{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scripts for Calibration of Cernox Sensors\n",
    "---------------------------------------\n",
    "\n",
    "Make a copy of this notebook for an other run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "from scipy.interpolate import splrep, splev\n",
    "from zcalib import read_curve, convert_res, compare_calib, make_calib, logrange, Sensor, CalibRun, nplog, npexp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('lsdat', 'READ /afs/psi.ch/project/SampleEnvironment/SE_internal/Thermometer_calibs/2012/73027 Cernox 5/X75610.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c1.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c1.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c1.dat')\n",
      "{'selected': 0, 'averaged': 60}\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c2.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c2.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c2.dat')\n",
      "{'selected': 0, 'averaged': 60}\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c4.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c4.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c4.dat')\n",
      "{'selected': 0, 'averaged': 60}\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c5.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c5.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c5.dat')\n",
      "{'selected': 0, 'averaged': 60}\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c6.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c6.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c6.dat')\n",
      "{'selected': 0, 'averaged': 60}\n",
      "calibration file has 199 points\n"
     ]
    }
   ],
   "source": [
    "run = CalibRun([\n",
    "        Sensor(3, 'X75610'), # the reference sensor must be the first\n",
    "        Sensor(1, 'X133982', 'CX-1050-SD'),\n",
    "        Sensor(2, 'X137461', 'CX-1030-SD'),\n",
    "        Sensor(4, 'X133928', 'CX-1050-SD'),\n",
    "        Sensor(5, 'X131824', 'CX-1050-CU'),\n",
    "        Sensor(6, 'X132254', 'CX-1050-SD'),\n",
    "    ],\n",
    "    t_points = (1.0, 1.2) + logrange(1.4, 310, n=195) + (330,),\n",
    "    caldate = '2018-11-20',\n",
    "    logT = False,\n",
    "    logR = True,\n",
    "    calib_data_file = 'calib_data/calib%s_p%d_c%d.dat',\n",
    "    outputpath='%s/%s.340')\n",
    "run.make(diflim=0.001, smoothref=1e-7, smoothtst=1e-7)\n",
    "# smoothtst depends on number of measured points (1e-7 for 60, 0.8e-7 for 48 and 0.4e-7 for 24 points)\n",
    "print('calibration file has %d points' % len(run.t_points))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2018-10-25/X133928.340')\n",
