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Area - Out of core 💾Working with on disk dataWorking with on disk dataArea – Performance 🐌MetaA meta-request to be implemented in multiple stepsA meta-request to be implemented in multiple steps
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What kind of feature would you like to request?
Additional function parameters / changed functionality / changed defaults?
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Meta issue tracking scanpy functions without dask support
Related #921
First we should test things more generically:
- add global
array_typefixture to use in all tests for features below
@ivirshup came up with places where we should prioritize dask support:
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normalize_total- seems to work: Fix normalize_total for dask #2466
- has tests: Allow dask arrays to propagate through _normalize_data() #1663
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log1p,normalize_per_cell,filter_cells/*_genes:- accept Dask arrays: Support running on distributed compute engines like Dask, and Spark via Zap #283
- Test that they are kept as Dask arrays throughout: Test full Dask support for
log1p,normalize_per_cell,filter_cells/filter_genes#2814
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sc.pp.pca: Dask PCA support #2563 Implement sparsecovariance_eighPCA using Dask #3263 -
sc.pp.calculate_qc_metrics(feat):calculate_qc_metricswithdask#3307 sc.pp.highly_variable_genes:-
sc.tl.rank_genes_groups- depends on Handle Dask arrays in some utilities #2621
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sc.pp.subsample/sc.pp.sample: so simple it has always been supported - Aggregate: https://flox.readthedocs.io/en/latest/
sc.get.aggregatewith dask #3659
Later:
- scale updates sparse scale #2942
- nearest-neighbors: Nearest Neighbors dask/dask-ml#982 may need to implement ourselves...
- umap: implement ourselves?
- metrics: depednent on squidpy decisions but should be dask-ifiable
- scrublet?
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Area - Out of core 💾Working with on disk dataWorking with on disk dataArea – Performance 🐌MetaA meta-request to be implemented in multiple stepsA meta-request to be implemented in multiple steps
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