{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Equilibrium Plasma Workflow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b4d411f9a53346ebbd65e4a73ae37734",
       "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": "0e0631fa2947466886c46f19ba2b7344",
       "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"
    },
    {
     "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 = '3.6.3'.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': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\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    }    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/1.6.1/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.6.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.6.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.6.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.6.3.min.js\", \"https://cdn.holoviz.org/panel/1.6.1/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\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": ""
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
      "text/html": [
       "<div id='92800fd8-a9c7-4ab4-aea0-0b640f7fe93a'>\n",
       "  <div id=\"f54b145c-ac78-43a5-abec-2f467b94622b\" data-root-id=\"92800fd8-a9c7-4ab4-aea0-0b640f7fe93a\" style=\"display: contents;\"></div>\n",
       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  var docs_json = {\"1a2df2de-18f5-4abf-9df9-a2aa1f448856\":{\"version\":\"3.6.3\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"92800fd8-a9c7-4ab4-aea0-0b640f7fe93a\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"b60f11b1-8bd8-41ec-851e-3204b31938c4\",\"attributes\":{\"plot_id\":\"92800fd8-a9c7-4ab4-aea0-0b640f7fe93a\",\"comm_id\":\"cb662eec629044fdacbd91f346901c76\",\"client_comm_id\":\"bcab9e2a0d9e4dd6a48be1e60c2ac4fc\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
       "  var render_items = [{\"docid\":\"1a2df2de-18f5-4abf-9df9-a2aa1f448856\",\"roots\":{\"92800fd8-a9c7-4ab4-aea0-0b640f7fe93a\":\"f54b145c-ac78-43a5-abec-2f467b94622b\"},\"root_ids\":[\"92800fd8-a9c7-4ab4-aea0-0b640f7fe93a\"]}];\n",
       "  var docs = Object.values(docs_json)\n",
       "  if (!docs) {\n",
       "    return\n",
       "  }\n",
       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
       "  async function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t  for (const child of root_el.children) {\n",
       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
       "\t  }\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ]
     },
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "92800fd8-a9c7-4ab4-aea0-0b640f7fe93a"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "import tardis\n",
    "\n",
    "from tardis.io.configuration.config_reader import Configuration\n",
    "from tardis.workflows.simple_tardis_workflow import SimpleTARDISWorkflow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "config = Configuration.from_yaml(Path(\"../../tardis/plasma/tests/data/plasma_base_test_config.yml\"))\n",
    "\n",
    "config.model.abundances = {\"type\": \"uniform\", \"H\": 0.75, \"He\": 0.25}\n",
    "\n",
    "config.plasma.initial_t_inner = 12000\n",
    "config.plasma.nlte = {\"species\": [\"H I\", \"He I\", \"He II\"], \"classical_nebular\": False, \"coronal_approximation\": False}\n",
    "config.plasma.ionization = \"nebular\"\n",
    "config.plasma.excitation = \"dilute-lte\"\n",
    "config.atom_data = \"kurucz_cd23_chianti_H_He_latest.h5\"\n",
    "\n",
    "config.montecarlo.iterations = 40\n",
    "config.montecarlo.last_no_of_packets = 1e7\n",
    "\n",
    "config.montecarlo.convergence_strategy = {\"t_rad\": {\"type\": \"damped\", \"damping_constant\": 0.5, \"threshold\": 0.01},\n",
    "                                          \"w\": {\"type\": \"damped\", \"damping_constant\": 0.5, \"threshold\": 0.01},\n",
    "                                          \"t_inner\": {\"type\": \"damped\", \"damping_constant\": 0.5, \"threshold\": 0.01},\n",
    "                                          \"t_inner_update_exponent\": -0.5,\n",
    "                                          \"lock_t_inner_cycles\": 1,\n",
    "                                          \"hold_iterations\": 4,\n",
    "                                          \"stop_if_converged\": True}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "workflow = SimpleTARDISWorkflow(config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c99ecf9be2e646bbb0c5bba04d13d502",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "TqdmHBox(children=(HTML(value='Iterations:', layout=Layout(width='6%')), FloatProgress(value=0.0, layout=Layou…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2884daa728444396948d19c1c8ba564b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "TqdmHBox(children=(HTML(value='Packets:\\u2007\\u2007\\u2007', layout=Layout(width='6%')), FloatProgress(value=0.…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "workflow.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "\n",
    "A = nx.nx_agraph.to_agraph(workflow.plasma_solver.graph)\n",
    "A.layout(prog='dot')\n",
    "A.draw('equilibrium_plasma.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "spectrum = workflow.spectrum_solver.spectrum_real_packets\n",
    "spectrum_virtual = workflow.spectrum_solver.spectrum_virtual_packets\n",
    "#spectrum_integrated = workflow.spectrum_solver.spectrum_integrated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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",
    "spectrum_virtual.plot(label=\"Virtual packets\")\n",
    "#spectrum_integrated.plot(label='Formal integral')\n",
    "\n",
    "plt.xlim(500, 9000)\n",
    "plt.title(\"TARDIS example model spectrum\")\n",
    "plt.xlabel(\"Wavelength [$\\AA$]\")\n",
    "plt.ylabel(\"Luminosity density [erg/s/$\\AA$]\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.13.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}