      "('z340', 'READ 2018-11-20/X133928.340')\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlkAAAF2CAYAAABd6o05AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nweP4W+Q45wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3c50dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compare known sensors\n",
    "plt.figure(figsize=(10, 6))\n",
    "tmin,tmax,dmax=1.4,310,0.001\n",
    "testlist = (('X133928', 'z340'),)\n",
    "for sensno, kind in testlist:\n",
    "    r0, t0 = read_curve('2018-10-25/%s.340' % sensno, 'z340')\n",
    "    r1, t1 = read_curve('2018-11-20/%s.340' % sensno, kind)\n",
    "    diff = compare_calib(r1, t1, r0, t0)\n",
    "    plt.plot(t0, diff, '-')\n",
    "plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
    "plt.legend([sensno + \".\" + kind[-3:] for sensno, kind in testlist] + [\"window\"])\n",
    "plt.xscale('log')\n",
    "plt.yscale('symlog',linthreshy=dmax)\n",
    "plt.grid(True, axis='y')\n",
    "plt.axis([1.0,350,-1,1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2018-11-20/X133982.340')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c1.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c1.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c1.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEHCAYAAACgHI2PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSx98yjmnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3c62e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2018-11-20/X137461.340')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c2.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c2.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c2.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEHCAYAAACgHI2PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3d3f2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2018-11-20/X133928.340')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c4.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c4.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c4.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEHCAYAAACgHI2PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nF/f/g71GnsalkY4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x44033d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2018-11-20/X131824.340')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c5.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c5.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c5.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEHCAYAAACgHI2PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLk6JXkTExf0/c+egvzmGlL0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x43f4190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2018-11-20/X132254.340')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p0_c6.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p1_c6.dat')\n",
