5 - Gaussian Fitting.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "# Fitting a Triple axis scan with LMFIT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "The ! allows you to run a system command from the command line.  Let's use ls to see what is in the Data/Fitting directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HB1_exp0762_scan0072.dat\r\n"
     ]
    }
   ],
   "source": [
    "!ls Data/Fitting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "Let's use the system command cat to see what is in the file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# scan = 72\r",
      "\r\n",
      "# date = 9/19/2017\r",
      "\r\n",
      "# time = 10:30:01 PM\r",
      "\r\n",
      "# proposal = 19284\r",
      "\r\n",
      "# experiment = Polarized neutron study on the UPt2Si2\r",
      "\r\n",
      "# experiment_number = 762\r",
      "\r\n",
      "# command = scan h 0 k 0.97 1.02 0.0025 l 0 e 0 preset countfile offon_mcu15\r",
      "\r\n",
      "# builtin_command = scan h 0 k 0.97 1.02 0.0025 l 0 e 0 preset countfile offon_mcu15\r",
      "\r\n",
      "# users = Garrett Granroth, Karel Prokes, Masaaki Matsuda, Jooseop Lee, Sachith Dissanayake\r",
      "\r\n",
      "# local_contact = Masaaki Matsuda\r",
      "\r\n",
      "# scan_title = (0,1,0) off/on 4.5 K\r",
      "\r\n",
      "# monochromator = Heusler\r",
      "\r\n",
      "# analyzer = Heusler\r",
      "\r\n",
      "# sense = +-+\r",
      "\r\n",
      "# collimation = 48-80-60-240\r",
      "\r\n",
      "# samplename = UPt2Si2\r",
      "\r\n",
      "# sampletype = crystal\r",
      "\r\n",
      "# samplemosaic = 30.000000\r",
      "\r\n",
      "# latticeconstants = 4.189588,4.189588,9.662000,90.000000,90.000000,90.000000\r",
      "\r\n",
      "# ubmatrix = 0.066991,0.228983,0.003071,-0.229093,0.066946,0.001089,0.000423,-0.007503,0.103447\r",
      "\r\n",
      "# mode = 0\r",
      "\r\n",
      "# plane_normal = 0.029673,0.010521,0.999490\r",
      "\r\n",
      "# ubconf = UB19Sep2017_100904PM.ini\r",
      "\r\n",
      "# preset_type = countfile\r",
      "\r\n",
      "# countfile = guide -16 parq\r",
      "\r\n",
      "# countfile = drive hguide off vguide off\r",
      "\r\n",
      "# countfile = count preset mcu 15\r",
      "\r\n",
      "# countfile = drive hguide on vguide on\r",
      "\r\n",
      "# countfile = count preset mcu 15\r",
      "\r\n",
      "# def_x = k\r",
      "\r\n",
      "# def_y = detector_1\r",
      "\r\n",
      "# col_headers = \r",
      "\r\n",
      "#   Pt.          h          k          l          e     time_1 detector_1  monitor_1      mcu_1     time_2 detector_2  monitor_2      mcu_2 focal_length         m1         m2       marc     mtrans     mfocus     fguide     hguide     vguide    tbguide     aguide     bguide     cguide         s1         s2        sgl        sgu        stl        stu   slita_bt   slita_lf   slita_rt   slita_tp         a1         a2          q         ei         ef    coldtip    tsample     temp_a\r",
      "\r\n",
      "      1    -0.0004     0.9701    -0.0000    -0.0069     15.018     40.000  22501.000     15.001     14.922    125.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.9734    -0.1441    18.1998   -32.8645   -33.1114    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4548    13.5001    13.5071     4.3153     5.2692     0.000\r",
      "\r\n",
      "      2    -0.0004     0.9727    -0.0000    -0.0069     14.842     54.000  22501.000     15.001     15.107    141.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.3216    -1.0590    19.1998   -32.9080   -33.2036    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4588    13.5001    13.5071     4.3020     5.1052     0.000\r",
      "\r\n",
      "      3    -0.0004     0.9751    -0.0000    -0.0069     14.951     46.000  22501.000     15.001     15.030    150.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.3216    -1.0590    19.2031   -32.9521   -33.2870    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4623    13.5001    13.5071     4.3024     4.9734     0.000\r",
      "\r\n",
      "      4    -0.0004     0.9777    -0.0000    -0.0069     14.908     59.000  22501.000     15.001     14.970    159.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.3147    -1.0590    19.2069   -32.9960   -33.3799    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4663    13.5001    13.5071     4.3024     5.2420     0.000\r",
      "\r\n",
      "      5    -0.0004     0.9800    -0.0000    -0.0069     14.855     65.000  22501.000     15.001     14.906    175.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.3151    -1.0723    19.2108   -33.0396   -33.4614    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4698    13.5001    13.5071     4.3089     4.8687     0.000\r",
      "\r\n",
      "      6    -0.0004     0.9827    -0.0000    -0.0069     14.911     84.000  22501.000     15.001     14.988    252.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7791     1.0521     0.0035    -3.3082    -1.0720    19.2140   -33.0834   -33.5544    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4737    13.5001    13.5071     4.3132     4.7641     0.000\r",
      "\r\n",
      "      7    -0.0004     0.9851    -0.0000    -0.0069     14.957    113.000  22501.000     15.001     14.954    316.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0053     1.7788     1.0521     0.0035    -3.3085    -1.0720    19.2172   -33.1277   -33.6386    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4773    13.5001    13.5071     4.3015     4.5514     0.000\r",
      "\r\n",
      "      8    -0.0004     0.9876    -0.0000    -0.0069     15.003    141.000  22501.000     15.001     15.092    585.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.3017    -1.0847    19.2205   -33.1718   -33.7288    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4812    13.5001    13.5071     4.3061     4.4372     0.000\r",
      "\r\n",
      "      9    -0.0004     0.9901    -0.0000    -0.0069     14.999    200.000  22501.000     15.001     15.075    951.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.3017    -1.0843    19.2205   -33.2156   -33.8170    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4849    13.5001    13.5071     4.3151     4.6551     0.000\r",
      "\r\n",
      "     10    -0.0004     0.9926    -0.0000    -0.0069     14.998    250.000  22501.000     15.001     14.929   1539.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7791     1.0521     0.0032    -3.2952    -1.0847    19.2205   -33.2594   -33.9032    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4886    13.5001    13.5071     4.3156     4.8553     0.000\r",
      "\r\n",
      "     11    -0.0004     0.9952    -0.0000    -0.0069     15.036    308.000  22501.000     15.001     14.958   2452.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.2952    -1.0970    19.2211   -33.3032   -33.9955    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4925    13.5001    13.5071     4.3028     4.7807     0.000\r",
      "\r\n",
      "     12    -0.0004     0.9976    -0.0000    -0.0069     14.955    353.000  22501.000     15.001     14.902   3038.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.2880    -1.0970    19.2205   -33.3477   -34.0788    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.4961    13.5001    13.5071     4.3177     4.6955     0.000\r",
      "\r\n",
      "     13    -0.0004     1.0002    -0.0000    -0.0069     14.774    361.000  22501.000     15.001     14.873   3554.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.2883    -1.0970    19.2211   -33.3916   -34.1705    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.5000    13.5001    13.5071     4.3203     4.6255     0.000\r",
      "\r\n",
      "     14    -0.0004     1.0026    -0.0000    -0.0069     15.044    334.000  22501.000     15.001     14.998   3611.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.2818    -1.1100    19.2211   -33.4356   -34.2555    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.5036    13.5001    13.5071     4.3219     4.5359     0.000\r",
      "\r\n",
