From 6eafbdca804f3dae9a0b0d1b4461be602ad68772 Mon Sep 17 00:00:00 2001
From: GudniRos <gkrosen@gmail.com>
Date: Thu, 7 May 2015 16:26:35 -0700
Subject: [PATCH] Adding fixes to code.

---
 MT Script-3D_twoHalfspace-simpegMT.ipynb      | 3144 +++++++++++++++++
 simpegMT/ProblemMT.py                         |  111 +-
 simpegMT/SurveyMT.py                          |   11 +-
 ...yerpy => test_ApparentResistivityLayer.py} |    0
 4 files changed, 3204 insertions(+), 62 deletions(-)
 create mode 100644 MT Script-3D_twoHalfspace-simpegMT.ipynb
 rename simpegMT/Tests/{test_ApparentResistivityLayerpy => test_ApparentResistivityLayer.py} (100%)

diff --git a/MT Script-3D_twoHalfspace-simpegMT.ipynb b/MT Script-3D_twoHalfspace-simpegMT.ipynb
new file mode 100644
index 00000000..b9067c19
--- /dev/null
+++ b/MT Script-3D_twoHalfspace-simpegMT.ipynb	
@@ -0,0 +1,3144 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import SimPEG as simpeg\n",
+    "from scipy.constants import mu_0\n",
+    "def omega(freq):\n",
+    "    \"\"\"Change frequency to angular frequency, omega\"\"\"\n",
+    "    return 2.*np.pi*freq"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Populating the interactive namespace from numpy and matplotlib\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pylab inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2529.536000000001"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum(100*np.cumprod(np.ones(5)*1.6))\n",
+    "\n",
+    "   "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# M = Mesh.TensorMesh([[(100.,32)],[(100.,34)],[(100.,18)]], x0='CCC')\n",
+    "# M = simpeg.Mesh.TensorMesh([[(100,5,-1.5),(100.,5),(100,5,1.5)],[(100,5,-1.5),(100.,5),(100,5,1.5)],[(100,5,-1.5),(100.,10),(100,5,1.5)]], x0=['C','C','C'])\n",
+    "M = simpeg.Mesh.TensorMesh([[(1000,6,-1.5),(1000.,6),(1000,6,1.5)],[(1000,6,-1.5),(1000.,2),(1000,6,1.5)],[(1000,10,-1.3),(1000.,2),(1000,10,1.3)]], x0=['C','C','C'])# Setup the model\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[ -5.64053465e+04  -4.26194973e+04  -3.20149979e+04  -2.38576907e+04\n",
+      "  -1.75828390e+04  -1.27560300e+04  -9.04310000e+03  -6.18700000e+03\n",
+      "  -3.99000000e+03  -2.30000000e+03  -1.00000000e+03   7.27595761e-12\n",
+      "   1.00000000e+03   2.30000000e+03   3.99000000e+03   6.18700000e+03\n",
+      "   9.04310000e+03   1.27560300e+04   1.75828390e+04   2.38576907e+04\n",
+      "   3.20149979e+04   4.26194973e+04   5.64053465e+04]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print M.vectorNz"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.colorbar.Colorbar instance at 0x7f32ce3c70e0>"
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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+      ],
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f32cde13450>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
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+       "O50AAAAASUVORK5CYII=\n"
+      ],
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f32cde13850>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Setup the model\n",
+    "# conds = [1,1e-2]\n",
