simpeg/simpegPF/notebooks/MagInversion.ipynb

{
 "cells": [
  {
   "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"
     ]
    },
    {
     "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",
    "from simpegPF import BaseMag\n",
    "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",
    "from pymatsolver import MumpsSolver\n",
    "%pylab inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mag Inversion\n",
    "\n",
    "## Step1: Generating mesh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cs = 25.\n",
    "hxind = [(cs,5,-1.3), (cs, 31),(cs,5,1.3)]\n",
    "hyind = [(cs,5,-1.3), (cs, 31),(cs,5,1.3)]\n",
    "hzind = [(cs,5,-1.3), (cs, 30),(cs,5,1.3)]\n",
    "mesh = Mesh.TensorMesh([hxind, hyind, hzind], 'CCC')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step2: Generating Model: Use Combo model\n",
    "\n",
    "### Here we combined $\\mu$ model$^1$, Depth model$^2$ and Active model$^3$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "chibkg = 1e-5\n",
    "chiblk = 0.1\n",
    "chi = np.ones(mesh.nC)*chibkg\n",
    "sph_ind = spheremodel(mesh, 0., 0., -150., 80)\n",
    "chi[sph_ind] = chiblk\n",
    "active = mesh.gridCC[:,2]<0\n",
    "actMap = Maps.ActiveCells(mesh, active, chibkg)\n",
    "dweight = np.ones(mesh.nC)\n",
    "dweight[active] = (1/abs(mesh.gridCC[active, 2]-13.)**1.5)\n",
    "baseMap = BaseMag.BaseMagMap(mesh)\n",
    "depthMap = BaseMag.WeightMap(mesh, dweight)\n",
    "dmap = baseMap*actMap\n",
    "rmap = depthMap*actMap\n",
    "model = (chi)[active]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sph_ind_ini = spheremodel(mesh, 0., 0., -200., 150)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "chi_ini = np.ones_like(chi)*chibkg\n",
    "chi_ini[sph_ind_ini] = chiblk*0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-500, 0)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112bcd750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1, figsize = (5, 5))\n",
    "dat1 = mesh.plotSlice(rmap*model, ax = ax, normal = 'X')\n",
    "plt.colorbar(dat1[0], orientation=\"horizontal\", ax = ax)\n",
    "ax.set_ylim(-500, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(33620,)\n",
      "(67240,)\n"
     ]
    }
   ],
   "source": [
    "print model.shape\n",
    "print chi.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step3: Generating Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "survey = BaseMag.BaseMagSurvey()\n",
    "const = 20\n",
    "Inc = 90.\n",
    "Dec = 0.\n",
    "Btot = 51000\n",
    "survey.setBackgroundField(Inc, Dec, Btot)\n",
    "xr = np.linspace(-300, 300, 81)\n",
    "yr = np.linspace(-300, 300, 81)\n",
    "X, Y = np.meshgrid(xr, yr)\n",
    "Z = np.ones((xr.size, yr.size))*(0.)\n",
    "rxLoc = np.c_[Utils.mkvc(X), Utils.mkvc(Y), Utils.mkvc(Z)]\n",
    "survey.rxLoc = rxLoc\n",
    "prob = MagneticsDiffSecondary(mesh, mapping = dmap)\n",
    "prob.pair(survey)\n",
    "prob.Solver = MumpsSolver"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'NotImplementedType' object is not callable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-12-63f359d726f9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdsyn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msurvey\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdpred\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/Users/sgkang/Projects/simpeg/SimPEG/Utils/CounterUtils.pyc\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m     81\u001b[0m         \u001b[0mcounter\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'counter'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     82\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcounter\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mCounter\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mcounter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;34m'.'\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 83\u001b[0;31m         \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     84\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/sgkang/Projects/simpeg/SimPEG/Utils/codeutils.pyc\u001b[0m in \u001b[0;36mrequiresVarWrapper\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    221\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvar\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    222\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mextra\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 223\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    224\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    225\u001b[0m         \u001b[0mdoc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrequiresVarWrapper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/sgkang/Projects/simpeg/SimPEG/Survey.pyc\u001b[0m in \u001b[0;36mdpred\u001b[0;34m(self, m, u)\u001b[0m\n\u001b[1;32m    307\u001b[0m         \"\"\"\n\u001b[1;32m    308\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mu\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mu\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfields\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 309\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mUtils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmkvc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mu\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    310\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    311\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/sgkang/Projects/simpeg/SimPEG/Utils/CounterUtils.pyc\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m     81\u001b[0m         \u001b[0mcounter\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'counter'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     82\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcounter\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mCounter\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mcounter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;34m'.'\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 83\u001b[0;31m         \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     84\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/sgkang/Projects/simpeg/SimPEG/Survey.pyc\u001b[0m in \u001b[0;36meval\u001b[0;34m(self, u)\u001b[0m\n\u001b[1;32m    320\u001b[0m                 \u001b[0md_\u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mpred\u001b[0m\u001b[0;34m}\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0mmathbf\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mP\u001b[0m\u001b[0;34m}\u001b[0m \u001b[0mu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    321\u001b[0m         \"\"\"\n\u001b[0;32m--> 322\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mNotImplemented\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'eval is not yet implemented.'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    323\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    324\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mUtils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: 'NotImplementedType' object is not callable"
     ]
    }
   ],
   "source": [
    "dsyn = survey.dpred(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "survey.dtrue = Utils.mkvc(dsyn)\n",
    "std = 0.05\n",
    "noise = std*abs(survey.dtrue)*np.random.randn(*survey.dtrue.shape)\n",
