tutorials/01B_quickstart_with_objects.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1B. Quick-start with object-oriented support"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Authors: *Thomas Bédrine* and *Valentin Christiaens*  \n",
    "> Suitable for VIP *v1.4.2* and Python *v3.10* onwards  \n",
    "> Last update: *2024/03/04*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Table of contents**\n",
    "\n",
    "* [1.1. Loading ADI data](#1.1.-Loading-ADI-data)\n",
    "* [1.2. Model PSF subtraction for ADI](#1.2.-Model-PSF-subtraction-for-ADI)\n",
    "    - [1.2.1. median-ADI](#1.2.1.-median-ADI)\n",
    "    - [1.2.2. Full-frame PCA](#1.2.2.-Full-frame-PCA)    \n",
    "* [1.3. Is the point source significant?](#1.3.-Is-it-significant?)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This quick-start tutorial shows:\n",
    "\n",
    "- how to load Angular Differential Imaging (ADI) datacubes; \n",
    "- how to use algorithms implemented in VIP to model and subtract the stellar halo, and search for faint circumstellar companions in the post-processed images;\n",
    "- how to quickly assess the significance of a point source found in a post-processed image."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's assume ``VIP`` is properly installed. If not, follow the instructions [here](https://vip.readthedocs.io/en/latest/Installation-and-dependencies.html). We import the package along with other useful packages which are installed together with ``VIP``. The ``hciplot`` package aims to be the \"Swiss army\" solution for plotting and visualizing multi-dimensional high-contrast imaging datacubes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import vip_hci as vip\n",
    "\n",
    "from hciplot import plot_frames, plot_cubes\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following box we check that your version of VIP is recent enough to run this notebook. It should be >=1.4.2.\n",
    "If not, close the notebook and run for example `pip install vip_hci --upgrade` in your terminal. Also make sure the Python version used is 3.10 or higher."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VIP version:  1.6.1\n",
      "Python version:  3.10.13\n"
     ]
    }
   ],
   "source": [
    "from packaging import version\n",
    "vvip = vip.__version__\n",
    "print(\"VIP version: \", vvip)\n",
    "if version.parse(vvip) < version.parse(\"1.4.2\"):\n",
    "    msg = \"Please upgrade your version of VIP\"\n",
    "    msg+= \"It should be 1.4.2 or above to run this notebook.\"\n",
    "    raise ValueError(msg)\n",
    "\n",
    "from platform import python_version\n",
    "vpy = python_version()\n",
    "print(\"Python version: \", vpy)\n",
    "if version.parse(vpy) < version.parse(\"3.10.0\"):\n",
    "    msg = \"To use this notebook, you'll need to upgrade your Python version to 3.10 or above.\"\n",
    "    raise ValueError(msg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are some object-oriented options to display your results, but ``hciplot`` allows lots of customization and interaction with the outputs. Interactive windows can also be generated with ``DS9`` - more information on that in [1A - Quick start](./01A_quickstart.ipynb)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.1. Loading ADI data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to demonstrate the capabilities of ``VIP``, you can find in the 'dataset' folder of the `VIP_extras` repository: a toy Angular Differential Imaging (ADI) datacube of images and a point spread function (PSF) associated to the NACO instrument of the Very Large Telescope (VLT). This is an L'-band VLT/NACO dataset of beta Pictoris published in [Absil et al. (2013)](https://ui.adsabs.harvard.edu/abs/2013A%26A...559L..12A/abstract), obtained using the Annular Groove Phase Mask (AGPM) Vortex coronagraph. The sequence has been heavily sub-sampled temporarily to make it smaller. The frames were also cropped to the central 101x101 area. In case you want to plug-in your cube just change the path of the following cells."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To inspect or retrieve the data, the easiest way is to provide their local path to the relevant functions in VIP - as illustrated below.\n",
    "\n",
    "Here we use the `download_file` utility of `astropy` with the `cache` option - which equivalently stores the local path to the file after downloading the data from an online repository:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy.utils.data import download_file\n",
    "\n",
    "url_d = \"https://github.com/vortex-exoplanet/VIP_extras/raw/master/datasets\"\n",
    "f1 = download_file(\"{}/naco_betapic_cube_cen.fits\".format(url_d), cache=True)\n",
    "f2 = download_file(\"{}/naco_betapic_psf.fits\".format(url_d), cache=True)\n",
    "f3 = download_file(\"{}/naco_betapic_derot_angles.fits\".format(url_d), cache=True)\n",
    "\n",
    "# alternatively, for local files simply provide their full or relative path. E.g.:\n",
    "#f1 = '../datasets/naco_betapic_cube_cen.fits'\n",
    "#f2 = '../datasets/naco_betapic_psf.fits'\n",
    "#f3 = '../datasets/naco_betapic_derot_angles.fits'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's first inspect the FITS file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: /Users/valentin/.astropy/cache/download/url/916f9dc5548cc5a02ae424dbd987fc6a/contents\n",
      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY       1 PrimaryHDU       7   (101, 101, 61)   float32   \n"
     ]
    }
   ],
   "source": [
    "from vip_hci.fits import info_fits\n",
    "\n",
    "info_fits(f1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The FITS file contains an ADI datacube of 61 images 101x101 px across.\n",
    "\n",
    "The derotation angle vector for this observation is saved in the `naco_betapic_derot_angles.fits` file. \n",
    "\n",
    "Now we load all the data in memory with the `Dataset` object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cube array shape: (61, 101, 101)\n",
      "Angles array shape: (61,)\n",
      "PSF array shape: (39, 39)\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.objects import Dataset\n",
    "betapic = Dataset(cube=f1, psf=f2, angles=f3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`Dataset` uses the `open_fits` function, which is a wrapper of `astropy.io.fits` functionalities. The FITS file is now a ndarray or ``numpy`` array in memory that are stored as attributes of `betapic`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you open the datacube with ds9 (or send it to the `DS9` window) and adjust the cuts you will see the beta Pic b planet moving on a circular trajectory, among similarly bright quasi-static speckle. Alternatively, you can use `hciplot.plot_cubes`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "  var py_version = '3.3.4'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
       "  var reloading = false;\n",
       "  var Bokeh = root.Bokeh;\n",
       "\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks;\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "    if (js_modules == null) js_modules = [];\n",
       "    if (js_exports == null) js_exports = {};\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    if (!reloading) {\n",
       "      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    }\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "    window._bokeh_on_load = on_load\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    var skip = [];\n",
       "    if (window.requirejs) {\n",
       "      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n",
       "      require([\"jspanel\"], function(jsPanel) {\n",
       "\twindow.jsPanel = jsPanel\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-modal\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-tooltip\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-hint\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-layout\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-contextmenu\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-dock\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"gridstack\"], function(GridStack) {\n",
       "\twindow.GridStack = GridStack\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"notyf\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      root._bokeh_is_loading = css_urls.length + 9;\n",
       "    } else {\n",
       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
       "    }\n",
       "\n",
       "    var existing_stylesheets = []\n",
       "    var links = document.getElementsByTagName('link')\n",
       "    for (var i = 0; i < links.length; i++) {\n",
       "      var link = links[i]\n",
       "      if (link.href != null) {\n",
       "\texisting_stylesheets.push(link.href)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      if (existing_stylesheets.indexOf(url) !== -1) {\n",
       "\ton_load()\n",
       "\tcontinue;\n",
       "      }\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    var existing_scripts = []\n",
       "    var scripts = document.getElementsByTagName('script')\n",
       "    for (var i = 0; i < scripts.length; i++) {\n",
       "      var script = scripts[i]\n",
       "      if (script.src != null) {\n",
       "\texisting_scripts.push(script.src)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (var i = 0; i < js_modules.length; i++) {\n",
       "      var url = js_modules[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (const name in js_exports) {\n",
       "      var url = js_exports[name];\n",
       "      if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      element.textContent = `\n",
       "      import ${name} from \"${url}\"\n",
       "      window.${name} = ${name}\n",
       "      window._bokeh_on_load()\n",
       "      `\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    if (!js_urls.length && !js_modules.length) {\n",
       "      on_load()\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n",
       "  var js_modules = [];\n",
       "  var js_exports = {};\n",
       "  var css_urls = [];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "\ttry {\n",
       "          inline_js[i].call(root, root.Bokeh);\n",
       "\t} catch(e) {\n",
       "\t  if (!reloading) {\n",
       "\t    throw e;\n",
       "\t  }\n",
       "\t}\n",
       "      }\n",
       "      // Cache old bokeh versions\n",
       "      if (Bokeh != undefined && !reloading) {\n",
       "\tvar NewBokeh = root.Bokeh;\n",
       "\tif (Bokeh.versions === undefined) {\n",
       "\t  Bokeh.versions = new Map();\n",
       "\t}\n",
       "\tif (NewBokeh.version !== Bokeh.version) {\n",
       "\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
       "\t}\n",
       "\troot.Bokeh = Bokeh;\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    }\n",
       "    root._bokeh_is_initializing = false\n",
       "  }\n",
       "\n",
       "  function load_or_wait() {\n",
       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
       "    // versions of Bokeh and its dependencies at the same time.\n",
       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
       "    // to determine whether there is an ongoing attempt to initialize\n",
       "    // bokeh, however for backward compatibility we also try to ensure\n",
       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
       "    // before older versions are fully initialized.\n",
       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
       "      root._bokeh_is_initializing = false;\n",
       "      root._bokeh_onload_callbacks = undefined;\n",
       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
       "      load_or_wait();\n",
       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
       "      setTimeout(load_or_wait, 100);\n",
       "    } else {\n",
       "      root._bokeh_is_initializing = true\n",
       "      root._bokeh_onload_callbacks = []\n",
       "      var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
       "      if (!reloading && !bokeh_loaded) {\n",
       "\troot.Bokeh = undefined;\n",
       "      }\n",
       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "\trun_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }\n",
       "  // Give older versions of the autoload script a head-start to ensure\n",
       "  // they initialize before we start loading newer version.\n",
       "  setTimeout(load_or_wait, 100)\n",
       "}(window));"
      ],
      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n  var py_version = '3.3.4'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  var reloading = false;\n  var Bokeh = root.Bokeh;\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      run_callbacks();\n      return null;\n    }\n    if (!reloading) {\n      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n      })\n      require([\"jspanel-modal\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-tooltip\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-hint\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-layout\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-dock\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 9;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    var existing_stylesheets = []\n    var links = document.getElementsByTagName('link')\n    for (var i = 0; i < links.length; i++) {\n      var link = links[i]\n      if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n      }\n    }\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n\ttry {\n          inline_js[i].call(root, root.Bokeh);\n\t} catch(e) {\n\t  if (!reloading) {\n\t    throw e;\n\t  }\n\t}\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
       "}\n",
       "\n",
       "\n",
       "    function JupyterCommManager() {\n",
       "    }\n",
       "\n",
       "    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
       "      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
       "        comm_manager.register_target(comm_id, function(comm) {\n",
       "          comm.on_msg(msg_handler);\n",
       "        });\n",
       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
       "        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
       "          comm.onMsg = msg_handler;\n",
       "        });\n",
       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
       "        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
       "          var messages = comm.messages[Symbol.asyncIterator]();\n",
       "          function processIteratorResult(result) {\n",
       "            var message = result.value;\n",
