{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cce5e0f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from numba import config\n",
    "\n",
    "#config.DISABLE_JIT = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2e58edf0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "42edcd57c8854e2b8358c4529311b162",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Iterations:          0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4dcd25d16be849b48f879bf23d20bd1e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Packets:             0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.32.0.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-MML-AM_SVG\"></script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing tabulator and plotly panel extensions for widgets to work\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<script type=\"esms-options\">{\"shimMode\": true}</script><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/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.7.3'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\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      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\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(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'tabulator': 'https://cdn.jsdelivr.net/npm/tabulator-tables@6.3.1/dist/js/tabulator.min', 'moment': 'https://cdn.jsdelivr.net/npm/luxon/build/global/luxon.min', 'plotly': 'https://cdn.plot.ly/plotly-3.0.1.min'}, 'shim': {}});\n      require([\"tabulator\"], function(Tabulator) {\n        window.Tabulator = Tabulator\n        on_load()\n      })\n      require([\"moment\"], function(moment) {\n        window.moment = moment\n        on_load()\n      })\n      require([\"plotly\"], function(Plotly) {\n        window.Plotly = Plotly\n        on_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 3;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\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.Tabulator !== undefined) && (!(window.Tabulator instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.7.1/dist/bundled/datatabulator/tabulator-tables@6.3.1/dist/js/tabulator.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(encodeURI(urls[i]))\n      }\n    }    if (((window.moment !== undefined) && (!(window.moment instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.7.1/dist/bundled/datatabulator/luxon/build/global/luxon.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(encodeURI(urls[i]))\n      }\n    }    if (((window.Plotly !== undefined) && (!(window.Plotly instanceof HTMLElement))) || window.requirejs) {\n      var urls = [];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(encodeURI(urls[i]))\n      }\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const 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 (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\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      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\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  const js_urls = [\"https://cdn.holoviz.org/panel/1.7.1/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.holoviz.org/panel/1.7.1/dist/bundled/plotlyplot/plotly-3.0.1.min.js\", \"https://cdn.holoviz.org/panel/1.7.1/dist/bundled/datatabulator/tabulator-tables@6.3.1/dist/js/tabulator.min.js\", \"https://cdn.holoviz.org/panel/1.7.1/dist/bundled/datatabulator/luxon/build/global/luxon.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.7.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.7.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.7.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.7.3.min.js\", \"https://cdn.holoviz.org/panel/1.7.1/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [\"https://cdn.holoviz.org/panel/1.7.1/dist/bundled/plotlyplot/maplibre-gl@4.4.1/dist/maplibre-gl.css?v=1.7.1\", \"https://cdn.holoviz.org/panel/1.7.1/dist/bundled/datatabulator/tabulator-tables@6.3.1/dist/css/tabulator_simple.min.css?v=1.7.1\"];\n  const 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 (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\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      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\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      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_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": ""
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": "\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",
      "application/vnd.holoviews_load.v0+json": ""
     },
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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",
      "application/vnd.holoviews_load.v0+json": ""
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from tardis.io.configuration.config_reader import Configuration\n",
    "from tardis.workflows.type_iip_workflow import TypeIIPWorkflow"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ae2665b",
   "metadata": {},
   "source": [
    "This notebook uses existing atomic data from the Vogl IIp paper converted to an updated format. It can be found on moria in /storage/group_storage/atom_data/iip_data/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f7d988ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "iip_conf = Configuration.from_yaml('iip_config.yml')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9969a92d",
   "metadata": {},
   "source": [