+    "# elev = 300\n",
+    "# sig = simpeg.Utils.ModelBuilder.defineBlock(M.gridCC,[-100000,-100000,-200],[100000,100000,0],conds)\n",
+    "# sig[M.gridCC[:,2]>elev] = 1e-8\n",
+    "# sig[M.gridCC[:,2]<-500] = 1e-1\n",
+    "# sig[M.gridCC[:,2]<-900] = 1e-2\n",
+    "elev=0\n",
+    "conds = [1,1e-2]\n",
+    "sig = np.ones(M.nC)*conds[0]\n",
+    "sig[M.gridCC[:,0]>0] = conds[1]\n",
+    "sig[M.gridCC[:,2]>elev] = 1e-8\n",
+    "# sigBG = np.zeros(M.nC) + conds[0]\n",
+    "# sigBG[M.gridCC[:,2]>0] = 1e-8\n",
+    "sigBG = np.ones(M.nC)*conds[0]\n",
+    "sigBG[M.gridCC[:,2]>elev] = 1e-8\n",
+    "colorbar(M.plotImage(log10(sig)))\n",
+    "colorbar(M.plotImage(log10(sigBG)))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Get the mass matrix \n",
+    "# The model\n",
+    "Msig = M.getEdgeInnerProduct(sig)\n",
+    "MsigBG = M.getEdgeInnerProduct(sigBG)\n",
+    "Mmu = M.getFaceInnerProduct(mu_0, invProp=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "freq = 1.0\n",
+    "C = M.edgeCurl\n",
+    "A = C.T*Mmu*C - 1j*omega(freq)*Msig\n",
+    "ARH = -(C.T*Mmu*C - 1j*omega(freq)*MsigBG)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 13.9 s, sys: 1.17 s, total: 15 s\n",
+      "Wall time: 15 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# Solve the systems for each polarization\n",
+    "Ainv = simpeg.SolverLU(A)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Need to solve x and y polarizations of the source.\n",
+    "from simpegMT.Utils import get1DEfields\n",
+    "# Get a 1d solution for a halfspace background\n",
+    "mesh1d = simpeg.Mesh.TensorMesh([M.hz],np.array([M.x0[2]]))\n",
+    "e0_1d = get1DEfields(mesh1d,M.r(sigBG,'CC','CC','M')[0,0,:],freq,sourceAmp=None).conj()\n",
+    "# Setup the primary field (p) for the x (east) polarization (_px)\n",
+    "ex_px = np.zeros((M.vnEx),dtype=complex)\n",
+    "ey_px = np.zeros(M.nEy,dtype=complex)\n",
+    "ez_px = np.zeros(M.nEz,dtype=complex)\n",
+    "# Assign the source to ex_x\n",
+    "for i in arange(M.vnEx[0]):\n",
+    "    for j in arange(M.vnEx[1]):\n",
+    "        ex_px[i,j,:] = -e0_1d\n",
+    "ep_px = np.r_[simpeg.Utils.mkvc(ex_px),ey_px,ez_px]\n",
+    "rhs_px = ARH.dot(ep_px)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Setup y (north) polarization (_y)\n",
+    "ex_py = np.zeros(M.nEx, dtype='complex128')\n",
+    "ey_py = np.zeros((M.vnEy), dtype='complex128')\n",
+    "ez_py = np.zeros(M.nEz, dtype='complex128')\n",
+    "# Assign the source to ey_y\n",
+    "for i in arange(M.vnEy[0]):\n",
+    "    for j in arange(M.vnEy[1]):\n",
+    "        ey_py[i,j,:] = e0_1d  \n",
+    "        \n",
+    "ep_py = np.r_[ex_py,simpeg.Utils.mkvc(ey_py),ez_py]\n",
+    "rhs_py = ARH.dot(ep_py)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We are using splu in scipy package. This is bit slow, but on the cluster you can use mumps, which might a lot faster. We can think about having better iterative solver. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 146 ms, sys: 73 µs, total: 146 ms\n",
+      "Wall time: 145 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "es_px = Ainv*rhs_px\n",
