unified_dashboard_dsastorage.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-02-19T00:09:34.907Z",
     "iopub.status.busy": "2022-02-19T00:09:34.902Z",
     "iopub.status.idle": "2022-02-19T00:09:36.609Z",
     "shell.execute_reply": "2022-02-19T00:09:36.623Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\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, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "    if (js_modules == null) js_modules = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls.length === 0 && js_modules.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\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",
       "    }\n",
       "\n",
       "    var skip = [];\n",
       "    if (window.requirejs) {\n",
       "      window.requirejs.config({'packages': {}, 'paths': {'tabulator': 'https://cdn.jsdelivr.net/npm/tabulator-tables@5.3.2/dist/js/tabulator', 'moment': 'https://cdn.jsdelivr.net/npm/luxon/build/global/luxon.min', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'gridstack': {'exports': 'GridStack'}}});\n",
       "      require([\"tabulator\"], function(Tabulator) {\n",
       "\twindow.Tabulator = Tabulator\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"moment\"], function(moment) {\n",
       "\twindow.moment = moment\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 + 4;\n",
       "    } else {\n",
       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n",
       "    }    if (((window['Tabulator'] !== undefined) && (!(window['Tabulator'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/js/tabulator.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['moment'] !== undefined) && (!(window['moment'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.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/0.14.3/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.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/0.14.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) >= 0) {\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) >= 0) {\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",
       "    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.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/js/tabulator.js\", \"https://cdn.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.3/dist/panel.min.js\"];\n",
       "  var js_modules = [];\n",
       "  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/css/tabulator_simple.min.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/dataframe.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/card.css\"];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n      background-size: auto calc(min(50%, 400px));\\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",
       "      }} 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",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, js_modules, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\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, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\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    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'tabulator': 'https://cdn.jsdelivr.net/npm/tabulator-tables@5.3.2/dist/js/tabulator', 'moment': 'https://cdn.jsdelivr.net/npm/luxon/build/global/luxon.min', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'gridstack': {'exports': 'GridStack'}}});\n      require([\"tabulator\"], function(Tabulator) {\n\twindow.Tabulator = Tabulator\n\ton_load()\n      })\n      require([\"moment\"], function(moment) {\n\twindow.moment = moment\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 + 4;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n    }    if (((window['Tabulator'] !== undefined) && (!(window['Tabulator'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/js/tabulator.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['moment'] !== undefined) && (!(window['moment'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.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/0.14.3/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.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/0.14.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) >= 0) {\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) >= 0) {\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    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.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/js/tabulator.js\", \"https://cdn.