Scripts added for the magnetic integral formulation

2026-10-29 13:40:11 +08:00 · 2015-11-10 14:23:29 -08:00
1 parent 6174c6fece
commit 6c71237328
@@ -141,4 +141,50 @@ class WeightMap(Maps.IdentityMap):
        return m*self.weight

    def deriv(self, m):
-        return Utils.sdiag(self.weight)    
+        return Utils.sdiag(self.weight)    
+
+
+    
+
+def readUBCmagObs(obs_file):
+    
+    """
+    Read and write UBC mag file format
+    
+    INPUT:
+    :param fileName, path to the UBC obs mag file
+    
+    OUTPUT:
+    :param dobs, observation in (x y z [data] [wd])
+    :param B, primary field information (BI, BD, B0)
+    :param M, magnetization orentiaton (MI, MD)
+    
+    """
+
+    fid = open(obs_file,'r') 
+
+    # First line has the inclination,declination and amplitude of B0
+    line = fid.readline()
+    B = np.array(line.split(),dtype=float)
+
+    # Second line has the magnetization orientation and a flag 
+    line = fid.readline()
+    M = np.array(line.split(),dtype=float)
+
+    # Third line has the number of rows
+    line = fid.readline()
+    ndat = np.array(line.split(),dtype=int)
+
+    # Pre-allocate space for obsx, obsy, obsz, data, uncert
+    line = fid.readline()
+    temp = np.array(line.split(),dtype=float) 
+        
+    dobs = np.zeros((ndat,len(temp)), dtype=float)
+    
+    
+    for ii in range(ndat):
+        
+        dobs[ii,:] = np.array(line.split(),dtype=float) 
+        line = fid.readline()
+        
+    return B, M, dobs
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@@ -0,0 +1,103 @@
+ 90.00   0.00 50000.00
+ 90.00   0.00   1.00
+100
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+5.000000e-01 5.000000e-01 5.500000e-01 4.996969e-01 0.000000e+00
@@ -0,0 +1,5 @@
+Mesh.msh		! Mesh file
+Obs_loc.dat		! Obsfile		
+Model.dat			! Susceptibility model
+null ! M_azm_dip.dat		! Magnetization model | null
+null				! Topography file | null
@@ -0,0 +1,5 @@
+Mesh.msh		! Mesh file
+Obs_loc.dat	! Obsfile
+null			! Topofile | null
+DISTANCE			! weighting flag DISTANCE | DEPTH
+G				! Define output TxTyTz | G
@@ -0,0 +1,35 @@
+MAG3Csen
+Generates sparse matrices for magnetostatic forward modeling: Tx, Ty, Tz
+Topographic model: nullcell.dat
+DISTANCE | DEPTH weighting: wr.dat
+
+Written by: Dominique Fournier
+Last update: July 14th, 2014
+
+INPUT FILES: 
+Mesh: 			 Mesh.msh 
+Obsfile: 			 Obs_loc.dat 
+Topography: 			  
+Weighting: 			 DISTANCE 
+Computed 0 pct of data in  0.04128 sec
+Computed 5 pct of data in  0.04634 sec
+Computed 10 pct of data in  0.05386 sec
+Computed 15 pct of data in  0.06035 sec
+Computed 20 pct of data in  0.06507 sec
+Computed 25 pct of data in  0.07160 sec
+Computed 30 pct of data in  0.08211 sec
+Computed 35 pct of data in  0.08901 sec
+Computed 40 pct of data in  0.09365 sec
+Computed 45 pct of data in  0.10179 sec
+Computed 50 pct of data in  0.10963 sec
+Computed 55 pct of data in  0.11704 sec
+Computed 60 pct of data in  0.12449 sec
+Computed 65 pct of data in  0.13205 sec
+Computed 70 pct of data in  0.13838 sec
+Computed 75 pct of data in  0.14311 sec
+Computed 80 pct of data in  0.14761 sec
+Computed 85 pct of data in  0.15447 sec
+Computed 90 pct of data in  0.15941 sec
+Computed 95 pct of data in  0.16424 sec
+Computed 100 pct of data in  0.17136 sec
+Sensitivity calculation completed in: 0.002860 min
@@ -0,0 +1,47 @@
+import os
+
+home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\Research\SimPeg'
+
+inpfile = 'MAG3Cfwr.inp'
+
+os.chdir(home_dir)
+
+#%%
+from SimPEG import np, Utils
+from simpegPF import BaseMag
+
+## New scripts to be added to basecode
+from fwr_MAG_obs import fwr_MAG_obs
+from read_MAGfwr_inp import read_MAGfwr_inp
+
+#%%
+# Read input file
+[mshfile, obsfile, modfile, magfile, topofile] = read_MAGfwr_inp(inpfile)
+
+# Load mesh file
+mesh = Utils.meshutils.readUBCTensorMesh(mshfile)
+
+# Load model file
+model = Utils.meshutils.readUBCTensorModel(modfile,mesh)
+    
+# Load in observation file
+[B,M,dobs] = BaseMag.readUBCmagObs(obsfile)
+
+rxLoc = dobs[:,0:3]
+
+# Compute forward model using integral equation
+d = fwr_MAG_obs(xn,yn,zn,B,M,rxLoc,model)
+
+# Form data object with coordinates and write to file
+data = np.c_[rxLoc , d , np.zeros((ndata,1))]
+
+# Save forward data to file
+with file('FWR_data.dat','w') as fid:
+    fid.write('%6.2f %6.2f %6.2f\n' %(B[0], B[1], B[2]) )
+    fid.write('%6.2f %6.2f %6.2f\n' %(M[0], M[1], 1) )  
+    fid.write('%i\n' %(ndata) ) 
+    np.savetxt(fid, data, fmt='%e',delimiter=' ',newline='\n')
+
+print "Observation file saved to " + home_dir + '\FWR_data.dat'
+
+
@@ -0,0 +1,100 @@
+import os
+
+home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\Research\SimPeg'
+
+os.chdir(home_dir)
+
+#%%
+from SimPEG import *
+import matplotlib.pyplot as plt
+import simpegPF as PF
+from simpegPF import BaseMag
+import matplotlib
+
+from fwr_MAG_obs import fwr_MAG_obs
+
+#%% Create survey
+
+B[0] = 90.
+B[1] = 00.
+B[2] = 50000.
+  
+M[0] = 90.
+M[1] = 0.  
+       
+# # Or create juste a plane grid
+xr = np.linspace(-1./2., 1./2., 10)
+yr = np.linspace(-1./2., 1./2., 10)
+X, Y = np.meshgrid(xr, yr)
+Z = np.ones((xr.size, yr.size))*.75
+rxLoc = np.c_[Utils.mkvc(X), Utils.mkvc(Y), Utils.mkvc(Z)]
+
+ndata = rxLoc.shape[0]
+
+#%%
+# Create mesh using simpeg and write out in GIF format
+nc = 30.
