Add efficient ClusterTable-based split_frequencies C++ function for SplitFrequency(NULL) by Copilot · Pull Request #252 · ms609/TreeTools

Copilot · 2026-02-16T12:50:11Z

SplitFrequency(NULL, forest) used an O(N·U·M) R-level loop comparing each unique split against each tree's splits. This adds a C++ implementation using the ClusterTable pairwise matching algorithm from consensus.cpp for efficient frequency counting.

C++ changes

src/consensus.cpp: Added calc_split_frequencies template — mirrors calc_consensus_tree but removes threshold filtering and early exit, iterates all trees, and uses std::map<vector<Rbyte>> for split deduplication across reference trees. Returns both the packed split matrix and per-split counts.
src/consensus.cpp: Added split_frequencies() entry point with the same stack/heap allocation strategy as consensus_tree().
src/RcppExports.cpp: Registered _TreeTools_split_frequencies wrapper and CallEntries entry.
R/RcppExports.R: Added R-side .Call wrapper.

R changes

R/Support.R: SplitFrequency() NULL path now calls split_frequencies() after RenumberTips + Preorder, then normalizes the ClusterTable output (filters trivial splits, complements bit patterns to match as.Splits convention where tip 1 is in-group).

Known remaining work

The R post-processing layer still has formatting gaps vs the as.Splits output:

Missing dimnames (node-number row names)
Some complement splits not normalizing correctly (e.g. 67 vs 18)
Minor ordering differences

The core C++ counting is correct; remaining issues are purely in the R format conversion.

Original prompt

This section details on the original issue you should resolve

<issue_title>Efficient implementation of SplitFrequency(NULL)</issue_title>
<issue_description>Computing the frequency of all splits would be MUCH faster if we used a ClusterTable approach.</issue_description>

<agent_instructions>Please update the SplitFrequency(NULL, forest) case so that it uses the efficient ClusterTable approach implemented in src/consensus.cpp. Essentially we want to calc_consensus_tree but without the early exit clause, so that we get counts of all splits in forest.

Recall that you will need to add any new API functions to RcppExports-manual.cpp as we can't use Rcpp::compileAttributes in this package.

Test cases that must pass tip tests/testthat/test-Support.R:
test_that("Node supports calculated correctly", {
treeSample <- list(
correct = ape::read.tree(text = "((((((A,B),C),D),E),F),out);"),
swapFE = ape::read.tree(text = "((((((A,B),C),D),F),E),out);"),
DEClade = ape::read.tree(text = "(((((A,B),C),(D,E)),F),out);"),
swapBC = ape::read.tree(text = "((((((A,C),B),D),E),F),out);"),
DbyA = ape::read.tree(text = "((((((A,D),C),B),E),F,G),out);")
)
expect_equal(
SplitFrequency(treeSample$correct, treeSample),
c("10" = 4, "11" = 4, "12" = 4, "13" = 3)
)

expect_error(SplitFrequency(NULL, treeSample), "must bear identical")
sameTips <- KeepTip(treeSample, TipLabels(treeSample$correct))
sameSplits <- do.call(c, as.Splits(sameTips))
expect_equal(SplitFrequency(sameTips),
structure(sameSplits[[!duplicated(sameSplits)]],
count = c(4, 4, 4, 3, 1, 1, 1, 1, 1))
)

monoSplit <- ape::read.tree(text = "((a, b, c, d), (e, f, g));")
expect_equal(SplitFrequency(list(monoSplit)),
structure(as.Splits(monoSplit), count = 1))

Internal nodes on each side of root

balanced <- ape::read.tree(text="((D, (E, (F, out))), (C, (A, B)));")
freq <- SplitFrequency(balanced, treeSample)
expect_equal(freq,
c("9" = 4, "10" = 4, "11" = 4, "12" = 4, "13" = 3)[names(freq)])

})
</agent_instructions>

Comments on the Issue (you are @copilot in this section)

Fixes Efficient implementation of SplitFrequency(NULL) #251

💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.

Co-authored-by: ms609 <1695515+ms609@users.noreply.github.com>

codecov · 2026-02-16T15:52:34Z

Codecov Report

❌ Patch coverage is 94.93671% with 8 lines in your changes missing coverage. Please review.
✅ Project coverage is 96.19%. Comparing base (2d350fe) to head (2174acf).
⚠️ Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
src/consensus.cpp	90.90%	8 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #252      +/-   ##
==========================================
- Coverage   96.20%   96.19%   -0.02%     
==========================================
  Files          75       75              
  Lines        5481     5618     +137     
==========================================
+ Hits         5273     5404     +131     
- Misses        208      214       +6

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github-actions · 2026-02-16T16:20:04Z

⚠️ This benchmark result is outdated. See the latest comment below.

