{
 "cells": [
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Datenquellen und Transformationen\n",
    "\n",
    "## Überblick\n",
    "\n",
    "Bokeh kann mit Python-Listen, NumPy-Arrays, pandas-Serien usw. arbeiten. Dabei werden diese Eingaben in eine Bokeh `ColumnDataSource` konvertiert. Obwohl Bokeh dies oft transparent macht, kann es gelegentlich sinnvoll sein, sie explizit zu erstellen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "hide_input": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "        .bk-notebook-logo {\n",
       "            display: block;\n",
       "            width: 20px;\n",
       "            height: 20px;\n",
       "            background-image: url(data:image/png;base64,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);\n",
       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-notebook-logo\"></a>\n",
       "        <span id=\"ae2d6dc8-1215-456d-b9d3-396116103af1\">Loading BokehJS ...</span>\n",
       "    </div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  const force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "const JS_MIME_TYPE = 'application/javascript';\n",
       "  const HTML_MIME_TYPE = 'text/html';\n",
       "  const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  const CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    const script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    const cell = handle.cell;\n",
       "\n",
       "    const id = cell.output_area._bokeh_element_id;\n",
       "    const server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd_clean, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            const id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd_destroy);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    const output_area = handle.output_area;\n",
       "    const output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      const bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      const script_attrs = bk_div.children[0].attributes;\n",
       "      for (let i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\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",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      const 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",
       "      const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    const events = require('base/js/events');\n",
       "    const OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  const NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    const el = document.getElementById(\"ae2d6dc8-1215-456d-b9d3-396116103af1\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\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, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\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 == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\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",
       "\n",
       "    function on_error(url) {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (let i = 0; i < css_urls.length; i++) {\n",
       "      const url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\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",
       "    }\n",
       "\n",
       "    for (let i = 0; i < js_urls.length; i++) {\n",
       "      const url = js_urls[i];\n",
       "      const element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\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",
       "  };\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",
       "  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.1.1.min.js\"];\n",
       "  const css_urls = [];\n",
       "\n",
       "  const inline_js = [    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "          for (let i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "if (force === true) {\n",
       "        display_loaded();\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",
       "    } else if (force !== true) {\n",
       "      const cell = $(document.getElementById(\"ae2d6dc8-1215-456d-b9d3-396116103af1\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  const NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    const el = document.getElementById(\"ae2d6dc8-1215-456d-b9d3-396116103af1\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\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, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\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 == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\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\n    function on_error(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\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    }\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\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  };\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  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.1.1.min.js\"];\n  const css_urls = [];\n\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {\n    }\n  ];\n\n  function run_inline_js() {\n    if (root.Bokeh !== undefined || force === true) {\n          for (let i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\nif (force === true) {\n        display_loaded();\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    } else if (force !== true) {\n      const cell = $(document.getElementById(\"ae2d6dc8-1215-456d-b9d3-396116103af1\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.io import output_notebook, show\n",
    "from bokeh.plotting import figure\n",
    "\n",
    "\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python Dicts\n",
    "\n",
    "Die `ColumnDataSource` kann aus `bokeh.models` importiert werden:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.models import ColumnDataSource"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`ColumnDataSource` ist eine Zuordnung von Spaltennamen zu Wertsequenzen. Dabei müssen alle Spalten immer die gleiche Länge haben:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "source = ColumnDataSource(\n",
    "    data={\n",
    "        \"x\": [1, 2, 3, 4, 5],\n",
    "        \"y\": [3, 7, 8, 5, 1],\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bisher haben wir Funktionen wie `p.circle` aufgerufen, indem wir direkt Listen oder Datenarrays übergeben haben. Dann erstellt Bokeh automatisch eine `ColumnDataSource` für uns. Es ist jedoch auch möglich, eine `ColumnDataSource` explizit anzugeben, indem als Quellargument eine Glyph-Methode übergeben wird:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"bf607eac-1287-483b-9eb2-770e92a59656\" data-root-id=\"p1004\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "  const docs_json = {\"74177fda-68c0-4512-ab4e-d99e91eb5da2\":{\"version\":\"3.1.1\",\"title\":\"Bokeh Application\",\"defs\":[],\"roots\":[{\"type\":\"object\",\"name\":\"Figure\",\"id\":\"p1004\",\"attributes\":{\"width\":400,\"height\":400,\"x_range\":{\"type\":\"object\",\"name\":\"DataRange1d\",\"id\":\"p1005\"},\"y_range\":{\"type\":\"object\",\"name\":\"DataRange1d\",\"id\":\"p1006\"},\"x_scale\":{\"type\":\"object\",\"name\":\"LinearScale\",\"id\":\"p1017\"},\"y_scale\":{\"type\":\"object\",\"name\":\"LinearScale\",\"id\":\"p1019\"},\"title\":{\"type\":\"object\",\"name\":\"Title\",\"id\":\"p1010\"},\"renderers\":[{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1056\",\"attributes\":{\"data_source\":{\"type\":\"object\",\"name\":\"ColumnDataSource\",\"id\":\"p1001\",\"attributes\":{\"selected\":{\"type\":\"object\",\"name\":\"Selection\",\"id\":\"p1003\",\"attributes\":{\"indices\":[],\"line_indices\":[]}},\"selection_policy\":{\"type\":\"object\",\"name\":\"UnionRenderers\",\"id\":\"p1002\"},\"data\":{\"type\":\"map\",\"entries\":[[\"x\",[1,2,3,4,5]],[\"y\",[3,7,8,5,1]]]}}},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1057\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1058\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"Circle\",\"id\":\"p1053\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"size\":