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Implement efficient seeking from non-null trees using tree_pos #2911
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #2911 +/- ##
==========================================
- Coverage 89.79% 89.59% -0.21%
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Files 30 30
Lines 30399 30472 +73
Branches 5909 5922 +13
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+ Hits 27296 27300 +4
- Misses 1778 1846 +68
- Partials 1325 1326 +1
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That is interesting. I can see the LD calculator causing problems as that does a lot of seeking backward and forward (was the original motivation for bidirectional seeking). I don't see anything obvious wrong, but it must be something to do with sample counts. One thing that we can at least make progress on is that I think we should keep the option of seeking linearly. So, we make a new option to We should specify this option in the ld_calculator, as that is definitely somewhere that linear seeking makes sense. |
Okay; that makes sense to me. I'll revert |
seek_skip might be a bit more descriptive? |
Description
Continuing from #2874, we want to finish moving over the tree-positioning code to use
tree_pos
efficiently. At the moment,tsk.tree_seek
will either calltsk_tree_seek_from_null
ortsk_tree_seek_linear
depending on whether we are starting from the null tree or not.seek_linear
repeatedly callsnext
orprev
until it reaches the given position, with the direction being determined by which would cover the shortest distance.As a first pass, I've implemented
tsk_tree_seek_forward
andtsk_tree_seek_backward
and I've incorporated them intotsk_tree_seek_linear
. We will need to revise some of thetest_highlevel.py
seek tests, because the direction we choose to seek along is different to the old approach in some cases. For example, we now seek forward to go from the first to the last tree in a sequence.Curiously, my implementation passes all the C tests with no memory issues detected by Valgrind, and it also passes all the
test_highlevel.py
andtest_tree_positioning
tests except for the ones dependent on seeking direction. However, it has caused chaos with other Python tests, causing failures and segfaults intest_stats.py
andtest_divmat.py
among others. The failing/crashing tests seem to be primarily be associated with LD calculations and divergence.I'm currently trying to determine whether the problems are due to an error in my implemention (most likely) or the subtle problems with the time ordering of inserted edges, discussed in #2792.
PR Checklist: