Notebooks/ReadSMX.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "class": "test_MAD"
   },
   "source": [
    "# Spike Notebook\n",
    "\n",
    "a simplified environment for processing Bruker NMR datasets with `SPIKE`.\n",
    "\n",
    "# Reading and handling processed data from Topspin\n",
    "\n",
    "***Usage***\n",
    "\n",
    "- This notebook contains a series of short recipes which can be used to read TopSpin processed datasets, and continue to work  with them \n",
    "\n",
    "## Initialization\n",
    "the following cell is to be run once, at the beginning of the processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:20:04.662203Z",
     "start_time": "2023-03-24T14:20:00.310307Z"
    },
    "lines_to_next_cell": 2,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "## STARTING Environment..."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    ========================\n",
      "          SPIKE\n",
      "    ========================\n",
      "    Version     : 0.99.32\n",
      "    Date        : 08-02-2023\n",
      "    Revision Id : 586\n",
      "    ========================\n",
      "\n",
      "loading plugins... ( use spike.plugins.report() for a short description of each plugins )\n",
      "*** zoom3D not loaded ***\n",
      "generic plugins loaded:\n",
      "Fitter,  Linear_prediction,  Peaks,  bcorr,  fastclean,  gaussenh,  rem_ridge,  sane,  sg,  test,  urQRd, \n",
      "user plugins loaded:\n",
      "msapmin, \n",
      "*** load_dump not loaded ***\n",
      "NMR plugins loaded:\n",
      "Bruker_NMR_FT,  Bucketing,  Integrate,  PALMA,  apmin, \n",
      "MS plugins loaded:\n",
      "FTMS_calib,  PhaseMS,  diagonal_2DMS, \n",
      "\n",
      "Interactive module version, 1.3.0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "code_show=false; \n",
       "function code_toggle()\n",
       "    { if (code_show)\n",
       "        {   $('div.input').hide();\n",
       "            $('div.prompt').hide();\n",
       "            $('#but').val(\"show python code\");\n",
       "        } else {\n",
       "            $('div.input').show();\n",
       "            $('div.prompt').show();\n",
       "            $('#but').val(\"hide python code\");\n",
       "        }\n",
       "    code_show = !code_show\n",
       "    } \n",
       "$(document).ready(code_toggle);\n",
       "</script>\n",
       "<form action=\"javascript:code_toggle()\">\n",
       "<input id=\"but\" type=\"submit\" style=\"border:1px solid black; background-color:#DDD\">\n",
       "\n",
       "</form>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "doc_show=false; \n",
       "function doc_toggle()\n",
       "    { if (doc_show)\n",
       "        { $('div.text_cell').hide(); $('#butdoc').val(\"show documentation\");\n",
       "        } else { $('div.text_cell').show(); $('#butdoc').val(\"hide documentation\");\n",
       "    }\n",
       "    doc_show = !doc_show } \n",
       "$(document).ready(doc_toggle);\n",
       "</script>\n",
       "<form action=\"javascript:doc_toggle()\">\n",
       "<input id=\"butdoc\" type=\"submit\" style=\"border:1px solid black; background-color:#DDD\">\n",
       "\n",
       "</form>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "hr         {height: 2px; border: 0;border-top: 1px solid #ccc;margin: 1em 0;padding: 0; }\n",
       ".container {width:100% !important; }\n",
       "</style>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAbAAAAEgCAYAAADVKCZpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAgAElEQVR4nOydd3gbVdbG36mq7k53eqWl0mvohFC/BZa+LG3pnSUEWEIJAULvdYGlB1jK0mGXtrDUhJJKem+2Y1tdU+73x0iaGWksWXKVfX7P4yej0dyZa0ejd865p3CMMQaCIAiCKDL4zp4AQRAEQRQCCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBEARRlJCAEQRBEEUJCRhBdAKMsc6eAkEUPWJnT4AgehK/bgzg7i9XgeOA2YePRi+/3NlTIoiihSwwguggVm+L4Lw3F2JpXRi/14bx+Yr6zp4SQRQ1JGAE0UF8srTO9lrVyY1IEK2BBIwgOggtbd3LLdLtRxCtge4gguggqn329S4SMIJoHXQHEUQH0TctYMMl0e1HEK2B7iCC6CAqvZLttSzQ7UcQrYHuIILoIEpc9qwVkec6aSYE0T0gASOIDqLEJdhek4ARROsgASOIDsIn2QWMougJonWQgBFEByGmrXk1RtVOmglBdA9IwAiik2iKkYARRGsgASOITiJEAkYQrYIEjCA6ibCid/YUCKKoIQEjiE4iFNc6ewoEUdSQgBFEJxFTyQIjiNZAAkYQnURcIwEjiNZAAkYQnQQJGEG0DhIwgugkouRCJIhWQQJGEJ0EBXEQROsgASOIToJciATROkjACKKTiFIeGEG0ChIwguggdGav3ktrYATROkjACKKDiKcJFgkYQbQOEjCC6CDSBSsc18AY9VQhiEIhASOIDiKStual6AxxjQSMIAqFBIwgOginsHkKpSeIwiEBI4gOIqRkilUwTi1VCKJQSMAIooOIOAhYuluRIIiWQwJGEB2EU/V5J1EjCKJlkIARRAfhFDYfiJGAEUShkIARRAcRdgjYaIgonTATgugekIARRAfhFMRBFhhBFA4JGEF0EE4h8wGKQiSIgiEBI4gOwsmF6LSPIIiWQQJGEB2EYyIzRSESRMGQgBFEB9EUy3QXUh4YQRQOCRhBdBBOARuUB0YQhUMCRhAdRMDBAqNaiARROCRgBNFBhB1rIZKAEUShkIARRAfRFHVaAyMBI4hCIQEjiA5A0xnCDgEbFMRBEIVDAkYQHYB1rUviudQ2uRAJonBIwAiiA7AKWKVXgpAQMU1nUDSywgiiEEjACKIDiKimgLlFHm7RvPWcqtQTBJEbEjCC6ACsJaN8sgCXYN56Tn3CCILIDQkYQRTAqm0RPPbtWvy0vrFFx1vXusrdItySeeu1NJBjXWMUr/yyEesao/lNliC6KWJnT4Agio2vV23D1e//DgB49ddN+PDMSXCJ2Z8FAzENHIAb9i7BoXgJddvvgXP+2xebg3HEW7AG9u9ldbjh42UAgLcXbMHLJ49r9e9BEMUOCRhB5IGmM9z4ybLU65iqIxBT4RLlrOPCiobTJ/bFYYt3AtQAqjkep++0GLP/Vw9FY1nHBmJqSrwAoJ6aYBIEAHIhEkReMCAjn6vSK+UcF1E0/GXYWkANJE6ko8ZruAJzRSGmW2ilLnruJAiABIwg8kLkOXgl+23Dc1wzR5tEFR1oWmTbx3lrAABxPbuAVXrsAtm/1NWSqRJEt4cEjCDyRM6x3uVEVNWBWK1t38ptMQDI6ULk0gSywaEkFUH0REjACCJPvJKQ95iwogF6PHMfMl2EuXCqqUgQPRESMILIkzJ3/mtQobgGqCHbvmT+Vy4LLJ1GEjCCAEACRhB5U7CAxett+5JCpOr5CRhV7iAIAxIwgsgTdwFrYIwxIFZn25e0wFoiYIVckyC6O3RXEESeeApYAxN4Dohvy9yHlglYiSv/axJEd4cEjCDyRBJyh81njuEBpSlzH1omYH7K/SKIDEjACCJPColClHgO0MK2fa6EEOotELD03DOCIEjACCJvygsI4nBLPBC3F/4VEy7ElsRwFCKaBNHdIQEjiDzx5enO0xlDqcwD0U22/ckEZY21xAIjASOIdEjACCJP0t15Wg4TKhBT0c8VTNvLpYI40BILTLYLGGuB6BFEd4cEjCBaScjS68uJpqiGXmJ63zAGAUYYvd4CBfOkiWaEcsEIggSMIPIl3eJqiGZvbxJWNFTzdRn7Zd4QvpasgaVX62iglioEQQJGEPmSHva+LZK9tFM4rqEStRn7XZwxriVB+en1EgOx7FYfQfQESMAIIk/SBawuFG/mSINAXIWPZVpgUkLAWrKalW6B5XJbEkRPgASMIPIkw52Xo7huKKbBpaWvgZkuRLQgIENJE81gnAr6EgQJGEHkSXoH5VztTRRdB5SGjP0SZ6xjtcQCU9OuGSQXIkGQgBFEvsTT3XlKdjFRNWQ0swQAOY81sHS3ZVOMLDCCIAEjiDyJpVlDoRzWEM8BiG7O2O9GYu2Myy1hGZGPOQJHCKInQAJGEHkST8vByhVGL/CcowXm5mMAzJJS2Ui3wHJdkyB6AiRgBJEn6RZYfbgFYpJWiR4A3IgCSFhouYanCRiF0RMECRhB5E1UsQtYbQ4B43k4CpiLMywwvgUuxHSrL0xh9ARBAkYQ+ZJexilXVQyZZ0A8MwrRjQiAlrkQ0y0wygMjCBIwgsibdOsnrOiIZalN6EcTnILl5YQLsSVRiOnnzxX5SBA9ARIwgsiTsIN41GexwnwsM4kZAOSEBZbszJyN9HU3ciESBAkYQeSNk/sukCUvy9uMgEnM6NAsi/mvgeVKniaIngAJGEHkiZNYZcsFcyHsuF/SQwBatgaWnjwdUfWMAr8E0dMgASOIPIkomcLh5FZM4mLpzSwNeC0Ml8jDLWbvtqxqekYeGEDlpAiCBIwg8kDVdEQdAjay5WV5WKCZk4XgEXnIQnYLLH39KwlFIhI9HRIwgsiDxmbWukJZqsPLuiUHTCwxt9UgPJIAj5TdAoupzuV+s627EURPgASMIPKg0RI8YTWcmrKtgVkFzDfI3FYC8Eg8vFL22zCqajhzQiVOHNsbFR7Rck0SMKJnQwJGEHmwLaJAFjjM3s+DL/b+EM8dFINfFrKLiWJZA3P3NbfVILyykDOMvjL0E85etzMu2TQJb076ABfsXAmPyJOAET0eMfchBEEkqQ+reOHY/qj5dCAAYKT8AI7ZYV6z1eE1nUFQrRbYQHNbaUSJLMCTwwJzL38gVYpKnn8DTnU/hF32m4P5FMRB9HDIAiOIPNB1hpoF55o74vXQddZsZQxNZ0DckgfmG2pux+pQ6hbhFnPchlu+tL+ObsbouqeQaxhBdHfoFiCIfOAAbPzAtmtDIIZocwLGdEC1RCF67RaYTxazh9FrMSC6KXN/cBnkFlTwIIjuDN0BBJEH6xujAGf3vG8OxjMK/CbRdNgL+XprzG01CL8sGP3CmiO6xXl/eB0knm5fomdDdwBB5MGahgggl9n2BWJqRouVJDqDvZWKpx/AJSwuLYpSOcc6VswiYCWjzO3IRqPKPUH0YEjACCIPGqIaINkFTOR5RFVnIWKMAZqllJToA0R/6mUZH8l+Qav15ukPSKWJE6tww7nCB0H0FEjACCIPwvFMAfPJgmN5KSDRREW1CJjgtQmYX4hlv6BqESmpxHZtW34ZQfRASMAIIg9CcRUQ3LZ9bpHPWgsRasjcFn2GECUo5UMOA1o21sVyjCWIbg4JGEHkgQ4YQmKhyis139Ay3YUoeABXdeplOZ/ZqdmGZnExCm5bKSoSMKKnQwJGEHnAgTPcgBYqPBLiGjPWu9KP16PmC14GeMEmYH449wpLoVsSpDmJLDCCsEACRhAtRElWhecl2/4qt7HfqeUJp1stqITwyRWpXR6WYx1Lt6yRCS7b+lmyISZB9FRIwAiihYTimtH6RI/b9g9y1QHIbDoJAJxqETAxIWC2QIxmWq0k0SwCxrts7kuJLDCih0MCRhAtxBAw3i4qAKr5egCAqmeug3HM4kJMBH8wi4BJWg4XYsYamFXAckQwEkQ3h4r5dgDrN23BvIVLsHDpSixesRobt9Ri49ZabGtsQiQaRzQeB8cBLkmGS5ZQXlqC6spyVFeUYfCAfhg2cABGDBmIsWNGoG91VYfNOxAK49V3P2mXc/M8B0mS4JIluCQJJX4fqivK0auqHL0qyiGKXe+jGYglBMy6rgWgnKsHUOZogfHpAgRAl6uRKh4Vq81+Udt4j239TWQ5csgIopvT9b4lugGMMfz3x1/wxof/wWff/ohlq9e1aJyqRhCKRFDf2IQVa9c7HtOnuhKTdhyDvXcej312Ho/x248C304lheobGnHpLXe3y7mzIYoChgzoh5FDBmHM8MHYdewO2G38juhTXdnhc7ESUlRIAgdodgErYfUAhjqvgTHFfMG7AACqVGEKWHxb9otarD2Vc0EUTQGT9LZfAzv3utvw4tsf5jXmg7/fj313ndDmc2kJdzz+HG5+8Om8x5X4vPj0+Yex46jhOY/98vt5mHLmpYVMr9P45vWnMW7MyM6eRrtDAtaGNAaCePLVt/DEy29i/eat7XKNzbX1eP/zb/D+598AAKorynDovnvg8Ml74tB99oDH7WqX63Ykqqph2ep1WLZ6HT744pvU/tFDB+HIA/fFMQfvhwk7jO7weUUUHS6RzxAwr7YFPJeoPJ8Gp6etYQHQeEtX5niOMHqLtadAgiB4kaycyOtho11LtlqK3Zg3P/4ctzz097zHCYKAZ2ff2CLxIro2JGBtQCwexwPPvoq7n34RgVDHRobVbmvEi29/iBff/hAlPi+OOmhfnHTkoZi820RwXPf6Yluycg2WPPUC7nrqBewwchguOOU4/PGIgztMtENxzRCwqN11J0TWodonQ3UK4rAGfAgyACAuVSNlR0U3Z7+oxYWocZ5UGUUAgBqC2kMFbN6CJTj3utscUxdycfvVF+Kwffdoh1kRHQ0FcbSSr3/6BZOOOh0zHniyw8UrnUAojBff/hBHnH05xk09Gfc/+woamnJEuRUpC5auwIUz7sSOU07Ec/98D7pDAEVb0xBRExZY2tpTaC16+2VoTnlgzCJgvCFgUcGyjhmvz35Ri7WncfYoRKghqFr7/95djQ2bt+L4i69FOBLNfXAa5554DC449bh2mBXRGZCAtYI7Hn8OU868DCvXbejsqWSwfM16TL/rESxdtbazp9KubNpahwv+dgf2O+m8dv9dw4pmNJ9U0x5UIuvRy9uMgOnWNbCEgPGl5r5YXfaLWsbrvGQEciTRolALsECKmXAkiuMvvhYbt+QIfnHgwD13wexpl7TDrIjOggSsAFRVxbnX3YabH3wamtZ127pvN2Iodhm7fWdPo0OYu2Ax9jr+bLz8r4/b7RrhuAaPyNtLQwFAdDMqvRKctIRjlkoaiQToCPymEGlhe8fmdKzjOdGeRK0r6EkGGGMMZ197K35e+HveY7cbPgTP331Tl4xuJQqHBCxPGGP48zW35B2p1Rn86f+mdvYUOpRQJIKzr70V9z/7SrucPxjX4BFZRhAHYnWocHOOQRx2ATIWsCKqDrj7WMZnC/gx17d4AOAtX8BMdb5mN2XG/U/i7U+/zHtcdWU5Xn/4dpSV+HMfTBQVJGB5Mv2uR/DPjz7r7GnkRJYknHTkIZ09jU5h+l2P4L5nXm7z826LKCgVnHKvGPrKAThJCWfba9xuEUW31UNEtGURqzwP2KI4mObotuyOvPj2h7jrqRfyHueSZbx6/0wMqenfDrMiOhsSsDz44PNv8MBzr3b2NFrEEQfsjeqK8s6eRqdxw72P493/fNWm52yMqvDzzoEDfYR66I5ikrmvKaYanZmTRJxz/gAYbsMEAlTYblmm9wgL7H9zf8NFM2YXNPbRW67B7hN2auMZEV0FErAW0hgI4sIZd3b2NFrM6T3MfZiOrus4Z/pt2NCG+XjhuIZSwTnStJQPOGkVbAtjnHG7hRUtzYWYJZCDM29RDizDhdjd9WvVug048bLrEFeU3AenMf38M/DHqQe3w6yIrgKtaLaQ+599BZtrc4Q856CyrBRTJu+JiTuMxvjtRqFvryqUlvhR6vNC03VEojHUNTRi09Y6rFi7AUtXrsGCpSvw0/zF2Fqfo2KDhYH9+uDAPXZu1VwLZZ+dx+PDZx/IeVxcURCLK2hoCmBr3TasXLcBS1etxQ+/LsS3P/+GhqZgznPkoikYwmW33oM5D85q9bkAIKRo8PPNCBjXACfnos2FmBCjQDStq7OSLZnZHM9xXIYLsZA8qGKhKRjCcRddi9r6HMneDhw35UBcd+GZ7TCrlrHruB1wylGHddr1a/r27rRrdyQkYC2gMRDEw8+/VvD4UUMH4drzz8DRB+0Llyw7HiPC8NeXl5Zg+KAa7DVpnO39Ves24LNvf8Ln3/6ET7/5PusX/GnHTGm38lJthSxJkCUJJT4vBvbrg4k7jkm9pygqvvh+Lp5941288++vWhXp+d5nX+OL7+div10ntnrODREFPs65AryXNcIxn5hZwwSNA6KqDtVXZd58kSzJzJwZdcgz1WaRgenNuC2LH03T8KerZ2DRspV5j91t3A54/NZp7TCrljNyyECc/cejO3UOPQESsBbw+gf/RjBcWOHUi04/ATddeg7crtZVixhS0x9/Pq4//nzckVAUFV/+MA9vf/IF3vz4c9Q3mj2lOI7Dacce3qprdTaSJOKgvXbFQXvtisXLV+GqWQ/gs29/LPh8dzz+j1YLmKYzhBUdXjg/OLhZALxT5ROrgCXER2cMTXwfpCo7RrLkEVoEi+cYrFGJAOu2LsRr7nwIH3/1Xd7jBg/oi1ceuK3V9xtRHHTtx/QuwisFVmS/8eKzccdfL2rzm0mSRBy45y544MarsPzzN/HK/TNx2L57gOd57L/7JAzq37dNr9eZjBk+BP968m7cePHZBZ/ji+/mYmEBT/JWIophBfqYsztLUuqdLTCHfZrO0MhZqnG0MIyeQ2bSV3fUr6defRuPvvhG3uNK/T68/vAd6F1VkftgoltAFlgOguEwvv91Qd7jTjziEPz1L6e3w4zsyJKEIw/cB0ceuA/WbtyMxkDr1466GhzH4a9/OR0ul4zpdz1S0Dlee/9T3HjJOQXPIRQ3BMytW5KOpXJz/Sq2FbLo8DyYtmYFAIrO0KBb1sCytVThzfEc09Nckny3cyF+9u1PuHLWfXmPE0UBz999E7YfMbQdZkV0VcgCy8H/5s2Hqua3BlPq9+G2qy5opxk1z8B+fbp1he1LzzgRxx9+UEFj3/7ki1ZdO5iowiEqlkCe0lHmdqwWooMLkXMSMI2hVrOkOES3OF4zptotLscltpwzLx5+X7kGp15xQ973GwDcNe1SHLTXru0wK6IrQwKWg0IWkY89ZHKn967qrtx5zcUo8XlzH5jGkpVrsKWu5ZGc6URVHWUe0W4tlVhausQb4Bg3w1uCdvR4qvhunWptqeI8r4ii2YI4OKakRNDYIXQbBatvbMJxF15TUPTphacdj3NOPKYdZkV0dUjAcrBiTZYk02Y46sB922EmBAD0rqrAmccfVdDY736eX/B1Q3ENJbJoD3n3DzG3lQZIDgrGWfO2dA2KrkPVGZoUyXQv6jFb48okhgWWGYZvRegGd7CiqDjlshuwvIB7bcp+e+L2qy9sh1kRxUA3+Pi3L/nkXyUZPWxwO8yESHLyUYcWNG7hshUFXzMc11DqFu1JxyUWF2J0C0SnKI700k+6UU+zKa4DssVKd7DCQoqWseaVHoXoGPlYZFx26z348od5eY/bafQIPDv7b10+ZYRoP+h/PgehAnoOkfuwfdlx1PCCEjVXrdtY8DUjakLArP27Ss3cNcTq4BTDkY6iM2iMIRhT05KZMyvSB2Mq7BYYl1GdvthjOO5/9hU8+8a7eY/r26sKbzx8O/ze/N3JRPeBBCwHhZSwEbqDX6eLU0ibmDUbc3Q/zkJM1eGXBXvrE3dvsy0KU8FrDknOaRaYoulgDAjEVEC2hHs7lJOKKHrmmpe1Er7gdgzsKBY++PwbXH/PY3mP83rceO3BWRjQQ6pNEM1D37Q5cMlS7oPSqG9oyn0Q0SqGDRyQ95imgHMVjZYQU3X4XYJ9DUwqs7kBBdXB3WwTMBVqIvO4IaoC7l6WC2TmgsU1BwGzNciUwDsmn3V95v++HGf89aa8O2lzHIenZ11vq9xC9FxIwHJQ6vPlPiiN1ibNErkpxE0biebvDk4SVnT0cSuAmhBB3gVIpYDLnIeoOBTltXVQjkDVDU9gU1QFZEsyczwzQTqq6kivPg/OvgZWjEtgm2vrcdyF0wqqbnPL5efhqIMoSIowIAHLQf8+vXIflMa/v/mhHWZCWPF5PLkPSiMWz98dnCSiaOgrWiwsdx9DTFymG0uIOwiYaFmjUcNguhF4EVY0QLKE0iuZVnt6HhiAjFqIxSZg0VgMJ156HdYW4M494w9H4PIzT2qHWRHFCglYDoYPqsl7zMv/+hiRaGZYNNF26Cw/1xMAuFzOhZRbQkzV0Vuw5IAl+3nJZkIyp2YGYkBwm9t6FBoYOACBmGYb62SBxVQHF2J6FGKRrYKdd8Md+P6X/CvbTN59Eu6/4Yp2mBFRzJCA5WDcdiPzHrOlrh73PP1iO8yGSFJIdKjP4859UDPENB1lnEWgXAnLXCpN7eIcrCiIljb2ShB6wgJTdQaVt1hgaubYiKIDSCsGnGaBCUVkgt32yDN47f1P8x43ZthgvHjPzRBFqnxH2CEBy8G47UbC783fXXXnk8+TK7EdKaRRZak///XMJFFFR5luuaYnUTBZym5F2QRMDYHjOAiJwIuYVcDimdZbRNWQsQZmi5vnisaF+Op7n2DmI8/kPa66shxvPHIHyktLch9M9DhIwHIgSxIm7z4p73GqquHky67HZ9/+1A6zIlaszb9qQ2uq9EdVHS5mtcCqwRiDbrPAcrgQtQg4mNUzwpw51imROaZmBm3Yq3Hk70btDP439zecf8MdeY9zu2S8ev9MDKnp3w6zIroDJGAt4PgpBxY0LhiO4Njzri6oNQSRne9/WZj3mNZ+EQrWJGa5EorOoPBWF2Egc5A1jB46dCDl9gux7PUQw3Ets5p9WmWOrm6BrVizHideOh2xeDyvcRzH4bFbrsXuE3Zqp5kR3QESsBZwxAF7o7qyPPeBDiiqiqtm3Y9jzrsaq9cXXgmCMPl50e/YUlef+8A0xrSixJckcPYqHHIFooqOKGeNJHRwIaZHDTKkXIhBZnFpqpniF1Nzl9kQu3AZpW2NAfzhwmtQu83BMs3B3y46C8cfXtiDI9Fz6Lqf/i6E2+XCRaed0KpzfPLf7zDxqNNw/T2PYlujw5M60WJeeuejgsbtMbHwp3m/LADhdeYOT3+oOrO7AZ1ciJwl8IBpYIylaiaGmcW9qGYmWYcVLUMAYS0OzFRIQsawLoGiqDj58uvx+8o1eY899ZgpHdJLjyh+SMBayAWn/AEDCsgJsxKNxXHv31/G9oeegBn3P4mt9c7dfYnm2VrfgGdfz7923phhg1FdUZgVDQBuUQCseV6ePtAYQ4RZ8rwcXYicTYR0XU0JWFC3BAc5jHVOZLa7FLuqBXbpLXfjy+/zL9C7764T8NCNV7fDjIjuCMWlthCf14M7p12MUy7/W6vP1RQMYfaTz+Oh5+fgtGOm4KLTTygo36wncs0dDyIUyb+Cw+H779Wq67pF3r5OJZVD1xnCVgFTm+tlxSMZcMGgpwQsoFnFLzOMPhzXMiwuW+YX0yB3wbqbD/5jDp7753t5jxs9dBBevu9WSFLxfy0tXbUWT736dodf99hDJ6OqvCz3gd2E4v+kdCDHHDwZpx4zBS+89UGbnC8SjeGJV97CU3PewZT99sD5pxyH/QuIeOwpPD3nbbz63icFjf3j1INbde1SFw9ENpk73H2ghBlCNiuqmRqYvAhoRhV5nimQEqITsI51EL+YlmmBMXAWAWOp9bSuwidff4/r7n4073G9Kivwz0fv7Dbh8t//sqCghO3Wssu47XuUgHW9x7cuzn3XX1FQJfRs6LqO9z77GkecfTkmHnkqHn/5nwiGw216jWLnmdf/hctn3lfQ2Ik7jMGOo4Zn7J+7vglXvLsYHyzOnVNWIUWNxpOAUd9Q8iOm6gi1xALjXalNTo+nrKawKpjuRabaC/XCOYyesbT2Ki1gW0TB339Yh49+r819cCv4feUa/OmqGdA0LffBaTxx23QKlyfyhgQsTzxuF+Y8OAvbjRjaLudfsnINrph5H0YdeBymzX6ooJpx3YmGpgDOu/52XDRjdkFfjAAw7bzMgIBATMVf31+Cb9c0YuZnK7ChKXtlj2rOmsRsfNGqOkNAM8UJSnMCZjo6mK7ClWgcFtMYIFgEULO7Ro1aiBaRYiyjH1gu1jVGMfWZuXjqh/W46dPlWLK18Ir82WhoCuD4i6ahMdCcGzU7L/+rsMAcomdDAlYAvasq8OEz92PiDu3X0qExEMSDz83BjlNOxFnTbsWi5ava7Vpdka31DZj9xPPYacpJeP6t9ws+z4TtR2Pq/ntn7F+0JYSwYqxL6Qz4YEl266ScTyvki4SA6S2wwCxWk84Ar5QQMFW3V6tXI5YhzIhC5C3tfFh6MeLcYfZPfb/O9ro9GmBquo7TrrwRy1avy31wM8x571O8+fHnbTcpokdAAlYg1RXl+Pi5B3HcYQe063VUVcMr76UMI0IAACAASURBVH6MXY75E06/8kYs7qZCpus6Fi5biSdfeQt/uOAajDzg/zDjgSdR31h4bzVRFPDgjKsc36sN2RNrf9mYPbXBxyzzSPQAC8c1hDTRtISYCmgOCbvWKESmWyywNAHTTLexqjNDntJKR9nchi1Qo00Be1HpUb3avoPxjPufwH/+92Orz3PZLXdjc23++X1Ez4WCOFqBx+3Cc3fNwN47j8e1dz3crhXoGWN446PP8NanX+K0Y6bgbxefXVBPrPZm49barNFXiqoirigIhsKob2zCpq11WLF2A5avXldQdGE2rjjzZEzYfrTjew1R1fZ6RV32a/uZJeXBZfTxUnVmFNwVfWYOmBYChLSq9xZXH8cUeBLJWzFVB0R7v7Akip4M17AX883Xgopr9gF8O5Tu+PG3RW1yntptjbhoxp147aHb2+R8RPeHBKwNOOfEYzB590m45Ka78OUP+ee+5IOmaXj2jXfx5sef44aLzsJfTjoWfBfKBVq2eh0uveXuzp4GDt1nd1x/4ZnNvh+I2QWsPqIgFFfhk51vCY9usQxc1QAMB15M1YyeX0kBU0OAXGEfbHEDcroKn9sQsLjGAN5aK9Fch1M1Bp5DWukoLq29Su7/dyOSsXh4//Nv8I8338fpxx7e2VMhioCu881X5IwcMhAfPHM/npg5vaAmmPnSGAjiqln345A/XUwlqtIYt91IPHfXDAhC82UqQvHMgJD1Tc1b0GLcDOJgiVYqjDEj2ViwN63MIM2F6JOTAqYDgiUIRDOvr+i6YS1ZBYsXW7DqZSfs8Ht2da6548EeH7xEtAwSsDbmlKMPw6/vvYSbLjsXlWWluQe0kv/N+w17Hn9Wm6xBdAf2nDgW7z99H0p82dd6IkqmZbIxi4AhZgZ5sIQFpjGWGYihObgiLVaUxjijLBUARWO2EPtUmD6yWGDWUHs+d4NORWuHqI12pikYwl+un2VPGSAIB0jA2gGP24Wrzj4Viz6Zg5sv/wt6V7XvWlVDUxDHnn81nnsj/xJL3YnjDjsA7zxxd4uSYTU988txWyQ9ys+CRcDgNiwwXXeIJHQSMIvdpDI0b4HpZgCIxhh4Pt1lKNoDN1qwnhVVi88CA4AvvpuLx176Z2dPg+ji0BpYO+L3enHlWafg4tNPwOsf/AePvvgG5i5Y3C7XUlUNF86YDY7ne9z6gdfjxuxrLsEZxx3R4jGKw9pQbSibgG1JbTLZEDBFZ0bFeLdVwJzyyUyhYboOt2iUg1J1BnCWMHmLdaXpyVF2wWJIi0rMgeog1B0Fx3G47M8n4sW3Pyqoe8AN9z6Gg/baFSOHDGyH2bUvpxx9GJ6YOb2zp9HtIQusA5AlCScfdSi+evUJfPbiozjxiEPgknO7f/KFMYaLZszGe5/9t83P3VU57rADMPed5/MSL8A5uCGrBRa1JDInXIgxVUdc1+1uQM3JDWkKjc4YOI6DR+KhaswesWi1wPREmSjdnrjM2RKZc5eid7I0OwKfx4MX7rkJt15xPh6+qbDivJFoDOded1vBCexE94cErIPZddwOePr267Ho4zmYdt6fCu4z1hyapuHc627Dmg2bch9cpPA8j6n774X/vPAInrtrBgb265P3OdLDywGgNtyMgDEGxJyDOFSN2deidIc8MIsbUGXGLecSeWiMpbVbMcVJYwwSz9nPx8tpYfS5LbDOWAIb1L8vPn3+YRxz8GQAwOGT98Kf/m9qQef6/pcFuOfpl9pwdkR3ggSsk+hTXYkbLjoLiz9+DXdPv7RV7e7TaWgK4tzpt7XZ+boKgwf0xWV/Pgk/v/sC5jw4C7uN37Hgczm5EBuas8DUkLm2JbjBRGONTWMMiq6nCZiTBWavxAEAJS7R2E7v95W8ZNICY2lBG8yeF5aN9CCIZAJ1e7L3zuPw5StPYOyYEbb9d1xzMYbU9CvonLc9+ix+XbysLaZHdDNIwDoZj9uF807+A3597yU88LcrUdO3d5uc96sff8bbn3zRJufqLLweN/bbbSKuu+DP+OLlx7DwozmYeeX5bdJ6Ju4gYPXNWWDWAA5XNZKWT0zVjTUmW7knB3eXxdXHc8Z1PRIPnbGM/l5JdMaMLtBamgXWzPFOhBWjdcvU0VX46+6lGFXd9lU4rJx1/FF498l70cvBq1Di8+KJmdMLylmMKwrOmT4TcSWLi5fokVAQRxdBkkScdcLROOXow/Dgc3Nw11MvIBhuXWWKWx56GkcfvF8bzbDtEAQBLlmCW5bhdrtQXVGO3lUV6FNdiSED+mH0sMHGz9DB7dYbKmmcVHsl9C914bdNwebXwKKWnCRX75TnLqYlXYjWQAwHF6LV1ZcwwUpcIgKxWJYgDma0XbFadLwMZrPYsgtYU1TFqwduQ78lpwObl+Do4edAUR+BJLbt31QUBcyedgnOPfHYrMftNWkcLj79BNz/7Ct5X2P+78sx8+FncNNl5xY6TaIbQgLWxXC7XLj63NNw0pGH4LJb78UHX3xT8LkWLV+Fr3/6BXtNGteGM8zOPjuPx4fPPtBh1ysUngOu3qMcx2oPAU2L8et2M3DeZyLCigavlBYcYRUwd2/DcoLholN0ljuIwyI0WsLp4ZeFTOstrZ2KS+DtUY2CGyy9Q3MW/PEVKJl7bMr9yS1/EqJcDky4M+u4fHn05mk4+ahDW3TsjZecjU++/g4Ll67M+zr3PvMyDp+8Z6tcx0T3glyIXZSafn3w+sO3497rL2/VE/NL71CbCieOGOnFsYvGAL8/BGz6FGO3PYb+pS7UOYXSWwXM0zcVAKLqDhZYRsV4OAZxeGXBiBDknYM4GGC4ENMtsDyCMvwbXsnIS+MWzQYaF7b8JC0gH7e3S5bx9KwbIEtS7oPTSAYohSPZW98QPQcSsC7OuScei9cevr1gEfv3Nz+08Yy6B0dV/Gzf4R+OurCCeic3YtxSyFeuTIWmazoz8rKaCcQw91kFzHAneqWEgFmjEK0h8wxG40urRSe4oXO53JUmXN33zm9s/jzruPZm7JgRmH7+GQWNXbZ6HW6497G2nRBRtJCAFQEH77UrHrt1WkFj127cjFXrNrTxjLoB6etH/Q5FTNWxzSmQwxLEoUmVsKZWKRlh9C0LNPCIfGYUoqXyvI6kC9FiQQlusDwEDIGl5vawP5vb9Z1fduyKs07G7gW6Ah9/+U189u1PbTwjohghASsSTjziEBx/+EEFjV28fHUbz6YbULaT7WXIa7RdaYg6CZiZAxbmK1NrYDpDYg0sRxi9RaS4REi9zyU61Do0j+M5QBa5tDUwD7Rmgj4y0BUgtMp8XXOMuR3o/JB0QRDwxG3T4fN4ch+cBmMM510/C03B9ukuTRQPJGBFxMwrziuogseyNWvbYTZFjsten1KUfACaCaWP1aU2Q1x5qkCuoulQtbQ8MKeGlhaRYomIxDK3g0vYUtuQ5zgHC8wDe/JylgWx4CrTyvQMAEq3M98LdY0HmuGDanDbVRcUNHbdpi24+vauHyxEtC8kYEXEgL69sf/uk/Iet6V2WzvMpsixiBIAuGLrAGQ2ujSONV2Ijaw8VV9Q0ZlR6SJXbpbF1acww4LySUJCfqwdlk2h4wC4JN7WpRmiB3ozx2cQtoiUfxgWBS09yiLr7OttncjZfzwaB++9W0FjX3jrgx5VNo3IhASsyJi6/155j2nrTsfdgsh6++vgcgBG7lQGihnE0aiXGK4/WOsM5rCKLK4+FYaAmYnM1lvQHCvwHNwCb+8vJnigwyqWWUQoYo2c7If5tSrgTpTcYnrm79+JPHrLNQW3Hrpoxl2o3daQ+0CiW0ICVmQMH5x/FYpINEufq55KOF3AVgAAAjEHC8oShdike402Jxa0nBaY+fePJwSsxOXgQrTEyPMc4BMUpESNlwBegm5N3cyyBsbiFgvTVYXFW0OAb7C5L7Sm2bEdTb9e1bjvhisKGrulrh6X3tz5HcCJzoEErMjoW12V9xi3q+0r3xc7eihtXTCwFF5JQFPMKYzedMFuU0scGi1mqY7BdHsiMzPErsSVFD1n640B8AsWy1n0G+M5a9J0lnyomKV9iVyJpbVhwDvI3NeFBAwA/nDYAQUHKb31yRd45d2P23hGRDFAAlZkhKP5J3H6ve1bA68Y4SNpAhZcif6lrkwLTIubgRScgG2KK7UG1qKkYls1eSlVHd4rCVmL+TIG+HmL5SwaQSYq59zBOR1ODaa2FaEEm4MxwNPfPCDa9boV3Hvd5ejfp1dBY6+87T5s2Lw194FEt4IErMjYXJt/Y8De1RW5D+ppBFelvV6OAWUuhOJpAqY0mdtSKYKKntEkkmVbl7JaSbwbyRrCpW6HMHqLmIk8Bx9vGZuwwOJwW86dZW3TYjVGuRIEYho0l6VihrW6SBehoqwEj958DbgWdJpOp6EpiAtubNsSWUTXhwSsyJj/+/K8x4wYVHwdbdsTTWf2HCnAsMD8soOANZrbUpnt/aSMaVyWdSmryIielPh5JAFukbe7HC3nEXkOpZxFPGXjIUThLAKmmFZWBjYBKwMAhPhq8/0uKGAAcNBeu+KcPx5d0NhP/vsdnp7zdhvPiOjKkIAVGW9/8mXeY8YMH5z7oB6EpulAeJ19pxrAMH8QUTXNwlID5rZUgrCipVatHO2EdL9iWh6XZnnfl140OA0/Z7220aIkBos7WMuSyGuxHNVE/7ImzpL7Ft2S9dqdycwrL8DIIYU9dE2/6xGsXEuVZ3oKJGBFxNz5izF3weK8xtT07Y0hNf1zH9iD0KNb7PlVCWpE40s9olisIquVI/oRUfSUGzDp6bK5EKHjyncX460Fm41gD1sYvNcmjpnJzAwbm2LYEjTWtnywXFs2rKgYk828M11xTpwGbJajLhhjt+lWAeuaFhhg9IF78rbrIAjZBd6JYDiCv1x/G3Q9e6V+ontAApaFWx/6O1565yMoSucnfeq6jksKCBfef/ed22E2xQ0XXuW4vy9nBDaErW5EqwUmltjfSx7CWStxRLG0Low7v1iFK95dAiVuFUCvJXcMKHGLtioemhbDCS/9gj++9CuW1YXhZtb1N8MCi2ssFdBhXLwZN6KtALExtlYrM/fFunbAwy5jt8dVZ59S0Nivf/oVDzz3ahvPiOiKkIBl4bffl+Gc6TOx3aEn4NaH/t6pRXGvmnU/5i1ckve4E6YWFprcneHDzqW1qpixP2y1wKwCIfkRVjQoiad7PmGCabDngQmJ/d+tbcSWBkvQjehL1VEEjHUwCLJlaByazhBTdczfHIRbt1RQSZS+ius6kHAJZszPimKO5VzlkAUOtZqlU3J0awvDKDuPa887A+O3H1XQ2JsffBoLl+Xfc4woLkjAWsDGLbWY9diz2HHKSZjy50vx9Jy3C4oGLIS4ouCyW+7B4y+/mffYQf37FlR6qrsjRNc57hfDK1HtlRBWLO4nBxdiTDXeT7oQeWv1DY63VatnNheiXcD8sgDrLchZzjO80gPeloxsBGAoGgMkS9UKa5Rk6qIsLXqyHGVuEVujUqKeIowQfKt12QWRJBFPzbq+oDzGWDyOc6bPhKp2vveEaD9IwPKAMYYvf5iHS26+GyMO+D8c8qeLMPvJFzB3/uJ28bl/9cPP2OMPZ+LJV98qaPyVZ51SUEhyd4e3FrPtva+53bQEA8vddjdhWhh9KK6lBCppgTFbfUJmrckLF7MEWkglNgHzyYKtgK+1ncpOfUtskYSQExaYpucWMC1sRkMKbkiSByUuEduiKuCy5Fl14UCOJNsNH4IbLzmnoLE/L/wddzz+jzaeEdGVKLzVbw9H13V8/dOv+PqnXzHj/idQUVqCXcftgF3H7YCdd9oOO4wchn69q3OfKI3V6zfi7U+/xKvvfYKfF/5e8PxGDK7BGX+YWvD4bo210G3fQ4AticjO4DIMLHMjoloFzLKWJJUhpGhQElEcQkJ7kvUNAQC6YuRwyQJCcQ0eZo0kLLVF2XslwRY6L1hyyFRdN9x8SZIWmNoCAbOuf0nl8MoCyt0itkVUwN0LCCeqcMRqgZIRmeO7GBeffgI++PwbfPnDvLzH3vnk85iy356YuOOYdphZ8yxdtRZPvdp5If3HHjoZVeVluQ8sckjA2ohtTQF89NW3+Oirb1P7Sv0+jBo6CAP69ELfXlXoVVkBj9sFj9sFTdMRDIURDEfQ0BTAkpWrseD3FdjW1Hq3Ds/zeOTmayAW2MW522NNYu69n5FAzIzQ+sE1DFGbC9EUCEUoMdaokgKWqIloC+LQo5AFHjVlLizZGoYLVgusFJxFwHyyAB2C6QZhGgQO0Fgix8waaOE2kpAVnQGS5YspnlnIVlOC5qqc6IVX4lHmkbAlGAcqLQ9VaRX5uyocx+Hxmddit//7c949wFRVwznTZ+Lr156C2+XKPaCN+P6XBfj+lwUddr10dhm3PQkY0TqagiH8+Nsi/Pjbog697pVnnYK9Jo3r0GsWFWGzDqDiHQrJNwwIGk0eR7vXY51qCZKwhKNHOWN/TDXcgJKQkB5mdyHyAHr5ZCyrDUPSzDU0JvrBWdyNPlmArsimgOlxiAIPTdUh8zwQt9czBBJrYLLli8maaJ1AjYctAuYDx3Eod4tYURdOJUQDsLsouziD+vfFndMuwXnXz8p77OIVqzHjgSdx+9UXtcPMiM6E1sC6GcceMhl/u/iszp5G10VpMr+4eRfWxsqA0tGptwfwaxFpxgKLwijnlAziEBMWmJ5WzNcj8yh1iSh1i4AlECMqVEAU7AJmq2Svq6kIRlnk7QV5E1GIGmM5RUi1Bo7whtVR4ZHQGFVTQmj8IsVhgSU57ZgpOPKAfQoa+/Dzr+O/P/7cxjMiOhsSsG7EIfvshqdvvx48T/+tzZJomwIA8A/F1rAK+IemdlXoGxBTnYM4IkgU1NWTFpghNootDyyCElmARxJQ7pZs61hBVMAlmv83ZW7RFnloBHQYr0UWN6MEOQFMNNa9eI6DKloFzCEaNm4NPDGstQqPiEBMBVyWbgZOY7s4D864Gr0q86/tqes6/nL9LATDmQnsRPFC33TdhNOPPRyvPTgLLplap2TFGoHoG4JwXLf1yZIjq+2Rm4q5JhliyQTihIAlLLAI85jHq0GUuEW4RR6VXslW8aIRFUbgRoJyjwQ+rRZislq9ELdUynD1gppwU7pEHlHeEsThYIEJijV60fiyr/AalfBjtrHF1wiyV2U5HppxVUFjV63biGtnP9zGMyI6ExKwIsfrceOBv12JR2+ZRkEbLcEawOEbDI5jgM+0wBBaZbOSrBZYMCFgyTB6MbEGFtD95vHxBpS5JbglHpUeu4DV6dVGAd8EpRlNLU1rTIxuNHd7B6QqeLhFHgHOEogRsRyXgNOsRYANC6zSY0RKRjhLMnO8uFyISY44YB+cdszhBY39+2v/sgVaEcUNCVgRM3n3Sfjmtadx1gmFVe/ukSSCNQBA8QyBSxBsLkQElxn5WUCilqHVAvOY+wG4Ei7EALMU2FUDKHU5W2Bb1HKbgJW4hLQyVDHIiXNKcYswuful3JZukUetbsnliqyHqumY8+smvLNwC3TGIKj25GsAqPYZ1wlzFrFVunYiczZmX3sJBvXvW9DYC2+8E9sai/d3J0xIwLIwe9oluPzMk7pcOOrYMSPx2kOz8N5T9xZctbvHYrHA6oWBRqBF6WikassHlqHSpWPB5iD+/uN6WzHesG4ERMS0pJgYQteg2i2w0oQLsb9XMaMEeRnroz74XKYLURJ4KJxV/IJGeSkAkrVaiG+QkcAMo/zUetXS1yu0Bp+tqMd9/12N2z9fiWd+XA9Rs+aeGZ/d3n5DwCJpYluslPi8eGLm9ILWezduqcXlM+9th1kRHQ0JWBYG9e+LW684H8s++yfmPHgbTph6ECpKS3IPbAfcLhnHHLwf3v/7ffjf60/j8Ml7dco8ip6g2U9tgz4A5W7RKI7rrTF2Mg2VbAPOeWOBURPRUrU+rBkClqym4ZGM26detYiC0gi/BLhEAQMlS6ULbw22hNSU6CWJ2SyiJvhlAT5ZgBAxBUz11Fj6iPFG5GQyATpejy2NpsvwlZ832SwrXTDcnrLAo8IjIsjsYlvM7LPLeFx42nEFjX3t/U/xz48+a+MZER0NLZq0AFmSMHX/vTF1/72haRp+mr8YX3w3Fz/8thA/zV+MTVvbZy1hYL8+2Hvn8Thkn91w+OQ94fd6cw9qQ8pK/Jh+/hl5jRk0oF/7TKYt0FWbC3F5bABGJdaG4B8KJIr8lqlrAfRBiQRATSbOcmhKCFiyGlQyICOqcYDgTnVf9vJxKLwP/ZnFDegbio1NMfv6GoAIZw/I8MsCxFIXEDKjJRv4AangDq8koC6sAu4+QGQ9AKC/ZAZtlHtEIGYKpy5XpZ5SKz1Syg0KWH+34uWmS8/Fp1//gEUFFO697JZ7sOeksehbXZX7YKJLQgKWJ4IgpEpGJdla34AlK1Zh6aq1WLNhEzZsqcXGLbWob2hCYyCIpmAQkWgciqpC1YyoM5cswSVL8Ljd6FVZgT7VlejXqwqjhg7GmGGDsdPo4ajp16ezfk0AQHlpCa678MxOnUObEl5r1gh098HqkARvwoqC14xELNfWAeiDatHiYpMr0BgzVCQZUOFNrJUFYprR7kQz2rGU8U3YxvtQzSzdC3yDsHl9LGW1JbFHFNaj1C2iWuCBwNLU7g16DaoTqumVBNSGFcDTLyVgfcR6AMZ5evllIGJeV/cMSG1X+2QENUuOm4ML8YmZ0/HEzOkZ+7sqLlnGj289167X2HfXCQjNz7+RLNH+kIC1Ab0qy9Grcjz23nl8Z0+FyEbAtL5QMgINESUVMq+XjExZKu7wUpS4dkW5YG0oWYGmmL2yedICa4wqRq3CqCFg5VwDotIAeOvNCiyqbxS2hOK2MHoAaLJGFIbXoXcvF6rcOrDCdHUui/dHZdICk3nUheNAb9PSreRqkRSwUpdoS1DmXeb5e/tlhG3dpi3dogmiCCEBI4oanTH8uK4JcU3HhP6lqQhCRyzrX/CPQKTezMGK+8fAnXzR8BuGV3lRwllcgFIZQmnNLJPX2hyMA9VDgMb5AICh4jp4K3cBFv6QOnaDMBo6Q4aA1bHeAC8ZlmFsK84cX4ay2FJgWSwxz2FY1CBhXKL6h1cSUBdSALcZgVeq1wIYZmy7RaDRTFAWPKaAVftkRKwCpjUvYMvrwnj8u7VYWR/BkAoPLthjIIZWdqwLmyByQQJGFC2KpuOaD37Ht2uMSL8+fhmPHrs9+pY0U7TVYoFpvuHgLIUoAt6xpoDVfY+xNR5UCvaGko0NhgWWLAeVFLBV9RFgxA7AhneNY785CX2SogQAHI95sTEAmkyXZYLGOAP8w4GmxQCAyncrbe+janfMXx1EfEczCnFbRIHu7peyGL3KWnilPRBWNJTKgq0EFWcpO1XllVAb1AFOAJhm9ATT4rammgCwNRjHhW8tSlmc65ti+GVjAM8cvyMGlLlBEF0FikIkipY5v25CMKbhrEl9cNLYPmAAHvvWudsyAKDJ7GhdLw5Bhcf84m4SBgDJ9SI1gD3LVqOCWapheAdiazBuO51L5OEWeURUHStd+9res/VN6XMAPl1j1E5MD+LYEogDvZqv71dbdSRWN0ShJqI4BJ6DKPColSydiht+xbBKIzijxhM2IycFt631SrVPQlhlaR2dM9fBnp+3IcNdGoxr+MfczutIThBOkIARRYnOGCqFJjzRewbOWjECF28cj9fG/QsxRUNU0ZwHNZjFXFfpw1DtM/t4NcY0W3PLscI8+DV7O5P6iCFKmsUNV5LI63psxXCg5pjMa/IyVg64GvM2NMEj8RkNRqOqjnmlZ9lbpCTpexCe2mB01LY4/uCTBKzULMnXjQtTAra9a5W5v3SMrWFmtVdGUzStHqIl0Tr5u3261FhDqylz4eYDazB1dBUEDvhwSS3qwwoIoqtALkSiKNnYEMCUTWcBtd8YO5RGSAtuxE07yVi09UKM65+WrxfdCoQTuVWCGz8H+xsRewnCio5QxV7wrX7Z2DH3Cvtwz0jEE1aQVYKMNS0FX61uwN+G345Tx52LQaUC3HX/AaJbsLDiLEz71gOdKfCImetzLpHH9P+JuH6PbzBB+xRuiQevNCIoD8KHoX3xzv+MwBBrJ2e/S8Bv4X7YTfAa1lZ4Lc7fS0WJux9GwZLbVG5vqdPLL2NzMAb4a8z1wPB6oGz71DFLa8NoiKrYtaYUdw16GeK8O3CQfzj23udlXPtlFJ8srcMfxxVWAYMg2hoSMKIo6bv2XlO8LMjzb0D13lMApPVDq//J3C4fiyV1cWzXt9x2yLfqPjiwmeuFXTXmC4tV47dU1vh0eQM+XV6J43bqg+N22geXvbMYm4JxAIbVkh5CDxgC1hhVcfVnAQC7GacHsPugckQteVqaRcB8soAf1odxdu99gY0fAgDK/r0jLpTKgJW1qeMilfvCkvWFSo+EhogC9Dart6iBFXi3fgsGV7gxoX8p5m1ogk8WcOvI/0Kcd4txUNMi7Lf5Chww7FF8uowEjOg6kAuRKDq0wGoIi+4wd4y9BagyvvzBVAxYZXzxMsbw6i8bMeuz5WBbvzKPr9oVi7YE0ctnWmAcgJd/58GG/inzgq4qrOZ2TL3ULS7E9KhCABA4DjzHJcTLxCp2SWSBy9jHAMRUDdaAQd4imuVuEQs3B9HQ7xTzAF0BYqZ4QfRjqfsA+7x4DhLPQfcNMw8LrcCDX6/GhW8twvNzN+DXjQGcN9EH/8Lr7JPa/B9cOGQhFm4OYmMgljFngugMSMCIokP45WozBLxiAth206BOfMA8YO0b0Ot+xNsLt+D+r9egKaaB2/hR6u2tvj2xLaLa1sAYgIVbQrg9PA3q2Dugb38donu9g22TXsYvYz/H3M3WVSgTJwETeQ6ZsgSUuaWMfYrmfN6wotvW2kSLgFV4jNYod63aBRj4h8zBvITA2IewIdmKwwAAIABJREFUcFtmNGZNuQd10khzR+3XKXfr49+txbqmKI7VHgJiWzPG9lt7FyYPq8B/lhVnFXui+0EuRKK42PwFsOa11MvGHe5GmSBC7LUrMOj41Hv8vKux04gH8PS+DdhO/gn4MeFC5ER8FZkIiW9EhccUlKSF868ljfho2WTIAo9gIu9ru97AxAFmBQuet3RVdrKqRB4CnylhJQ7HhpoJOIkoGsot81Nta2DGbfufFQ24dsitOHv8GahiG+DrtRNWbd2G+dFBeP4HBYePzjz38CovvlcmYCoSzTO3fo3bDmzEv2t8WNDow+mDVoH/9jFzwIS7gV+mGRbe1q9x6aT5uO63UThlQn/HeRNER0ICRnQt9EQBXTUEaBEosQAikUZwyjZ41K0Q599oHjv4JGhVZlHjtTVXY+Ca1wEwYMvnGL5lbOb5BxyBD1eqGFjutrnlrK68uMYQ18wv/20RBXHVFDCXYHXnZVpVgNmt2UpJRv8vIBhzFrCQohntWBLoaWtgSb5Y1YgvVvUC0Av/PG08/vTFzwBCqXmnM7DMjU+WSphatStQ9x0AwP3v3TEVwNTS0cD3qwGW+F37HgKMudzoYr3UaATZe+n12KH3O5jz6yaUyAJcIo/hVV7UlLkdRZsg2hMSMALQNehaFFq8CXq0DpoSANQIODUE6FHwWgScHgGnK+CYBo7FwTEFYCp4PZ4SGyMxNmZsa1HL6yjAFOMpXjfGQVeNf5luJNUyLXEO+7qRlPjJQCrDb32vx06WdawlylAMGH4O+OVPOP+evAuL+lyF+fOD2H+4PWFYFpr3pm+LqIhaBcySy1XuybyFmvsaz2xgCQTS8q2ShOOaLXTe6pS0rt1ZSc8xCziI49BKD75b24DGyRehLCFgKSx5cpDKgN2eNAJWdrwBWPkPI2esaREurHkO16w5Bd+taUzN0Svx6FPiApgxROQ5lLhElHtElLpE+GUBXllAiUuETxbgEnj4XQK8kpD61yMJ8Ei87cGiQ2As8VlNfG61qLGtNBk/yc+3FjOPU8Pm5zX5+U396ABYoupz4i/E8TA+GZyxzQnmDy8CnJT4VzQqs/BS4n0R4GUjp4+Xjc4JohcQvEaOn+g33hNcAO8yjrH8/XTGEFN1KBpDOK4hrGiIqjriqg5FZ4hrOqKqDlXXUe6SsNvgcoc/UNel+wtYYBm01W9AFzxgggeMk6ELLoD3gaU+CCXg5VLwghe85IEgyOB40fZB6FSYDl0NQ4sHoMUawdRQ4maKA3ocnB4HpwbBq40Q1AbwahMQbwS0kHkzqhHjC0gNAkrQ+FcLJ8RFA48iWhDlXagd/xz8FUNsuweWe3DHmivw1+2rIax6AYAOuPsZXYlFP1b3vRDXfOMBoGBUtb0sUvqXv5WYqqM2ZFozHsu6l5NVxXF2wTGPzXQhhpt1Ieq2YBHrR7GXz9nqK0kro5WejAwAg8vdiGsM1y6YgNnjH4Fv9ZNG8Ed0k5l87a1BbPeX4fINMl57+gA7Xgf8PA0AIC28Fff0nwt1n70QEqoQRBma9ArU6eWoVUsR1N2I6QJUxkHTGTSdIaYxRMIKtgbj0GEE2CR/PQ4Ax3EQOCPQxCXy8MsCPCIPn6jAJ2hwCSrcnAZZ0OHmFLgQhcxFIOkRiCwCUY+CZ3HwegS8GgCvhYzPtxI0H66UJuNzr4aMVjJqIPF+OOPvVLRwPMC7AckPCD7wUgk8oh8e0Y9S0SJ6UhlUwY8470cMXlR43cD6j4DBz3f2b5AX3V/AGhdA+HUaslTIax7BazzxCO7EU4/HeMoRPIknHtl8UgJvPEGBT3zbJNYYUk9hzHw6Y5phfWjxlAgZ1kliWw0Z4qMmBUZNCYzzV1d3gjOfMAWP8feXSoxq73IF4OmP5eV/xGZhFPZMq803osqLz1cF8L91f8BuA88Ez3Go9smIazp+WNuI3+eHkQxp33WgPXE4aw1FAOsao47HOomSpjM4GXROYpdugblFHlFVNyIRLZXjrQEdVtdiElkwKnRYaYpmCpgo8OhX4sLPm4I4qnZnnDHpKJw2aQBC4QZsXGlEav67cQx20/rAVpp6zJXAxo+Bzf8xXm94H+KG91EGoAzAADjAiaZVYbU4OD5hkSTny+z3ha4agpNmjRMtgOmJB9PcoiwmflJ3UU3xdXbv/gKmtuLpqoUfhOKHM8RY8gNypVFqSPQlxNtligkvWVwaMsBJYLwEnfdCT4i7zrvAEtuMd4HxckL0XWCcCI6TACHpHpHA8Tw4TgB4ARzvBuPd4HjjAYBPPJGnu5SGJ37SEXgOR2/fGy/M24j3FteCA/DQMdtB0xlemmcW5t2lphRjevlsY50ErNonpSyvtVYBs1hgTm5BTWeOFpg1aCRJOK7bXvtlIeWutK6PWf8GTi5Ep3lYBdDKPUeMxtXvL0F9WMHIxN/B5y3HfctGYO76JpS5m3Dc+MH2QbwI7Ps28MN5wKoXHc+bAVMBzdlF2uXgZcuDqRsQPYBYalgskt/Yl3TTJR6sdMEFHTIYx0OHAAYeOieCgQdL/P8z8OAMm9OwNBkDoIOHBi75L9PAQwHPtIRrXTFd7LpqCLkWTTzcJixKNWS6N/Wk2zNmjCkUsXOa9baG7i9gpaOMp0ctYvdjq6GEpRM23G3JD0bygwLn8OZOI2mNiCWJGyppAcrGjSX6ElZKOXSpDLpQCk3wgfEu6LwXTHBBF/xgUgk4wQvIZRAlHwTBDUGUwPOZZY5aAgdASPx0Bc7apQZxjWFFfRjH79QXE/obtQDvmjoa/15eh90GluOA4ZUZv2u6AMgCh4n9S/Hx0syQceu6V6k78xZyS4JjQIPTeplThfvaRLmmBosFZT1dhUeCyHOpLs0AUOGVEElzR25ocs7XGlzhwasnj0NU1W3u0IeO3g5bg3GUuAS4HdIDIPmBPV8w1sQ2fgKEVhrux1i90UQzuhWI1yVcdm1UcoqXEuJhPDCBE8yHKtGbWAPyJH7cifvED0glUDkP4rwXCueGymRE4EUYPsSYCwHdjwbdh5DmRkBzIaZzibUiHXFNR0zVEYprCIU1RBRjX1xjUBJrRsa6Udt+R8g8B59LgF8WUeLi4ZYSa4MiD58soNQtocRv7PMlOnd7ZeN1si6nm9cgcXEIWgiiHk64U8OG2CXX9dRgwoUaTLhRA8Z71bu36e/TEXR/AaucZPzkAWMMTNOgKmFoahBMjSTWnaKpoAROj4LT4wAzAhsA3fiXOT31cgDHgSXdJpwAxolgnAzGu1KLtoyTEpaQD7zoBy95wYte8IIMgedaLDBJ50z3/8/NxCXyuGzvwRn79xhcjj2yLFCnC06FR8LgCk/GcV6Jt1VkL3cQMK/EQ3QQsGoHyylddCq8ElY3GNaeVdysQSYCz2FElReLt5qVOvr4ZZubETDW7qKK5ihGHMfZxCuJtbxWs5SONn6ywZgZsMPURPX7RJAD9ITLUE9OBsn7IuVyTLroucJXZpMusiRJ8YkoGspUHdWqIVSqzqBqDIrOoOo6dN0IflB1Bo0xMJZYBGBA5oMtl1jzNH54noOY8BrwHCAJPCSeA88bCe5JoZEEI9VC5Dm4BB5uic8aSJQfXgDFFYxRKD3xOy4nHMeBE0XIYimSjQKJ7o9fFlK5Xzv1LcGkAaV40vI+zwGX7T3Y9kVT6eAWdIlCRvwPB2cXYjxNdJzOBwDutDJUO/b12wRsnyEV8LtEnD6xv61q/PqmGIZXdUIfL45LtGlpgSB2EJJgCIfTWiRRnND/JEEkuOngEbjyvSUQOODUif0wqtqHqWN64b3FW1HuFnHTwSOwS1rwhyjwqPJKqLNUaec442nbSplHzLDKGGMZVpOTlQYgw1o6dUI/bA3GIQocjtyudyoo5bzdB6LCI+H7tQ0YVuVNVakniO4ICRhBJNhjcDnmnDIOEs8ZOU0Apk0eimN36I3BFZ5mIxX7l7psAsbDwSXpkPDsFObub+YavjQB6+13YdaUUY7H/nFcXyq4S/QISMAIwkJNWsdhgeewfR9/1jFVaWHtTmHuXjlzfcMpUtGptqKxv2iy9Aiiw6C7giBaSf9Su+glgz9GWtaeduiTGaJc6hZxwR4DbftGVmeuVw0qd2fkeBEEQQJGEK1m6phqJEsfThxQmrLiThzfF26Rx7h+JThrF8dUX5w6oT/u+f/2zjw+iiJ74N85e6ZnkkC4QVE8uAwSkCPcoHKJgIqw3sixosAiqKyssOu1LsqKrIsL6uLqT0FWRUARWFAOBQUFAZEbEiCc4cg1R/ccPf37oydNhoTVsJIQrO/nwyc93W+Gel1V7716XV11ayOuq+VheOt6NK+blJCqTK+bxMt9fmLGn0DwK8Wi6/pF9sKTQFD5+PpAHj8c8zGwWe2EqehRLVbm0dPaA3ks2XWSjldWpXej6uf1fp5A8GtAODCBQCAQVEpEClEgEAgElRLhwAQCgUBQKREOTCAQCASVEuHABAKBQFApEQ5MIBAIBJUSsRLHrxhN01BDYUKRCKFwmKCikl/gwxcMoighAopCKBxBDYVQQiGiUY2ophGJRAmFI0SiUULhMOFwhKhmXAtHokQiETQtZshGo2hajJgeM1b5L2ULCovFgsVqwRbf0sVms2Kz2rDZrNhtNmxWKw6HA7dLwiU5kZxOJKcDtyThckm4nE6cTgcet4uU5CSqJntJ9nqRXRKSJJHkceOSpAq4w5cWmqZR6A9S6PfjDyqoqtEu1FCYUDgc/2u0pYCiEAgqBIIqQVVFUQ25SMRoN+FIlKimEYvFjIXr9Rh6TKe0SdGW+HLvVqsVm9Vqtg+nw47D4cBusyE5HbgkJy5JwuN2IUlOZJeLJK8Hr+xGdrvwym48shvZdebY7ZJw2O3iVYVKyiU5jf6Jya+yfU8WDoc93njduF1O3C6X0dCdTmS3G6/sxu2WSPZ4SPJ6cEtOpLiBdNjtyC4J2e1Gdks4HY5ybeSxWIygqsY7fRRFDRFQVHyBAAFFJRKJEI5EiEQ0QhHD+RT4AhT4fBT6AhQGggSCQdRQ2DQwgaCCLxBEUUP4AkEi0fPf/M5qteKw25GcDpxOw4jYbTacDgdOhx2rzYrdZsdht2Gz2bBajO1grPFtYSxY0DEMlq4b+moxw8lpmnGsaZrxLxYjHImgqGHUUIhwJEI4EiUWK33DxtJw2O24JKNeJclp1L3LhVty4nJJSE4HksM4TvF6SPLKuJxS3BAajtPhcBj6xp2p7HKZRtMwhDYkyYnLKcWNq71CjKMWDxwUNYyiqka78Rvtxh8IUuD3o6ihYk4njC8QpMDnJxBUCUciRjBTaAQzgaBCXoGPQn/gp//zs3DY7cjuovvkxOlwYLfbcTrs2G02cx86q8USP8ZsHwA6OrG4YytqI0Xto6gPRDXNcJyhsOlQy1pGwxa4cDmduFxOUrxekrwySbKM7HYjOR0kJ3lI9niMOpacyG4XSbKMR3aTkuQlyWMc2+1GP5Dj9sZqLb9El67rBBUVJRRCUUMU+Pxm8GDUd4hg/LM/YNRt0T0z7EmUBpfXZeyQu8utzP8Ll+QIzGKxENU0gqrK0ZyTBBQjAlRUlXAkSjhS9s32rFar0QmdzjNRf7EI0Gq1GKOF+HHxDljcSMfiHbFoJGNEo5H4sUYkEiEYNy7ng+R0kuz1mJ3JJTlxSxJySjL169bGK8vIbgmvLON2STjjDt3pcCC7XaSmJBtRqlsyO67sMiLaM07Kjt1esU1H1/W4UzNGAeFwhICiUlDoJ7/QR2EggKIY1/xBBZ8/gBo2RgBqyHD4QVU1OrMaotAXIBQJo6phCgMBCn2B82onZ2OxWAyjbbNht9twOOy44gFSkaGTnE5sNitWiwWbzZZgxM/VfiJRo+1E4u25KFAJKup5BSaS00lKkhfZLSE5HMhuNynJXmpWS8Uju6makkRqSjJJXg8pSV688bblkiSzXxjBnzEylt1uPLILp6P07WEuJFrcoSmhED5/AH/QGA0W/Q2qKkFFxR9UDAcfVAkoStzwhwmFQhT4A5zKLWD/oaMEFJVwOEyBL3Be97bIiUtOZzyD4MDhsGOz2sx2UVT3Z9uOWExPqPezgzsjCxJBDYcJhcIEFLVMgR0YbU1yGu3Q6XDQvmWzMutYUVySI7CfIhaLEVCMRqsoIQr8fnz+IEooRCgeqUSimhm9qmrISIPErytq2DSGRRFgLKYbf7VYiTRIUQRusVqwWqyms3M47DgdDhz2M9G602HH7XLhcbvMEWNRxO+RXSR5PMgul+k8nfHfMKJAD5LTed4RfywW47V3P8IXDBIKhXlu3Ij/+V5fTOi6zs7MA7gkJx63m1rVU/+rfCwWMw2hqhojv1DYGP2pISPFajiOEIoaNoxJyGgb4UiEaNy4hCMRIlENLaoZziZsyGpRLZ6+jaBpmmGktJhZ1uJY4iPXovbjsJ9pLw6HwwxU3G4JtySZ52SXhEd2k+QxRhLJHpnkJG882yCdMagXeRotGo1SvVUPbDYrDruD498uLfcyFA+aQmFjlOoLBPEHg/GsR4BgUDWD0qAaIhw22oOihFDjI95wOEw4EkWLGWn3aPRM3ZdmO4rbjbPT6/Z4ZqEogPC4XXg9MrLLheySjLp2SQlp96JUvNcj45Xd/5PNqGh+lQ7sfNFiMXZnHYw/e3FSp0b1ii7SL0ogqFCzTU/AiMhzN31RwSX6ZbmU9YvFYmzfm2Ua106t0yu6SL8ol3LdgeEcK6sTqUguyRTiheLI8RO0vm0wAHVr1WDvio8ruES/LKfzC8zjalVT/otk5eRS1u/w8RNkDBgKiLZZGTl0LIcmPQYBl2b9XSjENPoyEAqfeSbicl48W6X/Ugj9Ki+Xsm4g9BOUjnBgZcAfDJrHHvnS26pd6Fd5uZR1A6GfoHSEAysD0ahmHjsqeBbehUDoV3m5lHUDoZ+gdIQDKwPF57vYLsEdcoV+lZdLWTcQ+glKR7j6MlCvVg0mjRpKLBajTs1LawYiCP0qM5eybiD0E5SOmEYvEAgEgkqJGKsKBAKBoFIiHJhAIBAIKiXiGRjw4ZIvmPPJf9h/6Ag2m40mV1/JuKH30Pr6pqXKL1n9NbM++IR+N3XmwTtvTbj26RdfMe3tuZzKzadnpwx+P+IBalarWh5qnJNnXv0nazdu4UjOSVKSvGSkpzH+t/dRr3ZNU+axF6axaftuck7lklolmc6tW/D48HupXrWKKaOGQsycM5/ZC5dgsVoZfEcfRtx9e4Wsd1fEydx8/vjK62zdvZe8Ah+1a1SjT7cOjLpvIG6XsQL99r1Z/OujT1m3+Ud8/iANLq/LI/cMoHfX9gm/dezkKV6c+X+s+GYDtWtU4/Fh95aQKW+++2E7f3t7LruzDhIKR7jisjoMvbMvd/TsZq7ckHMql6Wrv2HT9l0cPn6C+27rzR09u5X4rU3bdvHCjLfZlXWA5o2vZeKooVx37VXlrVICH/9nJe8tXEpW9mGsViuNr7qSsUPuIqNF4np8X363iZfeeJfsI8dp17IZE0cO4crL6ibILF61llfeep8Tp/O4uUNrnnx4MLWrVytPdRIo8Pl5c+4CVq7byMGjx6hdvRq3nNU2wXiJ+eV/zmbluo14ZDfDB/XnwQF9EtYbDSoq/3jvI+YuWobdbmfYoH4MG9ivwtckrWjECAzDAHRp25LJ40fxx9HDCEei3PzAKHZnHSwhezq/gDHPTWX9lm3s2n8g4dr7ny5j8Phnub1HV/7+9BNs2r6LW4aNJRI5/1XffwnyC338pk93pk0ax8j77mTNhs30GvIo0WILk/oCQQbf0Ydpk8Yx9M6+LPz8S+4cNSFhdtSY56Yyc848Jo0exoQRDzDtX+/z+xenV4RKJoFgELfLyej7BzFt4jj639yZV956n8demGbKzF20jEPHchhx1+1MHj+SK+vV4c7RE5i/bJUpo4ZC9HpwDDsz9/Pas+O5pVsH7ho7kQXLV1eAVmc4cTqXRlddwaTRw3jpydE0vaYBDzzxDB8s/tyUWbV+I1P++S6n8wv4asNm9h8+WuJ3tu3J5OYHRlO/bi3efOEp3C4XN903koNHjpWnOiXIOZVLx1bN+csTI3l6zG8B6PHgGLbvzTJlVq3/nluHP0ZGehozn5/A6bwCbrp/FHkFPlNm3tIV3DvuT9x6YyemP/ME2/Zk0XvIo+e9KPYvwc59+/lw6Rf06JTBy394lP7duzB11hxGPv2SKRMIKnR/YDTb92YxdeJYxg29m8mvv8PEV15P+K0Rkybz9seLeHbsCB4bdg9/mfkOf5z2RnmrdPGhC0oQiUT0uu166y++/k6Ja0OffF6f9MpMvdVtD+hPTpmecK1l3/v0x16YZn4+euKk7knrrC9cvvqCl7ksbNy6Q5ev66Sv27T1nDKLV63V5es66VnZR3Rd1/WjOSd1+bpO+ieff2nKfLD4c93brIt+Or/ggpe5LLw8a7ae2vImPRaL6bqu60FFLSHTZ9g4vdeQMebnuYuW6cnNu+qn8vLNcyP/9JLeYeDwC1/gMnLr8HH67Q+PNz9rmmYeN+jSX3951uwS33l40mS9w8Dh5j3RNE1P63WX/tTLMy58gctANBrV63fqqz83fZZ5rt9Dj+sDR08wPyuqqtfJ6K2/9u6H5rm2dwzRRz8zxfx84nSennR9V/2jJV+UT8FLQVHVhLrRdV1//f2PdW+zLnpufqGu67r+78+W695mXfRjJ0+ZMvOWrtCTru+q5xf6dF3X9cyDh3X5uk768rXfmjLvzFukpzTvpvsDwXLQ5OJFjMBKoTAQJBSOcFntWgnnl67+hg1bt/PUI0NKfOdUXj67sg7Sq8uZlFOdGtVp0bQR67b8eMHLXBZO5uVjtVqpW6vGuWVy83G7JHPduXWbf8Rms3FzhzamTK/O7YjFYny3ZfsFL3NZOJmbx+V1apkptuLpmiJqVKuCpp15efSb77fStvl1VKtyZp29Xp3bsXX3voRVEioaTdPILSikft3a5rmfs9/UN5u20rtLO/OeWK1WenbKYN2mrResrOeDL2DshHB5vO9pmsa3W7bRu1i/ckkSXdu2ZN1mo1/lF/rYticzQaZGahVaN2tiylQELkkqUTc1UqvGt0cxdh3Yue8AtWtUS0h1Nmt0DZqmsX7LNgC+2bwVt0uiS5sWpkyvLu2JRKNs3LazHDS5ePl1J1CLcezEKV5/fz6+QICV6zZyT9+eDLrlZvN6fqGPMc9PZdbkiaUaxF2ZBwC4rNhzJeNzDXbs3X9By/5z+Pr7H1j21XpyTueyZsNm/jZpXIIRBPjPV+v4+vsfOHz8BN/9sJ03/vwHkr0ewEiHVKuSgux2mfLJ8b2htu/LoleXduWqz9m8t3ApuzIPsPdANvsOHOLNF546p+yBw0f5bOVa/vzYw+a5nZkHuKzO2XVXE03T2JOVTcu0xhes7D+H56bPIqCorN/8I6kpyTw1smQQdS7CkQj7Dh4u0Tbr1a7J7E/Kf1uSs8k5lcuM2fPwB4OsXLeRO3p2457+xsrzh4+fwBcIJjyvBaPsK77+DoA9+7PRdb2EzGW1a14Ufa8ITdOYOedjumW0MgOly2rX5FRuPv5gEK8sA3Dw6HHAeHbbs1MGO/cdoFb11IRnzTWrVcVht7Nj7366tGlZ/spcJIgRWJxINMqJ07kcO3GKvPhOtKHImfz5xKkz6d6hzTkbixLfBdZTzMADeGQZNRS6cAX/mQQUlZy4fv6AQm5+YYm9hwJBhROn8zh+4jRBJUR+4ZlnDEoohLeUNdo8sptQGXfAvRAU+HzknMrlaM4pQpEIecXKXpz8Qh+DfvcUGelpDB/U3zyvqCE87kT9itakUy6C+juZm8fxk6c5mZuHGjJ21/65FO1QfPYae17ZXebdiy8Emqad6XsFPgJBxSyXohr3/ux+5ZXdZp8rqp+Sfc99UdQdGCttPDnlNfbsP8hrzzxhnu93c2fsdhtjnp3KoWM5/LBrL5OmzsRisZj9Sg2VbJsWi+Wiqb+KRIzA4tSvW5uZz08AjPRZxoAh/PXN2Tw79iHWbNjCohVrWPvhP81t1WNajHA4QqE/QJJHJiluHAp8iduuF/h8JHk85atMKfTo2JYeHdsCsHbjFno+OIYbmjXhxnatTJkBvW5kQK8bAZi/bBX3P/40bdPTSGt4NUkemQKfv8TvFhT68Xrk8lHivzD6/kHm8Qv/+BeDn3iG3V/MIyXJa54v9Ae4/ZHfk+SRmfvqn7HZbOa1JI9M4Vn6Fel7MdTf9KfHAxCJROk34nFG/ukllr796s/6ruwyUlln11++z0/SRVB3dWvVMPve6fwC2g0YyuSZ7zB5/CizfIUl+tWZsifJPy1Tkei6znPTZ/H+p8tY/Na0hNmTNatVZf6MKTzz6ps07j6Q1JRkHh9+L8+/9hapVZIB8Mol+14sFqMgbnt+zYgRWCnUSK1C+5bX8/22XQD8uHsfp/MLaNJjEHUyelMnoze7sg7yxtwF1Mnoja7rpDW6GpvNRlb24YTfyso+QnrThhWhxjnp2Cqd1JRkU7/SuPXGjgBs2r4bgOZNGpJbUJiwL9PxU6cJKArpTS4u/fre1BlfIMjeA9nmOX8wyB2P/B5N05g/c4qZrimiedNryTx0JOFcZvZhXJKTxldfUS7l/jk4HHZ6d2n/X+vubOx2O2kNryYzO1G/rOzDNL/I6q5alRQ6tkpn03ZDv7q1alA9tQqZhxL7VWaxftXkmgY47PYS+mVeJH1v8sx3mDnnYz5542VaNG1U4nqn1umsmD2D/M0ryV67iJvat0ENhena9gYA0ps2JOdUbsKz2INHjhOLxUhvem256XExIhwYxjOC4vgCQb7ftpOGDS4HYPAdfchcvSDhX8MG9Rk2sB+ZqxfEh/MyrdIaJ0zN3rFvP7uyDlbo7riRSLREqnDrrn3kFhTSqEF9oKT+AGs2bAEwZTLS03DY7Xzy+ZemzPz/rEIDaH+WAAAEu0lEQVR2u2jVrMmFKv5PUlrZv9qwCafDwRX1jEg3EFQYMPJJgqrKJ29MTRiVFdG1zQ1s2bGHzGIByILlq8lo0axC33M7Wz9d11mzYTMN4/Xyc+nStgWLVqwxX+kIKipLvvwmYWJARXC2foGgwsYfd5j6WSwWurZpyYJlq812fDI3n6++20zneNndLomM9DTmL1tp/s7eA4f4cfc+Olfw86Epb7zL397+Nwtm/vWc75UW4XAYCbEXX3+HZo2uMe9B+5bXE9N1Fq1Ya8p+vGwlKUlemjeueAddkYgUInBDvwfo1Dqd+nVrk1foY9GKrwgoKmMG/wYwculnPz+w223Isith9tAzjz5E34ceY9iEP5PW8Gr+MfsjenRqW6EPWbfs3MPIp1+iW0YrqiYncehYDvOXrSIjPY0+3ToAsHzNeqa8+R4dbmhOstdDZvYRFixfxa03dqRN8+sAqJKcxJMjHmD8i38n+2gOUS3KjNkf86ffDUuY2FHe/P3/PmDV+u9pldYEh93Otj2ZLF79NY8Pu5caqcZL2M+99hZrN/5A14wbePS5l83vVk+twisTxwHQo1NbOrdpwS1DxzLyvjvZtG0Xy9d8y7J3/l4hehVx/+NP43Q4aHL1lSihEF99t5ktO/fw4fTJpsyR4yf4w1//AUB+oZ8PPvucH3bsoVmjaxj/0P0APDr4Lj747Av6DB/Lbd278v6ny/DKbob/5rYK0auItncMISM9jSvq1SGv0MfilWsp9AcYO+RuU2bCIw/S9e4RDBz9B7pmtGTWB5/Q5JorGdj7JlPm6TG/pffQRxk8/llaNG3IjNnz6JbRipvbt64ItQAjVf/s9Fk0alCfmXPmMXPOPPPa8489zBX16gAwYOSTNLrqCjxuF0u+/IbsI8dZ/NbfzBmjtaqnMvbBu3j0uansO3iIgKLw+pz5TJnwO9Pp/VoRi/kCCz9fzdoNxuw7l0uifctm3N6jm2kAS+PNfy+gweX16F5sWjkYkd+M2R9xMjefHp0yuKdvjwp9W94XCPLBZ5/z/bad5BYUUr1qFbq2vYH+3TubI4vT+QV88NnnbN6xm0J/gDo1qnNT+9bc0rV9wnMiXddZtf573lu4BKvFyoMDbq3Q0SUYMwo/WrqSHfuyUJQQV15ehz5dOyaUa/GqtWzZsafEd1OSvQnPziKRKO8tXMLKdRupXb0ao+4fSIPL65b4XnmyfvOPLFn9DZnZh7FYLDRvfC39u3dJGIGdzM3nzbnzS3z3qvqXcXffHubn0/kFzJg9j12ZxkocD987wJxlWlEsWrGGL7/bxOFjJ5AkJ+1apHF7j27Uqp6aIHc05yTT3/2Q7KPHad/yeoYO7FdiNnBm9mFmzJ5Hzqlcbm7fhnv796pQA7/3wCE+LPbCeXGG/aa/Gfy+t3ApX367CUVVaZnWmGED+1ElOSlBXtd1lq/9lrmLluOw2xg2sF+J1Up+jQgHJhAIBIJKiXgGJhAIBIJKiXBgAoFAIKiUCAcmEAgEgkqJcGACgUAgqJQIByYQCASCSolwYAKBQCColAgHJhAIBIJKiXBgAoFAIKiUCAcmEAgEgkqJcGACgUAgqJQIByYQCASCSolwYAKBQCColPw/3HmgcuMfSdUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 150
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Run date: 2023-03-24T15:20:04.659325\n"
     ]
    },
    {
     "data": {
      "text/markdown": [
       "## ...program is Ready"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# load all python and interactive tools - has to be run only once (but it does not hurt to rerun...)\n",
    "from IPython.display import display, HTML, Markdown, Image\n",
    "display(Markdown('## STARTING Environment...'))\n",
    "import json\n",
    "import matplotlib as mpl\n",
    "%matplotlib widget\n",
    "import spike\n",
    "from spike.Interactive import INTER as I\n",
    "from spike.Interactive import INTER_2D as I2D\n",
    "from spike.Interactive.ipyfilechooser import FileChooser\n",
    "from datetime import datetime\n",
    "I.initialize()\n",
    "print('Run date:', datetime.now().isoformat() )\n",
    "display(Markdown('## ...program is Ready'))\n",
    "from importlib import reload  # this line is debugging help\n",
    "\n",
    "# configurable items - you may change them to fit you preferences\n",
    "verbose = 1                              # chose from 0 (terse) to 3 more verbose\n",
    "mpl.rcParams['figure.figsize'] = (8,4)   # (X,Y) default figure size\n",
    "I.Activate_Wheel = True                  # True/False    scale with wheel control in the graphic cells \n",
    "I.reverse_scroll = False                 # inverse the direction of the mouse wheel, whether it is `True` (TrackPad) or `False` (Mouse)\n",
    "I.ParamList = ['SOLVENT', 'PULPROG', 'SFO1', 'NS', 'TE', 'TD', 'RG', 'SW', 'O1', 'D1','P1']    # the list of important parameters to display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Choose the file\n",
    "The `FileChooser()` tool creates a dialog box which allows to choose a file on your disk\n",
    "\n",
    "- use the `Select` button, click on the directory to move around `..` is for going back in the directory tree\n",
    "- click on the file to select it\n",
    "- modify the ( *optional* ) `path` argument, to start the exploration on a given location\n",
    "- changing `path='/DATA/'` to `path='.'` will start the browsing from the current directory \n",
    "- After the selection, the selected filename is found in `FC.selected`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing regular 2rr TopSpin files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:20:12.383770Z",
     "start_time": "2023-03-24T14:20:12.328836Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "81170217bed44d7b891b4c4676ec84c0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FileChooser(path='/DATA', filename='2rr', show_hidden='False')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# FileChooser\n",
    "FC = FileChooser(path='/DATA',filename='2rr')\n",
    "display(FC)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import  & display\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:21:13.002173Z",
     "start_time": "2023-03-24T14:21:11.822422Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading file  /DATA/HSQC_600/pharma_151201/13/pdata/1/2rr\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<b>folded HSQC\n",
       "</b><table class=\"dataframe\" border=\"1\"><thead><tr><th style=\"text-align: center;\">SOLVENT</th><th style=\"text-align: center;\">PULPROG</th><th style=\"text-align: center;\">SFO1</th><th style=\"text-align: center;\">NS</th><th style=\"text-align: center;\">TE</th><th style=\"text-align: center;\">TD</th><th style=\"text-align: center;\">RG</th><th style=\"text-align: center;\">SW</th><th style=\"text-align: center;\">O1</th><th style=\"text-align: center;\">D1</th><th style=\"text-align: center;\">P1</th></tr></thead><tbody><tr><td>MeOD</td><td>hsqcetgp</td><td>600.132880624</td><td>16</td><td>298.0177</td><td>2048</td><td>7298.2</td><td>10.0138079059537</td><td>2880.624</td><td>1.5</td><td>8.9</tr></tbody></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "2D data-set\n",
       "Axis F1 :NMR axis at 150.914064 MHz, 512 complex pairs,  from 49.583760 ppm (7482.886711 Hz) to 99.583760 ppm  (15028.589892 Hz)\n",
       "Axis F2: NMR axis at 600.132881 MHz, 2048 complex pairs,  from -0.206880 ppm (-124.155434 Hz) to 9.806928 ppm  (5885.459951 Hz)\n",
       "data-set is hypercomplex (order 2)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from spike.File.BrukerNMR import Import_2D_proc\n",
    "\n",
    "print('Reading file ',FC.selected)\n",
    "d1 = Import_2D_proc(FC.selected)       # creates a SPIKE NMRData object, from which everything is available\n",
    "display(I.summary(d1, output='HTML')) \n",
    "d1.set_unit('ppm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:29:42.743455Z",
     "start_time": "2023-03-24T14:29:41.876818Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Show2D(children=(VBox(children=(HBox(children=(Checkbox(value=True, description='Positive', layout=Layout(widt…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/mad/miniconda3/envs/OW/lib/python3.9/site-packages/IPython/core/pylabtools.py:151: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2215.56x1235.56 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "S2 = I2D.Show2D(d1, title=d1.params['acqu']['title'])\n",
    "S2.scale.value=5\n",
    "S2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Storing to open format\n",
    "\n",
    "Several possibilities\n",
    "\n",
    "### to native Spike/Gifa file format\n",
    "- binary for data / with axes description\n",
    "- json for spectrometer metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:26:23.519472Z",
     "start_time": "2023-03-24T14:26:23.331077Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing 2D\n"
     ]
    }
   ],
   "source": [
    "d1.save('my_file.gs2')\n",
    "with open('my_file.json','w') as Meta:\n",
    "    json.dump(d1.params, Meta)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The file with recovered as follow:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:30:24.773134Z",
     "start_time": "2023-03-24T14:30:24.336649Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<b>folded HSQC\n",
       "</b><table class=\"dataframe\" border=\"1\"><thead><tr><th style=\"text-align: center;\">SOLVENT</th><th style=\"text-align: center;\">PULPROG</th><th style=\"text-align: center;\">SFO1</th><th style=\"text-align: center;\">NS</th><th style=\"text-align: center;\">TE</th><th style=\"text-align: center;\">TD</th><th style=\"text-align: center;\">RG</th><th style=\"text-align: center;\">SW</th><th style=\"text-align: center;\">O1</th><th style=\"text-align: center;\">D1</th><th style=\"text-align: center;\">P1</th></tr></thead><tbody><tr><td>MeOD</td><td>hsqcetgp</td><td>600.132880624</td><td>16</td><td>298.0177</td><td>2048</td><td>7298.2</td><td>10.0138079059537</td><td>2880.624</td><td>1.5</td><td>8.9</tr></tbody></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "2D data-set\n",
       "Axis F1 :NMR axis at 150.914064 MHz, 512 complex pairs,  from 49.583760 ppm (7482.886711 Hz) to 99.583760 ppm  (15028.589892 Hz)\n",
       "Axis F2: NMR axis at 600.132881 MHz, 2048 complex pairs,  from -0.206880 ppm (-124.155434 Hz) to 9.806928 ppm  (5885.459951 Hz)\n",
       "data-set is hypercomplex (order 2)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1bc0e43364ae49b9bef83c7f928072c0",
       "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 src='data:image/png;base64,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' width=800.0/>\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": [
    "rec1 = spike.NMR.NMRData(name='my_file.gs2')   # data\n",
    "with open('my_file.json','r') as Meta:         # and metadata\n",
    "    rec1.params = json.load(Meta)\n",
    "# verify\n",
    "display(I.summary(rec1, output='HTML')) \n",
    "rec1.set_unit('ppm')\n",
