data_archive.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import intake\n",
    "import matplotlib.pyplot as plt\n",
    "from pathlib import Path"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The Data Catalog\n",
    "\n",
    "\n",
    "## Connecting to the Catalog with `sshfs`\n",
    "\n",
    "We can use `sshfs` to mount the catalog file system on CSD3 directly onto our local machine. The following commands show how to mount the data catalog in a new folder called `data`. The second command mounts the catalog. You will need to modify the command to use your CSD3 login name.\n",
    "\n",
    "```{note}\n",
    "This assumes you already have an account on CSD3. Please follow the guide [here](https://docs.hpc.cam.ac.uk/hpc/user-guide/quickstart.html) to setup your login.\n",
    "```\n",
    "\n",
    "```bash\n",
    "mkdir ~/mast-data\n",
    "sshfs -o allow_other,auto_cache,reconnect  ~/mast-data <your-csd3-username>@login-cpu.hpc.cam.ac.uk:/home/<your-csd3-username>/rds/rds-ukaea-mast-sPGbyCAPsJI/archive\n",
    "```\n",
    "\n",
    "\n",
    "## Opening the Catalog\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/yaml": "mast:\n  args:\n    path: /home/lhs18285/mast-data/mast/catalog.yml\n  description: The MAST Data Archive Catalog\n  driver: intake.catalog.local.YAMLFileCatalog\n  metadata:\n    version: 1\n",
      "text/plain": [
       "mast:\n",
       "  args:\n",
       "    path: /home/lhs18285/mast-data/mast/catalog.yml\n",
       "  description: The MAST Data Archive Catalog\n",
       "  driver: intake.catalog.local.YAMLFileCatalog\n",
       "  metadata:\n",
       "    version: 1\n"
      ]
     },
     "metadata": {
      "application/json": {
       "root": "mast"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "catalog = intake.open_catalog(Path('~/mast-data/mast/catalog.yml').expanduser())\n",
    "catalog"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Accessing a single record for the catalog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/yaml": "AMC_PLASMA_CURRENT:\n  args:\n    fastzarr: true\n    urlpath: /home/lhs18285/mast-data/mast/AMC_PLASMA_CURRENT.nc\n  description: Plasma Current\n  driver: intake_xarray_datatree.intake_xarray_datatree.DataTreeSource\n  metadata:\n    catalog_dir: /home/lhs18285/mast-data/mast/\n    description: Plasma Current\n    generic_name: IP\n    label: Plasma Current\n    mds_name: \\TOP.ANALYSED.AMC.PLASMA:CURRENT\n    pass_: 0\n    rank: 1\n    shape:\n    - 30000\n    shot: 28412\n    signal_name: AMC_PLASMA CURRENT\n    signal_status: 1\n    source_alias: amc\n    time_index: 0\n    type: Analysed\n    units: kA\n",
      "text/plain": [
       "AMC_PLASMA_CURRENT:\n",
       "  args:\n",
       "    fastzarr: true\n",
       "    urlpath: /home/lhs18285/mast-data/mast/AMC_PLASMA_CURRENT.nc\n",
       "  description: Plasma Current\n",
       "  driver: intake_xarray_datatree.intake_xarray_datatree.DataTreeSource\n",
       "  metadata:\n",
       "    catalog_dir: /home/lhs18285/mast-data/mast/\n",
       "    description: Plasma Current\n",
       "    generic_name: IP\n",
       "    label: Plasma Current\n",
       "    mds_name: \\TOP.ANALYSED.AMC.PLASMA:CURRENT\n",
       "    pass_: 0\n",
       "    rank: 1\n",
       "    shape:\n",
       "    - 30000\n",
       "    shot: 28412\n",
       "    signal_name: AMC_PLASMA CURRENT\n",
       "    signal_status: 1\n",
       "    source_alias: amc\n",
       "    time_index: 0\n",
       "    type: Analysed\n",
       "    units: kA\n"
      ]
     },
     "metadata": {
      "application/json": {
       "root": "AMC_PLASMA_CURRENT"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "catalog.AMC_PLASMA_CURRENT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/yaml": "shots:\n  args:\n    sql_expr: shots\n    uri: postgresql://dbreader:fairly-mast@localhost:5432/mast_db\n  description: Shot Index Table\n  driver: intake_sql.intake_sql.SQLSource\n  metadata:\n    catalog_dir: /home/lhs18285/mast-data/mast/\n",
      "text/plain": [
       "shots:\n",
       "  args:\n",
       "    sql_expr: shots\n",
       "    uri: postgresql://dbreader:fairly-mast@localhost:5432/mast_db\n",
       "  description: Shot Index Table\n",
       "  driver: intake_sql.intake_sql.SQLSource\n",
       "  metadata:\n",
       "    catalog_dir: /home/lhs18285/mast-data/mast/\n"
      ]
     },
     "metadata": {
      "application/json": {
       "root": "shots"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metadata = intake.open_catalog(Path('~/mast-data/mast/meta.yml').expanduser())\n",
    "metadata.shots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
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       "\troot.Bokeh = undefined;\n",
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       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
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       "  setTimeout(load_or_wait, 100)\n",
       "}(window));"
      ],
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i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.1.1/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.1.1/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.holoviz.org/panel/1.1.1/dist/panel.min.js\"];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      inject_raw_css(\"\\n    .scrolling {\\n      overflow: scroll;\\n    }\\n    \");\n    },    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      Bokeh = root.Bokeh;\n      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
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       "\n",
       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "    safe: true,\n",
       "    index: 0\n",
       "  });\n",
       "}\n",
       "\n",
       "if (window.Jupyter !== undefined) {\n",
       "  try {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  } catch(err) {\n",
       "  }\n",
       "}\n"
      ],
      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || 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the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>*[data-root-id],\n",
       "*[data-root-id] > * {\n",
       "  box-sizing: border-box;\n",
       "  font-family: var(--jp-ui-font-family);\n",
       "  font-size: var(--jp-ui-font-size1);\n",
       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
       "}\n",
       "\n",
       "/* Override VSCode background color */\n",
       ".cell-output-ipywidget-background:has(> .cell-output-ipywidget-background\n",
       "    > .lm-Widget\n",
       "    > *[data-root-id]),\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",
       "  var force = true;\n",
       "  var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
       "  var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n",
       "  var reloading = true;\n",
       "  var Bokeh = root.Bokeh;\n",
       "  var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
       "\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks;\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "    if (js_modules == null) js_modules = [];\n",
       "    if (js_exports == null) js_exports = {};\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    if (!reloading) {\n",
       "      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    }\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "    window._bokeh_on_load = on_load\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    var skip = [];\n",
       "    if (window.requirejs) {\n",
       "      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n",
       "      require([\"jspanel\"], function(jsPanel) {\n",
