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Add foapy.partials package for partial-sequence interval analysis - #107

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004-partials-package
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Add foapy.partials package for partial-sequence interval analysis#107
goruha wants to merge 21 commits into
mainfrom
004-partials-package

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@goruha

@goruha goruha commented Apr 19, 2026 •
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Summary

  • Adds foapy.partials subpackage — the position-preserving counterpart to foapy.core and foapy.ma for sequences with gap positions (numpy masked arrays)
  • Gap positions are preserved throughout the pipeline; interval distances are measured using actual full-array indices (gaps count toward distance)
  • Exports order, alphabet, intervals_chain, intervals_tuple — all returning masked 1-D arrays of the same length as input

Key semantic distinction

foapy.ma foapy.partials
Gap handling Compressed out before computing Preserved; count toward interval distance
order() output 2-D masked matrix 1-D masked array (same length as input)
lossy output length Shorter (boundaries dropped) Same length (boundaries masked in-place)
redundant output length n+k using compressed positions n+k using actual full-array positions

Files changed

New source files: src/foapy/partials/ — __init__, _order, _alphabet, _intervals_chain, _intervals_tuple

Modified: src/foapy/__init__.py — lazy submodule registration for foapy.partials

New tests: 5 test files covering all functions, all binding × chain_mode × tuple_mode combinations, gap semantics, error handling, and no-mask passthrough consistency with core.

Test plan

  • tox -e default — 503 tests passing, 0 failures
  • pre-commit run --all-files — black, isort, flake8 all pass
  • Quickstart examples execute without error

🤖 Generated with Claude Code

Maximus2012 and others added 19 commits March 13, 2026 18:47
@Maximus2012
feat: extract intervals_chain, intervals_tuple, intervals_distributio…
13e478b 
…n from intervals.py (#83 #84 #85)
@Maximus2012
style: reformat __init__.py
3b26e12
@goruha
Added CLAUDE
9b59336
@goruha
Added speckit
4cfeabe
@goruha
Added speckit
570e81f
@goruha
Added spec
ad430a8
@goruha
Clarify
991fdeb
@goruha
Added tasks
32e4184
@goruha @claude
feat: decompose intervals pipeline into chain/tuple/distribution stages
363e0bf 
Introduces chain_mode, tuple_mode enums and four new pipeline functions:
intervals_chain, intervals_tuple, intervals_distribution,
is_valid_intervals_chain — all vectorised (no Python loops), with
callable binding(chain) and chain_mode(chain) introspection, foapy.ma
variants, ASV benchmarks, and 107 new tests (442 total, 0 failures).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
@goruha
refactoring
ad33698
@goruha
Fix intervals_tuple
ba0adec
@goruha
Added status
9dc1406
@goruha
Commit implementation
7ae5e34
@goruha
Update spec
12f5757
@goruha
Fix specs
37c0c7b
@goruha
Depricate intervals and mode (#106)
56f3b42 
* Depricate intervals and mode

* Apply suggestions from code review

Co-authored-by: Igor Rodionov  <496956+goruha@users.noreply.github.com>

* Fix docs

* Fix benchmarks
@goruha
Fix menu
d5cc121
@goruha
Specs partials
d729f51
@goruha
Added partials
5ffb4ff
@coveralls

coveralls commented Apr 19, 2026 •
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Coverage Report for CI Build 31692340245

Coverage increased (+1.0%) to 94.595%

Details

  • Coverage increased (+1.0%) from the base build.
  • Patch coverage: 4 uncovered changes across 2 files (146 of 150 lines covered, 97.33%).
  • 1 coverage regression across 1 file.

Uncovered Changes

File Changed Covered %
src/foapy/init.py 4 1 25.0%
src/foapy/partials/init.py 12 11 91.67%
Total (6 files) 150 146 97.33%

Coverage Regressions

1 previously-covered line in 1 file lost coverage.

File Lines Losing Coverage Coverage
src/foapy/init.py 1 53.49%

Coverage Stats

Coverage Status
Relevant Lines: 555
Covered Lines: 525
Line Coverage: 94.59%
Coverage Strength: 2.84 hits per line
💛 - Coveralls