+
+hxind = [(1./nc, nc)]
+hyind = [(1./nc, nc)]
+hzind = [(1./nc, nc)]
+
+mesh = Mesh.TensorMesh([hxind, hyind, hzind], 'CCC')
+
+xn = mesh.vectorNx
+yn = mesh.vectorNy
+zn = mesh.vectorNz
+
+mcell = mesh.nC
+
+sph_ind = PF.MagAnalytics.spheremodel(mesh, 0, 0, 0, 0.25)
+
+chibkg = 0.
+chiblk = 0.01
+model = np.ones(mcell)*chibkg
+model[sph_ind] = chiblk
+
+#%% Forward mode ldata
+d = fwr_MAG_obs(xn,yn,zn,B,M,rxLoc,model)
+
+#%% Get the analystical answer and compute the residual
+bxa,bya,bza = PF.MagAnalytics.MagSphereAnaFunA(rxLoc[:,0],rxLoc[:,1],rxLoc[:,2],.25,0.,0.,0.,chiblk, np.array(([0.,0.,B[2]])),'secondary')
+
+r_Bz = mkvc(d) - bza
+lrl = sum( dBz**2 ) **0.5
+
+print "Residual between analytical and integral= " + str(lrl)
+#%% Plot fields
+
+plt.figure(1)
+ax = plt.subplot(131)
+plt.imshow(np.reshape(bxa,X.shape), interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()])
+plt.contour(X,Y, np.reshape(bxa,X.shape),10)
+plt.scatter(X,Y, c='k', s=5)
+ax.set_title('Sphere Ana Bx')
+
+ax = plt.subplot(132)
+plt.imshow(np.reshape(bya,X.shape), interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()])
+plt.contour(X,Y, np.reshape(bya,X.shape),10)
+plt.scatter(X,Y, c='k', s=5)
+ax.set_title('Sphere Ana By')
+
+ax = plt.subplot(133)
+plt.imshow(np.reshape(bza,X.shape), interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()])
+plt.contour(X,Y, np.reshape(bza,X.shape),10)
+plt.scatter(X,Y, c='k', s=5)
+ax.set_title('Sphere Ana Bz')
+#%% Plot foward data
+plt.figure(2)
+plt.subplot(121)
+d2D = np.reshape(d,X.shape)
+plt.imshow(d2D, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()])
+plt.contour(X,Y, d2D,10)
+plt.scatter(X,Y, c='k', s=5)
+
+#%% Compare fields
+
+plt.subplot(122)
+plt.imshow(np.reshape(dBz,X.shape), interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()])
+plt.contour(X,Y, np.reshape(dBz,X.shape),10)
+plt.scatter(X,Y, c='k', s=5)
@@ -6,7 +6,26 @@
   "metadata": {
    "collapsed": false
   },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Efficiency Warning: Interpolation will be slow, use setup.py!\n",
+      "\n",
+      "            python setup.py build_ext --inplace\n",
+      "    \n"
+     ]
+    },
+    {
+     "ename": "SyntaxError",
+     "evalue": "'return' outside function (get_T_mat.py, line 131)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;36m  File \u001b[1;32m\"get_T_mat.py\"\u001b[1;36m, line \u001b[1;32m131\u001b[0m\n\u001b[1;33m    return Tx,Ty,Tz\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m 'return' outside function\n"
+     ]
+    }
+   ],
   "source": [
    "from SimPEG import *\n",
    "import matplotlib.pyplot as plt\n",
@@ -21,9 +40,9 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "# Writing magnetostatic problem with total field formulation\n",
+    "# Writing magnetostatic problem with integral formulation\n",
    "\n",
-    "## - Here we focus on cell-centered system with FVM-Weak form"
+    "## - Create tensor matrix TxTyTz"
   ]
  },
  {
@@ -35,7 +54,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
@@ -63,29 +82,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[-425.15075  -425.15075  -271.950375] [ 425.15075   425.15075   271.950375]\n"
-     ]
-    }
-   ],
-   "source": [
-    "aa.size\n",
-    "print N[0],N[-1]\n",
-    "\n",
-    "Utils.mkvc?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
@@ -98,11 +95,20 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[0 0 0]\n",
+      " [1 1 1]]\n"
+     ]
+    }
+   ],
   "source": [
    "# Load in obsfile\n",
    "#Decl, Incl, B0, Mdec, Minc, obsx, obsy, obsz, data, unct = read_MAG_obs('Obs_RAW_REM_GRID_TMI.obs')\n",
@@ -117,12 +123,18 @@
    "X, Y = np.meshgrid(xr, yr)\n",
    "Z = np.ones((xr.size, yr.size))*280\n",
    "rxLoc = np.c_[Utils.mkvc(X), Utils.mkvc(Y), Utils.mkvc(Z)]\n",
-    "        \n",
+    "     \n",
+    "aa = np.array([[0,0,0],[0,0,0]])\n",
+    "\n",
+    "aa[1,0:3] = 1\n",
+    "print aa\n",
+    "ndata = rxLoc.shape[0]\n",
+    "\n",
    "# Write obsfile in UBC format\n",
-    "fid = open('Obs_loc.dat','w')\n",
-    "fid.write('%6.2f %6.2f %6.2f\\n' %(Incl, Decl, B0) )\n",
-    "fid.write('%6.2f %6.2f %6.2f\\n' %(Incl, Decl, 1) )\n",
-    "fid.close();"
+    "with file('Obs_loc.dat','w') as fid:\n",
+    "    fid.write('%6.2f %6.2f %6.2f\\n' %(Incl, Decl, B0) )\n",
+    "    fid.write('%6.2f %6.2f %6.2f\\n' %(Incl, Decl, 1) )  \n",
+    "    np.savetxt(fid, rxLoc, fmt='%-7.2f',delimiter=' ',newline='\\n')\n"
   ]
  },
  {
@@ -141,73 +153,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "Mx = scipy.sparse.diags(np.ones([mcell])*mx*B0,0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "scipy.sparse.dia.dia_matrix"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type(Mx)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "Mx1 = Utils.sdiag(np.ones([mcell])*mx*B0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "scipy.sparse.csr.csr_matrix"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type(Mx1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
@@ -224,41 +170,31 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0 24\n",
-      "1 24\n",
-      "2 24\n",
-      "3 24\n",
-      "4 24\n",
-      "5 24\n",
-      "6 24\n",
-      "7 24\n"
-     ]
-    },
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
+     "ename": "NameError",
+     "evalue": "name 'empty' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-13-0ffb93de4fd3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# Call the function to build tensor matrix\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mTx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTy\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mget_T_mat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mxn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0myn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mzn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mobsx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mobsy\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mobsz\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;32mprint\u001b[0m \u001b[0mTx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mTy\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mTz\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mC:\\Users\\dominiquef.MIRAGEOSCIENCE\\Documents\\GIT\\SimPEG\\Source\\SimPEGpf\\simpegPF\\notebooks\\get_T_mat.py\u001b[0m in \u001b[0;36mget_T_mat\u001b[1;34m(xn, yn, zn, obsx, obsy, obsz)\u001b[0m\n\u001b[0;32m    103\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    104\u001b[0m                 \u001b[0mR1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mdx2\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mdz1\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 105\u001b[1;33m                 \u001b[0mR2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mdx2\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mdz2\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    106\u001b[0m                 \u001b[0mR3\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mdx1\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mdz1\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    107\u001b[0m                 \u001b[0mR4\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mdx1\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mdz2\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
