PSEN_calib.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%matplotlib widget\n",
    "import h5py\n",
    "import glob\n",
    "import numpy as np\n",
    "import json\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import clear_output, display\n",
    "\n",
    "from alvra_tools.load_data import *\n",
    "from alvra_tools.channels import *\n",
    "from alvra_tools.timing_tool import *\n",
    "from alvra_tools.utils import *\n",
    "from alvra_tools.YAG_scans import *\n",
    "from ipyfilechooser import FileChooser\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "run: 0011\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/sf/alvra/data/p21622/raw/run0011-TT_calib_short/meta/scan.json'"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pgroup='p21622'\n",
    "runnumber = 11\n",
    "print ('run: {:04d}'.format(runnumber))\n",
    "\n",
    "#############################################################\n",
    "jsonfile = ''\n",
    "jsonfile = glob.glob('/sf/alvra/data/{}/raw/*{:04d}*/meta/scan.json'.format(pgroup, runnumber))[0]\n",
    "titlestring = str( pgroup + ' --- ' +jsonfile.split('/')[-3])\n",
    "jsonfile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'SARES11-SPEC125-M1.edge_position'"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "channel_PSEN126_arrTimes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing: scan.json\n",
      "Step 13 of 13: Processing acq0013\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "\u001b[32mSAR-CVME-TIFALL4:EvtSet             1001 / 1001 -> 0% loss ▇▇▇▇▇▇▇▇▇▇\u001b[39m\n",
      "\u001b[32mSARES11-SPEC125-M1.edge_derivative  1001 / 1001 -> 0% loss ▇▇▇▇▇▇▇▇▇▇\u001b[39m\n",
      "\u001b[32mSARES11-SPEC125-M1.edge_derivative2 1001 / 1001 -> 0% loss ▇▇▇▇▇▇▇▇▇▇\u001b[39m\n",
      "\u001b[32mSARES11-SPEC125-M1.edge_position    1001 / 1001 -> 0% loss ▇▇▇▇▇▇▇▇▇▇\u001b[39m\n",
      "\u001b[32mSARES11-SPEC125-M1.edge_position2   1001 / 1001 -> 0% loss ▇▇▇▇▇▇▇▇▇▇\u001b[39m\n",
      "\u001b[32mSLAAR11-LMOT-M452:ENC_1_BS          1001 / 1001 -> 0% loss ▇▇▇▇▇▇▇▇▇▇\u001b[39m\n",
      "\n",
      "\u001b[32mover the whole data set: 1001 / 1001 -> 0% loss\u001b[39m\n",
      "\u001b[32mcomplete channels: 6 / 6 -> 0% incomplete\u001b[39m\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "FEL rep rate is 100.0 Hz\n"
     ]
    }
   ],
   "source": [
    "#channel_list = [channel_Events, channel_PSEN126_arrTimes, channel_PSEN124_arrTimes, channel_delay_global]\n",
    "channel_list = [channel_Events, channel_PSEN126_arrTimes, channel_delay_global, channel_PSEN126_peaks,\n",
    "               channel_PSEN124_arrTimes, channel_PSEN124_peaks]\n",
    "\n",
    "from sfdata import SFScanInfo\n",
    "scan = SFScanInfo(jsonfile)\n",
    "delays_rbk = scan.readbacks\n",
    "\n",
    "edge_pos_back = []\n",
    "edge_pos_front = []\n",
    "peaks_mean = []\n",
    "\n",
    "for i, step in enumerate(scan):\n",
    "    check_files_and_data(step)\n",
    "    check = get_filesize_diff(step)\n",
    "    if check:\n",
    "        clear_output(wait=True)\n",
    "\n",
    "        filename = scan.files[i][0].split('/')[-1].split('.')[0]\n",
    "        print ('Processing: {}'.format(jsonfile.split('/')[-1]))\n",
    "        print ('Step {} of {}: Processing {}'.format(i+1, len(scan.files), filename))\n",
    "\n",
    "        results, _ = load_data_compact(channel_list, step)\n",
    "\n",
    "        edge_shot_back  = results[channel_PSEN126_arrTimes]\n",
    "        edge_shot_front = results[channel_PSEN124_arrTimes]\n",
    "        peaks_shot = results[channel_PSEN126_peaks]\n",
    "        peaks_mean.append(np.mean(peaks_shot, axis=0))\n",
    "        \n",
    "        delay_shot = results[channel_delay_global]\n",
    "        \n",
    "\n",
    "        edge_pos_back.append(np.mean(edge_shot_back))\n",
    "        edge_pos_front.append(np.mean(edge_shot_front))\n",
    "\n",
    "    delays_rbk = delays_rbk[:len(edge_shot_back)]\n",
    "edge_pos_back = np.asarray(edge_pos_back)\n",
    "edge_pos_front = np.asarray(edge_pos_front)\n",
    "peaks_mean = np.asarray(peaks_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a20083c72f954aa6ad6aeb8245a6ebdf",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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PMWvWLNy4cQMBAQH466+/8L///Q+zZs2SyqWlpWHYsGFISUnB559/jrS0NNm7Vh06dJB6A3/44QdMnz4dffr0wRNPPIGDBw/K7jU4OLhFJQYuo1Ao8PDDD+OLL75Ap06dEBQUhIMHD+Kbb76p13lXr16NkSNH4oEHHsCsWbOQlpaGhQsXIjAwUJbypWfPnpg+fTqWLFkClUqF2267DZGRkfjkk0/w2muvyYaA8/LysG3bNgCQnoNdu3bhxo0bsLGxkYbwASAhIQEJCQkAdD1aeXl50rMQEBCAgICAet1fQ3r22WexefNmTJgwAQsXLkS/fv2Qn5+PXbt2Ydy4cRg2bBjCw8Px9ttvY8qUKXj88ceRnp6ONWvW1PuZOnToEGbMmIEHHngAly5dwksvvYT27dtj1qxZtT5H//79MW7cOPTu3RtOTk44deoUvvrqK2kVGGM88sgj+N///odp06YhKSkJvXr1wp49e7By5UqMHTu2xvckAcDOzg6+vr74+eefMWLECDg7O8PV1bXZVmYhqrXmm39C1DTKZpMePnxYjB8/Xtja2go7OzsxefJkWULlshmqVX2mTZsmO2/ZTENDn8qzXNPT08UTTzwh3N3dhbm5uejatat48803ZTOL//nnn2qvX3GWYXXXBiASExMboSVrz9fXV4SHhxvcl5mZKWbMmCHc3d2FjY2NGD9+vEhKSqpyFvD169dlx5fNKK18j5GRkWLAgAHC0tJSODs7i0ceecRgwuyioiKxZMkS4ePjIywsLETXrl3F+++/r1euuueh8izfsrrW9HOrCZooEXRGRoaYO3eu8PHxEebm5sLNzU2Eh4eL06dPS2W++OIL0a1bN6FWq0XHjh3F66+/Lj7//HO9tjdmFnBkZKSYOnWqcHR0FFZWVmLs2LHi3LlzRtV94cKFIjQ0VDg5OUl1e+6552RJ3KtKBF32c6ooPT1dPPnkk8LT01OYmZkJX19fsWjRIlFQUKB3T1W1+V9//SWCg4OFWq02+P8KopZIIUQzTEMjakJLly7FsmXLcP36db13eoiIiEwR3wEkIiIiMjF8B5CIqA0QQsgmwRiiUqla7EzW1l5/otaGPYDU5i1duhRCCA7/Upu2a9cuvTyDVeV1bIk2btxYY/2bI28iUVvVKt8BfP311/Hjjz/i9OnTsLKywsCBA7F69WpZTi0hBJYtW4ZPPvkEGRkZ6N+/P/73v//J1kktLCzEggUL8O233yI/Px8jRozAhx9+WGOSVCKiliY7Oxtnzpyptoy/v79e3suWIj09HYmJidWW6datW7OkziFqi1plADhmzBhMmjQJt912G4qLi/HSSy/h+PHjSEhIkBacX716NVasWIENGzaga9eueO2117B7926cOXNG+h/IU089hV9//RUbNmyAi4sL5s+fj5s3b+Lw4cOy/FdEREREbUmrDAAru379Otzc3LBr1y7ccccdEELAy8sLzz77LF544QUAut4+d3d3rF69Gk888QQyMzPRrl07fPXVV5g4cSIA4OrVq/D29sa2bdv0lu0iIiIiaivaxDuAmZmZACAlcU1MTERqaqq0liWgy9Y+ZMgQ7Nu3DwBw+PBhaDQaWRkvLy8EBgZKZYiIiIjaolY/C1gIgXnz5uH222+X1vEsW2/S3d1dVtbd3R0XL16UylhYWMDJyUmvjKH1KgFdL2LFNUy1Wi1u3rwJFxcXzkwjIiJqJYQQyM7OhpeXl9567Kai1QeAzzzzDI4dO4Y9e/bo7asclIlKC34bUl2Z119/HcuWLat7ZYmIiKjFuHTpkslO/GzVAeDs2bPxyy+/YPfu3bIfoIeHBwBdL5+np6e0PS0tTeoV9PDwQFFRETIyMmS9gGlpaRg4cKDB6y1atAjz5s2TvmdmZsLHxweJiYmNOjNNo9Hgn3/+wbBhw2Bubt5o12kr2F7GYXsZh+1lHLaXcdhexqlre2VnZ8Pf39+kZ5W3ygBQCIHZs2fjp59+ws6dO+Hv7y/b7+/vDw8PD0RFRSE4OBgAUFRUhF27dmH16tUAgL59+8Lc3BxRUVF48MEHAQApKSk4ceIE3njjDYPXVavVBhdDd3Z2hr29fUPeooxGo4G1tTVcXFz4P4RaYHsZh+1lHLaXcdhexmF7Gaeu7VVW1pRf32qVAeDTTz+Nb775Bj///DPs7Oykd/YcHBxgZWUFhUKBZ599FitXrkSXLl3QpUsXrFy5EtbW1pgyZYpUdvr06Zg/fz5cXFzg7OyMBQsWoFevXrjzzjub8/aIiIiIGlWrDAA/+ugjAMDQoUNl29evX4+IiAgAwPPPP4/8/HzMmjVLSgQdGRkp6+595513YGZmhgcffFBKBL1hwwbmACQiIqI2rVUGgLVJXahQKLB06VIsXbq0yjKWlpZYu3Yt1q5d24C1IyIiImrZWmUA2JoIIVBcXFzjIufV0Wg0MDMzQ0FBQb3OYyrYXnIqlQpmZmYm/a4LERHJMQBsREVFRUhJSUFeXl69ziOEgIeHBy5dusRf4rXA9tJnbW0NT09PWFhYNHdViIioBWAA2Ei0Wi0SExOhUqng5eUFCwuLOgcjWq0WOTk5sLW1NdmElcZge5UTQqCoqAjXr19HYmIiunTpYvJtQkREDAAbTVFREbRaLby9vWFtbV2vc2m1WhQVFcHS0pK/vGuB7SVnZWUFc3NzXLx4UWoXIiIybfzt2MgYgFBLwOeQiIgq4m8FIiIiIhPDAJAa1c6dO6FQKHDr1q1Gu0ZSUhIUCgWOHDnSaNcgIiJqSxgAEhmQnJyM8ePHw8bGBq6urpgzZw6KioqqPebChQu499570a5dO9jb2+PBBx/EtWvXZGXOnj2LCRMmwNXVFfb29hg0aBD++ecfWZm5c+eib9++UKvV6NOnj951CgoKEBERgV69esHMzAz33HNPfW+XiKhl0ZYAidHA8f/T/VfLlF4NjQEgUSUlJSUIDw9Hbm4u9uzZg++++w5btmzB/PnzqzwmNzcXo0aNgkKhwI4dO7B3714UFRVh/Pjx0Gq1Urnw8HAUFxdjx44dOHz4MPr06YNx48ZJyxkCupm7jz32GCZOnFhl/aysrDBnzhwuW0hEbU/CL8C7gcDGccCW6br/vhuo204NhgEg6Rk6dChmz56NZ599Fk5OTnB3d8cnn3yC3NxcPProo7Czs0OnTp3wxx9/1Pqce/fuRVBQECwtLdG/f38cP35c2peeno7JkyejQ4cOsLa2Rq9evfDtt9/KjtdqtVi9ejU6d+4MtVoNHx8frFixwuC1tFot5s6di+7du+PixYtG339kZCQSEhKwadMmBAcH484778Rbb72FTz/9FFlZWVXeX1JSEjZs2IBevXqhV69eWL9+PWJjY7Fjxw4AwI0bN3D+/HksXLgQvXv3RpcuXbBq1Srk5eXh5MmT0rnef/99PP300+jYsaPBa9nY2OCjjz7CzJkz4eHhYfT9ERG1WAm/oGDzdBy8ZYd1xePweNFz2FnSG8hKAb5/hEFgA2IA2ISEEMgrKq7TJ7+opM7H1mbpvMo2btwIV1dXHDx4ELNnz8ZTTz2FBx54AAMHDkRcXBxGjx6NqVOn1jrJ9X//+1+sWbMGsbGxcHNzw9133w2NRgNAN6TZt29f/Pbbbzhx4gQef/xxTJ06FQcOHJCOX7RoEVavXo1XXnkFCQkJ+Oabb+Du7q53naKiIkycOBHx8fHYvXs3fH19AQB33XUXbG1tq/2UiYmJQWBgILy8vKRto0ePRmFhIQ4fPmzw/goLC6FQKKBWq6VtZWlo9uzZAwBwcXFBjx498OWXXyI3NxfFxcX4+OOP4e7ujr59+9aqHYmI2hIhBC7dzMPPR65g6c/Hcfc3VxFY+BkeLFqCVcVTEKm9Dfu0gQBKf49tX8jh4AbCPIBNKF9TgoDFfzb5dROWj4a1hXE/6qCgILz88ssAdMHXqlWr4OrqipkzZwIAFi9ejI8++gjHjh3DgAEDajzfkiVLMHLkSAC64LJDhw746aef8OCDD6J9+/ZYsGCBVHb27NnYvn07fvjhB/Tv3x/Z2dl477338MEHH2DatGkAgE6dOuH222+XXSMnJwfh4eHIz8/Hr7/+Cjc3N2nfZ599hvz8/Frde2pqql5w6eTkBAsLC9lQbUUDBgyAjY0NXnjhBaxcuRJCCLzwwgvQarVISUkBoFufOioqChMmTICdnR2USiXc3d2xfft2ODo61qpuREStWYGmBMcuZyIuOQNxFzMQl3wLN3IKK5TwBgC0QwZClOcQojyPwcpjpfsEkHUFuLgP8B/c5HVvaxgAkkG9e/eW/qxSqeDi4oJevXpJ28oCpLS0tFqdLywsTPqzs7MzunXrhlOnTgHQvdO2atUqbN68GVeuXEFhYSEKCwthY2MDADh16hQKCwsxYsSIaq9RNowcFRWF4uJi2b727dvXqp5lDK3aIoSocjWXdu3a4YcffsBTTz2F999/H0qlEpMnT0ZISAhUKpV0/KxZs+Dm5obo6GhYWVnhs88+w7hx4xAbGwtPT0+j6khE1JIJIXA5I18W7J1KyUKxVj4qZaZUoKeXPYJt0hHy70cIUZ5De9xAlYtn5VyrYgcZgwFgE7IyVyFh+Wijj9NqtcjOyoadvV2dEvpamauMPsbc3Fz2XaFQyLaVBUIVJzgYq+wcb731Ft555x28++676NWrF2xsbPDss89Ks26trKxqdb6xY8di06ZN2L9/P0JDQ2X77rrrLkRHR1d7fE5ODgDAw8NDNvwMABkZGdBoNAaHncuMGjUKFy5cwI0bN2BmZgZHR0d4eHjA398fALBjxw789ttvyMjIgL29PQDgww8/RFRUFDZu3IiFCxfW6j6JiFqi/KISHLt8C/GXblXRu6fjZqdGiI8TQnwdEeLjhMD2DrA0V+lm+16MqflCtlX/f5hqjwFgE1IoFEYPxQK6IKvYQgVrC7NWu6LD/v374ePjA0AXTJ09exbdu3cHAERHR2PChAl4+OGHAeju99y5c+jRowcAoEuXLrCyssLff/+NGTNmVHmNp556CoGBgbjnnnuwefNm3HXXXdI+Y4aAw8LCsGLFCqSkpEi9cpGRkVCr1bV6V8/V1RWALuBLS0vD3XffDQDS+5KVf4ZKpbJegTQRUVOrbe+euUqBAC8HhPg4ItjHCSE+jmjvaGV4NMV3IGDvpZvwAUPvrit0+30HNso9mRoGgNQkli9fDhcXF7i7u+Oll16Cq6urlL+uc+fO2LJlC/bt2wcnJye8/fbbSE1NlQJAS0tLvPDCC3j++edhYWGBQYMG4fr16zh58iSmT58uu87s2bNRXFyMSZMm4ffff8cdd9wBwLgh4FGjRiEgIABTp07Fm2++iZs3b2LBggWYOXOm1HN35coVjBgxAl9++SX69esHAFi/fj169OiBdu3aISYmBnPnzsVzzz2Hbt26AdAFlk5OTpg2bRoWL14MKysrfPrpp0hMTER4eLh0/fPnzyMnJwepqanIz8+XElwHBATAwsICAJCQkICioiLcvHkT2dnZUhlDeQOJiGpNW6J7xy7nmq6nzXcgoFRJvXtxybcQl5yBeGN792pDqQLGrNbN9oUC8iCwNGAcs0pXjuqNASA1iVWrVmHu3Lk4d+4cgoKC8Msvv0jBzCuvvILExESMHj0a1tbWePzxx3HPPfcgMzNTOv6VV16BmZkZFi9ejKtXr8LT0xNPPvmkwWvNnTsXeXl5GDduHLZv346BA43716JKpcLvv/+OWbNmYdCgQbCyssKUKVOwZs0aqYxGo8GZM2dks6DPnDmDRYsW4ebNm/Dz88NLL72E5557Ttrv6uqK7du346WXXsLw4cOh0WjQs2dP/PzzzwgKCpLKzZgxA7t27ZK+BwcHAwASExPh5+cHQDfcXTHFTVmZusz4JiICoEuxsv0FiMyruCTcECe6IN4sCHHWg3AqQ1lt754u6HOCl4Nlle9K10rA3cCDXwLbXwCyrpZvt/fSBX8Bd9f93CSjEPyNUWdZWVlwcHBAZmam1DNUpqCgAImJifD394elpWW9rqPVapGVlQV7e/tWOwTclNhe+qp7HjUaDbZt24axY8fqvftJ+thexmF7Gac52iu/qATH9v6OuL+/R5y2C+K1nXEDjnrl3O1Le/d8nBDs42hc756xquiJrKyu7VXd729TwR5AIiIiE6HLu1f67l7p51RKNkq0KgCTpXLmKEZPRSKClecRojyPEPsseM3bDYWqicIGpYqpXhoZA0CqlyeffBKbNm0yuO/hhx/GunXrmrhGRERUJq+ouELevVs4cikDN3L01zV3x83SvHu6T09FEiwVmvICuQCSYxiUtSEMAKleli9fLkviXJGpdqsTETWHqnv39N/d6+nlUD5ZIy8Gnn88U3XevTLMv9emMACkenFzc5OtuEFERDWo5fttNalt756HvaU0KzfYxxE9vSq9u5foJk2yrRbz77UpDACJiIiaSulMW/0ZrqurneEqhEDyzTwp2Iu/VMvePR8neDnWkEyf+fdMEgNAIiKippDwS2mOu0pBVlaKbvuDXwJddAns84qKkZCchfhLxvTuOaGnl73xM3OZf88kMQAkIiJqbNoSXc+fgR42IQSShTvitn6PQ918sCtBhXkH/tHr3bNQKdGzvb0sFUuNvXu1xfx7JocBIBERUWO7uE8KrPKEGke1HXWJlkvz7qXDASgCEHsFZb1wlXv3AtvbQ23WiL1wAXcD3cMb5P1EavkYABIRETUSIQQupuch/vgNxGkiEKftgtPCByWQB1UW0KCnIgl9uvpDCAUeu3sYfFztmr7CzL9nMhgAUqPbu3cvnnzySZw+fRrh4eHYunVrc1eJiKhR5BUV4+ilzNL1cnVr5qbnFgGwADBKKueJdIQozyFYeQ7ByvMIVCRCrSiGZvCv2HYyA54O9VtBiqgmXCeLGt28efPQp08fJCYmYsOGDY16raVLlyIkJKTe50lOTsb48eNhY2MDV1dXzJkzB0VF+i9gV5SamoqpU6fCw8MDNjY2CAkJwf/93/8ZLFtYWIg+ffpAoVDgyJEj0vYNGzZAoVAY/KSlpUnl/vzzTwwYMAB2dnZo164d7r//fiQmJtb7vomo9oQQSLqRix/jLuPlrccx9r1o9Foaicmf7sebf57BX6fSkJ5bBAuVEiE+jphutQv/M38PMepnEGM5G/+zeB8zzP5AX+U5qBUlgH17wLtfc98WmQj2AFKju3DhAp588kl06NDB4H4hBEpKSmBm1jIex5KSEoSHh6Ndu3bYs2cP0tPTMW3aNAghsHbt2iqPmzp1KjIzM/HLL7/A1dUV33zzDSZOnIhDhw4hODhYVvb555+Hl5cXjh49Kts+ceJEjBkzRrYtIiICBQUFUr7Ff//9FxMmTMC8efPw9ddfIzMzE8899xzuu+8+xMfHN1ArEFFluYXleffkvXtyng6W0iSNEF/dzFy1mQpISAe+/8TAmTnTlpoeewBJz9ChQzF79mw8++yzcHJygru7Oz755BPk5ubi0UcfhZ2dHTp16oQ//vij2vMkJSVBoVAgPT0djz32GBQKBTZs2ICdO3dCoVDgzz//RGhoKNRqNaKjo1FYWIg5c+bAzc0NlpaWuP322xEbGyudr+y4v//+G6GhobC2tsbAgQNx5swZALres2XLluHo0aNwcnKCSqWqU49jZGQkEhISsGnTJgQHB+POO+/EW2+9hU8//RRZWVlVHhcTE4PZs2ejX79+6NixI15++WU4OjoiLi5OVu6PP/5AZGQk1qxZo3cOKysreHh4SB+VSoUdO3Zg+vTpUpm4uDiUlJTgtddeQ6dOnRASEoIFCxbg6NGj0Gg0euckIuMZ6t3rvazq3r0Zt/vjw4dCELNoOGIWjcD/HgrBjMEdEeLjVD5xo2ymrb2n/GL2XrrtnGlLTahldLmYCiEATZ7xx2m1uuOKVICyDjG7uTVqXuNHbuPGjXj++edx8OBBbN68GU899RS2bt2Ke++9Fy+++CLeeecdTJ06FcnJybC2tjZ4Dm9vb6SkpKBbt25Yvnw5Jk6cCAcHBxw4cACArhdszZo16NixIxwdHfH8889jy5Yt2LhxI3x9ffHGG29g9OjROH/+PJydnaXzvvTSS3jrrbfQrl07PPnkk3jsscewd+9eTJw4ESdOnMD27duxZcsW2NnZwcnJCQBw1113ITo6utp7zsnJAaAL5AIDA+Hl5SXtGz16NAoLC3H48GEMGzbM4PG33347Nm/ejPDwcDg6OuL7779HYWEhhg4dKpW5du0aZs6cia1bt1bZbhV9+eWXsLa2xn/+8x9pW2hoKFQqFdavX4+IiAjk5OTgq6++wqhRo2Bubl7jOYlMSi1X3cgtLMbRy7cQn3wLcRczEH/pFm4a6N3zcrBEsK9ThVU1jJyZy5m21EIwAGxKmjxgpVfN5SpRAnCsz3VfvApY2Bh1SFBQEF5++WUAwKJFi7Bq1Sq4urpi5syZAIDFixfjo48+wrFjxzBgwACD51CpVPDw8IBCoYCDgwM8PDxk+5cvX46RI0cCAHJzc/HRRx9hw4YNuOsuXSLUTz/9FFFRUfj888/x3//+VzpuxYoVGDJkCABg4cKFCA8PR0FBAaysrGBrawszMzO4u7vD3t4eytKA+bPPPkN+fn6t7j01NRXu7vIlj5ycnGBhYYHU1NQqj9u8eTMmTpwIFxcXmJmZwdraGj/99BM6deoEQNejEBERgSeffBKhoaFISkqqsS5ffPEFpkyZAiur8lxffn5+iIyMxAMPPIAnnngCJSUlCAsLw7Zt22p1f0Qmo4pVN8To1bjoPqJ8zdyLt3A6NQuV0u7BQqVEYFnevdKgz6MhJmdwpi21AAwAyaDevXtLf1apVHBxcUGvXr2kbWUBUsWJCcYKDQ2V/nzhwgVoNBoMGjRI2mZubo5+/frh1KlTVdbN09NTqoePj0+V12rfvr1RdVMY6DEVQhjcXubll19GRkYG/vrrL7i6umLr1q144IEHEB0djV69emHt2rXIysrCokWLalWHmJgYJCQk4Msvv5RtT01NxYwZMzBt2jRMnjwZ2dnZWLx4Mf7zn/8gKiqq2joSmYwKq27kCjWOajshXnRB3I0uiP8qFzexU++Qir17IT6OCDC2d4+oFWEA2JTMrXW9cUbSarXIys6GvZ2d1KNl9HWNPaTSUKJCoZBtKwsytFqt8fUpZWNT3isphJCdt+L2ytvqUg9jhoA9PDykYeoyGRkZ0Gg0ej2DZS5cuIAPPvgAJ06cQM+ePQHoelGjo6Pxv//9D+vWrcOOHTuwf/9+qNVq2bGhoaF46KGHsHHjRtn2zz77DH369EHfvn1l2//3v//B3t4eb7zxhrRt06ZN8Pb2xoEDB6rskSUyBUIIJF3PRtxP3yNO8yjitZ1xWvhAW+mVdwto0MunHUJ8dUmWG6x3j6iVYADYlBQKo4diAejeATQv0R1blwCwFejcuTMsLCywZ88eTJkyBQCg0Whw6NAhPPvss7U+j4WFBUpKSvS2GzMEHBYWhhUrViAlJUXqYYyMjIRardYLxsrk5ene7awcoKtUKik4ff/99/Haa69J+65evYrRo0dj8+bN6N+/v+y4nJwcfP/993j99dcNXkulkvdKlH2vT0BO1BpV/e7eZFk5L9xAsPIcQko/AYqLUN+1FfAPaJZ6EzU3BoDUItjY2OCpp57Cf//7Xzg7O8PHxwdvvPEG8vLyZDNga+Ln54fExEQcP34c3bp1g4ODA9RqtVFDwKNGjUJAQACmTp2KN998Ezdv3sSCBQswc+ZM2NvbAwCuXLmCESNG4Msvv0S/fv3QvXt3dO7cGU888QTWrFkDFxcXbN26FVFRUfjtt98AQG+I2tbWFgDQqVMnvRQ5mzdvRnFxMR566CG9+oWHh+Odd97B8uXLpSHgF198Eb6+vnrpZojaEiEEktLzEHex9N295Fs4Y+jdPaVAL3FWCvaClefhocjQP2HOtaapOFELxACQWoxVq1ZBq9Vi6tSpyM7ORmhoKP78809pJm9t3H///diyZQvGjx+PzMxMaaasMVQqFX7//XfMmjULgwYNgpWVFaZMmSJL26LRaHDmzBmp58/c3Bzbtm3DwoULMX78eOTk5KBz587YuHEjxo4da9T1AeDzzz/HfffdZ/Dehw8fjm+++QZvvPEG3njjDVhbWyMsLAzbt2+XTRYhau1yC4tx9NKt0rx7t6qcmdve0QrBPo6lQ7mOCCg6DvWmZTVfwNbwKx1EpoABIOnZuXOn3jZDM1bL3turya1bt2Tfhw4davBYS0tLvP/++3j//fcNnsfQcX369JFtU6vV+OGHH5CVlSWbBWwsHx8fqefOED8/P726dOnSBVu2bKn1NQydo8y+ffuqPXbSpEmYNGlSra9F1KhqmWqlOkIIJN7I1Q3lVte7Z6ZEr/YOCPFxlGbnuttXendPO0iXWy8rBYChv2MK3X7fgUbVkagtYQBIRER1V0WqFYxZXW1i44q9e3HJtxCfnIGMPP1E5mW9e+V59xxgYVbDP+yUKt31v38EulU2KgaBXHWDCGAASPX05JNPYtOmTQb3Pfzww1i3bl0T14iImkyFVCsyWSm67Q9+CXS5C0IAiTdycexqDuLr27tXW2WrbhgMTldx1Q0yeQwAqV6WL1+OBQsWGNxXNmGCiNogbYkuuDIwxJoj1Dim7YS4LZE41N4Nsf+qkLt/r165ir17Ib5OCPC0r7l3zxhcdYOoSgwAqV7c3Nzg5ubW3NUgoqZ2cR+QdVXXuyc8ECe6IE6r+5wV3rq8exoAZ9MBKGBhpkTv9g6ygK/OvXvG4KobRAYxACQiolrLKXt372A64osWIF7bBRmw0yvXHtcRrDyPoD59kV+kxPT7x8DGSm3gjETUHBgANrLazpQlakx8DqkuhBD490aulGA57mIGzl7LLn13zxxACADAAkXorUiskHfvHNwVtwAAmpBfse1kRsMO7RJRvTEAbCRly5Xl5eUxNxs1u4r5ComqIvXulSZajr90C7eqmpnr7YCQxHUIKTqMAEUSLBSVV+ApTbXi3Q84+WfT3AAR1RoDwEaiUqng6OiItLQ0AIC1tbXemra1pdVqUVRUhIKCgjrntTMlbK9yQgjk5eUhLS0Njo6OekvIUSvQADn2DKnYu1eWhuXMtWxU7iwue3cvxFeXZDnYp8K7ewnjge9/MHB2plohaukYADYiDw8PAJCCwLoSQiA/Px9WVlZ1DiJNCdtLn6Ojo/Q8UitSxxx7hmQXaHD0UmbpqhrV9+6VBXshPk7oUd3M3NqkWtHoX4OImh8DwEakUCjg6ekJNzc3aOrxP0GNRoPdu3fjjjvu4BBeLbC95MzNzdnz1xrVJsdeFUGgEAIXrudKOfeq6t1TmynRu4ODlGQ5xMcJbsbOzGWqFaJWiQFgE1CpVPX6BaxSqVBcXAxLS0sGNLXA9qJWr5oce7ptCmD7Ql3gpVTJevfK1s3NzK9n754xmGqFqNVhAEhE1NKU5tgzRCsU+Fd4Iu5mZ8R/+TfiMixxNq2m3j1d0Gd07x4RtVkMAImIWpqca9Ifs4UVjmo7SYmW47WdkQlb3c7TGuiyLQMdnKxkQ7kN1rtHRG0SA0AiohZCqy2dmXvZCfGaGYjTdsZZ0QEC8kBOjSL0VvyLkN69EdyrF3v3iMhoDACJiJpJdoEGRy7dQtzFW4hLzsCRSxXf3RsuleugSEOI4pyUaLm74hIsHNyBicc52YKI6oQBIBFRE9D17uUg7uItxF/KQNzFW1W+uxfUwRHBNjcQfPY9hCjPwa10VQ0d5tgjovpjAEhEZEg9EzBnFWhKV9Uw1LtXztvZCsHepTNzfXXv7pmrSod8E0Rpjr1b5QdUzLFHRFRHJh8Afvjhh3jzzTeRkpKCnj174t1338XgwUxnQGTSqkvA3OUuveIVe/fKUrGcS8vR692zNFeid3tHBPs6ShM23OyqeXePOfaIqJGYdAC4efNmPPvss/jwww8xaNAgfPzxx7jrrruQkJAAHx+f5q4eETWHmhIw378R+cVA9PkbOH4lR1pZI6ugWO9U3s66mblln+6eduW9e7XFHHtE1AhMOgB8++23MX36dMyYMQMA8O677+LPP//ERx99hNdff72Za0dETc5AAmYp7562C+JEVxz+Lh3nS9wgYuNkh1qaK9G7g2NpsKdbM7ednbqJb4CIqHZMNgAsKirC4cOHsXDhQtn2UaNGYd++fQaPKSwsRGFhofQ9KysLgG7psfos9VaTsnM35jXaEraXcdheFVyMQXZ2Po6Ivjii7YT4kk44qu2ILNjoFfV2skSwtxP6eDsg2NsR3Txs9Xr32KZ8vozF9jJOXduL7QsohKj8loppuHr1Ktq3b4+9e/di4MCB0vaVK1di48aNOHPmjN4xS5cuxbJly/S2f/PNN7C2tm7U+hJRw9MKIC0fSMxW4GKOAonZClzLB0TZTNtSFkoBH1vA11bA307A11bA3qKZKk1E9ZaXl4cpU6YgMzMT9vb2zV2dZmGyPYBlFAr5/+iFEHrbyixatAjz5s2TvmdlZcHb2xujRo1q1AdIo9EgKioKI0eO5Nq2tcD2Mo4ptVd2gQZHLmfiSHIm4i/dwtHLmYbf3VOkIVh5QfdRnUdXxRWYF5cAtwBNliWier1vEu3VEEzp+WoIbC/j1LW9ykbwTJnJBoCurq5QqVRITU2VbU9LS4O7u7vBY9RqNdRq/Xd6zM3Nm+QvalNdp61gexmnrbWXVitw4bpukkbZ7Nzz1/Vn5lqZq3Rr5vo6IcTbAcF/3A3XnHOQTQIRZV8VgJ0XgLbXXo2N7WUctpdxjG0vtq0JB4AWFhbo27cvoqKicO+990rbo6KiMGHChGasGZEJqWeuvYoy83WrasQnZyAu+RaOVDEz19fFGsHeupx7IT5O6O5hB7OK7+4pXimdBayAfCZw6cjAnUuBf+tURSKiFsNkA0AAmDdvHqZOnYrQ0FCEhYXhk08+QXJyMp588snmrhpR21ddrr0akhzXqXevNO+eq20NM3MD7gYe/LKKuq3S5QH8d5uRN0tE1LKYdAA4ceJEpKenY/ny5UhJSUFgYCC2bdsGX1/f5q4aUdtWU669B7+UBYFlvXtxFzOkVTWyq+jdq5iGRa93r7aqS8DM2YNE1AaYdAAIALNmzcKsWbOauxpEpsNArr1yAlqhxPnf3kFcdm/EXcpEfPItnEvL0StpZa5CkLdDac9eLXv3jMEEzETUhpl8AEhETeziPtnQaqawxhFt59JEy11wRNsJ2YU2wE8nZYc1WO8eERExACSipqPVCpy/nIa44qGIE10Qp+2C86KDXjkrFCDI3RwhPbpK7+65NGTvHhGRiWMASESNJjNPg/hLulm58ckZOJJ8C9mFlgAel5XzU6QiRHEOwUrdp7viEszu+QXw7948FSciauMYABJRg9BqBc6l5ZSmYdEFfeerencPZxCiPYmQ0oDPRZFdoYRCN+PWd6DesURE1DAYABK1ZQ2YZ68yw717+jNz/Urf3Qv21b2/183dDmZnioDvl5SWMJBrb8yqBqsnERHpYwBI1FbVI89eZWW9e7q8e7oevgvXc/XKWVuoENTBEcE+jtW/u1dTrj0j60dERMZhAEjUFhmZZ6+yzDwN4i5lIL4uvXu1nZlbXa49IiJqVAwAidqaGvLsAQpg+0Jd8KVUoUQrcDUP2HzoMo5ezqqxdy/EV9e718e7AWbmMtceEVGzYABI1NZUyrNXWaawRlyGK+L/bwfisuxx5NIt5BSaAUcTZOX8XW0Q7O1Yt949IiJq0RgAErU1OdekP5YIBc6JDojTdkG80CVbviDa63bGFQG4AQCwUAqE+Dqjr5+ztLKGs41FM1SeiIiaAgNAojbkVl4R4m86I17zH2lVjRxY65XzV6QguIsPQgK6oZeXLS7E7cH48Ntgbm7eDLUmIqKmxgCQqJUq0QqcS8tG3MVbpXn3MvCv9O7efVI5axQgSHkBIYpzpXn3zsPZwR6IOA4oVdBoNEhSNM89EBFR82AASNSQGjHv3q28IsQnlwd7Ry9lIsfAzFx/VxsE22cjJHkDQpTn0FVxCWYKbenesjx7H3K2LRGRCWMASNRQGjDvXolW4Oy1bMQlZ0hB378GZubaWKgQ5F2ec0/27l6CKK2PtvwA5tkjIiIwACRqGPXMu5eRW4Qjl2ru3evoaoM+pUmWQ3yc0M3DDiplFeO3zLNHRERVYABIVF91yLtX1rsXd1GXaPnfG9X37oX4OiLY2wlOxs7MZZ49IiIygAEgUX3VkHcvQ9ggPqMd4n7YgbgsOxy9dAu5RSV65Tq62iC4NNgL8XFCV/dqeveIiIjqgQEgUX1Vyrt3Rnjr8u5pOyNedMG/wku3M74IQDoAXe9enwrr5dapd4+IiKiOGABS69SIs22NkZFbhPh0Z8RpHkCc6IKj2k7IhZVeuY6Kqwju4ouQnt3Yu0dERM2OASC1Pg0429YYJVqBM6nZ0kSN+ORbSJTe3btXKmeDfPSpkHevj/ICnCrk3SMiImpuDACpdanNbNsudzXIpW7mFiG+QhqWKt/da2eDEPtshFz8AiHK8+iiuASVoqx+zLtHREQtDwNAaj1qO9u20yijT1197145W7UZ+ng7IqQ0516wjyMcrSvn3atQP+bdIyKiFogBILUeNcy2BQSQdQW4dLDGU5X17pUFe9X27pXm3AvxdUQXN+bdIyKi1o8BILUeFWbbVis3DYC59LVOvXu+Tgj2rtC7V1vMu0dERK0AA0BqPWzda1XspsoVJzKycDrqHI5czsLRy7eQZ6B3r1NZ756vbii32t49IiKiNoQBILUevgN179RlpaDsPcBiocQZ4Y14bWdd7j1FDyRuygWgAk4nSofaqc3Qx8cRwd716N0jIiJqIxgAUuuhVOHm0NWI/+kdxGk7S3n38mCpV9TdSuD2Hu0R6ueCEB8ndHazZe8eERFRKQaA1GIVl2hx5lo24pJvIf6i7v29pHQVgAWycnbIQx/zywju0Rkhffsj0NMWe/+JwtixgTA3Nzd8ciIiIhPGAJBajPScQinnXnzyrSrf3evsZosQbwcE26QjxO4WOnu5Q+V/nzTbVqPRNHXViYiIWhUGgNQsiku0OJ2ajfhLFXv38vTKSe/u+TjpZud6O8HBmr16RERE9cEAkJpExd69uOQMHLucWXXvno+jNDu3cztbKPnuHhERUYNiAEgNTurdS85AXGnQd7Ga3r2Q0hU12LtHRETUNBgAUr3dqNi7d1HXu5evYe8eERFRS8UAkGqmLZGWNyu2dsNpi0DEXc5C3EVdD1/yTQO9e5Zlq2rogr0+3o5wsGLvHhERUUvAAJCqdePwL4iL/BLxOc6I03bBMaFAPmL0ynVxs5WGctm7R0RE1LIxACRJ2bt7ZUO5ceevIDlHBeBRWTk75KKP8gJCAgMREjqAvXtEREStDANAE3Yjp1Aaxo1PNvTunq4Hr4viMkKU5xCiOIcQ5Tl0UlyFUgEg1QvofFzKv0dEREStAwNAE6Ep0eJMxd69at7dC/ZxQohdFoKPLUMf5Xk4KPTLAQCyrujeDfQf3Mi1JyIioobEALCNqti7F5ecgeNVzMwte3cvxFc3YaNT2bt7x/8POHms5gvlXGuE2hMREVFjYgDYBhjdu1eaiiWounf3bN1rd/HaliMiIqIWgwFgK1Sb3j2FotLM3Iq9e7XhOxCw9wKyUgAIAwUUuv2+A+t9P0RERNS0GAC2cJoSLU5cyUJ0qgJ//3AcRy5nGuzds7c0Q58KvXt9fBxhb1mPmblKFTBmNfD9I9BNBqkYBJYGkWNWcQIIERFRK8QAsAU6lHQTf51KK10z9xYKNFoAKgApAOS9e2Xv73V0bYS8ewF3Aw9+CWx/Aci6Wr7d3ksX/AXc3bDXIyIioibBALAF+ishFet2J0rf7S3N0N6yCCNDuuA2fxcEedezd88YAXcD3cOllUBg664b9mXPHxERUavFALClSfgFQ459gluqblLePW97S2zvtBRjh3WCuXkzJFxWqpjqhYiIqA1hANiSJPwCfP8IwiAQZh4tbdbkWOn+cHob0GtCM1WOiIiI2gplc1eASmlLdO/aGZxxW7rtr6W6ckRERET1wACwpbi4Tz7RwpDsq7pyRERERPXAALClqO2KGlx5g4iIiOqJAWBLwZU3iIiIqIkwAGwpylbeQDW5/Oy48gYRERHVHwPAlqJs5Q0A+kFg6fc7lzL/HhEREdUbA8CWpGzlDXtP+Xa70u/dxzZ9nYiIiKjNYR7AlsbQyhtetwHb/2zumhEREVEbwQCwJaq88oZG03x1ISIiojan1Q0BJyUlYfr06fD394eVlRU6deqEJUuWoKioSFYuOTkZ48ePh42NDVxdXTFnzhy9MsePH8eQIUNgZWWF9u3bY/ny5RDCUCJmIiIioraj1fUAnj59GlqtFh9//DE6d+6MEydOYObMmcjNzcWaNWsAACUlJQgPD0e7du2wZ88epKenY9q0aRBCYO3atQCArKwsjBw5EsOGDUNsbCzOnj2LiIgI2NjYYP78+c15i0RERESNqtUFgGPGjMGYMWOk7x07dsSZM2fw0UcfSQFgZGQkEhIScOnSJXh5eQEA3nrrLURERGDFihWwt7fH119/jYKCAmzYsAFqtRqBgYE4e/Ys3n77bcybNw8KRTXpWIiIiIhasVYXABqSmZkJZ2dn6XtMTAwCAwOl4A8ARo8ejcLCQhw+fBjDhg1DTEwMhgwZArVaLSuzaNEiJCUlwd/fX+86hYWFKCwslL5nZWUBADQaDTSN+J5e2bkb8xptCdvLOGwv47C9jMP2Mg7byzh1bS+2bxsIAC9cuIC1a9firbfekralpqbC3V2+YoaTkxMsLCyQmpoqlfHz85OVKTsmNTXVYAD4+uuvY9myZXrbIyMjYW1tXd9bqVFUVFSjX6MtYXsZh+1lHLaXcdhexmF7GcfY9srLy2ukmrQeLSYAXLp0qcHgqqLY2FiEhoZK369evYoxY8bggQcewIwZM2RlDQ3hCiFk2yuXKZsAUtXw76JFizBv3jzpe1ZWFry9vTFq1CjY29tXW/f60Gg0iIqKwsiRI2Fubt5o12kr2F7GYXsZh+1lHLaXcdhexqlre5WN4JmyFhMAPvPMM5g0aVK1ZSr22F29ehXDhg1DWFgYPvnkE1k5Dw8PHDhwQLYtIyMDGo1G6uXz8PCQegPLpKWlAYBe72EZtVotGzIuY25u3iR/UZvqOm0F28s4bC/jsL2Mw/YyDtvLOMa2F9u2BQWArq6ucHV1rVXZK1euYNiwYejbty/Wr18PpVKezSYsLAwrVqxASkoKPD11q2hERkZCrVajb9++UpkXX3wRRUVFsLCwkMp4eXnpDQ0TERERtSWtLg/g1atXMXToUHh7e2PNmjW4fv06UlNTZb15o0aNQkBAAKZOnYr4+Hj8/fffWLBgAWbOnCkN1U6ZMgVqtRoRERE4ceIEfvrpJ6xcuZIzgImIiKjNazE9gLUVGRmJ8+fP4/z58+jQoYNsX9k7fCqVCr///jtmzZqFQYMGwcrKClOmTJHSxACAg4MDoqKi8PTTTyM0NBROTk6YN2+e7B0/IiIiorao1QWAERERiIiIqLGcj48Pfvvtt2rL9OrVC7t3726gmhERERG1Dq1uCJiIiIiI6ocBIBEREZGJYQBIREREZGIYABIRERGZGAaARERERCaGASARERGRiWEASERERGRiGAASERERmRgGgEREREQmhgEgERERkYlhAEhERERkYhgAEhEREZkYBoBEREREJoYBIBEREZGJYQBIREREZGIYABIRERGZGAaARERERCaGASARERGRiWEASERERGRiGAASERERmRgGgEREREQmhgEgERERkYlhAEhERERkYhgAEhEREZkYBoBEREREJoYBIBEREZGJYQBIREREZGIYABIRERGZGAaARERERCaGASARERGRiWEASERERGRiGAASERERmRgGgEREREQmhgEgERERkYlhAEhERERkYhgAEhEREZkYBoBEREREJoYBIBEREZGJYQBIREREZGIYABIRERGZGAaARERERCaGASARERGRiWEASERERGRiGAASERERmRgGgEREREQmhgEgERERkYlhAEhERERkYhgAEhEREZkYBoBEREREJoYBIBEREZGJYQBIREREZGIYABIRERGZGAaARERERCaGASARERGRiWEASERERGRiWnUAWFhYiD59+kChUODIkSOyfcnJyRg/fjxsbGzg6uqKOXPmoKioSFbm+PHjGDJkCKysrNC+fXssX74cQogmvAMiIiKipmfW3BWoj+effx5eXl44evSobHtJSQnCw8PRrl077NmzB+np6Zg2bRqEEFi7di0AICsrCyNHjsSwYcMQGxuLs2fPIiIiAjY2Npg/f35z3A4RERFRk2i1AeAff/yByMhIbNmyBX/88YdsX2RkJBISEnDp0iV4eXkBAN566y1ERERgxYoVsLe3x9dff42CggJs2LABarUagYGBOHv2LN5++23MmzcPCoWiOW6LiIiIqNG1yiHga9euYebMmfjqq69gbW2ttz8mJgaBgYFS8AcAo0ePRmFhIQ4fPiyVGTJkCNRqtazM1atXkZSU1Oj3QERERNRcWl0PoBACERERePLJJxEaGmowWEtNTYW7u7tsm5OTEywsLJCamiqV8fPzk5UpOyY1NRX+/v565y0sLERhYaH0PSsrCwCg0Wig0Wjqc1vVKjt3Y16jLWF7GYftZRy2l3HYXsZhexmnru3F9m1BAeDSpUuxbNmyasvExsZi3759yMrKwqJFi6ota2gIVwgh2165TNkEkKqGf19//XWDdYyMjDTYE9nQoqKiGv0abQnbyzhsL+OwvYzD9jIO28s4xrZXXl5eI9Wk9WgxAeAzzzyDSZMmVVvGz88Pr732Gvbv3y8bugWA0NBQPPTQQ9i4cSM8PDxw4MAB2f6MjAxoNBqpl8/Dw0PqDSyTlpYGAHq9h2UWLVqEefPmSd+zsrLg7e2NUaNGwd7evnY3WgcajQZRUVEYOXIkzM3NG+06bQXbyzhsL+OwvYzD9jIO28s4dW2vshE8U9ZiAkBXV1e4urrWWO7999/Ha6+9Jn2/evUqRo8ejc2bN6N///4AgLCwMKxYsQIpKSnw9PQEoOulU6vV6Nu3r1TmxRdfRFFRESwsLKQyXl5eekPDZdRqtV7gCQDm5uZN8he1qa7TVrC9jMP2Mg7byzhsL+OwvYxjbHuxbVvhJBAfHx8EBgZKn65duwIAOnXqhA4dOgAARo0ahYCAAEydOhXx8fH4+++/sWDBAsycOVPqqZsyZQrUajUiIiJw4sQJ/PTTT1i5ciVnABMREVGb1+oCwNpQqVT4/fffYWlpiUGDBuHBBx/EPffcgzVr1khlHBwcEBUVhcuXLyM0NBSzZs3CvHnzZEO8RERERG1RixkCris/Pz+Dq3f4+Pjgt99+q/bYXr16Yffu3Y1VNSIiIqIWqU32ABIRERFR1RgAEhEREZkYBoBEREREJoYBIBEREZGJYQBIREREZGIYABIRERGZGAaARERERCaGASARERGRiWEASERERGRiGAASERERmRgGgEREREQmhgEgERERkYlhAEhERERkYhgAEhEREZkYBoBEREREJoYBIBEREZGJYQBIREREZGIYABIRERGZGAaARERERCaGASARERGRiWEASERERGRizJq7AkREREQVlWgFDibeRFp2AdzsLNHP3xkqpaK5q9WmMAAkIiKiFmP7iRQs+zUB6ZnZ6KM4j4vCHUoHLywZH4AxgZ7NXb02g0PARERE1PxKihGzazuOfbsEb+QtxlH1THyvfhXhqgNIzSzAU5visP1ESnPXss1gDyARERE1Pa0WuHYCSNwNJO6GuLgPYUXZCDMvL3JdOEAJLQQABYBlvyZgZIAHh4MbAANAIiIianxCADfOlgZ8u4CkPUB+hrRbAeCWsEGMNgAx2gDs0/bEedG+dA8gAKRkFuBg4k2EdXJplltoSxgAEhERUcMTAshIknr4kBQN5FyTl7GwBXwHAf6DsbOoOx7dXgBRw9tpadkFjVdnE8IAkIiIiBpG5hVdoJe4G0iMBjKT5fvNLAGfAYDfYMB/CODVB1DpxnzVF9IhsL/GS7jZWTZCxU0PA0AiIiKqm5zr5QFfUjSQfl6+X2kOdAgF/O/QfTrcBpipDZ6qn78zPB0skZpZAGFgvwKAh4MuJQzVHwNAIiIiqp38W8DFveU9fGkn5fsVSsCzT3nA5zMAsLCp1alVSgWWjA/AU5vioABkQWDZlI8l4wM4AaSBMAAkIiIiwwpzgOT9QFLpe3wpRwGhlZdxD6wQ8IUBVo51vtyYQE989HAIlv2agJTM8nf9PBwsmQewgTEAJCIiIh1NAXD5oK53L3E3cOUQoC2Wl3HpUhrwDda9y2fj2qBVGBPoiZEBHlwJpJExACQiIjJVJRrgSpzUwyeSD0BRUigv4+ADdLwD8CsN+uy9Gr1aKqWCqV4aGQNAIiIiU6EtAVKPl6dmubgP0ORKuxUA0oQjYrQB2KvtifM2IXh85DAOvbZBDACJiIjaKiGA66flufgKMuVlrJyQ6nwb/pfUHvu0AbggvFA27UKRBTy1KQ4fPRzCILCNYQBIRETUVggB3PxXHvDlXpeXsbAD/AZJEzdK2gXg3jd2IqVEP8Eyl2BruxgAEhERtWaZl8vTsiTuBrIuy/ebWenSsZTN1PXsA6jKf/0fvJAum3FbGZdga5sYABIRETWhEq2o3wzXnLQKq23s1vX4VaQ0B7z7la62cYcuEXMVyZeB2i+txiXY2hYGgERERE1k+4kUvRx3njXluMvPAJL2lgd810/J9yuUgFeIboau/x2A9wDAwrrWdart0mpcgq1tYQBIRETUBLafSMFTm+L0ljlLzSyQJlqM6OYKs5J8KM7/BVwqDfpSjgGVj3LvVT6k6xsGWDrUuV5cgs00MQAkIiJqZCVagWW/JhgMsCxQhL7Kc0j56UeoPC7iriuHoTxWabUN164VAr7bAZuGexePS7CZJgaAREREjexg4k1p2NccxeituICBypMIUyagr/Ic1AoNUALgiq68cPSFwv8OwH8I4Hc7YN+4KVi4BJvpYQBIRETUmLQlKEo+hCdUvyJMmYDblKdho5CvtpEqnLBP2xP+fUfhRpENht47Debm5k1aTS7BZloYABIRETUkrVY3UaMsLUvSHgwpzMSQCvFcurDDfm0PxGh7Yp+2J/4VngAU+DogFHmn9jdb1bkEm+lgAEhERFQfUvLlXeX5+PJuyIuo7RGt6Yadhd2xT9sTZ0QHCCil/WUTLfr6OuHPSpN8iRoDA0AiIiJj3bpUnpYlcTeQfVW+39xalnxZ4RGEvFPXsX5THABOtKDmxwCQiIioJtnXSpMv79L18GUkyverLIAO/cpn6rbvC5hZyIrUZqKFRqNpirshYgBIRESkJ+8mkLSnfMWN66fl+xUqoH1IecDn3R8wt6rxtJxoQS0FA0AiIqLCbOBiTPl7fKnHoTdQ61GWfHmIbnjX0r5Ol+JEC2oJGAASEVGbVeW6u5p84NKB8nf4rsQBokR+cLvuFZIvDwKsuRIGtR0MAImIqE2quO6uOYoRpDiP0dZncb/TBThnHAVKiuQHOPmXB3x+gwE79+apOFETYABIRERtzvbjl/HRNz9igvIkwswTcJvyDKwVhbrVNsoytNh5AR2HlAd8jt7NWWWiJsUAkIiIWj+tFkhLABJ3QyTuxqCzuzBGnScrckPYI0YbgBhtT5yzDsZ3zz4ElUpZxQmJ2jYGgERE1PoIAaSfL3+HLykayEsHoMurZwcgU1jjgLYH9ml7IkYbgDPCG1LWvWzgYFIGJ2OQyWIASERErUPGxfK0LIm7gewU+X5zG8A3DCfVQXghzgkJwg9aVN3Dl5ZdUOU+oraOASAREbVM2aml6+mWpma5dVG+X6UGvPvp0rL436HLy6cyR9aFdJw4XPN6um52lo1UcaKWr9W+/PD777+jf//+sLKygqurK+677z7Z/uTkZIwfPx42NjZwdXXFnDlzUFQkn/F1/PhxDBkyBFZWVmjfvj2WL18OIQSIiKgZ5N0EEn4Gfp8PfHAb8FY34McZQPxXuuBPaaZLuHzHf4FHfgEWXgQifgOG/Bfw6Q+ozAEA/fyd4elgiapSKysAeDroUsIQmapW2QO4ZcsWzJw5EytXrsTw4cMhhMDx48el/SUlJQgPD0e7du2wZ88epKenY9q0aRBCYO3atQCArKwsjBw5EsOGDUNsbCzOnj2LiIgI2NjYYP78+c11a0RErU6VufZqUpAFXNxXPqR77XilAgrAMwjwH1yefFltV+NpVUoFlowPwFOb4qAA190lMqTVBYDFxcWYO3cu3nzzTUyfPl3a3q1bN+nPkZGRSEhIwKVLl+Dl5QUAeOuttxAREYEVK1bA3t4eX3/9NQoKCrBhwwao1WoEBgbi7NmzePvttzFv3jwoFPwfAxFRTSrm2ivjWWFtW5miPODS/vKA7+oRA8mXe1TIxTcIsHKqU71qs+4ukSlrdQFgXFwcrly5AqVSieDgYKSmpqJPnz5Ys2YNevbsCQCIiYlBYGCgFPwBwOjRo1FYWIjDhw9j2LBhiImJwZAhQ6BWq2VlFi1ahKSkJPj7++tdu7CwEIWFhdL3rKwsAIBGo2nUBbzLzs1FwmuH7WUctpdx2F7l/jp1Dc9tPgIBQK0q356Rk49nvz2M9/4TgCHWieiW8iOUGz+EuHoYCq283YSTP7R+gyH8BkP4DAJs3eQXqUc7j+jmiqFdBuPwxQzcyCmEq60afX2doFIqWuzPj8+XceraXmzfVhgA/vvvvwCApUuX4u2334afnx/eeustDBkyBGfPnoWzszNSU1Ph7i7P4O7k5AQLCwukpqYCAFJTU+Hn5ycrU3ZMamqqwQDw9ddfx7Jly/S2R0ZGwtrauiFur1pRUVGNfo22hO1lHLaXcdheOqv7lf9ZIUrgmJcE1+wEuOacgvMvZ2EmitC9Qvl8c2dctwvADdsAXLfrgQKL0jQsSQCSDjVqXW8A+PNUo16iwfD5Mo6x7ZWXl1dzoTauxQSAS5cuNRhcVRQbGwutVgsAeOmll3D//fcDANavX48OHTrghx9+wBNPPAEABodwhRCy7ZXLlE0AqWr4d9GiRZg3b570PSsrC97e3hg1ahTs7eu2KHhtaDQaREVFYeTIkTA3N2+067QVbC/jsL2Mw/bSOZh4E9M3HkA3JKO/8hQGKE6in+IUbBXy1CpFahekWXVBu373QdlpKMyc/OGpUIADsIbx+TJOXdurbATPlLWYAPCZZ57BpEmTqi3j5+eH7OxsAEBAQIC0Xa1Wo2PHjkhOTgYAeHh44MCBA7JjMzIyoNFopF4+Dw8PqTewTFpaGgDo9R5WvE7FIeMy5ubmTfIXtamu01awvYzD9jKOSbaXEMCNc0DiLvgficQ+s31wVuTIimQKa+zXBmCftif2aXvimfFjgMtHMPa2sabXXvVgks9XPRjbXmzbFhQAurq6wtXVtcZyffv2hVqtxpkzZ3D77bcD0P0LICkpCb6+vgCAsLAwrFixAikpKfD01P07MzIyEmq1Gn379pXKvPjiiygqKoKFhYVUxsvLS29omIjIZGUklU/aSNwN5FwDAHgBgALIFWoc1HaXVtuonHzZ1c5SWnqXiFqOFhMA1pa9vT2efPJJLFmyBN7e3vD19cWbb74JAHjggQcAAKNGjUJAQACmTp2KN998Ezdv3sSCBQswc+ZMaah2ypQpWLZsGSIiIvDiiy/i3LlzWLlyJRYvXswZwERkurKuliZf3g0k7QZuJcv3q9SAT39o/e7AE3tssDO7PTQGfpUooJtx29fXqdW8d0dkSlpdAAgAb775JszMzDB16lTk5+ejf//+2LFjB5ycdOkCVCoVfv/9d8yaNQuDBg2ClZUVpkyZgjVr1kjncHBwQFRUFJ5++mmEhobCyckJ8+bNk73jR0TU3OqcY6+2cm9UWF4tGkg/J9+vNAPah5amZhkMdOgHmFtCCeB+lxT8xVx7RK1SqwwAzc3NsWbNGllAV5mPjw9+++23as/Tq1cv7N69u6GrR0TUIIzKsVdb+bfKky8nRQPXTlQqoAC8+pTm4bujNPmyrcFT1SbXHtNtELVMrTIAJCJq67afSMFTm+JQeXHK1MwCPLUpDh89HFK7ILAoF0iOKR/WTTkCCK28jFvP0tU27gB8BxqVfHlMoCdGBng0bi8lETU4BoBERC1MiVZg2a8JesEfoBtqVQBY9msCRgZ46AdaxYXA5djySRuXDwGVki/DpTPgVxrw+Q0GbNvVq74qpQJhnVzqdQ4ialoMAImIWpiDiTdlQ6qVCQApmQU4mHgTYX4OwNV4IHGXLuC7dAAornSsg3eF5dUGAw7tG/cGiKjFYwBIRNTCpGVXHfwpoEWAIhlhypPwj1wHZMQDRdnyQjZu5QGf/x2Akx/A7AZEVAEDQCKiFsbNzrLCN4HOiisYqDyJgcoE9FeeglNZ8uVrpUUsHUvf4RuiC/hcuzLgI6JqMQAkImpJhEA/h0w8YRuNgMKjGKg8iXaKTFmRHGGJo6qeCBtxL5Qd7wDcewFKZRUnJCLSxwCQiKi5ZV6pkItvN1SZl7AIAFS63QXCHIe0XbFPG4gYbQBOCH+sfbgflHVNBUNEJo8BIBGRAY2agDnnuizgw80L8v1Kc6DDbThv0wdvn/fEX9k+KIJu7VJPB0usrU8eQCIiMAAkItJTXQLmEd1qXrNcT/4t4OLe8oAvLUG+X6EEvILLU7P4DAAsbNAZwNrGXgmEiEwSA0AiogpqSsD84ZSgmk9SmAMk79elZkmKBlKO6idfdg8sn6XrOxCwdDB4KubYI6LGwACQiKhUbRIwr/rjNOZ1r7RTUwBcPli+2saVQ4C2WF7GpUuFXHy3AzZ16EkkImogDACJiErVJgFzalYBFKIYisuxwKXSYd3kA0BJobywo09pwDdEN7Rrz3f2iKjlYABIRFSqqgTMSmjRQ3ERA5UncbvqJAYdOwOzI5XK2npUSL48WJd8mYiohWIASERUqjwBs0CX0uTLYcoEDFAmwFGRW15QCwgrZyj8y9bTvQNw7cLky0TUajAAJCISArj5L/rf3I1PrP8PISXH4KrIkhXJElY4qO2BU5ZBCOzYCbff/zjMLdTNVGEiovphAEhEpinzcmlaltKJG1mXoQQwCgAUQL6wQKy2G2K0PbFPG4CTwh8lUOHDB4KQlXhYl7qFiKiVYgBIRKYhJ61S8uV/5ftVFkCHfoD/YBwQPfHfGHMkZ5VIuyvmAdyW2MR1JyJqYAwAiajZNOpqG/kZQFKF5MvXT8n3K1S65MtlEze8+wMW1gCA/gD+GWK4bhqNpmHqR0TUjBgAElGzqG61jTotc1aYXZ58OXE3kHIMqJzRz6OXLi2L/x2ATxhgaV/l6ZiAmYjaMgaARNTkalpt46OHQ2oOAjX5wKWD5T18Vw4DokRexrWbPPmytXOD3gcRUWvFAJCImlRtVttY9msCRgZ4yIeDi4uAq3HlAd+lg/rJl538ytOy+A8G7Dwa70aIiFoxBoBE1KRqs9pGSmYBDl64jjDry+UBX/J+QJMrL2znWTqkO1i32oaTb+NWnoiojWAASERNqqrVNhTQoqvispR8OXTzWaA4W17I2qW0h2+wLvBz6cTky0REdcAAkIiaVMXVNvwVqbLVNmTJl4sBqB0Av0Hl7/G16wEomX+PiKi+GAASUdO5lYz+mbvxkfX36FNyHJ6Km7LdeUKNWG03HLcIwlOPPgaVVxCgVDVTZYmI2i4GgETUeLKvlSZfLk3NkpEEJYC7AEABFAozxGm7IkYbgL3anjguOkEDM3w0MQSqDnVIBUNERLXCAJCoDWvURMuG5N0EkvaUT9y4cUa+X6EC2vcF/O/AQUUgnt+vRlJW+XzgeuUBJCKiWmMASNRGNXiiZUMKsoDkmNKAbxeQegLy5MsKwLN3eWoW3zBAbQcA6Afg76FNHKASEREABoBEbVKDJFo2pCgPuHSgvIfvarx+8uV2PXRpWfzvAHwHVZt8mattEBE1DwaARG1MnRMtG1JcBFw5VB7wXY4FSorkZZz8K6y2MRiwc2+gOyEiosbCAJCojal1ouXEm/q9byXFQMrR8kkbyfuB4nx5Gfv28oDP0bvhb4KIiBoVA0CiNqaqRMsGy2m1wLUT6Ji2HarNm4BL+4HCLHlBa9fygM//DsC5I5MvExG1cgwAidqY8kTLhgh0UlxFmDIBt8d9Cfx5EOb5N9GrYhFLh9KVNkp7+Nx6MOAjImpjGAAStTH9/J3h6WCJ1MwCCAAdFGnSahsDlSfhrrilK5is+48wt0GaVSe4ht4LVedhgEdvJl8mImrjGAAStTGqnBSs630ep2O2YaDyJLyV12X7C4U5ctxC4BI4EvC/A8VuvbD/zyiMDRsLlbl5M9WaiIiaEgNAotYuN710tY3Smbrp5xAEIKj0b7dGqHBMdMRebU+csQrGhHH3YFSQX/nxGk1z1JqIiJoRA0Ci1qYgE7i4rzzgu3aiUgEF4BkE+N+BEr87EKfthtQCFW6zs8TTTLRMRERgAEjUoBpl6bWiXF06lsTdup6+q/GA0MrLuAWUT9rwGwRYOQEAVAD61+/qRETUBjEAJGogDbb0WnGhLuFyYnR58mVtpWFa507lq234DQZs3RroLoiIyBQwACRqAPVaeq2kGEg5UiH58gEDyZc7VMjFNxhw6NAYt0FERCaCASBRPRm99Fpp8mXpHb6L+4CibPmBNu3kyZed/JmLj4iIGgwDQKJ6qnnpNQHrrAu4uP04OmYf1r3Hl58hL2TpCPjdDvgP0fXwtevOgI+IiBoNA0CiejK09FpZ8mXdJwFuilvAwQoFLGwB34HlK2549GLyZSIiajIMAInqyc3OEu64Ka20MVB1Eh0UN2RlCoQ5Cj1D4RAwQtfL5xUMqJh0mYiImgcDQGqVGiXdijFyb0jJlwck7sYBy/Oy3RqhwhHRCfu0PRGj7YkU20DseHwMwBx8RETUAjAApFanwdKtGCP/ljz5ctpJaZcCgIASx7R+iNH2xD5tAA5puyEPligL9z66uw8TMBMRUYvBAJBaldqkWxnRzbX+FyrKBZJjygO+lKMGki/3lGbpKnwHIuVCPjZWCkw9GjswJSIiqgMGgNRq1DbdytAug40/uaagNPlyacB35bB+8mWXzuVpWfwGAzbyQHNMoCNGBng079A0ERFRLTAApFaj5nQrQEpmAQ5fzKiyjKREo1tSLXGXbsWNSweA4krndvAuTctSmnzZ3qvG06qUCoR1cqn5+kRERM2IASC1GobSrRhyI6dQf6O2BEg9Xr6e7sV9QFGOvIyte3nvnv8dgJMfc/EREVGbxACQWg03O8talXO1VeOGEMD108Cl0okbSXuAglvyglZO5cGe/x2Aa1cGfEREZBIYAFKr0c/fGZ4OlkjNLDDwHqCAn+IaxticxYD4H6A59zfMj2TJi1jYAX6DyoM+90BAqWyi2hMREbUcDACp1VApFVgyPgBPbYqDAoAH0hGmPImBqgSEKU+ivSIdKAZwClABEGZWUPgM0L2/5z8E8OwDqPjIExER8bchtR45aRiDfdjdYzuQFA1vkSLbrVWYQ+nTDyU+AxGTao7+9z0NcyvbZqosERFRy8UAkFqu/AwgaW95apbrpwAA3qW7hUKJW449kec1CB59RkPlOwCwsIZWo0H6tm2Ambr56k5ERNSCtcoXoM6ePYsJEybA1dUV9vb2GDRoEP755x9ZmeTkZIwfPx42NjZwdXXFnDlzUFRUJCtz/PhxDBkyBFZWVmjfvj2WL18OIQxlmaMmUZgDnIsCIl8GPh4CrPYHNj8EHPxYCv7g3gsY8DQweTMULyTBae4etH9gNVRdhgMW1s1bfyIiolaiVfYAhoeHo2vXrtixYwesrKzw7rvvYty4cbhw4QI8PDxQUlKC8PBwtGvXDnv27EF6ejqmTZsGIQTWrl0LAMjKysLIkSMxbNgwxMbG4uzZs4iIiICNjQ3mz5/fzHdoIjT5wKWD0pq6uuTLxfIyrl3LZ+n63g7YMMceERFRfbW6APDGjRs4f/48vvjiC/Tu3RsAsGrVKnz44Yc4efIkPDw8EBkZiYSEBFy6dAleXrrkvW+99RYiIiKwYsUK2Nvb4+uvv0ZBQQE2bNgAtVqNwMBAnD17Fm+//TbmzZsHBdOBNLwSDXAlrnRId5cu+CuplLPP0bc04BsC+N0O2HMJNSIioobW6