msprime
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Initial outline for Trajectory refactoring
Here's a rough outline for what I'm thinking the low-level C will look like. I think it's worth getting things right here in the Python version before looking at the C --- it's much faster to try different things out here.
As discussed in #1803
Does this look like roughly the right design @andrewkern, @molpopgen?
Looks like we're missing quite a bit of stuff from the Python version though @andrewkern?
Codecov Report
Merging #1808 (e73e8aa) into main (7a49bc6) will decrease coverage by
0.01%
. The diff coverage is87.69%
.
@@ Coverage Diff @@
## main #1808 +/- ##
==========================================
- Coverage 90.92% 90.90% -0.02%
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Files 20 20
Lines 10511 10538 +27
Branches 2226 2231 +5
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+ Hits 9557 9580 +23
- Misses 497 498 +1
- Partials 457 460 +3
Flag | Coverage Δ | |
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C | 90.90% <87.69%> (-0.02%) |
:arrow_down: |
python | 97.52% <ø> (ø) |
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Impacted Files | Coverage Δ | |
---|---|---|
lib/util.h | 100.00% <ø> (ø) |
|
lib/msprime.c | 85.38% <87.50%> (-0.01%) |
:arrow_down: |
lib/util.c | 98.06% <100.00%> (+0.01%) |
:arrow_up: |
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This looks like it is on the right track. One source of confusion, for me at least, is how msprime's "new" ploidy argument gets handled here? This came up in the review of the other PR from @andrewkern -- the neutral fixation time being tested was 2n instead of 4n, and it wasn't clear (to me) why. Presumably, these trajectories should be considering an effective size of ploidy*n?
We don't have ploidy in the Python version @molpopgen, but we probably should. But yes, I think it would be best if we did things in the general case with arbitrary ploidy.
But yes, I think it would be best if we did things in the general case with arbitrary ploidy.
Yeah, seems prudent to iron out any wrinkles ASAP