       "\twindow.jsPanel = jsPanel\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-modal\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-tooltip\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-hint\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-layout\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-contextmenu\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-dock\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"gridstack\"], function(GridStack) {\n",
       "\twindow.GridStack = GridStack\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"notyf\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      root._bokeh_is_loading = css_urls.length + 9;\n",
       "    } else {\n",
       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
       "    }\n",
       "\n",
       "    var existing_stylesheets = []\n",
       "    var links = document.getElementsByTagName('link')\n",
       "    for (var i = 0; i < links.length; i++) {\n",
       "      var link = links[i]\n",
       "      if (link.href != null) {\n",
       "\texisting_stylesheets.push(link.href)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      if (existing_stylesheets.indexOf(url) !== -1) {\n",
       "\ton_load()\n",
       "\tcontinue;\n",
       "      }\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.1.1/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.1.1/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    var existing_scripts = []\n",
       "    var scripts = document.getElementsByTagName('script')\n",
       "    for (var i = 0; i < scripts.length; i++) {\n",
       "      var script = scripts[i]\n",
       "      if (script.src != null) {\n",
       "\texisting_scripts.push(script.src)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (var i = 0; i < js_modules.length; i++) {\n",
       "      var url = js_modules[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (const name in js_exports) {\n",
       "      var url = js_exports[name];\n",
       "      if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      element.textContent = `\n",
       "      import ${name} from \"${url}\"\n",
       "      window.${name} = ${name}\n",
       "      window._bokeh_on_load()\n",
       "      `\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    if (!js_urls.length && !js_modules.length) {\n",
       "      on_load()\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [];\n",
       "  var js_modules = [];\n",
       "  var js_exports = {};\n",
       "  var css_urls = [];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      inject_raw_css(\"\\n    .scrolling {\\n      overflow: scroll;\\n    }\\n    \");\n",
       "    },    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }\n",
       "      // Cache old bokeh versions\n",
       "      if (Bokeh != undefined && !reloading) {\n",
       "\tvar NewBokeh = root.Bokeh;\n",
       "\tif (Bokeh.versions === undefined) {\n",
       "\t  Bokeh.versions = new Map();\n",
       "\t}\n",
       "\tif (NewBokeh.version !== Bokeh.version) {\n",
       "\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
       "\t}\n",
       "\troot.Bokeh = Bokeh;\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    }\n",
       "    root._bokeh_is_initializing = false\n",
       "  }\n",
       "\n",
       "  function load_or_wait() {\n",
       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
       "    // versions of Bokeh and its dependencies at the same time.\n",
       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
       "    // to determine whether there is an ongoing attempt to initialize\n",
       "    // bokeh, however for backward compatibility we also try to ensure\n",
       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
       "    // before older versions are fully initialized.\n",
       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
       "      root._bokeh_is_initializing = false;\n",
       "      root._bokeh_onload_callbacks = undefined;\n",
       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
       "      load_or_wait();\n",
       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
       "      setTimeout(load_or_wait, 100);\n",
       "    } else {\n",
       "      Bokeh = root.Bokeh;\n",
       "      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
       "      root._bokeh_is_initializing = true\n",
       "      root._bokeh_onload_callbacks = []\n",
       "      if (!reloading && (!bokeh_loaded || is_dev)) {\n",
       "\troot.Bokeh = undefined;\n",
       "      }\n",
       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "\trun_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }\n",
       "  // Give older versions of the autoload script a head-start to ensure\n",
       "  // they initialize before we start loading newer version.\n",
       "  setTimeout(load_or_wait, 100)\n",
       "}(window));"
      ],
      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n  var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n  var reloading = true;\n  var Bokeh = root.Bokeh;\n  var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      run_callbacks();\n      return null;\n    }\n    if (!reloading) {\n      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n      })\n      require([\"jspanel-modal\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-tooltip\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-hint\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-layout\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-dock\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 9;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    var existing_stylesheets = []\n    var links = document.getElementsByTagName('link')\n    for (var i = 0; i < links.length; i++) {\n      var link = links[i]\n      if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n      }\n    }\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.1.1/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.1.1/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.1.1/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      inject_raw_css(\"\\n    .scrolling {\\n      overflow: scroll;\\n    }\\n    \");\n    },    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      Bokeh = root.Bokeh;\n      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
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     "output_type": "display_data"
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       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
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\",{\"id\":\"182d684d-b50a-427b-ae4c-1360008be1f3\"},{\"id\":\"55ec07fd-b4b3-49f2-85c9-8f3dc8e97dbf\"},{\"id\":\"5e3b99fc-955a-4eb5-861b-0fe856ff82b5\"}],\"max_width\":5000,\"margin\":0,\"width_policy\":\"max\",\"height_policy\":\"min\",\"align\":\"start\"}},{\"type\":\"object\",\"name\":\"Column\",\"id\":\"5f6a5097-6e59-49fb-abe0-856177b0342d\",\"attributes\":{\"name\":\"Add Catalog\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: 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       "  var render_items = [{\"docid\":\"83549353-d110-44f6-a46c-630375fd50d8\",\"roots\":{\"cffca749-39cf-4bae-8844-10fe181dda3d\":\"abe4a537-1d18-4488-abb9-984e95e0e1cc\"},\"root_ids\":[\"cffca749-39cf-4bae-8844-10fe181dda3d\"]}];\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",
       "  const is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1\n",
       "  function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version && !is_dev) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "Column(width_policy='max')\n",
       "    [0] Row(width_policy='max')\n",
       "        [0] PNG(str)\n",
       "        [1] Column(width_policy='max')\n",
       "            [0] Column(name='Select Catalog')\n",
       "                [0] Markdown(str, max_height=40)\n",
       "                [1] MultiSelect(min_width=200, options={'mast': <Intake catalog: ...}, size=9, value=[<Intake catalog: mast>], width_policy='min')\n",
       "            [1] Row(name='Controls')\n",
