Minor changes...test runs fine from here

SimPEG/DCIP/DCIPUtils.py

@@ -1,16 +1,12 @@
-from SimPEG import np, Utils
+from SimPEG import np
 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
@@ -32,9 +28,6 @@ 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')
@@ -125,27 +118,34 @@ 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
 
-    :param string fileName: path to the UBC GIF 2D model file
-    :rtype: TensorMesh
-    :return: SimPEG TensorMesh 2D object
+        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
 
     """
     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])
@@ -169,19 +169,23 @@ def readUBC_DC2DModel(fileName):
 
     return model
 
-
-def plot_pseudoSection(DCsurvey, axs, surveyType='dipole-dipole', unitType='volt', clim=None, cblabel=True, axlabel = True, colorbar = True, contour = None):
+def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", 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...
 
-    :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
+        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
@@ -214,39 +218,39 @@ def plot_pseudoSection(DCsurvey, axs, surveyType='dipole-dipole', unitType='volt
         Cmid = (Tx[0][0] + Tx[1][0])/2
         Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
 
-        # Change output for unitType
-        if unitType == 'volt':
+        # Change output for dtype
+        if dtype == 'volt':
 
             rho = np.hstack([rho,data])
 
         else:
 
             # Compute pant leg of apparent rho
-            if surveyType == 'pole-dipole':
+            if stype == 'pdp':
 
                 leg =  data * 2*np.pi  * MA * ( MA + MN ) / MN
 
-            elif surveyType == 'dipole-dipole':
+            elif stype == 'dpdp':
 
                 leg = data * 2*np.pi / ( 1/MA - 1/MB - 1/NB + 1/NA )
 
             else:
-                print """unitType must be 'pole-dipole' | 'dipole-dipole' """
+                print """dtype must be 'pdp'(pole-dipole) | 'dpdp' (dipole-dipole) """
                 break
 
 
-            if unitType == 'appConductivity':
+            if dtype == 'appc':
 
                 leg = np.log10(abs(1./leg))
                 rho = np.hstack([rho,leg])
 
-            elif unitType == 'appResistivity':
+            elif dtype == 'appr':
 
                 leg = np.log10(abs(leg))
                 rho = np.hstack([rho,leg])
 
             else:
-                print """unitType must be 'appResistivity' | 'appConductivity' | 'volt' """
+                print """dtype must be 'appr' | 'appc' | 'volt' """
                 break
 
         midx = np.hstack([midx, ( Cmid + Pmid )/2 ])
@@ -255,7 +259,7 @@ def plot_pseudoSection(DCsurvey, axs, surveyType='dipole-dipole', unitType='volt
     # 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()
@@ -264,39 +268,38 @@ def plot_pseudoSection(DCsurvey, axs, surveyType='dipole-dipole', unitType='volt
 
     # 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, 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':
+        
+        if dtype == 'volt':
             cbar = plt.colorbar(ph, ax = axs, format="%4.1f",fraction=0.04,orientation="horizontal")
 
-        else:
+        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':
+        
+        cmin,cmax = cbar.get_clim()
+        ticks = np.linspace(cmin,cmax,3)
+        cbar.set_ticks(ticks)
+        cbar.ax.tick_params(labelsize=10)
+        
+        if cblabel:
+            if dtype == 'appc':
                 cbar.set_label("App.Cond",size=12)
-            elif unitType == 'appResistivity':
+            elif dtype == 'appr':
                 cbar.set_label("App.Res.",size=12)
-            elif unitType == 'volt':
+            elif dtype == 'volt':
                 cbar.set_label("Potential (V)",size=12)
 
 
+
     if not axlabel:
         axs.set_xticklabels([])
         axs.set_yticklabels([])
@@ -307,24 +310,27 @@ def plot_pseudoSection(DCsurvey, axs, surveyType='dipole-dipole', unitType='volt
 
     return ph
 
-def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
+def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
     """
-    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...
 
-    :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
+        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
 
-    :rtype: DC.Survey, Src, Rx
-    :returns: DC survey, Source
+        Output:
+        :param Tx, Rx -> List objects for each tx location
+            Lines: P1x, P1y, P1z, P2x, P2y, P2z
 
-    !! Require clean up to deal with DCsurvey
+        Created on Wed December 9th, 2015
+
+        @author: dominiquef
+        !! Require clean up to deal with DCsurvey
     """
 
     from SimPEG import np
@@ -340,17 +346,17 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
     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 / AM_sep )
+    nstn = np.floor( dl_len / a )
 
     # Compute discrete pole location along line
-    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
+    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
 
     # 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+AM_sep*dl_x, stn_y+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+    N = np.c_[stn_x+a*dl_x, stn_y+a*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]
@@ -360,14 +366,14 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
     SrcList = []
 
 
-    if surveyType != 'gradient':
+    if stype != 'gradient':
 
         for ii in range(0, int(nstn)-1):
 
 
-            if surveyType == 'dipole-dipole':
+            if stype == 'dpdp':
                 tx = np.c_[M[ii,:],N[ii,:]]
-            elif surveyType == 'pole-dipole':
+            elif stype == 'pdp':
                 tx = np.c_[M[ii,:],M[ii,:]]
 
             # Rx.append(np.c_[M[ii+1:indx,:],N[ii+1:indx,:]])
@@ -376,33 +382,33 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
             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 - MN_sep) / AM_sep ) , nrx])
+            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*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
+            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
             # 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+AM_sep*dl_x, stn_y+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+            P2 = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
 
             Rx.append(np.c_[P1,P2])
             rxClass = DC.RxDipole(P1, P2)
             Tx.append(tx)
-            if surveyType == 'dipole-dipole':
+            if stype == 'dpdp':
                 srcClass = DC.SrcDipole([rxClass], M[ii,:],N[ii,:])
-            elif surveyType == 'pole-dipole':
+            elif stype == 'pdp':
                 srcClass = DC.SrcDipole([rxClass], M[ii,:],M[ii,:])
             SrcList.append(srcClass)
 
-    elif surveyType == 'gradient':
+    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
@@ -410,23 +416,23 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
         Tx.append(np.c_[M[0,:],N[-1,:]])
 
         # Get the edge limit of survey area
-        min_x = endl[0,0] + dl_x * MN_sep
-        min_y = endl[0,1] + dl_y * MN_sep
+        min_x = endl[0,0] + dl_x * b
+        min_y = endl[0,1] + dl_y * b
 
-        max_x = endl[1,0] - dl_x * MN_sep
-        max_y = endl[1,1] - dl_y * MN_sep
+        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 / AM_sep )
+        nstn = np.floor( box_l / a )
 
         # Compute discrete pole location along line
-        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
+        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 / AM_sep ))
+        nlin = int(np.floor( box_w / a ))
         lind = range(-nlin,nlin+1)
 
         ngrad = nstn * len(lind)
@@ -435,12 +441,12 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
         for ii in range( len(lind) ):
 
             # Move line in perpendicular direction by dipole spacing
-            lxx = stn_x - lind[ii]*AM_sep*dl_y
-            lyy = stn_y + lind[ii]*AM_sep*dl_x
+            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*mesh.vectorNz[-1]]
-            N = np.c_[ lxx+AM_sep*dl_x, lyy+AM_sep*dl_y, 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]]
 
             rx[(ii*nstn):((ii+1)*nstn),:] = np.c_[M,N]
 
@@ -449,38 +455,44 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
         srcClass = DC.SrcDipole([rxClass], M[0,:], N[-1,:])
         SrcList.append(srcClass)
     else:
-        print """surveyType must be either 'pole-dipole', 'dipole-dipole' or 'gradient'. """
+        print """stype must be either 'pdp', 'dpdp' or 'gradient'. """
 
     survey = DC.SurveyDC(SrcList)
     return survey, Tx, Rx
 
-
-def writeUBC_DCobs(fileName, DCsurvey, dim, surveyType, iptype = 0):
+def writeUBC_DCobs(fileName, DCsurvey, dtype='3D', stype='SURFACE', iptype = 0):
     """
         Write UBC GIF DCIP 2D or 3D observation file
 
-        :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
-    """
+        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
+
+    """
     from SimPEG import mkvc
 
-    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'"
-
+    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'"
+    
     fid = open(fileName,'w')
-    fid.write('! ' + surveyType + ' FORMAT\n')
-
+    
+    
     if iptype!=0:
         fid.write('IPTYPE=%i\n'%iptype)
-
+        
     else:
         fid.write('! ' + stype + ' FORMAT\n')
-
+        
     count = 0
 
     for ii in range(DCsurvey.nSrc):
@@ -494,33 +506,33 @@ def writeUBC_DCobs(fileName, DCsurvey, dim, surveyType, iptype = 0):
         M = rx[0]
         N = rx[1]
 
-        # Adapt source-receiver location for dim and surveyType
-        if dim=='2D':
+        # Adapt source-receiver location for dtype and stype
+        if dtype=='2D':
 
-            if surveyType == 'SIMPLE':
+            if stype == 'SIMPLE':
 
                 #fid.writelines("%e " % ii for ii in mkvc(tx[0,:]))
                 A = np.repeat(tx[0,0],M.shape[0],axis=0)
                 B = np.repeat(tx[0,1],M.shape[0],axis=0)
                 M = M[:,0]
                 N = N[:,0]
-
+                
                 np.savetxt(fid, np.c_[A, B, M, N , DCsurvey.dobs[count:count+nD], DCsurvey.std[count:count+nD] ], fmt='%e',delimiter=' ',newline='\n')
 
 
             else:
 
-                if surveyType == 'SURFACE':
+                if stype == 'SURFACE':
 
                     fid.writelines("%f " % ii for ii in mkvc(tx[0,:]))
                     M = M[:,0]
                     N = N[:,0]
 
-                if surveyType == 'GENERAL':
+                if stype == '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]
@@ -528,31 +540,31 @@ def writeUBC_DCobs(fileName, DCsurvey, dim, surveyType, iptype = 0):
                     # 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='%f',delimiter=' ',newline='\n')
 
-        if dim=='3D':
+        if dtype=='3D':
 
-            if surveyType == 'SURFACE':
+            if stype == 'SURFACE':
 
                 fid.writelines("%e " % ii for ii in mkvc(tx[0:2,:]))
                 M = M[:,0:2]
                 N = N[:,0:2]
 
-            if surveyType == 'GENERAL':
+            if stype == 'GENERAL':
 
                 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)
@@ -561,9 +573,15 @@ def convertObs_DC3D_to_2D(DCsurvey, lineID, flag='local'):
 
         The Z value is preserved, but Y coordinates zeroed.
 
-        :param DC.Survey survey3D: 3D simpeg DC survey
-        :rtype: DC.Survey
-        :return: survey2D
+        Input:
+        :param survey3D
+
+        Output:
+        :figure survey2D
+
+        Edited April 6th, 2016
+
+        @author: dominiquef
 
     """
     from SimPEG import np
@@ -648,34 +666,39 @@ def convertObs_DC3D_to_2D(DCsurvey, lineID, flag='local'):
     DCsurvey2D.std = np.asarray(DCsurvey.std)
 
     return DCsurvey2D
-
-def readUBC_DC3Dobs(fileName, rtype = 'DC'):
+    
+def readUBC_DC3Dobs(fileName, dtype = 'DC'):
     """
         Read UBC GIF IP 3D observation file and generate survey
 
-        :param string fileName:, path to the UBC GIF 3D obs file
-        :rtype: Survey
-        :return: DCIPsurvey
+        Input:
+        :param fileName, path to the UBC GIF 3D obs file
+
+        Output:
+        :param IPsurvey
+        :return
+
+        @author: dominiquef
 
     """
     zflag = True # Flag for z value provided
-
+    
     # Load file
-    if rtype == 'IP':
+    if dtype == 'IP':
         obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='IPTYPE')
-
-    elif rtype == 'DC':
+        
+    elif dtype == 'DC':
         obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
-
+        
     else:
-        print "rtype must be 'DC'(default) | 'IP'"
-
+        print "dtype must be 'DC'(default) | 'IP'"
+        
     # Pre-allocate
     srcLists = []
     Rx = []
     d = []
     wd = []
-
+    
 
     # Countdown for number of obs/tx
     count = 0
@@ -694,7 +717,7 @@ def readUBC_DC3Dobs(fileName, rtype = 'DC'):
             # Check if z value is provided, if False -> nan
             if len(temp)==5:
                 tx = np.r_[temp[0:2],np.nan,temp[2:4],np.nan]
-
+                
                 zflag = False # Pass on the flag to the receiver loc
 
             else:
@@ -706,12 +729,12 @@ def readUBC_DC3Dobs(fileName, rtype = 'DC'):
         temp = np.fromstring(obsfile[ii], dtype=float,sep=' ') # Get the string
 
         # Filter out negative IP
-#        if temp[-2] < 0:
+#        if temp[-2] < 0:       
 #            count = count -1
 #            print "Negative!"
-#
+#            
 #        else:
-
+            
         # If the Z-location is provided, otherwise put nan
         if zflag:
 
@@ -749,9 +772,17 @@ def readUBC_DC2Dobs(fileName):
         ------- NEEDS TO BE UPDATED ------
         Read UBC GIF 2D observation file and generate arrays for tx-rx location
 
-        :param string fileName: path to the UBC GIF 2D model file
-        :rtype: (DC.Src, DC.Rx, ??, ??)
-        :return: source_locs, rx_locs, ??, ??
+        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
+
     """
 
     from SimPEG import np
@@ -791,9 +822,11 @@ def readUBC_DC2Dpre(fileName):
         Read UBC GIF DCIP 2D observation file and generate arrays for tx-rx location
 
         Input:
-        :param string fileName: path to the UBC GIF 3D obs file
-        :rtype: DC.Survey
-        :return: DCsurvey
+        :param fileName, path to the UBC GIF 3D obs file
+
+        Output:
+        DCsurvey
+        :return
 
         Created on Mon March 9th, 2016 << Doug's 70th Birthday !! >>
 
@@ -855,9 +888,12 @@ def readUBC_DC2DMesh(fileName):
     """
         Read UBC GIF 2DTensor mesh and generate 2D Tensor mesh in simpeg
 
-        :param string fileName: path to the UBC GIF mesh file
-        :rtype: Mesh.TensorMesh
-        :return: SimPEG TensorMesh 2D object
+        Input:
+        :param fileName, path to the UBC GIF mesh file
+
+        Output:
+        :param SimPEG TensorMesh 2D object
+        :return
 
         Created on Thu Nov 12 13:14:10 2015
 
@@ -923,9 +959,12 @@ def xy_2_lineID(DCsurvey):
         they were collected. May need to generalize for random
         point locations, but will be more expensive
 
-        :param numpy.array DCdict: Vectors of station location
-        :rtype: numpy.array
-        :return: LineID Vector of integers
+        Input:
+        :param DCdict Vectors of station location
+
+        Output:
+        :param LineID Vector of integers
+        :return
 
         Created on Thu Feb 11, 2015
 

SimPEG/Directives.py

@@ -144,18 +144,12 @@ class BetaSchedule(InversionDirective):
             if self.debug: print 'BetaSchedule is cooling Beta. Iteration: %d' % self.opt.iter
             self.invProb.beta /= self.coolingFactor
 
-
 class TargetMisfit(InversionDirective):
 
-    chifact = 1.
-    phi_d_star = None
-
     @property
     def target(self):
         if getattr(self, '_target', None) is None:
-            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
+            self._target = self.survey.nD*0.5
         return self._target
     @target.setter
     def target(self, val):
@@ -243,6 +237,12 @@ 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 UpdateReferenceModel(Parameter):
+
+#     mref0 = None
+
+#     def nextIter(self):
 #         mref = getattr(self, 'm_prev', None)
 #         if mref is None:
 #             if self.debug: print 'UpdateReferenceModel is using mref0'
@@ -253,158 +253,78 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
 class Update_IRLS(InversionDirective):
 
     eps_min = None
-    eps_p = None
-    eps_q = None
-    norms = [2.,2.,2.,2.]
     factor = None
     gamma = None
     phi_m_last = None
     phi_d_last = None
-    f_old = None
-    f_min_change = 1e-2
-    beta_tol = 5e-2
 
-    # Solving parameter for IRLS (mode:2)
-    IRLSiter   = 0
-    minGNiter = 5
-    maxIRLSiter = 10
-    iterStart = 0
-
-    # Beta schedule
-    coolingFactor = 2.
-    coolingRate = 1
-
-    mode = 1
-
-    @property
-    def target(self):
-        if getattr(self, '_target', None) is None:
-            self._target = self.survey.nD*0.5
-        return self._target
-    @target.setter
-    def target(self, val):
-        self._target = val
 
     def initialize(self):
 
-        if self.mode == 1:
-            self.reg.norms = [2., 2., 2., 2.]
+        # 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
+        
+        self.reg._W = None
+        if getattr(self, 'phi_d_last', None) is None:
+            self.phi_d_last = self.invProb.phi_d
 
     def endIter(self):
+        # Cool the threshold parameter if required
+        if getattr(self, 'factor', None) is not None:
+            eps = self.reg.eps / self.factor
 
-        # After reaching target misfit with l2-norm, switch to IRLS (mode:2)
-        if self.invProb.phi_d < self.target and self.mode == 1:
-            print "Convergence with smooth l2-norm regularization: Start IRLS steps..."
-
-            self.mode = 2
-            print self.eps_p, self.eps_q, self.norms
-            self.reg.eps_p = self.eps_p
-            self.reg.eps_q = self.eps_q
-            self.reg.norms = self.norms
-            self.coolingFactor = 1.
-            self.coolingRate = 1
-            self.iterStart = self.opt.iter
-            self.phi_d_last = self.invProb.phi_d
-            self.phi_m_last = self.invProb.phi_m_last
-
-            self.reg.l2model = self.invProb.curModel
-            self.reg.curModel = self.invProb.curModel
-
-            if getattr(self, 'f_old', None) is None:
-                self.f_old = self.reg.eval(self.invProb.curModel)#self.invProb.evalFunction(self.invProb.curModel, return_g=False, return_H=False)
-
-        # Beta Schedule
-        if self.opt.iter > 0 and self.opt.iter % self.coolingRate == 0:
-            if self.debug: print 'BetaSchedule is cooling Beta. Iteration: %d' % self.opt.iter
-            self.invProb.beta /= self.coolingFactor
-
-
-        # Only update after GN iterations
-        if (self.opt.iter-self.iterStart) % self.minGNiter == 0 and self.mode==2:
-
-            self.IRLSiter += 1
-
-            phim_new = self.reg.eval(self.invProb.curModel)
-            self.f_change = np.abs(self.f_old - phim_new) / self.f_old
-
-            print "Regularization decrease: %6.3e" % (self.f_change)
-
-            # Check for maximum number of IRLS cycles
-            if self.IRLSiter == self.maxIRLSiter:
-                print "Reach maximum number of IRLS cycles: %i" % self.maxIRLSiter
-                self.opt.stopNextIteration = True
-                return
-
-            # Check if the function has changed enough
-            if self.f_change < self.f_min_change and self.IRLSiter > 1:
-                print "Minimum decrease in regularization. End of IRLS"
-                self.opt.stopNextIteration = True
-                return
+            if getattr(self, 'eps_min', None) is not None:
+                self.reg.eps = np.max([self.eps_min,eps])
             else:
-                self.f_old = phim_new
+                self.reg.eps = eps
 
-            # Cool the threshold parameter if required
-            if getattr(self, 'factor', None) is not None:
-                eps = self.reg.eps / self.factor
+        # Get phi_m at the end of current iteration
+        self.phi_m_last = self.invProb.phi_m_last
+        
+        self.reg._W = None
+         # Update the model used for the IRLS weights
+        self.reg.curModel = self.invProb.curModel
 
-                if getattr(self, 'eps_min', None) is not None:
-                    self.reg.eps = np.max([self.eps_min,eps])
-                else:
-                    self.reg.eps = eps
+        # Temporarely set gamma to 1. to get raw phi_m
+        self.reg.gamma = 1.
 
-            # Get phi_m at the end of current iteration
-            self.phi_m_last = self.invProb.phi_m_last
-
-            # Reset the regularization matrices so that it is
-            # recalculated for current model
-            self.reg._Wsmall = None
-            self.reg._Wx = None
-            self.reg._Wy = None
-            self.reg._Wz = None
-
-             # Update the model used for the IRLS weights
-            self.reg.curModel = self.invProb.curModel
-
-            # Temporarely set gamma to 1. to get raw phi_m
-            self.reg.gamma = 1.
-
-            # 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
-
-            # Reset the regularization matrices again for new gamma
-            self.reg._Wsmall = None
-            self.reg._Wx = None
-            self.reg._Wy = None
-            self.reg._Wz = None
-
-            # Check if misfit is within the tolerance, otherwise scale beta
-            val = self.invProb.phi_d / (self.survey.nD*0.5)
-
-            if np.abs(1.-val) > self.beta_tol:
-                self.invProb.beta = self.invProb.beta * self.survey.nD*0.5 / self.invProb.phi_d
+        # 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
+        
+        # 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.
@@ -437,3 +357,19 @@ class Update_Wj(InversionDirective):
             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

SimPEG/EM/Analytics/DC.py

@@ -1,118 +0,0 @@
-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

SimPEG/EM/Analytics/__init__.py

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

SimPEG/EM/Base.py

@@ -1,7 +1,6 @@
 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)
@@ -62,15 +61,6 @@ 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):
         """
@@ -80,20 +70,6 @@ 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
@@ -151,6 +127,7 @@ class BaseEMProblem(Problem.BaseProblem):
         """
         return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u) * self.curModel.sigmaDeriv
 
+
     @property
     def MeSigmaI(self):
         """
@@ -169,7 +146,10 @@ class BaseEMProblem(Problem.BaseProblem):
 
         dMeSigmaI_dI = -self.MeSigmaI**2
         dMe_dsig = self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u)
-        return dMeSigmaI_dI * ( dMe_dsig * self.curModel.sigmaDeriv )
+        dsig_dm = self.curModel.sigmaDeriv
+        return dMeSigmaI_dI * ( dMe_dsig * ( dsig_dm))
+        # return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma, invMat=True)(u)
+
 
     @property
     def MfRho(self):
@@ -185,7 +165,8 @@ class BaseEMProblem(Problem.BaseProblem):
         """
             Derivative of :code:`MfRho` with respect to the model.
         """
-        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u) * self.curModel.rhoDeriv
+        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u) * (-Utils.sdiag(self.curModel.rho**2) * self.curModel.sigmaDeriv)
+        # self.curModel.rhoDeriv
 
     @property
     def MfRhoI(self):
@@ -202,10 +183,7 @@ class BaseEMProblem(Problem.BaseProblem):
         """
             Derivative of :code:`MfRhoI` with respect to the model.
         """
-
-        dMfRhoI_dI = -self.MfRhoI**2
-        dMf_drho = self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u)
-        return dMfRhoI_dI * ( dMf_drho * self.curModel.rhoDeriv )
+        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho, invMat=True)(u) * self.curModel.rhoDeriv
 
 class BaseEMSurvey(Survey.BaseSurvey):
 
@@ -214,7 +192,7 @@ class BaseEMSurvey(Survey.BaseSurvey):
         self.srcList = srcList
         Survey.BaseSurvey.__init__(self, **kwargs)
 
-    def eval(self, f):
+    def eval(self, u):
         """
         Project fields to receiver locations
         :param Fields u: fields object
@@ -224,8 +202,8 @@ 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, f)
+                data[src, rx] = rx.eval(src, self.mesh, u)
         return data
 
-    def evalDeriv(self, f):
+    def evalDeriv(self, u):
         raise Exception('Use Receivers to project fields deriv.')

SimPEG/EM/FDEM/FDEM.py

@@ -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, Fields3D_e, Fields3D_b, Fields3D_h, Fields3D_j
+from FieldsFDEM import Fields, Fields_e, Fields_b, Fields_h, Fields_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:`Problem3D_e`
-        or :code:`Problem3D_b`). Note that in this case, :math:`\mathbf{s_e}` is an integrated quantity.
+        if using the E-B formulation (:code:`Problem_e`
+        or :code:`Problem_b`). Note that in this case, :math:`\mathbf{s_e}` is an integrated quantity.
 
         If we write Maxwell's equations in terms of
         \\\(\\\mathbf{h}\\\) and current density \\\(\\\mathbf{j}\\\)
@@ -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:`Problem3D_j` or :code:`Problem3D_h`). Note that here, :math:`\mathbf{s_m}` is an integrated quantity.
+        if using the H-J formulation (:code:`Problem_j` or :code:`Problem_h`). Note that here, :math:`\mathbf{s_m}` is an integrated quantity.
 
         The problem performs the elimination so that we are solving the system for \\\(\\\mathbf{e},\\\mathbf{b},\\\mathbf{j} \\\) or \\\(\\\mathbf{h}\\\)
     """
@@ -87,7 +87,7 @@ class BaseFDEMProblem(BaseEMProblem):
                 du_dm_v = Ainv * ( - dA_dm_v + dRHS_dm_v )
 
                 for rx in src.rxList:
-                    df_dmFun = getattr(f, '_{0}Deriv'.format(rx.projField), None)
+                    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)
             Ainv.clean()
@@ -125,7 +125,7 @@ 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, '_{0}Deriv'.format(rx.projField), None)
+                    df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
                     df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
 
                     ATinvdf_duT = ATinv * df_duT
@@ -137,9 +137,10 @@ class BaseFDEMProblem(BaseEMProblem):
                     df_dmT = df_dmT + du_dmT
 
                     # TODO: this should be taken care of by the reciever?
-                    if rx.component is 'real':
+                    real_or_imag = rx.projComp
+                    if real_or_imag is 'real':
                         Jtv +=   np.array(df_dmT, dtype=complex).real
-                    elif rx.component is 'imag':
+                    elif real_or_imag is 'imag':
                         Jtv += - np.array(df_dmT, dtype=complex).real
                     else:
                         raise Exception('Must be real or imag')
@@ -166,7 +167,6 @@ class BaseFDEMProblem(BaseEMProblem):
 
         for i, src in enumerate(Srcs):
             smi, sei = src.eval(self)
-            #Why are you adding?
             s_m[:,i] = s_m[:,i] + smi
             s_e[:,i] = s_e[:,i] + sei
 
@@ -177,7 +177,7 @@ class BaseFDEMProblem(BaseEMProblem):
 ################################ E-B Formulation #########################################
 ##########################################################################################
 
-class Problem3D_e(BaseFDEMProblem):
+class Problem_e(BaseFDEMProblem):
     """
     By eliminating the magnetic flux density using
 
@@ -199,7 +199,7 @@ class Problem3D_e(BaseFDEMProblem):
 
     _solutionType = 'eSolution'
     _formulation  = 'EB'
-    fieldsPair    = Fields3D_e
+    fieldsPair    = Fields_e
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -288,7 +288,7 @@ class Problem3D_e(BaseFDEMProblem):
             return C.T * (MfMui * s_mDeriv(v)) -1j * omega(freq) * s_eDeriv(v)
 
 
-class Problem3D_b(BaseFDEMProblem):
+class Problem_b(BaseFDEMProblem):
     """
     We eliminate :math:`\mathbf{e}` using
 
@@ -310,7 +310,7 @@ class Problem3D_b(BaseFDEMProblem):
 
     _solutionType = 'bSolution'
     _formulation  = 'EB'
-    fieldsPair    = Fields3D_b
+    fieldsPair    = Fields_b
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -436,7 +436,7 @@ class Problem3D_b(BaseFDEMProblem):
 ##########################################################################################
 
 
-class Problem3D_j(BaseFDEMProblem):
+class Problem_j(BaseFDEMProblem):
     """
     We eliminate \\\(\\\mathbf{h}\\\) using
 
@@ -458,7 +458,7 @@ class Problem3D_j(BaseFDEMProblem):
 
     _solutionType = 'jSolution'
     _formulation  = 'HJ'
-    fieldsPair    = Fields3D_j
+    fieldsPair    = Fields_j
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -577,7 +577,7 @@ class Problem3D_j(BaseFDEMProblem):
 
 
 
-class Problem3D_h(BaseFDEMProblem):
+class Problem_h(BaseFDEMProblem):
     """
     We eliminate \\\(\\\mathbf{j}\\\) using
 
@@ -596,7 +596,7 @@ class Problem3D_h(BaseFDEMProblem):
 
     _solutionType = 'hSolution'
     _formulation  = 'HJ'
-    fieldsPair    = Fields3D_h
+    fieldsPair    = Fields_h
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)

SimPEG/EM/FDEM/FieldsFDEM.py

@@ -60,20 +60,6 @@ class Fields(SimPEG.Problem.Fields):
 
         return self._bPrimary(solution, srcList) + self._bSecondary(solution, srcList)
 
-    def _bSecondary(self, solution, srcList):
-        """
-        Total magnetic flux density is sum of primary and secondary
-
-        :param numpy.ndarray solution: field we solved for
-        :param list srcList: list of sources
-        :rtype: numpy.ndarray
-        :return: total magnetic flux density
-        """
-        if getattr(self, '_bSecondary', None) is None:
-            raise NotImplementedError ('Getting b from %s is not implemented' %self.knownFields.keys()[0])
-
-        return  self._bSecondary(solution, srcList)
-
     def _h(self, solution, srcList):
         """
         Total magnetic field is sum of primary and secondary
@@ -138,21 +124,6 @@ class Fields(SimPEG.Problem.Fields):
             return self._bDeriv_u(src, v, adjoint), self._bDeriv_m(src, v, adjoint)
         return np.array(self._bDeriv_u(src, du_dm_v, adjoint) + self._bDeriv_m(src, v, adjoint), dtype = complex)
 
-    def _bSecondaryDeriv(self, src, du_dm_v, v, adjoint = False):
-        """
-        Total derivative of b with respect to the inversion model. Returns :math:`d\mathbf{b}/d\mathbf{m}` for forward and (:math:`d\mathbf{b}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
-
-        :param Src src: sorce
-        :param numpy.ndarray du_dm_v: derivative of the solution vector with respect to the model times a vector (is None for adjoint)
-        :param numpy.ndarray v: vector to take sensitivity product with
-        :param bool adjoint: adjoint?
-        :rtype: numpy.ndarray
-        :return: derivative times a vector (or tuple for adjoint)
-        """
-        # TODO: modify when primary field is dependent on m
-
-        return self._bDeriv(src, du_dm_v, v, adjoint = adjoint)
-
     def _hDeriv(self, src, du_dm_v, v, adjoint = False):
         """
         Total derivative of h with respect to the inversion model. Returns :math:`d\mathbf{h}/d\mathbf{m}` for forward and (:math:`d\mathbf{h}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
@@ -189,9 +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 Fields3D_e(Fields):
+class Fields_e(Fields):
     """
-    Fields object for Problem3D_e.
+    Fields object for Problem_e.
 
     :param Mesh mesh: mesh
     :param Survey survey: survey
@@ -210,7 +181,7 @@ class Fields3D_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
@@ -455,9 +426,9 @@ class Fields3D_e(Fields):
 
 
 
-class Fields3D_b(Fields):
+class Fields_b(Fields):
     """
-    Fields object for Problem3D_b.
+    Fields object for Problem_b.
 
     :param Mesh mesh: mesh
     :param Survey survey: survey
@@ -500,8 +471,6 @@ class Fields3D_b(Fields):
             return 'E'
         elif fieldType == 'b':
             return 'F'
-        elif fieldType == 'bSecondary':
-            return 'F'
         elif (fieldType == 'h') or (fieldType == 'j'):
             return'CCV'
         else:
@@ -724,9 +693,9 @@ class Fields3D_b(Fields):
         return Zero()
 
 
-class Fields3D_j(Fields):
+class Fields_j(Fields):
     """
-    Fields object for Problem3D_j.
+    Fields object for Problem_j.
 
