{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Callback duration\n",
    "#\n",
    "# Get trace data using the provided launch file:\n",
    "#    $ ros2 launch tracetools_analysis pingpong.launch.py\n",
    "#    (wait a few seconds, then kill with Ctrl+C)\n",
    "#\n",
    "# (optional) convert trace data:\n",
    "#    $ ros2 run tracetools_analysis convert ~/.ros/tracing/pingpong/ust\n",
    "#\n",
    "# OR\n",
    "#\n",
    "# Use the provided sample converted trace file, changing the path below to:\n",
    "#    'sample_data/converted_pingpong'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#path = '~/.ros/tracing/pingpong/ust'\n",
    "path = '/workspaces/ROS-Dynamic-Executor-Experiments/analysis/tracing/full_topology_tracing/converted'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "# Assuming a workspace with:\n",
    "#   <...>/tracetools_analysis/\n",
    "#   <...>/ros2_tracing/tracetools_read/\n",
    "sys.path.insert(0, '../')\n",
    "sys.path.insert(0, '../../../ros2_tracing/tracetools_read/')\n",
    "import datetime as dt\n",
    "\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.plotting import output_notebook\n",
    "from bokeh.io import show\n",
    "from bokeh.layouts import row\n",
    "from bokeh.models import ColumnDataSource\n",
    "from bokeh.models import DatetimeTickFormatter\n",
    "from bokeh.models import PrintfTickFormatter\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from tracetools_analysis.loading import load_file\n",
    "from tracetools_analysis.processor.ros2 import Ros2Handler\n",
    "from tracetools_analysis.utils.ros2 import Ros2DataModelUtil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " [100%] [Ros2Handler]\n"
     ]
    }
   ],
   "source": [
    "# Process\n",
    "events = load_file(path)\n",
    "handler = Ros2Handler.process(events)\n",
    "#handler.data.print_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        .bk-notebook-logo {\n",
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       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-notebook-logo\"></a>\n",
       "        <span id=\"edbd8df0-d531-4331-a1ce-0bb8c1f3760f\">Loading BokehJS ...</span>\n",
       "    </div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\nconst JS_MIME_TYPE = 'application/javascript';\n  const HTML_MIME_TYPE = 'text/html';\n  const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n  const CLASS_NAME = 'output_bokeh rendered_html';\n\n  /**\n   * Render data to the DOM node\n   */\n  function render(props, node) {\n    const script = document.createElement(\"script\");\n    node.appendChild(script);\n  }\n\n  /**\n   * Handle when an output is cleared or removed\n   */\n  function handleClearOutput(event, handle) {\n    const cell = handle.cell;\n\n    const id = cell.output_area._bokeh_element_id;\n    const server_id = cell.output_area._bokeh_server_id;\n    // Clean up Bokeh references\n    if (id != null && id in Bokeh.index) {\n      Bokeh.index[id].model.document.clear();\n      delete Bokeh.index[id];\n    }\n\n    if (server_id !== undefined) {\n      // Clean up Bokeh references\n      const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n      cell.notebook.kernel.execute(cmd_clean, {\n        iopub: {\n          output: function(msg) {\n            const id = msg.content.text.trim();\n            if (id in Bokeh.index) {\n              Bokeh.index[id].model.document.clear();\n              delete Bokeh.index[id];\n            }\n          }\n        }\n      });\n      // Destroy server and session\n      const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n      cell.notebook.kernel.execute(cmd_destroy);\n    }\n  }\n\n  /**\n   * Handle when a new output is added\n   */\n  function handleAddOutput(event, handle) {\n    const output_area = handle.output_area;\n    const output = handle.output;\n\n    