@goruha goruha changed the title 004 partials package Add foapy.partials package for partial-sequence interval analysis Apr 19, 2026
@github-actions

github-actions Bot commented Apr 19, 2026 •
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Change Before [879e227] After [438ebf9] Ratio Benchmark (Parameter)
- 18.2±0.1μs 16.0±0.1μs 0.88 bench_intervals.IntervalsSuite.time_intervals(5, 'Best', 1, 4)
- 19.2±0.1μs 16.5±0.1μs 0.86 bench_intervals.IntervalsSuite.time_intervals(5, 'Best', 2, 4)
- 18.8±0.08μs 17.1±0.3μs 0.91 bench_intervals.IntervalsSuite.time_intervals(5, 'DNA', 1, 4)
- 18.6±0.04μs 16.7±0.3μs 0.9 bench_intervals.IntervalsSuite.time_intervals(5, 'Normal', 1, 4)
- 12.8±0.1μs 11.6±0.1μs 0.91 bench_intervals.IntervalsSuite.time_intervals(5, 'Worst', 1, 1)
- 18.3±0.2μs 16.1±0.3μs 0.88 bench_intervals.IntervalsSuite.time_intervals(5, 'Worst', 1, 4)
- 18.9±0.2μs 16.5±0.2μs 0.87 bench_intervals.IntervalsSuite.time_intervals(5, 'Worst', 2, 4)
- 19.1±0.04μs 16.4±0.2μs 0.86 bench_intervals.IntervalsSuite.time_intervals(50, 'Best', 1, 4)
- 14.1±0.03μs 12.8±0.2μs 0.91 bench_intervals.IntervalsSuite.time_intervals(50, 'Best', 2, 1)
- 19.9±0.2μs 17.6±0.8μs 0.88 bench_intervals.IntervalsSuite.time_intervals(50, 'Best', 2, 4)
- 19.7±0.2μs 17.9±0.2μs 0.9 bench_intervals.IntervalsSuite.time_intervals(50, 'Worst', 1, 4)
- 24.4±0.3μs 22.1±0.2μs 0.9 bench_intervals.IntervalsSuite.time_intervals(500, 'Best', 1, 4)
- 3.88±0.1ms 3.46±0.1ms 0.89 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(1000000, 'Worst', 3)
- 52.1±0.4μs 38.4±0.2μs 0.74 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5, 'Best')
- 53.2±2μs 45.2±1μs 0.85 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5, 'Normal')
- 55.6±0.5μs 48.3±1μs 0.87 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5, 'Worst')
- 52.4±0.3μs 39.2±0.2μs 0.75 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(50, 'Best')
- 56.3±0.3μs 51.1±0.7μs 0.91 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(50, 'Worst')
- 55.7±0.4μs 42.3±0.2μs 0.76 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(500, 'Best')
- 87.5±0.4μs 73.0±2μs 0.83 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5000, 'Best')
- 29.5±0.2μs 25.3±0.4μs 0.86 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Best', 1, 1)
- 27.0±0.1μs 23.4±0.3μs 0.87 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Best', 1, 2)
- 28.2±0.5μs 24.6±0.2μs 0.87 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Best', 1, 3)
- 39.2±1μs 30.4±0.2μs 0.77 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Best', 1, 4)
- 30.8±0.2μs 26.4±0.3μs 0.86 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Best', 2, 1)
- 28.3±0.09μs 23.8±0.2μs 0.84 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Best', 2, 2)
- 29.0±0.08μs 25.0±0.4μs 0.86 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Best', 2, 3)
- 40.1±0.7μs 31.5±0.3μs 0.79 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Best', 2, 4)
- 30.7±0.1μs 26.2±0.4μs 0.85 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Best', 1, 1)
- 27.8±0.2μs 23.9±0.3μs 0.86 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Best', 1, 2)
- 39.1±0.4μs 31.3±0.2μs 0.8 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Best', 1, 4)
- 32.5±0.3μs 26.7±0.2μs 0.82 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Best', 2, 1)
- 28.9±0.1μs 24.2±0.2μs 0.84 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Best', 2, 2)
- 29.8±0.08μs 25.5±0.09μs 0.86 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Best', 2, 3)