    "The config here is not particularly good or appropriate for a IIp currently. It is mostly to test a pure hydrogen ejecta with continuum processes and non-thermal equilibrium plasma calculations. None of the other values are necessarily appropriate to model a IIp. \n",
    "\n",
    "# MUST BE AT LEAST 2 SHELLS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ec3d33f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d9b127a2734b48699c9c881046bb11dc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "BokehModel(combine_events=True, render_bundle={'docs_json': {'558435f8-ed83-4daf-8a4e-b76967f74cb2': {'version…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "workflow = TypeIIPWorkflow(iip_conf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3c449e3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x74dd8637d6d0>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Azp0707dvX95+++0rtsnOziY7O7vweVpaGpGRkRoSKo9D62DmLVCnOTy+2exooKAAPr0VDv8ITfrAyCUaGhIRqeKcOiT0+OOPs2TJElavXl3mZGXu3LmMGTOGefPmlZqsAFitVrp161ZqD0tAQADBwcHFDimnwhosbvLfzmqF298Fv+pw6AfY9InZEYmIiJsoV8Jis9kYP348CxYs4PvvvycqKqpMr5szZw6jR49m9uzZ3HLLLWW6T0JCAuHh4eUJT8qrsCy/CTVYShIaBQP+bjxe9SKcOWBuPCIi4hbKlbCMGzeOzz77jNmzZxMUFERycjLJycmcP3++sM2kSZMYOXJk4fM5c+YwcuRIXn/9dXr27Fn4GvuEXYCXX36Z5cuXc+DAARISEhgzZgwJCQmMHTvWAW9RSmRGWf6y6DrGGBLKy4KDP5gdjYiIuIFyJSzvv/8+qamp9OvXj/Dw8MJj7ty5hW2SkpI4cuRI4fMPP/yQvLw8xo0bV+w1Tz75ZGGblJQUHn30UVq3bs3AgQM5duwYcXFxdO/e3QFvUUrkbkNCdlYr3D4VHloBXUaZHY2IiLiBStVhcSeqw1IBca/B+neMpMA+DCMiIuJCZf38VsIi7u/kHvjpYxg8xSjnLyIiVUZZP799XRiTSPnlnIMZg42aMaFNIeZPZkckIiImUJELcW/+1eH6vxmPv3sZTv5mbjwiImIKJSzebNE4mHU7HNtidiSl6zIaml1vrBqaNxJySt5sU0REqiYlLN4scSMcWAO556/a1FQWC9zxIdRsACd3wdd/NjZLFBERr6GExZu5ax2WK6kZBndPB4sP7JgLW2aaHZGIiLiQEhZvVljp1gMSFoAmveDGF43Hu5aol0VExItolZC3yssx5oSAe5Xmv5rYJ6BGPWg/zBgqEhERr6CExVvZh4PAM4aE7CwW6HR/8XM2m5IXEZEqTkNC3so+HORf03OLseXlwDfPwI9vmR2JiIg4mXpYvFXueWMoyJN6Vy61Zxls/MCYiNuwKzTpbXZEIiLiJOph8VYN2sGzR2DCTrMjqbg2t0OHe8GWD18+BOm/mx2RiIg4iRIWb+fJcz8sFrj1DajXGjJ+h/ljID/P7KhERMQJlLCIZ/OvAcP/a8zFOfQDrH7F7IhERMQJlLB4q51fGmX5498zO5LKq9scbnvbeLzuDdjzrbnxiIiIwylh8Van9xll+U/vNTsSx2h3F3R/zJhEbCswOxoREXEwrRLyVvZlzZ68SuhSA/8JMX+C2k3MjkRERBxMPSzeKutC4ThPKctfFr7+xZMVe1ImIiIeTwmLt8pKMb5WpR6Wi+1fDW93NubqiIiIx1PC4q3spfkDa5kahtMcWgfnTsGSJ+DkHrOjERGRSlLC4q2q4pDQxfo/B1F9ITcT5o6A7AyzIxIRkUpQwuK1bGCxVt0hIasP3DUNajaAU3vg6z8bmySKiIhHUsLirR6LgxfOQGQPsyNxnpphcM9MY6+hnfNg83SzIxIRkQpSwuLNLBawVvH/BRrHwICXjcffPgtJ282NR0REKkR1WKTqixkPRzZAQBDUaW52NCIiUgFKWLxR5mmY/xBUqw13z/DsDRDLwmKBu6eDj3/Vf68iIlWUEhZvdO60UZY/MMR7PsB9A4oeFxTAsc0Q2d28eEREpFyq+AQGuSJ7DZaAEHPjMENeNsy5F6YPgoM/mB2NiIiUkRIWb2QvWV9Va7CUxscfqocaGyT+bzScPWR2RCIiUgZKWLxRYcLihT0sFgvc8gY0aG9Uwp09HM6nmB2ViIhchRIWb1Q4JOSFPSwA/tXhvrkQFA4nd8O8kZCfa3ZUIiJSCiUs3qiql+Uvi5Br4P654FcDDq5VJVwRETenhMUb5WUDFu8cErpYeEdjubPFauzqfHqf2RGJiEgJLDZb1fizMi0tjZCQEFJTUwkO9uKeg7IqKICCPPD1NzsS822dBWFtoWEXsyMREfE6Zf38Vh0Wb2W1glXJCgCdRxZ/brN5T30aEREPoSEhkYsd3wYf9tFyZxERN6OExRstf95YGXNsq9mRuBebDb6dBMk74fNhWu4sIuJGlLB4owNr4dfFcP6M2ZG4F/ueQ0ERcGqPljuLiLiRciUskydPplu3bgQFBREWFsbQoUPZs2fPVV+3du1aunTpQmBgIE2bNuWDDz64rM38+fNp06YNAQEBtGnThoULF5YnNCmP7AuF47yxNP/VBEdoubOIiBsqV8Kydu1axo0bx4YNG1i5ciV5eXkMHDiQzMzMEl9z8OBBbr75Zvr06cO2bdt47rnneOKJJ5g/f35hm/j4eIYPH86IESPYvn07I0aMYNiwYWzcuLHi70xKpjospQvvAPfMMJY7b/svrPuP2RGJiHi9Si1rPnnyJGFhYaxdu5a+fftesc0zzzzDkiVL2LVrV+G5sWPHsn37duLj4wEYPnw4aWlpfPPNN4VtbrrpJmrXrs2cOXPKFIszljXbbDYWbjvGun2neO7m1tStGXD1F7k7mw3+fmEvnb/sgaAGZkfkvjZ+BN88bTy+/3/QYqC58YiIVEFl/fyu1ByW1FRjaCE0NLTENvHx8QwcWPwf+kGDBrF582Zyc3NLbbN+/foSr5udnU1aWlqxw9EsFgsfxR1gwdZjxO8/7fDrmyInw0hWwHtL85dVj0ehxx+h+SBoHGN2NCIiXq3CCYvNZmPixIn07t2bdu3aldguOTmZ+vXrFztXv3598vLyOHXqVKltkpOTS7zu5MmTCQkJKTwiIyMr+lZK1evaugCs33/KKdd3OftwkNUX/KqZG4snGPQK3DsbAoLMjkRExKtVOGEZP348O3bsKNOQjeWSIlz2UaiLz1+pzaXnLjZp0iRSU1MLj8TExPKEX2a9rq0DwI/7qlAPCxajd0XF0a7O6gM+F+or2mywebqWO4uImKBClW4ff/xxlixZQlxcHA0bNiy1bYMGDS7rKTlx4gS+vr7UqVOn1DaX9rpcLCAggIAA588p6R5VBx+rhSNnzpF45hyRodWdfk+nqtcSXjgDuefMjsTzfPd3WPcG/LIQ/jBf2xqIiLhQuXpYbDYb48ePZ8GCBXz//fdERUVd9TUxMTGsXLmy2LkVK1bQtWtX/Pz8Sm0TGxtbnvCcomaALx0bGst/q8w8FqsVAmqaHYXnaXvHheXOcbBUy51FRFypXAnLuHHj+Oyzz5g9ezZBQUEkJyeTnJzM+fPnC9tMmjSJkSOL9mYZO3Yshw8fZuLEiezatYvp06czbdo0nnrqqcI2Tz75JCtWrGDKlCns3r2bKVOmsGrVKiZMmFD5d+gA9nksP1aVeSxSMcWWO3+m5c4iIi5UroTl/fffJzU1lX79+hEeHl54zJ07t7BNUlISR44cKXweFRXFsmXLWLNmDZ06deIf//gHb7/9NnfddVdhm9jYWL744gtmzJhBhw4dmDlzJnPnzqVHjx4OeIuVF9vMPvH2NB6/ufVvy40Krj99bHYknqnFIBj8b+Pxdy/DzwvMjUdExEtUqg6LO3FGHRa77Lx8Or68gqzcAlb8uS8t6nvwipF1/4FVL0GnP8DQ98yOxnN98yxsfB98AmD01xDZ3eyIREQ8kkvqsHiLAF8fujUxas38uM/Dh4Wy7GX5VYOlUga9Ai0GQ0EenN5ndjQiIlWeEpYyunhYyKOpLL9jWH3grk9g1FfQ6X6zoxERqfKUsJRRbDNjCfaGA6fJyy8wOZpKyL6QsKiHpfICakKTXkXP03+H7Azz4hERqcKUsJRRu2tCCA70JT0rj5+PO34bAJexDwkFaqdmhzp7GKYPgi/uh9wss6MREalylLCUkY/VQs+m9qq3HjyPRUNCzpF5CjJOwMG18L/RkJ9rdkQiIlWKEpZyqBL7CmlIyDkadoH754JvIPz2DSx8DAryzY5KRKTKqFBpfm9l31do86GzZOXmE+jnY3JEFTD2R8hJB19tfOhwUX1g2H+NYaGf54N/DRjytvZsEhFxAPWwlEOzejUJCwogO6+ArUfOmh1OxVitxvwV7YPjHC0GGquHLFbYOguWP68S/iIiDqCEpRwsFkvhaqH1VWX3ZnG8tkPh9neNx3tXFA3DiYhIhSlhKadYT95XKDsd5o2CJY9rfoWzdbof7poGD36jFVkiIg6ghKWc7BNvdxxNJT3Lw1aCnDsDvy6CHfOMwmfiXO3vhpr1ip6fOWheLCIiHk4JSzldU6saTepUJ7/AxsYDZ8wOp3y0Qsg8W/8L73SB7V+YHYmIiEdSwlIBsdd6aJl+1WAxz+8/gy0fFv0Rfl1idjQiIh5HCUsFFE689bR5LKpya55Bk6HTA2ArgC8fgr2rzI5IRMSjKGGpgJgLFW93J6dzKiPb5GjKQUNC5rFa4ba3oe0dUJALc/8Ah340OyoREY+hhKUC6tQMoHW48aHvUcNCGhIyl9UH7vgImg+CvCyYPRyObTE7KhERj6CEpYJ6FdZj8aBhoWwNCZnO1x+GfQpN+hgVh/d8a3ZEIiIeQaX5K6jXtXX5ZN1Bz6rH0vsv0P1RVV41m181uO8L+PlL6DzK7GhERDyCelgqqFtUKL5WC4lnzpN45pzZ4ZSNvSx/tVpmRyIBNaHL6KJ9hvKyIS3J1JBERNyZEpYKqhngS8fIWoAHrhYS95JzDubcCzNvhvRks6MREXFLSlgqwT6P5UdP2Vco7jVY8gQc22p2JHKxrFQ4vQ/OHIBZQ42KxCIiUowSlkq4uICczRPmhez5BrZ+CmnHzY5ELhYcDiOXQFA4nNwFn91ZtKJLREQAJSyVEt2oFoF+Vk5lZPPb7xlmh3N19josWiXkfkKjYORiqF4Hjm+D2cMg2wP+nxIRcRElLJUQ4OtDtyahAPzoCcubVYfFvdVrCSMWQkAIHImH/95RVJ1YRMTLKWGppNhmHrSvkCrdur/wjjByIQTWgpN7ICXR7IhERNyC6rBUUq9rjYm3Gw+cJi+/AF8fN80B83Mh98Lyaw0JubdrusDoryH3PDRoZ3Y0IiJuwU0/XT1H24gQggN9Sc/OY+cxN+6+v3gSp3pY3F+D9hDZvej5sS2Qesy8eERETKaEpZJ8rBZiCndvduNhIXtZfr8a4KOONY+StB1m3QEzBsPZQ2ZHIyJiCiUsDtDrwvJmt554W6sJPHMYxm8yOxIpr2qhUD0UUg7DjJvh1D6zIxIRcTklLA5gn3i7+fBZsnLzTY6mBFarUZI/5BqzI5HyqhUJD34DdVtC2jGjp+X3X82OSkTEpZSwOECzejUICwogJ6+ArYfPmh2OVEXB4TB6KdRvD5knYOYtcDzB7KhERFxGCYsDWCyWomEhd91X6OAPsORx2DrL7EikomrWg1FLIKIznD8Dn94Gv/9idlQiIi6hhMVBYt19X6HknUaycmCN2ZFIZVQPNSriNoqBa6IhtJnZEYmIuISWiziIvYdlx9EU0rJyCQ70MzmiS6hoXNURGAwPzDce+wWaG4uIiIuoh8VBImpVI6puDQpssPGAG+62q7L8VYt/DeMAsNlg1cuwe5m5MYmIOJESFgcqqsfihvNY7HvSqIel6vllIax7A+aNgJ8XmB2NiIhTKGFxoF72fYXccR6LvXCcyvJXPa1vgw7DoSAP5o+BhNlmRyQi4nBKWBzI3sOy5/d0TqZnmxzNJQqHhJSwVDk+vjD0A+g8CmwFsOiPsGma2VGJiDiUEhYHCq3hT5twY8jF7YaFNCRUtVmtMOQt6DHWeL50IsS/a25MIiIOVO6EJS4ujiFDhhAREYHFYmHRokWlth89ejQWi+Wyo23btoVtZs6cecU2WVlZ5X5DZrPv3ux2w0KjlsCEnRDVx+xIxFksFrjpX9BrgvF8+fNwYpepIYmIOEq5E5bMzEw6duzI1KlTy9T+rbfeIikpqfBITEwkNDSUe+65p1i74ODgYu2SkpIIDPS8JZux7lpALjAEajUqWlkiVZPFAje+BP2eM3pcwlqbHZGIiEOUuw7L4MGDGTx4cJnbh4SEEBJSNG9i0aJFnD17lgcffLBYO4vFQoMGDcobjtvp3iQUX6uFo2fPk3jmHJGh1c0OSbyNxQL9nil+LuOkUXTO6mNOTCIileTyOSzTpk3jxhtvpHHjxsXOZ2Rk0LhxYxo2bMitt97Ktm3bSr1OdnY2aWlpxQ53UCPAl06RtQA32r05LxuWPAEr/gZ5OWZHI6527oyxYeL/RkPuebOjERGpEJcmLElJSXzzzTc8/PDDxc63atWKmTNnsmTJEubMmUNgYCC9evVi7969JV5r8uTJhb03ISEhREZGOjv8MisaFnKTeSxZqbD1U1j/DlhV3NjrHN8GKYdh1xKYNdRIYEREPIxLE5aZM2dSq1Ythg4dWux8z549eeCBB+jYsSN9+vRh3rx5tGjRgnfeeafEa02aNInU1NTCIzEx0cnRl12vC8ub4/efwmazmRwNRUuaA4KN1STiXa69AUYsNOYxJW6AaQPh7CGzoxIRKReXfXrZbDamT5/OiBEj8Pf3L7Wt1WqlW7dupfawBAQEEBwcXOxwF9GNalPNz4dTGTns+T3d7HCKljSrLL/3atIbHloOwQ3h9F74ZIDR8yIi4iFclrCsXbuWffv2MWbMmKu2tdlsJCQkEB4e7oLIHM/f10q3qFDATXZvVpVbAWPF0MMroX47yDwBM26BQ+vMjkpEpEzKnbBkZGSQkJBAQkICAAcPHiQhIYEjR44AxlDNyJEjL3vdtGnT6NGjB+3atbvsey+//DLLly/nwIEDJCQkMGbMGBISEhg7dmx5w3MbsRcNC5kuSzs1ywXBEfDgNxB1HdSoC3VbmB2RiEiZlHsG5ubNm+nfv3/h84kTJwIwatQoZs6cSVJSUmHyYpeamsr8+fN56623rnjNlJQUHn30UZKTkwkJCSE6Opq4uDi6d+9e3vDchn1foY0HzpCXX4Cvj4lzRzQkJBcLDIY/fGn0stQMMzsaEZEysdjcYlZo5aWlpRESEkJqaqpbzGfJL7DR+R8rST2fy4I/xdK5UW3zgln/Dqz4q7FB3p0fmReHuK+E2XB4Pdz6H/DxMzsaEfEiZf381hpXJ/GxWohpWodvf0lm/b5T5iYsXccYO/rqg0iuJD0ZvpoA+dmQngT3fAoBNc2OSkSkGK1xdSL7vkKmT7z1rw61GxvzF0QuFdQAhn0KvtVg3yqYeTOk/252VCIixShhcaKYC/NYthw5S1ZuvsnRiJSi5WAYvRSq14Wk7TDtRjhVclkBERFXU8LiRM3q1aB+cAA5eQVsOXzWvEA2fWKU5U/abl4M4v4adoExKyC0KaQcgWkD4MgGs6MSEQGUsDiVxWIpXC1k6r5CPy+E9W/rL2a5ujrNYMxKuKYrnD8LB9aYHZGICKCExencYl+hwsJxtcyLQTxHjbow6iu4+TW47pmrtxcRcQElLE5mn3i782gKqedzzQnCXjhOdVikrPyrQ/dHwGIxnuecg40fQkGBuXGJiNdSwuJk4SHVaFq3BgU22HjApF6WbFW6lUqw2WD+w/DN/4P5YyAv2+yIRMQLKWFxgZgLZfrXmzEsZLNd1MOivYSkAiwWaHM7WP3glwXw3zvg3BmzoxIRL6OExQV6XZjHst6MfYVyMsF2YUm1hoSkojoOhwe+NHrpDv8IH18PJ3aZHZWIeBElLC4Q07QOFgv89nsGJ9KzXHtz+3CQxQf8qrv23lK1NO0HD30LtRrB2YPwyY2we5nZUYmIl1DC4gK1a/jTJtzo3Yh39bBQjTB4cgeM/aFoAqVIRdVvC4+sgSZ9ICcDvv6zMSFXRMTJlLC4iH1YyOX1WHx8jbL89du69r5SddWoAyMWQo8/wvD/GiuKREScTAmLi9gn3v647zRVZINs8WY+fjD4XxDZvejcvu8gJdG8mESkSlPC4iLdm4Tia7VwLOU8iWfOu+7Gx7YYZfl3zHPdPcX7JO+EuQ/AR/3g8HqzoxGRKkgJi4vUCPAlulEtAH505WqhpO1GWf5fF7vunuJ9AmsZZf3PnYJPb4MtM82OSESqGCUsLhRrxr5CWRfK8qtonDhTrUh4aDm0vQMKcuGrJ2HpU5BvUnVnEalylLC4kH3ibfz+0xQUuGgei8ryi6v414C7Z8D1fzOeb/rYKDKXaeI+WiJSZShhcaFOkbWo5ufD6cwc9vye7pqbqiy/uJLFAn2fgnvngH9NOPQDbJ5udlQiUgUoYXEhf18r3aNCARcOC6ksv5ih1c3w8CroMhp6/9nsaESkClDC4mL23Ztdtq9QtoaExCRhrWHIW0YtIIC8HNjyqXZ8FpEKUcLiYvaJtxsPnCY33wX/cGvSrbiLb56Gr56AeSMgO8PsaETEwyhhcbE24cHUru5HZk4+O46mOP+Gd0+Hx36Aptc5/14ipbmmq7Hj8+6vYdpAOHvI7IhExIMoYXExq9VSrOqt0wVHQHgHqFbb+fcSKU3nETB6qbG/1Ylf4KP+cPAHs6MSEQ+hhMUEptRjEXEHjXrAo2sgvBOcPwP/HQo/fQzarkJErkIJiwns9Vi2HUnhfE6+825UUAArX4C41yDXhdsBiJQm5Bp46Ftofw8U5MH3/4DMk2ZHJSJuztfsALxRkzrViQgJ5HhqFpsOnaFvi3rOuVFOOvz4lvE4Zrxz7iFSEX7V4M6PjZ6W0KZQM8zsiETEzamHxQQWi4XYC70sTt1XyF6DxScA/AKddx+RirBYIHa8UbPFbu8q2PaZeTGJiNtSwmKSwnoszpx4a1/SrBos4gnSf4cFj8DicbBoHOScMzsiEXEjSlhMYp94+/PxVFLO5TjnJirLL56kRj2I+RNYrJDwGXxyA5zaa3ZUIuImlLCYpH5wINeG1cRmgw0HnNTLoo0PxZNYrdD3aRi5+MLS51/ho36w80uzIxMRN6CExUS9nF2PRVVuxRNF9YWx66BJH8jJgPlj4OuJUODEFXUi4vaUsJjI6RNvs7XxoXiooPowYpHR4wJQkAtWH1NDEhFzaVmziXo2rYPVAgdOZpKUep7wkGqOvUH7uyGyh7GEVMTT+PjC9X+FqOugYdei8/l5RRsqiojXUA+LiUKq+dH+GqP3wynDQtVqG2X56zZ3/LVFXCWqT1HSXVAAs4fB8uchP9fcuETEpZSwmMw+LLReZfpFru7gWtj/HcRPhRk3Q+pRsyMSERdRwmKyXs2K5rHYHL2fyo7/GWX5k3c69roiZmnWH4Z/DgEhcPQn+KAP7F1pdlQi4gJKWEzWtUlt/H2t/J6Wzf6TmY69+PY5xj4tSTsce10RM7W+FR5bW7SB4ud3w3f/MOa2iEiVVe6EJS4ujiFDhhAREYHFYmHRokWltl+zZg0Wi+WyY/fu3cXazZ8/nzZt2hAQEECbNm1YuHBheUPzSIF+PnRpVBuA9Y5eLaRVQlJVhUbBQ8uh28PG8x9eg6+eNDcmEXGqcicsmZmZdOzYkalTp5brdXv27CEpKanwaN68aCJofHw8w4cPZ8SIEWzfvp0RI0YwbNgwNm7cWN7wPJK9TP+Pjp7HosJxUpX5BcItr8Nd06B6XejxmNkRiYgTlXtt4ODBgxk8eHC5bxQWFkatWrWu+L0333yTAQMGMGnSJAAmTZrE2rVrefPNN5kzZ0657+VpYq+tCyt+I37/afILbPhYLY65sErzizdofze0HAz+NYrOHVh7YUm/Nv0UqSpcNoclOjqa8PBwbrjhBlavXl3se/Hx8QwcOLDYuUGDBrF+/foSr5ednU1aWlqxw1N1uCaEoABf0rLy+OV4quMuXLj5oYaEpIq7OFk5ngCf3QUfXw+//2paSCLiWE5PWMLDw/noo4+YP38+CxYsoGXLltxwww3ExcUVtklOTqZ+/frFXle/fn2Sk5NLvO7kyZMJCQkpPCIjI532HpzN18dKj6ahgAPrseTnQu6F3W6VsIg3yUox/p8/8YuxF9GG9436LSLi0ZyesLRs2ZJHHnmEzp07ExMTw3vvvcctt9zCa6+9VqydxVJ8GMRms1127mKTJk0iNTW18EhMTHRK/K7Sy16PxVETb7PTix4HBDnmmiKeoGk/+FM8NB8I+dnw7bPGSqL0kv8AEhH3Z8qy5p49e7J3b9G28Q0aNLisN+XEiROX9bpcLCAggODg4GKHJ7MnLJsOnSE7zwGbvAUEwWNxMHop+PhV/noinqRmGNw/D25+DXwDjWJz78XA7qVmRyYiFWRKwrJt2zbCw8MLn8fExLByZfHiTytWrCA2NtbVoZmmeVhN6gUFkJVbwNbDKZW/oI8fhHeEJr0rfy0RT2SxQPdH4NG10KC9UbPl7CGzoxKRCir3KqGMjAz27dtX+PzgwYMkJCQQGhpKo0aNmDRpEseOHWPWrFmAsQKoSZMmtG3blpycHD777DPmz5/P/PnzC6/x5JNP0rdvX6ZMmcLtt9/O4sWLWbVqFevWrXPAW/QMFouF2GZ1WJxwnPX7TxHTrI7ZIYlUDWGt4OHvIOFz6Dy66HxeDvj6mxaWiJRPuXtYNm/eTHR0NNHR0QBMnDiR6OhoXnjhBQCSkpI4cuRIYfucnByeeuopOnToQJ8+fVi3bh1Lly7lzjvvLGwTGxvLF198wYwZM+jQoQMzZ85k7ty59OjRo7Lvz6MUlul3RD2WE7vgh9fh1yWVv5aIp/MNgK4PgfXCP3nZGfBhH4j7PyhwwBCsiDidxebwDWzMkZaWRkhICKmpqR47n+Xo2XP0nrIaH6uFhBcGEBRYibknCbNh0R/h2hvhgflXby/iTTbPgK8nGI8bxcAdH0LtxqaGJOKtyvr5rb2E3EjD2tVpXKc6+QU2fjp4pnIXs9dgUdE4kct1GQ1D3wf/mnAkHj7oDTvmmR2ViJRCCYubiS0cFqpkPRaV5RcpmcUCne6HseuMirjZabDgEfhyDJxPMTs6EbkCJSxuxr6vUKXrsagsv8jVhUbB6GXQ/3mw+MDPX8K3k8yOSkSuQAmLm4lpaiQsu5PTOZWRXfELqSy/SNn4+MJ1/w/GrICG3eDGF82OSESuQAmLm6lTM4DW4UavyPr9lRgWsvewKGERKZuGXWHMSghqUHTuh9ch+WfzYhKRQkpY3FCvCzVY1ldmebMm3YqU38Xbgez6Cr77u7Ef0dp/G/tziYhplLC4IXuZ/h8rM4/l5tdg1NfGvioiUn4Nu0HLm6EgF1a/Ah/3h6QdZkcl4rWUsLih7lGh+FotJJ45T+KZcxW7SN3mENUHgkrej0lEShHUAO6dDXd+AtVqQ/JOI2lZ/apRJVdEXEoJixuqEeBLp8hagIOq3opIxVgs0OEeGPcTtB4CBXmwdgp8cZ/ZkYl4HSUsbiq2cFioghNv170Jmz6BnAr20IhIkZphMOy/cPcMqF4Huj1sdkQiXkcJi5uyT7yN33+Kcu+ekJcNq16EpX+BfHVdiziExQLt7oQnt0PLwUXndy+DY1vMi0vESyhhcVPRjWpTzc+HUxk57Pk9vXwvtle5xaJVQiKOFhBU9Dg9GRaNhU9uhJUvQm6WeXGJVHFKWNyUv6+VblGhQAXK9BcuaQ4q2p1WRBzPxx+aDwJbAfz4prEDdOJPZkclUiXp08yN2YeFyj3xNls1WERconoo3PUx3DsHataHU7/BtIGw/HnIPW92dCJVihIWN2avx7LxwGly8wvK/kJtfCjiWq1uhj9tgI73ATaInwof9NGkdxEHUsLixtqEB1Oruh+ZOfnsOJpS9heqyq2I61UPhTs+gPvnQVAEXHsD+Fc3OyqRKkMJixuzWi2FmyGWax6L9hESMU+LQfCneLjhhaJzp/fDwR/Mi0mkClDC4uYK67GUZx5Li5tg1FfQ71knRSUipapWC/xrGI8LCmDJ4/DprfD1n+F8ipmRiXgsJSxuzj7xdtuRFM7n5JftRTXDIKovXNPZiZGJSJnk5xhbZQBsng5Tu8HOL6G89ZVEvJwSFjcXVbcG4SGB5OQXsOnQGbPDEZHy8guEIW8Zm5HWaQ6ZJ2D+GPjsTmOoSETKRAlLWRTkmzbb32KxENusnLs3/7bcKMt/YrcTIxORconqA3/8Efo/Dz4BsP97eC9GdVtEykgJy9XsX238o7L6FdNC6HWtMSy0vqwTb7fOMsryH/7RiVGJSLn5BsB1/8+YlNu0H9RpBhHRZkcl4hGUsFxNQT6c2mP0WKQnmxKCvR7Lz8dTSTlXhr2B7MuatUpIxD3VaQYjFhnDRD5+xrm8HFj1EmRWcMNTkSpOCcvVXHsDNOwOeVnGDsgmqB8cyLVhNbHZYMOBMvxjpmXNIu7PYoEadYqer38L1v0HpnaFbZ9pUq7IJZSwXI3FAv2fMx5vng5px00Jo6hMfxkSFhWOE/E8Uf2gfjs4fwYWj4OZt8DJPWZHJeI2lLCURdN+0CgG8rONv4BMUFiPpSwTb7PUwyLicSK7waNrYMA/wK+6MQft/V7w3T+0L5EISljK5uJeli0zIfWoy0Po2bQOVgscOJlJcmopW9jbbBcNCamHRcSj+PhBrydg3EZoMRgKcuGH12DpU2ZHJmI6JSxlFdUXmvQxikDt/J/Lbx9SzY/21xg9JqVWvc09BwV5xmMNCYl4plqN4L45MPwzqB0FfSaaHZGI6XzNDsCjDPi7Mb7c7AZTbh97bV22H03lx/2nuKtLwys38vGHkUuMXhZ7aXAR8TwWC7QeAi1vBqtP0fmVL0BIJHR9qPh5kSpOCUt5mFzqvlezury/Zj/r953GZrNhsVgub+TjB02vc31wIuIcFyclSdvhx7cBG2yfAzf/H1zTxbTQRFxJQ0IVdf4sZJxw6S27NqmNv6+V5LQsDpzKdOm9K+LgqUxy8wvMDkOk6qjfDgb/G/yD4NgW+PgGY0WRi/8tEjGDEpaK2PklvNnRKPLkQoF+PnRpVBuA9SXNYzlz0Chyt3eVCyO73IYDp+n/2hpGTNtInpIWEcew+kCPR2H8JuhwL2Azara80wXWTzWKz4lUUUpYKqJ2E8hOhe1fuHzzMnuZ/hLrsRzfapTlN2n5td3q3cZffBsOnOGNlb+ZGotIlRMcDnd+CGNWQngnY87aD69Drvv3vIpUlBKWimjYFZoPAls+rP23S29tr8cSf+A0+QVXqIRZWJbf3BVCWw6fLXz83pr9rN6jLmsRh4vsDo+shtvegcFToJrRA4vNBqnHzI1NxMGUsFRUv2eNrzvnwUnX9SB0uCaEoABfUs/n8uvxtMsbuEHRuJy8AnYcMxKn61uFATBxbgLHU1T8SsThrFboPBI6DCs6t2sJvN0JVr0M2RmmhSbiSEpYKuqazsZyQ1sBrJ3istv6+ljp0TQUKKHqrb1onIk1WH5NSiMnr4Da1f147w+daX9NCGfP5TJ+9lZNwhVxhX2rjJpR694w9ibaMU97E4nHU8JSGfZelp/nw4ndLrttbLMLZfqvNPE2y/wqt/bhoM6NahPo58O793cmKNCXrUdS+L/l2htFxOmGvA33zjHm26UnwYJHYPogOL7N7MhEKkwJS2WEdzQKO1mscGS9y27b68I8lk2HzpCdl1/8m26wU/PWIxcSlsbGeHqjOtX5v7s7AvBR3AFW/fq7abGJeAWLBVrdDH/aCDe8AH41IHEjfNQf4v7P7OhEKqTcCUtcXBxDhgwhIiICi8XCokWLSm2/YMECBgwYQL169QgODiYmJobly5cXazNz5kwsFstlR1ZWKXvmuIsBfzeWGHZ9yGW3bFG/JnVrBpCVW8C2IynFv+kGOzVvu6iHxe6mdg14sFcTAP7yv+0cPXvOjNBEvItfIPT5Czy+GdoPA2wqNCceq9wJS2ZmJh07dmTq1Kllah8XF8eAAQNYtmwZW7ZsoX///gwZMoRt24p3TQYHB5OUlFTsCAwMLG94rhfaFOo0c+ktLRYLsc2M5c2X1WPpN8nYf6RpP5fGZJeUep7jqVn4WC10jCzeyzNpcGs6RtYi9Xwu42ZvIydP81lEXCI4Au762OhxaXZ90fmEObD/e/PiEimHcpfmHzx4MIMHDy5z+zfffLPY81dffZXFixfz1VdfER0dXXjeYrHQoEGD8objXk7sAqsf1L3W6bfqdW0dlmw/zo/7T1NsW7SITsZhkq2HUwBo1SCI6v7F//fy97Uy9b5obnn7B7YnpvCvb3bzwpA2JkQp4qXCWhU9Tk+GZU9BTga0vAUG/dP4A0zETbl8DktBQQHp6emEhoYWO5+RkUHjxo1p2LAht95662U9MJfKzs4mLS2t2GGqnz6G92KMjclcwD7xNiExhfSsXJfcsyzs81e6NK59xe9Hhlbn9WGdAJj+40G+/TnZVaGJyMX8qhnLoS0+sGcpTO0O3z4H586YHZnIFbk8YXn99dfJzMxk2LCimgGtWrVi5syZLFmyhDlz5hAYGEivXr3Yu3dvideZPHkyISEhhUdkZKQrwi9Z1HXGRLc9S10yEz8ytDqNQquTX2Djp4MX/QOzdZaxdUCOORUvt1xh/sqlBrSpz6N9jb/knv5yO0dOaz6LiMsFhsBNk+GP66FpfyjIhQ3vGvVbfnwbcj1gDqF4FZcmLHPmzOGll15i7ty5hIWFFZ7v2bMnDzzwAB07dqRPnz7MmzePFi1a8M4775R4rUmTJpGamlp4JCYmuuItlKxeiwuT2oDVk11yy8vK9BcUwJInYP4YU4pFZeXm88txY9JvaQkLwNODWtKlcW3Ss/IYN3vr5audRMQ1wlrByEXwwHwIa2tM3P/uZUhTpVxxLy5LWObOncuYMWOYN28eN954Y6ltrVYr3bp1K7WHJSAggODg4GKH6a77f0b36t7lcHSz029nHxaKP3AhYcnJAC4UhzJhWfMvx1PJzbdRt2YAkaHVSm3r52PlnfuiqV3dj53HUnll6S4XRSkiV3TtjTD2B7j9Pbju2eKLCU6qfpKYzyUJy5w5cxg9ejSzZ8/mlltuuWp7m81GQkIC4eHhLojOgeo0g473GY/XOL+XpWdTo4dlV1IaZzJzipY0+/gbyxldrGg4qBYWi+Wq7SNqVeON4Z0AmBV/mK93HHdmeCJyNVYfiP4DXPd00bmkHfBuD/j8HmNhgYhJyp2wZGRkkJCQQEJCAgAHDx4kISGBI0eOAMZQzciRIwvbz5kzh5EjR/L666/Ts2dPkpOTSU5OJjU1tbDNyy+/zPLlyzlw4AAJCQmMGTOGhIQExo4dW8m3Z4K+T4HV1yiNfWSjU29VLyiAlvWDANhw4LTpZfntK4Q6lzDh9kr6twzjj/2Mv+Senb+Tg6e026yIWzm6yUhk9q6A92NhyePGCiMRFyt3wrJ582aio6MLlyRPnDiR6OhoXnjBWB2TlJRUmLwAfPjhh+Tl5TFu3DjCw8MLjyeffLKwTUpKCo8++iitW7dm4MCBHDt2jLi4OLp3717Z9+d6oVHQ6X6oFmqUxHay2MJ5LKdMLctvs9nYcpUVQiX5y4AWdG8SSkZ2HuM+30pWruaziLiNbmOM+i2thxh7p22dBW9Hw+pXITvd7OjEi1hstqqxI1ZaWhohISGkpqaaP58l8zT4+kNAkNNvtfLX33lk1maa1q3B90OyYM5wCO8Ej611+r0vlnjmHH3+vRpfq4WfXx5EoJ9PuV6fnJrFLW//wOnMHO7v0YhX72jvpEhFpMKObIAVf4OjPxnPw9oYq4zKMAQsUpKyfn5rLyFnqFHHJckKQPeoUKwWOHAqk7NnL1S9NWHCrb3+StuI4HInKwANQgJ5895OWCwwe+MRFidohYKI22nUE8asgHs+hdpR0OXBomTFZtOO0OJUSlicyWaDXV87dcVQSDU/2l9jJCgb8lvBsP8ae4e4mH1Po/LMX7lUn+b1eLy/USV40oKd7Dvh+qXZInIVFgu0HQrjfoKuDxad/3UxzLwVjm0xLTSp2pSwONO6N2DuH4wuVCf+5RFzYXnzd8f9oM1t0PQ6p92rJGUpGFcWT97YgpimdTiXk8+4z7dyPkfzWUTckq8/+PgZj202WPtvOLwOPr4evnwIzhwwNz6pcpSwOFPH+8EnAI6shwNrnHYb+0aI8ftPY8aUpPM5+exKMib8VqaHBcDHauGt+zpRt2YAe35P58UlPzsiRBFxJosF/jDvQlkHC/w8H97pahSyTD1qdnRSRShhcabgcOj6kPF49atO62Xp1iQUPx8LEanbOBX/OZze75T7lGTH0RTyCmw0CA4kIqTy9V/CggJ5+95OWC0wb/NR5m/RP3gibi+kIdzxATwWZxShs+XD1k/h7c6w8UOzo5MqQAmLs/X+M/hWM2bV7/vOKbeo5u9DdKPajPBdSb0V4+C35U65T0nsy5k7Ny5bwbiyiL22LhNubAHAXxf9zN7ftXxSxCOEdzDK/D/4LTTuBfnZUMf5O9hL1aeExdmC6ht1DABWv+K0XpbYZnUI4sImgi6uw1JYMK6S81cuNa7/tfRpXpfzufn86fOtnMvJc+j1RcSJGsfA6KUwZhU0u77ofPy7EPd/pux3Jp5NCYsr9JoAftXh+Fan9X7ENqtLkOU8ADYXLakGo2Dc1sIeFscmLD5WC/8Z3on6wQHsPZHBXxf+bMocHRGpIIsFIrsVLX0+dwbW/Au+/ye81dFIXrQrtJSREhZXqFkPuj8CDdpDQE2n3KJTZC1CLEYPy9HzAU65x5UcPn2OM5k5+PtYaRvh+J6dujUDePveaKwWWLDtGNPWHXT4PUTERQJD4JY3ILQpnDsFy58zquZung75uWZHJ25OCYur9HsOHvsBmvR2yuX9fa3U8TX+Utl2wnVLge29K+2uCSbAt/wF48qiR9M6PHdzawD+uXQXi7apqJyIR7L6QId7jBouQ96G4IaQfhy+/jNM7QqH15sdobgxJSyu4hfo9PLVNS/MYdlwzHVzPez1V8q7f1B5jekdxUO9ogB46n/bifvtpFPvJyJO5OMHXUbBE1vhpilQI8xY/hzUwOzIxI0pYXG19GT46WM4e8ix183Pwz/fSFjWJeaQl1/g2OuXYKu9wq2DJ9xeymKx8NdbWnNbxwjyCmyM/WwL2xNTnHpPEXEy3wDoORaeTID75hpDRXarJ8NvK1TuXwopYXG1xeNg2VOw80uHXzp/2H/5G3/keLY/vxxPc/j1L5WRnceeZMcUjCsLq9XCa/d0pE/zupzLyefBmZs4cFIrDUQ8nn8NaH5j0fPff4G1U2D2PTD9Jjj4g3mxidtQwuJqrYcYX3ctcex1fXzxaXMbyU3vJg9f1u8/7djrX8H2xBQKbHBNrWrUD658wbiy8Pe18v4DXWh/TQhnMnMYOf0nTqRplYFIlRIUDrHjwTcQEjfAp7fCjJuNiuHqcfFaSlhcrdWtYLFC0nY44/gVL/Yy/ev3n3L4tS+19bBzljNfTc0AX2Y82I0mdapz9Ox5Rs3YRFqWVhiIVBnVQ2HgP+GJBOj2MPj4w+EfYdbtMH2QU/7tFPenhMXVatQ1qj8C7PrKcddNS4KdX3JDdaMs/6ZDZ8jJc+48lsL6K41qOfU+V1K3ZgCzHupB3ZoB7EpK49FZm8nK1UaJIlVKcDjc8rqRuHR/zNib7fQ+qBlmdmRiAiUsZmhzu/HVkcNCx7fC/DFEbp5M3Zr+ZOUWsO1CQuEMBQW2wgm3zl4hVJJGdaoz88Fu1AzwZcOBM0ycl0B+gbqLRaqckGvg5n/DhB1w93RjzgtAQQHMfwR2fW08lipNCYsZWt0KWODoJkh1UE2RrFQALIHBxDSrC+DUeSwHTmWSej6XQD8rrcNduxXAxdpdE8JHI7rg72Nl2c5kXlryi6rhilRVQQ2gab+i53uWwc55MPcP8EFv+GWhEpcqTAmLGYLDIbIHWH2NnhFHyLqwKigwpHAeS7wTExb7cFCHa2rh52Pu/0ax19blP8M7YbHAfzccZur3+0yNR0RcpFEM9HkK/IPgxC/wv9Hwfgzs+B8UaIi4qlHCYpYhb8FTe4tWDVVW9oWEJSC4MGHZlnjWaRsGmjXhtiS3dAjnpSFtAXh95W/M+emIyRGJiNPVqAM3/A3+vBOuexYCQuDkbljwMLzb3ah7JVWGEhazhLUyZsI7yoUhIQKDaRRanWtqVSM338bmQ86Zx2LmhNuSjIptwvj+xjb2zy/cyYpf9I+ViFeoVhv6TzISl+v/ajz3rwE16xe10VCxx1PC4g7ycip/jeyiISGLxXLR8mbHDwulns9l7wmjYJu79LDY/WVgC4Z3jaTABo/P2camQ2fMDklEXCUwBPo+DRN2wl3TirZDyU6Hj64zNlnMyzY3RqkwJSxmOroFPrkRZg+r/LXsPSwBIQDEXmufx+L4eiwJiSnYbNC4TnXq1nTdztBlYbFYeOWOdtzYuj7ZeQWMmbmJPcnpZoclIq4UEAR1mxc93/KpUfvq6z8bu0Nv+AByMs2LTypECYuZqtUyVgodjINzlewJ6PFHuP1daHodADFNjZVCO4+lknresUXVCuevOHn/oIry9bHyzn3RdG1cm7SsPEZN/4ljKefNDktEzNJtjLHJYlA4pB2Db5+B/7Qz9ivKdH5VcHEMJSxmqtMM6rcHW76xPK8yGsdA9ANQryUADUICaVqvBgU22HjAsb+Q7jh/5VLV/H34ZFRXmofVJDkti5HTNnI20wFDbyLiefyqGZssPpEAt7wBtZvA+TOw9l/wVkc4n2JygFIWSljM1uY24+uvix1+aWfMYykosJFwoWBctJv2sNjVqu7PrDHdiQgJZP/JTB76dJPTVk2JiAfwCzR6Wx7fCnfPgAYdoPkAo7fbLvWoaeFJ6ZSwmM1e9Xb/6qJ5KBWx62vYu6rYuGzshQJyjqzHsvdEBunZeVT396FVgyCHXddZwkOqMWtMd0Kq+bHtSArjZ28jN1+FpUS8mtUH2t0Jj8XBbe8UnT+1D95sD5/fA4d+1MoiN6OExWz1WkLdllCQC78tr/h15o+Bz++CzKJJtjFNjR6WPb+nczLdMTPj7cNBHRvWwtfkgnFldW1YENNHdyPQz8r3u08wacFOVcMVEWMVUUDNoueHfjCSlL0rYObNMG2Ayv67Ec/4xKnqKjsslJcDeVnG48CQwtO1a/jT5kLZ/A0OmseypbBgXC2HXM9VujSuzbv3d8bHauHLLUf59/I9ZockIu6m64Pw+Bbo8qCx0eLRTUbZ//d6wNb/OqYEhVSYEhZ30Gaosb9Qu7sq9np7DRYwlvNdpGgei2OWN9t7WMza8LAybmhdn8l3tgfg/TX7+eSHAyZHJCJup04zGPKmUcul90SjVMSp32DFXyFfCYuZlLC4gwbt4N7PjTHVirDPffEPMsZmL2Kvx+KIibdnM3M4cNKYIxMd6XkJC8CwrpE8PchYSfXPpbt4f81+kyMSEbcUVB9ufBH+/DMM+Af0e7Zo+Mhmg/h3IeOEuTF6GSUsVcFFZfkv1a1JKD5WC4dPn+Po2XOVus22RKN3pWndGtSu4V+pa5npT/2aFZbwn/LtbqZ8u1tzWkTkygKDodcT0POPRef2rYLlzxm1XL7+szFZV5xOCYs7Ob0f1r0JueUscnbRxoeXCgr0o0NDY15LZVcLbT2cArhfOf7yslgsPDWoJZMGtwKM4aG/Lf6ZggIlLSJSBn7V4ZqukJ9tlPuf2hVmD4cDa7WyyImUsLgLmw1m3Q6rXoT935fvtVlF+whdSS8HLW8uKhjn2QmL3WPXNePVO9pjscBnG44wcV6CljyLyNU16QUPr4LRS6HFYOPcb9/CrNvgg94aKnISJSzuwmKB1kOMx+VdLRTeEW6bCrHjr/jtiwvIVXToIy+/gITEFMDzVgiV5v4ejXjr3mh8rRYWJRznj59tJSs33+ywRMTdWSzQpDfc/4WxsqjbI0bPi60AatQraqfNFh1GCYs7sReR2/Nt+ZbP1W4MnUcUJTyX6Ny4Nv6+VpLTsjhwqmIbfu35PZ1zOfkEBfjSPMz9C8aVx20dI/hoZBcCfK2s2vU7D87YREa2KuKKSBnVaQa3vAYTf4U7P75ol+gMoxDd4nHw+y/mxlgFKGFxJw27Q80GkJ0KB9c67LKBfj50uTCMU9HVQlsvlOPv1KgWPlaLo0JzG9e3qs+nD3Wnhr8P8QdO88AnG0k5pyWMIlIO1Wobqz7tfvsWMn6HbZ/B+7HGsP9vK1SIroKUsLgTqxVa32o8/nVR2V+XtN0oy59ypMQm9mGh+ArWY7Hv0Ozu+wdVRs+mdZj9SE9qVfcjITGF4R9u4ERaltlhiYinancXPLTC6D23WOHAGph9j1GIbtM0yKncyk1vU+6EJS4ujiFDhhAREYHFYmHRokVXfc3atWvp0qULgYGBNG3alA8++OCyNvPnz6dNmzYEBATQpk0bFi5cWN7Qqgb7sNDuZZBfxmGJjR8aZfl3flliE3s9lvj9pyu0GsaTC8aVR8fIWsx7LIawoAD2/J7OPR/Gk3hG/6iISAVYLNCoBwybZewUHTPeWM156jdY+hfISDY7Qo9S7oQlMzOTjh07MnXq1DK1P3jwIDfffDN9+vRh27ZtPPfcczzxxBPMnz+/sE18fDzDhw9nxIgRbN++nREjRjBs2DA2btxY3vA8X6NYqF7HKLV/qozl40upw2LXoWEtavj7cPZcLruT08sV0qmMbA6fNj60O0XWKtdrPVGL+kF8OTaWyNBqHD59jns+iGffifL9NxMRKaZ2Yxj0Cvz5F7jpX9D9UQhtWvT9DR/Asa3mxecBLLZKVMyyWCwsXLiQoUOHltjmmWeeYcmSJezatavw3NixY9m+fTvx8fEADB8+nLS0NL755pvCNjfddBO1a9dmzpw5ZYolLS2NkJAQUlNTCQ4u+YPbIyRthzrNwb962dp/OgQOxsGdn0CHe0ps9uCMn1i95yR/vaU1D/dpWmK7S634JZlH/7uF5mE1WTnxujK/ztP9npbFA59sZO+JDEJr+DProe60u+bKS8dFRCrs7CF4O9pYYRTZE7o/Aq1vA1/PLdBZHmX9/Hb6HJb4+HgGDhxY7NygQYPYvHkzubm5pbZZv359idfNzs4mLS2t2FFlhHcse7ICF/WwlP5hGnuhHkt5J97aJ9xW9eGgS9UPDmTuYzF0aBjCmcwc7vtoAz8dPGN2WCJSFbW/B6y+kLgB5o+B/7SF71+BtONmR+Y2nJ6wJCcnU79+/WLn6tevT15eHqdOnSq1TXJyyeN7kydPJiQkpPCIjIx0fPDuoCzLmwsLx5XesxRzYeLtxgOny1UgraoVjCuP0Br+fP5wD3pEhZKenceIaRtZvUdFoUTEgWo3gTs/ggk/Q79JxmrRzBMQ92+j/P/eVWZH6BZcskrIYim+DNY+CnXx+Su1ufTcxSZNmkRqamrhkZiY6MCI3cCur+DdHrDyb1dvW0pp/ou1CQ8mpJofmTn57DyWWqYwcvML2HE0BahaBePKIyjQj08f6s71rcLIzivgkU838/UO/dUjIg4WHG5ssvjnn+HuGdC4F/jXMCbu2p3cA9neOafO6QlLgwYNLuspOXHiBL6+vtSpU6fUNpf2ulwsICCA4ODgYkeVYvWFk7uNxKW0Nfs2W5km3QJYrRZimhatFiqLXUlpZOUWEFLNj6Z1a5bpNVVRoJ8PH47owpCOEeQV2Hhizjbmbip5GbmISIX5+EG7O+HBZUYV3YALxTptNvjyIXi9NSx7Gk7+Zm6cLub0hCUmJoaVK1cWO7dixQq6du2Kn59fqW1iY2OdHZ77atof/GtC2jE4XsrMcZsNbn0TBr1qrC66il7X2sv0l60eS1H9lVpYq2DBuPLw87Hy5vBO3Ne9EQU2eGb+Tj754YDZYYlIVVYzrOhx5iljBWlOOvz0EbzbDT69zfjDtqxlMDxYuROWjIwMEhISSEhIAIxlywkJCRw5Yvy1OWnSJEaOHFnYfuzYsRw+fJiJEyeya9cupk+fzrRp03