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n    if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n      return\n    }\n\n    const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n\n    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n      // store reference to embed id on output_area\n      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n    }\n    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n      const bk_div = document.createElement(\"div\");\n      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n      const script_attrs = bk_div.children[0].attributes;\n      for (let i = 0; i < script_attrs.length; i++) {\n        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n      }\n      // store reference to server id on output_area\n      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n    }\n  }\n\n  function register_renderer(events, OutputArea) {\n\n    function append_mime(data, metadata, element) {\n      // create a DOM node to render to\n      const toinsert = this.create_output_subarea(\n        metadata,\n        CLASS_NAME,\n        EXEC_MIME_TYPE\n      );\n      this.keyboard_manager.register_events(toinsert);\n      // Render to node\n      const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n      render(props, toinsert[toinsert.length - 1]);\n      element.append(toinsert);\n      return toinsert\n    }\n\n    /* Handle when an output is cleared or removed */\n    events.on('clear_output.CodeCell', handleClearOutput);\n    events.on('delete.Cell', handleClearOutput);\n\n    /* Handle when a new output is added */\n    events.on('output_added.OutputArea', handleAddOutput);\n\n    /**\n     * Register the mime type and append_mime function with output_area\n     */\n    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n      /* Is output safe? */\n      safe: true,\n      /* Index of renderer in `output_area.display_order` */\n      index: 0\n    });\n  }\n\n  // register the mime type if in Jupyter Notebook environment and previously unregistered\n  if (root.Jupyter !== undefined) {\n    const events = require('base/js/events');\n    const OutputArea = require('notebook/js/outputarea').OutputArea;\n\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  }\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  const NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    const el = document.getElementById(\"edbd8df0-d531-4331-a1ce-0bb8c1f3760f\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.1.1.min.js\"];\n  const css_urls = [];\n\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {\n    }\n  ];\n\n  function run_inline_js() {\n    if (root.Bokeh !== undefined || force === true) {\n          for (let i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\nif (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      const cell = $(document.getElementById(\"edbd8df0-d531-4331-a1ce-0bb8c1f3760f\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));",
      "application/vnd.bokehjs_load.v0+json": ""
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_util = Ros2DataModelUtil(handler.data)\n",
    "\n",
    "callback_symbols = data_util.get_callback_symbols()\n",
    "\n",
    "output_notebook()\n",
    "psize = 450\n",
    "colours = [\n",
    "    '#29788E', '#DD4968', '#410967', '#44BFC8', '#F76F8E',\n",
    "    '#8B1E3F', '#81C784', '#FFB74D', '#9575CD', '#F06292',\n",
    "    '#4DB6AC', '#BA68C8', '#7986CB', '#AED581', '#FF8A65',\n",
    "    '#E57373', '#64B5F6', '#4FC3F7', '#81D4FA', '#4DD0E1',\n",
    "    '#26A69A', '#66BB6A', '#D4E157', '#FFEE58', '#FFCA28',\n",
    "    '#FFA726', '#FF7043', '#8D6E63', '#BDBDBD', '#78909C',\n",
    "    '#90CAF9', '#A5D6A7', '#FFF59D', '#FFD54F', '#FFCC80',\n",
    "    '#FFAB91', '#CE93D8', '#F48FB1', '#B39DDB', '#80DEEA',\n",
    "    '#A1887F', '#E0E0E0', '#E6EE9C', '#C5E1A5', '#FFCDD2',\n",