       "            console.log(message)\n",
       "            var content = {data: message.data, comm_id};\n",
       "            var buffers = []\n",
       "            for (var buffer of message.buffers || []) {\n",
       "              buffers.push(new DataView(buffer))\n",
       "            }\n",
       "            var metadata = message.metadata || {};\n",
       "            var msg = {content, buffers, metadata}\n",
       "            msg_handler(msg);\n",
       "            return messages.next().then(processIteratorResult);\n",
       "          }\n",
       "          return messages.next().then(processIteratorResult);\n",
       "        })\n",
       "      }\n",
       "    }\n",
       "\n",
       "    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
       "      if (comm_id in window.PyViz.comms) {\n",
       "        return window.PyViz.comms[comm_id];\n",
       "      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
       "        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
       "        if (msg_handler) {\n",
       "          comm.on_msg(msg_handler);\n",
       "        }\n",
       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
       "        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
       "        comm.open();\n",
       "        if (msg_handler) {\n",
       "          comm.onMsg = msg_handler;\n",
       "        }\n",
       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
       "        var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
       "        comm_promise.then((comm) => {\n",
       "          window.PyViz.comms[comm_id] = comm;\n",
       "          if (msg_handler) {\n",
       "            var messages = comm.messages[Symbol.asyncIterator]();\n",
       "            function processIteratorResult(result) {\n",
       "              var message = result.value;\n",
       "              var content = {data: message.data};\n",
       "              var metadata = message.metadata || {comm_id};\n",
       "              var msg = {content, metadata}\n",
       "              msg_handler(msg);\n",
       "              return messages.next().then(processIteratorResult);\n",
       "            }\n",
       "            return messages.next().then(processIteratorResult);\n",
       "          }\n",
       "        }) \n",
       "        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
       "          return comm_promise.then((comm) => {\n",
       "            comm.send(data, metadata, buffers, disposeOnDone);\n",
       "          });\n",
       "        };\n",
       "        var comm = {\n",
       "          send: sendClosure\n",
       "        };\n",
       "      }\n",
       "      window.PyViz.comms[comm_id] = comm;\n",
       "      return comm;\n",
       "    }\n",
       "    window.PyViz.comm_manager = new JupyterCommManager();\n",
       "    \n",
       "\n",
       "\n",
       "var JS_MIME_TYPE = 'application/javascript';\n",
       "var HTML_MIME_TYPE = 'text/html';\n",
       "var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
       "var CLASS_NAME = 'output';\n",
       "\n",
       "/**\n",
       " * Render data to the DOM node\n",
       " */\n",
       "function render(props, node) {\n",
       "  var div = document.createElement(\"div\");\n",
       "  var script = document.createElement(\"script\");\n",
       "  node.appendChild(div);\n",
       "  node.appendChild(script);\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle when a new output is added\n",
       " */\n",
       "function handle_add_output(event, handle) {\n",
       "  var output_area = handle.output_area;\n",
       "  var output = handle.output;\n",
       "  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "    return\n",
       "  }\n",
       "  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "  if (id !== undefined) {\n",
       "    var nchildren = toinsert.length;\n",
       "    var html_node = toinsert[nchildren-1].children[0];\n",
       "    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "    var scripts = [];\n",
       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
       "    for (var i in nodelist) {\n",
       "      if (nodelist.hasOwnProperty(i)) {\n",
       "        scripts.push(nodelist[i])\n",
       "      }\n",
       "    }\n",
       "\n",
       "    scripts.forEach( function (oldScript) {\n",
       "      var newScript = document.createElement(\"script\");\n",
       "      var attrs = [];\n",
       "      var nodemap = oldScript.attributes;\n",
       "      for (var j in nodemap) {\n",
       "        if (nodemap.hasOwnProperty(j)) {\n",
       "          attrs.push(nodemap[j])\n",
       "        }\n",
       "      }\n",
       "      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
       "      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
       "      oldScript.parentNode.replaceChild(newScript, oldScript);\n",
       "    });\n",
       "    if (JS_MIME_TYPE in output.data) {\n",
       "      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
       "    }\n",
       "    output_area._hv_plot_id = id;\n",
       "    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
       "      window.PyViz.plot_index[id] = Bokeh.index[id];\n",
       "    } else {\n",
       "      window.PyViz.plot_index[id] = null;\n",
       "    }\n",
       "  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "    var bk_div = document.createElement(\"div\");\n",
       "    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "    var script_attrs = bk_div.children[0].attributes;\n",
       "    for (var i = 0; i < script_attrs.length; i++) {\n",
       "      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "    }\n",
       "    // store reference to server id on output_area\n",
       "    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "  }\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle when an output is cleared or removed\n",
       " */\n",
       "function handle_clear_output(event, handle) {\n",
       "  var id = handle.cell.output_area._hv_plot_id;\n",
       "  var server_id = handle.cell.output_area._bokeh_server_id;\n",
       "  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
       "  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
       "  if (server_id !== null) {\n",
       "    comm.send({event_type: 'server_delete', 'id': server_id});\n",
       "    return;\n",
       "  } else if (comm !== null) {\n",
       "    comm.send({event_type: 'delete', 'id': id});\n",
       "  }\n",
       "  delete PyViz.plot_index[id];\n",
       "  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
       "    var doc = window.Bokeh.index[id].model.document\n",
       "    doc.clear();\n",
       "    const i = window.Bokeh.documents.indexOf(doc);\n",
       "    if (i > -1) {\n",
       "      window.Bokeh.documents.splice(i, 1);\n",
       "    }\n",
       "  }\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle kernel restart event\n",
       " */\n",
       "function handle_kernel_cleanup(event, handle) {\n",
       "  delete PyViz.comms[\"hv-extension-comm\"];\n",
       "  window.PyViz.plot_index = {}\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle update_display_data messages\n",
       " */\n",
       "function handle_update_output(event, handle) {\n",
       "  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
       "  handle_add_output(event, handle)\n",
       "}\n",
       "\n",
       "function register_renderer(events, OutputArea) {\n",
       "  function append_mime(data, metadata, element) {\n",
       "    // create a DOM node to render to\n",
       "    var toinsert = this.create_output_subarea(\n",
       "    metadata,\n",
       "    CLASS_NAME,\n",
       "    EXEC_MIME_TYPE\n",
       "    );\n",
       "    this.keyboard_manager.register_events(toinsert);\n",
       "    // Render to node\n",
       "    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "    render(props, toinsert[0]);\n",
       "    element.append(toinsert);\n",
       "    return toinsert\n",
       "  }\n",
       "\n",
       "  events.on('output_added.OutputArea', handle_add_output);\n",
       "  events.on('output_updated.OutputArea', handle_update_output);\n",
       "  events.on('clear_output.CodeCell', handle_clear_output);\n",
       "  events.on('delete.Cell', handle_clear_output);\n",
       "  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
       "\n",
       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "    safe: true,\n",
       "    index: 0\n",
       "  });\n",
       "}\n",
       "\n",
       "if (window.Jupyter !== undefined) {\n",
       "  try {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  } catch(err) {\n",
       "  }\n",
       "}\n"
      ],
      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        comm.open();\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        }) \n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>*[data-root-id],\n",
       "*[data-root-id] > * {\n",
       "  box-sizing: border-box;\n",
       "  font-family: var(--jp-ui-font-family);\n",
       "  font-size: var(--jp-ui-font-size1);\n",
       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
       "}\n",
       "\n",
       "/* Override VSCode background color */\n",
       ".cell-output-ipywidget-background:has(\n",
       "    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
       "  ),\n",
       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "</style>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
      "text/html": [
       "<div id='p1002'>\n",
       "  <div id=\"df4a15d3-b500-4968-97a0-4d3a8ea0d146\" data-root-id=\"p1002\" style=\"display: contents;\"></div>\n",
       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  var docs_json = {\"aee9ffb4-6a38-4043-b899-4b5793d497d4\":{\"version\":\"3.3.4\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"p1002\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"p1003\",\"attributes\":{\"plot_id\":\"p1002\",\"comm_id\":\"a54c4038f8d944db875638b6d87cb3bc\",\"client_comm_id\":\"490dcf0f18bc44848c309bdb2b648253\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"copy_to_clipboard1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
       "  var render_items = [{\"docid\":\"aee9ffb4-6a38-4043-b899-4b5793d497d4\",\"roots\":{\"p1002\":\"df4a15d3-b500-4968-97a0-4d3a8ea0d146\"},\"root_ids\":[\"p1002\"]}];\n",
       "  var docs = Object.values(docs_json)\n",
       "  if (!docs) {\n",
       "    return\n",
       "  }\n",
       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
       "  function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ]
     },
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "p1002"
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"logo-block\">\n",
       "<img src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAEAAAABACAYAAACqaXHeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\n",
       "AAAB+wAAAfsBxc2miwAAABl0RVh0U29mdHdhcmUAd3d3Lmlua3NjYXBlLm9yZ5vuPBoAAA6zSURB\n",
       "VHic7ZtpeFRVmsf/5966taWqUlUJ2UioBBJiIBAwCZtog9IOgjqACsogKtqirT2ttt069nQ/zDzt\n",
       "tI4+CrJIREFaFgWhBXpUNhHZQoKBkIUASchWla1S+3ar7r1nPkDaCAnZKoQP/D7mnPOe9/xy76n3\n",
       "nFSAW9ziFoPFNED2LLK5wcyBDObkb8ZkxuaoSYlI6ZcOKq1eWFdedqNzGHQBk9RMEwFAASkk0Xw3\n",
       "ETacDNi2vtvc7L0ROdw0AjoSotQVkKSvHQz/wRO1lScGModBFbDMaNRN1A4tUBCS3lk7BWhQkgpD\n",
       "lG4852/+7DWr1R3uHAZVQDsbh6ZPN7CyxUrCzJMRouusj0ipRwD2uKm0Zn5d2dFwzX1TCGhnmdGo\n",
       "G62Nna+isiUqhkzuKrkQaJlPEv5mFl2fvGg2t/VnzkEV8F5ioioOEWkLG86fvbpthynjdhXYZziQ\n",
       "x1hC9J2NFyi8vCTt91Fh04KGip0AaG9zuCk2wQCVyoNU3Hjezee9bq92duzzTmxsRJoy+jEZZZYo\n",
       "GTKJ6SJngdJqAfRzpze0+jHreUtPc7gpBLQnIYK6BYp/uGhw9YK688eu7v95ysgshcg9qSLMo3JC\n",
       "4jqLKQFBgdKDPoQ+Pltb8dUyQLpeDjeVgI6EgLIQFT5tEl3rn2losHVsexbZ3EyT9wE1uGdkIPcy\n",
       "BGxn8QUq1QrA5nqW5i2tLqvrrM9NK6AdkVIvL9E9bZL/oyfMVd/jqvc8LylzRBKDJSzIExwhQzuL\n",
       "QYGQj4rHfFTc8mUdu3E7yoLtbTe9gI4EqVgVkug2i5+uXGo919ixbRog+3fTbQ8qJe4ZOYNfMoTI\n",
       "OoshUNosgO60AisX15aeI2PSIp5KiFLI9ubb1vV3Qb2ltwLakUCDAkWX7/nHKRmmGIl9VgYsUhJm\n",
       "2NXjKYADtM1ygne9QQDIXlk49FBstMKx66D1v4+XuQr7vqTe0VcBHQlRWiOCbmmSYe2SqtL6q5rJ\n",
       "zsTb7lKx3FKOYC4DoqyS/B5bvLPxvD9Qtf6saxYLQGJErmDOdOMr/zo96km1nElr8bmPOBwI9COv\n",
       "HnFPRIwmkSOv9kcAS4heRsidOkpeWBgZM+UBrTFAXNYL5Vf2ii9c1trNzpYdaoVil3WIc+wdk+gQ\n",
       "noie3ecCcxt9ITcLAPWt/laGEO/9U6PmzZkenTtsSMQ8uYywJVW+grCstAvCIaAdArAsIWkRDDs/\n",
       "KzLm2YcjY1Lv0UdW73HabE9n6V66cxSzfEmuJssTpKGVp+0vHq73FwL46eOjpMpbRAnNmJFrGJNu\n",
       "Ukf9Yrz+3rghiumCKNXXWPhLYcjxGsIpoCMsIRoFITkW8AuyM8jC1+/QLx4bozCEJIq38+1rtpR6\n",
       "V/yzb8eBlRb3fo5l783N0CWolAzJHaVNzkrTzlEp2bQ2q3TC5gn6wpnoQAmwSiGh2GitnTmVMc5O\n",
       "UyfKWUKCIsU7+fZDKwqdT6DDpvkzAX4/+AMFjk0tDp5GRXLpQ2MUmhgDp5gxQT8+Y7hyPsMi8uxF\n",
       "71H0oebujHALECjFKaW9Lm68n18wXp2kVzIcABytD5iXFzg+WVXkegpAsOOYziqo0OkK76GyquC3\n",
       "ltZAzMhhqlSNmmWTE5T6e3IN05ITFLM4GdN0vtZ3ob8Jh1NAKXFbm5PtLU/eqTSlGjkNAJjdgn/N\n",
       "aedXa0tdi7+t9G0FIF49rtMSEgAs1kDLkTPO7ebm4IUWeyh1bKomXqlgMG6kJmHcSM0clYLJ8XtR\n",
       "1GTnbV3F6I5wCGikAb402npp1h1s7LQUZZSMIfALFOuL3UUrfnS8+rez7v9qcold5tilgHbO1fjK\n",
       "9ubb17u9oshxzMiUBKXWqJNxd+fqb0tLVs4lILFnK71H0Ind7uiPgACVcFJlrb0tV6DzxqqTIhUM\n",
       "CwDf1/rrVhTa33/3pGPxJYdQ2l2cbgVcQSosdx8uqnDtbGjh9SlDVSMNWhlnilfqZk42Th2ZpLpf\n",
       "xrHec5e815zrr0dfBZSwzkZfqsv+1FS1KUknUwPARVvItfKUY+cn57yP7qv07UE3p8B2uhUwLk09\n",
       "e0SCOrK+hbdYHYLjRIl71wWzv9jpEoeOHhGRrJAzyEyNiJuUqX0g2sBN5kGK6y2Blp5M3lsB9Qh4\n",
       "y2Ja6x6+i0ucmKgwMATwhSjdUu49tKrQ/pvN5d53ml2CGwCmJipmKjgmyuaXzNeL2a0AkQ01Th5j\n",
       "2DktO3Jyk8f9vcOBQHV94OK+fPumJmvQHxJoWkaKWq9Vs+yUsbq0zGT1I4RgeH2b5wef7+c7bl8F\n",
       "eKgoHVVZa8ZPEORzR6sT1BzDUAD/d9F78e2Tzv99v8D+fLVTqAKAsbGamKey1Mt9Ann4eH3gTXTz\n",
       "idWtAJ8PQWOk7NzSeQn/OTHDuEikVF1R4z8BQCy+6D1aWRfY0tTGG2OM8rRoPaeIj5ZHzJxszElN\n",
       "VM8K8JS5WOfv8mzRnQAKoEhmt8gyPM4lU9SmBK1MCQBnW4KONT86v1hZ1PbwSXPw4JWussVjtH9Y\n",
       "NCoiL9UoH/6PSu8jFrfY2t36erQHXLIEakMi1SydmzB31h3GGXFDFNPaK8Rme9B79Ixrd0WN+1ij\n",
       "NRQ/doRmuFLBkHSTOm5GruG+pFjFdAmorG4IXH1Qua6ASniclfFtDYt+oUjKipPrCQB7QBQ2lrgP\n",
       "fFzm+9XWUtcqJ3/5vDLDpJ79XHZk3u8nGZ42qlj1+ydtbxysCezrydp6ugmipNJ7WBPB5tydY0jP\n",
       "HaVNzs3QzeE4ZpTbI+ZbnSFPbVOw9vsfnVvqWnirPyCNGD08IlqtYkh2hjZ5dErEQzoNm+6ykyOt\n",
       "Lt5/PQEuSRRKo22VkydK+vvS1XEKlhCJAnsqvcVvH7f/ZU2R67eXbMEGAMiIV5oWZWiWvz5Fv2xG\n",
       "sjqNJQRvn3Rs2lji/lNP19VjAQDgD7FHhujZB9OGqYxRkZxixgRDVlqS6uEOFaJUVu0rPFzctrnF\n",
       "JqijImVp8dEKVWyUXDk92zAuMZ6bFwpBU1HrOw6AdhQgUooChb0+ItMbWJitSo5Ws3IAOGEOtL53\n",