       "                [0] Toggle(name='＋', width=50)\n",
       "                [1] Button(name='―', width=50)\n",
       "                [2] Toggle(name='🔍', width=50)\n",
       "        [2] Column(width_policy='max')\n",
       "            [0] Column(name='Select Data Source')\n",
       "                [0] Markdown(str, max_height=40)\n",
       "                [1] MultiSelect(min_width=200, options=OrderedDict([('ABM_CALIB_S...]), size=9, value=[name: ABM_CALIB_SHOT\n",
       "cont...], width_policy='min')\n",
       "            [1] Row(name='Controls')\n",
       "                [0] Toggle(name='📊', width=50)\n",
       "                [1] Toggle(disabled=True, name='⚙', width=50)\n",
       "        [3] Column(height=240, name='Description', scroll=True, sizing_mode='stretch_width', width_policy='max')\n",
       "            [0] Markdown(str)\n",
       "    [1] Row(width_policy='max')\n",
       "        [0] Row(height_policy='min', max_width=5000, name='Search', width_policy='max')\n",
       "        [1] Column(max_width=5000, name='Add Catalog', width_policy='max')\n",
       "        [2] Column(name='Plot', width_policy='max')"
      ]
     },
     "execution_count": 5,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "cffca749-39cf-4bae-8844-10fe181dda3d"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gui = intake.interface.gui.GUI([catalog, metadata])\n",
    "gui"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Relevant Shot Metadata\n",
    "\n",
    "Load all shot metadata for the MAST M9 Campaign. Sort by shot id."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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",
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       "    }\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>shot_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>reference_shot</th>\n",
       "      <th>scenario</th>\n",
       "      <th>current_range</th>\n",
       "      <th>heating</th>\n",
       "      <th>divertor_config</th>\n",
       "      <th>pellets</th>\n",
       "      <th>plasma_shape</th>\n",
       "      <th>rmp_coil</th>\n",
       "      <th>...</th>\n",
       "      <th>cpf_vol_ipmax</th>\n",
       "      <th>cpf_vol_max</th>\n",
       "      <th>cpf_vol_truby</th>\n",
       "      <th>cpf_wmhd_ipmax</th>\n",
       "      <th>cpf_wmhd_max</th>\n",
       "      <th>cpf_wmhd_truby</th>\n",
       "      <th>cpf_zeff_ipmax</th>\n",
       "      <th>cpf_zeff_max</th>\n",
       "      <th>cpf_zeff_truby</th>\n",
       "      <th>cpf_zmag_efit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18491</th>\n",
       "      <td>30469</td>\n",
       "      <td>2013-09-27 14:39:00+00:00</td>\n",
       "      <td>30467.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>700 kA</td>\n",
       "      <td>SS Beam</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>False</td>\n",
       "      <td>Connected Double Null</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>8.988730</td>\n",
       "      <td>9.047923</td>\n",
       "      <td>0.0</td>\n",
       "      <td>47466.250</td>\n",
       "      <td>49115.805</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.015299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18492</th>\n",
       "      <td>30470</td>\n",
       "      <td>2013-09-27 15:03:00+00:00</td>\n",
       "      <td>30467.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>700 kA</td>\n",
       "      <td>SS Beam</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>False</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>9.687049</td>\n",
       "      <td>10.055509</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17290.434</td>\n",
       "      <td>22310.516</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.015164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18493</th>\n",
       "      <td>30471</td>\n",
       "      <td>2013-09-27 15:20:00+00:00</td>\n",
       "      <td>30470.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>700 kA</td>\n",
       "      <td>SS Beam</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>False</td>\n",
       "      <td>Lower Single Null</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>8.817559</td>\n",
       "      <td>9.283702</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38063.582</td>\n",
       "      <td>40906.090</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.014340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18494</th>\n",
       "      <td>30472</td>\n",
       "      <td>2013-09-27 15:36:00+00:00</td>\n",
       "      <td>16492.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>Ohmic</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>False</td>\n",
       "      <td>Connected Double Null</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18495</th>\n",
       "      <td>30473</td>\n",
       "      <td>2013-09-27 15:51:00+00:00</td>\n",
       "      <td>16492.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>Ohmic</td>\n",
       "      <td>Conventional</td>\n",
       "      <td>False</td>\n",
       "      <td>Connected Double Null</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 280 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       shot_id                 timestamp  reference_shot  scenario  \\\n",
       "18491    30469 2013-09-27 14:39:00+00:00         30467.0       3.0   \n",
       "18492    30470 2013-09-27 15:03:00+00:00         30467.0       2.0   \n",
       "18493    30471 2013-09-27 15:20:00+00:00         30470.0       2.0   \n",
       "18494    30472 2013-09-27 15:36:00+00:00         16492.0       NaN   \n",
       "18495    30473 2013-09-27 15:51:00+00:00         16492.0       NaN   \n",
       "\n",
       "      current_range  heating divertor_config pellets           plasma_shape  \\\n",
       "18491        700 kA  SS Beam    Conventional   False  Connected Double Null   \n",
       "18492        700 kA  SS Beam    Conventional   False                   None   \n",
       "18493        700 kA  SS Beam    Conventional   False      Lower Single Null   \n",
       "18494          None    Ohmic    Conventional   False  Connected Double Null   \n",
       "18495          None    Ohmic    Conventional   False  Connected Double Null   \n",
       "\n",
       "      rmp_coil  ... cpf_vol_ipmax cpf_vol_max cpf_vol_truby cpf_wmhd_ipmax  \\\n",
       "18491    False  ...      8.988730    9.047923           0.0      47466.250   \n",
       "18492     None  ...      9.687049   10.055509           0.0      17290.434   \n",
       "18493    False  ...      8.817559    9.283702           0.0      38063.582   \n",
       "18494    False  ...           NaN         NaN           NaN            NaN   \n",
       "18495    False  ...           NaN         NaN           NaN            NaN   \n",
       "\n",
       "      cpf_wmhd_max  cpf_wmhd_truby  cpf_zeff_ipmax  cpf_zeff_max  \\\n",
       "18491    49115.805             0.0             NaN           NaN   \n",
       "18492    22310.516             0.0             NaN           NaN   \n",
       "18493    40906.090             0.0             NaN           NaN   \n",
       "18494          NaN             NaN             NaN           NaN   \n",
       "18495          NaN             NaN             NaN           NaN   \n",
       "\n",
       "       cpf_zeff_truby  cpf_zmag_efit  \n",
       "18491             NaN       0.015299  \n",
       "18492             NaN       0.015164  \n",
       "18493             NaN       0.014340  \n",
       "18494             NaN       0.000000  \n",
       "18495             NaN       0.000000  \n",
       "\n",
       "[5 rows x 280 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shot_index = metadata.shots.read()\n",
    "shot_index = shot_index[shot_index.campaign == 'M9']\n",