    "    '#F0F4C3', '#B0BEC5', '#B2EBF2', '#DCEDC8', '#F5F5F5'\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"c12d3f9f-1bda-4798-9a43-1f431f1508c4\" data-root-id=\"p1120\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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   "source": [
    "# Plot durations separately\n",
    "colour_i = 0\n",
    "for obj, symbol in callback_symbols.items():\n",
    "    owner_info = data_util.get_callback_owner_info(obj)\n",
    "    if owner_info is None:\n",
    "        owner_info = '[unknown]'\n",
    "\n",
    "    # We don't want to plot the ros2 topic \"/parameter_events\"\n",
    "    if 'topic: /parameter_events' in owner_info:\n",
    "        continue\n",
    "\n",
    "    # Duration\n",
    "    duration_df = data_util.get_callback_durations(obj)\n",
    "    starttime = duration_df.loc[:, 'timestamp'].iloc[0].strftime('%Y-%m-%d %H:%M')\n",
    "    source = ColumnDataSource(duration_df)\n",
    "    duration = figure(\n",
    "        title=owner_info,\n",
    "        x_axis_label=f'start ({starttime})',\n",
    "        y_axis_label='duration (ms)',\n",
    "        width=psize, height=psize,\n",
    "    )\n",
    "    duration.title.align = 'center'\n",
    "    duration.line(\n",
    "        x='timestamp',\n",
    "        y='duration',\n",
    "        legend_label=str(symbol),\n",
    "        line_width=2,\n",
    "        source=source,\n",
    "        line_color=colours[colour_i],\n",
    "    )\n",
    "    duration.legend.label_text_font_size = '11px'\n",
    "    duration.xaxis[0].formatter = DatetimeTickFormatter(seconds='%Ss')\n",
    "\n",
    "    # Histogram\n",
    "    dur_hist, edges = np.histogram(duration_df['duration'])\n",
    "    duration_hist = pd.DataFrame({\n",
    "        'duration': dur_hist, \n",
    "        'left': edges[:-1], \n",
    "        'right': edges[1:],\n",
    "    })\n",
    "    hist = figure(\n",
    "        title='Duration histogram',\n",
    "        x_axis_label='duration (ms)',\n",
    "        y_axis_label='frequency',\n",
    "        width=psize, height=psize,\n",
    "    )\n",
    "    hist.title.align = 'center'\n",
    "    hist.quad(\n",
    "        bottom=0,\n",
    "        top=duration_hist['duration'], \n",
    "        left=duration_hist['left'],\n",
    "        right=duration_hist['right'],\n",
    "        fill_color=colours[colour_i],\n",
    "        line_color=colours[colour_i],\n",
    "    )\n",
    "\n",
    "    colour_i += 1\n",
    "    show(row(duration, hist))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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     "metadata": {},
     "output_type": "display_data"
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   "source": [
    "# Plot durations in one plot\n",
    "earliest_date = None\n",
    "for obj, symbol in callback_symbols.items():\n",
    "    duration_df = data_util.get_callback_durations(obj)\n",
    "    thedate = duration_df.loc[:, 'timestamp'].iloc[0]\n",
    "    if earliest_date is None or thedate <= earliest_date:\n",
    "        earliest_date = thedate\n",
    "\n",
    "starttime = earliest_date.strftime('%Y-%m-%d %H:%M')\n",
    "duration = figure(\n",
    "    title='Callback durations',\n",
    "    x_axis_label=f'start ({starttime})',\n",
    "    y_axis_label='duration (ms)',\n",
    "    width=psize, height=psize,\n",
    ")\n",
    "\n",
    "colour_i = 0\n",
    "for obj, symbol in callback_symbols.items():\n",
    "    duration_df = data_util.get_callback_durations(obj)\n",
    "    source = ColumnDataSource(duration_df)\n",
    "    duration.title.align = 'center'\n",
    "    duration.line(\n",
    "        x='timestamp',\n",
    "        y='duration',\n",
    "        legend_label=str(symbol),\n",
    "        line_width=2,\n",
    "        source=source,\n",