+      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-44-eff1564841a7>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# Call the function to build tensor matrix\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mTx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mempty\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mndata\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mmcell\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfloat\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[0mTy\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mempty\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mndata\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mmcell\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfloat\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mTz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mempty\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mndata\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mmcell\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfloat\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mNameError\u001b[0m: name 'empty' is not defined"
     ]
    }
   ],
   "source": [
    "# Call the function to build tensor matrix\n",
-    "Tx, Ty, Tz = get_T_mat(xn,yn,zn,obsx[0],obsy[0],obsz[0])\n",
+    "\n",
+    "Tx = empty([ndata,3*mcell], dtype=float)\n",
+    "Ty = empty([ndata,3*mcell], dtype=float)\n",
+    "Tz = empty([ndata,3*mcell], dtype=float)\n",
+    "    \n",
+    "Tx, Ty, Tz = get_T_mat(xn,yn,zn,rxLoc)\n",
    "\n",
    "print Tx[0,0],Ty[0,0],Tz[0,0]\n"
   ]
@@ -334,198 +270,6 @@
    "M3 = Mesh.TensorMesh([hxind, hyind, hzind], 'CCC')"
   ]
  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step2: Compute Boundary indicies and set $\\mathbf{B}_{bc}$"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Step3: Generating model $\\mu$\n",
-    "\n",
-    "$\\mu = \\mu_0(1+\\chi)$"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "mu0 = 4*np.pi*1e-7\n",
-    "chibkg = 0.\n",
-    "chiblk = 0.01\n",
-    "chi = np.ones(M3.nC)*chibkg"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'spheremodel' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-12-72465b2c3978>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msph_ind\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mspheremodel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mM3\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m100\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mchi\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0msph_ind\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mchiblk\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mmu\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m1.\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mchi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mmu0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mNameError\u001b[0m: name 'spheremodel' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "sph_ind = spheremodel(M3, 0, 0, 0, 100)\n",
-    "chi[sph_ind] = chiblk\n",
-    "mu = (1.+chi)*mu0"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\SEOGI\\AppData\\Local\\Enthought\\Canopy\\App\\appdata\\canopy-1.0.1.1189.win-x86_64\\lib\\site-packages\\matplotlib\\lines.py:483: RuntimeWarning: invalid value encountered in greater_equal\n",
-      "  return np.alltrue(x[1:]-x[0:-1]>=0)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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truncated
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x57d1828>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "figsize(10,10)\n",
-    "M3.plotGrid()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0xaa7f390>"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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truncated
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xa0f8ef0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "M3.plotImage(np.log10(mu), imageType='CC')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0\n",
-      "119646\n"
-     ]
-    }
-   ],
-   "source": [
-    "print info\n",
-    "print M3.nC"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0\n",
-      "7.65372604673e-07\n"
-     ]
-    }
-   ],
-   "source": [
-    "B = -MfmuI*D.T*phi\n",
-    "rhsa = A*phi\n",
-    "print info\n",
-    "print np.linalg.norm(rhs-rhsa)/np.linalg.norm(rhs)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### BICG, qmr or BICGstab with Jacobi preconditioner works well (scipy), minres does not work ... Need to play with some other iterative solvers. Remeber that our system has null-space, which is constant"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xaa72208>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "figsize(16,5)\n",
-    "M3.plotImage(B, imageType='F')"
-   ]
-  },
  {
   "cell_type": "markdown",
   "metadata": {},
@@ -555,20 +299,6 @@
    "### Step5: Projection to receiver plane"
   ]
  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "xr = np.linspace(-300, 300, 41)\n",
-    "yr = np.linspace(-300, 300, 41)\n",
-    "X, Y = np.meshgrid(xr, yr)\n",
-    "Z = np.ones((size(xr), size(yr)))*0."
-   ]
-  },
  {
   "cell_type": "code",
   "execution_count": 19,
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@@ -0,0 +1,80 @@
+def fwr_MAG_obs(xn,yn,zn,B,M,rxLoc,model):
+    """ 
+    Forward model magnetic data using integral equation
+    
+    INPUT:
+    xn, yn, zn  = Mesh nodes location
+    B           = Inducing field parameter [Binc, Bdecl, B0]
+    M           = Magnetization matrix [Minc, Mdecl]
+    rxLox       = Observation location informat [obsx, obsy, obsz]
+    model       = Model associated with mesh
+    
+    OUTPUT:
+    dobs        =Observation array in format [obsx, obsy, obsz, data]
+
+    Created on Oct 7, 2015
+
+    @author: dominiquef
+     """ 
+    
+    #%%
+    from SimPEG import np, Utils, sp, mkvc
+    from get_T_mat import get_T_mat
+    
+    mcell = (len(xn)-1) * (len(yn)-1) * (len(zn)-1)
+      
+    ndata = rxLoc.shape[0]    
+    
+    # Convert declination from north to cartesian
+    Md = (450.-float(M[1]))%360.
+    
+    # Create magnetization matrix
+    mx = np.cos(np.deg2rad(M[0])) * np.cos(np.deg2rad(Md))
+    my = np.cos(np.deg2rad(M[0])) * np.sin(np.deg2rad(Md))
+    mz = np.sin(np.deg2rad(M[0]))
+    
+    Mx = Utils.sdiag(np.ones([mcell])*mx*B[2])
+    My = Utils.sdiag(np.ones([mcell])*my*B[2])
+    Mz = Utils.sdiag(np.ones([mcell])*mz*B[2])
+    
+    #matplotlib.pyplot.spy(scipy.sparse.csr_matrix(Mx))
+    #plt.show()
+    Mxyz = sp.vstack((Mx,My,Mz));
+    
+    #%% Create TMI projector
+    
+    # Convert Bdecination from north to cartesian 
+    D = (450.-float(B[1]))%360.
+    
+    Ptmi = mkvc(np.r_[np.cos(np.deg2rad(B[0]))*np.cos(np.deg2rad(D)),np.cos(np.deg2rad(B[0]))*np.sin(np.deg2rad(D)),np.sin(np.deg2rad(B[0]))],2).T;
+    
+    d = np.zeros((ndata,1))
+    
+    # Loop through all observations and create forward operator (ndata-by-mcell)
+    print "Begin forward modeling " +str(int(ndata)) + " data points..."