    "survey.dobs = survey.dtrue+noise\n",
    "survey.std = survey.dobs*0 + std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,2, figsize = (8,5) )\n",
    "dat = ax[0].imshow(np.reshape(noise, (xr.size, yr.size), order='F'), extent=[min(xr), max(xr), min(yr), max(yr)])\n",
    "plt.colorbar(dat, ax = ax[0], orientation=\"horizontal\")\n",
    "dat2 = ax[1].imshow(np.reshape(survey.dobs, (xr.size, yr.size), order='F'), extent=[min(xr), max(xr), min(yr), max(yr)])\n",
    "plt.colorbar(dat2, ax = ax[1], orientation=\"horizontal\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# m0 = (1e-5*np.ones(mesh.nC))[active]\n",
    "m0 = chi_ini[active]/dweight[active] \n",
    "dmisfit = DataMisfit.l2_DataMisfit(survey)\n",
    "valmin = abs(survey.dobs).max()\n",
    "dmisfit.Wd = 1/(np.ones(survey.dobs.size)*valmin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZdEMAfl9gt670HLCnwN5o8sF5XA7Y7bq9+4C7bkKrfJ4K7hbIUwCvL4BGV1CY\nX2suUlCOREHIMdeQgEgBvM5rAR71X1utNuzLDuyeu3WMEJS2sxbvEGkwHJtWKAXulqG8uJRM0WVp\nRrZxnuWOibdKrJRRqjjRpIVyIO1Z5Clwt4qWl9ezar3/Hp9YehPeCeZ3qBw91sZY8KlxfYpCcX96\nS8D9vpqOl+8hLfac1Z4CcvsNcwVcIbA7bCZwrBukPPipdXljrfhTwL11fnPz7B6ob9Wv564PsFt4\nF4vu/oAxrSUkYboAVEWk8h41Kj5lqecseM860oIpZynmhMvjaPsPTxZUUwIbfDesbWNtGZ3SRqf0\ni2c42HiPmWx+nUYzphX4JXu54Fn2GsA9BUPiosmj6yVKsX1XONxGmmNoO7fuxQvj6/pbBcACdMvx\nGPEs+DH8MgTYOp3nyfDK8Mq0ioKeu/fGy8PTWwLuD6HpnNNi1+EWaaUsAfIJvuWuF94JqIfDx3n6\nwQQf8D3rXVc1cPyaOkw301hwz1ns3jy7BftNX0eJk3ptVJltX5moheSW4/6RMF15LVgwL+ox7Kku\nel3WOefXHk8gPA55Ql0LfvAFqzdA36SdtVJwn/bVgOUZCVYxSMkPC+5a6Ze8lnntc6U+2jpvVXna\nmvfaTNdBgN9zy3sgb9NYYJdnSp97XoCcy97W11MIbLymMRa5Z4GnxlYK9K0y4imGj0dvCbjnGmfI\nOvfCrTadCh+6UtZ6ynJPgbtCYPnqllXwU9klzK6984De7qZ7aHCX/ylQ1xa7bcZGhQWVFnqA7y35\nIyaylruksfNlKfDQ6eV+yFK3z9WCzLPIQyY8ZxW8K6TfM2c5p9pN91OqzcaQtvb1fUp2eHUZYyTo\ncnPGgZDW4IXsKlmcfEHl02NYnqP5IHII+J4SovvIY3B3kYy59Ltbj4y13j0w9Vz0cNj3npU+pLin\nKAXcutwhxSLnaXo8ekvAPUWecLUCwAPssQ1+Ksh7/m/rP/esdlUnj/8FxPWvttwnTngK5FMWfArc\ntUJvldshcNfHxucAXix2/d7a8NZYXXAoUwTok4vldCWty7118kmcdRPq+BRpYSOV15ZoNPEpIXFf\nsHpbSAtya+3kBKcmbe2d6pIXGpIdksbTeD0r2gP2VBorK3S8ttzl/VKLaCyYiCDQ4VbmpdpZ+qXk\nuH2tde4d65xScgOHgO/R0HSXZxWjwr3pNp1maFxZZcBrL6uMeO3nGRufD73F4K4HkQ1PhVlN95Rn\neKAtv9aRsSTPAAAgAElEQVQFr39Tk+PVcT6bxVrnOcvdi7vvIrtTwT017z7khm/YA/tG1UMseU/+\nyaVxOupIS23/wpr5tcCw+Txwl/AhZs1p7LrxtMDzwmxZ7xLpAZJzCw2VcUp6j8bKjzHgngN2LywF\n7N6iWnnPgmO5IaSBpgJqjsfpEOAIw+oxqfsKE6ZPhyw4BG/dv4WKH1r0aoFck2fBW8XGc62P4Std\nli7fCr6cUm6B/RSceRh6C8HdWuRj0g2VMcY6T2nclpG9yXFrcpsV8XpuPZXVs9C9uJQFb3UJ+xoy\nvWf531Ng9b1c3ndZ9Fy7t1hOrPaNqaNOb2c5tubaGQWBbqGdnqe0pBfYWS1BmFYaQ17eUmvSevFC\nnqBJxXlpcuneBdKKllVybDpPcbIgPMZKGis/Unlz1ngK2HMePRtm5QN07+7NwXl1k7wpuZcDdzuf\n5gG21Ee/Z85FL4vphJnhUGnR7j0hb8ynLHg4Hgse+A71tQfMugxrCFjFwpbVMm4sPxy9heAO41we\ntiMs5bTrHOBbprTA7k2Qp66wr4qXbUIawMfEWUNgkngNva5HK+O2+axCL/cC7hrQNa9vOAT3rQrb\nOJcO98BdW/kiNyIK3FNas86kX0jitGtQgN+6KrTmnnMlpoSLCIUx4P4uAzsca4rg83bOIrNhY2iM\n/EjlGbLWU3EVx3LEhlktXDOlJz903TxmTr2HR1ZTt19dFMaU+mgZaNPbOXeZVtDP1/xjLfqcBS95\n7By85Rs7ZnJYoMehtuJzCmeKdFlaluj4C7hnKMXYNtxq6fYa0rjHWO8WJa1JnXHFaz6RLDU+WKfC\nU1dtHi1V8fQQKw+sAmuxUE/HSbjnftfueQvwa3xg15a8nc2w7nurrBMMyFsmssCuX0Cn1wxuH1KY\nvDmA12Vp8oSGJ4jedXB/E3oTJegU+eHJi7EWu2Y0axQ4Hjx3VayUmwN3I5NCcdgsnrPCU9hjfxM9\nsLbvKXPzsvrVO4nKLqiTfJp3NHmubo+swi00ZNANlaXzpcA9mrhcmR5Pe898GHpLwd2S1qi9OB2f\nA3DLwCmGlnvLjN7lAbux2AV4a3VZoB4T5sV51bFVt14+21zeuLaKsTe/rtfd6GvT1y0F8GsOwTw1\nEyJ10vXeHX4jAtEbE3Ye3iMB8kLdy68F9DGLgVJzflKuZ52+62TB1CpcOPeWPJf9feph5YcnK3Ly\nIwfszvqaAw3cGg1eeo+RnfrLuRiaUg4GwdqDqy8rwl7hFX6pVaF6vi1yqMXL3lXNQ9rtpvvM8qh2\nz6cs+DF85Y0tm87OLQ7RqXyaqpMnK85PbyG45wA8FTdG4x6y2oP5TQG7h5rOPJoYl557vTb30xFh\n+pr219hFdkbnAOe14Xg6TSiSXjBnt7wJeEu9PHC3xo63HiAlw8WLcOR20CTAnhv+2m2o763LQOiU\nxUBCFky+jOBuB9epbks9R5RS8MfUw7PaxwB4LjyzeHbHqJVKa2VLpdJ7sibxGjJko1OknVG0PArQ\n9gkOusGOYdmrquuxVgWnLH4NkClGtmNgyIL3+MqW64GyHjtj6NTxaTthSHidl94icB/bMPdtwLEW\nfU47z1nwolmrbNZi94BZ4qbOf2vp14kwbw4+5Za3eo40DfiWu56mSwG8ttgF2OVas7fgxWL3mtnr\nJky4pt3aHt3gQp4Grl9GP9gys/fw+7iFvbIt6TTvCvCnLJ8xbSL9Zjtb/7cLmTzQxsR56e9rsae0\nZ+s201q9zldwuHDOPDsUUBSHj9PDWR4lPKmdBBpTS5UODqfVLW9HOou+iXQnRMY+nxQkzFapB2gr\nXfMeHGoS8n4e3wmN8YxpOge/6HKDCfPkhoc51hN1iiLx5vSOgfsY024ob856F27KAfyAKz6YaA/E\n5b4yYalfe+8BvTwrB+5WVoWYGK/heGFszmIXoSHAvjLvLmHJejjd5Bm6dppgx1u2kBS4W0tjDLgL\nY59CXqPeJ83bSJ7g1R2a27LkuVatUiAgAYfArNPrZxaJsCHlPpVWA7d2s1sDILXqVfLr/eqq3iEc\ny4/I3hMu/L7zYAGz/hJFOrKXEVJtvQ5G87VW3ENQ017ybjqB9j7AMYDr9rd9aC192/9jFtnp//YZ\np1JqzNg4LUfsWLNy5nF5+C0Bd69RU+EpTTx3WZdJimmHrtQEd8FuLkwzpQViC9raBT818amwVJmT\n2MuLCGUkVBDKllBFQtmFhx7Q5bdzNBwOyEjYafKxB/nYAk0gNhC3gbgt+jU5Abahd7eHDsAF4MUF\nv+J4d4C3/siTsR5Z3iJ0ykjUFoTHdFpbyWn+WvjY8QKHlmNqHGryBIMVfO8KsMOxMuQBvY3LheVk\nQ6rNx/RPThbIYNQD1M6X24HsAbhOm1ggY6uqixNPH+yNZpED2nIXOSDFtureKtFSjlXcxbO2BYqw\n561AZ9G3ZWfV7xbaSRvqPasSpt0FMh4s/3l9Amle8JQBG275y+M5jwc16XidR2PIEJg/Dj+/JeDu\nkQfSXnxO+7bMKpSzzHMg7lnvfT08b5y2rD2Qlks0b51Gwmwem3cK1HF3haqFsqWoWsqqoZi0FGV3\nhSISQuwAPkQC+1/ogD3GsPsl9v/bQNsUtNvuarYl7baApiBuC1iHTjBMe4Cf0v0XYLe/Vi7qqceU\nNa/J8rMoGruM4r/U1rq4F4cYT4O7XhGf0jbg2LKwyoO8gLZY3iVAt2SF6hDAW6Gpy7C87ynstuyc\nO2gI1O1A9AA8tTAuZQR4+1eL48eoJTs7IBbrW4aiyAVUmHYWTFW4pBEDW6oByh3P3qovOFxDJ02x\n6nk8RlVowX7ebUWnHVg+EZeBVDJlzZ+6yE6HycvoMaT53OM5qZf2BNkxad3xunx7efEPT28xuMOw\nUM25zywT5xjbY94xFnxfrhRnXdF2cVzKOp9zCO4zDgHfteAjTCFMe1CftlA3nbVeNpRVQ1VtqSZb\nyrLpAD60hBC7XyKBloJDcO9iutA2FsTY/bbbgqYp2W4rwrai2ZbEprtYFcR1JwDiqgf4VejqK4Cu\nXfZec9quGiLLiy29ZSHALoJDg7p10+t7zegiTVOgkBM+FqR0hUWgfRmA3QpCId3BNtxzgXpaXgrY\nc/lySkLOFW+VfgvkExNmXfNmUUxQrnhbjEzPS5PpBfeSXuSC9yraQSW7WcRNL1isEUHvdpF6iGtf\nnhfoFuAJ4AM7Hosy5vXKeT3/br/aqEmDu5Spx4NWmPVUjOVLibcN4nmQckDtWRB6GsETOPp5Mm68\nNSMPQ285uAt5zHlqvpyWbk1Gz0p3zExxxVtgt4vnLJjPzP2MDuD1fw3u9nfaQt1SThvKWUNRNxST\nLcWkoQwNRdFQFVuqcktVbClDH96DuwZ1uQcOgZ2CGPYpmrKkKUq2RcWmmtC0JU1b0saSdlbRbkra\ndUmzLGlWZa/tFx2YL9mDvLXcPfdhTnZ7pK2Q3uNwuBLJuuh1uH5wak5eP+hUenyN/vMlLZC997WC\n0SNJk1Kkcp6AHFnhbinn+fMA37rgtZwQhlUL6vRCOSlGfvXaGWm6eX+JtS3gLotv9bS4Z7ACLPor\nqPLl9YU31334VKXV32Qq2C/Yg46/GmBbqIyBvaZgK5ICPK2sWV6D40/W5vKP4S/tebBgn8tjF3Hq\n59syhgzS89HZwD2E8N8A/xbwUYzxX+jDngP/A/ATwHeAPx5j/KyP+yXg36froT8TY/wbb/B0hjsh\nl3eM+y1n0XtueqN95xbPaVe6BW8N7mPCZhHqFqYNxWzNZLamqjdUZWehV2FLRX+Z+wKx2GMP4/v/\ngIH7PiYE2lCwDX1JVcU27krt7puKpinZrGvisqYRMF8HWPYW/JJjXck4QA6aXsjyqzf1pg2A3R74\n0iTQBVgQbxP3VuCM0cpTJpVX+c+PHo6ftSWXAvcx7aA9KZ4VJmGnClLtHvKEdQ7QPS+fdbtLGg3u\nfdlyDHVlkgcnOexlgACyFCtyRObZ9dky1kp/3V+wNzrkmbfm+dKk4rHWzi9NLR1vNwGiQEygc83D\noeIs/+G477X//76KtPaIjcmn6zBm7KRc9/JsG35fnDqdzmm5/7fAfwn8dyrsF4Fvxhj/YgjhF/r/\nvxhC+FngTwA/C/wo8DdDCD8TY0yo7FbzsWFe2oJjRrWWuqdRjdHK9Wovb66tIPkt9tSBM9Zy9wB8\nrq7Z4W+YtRTzhmLWUNRbinpDXa+pJysm1YZJsemsdTZMUKCuroLWAHzeLS8pWhS4U+3uN1RsmbAJ\nFdtiwiasWYUpVVXT1hOadUWclLRVSawKtxmPut2SxkV3Cw979+LOKAzKRS8P1Rm0q17A3AoZfW9d\nxdoasWPOuhM9K9NzFz6Otq/ogfg5pch4723TSTvYMO8+Vb6X3uN9q8x7i+c8xd663RML50JvJstp\ncoFj2eBN3+m1alfswV2G5HV/SRX1a2scEitdpv1kkZ0MUe26LzlUEAKdNS9hshtGb4OVOjUFtFXf\nHXYc6wJFjnoeNGlrTVGFaetZl2/n3KUOehxp3tVlD5EeS3Z6yb6DzvN4dDZwjzH+ryGED03wHwN+\nX3//K8C36ATCzwO/GmPcAN8JIfwW8HPA3/FLt0zpaUk6Xcr6TlnnjEiXm3c3/0OvhQeTZAzzWle8\nB+xX6re31ot5Q3m1ppqtmUy6qy7XTIsVdbFmwubgSoH7sdV+7Jb3AN6WtunViA0TNmHCtpiwntRM\nyg3rumZT12w2NdtJTSxrYhmgDHsBo7smxR92O57dwqOFlD5Iq+0LidKv2ry3c/C6YA/ctQUyBMJj\nt+zIM/SCvcelh+NnT3/XfLurgZM2pelZJSqnNKUU/TEeOg3wnlVuwb524sSsLjpg1yJKn2chMkG7\n3sXVLnTTXyX76ev3gPfpxvyq/xVrXkiqX/ZVueFQ+V2xX/gq9RJvm1jx+vwKPbUmc/jiTdgU3Y6Z\n3YJW/QIbDhfUWTiy/DKGDyzIWx6y4Rb4h6aEbFnWkhiqz+PRQ8+5fz3G+P3+/vvA1/v7b3DI+N+l\n0/gT5Lk1Uh09hnFDIiwH8FaLT62SDXurPeWd0xa7td5TwD6jA/PdFTuLfd4SZi3VfM1kvqSeLplW