    "shot_index = shot_index.sort_values('shot_id')\n",
    "shot_index.tail()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading Plasma Current\n",
    "\n",
    "Load data from the data catalog directly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of shots in dataset: 1580\n"
     ]
    }
   ],
   "source": [
    "dataset = catalog.AMC_PLASMA_CURRENT.read()\n",
    "print(\"Number of shots in dataset:\", len(dataset))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look at a single shot in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 30000)\n",
       "Coordinates:\n",
       "  * time     (time) float32 -2.0 -2.0 -2.0 -1.999 -1.999 ... 3.999 3.999 4.0 4.0\n",
       "Data variables:\n",
       "    error    (time) float32 dask.array&lt;chunksize=(30000,), meta=np.ndarray&gt;\n",
       "    data     (time) float32 dask.array&lt;chunksize=(30000,), meta=np.ndarray&gt;\n",
       "Attributes: (12/14)\n",
       "    signal_name:    AMC_PLASMA CURRENT\n",
       "    label:          Plasma Current\n",
       "    type:           Analysed\n",
       "    generic_name:   IP\n",
       "    source_alias:   amc\n",
       "    mds_name:       \\TOP.ANALYSED.AMC.PLASMA:CURRENT\n",
       "    ...             ...\n",
       "    signal_status:  1\n",
       "    pass_:          0\n",
       "    units:          kA\n",
       "    rank:           1\n",
       "    time_index:     0\n",
       "    description:    Plasma Current</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-655291cf-2400-4e27-83b2-3ee17eb52e9e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-655291cf-2400-4e27-83b2-3ee17eb52e9e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 30000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ddeccc6b-c029-4bd0-bc25-c6eee21d56b7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ddeccc6b-c029-4bd0-bc25-c6eee21d56b7' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-2.0 -2.0 -2.0 ... 3.999 4.0 4.0</div><input id='attrs-6f660e8b-12cf-4891-a11f-d92b7e067f39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f660e8b-12cf-4891-a11f-d92b7e067f39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be0c20ca-b6da-449e-962e-594fccadfaac' class='xr-var-data-in' type='checkbox'><label for='data-be0c20ca-b6da-449e-962e-594fccadfaac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([-2.      , -1.9998  , -1.9996  , ...,  3.999399,  3.9996  ,  3.999799],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e7c56c15-93bd-407b-8259-e0c3777b0efa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e7c56c15-93bd-407b-8259-e0c3777b0efa' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(30000,), meta=np.ndarray&gt;</div><input id='attrs-5a6b65f8-d1a8-4642-9352-58beb789a062' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5a6b65f8-d1a8-4642-9352-58beb789a062' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4f9f7d6-0e7b-4665-8562-865675b9b6a3' class='xr-var-data-in' type='checkbox'><label for='data-a4f9f7d6-0e7b-4665-8562-865675b9b6a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                        <td> </td>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 117.19 kiB </td>\n",
       "                        <td> 117.19 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (30000,) </td>\n",
       "                        <td> (30000,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >30000</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(30000,), meta=np.ndarray&gt;</div><input id='attrs-3bb8df12-b0c8-48dc-af32-fb8637c177c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3bb8df12-b0c8-48dc-af32-fb8637c177c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b62ac1f6-fa8d-4261-85c7-3800ed1a9906' class='xr-var-data-in' type='checkbox'><label for='data-b62ac1f6-fa8d-4261-85c7-3800ed1a9906' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 117.19 kiB </td>\n",
       "                        <td> 117.19 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (30000,) </td>\n",
       "                        <td> (30000,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >30000</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-26897b95-eaf5-42c6-addf-5bd67024fb08' class='xr-section-summary-in' type='checkbox'  ><label for='section-26897b95-eaf5-42c6-addf-5bd67024fb08' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e7653245-6528-4a62-955e-cefd924c578c' class='xr-index-data-in' type='checkbox'/><label for='index-e7653245-6528-4a62-955e-cefd924c578c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -2.000000238418579,  -1.999800205230713, -1.9996002912521362,\n",
       "         -1.99940025806427, -1.9992002248764038, -1.9990001916885376,\n",
       "        -1.998800277709961, -1.9986002445220947, -1.9984002113342285,\n",
       "       -1.9982002973556519,\n",
       "       ...\n",
       "         3.997999429702759,   3.998199701309204,   3.998399496078491,\n",
       "        3.9985997676849365,  3.9987995624542236,   3.998999834060669,\n",
       "         3.999199628829956,   3.999399423599243,  3.9995996952056885,\n",
       "        3.9997994899749756],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;time&#x27;, length=30000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-544f05c3-b460-419c-9cee-73f75e7485b3' class='xr-section-summary-in' type='checkbox'  ><label for='section-544f05c3-b460-419c-9cee-73f75e7485b3' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>signal_name :</span></dt><dd>AMC_PLASMA CURRENT</dd><dt><span>label :</span></dt><dd>Plasma Current</dd><dt><span>type :</span></dt><dd>Analysed</dd><dt><span>generic_name :</span></dt><dd>IP</dd><dt><span>source_alias :</span></dt><dd>amc</dd><dt><span>mds_name :</span></dt><dd>\\TOP.ANALYSED.AMC.PLASMA:CURRENT</dd><dt><span>shot :</span></dt><dd>28977</dd><dt><span>shape :</span></dt><dd>30000</dd><dt><span>signal_status :</span></dt><dd>1</dd><dt><span>pass_ :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>kA</dd><dt><span>rank :</span></dt><dd>1</dd><dt><span>time_index :</span></dt><dd>0</dd><dt><span>description :</span></dt><dd>Plasma Current</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 30000)\n",
       "Coordinates:\n",
       "  * time     (time) float32 -2.0 -2.0 -2.0 -1.999 -1.999 ... 3.999 3.999 4.0 4.0\n",
       "Data variables:\n",
       "    error    (time) float32 dask.array<chunksize=(30000,), meta=np.ndarray>\n",
       "    data     (time) float32 dask.array<chunksize=(30000,), meta=np.ndarray>\n",
       "Attributes: (12/14)\n",
       "    signal_name:    AMC_PLASMA CURRENT\n",
       "    label:          Plasma Current\n",
       "    type:           Analysed\n",
       "    generic_name:   IP\n",
       "    source_alias:   amc\n",
       "    mds_name:       \\TOP.ANALYSED.AMC.PLASMA:CURRENT\n",
       "    ...             ...\n",
       "    signal_status:  1\n",
       "    pass_:          0\n",
       "    units:          kA\n",
       "    rank:           1\n",
       "    time_index:     0\n",
       "    description:    Plasma Current"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['28977'].to_dataset()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look at the last 10 shots in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Time')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shot_nums = shot_index.shot_id.values.astype(str)\n",
    "shot_nums = shot_nums[-10:]\n",
    "\n",
    "dt = dataset.filter(lambda x: x.name in shot_nums)\n",
    "\n",
    "for index, shot in dt.items():\n",
    "    plt.plot(shot.time, shot.data)\n",
    "\n",
    "plt.ylabel(f'Current ({shot.attrs[\"units\"]})')\n",
    "plt.xlabel(f'Time')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Slice the last 10 shots along the time axis. Data is lazy loaded at the time of plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Time')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shot_nums = shot_index.shot_id.values.astype(str)\n",