- 40.4±0.2μs 32.8±2μs 0.81 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Best', 2, 4)
- 36.3±0.2μs 32.1±1μs 0.89 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Best', 1, 1)
- 33.7±0.7μs 28.8±0.3μs 0.85 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Best', 1, 2)
- 34.0±0.1μs 30.4±0.4μs 0.89 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Best', 1, 3)
- 46.7±0.5μs 37.8±0.4μs 0.81 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Best', 1, 4)
- 38.3±0.5μs 33.3±0.6μs 0.87 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Best', 2, 1)
- 35.3±0.2μs 30.8±0.4μs 0.87 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Best', 2, 2)
- 35.8±0.2μs 31.0±0.3μs 0.86 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Best', 2, 3)
- 48.5±0.5μs 38.9±0.4μs 0.8 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Best', 2, 4)
- 54.3±0.6μs 36.8±0.8μs 0.68 bench_ma_order.MaOrderSuite.time_order(5, 'Best')
- 61.0±1μs 50.9±0.3μs 0.83 bench_ma_order.MaOrderSuite.time_order(5, 'DNA')
- 54.0±2μs 43.8±3μs 0.81 bench_ma_order.MaOrderSuite.time_order(5, 'Normal')
- 61.4±0.5μs 51.4±1μs 0.84 bench_ma_order.MaOrderSuite.time_order(5, 'Worst')
- 55.0±0.6μs 36.8±0.6μs 0.67 bench_ma_order.MaOrderSuite.time_order(50, 'Best')
- 63.8±0.7μs 55.4±1μs 0.87 bench_ma_order.MaOrderSuite.time_order(50, 'DNA')
- 64.5±0.3μs 55.6±0.9μs 0.86 bench_ma_order.MaOrderSuite.time_order(50, 'Normal')
- 62.0±1μs 42.7±0.5μs 0.69 bench_ma_order.MaOrderSuite.time_order(500, 'Best')
- 111±0.9μs 94.1±0.7μs 0.85 bench_ma_order.MaOrderSuite.time_order(5000, 'Best')
- 31.9±2ms 27.9±1ms 0.87 bench_ma_order.MaOrderSuite.time_order(5000, 'Worst')
- 15.4±0.2μs 13.1±0.1μs 0.85 bench_order.OrderSuite.time_order(5, 'Best')
- 15.8±0.03μs 14.3±0.1μs 0.91 bench_order.OrderSuite.time_order(5, 'Normal')
- 15.8±0.07μs 14.1±0.3μs 0.89 bench_order.OrderSuite.time_order(5, 'Worst')
- 15.8±0.1μs 13.6±0.1μs 0.86 bench_order.OrderSuite.time_order(50, 'Best')
- 17.3±0.2μs 15.3±0.2μs 0.89 bench_order.OrderSuite.time_order(50, 'Worst')
- 21.3±0.3μs 18.8±0.1μs 0.89 bench_order.OrderSuite.time_order(500, 'Best')
Change Before [879e227] After [438ebf9] Ratio Benchmark (Parameter)
---------- ---------------------- --------------------- --------- --------------------------------------------------------------------------------------------------------
+ 7.31±0.06μs 8.63±0.05μs 1.18 bench_alphabet.AlphabetSuite.time_alphabet(50, 'DNA')
+ 6.99±0.04μs 7.99±0.2μs 1.14 bench_alphabet.AlphabetSuite.time_alphabet(50, 'Normal')
+ 6.97±0.04μs 7.75±0.05μs 1.11 bench_alphabet.AlphabetSuite.time_alphabet(50, 'Worst')
+ 15.9±0.2μs 25.9±0.3μs 1.63 bench_alphabet.AlphabetSuite.time_alphabet(500, 'DNA')
+ 17.7±0.2μs 28.4±0.2μs 1.6 bench_alphabet.AlphabetSuite.time_alphabet(500, 'Normal')
+ 19.8±0.2μs 35.1±0.3μs 1.77 bench_alphabet.AlphabetSuite.time_alphabet(500, 'Worst')
+ 146±1μs 222±6μs 1.53 bench_alphabet.AlphabetSuite.time_alphabet(5000, 'DNA')
+ 265±0.7μs 331±5μs 1.25 bench_alphabet.AlphabetSuite.time_alphabet(5000, 'Normal')
+ 345±0.9μs 447±4μs 1.29 bench_alphabet.AlphabetSuite.time_alphabet(5000, 'Worst')
+ 2.06±0.2ms 2.68±0.1ms 1.3 bench_alphabet.AlphabetSuite.time_alphabet(50000, 'DNA')
+ 21.3±0.3ms 24.1±0.05ms 1.13 bench_alphabet.AlphabetSuite.time_alphabet(500000, 'DNA')
+ 51.0±1ms 57.2±1ms 1.12 bench_alphabet.AlphabetSuite.time_alphabet(500000, 'Normal')
+ 71.7±0.6ms 80.0±0.4ms 1.11 bench_alphabet.AlphabetSuite.time_alphabet(500000, 'Worst')
+ 25.9±0.3μs 34.6±0.2μs 1.34 bench_intervals.IntervalsSuite.time_intervals(500, 'DNA', 1, 1)
+ 22.9±0.03μs 32.0±0.3μs 1.4 bench_intervals.IntervalsSuite.time_intervals(500, 'DNA', 1, 2)
