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[ENH] Fix patch sampling for discontiguous case #219
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #219 +/- ##
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+ Coverage 88.48% 88.50% +0.01%
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Files 54 54
Lines 4891 4896 +5
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+ Hits 4328 4333 +5
Misses 563 563 ☔ View full report in Codecov by Sentry. |
Is it possible to refashion something like this benchmark to see if there is a runtime slowdown? I'm unsure if the vector vs memoryview needs to be careful (i.e. does it create a copy instead of a reference unnecessarily)? Just run once on |
Apologies @j1c! I messed up the main branch, and as a result this PR auto-closed. Do you mind resubmitting it to I will try to take a look at this issue this upcoming month after NeurIPS submission time |
Fixes #215
Changes proposed in this pull request:
sktree/tree/manifold/_morf_splitter.pyx
dim_contiguous
, then we sample indices sequentially fromtop_left_seed
to thetop_left_seed+patch_dim
. If not, then we randomly sample indices based onpatch_dim
.vectors
because I was getting Python object/GIL errors on compilation when trying to usearrays
andvector[vectors]
interchangeably.sktree/tree/_utils.pyx
unravel_index_cython
to return rather than inplace replacement of one of the inputsintp_t[:]
tovector[intp_t]
for inputs/outputs for some functions for compatibility with changes to_morf_splitter.pyx
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