jqqacK2zz55JOsWLGCKVOmsHv3bqZMmcKqVauYMGFC5d6dJ/MLhBaDjMelFZGzWo2y/DHjwK/aVS8bc2Hi7eZDZ8u0Z86WCxNuvXH+ypX4WC28ekc7HutrrLL659JdvLFiT4X3aBIRKbOa9WDcJhixEFreYhSjO7gW5j4Ab3WEnxeYHaFTlTth2bx5M9HR0URHRwMwceJEoqOjeeGFFwBISkoqTF4AoqKiWLZsGWvWrKFTp0784x//4O233+auu+4qbBMbG8sXX3zBjBkz6NChAzNnzmTu3Ln06NEDr2YvIvfrEodtWd6sXg3CggLIzisonExbGnsPi7etECqNxWLh2cGteHpQSwDe/n4fL3/1a4UK8omIlIvVCs2uh/tmw5Pbofefjd71tKPGfBe7/FyHfW64i0rVYXEnVaoOi11OJvy7GeSdh0fXQkSny9tknobj24zMO7xjmS474YttLEo4zuPXX8tfBrYssd3vaVn0ePU7rBbY8dIgagb4VvCNVF2z4g/xwmJjU7Ob2zfg/+7uSA39dxIRV8rNgj1Loc1QsPoY5777B+xdAe3vhuaDoF7Lok0Z3Yzb1GGRSvCvAc0HGI93Lblym6RtRln+RePKfNmy1mOx9660qB+kZKUEI2Oa8Mawjvj5WFi2M5m73l+vUv4i4lp+gca+RfZkpaAAdsyD5B2w8gVj76K3OsDSp2DvSsg9b268FaSExd11vBc63m9Mwr2SMq4Quph9X6HtiSlkZJc8Uctb9g+qrDs7N2TOIz2pWzOA3cnpDJm6jh/3VWyTSRGRSrNa4bG1cPNrcO2N4BNgbI676WP4/G74sK/ZEVaIEhZ31+oWuON9iOpz5e9nla0Gy8Ua1q5Oo9Dq5BXY2HSo5MqtWzXhtsy6Ngnlq8d70aFhCCnnchk5/SemrTuoybgiYo7qoUaJ/wfmwzMH4b4voMtoCIqAJhd9nuTnwfSbYNVLcDjerVcbqZ/f09mLxl2lLP+lYpvV4ciZc8TvP03/lmGXfT87L5+dR43em87qYSmT8JBqzHsshucW7GTBtmP84+tf+eV4Kq/e0Z5APx+zwxMRb+VfA1oONg6bDXIvGrY++hMciTeOdf+BwFpGr0yLQcbX6qGmhX0p9bB4ApsNjidA/LuXf6+MZfkvZS/TX9LQxS/H08jJLyC0hj9N6pRjXyMvF+jnw+vDOvK3W9vgY7WwYOsxhn0YT1KqZ44Zi0gVY7EUX00U1gbu/Bja3W0kK1kp8POXsOAR+L9msHmGWZFeRgmLJ8hKgU9ugOXPwal9xb9XxrL8l7InLL8mpXE28/L9iuwTbjs3qlXqFglyOYvFwpjeUcx6qDu1qvux42gqQ975kc2lDL+JiJiiWi3oMAzungZP74cHvzWWSoe1NXaPbtDe7AgLKWHxBNVqQ9SFSVK7Fhf/Xhl3ar5UWFAgzcNqYrPBxoOXrxayT7iN1vyVCut1bV2WjOtNqwZBnMrI5r6PN/D5xsNmhyUicmU+vtA4Bm58Cf603tiMMaKz2VEVUsLiKVrfZnz99ZLlzR3vhYGvlDwptxS9ri15efPWwymAVghVVqM61Vnwp1huaR9Obr6N5xf+zPMLd5KTV/bdskVETFEr0lhx5CbcJxIpXatbjTLMSQlw9qK/0ptdD7HjISK63Je0DwtdmrAcTzlPcloWPlYLHRqWr+dGLlfd35ep90fz9KCWWCzw+cYj/OGTDZxMzzY7NBERj6GExVPUrGdsNQ4lF5Erp55RdbBYYN+JDE6kZRWe33Jh/krr8CCq+2shmSNYLBbG9b+WaaO6EhTgy6ZDZ7lt6jp2HE0xOzQREY+ghMWTXGlY6NA6SNxUocqFIdX9aBdh9KBc3MtSWDBO81cc7vpW9Vk0vhdN69UgKTWLez6IZ+G2o2aHJSLi9pSweJLWtxpfz+yH7HTj8Rf3w7QbjSqGFRBbOCxUtLy5cIWQ5q84RbN6NVk0rhfXtwojO6+AP8/dzj+//pW8fM1rEREpiRIWTxIcAQ9/D3/5DQKCjPos9sSlnKuE7C6dx5KVm88vx42l0qpw6zzBgX58PLIr4/tfC8An6w4yesamKy4xFxERJSyep2EXY+kZQE6GsU4eyl2Hxa57VCi+VgtHz54n8cw5dh5LJa/ARr2gABrWruagoOVKfKwWnhrUkvf+0Jlqfj6s23eK295dx+7kNLNDExFxO0pYPJXNBpkXhnGsfuBXseSiur8v0Y1qAcaw0BYVjHO5m9uHs+BPsUSGViPxzHnufG89y3YmmR2WiIhbUcLiiTZ+CG+2hw3vG88Dg41yyxUU06yoHktRhVsNB7lS6/BglozrTa9r63AuJ58/fb6V5xbu5FyO+25EJiLiSkpYPFHuOUhNhG2fGc8rOBxkF3vRPBb7Ds0qGOd6tWv48+mD3Xm0b1MAZm88wi1vr2N7Yoq5gYmIuAElLJ7Ivrw5N9P4WsEJt3bRjWoR4GvlZHo2pzKy8fOx0O4aFYwzg6+Pledubs3nD/egQXAgB09lctf763nnu71aRSQiXk0Jiyeq0wzqtzMeh7WB7o9W6nIBvj50a1K0hXibiBAC/XwqdU2pnF7X1uXbCX24pUM4eQU2Xl/5G8M/2sCR0+eu/mIRkSpICYunanO78TUkEqL/UOnLxV5bp/CxCsa5h1rV/Zl6XzT/Gd6RoABfthw+y+C34vjf5kRsNpvZ4YmIuJQSFk9lHxY6sLpox+ZKiL0w8Ragc+Nalb6eOIbFYuGO6IYse7IP3ZuEkpmTz9Nf7uCPn21VzRYR8SpKWDxVWCuw+kJ+Dvy6uNKXaxcRTP3gAAJ8rXS/aHhI3ENkaHXmPNqT/3dTS3ytFr79JZlBb8YR99tJs0MTEXEJJSyerP9zxlffyhd48/WxMu+xGBaN60VYcGClryeO52O18Kd+17JoXC+a1avBifRsRk7/iZeW/EJWbr7Z4YmIOJXFVkUGw9PS0ggJCSE1NZXg4Mot8/UYNhukJ0NQg0rVYRHPcz4nn8nf7GJW/GEAmofV5M17O9E2Qqu7RMSzlPXzWz0snsxigeBwJSteqJq/D3+/vR0zRnejbs0A9p7IYOi7P/Lh2v3kF1SJv0FERIpRwiLiwfq3CmP5hD4MaFOf3Hwbk7/ZzR8+2cCxlPNmhyYi4lBKWEQ8XJ2aAXw0ogtT7mpPdX8fNhw4w01vxrE44ZjZoYmIOIwSFpEqwGKxMLxbI5Y90YdOkbVIz8rjyS8SeGLONlLP55odnohIpSlhEalCmtStwZdjY5hwY3N8rBaWbD/O4DfjiN9/2uzQREQqRQmLSBXj62Nlwo0t+HJsDE3qVOd4ahYT5yWQnaelzyLiuXzNDkBEnCO6UW2WPtGHfy79lZvbhxPgq/2hRMRzKWERqcJqBPgy+c4OZochIlJpGhISERERt6eERURERNyeEhYRERFxe0pYRERExO0pYRERERG3p4RFRERE3J4SFhEREXF7FUpY3nvvPaKioggMDKRLly788MMPJbYdPXo0FovlsqNt27aFbWbOnHnFNllZWRUJT0RERKqYcicsc+fOZcKECTz//PNs27aNPn36MHjwYI4cOXLF9m+99RZJSUmFR2JiIqGhodxzzz3F2gUHBxdrl5SURGBgYMXelYiIiFQp5U5Y3njjDcaMGcPDDz9M69atefPNN4mMjOT999+/YvuQkBAaNGhQeGzevJmzZ8/y4IMPFmtnsViKtWvQoEHF3pGIiIhUOeVKWHJyctiyZQsDBw4sdn7gwIGsX7++TNeYNm0aN954I40bNy52PiMjg8aNG9OwYUNuvfVWtm3bVup1srOzSUtLK3aIiIhI1VSuhOXUqVPk5+dTv379Yufr169PcnLyVV+flJTEN998w8MPP1zsfKtWrZg5cyZLlixhzpw5BAYG0qtXL/bu3VvitSZPnkxISEjhERkZWZ63IiIiIh6kQpNuLRZLsec2m+2yc1cyc+ZMatWqxdChQ4ud79mzJw888AAdO3akT58+zJs3jxYtWvDOO++UeK1JkyaRmppaeCQmJlbkrYiIiIgHKNduzXXr1sXHx+ey3pQTJ05c1utyKZvNxvTp0xkxYgT+/v6ltrVarXTr1q3UHpaAgAACAgKKXR/Q0JCIiIgHsX9u2z/HS1KuhMXf358uXbqwcuVK7rjjjsLzK1eu5Pbbby/1tWvXrmXfvn2MGTPmqvex2WwkJCTQvn37MseWnp4OoKEhERERD5Senk5ISEiJ3y9XwgIwceJERowYQdeuXYmJieGjjz7iyJEjjB07FjCGao4dO8asWbOKvW7atGn06NGDdu3aXXbNl19+mZ49e9K8eXPS0tJ4++23SUhI4N133y1zXBERESQmJhIUFFSm4amySktLIzIyksTERIKDgx12XSkf/Rzcg34O7kE/B/egn4Nj2Gw20tPTiYiIKLVduROW4cOHc/r0af7+97+TlJREu3btWLZsWeGqn6SkpMtqsqSmpjJ//nzeeuutK14zJSWFRx99lOTkZEJCQoiOjiYuLo7u3buXOS6r1UrDhg3L+3bKLDg4WP9DugH9HNyDfg7uQT8H96CfQ+WV1rNiZ7FdbdDIy6WlpRESEkJqaqr+hzSRfg7uQT8H96Cfg3vQz8G1tJeQiIiIuD0lLFcREBDAiy++WGxFkriefg7uQT8H96Cfg3vQz8G1NCQkIiIibk89LCIiIuL2lLCIiIiI21PCIiIiIm5PCYuIiIi4PSUsV/Hee+8RFRVFYGAgXbp04YcffjA7JK/y0ksvYbFYih0NGjQwO6wqLy4ujiFDhhAREYHFYmHRokXFvm+z2XjppZeIiIigWrVq9OvXj19++cWcYKuwq/0cRo8efdnvR8+ePc0JtoqaPHky3bp1IygoiLCwMIYOHcqePXuKtdHvg2soYSnF3LlzmTBhAs8//zzbtm2jT58+DB48+LJKvuJcbdu2JSkpqfDYuXOn2SFVeZmZmXTs2JGpU6de8fv//ve/eeONN5g6dSqbNm2iQYMGDBgwoHBPL3GMq/0cAG666aZivx/Lli1zYYRV39q1axk3bhwbNmxg5cqV5OXlMXDgQDIzMwvb6PfBRWxSou7du9vGjh1b7FyrVq1szz77rEkReZ8XX3zR1rFjR7PD8GqAbeHChYXPCwoKbA0aNLD961//KjyXlZVlCwkJsX3wwQcmROgdLv052Gw226hRo2y33367KfF4qxMnTtgA29q1a202m34fXEk9LCXIyclhy5YtDBw4sNj5gQMHsn79epOi8k579+4lIiKCqKgo7r33Xg4cOGB2SF7t4MGDJCcnF/vdCAgI4LrrrtPvhgnWrFlDWFgYLVq04JFHHuHEiRNmh1SlpaamAhAaGgro98GVlLCU4NSpU+Tn51O/fv1i5+vXr09ycrJJUXmfHj16MGvWLJYvX87HH39McnIysbGxnD592uzQvJb9/3/9bphv8ODBfP7553z//fe8/vrrbNq0ieuvv57s7GyzQ6uSbDYbEydOpHfv3rRr1w7Q74MrlXu3Zm9jsViKPbfZbJedE+cZPHhw4eP27dsTExNDs2bN+PTTT5k4caKJkYl+N8w3fPjwwsft2rWja9euNG7cmKVLl3LnnXeaGFnVNH78eHbs2MG6desu+55+H5xPPSwlqFu3Lj4+PpdlyCdOnLgskxbXqVGjBu3bt2fv3r1mh+K17Ku09LvhfsLDw2ncuLF+P5zg8ccfZ8mSJaxevZqGDRsWntfvg+soYSmBv78/Xbp0YeXKlcXOr1y5ktjYWJOikuzsbHbt2kV4eLjZoXitqKgoGjRoUOx3Iycnh7Vr1+p3w2SnT58mMTFRvx8OZLPZGD9+PAsWLOD7778nKiqq2Pf1++A6GhIqxcSJExkxYgRdu3YlJiaGjz76iCNHjjB27FizQ/MaTz31FEOGDKFRo0acOHGCf/7zn6SlpTFq1CizQ6vSMjIy2LdvX+HzgwcPkpCQQGhoKI0aNWLChAm8+uqrNG/enObNm/Pqq69SvXp17r//fhOjrnpK+zmEhoby0ksvcddddxEeHs6hQ4d47rnnqFu3LnfccYeJUVct48aNY/bs2SxevJigoKDCnpSQkBCqVauGxWLR74OrmLpGyQO8++67tsaNG9v8/f1tnTt3LlzKJq4xfPhwW3h4uM3Pz88WERFhu/POO22//PKL2WFVeatXr7YBlx2jRo2y2WzGUs4XX3zR1qBBA1tAQICtb9++tp07d5obdBVU2s/h3LlztoEDB9rq1atn8/PzszVq1Mg2atQo25EjR8wOu0q50n9/wDZjxozCNvp9cA2LzWazuT5NEhERESk7zWERERERt6eERURERNyeEhYRERFxe0pYRERExO0pYRERERG3p4RFRERE3J4SFhEREXF7SlhERETE7SlhEREREbenhEVERETcnhIWERERcXtKWERERMTt/X8FMn+RV79ksAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "j_blues_ctardis = pd.read_csv(\n",
    "    \"/home/afullard/tardis-chvogl-configs/j_blues_first.csv\", index_col=0\n",
    ")\n",
    "plt.plot(workflow.plasma_solver.j_blues[0])\n",
    "plt.plot(j_blues_ctardis.values[0], linestyle=\"dashed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "39f01549",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solving opacity\n",
      "First iteration use usual fb cooling rate\n",
      "Solving Monte Carlo transport\n",
      "Updating simulation\n",
      "Solving plasma\n",
      "Solving opacity\n",
      "Solving Monte Carlo transport\n",
      "Updating simulation\n",
      "Solving plasma\n",
      "Solving opacity\n",
      "Solving Monte Carlo transport\n",
      "Updating simulation\n",
      "Solving plasma\n",
      "Solving opacity\n",
      "Solving Monte Carlo transport\n",
      "Updating simulation\n",
      "Solving plasma\n"
     ]
    }
   ],
   "source": [
    "workflow.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1679b997",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "spectrum = workflow.spectrum_solver.spectrum_real_packets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e2a38876",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x650 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.figure(figsize=(10, 6.5))\n",
    "\n",
    "spectrum.plot(label=\"Normal packets\")\n",
    "\n",
    "plt.xlim(500, 9000)\n",
    "plt.title(\"TARDIS example model spectrum\")\n",
    "plt.xlabel(r\"Wavelength [$\\AA$]\")\n",
    "plt.ylabel(r\"Luminosity density [erg/s/$\\AA$]\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5241d4a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='$\\\\text{Wavelength}\\\\,[\\\\mathrm{\\\\mathring{A}}]$', ylabel='$L_{\\\\lambda}\\\\,[\\\\mathrm{erg\\\\,s^{-1}\\\\,\\\\mathring{A}^{-1}}]$'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from tardis.visualization import SDECPlotter\n",
    "import astropy.units as u\n",
    "\n",
    "plotter = SDECPlotter.from_workflow(workflow)\n",
    "\n",
    "plotter.generate_plot_mpl(packets_mode=\"real\", packet_wvl_range=[500, 9000] * u.AA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4dd61c68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_id</th>\n",
       "      <th>last_interaction_type</th>\n",
       "      <th>status</th>\n",
       "      <th>radius</th>\n",
       "      <th>shell_id</th>\n",
       "      <th>before_nu</th>\n",
       "      <th>before_mu</th>\n",
       "      <th>before_energy</th>\n",
       "      <th>after_nu</th>\n",
       "      <th>after_mu</th>\n",
       "      <th>after_energy</th>\n",
       "      <th>line_absorb_id</th>\n",
       "      <th>line_emit_id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>packet_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.600751e+15</td>\n",
       "      <td>3</td>\n",
       "      <td>3.124369e+14</td>\n",
       "      <td>-0.489532</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>1.025662e+15</td>\n",
       "      <td>0.751245</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.398319e+15</td>\n",
       "      <td>0</td>\n",
       "      <td>8.548382e+14</td>\n",
       "      <td>-0.128988</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>8.734672e+14</td>\n",
       "      <td>-0.557376</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.431680e+15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.142404e+14</td>\n",
       "      <td>-0.674727</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>4.424209e+14</td>\n",
       "      <td>-0.937859</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.463596e+15</td>\n",
       "      <td>1</td>\n",
       "      <td>2.562137e+14</td>\n",
       "      <td>0.540415</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>9.269041e+14</td>\n",
       "      <td>0.665720</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.411122e+15</td>\n",
       "      <td>0</td>\n",
       "      <td>2.787898e+14</td>\n",
       "      <td>0.960644</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>8.398528e+14</td>\n",
       "      <td>-0.810407</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499962</th>\n",
       "      <td>2.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.459952e+15</td>\n",
       "      <td>1</td>\n",
       "      <td>4.341381e+14</td>\n",
       "      <td>0.370708</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>1.044356e+15</td>\n",
       "      <td>0.857608</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499971</th>\n",
       "      <td>1.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.437563e+15</td>\n",
       "      <td>0</td>\n",
       "      <td>1.882949e+14</td>\n",