     :param Mesh mesh: mesh
     :param Survey survey: survey
@@ -1019,9 +988,9 @@ class Fields3D_j(Fields):
         return 1./(1j * omega(src.freq)) * VI * (self._aveE2CCV * ( s_mDeriv(v) - self._edgeCurl.T * ( self._MfRhoDeriv(jSolution) * v ) ) )
 
 
-class Fields3D_h(Fields):
+class Fields_h(Fields):
     """
-    Fields object for Problem3D_h.
+    Fields object for Problem_h.
 
     :param Mesh mesh: mesh
     :param Survey survey: survey

SimPEG/EM/FDEM/RxFDEM.py

@@ -1,139 +0,0 @@
-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_bSecondary(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 = 'bSecondary'
-        super(Point_bSecondary, 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)

SimPEG/EM/FDEM/SrcFDEM.py

@@ -9,17 +9,12 @@ class BaseSrc(Survey.BaseSrc):
     """
 
     freq = None
-    integrate = False
-    _ePrimary = None
-    _bPrimary = None
-    _hPrimary = None
-    _jPrimary = None
-
-    def __init__(self, rxList, **kwargs):
-        Survey.BaseSrc.__init__(self, rxList, **kwargs)
+    # rxPair = RxFDEM
+    integrate = True
 
     def eval(self, prob):
         """
+        Evaluate the source terms.
         - :math:`s_m` : magnetic source term
         - :math:`s_e` : electric source term
 
@@ -56,9 +51,7 @@ class BaseSrc(Survey.BaseSrc):
         :rtype: numpy.ndarray
         :return: primary magnetic flux density
         """
-        if self._bPrimary is None:
-            return Zero()
-        return self._bPrimary
+        return Zero()
 
     def hPrimary(self, prob):
         """
@@ -68,9 +61,7 @@ class BaseSrc(Survey.BaseSrc):
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
-        if self._hPrimary is None:
-            return Zero()
-        return self._hPrimary
+        return Zero()
 
     def ePrimary(self, prob):
         """
@@ -80,9 +71,7 @@ class BaseSrc(Survey.BaseSrc):
         :rtype: numpy.ndarray
         :return: primary electric field
         """
-        if self._ePrimary is None:
-            return Zero()
-        return self._ePrimary
+        return Zero()
 
     def jPrimary(self, prob):
         """
@@ -92,9 +81,7 @@ class BaseSrc(Survey.BaseSrc):
         :rtype: numpy.ndarray
         :return: primary current density
         """
-        if self._jPrimary is None:
-            return Zero()
-        return self._jPrimary
+        return Zero()
 
     def s_m(self, prob):
         """
@@ -149,14 +136,15 @@ class RawVec_e(BaseSrc):
     :param list rxList: receiver list
     :param float freq: frequency
     :param numpy.array s_e: electric source term
-    :param bool integrate: Integrate the source term (multiply by Me) [False]
+    :param bool integrate: Integrate the source term (multiply by Me) [True]
     """
 
-    def __init__(self, rxList, freq, s_e, **kwargs):
+    def __init__(self, rxList, freq, s_e, integrate=True): #, ePrimary=None, bPrimary=None, hPrimary=None, jPrimary=None):
         self._s_e = np.array(s_e, dtype=complex)
         self.freq = float(freq)
+        self.integrate = integrate
 
-        BaseSrc.__init__(self, rxList, **kwargs)
+        BaseSrc.__init__(self, rxList)
 
     def s_e(self, prob):
         """
@@ -178,14 +166,15 @@ class RawVec_m(BaseSrc):
     :param float freq: frequency
     :param rxList: receiver list
     :param numpy.array s_m: magnetic source term
-    :param bool integrate: Integrate the source term (multiply by Me) [False]
+    :param bool integrate: Integrate the source term (multiply by Me) [True]
     """
 
-    def __init__(self, rxList, freq, s_m, **kwargs):  #ePrimary=Zero(), bPrimary=Zero(), hPrimary=Zero(), jPrimary=Zero()):
+    def __init__(self, rxList, freq, s_m, integrate=True):  #ePrimary=Zero(), bPrimary=Zero(), hPrimary=Zero(), jPrimary=Zero()):
         self._s_m = np.array(s_m, dtype=complex)
         self.freq = float(freq)
+        self.integrate = integrate
 
-        BaseSrc.__init__(self, rxList, **kwargs)
+        BaseSrc.__init__(self, rxList)
 
     def s_m(self, prob):
         """
@@ -208,13 +197,14 @@ class RawVec(BaseSrc):
     :param float freq: frequency
     :param numpy.array s_m: magnetic source term
     :param numpy.array s_e: electric source term
-    :param bool integrate: Integrate the source term (multiply by Me) [False]
+    :param bool integrate: Integrate the source term (multiply by Me) [True]
     """
-    def __init__(self, rxList, freq, s_m, s_e, **kwargs):
+    def __init__(self, rxList, freq, s_m, s_e, integrate=True):
         self._s_m = np.array(s_m, dtype=complex)
         self._s_e = np.array(s_e, dtype=complex)
         self.freq = float(freq)
-        BaseSrc.__init__(self, rxList, **kwargs)
+        self.integrate = integrate
+        BaseSrc.__init__(self, rxList)
 
     def s_m(self, prob):
         """
@@ -288,13 +278,14 @@ class MagDipole(BaseSrc):
     :param float mu: background magnetic permeability
     """
 
-    def __init__(self, rxList, freq, loc, orientation='Z', moment=1., mu=mu_0, **kwargs):
+    def __init__(self, rxList, freq, loc, orientation='Z', moment=1., mu=mu_0):
         self.freq = float(freq)
         self.loc = loc
         self.orientation = orientation
         assert orientation in ['X','Y','Z'], "Orientation (right now) doesn't actually do anything! The methods in SrcUtils should take care of this..."
         self.moment = moment
         self.mu = mu
+        self.integrate = False
         BaseSrc.__init__(self, rxList)
 
     def bPrimary(self, prob):
@@ -552,10 +543,10 @@ class CircularLoop(BaseSrc):
             if not prob.mesh.isSymmetric:
                 # TODO ?
                 raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-            a = MagneticLoopVectorPotential(self.loc, gridY, 'y', moment=self.radius, mu=self.mu)
+            a = MagneticDipoleVectorPotential(self.loc, gridY, 'y', moment=self.radius, mu=self.mu)
 
         else:
-            srcfct = MagneticLoopVectorPotential
+            srcfct = MagneticDipoleVectorPotential
             ax = srcfct(self.loc, gridX, 'x', self.radius, mu=self.mu)
             ay = srcfct(self.loc, gridY, 'y', self.radius, mu=self.mu)
             az = srcfct(self.loc, gridZ, 'z', self.radius, mu=self.mu)

SimPEG/EM/FDEM/SurveyFDEM.py

@@ -4,9 +4,126 @@ 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
@@ -15,7 +132,7 @@ class Survey(BaseEMSurvey):
     """
 
     srcPair = Src.BaseSrc
-    rxPair = Rx.BaseRx
+    rxPair = Rx
 
     def __init__(self, srcList, **kwargs):
         # Sort these by frequency

SimPEG/EM/FDEM/__init__.py

@@ -1,5 +1,3 @@
-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
+from SurveyFDEM import Rx, Src, Survey
+from FDEM import BaseFDEMProblem, Problem_e, Problem_b, Problem_j, Problem_h
+from FieldsFDEM import *

SimPEG/EM/Static/DC/BoundaryUtils.py

@@ -1,160 +0,0 @@
-import numpy as np
-
-def getxBCyBC_CC(mesh, alpha, beta, gamma):
-# def getxBCyBC(mesh, alpha, beta, gamma):
-    """
-    This is a subfunction generating mixed-boundary condition:
-
-    .. math::
-
-        \nabla \cdot \vec{j} = -\nabla \cdot \vec{j}_s = q
-
-        \rho \vec{j} = -\nabla \phi \phi
-
-        \alpha \phi + \beta \frac{\partial \phi}{\partial r} = \gamma \ at \ r = \partial \Omega
-
-        xBC = f_1(\alpha, \beta, \gamma)
-        yBC = f(\alpha, \beta, \gamma)
-
-    Computes xBC and yBC for cell-centered discretizations
-    """
-    if mesh.dim == 1: #1D
-        if (len(alpha) != 2 or len(beta) != 2 or len(gamma) != 2):
-            raise Exception("Lenght of list, alpha should be 2")
-        fCCxm,fCCxp = mesh.cellBoundaryInd
-        nBC = fCCxm.sum()+fCCxp.sum()
-        h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
-
-        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
-        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
-
-        # h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
-        h_xm, h_xp = mesh.hx[0], mesh.hx[-1]
-
-        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
-        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
-        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
-        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
-
-        xBC_xm = 0.5*a_xm
-        xBC_xp = 0.5*a_xp/b_xp
-        yBC_xm = 0.5*(1.-b_xm)
-        yBC_xp = 0.5*(1.-1./b_xp)
-
-        xBC = np.r_[xBC_xm, xBC_xp]
-        yBC = np.r_[yBC_xm, yBC_xp]
-
-    elif mesh.dim == 2: #2D
-        if (len(alpha) != 4 or len(beta) != 4 or len(gamma) != 4):
-            raise Exception("Lenght of list, alpha should be 4")
-
-        fxm,fxp,fym,fyp = mesh.faceBoundaryInd
-        nBC = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
-
-        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
-        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
-        alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
-        alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
-
-        # h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
-        # h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
-
-        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
-        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
-
-        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
-        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
-        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
-        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
-
-        a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
-        b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
-        a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
-        b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
-
-        xBC_xm = 0.5*a_xm
-        xBC_xp = 0.5*a_xp/b_xp
-        yBC_xm = 0.5*(1.-b_xm)
-        yBC_xp = 0.5*(1.-1./b_xp)
-        xBC_ym = 0.5*a_ym
-        xBC_yp = 0.5*a_yp/b_yp
-        yBC_ym = 0.5*(1.-b_ym)
-        yBC_yp = 0.5*(1.-1./b_yp)
-
-        sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
-        sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
-
-        xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
-        xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
-        yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
-        yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
-
-        xBC = np.r_[xBC_x, xBC_y]
-        yBC = np.r_[yBC_x, yBC_y]
-
-    elif mesh.dim == 3: #3D
-        if (len(alpha) != 6 or len(beta) != 6 or len(gamma) != 6):
-            raise Exception("Lenght of list, alpha should be 6")
-        # fCCxm,fCCxp,fCCym,fCCyp,fCCzm,fCCzp = mesh.cellBoundaryInd
-        fxm,fxp,fym,fyp,fzm,fzp = mesh.faceBoundaryInd
-        nBC = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
-
-        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
-        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
-        alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
-        alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
-        alpha_zm, beta_zm, gamma_zm = alpha[4], beta[4], gamma[4]
-        alpha_zp, beta_zp, gamma_zp = alpha[5], beta[5], gamma[5]
-
-        # h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
-        # h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
-        # h_zm, h_zp = mesh.gridCC[fCCzm,2], mesh.gridCC[fCCzp,2]
-
-        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
-        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
-        h_zm, h_zp = mesh.hz[0]*np.ones_like(alpha_zm), mesh.hz[-1]*np.ones_like(alpha_zp)
-
-        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
-        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
-        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
-        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
-
-        a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
-        b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
-        a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
-        b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
-
-        a_zm = gamma_zm/(0.5*alpha_zm-beta_zm/h_zm)
-        b_zm = (0.5*alpha_zm+beta_zm/h_zm)/(0.5*alpha_zm-beta_zm/h_zm)
-        a_zp = gamma_zp/(0.5*alpha_zp-beta_zp/h_zp)
-        b_zp = (0.5*alpha_zp+beta_zp/h_zp)/(0.5*alpha_zp-beta_zp/h_zp)
-
-        xBC_xm = 0.5*a_xm
-        xBC_xp = 0.5*a_xp/b_xp
-        yBC_xm = 0.5*(1.-b_xm)
-        yBC_xp = 0.5*(1.-1./b_xp)
-        xBC_ym = 0.5*a_ym
-        xBC_yp = 0.5*a_yp/b_yp
-        yBC_ym = 0.5*(1.-b_ym)
-        yBC_yp = 0.5*(1.-1./b_yp)
-        xBC_zm = 0.5*a_zm
-        xBC_zp = 0.5*a_zp/b_zp
-        yBC_zm = 0.5*(1.-b_zm)
-        yBC_zp = 0.5*(1.-1./b_zp)
-
-        sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
-        sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
-        sortindsfz = np.argsort(np.r_[np.arange(mesh.nFz)[fzm], np.arange(mesh.nFz)[fzp]])
-
-        xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
-        xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
-        xBC_z = np.r_[xBC_zm, xBC_zp][sortindsfz]
-
-        yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
-        yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
-        yBC_z = np.r_[yBC_zm, yBC_zp][sortindsfz]
-
-        xBC = np.r_[xBC_x, xBC_y, xBC_z]
-        yBC = np.r_[yBC_x, yBC_y, yBC_z]
-
-    return xBC, yBC

SimPEG/EM/Static/DC/FieldsDC.py

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

SimPEG/EM/Static/DC/FieldsDC_2D.py

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

SimPEG/EM/Static/DC/ProblemDC.py

@@ -1,296 +0,0 @@
-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()
-
-
-
-

SimPEG/EM/Static/DC/ProblemDC_2D.py

@@ -1,349 +0,0 @@
-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()

SimPEG/EM/Static/DC/RxDC.py

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

SimPEG/EM/Static/DC/SrcDC.py

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

SimPEG/EM/Static/DC/SurveyDC.py

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

SimPEG/EM/Static/DC/Utils.py

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

SimPEG/EM/Static/DC/__init__.py

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

SimPEG/EM/Static/IP/ProblemIP.py

@@ -1,372 +0,0 @@
-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)
-
-

SimPEG/EM/Static/IP/SurveyIP.py

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

SimPEG/EM/Static/IP/__init__.py

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

SimPEG/EM/Static/SIP/ProblemSIP.py

@@ -1,445 +0,0 @@
-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)
-
-

SimPEG/EM/Static/SIP/Regularization.py

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

SimPEG/EM/Static/SIP/RxSIP.py

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

SimPEG/EM/Static/SIP/SrcSIP.py

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

SimPEG/EM/Static/SIP/SurveySIP.py

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

SimPEG/EM/Static/SIP/__init__.py

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

SimPEG/EM/Static/Utils/StaticUtils.py

@@ -1,317 +0,0 @@
-from SimPEG import np
-from SimPEG.EM.Static import DC, IP
-
-def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", clim=None):
-    """
-        Read list of 2D tx-rx location and plot a speudo-section of apparent
-        resistivity.
-
-        Assumes flat topo for now...
-
-        Input:
-        :param d2D, z0
-        :switch stype -> Either 'pdp' (pole-dipole) | 'dpdp' (dipole-dipole)
-        :switch dtype=-> Either 'appr' (app. res) | 'appc' (app. con) | 'volt' (potential)
-        Output:
-        :figure scatter plot overlayed on image
-
-        Edited Feb 17th, 2016
-
-        @author: dominiquef
-
-    """
-    from SimPEG import np
-    from scipy.interpolate import griddata
-    import pylab as plt
-
-    # Set depth to 0 for now
-    z0 = 0.
-
-    # Pre-allocate
-    midx = []
-    midz = []
-    rho = []
-    LEG = []
-    count = 0 # Counter for data
-    for ii in range(DCsurvey.nSrc):
-
-        Tx = DCsurvey.srcList[ii].loc
-        Rx = DCsurvey.srcList[ii].rxList[0].locs
-
-        nD = DCsurvey.srcList[ii].rxList[0].nD
-
-        data = DCsurvey.dobs[count:count+nD]
-        count += nD
-
-        # Get distances between each poles A-B-M-N
-        if stype == 'pdp':
-            MA = np.abs(Tx[0] - Rx[0][:,0])
-            NA = np.abs(Tx[0] - Rx[1][:,0])
-            MN = np.abs(Rx[1][:,0] - Rx[0][:,0])
-
-            # Create mid-point location
-            Cmid = Tx[0]
-            Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
-            if DCsurvey.mesh.dim == 2:
-                zsrc = Tx[1]
-            elif DCsurvey.mesh.dim ==3:
-                zsrc = Tx[2]
-
-        elif stype == 'dpdp':
-            MA = np.abs(Tx[0][0] - Rx[0][:,0])
-            MB = np.abs(Tx[1][0] - Rx[0][:,0])
-            NA = np.abs(Tx[0][0] - Rx[1][:,0])
-            NB = np.abs(Tx[1][0] - Rx[1][:,0])
-
-            # Create mid-point location
-            Cmid = (Tx[0][0] + Tx[1][0])/2
-            Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
-            if DCsurvey.mesh.dim == 2:
-                zsrc = (Tx[0][1] + Tx[1][1])/2
-            elif DCsurvey.mesh.dim ==3:
-                zsrc = (Tx[0][2] + Tx[1][2])/2
-
-        # Change output for dtype
-        if dtype == 'volt':
-
-            rho = np.hstack([rho,data])
-
-        else:
-
-            # Compute pant leg of apparent rho
-            if stype == 'pdp':
-
-                leg =  data * 2*np.pi  * MA * ( MA + MN ) / MN
-
-            elif stype == 'dpdp':
-
-                leg = data * 2*np.pi / ( 1/MA - 1/MB + 1/NB - 1/NA )
-                LEG.append(1./(2*np.pi) *( 1/MA - 1/MB + 1/NB - 1/NA ))
-            else:
-                print """dtype must be 'pdp'(pole-dipole) | 'dpdp' (dipole-dipole) """
-                break
-
-
-            if dtype == 'appc':
-
-                leg = np.log10(abs(1./leg))
-                rho = np.hstack([rho,leg])
-
-            elif dtype == 'appr':
-
-                leg = np.log10(abs(leg))
-                rho = np.hstack([rho,leg])
-
-            else:
-                print """dtype must be 'appr' | 'appc' | 'volt' """
-                break
-
-
-        midx = np.hstack([midx, ( Cmid + Pmid )/2 ])
-        if DCsurvey.mesh.dim==3:
-            midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + zsrc ])
-        elif DCsurvey.mesh.dim==2:
-            midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + zsrc ])
-    ax = axs
-
-    # Grid points
-    grid_x, grid_z = np.mgrid[np.min(midx):np.max(midx), np.min(midz):np.max(midz)]
-    grid_rho = griddata(np.c_[midx,midz], rho.T, (grid_x, grid_z), method='linear')
-
-    if clim == None:
-        vmin, vmax = rho.min(), rho.max()
-    else:
-        vmin, vmax = clim[0], clim[1]
-
-    grid_rho = np.ma.masked_where(np.isnan(grid_rho), grid_rho)
-    ph = plt.pcolormesh(grid_x[:,0],grid_z[0,:],grid_rho.T, clim=(vmin, vmax), vmin=vmin, vmax=vmax)
-    cbar = plt.colorbar(format="$10^{%.1f}$",fraction=0.04,orientation="horizontal")
-
-    cmin,cmax = cbar.get_clim()
-    ticks = np.linspace(cmin,cmax,3)
-    cbar.set_ticks(ticks)
-    cbar.ax.tick_params(labelsize=10)
-
-    if dtype == 'appc':
-        cbar.set_label("App.Cond",size=12)
-    elif dtype == 'appr':
-        cbar.set_label("App.Res.",size=12)
-    elif dtype == 'volt':
-        cbar.set_label("Potential (V)",size=12)
-
-    # Plot apparent resistivity
-    ax.scatter(midx,midz,s=10,c=rho.T, vmin =vmin, vmax = vmax, clim=(vmin, vmax))
-
-    #ax.set_xticklabels([])
-    #ax.set_yticklabels([])
-
-    plt.gca().set_aspect('equal', adjustable='box')
-
-
-
-    return ph, LEG
-
-def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
-    """
-        Load in endpoints and survey specifications to generate Tx, Rx location
-        stations.
-
-        Assumes flat topo for now...
-
-        Input:
-        :param endl -> input endpoints [x1, y1, z1, x2, y2, z2]
-        :object mesh -> SimPEG mesh object
-        :switch stype -> "dpdp" (dipole-dipole) | "pdp" (pole-dipole) | 'gradient'
-        : param a, n -> pole seperation, number of rx dipoles per tx
-
-        Output:
-        :param Tx, Rx -> List objects for each tx location
-            Lines: P1x, P1y, P1z, P2x, P2y, P2z
-
-        Created on Wed December 9th, 2015
-
-        @author: dominiquef
-        !! Require clean up to deal with DCsurvey
-    """
-
-    from SimPEG import np
-
-    def xy_2_r(x1,x2,y1,y2):
-        r = np.sqrt( np.sum((x2 - x1)**2 + (y2 - y1)**2) )
-        return r
-
-    ## Evenly distribute electrodes and put on surface
-    # Mesure survey length and direction
-    dl_len = xy_2_r(endl[0,0],endl[1,0],endl[0,1],endl[1,1])
-
-    dl_x = ( endl[1,0] - endl[0,0] ) / dl_len
-    dl_y = ( endl[1,1] - endl[0,1] ) / dl_len
-
-    nstn = np.floor( dl_len / a )
-
-    # Compute discrete pole location along line
-    stn_x = endl[0,0] + np.array(range(int(nstn)))*dl_x*a
-    stn_y = endl[0,1] + np.array(range(int(nstn)))*dl_y*a
-
-    if mesh.dim==2:
-        ztop = mesh.vectorNy[-1]
-        # Create line of P1 locations
-        M = np.c_[stn_x, np.ones(nstn).T*ztop]
-        # Create line of P2 locations
-        N = np.c_[stn_x+a*dl_x, np.ones(nstn).T*ztop]
-
-    elif mesh.dim==3:
-        ztop = mesh.vectorNz[-1]
-        # Create line of P1 locations
-        M = np.c_[stn_x, stn_y, np.ones(nstn).T*ztop]
-        # Create line of P2 locations
-        N = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*ztop]
-
-
-    ## Build list of Tx-Rx locations depending on survey type
-    # Dipole-dipole: Moving tx with [a] spacing -> [AB a MN1 a MN2 ... a MNn]
-    # Pole-dipole: Moving pole on one end -> [A a MN1 a MN2 ... MNn a B]
-    SrcList = []
-
-
-    if stype != 'gradient':
-
-        for ii in range(0, int(nstn)-1):
-
-
-            if stype == 'dpdp':
-                tx = np.c_[M[ii,:],N[ii,:]]
-            elif stype == 'pdp':
-                tx = np.c_[M[ii,:],M[ii,:]]
-
-            # Rx.append(np.c_[M[ii+1:indx,:],N[ii+1:indx,:]])
-
-            # Current elctrode seperation
-            AB = xy_2_r(tx[0,1],endl[1,0],tx[1,1],endl[1,1])
-
-            # Number of receivers to fit
-            nstn = np.min([np.floor( (AB - b) / a ) , n])
-
-            # Check if there is enough space, else break the loop
-            if nstn <= 0:
-                continue
-
-            # Compute discrete pole location along line
-            stn_x = N[ii,0] + dl_x*b + np.array(range(int(nstn)))*dl_x*a
-            stn_y = N[ii,1] + dl_y*b + np.array(range(int(nstn)))*dl_y*a
-
-            # Create receiver poles
-
-            if mesh.dim==3:
-                # Create line of P1 locations
-                P1 = np.c_[stn_x, stn_y, np.ones(nstn).T*ztop]
-                # Create line of P2 locations
-                P2 = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*ztop]
-                rxClass = DC.Rx.Dipole(P1, P2)
-
-            elif mesh.dim==2:
-                # Create line of P1 locations
-                P1 = np.c_[stn_x, np.ones(nstn).T*ztop]
-                # Create line of P2 locations
-                P2 = np.c_[stn_x+a*dl_x, np.ones(nstn).T*ztop]
-                rxClass = DC.Rx.Dipole_ky(P1, P2)
-
-            if stype == 'dpdp':
-                    srcClass = DC.Src.Dipole([rxClass], M[ii,:],N[ii,:])
-            elif stype == 'pdp':
-                    srcClass = DC.Src.Pole([rxClass], M[ii,:])
-            SrcList.append(srcClass)
-
-    elif stype == 'gradient':
-
-        # Gradient survey only requires Tx at end of line and creates a square
-        # grid of receivers at in the middle at a pre-set minimum distance
-
-        # Get the edge limit of survey area
-        min_x = endl[0,0] + dl_x * b
-        min_y = endl[0,1] + dl_y * b
-
-        max_x = endl[1,0] - dl_x * b
-        max_y = endl[1,1] - dl_y * b
-
-        box_l = np.sqrt( (min_x - max_x)**2 + (min_y - max_y)**2 )
-        box_w = box_l/2.
-
-        nstn = np.floor( box_l / a )
-
-        # Compute discrete pole location along line
-        stn_x = min_x + np.array(range(int(nstn)))*dl_x*a
-        stn_y = min_y + np.array(range(int(nstn)))*dl_y*a
-
-        # Define number of cross lines
-        nlin = int(np.floor( box_w / a ))
-        lind = range(-nlin,nlin+1)
-
-        ngrad = nstn * len(lind)
-
-        rx = np.zeros([ngrad,6])
-        for ii in range( len(lind) ):
-
-            # Move line in perpendicular direction by dipole spacing
-            lxx = stn_x - lind[ii]*a*dl_y
-            lyy = stn_y + lind[ii]*a*dl_x
-
-
-            M = np.c_[ lxx, lyy , np.ones(nstn).T*ztop]
-            N = np.c_[ lxx+a*dl_x, lyy+a*dl_y, np.ones(nstn).T*ztop]
-            rx[(ii*nstn):((ii+1)*nstn),:] = np.c_[M,N]
-
-            if mesh.dim==3:
-                rxClass = DC.Rx.Dipole(rx[:,:3], rx[:,3:])
-            elif mesh.dim==2:
-                M = M[:,[0,2]]
-                N = N[:,[0,2]]
-                rxClass = DC.Rx.Dipole_ky(rx[:,[0,2]], rx[:,[3,5]])
-            srcClass = DC.Src.Dipole([rxClass], M[0,:], N[-1,:])
-        SrcList.append(srcClass)
-    else:
-        print """stype must be either 'pdp', 'dpdp' or 'gradient'. """
-
-
-    return SrcList
-

SimPEG/EM/Static/Utils/__init__.py

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

SimPEG/EM/Static/__init__.py

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

SimPEG/EM/TDEM/FieldsTDEM.py

@@ -1,142 +0,0 @@
-import numpy as np
-import scipy.sparse as sp
-import SimPEG
-from SimPEG import Utils
-from SimPEG.EM.Utils import omega
-from SimPEG.Utils import Zero, Identity
-
-class Fields(SimPEG.Problem.TimeFields):
-    """
-
-    Fancy Field Storage for a TDEM survey. 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']
-        b = f[srcList,'b']
-
-    If accessing all sources for a given field, use the :code:`:`
-
-    .. code-block:: python
-
-        f = problem.fields(m)
-        e = f[:,'e']
-        b = f[:,'b']
-
-    The array returned will be size (nE or nF, nSrcs :math:`\\times` nFrequencies)
-    """
-
-    knownFields = {}
-    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_Derivs(Fields):
-    knownFields = {
-                    'bDeriv': 'F',
-                    'eDeriv': 'E',
-                    'hDeriv': 'E',
-                    'jDeriv': 'F'
-                  }
-
-
-class Fields_b(Fields):
-    """Fancy Field Storage for a TDEM survey."""
-    knownFields = {'bSolution': 'F'}
-    aliasFields = {
-                    'b': ['bSolution', 'F', '_b'],
-                    'e': ['bSolution', 'E', '_e'],
-                  }
-
-    def startup(self):
-        self.MeSigmaI      = self.survey.prob.MeSigmaI
-        self.MeSigmaIDeriv = self.survey.prob.MeSigmaIDeriv
-        self.edgeCurl      = self.survey.prob.mesh.edgeCurl
-        self.MfMui         = self.survey.prob.MfMui
-
-    def _b(self, bSolution, srcList, tInd):
-        return bSolution
-
-    def _bDeriv_u(self, tInd, src, dun_dm_v, adjoint=False):
-        return Identity()*dun_dm_v
-
-    def _bDeriv_m(self, tInd, src, v, adjoint=False):
-        return Zero()
-
-    # 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)
-
-    def _e(self, bSolution, srcList, tInd):
-        e = self.MeSigmaI * ( self.edgeCurl.T * ( self.MfMui * bSolution ) )
-        for i, src in enumerate(srcList):
-            _, S_e = src.eval(self.survey.prob, self.survey.prob.times[tInd])
-            e[:,i] = e[:,i] - self.MeSigmaI * S_e
-        return e
-
-    def _eDeriv_u(self, tInd, src, dun_dm_v, adjoint = False):
-        if adjoint is True:
-            return self.MfMui.T * ( self.edgeCurl * ( self.MeSigmaI.T * dun_dm_v ) )
-        return self.MeSigmaI * ( self.edgeCurl.T * ( self.MfMui * dun_dm_v ) )
-
-    def _eDeriv_m(self, tInd, src, v, adjoint = False):
-        _, S_e = src.eval(self.survey.prob, self.survey.prob.times[tInd])
-        bSolution = self[[src],'bSolution',tInd]
-
-        _, S_eDeriv = src.evalDeriv(self.survey.prob.times[tInd], self, adjoint=adjoint)
-
-        if adjoint is True:
-            return self.MeSigmaIDeriv(-S_e + self.edgeCurl.T * ( self.MfMui * bSolution ) ).T * v - S_eDeriv(self.MeSigmaI.T * v)
-
-        return self.MeSigmaIDeriv(-S_e + self.edgeCurl.T * ( self.MfMui * bSolution)) * v - self.MeSigmaI * S_eDeriv(v)
-
-
-
-class Fields_e(Fields):
-    """Fancy Field Storage for a TDEM survey."""
-    knownFields = {'eSolution': 'E'}
-    aliasFields = {
-                    'e': ['eSolution', 'E', '_e'],
-                    'b': ['eSolution', 'F', '_b'],
-                  }
-
-    def startup(self):
-        self.MeSigmaI      = self.survey.prob.MeSigmaI
-        self.MeSigmaIDeriv = self.survey.prob.MeSigmaIDeriv
-        self.edgeCurl      = self.survey.prob.mesh.edgeCurl
-        self.MfMui         = self.survey.prob.MfMui
-
-
-    def _e(self, eSolution, srcList, tInd):
-        return eSolution
-
-    def _eDeriv_u(self, tInd, src, dun_dm_v, adjoint = False):
-        return dun_dm_v
-
-    def _eDeriv_m(self, tInd, src, v, adjoint = False):
-        return Zero()
-
-    def _b(self, eSolution, srcList, tInd):
-        raise NotImplementedError
-
-    def _bDeriv_u(self, tInd, src, dun_dm_v, adjoint=False):
-        raise NotImplementedError
-
-    def _bDeriv_m(self, tInd, src, v, adjoint=False):
-        raise NotImplementedError
-
-    # 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)

