Set notebook structure and implemented KTIP algorithm

[joehiggi1758]

Pull Request Checklist

Below is a simple checklist but please do not hesitate to ask for assistance!

• Fork, clone, and checkout the newest version of the code
• Create a new branch
• Make necessary code changes
• Install black (i.e., python -m pip install black or conda install -c conda-forge black)
• Install flake8 (i.e., python -m pip install flake8 or conda install -c conda-forge flake8)
• Install pytest-cov (i.e., python -m pip install pytest-cov or conda install -c conda-forge pytest-cov)
• Run black --exclude=".*\.ipynb" --extend-exclude=".venv" --diff ./ in the root stumpy directory
• Run flake8 --extend-exclude=.venv ./ in the root stumpy directory
• Run ./setup.sh dev && ./test.sh in the root stumpy directory
• Reference a Github issue (and create one if one doesn't already exist)

[review-notebook-app]

Check out this pull request on

See visual diffs & provide feedback on Jupyter Notebooks.

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 97.33%. Comparing base (9616686) to head (0f2766c).

Additional details and impacted files

@@ Coverage Diff @@## main #1040 +/- ##
=======================================
Coverage 97.33% 97.33% =======================================
Files 89 89 Lines 15027 15027 =======================================
Hits 14626 14626 Misses 401 401 

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[seanlaw]

@joehiggi1758 I know that this is still a work-in-progress but this looks fantastic! I haven't gone over things in detail but, at a high level, I really like how you're breaking everything down in consumable chunks and also explaining each part very clearly. One thing I would like to ask is if can please cross-reference sections/figures/algorithms within the paper so something like:

The next step is to calculate the lower bound (see Section X.Y and Figures A-C)

This way, we can quickly find where things are within the original source.

Finally, please leave me a comment here when you think it is ready for any type of feedback or if you had any questions. Great job so far!

[joehiggi1758]

@seanlaw hope you're having a great one!

I've been fairly busy with work lately, but still wanted to move this forward!

I'm about 85% there, the full MOMP implementation isn't working yet - but open to your feedback up to this point on the structure, breakdown and implementation of each sub function!

[seanlaw]

Thanks @joehiggi1758 and no problem on any delays. Please allow me some time to review it and provide feedback.

[seanlaw]

Moved to #1046