\nK6bVmpoVU1bUrKnpAF5+KwXwkyS472EcMLHH4G5L3DBhTc0mTFiHrhaTcsOqmrKuNqwmW9ZFCwVs\ny0CsArEs+q5Q/Wu9rkKtc1leEytCL46HDuCjFtTWzxj7zClAL8z/IfDQlbZApMmOdc+y+NzoTPzs\nWUYecOv3P7UdtIzw+kGHD/G/BXaPuVM7aTxwr/ePkmJV1IE8EEtcZIW23G+AJ+wt6wA8pwP3LZ1b\nfctehgjp6svedpkK37CfIhPslUWu2mmi98WrWcgdz4W+DELHa23fvlEXEtgfdFNxOC7EMtfgvDWV\n0Gm9+ThrXVsl3C56i/g86ZGUnfuanX0fz1p5OHq0BXUxxhhCyL3VI044ngrmXroEsMMh46ZA3S6k\n09a5dctri/2aDtivWsJVSzXfUM231NMl9WTJtFoyKzpQn7Fk6gB87yzfgfyk/7+3yY9d83C4oE47\n7VsK5Q/Y+we2fdi6f/qKaVeHsGFVTCmrLeWsoSxb1lXDtqrYlBO6hUUFFCFtrFmj2vK3Bne5rOse\nONTkrXveAnjuvwWORxzOnwPdn589Aafdqh4I63hdRu5xKQMgZxwMyYQhj6CnAFgBUO0fpfHeTsmL\ngV+zn0u/4vDgGfHgSZoJHeBf980hvyJ3ZGgH9Syx0jVfCGgvgLv+V15DmnnV3wu41+wPqhJReOBE\nCd2q+iawn9jX7jkrbzWDwyG/2bHjhem+zFnWj02PV4+HBvfvhxB+T4zxeyGEHwE+6sN/B/hxle7H\n+rAEfVPd/xTw02eoWoqJPcs+Z71rrbwvVzNuygVvAT63UE4D+zVw3YE7V1vKqxX1fMWsWjIrFszC\nklkP7HJpgD+E382BNZ8C98MFdQWe435NvStxTY2e3T8AdrHviy1l0QF7MWmhbojljG0RiKHqgT0c\nT2Xpe897jolPfaxK5t4PBIb15ds+HwJ4/fBz0P8D/NaZyjoLnYGfv8W+rT/sL1RYzjLTYOCRTTfk\n3fNoLJAPXVr51/529RgBZFHwpUraey+gL+7zK1WsNgwE6PWWOW/4Cu6JHrLsr1alFxZ4CXxm6iks\nIlY/6hX1R570FLqUt3PP1yqjVqRFgTtiVNM3enzovMKDdkpLykx5yu7Lr6fk+226Naiel+Fh6KHB\n/a8BfxL4C/3vX1XhfyWE8Jfo3Hc/Dfy9dDF/WN1rIWpdakOUcsfntO+cC84IEbE0NbDbaTkL9Pa0\nOWvFz1Gg3hJuIsXVtptfn6+Z1wtmZQfsc5bMWPSgvmK+u1/uwF0DulwC+CWNA9vdBez+HWyHI9BQ\nHqgLUvL+f/f0JbODOkwE7PtteeW0oQgN26KmKWpaKqL0j/WwdhU6nPvTc+2pT9BGc7WB7vANOxak\nE60God3zhfmv3Y2FeVCO5IV0HoB/DvhJle7XB8p5cDoDP/8B/PawHSNk+T1Hnpsd0vLBU+RTcSng\ntuHOKtnQ+9NDX65YzhrE9d70K+AZe3d8DTztw+aqWnaNjtpaG6YtzFrCJO5eJTaB2AS6raD9NSd9\nnryUd81eCRAXvkwRTNmfNilKhfYu6Cl2zbctfT2kEbxFM5qftBvAjg/hQetmH3KDp8aF5UNLnrXh\neZV0/IfseTkCfztR9vnonFvhfpVusc1XQgj/FPhPgT8P/FoI4U/Rb50BiDF+O4Twa8C36YbKn44x\nDklA+0SOmXiIPCY+RRO3wG4APphkuQV09oQ6uxXuCNgh3LRw3VBer5nOF8zmS+bForvCgjmLA0DX\n/7Vrvt7B7TG4H66YbykNuDcG3Js+hbbSxVK391NWRrmYMem345XllmLaUEwaVkXLsuhwN1DtvHpH\nnjf9fXhrmQuwTzgGdy1HoLcmLLBLwkplsGDugbu2GKzAyZE37/D50cPxszYRhaywtOsSDmqWqnEi\nT8qKT3noPKU/5W63K+i1P1186gLsxV75F0zTC2ln6vE3dGD+lL2sEHCfqeYygH7w6JuW4umWMGt2\nr95uS9iW3amRcmpjAEJUlnVfdmQvg27Y74df9r96TYAsqBNwn6jmDux5T8oVZYKCw/UuKTccKrNd\nZKd50CrXJMrBpLN8a5/p0dH8Hsfj2i6YFSNC1//h6Jyr5f+dRNQfSqT/ZeCXxz/B04xs+NCVS5dz\nwVlN3WrtYZ/NGvgpi33MFji9eO46Ulx1wF7Pl8xmC64md8xZcMWCK+T+bgfuEjZnceCal3vrqt+D\ne7OD77L/D+yAvD2KLXfgLkCun9CFTY+mBSq2+2cGdQxuG3fs0EZo6K2N3Sp3emHEodtdA7z9Ol2l\n4nW6nVzRHShMKyuV5Fe7/7Svc8zYGxqXwvie2xAn/GHp8fg5ZcVLmrGKey59ivd1P+ZkQkoWWEXf\n2xZX0S2wDXss04vnhNevVRFP6ID8qUr3pP8vR8uyzxumkVC3hLol1qGz3G+2lE83FPPtnr+aSLGN\nsC1otxVt0x081ZQlsYWwhdBEdptf14G4DMTbQHxV0r4qujl4Lc/kKGk56EYUF614y0p+aeZ1/9sE\niGXPbnr164RjTVzi9XY5OLbcvT60AD+W51DpPJL8kkeuz1cxF3q0BXVvTjlLXY8cjyF1PCYdiXCb\nL2XJl/tyAvndct62N2/OXVvu/eI5rlrKq95iny64Lm8VoHegLpdY61fccc2tAvdlD7OHC+724L7d\nwbXMuZc9pAM0PZDvZ+PLPmy/7W11oDoIuHfqhrcFr9w9Sx2Ys1tzFFm10MSiW4zTFhx8kc4Cu140\np4Fd5gIF4HW/7Ba7am1aWwjeZeOspei5FHMau7ZchLRV8XjzdI9LKVf8Q1AOsFN8nwJ27cGz1rsd\nD/1zBfT0MdKy1e2azjoW3r+mA3MdJivjZ+pRV8A8EmYN5XxDUW+JRSAWUExbytmWcrKlLtbUxZqr\n9o6ruKBoI6t2yqqdsSxmLMKcGANl2xJiu/fdybcibiu2H09pmR42j5As1lOH7XFLdzjOpH8fKw8L\nuo9JNWXvOduy/7iTZlbb/p61nFr7Aser5scCt0075NrXwG4vi1vvxoK6M9GQcPSsbwvMOevdlpET\nBJbRFTOnFHtrydvtLqkFdbv97C3hastkvmY6X3I1uVNgvmDOHdc9kGtr/ZrbHbjPlHt+ynp3P2PJ\nJG6od5Z7w24bXIyUvX0O7GK7Y2fFxi/3c+5hslvGp8F9yXznkhdAF3A/PBGvA3lpv1gEmrZk01bE\nturBHX9OXX6tW36j2r5RvwLyuyGlx5cWKiXHQkYLlCGLXJerXfs2PGVBBBX/rpGn1DwUefw8xOdW\nMbNMrWWAtxbHFCFe+2v2ir4slJVV7nIJ6F9xuJhWFtnVwFUkXHVrcCZXK6rpqvvWQxsoipaybKnK\nDVflgnl5x3t8xjNeUNH0UuOKVzyh4gktxc6L1vRqfhO7I6S3d1Ni7E6YPJha0M2q1xRDxzKL/l4v\n8jswbvs/MXQuuhg5lq3eJQ/SU2LCIymM0Dym+SoH2pq8dCmDU7v5dVqp5+Mo6m8JuJ+LxgJ9DtSt\ntRYO5UNqlfyQa97bFjeDMO+2u5VXa2b1gqtiP7d+1QO4WOj6Xoft594XPaCvmMUls7hk2q6YNA2T\nbUMRW4rYgToxEtpIEWP3H/qjZgOxX8kuR8+2oWBTlWzKklUxZRFmrMJefViwYsr8yHL3FvABe5gv\nCtq6O5++aSPbpug+RCMuPwHvTd9u2k1v21rm+azFr2VDPKX/C46/V+0piu+ixX0u8tpIW2Z2/j1V\nBpn4U+szpNRr95w+fc4sngkTKMtjw75SWa1bXk/TyyWWvKymV/g3ma2pnqyYzhfM6ztm1YIqbqji\nFkKgLQJl0XATXnPDbc9vHd3wmme84BkvWDDvF8B2PjzZNLuKM9q2V+2vtlRfWdFOSmJZESehUzrk\n4Br5NoRs2ZPt6xIvy1cm7N3yO8Wgv4kV3beiOXzRg3l5YeCUNzXlBbI8+aZ8acHcW2SXypdSQM5L\nX0Jwz1nrNmyIyYMZpJy+oM4DdnVOfDFrqa621FdLZkW3gO7KuOJveL0DcrkkTLvq9WK7WVwya5dM\nmxWTVWSyagkt0EZCRAFg7MKhP9At7C3rAPRuwM20YDMNHYyXnZ9A3PFT5izMHvty5yHYgztwCPU9\nuDdlybopaLY1cRs7N562zPWlF9KlwF1b9iJ8d7xprbUxVp3Wyj2l8UI+ecCsFyFpD0euHYfiT61T\nrs8tUtuTqNQXXsoAtZIRdopOwF0sc/1xGH1C3TXHIqqCarZm/uSW69lrbopX3ITXzGPH5y0F6zAh\nEHkWXvKUl9xxxWtuiASe8IqnvNztbpG411yzZEbJnDaWrJopMQTCVUNZL6Gc0lBAXe4Xx72g2zIn\n4C7H2Rbs3fNb9V4lh20CnVeOgr1WEPcvugP2kv0Xa7y+snPvXr+ew3LW7gevvLGu/oeltxTcTxGc\nFsA9oTzWTWddRspqL801BuC9RXU9wId5d1Z8NV9T10tm1bJbER8O59ctmN/0LKoB/4o7ruId87hg\n2qyZNivqzYZ6s6bebCgXUC4jwXNr65Wu9h37JoklFPNANYNyEqnqlrrasirXzMol07CiDusdqO/n\n2S2wm8/WhIKm7M6qpy5p5iVNU9M2/YpfsRikDcWa99p6y6HVbt9DFJqDDrXu+NR40eEpgD/wR2bI\nWgTvGtkV8TnK8bhe0+DlG8qv41PXkBzwmLw/HUaOltXJ9N51AUH9BTeRCdf0q+Mjxfst4f2mP7Ax\ndq722YbJbMPs+o5pfcdN9YpnvOApL7kOnQzocLciwMFi2yvuKGh38kHAfX+C5Ypbbqh6r1QsAkXV\nsi0qtnVF07Q0oaFZVZ1Vv+mm6bp3Vl0jUxAle76TT7rLu0p4BArJLBmFIbfqXhpUW77aNe+56VOX\nXd9yH77T+Wx5HuA/Lj+/heBuO2kMaUGsw8ZcwfxqRFBFeXPtKRd9ynpXW1mKWXdW/GS+ZDpZMguL\ng+1tGtjlesKrI3C/4TXX8bZbTNPeUS8b6lVDuWwoFw3FEsIiEmQPa2qhGhyDe3+FCop5JMwCxbxh\nMlsxnW2ZzVasp2V3tn2x2X15zm65A9C76o/OrC8q2rqgaQvWLdDUNNtif/61td5lz60Fd5lzFytC\n99GBEl5wODlvwTvlDtRCxm6JO0VgaHqXAT71rnpe1HNh2kV4Ns1YGSFIY5V/OOzzMSBv54lVcWKB\ni9tdeF7AXYZH2f+/AT6A8EGkeL6her4mlB1X1OWam8lrbiavKesNZbXlhte8z6e8x2fc8JonvKKk\n6VsxUqK3t+4/BNW1XNtXNTJhw5zFbv1NWXRfkZy2q87fF2e0Tze08xWb1YT1esp6WROKsnPTV6qt\nZ+zd7+JhW7I3xqd9OvkAzY5k1WHFfhm+bI2xi+1kDFhA13woNMZVfp/FnZ6yYOfbYyL8YektBHcY\nr5Hre+vX0oMg9d8Cu2bovhyN+XYRrV1Il9vjfmC5R4pZQzVbd8fKVsv+5LnFgQaurXcB9AOAj911\n3d5xtb1jvl1Q3UWq20hxS+cyu2W/h1Xc2ieCOxMo5sA8Ul43TK4b2usN2yYwJVBVDVXVn0bXb8vJ\nfkaWsF+oF7qV+E1V0MxK2rag3ZSwqWAV9nN6GuTXTnvLwrqUEiYYvhsjEuGNAStEUv/hUHBowM9Z\n8Z418C6RgHdqi5LHs6lydHm2LF2epZz3DifcavA2TDG/fDRKdAcB9yuVzO6OEbCXPe7PILwfqZ5v\nmH6w6M6BKFpmxZJn5QueFS92gP2EV3zAxzznk52ib71jBe1uG2xLgazckbgpKwKRhnJnxc/Dgpvw\nmtvimlc84RVPiJNuX8tqM4VlQ1tDG2raUHQH5IhXXW+Fk73x8gla/REbbaAHOjfggYyVwnS4KNNW\nqTL8u/kAACAASURBVPasdlH8Up4i4cP78pwdY1LWKa76h6G3FNxTlGNWTJwNz2nvpYkLh1ktUKT+\npw6uOdge18K0pag3TCZrptWKWbHqrfb9kbJ2Rby22DuAf8WT9pYn21vm6yX1YsNk0YF6kG84y5UD\nd2HS1HuKi00fePEEwhLKJYRlJM43lPM7yjpSVJFQ7ge6BnRZfa8/PtMt9FnSFCXbakIzqWjqCdu6\ngrroLtlrq9vRrpTP9YtZ4HzI8J4nxxszliTOnpplXYpjvU/vEnnu0VM8cbbtUwvvbF95z7flDckN\nu4rb5NP72UWxtHPMmu+vga/QffBFtr/1W+BCaJmWK26qV2p6a8U0dNtXZT/Kcz7hR/hdvsoPdmAt\nvFPS8JxP+Ao/3CnUa2pec7MrY01NIO52rzzjBXdc7TbPvuIJP+Cr/ICv7bxri2JGVTcUwGoJ61AR\n677ugb3RvaRTam5UF4lRoZtePlBzEKgFp54jTCnVYww+b3wIpRbiwaFl75Hd/jb07Iendwzc4Zjx\nPLAe0uQx6VNMr5IMAbvdCieu+APAj1C3UHffZJ9M1kzLlXtevOxjlwV1h1enZz9tbnmyvmN2tya8\ngvAyEmSBy0vgVX/lwF2Om0TVPwfud8BSwD1SrKB8smEWN0xoCKGFcu+H0xb7Htj3n42VY2y3RdV9\nOnZSsa5rmE56ZSjAOhx7RbQVPwbg9Tqdg/GQ6/8U02pr3YKXBnhvy8y7ThaUowkfW4ZWDlJufvD7\nLGel54DfaoPOFYpjT51WHsUlLTx/DXyV7tBe2fbWT9sXITItVjypXnNTvuI63FKz3jnYO95/xVf5\nAd/gn/E1PtodIHXLdT/nHnmPz/hJfnsH+Ldc76x+4TUB+oqtOUp6wgueMWWF3v56W14TCmiLkjip\n2IR59643/TvLcbWL/p3W6v1lHh72io98Tvaon/SCBXsijucpS5HmSc+DNnSSXVBpPIBPLa6zz388\nesvB3QrglIbu5Rm6UnNswX+05f2cmz7lnp9COWsoZmvquvseex3Wu/3oYrF7C+p21nt8zZP2lqfN\nLfO7FZPbhuJ1JLzgENBfqv/y9ScN7nr/uAZ3b5uv7Neds/+uc8/cYQVhG4kNTJotV+2ya8GyIBb9\nVjq6mXgRNBrk91+Y68B9U05Y12u2swntEpppeTj3LvVdO/VM3ev+OzhVMjcWPKVx6MAMa63qvEKP\nv/DmccluG9LhQ9veLJ1iCaWUdxuurXPPDW9d8cY815ik19hJ8jn7w2j0gTZqLV49XTOd3zG7XjCb\nL2j7veUlTX8+xf5jUFNW/XbX/fRcILJiyoI5k3bDNzbf44P1ZzSvSzavJ9yUC66eL3jy3itCA6EN\nHWSXW9oi8IonvORpb+lHZqx40s/ry5HS3Wr8KeuyZjudsH4yhXJKuyyJRbGfJhcFRmSLbFuVFfWw\n97DVKt2O/7ypD1kkY3nRelJyHp0hS9wjXYbd+uYt0LNj/dTx/Wb0FoO7B+ynaEYppSBlrZl0KS/d\nkPvXc9HL9yWmkXLaMJmtqScrpsWegbUrXrvjj7bAxdc82XYW++S2oXrZdMCur5ccgvsdnZtMg7sA\npTfnbi34mr3VsVTXel9maKBqG+asqYqGWBe0k2IH7t1BOPsvycmlP0KzpmZTTNhMJmxnE7azgnYR\nidOwdwOKxW4Vq1Q/6O4VcN8JF93RYwF+rCWh84iggrx18K5QDuClHe4D8Lk8OYv9VCvd09SLwyJt\nEvmVj8Lo41tlHPbzz3W15L1nn3D93kuaSck2dAovsHPDP+eTncdLHy8tC2mhOy66ahueL17w3uvX\n8LvQ/k7Bqp7w5J+fsXg2o2621OstFJEmBBbFlAi85mbXcgUNc7pDcMSs6HjzjnWYsJ516kZbBSjr\n7kRJsdQ1uK/pZI0sHNZnTYg8jECMzs4Vy9Cyrcfjwah+hTwP0anb4uz40js/5L8eQ97Z8kPTB+ej\ntxjcwde8x6Yda7V7QoHDcWeTpQClMpdxyYc6UtQNVb2hrrojI+1Z8Bbk52qby3W85bq9Y75eMrtb\n7y32T9nvRbUA74B77Oer4xZiw+5ciVD2V0X3oSt9IId8OUpbz+aDLQWRSbmlLBs2LNiWgSYUbEN1\n4ArUX5aTN999NjasmVQbJnFNW09gGmEVu/3ENYdueH3ZPsl4Vvf8asdETiEcunJky3mXgR2OrZw3\nJespSXlMPEUg1YeWma08MJpiUEp/Ctj1oTVitcsRsxXdF9zqlmq2Znq9YH59t+OHmvVOqX+PF3zA\nxzvX+rP2JR9sP+W99iVPwwueFS8pYwMtlJuW+WrNfLuC1xA+gVldMn25YrW4ZXa3YbbY0Fawvi65\nnc9YFHPuimsmYcOaCbItrqLhJU93c/NCTV2yKSpoA8tNSVNNDvfpi7Fwx3G45tcJ6pTJvh+iZ517\nCraO1+Cemq451YIew5Me31sl9vE8c28JuL+ptuMBdorRPS+AFfCmWh5AeMCu3XQHin/s5tunLcWk\n+/xpVWzRn2a1J7bL2W9zcdXHbqvb1faOerHp59jZg/lndCD/kmPL/Za9W74H9GbTXW0Dba+AFmV3\nlRWUk+7+YL2LbKWzl1KaQwmhgEnYcDW5YxtK1kXNOtS7j8x0C3lm/Xt37y7fg6/ChqrYUJbdF+R2\nH8uY0G3Fse2dAvmBWZfjcZMK98amJ4jeZG79VK/U20Ip0L0Pr5+qUOXySpi11DMrMTXme2tS5IAq\nsdKvgPforPgbYBoJT7YUT7bEJy3ruvtOg7jdP+BjvsIP+YCPueE1NWue8ynv8wnvb17w/uuXPF2+\nYjpZMZ2sKJoWVhCaSFk2tDMIN93zithSr7aUH7WULxrCy0g5g/qDBt5b89XZJ0ymWxbFjFXoDrh5\nxlNe8ZSP+eDwA1RhRVG0UEFRBhqmbJjtFX6hNYd7/COdvJBDew6aN3TH0bZB4WBqsZo0ul3QdooH\nbYjsc3PTahL2+dNbBO73pRT6DqWzAsII8pwiKfep+XZrydd0FmjdAVZZbamKjQvu+3tZWNdb8HHB\ndXvLfLNgsoiEl/EY2D9lP9+uf2X16qa31LfQbGG9gW0DTW+5VyWUJdQTKCqIVQfWBwvYNKDLvW7e\nCkIVqScbwtWWbVmyDgLuU1YsWPZCTT47I20wYcMkbLrPxJZbiqrpdhfUBUyCD+a6vR2Z7Bpru273\nAlOdbqlQv5LnvgB/X8D7opOjMJ+lvPvkSykZFrG9/ybY6gF6q6t48K+AD+gAvrfiiycN5fMVzFvW\ndTcldcNr3uMzPuBjvsoPeI/PmHNHzZqv8RE/yW/zweZTrl6tmb3c7Be2roA7iC20z6C9huIGwjMo\nVpF6tYWPgB8CHwPXUMRIVa2p+ISnk89YhpolM+7CNS/7M+1q1sjKelkHRAFtUbAtp9zytGs2AW1p\n0pV6f5EPG7r1PpZvGxSwSwEpizf0jQzHrvqUEXcKWde79/wvJm++JeD+EHQq4JvBYo35FNh7U3dH\nBkAklC2hbClDQ0XDRH0aVR/beuis7s+JZ9EdI7tsqO4ixWu67W6vOHTDy2K61/v7+Bq2t7C921vp\nTQvrBjYNbFu1Ey5C1fTrf1oot1AUUGygit0VPJ7S7z2BUEMxhWoWqWmYTtfMClkoNN9Z6wLoMgO/\nb4v+QJxiSygbQlUQq4A+GtddC5HztDhdPID8zjjR7sDGSXehQ7KLjM4tJHMWufe8XD9boDdp9KtU\n7I+VfcLhB2DEJS9rwvr1HSFAUTZMJlsmk06BnbLiKS/5Gh/xnE/6+fTXu6Njb+IrpqwoY7ennUgH\nols6hf4HEO4gPIHiCYTvAP+kf+5PAN+g89g1dDLhO8DHkfLrkcnXWwJbqmZJWQaapxWbJ3X/AaoF\nU2a7NTGyPz5OoLpZU5d3xDbQNt0ROnHVL7KTaQl5b5F/Ei74KQt5i9DNv8cS4oHPXvWTPnc6R5qP\nU9vVNAZYl34q31i6r1fp/vQlBfeU9TXGvapoCCwssFjA32n4EcqWomwoisYBs/1/mYGeGgt+2qyp\nVw3VrdruJta5nmOX8Nf7++0ClnewaaGJPbvE7toC2348V21vDLdQb/vqB5iUMGs74D9oNjhc1CpW\nzAyKWSTMYFI2TKs1s8nht+Q0uMu1X1rXf3imaAhl07kTyiLtdk9Z7Kn+OupkF/nVy0qac7sD33Xy\nBOy5yfO85DwGOfDX7jiTRmOBbHcTcBdQl2vG4eLNtiugLFom9YZJ1SmvNWue8pKv8gOe8YLrfrHc\nM17wPp/yhNfUcU0Zu48+7cC9pbPKvwN8CsUVxCvgH0H4h+yn0ebsvW23wPc6JaO8aylCoGo3TBdb\nqjqyZsLySX2wFXdLxYop8iW5OIHyZk09XdA0BW1T0GxqmlfFfnpCFtLps+ZlK21gPw+/7tuzVS6/\nWHMM7jBOkdbAnpLz3u4Nm/4+4J4bUw9H7zC457Qky+g2vZX82mLvfzWwpwx8HZ7y6pUQqkhRtRRV\nQ1XoXd56M9ge4A6s9th/l32zoVy23clzGtjt/HoP7O0raG5hcweLFdxtO3C3H1s72AkXe36Mh560\nuu2++xAjTIoOZ3cYqcFdLJoZhP6q6oZ6tu6+UEd3UIeefqhZ7xSbo2/BFw1l1RCrlrbsFPyTFs95\nfXUwbHrL4aiDPbAfo5k/rub+dtFDW+2pfkp1vtdXGU+O9xixSr11NgdbSSNMI9Vkw7RccVV029qe\n9s5wOXVStro94RXPeMnV8o7pckP1sqV4ETtrfUG3sPV3ge/RTcXVEGrg/wN+h07x+AbwNfaLXhd0\ncgMI1xDmkaLugCwWG66XC5pXJXf1K+4m12yLiqIHvme84D0+oylKQt3JsdV2ymo7JVYlbYjd95jk\n3ad0uCmr571dOFpHjnbOo+HQ45MbA7k+9yx5D+htWTjxmnILRlML/M5P7yi4eww7Nl8KBUzRKfwf\nsuCddTmhipSTptPYyy1VOASxQ8v1cN9793W3FZPNmnLRHLjcj8BdWe7NLSxuYbGEuwYW8RDM7QX+\nInQB++2mc+HPQ6eEF3qqSt5fNHf1Wdty3lJv1syagnmxZBGWB5a7XJW446VdQrfosKq2xKoiVi1R\nPrGpvSJDXhXbh/r/gRfO69xTwTpnPXwZKWdBv2m5Xr94YJ3idQfA3XwqqGSPC7KdMoUpMk6nsfsu\n+3XDpF4zD3c85SXPeMFzPuEJr6hZM2PJDa952oP9dXzN/PWK+gdbqk/bbleM7IaRNTaf0Vnk8gov\n6Zi86OO+x+Hx7bGv0yf971e7q7xpuNksmPygYf10yurpFOrIlDUT1myYADAPC35YfIUJG14Uz9gU\n3VfpDnBTFPySTrC84piVRFYeTHN7fSSaSQ5ojxjZPAj1oDFWuZSXSm8X/gUT/njK/VsI7kMN42lr\nY8pMaeXq3vL9GEC3A9ZZcBvKSFE1lBNtue8PYe2AfXMAdjvrvV0xa1bU6w3Fkv22tlf+FXtw39zB\n3RJer7osckCdPbtmCNzF8Gi2sO0Tyvw7ke7zsRbc1Wcui+uWet3SNKF7n2KZcMsftktFv6ug2tJU\nLUHcCpkFzclu9rwwIqQD7D8DmxgX9xpjMJzPsyDeJTpVOTqlXAvKKevc68cUIifipBgZb7rbPFmh\nrNQwjYT5lup6zWy64KboLPb3+XQ3zy78LlteZRvs9HZN/VFL9cO4n377fn+pbalx018vIK57nftT\niN+Fag3lCkLF/vz7F33d58DXoKxa5ssV8xcrlmHG8qom1HGndDeUBLr1QjEEtqFi2c4oQnvMV9I+\nVV9H+XKc4KxOtzs10mNYON6OY9PrfPZUOu0aGMtnejwNWe5i1QQn7LIVzpDHaKk0RSL+HHVIBI91\nyx/Nt3eMVZTdlpVuQd3WgJkcBGlc9HHDZNtQrdvuHPdF3J82J9ft4bW97ebYFytYNIdJreWeOqDO\nLvafsB+uVdMJjBCgKrpF7Lt5tRl7TaK/wjJSLkP3Tflpw6TsVsRbr4Xnlq9Ct2e+qNpu1X7KLT+k\neGWHzFggPpXGjGXwLY8vK1mA1fe2Le/jHbFKgQCHRm41gELRDfSC/Yp4/TGYicpq43ognVxtuL55\nyc3NC55PP+Z5+Jj3+KyfY7/tj4TdIIvWuuW0MxZcMdtsae+W+zU0L4Ef0Lnem65ObQurF7D6DDa3\n3bUo+1OiX8LXA3ytgJl8F6Jlv+jtNfDP6Mrvm2d2s+D55lNC0xKKyDZM+rUya+RM+1WcsmknNE1J\nWxX7s+XvVNfIh5qmdAsO5QMzJLrAHf5DrrjHXPtit+JJ2Od3KNVbCu5j052zYzPAnrIGx7rly0hR\ntntwP3LL+4vrJmyYNFsmq9h9j12AXYGnBfntXbd47m7bueIlyWvSlrs+oM4DePnIUwDKplt4V7Qw\n0+AuloGpX9ED/GTVMimbbkGRs87gyHoP3Zx7EVqKsu1cBQnlaWctjPGwnNL39yapzBDDj7UUvkyU\ns8gx4fchbcmJYNbauRk0At7aKyVTTzJ/LEwyP74m12ue3nzGV24+4v3wCe8Xn/Rz7N2JkzOWVHTf\nNO8WsNW7MyBu1kviXXG4xuaHwHf7Z77XrUdbfgyvf6fj+bsWXgT44St4+bvQXMF7VzB7yn4F+1P2\n4L6hc9P3ysn8/QXlek3RbtmGikWY7zxtO3CnA/dtUxHLgngdOuD+rG9OWUgY2J9uueBYllqsdPsp\n5yrVFvtDk7dl7vNVyt8ScH8o6+kNaQyopzx8B+6qSCgiIcQOrEhf5e5jqN0J7EXbEppI8Hzp5hvn\nsT+UZtP2F/tTIeVXHyuv7+FYH63YD+XdVvcI6wh1062oPzgSVrQH8z9sIbRQxMP3s99+P7r6tura\njmOQ9to61WcPoQ+6dB9r8l0Fdm8udEwenT5Vxpusa8gxrUkmX4GTMaTBXPQ3sezle+7quxJhEimr\nhqrcEGiRj7TG/t1q1txwy9P4kifxFTfbW67u7ri+WzB7vepWyQuGab7q67Et4HULH61g3fN8E+A6\nwizC1aI7x+Kugc0G2nWnlM9KCFfsz4HffTsi0MZAE8rdh50ayr6+IJ+YnZQbZtWSdR2IdUUzKzvr\n/T32n2mGDvSt1WDXzBx53oc09YK91HrTMSBkLXIvvR5zQ1MFD09vCbh/ASk1vlIAkurPPi4UHbCH\noD+Cevg9Zg3wBd32l0Ds5rVFG/YuhdZt221t89zvFtj1WTRSVc/R5bnxm9g9KzYdeB8Vrq8WaOMB\nuMt72raQ9gjEfVuFmLa+c8pXqp++YDrku036s51DlFIETiljLI1hXg7Hi/7SmZxEp8FdH2SjTquM\nRfe54w0Tlsx7T92aK0om/Xa4r8Qf8pX2hzxdvGb6gw31R1umrzdURX/wRDDP75WJpoQXk27xfOir\nNS/gqxN4OunOgGoX8HIFt69h+xKeN51yXj5j/xnaXmnYLsvuYJuy+1SNfBpWzr4vaJmEDfNqQVsU\n3G4LmsmUZlrB09DVUb4WJ94BqdiUDvjr/levYWgwa1887fzcTCwd6FnjHngXiXhd78ejLwG4pzrZ\nDgBPq3Ly5pT6MZdTTjd111vuPYBrUE+BfEFDiHE/hyVfYjLALqfOxW2npYvxnHLB66Midttw2XvS\n4HDoFhw7DbZ0h+G0WwgNFDmAbyFECNF7R/1RWOfqMh4CvO3eU/qnMHmSLkHvIbZzbfoLHVtD9n6o\nrTzLXced0ta5tBpEhuSEk9WOKTlTXU8RVdCWRT9PXVNTswnrnSVc0FLRULPmmlvej5/y3vol1WeR\nyffi4Xy0eMkCewWCzlO3jvtF8xXdjpb3SvixCpZrWPXbYFcr2K5hO4coR8SiMk6hjQXbUHZfaOy/\nASFfcgSo2FKHNU1Z0pYFm3LGMrR7BeeqL7Pl4Et4u5kPO50meBlCX59TBG2OJ4dIjy25z84TqPI9\nYPfq9LD0uKqEQyGEPxpC+M0Qwj8OIfzCwzwlZ7Z5mp9zAtWuwpw+TnQ+V9HsBkxQQH54H9PhbUxb\n6j3Kxk1/nOy2d81FB4g5BHanmIOwNpNuQydQNg1stt0Z9dF+Zc67orxfe9QWhRO+U35ChCL6XXyf\nEZ7t4yF3oGdVjLAA3wEax8tem4h1pM8rfrBaMo6Bh6zEnvRXBOVVhAlg74aXE1K3dJZrN41OQ8ld\ne8XLzTPWbU0Zm37b2y3X3BGIO+t4G6rO/S0HvdzRrWyXD0Pd9s/5gN2WtuK7cPUCnvebSe6AlxGW\nEWLszqSY1vB0Dl+5gq9dw82km23Y4VjB7rjc4rplUh6eO1HQ9q8fdwdtyTqZsm06gbMM3cP1wVp3\n7Of3tJF8tIjOat6pMaIL0HnvIwTGgPkQ6bEmdXu8KbbP1XIPIZTAfwX8Ibo1nv97COGvxRj/4Rmf\nwrDwPUEYh3TUqKpYkC/2lqcG74IU0O3BrqDn0JQrXoP7pptT2/S8pqfAU6BtV8vbV4G9TDua6o/d\nEbZrurn3cgthAOBDGwlx78E4BvN9u+w9Gt1v166x0/CtXL6PIibCJhk5pCy2Jv7dPrVuPC9rQauF\nnUaSN5kvH0NjlK0csPf5tMd2d+AKeysaDj/3Th8nHjYi2x7c223kGS8oi2b