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Refactor snipping to enable trans, inter-arm, etc pileups #475
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* pandas>2 groupby observed behavior in expected * another groupby fix in is_track
sergpolly
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Refactor snipping to enable trans pileups
Refactor snipping to enable trans, inter-arm, etc pileups
Jan 26, 2024
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Minimally invasive snipping refactor to enable pileups in trans:
pileups
behavior/API is unchanged !view_df
is no longer optional in the snipper-classes, it's a positional argument now_pileup
require explicitfeature_type
(bed/bedpe) parameter now - looks cleaner that way_extract_stack
is now more specialized - work forbed
features only,extract_stack_pairwise
deals with bedpepileups
functionnp.fmax
trick for "on-diagonals" is now inside internal_pileups
functionassign_view_auto
->combined_assignments_column=False
-> no longer returnsregion
column for BEDPE featuresmin_diag
doesn't require diagonal indicator matrixclr.matrix.fetch
results !pytest-allclose
for that https://cerfacs.fr/coop/pytest-allclose now inrequirements-dev
windows/features
- that were not view-annotated, but advertised as suchTODO
.flake8
->[ruff]
-section ofpyproject.toml
usingflake8-to-ruff
, ranrun format
on files modified by the PRfeature_type
to user-API + default_cols pileup: bed vs. bedpe inference #427Future Notes
region1==region2
- snipper-classes actually do that internally anyways - would yeild much cleaner code (same as in Refactoring snipping & pileups #227 (comment))lo/hi
business in the main-user facing function is not really used anywhere - snipper classes end up recalculating it anyways - so either cut it off, or actually make snipper-classes make use oflo/hi
columnspileups
functionMisc Notes
pileup
together with just an intra-arm expected - the script will crash/raise KeyError