+    
+    # Add counter to dsiplay progress. Good for large problems
+    progress = -1;
+    for ii in range(ndata):
+    
+        tx, ty, tz = get_T_mat(xn,yn,zn,rxLoc[ii,:])  
+        
+        G = Ptmi.dot(np.vstack((tx,ty,tz)))*Mxyz
+        #%%
+        # Forward operator
+        d[ii,0] = G.dot(model)
+    
+        d_iter = np.floor(float(ii)/float(ndata)*10.);
+        
+        if  d_iter > progress:
+            
+            arg = "Done " + str(d_iter*10) + " %" 
+            print arg
+            progress = d_iter;
+    
+    
+    print "Done 100% ...forward modeling completed!!\n"
+    
+    return d
+
+
@@ -0,0 +1,133 @@
+'''
+Created on Sep 27, 2015
+
+@author: dominiquef
+'''
+def get_T_mat(xn,yn,zn,rxLoc):
+    """ 
+    Load in the nodes of a tensor mesh and computes the magnetic tensor 
+    for a given observation location [obsx, obsy, obsz]
+    OUTPUT:
+    Tx = [Txx Txy Txz]
+    Ty = [Tyx Tyy Tyz]
+    Tz = [Tzx Tzy Tzz]
+
+    where each elements have dimension 1-by-mcell.
+    Only the upper half 5 elements have to be computed since symetric.
+    Currently done as for-loops but will eventually be changed to vector
+    indexing, once the topography has been figured out.
+     """ 
+
+    from SimPEG import np, mkvc
+    
+    ncx = len(xn)-1
+    ncy = len(yn)-1
+    ncz = len(zn)-1
+    
+    mcell = ncx*ncy*ncz
+        
+    # Pre-allocate space for 1D array
+    Tx = np.zeros((1,3*mcell))
+    Ty = np.zeros((1,3*mcell))
+    Tz = np.zeros((1,3*mcell))
+    
+    yn2,xn2,zn2 = np.meshgrid(yn[1:], xn[1:], zn[1:])
+    yn1,xn1,zn1 = np.meshgrid(yn[0:ncy], xn[0:ncx], zn[0:ncz])
+    
+    yn2 = mkvc(yn2)
+    yn1 = mkvc(yn1)
+    
+    zn2 = mkvc(zn2)
+    zn1 = mkvc(zn1)
+    
+    xn2 = mkvc(xn2)
+    xn1 = mkvc(xn1)
+    #%%
+    #==============================================================================
+
+    
+    dz2 = rxLoc[2] - zn1;
+    dz1 = rxLoc[2] - zn2;
+     
+    
+    dy2 = yn2 - rxLoc[1];
+    dy1 = yn1 - rxLoc[1];
+    
+    
+    dx2 = xn2 - rxLoc[0];
+    dx1 = xn1 - rxLoc[0];
+    
+    R1 = ( dy2**2 + dx2**2 );
+    R2 = ( dy2**2 + dx1**2 );
+    R3 = ( dy1**2 + dx2**2 );
+    R4 = ( dy1**2 + dx1**2 );
+    
+    
+    arg1 = np.sqrt( dz2**2 + R2 );
+    arg2 = np.sqrt( dz2**2 + R1 );
+    arg3 = np.sqrt( dz1**2 + R1 );
+    arg4 = np.sqrt( dz1**2 + R2 );
+    arg5 = np.sqrt( dz2**2 + R3 );
+    arg6 = np.sqrt( dz2**2 + R4 );
+    arg7 = np.sqrt( dz1**2 + R4 );
+    arg8 = np.sqrt( dz1**2 + R3 );
+    
+            
+    
+    Tx[0,0:mcell] = np.arctan2( dy1 * dz2 , ( dx2 * arg5 ) ) +\
+                - np.arctan2( dy2 * dz2 , ( dx2 * arg2 ) ) +\
+                np.arctan2( dy2 * dz1 , ( dx2 * arg3 ) ) +\
+                - np.arctan2( dy1 * dz1 , ( dx2 * arg8 ) ) +\
+                np.arctan2( dy2 * dz2  , ( dx1 * arg1 ) ) +\
+                - np.arctan2( dy1 * dz2 , ( dx1 * arg6 ) ) +\
+                np.arctan2( dy1 * dz1 , ( dx1 * arg7 ) ) +\
+                - np.arctan2( dy2 * dz1 , ( dx1 * arg4 ) );
+    
+    
+    Ty[0,0:mcell] = np.log( ( dz2 + arg2 ) / (dz1 + arg3 ) ) +\
+                -np.log( ( dz2 + arg1 ) / (dz1 + arg4 ) ) +\
+                np.log( ( dz2 + arg6 ) / (dz1 + arg7 ) ) +\
+                -np.log( ( dz2 + arg5 ) / (dz1 + arg8 ) );
+    
+    Ty[0,mcell:2*mcell] = np.arctan2( dx1 * dz2 , ( dy2 * arg1 ) ) +\
+                    - np.arctan2( dx2 * dz2 , ( dy2 * arg2 ) ) +\
+                    np.arctan2( dx2 * dz1 , ( dy2 * arg3 ) ) +\
+                    - np.arctan2( dx1 * dz1 , ( dy2 * arg4 ) ) +\
+                    np.arctan2( dx2 * dz2 , ( dy1 * arg5 ) ) +\
+                    - np.arctan2( dx1 * dz2 , ( dy1 * arg6 ) ) +\
+                    np.arctan2( dx1 * dz1 , ( dy1 * arg7 ) ) +\
+                    - np.arctan2( dx2 * dz1 , ( dy1 * arg8 ) );
+    
+    R1 = (dy2**2 + dz1**2);
+    R2 = (dy2**2 + dz2**2);
+    R3 = (dy1**2 + dz1**2);
+    R4 = (dy1**2 + dz2**2);
+    
+    Ty[0,2*mcell:] = np.log( ( dx1 + np.sqrt( dx1**2 + R1 ) ) / (dx2 + np.sqrt( dx2**2 + R1 ) ) ) +\
+                        -np.log( ( dx1 + np.sqrt( dx1**2 + R2 ) ) / (dx2 + np.sqrt( dx2**2 + R2 ) ) ) +\
+                        np.log( ( dx1 + np.sqrt( dx1**2 + R4 ) ) / (dx2 + np.sqrt( dx2**2 + R4 ) ) ) +\
+                        -np.log( ( dx1 + np.sqrt( dx1**2 + R3 ) ) / (dx2 + np.sqrt( dx2**2 + R3 ) ) );
+    
+    R1 = (dx2**2 + dz1**2);
+    R2 = (dx2**2 + dz2**2);
+    R3 = (dx1**2 + dz1**2);
+    R4 = (dx1**2 + dz2**2);
+    
+    Tx[0,2*mcell:] = np.log( ( dy1 + np.sqrt( dy1**2 + R1 ) ) / (dy2 + np.sqrt( dy2**2 + R1 ) ) ) +\
+                        -np.log( ( dy1 + np.sqrt( dy1**2 + R2 ) ) / (dy2 + np.sqrt( dy2**2 + R2 ) ) ) +\
+                        np.log( ( dy1 + np.sqrt( dy1**2 + R4 ) ) / (dy2 + np.sqrt( dy2**2 + R4 ) ) ) +\
+                        -np.log( ( dy1 + np.sqrt( dy1**2 + R3 ) ) / (dy2 + np.sqrt( dy2**2 + R3 ) ) );
+    
+    Tz[0,2*mcell:] = -( Ty[0,mcell:2*mcell] + Tx[0,0:mcell] );
+    Tz[0,mcell:2*mcell] = Ty[0,2*mcell:];
+    Tx[0,mcell:2*mcell] = Ty[0,0:mcell];
+    Tz[0,0:mcell] = Tx[0,2*mcell:];
+    
+    
+    
+    Tx = Tx/(4*np.pi);
+    Ty = Ty/(4*np.pi);
+    Tz = Tz/(4*np.pi);   
+       
+                   
+    return Tx,Ty,Tz
@@ -0,0 +1,31 @@
+
+Parallelized with OpenMP.  # of threads:  4
+
+MAG3D - Version 5.0 :  MAGFOR3D
+
+Developed by University of British Columbia 
+Geophysical Inversion Facility  (UBC-GIF)
+
+(C) Copyright 1992 - 2013, UBC-GIF,
+Department of Earth and Ocean Sciences, UBC
+http://gif.eos.ubc.ca/
+
+This program is licensed to:
+
+ For internal use within UBC-GIF.