      "('zdat', 'READ calib_data/calib2018-11-20_p2_c6.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEHCAYAAACgHI2PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3Xd4lFX+BfDzTQNCSEIKLZFEkbLSBpCAlQAKKLgg2LCC\nq9jFRVewrLIqShGQBQv+RHRRRFFRWGm6EDSwdOktSw8QWigJCWlzfn9MVAjpPcP5PE8ecu97596b\n4c3JnXfuzBhJiIiI+/Ko6AmIiEjZUtCLiLg5Bb2IiJtT0IuIuDkFvYiIm1PQi4i4OQW9iIibU9CL\niLg5r/IczMx8AbwHIA3AEpLTy3N8EZGLUXmv6PsCmEnyEQB/LuexRUQuSiUKejObYmaHzWxDjvoe\nZrbNzHaY2dBzDoUD2J/9fVZJxhYRkcIp6Yp+KoDu51aYmQeASdn1zQH0N7Nm2Yf3wxX2AGAlHFtE\nRAqhREFPMhbAiRzVUQDiSO4lmQFgBoDe2cdmAbjNzN4FMKckY4uISOGUxZOxYfjj8gwAxMMV/iCZ\nAuDBgjowM72lpohIEZHM9UpJpd1eSbLSfr366quVuu+i9lGU9oVpW1CbvI4Xtb6yfJX1/HRO6Jwo\nTP/5KYugPwCg4Tnl8Ow6txEdHV2p+y5qH0VpX5i2BbXJ63hZ3q9lqaznrXOi6qls54QV9JegwA7M\nIgHMIdkyu+wJYDuArgAOAVgJoD/JrUXokyWdl7iP4cOHY/jw4RU9DalEdE5cyMzAsrh0Y2bTASwD\n0MTM9pnZQJJZAJ4CsBDAZgAzihLyIjlV1VWdlB2dE0VT4hV9WdCKXkSkaMpsRS8iIpWfgl5ExM0p\n6EVE3JyCXkTEzSnoRUTcnIJeRMTNKehFRNycgl5ExM0p6EVE3JyCXkTEzSnoRUTcnIJeRMTNKehF\nRNycgl5ExM0p6EVE3JyCXkTEzZVr0JvZpWb2kZl9VZ7jiohczMo16EnuJvlQeY4pInKxK1bQm9kU\nMztsZhty1Pcws21mtsPMhpbOFEVEpCSKu6KfCqD7uRVm5gFgUnZ9cwD9zaxZ9rH7zGycmdX/rXkx\nxxURkSIqVtCTjAVwIkd1FIA4kntJZgCYAaB3dvtpJIcASDOz9wE4tOIXESkfXqXYVxiA/eeU4+EK\n/9+RTATwWGE6czgccDgciIyMRGBgIBwOB6KjowEAMTExAKCyyiqrfNGWf/t++fLlSEhIQH6MZL4N\n8ryhWQSAOSRbZZf7AehOclB2+V4AUSSfLkbfLO68REQuRmYGkrleFi/NXTcHADQ8pxyeXSciIhWo\nJEFvOP9J1VUALjezCDPzAXAXgNklmZyIiJRccbdXTgewDEATM9tnZgNJZgF4CsBCAJsBzCC5tfSm\nKiIixVHsa/RlSdfoRUSKpryu0YuISCWkoBcRcXMKehERN6egFxFxcwp6ERE3p6AXEXFzCnoRETen\noBcRcXMKehERN6egFxFxcwp6ERE3p6AXEXFzCnoRETenoBcRcXMKehERN6egFxFxc17lOZiZ9QbQ\nE0AtAB+T/LE8xxcRuRhVyCdMmVkggDEkH87juD5hSkSkCEr9E6bMbIqZHTazDTnqe5jZNjPbYWZD\n8+niZQDvFmdsEREpmuJeo58KoPu5FWbmAWBSdn1zAP3NrFn2sfvMbJyZNTCzkQDmklxXgnmLiEgh\nFSvoScYCOJGjOgpAHMm9JDMAzADQO7v9NJJDAPQD0BXAbWY2qPjTFhGRwirNJ2PDAOw/pxwPV/j/\njuREABNLcUwRESlAue66KQqHwwGHw4HIyEgEBgbC4XAgOjoaABATEwMAKqusssoXbfm375cvX46E\nhATkp9i7bswsAsAckq2yyx0BDCfZI7s8DABJjipG39p1IyJSBKW+6+a3frO/frMKwOVmFmFmPgDu\nAjC7BP2LiEgpKO72yukAlgFoYmb7zGwgySwATwFYCGAzgBkkt5beVEVEJDcFXQGpkBdMFUSXbkRE\nCm/TkU1oWbdlmVy6ERGRSmDNwTX5HlfQi4hUcWsOKehFRNyagl5ExI1lObOwPmF9vm0U9CIiVdj2\n49tRz69evm0U9CIiVdiag2vQrkG7fNso6EVEqrA1h9agXX0FvYiI21LQi4i4sSxnFtYlrEPb+m3z\nbaegFxGpouIS4xDqG4raNWrn205BLyJSRRXmiVhAQS8iUmUV5vo8oKAXEamyFPQiIm7MSSd+PfRr\ngU/EAgp6EZEqKe54HIJ9gxHsG1xgWwW9iEgVtPbQ2kKt5oFyDnoza2Zm75vZl2b2l/IcW0TEnRT2\n+jxQzkFPchvJx+D6PNlu5Tm2iIg7+TWhcNfngeJ/ZuwUMztsZhty1Pcws21mtsPMhuZx21sA/ABg\nRnHGFhER4OiZo6jvV79QbYu7op8KoPu5FWbmAWBSdn1zAP3NrFn2sfvMbJyZ1Sc5h+TNAAYUc2wR\nkYteUnoSalWrVai2XsUZgGSsmUXkqI4CEEdyLwCY2QwAvQFsIzkNwDQz62RmwwBUB7C4OGOLiAiQ\nlJaEWj5lGPR5CAOw/5xyPFzh/zuSSwAsKcUxRUQuSmW+oi8PDocDDocDkZGRCAwMhMPhQHR0NAAg\nJiYGAFRWWWWVL8pyelY6Mndl4q3X38KKFSuQkJCA/BjJfBvkeUPXpZs5JFtllzsCGE6yR3Z5GACS\nHFWMvlnceYmIuLtjKcfQZGITJA5N/L3OzEDScmtfku2Vlv31m1UALjezCDPzgWsL5ewS9C8iIrlI\nSiv8ZRug+NsrpwNYBqCJme0zs4EkswA8BWAhgM0AZpDcWpz+RUQkb0nphX8iFij+rpu786ifB2Be\ncfoUEZHCKZcVvYiIVJyk9CT4V/MvdHsFvYhIFVOUPfSAgl5EpMopyh56QEEvIlLlaEUvIuLmirrr\nRkEvIlLFaNeNiIib04peRMTN6clYERE3pydjRUTcnFb0IiJuTit6ERE3pxW9iIib04peRMTNaUUv\nkpICxMYC+pQycUMkkZyeDD8fv0LfRkFfxZ1IPYHRS0fjYNLBip5K5TFsGNCtG9irFzbMP4h33gHi\n4yt6UiKl40zGGVTzrAYvj8J/nIiCvgrbcHgD2k5uhy9XLoLjAwe+3/Z9RU+p4i1dCufXM/HJN8Mx\nc2dNJPW9D2tWE61aAW+8UdGTEym5or79AaCgr9L6fTIIR797HofGzEef1Dl4aM5D2Htyb0VPq0Jx\n8GCMuSMcw5fPw0O9NiOk/mp8dNVEbN0KTJsGTJpU0TMUKZmivv0BoKCvspbvX4XdRxPww6sDsWnM\nPMR81Brdav0VD895GHSXa9NHjwITJgADBgAZGQW3P3IE6du3YGpYBjI/WYBtz63HtL92RcqwZ+Gx\n/2fMnw+89RYwZ06Zz1ykzLjVin7XiV3uE1jnSM1IxcQVk3DlyJtQ/76hGDhkV7GeM3zpu3fRfNcD\n6DSiJ4JefBTr2RLJf78Gh5OP4qvNXxV4+/R04OOPgcWLi/FD5OCks+Sd5JSWBkRHAytWABs3AjNn\nFniTrJgYxFyShbBfp+HFoT5oUM8Lrz/xDX55vCdO3dwV+5P+jW+/Bf7yF2DLltKfclVBEot2L0Kv\nqffg8hHXI/zFG3Hls6/h6de3YulSwFkG/51SeoqzogfJSvcFgA3GNmDdMXV564xbOWbpGC7dt5Sp\nGamsytYdWscBg+pwaUQIM2FM9fHiuCtD+MTTZ4rUz9EzR+n1ciD/17YX+cQTZEYGOWsWT1arw2ef\nmcbG/2zM9Mz0PG+/ZQt56aXkDTeQl1zi6iIrq4BBN28mX3qJ7NuXfPRRcsoUMjGRH67+kAFvBfCr\nTV8V6Wco0N//Tv75z6TTSf7732SbNq7v83Hg/r4c1bs+g4PJpKTzj+256yaua+jDh0ddy6HvL2b4\nJU6uXVu6U64KDiUd4nUf3ES/Yc1Yq+tE9noyho+N+zdvGD2Evq/Uof9DfRneZjPHjydTUip6tuVn\n3aF1HB07mi/89ALjT8X/cSAtjfzlF3LBAnLv3pIPlJ5Ojh1Ldu9O3ncfi3MSzt42mzd/fvMF9a44\nzyNT8zpQFl8AegDYBmAHgKH5tKPT6eSeE3s4fcN0PvnDk2w7uS19R/jyqo+u4rMLnuU3W77htqPb\neDzlOLOcBaVUxXI6nfzilw/4RbtqPFi7LodFTOfJI2l0JiRwe6MgTr68Jf+7LP8QO9ebCyYzss8t\ndNaufV6iHXtxLNd4tmfn9ztz8urJud721CmySRPyww9d5RMnyNY3bGLvN9/hv7f/O7fJkyNHkiEh\n5AsvkDNmkBMmkP368WzN6vz6qgDO+/F9ho0N44erPyzS/ZKndevoDAnhm89tZOO732fYoIeZ0aQZ\n+dNP+d7sUEQI7x/wEJ97LpeDWVnMmPRPpgTU5JjeoWz0Zhv6O37i4MHk9OnkzJnk99+TsbGu38XK\n5MABVx78ljNnM84y7ngcT6SeyP+GGRmukBo7lvz4Yy7+9iPWfKUea/R8mWPGpl8Q5MkH93L2P+7l\nqC6+nNryCo4Oeo4/vrSYzszC/X4dP05u2FDg3+NKJSMrg6/FvMbQ0aEcPG8wn577NENHh/L7dV+S\nb71F1q9Ptm1Ldu1KBgW5AnrHjuINFh/vWrDceCP53XfkuHGu36tPPilSN5+t/4x3zrzzgvpKEfRw\nXSb6H4AIAN4A1gFolkfbXH/ApLQkLtq1iCN+HsGbP7+Zl//zcgaODKTXa16sM6YOr3j3Cnaa2on9\nvuzHR+c8ypf/8zJnLf2YKZPfJT//nFy/vkh3aGGkZ6bzwOkDdGaf3U6n65dy6lRy5Upy+6HdHP90\nFBMCvPhji368qmUSjxz54/YnDu/lllAvvnHdmEKP2fSNbvw46g7yscfOP+B0clPj3vz2T3cybGwY\nz6SfyXmYt95KPvLIH3X/WvcvBo+sw2q3P8Tgt+ryhx0//HEwM5N86CGyQwdyz54LVv3tRzbiwWf+\nQgYF8cSjA9j41SD+eujXfOd+Jv0MNx3exHWH1v1+n50nI4OZbdpxwpXjWf35Ruw06Q7WGxrNt7rc\nRN57b94dHz7MUzU8WLvpCu7alc8Edu2is3NnHmvVmJ2fC2fUa4+y723p7NuX7NXL9Ttdvz45Zkwh\nHuWUsWXLyJ5dU9mz1hI+cukCXnvJHAbccx+rvxrI+qMiWHNETXb5tAtXxK8g6fr/zcggnSmp5MSJ\nZHg46XAw5cHH+Z+27bivlge3hzbh6bcmkQcPum6wdSs5ejR53XWkvz95yy1MGfYcv3usC8deX52b\nAkMZXyOC8Z/m/Ud25UryqqtcNw8Pd3W1eXN53UtFc/YsuXo1OW8e+e2S7Yz6sANv/NeN3H9qv6tB\nVhbj3h/B3UEeTLjxanLjxt+q+d0XKXyv6Ts87hnCse0+L9oCf88eslEj1x+P7PN+3+FTXPPj5zwT\nVocn3hlZqG7OpJ9h6/db57qoqixB3xHAvHPKw/Ja1ecV9HlJz0znoaRD3Hh4I5ds/IGLPhnO2MG3\ncmN0c5729eJ3zT25qEMdnqwTwOMtL+eBd15n2qnECzvKzCT37SvUY9YV8SsY/Uk0vV/zZshbQQwa\nFcRr3+/JOv3eYN0bprPzwCkc2KkzV9f15K+B9djZdxGjo10r6Jw+Gj+I+2v4ct+mUwWOm5iSSJ8X\nazE5OJxct+6C4ykHErnPK5IvDuzIUbGjzjs2ciQZFUWeTckiP/2Upy8L4xE/DyZ1uprzhyxgo05L\nGTIqhLsSd5HJyeRtt5GdO3PNkiRefTXp7e16NPDGG+S6vTtZd0xd16OphATysceYWrsWx/QO5Ynj\nBy6Y17J9y3j3N3fT/y1/Np3YlI0mNGLE+AiO/+/48y4znX7hTf7XvzNDnu/I5xe8SJLcEh/PJg/X\nZlJIvTyXi/FT3uH8ZtXZPqoQy8msLPK995gVHMTxD7Vgt2ndmJyW/PvhjRvJa64h+/TJfsCUnk4m\nJpbbUv/oUfK5uw9was0nmOpbm2ltHdzqCGdciAeTa9bgf6+4jY/X/5bh/ocZ0GUy7bn69Oz1NC/x\n3sq/2jjuRxgX+PRi30tWsu5lh+nZ/zYGDW3P737a5boEcdddZO3apI8PGRbmuhT3ww8XnPf7Tu7j\nY3OeYO97/Bhf3Y+L2t3HI7v/uJ9SU8khQ8i6dcmPPyazTiczc+ceTproZGio69FRruLiXIH31lvk\nzp1lch+mZ6bzs/Wfsc+MPgwbG8a6b17K0L9dzajoPvy7I5ozmoVzYaQX59dpzq0d72fG4GfJgQNd\nJ3j79tz42XiGjg7lsn3L+MsvroV4u3auB7TbvljLY8GNOa3ag4xdWIjLrnFxZEQEOWECnU7yg8lZ\nrHPTB8TzwfR+vD2ve+Jqxgd48O3bwvjhqsnnnYskXZeP1q5lxrq1vH/GXbznm3tyXSRVlqDvB+DD\nc8r3AvhnHm0LvvNI15/nlSvJd98lBwwgmzcnfX1dafbEE66HRAcPMiktid9u+ZbPzf0rh/+tPf/T\nvCYTq4PftfPjjO7hXNGuHhMaBjGjmjfPhgbRWaMG2b49OX/+BUPuTNzJO2feySYj6nH1o72Z1bYN\nnV5ezPD04TGvWkyo7c/jtWswpZond3doxoQpk7l5kzPXgP9NYkoipzp8uLD9oAJ/5PeXfcLuXa5m\nZtsr82yzYtJKHvEMYpdHA5iY4vqDNn06Wa8euX9rEtm7N5PbtmSfQf5cv3ouOX06nY0bc1vtjhzR\n/TouHHwL2aoVOWAAP3gnlXXrui7JnzlDrlnjWljX6PQumw69n19/Tf78s+sy+rdvbeOS5o2Z4OfJ\nFY88wE0bYzhl7RReP/V6Rr4TyXeWjef+BYu4pd/L3B5xA9fXv5Izm9fnKzfU5ZQ+f+PqyL7c5RnJ\nqwe344BZA867JHfPxLd5yLd6nsGw6o7r+Pb1HTh6dIF34R+2b6fzssv4bf82vHbKNTx19o8/tGlp\n5CP3neHUBi+6zoeAALJhQ9cdWcrXJpxOcvductYs8qUnTnB89WFMrlabpx97iuO+GsLgUcEcPG8w\nj5456rqOM3Ei2a0bnX61mFmvAdOaNmNiYHUe9/Xglh7tuHrWx/x2bQwHffkCa78VzMFzh+T+/FZy\ncqF+loOnD/KZT57g5y2rcUeADwfceC+7PbCadeqn897ep5n09gekw0FWr04GB5Pt23PNa/9mSAi5\naJHr0uXZjLM8fuYYj00czYzg2jz6YH+eeug+ZgUHM+3D93N/dEe6/rjOnUv+61+uhzgFzDc1I5Xv\nrXyPEeMj2HZCZ3Yb/DH71PsXvwy/hycCQnjskrpcc2tHxr76IFNnz+KWkd9zfOuP+Y9ao/n9zR9w\n5xcrmHTayQMHyBemzKP3i6EMjfqJX3zhGnr/qf18ZdErvOadVvy8lQc3hXjwtpdacsraKTybcfbC\nCa1c6fpjOnky09PJBwZmMGDgvfzT+Cu57uBGbtrkeoTdJmgndze4nLHt6vGu+2ty1Jg+3PbaYKZ2\n68asGr483SiSu+rXYHINL579/F+5/uz5Bb25jpc9M+sHoDvJQdnlewFEkXw6l7Zs3bo1HA4HIiMj\nERgYCIfDgejoaABAzOLFwIcfIvr774HGjRETHg40bYroe+8FWrRAzLJlAIAOHaLx88/Ae+/FIC4O\nSEyMRkoKcOZMDAJxGIPqbUbdgASs8TuFxHqZSO3gi3jvOMRvXo9uB+tj4tokHKx+KZ6t2Q+7ff3h\neeX/cKbuJ3gi9lJ0WheHa3v0xporH8Ezn5/B2bPA7GltEBmSjJjVqwF/f0R37+6ab0wMAPwx/1zK\n//zubXz03n/gv3sPYuO25tn+yrF/Rs/x8ejcsz2iJ0/Os7+tU5bh1plv4Ml+3XFg12DExwML3qmL\nK/5xJxY2qIuHLtuEkY+Nxd0t73bdPjMTbRJSseCZCfg1eA3adX0K887+A7FLDa+8EoOwsPP7f3bu\nC2jkNxiZ6+7Cjh0xqFkTaNIkGgEBwJbVT6LDgc8x9MhpbAmpjSXVIlE7rRZ6H9+D1HRPTKt7JZyt\n26BDiytR8+gerFj7EZJS18En0heTrnciukY3PHLlI+jSucvv4x09fQoZL9yOzvdPwPYOf7rg591z\nTy986f8i3v3hRezbV/D9/Xs5IQGLr78emwLT8fH9tfD13d9h/4b9wLZt6DRuHNahDR7OuB1/fycE\nvYM8gccfR8xllwFPP43orl0L/f+bs3zqFLB+fTQWLSZWr/kJftXO4PXQdei/dyK+bRWJBdcHYX7w\nWnRv1B29fHqhQa0GF/Z37bVAQgJiFiwAAgLg3zECY1e+gzXL1sDM0Lt7b/ylzV9wYOOBIs8vt/J1\n11+HtR+8jb0vvo7TnuloEJKFjvHAtPBa2HJVY1S/42pkOjOR9dnP6LxwB3wiffF0lDfi044jMA2Y\nsskTzY4SA7sEIyG0BrIaEuHxJ/HYlFNYfCkwvZ8PaEDWriwQRCcAk+YCS+GJzHp1cN9pwNfLFz/f\nfjvQtSuiu/xxfqSkp2Cr31a8/fNYRC4LwaUr/4S7Uz3RJWMBYhvUgU+X6xA9ZAjQrFmuP9+uXcCG\nDdGYNQs4ciQGPj7ANddEw3HrYny49nb4+vjCr4kfDiUfQjSj0fWyrniwz0AsuHsqvL4biqVXB2JO\nnxr4Z5/J8NznCaSmInrjRuDttxHz5JPIuuZ6TP7oavwSeg8a+O7BiBteR48bevw+/u7dwC8/dkTD\nb8Yj2OsL1PA4BO8wYH7TJMyukYHUs5ciKH0IRl3eEZfN6AF74AGgZ0/ExMRg+fLlSEhIwPr160HS\nkIvyDPqOAIaT7JFdHgbXX6BRubRlnvNyOsEnnsTZZWuwcPBcxKcG48gR4PBhnPfvkSNAairQrh3Q\nrx/QoQPQqBHg6wvUqOHqKj4e2LcP2L0b2LMHOHAASEwEnN5JSKkTg9Sgubhp/QI88p+9OB5QDSkB\nIWi26yRW+XfDi5mvYZPzClxxBXD//a4te97exb9/dp/YjXk3/gk3RD6OJl+Py7VNYmoiGoyIxLGJ\nvvBb/QvQuHG+ff5v3GfwGz4ACZHt0KLpZfCK+Qkpr72C6zymosflN2FE1xEX3GbX3gz86aN68J6y\nHk89EI7nnwdq1z6/TVpmGkLHhGLPM3sQVCMoz/GP/u8U9s5ciTNrtiLDPwTV27dAuwdaoobvhefi\n2cyz2H1iN2pVq4Vw//Bc+xt6U3P0TAjB9b8uOa8+JfkEGBSErq0OYvnq+vneJ7lKSgJvvx3Hd23C\nP5ueRN8zEWi+4RCy/vkOPO7oj6GvJGPuj8n412eZiPDLQN17H4GFhACffuo6oYpg/8mDeOT9T7Fw\nz7/hWW8LsngSD633xN9jnFjb0AtjbgpAjVZtER0RjXta3YOGAQ2L/vOUtfR0YNUqpB7ch32N62CP\nXyb2n96P5PRkeJgHgmsEo56HP1pOnoXAT2dhZ2oYGnIftnR4EPOjR2LpmupYtcr10ginEwhMP4J5\n6I4jNRtievNXEeaXhFv2fogmh37B0v4jsKtLSxz0/RHLj85FtaXLMXaxD+qmeWFPj6uwP9gbuw7v\nRMbO7Wi3JwjtDyQjzb8+PK6/FsG3XAPr0R0Iz/18Kiwnnfj10K8wM7Su2xqeHp6/HyOBgV33YuiB\np3H5of/gl3AnQn0C0HxfGjw6dwZGj0ZWZCPcPzANC2vfjg5RwDd3zkQ1r2q5jpWU5MqjlBSgYUOg\nTh2ClgkvD2+sWeN6d49bkj7HUxFz4PHVjPNua2aVIug9AWwH0BXAIQArAfQnuTWXthcE/bFjwKIf\ns9Dg1YfhszcOD4T8gGZR/qhXD6hTB6hb98J/AwIAy/XHLqLMTGDVKtcLeK6+GggJKYVOL3Tj0Bvw\n9YTlCDiwFwgOvuD4eys+xFd/n4GF+4/BZ+uGQvW5ZnsMpr18C3q06IPq10bjmbiJuLbhtZh400RY\nHnfO/bPuR/sGUXiqw5O5Hl+yZwme/+l5rHhoReF/uFIwdsKbuP2lN3DJ6TMwjz/mvvzrCfB98iXM\nfSYZw4YVs3OnE/jxR5z8ZDIWB53C6Ib7sS5zPzKyMlxvHpVWC8lJnqgVfAa+Tiemz/dFi0Rv+M6e\nhxqNmoIEtm8HFi0CqlVzLSquvhrw8XF1v2j3IrwybzyWH4xF6JHbMfbufui1ezdqjRwPCwtzvZKr\nQ4eS30mVTUoK0leuw8ydbbExrjq8vV2Lr44dXb+jZq4F2bF9KfCYOAEhn41HcmA4djTuiXkthyL+\npB8OHAA2bADOngWatU5CQOv/4NLU2YjauBp+R4Czp4JRPbwjGveOQotHroFXgzrl+iMmJABt2gBf\nv3cE7TJ+wmc7Z2FC0o+4pevj6BTRGSMnJGJV9TfRvV1TfHH7Z/Dx9Cn2WGfPAqOumY07Tv0f/vS/\n81/5l1/Ql9s1+uzg7gFX2McBGJZPO6alkYsXu3b0tWtHBvplcHGDu7mvcRduW5NcpbZwFdZXaxbw\n/64IYurfXs71eIux13NKo97kq68Wqd8NCRvYa3ovtvmgDadvmF7gdtRvt3zLrp92zfP46NjRHDxv\ncJHmUBqOJR/jAT9j7Jfn7576ZlA0J1/SvlS2OZ/L6XSed+34q69cu+GGjojn/62Yyv/r35RHa3rw\n//oPoKP1WYaFuZ7PGzjQ9TSRvz/Z/pa1DBvajdX+1oi1u0zhx29uZdaLL7ueMOnc2fU8kDuezGXg\nyBHXNf8JE1y58OabrueWUyvBy2t++okMDSWXLnWV95zYw0GznmbwX7swcHAXfrVuTt7PQxTRopd+\n4sbQ6AvqURmejC3KFwDWquV6PvTFF8klP6Yxq09f8qab3PpVHFnOLLZ69FIm1fQnT54879jek3tZ\n46XaPB0Y5tqsXIZOpp5kzRE1mZaZluvx2766jZ9v+LxM55CX71uHc3Tn+8+r+651AF92vFIu4+/c\n6dqNU6MG2aAB2SFiGlfWr8W4UB8ue/YuHl4Vw8MnD3B+3Hz2/PRWNh0WyhEPP8m9/Ycwq2UrMjDQ\ntVGgsu4/lGKbP9+11b5vX9cf++Bg8plnSn+zVuzY5dzm3/6C+ioZ9MeOZc8+NZXs2ZPs3du1y8bN\nvTpzBj9U8CCZAAANVUlEQVRrGsTM114/r37w3CG85apeTGt94X9wWXB84OCyfctyPXbJuEsYdzyu\nXOaR08+vPsNZEUG//x3cdnQbdwd48IvXtpTrPE6fdr2A6exZ0pmVxeWfvsmfulzKPbU9mOYJnvT1\nZKa3F53BQa6N5cOHu3aNZGSU6zylfCUkkJ9+6nrUsWdP2Yyx+tNN3FXjTxfUV8mgJ+naz3fjjeSd\nd1a+lyuWkcysLLa+vwWTatVynTUkNx3eRP/XQ/ifkJ7kBx+Uyzye/OFJjo69cK/iwdMHWXtk7VJ7\nGFpU6QfjeaKa8R/jN5Ekh4y/hwk+NZl4vBJd/khPJ48dc+tHn1JxNv+wmwe9L7mgPr+gr7Rvaoak\nJOCmm4D69YHPPy/ZlpYqxNPDAz2vmYQPmmchYdA9OJh0EA/PfgRhS4bgutRYoH//cpnHdRHXIXZ/\n7AX1qw6uQlRYVJ5P5JY17/phOFE3FEtnvYFla0/Cb9Y32NXuDtQOqpj55Mrb2/Vk+m/bu0RKUY1Q\nP1TPOlOk21TeoO/WDWjaFJg6FfD0LLi9Gxk+sBO+rfcF0pYsxogHG8NzZ2t8smkZvO/rD/j7l8sc\nrm14LWL3xV7wzpQrD6xEVFhUucwhL4F9+6I75uLaT6/EvRu8ETX64Qqdj0h58q3jB19ncpFuU3mD\nvn17YPJkwKPyTrGseHsD8z75M4bUXYTHZ0Vi1uiZaNGhluu92ctJg1oNEFg9ENuObTuvfsWBFRUe\n9LXvfAB/jauJmVnX4RK/AHhe07FC5yNSnmqFVIMnsgr3GQ3Zym0ffVGYGel0ltIm+KorNRVIOZWB\n4PWLgBtvLPc/egO+G4D2DdrjiagnALhe1FRnTJ0CXyhVLr78EnjgAeC55/QZgXJRIYHTHgHwPbIX\n3qGBv9fnt4++8i6XL/KQB1yXeIPreQPdu1fII5teTXph9o7Zv5d/3vszWtZtWfEhDwB33gmsWwf8\n7W8VPRORcmUGnDE/JCcU/vJN5Q16qXA9Lu+B/+7/L06ePQkAmBc3Dz0a9ajgWZ2jWTPXy59FLjKp\nnn5IPaqgl1Lg5+OHTpGdMC9uHgBg/s75uKnxTRU8KxFJ86yJ1GOF33mjoJd89WnaB99t/w57Tu5B\nYmoi2tZvW9FTErnopXn74ewxreillNzS9BbM2T4H7T5sh1ub3QoP0ykjUtHSq/khPbHwQe9VhnMR\nN1CnZh3sGrwLJBFaM7SipyMiADKr1YSdLPylGwW9FKieX72KnoKInCOruh/spC7diIi4LaevH7JO\nKehFRNwWfWsiK0m7bkRE3JefH5CkFb2IiNvy8PcDUrSiFxFxW57+NeFxRtsrRUTclmegHyy1kl66\nMbNmZva+mX1pZn8pz7FFRNyFd6AfPNMq6aUbkttIPgbgLgDdynNsERF34VO7JnzSynBFb2ZTzOyw\nmW3IUd/DzLaZ2Q4zG5rP7W8B8AOAGUUdW0REgOohfvDJKNtLN1MBdD+3wsw8AEzKrm8OoL+ZNcs+\ndp+ZjTOz+gBAcg7JmwEMKMbYIiIXveohfqiWWYZvgUAy1swiclRHAYgjuRcAzGwGgN4AtpGcBmBa\ndn0nAH0BVAewuKhji4iI63NjPbLKf9dNGID955Tj4Qr/85BcAmBJKY0pInJR8g2tCY8ifEB4pd1e\n6XA44HA4EBkZicDAQDgcDkRHRwMAYmJiAEBllVVW+aIsMz0dGUhC7CvDsXLlciQkJCA/BX44uJk9\nDuBhAARwM8mE7Es3c0i2ym7TEcBwkj2yy8MAkOSofDvPe0xWxg8tFxGpFEhkePggOeEMatf1AVDC\nDwcn+R7JNiTbkvztz4Zlf/1mFYDLzSzCzHzg2j45O2dfIiJSCsyQYjWRfKRwT8gWZ3vldADLADQx\ns31mNpBkFoCnACwEsBnADJJbi9q3iIgUjusDwgsX9MXZdXN3HvXzAMwran8iIlJ0Z738kJxQuCdk\n9aZmIiJVkW9N7N2cVKimCnoRkSoos0FDJK7dW6i2CnoRkSrI09ECHls2Fqqtgl5EpAoKvr4Fgg9u\nQmF2oivoRUSqIP9rWqI5N2FvIa7eKOhFRKqixo0Rzn3YuDK1wKYKehGRqsjbG4nBjXFoUcEvWVLQ\ni4hUUWlNWuLs6k0FtlPQi4hUUb7tW6DG/wreeaOgFxGpooI7tUBE0iYkFfC6KQW9iEgV5eloidae\nm7CxgEW9gl5EpKpq2BABOImt/z2RbzMFvYhIVeXhgZMNmiPx5835Nyun6YiISBlgi5bgxvx33ijo\nRUSqsIBrWiBwf/4X6RX0IiJVmG9UC7TyzH9FX+BnxpYmM+sNoCeAWgA+JvljHu30mbEiIoVx5AiS\nwpvBP+NEnp8ZW65B//ugZoEAxpB8OI/jCnoRkUJKrlkHtVKOFv/DwXMysylmdtjMNuSo72Fm28xs\nh5kNLaCblwG8W9SxRUTkQimXtsj3eHGu0U8F0P3cCjPzADApu745gP5m1iz72H1mNs7M6meXRwKY\nS3JdMcYWEZEcfNqVctCTjAWQc3d+FIA4kntJZgCYAaB3dvtpJIeQPGRmTwHoCuA2MxtU1LFFRORC\ngde2zPe4VymNEwZg/znleLjC/zwkJwKYWEpjiogIALTIf0VfWkFf6hwOBxwOByIjIxEYGAiHw4Ho\n6GgAQExMDACorLLKKl+05d++X758ORIOHkR+Ctx1Y2aPA3gYAAHcTDLBzCIAzCHZKrtNRwDDSfbI\nLg8DQJKj8u087zG160ZEpAjMrHS3V5pZJFxB3zK77AlgO1zX3w8