3sZirfnn5gjmrMKUp\nSmIIxCZ0X0KUhbKyv/2WTqI/B34I8SMoP+7m1Z/Tebpl3doqdt9mqUqYVN0c+5P+gJlQszuri9jX\n/aort7huqcr9Il/5QlwkEGiZsNmdXrempmhawppOobmlA3Y5aEtc8xrcLcDv+mIMSOo4bXXfR2Cf\nA4y1YmEnOB+ePm+3/M8BvxVj/A5ACOG/B34eOCO4e2Q7OtfxJw6MnDGXAJ3uVoPXIZgVykot+2vn\nsm4joUlY78rkbpvuIzB2vt1e0RRh3fKa5JwJC+67K3bTAG3TTQ3sCnVBPlLE2L9fs3vXQ5Bve2A/\nds3vAd7pMlepynSt292SObdQZwgs4N1dHHcfXtZaVMpSekyFyBsk1rOg6qfc60fKoFRbu7e27LfH\nlS2haqkma2bVHU+qV8yKJWU/vhpKWgIzljznE6Z0e8xfbZ9w82pB/dFyz0NrYNXthPl41V28gMkL\naJbw8RZ+2Lvm++UtfNLA/7uGdYBNgJspfKWEZ/JN9QUdoEszbIFbqO5apndbrmdLnlavWJRzbrkG\nAiUtc+64oWZDxYI5RdF2n7KVhXnybXft9fbkozhQS/ZCicDed++ZHGP6dux4koqM3cpmF9tpUH8T\n6//+9HmD+48C/1T9/y7wr52n6HMIhRMHhOd694o4AiBrtVv3vIBaN8+uV5SHGI8X0xlgj20HsjLf\nngJ4bblLmBS9r+nhvbyGC+z9cbYTC+6O9R5aCDtwP1RgrKJz6Jbvgd1rW09g2PDR3XuqcPjS0T14\n2balNt3u605NlX1KPk/703VT4C5npmtZro1MrdA27Kz4ULUwaagmK66qW55VL5iHRXcQDIENFQ0V\nc+74Kj+gDmuWzHjZwORly833lvs56w07cP/dT+A3PwYWcLPpvGWfxP2hcxM6Z98nW/5/9t4t1J4n\nu+/7VHfv2zm/y/82mtFIk4wm/sfO5MHBItZTiMGRmQSCZIIReRAE6ylD4jyFICvBNomxiUHEClgE\ncjF+kMAPJthEVqQIyU+WhxDLyBkLS9aMg/6+SPO//C7nnH3p7spD99p77bVXVffe5/L7nd/vLOhz\neldXV1VX11rftVatqmbZ9HtbBfhCBVXVg3vLblcrAdkN8BzKFy2zi8j5YsnTxXPW5YSPeQ+AkoYz\nrmgpuGLereYp2+32upz3UwpXqmuHZrVkSc72dQ5Mmw6+17EeNMmjlc8hshvl3IRr/3R61eA+8ol/\nnl2H/T7gw5sr+p7R6OFsUZjXrEdeq8a8rvSbwG/xqoTDkTSygb+kzr8P+Mpxtx/VnBS3WLet/e9p\nfglBnVIirTdWlNoATKCYthSzNdV0zaTaUBY1shRuw4RLzrjgDAiccYl8nKUtA/EsEJ925QaZ7xeD\nNkJcw3rdxdkQoZnBYgrFptuNLjbdHhfrAOtzaM6gnXXL5jYbKCZQyh7weuneBGJZ0ISCplerd4p3\nZ3jIFtGy0oWi7RWZPiZG/P3SL6L8aEtB42oWw3N84b27Y8l62wSwtdshR3q8fLs/7s5AeNXg/hHw\nJfX7S3Qav6Gvcbwmf1MdeMTA8OaMPMXtYDpHO+Kt47kw7FP0LrvOdo+yQ5bdAU99nCKU3YfTqpLt\nl91kt1Z9wL7jGXPubQKnHWV7R+iCdcoARcH+DnLOJjOxgBhC/3wFenX7UJhd1O/aTrsNvZPRPP8q\nNPAP+0Ma/wt3WPfRNJKX/wh5iX3qHKlXjkf2PV6jrhj2N2Tx1mjD/iqWAEyhnNfMFiumsw1tFVgx\n7795WHHVf061pOWSM1qK7fckZudrqn9tTTuD8FF3cAk8gqqG7246T9nHz+CTF10A7effg/feh08/\nhY8/7jaxCnQ7SL7/eXjyZXiyhvm/gMtnMPsCFJ+H8D6da35Otz7987B6f8Ll4znP5o/5pHqHT3mX\nFbOtJ7Gli/5v5eFDB/DQwrqAi9BN/guoL/uj4VAp0q9n+4rskiCPJ61iphf1XpeH9fyLLSc3xfTl\n/pB2/fI12jCOXjW4/9/AhyGEL9NtdPgjwH98M0XnXqC9lsp7gMLD1CYO750rizq64JVyyivwKwJR\nvmOuQd4ImkLAnW4XObuRmwwE7bSyQ7g0+bXnzD1CV2dRGnC3X8UqgTLQbsG93Coy7YFDfn/SIhKI\nsQd4x3OqOngf5N2oXPPAB4l2vauXJ0XWUnzjaCQvS4fnwP0mrJsxlvvYuvR7Nfn1vJWn+Wr3vADY\nFMppw3S2oprWtJQs45w1MzZhQkD2dmm4YkFLQUXNgivmZysm/+qG9vMdX8VPIEzowD3A52v4fAP/\nX4TVsrPSv/gUfv/3dJ9yv3reTdGXdF9w/MLn4Mu/H6pP4eJ34eolFBVMP4DwDrtP1D4FvgvWkFqx\newAAIABJREFU70548eiMz+aP+01yn7Jm2lvrnXdBNrbpuitC2XbzbpvQKSJr1W9rOjd9bfpLs4ua\nvnQ2yHDelzdffhCldwLpceIpFPpaLqL/bgyEVwruMcY6hPCfAf8n3Xj7X242Uh52HR3YveCCfQlv\nf2cGwgl4v3fvAcAEiDuA0nHy/kzz/lYu3QeYORQsCmVD72abTPrltu3hZ1sr80glh6SL1zEvFtQn\ndNvOTkuY9nUHuWD3fd+z3kMXDbz1Xuw/e7sH8MVef3V9qwD+Oop69h17GoKuSP8e0iLeHBrPy7qf\nLA0tb7Cuc31+ikKgZUPqmpYdtj52TNCw221twm6J14L9TWb6+ff6asLy+SM27Yyiid2W0ouaalHz\nTvnZ9qtwZ1z2LemV+U0BnwWKTyBcQpDvxrd0FnH/ezbr1rLPVrB4DvGfw/QzeLqBadEtd3s8gyef\nQPMPu/snE5h8ESYzCC/pQP1R/4xr4DnEpxDbQEXNORdEAlfMaXmXJXNe8IRnPOWKMxoqYiyJbdHx\npuzcp5cHRnYW/AUd0ItBvul/17GLAtwqZEPj5Kas9FNIz8/YNmmF8vbpVVvuxBj/NvC3b7cWC+4C\n6Clh3LAbebbBnA4Yqer6nZcOY+X9/dn2rFfZ/tIDTAH3Csqq08gnTQe8Ftgl8l2TnY20FrvVKTS4\nTwNM+mU2Qe3GdWixqyOkFZqW3dTEgVs+hp2L1OJpSoEe866OAnev4hHK4htE43nZA9Sx6xZzSyFO\nAffUi7bg7rjxRYYL8wi4y/fKS3bgLvZDQwful1Pa5xVhHaGGMjZU79WUs5rzsttX/n0+ZsEVwNZr\nFzcFPAsU/5zuWxKyMcya3S5vAu4FnNWweAbtBqZLeLKBxyW8P4N359B8AvXHwCOYvgeTD/pptJdd\nGjLv1oM7V91SvJKGcy6oqPmUd2l7kH/OY57xztZ6bym28o0y7O/QJyJYwF2Wx0kk76ZPj7E7DhSs\noff6qnjOLp3QPtBjp5dPp1cO7rdPKfecZWqP0QfA/ZTDKacbux1ItUHPM3tgZvZu03Pu2pRWyBv6\nI1bdvJz1jHuWu5BWcXQVtipbVkU3515UvUveZjS7UHX47D9jdo+6brKe2IZ9Xo7O+THvKAvuqUq8\nPPbaAx26MK0amSPpSw/gjyXPzWOveYaAoHQ/cNuwu0UbjOJ2lrkr1dxYFzTLgqLo9pWfTFbMyiUL\nrpj2i+RrKpbMeckjir5tVWyZb2rCit1qMMELBZZT4MkU6llngIcVVBtYtB0/nk/gfAbLl9D0m9+U\nBVQLVd453UdkHtMXAiG0lH1EQCD2u9MV8gHqLjIgzlluzriqFyxfntG8nMBlgFXYD57LhTtIX9r1\nt8nMlhevq1CnBMFYy857MDvhebv0FoD7LVHOOLMyIzfG+uuxDbSxB7Hgb1mj591bStpQ9vnZj2zz\nLPj+vAj9XDiHc+6ekSuiDfZlSArQt2UGFUiXA/atj18Um3Kr8beULqBvwT7ujqQRZt9D6l29PQb2\na0B6cvUYsvlvyr2Z0u6stih+9ZptFGjTc4PdShU6N/mL/tZz9t1dABuoqDk7f8Gjx895f/p7fFf5\nu5xzwYaKz3iHT3mHp7y7HfsVDWfFaleGxJaxK5OLbuOoxzNoH3XeuqLdKfUU3Xw9k37Kruz4NUD3\n56w/PgA+1//v215OG6bFhrqH+A2T7Sdol30gYN1WXCwf8ezle6xezKmfTeFF0fWFfFsa1VcFu6/q\nyQZAe69aK385RUyn3YRbPlfPMeVK+2204O3SPQF30e5TVvgrohQ45MDeMxbazvKUeXex3r1jf5V7\nSVsUxDIQe+vcnwBny8hF1UXJTop+3j12Wr5sqCVxLZ5S7SkEMo22rSb0R9nVZT+SYdtEBbGXk22w\nz1cooHeO2B2xDURvanvIQk+9J/dF3xRdF9DuO+k5yVM0KZ3/JmXBEMNK3SqYK7Y7q10Du4iqHmi3\n7nIhZWEXbcNkumLx+IKz8JLz8JKKDWtmPOsD1p7xlIqaKRvOiiuaSUmcQ5hyyJB9uVWA6qxLi/0n\nH0tgGntAX0A4h6KGagXFVM3fP+2P9+mi5B/vnquYxX7ZXme1X7HYHltXfFuwXC94cfWU5qKEl2E3\nny4eB+1ht4G20tXbV209OzlhmvKmHUueQDgF2IVs22+f7gm4w3imti/9JrX7EdXlpmL1tm9qU5fY\nBNqmoGlK6rKijhV12H3RfdNryPqL5vKl801ZspkFinmgWEQK/b1o0cBlQ4oaqgiLCO0S6ro75Mn0\nJ1/tfvLgA3vJbtpvASxKOKtgPu+Fy3l/8Vydqza2c2gXgc2sYFOV2y+3+4f6yn2saNpOkLRNAXU4\n3MTHC6wdUsLuhMYKiesIk9eVhpae2We2c+qeoG8z148hAe+a/Lxob8aGsnNPbQNN2A8SE7eXBLtd\n0TGZGp/1puJqeQ4XLZPphnLSbneq6zaDOWPJgoaSgpaqquFpSxOhWEB4BOETuu+4t3SgfMnOCu43\niCLC7CXElx24Tz8A3oVy1nVV+ACKr9BtPTCn48/HfXes6NzzT6A9C7RlwZI5n/Iu/4Iv8Iyn+1+G\nK1rKyYZysYLVhHZeEdfFLky/6du47LtTUEh7IQ5mWuz7TjGuN25eFXn8+zDn7pB0knYSp/JoZ/JN\nt8GpV4+3FNjbHeTU71hD2wSapqQJJXUhIFb2/32wW4cJm6qiDgXVHMIiwFncB/dzdh+qqKFqu5Up\nMfa7yPXIHehkk/0IjN5b/sD1zk6ubXWJEhYzmOv6BdQNsLOAuAg0c9jMQqeohH0lRvao3gN2DfB1\nSdsU+zvg2a14x3pVku+cXIYTaUij0APoTaIhvtRWGBz6kazA1kq8zneqYi/MmvMqiLnZz3NJhLxY\n0uK9lyYIQAq4q7HabEoul2esLkpKGkIFZ1wwY0UgcsWCJXMaqg7cJz2495Hs5VM6MG778p/0/xfs\nhk7vUZj2W9JSQfgC8H4/fbYBvgvCV4A/wL73Qdo+Bd6DeB5oqm4Huk94bwvua6bI2vYitJTTDWVc\nEleBeFUQp8UuQl52qVv1dXjgntQBh4Bd0rV36FWRN5bhAdyTNMS0nk92bLkWkfW5qtp6gcZYhB7A\ny/awTaCtS5qNBvYO1MVKXzPdO7oAlhnLYsaSKeU0UsxryrPYRbmKZrxkt6607UVj6Fzzi74bywaq\n5vBrcRt8cLeR9pPQW+wlLBYwOe9cfttvQT9mF5jzRKWfQ7soWE9LVuWMVTFjyXz7bPKs1mshR9NU\n1HVFuymIdXC9Illva+p92alW1/V3rMnvaRJjLPc3jbSwHXq+6wTKyX/7wq17VFv93n0DczZt7LxG\nEjgnt0uE+YodUEn09yVbzTiuCuKqImwibVMRY7frm+zytmHCcx7zGe9wxiVl0bKeTNiECWfrFefV\nimrWdDz1Hvteq6I/f9EdYQ5B9nf/HPAucAbhu+j4cdG3rWfy9izQnkP9tGL53pzl+ZzvTN/lO+Fd\nPuFdPuOdPWOj6YPsitjCOhAvJ7TLkrgO+x+OkXl36Y8LdnKqn0LYKkHbDtVKVypgxgK9fYf2vXtC\nITcm9VhMKX85z5EGkNunewjuY8gy7lghmpP4cb/olLU+5Ja3Rw2xDh2w1xPqynPLT/YAfkUHgkvm\nLMOcZTFnMmmpFpHJedsx+pJOsCzpGEba0Cu0Veh4eRJhsuoseg3u+qtxHrjvTaEHOJt0W1xOzqEU\nQPeAXY4e3Jt5wXoyZVl0z2KBXQ75DpW22jdtB+5NXRKbIu0dGXLJe8B+oPAPCZgxZIXK20i2Y1PK\neiryYwxJ39q69A5ikk8xxUEZ3gBR12LbBdRJNTLeoGMM4T+Zixcwe8nO7TUL3c5tm5Ki6TaumbLu\ndqNjxYaK5zxlxoqShpqKy2LBcjLn/fCMWVtTFU0H2O+bNkxVG57117+L3Vz6U+CL/ePIZjK/y9bD\n1j6F+osFl5+b8sn8HT6Zv8dH5Xfzz4ovcsEZRf/gLQUbJrQUBCJl28KypHk+o31RES+L/luzdJ+n\nFU+ixCQI4IsyJMf22zDCd/oLGCkFbujd6Xsyct4lTzH08uSU0rvj/TcU3CEveO3AsPlTyA3desuw\nDwI5V28O2Ldu+UBbFzR1Sd3uAN3+F4AXAFwxYxlmLMOc6aRmNq9pzyEsu2Nrudeqbf24K2IXXFO1\nnSUfWqjb3UdlNrH7JntDlwa7KHsJmqv6tEkJ894Vv7XY5XjEPqj36fERxHOo5yXratKBe6+w6Ofr\ngL3yLfe27NzydUG08wljXPPeu9pT9D1hkbPmhhj3WGXgbSDPxZ66jrqeE54pK3zosPlTTC6M2/S3\n9aHrLdsd6GQ9Oyt2GrHekU005DmdlVsXNJuKzXpKQ0UoIkXRsmbGZ31AXUVDGwKrMOs+zFLB2WRJ\nuWgpQ0tR9WAju+NN+rqeAx/TRb1/b/+/nzKL5x0vhmd0mwV/GthMK+qzivppoHkfLj5Y8Fl4wu+F\n9/mXfBf/nO9mxZQzrqiod4ZGnLNs56zWMzbLKc1FRbwsd3JIPlErVoP0j1jtwqtyfYudLf7nrTyQ\n9t5f7jhFSdeUuken2zF+N/QGg3uOtMae09o8xlYafor3PVlgf+8BUICmoG1K2rbEWuwbxz2/Ytrr\n9h1jzcs169mKyXmgXEK5jB3jCNMkcCjEnYu+rXsvYwObtvv2e90qy73Ygfm06JbQFP2ymkrm1bXF\nLscTdhG4/fX2UaA5h82sc8kvt7bKdA/Y7fPrwLqmLYlN2VlPTUhb657Sn3tvezRkpUtBttIHAPcp\nNd9ohW4OvIWs0BSezgUtRZPX3p87ZC1Jxc4P38+/Rw63OxdLXYJSYl/EyqTXENuCy9Uj4osAi8B8\nvmQxvaSm5JIFFTVzukC7FXNe8Jhq3jJ7d0WcB84ur5jP17t94AULZWOdz9Hx4bt9nX2z2yeB9n3g\nMZSzSPuy5NnTx3z29Am8FykebViFKS/DOZec0VBSUhOYcMWCmopnPOUlj/i0fpcX68e8uHzCxfIR\ncRN2AC5fxYOdkrPp+yTroJH34oF7yuWWMuiu6zXT96ZWfMi5CJKUR+j26S0FdzgEd6/DUxZ8yCuH\nOWDRVvx2vAZiUxCbgiaW1JR7EfIa3HbA11vuvYt+VS7ZzDu2C6tIsYIgDNSoevWjxV7BLzpLPPZ5\n2xrWtXLLN70sCFD1W8pO+h3vKLvo223gnHXJa3DvLfd4TjeXdx5Yz0pW5dRY7J3yIuCuFZuNuOdj\nRdtWxKYk1iZaPgXwQ8rYAX57LzUnOHJj6YE68kBX93GOxlj1ghYpBUEDu/XMWHmg32ujypOwb7Vo\nXZqux5GA61ylyzruJZ307afNYhu4WD7icnNOFRveqT7l8fTZdsxPqDnjcrvbQ0nDbLHifHFBdbah\nmtfMr9YdeLd0FvuLvvzP9XXrDS16j177BOrPBUKMFE8Czbrg+buP+WfvfJ6ibFiESxpKLtiBe0W3\nFO6SM17yiOc84QWP+ax5h4+XH/Di8glxVcGm2M2fr9nvUhEu8ppccJf3I+a8FmZDypinhOfAfwx5\nyqc37avHoX04q1TeHt0TcNca+bGUErx29/SUe0e3Qb2YIetPg7gGchnUOm1N//3FgnZT0tQVddUF\nzazDfgDdbs59xow5SxYsWXEZ1kyLNeWkhcWG8smGUMfDKSpx2ekNJGSb2p53Qt3tZBc2XaBd0ysF\nZdlZ6bJXfLBr4cQl/8Qc77Kb43sK8Ulgs5hwVU24LM64Cos+KnjRg/zcnXffMGETO2BvmpK2LmFV\ndH1ngwS8/k5Z8J6idjAmNBB4Y8VSyrI4ha5jbbzOZJ/LA37N+zZYycqF4OS9yXZqq8xqkX2d2shU\nm9Vsg+hkGBR0a98F6C+AWSDO4KpZ8HH9Pm0dmRUrZsWaDRNe8IS2B9cJmw5QecqsXFHOI7GgA/8Y\nmVQNk6KmnLW7posuIiv9VnTegwB1VbF+VLJqF1wtpjRFyTrsPIWf8Q4veLw9XvKIqx7cX8THvGgf\nc9WeUccuKHDPQ3GpDok5kA1trti57SVO6MAtr/fFlP7X/OTJa8/TNoaHUvfZQ5eX2kc+lfYA7opa\nTg+ugUNhbLUtq8FbK8J7sSarB+x2sXgKfDahd6GXtJuSuqmoi4pNeRhItzvmrFixZMUVC6ZhzaTY\nUFUN1RxmcUOUNa7yKDpGSf+XOcG+faGBctNtcCFTiwChX9q79xEYORe3vA6eE1f8O2zBPT6B+BjW\niwmX1RmXxRmX4Wy7EYYA/HrvWU3kfDuhbiraTdmvnw1dH+b6+5ggO3fcaMopgXq8DCkAY+nuXHl3\nT1rgefPv2gLS+TzFYOz+9Me2zypnkUNNsRfwMewMTbWpDJemmCkdz8jHUS76oqvAspnznfoDVvWE\nD6rvMC8+7qPmn7BmyowVC654wWOeCbjPGuJkt8XToloTytiBe6uaKOAOuxmGAPWkZDmZc8EZy3JK\nUxQse7674oxnPO2B/QkveLK15C8450Ur4L6gjtW+h0KeTTaxEXD/jN3+G6LgCLjLXgDb19vPIWy1\npZSybdOOVYqtBykF6roNFpcs8Mu55M9NGd0s3RNwT9ExLzCleXkDwhPe8rvcZU+5e52I+D2w18C+\ndVsF4irQrivqdW+xhymrcsaUNUvmzFht/0/Ndi8VNWVoqIqGchaZhJqqrqmaliLG3ZjSW9LK2lzZ\ntEJZ7sHuZIO6zy521+BuLfenu6N9Gqgfl2zOSq6mcy6KMy76ubxLzvZ2u5L1vQdL49opm3pCvZ7Q\nrsve4xF2/egpUMcE2e3hsGfW23GREijHCJhThdF9JE9Agg/Kx/aFCE/5r9OjSR/z3qzXxbsuDA/d\nJDY73p6oyxv2l8fJWJU56atdc5qyZLWYU4YNl5yx4KpXJ3ZbM8sa+EvOeB6eQAnLcrbdw/KcK56G\nCxaT1fa7C6GIhCJ2q3NCSTMtqReBpoLLcsHL4hEXxfl2zfqK+dblLjwqxwXnXf3xrAuka+asNxPa\nVQmXRbeXvHwIRqLfl/1vfWg5qL1sW11W93WKcb13NpanPEPPy++lpZa9pQxHPT5vn+4xuEsHySiQ\n4IaxWpFY8GPcro6VphU3zxXvrbm27nkZ1PKpxlWgWZXE5ZSqqFmXG9blmhWzfj+6HaDLBq277W76\nDVtDS6giIbScnXf2/aRsdnu8a0CX45zOsrDu6zG72Ai4y6Y1Gtxlzr232OvHJVdnU65mM16U57wM\nj3jJoz0rQM4F7A8i6NsZ682M9XLaraFdhZ3wsACfWHq4d67ltw6I2hsnOS3AE/bHKJwppeFNJc8j\nllsK5wGykN7QSsuDlKKgXVg2TdK99+zNxevnkfn4/kMyG/aj5u0ja8+etlw3wMvOtV4+aQhV5Cos\n+Jj3eMyEyIstz2tvXuciX+xt2vykeMHl9DPOqitiLGhjoAwNZWho25KrWQfI7SzQTAKXxRnPwlOu\nWGzV6xUzPuUdnvHONgZoGxnPLgh23U66abJVSXxRwmcFfFp01rmsaRcFR1vnG/an0/aGv+Yp8fFr\nn31tbtL3pKxsj07hNW9spsq25d8db99jcIfDzjtGCxursSfMOk8H8MAjNe8uTC2BtyuIM2iWJc1s\nyrqqWU2nTHpgn7BhyXxnpStgl98FLSFEQtkSyk6iVGVDWbWEgg70p3SKxFz911p0qr3iwrPALkqD\n7D6ng+j65W7xSSA+prPYZzOeT895wfkW2OW/BnfXgo8z1s2U9XrKZjmFVbkP6p7AyL2PlCFwME68\n8WCt9pQ175Vn09zK31A65hlz1nzqmmjcKes9ZdF7IJ4Cd6sRyiR23GGRrGu3MR5aVohiL5Hz/bUw\nh7CJRAKXLFjGGZGCquf5InSfV1oy3wa5ySYyss7monzGupzwiIutlBADoaHc8px8r+KCcz7jHVbM\n+By/R0XNJWd8xrt8zHvEvt8uOONyy5tzlnHBuplRb0raqx7cn5XduvrP2OdDeVbBaC0HdazcgXDV\nLk5Pc7ce1iGwJ5F2DI2Z/slhz+3TPQd3j4QZIb9phSZvEKQs+Hh4q3XF5yxgba2LJS3jdtUF1bGG\ndt2teV2VM6qipiwON6E9AHZ2304DiGW37eNZXDIJGybTDcUMinkkWKs9Be7yH3xg15b7gi5K/hHE\nfrlbew6bxYT1YsLVdM6LsgN2CcrRhwZ1ayGs2lnnkt9MadeTHtiLvs/YPzTge275FOjvvVr7/m1k\noh033qBICZq3CcxzdFsBcEOUsu416Xcl7jkZLBW7iDk9Por+lgC12lRprYqd9MUu6daft3Tj9SXb\n6bFmWbL+dEEzLSmmDWHaQAl16DaweVo+Z1NOKGhZM6Wipu5Fefcduc96i/4xK+ZbpVkguaLeuveF\n31bMiHTfab/gnJqK3+MDvsP7fMz72zgfWX67ijOu4pxlveDqxTmbTxe0LybdhjUy1/6SHWhfsAuq\n02varQejbqG1jCo3aBBPRcfKu/P4L2Ws5fgwhSVCKbBO5b87esPAXTOkkNXUlQvt4N7cILGWmYqa\nz7nhvQFsv4wmn2VbsQWsdjphs5mymtRUVQfuUwPsYr1LEM0esBOIRUGcBJoysJgCi5pqHgkLum0o\nZbtJsdw3ps267TqmJQfu/ZK4eA5Nv9ztquqC5y6Ks60r3h4igPaBXQF8O2NVz9hspjTrCrbz7exb\n7N6c5pA35QC3cwLBU/5SGrqnDKSs/7eRBGDvJsCoo5RC5uXzwEAGjbisGpXeL5Fty31sCuyUR9nz\nfdmnreiAb0G3c1wF7bJi/VlJKKaERzWc16yrCZflGRfVGXWYEMvAminPeUJBS7f+vKElcM4lK2a8\n4DGRwCe8x6e8yzkXPOYFZ1wyY8WEDVcseMbTrdVf0nDJGZ/yLt/hA77DB3zM+/3c+5Ot+VBTsep5\ncvn8nPp357SXVbeZlF4BILgsG9hocNdGkfBu09IVok16bda35kadnrPYPcU6x7+avIA5/dsqB3pz\n/jHl3w7dU3DXrrnUde+l2khbrZlbbS9luSstnQAx+C55a7VvOHRFCbgLIG23iwy005J6MmVdtlQ0\nFGXTgXqo9wDdtdjlV+g+H1uHkjqUNGXBhIZp2VBOWsp5Q7GMhKtIoS13/TxyDv532HsZ1/YfgWnn\ngWZRdtvKzko2s5KL4pzLPnhOu+Jf8ogXPD6Ya9+bc4/98rh6zno1p15OicsSlmquPeeaT7no7fva\n8qB+7w37DGrHx9BvnHQ7Pj16m0B/bBCdFbB6Cm7IAk+Voa1ybWml+F8zgljvFQfyIRY7b7KAuCxB\nvaLj85lqmhTdT5PFF4FYdbIlbDovQKxKmnIK05LJeUNRtlxwvgXkECKT0K0xqWh4zhNmrIgEPuMd\nPuMdzrngJY8454IFV8xY8Qnv8THv9+C+IRC3y1E/bt7n95rP8WnzLhfNIy6ax92UX9XQNiWb1ZTN\n1ZT62Yz2eUm8DLstZV+y74IX48E6w7SHbc97Jhm1+9BTjHPW+JAiPZbPxvKqt+LD0t15qO4huNsO\nG9NZAuzRpIkV36o8dlDoXYi0xgh7G1gMWeyy1MwDeVlvqqJK20kJ5ZRNAauic81NQrcFZUmzB+gu\nsBPYfv89lGyKLgJ/Nl8znayZzdZMNxsm6w3lMhCWsYuQj6b99nEdgI8lHajPYT2t2EymrCYTVmU3\nrXAVFlyGs72guZTlfjjnPmfZLlhvFqyv5jSXU9qr8nDpjA2oGwL41LTd3gv1NHxPcHgT954VMYY8\nq+NtIvvsKbe98aC5ckC/g9TmOQ37gXn2vQZ1LvfIejIH2OXdx9h5liI7MC/YLXl7zP7qLthtPLNd\n8dVtbhWaQFuWxBBZzwMvi5p2HrbK/SRsmBUr5mHJvyRug+LmLAnELU/J8jlRn6est9b5mulWhsiE\n36f1e3xn9QHPl0+pVzM2qxlh3hDmdfexqxdTmhcV7Wcl8SrsLPP+QzV7c+yyDbaIYW2ty7UtaSPM\nE64pBXoI8E+hsbyoPVDamvfw6mGde4ZS2ngqr7XQU5q5teBTVrty7WvL3bPY9UcjKg6BXVz0AvB9\ncE2sCpr+c5LrSU2Ytd0yt7KPiFcQngX2/rOx6zBlFabMiyXzyZL5dMm8XTJvAtWqZbKKhCYSjGYd\nmrgbpwXEMuyEUu+4iGVgMwvUs4JlOeuOIBvszLdArZfRWEDfHcpyjwuWzaJbZrOaUV/NemAPh8Cu\ng2lzRyqwbutZsxZDbix44yjlNTrGSngbgP2UKOOUVTTGcveUrdThKfu6DsvkIg9UFHWM/aWwa3qh\nipTNn2TaHnYg+BI1BAtinz8G2JwFrqYt9azcfcq1XHFWXnbR7HHOZ7zDPKyYhyvK0Gwj6+cs9+be\nJ2z4uJ9TXzKniX30TiyIbcmzzVM+Xb7H5eU5XJRwWRLOa6jrbl+JTyvip2XXXrHWX9DFEojlLlN+\nonTLc9n4mBjpHjQlbz03vLzPId5MHcdQzqOkAVt7hlP0AO63QN6L1cJX58kJdTV4tGtNxqKNMhdw\nt9a77GKpP7c2ZffJtTLQVgV1OSGWLeWsW8telG0P6gLs+zZ8S4H+wIpsWztn1i8qW3bMX3ThMZNp\nw6SsKdteaYiR0HYCqpBzIBaBNgQIgVh0bv9IoCkKNlXFpiy3n21dbmuasVSR79o6t0vgLjjjqo/G\nvWTBVbtguZ6zWs1pririMnTArne1GuuW96x4a7VHO0bGArsH4G8LSJ9CGulyebTQbJ00IW3Fa4sv\nmDQpR9dhSYO6TJbb/GJ6CkoFduHuqu2xn7eyWWH3adVIF0g3UdWIkrpk53SYdfljKKg/nXabN82B\neaSdVcRJwaaaENpOSZ9XS86ml0yqzTZS54zLTtHv94WvqHnB4+1HXyRotd5MaNYVV+szNutZFxy4\n6eJbYigITQVLiB+H7itvAuAv2QG9BM9ZcF+zUwS2rvpIt/e1ZkwdIa8Z1VrwOd7UZPk147+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W5ysqKvZQf42qss7CKWvp6nlzw6AK+IKs4s0n3G1U7ce2tTc+daIdDKcorfPB7S91nyxpxHui47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\n9bxSfn7VvNyX9+r5Ocb4Whx0a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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f499090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d_ini = survey.dpred(m0)\n",
    "fig, ax = plt.subplots(1,2, figsize = (8,5) )\n",
    "dat1 = ax[0].imshow(np.reshape(d_ini, (xr.size, yr.size), order='F'), extent=[min(xr), max(xr), min(yr), max(yr)])\n",
    "vmin = d_ini.min()\n",
    "vmax = d_ini.max()\n",
    "plt.colorbar(dat1, ax = ax[0], orientation=\"horizontal\", ticks=[np.linspace(vmin, vmax, 3)], format = FormatStrFormatter('$%5.5f$'))\n",
    "dat2 = ax[1].imshow(np.reshape(survey.dobs, (xr.size, yr.size), order='F'), extent=[min(xr), max(xr), min(yr), max(yr)])\n",
    "vmin = survey.dobs.min()\n",
    "vmax = survey.dobs.max()\n",
    "plt.colorbar(dat2, ax = ax[1], orientation=\"horizontal\", ticks=[np.linspace(vmin, vmax, 5)])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "reg = Regularization.Tikhonov(mesh, mapping = rmap)\n",