      "     15    -0.0004     1.0052    -0.0000    -0.0069     14.899    346.000  22501.000     15.001     15.149   3370.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7791     1.0521     0.0035    -3.2815    -1.1100    19.2211   -33.4796   -34.3465    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.5075    13.5001    13.5071     4.3087     4.6306     0.000\r",
      "\r\n",
      "     16    -0.0004     1.0076    -0.0000    -0.0069     14.873    318.000  22501.000     15.001     14.693   2576.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.2750    -1.1103    19.2205   -33.5234   -34.4323    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.5111    13.5001    13.5071     4.3078     4.7448     0.000\r",
      "\r\n",
      "     17    -0.0004     1.0101    -0.0000    -0.0069     14.955    248.000  22501.000     15.001     14.909   1925.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7791     1.0521     0.0035    -3.2746    -1.1227    19.2211   -33.5680   -34.5213    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.5149    13.5001    13.5071     4.3109     4.6062     0.000\r",
      "\r\n",
      "     18    -0.0004     1.0127    -0.0000    -0.0069     15.021    193.000  22501.000     15.001     14.877   1235.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7791     1.0521     0.0035    -3.2685    -1.1230    19.2211   -33.6119   -34.6105    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.5187    13.5001    13.5071     4.3121     4.6649     0.000\r",
      "\r\n",
      "     19    -0.0004     1.0151    -0.0000    -0.0069     14.982    163.000  22501.000     15.001     14.980    684.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0053     1.7788     1.0521     0.0032    -3.2685    -1.1227    19.2211   -33.6560   -34.6957    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.5223    13.5001    13.5071     4.3141     4.9726     0.000\r",
      "\r\n",
      "     20    -0.0004     1.0177    -0.0000    -0.0069     14.881     93.000  22501.000     15.001     14.902    386.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.2616    -1.1353    19.2211   -33.7000   -34.7876    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.5263    13.5001    13.5071     4.3165     4.9570     0.000\r",
      "\r\n",
      "     21    -0.0004     1.0201    -0.0000    -0.0069     14.991     82.000  22501.000     15.001     14.964    201.000  22501.000     15.001     7.9186   -43.1188    41.9676    -0.2550     0.0000   290.0035     3.0057     1.7788     1.0521     0.0035    -3.2616    -1.1360    19.2656   -33.7437   -34.8715    -1.7000     0.6045     6.0010     0.0000    15.0000    15.0000    15.0000    15.0000    20.9835    41.9564     1.5298    13.5001    13.5071     4.3033     4.9927     0.000\r",
      "\r\n",
      "# Sum of Counts = 3851\r",
      "\r\n",
      "# Center of Mass = 0.999583+/-0.022780\r",
      "\r\n",
      "# Full Width Half-Maximum = 0.021844+/-0.008479\r",
      "\r\n",
      "# 10:42:28 PM  9/19/2017   scan completed.\r",
      "\r\n"
     ]
    }
   ],
   "source": [
    "!cat Data/Fitting/HB1_exp0762_scan0072.dat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "It is always good practice to import your libraries at the top of the file.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from lmfit import Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "Now load the data using the genfrom txt command.  Let's copy and paste the header names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([( 1., -0.0004, 0.9701, -0., -0.0069, 15.018,  40., 22501., 15.001, 14.922,  125., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7788, 1.0521, 0.0035, -3.9734, -0.1441, 18.1998, -32.8645, -33.1114, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.4548, 13.5001, 13.5071, 4.3153, 5.2692, 0.),\n",
       "       ( 2., -0.0004, 0.9727, -0., -0.0069, 14.842,  54., 22501., 15.001, 15.107,  141., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7788, 1.0521, 0.0035, -3.3216, -1.059 , 19.1998, -32.908 , -33.2036, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.4588, 13.5001, 13.5071, 4.302 , 5.1052, 0.),\n",
       "       ( 3., -0.0004, 0.9751, -0., -0.0069, 14.951,  46., 22501., 15.001, 15.03 ,  150., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7788, 1.0521, 0.0035, -3.3216, -1.059 , 19.2031, -32.9521, -33.287 , -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.4623, 13.5001, 13.5071, 4.3024, 4.9734, 0.),\n",
       "       ( 4., -0.0004, 0.9777, -0., -0.0069, 14.908,  59., 22501., 15.001, 14.97 ,  159., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7788, 1.0521, 0.0035, -3.3147, -1.059 , 19.2069, -32.996 , -33.3799, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.4663, 13.5001, 13.5071, 4.3024, 5.242 , 0.),\n",
       "       ( 5., -0.0004, 0.98  , -0., -0.0069, 14.855,  65., 22501., 15.001, 14.906,  175., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7788, 1.0521, 0.0035, -3.3151, -1.0723, 19.2108, -33.0396, -33.4614, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.4698, 13.5001, 13.5071, 4.3089, 4.8687, 0.),\n",
       "       ( 6., -0.0004, 0.9827, -0., -0.0069, 14.911,  84., 22501., 15.001, 14.988,  252., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7791, 1.0521, 0.0035, -3.3082, -1.072 , 19.214 , -33.0834, -33.5544, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.4737, 13.5001, 13.5071, 4.3132, 4.7641, 0.),\n",
       "       ( 7., -0.0004, 0.9851, -0., -0.0069, 14.957, 113., 22501., 15.001, 14.954,  316., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0053, 1.7788, 1.0521, 0.0035, -3.3085, -1.072 , 19.2172, -33.1277, -33.6386, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.4773, 13.5001, 13.5071, 4.3015, 4.5514, 0.),\n",
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       "       ( 9., -0.0004, 0.9901, -0., -0.0069, 14.999, 200., 22501., 15.001, 15.075,  951., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7788, 1.0521, 0.0035, -3.3017, -1.0843, 19.2205, -33.2156, -33.817 , -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.4849, 13.5001, 13.5071, 4.3151, 4.6551, 0.),\n",
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       "       (15., -0.0004, 1.0052, -0., -0.0069, 14.899, 346., 22501., 15.001, 15.149, 3370., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7791, 1.0521, 0.0035, -3.2815, -1.11  , 19.2211, -33.4796, -34.3465, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.5075, 13.5001, 13.5071, 4.3087, 4.6306, 0.),\n",
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       "       (17., -0.0004, 1.0101, -0., -0.0069, 14.955, 248., 22501., 15.001, 14.909, 1925., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7791, 1.0521, 0.0035, -3.2746, -1.1227, 19.2211, -33.568 , -34.5213, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.5149, 13.5001, 13.5071, 4.3109, 4.6062, 0.),\n",
       "       (18., -0.0004, 1.0127, -0., -0.0069, 15.021, 193., 22501., 15.001, 14.877, 1235., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7791, 1.0521, 0.0035, -3.2685, -1.123 , 19.2211, -33.6119, -34.6105, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.5187, 13.5001, 13.5071, 4.3121, 4.6649, 0.),\n",
       "       (19., -0.0004, 1.0151, -0., -0.0069, 14.982, 163., 22501., 15.001, 14.98 ,  684., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0053, 1.7788, 1.0521, 0.0032, -3.2685, -1.1227, 19.2211, -33.656 , -34.6957, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.5223, 13.5001, 13.5071, 4.3141, 4.9726, 0.),\n",
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       "       (21., -0.0004, 1.0201, -0., -0.0069, 14.991,  82., 22501., 15.001, 14.964,  201., 22501., 15.001, 7.9186, -43.1188, 41.9676, -0.255, 0., 290.0035, 3.0057, 1.7788, 1.0521, 0.0035, -3.2616, -1.136 , 19.2656, -33.7437, -34.8715, -1.7, 0.6045, 6.001, 0., 15., 15., 15., 15., 20.9835, 41.9564, 1.5298, 13.5001, 13.5071, 4.3033, 4.9927, 0.)],\n",