gJAFxcX9OjRA19++SVCQkKgVqvx8ccfw93dHX379gUAxMTEIDAwUAr+AGD06NEoLCzE4cOHMWzYMMTExGDIkCFQq9WyMosWLUJSUhL8/f31rl1YWIjCwvKAJStLl2ZEo9FAo9HolW8oZeduzGs0Cm0JcO04lEnRUCTtgeLSfig0ubIiwtYDwm8wtL63Q/jdrgsAK6rDPbfa9mombC/jsL2Mw/YyDtvLOHVtL7ZvKwwAFQoFoqKiMGHCBNjZ2UGpVMLd3R3bt2+Ho6MjACA1NRXu7u6y45ycnGBhYYHU1FSpjJ+fn6xM2TGpqakGA8DXX38dy5Yt09seGRkJa+vGf/8sKiqq0a9RL0LAruAK2mUnwDUnAS45p2FRkicrUmhmhxu23XHDNgA37AKQo/bQJV++CuDqSQAnG6w6Lb69Whi2l3HYXsZhexmH7WUcY9srLy+v5kJtXIsJAJcuXWowuKooNjYWffv2xaxZs+Dm5obo6GhYWVnhs88+w7hx4xAbGwtPT92QoaEhXCGEbHvlMmUTQKoa/l20aBHmzZsnfc/KyoK3tzdGjRoFe3v72t1oHWg0GkRFRWHkyJEwNzdvtOsYTQgg418okvZAeTEaiot7oci9Li+itoPwGVjayzcYSrcecFMo4daI1Wqx7dVCsb2Mw/YyDtvLOGwv49S1vcpG8ExZiwkAn3nmGUyaNKnaMn5+ftixYwd+++03ZGRkSEHXhx9+iKioKGzcuBELFy6Eh4cHDhw4IDs2IyMDGo1G6uXz8PCQegPLpKWlAYBe72EZtVotGzIuY25u3iR/UZvqOtW6dal80kbibiDriny/uTXgM0CauKHwCIKiNPmyqomr2iLaqxVhexmH7WUctpdx2F7GMba92LYtKAB0dXWFq6trjeXKum2VlZbwUiqV0Gq1AICwsDCsWLECKSkpUo9gZGQk1Gq19J5gWFgYXnzxRRQVFcHCwkIq4+XlpTc0bNJy0sqDvcTdQEaifL/KAujQr3ymbvu+gJlF89SViIiIaqXFBIC1FRYWBicnJ0ybNg2LFy+GlZUVPv30UyQmJiI8PBwAMGrUKAQEBGDq1Kl48803cfPmTSxYsAAzZ86Ueg2nTJmCZcuWISIiAi+++CLOnTuHlStXYvHixaY9AzjvJnCxYvLl07LdQqECvEKg6Fga8HXox/x7RERErUyrCwBdXV2xfft2vPTSSxg+fDg0Gg169uyJn3/+GUFBQQAAlUqF33//HbNmzcKgQYNgZWWFKVOmYM2aNdJ5HBwcEBUVhaeffhqhoaFwcnLCvHnzZO/4mYTCbOBijC4tS1I0kHIMQHkybAEFzir8sEsTgBhtAGK13WB3wxlLwgIwpiNTtBAREbVGrS4ABIDQ0FD8+eef1Zbx8fHBb7/9Vm2ZXr16Yffu3Q1ZtZZPkw9cOlDawxetS74sSuRl2nUH/O9AvCoQj/2jRgbsZLtzMwvw1KY4fPRwCMYEMggkIiJqbVplAEhGKC7SBXmJu3U9fJcOACXyJfHg5A/4Dy5NvjwYsHNHiVZg1uodyECB3ikFAAWAZb8mYGSAB1RKEx4yJyIiaoUYALY12hIg5Yiudy9xN5AcA2gq5Tuy8yqftOE/GHD00TvNwcSbSMnUD/7KCAApmQU4mHgTYZ24PBsREVFrwgCwtdNqgbSE8tQsSXuBwkx5GWuX8oDP7w7ApZMu+XI10rKrDv7qUo6IiIhaDgaArY0QQPr58lm6SdFAXrq8jNpBt46u/2Bd0NeuB1ApbU5N3OwsG7QcERERtRwMAFuDzEvwSd8N1c+/Ahf3ANkp8v3m1oBPWHkvn2cQoKxf2uV+/s7wdLBEamZBhTnB5RQAPBws0c/fuV7XISIioqbHALAlyr5W2sO3C0jcDfNbFxFccb/KAvDuXx7weYU0ePJllVKBJeMD8NSmOCgAWRBYNni8ZHwAJ4AQERG1QgwAW6Jdq4FDn0tfhUKFDGt/OPS5G6pOQwHvfoC5VaNXY0ygJz56OATLfk2QTQjxcLDEkvEBTAFDRETUSjEAbIk6DgWuHJImbRR7hSL672iMHToWqiZev3BMoCdGBnjgYOJNpGUXwM1ON+zLnj8iIqLWiwFgSxRwt+5TRqNpvrpANxzMVC9ERERtBwPAFqhEK2Q9bsEd7Go+iIiIiKiWGAC2MNtPpOi9c+frpMa87s1YKSIiImpTjEsOR41q+4kUPLUpTm8FjmtZuu9/nbrWHNUiIiKiNoYBYAtRohVY9muCwZx7ZdtW/XEaJVpDJYiIiIhqjwFgC1HT2rsAkJqlW3uXiIiIqD4YALYQXHuXiIiImgoDwBaCa+8SERFRU2EA2EKUrb1bXXplD3uuvUtERET1xwCwhShbexeAXhBY9n3hXd25AgcRERHVGwPAFqRs7V0PB/kwr7u97vudPdybo1pERETUxjARdAtjaO3d4A52+HP7H81dNSIiImojGAC2QJXX3tU081rARERE1LZwCJiIiIjIxDAAJCIiIjIxDACJiIiITAwDQCIiIiITwwCQiIiIyMQwACQiIiIyMQwAiYiIiEwMA0AiIiIiE8MAkIiIiMjEcCWQehBCAACysrIa9ToajQZ5eXnIysqCubl5o16rLWB7GYftZRy2l3HYXsZhexmnru1V9nu77Pe4KWIAWA/Z2dkAAG9v72auCRERERkrOzsbDg4OzV2NZqEQphz+1pNWq8XVq1dhZ2cHhULRaNfJysqCt7c3Ll26BHt7+0a7TlvB9jIO28s4bC/jsL2Mw/YyTl3bSwiB7OxseHl5Qak0zbfh2ANYD0qlEh06dGiy69nb2/N/CEZgexmH7WUctpdx2F7GYXsZpy7tZao9f2VMM+wlIiIiMmEMAImIiIhMDAPAVkCtVmPJkiVQq9XNXZVWge1lHLaXcdhexmF7GYftZRy2V91xEggRERGRiWEPIBEREZGJYQBIREREZGIYABIRERGZGAaARERERCaGAWAD2L17N8aPHw8vLy8oFAps3bpVr8ypU6dw9913w8HBAXZ2dhgwYACSk5P1ygkhcNddd+mdZ+fOnVAoFAY/sbGxUjlD+9etWye7xvHjxzFkyBBYWVmhffv2WL58eZOuh9gU7QUAZ8+exYQJE+Dq6gp7e3sMGjQI//zzj6xMcnIyxo8fDxsbG7i6umLOnDkoKiqSlWF7lePzVS4uLg4jR46Eo6MjXFxc8PjjjyMnJ0dWhs9Xudq0l6k8X0OHDtW7z0mTJsnOkZGRgalTp8LBwQEODg6YOnUqbt26JStjKs9XQ7VXa3i+mhIDwAaQm5uLoKAgfPDBBwb3X7hwAbfffju6d++OnTt34ujRo3jllVdgaWmpV/bdd981uKzcwIEDkZKSIvvMmDEDfn5+CA0NlZVdv369rNy0adOkfVlZWRg5ciS8vLwQGxuLtWvXYs2aNXj77bfr2Qq11xTtBQDh4eEoLi7Gjh07cPjwYfTp0wfjxo1DamoqAKCkpATh4eHIzc3Fnj178N1332HLli2YP3++dA62V3l7leHzBVy9ehV33nknOnfujAMHDmD79u04efIkIiIipDJ8vsrVpr3KmMrzNXPmTNl9fvzxx7L9U6ZMwZEjR7B9+3Zs374dR44cwdSpU6X9pvZ81be9yrT056tJCWpQAMRPP/0k2zZx4kTx8MMP13jskSNHRIcOHURKSorB81RUVFQk3NzcxPLly2u8fkUffvihcHBwEAUFBdK2119/XXh5eQmtVltjHRtaY7XX9evXBQCxe/duaVtWVpYAIP766y8hhBDbtm0TSqVSXLlyRSrz7bffCrVaLTIzM4UQbK+K7VXV9Ssylfb6+OOPhZubmygpKZG2xcfHCwDi3LlzQgg+X8a2V1XXr6ittNeQIUPE3Llzq9yfkJAgAIj9+/dL22JiYgQAcfr0aSGEaT1fDdFeVV2/opbWXo2NPYCNTKvV4vfff0fXrl0xevRouLm5oX///nrd4Hl5eZg8eTI++OADeHh41HjeX375BTdu3DD4L+hnnnkGrq6uuO2227Bu3TpotVppX0xMDIYMGSJLmjl69GhcvXoVSUlJdb3NBtNQ7eXi4oIePXrgyy+/RG5uLoqLi/Hxxx/D3d0dffv2BaBri8DAQHh5eUnHjR49GoWFhTh8+LBUhu3VV1aWzxdQWFgICwsL2SLyVlZWAIA9e/YA4PNVUW3aq4wpPF8A8PXXX8PV1RU9e/bEggULkJ2dLe2LiYmBg4MD+vfvL20bMGAAHBwcsG/fPqmMqTxfQP3bq0xrfr4aGgPARpaWloacnBysWrUKY8aMQWRkJO69917cd9992LVrl1Tuueeew8CBAzFhwoRanffzzz/H6NGj4e3tLdv+6quv4ocffsBff/2FSZMmYf78+Vi5cqW0PzU1Fe7u7rJjyr5XHuprDg3VXgqFAlFRUYiPj4ednR0sLS3xzjvvYPv27XB0dARguC2cnJxgYWEhtQXbq7y9AD5fZYYPH47U1FS8+eabKCoqQkZGBl588UUAQEpKCgA+XxXVpr0A03m+HnroIXz77bfYuXMnXnnlFWzZsgX33XeftD81NRVubm5653dzc6v22Wmrz1dDtBfQ+p+vhmbW3BVo68r+dTFhwgQ899xzAIA+ffpg3759WLduHYYMGYJffvkFO3bsQHx8fK3OefnyZfz555/4/vvv9fa9/PLL0p/79OkDAFi+fLlse+V3dETpC65VvRvWlBqqvYQQmDVrFtzc3BAdHQ0rKyt89tlnGDduHGJjY+Hp6QnA8D0LIWTb2V7l7cXnS6dnz57YuHEj5s2bh0WLFkGlUmHOnDlwd3eHSqWSyvH50qlte5nC8wXo3mcrExgYiC5duiA0NBRxcXEICQkBULdnpzZlTLm9Wvvz1dDYA9jIXF1dYWZmhoCAANn2Hj16SLOcduzYgQsXLsDR0RFmZmYwM9PF5ffffz+GDh2qd87169fDxcUFd999d43XHzBgALKysnDt2jUAgIeHh96/ZNLS0gBA718+zaGh2mvHjh347bff8N1332HQoEEICQnBhx9+CCsrK2zcuBGA4bbIyMiARqOR2oLtVd5ehpjq8wXoXjpPTU3FlStXkJ6ejqVLl+L69evw9/cHwOfL2PYypC0+X4aEhITA3Nwc586dA6C7z7J7ruj69evVPjtt8fkypC7tZUhre74aGgPARmZhYYHbbrsNZ86ckW0/e/YsfH19AQALFy7EsWPHcOTIEekDAO+88w7Wr18vO04IgfXr1+ORRx6Bubl5jdePj4+HpaWlNIwXFhaG3bt3y1IFREZGwsvLC35+fnW/0QbSUO2Vl5cHALJ3jsq+l/2rMywsDCdOnJANQUVGRkKtVkvvvbG9lLJ3ZCoz1eerInd3d9ja2mLz5s2wtLTEyJEjAfD5Mra9DGmLz5chJ0+ehEajkXraw8LCkJmZiYMHD0plDhw4gMzMTAwcOFAqYwrPlyF1aS9DWtvz1eCaYeJJm5OdnS3i4+OlWW1vv/22iI+PFxcvXhRCCPHjjz8Kc3Nz8cknn4hz586JtWvXCpVKJaKjo6s8J6qYrfTXX38JACIhIUFv3y+//CI++eQTcfz4cXH+/Hnx6aefCnt7ezFnzhypzK1bt4S7u7uYPHmyOH78uPjxxx+Fvb29WLNmTf0bopaaor2uX78uXFxcxH333SeOHDkizpw5IxYsWCDMzc3FkSNHhBBCFBcXi8DAQDFixAgRFxcn/vrrL9GhQwfxzDPPSOdhe5W3F5+vn2Tb1q5dKw4fPizOnDkjPvjgA2FlZSXee+89aT+fr59k22pqL1N5vs6fPy+WLVsmYmNjRWJiovj9999F9+7dRXBwsCguLpauM2bMGNG7d28RExMjYmJiRK9evcS4ceOk/abyfDVUe7WW56spMQBsAP/8848AoPeZNm2aVObzzz8XnTt3FpaWliIoKEhs3bq12nNWFQBOnjxZDBw40OAxf/zxh+jTp4+wtbUV1tbWIjAwULz77rtCo9HIyh07dkwMHjxYqNVq4eHhIZYuXdqkU9ybqr1iY2PFqFGjhLOzs7CzsxMDBgwQ27Ztk5W5ePGiCA8PF1ZWVsLZ2Vk888wzshQAQrC9yvD5+km2berUqcLZ2VlYWFiI3r17iy+//FLvOD5f5WpqL1N5vpKTk8Udd9whtUWnTp3EnDlzRHp6uuw66enp4qGHHhJ2dnbCzs5OPPTQQyIjI0NWxhSer4Zqr9byfDUlhRBtNMU1ERERERnEdwCJiIiITAwDQCIiIiITwwCQiIiIyMQwACQiIiIyMQwAiYiIiEwMA0AiIiIiE8MAkIiIiMjEMAAkaoWWLl0qLWbeEkREROCee+6pdfmdO3dCoVDg1q1b9bru0KFD8eyzz9brHHU914YNG6QlpKrSEn5OSUlJUCgU0hJttdGQ7VqdoqIidO7cGXv37pW2nT59GgMGDIClpWWNbVdYWAgfHx8cPny4kWtK1PYwACRqIhEREVAoFFAoFDA3N4e7uztGjhyJL774otr1dpuTEAKffvopwsLCYG9vD1tbW/Ts2RNz587F+fPnm7t6tVJUVIQ333wTISEhsLGxgYODA4KCgvDyyy/j6tWrjXrtBQsW4O+//27Ua7Rmn3zyCXx9fTFo0CBp25IlS2BjY4MzZ87U2HZqtRoLFizACy+80NhVJWpzGAASNaExY8YgJSUFSUlJ+OOPPzBs2DDMnTsX48aNQ3FxcXNXT0YIgSlTpmDOnDkYO3YsIiMjcezYMbz//vuwsrLCa6+91txVrFFhYSFGjhyJlStXIiIiArt378bhw4fxxhtvID09HWvXrm3U69va2sLFxaVRr9GarV27FjNmzJBtu3DhAm6//Xb4+vrWqu0eeughREdH49SpU41VTaI2iQEgURNSq9Xw8PBA+/btERISghdffBE///wz/vjjD2zYsEEql5mZiccffxxubm6wt7fH8OHDcfTo0SrPGxsbi5EjR8LV1RUODg4YMmQI4uLipP2PPfYYxo0bJzumuLgYHh4e+OKLLwyec/Pmzfjuu++wefNmvPLKKxgwYAA6duyIESNGYNWqVVi/fn2V9SksLMScOXPg5uYGS0tL3H777YiNjdUrt3fvXgQFBcHS0hL9+/fH8ePHpX3p6emYPHkyOnToAGtra/Tq1Qvffvttldc05J133sGePXuwY8cOzJkzB3379kXnzp0xevRofPTRR1i5cmWVx2ZkZOCRRx6Bk5MTrK2tcdddd+HcuXN65bZu3YquXbvC0tISI0eOxKVLl6R9NQ0Bl5SUYPr06fD394eVlRW6deuG9957T1Zm586d6NevH2xsbODo6IhBgwbh4sWLVZ7z4MGDCA4OhqWlJUJDQxEfH69XJiEhAWPHjoWtrS3c3d0xdepU3Lhxo8pzbtq0CaGhobCzs4OHhwemTJmCtLQ0ALp/KHTu3Blr1qyRHXPixAkolUpcuHDB4Dnj4uJw/vx5hIeHS9sUCgUOHz6M5cuXQ6FQYOnSpSgqKsIzzzwDT09PWFpaws/PD6+//rp0jIuLCwYOHGj0s0Fk6hgAEjWz4cOHIygoCD/++CMA3S/U8PBwpKamYtu2bTh8+DBCQkIwYsQI3Lx50+A5srOzMW3aNERHR2P//v3o0qULxo4di+zsbADAjBkzsH37dqSkpEjHbNu2DTk5OXjwwQcNnvPbb79Ft27dcPfddxvcr1Aoqryn559/Hlu2bMHGjRsRFxcnBV2V6//f//4Xa9asQWxsLNzc3HD33XdDo9EAAAoKCtC3b1/89ttvOHHiBB5//HFMnToVBw4cqPK6hu5h5MiRCA4ONvoeIiIicOjQIfzyyy+IiYmBEAJjx46V6gcAeXl5WLFiBTZu3Ii9e/ciKysLkyZNqnX9tFotOnTogO+//x4JCQlYvHgxXnzxRXz//fcAdEH6PffcgyFDhuDYsWOIiYnB448/XmW9c3NzMW7cOHTr1g2HDx/G0qVLsWDBAlmZlJQUDBkyBH369MGhQ4ewfft2XLt2rcrnANANo7/66qs4evQotm7disTERERERADQteFjjz2m9w+CL774AoMHD0anTp0MnnP37t3o2rUr7O3tZXXr2bMn5s+fj5SUFCxYsADvv/8+fvnlF3z//fc4c+YMNm3aBD8/P9m5+vXrh+jo6CrrT0QGCCJqEtOmTRMTJkwwuG/ixImiR48eQggh/v77b2Fvby8KCgpkZTp16iQ+/vhjIYQQS5YsEUFBQVVeq7i4WNjZ2Ylff/1V2hYQECBWr14tfb/nnntERERElefo3r27uPvuu2Xb5s6dK2xsbISNjY1o3769wXvLyckR5ubm4uuvv5b2FxUVCS8vL/HGG28IIYT4559/BADx3XffSWXS09OFlZWV2Lx5c5V1Gjt2rJg/f770fciQIWLu3LlVlre0tBRz5syRbbvnnnukewgLCzN4rrNnzwoAYu/evdL+GzduCCsrK/H9998LIYRYv369ACD2798vlTl16pQAIA4cOCCEqPnnZMisWbPE/fffL4TQtQkAsXPnzlod+/HHHwtnZ2eRm5srbfvoo48EABEfHy+EEOKVV14Ro0aNkh136dIlAUCcOXNGCFFzux48eFAAENnZ2UIIIa5evSpUKpV030VFRaJdu3Ziw4YNVZ5j7ty5Yvjw4Xrbg4KCxJIlS6Tvs2fPFsOHDxdarbbKc7333nvCz8+vyv1EpI89gEQtgBBC6tU5fPgwcnJy4OLiAltbW+mTmJhY5XBaWloannzySXTt2hUODg5wcHBATk4OkpOTpTIzZsyQemnS0tLw+++/47HHHqu2XpV7ml566SUcOXIEixcvRk5OjsFjLly4AI1GI3ux39zcHP369dN7TyssLEz6s7OzM7p16yaVKSkpwYoVK9C7d2+pLSIjI2X3VBuV7+HDDz/EkSNH8NhjjyEvL8/gMadOnYKZmRn69+8vbXNxcZHVDwDMzMwQGhoqfe/evTscHR2Neh9t3bp1CA0NRbt27WBra4tPP/1UukdnZ2dERERg9OjRGD9+PN577z1ZL66hegcFBcHa2lraVrGNAd3z9c8//8iere7duwNAlc9XfHw8JkyYAF9fX9jZ2WHo0KEAINXT09MT4eHh0usEv/32GwoKCvDAAw9UWdf8/HxYWlrW0Dq6ntgjR46gW7dumDNnDiIjI/XKWFlZVfmzJCLDGAAStQCnTp2Cv78/AN2woKenJ44cOSL7nDlzBv/9738NHh8REYHDhw/j3Xffxb59+3DkyBG4uLigqKhIKvPII4/g33//RUxMjDSMNnjw4Crr1KVLF5w+fVq2rV27dujcuTPc3NyqPE4IAUA/8KoY5FanrMxbb72Fd955B88//zx27NiBI0eOYPTo0bJ7qomhe/D09ETnzp3h7Oxc4z0Y2l75HgzdU23uEwC+//57PPfcc3jssccQGRmJI0eO4NFHH5Xd4/r16xETE4OBAwdi8+bN6Nq1K/bv329UvSvSarUYP3683vN17tw53HHHHXrlc3NzMWrUKNja2mLTpk2IjY3FTz/9BACyes6YMQPfffcd8vPzsX79ekycOFEWiFbm6uqKjIyMGusbEhKCxMREvPrqq8jPz8eDDz6I//znP7IyN2/eRLt27Wo8FxGVYwBI1Mx27NiB48eP4/777weg+4WXmpoKMzMzdO7cWfZxdXU1eI7o6Ghptm7Pnj2hVqv1Xup3cXHBPffcg/Xr12P9+vV49NFHq63X5MmTcebMGfz8889G3U/nzp1hYWGBPXv2SNs0Gg0OHTqEHj16yMpWDGQyMjJw9uxZqTcqOjoaEyZMwMMPP4ygoCB07NjR4CSMmu4hKirK4ESI6gQEBKC4uFj2vmF6ejrOnj0ru4fi4mIcOnRI+n7mzBncunVLuoeaREdHY+DAgZg1axaCg4PRuXNng71wwcHBWLRoEfbt24fAwEB88803Vdb76NGjyM/Pl7ZVDhZDQkJw8uRJ+Pn56T1fNjY2euc8ffo0bty4gVWrVmHw4MHo3r27NAGkorFjx8LGxgYfffQR/vjjjxp7l4ODg3H69OlaBa329vaYOHEiPv30U2zevBlbtmyRvU964sSJKt/zJCLDGAASNaHCwkKkpqbiypUriIuLw8qVKzFhwgSMGzcOjzzyCADgzjvvRFhYGO655x78+eefSEpKwr59+/Dyyy/Lgo2KOnfujK+++gqnTp3CgQMH8NBDD8HKykqv3IwZM7Bx40acOnUK06ZNq7aukyZNwn/+8x9MmjQJy5cvx4EDB5CUlIRdu3Zh8+bNUKlUBo+zsbHBU089hf/+97/Yvn07EhISMHPmTOTl5WH69OmyssuXL8fff/+NEydOICIiAq6urlJC6c6dOyMqKgr79u3DqVOn8MQTTyA1NbWmJpZ57rnnEBYWhuHDh+O9995DXFwcEhMT8eeff+KPP/6o8h66dOmCCRMmYObMmdizZw+OHj2Khx9+GO3bt8eECROkcubm5pg9ezYOHDiAuLg4PProoxgwYAD69etXq/p17twZhw4dwp9//omzZ8/ilVdekc2WTkxMxKJFixATE4OLFy8iMjJSLwitaMqUKVAqlZg+fToSEhKwbds2vdm5Tz/9NG7evInJkyfj4MGD+PfffxEZGYnHHnsMJSUleuf08fGBhYUF1q5di3///Re//PILXn31Vb1yKpUKERERWLRoETp37qw39FzZsGHDkJubi5MnT1Zb7p133sF3332H06dP4+zZs/jhhx/g4eEhS8IdHR2NUaNGVXseIqqkGd8/JDIp06ZNEwAEAGFmZibatWsn7rzzTvHFF1+IkpISWdmsrCwxe/Zs4eXlJczNzYW3t7d46KGHRHJyshBCf3JBXFycCA0NFWq1WnTp0kX88MMPwtfXV7zzzjuy82q1WuHr6yvGjh1bqzqXlJSIdevWif79+wsbGxthYWEhOnbsKGbOnCkSEhJk91Zxgkt+fr6YPXu2cHV1FWq1WgwaNEgcPHhQ2l82CeTXX38VPXv2FBYWFuK2224TR44ckcqkp6eLCRMmCFtbW+Hm5iZefvll8cgjj8iuU9NkBSGEKCgoEKtWrRJBQUHCyspKqNVq0b17d/Hcc89J7WnoXDdv3hRTp04VDg4OwsrKSowePVqcPXtW2r9+/Xrh4OAgtmzZIjp27CgsLCzE8OHDRVJSklSmpkkgBQUFIiIiQjg4OAhHR0fx1FNPiYULF0rHpKaminvuuUd4enoKCwsL4evrKxYvXqz3vFQUExMjgoKChIWFhejTp4/YsmWLbBKIELpJLvfee69wdHQUVlZWonv37uLZZ5+VJlpUbotvvvlG+Pn5CbVaLcLCwsQvv/yid04hhLhw4YIAIE32qcmkSZPEwoULZdsqTwL55JNPRJ8+fYSNjY2wt7cXI0aMEHFxcdL+ffv2CUdHR5GXl1eraxKRjkKIWvS/E1GbkJeXBy8vL3zxxRe47777mrs61Mbs3bsXQ4cOxeXLl+Hu7l5j+ePHj+POO+/E+fPnYWdnV6drPvDAAwgODsaLL75Yp+OJTBWHgIlMgFarxdWrV/HKK6/AwcGhytx+RHVRWFiI8+fP45VXXsGDDz5Yq+APAHr16oU33ngDSUlJdb5uUFAQnnvuuTodT2TK2ANIZAKSkpLg7++PDh06YMOGDRgxYkRzV4nakA0bNmD69Ono06cPfvnlF7Rv3765q0RENWAASERERGRiOARMREREZGIYABIRERGZGAaARERERCaGASARERGRiWEASERERGRiGAASERERmRgGgEREREQmhgEgERERkYlhAEhERERkYv4ftGP/ZLKH2VUAAAAASUVORK5CYII=",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m_front,b_front = np.polyfit(delays_rbk,edge_pos_front, 1)\n",
    "m_back,b_back = np.polyfit(delays_rbk,edge_pos_back, 1)\n",
    "#m_back,b_back = np.polyfit(delays_rbk[2:], peakpos[2:], 3)\n",
    "\n",
    "units = scan.parameters['units'][0]\n",
    "label = scan.parameters['name'][0]\n",
    "\n",
    "plt.figure()\n",
    "plt.title(titlestring)\n",
    "#plt.scatter(delays_rbk, edge_pos_back)\n",
    "#plt.scatter(delays_rbk, edge_pos_front)\n",
    "\n",
    "\n",
    "plt.scatter(delays_rbk, edge_pos_front)\n",
    "plt.scatter(delays_rbk, edge_pos_back)\n",
    "\n",
    "#plt.scatter(peakpos, delays_rbk)\n",
    "\n",
    "plt.plot(delays_rbk, m_back*delays_rbk+b_back, label = 'm_back={:.4f}'.format(1/m_back))\n",
    "plt.plot(delays_rbk, m_front*delays_rbk+b_front, label = 'm_front={:.4f}'.format(1/m_front))\n",
    "\n",
    "# fitting = np.polyfit(peakpos, delays_rbk, 2)\n",
    "# print(fitting)\n",
    "# calibTT = np.poly1d(np.polyfit(peakpos, delays_rbk, 2))\n",
    "# fit = calibTT(peakpos)\n",
    "\n",
    "#fitoutput = np.poly1d(delays_rbk[2:], peakpos[2:], 3)\n",
    "#fit = fitoutput(delays_rbk[2:])\n",
    "\n",
    "#plt.plot(peakpos, fit, label = 'm_back={:.6f}'.format(1/m_back))\n",
    "#plt.plot(peakpos, fit)\n",
    "\n",
    "plt.xlabel(\"{} ({})\".format(label, units))\n",
    "plt.legend(loc='best')\n",
    "plt.grid()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.3563611491108074"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2.067 / 0.8772"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-7.4204033605324615e-06, 0.04813237767160184, -103.9892516094055, 74856.99216626037]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "20e468f2f569434da17a8c8030781d4a",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#m_front,b_front = np.polyfit(delays_rbk,edge_pos_front, 1)\n",
    "#m_back,b_back = np.polyfit(delays_rbk,edge_pos_back, 1)\n",
    "#m_back,b_back = np.polyfit(delays_rbk[2:], peakpos[2:], 3)\n",
    "\n",
    "peakpos_fs = calibTT(peakpos)\n",
    "peakpos_mm = fs2mm(peakpos_fs, 0)[::-1]\n",
    "\n",
    "units = scan.parameters['units'][0]\n",
    "label = scan.parameters['name'][0]\n",
    "\n",
    "plt.figure()\n",
    "plt.title(titlestring)\n",
    "#plt.scatter(delays_rbk, edge_pos_back)\n",
    "#plt.scatter(delays_rbk, edge_pos_front)\n",
    "plt.scatter(delays_rbk, peakpos_mm)\n",
    "\n",
    "#_back,b_back = np.polyfit(delays_rbk,peakpos_fs, 1)\n",
    "\n",
    "#plt.plot(delays_rbk, m_back*delays_rbk+b_back, label = 'm_back={:.4f}'.format(1/m_back))\n",
    "#plt.plot(delays_rbk, m_front*delays_rbk+b_front, label = 'm_front={:.4f}'.format(1/m_front))\n",
    "\n",
    "fitting2 = np.polyfit(delays_rbk, peakpos_mm,3)\n",
    "print(list(fitting2))\n",
    "calib_energy = np.poly1d(np.polyfit(delays_rbk, peakpos_mm,3))\n",
    "fit = calib_energy(delays_rbk)\n",
    "\n",
    "#fitoutput = np.poly1d(delays_rbk[2:], peakpos[2:], 3)\n",
    "#fit = fitoutput(delays_rbk[2:])\n",
    "\n",
    "#plt.plot(delays_rbk, fit, label = 'm_back={:.6f}'.format(fitting2[0]))\n",
    "plt.plot(delays_rbk, peakpos_mm)\n",
    "\n",
    "plt.xlabel(\"{} ({})\".format(label, units))\n",
    "plt.legend(loc='best')\n",
    "plt.grid()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26.060856657661795"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#params = [ 7.43036920e-06,-4.74325814e-02, 1.00849561e+02,-7.13907195e+04]\n",
    "params = [ 1.07604871e-03, -6.60835880e+00,  1.35522703e+04, -9.28316517e+06]\n",
    "p = np.poly1d(params)\n",
    "#p(2160)\n",
    "\n",
    "peakpos_mm = fs2mm(calibTT(calib_energy(2160)), 0)\n",
    "peakpos_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23.882842885577702"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = [-7.420403360531298e-06, 0.04813237767159445, -103.98925160938983, 74856.99216624921]\n",
    "p = np.poly1d(params)\n",
    "p(2130)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.074913488471101"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = fs2mm(499.769, 0)\n",