{\"type\":\"value\",\"value\":20},\"line_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Circle\",\"id\":\"p1054\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"size\":{\"type\":\"value\",\"value\":20},\"line_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.1},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.1}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Circle\",\"id\":\"p1055\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"size\":{\"type\":\"value\",\"value\":20},\"line_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.2},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.2}}}}}],\"toolbar\":{\"type\":\"object\",\"name\":\"Toolbar\",\"id\":\"p1009\",\"attributes\":{\"tools\":[{\"type\":\"object\",\"name\":\"PanTool\",\"id\":\"p1035\"},{\"type\":\"object\",\"name\":\"WheelZoomTool\",\"id\":\"p1036\"},{\"type\":\"object\",\"name\":\"BoxZoomTool\",\"id\":\"p1037\",\"attributes\":{\"overlay\":{\"type\":\"object\",\"name\":\"BoxAnnotation\",\"id\":\"p1038\",\"attributes\":{\"syncable\":false,\"level\":\"overlay\",\"visible\":false,\"left_units\":\"canvas\",\"right_units\":\"canvas\",\"bottom_units\":\"canvas\",\"top_units\":\"canvas\",\"line_color\":\"black\",\"line_alpha\":1.0,\"line_width\":2,\"line_dash\":[4,4],\"fill_color\":\"lightgrey\",\"fill_alpha\":0.5}}}},{\"type\":\"object\",\"name\":\"SaveTool\",\"id\":\"p1039\"},{\"type\":\"object\",\"name\":\"ResetTool\",\"id\":\"p1040\"},{\"type\":\"object\",\"name\":\"HelpTool\",\"id\":\"p1041\"}]}},\"left\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1028\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1029\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1030\"},\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1031\"}}}],\"below\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1021\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1022\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1023\"},\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1024\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1027\",\"attributes\":{\"axis\":{\"id\":\"p1021\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1034\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1028\"}}}]}}],\"callbacks\":{\"type\":\"map\"}}};\n",
       "  const render_items = [{\"docid\":\"74177fda-68c0-4512-ab4e-d99e91eb5da2\",\"roots\":{\"p1004\":\"bf607eac-1287-483b-9eb2-770e92a59656\"},\"root_ids\":[\"p1004\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1004"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = figure(width=400, height=400)\n",
    "p.circle(\"x\", \"y\", size=20, source=source)\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `pandas.DataFrame`\n",
    "\n",
    "Es ist auch einfach, `ColumnDataSource`-Objekte direkt aus pandas-DataFrames zu erstellen:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"d7e6d202-3fef-4e4b-9d1d-8d2e556e26ac\" data-root-id=\"p1146\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "  const docs_json = {\"0e6b0a83-99c4-4d34-b00f-31b268dd15db\":{\"version\":\"3.1.1\",\"title\":\"Bokeh 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       "  const render_items = [{\"docid\":\"0e6b0a83-99c4-4d34-b00f-31b268dd15db\",\"roots\":{\"p1146\":\"d7e6d202-3fef-4e4b-9d1d-8d2e556e26ac\"},\"root_ids\":[\"p1146\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1146"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.sampledata.iris import flowers as df\n",
    "\n",
    "\n",
    "source = ColumnDataSource(df)\n",
    "p = figure(width=400, height=400)\n",
    "p.circle(\"petal_length\", \"petal_width\", source=source)\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transformationen\n",
    "\n",
    "Wenn Datenquellen nicht gemeinsam genutzt werden müssen, können Dicts, `pandas.DataFrame`- oder `GroupBy`-Objekte direkt an die Glyph-Methode übergeben werden ohne explizit eine `ColumnDataSource` zu erstellen. In diesem Fall erfolgt die Konvertierung automatisch.\n",
    "\n",
    "Glyph-Eigenschaften können nicht nur mit Namen von Spalten aus Datenquellen konfiguriert werden, sondern auch mit Transformationsobjekten aus `bokeh.transform`. Dabei ist wichtig zu beachten, dass bei der Verwendung dieser Objekte die Transformationen im Browser und nicht in Python erfolgen."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `cumsum`\n",
    "\n",
    "Im Folgenden betrachten wir zunächst eine `cumsum`-Transformation, die aus einer Spalte eine neue Folge von Werten erzeugen kann indem die Werte kumulativ summiert werden. Dies kann für Kreisdiagramme oder Doughnut-Diagramme nützlich sein:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"e9667079-f540-4acc-8fbe-6c3eaa9003df\" data-root-id=\"p1304\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "  const docs_json = {\"987ca53a-ac38-49d6-9f6c-5ca6ce21ec68\":{\"version\":\"3.1.1\",\"title\":\"Bokeh Application\",\"defs\":[],\"roots\":[{\"type\":\"object\",\"name\":\"Figure\",\"id\":\"p1304\",\"attributes\":{\"height\":350,\"x_range\":{\"type\":\"object\",\"name\":\"DataRange1d\",\"id\":\"p1305\"},\"y_range\":{\"type\":\"object\",\"name\":\"DataRange1d\",\"id\":\"p1306\"},\"x_scale\":{\"type\":\"object\",\"name\":\"LinearScale\",\"id\":\"p1318\"},\"y_scale\":{\"type\":\"object\",\"name\":\"LinearScale\",\"id\":\"p1320\"},\"title\":{\"type\":\"object\",\"name\":\"Title\",\"id\":\"p1307\",\"attributes\":{\"text\":\"Pie Chart\"}},\"renderers\":[{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1350\",\"attributes\":{\"data_source\":{\"type\":\"object\",\"name\":\"ColumnDataSource\",\"id\":\"p1341\",\"attributes\":{\"selected\":{\"type\":\"object\",\"name\":\"Selection\",\"id\":\"p1343\",\"attributes\":{\"indices\":[],\"line_indices\":[]}},\"selection_policy\":{\"type\":\"object\",\"name\":\"UnionRenderers\",\"id\":\"p1342\"},\"data\":{\"type\":\"map\",\"entries\":[[\"index\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"AAAAAAEAAAACAAAAAwAAAAQAAAAFAAAABgAAAAcAAAAIAAAACQAAAAoAAAALAAAA\"},\"shape\":[12],\"dtype\":\"int32\",\"order\":\"little\"}],[\"country\",{\"type\":\"ndarray\",\"array\":[\"United States\",\"United Kingdom\",\"Japan\",\"China\",\"Germany\",\"India\",\"Italy\",\"Australia\",\"Brazil\",\"France\",\"Taiwan\",\"Spain\"],\"shape\":[12],\"dtype\":\"object\",\"order\":\"little\"}],[\"value\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"nQAAAF0AAABZAAAAPwAAACwAAAAqAAAAKAAAACMAAAAgAAAAHwAAAB8AAAAdAAAA\"},\"shape\":[12],\"dtype\":\"int32\",\"order\":\"little\"}],[\"color\",{\"type\":\"ndarray\",\"array\":[\"#3182bd\",\"#6baed6\",\"#9ecae1\",\"#c6dbef\",\"#e6550d\",\"#fd8d3c\",\"#fdae6b\",\"#fdd0a2\",\"#31a354\",\"#74c476\",\"#a1d99b\",\"#c7e9c0\"],\"shape\":[12],\"dtype\":\"object\",\"order\":\"little\"}],[\"angle\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"eQLEMwAC9z+3V8R09kHrP+QcmNXVFeo/hZ74ygF34j8vDs2tzcrZP1vToA6tntg/iJh0b4xy1z93BYbhOoTUPzmtw/IJwtI/0I8to/kr0j/Qjy2j+SvSP/xUAQTZ/9A/\"},\"shape\":[12],\"dtype\":\"float64\",\"order\":\"little\"}]]}}},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1351\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1352\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"Wedge\",\"id\":\"p1347\",\"attributes\":{\"x\":{\"type\":\"value\",\"value\":0},\"y\":{\"type\":\"value\",\"value\":1},\"radius\":{\"type\":\"value\",\"value\":0.4},\"start_angle\":{\"type\":\"expr\",\"expr\":{\"type\":\"object\",\"name\":\"CumSum\",\"id\":\"p1339\",\"attributes\":{\"field\":\"angle\",\"include_zero\":true}}},\"end_angle\":{\"type\":\"expr\",\"expr\":{\"type\":\"object\",\"name\":\"CumSum\",\"id\":\"p1340\",\"attributes\":{\"field\":\"angle\"}}},\"line_color\":{\"type\":\"value\",\"value\":\"white\"},\"fill_color\":{\"type\":\"field\",\"field\":\"color\"}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Wedge\",\"id\":\"p1348\",\"attributes\":{\"x\":{\"type\":\"value\",\"value\":0},\"y\":{\"type\":\"value\",\"value\":1},\"radius\":{\"type\":\"value\",\"value\":0.4},\"start_angle\":{\"type\":\"expr\",\"expr\":{\"id\":\"p1339\"}},\"end_angle\":{\"type\":\"expr\",\"expr\":{\"id\":\"p1340\"}},\"line_color\":{\"type\":\"value\",\"value\":\"white\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"fill_color\":{\"type\":\"field\",\"field\":\"color\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.1},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.1}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Wedge\",\"id\":\"p1349\",\"attributes\":{\"x\":{\"type\":\"value\",\"value\":0},\"y\":{\"type\":\"value\",\"value\":1},\"radius\":{\"type\":\"value\",\"value\":0.4},\"start_angle\":{\"type\":\"expr\",\"expr\":{\"id\":\"p1339\"}},\"end_angle\":{\"type\":\"expr\",\"expr\":{\"id\":\"p1340\"}},\"line_color\":{\"type\":\"value\",\"value\":\"white\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"fill_color\":{\"type\":\"field\",\"field\":\"color\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.2},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.2}}}}}],\"toolbar\":{\"type\":\"object\",\"name\":\"Toolbar\",\"id\":\"p1311\",\"attributes\":{\"tools\":[{\"type\":\"object\",\"name\":\"HoverTool\",\"id\":\"p1336\",\"attributes\":{\"renderers\":\"auto\",\"tooltips\":\"@country: @value\"}}]}},\"toolbar_location\":null,\"left\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1329\",\"attributes\":{\"visible\":false,\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1330\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1331\"},\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1332\"}}}],\"below\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1322\",\"attributes\":{\"visible\":false,\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1323\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1324\"},\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1325\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1328\",\"attributes\":{\"axis\":{\"id\":\"p1322\"},\"grid_line_color\":null}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1335\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1329\"},\"grid_line_color\":null}},{\"type\":\"object\",\"name\":\"Legend\",\"id\":\"p1353\",\"attributes\":{\"items\":[{\"type\":\"object\",\"name\":\"LegendItem\",\"id\":\"p1354\",\"attributes\":{\"label\":{\"type\":\"value\",\"value\":\"country\"},\"renderers\":[{\"id\":\"p1350\"}]}}]}}]}}],\"callbacks\":{\"type\":\"map\"}}};\n",
       "  const render_items = [{\"docid\":\"987ca53a-ac38-49d6-9f6c-5ca6ce21ec68\",\"roots\":{\"p1304\":\"e9667079-f540-4acc-8fbe-6c3eaa9003df\"},\"root_ids\":[\"p1304\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1304"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from math import pi\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "from bokeh.palettes import Category20c\n",
    "from bokeh.transform import cumsum\n",
    "\n",
    "\n",
    "x = {\n",
    "    \"United States\": 157,\n",
    "    \"United Kingdom\": 93,\n",
    "    \"Japan\": 89,\n",
    "    \"China\": 63,\n",
    "    \"Germany\": 44,\n",
    "    \"India\": 42,\n",
    "    \"Italy\": 40,\n",
    "    \"Australia\": 35,\n",
    "    \"Brazil\": 32,\n",
    "    \"France\": 31,\n",
    "    \"Taiwan\": 31,\n",
    "    \"Spain\": 29,\n",
    "}\n",
    "\n",
    "data = (\n",
    "    pd.Series(x).reset_index(name=\"value\").rename(columns={\"index\": \"country\"})\n",
    ")\n",
    "data[\"color\"] = Category20c[len(x)]\n",
    "\n",
    "# represent each value as an angle = value / total * 2pi\n",
    "data[\"angle\"] = data[\"value\"] / data[\"value\"].sum() * 2 * pi\n",
    "\n",
    "p = figure(\n",
    "    height=350,\n",
    "    title=\"Pie Chart\",\n",
    "    toolbar_location=None,\n",
    "    tools=\"hover\",\n",
    "    tooltips=\"@country: @value\",\n",
    ")\n",
    "\n",
    "p.wedge(\n",
    "    x=0,\n",
    "    y=1,\n",
    "    radius=0.4,\n",
    "    # use cumsum to cumulatively sum the values for start and end angles\n",
    "    start_angle=cumsum(\"angle\", include_zero=True),\n",
    "    end_angle=cumsum(\"angle\"),\n",
    "    line_color=\"white\",\n",
    "    fill_color=\"color\",\n",
    "    legend_label=\"country\",\n",
    "    source=data,\n",
    ")\n",
    "\n",
    "p.axis.axis_label = None\n",
    "p.axis.visible = False\n",
    "p.grid.grid_line_color = None\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `linear_cmap`\n",
    "\n",
    "Mit der `linear_cmap`-Transformation kann eine lineare Farbzuordnung zur Spalte einer Datenquelle eine neue Farbsequenz erzeugen:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"f68bdd18-6c8e-46f6-87d7-61c98290d5f6\" data-root-id=\"p1458\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "  const docs_json = {\"bce58f20-29df-4fd8-9576-73b680b1ce5f\":{\"version\":\"3.1.1\",\"title\":\"Bokeh 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Q0AVgtfToqQ/QJC+uD1O2jhA4zGvReBIR0CIjgtIcQJRQMwlDtd6pFVAwIB3BJXhRkCgT3vg47hCQPrm8yBinFhAwaSlD305UUDya7CGTag1QLi+ryOvPOo/oNlRfw3ZU0AOqsVv88M4QKcL8NhrcExA5illTcQgIECzhx8yMsdWQC4CzER1nVJAVdJDPPGCNUB4kmKUygjyP2rAF3FGxU5AlsF5jbHoVEC8bGFyULUrQBqObJXODVhA9pNXNy6cJUCV7MhP994sQD8UsfwNx0BAdkmmeZfnU0DCR2Hy9EQrQKegLoqRslhAW4Ewg8p7VUAClDN7JztWQJnz9kM63DNAm8wsfN1vUEDgA8pXRO5VQI1SDfGtuh1AcICNY1e6SkAYwtXnoHNDQKT99JF7q0BA/f0LG0SsUUDgpxjwJBFRQCKwZCMGg01A64hPX8JuTEDBuPUFeLpKQEsdoHNkelBAgGoy8TIDIUB5ALT+zXZSQJxtiCSTxVNAKoBvbrb9TEBjhb16lwxPQCeh6J4rXldAWNiTaSO0UUA4+R/iNSPUP6jBuA4yKyJALeBXraKVUUCdnwjreB9UQCoT4JWy9FNAsOnFpLraUUAKhj5wpWgsQJYYfeYpdDtAtE7eKWMpSkA494oEReIcQFbj5Tx+4ylAXFbe6a9ZJECMMQb5xdgnQFoXIPnvsFRAZEuaNLD1P0DAYw7iyLU4QAHZYB4SZU1Ad1M0IFK1SEC2bHDldSZTQN5qKrKsZlRANGeJhVNZVkBM3p+WqpoqQDhugq97/UpAToCp1QgPNUDZ34HWm/pIQJvY8uO/GVhAgI2frjUuU0DdPjut3R0jQIET5tA2JFJAP2AzNPnlOECL5Unt8+ZEQP4F/M8vkUlAr+JByLt9U0AsRjJTQeIvQDDNYkUryEZArggOZlAAVkCyCft8VvdSQGgjQfmObylADkcHtmGy+j84giTusvFYQK3cqcwHUVVApBangSlPTkCk5ezZ57IRQAKFEfcwcFVAgJZvQItdEUAFhMd1vrs9QJwyZQEWPktArGRd6TF2U0DWiZHqt9ZNQFoetp0QRkdA2WgJnnzHTUAv54rIRVRSQFmX/kNBNkNAqWqWDIq4UkBr1eqAERc3QIJCk1rzV1RA3uu1rPSZTEB8/dsEr8lFQOneqOqMCUJAwLhRnCCjBkCS71WUYfVHQIPkQFuW8lhAkhKhqWxOQ0AdTVyLtHFRQCyRiQc9z1RAPVjbwBSzCkDqF5IM9/ZWQFyYn/2NljVAH2L0H5W6UEAn3Ti/R71PQLT3yrr/61VARlm3TuJrWECID5boN3hWQFGr9bJ1tFJAP13mi3ZvSkBUi9ezIVJVQGW4qMyx7FZADH9LGkvrVEAWvlNW2ftQQKpr8Dq5cUNAAMuD3MzbKkC6tdV+VTRMQJsSyK2TzUZAbNRxDGO09T/q1nR24QJQQDO6wKl/JVJA4IHUqI25SkAphNGxa3VUQDqFNkjnlC5ARtoEdOP5KUDo5BXgC2xFQEkIGnCLAkFA0u4tT/aVQkCU49Ht5DbmP0/9EeZi4EtAwFosBsSNUUBsFqheXxIjQMYbqnJUxVJAVGveXB+AVUCtGXjBtFdVQOiKKi0BRVZA4NgNXh8nzD9JReoYmPQpQNRNr81alldA0YQMUDo3Q0CHWzU8BQdOQNc5/wReKyVAOuAVEmGxSkBWFHlWbglMQCbYl9r/qUpAzalJYTuNUUBuQubpp+RUQLP9ohgE/kZA2koQ7LodTUCehbgBbJ9YQJxRkATKOElAFEGsKWHfQUCUmsYvIiclQO3lJ7qFqjFAhuCtFnMTUUBbPM+QKcVNQJpHQh+jrlBALOPPEStYVUCIAw+pW0RRQHXqPqmUUFFAMks/F/EII0CIiqt4ZTk3QDALBepY1TNA00eOJhEOTUDL2PqpsylHQJIqzTm8kVVA2SgEGkZmVEDS4nbAkRE+QBhhsQGYgUhA/FJqkvKzTED+9ejrhKdXQPJdyJ+r1VdAq4mG+HrCUkBkYoOusF5DQP/v/fqkEzxANj8gkrvqUkCVQrbxgtodQI0BRi3tEUJAKreXI+WwWEBsLuIGeohJQOiV6T2m5TVA3dVVHnNhRkDijhijzItOQOunEHo+BTpAMeh/VXxFR0CNDUHKdOpQQPrZcRIkvvA/AnaYwHuyRUDF09zULfVSQJbtb/LEAzZAWSebNQM0OUAJfq1ZdI06QCVQlDDhmU9AXXr1AippH0C+H9egSAYrQErYsosqMDtASPbpI8gaVUAGkQuuTUYkQNay9CuvrwBA8LKsnP2SIkDmjscMvEM5QLRWarp2AlRAb0vl/fy9QkAbnHvuLohQQHZ47BUDMElAp8nUS0UdWECZC3vNLdxRQMUmjOGOjh9AKP1a8P5MVUBSrvvqQagfQFLRitqlaVdAolD6GDjHO0AU99L62UggQNr/dgNRYDlAPBVtWDTYTUCnO33PHPlIQErwdGtkqzJAoYRmSqR/VUBI4c97xVlFQOui0+xLoFRAVNgfwEQwV0DlZM8qggwxQJA73g7qTUpA4qo8lbNOWECLJivgLrc/QNtVD4gDkEpAk9cCtDFjVkDmMPWlU3xHQLkjjeKKHlJAqkNFstT6NkCCCZORkkhJQDtOSUef8E1AXUBnQDIYNEAMFeWbUxRPQH07SHQIf1FAAPk1t9J7PEAtIlB8gSdWQPeZIFO4llVAiZQwQDmkMEAERo0DLKBTQJR35n2+mEZA68i4y2ZDSUD7hsGIBlNUQAo0ihN7eVZA4WImq65KTkAHgJtvnVlJQKZ8QExplxNATaQsNeQ1U0CzxzdHw8w7QLX6WQVrdVNANUCI0CtETUDuUp8C3yYeQE6echT9MlZA3lA8GTQ4IEDeFKd9pzlBQCyYwNdVE+c/p/QYWbHRDkD65x4wGZw2QKpOGpMb/B5AgwpzYiZZIkALZX3q9gJWQFppVSwBwTFAwCS3bhHO6j9Lk1LUFtVFQCOxFOXYyVdALxkKLqjuU0Bmv8zROjdJQHBLcXWDRhNAyKk+fPJUU0D1mF/9yAFVQAByGRbsL48/AYqRVmSaAEBC5py5wdJGQMHhiiD1dUZAi72Kb+cOUkDrC0acC1IUQOZo2z6xO/g/Q5OQmpz8CUC3dO4p+R8wQFRv2vMOO1FAi5RaxPn/OEC5hgKscJgzQKky+kBLgk1AyXGLYi0LV0CuBN2yehpSQJAlvL/M1ldAmAM7IeArRUApF8cOPOAxQOQ0fbhYHidADl/8rzvHVEAbg3r3NDZYQBHsQGKrAVZA4XGQ6J2IU0DqydgXOz48QDqHPtf3MEdAxr2zHj9QTUDM4Op2W+JDQJG7ZHzI30RAvW/wS3clQ0C3Mr8EoTw/QOR8eCs8aT5AixKmsL3FU0CEIFJMllsvQJDvA+SsqC5AmLRMBHjLU0A14Qltru9QQJgyc+n5HDNAFtx0KcawSUBvadd1KUsxQJ5xS1fYrz9A4g3Nn9fRRkBlhxg1Xe9QQLJGC3SqV1FAjrneK4U5VEDN4WnslnpLQMyKUxJB6CNAfnDCUOPYUUDINkAq8dc9QJs/2rVYFVZAMysviu+QOED9MusLxWglQMo4SxSTMStAMqL17yGHSkBQOZxF1yIgQDOMEIba10xAOs8ntenKVkDfGFjRTQscQLll7NnnezVAO8v13tiSOUAmnF1MlOw6QC1ja7Eg205ASf9LGUEjQkADqdr0dbtQQO8h84HGbxZAGeW1xBcTVkDNzXF1vIRWQNxyrr9+hzNASJSnVms8EkCExvsPr+xBQPelsctP11dAsjyv7ulkLUAflEDYt34gQDlW8xV0uhBAuNtsJKnxV0B9A5GTSDBWQGo3qfNk/lJAlSPs6VZRMkAgf3XfJ6ZCQOQkiEfecR9AlDX8azSrKUAKxkwIyPA2QKri9w+Frx9AvtOdt7JAKkANhtIA5MFVQEBNvl89N1hAvZBp333fVkDZgB8HtQ5DQGmFOACUj0dAwt4wutrOVUDi90I7Sc1QQI7VxToy2lBAz/BJOPAsNEDzqybN7h9XQAq6FKP7ClFA3OLkNTdEI0D06P3ypRFMQKsHOt8B1xRACA5v8NshRUDIBJgPYtBAQHAHkio6kNo/QTlePzT7IkAaiFmOO/xWQHxkX1mQQkVAObSXNXhAFEAhvvXUdCZCQBMvXD93JVBA8CfG0nmfNUAmfVbrGehVQDi60DLEG0FAWpWrpLHBM0A3qY+YmvpIQM+3/2JsCRRA6jR4htW/N0DUuTyj158vQAGBAP/Xk1ZABdKtbz+fDUBB5yNE4bVJQNJaenGxEFBAN/+ONx70TUB1u3sWAW8dQO5MXZp/ehxAlJ9tJ8WrS0DCDAd3Kj1MQLQWYdv7UEBA0vtHF7CSRkDmjselmvNTQCDIonqUQUNAu6u7xgZJSED2+TRU0jtQQFrQ20MDOFJAmrK6AEa/IUATWqdUuBtUQOkhQGVCDjxAXX899BfPMUBkXCX/0D8tQMCWK9jCBNU/Jhmpe8hhVEATET1ROzRYQINs3E2laE9A9wvPfgI0QUDt5aptiXxWQE3w/FXQVE5ALGmNKM16P0AZ+4giQ21YQLFGrVkO3VFA+Vw1aEAiR0C/a6Raa7tXQCnhi4k1AElA86+rXA99VUDNuTNr5FYoQAGbxpYi01hAcdh2sA6OQECWUjDt5MNUQPwVQMkQqFBAHWiTwN1EVkA0pfMBS6FKQLn9SIDDWxBAixtUnPzJLkDCA4PP6O8yQNU/bu3qWUxAD9LBoXEAWEAUn1dOSdJTQAfQHn+3aklAysYZUfY1FkCVMA2xLX1FQKMWD2Zfc1VAsW/hpB8cNEBRs7a6FytQQHy3E6ZyrERA5eMy81QpSEACiJRH/YE1QC9KuOGKFk1AdCTjd5NsV0A0Vir4EVBYQDklON6OCVdAWbYj9lgyQ0DtICc6H3FRQKpDTzkaahZAgb/K06xPR0BrpXlb0AonQBkk3GLxxx9AyNUthwLt9z/mzPFhBQlAQF2ROpnKDUVAxTJ6/4dXV0CRnaaiHo5FQJcPFVKwXkVAE0PoQuSdTUDrj5neu88nQPjp4wT4UEhAQCnSYZq1VkAkCQyAdm85QJBHtH9xMzpAA0Ohu1ETOkCKHmfyxdUhQGIo+vnLiFdAsj/MpsBrP0BYWquV6elIQP/ZA/WSMVNAXsl2ayKCTkB923jUIZlFQJlqLrN8jhRAn1+9dh7jSUDgFWgox8ROQN9O5jpAizBAgcFT1LhlLECTg+5H/95WQMQbhOWUlCRAO3TPa9SRT0AKQeXxwEhVQO86E83XqzhAsE45L9t6OECOHUWbxUQhQDacVpICglRA10Zw4wwEJUBkS5wMwlRSQEhFTZmQjkVAVVlEw4CsTkCvGoQ1yedUQDI8HGSx5jdApSu85DpVVUDhQC9+iD1YQKDeEmeGb1FAjFa3QuJfOkDudofG7R1SQO7NFhOjET1Akm+QjcnfVEBcnHMcyPFSQJ0m1AxEJVBA0ildNfiGU0BOTujV97BYQNBwS5NTCzJAASgq5oxSSkCmYxa9GQUnQAbBPzG3ukZApBAC4xB0UkAeuLwoU485QL5NCc/LCUxAniofYC3cVkCupkzXiVlCQK+x6JrtNk1AlLxugyZyGEDEaHH7YLZTQI97RIjnpUpA4B6EzRIpBEBFy9EiSKZRQGIlLKZB+y9Ahtyz/Zk1B0DnXGyEZ8wZQNvEEVeyfUBAMjVLS0sPVkAyWJEDcjAbQE5bPu0u205AicBMUZhSSUAnNPqddVdAQFint8GWA0xAoAUix5gJUEDlw0Nm5D4WQDsnR4adADdABjKXURkjPUDoGhqOB1xNQPWCXT6X5A9A93kqTMYGNkB8G1mxBtctQBkGjO86hUhALFyOhxMBKEBKc/lqmTJSQI5HKhIiCzdA5kUkEKUTNUARQvrHLpE0QIDHRXdEK8g/02BGyBUBNEBPloumuNJWQAexcQAb7DdAD1etVc1HPkCGC8wlVHcKQBaAjddv3TVAtWvsM3INQUDA2LCja9wlQCIh3W5EaUhA1wqOZARXP0Cg+kq1D3pEQCTjeDSWJDVAyFcrcn5y0D9C2khCFPNTQPBbwId87y5A+8/4c/O4VkCXBlNbLmY1QMKIJdQcPTRA8MT/iJLbRUD9WZgT3ck1QL+3yzu1YVRAJeFDjpCUNUBZt+eKNlxVQOrZvQI/ZzNAWuNeMUrkUEDM1zM0qrhGQKBtyff4eVBAXjT9Ik9jIEBu+9x3XK5RQBR5QJGLZyNAYUHJGqepNkAEZNuNfIVKQLw/Cf5CdVhAGfIPKF+ySkBmyYcp9hRRQD3X+KR0EzJAcOw00eVi/T8lGMt2G15EQOn289Al205Ayj2+/ahtJEDYecKgI59PQAChHKPdsBNADkD5n9tFQECRNpevwelLQEf5YglE51VAU3j18g8BREAvK4ETO/lFQM76Bz0CuDxARXBN0YMMLkDtvz+0L7lHQKjs3UetZDZAUJrNZz4pKEAtQWMDHWBQQJKYmR4SjlJAw+UgFVAbUUD3uLEvlCggQGvy3j7d8zVA8q91fYDPNUBz3yS8SosqQAUYx7m6YFFAnYi7dTPEUkAsCKDfFeFUQMsSEGyHgEJAPfh5wIiAREDVnbs4gG5NQI3s3xz5O0FApHpVzBXUTEB3AXelAJ5XQCd5fzHu0UFA/X7RaC0tVkCmmMRgKeFRQJuMKLuiw0VA4vnpKtsjP0Ak4xCzcbZXQMDv4X697yhAXoeervhhQEC0EC01zzVPQE4G40CWkx5ANJz7k61oQEB7H6S0nYhUQF8o31yYIzZA2A6OkHi36j8SMOP2UJpIQN2okubqkEdAwA+jqBXwSEB5wcfB+ZNNQBypFrgRyk5AgLmovPyxV0DtR3idXd1UQKhmASW4gDlA9t2bpqFNT0AtOFfqg3NGQD13Q44eS0FAN/5Z9eMSLEDy+rVdk85QQNSZkf5fF0BAS/G/nnCrU0A95Sdbj7xDQCLBWuS4vjlAjm3u8c3QL0ApWlgF8JxTQN8gajy/Q0JArbzPDq7oUEDYpPdN4vBQQI+yS44aNUFAIAmDwZrQTECcxEdKzRL+P7kQ6VdxzTFABDn7/pz9KEBnB4dCyfdOQCTAof1HuFJAVY+ZfVBmSEBmje0fGhQkQKmq5uPkZzJAuMcwpJSRUkCxk/49OXQxQPMqoYQXW0ZA4dN5InWwWEDM9JO8mOZVQLEWKUl86z5ApAR5oZyzN0BbU8nP861XQBc1vFeZQ1BACTip1r/NS0CJA54D3BMEQMb+bHiZw0lAeE0MnSEpO0CW4PHjanM0QPFrpe7a3FJAwMUtJZOWU0DCnMQSO4pBQB8ac0fp205AukE9JxkuIkDzdgyV1OdTQFKO3pwi1z5AFvipkNvuQUAN+LddnNQ3QKtd3oswg1RAP+aLHVVzE0ABa3fXOiRRQIdvC3gw+kpAW5gzdnOsL0D01eHZ9QpXQPOyfnL2ST1ACpAnnJouUUB2A7fw3y1AQDKbrIQ9t09AWkDJaHbqMkAhzwwQIJY7QI8APHxtfVJAmdns72NLR0BrZovdAc5UQCW32Vb6N1NAM6MfZPbXLkDXWRtMc9JOQPqbR8Z99TRAEw+HQZtPQUAqmxiqV9JRQH6MrRTRjlRALoDBTrFmIEBHh26EfMFIQJ68ghyEaTBALgTPR/8ONkBVGBPzyJtOQKniKhOyTFVAqBUczuhhIkAZiMOX26pUQMoHpWOfQU5AbNFo/o5uJ0AXsCvK2vFDQLG9DfIMw1NAKRqcCkdOWEAD3Q96r5pRQK6Au9OJgVNAMTYV98XHPUDUxgVrkvxRQNbnbPNN8lFAenLis1qoUkAOgVYJL7FVQBnBXGtvCU9AGthehMX9UUBFaUgnpcFBQFC8P1xNmThAztU2DeHnIkCdcgtmm1tVQNNbLCB2Dg5Afpvb9r48VkAUZLfUr+xBQCoPv0S9K0pAg0vMN6t9WEBo9OOQHjFTQNlSFQ+x6FJA6GkWM49MJ0AZrC+GblomQD8+VQO8kihAkBp7TYzXVUDMfjBro/9DQAedenVZqzdAbLtEexYrO0BFCDnSvFEzQIpOv7AJg1JAOEt2R9Q48T9NJguCaHlRQAOGfNlCPjpAmMw1ix7NRUB8l4ETqM5SQEo4cTBxsUBAvQ/+ZBE2U0ARimobzkpTQB0OVh5cSk5Abr6wUGBPSEAMJEnnJFFBQOnreM7/p1RAJF1W5PsTREB0QLKq+ZYtQDr8NxpAkzpALHbnwtoJT0AOwd+VU3pRQLq7NVJjb0xAMT4My/1RUkCSzyu7bRJVQIrNRjCaeiZAPRsm3J/7TEDpfm7XD3ZTQD7+4cFsLVJA5oT9TmrzTkDPhKXOSBdNQMNBfTsqPUVABD74t4TQQUBl9bqkYGcgQDPIhjhpCExAk42Zk9zgO0DS4BU3oulLQLmcfr90OVVAWCmu5nv0QkBEFnpjfhEzQE+WiNqXz0lA9NqpJTHmQkB5/UDueLU2QIDEcmVr3fI/eXblte9lVEBJ9J4iIAlVQMu6Co1CgCZAYmgMXce9IUAacaZQ5Z1AQHatMHHp4yZArrU5kvhoRkD67oXx4dBVQOGYRtsOazZAnHXaVu9DUEDMk3Iwt4ZGQEbOfUIM/U9AXDaSvCrTM0CsmHo6GQFMQMJYYDJBWFBASMTvjhq3UkDufIkHf9pDQOXhfs3FEVJAK+PbmXxPUEAdGw+J0rFHQNwKpEhE/0NATmcwhhP+VECbfVF/vAdPQL4H/ucPB1hAivLa+lj+QUC4wc9ySeEfQJiZZKHAxlhAPPkmxKlAVUDCtFp4RkdJQIhnDU/AaFhA6g/ivS5l/T9ZvQOxWodQQAX/6HQIGTJABVAUULp7H0CrSnIG0MEdQLwLt6vKoVBATPM8I99vQkD6hQ/guAZOQBrWhsMvGlFAe/y103JgSkBoVXN1iedWQE1g+tBMvkhAJiRRz7ApOEBlpOsiFUU0QNy6gasLre4/BmiXcDYNQ0DYvFKJZMhVQDVLDttXAlhAzKhBp8rCQEBgbvWntStTQMHcBhDIcSBAWHEevOGPVUANM2PH9xZTQKU/j++w7ylAJV1MzTRDRkDmiE2JhGIEQDxLL39Sqv0/Z5xjFjOxOUBHD+Zq3sJMQHKbbI5BXlZADSctyYEFO0AxHfquszc1QHldDo7TuDBARjm8LpRqS0CGRqqF2bNQQCtXIBhcCypAe57WuEhZQUAwkQO02d1VQM6f7oglVj9AKpJElLu+PUBwVPtJSppPQJ+pLgvGylhAeuZlDwXiUECA7/8BFjBOQO/Onir21S5AUzHa9rg8PUCio8xVAlhVQDDYv4ceZzlAv8H72A/zNUDQJNivKOtYQITNy08jNEBASNBjBS6RQ0AUtA8uFScIQG87QcayXSBAbbvP9NHJUUDSnJugie81QCJmFc+y+zhA8oLlGr0rOUAyexCoTFM2QCsrdyEbdiBA7ScfrbcjRUA4wPEJngE7QHg3kecfo0NAL+g0YFpLJ0Bxv7cIHU9WQEAlc+aZ6jdAP9X/HXMuRkCigCciahlMQDz8EvJGvkpAYqZ08y7nNkB03ooolfk2QKS+DOU3qTNAVze9jPQEVEA4pDBme4cmQDf8eMfZ51NAGq3jT+6tREB4pfovi0E2QEDQQoqgoVNAjNUed2VWRkCN6LWP569MQBh95ykYlFFA+ued8hVpUUC++Oyt6RwtQAY2SvbeN09Auz9SUumIM0CCODaz6DFQQE/497dWkVRAAkCdclxXVUDlYLCkqeBAQGjfi3/FPjVA7/VL6kG2RECNfaejygRWQHuvg792LVZAt4uh6XrGWECV+W7G0fhDQHgjZyOcIk9ABUvED7/NIkBXMvOLYMRWQG/ztJmz/iBAQli3xW/GO0BU5XaDu9JKQIStBF1U6D9ApyMvJFcnM0C4aZpEejBJQGEx28C+PVFAU5SLiwsDUECglI9Mi2g6QK/uVF51fStAf5hMTNEOVkCv1TI7XTVPQDXaVSi/8khA/2JOOnIpT0Dn/11xxcswQC5vTCrkvxNAAH07W4kHQ0CJ78+Rx5FWQMKSp/sTfFVA/dgqJSv9TkCxw8ezzNA9QHJOEmurmFdAcH5+OcL6VEDcyBSkPU5WQMg3BBG8pC5AIX58sWAOVUDIB5cGgThWQIkwKsWn5jxAAkgDE2pfIUDq3TFrLcYwQHrTZ7eeE0FAko1eufY2KkCqFjXlWCBQQDA4RZm6nEhArInO0kASV0DuKFcSi7BUQBeWB/7NGFJAa3SGs1bnOUDZadr9vQdFQGoFXABUHDdAREDlw3LqQkBjvYfFrx9QQB1fj/rcgUBAKcG45m8wPUDcpqbDoq33P8q2WgWEx0FAooBkSrTTVkDEGfaSxb5AQDc5VcTL/wNAogb29HbaQUDyDaeIXZtTQGtGMUq/X1FAiKfOeZ5sU0C/n1bqYZRGQOR6ELM5TVhAojomiUzvRkCmuz5EzsNSQPM3bmC3Y09A6PXEuJxTUEDiM3b0RQVYQHB6/fRmHjdAyy9PBg7rIUArVEUz/+VIQJPNPtFpHANARxTARjIhGEBeDfzBkXFIQMyQt31nCUpAhpUsACb2UkBetWik/C5LQEazb1lIE1dA41/AZiK6VkArSer8e/BKQA5ix7ucdVVAFM7qlvcVPUCyavYbySZOQMfR2znNmTBAU0B1DkGUSkCL3cKGlbVNQFv9Mw9FzEBAoakQKxZcBkBnn8SMFr83QDKy1ErmWDRA7BlMkWAhUEB8wXnqHo8EQN5qlO0XLUpAeD0JMrzrS0CBA06jgZI2QJBhcUUqLENA9aMywV1rVEC1z6t5L/4oQCsR9o62+k1A3nvB1uOQJUCwwYyAWhRXQO8YuzMDe0NAgolhe7KlQkBuTPI4o+Y0QOpEIgZUmwhAs2xpgkXTSkCDSwpOWFkxQKzE0kdpT1dAS7XfFanpUUDp+eToetNSQN0Ly8O51UBAGAN1gSUSHUB+fKZ9uoZLQC9Hl0rv0FNArEmdPi2wV0DTJNufck5RQPWoWqr3JD5AYjPOBopXG0AOAb4bZvwRQNd9j+abjCpAZd4fuyu4OkDTrCKBHTohQODbRi3XoE1AKcNe9c/wVUBMjKYV/P5QQCAGmAaLqTVALMBz/K13TUBnM3xzuMEyQMaJSngpMVJAjozXpa9iO0Bc5WeiEPFGQLmrUcCOFUNAOFHqf9FkV0Btg5Q26w5TQOv2fDkhAkBAwcf2qWqlG0CiHgDmh4FUQCiI7FoSalNAUDyOXmUeV0BuU2KQFC5GQDtrzQxqMUZApZBN0H0TMUAMlorrhs5GQKb2Y3+dNlJA0kArGYonUEBnpkE9rn4tQIA5ElghkVBA4Lf8V6iPTUDdFd3XgnhAQFG9IJL8NVBATKGMjGO0+D/N7Y4unPpWQC0sS+nyV1BA6P5brAmsQ0BM97S73NE4QMOGf5vbtExAxn0I1tlUV0A2B3akto1TQCKYQvVH4zxA4Q8E9hA1QkAwPSkAlBxNQJAs824/ff8/uhVwxHzk9z8/08H14hVBQJdzC