plots

Scripts to process and plot experiment results

Overview

The scripts in this directory serve the processing and plotting of the experiment results

parse_results.py transform the logs from the experiment runs into easier to work with CSV files.

plot_results.py then takes these CSV files and generates the plots you can see in the paper from them.

Requirements

The scripts assume they are run with Python 3.

The following python packages are required (version numbers indicate tested versions):

• matplotlib v3.1
• networkx v2.3

The required packages are listed in requirements.txt and can be installed using

pip3 install -r requirements.txt

Depending on your operating system and if you are in a virtualenv you might need to install tkinter to show the plots during script execution. On Ubuntu you can do this with

sudo apt-get install python3-tk

Usage

parse_results.py

This scripts takes the logs from your experiments runs and transforms them into easy to digest CSV files. Two files for each log are generated:

• A .times.csv which contains a line for each UDP packet sent during the experiment, logging its send time and reception time during the experiment and also some additional meta-data. It is used to generate the Packet Delivery Ratio and Source-to-sink Latency plots.
• A .stats.csv which contains all the statistical data gathered after the end of an experiment run. This includes: the number of failed transmissions, the packet buffer usage, and the number instances the (virtual) reassembly buffer was full.

The script takes no argument. Just execute it with

./parse_results.py
``

#### Environment variables
- `DATA_PATH`: (default: `./../../results`) Path where the logs to consider are
  stored.
- `GLOBAL_PREFIX` (default: `2001:db8:0:1:`) Global IPv6 address prefix used
  during experiments (has to be of length 64 bits)

### `plot_results.py`
This script generates various plots generated from the CSV files created with
[`parse_results.py`][#parse_resultspy]. It also tries to call `parse_results`
in case the CSV files for a log don't exist yet (on-the-fly CSV generation).
Because of that it is recommended to re-run `parse_results.py` after you
execute `plot_results.py` while new logs are still generated to incorparate data
added to the logs during your execution of `plot_results.py`.

For more information on the script, see

```sh
./plot_results.py

Environment variables

• DATA_PATH: (default: ./../../results) Path where the logs to consider are stored.

For on-the-fly CSV generation you also can set the environment variables used by [parse_results.py][#parse_results.py]