    "        line_color=colours[colour_i],\n",
    "    )\n",
    "    colour_i += 1\n",
    "    duration.legend.label_text_font_size = '11px'\n",
    "    duration.xaxis[0].formatter = DatetimeTickFormatter(seconds='%Ss')\n",
    "\n",
    "show(duration)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Subscription -- node: radiometric_node, tid: 45526, topic: /camera/debayered \n",
      " Avg Duration: 20.13 ms | Jitter: 0.02 ms\n"
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   "source": [
    "# Plot durations separately (with avg and jitter)\n",
    "colour_i = 0\n",
    "for obj, symbol in callback_symbols.items():\n",
    "    owner_info = data_util.get_callback_owner_info(obj)\n",
    "    if owner_info is None:\n",
    "        owner_info = '[unknown]'\n",
    "\n",
    "    # We don't want to plot the ros2 topic \"/parameter_events\"\n",
    "    if 'topic: /parameter_events' in owner_info:\n",
    "        continue\n",
    "\n",
    "    # We also don't want to plot pure timers\n",
    "    if 'Timer -- tid:' in owner_info:\n",
    "        continue\n",
    "\n",
    "    # Duration\n",
    "    duration_df = data_util.get_callback_durations(obj)\n",
    "\n",
    "    # Calculate average duration and jitter (standard deviation)\n",
    "    average_duration = duration_df['duration'].mean()\n",
    "    # If there's more than one data point, calculate jitter (standard deviation)\n",
    "    if len(duration_df) > 1:\n",
    "        jitter = duration_df['duration'].std()\n",
    "    else:\n",
    "        jitter = 0\n",
    "\n",
    "    # Print average and jitter for each callback\n",
    "    summary = f\"{owner_info} \\n Avg Duration: {average_duration:.2f} ms | Jitter: {jitter:.2f} ms\"\n",
    "    print(summary)\n",
    "\n",
    "    starttime = duration_df.loc[:, 'timestamp'].iloc[0].strftime('%Y-%m-%d %H:%M')\n",
    "    source = ColumnDataSource(duration_df)\n",
    "\n",
    "    duration = figure(\n",
    "        title=f\"{owner_info} \\n Avg Duration: {average_duration:.2f} ms | Jitter: {jitter:.2f} ms\",\n",
    "        x_axis_label=f'start ({starttime})',\n",
    "        y_axis_label='duration (ms)',\n",
    "        width=psize, height=psize,\n",
    "    )\n",
    "    duration.title.align = 'center'\n",
    "    duration.line(\n",
    "        x='timestamp',\n",
    "        y='duration',\n",
    "        legend_label=str(symbol),\n",
    "        line_width=2,\n",
    "        source=source,\n",
    "        line_color=colours[colour_i],\n",
    "    )\n",
    "    duration.legend.label_text_font_size = '11px'\n",
    "    duration.xaxis[0].formatter = DatetimeTickFormatter(seconds='%Ss')\n",
    "\n",
    "    # Histogram\n",
    "    dur_hist, edges = np.histogram(duration_df['duration'])\n",
    "    duration_hist = pd.DataFrame({\n",
    "        'duration': dur_hist, \n",
    "        'left': edges[:-1], \n",
    "        'right': edges[1:],\n",
    "    })\n",
    "    hist = figure(\n",
    "        title='Duration histogram',\n",
    "        x_axis_label='duration (ms)',\n",
    "        y_axis_label='frequency',\n",
    "        width=psize, height=psize,\n",
    "    )\n",
    "    hist.title.align = 'center'\n",
    "    hist.quad(\n",
    "        bottom=0,\n",
    "        top=duration_hist['duration'], \n",
    "        left=duration_hist['left'],\n",
    "        right=duration_hist['right'],\n",
    "        fill_color=colours[colour_i],\n",
    "        line_color=colours[colour_i],\n",
    "    )\n",
    "\n",
    "    colour_i += 1\n",
    "    show(row(duration, hist))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "callback_symbols = data_util.get_callback_symbols()\n",
    "\n",
    "def print_callback_info():\n",
    "    print(\"Callback object → symbol → owner info\\n\")\n",
    "    for obj, symbol in callback_symbols.items():\n",
