Pechelbronn_digitized.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Digitizing the Pechelbronn log\n",
    "\n",
    "[Original image](http://indico.ictp.it/event/a10175/session/25/contribution/15/material/0/0.pdf)\n",
    "\n",
    "Steps:\n",
    "\n",
    "- Import into Inkscape\n",
    "- Digitize with a line\n",
    "- Perform the steps in this notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fname = '../../Agile/Blog-and-wiki/Pechelbronn_log.svg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "\n",
    "with open(fname) as f:\n",
    "    soup = BeautifulSoup(f, 'lxml')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p = soup.find_all('path')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<path d=\"m 199.78713,695.03403 -6.66931,4.82268 -4.29366,1.93751 -6.30258,6.55896 1.4799,13.31914 -4.43971,5.91962 1.97321,10.85263 0,6.90622 3.94641,9.37273 -3.94641,7.39953 1.9732,11.83923 1.97321,7.89283 -4.43972,6.41292 -0.4933,10.35933 5.42632,8.38613 -0.4933,9.86603 -0.98661,8.87943 -0.4933,8.38612 5.42632,8.38613 -0.9866,8.38613 0,7.89282 1.9732,8.87943 -3.45311,8.38613 0.98661,7.89282 12.33253,6.90622 13.62131,9.39493 52.52552,8.38613 15.74123,9.84383 -53.76987,8.38613 -8.38612,6.41292 16.08781,10.63929 15.5279,8.19499 -15.03067,4.15975 -22.01136,6.11076 -20.22536,7.39952 17.26555,8.87943 7.89283,8.38613 5.02184,8.28381 -3.54194,9.96833 -14.79905,10.3593 1.97321,7.8929 8.87943,7.3995 20.71866,8.8794 6.90623,9.3728 -45.87705,6.4129 22.19857,8.8794 32.0646,9.866 87.80768,5.9197 -33.45568,10.1238 -11.43476,8.7104 -40.10415,8.8572 20.86539,8.8129 -14.79905,8.3861 -34.03781,9.3727 -16.44788,16.5812 10.10158,7.635 8.06176,9.3505 -35.00221,8.2173 -13.03918,8.3639 15.5279,8.8794 13.6213,7.915 19.14994,10.5061 2.51092,7.8349 -7.65728,8.7906 -11.06598,8.8573 -5.49293,7.9594 -0.94219,8.666 -18.50991,9.7994 5.14635,10.2484 10.6615,5.3906 -13.55469,9.0261 -4.50633,8.6662 26.40274,8.4305 0.81767,8.5994 -28.93586,8.9238 -1.88438,8.7019 -2.93761,8.1863 1.64884,9.2394 4.36438,6.0664 10.73768,12.3682 -7.06525,6.9768 -3.76877,8.9508 -4.00431,8.2442 -2.35549,9.1864 2.35549,8.7152 0.23554,4.4755 -2.11993,3.5332 6.59535,9.6575 6.12425,8.9508 -0.23555,8.0086 21.19933,8.4797 -0.4711,8.4798 -9.65747,9.1863 0,7.0665 -10.12857,9.4219 0.23555,11.3063 -3.76877,7.7731 -4.47541,7.7731 -1.41329,8.4797 3.53322,10.1286 0.94219,8.2442 -3.29767,8.0086 -2.35548,8.9508 0.70664,8.0087 0.94219,8.2442 1.64884,9.1863 0.23555,8.9509 -3.53322,8.7152 -0.4711,9.1864 0.23555,8.2442 -0.23555,8.9508 0.4711,8.7153 -0.23555,8.0086 0,8.9509 1.17774,8.7152 -1.17774,8.4798 1.17774,9.1863 -1.17774,8.0087 -1.64884,9.893 1.41329,7.302 0.4711,8.7153 -1.17774,7.7731 1.41329,8.2441 1.17774,9.422 0.70664,4.0043 -0.94219,4.7109 0.70664,3.7688 -0.47109,8.2442 -0.9422,5.182 0,10.1286 -0.47109,8.0087 -0.4711,8.7152 -0.23555,8.2442 -0.47109,9.1864 -0.23555,7.7731 -0.23555,8.4797 -0.23555,9.4219 0.23555,9.1864 0.23555,8.7153 0.23555,8.7153 0.70664,8.7152 0.70665,8.2442 9.18637,9.6575 -1.64884,8.4797 -5.8887,8.0087\" id=\"path4236\" inkscape:connector-curvature=\"0\" sodipodi:nodetypes=\"ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc\" style=\"fill:none;fill-rule:evenodd;stroke:#f60000;stroke-width:3;stroke-linecap:butt;stroke-linejoin:miter;stroke-miterlimit:4;stroke-dasharray:none;stroke-opacity:0.4979424\"></path>,\n",
       " <path d=\"m 125.26224,1363.0782 43.90383,0 44.01293,0 c 0,0 28.56301,0 42.84451,0 14.96348,0 44.20503,0 44.20503,0\" id=\"path4238\" inkscape:connector-curvature=\"0\" sodipodi:nodetypes=\"cccsc\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"></path>,\n",
       " <path d=\"m 163.9462,1124.1085 0,43.9038 0,43.9039 0,42.3045 0,43.2549 0,43.5196\" id=\"path4240\" inkscape:connector-curvature=\"0\" sodipodi:nodetypes=\"cccccc\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"></path>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "pairs = p[0]['d'][2:].split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "coords = np.array([[float(z) for z in pairs[0].split(',')]])\n",
    "for p in pairs[1:]:\n",
    "    point = np.array([float(z) for z in p.split(',')]) * np.array([1, -1])\n",
    "    coords = np.vstack([coords, coords[-1] + point])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = coords - np.array([0, coords[0,1]])\n",