Performance benchmark results

Call	Status	Change	Time (ms)
`as.Splits(bigTrees)`	⚪ NSD	5.95%	24.8 → 25.2, 22
`as.Splits(someTrees)`	⚪ NSD	1.87%	11.7 → 11.5, 11.4
`Consensus(forest1k.888, check = FALSE)`	⚪ NSD	0.94%	96.6 → 95.9, 95.6
`Consensus(forest201.80, check = FALSE)`	⚪ NSD	-0.76%	4.01 → 4.04, 4.07
`Consensus(forest21.260, 0.5, FALSE)`	⚪ NSD	0.23%	1.22 → 1.22, 1.22
`Consensus(forest21.260)`	⚪ NSD	0.36%	1.24 → 1.24, 1.24
`Consensus(forestMaj, 0.5, FALSE)`	⚪ NSD	1.44%	3.03 → 2.99, 2.98
`DropTip(tr2000, 5)`	⚪ NSD	0.71%	17 → 16.9, 16.9
`DropTip(tr80, 5)`	⚪ NSD	-0.79%	0.105 → 0.104, 0.107
`DropTip(unlen2k, 5)`	🟠 Slower 🙁	-39.17%	0.207 → 0.217, 0.295
`DropTip(unlen80, 5)`	⚪ NSD	-2.94%	0.0398 → 0.0405, 0.0414
`lapply(bigSplits, as.phylo)`	🟣 ~same	0.87%	31.7 → 31.4, 31.4
`lapply(someSplits, as.phylo)`	⚪ NSD	-0.64%	14.1 → 14.2, 14.1
`PathLengths(tr2000, full = TRUE)`	⚪ NSD	0.62%	16.4 → 16.2, 16.4
`PathLengths(tr80, full = TRUE)`	🟠 Slower 🙁	-230.14%	0.0349 → 0.113, 0.116
`PathLengths(tr80Unif, full = TRUE)`	🟠 Slower 🙁	-279.11%	0.0307 → 0.116, 0.117
`RootTree(tr2000, 5)`	⚪ NSD	2.38%	0.394 → 0.375, 0.394
`RootTree(tr80, c("t3", "t36"))`	⚪ NSD	-1.58%	0.0691 → 0.0688, 0.0709
`RootTree(tr80, "t3")`	⚪ NSD	-0.59%	0.0494 → 0.0489, 0.0502
`RootTree(tr80, "t30")`	⚪ NSD	-0.57%	0.0497 → 0.0491, 0.0506
`RootTree(unlen2k, 5)`	⚪ NSD	-1.03%	0.325 → 0.329, 0.329
`RootTree(unlen80, c("t3", "t36"))`	⚪ NSD	-1.25%	0.064 → 0.0636, 0.0657
`RootTree(unlen80, "t3")`	⚪ NSD	-0.49%	0.043 → 0.0428, 0.0435
`RootTree(unlen80, "t30")`	⚪ NSD	-1.99%	0.0428 → 0.0432, 0.0441
`TreeDist::RobinsonFoulds(forest201.80)`	⚪ NSD	0.39%	16.7 → 16.6, 16.6
`TreeDist::RobinsonFoulds(forest21.888)`	⚪ NSD	0.04%	3.31 → 3.29, 3.33
`TreeTools:::path_lengths(tr80$edge, tr80$edge.length, FALSE)`	⚪ NSD	-1.37%	0.103 → 0.104, 0.105
`TreeTools:::postorder_order(bal40)`	⚪ NSD	1.7%	0.00176 → 0.0017, 0.00175
`TreeTools:::postorder_order(bal40k)`	⚪ NSD	0.26%	0.434 → 0.432, 0.433
`TreeTools:::postorder_order(dbal40)`	⚪ NSD	1.12%	0.00187 → 0.00182, 0.00187
`TreeTools:::postorder_order(dbal40k)`	⚪ NSD	0.42%	2.4 → 2.38, 2.41
`TreeTools:::postorder_order(dpec40)`	⚪ NSD	1.61%	0.0031 → 0.00305, 0.00305
`TreeTools:::postorder_order(dpec40k)`	🟣 ~same	-0.17%	3610 → 3620, 3620
`TreeTools:::postorder_order(drnd80)`	⚪ NSD	0.97%	0.00517 → 0.00513, 0.00511
`TreeTools:::postorder_order(nbal40)`	⚪ NSD	0.5%	0.0022 → 0.00217, 0.00219
`TreeTools:::postorder_order(nbal40k)`	⚪ NSD	-0.34%	2.42 → 2.41, 2.45
`TreeTools:::postorder_order(npec40)`	⚪ NSD	1.16%	0.00337 → 0.00334, 0.00333
`TreeTools:::postorder_order(npec40k)`	🟣 ~same	0.34%	3650 → 3640, 3640
`TreeTools:::postorder_order(nrnd80)`	⚪ NSD	0.2%	0.00566 → 0.00564, 0.00565
`TreeTools:::postorder_order(pec40)`	⚪ NSD	3.42%	0.00175 → 0.00169, 0.00169
`TreeTools:::postorder_order(pec40k)`	⚪ NSD	-0.44%	0.431 → 0.43, 0.437
`TreeTools:::postorder_order(rnd80)`	⚪ NSD	4.49%	0.00222 → 0.00214, 0.0021