       "      dtype=[('Pt', '<f8'), ('h', '<f8'), ('k', '<f8'), ('l', '<f8'), ('e', '<f8'), ('time_1', '<f8'), ('detector_1', '<f8'), ('monitor_1', '<f8'), ('mcu_1', '<f8'), ('time_2', '<f8'), ('detector_2', '<f8'), ('monitor_2', '<f8'), ('mcu_2', '<f8'), ('focal_length', '<f8'), ('m1', '<f8'), ('m2', '<f8'), ('marc', '<f8'), ('mtrans', '<f8'), ('mfocus', '<f8'), ('fguide', '<f8'), ('hguide', '<f8'), ('vguide', '<f8'), ('tbguide', '<f8'), ('aguide', '<f8'), ('bguide', '<f8'), ('cguide', '<f8'), ('s1', '<f8'), ('s2', '<f8'), ('sgl', '<f8'), ('sgu', '<f8'), ('stl', '<f8'), ('stu', '<f8'), ('slita_bt', '<f8'), ('slita_lf', '<f8'), ('slita_rt', '<f8'), ('slita_tp', '<f8'), ('a1', '<f8'), ('a2', '<f8'), ('q', '<f8'), ('ei', '<f8'), ('ef', '<f8'), ('coldtip', '<f8'), ('tsample', '<f8'), ('temp_a', '<f8')])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# see https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.genfromtxt.html\n",
    "\n",
    "headers = \"    Pt.          h          k          l          e     time_1 detector_1  monitor_1      mcu_1     time_2 detector_2  monitor_2      mcu_2 focal_length         m1         m2       marc     mtrans     mfocus     fguide     hguide     vguide    tbguide     aguide     bguide     cguide         s1         s2        sgl        sgu        stl        stu   slita_bt   slita_lf   slita_rt   slita_tp         a1         a2          q         ei         ef    coldtip    tsample     temp_a\"\n",
    "# Note that by default, any consecutive whitespaces act as delimiter. \n",
    "data = np.genfromtxt('Data/Fitting/HB1_exp0762_scan0072.dat', names=headers.split())\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "If you want to see the list of names that can access the array use the dtype.names method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('Pt',\n",
       " 'h',\n",
       " 'k',\n",
       " 'l',\n",
       " 'e',\n",
       " 'time_1',\n",
       " 'detector_1',\n",
       " 'monitor_1',\n",
       " 'mcu_1',\n",
       " 'time_2',\n",
       " 'detector_2',\n",
       " 'monitor_2',\n",
       " 'mcu_2',\n",
       " 'focal_length',\n",
       " 'm1',\n",
       " 'm2',\n",
       " 'marc',\n",
       " 'mtrans',\n",
       " 'mfocus',\n",
       " 'fguide',\n",
       " 'hguide',\n",
       " 'vguide',\n",
       " 'tbguide',\n",
       " 'aguide',\n",
       " 'bguide',\n",
       " 'cguide',\n",
       " 's1',\n",
       " 's2',\n",
       " 'sgl',\n",
       " 'sgu',\n",
       " 'stl',\n",
       " 'stu',\n",
       " 'slita_bt',\n",
       " 'slita_lf',\n",
       " 'slita_rt',\n",
       " 'slita_tp',\n",
       " 'a1',\n",
       " 'a2',\n",
       " 'q',\n",
       " 'ei',\n",
       " 'ef',\n",
       " 'coldtip',\n",
       " 'tsample',\n",
       " 'temp_a')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtype.names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "# Plotting\n",
    "\n",
    "Note in the metadata the default columns to plot\n",
    "\n",
    "```\n",
    "# def_x = k\n",
    "# def_y = detector_1\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
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       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'$k (rlu)$')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f,ax=plt.subplots()\n",
    "data_x = data['k']\n",
    "data_y = data['detector_1']\n",
    "data_err=np.sqrt(data_y)\n",
    "ax.errorbar(data_x, data_y,yerr=(data_err),fmt='bo')\n",
    "ax.set_ylabel('counts')\n",
    "ax.set_xlabel('$k (rlu)$')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "# Fitting\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "For fitting we will use the LMFIT package.\n",
    "\n",
    "First we define a fuction.\n",
    "Note the Python Syntax is\n",
    "\n",
    "```def <function name> (<params>):\n",
    "    '''\n",
    "    <documentation string>\n",
    "    '''\n",
    "    <code>\n",
    "    return <value>```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "def gaussian_slope(x, A, center, fwhm, m, b):\n",
    "    '''\n",
    "    Gaussian with fwhm and a a linear background\n",
    "    '''\n",
    "    g=A * np.exp(-4 * np.log(2) * (x - center)**2 / fwhm**2)\n",
    "    return g+m*x+b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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QB96dMbaLJZdeNXoYl9LW/Sss3L3+JXZ7/SeoWOLI+0d0bMAoKYIgEAkARAA+tCn7pmWxbJv/WRB9KSztnH3obK3AY9a/Eb0LACoKQIgEEkABIA+sn7XwbJQNnXFjuhZfeKKh2Zlv9c3n3w1ehIA1BQBEIgkAAJAH3lwyuoskl0ybFzR0VkfV8z9yZwN2e/260OaipY2bwMGgFMlAAKRBEAA6CN/ct+MLJINfHZx9KQ+s/PAkeLcgfmrG8cu3Ro9CwBqhgAIRBIAAaAPvLH3cNnbf6fUydt/3/LFB/O3AX/n6deiJwFAzRAAgUgCIAD0gceOu/rvb1w7pmht74ye1aca4XcEgEoRAIFIAiAA9IHjL5Lxnafq79VxJ3qVY71c5AQAKk0ABCIJgABwlnad4O/jjanTv49Xz3/nEAAqSQAEIgmAAHCWfnrcFXLfdXX9XiH3gTq+0jEAVJIACEQSAAHgLH15xJwsiv3jk/OjJ1XMup0Hy94GPHvNruhZAFD1BEAgkgAIAGdh7+G24oLBo7Ig9uLCLdGzKuoTd03Nft+hLy2NngQAVU8ABCIJgABwFp5bsCmLYQMGjy72t7RFz6qou8evzH7n379xQlEqeRswAPREAAQiCYAAcBb+/ofzshj21cfmRk+quOVb95e9DXjhxj3RswCgqgmAQCQBEADO0KHW9uKdV4/OQtjT8zZGz6q4UqlUfOS2ydnvfXNTc/QsAKhqAiAQSQAEgDM0evEbWQQ7b9Co4s2DrdGz+sXNTc3Z7/6Ht032NmAA6IEACEQSAAHgDH336YVZBPvLh1+JntRvFm3aU/Y24NU7DkTPAoCqJQACkQRAADgDnZ2l4pJh47MA9uiMtdGz+k2pVCp+74YJ2e//yPTG+f0B4HQJgEAkARAAzsDiTXvLXgG3bufB6Fn96t9+vij7/f/6kdnRkwCgagmAQCQBEADOwD0TVmbx68O3Toqe1O+O/xuIAwaPLg61tkfPAoCqJAACkQRAADgDfzZ8Zha/rn1xafSkfrevpa04f9Co7H6Y8Pq26FkAUJUEQCCSAAgAp2nPodbi3IH5238nL98ePSvEFx+cld0PVz+/JHoSAFQlARCIJAACwGl6ceGWLHpdeNXooqWtI3pWiOGTV2f3xR/cPLEolUrRswCg6giAQCQBEABO03eefi2LXl95dE70pDCvv7Gv7GIoq7YfiJ4FAFVHAAQiCYAAcBo6O0vFJcPGZcHrsRlro2eFKZVKxe/dMCG7Px6etiZ6FgBUHQEQiCQAAsBpWLRpT9kr3tbtPBg9K9SVzyzK7o+/enh29CQAqDoCIBBJAASA0/CDCSuz2PWHt02OnhSuackb2X0yYPDo4uCR9uhZAFBVBEAgkgAIAKfhf9w/I4td1764NHpSuP0tbcX5g0Zl98v4ZduiZwFAVREAgUgCIACcojcPthbnDszf/jtlxY7oWVXhiodmZffLVc8vjp4EAFVFAAQiCYAAcIpeeG1zFrneefXooqWtI3pWVXhgyursvnn/TROLUqkUPQsAqoYACEQSAAHgFH3nqdeyyPU3j86JnlQ1mrfuK7s4yqrt+6NnAUDVEACBSAIgAJyCzs5S8dvXj8sC1+Mz10XPqhqlUqn4vRsmZPfPw9PWRM8CgKohAAKRBEAAOAVLt+wte4Xb+l0Ho2dVlSufWZTdP18e4RWSAPAWARCIJAACwCl4eNqaLG598JZJ0ZOqzshFb2T30a8PaSpa2zujZwFAVRAAgUgCIACcgr95dE4Wt658ZlH0pKqz68CRsldJzl23O3oWAFQFARCIJAACQC/aOjqLi4Y0ZWHrxYVbomdVpcvunpbdT3ePXxk9CQCqggAIRBIAAaAX89e/WfbKth37j0TPqkrXv7wsu5+++OCs6EkAUBUEQCCSAAgAvbhnwsosav3xnVOjJ1WtCa9vy+6rAYNHF4dbO6JnAUA4ARCIJAACQC/+/KFXsqh17YtLoydVrf0tbcV5g0Zl99e0lTuiZwFAOAEQiCQAAkAPWto6igFXjc6C1rhl26JnVbU/vX9Gdn/dNLo5ehIAhBMAgUgCIAD0YMaqnVnMOnfgyGLv4bboWVXttjHLs/vss/dOj54EAOEEQCCSAAgAPbilqTmPWffNiJ5U9WaKpgBQRgAEIgmAANCDP7kvfzvrzU3eztqbE71teuzSrdGzACCUAAhEEgAB4CT2tbQV5w4cmYWs6St3Rs+qCX/x7y6cAgDdCYBAJAEQAE5i/LJtWcQaMHh0cbi1I3pWTbh34srsvvv4nVOiJwFAKAEQiCQAAsBJXPfSsixiXfHQrOhJNePVDW9m9907rhxZ7Nh/JHoWAIQRAIFIAiAAnMQn7pqaBawfTFgZPalmtHd0Fu++Zkx2/73w2uboWQAQRgAEIgmAAHACOw8cKXsF2/z1u6Nn1ZSvPjY3u/+ufGZR9CQACCMAApEEQAA4gZcWbsni1UVDmoq2js7oWTXl4WlrsvvwA7dMjJ4EAGEEQCCSAAgAJzDoucVZvPqbR+dET6o5r7+xr+xVlBt3H4qeBQAhBEAgkgAIACfwsTumZOHqwSmroyfVnM7OUvHe68Zm9+Ozr/rvDQAakwAIRBIAAeA4uw+2lr1ybcGGN6Nn1aSvPzEvux8HPuvvAALQmARAIJIACADHGbN0axat3nW1v/93po7/O4AfvX1y9CQACCEAApEEQAA4zvUvL8ui1V8+/Er0pJq1cOOesldT7jxwJHoWAPQ7ARCIJAACwHE+c+/0LFjdNX5F9KSa1d7RWfz6kKbs/mxa8kb0LADodwIgEEkABIBuDhxpL84bNCoLVjNX74yeVdP++pHZ2f153UvLoicBQL8TAIFIAiAAdDN1xY4sVl0weFRxuLUjelZN+8GEldl9+ql7pkVPAoB+JwACkQRAAOjm9rHLs1j1p/fPiJ5U82at3pXdp+cOHFnsb2mLngUA/UoABCIJgADQzRcfnJXFqhtHvx49qea1tHUUFwzO31Y9ZcWO6FkA0K8EQCCSAAgAXY60dxQDrhqdhaoJr2+LnlUX/mz4zOx+vXVMc/QkAOhXAiAQSQAEgC7z1u3OItU5A0cWew95q2pfuGl0c3bffuGBWdGTAKBfCYBAJAEQALrcP3lVFqk+cdfU6El1Y1Lz9uy+HXDV6OJIu4urANA4BEAgkgAIAF3+5tE5WaQa8sKS6El1Y+/htuKcgSOz+3fuut3RswCg3wiAQCQBEACKoujoLBUXXzMmC1QvLdwSPauuXHb3tOz+vW/SquhJANBvBECoTcUpHlNO4XtdnlJ6PqW0OaXU2vXv810frzQBEACKoli6ZW8Wp95x5chi276W6Fl15doXl2b375dHzImeBAD9RgCE2tQXAfBtKaVHevn6h7tuVykCIAAURfHYjLVZnPrQrZOiJ9WdkYveyO7jd18zpujoLEXPAoB+IQBCbXrrSTs8pXRxD8e5PXyPm7p9nwUppT9PKf1O178Lun3uxor8BkcJgABQFMU/Pjk/i1Pf+9nC6El1Z/v+lrJXWS7ZvDd6FgD0CwEQatNbT9qhZ/j1F6aU2ru+x7yU0tuP+/yvdH286LrdBWf4c3ojAALQ8EqlUnHJsPFZmHp63sboWXXpD2+bnN3PI6avjZ4EAP1CAITadLYBcHi373HpSW5zabfb3H+GP6c3AiAADW/dzoNlr0xbt/Ng9Ky69K8/X5jdz9/40fzoSQDQLwRAqE1nEwB/KaW0pevrm3u57fKu223u+rq+JgAC0PCemb8pi1KXDBtflEr+Nl0lPD1vY3Zf/+4N7msAGoMACLXpbALged2+/sFebvtQt9v29PcEz5QACEDDG/zc4ixK/f0P50VPqlurdxwoe7Xl5j2Ho2cBQMUJgFCb3nrSLkspvZ5SOpxSOpBSWpVSeiKl9JEevvbT3b7+2738nO90u+0nz27yCQmAADS8T9w1NQtSD05ZHT2pbpVKpeI3rxub3d8vLtwSPQsAKk4AhNpUnMLxfErp/zrB136j220+38vP+Xy32/7DGez8tV6O9yUBEIAGduBIe3HuwPwVaXPX7Y6eVdf+5tE52f197YtLoycBQMUJgFCbDqWUfppS+npK6QMppfemlD6eUvp+SmlXOvaknpJS+o/Hfe2/dvv8Zb38nMu73fZ7Z7DzVEKlAAhAw5qxamcWoy4YPKpoaeuInlXX7p24MrvPP3Pv9OhJAFBxAiDUpl/t4XP/NaW0IB17Yv/zcZ8f0u1zH+3l53y0222vPoOdAiAA9OAHE/IY9dn7ZkRPqnszj4uu5w8aVRxuFV0BqG8CINSn81JKbenoE3vVcZ/rz1cAegswAPTgK8e9HfW6l5ZFT6p7B0/wtuvZa3ZFzwKAihIAoX