       "0vHZih9sC4vtofZ7Qu6523V/fmGcds1TY3V36pUsBwAbSlxnVh2xLfAD/IAIMDf7XYIkNmXfpp2l\n",
       "18rkAJAy9HKFaIr/qULkeQQKy9zf1JgDB2uaeFNGijo5QsUyacNUUTOnGO42xSnv4oOwpDi1zYkc\n",
       "efUc3I5Gk6PhyTuVKaOGyLUAYPGIoY9Pu/atL/L92+4q9wbflRJ2Trpm/jPjdBtfnqB/dIThcl8A\n",
       "KG7hbRuKnb8qsQsVvVlTrwQAQMUlf3kwJI24Z4JhPMtcfng5GcH49GsrxJpGvvHIaeem2ma+KSjQ\n",
       "lIwUdYyCY8j4dE1KzijNnIP2llF2wcXNnsoapw9XxsgYAl6k+KzUXbi2yP3KR2ecf6z3BFsBICdW\n",
       "nvnIaG3eHybqX7vbpEqUMT+9OL4Qpe8VON7dXuFd39v19FoAABRVePbGGuXTszO0P7tu6lghUonE\n",
       "llRdrhArLvmKdh9u29jcFiRRkfLUxBiFNiqSU9icoZQHo5mYBI1MBgBH6wMNb+U7Pnw337H4gi1Y\n",
       "ciWs+uks3Z9fztUvfzxTm9Ne8XXkvQLHNytOOZeiD4e0PgkAIAYCYknKUNUDSXEKzdWNpnil7r4p\n",
       "xqkjTarZMtk/K8TQ6Qve78qqvXurGwIJqcOUKfUWHsm8KGvxSP68YudXq4pcj39X49uOK2X142O0\n",
       "Tz5/u/7TVybqH0rSya6ZBwD21/gubbrgWdDgEOx9WUhfBaC2ibcEBYm7a7x+ukrBMNcEZggyR0TE\n",
       "T8zUPjikQ4VosQZbTpS4vqizBKvqmvjsqnpfzaZyx9JPiz1/bfGKdgD45XB1zoIMzYbfTdS/NClB\n",
       "Gct0USiY3YL/g0LHy/uq/Ef6uo5+n0R/vyhp17Klpge763f8rMu6YU/zrn2nml+2WtH+Z+5IAAFc\n",
       "2bUTdTDOSNa9+cQY7YLsOIXhevEkCvzph7a8laecz/Un/z4/Ae04XeL3UQb57IwU9ZDr9UuKVajv\n",
       "nxp1+1UVIo/LjztZkKH59fO3G/JemqCfmaCRqbqbd90ZZ8FfjtkfAyD0J/9+C2h1hDwsSxvGjNDc\n",
       "b4zk5NfrSwiQblLHzZhg+Jf4aPlUwpDqkQqa9nimbt1/TDH8OitGMaQnj+RJS6B1fbF7SY1TqO5v\n",
       "/v0WAADl1f7zokgS7s7VT2DZ7pegUjBM7mjtiDZbcN4j0YrHH0rXpCtY0qPX0cVL0rv5jv/ZXend\n",
       "0u/EESYBAFBU4T4Qa5TflZOhTe7pmKpaP8kCVUVw1+yhXfJWvn1P3hnXi33JsTN6PnP3hHZ8Z3/h\n",
       "aLHzmkNPuPj7Bc/F/Q38CwjTpSwQXgE4Vmwry9tpfq/ZFgqFMy4AVDtCvi8rvMvOmv0N4YwbVgEA\n",
       "sPM72/KVnzfspmH7HQGCRLG2yL1+z8XwvPcdCbsAANh+xPzstgMtxeGKt+6MK3/tacfvwhWvIwMi\n",
       "oKEBtm0H7W+UVfkc/Y1V0BhoPlDr/w1w/eu1vjIgAgDg22OtX6/eYfnEz/focrZTHAFR+PSs56/7\n",
       "q32nwpjazxgwAQCwcU/T62t3WL7r6/jVRa6/byp1rei+Z98ZUAEAhEPHPc8fKnTU9nbgtnOe8h0l\n",
       "9hcGIqmODLQAHCy2Xti6v/XNRivf43f4fFvIteu854+VHnR7q9tfBlwAAGz+pnndB9vM26UebAe8\n",
       "SLHujPOTPVW+rwY+sxskAAC2HrA8t2Vvc7ffP1r9o+vwR2dcr92InIAbKKC1FZ5tB1tf+/G8p8sv\n",
       "N/9Q5zd/XR34LYCwV5JdccMEAMDBk45DH243r/X4xGvqxFa/GNpS7n6rwOwNWwHVE26oAADYurf1\n",
       "zx/utOzt+DMKYM0p17YtZZ5VNzqfsB2HewG1WXE8PoZ7gOclbTIvynZf9JV+fqZtfgs/8F/Nu5rB\n",
       "EIBmJ+8QRMmpU7EzGRsf2FzuePqYRbzh/zE26EwdrT10f6r6o8HOYzCJB9Dpff8tbnGLG8L/A/WE\n",
       "roTBs2RqAAAAAElFTkSuQmCC'\n",
       "     style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <img src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\n",
       "AAAFMAAABTABZarKtgAAABl0RVh0U29mdHdhcmUAd3d3Lmlua3NjYXBlLm9yZ5vuPBoAAArNSURB\n",
       "VFiFnVd5VFNXGv/ee0kgGyQhbFoXIKCFYEXEDVErTucMoKUOWA/VLsNSLPQgFTOdyrHPiIp1lFIQ\n",
       "OlaPShEG3EpPcQmISCuV1bQ1CLKIULeQhJA9JO+9+UMT0x5aPfOdc895373f/e7v/t537/ddBF5Q\n",
       "JBIJl81mJwCACEVRQBCEQhAEAQCgnghCURRCkmS7Wq2+WlJSYn0Rv8jzDHAcD0EQJIVGo5mFQuGF\n",
       "jIyMu39kq1KpkOrq6gU6nS6aIAiGzWY7VVBQ0P9/AcjNzWXy+fxcOp2uiY+Przm0d6+n8dblv/Fo\n",
       "kzM4SzYfPlRePvFnjnt6ehh1dXVv2mw2nlar/byoqMj8wgBwHBchCJIZEhJSeu1yHVi7vtu02t8+\n",
       "NykQ7BMWoOUMhXQsXLv5IQAwSJJEEASxcDicoeTk5DtCoZBy9XX69Gnv3t7ebJIky3EcH3guAKlU\n",
       "GoGiaOKWLVsOvhs7/9XXPMde3/IyIFbMnaPDuD5AUdQuOf2XlD0npTExMWYAgNbWVpZcLg8xGAzB\n",
       "JEnSvby82tPT052LaTQatLy8fBtJkt/s3Lnz5h8CwHFcRKPRNu/YsePAjh072KTs0IGCxRg8RgUB\n",
       "TGpSx6cmHgMAfNqN6Xa1GvJ/D35gYAAViURkcXHxUrPZHDRv3rxv4uLiDI7xPXv2bLdYLBUFBQWD\n",
       "jj7M8ZGbm8tkMpmSrKysQiaTScXGxtpqL7dManT6tcu5mgEWWJyOhicozpk+c3NsbKzNFcBbWWEf\n",
       "1Td9/upA30i3ZJv0h8bGxiSFQmFcuHDhOACAWCy+0d3dvX3lypUtzc3N9t8AiIuLk4SEhByLiooy\n",
       "AgAcO3ZsNlPgH3Cttb35JZo+bCYXIQAA9MDiUW7sWS1KN687w6Mera2twa2trfMvXboUOS28Pyb1\n",
       "U08McRtf/sXBSmt5cc35pqamVQqFwhoZGallMpnU/fv3e7RaberVq1d/AABAn1IfQqfTNRs3blQB\n",
       "AFy+fJk7Nja2XCKRnD3dNSorusPq6NfTPR+gPiEEoLRFXO1tS2+zavv27ReftjNttyr0S1/j0rUP\n",
       "PEJQwNwQYGgAACQSyXmNRhMtk8lYAAApKSlKDMP0+fn5QU4ACIKkxMfH1zjYuHnz5uspKSlOfdX7\n",
       "u68fvOePcCzKQR4YVCgATGfa/F3pnzaHWOAXSDyaMCqH2+r8VXErP3D+snXr1tV2dXW94dATExOr\n",
       "6XT6JgAAVCKRcDEMM4WHh9sAAHJyUqNu//wDymKx7AAAVVVVPiaTKXxByrYMvBsxEMSTwPXhuL+8\n",
       "e/fu9fv371+flvbemogYNz+TnsBOFEwMFO8/KzEYDKFVVVX+AAChoaGT7u7ud48ePRro0DEMs+bl\n",
       "5bFRNpud4O3tfdGBzq5uy/5wTUPM/q2zC9atmbVqeHg4Pi0t7WxGRoZFH5rw76I7LI8HqHfwPL7d\n",
       "rfVagzw1NfW81t4ePUfsP/OrnWZ6fPSuUqFQSEkkkrOjo6OvuQR5q0ajiXLoPj4+lzgcTjwKACLH\n",
       "9SqXy2kzhBO8haGo+UA2wZW+p880DxeveGt9aHx9fT09ctlq3sC0NT9e6xsbjuZblSxl7wKtVotM\n",
       "m6PnXvlmZJBtX91CEMQsxyJsNlteXl4udugIghAajQYFAEhPTx9AEGQOimGY8y4oLt63KlJkdB4t\n",
       "P282Z/c/dPrDH04ktJ9P2tfWXP3+2o1vHzunEp6Xq0lsGt08KzUrcSGTQ3n3XeefLCs5UqnT6Rap\n",
       "VCoEACA7O/snvV4f5gJooLa2NsihoygKKEVRzquTND2OCpttGXdG1tOxwOlgzdvE9v30rV+m3W5I\n",
       "2jfJNQmLH85QUUzPNTwvkAx0+vVGhq2/VV9fT+dyuZ01NTXOXQOA3fGxevXq2waDYY5r8KIoij5b\n",
       "jzB5Cz2oKdOo0erOm+1tVuVtBMZXElNMRJR1fvvjx9iPLQ/RjpuB0Xu/Vp7YmH1864YNG3oNBkPw\n",
       "VD7mzp1rJUnSzZUBmqsBggAgGFC/n6jVA+3WoN3tu1Gg39cg2tEx1Cg3CIJHsclxnl2HRorMN8Z0\n",
       "fRW+vr7GJ36Q56Z5h9BIknzGAMJWtvdQYs0EZe3/FSwqk5tpXEMb1JoYD+n8xRdQJl/fMPEgzKhS\n",
       "L40KCD7lGzg92qIyovpb3y/msT2un2psvFpWVvYyl8vtc1nDSXFXV5c7iqLOtEyS5LNBAADfWeKm\n",
       "Ly4uuvR1++sfv51/P5sfnHm2/Iy+mBmwsaHJbpt+Q0jHSS7TZ/PSNVkNJ/973OxtemD1s91CPb12\n",
       "h9MfvZsk5meo1eqo5ORkxTNWn7HR1tY2l8PhOAsUiqIolCRJcETtv/61qzNySYK5trZ2TCgUUiwW\n",
       "S1FSUhLR+bA/kAzwXcAbHa/cFhrTXrJ/v+7IkSPu3Je4Xm5eboJv2wba5QbO5fQwxhsP679Y+nFO\n",
       "jgAAoKSkJILFYjnBGI1G0YYNGwYBnqRoiqIQlKKojurq6gUAAAKBgKQoiuGYkJWVpTCZTOKmI1Xd\n",
       "HwnDcm+cOnOMw+H0FxYWbqpvqv/r9EV+bky+O+/QoUPiqJRt9JphTLFHbKBCR87tWL9EPN9oNIZn\n",
       "ZWUpXHaMCQQCEgCgsrIyEgBuoGq1+qpOp4t2GPH5/BvFxcVLHXpgYGDD8ePH/56Xl2cCAMjMzOxP\n",
       "S0s7pWfow4RCbz/fAF9RT0+P9yeffHJySSqev+9nxLD1FaAlTR8vlJ8vxxzsFhUVLRMIBB0OvwaD\n",
       "YRlFUdfQkpISK0EQ9J6eHgYAQEZGxl2z2Rw0MjJCBwBITk5+xOVyfzpw4ECSw5lQKKQIbxtJm4EN\n",
       "8eZ7jPz0oNv+dK5FG/jq54eH+IFr/S1KabBy0UerAvI+++wzD4vFEpCWljYEACCTyVh2ux3FcXwS\n",
       "BQCw2WxVdXV1bzrQRURE1FVVVTn1zMzM/pkzZ35/9OjRd0pLS19RqVQIy4/tCwDgOcPTQvFQEQBA\n",
       "aWnpK0ERK2LbyVllN341GUJ4YDu8zD5bKyur7O+85tx9Z2fnO1ar9QjA04KkpaVFs2LFir8olcq7\n",
       "YWFhJpFINNnX16drbGyMjY6Ovg0AIBaLjcuXL5d3d3d7XbhwIW704b3F479MeD1qVfJ5Og/bvb4R\n",
       "LwaDMZabm9uwflNa/z/3HOIv5NsDEK7XS7FeevXPvYNLvm5S/GglCK5KpZorlUobXE8g5ObmMqVS\n",
       "6UG1Wu1BURSHoijOiRMnwgoLC7coFAqBo+9Fm0KhEKStmvvto3TeucFN7pVJYbytarXaQyqVHsRx\n",
       "3N15TF1BuBaljr4rV66wOzo63mAymXdzcnKuwwtIUVHRMqvVGkgQxMV7NXvyJijGvcNXB/7z5Zdf\n",
       "bicI4gSO40NTAgD4bVnuODIAT2pElUq1FEEQO4fD6QsPD++fqixHEATj8/ntjoCrqKhwS0hIsJWV\n",
       "leURBHEOx3G563pT3tn5+flBDAbjg6CgoMMpKSlK17GhoSFMJpMFPk04DJIkEQzDzCwW6+5UD5Oa\n",
       "mhrfO3fufECS5GHXnf8pAAAAHMfdURTdimGYPjExsTo0NHTyj2ynEplMxurs7HyHIAiKJMlSHMct\n",
       "U9k9N2vl5+cH0en0TRiGWX18fC65vnh+LxqNBq2oqFhgMpmi7XY7arVaj+zdu/fxn/l/4bSZl5fH\n",
       "5nK5CQAQMtXznCRJePpEbwOAZhzHX4ix/wHzzC/tu64gcwAAAABJRU5ErkJggg=='\n",
       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
       "  \n",
       "\n",
       "\n",
       "</div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ":Dataset   [x,y,time]   (flux)\n",
      ":Cube_shape\t[101, 101, 61]\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
      "text/html": [
       "<div id='p1004'>\n",
       "  <div id=\"f6e64cf6-3572-4390-8af2-abc4711da0a6\" data-root-id=\"p1004\" style=\"display: contents;\"></div>\n",
       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  var docs_json = {\"3d66248f-4f7e-4c22-bd98-5fe4b5e0a67e\":{\"version\":\"3.3.4\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"Row\",\"id\":\"p1004\",\"attributes\":{\"name\":\"Row00898\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHN0eWxlPSJtYXJnaW46IGF1dG87IGJhY2tncm91bmQ6IG5vbmU7IGRpc3BsYXk6IGJsb2NrOyBzaGFwZS1yZW5kZXJpbmc6IGF1dG87IiB2aWV3Qm94PSIwIDAgMTAwIDEwMCIgcHJlc2VydmVBc3BlY3RSYXRpbz0ieE1pZFlNaWQiPiAgPGNpcmNsZSBjeD0iNTAiIGN5PSI1MCIgZmlsbD0ibm9uZSIgc3Ryb2tlPSIjYzNjM2MzIiBzdHJva2Utd2lkdGg9IjEwIiByPSIzNSIgc3Ryb2tlLWRhc2hhcnJheT0iMTY0LjkzMzYxNDMxMzQ2NDE1IDU2Ljk3Nzg3MTQzNzgyMTM4Ij4gICAgPGFuaW1hdGVUcmFuc2Zvcm0gYXR0cmlidXRlTmFtZT0idHJhbnNmb3JtIiB0eXBlPSJyb3RhdGUiIHJlcGVhdENvdW50PSJpbmRlZmluaXRlIiBkdXI9IjFzIiB2YWx1ZXM9IjAgNTAgNTA7MzYwIDUwIDUwIiBrZXlUaW1lcz0iMDsxIj48L2FuaW1hdGVUcmFuc2Zvcm0+ICA8L2NpcmNsZT48L3N2Zz4=\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"p1007\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.3.8/dist/css/loading.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"p1020\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.3.8/dist/css/listpanel.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"p1005\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.3.8/dist/bundled/theme/default.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"p1006\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.3.8/dist/bundled/theme/native.css\"}}],\"min_width\":616,\"margin\":0,\"sizing_mode\":\"stretch_width\",\"align\":\"start\",\"children\":[{\"type\":\"object\",\"name\":\"Spacer\",\"id\":\"p1008\",\"attributes\":{\"name\":\"HSpacer00911\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"p1007\"},{\"id\":\"p1005\"},{\"id\":\"p1006\"}],\"margin\":0,\"sizing_mode\":\"stretch_width\",\"align\":\"start\"}},{\"type\":\"object\",\"name\":\"panel.models.markup.HTML\",\"id\":\"p1010\",\"attributes\":{\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"p1007\"},{\"id\":\"p1005\"},{\"id\":\"p1006\"}],\"width\":616,\"height\":522,\"min_width\":616,\"min_height\":522,\"margin\":[5,10],\"align\":\"start\",\"text\":\"&lt;img src=&quot;data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAmgAAAIKCAYAAACX07MYAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAABYlAAAWJQFJUiTwAAC12UlEQVR4nOy9eXwV5d3+f83JyR5ICAiiiAFZFBEXKBZUZHFBKhVrKvRREKo81ZZVseCOgnyrAlKEasWqaJ9facUNURDLWomoINalCChQRREBIUhClpMzvz8w0bnuZG4OOeGcHK7368VL58x2z8rNzHuuj+O6rgshhBBCCBE3BGLdACGEEEII4UUdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCGEEEKIOEMdNCFEjaxYsQKO4yAvLy/WTRFCiGMKddCEOEZ5+umnMXHiRLz//vuxbkpcsnbtWgwaNAgnnHAC0tLS0LJlS9xwww349NNPY900IcQxgDpoQhyjPP3007j33nt9O2gZGRlo3749TjnllKPXsDhg7ty56NatG/7+97/j66+/RlpaGr744gv85S9/wVlnnYVly5bFuolCiARHHTQhRI107doVn3zyCZYuXRrrphw1PvjgAwwfPhyhUAjXXHMNdu7ciX379mHbtm24+OKLUVRUhKuuugq7du2KdVOFEAmMOmhCCPEj7r77bpSXl6NLly6YO3cujjvuOADAySefjBdeeAEnnXQS9u3bhz/84Q8xbqkQIpFRB02IY4ynn34ajuNg5cqVAIBhw4bBcZyqPz/+IMDvI4GePXvCcRw8/fTT2L9/P37/+9/jlFNOQXp6Olq3bo27774bJSUlVdMvXboUl156KZo0aYLMzEz06NED//rXv3zbeuDAAUyZMgU/+clPkJ2djbS0NLRt2xajRo3CF198EZX98WP27duH1157DQBw8803IykpyTM+KysLN954IwDgb3/7G1zXjXobhBACUAdNiGOO9PR0NGvWDMnJyQCAhg0bolmzZlV/Kp8YHS579+5F165d8dBDD2Hnzp2oqKjA1q1bMWnSJFx99dUAgD/96U+4+OKL8c9//hPl5eUoLi7Gv/71L1x00UVYvXp1tcvdsGEDOnbsiDvuuANr165FcXExgsEgPv30UzzyyCM488wzq51327ZtVZ3Np59+OqJtefPNN1FeXg4AuOSSS6qd5tJLLwUA7NixAxs2bIho+UIIcbiogybEMcbAgQPx9ddfo3v37gCAP/7xj/j666+r/rz77rsRLe/ee+8FAPzrX//CgQMHcODAAcyZMwfBYBCvvPIKJk2ahDFjxmDChAnYs2cPCgsLsW3bNnTr1g1lZWUYO3assczCwkL069cP//3vf/HLX/4S//73v1FSUoIDBw7gs88+w//8z/9g7969uOqqq7Bv375a75NK/vOf/wAAjj/+eDRu3LjaaTp06GBML4QQ0UYdNCFErSgqKsLChQtx/vnnAwBSUlJwww03YMiQIQAOOV3XXnstpkyZgpycHACHfK6//e1vcBwH7777Lj7//HPPMh966CFs27YNv/rVr/CPf/wDnTp1qnrd2Lp1a/zf//0f+vbti507d+KJJ56I2rbs2LEDAHDCCSfUOE16enrVdlROL4QQ0UYdNCFErfjlL3+JNm3aGL9fdNFFVf9/2223GeNPPvnkqvk++ugjz7i5c+cCAG655ZYa1/s///M/AIA33njD83teXh5c14Xruhg6dOjhbcT3FBUVATjUCfMjIyMDwCFHTggh6oJgrBsghKjfnHHGGdX+3rRpUwBAWlpatR04AGjWrBk2b96MvXv3Vv32xRdfYPv27QCAfv36wXGcauctKyurml4IIRINddCEELWiefPm1f5e+UqyWbNmNXayKqepFPMB72vDb775xrr+4uLiw26rjczMTADAwYMHD2udWVlZUVu3EEL8GHXQhBBxRTgcrvr/vXv3VvleR4NK9+yrr76qcZqDBw9WfZhQU+dUCCFqixw0IURc0axZs6r/548H6prKLzS//vpr7Nmzp9ppfvzl5o+/6BRCiGiiDpoQxyiBwKHLP97CVlu1alXVSVu0aNFRXff5559flQ/3z3/+s9pplixZAuDQ07bTTjvtqLVNCHFsoQ6aEMcoDRs2BICo5ohFi8qvL6dOnYovv/yyxulc141q+7Ozs9GvXz8AwPTp0z2vW4FDX3k+9thjAIBf/epXNbp1QghRW9RBE+IY5fTTTwcAvPDCCygsLIxxa7xMmDABrVu3xu7du9G9e3f84x//8Ij7n3/+OR5//HGcc845eOmllzzz1qaSAHAoeDc5ORnvvPMOhg4dit27d1et8xe/+AU+//xz5OTkYPz48bXZRCGE8EUdNCGOUQYPHoyUlBS8+eabaNKkCU488UTk5eVVBc7GkpycHLz++us47bTT8Pnnn2PgwIFo0KABmjRpgoyMDJx88sn4zW9+g/fffz/qT7HOPPPMqkoIzz77LJo2bYqcnBycfPLJWLJkCTIzM/H8889HXBJLCCEiQR00IY5RTj31VLzxxhvo27cvsrOz8fXXX+O///1vVQZZrGnTpg3Wr1+PP/3pT+jVqxcaNWqEwsJCBINBdOrUCf/7v/+LV199Fddee23U133dddfhrbfewtVXX41mzZrh4MGDOOmkk/DrX/8a77//Pnr37h31dQohxI9x3HgzhIUQQgghjnH0BE0IIYQQIs5QB00IIYQQIs5QB00IIYQQIs5QB00IIYQQIs5QB00IIYQQIs5QB00IIYQQIs5QB00IIYQQIs6odx20+fPnY+TIkbjgggvQsGFDOI5jDaosKChAv379kJubi/T0dHTq1AkzZsxARUVFjfMsXLgQPXv2RHZ2NrKysnDuuedi7ty50d4cIYQQQgiDYKwbECmTJ0/Gv//9b2RlZaFFixb45JNPfKd/+eWXcdVVVyEtLQ0DBw5Ebm4uXnnlFYwdOxarV6/Gc889Z8wza9YsjBw5Eo0bN8a1116LlJQUzJ8/H0OHDsWHH36IqVOn1tXmCSGEEELUv0oCy5cvR4sWLdCmTRusXLkSvXr1wjXXXIO//vWvxrT79+9HmzZtUFhYiNWrV6NLly4AgJKSEvTu3RtvvfUW/va3v2HQoEFV82zbtg2nnnoqMjMzsW7dOuTl5QEA9u7di5/85Cf47LPPUFBQgG7duh3xNuTl5WH//v1o1arVES9DCCHEsc3WrVvRsGFDbNu2LdZNEXVAvXuC1qtXr8Oedv78+di1axeGDBlS1TkDgLS0NEyePBl9+vTBo48+6umgPfnkkygtLcX48eOrOmcA0KhRI9x+++24/vrr8dhjj9Wqg7Z//34U7t2PzXu3HvEygEj71VxQmuevZcFpY3bHfzyvnv+dwAWwbfPXOZb22dpj270Rb49lBuPwRro/LeeHpUC5sXus/w40ZvAdHfXjH+3jE+nlFuXL0Xp92WZw2H6JcAdEvL/4+IdtM/gOmu2p7QGo7QlXN8srwn58t7foiJbwzTffoH275miUHcB/Nn6HtLS0WrZJRJt610GLhGXLlgEA+vbta4zr0aMHMjIyUFBQgNLSUqSmplrnueyyyzzT2OjcuXO1v5eUlCATDfHT5EurfnPD3gvWCXgvaB6PMPlz5t+I3uFAEo333gCdpCQa7d8eA76h0/TG8tn/42GanudH2HYDjwxrB4L3R7L30jG2h3CCdKnR+mzz29pjwH/B8f7k9tD63Qo+P+j4Jif7rp6nd8tD1D5qP58fZWW0PMv5U0siPT4OXW98/ljPVx7P2xOonR5svb4s0zspKd4JbOebbXm2+4fl+NvuZ8b+5vaEyr0/8P2K7qd8Phj7M9IXT5b7r4Ft+d8v7+2KJZG140fce++92FcYxr7CMB555BHceuutR7wsUTfUu48EImHjxo0AgHbt2hnjgsEgWrVqhVAohC1bthzWPM2bN0dmZia2b9+O4uLiOmq1EEIIUXds3LgRf/7zn3BZnwyceXoK7p88AXv27Il1swSR0E/QCgsLAQDZ2dnVjq/8fd++fRHNU1RUhMLCQmRkZPiuf926ddX+3rlzZ2x+rzavN4UQQogjY/yYznBd4MG7muDLr0PoO+grTJ48GQ8//HCsmyZ+REJ30OIb1/vYnB65G680+ZG47ZE5j2cs6zNesfIrC34lUU6vpOgVQZhfcdkIe6c31hfhK0njlS61j1/pGK9YeH/weNqfTlqqd7zlFW6AX6mEaH8Zr8jolRG9cjRe0dDynBR6RcnH3zvWnJ9f8RmvSP1fGSHZ/9ZjtI/On4hfQVleiZv72/IKml8Z8/bYXsny+phanl/G/vFfm/UVoRXLKzvjfsaEI7w/2OD28PngRviKnF+J8vyG48nT1/KVJi+/6pVs5C7bm2++iZcXF2H4tQ3RoX0KOrRPwSU9MzB79gyMHDkSrVu3jniZom5I6FeclU/BKp+KMZW/5+TkRDxPTU/YhBBCiHjEdV3cOuYiZGY4mHhrbtXvD9zVGKEQcNvNZ8awdYJJ6A5a+/btAQCbNm0yxoVCIWzduhXBYNDzLwa/eXbs2IGioiK0aNHC+npTCCGEiCfmz5+PNetKcctNOTi+6Q9PWTt1SMWQqxvgHy8fwDvvvBPDFoofk9AdtN69ewMAFi9ebIxbtWoViouL0b1796ovOG3zLFq0yDONEEIIUR8oKyvDbb+/Bsc3TcItNzUyxt/3+8ZIT3MwbtSFhxGLI44GCe2g5efnY/z48Zg3bx5GjhzpCaq98847AQA33XSTZ55hw4bhwQcfxKxZszBs2DBPUO2UKVMAADfeeGP0G2v9zNs7uRk7QMurbYwGOzYRxmiYsRQ0PTsVPD/FDLgHD8IPIxYgSMvn2ILyct9ho33cHl4/T8/LZ3h6ar8R41Hm3z5brILhgLETZHPSbA4WCD6fbA6SzVG0LM/mgBkxIuy00erYSQukWZ6Ys+MW9nceDTjWg0eXlnp/sF1/Rvtof9HxNh1Fjtnwbg9P75bS/MnkdFLMhdFedmJDtP9oeQw7sKYTRvsryNvvbZ/NAbZtn9nACB0z2/yV00fQj3r00Ufx2bZyPPrgccjKNJ/NtDghiDH/m4P/N3MvFixYgCuuuOLwFy7qhHpXSeCll17CSy+9BAD4+uuv8frrr6N169a44IILAABNmjTxlGJ66