy	341b98d23a	use layer center and layer thickness to parametrize layer	2016-05-28 13:06:19 -07:00
D Fournier	406703f1c6	Merge branch 'dev' into ref/dev Conflicts: docs/examples/DC_Forward_PseudoSection.rst	2016-05-27 11:10:39 -07:00
D Fournier	7b72d3a92d	Merge branch 'dev' into ref/dev Conflicts: SimPEG/DCIP/DCIPUtils.py	2016-05-27 10:01:28 -07:00
Lindsey Heagy	efbc8f9057	add docs for ParametrizedBlockInLayer, moved docs from rst to python files and automodule the docs for maps	2016-05-26 23:06:57 -07:00
Lindsey Heagy	39ece11d8a	Merge branch 'dev' into maps/feat-parametrizedBlock	2016-05-26 21:32:57 -07:00
Lindsey	cf89f5f6a2	Merge pull request #322 from simpeg/bug/propmap Bug/propmap	2016-05-26 20:52:42 -07:00
Lindsey Heagy	aa1086eba3	use fixed prop map in EM	2016-05-26 18:03:09 -07:00
Lindsey Heagy	1c53129da6	fix bug in prop map linked derivs	2016-05-26 17:58:30 -07:00
sgkang	6fd3be77de	Merge pull request #304 from simpeg/dcip/dev Dcip/dev	2016-05-26 13:27:44 -07:00
Lindsey Heagy	c36b5a600d	add parametrized block in a layer map	2016-05-26 10:30:10 -07:00
seogi_macbook	51d82eee26	Minor fixes to be merged to dev	2016-05-26 09:32:19 -07:00
seogi_macbook	f6b49c680a	Merge branch 'dev' of https://github.com/simpeg/simpeg into dcip/dev Conflicts: SimPEG/EM/Base.py SimPEG/EM/FDEM/SurveyFDEM.py	2016-05-26 09:25:43 -07:00
seogi_macbook	339543b893	Incorporate Lindsey's comments on documenting codes	2016-05-25 23:28:58 -07:00
seogi_macbook	44ad57e90d	Merge branch 'dcip/spectralIP' of https://github.com/simpeg/simpeg into dcip/dev Merge spectral IP stuff, and incorporate Lindsey's comments	2016-05-25 14:22:58 -07:00
Lindsey	d98eef2560	Merge pull request #313 from simpeg/em/dev Em/dev: Naming conventions	2016-05-25 10:53:43 -07:00
seogi_macbook	21d817d9a2	fix bug for adjoint problem	2016-05-24 21:53:18 -07:00
seogi_macbook	f20fcb4504	Minor type error based upon numpy version Cross gradient?	2016-05-24 08:45:12 -07:00
Lindsey Heagy	2c87a50d29	add kwargs to raw vec e,m	2016-05-23 12:21:29 -07:00
Lindsey Heagy	beca0203df	typo fix	2016-05-23 12:11:03 -07:00
Lindsey Heagy	e25b496ab0	allow kwarg input of primary fields	2016-05-23 12:07:14 -07:00
Lindsey	e5ec512517	Merge pull request #319 from simpeg/targetmisfit Target Misfit	2016-05-22 12:36:21 -07:00
Lindsey	342414bd25	Merge pull request #302 from simpeg/fix/numpyDependency Installation (i.e., setup.py) is no longer dependent on Numpy	2016-05-22 12:03:37 -07:00
Lindsey Heagy	8936fa4021	use phi_d_star, chifact in defining target misfit	2016-05-22 11:42:23 -07:00
seogi_macbook	0179631fe3	Starting Cross gradient ...	2016-05-20 01:57:40 -07:00
seogi_macbook	c4c97ae054	Ad MultiRegularization for inverting multiple parameters	2016-05-20 00:04:20 -07:00
seogi_macbook	e8bd78f63d	Working Spectral IP: - Fwd - Jvec - Jtvec	2016-05-19 02:09:48 +09:00
Lindsey	d0a65dda1b	Merge pull request #317 from simpeg/em/ref/dev-cleanup em/dev cleanup	2016-05-18 08:13:06 -07:00
Lindsey Heagy	a506d5c6be	Merge branch 'em/dev' into em/ref/dev-cleanup	2016-05-18 07:31:15 -07:00