    "opt = Optimization.ProjectedGNCG(maxIter = 2)\n",
    "opt.lower = 1e-10\n",
    "opt.maxIterLS = 50\n",
    "invProb = InvProblem.BaseInvProblem(dmisfit, reg, opt)\n",
    "beta = Directives.BetaSchedule(coolingFactor=8, coolingRate=2)\n",
    "betaest = Directives.BetaEstimate_ByEig(beta0_ratio=10**2)\n",
    "inv = Inversion.BaseInversion(invProb, directiveList=[beta,betaest])\n",
    "opt.tolG = 1e-20\n",
    "opt.eps = 1e-20\n",
    "reg.alpha_s = 1e-5\n",
    "reg.alpha_x = 1.\n",
    "reg.alpha_y = 1.\n",
    "reg.alpha_z = 1.\n",
    "prob.counter = opt.counter = Utils.Counter()\n",
    "opt.LSshorten = 0.1\n",
    "opt.remember('xc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SimPEG.InvProblem will set Regularization.mref to m0.\n",
      "SimPEG.InvProblem is setting bfgsH0 to the inverse of the eval2Deriv.\n",
      "                    ***Done using same solver as the problem***\n",
      "=============================== Projected GNCG ===============================\n",
      "  #     beta     phi_d     phi_m       f      |proj(x-g)-x|  LS    Comment   \n",
      "-----------------------------------------------------------------------------\n",
      "   0 -4.89e+06  1.16e+06  2.70e-01 -1.59e+05    1.45e+05      0              \n",
      "   1 -4.89e+06  8.02e+05  2.15e+05 -1.05e+12    2.87e+07      0              \n",
      "   2 -6.12e+05  8.00e+05  2.15e+05 -1.32e+11    3.59e+06     10   Skip BFGS  \n",
      "------------------------- STOP! -------------------------\n",
      "0 : |fc-fOld| = 9.2136e+11 <= tolF*(1+|f0|) = 1.5946e+04\n",
      "1 : |xc-x_last| = 4.6116e-05 <= tolX*(1+|x0|) = 1.0566e+02\n",
      "0 : |proj(x-g)-x|    = 3.5921e+06 <= tolG          = 1.0000e-20\n",
      "0 : |proj(x-g)-x|    = 3.5921e+06 <= 1e3*eps       = 1.0000e-17\n",
      "1 : maxIter   =       2    <= iter          =      2\n",
      "------------------------- DONE! -------------------------\n"
     ]
    }
   ],
   "source": [
    "mopt = inv.run(m0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counters:\n",
      "  ProjectedGNCG.activeSet                 :        2\n",
      "  ProjectedGNCG.doEndIteration            :        2\n",
      "  ProjectedGNCG.doStartIteration          :        3\n",
      "  ProjectedGNCG.projection                :       24\n",
      "  ProjectedGNCG.scaleSearchDirection      :        2\n",
      "\n",
      "Times:                                        mean      sum\n",
      "  MagneticsDiffSecondary.Jtvec            : 5.36e-01, 5.89e+00,   11x\n",
      "  MagneticsDiffSecondary.Jtvec_approx     : 6.45e-01, 5.16e+00,    8x\n",
      "  MagneticsDiffSecondary.Jvec             : 6.31e-01, 5.05e+00,    8x\n",
      "  MagneticsDiffSecondary.Jvec_approx      : 6.31e-01, 5.05e+00,    8x\n",
      "  ProjectedGNCG.findSearchDirection       : 4.77e+00, 9.54e+00,    2x\n",
      "  ProjectedGNCG.minimize                  : 2.02e+01, 2.02e+01,    1x\n",
      "  ProjectedGNCG.modifySearchDirection     : 4.53e+00, 9.06e+00,    2x\n"
     ]
    }
   ],
   "source": [
    "opt.counter.summary()\n",
    "xc = opt.recall('xc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "  {\n",
       "    this.interval *= 0.7;\n",
       "    if(this.direction > 0){this.play_animation();}\n",
       "    else if(this.direction < 0){this.reverse_animation();}\n",
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       "\n",
       "  Animation.prototype.anim_step_forward = function()\n",
       "  {\n",
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       "    if(this.current_frame < this.frames.length){\n",
       "      this.set_frame(this.current_frame);\n",
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       "      var loop_state = this.get_loop_state();\n",
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       "        this.pause_animation();\n",
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       "\n",
       "  Animation.prototype.anim_step_reverse = function()\n",
       "  {\n",
       "    this.current_frame -= 1;\n",
       "    if(this.current_frame >= 0){\n",
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       "      var loop_state = this.get_loop_state();\n",
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       "        this.play_animation();\n",
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       "        this.pause_animation();\n",
       "        this.first_frame();\n",
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       "\n",
       "  Animation.prototype.pause_animation = function()\n",
       "  {\n",
       "    this.direction = 0;\n",
       "    if (this.timer){\n",
       "      clearInterval(this.timer);\n",
       "      this.timer = null;\n",
       "    }\n",
       "  }\n",
       "\n",
       "  Animation.prototype.play_animation = function()\n",
       "  {\n",
       "    this.pause_animation();\n",
       "    this.direction = 1;\n",
       "    var t = this;\n",
       "    if (!this.timer) this.timer = setInterval(function(){t.anim_step_forward();}, this.interval);\n",
       "  }\n",
       "\n",
       "  Animation.prototype.reverse_animation = function()\n",
       "  {\n",
       "    this.pause_animation();\n",
       "    this.direction = -1;\n",
       "    var t = this;\n",
       "    if (!this.timer) this.timer = setInterval(function(){t.anim_step_reverse();}, this.interval);\n",
       "  }\n",
       "</script>\n",
       "\n",
       "<div class=\"animation\" align=\"center\">\n",
       "    <img id=\"_anim_imgIZPNPUQZWJQOVJBN\">\n",
       "    <br>\n",
       "    <input id=\"_anim_sliderIZPNPUQZWJQOVJBN\" type=\"range\" style=\"width:350px\" name=\"points\" min=\"0\" max=\"1\" step=\"1\" value=\"0\" onchange=\"animIZPNPUQZWJQOVJBN.set_frame(parseInt(this.value));\"></input>\n",
       "    <br>\n",
       "    <button onclick=\"animIZPNPUQZWJQOVJBN.slower()\">&#8211;</button>\n",
       "    <button onclick=\"animIZPNPUQZWJQOVJBN.first_frame()\"><img class=\"anim_icon\" src=\"data:image/png;base64,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\"></button>\n",
       "    <button onclick=\"animIZPNPUQZWJQOVJBN.previous_frame()\"><img class=\"anim_icon\" src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAQAAAAngNWGAAAAAXNSR0IArs4c6QAAAAJiS0dEAP+Hj8y/AAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH3QURCAgyTCyQ6wAAANRJREFUKM9jYBjO4AiUfgzFGGAp4+yayUvX6jMwMDCsYmBgOCS4OAOrSYmMgcc8/pd5Q3irC+Neh/1AlmeBMVgZmP8yMLD8/c/cqv9r90whzv/MX7Eq/MfAwMDIwCuZdfSV8U8WDgZGRmYGrAoZGRgY/jO8b3sj/J2F6T8j4z80pzEhmIwMjAxsSbqqlkeZGP//Z8SlkJnhPwMjwx/Guoe1NhmRwk+YGH5jV8jOwMPHzcDBysAwh8FrxQwtPU99HrwBXsnAwMDAsJiBgYGBoZ1xmKYqALHhMpn1o7igAAAAAElFTkSuQmCC\"></button>\n",
       "    <button onclick=\"animIZPNPUQZWJQOVJBN.reverse_animation()\"><img class=\"anim_icon\" src=\"data:image/png;base64,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\"></button>\n",
       "    <button onclick=\"animIZPNPUQZWJQOVJBN.pause_animation()\"><img class=\"anim_icon\" src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAQAAAAngNWGAAAAAXNSR0IArs4c6QAAAAJiS0dEAP+Hj8y/AAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH3QURCAkR91DQ2AAAAKtJREFUKM9jYCANTEVib2K4jcRbzQihGWEC00JuNjN8Z2Q0Zo3VYWA4lL005venH9+c3ZK5IfIsMIXMBtc12Bj+MMgxMDAwMPzWe2TBzPCf4SLcZCYY4/9/RgZGBiaYFf8gljFhKiQERhUOeoX/Gf8y/GX4y/APmlj+Mfxj+MfwH64Qnnq0zr9fyfLrPzP3eQYGBobvk5x4GX4xMIij23gdib0cRWYHiVmAAQDK5ircshCbHQAAAABJRU5ErkJggg==\"></button>\n",