    "rec1.display(scale=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### to numpy format\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:34:59.139043Z",
     "start_time": "2023-03-24T14:34:55.077330Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "mybuff = d1.get_buffer()   # get_buffer() conserves real/imaginary state - in the case of hypercomplex data - as here - real and imagniary part in F1 are interleaved\n",
    "np.save('my_file_buffer',mybuff)   # extention .npy is added\n",
    "# alternatively, use the compresse data format:\n",
    "np.savez_compressed('my_file_buffer',[mybuff])   # extention .npz is added"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The file is recovered as follows:\n",
    "\n",
    "***but all metadata are lost*** (400Mhz is the frequency by  default !)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:47:21.486107Z",
     "start_time": "2023-03-24T14:47:21.177935Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2D data-set\n",
       "Axis F1 :NMR axis at 400.000000 MHz, 512 complex pairs,  from 0.000000 ppm (0.000000 Hz) to 15.707963 ppm  (6283.185307 Hz)\n",
       "Axis F2: NMR axis at 400.000000 MHz, 2048 complex pairs,  from 0.000000 ppm (0.000000 Hz) to 15.707963 ppm  (6283.185307 Hz)\n",
       "data-set is hypercomplex (order 2)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "20ee5b8965424c709fd0f82e0c19c95a",
       "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 src='data:image/png;base64,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' width=800.0/>\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": [
    "recbuff = np.load('my_file_buffer.npy')\n",
    "rec2 = spike.NMR.NMRData(buffer=recbuff)\n",
    "rec2.axis1.itype=1   # force complex in F1\n",
    "rec2.display(scale=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "recovering the meta data - inspired from spike.File.BrukerNMR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:49:06.323093Z",
     "start_time": "2023-03-24T14:49:06.135023Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<b>folded HSQC\n",
       "</b><table class=\"dataframe\" border=\"1\"><thead><tr><th style=\"text-align: center;\">SOLVENT</th><th style=\"text-align: center;\">PULPROG</th><th style=\"text-align: center;\">SFO1</th><th style=\"text-align: center;\">NS</th><th style=\"text-align: center;\">TE</th><th style=\"text-align: center;\">TD</th><th style=\"text-align: center;\">RG</th><th style=\"text-align: center;\">SW</th><th style=\"text-align: center;\">O1</th><th style=\"text-align: center;\">D1</th><th style=\"text-align: center;\">P1</th></tr></thead><tbody><tr><td>MeOD</td><td>hsqcetgp</td><td>600.132880624</td><td>16</td><td>298.0177</td><td>2048</td><td>7298.2</td><td>10.0138079059537</td><td>2880.624</td><td>1.5</td><td>8.9</tr></tbody></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "2D data-set\n",
       "Axis F1 :NMR axis at 150.914064 MHz, 512 complex pairs,  from 49.583760 ppm (7482.886711 Hz) to 99.583760 ppm  (15028.589892 Hz)\n",
       "Axis F2: NMR axis at 600.132881 MHz, 2048 complex pairs,  from -0.206880 ppm (-124.155434 Hz) to 9.806928 ppm  (5885.459951 Hz)\n",
       "data-set is hypercomplex (order 2)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "70d521bad7db40b9bc531b24eb581702",
       "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 src='data:image/png;base64,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' width=800.0/>\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": [
    "from spike.File.BrukerNMR import offset, zerotime\n",
    "# read json\n",
    "with open('my_file.json','r') as Meta:         # and metadata\n",
    "    META = json.load(Meta)\n",
    "rec2.params = META\n",
    "\n",
    "# then restore axes\n",
    "rec2.axis1.frequency = float(META['acqu2']['$SFO1'])\n",
    "try:\n",
    "    rec2.axis1.specwidth = float(META['acqu2']['$SW_h'])\n",
    "except KeyError:    # this happens on certain versions\n",
    "    rec2.axis1.specwidth = float(META['acqu2']['$SW'])*d.axis1.frequency\n",
    "rec2.axis2.specwidth = float(META['acqu']['$SW_h'])\n",
    "rec2.axis2.frequency = float(META['acqu']['$SFO1'])\n",
    "rec2.frequency = rec2.axis2.frequency\n",
    "rec2.axis1.offset = offset(META['acqu2'], META['proc2'])\n",
    "rec2.axis2.offset = offset(META['acqu'], META['proc'])\n",
    "rec2.axis2.zerotime = zerotime(META['acqu'])\n",
    "\n",
    "# verify\n",
    "display(I.summary(rec2, output='HTML')) \n",
    "rec2.set_unit('ppm')\n",
    "rec2.display(scale=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----\n",
    "# Importing DOSY from Topspin\n",
    "DOSY have a different format in Spike, so the import is different"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T14:52:01.068379Z",
     "start_time": "2023-03-24T14:52:01.021604Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "18ac2e2c6dc74bd2b5c658931975bf04",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FileChooser(path='/DATA', filename='2rr', show_hidden='False')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from spike.plugins.NMR.PALMA import Import_DOSY, Import_DOSY_proc\n",
    "\n",
    "# FileChooser\n",
    "FCD = FileChooser(path='/DATA',filename='2rr')\n",
    "display(FCD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T15:32:45.326017Z",
     "start_time": "2023-03-24T15:32:45.307026Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading file  /home/mad/Documents/ mad/cours/AISD/NNB/CAS170223/8/pdata/1000/2rr\n",
      "DOSY performed on 1H\n",
      "ste\n",
      "0.002 0.09617750000000001 0.0004 ste 1H\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<b>DOSY  - (u'eau',)\n",
       " - Processed with PALMA Version 1.0\n",
       "</b><table class=\"dataframe\" border=\"1\"><thead><tr><th style=\"text-align: center;\">SOLVENT</th><th style=\"text-align: center;\">PULPROG</th><th style=\"text-align: center;\">SFO1</th><th style=\"text-align: center;\">NS</th><th style=\"text-align: center;\">TE</th><th style=\"text-align: center;\">TD</th><th style=\"text-align: center;\">RG</th><th style=\"text-align: center;\">SW</th><th style=\"text-align: center;\">O1</th><th style=\"text-align: center;\">D1</th><th style=\"text-align: center;\">P1</th></tr></thead><tbody><tr><td>H2O+D2O</td><td>CF_ledgp2s</td><td>564.619755006216</td><td>256</td><td>297.9984</td><td>8192</td><td>812.7</td><td>29.9172881255384</td><td>-66632.993784</td><td>1</td><td>11.25</tr></tbody></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('Reading file ',FCD.selected)\n",
    "ddosy = Import_DOSY_proc(FCD.selected, postprocessed=True)       # the flag postprocessed determines state in F1    False: after XF2,   True: when fully processed\n",
    "display(I.summary(ddosy, output='HTML')) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T15:32:47.646140Z",
     "start_time": "2023-03-24T15:32:46.937063Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/mad/Documents/spike/spike/Interactive/INTER_2D.py:225: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  self.spec_ax.clear()\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Show2D(children=(VBox(children=(HBox(children=(Checkbox(value=True, description='Positive', layout=Layout(widt…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/mad/miniconda3/envs/OW/lib/python3.9/site-packages/IPython/core/pylabtools.py:151: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2222.22x1111.11 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ddosy.axis2.currentunit = 'ppm'\n",
    "SD = I2D.Show2D(ddosy, title=ddosy.params['acqu']['title'])\n",
    "SD.scale.value=5\n",
    "SD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-24T15:34:06.895829Z",
     "start_time": "2023-03-24T15:34:06.699224Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-rw-r-- 1 mad mad 33M mars  24 15:34 my_file_buffer.npy\r\n",
      "-rw-rw-r-- 1 mad mad 15M mars  24 15:34 my_file_buffer.npz\r\n",
      "-rw-rw-r-- 1 mad mad 17M mars  24 15:26 my_file.gs2\r\n",
      "-rw-rw-r-- 1 mad mad 18K mars  24 15:26 my_file.json\r\n",
      "-rw-rw-r-- 1 mad mad 33M mars  24 15:33 my_file.npy\r\n"
     ]
    }
   ],
   "source": [
    "ls -lh my_file*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "--------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "hide_input": false,
  "jupytext": {
   "encoding": "# -*- coding: utf-8 -*-",
   "formats": "ipynb,py:percent"
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "0018c3406ea340e7bfa8d990f42da727": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Done",
       "layout": "IPY_MODEL_385ef4626b2c42e9a393f21aef47b6ed",
       "style": "IPY_MODEL_9aa60213a02d45f0abc3bff501c242f8"
      }
     },
     "0068f0aa89b64904a484054fc36e252f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "0089f9c9601f4811b29c479d54d42082": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80%"
      }
     },
     "0094485db9da4177ad4da8d797c6ec12": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "025ec3d7ffeb43b3aa04453347810d92": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "02c5670517f045df8ab59cb5f9f44ef2": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "036e9e1201cf428084301243a1bada53": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Done",
       "layout": "IPY_MODEL_6e884f90398944ce9e49ba1ab490ae13",
       "style": "IPY_MODEL_1357862cca3149cba26cd32c11717d38"
      }
     },
     "04d73c6df79440d0acfe11dce615bf74": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_5d121360acf342b8976766d767c03bf6",
        "IPY_MODEL_9da015e1f2c044a48bc8982e17bfed41",
        "IPY_MODEL_1cf818bff09e4947aa9a744a96e187e9",
        "IPY_MODEL_5f4858b987a34694be6064366fc92b4d",
        "IPY_MODEL_59fadfb25a844ff1a31d653e07e1332f",
        "IPY_MODEL_8acb8361d1a947aa8dd91c80da0ed544"
       ],
       "layout": "IPY_MODEL_eb48c668fa814d8ab80f66c66707aab5"
      }
     },
     "05331af6be00451687585d553a710b38": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "05eaf8014e494752ab50d153c0a8ace3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "GridBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_b07aa323eeb94b8ca9de28021916effb",
        "IPY_MODEL_f7d77347107347ef8eda62f468a174f0",
        "IPY_MODEL_e9accee3d74a463492fc7212ae78424f"
       ],
       "layout": "IPY_MODEL_e4a10652a5d7498ba04241d2996fc2bc"
      }
     },
     "05ecd39f7b62490d898bacac25dfefa3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_40dc53c684c4472bbdf64259a7f8c5cd",
       "style": "IPY_MODEL_1b3b966a75d445f499a47eb2d183e0a4",
       "value": "<b>7</b>"
      }
     },
     "05ef19d07715445b88ac31fb28f77784": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "07af52ce85bb4825b891292050421b52": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "20%"
      }
     },
     "086c03b8860048d690c102025d5a6ae8": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "0874d82e408f49da80172dd4ddacfc77": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "08a5aa2a47134762ae8b0c15497abfca": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "layout": "IPY_MODEL_6d39be62597a41f9b039581a32469ff4",
       "step": null,
       "style": "IPY_MODEL_168e812970ad4933971faadc5a2373fc"
      }
     },
     "08e3eb9209b741a49fa8c670f7af1c4b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_b3a73b193e87478aa921541c1b92fb72",
        "IPY_MODEL_bfa4dfb8995746e8a37be5ebe92b6c17",
        "IPY_MODEL_21f4c236180c402c92058332d30afd7f",
        "IPY_MODEL_6e0715a109b4485c8f29aa038b98a5a4",
        "IPY_MODEL_6ad2e5b435e648d2bc8ce2cb81bac5d7"
       ],
       "layout": "IPY_MODEL_e7f1a7611a274c7d8402c0c7f84f68da"
      }
     },
     "08ff3041d42e4ef5a35b372a0f007ca5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "up",
        "down",
        "off"
       ],
       "index": 2,
       "layout": "IPY_MODEL_0dd6731475f54bde87f1e6bd839c8835",
       "style": "IPY_MODEL_3d5feeeb47fa4669b715ff7d4c9225ae"
      }
     },
     "094a790c634a423ca69843959a745c81": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "09ac6d48b8334b7589c4f0760982cacc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_44a18c305716419c9fc863ffc4e66ffa",
       "style": "IPY_MODEL_0d41694c544d495180950e918c1b6b12",
       "value": "<b>5</b>"
      }
     },
     "0a9163a4480c4a72bb6d9af3cf1f640a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "description": "P1:",
       "layout": "IPY_MODEL_69cc9ea696524704a1fa0b3bde7f9b01",
       "max": 360,
       "min": -360,
       "style": "IPY_MODEL_a9c0cb1f520a4c6f9bda7ff0ec603995"
      }
     },
     "0b2d81dd52254d78a891d3f489cc4707": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "0bc60f478f9e41acba74ad7d9cf225ae": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "0c441325b0c5469a89da4f4f34b37920": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "auto"
      }
     },
     "0cc7b968bd3e4fe4920ffafdaee95752": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "warning",
       "description": "Cancel",
       "layout": "IPY_MODEL_dc75c9f6dd0a4cdd92a9bd55752fb1c2",
       "style": "IPY_MODEL_4b54ddd705274ccbae82a998e01cb82e"
      }
     },
     "0ccf306cf99e42248f1505bd14f33b68": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "0cec88999059442e8ab6902a8990b847": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "0d41694c544d495180950e918c1b6b12": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "0d546889b19f42e4b17ed9e85e340726": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_43a1ef0abb3d4fa992642b191822becd",
        "IPY_MODEL_f20aae09d105477ca77455f7f6662f5e",
        "IPY_MODEL_2a87a251b5174f209a591ebc7c10d648"
       ],
       "layout": "IPY_MODEL_b75ba06fb6d54861a59369aa7b569040"
      }
     },
     "0da3b58fd8bc446aa568f2e0ddd04a39": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "0dd6731475f54bde87f1e6bd839c8835": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "0e14dd4af1364c1b9e36617fa005e540": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "0e4cacaf2daf46238bd5fac1b5e67412": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "0ee2905e83f84febae515d41a757f6c0": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "20%"
      }
     },
     "10eb527e17ca4db09d06ac09df0c239e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "113f3b21f835475c8da7bf6cc1532e4a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_2d7491deae8146d6bbac3f59b194e211",
        "IPY_MODEL_a1bf2000ce1741f2bf11ae39046a6380",
        "IPY_MODEL_1cc04684da42464f9157466fafe135ae",
        "IPY_MODEL_69c8a4dd3b4745d7ad30d9c1d1ad19d3",
        "IPY_MODEL_bcbb3777b377405299fc7c70d1029bcb"
       ],
       "layout": "IPY_MODEL_e9a937e757d44de7b41d9444d816f2f3"
      }
     },
     "1183e720e3d24c8caf8b95b2d4c197fb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "121de158df5d4b3d8d7d2ab40bc58905": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_05eaf8014e494752ab50d153c0a8ace3",
        "IPY_MODEL_a3d53f2e2bd743daacfefa6f53612fd2"
       ],
       "layout": "IPY_MODEL_a21f7d18335d49f59c983645d850c1ec"
      }
     },
     "123325aab81d4a6eae997e8128d351ab": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_7e9c489b5c974e899f7423335d0890e7",
       "style": "IPY_MODEL_e9053bdd792e4ac291215113b4fa9f33",
       "value": "<b>8</b>"
      }
     },
     "132e58a2b5ba422ab6ac6895c3895b6e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "1357862cca3149cba26cd32c11717d38": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "13bee2a5efb9416e99c7640629a42d1d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "140df7fc72244e50ae2f1ca62ce801d8": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_0d546889b19f42e4b17ed9e85e340726",
        "IPY_MODEL_c92f254cb6e7423e8d7101f56e8f68f1"
       ],
       "layout": "IPY_MODEL_33f864a43e3445c18d8155ce1cb847f5"
      }
     },
     "142cb6ba0f9347a0beffe819b60f42d3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "15298079d7b842bf98a1f86e388d10bc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_16a291d9b1d54e4a9a700f91feeb9c14",
       "placeholder": "output filename",
       "style": "IPY_MODEL_0b2d81dd52254d78a891d3f489cc4707",
       "value": "fid"
      }
     },
     "159262a422e14b31971b2a4a06e3de55": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_370fac5f973d46ff890cd2647493f018",
       "outputs": [
        {
         "data": {
          "text/html": "<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Start</th>\n      <th>End</th>\n      <th>Value</th>\n      <th>Calibration</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>5.364807</td>\n      <td>5.215547</td>\n      <td>232.805177</td>\n      <td>0.618664</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>4.901426</td>\n      <td>4.861800</td>\n      <td>11797.222656</td>\n      <td>31.350299</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>4.779893</td>\n      <td>4.747968</td>\n      <td>107.346950</td>\n      <td>0.285267</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4.526099</td>\n      <td>4.452739</td>\n      <td>120.520438</td>\n      <td>0.320275</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4.255451</td>\n      <td>4.218710</td>\n      <td>61.118079</td>\n      <td>0.162417</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>4.222530</td>\n      <td>4.157862</td>\n      <td>172.230920</td>\n      <td>0.457692</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>4.120226</td>\n      <td>4.036584</td>\n      <td>276.384743</td>\n      <td>0.734473</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>4.030903</td>\n      <td>3.965840</td>\n      <td>117.754752</td>\n      <td>0.312925</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>3.936848</td>\n      <td>3.865759</td>\n      <td>124.194429</td>\n      <td>0.330038</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>3.886549</td>\n      <td>3.621927</td>\n      <td>5998.210348</td>\n      <td>15.939827</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>3.630691</td>\n      <td>3.546038</td>\n      <td>312.855696</td>\n      <td>0.831392</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>3.536599</td>\n      <td>3.503353</td>\n      <td>57.850830</td>\n      <td>0.153735</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>3.471101</td>\n      <td>3.387009</td>\n      <td>210.582785</td>\n      <td>0.559609</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>3.387972</td>\n      <td>3.279854</td>\n      <td>2466.131455</td>\n      <td>6.553573</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>3.287957</td>\n      <td>3.262560</td>\n      <td>39.477643</td>\n      <td>0.104909</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>3.261188</td>\n      <td>3.226824</td>\n      <td>38.581195</td>\n      <td>0.102527</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>3.171784</td>\n      <td>3.132637</td>\n      <td>41.512185</td>\n      <td>0.110316</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>3.121806</td>\n      <td>3.069093</td>\n      <td>104.474181</td>\n      <td>0.277633</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>2.967317</td>\n      <td>2.904582</td>\n      <td>154.971708</td>\n      <td>0.411827</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>2.901866</td>\n      <td>2.886478</td>\n      <td>28.379498</td>\n      <td>0.075417</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>2.544180</td>\n      <td>2.496062</td>\n      <td>96.950514</td>\n      <td>0.257639</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>2.394475</td>\n      <td>2.286477</td>\n      <td>632.505049</td>\n      <td>1.680838</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2.293846</td>\n      <td>2.222744</td>\n      <td>124.474677</td>\n      <td>0.330783</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>2.146466</td>\n      <td>1.986674</td>\n      <td>396.472418</td>\n      <td>1.053598</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>1.713786</td>\n      <td>1.343189</td>\n      <td>1990.821394</td>\n      <td>5.290470</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>1.352996</td>\n      <td>1.251773</td>\n      <td>6070.832323</td>\n      <td>16.132815</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>1.248576</td>\n      <td>1.185243</td>\n      <td>199.954953</td>\n      <td>0.531366</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>1.096337</td>\n      <td>1.073986</td>\n      <td>35.624939</td>\n      <td>0.094671</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>1.003362</td>\n      <td>0.831576</td>\n      <td>1128.910046</td>\n      <td>3.000000</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>0.013311</td>\n      <td>-0.010171</td>\n      <td>385.260068</td>\n      <td>1.023802</td>\n    </tr>\n  </tbody>\n</table>",
          "text/plain": "<IPython.core.display.HTML object>"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "15c4ca3a56d44e168f2e4fa287464dc3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "/DATA/SM_ARTE_v3/SM_ARTE4_161123/1",
        "/DATA/SM_ARTE_v3/SM_ARTE4_161123",
        "/DATA/SM_ARTE_v3",
        "/DATA",
        "/"
       ],
       "index": 0,
       "layout": "IPY_MODEL_af6bc15d8b0d4814b2fb6740e526872d",
       "style": "IPY_MODEL_ad54e011f73a4715a53c79a9d6bc95d2"
      }
     },
     "1659b6218b52472aaee8231000855a3f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Reset",
       "layout": "IPY_MODEL_d62c090f057c494daeadb01cb4deccb4",
       "style": "IPY_MODEL_d12be3ac986740bc9cc146bf02abd014",
       "tooltip": "Reset to full spectrum"
      }
     },
     "168e812970ad4933971faadc5a2373fc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "16a291d9b1d54e4a9a700f91feeb9c14": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "filename",
       "width": "auto"
      }
     },
     "16f1f390f700400f89897392f15388e8": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "height": "10.16cm",
       "width": "80px"
      }
     },
     "171f6c3aed3e4b7f8c5c491db40cd51e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "black",
        "red",
        "blue",
        "green",
        "orange",
        "blueviolet",
        "crimson",
        "turquoise",
        "indigo",
        "magenta",
        "gold",
        "pink",
        "purple",
        "salmon",
        "darkblue",
        "sienna"
       ],
       "index": 5,
       "layout": "IPY_MODEL_c2e0d83eaddc454eaa7da8ffa5abef67",
       "style": "IPY_MODEL_af6e0466f6dc4f1097828c1e0b732829"
      }
     },
     "1900dcf9661c4fd78def1699c8bd9e97": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "1ab986463780490c9d26457ec565999c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "10%"
      }
     },
     "1ad7490a63164e3e9c3c06b102016c84": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_45431e2db3cd493284b80ee80a2fc57d",