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.3/dist/panel.min.js\"];\n  var js_modules = [];\n  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.3/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/css/tabulator_simple.min.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/dataframe.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.3/dist/css/card.css\"];\n  var inline_js = [    function(Bokeh) {\n      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n      background-size: auto calc(min(50%, 400px));\\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      }} 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  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, js_modules, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "  handle_add_output(event, handle)\n",
       "}\n",
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       "  }\n",
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       "  events.on('delete.Cell', handle_clear_output);\n",
       "  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
       "\n",
       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "    safe: true,\n",
       "    index: 0\n",
       "  });\n",
       "}\n",
       "\n",
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       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  } catch(err) {\n",
       "  }\n",
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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>.bk-root, .bk-root .bk:before, .bk-root .bk:after {\n",
       "  font-family: var(--jp-ui-font-size1);\n",
       "  font-size: var(--jp-ui-font-size1);\n",
       "  color: var(--jp-ui-font-color1);\n",
       "}\n",
       "</style>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No T3. Skipping...\n"
     ]
    }
   ],
   "source": [
    "from astropy import time\n",
    "import numpy as np\n",
    "import glob\n",
    "import os.path\n",
    "import json\n",
    "import matplotlib.pyplot as plt\n",
    "from functools import partial\n",
    "import signal\n",
    "\n",
    "from IPython import display\n",
    "import pandas as pd\n",
    "import panel as pn\n",
    "pn.extension(\"tabulator\")\n",
    "import hvplot.pandas\n",
    "import holoviews as hv\n",
    "hv.extension(\"bokeh\")\n",
    "\n",
    "from astropy.coordinates import EarthLocation\n",
    "from astropy.time import Time, TimeDelta\n",
    "import astropy.units as u\n",
    "\n",
    "import sched_funcs, antmon\n",
    "from event import labels, lookup\n",
    "from dsacalib import weights\n",
    "\n",
    "try:\n",
    "    from dsaT3.utils import archive\n",
    "except ImportError:\n",
    "    print(\"No T3. Skipping...\")\n",
    "\n",
    "try:\n",
    "    from dsautils import dsa_store\n",
    "    ds = dsa_store.DsaStore()\n",
    "except ImportError:\n",
    "    ds = None\n",
    "    \n",
    "trig_pane = None\n",
    "sched_pane = None\n",
    "calibration_pane = None\n",
    "bokeh_pane = None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trigger inspection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "base = '/operations/T3'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "fn_pngs = sorted(glob.glob(os.path.join(base, '*png')))\n",
    "fn_jsons = sorted(glob.glob(os.path.join(base, '*json')))\n",
    "fn_jsons = [fn for fn in fn_jsons if 'management' not in fn]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: different number of pngs and jsons\n",
      "Found 263 complete triggers\n"
     ]
    }
   ],
   "source": [
    "triggernames = [fn[:-5] for fn in fn_jsons]\n",
    "\n",
    "if len(fn_pngs) != len(fn_jsons):\n",
    "    print('Warning: different number of pngs and jsons')\n",
    "    # TODO: add logic to find list of triggernames?\n",
    "\n",
    "print(f'Found {len(triggernames)} complete triggers')\n",
    "\n",
    "##optional: parse management.json file to see what else is going on?\n",
    "#with open('/home/ubuntu/data/T3/management.json', 'r') as fp:\n",
    "#    dd = json.load(fp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def build_triggertab():\n",
    "    if triggernames:\n",
    "        dds = []\n",
    "        keys = ['mjds', 'snr', 'dm', 'ibox', 'ibeam', 'trigname', 'ra', 'dec', 'probability', 'label', 'save']\n",
    "        for triggername in triggernames:\n",
    "            dd = labels.readfile(triggername + '.json')\n",
    "            if dd == None:\n",
    "                continue\n",
    "            dd2 = dd.fromkeys(keys)\n",
    "            for key in keys:\n",
    "                if key in dd:\n",