       "    <button onclick=\"animIZPNPUQZWJQOVJBN.play_animation()\"><img class=\"anim_icon\" src=\"data:image/png;base64,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\"></button>\n",
       "    <button onclick=\"animIZPNPUQZWJQOVJBN.next_frame()\"><img class=\"anim_icon\" src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAQAAAAngNWGAAAAAXNSR0IArs4c6QAAAAJiS0dEAP+Hj8y/AAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH3QURCAkd/uac8wAAAMhJREFUKM9jYBie4DEUQ8B+fEq3+3UrMzAwMFxjYGBgYJizYubaOUxYFUaXh/6vWfRfEMIL/+//P5gZJoei4/f/7wxnY1PeNUXdE2RgYGZgYoCrY2BBVsjKwMDAwvCS4f3SG/dXxm5gYESSQ1HIwvCPgZmB8f8Pxv+Kxxb/YfiPJIdi9T8GJgaG/38ZFd4Fx0xUYsZt4h8GBgb2D2bLy7KnMTAwMEIxFoVCXIYr1IoDnkF4XAysqNIwUMDAwMDAsADKS2NkGL4AAIARMlfNIfZMAAAAAElFTkSuQmCC\"></button>\n",
       "    <button onclick=\"animIZPNPUQZWJQOVJBN.last_frame()\"><img class=\"anim_icon\" src=\"data:image/png;base64,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\"></button>\n",
       "    <button onclick=\"animIZPNPUQZWJQOVJBN.faster()\">+</button>\n",
       "  <form action=\"#n\" name=\"_anim_loop_selectIZPNPUQZWJQOVJBN\" class=\"anim_control\">\n",
       "    <input type=\"radio\" name=\"state\" value=\"once\" > Once </input>\n",
       "    <input type=\"radio\" name=\"state\" value=\"loop\" checked> Loop </input>\n",
       "    <input type=\"radio\" name=\"state\" value=\"reflect\" > Reflect </input>\n",
       "  </form>\n",
       "</div>\n",
       "\n",
       "\n",
       "<script language=\"javascript\">\n",
       "  /* Instantiate the Animation class. */\n",
       "  /* The IDs given should match those used in the template above. */\n",
       "  (function() {\n",
       "    var img_id = \"_anim_imgIZPNPUQZWJQOVJBN\";\n",
       "    var slider_id = \"_anim_sliderIZPNPUQZWJQOVJBN\";\n",
       "    var loop_select_id = \"_anim_loop_selectIZPNPUQZWJQOVJBN\";\n",
       "    var frames = new Array(0);\n",
       "    \n",
       "  frames[0] = 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\"\n",
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       "\n",
       "\n",
       "    /* set a timeout to make sure all the above elements are created before\n",
       "       the object is initialized. */\n",
       "    setTimeout(function() {\n",
       "        animIZPNPUQZWJQOVJBN = new Animation(frames, img_id, slider_id, 40, loop_select_id);\n",
       "    }, 0);\n",
       "  })()\n",
       "</script>\n"
      ],
      "text/plain": [
       "<matplotlib.animation.FuncAnimation at 0x120049b50>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from JSAnimation import IPython_display\n",
    "from matplotlib import animation\n",
    "from SimPEG import *\n",
    "\n",
    "fig, ax = subplots(1,2, figsize = (16, 5))\n",
    "ax[0].set_xlabel('Easting (m)')\n",
    "ax[0].set_ylabel('Depth (m)')\n",
    "ax[1].set_xlabel('Easting (m)')\n",
    "ax[1].set_ylabel('Depth (m)')\n",
    "\n",
    "\n",
    "def animate(i_id):\n",
    "    indx = 18\n",
    "    temp = dmap*(xc[i_id])\n",
    "    minval = (temp).min()\n",
    "    maxval = (temp).max()\n",
    "    \n",
    "    frame1 = mesh.plotSlice(temp, vType='CC', ind=indx, normal='X',ax = ax[1], grid=False, gridOpts={'color':'b','lw':0.3, 'alpha':0.5}, )\n",
    "    frame2 = mesh.plotSlice(chi, vType='CC', ind=indx, normal='X',ax = ax[0], grid=False, gridOpts={'color':'b','lw':0.3, 'alpha':0.5}, );\n",
    "    ax[0].set_title('True model', fontsize = 16)\n",
    "    ax[1].set_title('Estimated model at iteration = ' + str(i_id+1), fontsize = 16)\n",
    "    ax[0].set_ylim(-500, 0)\n",
    "    ax[1].set_ylim(-500, 0)\n",
    "    return frame1[0]\n",
    "\n",
    "animation.FuncAnimation(fig, animate, frames=2, interval=40, blit=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "matplotlib.rcParams.update({'font.size': 14, 'text.usetex': True, 'font.family': 'arial'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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3GfqtkvQlzc/Z7bmdXqGv66ZKXWZydPePmdnfAs8hSY2Ypke8A/gY8D+ZhAIi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\nIjX6/yfMAN86wQ4DAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11022bc50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "indx = 18\n",
    "iteration = 1\n",
    "fig, axes = subplots(1,2, figsize = (12, 5))\n",
    "vmin = chi.min()\n",
    "vmax = chi.max()\n",
    "ps1 = mesh.plotSlice(chi, vType='CC', ind=indx, normal='X',ax = axes[0], grid=True, gridOpts={'color':'b','lw':0.3, 'alpha':0.5});\n",
    "axes[0].set_title('$\\chi_{true}$', fontsize = 16)\n",
    "axes[0].set_ylim(-500, 0.)\n",
    "cb1 = colorbar(ps1[0], ax =  axes[0], orientation=\"horizontal\", ticks=[np.linspace(vmin, vmax, 5)], format = FormatStrFormatter('$%5.3f$'))\n",
    "axes[0].set_xlabel('Easting (m)')\n",
    "axes[0].set_ylabel('Depth (m)')\n",
    "\n",
    "vmin = (actMap*xc[iteration]).min()\n",
    "vmax = (actMap*xc[iteration]).max()\n",
    "ps2 = mesh.plotSlice(actMap*xc[iteration], vType='CC', ind=indx, normal='X', ax = axes[1], grid=True, gridOpts={'color':'b','lw':0.3, 'alpha':0.5});\n",
    "axes[1].set_title('$\\chi_{pred}$', fontsize = 16)\n",
    "axes[1].set_ylim(-500, 0.)\n",
    "cb2 = colorbar(ps2[0], ax =  axes[1], orientation=\"horizontal\", ticks=[np.linspace(vmin, vmax, 5)], format = FormatStrFormatter('$%5.3f$'))\n",
    "cb1.set_label('Susceptibility (dimensionless)')\n",
    "cb2.set_label('Susceptibility (dimensionless)')\n",
    "axes[1].set_xlabel('Easting (m)')\n",
    "axes[1].set_ylabel('Depth (m)')\n",
    "fig.savefig('model.png', dpi = 200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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jnvasX8cwEhor2+gZouxDP9PHyQk/5nQUzT0cLYfw5WeiGtCSk7ZLo1w+r7pp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\nX9b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      "text/plain": [
       "<matplotlib.figure.Figure at 0x5be7210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dpred_xc = survey.dpred(xc[iteration])\n",
    "fig, ax = plt.subplots(1,2, figsize = (12,7) )\n",
    "vmin = survey.dobs.min()\n",
    "vmax = survey.dobs.max()\n",
    "dat2 = ax[0].imshow(np.reshape(survey.dobs, (xr.size, yr.size), order='F'), extent=[min(xr), max(xr), min(yr), max(yr)], vmin = vmin, vmax = vmax)\n",
    "cb1 = plt.colorbar(dat2, ax = ax[0], orientation=\"horizontal\", ticks=[np.linspace(vmin, vmax, 5)])\n",
    "dat = ax[1].imshow(np.reshape(dpred_xc, (xr.size, yr.size), order='F'), extent=[min(xr), max(xr), min(yr), max(yr)], vmin = vmin, vmax = vmax)\n",
    "cb2 = plt.colorbar(dat, ax = ax[1], orientation=\"horizontal\", ticks=[np.linspace(vmin, vmax, 5)])\n",
    "ax[0].plot(rxLoc[:,0],rxLoc[:,1],'w.', ms=1)\n",
    "ax[1].plot(rxLoc[:,0],rxLoc[:,1],'w.', ms=1)\n",
    "ax[0].set_title('Observed', fontsize = 16)\n",
    "ax[1].set_title('Predicted', fontsize = 16)\n",
    "ax[0].set_xlabel('Easting (m)')\n",
    "ax[0].set_ylabel('Northing (m)')\n",
    "ax[1].set_xlabel('Easting (m)')\n",
    "ax[1].set_ylabel('Northing (m)')\n",
    "cb1.set_label('Total magnetic intensity (nT)')\n",
    "cb2.set_label('Total magnetic intensity (nT)')\n",
    "fig.savefig('obspred.png', dpi = 200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}