       "style": "IPY_MODEL_622d737505ce4570a765e576f9163727",
       "value": "<b>2</b>"
      }
     },
     "1b3b966a75d445f499a47eb2d183e0a4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "1b8894747a4846e7bf3f5b5b780c62a4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "1b93616b350a459197324d4d4c76a504": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_1ad7490a63164e3e9c3c06b102016c84",
        "IPY_MODEL_711ddce44b5341fbb849239190ffb3eb",
        "IPY_MODEL_d68cf4b8534b4cdaa1d6a0f6d60558a4",
        "IPY_MODEL_ae304f127c8146a3bf534ce68e16f161",
        "IPY_MODEL_fcceef8c980a4a63b34bdeb7eb205604"
       ],
       "layout": "IPY_MODEL_85dfa2e111b9455c9963b0c58cf63a22"
      }
     },
     "1b9cee1849b74fbebfa390d0134a23a0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "1c2a8e2939c0498484d9845e17c61a23": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "1cc04684da42464f9157466fafe135ae": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "layout": "IPY_MODEL_f59d44e8ec8e46fb8dffe4b20dfd3ebe",
       "step": null,
       "style": "IPY_MODEL_6758deb064c74bb486c62ccb01d7cd71"
      }
     },
     "1cf818bff09e4947aa9a744a96e187e9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "description": "Value",
       "layout": "IPY_MODEL_6779fe82a6314ae48e466219a3c310d0",
       "step": null,
       "style": "IPY_MODEL_4290232627f4410fbf3d4300aa183ac2",
       "value": 3
      }
     },
     "1d1d2c0502e84d6195b84ee8326b3bf1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "1de0691e049545e6bf51d03ff5bab3be": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_ffe28375aa344ea69e948224087e38d5",
        "IPY_MODEL_a8bca7695350476eaa3f2343b6c2219a"
       ],
       "layout": "IPY_MODEL_87ada72f739f48559703b719208962cb"
      }
     },
     "1e3ee020ff9943d1b551c1cd60901b54": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "1ea05e0fa82f4b3ba0ffe300e0b7f23c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "display": "none",
       "width": "auto"
      }
     },
     "1eb1bdb7e68f424ebef07b2b5f63c05d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "1f60f94342f84a4f988531ce0051276e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Add",
       "layout": "IPY_MODEL_e308804a1a6040cda772b52c127a421d",
       "style": "IPY_MODEL_bc9dcc0b168d408cac37c995d5b68a88"
      }
     },
     "208d10cfe7ae46babfb48cd96f477aaa": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "2142da298cd4480282c532b43838b8c3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "21c62f98c8f14bcab2a4031c8248dd6a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "40em"
      }
     },
     "2312009322ae4e3b922df45e2aeccc8d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Reset",
       "layout": "IPY_MODEL_e308804a1a6040cda772b52c127a421d",
       "style": "IPY_MODEL_ad941abb775d48e1b516fa3ed258df9b",
       "tooltip": "Reset to full spectrum"
      }
     },
     "2385d32c890f49398bb822f9e385442c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "243995574dcc4a9881f724b63aaf58b7": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "24b4dcfcfb07471a9315e083b23824c4": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "MPLCanvasModel",
      "state": {
       "_figure_label": "Figure 4",
       "_height": 500,
       "_image_mode": "diff",
       "_width": 1000,
       "layout": "IPY_MODEL_b8b987a8e8de4975b3f68d756655f278",
       "toolbar": "IPY_MODEL_32ee4b59c32540139988d6cfbf51ce09",
       "toolbar_position": "left"
      }
     },
     "266ee4b752fc45d894b94aea0a3fd919": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "description": "scale:",
       "layout": "IPY_MODEL_e2059c937489460189ef61db4a999451",
       "max": 200,
       "min": 1,
       "orientation": "vertical",
       "step": 0.1,
       "style": "IPY_MODEL_0bc60f478f9e41acba74ad7d9cf225ae",
       "value": 200
      }
     },
     "27267d9fa19343a8832c76ba935cc86d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "description": "scale:",
       "layout": "IPY_MODEL_16f1f390f700400f89897392f15388e8",
       "max": 200,
       "min": 1,
       "orientation": "vertical",
       "step": 0.1,
       "style": "IPY_MODEL_3c253f9bd15647fa915a6780623f391c",
       "value": 13.453135238626095
      }
     },
     "2773834bb19c45c9a8fbe119c525b48a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "28173aaa92c04140a6d5aaaf3c849012": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_b5ece940c2154762ad987b2cfebc7770",
       "style": "IPY_MODEL_0e14dd4af1364c1b9e36617fa005e540",
       "value": "integrals"
      }
     },
     "286463ca31fb4ac0bc81ed4f3c31eb1a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "28a8f25455f04d2dbd7e8ae700408647": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "29d47967d9134eb4a94671c396f3c5af": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "2a652f1cf81f4eb5805556e0b7a2ec96": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_05ecd39f7b62490d898bacac25dfefa3",
        "IPY_MODEL_95d6c20674844c00a01105d3c7ebfab7",
        "IPY_MODEL_4adad186faf447f4a6da684809a9547b",
        "IPY_MODEL_b40d16f3c196481990a4040360671451",
        "IPY_MODEL_820da354f8974686a3eae3d5ffa79ba9"
       ],
       "layout": "IPY_MODEL_b2677b80376949349bf8f8c88497a05d"
      }
     },
     "2a87a251b5174f209a591ebc7c10d648": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_5f26653a6e88403eab9a2e2f13b06dfd",
       "style": "IPY_MODEL_50fb7a377e7e43d9911dd2838d664d7e",
       "value": "Use buttons to add and remove integrals in the current zoom window"
      }
     },
     "2b5995cea4394d7e834256c23e9773ed": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "2bc236dbae824995917c060f9b8f709f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "2c13d392a32a458794203e270b9e34ed": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "2c71ce4a87b0444e967084745be3ec6f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "40em"
      }
     },
     "2c8de912ac12492c87290e2b303a21a1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_738e9a41d5a64c54a365c939f22c44ec",
       "style": "IPY_MODEL_63e605d3dd3040f980552466f8d615bb",
       "value": "<b>1</b>"
      }
     },
     "2ca0f26a406d49fc8ee07b225b060b9e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "continuous_update": false,
       "description": "extension",
       "layout": "IPY_MODEL_d923c32df5534ec2bc190b705908ee35",
       "max": 20,
       "min": 0.5,
       "readout": false,
       "readout_format": ".1f",
       "step": 0.1,
       "style": "IPY_MODEL_9019956d73c0470aa9480d96c76c5e04",
       "value": 5
      }
     },
     "2d7491deae8146d6bbac3f59b194e211": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_e770675e7ab54afda69dc1fa099b9d02",
       "style": "IPY_MODEL_dabb721536164b13ad9d15eac1d6e8f2",
       "value": "<b>9</b>"
      }
     },
     "2e2ce8f3ed964dd2bf0327b3bcce1373": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "2ea7ef0f5f9e45ba9a59e16c75ebb391": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "2eb954911c574fb09208aa8ce9118f3a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "2ed80f830e5047de8ec924d621551725": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "2f34395d13e54acf8db2bf6f21bba5a8": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "2f4caacdc61648c0be88d5461d4442af": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "40em"
      }
     },
     "304a8e5cdf0c43b69301a70a985a2ca8": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "30689cf235a5493195a173b58c8fc001": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "30bf0647211245a0a1ac2868d5dbff92": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_f62a70cd075546a1925584f48b58b5d0",
       "style": "IPY_MODEL_28a8f25455f04d2dbd7e8ae700408647",
       "value": "Select a peak with mouse and set calibrated values"
      }
     },
     "313b723fb332451bb7f1478bbc6595e5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_2f4caacdc61648c0be88d5461d4442af",
       "style": "IPY_MODEL_8c2897ad0a6e4d728ad1930b763fc301",
       "value": "None"
      }
     },
     "316cefd243e64613a00c095bd19c8b8d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "description": "P0:",
       "layout": "IPY_MODEL_afeb38015a0e49f2a52e071dcb65d550",
       "max": 180,
       "min": -180,
       "step": 0.1,
       "style": "IPY_MODEL_3a1c44b3f98d465c8fa106e347b75213"
      }
     },
     "31f699aac0774d56abec64ce741e4289": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "description": "pivot:",
       "layout": "IPY_MODEL_0089f9c9601f4811b29c479d54d42082",
       "max": 65536,
       "readout": false,
       "style": "IPY_MODEL_9b2c47c928104abaac69ffe1afe2272b",
       "value": 29187.74043008127
      }
     },
     "32e09935ce914924b4c6c3024ab29c8e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_2c71ce4a87b0444e967084745be3ec6f",
       "style": "IPY_MODEL_df8de11e30204b43bf3475713ce5aae9",
       "value": "None"
      }
     },
     "32ee4b59c32540139988d6cfbf51ce09": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_286463ca31fb4ac0bc81ed4f3c31eb1a",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "3388d8cb3429483f9f6700b5c2835904": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "33cbe83344474f8fbd78f6aba61a30db": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "warning",
       "description": "Cancel",
       "layout": "IPY_MODEL_e308804a1a6040cda772b52c127a421d",
       "style": "IPY_MODEL_7c3a76083f5b4c84a83fe3fa4d22037d"
      }
     },
     "33f864a43e3445c18d8155ce1cb847f5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "34e83b93d7574672a5796b9cd3372f26": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_ba700805d58c42919a1f233256c03c7f",
        "IPY_MODEL_2312009322ae4e3b922df45e2aeccc8d",
        "IPY_MODEL_266ee4b752fc45d894b94aea0a3fd919"
       ],
       "layout": "IPY_MODEL_5ea52031d73b404b990705bc8a36c540"
      }
     },
     "355dc1682171493486ca04a2ca46cbfb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_c60a67c01fe948ea88a4c9005cbcfe01",
        "IPY_MODEL_5145ac49dc8e48489e3d3c0b88775d7f",
        "IPY_MODEL_31f699aac0774d56abec64ce741e4289",
        "IPY_MODEL_bb178e13a098475f9467aeee54ee7bfc"
       ],
       "layout": "IPY_MODEL_a78fb299cdc740b186bddf01e523703c"
      }
     },
     "3638a154558446dd9f97d58dc923018f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "40em"
      }
     },
     "3666b57e78cd40818d2232f92ce10e4f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "36c8b2ad13fd4b09947e8a37501cf378": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "370fac5f973d46ff890cd2647493f018": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "border": "1px solid red"
      }
     },
     "371b6d4b11b4427dac51450311faae4b": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "3813bc33c5484939a473f12b8cc81084": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "385ef4626b2c42e9a393f21aef47b6ed": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "39a52c607165496f86fbc2bedbbbc060": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_ce592ff2be134df4a4bc871c0d1433cc",
        "IPY_MODEL_921ea8f6ecc94442a51a76fa90639c8e"
       ],
       "layout": "IPY_MODEL_54d3a8b16c094f93af13ef8ada3cd64a"
      }
     },
     "3a192f0a1d3b4d5086d36a0624e7709d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "3a1c44b3f98d465c8fa106e347b75213": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "3ae2beb5431242c094bf06648c06addd": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "3b1ecd888a2e4863bd4806ca0a3ffc33": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "3c253f9bd15647fa915a6780623f391c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "3d1b1685562b436ca729b0faeee79849": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "3d5feeeb47fa4669b715ff7d4c9225ae": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "3d8df43e1a4842fca73ada21d68a35c1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "description": "selection",
       "disabled": true,
       "layout": "IPY_MODEL_0ee2905e83f84febae515d41a757f6c0",
       "step": 0.001,
       "style": "IPY_MODEL_132e58a2b5ba422ab6ac6895c3895b6e"
      }
     },
     "3dfb46fcae944119bae41faa3aab0e74": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "3e97f14fdf8042d1a928f38a2d208734": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "3f2deedbc8434d5b874d934aa15aa36c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "3f57e226c06d41029b45cd966016fe0d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "GridBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_eb0228abb758418fb6770d70fb68f310",
        "IPY_MODEL_b54210b2a0dd44dda02e4b60d51757a0",
        "IPY_MODEL_ff5a816f8da3432182ab8d2be9e416a5"
       ],
       "layout": "IPY_MODEL_80a2438ecc2b4547a8880a2c9cf79f11"
      }
     },
     "3f6a74cbbaaa4a89b1b3d31481b5a963": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_e8270e6d857540d3ab604e9bbf72fe2d",
        "IPY_MODEL_446fc61b9f5048cb85c7869ecfb5f871",
        "IPY_MODEL_4dfcde38529f48e0a8f6f2be5e5528d3",
        "IPY_MODEL_a41a46a36df848b780a49dd818e1ce28"
       ],
       "layout": "IPY_MODEL_7ae31f1a09014a1fa0e1de2a17e37209"
      }
     },
     "3f6c4c1500e84e2bad3628ac77d18681": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "3fbf3b5abe174e8cba43bf9b9e25b936": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "402fa43ccafb4f8a8361b9f22df8e577": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "404b709dd2474e9eb55554bd16a8e379": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_4bc88614fb43446aa5471cbe27f715a7",
        "IPY_MODEL_ae0fafc35d404745a80bc3f85d846e3c",
        "IPY_MODEL_6189e10d66df48cc9570ccc82c1cdc04",
        "IPY_MODEL_e6bc7de25004458394c099a65fd0ef3c"
       ],
       "layout": "IPY_MODEL_1d1d2c0502e84d6195b84ee8326b3bf1"
      }
     },
     "40c1d1d51e0c477eaa3e5f05c165910f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Compute",
       "layout": "IPY_MODEL_6e884f90398944ce9e49ba1ab490ae13",
       "style": "IPY_MODEL_0068f0aa89b64904a484054fc36e252f",
       "tooltip": "Automatic definition of integrals"
      }
     },
     "40dc53c684c4472bbdf64259a7f8c5cd": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "4229f086c9c24d79bd84b703ffc4d68b": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "4290232627f4410fbf3d4300aa183ac2": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "429f1d38bc624883a63c10a77099ca5d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "display": "none",
       "width": "auto"
      }
     },
     "43a1ef0abb3d4fa992642b191822becd": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Add",
       "layout": "IPY_MODEL_6e884f90398944ce9e49ba1ab490ae13",
       "style": "IPY_MODEL_cfc92761bbcc447e8917df36e1b7f84e",
       "tooltip": "Add an entry from current zoom"
      }
     },
     "444cd60da12648178ed69db5bedfb682": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "446fc61b9f5048cb85c7869ecfb5f871": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "layout": "IPY_MODEL_78a116a286014fd5a7b3dc7dd43f2ded",
       "max": 10,
       "min": 0.1,
       "step": 0.05,
       "style": "IPY_MODEL_96bb51f9800e4ca8867c2e56639c1d73",
       "value": 0.5
      }
     },
     "44a18c305716419c9fc863ffc4e66ffa": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "44a62ff156a8484c86bd7510f86ca7b7": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "_current_action": "zoom",
       "layout": "IPY_MODEL_9ec4324c141044dd989f8b1d2e1beac0",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "44db0206fba847b789f9fbb077d0d90f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "45431e2db3cd493284b80ee80a2fc57d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "455b9419a85f4315936bd5bfdfc73139": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "MPLCanvasModel",
      "state": {
       "_cursor": "default",
       "_figure_label": "Figure 3",
       "_height": 500,
       "_image_mode": "diff",
       "_message": "zoom rect",
       "_rubberband_y": 500,
       "_width": 1000,
       "layout": "IPY_MODEL_da9685a3d0bf4caca8fb77ac099c943d",
       "toolbar": "IPY_MODEL_44a62ff156a8484c86bd7510f86ca7b7",
       "toolbar_position": "left"
      }
     },
     "472ef9796bd8446db39c4a111b758733": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "482d106950db4187a96865a88b31cf81": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_ba700805d58c42919a1f233256c03c7f",
        "IPY_MODEL_2312009322ae4e3b922df45e2aeccc8d",
        "IPY_MODEL_266ee4b752fc45d894b94aea0a3fd919",
        "IPY_MODEL_557cf3c2edc84b7dbb410d9efe414a1e"
       ],
       "layout": "IPY_MODEL_b54836b0931a433698f7e5612848b2a7"
      }
     },
     "48ffca90df1b472a917f75f4c24023b0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "4a2d8e3ef4a7483ca7d0008d06f91fbd": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_09ac6d48b8334b7589c4f0760982cacc",
        "IPY_MODEL_534c906ee5eb4c31b6f7a6d70bc66831",
        "IPY_MODEL_9a78167770ae4a2db1bd61604c05ac6e",
        "IPY_MODEL_171f6c3aed3e4b7f8c5c491db40cd51e",
        "IPY_MODEL_6953e94100ae4b7d96c8e8e6c13e0a38"
       ],
       "layout": "IPY_MODEL_64501473dfa24262b3d25edd28b59e1b"
      }
     },
     "4adad186faf447f4a6da684809a9547b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "layout": "IPY_MODEL_30689cf235a5493195a173b58c8fc001",
       "step": null,
       "style": "IPY_MODEL_2142da298cd4480282c532b43838b8c3"
      }
     },
     "4b0508b49e894e1ba6a87239e57f67e3": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "4b54ddd705274ccbae82a998e01cb82e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "4bc88614fb43446aa5471cbe27f715a7": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Done",
       "layout": "IPY_MODEL_58b6249fb5214aa1b133621980483b00",
       "style": "IPY_MODEL_1183e720e3d24c8caf8b95b2d4c197fb"
      }
     },
     "4bffb22c92414876a0b4a0219a5509e3": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "4ccd2c50e75b4a45841d25478cb73bf6": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "4dfcde38529f48e0a8f6f2be5e5528d3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_fb053362d0534c0cb724078a5465708f",
       "style": "IPY_MODEL_55373e1fd49b4678b68d34d44b2e9674",
       "value": "offset:"
      }
     },
     "4f5876ff8e464025a2e9810e10423339": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "10%"
      }
     },
     "4fe81dd3a12b42db9feb2647f6ee248d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "up",
        "down",
        "off"
       ],
       "index": 2,
       "layout": "IPY_MODEL_02c5670517f045df8ab59cb5f9f44ef2",
       "style": "IPY_MODEL_2b5995cea4394d7e834256c23e9773ed"
      }
     },
     "500debc2a0ae454ebe7ff4c28aae0fbe": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_0da3b58fd8bc446aa568f2e0ddd04a39",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "503fd24def8543f09a5b2419a5a0f3db": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "30%"
      }
     },
     "50ad0de35d8f4412a29a1186cf10ec53": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "_current_action": "zoom",
       "layout": "IPY_MODEL_bf8b1047bf8b4a9cb13f36ee34eb3ff3",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "50fb7a377e7e43d9911dd2838d664d7e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "50ff71276b164c8b8a48f692392d4396": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "51244b4357144021b81dfaeda42c6177": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "512d26d2e66c40aaaecf569b7bffe5a5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "auto"
      }
     },
     "5145ac49dc8e48489e3d3c0b88775d7f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "warning",
       "description": "Cancel",
       "layout": "IPY_MODEL_600210018dc347ecb928ed50ecd8f06c",
       "style": "IPY_MODEL_50ff71276b164c8b8a48f692392d4396"
      }
     },
     "5160b456c485411da7ab4989964af26b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "51dea7832ee141d2acfe53e93ace5e6b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_dbc48968702544f6b636ba2dfca6a2c7",
        "IPY_MODEL_aa96f7bd735c47ee8483477ebf111517",
        "IPY_MODEL_28173aaa92c04140a6d5aaaf3c849012",
        "IPY_MODEL_fa5f84523af244f080777014f33f5841"
       ],
       "layout": "IPY_MODEL_60f2f677a4044ab9a642592f9b66669a"
      }
     },
     "52648a9ca40c4c0ead1cf0f3bba4107d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_1f60f94342f84a4f988531ce0051276e",
        "IPY_MODEL_b8b3e8ea05104c588cae8407e603783a",
        "IPY_MODEL_a51c5561bfb046399685252bec764de7",
        "IPY_MODEL_6fd921b5a52341c5918c631b5c2ff51e",
        "IPY_MODEL_dd16d12961ee41a9abbe7af59a86f23e"
       ],
       "layout": "IPY_MODEL_0cec88999059442e8ab6902a8990b847"
      }
     },
     "534c906ee5eb4c31b6f7a6d70bc66831": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_dd019363291f40fdb9ed21e4afc05713",
       "style": "IPY_MODEL_b61895bb30b84327a90c0c79715cae73",
       "value": "None"
      }
     },
     "53f443e1b3774010be2d5648c816a2f8": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "54d3a8b16c094f93af13ef8ada3cd64a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "55373e1fd49b4678b68d34d44b2e9674": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "557cf3c2edc84b7dbb410d9efe414a1e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Done",
       "layout": "IPY_MODEL_e308804a1a6040cda772b52c127a421d",
       "style": "IPY_MODEL_402fa43ccafb4f8a8361b9f22df8e577"
      }
     },
     "570ee511cd7848869d1eaede2a9e0ca1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "20%"
      }
     },
     "583e87a74a4f4579801fc8cd233e3644": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "58b3f958e2b54bfeacfaa7ae2ec1f316": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_9e6f35a6f1094a87bc1c908e88eb9177",
        "IPY_MODEL_fe597743545f4e7fa3856db25cab2ae5",
        "IPY_MODEL_c3b91d8b5d30466d89258c1acc253cc2",
        "IPY_MODEL_0018c3406ea340e7bfa8d990f42da727"
       ],
       "layout": "IPY_MODEL_f7e01043c17645699bbfaaf9a0ab78cc"
      }
     },
     "58b6249fb5214aa1b133621980483b00": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "59433d2a171d45e78c211cb764d513e2": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "59fadfb25a844ff1a31d653e07e1332f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_6e884f90398944ce9e49ba1ab490ae13",
       "style": "IPY_MODEL_9f164acf521948b2b9229f3ed1b4cdad",
       "value": "&nbsp;"
      }
     },
     "5bf2b8aa21444924b2b35beb91f0194a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "5c2c25aad1c84d56908f8a595b2b8cba": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "5c885653c24c4633b4165b4f3b662cf7": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "100%"
      }
     },