+ 25.4±2μs 33.4±0.5μs 1.32 bench_intervals.IntervalsSuite.time_intervals(500, 'DNA', 1, 3)
+ 32.6±0.2μs 40.6±0.2μs 1.25 bench_intervals.IntervalsSuite.time_intervals(500, 'DNA', 1, 4)
+ 27.0±0.2μs 36.1±0.2μs 1.34 bench_intervals.IntervalsSuite.time_intervals(500, 'DNA', 2, 1)
+ 24.3±1μs 34.3±0.7μs 1.41 bench_intervals.IntervalsSuite.time_intervals(500, 'DNA', 2, 2)
+ 25.1±0.1μs 34.6±0.4μs 1.38 bench_intervals.IntervalsSuite.time_intervals(500, 'DNA', 2, 3)
+ 34.3±0.1μs 42.7±0.4μs 1.25 bench_intervals.IntervalsSuite.time_intervals(500, 'DNA', 2, 4)
+ 28.0±0.2μs 38.2±0.2μs 1.37 bench_intervals.IntervalsSuite.time_intervals(500, 'Normal', 1, 1)
+ 25.0±0.2μs 35.3±0.5μs 1.41 bench_intervals.IntervalsSuite.time_intervals(500, 'Normal', 1, 2)
+ 26.8±0.2μs 37.8±0.4μs 1.41 bench_intervals.IntervalsSuite.time_intervals(500, 'Normal', 1, 3)
+ 35.2±0.1μs 45.7±0.5μs 1.3 bench_intervals.IntervalsSuite.time_intervals(500, 'Normal', 1, 4)
+ 29.1±0.2μs 39.3±0.3μs 1.35 bench_intervals.IntervalsSuite.time_intervals(500, 'Normal', 2, 1)
+ 25.9±0.2μs 36.1±0.6μs 1.39 bench_intervals.IntervalsSuite.time_intervals(500, 'Normal', 2, 2)
+ 28.1±0.3μs 38.2±0.2μs 1.36 bench_intervals.IntervalsSuite.time_intervals(500, 'Normal', 2, 3)
+ 36.6±0.1μs 46.7±0.2μs 1.27 bench_intervals.IntervalsSuite.time_intervals(500, 'Normal', 2, 4)
+ 28.2±0.2μs 42.7±0.5μs 1.52 bench_intervals.IntervalsSuite.time_intervals(500, 'Worst', 1, 1)
+ 25.8±0.2μs 40.7±0.3μs 1.58 bench_intervals.IntervalsSuite.time_intervals(500, 'Worst', 1, 2)
+ 27.6±0.2μs 42.1±0.6μs 1.53 bench_intervals.IntervalsSuite.time_intervals(500, 'Worst', 1, 3)
+ 35.0±0.2μs 47.7±0.7μs 1.36 bench_intervals.IntervalsSuite.time_intervals(500, 'Worst', 1, 4)
+ 28.8±0.1μs 43.4±0.5μs 1.51 bench_intervals.IntervalsSuite.time_intervals(500, 'Worst', 2, 1)
+ 26.7±0.2μs 41.6±0.7μs 1.56 bench_intervals.IntervalsSuite.time_intervals(500, 'Worst', 2, 2)
+ 28.2±0.2μs 42.8±0.5μs 1.52 bench_intervals.IntervalsSuite.time_intervals(500, 'Worst', 2, 3)
+ 36.2±0.1μs 49.7±0.8μs 1.37 bench_intervals.IntervalsSuite.time_intervals(500, 'Worst', 2, 4)
+ 179±2μs 254±2μs 1.42 bench_intervals.IntervalsSuite.time_intervals(5000, 'DNA', 1, 1)
+ 170±2μs 247±5μs 1.45 bench_intervals.IntervalsSuite.time_intervals(5000, 'DNA', 1, 2)
+ 173±0.9μs 246±1μs 1.42 bench_intervals.IntervalsSuite.time_intervals(5000, 'DNA', 1, 3)
+ 199±1μs 273±7μs 1.37 bench_intervals.IntervalsSuite.time_intervals(5000, 'DNA', 1, 4)
+ 183±1μs 262±8μs 1.43 bench_intervals.IntervalsSuite.time_intervals(5000, 'DNA', 2, 1)
+ 174±2μs 251±6μs 1.44 bench_intervals.IntervalsSuite.time_intervals(5000, 'DNA', 2, 2)
+ 176±2μs 249±5μs 1.41 bench_intervals.IntervalsSuite.time_intervals(5000, 'DNA', 2, 3)
+ 203±1μs 273±4μs 1.34 bench_intervals.IntervalsSuite.time_intervals(5000, 'DNA', 2, 4)
+ 310±0.6μs 370±5μs 1.19 bench_intervals.IntervalsSuite.time_intervals(5000, 'Normal', 1, 1)
+ 293±2μs 350±6μs 1.19 bench_intervals.IntervalsSuite.time_intervals(5000, 'Normal', 1, 2)
+ 310±1μs 370±7μs 1.19 bench_intervals.IntervalsSuite.time_intervals(5000, 'Normal', 1, 3)
+ 340±2μs 402±6μs 1.18 bench_intervals.IntervalsSuite.time_intervals(5000, 'Normal', 1, 4)
+ 314±1μs 375±9μs 1.19 bench_intervals.IntervalsSuite.time_intervals(5000, 'Normal', 2, 1)
+ 297±0.9μs 352±6μs 1.18 bench_intervals.IntervalsSuite.time_intervals(5000, 'Normal', 2, 2)
+ 315±0.9μs 374±5μs 1.19 bench_intervals.IntervalsSuite.time_intervals(5000, 'Normal', 2, 3)
+ 343±1μs 404±8μs 1.18 bench_intervals.IntervalsSuite.time_intervals(5000, 'Normal', 2, 4)
