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Dear @geek-yang,
Small question. If you make a pull request, it means you are asking for a review by a team member right?
I noticed the first two points have been addressed nicely.
But I did not see any changes in 'files changed', that tackle the last point:
Cheers, Sem
-- Ah I know see this PR is 'still a work in progress' and it has not been set to 'Ready for review'!
Learned something again today! :)
Dear @geek-yang,
Small question. If you make a pull request, it means you are asking for a review by a team member right?
I noticed the first two points have been addressed nicely.
- Return dataarray with the shape ["anchor_year", "cluster_labels"] to be compatible with sklearn models (require inputs in the format of [samples, features])
- Add attributes to the returned values (e.g. latitude/longitude refer to the geographical center of each cluster)
But I did not see any changes in 'files changed', that tackle the last point:
- Replace errors with warnings when there is only one cluster found.
Cheers, Sem
-- Ah I know see this PR is 'still a work in progress' and it has not been set to 'Ready for review'!
Learned something again today! :)
Haha, thanks for your early review @semvijverberg . Indeed it is still a working progress. When it is ready for review, I will click the button ready for review and add you as the reviewer (see the right corner). Then you can check the code, leave your comment and let me know if you give me a pass or not. It will be done soon. But thanks for the early notice 😆 .
Hey @geek-yang,
Small remark. The suggestion to remove the intervals is not really needed. In a larger pipeline there is nothing wrong with not finding cluster at a specific lag.
Hence, my suggestion would be to remove the sentence "Please remove these intervals from the model before continuing." at line 118.
It is my opinion that after this minor change the PR can be merged.
Thanks for the work:)
Kudos, SonarCloud Quality Gate passed!
Tiny updates to RGDR module:
dataarray
with the shape["anchor_year", "cluster_labels"]
to be compatible with sklearn models (require inputs in the format of [samples, features])This PR closes #92 and closes #86