     "5ce53c81c4b1458ca99fc766f51b27ca": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "5d121360acf342b8976766d767c03bf6": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_955390d3d9c546acaff5a8f36c531e35",
       "style": "IPY_MODEL_5160b456c485411da7ab4989964af26b",
       "value": "Choose an integral for calibration"
      }
     },
     "5d5fccf3094e4689988e0ec03e034937": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_bee2846a351b4ba4bf5a6efcb94a6635",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "5d8476b42f5e4f66af053f3b4d55f0f4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_6cb4c62ed9eb4496b545367cf9bfc796",
        "IPY_MODEL_d001487b37344806aac005b33ed11465",
        "IPY_MODEL_c1582ef155774f0e95d1cd0d511ad3c0",
        "IPY_MODEL_d6c4bde1038641f9abdfeeb03ad5c6ae",
        "IPY_MODEL_4fe81dd3a12b42db9feb2647f6ee248d"
       ],
       "layout": "IPY_MODEL_05331af6be00451687585d553a710b38"
      }
     },
     "5e15622f64c847c9a3f20b787913e66c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_40c1d1d51e0c477eaa3e5f05c165910f",
        "IPY_MODEL_d6f2dd7662cc4332b74874a36e8a9307"
       ],
       "layout": "IPY_MODEL_208d10cfe7ae46babfb48cd96f477aaa"
      }
     },
     "5ea52031d73b404b990705bc8a36c540": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "5f26653a6e88403eab9a2e2f13b06dfd": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "5f3341c9ef0e404b898938b5cd92c64d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "5f43bbe77a7b4133812ac5bb55c4b38d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "auto"
      }
     },
     "5f4858b987a34694be6064366fc92b4d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Set",
       "layout": "IPY_MODEL_c10c1060cb28452a8728bdbf71c84f73",
       "style": "IPY_MODEL_c9d9d7f66fb443f9983dee117e759d43"
      }
     },
     "5f99c3376a5d4ef5a1b09f0ae2cf5ae4": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "30%"
      }
     },
     "600210018dc347ecb928ed50ecd8f06c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "6089c9684c104ed083e563a27ed4f0e9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "60ab0803ec86431e8cd0145eeb0dfd14": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "60f2f677a4044ab9a642592f9b66669a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "6115b9d259cc4134abdb5bb9ec57f918": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "622d737505ce4570a765e576f9163727": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "624b88aaa2bc4e058e79080295f6797f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "63118efb1b5848bf8d0860fd65d6e210": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "40em"
      }
     },
     "634797bd89b44eccab0dbd323ca16d11": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "6391ed63e88e461d9ab699680a7fc16d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "border": "1px solid red"
      }
     },
     "63e605d3dd3040f980552466f8d615bb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "64284de98b9e420caece01ae8421731e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "64501473dfa24262b3d25edd28b59e1b": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "64b52ca3c98b4c45886a925a4a157015": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "654d965c327943fab741396f4eb431f2": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_21c62f98c8f14bcab2a4031c8248dd6a",
       "style": "IPY_MODEL_f78a9569829944c8a4fbffb184dd9ef3",
       "value": "None"
      }
     },
     "664006c5444a42a4ad7ac08d7764dbd6": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "66d425db38d447b2960083e3ecf23811": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_6089c9684c104ed083e563a27ed4f0e9",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "6758deb064c74bb486c62ccb01d7cd71": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "6779fe82a6314ae48e466219a3c310d0": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "15%"
      }
     },
     "6953e94100ae4b7d96c8e8e6c13e0a38": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "up",
        "down",
        "off"
       ],
       "index": 2,
       "layout": "IPY_MODEL_a13b55abd59443af9740be61561087d8",
       "style": "IPY_MODEL_eb59d632c3da4521b11ed4d491943038"
      }
     },
     "699b6e3394d24b5e8cd299981904cda1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "warning",
       "description": "Cancel",
       "layout": "IPY_MODEL_429f1d38bc624883a63c10a77099ca5d",
       "style": "IPY_MODEL_2773834bb19c45c9a8fbe119c525b48a"
      }
     },
     "69c8a4dd3b4745d7ad30d9c1d1ad19d3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "black",
        "red",
        "blue",
        "green",
        "orange",
        "blueviolet",
        "crimson",
        "turquoise",
        "indigo",
        "magenta",
        "gold",
        "pink",
        "purple",
        "salmon",
        "darkblue",
        "sienna"
       ],
       "index": 9,
       "layout": "IPY_MODEL_3a192f0a1d3b4d5086d36a0624e7709d",
       "style": "IPY_MODEL_472ef9796bd8446db39c4a111b758733"
      }
     },
     "69cc9ea696524704a1fa0b3bde7f9b01": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "100%"
      }
     },
     "6a5bbab925c540dabe0b939f7dcfbf51": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "6b69025d5c5f4448885a5c6f358546fc": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "6cb4c62ed9eb4496b545367cf9bfc796": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_2f34395d13e54acf8db2bf6f21bba5a8",
       "style": "IPY_MODEL_ee59b1fd64724d238d58fdd768369807",
       "value": "<b>4</b>"
      }
     },
     "6d39be62597a41f9b039581a32469ff4": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "6e0a72db313a41bb8a980d38e39166ca": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "6e14ea2fb0bb470db126ad773aaeb94f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "6e884f90398944ce9e49ba1ab490ae13": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "6e8f9e30939e47aa8539bb7fdba4eec5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "6f6a6a5111f54a898997a1d8fd0e1d78": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "6fd921b5a52341c5918c631b5c2ff51e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatLogSliderModel",
      "state": {
       "continuous_update": false,
       "layout": "IPY_MODEL_b0eb61b9e22a4d3fb9535726bf4c1d81",
       "max": 2,
       "min": -1,
       "readout_format": ".2f",
       "step": 0.01,
       "style": "IPY_MODEL_cac7e99e5ab046e686f1d96bfd7a71f0",
       "value": 0.20892961308540392
      }
     },
     "703f91e7eb77477d9b5b3ad3f9f88247": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "40em"
      }
     },
     "70b765a01c7144cfa187789bc49c95c5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "height": "10.16cm",
       "width": "80px"
      }
     },
     "70fc0371b5934b57b71b0d07182da0e9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "display": "none",
       "grid_gap": "0px 0px",
       "grid_template_areas": "\n                    'pathlist filename'\n                    'dircontent dircontent'\n                    ",
       "grid_template_columns": "60% 40%",
       "grid_template_rows": "auto auto",
       "width": "500px"
      }
     },
     "711ddce44b5341fbb849239190ffb3eb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_703f91e7eb77477d9b5b3ad3f9f88247",
       "style": "IPY_MODEL_5bf2b8aa21444924b2b35beb91f0194a",
       "value": "None"
      }
     },
     "7144950c03434de39be6deb7c73a3861": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "720266e38174468cad374c0e931f8f73": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "15%"
      }
     },
     "738e9a41d5a64c54a365c939f22c44ec": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "73c9126568cc4dbabd20fc69432e366f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "742e148428214f718bd1c7d23368a8ff": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "74a6b026cf2b402ab2615b3821e83edf": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SelectModel",
      "state": {
       "_options_labels": [
        "..",
        "pdata",
        "acqu",
        "acqus",
        "audita.txt",
        "fid",
        "format.temp",
        "processed.gs1",
        "pulseprogram",
        "scon2",
        "shimvalues",
        "uxnmr.par"
       ],
       "index": 5,
       "layout": "IPY_MODEL_94bdc8043e9a4bdfa3337cd8d869e8ea",
       "rows": 8,
       "style": "IPY_MODEL_3fbf3b5abe174e8cba43bf9b9e25b936"
      }
     },
     "74c28c98fe584f36b0de66f1cd86adba": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Change",
       "layout": "IPY_MODEL_5f43bbe77a7b4133812ac5bb55c4b38d",
       "style": "IPY_MODEL_ffea2bd2d6414610826e691267dc853c"
      }
     },
     "75ebac3e976f4f08b5ce22a3787771b2": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "75f550bf43f244d7859216ec50de3633": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "76312298b31c4ae59222cc2b41e13aa3": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "767c69348b41414da4107293ba51cd0c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_adb9caaa5fc3433f9be3f146b6de5757",
        "IPY_MODEL_b857d40a36e345b9a672d6ff64d4af55"
       ],
       "layout": "IPY_MODEL_d6be33e9d6154a7186e11e047141992e"
      }
     },
     "76cc28d6723844cd89ab839b4d91f05d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "76dd7c93fe284c8182dc3fea0b1756d5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "7777a9ba606c41ec9fe62a095445bae5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "777eb10335484350ac8fffb47fd05ac3": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "77fc443050bd4252ad603745f77e4757": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "40em"
      }
     },
     "78a116a286014fd5a7b3dc7dd43f2ded": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "20%"
      }
     },
     "79b908da4e5b47dc8b05f3017af41b9b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_ba700805d58c42919a1f233256c03c7f",
        "IPY_MODEL_2312009322ae4e3b922df45e2aeccc8d",
        "IPY_MODEL_266ee4b752fc45d894b94aea0a3fd919"
       ],
       "layout": "IPY_MODEL_6b69025d5c5f4448885a5c6f358546fc"
      }
     },
     "7ad80cd723d2440f859ba1a4cf5924b4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "7ae31f1a09014a1fa0e1de2a17e37209": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "7b076b13f9754c82b150030e59e4d30d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "7b07fdcb03cc43759c5281301639eee4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_3f6a74cbbaaa4a89b1b3d31481b5a963",
        "IPY_MODEL_51dea7832ee141d2acfe53e93ace5e6b",
        "IPY_MODEL_39a52c607165496f86fbc2bedbbbc060"
       ],
       "layout": "IPY_MODEL_b3229f0f360f4ab089d85d62a24d9268"
      }
     },
     "7be27f1286c043bc8fce7fc3e5623149": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_59fadfb25a844ff1a31d653e07e1332f",
        "IPY_MODEL_a37083c33c5e4b9b9de86cdf5112e381",
        "IPY_MODEL_cca613eaf3e3418685f2f46812408f86"
       ],
       "layout": "IPY_MODEL_f47fc024ec014621a8a0ee101e3892a1"
      }
     },
     "7c3a76083f5b4c84a83fe3fa4d22037d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "7d2590c01c81476bb1ce0757799083f4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "layout": "IPY_MODEL_e78e7ffa06b3480593c327f2b0e84366",
       "step": null,
       "style": "IPY_MODEL_cee16a6a026f4b55b84f458faa6f1042"
      }
     },
     "7d52036388cd4b489a9d7b57f1bc8bcb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_36c8b2ad13fd4b09947e8a37501cf378",
       "placeholder": "",
       "style": "IPY_MODEL_2bc236dbae824995917c060f9b8f709f",
       "value": "<span style=\"margin-left:10px; color:orange;\">/DATA/SM_ARTE_v3/ARTEref_161123/1/fid</span>"
      }
     },
     "7d71afb0752740b2b0fa8d7b089a9826": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "auto"
      }
     },
     "7e2557b75d384a4c8c5693b06db899d1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_aee850ebb11741d6b5415abdaadc3562",
        "IPY_MODEL_455b9419a85f4315936bd5bfdfc73139"
       ],
       "layout": "IPY_MODEL_29d47967d9134eb4a94671c396f3c5af"
      }
     },
     "7e771c9b16584306b61aaf778063b14f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_d15383248e574ffda6da7b3b73dfd22d",
        "IPY_MODEL_c5bc8cba8c5d40ec90288ecf9c9556ed"
       ],
       "layout": "IPY_MODEL_3dfb46fcae944119bae41faa3aab0e74"
      }
     },
     "7e9c489b5c974e899f7423335d0890e7": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "7fa0c872f37149bf9e34040fa51b11fc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "black",
        "red",
        "blue",
        "green",
        "orange",
        "blueviolet",
        "crimson",
        "turquoise",
        "indigo",
        "magenta",
        "gold",
        "pink",
        "purple",
        "salmon",
        "darkblue",
        "sienna"
       ],
       "index": 1,
       "layout": "IPY_MODEL_4bffb22c92414876a0b4a0219a5509e3",
       "style": "IPY_MODEL_fa9303cfb55f4e47972800fdef9b3c6e"
      }
     },
     "80a2438ecc2b4547a8880a2c9cf79f11": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "display": "none",
       "grid_gap": "0px 0px",
       "grid_template_areas": "\n                    'pathlist filename'\n                    'dircontent dircontent'\n                    ",
       "grid_template_columns": "60% 40%",
       "grid_template_rows": "auto auto",
       "width": "500px"
      }
     },
     "812f5b748fd84209861d17df3e52a5ce": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "815c2377680842ec8e7cfc30bb54f486": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "auto"
      }
     },
     "81f0840efa2a4c5292109afb1f72973c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "dircontent",
       "width": "auto"
      }
     },
     "820da354f8974686a3eae3d5ffa79ba9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "up",
        "down",
        "off"
       ],
       "index": 2,
       "layout": "IPY_MODEL_59433d2a171d45e78c211cb764d513e2",
       "style": "IPY_MODEL_d843bd87cc42493085a635a5adae22c6"
      }
     },
     "823b118e6a3148b59694b0d221d3eddd": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_a993019dc3d641a9acd25c3d946b91b9",
        "IPY_MODEL_fb4ce1a2829a4944962869f0bfec06a6"
       ],
       "layout": "IPY_MODEL_0094485db9da4177ad4da8d797c6ec12"
      }
     },
     "839f780f8cce43dfae17db3a6bb94333": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_f450dea406df4273beb577062ffcc46a",
        "IPY_MODEL_654d965c327943fab741396f4eb431f2",
        "IPY_MODEL_08a5aa2a47134762ae8b0c15497abfca",
        "IPY_MODEL_917adb0b4e01486895755e372d11545a",
        "IPY_MODEL_ce6738e53ebc487eaf7e614ec56a7330"
       ],
       "layout": "IPY_MODEL_6115b9d259cc4134abdb5bb9ec57f918"
      }
     },
     "85c62aec68c442ecbf35cf2db560abe2": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "85dfa2e111b9455c9963b0c58cf63a22": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "86a65b8dd61d4f6a9c3a78b8057e32df": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "MPLCanvasModel",
      "state": {
       "_figure_label": "Figure 5",
       "_height": 500,
       "_image_mode": "diff",
       "_width": 1000,
       "layout": "IPY_MODEL_c7f8d47aa1fa4f91b2be7805282f1935",
       "toolbar": "IPY_MODEL_5d5fccf3094e4689988e0ec03e034937",
       "toolbar_position": "left"
      }
     },
     "86f55627a8f14ca5ab84c2e25baa8de9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "87ada72f739f48559703b719208962cb": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "8945586a14164d0ba69aff708c04d1ac": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_977124a4f0d042f7ba367f40454ec89b",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "89a0077d64f345158688219e00f3c9c9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "info",
       "description": "Copy",
       "layout": "IPY_MODEL_385ef4626b2c42e9a393f21aef47b6ed",
       "style": "IPY_MODEL_b31262acc4ff4d83858cc921d8e31230",
       "tooltip": "copy selected data-set to entry below"
      }
     },
     "8a3ce06047334fb1bb8d4d3b52a0bbd6": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_123325aab81d4a6eae997e8128d351ab",
        "IPY_MODEL_313b723fb332451bb7f1478bbc6595e5",
        "IPY_MODEL_7d2590c01c81476bb1ce0757799083f4",
        "IPY_MODEL_d03f91a643c54e61bbfb985022a9030c",
        "IPY_MODEL_bf4b1b08549c4b5da5ec9fe078e9e447"
       ],
       "layout": "IPY_MODEL_bc27e3b22b3e42e684e609a9ce5db6b1"
      }
     },
     "8acb8361d1a947aa8dd91c80da0ed544": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Print",
       "layout": "IPY_MODEL_6e884f90398944ce9e49ba1ab490ae13",
       "style": "IPY_MODEL_b0e5a24c36864f7083594357acf1aa99",
       "tooltip": "Print to screen"
      }
     },
     "8ae2ce461cf64607a2d023d96ba41f8f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "description": "calibration",
       "disabled": true,
       "layout": "IPY_MODEL_f2b1ecc005184d6a993c0bd0f1c6fc38",
       "step": 0.001,
       "style": "IPY_MODEL_2385d32c890f49398bb822f9e385442c"
      }
     },
     "8b997e15cf654007ad1b16ad8270d426": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_75f550bf43f244d7859216ec50de3633",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "8bc95cae32f54bbcb977119728b36b06": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "8bda77d9f3334138a57172adb65bf9f0": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "8c09d7e004224455bc2cfb6e60e9c900": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Set",
       "layout": "IPY_MODEL_4f5876ff8e464025a2e9810e10423339",
       "style": "IPY_MODEL_8d4e9abef33c4c4680e7046cd22e7bb3",
       "tooltip": "Set spectrum calibration"
      }
     },
     "8c2897ad0a6e4d728ad1930b763fc301": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "8d4e9abef33c4c4680e7046cd22e7bb3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "8d64f50fc2e04cb1b8a1e35a101390ee": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "8d7d3e3f58ee49179b1b8eb0c90a55a1": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_b75f1c40dd574f08884fb194080bea1f",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "8e0708b497f74ad895ddc841787e8472": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_58b6249fb5214aa1b133621980483b00",
       "style": "IPY_MODEL_c1f3fb249db346329ac686cb1b923e32",
       "value": "&nbsp;"
      }
     },
     "8e2c28cedc9e41d3bf99c3fcf13fb8f3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "8e7fbc3bb8804a788dfe2a4d9285c8d9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_243995574dcc4a9881f724b63aaf58b7",
       "placeholder": "",
       "style": "IPY_MODEL_9df933caf22942aca7e2f6bb3e5c6b6e",
       "value": "<span style=\"margin-left:10px; color:black;\">No file selected</span>"
      }
     },
     "8f66c3eb7d1843cf9c5ac512e8a1ff06": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "15%"
      }
     },
     "9019956d73c0470aa9480d96c76c5e04": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "9144f99157f3428b9734e2c2907cf884": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "auto"
      }
     },
     "917adb0b4e01486895755e372d11545a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "black",
        "red",
        "blue",
        "green",
        "orange",
        "blueviolet",
        "crimson",
        "turquoise",
        "indigo",
        "magenta",
        "gold",
        "pink",
        "purple",
        "salmon",
        "darkblue",
        "sienna"
       ],
       "index": 3,
       "layout": "IPY_MODEL_9dc741bd41314bcfbd4f09efcc79034c",
       "style": "IPY_MODEL_304a8e5cdf0c43b69301a70a985a2ca8"
      }
     },
     "91cec237e2a348749be14cd62c40f1a6": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "91d8e532638944309ded3e54f41ad1db": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_63118efb1b5848bf8d0860fd65d6e210",
       "style": "IPY_MODEL_1c2a8e2939c0498484d9845e17c61a23",
       "value": "None"
      }
     },
     "921ea8f6ecc94442a51a76fa90639c8e": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "MPLCanvasModel",
      "state": {
       "_cursor": "default",
       "_figure_label": "Figure 7",
       "_height": 500,
       "_image_mode": "diff",
       "_message": "zoom rect",
       "_rubberband_y": 500,
       "_width": 1000,
       "layout": "IPY_MODEL_c5bed30fb0c64a6d96d22babc4d2c60c",
       "toolbar": "IPY_MODEL_50ad0de35d8f4412a29a1186cf10ec53",
       "toolbar_position": "left"
      }
     },
     "93f8b360ed8b45a2a18b7e7f12fe8cbd": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "height": "10.16cm",
       "width": "80px"
      }
     },
     "94bdc8043e9a4bdfa3337cd8d869e8ea": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "dircontent",
       "width": "auto"
      }
     },
     "955390d3d9c546acaff5a8f36c531e35": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "95d6c20674844c00a01105d3c7ebfab7": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_f6533e8c04ae46fa9a6099f6006324b0",
       "style": "IPY_MODEL_0874d82e408f49da80172dd4ddacfc77",
       "value": "None"
      }
     },
     "96bb51f9800e4ca8867c2e56639c1d73": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "977124a4f0d042f7ba367f40454ec89b": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "983e405fc5924eaf9ae23984274423b7": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "983e71c9738940b58f0204dd841b0fe9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_3f57e226c06d41029b45cd966016fe0d",
        "IPY_MODEL_e42f702cfe814aeb81dbb42274890537"
       ],
       "layout": "IPY_MODEL_0c441325b0c5469a89da4f4f34b37920"
      }
     },
     "98c9751a182f46fabaa32d5d33baed31": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "99ecb8cba7a0441aa7b5af63a6234c85": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "9a78167770ae4a2db1bd61604c05ac6e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "layout": "IPY_MODEL_a1dfe37fa71d4ba5a9672f278e456c80",
       "step": null,
       "style": "IPY_MODEL_a62b2100eee44094a71bca97031f35f5"
      }
     },
     "9aa60213a02d45f0abc3bff501c242f8": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "9accd7e782874349a946a168e561cf33": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "9b2c47c928104abaac69ffe1afe2272b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "9b965bb80cbb43fcaa08d573fc2c1086": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "MPLCanvasModel",
      "state": {
       "_figure_label": "Figure 1",
       "_height": 480,
       "_image_mode": "diff",
       "_message": "x=0.968385     y=25697.7     ",
       "_width": 640,
       "layout": "IPY_MODEL_53f443e1b3774010be2d5648c816a2f8",
       "toolbar": "IPY_MODEL_be89fcbd61ab428a912dbe33fabc3ced",
       "toolbar_position": "left"
      }
     },
     "9ced57391f5d42d08264b35845ff7fe5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "filename",