SimPEG/EM/TDEM/SrcTDEM.py

@@ -1,246 +0,0 @@
-import SimPEG
-from SimPEG import np, Utils
-from SimPEG.Utils import Zero, Identity
-from scipy.constants import mu_0
-from SimPEG.EM.Utils import *
-
-####################################################
-# Sources
-####################################################
-
-class BaseWaveform(object):
-
-    def __init__(self, offTime=0., hasInitialFields=False):
-        self.offTime = offTime
-        self.hasInitialFields = hasInitialFields
-
-    def _assertMatchesPair(self, pair):
-        assert (isinstance(self, pair)
-            ), "Waveform object must be an instance of a %s BaseWaveform class."%(pair.__name__)
-
-    def eval(self, time):
-        raise NotImplementedError
-
-    def evalDeriv(self, time):
-        raise NotImplementedError # needed for E-formulation
-
-
-class StepOffWaveform(BaseWaveform):
-
-    def __init__(self, offTime=0.):
-        BaseWaveform.__init__(self, offTime, hasInitialFields=True)
-
-    def eval(self, time):
-        return 0.
-
-
-class RawWaveform(BaseWaveform):
-
-    def __init__(self, offTime=0.):
-        BaseWaveform.__init__(self, offTime, hasInitialFields=True)
-
-    def eval(self, time):
-        raise NotImplementedError('RawWaveform has not been implemented, you should write it!')
-
-
-class TriangularWaveform(BaseWaveform):
-
-    def __init__(self, offTime=0.):
-        BaseWaveform.__init__(self, offTime, hasInitialFields=True)
-
-    def eval(self, time):
-        raise NotImplementedError('TriangularWaveform has not been implemented, you should write it!')
-
-
-
-class BaseSrc(SimPEG.Survey.BaseSrc):
-
-    # rxPair = Rx
-    integrate = True
-    waveformPair = BaseWaveform
-
-    @property
-    def waveform(self):
-        "A waveform instance is not None"
-        return getattr(self, '_waveform', None)
-    @waveform.setter
-    def waveform(self, val):
-        if self.waveform is None:
-            val._assertMatchesPair(self.waveformPair)
-            self._mapping = val
-        else:
-            self._mapping = self.PropMap(val)
-
-
-    def __init__(self, rxList, waveform = StepOffWaveform(), **kwargs):
-        self.waveform = waveform
-        SimPEG.Survey.BaseSrc.__init__(self, rxList, **kwargs)
-
-
-    def bInitial(self, prob):
-        return Zero()
-
-    def bInitialDeriv(self, prob, v=None, adjoint=False):
-        return Zero()
-
-    def eInitial(self, prob):
-        return Zero()
-
-    def eInitialDeriv(self, prob, v=None, adjoint=False):
-        return Zero()
-
-    def eval(self, prob, time):
-        S_m = self.S_m(prob, time)
-        S_e = self.S_e(prob, time)
-        return S_m, S_e
-
-    def evalDeriv(self, prob, time, v=None, adjoint=False):
-        if v is not None:
-            return self.S_mDeriv(prob, time, v, adjoint), self.S_eDeriv(prob, time, v, adjoint)
-        else:
-            return lambda v: self.S_mDeriv(prob, time, v, adjoint), lambda v: self.S_eDeriv(prob, time, v, adjoint)
-
-    def S_m(self, prob, time):
-        return Zero()
-
-    def S_e(self, prob, time):
-        return Zero()
-
-    def S_mDeriv(self, prob, time, v=None, adjoint=False):
-        return Zero()
-
-    def S_eDeriv(self, prob, time, v=None, adjoint=False):
-        return Zero()
-
-
-class MagDipole(BaseSrc):
-
-    waveform = None
-    loc = None
-    orientation = 'Z'
-    moment = 1.
-    mu = mu_0
-
-    def __init__(self, rxList, **kwargs):
-        assert self.orientation in ['X','Y','Z'], "Orientation (right now) doesn't actually do anything! The methods in SrcUtils should take care of this..."
-        self.integrate = False
-        BaseSrc.__init__(self, rxList, **kwargs)
-
-    def _bfromVectorPotential(self, prob):
-        if prob._eqLocs is 'FE':
-            gridX = prob.mesh.gridEx
-            gridY = prob.mesh.gridEy
-            gridZ = prob.mesh.gridEz
-            C = prob.mesh.edgeCurl
-
-        elif prob._eqLocs is 'EF':
-            gridX = prob.mesh.gridFx
-            gridY = prob.mesh.gridFy
-            gridZ = prob.mesh.gridFz
-            C = prob.mesh.edgeCurl.T
-
-
-        if prob.mesh._meshType is 'CYL':
-            if not prob.mesh.isSymmetric:
-                raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-            a = MagneticDipoleVectorPotential(self.loc, gridY, 'y', mu=self.mu, moment=self.moment)
-
-        else:
-            srcfct = MagneticDipoleVectorPotential
-            ax = srcfct(self.loc, gridX, 'x', mu=self.mu, moment=self.moment)
-            ay = srcfct(self.loc, gridY, 'y', mu=self.mu, moment=self.moment)
-            az = srcfct(self.loc, gridZ, 'z', mu=self.mu, moment=self.moment)
-            a = np.concatenate((ax, ay, az))
-
-        return C*a
-
-
-    def bInitial(self, prob):
-
-        if self.waveform.hasInitialFields is False:
-            return Zero()
-
-        return self._bfromVectorPotential(prob)
-
-    def eInitial(self, prob):
-
-        if self.waveform.hasInitialFields is False:
-            return Zero()
-
-        b = self.bInitial(prob)
-        MeSigmaI = prob.MeSigmaI
-        MfMui = prob.MfMui
-        C = prob.mesh.edgeCurl
-
-        return MeSigmaI * (C.T * (MfMui * b))
-
-    def eInitialDeriv(self, prob, v=None, adjoint=False):
-
-        if self.waveform.hasInitialFields is False:
-            return Zero()
-
-        b = self.bInitial(prob)
-        MeSigmaIDeriv = prob.MeSigmaIDeriv
-        MfMui = prob.MfMui
-        C = prob.mesh.edgeCurl
-        S_e = self.S_e(prob, prob.t0)
-
-        # S_e doesn't depend on the model
-
-        if adjoint:
-            return MeSigmaIDeriv( -S_e + C.T * ( MfMui * b ) ).T * v
-
-        return MeSigmaIDeriv( -S_e + C.T * ( MfMui * b ) ) * v
-
-
-    def S_m(self, prob, time):
-        if self.waveform.hasInitialFields is False:
-            raise NotImplementedError
-        return Zero()
-
-    def S_e(self, prob, time):
-        if self.waveform.hasInitialFields is False:
-            raise NotImplementedError
-        return Zero()
-
-class CircularLoop(MagDipole):
-
-    waveform = None
-    loc = None
-    orientation = 'Z'
-    radius = None
-    mu = mu_0
-
-    def __init__(self, rxList, **kwargs):
-        assert self.orientation in ['X','Y','Z'], "Orientation (right now) doesn't actually do anything! The methods in SrcUtils should take care of this..."
-        self.integrate = False
-        BaseSrc.__init__(self, rxList, **kwargs)
-
-    def _bfromVectorPotential(self, prob):
-        if prob._eqLocs is 'FE':
-            gridX = prob.mesh.gridEx
-            gridY = prob.mesh.gridEy
-            gridZ = prob.mesh.gridEz
-            C = prob.mesh.edgeCurl
-
-        elif prob._eqLocs is 'EF':
-            gridX = prob.mesh.gridFx
-            gridY = prob.mesh.gridFy
-            gridZ = prob.mesh.gridFz
-            C = prob.mesh.edgeCurl.T
-
-
-        if prob.mesh._meshType is 'CYL':
-            if not prob.mesh.isSymmetric:
-                raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-            a = MagneticLoopVectorPotential(self.loc, gridY, 'y', radius=self.radius, mu=self.mu)
-
-        else:
-            srcfct = MagneticLoopVectorPotential
-            ax = srcfct(self.loc, gridX, 'x', mu=self.mu, radius=self.radius)
-            ay = srcfct(self.loc, gridY, 'y', mu=self.mu, radius=self.radius)
-            az = srcfct(self.loc, gridZ, 'z', mu=self.mu, radius=self.radius)
-            a = np.concatenate((ax, ay, az))
-
-        return C*a
-

SimPEG/EM/TDEM/SurveyTDEM.py

@@ -1,16 +1,10 @@
-import SimPEG
-from SimPEG import np, Utils
-from SimPEG.Utils import Zero, Identity
-from scipy.constants import mu_0
+from SimPEG import Utils, Survey, np
+from SimPEG.Survey import BaseSurvey
 from SimPEG.EM.Utils import *
-import SrcTDEM as Src
+from BaseTDEM import FieldsTDEM
 
 
-####################################################
-# Receivers
-####################################################
-
-class Rx(SimPEG.Survey.BaseTimeRx):
+class RxTDEM(Survey.BaseTimeRx):
 
     knownRxTypes = {
                     'ex':['e', 'Ex', 'N'],
@@ -27,7 +21,7 @@ class Rx(SimPEG.Survey.BaseTimeRx):
                    }
 
     def __init__(self, locs, times, rxType):
-        SimPEG.Survey.BaseTimeRx.__init__(self, locs, times, rxType)
+        Survey.BaseTimeRx.__init__(self, locs, times, rxType)
 
     @property
     def projField(self):
@@ -62,60 +56,144 @@ class Rx(SimPEG.Survey.BaseTimeRx):
         u_part = Utils.mkvc(u[src, self.projField, :])
         return P*u_part
 
-    def evalDeriv(self, src, mesh, timeMesh, v, adjoint=False):
+    def evalDeriv(self, src, mesh, timeMesh, u, v, adjoint=False):
         P = self.getP(mesh, timeMesh)
+
         if not adjoint:
-            return P * v #Utils.mkvc(v[src, self.projField+'Deriv', :])
+            return P * Utils.mkvc(v[src, self.projField, :])
         elif adjoint:
-            # dP_dF_T = P.T * v #[src, self]
-            # newshape = (len(dP_dF_T)/timeMesh.nN, timeMesh.nN )
-            return P.T * v #np.reshape(dP_dF_T, newshape, order='F')
+            return P.T * v[src, self]
 
 
-####################################################
-# Survey
-####################################################
+class SrcTDEM(Survey.BaseSrc):
+    rxPair = RxTDEM
+    radius = None
 
-class Survey(SimPEG.Survey.BaseSurvey):
+    def getInitialFields(self, mesh):
+        F0 = getattr(self, '_getInitialFields_' + self.srcType)(mesh)
+        return F0
+
+    def getJs(self, mesh, time):
+        return None
+
+
+class SrcTDEM_VMD_MVP(SrcTDEM):
+
+    def __init__(self,rxList,loc,waveformType="STEPOFF"):
+        self.loc = loc
+        self.waveformType = waveformType
+        SrcTDEM.__init__(self,rxList)
+
+    def getInitialFields(self, mesh):
+        """Vertical magnetic dipole, magnetic vector potential"""
+        if self.waveformType == "STEPOFF":
+            print ">> Step waveform: Non-zero initial condition"        
+            if mesh._meshType is 'CYL':
+                if mesh.isSymmetric:
+                    MVP = MagneticDipoleVectorPotential(self.loc, mesh, 'Ey')
+                else:
+                    raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
+            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}               
+        elif self.waveformType == "GENERAL":
+            print ">> General waveform: Zero initial condition"
+            return {"b": np.zeros(mesh.nF)}
+        else:
+            raise NotImplementedError("Only use STEPOFF or GENERAL")
+
+    def getMeS(self, mesh, MfMui):
+        if mesh._meshType is 'CYL':
+            if mesh.isSymmetric:
+                MVP = MagneticDipoleVectorPotential(self.loc, mesh, 'Ey')
+            else:
+                raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
+        elif mesh._meshType is 'TENSOR':
+            MVP = MagneticDipoleVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'])
+        else:
+            raise Exception('Unknown mesh for VMD')            
+        return mesh.edgeCurl.T*MfMui*mesh.edgeCurl*MVP
+
+
+class SrcTDEM_CircularLoop_MVP(SrcTDEM):
+    def __init__(self,rxList,loc,radius,waveformType="STEPOFF"):
+        self.loc = loc
+        self.radius = radius
+        self.waveformType = waveformType
+        SrcTDEM.__init__(self,rxList)        
+
+    def getInitialFields(self, mesh):
+        """Circular Loop, magnetic vector potential"""
+        if self.waveformType == "STEPOFF":
+            print ">> Step waveform: Non-zero initial condition"
+            if mesh._meshType is 'CYL':
+                if mesh.isSymmetric:
+                    MVP = MagneticLoopVectorPotential(self.loc, mesh, 'Ey', self.radius)
+                else:
+                    raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
+            elif mesh._meshType is 'TENSOR':
+                MVP = MagneticLoopVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'], self.radius)
+            else:
+                raise Exception('Unknown mesh for CircularLoop')
+            return {"b": mesh.edgeCurl*MVP}
+        elif self.waveformType == "GENERAL":
+            print ">> General waveform: Zero initial condition"
+            return {"b": np.zeros(mesh.nF)}
+        else:
+            raise NotImplementedError("Only use STEPOFF or GENERAL")
+
+    def getMeS(self, mesh, MfMui):
+        if mesh._meshType is 'CYL':
+            if mesh.isSymmetric:
+                MVP = MagneticLoopVectorPotential(self.loc, mesh, 'Ey', self.radius)
+            else:
+                raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
+        elif mesh._meshType is 'TENSOR':
+            MVP = MagneticLoopVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'], self.radius)
+        else:
+            raise Exception('Unknown mesh for CircularLoop')            
+        return mesh.edgeCurl.T*MfMui*mesh.edgeCurl*MVP
+
+
+class SurveyTDEM(Survey.BaseSurvey):
     """
-    Time domain electromagnetic survey
+        docstring for SurveyTDEM
     """
-
-    srcPair = Src.BaseSrc
-    rxPair = Rx
+    srcPair = SrcTDEM
 
     def __init__(self, srcList, **kwargs):
         # Sort these by frequency
         self.srcList = srcList
-        SimPEG.Survey.BaseSurvey.__init__(self, **kwargs)
+        Survey.BaseSurvey.__init__(self, **kwargs)
 
     def eval(self, u):
-        data = SimPEG.Survey.Data(self)
+        data = Survey.Data(self)
         for src in self.srcList:
             for rx in src.rxList:
                 data[src, rx] = rx.eval(src, self.mesh, self.prob.timeMesh, u)
         return data
 
     def evalDeriv(self, u, v=None, adjoint=False):
-        raise Exception('Use Receivers to project fields deriv.')
-        # assert v is not None, 'v to multiply must be provided.'
+        assert v is not None, 'v to multiply must be provided.'
 
-        # if not adjoint:
-        #     data = SimPEG.Survey.Data(self)
-        #     for src in self.srcList:
-        #         for rx in src.rxList:
-        #             data[src, rx] = rx.evalDeriv(src, self.mesh, self.prob.timeMesh, u, v)
-        #     return data
-        # else:
-        #     f = FieldsTDEM(self.mesh, self)
-        #     for src in self.srcList:
-        #         for rx in src.rxList:
-        #             Ptv = rx.evalDeriv(src, self.mesh, self.prob.timeMesh, u, v, adjoint=True)
-        #             Ptv = Ptv.reshape((-1, self.prob.timeMesh.nN), order='F')
-        #             if rx.projField not in f: # first time we are projecting
-        #                 f[src, rx.projField, :] = Ptv
-        #             else: # there are already fields, so let's add to them!
-        #                 f[src, rx.projField, :] += Ptv
-        #     return f
+        if not adjoint:
+            data = Survey.Data(self)
+            for src in self.srcList:
+                for rx in src.rxList:
+                    data[src, rx] = rx.evalDeriv(src, self.mesh, self.prob.timeMesh, u, v)
+            return data
+        else:
+            f = FieldsTDEM(self.mesh, self)
+            for src in self.srcList:
+                for rx in src.rxList:
+                    Ptv = rx.evalDeriv(src, self.mesh, self.prob.timeMesh, u, v, adjoint=True)
+                    Ptv = Ptv.reshape((-1, self.prob.timeMesh.nN), order='F')
+                    if rx.projField not in f: # first time we are projecting
+                        f[src, rx.projField, :] = Ptv
+                    else: # there are already fields, so let's add to them!
+                        f[src, rx.projField, :] += Ptv
+            return f
 
 

SimPEG/EM/TDEM/TDEM.py

@@ -1,553 +0,0 @@
-from SimPEG import Problem, Utils, np, sp, Solver as SimpegSolver
-from SimPEG.EM.Base import BaseEMProblem
-from SimPEG.EM.TDEM.SurveyTDEM import Survey as SurveyTDEM
-from SimPEG.EM.TDEM.FieldsTDEM import *
-from scipy.constants import mu_0
-import time
-
-class BaseTDEMProblem(Problem.BaseTimeProblem, BaseEMProblem):
-    """
-    We start with the first order form of Maxwell's equations
-    """
-    surveyPair = SurveyTDEM
-    fieldsPair = Fields
-
-    def __init__(self, mesh, mapping=None, **kwargs):
-        Problem.BaseTimeProblem.__init__(self, mesh, mapping=mapping, **kwargs)
-
-    def fields(self, m):
-        """
-        Solve the forward problem for the fields.
-
-        :param numpy.array m: inversion model (nP,)
-        :rtype numpy.array:
-        :return F: fields
-        """
-
-        tic = time.time()
-        self.curModel = m
-
-        F = self.fieldsPair(self.mesh, self.survey)
-
-        # set initial fields
-        F[:,self._fieldType+'Solution',0] = self.getInitialFields()
-
-        # timestep to solve forward
-        if self.verbose: print '%s\nCalculating fields(m)\n%s'%('*'*50,'*'*50)
-        Ainv = None
-        for tInd, dt in enumerate(self.timeSteps):
-            if Ainv is not None and (tInd > 0 and dt != self.timeSteps[tInd - 1]):# keep factors if dt is the same as previous step b/c A will be the same
-                Ainv.clean()
-                Ainv = None
-
-            if Ainv is None:
-                A = self.getAdiag(tInd)
-                if self.verbose: print 'Factoring...   (dt = %e)'%dt
-                Ainv = self.Solver(A, **self.solverOpts)
-                if self.verbose: print 'Done'
-
-            rhs = self.getRHS(tInd+1) # this is on the nodes of the time mesh
-            Asubdiag = self.getAsubdiag(tInd)
-
-            if self.verbose: print ('    Solving...   (tInd = %i)')% (tInd+1)
-            sol = Ainv * (rhs - Asubdiag * F[:,self._fieldType+'Solution',tInd]) # taking a step
-
-            if self.verbose: print '    Done...'
-
-            if sol.ndim == 1:
-                sol.shape = (sol.size,1)
-            F[:,self._fieldType+'Solution',tInd+1] = sol
-        if self.verbose: print '%s\nDone calculating fields(m)\n%s'%('*'*50,'*'*50)
-        Ainv.clean()
-        return F
-
-
-    def Jvec(self, m, v, f=None):
-        """
-        Jvec computes the sensitivity times a vector
-
-        .. math::
-            \mathbf{J} \mathbf{v} = \\frac{d\mathbf{P}}{d\mathbf{F}} \left( \\frac{d\mathbf{F}}{d\mathbf{u}} \\frac{d\mathbf{u}}{d\mathbf{m}} + \\frac{\partial\mathbf{F}}{\partial\mathbf{m}} \\right) \mathbf{v}
-
-        where
-
-        .. math::
-            \mathbf{A} \\frac{d\mathbf{u}}{d\mathbf{m}} + \\frac{d\mathbf{A}(\mathbf{u})}{d\mathbf{m}} = \\frac{d \mathbf{RHS}}{d \mathbf{m}}
-        """
-
-        if f is None:
-           f = self.fields(m)
-
-        ftype = self._fieldType + 'Solution' # the thing we solved for
-        self.curModel = m
-
-        # mat to store previous time-step's solution deriv times a vector for each source
-        # size: nu x nSrc
-
-        # this is a bit silly
-
-        # if self._fieldType is 'b' or self._fieldType is 'j':
-        #     ifields = np.zeros((self.mesh.nF, len(Srcs)))
-        # elif self._fieldType is 'e' or self._fieldType is 'h':
-        #     ifields = np.zeros((self.mesh.nE, len(Srcs)))
-
-        # for i, src in enumerate(self.survey.srcList):
-        dun_dm_v = np.hstack([Utils.mkvc(self.getInitialFieldsDeriv(src,v),2) for src in self.survey.srcList]) # can over-write this at each timestep
-        #
-        df_dm_v = Fields_Derivs(self.mesh, self.survey) # store the field derivs we need to project to calc full deriv
-
-        Adiaginv = None
-
-        for tInd, dt in zip(range(self.nT), self.timeSteps):
-            if Adiaginv is not None and (tInd > 0 and dt != self.timeSteps[tInd - 1]):# keep factors if dt is the same as previous step b/c A will be the same
-                Adiaginv.clean()
-                Adiaginv = None
-
-            if Adiaginv is None:
-                A = self.getAdiag(tInd)
-                Adiaginv = self.Solver(A, **self.solverOpts)
-
-            Asubdiag = self.getAsubdiag(tInd)
-
-            for i, src in enumerate(self.survey.srcList):
-
-                # here, we are lagging by a timestep, so filling in as we go
-                for projField in set([rx.projField for rx in src.rxList]):
-                    # Seogi: df_duFun?
-                    df_dmFun = getattr(f, '_%sDeriv'%projField, None)
-                    # df_dm_v is dense, but we only need the times at (rx.P.T * ones > 0)
-                    # This should be called rx.footprint
-                    df_dm_v[src, '%sDeriv'%projField , tInd] = df_dmFun(tInd, src, dun_dm_v[:,i], v)
-
-                un_src = f[src,ftype,tInd+1]
-
-                dA_dm_v   = self.getAdiagDeriv(tInd, un_src, v) # cell centered on time mesh
-                dRHS_dm_v = self.getRHSDeriv(tInd+1, src, v) # on nodes of time mesh
-
-                dAsubdiag_dm_v = self.getAsubdiagDeriv(tInd, f[src,ftype,tInd], v)
-
-                JRHS = dRHS_dm_v - dAsubdiag_dm_v - dA_dm_v
-
-                # step in time and overwrite
-                if tInd != len(self.timeSteps+1):
-                    dun_dm_v[:,i] = Adiaginv * (JRHS - Asubdiag * dun_dm_v[:,i])
-
-        # Seogi: suspcious spot
-        # Jv = self.dataPair(self.survey)
-        Jv = []
-        for src in self.survey.srcList:
-            for rx in src.rxList:
-                # Looping over data class append memory as well!!
-                # Jv[src,rx] = rx.evalDeriv(src, self.mesh, self.timeMesh, Utils.mkvc(df_dm_v[src,'%sDeriv'%rx.projField,:]))
-                Jv.append(rx.evalDeriv(src, self.mesh, self.timeMesh, Utils.mkvc(df_dm_v[src,'%sDeriv'%rx.projField,:])))
-        Adiaginv.clean()
-        # del df_dm_v, dun_dm_v, Asubdiag
-        # return Utils.mkvc(Jv)
-        return np.hstack(Jv)
-
-    def Jtvec(self, m, v, f=None):
-
-        """
-        Jvec computes the adjoint of the sensitivity times a vector
-
-        .. math::
-            \mathbf{J}^\\top \mathbf{v} =  \left( \\frac{d\mathbf{u}}{d\mathbf{m}} ^ \\top \\frac{d\mathbf{F}}{d\mathbf{u}} ^ \\top  + \\frac{\partial\mathbf{F}}{\partial\mathbf{m}} ^ \\top \\right) \\frac{d\mathbf{P}}{d\mathbf{F}} ^ \\top \mathbf{v}
-
-        where
-
-        .. math::
-            \\frac{d\mathbf{u}}{d\mathbf{m}} ^\\top \mathbf{A}^\\top  + \\frac{d\mathbf{A}(\mathbf{u})}{d\mathbf{m}} ^ \\top = \\frac{d \mathbf{RHS}}{d \mathbf{m}} ^ \\top
-        """
-
-        if f is None:
-            f = self.fields(m)
-
-        self.curModel = m
-        ftype = self._fieldType + 'Solution' # the thing we solved for
-
-        # Ensure v is a data object.
-        if not isinstance(v, self.dataPair):
-            v = self.dataPair(self.survey, v)
-
-        df_duT_v = Fields_Derivs(self.mesh, self.survey)
-        ATinv_df_duT_v = np.zeros((len(self.survey.srcList), len(f[self.survey.srcList[0],ftype,0])), dtype=float) # same size as fields at a single timestep
-
-        JTv = np.zeros(m.shape, dtype=float)
-
-        # Loop over sources and receivers to create a fields object: PT_v, df_duT_v, df_dmT_v
-        PT_v = Fields_Derivs(self.mesh, self.survey) # initialize storage for PT_v (don't need to preserve over sources)
-        for src in self.survey.srcList:
-            # Looping over initializing field class is appending memory!
-            # PT_v = Fields_Derivs(self.mesh, self.survey) # initialize storage for PT_v (don't need to preserve over sources)
-            # initialize size
-            df_duT_v[src, '%sDeriv'%self._fieldType, :] = np.zeros_like(f[src, self._fieldType, :])
-
-            for rx in src.rxList:
-                print ('_%sDeriv')%(rx.projField)
-                PT_v[src,'%sDeriv'%rx.projField,:] = rx.evalDeriv(src, self.mesh, self.timeMesh, Utils.mkvc(v[src,rx]), adjoint=True) # this is +=
-
-                # PT_v = np.reshape(curPT_v,(len(curPT_v)/self.timeMesh.nN, self.timeMesh.nN), order='F')
-                df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
-
-                for tInd in range(self.nT+1):
-                    cur = df_duTFun(tInd, src, None, Utils.mkvc(PT_v[src,'%sDeriv'%rx.projField,tInd]), adjoint=True)
-                    df_duT_v[src, '%sDeriv'%self._fieldType, tInd] = df_duT_v[src, '%sDeriv'%self._fieldType, tInd] + Utils.mkvc(cur[0],2)
-                    JTv = cur[1] + JTv
-
-        del PT_v # no longer need this
-
-        AdiagTinv = None
-
-        # Do the back-solve through time
-        for tIndP in reversed(range(self.nT + 1)):
-            tInd = tIndP - 1
-            if AdiagTinv is not None and (tInd <= self.nT and self.timeSteps[tInd] != self.timeSteps[tInd+1]): # if the previous timestep is the same --> no need to refactor the matrix
-                AdiagTinv.clean()
-                AdiagTinv = None
-
-            # refactor if we need to
-            if AdiagTinv is None and tInd > -1:
-                Adiag = self.getAdiag(tInd)
-                AdiagTinv = self.Solver(Adiag.T, **self.solverOpts)
-
-            dAsubdiag_dm_v = Zero()
-
-            if tInd < self.nT - 1:
-                Asubdiag = self.getAsubdiag(tInd+1)
-
-
-            for isrc, src in enumerate(self.survey.srcList):
-                # solve against df_duT_v
-                if tInd >= self.nT-1:
-                    # last timestep (first to be solved)
-                    ATinv_df_duT_v[isrc,:] = AdiagTinv * df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1]
-                elif tInd > -1:
-                # else:
-                    ATinv_df_duT_v[isrc,:] = AdiagTinv * (Utils.mkvc(df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1]) - Asubdiag.T * Utils.mkvc(ATinv_df_duT_v[isrc,:]))
-                else:
-                    # AdiagTinv = I
-                    ATinv_df_duT_v[isrc,:] = Utils.mkvc(df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1]) - Asubdiag.T * Utils.mkvc(ATinv_df_duT_v[isrc,:])
-                    # - Utils.mkvc(Asubdiag.T * Utils.mkvc(ATinv_df_duT_v[isrc,:]))
-                    # (Utils.mkvc(df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1]) - Asubdiag.T * Utils.mkvc(ATinv_df_duT_v[isrc,:]))
-
-                if tInd < self.nT - 1:
-                    dAsubdiagT_dm_v = self.getAsubdiagDeriv(tInd+1, f[src,ftype,tInd+1], ATinv_df_duT_v[isrc,:], adjoint = True)
-
-                if tInd > -1:
-                    un_src = f[src,ftype,tInd+1]
-                    dAT_dm_v = self.getAdiagDeriv(tInd, un_src, ATinv_df_duT_v[isrc,:], adjoint=True) # cell centered on time mesh
-                    dRHST_dm_v = self.getRHSDeriv(tInd+1, src, ATinv_df_duT_v[isrc,:], adjoint=True) # on nodes of time mesh
-
-                    JTv = JTv + Utils.mkvc(- dAT_dm_v - dAsubdiag_dm_v + dRHST_dm_v)
-                else:
-                    # dA_dm_v = self.getInitialFieldsDeriv(df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1], adjoint=True)
-                    # print np.linalg.norm(self.getInitialFieldsDeriv(src, df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1], adjoint=True))
-                    # print np.linalg.norm(df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1])
-                    # vec = - Asubdiag.T * Utils.mkvc(ATinv_df_duT_v[isrc,:]) + Utils.mkvc(df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1])
-                    # dAsubdiagT_dm_v = self.getAsubdiagDeriv(tInd+1, f[src,ftype,tInd+1], Utils.mkvc(ATinv_df_duT_v[isrc,:]), adjoint = True)
-                    dRHST_dm_v = Utils.mkvc(self.getInitialFieldsDeriv(src, Utils.mkvc(ATinv_df_duT_v[isrc,:]) , adjoint=True))
-
-                    JTv = JTv + Utils.mkvc( -dAsubdiagT_dm_v + dRHST_dm_v) #
-
-
-
-                    # # dAT_dm_v = self.getAdiagDeriv(tInd, un_src, ATinv_df_duT_v[isrc,:], adjoint=True) # cell centered on time mesh
-                    # dRHST_dm_v0 = self.getRHSDeriv(tInd+1, src, ATinv_df_duT_v[isrc,:], adjoint=True) # on nodes of time mesh
-                    # dRHST_dm_v1 = self.getInitialFieldsDeriv( Utils.mkvc(df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1]), adjoint=True)
-                    # JTv = JTv + Utils.mkvc(dRHST_dm_v0 + dRHST_dm_v1)
-
-                    # print 'here'
-                    # inFields = self.getInitialFieldsDeriv(f[src,ftype,tInd+1], Utils.mkvc(df_duT_v[src,'%sDeriv'%self._fieldType,tInd+1]), adjoint=True)
-                    #  # - Asubdiag.T * Utils.mkvc(ATinv_df_duT_v[isrc,:]), adjoint=True)
-                    # print inFields.shape
-                    # JTv = JTv + inFields
-                # dAsubdiag_dm_v = 0
-
-
-
-        # Missing the 0 step
-
-        # adding du_dm^T * dF_du^T * P^T vfor time 0 (no dRHS_dm_v at time 0)
-        # Asubdiag = self.getAsubdiag(0)
-        # for src in self.survey.srcList:
-        #     for projField in set(rx.projField):
-        #         v = AdiagTinv * (Utils.mkvc(df_duT_v[src,'%sDeriv'%self._fieldType,0]) - Asubdiag.T * Utils.mkvc(ATinv_df_duT_v[isrc,:]))
-        #         JTv = JTv - Utils.mkvc(self.getAdiagDeriv(0, f[src, ftype, tInd], v, adjoint = True))
-        #         # JTv = JTv + self.getInitialFieldsDeriv(Utils.mkvc(df_duT_v[src,'%sDeriv'%self._fieldType,0] - Asubdiag.T * Utils.mkvc(ATinv_df_duT_v[isrc,:])), adjoint=True)
-
-        # del df_duT_v, ATinv_df_duT_v, A, Asubdiag
-        if AdiagTinv is not None:
-            AdiagTinv.clean()
-
-        return Utils.mkvc(JTv).astype(float)
-
-
-
-    def getSourceTerm(self, tInd):
-
-        Srcs = self.survey.srcList
-
-        if self._eqLocs is 'FE':
-            S_m = np.zeros((self.mesh.nF,len(Srcs)))
-            S_e = np.zeros((self.mesh.nE,len(Srcs)))
-        elif self._eqLocs is 'EF':
-            S_m = np.zeros((self.mesh.nE,len(Srcs)))
-            S_e = np.zeros((self.mesh.nF,len(Srcs)))
-
-        for i, src in enumerate(Srcs):
-            smi, sei = src.eval(self, self.times[tInd])
-            S_m[:,i] = S_m[:,i] + smi
-            S_e[:,i] = S_e[:,i] + sei
-
-        return S_m, S_e
-
-    def getInitialFields(self):
-
-        Srcs = self.survey.srcList
-
-        if self._fieldType is 'b' or self._fieldType is 'j':
-            ifields = np.zeros((self.mesh.nF, len(Srcs)))
-        elif self._fieldType is 'e' or self._fieldType is 'h':
-            ifields = np.zeros((self.mesh.nE, len(Srcs)))
-
-        for i,src in enumerate(Srcs):
-            ifields[:,i] = ifields[:,i] + getattr(src, '%sInitial'%self._fieldType, None)(self)
-
-        return ifields
-
-    def getInitialFieldsDeriv(self, src, v, adjoint=False):
-
-        if adjoint is False:
-            if self._fieldType is 'b' or self._fieldType is 'j':
-                ifieldsDeriv = np.zeros(self.mesh.nF)
-            elif self._fieldType is 'e' or self._fieldType is 'h':
-                ifieldsDeriv = np.zeros(self.mesh.nE)
-
-        elif adjoint is True:
-            ifieldsDeriv = np.zeros(self.mapping.nP)
-
-        ifieldsDeriv = Utils.mkvc(getattr(src, '%sInitialDeriv'%self._fieldType, None)(self,v,adjoint)) + ifieldsDeriv
-
-            # ifieldsDeriv = Utils.mkvc(getattr(src, '%sInitialDeriv'%self._fieldType, None)(self,v,adjoint)) + ifieldsDeriv
-            # ifieldsDeriv = self.getAdiagDeriv(None, u, v, adjoint)
-            # ifieldsDeriv = ifieldsDeriv.sum()
-
-        return ifieldsDeriv
-
-
-##########################################################################################
-################################ E-B Formulation #########################################
-##########################################################################################
-
-# ------------------------------- Problem_b -------------------------------------------- #
-
-class Problem_b(BaseTDEMProblem):
-    """
-    Starting from the quasi-static E-B formulation of Maxwell's equations (semi-discretized)
-
-    .. math::
-
-        \mathbf{C} \mathbf{e} + \\frac{\partial \mathbf{b}}{\partial t} = \mathbf{s_m} \\\\
-        \mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f} \mathbf{b} - \mathbf{M_{\sigma}^e} \mathbf{e} = \mathbf{s_e}
-
-    where :math:`\mathbf{s_e}` is an integrated quantity, we eliminate :math:`\mathbf{e}` using
-
-    .. math::
-        \mathbf{e} = \mathbf{M_{\sigma}^e}^{-1} \mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f} \mathbf{b} - \mathbf{M_{\sigma}^e}^{-1} \mathbf{s_e}
-
-    to obtain a second order semi-discretized system in :math:`\mathbf{b}`
-
-    .. math::
-        \mathbf{C} \mathbf{M_{\sigma}^e}^{-1} \mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f} \mathbf{b}  + \\frac{\partial \mathbf{b}}{\partial t} = \mathbf{C} \mathbf{M_{\sigma}^e}^{-1} \mathbf{s_e} + \mathbf{s_m}
-
-    and moving everything except the time derivative to the rhs gives
-
-    .. math::
-        \\frac{\partial \mathbf{b}}{\partial t} = -\mathbf{C} \mathbf{M_{\sigma}^e}^{-1} \mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f} \mathbf{b} + \mathbf{C} \mathbf{M_{\sigma}^e}^{-1} \mathbf{s_e} + \mathbf{s_m}
-
-    For the time discretization, we use backward euler. To solve for the :math:`n+1`th time step, we have
-
-    .. math::
-        \\frac{\mathbf{b}^{n+1} - \mathbf{b}^{n}}{\mathbf{dt}} = -\mathbf{C} \mathbf{M_{\sigma}^e}^{-1} \mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f} \mathbf{b}^{n+1} + \mathbf{C} \mathbf{M_{\sigma}^e}^{-1} \mathbf{s_e}^{n+1} + \mathbf{s_m}^{n+1}
-
-    re-arranging to put :math:`\mathbf{b}^{n+1}` on the left hand side gives
-
-    .. math::
-        (\mathbf{I} + \mathbf{dt} \mathbf{C} \mathbf{M_{\sigma}^e}^{-1} \mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f}) \mathbf{b}^{n+1} = \mathbf{b}^{n} + \mathbf{dt}(\mathbf{C} \mathbf{M_{\sigma}^e}^{-1} \mathbf{s_e}^{n+1} + \mathbf{s_m}^{n+1})
-
-    :param Mesh mesh: mesh
-    :param Mapping mapping: mapping
-    """
-
-    _fieldType = 'b'
-    _eqLocs    = 'FE'
-    fieldsPair = Fields_b
-    surveyPair = SurveyTDEM
-
-    def __init__(self, mesh, mapping=None, **kwargs):
-        BaseTDEMProblem.__init__(self, mesh, mapping=mapping, **kwargs)
-
-    def getAdiag(self, tInd):
-        """
-        System matrix at a given time index
-
-        .. math::
-            (\mathbf{I} + \mathbf{dt} \mathbf{C} \mathbf{M_{\sigma}^e}^{-1} \mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f})
-
-        """
-        assert tInd >= 0 and tInd < self.nT
-
-        dt = self.timeSteps[tInd]
-        C = self.mesh.edgeCurl
-        MeSigmaI = self.MeSigmaI
-        MfMui = self.MfMui
-        I = Utils.speye(self.mesh.nF)
-
-        A = 1./dt * I + ( C * ( MeSigmaI * (C.T * MfMui ) ) )
-
-        if self._makeASymmetric is True:
-            return MfMui.T * A
-        return A
-
-    def getAdiagDeriv(self, tInd, u, v, adjoint=False):
-        C = self.mesh.edgeCurl
-        MeSigmaIDeriv = lambda x: self.MeSigmaIDeriv(x)
-        MfMui = self.MfMui
-
-        if adjoint:
-            if self._makeASymmetric is True:
-                v = MfMui * v
-            return  MeSigmaIDeriv(C.T * ( MfMui * u )).T * ( C.T * v )
-
-        ADeriv = ( C * ( MeSigmaIDeriv(C.T * ( MfMui * u )) * v ) )
-        if self._makeASymmetric is True:
-            return MfMui.T * ADeriv
-        return ADeriv
-
-
-    def getAsubdiag(self, tInd):
-
-        dt = self.timeSteps[tInd]
-        MfMui = self.MfMui
-        Asubdiag = - 1./dt * sp.eye(self.mesh.nF)
-
-        if self._makeASymmetric is True:
-            return MfMui.T * Asubdiag
-
-        return Asubdiag
-
-    def getAsubdiagDeriv(self, tInd, u, v, adjoint=False):
-        return Zero() * v
-
-
-
-    def getRHS(self, tInd):
-        C = self.mesh.edgeCurl
-        MeSigmaI = self.MeSigmaI
-        MfMui = self.MfMui
-
-        S_m, S_e = self.getSourceTerm(tInd)
-
-        rhs =  (C * (MeSigmaI * S_e) + S_m)
-        if self._makeASymmetric is True:
-            return MfMui.T * rhs
-        return rhs
-
-    def getRHSDeriv(self, tInd, src, v, adjoint=False):
-
-        C = self.mesh.edgeCurl
-        MeSigmaI = self.MeSigmaI
-        MeSigmaIDeriv = lambda u: self.MeSigmaIDeriv(u)
-        MfMui = self.MfMui
-
-        _, S_e = src.eval(tInd, self)
-        S_mDeriv, S_eDeriv = src.evalDeriv(self.times[tInd], self, adjoint=adjoint)
-
-        if adjoint:
-            if self._makeASymmetric is True:
-                v = self.MfMui * v
-            if isinstance(S_e, Utils.Zero):
-                MeSigmaIDerivT_v = Utils.Zero()
-            else:
-                MeSigmaIDerivT_v = MeSigmaIDeriv(S_e).T * v
-            RHSDeriv = MeSigmaIDerivT_v + S_eDeriv( MeSigmaI.T *  ( C.T * v ) ) + S_mDeriv(v)
-            return RHSDeriv
-
-        if isinstance(S_e, Utils.Zero):
-            MeSigmaIDeriv_v = Utils.Zero()
-        else:
-            MeSigmaIDeriv_v = MeSigmaIDeriv(S_e) * v
-
-        RHSDeriv = (C * (MeSigmaIDeriv_v + MeSigmaI * S_eDeriv(v) + S_mDeriv(v)))
-
-        if self._makeASymmetric is True:
-            return self.MfMui.T * RHSDeriv
-        return RHSDeriv
-
-
-# ------------------------------- Problem_e -------------------------------------------- #
-
-class Problem_e(BaseTDEMProblem):
-
-    _fieldType = 'e'
-    _eqLocs    = 'FE'
-    fieldsPair = Fields_e
-    surveyPair = SurveyTDEM
-
-    def __init__(self, mesh, mapping=None, **kwargs):
-        BaseTDEMProblem.__init__(self, mesh, mapping=mapping, **kwargs)
-
-    def getAdiag(self, tInd):
-        """
-        System matrix at a given time index
-
-        """
-        assert tInd >= 0 and tInd < self.nT
-
-        dt = self.timeSteps[tInd]
-        C = self.mesh.edgeCurl
-        MfMui = self.MfMui
-        MeSigma = self.MeSigma
-
-        return C.T * ( MfMui * C ) + 1./dt * MeSigma
-
-
-    def getAdiagDeriv(self, tInd, u, v, adjoint=False):
-        assert tInd >= 0 and tInd < self.nT
-
-        dt = self.timeSteps[tInd]
-        C = self.mesh.edgeCurl
-        MfMui = self.MfMui
-        MeSigmaDeriv = self.MeSigmaDeriv(u)
-
-        if adjoint:
-            return 1./dt * MeSigmaDeriv.T * v
-
-        return 1./dt * MeSigmaDeriv * v
-
-
-    def getAsubdiag(self, tInd):
-        assert tInd >= 0 and tInd < self.nT
-
-        dt = self.timeSteps[tInd]
-
-        return - 1./dt * self.MeSigma
-
-    def getAsubdiagDeriv(self, tInd, u, v, adjoint=False):
-        dt = self.timeSteps[tInd]
-
-        if adjoint:
-            return - 1./dt * self.MeSigmaDeriv(u).T * v
-
-        return - 1./dt * self.MeSigmaDeriv(u) * v
-
-    def getRHS(self, tInd):
-        return Zero()
-
-    def getRHSDeriv(self, tInd, src, v, adjoint=False):
-        return Zero()
-
-
-
-
-