6AV7VFAcUO6+CcFVkAvc2w2yQ9UQC3ShdKYsUhAkRM3f82mUkBMJif1pvcTQIQOgWfg8VBA1+HpXHQZVUCd+wst7yBYQDqyIBQewUtArnk7kbkIJUCKPRgmwMNVQJK3bwnlW0JAxG1yUtLbUkArwuHkVNRHQMEvGBHvmTRAfbqOIwP6SEAjXfAeKI1WQEGgwCIGz09ABVHqn4ubM0AZg7IUJGJOQJHStG1LYS5Ahn1RYYC1RUAcL7UwXtc/QMPgox1CIlZAzoQ673iYGkCo/V8n94tGQJD87Jg+aFJA7oIQs+nwVEBeZDkB4w1QQHIIV2mBsylAmq3oaYxZTkDVyqynRowmQJpqGrsmPR9A8xxxAMhbRkBBKxwX/yFCQBO/KbTY0FZAVL4B4cR6AUABdwDwRmI8QJq6g2OT+0lAphC36DTtSkAIbyftZLxUQMEBjYiRCDtA5Jgnr8FNBUCySMN5ra1FQJS7O0tgwU5AZwI6tLNnP0ARno2j5ppUQDWlpsmX8gFAdT7MnSLWTkCS6JM081tAQD29jJZRVFBAoj5bbOEXVUB7PNjXCkdYQOMlQk9CFB5Ab2Ztn2U1VkAFfg3aBY9VQMDQ8EWeTEdANi/rxdmZL0BNqQrosN1JQDg8XUpgNwpAnIaSYkpsVUBaDEE0pQUiQPY20ItSpkhAyHKROS5oWEAwQ23/dNxHQOHEw7YwoVBANYlgj7g/REAECty5HYBAQCX+lmMTIjpAGssXXfyOT0AmaQ58DA1GQNlzm//znlFACrdZk2S7G0CBPjMMT9BXQKd5O+Lhp1hAJh8iJUz4OUBpoAqyR4MuQOHSojr1Uz1AP5O75vctM0DcwMDTSwgmQPv1kYDQp1dAMH3/IL1APUBjT3Etklo/QN7waZHZnklAR8jkieD1MUBlOlClKFYzQByEt9n46TVAUMKCmGxQMkByCAf79ew/QBsKIdbkmDNAiX2s6U5LUUAapPjBfShQQBO1iIDuKi5AkELAKZ4WSUC4UIOw1BNUQHTmNr1SuUdAiiisM1QhT0Bez1mFWghQQHa2nfk72kNA9MRumxJoUEBuk/A1np1WQC7BwQtesUxAGQnoqAzpUkDVTuJWPlU0QObz+5ct3z9AYgabFjiUTECBg6Gl3q5AQBAePoPNfU1ACVJ7IMbhBUAYBIELK7kIQIyCoIIMdydAHZpDIg4/RUA+qNf6IgA0QE1PM2U23zxAVARlQpJ7SUA9DHg1gQkaQKKHbMFQzFJA8JG1beW3UEDqe4CgsbxVQKZsuaGIMhpAZTB1EV0rGkDHV8SQ38E9QPrZiPCelDxAyQIhE6jyQ0Bh4krFw6A2QIPTheOEEkRAdPYizL6/V0Ay0DM8YbBKQBF6BsKVaExAWlRlrCt0UUCGqLyiTW5VQOudNqNrxT1AKhVbcpaLV0CeqBnOcYxQQBWYJijOfypA+v9Q1NgNUkDkmSP8tFtXQC5rJXSCJx5A7FW6FR9TRkDxAMrHyMoFQFlqBjLIj1dAgxfkOnzND0A9lybKsrcrQHBkjiCJfE9Aq7X8VEH6VEA1DOu5j7ZWQF5+PDwZhFNA8sLI+hk5TUAxWADK4k9GQPLI83sx8jFAyPUhuPl9KkCLtmTChDBLQFxgrCY1eFdAD50Mx1UaQUDqssXkHRtPQFAszcUqnjxAz9y9DDWZPkBFZqaRuTJMQBI8rRzx0ldAihzKIDFEJUBC1Qw7zCkyQOdD7Dd0CUBAkCKp9R4fQ0DdTqHHEAYkQE49ILq4t0VAOu00BuoPUEBYe/RKu1ZMQDyQnBAuIFZAe38nochwNUDf9vMXywRHQP3RRHqi7kNAgU6KOvQeSUCiKJQzgYwOQHsqnbrXCD5AIFlXgew9MUD9N0kRf2FQQA1S7lCIWVJAopPZM8AwNUADdslC52lTQL99xg1j2gVA0AN/epX4VkAqq0dTGBlWQHGJ+hTVsFNAzoXiuBLnQEAkHRb2mHlRQPZfIWQcCVhAM8H7U0k1QECHvAVkksM+QM6TACdElR1AzxWslJ52IEDdfXwD2dBTQBUstmjiwjpAgdMj6RzcRkCxB6ZGJsEoQB89cTbk9lJAViKTCw1HVkAqtd1K2ZZYQDuZUdIgexFAOeZkAjwRRkDk8FK+4aFQQEkQntfG/EVAWLaAxFUwO0C1xFW9SH5BQHhyzrOCWFBAw5YzY5zXR0AxBnUtaIpXQHpx4aZJL0VA3MhEgbR/REDrNqV4MdtDQLOhhRUT+1ZAzblsTe2fVECJal7cWCFTQMbIh7aWmDhAkGNHEHmxQUCm7cSlhTYYQObRd0QGIU1AYHhf+mdwS0DZ0VW2Y9RHQI5IF14YFShAm8wZkOeuREA8oSaqbc42QGZ+1XC/IVNA9UQCCmqAT0DfTooDc4FAQKyc754cElRA1+HtPoI+SUDZinnjn4FTQEV92ObQslRAnav8z5M0Q0DCpLHGMI1YQFoIM0mNo0lAi2kJq64JV0B1MgFL8uxXQOOh/MRAajBArdpqTgIjVUC46W00+65SQHJsAnbk6VZAqRxtXffdPEDqTKtyFgtIQKmsyWUJgE9ADtDPddXQQUBSSO1LksYxQBlkt6P5DStAgAyglh4qLEBdJ3hYBUwTQCbjbNe3sUdAVYKkFt/JJEAiDAvFWmJJQJ9F8S6QAkJAL3ShpAiHOkAk6kSCNP9NQDmqtmmxZkdAIj9Wx7iHUEALMp397llOQKp8c9r/UkxAvD8KPtzYPUAzq7eXBjtFQDXRCpOG2h1APDGZq2qoI0AJgi01oWpDQHxhblm/q1RA+GA7fT6XVUDRkNWpHU4sQOE+ncMzZyZAv44DmVzkQkDRn76iSQBEQFc8pQ4URi5A1u5Odd4nU0C46xckKvYtQPSX9a7vzERA7+6Kg9oAQkBAAtiiKmJQQD2XcvCL/jhAnILpQUd+Q0D86vRlTFVPQOSxZJ21TilAUkcyAUeAVEB6wcfmVDtVQEYuMhuApUdAQUnnPtfaUEDiqrfzY2VTQAUvWSsf71hAT77wVhQPQEDi+wts9jtWQFpDPHQ8KERArNPXsFNaT0BPdc/073BRQNgOupEEQjpAfE9Fhp55VUCtViKbB/pNQIwYS1VOiBRALLRIxZXiVEAbunW21pAjQJzOIMNKDFZApzNR1qetVkBnHZdpnMMfQLTU2YHljj1AiFk0wb4sSEBCCKL4J8FIQNMGKMPY1CNAvxgsV/DdRUCWFxD7vFpEQGYNh8o8HEpA3b/c2VLuVkCyDr1ehbVDQHQuE3M/x0lA5O+uceI7VkAjpdn7rfxTQDQVaMrIFitAUpLQF8q1UEDCYkq/1HfxP8AfAL8IUUpA8FlFM2f0OEDRrxpHHsBOQJy1c6gAMkJAz5mEA0pWS0AxhNVCaLdFQI4QQfeznENAhvMkXiEeVECckB5biEI6QAA7XfZye1ZAKoUnVO/3PUCbBfNwVzgvQDdfGVkwmFNACSKYRuV7SECiVOQiZd8XQLCvbleGEjBAXHhvq7HqUUBkTg60q5UzQLamDBk04P0/MeYikIUcTUB+xxM2gEdAQPjabrzNSCtAPao6+mgFM0Detg8W/aJBQMPvG7gt1ElAY6EImoizUEBAhYsuU6FTQMCDHA0WNENAbt/pffZEDkAAYIvMX2FOQJYSKmMflVNAVdZ2J7k7OkAgh2GOltBQQOshlpSNb0JA+ottlYH1TEBaiHCOi11EQN67UmyzQFBAwXJsCkFfTUBmIaCTThFXQKqNbU/u5FZAfQSyRFykV0DP2QIa/09PQBNToVDwW0VAhMgN3mx5T0D9wSRbqRJDQN+edpWrIz1AGIIvZqZpSUDL5eYNegMlQPF2IBhlcURAld5eCDQtVUBIb6IYR/5GQMy4rspbAVBApiDs/eiEJkAgGt+RCaxRQIfrwolpgUVADQE79JQDUEBh3q1EICJGQInbZAoKpk5AabdWXnVJV0DTBFQsfd1JQD2qxrOJiFhAH7CmJ4DJUkDRSaYDllFGQHGdpY7yg1NAzI3FUbZWSkDEZenvNv5YQBa0oFCJA1JAh/RroUOLVkAgoxGtZrVGQMceoNrc8lFAzEohdUlNFEAO3gXiUOUbQMr7UTTGSSdADmjnaRzLVkAg0dqigUJFQBQ/LBJwWhdA6ydeF5MbRUCMzAFpnWBDQAyFm8kwZ1JADlhsbdhEVECmAHsoT1E1QArKSwD+ZRpAoshtOMWaUkDaeDAYvfsxQKC5pIcSSUBAzdGvJzV8P0DCx0A3IbRTQJUu2jEcZ1VApX0/Evg8V0CT3RvpsfRDQDmFdhpGIVhAwiMN9YW7OEDxv+o8pA04QPNH/qYo209Ay/Hi1xI9NEAQ4KYR3JZCQNc2xXcXQEdAVnXx3n6gSUCnSafmUhRXQJqnNAu8jFhAC4azVVgCWEAyR43JrfxPQN3YOScgF0pAjHqHooXtSECbdHv7SqVXQFmK3dibe1FA5J5ywNJyO0DKM8qtq1gvQGDLfGInflNAoyFk9fGJWEAeemsbUTr0P0vsy2WOASFA+TiPvsEnNUBnzq3JrrNSQJ1dPWCKkzJAmimv1NNmUUC7q3XLg1MrQJEVqz1V5E9AQ4UzoqCJRkCrXjrUgFVYQKDdGOKpXkxAdHqmjjqtTUCu+G4KJItWQIg4s7Vz+FdA6033rH4fN0CdNBKEjsA5QAykRKPpnk1AmrWNPj2iRUDq/fx2Gy1FQKR4eEorGUNAu0dBERn8TEDWM9df4F8iQJdpDfLjTlFApUI+od8OOUDr+gR/629XQL/1BIHoikxAv/lVWrUGIkAo9ElYAkpVQIddU7URXldAatfTI3tCTEBI3wSIG0c2QFcH8eRVKSFAN0asxWxnUkATCfgZvpNDQMIERiaF+VNA3qibwAOLVkAQPIhbAUsXQHt4icZU1EJAuZyJubHSWEBffDa3OF1UQDvzpRZKQ09AUFKW3ZcBS0BY6AkImENGQB9mHUfnFkRAFqGwb0hjSkAQqoVYnnwkQA555nbIQ1BA/gcKHzHYVkClm/r4/yRXQOZ35iVn7lFAtN/BY4//VUB12cigZuJEQH4bR/AePx9AMSuLnBUWUEBGeD0AwK9EQH5aDmJuvUVAgAsIfDqgKUDQ9yMxysUyQAJHuWQxl0RAqhhi1JI0VkCpwH7QLo0zQBrcr1L59jVATvjWY875PEDDQieGAmBAQPAYU4ooqlBAUg8JjR+CTkAq4zmLr0FAQD2ZaoN9rS5AsUSQwY61V0C5rX73y+tNQH9tBw4aLVZAPEAnrYOxQ0C9Gu/ZLwZVQKRYCoaNckpAoasnb1wBSUDUBiTVsM8EQPoyv7sFM0dAsMAiLIeNMUATnvw6IqMqQLekZHE37UlAzSDxqwvmQEDGj7CoFGFTQFk1/VEKQjZAzDRZ5NbbN0DDz8MowDxCQE3T6ImG4kBA7Si7J5V9KEA241oYBLo6QKhvSPKvvSdAvw30u2TMRED+di8bgA4pQCtdlToCw1hAJL5OXyVXFkDGb47wPihUQKHKz0RPuldAdFWHS2taSEBIcn8ol108QJIB8JTaQVdADXgcWwo9UEDnfcWWdTgzQBMQJW8w3lVA4spaQm8KV0A69X+BJJI6QGyHjyxIOFZAPR1UrzaqQEA0Is+9c1dWQGkL6b0aVktAWl/Nwe13WEAUKXVxyxpEQIGW6+nzc1JArzNXMjpeUUCOtUqEo0dDQCasnPoZsQtAZS4bsZPrVEBU8oOGyAxCQJo+sbxuGFhAcP8pvmxFVEA4Xsv+F9VMQNmcBkDBd1RAZuhnKdEdH0DkDNrPIcUXQEn+IyGz5jVAufxAIbTDUUAZQKDnhSgRQPpTekC4OTxAsB2JcfkpVEBgKPkbwH9QQN7BNIICfzFAXCfHINPRUkByI9yW7d4YQG5Xu07xAz5AVzJSD+C0RkA0U0uMu5NEQFHib2oR0R5AgOTAEzcGQECjESVtihFIQG+uEtzeK1hAak7hfYB2U0CHXFG44CwtQDjZ/hCyyEtATDeMu7axOEB5ytXyTexVQKG4XsOgDidAmDqZe+m4SkBi1kPRyJ9CQG+1gHEoB1RANrgeUDL6VkCuyKMKsZpQQN0lVKi/B0JAyG6ICTBnVUCprtvZZ6ZUQGLh+9+hl1ZAUn93oVR2JUBU7IQEJMdYQDDc9iDPXUtAWm0ZG62rRUBhqN8UbxwoQEoDUcYbOVFAHFvh6hXmSUAfMRGlNtEtQP3RNh8nHUNAevHXON43VUA0zWkeDb5LQI6cQHhXektAkBwprCyJMEDr//qifMdAQFSrZBomlztAaAFZKOnPMkAPXE/vS6pXQC2qpG2VhFRAAqY+W4AKVkBuUwgn4ZBRQP8IJl65JVVATvqgj7TcLEDSmP49jiRRQAM693F231RA83rwbTRLPEBB8lPSV1hFQP4yvldDxU1AbpWMoHX0UkDjUKqk5LdFQIkoQ31R5FRASS7eow7BSEAzQn98xmNQQO9djfHVGUtA4c+UYSphQkD7tNFItdVAQOPPoM5qfklAALrNCW/RNEDCusv+bPpVQMjqqX7lu0tAU1nckdwrVEAZg0+PiwBRQK3HCKSFKVZAm7ENglExRUCA0LCgRUZUQFrDagm+wjxA0jc07h0vMEBOLP9wC6tYQCenmwTOHEdAhc6n/BnnUkBhjdgHRt9QQMKXgzxV9D9AFnkG1c6ZUUB7Tz5r6ElDQF/9/BNgTlBAy+Gz7qezWEDISdquNq1PQHXrmy3p4VNAafvLx3afTkCXq2qlxxFSQNiFhQZy8B5Aq/FCSpq7T0BEEDcx7NhKQIaklVwd3VBAYZBmAk0xVUBMriCZFH04QAGptKWQglRAhHTFhcL4LUAIn0v3g+hCQEHwH4+1wUpAc7yA31fcT0CGXpKImsgxQKdwdd12/U5ATDmkX9gcVkD0mjYmHzJWQDVwyTmCVlVA4hBJ+yNsVEBQLoCbuufIP9KKI6CD6xxA3jJoEwegUkA/xOz1ij0yQClHlEVyMzpAjAYuXxfyRUBP8SWeCOdCQE6pIh8+dBJAbYpUJrM6REBZ9v7xMWsNQFX/MIH0k1dAdpyJQXnLLEDWTTtUkG0fQH0hoDD7clZA0Y3q/C90V0BJ3yn++ClCQAGQSfCYxlRAKDTvMK+QJEDAJSdC3A0aQBJZFnIuoktA0PLFLUhEVkBAAksinPZNQED15BJnWkVAiPUCyP27V0As28zuPTRYQI7YPjR/CERAwoUq1MLmQ0CjYQBQo2EzQK7idMyljCtABr2meDxvSkC5SDZu7iVHQGQW5tVkzDdARtXZSi4OUUDGlr6PAwJRQOjHtYeg5E5A1a7VPIY8TkCC8zx2qCZAQBiwszZ8gVZA+nimZgSuPkA9BE06r2FEQBH3LjHzE05ArsATcqP+V0AC89A5sFBEQDEel2VrdlZAhO4/p+4RNUDcN28LPyFEQI0M6fVKtElAe3Irh3FXVUBlfSSFP8NRQInnx48HN1BAw4kb5khpTkB5ptC+IUpPQKzEm7nNpERA86mm8r2RS0CKCnmRpStBQEyHTzQzUlJANMYwgjRNP0DZQV6O945KQJqGlq0Dafo/Izlw4F1pTEATFKeNddRFQO+4kPmvMkpAaF8LEy2dWEA7DLzpVslWQE2NllgEAlFAXj0RxiyrTUAwlSsIzhxDQKQvcBOVzxZAf3ITjoQBQkCiuJ5yeolLQPJE+P75zFRApPtWrDqMUUDVOS6xkHg4QIF93fiC31BASs/2UK88JUDzQ/YrVvpJQFvxBVksT0lA1hzD376RT0B6eiM8Gz9XQGdXC/SIGCRAlVHTgSKIQkA8nTRKzO5TQNjQmcPDllJAoeLIPiTXVkCKln1p9HNUQHgVOjxS3U1AmHIxOMM5TkBiPdjNkuAgQAazv86p1FBAxC1/lGt2VUCkQlHU4pdWQNGfJo+bj1JALIbgxaE5L0CfG3+reYxAQPWmlc9gYlhAAen8i0GkUUAZ+Qdmrj4pQD7CY5n1MVFASutL+yMyOkAxDY0+Ig9WQMdrIr2JlUBATvY96sr/RUCeAZbngMpUQBj+j5yUTB1AmFkc6fzmUEAhKxbLFXklQBOx6ugbr1BAnpZNbXH0VEAxg+zDaNcqQA4tLwELmCpAhWpJwzU6C0C49xOwPrc9QNc9rXMfnVNAsW/vzAbDLEANCHjcNGhXQGrImeMmM05AcGfV7oldK0B8vvF06DZPQJMP+0XL1UlA0K5z5blsVUATbfN7xyxVQHxMlek6j0hAJ8gfd8ROWEC2kU7JTTJOQJ4nDSUos0xAnflXepRiWEA2FkoACjQ4QKjiW+yknDJA+7IoxZdWNkDQm6TRYYpXQA2j6TXjDlNAenuErACfSUA6FhDikjkjQFydJauDESxA3OM9sPZCL0DQP2Hs0PxXQJ5IW+SxDUVASTXBLLM2VkB27/iV7/pCQGfgX8tu3zFAYCXna8ZFVkB1MNvsm6RYQEqwB99xnEVAwvARW629E0BBghkCvjk2QCNJgchHU0NAof4WxZpoQUAEFF/Qin9YQP6QAu3jQFNAkoEY+bZBUkCpcq3pY10YQAAIXT1dqDZA4YOkEm26SkB6j+9XrA1NQFYWdZgopU5A3aN1n654VkDGPTecs7JAQJmLvvPrJlZAuh6IxfYhVUAiQsCaeD9KQMX6hG17rlNA2pcdfhyIPkBY8b8435dAQGBHRja9BDtAn7ssQ13rQUCy13T3csZEQN3atBHU0ytAr4+DpY0+UEBDChBMYPAoQPaeALsMODxAikYwYJSHTkAhWw4ZjzNTQITVBPD3O01Adnu1B77JG0C7YTFjv2EoQCThaVWRZj1ARugSmuHBMECL9F8FWpxQQGjbv7wY1zZA6Hnyc8feUEC36G42iUsdQDL+M64qaixAoQCmCZPuOEBW11OVIpw0QKaxez1uZENABF+S4Yer4z9aUfBGwBs9QFSqQjXIN0hABVZPge17UUCEhb7xmVFDQLSGWiWb7khAqF8BGElVU0AIFORYlRwsQKdzppYt9EVAZ3gvHj8ZJUDVhtZ+CAcHQA5xc0e9+EBA1sqwA6KHQkA0Xhp0n0xIQMr5F6K9ZDpAEpI3Bd0XVEB8II4It/Q1QKid3VzzX09AIWrOpPaJQkDDsN5RYvFMQGYs+nL8qjNAmoxZHUAlRUA5nMkyJG4yQJYYy46WtEJAwzS5M5/APkCQcuNpPeBXQAAKuQvf1lBA52hUstGgPkA+fHccLQg6QEszsjt6wEFATqRNhZIGQkBT6hGMUANDQCfbEe2yyVFAqcb/MIqKVUB+CUTVDAlSQEivBR8RDfY/793iJh0OQUC+fzjAzkUgQBpQqIqG+kJASIOomnbZR0Ca8PDGzcZFQKYqOtloR1dA1S7uQJiOUEDya1mDg2xXQHY2sq8O11hA3oV+Wq2iT0Ab3RpHIohKQHbMB4bN0VZASxzWuX3TU0Ctp2ZkY2ZIQN0di1Bp5zZAoS6z/ug5UEDlVrYY1r5YQGDgCD8wtDRAbiW/g91GWEBkcW8DuHJXQJiRvS4U6EJA0gjDYT0YRkDIBXuCmjE2QCwSzSmnTFFA0ZssrRs1TkDW2Hn7li5VQJ6TkyD9w1BAXiW1YgKEJkD0XOkgQvo6QLdJTWD8jVhAH3M9lmKTOUCJMFGRDn1XQKQLg6FArElA8ExQrQ8JTEBzW6ONVBMGQG7Ikk47aVBAZhkd9ex/9T8ytSdW2WohQN37VKBenEpAeReMSpIUQkCF2JBkvnZKQOR3mDJjuDZAxInxO/e6JEBq1c0LdJ1IQPAEFOWLQjRAKN9RgeX7REA8HmBvBa35P4w6E5E7v1VA/5/myENuU0A4lqXRrLhPQGmu1E62xQFAhrSIk+oGRECCa3zUDL4uQGi9JS89jEdA6wfUUakCUUCzTngM28NVQHCH+gqSnjZAbUEgwH/TSEA4kW6KgvVYQK+1L2gWLSVAthokNcDbTkBweZacUz5JQBErYEb8ykNAarmkh9x4DkCdFjy1whBGQJM9LUHLHyNAtcWGG18GUEBAFprx5sfZP9YTu0PaO1FAayWV8TeyS0Byz8B7FpcFQDM+5bz0EklA1kQBTO80L0DGlwT22ltKQJzIr6+Ls05A+KpFM6+eTkCQhbY5Xl1BQCHgwK635DtACD5BNAZRVUCGW3lG2bwfQGQqKW9jgi1Auqd0reGuSEDJinNf4XpJQIpkql7VQ1dAD4jlI6AxKUB+W7yf4d4aQDU4TqJOf0FAIjTU2T3vHEAyoacNSbNIQOLW8CPMj/c/FiuMrzyuVUDskkuvnKkrQOTtTNrUJkFAAOC2CXziQEAFhERLscVTQBxwUsipeTtA2rcXy+BfUEDJRJrpCptAQH3dnlFYWE1A+lQE4quFKUAqqS14ydpRQGAPJP7mYlhAsDZ9H9C3RUA4ANKXRERHQArBFPCAiEZAyfaQQPh3T0AwGGrk2XRNQPvDmEgdFVZA/as2/PkPU0BUTugtH9FSQPHHRcSsslBAPi6uY7gwPUB9RI+ygrtVQNsPG19aKUZAXxoKUhvPU0AVqiph62lRQKozlbP3vFhAmXx+dop5UkCSEeKxzWhCQH6xuKu1vldAW+FwYzTIUkA+02UlRdBWQNyuzBQFli9AwabGnv+DTkCfYNSrMQozQDPk5sFb7lFAmN5ykNvOUkBtknlkK7ZXQHl+5PKkW01A1QhW4F6xSkDGEGUxIwg9QFz+62U/K1BAWW3ukxggJECDhYtGSqk+QOSIG1mvfE9AIrB05cayVUDuW9BvhqJKQOYhv/vWV0xA6K2ZCk/nUkCW4G6voGchQFPUx04QxVRA/zUbxM+HC0Dr71h6SvU6QGAn04y77rg/sDSaRYXxDkApTHcfYowqQGo7b0olTlNAI45BIfo8OEDSwUH7pZBIQLTANrFGFldAGaGFnTnTTEDVDC1X24xJQEYZQktt0DdAHPIqItlLWEDwsKjVSB0WQDjUtfeKO1VA1vyzF/jjMkAeBh5t0U9VQHwNFapdFklAjyvp/07YTEBMtoznbdZUQLgw2OP8vEVAhLIjGnyiMkC34UwZdKZBQI9Eqx3wAFRAn9I0cyvLRkDrOm4Rfc5WQKb6Nh+NDRZAADdW4tqfPUD3EwIFAz5KQLGTtoiihlZAhJ/8XIlrUEAnBxn2wKBQQLLFApZAo0lAzR9YEHHKTkDq0gbzuUtSQHLkfcnwBUBAL1Li7xwBUECYye+MRKNYQIQU713SKlJAaNKWw8rdUkBKchwMLiZRQDREqmrOqVdAxNKZzAqGUkA7s9edxm5IQG94vdJ7L0RAlwQc5EM0OEAIXdJ5z7hEQHBVXsWZZExAhDC0EzLlVkAOJd22xdEXQAsofErqYkNAVkkVSgtDVEBDRiqdUW1HQFXOqBtNS0dAZC7zyR3lQUCjsGoyp59BQMx+sTucxzxAds1hgQ3UQ0A4BO238sUYQNhU6+jdkDNAVCmjM0H7UkDni2Uv2qBMQEWqzM7BN1FAsBrScCbFMkBcjIvaxRdHQGuYkyJ1LVRAnBwlu+1F6j9XK3KxLVdGQANymJv32UBAkWRFcMwhO0ADy3sx5DlCQO9pcqpyKVRAIcI2Y/FxJEDj+E4lb7VAQI3GdjTBxjBAB3GWXv0dSECymX4qAxhEQPEV/6HjuzRArr4w0C9jUEDjJiKV7EkSQJtT+J0PAUlAC3mmnuEFREAnZFRS7BA6QI2o/NkUx0FAnaNBYq4nMkCDHS5qq8FKQKvBEPP9Qz5ALnHwDablOUDAUPnBtl1EQOtXYPag8VRAVGVC4f0cV0AcApqeL9JXQABd7JNzNRdA5ECw4zgxBEBi10BUhXFBQMDG2TbhnMc/GuRf0l2DMkAaA5SfKRj9P3c6yIGXB05A9wUq0V+jT0ChoAwyRZJPQFXY+OFPc1VAxMqob8vNRECbv2bY3V5UQPM2cp3iLTZA3wXabWCWWECpOQEpneBVQN6M2luMw0dAprXOGEtNO0C35PXpvhVXQB7yVxPjhzBA78vKrrBKSED0HNmVz8hUQFnvDwQvDEhA5jjtCiB3RECyQGUqlX0mQECm76hbIkpAhaaw1r4jV0BDF3ydAl1EQNL8p6eMQTFAuOJBmeoSPECe7+Ju5DFXQJAX2zT8flhAMO4vLcgeNkD1lmi4ypY6QGKK5S928kNAtfZEhqGeKkBXMpPHrp9CQGu9fdqnagJAVzGiNhJpR0DARiKsvjhWQIPtu+kiflBAHhRjAP7+RECFDb+3ixtWQFZ9KrZD1ytAa+qgdLqKVUACIPcH9BI4QOFokiABIFFA/D7YNbCIJUBppcrmlVJQQHPcR83QqDxA1Xy/cVjnUkAIcXQlwHMyQMzvD3VMc0tAc7uiQ8jHWECWhVBIArIqQIypvs/kOFRAEKyi/xd9WECclGwuIgVIQGddwQH99DtAkjCrvux9QkAX2Esh4mY/QMDkBB9Fw0JAnUnbT6eSN0DHpo1afhBRQP7LZd9NvjNAW56mrzBTKUBUzgZ07909QBpZ9Zrc7VRAhN3JoMOdU0Ddq5cGAfw1QJUfNn5lfldABiFWmFJNVUBLDO03j29TQLmgZLbfWT5AQ6DdvyZRUUAIo1NDiF5HQOfhcIIE3jVAmnLlYQMjLEC9yJ/lrN9BQAyYAauAjVBAvitugd7sQkBqVKmpgbhQQMv69svhiVRAqv2mMFxONEDGkI50nwJFQJBOUQ2zKlZA6l4V6yoaOEAMVDrQd6JYQK42JRUSD0dAehm9bnpKVUB2URya/BJQQNSaGMfLLBBAtSMBdaQLU0BhZhUuc7NWQBAbxaC9AUdAUquwxQkQH0BxrXTGZWtBQJH2xklfAVVAoqLIXBAvHUD2s5vS9OlHQPc6R4Tzb1VAq9QpHln2T0ByXqH45zpTQLsFFTUAH1VA+XpLNmWHSEAmqJBP/RtWQOpFPU17iUpAZdXnVRfkWEDT3GKhBW5RQBJQnMBpaFNAQXqbG14KVEDM8vV10S1HQIGSB8rRYlVAEXA1KaQiKUAyGF/ztic8QHRzjOqnnzpAxCuxhoa8RUAhzWJ1un9RQIg/Y3uP7yxARupfXHVwVECYKoXV7LUXQGDsLcaGSD9AXCbYCzuNUUCA/NTWyhxTQMWg5ZXNn1BATDWfNSXlOkAJzzjl0ZZWQFRk4OUX/ENAgZb1ICN3UkCOh/eZOWxOQBWOl5NwqFNA5CNgOmMbREAqBkKG2QEmQKRlIpnodSpA2nhwLu55OUAwymjyl0YhQFrqkaBJpk1AyKgV6RrhU0Bmjxjo7pFSQMZ0e8rRAShA3khLBsBmTEAigdwCE+kwQL8FIbbLr0dA+16IejJiTkDWhiJ91AlJQMnhS1UH2k1A9jc1Av8pUkDUdDH/W+vxPy75d1cVUi1AmoICq9mAV0CAKI7jhl5YQO8Zl1PEHkpALox9LE2pSECqr1dlJlBHQMgpPzW08VhAILNf4NVSR0Amsv5GAyxLQHsP55HLqj1AcenzwDWiR0Ad0azwS0Q/QF5qmPzkGVhA0GNYP3dyUUBGA3ggXao0QDi0HpTHEBBA0mg1GM7DT0BSvCvD5FpNQAjPiAdwBktAz+kxI29iREAcT9yHTlNPQFAgkxtOFkNATydGOkiCSEDQzt9kWJlMQKM6falwTkdACwQPo3PcVUBfsD62DjEsQEXY650OVUtA2+JSagjESEBIdY5yHK9XQAStV/P0rkBAOXLj1BEHKUAUZuXFv1dLQEpxpSKOck5ANOsOeJuWUEBcKhQyMwQtQHXH9Y8Oly9AFkyoHzyuKkD9frCKf/M8QFKBjgNcYlBARolJ9MXJU0Dm5LIPglc9QERnNTf1kktADvGdAcdkUkC3uzhmeQg0QAdTrhUxATxAt2eSuIe3VUCwDWxM0LlVQCLbZC++QEFAIm20cW+NTUD4TuBs6VYoQKpaxng46VJAMnXFqBuvQ0DACz5CER5YQGnN0UMPH0NArtcQ4+7BUkCeDY42pPNGQNnTjJHiv0xAh8pA8V4bU0AbKXElttxKQPRJ91gMmlRAkhjxVtpLLUBEjmXBRW1TQEz2rEmAClFAcBja3UPVUUA0tqdCcqJUQDpaEw7t+T5Aw+7F8Q84TUA7jHN+KsZEQPptGnpwy1dAXtQr6XEwQEAsBDw8iW9LQMDW2V9akTdAJM5LDCRJFkBpRGzO+BssQJZGwpfFNgNAG6FpKKh5UUA2T00oUy49QATxmXf6JRVAVp7jnNu4QUAME1VBdn9TQLTXZjSehkZALtC58xOESUAhk25EKPFUQKSiD9Ij70VAfZmWSd9uPEBsDlh0aCAxQLm1vWfyEkJAudqtMKUbQUAvhWWAVPkiQJC7CpyBy0BA5LtYML+BU0A0hz/KOW0lQCr0XLf4sipAbcpprA89PEDcSg0Lg4xSQF1Oa8XgilFAsobXZZMDTkDjqnm6TeZYQP6NxIouKUBAnpPweXPUUEAm2Abhq+NVQCOUAB4sqyBAZH/RdMKUUkCSQ1DSpiU+QPXa9R9X9iFAxxnfaphxQUCDFbd4QwQsQEsUXrtrJzFAJTPKyumnDEDhnK2zH9w2QOV4r10TGFJAoCdp1lvDUkBUFDBo8wk+QBeetfbaiVBA0UA7f7SnUUAlU2ngc5BPQKvZCW7FYU9AsFckEkzlRkB1TMok7WZIQGJ0LpzGtlhAX5ZIWoLuDkDHH7UAJ4JVQJJyvBPLJz1ALPwigTmT6z+Ef0/nc1dLQJJ578LojlNA5ieHvNxcVECGA2uVgyxLQLaUOlaLpgpAMJOPcgjgGED4tjLyQsRFQIBjlYbRw1NA937WG/O4V0ByOAD86ylSQJ06lph/V1ZAmRUmQkFAQEA4bLNFuzlLQAmnL0GmoERAD1QKOZRbQUCWlzxPeqpUQJzp5fLlzzFAzo6fCoPHMED4jW5QvwpJQDn7RMVU9FRAnFyOkYPHNUBw2RGrarxAQJHZLbngFlVA3cENXO+8PEAp4k4dUjJEQB76fFXmVVdA8g2s4yjsPkCxQbGkcJgiQPWYdbRoL0lA13fpO8fZO0B7v4yXinpVQHy49GN8VFdAZBo3GxjKNkAQVuaFLYoyQF5L974M0U5AuB0pgQoQJ0D82U5nNk1NQHWKkx7SvzVA3BbdwVyRV0CnC3V73i5RQCzySNX7TOY/f8SCraLoTEDVGOdLWthAQBX2I/7UyVRAcuLBoWjQSUD8kVX+B5YkQB7hfbpbazZA0nrkvOgOGkAIGBg2I+00QM2Ca/WqgU5Aap33RmdBTECKbig0RplOQCFEpxlbxjhAEKdF0baJSUBVqSA0RktKQFp7cYJi20lAs3NCimN1QEDgAgDJadRMQILhokwlqVJAMkPIy9eiUEBfvEWl4VVNQKa4Xs0g3EBACqXFHdq9VkCnZr4HBcNVQP7tC0sBsDpAsKjuqV4DNUBTB2646bAyQMSoNvNq60tAuez43PtpUECpRkaHV9ksQDEe1/mC9UJACdWC7/7ZPUCYUhRZhAhTQNCLoH5dejZAro6jMuD9QUAQ5Ur8PH9TQNP8byD/cCBAS5iH/XWYV0AJqLIEQTFSQD0fvgJNjxBAb7cJqxGmP0Bm0DMzTshNQK76/Xw09DVAVDjoybvLVkB/eooocHZAQHyvGZuCvkxA9aZOwIoWOkD859fu1RowQC/ounH4ulJAQRuaggHPTkB1Ixl7O245QItvrZHk5T9A/joOIlO0T0DfuhufXZpHQDykTbYwIixAe5dfcLFqP0Bv3saX2UFUQFHHN9nuvkVAi5uv0zivUEDnyiccTuVGQL2xZh29+jhA4W35l/rPSkBbQbLibxRAQLf7dmgiBzlAGhshhBF8WEC9yMJcEcJHQOKtFbqCW0pAtF3UHKDgS0CszWVbUYETQBkFzCvnHUhAqI6JySqXG0AC2QLR/LM5QDuIV8HztUdA/ZVozdEgTkBhNLWTrr1IQDtaH++JlEdAzyj09iShVkC6Gc1V0FFRQOmGszniwStABk5qs5hJKkAqS9kWYN0WQJCC6uyLYFVA0DsVUTzFQEAtrAec3YBSQLl4ZpLc5FJA2n5RURfGI0CGUSEdYrYnQPKS+RUUkyFAnXCaBxjuVkC255Zv5UZIQHpe7ZukVVRAIErdG1ThREBLm7pza11NQP+1ZL/i31NAkb6RMc+SUUDufuZiHvc6QGCJsj2/QlNAfv4jPUGnJEAIb1/RZoRGQIWgE338b09AzKeZz2h6UUAbVEExB6g9QLEjW3QcVVdAy3231wYMU0AAcOS0olxwPwDREEJgskRAMw0LsNEdTkCbr2nBkQpUQKWG2oG/QlNAdBHl86IUSEDoqE/uEfZSQMYkG6ChphZAFlraykk7R0DnT24xRY5QQLCeh8lyV1ZA5MlwCj1EKkAzEEyvY19MQGh+jjjXc1hAX77TJEm7SkDwH0UjlkpDQFoO6715Jk5A6BeUT/q1BkAEav44KU5FQFF+ZrCZ5QJAWtEK/4LzHEDDJdmSkrpXQFavYYh0p1dAccX8kG7UJ0AS4v3FG95OQHunP9xH9VNAXqzrOAQ7KkAJc7dx8htQQGRl7CakllRA1hjSLM9fQUAQ3LxobI1YQBCfPgS6JFdAxk9/S6xyTEDr86G5x2VTQPmcxW1B/UJAGV7lgPrKSEDz0AbBZ2tXQLdOvLrfpTVAy98zOC5fT0D7hUxQYmpNQEWYUjaW31NA3HDRjCJYNEABICvoALU2QDCVfZE4RVhASF9OkRsfUUCbAqVqJZwyQB39vu9vyFdA/XkMVU2LVECTAIQJs9tRQPAtXbx19gpALBcnD3yESEAFLeD0GaNAQOHnzcIIujVAeMruj3DBQ0AVlYdEvzw5QHY2ILbSR0FA7l8b9zSVAUAXrdj9/6dHQEnk8EFPPUpAgPXaiBxSTkB71e/UUAs7QExU4anyNDRAHvWAcJqZFUC0v8mct6dWQC6qhWsOYlhAXuzxJOOkWEBa7du4u400QLE5aw1OVFhA9Lfrzhj+RkANIUd3qh1WQIIkq3WCj0lA13a30dEPSUAACS534aGpP1Vp85Grt0dAbbYW3d99UkC1jZnXbUUzQARMFh2f+ldA/n0pYilKVUDvgaBwhgcDQLcJilxQxiVATAZ0/ftrLUC7XYAHsVxFQFW60Uu7JVRAKA+CJZCpU0C82QNEMpIqQGb7f6+TxUFARLWqPLAgKEAQYjGpnd1YQP+Wc6sNn1FA4FVEi3Tt4D9AVkP1o5w8QGEbgjBjdkxAWKNGvJUcHUCE04XEiqwhQDX1kw8kz1RAKLFFtP9z0z9bRDHBe2lKQLC10ipS6SdAJNSPIzTvWEC4/AQoKNIkQAhvuhwuET5ARSfxHQPGIUDpk3/gT4UbQAA0psB5kDxAkYImVpxDQkDWXVINhYZWQHlELP2b0jJAXWM6Ut7/S0BmfRKJeC84QA8knoPq30xARBipJZBLKUDz9Dh3RL1KQP/0/JWuu0pAZpDo9tXmS0BgXaebkXZPQFa3tnKk7hJAk3nB3mPsVkAgt4o2jrQVQMTgDMWYL1BAB4iD1JnnVEAi5/rnYRgfQA/aba+Y/ERAEcB1J6V4UkB1nI9o3BNWQBbMjjG22k1AUaOXYNuzSUBN0Ty9hJJPQJ0F9BnVxUZAnRUQ5CBDNUCVOPc9oDI6QBG4yWAG+SdAxoobmD02N0AIAHLCGWZEQKSOGiPB+0xAussPRdSMWEBc3wjnJYEeQOLei/PKvEVAH50YCs4fVkAjX/gCk3VYQIv+FMY62kxAO0U10ecqV0BSMn21GHU1QOsTQiE6fEBAPbzWxvsQT0BX3cZWm6NGQM94mbpu3FNAPfnPVWJvA0CTroCvHOJUQCt1cH8AxDRAQSw2ghDkTkCVEId0uh5PQCaxqc5IhERAzZLlkcEUBkBM7PH46Bg6QGloNk+1akJAZ99Z5PdVNUBIDptU+u9UQHavbUdYkTVAfKUm2UbNPUBUmt+a01dMQHhwz9X0+BdAnpcA98O1EEB8nae4Kfg6QGd+GMB7o1BAIRntllJjJEDRGs/AYDo7QIlF0bcQr0JAra9FxbBvRUDb4MgirLlBQPh7UcUg7U1AGnAAtZt0UkD1475jo3BFQGth08k1xUlAVI3NRUJXQUBTlDK6SdZEQM2wZHwEvFZA2ivsYJ/JT0DMPqcLrA0dQKSIEQpePh1AoqSEgpjoWECrJ9rCfTRCQKESOCI/vFNAwMm4JpaAMkB7+D9BEjMBQJUVQCvSIjNAeEKO373QU0DaDJqJYTs5QNFp08sX3DJACu6rHKzEOUAEOi2Ee0FMQHKru8WF61JA+42XGslJNUDhvdSv+msBQEHph3P17VFAOe8PdtLmTUAPmImo7KpQQE7f0qaZvlBACHVpDx3vSkCULCL/q1NYQI+UIpb4IC1A1+lYBDfJUkAn/hGm3y5TQC5366Rwd0ZAOqQiNyYeRUCO1DavBi3wPz6ZCEC2QkVAs+MflaHvI0D/3UWw0y85QOeJ1qU7pCpA0KBrPFHXVEChfwp6aNI+QN78Hv/sd0xAczVqoLOuAkAJYsMChL1TQGU5HHLsq1BAP69vokc/UkDx5nfZobFGQAhihO7cPRVA0gAyBpUP+T/0qH/NFyBDQNPOH3pIWwZAqZgTXw7bR0BuHFSxOuwsQFYXr0IWz1RAImuK1L0tN0DyBDShpp5WQKebdjpz51ZAh+/a6gBKU0By9c1gs3tBQBKb1L8RVUpAfL200qyuNkDDlwjsQXtDQADxdqAe3NA/sX5zgqoeWEDw0BY62NkRQChMf8883CFA9jmaEKRwS0A6cKYVFZFKQCsv2WPfW0hAWe3e1WrcK0CwbrNHj2ZUQMA6qlxU8KM/HigBypo8VUBt2hIGbABGQHtLDyUHXU1ADsFgjGyoIUBdSvJ/3uZWQL5a35Kr8k9A5XR9/5BzK0Bu5bnMdzBXQC0biXlA9FZAnymU6adQTkDuaioJmMI7QHk1trE6D0NApgPwGmW7EUA0FlOcmF9WQPijUpSBhk1ArKcNTBhfPUDOqv3oKGBEQBoj/yNSGFFAbuuMUWiuMUAdIJ3q0qpKQA7atHnYjjBApKCrRWALWED2dmbZQrn6PxLgVwnUQkdALPQTOq9wPED6nXWVJPRJQAXWkCMad1JAHxr3vBTKOUDUYne+b444QPKw9odt8VRACiwCJ4glRUCuRkCbojxLQL6Hur30eThAWpx/dE+pU0CUQ/9zyS9FQBbVWbfNOFVA7UlO8iomTkDDxpxfitBDQHat4AfnQ0pAAYHUWpYSQUD8Z0BjxrdGQGnBMGGmVkJA9R2yus9sSUAZUZn7lOY+QNnBmYdLf0hA1eQksWfqUECZhyemJppRQL5EtpKfAUFAV9E7Q2WLWECeAef2z0NDQOCaKywbHz9AyP4BUBpZUUC4N7u6/nE5QMDytdXhl0hAmSTPFQCwVUAauWhX3FMrQE2Kb4DoxTVAMhguYUWrQ0CmrYenwQlWQJGGFK2N0jRAoKAnRaTYLUB/HVsRQHFQQHeO5sojBSJAlxDI7tnPVkCvq73YXypXQGTD5tvs4SBAiRrSjQJuNED1WDCFQrpBQHgjkV8JQldAuuKIkRBXTUDmUqLbZ9BWQCZV9FBt41FAY2fadJM6Q0DUNhRQbAdVQESJEYJd9kNAxjyUGknCR0DgMp9HORxVQK75BYHNDRJAUeNa6j7zV0D68g6u791TQBadq59xiTdATTpB8tSYV0C5s56f4GJBQFDhodOFrSVA0m1rFevh9z9kz/c3optLQFjK56EN7jdABKgtG4klVUBhOSeOwqRTQDlh0FHdeVhA0imjaY5nSUCk7ayaUQ9SQC5v2Rs9CTVA+nb9Q82+Q0D6yzq0CSpTQCWns1ABDzRAwqzB2UktI0DFXEOnm0NMQP1CiCMRuEdAbdmic8JeQkAQktTP9Lw+QCOOrPt3vlJAxTBTWY+KTEC8OW5yTaJYQMwfgK5qF1NAJUW2669JREBqmdaox+1KQMLgARpekiFAS8t5Y2A1SUCKoDlyQKtYQK/mTVvtu0NA2rjJh8mxWECHbREaCkgkQM3q8APv71BAbHLIx9E9LUBgbb75Ea0xQLSn1Sj+Zz9Ac3X2n9YyS0CEKx7FXRhUQD+Wf5GtXEVANKN1I3f2VUDQVGE7IHhLQOBmXbxfiFNA156TH1NjU0AgllUxeeRVQO+lSklSv1ZALhCBzr0WQ0DyHbdfFv1XQAzUUyrH7zlA24MluW8OV0Cj6V29X8BPQFut14EwFlFADm8gQ9VZU0DnDgu2+W5HQJXki+4KvVFAd+MY929ySkDOVOFg4dJNQJ34hcpR8U1A0hkZXQs/WEC0aVUk2Es+QBq/SYnSgvw/KHU+0dJaQECTDqsSWpxEQCzkA1mL5TNA5G40Wz7h5j97DK6yiHNQQIyfoNpLHE5ACz/9TXq/VEDhNv+sIOZCQMg9CV8xiEJAuZIHZCBXREDy07b1KL1RQO8bt5ZRilhA541cQ5u1OUAciRhlCD5GQE7088xhuEpAW/3Lse9yU0A09ME0jc9KQCjj7wcVRwRAC3PmrhhCR0DRbGwL8PpKQLjyyoMxUS5AQJPneSRBHECa2qvbd0NKQD6am7X4cURAsfwkxu4aNEC/4UAbiMhRQHcIwqc6ekxAEZFFyliZIEAPkjhYCZY7QGfCzjlSPlVA3LOTUd/aM0BIdNq/qtY4QJOI6F5V+UJA5mrSzMcpMUCaD/6RyosyQJx4ZspkQlZA16nGwCq4UUA+Ko1OGYFYQJiTHBTxCElAiKhwEScoSkA7NRYxaiBTQAFuJHuac0BAb2Y2WEKmUkDt6merWc1GQJl9MYxQx1dAM4IB3KIgUUBlCEnvoYZUQAjUAbqmd1NAZUKQWtizUEBb0zvjCflOQHbMoIU+Rk9AUmq66m63MkDBO54XrhdQQLazTo7igjdAfKyY6SKcTEAPoAb0gjozQIgbttp3TURANg01mQ3CP0A6jtjtDPxWQPyq1rIHKVJA2RxNMkigTkBo+0FZQZtYQCCDY1CUuVNA/tz1QeXRS0DRNJZz3KdVQPL9NOr/qFhAuh1jdeIjSUD6uoZLlvIsQD9rxbdnDzhA8cgGEt4kTEA5nZNW/nJGQH0o4RCXDghAG3BXaCgmRkCr3687JrpPQM0aHuxQ1E9AAVnltFKxQ0C2nGkOJs1RQDA0b9dE2jNA+Ka6AYsTSUAhV0MTGOBUQNwHLyLxNRdA5LJwxpgUQkAEWqFSylQ4QELzsGcoylJAKKnpa6BvVEAy+tgGGW5NQFe+D/3nIVRAjPji6YFYMUDOSbuIyaRMQDJG284LkS5ADBVwQkj8TEAmx6n3e3NPQKC5BRhRNFdAehdbHoBzRECSAuG9jokuQJAh6Q+gVzBApu2Rh9gxN0CjtAsc57hRQOrM9p2BfzZAoQeSXQSYRUDY6FMv9HFRQA8R5/eeLVRANK351IFnWEBciTWZ3ZNDQGzPmfvOa0xA/W3AoLdcMUAcscORy+AzQM91uIyW+FNAMfJM+rQYS0CXxNgz1iREQHU5N4Xnyk5A7Tu7FjLERED0+BNNWCjzP5OWZHX5klVAtil/5OmlUEABIz6//CdSQG02GrpMllNAtozYgwxBV0AjMrz3rbJJQFuHWmqGyVNAXwcF+7gXR0By6iSwmkgiQISgy6/moj1AZDZ4e5dSNUCb6S3oVPtXQD5BgOievVhAaABqVdgEPUAG8V77dG9FQBV+wuhqYB5A4gKzAndWSkAim8SuUs1QQHTT70FAIExAyDWiVl9DREBHssFmt/1QQE25Rkj7ZlFAvYfrMBLrVUDjfF0hhkJTQIEPKuVqP0dApH58FmeTR0BMabM4Z0hQQHJBthzFHPo/qqmypiThEEAlU+vhtMgqQPHt5pYZNyJA2ll+hidhMEDuCeAZY8xPQNZD9IT0ZCVArrfgeVbUNkC7K5GrxysiQNIvyObOgldAt3sySVqdVUCP2IqZH8A9QP2WGT5sIC5AZY8GpgMUSEDbV1+mFBZCQLhKQTq5DlBAK0Ggg6H7NkBTxxo+NMFUQIIzCaBE+xVA8hmWLXcDT0AMqVDbTwdMQM781gGsivs/ZLJTsQ488j+GkKq5eDVLQIyRXRXENUxAaFAT5ioANkBhmLPUm9xBQFpeDezDfFdACPRjSgkjSUC+pL/bYllAQEat1tGBajVAaPH7Vlr/QECRD+hDum9BQNKA1TJy/D9AxN45TqeuQ0DWiBmDuG9GQJjxzXvuQEtAl2tBoBGcU0BLpx+xJikyQPcKBhByyzxAOUHLvwFVSkB4S+n6IC8zQO8jEQRiCkFA/iAGiRfyAECke6psBSErQK3+E1j6r0JAMhpCyFo9T0AnN9QxcyNAQOlMnKwFLkNARsynb9iIMED+MZXmrIxUQEkg7Ima+1dAtryiWJNFUEA5TFQktW40QLHmkM7y+09AWx4rK0eOUkAxAhRNeONHQEu2kWodE1ZAubtfkPwPUUDEixmc/SZWQJLPbMj9wVFAvd0zvWmUWEBBNSS0Uuc3QFZLeCpYaFRA7wV4ToehV0D6tDE8w4k+QPlwzTGon09AdaMlFfJ3LkD5Enn7oiUmQD38bRq8IUJAPhFSg2+tUECmXsGKgOJBQIPT+/ZeeENAI6e++3FNUkASkA+jjc9SQEH7MF6PU1JAMoj0XLoNPEBXtOFu8+RTQEwICnEqKjtAIep7gLZ8NkDbGBDoumZUQKUupHJdMyFAMeJFj7OUR0AVBWUblZxIQGRGrhtCB01Ab6GJj6KFQUCYRejRb6ZQQGh9wdVz91BANip9QSdPSUBRCU7Uk0lQQLXiX0cWJjZAQVIqxjZMVUD4U/X9AwISQMM4LArS+1VAePMwJcPNVUAw8AyFdlgfQIYw4gw/0ClATiVWsskdKED+eBWXH4s+QCrw3Ha5piBAfG8kT5CwOUCz2fUtBxw1QGrLh4mPrFBAEeDRn1miRUADC+bK/Qg1QCk/XOAs+AdAPYn5qi85E0DkYCJoLHs0QFhKFjwh2jJACnhaZUhZJkASxV6psN5WQKN8MgWI1gxAmG11THJtNUAW0FZKD8MhQC4FylKBglBArpRS959+KECBYzZK1HZRQG7J5/UmwzxA40g9uUA+V0CABs5Yj7g3QFooacGjzEpA9947L7ekUkB7j+654QBWQLfNKlm9mFNAiZQhZz5RRUCDuZXMSPJYQKc+iecpHEBAfvaiJmYSL0C77YaG6TdUQA72FMU61RZAnRKB7ZM0RUCV4AQS85pLQBI79ceqYlRAbVSf8Zp2UEAMDCM3KHFWQFoZAlO/5EhAhbM7HTeAU0B84GDBoepMQNLPP2MT5UBAbf8NNdkOMEBDeF8ODKcJQAFKRYve0VdA/or2d0GTTEBVrIJFcFYyQPBHM3b0h1dAfqp5l5J0KEA1n/bTA6RSQFC5xpckR/M/zyRm9FuRVEC/UIJ/Atc1QHMsbcXoZlJAP3FKO5sZU0DlBoUrx+9PQJKKUIyGhlJA2ioRj7/+UkCF4/PYTPs2QHDDHXeaMPc/rj+jcBorTkAeUorUV7T/P7HrSeE72ktAA7q2jNnqVkA40hVHstNLQHJLQPJdgkFAcObzqi02U0AENyfvk6hUQPc82+Dn01NAWDNlzSqIVkAq7osVeTtQQGTOb/ahtjlADHdJO9IfUUCh7D+khP4+QAggN/rAJ90/Yf+yp2WmSkCqOA1CEqxFQLhF1/w1pxlAlEkjDkH1VUAcou7xIAMlQMILrsabgFZAu4r5CRICOUAAo5HWiEcTQCDVbHzg6u4/V2c8gseZVkBvVVLwBt4TQAGr2/GsEVFAUclSBXI8UEDnvVHkYYFIQImY+2jQZ1hAJBLfExlJRkC9f1E3TYhPQOmnQVIPsktA7j1TkgD7PkAcf++LVD8sQPB2yEHwe1NAYL0elXzyR0DI8D1AzR1JQG4w/IicDkJA4oDK59O+MkCK0OLO4uNWQF9ajyt/qVZAX4doV0qGMECoDP2BVnZFQGObjULUZkVA9KT/JenbT0AvaFc2BchXQEpYzreDIidAIF6l36r8LUDuoDaKhyRRQBy4N6mkSlRAK1eGXHoaUUBntcZHKB1YQD8kGHINH0ZAQcC8oNo7R0CkdZcljQA2QCEPKJvIDUBA8EhHVA3/UUCYTV870yo/QAlCBwP3tUZAMF/XoPlRQUDzGfmV6ORDQKK7mw2PLFNA+09qiJeZVkD0GFGVMFs2QPzIbcbxcz9ATDyfE0QoPEBqT1YtxwAbQHebVOb10kpAvPa+teX+QECysdEBcHhLQAjNSWKtDABAMKzVkYOFREAGozBPlN4IQF7xgLLaE1FAATda6np8RUC2p+7hp8RRQK5Z74xrIS5AL8kCFB/dUUALMIfm5NRBQBddto2D+EZAXSD9NoHSMECf4cKOM2lUQOmWttGocDpAMfzvT95eRUBse/0wNpb4P+BXoJxyuh5AOHPUYdHjVkDkaTzdANpYQHUYuRJAtkBAQPcexRf8QEDjMb4P1jA2QNSivibnJe4/ikyivjj+RUDrgTi623o4QBJUbcQk7ERAbAN3lS19V0Bh7nN3kYtNQKrMfl+LkFdAeOptHYdjRUAUlcE/Gv1PQKW1y8GqKlBAjbdhkvBwKkBzdmIU/g4rQCREqxoad/g/6+GLoH+cWECges0eXuFCQEQyDpo5SkdAokGt/b1WMkDSCHnTPRtTQPUbuyo1WVhAlO2auFm/J0BvDh3lLyNPQPWOKBjuYUlAgQdDnGJmSkCGLDPUyFQwQBjTOPnC/ylAJeFjQqhOREB/kA3kwvlDQBKQh5BtOT9AsD5zaknbUEC6KqwT+kdRQMiXtYXG6iFAacdRLrWxUEAAzjjTSAM1QMw6/lCyQ/g/qMqmRcrRUUC/ZV5ZqhcgQHOXQXpuojpALzIb1+OHSkBA7Fz28fZUQBvSVxMmHlBAijZca6YeNEAEYY4QPrRBQNnZlVDp3FhAXl4HljNsQ0C8EqbqgitJQHXhz/KjlURAzt8njA+MV0DF45Dd/lIzQAQYdApcWhZAjMIyQU1XQUAmXvL+xQxTQM7UfYSvJVBARrd6ZZSlQ0BE6ANh3QpQQFp42GwPa1BATyxPI+JPVUCgYrnwDEUYQA476rwpmjZAyw1QJX1MIUDA6uKYV0cnQLRfXQWM1DZA4hpawBS8NEAKMDGFPF1LQJlsufTYLFBAJmvKAaacIEARB/KGVn1UQJlLwZIcx0tAENXXf2t2R0CojVVhpaNMQI3aU8/Q3jRAIZ1GoTCzS0CLzu9JzydYQFCOwDfBFypAGCqsNT8pFkCMq9NSC4YfQEu/E2OEZlVAjvGPWOLLN0D6/4D/qL0gQAD0AzJELT9AaZlSLaLtVUD4EdgJDo9RQF5ojWUjd1ZAvhScQ7EKOkDQ3gfBjbM8QD9OTxjHBUZAgbp7DyoXWECKy/nbDT9SQKrblrHqI0tAkxntkZs5VEASX+Z6EL0vQGHzAAHsWjJAMANCOM8bR0D8z8eHtvpBQBIJJ0Bps0hAQ7HSa+YDSECVq3X7vhVHQMGZYhxYJDRAyDFgQQghWEB+oiUSBchHQPu1CkYgOzFAWaZsBYacMUDlidrOPJs8QNr+fkYGDjxAYyXlGMXxREBZ5nU7PnlBQM2VT/WUW0hAlo5Sl/SzVkD+I2t4JMxKQBAsBDtmT05AG2l+E6YkO0CdWKVURi03QPmzJ+7Do0VAB4OhHXvwSECcwvkp/vMzQDoVWCw2QFFAhfCPtYpQSECoNCsblws0QPxtVHrM0UdA4uyIlN2wE0BV9NZcatdRQEJi17gP9VNAzCvPIBbJV0AR73QJBFtYQCaPaf2gL1VAbmC/s9YjFkDd3W8KuilVQDnE2SaGlEFAZpkVSjmKWEBVoFhu96JIQJcCeZr5CUdASnPTS4Y0T0BrBue0KMdDQEG2DYukclNAV37oV+znWEDrJRK45G1AQBY7CO29jDZAbNb3KCjTQUD55r9BjiJLQBrb/W17d0NAr82MCFrRUkD3Ks55qF8VQDCfbx+vX0dAz6yG3t6oHkAuhmhXNmFHQDLFTpIxShJANFzuUvIJKEAIpbDeguVTQJuuFxuK4lhAxOGfcx6iSUDKNvsZsq43QD+pY+zC9FJA66b7fl81R0CkyV+JpP5MQOqdcg46zC5AhZ0Od4J4WEDpWzYScDMyQHfRivFZi0VAqWaK8JQeRUAcYhvWdfpYQIYrpkGJYUdAybAhAxkyNkCZpkKtCQFYQIbdWUt5CVZAMOafWmvqVkDJZ4dirv9SQPfDBGaF31ZA8TK/Hba/GkAFmMPzW4hRQDV4wrrU1kVAesPK0yLWUUCYUJcmpgVBQOSrLFp3MR9A/a9rXvkZG0BE6VjO9RlTQHm4icQkHERAa5b7OvBEWEBZmeXHjK5WQLSqR9HZDVNAetMeCBXT8T9ZkjMiTSVNQCJskmWmQlZAFLFTKs1eQ0Amxdt+6p1WQPTjEyv6YlBAIsrOGToEOUAGxFKN7LE8QK7tzjIFbUVAEA7gSVcU0D+ppws/eHVBQDOmmndLli9A7BGXO9gDWECTi9qGGxgyQDM+akTS3DtAOv7VSdyaFECFVcKVb05OQIAx7RS98FhAuF+ahYr5MEC8LDroKStRQIbYBXh/5UVA7bcToJDsUUBHEjONzOpPQJDTiIlDcFBAHUy343V0VEBmXbFFyHVNQME1h5mUx1VAjTm9meuVUUBgbIn79ShTQL1l9ErhVzpAoCGSwrGnUUDxtmWB/DFLQAuvWGz2O1NA+3t0emDjSkARvGIsW8tTQJMMC0ESsUBAQyXHGEhAVkDWnvn2ymZHQF95tzb3ZxtAGA+l37BAS0AXNlWBJxlFQMhKIA4BIy1Acw7xIQL3VkCOgfdH6sBDQCkk82mSAztANd+gZVGrL0AScOZ7nvFPQNC+QDB9/zpA0HjCIiFCQkCkk3iuhQz0P9S92YLux1ZApDyDkrJbSUDMGOg8OM1YQHKyuN78BSRAK/JP4xJXMkBgj/eocmxKQLWfXycPS1BAeDDM7QdPLEDwKylqFxg0QA6ssH6nFFFARmrr0ekuUEC94zKVCyBBQAKDJKTrCkRAv2RlaZ6xVkCNdrl6meRDQImt8q+tESdAtgUhxc8VM0B1BpvmO1dXQGLu7uvuREJA86qFELFTTUABCRcI0I5TQIKaqUE8ElZApIVykvb5QUCnWrrw8rtNQH4s1aQ5HkhAIjHbrDWsREBiayU08g/9P9lQtk1FFERAAlBqyMyELkBrRMGq3wBTQBzQIOOoZ1BAVE/BcNvy/z9Srogx4YtCQFAWxTSqXlNASDy+byPESECZ4VXbpn9FQOy9KEhZQxNAbBOL52yVNEBPvfZtuLtWQHWWWc4ViQ5AZk5rOK4vQkC0BJaEZPhUQOvIzclf9EBAy+73eJXmQ0CGuIaGpFtDQEQ7CcPil1BAlH1L8pmfMkC5aEeHushSQIZ+UE6I2lBAuqf/ifZpOUDJDykMvZ9SQLCtsqmLxypADBbfF6W3OkC9Ux5BdEBHQP9V9Rln1k5Akr2dlQeAEEDYc2tvxKZYQAUGX4qKT1NAQGxuWjNEDUCfLRVJaBY2QK1bfp42PyRARwFUwYJ8JkCxtpgoE8pLQEAcOUOcQ1NAarMMTNYjMEDzl+d5zaowQP3bX+e8lwxAop3aqtheNkCfM2DoakNVQNC8+8MqylRA3/eWhEkLQkAY7lCqnINBQH0z+R0OSSxAAChgTiiUDECOSrP11yxMQPfR/uBxgU1ASX0QLvGSWECCLxLdzKgxQNq/vw2oJv8/aEEZBNCW/T8axvkiTv4yQEvzNBXoeUZAhubvHOKkMUD5pMxx8Q1OQGSUAtdoAVdAka8n1yTyVkC0iMtYuHBJQPB6yQndOt0/7brddwQORECmIjlDQH1QQNkFO5mMwFBA2jn5RrOQREBMRClnqKpVQNSkE8ch2VRAlqG7bOONTEDozdJgE2QwQK511LL011VALiEZZVvgMEAVs66DxylPQCVqZbXj2khAvVYgwrLJU0CDhujUAkVWQAL8jDuSbUNAi64QzQvXOkBjqeqds6c6QHreJu8zOFdAVgN0q3KIUkCXcASJ81xYQEHkyKZ4jVBAMw2/5vRqTUAQNrgGEz0uQAauwqWfCiJA3Yb/WBd2U0Ag5IbMPeWxP6U3d5PO1DlAKq4nUzeSVkCI6mPLuzZOQAttesoW1k5AYi3o0MGmEkD4sPaw4LhKQL7AneaU/k9Al8nSsw3ZNUA3StUQ/BdQQMb0MmcYQ1RACLvnrCD3SEBt03g+d8NOQC0j/ni8pktAuOUV7TwhS0AR2HD6A8I1QFytQ8h9VFJAcZoSe8vGV0C1mXmVrgFFQBA4rHmQG0hAHXubqV/TVUDhmDSGAONFQJwxuBq7kTlA5vLZPlyWOED3andoE4BXQFyQrQQFf+Q/qJDGpgqZQUB/07FIsZVVQPElDtNrMlJAzEGVfiW1U0DlG2e4PD5XQILJm1bMMTpAcqQqyZPaOEDrnxp4POdDQEUSvJ5ayDpA5PTsu1aLK0DWJ56NvMhMQP9gtWHcGlNAOp4A/vR5N0AWYBgn4/4tQDXYiXe0IT5AMd0FDSpJV0B4v0SSh4FRQOndhUJ6eTNA8ulmuaQWG0Day+DChEIyQGwHU3upqEhAcGvAszxkVEBjXZUUSkRMQEJdbUR+DFVAsMS8URhpV0ChBtqnmXEWQCOgSxyjWkdACCZfpRIBKUDXfC8GAmFUQMg6Sw3r+A9AGvJZ4meWVkDANpMEBFhRQGiQUV8TjFhAvgj+MfbUWEBWOUlsm4xSQLsLvN0lg1VA04d7lBiTS0A6qLvGDQoXQFkfyJ/rrD5AtN5PTOeq5j8q6+rRCkoQQCjxI4GhG05A3YWcP6jcOkC+A8ow2TE9QGHzAkdDq1BAmMQ5iG0XJkBE3QdyJKdRQPLLAau6QDVAvGbiOaipVUBaw36q0XBIQLyUn1c2STRAb2xPDH2uKUDWOdjw65E/QFRuY6jxgkJAPYK8orRjFEBw5pYmpzhAQL+wGDVlH0hALM/SLlQyV0B452b14oVMQNydnS179FZA3HKyT7/0SkD0GAkQFcVWQHh4dfmvdyRABYgBqDsXUEBIlipRlhxCQBc/EuONKFJAmbbjGovMTUCLknFH2tlRQCc8r9F4NDdALYxcnm7xTEA0sFOCym9VQFaKhdHp/lZAFFuMDci1L0Dnf8cpZDwhQHNRVfXLOUJAdhg4nq4UVkBvVd2DDCNRQPOgSe4sLlNAULu6xegXHEDStx0X4mhJQBXS/1mnmVBATR0klDBOUkBYaJZ745xUQMJhJ/WwWFRA8zD60oLkV0BgbH6N5Yi4P25ZMsBMnVFA4xBkkn43VkDuOYkRoTVVQKRBZYupsTVA4BjGhpagOUCdBubzdyFRQPbJNlI1gE1Aj/TOnTnOREB4gwI6wNJVQHqoFjGmd1RAgy49m6xgVEDGKysp3lNFQFqj/dNRXDNAQ9PEAl7jUkDSqXg9EJQ9QIsh6ierZlJAXkg+AqzFNkBUp1xnzeXkP1zIVPlqrjtAPe3YDHXRUkB+Bwx2Hv46QCDFTF27mDNAgZYW4S8qUEBy+LgrFVgWQNInMYk8QERAhsJH/3pGQEDeDiJva9NWQKDUK+YwPUVAei2xuyd+QkAumCqSTQ5AQFdnbqpS4lVAdBRhFOFRUkBYCz66chkYQGYwsZ36cSVAwE+n7pgWVkCmpoj8OUhUQFCNrRuUQlFApB9YX5CeVkBFIFZ61rAwQPBEAgwMtVBAfMfeNFmuR0CXDkwD2ktXQGz6mU7YdFBAgDBoEknrSkBzJ/J08mtHQCIFebgzSkJANHGO1zEuTUCKz8R80bBXQB43ciaLASNAAUH0nvgtKUAJHs3/TitLQDLQ/4Km2lVA204TduinMUDOhMfoPalTQGzOqpjUNU5AsjpJegN+PUA6g2DlOgAqQErfzb6itVhAHZGGC3jGP0AT5JilWUEvQBvAQQrsr01AJMPUetR9SEA=\"},\"shape\":[4000],\"dtype\":\"float64\",\"order\":\"little\"}],[\"r\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"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ottom_units\":\"canvas\",\"top_units\":\"canvas\",\"line_color\":\"black\",\"line_alpha\":1.0,\"line_width\":2,\"line_dash\":[4,4],\"fill_color\":\"lightgrey\",\"fill_alpha\":0.5}}}},{\"type\":\"object\",\"name\":\"SaveTool\",\"id\":\"p1493\"},{\"type\":\"object\",\"name\":\"ResetTool\",\"id\":\"p1494\"},{\"type\":\"object\",\"name\":\"HelpTool\",\"id\":\"p1495\"}]}},\"left\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1482\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1483\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1484\"},\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1485\"}}}],\"below\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1475\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1476\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1477\"},\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1478\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1481\",\"attributes\":{\"axis\":{\"id\":\"p1475\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1488\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1482\"}}}]}}],\"callbacks\":{\"type\":\"map\"}}};\n",
       "  const render_items = [{\"docid\":\"bce58f20-29df-4fd8-9576-73b680b1ce5f\",\"roots\":{\"p1458\":\"f68bdd18-6c8e-46f6-87d7-61c98290d5f6\"},\"root_ids\":[\"p1458\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1458"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "from bokeh.transform import linear_cmap\n",
    "\n",
    "\n",
    "N = 4000\n",
    "data = dict(\n",
    "    x=np.random.random(size=N) * 100,\n",
    "    y=np.random.random(size=N) * 100,\n",
    "    r=np.random.random(size=N) * 1.5,\n",
    ")\n",
    "\n",
    "p = figure()\n",
    "\n",
    "p.circle(\n",
    "    \"x\",\n",
    "    \"y\",\n",
    "    radius=\"r\",\n",
    "    source=data,\n",
    "    fill_alpha=0.6,\n",
    "    # color map based on the x-coordinate\n",
    "    color=linear_cmap(\"x\", \"Viridis256\", 0, 100),\n",
    ")\n",
    "\n",
    "show(p)"
   ]
  }
 ],
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   "language": "python",
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   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
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   "labels_anchors": false,
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   "report_style_numbering": false,
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