+    "es_py = Ainv*rhs_py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# Need to sum the ep and es to get the total field.\n",
+    "e_x = es_px #+ ep_px\n",
+    "e_y = es_py #+ ep_py"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "I want to visualize electrical field, which is a vector, so I average them on to cell center. Also I want to see current density ($\\vec{j} = \\sigma \\vec{e}$)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "Meinv = M.getEdgeInnerProduct(np.ones_like(sig), invMat=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "j_x = Meinv*Msig*e_x\n",
+    "j_y = Meinv*Msig*e_x"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(18598,)"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "e_x.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "e_x_CC = M.aveE2CCV*e_x\n",
+    "e_y_CC = M.aveE2CCV*e_y\n",
+    "j_x_CC = M.aveE2CCV*j_x\n",
+    "j_y_CC = M.aveE2CCV*j_y\n",
+    "# j_x_CC = Utils.sdiag(np.r_[sig, sig, sig])*e_x_CC"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then use \"plotSlice\" function, to visualize 2D sections"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
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+       "o9FoNBoH0Um1RqPRaDQajUbjIDqp1mg0Go1Go9FoHOT/AKmCS+vdI8WLAAAAAElFTkSuQmCC\n"
+      ],
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f32ce162250>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1,2, figsize = (12, 5))\n",
+    "dat0 = M.plotSlice(np.log10(np.abs(e_x_CC)), vType='CCv', view='vec', streamOpts={'color': 'k'}, normal='Y', ax = ax[0])\n",
+    "cb0 = plt.colorbar(dat0[0], ax = ax[0])\n",
+    "dat1 = M.plotSlice(np.log10(np.abs(j_x_CC)), vType='CCv', view='vec', streamOpts={'color': 'k'}, normal='Y', ax = ax[1])\n",
+    "cb1 = plt.colorbar(dat1[0], ax = ax[1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Is it reasonable?: Based on that you put resistive target that makes sense to me; current does not want to flow on resistive target so they just do roundabout:). And see air interface. It is continuous on current but not on electric field, which looks reasonable. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Calculate the data\n",
+    "rx_x, rx_y = np.meshgrid(np.arange(-3000,3001,500),np.arange(-1000,1001,500))\n",
+    "rx_loc = np.hstack((simpeg.Utils.mkvc(rx_x,2),simpeg.Utils.mkvc(rx_y,2),elev+np.zeros((np.prod(rx_x.shape),1))))\n",
+    "# Get the projection matrices\n",
+    "Qex = M.getInterpolationMat(rx_loc,'Ex')\n",
+    "Qey = M.getInterpolationMat(rx_loc,'Ey')\n",
+    "Qez = M.getInterpolationMat(rx_loc,'Ez')\n",
+    "Qfx = M.getInterpolationMat(rx_loc,'Fx')\n",
+    "Qfy = M.getInterpolationMat(rx_loc,'Fy')\n",
+    "Qfz = M.getInterpolationMat(rx_loc,'Fz')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "e_x_loc = np.hstack([simpeg.Utils.mkvc(Qex*e_x,2),simpeg.Utils.mkvc(Qey*e_x,2),simpeg.Utils.mkvc(Qez*e_x,2)])\n",
+    "e_y_loc = np.hstack([simpeg.Utils.mkvc(Qex*e_y,2),simpeg.Utils.mkvc(Qey*e_y,2),simpeg.Utils.mkvc(Qez*e_y,2)])\n",
+    "Ciw = -C/(1j*omega(freq)*mu_0)\n",