    "                    dd2[key] = dd[key]\n",
    "                else:\n",
    "                    dd2[key] = -1\n",
    "            dds.append(dd2)\n",
    "        df = pd.DataFrame.from_dict(dds)\n",
    "        df.set_index('trigname', inplace=True)\n",
    "        df_pane = pn.widgets.Tabulator(df[::-1], layout='fit_data_table', pagination='remote', page_size=10,\n",
    "                                      selectable='checkbox', height=400, width=1000)\n",
    "    else:\n",
    "        df_pane = pn.widgets.Tabulator(pd.DataFrame(), layout='fit_data_table', pagination='remote', page_size=10,\n",
    "                                      selectable='checkbox', height=400, width=1000)\n",
    "\n",
    "        \n",
    "    def set_label(label=False):\n",
    "        if label is not None:\n",
    "            if label == 'None':\n",
    "                label = ''\n",
    "            if len(df_pane.selection):\n",
    "                for trigname in df_pane.selected_dataframe.index:\n",
    "                    labels.set_label(label, candname=trigname)\n",
    "                return f'Labeled {list(df_pane.selected_dataframe.index)} as {label}'\n",
    "\n",
    "    def set_notes(note):\n",
    "        if note:\n",
    "            if len(df_pane.selection):\n",
    "                for trigname in df_pane.selected_dataframe.index:\n",
    "                    labels.set_notes(note, candname=trigname)\n",
    "                return f'Note added for {list(df_pane.selected_dataframe.index)}'\n",
    "        else:\n",
    "            if len(df_pane.selection):\n",
    "                for trigname in df_pane.selected_dataframe.index:\n",
    "                    labels.set_notes('', candname=trigname)            \n",
    "                return f'Note removed for {list(df_pane.selected_dataframe.index)}'\n",
    "\n",
    "    def run_lookup(event):\n",
    "        lookup_text.value = 'Looking...'\n",
    "        if len(df_pane.selection):\n",
    "            ss = ''\n",
    "            for trigname in df_pane.selected_dataframe.index:\n",
    "                ra, dec = df.loc[trigname][['ra', 'dec']]\n",
    "                result = lookup.find_associations(float(ra), float(dec), nvss_radius=3.3*3600, atnf_radius=3.3*3600)\n",
    "                for src in result:\n",
    "                    ss += f'{trigname} is {src[2][0]} arcsec from {src[0]} source. '\n",
    "            if ss:\n",
    "                lookup_text.value = ss\n",
    "            else:\n",
    "                lookup_text.value = 'Nothing found.'\n",
    "        else:\n",
    "            lookup_text.value = f'Nothing selected.'\n",
    "\n",
    "    def run_archive(event):\n",
    "        with pn.param.set_values(png_column, loading=True):\n",
    "            result = archive(datestring)\n",
    "            if len(result):\n",
    "                archive_text.value = f'Archived {\",\".join(result)}'\n",
    "            else:\n",
    "                archive_text.value = 'No files to archive'\n",
    "\n",
    "    get_name = pn.widgets.Button(name='Load plot for selected row', width=900, button_type='primary')\n",
    "    png_column = pn.Column('', width=900)\n",
    "\n",
    "    def set_png(event):\n",
    "        if len(df_pane.selection):\n",
    "            triggername = df_pane.selected_dataframe.index[0]\n",
    "            if len(df_pane.selection) > 1:\n",
    "                print(f'Only using first selected row {triggername}')\n",
    "            fn = os.path.join(base, triggername + '.png')\n",
    "            if os.path.exists(fn):\n",
    "                with pn.param.set_values(png_column, loading=True):\n",
    "                    image = display.Image(fn)\n",
    "                    _ = png_column.pop(0)\n",
    "                    png_column.append(image)\n",
    "            archive_text.value = f\"{df_pane.selection} {fn}\"\n",
    "        else:\n",
    "            _ = png_column.pop(0)\n",
    "            png_column.append(\"Nothing selected\")\n",
    "\n",
    "    _ = get_name.param.watch(set_png, 'value')\n",
    "\n",
    "    datestring = ds.get_dict('/cnf/datestring') if ds is not None else None\n",
    "    archive_text = pn.widgets.TextInput(value=datestring, width=250)\n",
    "    archive_button = pn.widgets.Button(name='Debug text', width=250, button_type='primary')\n",
    "#    archive_button.on_click(run_archive)\n",
    "\n",
    "    lookup_text = pn.widgets.TextInput(value='Ready', width=650)\n",
