Aquanalysis

Analyze swimming tracking data collected with Aquanote.

Repository structure

├── metrics.py              # Reusable analysis functions (load, stats, rankings, plots)
├── aquanote.ipynb           # Notebook demonstrating the analysis workflow
├── exemple_annotation_ligne_5_cycles.csv   # Example CSV data
├── figures/                 # Saved figures
├── requirements.txt
└── README.md

Features

• Descriptive statistics — per-swimmer and per-lap summaries of tempo, frequency, amplitude, and speed
• Rankings — rank swimmers or laps by any metric
• Visualizations — bar charts, box plots, cumulative speed charts, lap comparisons

How to run locally

Using venv (recommended)

1. Create a virtual environment:

python -m venv venv

2. Activate the environment:

• macOS/Linux:

  source venv/bin/activate

• Windows:

  venv\Scripts\activate

3. Install dependencies:

pip install --upgrade pip
pip install -r requirements.txt

4. Launch Jupyter:

jupyter notebook

Then open aquanote.ipynb.

Usage example

from metrics import load_csv, enrich_cycles, rank_swimmers, plot_ranking

df = load_csv("exemple_annotation_ligne_5_cycles.csv")
df = enrich_cycles(df)
rank_swimmers(df, "vitesse (m/s)")
plot_ranking(df, "vitesse (m/s)")