    "        info = data_util.get_callback_owner_info(obj)\n",
    "        # fallback if for some reason Ros2DataModelUtil doesn’t know this one\n",
    "        if info is None:\n",
    "            info = \"[unknown]\"\n",
    "\n",
    "        # We don't care about timers or the parameter events topic\n",
    "        if 'Timer -- tid:' in info or 'topic: /parameter_events' in info:\n",
    "            continue\n",
    "        \n",
    "        print(f\"{obj} → {info}\")\n",
    "\n",
    "#print_callback_info()\n",
    "\n",
    "# find the object ID at runtime by matching node & topic\n",
    "def find_cb(node, topic):\n",
    "    return next(\n",
    "        obj for obj in callback_symbols\n",
    "        if f\"node: {node}\" in data_util.get_callback_owner_info(obj)\n",
    "        and f\"topic: {topic}\" in data_util.get_callback_owner_info(obj)\n",
    "    )\n",
    "\n",
    "chains = {\n",
    "    \"0_camera2ground\": [\n",
    "        find_cb(\"debayer_node\",     \"/camera/raw\"),\n",
    "        find_cb(\"radiometric_node\", \"/camera/debayered\"),\n",
    "        find_cb(\"geometric_node\",   \"/camera/radiometric\"),\n",
    "        find_cb(\"mapping_node\",     \"/camera/geometric\"),\n",
    "    ],\n",
    "    \"1_semantic_reasoning\": [\n",
    "        find_cb(\"debayer_node\",          \"/camera/raw\"),\n",
    "        find_cb(\"radiometric_node\",      \"/camera/debayered\"),\n",
    "        find_cb(\"smoke_classifier_node\", \"/camera/radiometric\"),\n",
    "    ],\n",
    "    \"2_data_streaming_branch_camera\": [\n",
    "        find_cb(\"debayer_node\",     \"/camera/raw\"),\n",
    "        find_cb(\"radiometric_node\", \"/camera/debayered\"),\n",
    "        find_cb(\"geometric_node\",   \"/camera/radiometric\"),\n",
    "        find_cb(\"mapping_node\",     \"/camera/geometric\"),\n",
    "        find_cb(\"telemetry_node\",   \"/camera/mapped\"),\n",
    "        find_cb(\"radio_tx_node\",   \"/telemetry/data\"),\n",
    "    ],\n",
    "    \"2_data_streaming_branch_sensor_gps\": [\n",
    "        find_cb(\"sensor_fusion_node\", \"/gps/fix\"),\n",
    "        find_cb(\"telemetry_node\",   \"/sensors/fused\"),\n",
    "        find_cb(\"radio_tx_node\",   \"/telemetry/data\"),\n",
    "    ],\n",
    "    \"2_data_streaming_branch_sensor_imu\": [\n",
    "        find_cb(\"sensor_fusion_node\", \"/imu/data\"),\n",
    "        find_cb(\"telemetry_node\",   \"/sensors/fused\"),\n",
    "        find_cb(\"radio_tx_node\",   \"/telemetry/data\"),\n",
    "    ],\n",
    "    \"2_data_streaming_branch_sensor_gps\": [\n",
    "        find_cb(\"sensor_fusion_node\", \"/baro/alt\"),\n",
    "        find_cb(\"telemetry_node\",   \"/sensors/fused\"),\n",
    "        find_cb(\"radio_tx_node\",   \"/telemetry/data\"),\n",
    "    ],\n",
    "    \"3_flight_control_branch_commands\": [\n",
    "        find_cb(\"flight_mgmt_node\", \"/operator/commands\"),\n",
    "        find_cb(\"flight_mgmt_node\", \"/sensors/fused\"),\n",
    "        find_cb(\"flight_control_node\", \"/flight/plan\")\n",
    "    ],\n",
    "    \"3_flight_control_branch_lidar\": [\n",
    "        find_cb(\"flight_mgmt_node\", \"/lidar/scan\"),\n",
    "        find_cb(\"flight_mgmt_node\", \"/sensors/fused\"),\n",
    "        find_cb(\"flight_control_node\", \"/flight/plan\")\n",
    "    ],\n",
    "    \"3_flight_control_branch_gps\": [\n",
    "        find_cb(\"sensor_fusion_node\", \"/gps/fix\"),\n",
    "        find_cb(\"flight_mgmt_node\", \"/sensors/fused\"),\n",
    "        find_cb(\"flight_control_node\", \"/flight/plan\")\n",
    "    ],\n",
    "    \"3_flight_control_branch_imu\": [\n",
    "        find_cb(\"sensor_fusion_node\", \"/imu/data\"),\n",
    "        find_cb(\"flight_mgmt_node\", \"/sensors/fused\"),\n",
    "        find_cb(\"flight_control_node\", \"/flight/plan\")\n",
    "    ],\n",
