tracetools_analysis/README.md
2020-01-26 11:40:07 -05:00

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# tracetools_analysis
[![pipeline status](https://gitlab.com/micro-ROS/ros_tracing/tracetools_analysis/badges/master/pipeline.svg)](https://gitlab.com/micro-ROS/ros_tracing/tracetools_analysis/commits/master)
Analysis tools for [ROS 2 tracing](https://gitlab.com/micro-ROS/ros_tracing/ros2_tracing).
## Setup
Install:
* `pandas`
```
$ sudo apt-get install python3-pandas
```
To display results, install:
* [Jupyter](https://jupyter.org/install)
* [Bokeh](https://bokeh.pydata.org/en/latest/docs/user_guide/quickstart.html#userguide-quickstart-install)
## Trace analysis
After generating a trace (see [`ros2_tracing`](https://gitlab.com/micro-ROS/ros_tracing/ros2_tracing#tracing)), we can analyze it to extract useful execution data.
### Commands
Since CTF traces (the output format of the [LTTng](https://lttng.org/) tracer) are very slow to read, we first convert them into a single file which can be read much faster.
```
$ ros2 trace-analysis convert /path/to/trace/directory
```
Then we can process it to create a data model which could be queried for analysis.
```
$ ros2 trace-analysis process /path/to/trace/directory
```
### Jupyter
The last command will process and output the raw data models, but to actually display results, process and analyze using a Jupyter Notebook.
```
$ jupyter notebook
```
Then navigate to the [`analysis/`](./tracetools_analysis/analysis/) directory, and select one of the provided notebooks, or create your own!
For example:
```python
from tracetools_analysis import loading
from tracetools_analysis import processor
from tracetools_analysis import utils
# Load trace directory or converted trace file
events = loading.load_file('/path/to/trace/or/converted/file')
# Process
ros2_handler = processor.Ros2Handler()
cpu_handler = processor.CpuTimeHandler()
processor.Processor(ros2_handler, cpu_handler).process(events)
# Use data model utils to extract information
ros2_util = utils.ros2.Ros2DataModelUtil(ros2_handler.data)
cpu_util = utils.cpu_time.CpuTimeDataModelUtil(cpu_handler.data)
callback_durations = ros2_util.get_callback_durations()
time_per_thread = cpu_util.get_time_per_thread()
# ...
# Display, e.g. with bokeh or matplotlib
# ...
```
## Design
See the [`ros2_tracing` design document](https://gitlab.com/micro-ROS/ros_tracing/ros2_tracing/blob/master/doc/design_ros_2.md), especially the [*Goals and requirements*](https://gitlab.com/micro-ROS/ros_tracing/ros2_tracing/blob/master/doc/design_ros_2.md#goals-and-requirements) and [*Analysis*](https://gitlab.com/micro-ROS/ros_tracing/ros2_tracing/blob/master/doc/design_ros_2.md#analysis) sections.