+    "h_x_loc = np.hstack([simpeg.Utils.mkvc(Qfx*Ciw*e_x,2),simpeg.Utils.mkvc(Qfy*Ciw*e_x,2),simpeg.Utils.mkvc(Qfz*Ciw*e_x,2)])\n",
+    "h_y_loc = np.hstack([simpeg.Utils.mkvc(Qfx*Ciw*e_y,2),simpeg.Utils.mkvc(Qfy*Ciw*e_y,2),simpeg.Utils.mkvc(Qfz*Ciw*e_y,2)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Make a combined matrix\n",
+    "dt = np.dtype([('ex1',complex),('ey1',complex),('ez1',complex),('hx1',complex),('hy1',complex),('hz1',complex),('ex2',complex),('ey2',complex),('ez2',complex),('hx2',complex),('hy2',complex),('hz2',complex)])\n",
+    "combMat = np.empty((len(e_x_loc)),dtype=dt)\n",
+    "combMat['ex1'] = e_x_loc[:,0]\n",
+    "combMat['ey1'] = e_x_loc[:,1]\n",
+    "combMat['ez1'] = e_x_loc[:,2]\n",
+    "combMat['ex2'] = e_y_loc[:,0]\n",
+    "combMat['ey2'] = e_y_loc[:,1]\n",
+    "combMat['ez2'] = e_y_loc[:,2]\n",
+    "combMat['hx1'] = h_x_loc[:,0]\n",
+    "combMat['hy1'] = h_x_loc[:,1]\n",
+    "combMat['hz1'] = h_x_loc[:,2]\n",
+    "combMat['hx2'] = h_y_loc[:,0]\n",
+    "combMat['hy2'] = h_y_loc[:,1]\n",
+    "combMat['hz2'] = h_y_loc[:,2]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def calculateImpedance(fieldsData):\n",
+    "    ''' \n",
+    "    Function that calculates MT impedance data from a rec array with E and H field data from both polarizations\n",
+    "    '''\n",
+    "    zxx = (fieldsData['ex1']*fieldsData['hy2'] - fieldsData['ex2']*fieldsData['hy1'])/(fieldsData['hx1']*fieldsData['hy2'] - fieldsData['hx2']*fieldsData['hy1'])\n",
+    "    zxy = (-fieldsData['ex1']*fieldsData['hx2'] + fieldsData['ex2']*fieldsData['hx1'])/(fieldsData['hx1']*fieldsData['hy2'] - fieldsData['hx2']*fieldsData['hy1'])\n",
+    "    zyx = (fieldsData['ey1']*fieldsData['hy2'] - fieldsData['ey2']*fieldsData['hy1'])/(fieldsData['hx1']*fieldsData['hy2'] - fieldsData['hx2']*fieldsData['hy1'])\n",
+    "    zyy = (-fieldsData['ey1']*fieldsData['hx2'] + fieldsData['ey2']*fieldsData['hx1'])/(fieldsData['hx1']*fieldsData['hy2'] - fieldsData['hx2']*fieldsData['hy1'])\n",
+    "    return zxx, zxy, zyx, zyy\n",
+    "\n",
+    "zxx, zxy, zyx, zyy = calculateImpedance(combMat)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-3000., -1000.,     0.],\n",
+       "       [-3000.,  -500.,     0.],\n",
+       "       [-3000.,     0.,     0.],\n",
+       "       [-3000.,   500.,     0.],\n",
+       "       [-3000.,  1000.,     0.],\n",
+       "       [-2500., -1000.,     0.],\n",
+       "       [-2500.,  -500.,     0.],\n",
+       "       [-2500.,     0.,     0.],\n",
+       "       [-2500.,   500.,     0.],\n",
+       "       [-2500.,  1000.,     0.],\n",
+       "       [-2000., -1000.,     0.],\n",
+       "       [-2000.,  -500.,     0.],\n",
+       "       [-2000.,     0.,     0.],\n",
+       "       [-2000.,   500.,     0.],\n",
+       "       [-2000.,  1000.,     0.],\n",
+       "       [-1500., -1000.,     0.],\n",
+       "       [-1500.,  -500.,     0.],\n",
+       "       [-1500.,     0.,     0.],\n",
+       "       [-1500.,   500.,     0.],\n",
+       "       [-1500.,  1000.,     0.],\n",
+       "       [-1000., -1000.,     0.],\n",
+       "       [-1000.,  -500.,     0.],\n",