Lindsey Heagy	10c8791514	update base MT to import ProblemFDEM	2016-05-18 00:33:30 -07:00
Lindsey Heagy	c88263234b	rename FDEM --> ProblemFDEM	2016-05-17 23:56:06 -07:00
Lindsey Heagy	d5219be3d8	Merge branch 'dev' into dcip/dev # Conflicts: # SimPEG/DCIP/DCIPUtils.py	2016-05-17 23:26:17 -07:00
Lindsey Heagy	029171fb1d	use .format for strings	2016-05-11 09:09:26 -07:00
Lindsey Heagy	a690cab131	simple field receivers are `Point` receivers	2016-05-11 09:05:13 -07:00
Lindsey Heagy	c1b1c2467f	import from ProblemFDEM in baseMT, fixed a missed real_or_imag --> component	2016-05-10 19:57:16 -07:00
Lindsey Heagy	11e6b452c9	renamed FDEM.py to ProblemFDEM.py, changed real_or_imag to component	2016-05-10 17:26:16 -07:00
Lindsey Heagy	73c219ff5c	updated Problem naming in casing example	2016-05-09 12:29:52 -07:00
Lindsey Heagy	abd919e862	Merge branch 'dev' into em/dev	2016-05-09 11:32:59 -07:00
Lindsey	6e00b4c2fe	Merge pull request #312 from simpeg/em/ref/fdem_cleanup Em/ref/fdem cleanup	2016-05-09 08:25:39 -07:00
Lindsey	906cca30f3	Merge pull request #311 from simpeg/feat/cyl2cartinterp Feat/cyl2cartinterp	2016-05-09 08:24:16 -07:00
seogi_macbook	8803956d83	Working on SIP	2016-05-09 19:58:56 +09:00
Lindsey Heagy	0a714663d3	update Jtvec to work with Rx classes	2016-05-08 13:12:37 -07:00
Lindsey Heagy	cb042ac938	cleanup imports, docstrings	2016-05-08 13:00:29 -07:00
Lindsey Heagy	f7c46ed83b	Rx classes for FDEM	2016-05-08 12:41:06 -07:00
Lindsey Heagy	52747c0926	update example	2016-05-08 11:35:28 -07:00
Lindsey Heagy	d8eeb7cd05	use Problem3D_assumption, Fields3D_assumption	2016-05-08 11:18:36 -07:00
Lindsey Heagy	8278230476	Use LocTypeTo to allow interpolation to different grid locations	2016-05-08 10:35:27 -07:00
Lindsey Heagy	069127333d	allow interpolation to different cartsian grid locations	2016-05-05 16:41:21 -07:00
Lindsey	79e1378009	Merge pull request #305 from simpeg/feat/sparse-regularization Feat/sparse regularization	2016-05-04 22:30:06 -07:00
Lindsey Heagy	0379df2bf2	attempt to clean up docs in DCIP utils	2016-05-04 22:27:02 -07:00
Lindsey Heagy	66440b0478	add depreciation warnings to DCIP utils for activeind from topo	2016-05-04 22:14:41 -07:00
Lindsey Heagy	dbdcc3cefb	use sigma in MfRhoDeriv - due to propmap bug	2016-05-04 22:06:32 -07:00
D Fournier	4e296c4cd5	Update PreCond Directive to allow inactive cells mapping	2016-05-04 16:01:29 -07:00
seogi_macbook	c488dabf9a	working on IP	2016-05-04 12:48:29 -07:00
Lindsey	5e1de61a71	Merge pull request #308 from simpeg/bug/reg-indactive if mapping is none, create an identity map that is size indactive.nonzero	2016-05-03 21:20:54 -07:00
seogi_macbook	69ec374415	minor changes	2016-05-03 19:03:41 -07:00
sgkang	224105364d	df_dmT + du_dmT has dtype('o') This seems making problem depending on which machine you are using .... or numpy version. We may need to clarify what is sparse and dense for arrays!!	2016-05-03 17:39:07 -07:00
Lindsey Heagy	00bbe0f35e	if mapping is none, create an identity map that is size indactive.nonzero for regularization	2016-05-03 15:04:36 -07:00