    "    lookup_input = pn.widgets.Button(name='Run coordinate lookup on selected row', width=250, button_type='primary')\n",
    "    lookup_input.on_click(run_lookup)\n",
    "    lookup_pane = pn.Row(lookup_input, lookup_text)\n",
    "\n",
    "    label_group = pn.widgets.RadioButtonGroup(name='Add label for selected row(s)',\n",
    "                                              options=['astrophysical', 'injection', 'rfi', 'instrumental',\n",
    "                                                       'unsure/noise', 'save', 'None'], button_type='success',\n",
    "                                              width=500, value='None')\n",
    "    get_notes = pn.widgets.TextInput(placeholder='Freeform note', value='')\n",
    "\n",
    "    label_pane = pn.Column(label_group, pn.panel(pn.bind(set_label, label_group)))\n",
    "    notes_pane = pn.Column(get_notes, pn.panel(pn.bind(set_notes, get_notes)))\n",
    "    ln_pane = pn.Row(label_pane, notes_pane, sizing_mode='stretch_width')\n",
    "    a_pane = pn.Row(archive_button, archive_text)\n",
    "\n",
    "# build it all\n",
    "    dashboard_title = pn.pane.Markdown('# DSA-110 Trigger Dashboard')\n",
    "    header = pn.pane.Markdown('Add labels and notes for selected rows')\n",
    "    trig_pane = pn.Column(dashboard_title, df_pane, header, ln_pane, lookup_pane, a_pane,\n",
    "                          pn.Column(get_name, png_column))        \n",
    "        \n",
    "    return trig_pane"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#trig_pane = build_triggertab()\n",
    "#trig_pane.servable(title='dashboard')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scheduling\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-02-19T00:19:58.094Z",
     "iopub.status.busy": "2022-02-19T00:19:58.091Z",
     "iopub.status.idle": "2022-02-19T00:19:58.101Z",
     "shell.execute_reply": "2022-02-19T00:19:58.105Z"
    }
   },
   "outputs": [],
   "source": [
    "def schedule(targets=None, duration=None, delay=None):\n",
    "    \"\"\" Start should be astropy time object (default is \"now\")\n",
    "    Duration is in hours (default is 24 hours)\n",
    "    Delay is in hours from now.\n",
    "    \"\"\"\n",
    "\n",
    "    print(f'targets, delay, duration: {targets}, {delay}, {duration}')\n",
    "    ovro = EarthLocation(lon=-118.2951 * u.deg, lat=37.2317 * u.deg, height=1222 * u.m)\n",
    "    catalog = sched_funcs.read_srcs('/home/user/proj/dsa110-shell/dsa110-vis/catalog.yaml')\n",
    "\n",
    "    if targets is not None and targets != '':\n",
    "        catalog['sources'] = [src for src in catalog['sources'] if src['name'] in targets]\n",
    "\n",
    "    if duration is None or duration == '':\n",
    "        duration = 24.\n",
    "    else:\n",
    "        duration = float(duration)\n",
    "\n",
    "    if delay is None or delay == '':\n",
    "        delay = 0.\n",
    "    else:\n",
    "        delay = float(delay)\n",
    "\n",
    "    start_time = Time.now() + TimeDelta(delay*u.hour)\n",
    "\n",
    "    # calculate actions\n",
    "    print(f'Catalog: {catalog}')\n",
    "    catalog2, transit_times, max_alts, stimes, end_times, northy = sched_funcs.return_times_day(catalog, start_time, duration, ovro)\n",
    "    print(f'Catalog2: {catalog2}')\n",
    "    actions = sched_funcs.define_actions_simple(catalog2, transit_times, max_alts, stimes, end_times, northy, recording=True)\n",
    "\n",
    "    # save actions\n",
    "    names = [src['name'] for src in catalog2]\n",
    "    transits = [t.mjd[0] for t in transit_times]\n",
    "\n",
    "    sidereal_time = Time.now().sidereal_time('apparent', longitude=ovro.lon)\n",
    "    \n",
    "    fig, ax = plt.subplots(1, 1)\n",
    "    for name, ttran, alt, start, stop in list(zip(names, transits, max_alts, stimes, end_times)):\n",
    "        ax.plot([start, stop], [alt, alt], '-', label=name)\n",
    "        ax.plot(ttran, alt, 'kx')\n",
    "        ax.text(Time.now().mjd, 60, f'current sid time={sidereal_time.value:.2f}',\n",
    "                horizontalalignment='center', verticalalignment='center', rotation='vertical')\n",
    "        ax.legend()\n",
    "        ax.set_ylim(20, 110)\n",
    "        ax.set_xlim(Time.now().mjd - duration/24/10, stop+duration/24/10)\n",
    "        ax.set_ylabel('Elevation (deg)')\n",
    "        ax.set_xlabel(f'Time (MJD start={Time.now().mjd})')\n",
    "    return fig, actions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ovro = EarthLocation(lon=-118.2951 * u.deg, lat=37.2317 * u.deg, height=1222 * u.m)\n",
