simpeg/notebooks/DCexample.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "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",
      "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"
     ]
    }
   ],
   "source": [
    "from SimPEG import *\n",
    "import simpegDCIP as DC\n",
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cs = 25.\n",
    "hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]\n",
    "hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]\n",
    "hz = [(cs,7, -1.3),(cs,20)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "mesh = Mesh.TensorMesh([hx, hy, hz], 'CCN')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "blk1 = Utils.ModelBuilder.getIndicesBlock(np.r_[-50, 75, -50], np.r_[75, -50, -150], mesh.gridCC)\n",
    "sighalf = 1e-3\n",
    "sigma = np.ones(mesh.nC)*sighalf\n",
    "sigma[blk1] = 1e-1\n",
    "sigmahomo = np.ones(mesh.nC)*sighalf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<matplotlib.collections.QuadMesh at 0x15c5eac8>,\n",
       " <matplotlib.lines.Line2D at 0x15c5ef60>)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nyP8BTq1WovUUtLAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x15940f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mesh.plotSlice(sigma, normal='X', grid=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "xtemp = np.linspace(-150, 150, 21)\n",
    "ytemp = np.linspace(-150, 150, 21)\n",
    "xyz_rxP = Utils.ndgrid(xtemp-10., ytemp, np.r_[0.])\n",
    "xyz_rxN = Utils.ndgrid(xtemp+10., ytemp, np.r_[0.])\n",
    "xyz_rxM = Utils.ndgrid(xtemp, ytemp, np.r_[0.])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x159e1048>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAVIAAAFRCAYAAAAmQSVBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngiikABBEIQWAoP8Phk4K25ESlbsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x15b93f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1, figsize = (5,5))\n",
    "mesh.plotSlice(sigma, grid=True, ax = ax)\n",
    "ax.plot(xyz_rxP[:,0],xyz_rxP[:,1], 'w.')\n",
    "ax.plot(xyz_rxN[:,0],xyz_rxN[:,1], 'r.', ms = 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "rx = DC.RxDipole(xyz_rxP, xyz_rxN)\n",
    "tx = DC.SrcDipole([rx], [-200, 0, -12.5],[+200, 0, -12.5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "survey = DC.SurveyDC([tx])\n",
    "problem = DC.ProblemDC_CC(mesh)\n",
    "problem.pair(survey)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    from pymatsolver import MumpsSolver\n",
    "    problem.Solver = MumpsSolver\n",
    "except Exception, e:\n",
    "    problem.Solver = SolverLU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "No module named pymatsolver",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-10-d6799536a06f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mpymatsolver\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mMumpsSolver\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m: No module named pymatsolver"
     ]
    }
   ],
   "source": [
    "from pymatsolver import MumpsSolver"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "problem.Solver = SolverLU\n",
    "\n",
    "data = survey.dpred(sigmahomo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "u1 = problem.fields(sigma)\n",
    "u2 = problem.fields(sigmahomo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Msig1 = Utils.sdiag(1./(mesh.aveF2CC.T*(1./sigma)))\n",
    "Msig2 = Utils.sdiag(1./(mesh.aveF2CC.T*(1./sigmahomo)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "j1 = Msig1*mesh.cellGrad*u1[tx, 'phi_sol']\n",
    "j2 = Msig2*mesh.cellGrad*u2[tx, 'phi_sol']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for -: 'FieldsDC_CC' and 'FieldsDC_CC'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-22-fd20083b1fc4>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mus\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mu1\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mu2\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mjs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mj1\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mj2\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'FieldsDC_CC' and 'FieldsDC_CC'"
     ]
    }
   ],
   "source": [
    "us = u1-u2\n",
    "js = j1-j2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-300, 0)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZIAAAEZCAYAAAC99aPhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x15fa7860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mesh.plotSlice(mesh.aveF2CCV*j1, vType='CCv', normal='Y', view='vec', streamOpts={\"density\":3, \"color\":'w'})\n",
    "xlim(-300, 300)\n",
    "ylim(-300, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'js' 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-23-575f23801c4a>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mmesh\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplotSlice\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmesh\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0maveF2CCV\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mjs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvType\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'CCv'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnormal\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Y'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mview\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'vec'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstreamOpts\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m{\u001b[0m\u001b[1;34m\"density\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"color\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;34m'w'\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      2\u001b[0m \u001b[0mxlim\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m300\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m300\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mylim\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m300\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;31mNameError\u001b[0m: name 'js' is not defined"
     ]
    }
   ],
   "source": [
    "mesh.plotSlice(mesh.aveF2CCV*js, vType='CCv', normal='Y', view='vec', streamOpts={\"density\":3, \"color\":'w'})\n",
    "xlim(-300, 300)\n",
    "ylim(-300, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "a = np.random.randn(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print (a.reshape([1,-1])).repeat(3, axis = 0)\n",
    "print (a.reshape([1,-1])).repeat(3, axis = 0).sum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def DChalf(txlocP, txlocN, rxloc, sigma, I=1.):\n",
    "    rp = (txlocP.reshape([1,-1])).repeat(rxloc.shape[0], axis = 0)\n",
    "    rn = (txlocN.reshape([1,-1])).repeat(rxloc.shape[0], axis = 0)\n",
    "    rP = np.sqrt(((rxloc-rp)**2).sum(axis=1))\n",
    "    rN = np.sqrt(((rxloc-rn)**2).sum(axis=1))\n",
    "    return I/(sigma*2.*np.pi)*(1/rP-1/rN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data_analP = DChalf(np.r_[-200, 0, 0.],np.r_[+200, 0, 0.], xyz_rxP, sighalf)\n",
    "data_analN = DChalf(np.r_[-200, 0, 0.],np.r_[+200, 0, 0.], xyz_rxN, sighalf)\n",
    "data_anal = data_analP-data_analN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Data_anal = data_anal.reshape((21, 21), order = 'F')\n",
    "Data = data.reshape((21, 21), order = 'F')\n",
    "X = xyz_rxM[:,0].reshape((21, 21), order = 'F')\n",
    "Y = xyz_rxM[:,1].reshape((21, 21), order = 'F')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,2, figsize = (12, 5))\n",
    "vmin = np.r_[data, data_anal].min()\n",
    "vmax = np.r_[data, data_anal].max()\n",
    "dat0 = ax[0].contourf(X, Y, Data, 60, vmin = vmin, vmax = vmax)\n",
    "dat1 = ax[1].contourf(X, Y, Data_anal, 60, vmin = vmin, vmax = vmax)\n",
    "cb0 = plt.colorbar(dat1, orientation = 'horizontal', ax = ax[0])\n",
    "cb1 = plt.colorbar(dat1, orientation = 'horizontal', ax = ax[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "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": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}