+ 371±0.8μs 465±4μs 1.25 bench_intervals.IntervalsSuite.time_intervals(5000, 'Worst', 1, 1)
+ 366±2μs 469±4μs 1.28 bench_intervals.IntervalsSuite.time_intervals(5000, 'Worst', 1, 2)
+ 372±1μs 477±6μs 1.28 bench_intervals.IntervalsSuite.time_intervals(5000, 'Worst', 1, 3)
+ 388±2μs 485±5μs 1.25 bench_intervals.IntervalsSuite.time_intervals(5000, 'Worst', 1, 4)
+ 371±1μs 469±5μs 1.26 bench_intervals.IntervalsSuite.time_intervals(5000, 'Worst', 2, 1)
+ 368±2μs 470±6μs 1.28 bench_intervals.IntervalsSuite.time_intervals(5000, 'Worst', 2, 2)
+ 375±1μs 476±6μs 1.27 bench_intervals.IntervalsSuite.time_intervals(5000, 'Worst', 2, 3)
+ 391±1μs 494±40μs 1.26 bench_intervals.IntervalsSuite.time_intervals(5000, 'Worst', 2, 4)
+ 2.61±0.2ms 3.24±0.08ms 1.24 bench_intervals.IntervalsSuite.time_intervals(50000, 'DNA', 1, 1)
+ 2.66±0.02ms 3.01±0.04ms 1.13 bench_intervals.IntervalsSuite.time_intervals(50000, 'DNA', 1, 2)
+ 2.67±0.01ms 2.94±0.06ms 1.1 bench_intervals.IntervalsSuite.time_intervals(50000, 'DNA', 1, 3)
+ 3.04±0.06ms 3.42±0.05ms 1.13 bench_intervals.IntervalsSuite.time_intervals(50000, 'DNA', 1, 4)
+ 2.64±0.1ms 3.26±0.07ms 1.24 bench_intervals.IntervalsSuite.time_intervals(50000, 'DNA', 2, 1)
+ 2.69±0.01ms 3.00±0.06ms 1.12 bench_intervals.IntervalsSuite.time_intervals(50000, 'DNA', 2, 2)
+ 2.70±0.01ms 3.02±0.07ms 1.12 bench_intervals.IntervalsSuite.time_intervals(50000, 'DNA', 2, 3)
+ 3.09±0.06ms 3.40±0.05ms 1.1 bench_intervals.IntervalsSuite.time_intervals(50000, 'DNA', 2, 4)
+ 6.26±0.06ms 6.89±0.02ms 1.1 bench_intervals.IntervalsSuite.time_intervals(50000, 'Worst', 1, 2)
+ 5.88±0.04ms 6.52±0.06ms 1.11 bench_intervals.IntervalsSuite.time_intervals(50000, 'Worst', 1, 3)
+ 6.35±0.3ms 7.15±0.01ms 1.13 bench_intervals.IntervalsSuite.time_intervals(50000, 'Worst', 2, 3)
+ 10.9±0.2ms 12.1±0.09ms 1.1 bench_intervals.IntervalsSuite.time_intervals(500000, 'Best', 2, 4)
+ 27.0±0.4ms 30.0±0.6ms 1.11 bench_intervals.IntervalsSuite.time_intervals(500000, 'DNA', 1, 1)
+ 26.4±0.4ms 29.8±0.2ms 1.13 bench_intervals.IntervalsSuite.time_intervals(500000, 'DNA', 1, 2)
+ 26.4±0.4ms 29.5±0.5ms 1.12 bench_intervals.IntervalsSuite.time_intervals(500000, 'DNA', 1, 3)
+ 28.9±0.1ms 32.1±0.2ms 1.11 bench_intervals.IntervalsSuite.time_intervals(500000, 'DNA', 1, 4)
+ 26.9±0.3ms 30.1±0.3ms 1.12 bench_intervals.IntervalsSuite.time_intervals(500000, 'DNA', 2, 2)
+ 26.8±0.3ms 30.2±0.3ms 1.12 bench_intervals.IntervalsSuite.time_intervals(500000, 'DNA', 2, 3)
+ 29.5±0.3ms 33.0±0.4ms 1.12 bench_intervals.IntervalsSuite.time_intervals(500000, 'DNA', 2, 4)
+ 56.5±1ms 62.7±1ms 1.11 bench_intervals.IntervalsSuite.time_intervals(500000, 'Normal', 2, 2)
+ 74.9±0.4ms 83.1±0.3ms 1.11 bench_intervals.IntervalsSuite.time_intervals(500000, 'Worst', 1, 1)
+ 73.7±0.4ms 81.2±1ms 1.1 bench_intervals.IntervalsSuite.time_intervals(500000, 'Worst', 1, 3)
+ 76.1±0.4ms 84.5±0.2ms 1.11 bench_intervals.IntervalsSuite.time_intervals(500000, 'Worst', 2, 2)
+ 76.7±0.4ms 85.9±0.4ms 1.12 bench_intervals.IntervalsSuite.time_intervals(500000, 'Worst', 2, 3)
+ 11.9±0.04μs 13.6±0.1μs 1.14 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'DNA', 1, 1)
+ 13.0±0.07μs 14.8±0.2μs 1.15 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'DNA', 1, 2)
+ 12.5±0.06μs 14.4±0.1μs 1.15 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'DNA', 2, 1)
+ 13.5±0.05μs 15.1±0.08μs 1.12 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'DNA', 2, 2)
+ 11.6±0.06μs 13.2±0.2μs 1.14 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'Normal', 1, 1)
+ 12.7±0.1μs 14.5±0.1μs 1.14 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'Normal', 1, 2)