    "catalog = sched_funcs.read_srcs('/home/ubuntu/proj/dsa110-shell/dsa110-vis/catalog.yaml')\n",
    "start_time = Time.now()\n",
    "duration = 24\n",
    "catalog['sources'] = [src for src in catalog['sources'] if src['name'] in ['3C196']]\n",
    "catalog2, transit_times, max_alts, stimes, end_times, northy = sched_funcs.return_times_day(catalog, start_time, duration, ovro)\n",
    "print(max_alts, northy)\n",
    "actions = sched_funcs.define_actions_simple(catalog2, transit_times, max_alts, stimes, end_times, northy, recording=True)\n",
    "from astropy.coordinates import SkyCoord, AltAz\n",
    "deltas = np.linspace(0., duration, 6*60*int(duration))*u.hour\n",
    "times = start_time + deltas\n",
    "transit_times = []\n",
    "srcnames = []\n",
    "max_alts = []\n",
    "northy = []\n",
    "repeats = int(np.ceil(max(deltas.value)/24))\n",
    "src = catalog['sources'][0]\n",
    "coord=SkyCoord(ra=src['RA'], dec=src['DEC'], unit=(u.hourangle, u.deg))\n",
    "i = 0\n",
    "times0 = times[(deltas.value < (i+1)*24) & (i*24 < deltas.value)]\n",
    "aas = coord.transform_to(AltAz(obstime=times0, location=ovro))\n",
    "alts = aas.alt.value\n",
    "azs = aas.az.value\n",
    "tt = times0[(alts >= alts.max()) * (np.abs(azs.min()) < 10)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "plt.plot(times0.mjd, alts, '.', label='alt')\n",
    "plt.plot(times0.mjd, azs, '.', label='az')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-02-19T01:09:06.904Z",
     "iopub.status.busy": "2022-02-19T01:09:06.898Z",
     "iopub.status.idle": "2022-02-19T01:09:06.911Z",
     "shell.execute_reply": "2022-02-19T01:09:06.914Z"
    },
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [],
   "source": [
    "target_text = pn.widgets.TextInput(value='3C147', name='Targets (comma-delimited)', width=200, height=50)\n",
    "duration_text = pn.widgets.TextInput(value=None, name='Duration', width=50, height=50)\n",
    "delay_text = pn.widgets.TextInput(value=None, name='Delay', width=50, height=50)\n",
    "plot_button = pn.widgets.Button(name='Make plot', width=100, button_type='primary')\n",
    "plot = pn.pane.Matplotlib(width=700, height=400)\n",
    "run_button = pn.widgets.Button(name='Run actions', width=100, button_type='primary')\n",
    "#interrupt_button = pn.widgets.Button(name='Interrupt actions', width=100, button_type='primary')\n",
    "if os.path.exists('output_text'):\n",
    "    with open('output_text', 'r') as fp:\n",
    "        value = fp.read()\n",
    "else:\n",
    "    value = ''\n",
    "output_text = pn.widgets.TextAreaInput(value=value, name='Action log', width=800, height=300)\n",
    "\n",
    "def set_plot(event):\n",
    "    if len(cat_pane.selection):\n",
    "        target_text.value = ','.join(cat_pane.selected_dataframe.index)\n",
    "\n",
    "    with pn.param.set_values(plot, loading=True):\n",
    "        try:\n",
    "            fig, actions = schedule(targets=target_text.value, delay=delay_text.value,\n",
    "                                    duration=duration_text.value)\n",
    "            np.save('actions.npy', actions)\n",
    "            plot.object = fig\n",
    "            output_text.value = f'Actions for plot:'\n",
    "            for ln in actions:\n",
    "                output_text.value+=f'\\nWait until {ln[\"time\"]}'\n",
    "                output_text.value+=f'\\nCommand {ln[\"cmd\"]} {ln[\"val\"]}'\n",
    "                save_output_text(output_text)\n",
    "\n",
    "        except:\n",
    "            plot.object = None\n",
    "\n",
    "def run_actions(event):\n",
    "    fig, actions = schedule(targets=target_text.value, delay=delay_text.value,\n",
    "                            duration=duration_text.value)\n",
    "    np.save('actions.npy', actions)\n",
    "    output_text.value = f'Running actions:'\n",
    "    for ln in actions:\n",
    "#        if os.path.exists('interrupt'):\n",
    "#            output_text.value+='\\nInterrupted'\n",
    "#            os.remove('interrupt')\n",
    "#            break\n",
    "            \n",
    "        output_text.value+=f'\\n{Time.now().iso} (MJD: {Time.now().mjd}): Waiting until {ln[\"time\"]}'\n",
    "        save_output_text(output_text)\n",
    "        status = sched_funcs.pause_until(ln['time'])\n",
    "\n",
    "#        if status:\n",
    "#            output_text.value+='\\nInterrupted'\n",
    "#            save_output_text(output_text)\n",
    "#            os.remove('interrupt')\n",
    "#            break\n",
    "\n",
