Transpose the output of PairwiseDistance to match scikit-learn convention

[wreise]

Reference issues/PRs None

Types of changes

• [ ] Bug fix (non-breaking change which fixes an issue)
• [ ] New feature (non-breaking change which adds functionality)
• [X] Breaking change (fix or feature that would cause existing functionality to change)

Description Currently, the shape of a pairwise_distance.transform(X) is (X_fit.shape[0], X.shape[0]), where pairwise_distance = PairwiseDistance().fit(X_fit).

The above convention is the opposite the one in sklearn.neighbors.kNearestNeighbors. Hence, I propose to transpose the output of PairwiseDistance().transform to match that of sklearn.

Screenshots (if appropriate)

Any other comments?

Checklist

• [X] I have read the guidelines for contributing.
• [X] My code follows the code style of this project. I used flake8 to check my Python changes.
• [X] My change requires a change to the documentation.
• [ ] I have updated the documentation accordingly.
• [ ] I have added tests to cover my changes.
• [ ] All new and existing tests passed. I used pytest to check this on Python tests.

[ulupo]

I agree with this change, thanks for suggesting it! Another approach to this (that I might slightly prefer) would be to revise the code for _parallel_pairwise. I wonder what @gtauzin as he is the original author of this.

[ulupo]

@wreise may I propose the following changes which should yield a simpler approach (against my own initial suggestions of intervening on _parallel_pairwise, sorry!): https://github.com/ulupo/giotto-tda/commit/69d65859fb6c217d413dad051069d116d37517ab

[ulupo]

@wreise I've attempted to implement the approach I proposed in https://github.com/ulupo/giotto-tda/commit/69d65859fb6c217d413dad051069d116d37517ab, let me know what you think!

[wreise]

@wreise I've attempted to implement the approach I proposed in ulupo@69d6585, let me know what you think!

Thanks, @ulupo - it looks great!

[ulupo]

@wreise thanks. Let's wait for @gtauzin's approval!