+       "       [-1000.,     0.,     0.],\n",
+       "       [-1000.,   500.,     0.],\n",
+       "       [-1000.,  1000.,     0.],\n",
+       "       [ -500., -1000.,     0.],\n",
+       "       [ -500.,  -500.,     0.],\n",
+       "       [ -500.,     0.,     0.],\n",
+       "       [ -500.,   500.,     0.],\n",
+       "       [ -500.,  1000.,     0.],\n",
+       "       [    0., -1000.,     0.],\n",
+       "       [    0.,  -500.,     0.],\n",
+       "       [    0.,     0.,     0.],\n",
+       "       [    0.,   500.,     0.],\n",
+       "       [    0.,  1000.,     0.],\n",
+       "       [  500., -1000.,     0.],\n",
+       "       [  500.,  -500.,     0.],\n",
+       "       [  500.,     0.,     0.],\n",
+       "       [  500.,   500.,     0.],\n",
+       "       [  500.,  1000.,     0.],\n",
+       "       [ 1000., -1000.,     0.],\n",
+       "       [ 1000.,  -500.,     0.],\n",
+       "       [ 1000.,     0.,     0.],\n",
+       "       [ 1000.,   500.,     0.],\n",
+       "       [ 1000.,  1000.,     0.],\n",
+       "       [ 1500., -1000.,     0.],\n",
+       "       [ 1500.,  -500.,     0.],\n",
+       "       [ 1500.,     0.,     0.],\n",
+       "       [ 1500.,   500.,     0.],\n",
+       "       [ 1500.,  1000.,     0.],\n",
+       "       [ 2000., -1000.,     0.],\n",
+       "       [ 2000.,  -500.,     0.],\n",
+       "       [ 2000.,     0.,     0.],\n",
+       "       [ 2000.,   500.,     0.],\n",
+       "       [ 2000.,  1000.,     0.],\n",
+       "       [ 2500., -1000.,     0.],\n",
+       "       [ 2500.,  -500.,     0.],\n",
+       "       [ 2500.,     0.,     0.],\n",
+       "       [ 2500.,   500.,     0.],\n",
+       "       [ 2500.,  1000.,     0.],\n",
+       "       [ 3000., -1000.,     0.],\n",
+       "       [ 3000.,  -500.,     0.],\n",
+       "       [ 3000.,     0.,     0.],\n",
+       "       [ 3000.,   500.,     0.],\n",
+       "       [ 3000.,  1000.,     0.]])"
+      ]
+     },
+     "execution_count": 103,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rx_loc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(array([ 6.56710354]), array([ 58.13551072]))\n",
+      "(array([ 1.37802989]), array([-155.52240108]))\n"
+     ]
+    }
+   ],
+   "source": [
+    "ind = np.where(np.sum(np.power(rx_loc - np.array([-1000,0,elev]),2),axis=1)< 5)\n",
+    "def appResPhs(freq,z):\n",
+    "    app_res = ((1./(8e-7*np.pi**2))/freq)*np.abs(z)**2\n",
+    "    app_phs = np.arctan2(z.imag,z.real)*(180/np.pi)\n",
+    "    return app_res, app_phs\n",
+    "print appResPhs(freq,zyx[ind])\n",
+    "print appResPhs(freq,zxy[ind])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[ 14405.34243898+71568.97959157j] [ -1.45986245e+08 +2.02536180e+08j]\n",
+      "(array([ 1.08290485]), array([-155.59666352]))\n"
+     ]
+    }
+   ],
+   "source": [
+    "e0_1d = e0_1d.conj()\n",
+    "Qex = mesh1d.getInterpolationMat(np.array([elev]),'Ex')\n",
+    "Qfx = mesh1d.getInterpolationMat(np.array([elev]),'Fx')\n",
+    "h0_1dC = -(mesh1d.nodalGrad*e0_1d)/(1j*omega(freq)*mu_0)\n",
+    "h0_1d = mesh1d.getInterpolationMat(mesh1d.vectorNx,'Ex')*h0_1dC\n",