seogi_macbook	a7f89131b4	Playing with 2.5D DC inversion TODOs: Parallelize ky ... (currently pretty slow)	2016-05-03 11:26:28 -07:00
seogi_macbook	6e12bdc57a	Moving Dom's DCutils ...	2016-05-03 09:20:58 -07:00
seogi_macbook	354e57f24e	Problem3D_CC and _N for IP are all tested a) fwd b) jvec, jtvec c) adjoint	2016-05-02 16:47:16 -07:00
seogi_macbook	ddb11096c8	Working on IP	2016-05-02 15:05:31 -07:00
seogi_macbook	fa6033c438	Working 3D IP problem (CC and N).	2016-05-02 12:00:39 -07:00
Lindsey Heagy	dd45a6a085	name updates in DC_Forward_PseudoSection, DC_Utils, example for Utils_surface2ind_topo	2016-05-02 11:40:02 -07:00
seogi_macbook	bd63e67161	working on IP fix bug in RhoDeriv!!	2016-05-02 10:03:01 -07:00
seogi_macbook	d350dc258d	minor fix for Fields_N and started IP problem.	2016-05-02 08:55:29 -07:00
seogi_macbook	350818d802	add analytic test for 2D dc problems.	2016-05-01 13:21:48 -07:00
Lindsey Heagy	ba8f270b3a	start of surface2ind_topo	2016-05-01 13:17:16 -07:00
seogi_macbook	4df6f340d3	Add _e, _j, _charge for field objects Now it is possible to gram three of them from phiSolution	2016-05-01 13:13:20 -07:00
seogi_macbook	9b2eec0ea3	Working 2.5D nodal discretization (Jvec and Jtvec)	2016-05-01 12:33:39 -07:00
D Fournier	3d1dfc13d7	Change Update_PreConditioner to default False	2016-04-29 15:49:44 -07:00
D Fournier	a6e995e9fb	Merge branch 'feat/meshutils' into feat/sparse-regularization	2016-04-29 15:42:42 -07:00
D Fournier	056dc09fa6	Fix Update_Precondition directive	2016-04-29 15:10:30 -07:00
Lindsey Heagy	4257ea77b3	remove InjectActiveCellsTopo. you should use InjectActiveCells	2016-04-29 15:09:04 -07:00
Lindsey Heagy	a0174e4f30	kwarg name updates	2016-04-29 12:52:45 -07:00
Rowan Cockett	00db6746d4	Add a warnign about mesh attributes	2016-04-29 11:50:56 -07:00
Rowan Cockett	028a16a45a	Syntax bug.	2016-04-29 11:44:42 -07:00
Rowan Cockett	c83b460672	Surface to Indices (GoCAD and VTK)	2016-04-29 11:43:31 -07:00
D Fournier	225394f74e	Latest commit	2016-04-29 11:10:04 -07:00
Lindsey	ace9cad016	Merge pull request #303 from simpeg/dcip/ref Dcip/ref	2016-04-29 10:49:50 -07:00
seogi_macbook	38aef03f9d	Working 2.5D fwd (nodal discretization) On going Jvec and Jtvec	2016-04-29 09:35:03 -07:00
seogi_macbook	ef602eaab1	working Jtvec	2016-04-28 18:13:18 -07:00
seogi_macbook	0610289fdf	Working Jvec for 2.5D DC code	2016-04-28 11:18:37 -07:00
seogi_macbook	d14cd444ac	working 2.5D fwd problem.	2016-04-27 23:04:28 -07:00
seogi_macbook	92e2fd67de	minor fixes.	2016-04-27 15:25:40 -07:00
seogi_macbook	6a064c5f96	Minor changes	2016-04-25 11:00:32 -07:00
seogi_macbook	f944f9b76b	1. Add distributed source for nodal discretization 2. Add Analytic tests 3. Fix simple bug in PlotSlice for nodal variable 4. Add more analytic function (sphere)	2016-04-25 10:58:54 -07:00
seogi_macbook	dcd4fbf973	Implemented mixed B.C. to CC problem. Fix bugs in get fuction getxBCyBC_CC	2016-04-24 15:23:14 -07:00
seogi_macbook	edc2c5feb6	Merge branch 'dcip/BC' of https://github.com/simpeg/simpeg into dcip/ref	2016-04-24 13:57:01 -07:00