    "        output_text.value+=f'\\n{Time.now().iso} (MJD: {Time.now().mjd}: Command {ln[\"cmd\"]} {ln[\"val\"]}'\n",
    "        save_output_text(output_text)\n",
    "        sched_funcs.exec_action(ln)\n",
    "\n",
    "def save_output_text(output_text):\n",
    "    with open('output_text', 'w') as fp:\n",
    "        fp.write(output_text.value)\n",
    "\n",
    "\n",
    "run_button.on_click(run_actions)\n",
    "plot_button.on_click(set_plot)\n",
    "#interrupt_button.on_click(interrupt)\n",
    "\n",
    "catalog = sched_funcs.read_srcs('/home/user/proj/dsa110-shell/dsa110-vis/catalog.yaml')\n",
    "df_cat = pd.DataFrame.from_dict(catalog['sources'])\n",
    "df_cat.set_index('name', inplace=True)\n",
    "cat_pane = pn.widgets.Tabulator(df_cat, layout='fit_data_table', pagination='remote', page_size=10,\n",
    "                                   selectable='checkbox', height=400, width=800)\n",
    "\n",
    "scheduler_title = pn.pane.Markdown('# DSA-110 Scheduler')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "sched_pane = pn.Column(pn.Row(scheduler_title), pn.Row(target_text, delay_text, duration_text,\n",
    "                                                       plot_button, run_button),#, interrupt_button),\n",
    "                       pn.Row(cat_pane),\n",
    "                       pn.Row(output_text),\n",
    "                       pn.Row(plot))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#sched_pane"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calibration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0m\u001b[01;35m1229+020_2023-02-03T11:29:53_averagedweights.png\u001b[0m\r\n",
      "\u001b[01;35m1534+015_2023-02-03T14:35:06_averagedweights.png\u001b[0m\r\n",
      "\u001b[01;35m1604+012_2023-02-03T15:04:54_averagedweights.png\u001b[0m\r\n",
      "2023-02-03_0022+002.pdf\r\n",
      "2023-02-03_1534+015.pdf\r\n",
      "2023-02-03_1604+012.pdf\r\n",
      "2023-02-03_2136+006.pdf\r\n",
      "2023-02-03_2212+018.pdf\r\n",
      "\u001b[01;35m2136+006_2023-02-03T20:35:53_averagedweights.png\u001b[0m\r\n",
      "\u001b[01;35m2212+018_2023-02-03T21:11:46_averagedweights.png\u001b[0m\r\n",
      "\u001b[01;34mallpngs\u001b[0m/\r\n"
     ]
    }
   ],
   "source": [
    "ls /home/user/data/webPLOTS/calibration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def build_calpane():\n",
    "    path_calplots = '/home/user/data/webPLOTS/calibration/'\n",
    "    calplots = glob.glob(path_calplots + \"/*.png\")\n",
    "    menu_calplots = pn.widgets.MenuButton(name=\"Select a gain plot to display\",\n",
    "                                          items=[os.path.basename(cp) for cp in calplots])\n",
    "    load_button = pn.widgets.Button(name='Load displayed gains', width=100, button_type='primary')\n",
    "\n",
    "    calplot_column = pn.Column('', width=900)\n",
    "\n",
    "    def load_png(event):\n",
    "        with pn.param.set_values(calplot_column, loading=True):\n",
    "            print(menu_calplots.clicked)\n",
    "            image = pn.pane.PNG(os.path.join(path_calplots, menu_calplots.clicked), width=1000)\n",
    "            _ = calplot_column.pop(0)\n",
    "            print(len(calplot_column))\n",
    "            calplot_column.append(image)\n",
    "\n",
    "    def load_weights(event):\n",
    "        os.system(f\"update_bfweights.py {menu_calplots.clicked.rstrip('_averagedweights.png')}\")\n",
    "\n",
    "    menu_calplots.on_click(load_png)\n",
    "    load_button.on_click(load_weights)\n",
    "\n",
    "    calibration_title = pn.pane.Markdown('# DSA-110 Calibration')\n",
    "\n",
    "    calibration_pane = pn.Column(pn.Row(calibration_title),\n",
    "                                 pn.Row(menu_calplots, load_button),\n",
    "                                 pn.Row(calplot_column))\n",
    "    return calibration_pane"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "path_calib = '/data/dsa110/T3/calibs/'\n",
    "plot_cal = pn.pane.Matplotlib(width=700, height=400)\n",
    "calplot_button = pn.widgets.Button(name='Make calplot', width=100, button_type='primary')\n",
    "\n",
    "def set_calplot(event):\n",
    "    with pn.param.set_values(plot, loading=True):\n",
    "        try:\n",
    "            bfweights = ds.get_dict('/mon/cal/bfweights')\n",
    "            if 'bfname' in bfweights:\n",
    "                bfname = bfweights['bfname']\n",
    "            else:\n",
    "                latest = max(glob.glob(os.path.join(path_calib, 'beamformer_weights_corr03_*dat')), key=os.path.getctime)\n",
