weighted operations: performance optimisations
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Description
There was a discussion on the performance of the weighted mean/ sum in terms of memory footprint but also speed, and there may indeed be some things that can be optimized. See the posts at the end of the PR. However, the optimal implementation will probably depend on the use case and some profiling will be required.
I'll just open an issue to keep track of this.
@seth-p
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the performance discussion linked from PR 2922, then locate the weighted mean and sum entry points in xarray. Profile their memory footprint and speed across relevant use cases; done requires evidence-based optimizations, but the issue does not define specific acceptance criteria.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, performance
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100