       "width": "auto"
      }
     },
     "9d384ab2f333416883bbcf3e8debab85": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "9da015e1f2c044a48bc8982e17bfed41": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "IntTextModel",
      "state": {
       "description": "Entry",
       "layout": "IPY_MODEL_c20384acd1354015b9f231b52418522a",
       "step": 1,
       "style": "IPY_MODEL_1b9cee1849b74fbebfa390d0134a23a0",
       "value": 28
      }
     },
     "9dc741bd41314bcfbd4f09efcc79034c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "9df933caf22942aca7e2f6bb3e5c6b6e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "9e6f35a6f1094a87bc1c908e88eb9177": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_385ef4626b2c42e9a393f21aef47b6ed",
       "style": "IPY_MODEL_2c13d392a32a458794203e270b9e34ed",
       "value": "&nbsp;"
      }
     },
     "9ec4324c141044dd989f8b1d2e1beac0": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "9f164acf521948b2b9229f3ed1b4cdad": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "9fd56529c6f34ab491458405f7357928": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "a0857ad006e84dc8a8bc549eb63f2978": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "a0a5110f589a4b2583c33df547fee997": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_8e0708b497f74ad895ddc841787e8472",
        "IPY_MODEL_abe9d41e2ab6471ea4d9d1397130fae6",
        "IPY_MODEL_d7c311eec4de483189842e51ad622809",
        "IPY_MODEL_4bc88614fb43446aa5471cbe27f715a7"
       ],
       "layout": "IPY_MODEL_f0343ccdbeca43a980b1da356c14bb0c"
      }
     },
     "a11b5777c45c408f8d61f1ec3c5d6390": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "a13b55abd59443af9740be61561087d8": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "a1bf2000ce1741f2bf11ae39046a6380": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_3638a154558446dd9f97d58dc923018f",
       "style": "IPY_MODEL_99ecb8cba7a0441aa7b5af63a6234c85",
       "value": "None"
      }
     },
     "a1dfe37fa71d4ba5a9672f278e456c80": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "a21f7d18335d49f59c983645d850c1ec": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "auto"
      }
     },
     "a278abf75d7b4138a96903799c0e3214": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "pathlist",
       "width": "auto"
      }
     },
     "a2da8d71197f4a27b2f5a82ce7e2c5a1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "a2e31c34eabb454ca769813382decf65": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_ec23e43c23294b448734fdac6cb0971e",
        "IPY_MODEL_bf1c0ea678444cceae298da19f0c79bc"
       ],
       "layout": "IPY_MODEL_d230168c012941aea0517924455d3df9"
      }
     },
     "a37083c33c5e4b9b9de86cdf5112e381": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Reset",
       "layout": "IPY_MODEL_6e884f90398944ce9e49ba1ab490ae13",
       "style": "IPY_MODEL_bb6c2a7aa3f849838eaea8ec8823c12d",
       "tooltip": "Reset to full spectrum"
      }
     },
     "a3d53f2e2bd743daacfefa6f53612fd2": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_74c28c98fe584f36b0de66f1cd86adba",
        "IPY_MODEL_0cc7b968bd3e4fe4920ffafdaee95752",
        "IPY_MODEL_7d52036388cd4b489a9d7b57f1bc8bcb"
       ],
       "layout": "IPY_MODEL_815c2377680842ec8e7cfc30bb54f486"
      }
     },
     "a41a46a36df848b780a49dd818e1ce28": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "layout": "IPY_MODEL_07af52ce85bb4825b891292050421b52",
       "max": 1,
       "step": 0.01,
       "style": "IPY_MODEL_c0a5b3fca1224f6caed8ef2adeeafa01",
       "value": 0.3
      }
     },
     "a4bfa1b108d54a72bee3b35a664077e6": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "10%"
      }
     },
     "a51c5561bfb046399685252bec764de7": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_64284de98b9e420caece01ae8421731e",
       "style": "IPY_MODEL_13bee2a5efb9416e99c7640629a42d1d",
       "value": "threshold - % largest signal"
      }
     },
     "a5e0595ba5934f1d8200a64def6c29ff": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "a62b2100eee44094a71bca97031f35f5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "a6749a1d93924f4f8d1c9df91a2edb70": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_983e71c9738940b58f0204dd841b0fe9",
        "IPY_MODEL_89a0077d64f345158688219e00f3c9c9",
        "IPY_MODEL_d86f5b0e90564de0b55874b3e2c0ca1f"
       ],
       "layout": "IPY_MODEL_de2a2ae09165461bb4f6f2ce16c74f5f"
      }
     },
     "a7838ba1abe7438b91bce89489fa5d56": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_6391ed63e88e461d9ab699680a7fc16d",
       "outputs": [
        {
         "data": {
          "text/html": "<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Label</th>\n      <th>Position</th>\n      <th>Intensity</th>\n      <th>Width</th>\n    </tr>\n    <tr>\n      <th>Id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>5.3484</td>\n      <td>5.348360</td>\n      <td>4.348596e+04</td>\n      <td>4.606094</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>5.3417</td>\n      <td>5.341734</td>\n      <td>7.184966e+04</td>\n      <td>3.681060</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>5.3350</td>\n      <td>5.334997</td>\n      <td>4.189486e+04</td>\n      <td>5.340791</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>5.3177</td>\n      <td>5.317748</td>\n      <td>4.330909e+04</td>\n      <td>10.476216</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5.3131</td>\n      <td>5.313059</td>\n      <td>4.600839e+04</td>\n      <td>8.606673</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>5.3096</td>\n      <td>5.309587</td>\n      <td>4.310497e+04</td>\n      <td>26.336539</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>4.8816</td>\n      <td>4.881613</td>\n      <td>1.955067e+07</td>\n      <td>5.548722</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>4.7664</td>\n      <td>4.766436</td>\n      <td>1.324085e+05</td>\n      <td>3.768584</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>4.7611</td>\n      <td>4.761119</td>\n      <td>1.250912e+05</td>\n      <td>3.683045</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>4.5023</td>\n      <td>4.502270</td>\n      <td>5.247387e+04</td>\n      <td>4.996311</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>4.4889</td>\n      <td>4.488909</td>\n      <td>4.509191e+04</td>\n      <td>5.877753</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>4.4851</td>\n      <td>4.485082</td>\n      <td>5.876138e+04</td>\n      <td>5.066126</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>4.2025</td>\n      <td>4.202507</td>\n      <td>7.245457e+04</td>\n      <td>5.607799</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>4.1924</td>\n      <td>4.192449</td>\n      <td>7.816612e+04</td>\n      <td>4.575915</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>4.1850</td>\n      <td>4.185033</td>\n      <td>6.809884e+04</td>\n      <td>5.626519</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>4.1752</td>\n      <td>4.175162</td>\n      <td>6.741748e+04</td>\n      <td>4.845042</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>4.1071</td>\n      <td>4.107107</td>\n      <td>7.125682e+04</td>\n      <td>3.674085</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>4.0996</td>\n      <td>4.099596</td>\n      <td>7.938518e+04</td>\n      <td>3.493545</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>4.0917</td>\n      <td>4.091671</td>\n      <td>9.706022e+04</td>\n      <td>3.929852</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>4.0842</td>\n      <td>4.084230</td>\n      <td>1.152996e+05</td>\n      <td>3.674478</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>4.0705</td>\n      <td>4.070521</td>\n      <td>8.042869e+04</td>\n      <td>5.780534</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>4.0685</td>\n      <td>4.068491</td>\n      <td>7.661194e+04</td>\n      <td>10.233039</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>4.0574</td>\n      <td>4.057413</td>\n      <td>5.759074e+04</td>\n      <td>4.550022</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>4.0544</td>\n      <td>4.054421</td>\n      <td>4.921771e+04</td>\n      <td>4.995492</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>4.0035</td>\n      <td>4.003505</td>\n      <td>4.182722e+04</td>\n      <td>7.781900</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>3.9990</td>\n      <td>3.999030</td>\n      <td>4.751163e+04</td>\n      <td>7.326429</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>3.8910</td>\n      <td>3.891021</td>\n      <td>4.351407e+04</td>\n      <td>7.074809</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>3.8382</td>\n      <td>3.838174</td>\n      <td>4.285607e+04</td>\n      <td>6.030011</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>3.8359</td>\n      <td>3.835928</td>\n      <td>4.407221e+04</td>\n      <td>5.429410</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>3.8251</td>\n      <td>3.825104</td>\n      <td>5.257572e+04</td>\n      <td>5.613489</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>3.8235</td>\n      <td>3.823464</td>\n      <td>5.047226e+04</td>\n      <td>7.739030</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td>3.8106</td>\n      <td>3.810645</td>\n      <td>1.185928e+06</td>\n      <td>2.976299</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>3.8051</td>\n      <td>3.805135</td>\n      <td>1.674566e+06</td>\n      <td>4.276308</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>3.8029</td>\n      <td>3.802942</td>\n      <td>1.533577e+06</td>\n      <td>5.648007</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>3.7946</td>\n      <td>3.794568</td>\n      <td>1.779503e+06</td>\n      <td>3.919826</td>\n    </tr>\n    <tr>\n      <th>35</th>\n      <td>3.7898</td>\n      <td>3.789775</td>\n      <td>2.304654e+06</td>\n      <td>3.851295</td>\n    </tr>\n    <tr>\n      <th>36</th>\n      <td>3.7784</td>\n      <td>3.778386</td>\n      <td>7.751989e+04</td>\n      <td>5.044158</td>\n    </tr>\n    <tr>\n      <th>37</th>\n      <td>3.7744</td>\n      <td>3.774437</td>\n      <td>6.176049e+04</td>\n      <td>9.414273</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td>3.7694</td>\n      <td>3.769424</td>\n      <td>7.338621e+04</td>\n      <td>3.975763</td>\n    </tr>\n    <tr>\n      <th>39</th>\n      <td>3.7637</td>\n      <td>3.763715</td>\n      <td>4.146346e+04</td>\n      <td>6.595297</td>\n    </tr>\n    <tr>\n      <th>40</th>\n      <td>3.7561</td>\n      <td>3.756071</td>\n      <td>4.250501e+04</td>\n      <td>5.263114</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td>3.7480</td>\n      <td>3.747999</td>\n      <td>4.698374e+04</td>\n      <td>12.278724</td>\n    </tr>\n    <tr>\n      <th>42</th>\n      <td>3.7459</td>\n      <td>3.745877</td>\n      <td>4.986263e+04</td>\n      <td>6.949779</td>\n    </tr>\n    <tr>\n      <th>43</th>\n      <td>3.7400</td>\n      <td>3.740026</td>\n      <td>5.382394e+04</td>\n      <td>10.694675</td>\n    </tr>\n    <tr>\n      <th>44</th>\n      <td>3.7340</td>\n      <td>3.733967</td>\n      <td>5.057539e+04</td>\n      <td>10.005332</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>3.7308</td>\n      <td>3.730783</td>\n      <td>5.385324e+04</td>\n      <td>14.453853</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>3.7260</td>\n      <td>3.726033</td>\n      <td>6.881352e+04</td>\n      <td>19.408770</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>3.7161</td>\n      <td>3.716062</td>\n      <td>5.555715e+05</td>\n      <td>3.547344</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>3.7104</td>\n      <td>3.710377</td>\n      <td>5.814861e+05</td>\n      <td>6.958847</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td>3.7079</td>\n      <td>3.707851</td>\n      <td>7.913386e+05</td>\n      <td>3.970163</td>\n    </tr>\n    <tr>\n      <th>50</th>\n      <td>3.7027</td>\n      <td>3.702714</td>\n      <td>7.600141e+05</td>\n      <td>4.794050</td>\n    </tr>\n    <tr>\n      <th>51</th>\n      <td>3.6998</td>\n      <td>3.699766</td>\n      <td>5.074084e+05</td>\n      <td>6.521486</td>\n    </tr>\n    <tr>\n      <th>52</th>\n      <td>3.6966</td>\n      <td>3.696634</td>\n      <td>6.053844e+05</td>\n      <td>3.988575</td>\n    </tr>\n    <tr>\n      <th>53</th>\n      <td>3.6912</td>\n      <td>3.691234</td>\n      <td>5.105433e+05</td>\n      <td>3.504669</td>\n    </tr>\n    <tr>\n      <th>54</th>\n      <td>3.6858</td>\n      <td>3.685772</td>\n      <td>7.675680e+04</td>\n      <td>5.885354</td>\n    </tr>\n    <tr>\n      <th>55</th>\n      <td>3.6797</td>\n      <td>3.679704</td>\n      <td>6.112833e+04</td>\n      <td>6.585968</td>\n    </tr>\n    <tr>\n      <th>56</th>\n      <td>3.6761</td>\n      <td>3.676087</td>\n      <td>4.648135e+04</td>\n      <td>8.843753</td>\n    </tr>\n    <tr>\n      <th>57</th>\n      <td>3.6692</td>\n      <td>3.669223</td>\n      <td>7.568534e+04</td>\n      <td>6.289796</td>\n    </tr>\n    <tr>\n      <th>58</th>\n      <td>3.6571</td>\n      <td>3.657149</td>\n      <td>1.433348e+06</td>\n      <td>3.000622</td>\n    </tr>\n    <tr>\n      <th>59</th>\n      <td>3.6488</td>\n      <td>3.648842</td>\n      <td>1.120141e+06</td>\n      <td>3.149115</td>\n    </tr>\n    <tr>\n      <th>60</th>\n      <td>3.6412</td>\n      <td>3.641152</td>\n      <td>1.173541e+06</td>\n      <td>3.026709</td>\n    </tr>\n    <tr>\n      <th>61</th>\n      <td>3.6329</td>\n      <td>3.632874</td>\n      <td>9.438731e+05</td>\n      <td>3.065920</td>\n    </tr>\n    <tr>\n      <th>62</th>\n      <td>3.6176</td>\n      <td>3.617601</td>\n      <td>8.321931e+04</td>\n      <td>3.665813</td>\n    </tr>\n    <tr>\n      <th>63</th>\n      <td>3.5840</td>\n      <td>3.584028</td>\n      <td>8.864343e+04</td>\n      <td>3.694766</td>\n    </tr>\n    <tr>\n      <th>64</th>\n      <td>3.5752</td>\n      <td>3.575199</td>\n      <td>8.361691e+04</td>\n      <td>4.042354</td>\n    </tr>\n    <tr>\n      <th>65</th>\n      <td>3.5688</td>\n      <td>3.568786</td>\n      <td>7.939370e+04</td>\n      <td>3.650313</td>\n    </tr>\n    <tr>\n      <th>66</th>\n      <td>3.5598</td>\n      <td>3.559790</td>\n      <td>7.108112e+04</td>\n      <td>3.851444</td>\n    </tr>\n    <tr>\n      <th>67</th>\n      <td>3.4478</td>\n      <td>3.447784</td>\n      <td>4.216393e+04</td>\n      <td>6.530202</td>\n    </tr>\n    <tr>\n      <th>68</th>\n      <td>3.4426</td>\n      <td>3.442608</td>\n      <td>4.510044e+04</td>\n      <td>4.113421</td>\n    </tr>\n    <tr>\n      <th>69</th>\n      <td>3.4176</td>\n      <td>3.417636</td>\n      <td>8.668028e+04</td>\n      <td>3.361415</td>\n    </tr>\n    <tr>\n      <th>70</th>\n      <td>3.4123</td>\n      <td>3.412338</td>\n      <td>9.081222e+04</td>\n      <td>3.587306</td>\n    </tr>\n    <tr>\n      <th>71</th>\n      <td>3.4037</td>\n      <td>3.403667</td>\n      <td>8.737366e+04</td>\n      <td>3.785466</td>\n    </tr>\n    <tr>\n      <th>72</th>\n      <td>3.3984</td>\n      <td>3.398406</td>\n      <td>7.615378e+04</td>\n      <td>3.191977</td>\n    </tr>\n    <tr>\n      <th>73</th>\n      <td>3.3698</td>\n      <td>3.369750</td>\n      <td>7.180156e+04</td>\n      <td>5.103056</td>\n    </tr>\n    <tr>\n      <th>74</th>\n      <td>3.3674</td>\n      <td>3.367380</td>\n      <td>7.220322e+04</td>\n      <td>5.274814</td>\n    </tr>\n    <tr>\n      <th>75</th>\n      <td>3.3490</td>\n      <td>3.349019</td>\n      <td>9.273022e+04</td>\n      <td>6.174294</td>\n    </tr>\n    <tr>\n      <th>76</th>\n      <td>3.3473</td>\n      <td>3.347348</td>\n      <td>9.465098e+04</td>\n      <td>6.646837</td>\n    </tr>\n    <tr>\n      <th>77</th>\n      <td>3.3269</td>\n      <td>3.326874</td>\n      <td>4.233787e+04</td>\n      <td>4.922259</td>\n    </tr>\n    <tr>\n      <th>78</th>\n      <td>3.3225</td>\n      <td>3.322526</td>\n      <td>6.319016e+04</td>\n      <td>4.965101</td>\n    </tr>\n    <tr>\n      <th>79</th>\n      <td>3.3100</td>\n      <td>3.309964</td>\n      <td>1.627937e+06</td>\n      <td>2.979492</td>\n    </tr>\n    <tr>\n      <th>80</th>\n      <td>3.3077</td>\n      <td>3.307749</td>\n      <td>2.870889e+06</td>\n      <td>2.832763</td>\n    </tr>\n    <tr>\n      <th>81</th>\n      <td>3.3055</td>\n      <td>3.305510</td>\n      <td>3.817222e+06</td>\n      <td>2.747098</td>\n    </tr>\n    <tr>\n      <th>82</th>\n      <td>3.3033</td>\n      <td>3.303288</td>\n      <td>2.745771e+06</td>\n      <td>2.924610</td>\n    </tr>\n    <tr>\n      <th>83</th>\n      <td>3.3011</td>\n      <td>3.301113</td>\n      <td>1.421097e+06</td>\n      <td>5.953597</td>\n    </tr>\n    <tr>\n      <th>84</th>\n      <td>3.1522</td>\n      <td>3.152211</td>\n      <td>6.245716e+04</td>\n      <td>5.481694</td>\n    </tr>\n    <tr>\n      <th>85</th>\n      <td>3.1090</td>\n      <td>3.109018</td>\n      <td>5.764684e+04</td>\n      <td>3.581131</td>\n    </tr>\n    <tr>\n      <th>86</th>\n      <td>3.0958</td>\n      <td>3.095787</td>\n      <td>8.519656e+04</td>\n      <td>6.116503</td>\n    </tr>\n    <tr>\n      <th>87</th>\n      <td>3.0822</td>\n      <td>3.082208</td>\n      <td>5.825673e+04</td>\n      <td>3.672690</td>\n    </tr>\n    <tr>\n      <th>88</th>\n      <td>2.9534</td>\n      <td>2.953417</td>\n      <td>6.017846e+04</td>\n      <td>3.892933</td>\n    </tr>\n    <tr>\n      <th>89</th>\n      <td>2.9403</td>\n      <td>2.940297</td>\n      <td>6.639245e+04</td>\n      <td>4.179462</td>\n    </tr>\n    <tr>\n      <th>90</th>\n      <td>2.9329</td>\n      <td>2.932888</td>\n      <td>7.543779e+04</td>\n      <td>4.508775</td>\n    </tr>\n    <tr>\n      <th>91</th>\n      <td>2.9273</td>\n      <td>2.927339</td>\n      <td>4.569922e+04</td>\n      <td>7.199359</td>\n    </tr>\n    <tr>\n      <th>92</th>\n      <td>2.9199</td>\n      <td>2.919894</td>\n      <td>6.577030e+04</td>\n      <td>4.143495</td>\n    </tr>\n    <tr>\n      <th>93</th>\n      <td>2.9151</td>\n      <td>2.915122</td>\n      <td>4.197673e+04</td>\n      <td>2.951786</td>\n    </tr>\n    <tr>\n      <th>94</th>\n      <td>2.8942</td>\n      <td>2.894172</td>\n      <td>1.327678e+05</td>\n      <td>2.154699</td>\n    </tr>\n    <tr>\n      <th>95</th>\n      <td>2.5201</td>\n      <td>2.520121</td>\n      <td>1.087617e+05</td>\n      <td>6.737846</td>\n    </tr>\n    <tr>\n      <th>96</th>\n      <td>2.3709</td>\n      <td>2.370922</td>\n      <td>4.655375e+04</td>\n      <td>5.452259</td>\n    </tr>\n    <tr>\n      <th>97</th>\n      <td>2.3654</td>\n      <td>2.365351</td>\n      <td>6.286932e+04</td>\n      <td>4.902760</td>\n    </tr>\n    <tr>\n      <th>98</th>\n      <td>2.3590</td>\n      <td>2.359048</td>\n      <td>8.808812e+04</td>\n      <td>4.933075</td>\n    </tr>\n    <tr>\n      <th>99</th>\n      <td>2.3543</td>\n      <td>2.354346</td>\n      <td>7.064850e+04</td>\n      <td>8.828053</td>\n    </tr>\n    <tr>\n      <th>100</th>\n      <td>2.3488</td>\n      <td>2.348783</td>\n      <td>1.572950e+05</td>\n      <td>5.477979</td>\n    </tr>\n    <tr>\n      <th>101</th>\n      <td>2.3394</td>\n      <td>2.339375</td>\n      <td>1.743196e+05</td>\n      <td>5.541165</td>\n    </tr>\n    <tr>\n      <th>102</th>\n      <td>2.3286</td>\n      <td>2.328623</td>\n      <td>1.651007e+05</td>\n      <td>6.197469</td>\n    </tr>\n    <tr>\n      <th>103</th>\n      <td>2.3172</td>\n      <td>2.317219</td>\n      <td>1.848574e+05</td>\n      <td>5.333368</td>\n    </tr>\n    <tr>\n      <th>104</th>\n      <td>2.3065</td>\n      <td>2.306495</td>\n      <td>1.027659e+05</td>\n      <td>5.606206</td>\n    </tr>\n    <tr>\n      <th>105</th>\n      <td>2.2540</td>\n      <td>2.254007</td>\n      <td>4.455738e+04</td>\n      <td>8.755534</td>\n    </tr>\n    <tr>\n      <th>106</th>\n      <td>2.0425</td>\n      <td>2.042462</td>\n      <td>5.790660e+04</td>\n      <td>9.032217</td>\n    </tr>\n    <tr>\n      <th>107</th>\n      <td>2.0340</td>\n      <td>2.034045</td>\n      <td>9.600114e+04</td>\n      <td>18.189875</td>\n    </tr>\n    <tr>\n      <th>108</th>\n      <td>2.0257</td>\n      <td>2.025694</td>\n      <td>8.660091e+04</td>\n      <td>10.928056</td>\n    </tr>\n    <tr>\n      <th>109</th>\n      <td>1.6380</td>\n      <td>1.638011</td>\n      <td>4.423255e+04</td>\n      <td>26.240118</td>\n    </tr>\n    <tr>\n      <th>110</th>\n      <td>1.6028</td>\n      <td>1.602822</td>\n      <td>2.055044e+05</td>\n      <td>13.519730</td>\n    </tr>\n    <tr>\n      <th>111</th>\n      <td>1.5988</td>\n      <td>1.598802</td>\n      <td>1.958751e+05</td>\n      <td>27.694234</td>\n    </tr>\n    <tr>\n      <th>112</th>\n      <td>1.5936</td>\n      <td>1.593601</td>\n      <td>2.022957e+05</td>\n      <td>18.527893</td>\n    </tr>\n    <tr>\n      <th>113</th>\n      <td>1.5839</td>\n      <td>1.583900</td>\n      <td>1.308446e+05</td>\n      <td>15.178744</td>\n    </tr>\n    <tr>\n      <th>114</th>\n      <td>1.4395</td>\n      <td>1.439520</td>\n      <td>5.839417e+04</td>\n      <td>7.267443</td>\n    </tr>\n    <tr>\n      <th>115</th>\n      <td>1.4339</td>\n      <td>1.433917</td>\n      <td>5.109109e+04</td>\n      <td>14.752646</td>\n    </tr>\n    <tr>\n      <th>116</th>\n      <td>1.4296</td>\n      <td>1.429563</td>\n      <td>6.270292e+04</td>\n      <td>9.127178</td>\n    </tr>\n    <tr>\n      <th>117</th>\n      <td>1.4245</td>\n      <td>1.424531</td>\n      <td>5.158117e+04</td>\n      <td>24.720003</td>\n    </tr>\n    <tr>\n      <th>118</th>\n      <td>1.4205</td>\n      <td>1.420476</td>\n      <td>4.947768e+04</td>\n      <td>11.227207</td>\n    </tr>\n    <tr>\n      <th>119</th>\n      <td>1.4131</td>\n      <td>1.413123</td>\n      <td>5.708449e+04</td>\n      <td>18.263653</td>\n    </tr>\n    <tr>\n      <th>120</th>\n      <td>1.4117</td>\n      <td>1.411722</td>\n      <td>5.787642e+04</td>\n      <td>11.891096</td>\n    </tr>\n    <tr>\n      <th>121</th>\n      <td>1.4007</td>\n      <td>1.400654</td>\n      <td>7.425809e+04</td>\n      <td>8.198565</td>\n    </tr>\n    <tr>\n      <th>122</th>\n      <td>1.3949</td>\n      <td>1.394950</td>\n      <td>7.829040e+04</td>\n      <td>13.790337</td>\n    </tr>\n    <tr>\n      <th>123</th>\n      <td>1.3852</td>\n      <td>1.385197</td>\n      <td>8.567701e+04</td>\n      <td>24.107053</td>\n    </tr>\n    <tr>\n      <th>124</th>\n      <td>1.3808</td>\n      <td>1.380760</td>\n      <td>9.729362e+04</td>\n      <td>10.960274</td>\n    </tr>\n    <tr>\n      <th>125</th>\n      <td>1.3795</td>\n      <td>1.379510</td>\n      <td>9.657861e+04</td>\n      <td>18.622865</td>\n    </tr>\n    <tr>\n      <th>126</th>\n      <td>1.3711</td>\n      <td>1.371074</td>\n      <td>1.197692e+05</td>\n      <td>7.809472</td>\n    </tr>\n    <tr>\n      <th>127</th>\n      <td>1.3342</td>\n      <td>1.334162</td>\n      <td>4.970532e+05</td>\n      <td>5.274852</td>\n    </tr>\n    <tr>\n      <th>128</th>\n      <td>1.3175</td>\n      <td>1.317500</td>\n      <td>7.829622e+05</td>\n      <td>19.484916</td>\n    </tr>\n    <tr>\n      <th>129</th>\n      <td>1.3094</td>\n      <td>1.309425</td>\n      <td>7.308020e+05</td>\n      <td>54.144949</td>\n    </tr>\n    <tr>\n      <th>130</th>\n      <td>1.3072</td>\n      <td>1.307152</td>\n      <td>7.264125e+05</td>\n      <td>23.600092</td>\n    </tr>\n    <tr>\n      <th>131</th>\n      <td>1.3035</td>\n      <td>1.303476</td>\n      <td>8.264444e+05</td>\n      <td>6.283409</td>\n    </tr>\n    <tr>\n      <th>132</th>\n      <td>1.2858</td>\n      <td>1.285756</td>\n      <td>3.434272e+06</td>\n      <td>8.677081</td>\n    </tr>\n    <tr>\n      <th>133</th>\n      <td>1.2720</td>\n      <td>1.272027</td>\n      <td>4.703014e+05</td>\n      <td>5.672197</td>\n    </tr>\n    <tr>\n      <th>134</th>\n      <td>1.2339</td>\n      <td>1.233850</td>\n      <td>5.700152e+04</td>\n      <td>4.124077</td>\n    </tr>\n    <tr>\n      <th>135</th>\n      <td>1.2291</td>\n      <td>1.229138</td>\n      <td>5.419344e+04</td>\n      <td>4.859426</td>\n    </tr>\n    <tr>\n      <th>136</th>\n      <td>1.2249</td>\n      <td>1.224916</td>\n      <td>5.442450e+04</td>\n      <td>4.260391</td>\n    </tr>\n    <tr>\n      <th>137</th>\n      <td>1.2161</td>\n      <td>1.216106</td>\n      <td>4.931620e+04</td>\n      <td>4.788837</td>\n    </tr>\n    <tr>\n      <th>138</th>\n      <td>0.9726</td>\n      <td>0.972627</td>\n      <td>5.264115e+04</td>\n      <td>4.691572</td>\n    </tr>\n    <tr>\n      <th>139</th>\n      <td>0.9064</td>\n      <td>0.906437</td>\n      <td>4.101932e+05</td>\n      <td>4.767596</td>\n    </tr>\n    <tr>\n      <th>140</th>\n      <td>0.8966</td>\n      <td>0.896603</td>\n      <td>7.082192e+05</td>\n      <td>3.970098</td>\n    </tr>\n    <tr>\n      <th>141</th>\n      <td>0.8863</td>\n      <td>0.886350</td>\n      <td>3.746612e+05</td>\n      <td>4.035561</td>\n    </tr>\n    <tr>\n      <th>142</th>\n      <td>0.8730</td>\n      <td>0.872974</td>\n      <td>6.900813e+04</td>\n      <td>10.312412</td>\n    </tr>\n    <tr>\n      <th>143</th>\n      <td>0.8677</td>\n      <td>0.867673</td>\n      <td>5.850057e+04</td>\n      <td>19.891202</td>\n    </tr>\n    <tr>\n      <th>144</th>\n      <td>0.8621</td>\n      <td>0.862149</td>\n      <td>7.057265e+04</td>\n      <td>7.253293</td>\n    </tr>\n    <tr>\n      <th>145</th>\n      <td>0.8527</td>\n      <td>0.852672</td>\n      <td>4.577133e+04</td>\n      <td>5.907911</td>\n    </tr>\n    <tr>\n      <th>146</th>\n      <td>0.0071</td>\n      <td>0.007143</td>\n      <td>4.376208e+04</td>\n      <td>1.412642</td>\n    </tr>\n    <tr>\n      <th>147</th>\n      <td>0.0056</td>\n      <td>0.005639</td>\n      <td>6.480552e+04</td>\n      <td>1.558008</td>\n    </tr>\n    <tr>\n      <th>148</th>\n      <td>0.0041</td>\n      <td>0.004081</td>\n      <td>1.258839e+05</td>\n      <td>1.965843</td>\n    </tr>\n    <tr>\n      <th>149</th>\n      <td>0.0027</td>\n      <td>0.002700</td>\n      <td>1.404108e+05</td>\n      <td>1.893431</td>\n    </tr>\n    <tr>\n      <th>150</th>\n      <td>-0.0007</td>\n      <td>-0.000719</td>\n      <td>1.965013e+06</td>\n      <td>1.940414</td>\n    </tr>\n    <tr>\n      <th>151</th>\n      <td>-0.0037</td>\n      <td>-0.003681</td>\n      <td>8.187281e+04</td>\n      <td>1.872310</td>\n    </tr>\n    <tr>\n      <th>152</th>\n      <td>-0.0055</td>\n      <td>-0.005467</td>\n      <td>6.706985e+04</td>\n      <td>1.317563</td>\n    </tr>\n  </tbody>\n</table>",
          "text/plain": "<IPython.core.display.HTML object>"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "a78fb299cdc740b186bddf01e523703c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "a84eebf777844f60bb775c5f6ee65f0c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_d62c090f057c494daeadb01cb4deccb4",
       "style": "IPY_MODEL_444cd60da12648178ed69db5bedfb682",
       "value": "&nbsp;"
      }
     },
     "a8bca7695350476eaa3f2343b6c2219a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_34e83b93d7574672a5796b9cd3372f26",
        "IPY_MODEL_86a65b8dd61d4f6a9c3a78b8057e32df"
       ],
       "layout": "IPY_MODEL_76dd7c93fe284c8182dc3fea0b1756d5"
      }
     },
     "a993019dc3d641a9acd25c3d946b91b9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_557cf3c2edc84b7dbb410d9efe414a1e",
        "IPY_MODEL_33cbe83344474f8fbd78f6aba61a30db"
       ],
       "layout": "IPY_MODEL_e154627dd2684ed3a0087f24345f4026"
      }
     },
     "a9c0cb1f520a4c6f9bda7ff0ec603995": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "aa0b44aac0e440e2bc82a487218efec2": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "aa96f7bd735c47ee8483477ebf111517": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "CheckboxModel",
      "state": {
       "disabled": false,
       "layout": "IPY_MODEL_ce0ebce6a56241b7a70c76d815701574",
       "style": "IPY_MODEL_d005aac1c79c4a6da7625014a3769d7e",
       "value": true
      }
     },
     "abad509919ef40618b10657fc5181f79": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "abbc213d69984a468861148c97bd0a93": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "abe9d41e2ab6471ea4d9d1397130fae6": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Reset",
       "layout": "IPY_MODEL_58b6249fb5214aa1b133621980483b00",
       "style": "IPY_MODEL_c4d357d23b654e2a9d8bdb148a4b0b71",
       "tooltip": "Reset to full spectrum"
      }
     },
     "ac598ea43e124317b2436afebb50a175": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "accf2236d43e48e48d056d2a718bf612": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "ad54e011f73a4715a53c79a9d6bc95d2": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "ad941abb775d48e1b516fa3ed258df9b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "adb9caaa5fc3433f9be3f146b6de5757": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "GridBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_15c4ca3a56d44e168f2e4fa287464dc3",
        "IPY_MODEL_15298079d7b842bf98a1f86e388d10bc",
        "IPY_MODEL_74a6b026cf2b402ab2615b3821e83edf"
       ],
       "layout": "IPY_MODEL_70fc0371b5934b57b71b0d07182da0e9"
      }
     },
     "adfa7447275340869cb829701a256cd7": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "filename",
       "width": "auto"
      }
     },
     "ae304f127c8146a3bf534ce68e16f161": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "black",
        "red",
        "blue",
        "green",
        "orange",
        "blueviolet",
        "crimson",
        "turquoise",
        "indigo",
        "magenta",
        "gold",
        "pink",
        "purple",
        "salmon",
        "darkblue",
        "sienna"
       ],
       "index": 2,
       "layout": "IPY_MODEL_aa0b44aac0e440e2bc82a487218efec2",
       "style": "IPY_MODEL_db35fc78025f4f3c93275b0d13d1ef7f"
      }
     },
     "ae6fc09c2df1429cb5e8abcc24d91290": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "aee850ebb11741d6b5415abdaadc3562": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_a84eebf777844f60bb775c5f6ee65f0c",
        "IPY_MODEL_1659b6218b52472aaee8231000855a3f",
        "IPY_MODEL_27267d9fa19343a8832c76ba935cc86d"
       ],
       "layout": "IPY_MODEL_bd14b2ec375c4ab28bf44911cd96dc9a"
      }
     },
     "af6bc15d8b0d4814b2fb6740e526872d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "pathlist",
       "width": "auto"
      }
     },
     "af6e0466f6dc4f1097828c1e0b732829": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "af71e66edc04468cb606162be879ecf1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "afeb38015a0e49f2a52e071dcb65d550": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "100%"
      }
     },
     "b07aa323eeb94b8ca9de28021916effb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "/DATA/SM_ARTE_v3/ARTEref_161123/1",
        "/DATA/SM_ARTE_v3/ARTEref_161123",
        "/DATA/SM_ARTE_v3",
        "/DATA",
        "/"
       ],
       "index": 0,
       "layout": "IPY_MODEL_a278abf75d7b4138a96903799c0e3214",
       "style": "IPY_MODEL_1b8894747a4846e7bf3f5b5b780c62a4"
      }
     },
     "b0e5a24c36864f7083594357acf1aa99": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "b0eb61b9e22a4d3fb9535726bf4c1d81": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "30%"
      }
     },
     "b1e2bc35d3b44ab6a71dba08994a3099": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "b2677b80376949349bf8f8c88497a05d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "b31262acc4ff4d83858cc921d8e31230": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "b3229f0f360f4ab089d85d62a24d9268": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "b40d16f3c196481990a4040360671451": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "black",
        "red",
        "blue",
        "green",
        "orange",
        "blueviolet",
        "crimson",
        "turquoise",
        "indigo",
        "magenta",
        "gold",
        "pink",
        "purple",
        "salmon",
        "darkblue",
        "sienna"
       ],
       "index": 7,
       "layout": "IPY_MODEL_086c03b8860048d690c102025d5a6ae8",
       "style": "IPY_MODEL_3388d8cb3429483f9f6700b5c2835904"
      }
     },
     "b4591255a9c24a63802577e11f2f4636": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "b4ef66eb82e346569bba2005197e58f1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "b54210b2a0dd44dda02e4b60d51757a0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_adfa7447275340869cb829701a256cd7",
       "placeholder": "output filename",
       "style": "IPY_MODEL_da480a0070b6436fa2594ef85c897343"
      }
     },
     "b54836b0931a433698f7e5612848b2a7": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "b5ece940c2154762ad987b2cfebc7770": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "b5efbfbf26d547ffb79b8bb242e1f61f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "b61895bb30b84327a90c0c79715cae73": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "b63f4c8749ed4838b3592dfd48868699": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_52648a9ca40c4c0ead1cf0f3bba4107d",
        "IPY_MODEL_e1ccc9c9fe844388b4b65a956e9548a4"
       ],
       "layout": "IPY_MODEL_1eb1bdb7e68f424ebef07b2b5f63c05d"
      }
     },
     "b75ba06fb6d54861a59369aa7b569040": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "b75f1c40dd574f08884fb194080bea1f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "b857d40a36e345b9a672d6ff64d4af55": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_bd111c68aaec4be78f4d60e71a3ea16a",
        "IPY_MODEL_699b6e3394d24b5e8cd299981904cda1",
        "IPY_MODEL_dbf8d8fb037945e288e9660f26207be7"
       ],
       "layout": "IPY_MODEL_512d26d2e66c40aaaecf569b7bffe5a5"
      }
     },
     "b8b3e8ea05104c588cae8407e603783a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "warning",
       "description": "Rem",
       "layout": "IPY_MODEL_e308804a1a6040cda772b52c127a421d",
       "style": "IPY_MODEL_76cc28d6723844cd89ab839b4d91f05d"
      }
     },
     "b8b987a8e8de4975b3f68d756655f278": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "ba040b14431541caa1f7732d3ae2054c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "dircontent",
       "width": "auto"
      }
     },
     "ba700805d58c42919a1f233256c03c7f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_e308804a1a6040cda772b52c127a421d",
       "style": "IPY_MODEL_98c9751a182f46fabaa32d5d33baed31",
       "value": "&nbsp;"
      }
     },
     "ba8898bdfcc04693a71de6fd18080148": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_59fadfb25a844ff1a31d653e07e1332f",
        "IPY_MODEL_a37083c33c5e4b9b9de86cdf5112e381",
        "IPY_MODEL_cca613eaf3e3418685f2f46812408f86",
        "IPY_MODEL_036e9e1201cf428084301243a1bada53"
       ],
       "layout": "IPY_MODEL_73c9126568cc4dbabd20fc69432e366f"
      }
     },
     "bb178e13a098475f9467aeee54ee7bfc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_9accd7e782874349a946a168e561cf33",
       "style": "IPY_MODEL_60ab0803ec86431e8cd0145eeb0dfd14",
       "value": "<i>set by clicking on spectrum</i>"
      }
     },
     "bb6c2a7aa3f849838eaea8ec8823c12d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "bc27e3b22b3e42e684e609a9ce5db6b1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "bc36ff4035a0452e9c9bce1908f26be9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "bc9dcc0b168d408cac37c995d5b68a88": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "bcbb3777b377405299fc7c70d1029bcb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "up",
        "down",
        "off"
       ],
       "index": 2,
       "layout": "IPY_MODEL_7144950c03434de39be6deb7c73a3861",
       "style": "IPY_MODEL_6e14ea2fb0bb470db126ad773aaeb94f"
      }
     },
     "bd111c68aaec4be78f4d60e71a3ea16a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Change",
       "layout": "IPY_MODEL_7d71afb0752740b2b0fa8d7b089a9826",
       "style": "IPY_MODEL_1900dcf9661c4fd78def1699c8bd9e97"
      }
     },
     "bd14b2ec375c4ab28bf44911cd96dc9a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "be89fcbd61ab428a912dbe33fabc3ced": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_371b6d4b11b4427dac51450311faae4b",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "bee2846a351b4ba4bf5a6efcb94a6635": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "bf1c0ea678444cceae298da19f0c79bc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TabModel",
      "state": {
       "_titles": {
        "0": "Manual integration",
        "1": "Automatic",
        "2": "Integral Table & Calibration"
       },
       "children": [
        "IPY_MODEL_140df7fc72244e50ae2f1ca62ce801d8",
        "IPY_MODEL_df20714781a345b5a7cc10849db617b1",
        "IPY_MODEL_dfd91faa4906431982695b319a8c3d19"
       ],
       "layout": "IPY_MODEL_3f6c4c1500e84e2bad3628ac77d18681"
      }
     },
     "bf4b1b08549c4b5da5ec9fe078e9e447": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "up",
        "down",
        "off"
       ],
       "index": 2,
       "layout": "IPY_MODEL_777eb10335484350ac8fffb47fd05ac3",
       "style": "IPY_MODEL_1e3ee020ff9943d1b551c1cd60901b54"
      }
     },
     "bf5f5c98fe6f41a8a6e41874544181ac": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "bf8b1047bf8b4a9cb13f36ee34eb3ff3": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "c00d3f781b7641dab2e070f937edaab5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "c063e9ab524a4725a7fc25c774f13f31": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "c0a5b3fca1224f6caed8ef2adeeafa01": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "c10c1060cb28452a8728bdbf71c84f73": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "10%"
      }
     },
     "c129a8625c5144b5b645418e77e3e83d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "c1378385616444978461869aab8ae4cf": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_3666b57e78cd40818d2232f92ce10e4f",
       "style": "IPY_MODEL_094a790c634a423ca69843959a745c81",
       "value": "<b>6</b>"
      }
     },
     "c1582ef155774f0e95d1cd0d511ad3c0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "layout": "IPY_MODEL_cd27499091fc4e04aa0242cada7f4159",
       "step": null,
       "style": "IPY_MODEL_3f2deedbc8434d5b874d934aa15aa36c"
      }
     },
     "c1f3fb249db346329ac686cb1b923e32": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "c20384acd1354015b9f231b52418522a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "15%"
      }
     },
     "c2e0d83eaddc454eaa7da8ffa5abef67": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "c3b91d8b5d30466d89258c1acc253cc2": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "description": "scale:",
       "layout": "IPY_MODEL_70b765a01c7144cfa187789bc49c95c5",
       "max": 200,
       "min": 1,
       "orientation": "vertical",
       "step": 0.1,
       "style": "IPY_MODEL_3ae2beb5431242c094bf06648c06addd",
       "value": 15.4
      }
     },
     "c4d357d23b654e2a9d8bdb148a4b0b71": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "c5bc8cba8c5d40ec90288ecf9c9556ed": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "MPLCanvasModel",
      "state": {
       "_figure_label": "Figure 6",
       "_height": 500,
       "_image_mode": "diff",
       "_width": 1000,
       "layout": "IPY_MODEL_f2a24a2351f042ac90a0f09247980dfc",
       "toolbar": "IPY_MODEL_f6c7a686a37f4179a08ea69a763c4e6e",
       "toolbar_position": "left"
      }
     },
     "c5bed30fb0c64a6d96d22babc4d2c60c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "c60a67c01fe948ea88a4c9005cbcfe01": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Done",
       "layout": "IPY_MODEL_4ccd2c50e75b4a45841d25478cb73bf6",
       "style": "IPY_MODEL_142cb6ba0f9347a0beffe819b60f42d3"
      }
     },
     "c6c7d9c3d7ef476fb1b5a72d3c24baad": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "c7552dbff90a4e33b795a1387e5453f3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_cef61b017c8a43a6a7498bccb1f3be67",
        "IPY_MODEL_a6749a1d93924f4f8d1c9df91a2edb70",
        "IPY_MODEL_fde69c4f770a4a1495e8ecb5ea139fb3",
        "IPY_MODEL_1b93616b350a459197324d4d4c76a504",
        "IPY_MODEL_839f780f8cce43dfae17db3a6bb94333",
        "IPY_MODEL_5d8476b42f5e4f66af053f3b4d55f0f4",
        "IPY_MODEL_4a2d8e3ef4a7483ca7d0008d06f91fbd",
        "IPY_MODEL_f35bb9c55a1641f38769fece82abd970",
        "IPY_MODEL_2a652f1cf81f4eb5805556e0b7a2ec96",
        "IPY_MODEL_8a3ce06047334fb1bb8d4d3b52a0bbd6",
        "IPY_MODEL_113f3b21f835475c8da7bf6cc1532e4a"
       ],
       "layout": "IPY_MODEL_025ec3d7ffeb43b3aa04453347810d92"
      }
     },
     "c7bcbf57a288403fa667b8de2405a62f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "warning",
       "description": "Cancel",
       "layout": "IPY_MODEL_6e884f90398944ce9e49ba1ab490ae13",
       "style": "IPY_MODEL_5ce53c81c4b1458ca99fc766f51b27ca"
      }
     },
     "c7c60f5ddc824ecdbb527c59b3a841b8": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "c7f8d47aa1fa4f91b2be7805282f1935": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "c92f254cb6e7423e8d7101f56e8f68f1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_7be27f1286c043bc8fce7fc3e5623149",
        "IPY_MODEL_c5bc8cba8c5d40ec90288ecf9c9556ed"
       ],
       "layout": "IPY_MODEL_d502a41daca143a9a2c01115f7411d15"
      }
     },
     "c9d9d7f66fb443f9983dee117e759d43": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "cac7e99e5ab046e686f1d96bfd7a71f0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "cb84e03ef3c847c0b0894c4473dabe21": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "cba8dfc05bbb483c910416a0b926b5f4": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "cba98d86945f44c1b4650a72fa138217": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "cc0e98a2d18842c592d62142466ea284": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "cca613eaf3e3418685f2f46812408f86": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "description": "scale:",
       "layout": "IPY_MODEL_ee7be73adfc6432eb2e5314d161043bf",
       "max": 200,
       "min": 1,
       "orientation": "vertical",
       "step": 0.1,
       "style": "IPY_MODEL_bf5f5c98fe6f41a8a6e41874544181ac",
       "value": 107.63023339764726
      }
     },
     "cd27499091fc4e04aa0242cada7f4159": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "ce0ebce6a56241b7a70c76d815701574": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "15%"
      }
     },
     "ce592ff2be134df4a4bc871c0d1433cc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_9e6f35a6f1094a87bc1c908e88eb9177",
        "IPY_MODEL_fe597743545f4e7fa3856db25cab2ae5",
        "IPY_MODEL_c3b91d8b5d30466d89258c1acc253cc2"
       ],
       "layout": "IPY_MODEL_583e87a74a4f4579801fc8cd233e3644"
      }
     },
     "ce6738e53ebc487eaf7e614ec56a7330": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "up",
        "down",
        "off"
       ],
       "index": 2,
       "layout": "IPY_MODEL_0e4cacaf2daf46238bd5fac1b5e67412",
       "style": "IPY_MODEL_cba98d86945f44c1b4650a72fa138217"
      }
     },
     "cee16a6a026f4b55b84f458faa6f1042": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "cef61b017c8a43a6a7498bccb1f3be67": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_b5efbfbf26d547ffb79b8bb242e1f61f",
       "style": "IPY_MODEL_d12d3c879f7349449b80b08d576adca9",
       "value": "Choose spectra to superimpose"
      }
     },
     "cefcdcbb83874a808aad532466d80e7b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_355dc1682171493486ca04a2ca46cbfb",
        "IPY_MODEL_316cefd243e64613a00c095bd19c8b8d",
        "IPY_MODEL_0a9163a4480c4a72bb6d9af3cf1f640a",
        "IPY_MODEL_7e2557b75d384a4c8c5693b06db899d1"
       ],
       "layout": "IPY_MODEL_b4ef66eb82e346569bba2005197e58f1"
      }
     },
     "cfc92761bbcc447e8917df36e1b7f84e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "d001487b37344806aac005b33ed11465": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_77fc443050bd4252ad603745f77e4757",
       "style": "IPY_MODEL_3d1b1685562b436ca729b0faeee79849",
       "value": "None"
      }
     },
     "d005aac1c79c4a6da7625014a3769d7e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "d03f91a643c54e61bbfb985022a9030c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "black",
        "red",
        "blue",
        "green",
        "orange",
        "blueviolet",
        "crimson",
        "turquoise",
        "indigo",
        "magenta",
        "gold",
        "pink",
        "purple",
        "salmon",
        "darkblue",
        "sienna"
       ],
       "index": 8,
       "layout": "IPY_MODEL_4229f086c9c24d79bd84b703ffc4d68b",
       "style": "IPY_MODEL_f061ef580a2a41f3ae9c16fa3f5e90db"
      }
     },
     "d0e30bb3c1db499abeb61eb0e0aa0e08": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "d12be3ac986740bc9cc146bf02abd014": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "d12d3c879f7349449b80b08d576adca9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "d15383248e574ffda6da7b3b73dfd22d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_59fadfb25a844ff1a31d653e07e1332f",
        "IPY_MODEL_a37083c33c5e4b9b9de86cdf5112e381",
        "IPY_MODEL_cca613eaf3e3418685f2f46812408f86"
       ],
       "layout": "IPY_MODEL_634797bd89b44eccab0dbd323ca16d11"
      }
     },