    "shot_nums = shot_nums[-10:]\n",
    "\n",
    "dt = dataset.filter(lambda x: x.name in shot_nums)\n",
    "dt = dt.sel(time=slice(0., .25))\n",
    "\n",
    "for index, shot in dt.items():\n",
    "    plt.plot(shot.time, shot.data)\n",
    "\n",
    "plt.ylabel(f'Current ({shot.attrs[\"units\"]})')\n",
    "plt.xlabel(f'Time')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading EFM Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "efm_dataset = catalog.EFM_PSI_R_Z.read()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look at one time from the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "  display: none;\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
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       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
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       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
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       "  padding-right: 5px;\n",
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       "\n",
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       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
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       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
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       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
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       "\n",
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       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       ".xr-var-data,\n",
       ".xr-index-data {\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "  grid-template-columns: 125px auto;\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
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       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (height: 65, time: 71, radius: 65)\n",
       "Coordinates:\n",
       "  * height   (height) float32 -2.0 -1.938 -1.875 -1.812 ... 1.875 1.938 2.0\n",
       "  * time     (time) float32 -0.05 -0.045 -0.04 -0.035 ... 0.285 0.295 0.3 0.305\n",
       "  * radius   (radius) float32 0.06 0.09031 0.1206 0.1509 ... 1.939 1.97 2.0\n",
       "Data variables:\n",
       "    error    (time, height, radius) float32 dask.array&lt;chunksize=(71, 65, 65), meta=np.ndarray&gt;\n",
       "    data     (time, height, radius) float32 dask.array&lt;chunksize=(71, 65, 65), meta=np.ndarray&gt;\n",
       "Attributes: (12/14)\n",
       "    signal_name:    EFM_PSI(R,Z)\n",
       "    label:          psi(r,z)\n",
       "    type:           Analysed\n",
       "    generic_name:   \n",
       "    source_alias:   efm\n",
       "    mds_name:       \\TOP.ANALYSED.EFM:PSI_R_Z\n",
       "    ...             ...\n",
       "    signal_status:  1\n",
       "    pass_:          0\n",
       "    units:          Wb/rad\n",
       "    rank:           3\n",
       "    time_index:     0\n",
       "    description:    Poloidal magnetic flux per toroidal radian as a function ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4becc800-3278-4313-81a4-16858acd5141' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4becc800-3278-4313-81a4-16858acd5141' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>height</span>: 65</li><li><span class='xr-has-index'>time</span>: 71</li><li><span class='xr-has-index'>radius</span>: 65</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5eaecf50-ecb4-4752-b376-42498372b82c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5eaecf50-ecb4-4752-b376-42498372b82c' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-2.0 -1.938 -1.875 ... 1.938 2.0</div><input id='attrs-1d5095aa-765a-4fc8-80d4-c8492988c077' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d5095aa-765a-4fc8-80d4-c8492988c077' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b5d7e0b-cc19-49ad-bab4-e307dcd06613' class='xr-var-data-in' type='checkbox'><label for='data-5b5d7e0b-cc19-49ad-bab4-e307dcd06613' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-2.    , -1.9375, -1.875 , -1.8125, -1.75  , -1.6875, -1.625 , -1.5625,\n",
       "       -1.5   , -1.4375, -1.375 , -1.3125, -1.25  , -1.1875, -1.125 , -1.0625,\n",
       "       -1.    , -0.9375, -0.875 , -0.8125, -0.75  , -0.6875, -0.625 , -0.5625,\n",
       "       -0.5   , -0.4375, -0.375 , -0.3125, -0.25  , -0.1875, -0.125 , -0.0625,\n",
       "        0.    ,  0.0625,  0.125 ,  0.1875,  0.25  ,  0.3125,  0.375 ,  0.4375,\n",
       "        0.5   ,  0.5625,  0.625 ,  0.6875,  0.75  ,  0.8125,  0.875 ,  0.9375,\n",
       "        1.    ,  1.0625,  1.125 ,  1.1875,  1.25  ,  1.3125,  1.375 ,  1.4375,\n",
       "        1.5   ,  1.5625,  1.625 ,  1.6875,  1.75  ,  1.8125,  1.875 ,  1.9375,\n",
       "        2.    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05 -0.045 -0.04 ... 0.3 0.305</div><input id='attrs-d0f42bac-7587-4649-af17-4d264d2e3e5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0f42bac-7587-4649-af17-4d264d2e3e5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-320a7ce7-b697-4ea7-9bbf-18bd9836be5c' class='xr-var-data-in' type='checkbox'><label for='data-320a7ce7-b697-4ea7-9bbf-18bd9836be5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>S</dd></dl></div><div class='xr-var-data'><pre>array([-0.05 , -0.045, -0.04 , -0.035, -0.03 , -0.025, -0.02 , -0.015, -0.01 ,\n",
       "       -0.005,  0.   ,  0.005,  0.01 ,  0.015,  0.02 ,  0.025,  0.03 ,  0.035,\n",
       "        0.04 ,  0.045,  0.05 ,  0.055,  0.06 ,  0.065,  0.07 ,  0.075,  0.08 ,\n",
       "        0.085,  0.09 ,  0.095,  0.1  ,  0.105,  0.11 ,  0.115,  0.12 ,  0.125,\n",
       "        0.13 ,  0.135,  0.14 ,  0.145,  0.15 ,  0.155,  0.16 ,  0.165,  0.17 ,\n",
       "        0.175,  0.18 ,  0.185,  0.19 ,  0.195,  0.2  ,  0.205,  0.21 ,  0.215,\n",
       "        0.22 ,  0.225,  0.23 ,  0.235,  0.24 ,  0.245,  0.25 ,  0.255,  0.26 ,\n",
       "        0.265,  0.27 ,  0.275,  0.28 ,  0.285,  0.295,  0.3  ,  0.305],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>radius</span></div><div class='xr-var-dims'>(radius)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.06 0.09031 0.1206 ... 1.97 2.0</div><input id='attrs-06723e84-2fd1-4306-8485-cf1031d9204d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06723e84-2fd1-4306-8485-cf1031d9204d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cf5a14e-63b1-4e08-ace6-b88b13a0bb26' class='xr-var-data-in' type='checkbox'><label for='data-9cf5a14e-63b1-4e08-ace6-b88b13a0bb26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0.06    , 0.090312, 0.120625, 0.150937, 0.18125 , 0.211563, 0.241875,\n",
       "       0.272188, 0.3025  , 0.332813, 0.363125, 0.393438, 0.42375 , 0.454063,\n",
       "       0.484375, 0.514687, 0.545   , 0.575312, 0.605625, 0.635938, 0.66625 ,\n",
       "       0.696563, 0.726875, 0.757188, 0.7875  , 0.817813, 0.848125, 0.878438,\n",
       "       0.90875 , 0.939063, 0.969375, 0.999688, 1.03    , 1.060313, 1.090625,\n",
       "       1.120937, 1.15125 , 1.181562, 1.211875, 1.242188, 1.2725  , 1.302812,\n",
       "       1.333125, 1.363438, 1.39375 , 1.424062, 1.454375, 1.484687, 1.515   ,\n",
       "       1.545313, 1.575625, 1.605937, 1.63625 , 1.666562, 1.696875, 1.727188,\n",
       "       1.7575  , 1.787812, 1.818125, 1.848438, 1.87875 , 1.909063, 1.939375,\n",
       "       1.969687, 2.      ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a26da0e-4468-43c4-8bc4-166f91ebc9cc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6a26da0e-4468-43c4-8bc4-166f91ebc9cc' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time, height, radius)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(71, 65, 65), meta=np.ndarray&gt;</div><input id='attrs-73606781-5b09-4b4c-99e5-c6d43e5c1d41' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-73606781-5b09-4b4c-99e5-c6d43e5c1d41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-806f2db5-a95a-4369-b55e-c8467e4b7703' class='xr-var-data-in' type='checkbox'><label for='data-806f2db5-a95a-4369-b55e-c8467e4b7703' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.14 MiB </td>\n",