    "t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "526.3157894736842"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1/0.0019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'channel_PSEN_signal' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-7962453b1e9b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mtargetM1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'babyYAG2'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mchannel_list\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mchannel_Events\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mchannel_PSEN_signal\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mchannel_PSEN_bkg\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;31m#, channel_cam125_signal]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'channel_PSEN_signal' is not defined"
     ]
    }
   ],
   "source": [
    "targetM2 = 'YAG'\n",
    "targetM1 = 'babyYAG2'\n",
    "\n",
    "channel_list = [channel_Events, channel_PSEN_signal, channel_PSEN_bkg]#, channel_cam125_signal]\n",
    "\n",
    "\n",
    "########################################################################\n",
    "json_file = fc.selected\n",
    "from sfdata import SFScanInfo\n",
    "scan = SFScanInfo(json_file)\n",
    "\n",
    "if ' as delay' in scan.parameters['name'][0]:\n",
    "    print ('Scan is done with the stage in fs')\n",
    "    Delay_fs = scan.readbacks\n",
    "    Delay_mm = fs2mm(scan.readbacks,0)\n",
    "else:\n",
    "    print ('Scan is done with the stage in mm')\n",
    "    Delay_fs = mm2fs(scan.readbacks,0)\n",
    "    Delay_mm = scan.readbacks\n",
    "\n",
    "#edgeM1_avg = []\n",
    "#errbars_M1 = []\n",
    "arrTimes_avg = []\n",
    "errbars_M2 = []\n",
    "arrTimes = []\n",
    "arrAmpl = []\n",
    "\n",
    "for i, step in enumerate(scan):\n",
    "    check_files_and_data(step)\n",
    "    clear_output(wait=True)\n",
    "    filename = scan.files[i][0].split('/')[-1].split('.')[0]\n",
    "    print ('Processing: {}'.format(json_file.split('/')[-1]))\n",
    "    print ('Step {} of {}: Processing {}'.format(i+1, len(scan.files), filename))\n",
    "\n",
    "    subset = step[channel_list]\n",
    "    subset.drop_missing()\n",
    "\n",
    "    Event_code = subset[channel_Events].data\n",
    "\n",
    "    FEL_raw  = Event_code[:,12] #Event 12: BAM bunch 1\n",
    "    Ppicker  = Event_code[:,200]\n",
    "    Laser    = Event_code[:,18]\n",
    "    Darkshot = Event_code[:,21]\n",
    "\n",
    "    FEL = np.logical_and(FEL_raw, np.logical_not(Ppicker))\n",
    "\n",
    "    index_good = np.logical_and.reduce((FEL, Laser, np.logical_not(Darkshot)))\n",
    "    index_off  = np.logical_and.reduce((np.logical_not(FEL), Laser, np.logical_not(Darkshot)))\n",
    "\n",
    "    #print (np.shape(index_good), np.shape(index_off))\n",
    "\n",
    "    sig_1  = subset[channel_PSEN_signal].data[index_good]\n",
    "    back_1 = subset[channel_PSEN_bkg].data[index_good]\n",
    "    #sig_2  = subset[channel_cam125_signal].data[index_good]\n",
    "    #back_2 = subset[channel_cam125_signal].data[index_off]\n",
    "\n",
    "    #print (np.shape(sig_1), np.shape(back_1), np.shape(sig_2), np.shape(back_2))\n",
    "\n",
    "    #back_avg_2 = np.mean(back_2, axis = 0)\n",
    "\n",
    "    bkg_files = find_backgrounds(step.fnames[0],'/scratch')\n",
    "    print (\"File recorded at {}\".format(datetime.fromtimestamp(bkg_files[2])))\n",
    "    print (bkg_files[0])\n",
    "    print (bkg_files[1])\n",
    "    background_from_fit_1 = np.loadtxt(bkg_files[0])\n",
    "    peakback_1 = np.loadtxt(bkg_files[1])\n",
    "\n",
    "    #back_avg_2 = np.mean(back_2, axis = 0)\n",
    "    \n",
    "    #print (np.shape(back_avg_2))\n",
    "    #print (np.shape(sig_2))\n",
    "\n",
    "    edgepos_M2,_,_ = edge(targetM2, back_1, sig_1, background_from_fit_1, peakback_1)\n",
    "    arrTimes_M2, arrAmpl_M2,_,_ =  (targetM2, 1.91,back_1, sig_1, background_from_fit_1, peakback_1)\n",
    "    \n",
    "    index_amp = (arrAmpl_M2 > 1) & (arrAmpl_M2 < 3)\n",
    "    index_times = (arrTimes_M2 > -400) & (arrTimes_M2 < 400)\n",
    "    index_total = index_amp & index_times\n",
    "    \n",
    "    arrTimes_filter = arrTimes_M2[index_total]\n",
    "    \n",
    "    arrTimes.append(arrTimes_M2)\n",
    "    arrAmpl.append(arrAmpl_M2)\n",
    "    #edgepos_M1, edgeswfm_M1,_ = edge_selfRef(targetM1, back_avg_2, sig_2)\n",
    "    \n",
    "    #edgeM1_avg.append(np.mean(edgepos_M1))\n",
    "    #errbars_M1.append(np.std(edgepos_M1))\n",
    "    \n",
    "    arrTimes_avg.append(np.mean(arrTimes_filter))\n",
    "    errbars_M2.append(np.std(arrTimes_filter))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ae177db953ea4746914bc051bb060c98",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist(arrTimes_M2, bins = 100)\n",
    "#plt.hist(arrAmpl_M2, bins = 100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "60f49c0df325430f85ddb08859576b8e",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m_M2,b_M2 = np.polyfit(Delay_mm[:6],arrTimes_avg[:6], 1) \n",
    "\n",
    "plt.figure()\n",
    "plt.title(fc.selected.split('/')[-3])\n",
    "plt.plot (Delay_mm, m_M2*Delay_mm + b_M2,  '--', color='black')\n",
    "plt.errorbar(Delay_mm, arrTimes_avg, yerr = errbars_M2, fmt='.',label = str(m_M2))\n",
    "#plt.plot(Delay_mm, arrTimes_avg)\n",
    "plt.legend(loc='best')\n",
    "plt.xlabel('Energy (eV)')\n",
    "plt.ylabel('t0 from TT (fs)')\n",
    "#plt.ylim(0,300)\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "An offset of 3.1281 fs corresponds to an offset of 0.4692 um\n"
     ]
    }
   ],
   "source": [
    "offset_time = 3.1281      # this is in fs\n",
    "\n",
    "offset_space = 3e8 * (offset_time * 1e-15)/2/1e-6          #factor of 2 because of the delay stage, results in um\n",
    "print (\"An offset of\",offset_time,\"fs corresponds to an offset of\",np.round(offset_space,4),\"um\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/sf/alvra/anaconda/alvra-analysis/lib/python3.8/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
      "  and should_run_async(code)\n"
     ]
    }
   ],
   "source": [
    "t0_mm = 24.966\n",
    "t0_mm = 40.131\n",
    "Delay_fs = mm2fs(Delay_mm,t0_mm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.8692375052318133\n"
     ]
    }
   ],
   "source": [
    "m_M2,b_M2 = np.polyfit(Delay_fs,edgeM2_avg, 1) \n",
    "\n",
    "plt.figure()\n",
    "plt.title(fc.selected_filename)\n",
    "\n",
    "plt.plot (Delay_fs, m_M2*Delay_fs + b_M2,  '--', color='black')\n",
    "plt.errorbar(Delay_fs, edgeM2_avg, yerr = errbars_M2, fmt='.',label = str(-1/m_M2))\n",
    "plt.legend(loc='best')\n",
    "plt.xlabel('Delay (fs)')\n",
    "plt.ylabel('pixel')\n",
    "plt.grid()\n",
    "plt.show()\n",
    "\n",
    "print(-1/m_M2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/sf/alvra/anaconda/alvra-analysis/lib/python3.8/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
      "  and should_run_async(code)\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
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       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.833608113632988\n"
     ]
    }
   ],
   "source": [
    "idx = np.isfinite(Delay_fs) & np.isfinite(edgeM1_avg)\n",
    "m_M1,b_M1 = np.polyfit(np.array(Delay_fs)[idx],np.array(edgeM1_avg)[idx], 1) \n",
    "\n",
    "plt.figure()\n",
    "plt.title(fc.selected_filename)\n",
    "plt.plot (Delay_fs, m_M1*Delay_fs + b_M1,  '--', color='black')\n",
    "plt.errorbar(Delay_fs, edgeM1_avg, yerr = errbars_M1, fmt='.',label = str(-1/m_M1))\n",
    "plt.legend(loc='best')\n",
    "plt.xlabel('Delay (fs)')\n",
    "plt.ylabel('pixel')\n",
    "plt.grid()\n",
    "plt.show()\n",
    "\n",
    "print(-1/m_M1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/sf/alvra/anaconda/alvra-analysis/lib/python3.8/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