SimPEG/EM/TDEM/__init__.py

@@ -1,3 +1,3 @@
-from TDEM import BaseTDEMProblem, Problem_b, Problem_e
-from FieldsTDEM import Fields, Fields_b
-from SurveyTDEM import Survey, Src, Rx
+from SurveyTDEM import * #SurveyTDEM, RxTDEM, SrcTDEM
+from BaseTDEM import BaseTDEMProblem, FieldsTDEM
+from TDEM_b import ProblemTDEM_b

SimPEG/EM/TDEM_old/SurveyTDEM.py

@@ -1,199 +0,0 @@
-from SimPEG import Utils, Survey, np
-from SimPEG.Survey import BaseSurvey
-from SimPEG.EM.Utils import *
-from BaseTDEM import FieldsTDEM
-import SrcTDEM as Src
-
-class RxTDEM(Survey.BaseTimeRx):
-
-    knownRxTypes = {
-                    'ex':['e', 'Ex', 'N'],
-                    'ey':['e', 'Ey', 'N'],
-                    'ez':['e', 'Ez', 'N'],
-
-                    'bx':['b', 'Fx', 'N'],
-                    'by':['b', 'Fy', 'N'],
-                    'bz':['b', 'Fz', 'N'],
-
-                    'dbxdt':['b', 'Fx', 'CC'],
-                    'dbydt':['b', 'Fy', 'CC'],
-                    'dbzdt':['b', 'Fz', 'CC'],
-                   }
-
-    def __init__(self, locs, times, rxType):
-        Survey.BaseTimeRx.__init__(self, locs, times, rxType)
-
-    @property
-    def projField(self):
-        """Field Type projection (e.g. e b ...)"""
-        return self.knownRxTypes[self.rxType][0]
-
-    @property
-    def projGLoc(self):
-        """Grid Location projection (e.g. Ex Fy ...)"""
-        return self.knownRxTypes[self.rxType][1]
-
-    @property
-    def projTLoc(self):
-        """Time Location projection (e.g. CC N)"""
-        return self.knownRxTypes[self.rxType][2]
-
-    def getTimeP(self, timeMesh):
-        """
-            Returns the time projection matrix.
-
-            .. note::
-
-                This is not stored in memory, but is created on demand.
-        """
-        if self.rxType in ['dbxdt','dbydt','dbzdt']:
-            return timeMesh.getInterpolationMat(self.times, self.projTLoc)*timeMesh.faceDiv
-        else:
-            return timeMesh.getInterpolationMat(self.times, self.projTLoc)
-
-    def eval(self, src, mesh, timeMesh, u):
-        P = self.getP(mesh, timeMesh)
-        u_part = Utils.mkvc(u[src, self.projField, :])
-        return P*u_part
-
-    def evalDeriv(self, src, mesh, timeMesh, u, v, adjoint=False):
-        P = self.getP(mesh, timeMesh)
-
-        if not adjoint:
-            return P * Utils.mkvc(v[src, self.projField, :])
-        elif adjoint:
-            return P.T * v[src, self]
-
-
-class SrcTDEM(Survey.BaseSrc):
-    rxPair = RxTDEM
-    radius = None
-
-    def getInitialFields(self, mesh):
-        F0 = getattr(self, '_getInitialFields_' + self.srcType)(mesh)
-        return F0
-
-    def getJs(self, mesh, time):
-        return None
-
-
-class SrcTDEM_VMD_MVP(SrcTDEM):
-
-    def __init__(self,rxList,loc,waveformType="STEPOFF"):
-        self.loc = loc
-        self.waveformType = waveformType
-        SrcTDEM.__init__(self,rxList)
-
-    def getInitialFields(self, mesh):
-        """Vertical magnetic dipole, magnetic vector potential"""
-        if self.waveformType == "STEPOFF":
-            print ">> Step waveform: Non-zero initial condition"
-            if mesh._meshType is 'CYL':
-                if mesh.isSymmetric:
-                    MVP = MagneticDipoleVectorPotential(self.loc, mesh, 'Ey')
-                else:
-                    raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-            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}
-        elif self.waveformType == "GENERAL":
-            print ">> General waveform: Zero initial condition"
-            return {"b": np.zeros(mesh.nF)}
-        else:
-            raise NotImplementedError("Only use STEPOFF or GENERAL")
-
-    def getMeS(self, mesh, MfMui):
-        if mesh._meshType is 'CYL':
-            if mesh.isSymmetric:
-                MVP = MagneticDipoleVectorPotential(self.loc, mesh, 'Ey')
-            else:
-                raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-        elif mesh._meshType is 'TENSOR':
-            MVP = MagneticDipoleVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'])
-        else:
-            raise Exception('Unknown mesh for VMD')
-        return mesh.edgeCurl.T*MfMui*mesh.edgeCurl*MVP
-
-
-class SrcTDEM_CircularLoop_MVP(SrcTDEM):
-    def __init__(self,rxList,loc,radius,waveformType="STEPOFF"):
-        self.loc = loc
-        self.radius = radius
-        self.waveformType = waveformType
-        SrcTDEM.__init__(self,rxList)
-
-    def getInitialFields(self, mesh):
-        """Circular Loop, magnetic vector potential"""
-        if self.waveformType == "STEPOFF":
-            print ">> Step waveform: Non-zero initial condition"
-            if mesh._meshType is 'CYL':
-                if mesh.isSymmetric:
-                    MVP = MagneticLoopVectorPotential(self.loc, mesh, 'Ey', self.radius)
-                else:
-                    raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-            elif mesh._meshType is 'TENSOR':
-                MVP = MagneticLoopVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'], self.radius)
-            else:
-                raise Exception('Unknown mesh for CircularLoop')
-            return {"b": mesh.edgeCurl*MVP}
-        elif self.waveformType == "GENERAL":
-            print ">> General waveform: Zero initial condition"
-            return {"b": np.zeros(mesh.nF)}
-        else:
-            raise NotImplementedError("Only use STEPOFF or GENERAL")
-
-    def getMeS(self, mesh, MfMui):
-        if mesh._meshType is 'CYL':
-            if mesh.isSymmetric:
-                MVP = MagneticLoopVectorPotential(self.loc, mesh, 'Ey', self.radius)
-            else:
-                raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-        elif mesh._meshType is 'TENSOR':
-            MVP = MagneticLoopVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'], self.radius)
-        else:
-            raise Exception('Unknown mesh for CircularLoop')
-        return mesh.edgeCurl.T*MfMui*mesh.edgeCurl*MVP
-
-
-class SurveyTDEM(Survey.BaseSurvey):
-    """
-        docstring for SurveyTDEM
-    """
-    srcPair = SrcTDEM
-
-    def __init__(self, srcList, **kwargs):
-        # Sort these by frequency
-        self.srcList = srcList
-        Survey.BaseSurvey.__init__(self, **kwargs)
-
-    def projectFields(self, u):
-        data = Survey.Data(self)
-        for src in self.srcList:
-            for rx in src.rxList:
-                data[src, rx] = rx.projectFields(src, self.mesh, self.prob.timeMesh, u)
-        return data
-
-    def projectFieldsDeriv(self, u, v=None, adjoint=False):
-        assert v is not None, 'v to multiply must be provided.'
-
-        if not adjoint:
-            data = Survey.Data(self)
-            for src in self.srcList:
-                for rx in src.rxList:
-                    data[src, rx] = rx.projectFieldsDeriv(src, self.mesh, self.prob.timeMesh, u, v)
-            return data
-        else:
-            f = FieldsTDEM(self.mesh, self)
-            for src in self.srcList:
-                for rx in src.rxList:
-                    Ptv = rx.projectFieldsDeriv(src, self.mesh, self.prob.timeMesh, u, v, adjoint=True)
-                    Ptv = Ptv.reshape((-1, self.prob.timeMesh.nN), order='F')
-                    if rx.projField not in f: # first time we are projecting
-                        f[src, rx.projField, :] = Ptv
-                    else: # there are already fields, so let's add to them!
-                        f[src, rx.projField, :] += Ptv
-            return f
-
-

SimPEG/EM/TDEM_old/__init__.py

@@ -1,3 +0,0 @@
-from SurveyTDEM import * #SurveyTDEM, RxTDEM, SrcTDEM
-from BaseTDEM import BaseTDEMProblem, FieldsTDEM
-from TDEM_b import ProblemTDEM_b

SimPEG/EM/Utils/testingUtils.py

@@ -20,61 +20,56 @@ 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 = 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')
+    Rx0 = EM.FDEM.Rx(XYZ, comp)
 
     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, mesh.getEdgeInnerProduct()*S_e))
+                Src.append(EM.FDEM.Src.RawVec([Rx0], freq, S_m, S_e))
 
             elif fdemType is 'h' or fdemType is 'j':
                 S_m = np.zeros(mesh.nE)
                 S_e = np.zeros(mesh.nF)
                 S_m[Utils.closestPoints(mesh,[0.,0.,0.],'Ez') + np.sum(mesh.vnE[:1])] = 1e-3
                 S_e[Utils.closestPoints(mesh,[0.,0.,0.],'Fz') + np.sum(mesh.vnF[:1])] = 1e-3
-                Src.append(EM.FDEM.Src.RawVec([rx0], freq, mesh.getEdgeInnerProduct()*S_m, S_e))
+                Src.append(EM.FDEM.Src.RawVec([Rx0], freq, S_m, S_e))
 
     if verbose:
         print '  Fetching %s problem' % (fdemType)
 
     if fdemType == 'e':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem3D_e(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem_e(mesh, mapping=mapping)
 
     elif fdemType == 'b':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem3D_b(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem_b(mesh, mapping=mapping)
 
     elif fdemType == 'j':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem3D_j(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem_j(mesh, mapping=mapping)
 
     elif fdemType == 'h':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem3D_h(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem_h(mesh, mapping=mapping)
 
     else:
         raise NotImplementedError()
@@ -95,7 +90,7 @@ def crossCheckTest(SrcList, fdemType1, fdemType2, comp, addrandoms = False, useM
     prb1 = getFDEMProblem(fdemType1, comp, SrcList, freq, useMu, verbose)
     mesh = prb1.mesh
     print 'Cross Checking Forward: %s, %s formulations - %s' % (fdemType1, fdemType2, comp)
-
+    
     logsig = np.log(np.ones(mesh.nC)*CONDUCTIVITY)
     mu = np.ones(mesh.nC)*MU
 

SimPEG/EM/__init__.py

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

SimPEG/Examples/DC_Forward_PseudoSection.py

@@ -2,7 +2,7 @@ from SimPEG import Mesh, Utils, np, sp
 import SimPEG.DCIP as DC
 import time
 
-def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', unitType='appConductivity', plotIt=True):
+def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', dtype='appc', plotIt=True):
     """
         DC Forward Simulation
         =====================
@@ -15,14 +15,14 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
         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"
+        stype   = survey type "pdp" (pole dipole) or "dpdp" (dipole dipole)
+        dtype   = Data type "appr" (app res) | "appc" (app cond) | "volt" (potential)
         Created by @fourndo
 
     """
 
-    assert 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)"
+    assert stype in ['pdp', 'dpdp'], "Source type (stype) must be pdp or dpdp (pole dipole or dipole dipole)"
+    assert dtype in ['appr', 'appc', 'volt'], "Data type (dtype) must be appr (app res) or appc (app cond) or volt (potential)"
 
     if loc is None:
         loc = np.c_[[-50.,0.,-50.],[50.,0.,-50.]]
@@ -73,8 +73,8 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
     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, surveyType, param[0], param[1], param[2])
-    survey, Tx, Rx = DC.gen_DCIPsurvey(locs, mesh, surveyType, param[0], param[1], param[2])
+    # [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])
 
     # 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, surveyType='dipole-dipole', u
         rxloc_N = np.asarray(Rx[ii][:,3:])
 
 
-        # For usual cases 'dipole-dipole' or "gradient"
-        if surveyType == 'pole-dipole':
+        # For usual cases "dpdp" or "gradient"
+        if stype == 'pdp':
             # 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, surveyType='dipole-dipole', u
         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')
@@ -188,13 +188,15 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
         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, surveyType=surveyType, unitType=unitType)        # plt.scatter(Tx2d[0][:],Tx[0][2,:],s=40,c='g', marker='v')
+        dat = DC.plot_pseudoSection(survey2D,ax2,stype=stype, dtype = dtype)
+
+        # plt.scatter(Tx2d[0][:],Tx[0][2,:],s=40,c='g', marker='v')
         # plt.scatter(Rx2d[0][:],Rx[0][:,2::3],s=40,c='y')
         # plt.plot(np.r_[Tx2d[0][0],Rx2d[-1][-1,-1]],np.ones(2)*mesh.vectorNz[-1], color='k')
         ax2.set_title('Apparent Conductivity data')

SimPEG/Examples/EM_FDEM_1D_Inversion.py

@@ -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.Point_b(np.array([[rxOffset, 0., 1e-3]]), orientation='z', component='imag')
+    rxOffset=10. 
+    bzi = EM.FDEM.Rx(np.array([[rxOffset, 0., 1e-3]]), 'bzi')
 
     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.Problem3D_b(mesh, mapping=mapping)
+    prb = EM.FDEM.Problem_b(mesh, mapping=mapping)
 
     try:
         from pymatsolver import MumpsSolver

SimPEG/Examples/EM_Schenkel_Morrison_Casing.py

@@ -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.Problem3D_h(mesh, mapping=mapping)
+    problem = FDEM.Problem_h(mesh, mapping=mapping)
     problem.pair(survey)
 
     # ------------- Solve ---------------------------

SimPEG/Examples/EM_TDEM_1D_Inversion.py

@@ -42,10 +42,10 @@ def run(plotIt=True):
 
 
     rxOffset=1e-3
-    rx = EM.TDEM.Rx(np.array([[rxOffset, 0., 30]]), np.logspace(-5,-3, 31), 'bz')
-    src = EM.TDEM.Src.MagDipole([rx], loc=np.array([0., 0., 80]))
-    survey = EM.TDEM.Survey([src])
-    prb = EM.TDEM.Problem_b(mesh, mapping=mapping)
+    rx = EM.TDEM.RxTDEM(np.array([[rxOffset, 0., 30]]), np.logspace(-5,-3, 31), 'bz')
+    src = EM.TDEM.SrcTDEM_VMD_MVP([rx], np.array([0., 0., 80]))
+    survey = EM.TDEM.SurveyTDEM([src])
+    prb = EM.TDEM.ProblemTDEM_b(mesh, mapping=mapping)
 
     prb.Solver = SolverLU
     prb.timeSteps = [(1e-06, 20),(1e-05, 20), (0.0001, 20)]
@@ -53,9 +53,9 @@ def run(plotIt=True):
 
     # create observed data
     std = 0.05
-
+    
     survey.dobs = survey.makeSyntheticData(mtrue,std)
-    survey.std = std
+    survey.std = std 
     survey.eps = 1e-5*np.linalg.norm(survey.dobs)
 
     if plotIt:

SimPEG/Examples/Forward_BasicDirectCurrent.py

@@ -1,25 +1,22 @@
 from SimPEG import Mesh, Utils, np, SolverLU
 
+## 2D DC forward modeling example with Tensor and Curvilinear Meshes
+
 def run(plotIt=True):
-
-    """
-        Mesh: Basic Forward 2D DC Resistivity
-        =====================================
-
-        2D DC forward modeling example with Tensor and Curvilinear Meshes
-    """
-
     # Step1: Generate Tensor and Curvilinear Mesh
     sz = [40,40]
+    # Tensor Mesh
     tM = Mesh.TensorMesh(sz)
+    # Curvilinear Mesh
     rM = Mesh.CurvilinearMesh(Utils.meshutils.exampleLrmGrid(sz,'rotate'))
-
     # Step2: Direct Current (DC) operator
     def DCfun(mesh, pts):
         D = mesh.faceDiv
+        G = D.T
         sigma = 1e-2*np.ones(mesh.nC)
-        MsigI = mesh.getFaceInnerProduct(sigma, invProp=True, invMat=True)
-        A = -D*MsigI*D.T
+        Msigi = mesh.getFaceInnerProduct(1./sigma)
+        MsigI = Utils.sdInv(Msigi)
+        A = D*MsigI*G
         A[-1,-1] /= mesh.vol[-1] # Remove null space
         rhs = np.zeros(mesh.nC)
         txind = Utils.meshutils.closestPoints(mesh, pts)
@@ -40,17 +37,39 @@ def run(plotIt=True):
     if not plotIt: return
 
     import matplotlib.pyplot as plt
+    import matplotlib
+    from matplotlib.mlab import griddata
 
     #Step4: Making Figure
     fig, axes = plt.subplots(1,2,figsize=(12*1.2,4*1.2))
+    label = ["(a)", "(b)"]
+    opts = {}
     vmin, vmax = phitM.min(), phitM.max()
     dat = tM.plotImage(phitM, ax=axes[0], clim=(vmin, vmax), grid=True)
-    dat = rM.plotImage(phirM, ax=axes[1], clim=(vmin, vmax), grid=True)
+
+    #TODO: At the moment Curvilinear Mesh do not have plotimage
+
+    Xi = tM.gridCC[:,0].reshape(sz[0], sz[1], order='F')
+    Yi = tM.gridCC[:,1].reshape(sz[0], sz[1], order='F')
+    PHIrM = griddata(rM.gridCC[:,0], rM.gridCC[:,1], phirM, Xi, Yi, interp='linear')
+    axes[1].contourf(Xi, Yi, PHIrM, 100, vmin=vmin, vmax=vmax)
+
     cb = plt.colorbar(dat[0], ax=axes[0]); cb.set_label("Voltage (V)")
     cb = plt.colorbar(dat[0], ax=axes[1]); cb.set_label("Voltage (V)")
 
+    tM.plotGrid(ax=axes[0], **opts)
     axes[0].set_title('TensorMesh')
+    rM.plotGrid(ax=axes[1], **opts)
     axes[1].set_title('CurvilinearMesh')
+    for i in range(2):
+        axes[i].set_xlim(0.025, 0.975)
+        axes[i].set_ylim(0.025, 0.975)
+        axes[i].text(0., 1.0, label[i], fontsize=20)
+        if i==0:
+            axes[i].set_ylabel("y")
+        else:
+            axes[i].set_ylabel(" ")
+        axes[i].set_xlabel("x")
     plt.show()
 
 

SimPEG/Examples/Inversion_IRLS.py

@@ -1,7 +1,7 @@
 from SimPEG import *
 
 
-def run(N=100, plotIt=True):
+def run(N=200, plotIt=True):
     """
         Inversion: Linear Problem
         =========================
@@ -18,8 +18,6 @@ def run(N=100, plotIt=True):
     mesh = Mesh.TensorMesh([N])
 
     m0 = np.ones(mesh.nC) * 1e-4
-    mref = np.zeros(mesh.nC)
-
     nk = 10
     jk = np.linspace(1.,nk,nk)
     p = -2.
@@ -52,47 +50,57 @@ def run(N=100, plotIt=True):
     wr = np.sum(prob.G**2.,axis=0)**0.5
     wr = ( wr/np.max(wr) )
 
-#    reg = Regularization.Simple(mesh)
-#    reg.mref = mref
-#    reg.cell_weights = wr
-#
+    reg = Regularization.Simple(mesh)
+    reg.wght = wr
+
     dmis = DataMisfit.l2_DataMisfit(survey)
     dmis.Wd = 1./wd
-#
-#    opt = Optimization.ProjectedGNCG(maxIter=20,lower=-2.,upper=2., maxIterCG= 10, tolCG = 1e-4)
-#    invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
-#    invProb.curModel = m0
-#
-#    beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
-#    target = Directives.TargetMisfit()
-#
+
+    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
+    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)
-    reg.mref = mref
-    reg.cell_weights = wr
 
+#==============================================================================
+#     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)
-    eps_p = 5e-2
-    eps_q = 5e-2
-    norms   = [0., 0., 2., 2.]
+    reg.eps_p = 5e-2
+    reg.eps_q = 1e-2
+    reg.norms   = [0., 0., 2., 2.]
+    reg.wght = wr
 
-    opt = Optimization.ProjectedGNCG(maxIter=100 ,lower=-2.,upper=2., maxIterLS = 20, maxIterCG= 10, tolCG = 1e-3)
-    invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
-    update_Jacobi = Directives.Update_lin_PreCond()
-    IRLS = Directives.Update_IRLS( norms=norms,  eps_p=eps_p, eps_q=eps_q)
+    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=[IRLS,betaest,update_Jacobi])
+    inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS])
+
+    m0 = mrec
 
     # Run inversion
     mrec = inv.run(m0)
@@ -109,7 +117,7 @@ def run(N=100, plotIt=True):
         axes[0].set_title('Columns of matrix G')
 
         axes[1].plot(mesh.vectorCCx, mtrue, 'b-')
-        axes[1].plot(mesh.vectorCCx, reg.l2model, 'r-')
+        axes[1].plot(mesh.vectorCCx, ml2, 'r-')
         #axes[1].legend(('True Model', 'Recovered Model'))
         axes[1].set_ylim(-1.0,1.25)
 

SimPEG/Examples/Utils_surface2ind_topo.py

@@ -1,41 +0,0 @@
-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)

