{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calibration of a 2 theta arm with a Pilatus 100k detector\n",
    "\n",
    "The aim of this document is to explain how to use pyFAI.goniometer for calibrating the position of the detector from the goniometer encoders.\n",
    "\n",
    "Those data have been acquired at ROBL (ESRF-BM20 German CRG) in winter 2017 by Christoph Henning using a Pilatus 100k detector and LaB6 as calibrant. One hundred and twenty one images have been acquired with the detector moving between 5 and 65 degree with a step size of half a degree. The motor position is registered in the filename.\n",
    "\n",
    "A prior manual calibration (using pyFAI-calib) has been performed on four images locate at 31.5, 33.5, 35 and 35.5 degrees. Those images were the first with two rings. The control points extrated during this initial calibration has been used as a starting point for this calibration. Then more images have been added to make the model more robust.\n",
    "\n",
    "The raw data files are available at: http://www.silx.org/pub/pyFAI/gonio/Pilatus-100k-LaB6/\n",
    "\n",
    "## Initialization and loading of the libraries\n",
    "\n",
    "Initialization of the plotting library, matplotlib, to be used with the jupyter notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mntdirect/_scisoft/users/jupyter/jupy35/lib/python3.5/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using pyFAI version 0.15.0-beta2\n"
     ]
    }
   ],
   "source": [
    "%pylab nbagg\n",
    "\n",
    "import time, pyFAI\n",
    "start_time = time.time()\n",
    "print(\"Using pyFAI version\", pyFAI.version)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['LaB6_gonio_BM20', 'del_45.0_0001p.cbf', 'del_08.5_0001p.cbf', 'del_20.5_0001p.cbf', 'minimum-mask.edf', 'del_09.0_0001p.cbf', 'del_53.0_0001p.cbf', 'del_60.0_0001p.cbf', 'del_63.5_0001p.cbf', 'del_56.5_0001p.cbf', 'del_12.5_0001p.cbf', 'del_53.5_0001p.cbf', 'del_42.5_0001p.cbf', 'del_16.5_0001p.cbf', 'del_05.5_0001p.cbf', 'del_47.0_0001p.cbf', 'del_39.0_0001p.cbf', 'del_47.5_0001p.cbf', 'del_57.0_0001p.cbf', 'del_35.5_0001p.poni', 'del_07.5_0001p.cbf', 'del_41.5_0001p.cbf', 'del_51.0_0001p.cbf', 'del_33.0_0001p.cbf', 'del_22.0_0001p.cbf', 'del_43.5_0001p.cbf', 'del_64.5_0001p.cbf', 'del_35.0_0001p.cbf', 'del_13.5_0001p.cbf', 'del_08.0_0001p.cbf', 'del_29.0_0001p.cbf', 'del_45.5_0001p.cbf', 'del_63.0_0001p.cbf', 'del_61.5_0001p.cbf', 'del_31.5_0001p.npt', 'del_11.0_0001p.cbf', 'del_46.5_0001p.cbf', 'del_11.5_0001p.cbf', 'del_56.0_0001p.cbf', 'del_18.0_0001p.cbf', 'del_06.5_0001p.cbf', 'del_46.0_0001p.cbf', 'del_58.5_0001p.cbf', 'del_35.5_0001p.npt', 'del_30.0_0001p.cbf', 'del_15.5_0001p.cbf', 'del_36.5_0001p.cbf', 'del_13.0_0001p.cbf', 'del_55.0_0001p.cbf', 'del_27.5_0001p.cbf', 'del_31.5_0001p.cbf', 'del_24.0_0001p.cbf', 'del_38.0_0001p.cbf', 'del_48.5_0001p.cbf', 'del_16.0_0001p.cbf', 'del_52.5_0001p.cbf', 'del_38.5_0001p.cbf', 'del_54.5_0001p.cbf', 'del_48.0_0001p.cbf', 'del_31.0_0001p.cbf', 'del_28.5_0001p.cbf', 'del_21.5_0001p.cbf', 'del_06.0_0001p.cbf', 'del_25.5_0001p.cbf', 'del_40.5_0001p.cbf', 'del_44.5_0001p.cbf', 'del_39.5_0001p.cbf', 'del_35.5_0001p.cbf', 'del_62.0_0001p.cbf', 'del_36.0_0001p.cbf', 'del_57.5_0001p.cbf', 'del_28.0_0001p.cbf', 'del_17.5_0001p.cbf', 'del_24.5_0001p.cbf', 'del_35.0_0001p.poni', 'del_50.5_0001p.cbf', 'del_18.5_0001p.cbf', 'del_27.0_0001p.cbf', 'del_19.5_0001p.cbf', 'del_21.0_0001p.cbf', 'del_17.0_0001p.cbf', 'del_50.0_0001p.cbf', 'del_44.0_0001p.cbf', 'del_30.5_0001p.cbf', 'del_51.5_0001p.cbf', 'del_62.5_0001p.cbf', 'del_05.0_0001p.cbf', 'del_26.5_0001p.cbf', 'del_31.5_0001p.poni', 'del_23.5_0001p.cbf', 'del_33.5_0001p.poni', 'del_37.5_0001p.cbf', 'del_19.0_0001p.cbf', 'del_29.5_0001p.cbf', 'del_10.0_0001p.cbf', 'del_40.0_0001p.cbf', 'del_58.0_0001p.cbf', 'del_49.5_0001p.cbf', 'del_09.5_0001p.cbf', 'del_15.0_0001p.cbf', 'del_43.0_0001p.cbf', 'del_60.5_0001p.cbf', 'del_34.0_0001p.cbf', 'del_20.0_0001p.cbf', 'deviation-mask.edf', 'del_41.0_0001p.cbf', 'del_07.0_0001p.cbf', 'del_54.0_0001p.cbf', 'del_33.5_0001p.npt', 'del_33.5_0001p.cbf', 'del_32.0_0001p.cbf', 'del_59.5_0001p.cbf', 'del_14.0_0001p.cbf', 'del_32.5_0001p.cbf', 'del_59.0_0001p.cbf', 'del_65.0_0001p.cbf', 'del_25.0_0001p.cbf', 'del_61.0_0001p.cbf', 'del_34.5_0001p.cbf', 'del_52.0_0001p.cbf', 'del_22.5_0001p.cbf', 'del_10.5_0001p.cbf', 'del_42.0_0001p.cbf', 'del_64.0_0001p.cbf', 'del_14.5_0001p.cbf', 'del_26.0_0001p.cbf', 'del_49.0_0001p.cbf', 'del_35.0_0001p.npt', 'del_55.5_0001p.cbf', 'del_23.0_0001p.cbf', 'del_12.0_0001p.cbf', 'del_37.0_0001p.cbf']\n"
     ]
    }
   ],
   "source": [
    "#Download all images\n",
    "\n",
    "import os\n",
    "from silx.resources import ExternalResources\n",
    "\n",
    "#Nota: Comment when outside ESRF\n",
    "os.environ[\"http_proxy\"] = \"http://proxy.esrf.fr:3128\"\n",
    "\n",
    "downloader = ExternalResources(\"pyFAI\", \"http://www.silx.org/pub/pyFAI/testimages\", \"PYFAI_DATA\")\n",
    "all_files = downloader.getdir(\"LaB6_gonio_BM20.tar.bz2\")\n",
    "print([os.path.basename(i) for i in all_files])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Loading of a few libraries\n",
    "\n",
    "import os\n",
    "import random\n",
    "import fabio\n",
    "import pyFAI\n",
    "from pyFAI.goniometer import GeometryTransformation, GoniometerRefinement, Goniometer\n",
    "from pyFAI.gui import jupyter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display of an image and its headers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "List of images: /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_05.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_05.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_06.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_06.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_07.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_07.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_08.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_08.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_09.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_09.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_10.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_10.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_11.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_11.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_12.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_12.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_13.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_13.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_14.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_14.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_15.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_15.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_16.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_16.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_17.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_17.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_18.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_18.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_19.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_19.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_20.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_20.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_21.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_21.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_22.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_22.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_23.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_23.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_24.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_24.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_25.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_25.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_26.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_26.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_27.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_27.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_28.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_28.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_29.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_29.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_30.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_30.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_31.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_31.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_32.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_32.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_33.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_33.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_34.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_34.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_35.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_35.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_36.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_36.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_37.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_37.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_38.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_38.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_39.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_39.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_40.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_40.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_41.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_41.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_42.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_42.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_43.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_43.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_44.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_44.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_45.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_45.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_46.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_46.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_47.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_47.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_48.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_48.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_49.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_49.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_50.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_50.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_51.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_51.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_52.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_52.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_53.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_53.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_54.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_54.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_55.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_55.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_56.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_56.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_57.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_57.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_58.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_58.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_59.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_59.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_60.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_60.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_61.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_61.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_62.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_62.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_63.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_63.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_64.0_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_64.5_0001p.cbf, /tmp/pyFAI_testdata_kieffer/LaB6_gonio_BM20/del_65.0_0001p.cbf.\n",
      "\n",
      "Image headers:\n",
      "_array_data.header_convention: PILATUS_1.2\n",
      "_array_data.header_contents: # Detector: PILATUS 2M, 24-0111\r\n",
      "# 2016-05-17T18:12:57.232113\r\n",
      "# Pixel_size 172e-6 m x 172e-6 m\r\n",
      "# Silicon sensor, thickness 0.000450 m\r\n",
      "# Exposure_time 9.9977 s\r\n",
      "# Exposure_period 9.9977 s\r\n",
      "# Tau = 1.991e-07 s\r\n",
      "# Count_cutoff 1071182 counts\r\n",
      "# Threshold_setting: 4024.0 eV\r\n",
      "# Gain_setting: low gain (vrf = -0.300)\r\n",
      "# N_excluded_pixels = 1\r\n",
      "# Excluded_pixels: badpix_mask.tif\r\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\r\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\r\n",
      "# Image_path: /ramdisk/\r\n",
      "# Wavelength 0.7749 A\r\n",
      "# Start_angle 0.00 deg.\r\n",
      "# Angle_increment 0.00 deg.\r\n",
      "# Omega 0.00 deg.\r\n",
      "# Omega_increment 0.00 deg.\r\n",
      "# Phi 0.00 deg.\r\n",
      "# Phi_increment 0.00 deg.\r\n",
      "# Kappa 0.0 deg.\r\n",
      "# Oscillation_axis PHI\r\n",
      "# Detector_distance 0.157 m\r\n",
      "# Detector_Voffset 0.0 m\r\n",
      "# Beam_xy (542.41, 732.4) pixels\r\n",
      "# Flux 0 counts\r\n",
      "# Temperature 0.00 K\r\n",
      "# Blower 0.0 C\r\n",
      "# Lakeshore 0.00 K\n",
      "Content-Type: application/octet-stream;\n",
      "conversions: x-CBF_BYTE_OFFSET\n",
      "Content-Transfer-Encoding: BINARY\n",
      "X-Binary-Size: 95035\n",
      "X-Binary-ID: 1\n",
      "X-Binary-Element-Type: signed 32-bit integer\n",
      "X-Binary-Element-Byte-Order: LITTLE_ENDIAN\n",
      "Content-MD5: darooj/7FEQRNdNzNDo0XQ==\n",
      "X-Binary-Number-of-Elements: 94965\n",
      "X-Binary-Size-Fastest-Dimension: 487\n",
      "X-Binary-Size-Second-Dimension: 195\n",
      "X-Binary-Size-Padding: 4095\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f1d597180b8>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading of the list of files, and display of the last one with its headers\n",
    "\n",
    "image_files = [i for i in all_files if i.endswith(\".cbf\")]\n",
    "image_files.sort()\n",
    "print(\"List of images: \" + \", \".join(image_files) + \".\" + os.linesep)\n",
    "fimg = fabio.open(image_files[-1])\n",
    "\n",
    "print(\"Image headers:\")\n",
    "for key, value in  fimg.header.items():\n",
    "    print(\"%s: %s\"%(key,value))\n",
    "    \n",
    "jupyter.display(fimg.data, label=os.path.basename(fimg.filename))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Definition of the geometry transformation\n",
    "\n",
    "This is the most difficult part to understand.\n",
    "\n",
    "The next cell defines 2 functions, one for transforming the geometry and the other one to read the goniometer angle from the metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "filename del_65.0_0001p.cbf angle: 65.0\n"
     ]
    }
   ],
   "source": [
    "#Definition of the goniometer translation function:\n",
    "# The detector rotates vertically, around the horizontal axis, i.e. rot2\n",
    "\n",
    "goniotrans = GeometryTransformation(param_names = [\"dist\", \"poni1\", \"poni2\", \"rot1\",\n",
    "                                                   \"rot2_offset\", \"rot2_scale\"],\n",
    "                                    dist_expr=\"dist\", \n",
    "                                    poni1_expr=\"poni1\",\n",
    "                                    poni2_expr=\"poni2\", \n",
    "                                    rot1_expr=\"rot1\", \n",
    "                                    rot2_expr=\"rot2_scale * pos + rot2_offset\", \n",
    "                                    rot3_expr=\"0.0\")\n",
    "\n",
    "\n",
    "#Definition of the function reading the goniometer angle from the filename of the image.\n",
    "\n",
    "def get_angle(basename):\n",
    "    \"\"\"Takes the basename (like del_65.0_0001p ) and returns the angle of the detector\"\"\"\n",
    "    return float(os.path.basename((basename.split(\"_\")[1])))\n",
    "\n",
    "basename = os.path.basename(fimg.filename)\n",
    "print('filename', basename, \"angle:\",get_angle(basename))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Definition of the detector, its mask, the calibrant\n",
    "mask_files = [i for i in all_files if i.endswith(\"-mask.edf\")]\n",
    "mask = numpy.logical_or(fabio.open(mask_files[0]).data, fabio.open(mask_files[1]).data)\n",
    "pilatus = pyFAI.detector_factory(\"Pilatus100k\")\n",
    "pilatus.mask = mask\n",
    "    \n",
    "LaB6 = pyFAI.calibrant.CALIBRANT_FACTORY(\"LaB6\")\n",
    "wavelength = 7.7490120575e-11\n",
    "LaB6.wavelength = wavelength"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty refinement object:\n",
      "GoniometerRefinement with 0 geometries labeled: .\n"
     ]
    }
   ],
   "source": [
    "#Definition of the geometry refinement: the parameter order is the same as the param_names\n",
    "\n",
    "param = {\"dist\":0.8, \n",
    "         \"poni1\":0.02, \n",
    "         \"poni2\":0.04, \n",
    "         \"rot1\":0,\n",
    "         \"rot2_offset\":0,\n",
    "         \"rot2_scale\": numpy.pi/180. # rot2 is in radians, while the motor position is in degrees\n",
    "        }\n",
    "#Defines the bounds for some variables\n",
    "bounds = {\"dist\": (0.79, 0.81), \n",
    "          \"rot1\": (-0.01, 0.01),\n",
    "          \"rot2_offset\": (-0.01, 0.01),\n",
    "          \"rot2_scale\": (numpy.pi/180., numpy.pi/180.) #strict bounds on the scale: we expect the gonio to be precise\n",
    "         }\n",
    "gonioref = GoniometerRefinement(param, #initial guess\n",
    "                                bounds=bounds,\n",
    "                                pos_function=get_angle,\n",
    "                                trans_function=goniotrans,\n",
    "                                detector=pilatus, wavelength=wavelength)\n",
    "print(\"Empty refinement object:\")\n",
    "print(gonioref)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "del_31.5_0001p Angle: 31.5\n",
      "Detector Pilatus 100k\t PixelSize= 1.720e-04, 1.720e-04 m\n",
      "Wavelength= 7.749012e-11m\n",
      "SampleDetDist= 8.058209e-01m\tPONI= 5.700310e-03, 4.599931e-02m\trot1=-0.000000  rot2= 0.560707  rot3= -0.000065 rad\n",
      "DirectBeamDist= 951.518mm\tCenter: x=267.438, y=2975.017 pix\tTilt=32.126 deg  tiltPlanRotation= 90.000 deg\n",
      "\n",
      "del_33.5_0001p Angle: 33.5\n",
      "Detector Pilatus 100k\t PixelSize= 1.720e-04, 1.720e-04 m\n",
      "Wavelength= 7.749012e-11m\n",
      "SampleDetDist= 8.061475e-01m\tPONI= 1.998418e-02, 4.623309e-02m\trot1=0.000061  rot2= 0.577898  rot3= -0.000000 rad\n",
      "DirectBeamDist= 962.435mm\tCenter: x=268.511, y=3172.837 pix\tTilt=33.111 deg  tiltPlanRotation= 90.005 deg\n",
      "\n",
      "del_35.0_0001p Angle: 35.0\n",
      "Detector Pilatus 100k\t PixelSize= 1.720e-04, 1.720e-04 m\n",
      "Wavelength= 7.749012e-11m\n",
      "SampleDetDist= 8.053432e-01m\tPONI= 5.551240e-03, 4.624546e-02m\trot1=-0.000016  rot2= 0.622009  rot3= 0.000012 rad\n",
      "DirectBeamDist= 990.936mm\tCenter: x=268.944, y=3389.181 pix\tTilt=35.638 deg  tiltPlanRotation= 89.999 deg\n",
      "\n",
      "del_35.5_0001p Angle: 35.5\n",
      "Detector Pilatus 100k\t PixelSize= 1.720e-04, 1.720e-04 m\n",
      "Wavelength= 7.749012e-11m\n",
      "SampleDetDist= 8.061272e-01m\tPONI= 5.998339e-03, 3.450065e-02m\trot1=-0.014779  rot2= 0.630136  rot3= 0.000007 rad\n",
      "DirectBeamDist= 997.856mm\tCenter: x=269.857, y=3453.432 pix\tTilt=36.113 deg  tiltPlanRotation= 88.839 deg\n",
      "\n",
      "Filled refinement object:\n",
      "GoniometerRefinement with 4 geometries labeled: del_31.5_0001p, del_33.5_0001p, del_35.0_0001p, del_35.5_0001p.\n"
     ]
    }
   ],
   "source": [
    "#Let's populate the goniometer refinement object with all control point files:\n",
    "\n",
    "ponis = [i for i in all_files if i.endswith(\".poni\")]\n",
    "ponis.sort()\n",
    "for fn in ponis:\n",
    "    base = os.path.splitext(fn)[0]\n",
    "    basename = os.path.basename(base)\n",
    "    fimg = fabio.open(base + \".cbf\")\n",
    "    sg =gonioref.new_geometry(basename, image=fimg.data, metadata=basename, control_points=base+\".npt\",\n",
    "                              geometry=fn, calibrant=LaB6)\n",
    "    print(sg.label, \"Angle:\", sg.get_position())\n",
    "    print(sg.geometry_refinement)\n",
    "    print()\n",
    "    \n",
    "\n",
    "print(\"Filled refinement object:\")\n",
    "print(gonioref)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
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       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
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       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
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       "            event.step = -1;\n",
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       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n",
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n",
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n"
     ]
    }
   ],
   "source": [
    "#Display all images with associated calibration:\n",
    "nimg = len(gonioref.single_geometries)\n",
    "fig,ax = subplots(nimg, 1, figsize=(8,nimg*3))\n",
    "for i, sg in enumerate(gonioref.single_geometries.values()):\n",
    "    jupyter.display(sg=sg, ax=ax[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function before refinement: 4.676280279481871e-05\n",
      "[0.8        0.02       0.04       0.         0.         0.01745329]\n",
      "     fun: 3.4745458906298305e-09\n",
      "     jac: array([ 1.55798347e-08,  6.20440474e-08, -8.86844706e-09,  9.38192904e-09,\n",
      "        4.54171479e-08,  5.30001824e-06])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 145\n",
      "     nit: 18\n",
      "    njev: 18\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 0.80587963,  0.01626972,  0.04374852, -0.00299843, -0.00217847,\n",
      "        0.01745329])\n",
      "Cost function after refinement: 3.4745458906298305e-09\n",
      "GonioParam(dist=0.8058796325498109, poni1=0.016269720089887214, poni2=0.04374852459791066, rot1=-0.00299843026796996, rot2_offset=-0.002178469918866194, rot2_scale=0.017453292519943295)\n",
      "maxdelta on: dist (0) 0.8 --> 0.8058796325498109\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ 0.80587963,  0.01626972,  0.04374852, -0.00299843, -0.00217847,\n",
       "        0.01745329])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Initial refinement of the goniometer model with 5 dof\n",
    "gonioref.refine2()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This function adds new images to the pool of data used for the refinement.\n",
    "# A set of new control points are extractred and a refinement step is performed at each iteration\n",
    "# The last image of the serie is displayed \n",
    "\n",
    "def optimize_with_new_images(list_images, pts_per_deg=1):\n",
    "    sg = None\n",
    "    for fname in list_images:\n",
    "        print()\n",
    "        basename = os.path.basename(fname)\n",
    "        base = os.path.splitext(basename)[0]\n",
    "        fimg = fabio.open(fname)\n",
    "        if base in gonioref.single_geometries:\n",
    "            continue\n",
    "        print(base)\n",
    "        sg = gonioref.new_geometry(base, image=fimg.data, metadata=base,\n",
    "                                   calibrant=LaB6)\n",
    "        print(sg.extract_cp(pts_per_deg=pts_per_deg))\n",
    "    print(\"*\"*50)\n",
    "    gonioref.refine2()\n",
    "    if sg: \n",
    "        sg.geometry_refinement.set_param(gonioref.get_ai(sg.get_position()).param)\n",
    "        jupyter.display(sg=sg)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "del_38.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# c ring 10: 30 points\n",
      "\n",
      "del_37.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "# d ring 9: 36 points\n",
      "# e ring 10: 30 points\n",
      "\n",
      "del_39.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "# f ring 10: 15 points\n",
      "# g ring 11: 30 points\n",
      "\n",
      "\n",
      "del_38.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "# h ring 10: 30 points\n",
      "# i ring 11: 30 points\n",
      "\n",
      "del_34.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# j ring 8: 36 points\n",
      "\n",
      "del_39.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# k ring 11: 30 points\n",
      "\n",
      "del_37.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# l ring 10: 30 points\n",
      "\n",
      "del_32.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# m ring 7: 36 points\n",
      "\n",
      "\n",
      "del_30.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# n ring 6: 36 points\n",
      "\n",
      "del_31.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# o ring 6: 36 points\n",
      "\n",
      "\n",
      "\n",
      "del_30.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# p ring 6: 36 points\n",
      "\n",
      "del_33.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# q ring 7: 36 points\n",
      "\n",
      "del_34.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# r ring 8: 36 points\n",
      "\n",
      "del_36.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# s ring 9: 36 points\n",
      "\n",
      "del_36.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# t ring 9: 36 points\n",
      "\n",
      "del_32.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# u ring 7: 36 points\n",
      "**************************************************\n",
      "Cost function before refinement: 4.097864013507303e-09\n",
      "[ 0.80587963  0.01626972  0.04374852 -0.00299843 -0.00217847  0.01745329]\n",
      "     fun: 4.095358587426548e-09\n",
      "     jac: array([-2.09621602e-08, -3.75474077e-08, -4.46324245e-07,  3.60680487e-07,\n",
      "       -3.44887518e-08, -5.55667005e-05])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 17\n",
      "     nit: 2\n",
      "    njev: 2\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 0.80587964,  0.01626894,  0.04374861, -0.0029985 , -0.0021791 ,\n",
      "        0.01745329])\n",
      "Cost function after refinement: 4.095358587426548e-09\n",
      "GonioParam(dist=0.8058796378951448, poni1=0.01626894207056116, poni2=0.043748607973928, rot1=-0.002998497653594761, rot2_offset=-0.0021790961565278, rot2_scale=0.017453292519943295)\n",
      "maxdelta on: poni1 (1) 0.016269720089887214 --> 0.01626894207056116\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
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     "output_type": "display_data"
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Append all other images bewteen 30 and 40 degrees\n",
    "\n",
    "images_30_40 = [i for i in all_files if (\"del_3\" in i and i.endswith(\"0001p.cbf\"))]\n",
    "random.shuffle(images_30_40)\n",
    "optimize_with_new_images(images_30_40, pts_per_deg=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "del_49.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "# v ring 17: 8 points\n",
      "# w ring 18: 3 points\n",
      "\n",
      "del_41.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# x ring 12: 10 points\n",
      "\n",
      "del_62.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# y ring 25: 8 points\n",
      "\n",
      "\n",
      "del_46.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "# z ring 14: 7 points\n",
      "#aa ring 15: 10 points\n",
      "\n",
      "\n",
      "\n",
      "del_10.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ab ring 0: 29 points\n",
      "\n",
      "del_20.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ac ring 3: 17 points\n",
      "\n",
      "del_51.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ad ring 18: 8 points\n",
      "#ae ring 19: 8 points\n",
      "\n",
      "del_15.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#af ring 1: 24 points\n",
      "\n",
      "del_17.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ag ring 2: 10 points\n",
      "\n",
      "del_23.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ah ring 4: 16 points\n",
      "\n",