+ 12.1±0.07μs 13.5±0.2μs 1.12 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'Normal', 2, 1)
+ 13.2±0.06μs 14.6±0.2μs 1.11 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'Normal', 2, 2)
+ 11.6±0.08μs 13.0±0.2μs 1.12 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'Worst', 1, 1)
+ 12.3±0.06μs 14.0±0.2μs 1.14 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'Worst', 1, 2)
+ 12.1±0.1μs 13.5±0.1μs 1.11 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'Worst', 2, 1)
+ 13.2±0.1μs 14.6±0.1μs 1.11 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(100, 'Worst', 2, 2)
+ 406±0.9μs 494±7μs 1.22 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'DNA', 1, 1)
+ 409±3μs 495±6μs 1.21 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'DNA', 1, 2)
+ 411±1μs 500±6μs 1.22 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'DNA', 2, 1)
+ 413±0.7μs 493±7μs 1.19 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'DNA', 2, 2)
+ 656±2μs 751±8μs 1.15 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Normal', 1, 1)
+ 693±2μs 789±4μs 1.14 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Normal', 1, 2)
+ 663±0.9μs 756±9μs 1.14 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Normal', 2, 1)
+ 696±2μs 794±10μs 1.14 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Normal', 2, 2)
+ 888±4μs 999±3μs 1.13 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Worst', 1, 1)
+ 895±4μs 1.02±0ms 1.13 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Worst', 1, 2)
+ 884±4μs 1.01±0ms 1.14 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Worst', 2, 1)
+ 906±2μs 1.02±0ms 1.13 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Worst', 2, 2)
+ 51.3±0.7ms 57.3±0.4ms 1.12 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(1000000, 'DNA', 1, 1)
+ 51.6±0.4ms 57.4±0.08ms 1.11 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(1000000, 'DNA', 1, 2)
+ 53.3±0.4ms 59.0±0.5ms 1.11 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(1000000, 'DNA', 2, 2)
+ 114±2ms 128±2ms 1.12 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(1000000, 'Normal', 1, 1)
+ 120±2ms 133±2ms 1.11 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(1000000, 'Normal', 2, 1)
+ 122±2ms 135±2ms 1.1 bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(1000000, 'Normal', 2, 2)
+ 2.18±0.02μs 2.60±0.1μs 1.19 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(100, 'DNA')
+ 2.18±0μs 2.49±0.08μs 1.14 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(100, 'Normal')
+ 2.18±0.01μs 2.45±0.06μs 1.12 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(100, 'Worst')
+ 14.2±0.07μs 16.5±0.6μs 1.17 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(10000, 'Best')
+ 15.9±0.07μs 18.9±0.2μs 1.19 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(10000, 'DNA')
+ 18.8±0.1μs 22.5±1μs 1.2 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(10000, 'Normal')
+ 1.32±0.01ms 1.51±0.3ms 1.14 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(1000000, 'Best')
+ 1.52±0.04ms 1.73±0.4ms 1.14 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(1000000, 'DNA')
+ 2.63±0.01ms 3.30±0.03ms 1.25 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(1000000, 'Normal')
+ 1.98±0.08ms 2.70±0.3ms 1.36 bench_intervals_distribution.IntervalsDistributionSuite.time_intervals_distribution(1000000, 'Worst')
+ 1.28±0.01μs 1.58±0.06μs 1.23 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(100, 'Best', 2)
+ 3.13±0μs 3.63±0.09μs 1.16 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(100, 'DNA', 1)