SimPEG/Examples/__init__.py

@@ -8,9 +8,9 @@ import EM_FDEM_Analytic_MagDipoleWholespace
 import EM_Schenkel_Morrison_Casing
 import EM_TDEM_1D_Inversion
 import FLOW_Richards_1D_Celia1990
+import Forward_BasicDirectCurrent
 import Inversion_IRLS
 import Inversion_Linear
-import Mesh_Basic_ForwardDC
 import Mesh_Basic_PlotImage
 import Mesh_Basic_Types
 import Mesh_Operators_CahnHilliard
@@ -20,9 +20,8 @@ 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", "Inversion_IRLS", "Inversion_Linear", "Mesh_Basic_ForwardDC", "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"]
+__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_Schenkel_Morrison_Casing", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Forward_BasicDirectCurrent", "Inversion_IRLS", "Inversion_Linear", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward"]
 
 ##### AUTOIMPORTS #####
 

SimPEG/Examples/simpegEMpaper_example_1.py

@@ -1,157 +0,0 @@
-from SimPEG import np, Mesh, Maps, Utils, DataMisfit, Regularization, Optimization, Inversion, InvProblem, Directives
-from SimPEG import SolverLU
-from SimPEG.EM import FDEM, TDEM, mu_0
-import matplotlib.pyplot as plt
-import matplotlib
-matplotlib.rcParams['font.size'] = 14
-
-def run(plotIt=True):
-    # Set up cylindrically symmeric mesh
-    cs, ncx, ncz, npad = 10., 15, 25, 13  # padded cyl mesh
-    hx = [(cs,ncx), (cs,npad,1.3)]
-    hz = [(cs,npad,-1.3), (cs,ncz), (cs,npad,1.3)]
-    mesh = Mesh.CylMesh([hx,1,hz], '00C')
-
-    # Conductivity model
-    layerz = np.r_[-200., -100.]
-    layer = (mesh.vectorCCz>=layerz[0]) & (mesh.vectorCCz<=layerz[1])
-    active = mesh.vectorCCz<0.
-    sig_half  = 1e-2  # Half-space conductivity
-    sig_air   = 1e-8  # Air conductivity
-    sig_layer = 5e-2  # Layer conductivity
-    sigma = np.ones(mesh.nCz)*sig_air
-    sigma[active] = sig_half
-    sigma[layer] = sig_layer
-
-    # Mapping
-    actMap = Maps.InjectActiveCells(mesh, active, np.log(1e-8), nC=mesh.nCz)
-    mapping = Maps.ExpMap(mesh) * Maps.SurjectVertical1D(mesh) * actMap
-    mtrue = np.log(sigma[active])
-
-    # FDEM problem & survey
-    rxlocs = Utils.ndgrid([np.r_[50.], np.r_[0], np.r_[0.]])
-    bzi = FDEM.Rx.Point_bSecondary(rxlocs, 'z', 'real')
-    bzr = FDEM.Rx.Point_bSecondary(rxlocs, 'z', 'imag')
-
-    freqs = np.logspace(2, 3, 5)
-    srcLoc = np.array([0., 0., 0.])
-
-    print 'min skin depth = ', 500./np.sqrt(freqs.max() * sig_half), 'max skin depth = ', 500./np.sqrt(freqs.min() * sig_half)
-    print 'max x ', mesh.vectorCCx.max(), 'min z ', mesh.vectorCCz.min(), 'max z ', mesh.vectorCCz.max()
-
-    srcList = []
-    [srcList.append(FDEM.Src.MagDipole([bzr, bzi],freq, srcLoc,orientation='Z')) for freq in freqs]
-
-    surveyFD = FDEM.Survey(srcList)
-    prbFD = FDEM.Problem3D_b(mesh, mapping=mapping)
-    prbFD.pair(surveyFD)
-    std = 0.03
-    surveyFD.makeSyntheticData(mtrue, std)
-    surveyFD.eps = np.linalg.norm(surveyFD.dtrue)*1e-5
-
-    # FDEM inversion
-    np.random.seed(1)
-    dmisfit = DataMisfit.l2_DataMisfit(surveyFD)
-    regMesh = Mesh.TensorMesh([mesh.hz[mapping.maps[-1].indActive]])
-    reg = Regularization.Simple(regMesh)
-    opt = Optimization.InexactGaussNewton(maxIterCG=10, maxIter=4)
-    invProb = InvProblem.BaseInvProblem(dmisfit, reg, opt)
-    # Inversion Directives
-    beta = Directives.BetaSchedule(coolingFactor=5, coolingRate=3)
-    # betaest = Directives.BetaEstimate_ByEig(beta0_ratio=10.)
-    invProb.beta = 1.
-    target = Directives.TargetMisfit()
-
-    inv = Inversion.BaseInversion(invProb, directiveList=[beta,target])
-    m0 = np.log(np.ones(mtrue.size)*sig_half)
-    reg.alpha_s = 5e-1
-    reg.alpha_x = 1.
-    prbFD.counter = opt.counter = Utils.Counter()
-    opt.LSshorten = 0.5
-    opt.tolG = 1e-10
-    opt.eps = 1e-10
-    opt.remember('xc')
-    moptFD = inv.run(m0)
-
-    # TDEM problem
-    times = np.logspace(-4, np.log10(2e-3), 10)
-    print 'min diffusion distance ', 1.28*np.sqrt(times.min()/(sig_half*mu_0)), 'max diffusion distance ', 1.28*np.sqrt(times.max()/(sig_half*mu_0))
-    rx = TDEM.Rx(rxlocs, times, 'bz')
-    src = TDEM.Src.MagDipole([rx], waveform=TDEM.Src.StepOffWaveform(), loc=srcLoc) # same src location as FDEM problem
-
-    surveyTD = TDEM.Survey([src])
-    prbTD = TDEM.Problem_b(mesh, mapping=mapping)
-    prbTD.timeSteps = [(5e-5, 10),(1e-4, 10),(5e-4, 10)]
-    prbTD.pair(surveyTD)
-    prbTD.Solver = SolverLU
-
-    std = 0.03
-    surveyTD.makeSyntheticData(mtrue, std)
-    surveyTD.std = std
-    surveyTD.eps = np.linalg.norm(surveyTD.dtrue)*1e-5
-
-    # TDEM inversion
-    dmisfit = DataMisfit.l2_DataMisfit(surveyTD)
-    regMesh = Mesh.TensorMesh([mesh.hz[mapping.maps[-1].indActive]])
-    reg = Regularization.Simple(regMesh)
-    opt = Optimization.InexactGaussNewton(maxIterCG=10, maxIter=4)
-    invProb = InvProblem.BaseInvProblem(dmisfit, reg, opt)
-
-    # Inversion Directives
-    beta = Directives.BetaSchedule(coolingFactor=5, coolingRate=3)
-    invProb.beta = 1.
-    # betaest = Directives.BetaEstimate_ByEig(beta0_ratio=1.)
-    target = Directives.TargetMisfit()
-
-    inv = Inversion.BaseInversion(invProb, directiveList=[beta, target])
-    m0 = np.log(np.ones(mtrue.size)*sig_half)
-    reg.alpha_s = 5e-1
-    reg.alpha_x = 1.
-    prbTD.counter = opt.counter = Utils.Counter()
-    opt.LSshorten = 0.5
-    opt.remember('xc')
-    moptTD = inv.run(m0)
-
-    if plotIt:
-        fig, ax = plt.subplots(1,1, figsize = (4, 6))
-        plt.semilogx(sigma[active], mesh.vectorCCz[active], 'k-', lw=2)
-        plt.semilogx(np.exp(moptFD), mesh.vectorCCz[active], 'ko', ms=3)
-        plt.semilogx(np.exp(moptTD), mesh.vectorCCz[active], 'k*')
-        ax.set_ylim(-1000, 0)
-        ax.set_xlim(5e-3, 1e-1)
-
-        ax.set_xlabel('Conductivity (S/m)', fontsize = 14)
-        ax.set_ylabel('Depth (m)', fontsize = 14)
-        ax.grid(color='k', alpha=0.5, linestyle='dashed', linewidth=0.5)
-        plt.legend(['True', 'Pred (FD)', 'Pred (TD)'], fontsize=13, loc=4)
-        plt.show()
-
-        fig = plt.figure(figsize = (10*1.3, 5*1.3))
-        ax2 = plt.subplot(122)
-        ax2.plot(times, surveyTD.dobs, 'k-', lw=2)
-        ax2.plot(times, surveyTD.dpred(moptTD), 'ko', ms=4)
-        ax2.set_xscale('log')
-        ax2.set_yscale('log')
-        ax2.set_xlim(times.min(), times.max())
-        ax1 = plt.subplot(121)
-        ax1.plot(freqs, -surveyFD.dobs[::2], 'k-', lw=2)
-        ax1.plot(freqs, -surveyFD.dobs[1::2], 'k--', lw=2)
-        dpredFD = surveyFD.dpred(moptTD)
-        ax1.plot(freqs, -dpredFD[::2], 'ko', ms=4)
-        ax1.plot(freqs, -dpredFD[1::2], 'k+', markeredgewidth=2., ms=10)
-        ax1.set_xscale('log')
-        ax1.set_yscale('log')
-        ax2.set_xlabel('Time (s)', fontsize = 14)
-        ax1.set_xlabel('Frequency (Hz)', fontsize = 14)
-        ax1.set_ylabel('Vertical magnetic field (T)', fontsize = 14)
-        ax2.grid(True,which='minor')
-        ax1.grid(True,which='minor')
-        ax2.set_title("(b) TD observed vs. predicted", fontsize = 14)
-        ax1.set_title("(a) FD observed vs. predicted", fontsize = 14)
-        ax2.legend(("Obs", "Pred"), fontsize = 12)
-        ax1.legend(("Obs", "Pred (real)", "Pred (imag)"), fontsize = 12, loc=3)
-        ax1.set_xlim(freqs.max(), freqs.min())
-        plt.show()
-
-if __name__ == '__main__':
-    run()

SimPEG/MT/BaseMT.py

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

SimPEG/Maps.py

@@ -533,6 +533,83 @@ class ActiveCells(InjectActiveCells):
             FutureWarning)
         InjectActiveCells.__init__(self, mesh, indActive, valInactive, nC)
 
+class InjectActiveCellsTopo(IdentityMap):
+    """
+        Active model parameters. Extend for cells on topography to air cell (only works for tensor mesh)
+
+    """
+
+    indActive   = None #: Active Cells
+    valInactive = None #: Values of inactive Cells
+    nC          = None #: Number of cells in the full model
+
+    def __init__(self, mesh, indActive, nC=None):
+        self.mesh  = mesh
+
+        self.nC = nC or mesh.nC
+
+        if indActive.dtype is not bool:
+            z = np.zeros(self.nC,dtype=bool)
+            z[indActive] = True
+            indActive = z
+        self.indActive = indActive
+
+        self.indInactive = np.logical_not(indActive)
+        inds = np.nonzero(self.indActive)[0]
+        self.P = sp.csr_matrix((np.ones(inds.size),(inds, range(inds.size))), shape=(self.nC, self.nP))
+
+    @property
+    def shape(self):
+        return (self.nC, self.nP)
+
+    @property
+    def nP(self):
+        """Number of parameters in the model."""
+        return self.indActive.sum()
+
+    def _transform(self, m):
+        val_temp = np.zeros(self.mesh.nC)
+        val_temp[self.indActive] = m
+        valInactive = np.zeros(self.mesh.nC)
+        #1D
+        if self.mesh.dim == 1:
+            z_temp = self.mesh.gridCC
+            val_temp[~self.indActive] = val_temp[np.argmax(z_temp[self.indActive])]
+        #2D
+        elif self.mesh.dim == 2:
+            act_temp = self.indActive.reshape((self.mesh.nCx, self.mesh.nCy), order = 'F')
+            val_temp = val_temp.reshape((self.mesh.nCx, self.mesh.nCy), order = 'F')
+            y_temp = self.mesh.gridCC[:,1].reshape((self.mesh.nCx, self.mesh.nCy), order = 'F')
+            for i in range(self.mesh.nCx):
+                act_tempx = act_temp[i,:] == 1
+                val_temp[i,~act_tempx] = val_temp[i,np.argmax(y_temp[i,act_tempx])]
+            valInactive[~self.indActive] = Utils.mkvc(val_temp)[~self.indActive]
+        #3D
+        elif self.mesh.dim == 3:
+            act_temp = self.indActive.reshape((self.mesh.nCx*self.mesh.nCy, self.mesh.nCz), order = 'F')
+            val_temp = val_temp.reshape((self.mesh.nCx*self.mesh.nCy, self.mesh.nCz), order = 'F')
+            z_temp = self.mesh.gridCC[:,2].reshape((self.mesh.nCx*self.mesh.nCy, self.mesh.nCz), order = 'F')
+            for i in range(self.mesh.nCx*self.mesh.nCy):
+                act_tempxy = act_temp[i,:] == 1
+                val_temp[i,~act_tempxy] = val_temp[i,np.argmax(z_temp[i,act_tempxy])]
+            valInactive[~self.indActive] = Utils.mkvc(val_temp)[~self.indActive]
+
+        self.valInactive = valInactive
+
+        return self.P*m + self.valInactive
+
+    def inverse(self, D):
+        return self.P.T*D
+
+    def deriv(self, m):
+        return self.P
+
+class ActiveCellsTopo(InjectActiveCellsTopo):
+    def __init__(self, mesh, indActive, valInactive, nC=None):
+        warnings.warn(
+            "`ActiveCellsTopo` is deprecated and will be removed in future versions. Use `InjectActiveCellsTopo` instead",
+            FutureWarning)
+        InjectActiveCellsTopo.__init__(self, mesh, indActive, valInactive, nC)
 
 class Weighting(IdentityMap):
     """

SimPEG/Mesh/CurvilinearMesh.py

@@ -2,7 +2,6 @@ from SimPEG import Utils, np
 from BaseMesh import BaseRectangularMesh
 from DiffOperators import DiffOperators
 from InnerProducts import InnerProducts
-from View import CurvView
 
 # Some helper functions.
 length2D = lambda x: (x[:, 0]**2 + x[:, 1]**2)**0.5
@@ -11,7 +10,7 @@ normalize2D = lambda x: x/np.kron(np.ones((1, 2)), Utils.mkvc(length2D(x), 2))
 normalize3D = lambda x: x/np.kron(np.ones((1, 3)), Utils.mkvc(length3D(x), 2))
 
 
-class CurvilinearMesh(BaseRectangularMesh, DiffOperators, InnerProducts, CurvView):
+class CurvilinearMesh(BaseRectangularMesh, DiffOperators, InnerProducts):
     """
     CurvilinearMesh is a mesh class that deals with curvilinear meshes.
 
@@ -331,6 +330,102 @@ class CurvilinearMesh(BaseRectangularMesh, DiffOperators, InnerProducts, CurvVie
 
 
 
+    #############################################
+    #            Plotting Functions             #
+    #############################################
+
+    def plotGrid(self, ax=None, nodes=False, faces=False, centers=False, edges=False, lines=True,  showIt=False):
+        """Plot the nodal, cell-centered and staggered grids for 1,2 and 3 dimensions.
+
+
+        .. plot::
+            :include-source:
+
+            from SimPEG import Mesh, Utils
+            X, Y = Utils.exampleLrmGrid([3,3],'rotate')
+            M = Mesh.CurvilinearMesh([X, Y])
+            M.plotGrid(showIt=True)
+
+        """
+        import matplotlib.pyplot as plt
+        import matplotlib
+        from mpl_toolkits.mplot3d import Axes3D
+        mkvc = Utils.mkvc
+
+        axOpts = {'projection':'3d'} if self.dim == 3 else {}
+        if ax is None: ax = plt.subplot(111, **axOpts)
+
+        NN = self.r(self.gridN, 'N', 'N', 'M')
+        if self.dim == 2:
+
+            if lines:
+                X1 = np.c_[mkvc(NN[0][:-1, :]), mkvc(NN[0][1:, :]), mkvc(NN[0][:-1, :])*np.nan].flatten()
+                Y1 = np.c_[mkvc(NN[1][:-1, :]), mkvc(NN[1][1:, :]), mkvc(NN[1][:-1, :])*np.nan].flatten()
+
+                X2 = np.c_[mkvc(NN[0][:, :-1]), mkvc(NN[0][:, 1:]), mkvc(NN[0][:, :-1])*np.nan].flatten()
+                Y2 = np.c_[mkvc(NN[1][:, :-1]), mkvc(NN[1][:, 1:]), mkvc(NN[1][:, :-1])*np.nan].flatten()
+
+                X = np.r_[X1, X2]
+                Y = np.r_[Y1, Y2]
+
+                ax.plot(X, Y, 'b-')
+            if centers:
+                ax.plot(self.gridCC[:,0],self.gridCC[:,1],'ro')
+
+            # Nx = self.r(self.normals, 'F', 'Fx', 'V')
+            # Ny = self.r(self.normals, 'F', 'Fy', 'V')
+            # Tx = self.r(self.tangents, 'E', 'Ex', 'V')
+            # Ty = self.r(self.tangents, 'E', 'Ey', 'V')
+
+            # ax.plot(self.gridN[:, 0], self.gridN[:, 1], 'bo')
+
+            # nX = np.c_[self.gridFx[:, 0], self.gridFx[:, 0] + Nx[0]*length, self.gridFx[:, 0]*np.nan].flatten()
+            # nY = np.c_[self.gridFx[:, 1], self.gridFx[:, 1] + Nx[1]*length, self.gridFx[:, 1]*np.nan].flatten()
+            # ax.plot(self.gridFx[:, 0], self.gridFx[:, 1], 'rs')
+            # ax.plot(nX, nY, 'r-')
+
+            # nX = np.c_[self.gridFy[:, 0], self.gridFy[:, 0] + Ny[0]*length, self.gridFy[:, 0]*np.nan].flatten()
+            # nY = np.c_[self.gridFy[:, 1], self.gridFy[:, 1] + Ny[1]*length, self.gridFy[:, 1]*np.nan].flatten()
+            # #ax.plot(self.gridFy[:, 0], self.gridFy[:, 1], 'gs')
+            # ax.plot(nX, nY, 'g-')
+
+            # tX = np.c_[self.gridEx[:, 0], self.gridEx[:, 0] + Tx[0]*length, self.gridEx[:, 0]*np.nan].flatten()
+            # tY = np.c_[self.gridEx[:, 1], self.gridEx[:, 1] + Tx[1]*length, self.gridEx[:, 1]*np.nan].flatten()
+            # ax.plot(self.gridEx[:, 0], self.gridEx[:, 1], 'r^')
+            # ax.plot(tX, tY, 'r-')
+
+            # nX = np.c_[self.gridEy[:, 0], self.gridEy[:, 0] + Ty[0]*length, self.gridEy[:, 0]*np.nan].flatten()
+            # nY = np.c_[self.gridEy[:, 1], self.gridEy[:, 1] + Ty[1]*length, self.gridEy[:, 1]*np.nan].flatten()
+            # #ax.plot(self.gridEy[:, 0], self.gridEy[:, 1], 'g^')
+            # ax.plot(nX, nY, 'g-')
+
+        elif self.dim == 3:
+            X1 = np.c_[mkvc(NN[0][:-1, :, :]), mkvc(NN[0][1:, :, :]), mkvc(NN[0][:-1, :, :])*np.nan].flatten()
+            Y1 = np.c_[mkvc(NN[1][:-1, :, :]), mkvc(NN[1][1:, :, :]), mkvc(NN[1][:-1, :, :])*np.nan].flatten()
+            Z1 = np.c_[mkvc(NN[2][:-1, :, :]), mkvc(NN[2][1:, :, :]), mkvc(NN[2][:-1, :, :])*np.nan].flatten()
+
+            X2 = np.c_[mkvc(NN[0][:, :-1, :]), mkvc(NN[0][:, 1:, :]), mkvc(NN[0][:, :-1, :])*np.nan].flatten()
+            Y2 = np.c_[mkvc(NN[1][:, :-1, :]), mkvc(NN[1][:, 1:, :]), mkvc(NN[1][:, :-1, :])*np.nan].flatten()
+            Z2 = np.c_[mkvc(NN[2][:, :-1, :]), mkvc(NN[2][:, 1:, :]), mkvc(NN[2][:, :-1, :])*np.nan].flatten()
+
+            X3 = np.c_[mkvc(NN[0][:, :, :-1]), mkvc(NN[0][:, :, 1:]), mkvc(NN[0][:, :, :-1])*np.nan].flatten()
+            Y3 = np.c_[mkvc(NN[1][:, :, :-1]), mkvc(NN[1][:, :, 1:]), mkvc(NN[1][:, :, :-1])*np.nan].flatten()
+            Z3 = np.c_[mkvc(NN[2][:, :, :-1]), mkvc(NN[2][:, :, 1:]), mkvc(NN[2][:, :, :-1])*np.nan].flatten()
+
+            X = np.r_[X1, X2, X3]
+            Y = np.r_[Y1, Y2, Y3]
+            Z = np.r_[Z1, Z2, Z3]
+
+            ax.plot(X, Y, 'b', zs=Z)
+            ax.set_zlabel('x3')
+
+        ax.grid(True)
+        ax.set_xlabel('x1')
+        ax.set_ylabel('x2')
+
+        if showIt: plt.show()
+
+
 if __name__ == '__main__':
     nc = 5
     h1 = np.cumsum(np.r_[0, np.ones(nc)/(nc)])

SimPEG/Mesh/CylMesh.py

@@ -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', locTypeTo=None):
+    def getInterpolationMatCartMesh(self, Mrect, locType='CC'):
         """
             Takes a cartesian mesh and returns a projection to translate onto the cartesian grid.
         """
@@ -338,22 +338,19 @@ 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', locTypeTo=locTypeTo+'x')
-            Y = self.getInterpolationMatCartMesh(Mrect, locType='Fy', locTypeTo=locTypeTo+'y')
-            Z = self.getInterpolationMatCartMesh(Mrect, locType='Fz', locTypeTo=locTypeTo+'z')
+            X = self.getInterpolationMatCartMesh(Mrect, locType='Fx')
+            Y = self.getInterpolationMatCartMesh(Mrect, locType='Fy')
+            Z = self.getInterpolationMatCartMesh(Mrect, locType='Fz')
             return sp.vstack((X,Y,Z))
         if locType == 'E':
-            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)
+            X = self.getInterpolationMatCartMesh(Mrect, locType='Ex')
+            Y = self.getInterpolationMatCartMesh(Mrect, locType='Ey')
+            Z = spzeros(Mrect.nEz, self.nE)
             return sp.vstack((X,Y,Z))
 
-        grid = getattr(Mrect, 'grid' + locTypeTo)
+        grid = getattr(Mrect, 'grid' + locType)
         # 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
@@ -369,7 +366,7 @@ 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:,:],
-                    }[locTypeTo]
+                    }[locType]
             if 'F' in locType:
                 normals = np.c_[np.cos(theta), np.sin(theta), np.zeros(theta.size)]
                 proj = ( normals * dotMe ).sum(axis=1)

SimPEG/Mesh/DiffOperators.py

@@ -584,67 +584,7 @@ class DiffOperators(object):
 
         return Pbc, Pin, Pout
 
-    def getBCProjWF_simple(self, discretization='CC'):
-        """
 
-        The weak form boundary condition projection matrices
-        when mixed boundary condition is used
-
-
-        """
-
-        if discretization is not 'CC':
-            raise NotImplementedError('Boundary conditions only implemented for CC discretization.')
-
-        def projBC(n):
-            ij = ([0,n], [0,1])
-            vals = [0,0]
-            vals[0] = 1
-            vals[1] = 1
-            return sp.csr_matrix((vals, ij), shape=(n+1,2))
-
-        def projDirichlet(n, bc):
-            bc = checkBC(bc)
-            ij = ([0,n], [0,1])
-            vals = [0,0]
-            if(bc[0] == 'dirichlet'):
-                vals[0] = -1
-            if(bc[1] == 'dirichlet'):
-                vals[1] = 1
-            return sp.csr_matrix((vals, ij), shape=(n+1,2))
-
-        BC = [['dirichlet','dirichlet'],['dirichlet','dirichlet'],['dirichlet','dirichlet']]
-        n = self.vnC
-        indF = self.faceBoundaryInd
-        if(self.dim == 1):
-            Pbc = projDirichlet(n[0], BC[0])
-            B = projBC(n[0])
-            indF = indF[0] | indF[1]
-            Pbc = Pbc*sdiag(self.area[indF])
-
-        elif(self.dim == 2):
-            Pbc1 = sp.kron(speye(n[1]), projDirichlet(n[0], BC[0]))
-            Pbc2 = sp.kron(projDirichlet(n[1], BC[1]), speye(n[0]))
-            Pbc = sp.block_diag((Pbc1, Pbc2), format="csr")
-            B1 = sp.kron(speye(n[1]), projBC(n[0]))
-            B2 = sp.kron(projBC(n[1]), speye(n[0]))
-            B = sp.block_diag((B1, B2), format="csr")
-            indF = np.r_[(indF[0] | indF[1]), (indF[2] | indF[3])]
-            Pbc = Pbc*sdiag(self.area[indF])
-
-        elif(self.dim == 3):
-            Pbc1 = kron3(speye(n[2]), speye(n[1]), projDirichlet(n[0], BC[0]))
-            Pbc2 = kron3(speye(n[2]), projDirichlet(n[1], BC[1]), speye(n[0]))
-            Pbc3 = kron3(projDirichlet(n[2], BC[2]), speye(n[1]), speye(n[0]))
-            Pbc = sp.block_diag((Pbc1, Pbc2, Pbc3), format="csr")
-            B1 = kron3(speye(n[2]), speye(n[1]), projBC(n[0]))
-            B2 = kron3(speye(n[2]), projBC(n[1]), speye(n[0]))
-            B3 = kron3(projBC(n[2]), speye(n[1]), speye(n[0]))
-            B = sp.block_diag((B1, B2, B3), format="csr")
-            indF = np.r_[(indF[0] | indF[1]), (indF[2] | indF[3]), (indF[4] | indF[5])]
-            Pbc = Pbc*sdiag(self.area[indF])
-
-        return Pbc, B.T
     # --------------- Averaging ---------------------
 
     @property

SimPEG/Mesh/View.py

@@ -218,7 +218,7 @@ class TensorView(object):
             return out
         viewOpts = ['real','imag','abs','vec']
         normalOpts = ['X', 'Y', 'Z']
-        vTypeOpts = ['CC', 'CCv','N','F','E','Fx','Fy','Fz','E','Ex','Ey','Ez']
+        vTypeOpts = ['CC', 'CCv','F','E','Fx','Fy','Fz','E','Ex','Ey','Ez']
 
         # Some user error checking
         assert vType in vTypeOpts, "vType must be in ['%s']" % "','".join(vTypeOpts)
@@ -552,8 +552,7 @@ class CurvView(object):
     def __init__(self):
         pass
 
-
-    def plotGrid(self, ax=None, nodes=False, faces=False, centers=False, edges=False, lines=True,  showIt=False):
+    def plotGrid(self, length=0.05, showIt=False):
         """Plot the nodal, cell-centered and staggered grids for 1,2 and 3 dimensions.
 
 
@@ -561,63 +560,60 @@ class CurvView(object):
             :include-source:
 
             from SimPEG import Mesh, Utils
-            X, Y = Utils.exampleLrmGrid([3,3],'rotate')
+            X, Y = Utils.exampleCurvGird([3,3],'rotate')
             M = Mesh.CurvilinearMesh([X, Y])
             M.plotGrid(showIt=True)
 
         """
-        import matplotlib.pyplot as plt
-        import matplotlib
-        from mpl_toolkits.mplot3d import Axes3D
-
-        axOpts = {'projection':'3d'} if self.dim == 3 else {}
-        if ax is None: ax = plt.subplot(111, **axOpts)
-
         NN = self.r(self.gridN, 'N', 'N', 'M')
         if self.dim == 2:
+            fig = plt.figure(2)
+            fig.clf()
+            ax = plt.subplot(111)
+            X1 = np.c_[mkvc(NN[0][:-1, :]), mkvc(NN[0][1:, :]), mkvc(NN[0][:-1, :])*np.nan].flatten()
+            Y1 = np.c_[mkvc(NN[1][:-1, :]), mkvc(NN[1][1:, :]), mkvc(NN[1][:-1, :])*np.nan].flatten()
 
-            if lines:
-                X1 = np.c_[mkvc(NN[0][:-1, :]), mkvc(NN[0][1:, :]), mkvc(NN[0][:-1, :])*np.nan].flatten()
-                Y1 = np.c_[mkvc(NN[1][:-1, :]), mkvc(NN[1][1:, :]), mkvc(NN[1][:-1, :])*np.nan].flatten()
+            X2 = np.c_[mkvc(NN[0][:, :-1]), mkvc(NN[0][:, 1:]), mkvc(NN[0][:, :-1])*np.nan].flatten()
+            Y2 = np.c_[mkvc(NN[1][:, :-1]), mkvc(NN[1][:, 1:]), mkvc(NN[1][:, :-1])*np.nan].flatten()
 
-                X2 = np.c_[mkvc(NN[0][:, :-1]), mkvc(NN[0][:, 1:]), mkvc(NN[0][:, :-1])*np.nan].flatten()
-                Y2 = np.c_[mkvc(NN[1][:, :-1]), mkvc(NN[1][:, 1:]), mkvc(NN[1][:, :-1])*np.nan].flatten()
+            X = np.r_[X1, X2]
+            Y = np.r_[Y1, Y2]
 
-                X = np.r_[X1, X2]
-                Y = np.r_[Y1, Y2]
+            plt.plot(X, Y)
 
-                ax.plot(X, Y, 'b-')
-            if centers:
-                ax.plot(self.gridCC[:,0],self.gridCC[:,1],'ro')
+            plt.hold(True)
+            Nx = self.r(self.normals, 'F', 'Fx', 'V')
+            Ny = self.r(self.normals, 'F', 'Fy', 'V')
+            Tx = self.r(self.tangents, 'E', 'Ex', 'V')
+            Ty = self.r(self.tangents, 'E', 'Ey', 'V')
 
-            # Nx = self.r(self.normals, 'F', 'Fx', 'V')
-            # Ny = self.r(self.normals, 'F', 'Fy', 'V')
-            # Tx = self.r(self.tangents, 'E', 'Ex', 'V')
-            # Ty = self.r(self.tangents, 'E', 'Ey', 'V')
+            plt.plot(self.gridN[:, 0], self.gridN[:, 1], 'bo')
 
-            # ax.plot(self.gridN[:, 0], self.gridN[:, 1], 'bo')
+            nX = np.c_[self.gridFx[:, 0], self.gridFx[:, 0] + Nx[0]*length, self.gridFx[:, 0]*np.nan].flatten()
+            nY = np.c_[self.gridFx[:, 1], self.gridFx[:, 1] + Nx[1]*length, self.gridFx[:, 1]*np.nan].flatten()
+            plt.plot(self.gridFx[:, 0], self.gridFx[:, 1], 'rs')
+            plt.plot(nX, nY, 'r-')
 
-            # nX = np.c_[self.gridFx[:, 0], self.gridFx[:, 0] + Nx[0]*length, self.gridFx[:, 0]*np.nan].flatten()
-            # nY = np.c_[self.gridFx[:, 1], self.gridFx[:, 1] + Nx[1]*length, self.gridFx[:, 1]*np.nan].flatten()
-            # ax.plot(self.gridFx[:, 0], self.gridFx[:, 1], 'rs')
-            # ax.plot(nX, nY, 'r-')
+            nX = np.c_[self.gridFy[:, 0], self.gridFy[:, 0] + Ny[0]*length, self.gridFy[:, 0]*np.nan].flatten()
+            nY = np.c_[self.gridFy[:, 1], self.gridFy[:, 1] + Ny[1]*length, self.gridFy[:, 1]*np.nan].flatten()
+            #plt.plot(self.gridFy[:, 0], self.gridFy[:, 1], 'gs')
+            plt.plot(nX, nY, 'g-')
 
