Algorithms

Structure and Organization of the Repo

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

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 cs

Building the Book

To build the book locally, you should first create and activate your environment, as described above. Then run

jupyter book build .

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 --kind explicit

This file lives in conda-linux-64.lock. It should be regenerated periorically.

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 remove cached notebooks, run

jcache cache remove -p _build/.jupyter_cache

Contributing

Pre-commit

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.

Pull Requests and Feature Branches

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 origin my_new_feature

Then navigate to https://github.com/compressed-sensing/algorithms to open your pull request.

Synchronizing from upstream

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	git@github.com:compressed-sensing/algorithms.git (fetch)
origin	git@github.com:compressed-sensing/algorithms.git (push)
upstream	git@github.com:compressed-sensing/algorithms.git (fetch)
upstream	git@github.com:compressed-sensing/algorithms.git (push)

If you don't have upstream, you need to add it as follows

git remote add upstream git@github.com:compressed-sensing/algorithms.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.

References

This repository is built based on L96_demo.

compressed-sensing / algorithms