Fixed crash when BW_ENABLED=False, user-friendly README.md

README.md

@@ -3,7 +3,7 @@
 Automatically extract data dependencies and end-to-end (E2E) latencies from ROS2 trace data.
 
 ## Prerequisites
-* Python 3.10
+* Python 3.10 or newer (this is crucial!)
 * [JupyterLab](https://jupyter.org/install#jupyterlab) or [Jupyter Notebook](https://jupyter.org/install#jupyter-notebook)
 * [ROS2 Tracing](https://github.com/ros2/ros2_tracing)
 * [Tracetools Analysis](https://gitlab.com/ros-tracing/tracetools_analysis)
@@ -19,4 +19,34 @@ pip3.10 -V
 pip3.10 install -r requirements.txt
 ```
 
+Make sure that ROS2 Tracing and Tracetools Analysis were compiled with `colcon build [...] --symlink-install [...]`. Without `--symlink-install`, the build folder structure will be incorrect and the libraries required by this tool cannot be located.
+
 ## Usage
+
+The `trace_analysis.ipynb` notebook is the entry point for users.
+Configure the notebook according to the comments in the user settings cell.
+Settings can either be changed in the notebook or via environment variables:
+```python
+# In the notebook (User Settings cell near the top):
+TR_PATH = "path/to/trace/dir"
+E2E_ENABLED = True
+...
+```
+
+```shell
+# In the shell of your choice (choose Bash!):
+# Each setting is named the same as in the notebook but prefixed by "ANA_NB_".
+ANA_NB_TR_PATH="path/to/trace/dir"
+ANA_NB_E2E_ENABLED="True"
+```
+
+You can run the notebook via the "Run All" command in Jupyter or you can execute it headless
+from the command line:
+```shell
+jupyter nbconvert --to notebook --execute trace-analysis.ipynb
+```
+
+nbconvert can also be called from Python directly, 
+read more info on nbconvert [here](https://nbconvert.readthedocs.io/en/latest/execute_api.html).
+
+The output files are found in the configured output dir (default: `out/`). Inputs are processed and cached in `cache/`.

misc/utils.py

@@ -17,7 +17,7 @@ from IPython import get_ipython
 def skip_if_false(line, cell, local_ns=None):
     condition_var = eval(line, None, local_ns)
     if condition_var:
-        result = get_ipython().run_cell(cell)
+        get_ipython().run_cell(cell)
         return None
     return f"Skipped (evaluated {line} to False)"
 

trace-analysis.ipynb

@@ -24,10 +24,7 @@
     "from misc.utils import ProgressPrinter, cached, parse_as\n",
     "\n",
     "%load_ext pyinstrument\n",
-    "%matplotlib inline\n",
-    "\n",
-    "A=True\n",
-    "B=None"
+    "%matplotlib inline"
    ]
   },
   {
@@ -68,7 +65,7 @@
     "OUT_PATH = \"out/\"\n",
     "\n",
     "# Whether to annotate topics/publications with bandwidth/message size\n",
-    "BW_ENABLED = True\n",
+    "BW_ENABLED = False\n",
     "# Path to a results folder as output by ma-hw-perf-tools/messages/record.bash\n",
     "# Used to annotate message sizes in E2E latency calculations\n",
     "BW_PATH = \"../ma-hw-perf-tools/data/results\"\n",
@@ -139,7 +136,9 @@
     "TR_PATH = _expand_path(TR_PATH)\n",
     "OUT_PATH = _expand_path(OUT_PATH)\n",
     "BW_PATH = _expand_path(BW_PATH)\n",
-    "CL_PATH = _expand_path(CL_PATH)"
+    "CL_PATH = _expand_path(CL_PATH)\n",
+    "\n",
+    "os.makedirs(OUT_PATH, exist_ok=True)"
    ]
   },
   {
@@ -226,7 +225,6 @@
    "execution_count": null,
    "outputs": [],
    "source": [
-    "%%skip_if_false DFG_ENABLED\n",
     "from latency_graph import latency_graph as lg\n",
     "\n",
     "def _make_latency_graph():\n",
@@ -1251,7 +1249,7 @@
     "                if \"DDS\" not in legend_entries:\n",
     "                    legend_entries[\"DDS\"] = r\n",
     "\n",
-    "                topic_stats = msg_sizes.get(pub.topic_name)\n",
+    "                topic_stats = msg_sizes.get(pub.topic_name) if BW_ENABLED else None\n",
     "                if topic_stats:\n",
     "                    size_str = bw_str(topic_stats)\n",
     "                    ax.text(r_x + r_w / 2, r_y + arr_width + margin_y, size_str, ha=\"center\", backgroundcolor=(1,1,1,.5), zorder=11000)\n",
@@ -1346,7 +1344,10 @@
     "items = list(critical_paths.items())\n",
     "items.sort(key=lambda pair: len(pair[1]), reverse=True)\n",
     "\n",
+    "out_df = pd.DataFrame(columns=[\"path\", \"timestamp\", \"e2e_latency\"])\n",
     "for key, paths in items:\n",
+    "    path_records = [(\" -> \".join(key), p[0].timestamp, p[0].timestamp - p[-1].timestamp) for p in paths]\n",
+    "    out_df.append(path_records)\n",
     "    print(f\"======== {len(paths)}x: {sum(map(lambda p: p[0].timestamp - p[-1].timestamp, paths))/len(paths)*1000:.3f}ms\")\n",
     "    paths_durations = []\n",
     "    for path in paths:\n",
@@ -1381,7 +1382,8 @@
     "            E2E_PLOT_TIMESTAMP = j\n",
     "        dur_str = colored(f\"{duration * 1000 :>.3f}ms\", colors[E2E_PLOT_TIMESTAMP])\n",
     "        print(f\"  -> {dur_str} {part}\")\n",
-    "\n"
+    "\n",
+    "out_df.to_csv(os.path.join(OUT_PATH, \"e2e.csv\"), sep=\"\\t\")"
    ],
    "metadata": {
     "collapsed": false,