github-actions · 2026-02-16T16:26:08Z

⚠️ This benchmark result is outdated. See the latest comment below.

Performance benchmark results

Call	Status	Change	Time (ms)
`as.Splits(bigTrees)`	⚪ NSD	4.83%	23.9 → 20.8, 23.6
`as.Splits(someTrees)`	⚪ NSD	-1.89%	11 → 11.3, 11.1
`Consensus(forest1k.888, check = FALSE)`	⚪ NSD	-3.08%	95.3 → 101, 96.7
`Consensus(forest201.80, check = FALSE)`	⚪ NSD	-0.47%	4.01 → 4.07, 4.01
`Consensus(forest21.260, 0.5, FALSE)`	⚪ NSD	-0.55%	1.23 → 1.23, 1.23
`Consensus(forest21.260)`	⚪ NSD	-0.11%	1.24 → 1.24, 1.25
`Consensus(forestMaj, 0.5, FALSE)`	⚪ NSD	-1.03%	2.93 → 2.96, 2.95
`DropTip(tr2000, 5)`	⚪ NSD	-0.51%	16.9 → 17, 17
`DropTip(tr80, 5)`	⚪ NSD	-1.01%	0.104 → 0.106, 0.103
`DropTip(unlen2k, 5)`	⚪ NSD	-37.07%	0.208 → 0.289, 0.216
`DropTip(unlen80, 5)`	⚪ NSD	0.84%	0.0407 → 0.0403, 0.0405
`lapply(bigSplits, as.phylo)`	🟣 ~same	-0.84%	30.8 → 31.1, 31
`lapply(someSplits, as.phylo)`	🟣 ~same	-2.82%	13.5 → 13.9, 13.7
`PathLengths(tr2000, full = TRUE)`	⚪ NSD	-0.96%	16.3 → 16.4, 16.4
`PathLengths(tr80, full = TRUE)`	⚪ NSD	2.56%	0.0294 → 0.113, 0.0277
`PathLengths(tr80Unif, full = TRUE)`	⚪ NSD	2.73%	0.0309 → 0.115, 0.0294
`RootTree(tr2000, 5)`	⚪ NSD	-0.33%	0.375 → 0.377, 0.377
`RootTree(tr80, c("t3", "t36"))`	⚪ NSD	-1.83%	0.0685 → 0.0702, 0.0692
`RootTree(tr80, "t3")`	⚪ NSD	-3.16%	0.0478 → 0.0495, 0.0491
`RootTree(tr80, "t30")`	⚪ NSD	-2.03%	0.0485 → 0.0495, 0.0494
`RootTree(unlen2k, 5)`	⚪ NSD	0.13%	0.331 → 0.33, 0.33
`RootTree(unlen80, c("t3", "t36"))`	⚪ NSD	-1.8%	0.0626 → 0.0638, 0.0635
`RootTree(unlen80, "t3")`	⚪ NSD	-1.58%	0.0424 → 0.0433, 0.0429
`RootTree(unlen80, "t30")`	⚪ NSD	-1.91%	0.0424 → 0.0433, 0.0432
`TreeDist::RobinsonFoulds(forest201.80)`	⚪ NSD	0.17%	16.1 → 16.2, 16.1
`TreeDist::RobinsonFoulds(forest21.888)`	⚪ NSD	-1.56%	3.28 → 3.32, 3.34
`TreeTools:::path_lengths(tr80$edge, tr80$edge.length, FALSE)`	⚪ NSD	-0.1%	0.103 → 0.105, 0.102
`TreeTools:::postorder_order(bal40)`	⚪ NSD	1.73%	0.00173 → 0.0017, 0.00171
`TreeTools:::postorder_order(bal40k)`	⚪ NSD	-1.97%	0.424 → 0.435, 0.429
`TreeTools:::postorder_order(dbal40)`	⚪ NSD	0.6%	0.00184 → 0.00182, 0.00183
`TreeTools:::postorder_order(dbal40k)`	⚪ NSD	-3.03%	2.32 → 2.41, 2.37
`TreeTools:::postorder_order(dpec40)`	⚪ NSD	0.62%	0.00308 → 0.00305, 0.00306
`TreeTools:::postorder_order(dpec40k)`	⚪ NSD	0.17%	3620 → 3620, 3610
`TreeTools:::postorder_order(drnd80)`	⚪ NSD	-0.2%	0.00513 → 0.00512, 0.00516
`TreeTools:::postorder_order(nbal40)`	⚪ NSD	0.46%	0.00217 → 0.00214, 0.00218
`TreeTools:::postorder_order(nbal40k)`	🟣 ~same	-2.77%	2.34 → 2.41, 2.4
`TreeTools:::postorder_order(npec40)`	⚪ NSD	0.63%	0.00337 → 0.00334, 0.00335
`TreeTools:::postorder_order(npec40k)`	⚪ NSD	-0.02%	3620 → 3620, 3620
`TreeTools:::postorder_order(nrnd80)`	⚪ NSD	0.35%	0.00568 → 0.00566, 0.00566
`TreeTools:::postorder_order(pec40)`	⚪ NSD	1.67%	0.00173 → 0.0017, 0.00171
`TreeTools:::postorder_order(pec40k)`	⚪ NSD	-1.41%	0.424 → 0.433, 0.425
`TreeTools:::postorder_order(rnd80)`	⚪ NSD	0.46%	0.00216 → 0.00216, 0.00215