+
+
+MAGFOR3D started on: 11/05/2015  14:43:03
+
+
+magfor3d  Mesh.msh Obs_loc.dat Model.dat
+
+           # of surface  data:     625
+           # of borehole data:       0
+ 
+              model was read from file: Model.dat
+ 
+     TOTAL cpu time:   0:00:01.49
+
+MAGFOR3D ended on: 11/05/2015  14:43:04
+
@@ -0,0 +1,628 @@
+     90.00      0.00  50000.00  !! incl, decl, geomag
+     90.00      0.00      1     !! aincl, adecl, idir
+    625                         !! # of data
+ -2.550000000E+01 -2.550000000E+01  2.500000000E+01   -1.236074E+00
+ -2.550000000E+01 -2.337500000E+01  2.500000000E+01    1.500213E+00
+ -2.550000000E+01 -2.125000000E+01  2.500000000E+01    4.762224E+00
+ -2.550000000E+01 -1.912500000E+01  2.500000000E+01    8.540956E+00
+ -2.550000000E+01 -1.700000000E+01  2.500000000E+01    1.278550E+01
+ -2.550000000E+01 -1.487500000E+01  2.500000000E+01    1.739269E+01
+ -2.550000000E+01 -1.275000000E+01  2.500000000E+01    2.220054E+01
+ -2.550000000E+01 -1.062500000E+01  2.500000000E+01    2.698887E+01
+ -2.550000000E+01 -8.500000000E+00  2.500000000E+01    3.148978E+01
+ -2.550000000E+01 -6.375000000E+00  2.500000000E+01    3.540971E+01
+ -2.550000000E+01 -4.250000000E+00  2.500000000E+01    3.846152E+01
+ -2.550000000E+01 -2.125000000E+00  2.500000000E+01    4.040207E+01
+ -2.550000000E+01  0.000000000E+00  2.500000000E+01    4.106811E+01
+ -2.550000000E+01  2.125000000E+00  2.500000000E+01    4.040207E+01
+ -2.550000000E+01  4.250000000E+00  2.500000000E+01    3.846152E+01
+ -2.550000000E+01  6.375000000E+00  2.500000000E+01    3.540971E+01
+ -2.550000000E+01  8.500000000E+00  2.500000000E+01    3.148978E+01
+ -2.550000000E+01  1.062500000E+01  2.500000000E+01    2.698887E+01
+ -2.550000000E+01  1.275000000E+01  2.500000000E+01    2.220054E+01
+ -2.550000000E+01  1.487500000E+01  2.500000000E+01    1.739269E+01
+ -2.550000000E+01  1.700000000E+01  2.500000000E+01    1.278550E+01
+ -2.550000000E+01  1.912500000E+01  2.500000000E+01    8.540956E+00
+ -2.550000000E+01  2.125000000E+01  2.500000000E+01    4.762224E+00
+ -2.550000000E+01  2.337500000E+01  2.500000000E+01    1.500213E+00
+ -2.550000000E+01  2.550000000E+01  2.500000000E+01   -1.236074E+00
+ -2.337500000E+01 -2.550000000E+01  2.500000000E+01    1.500213E+00
+ -2.337500000E+01 -2.337500000E+01  2.500000000E+01    5.120495E+00
+ -2.337500000E+01 -2.125000000E+01  2.500000000E+01    9.462184E+00
+ -2.337500000E+01 -1.912500000E+01  2.500000000E+01    1.452843E+01
+ -2.337500000E+01 -1.700000000E+01  2.500000000E+01    2.026581E+01
+ -2.337500000E+01 -1.487500000E+01  2.500000000E+01    2.654716E+01
+ -2.337500000E+01 -1.275000000E+01  2.500000000E+01    3.315905E+01
+ -2.337500000E+01 -1.062500000E+01  2.500000000E+01    3.979907E+01
+ -2.337500000E+01 -8.500000000E+00  2.500000000E+01    4.608819E+01
+ -2.337500000E+01 -6.375000000E+00  2.500000000E+01    5.160156E+01
+ -2.337500000E+01 -4.250000000E+00  2.500000000E+01    5.591631E+01
+ -2.337500000E+01 -2.125000000E+00  2.500000000E+01    5.866986E+01
+ -2.337500000E+01  0.000000000E+00  2.500000000E+01    5.961669E+01
+ -2.337500000E+01  2.125000000E+00  2.500000000E+01    5.866986E+01
+ -2.337500000E+01  4.250000000E+00  2.500000000E+01    5.591631E+01
+ -2.337500000E+01  6.375000000E+00  2.500000000E+01    5.160156E+01
+ -2.337500000E+01  8.500000000E+00  2.500000000E+01    4.608819E+01
+ -2.337500000E+01  1.062500000E+01  2.500000000E+01    3.979907E+01
+ -2.337500000E+01  1.275000000E+01  2.500000000E+01    3.315905E+01
+ -2.337500000E+01  1.487500000E+01  2.500000000E+01    2.654716E+01
+ -2.337500000E+01  1.700000000E+01  2.500000000E+01    2.026581E+01
+ -2.337500000E+01  1.912500000E+01  2.500000000E+01    1.452843E+01
+ -2.337500000E+01  2.125000000E+01  2.500000000E+01    9.462184E+00
+ -2.337500000E+01  2.337500000E+01  2.500000000E+01    5.120495E+00
+ -2.337500000E+01  2.550000000E+01  2.500000000E+01    1.500213E+00
+ -2.125000000E+01 -2.550000000E+01  2.500000000E+01    4.762224E+00
+ -2.125000000E+01 -2.337500000E+01  2.500000000E+01    9.462184E+00
+ -2.125000000E+01 -2.125000000E+01  2.500000000E+01    1.514079E+01
+ -2.125000000E+01 -1.912500000E+01  2.500000000E+01    2.182415E+01
+ -2.125000000E+01 -1.700000000E+01  2.500000000E+01    2.946374E+01
+ -2.125000000E+01 -1.487500000E+01  2.500000000E+01    3.790908E+01
+ -2.125000000E+01 -1.275000000E+01  2.500000000E+01    4.688522E+01
+ -2.125000000E+01 -1.062500000E+01  2.500000000E+01    5.598335E+01
+ -2.125000000E+01 -8.500000000E+00  2.500000000E+01    6.467387E+01
+ -2.125000000E+01 -6.375000000E+00  2.500000000E+01    7.234807E+01
+ -2.125000000E+01 -4.250000000E+00  2.500000000E+01    7.838868E+01
+ -2.125000000E+01 -2.125000000E+00  2.500000000E+01    8.225910E+01
+ -2.125000000E+01  0.000000000E+00  2.500000000E+01    8.359270E+01
+ -2.125000000E+01  2.125000000E+00  2.500000000E+01    8.225910E+01
+ -2.125000000E+01  4.250000000E+00  2.500000000E+01    7.838868E+01
+ -2.125000000E+01  6.375000000E+00  2.500000000E+01    7.234807E+01
+ -2.125000000E+01  8.500000000E+00  2.500000000E+01    6.467387E+01
+ -2.125000000E+01  1.062500000E+01  2.500000000E+01    5.598335E+01
+ -2.125000000E+01  1.275000000E+01  2.500000000E+01    4.688522E+01
+ -2.125000000E+01  1.487500000E+01  2.500000000E+01    3.790908E+01