-            # nX = np.c_[self.gridFy[:, 0], self.gridFy[:, 0] + Ny[0]*length, self.gridFy[:, 0]*np.nan].flatten()
-            # nY = np.c_[self.gridFy[:, 1], self.gridFy[:, 1] + Ny[1]*length, self.gridFy[:, 1]*np.nan].flatten()
-            # #ax.plot(self.gridFy[:, 0], self.gridFy[:, 1], 'gs')
-            # ax.plot(nX, nY, 'g-')
+            tX = np.c_[self.gridEx[:, 0], self.gridEx[:, 0] + Tx[0]*length, self.gridEx[:, 0]*np.nan].flatten()
+            tY = np.c_[self.gridEx[:, 1], self.gridEx[:, 1] + Tx[1]*length, self.gridEx[:, 1]*np.nan].flatten()
+            plt.plot(self.gridEx[:, 0], self.gridEx[:, 1], 'r^')
+            plt.plot(tX, tY, 'r-')
 
-            # tX = np.c_[self.gridEx[:, 0], self.gridEx[:, 0] + Tx[0]*length, self.gridEx[:, 0]*np.nan].flatten()
-            # tY = np.c_[self.gridEx[:, 1], self.gridEx[:, 1] + Tx[1]*length, self.gridEx[:, 1]*np.nan].flatten()
-            # ax.plot(self.gridEx[:, 0], self.gridEx[:, 1], 'r^')
-            # ax.plot(tX, tY, 'r-')
-
-            # nX = np.c_[self.gridEy[:, 0], self.gridEy[:, 0] + Ty[0]*length, self.gridEy[:, 0]*np.nan].flatten()
-            # nY = np.c_[self.gridEy[:, 1], self.gridEy[:, 1] + Ty[1]*length, self.gridEy[:, 1]*np.nan].flatten()
-            # #ax.plot(self.gridEy[:, 0], self.gridEy[:, 1], 'g^')
-            # ax.plot(nX, nY, 'g-')
+            nX = np.c_[self.gridEy[:, 0], self.gridEy[:, 0] + Ty[0]*length, self.gridEy[:, 0]*np.nan].flatten()
+            nY = np.c_[self.gridEy[:, 1], self.gridEy[:, 1] + Ty[1]*length, self.gridEy[:, 1]*np.nan].flatten()
+            #plt.plot(self.gridEy[:, 0], self.gridEy[:, 1], 'g^')
+            plt.plot(nX, nY, 'g-')
+            plt.axis('equal')
 
         elif self.dim == 3:
+            fig = plt.figure(3)
+            fig.clf()
+            ax = fig.add_subplot(111, projection='3d')
             X1 = np.c_[mkvc(NN[0][:-1, :, :]), mkvc(NN[0][1:, :, :]), mkvc(NN[0][:-1, :, :])*np.nan].flatten()
             Y1 = np.c_[mkvc(NN[1][:-1, :, :]), mkvc(NN[1][1:, :, :]), mkvc(NN[1][:-1, :, :])*np.nan].flatten()
             Z1 = np.c_[mkvc(NN[2][:-1, :, :]), mkvc(NN[2][1:, :, :]), mkvc(NN[2][:-1, :, :])*np.nan].flatten()
@@ -634,50 +630,16 @@ class CurvView(object):
             Y = np.r_[Y1, Y2, Y3]
             Z = np.r_[Z1, Z2, Z3]
 
-            ax.plot(X, Y, 'b', zs=Z)
+            plt.plot(X, Y, 'b', zs=Z)
             ax.set_zlabel('x3')
 
         ax.grid(True)
+        ax.hold(False)
         ax.set_xlabel('x1')
         ax.set_ylabel('x2')
 
         if showIt: plt.show()
 
-    def plotImage(self, I, ax=None, showIt=False, grid=False, clim=None):
-        if self.dim == 3: raise NotImplementedError('This is not yet done!')
-
-        import matplotlib.pyplot as plt
-        import matplotlib
-        from mpl_toolkits.mplot3d import Axes3D
-        import matplotlib.colors as colors
-        import matplotlib.cm as cmx
-
-        if ax is None: ax = plt.subplot(111)
-        jet = cm = plt.get_cmap('jet')
-        cNorm  = colors.Normalize(
-            vmin=I.min() if clim is None else clim[0],
-            vmax=I.max() if clim is None else clim[1])
-
-        scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)
-        # ax.set_xlim((self.x0[0], self.h[0].sum()))
-        # ax.set_ylim((self.x0[1], self.h[1].sum()))
-
-        Nx = self.r(self.gridN[:,0],'N','N','M')
-        Ny = self.r(self.gridN[:,1],'N','N','M')
-        cell = self.r(I,'CC','CC','M')
-
-        for ii in range(self.nCx):
-            for jj in range(self.nCy):
-                I = [ii,ii+1,ii+1,ii]
-                J = [jj,jj,jj+1,jj+1]
-                ax.add_patch(plt.Polygon(np.c_[Nx[I,J],Ny[I,J]], facecolor=scalarMap.to_rgba(cell[ii,jj]), edgecolor='k' if grid else 'none'))
-
-        scalarMap._A = []  # http://stackoverflow.com/questions/8342549/matplotlib-add-colorbar-to-a-sequence-of-line-plots
-        ax.set_xlabel('x')
-        ax.set_ylabel('y')
-        if showIt: plt.show()
-        return [scalarMap]
-
 
 if __name__ == '__main__':
     from SimPEG import *

SimPEG/Optimization.py

@@ -1008,4 +1008,4 @@ class ProjectedGNCG(BFGS, Minimize, Remember):
             indx = ((self.xc<=self.lower) & (delx < 0)) | ((self.xc>=self.upper) & (delx > 0))
             delx[indx] = 0.
 
-            return delx
+            return delx

SimPEG/PropMaps.py

@@ -74,7 +74,7 @@ class Property(object):
                 if linkedMap is None:
                     return None
                 linkMap = linkMapClass(None) * linkedMap
-                m = getattr(self, '%sModel'%linkName)
+                m = getattr(self, '%s'%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):

SimPEG/Regularization.py

@@ -1,6 +1,4 @@
-import Utils, Maps, Mesh
-import numpy as np
-import scipy.sparse as sp
+import Utils, Maps, Mesh, numpy as np, scipy.sparse as sp
 
 class RegularizationMesh(object):
     """
@@ -313,9 +311,6 @@ class BaseRegularization(object):
             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)
-
         self.regmesh = RegularizationMesh(mesh,indActive)
         self.mapping = mapping or self.mapPair(mesh)
         self.mapping._assertMatchesPair(self.mapPair)
@@ -405,238 +400,7 @@ class BaseRegularization(object):
 
         return mD.T * ( self.W.T * ( self.W * ( mD * v) ) )
 
-class Simple(BaseRegularization):
-    """
-    Simple regularization that does not include length scales in the derivatives.
-    """
-
-    mrefInSmooth = False  #: include mref in the smoothness?
-    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")
-    cell_weights = 1.
-
-    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
-        BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
-
-        if isinstance(self.cell_weights,float):
-            self.cell_weights = np.ones(self.regmesh.nC) * self.cell_weights
-
-    @property
-    def Wsmall(self):
-        """Regularization matrix Wsmall"""
-        if getattr(self,'_Wsmall', None) is None:
-            self._Wsmall = Utils.sdiag((self.alpha_s*self.cell_weights)**0.5)
-        return self._Wsmall
-
-    @property
-    def Wx(self):
-        """Regularization matrix Wx"""
-        if getattr(self, '_Wx', None) is None:
-            self._Wx = Utils.sdiag((self.alpha_x * (self.regmesh.aveCC2Fx*self.cell_weights))**0.5)*self.regmesh.cellDiffxStencil
-        return self._Wx
-
-    @property
-    def Wy(self):
-        """Regularization matrix Wy"""
-        if getattr(self, '_Wy', None) is None:
-            self._Wy = Utils.sdiag((self.alpha_y * (self.regmesh.aveCC2Fy*self.cell_weights))**0.5)*self.regmesh.cellDiffyStencil
-        return self._Wy
-
-    @property
-    def Wz(self):
-        """Regularization matrix Wz"""
-        if getattr(self, '_Wz', None) is None:
-            self._Wz = Utils.sdiag((self.alpha_z * (self.regmesh.aveCC2Fz*self.cell_weights))**0.5)*self.regmesh.cellDiffzStencil
-        return self._Wz
-
-#    @property
-#    def Wsmooth(self):
-#        """Full smoothness regularization matrix W"""
-#        print 'wtf why are we using Wsmooth'
-#        raise NotImplementedError
-#        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"""
-#        print 'wtf why are we using W'
-#        if getattr(self, '_W', None) is None:
-#            wlist = (self.Wsmall, self.Wx)
-#            if self.regmesh.dim > 1:
-#                wlist += (self.Wy,)
-#            if self.regmesh.dim > 2:
-#                wlist += (self.Wz,)
-#            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 _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 _evalSmall2Deriv(self, m, v = None):
-        rDeriv = self.Wsmall * ( self.mapping.deriv(m - self.mref) )
-        if v is not None:
-            return rDeriv.T * (rDeriv * v)
-        return rDeriv.T * rDeriv
-
-    @Utils.timeIt
-    def _evalSmoothx(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wx * ( self.mapping * (m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wx * ( self.mapping * (m) )
-        return 0.5 * r.dot(r)
-
-    @Utils.timeIt
-    def _evalSmoothy(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wy * ( self.mapping * (m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wy * ( self.mapping * (m) )
-        return 0.5 * r.dot(r)
-
-    @Utils.timeIt
-    def _evalSmoothz(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wz * ( self.mapping * (m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wz * ( self.mapping * (m) )
-        return 0.5 * r.dot(r)
-
-    @Utils.timeIt
-    def _evalSmooth(self, m):
-        phiSmooth = self._evalSmoothx(m)
-        if self.regmesh.dim > 1:
-            phiSmooth += self._evalSmoothy(m)
-        if self.regmesh.dim > 2:
-            phiSmooth += self._evalSmoothz(m)
-        return phiSmooth
-
-    @Utils.timeIt
-    def _evalSmoothxDeriv(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wx * ( self.mapping * ( m - self.mref ) )
-            return r.T * ( self.Wx * self.mapping.deriv(m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wx * ( self.mapping * m )
-            return r.T * ( self.Wx * self.mapping.deriv(m) )
-
-    @Utils.timeIt
-    def _evalSmoothx2Deriv(self, m, v=None):
-        if self.mrefInSmooth == True:
-            rDeriv = self.Wx * ( self.mapping.deriv( m - self.mref ) )
-        elif self.mrefInSmooth == False:
-            rDeriv = self.Wx * ( self.mapping.deriv(m) )
-
-        if v is not None:
-            return rDeriv.T * ( rDeriv * v )
-        return rDeriv.T * rDeriv
-
-    @Utils.timeIt
-    def _evalSmoothyDeriv(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wy * ( self.mapping * ( m - self.mref ) )
-            return r.T * ( self.Wy * self.mapping.deriv(m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wy * ( self.mapping * m )
-            return r.T * ( self.Wy * self.mapping.deriv(m) )
-
-    @Utils.timeIt
-    def _evalSmoothy2Deriv(self, m, v=None):
-        if self.mrefInSmooth == True:
-            rDeriv = self.Wy * ( self.mapping.deriv( m - self.mref ) )
-        elif self.mrefInSmooth == False:
-            rDeriv = self.Wy * ( self.mapping.deriv(m) )
-
-        if v is not None:
-            return rDeriv.T * ( rDeriv * v )
-        return rDeriv.T * rDeriv
-
-    @Utils.timeIt
-    def _evalSmoothzDeriv(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wz * ( self.mapping * ( m - self.mref ) )
-            return r.T * ( self.Wz * self.mapping.deriv(m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wz * ( self.mapping * m )
-            return r.T * ( self.Wz * self.mapping.deriv(m) )
-
-    @Utils.timeIt
-    def _evalSmoothz2Deriv(self, m, v=None):
-        if self.mrefInSmooth == True:
-            rDeriv = self.Wz * ( self.mapping.deriv( m - self.mref ) )
-        elif self.mrefInSmooth == False:
-            rDeriv = self.Wz * ( self.mapping.deriv(m) )
-
-        if v is not None:
-            return rDeriv.T * ( rDeriv * v )
-        return rDeriv.T * rDeriv
-
-    @Utils.timeIt
-    def _evalSmoothDeriv(self, m):
-        deriv = self._evalSmoothxDeriv(m)
-        if self.regmesh.dim > 1:
-            deriv += self._evalSmoothyDeriv(m)
-        if self.regmesh.dim > 2:
-            deriv += self._evalSmoothzDeriv(m)
-        return deriv
-
-    @Utils.timeIt
-    def _evalSmooth2Deriv(self, m, v=None):
-        deriv = self._evalSmoothx2Deriv(m, v)
-        if self.regmesh.dim > 1:
-            deriv += self._evalSmoothy2Deriv(m, v)
-        if self.regmesh.dim > 2:
-            deriv += self._evalSmoothz2Deriv(m, v)
-        return deriv
-
-
-    @Utils.timeIt
-    def eval(self, m):
-        return self._evalSmall(m) + self._evalSmooth(m)
-
-    @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})}
-
-        """
-        return self._evalSmallDeriv(m) + self._evalSmoothDeriv(m)
-
-    @Utils.timeIt
-    def eval2Deriv(self, m, v=None):
-        return self._evalSmall2Deriv(m, v) + self._evalSmooth2Deriv(m, v)
-
-
-
-class Tikhonov(Simple):
+class Tikhonov(BaseRegularization):
     """
     L2 Tikhonov regularization with both smallness and smoothness (first order
     derivative) contributions.
@@ -726,131 +490,56 @@ class Tikhonov(Simple):
             self._Wzz = Utils.sdiag((self.regmesh.vol*self.alpha_zz)**0.5)*self.regmesh.faceDiffz*self.regmesh.cellDiffz
         return self._Wzz
 
-
     @property
-    def Wsmooth2(self):
+    def Wsmooth(self):
         """Full smoothness regularization matrix W"""
         if getattr(self, '_Wsmooth', None) is None:
-            wlist = (self.Wxx)
+            wlist = (self.Wx, self.Wxx)
             if self.regmesh.dim > 1:
-                wlist += (self.Wyy)
+                wlist += (self.Wy, self.Wyy)
             if self.regmesh.dim > 2:
-                wlist += (self.Wzz)
+                wlist += (self.Wz, self.Wzz)
             self._Wsmooth = sp.vstack(wlist)
         return self._Wsmooth
 
+    @property
+    def W(self):
+        """Full regularization matrix W"""
+        if getattr(self, '_W', None) is None:
+            wlist = (self.Wsmall, self.Wsmooth)
+            self._W = sp.vstack(wlist)
+        return self._W
+
     @Utils.timeIt
-    def _evalSmoothxx(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wxx * ( self.mapping * (m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wxx * ( self.mapping * (m) )
+    def _evalSmall(self, m):
+        r = self.Wsmall * ( self.mapping * (m - self.mref) )
         return 0.5 * r.dot(r)
 
     @Utils.timeIt
-    def _evalSmoothyy(self, m):
+    def _evalSmooth(self, m):
         if self.mrefInSmooth == True:
-            r = self.Wyy * ( self.mapping * (m - self.mref) )
+            r = self.Wsmooth * ( self.mapping * (m - self.mref) )
         elif self.mrefInSmooth == False:
-            r = self.Wyy * ( self.mapping * (m) )
+            r = self.Wsmooth * ( self.mapping * (m) )
         return 0.5 * r.dot(r)
 
-    @Utils.timeIt
-    def _evalSmoothzz(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wzz * ( self.mapping * (m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wzz * ( self.mapping * (m) )
-        return 0.5 * r.dot(r)
-
-    @Utils.timeIt
-    def _evalSmooth2(self, m):
-        phiSmooth2 = self._evalSmoothxx(m)
-        if self.regmesh.dim > 1:
-            phiSmooth2 += self._evalSmoothyy(m)
-        if self.regmesh.dim > 2:
-            phiSmooth2 += self._evalSmoothzz(m)
-        return phiSmooth2
-
-    @Utils.timeIt
-    def _evalSmoothxxDeriv(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wxx * ( self.mapping * ( m - self.mref ) )
-            return r.T * ( self.Wxx * self.mapping.deriv(m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wxx * ( self.mapping * m )
-            return r.T * ( self.Wxx * self.mapping.deriv(m) )
-
-    @Utils.timeIt
-    def _evalSmoothyyDeriv(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wyy * ( self.mapping * ( m - self.mref ) )
-            return r.T * ( self.Wyy * self.mapping.deriv(m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wyy * ( self.mapping * m )
-            return r.T * ( self.Wyy * self.mapping.deriv(m) )
-
-    @Utils.timeIt
-    def _evalSmoothzzDeriv(self, m):
-        if self.mrefInSmooth == True:
-            r = self.Wzz * ( self.mapping * ( m - self.mref ) )
-            return r.T * ( self.Wzz * self.mapping.deriv(m - self.mref) )
-        elif self.mrefInSmooth == False:
-            r = self.Wzz * ( self.mapping * m )
-            return r.T * ( self.Wzz * self.mapping.deriv(m) )
-
-    @Utils.timeIt
-    def _evalSmoothxx2Deriv(self, m, v=None):
-        if self.mrefInSmooth == True:
-            rDeriv = self.Wxx * ( self.mapping.deriv( m - self.mref ) )
-        elif self.mrefInSmooth == False:
-            rDeriv = self.Wxx * self.mapping.deriv(m)
-        if v is not None:
-            return rDeriv.T * (rDeriv * v)
-        return rDeriv.T * rDeriv
-
-    @Utils.timeIt
-    def _evalSmoothyy2Deriv(self, m, v=None):
-        if self.mrefInSmooth == True:
-            rDeriv = self.Wyy * ( self.mapping.deriv( m - self.mref ) )
-        elif self.mrefInSmooth == False:
-            rDeriv = self.Wyy * self.mapping.deriv(m)
-        if v is not None:
-            return rDeriv.T * (rDeriv * v)
-        return rDeriv.T * rDeriv
-
-    @Utils.timeIt
-    def _evalSmoothzz2Deriv(self, m, v=None):
-        if self.mrefInSmooth == True:
-            rDeriv = self.Wzz * ( self.mapping.deriv( m - self.mref ) )
-        elif self.mrefInSmooth == False:
-            rDeriv = self.Wzz * self.mapping.deriv(m)
-        if v is not None:
-            return rDeriv.T * (rDeriv * v)
-        return rDeriv.T * rDeriv
-
-    @Utils.timeIt
-    def _evalSmoothDeriv2(self, m):
-        deriv = self._evalSmoothxxDeriv(m)
-        if self.regmesh.dim > 1:
-            deriv += self._evalSmoothyyDeriv(m)
-        if self.regmesh.dim > 2:
-            deriv += self._evalSmoothzzDeriv(m)
-        return deriv
-
-    @Utils.timeIt
-    def _evalSmooth2Deriv2(self, m, v=None):
-        deriv = self._evalSmoothxx2Deriv(m, v)
-        if self.regmesh.dim > 1:
-            deriv += self._evalSmoothyy2Deriv(m, v)
-        if self.regmesh.dim > 2:
-            deriv += self._evalSmoothzz2Deriv(m, v)
-        return deriv
-
-
     @Utils.timeIt
     def eval(self, m):
-        return self._evalSmall(m) + self._evalSmooth(m) + self._evalSmooth2(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):
@@ -868,134 +557,184 @@ class Tikhonov(Simple):
             R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}
 
         """
-        return self._evalSmallDeriv(m) + self._evalSmoothDeriv(m) + self._evalSmoothDeriv2(m)
-
-    def eval2Deriv(self, m, v=None):
-        """
-        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})}
-
-        """
-        return self._evalSmall2Deriv(m, v) + self._evalSmooth2Deriv(m, v) + self._evalSmooth2Deriv2(m, v)
+        return self._evalSmallDeriv(m) + self._evalSmoothDeriv(m)
 
 
-
-class Sparse(Simple):
+class Simple(Tikhonov):
     """
-        The regularization is:
-    
-        .. math::
-    
-            R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top R^\\top R W(m-m_\\text{ref})}
-    
-        where the IRLS weight
-    
-        .. math::
-    
-            R = \eta TO FINISH LATER!!!
-    
-        So the derivative is straight forward:
-    
-        .. math::
-    
-            R(m) = \mathbf{W^\\top R^\\top R W (m-m_\\text{ref})}
-    
-        The IRLS weights are recomputed after each beta solves.
-        It is strongly recommended to do a few Gauss-Newton iterations
-        before updating.
+    Simple regularization that does not include length scales in the derivatives.
     """
-        
-    # set default values
-    eps_p = 1e-1        # Threshold value for the model norm
-    eps_q = 1e-1        # Threshold value for the model gradient norm
-    curModel = None     # Requires model to compute the weights
-    l2model = None
-    gamma = 1.          # Model norm scaling to smooth out convergence
-    norms = [0., 2., 2., 2.] # Values for norm on (m, dmdx, dmdy, dmdz)
-    cell_weights = 1.        # Consider overwriting with sensitivity weights
+
+    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):
-        Simple.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
+        BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
 
-        if isinstance(self.cell_weights,float):
-            self.cell_weights = np.ones(self.regmesh.nC) * self.cell_weights
+        if isinstance(self.wght,float):
+            self.wght = np.ones(self.regmesh.nC) * self.wght
 
     @property
     def Wsmall(self):
         """Regularization matrix Wsmall"""
         if getattr(self,'_Wsmall', None) is None:
-            if getattr(self, 'curModel', None) is None:
-                self.Rs = Utils.speye(self.regmesh.nC)
-
-            else:
-                f_m = self.mapping * (self.curModel - self.reg.mref)
-                self.rs = self.R(f_m , self.eps_p, self.norms[0])
-                self.Rs = Utils.sdiag( self.rs )
-
-            self._Wsmall = Utils.sdiag((self.alpha_s*self.gamma*self.cell_weights)**0.5)*self.Rs
-
+            self._Wsmall = Utils.sdiag((self.regmesh.vol*self.alpha_s*self.wght)**0.5)
         return self._Wsmall
 
     @property
     def Wx(self):
         """Regularization matrix Wx"""
-        if getattr(self,'_Wx', None) is None:
-            if getattr(self, 'curModel', None) is None:
-                self.Rx = Utils.speye(self.regmesh.cellDiffxStencil.shape[0])
-
-            else:
-                f_m = self.regmesh.cellDiffxStencil * (self.mapping * self.curModel)
-                self.rx = self.R( f_m , self.eps_q, self.norms[1])
-                self.Rx = Utils.sdiag( self.rx )
-
-            self._Wx = Utils.sdiag(( self.alpha_x*self.gamma*(self.regmesh.aveCC2Fx*self.cell_weights))**0.5)*self.Rx*self.regmesh.cellDiffxStencil
-
+        if getattr(self, '_Wx', None) is None:
+            self._Wx = Utils.sdiag((self.regmesh.aveCC2Fx * self.regmesh.vol*self.alpha_x*(self.regmesh.aveCC2Fx*self.wght))**0.5)*self.regmesh.cellDiffxStencil
         return self._Wx
 
     @property
     def Wy(self):
         """Regularization matrix Wy"""
-        if getattr(self,'_Wy', None) is None:
-            if getattr(self, 'curModel', None) is None:
-                self.Ry = Utils.speye(self.regmesh.cellDiffyStencil.shape[0])
-
-            else:
-                f_m = self.regmesh.cellDiffyStencil * (self.mapping * self.curModel)
-                self.ry = self.R( f_m , self.eps_q, self.norms[2])
-                self.Ry = Utils.sdiag( self.ry )
-
-            self._Wy = Utils.sdiag((self.alpha_y*self.gamma*(self.regmesh.aveCC2Fy*self.cell_weights))**0.5)*self.Ry*self.regmesh.cellDiffyStencil
-
+        if getattr(self, '_Wy', None) is None:
+            self._Wy = Utils.sdiag((self.regmesh.aveCC2Fy * self.regmesh.vol * self.alpha_y*(self.regmesh.aveCC2Fy*self.wght))**0.5)*self.regmesh.cellDiffyStencil
         return self._Wy
 
     @property
     def Wz(self):
         """Regularization matrix Wz"""
-        if getattr(self,'_Wz', None) is None:
-            if getattr(self, 'curModel', None) is None:
-                self.Rz = Utils.speye(self.regmesh.cellDiffzStencil.shape[0])
-
-            else:
-                f_m = self.regmesh.cellDiffzStencil * (self.mapping * self.curModel)
-                self.rz = self.R( f_m , self.eps_q, self.norms[3])
-                self.Rz = Utils.sdiag( self.rz )
-
-            self._Wz = Utils.sdiag((self.alpha_z*self.gamma*(self.regmesh.aveCC2Fz*self.cell_weights))**0.5)*self.Rz*self.regmesh.cellDiffzStencil
-
+        if getattr(self, '_Wz', None) is None:
+            self._Wz = Utils.sdiag((self.regmesh.aveCC2Fz * self.regmesh.vol*self.alpha_z*(self.regmesh.aveCC2Fz*self.wght))**0.5)*self.regmesh.cellDiffzStencil
         return self._Wz
 
+    @property
+    def Wsmooth(self):
+        """Full smoothness regularization matrix W"""
+        if getattr(self, '_Wsmooth', None) is None:
+            wlist = (self.Wx,)
+            if self.regmesh.dim > 1:
+                wlist += (self.Wy,)
+            if self.regmesh.dim > 2:
+                wlist += (self.Wz,)
+            self._Wsmooth = sp.vstack(wlist)
+        return self._Wsmooth
+
+    @property
+    def W(self):
+        """Full regularization matrix W"""
+        if getattr(self, '_W', None) is None:
+            wlist = (self.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 _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)
+
+
+class Sparse(Simple):
+
+    # set default values
+    eps_p      = 1e-1
+    eps_q      = 1e-1
+    curModel = None # use a model to compute the weights
+    gamma    = 1.
+    norms    = [0., 2., 2., 2.]
+    wght     = 1.
+
+    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 Wsmall(self):
+        """Regularization matrix Wsmall"""
+        if getattr(self, 'curModel', None) is None:
+            self.Rs = Utils.speye(self.regmesh.nC)
+
+        else:
+            f_m = self.mapping * (self.curModel - self.reg.mref)
+            self.rs = self.R(f_m , self.eps_p, self.norms[0])
+            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.mapping * self.curModel)
+            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
+
+    @property
+    def Wy(self):
+        """Regularization matrix Wy"""
+
+        if getattr(self, 'curModel', None) is None:
+            self.Ry = Utils.speye(self.regmesh.cellDiffyStencil.shape[0])
+
+        else:
+            f_m = self.regmesh.cellDiffyStencil * (self.mapping * self.curModel)
+            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
+    def Wz(self):
+        """Regularization matrix Wz"""
+
+        if getattr(self, 'curModel', None) is None:
+            self.Rz = Utils.speye(self.regmesh.cellDiffzStencil.shape[0])
+
+        else:
+            f_m = self.regmesh.cellDiffzStencil * (self.mapping * self.curModel)
+            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
+
+    @property
+    def Wsmooth(self):
+        """Full smoothness regularization matrix W"""
+        #if getattr(self, '_Wsmooth', None) is None:
+        wlist = (self.Wx,)
+        if self.regmesh.dim > 1:
+            wlist += (self.Wy,)
+        if self.regmesh.dim > 2:
+            wlist += (self.Wz,)
+        #self._Wsmooth = sp.vstack(wlist)
+        return sp.vstack(wlist)
+
+    @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
+
     def R(self, f_m , eps, exponent):
 
-        # Eta scaling is important for mix-norms...do not mess with it
         eta = (eps**(1.-exponent/2.))**0.5
         r = eta / (f_m**2.+ eps**2.)**((1.-exponent/2.)/2.)
 

SimPEG/Survey.py

@@ -1,5 +1,4 @@
 import Utils, numpy as np, scipy.sparse as sp, uuid
-import gc
 
 class BaseRx(object):
     """SimPEG Receiver Object"""

SimPEG/Utils/__init__.py

@@ -7,4 +7,3 @@ from CounterUtils import *
 import ModelBuilder
 import SolverUtils
 from coordutils import *
-from modelutils import *

SimPEG/Utils/modelutils.py

@@ -1,63 +0,0 @@
-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)
-
-

docs/em/api_TDEM.rst

@@ -347,10 +347,10 @@ and
 
 
 
-TDEM Problem
-============
+TDEM - B formulation
+====================
 
-.. automodule:: SimPEG.EM.TDEM.TDEM
+.. automodule:: SimPEG.EM.TDEM.TDEM_b
     :show-inheritance:
     :members:
     :undoc-members:
@@ -359,7 +359,7 @@ TDEM Problem
 Field Storage
 =============
 
-.. autoclass:: SimPEG.EM.TDEM.SurveyTDEM.Fields
+.. autoclass:: SimPEG.EM.TDEM.SurveyTDEM.FieldsTDEM
     :show-inheritance:
     :members:
     :undoc-members:
@@ -369,19 +369,19 @@ Field Storage
 TDEM Survey Classes
 ===================
 
-.. autoclass:: SimPEG.EM.TDEM.SurveyTDEM.Survey
+.. autoclass:: SimPEG.EM.TDEM.SurveyTDEM.SurveyTDEM
     :show-inheritance:
     :members:
     :undoc-members:
     :inherited-members:
 
 
-.. Base Classes
-.. ============
+Base Classes
+============
 
-.. .. automodule:: SimPEG.EM.TDEM.BaseTDEM
-..     :show-inheritance:
-..     :members:
-..     :undoc-members:
-..     :inherited-members:
+.. automodule:: SimPEG.EM.TDEM.BaseTDEM
+    :show-inheritance:
+    :members:
+    :undoc-members:
+    :inherited-members:
 

docs/examples/DC_Forward_PseudoSection.rst

@@ -20,9 +20,9 @@ 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
+stype   = survey type "pdp" (pole dipole) or "dpdp" (dipole dipole)
+dtype   = Data type "appr" (app res) | "appc" (app cond) | "volt" (potential)
+Created by @fourndo on Mon Feb 01 19:28:06 2016
 
 
 

docs/examples/Forward_BasicDirectCurrent.rst

@@ -1,4 +1,4 @@
-.. _examples_Utils_surface2ind_topo:
+.. _examples_Forward_BasicDirectCurrent:
 
 .. --------------------------------- ..
 ..                                   ..
@@ -8,17 +8,14 @@
 ..                                   ..
 .. --------------------------------- ..
 