      "del_22.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ai ring 3: 17 points\n",
      "\n",
      "\n",
      "del_43.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#aj ring 13: 10 points\n",
      "\n",
      "del_24.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ak ring 4: 15 points\n",
      "\n",
      "del_29.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_65.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#al ring 27: 8 points\n",
      "#am ring 28: 8 points\n",
      "\n",
      "del_54.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#an ring 20: 8 points\n",
      "\n",
      "del_28.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_58.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ao ring 22: 8 points\n",
      "#ap ring 23: 8 points\n",
      "\n",
      "del_15.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#aq ring 1: 24 points\n",
      "\n",
      "del_19.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ar ring 2: 19 points\n",
      "\n",
      "del_44.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#as ring 13: 10 points\n",
      "#at ring 14: 10 points\n",
      "\n",
      "\n",
      "del_40.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#au ring 11: 10 points\n",
      "#av ring 12: 10 points\n",
      "\n",
      "del_52.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#aw ring 19: 8 points\n",
      "\n",
      "del_40.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ax ring 11: 10 points\n",
      "#ay ring 12: 10 points\n",
      "\n",
      "del_53.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#az ring 19: 8 points\n",
      "\n",
      "del_26.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ba ring 5: 14 points\n",
      "\n",
      "del_26.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bb ring 5: 14 points\n",
      "\n",
      "del_07.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "\n",
      "del_61.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bc ring 24: 8 points\n",
      "#bd ring 25: 8 points\n",
      "\n",
      "del_51.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#be ring 18: 8 points\n",
      "#bf ring 19: 8 points\n",
      "\n",
      "del_64.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bg ring 26: 8 points\n",
      "#bh ring 27: 8 points\n",
      "\n",
      "del_42.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_16.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bi ring 1: 24 points\n",
      "\n",
      "del_11.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bj ring 0: 28 points\n",
      "\n",
      "del_29.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bk ring 6: 7 points\n",
      "\n",
      "\n",
      "del_20.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_06.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_42.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bl ring 12: 10 points\n",
      "\n",
      "del_24.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bm ring 4: 16 points\n",
      "\n",
      "del_07.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_45.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bn ring 14: 10 points\n",
      "#bo ring 15: 2 points\n",
      "\n",
      "del_49.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bp ring 16: 9 points\n",
      "#bq ring 17: 9 points\n",
      "\n",
      "del_21.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#br ring 3: 17 points\n",
      "\n",
      "del_57.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bs ring 22: 8 points\n",
      "#bt ring 23: 8 points\n",
      "\n",
      "del_21.5_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bu ring 3: 17 points\n",
      "\n",
      "del_60.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bv ring 24: 8 points\n",
      "#bw ring 25: 8 points\n",
      "\n",
      "\n",
      "\n",
      "del_48.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bx ring 16: 9 points\n",
      "#by ring 17: 9 points\n",
      "\n",
      "del_46.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bz ring 14: 10 points\n",
      "#ca ring 15: 10 points\n",
      "\n",
      "del_13.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_44.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cb ring 13: 9 points\n",
      "\n",
      "del_25.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cc ring 5: 14 points\n",
      "\n",
      "del_25.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cd ring 4: 16 points\n",
      "\n",
      "del_56.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ce ring 21: 8 points\n",
      "#cf ring 22: 8 points\n",
      "\n",
      "del_08.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "\n",
      "del_10.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cg ring 0: 32 points\n",
      "\n",
      "del_59.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ch ring 23: 8 points\n",
      "\n",
      "\n",
      "del_27.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ci ring 5: 14 points\n",
      "\n",
      "del_17.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_19.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cj ring 2: 19 points\n",
      "\n",
      "del_53.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ck ring 20: 8 points\n",
      "\n",
      "\n",
      "del_58.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cl ring 23: 8 points\n",
      "\n",
      "del_12.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cm ring 0: 9 points\n",
      "\n",
      "del_13.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_55.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#cn ring 20: 8 points\n",
      "#co ring 21: 8 points\n",
      "\n",
      "\n",
      "del_14.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cp ring 1: 24 points\n",
      "\n",
      "del_09.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cq ring 0: 14 points\n",
      "\n",
      "del_05.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "\n",
      "del_57.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#cr ring 22: 8 points\n",
      "#cs ring 23: 8 points\n",
      "\n",
      "del_50.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ct ring 17: 9 points\n",
      "#cu ring 18: 8 points\n",
      "\n",
      "del_16.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_05.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "\n",
      "del_62.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cv ring 25: 8 points\n",
      "\n",
      "del_11.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cw ring 0: 28 points\n",
      "\n",
      "del_41.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cx ring 12: 10 points\n",
      "\n",
      "del_08.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "\n",
      "del_60.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cy ring 24: 8 points\n",
      "\n",
      "del_06.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "\n",
      "del_18.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cz ring 2: 19 points\n",
      "\n",
      "del_27.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#da ring 5: 14 points\n",
      "\n",
      "del_14.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#db ring 1: 10 points\n",
      "\n",
      "del_52.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dc ring 19: 8 points\n",
      "\n",
      "del_63.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dd ring 26: 7 points\n",
      "\n",
      "del_47.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#de ring 15: 10 points\n",
      "#df ring 16: 9 points\n",
      "\n",
      "\n",
      "del_54.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dg ring 20: 8 points\n",
      "#dh ring 21: 3 points\n",
      "\n",
      "del_47.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#di ring 15: 10 points\n",
      "#dj ring 16: 9 points\n",
      "\n",
      "del_59.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dk ring 24: 8 points\n",
      "\n",
      "del_45.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dl ring 13: 9 points\n",
      "#dm ring 14: 10 points\n",
      "\n",
      "del_56.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dn ring 21: 8 points\n",
      "#do ring 22: 8 points\n",
      "\n",
      "del_48.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dp ring 16: 9 points\n",
      "\n",
      "del_28.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_09.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "del_23.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dq ring 4: 11 points\n",
      "\n",
      "del_61.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dr ring 24: 8 points\n",
      "#ds ring 25: 8 points\n",
      "\n",
      "del_12.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "\n",
      "del_18.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dt ring 2: 19 points\n",
      "\n",
      "del_64.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#du ring 26: 7 points\n",
      "#dv ring 27: 8 points\n",
      "\n",
      "del_63.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dw ring 26: 8 points\n",
      "\n",
      "\n",
      "del_55.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dx ring 20: 8 points\n",
      "#dy ring 21: 8 points\n",
      "\n",
      "del_22.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dz ring 3: 17 points\n",
      "\n",
      "del_50.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ea ring 17: 9 points\n",
      "#eb ring 18: 8 points\n",
      "\n",
      "del_43.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ec ring 13: 9 points\n",
      "**************************************************\n",
      "Cost function before refinement: 1.5011003040506577e-08\n",
      "[ 0.80587964  0.01626894  0.04374861 -0.0029985  -0.0021791   0.01745329]\n",
      "     fun: 1.2457867804583228e-08\n",
      "     jac: array([-9.40558914e-08,  8.95540001e-07, -1.79978717e-08,  9.93416860e-09,\n",
      "        7.23899196e-07, -1.02596643e-03])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 49\n",
      "     nit: 6\n",
      "    njev: 6\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 0.80588807,  0.01627369,  0.04329277, -0.00263014, -0.002175  ,\n",
      "        0.01745329])\n",
      "Cost function after refinement: 1.2457867804583228e-08\n",
      "GonioParam(dist=0.8058880718667252, poni1=0.01627369140392072, poni2=0.04329276923753028, rot1=-0.002630135406714632, rot2_offset=-0.002175004693620503, rot2_scale=0.017453292519943295)\n",
      "maxdelta on: poni2 (2) 0.043748607973928 --> 0.04329276923753028\n"
     ]
    },
    {
     "data": {
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       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Append all other images\n",
    "\n",
    "all_images = [i for i in all_files if i.endswith(\".cbf\")]\n",
    "random.shuffle(all_images)\n",
    "optimize_with_new_images(all_images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "First & last rings\n",
      "Total number of images: 121\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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mLfWbfRTOpoAHgNL5g16imd6vtEGPqedrJ3zO3YNTpidFr73mqPP7DBN/bXz4HnKd7Q/nTo/23oMPWNd4bFgvnhtQS4YLDPux+cP9vvn9hYALClZR7mmtdaPzs+AEMxVMgZm+2ywuBYFnqwTwAxv14AAhQdLhrKFubMhtdI1g8C9BhgoHjMPU0AEcIMSwoiisO3ZotQwDCh2nmEFy2f0C8bA9UH5GVgbACXr5P/pJxsdszcu39fg/TMOrouNEPW1wTYjRX14AXgZEwM3g0HAg+eO62IjcnTDoRH4AvxhcA04zATRDrOPydwd3XBoGAvADP8bUGCIKcNjRD3d90ub9/cjc3cM88frycyHy0/A5/ltwEVZ7gvWD2s1nQID5uzvdKjsMKTzwPPpi5x39LfBDPWgLrn2E2BybQJJz0uznF4TgFazeIBzzwnX3TrMbOfRDTNAD0h0/Rlz5sm5HbtHEQ/6wcCeteG+NUPvMcaZoEz3I+vWERTG36w4427HyWvccyYBtp10A0sDdRhaO2CedzwnHRe31Wv49LZ9/cG52wd9VwxgScn6yjWttf7hd64qEBY4Rtueo2n+j7/zO0fG4MG52wdDlGEFM0c8J5Xg0ub9Q7iR56HwHIpA6dmjN+tgkGrFZPaIZ5gZspeLQTCjgHFKEOfwle+nznjK1A1AjKJM9od22XjzPeVawVoJ2+t3CAtjANvlcXn8+lv78fmDaww899BGK/JjGw/1I3N3jMbGyt91NDvl0CzMGHPl/I5dw/My3Eg/UWePt9tsUILRBtwz3pSB8WOuwfCYlfA4ul48C5bXzgAhO4C8Q2oGsp5zNsYYcBtYvofZg4EEXBu4A55pL+DJY7q8daE/ccPOoc6MFfUz4DELb+aGe3BivCb9HMbOwIP77GCx1pizOJ1m0JPZ5347RLBMZrQ8fymL79NRSh3CM60bYeeccmEwyPymTOYV+sBRCtqAw80zHpy7fcTGeT0wT5i7diQSLLtdgG3rB9fV88xzz86dx4+57/G4GoNoRjgdLdp8ZOPuAoAlJeso17TW+n1za5kiGC97bmY/MsSa4a9zO3YPxh/mxYbACsuKBqBAPZY27x+FKM2SmCmw8l7eujCEygAkaXwBPDbmgB0rKOfGGVDaeJstNIhLwGAjbcbL4MsKOpU7dQKswBgYtLg8sxMOjRksWflj2G3YMreS+wG81AtW1IacfoY1gSn2mGHskz0gVJghdMqiXmZpaDvfGwDY6DO/aS9Gk9C/AZNDyQaYGVb1tWakruaUMNfOXrdnYJ08n7xODESd52eDa2BrQJZz1fV1PcnbMqvtecFYMI8MSgzcvKbJifTccegaJo2+Q0d4zGlzrneHap07Z+cKgOT5Rhl2LphvHl+3HZaKeUO5tIN1QN95LAd2betiP/XuP93PLh7uj+z6c/38we/upxfu6mf3v3f4e3b/e/u5g4f7Y4t39rP739uXF+4e/p47eHh0/Ym97+unF+7qnzhwuJ/ad08/te+e4dqTe+8ZPnts8c7+2OKd/fTCXf30wl39scU7+/LC3cO9fHdq3z392K3f2x/d8z3D++WFu/vywt39scU7+ycOHB7+f2zxzn5y7z1D/SiH63jGib3v66f23TMrb+/d/YndB/vytlXGmb5kblcIuKRkfWXIAUy2IRkzDK+9x8zLsbe3vHVhFDJwbhlesIFOeugYRStxjJxDtNQB4EJZbouBBEaA9mBMnrhh56gNGF4bAoyAmSizIlxrAJZ9Q1+aUct6cc/nv++b+i9997eNAHnmWtlQY9Rg9KhXsn5mDjxmgHYbSM+BZIzMRhzbeGi410yJn2PACBCiTAMmg5k03gZiridjzzyg/b7Hht5sG9fTL8mqGVhlP9s5AtAZ+BqUMC9gt/jrsJ/D5ga2BruMh1kZMz+AYDsArr/voz6PX3/rCDSZyUnnIXPa3AdToM1Oi9tBXSkDp8jPdzTBzKYdLLPmuZY838xcei16fP38rAt6xc4k7xlD5rzn3tnd39kf/wf/tF84fqI/vXSqP7V0qj91Ynn0d/b58srr1JrX6PsTy7P3J/L65VH5F07MruUZF/T/8HfNa3lNWU+Prl8e/z/6eyrqFu07fqKf+5EP9rO7v3PQe2YXCwCWlKyvjHIAk71BsTkh2UDQAMY5Mg7dopzJiUsFSzmAsKkNAQ4pGlQZ7Jn9s/H2Z+TZ8ByMvUO7ZoAI8VFvh8NgjrzjDYMEgOAa2AIDpmRw6FtYPQNYnkn4lb6jXg630u/8D8uSLJqBTQIlg8U0vpnjBNA3MAL4eyw8HswtjLiNqYEKzzIL6znDX8DPEzfsHIy9AZg3YRjIHtt4qN9/7XeMgAr1Nptr4OM6GUwyxxl3+t9A2jmHnnMGFO4Tt5O2MU/MdrrvaJ/ntsfX4X6ne3he8zn3siPfaQ20j3sB/15vdtIcpjWwBESaUWV9ZD4cbBxjkCFl73JlI0WG3K1bXIY3eZjJ5Tv+N6g0q+n/mTdnr9vTl6/b35+474F++fFP9l/89JX+2YvP9s9deqa/cPHZ/rmLK38vPTN6vXBx9vezn9Z3F59ZvS+uX/P5xWf65y5ducrn/mz1mhdUrxcurtZhtY5Xhtfw/uLaeqyWPyv7s3rWL336cr/8+Cf7Jz/6QD+5fRWwE+GpHMCSkvWVgQG0h4xixDCZ3SKfysnXGJtkHRzyI/zmnD28dYe3ks0ChMIiJoNAGTYWfs8zzcBYuQNOUPQJRpJNMFuAkoc9ol94D+ikHAwYgAFQZW+Ye9M4YTRhjRgXQIA3nzh/0882COUaA0SeRd0dhjPYoI8YX+dJGWAayDivzMCN9gKIPd8MIGxkDRIZP88H95mvN4ME2HE4MwEw/eUcMsrDKTGwoL04OzmPfU3mjDnU7pxJg2aAy9nr9vQnbtg5YjJz3bntdsoYc+ZAsptX2/jC3Ia9Zzez55OBPS87jX628xj9bINV6uy+tGOSjNxUvwFMaQNj7T4ws57Orcc3dYKPeaIMO0XH5w/2E7vv6U+dONVfuPhMf/nK8/3ly8/3l68837/wzHP9lZX3r1x5bvjuxUuf6S9feb6/cmXl85XrX77yfH/p8meG9y9d5rrnVq9duY77Xll5zouXP9NfufLccA/XvKSyh2ddpszV8njmK/Fc18X3vKK6rn42q+dnLz7Tnzpxqj+27/AwV5hrBQBLStZXRjmAKDsbNodyULQo9kxudjjEitghWb93iNVgCCNnw+swjuvAZ49ff+sobGgm0YaKcniW64DiRpmbLbGi8l8bWcrPsGYaV4B2giTqSr9iOA1mzJjxHffTd+4jM2cOH9poOXnffWOWyhs4kq0zO+Q55DIfv/7WITzmtAEbXPrc42o2zexbgkUDOOoBaCUFwCAVtseJ7NyX893HlPhzQFsyTLC0U7vAczen+8ibXTLMbiCZfU37za5O5fIZYDH29C3rx/mV7svT2/aNdhtTJwNZ5qGZOdfJzlWmZLht6aykQ+Qd+x4XA00D/sx15Xsci3Q6uYZn+dm5Bq1zDCIH/bZwd39qabl/7tIz/aXLzw9ALAHTiwZWBoBXZqAwAd8qKARwJdhafQ6A09+9fHkG0l66bEA4rpfLdN0AhQaw1GkGbNc+C1D4uUvP9KeWlvuJve8b9d3y1tlB060AYEnJusk1rbX+8OadgyLFKBhYYBy9oQL2wSAH5oMQlBc4hh3jn0yBDTxGyM+0ATRAAJzYUJmx8JEy9v4Jddn4oOgN1Bymy1Cun4VRcniWskgi9+YQjDh1t1HjOwNfjE4ye960YQbXBhs2wrsAaQvP4JmEtKfYHx/3Q4gtd0J6XJ64YedQZ4+hAZvDdmYO89oEM7A9NvAAZ57JRiCnHLjubr9z9+xA5CYQ5qPZyQRGnjMGJfQx/yfzxXxkHpi1Y3w9J81oeX4b6JidBghnWB6gw3zMMniun8GzDfRh2p0ry3pOZ8l5e3mM1BA+3ToLD5uVRG8YKDu8fHrbLFx+bOOhEWNtXeQ1n+xostbe/OHwsMEyz/Z3zKfHFu/sTy+d6p+79IyYtDGoMpvm714K9g9wZcaQvwC8KQD2Sj4rygb8GTC+svIaPYf/L68ygQOrKPZwtZ5jtvLlK8/PAOCJ5X564a6hD5lLH7l2sQBgSck6yjWttX5k42o41950GmCMLMocpWjljCEDIGLgACCURT4eYMw5W2ZYbFQxHGe27x1CYGYaDJwcvkm2JVkHh5LMtpl19AG+AAH6xJtVKM/G36wLm1tsDA3CzALZSNnAZZvc/wZeUy+XiZHLNicr6r4AmDg8auDpMDqfm5XJZ7iPk1lk7jjUacbOgMBzweyP2S/nZ2G8Pf5myFyOGUADJ+aB6+4QNOPrPFKzrdSDI1k8/wHrtJ1xdd1ynJg/1MdrYIoxdjqHgZvXvfN4/Wz60X3t3a/uN48nQJPwqTcreX47T9fzlTaztni2N83wP6yzcwGn9ILH7Ox1ewbHwWyxATW6DKfHrKB3B5/fsas/tnjnjAFcCQGvsm9jEOZQqj+bYuDMAL68wh4CsgCCA0N35fkRAJxiCsd1WAV/CR5dxy8881y/+OjJ3lrrZz768Uk20aDylQCAjy3eOXI0z143+xm8VgCwpGTdZNgEkvkuKF2MLgbJHrNz0dJYZ0jEnr7DU5TjnCwUrxkxAKNZMJR6AiYzJX4exiTBjBXRlOHDwJgdsLFKFs3hP4yCgWcCUBtxg4BkvgzAARVmYBgrh2tdDkwVQMDXmZECeBjsw1Iylk/eeMuaJHjG2KAAo/zkjbesMfIGFA63euzNSpn59GYlvk8QyrmStBN20+Posp3SYDaRlwGUGV+zVp7b9D2fUW/GyWNqkGbnwaCMNebQJ2W5/R4vs2Vm46g3c8jrGJaeupqlz3aYFXP9zu/YNfRRAlePM3Vwjinjf+Gmm4c6+cgjb7ry8xlX9A/9kxtrPA89r3xkTQJGr910HMyqUz79MAOAp4YQ8JDrB9i7vBrifUXgaU3uX4DCVZAFmPzMKFdvnAs4Zg3HTN9zo9c4v/D5tcyknjEAwI98fMQqrgkxD//PQsBPL50aGEA7OXUOYEnJ+srAAKL4EhQ4URyDkjlIKGIrfxixKeYB45WMkTegYPyc72Vw6V2IBgYOESbzlyANUJlgLNkjGwyHrwxyXX8bIBsM/1yV64ahtAE0O0he4tUMXgJdgyZCrMlImvUwgDGjxxhgGDF4ZvTMCJnVMytyetu+/uSNt4zA7dnr9ozOhsz8LY8JIHd568KwicbMcDI5NtR5rTdI0BaHV9OZ8HvGi3Fx2NQgzUAAsGjHhTzAZA9ZFwb+HiuAooG51yDrl8PG3efMM9pDXQx6zSTDbnl9JRvs5xrM4TzQdl/HPMkx8vjZsXNaBXWmf2FOYT4pi3mKTqKfaV+OO3UFqOb1dmjRTdTfqS7e+MI4DwzgpStrNlIYZAHgYPBg6l68tArWfuXSc/3RpU/1f/Xgk/3E0s/0z19c3chhADnaPHJ5HCoeP9NgMpjFEQAdbzbhuk8LADq/8eUoh5DwS5c/01+4+Gx/6sRyX164e41j98CGPQUAS0rWUa5prfUHNqwCFkJWMCbJpmUYxTmAZotQylyfTBcK2qAGA8b13s1ndsLntGEwuM8G1IYZgOPdyt6RDFPgNnpnn/MCDUrNRqD0MzSYhhYjkwDahsubapx/x4v+wgiZRUoAlYybgb2BOYYRY+Y0AOpl45ZAj+McMjzKXMhcMAADz/FRIlPMLoCUc+uSTTS48Fyhrud2rB5O7nmWgItxBUAYoCV4WN660H/5z3/zYMx8jE+GF80sUibg0ACUMcwcRzPfZkg9pxzaBzzBxlF/7ud754NmX3jtukyfm2mnySDI50F6PAw2PSc8nvk7uXYOXVcz1znnmXvewZ26jONjzPg5DzidQ+ahgaJZR6/p09v29eWFu1dyAK+sCblmrtxUzhzXf/ToU33TB471P/xXjwyvTR841j967Km14eHLZvGuHlL2ZhNYwb4KskgAACAASURBVARwH/mxD/bN1871r3nLW/rXfs3v6zdff0P/1MOPjgDgP/uhv9c3veOd/ave9Kb+rX/kj/aj//xDawAo7fzcxVUG8Pj8wSHcfnrbvtoFXFKyzjKEgFFkNlqwRxlKdC6VQRyKMvP58ugX57k55ILRsIGDJcKwmNmjDvbWbdgdboLRSNBlow/wwoAYwMCqADzy5XCd62lwS50NDDHizr00U0F9HVJOoGyWiOdh8AESMCEJQM1aGgAYFNKvDjsDZpK1M7iiv2yck0kzEEhj6/Zx/dLm/QP4MFBJsAjwOLbx0JpNPQBSpx1QlsORBgXMe68HzxFClgZ+brvnucGvy51i1NxOH93jNTd16PXS5v2dHDg2Qpm59liTC+jwu+vssKzTALiO+UV77EhkO9M5Yk5ztmD2scE0zpbBmfsuGeDzO3YNc8Vj7/fLW1c3muBosWZYn54PTncwyEwHblhfBw/3p5dO9V++fEVs3TiU61CrwRufffToU/0bBfx4fePKaxUEZrmxGzjCyuOdyM7xW332h374R/qHfvhH+tPHHu1nPvrxvvPGm/qf/GPf0l+89Gy/+OhSb631t731rf1f/PCP9CeOPNS/6+Ch/pav/ur+r8+dHzGLo13AKwyg5/wjm26rEHBJyTrL6CBo/5IDihXgY4WJkjRwQPmRGwYgwhABeKywHWo0w2RlbuCYXrZ3HCd4sAFLZtMK3sbcRtdhJ++MNBMJKMNwUT//UgJtdN0xaNzPa4olpV0cBEzZ2ZdmuXifOWRmczN8ZaBC3xuUcl1u5jGgpY2eI9Snta8cAXKDR7MzBgHJZJl5M9Azi8V9PmbGYCdz+7jWnznkx25uf+9+TYDk8L7BmFk9xsBsXc51A7GTWxZHTIkNZ4ZavaPYn2fqAuWbMTU4MsDkWoMis8cGfZ6/yfh5PAF37mvWstedwapBt8O36Bk+s4PqDTieG+gFj6HBo+eSQ8xP3LBzlOLisfD6GspfuGvIAUxA9sqV6Xy81f+f7y9eenYN85cgcP4Dx1bCwZ9ZAzC9sWO8McTHs6xlBKdyDl++8nz/uU883ltr/fzHHxwYwA/8j395uO5XPn2lv+2tb+3f/5f+yugcQOoGADy7/71r5kFtAikpWV+5prXWH9q0emQJyhGF6NBpAgQzK84Pw7D4J9usJM1oYKwyB8gevg0zxtLsGcbUdQC8poLHo+f5GbJNltBtMNjwTlIbWBtyjJAPb6YONsB59AjAxkDw5JbVE/MZJ7OVtOX8jl39yRtvGQEFhw9PbxvnciZz5LKObhjnHprNTJDAzmPX2+8zTYC6mqk0IPM8S+bGoVmDO4Oy3KDEXEmWKYG/xxDAyPxwvmiyeQYmPCOZUV650cnOioG8mVEDS88d3qdT5jab3Wc90T9m6hMM+71ZRvoigZnvY4ySDaQtrCEz4LkRzevL7XLYPOvutrt/DSpzXVGm55Ln8NQasaM15biif7wJZGonrvPy8rOXLn+mL538mauCP79OLH1qIrSbx8qsAs81R8PkUS8rf58+erwfuHV3/8Zv+Ib+lq/+6v7Vv+f39tZa/+l/9E8GAHj0x39i9Ozd3/7u/qcX969t0+Xnh3MAP3Hg8MgBPrllsX4KrqRknWU4B9B5Og6HWllimG1YnJtj0AigcTiYsjCQGFTAkxkEnn3hppvXhJMAKAZnBokofyfLZ84QSseG14CKtjlkSF0NNpJ98W/pmgU08HV9zUjZ0KdBBWQ73JY7OA0EvPHlyRtvGXbE0v+uD/cZRBhc2ZCa/XOo2blyDn3Sb4BWzwPYGfqKXCz6NMN3Tg8w62Tmh3mVYTobZtqcoUjnXeZYUUeuZ504D9Phvzy8OoEj68lrhLa4r9zvPu7G7Kt32Rr4+X6PWYJz96/b7z5jDD033bfMTeZnzgE7Dp5nnh9e/wncvW6TNXaYnvLoEzamuU1es4wZ5TqsTZ3tNC1vXRhyox3mZ/wShA4M4MVngv17bg04W3PEy+Xn+7968MJrAoD/6sELI8aOXbcuy5s+pg57Hu0+Xvn7R/+7b+rfvm17f+Cf3ds/+cCx/vjHH+qttf6TP/Kj/dPHZwDwoR//ydV6XzYAjBDzCgB8eulUP7v/vcN44gg8vHlnAcCSknWUUQgYI2fGxhsrbAwMFPw7nihDsxdmkQAfZkQweBhFszcOj5ppom5HNxwaGXSHWskrSlYKIGlWKQ2VjanDUgYEKPzcWWrj6E0n53bsHgEx95GNj/OpEkg5FGlWjj5yuNo5WZRr0O7wGmOZuYZTIWHGIYEY43dyy+IoDG7WySzL0Q2H1uTi+RgZ93nmGxrQ8B3GJNMFpsBiMsmwpswLQIXBHGVwFiGAyA6O5wD1YOeyc/cAQllXzwnK5/iefJbH2cyW2Wmzy+m4eX5keNXjzXyjXgZfnpv0D+kKtJl73ee0zzuNzdC5T8xKopfcl3nwtFm/ZCet47y+ckeqWX+u8W9BMycYg9Q/g45YyQFkE4g3gPjMvqmNGq9cea6fWPrUa2QAf2ZNjmG+1mzymPgVEXIAX7r8mf5zn/jkCsP3k8P9D3/op1YA4D8YACDh3i8881z/lU9f7t/w1j/Yv/8v/ZVRmBk2EAbw5N57RpvGTswf6I9uvbkAYEnJOsrwW8DezWtP27/UYGNlYAQgwKhgiAFHPmk/Q0IGUhgT8mwcenIuVYaLOR/QQCONsdkL7wylTbTdxtBMhdkr5xUasGCMYR9cXwAuRs5MwVSoy3mYBmtmOQF8lGEGBxDJBhz3H38N0CljimFKNoz72I1rhoh+dVtpE/emUc6xdh8bxLMBwbtj7aiYNeLgboMQb4ahX2iXN3owjgZ1/ok9g+Rk2KiDQUiyV14DBkbeGOP2mJ20k+K+p16kG9gByFzZZHUNNnP8GAPPvwStBoGeT5mX57Av96MzqL9BO06G2XwDQadDGKx5oxYg3g4rOmNq05bHxk6RQayZfutL5wbyXHYB//LlK2sAGWfkrc39WwWKn7/4fN/0gWOTm0CcA/jipWdHO4rH5/FNhZydj/j8mo0i5B9+3e/72n7Hnn396WOP9gf+zx/v1/6ptw8MIOcA/qE/+PX9Q3//R/uTDx7th2+7vb/59351/7mzj88A7uXnBQSfGxjAE3vfN+rzpc37KwewpGSdZfRTcDYeyVDZc0+v3+Gu9MZtJDFCKFMAC7vwbDAMQnhGGh+zTMlkGcxkaNMg0YZ7afP+0dl0ZqAwaJk3Z9bSRo1yj8zdsYaBSoNlAIDRchiPuhmw8twEiQZoZlJ4tsOogFXK91+u8cHSBg9+lkGWNwjYoHLmokGXDbNDcJRt5o0+cd6p51nOLYNqdsMmI+S6YtgNgGHSPIcZP9/nvnB42GfomcmiLQZ5Bsy0xekNrgfz2yDSTovZ9ZwPPBeAnfU0u+rxzlw/g/qz1+0ZnaHnDVIOtZs5oz+8ScNtMot6csvi4GAaAOIAMAaOMHj+u678z8vjTVk+Hig3onj+OjJgtpTrnrhhZz938PBKDuCVNcBrBP4ElMaM3fP9o8eeGnb8XnUXsH+T15s74nDmVeZPu49XPp+dOfj8KHz88Q/e27/lm7+5f9Wb3tS/7Vv+eD/6zz80A4B//0eHXcAf/KG/2ze8/e39Tb/rd/U//s1/pB+591+MnmPA+7lLV/pTS6f6Y4t3jnTlme1767eAS0rWWYYQ8NLm/f3JG29Z49WbgTHDh9G3QuR+h00wvijvDL+YtbGhcTgU5T0VLjOAMivoXLoEUzYwGF0DRLMYBiZ5b7I8NigOS5Lf5nZfrS5cbwYuw2EGiLkD2UzP8fmD/fHrbx3ec5yNGS4zpzgAHjv3NWO7vHVhCN+YOXN/eH4YKBnQeK5wva+z4c78P4x9ziHqwOHZPN9s5NQzDGaonwG/gZTHiGcCTMxQ0ofeRQpb7c8M4pzLxtgZlDBujCEgyvOL9jCvvS7cTgMqv/fcNZtmxsZOBYyYnSY7bZnSwVrHgbnaGiRykHrBbTJTTBvt8DnM7XqhVxK8wTJ7Hbj/Eii6PF8z3Lv3nv7UieUhBOxdvy+JbYOpMyj02X4fPbb2HMD5lXMADe6mzhC8al7giI38zOgwaOckTv1cXJ4zOPoVkyjDbYIBPLXvnpGjdfa6PXUOYEnJOss1rbV+/9zeEYjA4KKsbRgcCiIMnPl/zvtxmYBEM2wYENjAVLrLWxdGrCLlmGVwzpJzhKhzGtFkjgAyBgwYGc5QM5jkOwMZgwTqRBg2dytb8WGA6NsH524fdvIaXBuMXm1nNZ/590npK+csndm+d9jhS7+7HDNlNpwAA4fN/fuv3vBD2+kHG/hkl51j6vC2HQye6baakTLocl+4zX45lAobzTykD/NZrAUcIW8OYi7RL/5d7WMbD60JrZqlMnM45fRQfwNyg1aDLtpCHT2eBnWENqf60uOf65f2w74bkHu9pwPgdWpG0GvdrJodu2RS7aCk3srd+b7PustAGMDo8fG4uA/NuKNfAKr0uXN4fRC02bjxb/auBU6vTHz34qVn+6NLn+r/8siF/ujSp/rnL47P85veXCJwqbLz/L+8b00ZCeriu/G9498hdr0+d+nKcBA0fcR6LwBYUrK+MjCABmAGGg7VWvlhuK1kbfRQmg69ZbgFYET+oQ999RlhZsQAC/nLBjZkNmwOu+a11DfZKwMEgxHqBYuWIMV5fgaJBjV+lpk1DCYAwMYG8GVjigFPA0aZaQAd7jPDBMCA+UjGw4bRLGca9ilW0d8bKBmo2kCncbVBZl75V2CYC+7zYxsP9aMbVs+u9O7mKbaR97SfRH/em3llDpj982fMaa438DCggzHLsbfjBfPOHEx21Eyl807df+7D/MysNd/hFPAsQCdlwjKms2CGOuc1nxt8Ad4S8OOQUIbzML3pyGsfB83MJWsx83O9/mjD0Q2Huo9FMnhEP9GWzP20rnHaAfcfnz/YT+27ZxQCHsCdN38kexebOF689BmFdVePclll7saHOo/Zu+eH3x42A7j6KySrGzWmAJtzB6c+eynqlUfLvHT5M8PvHr9y5bn+wsXZJpCz+987cgROzB/oj2y5pQBgSck6ysAAomwxYFOeLgDHij5ZKiteFji7AlHcUP42nqn0k90wG+IQl43457/vm/ovffe3rTFAZkfMUjkPy+whBspsiEPAZtnoA5+XBjNxcsviwOQBKiiPfnYuovvBDKtz/RzqBbBg/DP/kr42I2Ug4X4128Ghw9nmdBAMPgFaNu5mhh12S1Do9nne+Hn+6TqDTf9vQ81cMmBk7gAUHIo005OMmMEHY+RzD3NNUHfv8rUT4Xw+ynS+GRtY3Oc8F6aSuWuHwX1PvwFwvAFmafP+0RE7CUo9RgneGHfWH3rhxPzqzwt6LthZNAuZ/3t+GLgZqPM9QNXXGOSaDaTfkmV2eNps9Nnr9ow2oZkNtXPI/Y9ff+uwk9mh48FB2v/e/tTScn/h4rNrANL4XL61AM7M2ihcPBm+5afcxt+x29hHvCTTl3XIswFf9PEwAq+reYzKMcxfNNFnX3jm2WEX8PLC3cPYM+/vm1soAFhSso4yHATtcI5BHMpvivlgAds4O/SUv1rh3YEYK7MnZusctkuWx568wZk9cB/y/GohJcAR32O48ngX/0qKN0b4LDvaDzhwONCsJs+1QTWI4Dw8Ps/f7XWb3SfcSx8mW0e9ks0F4CRDh3LODS4YOPdhMqfOGXS9bbSdRO9QkIF+huQw2jzL4JTxM7vp+k1db7DJ/958YZCWKQeuH2yS14pZXM9lAzWDcMYnwZLDmgZe1Mm/hGHw57rT5/nzdAaXdroSCFOOmc0p9i/nI8DOoM5rkpfHyIyd0zYMVs3Ap15KQO5xpyyz5oRw3TbqlH1KG3FqDb55rndUzwDg6i+BAOa+8Myzk6HYly+vgicDRP9ucL6cj5eh3CHULGbRgO9qgPBqv1AyKm8NY6jNJRMg9ZUrz49yAO2UnNm+t3YBl5SsswwhYJQcytAG00rQLCDGiNANHrEZJkBJGncbRYwZStXs2JSRcX4iwOrcjt39hXu+pf/Cd75zEshYQaNwHO4xWEUxYVgNFGiDQZGNnOvtEJ9ZL7NCrmf2ndlKgz2uM/vB8wgd0qf+LncqJstrg+lxMXA+uWVxOHuRsWGzSYba3N9TIWCzcdRv6veaqS/9n8efTAEUGxazf2aa6FOe7XzXZOVcJ1hBxizZSsbkiRt29qXNs1+CoT/I96S8BBDOgUtQ5vGhP5+4YecAipxz580kCYDoj1zDzDs7ZVxrQJ4ga6q+PiYFMOVQOGPhtQjgM0CeWssAWa8Pz5sE+e4/5gfrNsG/6+y+M5jH0fDP3J3cstj/03/50GjOnd62+lvAMIAOARuwJes3PkPvuTXAik0bycjlpo3MzRuxiHFEy0ujMqbPJQSIJqAcfR5Mod+/cHEGAM8dPLxGr9dvAZeUrK9c01rrH7l2la1BwZmZ8o5Y2DkbhlTOBjfeWPHEDTtHO3INipzj5eNdkqUwG+Bz7fL4kgs33TwyNlb8ecRGhrDMlFhJWdkDkAAxNm6nt+3rRzccGsJvBnewbZRLn2DEHaZ0eNHs6tLm/QPTh8EyE2XW0ve6HWYxPR6+HkDk9plR9PgDbnzwdbIhAysiFjQ3p8Aos3HFOW48w+HnDK8C5ph3DjUD7Cjbhp97DEJcJ9ri55lhNpOcv4JhNvDJG29ZA+gAb66nxyFZM4+xmTOzn3YQHKblGeTzmZU0U2jgliF5v/e6ZA6a+XYZyZAxbxzCN8NsPWSnizaSi2u9xRycGis7YtZrHvsEcJ7b9GXOkQTCgPzHr7+1nz/wXf3ppZP9//n0s6OwajJsa1m659eALd9ztRDuUJ7A40tiFaeYx7XHz6xl+Px+dL7flfFGFBhCv/dns98CPtXPH/iu0TwrBrCkZP1lCAGzCFOxG7D5VzzIQ7IBtFEzWEJZokDZ5Wrmxp67Q6r5O8EYOf/aAM83e2MGK5k7syA8KxmHDCOZaXCo2KGoNNSEcg2qze45FEsiOrl62Z8J4jBk1N8MjYGYw7DU3+W6fs5f8nlqnMFGLpmBrssyU5SGPpkswJ+NPPPN8zAZISfmc032A/0L+HLIEKfBc8p1cN09zn5WghXPX9YF/WQASjnu25wPtJ05RX+YWT173Z7BkTBbaQDsdcqzYWn5zpuw/EzPfZ9ZCSjL7zIX1+NnI2/nMFMOvAGENnk3Lesj5yfjRN/DiHonPGWnLvMGEuaGgSx18RE8zntM/cV99Mfy1oV+7t0H+oWHH+3/9mcvjUDbS5fXhlMT+E3lAuYmjFG+3ei6tcByakPHaFNKlj/BVA6gdM2vl0zkKEZ+4EuXn++/8LOX+pPHHu2nb1o94of5ULuAS0rWV65prfUjG8cHEZt9QoFaIWIorMDNEPhlFitDgz5Dzd56AtEz2/euCU07Xwtj/B/Oflv/tY/9gUEZJzBy4va5HePz2mz4uSePLjEYc1/4swxVJ9AyqDGANONh4GajnMCKz2mXWQ6f3+a+NMigHzn/L5PwqaN3uyYAzLmCoTTYcRkGTQZYDos71wpQAxhyCJrnmv31MzDSOBueY5RvhhrAwfMdKjXg9/gBpHJHstcEfWWG1esjgZrXSG7wgCHN9TYVrjZLeHz+4MCKe17Rt2z8OTF/YJgPDqnn7zJ7I5dZdrN1brPXLp8bHPJs+sN94tQKxp9+pF7eoU77+OzJG29Z44B4XBKIUrdkZK3LrCPMTKdztbx1oX/i/T/Un14+03/hZy/1z158tn/u0pX+uYvP9M9demb1r/5/4eL4/1++fGX1mkuz9y/4vuF1ZeWeZ/X+ynDP2muvRB3ymllZq+WNy37h4rNRbv6/+owXLj3Tf+FnL/afOf1Yf/z7f2DkmKLHiwEsKVlfGQAgTNsTN+wc/gckGQzZiBLOMmNigJHJ61ybu1oxNGbsMHJm6XK3pr1H6pqgysYpAZyVPMAXwzFK5L5u/NvGDmM6VI6RzrKnWKNkVcxUTRkr35sgwMCRchN4OmRlAJNhsASbafBoq/sEdjANKsrdbXb40AyZ55GBmYED+Y1TDGTeT5/RDjsXtBEmx86FgSjzB+DhvwZmZi0NbhKIeu6Y4TTbnscfwYIbZDgUSyjXId90TLxGzHzTX04lSGZuahypbx5143P5DADp42QQKcMMIuX7JIEM37JeAPfOHbWuMWinXdZjrmeuN/qV9exfOsm5ZUDtdUO7lrbs7594/w/1Cw8/2p86cao/vXSqP3ViuT+1tNyfWpq9f3rpVH9qaXnl76nhL/9fOLH6nf93GcP7le9dVpb39MRzL0zcl/evvZe2jMsffXZiuT914lS/8PCj/dwHfrCf3TFOccFBqV8CKXkjyY7W2gOttV9ss0m/EN/fu/K5X8fimq9rrf1Ea+3l1tqLrbUPttbe/DrqMGwCWd66MPrNXgySDQ4K1OE3mJMEZfaGybkym0OCfIbjbERsdBzm8Q5PGx4bABt9l8/nHLhsdiyvtUE8MX9gzYG+CYgd7rPRpV8SmLqfacuTN96yZgd2gk4MJGXbWHpzCv2R4eYMXznsBTinjg6RY4zNkiU49XuHXQ2UuC6BZrIn3jmaLJL7wwbXoNHPSXbMAMxz2mFsQKLBCfd43D1+yVyn08B4OPzsMGSCr3RaWCOulxlxzzuDbDs5HN5tB422J0BjjXMNDKH1hec/c9iOwignLnJb7Rj5Gae3rW46YoxIqSDU6007Zv+Y9049SRBMGbzHmfWmHfe1c1LtpNGXDidntACG+Oy7DvRTe+/q5w4e7p84cLif3f/efnb/e/vphbv6Y4t39sdv+67+2OKdo9e5g4f7qX33zH45Y+Guvrxwdz+9cFd/4rY/O9z/2OKdwzXLC3cPZZ5euKuf3f/e/okDs+dx7/mD3z3c+4kDh/tji3f2Jw/9mX7u4OF+Yu/7+umFu/rjt31XP3/wu/vJvff0cwcP92O3fm8/te+efnLv7HV2/3v7uYOH++O3fVdfXri7P7Z4Zz+5955RvXl/euGufnbxcD/z7avpM4yVHeBiAEveSLKztfa3W2uL7eoA8Ghr7a16fW1cc7S19jOttfnW2vbW2vOttZ98HXUYfgvYbMbJLas/XWbDbUWKwkOxWykub53lFd1/7XeMwJjPGXNYy+DM53IZPBn4YNApK3fPmpVLdsGMAEya8/8wkDa6Gd4y2JlKuLcxx4gZLKPwOG/M4JnnGVBwPQb8/I5dw0+x2dgYgHkXKO8N7JxDST/6+d7l6PIN4mFd6Qe+8wYbszUGX8k6MY48nz400wJ4NQAnn9ThTOrlz+gX5pjBNHU2o8zzE5QCBAxwpvrfAMBleY4CQJgTU2PBtc6/9fxzv8FU+RdDvJObuePNFAlu6dMp4Ovx8Jz22uG56SRlm8ymuc+SNU9Hw1ECnu8zEc0UJiDmM7PV1id5/JWBLRtO7BR753jqHfefwTXg2HOTa3gBsu3sJGBOp8ZHPLnfPE88v8yUn9uxewR6mVOer07roEw26zky4/r6NATXx3mtrOnj8wf7o1tvLgBY8oaUqwHAj73KPd+6ct8GfXZLa+2/tNa+/jU+dwgBp0FEORrImNEye4bi9gHI3mU6ZWhQ4hgkQCMK2zvznABuw5F1tpGyMqZuDmE58d3GxSDOSs2hOvrGuWdmLgzq/OsmNn5+7tnr9gyG2yFSA7LsPyfn+xzDDIXZWLnPzBLyOnvdnhGr44OlbaxyAwxl2kEwaKIO5OKh8HMuOfSX5SdL5d3TBmn0FXPRwD3BhwGeD9MGPNp4GXiYGctfrrhaCJayzFad3rZvYNMMLg2cKWcqtMo8MNNlJi7P7DPw9osxct8zr7why4bbbDB1ANByv0Ey11NO7sS2o5gAJqMABsBewwZ9bAbJ+ZHjb0bQ69u5ofS7HScD9mRR+czOrHdgA7B8/qbXUDpH7gfnQ3qsWKMGsdYlS5tXD/9mzHJ92cE0cDVgZY16LnrzDG2Z0slfjOV+YMOeAoAlb0i5GgB8sbX22dbas621f9ha+/36/s7W2q/EPb+ztfaf2oxVfC0yOgeQRW5lZJbHRs7sgxXgg3O3jxgWDLHDefz1Z5Tn3Y3cn8eVWJnbe7eHbJBi5YmiMouD8swQUjJnyU7idXtHog0O15vBTNZoykNOb9sv+p5xoVwAqH/qjfpjyE9uWRwMjzdfOD8QIG6jzOfuJ4y+60Af+1qzQmYHqV8yLlPMoI2P2TADTMbMbLXnBG0xc2yjn2NvA87n9DGGPA8QNtAxy/bIptvWAFsDasbP7KYBGc81y5wbJCiXkCXlGSx6owKMbYLtbIsdsWQ7Ac70kVlKg2jmbII7rqMcdAvgnj43CEUnmNkzqDaDyTPNoOHY5HwjTM3YTG3g8r2OZOQ6dV2sQ+kjh5npW4ejDbrsFDNn7Gyy1pkzlDvVV9Y/MPze4fzIpttGa8b6nr5hTvA+f3fcujydRjYXLW9dGCIY1hd1DmDJG1WmAOAdrbW9rbU/tfLd5dbaJ1trX7ny/V9vM2CY8tnW2vde5Tlf1WaLi9fbWmv9gQ2rjIQZBRZynhlntoQQcCo+MxUGDAZWDqNQlpVughCUm69FQfnIldzEMRWaoE5WlAZQBiVmqPJYDoMb2pIAhbY6v84MD23E0PFMA2+HUqkLRoNnYrxcp0yEp+wEBrx3KMjsiBlRxog+M3NCO81KGOC4DAzLFNuT7JWNbebQAVIMPLM89xXtZzepx9JzwsbV7BqfZbs9hmZFzmzf25+88ZZhPACOAFzn4rl/YZsMVLwRhv6jPAyunSm3gzlpcIQDl3m1XrvJrhkwJTvtueQ157lIuR57AwnamfOEuuch3DyLvjT7OQWseZ4jE/6ZxlzbnmPMd/SOHQ2zcgkMGWuPMf3uXfZmSl1msqguG9aP612e8y49nnZEPQ7uQz8DLSUOTQAAIABJREFUwGh9lU5rsrF2cJhXU8w5998/t7cAYMkbUqYAYMo3rVz37SvvvxQA+P62dmNJf3jzzjVGyOALZYUizF/iAPzYWNgDnmIODPIMIvEqUYYYJh8/YiBkEMH3qSDNJj1+/a39kU23jcIx1JUNGAZMKGsAxFS51MkgARbBbIKZHeqMonUo3EYDpeoy6Jc06t6BbHBipsSh9AQDrh/Gw8afMUgjASBxXqL7hTLNplC//Ek0+tQg3+Ejnm+wk4ynrzM4sHHP/sm5nmDXht3l+W8aRc8fM5B8z9phXtrQT4EGyljeutAv3HTzyLADmgx4GZfMQ+V5PMMbM+z4nNm+d8gFZj543Sd4N+A0ADLTCHACENuZOLllcZQjNzVmHvupPmf8kmmmj7yj2iyvcyXpJ9apHR2AjhkxgzXqALtmZ5r1413jtNtz2f0ypTPNmnmtWZ9RJzOgydLZ0cmyuSadTp7j1Ao7eAbTmWfoY7fsEFBGhYBL3qjyWgBga6290Fr7npX/v5QQ8CQDyG8Boyy9O5dF+vj1tw5GGSUAqDDLBeBJo2Qj6V2IBgdWojac9o55rq8x42UP1wbB4Cl3B2IgeJZDm97cYOVpEOFQV4ZcCBPbsFjBwxRRjpWxGUD61megGbA7dOQ2wRAlcLWRznwiyiBkwz1maWijw4o5HgZ4Nk4GnjZ6gAzGgDo5rO05k05IzjPXEQNPyNJzy8aR9icjZeBnFtFj7X41CDH4M3jhuX4GhtM5jJ4vPMPMWrJ5nr8wN1OMnJ0L+sXz02DiaqFB1nOyxOmoJVvktUzZPnKKcc+6AKSSfTQIMlBhLA1I7TBynwFxgkCDdNrDPZ7rHnuu86YRr0vPBQNIdAg5knwOGGV8/Csr1JFrMhcVh9fsdoI2Ig7pFLnuPBsbwf3p1FmvWHfSR6Sh8BwY7DoIuuSNKq8FAH5Dm23w2Lvynk0gc7rmPe1L2ARydP7WQamaiUp2C+XFQjZ7ZACVCsaAjM8NSlwuz/SGCoyUgYFDsfa8DQ6SGTBAsUHx91ZorpOZzvTKHc5FET9xw85h04O9YrMQy1sXBoBIP0wxVFbIhLqdt8ezkwlA6ZsB8vgZwPp5jKFBVhpwP8uGwawlzwCIJgjlDDcbk6vlbmLQzHKZVckQnw1hMoHua+Zngh2YqGRnPBcM1GmXw7sGCHYCnCJggJPsFmAw5y994Tws+tjP8/h6/bFm6G8DSMCEAbnbw7y2Tkjn0aDMjpxZJbNygL1MATFQxBHzGuU7O1MG4wliDfg8z12W9ZoZU4+H65Lz02Ub6HvcAD+UgWNicO51nywydaYMduPmjuQsK/Uic4B6WTfxfTp61tes6XSerLetQz02djCpZ4WAS95I8ubW2jtWXr219hdX/v9vV777wdba5tbaN7ZZ2PdCa+25NmPxkKOttadaa5taa9tWvn/dx8DwU3BWGM7Xs2dupsm7OZONMDBIsOK8F7MdKEYzFw45oJzNxqDonBg/5dVaSVnxX7jp5pHCxDPHazZooW14tlbOrlcaF3vQ7p+8F0NI237tx97U/+MPf9UaAEDCfLJuBt98DthIkJzgGMXvg5bzGdzLjk9AhkGMDwc3G+BymBMGiQZtgA33qY19Ml2UR1lmTm0szViYtTRocjthvW0Qp1IH0sBmfbPfnZ/q8KuNI33hZ1CumSyHNAEuzHsDdww9c4vdx2bMzWLyvCNzd4zawHhg3Hk2ZWRqAoCaejiVgvHwumAO0Ve+NhlGs6aeGzyH+plFNWg1+KKcKSY0+557zXqaGca5TTYQ4Jg7uRPo2/FO55h5yLE07guPNY6iHVraYfYznRbrDzvYTllJvea1k+vRDjvfO9zu/igGsOSNJDe0iXy8Ntv9+3taaw+3WT7ff2yt/Xxr7R+31v6bKOPr2gzwvdJae6m19s/al3AQtH8KLg1hetpWygY6KN9UbjYA3khir5breJZDtCe3LPYjc3eMwjLeeWzj5ETkJ27YOShzwinesIAxxwijQB1WdHgTxYhiTuWewNntscFJsAzYmQItNs5mJQyezSykYTRoZWelFbb70QAKA7S8dXZ0C7mRtNe5gH5RFn0HiEsGwG3i2Rg0X5/h8XQsnOhv5sOshecoz8P4mMl0nWyEYdfMKAFiXCfvPmYMHRqlf5zzaOCbwNBzgL8uy+DBICiZVtbIuR3jn/wzAHKdPZcAEhnGNNigPwxgcgNP1pM5dm7H7tFxQAYosLB2fMz2eoy4ziFHg1hfT1ufvPGWYX4ZzBoAJ7PnMnNOZb4qnzlUa+fHYNn97vWY7Jmvta7z+JslNYD1HHQUwPW2k+KxM8i3rvczaSefkzuarLT1klnX5a0LxQCWlKyzDAAQQ+BFau8NEOVrzMI5bIXnaYbACtAAMA2er0GpmImyoUPR8dwMUxLO9vV42xieBHYAVj/PytnAzOd4OQxsLxgQwTUAANgAh34ScKchs7HKfva1AES+80HZgDLuMbAzYDB4T+PAc80++rge6mCgYcBH22zYkr1lB6zblaDJY3162/i3l80g5U7lBME2jBh32g5DnQbf4JRjPZhb9IeflQwYfe+5Rj8cmbtjNK94nufF1KYRxoS6s+GJemDEs+94htMtvCOe/rDDYlBhUGTw6bVLGoLz2Nw+AwHmRbLRXgdm/M0ss8YSeCbLyzX+CczsR9IAKNtzj+8cYfD8Z84YZDI/HXq3E2NWMUGfwWwCKV/v/MnUt8wBrwXrYue20i+uP7o8mUuz4f7e688AkjqiA6hP/RJIScn6yhACPnvdnoHtwFCxwG3YHGLKEAsGOo81cNjYCtLGw+AgQ1coNx9RgiExK+jy8PJhCBy28n02Nv4sFaaNPoqROpO/dG7H6o/Tc3TOlEGE+XBOjncGYhB4jo+Xseed/QAIs5GmfB/lY9bg6IbVUJLZRfoUFjXzi8yOmUGg7QZONkbJBBkgndyyONTHZU+xBdTLO58NZs9s3zsKbRnoGDTYwObLTG4yRHZ4DBoMMkmRMLtFPb2uqJ/DclzrUBkOhxko122q/mZvzdb6Oofwsz8MvJhXBpDe5GSw4LolC2dgQruYe1yTbLaBoBlEg9NksZ3PaABI+byYn5RP+NQAxvPP88bzGdCDTqQM/6rHVJ8b7Doc7fVqvedQvdtlZ816xfflWk2nlPp7jH00lvt6afP+kRPssc+Xx8xA145thYBLStZXrmmt9fvnxr96kQAPSp+FjkKwF0sIz8eD8L0NLywAiiPzS+wVOxwFQMP4U74VsXP/rOBsEK2wbTys3AF7eUQJ4NTXAdLMaNhQmVnkf+phJsRKnzql8cqf+XIf2MCbqcgcMhtY9xF14wV4dnnO23PfOW8vQYBzsXIXpeuQAIY+8pE9Bos8x3Ng6q/ZITNQzkvj+fS9Q8M2Xu5fjJmPRnH9k8nlcyfdsz48T8ycpGFlXbqvkqHxXHAerwFdttt9lJ9NsdOezwbf3vFtx8T1Ywx8jQGj53GCLsowGwqLa+aMMTH7ZRDjPnc7c+ztwBqse93QRjvBBscJohmjZCSz3wGwzp1LgG5GnL6jT832Lm9dGOlv2kafmbnkHrc19YeZecqhr5z7l2vPY0EExruhH968swBgSck6yrALGEVgAJJKIRWBDZc9bodF7L3aO89QsBUxZVjBoThRLDBjNnapyDM0ggEgZ8nK3M+jbjBveRq/lTQGyIaPuhzdcGgN6DL4oq0GxxhEe8b2vG1QeHaOgetiIMLfqZ3MBuoOozkMZwbP4TcUuYErY2CgCtNjAzdl8PmefrEjYrbMYJDxyx3FHnenMABY3CacGPrObcHxMUudbIeZU7830HCo0exJsjIYShtd51PR7wbF7v9cbwmkDEQNEs3yptH3WDh3DBbPfeW1ZaZ8irWjTgYcPIfyACXJUFqPGJjjLLlfeXkHtOey+9P1cJoAzHeCWdYAusTgNlnddBRg970uDB7tFNhBt6OFLkmH24DP85l5bx3NGDO3s212iLxJjjKos/V0Akav4zx8vABgScn6yppdwBhUlI9ZERa+DSp/rWAcurFBsaH29YQ2XQcMhtkQs2ckfifYs8JC0TkHDyWGsef9FJNm1i8T250TadaS/kt2zF63wQTPo1/Movp5Nqauw+lt+/qFm24egSQzSQY49K/Lt6HlOo9rsqQAJwNNADjl8JNSCT4Yb+YBxtSG3wCBz0got2HzOAE+MJ42gs5jmgIRGESX53CbWTU7C8nmmInx3HHfZ7/D0BkgJghKlpmjcxgDh03NVgEsvJ7cp84TTdBgNslt8OYFs8UJzplLBiQOP3rO2yE0aKFNzF8zislU+qcOmd/UxQ6anSmPS+bFpcPBX69x1gFpKdQPsMhROehLrzGHdpnL7DjH2fRvUruNObe9vtE3ngfWBc5PtaOZa9ROBf3jdbG8dWEU+jd45Hn0g51mxti2wXPoY3P7CgCWlKyjXNNWfgkkmTQfQmqjkp6rk4ANUuw1oojJhclf1XDujpVi7jZ1fovZNLxJlBM5fwZRySihdBzupk1+hkEXzEKyV36On+fveT6sB8o5w8zpuafhBiwbyJnpo/6UZ+aWOmeIJ42fx8bAhvEz02igkAA1GWM+4/5kYV1vzwXaAQByO90fCRDMpJjVcl1tkKlT9pnr4LmUQC/nzeltq4ees7HCLJwNtwGSnY10JOxsMH/MMtJ/Bi8YfuaI81edbwtYyfmH4YZ1xzk7tvHQaGxxtlymwbOZIv533Q1A/d5zMvWGnTuDbNYVffXg3O2jtBbmS/7MpYG/52LOG89VOzeMl1k1g1GDqWTmuY7+pd/9K0AG0dTHRwCho9xvHgd/5znGmkrG189wmeRKeuxTpzI+9L11DH8BtifmDxQALClZZxkYQLxMMx4YYZRDeoF+751t6eVhkGzkAG0GYzZ4VopToMj1sOfJPd4sYQ8eAIYiM4DybjUbIepuj/X0tn0jjz1DMmY0HJ4xA2Ll6f5mHKaARrIUPCf7yXlRVsxmfdjk4XCgy06wlSxvMgj0u/vUCj/bgLFz+/jfYMN96/bSt7CENrouawpkMr84HsisTDofBhYYPwNfg5mpMJ/raYBh42pGhDnK9w7XOT2CttjYUjcOB3Z9HA43mHQ41CDafZLf8551YtbQbBPryjmX7lM7d7BqlOk8VI9bznUzc8wXn0dpPcaYPXnjLSMdcX7H6rmjGRkwQEy9wBzys+hvs4KeBx5X2p15eC7TjJrBq3WboyDM3ylWk/c+uoc+BdAbQNNnOW+8HlmTTqHIeW+nzmPnHMcCgCUl6ysDA2ilZOWFMXYYwkdZ5IG9Bj9mT/gcJeMNBX6hrKZClwYzhCAMWAFwZtps1G2kAT+uI3VIxsHKzEwkStrKOEGBlbOVsRnBKfCVu30NTKx0HeIxIDOIT0PJ+PIXZtGAwoY5gayBJQYPJsXAxHPDL773zmIDcpgpxgSWy21hDpBX6P7LsTu5Ze0vuDAHDKxyLPjLGYpmbjzmZmOT2XM9eO/E9wRjGEXWW4LDBI12FHAeaLPB2NENh0YMD/f6eBbaxrj5M89Fl+s+zLZ6dy1MrUGymXDK9LE1nvv+ab4EgHZCzGTZqTRjbwfI7TXbbbbOutDpDayZ8ztWj4XxuZF2GqwTPCepJykt6TSZ2Zv6nr6eisA4ZYb7rM/sbHou8r1z9MzIGwymrvXZol5H1lHp+PF97QIuKVlfGXYBp6J0yMmsjoENRsyhPJQ4CpUFbgYAZWNwYGbNOyvt9ZN4DAjFaE6BRCthGBKHdRweSfCAYkfZ01aUtgHT8fmDQ70cXpliMQ0gqC/hD/eN8xOtuG0UHRbyz2jZqJuxsNefnjiG++l3vWcAin4eBhqgZ0PCOBqIe2zTgCWbmWydj01xXzokmCwUz6APfOCxWUmPn8GynQ+Hs103+hwDZ3DEdZ5HmXvFHKQcz00ARJaTZzYaaOXGIwOVZLLNLDIW/AXApeNigE6Z7mMDjSljb3BGX1JWhlDNMvlXNJzrl0dDcU2CCIP9dIx45Zh7fiWgSaBi8GndZODocsya+xqvP+YRoNth9GMbD63JebTOS2fTTjE7fx1pYe54XqAvcBJcdo6p2V3mg1k+z43sY48B7fXu7DoHsKRkfWUNA2gjnkxVKgArh6mE72SOuM4Ky9+jADOsaaWLl80Lb9wMjEGKDV4aKjNZ9uYxjA6hOV/MIWMMgBkZG58pbx0lbsVphsoKnv42qLSx90+VGcTzmRU8bXb/AKZdB4ML5zUZIDuUbdbOY2ewTTvtLDAfnINp1siAHsPuRHKeSZ0NGgzy3M/0G9eY3WaOOneVeWkAZcDkcUuD7jb4WWkQT2/bt+bnz7yRIcHUme2rOy6Zs2ZVzAaZObND4HGhHfRDrrkMAVIvs1i8PO+SmUrHx+vQ/WuQS33SGTSQ5rlnts9+2pFncb/HgPpTb49xOmuMrR07wtmuy9WAj9clc9P6J/9nDTL/PBfTWbNOpp/PbN/bH5y7fegr51qSs8f9XhuMEQw0a8HPszOVc8fr1cdUeS4sbR7/bOjU8UlHNu4uAFhSso4y5ACy+O2hG7jY27eRcijLyshgEmWVTKGT76eM5hQA82HIsGfksWXIxUyJjbeNuMGbDbmBFMo5E+4BLAayVugZlsncL7NDDsNQVx9Xg2G8cNPNw/jASHlzAYYNYwKb4fxMK2kfn+Nwr4EWdU8ngfK86YZxNUChbAMxG7/T2/aNdksScjUY9LEunm9pxGx4HI4ySKCvYeUc8kwmCwNsgEI55JlhfFkPzCfAmH83mX7Jo2I8bgbpyQYmaHDuVzoN7heORUkGJ50KA0j+z/7DaaBPDGCd08V36ZSYwbXj6D5gzbi91Gdp8/5+4aabR/PI68qRBesw3hucTTG46UB4HqNvXK7XrddMOnx2jnBm0gF0H2aKhevo8q2TE4zl7/waQDMHT25Z7A/O3T7SS64bY2e9YYeUuW+wTXpAOt65Rt2PD2zYUwCwpGQdZRQCtsK0ojy64dBoAaO8MjEZJcT3Ni42eDYoTjRPhtBhL4cQ03tPo2bgZ4VmNohnGwxYsdorpl7ecerykim1kk1WzUbFjITZBxsgg9Esx213HpMBrYESOZj5u7tmcHNDgI2MQa5ZBIeYqKN3XKaBcv/xN42/DS/1SccAI2KwSTk+44/vAHNm3jIHkjr7V2fSaPlllixBA895+l3vGcYoQXQaR4MRz+8EJwmmAd4OuTudw85aOi8ep2Qp7bxQB+eFwTCThuB6GujxHbluOGx5IoCdR7fPzFP2H2DUrLRz+hgngy0zW/zP/TkWziVOUOg16TnGnOR5XtfMS+sgXgZ6tDeP7GG8WOvenZ/MuwG4wbnb4rJhQ70Jy/Mv1xN9RhqMHXmzvLyov38Wj78VAi4pWV+5prXWH9iw9ofvDSQyARiWBuYHpePdcmn8vVPPigQFmUbeyiHZnlQqZjqoH56vjdnZ61Z/lsmgBgDzyKbbRj8bZwbw9LZVliOV8PH5g0MSOLk0bj9G3HmO9LXLoy0GtChUynCSvBkts6uMnfs6f0bPbJHDTAkqfBgx/6P0E2Q73Ehb6CMbOhsr9yOGPA0TBiw3g9gYJdjzgcuuE3WZCsdl+MoALR2aBKkGLQmOeKadDzOmzt0DBDilge89/zNMP8VwJ0vFzlfnJ1IPpwX4XDx0gBlsrzszw8xxNljRfuYn7BbPo189n+0YTe2e9brwuNrpzHI8fqxjz1GDVQCQ7zUAMlAi19KfuY70pdMLrAuWNq+eJcpa4N5kv61frefMHno8zOIZTHu9J0jLvuPlZ7LO0bEG2VPX0g9TDg/9R78WA1hSsr4y/BKIlaqBSibFO2fD4M9KyUxJeqQZaiRnx0re3qIZuQxz8TlgClbBis1gx8YLg5bK3obYSt/sQDIFVuDUJUO3ZkfxsBMMw2bkZ36ugTLjZGNIm1yOWTr3Ifc6FJQglHZkP9lYevwBKzaABosGF65fzhsfUcO8M4Po8fR8TaYsAYLBk8GkmdZzO3aPDpeG0Tl73Z7RAeTpeNjI+hrqnk4JzwSUGZC5TNgbs+6e02aw86xBwtS549YGOVMgkoW0A8aacu4p883nC9K+ZC+5Jsef9/lrIZTl334G0LDWzeRfuOnmoQ/MRjG/PPcM6HIu8PJmr6yT/9IGM/52bgwAE1ym3jNDaBbQTrnHnzQGxtnXGPz6aBgzrfSF70NPOScxnVDrds8tOz/U3Q7QhZtu7mbcef59cwsFAEtK1lGuaa31j82tHvjM4rUhS886PT8zSMtbF4YDQq3UrHRRBJkDg8JFGaehdKK786yS7UD5Z84T36WCNSvj5xrsecOHP0vmzqzEyS2Lg7K08aT9DseZDcw6MiY899jGQwN7QBiN+mO0DfgAxgZ2BsfUzd/lTkF78g5Nut0G7WbVcnd0zo1kqhIM2qAylrTHoC4dERs5rqXe3J9Hephlc+iNNjkHzPMaw+u+TaDAM52X6ud4rST7BBj3WCxvHf++crbfaRE29J6vZsCOzx8cgJZ3LdvJ8VzmedTFcyzBpB0Hzz3miDfxGGiZ1aSPkkUyWPOxJpSVOihBIKCGctxe6ylAtvWjnSfrSxwF+sVne5ptZF64z8z0GdAzLt4pjVOC02JATh8zZ85sn0UC0N/WQQbr1gMGr6lDucfMYJ7KkIw6ZVK+dWptAikpWV+5prXWj2wcG3Eb6jRiKAMrpmQ/fK0BRoaqrIy53+DRoAuFNmWU/Ex7+zY4eZ2Vng2BlV9651Z4sBIZRsFTz1weAJsZGxtMsywYRXvxabwdmnU/mrHJg21pm5kps54GUh5fA3AzqMl0Grw5xOo+d8jRfct40FdmiWBMPS60JzeF5HPct+5/+jqZQwMmA1yeZ1Dh8u1AJfihj5gbgEDaSv8wBg61+qfBaJPZvDS07guvswT/9KdBsOe5629mB2Bph82OnB2GzEllnrh9PlbHToXDv7SVcgEw6AXWA3mw9JV3l1v35Dia6c514/GnjnbMpo7jYbzSiWGu8gw7wmbOvekCnWO21v3CGqBN+T3P4nvPfwPABPboiHRufS3zybrq1Rwd53GSh4yOP7llsc4BLClZZxk2gdigYYymwJuNpxe3D6C10mNxEwZAURowcR2KOI/EMCA0A4iSzx11RzccGnnlKGXac2b73gG8GdjZWFJPsw5Oqvd19urpR5R3MgZuj++xwiVvKJlT+hFDmrlBNmg2nNkXHisDYBvmNCQ2uDYA+fNwBrCUbcNpoG3QQZ851DwFjqm3gYbBtRnPBM0YaO71vHjyxltGKQE23oAcgBLtcV7cVNgtQa7ZK/ep5xFtyI0tU86Zz6rzWBsEJkvruepxNLAxoDRwItTIy+Dem1zo5wRBTgOgzn6+nQc7dwlMvZadK2ngiVNjJ9Xtz74382t2Dl1jIGYQ7/fpMFKW2WXmlx0n+sY7gb0Wc0wyZM//BpN2nDJVgx33ZjszdYC2sJYZfx9R4yiBowmeazzb85O2w7ryvPvn9hYALClZR7mmtdbvmxuzBzYGGFQWMuAEr9PhG8KdabysyKw8OcrBwBFFnMbfxhXFb3YCFgCmIJObDTwAOChi2mkm06Gj9IzZ8WbjYSPseqeSNSOCIcaImCEwYDJYzpAKxiKNjvsfwzLFDgCkzWrRHsbY42FAnDtuE1gkY5h1JFTFNd7laKDk3arOgeMvR5zALDqvKw0S83PqSBTql8d8mP2wo0F/mf0wsPHYuI+5xmMPCLAhNeNtx8OAI49icjuoK+FIO18ZSmZsSSegDANyz3HWXDoQOUe8dhOEoTcMoLMc1jVAJJlCg2KvR49N6pIpIGy94rp7bpBykbrDTKvBHaFZ7jPANcNtEGvm0nMOp8b9jfOTjpT1ltNG6Gc7UHZEc11Zn1HPdKo9l2BjKYt5Z1IBp8jPACgWACwpWV8ZzgE0CDOjZGbCANELHUOUzAkG1kDj6IZDA3Ni5YPiTFbNTI7BYYZJKCfDF9T1yRtvGTFoBnhmD5LxdIgHIIJRmvL6M+HZxgywY0ORZdBO5xaZMfG1GESDQjMplGMPHKB04aab17CZU0fMMPZO6E7DwP9mI21ckpXyC8dhCiQmqAS8YTAxOK6H+9EAy0CAeUvf2EB5Hpj9MbhzffwMtxmj5vrAeDhXy4DRYCmdHgP67HPXxWsoga37eCoVgPozhwEeXkceGwA865dfADKAcmjTrBPsmfMfvR6mmEuvc5dvJ46+pX8cYjSIcqoE+os6Htt4aMRoGqB6A4QZMess92emgqBf0xkgfzQdPzOvbpM3pfhayqdNnv+e1waDBo6O4NBP1Mu2wE5zsvfuHxw71gU6CAbQOqJyAEtK1leGHEAUSHrOvHdYx2ADVsq7NK1MMbRLm/cPXiiKDAWAUfIxI+k5JhtIXTJ8ATBg96MNKwrLCec24DbIU+E0h5jMGphN417/D7hKpoD7k0kxA2Uwl8bT7eJet8PshBkAMz4YT4eprcgNJvxsgwsD52TwEmTxnZlR+giDBHhKYON5kQySxywNrBkWj7vrAFvjs/R8jdkryuH5nsNuT7KCLsuOj8Gg2+Z2GPzTZq7hfn42zGyO5xubEewgUW/mp50A6s7GEOYLDhCAn74wcGBu4/QYpHtHL/fCVBuQ2CEyGGJs7OQAevx5zo0sk/fOb/RaszND+ckMm8lj3lIP+pD1RdthdrnGTp0dYOatHSrqYKDoM/isE9DJT954y4hhdToO68VzOK91/2XagfvU91A/15Pr7VS4fZUDWFKyvjIwgDa6Nj5esAY8eeYfSo8yrIQp2zkuVqQGM1amvs5GEFDpfCwzkGa2XM8s5/j8wX7hpptH9U7DacMOCwZwzTAa7Z06ssQHn6KcbXycK2OFibFO1oM62dAZbPOdWQgzdD464uiG1YOhM7fLxon/Pa7+ZQsbVTMtZgvd/wmGfQ1j6t0bzIpQAAAgAElEQVSZBhkAfBt+s1s21slYZA6kmTSDZzs0PDcBjttMHZ3/mOM0NecNTA0unS/mDSwAVP5Px4gQt+dAGmqHllkLzjW0M2IWiT5iPdixskPgz5NBPbbx0HAWnzd6MX52IPIvZXPwNKyedRTzMUFl6hD0EmFdRyb4/Gr9xvphDMyU2ZE2IJ+KVthh8Rzxxgrr5nScMj/UkQv6zHMk2Tg7WYxH3uc0HzsSuW48R+hT2magbCeZOp/cslgHQZeUrLOMfgvYCiFDTE6QnwoH8ZlDHihpKzcrcYARChEj52fac8wctjPb9w4etUMxBgUoH76nTlOAiv99BpyNkoGQjZwNpcuz0fLmDbNs2S6DFofiDAIBOxduunnEkgJKzBS5/09v2zdskLGh9o5E961ZvzQy3A9z5jljUOG+yXAtBsO5hjaa1MGALoE6TJIZFLffxp+y3Xce1+xfGyuPqdmwDHl7DJ1vRdnO2TLgMOviuZsAP8F5jqUBLCASdpV5l2AFpyadPMYo2fDzO2YbtbxODJTcT4x/Om1uo9e7wabfG9A79Mo1ZiHtdFD/ZNtcZxwg+j/P0JwC8h4vOwoGl+7LBPzpUKXO8Fr0vKYuTkGh7nnIt8Eic9R9nbocZjJ/j9v9x1E7yexxrXdlm+VjrcAKo+cdjamDoEtK1leuaa31R7bcMlKAZk1S2VhRo7zx4vmL0jDThTdukGSAZQ/c7McUiHFID2WXAMbGCIDgnbUOSxpUWqFNJWNjyKyknevFr4D42Q4/ch3gwDlbXJ/MggGOyyb0g8GzMUTxmwkwewRAS+bAzKSNypRBNjikDt5U4jFMBoy2ZI7dFDMMc5nh6mTAnH+WIVmDuwQGHsMEX9TLRs8G0ecJXi2FIJmWcztmG4kYa9Za9pPZKLOBdtIMUm20Exwk+LBzxNp1+VOgxeFczyWX577xvHH+nYGFAWHmkLlt/HW4kt3f6Sg+OHf7ANIc2jVT67Yyd732aB9zJXfouv/t+PhXPxx18PinbqBO2T+ew4Btl+GzGs2SmzmkLed27B4O3XfqhO9FX/hvMsxeJ94MSL3tSFF3z0ccdspjPJc27++PbLmlAGBJyTrKkAOIkXXoKxe2wRvK3myCWT6zejbo/g62DWWFEjQo8fX2jgGUMFhWTA7t5PNs7MxSOPRpRQxjY4bF7A0KDAOJMnMYMFkAK3L6iJAYCteK1cY22QeDKTNlGH9AHaFgAwza7773fQZmyZrSXo+JwYedAdfTYAjj5fA9L8bS4IYxcu4n99mYTLF1BkPUywfiOhQIMHFbsx2e024T7TKIoE2Aefexn2NAZqbKbB3zJhkg+sogeorxcvkGKbkuGCuvQa//1BUGg1ln1grPdGjV4+c55TbYWXN9GVuvK+sgO6zpNJoxNpByG6Z0YQI5z6sc02S2k2n2Gqb/DPA9L0h5cGTCINrOKX2f7KxZOwAeR8LkM+0cWvfjqNtptcPl9Zrz0nPPbeG+AoAlJesrwy+BmEmzl+z3CaRsOO0lcp2VrUMOvsdKDMXtsBMslBWH2cg0UA6nONkYhQY48732uDGuVm728DFmNjRW+LTH9TADBeOVB91agRocmoFxPo3BRQIjyjOT5XCjjZ/HDcNgwOvvGAuMjHOaDJptWN2/U0Dp5JbFfmzjoTUsiUGzjbGNO+NHXznUPMWiuS98NAdOiIG4DbgPsGUc3Z9eHzaMBtc+jDeBlecY888OBfPAbI9BuoF5glwDQIeyPd+ZO1NMLICNMQV40e8ef88V94lZLc97OzlTbKbL4XeM/bkZTdfL84R8Xb8MBtkg4fKoq1Mz3O9mImmjwS6fO5TMfKHcZMsYr3TEnR/o944seK2YucxxYJyZ59Zl7hecI0dA6H8c4qkjpVhvUzqM73ykk+fx8taF/vDmnQUAS0rWUYYQMAbSoatkOsyC8Z7r00NnwWcI0x48yeontyz2oxsOjYBWGhj/BmsadYMdKz4UohPOMzxjdsCABoNrVnEqJJJ9YEAIaHOf2avmf4MVA7H0zO3NOxyDx59AnbCkz7xD8ScryfOWNu/vR+buGPVfslkGiAYlNiYGCSh9+oN703jagTBzZjBqhs7A2exYsok2Rmm4zYYaUJnhgWF2/p7vSSBtR8IgnfKZj8yt3HnrV84D+vbBudtHQJpxSaY2ASzzBrDi+Xhs46HR/Pc8BlR4HXvM7JB5PliXZBjb9TRQdHmAJeemmXk34LEOcpjT+Y2uW7LWOAHWXXYYDSjNbnk9+WB0z4sc02xjAjc7u8muZdg328CazzXluXJ+x+qvuRg851y0g2YAz/8+GuvBudsHXcH8sAPH88zcW39++J2LBQBLStZRhhAwRgHQYKPqPDJ73Ml4sMjzTEAbDpQUHmUyJjYUZlCsUM28uQ4JMvCUaU/+MkEyE5R7bsfqZhbKSa/fSp520R7XHWVs4MAzeZYZQoeC3FbybfDU2Xxh1s9jYnCG0naOkwE2+U9+vlmRZIeTrfSzDTQMCjAwHk8bOIfrKdPjDCPnZ5t1db8zRs7RSrCNkWKMnY9Gf9tgwrycmD8wGHkzawlCqSsOiJm/rO/y1oVhIwIsD+yLWUCPazoTZtDsRDDvYTnNerNWDE7zyKVXc1RoP3Pf4+m/BgUJWPw57UjQayfFAMVzwMx15uExbrnBATDlsvibua+5dr3LPR1SNhihe6wH7fwB+FjDjJFTI3LtOIwKOHPd6COPR4L2jIDw10dEoV/QU7nGPd/53+ze8tbxBjGnlyS4p151DmBJyfrKsAvYC9FKzgrfIA+laiVtxW6FZ2VvxWhFnB41jJ+BpI0ORtvKyYrMwMqGyiDQoRSMBvXyMRkGnnxGOQ6j0CfJhtrT5a9ZiGyfwzvJHvB87w42U3lm++qZf/auT2/bNwIiCSrMJHps8ufMUOaug3PezGQYVCSLZSCd720oDTx97t4Uo+VUBM8/z0fam8nrySAbPNLenM+89zjkuPH9FOPmnzz03LJR5TMzqme27x3tYp5ykGx0WcNex8kM8bxkXnm+f7HFgN2bY1JfeBey22bnJplCQIN1guecGUPXH2CX7KXbRzs8B7OP0onwnPa4n9+xa7Tzn/utL8zWWRexeQuQxPNg1DInlrVGfT2WXm+sR+rtFBgDSzv4bu/JLYujX8nxGuT6dO7sLPGyw8t1Oaf53DmLH5vbVwCwpGQdZXQQtL3SDJ/hmaNwUBz29rnPICkNmUMQGE4bcnv3PNcG3IovjXKG+Qxazb7wHcoOJeSEaIDq1QCumQMD2vTSE8g4T8mKOwFOAiaAhMEv9Uo2kWdZwRsseyeejUse22PDTd8ybp4rBkA2mgZLNiAYG4NsG9Az22cMMWAAY+txeeKGnQMo8TO4xn3C597k4DEwGHI4zm2AQTJ4AvQwZmnsDHA8Jm7zFFjPXD/6i/KSQTQTZWadNeh15b6xY8YYGmBzjY396W37Rv3Ofe4H92lGAViDPtDZc5lxoCzmZM57s0isHcaLKATrkmenM5D1S+YbdhmQZrDtcxP5zus2IwrWdwa/3nyWDg/9Q05o9rnBPMDRBzezRh0B4Xl5VBb1sY6kbU79QN8xDgbmzCvrZDskp7etHkPFM82QFgNYUrK+MgBA5zdZKRo4AQDsBdvgmf0ymOJeMx0GmFMsiYES+U4GAQ7NcOhrGjUzVwZmVp7JJDi/Lb+jbkc3HBq85GSObLC5B4Pk5G9YAJSpgYJDclbEAAgzXm4ndSHMg9fv43ey7w3wnP9kMGu2wGDAbCZ1TlBFOcfnD/ZHNt3Wj244NIAFG2j3uYE+z3b43QALA8LuUTNwOC1uA3MsHRP61/OO9pnBdJ5WslSsAcpx2cxpt4/+SoPudebxBXCQkwUT5/rZiaA/AB+eH8ku5w5wmE8DBM8N5rJDoZ4bfhnUECbMHeTc7+v9uVlg6yl0h50Z7mM+J7BNcO31arYs81udX2kHmLlJvxgYOmfOYDl1TLLffk8/ZxoJz3Od3OfuI3+Po2OwZweTPoehNrubTpyBI2OUtsS2wE4FwLYYwJKSL48MABC2zos785ZQ3jbGNoIOzxhcoMBRylZIBiVWzGaSUFZmYKgDv2nrsvxTan6+WUIrKAMev8eYmzGzgbPBSwWcAGtp8/7RLlUMP/lezoEzG2EF7KNVzGYZgLo/DUQcfpwC32wOSZDlg1ptQGiXGY309hnnNOJTLI9/UcTzBQNrZtPsqsPlCSJcp5wjLs/gOsG+AZyBuO9PwGHgZOPIi3ry27nZJwALj6+PFeKvmW5/NwWSuJ46eMe6AZlZ/WRw80xL56zBiBnc2plzPpudDo+d2+ZcVYMkA3H/pU78QoePMUlgxTP5XfIjc3es0Rd2eOwo2HHMCIbzZz3/PE9ybVk/wV6iP3Lu0ue04+SWxVH41TmnrrsdeQMwM8HW+X4mx77w9+iGQyNG8/S2WSpD/kRoAlSz656D1PP4/MF+39xCAcCSknWUNTmANob2uK2MbSDM0GS+i5kUjBXf2RtOIGUQZnCUwID3/JybwRdHFqRx5Dof0WDmJZW6jcgUg8jzbBAMAACvCZgy1wrDhfI2S8P/2a8odhs+2oBhT+DGeOSh2DbyAE762v3KGOeRMwYxTjJP5tf96tAkwMNjlc+nz9z+M9v3Du3mSA+DhKlx45cIGBsMr8FzzjEzYdTVbfZcMjNiIJzrx2ygw4hmepKtsxEnDzX70W19+l3vGZUBOLGhZzydF8mzMqRo0EU/H91waMQEcZ9/KYRyPM8Yh9xwYbbIbZnamGRQiaPmMPH5HbtGYWQDHfcxvx+eDNsU04/TmfMZXWVQm6wyYIr6W0d5g0sywkub9w/hU8aD9hzbeGjk/Hh+8hl96s1JfO6+9O5qPscJw1GwI+Ty6WfqaEck1wNlMD5ntu+tn4IrKVlnGc4BdJ6HPV57zijC+6/9jjWAyQbdBmZp8+rvRmKAHFYzOLEni6JBEQGMeC5HaTj84nq7vARrvseKCAUHmKL9ZsGeftd7BsNlo5ohFZ5nZs/sCkYIo+BwC23xy8yDyydU452TGFUDB4N2jIcButlcj2cyplbogAkDMbN0ZqBcPnViRy318QHB/r3eBJoGqgaKPJPcQbNtfG9myaA02bIEsvQV88NzKucZZTovjvwrMyT0GfPEY2XmyeCU/jgxf6Af23ho+M55eZ7rZsp4jsfDjLwNs9eS65SA2OyR2+4+zpQGM9++zoDYgM/smYEE9XdEAjDnMfGcS30AYDRo8tydGmPq6DXPfEGv5dFXfGYd63Vlto7n0T8wfTlnM8rAPa47ToLBGuuNvjKgzjWX696pATwvdYqfP3XmoeeJdfdDm3YVACwpWUe5prXWT2x796DcCOWQt2EAguJLBYzyQ0nZMKBkUOoZdrCXmgAjla4ZFispK0R71BnKSUYhvXiUJG13W6bqZYMICMsQt/sKRWlFTd/hZaMkHeKlDIwd9baSdj+4HJ5F3zncdHLL4mAA+MxGOQ2BjYhDV7CeVvIwaDZaGCL3hw2XARzfm2Ews5JA0MyKQYgBopnmM9v3Dr9na9BnY8j/BrRTwM/zPRniBMXM3ePzB0dpFw77mh30Ly/Qbpg1h8jNnrn+ydQbfPPiHurinfLJ/JnV8Th43lBH+sn9Dyilb1kzUyw5LG3qAj+XvktG1d/lMVYnt8yOT/H88PqwTkg2DocwHTGDKYMbxsYREIPRBHNc6z7IOW4ACfPm9jM3ANDkIHtdmI3kGgNnpyD4f+sbA1Uzkg77JnlgVj31ZG0CKXkjyY7W2gOttV9ss0m/EN9/RWvt+1trv9Ra+9XW2qOttT8a13xda+0nWmsvt9ZebK19sLX25tdRhyEEnCFEe3BOfnYI10rIni7X2mhh+PD8czcwoBMFRDgBBZ7epj3vczt2j3ZT2tAbqNmomQlMg5bAN/P/HIajTDNSNnauk38gHfbMfQWQSGPuumCczdTZeNtTp+8MQgzCzCxm2QlckkHifuf1GLAacNnQpuEzqKQtBsk22oyzjQpzhrlCPR26mzLkBoJ+luvJ/HS9k3VxOM1ORYIlhwLTwBpc2pD7WR5Xr0fazbg67J3MmteSDbTnRDKrOCh8nnOaueI65RrM/rdDAAj9/9l78/Csqqv/ewMS5hQQEBBBREFlEAiQkOFOCCEhIQlhClp9nMUJBK3Wt9Zfawdbtc7WWsf69HV67KS1ikPVQqGBQgryONSpWtuq1VJnBQKs94+b78nnrBwG+7uu/PF69nXlSnLf55w9rb3Wd33X2vuQ7VI/eMYd55byzTkQCBEwJnvmdVUS+KJTQvBPMEd5Vh98OJ3y7EEdN0BxfDSOfL7up0xxMxn1G9cOd36TZeOapKPJ79UXpgpwrKhvBD65Npj3SUdVup95zN7xS0PAafkileoQwndDCHNCMgC8MGRB3ewQwrgQwoMhhL+EELrimuUhhI0hhPwQQnEI4eUQwj2fow25IQRbnt/6FggfOqSSogKmB0cGSIubjIjAD6+nspSRoQcuA6q6veHyrJ4UFw2PZyt4pp33+vVcKUSyD2yTDI4Hc0qOlmGiAqf3S+NPr591s+0Cxhw7spHy2mVEVTeBkYyixpn1su/MTfOsGUGIN/JqG0Pcmj+BCuaAeeNKg0DmUH97sE82Q21kbqLmxQNN5trx+A2G/jwTxGfpb4FK/q3rufmAxpYgmaBSTKSANdcegYRYdBlQjoHq8SCJRpYpDQIIlGu2WQwyHQSmZYgtogwQaBNEkRUSs84DginPuk59ofPlD4f2B3VrrRCUqe9qK3UawRGdOoItzi+dQK0jzYkHVlxbAlMM8fs1RpaU4FXr2etfDzA9801WlP3y7DRljn3X3zwGi+uEh5PT0SXo41xKt1H+aFf0rBQApuWLWjwA7BCyzN/5+OxLIYQtIYSjd/1/xK77JuGamSGEnSGEwftYb7QLOElBMoeJrCBBhWcbxCQRyNA4+VARFReNjZQLjbwMvQeqPq+O3qg8T68QpZhklMhWkY2joaCCXFk0O5aHqOcSiBJE0oD4a9RWz77KCPwm7+ioTu4GFTurM/G8YdOY0XgSeNNwU0ET1BAUECStLqmLjuchuGD/+Ft98/1T+33eGzfSeGaEeU0C4xxfGlqxLzReSW9KYPK6xpbzJlDD3co0mpJD9oufk+1kvhlBMe/xAJvjTAPMdUuD7I06ZcfLna4jSGG7kthI1cX8WD1D65RgiGuUDCudFrFgYrEY+uS8Elh6ppJgUSFZ6RbOAQEuGU3pDDpA3rnUuDBiwjEju09mUnItOSS486DO99frZ+omRjNUh8aVR3P5dcG3C6nvfG0j1x3BKnU+j3xhP/yucjruGhOO+YrCNAcwLV/c4gHgIbs+G++uWxFCuG7X3yeHEN5z3+8XQtgesqxiUukSsotLPwcGMIBiL5SYTwVBxSnFpVdiKYwjQ6BzynwSN8MDHohRkRKwkLVj2MQbR4ZNmDfEMJL3cJvLqyIwKeOg8+qk3GQktEmDz6HnTwUvpcZ+8Aw3KWwCBYI1gj8yEMzX0zOZp0eDoXZobAUcCAjI1GgnIZlKGi4ZIRkGghLNB1kbhrt0L/8naCCT6Z0HjqXefsHn+bAgjZ3qo2OgeaMs0hkgC6hrFeKk06I+a6z4RgzNkb7ncSk05mwf5VfGmZsnPFPE+pOOEyEAIbBVHimdE/9D+ZCMq/0KI2tMGVbmfRxbyR3D9JIPjh/Xl48SkGljyJbrkUdCcQ0kASg+T/f7kLJntwh+H85bGNuo5Nce2XI5mX7exE5qjHyqCfUK5U51cs4oU9ycpfVPRlO6nWtbjpWuZ10cQwJpjaPWPM8b5TmkdAypbzROKwqzZwWmOYBp+aIWDwALd302yF13fwjhf3b9fVEI4cWEZ70TQjhzN/Vcsuu5sZ/fTG7L/NCIks2Ssibgoeer5HYqHymPp6fOib1HlUBHhpKKWoDI78ilcuauThk2ho7JPKleD4QEpphgLaUmA+zBgv4nS6Y++zArlTpBLg0dmR3m5XAsCHaZ60YGjWPr66ayJ+jWOBGgEJD4MB0BPcOzZGz1HBkWhuN9uI5hK9apH+ahytDw7EAaVQIvOTICmPyOAJ516/kEs2SpCAxp6NRO9dPLseZE4XyNAx0hD7TZXs8MMdwrw0q50Xpg/ewnAQodGfWX805HzrNlqkvjRsfE95+HP68trbHlk1rzOdVvsvbUQ+onHUnfZ7Jtuk5jJWCk6zn36hf7tKKwwZrLq2Jrj8BSc69rCUS906S1xbQOH2HQ/HLs1N/m8qoIuGvstB70DDlE3C0s3eDBNkEbmWatUx695YGo32Cm754qmBs5/tSZ0hX+DFOmYEh/pAAwLV/U0l4AMJEBfGRKqzKR0mFIUCwawaGMnBa7wqEM61FJUOFKyTOPiN42mSDWm2QYqHgJNn0Ij4BTSol9phKWYhLAoAH2AMArSTJhAoMMfQnEEgio7WRIfH4OmSTWwxAuWR6efUbDTeXNt2cIjJBt8Ywpj38g65Ok8PlcyRJBuQyx2kfmgHVLrvwc+NfZsZ0eWOoIITJqlC+OnZheGnPNHcdRxpOAjKDaz63mlXOjNsspIujjGOr5DHFq/jwTw3VH4KJneEZM+Xi+vR6YEKBxHDiHZKQEkjwoJYAhIGUomUCe7SCrt7qkLsYukbmjXFCfeWZOjL9/hu7xrCTTS6h/BH7VN+6s5iYHObN+h7/GlsCbY6h2EazzR+uVspLERlN/a/wI9PzYEVyqn3x3MeWFcqI59LpEMirdp3vEnqc5gGn5opb2CgH7EtsFLOWhxe5DLTIABDn0zKXoFEogEyLwRhCl+wkAeZyIZxx8jhKZDd7H3DPm+BEEkDlhCIiKmywemZkkhoxhE7JhXlkSQOpvGjUPcNkeglPNjwcKaltSvTTaHHfdrzFR38moCliQfeVvLwtkjTg+YjjUPhlLfyyOlyd978GBQA9lKck54PPIMHLeyIKJXfLGXkBM/aZj4eeYQMs7EASfHmzJaNKYryyaHdslr3GmXLAuMove8Pu2EHT4XEg9kw4h20C5o/NGIEUZI+Dh+FA3qG61yb/P2OsPH8olg895pMPn+8+1R7ZUY5k0rzxFgOOteuhoco14x1jP8jpQP55149gmATfOsdfhHHPqCAFByhDnm+PGnf+8XzLqQ+JMa6He4P0rChvsoUl1KQBMyxey7G4TyFfwWW5I3gSSh2sqw3+wCeShSW1fhE5AQIaIwIOhAik9ec0KRVDZeLDCuvg9fxPYMUTrlQwVHkEK6yaAIkDwoTIaNRkCgmDWR1bSKzQpRjIJAkc0Bhx39Xt3wJGAkcZFrCGZGPaBBlVjyLH1fda1MugKu3J+NM56g4IMro5q8c9g3XpGUghUwJzz4o0rZZRt8kcZeWNLeSDTmMSYcE0QwIpJopPkwTSdC467jDd/eJ3a4kE9Q+0CyTTOdFK4BmSUmU/K52hcyMJ5EMF1mvS55IPh4qT0CTF2Hmh6gERwQr3Dtas15PM8yWSrbZw/PZfOgHdoCIh3B1Q9u652McROp2ZlUTyHmWDVM4W8xzuRlAMP1Ai29Ayfu+oBO8dDINiDRTqDjGQIWEun+c1a3BynexWG1/eU7XQTSFq+SKVnyDJ840NW6M/d9ffQXd9fGLIMX30IYWwI4YGQfAzMn0IIU0IIRSGEl8J/cAzMI1Najx9YXVIXbY54emrrgbU05lIKCmkxN9CDLG+MdB8Vmg8TeeUjRU4Fubtr+b0HfwIVfJOHFKeO4iB4IwAVq0YGKsmY+jbqer/jjgCEBodghsZW/zOc7BkFgleGXrTRZV1ZdQTayTj4Z6htUtbryqojOeA4S1783HgWgU4DDSyNLFkbAUpvdHU9z6SjkfPgjb896NNYcpz0P0PW3tHg3DIESUDLHEIPdvkuV4VC+WzvnLC/bDMNpwfTBBi61if4Sya8o0GQxnAp15pkiuueIJZrQddrHiRPeg+yl3vpFP6fpCPogLBepkkk5atpfJhLTPDJMKd26mrNSdfpOzoV0hViKyVXkgHmjBK80TlUX1eX1EVj5IEWHU4CTc2JHxvWLTbUh3kpY2wb/9c6V5skO0mgVfNFQMq1yjWrsVpVXG+/zqtPAWBavjClLCRsyAgh3Lnrex0E/XbIMn+/DSGMdM/oG7KA76MQwgchhDvCf3AQ9CNT4uEaLWAmDZN584wMPXyG1uiZi6GiYaexIeMhhac2SJGLRaK3TNBHo6jfUsTei2ayNw0nn0VmjzvcqFzFihEcJh2OLAXtPXoqbQ+gNHYaSzIjBIAe/ApwUoHL4Os6snkEyvxe/wuQ0TCzDwQfBF56O4rq57tWdR/BAcdfOY9JgF/3kn3TuEtmtKuZzCMZQLGmqkvGn0CYa8KH3GlA9bnkUnNNtsUzMuunzYwxZxxfXcccPxld7YSm40GZ8sw55cQfIEygrjHS3+w3wZ8AjNYNgZHaqL4ksWlJa08bFPSboI6yJdBJlo9yrDFhXWRdub40HhwjhqHJWHkQTBAqsMZ+iaGlrLE9dOLUHv2QJeS8+7xBAVyeh8j1SwfG5+t64M1+6ns/Bzxvke3z4863PpHF9+tE642sYpoDmJa0tG/JDSHYbwurYsaY4RyGUkj/U3lIGUkxSRFKYdMTJpNF5abrZfw8A+QVuGdwZHBpdD3L5kOnUlIyIvTmySrJmBHYSslK2VPBaUzIXkk50oixn2qLjIkHN6qHBll1EADpWR4YCpQy3MywmlhRsogaZwERhrLItiWBV7aDievqm58rjqfkggyZjMaT+fMiIEmg5QEp60gK7RFMEyhLXskK6pxFD7zI7tDxUH+1oYQsk2SDwIYg1ztalCu1TbLA8fc5YAIZfE+0ZwnVHq4VD8abMrXROZQExZRdrgmCRMmJzl4UOydZY5SB60P6xMsR/6cDQGAlcM2+EdjTufEbNDxzzAOzOS36L3UAACAASURBVDaSCYIXMmEebBNQc41R/tdPm9mGURd4ay6vimSJQJKyq/VNdpxzS/mn/HEc1UaCf/6vMWSfyZ7qmhWFDZHOkKyQ2eR9JBhSAJiWtLRvyQ0h2K/z6tuwdwRpXPT0UKlYFDqjUSBIkbKVUpNXqfoI8vRbhkPhWSo+H1Ziwr4UDRUM28KNB1LsBJvqW1JiuvpJ5o/9IwijsRKgIWhT/5nXQ2NKloRzQaVPloEgnoaOLJLAMhkjskRi6gg2PQumZ4t9IBiSMRXoIBuQdC2BD/uvsWX4M2ljxKriels+qTE2LgT+TJinEfSOBMdQbZKhby6vihlDrROG+uiAKMzZXF4Vmz8xPJQBP65qo3bnEuyz38y3oiEngNIaIEMnGWaoz4NvPy/M86W8qF6Ng+SGuoMgmiBJ8s68Vf3WZheNzeNTFsSAAwELx8DPLeeDbRHA4lEk7C/1ENNfqHtYp8ArnUs9T/NAtoyMp+aDAEr/UxeRdeb8+53ClCuesqAjdzRXXJsEvX5sV5fU2YaKyphu1dzRodP4atx8epDGTtfyqC7d9/jUmSkATEta2rFEu4AFSGQ8pYSlBJMMghYxmRcyVJ5p8gZGSooskPf6yT5KaTG8RmbLM2I0nFK8PgxNxZwE/GTMpag9u6kwDEGHD68QQNKA0iALHPg8Qf7QaJAxlDGSYRFYYb4bjw4hkGFuktqo+ebRHMxdIuDwhxVLjtQvAUkxygR4Hvix3zS0NMDsH5kwMlKeFVNdDEsS3CYZQNWruiTz6hfbyTrIRnqGRIaTckfgQxBGuZHck5H3rLbu4zgk5fgljRGdCc9Wqs1kEv1GAc9GsZ+SbbJTdHq8jHNuuE7oHNAJ5UYDMnFk4TwA1HwSPHv99fiUBbHdwwRiPOR4RWFD7ABxjTvXAvuhsRfApxNIR5F6UH1kHZQrgno9iyCOu4q5nvxuYy9DSWFs6gCOu9rNw7F9jivncXVJXeyEhhWFDfZA3uwUAKYlLe1Yol3AMvxSOjK2Uhb+TCx5vQKKNGzciUnDSJaQOVUEigIy3htePqkxZnh03AAVI40RGTEaaYZRqHh5L/NmCDTYVrKlPtSysmh2FIbyB9V6wEDFyGd75eyNM5kWggmCBv0QIBBwe9Dq2ROfp+R3NWrsyFQpd03yo/6JMSUAJIClcec4q++URc43ASfHj89gfWSBZNA4hjzImQCN4TnP2nj58m0ggEwCdcxr8yFCMlIEHwLXSWdp6joPnjmX6qcHbQwtU/Y0NtwYoefRYSBI8ekXqoehcR9Z8PPE3Dc6a3zVGMec65nrSHOhfrLfdD4IEjXvdKi8k8I1oPGRQ+idRq57fb6isMGWT2qMORUrCuPhZ+XVqT0Ek5IFyoCfN80Fx5AOdVIqip5F5k7jREdUbeKcqB/UwXQ22A89e11ZdboJJC1paecSvQtYxoALXgrV5w0RWFCpERyQCaEBIJvGoyl0j56jvCvPGPlkZQI/KihvGBjSpHJLCuNIUel+5ibRoHGzChPK6SGrzbo2yXOXcWX/BRo8AKBC5TM9AFI7VDdDhl7ZC/D6kCsNAQ2D/5yghAaUhorOg3cKNOYy9ty4wXCS6pDB8psayCQ2ZWqjdxV7Fk7fJ+VUqn8cC/Vdh1JTtr3B5RyT+ZF8EHhx0wgBj++Lny+CRM9ukR1PchDWZGbFdqrqWdz0pfkiY84xknxrZ7vGUKyWcjQJFj1DS2aN80zgrs/YF8mKXqlIgKs+qt2Ua80ZN3OpXrLudKw4/rqOa4CsPVMeVI9nmTVW3llg3/SGGzqLXlYI5vVsD5K5HumMS49p3eleHpdD51usHvWmxl06lLrROw/+c6//1I81mVnpm0DSkpZ2LrFzAGlU6VVKuXqlxVAFGQx/8GcSeCTbRuDCtyT4cGcSayAjmMTQybOkwhFgSQrf+tAdQx5UuFTYrNcbDuZONWVqbUNFZYzR8J4zn03lT3aAc6M2MzeOxo1GQTlaVLjM3/Hzr3vVBw/efXiVjK5nzci4sB+exZAhp6HRM2SY+UymJ5AJY/2c+ySGULJIpkRMFtkdPZfXUl4kVwy7a3zoeHjQTVBLEJHkgHGzkRhmMkPe+CYxLwJHBNVqJ0GtlzWua+bOci50fAoBhGRRbeAcUL592gWZSP4vGSUYUpuS2C/JEZ1Nsb90rjwr5cEU1ydl0MuwZ+iYPsPnegBMQEm2Tn30DHKSPqS+1ZpRvwRSJUfMw+a6p6zTOddvjRflzYeYvWzoXulc9YmOzFMFc1MAmJa0tHOJdgGL0ZICZniCnis9YgIqepHew04KTzA3SYZcBo65QvKwpcDJkvhn0TgngQ7PWFLJCkgSgFKBESTRo/dj4I2299IF+AhgWT+NHg0Zk+BpKBmuJggkcJWypieva2XQNAcyYjTY+i3mSEaK7yAm8CWoXFdWHTFn3iDICMoY06BKbnRe3Mqi2fbo5MaY8SIIpoGlkSazTZaNLLbmguBH4yP2l+OjeSTzu7qkdePR6pLW189R9hUiZNsJglYV19vDeQujvvOImD3Jg2cl9Sw/BmwP5YXgVvd4psavOTkDdAD4TLLjTN3QulEfCKAJ5CinPtrg5VbP4v8Ea5Q1tpkghACOzi0dAY2rl3XpSvaF8sz0GcqXB5uSsSS9meTcccy4uUj1aZ2y75o7rkeBOOmzdWXVMTZ+ZVH83eXsh3SVB6de33vwzvbqvnQTSFrS0r4lN4RgD+S1BWUEQXxfpnL+pGAYzvLMk1c8NKxkBbyX7sNdXnEyrMCcQraBDJEHcvR4FUpSuEp9Yw6ON5RrS2vs4byFEYsiBUnGiEDB94NKj2EyMkBkN8jk8DuOrQdXAnv+PbNMSieL4EPR6gMZFh/u4TwQONBwa27Itggg6LmaF4bOOG7+oGE6HzK23JSjZ7FNDIN5IE3Dz9QB/rBPHFNuzJAskElSf2mIxcSxT5Ihhtf837tjVrx8k0klKyoZZeqAB4+83gO7JOaHY+eNPNkez7ZprWu+9Pfa0hp7dHJjm357Bo7jS5DhQ7oKR3sGS/XqpAEypB7YcJ1wQ5rm3r9pRffrPo0v9SjXruSD88t3hUsO1D7vvHqQS+eTURqmmfgc4iSWVswrw/OSHekSsoXSEUnvGKcjQadMbX4yf17KAKYlLe1cckMI9vjUmbHjI6hsyQaQ3vcGhknBVIZeGZHtofHi9zTunsGjh06mg88jm0OWikrTsxwModBzV51kw7i7kiyDD8UxbEmWQAqZAJP9J3BSG6mMyciqLoaRpJBpYAhQudtYfdBcigX14SUCT89mcazp7RMUqX9khChXNAg07qqX1z2ctzB2MC2NGuWB48HwLJ/HdAMCbAJ47fJk6JtzS6eDMqJ55tmOZEcJFDyLpF2oPmxGWWVb5Ex4EK77xNhyPfnz8DjWnmHyDA9BjOZhbWlNxHx63cE2EfBTxuksEOz79co8YB4WLmdB+kj1kDHWXEpmCcrVV84DQ9pqM50IMpkcs5VFs+03eUdH/ePcc0MM2XA9j86s6mR7CIr9fGtznGSTDqWu0djIGaA88ZQEz4ISeHs9Q6eD4+ujMqqbzr5+0ncBpyUt7VtyQwj2ZGFlDCR4Cp+LOolJ0rVkAGiUBSzoxdIgkmnQM6kwZbwfzlsY8xilzHanTPU5mSfdL/aOeTs6loDMEEEn2ygjT2DCv8nsMDSVpMgJUmiIaZQ4vgrLMJSkOmk8ydD5caHR1TMUqmXivJLSNS5keAUC/WYKshYEtQQ/YgLIanhmjyBM9xIYN2VqY28eIGPCg2h5r7+fTDfBJFloAlQyYmTgCGz8d2TEKbOalyR2jTJCUEIZInhnu9ZkWt+A4ueeTCcdCN9G1cs6NW8Kw3u2yY+V5lT1EURwrunQECx4UMx5ofMltsyzY1zzfpzp6K3JzLLm8qqYfhMDSOaWDC91U1OmNnY4OeeQbZc+ovywLVxDdIo1Z3SkCLzJ/FIfr8nEjw7ivFJX+LZxrHn8EVk+yjLHWfXSeZBDyXxiz5A/PTU9CDotaWnvEu0C5mL0bFWS90+PnOFBhveYw0QPkIqGz2aYSODIh4987pPaorAcDTETn6lECWZoBMl+0nP1/SQA8sDIgx0CPNUlpchjdzSuYov4xg59x00cVOoegApIeHZW46m58AZI1+gzzZUYFKYIqM9Mzle9/jVz/rl+zLxMkB3yzoH6xe/IxhHQaDw8u9KUqbXm8qpY7hKZSs4fHR8ZNF1PEOONNGXBP0PtUjoF+yajTXnygMADCzJeeg7XCMEXn0fA5p0Brkm/K1vsod+cQVCRBLwoS2S6vEPCceRuWu7gTQL6fly0Xhmm9s8no0iHlukYZPn0ndpKhlx9IuvHcaFT6sG25NdHR+jckMXT/Hj58HqIa0N5fgT7TZnaKA2GTr3YZ93nHV31h8dKsW10rrTG1S7pN66Hx6cssEemzEoBYFrS0o4l2gXMRc5wojcYUkwCLlImUl5SGDT2VLw0wr/JOzqmzKmQaVQJCrhjVs9kXg89VtbpjYrqojKnApQiVeiMxk/9lbEmwFV/GYoiyOLxMVKIukbveaVx0Y8HcmTDCCI8A0WQ+2T+vNhrsjifHhQQ1NHwesCm/osBEXOi+vQsbiLwjIrGjQaccuKZNY2dDAmBqcaLDgRzCAWiPLvrz2skiCRjTAOnazzjwzlh+I+hVI2ZjKwH1yuLZsc2wHjjyfYJoPhwKNceGRqF4vUMzgNZYx8y5xhzN3sSgKMTw1xhH0pUO3yqiP4moCIzx9xBpmPwPtavMeE61vN4IDHlnH+TWSN4pB7x+ka/2TeCdDJ/dEDULkY6yAqrT3Qw6GCxrfybrDufyTXH67mzuikT37hBmVBbCS71PR0mglT2X3WlOYBpSUv7lggA0julEqXi5/ERNBQENFQWVKxUfmLABBCkCPQ3FTRBEo0q2TcpSilEMitURs3lVTGlTMOlnW9kKAg8CGipmD1gUL8YIiEYkRFkWFdMmvoiZc6cOI2z5kRjxTC0FLEUuHalEkTpuTQsVMTMrRMIU/9paAhq2T7vLOgNEn6cCB6bMrUxhkXtSAI9lEOyJKqLxpbAl4yYD9cRsElOBfz1LAEs9j/J0aADQLZKoXKuD+ZDetaW/VOoPSnkp/sYpvcghOkOqkPtEqvsGZskMMa/nypofdUcN1ARhHoWnetczyC7RpkkM6h2e+Ce5JBKHnXYtBxSAkCtO42LZy05Zh4U+txjAm06RT59gbJF3eNz+uQAS9Z5r/QE54nfaY6oC1iv+ixZEYPKOSLgJ2tMoMgffUdQR/BJXSV5986p5jANAaclLe1bol3AUgYCJzSeVFgCEDJM3iPmUSEECFr0ZA5pbJlXQ3ClungfQ8zKCxTwEsOmZ0r5KFeICoeAyzM5PtxEZkU5VmRDPNgg00GgSlBDQ0imhGMqZap76PXrOypjeuhkYujZKxGegEL1e+OmZ9HgEhzKMDPURqbCMzkebPix0L08LsIDOoZ6KScCxARUHB/P1rBOzpvuYch/+aTGGCvEPEnKB8fG73DmXHMDjeRaY//o5MaoD5wfjRXz+zRG+qHMsn8CNHI89H5jD7JUD1lugg86FRy7JOZN/SQg4X0EOARDuicJkFIGda9klZu26DRKnghOyOZ6p4XghWuCjK+e59tIufQMHKMcaoPqpdNLFlvjwGOwPCjU88l4c6zUtqcK5kZ5vgTGPgxPh3FFYUMkj3qexoNjR1ZeDhD1rOSac846VhXXpyHgtKSlnUtuCMEemTIrxpJICXCzgQ/XyeAkeXM0qHzVlwwCQRONjAzJ01PnROeh0XOVstKPFBUZHIZAqDBpRPU5Q1NUVp4N0xiQXSSLqLHR/75NBAzeKLP/GnOGsqXQyfR59pPjSCDdXF4VCyETNJK54NxxxyTZT732jw4CwYIfS4I2/S/jw2s0Htp9zLdtaIySWEw6A7qHx4/oO7KvK4tmt9kcQWAlYE/wQ1DAvzUuBCK6j0ZN1xGsaq49Q6J2kK0jUCSQIgAkKCaDRUBBGRF7J6apubyqDZuj+WEYX3qADiH1g2RD1xKAeEDHkCfbynmhLvJgQvrj6alzorQGyonGXkwsPxM77gGVrvHMGeXVhzL5Bg31kcBQa4JOq9hfrUsx0tyNTV1G3eIdYrLFlD3qaq+vJAM+N1jjr7XkowhqB0+MoO7m5iY6dl4vaUy9Y58CwLSkpX1LbgjBlue3KiSdaSWPkYqNhkGfiyXR51IuDOd475+KmCwWFQYNB8ELWTSv5LxhJwiTEl5VXB/1UcZNG0iaMrWxHDnVm2Sok96p64GUvmNIyAMujbsMha5JYgJ4vwCLDACBG/vsmQi+GYV9IoDxuT808GQ3NP++ToJSOgwcSzKvHnzSqBFsarwZLtcYM9SuNhKY636/s5Xsl+ZfzyCg5xgSEGneVQfzzth33w49j+FtzZ/P9aQRZd0EHv56z7DRmeLYaSzYP8qHriWw45xRJj1YovNBoK22MnRKcEX2dENFZQTW1mRmRWBf/VC7OLfUDXQ4VL9kxbPUT+bPix3mzUiHd0QkcyuLWt9Coz6zTbtbj3QE+JnWNYGx2FrqUTrfXob1XP6dpAs0ZlzTdEipwzif1F0ri7LH3fCoJDlRlGuGqBnJoM5Ij4FJS1rat0S7gLlzMwmIrCjMvhWESlUKkoZM13OH5aOTG+3hvIVtAEpSvp0UV9LmCrJWUhoK/cij9UqdbIgHjlKyYtgUIvHAjmCGAFNKkGyDlKg+JxhWvWQ/eFAtDaheKp+U86XfZOlkpJ+e2vr2Cg829KN7WR+ZC4b7eFQOQbo3AmRwfMiLgI7tUFtk2DlGMiCUEzILK4tm2/JJjZFx0TPImPg2kZlqytS22XRDeaNRJOtCAEO2UsZU8+ABtOoUwOCObg84aLgJ9L3zIXkWC7WnkCnljgCA6QFiyzxIoBPw6OTGGGvFOfMOiu5X6I8AlO3zUQeCXMop5ZhrmyBKP3ybBe+l86K1xFxP70DSQZUskm2XnPE94gT/dFy5zrxuIytJhlfz68GjZ005Z3I6OH6UZ+pf1adx9OPggZp/VhLg13c6hYHsIuVWYyX5fbJoRgoA05KWdiwRAygAQ+PHkKwUhA9tkGHQM3QPj8pgyGF34SYCO4Z5adyk3ARKdb3Px6LxZFsZSpXBIcNGw6DfUlACc3oWPWaxYXq+PyKD4+BBJBW12sFNERovGgGCP46P2qK5lMHSbzJGnpXgmChM6JkBgRsabRoJgnCOpQfgqk8bK7jT2htfjScPqPaAzefKsd2e+SJ7w3uSGBP9ZphRYEjXepDHZ7AtYpM8mFGfyCr6+WaaAFkp/zo+Xe8ZeBp41SmZZXvorFC2CDTkGHD9Kd1A+WJevrT26PBoPtUPAnUCCa0f6grpGK05jivHgmF6MoDqj9YodQV1FJlNH5qVfLPNkgv1J8mhocMhPct69b2fC8qTAKd3VtQ+n27inTeuI+ofgkHKi5dtyqwcAtah+ZGs6hr1iXZCfUo3gaQlLe1bIgDIMAzDUj7kSo9RC7gpUxspfnrsUo7+sFApD+44JbviQaWUiA/d6Pny9qXMCHpk7HcHerhb04cuCVilxNQGjgeBG5UjlTH7QxZSRkXPphH0PzLkMkoyNjKgns1KYi98KFBjSzaXDoDG0ofnWYc3EvzhvT4cqJCb2iQ5UE4aQ8QE6QT4BIlqg0/cJ4umdkmGfR4fHQiyWgSOahtZQOWDeaPK52qsBYYIrMX2ikUnI0/gTuBBxo+hQ7bZM4/MKSQ49wyh/leel9olWZM8q40MAXIM/AkBXF8MtROUyAH0IJgARGNCBpPtISNFJpAgV2uIIJlAnXmGapf0igeVBOpqn9cVdB7EimpsufFFbdQcSO7I0tMJkp5SGwWyta7YDjKSyuklEKU8UU/R0aP+kHOktvqcS86v9K0nGFRPegxMWtLSviXaBSyF44/SkGHyzArBoJSQlBMXu2dsZND8EQtS+jTOUvBke8gqUllR0dB79wBN3xMg6RmsJ4lpUh1kxsim+Dwhggk/Nuw36+OzaMzJMGhsNe7stz8fjM8g28R7mjK10ZE9NP4E8xoL9YXHUQhUEKCLmaHRYFiaRlpghgDLs3mUO86hgI0MLpk3zgUNu55F1klJ7GRwaVSZd8i8R/WDwElGnkBJ7aVMcoe9+iCmkQwfHSoygKxfQDbpKB7JE5kgMmucQ7WHDC8BkgdxNPbeYfCMKduzoaIyxg7RWUpieNUG75RyvsjGa36SdvFq3Lm2yAJ6kEPQxc0bXEtsA+vyuo/zSYcjac6o26jPKHvSAdKp1FW+HUltogx459ODdeow1uEdagI/jaXq9/ZD625l0ex0E0ha0tLOJTeEYL8trIp5e1rUUiw+vCalzaNSCBikTJPAkBa/2AUCPA80qAzpiTMcJKbOAzzP+HDnbFOm9UXmZKjIWnklTECoOqlUPQCg8ZTSZpK6Z7bUR89OJPWLh0mTZdWzCGb1OcM1HB/9Vh26l+9MlbFVGJaAQqBJBoLMqGcVyRrQcJC18wCdoIPvuhUYZshN3/H1cJRNPcuHbzX/DE/5MfHGS98zbYJ9ZK4X69J88rw8tov5oZRfgTyFXxkOVf0efEjOKN+SG7LinqUhaycwpedx7Uk+fd8l877vdCi8o6fncIxZZ1I+KHMmNT7+DE7PImu8NU6ULz3DgyPPhiWtX/6tNeU3ZlGf6G/qHDHBrF/AkjpG/eSa9mkAlHP2g/JBZp5rmrqY65djz3qoX0gcPJy3MAZUvcNC+VxVXG+PFVSnADAtaWnHEoWA/5hXYf87vtBWF8fzqaSQqZS1wGlYpSS4u9YDA4IjepBSfp4pooJjngxzdbzyJtjwoSSCUzJDPAJHRlhtI0MhRUqj4o2cjCnBnuogUOO4amw8G+JDPQRHPEYnyeOnkfDGh0CrKVMbHZpLVoMGgiDWg3TNBe8hq0lW0BsCjZPayt2vTZna6PBljQ3bQjaMcumZWw9gNacyjgqXaTwFzASWxKyQzRSz7Q0iQYVvO5kigRPJm+aDc0mWletM/dbY0aCy/Wsy2XMv15ZmD2TnphOmb+g3mSbKiiIABPSSA+bPeQDEs+gImHjgOp0AOiIab65n7c4muNFnZJC9w6rvuK4I2KhjvF7QuIjNTZIrAU4CZoIjpQjob11D4EvWVmCXgI75jb79BONcZxoPnXDgWT62lfO7p+85/t5JI2Bku+iI8LlaAwxTpwxgWtLSviUCgP8YcohZCLY1p4u9PXCoPXtEvq0tmhkpECkjhYh5sCrzmRieIOvG/Bqfq0Ojrf9lIHXAM5Wv9zZlwGloyAxSyVNZk/2gl07lpudI4SaxfWQidE4gD3f2TINnwuh164fjITBEpkWGVe0UG8UwtAdDUsxkBsgUSMnrGil/gRAZJgJhKXHPVMl4qm9MByCzRoeCY6NxEIgi2FN7PNslY0o2i2Ol32SrCfb8+FJ21HbJkK7nnGldMHdUfVxR2BAxk9wZSZlPApJJDJWewfUmuVaKAkONSTvCPdPFa7xcc1crQZPa4oE7261+q27tvObaJIDnelM7ydh651EgjLLD6APb7x0Xrg2Cb89G6rnryqpjrzzUekk6SJl6hCCIdXB9M9+QzqbGUP9LH5M98/31QJipJ/6sPu/YaR6YKkHnWTLGlB86AQTP1M9cC17PSd+nm0DSkpb2LbkhBPtd8XT7rGt3sxBiP9s7drT39h9gL44Yb8350yNlQk9dLAQVyVMFc9vkDjZlamPhQ7JyUhgKMVJ5UOl4j5kAiIbIKz6CNhopMpJUXr5d6rNXajKQAjcCMjwglcDS73SUUiQ4IjARuBJY0HjTACftFCRQIXDRZxyT5ZMaI1ZLdfB5uo9HrHhgQcXOI0rIWJBZI2jjWy/8nJH9IkupvnsDQ1aQAF1tlCwJiKketc3vDBYwIPtDmfOOgsaPYTwaWrJVlCWdS8lnM5dOTB4dFrJWnFvKKTdZ+bSGJ/Pn2ZP58+zRyY3RGiaYIRhNAtcETVzjnHsP8DRnmlOOIZ0Asttet/B/Old6DkGg7wPng/OiOpm/xiOd6CzSYST44bWMYOhesZ5kbQkSNb/8Xu3gmNP51bPlkHANaMzlzEkG5MRTz/n50dhTpgg4KWecF4JARYi8rhTA59jrnsenzkwBYFrS0o4lN4Rgm+on2l+PONLe27+/7ejYsQ0Q1M/HPXPthdGTY96wlKIWOUOAfIsAWSMqDSlMGh0aR69wyZj5vC8aXSk6GS7teCNYoRFKUp5StFLcNLw0wDLi2s0nwEJFt3xSYxsmhUqTAETGmcwk8y1lMBiiolEj4PQ5VgyfE3ARWFIpC9TQEBCscc60o5dePefWg1SyLmRcOMc0SnQCyG56dopG17PFvJfhTskJHRS2S+wnGToCQ+aeJQEgsS+SO/1NI0nZkhOlz5JArdag+iR58mPtw4kErpr/5vKq2BrSDzc2cMe85I4OgsZTMkCAoM8kD0ksrcaNAFMOkkLHlHF/NI8HgwJHnt3SMxhSJ6Prd8MSnHMteSeHzCfnlk4kQZcHY7pOqQo8F5DsvF/n1BNay5JhOp2UX78m6Xywr7yP9/CUCMok2+rXNIGirmdEKd0FnJa0tG/JDSHY5lu62daru9pr86fYC1XF9pejxtm7g4bY1s5d2oDAl8blxQ11YbWtK6yMhcWoSMju6Rp6uQRi+k0gRMW9O6+ZoDOJofAMglduehZDl2TSqMD8GWJqF3OBGBry3i8VrcJJMh70vJP67I0j++E9d4I1bhhRv5hfpuv1GZW35kptIVghyPDfq99kTghgyFIxROfDm5QRgisPbsi6Cazob/3omQTzZMY4vuq7Z3PINBEsao49S+PHSZ+xLj2LTDnny4+vZ/OY/yXwogObkwDI6pI621BRGY2JQI5kgDLq28mNFWQOlY/nWUc6VqxH408nhruAtgAAIABJREFUiU4FWXyGzAle2T4yfbtzQL1cEojR2dD8+Nw7Amk/H2T+fD4pIyHUP7pX8qjneHAtXcM2SVY4vvqca4YOBNcPr6WccM1Th5EhJOtMmeJcaG71TOoezgXnKwWAaUlL+5YsALyjp7U8OMBa7s+1bTfl2CcX97e3TxptL9UV2otTJtubBx9iH/fMte0dO9n6kkpbP21m5J2+OnKs7Qwd7IPcvvb6sMNt04RiW1PSyhgxPELDwnCCDBbZLnrg/JvKnG8eSVJgZHHozZNpIaDyhsIfbUND7IEJE8W9t/z4lAWxMIqUI5kkMkErChtiO1F1jzx6Gi6fTK9r10+bGRlz5gDxXhoyH/LxTMDumALNK+dMeZAEVgoJMbzHDQsETtz1SIPPOeX1fK+r5sIbUBlIAm22UewtZVbPJNMsufOMC4GyN4ScRzkYer7m2oclPcgl26j+Edj7t82of5Ijgiz1RYCR8k02kQCD57dxF7LAOxP6PevGcafDwpCyWG8CvhWFrRthKBuejVab6fx5Z495chwXv9bJEBNUUZY920p2nhEGjU+Sk6Y1SsaR40FZ56Y0Och+gxfBpthj6jTNv2+T+siNOZxjMZFsj9cn7DuBMueD+oY51arj6alz0lfBpSUt7VxyQwj2/Lyj7KMLB1nLfb2yQPChgdby897WckcX23JFD3tjYZ49X1Nqz07LRKEiGaF39x/UhiXc2jnH3hlwoL00arytL6iIgTMpDhoEeu4EGQR8VD406gR4BCf+8FMCIXrfYlDI2HAXIhW/914JRLUrUW0j+0VGUAwbFape3UYgQRDk28wwEQ23rmPY1xsLAisd9UJwQnAjAyxwSkNHUE+DSIDB8eY8eKPhARrH2YMhGh2ygv5+to9gzn/vASENMsGEQIPmVQaceX2ae7LKkh0yhB70qE7PYhHMkT0SW0RmicZXgNizdxwv9vmpgrlRXyhHOuJH8yMQT0DJsKRSJSin+puOIOVTgE/tfXzKgjbMp9onR8OzSmT8/Fh4p4cpBWIjOSeeOfMyIxnkczSHZA7JnFGvkOnmeqCM0znU/ayDzo7fZU82mXm3dCDUtiQglsQA0zGUXHN+NGfcOCanj86axtaH/1VfugkkLWlp3xKdA6jF31xeZRtnVNgrDVPtnVMPt0+/1cdaftnXWpYPsZaHB7cCw8t62vtLh9nbhwy3LT267TZvULmDr4w8KqZAqZTlYQp0MUxMxoUMHYGDBwwCPWTp/K5iMY66RkCM4RTPONFQkNkhgPEgiW3yYI1sjmcXCP5Ur2dDZFRUJ/vM62mMVTfzqXicCa8h6GV4UUaKRtXXre80r1T4+px1EaT4EBuZYs0jGWXmcqkeGSEaV5+YzmN3yE5ynuiM0NgLbNJA0yHQMwgU9LfmkABFRvWJ/PltDvlW//m3P2LJA1sCZs6jXsdFUKK2eYaQAETt5pj431zDTHugXGgNcm4Z4uS8af3R2fFMHkOLDHVzfsmsKlc1KWSatN48i6twt57LvF7PEtMBZMqBd8b0N8Pe+pxzwWdQr0lWCMy4rgggCT4ZOeFaodPB3flk9fyGNtbF8aRMiJnUPc3lVZH+W1k0254srEwBYFrS0o4lN4Rgv5lc22bhS9E9O3Oa/ePY8fbh+UNs69VdreWu7lmGcPkQa3lwgG27Icc+vaSvbV443P41YZh90H9/296pUxsQ+NohR8YYgLXF1fZMXok1lcTPCfR5fQzZ0nCRvRIjScPhQaF+xI5QQfFHSpTjwM0BBIhkIuQBM/xB5ehP69czyEJ45cmwLOsh8GTYhkdJqK9iJNQnJmAzdEbQ5cGQDJAHtj75nCyK5k1A3nv9CpmTOZF8qD2qR3Pw6OTGGEPjWTeBeBpy3Z8ERtVOntXGjSuedfOsHA04WSMyJl6u6PxoXDg2HqwnbT4SkOVnPCjZA2rJJcNwAgAMBRJA6dqk/DLP/iY5DGy/dIl3ltgm/c3n6jgbOXQCEeyD6ieoo3NA8CJAQ/nmQeYCNgSUnhXTfPljg1QvHRE5HQKTXjdpPHkOqebAM4RiPgn0vSOltby79Un9ouuZ4+odVjnLvF+feWaefRW4o/yLYaYsarzXT5tpm6rK7Y8zilIAmJa0tGOJzgGkESdDwdDQszOn2cuzC+3d00bZJxf3t5abc2JgsOWnXW3r1V3tw3MH2SuTJtg/Dx5mn/bqaRaCbczLxBT9pqOKdoWLu9i7/Qfbn0dMsDUTK2MGnmBBCpTGhrvkvPLlb+XDyEDKeNOQM++ISs2zhFKCVLye0dTfHpzQ8NOQkT2ggSDA4HhojDRfMg4yJDw7jwBPyltAmmDQh2poMAQ2+Lq4J/LnRyyqD6/TqNOA+tCX2sH+E6jpM/VvVXF9tNua40UQIiDjgaLq47tKtbOUc50E6LxzobHzgEX3EEBwLgkoCGzpSGgMfEiWGxrI+FGefP10HtQnyv5TBXNjYUKBcsqwHBTl/VIuKN9+bdLRofwmhZB1LwGxns8NCQRI3JXNNcRruZ6Y1sFjpMRIql/N5VXReNKp4kYNhjG5TgVyCag1zjruiM8ggKXzQqdDz0jSCx5MJu3wFmhmribZdDJ6dBY9OynHjPKkMaZzS5mQTuBnmofm8ip7pnK6bZxRYW+fNNo+uzTXNt/cJQWAaUlLO5YoBEz2wIc81mRmRR6dQsQbZ1TY8zWl9t6S4bb1ym7WcmcXa3mgXzZM/NBAa7k9x7Zc0cPeXzbU3pwzxp6bWWrPVE6PwqxvDBuZGC7+tGt3e+uAYfbKEUfZ+oKK2NlcUvj0Vqloff4PwzUCBDQkNIzq+xP586MjY5ZPaoydS+jZGbVpbWlNBIak3AVcmF9DwydDoHarn0ri9ufCkS1hojlZFV1LEMvdsRwzMmw0HhobsiSemaT3r/76s71ktMiOeFDLMaHx8mBOxkpzqLEi86q2eIBCJpBMqQcuBCNk0SRP2rEtkETQJ1DMuSUIIOuosVN/KM8EphoPz9xRFgg+NUZ+ftVnPs+DVYIoMjlkHv1hz9yZS1klmKQzQAdD4811nPQ3QS9lnXPNcCbZMzKXaqOezTxX9l0yReeDzhvTIChbahsdTYJV6iXfVo2D/+3HyYMy5n9ybHQvn6XP+TaVJMdVrOvunqc2a9wJ6Ch3dNb1/YrChshuPFddZn87eqJ9eO6B1rK0s20/toftOKqLbb62VwoA05KWdixRCJgJ3h5QyTtlCFK7TDdUVNqGikp7YVbG3jxunH30tYG27YZdzOBjQ7M/v+xrLbfn2GeX5tobC/Ps2ZnT7C9jx9l7ffsnhov5816f/rH8KxoIhotpgJkXRDaKoRnPgMnrl1LmzlxvgGjY9B2NFcGllKWMi2cTGYqRUeHuXV3HhG2yRWRJfZ0yYPTiaWh4PY2cB2oCBczF9Mad7SWrwXCqfnMONF66jv2isXp66pyInWF/POiVcZXc8tgRD/DE/vAefcfQ4ppM68YKsqxkJmkwJWcaSx4U7mWOjgQNvpc7XU9wz40jqoObArzssy46U8xb5fO17rlJigwo2TYvT6xfYT71jWBffaJ80tHgWtE60Pior5RbD0QpU16myagSLBLcSTa5y9azr9RJBFSae++UcBwJrgjmNUfSeWLfyUaTaVN7fG6v2sB2UldSNtU/ybqXB+kmMuCSJ10nB0mkwaaqcnt25jR7vqbU3l881Lae3dW2z+9kOyZ0tp1dOsR0/V+nHJgCwLSkZVe5JGQXA3/+jO+7hhBuDCFsDiF8HEL4RQjhgM9ZR24IwZ7cdY4f2RotZOXgSAHQmDA0QTC4oaLS3j1tVHYDya052Y0jDw/O/tzTw7bdmGOffKOf/ev0kfZyXYG9PGmSvXXIIfbBl/rajg5xpfD2AUNj7MCKwgb7+8GH2Z9H5dnaKZUxRkzXMKTGs/bIJFERE7zJIGpXr2e7CPg8S0CAyV13ZB+ZPE3lSmCgcAuNitosZU6wQZZA80YgKEBJw+pZNjJiBGQedGiHo88bJBCTkVQ7CDpl6HSP3pzCPEUaYDIYahdDqwS4ai/nWPJAo8ndigQIBIU0zkz094bRszM+vE7QL6PIfrHdZGbYXjIrNNTcEMG6OH7e6RFgUDK+Z7J8P7m+9GwxYWSffJ3c3ORlRGPAcZeMUL9w48LuxoWpB1pzkl0eOUQmi5vEeAA6QTBZT31Gh4NyR2ArHSMn2f/POeczvQ5LAm7Ut7qfoNYz0RofjQPXEdcKZcwDd6bOEGhT7ulkrJ82056pnG6bqsrtjYV59u/Fh1hLbY7tGNPBdnbrsEdn/8XBw1IAmJa07CqXhBCeDSEMxE8/fH9TCOGNEEJ5CCEvhNAUQlj9OevIDSHYA3mtIQt6dvyhkkkKM9Ag8uXzMnoKHb+xMM/eWzLctny/VxYc3p+bBYYPDrCWu7rbtqs625bjetmn4/vYZ3162utjR0dgbF1Ztf1xaqXthNL4rFt3e/uAofbnwybY6qOq7OmCtsd+CBTR2BAISYkxtEemQIpVhk2KkQZV4EgskRTl8kmNbcIuMk46PoFhlaSdfMzvI7BoLq+KwJNy49gfgkqxCDR2upZgTgcI8xoCC4bcvHGhYSY48awKx9cDgKZMbYzlIfgkyNF4iWGRs+LbqPYz141zu6q4Pnaci+aaz/PskMCT33SjeVXdHhSxXwTo7CvZPrJUvJ8ywOfot0AAZUlgg20jg6M+k73VOiLI0/0EhwL2BMGMJvjcR8rew3kLY3MmwERdQoeOY70mMysaE8qE34VN+fGARWPEHfNJek99VV/Yb7LmZMO4LjjPnDcydTxM3uc8+zXk1wwZUIJNzi3BKueT8qa1xDQDAsINFdlzYJ+rLrMXZmXstflTbPNZI+yzS3Ot5aYca/nhANv2xPCsTr+ru227rou1DMtJBHxbc7rYP/sfaK+NGmPrJ0+3R6bMSgFgWtKyq1wSQti4m+++FELYFkKYj88OD9nFU/A56ohCwFK8PMaBSozKmawSD6P1HiRBgO7ZUFFpG2dU2IaKSnuuusz+Mi/f3l86LLuh5L5e2TzChwZmf9/V3bbdmGP/XnyIvTZ/ij1fU2qvjhu/Ry9yS05X+1f/QfaXEaNt5ZTamHKVoeHhuFT0BABS3D7MLMPEfCOOD71jGVoZCm/YxQbSqDCs6BW92kembnVJXRvgSkBOhsvnDelZnCfNsfrPH7Jb2kzycN7CaGOFGFMmi9PI8nP2T2PAN78w1OYNrNgZb1RpQMmSqZ/cMc1+JTHIDEuKAVE41DMjZKXEBJGFoawRwOjAbNXLXeRk5CS/rEN94pwTcJDBp4zxLTzMaRPj5DfYrCurjt4XrX7v7rgRghV/GDsBjPrpQQ7BKllk6iO/a15rwO9ap4On9khmGfIm20g9RtaNoXXW7WWT4+11KJ1NsaOaRx7azOsoh9Krfkc3WXb1h+FY5n4SrJLtJNun39IrSvV5pnK6PVddZi/WldircwuyDvx1Obb9wl62Y05P2zmys+3sGGxnt2CffL2fvXvaKHt1boFtqiq3tw8dHgG+fw0YZC+NOMqa86bZutKZUZ2PT1mQvgs4LWlBuSSE8EkI4c0Qwl9CCHeHEIbu+q48ZBdKb3fPX0MI5+7hmV1CdnHp58CwaxewFJEUMH8/PXVO9MJ6GV6GIGQw6CH73YR6njxT7QRbP22mNZdXZcHd3ALbfNaIrHIRINSmkvtzsxtLvtXDPm7obx+OHmAffal3m5CxfnaGDtZUWB0xPE2ZWls3pcKaCqqj+qUkycwRcBEM08gzdCMQ7BkwAQD/hgHPgJBx0ncCVDSavs0CKvpe7x5WP8iU8RlJxoDPVDtoRBn69m/dILgiq8a5Z14dDaLu471kpDgnNMZ0MmjI/QHOnnGhsfYAmwaVTBDZY84JDTlBtTZHEKh61lxj4seJzBbnSWvLrynKIuXJh/v1o/7oWjobZI14/qCemTRuAqBe7tRn5qCR5dMzfO6lZJxyonu465c7WgnkCV7Yd83Dlu/3sm3XdYnazM0gBLQElD7cShCterihh6weHTHNnQfIGkPpEDrWXnaknzkHejZ1AdNHyFIqkkKdrDr13YaKyii6sHFGhb1YV2JvHj/WPrpgoG07P8e2n9TZdpTl2M5Bu8/dfn5KYaTX15bWWHP+dNs0JWMrC+tjbyiiflpVXG+PFVSnADAtadlVqkMIC0II40IIVSGEP4QswOsVQvhyCGFrwj1/DCFcvodnXhLa5hXar/PiB/gSsFHRMLleylihBd4rZoMMSlJIRb/XT5sZheE2VFTaM5XTsxtF5uXb5rNGZMHg/bmtR87selPJ1qu72odLB9u/Kofb5sOH2If79402lXzc60uxN5asLqmzzQMG2c4Q7OPuufbWwKH20mHjbcOkUltT0nogMA0BwSFBl4y3D3/L4Eh5c9zYXxoTAhMCFzJLNDKeaZVBIrCQ9y4AwZxAMrJqA9kssU0ypLqGIT2GRf1uYX0nJS9QQfDGa/VbmyokJwTRnlmmDJExogHUNRsqKmMGn86K6tCRNgRhBKJkhTV2BFoaK4INAgRvsBma5jM1X5JZz7BJNuhIkHHimqQcqr8Cp2S21V62lWF9Mox+3DQ2PKuT80S2inPGdcVnSxcIIPGsT80fHRYyoHQICHD0nWSNTiudBIISfc+285me3dOYMvzPPlM/aH2xHs0hmX6ukaSIgndIGFbm2vDjpWvJDK4rq7ZNVeX2TOV0e7GuxF6qL7K3TzzSPr5ogLXc0yMbjbl94B4jLxaCfdqjh7174BB7ZnImJrtMc1Gd7J/6lQLAtKRl96V3COGDEMIp4T8HgIkM4GMFredPeQCTxCQxj0SGhAqQhko/SogWQ0Aww2cqjCLmZf20mfbCrEzrm0ku6WvbbszJHkitt5P8sq+13Jl9bd2n/6eP/b18jL0yaaI9O3Oabaoqj5Tcli5dExVXS6f97P0+/exvQw+150dPsbUFVZGSJxMjJkIAiSBNY0FGggBFfeTZd57N0f9JLJgHmp6xVP1NmdbQIplJjQGBqL7zAIXMGd9TK2PEPtCT9zuRPeD0LJj6KCZKRlVgRW0hOCLI0HdkcTzQlEH28khDTLaOYWr2Tbvk9Wz+rbEgw+XXgZ9HjbvqUh8JCsmqkaGnkecbZjR2fiPK6pI6Wz6pMRpTvo2BgF/MJZ+jMdZxStwEQGdFwFN9WVtaE3sVmAdoXjaTdIsPt5L99euGINLLkgdxyhsV0NY4PZE/P/bKOYIkpl0Q+LNt6rvGhU6J5pCATjLDZ7HNq4rrY28docOmtkknST5Zv/SnH6N1ZdX2TOV021BRmY2+zCyx9+cPsW213WzH1I62c3BH2zGvR+ubn27PsS2Xd7cd3TpGOnNHhw720Zd625sHDbcXR+fZ2oKqNukG0o9sA+eNO+lXFqWvgktLWvZW1oUQvh/+8xCwL7khBPvZ+PiuTnr9Utb6zHu39IKfnjon9r5UAgPvOT89dU4ECukNJyU/07iuK6uODqT++KIB2STjn3ZtzR18aGA2dHxrjm25rKd9eMFge/P4sfZS7VT710EH2ic9c21n2PNutFcPGROFlJoytbayoN5+n18bMyQEeTTozOvS9z6URmBAA+TfzekZLR7F4g0ngYcMldrrz5zjHKu93kiTvaD3zrAVjTXZUBocMrD6TXDFfquvAp3MhaRcPJk/z5ZPaoyMLFlQ3kfjTODHkC4NKcGV8rJouD0D540+mRwCF7HbzEf0zBhz/Dh2fpzF7pEJJkOk/us+v2uc88G5lhyqX2TWWJ8MNp0VAUfNPVk3gg6OIYE655mOBYEUz24U0PE5mbxXc6uUFfaLrDHlhGuTebAE21xb/tnUGQSx3lljFIVyTVmkIyDgTuaMqTTqD0O8qk/RFb3V6dmqMntjxlH278KhtnViD9sxrIPt7NxWB+44tIN9eklfe2Nhnr1UX2QbZ1TYPw49zN44ZJQ9P6HAVhfGWUSy/QLTPOyeYN6DV81XugkkLWnZfekZQvh3COGc0LoJZB6+HxX+LzaB0PgwZ4RK0V/jGSXvwRNQaKErZEilT6bFsyQyWCsKG6y5vMo2VFRGnm1zeZU9O3OavdIwNfu6ugsGZ/MH7+qe3VXM9xf/tKttvbarvb90mP1t3nj7a8E4e3vkIfZB/362LSe+S+3ZCYWRsVyTmWXPjCmynSHYJ9172lv9D7KXh4+1/z2q0JoKW5W9T+Ani0dDT8MnhoWf02AQwHkAThZAxkHjTkNK40bDQ5CS9FtG0LPBZNU8i8g3GZDRILAiY5p0jcZRjocAAM9888DBA96kH7JhHtB5YCswR+POtymoPg8INYcEC2Rek0KDZOE4/5QXOgO6nuvHt4OsnOZN7VW7eL4fWS2y2GT8dA1lk6yhd148M8a1LR1A8ELgSyaR80u5Vr0aG7GYlCWCQYbxedgxdZbGQnJHnab+qn6uSUY1kp6r8X50cmNsTVM/alwIPCmrkk3mQfqcSOVV61nry6psY0U2rPvGwjzbckUP2zGr415DuTs7drCP9+8dbdJQTiDnnbnCBMpqL8P1TJFQO2U/uOZSAJiWtLSWK0MIpSGEg0MIhSGEJ0II74YQ+u/6/qaQZfymhewxMH/Y9fN5Sm4IwR6aFA+/0OglgQN6dQR39NhXFDbEFB7ZJIVR6d3T62dyOY0DmYekNgksyrgpn/CFWRn729ET7f1lQ23bTTmteS06m/BX+1vLFTnWcnIn21bYxf55wuH22vwptqmq3JrLq+y1g4/czUaTLCj854Ah9vqII2zj2OKoDT406EN/ZEHINpExlOFjAnzSmwgImgmiGKLSWDVlaqOdu3quD2fROKtehqsIrGj4VKfAI/tI46h6xNzpXsmIcr/YJ4JX3a9QHj8j20UGRmyNni1AR/AmkEHwpGfpO78JRkDVM2BqM3OzvAyo32oHgQDZPIIEzjsdAj1fY0Sj7Nlo9kvXEGB5Ru3xKQsiWfRv/aAeULhS402ngfUSSGj8NCf+XvWH9VAvEPRpvPQ9N1aRqfb5pJ7Jllx79k5A3a8nOSNeL3pmW/1VmgudOY45Hat1ZdW2cUZFNL46DktvYnqxriT7es5TRtqnZ/a2luM72Y7Z3WzHuBzb2aODtdzUN+sA39HFPjx/iL03bUgbPfZZt+62ecAge+Oww+2lyZPtD0Xx8ww1hlrfJAbIquparn3JDdeiIj+aQ41fGgJOS1pay30huwN4awjh77v+H4HvdRD0v0N2t/AvQ/aswM9TckMI9vjU1uM7+J5MGSjuHNOCZ+4fjTBZIn1OZUsjS8/eK1fmY4kVkKftQ9Q+b4pKi2whGcM3jx9rH54/xLZc0SMLCh/oZy2PDc2eYaUw8s059tHXBtpHmQG2pXd327mbHcf6+ahbbgQeNH6bJhTbn/LLbcP0GTHlSYDCxHqCabKKAmYeoLH/XlF7RsfPheqkEWSIjUDFs0lkAJi3SUaHYM+zkAw56nMm0dPAeLDDZ9P4+HoZEuOuT8+Eqm9ktBlS1rxwHDzz5wELGUL1V+30B2R7hkT3UV7EDnnGimCEYIhMnWRGY+KZLj3Pn7/I3EmG+zgvdFzYFg8QmZ+2trQmApVkhTS+q4rr2+gcAjGCU7UxCXDIiZScE6xQFvm5wJgPTSs/0ANpjZv6QN3DdA2CVI2Brtf86zOGt6W3eAzL6wvy7L3ZQ2174362o6yj7Ry1X5u3akQ6acYAe71xkr0wK2PryqrtueJie6/fAPv78MPsxXGTbN3UGbaquD6qR2Mr/UtnkswknXbqCDodXscQJNJ5UtrQQ5PqUgCYlrS0Y4kOgiaw0iJmvo/3emWYCCCkSMTOePbPKwYpWbIGNP56vy4Nr4yY6iBI1N9kMpSXQsDVlKmNwOAzldPt+ZpS++fJR9pHFw6yLVf0yB5QrSNotOv4/lxruTnHtp2bY1uqetpHw/e3z3J7xEDh5oGDIrAphf5ptx7ZjSb7dbYPeu9vbx14sL06cpw9O7HQmksqY4BM4MAbUI2XB2NUpJwjJbITOMmoal5leD2Y9GycmD+2j2wJjStBkOaV7SYYJJunHDmyYJ7hY1s4ZuofHRjVQ/bSj6PGTdcmve1GfZQMSl5p1AludQ0PpPbhTbJf+s3PJd8e1KkOsY2SE4I7ARXOOZ8jIEvD7Ne1+qu+CgyT/SXI1bM1Dn69Uj94QKz+eKDAXeViznxYluMmedTcCMDpGgJuMp3SEWTspZd0ADX7w5w9PeOJ/Pn2o6qz7Mo5y+zmmjPsD5la+11Rg91ee5pdNWep3VF3qv2+pPV+1qO59ucHri2tyb5CrarM3ph5lL1/9EH26bf6ZDe/3dPDWh7obzt77NkZtRBsa5cu9tcjRsdCrXQOCdzJQq8san31nNopXaH7NDayBZ4pf3zKggjke9baM9mS2V9MnJMCwLSkpR1LbgjBHpkyK6Z4ydRxJ5+MAXcj0oiIcZNyJYggi+IVd3N5VRtPkkCUeSL02gUY+bYAKnfP2BAA0ONWaEVnXz1fU2p/mZdv75x6uG25rKe13L7rGJoHB2TB4IMDorzCbVd3ti1n9LRPyvvau9NH2It1JbahotI2VZXbhtLpsbeWJIWQP+3Wwzb3G2ibJhS3AbgcQ429D02SGSTLQlZF/ScL68M03G2o395oy2OXnMiIe/ZR12l8Gfbj/NOwktVh2JxjorYQGPhwntrPnEj1TbKk63jOmupmGJ5glQye2sgQH48l8X3jb/XdgwsCVDK/BIkEYTzzTmNNJpkbThjO9A4dx0vGXWPkz7cTUPfOiJ6h6+V0yYHj2qd8EHSzzRoLfyzQ8kmNsXxI9c+HpL0e4Phr7Ll+mjK1sXf2riyebTfXnGFXzllmt9UustWZOvtDptZ+NPNMu2rOUrtuxhL7bcE8u2HO2TZh2X027MLfRD+jz/uZjT7vZ7HPJiy7z65rWGJNmdqYgyigV8cmAAAgAElEQVS9s7Fiuv15WqG9VTLKPsgfaFvH9rAdQzvazq67NmQc1SX7TvWHB2f10E+72o5D47l8W7p1tfcGZJm9l8dNtPUFFZHcan65frTRik6GZMe/CUQglYw3nUQ6gx4I+jxyXe8P7n4yf549kDc7BYBpSUs7ltyw6xgYAiwpXylnGjoqbi1k5sD4/DUaSP1m+MQbLIIOgU+Gi/W9jAtDxWRtGCIiSyEFRwPAMIdybGSI9TLzVxqm2tsnjbYPzx+Sfe2R8ggfGtjKFD7Qz1ru6WGfXZprH31toP37xEPs/cMH2sf9e7fZaOJ/nhtfELVlXVm1vZCXb+/2G2yvHzTKnhs52TZMLLX1mco2uwx9fpR+ZKwJ3mj0NS8yoLqGrBjPkdO1TD7X+Puwlg8Z0VB4VpPOBeVI863vvWNBAy+nRECP/RHQ8wygwCPD3b7dZHr0m+CVYFDyx9C52k6HiQygrmFd+p55bJJlgnHNLxljz/p5YMXzIFWHxpusI+eEc++dKH3O9iu3kvPIvj5VMDdiqMn4cc1yjqlPKM/cFETQmeSYqm4yT5Q9Aumr6pe2AXVHJoC60ef9zIZ99aHsDz7f02c3zjvLNlRURqcYvFsywrYN7rrXd+Tu7BHs00t62+azRtgbC/Ps5dmF9tqYsfbXww63P0+YYuuLZkTRDu6MliyJ3dNa1xjRQeRYS66pZ+ggUd4pJ2T9JW8MadO5le5gyDk9BzAtaWnfEm0CYZ6Ndulp0cuAkmUhc0OQsaq4Pjqigwvdsx4K6zAEJIUgg8nrqZR8KCcpTC2FxKMaCBxosMkY8W8xmvTcN86oiA5M/dvRE+29JcOzZxPekGMtd3ZpfbexjqT5Zd8sU3hjjn109gH276qh9t6EA+2DgwbYp7k9bUfHrCf/p5LptiYzyzbOyHruLx88NvHtJp91627v9hlofx18mL102HjbNL4opuCZD5gE+qjwNa/eYJBh8YBK47qiMJsX5nctkk3T38yn8wywGCoCdc/kKJ1ADgfzG5nT5tk4yYaAHmWXoNQzbTSkfiOHgBeZ1SS2TuuHyf1+nZC5IsNJdoWgjSwuGS0yeH7utOmFoXy+a5cg1reJIFxzI+BFh4pAkwwir+H8E5BzTHQv2WAP+jk+3FjCNAD18Q+ZWru99jT7fv1X7LbaRfa7oqwu+n1Jvf24Osvm3V57mq3OZNtwRd2yzw3qYp/t+jn0/F9Z+Sk32aI5F9llpSfYz8ZMtz8NGmXzTr7CPrm8p7XckdUT28/P3SPw296zs304YH97e/jB1lw2I3oXL2WFrDLBvcaHAJ06j/Pk16zWuOaeebtiDvV8z5bTGZcMKbeQDjoJBf1ON4GkJS3tWyIGkF6cQjZU1N5zZ4iQzJzPAaMB8/lMUtYCEz5M6M+DI2MiQ6DEbDJjygXz51Tp2f68LYYsxCLpOrVTYKe5vKpN2ISvDxOY2jijImIOX2+cZO+eNiobTr55Vx7PL/tmgeIjB1nLLf1aQ8o35mQ3pkxIPrTa/3zcM7cNc/XnURPtxSMm2sYJGVtXVNkm34yGQX3V/HiDIcUvha6502+OpWch/WYHggGxAgyNCliQfVa9PILFsz+aN9ZNkMNQoBhryY3CYbrfOzpkvCSTq4rr7dHJjW0MrO+fDCBf7UfDzXmRDHs2ltdyrXhHjPMi+aTB9a9n4w+ZG7ZHa53OFw0+ga/GlyCTAEVjIQDvQ7ePTm6MrbmkY1V0ZqUcstUldfb7knq7rXaR/WDOMvvRzDPtyalZZyKJyZu47D5bctx32nw+Ydl9tvi/vmPDv/rrREC3p5+Dv/pru3jGGXZ7Xr09dUievdZ7kG3vkHzUyqKGi+yJc6fbP08+0l6qL7LXSieahWDbcrrYB332t3cOGmp/GTnWnh1faM3FFZF+Y/qBxk4y5dcf5YvjJ53uN17pt/KDCSKlK8TaKVROh9uH3yVn1Nuae65BMr/SE7/Ka0gBYFrS0o4l2gUstkwL2jM1+t1cXhXLKZJyoVHyzAFZAilu5e0xRMTwBI0G30ZBQ6r6yG6QVUgywDLiZPto6PUuTLZlXVl17B3IAkvMIaPB1xhIeW+cURE7kuaFWRn7x7Hj7f2lw+yTi/vHQeFDA7P5Pg8daC3X9rLty7rY9jmdbHteR9sxqJPt3C8eLnpv4ICInVRO0Wfduseu2ZaTYx/k9rF3Bhxofzv4MHv1iKPs2fGF0XuR1X4peip4hgYJ6jkOZNs8W0WWze8c98aG4IXMMFkyOgAETZJJDxoE0pgfKXkhyBRg1fzRuEmW/LEzZKHZT4FLn05BFlDPZdhafWQbyOppHfBz/+PDy2qDNqb4VAmOvwftfBPIUwVzY6CaLI8P23INk3minuA8CRj6kCPliJsn5GRd17AkEeSdfex398za7SObN/K8X1j5KTfZifO/ad+cvsjuyKuzi2ec0ea6zd32zOTp55Lpp9n1C8+KQNuG8gr7U1FFbC1xJzF1idYk1xzn2wMu6iOus/XTZsZyRakvCfa1dijbdHC5RrRWJSN6ttom4JlEGGiu013AaUlL+5fcELLvAhbl7w2LGBcfiqFH55ke7iDU5zK6DBuSdZCSodGUcVco7vEpC2K7HLkrk0ZIBoOvm2K/lP+V1Jfm8qo2zAjZpjWZWdH5hh4gkxlkIr88eY2VFPGGikrbOKPCNlWVR2cVvnPq4fbR1wZm2cI7u2R3I/+8d+uZhQ8NspZb97ft53e27Qs72baTc+zTb/Wx95cOs7dPGm0v1xXs9bga/bx2+JjIGDWXV9n6ggp7ZfgYe3n0RHtmYok1Fcy0ppJWZtPny2lM+Jo/ghsyqWL8COIFqDU2MmK8VwCOTIOu03eUJwJVD1C125IglSDEhxb5yjSmQZAR5VtFBCCZj6Z2JL1Bw7OC+s3Efc9+M1XDO0LqN8EUZZFAy4N5zcXuHEACbRl7gj/1a2XRbHty6lz7Sd0pduWcZfbj6jPtd0XxN9vwkG2OCedLz7ml5vQohMvdtNfUn/P5QF70k/z5/GMus2sLj7ZfjJ5mfzzwSHurZ9/ENbNq2Lg29zYPHtV67EpON9t0wAh78IiMXVN0jC2pu8BqTrzODj/35zbswt/YbbWLInnyLKvPg5aupONDVp7rkHLL0xT4BhbqTc8oUv+KDKBcqS6+iUbyRP0vp/jpqa0HPRMY6m/aCLGKaQg4LWlp3xILAXPha5FrsdLr50GtNCDcWcYcEhoWeocEh1ImzOMhc6iQtPLd2Ba+y1T38xBrGkUf/uD/zC/jtZ7h8J4zQ82enWEoToqc4TMpYOX3KP9MieKvzZ9if//yBPv34kPsk2/0s63Xds0eU3N/buth1suHtB5Xc08v237mfra9tpO1jM+x7UM6245unRKN2YsTJkcn/K8trbGXjsprc01Lp/3skx69bHOfA+ytQcPsb8NH2guHTbRVRXUxo8D+CwhpLAUQCX58WFHjyXA2WTsyEh6IsW7JF4G7dzwIbvwbHZTnRNaFITgmsesZZCr966/UR7JxDI9y/gl8yfawLWQa+UYdtomGXs/RMynLMvyUWbKHZGQ1x34nuhy0dWXV1lxelcjKTVh2n11ZtywCEyuLZtvvihrs5poz7Ko5S+3O+lNsdaZ1TTxVMNeumX2OTUx4znUNS2x1pi5bx25BXhYITlhyt9WccK2dOvdiu3jGGXZT/jz79eEltn7w4TbqvJ/Hrr+66Mv75DT9LXdAm7oWHvM9W3jM92zyWf+9+zZ99SGbsOw+W1nc6iiRFedmH8kYoyoEaZxvOrCMbtCBJXvKlAsCbubZEsRpjgn65EwRWPJ6z9JzLUqGmA4kpz7dBJKWtLRviQAgvXgycfTU/GYLgjwaaAExD5DIktGI0KiSjZMxIKDkhgeGEgjMpNCo+KiY6PU+OrmxDRCVgWRYhcrOAxKyV2wLmRqNHdtCg01WSQwSAaEOam0ur7LnqsvsjYV59s6ph9sH5+06I+y6LnFg+NDAVmD48GBr+Wkva7m0q20/Yz9rmZVjLZNy7MPTB9s/jh1vr82fkg1Ljx65T0Zwe8dOtrq4Npbc/dfhh9t7+/e3twcNtTeGjbRXR461F8dOsk0TS2xDYbmtKYmDZLJwa8pq7Jaa0+2quefYLTWn28ri+OvMGAZcV1Ztj+UvsDvqTrVr5i2xW2pOt98VtZ79RoNJoMXQqGfCPItLB4HzSKBPkMa5p+xKXtUmybNfD5SpJ/PnRePKHEGCJwEuMo809LpGgM6DUYIBrkf9bsrU2upMnd1Wu8iunLPMbqldFOXZ3VxzRjTeqkvPuGb2nlm5K2adZ2sys+y6hiU2cdm9bcDd9Q2LbW1pjd0476w9Pueixgsts+gWm7j4rtj3U8+8w9YMGW2v9x5oWzrtt0cZnnbqj2P3nldzbuz7d7r3tubBo+yBI0rt+qkL7fzqpbbgy5dlQd7n3Ryy67PrGpa0CW9TXnn4tcLvynvkjm06p5I/PYPsLM9TpPxKzy2f1BhjwL3j4qM+0ru8jiy6l2kx9JJdbxdWFDbE8rzTV8GlJS3tW6J3AfMNFDR88tbEwtFY0sukQZXxZYhDRldMHkGYvE8fOmZYjs+U0qThI4jzoRQqqth5X0Wt+VlJCo/KWffoOild316ODXPOaJxpjFmP2kk2SiyYdp8KHBIQ6lDr52tK7ZWGqfbWCWNs81kj7JOL+2c3lNyQ0xpKfnBAazh5+ZDWMw3v6m4t3+tsLcd1spaKHNs2rqttHdzdWnrm2M6O8ZDyZ9172MYZFdEbCtaW1tjm/Q/Yo8Hd0aGDbcnpaq8PGRkBkyfy59s19efYV2rPs6OPvtRmnPxDy1v8/9qkc+6xH849K/bmBTEjV9YtS2SYbphztq0uqYsYTT1/bWmN/a6oIQsw5yzNhuBKs/Py+5L6bIhx9nl20YKv21XzzrHbahfZyuK2oV6FJO+oO9UubzjPLm78ml3WcG50+G9TJpsgr/PjbqhabI/lL2gNXxfPtttqF9lVc8+xW2ctinaers7U2e21p9nls8/LgtniBrutdpFdM+8cu6nmDPvRrt2qN9ecYTfVnGFXNJxrt9eeFoFk7XTVQcRPTJ1nN9ecYd+tu8B+NDMbftXGpT9kau222kV2+ezz7Pba06yptJWJohNzzexz2oyxH+8fzj0rLrPFs7OM3R4YsInL7rXr5569R5B0w7yz7PR5X7cLqxbbD0qOszvy6uyhUcW2Zshoe7XPYPswp1skU5eWnRR7xvgld++TA2Mh2NFHXxq7N//MO+3E+d+0ipNvjMK1bdqX0N7Rjkkck3BkzMRl99oP554VrX06o0mOMfUN9VsSi0tGmCCerDd1MOujI632UPeRxZN+53qQ3ucZmGLL+Sy1n2kOzAfUc1IGMC1pad8SHQRN9oysB/NJCL64sKUgVhZld+oxHEdmToBJ15Jx4GHOBGxkGFm/lJqUGF9NtHxSY/R85s748ISAiHJXPKOhUOAT+fNjipQsFl8DJWVKRcxDiGlkCTj95gNdx/aS+dFzpeQFDPWZD8WofdoowtzDF+tK7LnqMnt1boG9fdJoe2/JcPvwgsH22Xd6ZxnFu7pbyz09reW23tZyRR/b/rU+tv3rfVuPutkFIHcesveXzFsItnnEgfZ8Taltqiq3G+edZcPPf8B2hDjA3BE62OZuvWxzz972YW4f+/f+B9i7gw60e6saY+Bh7NL7bOZJ11vBGXfYkUv/x66ffXY0HnIQkneD3mtnH/vdNiwUNxL8oHZZjKm9Yc7Zu71+wrL7bPFudpde17Bkt5sVzjz20jafH7yPO1EnLrvXlvzXt238Xu7PtmGxXVW/NJF1u2b2OTHZvK5hyV5y6MhoLY7yvG6vPS3+7CV3W8NxV9qJ879pS2u/YpdMP82uLTzG7h1fZQ8enrGVw8bbswMOsccPzW9t+4W/tglfv9vWDkl+97b/uW3S7Dbt2tKps73fpYe90G+YPT08z+4+qsquLD7WvlKzzI5Z+F0rO/XHNvIrv9w7wHNjeqQDehOWZmXk9yX12bd+7GKvn5w6135X1GA/qTslAu6/L2nVW9It0gn+dXzSd3I+mJIjnfb4lAUxnUjAxZMLpGe0/nnuHnW3nGumA6itZNUZtVG7VxW37oj3TLd0qpxs6n0yidKJv86rTwFgWtLSjiUCgFqkCp2SmqcHSeAlBcada1RMeoaYGC147qakt+nBH3OOxEBScRLkEChKEUr58aXwPry7smh27N2fDNGSlXyqYG7slUp65qri+qgu9t2Hxgl2n8ifHwsjMkxH4Mx2MpGfbIG/n9fwnDwpXR6nIiZRALK5vMo2VFRGh8pq1/JL9UX2t6Mn2pvHj7V3Txtln3yjn225rGc2H/H2Xecf3tXdWu7oYy1X72/bL+5j28/ubTuO6WU7qrrbjomdbefBnWxn7w62/bjO1nJnF9tyW1fLv+hOy1v8031mbU5aeEnMUC9quCier9iho23r3Nm2dOtmn/TqZW/0O9AeOzTf7j6qqo2xbzjuB7ao4Wt2XOO3bc6xP7CZJ11vmUW32KSzf2pjlt5nI77yK7u+YbE1l1ftfsOBD/vtaUPC59mRug8AcJ/v30sbDr7gQbul4VTbUFhufyyutInn3htdd8S5P7MldRfYhVWL7dvTTrGri75st0xusHvGVdpDo4rtD8PG2ad9etnWXl3tf46ZH3v2t8tP3ac5fb33wDZ9e2RkYeK1H+R0t1f6HmhNB42xR0YV2rk157a5d+R5v/jPxnwPn19Vv9RWZ+rs1lnZkPits7JnCko/KG/Oh9f9rnVuZvLpK0nOL3Ul36SyfFLrG1akl8imEdgx8kAGkPmj1F0+B1v30tn0+ady6pmqo77QIdMzGCLWGP164jHpJpC0pKWdS24IwZbn18S8OikB77Fp0QrcrS2tsYfzFsaUEcEXlR0Th/VcsmnyfnnGWxILxrPACEalfKlsCfjI+nmP1nvd3EQilo+v21IeF59DxcvzthT2JiDWfcpRezhvYSyMI9aQxoB99Ge6MaTic3TUZs0Lz/RKCgutycyKgUL91r3PVE6PhX/XT5uZPdNs/hR764Qx9u5po+yD8w6yTy7ub599p7dtvbJb6yHZCkM/0M9+/9OSiMX7zrST7ab8eXb/mAr77YjJtmHQSPvrlw6IhfuS8ra+OnPJPoGMd3r0bgMUfnVE6V7va+nYyd4edFAMFA278De24uAJtmbIaFs5bLz9dsRke2RkoT14eMZ+Pqbc7h1XaXeNn2k/mVhr1SdeHwMWBWf+xK4qPtZ+UHKcXZ453i7LHG/fLz3Rvld2ol1adlLsZ8T5D8Tae/TRl9o1RcfYtYVH2w8LFthN+fPslkkNdntevf33hFl291FVdv+YCrs8c3ybvv7iyDJ75oBD7c/9htprvQfZWz372ntde9pn+8XfTrNxwvjYfVPPvGOfwXnzdyfE7v1KzbK93rOtYyd7pe+Bbdp7wvxv2v9TtdhOnXuxNRx3pRWdflubTRvnH/ONPYK2xcd9p+0mkqXJrOv4XZ97NnXisnvtmvpzYqwWQ7jc3ESAxVAtdU9SuokPi2rNUg8LOPq0FjrP1CveSVYEIwl4ModPOllt8HnNzAUnOCXI1edsD3Ww9KN0qq57In9++i7gtKSlnUtuCMEeyGtNMmZoUwuZ53+RjSPTxTw3enh+y7+U2JP582KKic/y4ETM3PJJjTFAxUR2n2jMeqRE/TtsqfxWl9RFzBfBlDx7KVL1iUCRYVwyeEkhcIE3rxg9Q0cF771xzY/AHg0K2UE/JwJyNBpkFgXy1FaNGdlUXcP8Q4Wf15bWRAziM5XTo3ciPztzmj07c5q9Nn+KvTZ/iv3j2PH232d8eZ+Yrgd+WGktd/Sx336r1A49/1ex7xqP+b7dM67SHh5ZaKuGjbNNB4ywj/p1s529OtgO5C2+2mdwm+c+fuiUfQI2zxx+ZJt7P+ncZZ/uXdRwUey++V++bJ8BlQc8N0xt3Kf71hw0pk17//eAEft073OzR8buG7v0vn26b2fXYFsvyrH8i+60gy/MhqBrTrjW7sirs6uLvmzfqDjdls46z86ce6HV/9dVVrLoVhuz7H92y3aOPff+veYSNpXOSnwX78Rl99pV9Uuzjk/hnGhzkfIu12RmWVPpLLutdpFd0XCu3TqrNedzdabOflx9ZmyzC1k8rRHmPvr0FG6gYLjUh3K9TtV69TqJTjGdSl4nvSc9518fyF3t1Cl81SbzAuXck/ljdIiMIXeFM9zLaAYjR4yI0PleVVyfbgJJS1rauUQhYIYxmKOmhauwJUEWlY/+lsKTwiKTJkBG1o+gUAqNf1M5Smkx5ODzBVUHPU4qZPaRuXdUzgxPEKDy1XX6m16+2krl7hWj7vXeOzfNMITOXcg0PgJknB8p7EcnN8aOWlDImhtvCKDJ/vm50edJYSSBZm5O0W89q7m8Knqtmv5eP22m3Vl/yj4BwAdPmGdvHj/Wlp8xa5+u//2PJ1nLPT3slzdX26jzfm6Tz/pvKzrj9jbXnTr3Yvt+6Yl23dSFduuk2Xb3UVX2qyNL7bHDCmzFwRPsjwceaZsOGGGPzSpsc2/Lbt704H9Omft/YvctPOZ7/zEAvG7qwn1j4gaPatPe5sGjrKVDR/u4c1fb3C3X/tGrn73aZ7A93/9g+9OgUbZ66Dh7a2x/e+Hk4bH7DrngQftW+Wl2wcxz7Oz6r9oJ879p84693KpOusGKzrjdxi69z355zAJ7rrrMnqsus1uPPnXP78JdcHobNtVfN2HpfXt9Jdt1DYsjuf1DptbuqDs1u1t51w5ypjbQeZFM0kFlGgoZK64zv4lBz/VMnGfjk1IvksKraot0I3UD9bFYSDqXag/rJ0vH6+iw8nPP1D06uTGW98yoA3UF6+NB7NSLqochY+oasooP5M1OAWBa0tKOJfYuYO/daSELiMhbIxBkSFXA5umpc6LjVeTFMkQgVpAMFMPO9KIZGqEHTobLK07VzfwVr+jkKVMRKuTJk+0FzngdQxnMV2SIhR48Aa6YROYY8vxEAVm1kePrc2x4HdsjYEZWU0BNdfGVYNwsQybCMxl8S8WKwoZYCMznJNJIrC2tiXIMI5C5t7PcdjE96yt2sYwVVXsFD3nn3mPP12Xs1bkF9otjF+4TYNzbz80/mJNY12Ff+ZWNXna/TVhyt+WfeacVnX6bTTv1xzbj5B9azYnXWd3xV9vYpXF26qhz7rET5n/TTpr3DTt17sV22pyv26I5F9mihuzP6Q1fs9MbvmaLGi6yQy54MHZv2Wk32/ELvmXHNX7bjln4XWs85vs279jLreG4K23WCdda1Uk3WPkpN1nBmT9p09592VhyX+Ox9kJ9seXtaYx3Mz9if9dPm5m4WWbisnvtmtnnRG/v2BO4u2b2ObaquH43G2ey7J6AEAGUZFVrVyFXnTCg9cYc2RWFDfZw3sJoDch507pKevOMdI0cTepNAh7Kvxg15sORMdT1Anc8Yoe65Mn8edFmOTJqdNoYEVEf1Mak/vu3P6lfSrWhTeDmDeYWqi3SxZ5p5PjQZjB3PH0XcFrS0v4lYgC1SPVOToYhmTQsZfD4lAX2cN7CWG4Jwww8yuCJ/Pn26OTG2O613QEzKkGGOwgaqfik2AgSGUbmBhD2he3TcSP+YGHv0fM3wSyVIF8zR2aS9TPvhwe3MgxORlPjoWd6pU0GgSwBx4nKWAbG10dWkCyCxlMso4wKwTDHSbLgWRfWs6q4fq/nxl1Tf07sLR83zNnzESLXNSxpTTwvq9krwNwbwMk7915rKq/eM/Dc2/P2tnnk/wagft4NI7sFcq0HFF9Vv3SfdwELjPHVd2tLa+zJqXPt5poz7PLZ59lttdnQq9IkmjK1icfMTFh6n11Tf05sbT2RP99+XH2mXTlnmd1ee5r9rih+Dp1knEdQeadIeuWJ/PkRIKTOWVta0+a1g3zVGVk/z9DTSSLbrsPEubGMeotOsI+SEDwlhU89k0eWkNEKXs++ySllpILOuQ8HS8fyeQR+K4uyedlkSjk/fJbAK9uuXMCVRbPtN5NrUwCYlrS0Y4leBeeVD5WIZ6mkPJKYPG7SYH4Lwx/yJulF09MlkKSXv3xSY8xDVxuoTBmmYOiawFMgwYMktZNeNe9RnfSG2VYaJbVDY0cjQVClz3yonEqf+TRUsFLkag/zFTVP3HXH3XgCwrr+8SkL2jAEBMC6h8yl+kgjydQAP++6h3N1Zd2yxDc+XFN/TiQbYpfWltbYNfVtwcPEZffa9Q2Lo/o0tz+o3XMocW+g7ar6pVnA8v/jXcDqJ3NB93oO4NLsmz0IJpJklI6PziLUOtK5iHxdnOSMYIvAhWy0T8egXK8samXzuXP//2Pv3ePtrKp771HbtxYPxlpqc9K8IRfuWK0aEiDE0Pa0VZSreOnpOacGciObEGLLiUDARjnRSASJlKtIsa1UsBbFACYBuSTc7DHZO7Ht25qQvRPube3p5fT04nG+fzzr+6zvGlnBRJuNyhyfz/rsvZ71PPMy5mX85m+MOZ8camIAx5hx38+bHlhQegFnYOQx73sMDhknOazCQDG7fe1hMIPosBDmOgAui/kMLB+c0RyTxVFZlIFFIfk63g/9oWMzd7CI+eB968Rz3v3Hn9ECRpftwRmn1xjAKlVGWdo3gZjm96SezwE0KAJwAJYAdP3cAxy1sm76u3rADqCKSa/fCp9Vo4EW/9uV6dUwLB9glYmK35iA7CYyyMFt+uisk3ve/btu+rvalSx1hF3IcT2eIJlEcTlxv13cZhAJHKecTLA2EujbYNDg3SymQbONHf8bDBpAe1Vv9xr6sOsrG7Aegy+d2CA8dMJp7UHNHztjSbnp5OaIDeqR32t737FntsH6Hz3tN8vNp8wtD8/qvnXDwHPjzFP7AsY3nv/ZsuA/f3iPIOeN5zdvpQC0P6V7LQoAACAASURBVH7i214QFHEm355egdbv2Tct+cNyzn/+3s4B7LfTdXJ6/k1LPluuOXOgrD590R7OKVzU037Evd4/44zyybc3B1ffdMrc8smT55ePnPpb7aYJ+iz90kwRbJ8XCTncwgsXu1EdZsK9PkvTbk76mIGiY2H9jPudvRReLAEq0YU9BQ73YDx5bPAdPdw19T09C148DdzjhaPLz5xm9tCLcb5nVs66sAeH8jBHWQ9m8vvFBjL+mH+z1yEv/AxcvVnPQNYemsyoVhdwlSqjKy0D6Jg+D3ivInl1kNkpAyqDQJ5h4jTr42e9GjSA4jkMMBM6bBCThkGMJzZPYtlw5Bes500jBlDEzQHI7G725GlACfPgSdz327Vk0GY3ega7NnCZxTCLaEBJuTwZewVvZpD0vvZLb2nLaHbBcVfo2zsEDb5hI61HdMA1fidO0cA/9zEMhtvNBsz9gr5mt/pDM08rnzp5Xrn89PeVm0+ZWza8uRPf1TnbbeXp7ysXnrmsfOwd55dPnTyv3D+jC0LQ54MzTi8b3nxqA4rOXFwueuey8pHTfrNlrx5+8yntmzbYkPDwrC5QfnjWKe3r6z759vnlvuPf0brVbzl1TrniHYvLp06eVx5882ktuL3plLlteteetLBc/7YFrVt1w5s7LvwZZ5Rr3zJQLj/9feXGty0oGzvgmDeGsPP1sVlvLw+ccHq5+ZS55SOn/la54W3nlIdmdmOyYMy8OHDbeXzYgLttDYgcTmF20cwd/f1//uJbew4pdt+kfd0O66a/qyfUIvcpAxH+5nc+e14AoJr9MzAzu5k3SfkolH7zifu5y8ruevd37slndbo9aAv6fo6Zdnk9P3CvXa8G3/YWeF7zfR6TzAukZ7CXfzPzmnc/e+FeD4KuUmV0pT0H0JOQV39+Fy8Tfp6cefuH3Qc20n7frp/DANqF43deAiwxYH/yCye1bKIn+cwo+dkMKOxKyaCTe8yccb+NB/d4xc2EaYbDO3FdPiZoJnuDuBxzwwTtHcAGseiGe4lpyrGRrgs7dQ3E7dIB+HuVDqDNBikbP+vXDAOsZmYAaXueNfNM/bjX57A5jsnnStq1R3/ysUFuQzMzXiRkVptyudz8Znbc7k8vPsxIuq3cruSXwyScBvcbRPiIEPd/DHo22jk+lPGXmWg/kxk764N7cx/z//kYk7x4c/wqbeh+ke/PoM8xqz7CxOybmTP36dymHotuc9fB86AXdgY6jLHcl2BMc3/NbxqyCzbX3X3L858Xj461QzcGtQ4XoQ08/7j/0S8dTuL5gv+JH7de0BVjLuuTsj044/QKAKtUGWVpXcDevZWPEGGAm6Hy6tZHBPj5e455dzu5G3DwjI1dngzstvSK0/F+66a/q/3dO+d87hXPmSUzgPGK35Omj3kgn8xg2rjY8BlsZkOJPlw+JnwzqDk/9GGjZKBogMEknsFGdhNj8Kxngy3n43xtgLLrz8bZiwCDFevd/cIGzqyUDarblLIYBOc62Ri5LYiBoizui3dNfU8Ps2MgTX0oK+1nwGDW12yZrzmd3A+zq9T14zmDHLM0PmAXHeQDe3nGRtztaj05DszgIzNe6NfnSPZjvqwj4umoo5lEt10/kEY/uueYd/f0d8pvgO1+649Zs8dmvb3nTUPeRW/QyxzhNnVa6Mnj2x+DaNhQM4Hu07QnsX1++5AXYK4Pz5qZN4tr5tJzsMG5gaP7tsGl5xcvLLzwNtgEcHvxgg5Ip74LuEqV0ZX2GJgM7JjENv/yr7aTso0KhgjjwqrRDENm0GxAnJ9XrN7JalDIZGlD5AnLk4/zycaESdin7fcz8l+e9u6eiZ9PZrGyAc2MpifXzC6Qn1fWpGGdG9iiI4ME2oDfmXRhSpl0MYguA/GPBh6AL+8SRM828gY3BhVmkuw+MsCDDQGsU376AboCDPO332YZ9ycbWtJw3KmBqoGJDaHLaRDvtDOzkl1bG2c2cXDehW6gk5loNuGYFTWQMkim3nlx4LFpQOx+CEvMIsfG2osZp2Owk/uqmTWDePTn8y+JLzRQIw/6AXpzOc1Gu27ohT7suSQvBuhX2SXrvtoPDNPWXgQDCplDCMtgEc01HxlDPvaocG8GR4wbgzL3V0BdZmq9oY5+YsDtscOHOYF0iD/0ovHL0969mx684GQeMatsANiPScejQB9Zf+w76yaQKlVGWVoA6AmkHwCxWwaDml2cZvuYBAwAPfF4Fetz95jsvImDSd/AjvQMOkgzsxc8799s1OzGywAoT6w2lugEA+4Vthk76mgDkQ1OLj/3GPD1e6+vQZHdPAZHBrkZxKHXDNQNjqhbZtRsnAyc3G70ibx4MBtsI+32sT4xePSrzDL6TSzWoYFyrlsGsLmv5P7mBUhmRM3C8bs3FThPAxh0ZAYLQ9wvfMBlNXtlUGDdAbqoN4yT+4DHoBkzQJjDClxngw0vjAygHTOXd96b/fSihHFlNonn6Pf94nZ9zX9dVuYE91XGGW1B+xnM8qx160Wc0zNQzcDNcxVtR/sDKA1SmVus+7zwATQzDrxgtQ76tTd/WTy6rpSbseWQHMf8MS7WTX/XbpvSmJ+oL54As62kW4+BqVJldKXnGBi7jxicAD1P9tlg+pVxDPy7pr6nB0RiAJjszPwwcTKxeAch+fi1cV7xZtbRriEmMMqfmUyDJiZrGxFiGw2kmAgNgvw/9c9vEXF5M0DxCtmTfHYBZxdjBox+Lhthu5lcBht+u85s6O2myWCe2EyMl13xXgCw+9ntahBGeW1U7bamf/G/gafLwwIFVsWsgw2cFyJc4+Mdq2Z+0JUNu0FrLot3bruvZYYKfdFvOC/TAMX1tkF3WxvcUx4fPkwa/O54R7v06OsGtZmxBxAaFGe2z6EMeax7YxU6oN2oC32WecX6MjPpcZBBqMEUYMULSINH9/uNM0/tmXN8YD3P0KcNZPfEjjpPj6N+HhL3V7OreY6zPiifmTjKm+dS99u8yOH1jmaD82IVt7RtAmVhkZmPoMkLYrN//K0AsEqV0ZUxEVE+/6be9+faNWj3K5MN7oTscvPkY9bMbi0mljxx4wIjTbuUSINnXQ4bNw6btuFj8rELOU9cmU3ijRU2ajaqTGZM0A5wNtPhlT915l3DZh2zW7ufa9yGCYPktxz0i9m0kTTz4LwyS+LrGaxlg+DNOBkw2oXP8ReuMzr3AsFloP/Qz8wqEpPJJg/3O8co0Sf6GWe3S64/wKEfE5PvMZNhHRu4mUXyvb4f1t1sC/2YshosoXfrz2PFfTWHDNC2bk8DYwNz9z/aNYNvA2YWOu7zZpMMOuij1M9ssZl1exbM4Jn9dlykN1pkoOWQBwMzf3LMpRl3ALP7gXXmuppJZjyYIbz/+DPaDUg+aor+QHm9wPAcxnV055MHPAcYRHq+9fNuE//v0xhY7GUgal1kgM6i3qcCmBWnn99//BkVAFapMsrS8yq4HPNlQPCV497RBsd/5bh39Bh1T1JeXeZVOel7hZsNERMjE4sZDk/QnuR8rIndP9nVlpkjT/B5Ze5J2vE4rpONEmk6X+43GDJIMRBC/3a1MKHasJipMHh8dNbJPYfU2g1PHgYNNuBMymZDzeZgIMyomnVAXwbw1r0Bbe4PZjC8K5NnMbo2TPQBMx1mpShjDkgnDccfUVa7o1xOjF8+UNvgMbO0Zh3RjQ2tFx02lu7bZhypE+MA8E+fgflzv3Rfpb298KEO+U00/YAybL1ZWgNLM5VeAFkv/u5+aNYyu1c9vrwA5X4fCeU8vQgwYHxwRu8uXNfVYN0slfu362Ewa1aVtL07nX5usO77clkyY2evCwxbZuYoE25Yb/zxook+5s0nnnc9P7m+tLfjkPPCwkyvwSy/m8n3fEY+FQBWqTK60rqAbTSy0bR7MBsWAxgbIAwphsaTpo1rji/yJIyhwmBj9DwxYSg8+TCBZmMG0DEYsVsjA0gbdSZtGASzmXnl6wndrAnXDYBxszER+gwws2Q863d02ljm/N1eBqnegeiVvgGSwYHblbJk8GO9UG6zdORvlxTPZNBs/WFwKKuBE4bMBpY277dRIbtBzQphiNh8YLbTjA/X+zFuZq8ysDAAdnu6/Bh2M4X0VVhM2gtdog/6jduXeuX+Qbkw3mZcsxGnjLnuboNHZ53cs0Pbv1Mnt+fGmd2YMjO7lNN9Oi+UeNag1vFlsJEe02aDrQMvEDKLlevsmEMvlr5TexuIEZLifuxxZze8y+MFYT+dUi+3VZ6PPR95MUCYiheLBuZ5I57dugalBs+ef+3CNgNq+2LQWTeBVKkyutK6gD0x3Xds96XjeSMEA9YbRTxxM9Bt9JhwMijx6tUG2awg+Rv4mLXgd7urzDy4LBiWbAi9C86AwEwHzxvQ5J3ETJoGs3bbmM3zStmTvA27WVCzQ2bnqL8BISDIAOGFDKGZEvTKET6UOQM8AwyDIOKQaDsbANLJTHA2JrQJQM59LjOqbmP/Tz/JTJv7op/HgGZg5NjJzCKZ6UPP1o0NPHrLIJj6ZJbTRtm/Z5ftnj4ZdHlsGri4/Q0W3A8oFzr2+YI8n13mZk3dtx6b9fYWMPK/+zfX86YQt7eZwD/5hZN6+hN9LLO4BvQAagCj3a2U3zq0p8L6s74yA0i5aTvqYN3Rxv3YYvfV7FJ3vsxhjDvqT79xX/Mi194GfnOaLh95cC3XMZeHeqyZ+mu7za2ea5gveKYygFWqjK60B0Fnt4PBg8Ef991zzLvbCZWJ3StfT9qm+0mH1aRjYvh8edq7CwHuTMx2LXqlCTtkcAJr4rLYVcFkaZYPY2ajYcNP3l6xAgZsWB3YbuDFNZfDQe4Z8GVAYR15x2U/NimzJp7g+WS2JP9mQJld6TkAP5fPOjVAyqwhIOHhN5+y28G5G2ee2r7/FyBhJoQ65XgsG+p+oCEbIi9CDCIMps3yeiFjl7X1kJk3t7l15jKji7umvmc3tydAib7lxYSBRmaxzQq7rlzPrlDrgN89BxhMZ0bpf/7iW9trZhPpL14Y5Rg7s9/0B7eBXeQAWf9mMGwQz/ElXhCSVj4EmvJ4cWQdAIRyP/OHupO36+xFq8cvAIx+ZcDs5+mv9x9/Rs9GK1hR+pjLmZlAgKJjl32SA/Xif5+z6oVo3inu9F0PzyleuDEXUi8Wm5UBrFJldGVMRJQ1005u3RUM9Mw0OO7Eq+TsMjIIYkI2YPJEYuPsSZpjZux+y5OjV68ASvI1uGOSsgsH8JWZwlw2DJVdh7AiX5727t1ABJNaPzexAR7l6+cm945mp+FyMaEaqGVj6t+Z2IkRzO5A9OF25xxEDCqMmtsUtuHhN5/SGlsbaIwSAMSv7yIfswmZVaLufv2bjVIGauRhlhRDZ7Yus60G+y4b18xy037O28yNF0kGvq6rjXBmAHPAvNspM09ZT2bQ6fOMT9qXxY8XQ6RFfi4LdbSLOruYHbPqTQcAQ/JmE01moj0HbJx5arsLOvdt9xPvyEY/GWjTXt7w4IWQ39dLP7eOvRgwoKWcjA/3HxYGnm9yKAXlIV//Rt0YWz7eiDL5lYdeiHr8uV+5DtYVfYv2MZufGULaJOvC4xO3ukE587GBLt4TL3QqAKxSZfSl3QTC4PVKE8PAhAHL4BV4BleZJfR5ZvlYg34G3y8t90qYfJjoDKgw8IBAJiAbOsCk78sggrJ7UjdbaFbAwAy9cfAvBsIn92c2CMbjoRNO63m3cWYhPLnbFU96dnmbSXC9eM558tduGNrBBikzTX4LBuU0o5ABt11GGJfMivlNK3mhYNe+XXmwvAA9QCaxVvRXL0AM8gxC1h/7zrbN+ZuPgjEwIz23RT9A0y9WizLZ3ZhdshmwmoWiT/Ab49F5Z9e0x3MGpZlxpt94LAOyfLQRn9zHfZCwWXDHwhrUGhzb3U6dHI/HM4SneAFDG6IvL1bzwsmsuOcI93ezXDn2GGBEfWD7PC/yf34Li9lGtx3t4z5lQO6+mOPoDNjNopv19vj0gjb3AwPf9ce+s2fziMMJmPsNvNERgNHubesettsLn40zTy33HPu2CgCrVBlF6XEBM9kw4TGxeYJh8ssGx6wF9zEJesdZnvyZCLLRzzs4zZyxqjeLyGSZwVxmMrLBo84GmTYaZua4xmrZE6kZ1MxQcb83PXiF7E0AlMdA3DphQjbLYpeL45+chydhjAiMGW3l3dx2P7kONhA2rBgct6V/p1wGeC4L9c8udIM3MwgZUMNumtnjOcdq2oj5jLzM8tHu5JEBIuXtx8AZ+GTm3KyjjW6OFbOOHMaATr0Q8sYh0jYTx6LIfdOg1df7gSWDTs8TfABkXoS4X7otPK4MSryQcBt7EWqdGZAZ6HAdhj+zb5SdvF1HLxbpb+6z3JcXA/zFfU/+Hst259O2jBePK9rMi1iD4xwC4/wdg+k+ZH3SZ/vNu3mMGRi7X7rMbk9/N5OZ52j6g8fJ/cefUb50zCkVAFap8l3IuRExHBH/HBGPR8T0vXxuTESUL0zd/QgXzqWyQWRCYkI2GMlgw4acicW/mR3iOyDEQMsMm5knr1ZtQDwBGYTBtHC4sw2UmS8MK9cMOr1it5vFoMbsmydA77JmsoQtMQj1RGojjdvonmO6O0I9GRtgkR/B7ja+AEnr22UFlHvChs20IfMmGRsiwIbj9XCVZXeXdUfZ/XrBfobDRow+wjuD7dZyH3BYgBkpA31085Xj3lHMclp3MBu0GS5DABl9PrsKbWgNXG08iYklH+6xfjJYQ9fUBz1kFsphBTzPeOR5t4vvNSvl3/otDNzWZlkpj+vs8ec6+a/BpwGa6+R5BaDuMrsMbud8tI1DBtz3nJ7rYPBGf/FCzB//7thHLwjtYs/zH+MigysvPtzfPG64N48n6pDBY792cP/wIsZA2V6gDFJZsOd50v30wRmnVxdwlSrfhbwnIv4lIs6KiKMj4saI+NuI+Jm9eHZMRJQ7pp7eGi9YPwwDA9Vvxcir6Rxf51gax2x5EmLyMWuWJyUmJBtwr8Y9IWY3k8vhCdKTmYGUGROXl/KZxbEhyZMZRtmTn12wGSQb/Bjk9HNN9WMIeC4Hcvte/80B9dmw53bP5TTzYOOL/gx4M2uSjVpmD9ynbGAyEDOgdHnMpBhc0DdIj7Led+yZravX7FKOz0N/XjDQT6kH93FWZnYX2qhjlM1Eub5m/GA2Dfpcv36AF305Hy+EACVms9Cr2yiz3t7BnN2t/QCOAZMZa48ju7sz62rw5zayV8J1oo8/OOP09i0d/T6eXxwf6D6cwaPnm5w38xPj3/eweAJk5TQ8J9Fe/cIN+O6FAunAnDOvZmbX79j+ynHv2O2tPB7zD7/5lHbh6PHvo5XcJ6x/5kueeeiE03aLle7nBSDmuwLAKlX2XR6PiN/R95dFxFMRceFePNvGAHpF6ZWiXZwGKvxvAAU7yKSUQYQnQU9u3nziiQFGzitRuyY84WdwkkEeZcqTr11CGag8OOP09hgMdGBmhInVq1jHOTHh+hmDJBs4/jL554B019sgN4O4DPpymcwIwIiacXKb2fVGXdmxl3VllyflNkNGfjYaG2c27ksAievjc8mycXZcFYwdfZUNFjzLAsTtz1/HQZqdoo9kQ8yzBk3U2QCLHfI2duSRDaH7sQFQZuQwzI6NQ88GqQav6DG7m/Mih7Ssf+pJu2WQ4PHr/v7gjNNbkOL+Q/npE9Tf4I9rAALAC8+gvwxMM4PpBYNDMzwG0YeBkjdn8EEXuT3I0xso/Bv5e/GX7/E48NyHDj3Hur08rvLC1DplrNJnPC653+/59rzJmGH+g9n+ynHv6IkL7Mfw+dQG97v1x75zNzDqfvOFqadVAFilyj7Ij0fEtyLi9HT90xHxxT73vzyawcVnfHRcwGZsGKA2YoCFvFHEbi8mE4w0g99uBgMbJpkMDvy7JzsMmycRgzm74foxhnkSyvk67QzWcoxjBsO+zxOrWVWMjQEE9zr9rKs8Wdp1i/FGlzZq2cVjY2m9GiybxXWdsjvZxsQAhjqYhbBhttvXxpJyejd3Bvn9XOvogHJhkDH83Ou3f+SFQ453NHvjfme3nwGCFzKZHbTLzTrGIFsnXghYL3Zbo0eMq/XJve5HNtboymEcrp8BH/3MQCWzxdaVAQz1NkD1bl36jBdSbOJgDJJHXmR4jMFIZhen0/Z447qZc8rphaP7dWaV0anHj0Ha+mPf2cYCur79dOtFpceUx1nuY/QzrntxazDlPudFmUFt7vMZoFJWLyBcRthrxloONXCf5cPmkH6LgTumnl4BYJUq+yA/G82AOT5dvzwaZjDL8s79PZ/b3vjW8qVjTin3HPu2cs+xbyt3T397+/fOqaeWLx1zSll73EnlC1NPa+/hc8fU09v7Pv+mM9r7ufdLx5xSvnTMKeXu6W8vX5h6Wvv7Pce+rXxh6mll3fFvbf+S5peOOaWsmXZy+9w9x76t57k1005u/949/e3l7ulvL3dMPb3Na+1xJ7XP+Zk7p57a/v+lY07pyZO0qMMXpp5W1h53Ulkz7eRy74y3lDunnlrWTDu5fGHqaW3+5LFm2sll7XEntde+dMwpbV5cp07ohTLePf3tPemho7XHndQ+w31Og3JZF3dMPb2sO/6t5Y6pp7d5Ug/KZN3fPf3tbTlIi3LfO+Mtbdl4Bj3fd8KvlDXTTm4/PPv5N53RU7Y7p57aloW0qQMfrnEf9edDH0DX645/a9su6IvfaTfq7Txyv6H9abt+5SNd0nZfXHvcSW0Zudf1WjPt5HLfCb9S7p3xljZ92sj9kudyPug/93/60+ffdEb7G23IWKJ+pLVm2sll3fFvbdOjPB7v98341fZej1OXyelyD/2StqOe645/a/s744p+go6pl/sc5SFdz0XWE3MP7ef8SM/9jnJRVvchj0Halr7hdv+jN57Rpk0d7ph6evncG97RMzYpA2Vz2XN/9Zj0nOU51zpAx7m/uS9Tj3uOfVv53Bvesdt86fHgOcxztfNg/mDu8vjweOH5PM+6PLYz1I12/KOpv1IBYJUq+yD7CgAzA3hE9AGE9VM/9VM/9VM/L9JnfFSpUuU7yr66gLP8SHRB4PjoBYf18719xle9Vr3+AH2qXqtevx8+46OxS1WqVNkLeTwirtb3l0XEk7F3m0AimkFXOn+r/PtJ1ev+karX/SNVr/tHql6rVKmy3+Q90Zz/996IOCoibojmGJixe/l8naD2j1S97h+pet0/UvW6f6TqtUqVKvtVFkXESDTnAT4eEcfuw7N1gto/UvW6f6Tqdf9I1ev+karXKlWqfN/Ky6PZHfzyF7kcP2xS9bp/pOp1/0jV6/6RqtcqVapUqVKlSpUqVapUqVKlSpUqVapUqVKlSpUqVapUqVKlSpUqVapUqVKlSpUqVar8u8m5ETEczTEyj0fE9Be1NN//MisivhQRT0ezsy8fwP0jEfGhiHgmIv5PRNwbEYele34qIj4TEX8fEf8rIj4VEQfuvyL/QMhFEfEnEfEPEfF8RHwhmgPKLT8REddExN9ExD9GxOdj96OODo6IuyLinzrprIqIH9tvpf7+l4URsSWavvb3EfFoRJyk36tO/33kwmjmg6t0req2SpUq37fynmiOjTkrIo6OiBujOT/wZ17MQn2fy0kR8T8i4ozoDwDfHw2oOy0iXh/N21ieiMYYIPdExGA0R/XMjIhvRMSt+7XUL64sj0ZXLyRfjojZEfHaiPj5aIziP0ZztBFyXUTsjIhfioip0YCZh/X7j0bE1ohYHxFviKat/ioiPvw9lv8HWU6JiLdFswg5PCJWRMS/RqPniKrTfw+ZFhE7ImIoegFg1W2VKlW+b+XxiPgdfX9ZRDwVe/8GkZe6ZAD4I9Ewfxfo2quiYVd/rfP9qM5zx+iet0bEt6N5r/MPoyyP7wwAs7ym88wzne+viga4vFP3HNm557jO95Mi4v9Gw7K8JxqD+y+dex6NxhBb9vQe0r3t/y+PiI9Gwwb/n2jG06/s5bNZfjKaBdhfRcT/joj7I+JNe7j31IjYFE2/2hkRH4z+rNGe0vxmRMyJrk6vjIg/iGYhgg766RQ5JyL+LprXUL7U5cCI+MuI+OWIeCC6AHBf+ytSdVulSpX9Lt/rO4Sr7A4Ap3SuvSHd92BErO78f3Y0LKvlx6JpizP2Qxm/H2R57DsAPLTzzFOd77/U+f6T6b6RiHhf5/8PRcOsLo8GUN8eERd3nvtcRPy39GyJiHUR8V/T57Wxd/KHEfFv0bjt5kfEI53vM/fyeeRl0TBD/xgRvx1NWMafRuOyzeEDJ0VTt69ExLyI+EQ0IOK6vUzzn6IBJkdHV6cbo3G9fyUacPjPsbtOLZM7z71xH+v5wyifjoiPd/5/ILoAcF/6q6XqtkqVKvtdfjaaieb4dP3yaJiMKt9ZMgCc0bk2Lt13e0Tc1vn/4oj4iz5pPR9NvNYPoyyPfQOAL4uINRHxXDTxqRERvx4Nm5flq9GwcBEN2/VYNAAJI/uKTt4n7f5olOhlwPdFpneeN9v7ExGxLRoguC/y7k5aZoteE81CIYcG/Gk0oMGM3/+Ips5H7iHN10UDBL/Vue+Bzj3odEI0Oo+I+Ho0wNM6XZvK8EI6fSnJr0XjwiW844HoAsC97a9Vt1WqVBl1qQDwe5cKAHeXmdFs5vjniNgeEQuiPwD8rxHxtWhcp9+MiM9GA0QiGjZrOBq9DXeu7a1BfSYal+zLonHJ40p+IQB4QPTGaO6NXB4NoMqv97qok+6E3Z7Ys9weEc9GF4QhN0TjuuUNEkd30h5I9zGWL9lDmj8eDaM6NSI2d+79+eiv0xcCgMujy3CXTtn+Jhp2e1/194MuE6JZoLxe1x6ICgCrVKnyAyDVBfy9S3UB98rronExjkQTR3dJNCBkKHoB4LJomKjPRgN6PxBNnNqOaIzirmhcYbdEFwDurUvtW9H03yUR8dfRjWlb3hP6/gAAIABJREFU2ae8JRpm7Nud//8sGsO9N7K+c3+W/9RJ65S9TCeiib27u8/1OZ20Xtf5/l863/vt1N8VzS7TvU3zc9Ffp1+PPbuAl3fu//PO349ExO93/v+9PdTth1VOj6be39KnRNOXvhXdflBdwFWqVPm+lMcj4mp9f1lEPBl1E8jeyp42gfyWro2J/ptApuqeX40fjk0gd0TD6B2sa0dF1zhGREzsfL84Pftz0cSy/V10495uiS4AJKj+TD1zRPQG1b+r8/1voolpuyAaFu3fOtcXpDwfjojzo9lUcU407rwSe8fEfj0i7utzHZYu5/VC8o/RHAWU5W2dtN7S+X5B7Jld/Go0G132Ns110V+nfxn9Nyr8THQB4GA07QQzeU3nutmwH3Z5ZTR91p8/iQYQ/1zsXX+1bpH50avbKlWqVNkv8p5owMl7ozHUN0TDTuWzqqp05cBoGD7cYO/r/A/oeX80Ojw1GubmC9H/GJhN0TA5J0RjdH/Qj4H50WjYvz/s89td0QWA74sG7B4aET+tz83RGMM/iYj/2PncFrsfAzMSEb8YDYB+JHrj7SZGl/FbGg1wej6aYzX+NBqW7IXkx6MBgX8bjVv4hWR79GfYYIGXfIfnLf83Iq7tcx2GjkXGpZ3v/Y5peih62STS/Eg0Z1dOiqY/3tpJ47c792Wd/lM0AAThqJK1nXtLNMcc+agSdre+1BeOD8Tux8C8UH+1bn8+evtrlSpVqux3WRTNJPUv0TCCx764xfm+l1+I/keH3NL5nYOgn40GXN8bzflrlp+KxhD/QzTG9ub4wT8I+j9Go4cP9fntyugCwGtjz8ev9Pv8tdLhYN1vRhN/9sedfJGfjq4b7p+icSt/LBoX+wc6v5md7CcLOvd9p528PygM4KeiYVH/JRpwQQwgaWad/l3svollYjRgFyb1xujdhPL/RAM4r3+hSr4E5IHofxD0nvprRFe3ub9WqVKlSpUqPxCytwDw+mgA2luiOTstf47Tc7dE1wW8N/KyaFzQz/T57Zzobn54IQF0nfod7vtBjwF8XZ/fIhpg+8AeflveeXZyuv5jUQFglSpVqlSp8pKUvXUB//fO/5kV7Se3xL4BwIiGBftW7H6Q7oc6+X6nOMtF0X93fJZV0X8XMOcO7ssu4M9F/13AN0bvLuDXxgvvAr70u0gzy94AwF9N16sLuEqVKlWqVHkJy95sAjmk8/0z0bjLLT8SEQfp+y2x7wBwSSevebr2E9HE7P2prr2mz7OvjOYcv7+KXgD509GAnFfo2rGx+zmAL4+GeXtsH8v8ntj9HMCfjiYW8bPp3j+PJtbvR3XtsmhY1aO+yzQtewMA8ykBbAL5TuxqlSpVqlSpUuWHUF4fDQAciWYzzLLofwzMhZ3vD0fDCJ4Tzdlofxm9gOqW2HcAeEA0IOZfo2HpzosmPu5b0Xu22vJogNRl0YDFD3Ty+nY0rtZI95Zo4j8tt0cTF3d5NLs3H+58n7WPZf7RaJjLf+iUYyC65/Edke49uVPG+zrlXh2N+/XG7yHNWdEc2XNJNGfb7dB312V5NHrYEhF3dtLkGJjP7GOdq1SpUqVKlSo/RDIrIv5nNJsOXugg6HdExIZoNiv8YzTM1u9Er2v4lth3ABjR7JK9JZrjYP45GkbuLemeX4nmKJRnogGLfxvNbsz8vuCIPQPAn4gGZD7TyeerffLZW3l1RNwUzaaX/x0NC3fMHu49PZrNHP8cTezfZdFsxPhu01wee96Es7zPfUdF42L++2g2OFwdL72DoKtUqVKlSpUqVV4SsjwaAPjTL3I5qlSpUqVKlSpVqoySLI8KAKtUqVKlSpUqoyg/Fd0Dovt9+m3qeLHlVfHCZc5nwn2/y/KoALBKlSpVqlSpMoryQLzwgdHDL1bBXkBuie980PUPkiyPCgCrVKlSpUqVKqMoU6P/wdF8TnjxirZHOTpeuMy//OIVrUqVKlWqVKlSpUqVKlWqVKlSpUqVKlWqVKlSpcoPr/xIRIyP5pVW9VM/9VM/9VM/L+ZnfOz+lqAqVarsBxkf3zlQvX7qp37qp37qZ7Q+46NKlSr7XcZERDln7Fnl0oPnlgvGzy+XT2n+5/sF4+eXCyfMK+ePW1DOH7egXDhhXrlwwryycOyCcunBc8v54xaUhWOb6xeMn18uPXhu+fCUs8sF4+eXKw6Z3T7vtC6bNKcsnzi3XHXYb5TLJs0pH51yVvv7pQfPLRdOmFcuPXhuWT6x++H6r796QVuWua9Z0FM+/79wbHMP5Zn7mub/Kw6Z3dbtsklz2rJRnw9PObssHLugp0yXTZrT/s53dOF6XTB+fpn7mm7e6Gnh2AVl+cSm/MsnNnlcevDcVg/UjfqTnvVOnZZPnNvmQ94XjJ/fpk8e6BkdUFfqZh3Pfc2CnvxI78NTzm6fu2zSnN3KSfouy4ennF0+POXstpyXTzmrreflnXxpU+uSslx68Nzy0Sln9ejtw1PObsvg//lL+ywcu6Atp9uOtvT9549b0NP+lP2C8fNbHcx9TTe95RPntv35sklzygXj55erDvuN8uuvXtCTLml+eMrZ5eOHvrcdTzx/xSGzy1WH/Uab36UHzy3XHP7fykennFXOH7eg1R36QncfP/S9bf7cQ70uPbi5l+9XHDK7XD7lrLY+l02aU644ZHaP3j7auZ92vGD8/PZ5dM7vH+2kRT7cf8Uhs9s2Yy4gT8ro/kBboAv6AnmSP8/QTujmikNm95SZ5z2OPjzl7LZcpOn6kq51x/20G+PAfZT8rjhkdvn4oe9tr3nM8uzl6m/onHTQFWXit4VjF/T0Pc+v6MNpfPzQ9/bM09TBfdnj9fxxC3r6BPMUc1XOkz7DvEk5Geu0rdvP7UHe3H95p90vmzSnveZ2u/TgueV9498LABzzItvFKlVeEjImIsr54xaUpePPK8smLCorJg2U5RPPLVceek5ZMm5xufLQc8rS8ee1168+bEFZNmFRe+/S8eeVpePPKysnN78vn3huWTm5e31g7OKybMKisnLyQLn28PllYOzismrKwrJswqKyasrCNo0Vkwba5wbGLu4px6opC8vA2MVt2qumLCzLJ55bVkwaKANjF7flXDZhUZvvknGL23TIZ/nEc8vqwxaUVVMWtnlSPsp45aHntPcsGbe4XHv4/Da/JeMWt2lR7isPPacsn3huWTZhUTlzzHll+cRzW126jDyzJz2tnDzQlnXl5IGyZNzi9rfZBzX/ozeeJS3qQh3I5+rDFvTUn7JQnmUTFrV64x70Ofugbrstm7CoLBm3uKzutP2Vh57T0y7oh7xXTGrKv2LSQPsM5XX90f31R8xr06TtqDvpWXekTXnRDc+gd3RDG9I/Vh+2oNx01Jz2nuuPmNeWccm4xW17ojvaZMWkgba9uddlcz9ZPvHccu3h83vSchu6TeiXVx+2oAyMXdzm5fHodkXnHjPuU5Rj9WEL2vGETqkLZaBNnAbpuq2pB2OE/50e/Zj/GbMrJg2U64+Y1+bD83zQVx4X9BGPH/Lz3ECZrjz0nJ77Vh+2oCwZt7htK89bnl+WTVhUru7cy5hx36It0Oe1h89v80Cv6Hj5xHN7+hr6XTFpoG1f+gZtTZ15dmDs4rY/oD/6Dzpn7HgcUV6PT8ZAnpNWTVlYru7Mc9TNbcH8Tz8jffr3ysnN2KbM6AC9U44l4xb36J6+xLXZBy1We8ytALBKlVGUMRFRLps0px2EntiZ3Gx4mBSYOAzgmIBnH7S4nfgY6Ex6pI0BWt2ZcJkomDSYYFZObtIDHBhUnTnmvHYS5TnKRBqkY+PNRJcB4mpN/tkocj9lv1rAZvZBi9vJkGcBUNaPDQs6tMEzWPakjW4ox5WHntMajNkH9RpI/qfe3EtZbPhdLtrbBgOdUV8Mn8uHASAP9IshxSiRL+m7nDaCWf8ZwHvR4PYmfQNxjA758pcysShxOaiTgTEG1XUEYNOOGHi3s8tNeQGe1HX2QYvbvnrt4fN36+cej7MP6rYPY+vKQ89p28YAYdWUheXaw+eX1QIdAAoWONa39W7gaTDnfmg9Xn/EvHasGuBQFi8uaRPaw4s5rnM/fQx9+HcDY65d3QEetIuf4X7GkMfrlYee0/bHvJgyKMoLgZWTB9o5CHADYAWAkRZ9kgUm+maRYABosGXAPDB2cbtY4r4MojNANtilfzM3oC/PaTzHQsnzQV5g0CfQ8dW6n79njunOY4A99wXyWjVlYTl/3IIKAKtUGUUZExHl0oPn9rBODHRP1J4MvPrMq0AMkRkAwJlX+RgoT/heLTMBGUiS1pljusafyZRJyROQf7/pqDnthMdql8nQrGY/gGTDk8GRwbANDMDBrBqTpFfjq6YsLGeOOa8HtBpIZTaG8s8+qAtGySODBiZ+M1XoLk/ENriUHX0DNNGjQfbA2MVtnZyXjSvgBx0YjGdjhj5XH7agNZoGaBgggxbrzfdSJ+vcQGDl5IaZMlNqHRug2GDSrgZIBo2AA7f9wNjFLYAzE+V6kS7AzoycQYr7pvVNuQEZPAMgYKy6LRhjjIkMWjPLZ7DtsZD7sdllwAvAyGPebH8G6rQr48btb7DkBavzZR65/oh5PWxcZtvNwKOPPG7c5qsPW9D2B9qWcWO2zOPAfRuwBVClnAa3eX7xgiq3j4Gr+0BmbikXng3PMdan2WJ7XzxvefwaZPKsQSl5sPhxvzUQ//CUsysArFJlFGVMRJTlE+f2rMTNhJjtwmh6tZqNEKtAmBVWfjZ6mZUxmPBERpq4QDNgsBE2g+R6kBcT6MrJA+WGI+e2v117+Pye571y9yRMuQ14DWZtQA2mYHbMNpk5I528Gs/uG4NeA0y7qDNLa7dLZnYAkAAk3E4Gh7BLNjQG8tSL/kL6GAcbFHRvnWFM0QnlN2C0YeV3g6czxzT52o2LC8pMGmUy+2Y92ejTxgZNBkdmsT0e3K7olX5hJs2gNefn8WRQYDdfBik2stcfMa/tT4AcAzb6dWaX6fvohvIa+Fi3bmvuyYwwngDqlsFZbs/MHtHffR9p5HmAftRvPgDs+JrbzmDbwNHMtHXhxQX904syM4TMnQC+m4+aU1ZOHiizDpjfA57yQpT2sk7Qp92sefHsvsYYs6vc84fnbM9XZntpLy8cPHatP4cMub0oo13y7i/U6dKDqwu4SpXRlJYBzO6lvCr3RMu9AASzF4AJJjW7m5j4mBTMjDAZOI4Eg8eE6NUlaVNmAzLyMkBxnnb/mpHAAGcm0StqT+he+cKMZebNLIjLa1c3xmLp+PNa3eayMDFzL8wOIMKgffnEc1v2jLJj/AGMfOc+69z6pNzkxSTuuB4DoxwfRpthhK4/Yl6b/5Jxi8sNR85ty+X+Qh4GjzxrkI8hcWyewTyGNTOQ7ufuAwY4mRWDScosFd/pAzaYBppuSxti12nWAfPbtsxMrOsz+6DuuOFe188gnnIbhPNMZt2tW/Knrc06wujdcOTclpVHD3YLZiCN/m7usEEed/1YXLeV9WSg6fzQCf3NfciAhL7tPmz2PTP7rjvtYfBscLli0kD5zQlLytyjLi7XzLywXDZ9WVk14+KyasbF5SPHLSsfOW5ZuWrGRWXVjIvLVTMuKtfNen/727zXNr9dNeOics3MC8stv3hB+cQJzT0fmHZJ+chxy8onTriofOS4ZeW6We8vnzxxaXvtqhkXtb+tmnFx+eSJS9u0P3FC89sHpl3S/u/rlOUD0y4p1816f7ls+rJy2fRuup88cWn77DUzLyzXzLywfGDaJe09N564tKyacXH5wLRL2nRWzbi4LfeS1y8rlx1xfgvUvUBBb5dPOasCwCpVRlHGRERZOLYbLM7HzAWgIbtG7VKxq8mrV4MIgyGMrFkvT+7ZbcfE6xU8QAzjYpdHNlhmMj3Rs2rPLAVuNK6ZqTDgwjjxG5OawQig5uaj5vSspG0QbZj47e9+c0J5fu6RrSEzuwfTg1HETQNIwhC6PM4zs56uL0wDLj2zn+jH7Kb1Ypc893ilb5bJge5u66uVj/uFXc0G2QYbAAUArUERbLQZMPRm0A0YBRzaxZw3DXkTkgEp6REfevNRc3Zjt/JiIbOpjucyE8WiyX3G4M2bfGAizQYCiACSZrz7LQBpW0AbizQvRry48lijLQj5AGC73ShbjnOlD9nt6ZhS69yLOs8BXqShJ/KnfakTY4DFBv2V+ub+ayYZfa+asrB84pjfKus+u7Y8vHZDeWTdxvLo+o1l47qN5ZF1G8tX791QHlvfXH+4c+2RdRvLV768oTx+74by+Pru74+t31Ae7vx9dH3zd+O6jWXj2t5nue/R9Rt771Me/M7/j3fS5P5H9DvXclrc39Zpbef3tc21h9bunhb5PfDljeXhux4oX1x6Xbnp6Dk9nhX6zWWT5lQAWKXKKEq7C5iJz4b42sPn9xgmT6oGN0zqdjdhRJeMa4wVAe58DNIwXnYfZPcTEy+TBiCIydw75kjTaRtwYpgNEm3sMSAGE2YaMJJ2BzuYObu3/bxZO5fFzA3G2e4V4oXsVqSsgJhbjj67BW8YJOoFM2vXamYpzTJh2LNBzW5EuxLRma/ZsJspMcMCGPRCgTwz4wcIM0OVA+bRvUGwFy7Wp3VIH73hyLk9LLOBvQGq65X7BrpBtwY8BiZmBzOQPXNMl4ldOv68ng0DgCynu3T8ea0r3CCUevs++gL9A7DFphTr2300uwoNxl3/q8U803dgfPnNYJQ5pF8fgdH2d8avx7wXIrMPWtzmQ928+GPssjgzEHf+/h83rsdwZhdXThkod3/sM2XTI18rI4Pbysjg9rJj8/aybfP29v+RoW1leHB72TW0rewcau55onMP9w4PNvc1aTT3jHSeGRlsfh/upLdjc/P8yGAnn6FtbRrf2LS9zWPH5ub/HZ3fdnXKMTy4vYwMbmvz3zW0rcm78/uI8qQcvr5T9eHvrlT2bZu3l29s/ovy1fsfKb/3vht7FkL01QoAq1QZXWkZQLs9AH9MiKbpHe/HxOu4JoMnJmSYJAy+gZ3BnydhDFsGUHZf2e2HMXFAtt1Edqth6DwB2dDarZcBIvW79vD55drD57c7MNltiYHMxiSDA69+7a7mWg76B6Avm7Co3HL02T06s4sMFhDDRlsAesx2GaRitG2sDY5geKkbYMnsioFDBppmzdAz/5MfOnT8Im3VD5CSfz+XcQZc6NMuWsCkNy/4HsqLgac+Bld2ZxvEf/q1Z+2mw/y8WTYDJvRDvfcE9gzkWIj5qA4AtIHRikkDPZsiVk1ZWG44cm67yHJQvtlfM4qZYVs6/rwy64D5PUwgdTEApL2WTWhiNg3WDKIcOmC2jZhXA1IvTNGjy+2+xJiB9fSmG9LkfwNgs3385nAQj7Or3vC+8sg9D5Ztm75Rnh4abj5bhsuTQyPluS3D5ZnO57mtw+WpoZGya7D5PL2l+f70luaZJzaPlCeHRsrTQ8Pluc417n9a359J95Mu9+4cHCnPb91Rnuxce3pouDy/dUebLs8PD3bze3pouOwcbO4f7pSPZ5/spPvcluGyq/PMM1uGy7Od8j/bSW/X4Ehb152D3Xr+5aa/KA+teaD8zusW9fSPFZMGygXj51cAWKXKKEq7CcSTqMGGB2ie9O2SMWODO2Xp+N2PEjAYA/wAXHycgtkegwkMZXa5ZdDAhGy3jV1dTPiOW+O6Y3kw8HZpYmQwFjd3Yr9gYOwy9GYLDGPeSOJYs9ViLcyG7CmezIbd17Mhc0wVOobNQC82qhhDAxvayOwNZTSD6/5ghgkd0ZZ2pRuIeoGR3crugwbVpOXNAORj0Afb5HxpKxZALr+BihnrrBOzULlNMwNtsLpycu+mJNgpLz68wKJOuN5xiwNe7TI2mKLfoDuAovN1e2UGmTrxm12npG3w6nFMf2HHOP0cAIvOPO4YN2zyMSDNiwdv4vB12tOMrtnA3DfNKrsN3Q54G7hmV/6yCYvKx4+/sDy6bkPZtnl7C6aGO0AM0Mb1J4c61zsA0b/tGmzAFOBpZ+c795He0wJxALZnBcj+/GvDLUAb7gC557YOt2APoPZ0Jy/yf27rcAtKuZc0Dei4Tjme37qjrQ91e7oDFncNjpThwe1l49qN5XdOeH87X6HHCyfMqwCwSpVRlNYF7Lg4jJZBlt0kXrkZ0DlWxobALji7VMxS8D+TridcuwivFngyI8F1GzIbDIM8nsmxejk+jMkJUJuDwjEeMChmDTB4Zl94hroYnBHTl8GpWVIzsfn8P28esV7NUmTQaD0aGKMDnwtGOfjuBYPZQIMts4bcY0bHwN3smO8jTdoYAw7YpN4GVBmQ8Gw+e5B6cc6kmUm7jF0vf3I/MrA3G27QwZhhcQSDTN82YDLozeEDLITMuBsUo3Pf59+pl9vO7KpZQPLNQDkvRnzsEzr3IhCdnDmmC9q9GLA7ljr5d883GdR7EWkAmoEdY4K+lxdNLC69YDXb64UgR17RHismDZRPnri0PPjljeWpoW0tEAKQAZhg0QBzAKgnNo+0wG94sAFzALOdAoRPDnV/A5S1AK7zLPmQF6whH4DdswJ5TwkU8rzvf05A8UmVG2AKG2hwCEDc2QGaO4e2lUfWbSzXzXp/j5t/xaSBsnBsPQewSpXRlDERUS6cMK+HCWLCwzDhPrORZiK+Wqvk7ALMLhhYCiZTGzAMhoGowZOZNJg1swiUZ/nEZkeuGQEmGRut1YctaAO9KbOD5/kOGDEwdrpmSx1PR7nYlGHghEHMcWn9jGsGgQaxNpTok99hTjI7ZtcXIBOQnd2s/LZabm6Ajt19GFPy8QGxGVzaEPfbgAGDZ4AJ+L7+iHmt655Yt2UTFrWG2OwQMX2uixcIZgHtcgf4Aqjcnta9XajeNEVf9CLKfZH0c/v5zSu0T2awvfhyXwDEWmeUN5/Z6UURbLV32puJy0DXv5n1dd/1AgqXLQurvNhyHK4Xn2a00YPnCLfL7IMWt33BY9Tg2QCWMeXFHOXHze66UV7KZNbccxvpXzZ9WXls/YYyPLi9BUitG3dLl9l7cmikx837TAeIbdvUZQRx6fI7z8LMtS5jMYUt8wYzJzd0y/YJ1PE8QHHbpm75AKUGmNll7frg8sVlbCDIsyOD28qDX95YVs24uB03tFs9BqZKldGVNgbQ7JJX8UzAfh2ZDUFmcew6zuDLzB9Aw+fAYRCYxH20hI2E2QSvIA0mKCOG3S4vjCjshN052WiYtaScOd4LQwuj42NysisOo8jxJwBtdnZ6k4wZJoAOenS8201HzemJzUQf1jvttFoGzAYe0GTwSzpmLDnZ3+UCJHIN3XkXNYCU+83o5FhOyuEYMLNzZnFpWzPDZi59+DCAl75EOdC5dWXQY1c4zCvgI99rt5aZQIcB5IODfZ4abUv/AGAanNsFbSCLrmGkDIbMZnlRwPj28U7WOWNyybjFPW+9QPfUz4DMAJjymaElXpFNV24Ps8xeIBlYe9FoMJ/HpRlELxDRtcNK+sWrevzSHvQTv8HFi6vLpi8rj67fWHYObWvZPbNrgDqAE6AJkPeMgCLADWYw/wYw43lA3FMJVMIImpUDeMIsAhiJNwSc7hpsgOqjd28sEVHW3X5X2bZppE3bLmBAXw+z2UlrZyducMfm7eWx9RvKVTMuatudsVFjAKtUGV1pGUCYvLy6d5yUXS0GenYrYUj6sT6AFDNGTMAYctxDNvZM/qTpeCz+9+5VnyUHSLGL2EyKD2fOhpTJyW6hfFg1RsWsDc/ZEJptgn2xS87xRgZSdnO53AbnftY7Ys0Ucc2gDX1nVhYjRztnt60ZHnRww5Fze9zWAEj+N9CjHQENdhdmlyvfDUjNgNJW6NCbPdyedmt7o4Q3Trj9+rkaXXYDQce7kr4PprZLm/6a9WmQ5L7tsmZATBro2OMSYLt84rltXzMzbKbOixq3t93JmbE06OJ/nzGJzhgD9E0v1hgnjHmDO9cxA/78RhXqbMBp9tRjmrKZjTUgt54dRsDCxGOYftBT1xkXl0fWbSzDg9u74EsA7WmBrR4Wb6gL5AB1O/VsZu8MGmH8cA3jQn6u454lns8bNhyPiHvWGzhgIAGKAMC1t93duqRzjODTAoLDHeDoGMBntwyXb2zaXh5Zt7FcNPWSnkXe0vHnVQawSpVRlpYBZFIzy+AJECaC7w5kt4G0a8VgyEYdkOhDojHyBpIceTLxwLe0k7ZZDu4305cBmcEgz2K4YNX8HlW7oZyf3ZWkmwGZ3VCkia6ysbLx9f8GYwBYB/pj6Ax8YRGXju/GOhL/RbqAAJ/v6CNTKBsxY+jIgfz9WF82MAAeMbx+PzLMkFlaG3S7H2GHbPjtFjRTbFbRIID+wKLDzHR2ZV59WO9B5Y5ldFnRqxdCpPn3//1ne1g+gxu+X3/EvB6m0qyp2SlveKHOdk/C4rqceYHGXzOT/RZdBncGmQbNjEu7VQ3kl4xbvNuZlA4LMOPmfmeXucMSfC9j0mOfezOoc59yDB9tTN8xCHX+Hg/cj04Aejzj8AzSZXytmnFxeWz9hpYBhLXDNQpQc9ydGTiYtScHd5Q1675efv/OwbJm3dfL04M72uef27I7C7gzAcRnlSfxeuwG9gYU7+B9ZksvkwdofHpouDx+z4aGAbztrh7gB7Dbtql3UwhlYTfxLjGAD61tXMD0B+btugmkSpXRlfZNIBhWu0QwXD6iwqyDJ327AjGYPmbBRo5deUy8BgdMwo6d4j6zkpmRMHtjNsOsoZkNB6KbFcBg+O0J5ItLGuNm97MNhvMyE2imBjDmIzkMhCiTWVSDbgMSdvTmctlNx/024AbTlN3uQdffDJYZHtoKo4hBtIGGZUOPuMGpm0FAZpCI/cPQA9gcr2lwSr1nHTC/BcZ2hZvd417XHwBgEOA2x9ib0QW0co168Lxdjl4ArZjU+2acfDbh8ondDSrojjYw+OvHiJoRvoyOAAAgAElEQVRJMyNv1+6KSd13IbuvGdjQN2kjFmXMF+geXdrNTvvldkC/VwsAUx670CkTzxioe6FnYO3FQGY1aUe+u4wOofD85zHGd29A8nhdOv68cuOJS8uj6zeWkcHtPbtfvRnk+a072o0UOzubPXC9PrNluNy6ZqhM++CXy8T3r2k/0z64tty6ZqgnXs8xeDB3fABe/JY3jRCDCIB8cmik/N41ny7T33hMGXPgmPLqV/1k+eU3/1K5/86HylNDI+WxDgO4/va7emL+fEwMdcTNbddwd0f09vLo+o3lI8ct67ElS8efV84fVzeBVKkymtLuAraLzMaXyQ+DvWJS94xAAw4mWoMbuy3zGWyk58N6MfzZWGP4SNuGxcAxu9bsYsOQwMQ4PfLMr0nzC9v7MTsYdQxfdrlm12tmpAwuPBHaGLFCZiOMWRuDS4w0BjkfdG0XHWcOAnp8FEY2aDaoNohmiGhXwIhdw9Ql4kd3c2GatTNDYzdbdvsatBlU+QOoNrNld50ZQsAAb2nJLlvOCDSgMsuW3cVerBjEABYM2KlT3vhidyN9LbfFyskNeMwLBrNnvD/aevKh43w3iw6bRzk8LvmYETVgNNhy3d1+ebHlcewPCyUDO8cIE4PntmGecD6kbfBsJtFvJnGbeoFjrwFp+ODqnjCKjgv4ic3bW4A23Nlc4aNgOI4FUIYr99Y1Qz3AL39+/0tbes7ge3pL91w/8npaoK+NP+yAsQw+vVP4+o9dV2664vry0J0PlnW331V+5cRfLkcddmQZ2bSjdQF/+bN39xwFY3f0c8kdbeYTkDs8uL08vG5juWrGRe08hM7rQdBVqoyutOcAenK129Jsi8EUk6g3UdgNZgNh0AI48ATLJOu4KU/CGM6bOi9SNwNioMBkwu/EC9koYwApez43zu4lfzBsGBDqAvi0i8xAh/LY6FFuu6zNrABcze44X7sR+RBL5frZpUv+gHdeRg8YJRbK5eaTgZjZupWTu27lfuzi8ondty24XNar467s2s5Mlt/8YvbJ6dhN7mddTi9WzLZlNyNuPbPjBmCkS/m9IcJprk6LCOvCTC/peVex+7Lj2wy4qQcsmkFxBkL9GGzaxAsRu2D9rIHqikkD5fdfe1YPw+hYRO6nf2Zg2a9PkG8eQ3ZLe+OY+xkfymjmz4spLxpZFLkveD7hOdh/M5B5TC+bsKh8YNol5ZF1zSYQb7ogbs6xdt4csnNwpOzavGM35i9/pn1wbRnZ3N0Y4iNd2oOdtRM3g07K4M0hz27pPXga9nDrA5tKRJT7P7+2PHzXxtYFPDzYnC/IvYDLbZtG2uNrYBd9RMyzW4bLSIcBvGrGRa3Xgr5XAWCVKqMrYyKifHTKWa2hACAw0QIscsydXSQGVNmAZ/BjUMRvPu/PbkfStwvZDEZmqvh44jbIysYpMxhOhzK63GYnbdy82QRXGSAClx/G3caSI2LIw8yZjRc6g0XNOzzt0uJeDFtmjbyz2qAdNxvuefRicE85/UYRMyoA8OwCJk7M+Tlmk/wcJ2YAQ98wgMuHL/cLCXCwvpkds0p+3qwk7c8xJu4jMIN5gWDAZuDBNa57fDhW0fXBNZzPLjTINiuaF0RevAEOzVT73EiDLS+uvLhxzKE3mHjTkEGjXwXpPugjgphPeM2bgTv6t+vVcbcOUzCTyfM+e5CYyQzWmLMcN2uA7nhZA24Das8NZ445r6yacXF5dH2zCQSAtG2TNlTYLbqle4be01uGy13rv/6C4I/PF9f+aQvocMMOC9jB7LU7f7d0/+ZDp2ECnxoaKRvufKCc9tZTy8HjJ5QD/8OB5RUHvKJERPndq3+3PNIBgPfdflebD8zlsJhE8mczCvGJf/61pgwjnXMAV824eDemtu4CrlJldGVMRJTLJs3pmTTtYmRizowV7jozhVenCRNXlwGCDdPsg7qv4fJE6hW2N5k4jsyrcZgRDBruNQwSE7o3PTCZ+/2q3umb2U9cxxnYOH2DUsqNATIDQj52CdtdaaNv0JBjv/q5aMmf/zFyZmPdDnaDYswNjmBJbCj9vl6Dn1uOPrsnTbv9zTKZqQE85003Gdga4JGe62TXfQbPlMUMj5k26gKr6L5tFs8smPuBX5/mdlg5eaA9JJx2Jn8DEp6jHGbQXQbr3EfDmCml73CGp1lNgy73GVhl9JoZwMwEekHmucFMrfM1+wqoM8vsMWNG0ptd6Fe+z+DBfQDXbu5zBoDoL7eJY1StXy/C0JfPBCS/G09c2rqAfV4fgM+7Zp8UC/fU0Ej59J2DewUAb/7CULPDtsPeccj0s2IAfS4f7CPMnd/44Y0eh0w6pJx4/JvLZ2/8THnwjnvLg3esKxFRPvXxG8pXtQkkv/YNAAgD6fhCAC5sJS7gG09c2rN4XD7x3BoDWKXKKEvPq+AMWmyoWaUzETJZZtYM4MUGC+6BFcM4sckCcMQ9OW4rG1UDCYNPztHLrI6ZRLt2fSyGDQB52W1MGcy6ATIxFnZP2SDZ8NgAmV3zTlZ07zhBnnWcmJlJjLB3MvvokNxmPOty004+m81gOjNPBuUGXgbvq6b0bt7gupldM2gGOwYBBnuwhmahfWagAYfBOe2Gy99Ah3YiLYCgAT2HStudn8HR6sMWtEwWaVhvZpCswwwMGUdZV+RpkOtFjcGVXf79FljUzYsbg1Ez0NY3vwHAWMR5rBsg+jn06HnF4N47vxkT2W1sxoiQCXTsUAX3HccGu0/DWnpe8RjKjK93C7ufs9udMi15wyXtQdB+V27eMOEz84ihu3Pdn+41A9ie97elCyRh8gB9Thtg+HQCiXz/s4c2l4god95yW1vOL97yuQ4AvLGNAVx/+109Gz68yQMW0htRzAY2/28vG9d1N4E4vrweA1OlyuhKewyMDQSMD0yIA9ZZ/XoF75eoE0uYDYHjxrLrLG/K4P8bjpzbGozMXDgPswqU3y4ss4V+o4jZLyZ6G1SDj+yCspEwW4chMSC0mxcD5ni/bBCdpgGSWT1v+MDIoXvYCINqs1SuM8bMLkmMqllUs3bUIwO0DMANfgFZZllyfa1/9GPGzX0Unc46YP5ubJLdsFwH4HGPAT39nH7so3B8LA9pGtx7YQMwwh2ZD9Y2i2qAalDmv2a32ZlqdzKuddIkpODKQ89pwzZIb7VApUGvmUD3DdrRbKLrwn3UGb14E4pjIvkYAJvlM8hz3+N/AzmPfcrs+nmc5R29HmduWy/SuOYFKoygF09e/LKzGwZwZHB790iXoe65eX4tm8/ba77vXQzgrs07eo6RgWlzbCG7itsduAJ8GYA+PTRcdm3eUV79k68u7zz5jPLwlx4ot994a3nDa3++RET55JU39hwD86RApt8DDBOYdyYbMG7b3I0BdOzs7IMWVxdwlSqjLC0AtHE382R2bGDs4nLTUXPKsgmLelbpjkfLE7An7+wu9URuUOQYOiYIGz27QDHydh9m1glgY6bKoNJA0Ayeg/EBJRhsYrSoOwYDvdi4wugAwkjXRt7B6AZTduvZdWXWhHbCYGF0+W59+GxA5+E4Royc87VeM6tKO8Kw+bVkAG7c/ZQB16iZRbNg3mTiOvPxpgz6CAaF9vQiIIPvDF4NTDLoxpWLzs0yZv35ecYMaeUx5ZhPnl0xqXvItMvuMsKYcL/jUDOz5vbzEUS5XQ36DG4os12elN8samakWTg6bMPX3Z/tBqSeZhvpV+5rPhszA12HeljfHidefHkh0A8Eew5x36CtCH9ZNWVhuWjqJWVj5yBoXLMANEAXjGDrGuYQ5aHh8pk1W14QAN66ZqjnbEFcroAy/rdr2RtBfAbhtk29+d9+4x+Uw6YcWl7+4z9ejjr8qHL7Tbe1DODjd29oGUAfX+PXzQEIXe+dg91X3j01NFKe2Ny4gK+ZeWHbzszDlQGsUmV0peccQMCJJ+GbO68ZszEEAPk7L5U3A8Vki7FnknT8jt2k3hSAweUZv2rMwMXA0kbLR7qYAcNwEJ/ojQIGQQBAG3XedmEQ6V22sEcY6rzD2MbHjAvPkh7fHYdGm5h5xNCbUaWuZngyCwvAMyMLCOl3nI3BDu2UWT+DQjNvlJWDvV0Ps5p2XdoFCxAlHwN56kPe6M3G3PGfGRCY1bIrkDToIxh4g3nSYTNIPzevgciewAqucgNR8nH/NvB2jCh9ysy7gaUXBLCVXtSQB+mgQ7OCpJvdz/R3xrwZ6msPn9+TnmNt+y1wYLT9G+dHmoVnLjA7bcYZRtTt63LlfkEdfY6m6+12ZGxl9pp5ZMWk7kHQI52DoHHTDssl6ncEAwiJmXtmy3D5gzVbyjEfXNsD/I754Npyy51bWhDptL2pA6D59FCzK9fnAwIO2UE8LMDGc2woIV2YSwM78jOIxcXbxhduaY6FIU2OjXlic/MmkMumL2vBX/dtKhUAVqkymtIygBh+ABsTuydsXMMACCb6qwX4PKk63iq7VjCqgAXywk1oY583oJg5w1j4MGmzXI6nsjHAyNp9aPe268n/fquIGQDvLsYoGOQZ5HA/OjBrmllIxwPaYBpkrE6gCqPsN3FQf7cTxow6mh20YSUPM2Kwi9lYAzitH9fH7UD+ZlkMkNEJOoT1A+z0czMDjgzkzTK4Pfq54g28WSRkQOm+5re9kI/f5OFFAPo10MoMrNlzA267hAFKjA3a2n3fjKdDGwC0Htc8ZxCaF3u0rV3cLJi82HJbeUHmPsK8gd4A+O77HhfUxQsBu2IZx+5f7kOZQSXmzOV1zK/BfwbGXvQYkFPPJeMWl0+ccFF5WAyg2TC/r5d4Od6V69+e3TJcdm5uYgJv+eJgWbP+62Vkc/NKN96pCwP4VMfdCwPI/2y6YAeuXcBPC4CaffQuYb8VBDBpFhOX7vBgLxgkTQNVM5S8C/iamRf2vN1mxaSBegxMlSqjLGMiovz6qxe0hs87NzHmdp0Y5Pk6MTI22oA8Jn0bjRz/5BhBJnsm8lkHzG+fg000WwIA+LvfnFCeO/vons0OGH8bFoy42SMbaQwnTAvPGIg53snACMPiQHQbN8pvA2JjawbG7J6NIkyOGSgzr+RnMGLX3sDY7rtqDb4BUBhUMz6AIoMj0jtzTHfnJf3B7NfA2O47h80MU4esj7wpIjNoKycPtC5lM8E8Z8YQEGZXpkGwQRBlQmeATerBNfqXz10EeOfYQtoiL24MTgEcBlB2ZTs9u7q90HAMpGPuzBhSZ4B0BoLZ/W6wbtDpsQeD6YVDv/HiXcsGqHnBQB9z/OrS8eeVG46cuxuo9DzgjxdIBoy5T2dW3rrkXn7zRjb3ES9qVk1ZWK6a0QDAkQ4AhJXzWYDEym3b1IA33pnrM/rya9n85g2AXD5nEGbPLONzW3bfpGHXsQEbzJ8Baz4smg+soOML/bYTb0ShbBwE/ci6jeUTJ1xUZh0wvwfU113AVaqMrrRvAmFyZmLrxwSx48+Aza4fx2TBdHmXpkGNjQv/A2ByDI/ZIf7HOGK0DcScR44PBDCZ1SE2bXViRyiTdWNGwS5n7veB2mYZfOyEGQlPgN5VacNtl2+/mDIbRLt8zYZikL0phnKiWwwoYMYA3WnaDchfM3Y20nb92WiTHnWzay67OM2UGZAZ/Nnwe7cp/ffaw+e3IMJsH39dD3Rv16TBPH3A17zIuP6IeT2vussgLAOXvPPa/d392OPKv3lcGax5k4R1bGAGkCZeL4PWKw89p9x81Jz2OVjPM8f0vpEm90cDJQP3zLjTJ1dOHmgXEtQTfZkxJg23s2OGPad4bjBoxpPhI3TyOEK3S8Z133XsEwtyW/LsNTMvLI+v39AeA4P780kBOR8JY5DojSJ+V+8zW5o3eBjwkfa2TV3m7ymxct6FS/rEBcIgDg82byPxpo382jh2ELfAs/M9bzrxhhK7hAGr1HtkaFt5dP3G8skTl7b6Z4zVGMAqVUZX2nMAbbS90oX1MBtlw21gYmADk2BGzYaOVb1dqzxjtsOTMXGHXDeDt3LyQPmbgUPKk7/+xr6viTJLh1vY7iVYJbNnZl+oE/nDIGYXXnY5+72xPkPMxpeJ0GyI9YhuDerM+hgo+XfK5AB632u3YWY7ibWy+93sD4aR7wapxPtRRrNk5J1j98jX6RsIo+/cB/Pr3QwASPuGI+f2vKsXt5MXKNcfMa/ccOTcHqBAvSkroMRg2AuOlZO779btF6vqtBwKkZk2x276eevO3xlfBrEGWLDwlMf93YDPoNgLQLt8zagyPsyUkTcAmD7D0U958WX2kz5Cn6Zsjt1zfDFlRmd2LefQg9wOxBjznAEgeQAqHbtq8I2ngny/9e0/KB+Ydkl5aG3DAAJ+el7dlnbGwpT1uGKHel2xdqO2b98Y6jKExPrl6y2wE6vocwnN5uX3BMNUAkD5fdfgSN/yAk79PmAfS8Or8HZ1DoK+ZuaFuy0AKwNYpcroShsDiLHfE9Pm4PhsrG38syvJLBqAwLFAZm3I1+8j7ReQbsOQmSu79MwEZKaGswDNqJkdpJzZYFFOwOKZY7pn+Xl3r1lTDJfvt8Fy+tYrhj0bVxsg9OH4O4y2QaEBtcE7wNsA3O1nw2sG04aVtvcGE3Rt5iqzS5SB8AGzSpQZI3zt4fNbwGkAaFbTeuTokqsP6z2kmbqSthctBh7o07GE7t9mvWj7frF9fi4zp8SiZWbYrCTMl+Ni+Z17vFkl938DIo9lL/hcNgNBP+9YU9JD93xg1RwiQDpmKb1g9MLK7c2iJOvCoM/tSuiC9WL9uy5mI50Oz8Dg5nHj9jPwJZ3ZBy0ul01f1nEBb2uZt+e37ujZWAEwbDdsbOkyb7hie2LqxBLCxgHietzBKaYQkNcDDod6Xc0APccU+h2/Tpe0KZcZzBbIauOHX1W3qxO7ODK0rTy2fkO5btb7exYuKycPlIVjKwCsUmU0pWUAmdz8vl0bPLNITKSzDpjfsyvSBhRgZZemAZQNC4dCO9gaY5ZBHMyNQUIGi3avmblyOc2S2AD5tVRmPEjLO4cNBMzIYBRcZpgsAxcDRoMRjKfrZSbR+gRY8YxdzW4v2tK7mHHnGbTYLQNLiT4dU2g9ZzBowOL395pV8uTfbyFhZtDuam8YAEgsn3huT2xojmO1DrwwcN+gDrk/mAGmLiwO3P7cRxyg2yPnaTbUfZK2NqtLuj7bkfLYDZn7oeM+AX/WN8+hR8AcdTLDR/nzZgvy7+dCd1ubvSYvx/y6H+b6k7YZ3Azcl4xb3C5gKa+BpsdkZlApFyyigasBeb9xze8w3isnD/RsAgGYwfjlw5uf37qjx63KTtnh9Nc7aR1PCDADkMHO4eIlXbN+xP55g8pO5cGmEscYElto9i+DP8cSAjApE+8a3jU4UnZ0zgH8xAkXtXMR/fLCCfMqAKxSZRSljQHMgCEDKcdB2S1iI+YNDrjXmJRt+M24MAEAAB2jxf2O+wJ48ruPrfmnrSeWf73vkL6GznXLIMoGg++rpjTvQDb4c0zc8onntozVqikLW5eS2QZ+s2sruxINMDBCftduZvAMzG0AaR++057ZhZuNsYEmaZqVcr+gnPlwXbss0fvsgxa3bj+3h9k/wLX7icFDBpZ+nnvsPjSrafBl951ZQC8kVk1Z2O4ANwtmtnHp+PPaY0aogxkvAyLXh5AE9wvi6fyMdypz3iZAyew19QaI0iboBwaUtB0rZ4BMvgar7pdmQ9GzFycGxWbIvAnDMadecNFWtD/p+CgoyukNZhmUu2+hFxYtxPbmMcn9ftdvHpMOE/AChHnDfXb2QYu754LOuLg8vG5j2aYYQIDc81t39GwCAaT5GBe7VGHfeN6bNvw+YcAdO4B7wKJ3/PbJz691AwQ+v3VHCw6fFuCEvTQQNYP5/NYdXYYwuY0Bj2wCueUXL+iZo5ZNWFRdwFWqjLL0HATdPY+pNx7Gk7aNohkXJlrHxTHh233kSdX52AXsSdvgLU/8BjaenPkddox8bHztLqResBwwkJxtmEGXGUzSNXC1YfW5gwY41IWywL7mGCcDQI6rABRQH1ytBkd2n+UYTpfDQAbdmdEB7JlBpb2sc+vegN/vczWo6+da9U5TNjv0Y5a8kKA+Zo0BRRj7vLmBTQBmi+zmo1/Q/7lOzBd1hPXhY3aV530upPuHAW1mPe1WpHxmNL2JwkyX+yb3W+cum992Ypep+4d1hl48D+TFg/tXv/5GnQB+Hn95AeGFRXbB3nDk3LJi0kAPwMssuhcEDhPx4tLHOrGj22yeY4S9QPDiEx0yB6yacXF5fP2GMjK4recQZrtU+fgIlZ3akGEGjY/j6gBmT2zuum+f37qjhw103KDfyuEz/AwiYRQda2iA540luIvzUTA+3uYplRVg+eRQwwA+3HkVnFnWpePPqy7gKlVGWcZERLl8ylk9E6PZP4w8EyWrXr8ezsAuuwgxJGYSzBAwkdpYY1wAOsTmmdHBGBJHZZdU3j2LiwhjQhm9AgXoUQ67tl0e8rBuDIoc5E/5Zx3QjV/L7IMBSGYtnbcZIhtfDJl3Y2fwYECDLihDBodm0Qy4vDiA+USfBriO7XQsldsYwJndt+Tvnct2ZS6feG4b20dcoJkf+oPZaQMiM864Fc2uGoj5bRsGHbRDfgeuWWTHB3JP3mFuQGPgiF4yO2u22212/RHz2jGDjgHd9Av6pd/Qgu76sZMe/247L9gyMDXINEg1kGaXL3VH/4SB5AWm+6XBp4+4MTAlVCIv7LwpyvMNafO7d/d6oWEwTD1oKx9KvWLSQLls+rL2VXAtWBvqPRLFO4E5AiYf1gy48ts92BTyrMAXQMt/vTOXXcLbNvW6op8Rg8dRNM9t7W5YeW5rL4hrdylrE8twype0n9jcBZg8TxojHQbwqhkXtX1m9kHNeProlLMqAKzykpFZEfGliHg6mk5/evr9ls51f76c7vmpiPhMRPx9RPyviPhURBy4D2UYExFl7mu6u1INcJj4csyXV/C4Z715wLvoDBaYKLlmkOJVvF1fgBGDGjMQdsvaeAEmDXyyUTLrhxG94ci5rYHhXgChGTXq40OJKRdlMjjwXwMPAwUMDvqz0fFBy5RtybheIGIDbSbJDJ6P2Ln28Plt+5kJMlNiIOIDc7meGZMcYG/2xawdRpr77SqnXQzizUoB2Kw/QASG225x9xXAVWaTnbd1YTbWuuHj+DPS805wAyLGmJk7+kNmYfMmB7eD7zPA4jnAK7ufzcitmNTspkeP3O/yG4x6QefyUC+PdS+S/N39n34Cg7xiUncTEO3Gh3mF+gPmXDbGLYA2M4p57mKe8SH1dkMSyuH3m3u+yKwVf7l22fRl5bH1G8quoW09Gyxg4XwEC2wa/3MvQAtwyDNsKHlWwPFJMXgAQ9i7fCyL2T5vRHlua+/r5J7b2ruzt40LHOrd6NGzSWRLd+eydxh7Q8nTW4bLyOC29l3A1v3S8fVVcFVeWnJSRPyPiDgj9gwA74mI/6jPq9M990TEYEQcGxEzI+IbEXHrPpShjQFkAgO43HTUnNbo+4gXG2YDDq4ZxMBKMLk6Zs7Gmzw9qfcDDDAeuaz+n+92Q3qih02kTBhB0gdcZabGIGj1YQvaI2k4ngSXGgDDTKbfeGFA4frBQthYmVmBlTLwJHjextvMhZlI6pRdYgCKfkyOmUMApZlJgIjjQ7PBzHFlmdlxn7LLl+fd18ySGuiTLzr3gdRm02B/zA5lfff73wshnvVbQGg73spBvazfzJ75d8ALzJR1Tj183A332+3vvku/ZEwAfO2K92LPgNh9EJ0R90jZ7WoF0BkEmd01eGVBk9k19z30Yl27/flLaIUXKjxvNt96Navscvhd3SxgKb8XNmzwQQe4jhn3Vx56TvnECRc1r4LrMIDeedseiLy1u8kCwESsHOALlysxdS1gHOpl5sws+l2/fjUb5//5TEBv/AAoeoPJrsHe9wkDHJ/Y3M2r39l/3Jt3EHcBYLMJ5JqZF+62EPzwlLMrAKzykpQ9AcAvvMAzR3WeO0bX3hoR346In93LfHsOggag4d5lsgPkEPCMIcgB4WYLPKEDMHJguSdZT+aeqFdMGtjNdcRfHxybQY2/Y+jNnBgQGBD2A44GwBghAzkzVdl4m1VxzJnLYHYisw3Ow8yGAbf1BlNCfBSbCUjXDJ6ZIbvRMshHhxnM22BnwI4hpvwYVtfHuz8N/Nz+AHTaE7bW5wJSBoN4gwYbfD52M5OvDwh2O9N3cP3lPkDZ8sICvcB2+dget5MB4MDY7oYCAyUDUlhXxlVm3u2Od3sAoGG47PZ1f3a+Zo29I9wxnGahAUaAJY8bxzb2cynnurjemaFlkeX4O+awDDx93iOAPLdXHgOZufSCzItGQlC8C/iRdRvLzg4DyOYP78R9fuuO8tyW7oHK+WiXnYMj5cnBJ8pf3/u58s0115Xn1/9RGd78RI8LuOd9wEPdTRh2Hz+ZAKF/e04gzRs1YPdaJlF5+UxCu6LzPbiADQrJd2Swew6gF/ZLx59XdwFXecnKngDg/4qI5yPiLyLiuog4SL+fHRF/m575sYj4VjSs4t7ImIgolx48t4cN6Mc87GnixNBxfEqOPTNDAUuCsbB7z6xCZpJgLgB6BkoGG2ai7PbM4BSDZdbNbjmnadCA8c1uIAM9gxHH5WUwYjaKOnpCzGDIgNRuZwNdzk80OKc+/E978bzdcTZ0GcC6X2SwSN+YfdDi9nBvb+ZwfZ2uFwZZP8SsZfesX1NnQJ3BH21lxsrl8qYRg0PyyXp3SIFjYWFll088t+d8R7OumTXyIsAhA9Yv+jTI8rh03UnXbmBc4MREZvYug8oMcrKb24snjxn3V/SbdWqQ7AUP1w3yDZwpr120PJPDQZgjyIPyus3cpp6XMkNJGpnJ9yIDvXjOYBPIY+s3lOHOQdDeNOG3bHijBn/ZQPHcXZ8q//aRw0r57THt51srDyvfvPum3sOi9Qo3wBagjtFNkSsAACAASURBVN3H+YDnfDxL6+rdMlx+/9pPl2lvOKaMeeUry6tf9ZPlP735l8ojdz1YnhwaKY/evbFERLn2o9eU6W+cVn7i5S8vP//a15evfPH+ctdn7iyvP/p15RUHvKL84gknls1f2dSyjY4b3DU4UkYGt5WH1jYuYM8FS8efV2MAq7xkpR8A/LWIODUiXtf57c8i4qsR8aOd3y+OBhhmeT4iFu4hn5dHM7j4jA8BQLNQTIgYG7N1ngjNNHCcA2ALg2DmCiYBI2xj6vgsT964V7Lb0UfAGKC4PLh/mMTtSsOY+Hy7aw/vvp8y33vmmK6rEkNt44nRB6RmQ5GZLhs5gAQfNh3gmnJsnBmIZROauCXAHO3oeDw2Cpgt9POZ0bQ7j/K4LxiU0cZmm+zKpM0A/gYY2S3ttrKu3N9yOwIKsxvTrw1zW9lFTKycWS90lze0ACq8uacf6Ocvb3kBiOb+mY+kQRd5EebxkJlu9wn3OS92uO7jYpyez5E0ADRjbb26TxuE0r/NHHvRZz0DaM22e5HAjlyzj5kx9IYY2tvlNNj04ga2zgDb7eZ8KI/Zb/TOPWY2l088t1w36/1l47qNZcfm7T27d83YZYDmN4P87T03lW//9qvKtwX+ym+P6Vx7Vfnruz/V83aPp4ZG2oOf7drF5UreuIPbswe3dN80wm+fvOK6cuMV15fH1jxQ1t52d/nVE3+5HHnYkeWJTTvKI3c1APDQyYeUW6/9dLn3j+8tb3r9G8vrj35dOf6Y48oXP/1HZe1n15TJB08qv/Gu/9IeSeMNL7t0DMxVMy5q51L6S40BrPJSlX4AMMuUzn3/qfP9uwGAy2P3jSXlwgnz2snPEziG2IbSIMGrd7NFXpE7FigfO2EGzowBuxgxEjaqPIchybuGATyUH2NiQ2xXld2oGCy7ACmvjTducjM2V2snLsbW723FkNv9Rb7EHnnTiI2r3V3sqnWQvAG29Wc3sdkeA2fyMMPk3btmg9yWPh8NoEXgPO671Z2YOIL0c+yV28BuVTO+ZvYMOM28YqgBzeSfGS+7LX2P9WmXot2jBhEsdFZNWdi6HBk7Blj5k0GMmaW8scNxoysndwFTjqnEZc24M2tnEGO3uF2s7GQ1QMosKoDVC5fMTrrfGnyZ5Xf/zruiWeS4zswj9CEzbcw/Nxw5t6dveUw4PfS/dPx55Zajz+7p+3Y7m9n3cULLJiwqNx01Zzem0vGPKyYNlA9Mu6Q8sm5jeWLz9t4DleW6bTdviH3b1XH7fmvlYbuBP4PAf1t5eHlmaHv3vcDaENLG4GnXMSzhtk1dALptUze+j5hDH90CaBy8f3OJiHL37evKwx0A+JEPfLQFmNd/9BMlIsrtN97aAtJl5y8th0ya0rq9d6ruz2wZLts2by8b13ZfBWdGefnECgCrvDRlbwBgRMRfRcSCzv/fjQu4LwO4fOLc1gg5iJ1J1kbLk7bdITaABh6OocIYEJ9GnhhSu1YxcANjuwfm4r7Nrll/z0wb6RiEYPgoA+WzS867nM1y2rB4M4t1BfNodsZlQycYS4OvbFAyWLBRzcDVu0mXTejGudmo2zgafJAmBi4zjtand1Bm93R2iXmxYCNssOfruWxmps06GvDQz8y0UR67jEnLzLCZWACHmTYzRN5MYSYWdjjv/uXtLYAZ9GsdkT/9i7GBzulj6ACAiY7MdHoRRJ/miA3qRJlI12yoQZS9Ae6rXhx5seS+QH55oeFyAursqqWe1x8xr+ecQMagy2ZATRlgXD02GXtcz/GaxHX6NXIGdu4XbovsBaC9rpv1/vLY+g3lL762ved1bbBusHV//jUdotxxxf71fZ/rC/zy52/u+1z73LB2/3pn7m7v+h3q7kLGbcxz7ALecOcD5bS3nloOHj+hHPgfDiyvOOAVJSLK7/3O77Yu4Htu/WLrOr7tk39YIqJsvf9rrZv7yg9dXl415lU9B0T77STsAr5m5oU9C8VVUxaWC8bPrwCwyktS9gYA/r/RbPA4tfOdTSBTdc+vxnexCeSC8fN3i/1hUmMi7PcuULsQ7UJiAvY7gGEa7CbCQAA6mAjs5rGrkHTtimESN0NhAIELKserUWYDp+zyxIhlJsqMlZk5XEtmPeyys2vOTOiVh57T7io28Pu3z76y/NvNL28ZOhsuu/cMjgDwBuF2A9rFN+uA+W1+Zqdg03LgPO79zAQ73s/nJ/LJbKPBHvrM7ksMP6BmxaSuW9xAw67tfJwJ+dk9Tb8B8JsZAwhxn12MS8ef1+OmN6B3vOWyCYvKp197Vg+As6ua+vGsWfYMilx2M4FZZyygYOzcP/x3T6w3gNjtSv15G47jRM3Q2V1PW9BeBk1mv81EGtDhNjeT6LhJx/HRD+2F8MLCYSXu2+jD84PfU81vZtudX2aI7VG48tBzWgZweHB7y6zZDcor4LZt6j1rb9umkfLNNdftFQD85pprW2AJE8huXr+lA/aP17CRP0e/wEg+09kUcsikKWXmcbPKrTd8pnzlj+8tG+5YWyKifOrjN5TH79lQIqLce/tdrdv4859qAOD/t3GobNvUpHvlhz5WXnngmB63tg+TxgW8asbFPYz6ysn1XcBVXlpyYES8ofMpEfG+zv8Hd35bFRHHRcSkaNy+X4uIv4yGxUPuiYhNETE9Ik7o/L7Px8AsHNt1WzloH2BmNqWfAfOzTKZ+x69BmcETk6oZvxz7ZAbFhhkDYQDDM9nd5CB7XMRmMe2iNQDmHkBVZlgwtvmdlpkJM5jGmFB+gw+DjcywmpED+NhQ8pyP0+E6MXp2hdkNC+gDDAPWDXSWjj+vZzPBikkDZeKBb+mZxEnLbjIbXusFXVA294cMjqg/bdtvY1IGfgadZk4NMikX+qRMlBO2LbPFAFj05/ajrJSLvA0+KCsLDI4Q4rnMAK6cPNCGMvD+bepPm7kv250J4577H/c6xtH9IvfBZRMWte3tfPptuqFOHNVi0OV8s4uWvuwxQt/MQNtj37GafKx7g1bydQhFjnHMJw5Qf8rpfufflk1Y1B4E7RhAjnAB8LVs3NbhHvbuufV/tFcAcNvaW1vAx8aRYQE/0gOU5cOhfVYgAHLrg4MlIsodv3t7u5P387/7RyUiys1X3VAe6zCAa2+7uwV2f9wBgH+2YUsLQq/44MfKmFeO6dlR7CNvdg5t6zkI2v2ivgquyktJfiH6xONFs/v3gIhYG008379GxHBE3BgRY1MaPxUN4PuHiPi7iLg5vouDoC8YP7/HhWMjjRvJLrTsWmETggGhJ0sbKxusDBYAXxgqDqwFZGFsASnZ6GG0cznMnmDg8waSDEC5LxsUM5sASW+Q8buD0Z1dxWYAMcrkbdBqnWUQnBkR/gJEczC8GT7/DgCxMbUBXj6xu/HFGz0MkM1sUsd8Fp7ZEgw94Nm7xjG+maExSDfT5jdb9DtqxW3rTRu5jr7er6+7b8MyGuDzl7Ll8eF4TPc774IGgKKDzLSaeSSPbEApM21qfaB3u9y9AcTH4jg9L3ysV4M6s4ZmzTMYz0ArA/UVk7pv9nFeLEpdb48NyuFx7Xp4IePFiplCx6AS35nraEY8M5nLJiwqv//as8qqGReXR9ZtLN/YtL3dndvuvt3Sfa3bM1u6cXddF+32Tgzgq/YYA/itlYeXnZuf6DmkGTD4ZIfte1aAy3GAZgRbMNopx87NO8qrf/LV5Z0nn1EeXfNAue3GW8sbfu7nGwbwqhvK43c3DOD6DgP47Jbh8rmbPlsiogw+tKV1P8MA2v27bVMXcI4MbiuPr99QLpp6SatT2rkCwCpVRldaAIhBxljDODBIMzNjY4Kxu+moOT2GiskbJgCjBujBpeaYOIMFAy4fqeIdgNkgmokz42HXkY0Pz3MvdYaNsfsXwIGxpOw2EDZINjgY3AxAYXgMlFYLxO6JHc27GGGVMmtiV6tBXAbBNuLo0EDAby/JLkhAC0D46sMWlGsPn9/GbppRAiDbnUdd7c7FSFM22OdZB8zvYRvtxiRd6gGDl/NzXKs3FBm00RddXnRkcGOGHABhIGHATrvQXh4T1reZbhY8nFHo+DuXxUwq/RB3qvuWAbLZert3+W7dmr1zmjxDmQx+zboZAHojlQG58wdI8jG7674HWPbGIfqG6+HNObQ7CznnRVvTx82ae7HnseP43GtmXti8Cm5oW89hzDBwuE8dq/fclu4bNr7Z7gJ+1W7g79u//aryN3d/qnWnsgkEV7PPB/QOYH7ryWuoezQN5xXeduMflMOnHFpe/uMvL0cdflS54+YG4N1y1Q3lqx0X8D2fvbt1I9/2yeb3P98w1Kb58Q+tKmMOHNPjXmbX8s7BhgF8dP3G8okTLtrNbV9dwFWqjK6Mic4u4OyuZFLOcWAAP0CeGQiDN8CfJ2IbguUTzy03HTWnZ8KGLfP5bUz4dhn9/+y9aZhW1ZX3fZwFsRAREbCoopgHEURQGQpQo4nGqMEpoDIVIEgRTRscMIpR0tj0Y6RJDKSNj74x2om26XSbN4lmaBONMYlxyPzEWaPROGRwTDTr/VD1O/W7F7fK0x/qw5tzruu+Cu77DHuvvfZa//Vfa++zSY4QRwcoNcDj+a4ldDszADMQswPE+cDwATLsiEmR+20QtPmqEUu3SovSN+6FnABybIdhZtMO1+lIs0lc7xQ3MqDO0ECV8fRfOzYcJrLxKlRkTX0gqTWnQA0GvIDHDtcrpQ1AkauBoVN2Br15IYvTp5nh5ByDKQAj90f2lDVkgG0gbgbZrBL1c9ajnFKkLdSx8hzqSbnGWxI5yHIKmqCA+wBW/Lo/s9rohkGwa3nNnrnulnvxvcEn4+8AI88/A16zrB4rgy50n8CUvvqvZcM9rYfojJ9npt0svm1SHjPbFIN9vvv09PPiB7d/L5564KF4TG/OYHUtzBsf2MASzHWCwDfX530AR8SLX7u69q0dDz5Ws93LswaAqgF8Rud5JTL1id7wGWAKKPSr5vIr5+hX2X59ypXGuu9TDzxevgnkszNX1wD2BX1XRVu/CgBWR3V051GzETSGkUmJYceAYywNFJwCc8on1+w5asfBmRHEceZ9v2APbaw3Knp3mis7PhtoO2ezfwamdrY802ACp0zfcRB2ODiLnK6100EOruXKixEMePyKKsu5XhrKqzo9Dji27CjzvZye93YyXLemsXYPQafbvBrbY5uZWj6k9ri/AS5jaT2iLYy95X3FsDPimtGLa8CwHYzTgSxmcQBh0Amw84pXxsEBkdO065pr91vMYI12ZEbTfTaAtq7k1C1g2YDX7aFWEwCat3FxEMLcsw464GF+eP6ZnfbbXJh7fo8u7SEg9NtgHNQhCzOq6KADGdqF3F2L6Hdme8z53bpmZo92W69sD+mLWXXrlRnMT08/L+6+/c548oGHuure7q/drPm3AnEALG/B8tsHHo9nHng4nr395nj+vzreBPLU/Y+UNXsGltT+wTbyFo78Tl7Yx6cEPp/96WM1v9cDfl5QAuv43E8frXnPr1PNfl0d93hGwPFx7QNo8Lx+SJUCro7q6O6joSiKuLxlYekcYE0MAs1UMWE3j1yyVfrQqwkdibf2WBpXj15cE2VjWHEuToU5os+ACgBgho4awczqOcVrVhLD775e0/nu43XNXYyinZQXYdAGwEbuLwCM62F3vPdcvr+dlWuaDCCo1bLcDNwMDBhLj6P3NbPsGGMcrlejGuwaeNtZuv3oAc9FJzJzTH+cCrSjtywM2jODm8ET/3eqm9pIy5b/+1kG2mY8GTuuQf8YS6dIAa9mgM1887tZJKfC2AbGoMXBlkEQc8kByOpB7eVcc79ogzdgph3ol4G60/xnDVhVpkwtN+TKd9TOWU883hk8ZoBuILWuuSPdX69G1HPUgYLnn9PamX3NqeJ6gZfl7jFjDrtkwTbqrAkXxl233RmP3/9QPPvT2ncAexGGwRNgMC+YAERxH79+7e0+fu3aY3q2WUE2hIaZA6DlrWqeElAs32qi9xTznOd++mhNTaNrHJ998LEaJtCrgG0HNrRU28BUR3V099FQFEW09autgwJIeJuUeuyVU6d2xKb1MeyAGYrovflxBi+wRmaGcCQGemZrctrV7JRTQbAhmU3A0Rmk8DyvqKQ9XuxhVgyH5LS307zUxSFLgLSZHe5jh2gQ4f4ZQGQwhawNLu3API71xtqLLDy+ZvcMJjPb4ro1s0kuM8Bx1usrwMOAzoyP28iYui4SOdJus5EGVAYdgD6vNDaw4GPwTh8cgDjFmcGmQXpmt3m/NXMLgOmyBDN9ZkQdONG2eil72svCE3QiA6L8Kj63GVlaHw1KCXrQL6d7DdgNAjz/CTKcVcjzm+8dEPBxWtrz0kEAemOW1/PXz7VMsDWUDDCm65pXxJVTz4+7Ot8F7Pf7AqgeE0MG8+dUrOv1WLABOHMtIaDO9X5+48jTYvu4ljQw4JPXwQEUaa8ZwJpVww92MYbcy3sZwmKaKXxM5z52/+Px6H0Px7e//r34x4PX1Mht9aDqXcDVUR3dfTQUnRtBZxDi1FBOlZiJMEsF6IMBMEtgR2c2hr84Ci/2gEGyE7ADNCDzogEDPztlOwiDBl+Hg6HNOBKu94IW0sJmOAAu9dJNyJH+eLXnmsaVZX1T3lDYqTSDRIMmnmHQjQzNINE+g0CDNz/PewrmdJjH1M7UC4bcToMJj43ZX7OJeTWnU3MwrGa5MkOYAwv33f3JLI9BlmXnGsDMIhm08AwzsMgit8XfcZ3HyWw155LS9VttKKlg/mQmGcZs9aCujc0NLtFxj70ZStcIWi9I4ZtVRCe9cMNjZPbTtob+u9TC8gLUoWPUaJpVt50wS5774gDPgYT32lw9qL0EsQ5sczCF7iDf8yddGHd+48747QMP1V2RC8ACzBlEmRn8nYAg6VNv9PzE/bUpXs7xe3+9EbQZP34D+HEewC2ziTUM4oO1C08Ap64DNLv5TAKc1ABumHrBVjalYgCrozq69ygBIA4rv3bJbEUGb37ThIGXHYDTl4727PB5jlOUZgzsmHgOzgUjbzADK8JGrnb2ZlLMnvE79wDsmTFyahVH5PPdX6fU/BvXAyp5BvJyatngjOsMCHxvM3E4LfpmUJoBvOULUDD48pYYliV9NGj3vTLD57GxLAxUzchZB53a9bMBeGYSuIdBSR4vs3bcj2fyXANts6vI1Glp98e6Yn1CRmZQDTaRL4Akv1EHsOnaTrOXDnAIFgyIrY+uec3gzcwpYP7qztpK2gf4AlCaQbd+eVGKmXCPA7pNmh35IN+NkrlZPso+bBdsm3i2WVrbNI9b3qDe9odrvWgpzwWz5p885Lz47jfujEfv79gGxu/EhQF86CddQIw99/w+X4BZV9q09l3CT4vJA2Q+99NHy3Sz3zUMkAMcPvNgxwINAOjvOtO0T6T75zeI+JVu9IX6QM795b2P1QJPsYawiI/f/1B8/7bvxaemnbtVIF7VAFZHdXTv0VAURVzavLiGsTFIcuSe69bsSAxi6rEqTls5fWowZsdrJglj7BWgXjiS01te1Womx9E8joa2cD4GyexWBqkGFU7Bme3ByZnZweF5YYUdv0GTP04h4+BzOg5nyT3MyGJgM7ijjgr2AieYWT6DM8Z99aD28k0iud6qXiDg8TSzmRkiWBmf47pEs2q+B47Y4+xnGgQaYBoMcB3PZkxcK+p+wZ4xDjzTqctcIgCI3DKqrQYUGxhm+ZvtZfwNolicwv9ZmOGVw8xh2so8zGnezAbnlLNf3+VyD2cC6Fdrj6U1wNTyc1DhACAHk8iAFL6BKHIADDLGmTU02LS9crsMJDPryjypVz7CM7jXlRPOju9/7Y54+L7fdNTAabPnckGFmD2Yted++miZdoV1o/7PK369arhMKT/Y9SYQLxSpAXEJ1D2r/wNEfydQyf1o82O6JwtN/I7jp1O7YA29BczTDzwWv/7Jr+O7t/53nNPykXLssasVA1gd1dG9R0NRFPHhAV3AwStNM2jCwcICLOi7qmTZAByZNTMQMgNoBoXvvU8e9+N5ma3BeMBAZBbELAnG31upeG9B77tnpoDf2HsOWWD48x5xAEue4dSWGT2/ZQMWA1ngWHPabcuottg8cknp0JwSRVYG62bf7CjNoBpsucaQ8+0gnSrM/djQsrwEg2bFeLWXxwKQYGfsEoIto9rKtOCWUW3lilbGCh0BsBlUAw7569S9V6ZmoOGUuAGc07052DEotLx8jlPjBpNedGMnaPa2HvPLfV0m4XZ60YjBmedYPZ2vl3qlXw7Gcn+9SMhA0jpAjStjZ5BLn5nfDuY81wzOmDcG7/TTtgDAalBrAOqAl/+7PAA94zuCJINo6/GGls7tq5rPjC//041x//fvjYfueziefOChePS+h+PxBx6Kx+9/uOPzwEPxxAMPxZMPPBS/+cnD8UTn/x+//6F47P6H49H7Ho5H7nu4s46w45pH73s4Hrqv4y//f/z+hzt+77z2yc6/j9//cPzmJx33ePS+jnMeK6/pesZDnR/a8+t7u+73RGe7H+m8/vH7O9rjZz3a2T++55qudj5UtvWx+x+O39z367jn29+Pf//o5hqigLGtAGB1VEf3HuUiEDMqZhxshNc0drydw8Y7pyV9vo2mmR4bTgMrHDDskr8zwHIaxu2202TFLN9xD7+uqt4qSFgOb8ti52OHgpOplxYCyDrF7DSVwS7PBlTAODj9WI/5M2g9a0DXPn/1GA2AgQGS366CU8/b8JgBdLrS4wpgy0DEepTZNdoMe4JsnVYz8+K6NfTOxf+0z0X69ery8spNb3tjQOVUp1Pocxray++9wAEA4HpUs7gGxYwp7Czjyv3NoLN3opnAemNrHedZHkdkCghDb7kuzyeDfoN06737BzPoOeIAhGu9ZY3nhRk/+sS9aDdtNGPtgMwBRf7e5R8uWTCIRE7I3QCacWXOGFx6rm5oWR6fnHRO3PGlr8f3b/te3PmNO+Ou2+6M79/W8ffu2zs+37/tzvjuNzr+8v+7brsz7rztzvjB7d+rOY9z7uz89w9u/17c03nOD27/Xvzg9u/FXbruu9/oeo7vc/ftd8Y93+y69vu33Rl3fqPr2TzrTrW15vtvdH5uq213vv77qZ/fv+3O+MFt34vv3vrfsWXVv8aawV2stLME1UbQ1VEd3XuUNYA5LYeBy4syzHDZ2RDtY8ydHjGww0gC5nCApHFIvfHXTBcOnOvNeGGIzQAazJqB2jh8WVnb5nSiC8q9WhY5GCz6jSH+t52BmQVvCmwGMPeJNC2AzIDSDs/MnWsxXcdpRwyzZabJoNAONbOnjK8BrAGZAZ1/o38GeXwYE/qBXpgZMND1PZ0CtfO2QwekmKE201gPlCILyxe94Lt6jotx41lmWdEVrmvtsbRm3D0PXBNn+ZrlclCCvJkr/jfPZmERjLeDLQMuFjcZXJn19ZgZyFnnM9NsGdq+mPkzEKSfBmMAYsaJZ3B/v/7QwZRBtttnVt4BCgylz3F73KecBagXpH1y5Ir41CGr48qp58elU9bERZMvjM+0nhvnT7ow/mXa+XHl1PPj/EkXxmdnro5rZ58Tn525Oi6afGFcNPnCuHbWR+MzrefGZ1rPjU9PPy8unbIm/vHgNXH+pAvj/EkXxpVTO66/aPKF8Y8Hd9z7yqnnl+dsmHpBfKb13Lho8oVx1oSOcz49/by4cur5cdaEjnM3TL2gvIa2XTplTWyYekF5X9r92Zkd/fj09PNiw9QL4h8P7jjv09PPK7+7aPKFcemUjmvOn9T174smd7ZnxupY1fyREkij82a3KwBYHdXRvUfJADr9wca4pufN0GBAbRBtaDHuGHFH9xhr782G0a3HGDjlB3OW0zBO0QBa+B4Dw/YrvJUjAxCnwwAPbrvfMey0oYGDnZtZKbZjwQFSyM+HdjhFTv/pk1PFgEhfa0Ds9LqBiB0rxtcLAGBkXdPE7xhsg1WAADJ2raJrwjKrY+DoFHEGrQCTzHoCkBhLMz4AHXTTdVtmq+14rK/enHv1oPatVnnXA7WcawBPv9YP6UqDZvDkmlnPKd/PwNDAzQEE42ZZOv3N+BP4GBQbgHF/g+XcT2oYWWSF3ngxU66BRG4ZpDI2ZiU9vx1YWCYei00K1LyK1202A+7AzrqELtJGg84837MuIbumXkfWpK4z8MVGoiO5nWZ4s+30wq7MYnPvHBDl8g90BqCbdSpnMjLofjs7Z6DM/d1nZEwQvEmg2QxqBQCrozq69yjfBOLUoIGfJ7GdsxccMJmdArJxNmDxhLdBsvFj1aEZiXqAFKPuqBKD5P0CzRoBBgA6OAX3zUbZYAVj6fSWU9gYewCZnYDvZWYNeXGuHZANrJklwA/GNKfUfL4ZR9cGenycgsNYm22kXbkP3gvOepMdCE4L4AiAsiM3AFrT2FFq4I2H7Ri5n5/FbwaJZojqMXN2egYEtMX9vXr04vJVfwbODniQh8GuWVXArNP/1jlk7FS69cAMPM8yM55liS4Z9KLr3qrJgMdjYpkga65xqYZZTJ7lsg/uY9bam0XTzgy+aauDRe7JQhee5X4Y0LusgbFAPmcNWBXXdG6ajUwJKHgWNsaBk/9tfbPOY+PyIhjAJkAXhrNeQMCzbOcc+FonMpAzuDcba7vuMXZQ5Dpjs5/cywGtg1XPqwwwbQfNZNvuVzWA1VEd3XvULAK5akTXqj0XvZupsqFwKteT2ZPb9UJ2Ht7A104Nw2HmxYxBboeBZ94/z2yKDWwGuD7PRj9H+wZRjpYNajGoLIowg2JnYedtdsMgzIxTroPM6VwcISyGr+X5jC1pQQNRg0VkaueVwaxB3OaRS8rvAMR+fmZN7STXNK4s9a7e2BjU0EeAmAEFupRT2l61nUFBTqc6PWq9N7PswCHPD8vPztWMLP1GRmbqPCa0wylW6hvryTgHX2cNWFWWZJhhzHphSIOo3wAAIABJREFUeWSm1uAiBzLImmcSxFjOjBn3BsjBQPF8FpTRRwcnfl0gH+5z1oBVpW3huYw5/XBZieexAx4HQrTb4IaAwyDSDKEZNQcR2R762Wa/rOsOUs3IZpbdTDD/tx7RbgfnyNPt5LzMLHsMkKmzAcwpl0F4nGxbCEZsU6yLyPbS5sUVAKyO6ujGo6EoijivcclWjsQ1Na7rwSHYOdpg5q1I7Gzs5O3seYYXJ7gwPTsfM2dmnQxUbdTeKRXovvAMp5Mxfhg3rvcbJzJrZ1bPkXg20Bl4OjViR2GZ8ztgF6BsltWgxODPjsIpZRwP7aM/jCfG269AM8NlFiHL0aDCRh8HmNk7g2DSimalzFC4FjTL2uzWFcPOqKlPtS4ilzWNXawxYILfcxmCddfACd00CHO6jv4DGPxbvrd1xcytAd2CvqvKrVbQC1hPjyt9w9kyfxhnQAeyNptO3WAG55mV8irtdc1dqX3r9+aRS2oYZzP3HuP8yjnamee0gZZZfOuXbZYBNfewDbCd8nzLTFpmrh0c0kaCGjPkZv25pwNQ10mbPfV85Br01kwuMjMjmoMD2FfGysE07WIBnplIdNnBEjrkuUh623L3huYGvLSfuVGlgKujOrr3KBeBeHUiThajY+NhtosJ7ag/gwH+urYMQOZVwtzb7/jMEbKZOdejGAQCBDCiOBkDCPqTAY5TQIBQb61h5sHsVJaPwYQjahf2O3UNWHCaLaetMvN4zejFpdG2Mc7pcDsUfjPTZfCME7WBN9NBOs7tQm7eEsagKQMNHJ7HyWDVgYXladbFjpJtY2g7z6FvgEiPo50jug4AZ+yd5jUrbTBkZgX5GqCizzg/10Wa0TaARzcyEMyMpMEy7TNDbcBrgMm9zHBlR2zwaHDOX/TMaeg8X2mLQVq2IX6WA7h6QZVTyvmadc0raupqkWGuM3YgRvtgurKsHYDlFDRz23OST07FW97sMED6Gl21LTOwY1xzgODgy8+yrfN4OzVvIGv5O6tD31zPaICIffK4OrCwLNx/7u8V1GaZq42gq6M6uvdoKIoilvevdTxMUgMOOw1HzBR9u57JzsKAoR4r+HbRbmY+AFncA0NugJidstlFsyCwlN7mwwCTCJi2ebsUA0A7JBvz7IjsKDDG3qImAzQ7SgMe9/OqEUtrXg3nNBZ1ak5HZmeVF7ngdDOocZoNUGgWAMdgnTCAtnMwqEAPMmuWmUHkAoBbP2RFzQpuBxnIgufhxAyEOM9gMaec+TfnZIbRQDmPIc4bAGng4VSiU6web4OSzHTTNi+MsUzXNHak9zePXFKz5yXXOk3ntjNGZhORE/33WzcygHa2wIEkQBH9YDGMxyinaZGHWTfay7hYV9EPBzOMPe3aMqqtBvwa4Hie2I5Z/z2vkLeZ4wzw3HYHrXy2jGrb6u0j2FH3gz7m7IsDM+7hhTeZTTRry2/e5/CKYWeU+rZ55JKaMc62GOBHiQtBvG2y9dbzhGc5ELIeVzWA1VEd3XuUNYD1HKVZE4weE96gzNs9ZDbOLItTOzboGD+icLMEuXiZ9mVQZoOXwaVTlxh8vxM0A0JAj2sWzTqYAcp/zTBsHrmkZssXA6SrRiytMczIzSuwM1tGDZhTSq4Rs6HN0b/TMgYFWV52GP6/nRVbmWRAD7OFgzUwBNg4Dc9efwYoPp8+m9l1uwwcXd/X1OvImpS3dTKn0w0KzIRkxoX0pVP/ABE7a9dNGSDZKXrTZDtV17iapfb9DGTMdOb0np0ygDKPO9eZteEay9eBh5m+zBh6bJwZyGw0zKhBeAZbOdi0vBy4XTtmUWkPbHd8T9rveWWAZsYR3XSql7Hxd377ihku1+PSdua6ddggzul5Uro5qKHdDpDReweb3M8Aj3H2femjF9NY3q6nRC4EMAayyMPjnK/LthvQbpb0rAGr4mOD2yoAWB3V0Y1H+So4DGJOXbARrY0wRp9I0s7IzEGuiaM+xMAlR6Y2ZhjqekbbBpE2OYI34+Y0gwvODRJzmsQANgMt10y5nThCs2TeR5Hn27EYKNhRemX0pnQPswbZYbrfMGVeqWmm9qoRS9+2uJ1/Z7bW9ZBmy8xs0Q6AAAAHUEc/YJrNbjoFVc9xIBsDTjtTMw92gpYt/bJumWHMaVozxBkEud9mIGkLfeL5Zmk8jyw3O3XkhlPleU4T0yecut9yYx2i5iuDMfTEuuF56QDAoA0Az3Y8TkHSH8aK71t7LK25H8CCeWGWy1s2AboM2C0bM5sEfdwX8I5eWW4GgTn16tIGs4v1gieDHwcGXiCCfjiFS/9dHoLtfLs5Zn1GLjzHpQvIge9ps3XAAVt+jkF4tlmAOIJ6M4D1gkmXJmwavmyrvqxtOrMCgNVRHd18lItAzJh4krueyYbJjJMZJke/XtTwdqAPI4HDBcDgwO0wzeTwm6P3DOrsiPjNHxtGLxTBULvddlSAGkfhTv0iJzsbG3cDHa9idB9g+ugvDt2yQ75O3duoAti8hyHsiwElwMDbxeDkDQzMYlqGOKA8ToyjmWCDLjtBjw9OiX9nMGl5cY+cZjNgMOAwk+XzvQk415qZNeg2Y8kYOCXplGZ2rk6J47T9lgsAGf2l78gQhtigGnBoRtu1pdYbzw8HF9wfOZkRpF0GpMwZ2uLNx/1vgiXrEmDb4JvveS5zwGwnvzHf+beZXhgt5q+DMuRBiYdtg/XT8snBlVO6BFTokwMj7uNtXpjTAG7f10EB85b9GtF75OTSl5xtyaDU89F6jw0w82mZO0Dh/g7yPf88Zp4r2CbbbMbYuoGsqhRwdVRH9x7lIpDMQjCJWc2GAcEBMbmp9Vo9qL3G+JI2y2ksG21ASwYIPN+FydyH/zvFY5bNhs/X4VAxYhg4O0anLTBWNqLcj/YbiNhRY6idLsoAlOs2JmbG7ECWiVM7RN9mKZG367Co6QGs4MDcDjsf13MhG6dsLGcDPDOX1h3O94pewIFXMCM/OzHXHObUlJ1wvm8+xyDMOk4frh2zqNQLM0Ur+neNtWXq+1I7ZXBnwJaDKI+nxz+zPQbCZg/tTGlLZoOYAwBTdMPMYQZOtMusMm1jPJwuBkx4vjOWliHfe6GV2UmzqAZ7jL/LKDiHecBYsy+dmTqXbThYsfwM2FwawNhajg6CyDSsa+4q5XCpSp47BEl5jlmf6wVWtpsr+nfsWWhg5jmT9Y1+eXNqg2cv0MiBGPLMwarBptlBxhCQWq+f2HTmIYDf/a8WgVRHdXTv0VAURZwzaGlpoHCcpvDrpcyc7iIVbOOH8TfA4To7FYysnYjfBuDfcSqwcN6g2qDVQMXXuejeBfmOjM1EmC1xGzBaABwzGzgXAyMMJrVzGD4As40lTsXgyQDLTK3ZMcvOAJp+MKaAU4MNj5kBuMEvbfS44cyvHbOoBOUuC+DZZj7NttiB8QxkQ5H5msaVJXjByaxpXFmzSAkwg37yhgozjQZuXu1t1sljsKBvbT2WC/8NmvOKRoMI+mgWyWNiOXKNF8+gz2adnEb3mPmZDjb8vLz3pvWaVJ7vB9jZJHY0M6foi8GmazsJpHJAZNBDOwB2LpMg6PSbR96O2XXQmGtffY7b7OBh/ZCuxVGb6oBUxsfpXvTQOogcHLx4LPn4ulx7agZ988glNSUnDgoMwJEt88gBie0ENgpdyKw6waUDVq7JbCO/e77TfjPfBtms3LfcVw9qr1LA1VEd3XzUrALOBpMo0RMVI+V6PpwYjoRNeu34+euaL7N4GCKnWXBSTrvBJJgBwuDYCGMUMYAYT6fOAFmkahxxA7LMYjhKdpobR+mo2MDV20ZgpDGkmW1Dpq4D87Vug1fvOSo3g2C20mDP4BRnQJs9ngZF9M0A0QCT8cxF/QBfp4vsfHEgcxq6tjLJTA7nbxTwM8NSj9U0e2mQ6ZpKs8wea+vQuubaFZ5msOmv28yzuEfWabNndpDuE3oK425drgd87FD5jdWvZifNpF0zenFNGpOgyDrCXGasmBcANLff9sLAZ0PL8prNxw1UHTTlgMQMnFdee1y4JjPx1L76N7PztM8BJH8zIOI7zwX0K7PDBkj0xQwi9/Ic8ZzDFlkPraeWoe2AAbYZbPpn0GqddJC5ZVRbDUvslcUG677OdswBKZu1O0DO9su6s6BvtQ9gdVRHdx/lq+AcfdoY4nhgezBmTgtn52XA4N+dsrKRt6PHKOCYMDYYOK8kzpEtz8vpQYMOnmVQ6YjWKRIbV29qbFBrJ+xCbDOodp5mWjknA0/a6P7zTL/dgfPpu5lWQIprbJCF98yz87MxNlOEjNy/7HgtCxfSM96AD28z4fbkWrRNnYyPAxJKDuqNj+vmNiWGifFw2tS1ntZD634e4w0ty2vAo2s/YT5d4J6DBkCkWUkD/QxsPBfWNtUu2kEuMDWev/TTrLvZSLNaBmHc1ww9vxnEehW4gyt03UBlkwIjs622Ha5j9H3dZn9yvSf67LS975H74PljW4asrDu0mzpHroFpdhCDfm4euaQmi2G2zEwuuuYUK/Pe40d7sMFkQQBdzE3bGXTFgZwDt1zygNxdt207aftHm50mziUzXnzi53o+on/8betXAcDqqI7uPMoaQKcQ/DdHoU692HjZSbrQF+PnKNYGjaj36tGLy/s62vV9MSpmcXge7/TMDganbWYEI4ZxzE6dPjriN0ikD2bRaJedjFNJdugGWRhdrs8OyJH4hpbl5Ya3ZhfMymGYDQjsbL2NST0AbtACsDFzhLz5PW9hgQzcLjsYMzukWT3eZmfsBA0qMouRmS2zr4wpOuN+GGzbAbOC1P3keaQhAZJ5LKy36CPnek4BIHDc3taoHqB2+hm5uz6N57je1P934EaqNQdSXrCAXKzXBpNOUbqP3B8ZZPbV4MTsLucA1qitoy2Mid9MYvACGAfcGExm3QHAOtg12+gxcTmDdSwHnw6O/UpKlwUAdlxHbRuQ567LPJCbmUQHVp4rthHMT8uH/5tJNnOLXa/HxDtwtk1zAGtbZobdTKB1kntWi0Cqozq69yhTwI7UDPDsNA2WOOcTLSvio4dcECsPvSSWTf5YnLNv17YQLkh3OsFGOUfEfFy0v665o37OUXOOLvNqNrNpAEEMJs/OKUKcrJ2CHZRZRgydDbBZQAwqbIDBIffLq6QBAWY1DKTsIJEB51AnlIFIBk9mbOiLmQMDdf4NkwCL5etgvezMzHoAwJxGNBNLX7wq8e3qpwxKzc7hJF0b5vSeQZvlaWbIYMAres2O8W/3gW1NXO9Eex0A+c0ozCHGwfPOwGJd84po6nVk2Q7rqUEA7Ycdht2xvHPJhEEBfWdOGQBaB2hn3iSefjh1ic4DCNE3P9OgG2DkeUsfsi5l5tC/m+lmbmfbY9vidLazGgB0gzgztOg7bTLLCQjDZmD/DDT5a8Bnu0GbzMbWswMG6PVe90faG3nUC2CpsczjYoCXFxEB4i0HmPz8nLMGrCrLEZC35xXPntunYgCrozq68yg3gjbDYCdlx8rbJzjntEMujXHtN0XTubeWn5Erb46zZ11U49TMNG0avqx8I4CNuNlFjAJ/+Z7o/4phZ8QnWlZE+5QL49iDPxHzJlwcl6dI24yTDU2uV6F9edEJRti1jI6azUDZIbs/OO78OrAMds1Aug4tgzc7ODNNpIBYtJBTtHZ+GG6cNLWQZhnXNp1ZU7Nl5sfAyM6R39w3gJRBvxkDf5A/Do10MX2ATUUPkSPOyqCG75C3WRru7aDAoIjvudZpdffVKTQzWQYDBAMOoKzrtMtpY+RD/wFMrl01G5WBb06PWp7WQcC72SKPC/ptVheG0PN5TWNX/asZRO8IkPvlICynbJm79MfBE2MO0MAeALYAQcgT8JMDEmTD2BsgWbdorzMang8GZIwr/fN3Oeh18OZSj3rzl+f5O9qFjtBf9L/ePLBddOrVzCzXGrRvlCwddJjFtK7lzf4NEHm2gzv0bG3TmVUKuDqqo5uPsgZwy6i20uCTbgFEbWjpeJ2S6wDbpl0STav/q+MjAMh3S6dfUjpEQOPmkUtqHI6j45zGNMNGOgincPbsj8WYBDzHtN8US6dfslVUz9+rRiwt68+ctjZzZyYEB4mBthOxU8UpmBlYP2RFXDVySSyedFHMOmBdfPigNfGJltoUHW10ugijaZZzYydgttzcTht7OzIALyks2onxdzrGTGRm21hxbeAGM2Hn5HvXA5/ejNeOjOd4IQpOA52kjYyHgad1xW20HJzOBUAAmM3+Of3F+VtGtdUERX6jBoEM+pPTkR4Hg0D02avIDb5gxOifZWLwmedKPRDHvwneDPIBIOiPmW7a7joyAz9sBHqXV64beKHjBuw5kHIw43lkhjP/ZgbX4CkDFsbd7JpZODO4sJCMg+vd0B1kbqbY6XIz6WZE3R7Lw0DS88Ag1HPDcx0ZsEo6L6RjvHMbGH+fnzMAgEH2LTx/8Mpon3JhzDmkI+i+dEjXdcgUfeGZlK14n0oW3LnEZvWgah/A6qiO7j4aiqKIh04dGc8uGhPPLhoTz8wfF79bODZ+t3BsPDN/XPx23oR48pQD4omTJ8WTpxwQv503IR47ZVIc+A9f2Br8CQROOvuGuO/Iw+K+w4+IH89+b9x76JHx49nvjR/Pfm/8aNb74sez3xvfOeT4+M4hx8d3px0b3zpoTtx+0Alx+0EnxNcOPClunXRK3DblxPjKxLlxy4R58Z8HfCi+OP70WHP4Be8IPM+edVFsHL4sPj92YWwZ1VbjbLeMaotrxywqawZhEviYDbx2zKKSDfCWIYDhzSOXlO/0pH6RdOPS6ZfE6DoA9cOzLi6ZLEBpPaexrnlFDfix48Dx+r2q/GbWju/NVABAbeRhauwszF6ZXbEMcEKrB9W+3eSa0YtLp2G5GZCZwfJbSmBDAVs4eoMrzjXwBqy7jQZHfE8wwbjZyTlltXH4snKrCupHqdczA2YAYpCLbGHmnIY1UPOYADQBXYCOemNjQApAMZBCJgRsZnZw2N4uxAyvdcaMtHUUkGmwyz2zThqAGLQu6LsqPjxwVXzk4DVx+ozLYt6Ei+OfNW4GIcjITBU64XljQMEzzCjSNnTr0iErYvGki2Lu9HWxbPLHYvk+W78Ng+AB/TVIRl6WASDHgR7XOmWc7YqDQuTKPTYOX1aW2pw+47L4yMFr4qLmLhYwZwMMKtElM8Mu2XCJB/J2WQeAd+n0S2JssmljO20a7TBY36j5m9lqp/G9jc4nWhZVALA6qqMbj4aiKOK5Qb3i9SG7x2vDdo/XRvSOV0f3jlfH7REvzhsSL65siRfOGB4vrBgaf5i3b7w8o1/87LAx8eH3/0Os+MC5seT4NTH/hLXxoZMvixPmro9jT/tfccSiT0XTubfGN858b7xwxvCOeyweGi8ubY7n24bH79tGxHNto+p+AJ78fWruxHji5Enx1NyJHcDzI+8MPA/8yA3xi2Na45dHt8bP3js7Hjzy0HjwyEPj5++bFQ8ccVj8aNb74q4Zx8Tdre+PH816X9w5/QPxg9aj47vTjo27ZhwT3znk+PjPAz4Ud0w9Lm6bcmLcOumU+Prkk+LLE+fFVyedHLdOOiWuG7swbt7/1Lhlwry4cb/5cd3YhfGViXPjxv3mx0XvOe8dAWr7zItL475lVFtcN3ZhXDd2YVwzenFcPXpx+RfWj204ALOkvjaPXBLXj1tQglcvaAGcXTHsjLh69OK4asTSuG7swvI6Mxc4JIy9nZmvx1nMaWivOWdF/64FOYBhb/DsdBXglxW+ODocA2AT54CzMlNj9paNr2EXcFZ2PE7buz7LKUCnTwEaBkM4T0Ax7d/Qsrxkt3FmABYcG/83aMwMOIA+s0buj1c2X96yPE7e/+I4fcZl8dFDLoiLmrsW58BkwVDSRqcOAQTUZflZmXEy8GE8M3j2dTlgcfoRXVnTuDLmHnzpViz+2PabYsG0j9cwwBuH1y7QMrubVzHTBzP2eSECY3/GjPqAZu7Bl5b9dVDhffHMVDLursnLIC+XkXAvtl0BLBlYG1C9XVsXTPt4Ob6AYsAvfWAOO+XqcYJpzJuy0+Yrhp0RZ8/+2DvatBWta+OqEUvLjaqZ09d0PhdZbGhZHteOWRSbhi+La0YvLmWxoWV5XD16cVzavLgCgNVRHd14NBRFEX8siog6nwcOmBH3zDwq7j30yLj30CPjibGj656XP8/u1ieazr01/nfb6fHbeRPiqbkT45WmPWrO+dv2Rfxtx+3irV22jzd77BBv9tox3mzYKV6d0CeeXzYinl82ogSPb7T0jL809Yhnh+wd/zVyenx5zMy4adxh8YX9j4xrDzg6rj7w2PjMlA/Gexf+SwfwbD8yXlgxNF5c0BSvtPaNl2ftFX+etXf8+bC940+HDYg/Hdk//njEoPjTUQPjD0fvGy+9vzGeWzSyBoA+N29kPPfBEfHsCSPiuZNHxDMnjY6nT9wvnjph/3h63th47MRJ8dt5E+LpU8fHEydPioc/eHA8evKBceBHbnhXZvRnR8+MXx8zIx488tB44IjD4p6ZR8Xdre+P+w4/Iu47/Ii4/z2Hxw9aj467W98fd804Jr477di4u/X9JWN6x9Tj4rvTjo3bppwYtx90Qnx10snx5Ynz4lsHzSkB6+fHLowbxs2Pm/c/Nb44/vT42oEnxVcmzi3B6vXjFsQN4+bH9eMWxBfHnx6bhnds6HzjfvNjy6i2uGn8aXHN6MVx/bgFcfXoxXHLhHklOAUA8W+AJQCQdDvOj7rPzSOXlL/jjHFQOAM7R4AR113TeS2Aj3u7xMAreM3iGgxy33XNK8o+4MgNMM1C0b5NAhlOnWU2kPvm9zi73pJ78W+nl80gAng2Dl8WbdPqg4GzZ3+slIeBPc91et4sIM7ebKFZODNggGe+BzDDZHv8DSgNjja0LI+VMy9+R0DRNu2ScqwAJIyvyzYMVLzFDqzXuuauTdV9v3crXwEEXjHsjBJA0h9kRrBC/2kPugCju7ET7Jjl5Vwzx2b1rx69OK4dsyiuGb042rdBVsib+cFYIu/1Qzr0/AujT4/PDT09/nfLqXFN87z4/JAPxbVNp8S/t3ww/q1pTny5+di4fuDx8YV9jy/be82YRTF+1Zfi+Hn/FO3HnBMfOersOPfIlbHmPctj7WFL4rJZC+PKQz4UP9zrgHhgr/3jniEz4isT58ZN40+Lm8afFp8fuzAe6zs0ntxjcPy2d2M823tAPLv7PvFcr/7xYq+94sWefeNPPXvHKz16xXeHHVQBwOqojm483hEAfm7fU0rHe+2YRXF7v9ZtAoBPNvSLpnNvjX+afXZcP25B3DJhXjzW0LRN1/6u/+D40az3xd2t7497Zh4V97/n8Hhzhx226drlx54XTefeGlcvXBCPnjAlnj18xDZdF0URvz99eDy/bET8fkkHEHz1wD7ves3ftiviLwN27QCbK1vitlVHRNO5t8bXhx8cT/TuH4/0GRC/2XPf+EW/5vhp/6Fx34Dh8eOBo+LFgX3iLwN7xJ9m71Oyq88vGxEvLB4arw/dPV4fvnu8NqIhXh3RO14d1TteHbNHvLbfHvHq+D7xyvg945X9+8YLH2opU/ZPn75fPHvsiPjjgQPijwftE3+YPDD+MGVQvHBgU7wwpSleOKgpnj+4OZ6f2hzPTR8aT55yQPl57KQD44nDx8czraPiqelj4umZo+O3s8bEk63j4rEZE+KJWePj0ZkHxKMzD4hH3nNgPHTcIfGLo2bGz947O+47/Ij46YzW+NWsqfGrQ6fGz2dPj5/OmhkPzpwdD86eFQ8eOisePGxW3DvziLh7xtHxg9ajS2B75/QPxN2t7487ph4X98w8Ku6ZeVR8d9qx8e2DP1hTDvCtg+bEdw45Pn7QenR8++APxtcnnxRfO/Ck+Oqkk+O2KSfGLRPmxdcOPClu3v/Usmzgawd2MLZfmTg3bp10SnztwJPKcgLOu2XCvLhp/Glx66RT4ovjT48vT5wXt0yYFzfvf2p87cAOAH316MVx3diFJdN7w7j5ccuEeeV9OP+6sQvji+NPj1smzIvNI5eUwPmL40+PzSOXxI37zS8d+uc7Gd8tozrqbq8WyL5h3PyS/eX5N4ybXwLvC96l/OGjh36sZIa/OP702DKqLW7cb34JjAFJW0a1xefHLqxZ1EXbPj92YVkicf24BXHViKXx+bELY/2Qrj0c1zWviOvGLozrxy0o+2WQA6MNCNk8cknJ/Fw9enEHgH2HIGm/9i/F/+5s3+fHLuxgK0cujqtHLYp/G3da/D9j5pepfJimG0bOi2uHnhbXDj01rm05Nf5j1Alx/dBT4tZRx8dNQ0+ML7WcEF8ZdnzcNHZu7LfqS+Xzx531xTju1H+OOfMujxPnro9TTl4XbcdeGHcNnR13NB8aPxo6Pe5qmhnfaZwdN4w9Pa4ftyBu3v/UuHn/U+OesYfGvfseFD8eOCUe3HdSPDhoUjw48ID4+cAJ8eA+E+M3A8fGI4NGx48bD45bJsyLr0/u0NvbDzohHt53TDy+V0s83ndIPL3X4Hiqz+B4uk9jPLPHoHh2j4Hx+z32ied77x2rj/pwjawmtH8hftGvOX7dd3A81GdQPNmwd7y2c494Y+dd4i877Rx/3XHHeHOHHeKt7bePBydNLwP4B444LB4dNW6bbOFfd9k5Hjzy0Pjl0a1x4wmnRdO5t8Z/jpqxTde+PGTPeOykAzvsyskdQfJbO2+b/X78kIEVAKyO6ujGo6Eoilg/aG6s2WthXDVoXlyz78lx3aAT4l/3mRP/3FS7ncuNQ06ML/c9LL6+18y4rHVRXDprUVzeenpcMW1ubDrkpNgy+fi4ZtIxsfGQk2PMypvinH3bSwdw956T4vEeg+LxXQbE4zv1j9/tsle8sHOfeHGn3vHHHXvFyzv0jNd22CXu3WN8rGlcGdd1Op11zSvize223yYDsuTayZimAAAgAElEQVT4NdF07q1xWes5HWncYYdvMwD878kfKJm1O6YeF48OHLltBq9P7zLVvHne0mg699a4f5/h23TtH8YN6GART9+v43PCthnoKIr4w/GN8fslI0vQ+qfD9tmm697aeft4qX1IPL9sRLzU3pHif33k7tt07RvDd+tI568YWn7e6rltxv3Ps/qX7X1+2Yh4cU5zBwu8w3bxtx07Pm/ttH3HZ+ft461dto+3dt0h3tx1h3juQx0lA9Sp/vGQAfFmr53ir712ir/uvnPnZ5f4a++Oz186P68O7l3KFrb25RF94409e8Qbe/aMN/r2jNf77hZv7NXx9/W+u8Xre+0Wr/frFc8fMDieOHlSPDLnoHji5Enx6Acnx6t77x6v9muIV/duiNf67x6v7N07Xt274/+v7N27/Dwxa3w8esKUeGTOQfGLo2bGU7PGxsv994g/99uz/LzSf494ee8+8XL/PvFy/z3i5f594s/77BmPzDkofn3MjPj1MTPiF0fNjGfGDeu4du8943tDJsS3WyaVn+8M6fj895AD4sqpp8Sks2+IX35gevzm2Knxi6NmxkuD+sfLe+0Rf+67R7zMZ8+Ozyt9e8fLfXrHy3v2jicmjo1fHt0aP3/frPjl0a3xi5lT4+XeDfFy74Z4pXdDvNp793i1Yfd4taFXvNbQK17dvePz2u67xc+nT++45qiZ8YujZsYT+42J13v2iNd79Ii/9Nwl3uixa7zRY5f4y667xBu77hKv7Nojnt2tT/xkwMitwN9/jpoRL++0a7y64y7x5vbbx9+2267jk3TphcED45dHt5b9/PUxM+Kt7bfbJj28a8b0mmeecsontnnOPTanI2B69IQp8cTJk+KPo/tv03Wv7d0rnj59v3hq7sRyvv+lz67bdO36mfNr2jux/Qvb3N4Xj2+KF84YXmZT/nzotrX3rV23L0t/vtB+UjSde2v8+9jZ22YjRuzWFdB2ZnDe6vH2NuJvRYcNeGvH7eOJqQOiKCoAWB1/H0drURT/VRTF00WH0h+Xft+uKIqPF0XxTFEUrxVF8c2iKIanc/YsiuILRVH8qSiKPxRF8bmiKHr9X7ShfBewU1+s5qImhBQDEfeaxpVxxox3TqMsmPbxsr7KKxi9EMCF7tR0UX9Eymjj8GXxqZZFceXgRfFP+y6IwxZcFTOWfDYOXfyZOHLhpjh6/pVx/Kkb4sS562PCyutjbPtNcXln6uXKxgXxjf6z47/6zo7b+7XGV/vMiG/vOTXu7HtQ3NFnSnxvjwPjh30mxr199o/PjVpY1hhdNWJpfGvQ7PhVr2Hx8O5D4pFeTfFQz6Z4vOe+8VTPgfF0j33i6V33jt/t0i9+0XtkmfK5rPWcaDr31rijeWI813OPeGnXXvHHnXvGqzvuEm9sv2O8VdQ6qbv3mhw3jT+tZJG+NeED22zcH5g4I24/6IS4Z+ZRcdeMY+JnQydv03V/3Wmn+Pn7ZpXO/mfvnR0vDdw2x/CnffvGYycdGE+eckA8NXdiPHnKAfHmLjtumzM6ZHCZXn9m/rj4/TFDt7mvz8/rcijPLxsRrxzUd5uue7Pvzh1AtfO6F1e2xF8GbZvjfW1i73hxZUu81D6k4x7LWra5vX86bkD53BdXtsSfj942+f5t+6IE1i+1D4k/fLgpXhvXe5uu/ebQydF07q1x26ojSpD+Zu9tG5uXp/XrYKI7Py+e0rzNfX1pbmO8uLKllNXLrXtt03WP9+6/FQD8xvCDt21sxjbE75eM7Grvypb42w7bBgDvOHpqzTNPnLt+m/v6wuKhJbh5cWVLvDJxz2267i/79CjbSsD21367bNO1G2acWtPe/T78b/HajjvHn3fuEX/YZbf4fc/e8UrPHvHmbjvFm7vvFH9t2Dn+uscu8Zc+u8Rz7x9RZgiePnV8/P7wofHqgIZ4bd+GeLWxd7zS2CdebtozXmnZM/7cslf8aWi/+MPQ/vHS6AHxyJyD4tETpsQtp54YTefeGqedeElcfNjSWHPEilj93vb4yFFnR/sxH43lx54XbR+8MP572qHx+JT94qHpk+OBIw6LB444LH7+vllx3+FHxM+nTY8HD5kZP53RGg+2zor7Wg+Ne2ccEQ8cPjt+NOt9ccfU4+KOqcfFf0w6Njp9YQUAq+P/98f7iqK4rCiK44uiLgA8t+gAdccWRTG+KIqvFEXxSFEUu+qcrxVFcX9RFAcVRTG9KIrfFEVxw/9FGxqKoojzGrtSO15p6W1Lct3TuuYVsWDax7faB3DMyq5Cau9pR50TL3v3Ks16e2VRcE0NEVsyrGhd+67A06sueYZXNfK6JtrHXxeXUzPklWq+jwuqafflLctj5Mqb3zG9NebML8a65mXxyea2+PSwtrJQ/4phZ8Q/D1kWH+83P/5l4Lz41MAPxecHnxg3NM6JGxs/GNcPPD6u2+f4+MI+x8aWvY6L60acVqb11jadGZ8cdFrc0u898Z/9Do+v9js07hgwI27a49C4ba/W+EbfGfEfvVvj632mxbf7TS+BPP356j6Hx917TIw7GybG3Q0T4ocN4+PHDfvFD3uNi3t3Hxs/3G1M/KL3yPhq31llX6mJ+mXDiPhVzyHxf3o2x696NMcjPRvj0Z6N8WTPQfFEj4HxZI+B8VSPAXFD//eXKcGrRiyNf2+Z08EC77pnPL/znh1s8M57xEs7947nd9wjXtqpIV7asSFe3GH3uKB/x4prit2/2XdavLJDj3h1h13j1e13jVe33yVe237neH37neON7XeKN7bbKd7Ybsd4tke/WNe8Im4YN78MJp7sOTDeKrZmlfLnnt4TyhXjm4Yvi2tGLdhmoPDVwe+LzSOXlDWWdw6ZtU3XvVlsHzeNPy1u3G9+ubjol3tuW90tAHDloZeUKec/7tywTdf+aMCUMoi5buzC+PLwE2p+/1tRxFvFdvFWsV28ud32+uwQ/9ZyYty8/6llyviugdPj9R12jjd22Dle22HXjjHacdd4bcce8cqOPeOlnXePJxv6xQ8Hjdlqflwz6Zj41V6D45d7NcXvdusXL/XoEy/sumf8vsde8cyue8fve/aLZ3r0jx/tPblcPHX9uAVx3diF8djuTfFkr33j0d0Gx8O7NccjuzfHQ7sPid/sPjQe6d0SD/UeGr/ZY1hcPbEWUE1fdnV8btIH4rOTj4vPTPlgfPrgE+JfDjk5vtM4Ne7pOyke6D8x7t17Uvy4/4HxryMXlrV/14xeHDc3HRdf3Wt23NZ/dnxrwKz45sDZ8f/uc3h8c9Bhccfg2fGtwYfHN5uOiC82fjDWD1kR145ZVKb9PzNobtzUfHzc2HRifGbQh+KGISfHzcNPjI37nh6fHjw/Lhu4OC456KwYds6X69sSfU7e/+KaBS8E7F5ggZ31AjRsHPW83nqHRTOXtyzvWKzzDjZtbPtNcemQrTdN94IYSg3cLi9MumLYGfHhAdU+gNXx93lkALhd0cH8naPvehdF8XpRFKd0/n9053UH6pz3FkXxt6IoBm7jc8uNoPMKNhdauyiecygsn7/Xqjh5/4vLDZnPH1z7Hk0YRW9Pwuo2v7GAD6DKqyFbeywtz1/TuDJWzrw4Rq28eSvguWDax2u2nQBwAD4xagBEttHIb55w0bxXbsJoemNYAGG5z9y7ANS2aZfUbBSLbLwTv1ddYrR5jgEY53mbF4+jVy4C5jcKzDJOjBVbsPgNLnlVKKtVbdC9kpZtW1gQYHnn5+XtbVj5TLG/95/znmw5QPA2IABqA3T2/eOZlssVQ5fF2sErYsOQM+LCfVfEJ4cujYv2XR6fHbmolOmaxpWxvnl5XNncFlc2t8W6xiVxZXNbfKJxSVwyaGl8fNDS2Ni8KK5oWhxbWhbE5c1dCymuGrE0rhy6JD49ZEFsaloYm1vmx5WDF8VVQxaUfzc1LYxNTQvjysGLalaNrh7UHp8bMT82NS2Mj078hxi/6sYYv+rG2O/D/7bVZ9TZHfPhIwevKZ36/2paEhcOWBabhy6KK5vb4pPNbXFZ49K4YODyuGDg8rhiyNLYNKwtLm8+o2Y16bqm5bFhSNcqVmTG4h+2+vG2LDD41PkBlFiQwfz452FnvCugGL3ypli+T9eKa6/eZn545fe1YxbVrPRGN9mfEJmuH7Iiztm3PUavfHdAc7m21kEXvb0JCzqQG6CL9vJs5vSaxq4NzFms4i2VAGQsgFo/ZEVc1Hzmu9ZLjm2/KS5q7troPi/0waahi+5TlqPnnLeVebdFMyta15Z9ZEsozx0vLPJft++KYWfExwa3VQCwOv4ujwwAWzq/m5DOu6Moio2d/15UFMVL6fcdi6J4s+hgFbflaCiKIi5tXlzDxnmlmt86kcEO37/de2S93xjABUMIKPD2EnkDVIyo08QYzE+0rIhlkz8WS2ZeGmdOvjAuau56p+uWUW3l1gb0AaBBuwyMvL+aN06GecyA1HtXAUwM3OYefGmHk0krNU875NLymQZW3mzWv/n/lgHtM4gDJHnlqFcv5mcaBCJz/nqjXMCz2VkAlx2GZWRw5/37HPW7D2ac/QyvqmT8vCrUjIO3WVk/ZEX5WjJv5UEfkZWfYSCdt4SxQwTQsAWKV3MaoFu2nlPss8Z33sMwr8TlAxPzbsBljIATW/awTY7BtDcAJjBALznH24Y4eMtz1jrmIMn78jFW9HHBtI+/I6A4fvJlNduRYG9YlctYok+WmQNP9JGxQBffDdCwvQr7Rho40QbbPpe6AOqsE96Y2gwZW6/Qfrbw8dZF77YFy9yDL63RXcvfgavHwRtz0z6veLZ9Z6xPPOiyrWza6M5sj4M/21TLAN2hbQ5UsU/nNS6pAGB1/F0eGQBO7fxuQDrvS0VRfLHz3xcURfHrOvd6riiK5W/znF2KjsnFZ1DRyQBiEJiksDdMVEdrdgpmCwEOTiEYgPFaIX6zQzcQ8L5dNkYYs7wxsIGDgY3f5GH2x3tVeY+7vBk0/cVB2nhm8EZ7eP45+7ZH+5QL4+Rp62LxpIvi/MFdGwKbDcvsnh2DwZ3HB/l6WxPkye/0y0AdGbq9jv4BKGYiM6iH2eE5yGhd84ryTQMGCgYMMKu0v95mzmZH/ZYK9NGMtPcjdH94JuNmYEa/MlDJLCkrZlnEhF6Y1ciOzufkccuAGMaV/easn2ZX3cYTD7rsHcHAGTMuqQHH1qd6YNxsFXM0M0hmsLxxNDK2LiIT1/Aylwn6eM6JB1221T6AI8/sepuPQb1LRKwf/OasRM5YMJ7W2U3Dl8WCaR/fajudMStvipUzL64BKoyxwZ71w3plUG27yX6LzDXvF4k8PAbW8zWNHfXWb5fx8Pz3mK1rXlGzQbvnN7aVNhKQ2D4YQHPNp0YsjXMOuSAWtnYE3ZcO6XrLioM1/np+24Zv0rykLGht05mxvH+VAq6Ov8+juwDg2s771nw+NritJhWanUVmuDCGdgp879QhhtjvuzSLBUNhMICRwrD6Pas5XQzowPianbLBsbFd23RmuZkx4NHOF2cyp6G9rFWkf2YfMpA7a8CqaO1Ru5ExbSe9aaeFgTWY9bO8AW5m7jLAtkztVJxq8VslcmpobdOZNZvI5hSr2SyzApa7n1tv02YzZTzH4Az2xAyJx9rvxc1ty9dafzP4c7v9ejDriRkVfiOV6Dc7ZBbWwASZIxsDAPaNc9uy/AGIpO44r94bGUZ3ggGeYYdvR2wQ47lOsGRdtn6jo2Y83U8zV2Z2kJ9rgT23P9GyIs6ben4sbu1i8a1b1nfGw7I2q+bgNbPyZga9yfenRiyNjxy8JpbPviTap1wYn+oc4xxMOGAwI+1AibY5IMX2MZfNUme7CiAHFLmva5s66osXT7ooTp9xWZy8/8WxfJ9VNbJkTtuuWU70AdY5B8vMBa7xuNmuWD9trzIzTLtsxwhMmBvIDTtZpYCr4+/16K4UcF0GcHn/LuYLJ5XTQTYiGVhhLBz5OvVoNoKJ71RhTiHjSGy0DEbNQBiUuP12XD7PAC0bO67hHtmh2XDRHqc96I8dAIbdTIVBpO9vp4lxzCwMbeLfdpS+vwGYZUzfzFjZebgdZnrtrLg3Y+jV2x5Xg9fsOPIY2qHYcfFe3Mwk+Dm+J/dyitiOzn1yG31NZplhrwGglqvlle9pAOH55HMzU5qvdVvRveX7rIplkz8Wc6eviwUHdLDLrt3yKwGZC55jbmNmt6zbXAOgyOl+64Xb79/8KjnbirVNZ5ag2gDcrJOzC5aXz+G3zLp6Hlq/0Klsu6yTTic7CHDK0s+G/TRTmcfaOkqA47lkQOigi7FxZsIBlb93iYNT/mbfOdfj5VpffjdrnAMZz2X/tU21niFz98l6RZurFHB1/L0eb7cI5B/0XUNRfxHIJJ1zRPE/WASyvP+yupM7Gy4cST12zmwU3+GIfK9sbM2aZLBmFsXX+B5meXA69MG1ZfXOg2VxvZ/ru+i7I3gbToM41y36WXZedk423vUi+czCZNkY6JixcjoIAJBTapabnZ2vNdjPoD/31/fLDI6DB7+NwmNKCshMsgFmBkhmK7IzMRDILFF2UnbIaxq7CtjNiBiM5NSWAwePHedTO0afSWkbsCATlz2saVxZBg2ca9DuoMN66XYRnPhcA3zLwCAhn2MmKDM8GWBzrmsKYTYta+ThEhHGEF3JwNpAsB74y7qSmah6OpNBjPuIzBkfdDTrve2lQb7vbcDs1CvtcVCBnjjAzDYjg0me7dpEdNg22kymwb7rj5mDOchbP6TrtYx8Z1vi0o4cwGY2vN4cXT2oqgGsjr+vo1fRwfBNKDqU/uzOfw/u/P3cooPh+0BRFPsVRfEfRf1tYH5SFMWUoiimFUXxf4r/4TYwOOLMsuUo3CvXDNJy4bCBAEYoR338ntOO2UjRDu7l6+0M+DfMg51UBmc+h/SXgY6jcYMzWAs77myQDTCdjnXRP/elJon7+55ZJqsHtZc1eOuHrCgBth20gbGd5JyG9hr50SbXwnnsnCq04+RcAyQDWcaAlLdBM7Lm3tnh8W/GAzkwVnzHKmN0z+lLxjSzUDhxnLp1dU5De81KYfqXA4ecsmL87ODNeqAvbjv9ntPQXi4yMDtsMGfmhDlm4LCuuaM+0UxOZmKRq7dzYj5xPgtm8hx1WwwWnK628+eZ1J9SQpHHCbn5r0FiBhSAJAC6ZWLdMyAFXNr+GChxvf9tkGTmj+fTb+uDdTtnA9BlA1K/9zcHuLktXuiyfkiXndrUqcPIlFIa5pfl4rGmH9zbQWXeVcBtcrCAvnh+Wv9sizw36gUujBnXVdvAVMff0