• Clone the repo with the --recurse-submodules flag, or
• Clone the repo as normal and run git submodule update --init --recursive inside it afterwards.

This notebook relies on the dataset associated with the paper, available at https://doi.org/10.22002/exv89-7v481. It must be downloaded to the directory named data in the same directory as this readme and the notebook. That is, once the data are downloaded, the directory structure should look like so:

.
├── airs-pan-paper-figures.ipynb
├── data
│   ├── climatology_PAN_prior.nc
│   ├── goes-abi
│   ├── modis-clouds
│   ├── spectral-signatures.nc
│   ├── states.csv
│   ├── strategy_tables
│   ├── uncertainty
│   ├── validation
│   └── west_coast_fire_pca.nc
├── environment-specific.yml
├── environment.yml
├── README.md
└── src
    ├── airs-pan-ml
    ├── jllutils
    └── muses_utils

This assumes that you have the micromamba program available to manage Python environments. If you use conda or mamba, subtituting those commands for micromamba below should work. If you use other environment management tools (poetry, uv, pipenv, etc.), you will need to make an environment with all the dependencies listed in environment.yml, then add the custom dependencies from src/.

• In the top directory (i.e., the one with this README), run:

micromamba create -n laughner-et-al-notebook -f environment.yml

(You can change the name following -n to whatever you like, just replace that in any of the following commands.)

• If any dependencies cannot be found, try micromamba search DEP, e.g., micromamba search pyhdf and update the version in the environment.yml file - conda-forge only seems to keep somewhat recent versions of some packages.
• Activate the new environment with micromamba activate laughner-et-al-notebook.
• cd into each of the directories under src and run pip install -e . in each.
• Unless you have a preferred way of creating notebook kernels, if using Jupyter Lab or the vanilla Jupyter Notebook to execute the notebook, run ipython kernel install --user --name='laughner-et-al-notebook' to create a Jupyter kernel for it.
  • If using VSCode or another way of running notebooks, follow the instructions for that program
• You will likely need to set the notebook to use this kernel at least the first time you open it.