aWXkJ+fj7S0NAwaNAi5ublYsGABNm7ciPz8fPzjH/8w/rJ75JFHMGrUKDRu3BgDBw6sKvW0fft23HLLLbUu9XToK84tODdw8Q8/co6SRYI2bjCGJB3dDprxF6wt18gyfZ130CwdLGsHiuH2WHKxrHAHh9tvfJQQWQfN+AvQ9he4pYMG7iBYc7wsHTTuUNWyg2aMj7CDxlg7LExtc/ksuWvcQXNSvR8JmB0ey/kT9Q4ata/WHTSaPuifu2ftoBG2DppN8o94fs6tNBp0ZB20t8NvAAD2u3t9Z9+3bx/atG6Mpk2S8P6ylgjyP2C/p3B/Bdp1+y8aN0rCR58UI2j7h4WoU+rd3n///feNouVbtmypyjI7+eSTPR2oAQMGYOXKlbj//vvx/PPPo6SkBG3atMH06dMxatSoav9iHTlyJPLy8jB16lQ888wzCIfD6NChAyZPnozrrruubjdQCCGEiCJ/+MMfsGdvGE/+sVmNnTMAyG6YhLtvycWoO3bjiSeeqJu3ReKwqXdP0BIBPUHTEzQ9QdMTNO8K9QTNd3o9Qat2+sN5gvb555+jXbs8/PScVCx9/kTrvaq83MUZPT9H4f4wPt2yFw0aNPBvm6gz6t0TtMTBoYuYbvCcexSM7HsOq5NCNxw3TOtzLDls3B/kXCfKYQskcYeSlsfz2zoY9Bd0mDpw/BeMzQEySvXYHC8bllI9RoeZ/4KkUklG6aQy/gvB/6ZrLJ/r7vHyuLSTpb2MQ1aXsX9tHTZbDqCtNJTRINqftvUxtg49l76y5MIx1uuVSxvx+Wz5B4hRqssGzW9crxHmLtr+gcg3lAB1QMPcATScTepQcvuM2qLcwMg6VPbSTxF22K2l+Wr4B3q5/R+Gd955J0pLXTx4d5PD+odkcrKDKbc3xi9v+BoPPfQQ7rvvPus8om5I6K84hRBCiGOV9evX469/fRaDrsxCl7MOvxj6lf0y0f0naZg2dTK++uqrOmvfX//6VziOA8dx8MQTT1Q7zcKFC9GzZ09kZ2cjKysL5557rqE5MXPnzkXXrl2RlZWF7Oxs9OzZEwsXLqyLTahT1EETQgghEgzXdXHr6POQnAzcf1vjiOZ1HAcP3NUYxQdd3HPPPXXSvi+++AIjRoxAVlZWjdPMmjUL/fv3x0cffYRrr70Ww4cPx1dffYWhQ4di3Lhx1c4zbtw4DB06FDt27MDw4cNx7bXX4sMPP0T//v0xa9asOtmWukIdNCGEECLBeP3117H0Xwcx4tc5yDvJ3+Grju4/SccvfpaJJ598Ah9//HFU2+a6LoYNG4bGjRvX+CHCtm3bMG7cOOTm5mLt2rWYPXs2Hn74YXzwwQc45ZRTMG3aNLz11lueeQoKCjBt2jSccsop+OCDD/Dwww9j9uzZWLduHXJzczFu3Dhs27YtqttSl8hBixmux3MwnBJb7TZjcRanjJwbI9eMF8fSOUvY7PSkWmpPsiPDTgsvz/YRgeFs+H+EYEjShuNlcYBsHwWwg0RE/BGBBaNWpaX9hvPF8P7gj1QckqT5fGDp3jieFqeMzlfzIxRLzl46vb6pKTfqhxX4Tm8cLa7Vavtoha8HW21Vnp8dK9tHCuzI2a4Xgp0vA8v1bOTkGdtn2d+264PvV5acv3AZO2SR1t605MwZTqz/9Wf7SMJw8iwOXNX9qwYHraKiAreOvQI52QHcNsoMpT1cptzeGAteL8Kto7vitX8WHfFymJkzZ2LZsmVYsWIFli1bVu00Tz75JEpLSzF+/PiqPFIAaNSoEW6//XZcf/31eOyxx9CtW7eqcY899hgA4I477kCjRj9sd15eHn73u99h0qRJeOqpp3DvvfdGbVvqEj1BE0IIIRKIuXPn4qNPynDHmEbIbWT5x6cPbVun4DdDsrFoaXGNHalI2bBhAyZMmIDRo0ejR48eNU5Xub6+ffsa4y677DLPNLWZJ57REzQhhBAigZh8729wcosgfjcsp9bLumtsLp75x35c8fOL0K792dVOs27dusNaVigUwuDBg9GyZcuqyjw1sXHjRgBAu3btjHHNmzdHZmYmtm/fjuLiYmRkZKCoqAhffvklsrKy0Lx5c2Oetm3bAqi+zna8oidoQgghRAKxZ18Gup6ThtTU2qsVxzVJQod2KQhVWF6DHwb33Xcf1q9fj6effhrp6em+0xYWFgIAsrOzqx1f+XvldIc7/b59+yJud6zQE7RY4Tie7B6ro2ALIrXl8FhypazLZ2wOEbefHCXb+oycLZuzQtvncpE6Dn41crn8c7a4fYbzcrDEO56DQEGww2PkrnHQcC3/LWXLceOcNXYE2Ymx5ZjZgmtt7XNpenY0k2g8t5fh3cfnC+ds2UrckHNonI82Z9F2ffP5QNdDuMTb3kAa/eVpOJ+Uy2bJsTOOB98PLLlwfH3x9c/ttW2/eX/gnDYuVkzXl+X8M4K7bfcjmzNm5JjR/rAEhbt8/vP8le05ijnzbdu2PewnZdXx9ttvY8qUKbjllls83pioGT1BE0IIIRIM13VR4Yaj8qe23cBQKIQhQ4agXbt2mDRp0mHNw0/IGH5idrjT5+TkHHa7Y406aEIIIYSoMw4cOIBNmzZhw4YNSEtLqwqndRyn6ovK4cOHw3EcjBkzBgDQvn17ANU7Yzt27EBRURFatGiBjIwMAEBmZiZOPPFEHDhwADt27DDm2bx5M4DqnbZ4Ra84hRBCiASk9s++okNqaiquv/76ase99957WL9+Pc4//3y0b9++6vVn7969sXr1aixevNh4Jbpo0aKqaX5M79698eyzz2Lx4sUYNmzYYc0Tz6hYegw4VCx9K85NuqTGaYxagRbHIuLi5YThgPD6eXouns21Ag2Hixwny2ln5D7ZnBd2tjgnjNfHzpklx8yo9WgpTm04QLw+3t8szNqOJ8M5ZLbi4pQbZnWkbM4Sj7cVPzdypSwP843jF1mum1lr1FLsnWFHyOYIsuNmu83S+cHXn+kEWqYv59qu/s6bgS3HkOFi6rb9w9ebJcfNqCVL52uYjy9hc2qtxdwjhdvP90vCKC5v5MrR/eL73Lo1pYc6HfvDezzjs7OzcfGFITz75+MOu8l+XHj5DpSUt8cHH3wQleX9mIkTJ+Lee+/FnDlzcMMNN1T9vnXrVpx22mnIzMzEunXrqrLQ9u7di5/85Cf47LPPUFBQ4Om8FRQU4LzzzsMpp5yCd999tyoLbdu2bejcuTOKiorwySefeHLV4hk9QRNCCCESDBdARZSev8TiMU6rVq3w0EMPYdSoUejSpQsGDhyIlJQUzJ8/H9u3b6/2Y4Pu3bvj5ptvxvTp09GpUyfk5+ejrKwMf//73/Htt9/ikUceqTedM0AdNCGEEELEISNHjkReXh6mTp2KZ555BuFwGB06dMDkyZNx3XXXVTvPtGnTcMYZZ2D27Nl4/PHHEQgEcM455+DWW2/F5ZdffpS3oHaogyaEEEIkGC5chDluKQ6ZOHEiJk6cWOP4/v37o3///hEtc+jQoRg6dGjtGhYHqIMWM7y1ONlhMhwSdoo4x6zckqtjyfmxYjhqltqAtYSdL8bMDSNnw39204kxHD//2p4GFufMVsvPcGy4fbZcLtvx5NGci2WrRckYjox/7pytlmLEOWl8/llqF1qXb3PSOFcrxTI9O5yWnDyzViiPpvOdJ7DleEXqlNF4w8GMMLfPHO/fcbDljrnUfLPWsH/7rLmPllrFZu1jvn4stTQjdM6M1Zfbc9BcABVR+kjAyJUURwXFbAghhBBCxBl6giaEEEIkGC5chBXSUK9RB00IIYRIMKL7ilPEAnXQYoUTqMqyAWB3eKy15ixOBDsxllpwRnsidHRstS9tcC1EdlJ4eQGufWmr3WlzcLg9nMvG8P5jx8iaO8W1LWl9vHx2dHh9nLvEx8cY9m+ew/uLHZ8kW86X5fxmx47bb3POjOXT+nn5NseI96etFiNfH5wLyOenLSfMuJ5o+oBle7hWboiuB94fNifR4lAGUvydUIdzzzg3jddnuf6t55OFSO8Xxv3HqB1L86d4cwatjmiIjpdRy7MGpzX+vwEQtUAdNCGEECIBUf+tfqMOmhBCCJFguG4Ug2qjshQRKeqgCSGEEAnGIQdN1GfUQYsVbtibLWTkRHkHbTlojJGDZquNaDgOND5scWQYdlDYKeHagtwcS+09dkYMR8XizFhrDVqcHMZwjKg2oC1HzXCQyinIzZaDZquVybDDxe3jE4BzsWzrszmKvD5brUw+33l/sJPE01vOV2utWNvyjaA5gudnB4vb40T4zCLgv71mbVpaf6TXD9XOdC3Xl+16Nq4P3v82h5P2v+GUWWoLc+1YzlkznF5yUvn+astdY5yg5fjw7JXj9WgroVEHTQghhEgwXETPQVM/MDaogyaEEEIkGIeKpUdvWeLoo0oCQgghhBBxhp6gxQon4PEYbI6SNTeJIWfIseQO2RwPM0fN8vCcc5q4NiU7W5R75QRT4QfncvH+CFPtQ2N+S66ZNUeN9wc5UY4th8xYIe3PVNp+drTYwbLlirEDRVhrf7JDZMuRsziD7DQ6qeQo8vQ2540dStp/hhNouX6M451GywtxDpalFmW6NxfLsRwPA1sOHjumFicNSXx/IKfT5lzy/rA4pY7ta0J22Ph+YZzvkZ1/VueUseVI8ups4+l+aHWCLVTtj1DNf29E8xWniA3qoAkhhBAJxqGvOCML8PVbljj66BWnEEIIIUScoSdoQgghRIJx6COB6DxBE7FBHbQ4wZabw7XwbNNzrTkDWy1Bbp/huPjnGFnbz06VsUJL+ziHCd7tNRwzm4NnceqMnCpbrhpjcwZ5dnbYbDloTIS1Cg3H0bE4Mrbtp/EO52KFubYq7X+en2s5Ei45VqbTGNn+szpV7JiFLLlixgosL43YoQrx+WqrBWpxsMr8j5fV+WOnLWyZ3uasGsv3dxit3Q4+3/h4co4i3z/ZseP7nyVnzzg/aP18fw7bnFVqb7ikpPp2eBeCsF5x1mv0ilMIIYQQIs7QEzQhhBAiwYjmRwKH8cxS1AHqoAkhhBAJhusC4Sg5aK6rLlosUActVriux5MwnC2uzcZOiS2nh2snkkNh1OazOBu26Y3cNfhjLM82veF00PrY2bHVcmRSyVmz1WI0Gki2QLJ3eU6Q20MODNjhiaz2qZFLFozQXrA4ZIZDx04PH0+jtic5i7b28Pp5/xnOHJ+Plvbw8vj6sORyGRjOkMWpM2qbsrPp7zAh6O+YsbPnqfsLAMn+zppR+zfA+8OSm0gOl83RtN5vONbQUjvX6jByzprFoWWMWpy8f/n65f3J7ePzjc+nmhzScr8cNCeKT9BELJCDJoQQQggRZ+gJmhBCCJFgRDuoVs/ijj7qoAkhhBAJhgsHYTc6L8lcdc9igjpo9RWLk8Y5UwaWnDG+HDlXyja94ezYnBFbzhXnpllql1qdM4Zzn2w5X1Rb0epw2WobsjPE+89Wi5Ph+Xn9PL9teVx7kp1Hzoni42PZfs4NM3LLePsj3L9mrliF/3jGVruRal867MBxDmC5fw6gMd6Wa8fXPyzXCztkLJOzc2bJRbPmHNruB4RbVBzR9BHD54tR29c/d9F2voS59isdL9fmtBo5dt5B6/wiIVAHTQghhEgwohuzIWKBOmhCCCFEgnHoK85oveIUsUBfcQohhBBCxBl6ghYrHMfjpbDzYK0dyA6FY6s16V97zlifJbfJyLWy1AJkJ8VJT/dO73JtUUuOFDsg7GxYcsNsDo/hmKRSrpOlFqKxv4ycI14/OUzG/uRcJK6FaHF8OPfLNj/vf5sDxE5ahFhrm/L5aTg6/rlr5gr9978x3pazZds/7NgZuWx8vlAun8UBszltBpHuX5vTSbllDt9/LLV8DZIs15vhQEb2Ks+1OJJGLpqxAJqe7g+8/eESr8MbSPGv5Wo6xd7hqlqeJRYXLkofCegbztigDpoQQgiRYEQzqFavOGODOmhCCCFEguG6QEXUYjZELJCDJoQQQog6Z/z48ejTpw9OOukkpKenIzc3F2effTbuvfde7NmzxzPttm3b4DhOjX8GDRpU43rmzp2Lrl27IisrC9nZ2ejZsycWLlxY15sXdfQELVZQLU5jtKUWnOE0WXJxDOcs4D30Rs4ZOVxGbT3L8hHyd7rM9fk7bZyTxVtrOHQBizMTttS6Y4eNHSCjViGt35bLxU5YmJ0nS/t5fxtOnr8zaK01anPWCJdrOXL7ef1ca9GWc8a1QC05flaMXDj/Wp+ROmnW8bbanpHm8gW4tiM5TuxM0fXC15d1/Xy+GM4o16b1z80znVmLkxlhDpiRs5fCtUq9559xv+H22e7PhJGDZrs/uJyrx7VCK8fXvBwXDsJRewYTnVelDz/8MM455xxcfPHFaNq0KYqKirBmzRpMnDgRjz/+ONasWYOTTjrJM8+ZZ56JAQMGGMvq2LFjtesYN24cpk2bhhYtWmD48OEoKyvDvHnz0L9/fzzyyCMYMWJEVLblaKAOmhBCCJFgRLvUUzTYv38/0tLSjN/vuOMOTJkyBf/v//0//OlPf/KMO+usszBx4sTDWn5BQQGmTZuGU045Be+++y4aNWoEALj11lvRuXNnjBs3Dpdffjny8vJquylHBb3iFEIIIUSdU13nDACuvvpqAMDmzZtrtfzHHnsMwKEOX2XnDADy8vLwu9/9DqWlpXjqqadqtY6jiTpoQgghRILhwkGFG4jKH6MUWJR55ZVXAACdOnUyxn311Vf485//jClTpuDPf/4zPvjggxqXs2zZMgBA3759jXGXXXaZZ5r6gF5xxoqAAyflh6wjdrjcsjLPsOFgEOycWMcbjo/FkbHlQLEzZskVMnLS2GHhXCFbzhY7KZzbxI4aO3aW/edSbUWunWnAyyOHyzWOB7eHnRxL7UlbrUbe/5Zhl/a3w86QxTFyuf0Mn1+8/cbx9K+daN0+IzfQkoPG51ukOXK28Xw+2nLYLI6hk8Q5WuQw2ea37C/j+uTLJdLat3x+8XjD+ePasv65j7w97JzZcgxtjqBtf/L8LjutlpwzW+1OJ7lyfM0dp2g6aC4OPd3q3LlztePXrVsX0fKmTp2KAwcOoLCwEGvXrsWbb76JTp06YcKECca0b7zxBt544w3Pbz179sTcuXPRsmXLqt+Kiorw5ZdfIisrC82bNzeW07ZtWwDApk2bImprLFEHTQghhBBHjalTp2Lnzp1Vw3379sXTTz+N4447ruq3jIwM3HXXXRgwYABat24NAPjggw8wceJELF++HH369MH777+PzMxMAEBhYSEAIDs7u9p1Vv6+b9++utikOkEdNCGEECLBcBG9HDTg0BOoSJ+U1cTXX38NANi5cycKCgowYcIEnH322Vi4cCHOOeccAEDTpk1x3333eebr0aMHlixZgvPPPx9vv/02nnjiCYwePToqbYpH5KAJIYQQCUZlJYFo/HHrqNRTs2bNcOWVV2LJkiXYs2cPhgwZYp0nGAzihhtuAACsWrWq6vfKJ2SVT9KYyt9zcnJq2eqjh56gxYqwa9Rn+zFO0OI4scNAH0IbThU7U+xIlPvnBBmOBTtzPk0FYHfAUtixovZxLU9b7UBYcq14deWR5UpxThQ7Osb+481n54tzq5Jp/ZwTZsudsuWWsVNlTEDnF28Pw+3h5Ru5T/65Zi7YASKniGs7Erx9TojOV3agaLzVWTNWaMlV4xOO28/L5+Npc/JqiWtx1my5arbcQ76eEKb9bTiURgN9pzecMFvumiXHzHB+DSeP5uecScPpo/sZt9/mGNtyHavBdaNXi7OuKwmcfPLJ6NChA95//33s3r0bTZo08Z2+8lVoUVFR1W+ZmZk48cQT8eWXX2LHjh2Gh1b5hWi7du2i3Pq6Q0/QhBBCCBFTvvrqKwBA0mGETq9ZswYAqty0Snr37g0AWLx4sTHPokWLPNPUB9RBE0IIIRKMQ684A1H5Ew02bdpU7evHcDiMO+64A9988w26d+9elV/23nvvIVzN17RLly7Fww8/DAC49tprPeNuvPFGAMD999+PvXv3Vv2+bds2zJ49G6mpqRg2bFhUtudooFecQgghRIJx6COBaFUSqP1yXnvtNdx22204//zz0apVKzRu3Bg7d+7EypUrsWXLFhx//PGYM2dO1fQ333wzNm/ejO7du6NFixYADn3FWZljNmnSJHTv3t2zju7du+Pmm2/G9OnT0alTJ+Tn56OsrAx///vf8e233+KRRx6pN1UEAHXQYofjeLK9DGeBMGvVWawAW64PLS+QXn3Cc9XkEdZ+tOWeGblqfCNJTvEMOjUkUNcIOy7krFlz4Wy1FHl7WdHi5VucM65d6XJumiWXy5g/lRoUaU6YzXEy2ud/vrmcm2dbH+daVZADxPvDqA3JTqF/7pxxfbFDZttfIf/jaWCr/WnkvNlqN/J4m4NJ7eXlWbbXMXLjqLalpfYnHO/17R48SKO94625bOXe3Ehbzhlvr9VJ4/bbXsOxk8b3H95fvP2UA2nUBq106qLsItYlF110ET799FO8+eabWL9+Pfbt24fMzEy0a9cOgwcPxqhRo5Cbm1s1/eDBg/Hiiy/i3XffxaJFi1BeXo5mzZrh6quvxogRI3DBBRdUu55p06bhjDPOwOzZs/H4448jEAjgnHPOwa233orLL7/8aG1uVFAHTQghhEg4olksvfZ07NgRs2bNOuzpr7/+elx//fVHtK6hQ4di6NChRzRvPKEOmhBCCJFgVJZ6itayxNEnfrrXQgghhBACgJ6gxQ7X9XoK7FywAxLyz30yHC/DWfN3YthxsDo3FqeNa2kaThDnatlcCsoRMhwOzrGy5RDx5Lw+W61GHm9zithJY6fGyHGjydOoFijlttlyzQxHjCHHq9b/dDOcL3LwONcsZDk/DYXOsIh4Au9Y3h5bbptx/bGTSAuk+V3OEeMcO6O2qOV6szltjK02KBOhY2q9Xjmnke4vpqNK+4/3N2O7HxrXO90/jOuRnETOeeT2c+1hSw6a4cxVeDMwORcNdL4Yy690MMP+tTij9QVm/THdEotj5gnaq6++iksuuQQtWrRAeno6WrdujV/+8pd46623qp2+oKAA/fr1Q25uLtLT09GpUyfMmDEDFRaZVAghhIg1h4Jqnaj8UQ8tNhwTHbTx48fj8ssvx3vvvYe+ffti9OjROOecc/Dyyy/jvPPOw1//+lfP9C+//DJ69OiBVatW4corr8SIESNQVlaGsWPHYtCgQTHaCiGEEOLwiGYOmhy02JDwrzi//vprTJ06Fc2aNcMHH3yApk2bVo1bvnw5evfujbvvvrsq8G7//v0YPnw4kpKSsGLFCnTp0gXAocyV3r17Y/78+Zg3b546akIIIYSoMxK+g/bf//4X4XAY5557rqdzBgC9evVCgwYNsGvXrqrf5s+fj127dmHIkCFVnTMASEtLw+TJk9GnTx88+uijte+gBQJw0tOrBjkHh2tVsqNi1HpkbDlQ7IDYXt3y/Fzb04bNseGcICO3y1bbkSZnR81Sa9CshWhxknh7LLllnItl5JalUS5Uiv+laXPKOHeMHTCrY2gZz86ckftlOGCW/UewY2c6bP61R42cNYIdMQN+txDknDNLjhtvfzo5mYyltqj1fOXrl2v52pzKNEv7IqxN6iRZ3omxo+f4338MJ41zySw4oJw0nr/CO97h65edM0sunJHjVuZdvjE/5dYZjhxfb7bzF4feSkarFqeIDQnfQWvbti1SUlLwzjvvGEVYV61ahe+++w4DBgyo+q0ypbhv377Gsnr06IGMjAwUFBSgtLQUqSzCE507d6729w0bNiCIjCPYGiGEEMLOoVec0aokIGJBwnevc3Nz8cADD2Dnzp3o0KED/vd//xe33XYbrr76alxyySW4+OKL8ec//7lq+o0bNwKovuJ9MBhEq1atEAqFsGXLlqO2DUIIIYQ4tkj4J2gAMGbMGOTl5eHXv/61p9ZXmzZtMHToUM+rz8pirtnZ2dUuq/L3ffv2Wde7bt26an/v3LkzNr//38NtvhBCCBEx0XvFqY8EYsEx0UF78MEHcfvtt2PUqFEYMWIEjj/+eHzyySe47bbbcM011+D999/Hgw8+eHQb5YbhlvwoC8eonWmpvWlxzIzcHnYu2Cmz5STZcsB4fpvTFibnhnOQeLzNUbM5Tbbts41nJ4Sx1JI0HKwky6Vn5GRZal/anJQIc/EMbLViLbVFjVqafLyDFkeSctIc0DA7a0btU3bmXN/xRu1Qri0atOS4WXLvDGy1cy21XG1OpHPQm7tl5L7x+my5a7ZatbbzkWtLWnPVLDltnItm5JTR+RKmXDranjA5Y+yg2bYvXEr7O9J4pgA7cjXksvnsN73irP8k/CvOFStWYPz48fj5z3+O6dOno3Xr1sjIyMA555yDF198ESeeeCKmTZtW9cqy8glZ5ZM0pvL3nJyco9J+IYQQQhx7JHwHbeHChQAOfbHJZGRkoGvXrgiHw1i/fj0AoH379gCATZs2GdOHQiFs3boVwWAQrVu3rsNWCyGEEEfOoaDaQFT+iNiQ8Hu+9PtHzT+O0vgxlb+nfP9ZdO/evQEAixcvNqZdtWoViouL0b17d+sXnEIIIUSsqCyWHo0/CqqNDQnvoF1wwQWYNWsWHn/8cfzmN7/BiSeeWDVu0aJFWL16NdLS0tC9e3cAQH5+PsaPH4958+Zh5MiRVVloJSUluPPOOwEAN910UxRa5phZNz+GcrBcruXHThLlKDnUgTScNF4fOzfsvHBuj80xoRwhI+eJx3POTxLlmLETQ/vHaI2lNqXh9NlyzXh57KxZ1ucUl3iXR9tv5JZZHCpjPMeWsaPGThw7Y1w7kVdncbYCZeTIJPH+8/+3YKDce3zDND3P7dLp5GbQ+UtOGg+HUyknzNI+N0Jlj7fXKfV3kBzQeDoAfL7YnEvj/DUaSNdzhSUHkB01vnfx9WRZn+GUsqPF03Ouoa1WKeespVIumcUZNZwzIuL7I99fKccyfNB7f+DpAyc08wxXbPnct33A9zlo6ljVaxK+g5afn4+LLroI//znP3HaaafhyiuvxPHHH48NGzZg4cKFcF0Xf/jDH9C4cWMAQMOGDTFnzhzk5+ejZ8+eGDRoEHJzc7FgwQJs3LgR+fn5GDhwYIy3SgghhBCJTMJ30AKBAF577TXMnj0b8+bNw4svvoji4mLk5uaiX79+GDVqFC655BLPPAMGDMDKlStx//334/nnn0dJSQnatGmD6dOnY9SoUYeV4iyEEELEispXnFFZFj9SF0eFhO+gAUBycjLGjBmDMWPGHPY85513Hl577bW6a5QQQghRh+gVZ/3mmOigxSeu16siycXI7WLnhJ0QGm84Z7ZafAznpnEOFDsc7GyUeHOAuLadkQvE7SPnxKg9yvuHt4dr9/Hy2Rljp8RW65Tmt+ZoJaXDF16/zYky1meZ3nDsaDzfyHm8rTYnOW/G+ozahd7hcLJ/+8MpvD/5fGZnyT9nzXDq+Pym+R0ulWl5MGHkotli9KgWo+FYllEDeHtttTIjvf4ZdrxstVX5fmCpNWrA10M5Obh8/vH9LomcM0v7fX1gmA6sNbeN20fb79L9z3Da+P75zR7/9YmERB00IYQQIsFw3Si+4ozKUkSkqIMmhBBCJBgugHCU3DF10GJDwuegCSGEEELUN/QELWY45EH45w5Zc3VstSTZ4TCaY3HYyEkzcn/Y4TCcMWovO2CW2pMG7LQxEdYyZCeKMXKoLLlknKtlc8q41qTRXnYMbcPUvnDQ33GzvQkJlPk7PEmWnK+wJVeK4ePBTlc4Leg73jierGi57MDR+UnOUTjL6zQFyv1z34z1cy5XKecawheXc9v4/hDyd+iM6ymVcwrp+NlyAgkjR8/YH5bapHy/4NqZvEIjB81S65KdWsayvcb6je213L/5/pjM20tOGq+OansG0r7PuTxY83E5VItTxdLrM+qgCSGEEAmGXnHWf9RBE0IIIRIM13Wi1kGDCz1EiwFy0IQQQggh4gw9QYsZrtdjoBw0w2lgjNwfmp6H2UGx5Frx/JzbY3XEjNwjygEK06nHjgg5F1xb1JajZtTOJBzOSWMsOUeuZfuNWpLsmEWak8UOi6WaRcROGsfCsZKU4p8jFkrzz4UzG0jrMxxAmj+V9mc513b0rz1pOFrsSIUiq1XKmM6bv0MHjiEzio36L89Wu9Vsn2X9fL0GItt+s7Zn2He8cf+g3C/b/ciAx/P6eYO5uKqxff7rYwfXyC1LsdQSrqDtNXLZ6Hri/VN5//M5Li4QNQdNxdJjgzpoQgghRMIRxVecIiboFacQQgghRJyhJ2hCCCFEgnHoK05VEqjPqIMWK1x4PAgnxZuzZDhfnAtlcZLcsjLPcIAcLiPHjB0wS+6RQcDiiPDyLLlFDucEsbPCjgbXxkyz1NKs8Hd8DKeHY5ySLTlnNH9FKuVs8fzsoPAdkZ0Xm2NGzlg4mdqTYnGW+HDSq5IAO1tcGpXW53DMm+Fs+ee6sQKTVMo5YOxAcc4W15bl8x++8PICllqkhoPFDlgq52bRCvl8suX68fVrqxXJuWw8nmtPcg4bX482p9Nw/mj6CJ06I2eM7hdGrUw+38LssPL56F+rlO+XTjodD8414/u1zeHl9dXk4PnsJhdOFIul61VpLNArTiGEEELUOePHj0efPn1w0kknIT09Hbm5uTj77LNx7733Ys+e6gvCFxQUoF+/fsjNzUV6ejo6deqEGTNmoMLnH/kLFy5Ez549kZ2djaysLJx77rmYO3duXW1WnaEOmhBCCJFguC5Q4TpR+ROtV5wPP/wwioqKcPHFF2P06NG45pprEAwGMXHiRHTq1AlffPGFZ/qXX34ZPXr0wKpVq3DllVdixIgRKCsrw9ixYzFo0KBq1zFr1iz0798fH330Ea699loMHz4cX331FYYOHYpx48ZFaUuODnrFKYQQQiQcTtQctGixf/9+pKWlGb/fcccdmDJlCv7f//t/+NOf/lQ17fDhw5GUlIQVK1agS5cuAIBJkyahd+/emD9/PubNm+fpqG3btg3jxo1Dbm4u1q5di7y8PADA3XffjZ/85CeYNm0arrrqKnTr1q3uNzYKqIMWJ7AzBsf/wjIcC8oNMxwtS24PUtjpoFPD0h6EKUeJHz+n00VJyzNqjbKjwU6SUYuQ2lPu73y47OCwE2M4UOQYlYd9h9lRC9icMlutToacmXCy5Xxhh44VJ8pFC7CiQw6P1W3hUok2J40VIHbyaP2hNM6ZI0esjIbLOXeOnCEQ7KjxeD5/+Hy01P50wyzVWfanzVmyOGqMU8bXK83PzpTh1FkcUspVM5xCYwb/69ua+8ft4/WF+AbBC6Dr18hxpOZY7q/G8bI4rlz72NY+6/04TqmucwYAV199NaZMmYLNmzdX/TZ//nzs2rULQ4YMqeqcVS5j8uTJ6NOnDx599FFPB+3JJ59EaWkpxo8fX9U5A4BGjRrh9ttvx/XXX4/HHntMHTQhhBBCxIao1uJ0gc2fbkbnzp2rHb9u3bpaLf+VV14BAHTq1Knqt2XLlgEA+vbta0zfo0cPZGRkoKCgAKWlpUj9/iM4v3kuu+wyzzT1AXXQhBBCiATDxWE86T5sovsV59SpU3HgwAEUFhZi7dq1ePPNN9GpUydMmDChapqNGzcCANq1a2fMHwwG0apVK3z88cfYsmULTjvtNOs8zZs3R2ZmJrZv347i4mJkZGREdZvqAnXQhBBCiATD/V7wj8qyALRt27bWT8oqmTp1Knbu3Fk13LdvXzz99NM47rjjqn4rLCwEAGRnZ1e7jMrf9+3bF9E8RUVFKCwsVAdN+OA4Hk+MHSx2KkwnjC48zuWxOBIBdsI4Z4dqyRmOG+cuMTS/4Zgl+TsYxm2Fa2vy/rLVquTcN3ZcDOcs0hw4/9E2R8yKJVeNd5jNMeOcsjAdjwpvLB+Syml1/jFRhnNmtI+2J4lraxr4tzdYahT39E6fYqnNaivNyo4hrd+p4FqhdP0a03NtTVvuFztO/jlohvPGTh/lwjkHvQeY5zecNMZwKjnnzVIL1ZbbZnHYbI6gzTFEudcB5lxKWy4a5yo67Fqxs2ccT38nl3PV3Mr7cT1NkP36668BADt37kRBQQEmTJiAs88+GwsXLsQ555wT49bFD/XTNBRCCCGEL2E3EJU/dUWzZs1w5ZVXYsmSJdizZw+GDBlSNa7yKVjlUzGm8vecnJyI56npCVu8oQ6aEEIIkWC43xdLj8Yft44rCZx88sno0KEDPv74Y+zevRsA0L59ewDApk2bjOlDoRC2bt2KYDCI1q1bV/3uN8+OHTtQVFSEFi1a1IvXm4A6aEIIIYSIMV999RUAIOl73aZ3794AgMWLFxvTrlq1CsXFxejevXvVF5y2eRYtWuSZpj4gBy1WOI7XcygnB4QcDc7l4fHhMpqfnDWjFqfN+aJYNsNR49whdtLYsWDnzHDsyHmzrY+dDcoxM9QMdspo/xi5aBYnxnDYWMZlB4wdHsOJYyeJjj/vP14cO0zsfPH8FmeNYecrQHuYl8cOm8sKpeF8cQ4b5a5ZHC2bc8frMxwtVvr48Brnr3f+JHbO+Hxl+PgbtU3ZMeMD7h20rY/HO6VUK9JSG9fI9eL7EV9/5KAZtVeN64fGs8PGuY18f7Atj2tj0v3KDVtqgYY4J87//uSWlPi2r8bampXzc/uNHLXvj4dvLc5ofsVZezZt2oRmzZoZrxfD4TDuuusufPPNN+jevTsaNWoEAMjPz8f48eMxb948jBw5sioLraSkBHfeeScA4KabbvIsa9iwYXjwwQcxa9YsDBs2rCoLbe/evZgyZQoA4MYbb6zLzYwq6qAJIYQQiYYbvRy0aHyM8Nprr+G2227D+eefj1atWqFx48bYuXMnVq5ciS1btuD444/HnDlzqqZv2LAh5syZg/z8fPTs2RODBg1Cbm4uFixYgI0bNyI/Px8DBw70rKNVq1Z46KGHMGrUKHTp0gUDBw5ESkoK5s+fj+3bt+OWW26pNyG1gDpoQgghhKhjLrroInz66ad48803sX79euzbtw+ZmZlo164dBg8ejFGjRiE3N9czz4ABA7By5Urcf//9eP7551FSUoI2bdpg+vTpGDVqlJkOAGDkyJHIy8vD1KlT8cwzzyAcDqNDhw6YPHkyrrvuuqO1uVFBHTQhhBAiwaj8SCA6y6o9HTt2xKxZsyKe77zzzsNrr70W0Tz9+/dH//79I15XvKEOWsxwvV4C14pkx4NzxchhSEojx8zmpNhyzGy5YOyYsDNiwcmovibbD+v3d7asuWfcHkstTnbG3ADlyNmmT/ZOH2ZniEsb0vRGLUpyngwHi++7rPgkW5wzXj45Y0yAnMQKo300PtWyfFaOSsg5o1qVYcvpGk6hXLUSGi7jv2L8nTcmQKUS+fzgnLtgCTlP7Kjx+WQ5njxs5qZZcsVI0nPT2LGyOJLkYLl0P3LT6P5UTk4aLw+EzSHjXEZLzqFRC9hWu9Lm0DIWJ9h0cC33R5sDSFQ5xqGaO2DRLPUkYoM6aEIIIUSi4TpRyzCr65gNUT2K2RBCCCGEiDP0BE0IIYRIMOItZkNEjjposcKFxzswnDGq/eZSzhmSOReHg6j8c8GMWnPsnLETwQ4F50JxjpvNcSslqYlz0ED7w3B2/HPNDDiHyHBY/GtVcnOsThvXzkz2zzVjx8yonchOi5Fjxs4Z57rR9Jb7dkUKt4dz27zTs4MWpsPJDhm3h9cXKGfn0N9J4xwzPuMDrCRZYuz4+Bnt59KyXFuTjx83j8YHyrwNNBxGPr3YmTPOB3aiyIkL8QnBB4Rz7vh8pB1YSpJehLVsjdw0ylUzchAtzpmRI0bbzzmQRq1NctaM3EbDgeXpWdqk7aH7nZHLxs4t5cBVrd9HlYumg1ZPS37We/SKUwghhBAiztATNCGEECLhiF7Mhh6hxQZ10IQQQogEw41mJQG5bDFBHbRY4cDjdTnsNFlycWzOglGr0pYjFCHcXiO3jNfHDpUlZ42dFGP5lvaHU8nxYGfGlqNkSEa+qzO2pyKVaqWmeIdD6TSeakdyLpcTZseM1m9x0kKcS0ZXvumc0Xia3yGFx6g9Soe/whvTZxDgUqylFufMqL1J49mZovYmseNGjiDvf14e56IZO8BSKzVAuWjG8bTUHjWdSO+gU0bLp9w9zhEMlNAGGbVTaX8YtWfpfsPXG9fqTLXcH9g5szmmpHwZ60/z5i4aDprl/mQ4teS08fycU2k4wFxrlx034/5DB7hy+eo3JTTqoAkhhBAJiNGRPtLlRGUpIlLUQRNCCCESDBeOYjbqOeqgCSGEEAmGYjbqP+qgxQrX9WabUQ6PNRenjKQLdrTYgaAcHcaai8a1KSn3jNdn5Bhx+zjXjbbXqCXI28MOBzkq7KBwLpSxfFvOGi2vIp1z2/zhWpHsJLFTVU7OGteStOWaGTlkPEyH23C4DKfLO2woiByDxbFV7PCxo8W5auxAWZbH28P7x6w16l8L03Du2PniFYCnZwfO8leccb7RaHakjJwv//OL5w+U8/Xp3zw+/12+3jmHjK83Ywd6ccoNqc+LUVvU//p1LQ6cccKx88bOFztrXNuTl8e5kbx/+H7MDjLvb3bUqkZAJDDqoAkhhBCJRjS/4lTR9ZigDpoQQgiRYLhwovaRgIgNqiQghBBCCBFn6AlazHC8WTgB/0PBuTqGo0ZOmpGzw8uz1crkHCkjt4cmZynJkuOGNArGYqeE4FwvI2fNmJ4dNXZGaJD/ocm1LWl/hbm2JuWYcQ5aBdX2rDAcMdrfHLPEh4uVJVp/yBv7ZO4/np8crQp2tjh3jHPFSInk/WnU3uRashYnjB03Wy6accJnUg4ZnX622qG8/OBB7/JS9vMKLf/2pesriS4odiSNy8OojWlxKolwMjtk5FDx+U/XP0/vprKDSuNhcUQ595Br53L7GN4f7NTaHDbGUtuTl284wTa49jBvr6X9h7M+fSRQ/1EHTQghhEg0olpJQMQCveIUQgghhIgz9ARNCCGESDBc6NVkfUcdtJjherNtOOfGqGVJzkZpqf94dibSqRYd5fCw42arlemQM8K5PQ47FuzEcO4Rj7fV4uScI24/4XDtQ3bSGHZ6jFqN3uWF+WE0x8qxU8Y5V+z0RejksSNljKfdY+Sc8e5lBSaJcrQstSmtuWXcHlq+sT2l/o4aY9YSpfWzc0fOXiiDrh8+fsm8/eSUUW5duIJrcdL4IDtlNEwSn+GoeZtnxrQZ4/1z9RDiE9TfSQuUWWoH8/nMuWQ254xzE/kCYiw5ZAaW3EXOQTMcMHbW+P5WS+eNl+dU5j76XgeOHLR6jjpoQgghRILhInq1OJWDFhvkoAkhhBBCxBl6giaEEEIkGm70XnGK2KAOWszgHDSWbvxzjYwcM3bWuHYcOQ5ORoZ3fMB/+S4tj3PPjBw0hp02I4grstqYXAuQnwVH7nBZ1sc5Y+mUi0bj2VHiHDSjNiURplqK1lqZfPpYalXacr8q0smRSuH96R2uOMgOlXdqdrrCaew40WCZ94dgMZ1vpCTx/Lw/DEeOnDFuXwW3j/en4aCxxOdfqzFQ7t9gm0PGf+8mlfk7WQEa7wbIKQSP988NNNrDsYTW2pneGbgWp8vXP+ewscPG0xtOGd8guPgqS5P+TppxfyQn2Lg/G7VTLQ4hz8/3u8payD7HJZqvOOWgxQa94hRCCCGEiDP0BE0IIYRIQPjFhKhfqIMmhBBCJBiuG8WvOEVMUActVjjwemeGE0GOhSXny8gJMpwqfyeGnRnXtjzCJSfE6qQZzgg7MOyoUU4Sty+ZnBDOheNagRWcu+XvpPEw1z5kZ8gYZuWKcq6M3DHb7uPDx86af6lSsxYpKzNJFmcs1Xu8ww24eKZ3/uQ0r2OUluIdDtD0B4u9wWWhJO8OYkeNt8fIYaPjF6Dt4+nZETNqz9LxM2u50jBf3in+51cgxAcIvlSksaPF81NuGeUChoM0nnPQ+FEMX5+cq1bGxVNB4+n6tdQOZUfNuB/y8tg5szlmNoeNc8r4/szTs1NnOGh0f2JnmIi41qdICNRBE0IIIRIORzlo9Rx10IQQQogEw41isXSpbLFBX3EKIYQQCYgbpT/RYM+ePXjiiSdw5ZVXok2bNkhPT0d2djbOP/98/OUvf0GYXvtu27YNjuPU+GfQoEE1rmvu3Lno2rUrsrKykJ2djZ49e2LhwoVR2pKjh56gxZIfew/sNHDOWLIlF4cJcLFDcrhsOTu22nXcvjReniV3iIdTaHmcE5RM7aPlh1No/fxPD2ovOzdcWzBM7alI4WAt76CRg2YZDqX555xxzhbDtSON3LMIc9JCaZQDluk9X1JzD3qGj8/5zjOcleLNgUpL8jpBLTL2eYYbBYs9w8lU7HJ7aSPP8L/3nOAZ3l2Y5RkuL6VcuhI+n6lWZhE7V+QYkoNmKGWGk+YdNmqBprDDyAv0DvL5wU6j4ajBf/lJBy05aRYnja9Hw/ljp5OuR4ecNheUg2bkFvLxo/mNWr20/eyccfv5/sSwY8q1hTkH7aD3+gDVPnbYMTOcPv9aw8b9unJ6djHjmOeeew433XQTmjdvjl69eqFly5bYuXMnXnjhBdxwww1YtGgRnnvuOTj0d8OZZ56JAQMGGMvr2LFjtesZN24cpk2bhhYtWmD48OEoKyvDvHnz0L9/fzzyyCMYMWJEXWxenaAOmhBCCJGAxNNXnO3atcOCBQvws5/9DIEfdUinTJmCrl274vnnn8cLL7yAq666yjPfWWedhYkTJx7WOgoKCjBt2jSccsopePfdd9Go0aF/6N16663o3Lkzxo0bh8svvxx5eXnR2qw6Ra84hRBCiATD/f4jgaj8iUJ7evfujf79+3s6ZwBw/PHH48YbbwQArFixolbreOyxxwAAd9xxR1XnDADy8vLwu9/9DqWlpXjqqadqtY6jiZ6gCSGEEMKXzZs3o3PnztWOW7duXa2Wnfz9K+Qgv8oF8NVXX+HPf/4z9uzZg8aNG6Nbt27o1KlTtctZtmwZAKBv377GuMsuuwyTJk3CsmXLcO+999aqvUcLddBiRdj11G9zUigIi2tBcg4QDxu5Y1yskGBHgy+MMOWakYNh1OZkpyxMjgiPZ4fE5qhxLhk7MpxTFLQFgRFG7UAaTOL2eQcN58zIJePcK14+fMcb66PN4+nN2puUa8a1N8k5S872OmV5Tb71DPdo8qlnuEP6l57hM1K+9gw3S/KuMCtAEp2FdU28OVAL95/lHb+vpWf4myKvo1ZYlO4ZLkn15qyFD3oPADtqXPszqYRzy7zjbU6acXw5R4xz1oz5Lbldtlw2Xj2dr4Fybg8Ns3OWbHPW2LmiBpADZzhn7JhxLU52Zm25bZFG7FP7DeeMHTMadku81xPYabPlovH9rbL9YR+30DV3+xFTh59xhkIhPPPMMwCq71i98cYbeOONNzy/9ezZE3PnzkXLlj9c90VFRfjyyy+RlZWF5s2bG8tp27YtAGDTpk3RbH6dcky94ly6dCmuvPJKHH/88UhNTcUJJ5yASy+9FK+99poxbUFBAfr164fc3Fykp6ejU6dOmDFjBips8rwQQggRB0TrFSdwqIOzbt26av/UhgkTJuCjjz5Cv379cOmll1b9npGRgbvuugvr1q3D3r17sXfvXqxcuRK9evXCihUr0KdPHxQVFVVNX1hYCADIzs6udj2Vv+/bt69W7T2aHDMdtN///ve46KKLsHbtWvz85z/HLbfcgp/97GfYtWuX8d775ZdfRo8ePbBq1SpceeWVGDFiBMrKyjB27FjfT3uFEEIIcXjMnDkT06ZNw6mnnopnn33WM65p06a47777cM455yAnJwc5OTno0aMHlixZgnPPPReffvopnnjiiRi1/OhwTLzinDNnDh566CFcd911ePzxx5FCrxPLy394f7F//34MHz4cSUlJWLFiBbp06QIAmDRpEnr37o358+dj3rx56qgJIYSIW1xE8yvO6H8NOmvWLIwePRodOnTA0qVLkZube1jzBYNB3HDDDXj77bexatUqjB49GsAPT8gqn6Qxlb/n5OTUvvFHiYTvoJWWluKOO+5Ay5Ytq+2cAT8IigAwf/587Nq1C0OGDKnqnAFAWloaJk+ejD59+uDRRx+tfQfNcbzZNpRD5lBOD9fGNHJxOCfNUlvOyPUxnC9/h8th94Fz1FLIWUtiZyzsO96cn5wcykUz5ifCqZSTRc6MUSuRahuauWE03uaMGTlnvD7OSfOO5/VXpPk7ZWEa7wZJImnoPZ8aNTrgGW6fu8sz3DVnq2f4iqyPPMOtkr3OF8DDtaNzqve67XzcfzzDH2S/5xleQI7ae/tO8gx/lel9DfJtYaZnuDzZu76kQu8ODpCTZp4f3mGE/f+C45w0dn6Syuh4Gk4QOWQVfH7Q8un85Vw1ozZoBZ/QtHZ2uthxrWCnjYufcs6g//XMTi7vXZdzFdlZY6eU22ORt6y5aHy/5fsj32/Z6eXawnz/r2xvic95FU0HLcrMmDEDY8eORceOHbF06VI0bdo0ovmPO+44APC84szMzMSJJ56IL7/8Ejt27DA8tM2bNwM4FPdRX0j4Dtobb7yBXbt2YcyYMQgEAnj11Vfx0UcfIS0tDV27dkW3bt080/t9BdKjRw9kZGSgoKAApaWlSCXRmKnpi5cNGzYgiPRqxwkhhBC1J3q1OKPZz3vggQcwYcIEnHXWWXjjjTfQpEmTiJexZs0aAEDr1q09v/fu3RvPPvssFi9ejGHDhnnGLVq0qGqa+kLCO2jvvvsugENPwM4++2xcfvnlmDBhAsaMGYPu3bvjwgsvxK5dPzwt2LhxI4Dqe9nBYBCtWrVCKBTCli1bjs4GCCGEEAnApEmTMGHCBHTu3BlLly717Zy99957Rvkn4NDHfg8//DAA4Nprr/WMq8xTu//++7F3796q37dt24bZs2cjNTXV6LjFMwn/BO2bb74BADz00EPo0KED/vWvf+Gss87C1q1bMW7cOCxZsgS//OUvqz4UiOaXIDV93dK5c2dsXr8tsg0RQgghDpNDDloUF1ZL5s6di7vvvhtJSUm44IILMHPmTGOavLw8DB06FABw8803Y/PmzejevTtatGgBAPjggw+q3nJNmjQJ3bt398zfvXt33HzzzZg+fTo6deqE/Px8lJWV4e9//zu+/fZbPPLII/WmigBwDHTQKnvgwWAQCxYsqDo4Z5xxBl588UW0b98eK1euxFtvvWW87qxTHHi9rXKvY8C16qy1N41ac5ZH2xZHzYCdEHbejNp3VEuOFmc4Y0aOGs9PzhcrcpyTxrlJnONE2xtK9e7fUDo7Zv65VJxzxjFwZm6Zfy1OXn4oi2plWhwzN83r3KTnlHiGz2ruzS3rluN9Inxm+n89w+ekeOfPCkTXMastnVK80lenJp94hv8v1evUrUrzPiHfGGzmGd4RaOgZLguzk0XOKNXyTOLSi4bS6e+MseNm1nb1jmdHzYwh9L8+3IB3/iDnbvH1RH9jO5xjZuSQeQddvp+wo8b3I7+8r2pwrDmRBK+PnC8jJ5Jn51w0vp9Z4plcun86KXz/Z+nv++X73eZdAHFU6mnr1kMea0VFBWbMmFHtNBdeeGFVB23w4MF48cUX8e6772LRokUoLy9Hs2bNcPXVV2PEiBG44IILql3GtGnTcMYZZ2D27Nl4/PHHEQgEcM455+DWW2/F5ZdfXhebVmckfAet8ouNs88+2+g5Z2Rk4NJLL8Vf/vIXvPPOO+jWrVtCfgkihBBCxJKJEycedk1NALj++utx/fXXH9G6hg4dWtXRq88kvIPWvn17ADV3qCrrdR38/l9AldNXlzYcCoWwdetWBINBQ04UQggh4oloBtWKo0/Cd9D69OkDx3Hwn//8p1rh8KOPDsUFtGrVCsAPX3gsXrzYmHbVqlUoLi5G9+7drV9wCiGEELHEjdIfERsS/hXnySefjP79+2PBggX44x//iLFjx1aNW7JkCV5//XXk5ORUxWrk5+dj/PjxmDdvHkaOHFmVhVZSUoI777wTAHDTTTfVul0OHG82DjlmnKNjwI4COxPsPNg6lBYHzHA42DljeHqjVqB/7U2X90cyS120PnJezJw0ro1JjhnnRBEVFJ9nc9I4F8twiHh5lpwzI/csjZwVcs5yG3/nGT6vuTfH7KYmKz3Dp6VkwJ/IamfGG9c02OMZPiN1uWf49YzTPcP/Sm3rGf7E9eY0hcq8MTlOhb+zyLU6jb/16PxnB42Hk0r9ryfHWD6tnpwznj6UTrVJS7znVxJdb2GujWuphemU0/2J5gePj/D+49L90Sktq2HKygk4J47ul+y0WXIl3XKLw+bw/qJanbaSgvEacCaiSsJ30ABg9uzZWL9+PW6++Wa8+uqrOPvss7F161a89NJLSEpKwhNPPFHlnjVs2BBz5sxBfn4+evbsiUGDBiE3NxcLFizAxo0bkZ+fj4EDB8Z4i4QQQgg/nCh+JKDXnLHgmOigtWjRAuvWrcN9992HBQsWYNWqVWjYsCH69++P2267DV27dvVMP2DAAKxcuRL3338/nn/+eZSUlKBNmzaYPn06Ro0aZXwRJYQQQsQTbhQrCeiBXWw4JjpowKHSEI888ggeeeSRw5r+vPPOw2uvvVbHrRJCCCHqCHWs6jXHTAct3nBdF+HSH3kHnNPFOWHkYLjkVBjTc25auXd6N+B1LIzanuyg8XCQJSv/3CLXViuUHRVLDpKb4n/qBkq9zkg4hdprcc5sbwZ4vMNKjDGeHDnafs6tcjkXLYnOD3LOMhp6c8rOaerNObutqde5ah6Mrxyzo42Rm5b7mWf4wkxvjtqctJ6e4TeTvF9xl6R4nbRACdW6LPOvZWmcL1w6kmouBg+SA2k4ZjQ/5aQ5ltqgSfQ3u0uOmBlzZqm9GSJnksezc8bXvyVn0chNPMjSnwXXUovT4sxah43apCwZWm447KTpLc4xgTpoQgghRAKiiIz6jTpoQgghRKKhjIx6T8LnoAkhhBBC1Df0BC1GOI6DwI+yydwQORPkkBlfjhq1MCv8h5MpeIvg9XOuj7E8m+LBTlmIavulWBw7riXKOWn85N7icLADxrUPwzScxLFyKZzT5h3PSg/XSuRanewIGbUK2SmiWpvBFO/+PK7BAc/wxY0+8gwf685ZpHRN9Z7/XU9a7Rl+JnujZ3j+zi6e4S17GnuGDxZ5r79wGRfLpAaUkfNVxNeH/7+tjRw0OqGCpf45aOxIcm4a5wjykxon1f965OvPrB1M9w92uDgXLcBSHOemWXLFuD0R1v40nTVaP+e8sfPL93+bc1Y53vaETK846zXqoAkhhBAJSNTiMfSqNCboFacQQgghRJyhJ2hCCCFEouFGs5KAiAXqoMUI13XhlvnUh7PV5qTam0aOGdfqJNhpc9nxYCcilRw2rv3JuWs8zO1nZ8zicIQaUG4b5SoFaNh0uPydGR7mWors6HBtxAoqVck5Vg4rR6y48ObTaHZsAkneBTROK/IMn57yNS0gHSJ6DGm42zP80/TnPcN/zrrAM7x6pzc3bd8B7/EoO0i1HOnlRjiFcsmSeJidMf9cQaN2rCXGy1ge1+Ikx9KoFUqE0733q6QD3gvGyEVjJ4udVSOXkXLRyi25iuzg8v3U5rDZcsnC/tvD918j19KQVisn9F+tXk3Wb/SKUwghhBAiztATNCGEECIR0RO0eo06aEIIIUSi4UIOWj1HHbRY4cDrUXDuGTkIhqPAzgM7C+yIkVPBSoNjcdaMWnJpXifMWnuTcJOTfIfZMeHamsbyLPchdtQqKMfJzI3yDrIzVsFKF89vkQds6zO2h4LWAuSkpSV5909A/3Q+qrRLzvQM98953zO88btmnuE9+7y5dG45nY/lju+wzSEzcvq4tivdPwJ8eVEumFEblmPJeH7L9cgOqXH98/R8/+H7n+GcUYPYeQ1YcibJSbPlVBrOrlFLlBw0LmbKThrgO/6wa3EqZqNeIwdNCCGEECLO0BM0IYQQIhHRk696jZ6gCSGEEIlGpYMWjT/WPI/EZ/fu3faJAKxduzZq69QTtDjBdMrYkbD0pdnRYEmEc3hADgU7DpzDVk65a+zIsXPGDgblFLmp/s5bRSrnqnEtOv9agrz+MC2vgmqBGg4Pl/JL9r9BsaPGzo/VMePJ+XCzQhPwrjCVJKA0I2hNHE3aJO/3DDdMLvEMu3wCUO1NJ8SOGNem9F+/7Xw2nMpkXj5dX3R/SmKHKsw5a1y7lnPZaLiM1mfU6uQLkpyzkP/9C6WUOcm1Njknju+nDDtnAXbo/Oc3ci0ZIyeNcuIqj4eekB01zjrrLPx//9//hx49etQ4zfTp03H77bejpKSkxmkiQU/QhBBCCCF8+Pbbb9GnTx/cd999Rgd77969+PnPf45x48bhxBNPjNo61UETQgghEhE3Sn8E3nnnHbRt2xb33nsv+vTpg6+/PlSt5c0338SZZ56JhQsXIj8/H+vXr4/aOtVBE0IIIYTwoWPHjli3bh2GDBmCFStW4Mwzz8SIESPQu3dv7N69G48++ij+8Y9/oGHDhlFbpxy0WPIjr8Naa5MdNc4tM3J3aF3sSLCjRn11ozYd5ZKxc8I5ReykuSk0zDFGKf45SKx0uJRjZpTyZIcF/uMr0qn2ITk5Ro4UDTsUO8cODtfqDFGOWiiTnTlybNK8BzQzzevUNE8r9Ay3DGZAxI7mSd7934ActKSg93hWJPH1QucD18qkH/h8DFNMYQVdcG6Z//XB0wdL/GtvBtgpC7FDRtcTPxtI8c8lC5T55yCCt8fiwCLs/2zCSWJJz792puH48v2aciidsPeG4bIzx+0xfnBqGEEoBy2qpKen46mnnkLHjh1x66234tFHH0WTJk2wbNkynH766VFfn56gCSGEEImG68CJ0h/xA0uWLMFDDz0EAGjQoAF2796NBx98EEVFRVFflzpoQgghRCIiBy1qVFRUYMKECejXrx+Ki4vxf//3f/j0009xySWX4Nlnn0Xnzp3x/vvvR3Wd6qAJIYQQQvhwwQUX4MEHH8SZZ56J9957D7/61a/QpEkTLFq0CH/4wx+wZcsWdOvWDTNnzozaOuWgxQzHW2/SkstjOGecw8PYasXR8oxan5w7xMuz5fg4lhwkctiSSr0ORyjTUhuUV89P4Tk2iXLPKtLIYePcJlbuWPnjXCkutZfsP1yR7t2AUAblMGV4F5iW6XXOmmYe8Ay3TN3jGU6y5eaJOoX3f3qS1znKIIewIotyAllxKmbJjJwtciCN2q3sSCbx9UmOGTtjllw/w2GlWrF8vdscUePRAd9vOPeMHVnGyHmk6Xl57NCWlvovnx1fozYnHdBkdtLo+i+j3DbC+f5+7NgktDh6+rVnzx68+OKLePXVV/Hhhx/iyy+/REpKCs444wwMGzYMw4YNQ6Ca41hQUIDJkydjzZo1OHjwINq2bYtf//rXGDlyJJJqcPcWLlyIqVOnYv369aioqMDpp5+O3/72t7juuuuOuP1r1qzBiBEjMHXqVKSkpHjG/f73v0ePHj3wq1/9CmPHjsWoUaOOeD0/Rh00IYQQItGIs9eTzz33HG666SY0b94cvXr1QsuWLbFz50688MILuOGGG7Bo0SI899xzng9EXn75ZVx11VVIS0vDwIEDkZubi1deeQVjx47F6tWr8dxzzxnrmTVrFkaOHInGjRvj2muvRUpKCubPn4+hQ4fiww8/xNSpU4+o/c8//zyuvPLKGsf/9Kc/xfr163HDDTcc0fKrI2odtJ07d6JZs2bRWpwQQgghEoR27dphwYIF+NnPfuZ5UjZlyhR07doVzz//PF544QVcddVVAID9+/dj+PDhSEpKwooVK9ClSxcAwKRJk9C7d2/Mnz8f8+bNw6BBg6qWtW3bNowbNw65ublYu3Yt8vLyAAB33303fvKTn2DatGm46qqr0K1bt4jb79c5qyQnJwfz58+PeNk1EbX3IC1btsTAgQOxbNmyaC1SCCGEEEdKtGpxRuFJXO/evdG/f3/jNebxxx+PG2+8EQCwYsWKqt/nz5+PXbt2YdCgQVWdMwBIS0vD5MmTAQCPPvqoZ1lPPvkkSktLMWLEiKrOGQA0atQIt99+OwDgscceq/3GHCWi9gStXbt2eO655zB//nyccsop+M1vfoOhQ4eicePG0VrFMYVDuTlWR4xr43EQGr+rt9TeNODp2RVgh6Pc62AEyEkLZ3jf4bMTEyjzLzboci1Qw5nxd8yYMCt2Ru4UTR/0TlBCpznnUnEOmpGrlkzHl4aDlJuVRk5TXvIuiPhhd4X3k/uMgNcpapLlHc+5Y6WlXmmxnHPPSuiEtZ2vPDlf7pwjGPYfTjJyx+ALO21JHOzG16eR80a1Sl1y9uj+YtTm5FwyHmbo/mW9fzJ8fzZuKLR9Icq9ZAeOcjEra3O6lh1v1CiOU5KTD53vwR/9vVf5sKdv377G9D169EBGRgYKCgpQWlqK1NRU6zyXXXaZZ5pIue+++w5rOsdxcNdddx3ROpioddA+/PBDFBQU4PHHH8dzzz2HW2+9FXfeeSd+8Ytf4De/+Y1vgVEhhBBCxC+bN29G586dqx23bt26I15uKBTCM888A8Dbsdq4cSOAQw9/mGAwiFatWuHjjz/Gli1bcNppp1nnad68OTIzM7F9+3YUFxcjIyOyMO+JEyfWOK7Sm3NdNz47aADQvXt3dO/eHX/84x/xzDPP4PHHH8ff/vY3zJs3D+3bt8dvfvMbDBkyBI0aNYrmaoUQQgjxY+LsI4GamDBhAj766CP069cPl156adXvhYWHqqNkZ2dXO1/l7/v27YtonqKiIhQWFkbcQVu+fHm1v+/btw/vvvsuZs6ciZ/97GdVr2ujQZ18xZmdnY2RI0di5MiRKCgowJw5c/CPf/wDN998M26//Xb88pe/xIgRIzzvlYUQQggRRaLYQWvbtm2tnpRVx8yZMzFt2jSceuqpePbZZ6O67Ghz4YUX1jjuiiuuwMCBA9G1a1fPRwu1pc5jNpo0aYJGjRohLS0NBw8eRGlpKZ555hk8++yz6N+/P5588knk5ubWdTPiDschj8ziRBjOGZPMxSFpeexQsLPGw0H/9bETYbQvg6Qrnp6Xz05bqr8TZ+QsUe0/Lk9iViuh2pvklNmcNcf1X18FO23UXiNHjdtb7p2gvNy7wBBJRSkcxCZiysZyb7HVXWUNPMNhOt7JSd7jV+awg+o9H+h0QiBkO1/pB1bI+HKjxRm1c7kWZzlLbNQ+S+4ZO6VOueV8Nu5flhxJ27DNKeP1cc6gUdvYMr/rXR/XHnVtDlz59/dTn93qIHoOWl24bLNmzcLo0aPRoUMHLF261OgHVD4Fq3wqxlT+npOT45ln9+7dKCwsrNZ/tz1hqw1nnHEGrrjiCkyZMgVXXHFFVJZZJ2mW5eXlmDdvHnr16oXTTjsNM2bMwHHHHYfp06dj9+7dWLZsGS699FIsWLAAv/vd7+qiCUIIIYSIQ2bMmIGRI0eiY8eOWL58OY4//nhjmvbt2wMANm3aZIwLhULYunUrgsEgWrdufVjz7NixA0VFRWjRokXErzcPl5YtW+Kjjz6K2vKi2kH79NNP8fvf/x4nnngirrnmGrz55psYMGAA3njjDXzyyScYM2YMcnJy0LNnT7z22mv4xS9+gcWLF0ezCUIIIYSIVh3OKD89e+CBBzB27FicddZZWL58OZo2bVrtdL179waAavsIq1atQnFxMbp37171BadtnkWLFnmmqQvefvttpKen2yc8TKLWQevTpw/at2+PqVOnIjk5GXfddRf++9//4vnnn0efPn2qnadz587Yv39/tJoghBBCiEqilYMWJSZNmoQJEyagc+fOWLp0KZo0aVLjtPn5+WjSpAnmzZuHtWvXVv1eUlKCO++8EwBw0003eeYZNmwYUlNTMWvWLGzbtq3q971792LKlCkAcMQS/+eff17tny1btmDlypW49tpr8eabb+Liiy8+ouVXR9QctOXLl6NXr1747W9/iwEDBtRYI+vH9O/fHyeccEK0mlCvcF3X6xmwg2U4FeRoGM6axaFg54Jrx5FD4XKpT3KyDOcs1Ztr5pRxcUCCHZMUx388kUTj2WEJp3pPbdOBYWeE9q9RO5C231KLM0D7L0yOEDtsSUXeBYaoNmJFiBw0Oh8CHFQljiqlrvd8f7Oog2d4Z4nXQfuuNNUzXFpOuWdldGsuo/OTzi9jmJUpVpoox4xi2oxamYEQT+8/nv9ON3LKjOvL//x1+e+TNFpescVB4/sljXf5fmsjbMlZYwyHmIsFUw6iZfVV+yN6fac6Z+7cubj77ruRlJSECy64oNqi4nl5eRg6dCgAoGHDhpgzZw7y8/PRs2dPDBo0CLm5uViwYAE2btyI/Px8DBw40DN/q1at8NBDD2HUqFHo0qULBg4cWFXqafv27bjllluOqIpAZdvMv3d/wHVdtG3b9ohLSVVH1DpoGzZsqHr/e7h07NgRHTt2jFYThBBCCPE98RRUu3XrVgBARUUFZsyYUe00F154YVUHDQAGDBiAlStX4v7778fzzz+PkpIStGnTBtOnT8eoUaOq7TCNHDkSeXl5mDp1Kp555hmEw2F06NABkydPrlWx9CFDhlS7vkAggEaNGqFr16644oorPK9ca0vUOmiRds6EEEIIUUfEWQ7axIkTfcNea+K8887Da6+9FtE8/fv3R//+/SNelx9PP/10VJd3ONTJV5xCCCGEEOLIqfMcNFE9juN46q0ZuTeUy8O12aw5ZsYKeXpaHztmyeyokbMRCvmOd1K8TpqR0xbyzwEC5zpxbU2q7ccOCw+7Qe/2sJPGw0nlnIvmbU4FP8W25EwZrggrM0F2ZvyPZzkFrX0Xptw5lPjOL6LLyoPez/Z3lHlzlg6GvI5Zabn3eigr9Q6Hi73DTqn3BEw+4B1OIofMcMosilWAS/OSQmp7VcY5gklllhXy/YKdU5o9UEq1KNnZ5ftTind/8/3H2e+therQ8txy2gE2p41hp45z0uh+7fL+MGp1eu+3lbWaHZuEFq0naHH0JO5YQh00IYQQIgGpR98QxB1HGsfhOA6WLl0alTaogyaEEEIkInrydcSsWLHiiObz+9IzUuSgCSGEEEL8iIcffhhvvfUWwuFwRH8qbGXDIkBP0GKE67reepaUw+Oyw0COmuF4cY4ZO1m2Wp4MOx6E8a8Ezimyrc+SS2Q4Zzy9f4yZ1REJJ/H6aTyXNqX2mbUPKbcs1X/5RgxSBm1Qinc4mOy96FOD3vNhS2kz7/wZ/4WoO8qpluK2cm+eI9dKPUg5ZxVh7wlQEfIOp+zyvzU7pEixc2Y6aFy7lsZzTiBfj7x+dqZYIaPrK2DUsuRinf45kC7dD5yDtIHsmJGzhoOltD5yvGh9lY5X1Xh20tjB5e3jWr4cnMi5lby9vP/p/ho+WPL9dD6uX5x9xVnfuPnmmzFx4kSce+65AICkpCRMnDgRd91111FrgzpoQgghRIIRzWLpxyKpqakoKfnhYyvXdc2Ocx2jV5xCCCGEED+iVatWeP3117Fz586q36Lplx0O6qAJIYQQiUgcFkuvL/zmN7/Be++9hxNOOKGqdOXEiRORlJTk+ycYjN6LSb3ijBmO1ytgh8slx8KopcmOAzkYqbQ8dib4XwLsSNhER5tDZnsUzLlFQcu/FSyjXc5t45whzhVip4VUjqRS7/zlGf7Tu5wjR+Ptw+zE0PLoXcWu4kzP8Ibi5p7hVeleB60Hx6SJWrGz4qBnuNz1nn+lJDFWUHHKigqqHVvunb+CFNNgMTldfHkaMXqU60cKllGL0+Y1W3L+OCeQa3MmlXpP+ADnnrHjWezvjBnOGudI8jDX2uTrj+8PttyzZH8HmO+3Rm4kO2ecc8a1S/kv/bTvgxhDPjfGaHaujsFO2qhRo9C0aVO8+uqr+Oqrr7B8+XK0bNkSeXl5R60N6qAJIYQQQhCDBg3CoEGDAByquTls2DDcfffdR2396qAJIYQQCUi0PhJQ4C1wzz33oGfPnkd1neqgCSGEEAmHA7jqWkWLe+6556ivUx20mOF6PC92DJwsr2Nkq73ppHpzlgzngZ0Mro1JuUWGE5FKxSdtDho5dVwLkx0MzmEKpyT5jrc5a0atTnbebCXs2Kmh9XPOmZELRQ5ZgEufllLtQnJqKqh9B12vRFZa4j3e/yrxHp+vDzbwDO9rvtoz/PPMYogj5z9ljTzDu8u9+3tXSZZnmHPPkpI4p5CLT3LOGJ1PpKgaThnX0rSUxjQdNl4+S5f+0xtw6Ux2rPj6TuVcM0vtX6P2JTu7/jlrBjYHN2xzdMlZNXYo3Q8t63fL+IBXzu+z413FbNR39BWnEEIIIUScoSdoQgghRCKirzjrNeqgCSGEEImIOlb1GnXQ4gWuDVfmlUiMBONkS604dtbYOWPHgp2QZK/jZMXmpLHzYeS+kUNTRjlCNueMc8g4p4mmZ6cm7LIjRDPQ9iWREmI2iJwaah+XAg2UkWNUzttLuVlB7/EpyvLmMn1c5j3e/wh29QznJS/2DHdKUVCaH68We/fPv4tP9gxvLmrqGS4s805fwU5igB00cjCT2aGiBkXqfvPlaeT2UU5ZiJ1Nmt4IQmMHjrav3N/5MhxOzknjHLQQ5YglcU4h7bBS/wvWyD0zHDa+IdD2sAPH91duv1G7kyU92v+0PKn/xwbqoAkhhBAJhqOPBOo96qAJIYQQiYg6aPUafcUphBBCCBFn6AlaLPmR1+Gyw8BYHQaLlcCOGOeuca03m0NmtM+/Np7hhHCtzEBkzptDDkqAnQ2qzemQouem+OcQOazoUU6T6aBxbVPvYHIR1yb0TkClG5HyHY2n3RPK4PZ5929ZkteB+rRBE8/wwqwzPcOtc//tGc4KHNtO2mP7TvQM/6f4BM/w1yUNPcPfFHtz0EpC3gOaluy9HpIo56yYhl0K6nMoBowxcs4stwN2zHj+QDmNZyctwM6k/6MaY/oy/1qcBnx/5PsNO18skbJTy/czzn1MtuRKGu2hHZ5E85MD57AzRwfM5ZxIm+NbE3qCVq9RB00IIYRINKLpoKmjFxP0ilMIIYQQIs7QEzQhhBAiEdGTr3rNMdlB++tf/4rBgwcDAObMmYMbbrjBmGbhwoWYOnUq1q9fj4qKCpx++un47W9/i+uuuy5KrXA8HgU7Bpx7w9eZww6VrXYcj04hR4JziMjxMJwIdtbYCbE5cTanjR0Li4PBjozRnmTOfeLcNdo+Uk7YoSun5XOtzTAHnfGVxpsXtgxzbho5dazwce3G/ZTj9f7+Fp7hx2mBvTM3eIbP4lqs9ZwdoQOe4af2dfYMr93X0jP8bYm3Nm5RmTd3jpXQlKD3gkuid00HyRmsKPaeIMkH+Xz1Lp+PP2M6lDR/iJ1Krm3pv/ykUrpeLNcjX288bDqvlp6F7f7BHK6zVTk5O2e22pmMxSk2nGPL/duojVx5/1UHLKE55l5xfvHFFxgxYgSysrJqnGbWrFno378/PvroI1x77bUYPnw4vvrqKwwdOhTjxo07iq0VQgghjozKLLTa/hGx4ZjqoLmui2HDhqFx48a48cYbq51m27ZtGDduHHJzc7F27VrMnj0bDz/8MD744AOccsopmDZtGt56662j3HIhhBBCHEscUx20mTNnYtmyZXjqqaeQmZlZ7TRPPvkkSktLMWLECOTl5VX93qhRI9x+++0AgMcee+xoNFcIIYQ4Mtwo/hEx4Zhx0DZs2IAJEyZg9OjR6NGjB5YtW1btdJW/9+3b1xh32WWXeaapHa7HozBqwZHzYDhf7CywI2RzOGyQY+VYameazpildmaQHTqu1elfm85YXrK/I5JU4nU4wsnk2NFwBTt4JIEFOMaJdw8331JLkR0jXh7noIUt62NKirzO1AdfeXO9thXmeoaXpJ/mGW7TYLdn+JKcDz3Dl2V85xlOdiJ0dmrJO6VeKWtLmbc25pZS7/Bnxcd5hjcXeof3HfQ6e6Wl3gOQlGRzoLy5V0UV3v1/YJ83yC5wwHt9JxVT7dYS79KNnDKLc8aOWZIl58ysrcnXt3eQS1MajlmkGA4r1+K0Obc03uKU8f3VaL1te4z7ocXZZSwOsnE/rWy/j+rrIHqvJ/WaMzYcEx20UCiEwYMHo2XLlpgyZYrvtBs3bgQAtGvXzhjXvHlzZGZmYvv27SguLkZGRoYxzY/p3Llztb9v2LABQaQfZuuFEEIIcaxxTLzivO+++7B+/Xo8/fTTSE/37xgVFhYCALKzs6sdX/l75XRCCCFE3BFnrzjnz5+PkSNH4oILLkDDhg3hOA6uvfbaaqfdtm0bHMep8c+gQYNqXM/cuXPRtWtXZGVlITs7Gz179sTChQujsxFHmYR/gvb2229jypQpuOWWW9CtW7ejuu5169ZV+3vnzp2x+f1tR7UtQgghjjHi6NXk5MmT8e9//xtZWVlo0aIFPvnkE+s8Z555JgYMGGD83rFjx2qnHzduHKZNm4YWLVpg+PDhKCsrw7x589C/f3888sgjGDFiRG0346iS0B20UCiEIUOGoF27dpg0adJhzZOdnY3du3ejsLAQjRs3NsbbnrAdNi68nkSkOTtMaal32LI8J+h1Ylx2Omy17TiYix2PZHI62Cnj5XGuES+famEazpnFUQtbHDUjt4k313BMLDlVvDsjdMYYI2eNS5dyDFwJ1fKkGcr2e4f3VHg/mtmV2sgz/Fm219Ha2MzrdP2r0XbPcJ+G//EM90r35o6lOpHVXmU2lRd5hv/+7QWe4ff3enPeOLestNx7fpaU0f4p8Y4Pl5KzlOw94Ek0HCr3Th8qpdq3e73rS93jPSGCBz2D1Tho3mGbc8a5Z2awIi/P/3oKhCw5XwF26LwN5Fq6xvVug3PXyEG05qTZchXZSSvjYr6W3DZyxoxctUhhJ6/KkY1wv8WQhx9+GC1atECbNm2wcuVK9OrVyzrPWWedhYkTJx7W8gsKCjBt2jSccsopePfdd9Go0aF72K233orOnTtj3LhxuPzyyz0f/8U7Cf2K88CBA9i0aRM2bNiAtLQ0zyPSe++9FwAwfPhwOI6DMWPGAADat28PANi0aZOxvB07dqCoqAgtWrSw+mdCCCFELImnHLRevXqhbdu2ZuH3KFGZrnDHHXdUdc4AIC8vD7/73e9QWlqKp556qk7WXVck9BO01NRUXH/99dWOe++997B+/Xqcf/75aN++fdXrz969e2P16tVYvHix8Up00aJFVdMIIYQQcUsCRGR89dVX+POf/4w9e/agcePG6NatGzp16lTttLYEhkmTJmHZsmVVD2fqAwndQUtPT8cTTzxR7biJEydi/fr1uO666zylnoYNG4YHH3wQs2bNwrBhw6oeh+7du7fqC9CaQm6FEEKIeCFq8RgusHnz5hqTCWryrWvLG2+8gTfeeMPzW8+ePTF37ly0bPlDObaioiJ8+eWXyMrKQvPmzY3ltG3bFkD1b8bimYTuoB0JrVq1wkMPPYRRo0ahS5cuGDhwIFJSUjB//nxs3749eh8bOPB6WIbTYKnVxg4XOwrsRFhqYzqpXkfHcMps60/z5rCxc+aE/GuLGrUzuX3G/qAJwpQjlELOD+1fl9bHuWiG2sGKCe1fIyeNnB+uzZlUasmVYmXIcNgc32FeXqCcnDk6vIGymhyXQ4T2exvwaXEzz/DuA16HbXOO11F7MX2/Z7h9xk7P8IWZXmG4ddDbwP+GvOt/cX9Xz/DyL9t6hvfuoVJu5XR8gxYnq5zPX9rfIdo/xd7ZA6XklFGuGQ8nexU9wzHj84WdR6OWJscqspNGtWeNXDWunclOGl8u5RzkBxr2v785pXRCGrU96f7B53uyJSeS7x+2+y3fj1wez04rra/c3zkzctFo+Vz7+FgjIyMDd911FwYMGIDWrVsDAD744ANMnDgRy5cvR58+ffD+++9XBc4fbvrCvn376r7xUUQdtGoYOXIk8vLyMHXqVDzzzDMIh8Po0KEDJk+eHMVi6UIIIUQdEsVXnG3btq2zJ2VM06ZNcd9993l+69GjB5YsWYLzzz8fb7/9Np544gmMHj36qLQnViT0RwJ+TJw4Ea7rel5v/pj+/ftj5cqV+O6771BUVIR3331XnTMhhBD1gzjLQYsGwWCw6u/sVatWVf1uyyet/D0nJ6duGxhljtkOmhBCCCHqF8cddyjyp6joh6idzMxMnHjiiThw4AB27NhhzLN582YA1VcIimf0ijNGOHA89S2NWpzsULBjwY4ZD9tqWbKTVVLiO95J89YmNNpDjojDtTVpesMpSSanhHOH2AmhXDM3GOG/NXj7aDhsccqYQJCXxzlp/k6a1UFj54cdIWN93uEKOnwsKRkyMTtQtP7wfu/x3Aev8/XdAW/Fjv8keZ21N5Nbe4YXNPB+mdU+x+uohaj46H/2epe395sG3vZSzhgCtP9T6fxPYueJnT1yCIu8O4Rz6gKl7Bx6xyd7Y9wQYEeM9j+fH1xL01g/5wby7YDPP3bQLPcLdhgZ6/yWnDU+4awPccJcu9LfqeT7nZNCDi47cpZamkbOGdf6pOmdDO/1Ed7vrWVr1EKm9VdGVfiZxdGsxRlPrFmzBgCq3LRKevfujWeffRaLFy/GsGHDPOPqawKDnqAJIYQQiUg9fc353nvvIVzNhxJLly7Fww8/DABGmajKdIX7778fe/furfp927ZtmD17NlJTU42OW7yjJ2hCCCGEqFNeeuklvPTSSwCAr7/+GgDw1ltvYejQoQCAJk2aYOrUqQCAm2++GZs3b0b37t3RosWhqiAffPBBVdbZpEmT0L17d8/yu3fvjptvvhnTp09Hp06dkJ+fj7KyMvz973/Ht99+i0ceeaReVREA1EETQgghEo8oVgGIRvb/+++/j7lz53p+27JlC7Zs2QIAOPnkk6s6aIMHD8aLL76Id999F4sWLUJ5eTmaNWuGq6++GiNGjMAFF1xgLB8Apk2bhjPOOAOzZ8/G448/jkAggHPOOQe33norLr/88ihsxdHFcQ35SdQ1lcXSu2X0/+FHdqwsuWNGuQzOJePcHiN3x/Ud73B7LDllRo6QbX1cq5OdNp6eHZJUmp72B+ecgRy1cIp3f3EOGucsGY4aTR9mh46oSCGnxHLZGTlnXJo01ftDWZZ3uLwBOWis2NCwAcfqkWMXZiXS4nRxzhrnuoVTKZeroVfCSkn1Oj5lVNsSu705fMHv+Ph5Jw95FSBj/ezwBQ+QU3aQhsu8ywvQMOeQBTk3zVr7kn7gy4Pm59qcwWLvD7banIFy3h+0/HIOIqT5yyw5ZHS9OsUk6RnOGuWEcc4i546xw2rcH+l8ZYeMnV4b5XTAHf/7ucv3d9v9n6icf03pIbdqf3iPZ3x2djacpq1xct8hvss5XD59bgZOaZqNDz74ICrLE4eHnqAJIYQQiYgev9Rr9JGAEEIIIUScoSdoQgghRKLhulaVQsQ36qDFDMfrHZT7534ZzhnDzhnDuWTsiHFtSc4VCtD87GywU8JOBbefHZNSr8NhOGlBlpZo8dReN4Mcs6DFMTMcHnaqOBfLOz6Jp+eYM3Z+eH9ZnBej9iA9/A4msYPH2+Mdz4eXHTWXlUA+nKwwFvPxpRw5rgVK6+ccu7IS73BJpv+tKolzwMr5AND0JZz7Rdcb17osodqZ5JAlHfTPMTOWx7ljfLkZ5wv8MRwy//PZcMosw+yUGddDKR9Qy/VknM4WB8t2/zOcU76/hf2HjdxFPn/871+Gc8a1NXl/kBMXLvU6eEbuGu0P698HVSs+vMmO2nJEROgVpxBCCCFEnKEnaEIIIUSCkaiVBI4l1EETQgghEo04K3QuIkcdtBjhwOsRuJzTY+SQkWNETpkDy/gUdrhYerHkqHEsj6U2neF48PZZMHKPKOfIYSeNnS7KaQrQ+DArHEaOmr/jkUTOjZFbFqRhVlbYCbTU4rQ5SKbjRLloGd7xFd7YMAQoV41zwri2JDtpRnsMJ8p/ej4d2WkLOVR7lXLWDKmJLx+K2eKcM5apjdqbVKqWl8fbFyz1r5XJx4udMcasbek/Py/fuH/w+Ui5Z7bavexU2nLRjNqWtvF8fRBOiMZzDhpjyRUzis2yU8a4LHHS/YD3H98PqfanrRZojTlu0UiQFXGLOmhCCCFEAqJXnPUbddCEEEKIREQdtHqNOmhCCCFEohFNB00dvZigDlqMcF0XbtmPsr8suWduCeXkpHslIc+yqsNaW45r57GD4u9EGLk9Niy1Nq25Q+yosEPCtQ3JWQmw40Hr59w0hxUXjkliZYacoADnzCVzLUFLDho5bezAMYEQ7z/v+pLIoTKcNJrfyK3yjz0zHDAjF473F21+EjtvnMtm5Mj5L89wvg7SMOemcXu41CLnhNH5YZvecMjI6WLHz3DULMfDlqsXMXw90vVkDUSNsD2cg+iE/HPWjPsHX9+8fM5xtGGZ3lrS2pbzZmmvKQ1KPjsWUAdNCCGESEDkoNVv1EETQgghEhF10Oo1qiQghBBCCBFn6AlazHA9WWVGDBbnDqWRJGQsjqUZS64Zw44L18IMUG4PO3JcSy4tjdrj75i5nGtGOJRz5Kam1DBlDfOT4+EaQVmW+S05ULz/jRw1HjZyp/zXZwS3US1E3nsu5YYFS73rC1NtTsOhohyvihR/54WdqVCGfy4ZO2UMO3LsnFWkcS1N7/TsDAbJOePtC3MtU25fpLluXEqWctSM2ph8PnGtSyM3jc5nmp6dL57f5qgZ4y3OmekERparZtbujDDnjOHrnRwyJzmZxpMTxs4ZX7+WXDWH73fsoPL8vP3k9LJjXPV3h4/75rjRe8Up4y02qIMmhBBCJCL6irNeo1ecQgghhBBxhp6gCSGEEAmIvuKs36iDFicYzhnXdmNnwZaDw9NzThmPZ2eNHRSjtqTFeWOM5ZPTcpCkI8OBs+QI0bCT4nVMzCAuckJABP0dEoadM74xuoYT5O9QmbX4KDeNFRiuTcgKG+V8sbPE7Q9Tbc6KcsqJ48OZTPu3hBy2ZD5/vJNba48aDpatVioPU24ZxwYm0/lgOFveYcNR48uTj4/lL0o+H4IH6fpnx4xgJ82ag8YOnGXYcAi5lim3j+dnJ4tr67JzZqtlGWmt35pqWVYtj50wduD873eOrdQwO2wsbZZ7pUZrTltl+/wOs4ql13vUQRNCCCESEGuAsIhr5KAJIYQQQsQZeoImhBBCJCJ6gFavUQctZjgeL4FzxczJOVeKnCRyPFx2Ohh2Imzjbc4aw9Oz88Pbw46K5dG84QSlsnPGuWSR5Z4FyskBov1h1paMMFeK28OwAwXOvfKfn50kOHR+8OlBElyActI4V8ylw885aWF25pLoeLj+zl7A4oxVpPIB8A4mF9H8lFvGtS259miYTyfaXoeWx85ZoILXz+vzDieVGQeclu9fi5Nz3AIWp8/IRbPVhmQHsIQOCOeI8flt5Aj654hFXKvXkitm5JC53F7L/SxMF4AlB40xnDK+f1ruB4bzW3k9+9zGo5mDpo5ebNArTiGEEEKIOENP0IQQQohERE++6jXqoAkhhBAJiHLQ6jfqoMUM1+tFcC4V53pRjpmR88XTc61LrkVnzUXj5VucNptTYa3F5++kuUauGc3P7WMHyqgNSPuHFs+Oi5HTxLuDc6B4fnbaODfMcG5ocYaD5L/9Rm1EzskyajfSYLK3AUnswBmxTt7jn1RmqU1K/7RnJ4pzzNjpcou4vd5hY3llfL75L99wHHl/8eFgx9DyFyPvP97fXJvTFpdgtJ+dL6rFyo6lE7KcPzYnjIPg+H7E14811zDsP55h55S3n+8ntP0IkVPHtTBtuWzsBPP+syzPuN+nUO1jri1atTpVyUxk1EETQgghEg0F1dZ71EETQgghEpBoveLUq9LYoA6aEEIIkYiokkC9Rh20mOHNQTOdCf/acW4ZBTFxbUt2GCy1K8GOF2M4ahaHhB03W84bL4+nN3KALDlq7ASx42c4ZrR/+Z+M7PSRQ2Y6SLS8ZA4Os9RepeNvOFCWWomGg0ROU9iSsMPzG7UpySlLIscpTNvLpQcZzhljuJYmLy/JyCXzd8ps6k6AYqvCdDrz+jnnzLY+s/aqf86Z6fDR+m2OJM/O53OS//XADqXhYAX5/GaHzFJrk3PRbPcTcmqN3EfOLeTxfP/g5fP1Y3F22SEzchctzppx/G3OXdX09acDNn/+fKxcuRLvv/8+/v3vf+O7777DNddcg7/+9a81zlNQUIDJkydjzZo1OHjwINq2bYtf//rXGDlyJJJqyOJcuHAhpk6divXr16OiogKnn346fvvb3+K6666rq02rM9RBE0IIIRKMqAbVRoHJkyfj3//+N7KystCiRQt88sknvtO//PLLuOqqq5CWloaBAwciNzcXr7zyCsaOHYvVq1fjueeeM+aZNWsWRo4cicaNG+Paa69FSkoK5s+fj6FDh+LDDz/E1KlT62rz6gQF1QohhBCJiBulP1Hg4YcfxqZNm7B//348+uijvtPu378fw4cPR1JSElasWIG//OUveOihh/D++++jW7dumD9/PubNm+eZZ9u2bRg3bhxyc3Oxdu1azJ49Gw8//DA++OADnHLKKZg2bRreeuut6GzMUUIdNCGEEELUKb169ULbtm3tZQ1x6HXorl27MGjQIHTp0qXq97S0NEyePBkAjE7ek08+idLSUowYMQJ5eXlVvzdq1Ai33347AOCxxx6LwpYcPfSKM04wTlpL7U2Uc3FBlmL4ImBHhGtl0vLYSUu2nCqOv3PhWhw5c3kWB42dF6PWJTtbFgfEcLa49iXnivk7btb2MzR9oNR7PNwg5Tix08aLC1mcMFqe4azR/jTOT56elUCqLVmRQrlq5TQDxVAl8f6lFRjjCVttVHYQub3hoH/umVkr07J+HuTYQLr8GMN545w0Hqbz3cjR4+ux1N95MpxNPuCW2pou3T+c8lANU34PO1+8PL6eudYlS5OW5UUM319o/xv3V1vtUIKdtprvb/6dnXh6xRkJy5YtAwD07dvXGNejRw9kZGSgoKAApaWlSE1Ntc5z2WWXeaapL6iDJoQQQiQa0cxBc4HNmzejc+fO1Y5et25dlFZ0iI0bNwIA2rVrZ4wLBoNo1aoVPv74Y2zZsgWnnXaadZ7mzZsjMzMT27dvR3FxMTIyMqLa3rpCrziFEEIIETcUFhYCALKzs6sdX/n7vn37Ip6ncrr6gJ6gCSGEEAmHay0RFglt27aN+pMy4Y86aDHDW4vT5dqEltpubrJ/bpmRk2bkmHklGCPnh50O5vv3/jUt3w2Ts2KrzWmrbWk4eNQ+djx4ebw/ef3lXOvOOz3nXBlOGD+MDlhypLg9XKuTt9eyfUZuGdV2DIR4Bu+gyzlytLyAUYuTnDnv3HAptyyZ9keFRUHkVzPsiDmW05MxHCyjFihtLytwrAyxg0bzh7nWKmGcT8byvMNJfPx4e2x/EbMzyLU4OaeLsdXitTmKfD+K0LG11dZEkveEMhy1cpIc2Zm15Y5FmqtGGLWQje33d/xsOYI1r/gI54sxtqddlb/n5OR45tm9ezcKCwvRuHHjGuep6QlbPKJXnEIIIYSIG9q3bw8A2LRpkzEuFAph69atCAaDaN269WHNs2PHDhQVFaFFixb1xj8D1EETQgghEg7HPfQkNip/jnLbe/fuDQBYvHixMW7VqlUoLi5G9+7dq77gtM2zaNEizzT1BXXQhBBCiEQkWkG1R/lVaX5+Ppo0aYJ58+Zh7dq1Vb+XlJTgzjvvBADcdNNNnnmGDRuG1NRUzJo1C9u2bav6fe/evZgyZQoA4MYbb6z7xkcROWj1BCMXh4ctTho7Zux0VFNs0TvMzgc7ajYHgx0XzmGy1cKz5SylWk5lzhHi5fH6yCEyamFyLhQ7ZkF/h8yY3hbeyMeLa4vaSvdxewh2qNiJYufJqP1oqRVp/BOcpBrOBWPnK1DmnysWMBwzgreP9h/nirlcm5X3N28vK0Wc02ZRuMxcM7o+DIXOklvH87PDZtTqtOSaRSibG9erLRfQOL/JkaXlG44tE7ZcEHy/49HG/dY76FCum2vJpTScM94+Wy5aaSmtv9K58zkubjWu7RFT++W89NJLeOmllwAAX3/9NQDgrbfewtChQwEATZo0qSrF1LBhQ8yZMwf5+fno2bMnBg0ahNzcXCxYsAAbN25Efn4+Bg4c6Fl+q1at8NBDD2HUqFHo0qULBg4cWFXqafv27bjlllvQrVu3Wm/H0UQdNCGEEELUKe+//z7mzp3r+W3Lli3YsmULAODkk0/21MocMGAAVq5cifvvvx/PP/88SkpK0KZNG0yfPh2jRo2qtiLByJEjkZeXh6lTp+KZZ55BOBxGhw4dMHnyZBVLF0IIIUScEEdfcU6cOBETJ06MaJ7zzjsPr732WkTz9O/fH/37949onnhFHTQhhBAiEYmjDpqIHHXQYobjyfJhJ4wdiADljhnXnS3HiJ0HI0eIJCDOGaPpHYvzZiyP22fL+WLYpWCnq4RyjizT87DhFJV6l2fkuBm5dP4OnTW3yqhtyc4ObW+R10lxU8iJoe9/jJw0I8gLNGzJtWIHjdoXKKP2siPlP7vx+ZLhaBn70zto1MK0OHXG/DS5U0q1Oqm2aJhy52wOmZFLx5eHxSEzcvPYMTT2Lx0PEOyM8f2Ba3vacs2YCGvRGo6trdYwn190fzLWzrmN3D52yHh/8PnF90Nbrhpfj+T0usb2UHBgpUOnDlhCow6aEEIIkWA4bhSLpasjGBPUQRNCCCESkSiWehJHH+WgCSGEEELEGXqCFitc1+MdcA6Yk8K15Sy5ROyYWWq9WWGHjHLRjFp0nCtk+5cb56CxY2JzPowcquhmXbNjZWxNitc5MWoZslQVqbNjcfbcdEsxS6P2Ii0v2Xt8DWWPnK+ALbeNxvO//MIB7/oC1J6KFH+HitvDTp2xfYT1VY8lJ423N0C1QdkZY6fRzCmzOH0WuFarkXNGjp15flp2CDuokU7PRFgr1HDOCL5fuFwrlven4SRyTpl/+1zb9jG267fc3znjHDeX7q9Vfz+E/O8jUXvFKWKCOmhCCCFEouG6ZsdU1CvUQRNCCCESEH0kUL+RgyaEEEIIEWfoCVqcwM6EUXuNc4zYUbM4aUbuj1FrjhwHzvminB4nlRwort1JVFeWwxfOZbI4KZHmnjFG7UBbThs7KTy9JTfMDdLxYfj4cQ4dO098fnDQGBPwzxUzHCzODQuwM+MdNJwoct7YybLW0iTMXDX/Yd4/ZhAYjTba4+/AmfvfOzc7d0bum7F+/9wzs30EO1C22rOGU0rL5/Odz19bbU1uD9fe5dq+hHF/Y/hVHjlbfP+yYdQGttUettXSNO4X5DQmUW5bBe9f//tz9SuFnnzVc9RBE0IIIRIMB9Erlh7dT7DE4aJXnEIIIYQQcYaeoAkhhBCJiF5x1msSvoO2Z88evPjii3j11Vfx4Ycf4ssvv0RKSgrOOOMMDBs2DMOGDUOgGr+poKAAkydPxpo1a3Dw4EG0bdsWv/71rzFy5EgksR90JDiOx3MwcnssuGVUe5LaxA6bKcVw7hSt35arxrleXIsyxE4TOVRcW5QdNxC2HCfb9vF4W+1MdnR4e43l+ztmRi4W5yDZnDR2iNh5ouVzbUbDKWNHLInbZ8kVs9QWdcnhCZR6tzccoPG8PlbeeDw7Z5brJ8DnT6Q5dBYMZ9M43pYcOT6dbM6ZxSkzcgQttVWtuWc8Pztf7LhS+7iWJd+/jFwz3j7KBTMcNs5h5PuJLReSHVp2ymzniy23jYbN2sv+uZKGM3w4fwe50XvFqY5ebEj4Dtpzzz2Hm266Cc2bN0evXr3QsmVL7Ny5Ey+88AJuuOEGLFq0CM8995znAn755Zdx1VVXIS0tDQMHDkRubi5eeeUVjB07FqtXr8Zzzz0Xwy0SQgghRKKT8B20du3aYcGCBfjZz37meVI2ZcoUdO3aFc8//zxeeOEFXHXVVQCA/fv3Y/jw4UhKSsKKFSvQpUsXAMCkSZPQu3dvzJ8/H/PmzcOgQYNisj1CCCHEYRHZg2ARZyT8RwK9e/dG//79jdeYxx9/PG688UYAwIoVK6p+nz9/Pnbt2oVBgwZVdc4AIC0tDZMnTwYAPProo3XfcCGEEOJIcd3o/dE7zpiQ8E/Q/EhOPpQ9E/yRz7Bs2TIAQN++fY3pe/TogYyMDBQUFKC0tBSp5FFFhuv1Dmy1MmubA8a1+yxOFuf2OOxsWRwUwxEhXHa6uPYc1W5kh8VYvuHIWP7pGGltPXZk2KkzcqvIMYvUCWIHjnO9+HgQTpnFwSFstSfNFVhy0rjWKs0eKPUe74p0i5PGq7e4NezQGbUoI90fPLtxvPy31zyeND7on3PHOYXG/uXxNkfNdv5bcv0MePvYwSyn652dWT4+7JwFLM6VpfYmO18OHyF26NgR4/sVYdyfbI4Yt6+CnT26/wWP7FmKanHWb47ZDlooFMIzzzwDwNsZ27hxI4BDr0aZYDCIVq1a4eOPP8aWLVtw2mmn+a6jc+fO1f6+YcMGBJF2pE0XQgghRIJzzHbQJkyYgI8++gj9+vXDpZdeWvV7YWEhACA7O7va+Sp/37dvX523UQghhDgiXNiffEayLHHUOSY7aDNnzsS0adNw6qmn4tlnn62z9axbt67a3zt37ozN67fW2XqFEEIIdazqN8dcB23WrFkYPXo0OnTogKVLlyI3N9czvvIJWeWTNKby95ycnDptJzsIZu1MchbYybLknBnXLZeSM5w2diC4tic5MXxm8fJClOOWTLU9OdeLHRZ2SmyOno0Uby08wyFhJ8/muPH+cGl5nGNm1MIk583mKFpqERoYTiGND3B7yImx1B40l+cd5O0NlLBzRLUKSy3OFJ8PnDtmOGU2x83fsTO23+YU2rDVzmRstS9tDhrntnEuWTJdD5acMz5efLby/cmW+2WczyztGferCD9X5PtreWkNE36/er4eeX9anD1rziW331astXL7o/WETMQlCf8V54+ZMWMGRo4ciY4dO2L58uU4/vjjjWnat28PANi0aZMxLhQKYevWrQgGg2jdunWdt1cIIYQ4EiprcUbjj4gNx0wH7YEHHsDYsWNx1llnYfny5WjatGm10/Xu3RsAsHjxYmPcqlWrUFxcjO7du9fyC04hhBCiDnHdQ08io/FHfbSYcEx00CZNmoQJEyagc+fOWLp0KZo0aVLjtPn5+WjSpAnmzZuHtWvXVv1eUlKCO++8EwBw00031XmbhRBCCHHskvAO2ty5c3H33XcjKSkJF1xwAWbOnGlMk5eXh6FDhwIAGjZsiDlz5iA/Px89e/bEoEGDkJubiwULFmDjxo3Iz8/HwIEDo9Ayx+ttkHMRJieCnTQrltqaBpbH2EbtT3Zw2FkJWZwhdto498jmYDC2x/CWXDbD2WFnhLfX5rzZcqR4mGtL2nK7DIfH34kxan1aay3S4kJeB9DlXD129Dhni53CZG97ksq4lqWltqHhXJHzZ6sVa9t+doKstXItuYCEkWtnOT5GzhmfH7y/bU6cpX2G82lM4O+EuYazapnfMt4lB9FhZ5TXF+D9Qw7dwRLvMDu9ttq+xv6m9hrXIzu1/rVPXXbw6P7oVDq7trjCKD35ivBuLKJEwnfQtm499LVkRUUFZsyYUe00F154YVUHDQAGDBiAlStX4v7778fzzz+PkpIStGnTBtOnT8eoUaOsoZ9CCCFETIlmzIbeccaEhO+gTZw4ERMnTox4vvPOOw+vvfZa9BskhBBCHA0k+NdrjgkHTQghhBCiPpHwT9DiFtf1eAgO5z6leb8SZUfCLWenhBwcrg3H/5JiJ82WC8W5QTwBOStu2N95c9Kp1JXhVLHjRjlphMvOm5FjZqmlx46JzSHj19y0fm4P50q5ad7tcWy5V7y+CGt5ms5ShDlyXPsx0tw5Pj/ZsbHkaBnODztltP+cYnKMMtO90/P1wfvfev2Qg1fKtWUtjpXl+FmdMyOHLMLjwdeHkZtmcVh5mJwu4/gY5y/vf39n1Um1Xf8WZ87mNNpqs5LTyLWJwwcPeldHX/kb9yfev1x7mJ01vj2Wf+8E+z0hc2HmER4pehAXE9RBE0IIIRIOZZjVd/SKUwghhBB1Tl5eHhzHqfZPdcHxAFBQUIB+/fohNzcX6enp6NSpE2bMmIEKWzWTBEBP0IQQQohEJA6foGVnZ2PMmDHG71lZWcZvL7/8Mq666iqkpaVh4MCByM3NxSuvvIKxY8di9