       "                        <td> 1.14 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (71, 65, 65) </td>\n",
       "                        <td> (71, 65, 65) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "          -1.5, -1.4375,  -1.375, -1.3125,   -1.25, -1.1875,  -1.125, -1.0625,\n",
       "          -1.0, -0.9375,  -0.875, -0.8125,   -0.75, -0.6875,  -0.625, -0.5625,\n",
       "          -0.5, -0.4375,  -0.375, -0.3125,   -0.25, -0.1875,  -0.125, -0.0625,\n",
       "           0.0,  0.0625,   0.125,  0.1875,    0.25,  0.3125,   0.375,  0.4375,\n",
       "           0.5,  0.5625,   0.625,  0.6875,    0.75,  0.8125,   0.875,  0.9375,\n",
       "           1.0,  1.0625,   1.125,  1.1875,    1.25,  1.3125,   1.375,  1.4375,\n",
       "           1.5,  1.5625,   1.625,  1.6875,    1.75,  1.8125,   1.875,  1.9375,\n",
       "           2.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;height&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-663758d9-2299-4abc-99c4-d034e4acbfe0' class='xr-index-data-in' type='checkbox'/><label for='index-663758d9-2299-4abc-99c4-d034e4acbfe0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -0.04999999701976776, -0.044999998062849045,  -0.03999999910593033,\n",
       "        -0.03500000014901161, -0.029999999329447746,  -0.02499999850988388,\n",
       "       -0.019999999552965164, -0.014999999664723873, -0.009999999776482582,\n",
       "       -0.004999999888241291,                   0.0,  0.004999999888241291,\n",
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       "         0.02499999850988388,  0.029999999329447746,   0.03500000014901161,\n",
       "         0.03999999910593033,  0.044999998062849045,   0.04999999701976776,\n",
       "        0.054999999701976776,   0.05999999865889549,   0.06499999761581421,\n",
       "         0.07000000029802322,   0.07499999552965164,   0.07999999821186066,\n",
       "         0.08500000089406967,   0.08999999612569809,    0.0949999988079071,\n",
       "         0.09999999403953552,   0.10499999672174454,   0.10999999940395355,\n",
       "         0.11499999463558197,   0.11999999731779099,                 0.125,\n",
       "         0.12999999523162842,   0.13499999046325684,   0.14000000059604645,\n",
       "         0.14499999582767487,   0.14999999105930328,    0.1550000011920929,\n",
       "          0.1599999964237213,   0.16499999165534973,   0.17000000178813934,\n",
       "         0.17499999701976776,   0.17999999225139618,    0.1850000023841858,\n",
       "          0.1899999976158142,   0.19499999284744263,   0.19999998807907104,\n",
       "         0.20499999821186066,   0.20999999344348907,    0.2149999886751175,\n",
       "          0.2199999988079071,   0.22499999403953552,   0.22999998927116394,\n",
       "         0.23499999940395355,   0.23999999463558197,    0.2449999898672104,\n",
       "                        0.25,    0.2549999952316284,   0.25999999046325684,\n",
       "         0.26499998569488525,   0.26999998092651367,    0.2750000059604645,\n",
       "          0.2800000011920929,    0.2849999964237213,   0.29499998688697815,\n",
       "         0.29999998211860657,    0.3050000071525574],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;time&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>radius</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ea5893f6-0038-44ba-b0c1-e10b0c53014c' class='xr-index-data-in' type='checkbox'/><label for='index-ea5893f6-0038-44ba-b0c1-e10b0c53014c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.05999999865889549, 0.09031249582767487, 0.12062500417232513,\n",
       "        0.1509374976158142, 0.18125000596046448, 0.21156251430511475,\n",
       "       0.24187500774860382,  0.2721875011920929, 0.30250000953674316,\n",
       "       0.33281251788139343,  0.3631250262260437,  0.3934375047683716,\n",
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       "        0.5146874785423279,  0.5450000166893005,  0.5753124952316284,\n",
       "        0.6056250333786011,   0.635937511920929,  0.6662500500679016,\n",
       "        0.6965625286102295,  0.7268750071525574,    0.75718754529953,\n",
       "        0.7875000238418579,  0.8178125023841858,  0.8481250405311584,\n",
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       "                 1.2421875,  1.2725000381469727,  1.3028124570846558,\n",
       "        1.3331249952316284,   1.363437533378601,  1.3937499523162842,\n",
       "        1.4240624904632568,  1.4543750286102295,  1.4846874475479126,\n",
       "        1.5149999856948853,   1.545312523841858,   1.575624942779541,\n",
       "        1.6059374809265137,  1.6362500190734863,  1.6665624380111694,\n",
       "         1.696874976158142,  1.7271875143051147,  1.7574999332427979,\n",
       "        1.7878124713897705,  1.8181250095367432,  1.8484375476837158,\n",
       "         1.878749966621399,  1.9090625047683716,  1.9393750429153442,\n",
       "        1.9696874618530273,                 2.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;radius&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e800d166-d9e3-404c-aa36-3acba5721034' class='xr-section-summary-in' type='checkbox'  ><label for='section-e800d166-d9e3-404c-aa36-3acba5721034' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>signal_name :</span></dt><dd>EFM_PSI(R,Z)</dd><dt><span>label :</span></dt><dd>psi(r,z)</dd><dt><span>type :</span></dt><dd>Analysed</dd><dt><span>generic_name :</span></dt><dd></dd><dt><span>source_alias :</span></dt><dd>efm</dd><dt><span>mds_name :</span></dt><dd>\\TOP.ANALYSED.EFM:PSI_R_Z</dd><dt><span>shot :</span></dt><dd>28977</dd><dt><span>shape :</span></dt><dd>[71 65 65]</dd><dt><span>signal_status :</span></dt><dd>1</dd><dt><span>pass_ :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>Wb/rad</dd><dt><span>rank :</span></dt><dd>3</dd><dt><span>time_index :</span></dt><dd>0</dd><dt><span>description :</span></dt><dd>Poloidal magnetic flux per toroidal radian as a function of radius and height; f(nw, nh, B)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (height: 65, time: 71, radius: 65)\n",
       "Coordinates:\n",
       "  * height   (height) float32 -2.0 -1.938 -1.875 -1.812 ... 1.875 1.938 2.0\n",
       "  * time     (time) float32 -0.05 -0.045 -0.04 -0.035 ... 0.285 0.295 0.3 0.305\n",
       "  * radius   (radius) float32 0.06 0.09031 0.1206 0.1509 ... 1.939 1.97 2.0\n",
       "Data variables:\n",
       "    error    (time, height, radius) float32 dask.array<chunksize=(71, 65, 65), meta=np.ndarray>\n",
       "    data     (time, height, radius) float32 dask.array<chunksize=(71, 65, 65), meta=np.ndarray>\n",
       "Attributes: (12/14)\n",
       "    signal_name:    EFM_PSI(R,Z)\n",
       "    label:          psi(r,z)\n",
       "    type:           Analysed\n",
       "    generic_name:   \n",
       "    source_alias:   efm\n",
       "    mds_name:       \\TOP.ANALYSED.EFM:PSI_R_Z\n",
       "    ...             ...\n",
       "    signal_status:  1\n",
       "    pass_:          0\n",
       "    units:          Wb/rad\n",
       "    rank:           3\n",
       "    time_index:     0\n",
       "    description:    Poloidal magnetic flux per toroidal radian as a function ..."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "efm_dataset['28977'].to_dataset()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look at the data array itself. The array is not yet loaded, but we can see its size and shape."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;data&#x27; (time: 71, height: 65, radius: 65)&gt;\n",