+    "indSur = np.where(mesh1d.vectorNx==elev)\n",
+    "\n",
+    "print (Qfx*e0_1d),(Qex*h0_1dC)#e0_1d, h0_1d\n",
+    "print appResPhs(freq,(Qfx*e0_1d)/(Qex*h0_1dC).conj())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import simpegMT as simpegmt\n",
+    "sig1D = M.r(sig,'CC','CC','M')[0,0,:]\n",
+    "anaEd, anaEu, anaHd, anaHu = simpegmt.Utils.MT1Danalytic.getEHfields(mesh1d,sig1D,freq,mesh1d.vectorNx)\n",
+    "anaEtemp = anaEd+anaEu\n",
+    "anaHtemp = anaHd+anaHu\n",
+    "# Scale the solution\n",
+    "anaE = (anaEtemp/anaEtemp[-1])#.conj()\n",
+    "anaH = (anaHtemp/anaEtemp[-1])#.conj()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[ 0.00019869+0.00019869j  0.00019869+0.00019869j  0.00019869+0.00019869j\n",
+      "  0.00019869+0.00019869j  0.00019869+0.00019869j  0.00019869+0.00019869j\n",
+      "  0.00019869+0.00019869j  0.00019869+0.00019869j  0.00019869+0.00019869j\n",
+      "  0.00019869+0.00019869j  0.00019869+0.00019869j  0.00019869+0.00019869j\n",
+      "  0.00019869+0.00027765j  0.00019869+0.00038029j  0.00019869+0.00051373j\n",
+      "  0.00019869+0.0006872j   0.00019869+0.00091271j  0.00019869+0.00120587j\n",
+      "  0.00019869+0.00158698j  0.00019869+0.00208242j  0.00019869+0.00272649j\n",
+      "  0.00019869+0.00356379j  0.00019870+0.00465228j]\n",
+      "(array([], dtype=float64), array([], dtype=float64))\n",
+      "(array([], dtype=float64), array([], dtype=float64))\n"
+     ]
+    }
+   ],
+   "source": [
+    "anaZ = anaE/anaH\n",
+    "indSur = np.where(mesh1d.vectorNx==elev)\n",
+    "print anaZ\n",
+    "print appResPhs(freq,anaZ[indSur])\n",
+    "print appResPhs(freq,-anaZ[indSur])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ -5.64053465e+04,  -4.26194973e+04,  -3.20149979e+04,\n",
+       "        -2.38576907e+04,  -1.75828390e+04,  -1.27560300e+04,\n",
+       "        -9.04310000e+03,  -6.18700000e+03,  -3.99000000e+03,\n",
+       "        -2.30000000e+03,  -1.00000000e+03,   7.27595761e-12,\n",
+       "         1.00000000e+03,   2.30000000e+03,   3.99000000e+03,\n",
+       "         6.18700000e+03,   9.04310000e+03,   1.27560300e+04,\n",
+       "         1.75828390e+04,   2.38576907e+04,   3.20149979e+04,\n",
+       "         4.26194973e+04,   5.64053465e+04])"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mesh1d.vectorNx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "2.7.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/simpegMT/ProblemMT.py b/simpegMT/ProblemMT.py
index 9967a5d4..f86ab863 100644
--- a/simpegMT/ProblemMT.py
+++ b/simpegMT/ProblemMT.py
@@ -165,11 +165,16 @@ class MTProblem(Problem.BaseProblem):
             :rtype: scipy.sparse.csr_matrix
             :return: A
         """
-        mui = self.MfMui
+        from SimPEG import Mesh
+        Mback = Mesh.TensorMesh(self.mesh.h,self.mesh.x0)
+        Mback.setCellGradBC('dirichlet')
+        mui = Mback.getFaceInnerProduct(1/mu_0)
+        sigmaBG = self.backModel
+        MsigBG = Mback.getEdgeInnerProduct(sigmaBG)
         sigBG = self.MeSigmaBG
-        C = self.mesh.edgeCurl
+        C = Mback.edgeCurl
 