      "  and should_run_async(code)\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'signal' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-42-30b8486030f5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mnus_new\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlinspace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnus\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnus\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2047\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mendpoint\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;31m#filter = np.concatenate((np.ones(5), 1-signal.tukey(65), np.ones(1430), np.zeros(1500)))\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mfilter\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconcatenate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mones\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m50\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0msignal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtukey\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m40\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m40\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1977\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2047\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      6\u001b[0m \u001b[0mfilter3\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconcatenate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mones\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'signal' is not defined"
     ]
    }
   ],
   "source": [
    "lambdas = 467.55 + 0.07219*np.arange(0,2047)      #calibration new spec 23-9-2020\n",
    "nus = 299792458 / (lambdas * 10**-9)\n",
    "nus_new = np.linspace(nus[0], nus[-1], num=2047, endpoint=True)\n",
    "#filter = np.concatenate((np.ones(5), 1-signal.tukey(65), np.ones(1430), np.zeros(1500)))\n",
    "filter = np.concatenate((np.ones(50),signal.tukey(40)[20:40], np.zeros(1977), np.zeros(2047)))\n",
    "filter3 = np.concatenate((np.zeros(100), np.ones(100)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f090a024023b43fa9fed09ae437e7c3d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FileChooser(path='/sf/alvra/data/p17589/raw/scan_info', filename='', show_hidden='False')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "background_from_fit = np.loadtxt('/sf/alvra/data/p17589/scratch/2020-10-10-16:10-psen-background.txt')\n",
    "\n",
    "fc = FileChooser('/sf/alvra/data/p17589/raw/scan_info/')  #this is for RC\n",
    "fc.use_dir_icons = True\n",
    "display(fc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "\u001b[32mSAR-CVME-TIFALL5:EvtSet                     501 / 501 -> 0% loss ▇▇▇▇▇▇▇▇▇▇\u001b[39m\n",
      "\u001b[31mSARES11-SPEC125-M2.roi_background_x_profile 499 / 501 -> 0% loss ▇▇▇▇▇▇▇▇▇▇\u001b[39m\n",
      "\u001b[31mSARES11-SPEC125-M2.roi_signal_x_profile     499 / 501 -> 0% loss ▇▇▇▇▇▇▇▇▇▇\u001b[39m\n",
      "\n",
      "\u001b[31mover the whole data set: 499 / 501 -> 0% loss\u001b[39m\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "Probe rep rate (FEL) is 50.0 Hz\n",
      "Pump scheme is 1:1\n",
      "Loaded 250 pump and 0 unpump shots\n",
      "352.70204081632653\n",
      "9.448301646239605\n"
     ]
    }
   ],
   "source": [
    "\n",
    "channel_list_pp = [channel_Events, channel_PSEN_signal, channel_PSEN_bkg]\n",
    "channel_list_all = channel_list_pp\n",
    "\n",
    "json_file = fc.selected\n",
    "\n",
    "with open(json_file) as file:\n",
    "    data = json.load(file)\n",
    "numFiles = len(data['scan_files'])\n",
    "stagePos = np.array(data['scan_readbacks'])\n",
    "\n",
    "Timezero = stagePos[0] + (stagePos[-1] - stagePos[0]) / 2\n",
    "\n",
    "#numFiles = 1\n",
    "print (\"Processing\",numFiles,\"files\")\n",
    "print (json_file)\n",
    "\n",
    "timingMean = []\n",
    "timingStd = []\n",
    "#stagePos = \n",
    "edgeSigMean = []\n",
    "\n",
    "\n",
    "for i in range(0,numFiles):\n",
    "    clear_output(wait=True)\n",
    "    filename = (data['scan_files'][i])\n",
    "    resultsPP, results = load_data_compact_laser_pump(channel_list_pp, channel_list_all, filename[0])\n",
    "    \n",
    "    sig = resultsPP[channel_PSEN_signal].pump\n",
    "    back = resultsPP[channel_PSEN_bkg].pump\n",
    "    \n",
    "    edgePos = [] # edge positions\n",
    "    edgeSig = []\n",
    "    \n",
    "    for k in range(0, len(sig)):\n",
    "        # background subtraction\n",
    "        sig2 = np.nan_to_num(sig[k] / back[k]) / background_from_fit\n",
    "    \n",
    "        # interpolate to get evenly sampled in frequency space\n",
    "        sig3inter = interp1d(nus, sig2, kind='cubic')\n",
    "        sig4 = np.pad(sig3inter(nus_new), (0,len(sig3inter(nus_new))), 'constant', constant_values=0)\n",
    "        sig4power = np.abs(np.fft.fft(sig4))**2\n",
    "\n",
    "        # Fourier transform, filter, inverse fourier transform, take the real part, and do a moving average\n",
    "        sig4fft = np.fft.fft(sig4)\n",
    "        sig4filtered = sig4fft * filter\n",
    "        sig4inverse = np.fft.ifft(sig4filtered)\n",
    "        sig4invreal = 2 * np.real(sig4inverse)\n",
    "#        sig4inter = interp1d(nus_new, sig4invreal[0:1647], kind='cubic')\n",
    "#        sig5 = sig4inter(nus)\n",
    "        sig4savgol = savgol_filter(sig4invreal[0:2047], 201, 1)\n",
    "        sig5 = sig4savgol\n",
    "        \n",
    "        # cross correlation, isolate the peak, save it if we have no division by zero errors\n",
    "        xcorr2 = np.correlate(sig5, filter3, 'same')\n",
    "        peak2 = savgol_filter(np.diff(xcorr2)[250:2047-250], 201, 3)\n",
    "        peakxcorr, _ = find_peaks(peak2[:],height=np.max(peak2[:]))\n",
    "        if (peakxcorr > 0) & (peak2.max() > 0.05): \n",
    "            edgePos.append(peakxcorr[0])\n",
    "        edgeSig.append(sig5)\n",
    "    \n",
    "    timingMean.append(np.mean(edgePos))\n",
    "    print(np.mean(edgePos))\n",
    "    timingStd.append(np.std(edgePos))\n",
    "    print(np.std(edgePos))\n",
    "    edgeSigMean.append(np.mean(edgeSig))\n",
    "    \n",
    "Delay_fs = (stagePos - Timezero)*2/(3e8*1e3*1e-15) # change to right t0 !\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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 overridden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.993008440575784\n"
     ]
    }
   ],
   "source": [
    "m,b = np.polyfit(Delay_fs.T[0],timingMean, 1) \n",
    "\n",
    "plt.figure()\n",
    "plt.title(fc.selected)\n",
    "plt.plot (Delay_fs, m*Delay_fs + b,  '--', color='black')\n",
    "plt.errorbar(Delay_fs, timingMean, yerr = timingStd, fmt='.',label = str(-1/m))\n",
    "plt.legend(loc='best')\n",
    "plt.xlabel('Delay (fs)')\n",
    "plt.ylabel('pixel')\n",
    "plt.grid()\n",
    "plt.show()\n",
    "\n",
    "print(-1/m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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 overridden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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"
    },
    {
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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 0x2b2cb39f6a90>]"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sigmas = np.arange(10, 200, 2)\n",
    "plt.figure()\n",
    "plt.plot(sigmas, timingMean)\n",
    "plt.plot(sigmas, timingStd)\n",
    "#plt.plot(edgePos)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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 overridden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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"
    },
    {
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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 0x2b2cb3f1fbe0>]"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(edgeAmp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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 overridden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(array([  87.,  170.,  390.,  677.,  791.,  791.,  820., 1027.,  680.,\n",
       "          67.]),\n",
       " array([0.000135  , 0.00022674, 0.00031847, 0.00041021, 0.00050195,\n",
       "        0.00059369, 0.00068543, 0.00077716, 0.0008689 , 0.00096064,\n",
       "        0.00105238]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist(edgeAmp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:alvra-analysis]",
   "language": "python",
   "name": "conda-env-alvra-analysis-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}