-
-Here we show how to use :code:`Utils.surface2ind_topo` to identify cells below
-a topographic surface.
-
-
+Forward BasicDirectCurrent
+==========================
 
 .. plot::
 
     from SimPEG import Examples
-    Examples.Utils_surface2ind_topo.run()
+    Examples.Forward_BasicDirectCurrent.run()
 
-.. literalinclude:: ../../SimPEG/Examples/Utils_surface2ind_topo.py
+.. literalinclude:: ../../SimPEG/Examples/Forward_BasicDirectCurrent.py
     :language: python
     :linenos:

docs/examples/Mesh_Basic_ForwardDC.rst

@@ -1,25 +0,0 @@
-.. _examples_Mesh_Basic_ForwardDC:
-
-.. --------------------------------- ..
-..                                   ..
-..    THIS FILE IS AUTO GENEREATED   ..
-..                                   ..
-..    SimPEG/Examples/__init__.py    ..
-..                                   ..
-.. --------------------------------- ..
-
-
-Mesh: Basic Forward 2D DC Resistivity
-=====================================
-
-2D DC forward modeling example with Tensor and Curvilinear Meshes
-
-
-.. plot::
-
-    from SimPEG import Examples
-    Examples.Mesh_Basic_ForwardDC.run()
-
-.. literalinclude:: ../../SimPEG/Examples/Mesh_Basic_ForwardDC.py
-    :language: python
-    :linenos:

setup.py

@@ -5,17 +5,16 @@ 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',
@@ -52,16 +51,11 @@ 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
-
-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())
+    cythonKwargs = dict()
 
 ext = '.pyx' if USE_CYTHON else '.c'
 
@@ -100,8 +94,8 @@ setup(
     classifiers=CLASSIFIERS,
     platforms = ["Windows", "Linux", "Solaris", "Mac OS-X", "Unix"],
     use_2to3 = False,
-    cmdclass={'build_ext':NumpyBuild},
-    setup_requires=['numpy'],
+    include_dirs=[np.get_include()],
     ext_modules = extensions,
     scripts=scripts,
+    **cythonKwargs
 )

tests/base/test_PropMaps.py

@@ -1,7 +1,6 @@
 import unittest
 from SimPEG import *
 from scipy.constants import mu_0
-from SimPEG import Tests
 
 
 class MyPropMap(Maps.PropMap):
@@ -188,34 +187,6 @@ 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()
 

tests/base/test_regularization.py

@@ -65,8 +65,10 @@ 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, indActive=indAct)
+                        reg = r(mesh, mapping=mapping, indActive=indAct)
                         m = np.random.rand(mesh.nC)[indAct]
                         reg.mref = np.ones_like(m)*np.mean(m)
 

tests/em/fdem/forward/test_FDEM_analytics.py

@@ -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.Point_e(XYZ, orientation='x', component='imag')
+        rxList = EM.FDEM.Rx(XYZ, 'exi')
         Src0 = EM.FDEM.Src.MagDipole([rxList],loc=np.r_[0.,0.,0.], freq=freq)
 
         survey = EM.FDEM.Survey([Src0])
 
-        prb = EM.FDEM.Problem3D_b(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem_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.Problem3D_h(mesh, mapping=mapping)
-        prbm = EM.FDEM.Problem3D_e(mesh, mapping=mapping)
+        prbe = EM.FDEM.Problem_h(mesh, mapping=mapping)
+        prbm = EM.FDEM.Problem_e(mesh, mapping=mapping)
 
         prbe.pair(surveye) # pair problem and survey
         prbm.pair(surveym)

tests/em/fdem/forward/test_FDEM_forwardHB.py

@@ -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()

tests/em/static/__init__.py

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

tests/em/static/test_DC_2D_analytic.py

@@ -1,69 +0,0 @@
-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()
-

tests/em/static/test_DC_2D_jvecjtvecadj.py

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

tests/em/static/test_DC_analytic.py

@@ -1,71 +0,0 @@
-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()
-

tests/em/static/test_DC_jvecjtvecadj.py

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

tests/em/static/test_IP_fwd.py

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

tests/em/static/test_IP_jvecjtvecadj.py

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

tests/em/static/test_SIP_jvecjtvecadj.py

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

tests/em/tdem/test_TDEM_b_DerivAdjoint.py

@@ -3,218 +3,310 @@ from SimPEG import *
 from SimPEG import EM
 
 plotIt = False
+tol = 1e-6
 
-testDeriv   = True
-testAdjoint = True
+class TDEM_bDerivTests(unittest.TestCase):
 
-TOL = 1e-5
+    def setUp(self):
 
-def setUp(prbtype='b', rxcomp='bz'):
-    cs = 5.
-    ncx = 20
-    ncy = 15
-    npad = 20
-    hx = [(cs,ncx), (cs,npad,1.3)]
-    hy = [(cs,npad,-1.3), (cs,ncy), (cs,npad,1.3)]
-    mesh = Mesh.CylMesh([hx,1,hy], '00C')
-#
-    active = mesh.vectorCCz<0.
-    activeMap = Maps.InjectActiveCells(mesh, active, np.log(1e-8), nC=mesh.nCz)
-    mapping = Maps.ExpMap(mesh) * Maps.SurjectVertical1D(mesh) * activeMap
+        cs = 5.
+        ncx = 20
+        ncy = 6
+        npad = 20
+        hx = [(cs,ncx), (cs,npad,1.3)]
+        hy = [(cs,npad,-1.3), (cs,ncy), (cs,npad,1.3)]
+        mesh = Mesh.CylMesh([hx,1,hy], '00C')
 
-    rxOffset = 10.
-    rx = EM.TDEM.Rx(np.array([[rxOffset, 0., -1e-2]]), np.logspace(-4,-3, 20), rxcomp) #,]
-    src = EM.TDEM.Src.MagDipole([rx], loc=np.array([0., 0., 0.]))
+        active = mesh.vectorCCz<0.
+        activeMap = Maps.InjectActiveCells(mesh, active, np.log(1e-8), nC=mesh.nCz)
+        mapping = Maps.ExpMap(mesh) * Maps.SurjectVertical1D(mesh) * activeMap
 
-    survey = EM.TDEM.Survey([src])
+        rxOffset = 40.
+        rx = EM.TDEM.RxTDEM(np.array([[rxOffset, 0., 0.]]), np.logspace(-4,-3, 20), 'bz')
+        src = EM.TDEM.SrcTDEM_VMD_MVP([rx], loc=np.array([0., 0., 0.]))
 
-    if prbtype == 'b':
-        prb = EM.TDEM.Problem_b(mesh, mapping=mapping)
-    elif prbtype == 'e':
-        prb = EM.TDEM.Problem_e(mesh, mapping=mapping)
+        survey = EM.TDEM.SurveyTDEM([src])
 
-    prb.timeSteps = [(1e-05, 10), (5e-05, 10), (2.5e-4, 10)]
-    # prb.timeSteps = [(1e-05, 10), (1e-05, 50), (1e-05, 50) ] #, (2.5e-4, 10)]
+        self.prb = EM.TDEM.ProblemTDEM_b(mesh, mapping=mapping)
+        # self.prb.timeSteps = [1e-5]
+        self.prb.timeSteps = [(1e-05, 10), (5e-05, 10), (2.5e-4, 10)]
+        # self.prb.timeSteps = [(1e-05, 100)]
 
-    try:
-        from pymatsolver import MumpsSolver
-        prb.Solver = MumpsSolver
-    except ImportError, e:
-        prb.Solver = SolverLU
+        try:
+            from pymatsolver import MumpsSolver
+            self.prb.Solver = MumpsSolver
+        except ImportError, e:
+            self.prb.Solver = SolverLU
 
-    m = np.log(1e-1)*np.ones(prb.mapping.nP) + 1e-2*np.random.randn(prb.mapping.nP)
+        self.sigma = np.ones(mesh.nCz)*1e-8
+        self.sigma[mesh.vectorCCz<0] = 1e-1
+        self.sigma = np.log(self.sigma[active])
 
-    prb.pair(survey)
-    mesh = mesh
+        self.prb.pair(survey)
+        self.mesh = mesh
 
-    return prb, m, mesh
+    def test_AhVec(self):
+        """
+            Test that fields and AhVec produce consistent results
+        """
+
+        prb = self.prb
+        sigma = self.sigma
+
+        u = prb.fields(sigma)
+        Ahu = prb._AhVec(sigma, u)
+
+        V1 = Ahu[:,'b',1]
+        V2 = 1./prb.timeSteps[0]*prb.MfMui*u[:,'b',0]
+        self.assertLess(np.linalg.norm(V1-V2)/np.linalg.norm(V2), 1.e-6)
+
+        V1 = Ahu[:,'e',1]
+        return np.linalg.norm(V1) < 1.e-6
+
+        for i in range(2,prb.nT):
+
+            dt = prb.timeSteps[i]
+
+            V1 = Ahu[:,'b',i]
+            V2 = 1.0/dt*prb.MfMui*u[:,'b', i-1]
+            # print np.linalg.norm(V1), np.linalg.norm(V2)
+            self.assertLess(np.linalg.norm(V1)/np.linalg.norm(V2), 1.e-6)
+
+            V1 = Ahu[:,'e',i]
+            V2 = prb.MeSigma*u[:,'e',i]
+            # print np.linalg.norm(V1), np.linalg.norm(V2)
+            return np.linalg.norm(V1)/np.linalg.norm(V2), 1.e-6
+
+    def test_AhVecVSMat_OneTS(self):
+
+        prb = self.prb
+        prb.timeSteps = [1e-05]
+        sigma = self.sigma
+        prb.curModel = sigma
+
+        dt = prb.timeSteps[0]
+        a11 = 1/dt*prb.MfMui*sp.identity(prb.mesh.nF)
+        a12 = prb.MfMui*prb.mesh.edgeCurl
+        a21 = prb.mesh.edgeCurl.T*prb.MfMui
+        a22 = -prb.MeSigma
+        A = sp.bmat([[a11,a12],[a21,a22]])
+
+        f = prb.fields(sigma)
+        u1 = A*f.tovec()
+        u2 = prb._AhVec(sigma,f).tovec()
+
+        self.assertTrue(np.linalg.norm(u1-u2)/np.linalg.norm(u1)<1e-12)
+
+    def test_solveAhVSMat_OneTS(self):
+        prb = self.prb
+
+        prb.timeSteps = [1e-05]
+
+        sigma = self.sigma
+        prb.curModel = sigma
+
+        dt = prb.timeSteps[0]
+        a11 = 1.0/dt*prb.MfMui*sp.identity(prb.mesh.nF)
+        a12 = prb.MfMui*prb.mesh.edgeCurl
+        a21 = prb.mesh.edgeCurl.T*prb.MfMui
+        a22 = -prb.MeSigma
+        A = sp.bmat([[a11,a12],[a21,a22]])
+
+        f = prb.fields(sigma)
+        f[:,:,0] = {'b':0}
+        f[:,'b',1] = 0
+
+        self.assertTrue(np.all(np.r_[f[:,'b',1],f[:,'e',1]] == f.tovec()))
+
+        u1 = prb.solveAh(sigma,f).tovec().flatten()
+        u2 = sp.linalg.spsolve(A.tocsr(),f.tovec())
+
+        self.assertTrue(np.linalg.norm(u1-u2)<1e-8)
+
+    def test_solveAhVsAhVec(self):
+
+        prb = self.prb
+        mesh = self.prb.mesh
+        sigma = self.sigma
+        self.prb.curModel = sigma
+
+        f = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+        f[:,'b',:] = 0.0
+        for i in range(prb.nT):
+            f[:,'e', i] = np.random.rand(mesh.nE, 1)
+
+        Ahf = prb._AhVec(sigma, f)
+        f_test = prb.solveAh(sigma, Ahf)
+
+        u1 = f.tovec()
+        u2 = f_test.tovec()
+        self.assertTrue(np.linalg.norm(u1-u2)<1e-8)
+
+    def test_DerivG(self):
+        """
+            Test the derivative of c with respect to sigma
+        """
+
+        # Random model and perturbation
+        sigma = np.random.rand(self.prb.mapping.nP)
+
+        f = self.prb.fields(sigma)
+        dm = 1000*np.random.rand(self.prb.mapping.nP)
+        h = 0.01
+
+        derChk = lambda m: [self.prb._AhVec(m, f).tovec(), lambda mx: self.prb.Gvec(sigma, mx, u=f).tovec()]
+        print '\ntest_DerivG'
+        passed = Tests.checkDerivative(derChk, sigma, plotIt=False, dx=dm, num=4, eps=1e-20)
+        return passed
+
+    def test_Deriv_dUdM(self):
+
+        prb = self.prb
+        prb.timeSteps = [(1e-05, 10), (0.0001, 10), (0.001, 10)]
+        mesh = self.mesh
+        sigma = self.sigma
+
+        dm = 10*np.random.rand(prb.mapping.nP)
+        f = prb.fields(sigma)
+
+        derChk = lambda m: [self.prb.fields(m).tovec(), lambda mx: -prb.solveAh(sigma, prb.Gvec(sigma, mx, u=f)).tovec()]
+        print '\n'
+        print 'test_Deriv_dUdM'
+        Tests.checkDerivative(derChk, sigma, plotIt=False, dx=dm, num=4, eps=1e-20)
+
+    def test_Deriv_J(self):
+
+        prb = self.prb
+        prb.timeSteps = [(1e-05, 10), (0.0001, 10), (0.001, 10)]
+        mesh = self.mesh
+        sigma = self.sigma
+
+        # d_sig = 0.8*sigma #np.random.rand(mesh.nCz)
+        d_sig = 10*np.random.rand(prb.mapping.nP)
 
 
-class TDEM_DerivTests(unittest.TestCase):
+        derChk = lambda m: [prb.survey.dpred(m), lambda mx: prb.Jvec(sigma, mx)]
+        print '\n'
+        print 'test_Deriv_J'
+        Tests.checkDerivative(derChk, sigma, plotIt=False, dx=d_sig, num=4, eps=1e-20)
 
-# ====== TEST A ========== #
+    def test_projectAdjoint(self):
+        prb = self.prb
+        survey = prb.survey
+        mesh = self.mesh
 
-    def AderivTest(self, prbtype):
-        prb, m0, mesh = setUp(prbtype)
-        tInd = 2
-        if prbtype == 'b':
-            nu = mesh.nF
-        elif prbtype == 'e':
-            nu = mesh.nE
-        v = np.random.rand(nu)
+        # Generate random fields and data
+        f = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+        for i in range(prb.nT):
+            f[:,'b',i] = np.random.rand(mesh.nF, 1)
+            f[:,'e',i] = np.random.rand(mesh.nE, 1)
+        d_vec = np.random.rand(survey.nD)
+        d = Survey.Data(survey,v=d_vec)
 
-        def AderivFun(m):
-            prb.curModel = m
-            A = prb.getAdiag(tInd)
-            Av = A*v
-            prb.curModel = m0
-            ADeriv_dm = lambda dm: prb.getAdiagDeriv(tInd, v, dm)
+        # Check that d.T*Q*f = f.T*Q.T*d
+        V1 = d_vec.dot(survey.evalDeriv(None, v=f).tovec())
+        V2 = f.tovec().dot(survey.evalDeriv(None, v=d, adjoint=True).tovec())
 
-            return Av, ADeriv_dm
+        self.assertTrue((V1-V2)/np.abs(V1) < tol)
 
-        print '\n Testing ADeriv %s'%(prbtype)
-        Tests.checkDerivative(AderivFun, m0, plotIt=False, num=4, eps=1e-20)
+    def test_adjointAhVsAht(self):
+        prb = self.prb
+        mesh = self.mesh
+        sigma = self.sigma
 
-    def A_adjointTest(self,prbtype):
-        prb, m0, mesh = setUp(prbtype)
-        tInd = 2
+        f1 = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+        for i in range(1,prb.nT+1):
+            f1[:,'b',i] = np.random.rand(mesh.nF, 1)
+            f1[:,'e',i] = np.random.rand(mesh.nE, 1)
 
-        print '\n Testing A_adjoint'
-        m = np.random.rand(prb.mapping.nP)
-        if prbtype == 'b':
-            nu = prb.mesh.nF
-        elif prbtype == 'e':
-            nu = prb.mesh.nE
+        f2 = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+        for i in range(1,prb.nT+1):
+            f2[:,'b',i] = np.random.rand(mesh.nF, 1)
+            f2[:,'e',i] = np.random.rand(mesh.nE, 1)
 
-        v = np.random.rand(nu)
-        u = np.random.rand(nu)
-        prb.curModel = m0
+        V1 = f2.tovec().dot(prb._AhVec(sigma, f1).tovec())
+        V2 = f1.tovec().dot(prb._AhtVec(sigma, f2).tovec())
+        self.assertTrue(np.abs(V1-V2)/np.abs(V1) < tol)
 
-        tInd = 2 # not actually used
-        V1 = v.dot(prb.getAdiagDeriv(tInd, u, m))
-        V2 = m.dot(prb.getAdiagDeriv(tInd, u, v, adjoint=True))
-        passed = np.abs(V1-V2) < TOL * (np.abs(V1) + np.abs(V2))/2.
-        print 'AdjointTest %s'%(prbtype), V1, V2, passed
-        self.assertTrue(passed)
+    # def test_solveAhtVsAhtVec(self):
+    #     prb = self.prb
+    #     mesh = self.mesh
+    #     sigma = np.random.rand(prb.mapping.nP)
 
-    def test_Aderiv_b(self):
-        self.AderivTest('b')
-    def test_Aderiv_e(self):
-        self.AderivTest('e')
+    #     f1 = EM.TDEM.FieldsTDEM(mesh,prb.survey)
+    #     for i in range(1,prb.nT+1):
+    #         f1[:,'b',i] = np.random.rand(mesh.nF, 1)
+    #         f1[:,'e',i] = np.random.rand(mesh.nE, 1)
 
-    def test_Aadjoint_b(self):
-        self.A_adjointTest('b')
-    def test_Aadjoint_e(self):
-        self.A_adjointTest('e')
+    #     f2 = prb.solveAht(sigma, f1)
+    #     f3 = prb._AhtVec(sigma, f2)
 
-# ====== TEST Fields Deriv Pieces ========== #
+    #     if True:
+    #         import matplotlib.pyplot as plt
+    #         plt.plot(f3.tovec(),'b')
+    #         plt.plot(f1.tovec(),'r')
+    #         plt.show()
+    #     V1 = np.linalg.norm(f3.tovec()-f1.tovec())
+    #     V2 = np.linalg.norm(f1.tovec())
+    #     print 'AhtVsAhtVec', V1, V2, f1.tovec()
+    #     print 'I am gunna fail this one: boo. :('
+    #     self.assertLess(V1/V2, 1e-6)
 
-    def test_eDeriv_m_adjoint(self):
-        prb, m0, mesh = setUp()
-        tInd = 0
+    # def test_adjointsolveAhVssolveAht(self):
+    #     prb = self.prb
+    #     mesh = self.mesh
+    #     sigma = self.sigma
 
-        v = np.random.rand(mesh.nF)
+    #     f1 = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+    #     for i in range(1,prb.nT+1):
+    #         f1[:,'b',i] = np.random.rand(mesh.nF, 1)
+    #         f1[:,'e',i] = np.random.rand(mesh.nE, 1)
 
-        print '\n Testing eDeriv_m Adjoint'
+    #     f2 = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+    #     for i in range(1,prb.nT+1):
+    #         f2[:,'b',i] = np.random.rand(mesh.nF, 1)
+    #         f2[:,'e',i] = np.random.rand(mesh.nE, 1)
 
-        prb, m0, mesh = setUp()
-        f = prb.fields(m0)
+    #     V1 = f2.tovec().dot(prb.solveAh(sigma, f1).tovec())
+    #     V2 = f1.tovec().dot(prb.solveAht(sigma, f2).tovec())
+    #     print V1, V2
+    #     self.assertLess(np.abs(V1-V2)/np.abs(V1), 1e-6)
+
+    def test_adjointGvecVsGtvec(self):
+        mesh = self.mesh
+        prb = self.prb
 
         m = np.random.rand(prb.mapping.nP)
-        e = np.random.randn(prb.mesh.nE)
-        V1 = e.dot(f._eDeriv_m(1, prb.survey.srcList[0], m))
-        V2 = m.dot(f._eDeriv_m(1, prb.survey.srcList[0], e, adjoint=True))
-        tol = TOL * (np.abs(V1) + np.abs(V2)) / 2.
-        passed = np.abs(V1-V2) < tol
+        sigma = np.random.rand(prb.mapping.nP)
 
-        print '    ', V1, V2, np.abs(V1-V2), tol, passed
+        u = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+        for i in range(1,prb.nT+1):
+            u[:,'b',i] = np.random.rand(mesh.nF, 1)
+            u[:,'e',i] = np.random.rand(mesh.nE, 1)
+
+        v = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+        for i in range(1,prb.nT+1):
+            v[:,'b',i] = np.random.rand(mesh.nF, 1)
+            v[:,'e',i] = np.random.rand(mesh.nE, 1)
+
+        V1 = m.dot(prb.Gtvec(sigma, v, u))
+        V2 = v.tovec().dot(prb.Gvec(sigma, m, u).tovec())
+        self.assertTrue(np.abs(V1-V2)/np.abs(V1) < tol)
+
+    def test_adjointJvecVsJtvec(self):
+        mesh = self.mesh
+        prb = self.prb
+        sigma = self.sigma
+
+        m = np.random.rand(prb.mapping.nP)
+        d = np.random.rand(prb.survey.nD)
+
+        V1 = d.dot(prb.Jvec(sigma, m))
+        V2 = m.dot(prb.Jtvec(sigma, d))
+        passed = np.abs(V1-V2)/np.abs(V1) < tol
+        print 'AdjointTest', V1, V2, passed
         self.assertTrue(passed)
 
-    def test_eDeriv_u_adjoint(self):
-        print '\n Testing eDeriv_u Adjoint'
-
-        prb, m0, mesh = setUp()
-        f = prb.fields(m0)
-
-        b = np.random.rand(prb.mesh.nF)
-        e = np.random.randn(prb.mesh.nE)
-        V1 = e.dot(f._eDeriv_u(1, prb.survey.srcList[0], b))
-        V2 = b.dot(f._eDeriv_u(1, prb.survey.srcList[0], e, adjoint=True))
-        tol = TOL * (np.abs(V1) + np.abs(V2)) / 2.
-        passed = np.abs(V1-V2) < tol
-
-        print '    ', V1, V2, np.abs(V1-V2), tol, passed
-        self.assertTrue(passed)
-
-
-# ====== TEST Jvec ========== #
-
-    if testDeriv:
-
-        def JvecTest(self, prbtype, rxcomp):
-            prb, m, mesh = setUp(prbtype, rxcomp)
-
-            derChk = lambda m: [prb.survey.dpred(m), lambda mx: prb.Jvec(m, mx)]
-            print '\n'
-            print 'test_Jvec_%s_%s' %(prbtype, rxcomp)
-            Tests.checkDerivative(derChk, m, plotIt=False, num=2, eps=1e-20)
-
-        def test_Jvec_b_bx(self):
-            self.JvecTest('b','bx')
-
-        def test_Jvec_b_bz(self):
-            self.JvecTest('b','bz')
-
-        def test_Jvec_b_dbxdt(self):
-            self.JvecTest('b','dbxdt')
-
-        def test_Jvec_b_dbzdt(self):
-            self.JvecTest('b','dbzdt')
-
-        def test_Jvec_b_ey(self):
-            self.JvecTest('b','ey')
-
-        def test_Jvec_e_ey(self):
-            self.JvecTest('e','ey')
-
-
-# ====== TEST Jtvec ========== #
-
-    if testAdjoint:
-
-        def JvecVsJtvecTest(self, prbtype='b', rxcomp='bz'):
-
-            print '\nAdjoint Testing Jvec, Jtvec %s' %(rxcomp)
-
-            prb, m0, mesh = setUp(prbtype, rxcomp)
-            m = np.random.rand(prb.mapping.nP)
-            d = np.random.randn(prb.survey.nD)
-            V1 = d.dot(prb.Jvec(m0, m))
-            V2 = m.dot(prb.Jtvec(m0, d))
-            tol = TOL * (np.abs(V1) + np.abs(V2)) / 2.
-            passed = np.abs(V1-V2) < tol
-
-            print '    ', V1, V2, np.abs(V1-V2), tol, passed
-            self.assertTrue(passed)
-
-        def test_Jvec_adjoint_b_bx(self):
-            self.JvecVsJtvecTest('b', 'bx')
-
-        def test_Jvec_adjoint_b_bz(self):
-            self.JvecVsJtvecTest('b', 'bz')
-
-        def test_Jvec_adjoint_b_dbxdt(self):
-            self.JvecVsJtvecTest('b', 'bx')
-
-        def test_Jvec_adjoint_b_dbzdt(self):
-            self.JvecVsJtvecTest('b', 'bz')
-
-        def test_Jvec_adjoint_b_ey(self):
-            self.JvecVsJtvecTest('b', 'ey')
-
-        # This is not working because Problem_e has not done
-        # def test_Jvec_adjoint_e_ey(self):
-        #     self.JvecVsJtvecTest('e', 'ey')
 
 
 

tests/em/tdem/test_TDEM_b_MultiSrc_DerivAdjoint.py

@@ -3,12 +3,10 @@ from SimPEG import *
 from SimPEG import EM
 
 plotIt = False
-testDeriv = True
-testAdjoint = True
 
-TOL = 1e-5
+class TDEM_bDerivTests(unittest.TestCase):
 
-def setUp(self, rxcomp='bz'):
+    def setUp(self):
 
         cs = 5.
         ncx = 20
@@ -23,78 +21,131 @@ def setUp(self, rxcomp='bz'):
         mapping = Maps.ExpMap(mesh) * Maps.SurjectVertical1D(mesh) * activeMap
 
         rxOffset = 40.
-        rx = EM.TDEM.Rx(np.array([[rxOffset, 0., 0.]]), np.logspace(-4,-3, 20), rxcomp)
-        src = EM.TDEM.Src.MagDipole( [rx], loc=np.array([0., 0., 0.]))
-        rx2 = EM.TDEM.Rx(np.array([[rxOffset-10, 0., 0.]]), np.logspace(-5,-4, 25), rxcomp)
-        src2 = EM.TDEM.Src.MagDipole( [rx2], loc=np.array([0., 0., 0.]))
+        rx = EM.TDEM.RxTDEM(np.array([[rxOffset, 0., 0.]]), np.logspace(-4,-3, 20), 'bz')
+        src = EM.TDEM.SrcTDEM_VMD_MVP( [rx], loc=np.array([0., 0., 0.]))
+        rx2 = EM.TDEM.RxTDEM(np.array([[rxOffset-10, 0., 0.]]), np.logspace(-5,-4, 25), 'bz')
+        src2 = EM.TDEM.SrcTDEM_VMD_MVP( [rx2], loc=np.array([0., 0., 0.]))
 
-        survey = EM.TDEM.Survey([src,src2])
+        survey = EM.TDEM.SurveyTDEM([src,src2])
 
-        prb = EM.TDEM.Problem_b(mesh, mapping=mapping)
-        # prb.timeSteps = [1e-5]
-        prb.timeSteps = [(1e-05, 10), (5e-05, 10), (2.5e-4, 10)]
-        # prb.timeSteps = [(1e-05, 100)]
+        self.prb = EM.TDEM.ProblemTDEM_b(mesh, mapping=mapping)
+        # self.prb.timeSteps = [1e-5]
+        self.prb.timeSteps = [(1e-05, 10), (5e-05, 10), (2.5e-4, 10)]
+        # self.prb.timeSteps = [(1e-05, 100)]
 
         try:
             from pymatsolver import MumpsSolver
-            prb.Solver = MumpsSolver
+            self.prb.Solver = MumpsSolver
         except ImportError, e:
-            prb.Solver  = SolverLU
+            self.prb.Solver  = SolverLU
 
-        m = np.log(1e-1)*np.ones(prb.mapping.nP) + 1e-2*np.random.randn(prb.mapping.nP)
+        self.sigma = np.ones(mesh.nCz)*1e-8
+        self.sigma[mesh.vectorCCz<0] = 1e-1
+        self.sigma = np.log(self.sigma[active])
 
-        prb.pair(survey)
+        self.prb.pair(survey)
+        self.mesh = mesh
 
-        return mesh, prb, m
+    def test_DerivG(self):
+        """
+            Test the derivative of c with respect to sigma
+        """
 
-class TDEM_bDerivTests(unittest.TestCase):
+        # Random model and perturbation
+        sigma = np.random.rand(self.prb.mapping.nP)
+
+        f = self.prb.fields(sigma)
+        dm = 1000*np.random.rand(self.prb.mapping.nP)
+        h = 0.01
+
+        derChk = lambda m: [self.prb._AhVec(m, f).tovec(), lambda mx: self.prb.Gvec(sigma, mx, u=f).tovec()]
+        print '\ntest_DerivG'
+        Tests.checkDerivative(derChk, sigma, plotIt=False, dx=dm, num=4, eps=1e-20)
+
+    def test_Deriv_dUdM(self):
+
+        prb = self.prb
+        prb.timeSteps = [(1e-05, 10), (0.0001, 10), (0.001, 10)]
+        mesh = self.mesh
+        sigma = self.sigma
+
+        dm = 10*np.random.rand(prb.mapping.nP)
+        f = prb.fields(sigma)
+
+        derChk = lambda m: [self.prb.fields(m).tovec(), lambda mx: -prb.solveAh(sigma, prb.Gvec(sigma, mx, u=f)).tovec()]
+        print '\n'
+        print 'test_Deriv_dUdM'
+        Tests.checkDerivative(derChk, sigma, plotIt=False, dx=dm, num=4, eps=1e-20)
+
+    def test_Deriv_J(self):
+
+        prb = self.prb
+        prb.timeSteps = [(1e-05, 10), (0.0001, 10), (0.001, 10)]
+        mesh = self.mesh
+        sigma = self.sigma
+
+        # d_sig = 0.8*sigma #np.random.rand(mesh.nCz)
+        d_sig = 10*np.random.rand(prb.mapping.nP)
 
 
-    if testDeriv:
-        def Deriv_J(self, rxcomp='bz'):
+        derChk = lambda m: [prb.survey.dpred(m), lambda mx: prb.Jvec(sigma, mx)]
+        print '\n'
+        print 'test_Deriv_J'
+        Tests.checkDerivative(derChk, sigma, plotIt=False, dx=d_sig, num=4, eps=1e-20)
 
-            mesh, prb, m0 = setUp(rxcomp)
+    def test_projectAdjoint(self):
+        prb = self.prb
+        survey = prb.survey
+        nSrc = survey.nSrc
+        mesh = self.mesh
 
-            prb.timeSteps = [(1e-05, 10), (0.0001, 10), (0.001, 10)]
+        # Generate random fields and data
+        f = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+        for i in range(prb.nT):
+            f[:,'b',i] = np.random.rand(mesh.nF, nSrc)
+            f[:,'e',i] = np.random.rand(mesh.nE, nSrc)
+        d_vec = np.random.rand(survey.nD)
+        d = Survey.Data(survey,v=d_vec)
 
-            derChk = lambda m: [prb.survey.dpred(m), lambda mx: prb.Jvec(m0, mx)]
-            print '\n'
-            print 'test_Deriv_J %s'%rxcomp
-            Tests.checkDerivative(derChk, m0, plotIt=False, num=3, eps=1e-20)
+        # Check that d.T*Q*f = f.T*Q.T*d
+        V1 = d_vec.dot(survey.evalDeriv(None, v=f).tovec())
+        V2 = np.sum((f.tovec())*(survey.evalDeriv(None, v=d, adjoint=True).tovec()))
 
-        def test_Jvec_bx(self):
-            self.Deriv_J('bx')
+        self.assertTrue((V1-V2)/np.abs(V1) < 1e-6)
 
-        def test_Jvec_bz(self):
-            self.Deriv_J('bz')
+    def test_adjointGvecVsGtvec(self):
+        mesh = self.mesh
+        prb = self.prb
 
-        def test_Jvec_ey(self):
-            self.Deriv_J('ey')
+        m = np.random.rand(prb.mapping.nP)
+        sigma = np.random.rand(prb.mapping.nP)
 
-    if testAdjoint:
-        def adjointJvecVsJtvec(self, rxcomp='bz'):
-            print ' \n Testing Adjoint %s' %rxcomp
-            mesh, prb, m0 = setUp(rxcomp)
+        u = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+        for i in range(1,prb.nT+1):
+            u[:,'b',i] = np.random.rand(mesh.nF, 2)
+            u[:,'e',i] = np.random.rand(mesh.nE, 2)
 
-            m = np.random.rand(prb.mapping.nP)
-            d = np.random.rand(prb.survey.nD)
+        v = EM.TDEM.FieldsTDEM(prb.mesh, prb.survey)
+        for i in range(1,prb.nT+1):
+            v[:,'b',i] = np.random.rand(mesh.nF, 2)
+            v[:,'e',i] = np.random.rand(mesh.nE, 2)
 
-            V1 = d.dot(prb.Jvec(m0, m))
-            V2 = m.dot(prb.Jtvec(m0, d))
+        V1 = m.dot(prb.Gtvec(sigma, v, u))
+        V2 = np.sum(v.tovec()*prb.Gvec(sigma, m, u).tovec())
+        self.assertTrue(np.abs(V1-V2)/np.abs(V1) <1e-6)
 