-        return C.T*mui*C - 1j*omega(freq)*sigBG
+        return C.T*mui*C - 1j*omega(freq)*MsigBG
 
     def getADeriv(self, freq, u, v, adjoint=False):
         sig = self.curTModel
@@ -198,7 +203,7 @@ class MTProblem(Problem.BaseProblem):
         eBG_bp = homo1DModelSource(self.mesh,freq,backSigma)
         Abg = self.getAbg(freq)
 
-        return -Abg*eBG_bp, eBG_bp
+        return Abg*eBG_bp, eBG_bp
 
     ##################################################################
     # Inversion stuff
@@ -228,70 +233,72 @@ class MTProblem(Problem.BaseProblem):
 
 
     def Jvec(self, m, v, u=None):
-        if u is None:
-           u = self.fields(m)
+        # if u is None:
+        #    u = self.fields(m)
 
-        self.curModel = m
+        # self.curModel = m
 
-        Jv = self.dataPair(self.survey)
+        # Jv = self.dataPair(self.survey)
 
-        for freq in self.survey.freqs:
-            A = self.getA(freq)
-            solver = self.Solver(A, **self.solverOpts)
+        # for freq in self.survey.freqs:
+        #     A = self.getA(freq)
+        #     solver = self.Solver(A, **self.solverOpts)
 
-            for tx in self.survey.getTransmitters(freq):
-                u_tx = u[tx, self.solType]
-                w = self.getADeriv(freq, u_tx, v)
-                Ainvw = solver.solve(w)
-                for rx in tx.rxList:
-                    fAinvw = self.calcFields(Ainvw, freq, rx.projField)
-                    P = lambda v: rx.projectFieldsDeriv(tx, self.mesh, u, v)
+        #     for tx in self.survey.getTransmitters(freq):
+        #         u_tx = u[tx, self.solType]
+        #         w = self.getADeriv(freq, u_tx, v)
+        #         Ainvw = solver.solve(w)
+        #         for rx in tx.rxList:
+        #             fAinvw = self.calcFields(Ainvw, freq, rx.projField)
+        #             P = lambda v: rx.projectFieldsDeriv(tx, self.mesh, u, v)
 
-                    df_dm = self.calcFieldsDeriv(u_tx, freq, rx.projField, v)
-                    if df_dm is None:
-                        Jv[tx, rx] = - P(fAinvw)
-                    else:
-                        Jv[tx, rx] = - P(fAinvw) + P(df_dm)
+        #             df_dm = self.calcFieldsDeriv(u_tx, freq, rx.projField, v)
+        #             if df_dm is None:
+        #                 Jv[tx, rx] = - P(fAinvw)
+        #             else:
+        #                 Jv[tx, rx] = - P(fAinvw) + P(df_dm)
 
-        return Utils.mkvc(Jv)
+        # return Utils.mkvc(Jv)
+        pass
 
     def Jtvec(self, m, v, u=None):
-        if u is None:
-            u = self.fields(m)
+        # if u is None:
+        #     u = self.fields(m)
 
-        self.curModel = m
+        # self.curModel = m
 
-        # Ensure v is a data object.
-        if not isinstance(v, self.dataPair):
-            v = self.dataPair(self.survey, v)
+        # # Ensure v is a data object.
+        # if not isinstance(v, self.dataPair):
+        #     v = self.dataPair(self.survey, v)
 
-        Jtv = np.zeros(self.mapping.nP)
+        # Jtv = np.zeros(self.mapping.nP)
 
-        for freq in self.survey.freqs:
-            AT = self.getA(freq).T
-            solver = self.Solver(AT, **self.solverOpts)
+        # for freq in self.survey.freqs:
+        #     AT = self.getA(freq).T
+        #     solver = self.Solver(AT, **self.solverOpts)
 
-            for tx in self.survey.getTransmitters(freq):
-                u_tx = u[tx, self.solType]
+        #     for tx in self.survey.getTransmitters(freq):
+        #         u_tx = u[tx, self.solType]
 
-                for rx in tx.rxList:
-                    PTv = rx.projectFieldsDeriv(tx, self.mesh, u, v[tx, rx], adjoint=True)
-                    fPTv = self.calcFields(PTv, freq, rx.projField, adjoint=True)
+        #         for rx in tx.rxList:
+        #             PTv = rx.projectFieldsDeriv(tx, self.mesh, u, v[tx, rx], adjoint=True)
+        #             fPTv = self.calcFields(PTv, freq, rx.projField, adjoint=True)
 