       "dask.array&lt;open_dataset-data, shape=(71, 65, 65), dtype=float32, chunksize=(71, 65, 65), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * height   (height) float32 -2.0 -1.938 -1.875 -1.812 ... 1.875 1.938 2.0\n",
       "  * time     (time) float32 -0.05 -0.045 -0.04 -0.035 ... 0.285 0.295 0.3 0.305\n",
       "  * radius   (radius) float32 0.06 0.09031 0.1206 0.1509 ... 1.939 1.97 2.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'data'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 71</li><li><span class='xr-has-index'>height</span>: 65</li><li><span class='xr-has-index'>radius</span>: 65</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fe0eaa32-5c86-45d9-93af-1548d09724fd' class='xr-array-in' type='checkbox' checked><label for='section-fe0eaa32-5c86-45d9-93af-1548d09724fd' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(71, 65, 65), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.14 MiB </td>\n",
       "                        <td> 1.14 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (71, 65, 65) </td>\n",
       "                        <td> (71, 65, 65) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"240\" height=\"230\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"109\" x2=\"80\" y2=\"180\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"109\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"180\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,180.44739022369512 10.0,109.85915492957747\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"119\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"190\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"119\" y1=\"0\" x2=\"190\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 119.85915492957747,0.0 190.44739022369512,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"190\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"180\" x2=\"190\" y2=\"180\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"180\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"190\" y1=\"70\" x2=\"190\" y2=\"180\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 190.44739022369512,70.58823529411765 190.44739022369512,180.44739022369512 80.58823529411765,180.44739022369512\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"135.517813\" y=\"200.447390\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >65</text>\n",
       "  <text x=\"210.447390\" y=\"125.517813\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,210.447390,125.517813)\">65</text>\n",
       "  <text x=\"35.294118\" y=\"165.153273\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,165.153273)\">71</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-64dc0663-294c-4741-8a6e-3497ed279e0d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-64dc0663-294c-4741-8a6e-3497ed279e0d' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-2.0 -1.938 -1.875 ... 1.938 2.0</div><input id='attrs-74e611d5-3850-46cd-87c1-15ef69bd3542' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74e611d5-3850-46cd-87c1-15ef69bd3542' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfecd2fc-648b-465f-9d7c-8b20d0e59965' class='xr-var-data-in' type='checkbox'><label for='data-dfecd2fc-648b-465f-9d7c-8b20d0e59965' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-2.    , -1.9375, -1.875 , -1.8125, -1.75  , -1.6875, -1.625 , -1.5625,\n",
       "       -1.5   , -1.4375, -1.375 , -1.3125, -1.25  , -1.1875, -1.125 , -1.0625,\n",
       "       -1.    , -0.9375, -0.875 , -0.8125, -0.75  , -0.6875, -0.625 , -0.5625,\n",
       "       -0.5   , -0.4375, -0.375 , -0.3125, -0.25  , -0.1875, -0.125 , -0.0625,\n",
       "        0.    ,  0.0625,  0.125 ,  0.1875,  0.25  ,  0.3125,  0.375 ,  0.4375,\n",
       "        0.5   ,  0.5625,  0.625 ,  0.6875,  0.75  ,  0.8125,  0.875 ,  0.9375,\n",
       "        1.    ,  1.0625,  1.125 ,  1.1875,  1.25  ,  1.3125,  1.375 ,  1.4375,\n",
       "        1.5   ,  1.5625,  1.625 ,  1.6875,  1.75  ,  1.8125,  1.875 ,  1.9375,\n",
       "        2.    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05 -0.045 -0.04 ... 0.3 0.305</div><input id='attrs-59912b0c-1bab-4bcb-bf03-1ef56a0a1166' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59912b0c-1bab-4bcb-bf03-1ef56a0a1166' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23e21f54-5f8a-462b-bd67-f27af69159cc' class='xr-var-data-in' type='checkbox'><label for='data-23e21f54-5f8a-462b-bd67-f27af69159cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>S</dd></dl></div><div class='xr-var-data'><pre>array([-0.05 , -0.045, -0.04 , -0.035, -0.03 , -0.025, -0.02 , -0.015, -0.01 ,\n",
       "       -0.005,  0.   ,  0.005,  0.01 ,  0.015,  0.02 ,  0.025,  0.03 ,  0.035,\n",
       "        0.04 ,  0.045,  0.05 ,  0.055,  0.06 ,  0.065,  0.07 ,  0.075,  0.08 ,\n",
       "        0.085,  0.09 ,  0.095,  0.1  ,  0.105,  0.11 ,  0.115,  0.12 ,  0.125,\n",
       "        0.13 ,  0.135,  0.14 ,  0.145,  0.15 ,  0.155,  0.16 ,  0.165,  0.17 ,\n",
       "        0.175,  0.18 ,  0.185,  0.19 ,  0.195,  0.2  ,  0.205,  0.21 ,  0.215,\n",
       "        0.22 ,  0.225,  0.23 ,  0.235,  0.24 ,  0.245,  0.25 ,  0.255,  0.26 ,\n",
       "        0.265,  0.27 ,  0.275,  0.28 ,  0.285,  0.295,  0.3  ,  0.305],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>radius</span></div><div class='xr-var-dims'>(radius)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.06 0.09031 0.1206 ... 1.97 2.0</div><input id='attrs-f94054b0-8ede-4f95-8750-8c22bfcc3123' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f94054b0-8ede-4f95-8750-8c22bfcc3123' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f85b789-6eb7-4b13-ac46-3837ffd9d20c' class='xr-var-data-in' type='checkbox'><label for='data-6f85b789-6eb7-4b13-ac46-3837ffd9d20c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0.06    , 0.090312, 0.120625, 0.150937, 0.18125 , 0.211563, 0.241875,\n",
       "       0.272188, 0.3025  , 0.332813, 0.363125, 0.393438, 0.42375 , 0.454063,\n",
       "       0.484375, 0.514687, 0.545   , 0.575312, 0.605625, 0.635938, 0.66625 ,\n",
       "       0.696563, 0.726875, 0.757188, 0.7875  , 0.817813, 0.848125, 0.878438,\n",
       "       0.90875 , 0.939063, 0.969375, 0.999688, 1.03    , 1.060313, 1.090625,\n",
       "       1.120937, 1.15125 , 1.181562, 1.211875, 1.242188, 1.2725  , 1.302812,\n",
       "       1.333125, 1.363438, 1.39375 , 1.424062, 1.454375, 1.484687, 1.515   ,\n",
       "       1.545313, 1.575625, 1.605937, 1.63625 , 1.666562, 1.696875, 1.727188,\n",
       "       1.7575  , 1.787812, 1.818125, 1.848438, 1.87875 , 1.909063, 1.939375,\n",
       "       1.969687, 2.      ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bc62bfc1-e13a-49ab-a070-4874fc1f3405' class='xr-section-summary-in' type='checkbox'  ><label for='section-bc62bfc1-e13a-49ab-a070-4874fc1f3405' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1e839f9b-7a19-4a19-8a1e-6b48103ba53e' class='xr-index-data-in' type='checkbox'/><label for='index-1e839f9b-7a19-4a19-8a1e-6b48103ba53e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   -2.0, -1.9375,  -1.875, -1.8125,   -1.75, -1.6875,  -1.625, -1.5625,\n",
       "          -1.5, -1.4375,  -1.375, -1.3125,   -1.25, -1.1875,  -1.125, -1.0625,\n",
       "          -1.0, -0.9375,  -0.875, -0.8125,   -0.75, -0.6875,  -0.625, -0.5625,\n",
       "          -0.5, -0.4375,  -0.375, -0.3125,   -0.25, -0.1875,  -0.125, -0.0625,\n",
       "           0.0,  0.0625,   0.125,  0.1875,    0.25,  0.3125,   0.375,  0.4375,\n",
       "           0.5,  0.5625,   0.625,  0.6875,    0.75,  0.8125,   0.875,  0.9375,\n",
       "           1.0,  1.0625,   1.125,  1.1875,    1.25,  1.3125,   1.375,  1.4375,\n",
       "           1.5,  1.5625,   1.625,  1.6875,    1.75,  1.8125,   1.875,  1.9375,\n",