6NSsee3P9ft4/3598A7I2LgADQsDo7S8VvXDsmC1EvL3JBiv5w+d3Tsvt9+GQXXgGgvgmAUL9uS8ee3L/T7eOuAgwAVWDV9v1ZhHrHlSOLLXsOR89qCFc9vzi737/2+LzoSQBQUQIg1K9b04kD4HndPv5gL9/joW63PbcCGwVAABrWU3M3ZBHq0hsnRE9qGM8t2JTd9799/biiVCpFzwKAihEAoX6NTMee3P+t28d/KaW0pevjzb18j+au223u+rq+JgAC0LD+7eeLsgj1zSdfjZ7UMNbvOlj26st1Ow9GzwKAihEAoT6dm1JqTUef2KtP8Pnh6dgT/9KTfI9Lu93m/gpsTEkABKCB/dEdU7IA9cj0tdGTGkapVCouGTYuu/+ffdV/iwBQvwRAqD2fSSn9hx4+/19TSgvSsSf2d09wmwtTSh1dn5+XUnr7cZ9/e9fHi5RSe0ppwNlNPikBEICGtPdQW9kr0BZseDN6VkP5+hPzsvv/qucXR08CgIoRAKH2rE9H38J7T0rpL1JKv59Sem9K6Y9SSt9PKe1Mx57U01NKv3yS73NTt9stSCldkVJ6X9e/3QPijZX5NVJKAiAADWry8u1ZfBpw1eiitb0zelZDeWDK6uwxuOzuadGTAKBiBECoPevTsSdtT8czKaVf7eH7vC2lNKKX7/FI1+0qRQAEoCHdMXZ5Fp8+N3xm9KSGM2ft7uwxOHfgyOLAkfboWQBQEQIg1J4Pp5SuSSk1pZRWpJR2p6Nv092TUlqcjl7Z9/dP4/t9MqX0Qjr6qsLWrn9fSCld3neTT0oABKAh/dXDs7P4dMOo16MnNZyWto7i/EGjssdhxqqd0bMAoCIEQCCSAAhAw+noLBUXDWnKwlPTkq3RsxrSZ++dnj0O90xYGT0JACpCAAQiCYAANJzX39hXdgGQ7ftbomc1pGtfXJo9Dl95dE70JACoCAEQiCQAAtBwnpy9PotOH7hlYvSkhvXSwi3ZY/GeoWOLzs5S9CwA6HMCIBBJAASg4Xz36YVZdPrnny6IntSwNu85XPZqzFXb90fPAoA+JwACkQRAABrOR2+fnAWnx2eui57UsEqlUvG7N4zPHo+fz/ffJADUHwEQiCQAAtBQ9h5uK3vF2cKNe6JnNbS//+G87PG46vnF0ZMAoM8JgEAkARCAhjJ95c4sNg0YPLo40t4RPauh3T95VfaYfPqe6dGTAKDPCYBAJAEQgIZy78SVWWz6k/tmRE9qeDNX51H2/EGjipY2URaA+iIAApEEQAAaytcez99ueu2LS6MnNbz9LW3FOQPzt2XPX/9m9CwA6FMCIBBJAASgYZRKpeKSYfkFJ55fsDl6FkVRfPzOKdnj8sj0tdGTAKBPCYBAJAEQgIaxec/hsguArN15MHoWRVH8y88WZo/Lt36yIHoSAPQpARCIJAAC0DBGLnoji0zvGTq2KJVK0bMoiuLJ2euzx+ZDt06KngQAfUoABCIJgAA0jBtGvZ5Fpi+NmBM9iS5LNu8te3Xm7oOt0bMAoM8IgEAkARCAhvGFB2ZlgemOcSuiJ9GlraOzeOfVo7PHZ9Ly7dGzAKDPCIBAJAEQgIbQ3tFZvOvqpiwwTWzeFj2Lbj43fGb2+Nwp0AJQRwRAIJIACNj2apkAACAASURBVEBDWLZlX9lbTHcdOBI9i26Gvbwse3y+8qi3aANQPwRAIJIACEBD+MmcDVlc+sAtE6MncZyXFm7JHqP3XuciLQDUDwEQiCQAAtAQ/u3ni7K49D9/siB6EsfZuPtQ2as01+86GD0LAPqEAAhEEgABaAh/fOfULCw9PG1N9CSOUyqVit++flz2OL3w2uboWQDQJwRAIJIACEDdO3CkvThnYP7KsnnrdkfP4gT+9rG52eM09KWl0ZMAoE8IgEAkARCAujdr9a4sKp03aFTR0tYRPYsT+MGEldlj9af3z4ieBAB9QgAEIgmAANS9B6aszqLSJ38wLXoSJzFlxY7ssRpw1eiitb0zehYAnDUBEIgkAAJQ9/7hh/OzqDT4ucXRkziJPYdayy4EsmjTnuhZAHDWBEAgkgAIQN279MYJWVB6et7G6En04A9vm5w9Xj+ctS56EgCcNQEQiCQAAlDXtu1rKXtF2cpt+6Nn0YNvP/Va9nh95+nXoicBwFkTAIFIAiAAdW3csm1ZTHr3NWOKjs5S9Cx68NiMtdlj9kd3TImeBABnTQAEIgmAANS128cuz2LSFQ/Nip5EL17d8Gb2mJ0zcGRx4Eh79CwAOCsCIBBJAASgrn15xJwsJt0w6vXoSfSipa2jOH/QqOxxm71mV/QsADgrAiAQSQAEoG6VSqXit64fl4WklxdtiZ7FKbj87mnZ4/bwtDXRkwDgrAiAQCQBEIC6tenNQ2UXANmw61D0LE7Blc8syh63b/1kQfQkADgrAiAQSQAEoG6NXvxGFpF+87qxRankAiC14MnZ67PH7sO3ToqeBABnRQAEIgmAANStm0Y3ZxHprx+ZHT2JU7Rk896yV2/uPdQWPQsAzpgACEQSAAGoW3/58CtZQLp1THP0JE5Ra3tnMWDw6Ozxm7FqZ/QsADhjAiAQSQAEoC6VSqXi4mvHZAGpacnW6Fmchs/eOz17/IZPXh09CQDOmAAIRBIAAahL63YeLHsL6ZY9h6NncRquen5x9vh940fzoycBwBkTAIFIAiAAdemF1zZn8eiSYeNdAKTGPD1vY/YYvv+midGTAOCMCYBAJAEQgLo07OVlWTz628fmRk/iNDVv3Vf2Ks5dB45EzwKAMyIAApEEQADq0hcenJWFozvHrYiexGlq7+gs3nl1fiGQScu3R88CgDMiAAKRBEAA6k5HZ6m4aEhTFo4mvL4tehZn4HPDZ2aP4w8mrIyeBABnRAAEIgmAANSdldv2l711dPv+luhZnIGhLy3NHsevPT4vehIAnBEBEIgkAAJQd56ZvymLRpfeOCF6EmfouQX5Y/m7N4yPngQAZ0QABCIJgADUnWtfzF819ndPeNVYrVq1/UDZqzm37fNqTgBqjwAIRBIAAag7/+P+GVkwum/SquhJnKHOzlLx7mvGZI/nuGX+niMAtUcABCIJgADUlfaOzuLCq/Irx05dsSN6FmfhiofyKzrfMXZ59CQAOG0CIBBJAASgrizbsq/sLaNvHmyNnsVZuGHU69nj+ZVH50RPAoDTJgACkQRAAOrKU3M3ZLHoA7dMjJ7EWXp50ZbsMf2t68cVpVIpehYAnBYBEIgkAAJQVwY/tziLRd/88avRkzhLG3YdKntV58bdh6JnAcBpEQCBSAIgAHXlM/dOz0LRA1NWR0/iLJVKpeI3rxubPa5NS96IngUAp0UABCIJgADUjbaOzmLA4PwCIDNX7YyeRR/4q4dnZ4/rbWNcCASA2iIAApEEQADqxtIte8veKrr3cFv0LPrAjaNdCASA2iYAApEEQADqxvEXAPngLZOiJ9FHXlqYXwjkkmEuBAJAbREAgUgCIAB14+rnl+QXAHnSBUDqxdqdB8te3bltX0v0LAA4ZQIgEEkABKBu/Ml9M7JAdP/kVdGT6COdnaXi3deMyR7fCa9vi54FAKdMAAQiCYAA1IX2js7iwqvyC4BMW7kjehZ96AsPzsoe37vHr4yeBACnTAAEIgmAANSF5q37yt4i+ubB1uhZ9KHrXlqWPb5ff2Je9CQAOGUCIBBJAASgLvxs3sYsDr3/ponRk+hjz766KXuMf//GCdGTAOCUCYBAJAEQgLpw7YtLszj0Dz+cHz2JPrZi2/6yV3nuOnAkehYAnBIBEIgkAAJQF/5s+MwsDN070d+HqzftHZ3FO6/O/87j1BX+ziMAtUEABCIJgADUvI7OUvGuq5uyMDR5+fboWVTAn97vSs8A1CYBEIgkAAJQ81ae4K2hO701tC5d/fyS7HH+5pOvRk8CgFMiAAKRBEAAat7xF4e41MUh6tZTczdkj/WHbp0UPQkATokACEQSAAGoede9tCyLQl9/Yl70JCpkyea9Za/23Hu4LXoWAPRKAAQiCYAA1LwvPDArC0J3j3cBkHrV2t5ZXDB4VPZ4z1y9M3oWAPRKAAQiCYAA1LTOzlJx0ZD8AiATm7dFz6KCPnXPtOzx/vepa6InAUCvBEAgkgAIQE1bveNA2VtCt+9viZ5FBV35zKLs8f7nny6IngQAvRIAgUgCIAA17YXXNmcx6He+Pz56EhX2o1fWZ4/5R2+fHD0JAHolAAKRBEAAatqwl/MLgHz1sbnRk6iw1zbuyR7zcwaOLA4eaY+eBQA9EgCBSAIgADXtiofyC4DcOW5F9CQqrKWtozhvUH4hkHnrdkfPAoAeCYBAJAEQgJrV2VkqLr5mTBaCxi1zAZBG8Im7pmaP+2Mz1kZPAoAeCYBAJAEQgJq1bufBsguAbN3rAiCN4LtPL8we9+/9bGH0JADokQAIRBIAAahZLy/akkWgS4aNK0qlUvQs+sGjM9Zmj/0n7poaPQkAeiQAApEEQABq1s1NzVkE+tKIOdGT6Cdz1+3OHvvzBo0qWto6omcBwEkJgEAkARCAmvWlEXOyCHRzU3P0JPrJgSPtxTkD87d/L9y4J3oWAJyUAAhEEgABqFmXDBufBaCXF22JnkQ/+sjtk7PH/8nZ66MnAcBJCYBAJAEQgJq0fV9L2QVA1u48GD2LfvStnyzIHv+Bzy6OngQAJyUAApEEQABq0qTm7Vn8uWhIU9HZ6QIgjeShqauzc+Az906PngQAJyUAApEEQABq0r0TV2bx53PDZ0ZPop/NXLUzOwcGDB5dtHV0Rs8CgBMSAIFIAiAANekfn5yfxZ9rXlgSPYl+tvdQW9nbwJdt2Rc9CwBOSAAEIgmAANSkD906KQs/T8/dGD2JAB+4ZWJ+HsxzHgBQnQRAIJIACEDN2ddS/sqvJZv3Rs8iwDd+5JWgANQGARCIJAACUHNmr9mVRZ/zB40qjrR3RM8iwH2TVmXnwp/5W5AAVCkBEIgkAAJQcx6dsTaLPpfdPS16EkEmL8+vBv2uq5uKDleDBqAKCYBAJAEQgJrzvZ8tzKLP9362MHoSQXbsP1L2dvBV2/dHzwKAMgIgEEkABKDmXHb3tCz4jJi+NnoSgX7vhgnZ+fD8gs3RkwCgjAAIRBIAAagpR9o7ivMHjcqCz+w1u6JnEehrj8/NzodhLy+LngQAZQRAIJIACEBNWbJ5b9lbPve3tEXPItCd41Zk58MVD82KngQAZQRAIJIACEBNeXruxiz2fOjWSdGTCDZu2bbsnLj4mjFFpwuBAFBlBEAgkgAIQE255oUlWez5xo/mR08i2Bt7D5e9KnTdzoPRswAgIwACkQRAAGrK54bPzELPvRNXRk8iWKlUKn77+nHZefHyoi3RswAgIwACkQRAAGpGZ2epuGhIUxZ6JjVvj55FFfjSiDnZeXHT6OboSQCQEQCBSAIgADVj7c6DZW/13L6vJXoWVeCWpubsvPjrR2ZHTwKAjAAI9eeWdOxJXaSU/vAUvubylNLzKaXNKaXWrn+f7/p4JQmAANSMlxdtySLPJcPGFaWSiz1QFKMWv5GdG++9bqxzA4CqIgBCfXlvSqk9nXoAfFtK6ZHjbn/88XDX7SpBAASgZtx83Ku8vjRiTvQkqsSGXYfKXh26ec/h6FkA8AsCINSPt6WU5qajT+bt6dQC4E3dbrcgpfTnKaXf6fp3QbfP3VihzQIgADXjy8f9nbebm/ydN44qlUrFxdeOyc6PMUu3Rs8CgF8QAKF+fDsdfSI3p6PBrrcAeGE69mrBeSmltx/3+V/p+njRdbsL+nyxAAhADblk2HhXeuWkrnhoVnZ+3DFuRfQkAPgFARDqw39PKR1IR5/IH04pDU29B8Dh3W5z6Uluc2m329zfZ2uPEQABqAnb97WUvcVzzY4D0bOoIte/vCw7P772+LzoSQDwCwIg1IeX09En8eNd/3to6jkA/lJKaUs69orBnizvut3mrq/rSwIgADVhUvP2LO5cNKSp6Ox0kQeOefbVTdk58vs3ToieBAC/IABC7ftiOvoE3p1S+i9dHxuaeg6A53X7/IO9fP+Hut323LNemxMAAagJ901alcWdzw2fGT2JKrN86/6yV4m+ebA1ehYAFEUhAEKt+9WU0tZ09An89W4fH5p6DoCf7vb5b/fyM77T7bafPKu15QRAAGrCPz45Pws717ywJHoSVaato7MYcNXo7DyZvnJn9CwAKIpCAIRa9+/p6JN3Rsrfnjs09RwAv9Ht85/v5Wd8vttt/+E09/1aL8f7kgAIQA340K2TsrDz1NwN0ZOoQp+5d3p2njw0dXX0JAAoikIAhFr2wZRSKR29Qu/Fx31uaOo5AP5rt89f1svPubzbbb93mhuLUz0EQACq1b6WtrK3di7ZvDd6FlVo4LOLsvPkn3+6IHoSABRFIQBCrfpP6ejFO4qU0q0n+PzQ1HMAHNLt8x/t5Wd9tNttrz7NnQIgADVvztrdWdQ5f9Co4kh7R/QsqtAPX1mfnSsfu2NK9CQAKIpCAIRaNTQdfdJuSCn97z18PvoVgN4CDEDNe3TG2izqXHb3tOhJVKn569/MzpVzB44sDreKxQDEEwCh9rwrpdSajj5pP3uS2wxN1fE3AHvjIiAAVL3v/WxhFnW++/TC6ElUqUOt7cU5A/O3iy/Y8Gb0LAAQAKEGPZSOPmHXpJT+/CTHM+nYE/v6bh9/69WCrgIMAKfosrunZUFnxPS10ZOoYh+9fXJ2vvzolfXRkwBAAIQa9Hg6jb+td9xxTtf3OK/bxx7s5ec91O225/bZb3GUAAhAVWtt7ywuGDwqCzqz1+yKnkUV+9ZPFmTny8BnF0dPAgABEGrQ4+nsA+AvpZS2dH2suZef99bFRjZ3fV1fEgABqGpLNu8tuwLwvpa26FlUsQemrM7Ol8/eNyN6EgAIgFCnhqae/wZgSikN73abS09ym0u73eb+Pl14lAAIQFV7eu7GLOZ88JZJ0ZOoctNW7sjOmQuvGl20d3RGzwKgwQmAUJ+Gpt4D4IUppY6u28xLKb39uM+/vevjRUqpPaU0oAI7BUAAqto1LyzJYs43fjQ/ehJVbvfB1rJXja7Ytj96FgANTgCE+jQ09R4AU0rppm63W5BSuiKl9L6ufxd0+9yNFdopAAJQ1T7/wMws5Nw7cWX0JGrApTdOyM6b5xb47xwAYgmAUJ+GplMLgG9LKY3odtsTHY903a4SBEAAqlZnZ6m4aEhTFnImNW+PnkUN+Opjc7Pz5vsjl0VPAqDBCYBQn4amUwuAb/lkSumFdPTCIK1d/76QUrq8MvN+QQAEoGqt3Xmw7K2c2/e1RM+iBtwxdnl23vzFv78SPQmABicAApEEQACq1suLtmQR55Jh44pSqRQ9ixrQtGRrdu68Z+hY5w4AoQRAIJIACEDVuqWpOYs4XxoxJ3oSNWLj7kNlrx7d9Oah6FkANDABEIgkAAJQtb48Yk4WcG5uao6eRI0olUrFb1w7Jjt/xi7dGj0LgAYmAAKRBEAAqtYlw8ZnAeflRVuiJ1FDrnhoVnb+3DluRfQkABqYAAhEEgABqErb97WUvYVzzY4D0bOoIde/vCw7f772+LzoSQA0MAEQiCQAAlCVJi3fnsWbi4Y0FZ2dLuLAqXtm/qbsHHr/TROjJwHQwARAIJIACEBVum/SqizefG74zOhJ1JjmrfvKXkX65sHW6FkANCgBEIgkAAJQlf7xyflZuLnmhSXRk6gxbR2dxYCrRmfn0YxVO6NnAdCgBEAgkgAIQFX60K2TsnDz1NwN0ZOoQZ+5d3p2Hj00dXX0JAAalAAIRBIAAag6+1vayt66uWTz3uhZ1KArn1mUnUf/66cLoicB0KAEQCCSAAhA1ZmzdncWbc4fNKo40t4RPYsa9MNZ67Jz6Y/umBI9CYAGJQACkQRAAKrOozPWZtHmsrunRU+iRs1f/2Z2Lp07cGRxuFVMBqD/CYBAJAEQgKrzvZ8tzKLNd59eGD2JGnWotb04Z2D+dvIFG96MngVAAxIAgUgCIABV5/K7p2XBZsT0tdGTqGEfuX1ydj49OXt99CQAGpAACEQSAAGoKq3tncUFg0dlwWb2ml3Rs6hh//MnC7LzadBzi6MnAdCABEAgkgAIQFVZsnlv2RWA97W0Rc+ihj0wZXV2Pn32vhnRkwBoQAIgEEkABKCqPD13YxZrPnjLpOhJ1LipK3Zk59SFV40u2js6o2cB0GAEQCCSAAhAVbn2xaVZrPnGj+ZHT6LG7TpwpOxVpSu37Y+eBUCDEQCBSAIgAFXl8w/MzELNvRNXRk+iDvzeDROy8+r5BZujJwHQYARAIJIACEDV6OwsFRcNacpCzaTm7dGzqANffWxudl59f+Sy6EkANBgBEIgkAAJQNdbuPFj2Vs1t+1qiZ1EHbh+7PDuv/vLhV6InAdBgBEAgkgAIQNUYueiNLNJcMmxcUSqVomdRB5qW5OfWb1431rkFQL8SAIFIAiAAVeOWpuYs0nxpxJzoSdSJjbsPlb26dPOew9GzAGggAiAQSQAEoGp8ecScLNDc3NQcPYk6USqViouvHZOdX2OXbo2eBUADEQCBSAIgAFXjkmHjs0Dz0sIt0ZOoI198cFZ2ft01fkX0JAAaiAAIRBIAAagK2/e3lL1Fc82OA9GzqCPXvbQsO7++/sS86EkANBABEIgkAAJQFSYt357FmYuGNBWdnS7SQN95Zv6m7Bx7/00ToycB0EAEQCCSAAhAVbhv0qosznxu+MzoSdSZ5q37yl5luudQa/QsABqEAAhEEgABqAr/+OT8LMwMeWFJ9CTqTFtHZzHgqtHZeTZz1c7oWQA0CAEQiCQAAlAVPnzrpCzMPDV3Q/Qk6tCn75menWf/PnVN9CQAGoQACEQSAAEIt7+lreytmUs2742eRR268plF2Xn2v366IHoSAA1CAAQiCYAAhJuzdncWZc4fNKo40t4RPYs69MSsddm59vE7p0RPAqBBCIBAJAEQgHCPzlibRZlP3DU1ehJ1av76PDafN2hU0dImNgNQeQIgEEkABCDcv/xsYRZlvvv0wuhJ1KmDR9qLcwbmbzd/beOe6FkANAABEIgkAAIQ7vK7p2VBZsT0tdGTqGMfuX1ydr49OXt99CQAGoAACEQSAAEI1dreWVwweFQWZGav2RU9izr2Tz9+NTvfBj+3OHoSAA1AAAQiCYAAhFqyeW/ZFYD3tbRFz6KODZ+8Ojvf/uS+GdGTAGgAAiAQSQAEINTT8zZmMeaDt0yKnkSdm7piR3bOvfPq0UVHZyl6FgB1TgAEIgmAAIS69sWlWYz5xo/mR0+izu08cKTsVaertu+PngVAnRMAgUgCIAChPv/AzCzE3DtxZfQkGsDv3jA+O+9eeG1z9CQA6pwACEQSAAEI09lZKi4a0pSFmInN26Jn0QD+9rG52Xl3w6jXoycBUOcEQCCSAAhAmHU7D5a9FXPbvpboWTSA28cuz867v3z4lehJANQ5ARCIJAACEGbkojeyCHPJsHFFqeRiDFRe05L83HvvdWOdewBUlAAIRBIAAQhzS1NzFmG+NGJO9CQaxIZdh8pefbplz+HoWQDUMQEQiCQAAhDmyyPmZAHmptHN0ZNoEKVSqbj42jHZ+Tdumb8/CUDlCIBAJAEQgDDv+35+JdaXFm6JnkQD+eKDs7Lz767xK6InAVDHBEAgkgAIQIjt+1vK3oK5ZseB6Fk0kKEvLc3Ov797Yl70JADqmAAIRBIAAQgxafn2LL78+pCmorPTRRjoPz+fvyk7B99/08ToSQDUMQEQiCQAAhDivkmrsvjyZ8NnRk+iwbz+xr6yV6HuOdQaPQuAOiUAApEEQABCfPPJV7PwMuSFJdGTaDBtHZ3FgMGjs/Nw5uqd0bMAqFMCIBBJAAQgxIdvnZSFl6fmboieRAP61D3TsvPw4WlroicBUKcEQCCSAAhAv9vf0lb21sslm/dGz6IB/dvPF2Xn4befei16EgB1SgAEIgmAAPS7OWt3Z9Hl/EGjiiPtHdGzaEBPzFqXnYsfv3NK9CQA6pQACEQSAAHod4/NWJtFl0/cNTV6Eg1q/vo8Rp83aFTR0iZGA9D3BEAgkgAIQL/7l58tzKLLd59eGD2JBnXwSHtxzsD87egLN+6JngVAHRIAgUgCIAD97vK78wsvjJi+NnoSDewjt03Ozscfz3ZBGgD6ngAIRBIAAehXre2dxQWDR2XB5ZU1u6Jn0cD+6cevZufj4OcWR08CoA4JgEAkARCAfrV0y96yKwDva2mLnkUDGz55dXY+/un9M6InAVCHBEAgkgAIQL96et7GLLZ88JZJ0ZNocFNW7MjOyXdd3VR0dJaiZwFQZwRAIJIACEC/uvbFpVls+caP5kdPosHtPHCk7FWpq7bvj54FQJ0RAIFIAiAA/erzD8zMQss9E1ZGT4Lid28Yn52XL7y2OXoSAHVGAAQiCYAA9JvOzlLx7mvGZKFlYvO26FlQ/M2jc7Lz8sZRr0dPAqDOCIBAJAEQgH6zbufBsrdabtvXEj0LitvGLM/Oy796eHb0JADqjAAIRBIAAeg3Ixe9kUWWS4aNK0olF1sg3ujF+bn53uvGOjcB6FMCIBBJAASg39zS1JxFlr9+xKusqA4bdh0qe3XqG3sPR88CoI4IgEAkARCAfvOV4/7O2k2jm6MnQVEUR/8+5cXH/X3K8cv8fUoA+o4ACEQSAAHoN+/7fn6l1ZcWbomeBL/whQdnZefn3eNdoRqAviMAApEEQAD6xfb9LWVvsVyz40D0LPiFoS8tzc7Pv3tiXvQkAOqIAAhEEgAB6BeTlm/P4sqvD2kqOjtdZIHq8fP5m7Jz9A9unhg9CYA6IgACkQRAAPrFfZNWZXHlz4bPjJ4EmWVb9pW9SnXvobboWQDUCQEQiCQAAtAvvvnkq1lYGfLCkuhJkGnr6CwGDB6dnaczV++MngVAnRAAgUgCIAD94sO3TsrCylNzN0RPgjKfumdadp4+PG3N/8/efQfZdR12gj62d11jb83ujmdqtmrLVQIpBgUq2MqUZIkaW8lWsCVKtCxLsuhVGnts2pIIgAAzwSQGiQkUE0hRFDNAEt1ohEYGiJxzzjk0QqPR6Z39A5DRp18DjQa6+7zwfVW3WMK7/fCD6p0DnN+7957ckQCoEApAICcFIAB97nBTS9GtlUu2NuSOBUV++tLi5HN6zfMLc0cCoEIoAIGcFIAA9Lk5G/cnpcpbB9XE461tuWNBkREzNiaf1U/fOyV3JAAqhAIQyEkBCECfe2r6hqRU+cx9ShVK09xOZfWFg2piU4uyGoDzpwAEclIAAtDnfvzioqRU+bcXFuWOBF06crw1DhiY3q6+eOvB3LEAqAAKQCAnBSAAfe5z96cbKzw+bUPuSHBan7x7UvJ5fW62DWsAOH8KQCAnBSAAfep4a1u8aHBNUqi8uX5f7lhwWj/69fzk83rdyCW5IwFQARSAQE4KQAD61NJtDUU7AB9qaskdC07roUlrk8/rlx+anjsSABVAAQjkpAAEoE/9ZvbmpEz5xF0Tc0eCM5q8ek/ymX3bkDGxrb2QOxYAZU4BCOSkAASgTw0ZuTQpU3706/m5I8EZ7Tl8vOiq1bW7j+SOBUCZUwACOSkAAehTX35oelKkPDxpXe5I0K0P3Do++dyOWrgtdyQAypwCEMhJAQhAn2lta4+XDqlNipSpa/bkjgXd+s6Ts5PP7bCaFbkjAVDmFIBATgpAAPrM6l2Hi26l3H+0OXcs6NbddauSz+03H5+VOxIAZU4BCOSkAASgz7wyf2tSonxk2ITckeCs1CzZkXx2/+TmcbFQsBEIAOdOAQjkpAAEoM/c9PrypET5x6fn5o4EZ2XTvqNFV6/uaDiWOxYAZUwBCOSkAASgz1w5fGZSoNw/fk3uSHBW2tsL8bLr65LP74QVu3LHAqCMKQCBnBSAAPQJBQrlrnOB/fMJCmwAzp0CEMhJAQhAn9i4t/gWyl2HmnLHgrN2w2vLks/v955xCzsA504BCOSkAASgT7yxeHtSnrzvFpsoUF5enLsl+Qx/9I763JEAKGMKQCAnBSAAfeL22pVJefKtJ2bnjgQ9snz7oaKrWBuOteSOBUCZUgBC+fk/QwhXhRDuCSFMCSGsCyEcCiG0hBD2hBAmhxB+GkL4r2f5fpeHEJ4NIWwOIRwPIewKIYwNIfxtb4Y+DQUgAH3im4/PSoqTu+pW5o4EPdLc2h4vGlyTfI5nrtuXOxYAZUoBCOXnz8OpQXumY28I4TPdvNeNIYT2M7zH6BDCf+rtP0AHCkAAel2hUIjvvWlsUpzULtmROxb02Od/PjX5HD82dX3uSACUKQUglJ8/DyFsCSE8HUL4XyGEvw4hfDicuJLvayGEF0MIbeHEoG4OIbznNO/z/XBq8K8LIXw3hPCBEMKXQggTO7z2XB/9OUJQAALQB7YdPFZ06+SW/Y25Y0GP/eSlRcnn+JrnF+aOBECZUgBC+fm9szjny+HUwH61i9f/KITQcPL1zSGE/9bF7/F6h/f45Dlm7Y4CEIBeV7dsZ1KavOuGOhuAUJZGzNiYfJY/c9+U3JEAKFMKQKhcq8KpW4E7+2k4NfCvOs3P/3E4dSVh96qjlgAAIABJREFUTV8EDApAAPrAPeNWJ6XJVY++mTsSnJM5G/cnn+ULB9XEppa23LEAKEMKQKhcc8OJgX2ki9dmnnztUAjh98/wHnUnzzseQvjPvR0wKAAB6APffWpOUprcOnp57khwTo4cb40DBqa3sy/eejB3LADKkAIQKtOlIYTWcGJgz+302u+HU1f21XXzPoPCqQniil7OGIICEIA+8MHbxieFyaiF23JHgnP2ybsnJZ/n38zenDsSAGVIAQiV4w9DCBeHEP4thLArnBrYf9fpvMs6vHZ/N+/51x3O/VFvhj1JAQhAr9p9uKloA5C1u4/kjgXn7Ee/np98noeMXJo7EgBlSAEI5e074dQA7uq4PYTwO51+5rMdXv9xN+///k7v1VN/3M3xH++vAASgN0xctTspS94+dExsa7cBCOXrwYlrk8/0Xz80PXckAMqQAhDK23dC18XfwhDCB07zM1d2OO8H3bz/2zuc+8A55DtTOZkcCkAAesMD9WuSsuQrD8/IHQnOy6ROpfbbhii1Aeg5BSCUt/87nLil97JwovC7KoTwajgxoNeFEP6qi5/5+3Bq0H+3m/e/sMO5j59DPgUgAP3q+8/MS8qSG15bljsSnJc9h48X3da+Ztfh3LEAKDMKQKhMfx9CKIQQ2sOJqwQ76s8rAN0CDEC/+tid9UlR8sLcLbkjwXn70G0Tks/1K/P9uwmAnlEAQuV6IZwY2EdDCH/U4df78xmA3bEJCAC9pqGxpehKqeXbD+WOBeft6hFzk8/1ja+7shWAnlEAQuX6Rjg1uL/R4dftAgxARZqxdm9Sklw8uDa2tLXnjgXn7f7x6bMtv/qIZ1sC0DMKQKhcfxFODe5BHX7990MIbSd/va6b9xjU4T2u6IOMCkAAes2jU9YlJckXHpiWOxL0ivqVu+xuDcB5UQBC5fpOODW4/7nTazNP/vqhcKIQPJ26k+cdDyH8596PqAAEoPf883MLkpJk4CtLckeCXrH7cFPR7e1rd9sIBICzpwCEylUTTg3uT3Z67acdXrvqND//x+HUlYI1fRNRAQhA77niZ5OSguTZWZtyR4Je88Hbxief71cX+LcTAGdPAQjl5zshhP/UzTnXhFMDe0MI4fc6vf5HIYSGk69vCiH8106v/14I4fVw+gKxtygAAegVR463xgED0yukFm45mDsW9JqrR8xJPt83vb48dyQAyogCEMrPphDC/hDCL0MI3wohfDSE8J4QwsdCCD8MIUwPpwZ1cwjhz0/zPt/vcN66EMI/hBO7/n4xhDCxw2vP9c0fI4SgAASgl8zZuD8pRy4cVBObWtpyx4Jec9/41cln/MpHZuaOBEAZUQBC+dkUTg3aMx1bw4mNQM7kphBC4QzvURO6v9rwfCgAAegVT03fkJQjn7lvSu5I0KsmrEg3AnnH0DGx3UYgAJwlBSCUn0tDCP8WQnglhLA4hLArhNAaQjgcTlzJ93I4cZvwH57l+10eQvh1CGFLOHHF4O4QwrgQwt/2ZujTUAAC0Cv+/cVFSTnyby8syh0JetXuQ11tBHIkdywAyoQCEMhJAQhAr/jMfVOSYuTJ6RtyR4Je94Fb041ARi7YljsSAGVCAQjkpAAE4Lw1tbTFCwfVJMXInI37c8eCXvfdp9KNQG5+w0YgAJwdBSCQkwIQgPO2aMvBpBQZMHB0PHK8NXcs6HX3juu0EchwG4EAcHYUgEBOCkAAztuzszYlpcgVd0/KHQn6xPjl6UYg77y+zkYgAJwVBSCQkwIQgPM28JUlSSnyT88tyB0J+sSuLjYCWbfHRiAAdE8BCOSkAATgvH3xgWlJITJ88rrckaDPvL/TRiCjFtoIBIDuKQCBnBSAAJyXlrb2ePF1tUkhMn3t3tyxoM/8Q6eNQG4dbSMQALqnAARyUgACcF5W7DhUdEvkwcbm3LGgz9zTaSOQrz9qIxAAuqcABHJSAAJwXl6cuyUpQz56R33uSNCnxnXaCOQyG4EAcBYUgEBOCkAAzssNry1LypDvPTM3dyToUzsbijcC2bD3aO5YAJQ4BSCQkwIQgPPylYdnJEXILyasyR0J+lShUIjvuyXdCOS1RdtzxwKgxCkAgZwUgACcs7b2Qnz70DFJETJx5e7csaDPfefJ2cnn/raaFbkjAVDiFIBATgpAAM7Zml2Hi26F3H24KXcs6HP3jF2VfO6vevTN3JEAKHEKQCAnBSAA5+yV+VuTEuRDt03IHQn6xdhlO9ONQG6oi4WCjUAAOD0FIJCTAhCAc9Z5A5CrR9gAhOqwo+FY0dWvG20EAsAZKACBnBSAAJyzzhuA/NwGIFSJExuBjEs+/6/bCASAM1AAAjkpAAE4J61t7fFtQzptALLKBiBUj2932ghkmI1AADgDBSCQkwIQgHOyamfxBiB7jxzPHQv6zc86bQTyt7+0EQgAp6cABHJSAAJwTl6al24A8pFhNgChutR12gjkXTYCAeAMFIBATgpAAM7J9aOWJuXH956xAQjVZfvB4o1ANu2zEQgAXVMAAjkpAAE4J3/90PSk+Hig3gYgVJdCoRD/9OZ0I5A3FtsIBICuKQCBnBSAAPRYa1t7vOS62qT4mLx6T+5Y0O++9USnjUBqbQQCQNcUgEBOCkAAemzFjkNFtz7uP9qcOxb0u7vr0o1AvvGYjUAA6JoCEMhJAQhAj70wd0tSelx+e33uSJDFmKXpRiDvvnGsjUAA6JICEMhJAQhAjw0ZmW4A8oNfzcsdCbLY1sVGIJv3NeaOBUAJUgACOSkAAeixLz2YbgDy4MS1uSNBFoVCIb73prHJeBi9eEfuWACUIAUgkJMCEIAeaWlrjxd32gBk6hobgFC9vvn4rGQ83F67MnckAEqQAhDISQEIQI8s295QdMvjwUYbgFC97hyzMhkPf/fYrNyRAChBCkAgJwUgAD3y/JzNSdnxsTttAEJ1q12yw0YgAHRLAQjkpAAEoEcGv7okKTt+9Oz83JEgqy37G4uuit2y30YgAKQUgEBOCkAAeuSLD0xLio5HJq/LHQmyKhQK8T2dNgKpWWIjEABSCkAgJwUgAGetubU9Xjw43QBk+tq9uWNBdp03ArljjI1AAEgpAIGcFIAAnLWl24o3AGlobMkdC7K7o9NGIN983EYgAKQUgEBOCkAAztpzs9MNQD5x18TckaAk1HTaCOQ9N9kIBICUAhDISQEIwFkb+MripOT4n7+2AQjEaCMQALqnAARyUgACcNY+d//UpOD45ZT1uSNBSSgUCvG9nTYCeWPx9tyxACghCkAgJwUgAGelqaUtXjioJik4Zq3flzsWlIxvPTE7GR+31azIHQmAEqIABHJSAAJwVuZt2p+UGxcMHB2PHm/NHQtKxj3jVidj5MrhM3NHAqCEKACBnBSAAJyVJ6ZtSMqNT987JXckKCkTVuxKxsjbh46Jbe02AgHgBAUgkJMCEICz8i+/WZCUGz9+cVHuSFBS9hw+XrQRyOpdh3PHAqBEKACBnBSAAJyVT949KSk2nnlzU+5IUHI+MmxCMk5emLsldyQASoQCEMhJAQhAtxqOtRRd2bR468HcsaDk/OBX85Jxct3IJbkjAVAiFIBATgpAALo1bc3epNS4eHBtbG5tzx0LSs7Dk9YlY+ULD0zLHQmAEqEABHJSAALQrQcnrk1KjS8+OD13JChJM9amZflFg2vi8da23LEAKAEKQCAnBSAA3fr/np6blBpDRy3NHQlK0qGm4tvlF25xuzwACkAgLwUgAN360G3pxgYvzfN3BpzOFT9LN8x5eubG3JEAKAEKQCAnBSAAZ7T7UFPRFU1rdx/OHQtK1jXPL0zGy7+9sCh3JABKgAIQyEkBCMAZjVu+Kykz3nl9XWxvL+SOBSXrqekbkjHz5/dMzh0JgBKgAARyUgACcEZ3161KyoyvPzozdyQoafM3H0jGzICBo+OR4625YwGQmQIQyEkBCMAZffPxWUmZMaxmRe5IUNKaWtriWwfVJONm5rp9uWMBkJkCEMhJAQjAaRUKhfiem8YmRUbNkh25Y0HJ+8tfTE3GzfDJ63JHAiAzBSCQkwIQgNPatO9o0QYgWw805o4FJW/Qq0uScfOjZ+fnjgRAZgpAICcFIACnNWrhtqTE+NObx8VCwQYg0J3n52xOxs7lt9fnjgRAZgpAICcFIACndfMby5MS4ztPzs4dCcrCih2Hiq6e3XfkeO5YAGSkAARyUgACcFpffWRGUmDcN3517khQFlrb2uPbhoxJxs/ElbtzxwIgIwUgkJMCEIAuKTDg/HQu0O8dp0AHqGYKQCAnBSAAXVq+3S2McD4630L/bbfQA1Q1BSCQkwIQgC49O2tTUl587E6bGEBPvL5oezKG3nPTWJvoAFQxBSCQkwIQgC79+MVFSXnxT88tyB0JysqW/Y1FV9Fu2Hs0dywAMlEAAjkpAAHo0p/fMzkpLp6YtiF3JCgrhUIhvu+W8ck4enWBf28BVCsFIJCTAhCAIoebWuKAgemVS/M3H8gdC8rO1SPmJuPo+lFLc0cCIBMFIJCTAhCAItPX7k1Ki4sG18SmlrbcsaDsPDhxbTKWvvjAtNyRAMhEAQjkpAAEoMgD9WuUFtALlOkA/JYCEMhJAQhAkatHzHHbIvSCrm6nn7fJ7fQA1UgBCOSkAAQgcWLjgnFJYTFywbbcsaBs/cW96YY6j9tQB6AqKQCBnBSAACS27G9Myoq3XDs6btx7NHcsKFs/eWlRMp7+6bkFuSMBkIECEMhJAQhA4vVF25Oy4r03jY2FQiF3LChbv561ORlTH7uzPnckADJQAAI5KQABSNz8xvKkrPj2k7NzR4Kytnz7oaKravceOZ47FgD9TAEI5KQABCDx1w9NT4qK+8avzh0JylprW3t825Axybgav3xX7lgA9DMFIJCTAhCA/9Dc2h4vvq42KSomr96TOxaUva8Nn5mMq7vrVuWOBEA/UwACOSkAAfgPi7ceLLpVsaGxJXcsKHvDalck4+rvHpuVOxIA/UwBCOSkAATgPzw9c2NSUlxx96TckaAijFm6Ixlbl11fF9vbba4DUE0UgEBOCkAA/sM1zy9MSoprnl+YOxJUhJ0NTUVX167dfTh3LAD6kQIQyEkBCMB/+OTdk5KC4umZG3NHgorxodsmJOPrhblbckcCoB8pAIGcFIAAxBhjPNjYXHSF0pKtDbljQcX4wa/mJeNr0KtLckcCoB8pAIGcFIAAxBhjnLRqd1JOXHJdbWxpa88dCyrG8MnrkjH2ufun5o4EQD9SAAI5KQABiDHGeN/41Uk58TcPz8gdCSrKrPX7kjF24aCa2NjcmjsWAP1EAQjkpAAEIMYY498/MTspJ25+Y3nuSFBRGptb44WDapJx9ub6fbljAdBPFIBATgpAAGJ7eyFedkNdUkzULNmROxZUnL/8xdRknD04cW3uSAD0EwUgkJMCEIC4etfhog1AdjY05Y4FFWfoqKXJOLt6xJzckQDoJwpAICcFIADxudmbk1Li8tvrc0eCijRq4bZkrP3JzeNioVDIHQuAfqAABHJSAAIQf/zioqSU+J+/np87ElSkLfsbi6623bD3aO5YAPQDBSCQkwIQgHjFzyYlhcST0zfkjgQVqVAoxPffOj4Zby/N828wgGqgAARyUgACVLkDR5uLrkhatOVg7lhQsb7/zLxkvA16dUnuSAD0AwUgkJMCEKDK1a/clZQRlw6pjS1t7bljQcV6dMq6ZMx95r4puSMB0A8UgEBOCkCAKndX3cqkjLjykZm5I0FFm7dpfzLmBgwcHQ81teSOBUAfUwACOSkAAarcVY++mZQRt9euzB0JKlpTS1u8aHBNMu6mrtmTOxYAfUwBCOSkAASoYq1t7fFtQ8YkRcTYZTtzx4KK9+WHpifj7r7xq3NHAqCPKQCBnBSAAFVs6baGog1A9h45njsWVLxb3liejLu/f2J27kgA9DEFIJCTAhCgij09c2NSQvzZXRNzR4KqULNkRzL2LruhLra3F3LHAqAPKQCBnBSAAFXsX36zICkhrnl+Ye5IUBV2HWoquvp29a7DuWMB0IcUgFCe3h9CuD6EMC6EsC2E0BxCOBpCWBNCeCqE8LEevt/nQggjO7zXtpP/+3O9lPd0FIAAVexjd9YnBcSv3tyUOxJUjctvT8ffc7M3544EQB9SAEL5mRpODdozHU+HEH6/m/f63RDC4928z2Mnz+sLCkCAKrX7cPEVSMu3H8odC6rGPz2XXoH74xcX5Y4EQB9SAEL5WRdODNjtIYT7QwhfCSF8IITw4RDCNeHE1Xu/HdTPdfNet3c4d0EI4aqT73XVyf/929eG9fYf4iQFIECVGrN0Z1I+vGPomNjmGWTQb56cviEZg1f8bFLuSAD0IQUglJ/RIYSvhRB+7zSv/7cQwupwamD/2WnOuySE0HrynLkhhD/o9Pofnvz1ePK8i84rddcUgABValjNiqR8+MZjb+aOBFVl8daDRVfhHjjanDsWAH1EAQiV6a/CqYH9i9Oc83CHcz58mnM+3OGch3o5YwgKQICq9ZWHZyTFwz1jV+WOBFWlpa09XjqkNhmH9St35Y4FQB9RAEJl+j/CqYFd08XrvxNO3EIcQwgru3mvVSfP23by53qTAhCgCjW3tseLr0uLh4mrdueOBVXnyuEzk3F4V93K3JEA6CMKQKhMfxRODezXu3j9wg6vD+/mvR7tcO4FvZgxBAUgQFWat+lA0a2HDY0tuWNB1bljzMpkHH5t+MzckQDoIwpAqEx/HU4N7Du7eL3jLcL/2s17XdPh3M/3YsYQFIAAVWn45HVJ6fAX907OHQmq0oQVu5KxeMl1tbG5tT13LAD6gAIQKs/vhhBmh1MD+31dnPODDq9/tZv3+2qHc7/fwyx/3M3x/qAABKg6V4+Ym5QOg19dkjsSVKWGxpaiq3Hnbz6QOxYAfUABCJXn38OpQf3Kac75SYdzPtvN+32uw7n/3sMs8WwPBSBAdWhvL8T33DQ2KRxGLtiWOxZUrU/fOyUZj8Mnr8sdCYA+oACEyvKJEEJrODGgd4cQ/vtpzhsaTg38T3Xznp/qcO6QHuZRAAKQWLPrcNEVR1sPNOaOBVVr8KtLkvF49Yi5uSMB0AcUgFA53hlCOBBODOamEMKfneHc/roC0C3AACR+PWtzUjZ8ZNiE3JGgqo1csC0Zk++9aWxsby/kjgVAL1MAQmW4IISwPZwYyG0hhC91c35/PQOwOzYBAagy//r8wqRs+OfnFuSOBFVt28FjRVflrtl1OHcsAHqZAhDK3/8bQlgfTgziQgjhW2fxM3YBBiCLj95RnxQNz8zcmDsSVL2PDJuQjMtfz9qcOxIAvUwBCOXtv4UQlodTg/h/nuXPXdjhZ4Z3c+6jHc694NxinpYCEKCK7GgovtJo5c5DuWNB1fvn5xYk4/Ka5xfmjgRAL1MAQvn6v0II88OpAXxtD372d8KpW4ZXdnPuypPnbTv5c71JAQhQRV5btD0pGS67oc6zxqAEPDNzYzI2P3pHfe5IAPQyBSCUpz8MIUwPpwbvrefwHg93+PkPn+acD3c456Fz+D26owAEqCJDRy1NSobvPDk7dyQgxrhy56Giq3N3NBzLHQuAXqQAhPLz+yGEseHUwL3/HN/nknBiw5AYQpgbQviDTq//wclfjyGE1hDCxef4+5yJAhCginz2/qlJwfDgxLW5IwExxvb2QrzshrpkfL6+aHvuWAD0IgUglJ9XwqlBWx9CeFcI4bIzHJec4b1u7/BeC0IIXw8hvP/kfxd0eG1YH/w5QlAAAlSNQ00tccDA9AqjORv3544FnPSdJ2cn4/P6UUtzRwKgFykAofzEHh6bzvBevxtCeKKbn3/85Hl9QQEIUCUmrtqdlAsXD66NTS1tuWMBJz04cW0yRj97/9TckQDoRQpAKD+9WQD+1udDCKPCiY1Bmk/+d1QI4XO9G72IAhCgStxVtzIpF77y8IzckYAO5mzcn4zRAQNHx0NNLbljAdBLFIBATgpAgCpx5fCZSblwx5iVuSMBHTS1tMWLB9cm43TSqt25YwHQSxSAQE4KQIAqcLy1LV58XVos1K/clTsW0MlXHp6RjNO76hT1AJVCAQjkpAAEqALzNhXfWtjQ6NZCKDV3jElv1b9y+MzckQDoJQpAICcFIEAVeGTyuqRU+Mx9U3JHArpQv3JXMlYvua42Hm+1WQ9AJVAAAjkpAAGqwD88NScpFa4buSR3JKALDY0tyVh9y7Wj49yN+3PHAqAXKACBnBSAABWurb0QL7u+LikURi3cljsWcBqfuW9KMl4fnLg2dyQAeoECEMhJAQhQ4ZZsbSi6omj3oabcsYDTuOG1Zcl4/ebjs3JHAqAXKACBnBSAABXusanrkzLhirsn5Y4EnMGYpTuSMfu2IWNiS1t77lgAnCcFIJCTAhCgwl09In3+38BXFueOBJzB/qPNRVftztt0IHcsAM6TAhDISQEIUMHa2gvxXTd4/h+Um0/fmz4H8KFJngMIUO4UgEBOCkCACrZ0W/Hz/3Y2eP4flLqho5Ym4/bvn5idOxIA50kBCOSkAASoYI9P25CUCJ+4a2LuSMBZqFmSPgfwHUM9BxCg3CkAgZwUgAAV7B+fnpuUCD99yfP/oBzsPXK86OrdBZs9BxCgnCkAgZwUgAAVqr29EN9949ikQHh1gbkeysWf3zM5Gb+PTF6XOxIA50EBCOSkAASoUMu3Hyq6gmj7wWO5YwFn6bqRS5Lx++0nPQcQoJwpAIGcFIAAFerJ6enz/z5+p+f/QTl5Y/H2ZAy/8/q62Oo5gABlSwEI5KQABKhQ339mXlIe/PjFRbkjAT2w+3BT0VW8i7cezB0LgHOkAARyUgACVKD29kJ8703p8/9enmeeh3LzqZ9NSsbxo1M8BxCgXCkAgZwUgAAVaNXOw0VXDm090Jg7FtBDg15NnwP43afm5I4EwDlSAAI5KQABKtCIGRuT0uCjd9TnjgScg9cWpc8BvOz6utjWXsgdC4BzoAAEclIAAlSgHz6bPv/v317w/D8oR7sPFT8HcOm2htyxADgHCkAgJwUgQIUpFArxT28elxQGL87dkjsWcI6uuDt9DuBjU9fnjgTAOVAAAjkpAAEqzOpdxc//27Lf8/+gXA18ZXEynq8e4TmAAOVIAQjkpAAEqDBPTt+QlAWX314fCwXPDINyNWrhtqLnALa2teeOBUAPKQCBnBSAABXm6hFzk7Lgxy96/h+Us92Hi58DOH/zgdyxAOghBSCQkwIQoIK0trXHy66vS4qCkQu25Y4FnKe/uHdyMq5/MWFN7kgA9JACEMhJAQhQQeZvPlB0pdDuw025YwHn6cbXlyXj+uuPzswdCYAeUgACOSkAASrIA/VrkpLgL+6dnDsS0AvGL9+VjO2LB9fGY81tuWMB0AMKQCAnBSBABbnq0TeTkuCG15bljgT0gsNNLfHCQTXJ+J66Zk/uWAD0gAIQyEkBCFAhmlra4sXX1SYFwbjlu3LHAnrJlx+anozv22tX5o4EQA8oAIGcFIAAFWLamr1JOXDBwNHxUFNL7lhAL7m7blUyxr/wwLTckQDoAQUgkJMCEKBC3F67MikHvvTg9NyRgF40Y11a8g8YODoebGzOHQuAs6QABHJSAAJUiC88MC0pB+6uW5U7EtCLmlra4qVD0tv8xyzdkTsWAGdJAQjkpAAEqAANjS1xwMDRSTEwY93e3LGAXvbNx2cl43zIyKW5IwFwlhSAQE4KQIAKMGbpzqQUuOS62tjU0pY7FtDLHp60LhnrV/xsUu5IAJwlBSCQkwIQoAIMHbU0KQX+7rFZuSMBfWDx1oPJWH/LtaPjzoam3LEAOAsKQCAnBSBABfjUzyYlhcBDk9bmjgT0gbb2QnzXDXXJeH95nn/DAZQDBSCQkwIQoMztbGgquiJo0ZaDuWMBfeR7z8xNxvs1LyzMHQmAs6AABHJSAAKUuZfnbU3KgHfdUBfb2gu5YwF95JmZG5Mx/8HbxsdCwZgHKHUKQCAnBSBAmbvmhYVJGfC9Z+bmjgT0oXV7jhRd9bt29+HcsQDohgIQyEkBCFDGCoVCfP+t45Mi4OmZG3PHAvpQoVCIHx42IRn3T0zbkDsWAN1QAAI5KQABytjy7YeKrgTauPdo7lhAH/vJS4uScf/tJ2fnjgRANxSAQE4KQIAy9vCkdUkJ8PE7J+aOBPSDNxZvT8b+pUNqY1NLW+5YAJyBAhDISQEIUMauevTNpAQYMnJp7khAPzjY2BwvGJhe/Tt1zZ7csQA4AwUgkJMCEKBMHT3eGi8aXJMUAOOW78odC+gnX35oejL+b3ljee5IAJyBAhDISQEIUKbGL9+VLP7fOqgmHjnemjsW0E/uHbc6mQP+4t7JuSMBcAYKQCAnBSBAmRo6ammy+P/6ozNzRwL60fzNB4o2AdrRcCx3LABOQwEI5KQABChTf3bXxGTh/9CktbkjAf2orb0Q333j2GQeeH7O5tyxADgNBSCQkwIQoAxt3Hu06MqfZdsbcscC+tmPfj0/mQd+9Oz83JEAOA0FIJCTAhCgDD09c2Oy6H/fLeNje3shdyygn70wZ0syF7zrhrrY2taeOxYAXVAAAjkpAAHK0NUj5iSL/mueX5g7EpDBjoZjRVcDz9t0IHcsALqgAARyUgAClJnm1vb49qFjkgX/qIXbcscCMvn0vVOS+eCecatzRwKgCwpAICcFIECZmbFub7LYHzBwdNx35HjuWEAmt45enswJX3pweu5IAHRBAQjkpAAEKDO3165MFvtfeGBa7khARtPWpF8KXDBwdDxwtDl3LAA6UQACOSkAAcrMZ++fmiz2765blTsSkFFTS1u8dEhtMi+8vmh77lgAdKIABHJSAAKUkd2Hmooe+D97w/7csYDMvv3k7GRe+PcXF+WOBEAnCkAgJwUgQBl5Yc6WZJF/2fV1saWtPXcsILMnp29I5ob33TJt3TWEAAAgAElEQVQ+trcXcscCoAMFIJCTAhCgjHzvmbnJIv+Hz87LHQkoARv3Hi26OnjhloO5YwHQgQIQyEkBCFAmmlra4tuHjkkW+C/PM3cDJ3zqZ5OS+eGesZ4PClBKFIBATgpAgDIxefWeZHE/YODouO/I8dyxgBJxW82KZI74/M+n5o4EQAcKQCAnBSBAmbh+1NJkcf/XD03PHQkoIW+u31d0G/COhmO5YwFwkgIQyEkBCFAGCoVCvPz2+mRh/+DEtbljASWkpa09vuuGumSeeHbWptyxADhJAQjkpAAEKAOrdh4uurJn5c5DuWMBJeafn1uQzBPffWpO7kgAnKQABHJSAAKUgYcmrU0W9ZffXh8LhULuWECJGbVwWzJXXHJdbTzW3JY7FgBRAQjkpQAEKANfeXhGsqgfMnJp7khACTrY2BwvHFSTzBcTVuzKHQuAqAAE8lIAApS4/Ueb4wUD09t/J63anTsWUKKuHD4zmS8GvbokdyQAogIQyEsBCFDiXpm/NVnMv23ImNjU4pY+oGvDJ69L5owP3TbBIwMASoACEMhJAQhQ4n706/nJYv4fn56bOxJQwtbuLt40aOm2htyxAKqeAhDISQEIUMJa2trjZdfXJQv538zenDsWUMIKhUL8+J0Tk3nj5xPW5I4FUPUUgEBOCkCAEjZj7d6iK3l2H2rKHQsocTe+viyZN774wLTckQCqngIQyEkBCFDCbn5jebKI/4JFPHAWpq3x5QFAqVEAAjkpAAFKVKFQiB+7sz5ZwN83fnXuWEAZaG5tj+8YOiaZP349y+MDAHJSAAI5KQABStTy7Yc8yB84Z503EPrWE7NzRwKoagpAICcFIECJumfc6mTx/tE76mOhUMgdCygTry3answhFw2uiQ3HWnLHAqhaCkAgJwUgQIn69L1TksX7LW8szx0JKCOHm1rixYNrk3lk5IJtuWMBVC0FIJCTAhCgBK3fc6To9t+5G/fnjgWUmX94ak4yj3z/mXm5IwFULQUgkJMCEKAEPTxpXbJof/+t42N7u9t/gZ55Yc6WZC65dEhtPNbcljsWQFVSAAI5KQABStAXH5yeLNoHv7okdySgDO0/2hwvGJheTVy3bGfuWABVSQEI5KQABCgx2w8eK7r9d+qaPbljAWXqqkffTOaTa55fmDsSQFVSAAI5KQABSsxT0zcki/V33VAXW9rac8cCytSIGRuL5pTmVnMKQH9TAAI5KQABSszXH52ZXq3zgqt1gHO3o6H4quIpq11VDNDfFIBATgpAgBLS1fO6xnpeF3CevtTpuaKDPFcUoN8pAIGcFIAAJaTzjp1vGzImNrXYsRM4P49MTncWf98t42ObncUB+pUCEMhJAQhQQv7hqTnJIv2Hz87LHQmoABv2Hi26DXjuxv25YwFUFQUgkJMCEKBEHG5qiRcPrk0W6KMWbssdC6gQn753SjK/3PLG8tyRAKqKAhDISQEIUCJGLtiWLM4vGlwTDzW15I4FVIh7xq1O5piPDJsQ290GDNBvFIBATgpAgBLx3U63/37nydm5IwEVZMWOQ0W3Ac/b5DZggP6iAARyUgAClICDjc3xosE1ycL8lfnmZaD3FAqF+D/umZzMMze8tix3LICqoQAEclIAApSA38zenCzKL7muNh52+y/Qy34+YU3RbsCtbe25YwFUBQUgkJMCEKAEfOOxN5NF+Q9+ZfdfoPet33Ok6Dbg6Wv35o4FUBUUgEBOCkCAzHYfbooXDEwX5DVLduSOBVSov/zF1GS+ufblxbkjAVQFBSCUp/8eQvirEMLNIYQxIYR94dRAHnEO7/e5EMLIEMK2EELzyf+OPPnrfUkBCJDZU9M3JIvxdwwdE481t+WOBVSo4ZPXJXPOu28cG5tb3QYM0NcUgFCe4hmOET14n98NITzezfs9dvK8vqAABMjsbx6ekSzG/+U3C3JHAirYtoPHim4DnrBiV+5YABVPAQjlqePA3RxCGBvOrQC8vcPPLQghXBVC+MDJ/y7o8NqwXsrdmQIQIKOtBxqLFuL1Ky3Egb71FV88APQ7BSCUp5vCiVuA/5+T/3tA6HkBeEkIofXkz8wNIfxBp9f/8OSvx5PnXXQ+gU9DAQiQkVvxgBxGzNjo0QMA/UwBCJVhQOh5Afhwh5/58GnO+XCHcx46r4RdUwACZPT5n3sYP9D/utp8aPRimw8B9CUFIFSGAaFnBeDvhBC2nzx/ZTfnrjp53raTP9ebFIAAmazbc6To9t/pa/fmjgVUiW889mYy/3z/mXm5IwFUNAUgVIYBoWcF4IUdzh/ezbmPdjj3gnNO2DUFIEAm949fkyy+33fL+NjWXsgdC6gSv5m9OZmDLr6uNh5uaskdC6BiKQChMgwIPSsA/6rD+f/azbnXdDj38+ecsGsKQIAMCoVCvOLuScni+4bXluWOBVSRg43N8aLBNck89MLcLbljAVQsBSBUhgGhZwXgDzqc/9Vuzv1qh3O/38Ncf9zN8f6gAATod/M2HSi6/Xfepv25YwFV5rtPzUnmoa8Nn5k7EkDFUgBCZRgQelYA/qTD+Z/t5tzPdTj333uYK57toQAE6D+DXl2SLLo/cdfEWCi4/RfoXzVLdhR9GbFlf2PuWAAVSQEIlWFA6FkBOLTD+Z/q5txPdTh3SA9zKQABSkxTS1u87Ia6ZMH9QP2a3LGAKnS8tS2++8axyXx03/jVuWMBVCQFIFSGAaE0rwB0CzBAiXl90fZksT1g4Oi47eCx3LGAKjVk5NJkTvrYnfWx3YZEAL1OAQiVYUAozWcAdscmIAD97FtPzE4W29947M3ckYAqtmjLwaLbgGet35c7FkDFUQBCZRgQ7AIMQDd2HWqKFwxMF9qvzDf/AvkUCoX4P+6ZnMxLP3lpUe5YABVHAQiVYUDoWQF4YYfzh3dz7qMdzr3gnBN2TQEI0I8embwuWWS/Y+iY2NjcmjsWUOXMTQB9TwEIlWFA6FkB+DshhO0nz1/ZzbkrT5637eTP9SYFIEA/6eoqmx+/6CobID9XJwP0PQUgVIYBoWcFYAghPNzhZz58mnM+3OGch84rYdcUgAD9xHO2gFLm+aQAfUsBCJVhQOh5AXhJCKHt5M/MDSH8QafX/+Dkr8cQQmsI4eJeyNmZAhCgn9hpEyhlr9mhHKBPKQChPH0shPCdDsePw6mBPL3Ta985w/vc3uHnFoQQvh5CeP/J/y7o8NqwXk1/igIQoB8cb22L775xbLK4vm/86tyxAP5DU0tbvOyGumSeeqB+Te5YABVDAQjlaUQ4NXDP5jid3w0hPNHNzz5+8ry+oAAE6AdvLN5edPvvlv2NuWMBJAa9uiSZpz5+50RXKgP0EgUglKcRoXcKwN/6fAhhVDixMUjzyf+OCiF8rpdzd6YABOgHVz36ZrKo/trwmbkjARSZv/lA0ZcVU9fsyR0LoCIoAIGcFIAAfWzt7iNFC+pRC7fljgVQpFAoxE/fOyWZr77/zLzcsQAqggIQyEkBCNDHbn5jebKY/pObx8XjrW25YwF06emZG5M568JBNXHXoabcsQDKngIQyEkBCNCHmlqKN/8YVrMidyyA0zrU1BLfNmRMMm/9fILNQADOlwIQyEkBCNCHXp63tej23417j+aOBXBG1768OJm3PjJsQmyzGQjAeVEAAjkpAAH60N88PCNZRH/z8Vm5IwF0a8nWhqIvLyas2JU7FkBZUwACOSkAAfrIih2HihbQY5buyB0L4Kx84YFpyfz1D0/NyR0JoKwpAIGcFIAAfWTIyKXJ4vkDt46PLW3tuWMBnJXn52xO5rABA0fHrQcac8cCKFsKQCAnBSBAHzh6vDW+8/q6ZPF8z9hVuWMBnLXG5tZ4Wad57O468xjAuVIAAjkpAAH6wHOz0ytnLhg4Om47eCx3LIAeuX5UeiXz+25xJTPAuVIAAjkpAAF6WaFQiJ+7f2qyaL56hGdnAeVn1c7DRc8yfX3R9tyxAMqSAhDISQEI0MtmrttXtGCuX2n3TKA8ffWRdDfzLz80PXckgLKkAARyUgAC9LKrR8xJFsufuGtibGsv5I4FcE7eWLy96EuNeZsO5I4FUHYUgEBOCkCAXrR+z5GihfKIGRtzxwI4Z61t7fHy2+uTee2Hz87LHQug7CgAgZwUgAC9aMjI9IH577qhLh493po7FsB5+eWU9UUbG23Z35g7FkBZUQACOSkAAXrJwcbm+LYhY5JF8u21K3PHAjhvh5pa4juGpvPbzW8szx0LoKwoAIGcFIAAveShSWuTxfFbB9XEHQ3HcscC6BU3vr4smePeeX1dPNzUkjsWQNlQAAI5KQABekFza3v84G3jk8Xx//rNgtyxAHrN5n2N8YKB6TNOH5u6PncsgLKhAARyUgAC9IKRC7YVbf6xeOvB3LEAetX3n5mXzHMfvaM+tra1544FUBYUgEBOCkCA81QoFOJf/mJqsii+8pGZuWMB9Lq5G/cXfdlRs2RH7lgAZUEBCOSkAAQ4TzPX7StaENct25k7FkCvKxQK8YsPTk/muy8/ND0WCoXc0QBKngIQyEkBCHCe/u6xWcli+ON3Toxt7RbDQGV6bdH2oi89ZqzdmzsWQMlTAAI5KQABzsP8zQeKFsJPz9yYOxZAn2lpa48fvaM+mfe+/qjHHgB0RwEI5KQABDgP33lydrII/sCt42NTS1vuWAB96tlZm4q+/JizcX/uWAAlTQEI5KQABDhHS7c1FC2AH5u6PncsgD53vLUtfnjYhGT++/snZueOBVDSFIBATgpAgHP0vWfmJovfP715XGxsbs0dC6BfPDV9Q9GXIAu3HMwdC6BkKQCBnBSAAOdg5c5DRQvfhyatzR0LoN80tbTF990yPpkHrx4xJ3csgJKlAARyUgACnIN/em5Bsuh9941j4+GmltyxAPrVo1PWFX0Zsmx7Q+5YACVJAQjkpAAE6KF1e47EAQPTBe9941fnjgXQ744eb43vvWlsMh/+8Nl5uWMBlCQFIJCTAhCgh655YWGy2H3n9XWxodHVf0B1eqB+TTInDhg4Oq7edTh3LICSowAEclIAAvTAml2H4wWdrv67q25l7lgA2RxqaomX3VCXzIvfe2Zu7lgAJUcBCOSkAATogX98Ot359+1Dx8R9R47njgWQ1T3jVhc9C3D+5gO5YwGUFAUgkJMCEOAszdu0v2iBe884z/4DONTUUvQswCuHz4yFQiF3NICSoQAEclIAApyFQqEQv/rIjGRx+yc3j7PzL8BJj01dX/QlycSVu3PHAigZCkAgJwUgwFmYsGJX0cL2iWkbcscCKBlNLW3x8tvrk3nyM/dNie3trgIEiFEBCOSlAAToRlt7IX763inJovajd9TH461tuaMBlJSX5m0t+rLk1QX+jQkQowIQyEsBCNCNly1oAc6KL0wATk8BCOSkAAQ4A7e0AfRMV49MeHK6RyYAKACBnBSAAGfwyOR1HmoP0ANdbZr03pvGxoONzbmjAWSlAARyUgACnMbOhqb49qFjkkXslcNnxkLB1X8AZzJv0/6iL0+GjFyaOxZAVgpAICcFIMBp/PNzC5LF64CBo+OiLQdzxwIoCz98dl4yh14wcHRcuq0hdyyAbBSAQE4KQIAuvLl+X9HVKwNfWZw7FkDZ2HbwWLx0SG0yj/7NwzNcRQ1ULQUgkJMCEKCT1rb2ol0s333j2Lj/qOdXAfTEA/Vrir5MeWW+f3MC1UkBCOSkAATo5MnpG4oWrM/M3Jg7FkDZaWppi39218RkPn3fLePj4aaW3NEA+p0CEMhJAQjQwZ7Dx+Nl19cli9XP3T81trW7ZQ3gXNSv3FX0pcotbyzPHQug3ykAgZwUgAAd/PuLi4oWqnM37s8dC6CsffepOcm8euGgmrhq5+HcsQD6lQIQyEkBCHDS1DV7isq/a55fmDsWQNnbtO9ovHhwuiHIFx+c7upqoKooAIGcFIAAMcYjx1vj5bfXJ4vTd15fF3cfasodDaAi/GzsqqIvWR6dsi53LIB+owAEclIAAsQYrxu5pGhh+qs3N+WOBVAxmlra4hV3T0rm2Uuuq43r9xzJHQ2gXygAgZwUgEDVm7Fub1H5d9Wjb8Z2t6YB9Kq5G/fHAQPT+fYrD89wKzBQFRSAQE4KQKCqNTa3xo/fOTFZjL5tyJi4eV9j7mgAFenG15cVfenyxLQNuWMB9DkFIJCTAhCoal0tRJ+cbiEK0Fe6+uLl0iG1cdO+o7mjAfQpBSCQkwIQqFqz1u/r8lY0t/4C9K2Z6/YVffly5fCZbgUGKpoCEMhJAQhUpQNHm+OHbpvgYfQAmXS1+dLPJ6zJHQugzygAgZwUgEDVKRQK8eoRc4oWno9OWZc7GkDVOHK8NV5+e30yD18wcHScvWF/7mgAfUIBCOSkAASqzpPTNxSVf9947E23ngH0s7kb98cLB9Uk8/GHh02IB442544G0OsUgEBOCkCgqizd1hAvHlybLDb/9OZxcfehptzRAKrSA/Vrir6UuXrE3Fgo+FIGqCwKQCAnBSBQNY4cb42fuGti0UJz0qrduaMBVK229kL821++aUd2oOIpAIGcFIBAVSgUCvGfn1tQtMAcVrMidzSAqrf7UFP805vHJfPzxYNr46ItB3NHA+g1CkAgJwUgUBUembyuqPz70oPTY0tbe+5oAMQYJ63aXTRPf+i2CR7RAFQMBSCQkwIQqHgTVuyKAwami8rLrq+LW/Y35o4GQAfDalYUlYBffHB6bGppyx0N4LwpAIGcFIBARVu963B85/V1yWJywMDRcdzyXbmjAdBJS1t7/NrwmUUl4L8+v9CmIEDZUwACOSkAgYp14Ghz/PidxZt+PDhxbe5oAJzG/qPN8WN31hfN3cMnr8sdDeC8KACBnBSAQEVqaWvvclfJ//WbBa4iAShxq3Yeju8YOqbo6u36la7eBsqXAhDISQEIVJz29kK85vmFxc+RemCa50gBlIlxy4uf3/r2oWPigs0HckcDOCcKQCAnBSBQUQqFQrzhtWVF5d8Hbh0fdzbYSRKgnDw0aW3RfP7uG8fG1bsO544G0GMKQCAnBSBQUe4fv6ZosXjpkNq4cMvB3NEA6KFCoRD/tYsruj9423g7uQNlRwEI5KQABCrGiBkbixaJbx1UEyeu3J07GgDnqLm1PX7ridlF8/uf3TUx7j7sym6gfCgAgZwUgEBFGLlgW9HicMDA0XHUwm25owFwnhqbW+PfPDyjaJ7/zH1T4sHG5tzxAM6KAhDISQEIlL0X5m6JF3R6UPxbrh0dn5m5MXc0AHpJQ2NL/Mx9U4rm+s/ePzXuPXI8dzyAbikAgZwUgEBZe3pm8W2/b7l2dPzFhDW5owHQy3Yfaoofv3Ni0Zz/qZ9NstETUPIUgEBOCkCgbD0yeV2X5d8tbyyPhUIhdzwA+sDmfY3xQ7dNKJr7P37nRBuDACVNAQjkpAAEyk6hUIj3jF3VZfl3x5iVyj+ACrd5X2P86B31RX8HfHjYhLh+z5Hc8QC6pAAEclIAAmWlubU9/vSlxV2Wfw/Uu+0XoFrsaDgWr7h7UtHfBe+9aWycvWF/7ngARRSAQE4KQKBsHGxsjl9/dGaX5d/j0zbkjgdAP9tz+HiXG4NcNLgmvjzPv22B0qIABHJSAAJlYf2eI/GTXVzpMWDg6PjrWZtzxwMgk4ONzfGLD0zr8suhO8esjO3tHgsBlAYFIJCTAhAoedPX7o3vvnFs0cLu0iG1sXbJjtzxAMjsyPHW+A9PzemyBPz+M/Pi0eOtuSMCKACBrBSAQMlqbWuP94xbHQcMLF7QffC28XHJ1obcEQEoEW3thXjzG8u7LAGvuHtSXLbd3xlAXgpAICcFIFCSdjY0xSuHd/28v7/8xdS4s6Epd0QAStCvZ22Obx1UU/R3x8XX1canZ260UzyQjQIQyEkBCJSc+pW74ntvKr7l9y3Xjo7fe2ZubGx2KxcApzd97d74rhvqTntLcENjS+6IQBVSAAI5KQCBktFwrCVe+/LiLhdsbx1UE4dPXudh7gCclc37Gk+7OcgHbxsfxy/flTsiUGUUgEBOCkCgJNQt2xk/cOv4Lhdql99eH+dvPpA7IgBlprm1Pd46uuvnAr7l2tHxn55bEPceOZ47JlAlFIBATgpAIKvdh5vij56df9rF2feemetWLQDOy5keLfHem8bGV+Zv9WxAoM8pAIGcFIBAFk0tbfHBiWvjO4aO6XJB9o6hY+Kv3txkQQZAr9jRcCx+8/FZp/3C6W8enhEXbjmYOyZQwRSAQE4KQKBfFQqF+Nqi7fHy2+tPuwj79pOz47aDx3JHBaDCFAqF+PK8rfHdN3Z9NeBbrh0d/+U3C/wdBPQJBSCQkwIQ6BeFQiFOWb0nfvmh6adddL33prHx1QVuwwKgb+05fPyMj5+45LraOKx2hecDAr1KAQjkpAAE+lShUIj1K3fFLz54+uJvwMDR8d9fXGShBUC/GrtsZ/z4nRNP+/fTpUNq481vLI+7DzXljgpUAAUgkJMCEOgTLW3t8fVF2+Nf/mLqaRdWb7l2dPza8Jlx6baG3HEBqFLHW9viL6esj5fdUHfav6suvq42Dh21NK7fcyR3XKCMKQCBnBSAQK/afbgp3j9+TfzArePPWPx94q6JsW7ZTrf7AlAS9h05HoeOWhovHFRzxr+//v6J2bF+5a7Y3u7vL6BnFIBATgpA4Ly1trXHSat2x396bkG8aPCZF04fv3NifH7O5tjc2p47NgAU2bD3aPzxi4u6LQI/fufE+ODEtTYMAc6aAhDISQEInJNCoRCXbz8Ub3ljeXx/N1f7veXa0fGKuyfFl+dtja1tij8ASt+W/Y1x4CtLuv1ia8DA0fHrj86ML8zdEg83teSODZQwBSCQkwIQOGvt7YU4b9OBOKx2Rbzi7kndln5vuXZ0/OojM+Ibi7fHNrdKAVCGth08FofVrIjvvnFst3/nXXxdbfzuU3Pi83M229gKKKIABH7rLSGEe0IIq0IIjSGEAyGEuSGEn4QQ/rCPfk8FIHBGB442x9GLd8SBryw+qyv93nLt6HjJdbXxpy8tjsu229wDgMpwrLktPj9nc/zs/Wfe3KrjlYFffWRGfHDi2rhoy0FfhAEKQCCEEMIXQgiHwqnJoPOxOoRwUR/8vgpAINHQ2BInrtod7xizMv7VL6bFAQO7X+T89vjCA9Pik9M3xANHm3P/MQCgTxQKhTh34/448JXFZ9w5uPPxnpvGxh8+Oy8+8+amuGLHIYUgVCEFIPAnIYRj4cQkcCSEMDiE8JEQwqdCCL8MaQn4n3v591YAQhVrbm2Py7Y3xBfmbIkDX1kc/+LeyWe9kPnt8ZFhE+KdY1bGtbsP5/7jAEC/amppi6MX74hXj5gT39rNpiGdj8uur4vffHxWvG/86jhx5e64+1BT7j8O0McUgMDUcGICaA0nir/OfhJOTRI39vLvrQCEKlAoFOKOhmNxyuo98fFpG+JPX1ocP//zqfHiwbU9Lvzecu3o+Of3TI531a2Mi7YcjO2uYACA2NDYEkcu2BZ/+Oy8+PahY87p79f33TI+fvvJ2fGOMSvjqwu2xqXbGuKx5rbcfzSglygAobp9MJyaAIaf5pzfDSGsOHnOwRDC/96Lv78CECrEsea2uHb34Thx1e74zMyNcVjNivijZ+fHLzwwLb7z+rO/Ramr49IhtfFbT8yOv5yyPq7fcyT3HxUASlpTS1ucsGJXvH7U0njFz85u06wzPUvwo3fUx797bFa89uXF8YH6NXHkgm1x3qb9cdehJl/EQRlRAEJ1GxZOTQAfOsN5Azuc9+le/P0VgFDCCoVCPHK8NW7adzTO27Q/1i3bGZ+dtSn+fMKaOHTU0vjDZ+fFLz04Pb7vlnHntbjofFx8XW386iMz4l11K+PMdfvi8VZXHwDAudp+8Fh8ce6W+K/PL4wfu7O+1//OvuLuSfGbj8+K//bCojisdkX85ZT18dUFW+OU1Xvi8u2H4u7DTbG1rT33/w1Q9RSAUN1+e/vv0RDC/3aG8z4STk0UN/Xi768AhD7Q1l6Ih5ta4u7DTXHzvsa4cuehuGDzgThj7d44YcWu+Pqi7fG52Zvjo1PWxbvrVsXrRy2N//r8wnj1iDnxykdmxs/cNyVefnt9vHTIud2i29PjY3fWxx/8al58bOr6uGDzgdjcapEAAH1l96GmWLtkR7zljeXxKw/POOdbhnt6JeGf3DwufvLuSfGLD0yLf/fYrPjDZ+fFn760ON46enn8+YQ18anpG+LL87bGMUt3xImrdsc31++LC7ccjKt2Ho6b9h2Nuw81xYZjLbG5tT0WCq48hJ5SAEJ12xtODP5F3Zz3X8KpieLFXvz9y64AnLRqd5zY8VhZfNSv3FV0TFhRfIxfnh7jujjGLttZdNR1cYxZ2vnYUXTULik+aro4Ri9OjzcWby86Xl9UfLzWxTFq4bZuj5ELio9XF2wtOl6ZX3y8PC89XurieHHulqLjha6OOenx/JzNRcdvZhcfz83eHH/15qb4zMyN8anpG+Lj0zbEX05ZHx+ZvC4+NGltfKB+Tbx//Jp4z7jV8e66VfHOMSvjsNoV8dbRy+NNry+PN7y2LA4dtTQO/v/bu/doOcv6XuBfU2/o0nPa0tZ1Skv0IGWprUWpAuIFUBQRrEuleNRqrV1aWk6lXgpWNKANRSQiF+UqgWLKRTggN7mECAkJJCHcAwHCxQDljgjhIoTn/PHu6bx7Z++ZvXdm9kwmn89av5WVeZ95581a33nzvL95L2deX/Y547ry1dOvLV8+7dqy9ynXlL3mLCtf/I+l5XMnLC6fOu7KsvtRC8tHjlxQdjns8rLTrMvK9gfPK9seOLf8xXcuLm/e/8Lyhv0uKJt9fWI3AZ/KesN+F5TdDp9f9j71mnLs5SvLFbc/VH61+je9/loDwAZtzZoXysoHnyhnX3tvmXn+8vI3Jywu7zzo0jJ9n97PHQi/JuoAABOUSURBVMaq1+17XnnDfheUt377orLtgXPLDt+bV97//cvKLoddXv7yyAXl4z9aWD5xzKLy6eOvKp87YXH5wklLyz/85OrypVOuKV857dqy75nXl2+edUPZ/2c3lW+fc1P5t/OWl5nnLy8HXXBzOfjnt5RDLrylzLpoRTn04lvL4XNvLUdcelv54bzby1G/uL0cc9nKctz8O8qPF9xRZl9xZzlp4Z3lPxbdVeZcVc0XT13yy3J6bX5an7s25rWNOe9oc+PGPLoxx27Mv+vz88a8vTGnHz7vr44HGscJjWOI+jFG4/ijcVzSOGYZ7dimr2rksVif1LxbHuj113hcNABhw/XyNL/8545j/JNDYxdN4DM2aVNbZT1rAPbzREipfqi3HHBR2e3w+WXPk68uM89fXk5adFf5xYoHy72PPeXXegBYjzz17PPlhnt+Vc6+9t5y5Lzbyr5nXl8+ddyVZfuD55XX/+vUXCWg1PpQ0/c5t9df13HRAIQN1++l+eU/ZRzjHxgae8MEPqOMtzQAlerv+pNvnF/e8e9zy25HLCh/O3tx+drp15Xv/vzmMvuKO8vcm+8vK+7/dVn97HO9/ooCAFNgzZoXygOPP12W3vVIOeuae8oRl95WZvzsxrLXnGXlE8csKjvNuqy85YCLzJ3VBlEagEC/+6M0v/wnjWP8L4fG3j6Bz9AAVKpPaotvXFDeckB1mcyOh/yifPiIBeVTx11Z9vzJ1WWfM64rM89bXg6fe2s5ceGd5cxlq8oly+8vS+96pNz18JPlyWeec/YeADBhz695oTz462fK8vseL/Nvfaicf/195ZTFd5djL19ZDrnwlvKts28se596Tfn8iUvK7kctLDsfennZ/uB5ZeuZl5Q373/hlN2PWKl1KQ1AoN9NxRmAA3cJ8LYHzi3bzLxkWG174Ny29Y5/X7u2O2jteudBlw6rd3137Xr3iHrPwfPWqu1Hq+8Nrx1GqR0P+cWweu8o9b5Za9dOsy4bVu//fvv6wKGXr1U7j1If/MHw2uWwtetDh80fVrsevnbtNlodsWBYfXiU+ssjh9dHRqmP/eiKsvtRC8seRy8qnzz2yvLp468qn/1xdc+Zz5+4pHzhpKVlz5OvLv84Z1n5v/+5rOx9yjXly6ddW752+nVlnzOuK18/8/qy31k3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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x116a07358>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's plot this function to see what it looks like\n",
    "x = np.arange(0, 100, 0.5) # From 0 to 100 with 0.5 step\n",
    "y = gaussian_slope(x, 60, 50, 20,0,0)\n",
    "f2,ax2=plt.subplots()\n",
    "ax2.plot(x,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "## LMFit\n",
    "\n",
    "Non-Linear Least-Squares Minimization and Curve-Fitting\n",
    "\n",
    "Very powerful that has many options. \n",
    "\n",
    "We will do a simple gaussian fit.\n",
    "\n",
    "See: See: https://lmfit.github.io"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "First we need to declare the Model.  By Declaring the Model LMFIT does some nice things for us.\n",
    "\n",
    "1) it assumes the first parameter is the independent variable\n",
    "\n",
    "2) it assumes the rest of the parameters are parameters and it takes care of keeping track of the parameter names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "gmodel = Model(gaussian_slope)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "type gmodel. ```<tab>``` to see what methods are available on gmodel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-10-15075805e989>, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-10-15075805e989>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    gmodel.\u001b[0m\n\u001b[0m           ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "gmodel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['A', 'center', 'fwhm', 'm', 'b']\n",
      "['x']\n"
     ]
    }
   ],
   "source": [
    "# Nice things\n",
    "print(gmodel.param_names)\n",
    "print(gmodel.independent_vars)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "To do the fit use the gmodel.fit method.  press ```<shift>+<tab>``` when the cursor is inside the parenthesis to see more info. Since we have weights, we will use them. Return the results of the fit into result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "# Fitting\n",
    "result = gmodel.fit(data_y, x=data_x, A=3500, center=1, fwhm=0.02,m=0,b=50,weights=1./(data_err)**2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "type result. ```<tab>``` to see the methods available for the results. A nice overview is given if you print(result.fit_report())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-13-9c21d2297c6a>, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-13-9c21d2297c6a>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    result.\u001b[0m\n\u001b[0m           ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[Model]]\n",
      "    Model(gaussian_slope)\n",
      "[[Fit Statistics]]\n",
      "    # function evals   = 33\n",
      "    # data points      = 21\n",
      "    # variables        = 5\n",
      "    chi-square         = 0.093\n",
      "    reduced chi-square = 0.006\n",
      "    Akaike info crit   = -103.900\n",
      "    Bayesian info crit = -98.678\n",
      "[[Variables]]\n",
      "    A:        328.176419 +/- 12.15983 (3.71%) (init= 3500)\n",
      "    center:   1.00136944 +/- 0.000367 (0.04%) (init= 1)\n",
      "    fwhm:     0.02187793 +/- 0.000988 (4.52%) (init= 0.02)\n",
      "    m:       -160.019946 +/- 294.7933 (184.22%) (init= 0)\n",
      "    b:        198.346762 +/- 285.9407 (144.16%) (init= 50)\n",
      "[[Correlations]] (unreported correlations are <  0.100)\n",
      "    C(m, b)                      = -1.000 \n",
      "    C(fwhm, m)                   = -0.853 \n",
      "    C(fwhm, b)                   =  0.851 \n",
      "    C(center, b)                 =  0.836 \n",
      "    C(center, m)                 = -0.835 \n",
      "    C(center, fwhm)              =  0.712 \n",
      "    C(A, b)                      =  0.469 \n",
      "    C(A, m)                      = -0.469 \n",
      "    C(A, center)                 =  0.365 \n",
      "    C(A, fwhm)                   =  0.149 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(result.fit_report())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "Now let's make a plot of the fit results, the data and the difference curve.\n",
    "This time subplot will produce an axis handle that is an array of two items one for data and the fit and one for the difference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'difference (counts)')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f2,ax2=plt.subplots(nrows=2,ncols=1,sharex=True)\n",
    "ax2[0].errorbar(data_x,data_y,yerr=data_err,fmt='bo',label=\"Raw\")\n",
    "ax2[0].plot(data_x, result.best_fit, 'r-',label=\"Fit\")\n",
    "ax2[0].legend()\n",
    "ax2[0].set_ylabel('counts')\n",
    "#ax2[1].plot(data_x,result.residual)\n",
    "ax2[1].plot(data_x,data_y-result.best_fit)\n",
    "ax2[1].set_xlabel('$k (rlu)$')\n",
    "ax2[1].set_ylabel('difference (counts)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x116a9a358>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x116b6c9e8>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "To save my nice figure I use."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "f2.savefig('test.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  },
  "toc": {
   "colors": {
    "hover_highlight": "#DAA520",
    "running_highlight": "#FF0000",
    "selected_highlight": "#FFD700"
   },
   "moveMenuLeft": true,
   "nav_menu": {
    "height": "85px",
    "width": "252px"
   },
   "navigate_menu": true,
   "number_sections": true,
   "sideBar": true,
   "threshold": 4,
   "toc_cell": false,
   "toc_section_display": "block",
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}