zGrqFOPVxTFtZ2/sxH074oO5u+bRVGMSPfYs+gAfH8uiuKPRVFcU/wPNoL+wO5dznRd84qa7RZwJhgbs0iuJ2FSXzHsjBrmz84dQ0ZhOkaotUfXSl+zFTmaxkC5tg2DWI8FAQQ5/UkfnOZ2isWGH0eyon+HkSVFyHdmvpwa8/8xrPw1uMMBOR1k4GzjmsGggaadvRfZWH5Oiy3o2+WM8zP83lTOz3VD6AkgBgdiZtbAm2tZ0e2xXtNYW3/Gs94JDHhVJfczGEFHXdx+1oCuWiyvuMysnEEsQN1ts6639lhaswjEoB9d8AIP9MZ9MZiwHnqBgXUjO2vPE+t/zVY3OsfpRoM7A0cDcK5BhyjaR57WSeaz5wh/DfoBLJaFATljRJ8MKHiW063cg3YBPNc2nVnTXrPuni9uo5ldykEcTCAP9M9MG3LNDKBXMddjwZhjnve2u5aN9RYb4/PoK23zPK4nV9sTrnUA6MAWAO65m0sAbMNyn+oFapy/tunMaOtXAcDqqI7uPMo3gRjsUANiBrC1R1dUD4vjGjQzNRhOnAjnYPC8OhNA5mgZA+V9rQxEbPgwHhidzEjRH4AXbbLTz8bJ6TeYO7NZ9dhBs5g4QqeIzcrQDrOB3p/PBeE4FQOwXE+H4bdxN+i1sbYMfQ/6BBtkQMwzYFSRVwaJTvuYpWFczQQDIA1SLdOzBnQs/LAzI13PM2EPcPhmSrMzNEOGjM2GGiibeTSY5z523hl4cL3LBpCbx8LBiRk2nmGAjm7wf2S8ZVRbTRCDblnP0S8zRcwJy8wANpczOCVJihcmOv/OuACyqQXeJPBtRsxzq7XH0rK91nXuh8zMdqPznssGznkMPX8875Azi24AsdybGlDkkwGSA2ivvs1Mn/fYdNvoG8+jn041u4/ZjsAk57lmxpU+0c8cLGdd57u88t99M5hc0HdVaTsNpmEmfY1/J5i4tHlxBQCrozq68ShrAA0OMBYYc5wHE5aXyxPNYxCaeh1ZAryrRy8uV8U6YsRo2/nllWEYShtQR9VmMAzkzJ6YxTIAxPGZYXFknA2i78851Hb5WjvSzFxh8My44FQAwF4BmI2sQRByMZhyHw0YcZ4YabfXK2r5N07bTKadUgbKZgDy2Hgsc38MdPgep+4taRgz2onjMpC2I71i2Bklm0yK2OCEcXCqzAykgwSng+14kYeDD7NRlk0GbmZ+nO5HT3D6vh/nO7XHdXzoF7KwvqIn+XfkwP0NCml/7ouZpgz4zJ4bjHJ+XvnKGLnmkcDT6UIHjGaW6oFOdC0HQmajzNDmbIDBl8Gk2S3bBcbJDL6BqtlhM4D+jnnKzgQwbYA2z50cJBhgMX7osuepAxHakYMQlyfYTnrecx121qAWUsCZFd6kw5g7oLS9RkfPGbS0AoDVUR3deDQURRGXtywsjUQuArexct1NTneZcXKUDFNksMgnr7I12MG5cb1TNT7XBskRsYGpWQFH9RkUOF1opsUsUQZTXGdH4ajcrIoBBAbXMrJztYG3rLJBBzxiUA28svydrrWjyKkxNkB26s/O0W10KtbAKjORnONFKXY4Xozi1dsGRwbVvtZ1VsgeWTgI4f8EMw5KDAKsg8gaYJKDgxxkWBaWDwA7B0Rmdq2LBGCMLdcZIPMc/m1wCXNjIEo7Od+AD31ADg6EuK+DAfSKukqv+mdMnFp0G+mXdSuzrOifGXzXvxpkmRV0faaBpO2ba525h+tCHaR4/JBRBjNm29BPwCxvteE7t98y9XzIqV3KT8zAMWccKCMr+mLZZsYtB+Pomcfccw8Z8DvPti1FL/LuCwa+Dl54BvpR7QNYHdXRvUdDURQxt8+yGkaECQtosdM2GHAUbIYms3I2yq77weHiSM2oYHRy3UgGUa4tsvGyEc3AyGAjO5AMIA0ezThgWNc0riyBHq+sM0OF3AyI7EjNQhpsGsy4XThtnAoAx87JDE4Gd/zbm7EaYNg5mLHMcjZYol+tPZbW1IF5LBhj1xg6SHDtHw6CdxYbuBjgZZCVQSUOyUAWRsJOOY+9WbJcB2iwlovrzQQ7KMhtRNaeOwaD+VlrmzqY4aZeR9bVR4NI6xQ6nBeZeNET/TM7mVmv1h5LS9BGWw26kaX/DbByu8yC53EyYHHas7VHbU0q97e+ZOYKGThIdR8Brg7AaAOLl5hbOSOCfsKiozu0j1IZj7vr9WxDPc+5L0woc5o+G5jXA50E2LTTZSIEXsjYc497uWyH6+kXASFAjfeoO4B3/apthMGo+2b70qV71T6A1VEd3XmU7wImCrTTtrNy+sEpHnb4tyHLq2od+cKkONWC82DrDD/ftXiZTePjOh6zWJktsnP383GQGHQzFgadTq+5TsbsgJ3w+iFdK3VdC5nZhww2MzAD2MAE2JnQVrMuaxq7Vv0aINAO10PRNzOjyATgT1SPs8vpUTuzDDTMCtVLH5qpBGS4HQY6lo1BoccBsG/nnkFsdlJmZXD21jECDcYSh2cwllORDqRoE8CW8w0qkB0Awkydgw6DBY8lcmdhjoGrHbEXNKCzTsWZSbO+GxyS7qMfHg8zQZ6zgGXLjHtxP/fJDKh1CvlQKlEPcHB+rjc0GETG1hfrm+Vk9gxGDzYyM5a2bQa8yGujmDbPLdtJLxyy3tMOs7NmOQnA0FcYYM4lUPWiFMbAfSdl7mDSjC6/G8jyHGoArRu237Y1tjnrmldUi0Cqozq6+ShrAO2UMdIufM4MA2kfsydebYghAdyZzbARsCMAgObUjBk5R/JmhYho3f7s4DJbSVE89801Z3yX3ymc2RwbfhwUhpZzXNvntA0ObNPw2tSbwSuO6p2Kt/P40O8MAlz/Y+DC2yZyeu3q0YtLI59BNI4rO8ucigI0kvYzO2nA6vRnBotOVbr2zcwxeolT9djSTgMfO1+DQJwqr0qzM/cY4XAta7MnyBiA43P4LafoDCjNInq8M/Nu2VjGHl/rCZ8cWBmsG5h63gIU6bMXMRlAmhXifDNhzJk85wDZzAezi4AkB2F5OyAHrIynX0FpNtHzAlk5+CKAs61iDnghCfVxACqnOB2kWoZmrw1CrS/IrN6iO+uJA22XXBiQ2U4668Dcykw3844xRlZsa5SDBuRB6pv7YtMZx2wzHLRXKeDqqI7uPRqKooi1TW01URyT2s6X9KajbkdxNtq1tP6ZNZPeaTwzEzaudrR2VhnU5GiYe+RIOUe0tNsOGkeFIbNBw1CabcFx5kJvp1IwzhhYVlCbgckpV/roiNxpMTv2bPjNNhig4Zg4B4fthQXZqWT2zWk0+uA0lPXGzov2+t8eF/fRfc9yQTY4QlhX2ozDRdbWI54D+5LTngavZlQAF7QL50ngYBkYIJpNRr6eDzkVimwMdC1/p9WtZ8jCQVjWJf91StrpU4Irg2/6kdkxMz7IhRRxDiCQoUEZoCQz9gaImdn0ivisj9YdAwyno3kO8x5d9ZhlBjPbJVZ4W8fyXELPYNrM7DJWvob2M4bOwBggOhuBXB0gur1rGru2xXLZhmtQaZdZWoNY23jaR7sZX+acbaZlCUuKrjI+3mzdwdnqQe3VIpDqqI5uPsptYAzIvMEwxsHgzcAM42aHbUNp4+t0agZSdvyAFp4DcDIrZKPvAn2Mop2ro3iu90rBDEzqRbH/jRIAACAASURBVOu0y+yb01cGNcjSjtT38KvT7KT9fBw+bcSBcM96CyUMltz+XB9ocIRsnYbKbJOBvvXEY+mxcPvMemW21ADKrBMO0oAUoG5wyDihQ7C6Zltpt4MXdNFyM4NqQGU9czsMgPIY5mDICx6sm+ilGVyDWZ7HuBjEeH5s6mTjGXPXWvk7AJ7np+WCDGkTdoA2oX9m1j2X3WcDV+7lrY485jmQ8PMNps2qeRyst4ytGesMZhhTpzFtx9wWs3C028Gb5yQyBfTwbGcq8jw0eKond/SG3zePXLJVsEy7nX1BZ/08tlXCtliHMqtJf7Ch6Cffm4EmS5KvNcAzS5j9CLKvGMDqqI7uPWoWgeSJj8MyQDLDw2T2/liZPcAAbFQUbyeMoXI9idkkDHGO/m1cHAnb+BlAbB65pCZ15k1sHZE67WamwEDCLJRXj5LGtPxch4OsDD7sxHCkGThb5jhiZAwQwoE7iresDdoyaOa+yNXOw4yYwRAy4X527papDXw95+JFOGYJDGANJBg7M5cZPHKNHSp9BEAZ/AEsnaZyKo/v0Wc7ZO/rBvBlfAziuN7F+MjH35lJQ6eQA+3xuCATByJmzxyk2HmbdTIAy4sB0B0z5g6C/Mm6YYefyzMAIQ5WnCo3q5XBl/UKvYVZMuNn1tagzlvG2E5wX2TmLZfcHre5HtBykEUbWcwCmOR+OSDhWgeNDqxyfZ2DXgM2AkkHbdmG1WPhfK+8vRVzxWBwRf9VNfORfri/yIGUfZYfcqheBVcd1dG9R8kA2gEyifN2CTacOFGMJ9/nlA/XmT3B0C3ou6rc/NWsmu9hY4oBu2LYGTWbBDuStWNymzOYoX0GCvy+elB72a6c1jJooo2uKTMr4Ps5VWgwC5i0AzIjYCeHXLy4ws9b07iyrNGhTWZ8DB5sgAEXljnnOFpHXrTRewnaofAxQMnshwMEt6m1x9KatJ8Bm0EvzJf7jYMyWKA/dsY4QbNRBhfeb5A+mcHw+Oe+ebGMmcBc48f4ebV0lh3nm1XiO/TO6WizhcwzP5f57cAuBx8O7Px/6wP9d7oV/fK8z8X+ACv0JafIrQc53ek5WM8mmHlHvoD/XOub2esManMwCAvJb8jA4+970leAG/rrtx+ZIbNMbZdo0+aRS2rmg/ua7R7PqjeGmeHmuywTb5WDzJnnmcmkvdkOwDhnoO378RsBWMUAVkd1dO9RrgJ2isUG0YZ+bdOZcfXoxWV07yjUTswRKpN/Q8vyks2wc8M4548Bko0hz+IdqDjq/Hqs7Ghpf06RmDngN4yYN7gF7Bp0GjBh1Aw4WCnIPWzwMiNKvzIgNqNRD7Q56s+LHDKIzs7m7e6THZT3++Kv2Rwzvy5Ux/m6HQZeBmBekZjTkgbHTj2ZfcmBgJ0dffIYstrcOuzNeH1v98kMrfXRjKSdM8+wfphpsjPO7E+9BQvIFSfvRUEGrQaHDtgsV9eRGRyZ+bRjN9PrFeneesRpWmSPbXHACEh1n20zLA/6R60h/WnqdWTN+DrIc9BlXUY3fF+zhQZa1g8HT2wV45WxyKjeuNRjKL2ZvvXMpSzrmmvT6rSJ7Wn8XOSKThEYem7lwA8ZAcCs836eA3dvO2Wbga6ZTTd7zPhzHuyg7VRVA1gd1dG9R7kK2OyeHaDBwLrm2te42fCaAXBtkCNUjIqds4GXDZjrcTBSNmLe/sROx0DEES5GCAdhRikDngzMzFC4TWYkcNhOGWbA5P4acNspGqR4BR9tN0jGCWfg5nv4XLffDGUeG7MfBotmOrivWafM+sGArWlcWa4mtvNhDDPY9b+daraz8Njwb7+FwOyHAaVBpcGWx8BMnRkudDaDouxQ3R8DVq+UNUg0o+fAh7nAamT02n3JW83wG/OUkoDVg9rL9+Ia/PuemY21XJCNgyLabIDuuWNdNzPIMz2OpBHN7GYm1/dB3/J+lg4IDPIZM68iB7y6/pW0ueemF1AYbCHbbEtsF5D3nIb2mh0CLB8Hbg6oHTxxrrMyHiPG3LYUoO43ixggG+B6PN2/DADNetpH2D6ZgUTWgOZso5kzZw1YFR8eUDGA1VEd3XnU7APIykob8bdjnnA6OCpYkpwqyjUrBnw2WhlomFWxo8ZQmrXIG0mzHQbRqBk3O7PMMjpl5roz0hm00+DCTswsJU4KGRmkum8wbP7OaTAzZwY2mdlbP2RFzZtHDJBoh8GhWRye7QUfXpGIAzWr8HYg0U7FTJQdbHYiZhAN2s1A0EZYKANwO2pW7pqZNFCCSfIzXHRPv9Ed5oTBLXJ0IJHbz2a5Bnobhy8ri/gZO2/waxBlWWZmDCDm6zJTapDksW/tsbRk0vJ89EISjwN1XgA1AwID1wV9V8U1oxfXsJBOuzsD4Plk9svburhUhO8AGp5Lmbk0iEeOlqX3+zSL5Wt8HTbMTLnnK892QOU+uia3Hgij/QaEvg9jyPMBpGbvNybQzHg7QGeuwSA7sML+GxB6bln3+N0lL8hnbVPXBuRXDDujxna6bfxuu1algKujOrr3aCiKIs5rXFI6gMyCmf3b0LK85iXw9QCVDTCGD4Nj8IbhsIHJwAgnhgPKbAD/N8OG01o9qL2sJ7Ozx/jjoGzwMbY4t8wiGfTxDMCX0+SkcTGwANDMjtlom/3Jz8lRPcY3A2IbV4+jGSIDeoN894+xMzg32Ml1bRj/DNxdi5hZNbeD/jmd79QiY+hNki1bgA2gzCDZzt2gARnmlK7Brtk9g3yzMmb57OQ5L5dVMGZOgRnAeQw8NgYImUGs1zf6BZi3zjIPXFtpYJPBaA7qACGWhfWJcg8zkowTumFwbXBvIMHYGyA6yOR3rs17IDrlSV/MeNJfzy/bvAwyM3BDF5mLORgCvNYDUzlY9FwlgM17duZ3S3OugexVI5aWdsV6t1GBTQa864d0zS3PTWwLgZVZUAfltCMHrfQTmaAztrleXFSlgKujOrr3KBlADIiNHAaCSU3tyepB7TVbqziSBBgAoHDSNupOrxj4ZdYCA8LCBgr9DdYcVfNbTpcYrNgB2Snk1JzBFAbKb+wwS2OnZcNnZ/12AMhys1P27wAGM7Cuq+J7nGCu9bJjN4D2GDOeZnMyyLVTpF7K53nsDLphJl0DZGCNc0Jv8mKLzFw4FYXzy3vZGbAhM2rGkDNy8WrHjWI+GRMCEC/uQbY8N6fVDDo412DL8ue7vOo0s3dmhgwY6AMgATkYmHl7F4+zdc06Yp2Z09BRz2p2mu/z+NA2g6Z6oJuPQZ/BnlfMes65zpASCQNor2JG5p5/Bo8G2k4lr206s3w+6dP1Q1aUdcfcz+l99Mw6x/6ADuToS70VzwZXefcABwi2TbZztisOoB3YUufqEhvbbwcOuT+0I2cTzEw6IEFGeeNy99MMZsUAVkd1dO/RUBRFXNq8uCZNZ6NlUOS0Bv92LR7GxSk37uX6ITtN1+EY9DjVaEAIAPA2LAZjBm84KRyvt9TAODrq5/78nldY2rHCUhnoOt1lZsDgepNSaBRUZydiYIoRdarQoCaDjpxSxPD7OQa2gAM7dqedDGAw8jCWOBDu6UUf9bY2MWA1uLVD4H457eo2GFR4wYydlUEmAYhlx1ibiXMfGQcDjgV9u4IQQLkdvxkbzwEzedzHQBqZmulz+QLzLQNrs1f8tc4hG7Oc3ogXfc1zwEDIb3VAzmY9PU8BNcjM4+oxMuhkHNwWM4+00+UZtJV7mHUySIUJQ6+Qa9Zz5phTuJarmSx0OANPgzt0L+85SFvN4nsu+rk5QHVghpwzOwiQBHRZjzyXHGzSltYeS2sAvAE6MnH63cFhntvoh9laZ2z4nfuzJVXFAFZHdXTvUe4DaOBhRgqjgmGzgXMqyWDExiunV/wcjCcGDIfLOX41HI7D6WWDJDMGGF8bUkCmmSobbQNAnmlwkWuE7PjtJDB2yMTMhA26wRQGFGaGZ+A8DQoMEszS0E/a5kjbbJedhxeQIG/6g4NyKtsshZ2vWSD6BajcMqqtps2WN7Wj3ANQCfA2QOc8AyozDQYYTqMadJiJsm66Ns3Bh1P2rl+0juY+mXmyU0e/6gUUGdBxf+s/120Z1RZXjVhaw1p6vmVm3EwOQY0DAzPnOWWPvC1ng10DK7fT88yg46oRS2t03sEkgRqbPztQMMPsFasOKp0ZsK47qMRe5QATuToowMahe6Rf6b/10MCZ8fA7f7OeZvbQbXMgYLaW9pg1RP70h/uYabZOWo8MavM53MMgzqw3DCVtdhCHvA0UbTttCxxEbGhZXgHA6qiObj4aiqKIjw1uK40tBsogj6JxjAHGlwmP0Tfr5dRDfs9tZnnslG28bPhdF2cWyODEbNwVw84o2Siv+LPhtPO0cwTA4bxcE+jrnKrDqNlR5FQs9yAlClDKDtMpHzNR2TBnQGmnbYYQx5HTPdxjU+cbNBi/7Ag8Fpa/wYOBGjLx74yJx9EO2zI0W+N0r/XBqVq3DdnZ2ZrVy8Df+m5dNKNqZ4ZsHCgYzHBvghKXVNA379toQGRAABB2fZflb11G7zgPmft379nIOaQEkbE34PaYcG1ecWwAa6bWAMbjZ3BrHXMNWk6L2h64/Q5KM7NsO0GbGbvM6jMGtnnWJfri1DrzmFQ18shg03ri0gW/09tzHEDuMd8kIGm9tc57sY2ZNc8D/982wnY523QH/A5EzcabbfczvDE8toDvHHiY+a02gq6O6ujeo6EoivinloWlESdFhIHJBeQ2+nZWNhQwR/XYlsz+OdWAcfarvMw65IjR7IzvTZrVQMFtpY0GYWa4zOZlFsNGz/cwMKKAOxvcbDTNiuFY7Nj4Ldfc5BXXyMlpGcbHYHtF/1Vx9ejFNaAoOyfXORqMZkaTZ9nwG1B5IQwrAT1GHlPuYabSAMHsIu3MfbfscKY8w9fyujh03XKnDQ50zALxf2/t4fICzwOndhm3HKQ4WDF4Mxh3UOZx8pzJW7HwG+3cMqqtBsR67qLjBlVe4YvjNutp0ICc/HzLK4NRnun6QS8EQT7UpHouGGhlptLz0UFeBoXWwZxNMMtmltQA0X2h7YyDdyPgOYBIj6NBpoMay49+2ZZZlsxLL7ZxUON+oDMwmbZH6E6u486BeQ7AAW/eKsbzzjKk/YyT5efxndunqgGsjurozqNcBcwE9TYw/n924JtUc0Jkb4bAxb84KcCe680MJjBmBmEYfc7xylTAEM7JQC8zU3bopINpv1O9Bh1m4szg0F8zU8jL0TV/M5tiUOI049qmM8u6QKeyLDPYDjMNNrROq5mlwplxDvfzZrGu3TKjkVdr28nZgLuv3kYlM2YGa3Yw/m3j8K7329ZjnAgUco2gHb91wewizzCohQlyig/gClihbrNeUMLvXg2Z094GWnaqbr9BLGOd9T6DWwcinI9ue4563mUGLG+JkoM9nrumsestDw52DAoYZ69a5XkGW07Rsm2O5YIOuC6PNprVNtvr+WggT/s9B7jWQUYGrVxnUMY5ZgP53deiW4xfDiB9H0Ct9TUHnhl80gf6YX1yahZ9Mljzsw3gHADYxuTFNXnBB+NmwOegNY+TZYV81ja1VQCwOqqjG49yFTBGyYyZHXE2Qt7ricnvFAHRMAbTLIUZJqJGIlAcnwuQzS6ZlcIY2bkZPBIh8yyDQIyfQQEpMVgPHMWK/l2rAQGpBjv89apEp1LtlHOET9sxsgY1ZnTMiCAzxoF+Wt6O6A08+Q2WKddCGTg7RWOmxeNnZ2dWK4NK+si1Zh+yE7YjRF9cC+UVmzByBu1ejAHDY8bI/XVdFeO6SXPAbKMdbmZ9zWKa4UEHAIpmVtGTDK7tLO2k87Yglg3P4xz3Mf/fTGpmojyG6CcBD89ivL2aGp12gAQA9GvBMiBHVtzLbBhghBIF67MBtVPZtJ1xtdwNUgzmMjvnICOD2nry8i4H3MslCugX9oPnG6Dl4Mwssut2PTYGxrYrLhdhLHIqOQeOgGPa53pgz3EHBwaOttHW01zmwzMdPBIsVRtBV0d1dO9RsxE0k9TGwg7BDI63WNkoA28jxSQHUJmJcwp0TePKcoNafmMbBKfHbGjzwgQzQKsHtdek58y6sJiALR0cOQMSMGhm/mgX7WDfOT9zUydYNhNl9s+OCMNsZotnsFEx1zlqt+PBKRiA2EHa2DrC5992BGZKaZuBtesJzbIBvnIgYIDcFeF3OSmuzzrhGrHs2HluBlm0kXv7bTXZiaM/ZnDQWXTabJxBPkGAzzVgYEy8EjvPBY837aWtOHy3xzqEjjmAQafNxpjFNnDPckJWniMGSq6t29CyvNxX087frJzBsQM9r0ZGZ1wXyXdmxx1c5ACFQDWnvjNLx/f1VlLzTPc5z0PGhHv5/rYRng+rB3XtP5oBugNWB3G+h5+PzBxAIIN6ZSnWATPQjEneF3VN48pyKyd02yDZwB6mN8vJe71aDmYprfekta0PXfpUMYDVUR3deZQA0EbXUTqT2aAHY+RtVUz752gvbwmQUyAGNAZd3C+vjjNYdURv9ic71wzGqIXBaL0d0whL5mcZWGLQvYdbBswGWa09lm4lj+y0zJAwFrBYvl++3tG5I3DSaABOAB5jDqDaMqqtdJaMeQaT7pcL4A2G7WS8DQX3tIPy6l6zt5nhMFNqcJ4BtZ0+gQrjw71gp+iDWRee6TYReBiU8f/8ui4zrRnEw5pxH9hR98/pxgwy/To/dAMd8CbuZjM9Xg4I8uIT5GV98NxBJznHaVrrPe3iOgMYs8O2IzzHwAYdMNA1m2qQZttjfchMppk+s7E5wOJadNO2IbO4nk8Oxtzuq0YsrZm7yNJBF31DP3IKGFn6epi9XOrh+wPQuK+BpmWdMxuWn7M7HhsHJuiUAy7fizlTLxvCPap9AKujOrr3KN8FbHDjtEmOJDGMGSzZANlI+P9cn422mShHyzg9LwrBCeLcbSDNRPC7WR+32fVYdrIGhGaODKa8v1sGRXZABjF2IplJs0M3O2qHxndmVR2t+1V3ZubsJPJ4AsDov8fCRr9e+wyw3UYAkcGUHYHBoB0y4885C/quii2j2mpAh+uO3J68bYeBgZ9BW71AwXppgGqACWPFM13z5ue4zpV20y/kn5mvNY1d73x1ys5j67abbdwyqq2GdaPvBr+ZbQR8Oogx+LWO2LHntuV+W+6MoYGamU107+3S5ZyfU8LZFuXUvGt5Myvo+9tW8JsXpcCG+dkOTAyUOIddB1wK4SCNubF6UG16lY8DO19vQEqAYNbXjKvtA+OMLnv1MzpsW+HFGwbctl3Whdx+g37bA/TA7CYy9jxb0X9VtQ1MdVRHNx8NRVHEB3bvKrbHiLb2WLrV1gfeKDS/WzdH0ESgmRlwVGmmDwcEM4eRsREzUDAQ5HqzJwZtNv78mzSrHSfXml3BOWSW0pGtWQA778zqZQBlcEEfcgrZTtbycxTPM83iuP8YWbO5ZjFor4Ex96M2K2/dwIpCg1Xk5/5n1tdOIjPGmUE1e2SwgHPjPMvWAC+DB+ucAaWBDvfOY8DzvHgI8Gm5ZVakHqvIebxZBzk7KDCT7Xsz99x/+mKATB+YH/54rvJvnpFXMwMAuA7mkv97oYcDPeuLA6p6AYqZf+sDOuPAyoFPDobQH7PofGdgmsGtgTXXcZ5BnoNU/ua0tdvgviBLB8Wc661qsn3IDCA66gUdZt1slwx8sTUOOh0Iua25ZtdzxcCWPpvdBNi7zwbznn/ci/MqBrA6qqN7j5oaQBg3OwO/Yiu/9srgBkPufdP43W9PMEhwRGrD6W0hbJwwGq6d4TqnQ3F8RLYYb6dQMgtjI2kD5ojXixoMhAyeMzjMEX0GmHZqZmsyy8HHe+n5YyaEMeR77ut0o4FTBkKkviwjwAoycQoJORvwWF/MANEnHJhlk9kuL+6g/KAeu2N2wSyUna+ZRQMIOyicYmbwuMagyiAWB2lW2rK3IwY0oEtmwszSGYgYvNBmBxcGQwYMdtgGJYw542hZGnjwMXPrcaGuzEGDgyDrmpmwemxlDtw8ng4OrDO5fQZ4vsZlCFl/zIBmm4bM8kISB4O2Neg7JQYZuOUAlfeqr2teUROQujzFi/Ko13Ng408OqLwYxL8bMFpPGSfrNPMBWZr9y+UdGTRbjtYzy8VBSsUAVkd1dO9RpoBtCDAQpKYMZmxQXCdng4qBt8OpB1js7Mwe2Li5TsgsRL6vwZKdUY6s3Vand+oZSDtFgwobrrczfgZCBoI+30wIf/P5mV3dPHJJXDWi9rVNLsD2WwsMpsxq2JllkG+GznKd09BeMn5mHl3zZKbK26E4vWUZWaauEaMvlpdZD/Qrsyhv56i53guXDB4NpJCD09fcD6aOa/P2OE6zMZaAXY8n9ybYcAo7s195DhnMml2zg7Zjz7IlSMtz1uDYANz1fllWXqQDoMmpemRt/TQwo7bYgYVl3tpjaY2c6+kJ989sHDqZgxmucxDpuceKejNYef4wDi4v8XNZ+WyQaNDjQNopXNuezFKamWYMuB9ysu4SjDsg96pcA236nkEyf13bal1k3DMLbybW+kq/6LdlWgHA6qiO7j3KN4F4tS2TmDeAmAEwK2Nw6PSVJ7vP+f/ae/Mwq4pr/X+pIA7QioINIjIoo4oyCYqMGpFZQQZBRaCbhhYJuSHEe4mGxGAwGg22QUgcv86zOERjjHE2xgxq1Dhch6g4IcigIoKs3x+7392fszhqmwSu+aXW85wH+py9a1etqlrrXe+qqq1okmsI6bBk9GngZKhYFxoxlrMQRjemXegIZHBlMAkOdQ8ZLRlTOWkdJhzXUtE5qf4EQRGsRgMZwWEEM3KeS9qX5euUeJ0cdmRQ6CSlZzk1OZxir7qSk2JfyzlS9wRkbKfawfQrHQuBB/8mKKTjU5nc9cr0KoEVgR53W0s36kuWRwAsgEJml45Vz+TY0bN5NqWerbe/xKCDY5/zhqlwPpMBUgT5GvtklAXQmEKPaWCyjdIHGXUCvGKBBOtBNljBCJkfjlmVr2CGm8rUZtZNgcjn9ZXeZ0vAWYz9k/0h0I66V78TOJFFZbpVf89rcXKBneA41/+5rIHBlPqbwHhBq8rN7F4MJlmugl6CNs7Hxe3KCzaZxLHCfmTWhHOTADW2M5ZBQoDjLW7I0r0pBZwkydaVEjPzeS3KCiJAOm+CO6UsCKRkGOVINOmZepMD4LqPeS2y3XHRuMV0D42HnFMEEjSAMshMfzCVM6vpTG9Rf+Bm9+tv1b9F/YG5M4hRvowjI3w5I+mLadRz952Wt5VRO528jLV0SaBFlovGWN9H1iYCv7gYv1h75jSrOaxW10rXfEUYfyebx7QRHbCeKcdIFiwyEfNanJyfpUinxA/XIUZwwD4k0IqMg9pDB82xqnqon+IbPyLIUJ+S7VFdqtpsvtucYI/rEjWOmTKTM45sK0Eyxy9Zaunx7NbTcwaXc4xMfbFUIb+PGzJ4/A/nkNhf3sdAicEQf9e4YDAjhlHfE8SS6eZuXeqToJ+MNdPCDJjO3XdafiC1+l7X0+4Q7KluTIUzYOGzCJo5fzjeGTSq/2U7FJSTvY5r9bg2VL9TN5wftNEqn0FULEdzQe3jsTDqH7KI81qcnNtR2SVtpIt2fW7ztAYwSZKtLTkAVBpQhkcArbK05tVsNPRc5E1DIqMmw0NAyYhVDlHGlcaAkbauZdpHDiKmYwgwyUrRMZD9ifWMjA/ZLe4SJOsmA0+ARUaBBpHfUTd0imTfyFqorVxMzRRdBDNqN8EeAb7AvIw+U1RycnQqjPhjClZOQbrnu6PlXFWeAAidVVw3Rz2T4YvgiuNNfUEdy+ETGJKNks7ZNgYSkdmgDtXXcbmCQE182wxZFTpvrgVUHaQXOnDqUmvvYtBFp00wSSad85t/R7ZW81p9fXbr6bkzJ5DlmtliAR7nguohJoqspfqCgJnBCYERGTgGSKobQXBk+6QfgmzOA/WtwCfrwVca8jqCQulEAZVYyDj+2R+6t1hmg2OSz4iAWYxfsUBegUgVlnBEgMxAQH3Ds1LnNp+Rn8jATStkUDk3OCd4DdvMuTG3+Yx0EHSSJFtZCt4EInCxpH1ZQZRIo0kHLqNLhyonJuOjCJ5Uv/7W8+LbCwgmIqgRG0PjTLBEAMk0sNgt7raUw+IBvzTuBAJiJLhWL4I+paHIntBpRYYjgmI5xDnNTvEW9Qdulm6LRz/oOWKr9H+1Uc6JdYlOU//nJosIlvk92RD1bwQVZKVo5OPmHbKTkcmKTpZBAYEY132pjefuOy1/hyoBn8rlOizdxw081A3ZG+lC4I5rL+mI1RdkgaVf9kEMElQOx4bGA3ei62+u3YyMKnVEUM1XhDFdSGaIY5lMH9lLtolzlIwXgTfZ2gjy1QaWo/4Ry8exw4BSQZrWNZJZIqsbvyerzT6JyxFYBm0hGUzaNfUfy1Y/KOiKATDHFoMSBVsEjuwzgjxmJDgXGKBGIK26sQ+1bpD9fXbr6b64XflmQE73xr7lnIopZtkwBuV6fnoXcJIkW1dyAKiJTkceDR6jOkWE+j+BkQyFHCCBFcERUzo0KpHdk4EQYFPZTJvpZexkA5iaY8qDBj+u2+OHC9zlNHgYLw2zzvaKKRWmtuUYBTilnxgtS1/6N6Z5I2hkmlJtI5shZ8D0jdqwuF25z20+I2eUBP65JlT6k665e5T9P69F4RElZOliHxZjMsjysq8YiNCxK33I3wiQo9MUoFDfsX+Y1tU9+pepcf5ffUNHTOBAtodrrwhsOcciUNI1LFNzRjrjWI4si/QdASRZdDJLEZSqbD1XfxcLmDSeyZ7zeaqL6qYxKlDEgI7jiRsMGAwIzBCoEDQVy1poTqu+C3ENA159p3ErO6JnCSQJeBPQR2ZR9oxjXmODwRkBdDEAz93StAtqM0GzdEC2TbpTHWPWgR89l+tOaQP1HXXJQJVjSLoTgIxBmObGnGanJACYJMlWo84y2gAAIABJREFUlhIz89nNphYwDwSAMmJMpck4cF2QvuPvS9qXFTAT+pfrVmQs+CoiprIETOXsBTJkkMVSMI3JtpA5ImMjhkwOnkY4skRMYzFSp1NmikuOIhpIOgyVISaCbVZ5TOmo3dFBxfL1UT/IIfH3CLAiiCAjUYwFIaCjcyMI4norBhX8W2ydwIiuZxqd+tKYJJMRgZ/+5UYG6ZHjgU6TDjUyV6w3WUONLzlgpk4JoAlmtFOTuopsIwMvrrti39BJsw/JvLO+0oNewUVQJh0yfRtBAUEinTrnNOur/tM4iX2rdioVzHJiMCgwX4zVJyPLcaQ+4VmhavOspjU7ZmMZfOc5202gPL9lzcYMXcONKdJ3BNsEfAT6Gg/6jsctEWQLAHLnNQMZAjwFw1y+ETdSqSyygdQvbZ0CobgTOAYAukcboZgKJyCNvkb9k3YBJ0lSI/Msmwz8PI/fdzCzn5vZCjP70MxuMrPSr/iMEjPz8Q0rCpwBIzhNcDlRAjMyQJrcYgVjqkQOMkaKdNDF0li6RsZLYJHRLesZDTHLlIMSG0dwSMdYbHcvo1W2mY5UbdJzZSBjtE+nzxQoXytGB6QP02AEeuwHMpx06EzHkGVQG8kIkHGhboqBStWH/UCGITp2OlIuAaBTJ4vAvmN6jswp+13PjjqPr7qKupBO9ezYXxzLvJ961jPFgjJ9R8dPB8h5tKBV4a5PrsckG0d2kSk2XS/AJJ3pX77hgoFbBHnqH7JfnOMKyNhfkd0hMFF/yC5QF9QxNygR+LMvmcrV2XmRkdIGKo5BBjoExQR8eob0FYO/2N/R3nCcaH4WY2x5dijHlPpTS000NzReIhNHoC8wqT5m5oPtpq1iapjfs394YgLbGMEtszYaN/pXoJ8ZGQJP6Wd4g8QAJkkimWdmz5hZE3wa4fcLzex1MxtgZl3N7DEze+QrPiM/BkZGY3G78gIHx4ibxk5gj6CKjoIsg1gtOS9GpWLyCPQimxHXGxL4yFjpe7EAdBx0tnSmMm4xvUh2RetfaLSVBtLuXjkjPUPrp+gQdR11SedMNocpHOlAgEKLuaVvpu35FgcacdVrIRggrt2J63giUFMb6Mi0wJ8Aie0nIP68tCD/TzaUoJ3OhI5NfRnHBEG/xhBBN4GLxiEBmOqlMRTXKREEkxEke0LQKraajEsEzzGNTICt/iGjSWAl0CQ98IilWDcCGY0HMbia8wR8sRyCJ41fjVGNSbadoJAMF5mfWU1n5ssnIrNOcKlncQ1ZBC4xoOE6SV1DtpMBIG2a+j6yVUzHM0CZ37IyX7PLOcX+UxDC/o4BGjfcMECSXuKmItWDS1U4Z1g/jk8CVemEAS11H+0B6856FgPMarfKZaBHRlB6TingJElqZJ6ZPfk5v+1iZp+a2bH4rr1lk6fnV3hGwRrAmAojSBJQkRHRhCaTR4YlOjrdQ2Ore5iikzORMWRUTGZJDieum1PULIPNKFfM4Zxmp+TsAdmuCDD0PDKWTMNFAETgyjSmnC2dBq+loY07OSMzIUAhfcxvWVmwVodgOuqVzoxORM5C/Skny3WV7L8IdugEIhiSo6a+Cd51XZ8dpxaAfgKxyLKyTF2rTR8MFPRbnx2n5vdzvMT0o8rm2kyOD34fGUumy6gz9QWPviBgUxkMEjQWqrDMQjrmGWoENQIu1BHHNNNz/J7jjMCXgRvrpTrHDUbUBZdqEHyob8hYc34WmxuqI3VFBoksJYENg0DpUNdoXDO4Yb9GFlp2MNZRZfPIJuma9khjgvObAJXHDEmn7BOCaraDgFZjjUEUWVzpT2OK67ilr1lNa15FydSvgDv7jgBadVe/x4O7VV8CaPaR7FlKASdJUiPzzOwjM3vLzF4xs6vMbO/q3wZYNlF2Dff83cy+9RWekR8DIyNNQ0onwzSMHBadbIwwycYxqqQxlnGgcSUbQ0dLQKf/yyjKYHF9lBg6/S1DFRkgRqFkMsisRSAaHacMvkAOy+VCf9Xzkg5TNgMpahONvq6P63cE4GjIpdNiqXa1n6ka/U7np7VUdLoEiARXGgs09tK17hVYpVMlKyjgUsz5UbdxHEQwGtlSfa/dwFHHBJ90YAxk9DfZrsgycSew+p3lkAFhvckCLWiVsUcEbXEOqgwBVjKJ3BnOukXgpPGiZ/N1Y3T8ApgsSwefk1GLDlzAWe3TemBurmHQwj6hbeHrJtmf1Jvmg8riXCY4i3bh04X1fMMl9Qr6jHODbDltHQMmBjZc+8v1xXGuEiiTEeVYkd3jjn7a05hijWNNtpApcumf+qM9Y8AcbRbL5TyUzqON1HUCtmwvx14E0LOazswDjAQAkySpkUFmNtrMOpnZQDN71DKA18DMxpvZ+iL3/MHMzvqCMutZNrn0aWZmfmrz8gLgoY8YlmJvCZHDYhQaAZYiUhoQplLp+JU2jTtIaVgikxjTdLGO0XmQWZBzYHqR9YrgV+myGJXPa3Fynu6NTl/sEw0eU8halE+dEmDx+QQ7ZELjGXLcoStDL4dPp0MARUBD/S9olYFaAXRdR+aUzkYgQHWmoy7mXJieE4AiUCC4J+iUHjSuyLqQhWZ9izlNjiE6WOmA4Do6bI1JBiLUQWSduDwiMphkcxjEsHzpj+Nf16ivz249vWANIfuAAQjHl9hRjmfqVayn2jOraebgtQSAAZ/6VO3RejQeycNjTLhZpNiYVCDIdWMCv9woxTFEYBpTm2qXnsk3ujBlSeaLAQLnn/6WzaLO1C8MKOOGMAJD6ZZznn0sHTMIkI4EttQWAkAemaWxFO0f+5wZEo1vznOy5+o7lsnr4jvhSQgQCKtN81tWJgCYJMkXyK5mttrMptg/DgDn2eYbS/zU5uX5JJah5SRlJEoDzpSejAGdqsojC0QnGCN8AjgaDwIBGSs+k4ZODpOsENNdSoHIUcjQyThzpySdM50DAYCey92ddDbSB9kNGl2Bl7iuimsD6TSUSmRaJ7IUdOgE3dRt3MGtZxAw0jHEZxVjnQiECFJjW/R83sPxRaBCZylQoH6kcxeQkf7ImtJB6nrWsdhY14fAgACC7SAY45IBBkGqk8rhXCP4o2PUdXqLBwMj6VX/EkhwIwXTjZEli4BQQYIALFk9AR/V96IOUwrAMVmlGECpPZxvkU3W/znHCS4IgBWQxSUOZKzJOMV1gAK00iOZS25IE/CMAcioklPy184JlEagSZ1IL+oTlaXdsmTuNQZpI9mHnPtRT1wLSJ0QfEq/GhvSUxXAsNqj69V+Xa85qUBWbeSz6U8YENOuxrl1RsspCQAmSfIF8oSZ/dj+8RTwFzKAXPcho09DI6PIdKiuiywC7yEgpNOJ0SCNAcGfjAkP1pXREtPAg13pKAkquDNTho1AVEaZzAnBnByHDDbX9REA0HgXA74yiGTa+IyqNhV5ii7Wc0n7Mq8srVmPRsBBB6x/da2eISdHwErDHVmByK5Qr3Qo3ICiuql8tYVpZDkujQGCCTJyAji8j2kx1o+pRaa6eSQGAZL6RQcakwGRziMAic5e7SOQI4umAIWMN1mdytKZBWsZyQITPOgNGXTsdKwc53TQ7DMuYVC9VDeCWLJfTOVy/BAgcgMAgZyu59q1yEJzKQDnoe7XGjuBNQYZtA8cuzFYlR7ZN1xOQoaTrDvnv2yD6sWglnMwzqE4j6gPtY9tI0stUMdTFRhsMYDjeNYzaKvI1nK9KLMgBOq0VxxLrDvZQc1/lhUDFAZFDM5Vv8QAJkny+VLfzFaa2Uyr2QQyCr+3s39wE0hZ44oCwEKGQZOZzBQdI52WJjYXCfM3AiQ6E+7GpCGSkaehlBHXuV10GpEtYtpPbeGatVlNZxa8j1j3qM6jSrLXIcmBcgE+gU5MOcpIkvWSoSWbyPaxXZ/HjjLVSdBNg6r1WjTUfDZZFvYNyyG7FK/RfXyjipyU+o66ZABBhpSOJ6YACVQUYOi5PBhYY4R9RoBNh0hgEceYwCTHJpcykH36PIY6MixMSetZmhu6R2s4BbLIDunvYmm4eS1qlh1o3Gj9KccuwY7K43xg0MK1YgTbHDNVbSo2e5sF07DqRx6wzGCHTFIsm+NRfRAZeh4To98ZbGiscQxybpLx0lji8/iGGz2P/a0yublFddHYYx8SNHPdpuop/S9uV15gK6SjmAGg/jj3yeIXewtQDK50rZ5FwKqyFZRwpziDLNa12BplAkYGpATFZA4XtKpMr4JLkgRyjpn1NbOWZnaomf3GzJabWePq3y+0jPHrb9kxMI9Wf76KlJiZTy+tyHdxEgByxxqZmehw5Dw10bleiGvUGA1HRowMCFO2SnkqvRHTEXQaNGJkx+KzCWQIxLg+MW6GINjTvVqwHdfIEUDIUcUoXNfK4EoXTNfqOu4yjEwp0zV0dupPsprF+opgnKlxlUWHGx0HnQfBEp0PmToyoqq7HAR3GZJlpi6YMpJzpfORTgSO4lETqisPHSdrRCcW2aXIyrHP1c7IqkpvcshqS3ToDFToWJn2jYwy+4DAkICVfavnKdUn3XKeci0ax1QExEwpMn0ax75+U/9yTBGIMXDUcyMzJpZJbSMLSH1Qx9zwQx3wbRZxqQjnJO/l/BXYI0sYf+dbiThn2Y9kvyNo5fu1Of7IQsb5ReDKgItBufqEQTnnL3ftMijgPFD/xMBdz2RgF20dg0TVS21KDGCSJDVyrWU7gNeb2ZvVf++D33UQ9ErLdgvfbNlZgV9F8jeByCgwbSADTdZGoEyTmAY3OhQ6BbJmZPTINOn1TXSW8YXsMt404GQf6YC5A5HsknaHMlqXU5IzjoaNTIUWYkcmipE2AaCuI1OkewgIyLQRRPP5ZFQ+z2mS/SOoIchhFM7vuHaK6+p4HVkusjhyAGQoyP6xTnKY1DmvU5uYOpVjEkDkeI0MpHRDdiiyddEREujrmWSO+AyybLw36pvtEaDTmCWo13U85ofOnfpnHwtEy7nTyQpUczzpw01NnHPsQ5XP5RCRHeS855gVAKQueSYi2TrpUG3km0+kA/YVr+dYEZCIr/Uj+ONmH7JntAMMAjinWBbXXcqO6HdmKwRWtfyE4JHzmXaE9kLjalHbqbneVBYDD453rh1U+aq/lhKovYvbledBJsdssY1f9AOcfwpWGAAyOCJ4JUMoHaidp+1dlgBgkiRbUXIAyKiaYEbGi45Fk1rGWBOf0XiM0OlA5CwIsHQ/d7PxN7IrjGyLgaPICnBBMo0tf2PZdDiRHZITI4CLdaUjKZbm4gJssix0TmTzCGoIFphGiowPQWbcGUwnzNfqcQdvTAnGftcz46J0PY/pRvY9AQTXDUov1OG8FicXLDKnkySDQhZX13DDA1lotVVt4eutWDc9h2upIhPKukp3ZBa5Rjaml1vUH+jzW1YWpBPJnhH8S5cENZWl2fIF7jhWG9Qv7CeOcTpiATyNX82j2A4yXgSSDJQ4D7n2Uc8k4NWzlIblnI71ZKqXQELPI3NNVlE2JgIyjRsGSrpf7DCBoXTPt2+wfrQZmqtcw6uxpvYRgMU5rjowwKYOqXsGi9HW0WYJABazD1zvyUBI9xX7niCT7VV9aBcIGjl2NG6Vaj5p98QAJkmytaWAASTjEsEVKX0xHXT8MiY0qHKSdPBc1E0QM7f5DF/UdmqBAY7RdlxPIkccX1NE1oE7cAmeIjiiM6dhVuqZYIsMoa6lU6KjjECZTlx1Z9RPB8F0s8qNC7Yj4yR9EYAKoNCp8FBjgoyYYuJvZHjJFHwe80sGjP3JMSJmjU5K5XJHNhkT3qM1aXJKehZZEOqU4I+MDfsovts1Ajyt29NY4Nhk/8ppE0TQGYqtIoAlENf4JsihLuX09XcEenEMMm0usEEgx7JVLq+hnuNuUJXPOUu2mulgMmnFAryYHibIUnnRFhXrA4LWGPjRDsS+1j1ab8pTBrjOT7rkHCHAUht08oDsUrH5SSDIpQd8FscTx5DKI3MY12zH9D5tB8csAS7HBMeN9M61n9Ff6HvVV6CPPoFB4PyWaQ1gkiRbW/KDoAkwFHHHlIr+T8PMFCzZrciwETARIMkpcaeuDIkAKdMwrAOZLX3IfJH90UaFyCJG5kjGS445RvkyqnqONqOQpSIbRsZJZciB0cnKQHONjtpDkKt7YyqYIIJpzphmJ6On+jGdKICj+nNdKB0QAYqAAZ0MHaSYxhhMCGxFhrQY4FbfqI0EedI5+53snuoifUQgoWvICGmHOQElgQaBD4HZglaVBaCUdS4WEKlvCfrZ3zGgUNvFqPFoIQZlZID0fALAuDkqAlnVk8yzyuI4JrAlw0P2iP9SdwSuehYDOfYbwSbbRVDJMUWgySAzAhCCSelW7BWP75F+laHg0UjUl+YTQZb6mqlp1ovznKCMAV8cO7RfLeoP3Mwuc3zKDlIHkY3jd7IZGp/RxhDgkYVVkMjlErEuBPlcbjKraWIAkyTZ2pIDQBpuvlSdLAIND41UTC9G9qdYhE3jTMfAyJ/MCQ2XHKXSDtHQkG2kcS22OHpxu/I8ypcjZrtjeoTOQoaMkTLZR66LYaRMh8f2U29L2pcVOH21j+UTAEUgQtYwplBVb11HxiCCydjPTKepfeoP6kZjgRtgouOSc61qU3iWmFjiCJyZUtP/BZ41frj5hU6TSw4i68KggyCS6VSmgGc1nZmvV+WYZhm6XnXgEUYECLF9BBqRXY2sDEGDwCcDGs7bOAcEIFX/uDuewJQsEZkf1UXzkMtF9AyNNYHOCEQZxMRNVQSauk5ASr+p/gwgI8NFAC19EvCpLRrPeg6DHQF72UUym/o9zi0Bqxh4kR0j205gpblCYM3lCtFGco7xSBaWRxur3xWgkjlVPTWeqtoUvtJPutV8pb61tpSgX/aV40hzn3M6vQs4SZKtK/kuYBo/MgJ0JDLsXN9C9kQTmxsTZDCiA2WqQMZAjkTrgmQYuCNOdSMTofsZtRKYLGhVmZ/1FpmNaPh0JIfaqrRPBAcEsHTUBLByymQjpDuVxbUzLJdpHhpOOjIBGvYTAc+cZoVMFh2U6swonyyr+pQRv5yL/k8GiKCPzovRfzT6ZIIICvUv1yRGNkl9G9ez6Xf1CwEsQUHsz3iciMYQny8ApH7ghqmod7V1cbvyvH0EmgTtDLIEJBa1nbrZxgzpluno+S1r3tMqR0tAEcerdMQxRuZIjDbBB9eDxjRhBAjUNwM9tYG64lyRfsjoqRyBKTKXBHHSi+5f0KrSl7QvKzjMPNox6ZbBGMfGkvZlef367Dg1Z9liRkR1kA6oe40RAaMW9QcWBIT6V3ZLY4mAmaya9Kt+ikEE+5XjO9omsv5qB3XPwJK2lrYpBhgxvcuggsEa76P/mNPslMQAJkmylaXgGBhF1kwzatLTyNLYRpZFzksTvNgbMmh8CWgU3XMtGB07gZiOaYlMYEw/y1gvaV9WsJZNAFW74hjBx3PN6GzIItERyoEJRKkOLEOGmwZaETyfMavpzHzXH42/wLGcihwMUzFsCwG3DLfK4nt6VXeyF9Slrmff0XnpmXTydBYx7SZgzWCAIEZ9zVQ2d9zGzRVkP1RG3AFM5ixuIuA41finTlimxl0xhxdTZWQDFaDEV+WR+SErRR2zH9RWbRZQWwhMeG9kKTUvOPekWwJ2vWlDQVGxsuIzND7Yh2wvASwBV/wQtEWwxTSk9KaxpOdHAM/jdKRn6p4AhW9MUbs0/mLQ+nmfCE4J9DnfOfe4RjIyhgxCdD3tEVnPCPY4HvWvgj8GTGRWaY817lkPzhHacQZ4YnIZ3DBo4jIaPS8xgEmSbF3JN4FEY64JK0NARq/Ye2WZmtO1MgQEPDKgxVI1AiB0nGRm6OjINNGYMYV1duvpvrhdeV42F18zEtf3dCqVpTVvaFC5YiEIRCLbx0ieDIaer3pxI4EYCTplgQYZRz1DxpdgUm0Se0CDrzrKiasspWS4ZkngVX2s5xDU6h7pifrkOW1iywjGIxhkv2sMRXDLcUkHqH6JzAidttip6OgI1FQXpqA1tlQPARY9l6lqOuJiTBZTqHTA0ld0+nT0EWgpOImbniII5bxVHxG0cGF+ZKM45qQHvkuW36ufCa7YF0zHk93knFP5HDfsA6ZJ2U49L47feF6nWLfK0pm+Yeke/snjnQvAsOrL/idoYv9qDEivAkxaX0yGK64T1XUcy5FNI0DXdcqMsA7U+dzmMwre6FKMqdNY1bXSB22N9E+WlXqUvWEmhuO6KrCtsjmyFwxkY7pec316aQKASZJsTSkxM/9m04qCKJ/GMDolOQDuVGSkyyiZb22gMaFxJRPG1G18LqNoAjUuNlaZZ7eenqdwGDEzMifLSZBJAylDxTVPXFg9q2nNWjACWxri2B6mqZiKJUNAoEzARXBOwMDvmRIWQKRD17P1d3ynrtpNRysnS8BKJ0nwQQAaHX0EDQQxXCKg6whIBARUDkELnag+BJKqm8YC2USyLBz/DC6ijglSGEiwPDlTtVP36zuykvyNbKrayJQ8QQWDAvahnCtBF9lvjivOP/Y3AUac/1yKwbrPalrzTmYCUIIC6orBG/Wi9ur/ersN5wTrpv4h01fMZnCOaO5osxeDG40N2QaVs6jt1Lw8lqU2M/iIdktlsm5cY6h+JuMW7SWDSPaj2kE7wuCGc19rZsniqUwGPtFWMENAm8LAj2CX6fC4PlJt1v3qj5QCTpJk60qJVb8LmI6CDAMNNcEFDVgxRocGkAaBaWX9n85a15ERi6yTAInAH9f4kckiaCLTwzLmNDul4EXoukZRtYyy9CAnT+BGZx3bS0dIkCFjrLbScOtepUukI4FbOn+uweP3kd3hMThkf6Ix5m5ptmtxu/KC41rimi/VPaZtIytEx643dhTTnZ4jtpkL6rXeigCDjpLssPqV5+LNbT6jAKiwP9U2HqLMNvC4DTLTEYhGYKXnCvSTsWY79MYMssbUs8atnquxoTpqHsQlGpxPGtNiXvg8bkbRWFT9+dw4dgiwCY45F9XHMdXItDYBpp5LEKbnqGwulYj6JKjjeI1jW/UmKGcfarmE6hZZb+lTDKHuIdiN44DzXnrgHFWbaTsYZHPOcL4yCCNzyPZSPxoHChiVYZFOOPY4djVnpJdod1U3Bju0PS3qD8ztvuxVWePEACZJsjUlXwMoRxPP99L6FBr+CAQjAyeWhVEojY0+ZCCKMUZyBAIlXFuna+VsaMhkeMjAkFXgGjk+OzKeMq5kG/Wv/k8gx8hYKRGVxV2dWl8lpyGwqTbwVVt0FvqOOw9pWOUMdR/7Mm6IoE55D1kvOlDpe27zGTlgpsOk8df4iM4sgmCxrdwIQyDKdhPMijFSvzNtL2Aghx439URGiAEJy41sTgQFAh0Eb0y9UafqG66t43PV/9ygER222kAHqw8BFB0vAS/BKuu5oFUhiIoOW8FDVXUfRRDGMUnQF3fQckd8ZDypV4JC6UQBAAExx2c8U0+6ixvZGIBwPNF+0B4xMNU45r3SOUE50/kcPxFcM5CMbzfS9wzkNJ6kY2ZXNN5o44oBWva5/q97ycKqrryHAQHv4xjkc3Q9n6P/c8c5A6GUAk6SZOtKwUHQdKSMLGPUTYdaDDSRHSEokoGjUaSxlSElk0jWQUZDzBGNGSNVOhI6xAWtag51jQ6EQC6mJwhEZFi5O0//xs0tZPQIomj4+TedEtPcYobIzMhBkD1ke8g6EEDpI9BFp0JWljpQf1ZhHaH6huxD1PXc5jM2WwdIR8zjdriWS3omS6R/+e7ZCEgYBKh+LIfnk7FvWT6dFh09x/GcZjUsFtP40hPXUQmgRmfH8UxHHtmZmD4jOCdQla4VHKjddN6qIwG55kKfHacWnGfJea6sAAGY3uSgfxkosE4MgAiaGCjGoE31oY3gHCKby4COjGcEPJFZJyBW/WLqmcwh20TQFJnmGPRqXHOuEpiTRSXo07Un7Z4x5czQMJhRWcw4SK+c89KfxmYMNlhXjnuVp/HATAgBocqgjY+gOwJb2qA5zdIu4CRJtrbkDCAnNA1N3AFGECFnQsca1/1EI8fjWOI6E4IO3SOnFyN3ArjIJsiQ892oMaVMMMtylJok+IpMDFkUXhfXD8lx6bVf0hVZ0GhUGb3TEUu30i83dbDdn3dvBNsyzHSK/Fv/0kGrflzzo/RYfBVUBNORUWB/kBXUs9n/HH9V1QxavCeyjQT/xdg+gsz5LQt3g7OedF5is/Qsgshi7Ifqp3oIMAss8Dw5MjcEg2ofQRsBHZdhiE1WeXEZBPXIg4wJcPgd28UggddxzPA3PpPjicBJOmVQyD7Rb5Hl12YEsY5xzSKBGwEQ66J+0Jo49QcBDYNY6VLPIPBkX3MtY7H5RmCl+XXuvtMKNpwxRa+6Lmo7tQAIaixTB/pNZXF8xmCGDCftGkEfg0fVi2A56pVjTNfG4ErjKALi+S3Tm0CSJNnakq8BlKGJaQ8aaUbiZKMiSydDEFkyRfh8fykdwJxmpxRE/iybxiRubqCTJjijoacD4UJksgw04LqfbBGZpCpsiKCzIOtDhmlW05oDj+kEyUyorTw0NaZU6fCpc9WFzp3ppmJMgeolg6/ULhe1q65iaDk2xKjKUY0qOSVfdxTTQzT06leWJ2aWIF1MBlkcArw+O07NU3B0cEpZqg1k1pgKv6jDlJzNIkNBQKH6aryyrzh2OD/4XP5OB62+js9T/bUGUfUjG8sNMSybfcxxzkCBY1o6405pjiO1hztfI/AVm0Rmj/3MAIOAjuwQx4P0R+BK9o9BEoMUBlxiS+NaQDKpBMcMGDVuyE4SELP+xexeDL4I/OO5eJwLBEoCvDzwmjaO4EpjigEWgxvNVY0J1Z07r8UMMhNBQKjxzzFahaUMZP1UJ44LBgwxwGefJgCYJMnWlRIz87LGNe+q1GusCI5kJGQ85aTmt8zSsfH1ZQSHMqRMoTLKJqMSo0gZNl0f14URxBAcyWkqqufnFYCdAAAgAElEQVTCdEbsdNQydHy26kdnrXIiMI5gkOtsmKoiuxDT58UAnHQisKN6LW6XbdzR5gy1m6kePocOrBjLojaQoeMay8jGMqIngyO9LsSascgY6fvF7coLDpbm9dK9AIvaRJaM7YtMjxwcNxBEFoQOTuVwN6XqwH4isGCgw/JigMKg4fMYt8h+sr4at2Jb57eseSsFAZbK4S5Sgi+NKbWXc5UghiCM/cLxQcAVQQ+BVxwnfAYBbGQWpVfqa16LkwsOrCe4JvPN5ytgLMYYx+N01HdsI58jeya9SXcEp6oj209AVllaw1zG4Ijt1LXsM+qJAJDBAYEo50jUSXwe1/9pnHIeaN4ReHN+FgPa7EuNf56fqXv13LQGMEmSrSv5q+DItMU0GtdsCExFir+ydGb+0nM5dQIIGnqCHRooGQpFnJERIPtBMKbro5OLaTimmhmBRmdFdoTROsuiAVR7oiGks2MaiOxYXDzP+2mAz249vWBnqq4laJCBJujRNXJMZKjElInlk87INMjp8e0QZCsiUOJzo7Mhi6TxxL4nwyWQprVnZM2KLabnrkuyywwU6CDVXjJNdEa6hswVWS6ODwIZATD2EYEMn8EAhGOWQE5/y3Fy167+JQhlSjD2j9pBUM3f+fo99ZfqrACEYODcfaflAZbmvNKP0ovWubJtHJ+sQ5yPDCoVkHDTBdln1VsAK4IRHiNDZltAS78TzFGnMdBgYMz+5fo6zknpnow110zyaCLahjnNTikIksjQcY6QeSOw5Jxke1Xu581h2luCSb4sgEExN/3Ma3FywdpfBvH6xM2G81qkg6CTJNnakp8DGFNSZLgYfceIWMaVjpcgiou/eQ9BAg0e0zHRIUfjO6tpjeMniIisA5k/GmUZH4JIGdpYXzJQfLsJI3w5JQFZAROmTuQ4xeAQZJPdYtvl5CJApV6UlomgLzJoxdhXXU+jTJaFrx7Tc7khhKwX+4Asl/RMVonAS84x3k/HEvufTBZBuNrBdVGqPwEuQQYBvuokZyu2m4Awrinl/xe0qixw3nKmZBpVPwYS7FsCAa1J1c7yCLDZPi6vEPslPTCgUX04D7hcIgZ/BNJcP0hWMLLNar+uJchSfxFIxHnMvtN3CkTIhElvajv7jsAyBnXUscrkuFU/z2l2Sn6gPOdyZL4jC8ffCZ6XtC8rAPca4xxvrDv7nPWXzgW2CG7je4OZlaFO2Q8xja55wTnCFHsEfJz/7MPI2lPfBMLDGyQAmCTJ1pQSM/MzWk7JDYomPIGTjJUYPqY4aLjICp7derr/oOV0v6rnSL+x32C/qPuxflbraQWRIZ2NjEhc60NAIociY7e4XXlBNEoGTXUg4OHr48g4CWwKBMnQ0ch+HgMkI61DYrneUQ4pOhUCORlGnuUWF/zH1DWdM9k0Oj+yOupXGW3+zhQv31NM/ahdAtvUDXd0qp9iG+m4dA1ZLzovjjc6QabAeP4YxwnTijH9REaELAgZJAFQMiFc8iAASOaN7Sk2BtmHZHvZNva9ns2NNvxXwFNgPqbl1T6OlQhs1A6tS2PAE0FOHKfSt8pa3K68AIhLlwToMQ2vPtFYjwFlVXWqm4BGuiRApF7iRgsCbNkyMsLcMU3bxfHE9cAMKCIw4/pSAmmWqf5Wv8RAKAZb7C8GD2w/2UaOQ7F0qgvnEJcK0N4QiLM+ZPcUVGsOMBhjIMi+5LINZi1kb6jbtAYwSZKtKwXvAtZklNHgzk4xTGRKGKXLEMow39Z/iK+e3cT9+yX5Z9W3m/itfYfk5RIs0TDqfbcCHTpiRUZZBmNxu/IcwMXoOwI0GX0ZLwIWOU9Gpue1meo39zraL+411K/oMdK/t3fh8RxkX9SOCDwWtyvPnSHX/choRwcgZ7cQTA+dgZ7JNA/rLkchR0XQTCDASJ9/a42O7o0ARuCZaRyOmwhO1S6BAaacmFYnyyQAy7V3am8EGqondS4HVIzFpbMhkKczj8GE9KCNMQReup7103jkWCBoJSjWvWJ0CKY5pzhO4gYQlRlBn9aIEngRVKkPqgKjFtk11TOyXOzjCKRYPgGD2qa+47ozlU82lGM5Ppt1jMzr/JY1R0XFeUbwyj7WdTGQ4Txn4CL7yHlF+0MARVaZ81jjlcdBqQ9iHeO6ZzJ3ajdthb4XIKcumLGJ439R26m+qO3UgiCfbB/PKOUyEQVQ1KcYWz2DddY84PKXtAYwSZKtKyVm5me2nuxnt87em7u4XXnOZi1olbF+VW0q8rSFNh3oN4IwTfSrDhvmm04v8U2nlxQAQH1314BBudHgO2cZmcrYct3h/JaVed10v+pBFqUYw6BXttHYESQyzXljn6H+wbcLwesH1eCV7ByZQ0W0dGDcnBEZTn0vJ8IU6aymNe8hZvQuJ0L2gNG3DOlZraf54m6j/cKeQ/2i7sf69/auLAAHZAeYCiUAUp1b1B9YwH5QZ3IyCgwIpsl4CgxHJoIgQLrisUJak8Y0OtfKRSaUDFhkN6QbPV/lSA8CVwxK1A7VUanYyDhqLChQmdW08KBeBjk8wiQCCwYJukfggIcFCxAUAx8CHuovsuAEL0yDiiVmOWTX5jSr2Z3PgFDjlfrXWInME1mr2G+ql0BwDCYZ4C1otfl7qqUvsZEqm21lW2gHGHwwENU4INMswMwgRNfomQSo0pHGOm2k7AH7nwxiPFaJLCnTvpEpZ5sZsOr3Oc2yt3CIAY2sOe0AAZ7WeTL44nzSh+OTH9WBwWUMMtM5gEmSbF0pMTN/ZEBff6LfIH+k97D882CvEf5438H+YK8Rfl/PkX5XtzF+R9dxfs/Bo/2ubmP8zq5j/eaDJvjNB03w6zqd6Hd0Hec3HzTBb+syzj/8Tulm4I8gcM3sJn5px8l+SYcpXtWmwi/pMCVn9GQoz2493S/pMMUXVoNMGSylrcj6EBQKVMmIxzWCAhtkwQRwF7Wd6jf2GfqF4PWO/oNzECdHzvQHWQsCHH4vlo/PlyFkepEMRNzZKeAV18Bd3mu4rwrgdcV/NfGLDxmRs6lkzhitE8jo7EKyfAQ8CgbkWJha51o/ppaYPhS4/9aeM/yKHiP98sOG+lU9R/q39ix0WLqPAJBpONW5WGqN7AfZtejEdE8x9odpKzK9/Oh5cnYCbFx0H1k03SvwQ4Ag8KjfCDhVJ46xyBRGoEMHLfAQGabIhlGXZJoV9BBs8BQAgoJirFRkAQm6CHLEjFG/6gMudSB4JIBW4BBTv5w/1Jf6Qjolc0/GTmWzLgK2HPfsc6ZUI+iRjnT0DzMqxYK8s1pP86ouo/2q3kP8ou7H+slNasAf2VgC9Rjoxc1F0iHHnGwnAb76TeOToI+pY+mWGQWOoXktTs6zPLQppzYvTwAwSZKtKCVm5ssuaOSrF+3pq6v29A9+2txXnbOXrzijlb9X2dbfndzR3zq+k787uaO/XdbR353Rzt+e2tHfmryfv3X8Af7m+M7++tiu/ub4zv7GuC7+7qQORYFf/Lw8ups/deTh/sxR/f2P/Y/yx/sO9j/2P8of6zPUH+sz1B/sNcJ/32eIP9J7mN/VbYw/cOjRfl/PkX5fz5H+2x6j/Dc9jvWbD5rgd3Ub43d3H+O3dTnOb+h0gt/Q6QS/pfMEv3r/iX5dpxP9hk4n+MJqkKnvLus42S/qMMWXtC/zc/ed5lfuf5IvaV/mF7Yr8zWzm3wheF07u9TPb5uxoIvaTs0ZU4JNgVSBNv0t9nRxu/ICVksbQqraVGxmXHV8AplOGVYB3Us6TPFz9532peD11r5DClKRZNvIhjH1J6fANWNMzxM8kvETCOIaQ14rpnhNWCaw8ttN/MY+QwuAjdhbgXummwRKWK7qLodDsESGSvWa1GiGL+422m/pP8ivPWSkn9mq8N2zbBOZD+qAAJIMalxzJZBBZkwOl+Baz1GdyXrK0cagIKYD6exVjtovYMH6EQzPb1lZEDwJ1MxtPqNgJ25MsbJOeq+x6qoxLjZJ117Yrsyv6DHS7zpioF/RY6Rf0La8IEAiUCZbzd/V3wyW1BZuimE9OYelN4GcKgRLZC3PazPVrz/0GL+411Bf3G20T2qUzRXNYTJ5DFq4nIFgXveI/dSc1rzhWLvqsGG+MgR3q2Y38ct7DS+wGRq7YuY1PwjGdQ3BJZf4qN+Z7eDYZYpXR4eR6eTfZF8ZkGguq15ntJySAGCSJFtRSszMV682d9/8s+L01v7OpP383ckdfXl5O199cdPNrtm0wXzTJ9v4Zx9u65+t3s4/+2A79ze23RxA/bae+/9u5/5CHffn6vinf9nRP3m8vn/ySImve2AX//i3u/rH9zT01Yv39BWV+/h7Ze39vbL2/n5FW199aVNffXkTX3XJnr764qa+8oK9feXPWvj7P23l75/V2pfP38ffndfWl5Uf4G+M6+Ivj+zpr4/t6q+O6+6vTe3sfy8/yF+d2NVfOaGbPz+qlz9/TC//2/DD/IVhh/lzg/v6C8N6+5PfOMJfG9ulVuD16aG9/cFeI/x3hxzj9/Uc6Q8cerT/tscov6PrOL+7+xhf2nm833jg8X7jgcf73d3H+I0HHu9X7Dcp/35p5/F+XacTfWnn8Tn4vHL/k/zK/U/yaw6Y6FfsNyn/XFINVAUy5zaf4RdVM6P6LGlf5he0Lfe1s7+YeV37nVK/uGOW7lcZV+w3KTfSMubaXLMQEbxA02UdJ+fGe1HbqQUba8joEPQIxPG6m/t+MVi9a8CgvGw6Ci1FkNOXXgg+5HTl4C/qMCVPEcq5Cbz9+vBBnwtC6ayVqo9HfsSUuMCRnJ92jwq0q45zm8/I07tcmyoAw40Dagv1yvbzSBuysQw8BG4iCyxQJqAgxy/9qI8JKARKmIYUyKosnZkHVno+1yLqefr7qsOGbbZWeM3sJn5n/8G5DgTGBJKVDSCTx74nuDh332n52GPaUdeQ5VN9CfrJ3t/cd6iv/U7pZktDlvQcUcDUa5xwvSFT1+p/riHU75p3BM6zms70n3QZ/oXz5cY+QwsYajJxGicEbwwKBP41NjQWBOxmNZ3p/92y0hcfNMn/X8/j/aIeJ/r3O0/2S/qN90X9xvuVR43xSweN8euOGek/7z1hs/FzY9kgv6ZyoN/7nX7+m1P7+gOnH+YP//AQf3D+If67BT398fO6+sMLu/kvv3F0AoBJkmxF+UIAeO2gYwuc0+/m9i563WafVdtsDkKerVOre1+/pZXf2XWs39dzpN/dPWP+NnxYu3tfnnegP3Xk4f70wAH+9MAB/sq3On/pPZs2bOOfrd/Gl03p5Cum7ltT31/Vc39/W/f3tnV/Z1v3t7bNgO3ft/MNL9XzT57d2dc/s5N/dPdu/u7kjv7u5I7+fkVbf7+irX906+6+7qESX3f/Lv7xfbv6x/fu6h/fs6t/fFdD//hXDf3j23fzj5bu7qt/uqevnNHaPzilla+o3MdXfrOVr71iD197eamvvazU115c6mt/2cTX/LI0Y2gv2NPX/LyJr17YzFfOap0/b8W0Nr76u3u5L97ZfdHO7j/f2b1qZ/fzd3b/WX338+q7/7S++zn1/YPvtPB3Ju3nb514gL8zaT9/e+L+/vbk/fztyR39rYn7+zuTMsb37Yn7+5vjO/tbJ2Ys79sT98+/e31sV39jXBd/Y1wXf21MN399bNcMcB97sL804lB/bUw3f2VUD39lVA9/eWRPf3lkT39xeC9/acSh/sKw3v7i8EN9w3/v9oVgdf2pu/szR/XzJ79xhD83uK8/+Y0j/NlB/fyZo/r7k984wv80YKA/3new/+WII/2JfoP8j/2P8j8NGJj//fs+Q/yP/Y/yB3uNyJnlx/sO9kd6D/Pf9xnij/UZ6i+OOvgLneozRx/q9/Uc6Y/0Hua/6XGsL+083u/oOs7v6znSf9PjWL+7+xh/sNcI/22PUX7PwaP97u4ZG31n17G+tPN4v7PrWL+7+xj/TY9j8/vv7p4tpVjaebzf0OkEv/mgCQXX33jg8X5L5+y7u7qN8Vs6T/Clncf7zQdNyIOEO7qO8zu6jvM7u471WzrXLMG45oCJfkvnCXm5N3Q6wW888Hi/5oCJOft9W5fj/Ir9JuX3KSC55oCJfnf3MX7l/if5LZ2zpR03Hni839F1nF/SYYovblfuV++fBSd3dB3n13U60W8+KGPaGfAosFH79N0V+03yy/eb5Dd0OiFvwx8G9/9C/f9hcP+8/Nu6HJcvObmj67i8jlqCcluX4/Jn39DpBL+z69h8WcoNnU4o6A+Vpf685+DR1QHcWP9Nz1F+/2EjfGmPcf67viP8131G+u+OGO7PTujhm05vUFjXBfV908KdfdP5O/tLMw/0v5zUx5+Y2N+fntrLn5rWy/84ta//dcYh/uTkPv5I72H+8GHD/XeHHON/7H+UP/utHv7i97v4Sz88yF9dsL+/etb+/to5Hf218zr6G1Xt/e9V7X3ZL/b1F0/p5s8O6uvrT22UPfvMBu4Pb+/+6Pbuv6/r/oe6vumJuv7ZE/X8g3tLfdX9jX3Nw4187WO7+Usn9fAXh/fy5wb39ReH9/K3zmjv617Y2de9tLOvf21HX//GDr5+2Q6+4d3tfcPy7X3Dyrq+cU0d//TNHfyVUT389bFd8/n90aMNa2WDP3qgYW4r9Pnso21rZ/vPa5oAYJIkW1FKzMyX/k8Pv2v+oX7/Tw/2e3/Wze88v4s/9MsD/RcHn1iwgPfak4b48/e28OcfaO6vPLanL/vzHv7OM4387b/t5u+/vKt/8HoDX/POTr7x9TqbO/fnawfinrm6g19SzdiIjdiwbrta3XtTxVF51L+kfZnfdNyw2gFWN7/+4PF+/4BBNfV9YPta3bfqqd38rm5j/HeHHJOvl1z73C61uvfty1r7i8N7+YvDe/kLw3r7ayd2rXV935nbzpdNOCgHYWt/WVqr+zZ9tK0vL2/n75W193cm7efLy9v5uocL67vpM/NNG803fbpNxu6u29Y/+3hbX/dQSc7Orqjcx5eXt/MNr9Xzjcvr+Mb36vrGd+v6hre3941v1fUNy+r6hje39w1vbO8b/r69r1nUxFdMa+MrKvfx1ae0yIDpa9u5v7Kd+8vVn//dzv2l7dxfrOP+Qh3/9Okdff2TO/v739w3A7qV+2SM8M/39HWPN/BP/lDfP/l9A//ksQa+7tESX/dIia97uMQ/ebjE1z24i3+4dHd/v6JtzmC/V9be116zR8Y237eLf/ZIPd/0aLUz1eeR7LPpih1949xd/d3JHfytEw/wtybu7x/e0cjX3tbI197W2NfeuoevXdrY1yxt7GtuKfW1Sxv7h0sb+ZqbSn35nDb+1okH+NsT9/dlEw7yd7/T1tfcvIevuXkPX31jE19zU6mvvqGJr7quqa+6rqmvvqGJr7mx1Fdf3yR71vGd/K0TD/BlEw7y989q7auub+qrb2yy+eeGJnl5K3++t785vnP+eW1MN195+V6++pZSX3NLqa++uYmvWbqHr1la6mtu28PX3LaHr15a6mtu38PfPa2tv3rswf7GuC7++tiuvqy8k6+5cw9ffecevvauxr7mrsa+9teNfM3djX3Nrxv72nsa+Zp7GvuHv93dXy87MAcJr43p5u+e0cY/fGA3//CB3fyjhxr6R4809LUP7eYfPtLQP3y0oX/4WEP/6PFdfe09jXzD/zQstBO/2z7r///dzje9vJ1/9nIdX/dsff/kbzv7+hd29vUv7uTrX9rJP7iyWa6nZRMO8reO7+SfvraDb1hWzze8Vc83vLO9b3ivrm9YXtc3vF/XN66s4xs/qOMbV9Xx9xe09rcn7p/rePmP9vFNG7bxTZ/VYu78oEGhTXuodjbi0+d39Pcr2vry8nb5Z8Pr9Wp174c3NfIPKlvVPPMn9WttI1b+sIWvqNzHV0xr4ytntPa1l+1Rq/s+W7NdPl8UYH7yeINa3bvu0V0KsjfLy9v5Z2tqZ79fPXvvBACTJNmKkr8LmAvrudZI3wmQaacd1z7xyI95LU722/oP2Tyy/2ED3zS/gW/6cX2/79j+vuSw4/1Hh57olxw51quOHOdXHTPSrx0zwpf0H5+vc1Ma585Zh/uvvtPf753bx2/5n75+7w97+R1n9PKHzjnYHzi3uz9wfle/54IuvqDvhHwR/eJ25b7kiHH+1K1t/Mnb9/GXf9PCX72/ub9wf3N/47E9fdkTTXzZn/fwd//ayN98ppH/pG2Fn9lqmq9RGvW39dw/2sb9E3P/1Nw3fk7U+vumBa+nOnffaf7OM41qZfDuPatHvhHmog5T/JIeJ9TauD844Ui/odMJfs0BE/3GA4/35888oFb3bVhVN2exxG69d3ezWt27/J49/Y/9j/K/HHGkPz1wgD915OG+YWXd2gHW8/b1l0f29JdGHOrvnNTR/cKda93WN6d2KlhnuvraJrVzvK/tkAEFgKr1z+1Uu+c+tH22gWbaPtk62En71bq+q85p7svL2/mKaW0ywFpVO/1u2mg5SF4xrY2vmNbG191fUqt71z+1c/7MlTMydnjjO7XrmzVXleZs8vsVbX3F/7SqdVs/OK0GZKyo3MfXXl07kLFxeZ3N2d+/1S5IXHf/Lrlul5e38/cr2vqmT7epXX3Pb14AbFads1et2+pnBAD4YO0A4Prnd/K3J+7v70zaL2fdP311h1rdu/KaPQszEwtqB8Tczd+cs5+/OLyXv3rswf7KqB7+7rn7ZONswzb+2Sfb+mcfbecb19TxDR/U9U/f397Xv1PPP1m2o3/8fAN/euCAfH32U0ce7q8vaedr/ribr/7D7v7BI4191UONfcVvm/j7v97T37tzL19++17+9s0t/KX5BxWw5vccPNpfOPtAf+X8jv7STzv5X+d39efO6OJ//X53f+Z73f2P3+7lj87s649W9vPr+w1LADBJkq0o+avgBPy4s0+Lu7mWhEebaP0Mj3LQ+pIb+wzdbG2VdqMKVPKVcVqDw4Xy3KGmdTVceB53UnKNFY/A4DEV3KjB9qh9vz78KN90eol/9nkbKfoP9gVtK/wnHcv9vE5T/NS2Ffl6Hy32vnzAcX7pUWP8Z0eO82uOGennDR3tNxw33BePPsavmjDMr5s41G+aMsgX9RtfsGD6vA7lfvt3+vudp/bzO+b29V+d3ttvOb233/HDXv7w2Qf7g+cc7Hed3cN/X9XFqw6emK/5WdR2qv9yxEj/5JGdfNMTdd3/VNf9z3Xdn6zr/lQd97/W8U3P1PFPn67nz9zcpmDN1Ln7TvM7fnyIL/tDE3/nT3v423/ew996qrG/89dG/t5zu/vy53fz915o6Mtf2tWfvOiAfD2RNtKsfHFX/3j5Dv7xih3845X1/JPV2/v6tXV9/Yd1fMO67Xzj+m1946fb+mOnHuaXdZycraXqdXSWrq6lI7u937G+pH2ZX9Rhil/X6UR/5vwDawfE/rar39F1XL5r/c6uY/29J2oHUAQAnx5xmN/Xc6Q/1Lf2bPKTM3r5E/0G+WN9hvrv+wzxZ+ccXKv7PtuwTZ7WfvIbR/hfjjjSl99aO4Cy+rFG/tSRh/ufBgzMQfonb+5YO6BwQdv8nt/3GeLPHn9Yrdv64pQe/sxR/fNlF6+d17FW9214d/t/GAC+t7S5P/mNIwqWAqxfsb1vXFvHN6yu6xtW1fVPV27v69+v5+vfq+fr393BP3lrR1+3bEd/7r965MsAHu872J+a0ts/fKHE1zy3q699Zldf/deGvvIvjfyDP+/uHzzRyFc+3tjX/mmXbO1yBIDX7ZjNsT9nc+79u5r432/Yx1+/fh9/7Zo2/soVbf2Vy9v5kz/qno9DpZz/NPcQf/bcg/zJs7r6k2d29yd+0NOf+mF3//PpPfyx/z7MH53T25/4Ti+/fdjRfne/oTXP/EED90t2cv/lTu5Lds4CqUU7u1+wsz98fD+/asBYv+nw0X5dn3F+6QHZOuJrDphYfZpCmV/WcZJf1nFyviZVG88u3y/7flHbqb6kfVnB7xdVbzLTaQlae6xjwy7qMMXPbj09X6vMdZOyMwtxLzeEXIRsTzoGJkmSrSslZuan7V1WAKq4UFgHMwsUcpcgd4vG4w1GlZziZ7aa5lf0GOm39B+Un0en892425Gv1SIA5I5U/asF2zomgkdXcGcnjy7hLj4ec6H28BDeBa0q/c7+gzc7SmX17CZ+R//BBW3X5gjuSuSzefwDF3trwwJ3DHK3KheRx521PH4k3ntt7y8+f/Gqw4blZ9VxMTp3dqos6op9wc0IXCSvMrSLURsRdBQHz2773t6Vvmp2qX/2gwaZU/1RA/f5DbL1TT9u4Jt+3MDXnL6H/6zbRP/ufmW+uH1ZwY7ecw6Y4hf1G+8LDjnRrzxirC/qN94vHHCc/+Lw4/yyo8b4dUNG+fXDRvqS/uPzQ211LMWFA47zy4Yf6/eX9XH/RbUj1eei6s/FO2XrJr9f4ou7jc6cWevpfvVxI/zK44b70hOH+DUThvtNJw7xmycO8RsnDvH/N2G43zF5kF99wlBf3G2iL2hV6Zd1nOxL2pf5ZYcc7zdNGuy3Th7kd5Yd5b8qH+i3Thnk10wc4ndPPdJvnjzYr5k4xK+bONQv6TAlX7C/sE2FXzVotN86ZZD/euqRvnTKIL9p0mBfOnmQ3z5lkN9ZNtBvnzzIl04a7LeNynaCygkvajvVrxl9tN9+0iC/vLrON50w1K+fMMxvPn6oXzrmaL9p/DC/4/jBfm3fcfmGmao2Ff7LAyb5TWNG+HXHHu1XjzrGrzh6pN8w6mi/7djhfunQ0X7F8GP9tL7H+WWDR/tlnU7KN9hUtanw8w+c7DcMGuWXHDHOrzxirF/YZ4JfffhYv3LAOL+0z3i/ou9xfk2fcb508ODNAaDGwPzqMXFGA7+x33D/eYcyP79duZ+7b0WeGRDLz7NAq9pU+NX7T8x3xV++3yRfWP09z9jjxpC5zWfkS040VrRLX+ynL+IAABcySURBVJ9bDxtRq81h1x96TL75IW7CUB05b3hcjmyEsh4EWGe2mvalG7xWz27i57ctL7Ah8egrATxuNtKGnHP3nZYfns3d4hqHPNqFR/HQD/D8wmijNAe5yYZHyMxrcXICgEmSbGXJXwVHZ86Ur/6vIx24Q5HnbpHJ41EcMgQyfjII2gEZz6MT+NGhq7pGAFE792TE4sHIPL5AxznwzK94Gj/bzKM4Ru9ysld1Ge3X9R3i53Ue7T9oOT1Pd8tgyjBqJybfW0tQFc9z43sxdSagABZ3dKo9NMrUOa9TGy4+ZISvKsK8XnXYsILz8nhsi9olR0X9kWHVNQR5OvSYB2Jz16yOguHOyjnNTvHLe33xrsZrew/LGWHuMqXTFOsbz7PTrlmeecedq7OazvQzW03zVd/+4iN/Vs9u4t/dq/CVXHzlHgMJtU3fCyirXnE+8Zw7ziUeKcTdxDpCJB5qHI+M4bEoPJdSdWcQwR3R2u17SYcpBbuaubt2cbvyzQ5vZvCnfmebWQbByPf2rqxZbvE5+l9TrX+CvHiEEY/1IaiJZ3LGY1J4Dh/HB8/V1Bz/7l4n++ovOR5qzewm2Rl91YAzgj8GygwKeSAzd87HnbxfNl9u6z8kPw+V40w2aCGAHoMp6oP2mgGp6i2dqG+19EV2j8fG0G7FI400BrmTe1bTmelVcEmSbGUpMTP/ZtOKAqNAw85olccIyADI0JAVU4QYX5FF48ePGEaCDxkPMneKQAU29AyeaUXjFw2dHCiBgpw320YjJkPFa1gntonsGq/VmWcCLfGds9IzXxHHetCIylnIUemNITyA9lt7Zufa3XXEQK/qMtrPa1MT2av9qrccMiN3PUeGmefwkdnka/niMRx0AtQL2dxrew/b7I0rK/6riVd1H1HgYPhmGgEZjjvpm3qNAGZOs5r3SCsNpbWqn5fuv+qwYZsBHJ5rxsPJeXwLjznR79Qff6NTVF9HRlnf6Y0dC9EfXOqgMRePm4mOmGe6MdAgOFR5PMfxkg5T8usYRGn+qk84BphNoC5nNZ3pS3qO+FLGmvNN5Wg8cP5y7Enf8WxIzWECmLiUhPaJzNyXAbBb+w7J5wSDwGJnF0p/0rH0KL3QNhCUFntDEV+vKUDFIFJ1IGhmn8om6nueMcn+47yinaAdZDaFNpr6Zf9HFvHM1pMTAEySZCtKiZn57GY1J9DTefENG3xLAlksGXUxYGSWdK3uZxQoZy1jrXJkQHRYLI24ftO1+o1pBRqZyHTRackwkrWUM4mvaCKQJAtI4yWjTlAivVCHc5vP2Cx1TSch4yvgxO9lUHUf26l68fDbWL50wTPKBAoIENlPKpN9T8Yg/kbnF51gZJdnNZ3pJzeZ4Zf2GOW3DxiUv9kgPlO6J9DheKGDZR/Fccv6y+ldfMiIok712t7DCsYO3zahZ8dAYX7Lyvz1dQRB0rOcuvqC80NgROOZ4499oXIJ6sgOEqRzPkWWh+OaB/iSKaNuGexwTS37SO2RbgXKI9NEFurGPkM3W27xwbezIEDt4j2cb9QFWTQGCXOa1Zw7qLqRmSdwYT+yfRoDVd1H+PL/2ryu1/YeVgCmFMzRPnIc6f/sZ81XjlXZJtnheS2yQ8sv7THKr+o9xK/oMdK/u1fNc2MwIT3xtZLSk4JS1Ztzkowqy1TwIbtNeyRbzewMx1cE2upLZYZO2n2mlzVODGCSJFtTcgaQTBSZP4IPRfsyjARjmsSa3GJbeK9+E9CMIIZvGJDRloHSq7XIIkXnSIMmg6l6EEzRedAg6RmKTGW8oqONIIMOUferHcVAJ503gdlCtJmsCRlBAjUxrTqgl5G19K20H50igSI/laUz81Q/2yM9UTdxzSZZYjp89a/qy9d76Td+1G6CbK3FIntIJk7snuoqgF0MwEaGam7zGX5ykxle1WW03139Jopz9qko6Bc5SAYzXMfK14XpGv1fICgyQ9RdTOOrz+L16oPIsApMMNWuawgaCQz4LmGy3JyrBF9imwnmpXeCYAEBgorYZo0HXXtW62l+esfRvrT/IL+q50if1KhmfDDg0HN4aDZ1rjFCIKL+IvNK3alf+uw4Nf+XfcF5y4Blaf9BfnrH0f69vWuCDOlAtku2MTLkGjMCY3ETGec4QbsCCGZoyNpxXMgG8ncyc1pKM7f5jHztn+qhND7fwc5AnXrXvOa8jZmiOFbmNDslf6baMarkFJ9emgBgkiRbU3IAKKdGA0QjxA0HNKJ0eGRr5MSYTpDTZupJEaUMVUw/M0qX0RDLwldvkVmJzBSdM1NdjELlbLRoXEaXQIlROd8MwSif6UmmTVRHpbClazIMArDUm5wdWVLVjYwH02sEfwIwcgoRtBKkMnXKNtEZRqYiglgCCLIEMvoMNMSoaWxJD9KNgJMcidgMOlUCusjYSIcEx9STnBXbSTZL7VI/cWMOGXN9R2ZPjBrBEB02ATSdI8eu+ljjgDvWqzDOVA6DLrV5VEnN2j+lCOPc5XjgXNR44RshOE74vmPpiQED36xB8KBnxKCQYF2gNtoiZhLI3sdgSeNP18Sghn2oawlWBXw1Zlk36ZL6JzCPQVaxOUtGjIFqzCgsbFPhLeoPLJhP8Q01AmH6TvOH5RMYxpQvxzr/r7JYX9pczo0YwLGfNYYj26mP+jdtAkmSZOtKvgtYhpzOioaaETONHVOcTHHIWJChI0AkEGP0KicrVoUgILJhql+xdXcCVHx1Fx2JjBujdxkjvQpNAIV1ouOQkRTI6LNjzQvO6Sj1/xg9k2EksCLbRMemj9rAlKL6h6BG95IpIlhR2wmeeaZhdJLRaEv/AsSK5BkoCOxIB6pHsQXj1JN0I1ZpYZuKfCzEdaDUCdsZmZJLOkwpAHzSdXSUTO3LyfJvBjNRnwS46g86WbaRzCnHezFWkABP4I9rCGP94ngQSOLRSpEtZt+SUSPjHQOemOKkHYjzmyCKYycCX7FPBCUCLdIPU44MnsQYxyUATGeLZY2vfSPrzPFE0CM7w0BPNlO/qS0cVwTNxRhgtTcGDBxLtIscwxxL1CPtM+dJnMP8rhh40++0XUuqd+ZLfwqEFKAxOJQemYrm/FTbEgBMkuQfk5PN7DUz+8TMHjezg2t5X4mZ+fTSijwNFBmjCDpI6dPxKdpn2oopATIejADjGqYISGY1nVmwhocOQvUSKCDQI2DV9zSkTJFxN6baQ0PNdqsuNPCRMWMaODpFpnDkVMSCMn0agQRBHEGS/ub6LRleOmuCKumbjos6pXMmE0sQEAE1HaDqLuDEdhMESE/qU40N/SbGNAIUPj8yD6wzv2P/k2HhmBGg4hjnv+xHgVOm9wjWyOpwrki36kMBA7E87Oe5zWfkTlOp5GLMCxfsCyCoPtIjGSn2tcoTqJSOCVpiYFVsXKvu3DAVAZ6Ye7KgrIfmHW2CAgCmDyOTGlOXnBsqh/eSoaVe+G8MMGmPmNVgf3AOF9NZHH8E3wRtnAdiftW3GmvRlhBwRfvBMSU9a/zR7mveaS5wx+9Ju8/M5wcDPJWhuUx7G+2hdEogqPITAEyS5B+TsWa23swmmVlHM/uFmX1gZnvU4t6CcwAVoZKFYITcZ8eaYwZ0VllMC5HxkINjGogLlslYkFGgw5bR4AYAMlJMkREoRTaNwIb1Vjlk7qJhU/0iMCa4YQpT9ZQOpUdeI12RiYlsD0EzQRhZKabSaKwJhqQzOVOm4PlMORge5SHgoWdHvRFwRTBGkMzr6OTIekSmTIwVj8hRn5NNI1OpNDGZT5UZ+ziydGTB1d54XBGDAoIssq0aJ9Idx3EE1QQGAnOcd9Q/GXUyNKqHxgDLPLv19JyVie2sLJ3pLeoPzMc4nbfujSwyAzwCWdWVfazfGGzFuU1WnQyj2qNlHwQ8tFGcE/E5BFIcd7pH7Thp95l5qlfPj2wlbQFtFjeq6RkCS7pf7DjnHPuJczvaO+qe/cx+l03VdWSmaf8qS2vaqftHldQEUdKXwLp0wOdLn1zCQnaQ9pL2jYFtVZuKgv7T9QkAJkny1eVxM7sAf29rZsvM7NRa3Ju/Co5MDg0jmTkZjRitMkWkf2kwySzEMmUoCHgYrcoR6bkCS4z+aSgjU6jvuZaODozPlOEmUxOjaILcyHzReTMdKCBBBxijfxp26ozPIuCh8acDVX3YT2R8aHQjQ6T/kwVhX7MfaOjp6KOeYjqNjjAuVFdZdPbUPR0+QYvKjECHoE1gheNbTJ6AJvUZ102SKeLYI6giC0jwznqTEWNfkB3jeNB84VpI1YNrArlppNj8ius/BSb5DAJVAueYFhRrRHuh+jAVG8ee7uXc4VjnmCFQZn8SHKvuxU4LiAA9gn0yhGRPyZBGsK+5J+DHesRPBELSO5d6tKg/sGC8RBuh8ax2SLcE2Zznajc3k+mMTupF85n3xfnCzV56VrTjvEfXMcBmuzXGOYYIXOc2n5HOAUyS5CvK9ma20cyODt9fbmZLa3F/iZn5+IYVRSNeAry4ZotpQ7EkcQ2K0jY89oTgLAIMGUFdT0fG7xjly4DKCdBhRMZKjo4gUfeJaVGbeK0MPg0bgS9ZO+qKxlNtptHlGsQIPAgcWIbaGoEFGVIBSQLKyIDIoRFgRifPetGA05kXYxvELEi3el5cUB7XQ0UmhN+JqVDbCTI4fsiUxFS1GJfPGyvsM56ZpjGuORKZrcgYyvGx/rEPCBDlDCMAIMBe1LZmbZXaH1lA6UNtiazhrKY161gJYFhHzQECOzKLApicj1yXpmtYj2IB2oJWlfkYEegSOJLeCbqKrR9lWlg6VXulU46lqBvdL53EecY1bJqv8Xm0a0zrkgFWXTlO1OZYPz4rBlB8HgEgbTIDQtaNQROzEXH+E4ir3rHd0X7QBnJs6Fqy02qb7CRtRNoFnCTJV5M9LZswh4Tvf2IZMxilnmWTS59mZubfajbRD93hJJ9eWuGzm0318Q2zf09tXu7zWpT57GZT/ZtNK3x6aYV/s2mFn7Z3mU8vzf4e37DCT21env+m/89uNtWnl1Z4WeOa68Y3zK5RWbObTfVDdzgpL1//H9+w5vdvNq0pg89T3c5oOcXPaDnFv9k0u352s6k+r0XZZs8pa1xTN7VJ5as8tl2/nbZ3TVmzm0310/Yuy8tTfXSt/lWZvF/1n91sqg9vUJG3kZ9Tm5f7GS2n5PeWNa75nNq83MsaZ2UPb1DTF/pO/5deVAfqkG1jn0qn7GP9Pb5hzb3DG2R9dGrzcj90h5MK7i9rXJE/V9ezbP3NtrEvdU1Z45qxp3qqvRwD7DeVq7qzHRyDKk/f6f/qd9Y7PovjgX1J3euj8qU/PVdtKmuc6VLfsTz14Rktp+T149zR7xpDKr+scdY3Ue+qE+fH9NLs+XEesh7sF80p9R2/l05UD46BeS3K8vkSbYLqxHLUD9LbN5tmZUwvrXmGxr/azvmnstVutUe6ju1kPThHNXbGN6zwM1tP9kN3OMlP27usQI9xrrKe0i3tmNoe+1rt0vziHJE+WV+VdUbLKQXjjGNXOlAdZIM4X9gn0oPqrT7VGNS17Bf9X+Wdtnfh+ODYpb2hfacNm91sqp+4+6QEAJMk+QryVQHgvOrr0yd90id90id9vo6fZpYkSZIvla+aAo4MYImZ7W81ky7+lj7/+KdZ0mvS67/RJ+k16fXr8GlmZttYkiRJaiWPm1kV/t7WzN602m0CMcsmnVf/m+RfJ0mvW0aSXreMJL1uGUl6TZIkyRaTsZad/zfRzDqY2RLLjoEpreX9yUBtGUl63TKS9LplJOl1y0jSa5IkSbaozDCzv1t2HuDjZtbjK9ybDNSWkaTXLSNJr1tGkl63jCS9JkmS5Gsr9SzbHFLv/7ge/3+TpNctI0mvW0aSXreMJL0mSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZJ/TE42s9csO0fwcTM7+P+0Nl9/6WNmt5vZW5Yd7RDfwLKNmf3QzN42s3Vmdq+ZtQnX7GZmV5nZGjNbZWYXm1n9LVflfwv5bzN7wszWmtl7ZnarmbUL1+xgZj83sxVm9qGZ3WSbn3W5t5ndaWYfV5dztpnV2WK1/vrLdDN72rKxtsbMHjOzQfg96fRfI6daZg9+hu+SbpMkSfK1lbGWnRs4ycw6mtkvLDtAeo//y0p9zWWQmf3IzI6x4gDwu5aBuhFm1smy1/G9YpkzkNxlZk9adlbjYWb2kpldvUVr/fWXu83sJDPbz8wOtMwp/t3MdsY1F5rZ62Y2wMy6WgZmHsHv25nZX83sN2Z2kGV9tdzMztyyVf9ayzAzG2xZENLWzOab2aeW6dks6fRfId3N7FUze8oKAWDSbZIkSb628riZXYC/tzWzZVb7V8j9p0sEgNtYxvzNxne7WMaujqv+u0P1fd1wzVFmtsnM9txiNf33k8aW6alP9d+7WAZcjsU17auv6Vn99yAz+8wKWZZpZrbasndmJ8lkpZlNsaTTf4XUN7MXzewIM7vfagBg0m2SJEm+trK9mW20zRmsyy1jrZJ8uUQA2Lr6u4PCdQ+Y2cLq/0+2jGWl1LGsL47ZAnX8d5V9LdPl/tV/D6j+e9dw3d/N7FvV//+hZcwqpVX1fZ23TDX/rWQ7ywKR9ZYx/kmn/7xcbmbnVf//fqsBgEm3SZIk+drKnpYZmkPC9z+xjBlM8uUSAeCh1d81Ddddb2bXVf//f8zshSJlvWfZeq0kGRN9h5k9jO/GWwZcovzBzM6q/v8vzOzX4fedLOuTQfafKwdYtgZto2XLEwZXf590+s/JOMtSuFrecb/VAMCk2yRJknxtJQHAf14SANwycqFlG5P2wnfJof7jsr1ljGpXM/uxZevMOlrS6T8jzc3sXcvW+UrutwQAkyRJ8m8gKQX8z0tKAf/r5QIze8OyVBglpdT+dXKvmS2xpNN/Ro62TAcb8XHL1vJuNLPDLek2SZIkX2N53Myq8Pe2ZvampU0gtZXP2wTybXxXYsU3gXTFNUda2gSyjWXgb5ltfmyOWc2i+lH4rp0VX1TPXexTLVtUX+9fXN9/Z7nPzC6zpNN/RhpYtj6VnyfM7Irq/yfdJkmS5GstYy0DJxMtAyZLLGOn4llVSWqkvmUM30GWGfNvVf9/7+rfv2uZDodbtvbqVit+DMyfLTtzsZdluwj/04+BWWTZ+rS+ZtYEnx1xzYWWMSj9LQPQj1Z/JDpW49eWHSUz0LLU+n/ysRo/tmwndUvLxuOPLQs2vlH9e9Lpv07ut82PgUm6TZIkyddWZlhmpNZbxgj2+L+tztde+lkG/OLnsurfdRD0O5aB63stO3+NsptlgG+tZdH+JZYOgi6mU7fsbECJDtZdaWYfmdnNloFESgsz+5VlB+suN7Nz7D/7YN2LLVtPud4ycHGv1YA/s6TTf6Xcb8UPgk66TZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZJsFfn/AHZ5kp/GwNuGAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check the calibration of the first and the last image with rings\n",
    "\n",
    "print(\"First & last rings\")\n",
    "\n",
    "print(\"Total number of images:\", len(gonioref.single_geometries) )\n",
    "\n",
    "fig = plt.figure()\n",
    "for idx,lbl in enumerate([\"del_10.0_0001p\", \"del_65.0_0001p\"]):\n",
    "    sg = gonioref.single_geometries[lbl]\n",
    "    if sg.control_points.get_labels():\n",
    "        sg.geometry_refinement.set_param(gonioref.get_ai(sg.get_position()).param)\n",
    "    jupyter.display(sg=sg, ax=fig.add_subplot(2, 1, idx+1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function before refinement: 1.2457867804583228e-08\n",
      "[ 0.80588807  0.01627369  0.04329277 -0.00263014 -0.002175    0.01745329]\n",
      "     fun: 1.0840209527662121e-08\n",
      "     jac: array([ 4.62724835e-08, -1.16963339e-08,  5.90127193e-07, -4.83917202e-07,\n",
      "       -3.87120527e-09, -1.39958960e-08])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 36\n",
      "     nit: 4\n",
      "    njev: 4\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 0.80588823,  0.01622094,  0.04329203, -0.00262952, -0.00221753,\n",
      "        0.01745631])\n",
      "Cost function after refinement: 1.0840209527662121e-08\n",
      "GonioParam(dist=0.8058882322872523, poni1=0.016220937406978945, poni2=0.04329203358397654, rot1=-0.0026295185046565014, rot2_offset=-0.002217531057579051, rot2_scale=0.017456308042413993)\n",
      "maxdelta on: poni1 (1) 0.01627369140392072 --> 0.016220937406978945\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ 0.80588823,  0.01622094,  0.04329203, -0.00262952, -0.00221753,\n",
       "        0.01745631])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Final pass of refinement with all constrains removed, very fine refinement\n",
    "\n",
    "gonioref.bounds = None\n",
    "gonioref.refine2(\"slsqp\", eps=1e-13, maxiter=10000, ftol=1e-12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MultiGeometry integrator with 121 geometries on (4, 66) radial range (2th_deg) and (-180, 180) azimuthal range (deg)\n"
     ]
    }
   ],
   "source": [
    "#Create a MultiGeometry integrator from the refined geometry:\n",
    "\n",
    "angles = []\n",
    "images = []\n",
    "for sg in gonioref.single_geometries.values():\n",
    "    angles.append(sg.get_position())\n",
    "    images.append(sg.image)\n",
    "    \n",
    "multigeo = gonioref.get_mg(angles)\n",
    "multigeo.radial_range=(4, 66)\n",
    "print(multigeo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of bins: 5070\n"
     ]
    }
   ],
   "source": [
    "# Calculate the optimal number of point for integration\n",
    "over = 1\n",
    "npt = int(over * numpy.deg2rad(max(multigeo.radial_range) - min(multigeo.radial_range)) / \n",
    "          numpy.arctan2(pilatus.pixel1, gonioref.nt_param(*gonioref.param).dist))\n",
    "print(\"Number of bins: %s\"%npt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f1cecab69b0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Integrate the whole set of images in a single run:\n",
    "\n",
    "res = multigeo.integrate1d(images, npt)\n",
    "jupyter.plot1d(res)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the goniometer configuration with 1 angle\n",
    "\n",
    "gonioref.save(\"ROBL_v1.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0840209527662121e-08 1.0840209527662121e-08\n",
      "Cost function before refinement: 1.0840209527662121e-08\n",
      "[ 0.80588823  0.01622094  0.04329203 -0.00262952  0.         -0.00221753\n",
      "  0.01745631]\n",
      "     fun: 4.400458242407975e-09\n",
      "     jac: array([ 2.17205115e-08, -9.54599980e-08, -7.19830950e-09,  7.05737097e-09,\n",
      "       -2.67150840e-08, -8.02348069e-08, -1.81738672e-06])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 113\n",
      "     nit: 12\n",
      "    njev: 12\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 8.05880145e-01,  1.62057756e-02,  4.16992199e-02, -1.34222884e-03,\n",
      "       -1.31951269e-04, -2.22916926e-03,  1.74567370e-02])\n",
      "Cost function after refinement: 4.400458242407975e-09\n",
      "GonioParam(dist=0.8058801453609882, poni1=0.016205775638975062, poni2=0.041699219865116, rot1=-0.0013422288394505186, rot1_scale=-0.00013195126938364668, rot2_offset=-0.002229169264716073, rot2_scale=0.01745673704157699)\n",
      "maxdelta on: poni2 (2) 0.04329203358397654 --> 0.041699219865116\n"
     ]
    }
   ],
   "source": [
    "#Can the refinement be improved by freeing another degree of freedom ? what about rot1 ?\n",
    "\n",
    "goniotrans2 = GeometryTransformation(param_names = [\"dist\", \"poni1\", \"poni2\", \n",
    "                                                    \"rot1\", \"rot1_scale\",\n",
    "                                                    \"rot2_offset\", \"rot2_scale\"],\n",
    "                                     dist_expr=\"dist\", \n",
    "                                     poni1_expr=\"poni1\",\n",
    "                                     poni2_expr=\"poni2\", \n",
    "                                     rot1_expr=\"rot1_scale * pos + rot1\", \n",
    "                                     rot2_expr=\"rot2_scale * pos + rot2_offset\", \n",
    "                                     rot3_expr=\"0.0\")\n",
    "\n",
    "param2 = (gonioref.nt_param(*gonioref.param))._asdict()\n",
    "param2[\"rot1_scale\"] = 0\n",
    "\n",
    "gonioref2 = GoniometerRefinement(param2, \n",
    "                                 pos_function = get_angle,\n",
    "                                 trans_function=goniotrans2,\n",
    "                                 detector=pilatus,\n",
    "                                 wavelength=wavelength)\n",
    "gonioref2.single_geometries = gonioref.single_geometries.copy()\n",
    "\n",
    "print(gonioref2.chi2(), gonioref.chi2())\n",
    "gonioref2.refine2()\n",
    "gonioref2.save(\"ROBL_v2.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "First & last rings\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check the calibration of the first and the last image with rings\n",
    "\n",
    "print(\"First & last rings\")\n",
    "\n",
    "fig = plt.figure()\n",
    "for idx,lbl in enumerate([\"del_10.0_0001p\", \"del_65.0_0001p\"]):\n",
    "    sg = gonioref.single_geometries[lbl]\n",
    "    if sg.control_points.get_labels():\n",
    "        sg.geometry_refinement.set_param(gonioref2.get_ai(sg.get_position()).param)\n",
    "    jupyter.display(sg=sg, ax=fig.add_subplot(2, 1, idx+1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MultiGeometry integrator with 121 geometries on (4, 66) radial range (2th_deg) and (-180, 180) azimuthal range (deg)\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1cec9447f0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Create a MultiGeometry integrator from the refined geometry and display the integrated image:\n",
    "\n",
    "multigeo2 = gonioref2.get_mg(angles)\n",
    "multigeo2.radial_range=(4, 66)\n",
    "print(multigeo2)\n",
    "\n",
    "res2 = multigeo2.integrate1d(images, npt)\n",
    "\n",
    "#Display the 2 curves with a zoom\n",
    "fig = figure(figsize=(10,5))\n",
    "ax = fig.add_subplot(1,2,1)\n",
    "ax.plot(*res2, label=\"rot1 & rot2 rotation\")\n",
    "ax.plot(*res, label=\"rot2 only rotation\")\n",
    "ax.set_xlabel(res.unit.label)\n",
    "ax.set_ylabel(\"Intensity\")\n",
    "ax.set_title(\"Azimuthal integration of 121 images merged\")\n",
    "ax.legend()\n",
    "ay = fig.add_subplot(1,2,2)\n",
    "ay.plot(*res2, label=\"rot1 & rot2 rotation\")\n",
    "ay.plot(*res, label=\"rot2 only rotation\")\n",
    "ay.set_xlabel(res.unit.label)\n",
    "ay.set_ylabel(\"Intensity\")\n",
    "ay.set_xlim(10.5,11)\n",
    "ay.set_title(\"Zoom on first peak\")\n",
    "ay.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the first model, the refinement was not perfect on the very low angles and indicates a miss-fit. Relaxing the constrains on *rot1* allowed to spot a non (perfect) orthogonality between the goniometer axis and the incident beam. Releasing the distances is also possible, for example to cope with the sample not perfectly mounted on the center of the goniometer. \n",
    "\n",
    "## Evaluation of the peak-profile\n",
    "\n",
    "For every peak, as listed in the calibrant's definition, the peak height can be extracted and the nearest minimum evaluated. The the full width at half maximum can be measured an ploted as function of the scattering angle. \n",
    "The FWHM can be fitted against Caglioti's formula: \n",
    "\n",
    "FWHM² = U tan² $\\theta$ + V tan $\\theta$ + W"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Line profile function...\n",
    "#Peak profile\n",
    "\n",
    "from scipy.interpolate import interp1d\n",
    "from scipy.optimize import bisect\n",
    "\n",
    "def calc_fwhm(integrate_result, calibrant):\n",
    "    \"calculate the tth position and FWHM for each peak\"\n",
    "    delta = integrate_result.intensity[1:] - integrate_result.intensity[:-1]\n",
    "    maxima = numpy.where(numpy.logical_and(delta[:-1]>0, delta[1:]<0))[0]\n",
    "    minima = numpy.where(numpy.logical_and(delta[:-1]<0, delta[1:]>0))[0]\n",
    "    maxima += 1\n",
    "    minima += 1\n",
    "    tth = []\n",
    "    FWHM = []\n",
    "    for tth_rad in calibrant.get_2th():\n",
    "        tth_deg = tth_rad*integrate_result.unit.scale\n",
    "        if (tth_deg<=integrate_result.radial[0]) or (tth_deg>=integrate_result.radial[-1]):\n",
    "            continue\n",
    "        idx_theo = abs(integrate_result.radial-tth_deg).argmin()\n",
    "        id0_max = abs(maxima-idx_theo).argmin()\n",
    "        id0_min = abs(minima-idx_theo).argmin()\n",
    "        I_max = integrate_result.intensity[maxima[id0_max]]\n",
    "        I_min = integrate_result.intensity[minima[id0_min]]\n",
    "        tth_maxi = integrate_result.radial[maxima[id0_max]]\n",
    "        I_thres = (I_max + I_min)/2.0\n",
    "        if minima[id0_min]>maxima[id0_max]:\n",
    "            if id0_min == 0:\n",
    "                min_lo = integrate_result.radial[0]\n",
    "            else:\n",
    "                min_lo = integrate_result.radial[minima[id0_min-1]]\n",
    "            min_hi = integrate_result.radial[minima[id0_min]]\n",
    "        else:\n",
    "            if id0_min == len(minima) -1:\n",
    "                min_hi = integrate_result.radial[-1]\n",
    "            else:\n",
    "                min_hi = integrate_result.radial[minima[id0_min+1]]\n",
    "            min_lo = integrate_result.radial[minima[id0_min]]\n",
    "\n",
    "        f = interp1d(integrate_result.radial, integrate_result.intensity-I_thres)\n",
    "        tth_lo = bisect(f, min_lo, tth_maxi)\n",
    "        tth_hi = bisect(f, tth_maxi, min_hi)\n",
    "        FWHM.append(tth_hi-tth_lo)\n",
    "        tth.append(tth_deg)\n",
    "    return tth, FWHM\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1cec8d0390>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = subplots()\n",
    "ax.plot(*calc_fwhm(res, LaB6), \"o\", label=\"rot2\")\n",
    "ax.plot(*calc_fwhm(res2, LaB6), \"o\", label=\"rot1 + 2\")\n",
    "# for lbl, sg in gonioref2d.single_geometries.items():\n",
    "#     ai = gonioref2d.get_ai(sg.get_position())\n",
    "#     img = sg.image * ai.dist * ai.dist / ai.pixel1 / ai.pixel2\n",
    "#     res = ai.integrate1d(img, 5000, unit=\"2th_deg\", method=\"splitpixel\")\n",
    "#     t,w = calc_fwhm(res, calibrant=calibrant)\n",
    "#     ax.plot(t, w,\"-o\", label=lbl)\n",
    "ax.set_title(\"Peak profile as function of the angle\")\n",
    "ax.set_ylabel(\"FWHM of peaks (in degrees)\")\n",
    "ax.set_xlabel(res.unit.label)\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1.78018609e-07 -1.05916053e-08  1.61092184e-07]\n",
      "[[ 4.20844197e-14 -3.16262369e-14  4.92066606e-15]\n",
      " [-3.16262369e-14  2.47707384e-14 -4.08398025e-15]\n",
      " [ 4.92066606e-15 -4.08398025e-15  7.48147437e-16]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1cec8d5400>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Fit against Caglioti's formula:\n",
    "# FWHM^2 = Utan2 + Vtan + W\n",
    "tth_deg, FWHM_deg = calc_fwhm(res2, LaB6)\n",
    "\n",
    "def model_Caglioti(tth_deg, U, V, W):\n",
    "    tantheta = numpy.tan(numpy.deg2rad(tth_deg)/2.0)\n",
    "    FWHM2 = U*tantheta*tantheta + V*tantheta + W\n",
    "    return numpy.rad2deg(sqrt(FWHM2))\n",
    "\n",
    "from scipy.optimize import curve_fit\n",
    "fit,cov = curve_fit(model_Caglioti, tth_deg, FWHM_deg, p0=[1e-6,1e-7,1e-8])\n",
    "print(fit)\n",
    "print(cov)\n",
    "ax.plot(tth_deg, model_Caglioti(tth_deg, *fit), label=\"U:%.1e, V:%.1e, W:%.1e\"%(fit[0], fit[1], fit[2]))\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total execution time: 21.477s\n"
     ]
    }
   ],
   "source": [
    "print(\"Total execution time: %.3fs\"%(time.time() - start_time))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "This notebook exposes the how to calibrate the goniometer for a small detector moving on a 2theta arm. \n",
    "Once calibrated, the geometry can be saved and restored and stays valid as long as the detector or the goniometer is not unmounted from the beam-line. This configuration can subsequently be used to integrate the data acquired with any  sample, in minutes instead of hours. The resolution limit is now the pixel size. Fortunately, pixel detector with small pixel like the MaxiPix or the Lambda detector exists and offer higher resolution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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  "language_info": {
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "pygments_lexer": "ipython3",
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