BWAmgP8mCP/ok9/4V9CIiRZBf\n0Bdne+V0AMsANDGzfWY2kGQWgKcALASwGcCM4oa8iIiUrgp5wVRBtKIXESmaUl3Ri4hI1aKgFxFx\ncwp6ERE3p6AXEXFzCnoRETenoBcRcXMKehERN6egFxFxcwp6ERE3p6AXEXFzCnoRETenoBcRcXMK\nehERN6egFxFxcwp6ERE3p6AXEXFzCnoRETdXrkFvZpea2Udm9lV5jisicjEr16AnuZvkQ+U5pojI\nxa44Hw4+xcwOm9mGHPU9zGybme0ws6GlN0URESmJ4qzopwLofm6FmXkAmJRd3xxAfzNrln3sPjMb\nZ2b1z71JMecrIiJFVOSgJxkL4ESO6igAcST3kswAMANA7+z200gOIXnIzILM7H0ADq36RUTKh1cp\n9RMGYP855Xi4wv88JBMBPFaYDh0OBxwOByIjIxEYGAiHw4Ho6GgAQExMDACorLLKKl+05d++X758\nORISEpAfI5lvg1xvZBYBYA7JVtnlfgC6kxyUXb4XQBTJp4vcuev2LM68REQuVmYGkrleFi/w0o2Z\nPW5mv5rZWjOrl0ezAwAanlMOz64TEZEKVtwVfSRcK/qW2WVPANsBdAVwCMBKAP1Jbi3WpLSiFxEp\nkhKt6HPpbDqAZQCamNk+MxtIMgvAUwAWAtgMYEZxQ15EREpXsVb0ZU0rehGRoinVFb2IiFQtCnoR\nETenoBcRcXMKehERN6egFxFxcwp6ERE3p6AXEXFzCnoRETenoBcRcXMKehERN6egFxFxcwp6ERE3\np6AXEXFzCnoRETenoBcRcXMKehERN+dVnoOZmS+A9wCkAVhCcnp5ji8icjEq7xV9XwAzST4C4M/l\nPLZUUTExMRU9BalkdE4UTYmC3symmNlhM9uQo76HmW0zsx1mNvScQ+EA9md/n1WSseXioV9qyUnn\nRNGUdEU/FUD3cyvMzAPApOz65gD6m1mz7MP74Qp7AMj1sw2rgrI8yUqj76L2UZT2hWlbUJu8jlfV\nX96ynrfOiaqnsp0TJQp6krEATuSojgIQR3IvyQwAMwD0zj42C8BtZvYugDklGbsiKehL1ka/1OXf\nv86J8lXZzgkjWaIBzSwCwBySrbLL/QB0Jzkou3wvgCiSTxehz5JNSkTkIkQy1ysl5brrprDymqyI\niBRdkS7dmNnjZvarma01s3p5NDsAoOE55fDsOhERqQClcekmEq5LNy2zy54AtgPoCuAQgJUA+pPc\nWqKBRESkWEq6vXI6gGUAmpjZPjMbSDILwFMAFgLYDGCGQl5EpOKUeEUvIiKVW6V8MjYnvXWC5GRm\nlwJ4CYA/yTsqej5S8cysN4CeAGoB+JjkjxU8pUqjSqzos7doniD5g5nNIHlXRc9JKgcz+0pBL+cy\ns0AAY0g+XNFzqSwq5N0r9dYJklMxzglxcyU4J14G8G75zLJqqKi3Kb4o3zpB8lXUc+L3ZuUzPakA\nRT4nzGwkgLkk15XnRCu7Cgn6i/WtEyRvRT0nzCzIzN4H4NBK3z0V45x4Cq5t3beZ2aBynWwlV5me\njA3DH5dnACAerv9UkEwB8GBFTEoqVH7nRCKAxypiUlKh8jsnJgKYWBGTquz0CVMiIm6uMgW93jpB\nctI5ITnpnCiGigx6w/lPpK0CcLmZRZiZD4C7AMyukJlJRdE5ITnpnCgFFbW9Um+dIOfROSE56Zwo\nPVXiBVMiIlJ8lekavYiIlAEFvYiIm1PQi4i4OQW9iIibU9CLiLg5Bb2IiJtT0IuIuDkFvYiIm1PQ\ni4i4uf8Hqay8UUb9ROEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x4e92f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compare calibration files from points 0,1,2\n",
    "# with the optimized (average or selection of best)\n",
    "\n",
    "for sensor in run.sensors:\n",
    "    r0, t0 = read_curve(sensor.outputpath, sensor.outputkind)\n",
    "    plt.figure()\n",
    "    dif = [0,0,0]\n",
    "    for j in range(3):\n",
    "        rr, rt = read_curve(sensor.caldat_file[j], 'zdat')\n",
    "        rc, tc = make_calib(run.rref, run.tref, rr, rt, run.t_points)\n",
    "        dif[j] = compare_calib(r0, t0, rc, tc)\n",
    "        plt.plot(t0, dif[j], '-')\n",
    "    plt.xscale('log')\n",
    "    plt.yscale('symlog', linthreshy=0.001)\n",
    "    plt.grid(True, axis='y')\n",
    "    plt.axis([min(t0),max(t0),-1,1])\n",
    "    #plt.legend(['dif1','dif2','dif3','est'])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "2.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}