       "           2.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;height&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-12ef7eaa-3578-4f20-8218-7f34f19b79b8' class='xr-index-data-in' type='checkbox'/><label for='index-12ef7eaa-3578-4f20-8218-7f34f19b79b8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -0.04999999701976776, -0.044999998062849045,  -0.03999999910593033,\n",
       "        -0.03500000014901161, -0.029999999329447746,  -0.02499999850988388,\n",
       "       -0.019999999552965164, -0.014999999664723873, -0.009999999776482582,\n",
       "       -0.004999999888241291,                   0.0,  0.004999999888241291,\n",
       "        0.009999999776482582,  0.014999999664723873,  0.019999999552965164,\n",
       "         0.02499999850988388,  0.029999999329447746,   0.03500000014901161,\n",
       "         0.03999999910593033,  0.044999998062849045,   0.04999999701976776,\n",
       "        0.054999999701976776,   0.05999999865889549,   0.06499999761581421,\n",
       "         0.07000000029802322,   0.07499999552965164,   0.07999999821186066,\n",
       "         0.08500000089406967,   0.08999999612569809,    0.0949999988079071,\n",
       "         0.09999999403953552,   0.10499999672174454,   0.10999999940395355,\n",
       "         0.11499999463558197,   0.11999999731779099,                 0.125,\n",
       "         0.12999999523162842,   0.13499999046325684,   0.14000000059604645,\n",
       "         0.14499999582767487,   0.14999999105930328,    0.1550000011920929,\n",
       "          0.1599999964237213,   0.16499999165534973,   0.17000000178813934,\n",
       "         0.17499999701976776,   0.17999999225139618,    0.1850000023841858,\n",
       "          0.1899999976158142,   0.19499999284744263,   0.19999998807907104,\n",
       "         0.20499999821186066,   0.20999999344348907,    0.2149999886751175,\n",
       "          0.2199999988079071,   0.22499999403953552,   0.22999998927116394,\n",
       "         0.23499999940395355,   0.23999999463558197,    0.2449999898672104,\n",
       "                        0.25,    0.2549999952316284,   0.25999999046325684,\n",
       "         0.26499998569488525,   0.26999998092651367,    0.2750000059604645,\n",
       "          0.2800000011920929,    0.2849999964237213,   0.29499998688697815,\n",
       "         0.29999998211860657,    0.3050000071525574],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;time&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>radius</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-366023e1-045a-4a3a-bc15-ae0adc2f465c' class='xr-index-data-in' type='checkbox'/><label for='index-366023e1-045a-4a3a-bc15-ae0adc2f465c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.05999999865889549, 0.09031249582767487, 0.12062500417232513,\n",
       "        0.1509374976158142, 0.18125000596046448, 0.21156251430511475,\n",
       "       0.24187500774860382,  0.2721875011920929, 0.30250000953674316,\n",
       "       0.33281251788139343,  0.3631250262260437,  0.3934375047683716,\n",
       "       0.42375001311302185,  0.4540625214576721,            0.484375,\n",
       "        0.5146874785423279,  0.5450000166893005,  0.5753124952316284,\n",
       "        0.6056250333786011,   0.635937511920929,  0.6662500500679016,\n",
       "        0.6965625286102295,  0.7268750071525574,    0.75718754529953,\n",
       "        0.7875000238418579,  0.8178125023841858,  0.8481250405311584,\n",
       "        0.8784375190734863,  0.9087499976158142,  0.9390625357627869,\n",
       "        0.9693750143051147,  0.9996875524520874,  1.0299999713897705,\n",
       "        1.0603125095367432,  1.0906249284744263,   1.120937466621399,\n",
       "        1.1512500047683716,  1.1815624237060547,  1.2118749618530273,\n",
       "                 1.2421875,  1.2725000381469727,  1.3028124570846558,\n",
       "        1.3331249952316284,   1.363437533378601,  1.3937499523162842,\n",
       "        1.4240624904632568,  1.4543750286102295,  1.4846874475479126,\n",
       "        1.5149999856948853,   1.545312523841858,   1.575624942779541,\n",
       "        1.6059374809265137,  1.6362500190734863,  1.6665624380111694,\n",
       "         1.696874976158142,  1.7271875143051147,  1.7574999332427979,\n",
       "        1.7878124713897705,  1.8181250095367432,  1.8484375476837158,\n",
       "         1.878749966621399,  1.9090625047683716,  1.9393750429153442,\n",
       "        1.9696874618530273,                 2.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;radius&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-54f01b26-5db3-4a63-a4ba-6de1b1932643' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-54f01b26-5db3-4a63-a4ba-6de1b1932643' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'data' (time: 71, height: 65, radius: 65)>\n",
       "dask.array<open_dataset-data, shape=(71, 65, 65), dtype=float32, chunksize=(71, 65, 65), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * height   (height) float32 -2.0 -1.938 -1.875 -1.812 ... 1.875 1.938 2.0\n",
       "  * time     (time) float32 -0.05 -0.045 -0.04 -0.035 ... 0.285 0.295 0.3 0.305\n",
       "  * radius   (radius) float32 0.06 0.09031 0.1206 0.1509 ... 1.939 1.97 2.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "efm_dataset['28977'].to_dataset().data"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define some operations over the dataset. This is a nonsensical example for demonstration purposes only!\n",
    "\n",
    "- Filter by shot number\n",
    "- Choose the last 10 frames\n",
    "- Crop the height and radius\n",
    "- Average over the last 10 frames\n",
    "- Sum all shots together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
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       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 900 B </td>\n",
       "                        <td> 900 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (15, 15) </td>\n",
       "                        <td> (15, 15) </td>\n",
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       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 60 graph layers </td>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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      ],
      "text/plain": [
       "dask.array<add, shape=(15, 15), dtype=float32, chunksize=(15, 15), chunktype=numpy.ndarray>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shot_nums = shot_index.shot_id.values.astype(str)\n",
    "shot_nums = shot_nums[-10:]\n",
    "\n",
    "dt = efm_dataset.filter(lambda x: x.name in shot_nums)\n",
    "task = dt.map_over_subtree(lambda x: x.data[-10:, 25:-25, 25:-25].mean(axis=0))\n",
    "task = sum([ds.data.data for ds in task.children.values()])\n",
    "task"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9ac08e0515bd4f129ffc334a8bd5c666",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "CytoscapeWidget(cytoscape_layout={'name': 'dagre', 'rankDir': 'BT', 'nodeSep': 10, 'edgeSep': 10, 'spacingFact…"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "task.visualize(engine=\"cytoscape\", optimize_graph=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f88837bdfd0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 480x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result = task.compute(optimize_graph=True)\n",
    "plt.matshow(result)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now do the same for 1000 shots..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f8870fd04f0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 480x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shot_nums = list(dataset.children)[-1000:]\n",
    "\n",
    "dt = efm_dataset.filter(lambda x: x.name in shot_nums)\n",
    "task = dt.map_over_subtree(lambda x: x.data[-10:, 25:-25, 25:-25].mean(axis=0))\n",
    "task = sum([ds.data.data for ds in task.children.values()])\n",
    "\n",
    "result = task.compute(optimize_graph=True)\n",
    "plt.matshow(result)"
   ]
  }
 ],
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