+ -2.125000000E+01  1.700000000E+01  2.500000000E+01    2.946374E+01
+ -2.125000000E+01  1.912500000E+01  2.500000000E+01    2.182415E+01
+ -2.125000000E+01  2.125000000E+01  2.500000000E+01    1.514079E+01
+ -2.125000000E+01  2.337500000E+01  2.500000000E+01    9.462184E+00
+ -2.125000000E+01  2.550000000E+01  2.500000000E+01    4.762224E+00
+ -1.912500000E+01 -2.550000000E+01  2.500000000E+01    8.540956E+00
+ -1.912500000E+01 -2.337500000E+01  2.500000000E+01    1.452843E+01
+ -1.912500000E+01 -2.125000000E+01  2.500000000E+01    2.182415E+01
+ -1.912500000E+01 -1.912500000E+01  2.500000000E+01    3.049265E+01
+ -1.912500000E+01 -1.700000000E+01  2.500000000E+01    4.050278E+01
+ -1.912500000E+01 -1.487500000E+01  2.500000000E+01    5.168563E+01
+ -1.912500000E+01 -1.275000000E+01  2.500000000E+01    6.369637E+01
+ -1.912500000E+01 -1.062500000E+01  2.500000000E+01    7.599288E+01
+ -1.912500000E+01 -8.500000000E+00  2.500000000E+01    8.784643E+01
+ -1.912500000E+01 -6.375000000E+00  2.500000000E+01    9.839660E+01
+ -1.912500000E+01 -4.250000000E+00  2.500000000E+01    1.067531E+02
+ -1.912500000E+01 -2.125000000E+00  2.500000000E+01    1.121307E+02
+ -1.912500000E+01  0.000000000E+00  2.500000000E+01    1.139877E+02
+ -1.912500000E+01  2.125000000E+00  2.500000000E+01    1.121307E+02
+ -1.912500000E+01  4.250000000E+00  2.500000000E+01    1.067531E+02
+ -1.912500000E+01  6.375000000E+00  2.500000000E+01    9.839660E+01
+ -1.912500000E+01  8.500000000E+00  2.500000000E+01    8.784643E+01
+ -1.912500000E+01  1.062500000E+01  2.500000000E+01    7.599288E+01
+ -1.912500000E+01  1.275000000E+01  2.500000000E+01    6.369637E+01
+ -1.912500000E+01  1.487500000E+01  2.500000000E+01    5.168563E+01
+ -1.912500000E+01  1.700000000E+01  2.500000000E+01    4.050278E+01
+ -1.912500000E+01  1.912500000E+01  2.500000000E+01    3.049265E+01
+ -1.912500000E+01  2.125000000E+01  2.500000000E+01    2.182415E+01
+ -1.912500000E+01  2.337500000E+01  2.500000000E+01    1.452843E+01
+ -1.912500000E+01  2.550000000E+01  2.500000000E+01    8.540956E+00
+ -1.700000000E+01 -2.550000000E+01  2.500000000E+01    1.278550E+01
+ -1.700000000E+01 -2.337500000E+01  2.500000000E+01    2.026581E+01
+ -1.700000000E+01 -2.125000000E+01  2.500000000E+01    2.946374E+01
+ -1.700000000E+01 -1.912500000E+01  2.500000000E+01    4.050278E+01
+ -1.700000000E+01 -1.700000000E+01  2.500000000E+01    5.338768E+01
+ -1.700000000E+01 -1.487500000E+01  2.500000000E+01    6.794195E+01
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+ -1.700000000E+01 -1.062500000E+01  2.500000000E+01    1.000988E+02
+ -1.700000000E+01 -8.500000000E+00  2.500000000E+01    1.160147E+02
+ -1.700000000E+01 -6.375000000E+00  2.500000000E+01    1.302989E+02
+ -1.700000000E+01 -4.250000000E+00  2.500000000E+01    1.416880E+02
+ -1.700000000E+01 -2.125000000E+00  2.500000000E+01    1.490509E+02
+ -1.700000000E+01  0.000000000E+00  2.500000000E+01    1.515995E+02
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+ -1.700000000E+01  2.125000000E+01  2.500000000E+01    2.946374E+01
+ -1.700000000E+01  2.337500000E+01  2.500000000E+01    2.026581E+01
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+ -1.487500000E+01 -1.062500000E+01  2.500000000E+01    1.282329E+02
+ -1.487500000E+01 -8.500000000E+00  2.500000000E+01    1.491979E+02
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+ -1.487500000E+01  1.275000000E+01  2.500000000E+01    1.069050E+02
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+ -1.275000000E+01  1.700000000E+01  2.500000000E+01    8.374661E+01
+ -1.275000000E+01  1.912500000E+01  2.500000000E+01    6.369637E+01
+ -1.275000000E+01  2.125000000E+01  2.500000000E+01    4.688522E+01
+ -1.275000000E+01  2.337500000E+01  2.500000000E+01    3.315905E+01
+ -1.275000000E+01  2.550000000E+01  2.500000000E+01    2.220054E+01
+ -1.062500000E+01 -2.550000000E+01  2.500000000E+01    2.698887E+01
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@@ -0,0 +1,27 @@
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
+   1.0000000e+00
@@ -12,21 +12,21 @@ def read_MAG_obs(obs_file):

    # First line has the declination, inclination and amplitude of B0
    line = fid.readline()
-    line = line.split(' ')
+    line = line.split()
    Incl = float(line[0]) 
    Decl = float(line[1])
    B0   = float(line[2])

    # Second line has the magnetization orientation and a flag 
    line = fid.readline()
-    line = line.split(' ')
+    line = line.split()
    Minc = float(line[0])
    Mdec = float(line[1])
    FLAG = float(line[2])

    # Third line has the number of rows
    line = fid.readline()
-    line = line.split(' ')
+    line = line.split()
    ndat = int(line[0])

    # Pre-allocate space for obsx, obsy, obsz, data, uncert
@@ -39,7 +39,7 @@ def read_MAG_obs(obs_file):
    for ii in range(ndat):

        line = fid.readline()
-        line = line.split(' ')  
+        line = line.split()  

        obsx[ii] = line[0]
        obsy[ii] = line[1]
@@ -0,0 +1,52 @@
+def read_MAGfwr_inp(input_file):
+    """Read input files for forward modeling MAG data with integral form
+    INPUT:
+    input_file: File name containing the forward parameter
+    
+    OUTPUT:
+    mshfile
+    obsfile
+    modfile
+    magfile
+    topofile
+    # All files should be in the working directory, otherwise the path must
+    # be specified.
