lair is a collection of tools that I have developed/acquired for my research regarding land-air interactions. The lair package is designed to make it easier to work with atmospheric data.
The lair package is installable from the git repository via pip, however, some dependencies can only be installed via conda.
Additionally, many components of lair require access to CHPC which encourages the use of conda. Therefore, we recommend using conda to install the package.
If you are using CHPC, it is assumed that
miniforge3is installed following the instructions at https://www.chpc.utah.edu/documentation/software/python-anaconda.php
To create a new conda environment for lair, use the following command:
mamba create -n lair -c conda-forge python=3.10 esmpyIf you already have a conda environment, simply install the dependencies:
mamba activate <lair-env>
mamba install -c conda-forge esmpy
lairrequires Python 3.10 or higher.
Now we can install the package via pip. Either directly from the git repository:
pip install git+https://github.com/jmineau/lair.gitor by cloning the repository and installing it as an editable package:
git clone https://github.com/jmineau/lair.git
cd lair
pip install -e .Verbosity for the lair package is set via lair.config.verbose as a boolean.
For early versions of the package, verbose will be set to True by default. This will be changed in future versions.
This package was partially inspired and uses some code generously provided by Brian Blaylock's Carpenter Workshop python package.
- Portions of this package were written with AI-based tools including Github CoPilot, ChatGPT, and Google Gemini.
- Additionally, various code snippets were borrowed from StackOverflow and other online resources.
Contributions are welcome! Please take a look at current issues and feel free to submit a pull request with new features or bug fixes.
If you use any portion of this package in your research, please cite the software and/or acknowledge me.
A DOI will be provided in the future.