2D ensemble weights #231
2D ensemble weights #231
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I can't turn the PR into a draft, but you can wait a little before reviewing this. While updating the Notebooks, I realized that |
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Alright, this is good for review. |
docs/notebooks/5_warminglevels.ipynb
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| "Next, the weights and the datasets can be passed to `xs.ensemble_stats` to calculate the ensemble statistics." | ||
| "Next, the weights and the datasets can be passed to `xs.ensemble_stats` to calculate the ensemble statistics. Note that if `split_experiments=True` is used, the datasets should be split before being sent to `ensemble_statistics`." |
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I don't understand this sentence. If we need to do it separatly doesn't that defeat the purpose ?
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You bring out a going counterpoint that even though we can now more easily weight the experiments separately, it's not really useful. For now, I've removed the text related to this from the notebooks, and split_experiments == False is the default anyway.
Two options:
- I change it so that an equal weight is given to all experiments. i.e. if SSP585 has 30 simulations and SSP245 only has 5, the total weight is still 1 each. This would allow for some fancy ensemble statistics that are not possible if you compute each experiment separately.
- I keep it as it is, it just won't be too useful.
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I don't see when we would want 1... so I would vote for 2 !
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A case for 1 (which is kinda what I had in mind when designing the option) would be if you want to make statistics on the full scope of possible climate change. @sarahclaude will need to do that for her project (although in her case, we would need to allow the weight between experiments to differ from 1).
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Yes it will be useful to be able to associate weights to experiement in an ensemble! I am not using it directly in ensemble_stats.
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# Conflicts: # HISTORY.rst
Pull Request Checklist:
number) and pull request (:pull:number) has been added.What kind of change does this PR introduce?
generate_weights:independence_level: GCMwere changed substantially. See Incorrect weights for independence_level="GCM" #230.institutionsplit_experiments: Pretty self-explanatoryskipna:timeorhorizondimension. If the dimension is not the same across all datasets, they are first reindexed to cover allhorizon/time.produce_horizonso it can accept multiple periods or warming levels.cleanupto prevent raising an error when nocat:attribute exists in the datasets.xs.ensemble_stats.xs.generate_weightsDoes this PR introduce a breaking change?
FutureWarninginensemble_statsthat was there sincexscen 0.4.0.stats_kwargsis not fully abandoned.independence_level: allwas renamedmodelfor better consistency.independence_level: GCMwere changed substantially. See Incorrect weights for independence_level="GCM" #230.periodinproduce_horizonhas been deprecated and replaced withperiods.to_levelwere updated to reflect more recent changes.Other information: