[ENH] DTW AROW implementation

[tanishy7777]

Reference Issues/PRs

Fixes #751

What does this implement/fix? Explain your changes.

This PR aims to add DTW AROW algorithm, which is a modification of the DTW distance metric, that locally finds the best alignment between two time series that may have some missing values.

Does your contribution introduce a new dependency? If yes, which one?

Any other comments?

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I have added the following labels to this PR based on the title: [ $\color{#FEF1BE}{\textsf{enhancement}}$ ]. I have added the following labels to this PR based on the changes made: [ $\color{#5209C9}{\textsf{distances}}$ ]. Feel free to change these if they do not properly represent the PR.

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[tanishy7777]

I have compared the results against the implementation here https://github.com/aras-y/DTW_with_missing_values Which has one of the original authors from the paper as a contributor

Zoomed in version

[tanishy7777]

Equivalence of original implementation and my implementation for a few other cases(from test_distances.py) Note: The original implementation dosen't support unequal no of channels thats why 1 extra output in the image for my implementation

[tanishy7777]

Equivalence for cost matrix and alignment path

[MatthewMiddlehurst]

Thanks. Currently the functions are not suitably documented and the top file comment seems to be incorrect. Please look at other files for some examples

[tanishy7777]

Thanks. Currently the functions are not suitably documented and the top file comment seems to be incorrect. Please look at other files for some examples

Np! Will fix this soon.

[MatthewMiddlehurst]

Hi, any progress on this?