+
+    Created on Jul 17, 2013
+    
+    @author: dominiquef
+    """
+
+    
+    fid = open(input_file,'r')
+    
+    line = fid.readline()
+    l_input  = line.split('!')
+    mshfile = l_input[0].rstrip()
+    
+    line = fid.readline()
+    l_input  = line.split('!')
+    obsfile = l_input[0].rstrip()
+    
+    line = fid.readline()
+    l_input = line.split('!') 
+    modfile = l_input[0].rstrip()
+    
+    line = fid.readline()
+    l_input = line.split('!') 
+    if l_input=='null':
+        magfile = []
+        
+    else:
+        magfile = l_input[0].rstrip()
+        
+        
+    line = fid.readline()
+    l_input = line.split('!') 
+    if l_input=='null':
+        topofile = []
+        
+    else:
+        topofile = l_input[0].rstrip()
+      
+    return mshfile, obsfile, modfile, magfile, topofile
@@ -0,0 +1,3 @@
+0.000000000000000000e+00 1.000000000000000000e+00 2.000000000000000000e+00 3.000000000000000000e+00 4.000000000000000000e+00
+0.000000000000000000e+00 1.000000000000000000e+00 2.000000000000000000e+00 3.000000000000000000e+00 4.000000000000000000e+00
+0.000000000000000000e+00 1.000000000000000000e+00 2.000000000000000000e+00 3.000000000000000000e+00 4.000000000000000000e+00
@@ -0,0 +1,27 @@
+   9.8795652e-01
+   5.5014643e-01
+   3.6763740e-01
+   9.9389003e-01
+   5.5768086e-01
+   3.7348300e-01
+   9.8795652e-01
+   5.5014643e-01
+   3.6763740e-01
+   9.9389003e-01
+   5.5768086e-01
+   3.7348300e-01
+   1.0000000e+00
+   5.6536871e-01
+   3.7943638e-01
+   9.9389003e-01
+   5.5768086e-01
+   3.7348300e-01
+   9.8795652e-01
+   5.5014643e-01
+   3.6763740e-01
+   9.9389003e-01
+   5.5768086e-01
+   3.7348300e-01
+   9.8795652e-01
+   5.5014643e-01
+   3.6763740e-01
@@ -0,0 +1,18 @@
+from BaseMag import BaseMagSurvey
+
+class MagSurveyIE(BaseMagSurvey):
+    """Base Magnetics Survey"""
+
+    rxLoc = None #: receiver locations
+    rxType = None #: receiver type
+
+    def __init__(self, **kwargs):
+        Survey.BaseSurvey.__init__(self, **kwargs)
+
+    def setBackgroundField(self, Inc, Dec, Btot):
+
+        Bx = Btot*np.cos(Inc/180.*np.pi)*np.sin(Dec/180.*np.pi)
+        By = Btot*np.cos(Inc/180.*np.pi)*np.cos(Dec/180.*np.pi)
+        Bz = -Btot*np.sin(Inc/180.*np.pi)
+
+        self.B0 = np.r_[Bx,By,Bz]
@@ -2,20 +2,24 @@
 "cells": [
  {
   "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
-     "ename": "ImportError",
-     "evalue": "No module named SeogiUtils",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-1-9621b2e4677d>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0msimpegPF\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mMagAnalytics\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mspheremodel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCongruousMagBC\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0msimpegPF\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mMagnetics\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mMagneticsDiffSecondary\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mMagneticsDiffSecondaryInv\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mSeogiUtils\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mSeUtils\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      7\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0msimpegEM\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mUtils\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSolver\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mMumps\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mMumps\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'pylab inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mImportError\u001b[0m: No module named SeogiUtils"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Populating the interactive namespace from numpy and matplotlib\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: pylab import has clobbered these variables: ['linalg']\n",
+      "`%matplotlib` prevents importing * from pylab and numpy\n"
     ]
    }
   ],
@@ -25,8 +29,8 @@
    "from scipy.constants import mu_0\n",
    "from simpegPF.MagAnalytics import spheremodel, CongruousMagBC\n",
    "from simpegPF.Magnetics import MagneticsDiffSecondary, MagneticsDiffSecondaryInv\n",
-    "import SeogiUtils as SeUtils\n",
-    "import simpegEM.Utils.Solver.Mumps as Mumps\n",
+    "# import SeogiUtils as SeUtils\n",
+    "# import simpegEM.Utils.Solver.Mumps as Mumps\n",
    "%pylab inline"
   ]
  },
@@ -41,7 +45,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
@@ -65,7 +69,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
@@ -89,7 +93,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
@@ -100,7 +104,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
@@ -112,7 +116,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
@@ -123,15 +127,15 @@
       "(-500, 0)"
      ]
     },
-     "execution_count": 29,
+     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
-      "image/png": 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truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAVwAAAEmCAYAAAAuryiLAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
      "text/plain": [
-       "<matplotlib.figure.Figure at 0x4593050>"
+       "<matplotlib.figure.Figure at 0x18eab5f8>"
      ]
     },
     "metadata": {},
@@ -140,14 +144,14 @@
   ],
   "source": [
    "fig, ax = plt.subplots(1,1, figsize = (5, 5))\n",
-    "dat1 = mesh.plotSlice(rmap*test, ax = ax, normal = 'X')\n",
+    "dat1 = mesh.plotSlice(chi, ax = ax, normal = 'X')\n",
    "plt.colorbar(dat1[0], orientation=\"horizontal\", ax = ax)\n",
    "ax.set_ylim(-500, 0)"
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
@@ -156,8 +160,8 @@
     "name": "stdout",
     "output_type": "stream",
     "text": [
-      "(33620,)\n",
-      "(67240,)\n"
+      "(33620L,)\n",
+      "(67240L,)\n"
     ]
    }
   ],
@@ -175,7 +179,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
@@ -186,7 +190,17 @@
    "Inc = 90.\n",
    "Dec = 0.\n",
    "Btot = 51000\n",
-    "survey.setBackgroundField(Inc, Dec, Btot)\n",
+    "survey.setBackgroundField(Inc, Dec, Btot)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
    "xr = np.linspace(-300, 300, 81)\n",
    "yr = np.linspace(-300, 300, 81)\n",
    "X, Y = np.meshgrid(xr, yr)\n",
@@ -1,5 +0,0 @@
-31 31 25
-425.15 -425.15 271.95
-92.82 71.40 54.93 42.25 32.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 32.50 42.25 54.93 71.40 92.82 
-92.82 71.40 54.93 42.25 32.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 32.50 42.25 54.93 71.40 92.82 
-12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 12.50 32.50 42.25 54.93 71.40 92.82 
@@ -1,2 +0,0 @@
- 90.00   0.00 50000.00
- 90.00   0.00   1.00
@@ -0,0 +1,36 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "obs = BaseMag.UBCmagObs('Obs_loc.dat')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
@@ -1,127 +0,0 @@
-'''
-Created on Sep 27, 2015
-
-@author: dominiquef
-'''
-def get_T_mat(xn,yn,zn,obsx,obsy,obsz):
-    """ 
-    Load in the nodes of a tensor mesh and computes the magnetic tensor 
-    for a given observation location [obsx, obsy, obsz]
-    OUTPUT:
-    Tx = [Txx Txy Txz]
-    Ty = [Tyx Tyy Tyz]
-    Tz = [Tzx Tzy Tzz]
-
-    where each elements have dimension 1-by-mcell.
