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Project description
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
-
Clone this repository on your machine :
git clone git@github.com:EPFL-HOBEL/Airpeak.git
-
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 :
-
Go inside the root directory of this package (where pyproject.toml is) and run this command :
pip install .[docs]
-
Run from root directory
make -C docs html
-
Open docs/build/html/index.html with your favorite browser.
Reference
-
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
-
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 💻 🔣 |
Quentin Eschmann 💻 📖 |
This project follows the all-contributors specification. Contributions of any kind welcome!
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