seogi_macbook	1936a04683	Working on implementing mixed BC to DC problem	2016-04-24 13:56:37 -07:00
seogi_macbook	fcc2b8b22a	Handling null space of A	2016-04-24 13:32:44 -07:00
seogi_macbook	eeee594f09	Problem3D_N is tested!	2016-04-24 13:29:38 -07:00
seogi_macbook	0bb001973c	workking nodal discretizations	2016-04-24 13:01:03 -07:00
Brendan Smithyman	f55d9573a6	Installation (i.e., setup.py) is no longer dependent on Numpy already being present.	2016-04-24 13:21:49 -04:00
D Fournier	d8bfb27415	Quick fix to MeshIO	2016-04-23 15:25:44 -07:00
seogi_macbook	0e16645b67	working Jtvec	2016-04-23 11:06:24 -07:00
seogi_macbook	8cac166fba	Working Jvec: Getting closer to understand how modular EM code is working ...	2016-04-23 10:40:47 -07:00
seogi_macbook	73001abfc5	fix bug	2016-04-23 01:24:31 -07:00
seogi_macbook	a9362bd38e	Merge branch 'dcip/ref' of https://github.com/simpeg/simpeg into dcip/ref Conflicts: SimPEG/EM/Static/DC/ProblemDC.py Confused about ... this line self.mesh.getFaceInnerProduct(self.curModel.rho)(u)	2016-04-23 00:37:06 -07:00
seogi_macbook	64b94861a0	working on DC problem CC and N	2016-04-22 23:09:31 -07:00
Lindsey Heagy	8775364d8f	start of the sketch of Jvec (not to be trusted yet!)	2016-04-22 17:48:26 -07:00
Lindsey Heagy	5ec6e79a39	MfRhoIDeriv	2016-04-22 17:47:36 -07:00
D Fournier	79183ae9fb	fIX MESH io	2016-04-22 16:05:43 -07:00
D Fournier	606488d152	Major fix to IRLS.	2016-04-21 21:58:40 -07:00
Lindsey Heagy	cd5339322e	sketch of DC	2016-04-21 11:00:20 -07:00
seogi_macbook	8739ba0f20	working dc fwd	2016-04-15 16:53:43 -07:00
Lindsey Heagy	119bc801c7	start of DC refactor in EM/Static	2016-04-15 14:51:19 -07:00
GudniRos	23d2783bc1	Finalizing the pull request from mt/iss290 in to dev.	2016-04-15 12:31:00 -07:00
GudniRos	b58ba55ffd	Merge branch 'mt/iss290' into dev	2016-04-15 12:21:57 -07:00
GudniRos	0d6fe5f7a1	Merge branch 'dev' into mt/iss290	2016-04-15 12:03:09 -07:00
Lindsey	bd318f0092	Merge pull request #294 from simpeg/patch/mutable-arguments remove mutable arguments.	2016-04-08 17:12:20 -07:00
GudniRos	90b0301408	Fixing bug in write out.	2016-04-08 09:40:26 -07:00
GudniRos	083742cb40	Removing repeated directives	2016-04-08 09:34:30 -07:00
Lindsey	2a351be971	Merge pull request #289 from simpeg/patch/sparse-dcip Patch/sparse dcip	2016-04-07 18:43:07 -07:00
Rowan Cockett	3e4f47711c	remove mutable arguments.	2016-04-07 16:35:47 -07:00
D Fournier	e305600de5	Update example list. Add comments for the DC_Forward_PseudoSection example. Fix Z of pseudo section plot.	2016-04-07 13:09:28 -07:00
GudniRos	8a18e479ab	Removed the testProjDeriv (not needed, included in Jvec).	2016-04-07 11:48:17 -07:00
D Fournier	d13c540be0	Uppercase on class names. Add flag for Directive.Update_Wj. Remove trailing spaces. Remove old DC example.	2016-04-07 09:25:20 -07:00
GudniRos	f15a628136	Moved the osr import into the projection function.	2016-04-07 09:01:30 -07:00
GudniRos	fb60f45a3c	Fixed osr import in ediFilesUtils, moved into class which imports only on build up. Fixed the boolean error in Directives.	2016-04-07 08:46:51 -07:00