-                    w = solver.solve( fPTv )
-                    Jtv_rx = - self.getADeriv(freq, u_tx, w, adjoint=True)
+        #             w = solver.solve( fPTv )
+        #             Jtv_rx = - self.getADeriv(freq, u_tx, w, adjoint=True)
 
-                    df_dm = self.calcFieldsDeriv(u_tx, freq, rx.projField, PTv, adjoint=True)
+        #             df_dm = self.calcFieldsDeriv(u_tx, freq, rx.projField, PTv, adjoint=True)
 
-                    if df_dm is not None:
-                        Jtv_rx += df_dm
+        #             if df_dm is not None:
+        #                 Jtv_rx += df_dm
 
-                    real_or_imag = rx.projComp
-                    if real_or_imag == 'real':
-                        Jtv +=   Jtv_rx.real
-                    elif real_or_imag == 'imag':
-                        Jtv += - Jtv_rx.real
-                    else:
-                        raise Exception('Must be real or imag')
+        #             real_or_imag = rx.projComp
+        #             if real_or_imag == 'real':
+        #                 Jtv +=   Jtv_rx.real
+        #             elif real_or_imag == 'imag':
+        #                 Jtv += - Jtv_rx.real
+        #             else:
+        #                 raise Exception('Must be real or imag')
 
-        return Jtv
+        # return Jtv
+        pass
\ No newline at end of file
diff --git a/simpegMT/SurveyMT.py b/simpegMT/SurveyMT.py
index 7bc7165e..b2797c62 100644
--- a/simpegMT/SurveyMT.py
+++ b/simpegMT/SurveyMT.py
@@ -129,7 +129,6 @@ class RxMT(Survey.BaseRx):
         return Pv
 
 
-# Call this Source or polarization or something...?
 # Note: Might need to add tests to make sure that both polarization have the same rxList. 
 class srcMT(Survey.BaseSrc):
     '''
@@ -195,7 +194,7 @@ class SurveyMT(Survey.BaseSurvey):
 
     # TODO: Rename to getSources
     def getSources(self, freq):
-        """Returns the transmitters associated with a specific frequency."""
+        """Returns the sources associated with a specific frequency."""
         assert freq in self._freqDict, "The requested frequency is not in this survey."
         return self._freqDict[freq]
 
@@ -270,14 +269,6 @@ class DataMT(Survey.Data):
                     outArr[comp] = outTemp[comp].copy()
                 for comp in ['zxx','zxy','zyx','zyy']:
                     outArr[comp] = outTemp[comp+'r'].copy() + 1j*outTemp[comp+'i'].copy()
-                # for uniFL in uniFLmarr:
-                #     mTemp = mkvc(rec2ndarr(mArrRec[np.ma.where(mArrRec[['freq','x','y','z']].data == np.array(uniFL))][impList]).sum(axis=0),2).T
-                #     compBlock = np.sum(mTemp.data.reshape((4,2))*np.array([[1,1j],[1,1j],[1,1j],[1,1j]]),axis=1).copy().view(dt[4::])
-                #     dataBlock = mkvc(recFunc.merge_arrays((np.array(uniFL),compBlock),flatten=True),2).T
-                #     try:
-                #         outArr = recFunc.stack_arrays((outArr,dataBlock),usemask=False)
-                #     except NameError as e:
-                #         outArr = dataBlock
 
         # Return 
         return outArr
\ No newline at end of file
diff --git a/simpegMT/Tests/test_ApparentResistivityLayerpy b/simpegMT/Tests/test_ApparentResistivityLayer.py
similarity index 100%
rename from simpegMT/Tests/test_ApparentResistivityLayerpy
rename to simpegMT/Tests/test_ApparentResistivityLayer.py