This project uses Jupyter Book to organize a collection of Jupyter Notebooks into a website.
- The notebooks all live in the notebooks directory. Note that the notebooks are stored in "stripped" form, without any outputs of execution saved. (They are executed as part of the build process.)
- The table of contents is located in _toc.yml.
- The book configuration is in _config.yml.
- The references are in _references.bib.
The environment in which to run the notebooks and build the books is defined in environment.yaml. To recreate and activate the environment locally, run
conda env create -f environment.yaml
conda activate L96M2lines
To speed up the continuous integration, we also generated a conda lock file for linux as follows.
conda-lock lock --mamba -f environment.yaml -p linux-64
This file lives in conda-linux-64.lock. It should be regenerated periorically.
To build the book locally, you should first create and activate your environment, as described above. Then run
jupyter book build .
When you run this command, the notebooks will be executed. The built html will be placed in '_build/html`. To preview the book, run
cd _build/html
python -m http.server
The build process can take a long time, so we have configured the setup to use
jupyter-cache.
If you re-run the build command, it will only re-execute notebooks
that have been changed. The cache files live in _build/.jupyter_cache
To check the status of the cache, run
jcache cache list -p _build/.jupyter_cache
To clear the cache, run
jcache cache clear -p _build/.jupyter_cache
We use pre-commit to keep the notebooks clean. In order to use pre-commit, run the following command in the repo top-level directory: The pre commit
pre-commit install
At this point, pre-commit will automatically be run every time you make a commit.
In order to contribute a PR, you should start from a new feature branch.
git checkout -b my_new_feature
(Replace my_new_feature with a descriptive name of the feature you're working on.)
Make your changes and then make a new commit:
git add changed_file_1.ipynb changed_file_2.ipynb
git commit -m "message about my new feature"
You can also automatically commit changes to existing files as:
git commit -am "message about my new feature"
Then push your changes to your remote on GitHub (usually call origin
git push my_new_feature origin
Then navigate to https://github.com/m2lines/L96_demo to open your pull request.
To synchronize your local branch with upstream changes, first make sure you have the upstream remote configured. To check your remotes, run
% git remote -v
origin [email protected]:rabernat/L96_demo.git (fetch)
origin [email protected]:rabernat/L96_demo.git (push)
upstream [email protected]:m2lines/L96_demo.git (fetch)
upstream [email protected]:m2lines/L96_demo.git (push)
If you don't have upstream, you need to add it as follows
git remote add upstream [email protected]:m2lines/L96_demo.git
Then, make sure you are on the main branch locally:
git checkout main
And then run
git fetch upstream
git merge upstream/main
Ideally you will not have any merge conflicts. You are now ready to make a new feature branch.
Arnold, H. M., I. M. Moroz, and T. N. Palmer. “Stochastic Parametrizations and Model Uncertainty in the Lorenz ’96 System.” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1991 (May 28, 2013): 20110479. https://doi.org/10.1098/rsta.2011.0479.
Brajard, Julien, Alberto Carrassi, Marc Bocquet, and Laurent Bertino. “Combining Data Assimilation and Machine Learning to Infer Unresolved Scale Parametrization.” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 379, no. 2194 (April 5, 2021): 20200086. https://doi.org/10.1098/rsta.2020.0086.
Schneider, Tapio, Shiwei Lan, Andrew Stuart, and João Teixeira. “Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations.” Geophysical Research Letters 44, no. 24 (December 28, 2017): 12,396-12,417. https://doi.org/10.1002/2017GL076101.
Wilks, Daniel S. “Effects of Stochastic Parametrizations in the Lorenz ’96 System.” Quarterly Journal of the Royal Meteorological Society 131, no. 606 (2005): 389–407. https://doi.org/10.1256/qj.04.03.