-    Only the upper half 5 elements have to be computed since symetric.
-    Currently done as for-loops but will eventually be changed to vector
-    indexing, once the topography has been figured out.
-     """ 
-
-    from numpy import empty, pi, log, arctan, sqrt, shape
-    
-    ncx = len(xn)-1
-    ncy = len(yn)-1
-    ncz = len(zn)-1
-    
-    mcell = ncx*ncy*ncz;
-
-    Tx = empty([1,3*mcell], dtype=float)
-    Ty = empty([1,3*mcell], dtype=float)
-    Tz = empty([1,3*mcell], dtype=float)
-
-    count = 0
-
-    
-    for ii in range(ncz):
-
-        print ii, ncz
-
-        dz2 = zn[ii] - obsz;
-        dz1 = zn[ii+1] - obsz;
-
-        for jj in range(ncy): 
-
-            dy2 = yn[jj] - obsy;
-            dy1 = yn[jj+1] - obsy;
-
-            for kk in range(ncx):   
-
-                dx2 = xn[kk] - obsx;
-                dx1 = xn[kk+1] - obsx;
-
-                R1 = ( dy2**2 + dx2**2 );
-                R2 = ( dy2**2 + dx1**2 );
-                R3 = ( dy1**2 + dx2**2 );
-                R4 = ( dy1**2 + dx1**2 );
-
-                arg1 = sqrt( dz2**2 + R2 );
-                arg2 = sqrt( dz2**2 + R1 );
-                arg3 = sqrt( dz1**2 + R1 );
-                arg4 = sqrt( dz1**2 + R2 );
-                arg5 = sqrt( dz2**2 + R3 );
-                arg6 = sqrt( dz2**2 + R4 );
-                arg7 = sqrt( dz1**2 + R4 );
-                arg8 = sqrt( dz1**2 + R3 );
-
-                
-
-                Tx[0,count] = arctan( dy1 * dz2 / ( dx2 * arg5 ) ) +\
-                            - arctan( dy2 * dz2 / ( dx2 * arg2 ) ) +\
-                            arctan( dy2 * dz1 / ( dx2 * arg3 ) ) +\
-                            - arctan( dy1 * dz1 / ( dx2 * arg8 ) ) +\
-                            arctan( dy2 * dz2 / ( dx1 * arg1 ) ) +\
-                            - arctan( dy1 * dz2 / ( dx1 * arg6 ) ) +\
-                            arctan( dy1 * dz1 / ( dx1 * arg7 ) ) +\
-                            - arctan( dy2 * dz1 / ( dx1 * arg4 ) );
-
-
-                Ty[0,count] = log( ( dz2 + arg2 ) / (dz1 + arg3 ) ) +\
-                            -log( ( dz2 + arg1 ) / (dz1 + arg4 ) ) +\
-                            log( ( dz2 + arg6 ) / (dz1 + arg7 ) ) +\
-                            -log( ( dz2 + arg5 ) / (dz1 + arg8 ) );
-
-
-                Ty[0,mcell+count] = arctan( dx1 * dz2 / ( dy2 * arg1 ) ) +\
-                                - arctan( dx2 * dz2 / ( dy2 * arg2 ) ) +\
-                                arctan( dx2 * dz1 / ( dy2 * arg3 ) ) +\
-                                - arctan( dx1 * dz1 / ( dy2 * arg4 ) ) +\
-                                arctan( dx2 * dz2 / ( dy1 * arg5 ) ) +\
-                                - arctan( dx1 * dz2 / ( dy1 * arg6 ) ) +\
-                                arctan( dx1 * dz1 / ( dy1 * arg7 ) ) +\
-                                - arctan( dx2 * dz1 / ( dy1 * arg8 ) );
-
-                R1 = (dy2**2 + dz1**2);
-                R2 = (dy2**2 + dz2**2);
-                R3 = (dy1**2 + dz1**2);
-                R4 = (dy1**2 + dz2**2);
-
-                Ty[0,2*mcell+count] = log( ( dx1 + sqrt( dx1**2 + R1 ) ) / (dx2 + sqrt( dx2**2 + R1 ) ) ) +\
-                                    -log( ( dx1 + sqrt( dx1**2 + R2 ) ) / (dx2 + sqrt( dx2**2 + R2 ) ) ) +\
-                                    log( ( dx1 + sqrt( dx1**2 + R4 ) ) / (dx2 + sqrt( dx2**2 + R4 ) ) ) +\
-                                    -log( ( dx1 + sqrt( dx1**2 + R3 ) ) / (dx2 + sqrt( dx2**2 + R3 ) ) );
-
-                R1 = (dx2**2 + dz1**2);
-                R2 = (dx2**2 + dz2**2);
-                R3 = (dx1**2 + dz1**2);
-                R4 = (dx1**2 + dz2**2);
-
-                Tx[0,2*mcell+count] = log( ( dy1 + sqrt( dy1**2 + R1 ) ) / (dy2 + sqrt( dy2**2 + R1 ) ) ) +\
-                                    -log( ( dy1 + sqrt( dy1**2 + R2 ) ) / (dy2 + sqrt( dy2**2 + R2 ) ) ) +\
-                                    log( ( dy1 + sqrt( dy1**2 + R4 ) ) / (dy2 + sqrt( dy2**2 + R4 ) ) ) +\
-                                    -log( ( dy1 + sqrt( dy1**2 + R3 ) ) / (dy2 + sqrt( dy2**2 + R3 ) ) );
-
-                Tz[0,2*mcell+count] = -( Ty[0,mcell+count] + Tx[0,count] );
-                Tz[0,mcell+count] = Ty[0,2*mcell+count];
-                Tx[0,mcell+count] = Ty[0,count];
-                Tz[0,count] = Tx[0,2*mcell+count];
-
-
-
-                count = count + 1
-
-    Tx = Tx/(4*pi);
-    Ty = Ty/(4*pi);
-    Tz = Tz/(4*pi);        
-                   
-    return Tx,Ty,Tz