    "    \"3_flight_control_branch_baro\": [\n",
    "        find_cb(\"sensor_fusion_node\", \"/baro/alt\"),\n",
    "        find_cb(\"flight_mgmt_node\", \"/sensors/fused\"),\n",
    "        find_cb(\"flight_control_node\", \"/flight/plan\")\n",
    "    ],\n",
    "}"
   ]
  },
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   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
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     "name": "stdout",
     "output_type": "stream",
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      "0_camera2ground  —  Avg: 74.78 ms | Jitter: 48.55 ms\n"
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   "source": [
    "# Grab all callback instances\n",
    "inst = handler.data.callback_instances\n",
    "#    turn the nanosecond timestamp into pandas datetime\n",
    "inst['timestamp'] = pd.to_datetime(inst['timestamp'], unit='ns')\n",
    "\n",
    "# For each chain, walk it step-by-step in time\n",
    "chain_dfs = {}\n",
    "for chain_name, objs in chains.items():\n",
    "    starts = inst[inst['callback_object'] == objs[0]]['timestamp']\n",
    "    latencies, times = [], []\n",
    "    for t0 in starts:\n",
    "        t_prev = t0\n",
    "        for obj in objs[1:]:\n",
    "            # find the very next invocation of this stage\n",
    "            nxt = inst[\n",
    "                (inst['callback_object'] == obj) &\n",
    "                (inst['timestamp'] > t_prev)\n",
    "            ]\n",
    "            if nxt.empty:\n",
    "                t_prev = None\n",
    "                break\n",
    "            t_prev = nxt['timestamp'].iloc[0]\n",
    "        if t_prev is not None:\n",
    "            times.append(t0)\n",
    "            latencies.append((t_prev - t0).total_seconds() * 1000)  # ms\n",
    "    chain_dfs[chain_name] = pd.DataFrame({\n",
    "        'start': times,\n",
    "        'latency': latencies,\n",
    "    })\n",
    "\n",
    "# 4) Plot each chain exactly like your callback plots\n",
    "colour_i = 0\n",
    "for chain_name, df in chain_dfs.items():\n",
    "    avg     = df['latency'].mean()\n",
    "    jitter  = df['latency'].std()\n",
    "    summary = f\"{chain_name}  —  Avg: {avg:.2f} ms | Jitter: {jitter:.2f} ms\"\n",
    "\n",
    "    print(summary)\n",
    "\n",
    "    src = ColumnDataSource(df)\n",
    "\n",
    "    p_time = figure(\n",
    "        title=summary,\n",
    "        x_axis_label='start time',\n",
    "        y_axis_label='chain latency (ms)',\n",
    "        width=psize, height=psize,\n",
    "    )\n",
    "    p_time.title.align = 'center'\n",
    "    p_time.line(\n",
    "        x='start', y='latency',\n",
    "        source=src, line_width=2,\n",
    "        line_color=colours[colour_i],\n",
    "        legend_label=chain_name,\n",
    "    )\n",
    "    p_time.legend.label_text_font_size = '11px'\n",
    "    p_time.xaxis.formatter = DatetimeTickFormatter(seconds='%Ss')\n",
    "\n",
    "    # histogram\n",
    "    hist_vals, edges = np.histogram(df['latency'], bins='auto')\n",
    "    hist_df = pd.DataFrame({\n",
    "        'count': hist_vals,\n",
    "        'left':  edges[:-1],\n",
    "        'right': edges[1:],\n",
    "    })\n",
    "    p_hist = figure(\n",
    "        title='Latency histogram',\n",
    "        x_axis_label='latency (ms)',\n",
    "        y_axis_label='frequency',\n",
    "        width=psize, height=psize,\n",
    "    )\n",
    "    p_hist.title.align = 'center'\n",
    "    p_hist.quad(\n",
    "        bottom=0, top=hist_df['count'],\n",
    "        left=hist_df['left'], right=hist_df['right'],\n",
    "        fill_color=colours[colour_i],\n",
    "        line_color=colours[colour_i],\n",
    "    )\n",
    "\n",
    "    colour_i += 1\n",
    "    show(row(p_time, p_hist))"
   ]
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