github-actions · 2026-02-17T08:23:13Z

Performance benchmark results

Call	Status	Change	Time (ms)
`as.Splits(bigTrees)`	⚪ NSD	-1.56%	24 → 22.2, 25.1
`as.Splits(someTrees)`	⚪ NSD	-0.2%	11.4 → 11.4, 11.3
`Consensus(forest1k.888, check = FALSE)`	⚪ NSD	-4.48%	95.4 → 102, 97.8
`Consensus(forest201.80, check = FALSE)`	⚪ NSD	-0.89%	4.05 → 4.11, 4.06
`Consensus(forest21.260, 0.5, FALSE)`	⚪ NSD	-0.79%	1.22 → 1.24, 1.23
`Consensus(forest21.260)`	⚪ NSD	-1.15%	1.24 → 1.27, 1.24
`Consensus(forestMaj, 0.5, FALSE)`	⚪ NSD	-1.13%	2.97 → 3.01, 3
`DropTip(tr2000, 5)`	⚪ NSD	-0.5%	16.6 → 16.5, 16.9
`DropTip(tr80, 5)`	⚪ NSD	0.77%	0.106 → 0.104, 0.106
`DropTip(unlen2k, 5)`	⚪ NSD	1.03%	0.213 → 0.207, 0.216
`DropTip(unlen80, 5)`	⚪ NSD	0.29%	0.041 → 0.0404, 0.0412
`lapply(bigSplits, as.phylo)`	⚪ NSD	-1.07%	31.1 → 31, 31.5
`lapply(someSplits, as.phylo)`	⚪ NSD	-0.79%	14 → 14.2, 13.9
`PathLengths(tr2000, full = TRUE)`	⚪ NSD	-0.26%	15.9 → 15.7, 16
`PathLengths(tr80, full = TRUE)`	⚪ NSD	-273.64%	0.0294 → 0.111, 0.0322
`PathLengths(tr80Unif, full = TRUE)`	⚪ NSD	2.78%	0.0317 → 0.028, 0.0319
`RootTree(tr2000, 5)`	🟣 ~same	-5.26%	0.376 → 0.394, 0.396
`RootTree(tr80, c("t3", "t36"))`	⚪ NSD	-1.58%	0.0703 → 0.0712, 0.0716
`RootTree(tr80, "t3")`	⚪ NSD	-2.38%	0.049 → 0.0502, 0.0502
`RootTree(tr80, "t30")`	⚪ NSD	-2.23%	0.0495 → 0.0509, 0.0503
`RootTree(unlen2k, 5)`	⚪ NSD	1.55%	0.33 → 0.326, 0.323
`RootTree(unlen80, c("t3", "t36"))`	⚪ NSD	-0.11%	0.065 → 0.0654, 0.0647
`RootTree(unlen80, "t3")`	⚪ NSD	0.05%	0.0433 → 0.0433, 0.0433
`RootTree(unlen80, "t30")`	⚪ NSD	-0.23%	0.0436 → 0.044, 0.0433
`TreeDist::RobinsonFoulds(forest201.80)`	⚪ NSD	-0.39%	16.3 → 16.6, 16
`TreeDist::RobinsonFoulds(forest21.888)`	⚪ NSD	-0.58%	3.29 → 3.33, 3.28
`TreeTools:::path_lengths(tr80$edge, tr80$edge.length, FALSE)`	⚪ NSD	1.42%	0.103 → 0.1, 0.103
`TreeTools:::postorder_order(bal40)`	⚪ NSD	1.71%	0.00175 → 0.0017, 0.00174
`TreeTools:::postorder_order(bal40k)`	⚪ NSD	1.28%	0.433 → 0.424, 0.432
`TreeTools:::postorder_order(dbal40)`	⚪ NSD	1.02%	0.00186 → 0.00183, 0.00186
`TreeTools:::postorder_order(dbal40k)`	⚪ NSD	1.56%	2.38 → 2.34, 2.38
`TreeTools:::postorder_order(dpec40)`	⚪ NSD	0%	0.00307 → 0.00306, 0.00307
`TreeTools:::postorder_order(dpec40k)`	🟣 ~same	0.08%	3620 → 3610, 3610
`TreeTools:::postorder_order(drnd80)`	⚪ NSD	0.39%	0.00519 → 0.00516, 0.00517