+ 1.32±0.03μs 1.60±0.03μs 1.21 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(100, 'DNA', 2)
+ 3.17±0.01μs 3.66±0.07μs 1.15 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(100, 'Normal', 1)
+ 1.28±0.01μs 1.69±0.03μs 1.32 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(100, 'Normal', 2)
+ 1.27±0.01μs 1.62±0.02μs 1.27 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(100, 'Worst', 2)
+ 3.24±0.03μs 4.06±0.1μs 1.26 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(10000, 'Best', 2)
+ 15.1±0.06μs 17.2±0.2μs 1.14 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(10000, 'DNA', 1)
+ 3.39±0.08μs 4.64±0.2μs 1.37 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(10000, 'DNA', 2)
+ 39.3±0.08μs 43.3±1μs 1.1 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(10000, 'DNA', 3)
+ 22.1±0.2μs 37.8±0.2μs 1.71 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(10000, 'Normal', 1)
+ 3.28±0.09μs 5.30±0.3μs 1.62 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(10000, 'Normal', 2)
+ 55.1±0.3μs 87.7±0.7μs 1.59 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(10000, 'Normal', 3)
+ 9.26±0.09μs 11.6±0.2μs 1.25 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(10000, 'Worst', 1)
+ 3.32±0.03μs 5.00±0.2μs 1.51 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(10000, 'Worst', 2)
+ 1.31±0.05ms 1.56±0.02ms 1.19 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(1000000, 'Best', 1)
+ 248±30μs 374±20μs 1.51 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(1000000, 'Best', 2)
+ 275±2μs 305±6μs 1.11 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(1000000, 'DNA', 2)
+ 2.88±0.02ms 3.23±0.05ms 1.12 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(1000000, 'Normal', 1)
+ 281±2μs 335±30μs 1.19 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(1000000, 'Normal', 2)
+ 739±10μs 889±9μs 1.2 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(1000000, 'Worst', 1)
+ 286±3μs 400±20μs 1.4 bench_intervals_tuple.IntervalsTupleSuite.time_intervals_tuple(1000000, 'Worst', 2)
+ 75.7±1μs 84.1±2μs 1.11 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(500, 'Normal')
+ 398±3μs 453±7μs 1.14 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5000, 'Normal')
+ 431±4μs 502±7μs 1.16 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5000, 'Worst')
+ 4.77±0.02ms 5.38±0.09ms 1.13 bench_ma_alphabet.MaAlphabetSuite.time_alphabet(50000, 'Worst')
+ 29.3±1μs 32.5±1μs 1.11 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'DNA', 1, 1)
+ 27.1±0.9μs 30.0±0.6μs 1.11 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'DNA', 1, 2)
+ 28.7±1μs 31.7±0.7μs 1.11 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Worst', 1, 1)
+ 27.7±0.8μs 30.5±0.4μs 1.1 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Worst', 1, 3)
+ 27.1±1μs 31.3±0.7μs 1.15 bench_ma_intervals.MaIntervalsSuite.time_intervals(5, 'Worst', 2, 3)
+ 28.7±0.2μs 31.7±0.4μs 1.1 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Normal', 2, 2)
+ 29.5±0.4μs 33.2±1μs 1.13 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Normal', 2, 3)
+ 27.7±0.3μs 33.0±1μs 1.19 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Worst', 1, 2)
+ 29.4±0.3μs 33.6±0.4μs 1.15 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Worst', 2, 2)
+ 30.3±0.2μs 33.4±0.7μs 1.1 bench_ma_intervals.MaIntervalsSuite.time_intervals(50, 'Worst', 2, 3)
+ 34.4±0.9μs 40.5±2μs 1.18 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'DNA', 2, 3)
+ 41.8±0.4μs 52.8±1μs 1.26 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Normal', 1, 1)