    "c = c * np.array([1, -140/1209.22377])\n",
    "coords = c + np.array([0, 139])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = np.arange(139, 279+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = np.interp(d, coords[:,1], coords[:,0])\n",
    "r = r - np.min(r)\n",
    "r = r / np.max(r)\n",
    "res = 18 * r + 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Hu6rMbqW6toFTBRVUmMxXfrDg0bpscrOZM2cya9Ysx+K55+h0OrZu3dpsyYKNGzeSm5vL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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b9e0588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(3, 7))\n",
    "\n",
    "ax = fig.add_subplot(111)\n",
    "ax.semilogx(res, d)\n",
    "ax.set_title(\"Diefenbach No. 2905\", size=16)\n",
    "ax.set_xlabel(\"Resistivity [ohm.m]\", size=12)\n",
    "ax.set_ylabel(\"MD [m]\", size=12)\n",
    "ax.set_ylim([130, 290])\n",
    "ax.grid('on')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "plt.savefig(\"../../Agile/Blog-and-wiki/Pechelbronn_log_plot.png\", dpi=180)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  4.3887391 ,   2.85342702,   2.36525565,   2.48066798,\n",
       "         2.        ,   2.18885754,   2.27006814,   2.61885075,\n",
       "         2.23403111,   2.40714968,   2.65487833,   2.12425697,\n",
       "         2.07934099,   2.72583211,   2.67389656,   2.56526731,\n",
       "         2.49683948,   3.09135723,   3.03011393,   3.03318389,\n",
       "         3.25709305,   2.85145655,   3.19826338,   4.93931234,\n",
       "         7.63768533,  12.84723576,  13.4441711 ,   7.61632686,\n",
       "         7.47204332,   9.11532458,   9.74513338,   6.04116772,\n",
       "         4.11616955,   5.96903893,   6.88082902,   7.28068721,\n",
       "         6.82686744,   5.34298518,   5.38759582,   6.72234221,\n",
       "         9.01647038,   9.78183381,   4.92059263,   7.69070133,\n",
       "        12.031705  ,  20.        ,  17.02828857,  14.94904794,\n",
       "        11.5984186 ,  13.33439299,  11.11820116,   7.65433754,\n",
       "         6.62397517,   6.05706875,   7.28353051,   6.97565123,\n",
       "         3.32212242,   2.75582161,   4.56423536,   6.3900945 ,\n",
       "         8.05600943,   8.09354961,   7.10195983,   5.91774249,\n",
       "         5.3663145 ,   4.75306657,   3.12891264,   3.65051467,\n",
       "         4.45141283,   3.17747649,   3.68823312,   5.99188626,\n",
       "         5.03195508,   2.51946686,   2.25540659,   2.05955927,\n",
       "         2.38385499,   3.21532338,   3.89645149,   3.03211717,\n",
       "         2.57670297,   2.14707246,   2.01796229,   2.24403087,\n",
       "         2.22736208,   2.93698883,   3.52894838,   4.11051929,\n",
       "         6.04042682,   5.70401696,   4.83687322,   4.40388255,\n",
       "         3.62524774,   3.64688781,   3.1413042 ,   2.62315988,\n",
       "         2.56049729,   2.91464527,   2.99011071,   2.58585575,\n",
       "         2.35471636,   2.45146478,   2.58601801,   2.7453495 ,\n",
       "         2.71256502,   2.33745734,   2.28928865,   2.31286674,\n",
       "         2.29143342,   2.34223435,   2.31579123,   2.32956804,\n",
       "         2.44456665,   2.33008918,   2.4507335 ,   2.29560801,\n",
       "         2.1224883 ,   2.29452776,   2.32574011,   2.2410949 ,\n",
       "         2.40650898,   2.54551659,   2.51739781,   2.52763172,\n",
       "         2.40077101,   2.40077101,   2.34008511,   2.28560009,\n",
       "         2.25336707,   2.20107574,   2.16997917,   2.14159615,\n",
       "         2.11942701,   2.1460733 ,   2.17414682,   2.20222033,\n",
       "         2.2859124 ,   2.39920866,   3.38725027,   3.29359996,   2.57073177])"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'>'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-227-cfcf7f65c24a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"{:.1f}  {>:.3f}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m: '>'"
     ]
    }
   ],
   "source": [
    "for x, r in zip(d, res):\n",
    "    print(\"{:.1f}  {:.3f}\".format(x, r))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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