`TreeTools:::postorder_order(nbal40)`	⚪ NSD	0.46%	0.0022 → 0.00217, 0.00221
`TreeTools:::postorder_order(nbal40k)`	⚪ NSD	1.17%	2.42 → 2.37, 2.4
`TreeTools:::postorder_order(npec40)`	⚪ NSD	-0.9%	0.00334 → 0.00338, 0.00337
`TreeTools:::postorder_order(npec40k)`	⚪ NSD	0.01%	3630 → 3620, 3630
`TreeTools:::postorder_order(nrnd80)`	⚪ NSD	0.35%	0.00572 → 0.00571, 0.00569
`TreeTools:::postorder_order(pec40)`	⚪ NSD	1.15%	0.00174 → 0.00173, 0.00172
`TreeTools:::postorder_order(pec40k)`	⚪ NSD	0.76%	0.43 → 0.425, 0.429
`TreeTools:::postorder_order(rnd80)`	⚪ NSD	0.91%	0.00219 → 0.00215, 0.00218

Initial plan

465c56c

Copilot AI assigned Copilot and ms609 Feb 16, 2026

Copilot started work on behalf of ms609 February 16, 2026 12:50 View session

WIP: Add split_frequencies C++ function using ClusterTable approach

271af51

Co-authored-by: ms609 <1695515+ms609@users.noreply.github.com>

Copilot AI changed the title ~~[WIP] Update SplitFrequency(NULL) to use ClusterTable approach~~ Add efficient ClusterTable-based split_frequencies C++ function for SplitFrequency(NULL) Feb 16, 2026

Copilot AI requested a review from ms609 February 16, 2026 13:44

Copilot finished work on behalf of ms609 February 16, 2026 13:44

ms609 added 3 commits February 16, 2026 15:22

Support counts parameter

d080ac6

Sort for testing

67d9f07

Print split counts

749a7ae

ms609 marked this pull request as ready for review February 16, 2026 15:42

ms609 added 3 commits February 16, 2026 16:01

printing small split sets

9714365

Checks

ede0e83

Catch zero-length forest

c4f1eed

Repository owner deleted a comment from github-actions bot Feb 16, 2026

ms609 added 3 commits February 17, 2026 07:49

r<4.1 <|

6ed9e9e

Coverage

d9a5231

Test heap

2174acf

Repository owner deleted a comment from github-actions bot Feb 17, 2026

ms609 merged commit 7e5f175 into main Feb 17, 2026
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ms609 deleted the copilot/update-splitfrequency-implementation branch February 17, 2026 08:16

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Add efficient ClusterTable-based split_frequencies C++ function for SplitFrequency(NULL)#252

Add efficient ClusterTable-based split_frequencies C++ function for SplitFrequency(NULL)#252
ms609 merged 11 commits intomainfrom
copilot/update-splitfrequency-implementation

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