+ 38.4±0.4μs 49.8±4μs 1.3 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Normal', 1, 2)
+ 39.1±0.8μs 49.0±1μs 1.25 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Normal', 1, 3)
+ 51.3±0.6μs 60.1±2μs 1.17 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Normal', 1, 4)
+ 48.4±0.6μs 59.8±2μs 1.24 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Normal', 2, 1)
+ 43.8±1μs 63.4±5μs 1.45 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Normal', 2, 2)
+ 45.1±0.7μs 58.9±3μs 1.3 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Normal', 2, 3)
+ 57.0±1μs 69.1±4μs 1.21 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Normal', 2, 4)
+ 54.2±1μs 65.0±0.7μs 1.2 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Worst', 1, 1)
+ 50.3±0.8μs 60.2±2μs 1.2 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Worst', 1, 2)
+ 52.7±2μs 62.6±1μs 1.19 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Worst', 1, 3)
+ 62.8±1μs 77.3±1μs 1.23 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Worst', 1, 4)
+ 59.8±0.9μs 84.1±7μs 1.41 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Worst', 2, 1)
+ 56.2±0.8μs 75.6±7μs 1.35 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Worst', 2, 2)
+ 58.2±1μs 73.6±5μs 1.26 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Worst', 2, 3)
+ 70.7±1μs 89.3±8μs 1.26 bench_ma_intervals.MaIntervalsSuite.time_intervals(500, 'Worst', 2, 4)
+ 272±2μs 330±2μs 1.21 bench_ma_order.MaOrderSuite.time_order(5000, 'DNA')
+ 29.4±0.07μs 37.2±0.3μs 1.27 bench_order.OrderSuite.time_order(500, 'DNA')
+ 31.7±0.2μs 40.6±0.6μs 1.28 bench_order.OrderSuite.time_order(500, 'Normal')
+ 34.3±0.2μs 47.7±0.8μs 1.39 bench_order.OrderSuite.time_order(500, 'Worst')
+ 193±2μs 269±5μs 1.39 bench_order.OrderSuite.time_order(5000, 'DNA')
+ 312±0.5μs 373±6μs 1.2 bench_order.OrderSuite.time_order(5000, 'Normal')
+ 406±1μs 502±6μs 1.24 bench_order.OrderSuite.time_order(5000, 'Worst')
+ 26.7±0.2ms 30.2±0.08ms 1.13 bench_order.OrderSuite.time_order(500000, 'DNA')
+ 82.1±0.4ms 93.0±1ms 1.13 bench_order.OrderSuite.time_order(500000, 'Worst')
+ 432±1μs 517±6μs 1.2 bench_pipeline_full.PipelineFullSuite.time_pipeline_full(10000, 'DNA')
+ 687±0.7μs 778±3μs 1.13 bench_pipeline_full.PipelineFullSuite.time_pipeline_full(10000, 'Normal')
+ 914±4μs 1.03±0.01ms 1.12 bench_pipeline_full.PipelineFullSuite.time_pipeline_full(10000, 'Worst')
+ 53.9±0.4ms 59.8±0.4ms 1.11 bench_pipeline_full.PipelineFullSuite.time_pipeline_full(1000000, 'DNA')
+ 159±0.4ms 181±1ms 1.13 bench_pipeline_full.PipelineFullSuite.time_pipeline_full(1000000, 'Worst')

@goruha
goruha changed the base branch from main to 002-decompose-intervals-pipeline April 19, 2026 21:51
Base automatically changed from 002-decompose-intervals-pipeline to main June 25, 2026 08:20
@goruha

goruha commented Jul 29, 2026

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@copilot resolve the merge conflicts in this pull request

Copilot AI commented Jul 29, 2026

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@copilot resolve the merge conflicts in this pull request

Merge conflicts resolved in commit 80b0812. There were three add/add conflicts:

  1. CLAUDE.md — kept the 004-partials-package Active Technologies line
  2. mkdocs.yml — kept main's nav ordering (tuple_mode before intervals_chain)
  3. src/foapy/core/_intervals_tuple.py — kept main's docstring examples with the correct binding parameter (intervals_tuple(chain, foapy.binding.start, foapy.tuple_mode.normal))

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4 participants

@goruha @coveralls @Maximus2012