D Fournier	822f6d333d	Minor revisions + remove trailing white spaces	2016-04-06 22:29:57 -07:00
D Fournier	6000034826	Merge branch 'dcip/dev' into patch/sparse-dcip	2016-04-06 22:18:31 -07:00
Lindsey Heagy	636d178fbf	removed examples that are in Examples PR	2016-04-06 16:19:39 -07:00
Lindsey	0575490f56	Merge pull request #288 from simpeg/feat/gitter-badge Add gitter chat	2016-04-06 16:15:59 -07:00
Lindsey Heagy	ae9ca6cec9	Merge branch 'feat/sparse-regularization' into patch/sparse-dcip # Conflicts: # SimPEG/Examples/__init__.py # SimPEG/Optimization.py	2016-04-06 14:53:45 -07:00
Rowan Cockett	2bd5829b42	Add gitter chat	2016-04-06 13:15:03 -07:00
D Fournier	15d59a5b50	Fix typos in Directives.update_Wj. overseer @lheagy	2016-04-06 09:00:13 -07:00
D Fournier	ba977206ea	Create sensitivity re-weighting directive Adapt Map/polymap for actInd (topography)	2016-04-06 07:22:18 -07:00
D Fournier	df620b42bd	Fix plotting for Linear_IRLS example	2016-04-05 13:23:08 -07:00
D Fournier	7a6f4e0780	Merge branch 'master' into feat/sparse-regularization	2016-04-03 17:26:57 -07:00
D Fournier	2ee158e5d7	Add distance weighting to example TO DO: Create example with and without distance weights	2016-04-03 17:26:04 -07:00
D Fournier	8f73b2e7be	Update directives Add IRLS example	2016-04-03 17:18:39 -07:00
D Fournier	16d62a6d0a	Merge branch 'Examples' into feat/sparse-regularization Conflicts: SimPEG/Examples/__init__.py	2016-04-03 11:11:35 -07:00
Lindsey Heagy	f59cfa9481	Merge branch 'dev' into em/dev	2016-04-02 08:35:09 -07:00
Lindsey	a220c75d78	Merge pull request #273 from simpeg/em/patch/srcIntegration make integrate = False default for all sources	2016-03-31 11:17:54 -07:00
Lindsey Heagy	9c220ef37c	default is mrefInSmooth = False	2016-03-29 23:05:04 -07:00
Lindsey Heagy	936a7aaadc	make integrate = False default for all sources	2016-03-29 21:32:08 -07:00
Lindsey Heagy	b765699d2f	seperated out smallness and smoothness contributions	2016-03-25 23:26:52 -07:00
Thibaut Astic	a9c9ce6bc8	remove ipywidget	2016-02-15 19:50:04 -08:00
Thibaut Astic	6286e48830	Sphere Electrostatic example. code cleaned, commented and updated.	2016-02-15 13:13:44 -08:00
Thibaut Astic	4cf5d49524	Ignoring non functioning examples	2016-02-12 15:48:48 -08:00
Thibaut Astic	88ef74ac38	MT_1D_analytic example	2016-02-12 15:40:48 -08:00
seogi_macbook	3a506b9051	Fix DC examples ...	2016-02-11 08:54:44 -08:00
seogi_macbook	fa6bcd3ffa	Minor changes	2016-02-11 00:10:25 -08:00
seogi_macbook	47895ef270	consistent file name	2016-02-10 23:58:48 -08:00
seogi_macbook	429d8b1191	Add EM_FDEM_SusEffects example	2016-02-10 23:45:19 -08:00
seogi_macbook	774d612c18	Merge branch 'master' of https://github.com/simpeg/simpeg into Examples Conflicts: SimPEG/Examples/__init__.py	2016-02-10 23:38:51 -08:00
Lindsey Heagy	433457f649	docs and import for DC_PseudoSection_Simulation.rst	2016-02-03 20:12:55 -08:00
D Fournier	3eeb5dbd3c	Remove dependency from Utils. Replace by internal function.	2016-02-03 20:03:05 -08:00
D Fournier	df78f7b33a	Branch off master Add DC_Pseudo_Section example.	2016-02-03 14:35:03 -08:00