-            tol = TOL * (np.abs(V1) + np.abs(V2)) / 2.
-            passed = np.abs(V1-V2) < tol
-            print '    ', V1, V2, np.abs(V1-V2), tol, passed
-            self.assertTrue(passed)
+    def test_adjointJvecVsJtvec(self):
+        mesh = self.mesh
+        prb = self.prb
+        sigma = self.sigma
 
-        def test_JvecVsJtvec_bx(self):
-            self.adjointJvecVsJtvec('bx')
+        m = np.random.rand(prb.mapping.nP)
+        d = np.random.rand(prb.survey.nD)
 
-        def test_JvecVsJtvec_bz(self):
-            self.adjointJvecVsJtvec('bz')
-
-        def test_JvecVsJtvec_ey(self):
-            self.adjointJvecVsJtvec('ey')
+        V1 = d.dot(prb.Jvec(sigma, m))
+        V2 = m.dot(prb.Jtvec(sigma, d))
+        print 'AdjointTest', V1, V2
+        self.assertTrue(np.abs(V1-V2)/np.abs(V1) < 1e-6)
 
 
 

tests/em/tdem/test_TDEM_combos.py

@@ -0,0 +1,94 @@
+import unittest
+from SimPEG import *
+from SimPEG import EM
+
+plotIt = False
+
+def getProb(meshType='CYL',rxTypes='bx,bz',nSrc=1):
+    cs = 5.
+    ncx = 20
+    ncy = 6
+    npad = 20
+    hx = [(cs,ncx), (cs,npad,1.3)]
+    hy = [(cs,npad,-1.3), (cs,ncy), (cs,npad,1.3)]
+    mesh = Mesh.CylMesh([hx,1,hy], '00C')
+
+    active = mesh.vectorCCz<0.
+    activeMap = Maps.InjectActiveCells(mesh, active, np.log(1e-8), nC=mesh.nCz)
+    mapping = Maps.ExpMap(mesh) * Maps.SurjectVertical1D(mesh) * activeMap
+
+    rxOffset = 40.
+
+    srcs = []
+    for ii in range(nSrc):
+        rxs = [EM.TDEM.RxTDEM(np.array([[rxOffset, 0., 0.]]), np.logspace(-4,-3, 20 + ii), rxType) for rxType in rxTypes.split(',')]
+        srcs += [EM.TDEM.SrcTDEM_VMD_MVP(rxs,np.array([0., 0., 0.]))]
+
+    survey = EM.TDEM.SurveyTDEM(srcs)
+
+    prb = EM.TDEM.ProblemTDEM_b(mesh, mapping=mapping)
+    # prb.timeSteps = [1e-5]
+    prb.timeSteps = [(1e-05, 10), (5e-05, 10), (2.5e-4, 10)]
+    # prb.timeSteps = [(1e-05, 100)]
+
+    try:
+        from pymatsolver import MumpsSolver
+        prb.Solver = MumpsSolver
+    except ImportError, e:
+        prb.Solver  = SolverLU
+
+    sigma = np.ones(mesh.nCz)*1e-8
+    sigma[mesh.vectorCCz<0] = 1e-1
+    sigma = np.log(sigma[active])
+
+    prb.pair(survey)
+    return prb, mesh, sigma
+
+def dotestJvec(prb, mesh, sigma):
+    prb.timeSteps = [(1e-05, 10), (0.0001, 10), (0.001, 10)]
+    # d_sig = 0.8*sigma #np.random.rand(mesh.nCz)
+    d_sig = 10*np.random.rand(prb.mapping.nP)
+    derChk = lambda m: [prb.survey.dpred(m), lambda mx: prb.Jvec(sigma, mx)]
+    return Tests.checkDerivative(derChk, sigma, plotIt=False, dx=d_sig, num=2, eps=1e-20)
+
+def dotestAdjoint(prb, mesh, sigma):
+    m = np.random.rand(prb.mapping.nP)
+    d = np.random.rand(prb.survey.nD)
+
+    V1 = d.dot(prb.Jvec(sigma, m))
+    V2 = m.dot(prb.Jtvec(sigma, d))
+    print 'AdjointTest', V1, V2
+    return np.abs(V1-V2)/np.abs(V1), 1e-6
+
+class TDEM_bDerivTests(unittest.TestCase):
+
+    def test_Jvec_bx(self): self.assertTrue(dotestJvec(*getProb(rxTypes='bx')))
+    def test_Adjoint_bx(self): self.assertLess(*dotestAdjoint(*getProb(rxTypes='bx')))
+
+    def test_Jvec_bxbz(self): self.assertTrue(dotestJvec(*getProb(rxTypes='bx,bz')))
+    def test_Adjoint_bxbz(self): self.assertLess(*dotestAdjoint(*getProb(rxTypes='bx,bz')))
+
+    def test_Jvec_bxbz_2src(self): self.assertTrue(dotestJvec(*getProb(rxTypes='bx,bz',nSrc=2)))
+    def test_Adjoint_bxbz_2src(self): self.assertLess(*dotestAdjoint(*getProb(rxTypes='bx,bz',nSrc=2)))
+
+    def test_Jvec_bxbzbz(self): self.assertTrue(dotestJvec(*getProb(rxTypes='bx,bz,bz')))
+    def test_Adjoint_bxbzbz(self): self.assertLess(*dotestAdjoint(*getProb(rxTypes='bx,bz,bz')))
+
+    def test_Jvec_dbxdt(self): self.assertTrue(dotestJvec(*getProb(rxTypes='dbxdt')))
+    def test_Adjoint_dbxdt(self): self.assertLess(*dotestAdjoint(*getProb(rxTypes='dbxdt')))
+
+    def test_Jvec_dbzdt(self): self.assertTrue(dotestJvec(*getProb(rxTypes='dbzdt')))
+    def test_Adjoint_dbzdt(self): self.assertLess(*dotestAdjoint(*getProb(rxTypes='dbzdt')))
+
+    def test_Jvec_dbxdtbz(self): self.assertTrue(dotestJvec(*getProb(rxTypes='dbxdt,bz')))
+    def test_Adjoint_dbxdtbz(self): self.assertLess(*dotestAdjoint(*getProb(rxTypes='dbxdt,bz')))
+
+    def test_Jvec_ey(self): self.assertTrue(dotestJvec(*getProb(rxTypes='ey')))
+    def test_Adjoint_ey(self): self.assertLess(*dotestAdjoint(*getProb(rxTypes='ey')))
+
+    def test_Jvec_eybzdbxdt(self): self.assertTrue(dotestJvec(*getProb(rxTypes='ey,bz,dbxdt')))
+    def test_Adjoint_eybzdbxdt(self): self.assertLess(*dotestAdjoint(*getProb(rxTypes='ey,bz,dbxdt')))
+
+
+if __name__ == '__main__':
+    unittest.main()

tests/em/tdem/test_TDEM_crosscheck.py

@@ -1,76 +0,0 @@
-import unittest
-from SimPEG import *
-from SimPEG import EM
-
-TOL = 1e-5
-FLR = 1e-20
-
-np.random.seed(seed=25) # set a seed so that the same conductivity model is used for all runs
-
-def setUp(prbtype = 'b', rxcomp='bz'):
-    cs = 5.
-    ncx = 20
-    ncy = 15
-    npad = 20
-    hx = [(cs,ncx), (cs,npad,1.3)]
-    hy = [(cs,npad,-1.3), (cs,ncy), (cs,npad,1.3)]
-    mesh = Mesh.CylMesh([hx,1,hy], '00C')
-#
-    active = mesh.vectorCCz<0.
-    activeMap = Maps.InjectActiveCells(mesh, active, np.log(1e-8), nC=mesh.nCz)
-    mapping = Maps.ExpMap(mesh) * Maps.SurjectVertical1D(mesh) * activeMap
-
-    rxOffset = 10.
-    rx = EM.TDEM.Rx(np.array([[rxOffset, 0., -1e-2]]), np.logspace(-4,-3, 20), rxcomp) #,]
-    src = EM.TDEM.Src.MagDipole([rx], loc=np.array([0., 0., 0.]))
-
-    survey = EM.TDEM.Survey([src])
-
-    if prbtype == 'b':
-        prb = EM.TDEM.Problem_b(mesh, mapping=mapping)
-    elif prbtype == 'e':
-        prb = EM.TDEM.Problem_e(mesh, mapping=mapping)
-
-    prb.timeSteps = [(1e-05, 10), (5e-05, 10), (2.5e-4, 10)]
-    # prb.timeSteps = [(1e-05, 10), (1e-05, 50), (1e-05, 50) ] #, (2.5e-4, 10)]
-
-    try:
-        from pymatsolver import MumpsSolver
-        prb.Solver = MumpsSolver
-    except ImportError, e:
-        prb.Solver = SolverLU
-
-    m = np.log(1e-1)*np.ones(prb.mapping.nP) #+ 1e-2*np.random.randn(prb.mapping.nP)
-
-    prb.pair(survey)
-    mesh = mesh
-
-    return prb, m, mesh
-
-def CrossCheck(prbtype1='b', prbtype2='e', rxcomp='bz'):
-
-    prb1,m1,mesh1 = setUp(prbtype1, rxcomp)
-    prb2,m2,mesh2 = setUp(prbtype2, rxcomp)
-
-    assert (m1 == m2).all(), 'Models for two formulations are different'
-
-    d1 = prb1.survey.dpred(m1)
-    d2 = prb2.survey.dpred(m2)
-
-
-    check = np.linalg.norm(d1 - d2)
-    tol   = 0.5 * (np.linalg.norm(d1) + np.linalg.norm(d2)) * TOL
-    passed = check < tol
-
-    print 'Checking %s, %s for %s data'%(prbtype1, prbtype2, rxcomp)
-    print '  ', np.linalg.norm(d1), np.linalg.norm(d2), np.linalg.norm(check), tol, passed
-
-    assert passed
-
-class TDEM_cross_check_EB(unittest.TestCase):
-    def test_EB_ey(self):
-        CrossCheck('b','e','ey')
-
-if __name__ == '__main__':
-    unittest.main()
-

tests/em/tdem/test_TDEM_forward_Analytic.py

@@ -29,12 +29,12 @@ def halfSpaceProblemAnaDiff(meshType, sig_half=1e-2, rxOffset=50., bounds=None,
     actMap = Maps.InjectActiveCells(mesh, active, np.log(1e-8), nC=mesh.nCz)
     mapping = Maps.ExpMap(mesh) * Maps.SurjectVertical1D(mesh) * actMap
 
-    rx = EM.TDEM.Rx(np.array([[rxOffset, 0., 0.]]), np.logspace(-5,-4, 21), 'bz')
-    src = EM.TDEM.Src.MagDipole([rx], waveform= EM.TDEM.Src.StepOffWaveform(), loc=np.array([0., 0., 0.]))
+    rx = EM.TDEM.RxTDEM(np.array([[rxOffset, 0., 0.]]), np.logspace(-5,-4, 21), 'bz')
+    src = EM.TDEM.SrcTDEM_VMD_MVP([rx], loc=np.array([0., 0., 0.]))
     # src = EM.TDEM.SrcTDEM([rx], loc=np.array([0., 0., 0.]))
 
-    survey = EM.TDEM.Survey([src])
-    prb = EM.TDEM.Problem_b(mesh, mapping=mapping)
+    survey = EM.TDEM.SurveyTDEM([src])
+    prb = EM.TDEM.ProblemTDEM_b(mesh, mapping=mapping)
     prb.Solver = MumpsSolver
 
     prb.timeSteps = [(1e-06, 40), (5e-06, 40), (1e-05, 40), (5e-05, 40), (0.0001, 40), (0.0005, 40)]
@@ -50,8 +50,6 @@ def halfSpaceProblemAnaDiff(meshType, sig_half=1e-2, rxOffset=50., bounds=None,
 
     ind = np.logical_and(rx.times > bounds[0],rx.times < bounds[1])
     log10diff = np.linalg.norm(np.log10(np.abs(bz_calc[ind])) - np.log10(np.abs(bz_ana[ind])))/np.linalg.norm(np.log10(np.abs(bz_ana[ind])))
-
-    print ' |bz_ana| = ',np.linalg.norm(bz_ana), ' |bz_num| = ', np.linalg.norm(bz_calc), ' |bz_ana - bz_num| =', np.linalg.norm(bz_ana-bz_calc)
     print 'Difference: ', log10diff
 
     if showIt == True:
@@ -63,12 +61,6 @@ def halfSpaceProblemAnaDiff(meshType, sig_half=1e-2, rxOffset=50., bounds=None,
     return log10diff
 
 
-class TDEM_SimpleSrcTests(unittest.TestCase):
-    def test_source(self):
-        waveform = EM.TDEM.Src.StepOffWaveform()
-        assert waveform.eval(0.) == 0.
-
-
 class TDEM_bTests(unittest.TestCase):
 
     def test_analytic_p2_CYL_50m(self):

tests/mesh/test_Mixed_boundaryPoisson.py

@@ -1,411 +0,0 @@
-import numpy as np
-import scipy.sparse as sp
-import unittest
-import matplotlib.pyplot as plt
-from SimPEG import *
-
-MESHTYPES = ['uniformTensorMesh']
-
-def getxBCyBC_CC(mesh, alpha, beta, gamma):
-# def getxBCyBC(mesh, alpha, beta, gamma):
-    """
-    This is a subfunction generating mixed-boundary condition:
-
-    .. math::
-
-        \nabla \cdot \vec{j} = -\nabla \cdot \vec{j}_s = q
-
-        \rho \vec{j} = -\nabla \phi \phi
-
-        \alpha \phi + \beta \frac{\partial \phi}{\partial r} = \gamma \ at \ r = \partial \Omega
-
-        xBC = f_1(\alpha, \beta, \gamma)
-        yBC = f(\alpha, \beta, \gamma)
-
-    Computes xBC and yBC for cell-centered discretizations
-    """
-    if mesh.dim == 1: #1D
-        if (len(alpha) != 2 or len(beta) != 2 or len(gamma) != 2):
-            raise Exception("Lenght of list, alpha should be 2")
-        fCCxm,fCCxp = mesh.cellBoundaryInd
-        nBC = fCCxm.sum()+fCCxp.sum()
-        h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
-
-        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
-        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
-
-        # h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
-        h_xm, h_xp = mesh.hx[0], mesh.hx[-1]
-
-        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
-        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
-        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
-        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
-
-        xBC_xm = 0.5*a_xm
-        xBC_xp = 0.5*a_xp/b_xp
-        yBC_xm = 0.5*(1.-b_xm)
-        yBC_xp = 0.5*(1.-1./b_xp)
-
-        xBC = np.r_[xBC_xm, xBC_xp]
-        yBC = np.r_[yBC_xm, yBC_xp]
-
-    elif mesh.dim == 2: #2D
-        if (len(alpha) != 4 or len(beta) != 4 or len(gamma) != 4):
-            raise Exception("Lenght of list, alpha should be 4")
-
-        fxm,fxp,fym,fyp = mesh.faceBoundaryInd
-        nBC = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
-
-        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
-        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
-        alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
-        alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
-
-        # h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
-        # h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
-
-        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
-        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
-
-        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
-        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
-        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
-        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
-
-        a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
-        b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
-        a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
-        b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
-
-        xBC_xm = 0.5*a_xm
-        xBC_xp = 0.5*a_xp/b_xp
-        yBC_xm = 0.5*(1.-b_xm)
-        yBC_xp = 0.5*(1.-1./b_xp)
-        xBC_ym = 0.5*a_ym
-        xBC_yp = 0.5*a_yp/b_yp
-        yBC_ym = 0.5*(1.-b_ym)
-        yBC_yp = 0.5*(1.-1./b_yp)
-
-        sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
-        sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
-
-        xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
-        xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
-        yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
-        yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
-
-        xBC = np.r_[xBC_x, xBC_y]
-        yBC = np.r_[yBC_x, yBC_y]
-
-    elif mesh.dim == 3: #3D
-        if (len(alpha) != 6 or len(beta) != 6 or len(gamma) != 6):
-            raise Exception("Lenght of list, alpha should be 6")
-        # fCCxm,fCCxp,fCCym,fCCyp,fCCzm,fCCzp = mesh.cellBoundaryInd
-        fxm,fxp,fym,fyp,fzm,fzp = mesh.faceBoundaryInd
-        nBC = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
-
-        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
-        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
-        alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
-        alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
-        alpha_zm, beta_zm, gamma_zm = alpha[4], beta[4], gamma[4]
-        alpha_zp, beta_zp, gamma_zp = alpha[5], beta[5], gamma[5]
-
-        # h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
-        # h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
-        # h_zm, h_zp = mesh.gridCC[fCCzm,2], mesh.gridCC[fCCzp,2]
-
-        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
-        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
-        h_zm, h_zp = mesh.hz[0]*np.ones_like(alpha_zm), mesh.hz[-1]*np.ones_like(alpha_zp)
-
-        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
-        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
-        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
-        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
-
-        a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
-        b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
-        a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
-        b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
-
-        a_zm = gamma_zm/(0.5*alpha_zm-beta_zm/h_zm)
-        b_zm = (0.5*alpha_zm+beta_zm/h_zm)/(0.5*alpha_zm-beta_zm/h_zm)
-        a_zp = gamma_zp/(0.5*alpha_zp-beta_zp/h_zp)
-        b_zp = (0.5*alpha_zp+beta_zp/h_zp)/(0.5*alpha_zp-beta_zp/h_zp)
-
-        xBC_xm = 0.5*a_xm
-        xBC_xp = 0.5*a_xp/b_xp
-        yBC_xm = 0.5*(1.-b_xm)
-        yBC_xp = 0.5*(1.-1./b_xp)
-        xBC_ym = 0.5*a_ym
-        xBC_yp = 0.5*a_yp/b_yp
-        yBC_ym = 0.5*(1.-b_ym)
-        yBC_yp = 0.5*(1.-1./b_yp)
-        xBC_zm = 0.5*a_zm
-        xBC_zp = 0.5*a_zp/b_zp
-        yBC_zm = 0.5*(1.-b_zm)
-        yBC_zp = 0.5*(1.-1./b_zp)
-
-        sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
-        sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
-        sortindsfz = np.argsort(np.r_[np.arange(mesh.nFz)[fzm], np.arange(mesh.nFz)[fzp]])
-
-        xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
-        xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
-        xBC_z = np.r_[xBC_zm, xBC_zp][sortindsfz]
-
-        yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
-        yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
-        yBC_z = np.r_[yBC_zm, yBC_zp][sortindsfz]
-
-        xBC = np.r_[xBC_x, xBC_y, xBC_z]
-        yBC = np.r_[yBC_x, yBC_y, yBC_z]
-
-    return xBC, yBC
-
-class Test1D_InhomogeneousMixed(Tests.OrderTest):
-    name = "1D - Mixed"
-    meshTypes = MESHTYPES
-    meshDimension = 1
-    expectedOrders = 2
-    meshSizes = [4, 8, 16, 32]
-
-    def getError(self):
-        #Test function
-        phi_fun = lambda x: np.cos(np.pi*x)
-        j_fun = lambda x: np.pi*np.sin(np.pi*x)
-        phi_deriv = lambda x: -j_fun(x)
-        q_fun = lambda x: (np.pi**2)*np.cos(np.pi*x)
-
-        xc_ana = phi_fun(self.M.gridCC)
-        q_ana = q_fun(self.M.gridCC)
-        j_ana = j_fun(self.M.gridFx)
-
-        # Get boundary locations
-        vecN = self.M.vectorNx
-        vecC = self.M.vectorCCx
-
-        # Setup Mixed B.C (alpha, beta, gamma)
-        alpha_xm, alpha_xp = 1., 1.
-        beta_xm, beta_xp =  1., 1.
-        alpha = np.r_[alpha_xm, alpha_xp]
-        beta = np.r_[beta_xm, beta_xp]
-        vecN = self.M.vectorNx
-        vecC = self.M.vectorCCx
-        phi_bc = phi_fun(vecN[[0,-1]])
-        phi_deriv_bc = phi_deriv(vecN[[0,-1]])
-        gamma = alpha*phi_bc + beta*phi_deriv_bc
-        x_BC, y_BC = getxBCyBC_CC(self.M, alpha, beta, gamma)
-
-
-        sigma = np.ones(self.M.nC)
-        Mfrho = self.M.getFaceInnerProduct(1./sigma)
-        MfrhoI = self.M.getFaceInnerProduct(1./sigma, invMat=True)
-        V = Utils.sdiag(self.M.vol)
-        Div = V*self.M.faceDiv
-        P_BC, B = self.M.getBCProjWF_simple()
-        q = q_fun(self.M.gridCC)
-        M = B*self.M.aveCC2F
-        G = Div.T - P_BC*Utils.sdiag(y_BC)*M
-        # Mrhoj = D.T V phi + P_BC*Utils.sdiag(y_BC)*M phi - P_BC*x_BC
-        rhs = V*q + Div*MfrhoI*P_BC*x_BC
-        A = Div*MfrhoI*G
-
-        if self.myTest == 'xc':
-            #TODO: fix the null space
-            Ainv = Solver(A)
-            xc = Ainv*rhs
-            err = np.linalg.norm((xc-xc_ana), np.inf)
-        else:
-            NotImplementedError
-        return err
-
-
-    def test_order(self):
-        print "==== Testing Mixed boudary conduction for CC-problem ===="
-        self.name = "1D"
-        self.myTest = 'xc'
-        self.orderTest()
-
-class Test2D_InhomogeneousMixed(Tests.OrderTest):
-    name = "2D - Mixed"
-    meshTypes = MESHTYPES
-    meshDimension = 2
-    expectedOrders = 2
-    meshSizes = [4, 8, 16, 32]
-
-    def getError(self):
-        #Test function
-        phi_fun = lambda x: np.cos(np.pi*x[:,0])*np.cos(np.pi*x[:,1])
-        j_funX = lambda x: +np.pi*np.sin(np.pi*x[:,0])*np.cos(np.pi*x[:,1])
-        j_funY = lambda x: +np.pi*np.cos(np.pi*x[:,0])*np.sin(np.pi*x[:,1])
-        phideriv_funX = lambda x: -j_funX(x)
-        phideriv_funY = lambda x: -j_funY(x)
-        q_fun = lambda x: +2*(np.pi**2)*phi_fun(x)
-
-        xc_ana = phi_fun(self.M.gridCC)
-        q_ana = q_fun(self.M.gridCC)
-        jX_ana = j_funX(self.M.gridFx)
-        jY_ana = j_funY(self.M.gridFy)
-        j_ana = np.r_[jX_ana,jY_ana]
-
-        # Get boundary locations
-        fxm,fxp,fym,fyp = self.M.faceBoundaryInd
-        gBFxm = self.M.gridFx[fxm,:]
-        gBFxp = self.M.gridFx[fxp,:]
-        gBFym = self.M.gridFy[fym,:]
-        gBFyp = self.M.gridFy[fyp,:]
-
-        # Setup Mixed B.C (alpha, beta, gamma)
-        alpha_xm, alpha_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
-        beta_xm, beta_xp =  np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
-        alpha_ym, alpha_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
-        beta_ym, beta_yp =  np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
-
-        phi_bc_xm, phi_bc_xp = phi_fun(gBFxm), phi_fun(gBFxp)
-        phi_bc_ym, phi_bc_yp = phi_fun(gBFym), phi_fun(gBFyp)
-
-        phiderivX_bc_xm, phiderivX_bc_xp = phideriv_funX(gBFxm), phideriv_funX(gBFxp)
-        phiderivY_bc_ym, phiderivY_bc_yp = phideriv_funY(gBFym), phideriv_funY(gBFyp)
-
-        gamma_fun = lambda alpha, beta, phi, phi_deriv: alpha*phi + beta*phi_deriv
-        gamma_xm = gamma_fun(alpha_xm, beta_xm, phi_bc_xm, phiderivX_bc_xm)
-        gamma_xp = gamma_fun(alpha_xp, beta_xp, phi_bc_xp, phiderivX_bc_xp)
-        gamma_ym = gamma_fun(alpha_ym, beta_ym, phi_bc_ym, phiderivY_bc_ym)
-        gamma_yp = gamma_fun(alpha_yp, beta_yp, phi_bc_yp, phiderivY_bc_yp)
-
-        alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp]
-        beta = [beta_xm, beta_xp, beta_ym, beta_yp]
-        gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp]
-
-        x_BC, y_BC = getxBCyBC_CC(self.M, alpha, beta, gamma)
-
-
-        sigma = np.ones(self.M.nC)
-        Mfrho = self.M.getFaceInnerProduct(1./sigma)
-        MfrhoI = self.M.getFaceInnerProduct(1./sigma, invMat=True)
-        V = Utils.sdiag(self.M.vol)
-        Div = V*self.M.faceDiv
-        P_BC, B = self.M.getBCProjWF_simple()
-        q = q_fun(self.M.gridCC)
-        M = B*self.M.aveCC2F
-        G = Div.T - P_BC*Utils.sdiag(y_BC)*M
-        rhs = V*q + Div*MfrhoI*P_BC*x_BC
-        A = Div*MfrhoI*G
-
-        if self.myTest == 'xc':
-            Ainv = Solver(A)
-            xc = Ainv*rhs
-            err = np.linalg.norm((xc-xc_ana), np.inf)
-        else:
-            NotImplementedError
-        return err
-
-
-    def test_order(self):
-        print "==== Testing Mixed boudary conduction for CC-problem ===="
-        self.name = "2D"
-        self.myTest = 'xc'
-        self.orderTest()
-
-class Test3D_InhomogeneousMixed(Tests.OrderTest):
-    name = "3D - Mixed"
-    meshTypes = MESHTYPES
-    meshDimension = 3
-    expectedOrders = 2
-    meshSizes = [4, 8, 16]
-
-    def getError(self):
-        #Test function
-        phi_fun = lambda x: np.cos(np.pi*x[:,0])*np.cos(np.pi*x[:,1])*np.cos(np.pi*x[:,2])
-        j_funX = lambda x: +np.pi*np.sin(np.pi*x[:,0])*np.cos(np.pi*x[:,1])*np.cos(np.pi*x[:,2])
-        j_funY = lambda x: +np.pi*np.cos(np.pi*x[:,0])*np.sin(np.pi*x[:,1])*np.cos(np.pi*x[:,2])
-        j_funZ = lambda x: +np.pi*np.cos(np.pi*x[:,0])*np.cos(np.pi*x[:,1])*np.sin(np.pi*x[:,2])
-
-        phideriv_funX = lambda x: -j_funX(x)
-        phideriv_funY = lambda x: -j_funY(x)
-        phideriv_funZ = lambda x: -j_funZ(x)
-
-        q_fun = lambda x: 3*(np.pi**2)*phi_fun(x)
-
-        xc_ana = phi_fun(self.M.gridCC)
-        q_ana = q_fun(self.M.gridCC)
-        jX_ana = j_funX(self.M.gridFx)
-        jY_ana = j_funY(self.M.gridFy)
-        j_ana = np.r_[jX_ana,jY_ana,jY_ana]
-
-        # Get boundary locations
-        fxm,fxp,fym,fyp,fzm,fzp = self.M.faceBoundaryInd
-        gBFxm = self.M.gridFx[fxm,:]
-        gBFxp = self.M.gridFx[fxp,:]
-        gBFym = self.M.gridFy[fym,:]
-        gBFyp = self.M.gridFy[fyp,:]
-        gBFzm = self.M.gridFz[fzm,:]
-        gBFzp = self.M.gridFz[fzp,:]
-
-        # Setup Mixed B.C (alpha, beta, gamma)
-        alpha_xm, alpha_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
-        beta_xm, beta_xp =  np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
-        alpha_ym, alpha_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
-        beta_ym, beta_yp =  np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
-        alpha_zm, alpha_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
-        beta_zm, beta_zp =  np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
-
-
-        phi_bc_xm, phi_bc_xp = phi_fun(gBFxm), phi_fun(gBFxp)
-        phi_bc_ym, phi_bc_yp = phi_fun(gBFym), phi_fun(gBFyp)
-        phi_bc_zm, phi_bc_zp = phi_fun(gBFzm), phi_fun(gBFzp)
-
-        phiderivX_bc_xm, phiderivX_bc_xp = phideriv_funX(gBFxm), phideriv_funX(gBFxp)
-        phiderivY_bc_ym, phiderivY_bc_yp = phideriv_funY(gBFym), phideriv_funY(gBFyp)
-        phiderivY_bc_zm, phiderivY_bc_zp = phideriv_funZ(gBFzm), phideriv_funZ(gBFzp)
-
-        gamma_fun = lambda alpha, beta, phi, phi_deriv: alpha*phi + beta*phi_deriv
-        gamma_xm = gamma_fun(alpha_xm, beta_xm, phi_bc_xm, phiderivX_bc_xm)
-        gamma_xp = gamma_fun(alpha_xp, beta_xp, phi_bc_xp, phiderivX_bc_xp)
-        gamma_ym = gamma_fun(alpha_ym, beta_ym, phi_bc_ym, phiderivY_bc_ym)
-        gamma_yp = gamma_fun(alpha_yp, beta_yp, phi_bc_yp, phiderivY_bc_yp)
-        gamma_zm = gamma_fun(alpha_zm, beta_zm, phi_bc_zm, phiderivY_bc_zm)
-        gamma_zp = gamma_fun(alpha_zp, beta_zp, phi_bc_zp, phiderivY_bc_zp)
-
-        alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp, alpha_zm, alpha_zp]
-        beta = [beta_xm, beta_xp, beta_ym, beta_yp, beta_zm, beta_zp]
-        gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp, gamma_zm, gamma_zp]
-
-        x_BC, y_BC = getxBCyBC_CC(self.M, alpha, beta, gamma)
-
-
-        sigma = np.ones(self.M.nC)
-        Mfrho = self.M.getFaceInnerProduct(1./sigma)
-        MfrhoI = self.M.getFaceInnerProduct(1./sigma, invMat=True)
-        V = Utils.sdiag(self.M.vol)
-        Div = V*self.M.faceDiv
-        P_BC, B = self.M.getBCProjWF_simple()
-        q = q_fun(self.M.gridCC)
-        M = B*self.M.aveCC2F
-        G = Div.T - P_BC*Utils.sdiag(y_BC)*M
-        rhs = V*q + Div*MfrhoI*P_BC*x_BC
-        A = Div*MfrhoI*G
-
-        if self.myTest == 'xc':
-            #TODO: fix the null space
-            Ainv = Solver(A)
-            xc = Ainv*rhs
-            err = np.linalg.norm((xc-xc_ana), np.inf)
-        else:
-            NotImplementedError
-        return err
-
-
-    def test_order(self):
-        print "==== Testing Mixed boudary conduction for CC-problem ===="
-        self.name = "3D"
-        self.myTest = 'xc'
-        self.orderTest()
-
-
-
-if __name__ == '__main__':
-    unittest.main()

tests/mesh/test_cylMesh.py

@@ -146,20 +146,6 @@ 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')
@@ -191,37 +177,6 @@ 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')
@@ -230,42 +185,11 @@ class TestCyl2DMesh(unittest.TestCase):
         Pe = Mc.getInterpolationMatCartMesh(Mr, 'E')
         me = np.ones(Mc.nE)
 
-        ecart = Pe * me
+        erect = Pe * me
 
-        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')
+        excc = Mr.aveEx2CC*Mr.r(erect, 'E', 'Ex')
+        eycc = Mr.aveEy2CC*Mr.r(erect, 'E', 'Ey')
+        ezcc = Mr.r(erect, 'E', 'Ez')
 
         indX = Utils.closestPoints(Mr, [0.45, -0.2, 0.5])
         indY = Utils.closestPoints(Mr, [-0.2, 0.45, 0.5])