A memory efficient implementation of the .mtx reading function #3389
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #3389 +/- ##
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- Coverage 75.44% 75.41% -0.04%
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Files 113 113
Lines 13250 13266 +16
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+ Hits 9997 10005 +8
- Misses 3253 3261 +8
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Please note that the selection of the chunk size of |
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Thank you! Since you don’t seem interested in appearing in a release note:
… I’ll merge this as-is. If you want a release note after all, please comment, and I’ll add one! |
meeseeksmachine
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Feb 25, 2025
…tx reading function
flying-sheep
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Feb 25, 2025
…ing function (#3483) Co-authored-by: Gustavo Jeuken <[email protected]>
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Pandas
read_csvfunction is very memory intensive, and this makes loading data (especially large datasets from EBI Single Cell Expression Atlas) impossible on computers with 16gb of ram or less. The subsequent analysis of such datasets with scanpy, however, works well on such computers.Loading the data into chunks, using the same pandas function, solves this problem.