erVeO65545Ci2OHOmhxSriEctDIeTCGbbk9tmgQo3YcOW/kYATIIYv4NsA5Vey0sHPGOWlGrUd26iy1KW25cLYcMovzZuxtzlkqoVy52tZyZIJcO5Nymmy5aLZcLnLCuHaomavmvz+dckuum63WJOe+ZWX4r5+dNoadO84tsx0fdsi4lio7ebbambx/edjIzbI4bJGeX3y9MrZatoZj5p8zyPvXSYosx83qANpyH43cQ//7p5PivV9x7U3ONYs415Kvl8r5y33aFdWYjeiRk5NzWMkK+/fvx/Dhw5GUlIQVK1agS5cuAA4Fz/fu3Rvz58/HvHnzMGjQoDpucezQK04hhBBCxBXz58/Hrl27MGjQoKrOGQCkpaVh8uTJAIBHH300Vs07KugJmhBCCJGIRPErzs2bN6Nz587Vjl63bt1hL6q0tBR//etf8fnnnyMzMxOdOnVCjx49kERPFZctWwYA6Nu3r7GMHj16ICMjAwUFBSgtLU3Y2tjqoAkhhBAJhuNG8yvO6L0q/frrrzF48GDPb61atcJTTz2FCy+8sOq3jRs3AgDatWtnLCMYDKJVq1b4+OOPsWXLFpx22mlRa188oQ5avEC5QE5yDc5BJWFL7TeLY2PkpFFOl2E2BL2/hEv9a4U6XPvS4nCYuVTUfnZCOEfN5pxZahEate84l4sdJ1stTHbOaH9wrUPDIYzUKTTWz84dnV82p6ictjfJf5gxanHact7YeWNsOWWMzVHi89VSG9Fw0qzLt+Ss2Wq7Gg6fzcnzv975fHV4fxvXZ4S1W43rla+PCB1Qw4Hl1fs7jnw/Mu5XFifXyH1k5zJscRj5/uFyrpnFSbPcv4z7VU1E0UFr27ZtRE/KqmPYsGG44IILcPrpp6NBgwbYsmULZs2ahccffxyXXXYZ3nrrLZx55pkAgMLCQgCHPiqojsrf9+3bV6s2xTPqoAkhhBCizrnnnns8wx07dsRjjz2GrKwsTJs2DRMnTsSLL74Yo9bFH/pIQAghhEhEXDc6f+qYG2+8EQCwatWqqt8qn5BVPkljKn/Pycmp28bFEHXQhBBCiETDdQ+9Go/Gnzruox133HEAgKKioqrf2rdvDwDYtGmTMX0oFMLWrVsRDAbRunXrum1cDNErzljhkHdg5CT5O1Jce86o/WbrepNzZnV2IkxtNnKMbLFExd5adk4G1U7k/cO1/2xwbUCjAZwbRc5VmddhMbA4dHx/Mxw9ozn+tRcNh8hwWCx3VJvD4lhqQ7LDE2kuFTtXRq4ZLZ+3l3Om2Nm0tNeFJXfM2D6Lc2h1AiO8vqw5Yrw6y/rYYSqj8bacROvx5Zw4qkVry22zwfdD3j+2Wpt8vfH+IMfMrM1r2T+8PTbHle43bijC2q0Jxpo1awDA09nq3bs3/u///g+LFy/Gr371K8/0q1atQnFxMXr06JGwX3ACeoImhBBCJCZRe8VZ+0doGzZs8Dwhq2Tbtm0YMWIEAODaa6+t+j0/Px9NmjTBvHnzsHbt2qrfS0pKcOeddwIAbrrpplq3K57REzQhhBAi0ThK/tjh8ve//x3Tpk1Djx49cPLJJ6NBgwb47LPP8Oqrr6KkpAT9+vXDuHHjqqZv2LAh5syZg/z8fPTs2RODBg1Cbm4uFixYgI0bNyI/Px8DBw6M4RbVPeqgCSGEEKJO6dWrFzZu3Ij169dj9erVKCoqQk5ODs4//3wMHjwYgwcPNuJPBgwYgJUrV+L+++/H888/j5KSErRp0wbTp0/HqFGjrHEp9R110GKF68It/yHcx+Hak47FqaDab+xgGDk+ZWW+w0YODw9zLThukMWhMWrbEUZOWCm1jy/ESHOUuLYp7z8D/1qBVizHz3CG2FGxOEdG7UNb+2zOFDteEdZuNRwthpdPOWzs3BnHJ0j7kx1Hrm3KzhPngPF4do5stSttzlmEyzOdTdv+pFs35eoZ55/t7zF2MG05eTw75/7x8ePl8/y22rbsEPL9jM+/NHJyeflGDhnnHNL9gxy1AF1/4XJyVG05a0Hv/OwUG/dvbr9b2T7LE7I4eoJ24YUXeoJoD5fzzjsPr732Wh20KP5RB00IIYRINFzAifRjDJ9liaOPOmhCCCFEwhFfDpqIHH3FKYQQQggRZ+gJWqxwHK93FmEOmkO18rg2HDsshmPGTkfIf34DS46a4bhZcr+M2nUszdge1VscF5vTYZNNbQ6d4USx4+RacsPYGbLUmnRL2XkhB9FW25KXRzlxDueS2XLMIpV1bbVbGZsTFeH2GrlrHNQXYa1Pw6EzcrQs+6vc38kzHUXKAeT9yU4VO2oML9/IGfM/f52kFN/xxvVjc/QYPj94e225jpYcsnAZbw8tn7Y/zOdjwP/84/mN/WFxVmtcfkWErugRoydxsUAdNCGEECLRcBG9Dpr6ZzFBrziFEEIIIeIMPUETQgghEg438pJaIq5QB62ewA6D4WyxU2apHcjOjzG/ZXrDMbFNzwQ4d4gcHmN7yBGhxRnrj9CJsjpmnDNn2V/WHDRbzhvnnBFGbhznanHtziT/HC8jR8xWu9SoFUo5TXz8S3n53u2raJbjGU76eq93ej4+vHx2yizTGw6iZXlGDpUNdqwirGVpOJV8PlleXRnnIztMYa7VSevjXEauLUu5YIaTRjloPGzLPWOM7Ym01qnh0HkHHXYwDUeXHUPL/cU4Xv7zG7U6GTpeVf6yn7oXzVecIiboFacQQgghRJyhJ2hCCCFEIqKvOOs16qAJIYQQiYbr2uNLDntZ0VmMiAx10GKG48kqMhwLY3KLA8XOGTsS5Di4Ro4POUlGbUz/WpZGzlptMXLRKMfM5pzZHJEKmp9q94EcG+P4cE4SOzyW/R8x7ADx8SZnzchhY4xaoLQ8doxs8/Px5+XxeMrlMpwzw6kjZ4zbw8snx41z+Qwsf5EZjhpNz7llxvXF5we3l8ezo8VOU6QOKjtnlvPbAe0vo3YlXY/eqc3rxbb/LTlp9uPHzp1/7U7jfkpSmuv41+YMpFKtT1stWsLqnNkX8P1/a7cYEd+ogyaEEEIkIvpIoF6jDpoQQgiRcLj2NzMirlEHTQghhEg0XEQvB00dvZigDlqscF1PPTfOxTEcMHIczFwgdk5sDpL/9LacIiOXjB0d2wXNzg8tL1xmyVVjR8VwXtjhYUeN5i+h2pYWx8pwWowcNHJ8aH8G0tO80xu1Fi0OEh8/zqWzTc8Ona1Woi2HyuJk2WqPOrA4f+wE8fjig95h43y05IpFGDhkr5XJ148lF40dJsPpo+WTQ2bUhiSM64dzv9g5NPY3jefjbcuJMxw2S61Srm1quX65lirfL9kZszpu7JDacg1Dllqnxvns+I63lBb+oT0RlsAV9Qt10IQQQoiEwz2Mnp6IZ9RBE0IIIRINVRKo96iSgBBCCCFEnKEnaLHC8WYJGbUgjVqaFseMnSKLE2bU0jMehfvnmpm16iininLSDMo5h42cJHZ82DlhDCfI5vRYHCnK0TKmt+WAEYGMDJrf0j5jASyb0PTsIPHyLLU9Dej4GDlZfDx42KiNyceTzkebI2aD94/NAePpbbUteXk258qWQ8fw+edS+4zcNM4JtOQe8vVpuX5ttS2N5VkcVT7fXVYSefmW42Grtcu1Ndn54vZzLpnj8PnunZ+dPyMH0uKAGvvH4qQdMVH7SCA6ixGRoQ6aEEIIkWi40XTQ1EOLBXrFKYQQQggRZ+gJmhBCCJGIROsVp4gJ6qDFCheex8/WWpacS0S5O07Q6xiFi4q845PJCTNqRfo/TDWcFXaSuP0Wh8UKO2AWbDljRq08iwNnLJ+dE3a6LE6bLTfOyJmyTm+58bIjZKlNaiyN1sfOmbU2YiDKtVmpFizneBm5Z+xU8f7i42PLqWJ4fQdLfJdnOKF8/iT7t8/4i5aPD9eG/O6Ad7ylVq2Zu0j7x+KcMcZ43n6Gz3dbbiGfD+zgWpZf644LO2UhrgVqOf/5/OD7s7F8i/NY7SpUSaC+ow6aEEIIkYjwPxyPFHX0YoIcNCGEEEKIOENP0IQQQohEw3X15Kueow5azHA9nofDygLXKjRynMhZ4Bwfchp4fsNNsDlK5HAZOUP8KJ0dMnZALM6azbkyHBV25DgXjKdnZ8XITaL9nWypVWnLUbM5ebz/bA4UY8tVMtbHOW7+22PkNlkdG8urFXaS2Cmy5aBxjh/D2xdp7pwNdoLIAXPCluPB7ePzl51J0PXnevdPmBw4I5eMr/dyi2Pm+Dtq1tw4dhRtx5OOj7E+rs3J9wdb7WDOPTPuN/7Oq7F/bM6YpfYsXz9Ge2z340oHOdKax0eK+nkxQa84hRBCCCHiDD1BE0IIIRKNqH7FqUdosUAdNCGEECIRUQ5avUYdtJjheLwEW86NW+F1FgKUo+TaFA/+l5TN0SGstTWZsMXJYGeOt8dwZsgp4/ZYnDZeXoBzo4zapLy/LLU+2Tnj9iZbto8hxy1cXOwZ5twra06a7XiHaNiWW8XzG8fL4ogdjMxJjBh26mj7rLl27DAyPL2Ru2Zxf9iRYoeMcvxMJzAyt4idMD5fDKeT28f7g3PUDCfUUvuUnSu+HslJNHIO02j/cE6k5fyz5k4aM7AjGOH5yU6idfmWySvbH47QVY0x27dvx913343Fixdjz549aN68OQYMGIB77rkHjRo1inXz4g510IQQQohEI6q1OGvPZ599hu7du+Obb77BFVdcgVNPPRXvvPMO/vjHP2Lx4sVYvXo1GjduHOtmxhXqoAkhhBAJiBulV5zRcNl++9vf4ptvvsHMmTMxcuTIqt9vvvlmPPzww7jjjjvw2GOP1Xo9iYS+4hRCCCESjconaNH4U0s+++wzLFmyBHl5efjd737nGXfvvfciMzMTzz77LIqoROGxjp6gxQmGQ8SOFjkcRi4PO0M2J4u75uw88PzsXHEOmKWWpTVHyeZ0cC0+dn4stfsCNqeK4e3n5dscNcv+MLDtD4szY3NijFyqgCVnL9Laf0ZuHOfK2fYfDfP87BTx9cCOlOV4GNvL2NZv5GpRThcv38g986/VaWyPDdqf1tqNtvPFqL1pqVXLTpxR69eSm2Zcz3S8KHeM12fNEYvQiTMbyA5nhA6azdGzOWrRrm17BGzevBmdO3eudty6det8512+fDkA4JJLLkGArsUGDRrgvPPOw5IlS7BmzRr06dMnOg1OAPQETQghhEggyvdXoBDfIhwO/VBR4Aj/lIVLUIT9CEb6j9wfsXHjRgBAu3btqh3ftm1bAMCmTZuOeB2JiJ6gCSGEEAnErL/MxPXXX48v8BlORvWdosNlC/6DCoTw8ssvo3fv3ke0jMLCQgBAdnZ2teMrf9+3b98RLT9R0RM0IYQQIoG47rrrkIVsbMUGlLtl9hlqoNj9Dl9iCxrj+CPunIkjR0/QYoit3hpN7Bk0nCN2JNhhsYiehsPBjkSSJQfIUnvOcFhsOUSWHDMjd8mSQ2Y4WAzPz7X/jFwoWp4tB42dqEgdtwjh2qJG7hfXZrXlatlq+tkcL+v20vlTTk4Vn18hy/4xal+Ss8TTR5grhjKLA2m8DqLzmWuP2nL1InUcI61dSRjXF8PHm0Yb16tRC9jiqNkcMVttTx7P979IY/bYAePlWZwy4/5hcwSN85dr4fr/1Z2UlITnFs3DZZddhq3YgHY40399NfApPoILFys/+ucRzV9J5ROyyidpTOXvOTk5tVpPoqEnaEIIIUSCcemllyIXTfEFPsNBN/KvI/e5u/ENvsQNN9yA008/vVZtad++PYCaHbPNmzcDqNlRO1ZRB00IIYRIMBzHwT/fWwwXYXyKjyKa13VdbMYHCCAJ9957b63b0qtXLwDAkiVLEKanu9999x1Wr16NjIwM/PSnP631uhIJddCEEEKIBOTss8/G4MGDsRNfYL/77WHPtwtfoRDf4o67bscJJ5xQ63accsopuOSSS7Bt2zbMnj3bM+6ee+5BUVERBg8ejMzMzFqvK5Fw3OiVuxeHSefOnbH5vS04N3BxzRPxYWEHgh0Hdl4sDphx2NlBq8Un1QBMR8bm0NhqMVpy2Qznip0iw2Hxz00z2ss5U7y/bLlx7BRFWMvPcIh4fm6/pRao9XhYzgebY2TAjk6kjiFh1hr1dwaN3DTOLTPOB//pGavTV861PynXy5arZ8FwmmwJ8pZamlZHLdLar0ZuHdUGZUfL0n5rLU2LI+aGyn3HG84X7R+jvTYnmLHcz61O6vfzv12xBAB8O1+ff/45Wp3cCg2Ri8640Hpthd0w1mAJQijH7v270KBBA9/pDxcu9XTaaafh7bffxvLly9GuXTsUFBSo1BOhJ2hCCCFEgtKyZUvcOv5W7MNu7MYO6/RfYguKcQB/fHRG1DpnwKGnaGvXrsXQoUPx9ttvY9q0afjss88wevRorFmzRp2zatATtBigJ2jVjNcTNF/0BM2LnqB50RM0Qk/QPBQWFuK4nKZIQSrOxcUI1PAVbMgtx2osQjJSUVj+ba3CaUXt0RM0IYQQIoHJzs7GQzMeRBG+w1fYVuN027AR5SjD//fSs+qcxQF6glYD27dvx913343Fixdjz549aN68OQYMGIB77rkHjRo1qtWyq56gORf98KPlX0xGLTr+FyBj+xehpbZbRBltMP8FGUhN9Z/B8sTKeKJiqVXIT9CsT+Qs62OMJwy26fnmFukTo0j3j23+2uas2Z4QRoolN81WW9N4AmWpzRrxEw/bExrb9lueiNmOn/mEMrLcPJdrh0b4RMn6hMo4HyxPmC33E2P6YLLveOv9zFbb0nY9RHq9RDnH0FieMf7Q8TvcJ2gAUFZWhpzUXFQghO64DEHHe48qcYtRgMVoiFx8G/7GnoUn6hw9QauGzz77DJ07d8ZTTz2Frl27YuzYsWjdujX++Mc/olu3btizZ0+smyiEEEIcNikpKZj7j6dQhlL8FxuN8Z/hY4QRxutvv6rOWZygDlo1/Pa3v8U333yDmTNn4qWXXsIf/vAHLFu2DGPHjsXGjRtxxx13xLqJQgghRETk5+cjG7n4HJtQ6h6s+v07dx924L8YOHAgunbtGsMWih+jDhrx2WefYcmSJcjLy8Pvfvc7z7h7770XmZmZePbZZ1FUFHkysxBCCBErHMfBwn+9jApUYAv+U/X7p/gQDhxMmTIlhq0TjCxAYvny5QCASy65BAHyZBo0aIDzzjsPS5YswZo1a9CnT5+6awg7KZav/uzOiL/DZpvf+hWf/9rttQMNJ4naw18lGl/ZkcMSofNje6TPzpPh/NBXaTZHznCiSry1GY3W8P6xfHVnPR62VxgRfmVqLM/ylanpFFJtU16epZahbXlhy/RWxy5Sp8h2Ptm+SrYdH8tXxUYtS1iub5ujx1+FO/77I5BCDhk7grQ+83ynX0L81THNb/tql9dvO56ROmdMpE5cpOtH5f6I3HU7//zzMWDAALz00ks4yW2LUhzEHuzEmDFj0Lp164iXJ+oOddCIjRsPvZuvqSZY27ZtsWTJEmzatMnaQevcuXO1v2/YsAFBWCR6IYQQog74wx/+gJdfehmb8QFKcRBBJOPOO++MdbMEoVecRGFhIYBDnyVXR+Xv+/btO1pNEkIIIaJG+/btcdNvb8IefI0DKMSUB+9XUGwcoidodci6deuq/T03NxeFB/fjbfefP/xofVLNj9T5M37bZ9k8e4TzhyJ75WJMH/FHQVH+bL2WOKX0yoQnMNpn2R/G9nGwaYT7j1df24+wars8y/xOCQcn1y62w6EVWNODyvgHy/VVW2z707a6SI9/pNjOX26A7XDx+Wu7P1jH8wot7TEvULONtaG29+sorb8I3yFwhM9Z7rnnHjz+pzlIRgpGjhwZxcaJaKEOGlH5hKzySRpT+XtOTs4Rr6Nhw4YAgJKSEgDAaaeddsTLOpbZsGEDAO2/I0X778jRvqsd2n+1o3L/Zac1rPr7JFKaNm2Kctf4l4qII9RBI9q3bw8A2LRpU7XjN2/eDKBmR+1w2LZtG4AfHLWanrQJf7T/aof235GjfVc7tP9qh/bfsYEcNKJXr14AgCVLliBMX1Z99913WL16NTIyMvDTn/40Fs0TQgghxDGAOmjEKaecgksuuQTbtm3D7NmzPePuueceFBUVYfDgwcjMzIxRC4UQQgiR6OgVZzX86U9/Qvfu3TFq1CgsXboUp512Gt5++20sX74c7dq1w/333x/rJgohhBAigdETtGo45ZRTsHbtWgwdOhRvv/02pk2bhs8++wyjR4/GmjVr9DmyEEIIIeoUPUGrgZNOOglPPfVUrJshhBBCiGMQx7UGBgkhhBBCiKOJXnEKIYQQQsQZ6qAJIYQQQsQZ6qAJIYQQQsQZ6qAJIYQQQsQZ6qAJIYQQQsQZ6qAJIYQQQsQZ6qAJIYQQQsQZ6qAJIYQQQsQZ6qDFgO3bt+PXv/41TjjhBKSmpiIvLw9jxozB3r17Y920mLNnzx488cQTuPLKK9GmTRukp6cjOzsb559/Pv7yl78gHA5XO19BQQH69euH3NxcpKeno1OnTpgxYwYqKiqO8hbEJ3/961/hOA4cx8ETTzxR7TQLFy5Ez549kZ2djaysLJx77rmYO3fuUW5p/LB06VJceeWVOP7445GamooTTjgBl156KV577TVjWp1/Xl599VVccsklaNGiBdLT09G6dWv88pe/xFtvvVXt9Mfa/ps/fz5GjhyJCy64AA0bNoTjOLj22mt95zmSfaRrup7jiqPKp59+6jZt2tQF4F5xxRXu+PHj3V69erkA3Pbt27u7d++OdRNjyqOPPuoCcJs3b+7+z//8jzthwgR32LBhbnZ2tgvAveqqq9xwOOyZ56WXXnKTkpLczMxM99e//rU7btw4t3379i4ANz8/P0ZbEj98/vnnbnZ2tpuVleUCcOfMmWNM88gjj7gA3MaNG7u//e1v3TFjxrgtWrRwAbi33HJLDFodW2699VYXgNuiRQt3+PDh7m233ebecMMN7tlnn+3eeuutnml1/nn5/e9/X3UuXX/99e748ePdq666yk1OTnYdx3GfffZZz/TH4v4788wzXQBuVlaWe+qpp7oA3GuuuabG6Y9kH+marv+og3aUueSSS1wA7syZMz2/jx071gXg/uY3v4lRy+KDpUuXugsWLHArKio8v+/YscM96aSTXADu/Pnzq34vLCx0jzvuODclJcV99913q34/ePCg261bNxeA+7e//e2otT/eCIfDbp8+fdzWrVu748aNq7aDtnXrVjc1NdXNzc11t27dWvX7t99+655yyikuALegoOAotzx2PP744y4A97rrrnNLS0uN8WVlZVX/r/PPy44dO9xAIOA2a9bM3blzp2fcsmXLXABuq1atqn47VvffsmXL3E2bNrnhcNhdvny5bwftSPaRrunEQB20o8inn37qAnDz8vKMDsj+/fvdzMxMNyMjwz1w4ECMWhjf3H///S4Ad8SIEVW//eUvf3EBuEOGDDGmX7p0qQvA7dGjx9FsZlwxY8YM13Ecd+XKle4999xTbQftrrvucgG4d999tzG/3/5NREpKStzjjjvObdmyZbWdM0bnn5c1a9a4ANyf//zn1Y5v0KCBm5WVVTWs/edaO2hHso90TScGctCOIsuXLwcAXHLJJQgEvLu+QYMGOO+881BcXIw1a9bEonlxT3JyMgAgGAxW/bZs2TIAQN++fY3pe/TogYyMDBQUFKC0tPToNDKO2LBhAyZMmIDRo0ejR48eNU7ntw8vu+wyzzSJzhtvvIFdu3bhF7/4BQKBAF599VU88MAD+OMf/1itP6Xzz0vbtm2RkpKCd955B7t37/aMW7VqFb777jtcdNFFVb9p/9k5kn2kazoxUAftKLJx40YAQLt27aod37ZtWwDApk2bjlqb6guhUAjPPPMMAO9Nx2+fBoNBtGrVCqFQCFu2bDk6DY0TQqEQBg8ejJYtW2LKlCm+0/rtw+bNmyMzMxPbt29HcXFxnbQ1nnj33XcBAGlpaTj77LNx+eWXY8KECRgzZgy6d++OCy+8ELt27aqaXuefl9zcXDzwwAPYuXMnOnTogP/93//FbbfdhquvvhqXXHIJLr74Yvz5z3+uml77z86R7CNd04mBOmhHkcLCQgBAdnZ2teMrf9+3b9/RalK9YcKECfjoo4/Qr18/XHrppVW/a59Wz3333Yf169fj6aefRnp6uu+0h7sPK6dLZL755hsAwEMPPQTHcfCvf/0L3333HT744ANccsklWLVqFX75y19WTa/zz2TMmDF44YUXEAqFMGfOHPzhD3/Ac889h5NOOglDhw5F06ZNq6bV/rNzJPtI13RioA6aiHtmzpyJadOm4dRTT8Wzzz4b6+bEPW+//TamTJmCW265Bd26dYt1c+oVlTEuwWAQCxYswPnnn4+srCycccYZePHFF9GiRQusXLmyxrgIATz44IPIz8/H0KFD8dlnn6GoqAjr1q1D69atcc011+D3v/99rJsoRL1AHbSjiO1fLZW/5+TkHK0mxT2zZs3C6NGj0aFDByxfvhy5ubme8dqnXkKhEIYMGYJ27dph0qRJhzXP4e7Dmv41nkhUnidnn3028vLyPOMyMjKqnt6+8847AHT+MStWrMD48ePx85//HNOnT0fr1q2RkZGBc845By+++CJOPPFETJs2rep1nPafnSPZR7qmEwN10I4i7du3B1CzY7Z582YANTtqxxozZszAyJEj0bFjRyxfvhzHH3+8MY3fPg2FQti6dSuCwSBat25d5+2NBw4cOIBNmzZhw4YNSEtLqwqndRwH9957LwBg+PDhcBwHY8aMAeC/D3fs2IGioiK0aNECGRkZR207YkXlvqipQ9CoUSMAwMGDBz3T6/w7xMKFCwEAvXr1MsZlZGSga9euCIfDWL9+PQDtv8PhSPaRrunEQB20o0jlTWvJkiVGIv53332H1atXIyMjAz/96U9j0by44oEHHsDYsWNx1llnYfny5R5v5cf07t0bALB48WJj3KpVq1BcXIzu3bsjNTW1TtsbL6SmpuL666+v9s/ZZ58NADj//PNx/fXXV73+9NuHixYt8kyT6PTp0weO4+A///lPtVUrPvroIwBAq1atAOj8Yyq/JPzxhxQ/pvL3lJQUANp/h8OR7CNd0wlCrHM+jjUUVGvnvvvucwG4nTt3dvfs2eM7bWFhodukSZNjLujySKgpB23Lli0KtfwRP//5z10A7vTp0z2/v/76667jOG5OTo67b98+13V1/jF///vfXQBus2bN3O3bt3vGvfbaa67jOG5aWlpVxRTtP3sO2pHsI13TiYE6aEcZLvU0YcKEqlJP7dq1O+ZLPT399NMuADcpKckdM2aMe8899xh/nnrqKc88L774YlUZlOuvv9699dZbPWVQuDTUsUpNHTTXdd2ZM2eqLMz3fPHFF1VVK/r06eOOGzfOveqqq9ykpCQ3GAx6Klm4rs6/H1NRUeFedNFFLgC3QYMG7pAhQ9zf//73bv/+/V3HcVwA7owZMzzzHIv778UXX3Svu+4697rrrnMvvfRSF4DbunXrqt/4mjuSfaRruv6jDloM+Pzzz92hQ4e6xx9/vJucnOy2bNnSHT16tPvtt9/Gumkxp7IT4ffnwgsvNOZ788033csuu8zNyclx09LS3I4dO7rTp093Q6HQ0d+IOMWvg+a6rrtgwQK3R48eblZWlpuRkeF26dLFffrpp49yK+ODb775xh0xYoTbsmVLNzk52W3cuLE7YMAA9+233652ep1/P1BWVuY+/PDD7rnnnus2aNDATUpKco877jj3Zz/7mfv6669XO8+xtv9s97mTTz7ZmOdI9pGu6fqN47quWyfvToUQQgghxBGhjwSEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEEIIIeIMddCEEHHBgAED4DgOZs6caYy766674DgOrv//27VDlVjiMIzD74KKeBVqErbMCiJoMClG2SIG0wlWgwhG8Q5s3oAgBrEKtkXBBVcwbtOiRdiwQRD3tAPnAtz5g8/Thilv/PHN/PlTwzKA8WuMRqNR3SMAPj4+0mq18v7+nvv7+7RarSTJ7e1tNjY2srCwkG63m5mZmZqXAvw8gQYU4+7uLmtra5mbm8vj42OGw2GqqspgMEi3202z2ax7IsBY+MQJFGNlZSUnJyfp9/vZ29vL7u5u3t7ecnp6Ks6AX8UFDSjKaDTK5uZmbm5ukiQ7Ozs5Pz+veRXAeLmgAUVpNBppt9v/nvf39+sbA1ATFzSgKP1+P4uLi5mcnMxgMEiz2czDw0Omp6frngYwNi5oQDE+Pz+zvb2d4XCYi4uLHB0d5fn52RUN+HUEGlCMg4OD9Hq9HB4eZn19PcfHx1ldXc3Z2VkuLy/rngcwNj5xAkW4urpKu93O8vJyOp1OJiYmkiSvr6+pqipfX1/p9XqZn5+veSnAzxNoQO1eXl5SVVW+v7/z9PSU2dnZ/95fX19na2srS0tL6XQ6mZqaqmcowJgINACAwvgHDQCgMAINAKAwAg0AoDACDQCgMAINAKAwAg0AoDACDQCgMAINAKAwAg0AoDACDQCgMAINAKAwAg0AoDACDQCgMAINAKAwAg0AoDACDQCgMH8B4/w2oyTrMlQAAAAASUVORK5CYII=&quot;  style=&quot;max-width: 100%; max-height: 100%; object-fit: contain; width: 616px; height: 522px;&quot;&gt;&lt;/img&gt;\"}},{\"type\":\"object\",\"name\":\"Spacer\",\"id\":\"p1012\",\"attributes\":{\"name\":\"HSpacer00912\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHN0eWxlPSJtYXJnaW46IGF1dG87IGJhY2tncm91bmQ6IG5vbmU7IGRpc3BsYXk6IGJsb2NrOyBzaGFwZS1yZW5kZXJpbmc6IGF1dG87IiB2aWV3Qm94PSIwIDAgMTAwIDEwMCIgcHJlc2VydmVBc3BlY3RSYXRpbz0ieE1pZFlNaWQiPiAgPGNpcmNsZSBjeD0iNTAiIGN5PSI1MCIgZmlsbD0ibm9uZSIgc3Ryb2tlPSIjYzNjM2MzIiBzdHJva2Utd2lkdGg9IjEwIiByPSIzNSIgc3Ryb2tlLWRhc2hhcnJheT0iMTY0LjkzMzYxNDMxMzQ2NDE1IDU2Ljk3Nzg3MTQzNzgyMTM4Ij4gICAgPGFuaW1hdGVUcmFuc2Zvcm0gYXR0cmlidXRlTmFtZT0idHJhbnNmb3JtIiB0eXBlPSJyb3RhdGUiIHJlcGVhdENvdW50PSJpbmRlZmluaXRlIiBkdXI9IjFzIiB2YWx1ZXM9IjAgNTAgNTA7MzYwIDUwIDUwIiBrZXlUaW1lcz0iMDsxIj48L2FuaW1hdGVUcmFuc2Zvcm0+ICA8L2NpcmNsZT48L3N2Zz4=\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"p1007\"},{\"id\":\"p1005\"},{\"id\":\"p1006\"}],\"margin\":0,\"sizing_mode\":\"stretch_width\",\"align\":\"start\"}},{\"type\":\"object\",\"name\":\"panel.models.layout.Column\",\"id\":\"p1013\",\"attributes\":{\"name\":\"WidgetBox00899\",\"css_classes\":[\"panel-widget-box\"],\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"p1007\"},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"p1022\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.3.8/dist/css/widgetbox.css\"}},{\"id\":\"p1020\"},{\"id\":\"p1005\"},{\"id\":\"p1006\"}],\"margin\":0,\"align\":[\"end\",\"center\"],\"children\":[{\"type\":\"object\",\"name\":\"panel.models.layout.Column\",\"id\":\"p1014\",\"attributes\":{\"name\":\"Column00908\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"p1007\"},{\"id\":\"p1020\"},{\"id\":\"p1005\"},{\"id\":\"p1006\"}],\"width\":290,\"min_width\":290,\"margin\":0,\"align\":\"start\",\"children\":[{\"type\":\"object\",\"name\":\"Div\",\"id\":\"p1016\",\"attributes\":{\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"p1007\"},{\"id\":\"p1005\"},{\"id\":\"p1006\"}],\"width\":250,\"min_width\":250,\"margin\":[20,0,0,20],\"align\":\"start\",\"text\":\"time: <b>0</b>\"}},{\"type\":\"object\",\"name\":\"Slider\",\"id\":\"p1018\",\"attributes\":{\"js_property_callbacks\":{\"type\":\"map\",\"entries\":[[\"change:value\",[{\"type\":\"object\",\"name\":\"CustomJS\",\"id\":\"p1026\",\"attributes\":{\"tags\":[[5308446368,[null,\"value\"],[null,null]]],\"args\":{\"type\":\"map\",\"entries\":[[\"bidirectional\",false],[\"properties\",{\"type\":\"map\"}],[\"source\",{\"id\":\"p1018\"}],[\"target\",{\"id\":\"p1016\"}]]},\"code\":\"try { \\n    var labels = ['time: <b>0</b>', 'time: <b>1</b>', 'time: <b>2</b>', 'time: <b>3</b>', 'time: <b>4</b>', 'time: <b>5</b>', 'time: <b>6</b>', 'time: <b>7</b>', 'time: <b>8</b>', 'time: <b>9</b>', 'time: <b>10</b>', 'time: <b>11</b>', 'time: <b>12</b>', 'time: <b>13</b>', 'time: <b>14</b>', 'time: <b>15</b>', 'time: <b>16</b>', 'time: <b>17</b>', 'time: <b>18</b>', 'time: <b>19</b>', 'time: <b>20</b>', 'time: <b>21</b>', 'time: <b>22</b>', 'time: <b>23</b>', 'time: <b>24</b>', 'time: <b>25</b>', 'time: <b>26</b>', 'time: <b>27</b>', 'time: <b>28</b>', 'time: <b>29</b>', 'time: <b>30</b>', 'time: <b>31</b>', 'time: <b>32</b>', 'time: <b>33</b>', 'time: <b>34</b>', 'time: <b>35</b>', 'time: <b>36</b>', 'time: <b>37</b>', 'time: <b>38</b>', 'time: <b>39</b>', 'time: <b>40</b>', 'time: <b>41</b>', 'time: <b>42</b>', 'time: <b>43</b>', 'time: <b>44</b>', 'time: <b>45</b>', 'time: <b>46</b>', 'time: <b>47</b>', 'time: <b>48</b>', 'time: <b>49</b>', 'time: <b>50</b>', 'time: <b>51</b>', 'time: <b>52</b>', 'time: <b>53</b>', 'time: <b>54</b>', 'time: <b>55</b>', 'time: <b>56</b>', 'time: <b>57</b>', 'time: <b>58</b>', 'time: <b>59</b>', 'time: <b>60</b>']\\n    target.text = labels[source.value]\\n     } catch(err) { console.log(err) }\"}}]]]},\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"p1007\"},{\"id\":\"p1005\"},{\"id\":\"p1006\"}],\"width\":250,\"min_width\":250,\"margin\":[0,20,20,20],\"align\":\"start\",\"show_value\":false,\"tooltips\":false,\"start\":0,\"end\":60,\"value\":0}}]}}]}}]}},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"p1027\",\"attributes\":{\"plot_id\":\"p1004\",\"comm_id\":\"2f8c19e60474450ca56f35999f26328c\",\"client_comm_id\":\"8bf51115fb814ee9afdedb90917d4b42\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"copy_to_clipboard1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
       "  var render_items = [{\"docid\":\"3d66248f-4f7e-4c22-bd98-5fe4b5e0a67e\",\"roots\":{\"p1004\":\"f6e64cf6-3572-4390-8af2-abc4711da0a6\"},\"root_ids\":[\"p1004\"]}];\n",
       "  var docs = Object.values(docs_json)\n",
       "  if (!docs) {\n",
       "    return\n",
       "  }\n",
       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
       "  function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       ":DynamicMap   [time]\n",
       "   :Image   [x,y]   (flux)"
      ]
     },
     "execution_count": 6,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "p1004"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plot_cubes(betapic.cube, vmin=0, vmax=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Full-Width Half-Maximum (FWHM) will automatically be computed and stored as the attribute `fwhm` while we do another operation : normalizing the PSF. This can be done with the function `normalize_psf` of the ``Dataset`` object :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Mean FWHM: 4.801\n",
      "Flux in 1xFWHM aperture: 1.307\n",
      "Normalized PSF array shape: (19, 19)\n",
      "The attribute `psfn` contains the normalized PSF\n",
      "`fwhm` attribute set to\n",
      "4.801\n"
     ]
    }
   ],
   "source": [
    "betapic.normalize_psf(size=19, imlib='ndimage-fourier')\n",
    "betapic.psf = betapic.psfn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From now on the FWHM can simply be accessed with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.800919383981533"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "betapic.fwhm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\"> \n",
    "    <b>Note: </b>\n",
    "<a class=\"anchor\" id=\"note1\"></a>                                       \n",
    "\n",
    "The `normalize_psf` function performs internally a fine centering of the PSF. The input PSF should nevertheless already be centered within a few pixel accuracy for the fine centering to work.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize the normalized PSF with `hciplot.plot_frames`. Feel free to adapt the `backend` argument throughout the notebook: `'matplotlib'` allows paper-quality figures with annotations which can be saved (default), while `'bokeh'` enables interactive visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 400x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plot_frames(betapic.psf, grid=True, size_factor=4) #, backend='bokeh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's finally define the pixel scale for NACO (L' band), which we get from a dictionary stored in the `config` subpackage:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.02719\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.config import VLT_NACO\n",
    "\n",
    "betapic.px_scale = VLT_NACO[\"plsc\"]\n",
    "print(betapic.px_scale)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.2. Model PSF subtraction for ADI"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When loading the ADI cube above, we assumed all calibration and preprocessing steps were already performed. In particular, the star is assumed to be already centered in the images. If your data require calibration/preprocessing, feel free to check tutorial `2. Pre-processing`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\"> \n",
    "    <b>Warning: </b>\n",
    "<a class=\"anchor\" id=\"note1\"></a>                                       \n",
    "\n",
    "VIP's convention regarding star centering is:\n",
    "\n",
    "- for **odd** number of pixels along the x and y dimensions: the star centroid should correspond to the central pixel of the image;\n",
    "- for **even** number of pixels: the star centroid should be located on coordinates (dim/2,dim/2) in 0-based indexing (i.e. on the top-right pixel of the 4 central pixels).\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2.1. median-ADI"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most simple approach is to model the PSF with the median of the ADI sequence, subtract it, then derotate and median-combine all residual images ([Marois et al. 2006](https://ui.adsabs.harvard.edu/abs/2006ApJ...641..556M/abstract)). We can do this through the `PPMedianSub` object, obtained with a `MedianBuilder`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No changes were made to the dataset.\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Starting time: 2024-07-04 11:58:56\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Median psf reference subtracted\n",
      "Done derotating and combining\n",
      "Running time:  0:00:02.464630\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.objects import MedianBuilder\n",
    "\n",
    "medsub_obj = MedianBuilder(dataset=betapic).build()\n",
    "medsub_obj.run()\n",
    "ff_med = medsub_obj.frame_final"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This can also be done in concentric annuli of annular width `asize`, considering a parallactic angle threshold `delta_rot` and the `nframes` closest images complying with that criterion as model for subtraction to each image of the ADI cube:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No changes were made to the dataset.\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Starting time: 2024-07-04 11:58:59\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "N annuli = 9, FWHM = 4.800919383981533\n",
      "Processing annuli:\n",
      "0% [##############################] 100% | ETA: 00:00:00\n",
      "Total time elapsed: 00:00:00\n",
      "Optimized median psf reference subtracted\n",
      "Done derotating and combining\n",
      "Running time:  0:00:02.630582\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "from dataclass_builder import update\n",
    "\n",
    "update(medsub_obj, MedianBuilder(asize=betapic.fwhm, mode='annular', delta_rot=0.5, radius_int=4, nframes=4))\n",
    "medsub_obj.run()\n",
    "ann_med = medsub_obj.frame_final"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize the final images:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_frames((ff_med, ann_med))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Strong residuals can be seen near the center of the image, with a faint potential point source in the south-west of the final image."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2.2. Full-frame PCA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's try the Principal Component Analysis (PCA) algorithm ([Amara & Quanz 2012](https://ui.adsabs.harvard.edu/abs/2012MNRAS.427..948A/abstract), [Soummer et al. 2012](https://ui.adsabs.harvard.edu/abs/2012ApJ...755L..28S/abstract)), and set to 5 the number of principal components `ncomp` considered for model creation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No changes were made to the dataset.\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Starting time: 2024-07-04 11:59:02\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "System total memory = 17.180 GB\n",
      "System available memory = 3.169 GB\n",
      "Done vectorizing the frames. Matrix shape: (61, 10201)\n",
      "Done SVD/PCA with numpy SVD (LAPACK)\n",
      "Running time:  0:00:00.042851\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Done de-rotating and combining\n",
      "Running time:  0:00:02.579689\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "These attributes were just calculated:\n",
      "\tframe_final\n",
      "\tcube_reconstructed\n",
      "\tcube_residuals\n",
      "\tcube_residuals_der\n",
      "\tpcs\n",
      "\tcube_residuals_per_channel\n",
      "\tcube_residuals_per_channel_der\n",
      "\tcube_residuals_resc\n",
      "\tfinal_residuals_cube\n",
      "\tmedians\n",
      "\tdataframe\n",
      "\topt_number_pc\n",
      "The following attributes can be calculated now:\n",
      "\tdetection_map\twith .make_snrmap()\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.objects import PCABuilder\n",
    "\n",
    "pca_obj = PCABuilder(dataset=betapic, ncomp=5).build()\n",
    "pca_obj.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize the final image. This time let's set the `grid` option on, to better read coordinates from the image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_frames(pca_obj.frame_final, grid=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The improvement is clear compared to previous reductions. Very low residuals are seen near the star, and the companion candidate appears as a bright point source surrounded by negative side-lobes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.3. Is it significant?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's see whether the candidate is significant. For that let's first set the x,y coordinates of the test point source based on the above image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "xy_b = (58.5,35.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now with this point and the previously obtained frame, we are able to compute the significance of that candidate, by using the built-in function `compute_significance`. This function needs at least the coordinates of the candidate and a corrected frame. If no detection map was generated through `make_snrmap`, it will be created inside `compute_significance`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Starting time: 2024-07-04 11:59:04\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "S/N map created using 5 processes\n",
      "Running time:  0:00:02.848964\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "At a separation of 16.8 px (3.5 FWHM), S/N = 7.7 corresponds to a 5.2-sigma detection in terms of Gaussian false alarm probability.\n",
      "5.2 sigma detection\n"
     ]
    }
   ],
   "source": [
    "pca_obj.compute_significance(source_xy=xy_b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\"> \n",
    "    <b>Congratulations! </b>\n",
    "<a class=\"anchor\" id=\"det1\"></a>        \n",
    "    \n",
    "The detection is significant! You obtained a conspicuous direct image of an exoplanet! Although from this image alone one cannot disentangle a true physically bound companion from a background star, this source has now been extensively studied: it corresponds to giant planet $\\beta$ Pic b (e.g. [Lagrange et al. 2009](https://ui.adsabs.harvard.edu/abs/2009A%26A...493L..21L/abstract), [Absil et al. 2013](https://ui.adsabs.harvard.edu/abs/2013A%26A...559L..12A/abstract)).\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You're now ready for more advanced tutorials. If you wish to know more about:\n",
    "\n",
    "- pre-processing functionalities available in VIP (star centering, bad frame trimming, bad pixel correction...) --> go to **[Tutorial 2](https://vip.readthedocs.io/en/latest/tutorials/02_preproc.html)**;\n",
    "- post-processing algorithms leveraging Angular Differential Imaging --> go to **[Tutorial 3A](https://vip.readthedocs.io/en/latest/tutorials/03A_psfsub_ADI.html)** or **[3B](https://vip.readthedocs.io/en/latest/tutorials/03B_psfsub_ADI_as_objects.html)** (the latter for Object-Oriented example usage);\n",
    "- metrics to evaluate the significance of a detection or the achieved contrast in your image --> go to **[Tutorial 4](https://vip.readthedocs.io/en/latest/tutorials/04_metrics.html)**;\n",
    "- how to characterize a directly imaged companion --> go to **[Tutorial 5A](https://vip.readthedocs.io/en/latest/tutorials/05A_fm_planets.html)**;\n",
    "- how to characterize a circumstellar disk --> go to **[Tutorial 5B](https://vip.readthedocs.io/en/latest/tutorials/05B_fm_disks.html)**;\n",
    "- how to characterize a companion in a disk using JWST observations --> go to Tutorial 5C (to come soon);\n",
    "- post-processing algorithms leveraging Reference star Differential Imaging --> go to **[Tutorial 6](https://vip.readthedocs.io/en/latest/tutorials/06_psfsub_fm_RDI.html)**;\n",
    "- post-processing algorithms leveraging Spectral Differential Imaging --> go to **[Tutorial 7](https://vip.readthedocs.io/en/latest/tutorials/07_psfsub_fm_IFS-ASDI_planets.html)**;\n",
    "- the difference between FFT- and interpolation-based image operations (rotation, shifts, scaling) --> go to **[Tutorial 8](https://vip.readthedocs.io/en/latest/tutorials/08_imlib_and_interpolation.html)**."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}