     "d230168c012941aea0517924455d3df9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "d3f6ea128c384c858211e011c0843a34": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "d502a41daca143a9a2c01115f7411d15": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "d522538016a144479e147bdc76cd2b8c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "d555c757c5f447dc8fe2b298e479db14": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "pathlist",
       "width": "auto"
      }
     },
     "d5fcd1516d914798b473c103c426ba6f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "15%"
      }
     },
     "d62c090f057c494daeadb01cb4deccb4": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "d68cf4b8534b4cdaa1d6a0f6d60558a4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "layout": "IPY_MODEL_6e8f9e30939e47aa8539bb7fdba4eec5",
       "step": null,
       "style": "IPY_MODEL_f18f3400df1d4769b77c56b38aa3a28e"
      }
     },
     "d6be33e9d6154a7186e11e047141992e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "auto"
      }
     },
     "d6c4bde1038641f9abdfeeb03ad5c6ae": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "black",
        "red",
        "blue",
        "green",
        "orange",
        "blueviolet",
        "crimson",
        "turquoise",
        "indigo",
        "magenta",
        "gold",
        "pink",
        "purple",
        "salmon",
        "darkblue",
        "sienna"
       ],
       "index": 4,
       "layout": "IPY_MODEL_e3c37ebef6f24d40bc728fd92df8cbc1",
       "style": "IPY_MODEL_df5dd52f10c647619cfca0889c164829"
      }
     },
     "d6f2dd7662cc4332b74874a36e8a9307": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_4b0508b49e894e1ba6a87239e57f67e3",
       "style": "IPY_MODEL_2eb954911c574fb09208aa8ce9118f3a",
       "value": "Define integral shapes using the sliders below"
      }
     },
     "d73cd84b0c0940a29a8df3daf3287c16": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_a2e31c34eabb454ca769813382decf65"
       ],
       "layout": "IPY_MODEL_2ea7ef0f5f9e45ba9a59e16c75ebb391"
      }
     },
     "d7ae0aa810d44139b3325da56c2b6b1a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_f87f44f4687f4d38b83c2bbcb9a73e8e",
        "IPY_MODEL_e6b8a05393d141ed97006cc6e6e65021",
        "IPY_MODEL_2ca0f26a406d49fc8ee07b225b060b9e"
       ],
       "layout": "IPY_MODEL_b4591255a9c24a63802577e11f2f4636"
      }
     },
     "d7c311eec4de483189842e51ad622809": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "description": "scale:",
       "layout": "IPY_MODEL_93f8b360ed8b45a2a18b7e7f12fe8cbd",
       "max": 200,
       "min": 1,
       "orientation": "vertical",
       "step": 0.1,
       "style": "IPY_MODEL_64b52ca3c98b4c45886a925a4a157015",
       "value": 129.5
      }
     },
     "d7e0e05be37848378442ff8c517ba6ba": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "15%"
      }
     },
     "d843bd87cc42493085a635a5adae22c6": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "d86f5b0e90564de0b55874b3e2c0ca1f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "IntTextModel",
      "state": {
       "layout": "IPY_MODEL_a4bfa1b108d54a72bee3b35a664077e6",
       "step": 1,
       "style": "IPY_MODEL_8d64f50fc2e04cb1b8a1e35a101390ee",
       "value": 1
      }
     },
     "d8a2ab056f6d4e429a5b4c3595f73c0a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "d8e73a9d06f54a97a59f0a8808a08856": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_f4d6c24f113643509d414d5445bb9f5f"
       ],
       "layout": "IPY_MODEL_cb84e03ef3c847c0b0894c4473dabe21"
      }
     },
     "d8eb407f15b74009ab93863be1e4ac3b": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "d923c32df5534ec2bc190b705908ee35": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "30%"
      }
     },
     "da480a0070b6436fa2594ef85c897343": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "da62af78f3594c9192f0c67836db89d8": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70%"
      }
     },
     "da9685a3d0bf4caca8fb77ac099c943d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "dabb721536164b13ad9d15eac1d6e8f2": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "daed713461ed429fb297b73c35be8752": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_f1e23dfe17984a7b9aa59d7473874228",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "db35fc78025f4f3c93275b0d13d1ef7f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "db6dccfa2c5b4d9eaaa98251b4bee843": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "continuous_update": false,
       "description": "bias",
       "layout": "IPY_MODEL_570ee511cd7848869d1eaede2a9e0ca1",
       "max": 10,
       "min": -10,
       "readout": false,
       "readout_format": ".1f",
       "step": 0.1,
       "style": "IPY_MODEL_7b076b13f9754c82b150030e59e4d30d"
      }
     },
     "dbc48968702544f6b636ba2dfca6a2c7": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_bc36ff4035a0452e9c9bce1908f26be9",
       "style": "IPY_MODEL_a2da8d71197f4a27b2f5a82ce7e2c5a1",
       "value": "Show Peaks"
      }
     },
     "dbf8d8fb037945e288e9660f26207be7": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_ac598ea43e124317b2436afebb50a175",
       "placeholder": "",
       "style": "IPY_MODEL_2e2ce8f3ed964dd2bf0327b3bcce1373",
       "value": "<span style=\"margin-left:10px; color:orange;\">/DATA/SM_ARTE_v3/SM_ARTE4_161123/1/fid</span>"
      }
     },
     "dbf9c05d5bbf47b2895109e2a1e65260": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Select",
       "layout": "IPY_MODEL_9144f99157f3428b9734e2c2907cf884",
       "style": "IPY_MODEL_b1e2bc35d3b44ab6a71dba08994a3099"
      }
     },
     "dc0eefcde81f469ba259c3f66ae3a54e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "dc75c9f6dd0a4cdd92a9bd55752fb1c2": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "display": "none",
       "width": "auto"
      }
     },
     "dc8b8d7f6a7949508e20597ff6c50631": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TabModel",
      "state": {
       "_titles": {
        "0": "1D Display",
        "1": "Peak Table"
       },
       "children": [
        "IPY_MODEL_86a65b8dd61d4f6a9c3a78b8057e32df",
        "IPY_MODEL_a7838ba1abe7438b91bce89489fa5d56"
       ],
       "layout": "IPY_MODEL_e257571f97584d63baa1c0bad16969ef"
      }
     },
     "dc8e10175b71475fa9b4550621b28343": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "dd019363291f40fdb9ed21e4afc05713": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "40em"
      }
     },
     "dd16d12961ee41a9abbe7af59a86f23e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "marker",
        "bar"
       ],
       "description": "show as",
       "index": 0,
       "layout": "IPY_MODEL_7777a9ba606c41ec9fe62a095445bae5",
       "style": "IPY_MODEL_d3f6ea128c384c858211e011c0843a34"
      }
     },
     "de2a2ae09165461bb4f6f2ce16c74f5f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "df20714781a345b5a7cc10849db617b1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_5e15622f64c847c9a3f20b787913e66c",
        "IPY_MODEL_d7ae0aa810d44139b3325da56c2b6b1a",
        "IPY_MODEL_7e771c9b16584306b61aaf778063b14f"
       ],
       "layout": "IPY_MODEL_c6c7d9c3d7ef476fb1b5a72d3c24baad"
      }
     },
     "df50504b8e774dabb419f28c79a0b6d8": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "auto"
      }
     },
     "df5dd52f10c647619cfca0889c164829": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "df8de11e30204b43bf3475713ce5aae9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "dfd91faa4906431982695b319a8c3d19": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_04d73c6df79440d0acfe11dce615bf74",
        "IPY_MODEL_159262a422e14b31971b2a4a06e3de55"
       ],
       "layout": "IPY_MODEL_6f6a6a5111f54a898997a1d8fd0e1d78"
      }
     },
     "e154627dd2684ed3a0087f24345f4026": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "e1ccc9c9fe844388b4b65a956e9548a4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_79b908da4e5b47dc8b05f3017af41b9b",
        "IPY_MODEL_86a65b8dd61d4f6a9c3a78b8057e32df"
       ],
       "layout": "IPY_MODEL_86f55627a8f14ca5ab84c2e25baa8de9"
      }
     },
     "e2059c937489460189ef61db4a999451": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "height": "10.16cm",
       "width": "80px"
      }
     },
     "e257571f97584d63baa1c0bad16969ef": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "e308804a1a6040cda772b52c127a421d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "e3c37ebef6f24d40bc728fd92df8cbc1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "80px"
      }
     },
     "e3f2d35fc5d64203914355525667c0f5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "layout": "IPY_MODEL_6a5bbab925c540dabe0b939f7dcfbf51",
       "step": null,
       "style": "IPY_MODEL_10eb527e17ca4db09d06ac09df0c239e"
      }
     },
     "e42a089857eb435ca8ca40037bce830e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "e42f702cfe814aeb81dbb42274890537": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_dbf9c05d5bbf47b2895109e2a1e65260",
        "IPY_MODEL_e47d1770a3924322bbfd0980588bb79a",
        "IPY_MODEL_8e7fbc3bb8804a788dfe2a4d9285c8d9"
       ],
       "layout": "IPY_MODEL_df50504b8e774dabb419f28c79a0b6d8"
      }
     },
     "e47d1770a3924322bbfd0980588bb79a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "warning",
       "description": "Cancel",
       "layout": "IPY_MODEL_1ea05e0fa82f4b3ba0ffe300e0b7f23c",
       "style": "IPY_MODEL_3e97f14fdf8042d1a928f38a2d208734"
      }
     },
     "e4a10652a5d7498ba04241d2996fc2bc": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "display": "none",
       "grid_gap": "0px 0px",
       "grid_template_areas": "\n                    'pathlist filename'\n                    'dircontent dircontent'\n                    ",
       "grid_template_columns": "60% 40%",
       "grid_template_rows": "auto auto",
       "width": "500px"
      }
     },
     "e5e069afb1c74de4ac2f0c7e836b3a32": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "e6b8a05393d141ed97006cc6e6e65021": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "continuous_update": false,
       "description": "separation",
       "layout": "IPY_MODEL_5f99c3376a5d4ef5a1b09f0ae2cf5ae4",
       "max": 20,
       "readout": false,
       "readout_format": ".1f",
       "step": 0.1,
       "style": "IPY_MODEL_6e0a72db313a41bb8a980d38e39166ca",
       "value": 3
      }
     },
     "e6bc7de25004458394c099a65fd0ef3c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_2ed80f830e5047de8ec924d621551725",
       "style": "IPY_MODEL_d522538016a144479e147bdc76cd2b8c",
       "value": "Choose baseline points"
      }
     },
     "e770675e7ab54afda69dc1fa099b9d02": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "e78e7ffa06b3480593c327f2b0e84366": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "e7f1a7611a274c7d8402c0c7f84f68da": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "e8270e6d857540d3ab604e9bbf72fe2d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "layout": "IPY_MODEL_983e405fc5924eaf9ae23984274423b7",
       "style": "IPY_MODEL_7ad80cd723d2440f859ba1a4cf5924b4",
       "value": "Integral scale:"
      }
     },
     "e9053bdd792e4ac291215113b4fa9f33": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "e9a937e757d44de7b41d9444d816f2f3": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "e9accee3d74a463492fc7212ae78424f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SelectModel",
      "state": {
       "_options_labels": [
        "..",
        "pdata",
        "acqu",
        "acqus",
        "audita.txt",
        "fid",
        "format.temp",
        "processed.gs1",
        "pulseprogram",
        "scon2",
        "shimvalues",
        "uxnmr.par"
       ],
       "index": 5,
       "layout": "IPY_MODEL_81f0840efa2a4c5292109afb1f72973c",
       "rows": 8,
       "style": "IPY_MODEL_5f3341c9ef0e404b898938b5cd92c64d"
      }
     },
     "ea9a940dfdec4245b16775df972eb434": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_a84eebf777844f60bb775c5f6ee65f0c",
        "IPY_MODEL_1659b6218b52472aaee8231000855a3f",
        "IPY_MODEL_27267d9fa19343a8832c76ba935cc86d",
        "IPY_MODEL_45d5a8b8fb664cf1a3058f06c8d90961"
       ],
       "layout": "IPY_MODEL_af71e66edc04468cb606162be879ecf1"
      }
     },
     "eb0228abb758418fb6770d70fb68f310": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "/home/mad/Documents/spike/Notebooks",
        "/home/mad/Documents/spike",
        "/home/mad/Documents",
        "/home/mad",
        "/home",
        "/"
       ],
       "index": 0,
       "layout": "IPY_MODEL_d555c757c5f447dc8fe2b298e479db14",
       "style": "IPY_MODEL_accf2236d43e48e48d056d2a718bf612"
      }
     },
     "eb48c668fa814d8ab80f66c66707aab5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "eb59d632c3da4521b11ed4d491943038": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "ec23e43c23294b448734fdac6cb0971e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_036e9e1201cf428084301243a1bada53",
        "IPY_MODEL_c7bcbf57a288403fa667b8de2405a62f"
       ],
       "layout": "IPY_MODEL_cba8dfc05bbb483c910416a0b926b5f4"
      }
     },
     "ec7fe2e1fa654f86a87ff697cda7b14f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "ecc6dc097f4b407abdce8694f3887488": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "ecfda34b356d477db54ee1c3d6793284": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatTextModel",
      "state": {
       "layout": "IPY_MODEL_3813bc33c5484939a473f12b8cc81084",
       "step": null,
       "style": "IPY_MODEL_51244b4357144021b81dfaeda42c6177"
      }
     },
     "ee59b1fd64724d238d58fdd768369807": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "ee7be73adfc6432eb2e5314d161043bf": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "height": "10.16cm",
       "width": "80px"
      }
     },
     "f0343ccdbeca43a980b1da356c14bb0c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f061ef580a2a41f3ae9c16fa3f5e90db": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "f18f3400df1d4769b77c56b38aa3a28e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "f19bbe263cfe4fadbba3b7c8f0dda4f6": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_abad509919ef40618b10657fc5181f79",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "f1e23dfe17984a7b9aa59d7473874228": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f20aae09d105477ca77455f7f6662f5e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "warning",
       "description": "Rem",
       "layout": "IPY_MODEL_6e884f90398944ce9e49ba1ab490ae13",
       "style": "IPY_MODEL_742e148428214f718bd1c7d23368a8ff",
       "tooltip": "Remove all entries in current zoom"
      }
     },
     "f2a24a2351f042ac90a0f09247980dfc": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f2b1ecc005184d6a993c0bd0f1c6fc38": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "20%"
      }
     },
     "f35bb9c55a1641f38769fece82abd970": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_c1378385616444978461869aab8ae4cf",
        "IPY_MODEL_91d8e532638944309ded3e54f41ad1db",
        "IPY_MODEL_ecfda34b356d477db54ee1c3d6793284",
        "IPY_MODEL_fc905d4dc9f94b2498c29133b42dc301",
        "IPY_MODEL_08ff3041d42e4ef5a35b372a0f007ca5"
       ],
       "layout": "IPY_MODEL_05ef19d07715445b88ac31fb28f77784"
      }
     },
     "f41f6de1c8d1470f9487d9372175b302": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "MPLCanvasModel",
      "state": {
       "_figure_label": "Figure 2",
       "_height": 480,
       "_width": 640,
       "layout": "IPY_MODEL_a0857ad006e84dc8a8bc549eb63f2978",
       "toolbar": "IPY_MODEL_daed713461ed429fb297b73c35be8752",
       "toolbar_position": "left"
      }
     },
     "f450dea406df4273beb577062ffcc46a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_624b88aaa2bc4e058e79080295f6797f",
       "style": "IPY_MODEL_e5e069afb1c74de4ac2f0c7e836b3a32",
       "value": "<b>3</b>"
      }
     },
     "f47fc024ec014621a8a0ee101e3892a1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f4b30714278e455e9513a9fc72c81de8": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "up",
        "down",
        "off"
       ],
       "index": 2,
       "layout": "IPY_MODEL_ae6fc09c2df1429cb5e8abcc24d91290",
       "style": "IPY_MODEL_dc0eefcde81f469ba259c3f66ae3a54e"
      }
     },
     "f4d6c24f113643509d414d5445bb9f5f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TabModel",
      "state": {
       "_titles": {
        "0": "Spectrum",
        "1": "Data-List"
       },
       "children": [
        "IPY_MODEL_7b07fdcb03cc43759c5281301639eee4",
        "IPY_MODEL_c7552dbff90a4e33b795a1387e5453f3"
       ],
       "layout": "IPY_MODEL_44db0206fba847b789f9fbb077d0d90f"
      }
     },
     "f59d44e8ec8e46fb8dffe4b20dfd3ebe": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "f624cce7a16842b58f6140ad1a8b4de4": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f62a70cd075546a1925584f48b58b5d0": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f6533e8c04ae46fa9a6099f6006324b0": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "40em"
      }
     },
     "f6c7a686a37f4179a08ea69a763c4e6e": {
      "model_module": "jupyter-matplotlib",
      "model_module_version": "^0.7.2",
      "model_name": "ToolbarModel",
      "state": {
       "layout": "IPY_MODEL_8bda77d9f3334138a57172adb65bf9f0",
       "toolitems": [
        [
         "Home",
         "Reset original view",
         "home",
         "home"
        ],
        [
         "Back",
         "Back to previous view",
         "arrow-left",
         "back"
        ],
        [
         "Forward",
         "Forward to next view",
         "arrow-right",
         "forward"
        ],
        [
         "Pan",
         "Pan axes with left mouse, zoom with right",
         "arrows",
         "pan"
        ],
        [
         "Zoom",
         "Zoom to rectangle",
         "square-o",
         "zoom"
        ],
        [
         "Download",
         "Download plot",
         "floppy-o",
         "save_figure"
        ]
       ]
      }
     },
     "f78a9569829944c8a4fbffb184dd9ef3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "f7d77347107347ef8eda62f468a174f0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TextModel",
      "state": {
       "layout": "IPY_MODEL_9ced57391f5d42d08264b35845ff7fe5",
       "placeholder": "output filename",
       "style": "IPY_MODEL_8e2c28cedc9e41d3bf99c3fcf13fb8f3",
       "value": "fid"
      }
     },
     "f7e01043c17645699bbfaaf9a0ab78cc": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f804c81d91744c529fe14b317c6d045e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f87f44f4687f4d38b83c2bbcb9a73e8e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatLogSliderModel",
      "state": {
       "continuous_update": false,
       "description": "sensitivity",
       "layout": "IPY_MODEL_503fd24def8543f09a5b2419a5a0f3db",
       "max": 2,
       "min": -1,
       "readout": false,
       "readout_format": ".2f",
       "step": 0.01,
       "style": "IPY_MODEL_dc8e10175b71475fa9b4550621b28343",
       "value": 0.14791083881682077
      }
     },
     "fa5f84523af244f080777014f33f5841": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "CheckboxModel",
      "state": {
       "disabled": false,
       "layout": "IPY_MODEL_720266e38174468cad374c0e931f8f73",
       "style": "IPY_MODEL_abbc213d69984a468861148c97bd0a93",
       "value": false
      }
     },
     "fa9303cfb55f4e47972800fdef9b3c6e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "fb053362d0534c0cb724078a5465708f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "fb4ce1a2829a4944962869f0bfec06a6": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "TabModel",
      "state": {
       "_titles": {
        "0": "Peak Picker",
        "1": "calibration",
        "2": "Peak Table"
       },
       "children": [
        "IPY_MODEL_b63f4c8749ed4838b3592dfd48868699",
        "IPY_MODEL_1de0691e049545e6bf51d03ff5bab3be",
        "IPY_MODEL_a7838ba1abe7438b91bce89489fa5d56"
       ],
       "layout": "IPY_MODEL_75ebac3e976f4f08b5ce22a3787771b2"
      }
     },
     "fc905d4dc9f94b2498c29133b42dc301": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "black",
        "red",
        "blue",
        "green",
        "orange",
        "blueviolet",
        "crimson",
        "turquoise",
        "indigo",
        "magenta",
        "gold",
        "pink",
        "purple",
        "salmon",
        "darkblue",
        "sienna"
       ],
       "index": 6,
       "layout": "IPY_MODEL_9fd56529c6f34ab491458405f7357928",
       "style": "IPY_MODEL_8bc95cae32f54bbcb977119728b36b06"
      }
     },
     "fcceef8c980a4a63b34bdeb7eb205604": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DropdownModel",
      "state": {
       "_options_labels": [
        "up",
        "down",
        "off"
       ],
       "index": 2,
       "layout": "IPY_MODEL_9d384ab2f333416883bbcf3e8debab85",
       "style": "IPY_MODEL_48ffca90df1b472a917f75f4c24023b0"
      }
     },
     "fde69c4f770a4a1495e8ecb5ea139fb3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_2c8de912ac12492c87290e2b303a21a1",
        "IPY_MODEL_32e09935ce914924b4c6c3024ab29c8e",
        "IPY_MODEL_e3f2d35fc5d64203914355525667c0f5",
        "IPY_MODEL_7fa0c872f37149bf9e34040fa51b11fc",
        "IPY_MODEL_f4b30714278e455e9513a9fc72c81de8"
       ],
       "layout": "IPY_MODEL_d0e30bb3c1db499abeb61eb0e0aa0e08"
      }
     },
     "fe597743545f4e7fa3856db25cab2ae5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "success",
       "description": "Reset",
       "layout": "IPY_MODEL_385ef4626b2c42e9a393f21aef47b6ed",
       "style": "IPY_MODEL_664006c5444a42a4ad7ac08d7764dbd6",
       "tooltip": "Reset to full spectrum"
      }
     },
     "ff5a816f8da3432182ab8d2be9e416a5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SelectModel",
      "state": {
       "_options_labels": [
        "..",
        "DisplayFTICR2D.ipynb",
        "DisplayFTICR2D.py",
        "EasyDisplayFTICR2D.ipynb",
        "EasyDisplayFTICR2D.py",
        "Proc1DNMR.ipynb",
        "Proc1DNMR.py",
        "Proc2DNMR.ipynb",
        "ProcDOSY.ipynb",
        "ProcessFTICR-MS.ipynb",
        "README.md"
       ],
       "index": null,
       "layout": "IPY_MODEL_ba040b14431541caa1f7732d3ae2054c",
       "rows": 8,
       "style": "IPY_MODEL_d8a2ab056f6d4e429a5b4c3595f73c0a"
      }
     },
     "ffe28375aa344ea69e948224087e38d5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_30bf0647211245a0a1ac2868d5dbff92",
        "IPY_MODEL_3d8df43e1a4842fca73ada21d68a35c1",
        "IPY_MODEL_8ae2ce461cf64607a2d023d96ba41f8f",
        "IPY_MODEL_8c09d7e004224455bc2cfb6e60e9c900"
       ],
       "layout": "IPY_MODEL_f804c81d91744c529fe14b317c6d045e"
      }
     },
     "ffea2bd2d6414610826e691267dc853c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}