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A Python package for recognizing build-up and decay events from pollutant concentration data and estimating pollutant loss rates.

Project description

GitHub License All Contributors Dev Documentation DOI

Airpeak

A Python package for recognizing build-up and decay events from pollutant concentration data and estimating pollutant loss rates.

Installation

You can simply install this python package by running this in your terminal.

pip install Airpeak

or

  1. Clone this repository on your machine :

    git clone git@github.com:EPFL-HOBEL/Airpeak.git
    
  2. Go inside the root directory of this package (where pyproject.toml is) and run this command :

    pip install .
    

Documentation

You can either read online documentation from this link.

Or follow these steps and build them locally :

  1. Go inside the root directory of this package (where pyproject.toml is) and run this command :

    pip install .[docs]
    
  2. Run from root directory

    make -C docs html
    
  3. Open docs/build/html/index.html with your favorite browser.

Reference

  1. Du, B., & Siegel, J. A. (2023). Estimating indoor pollutant loss using mass balances and unsupervised clustering to recognize decays. Environmental Science & Technology, 57(27), 10030-10038. https://doi.org/10.1021/acs.est.3c00756

  2. Du, B., Reda, I., Licina, D., Kapsis, C., Qi, D., Candanedo, J. A., & Li, T. (2024). Estimating Air Change Rate in Mechanically Ventilated Classrooms Using a Single CO2 Sensor and Automated Data Segmentation. Environmental science & technology, 58(42), 18788-18799. https://doi.org/10.1021/acs.est.4c02797

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Bowen Du
Bowen Du

💻 🔣
Quentin Eschmann
Quentin Eschmann

💻 📖

This project follows the all-contributors specification. Contributions of any kind welcome!

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