    "                bfname = latest.split('/')[-1].lstrip('beamformer_weights_corr03_').rstrip('.dat')\n",
    "                print(bfname)\n",
    "            gains = weights.read_gains(path=path_calib, bfnames=[bfname])\n",
    "            fig = weights.show_gains([bfname], gains, [0], ret=True, show=False)\n",
    "\n",
    "            plot_cal.object = fig\n",
    "        except:\n",
    "            plot_cal.object = None\n",
    "\n",
    "\n",
    "calplot_button.on_click(set_calplot)\n",
    "calibration_title = pn.pane.Markdown('# DSA-110 Calibration')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#calibration_pane = build_calpane()\n",
    "#calibration_pane"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Antenna status (bokeh plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_bokeh():\n",
    "    try:\n",
    "        pall, source, source2, source3 = antmon.makefig()\n",
    "    except:\n",
    "        pall = None\n",
    "    bokeh_pane = pn.pane.Bokeh(pall)\n",
    "    return bokeh_pane\n",
    "# automatic updates\n",
    "#bokeh_pane.servable()\n",
    "#def update(source, source2, source3):\n",
    "#    antmon.update(source, source2, source3)\n",
    "#    bokeh_pane.param.trigger('object')\n",
    "#cb = pn.state.add_periodic_callback(partial(update, source, source2, source3), 1000, timeout=5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "trig_pane = pn.param.ParamFunction(build_triggertab, lazy=True)\n",
    "bokeh_pane = pn.param.ParamFunction(build_bokeh, lazy=True)\n",
    "calibration_pane = pn.param.ParamFunction(build_calpane, lazy=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "dashboard = pn.Column(pn.Row(pn.layout.tabs.Tabs(('Triggers', trig_pane),\n",
    "#                                                 ('Scheduler', sched_pane),\n",
    "                                                 ('Calibration', calibration_pane),\n",
    "                                                 ('Antenna Monitor', bokeh_pane),\n",
    "                                                dynamic=True, active=2),\n",
    "                             margin=(10, 10, 10, 10), background='#f0f0f0'))\n",
    "\n",
    "# Potential speedup with (dynamic=True) https://panel.holoviz.org/reference/layouts/Tabs.html?highlight=tabs#dynamic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/user/proj/dsa110-shell/dsa110-vis/antmon.py:97: FutureWarning: In a future version of pandas all arguments of DataFrame.set_index except for the argument 'keys' will be keyword-only.\n",
      "  df.set_index('ant_num', 0, inplace=True)\n",
      "/home/user/proj/dsa110-shell/dsa110-vis/antmon.py:109: FutureWarning: In a future version of pandas all arguments of DataFrame.set_index except for the argument 'keys' will be keyword-only.\n",
      "  df2.set_index('ant_num', 0, inplace=True)\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
      "text/html": [
       "<div id='1002'>\n",
       "  <div class=\"bk-root\" id=\"29b6f2e9-3d59-4acb-8396-b9d48194362b\" data-root-id=\"1002\"></div>\n",
       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  function embed_document(root) {\n",
       "    var docs_json = 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       "    var render_items = [{\"docid\":\"30aabe42-5486-4829-ab00-0332df511c85\",\"root_ids\":[\"1002\"],\"roots\":{\"1002\":\"29b6f2e9-3d59-4acb-8396-b9d48194362b\"}}];\n",
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       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['Tabulator'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
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       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
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      ],
      "text/plain": [
       "Column\n",
       "    [0] Row(background='#f0f0f0', margin=(10, 10, 10, 10))\n",
       "        [0] Tabs(active=2, dynamic=True)\n",
       "            [0] ParamFunction(function, _pane=Str, lazy=True)\n",
       "            [1] ParamFunction(function, _pane=Str, lazy=True)\n",
       "            [2] ParamFunction(function, _pane=Bokeh, lazy=True)"
      ]
     },
     "execution_count": 16,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "1002"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dashboard.servable(title='dashboard')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#np.load('actions.npy', allow_pickle=True)"
   ]
  }
 ],
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   "language": "python",
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