       "      <td>0.429626</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>1.259660e+15</td>\n",
       "      <td>-0.943433</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499972</th>\n",
       "      <td>1.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.409404e+15</td>\n",
       "      <td>0</td>\n",
       "      <td>2.468562e+14</td>\n",
       "      <td>0.827173</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>1.012108e+15</td>\n",
       "      <td>-0.557570</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499975</th>\n",
       "      <td>2.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.425646e+15</td>\n",
       "      <td>0</td>\n",
       "      <td>3.835769e+14</td>\n",
       "      <td>0.105933</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>9.356927e+14</td>\n",
       "      <td>0.364530</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499986</th>\n",
       "      <td>1.0</td>\n",
       "      <td>CONTINUUM_PROCESS</td>\n",
       "      <td>IN_PROCESS</td>\n",
       "      <td>1.401034e+15</td>\n",
       "      <td>0</td>\n",
       "      <td>9.205980e+13</td>\n",
       "      <td>0.704195</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>9.892475e+14</td>\n",
       "      <td>0.503802</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>51725 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           event_id last_interaction_type      status        radius  shell_id  \\\n",
       "packet_id                                                                       \n",
       "2              12.0     CONTINUUM_PROCESS  IN_PROCESS  1.600751e+15         3   \n",
       "6               2.0     CONTINUUM_PROCESS  IN_PROCESS  1.398319e+15         0   \n",
       "22              2.0     CONTINUUM_PROCESS  IN_PROCESS  1.431680e+15         0   \n",
       "25              2.0     CONTINUUM_PROCESS  IN_PROCESS  1.463596e+15         1   \n",
       "35              1.0     CONTINUUM_PROCESS  IN_PROCESS  1.411122e+15         0   \n",
       "...             ...                   ...         ...           ...       ...   \n",
       "499962          2.0     CONTINUUM_PROCESS  IN_PROCESS  1.459952e+15         1   \n",
       "499971          1.0     CONTINUUM_PROCESS  IN_PROCESS  1.437563e+15         0   \n",
       "499972          1.0     CONTINUUM_PROCESS  IN_PROCESS  1.409404e+15         0   \n",
       "499975          2.0     CONTINUUM_PROCESS  IN_PROCESS  1.425646e+15         0   \n",
       "499986          1.0     CONTINUUM_PROCESS  IN_PROCESS  1.401034e+15         0   \n",
       "\n",
       "              before_nu  before_mu  before_energy      after_nu  after_mu  \\\n",
       "packet_id                                                                   \n",
       "2          3.124369e+14  -0.489532       0.000002  1.025662e+15  0.751245   \n",
       "6          8.548382e+14  -0.128988       0.000002  8.734672e+14 -0.557376   \n",
       "22         4.142404e+14  -0.674727       0.000002  4.424209e+14 -0.937859   \n",
       "25         2.562137e+14   0.540415       0.000002  9.269041e+14  0.665720   \n",
       "35         2.787898e+14   0.960644       0.000002  8.398528e+14 -0.810407   \n",
       "...                 ...        ...            ...           ...       ...   \n",
       "499962     4.341381e+14   0.370708       0.000002  1.044356e+15  0.857608   \n",
       "499971     1.882949e+14   0.429626       0.000002  1.259660e+15 -0.943433   \n",
       "499972     2.468562e+14   0.827173       0.000002  1.012108e+15 -0.557570   \n",
       "499975     3.835769e+14   0.105933       0.000002  9.356927e+14  0.364530   \n",
       "499986     9.205980e+13   0.704195       0.000002  9.892475e+14  0.503802   \n",
       "\n",
       "           after_energy  line_absorb_id  line_emit_id  \n",
       "packet_id                                              \n",
       "2              0.000002              -1            -1  \n",
       "6              0.000002              -1            -1  \n",
       "22             0.000002              -1            -1  \n",
       "25             0.000002              -1            -1  \n",
       "35             0.000002              -1            -1  \n",
       "...                 ...             ...           ...  \n",
       "499962         0.000002              -1            -1  \n",
       "499971         0.000002              -1            -1  \n",
       "499972         0.000002              -1            -1  \n",
       "499975         0.000002              -1            -1  \n",
       "499986         0.000002              -1            -1  \n",
       "\n",
       "[51725 rows x 13 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "workflow.transport_state.tracker_last_interaction_df[workflow.transport_state.tracker_last_interaction_df[\"last_interaction_type\"] == \"CONTINUUM_PROCESS\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b23aa300",
   "metadata": {},
   "outputs": [],
   "source": [
    "from tardis.visualization.tools.liv_plot import LIVPlotter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "41cc71e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Last Interaction Velocity (km/s)', ylabel='Packet Count'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotter = LIVPlotter.from_workflow(workflow)\n",
    "\n",
    "plotter.generate_plot_mpl(packets_mode=\"real\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "424f075c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tardis",
   "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": "3.13.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}