feat: decompose intervals pipeline into chain/tuple/distribution stages

[goruha]

Summary

• Introduces chain_mode (boundary/cycle) and tuple_mode (lossy/normal/redundant) enums, decomposing the monolithic intervals() into three composable stages: intervals_chain → intervals_tuple → intervals_distribution
• Adds callable introspection via binding(chain) and chain_mode(chain) — detect metadata from a plain ndarray chain without extra state
• Adds is_valid_intervals_chain(chain) validator (never raises), foapy.ma variants for masked-array sequences, and four ASV benchmark suites
• All implementations are fully vectorised (no Python loops); backward-compatible — existing intervals() and mode enum unchanged

Test plan

• 107 new tests across 10 new test files (442 total, 0 failures)
• Pipeline consistency tests verify intervals_tuple(intervals_chain(X, b, cm), tm) matches intervals() for all lossy/normal/cycle combinations
• binding(chain) and chain_mode(chain) round-trip tests against chains produced by intervals_chain
• foapy.ma variants tested with partially masked sequences
• pre-commit (black / isort / flake8) passes clean

🤖 Generated with Claude Code

[coveralls]

Coverage Report for CI Build 24634835304

Coverage decreased (-0.3%) to 93.596%

Details

• Coverage decreased (-0.3%) from the base build.
• Patch coverage: 1 uncovered change across 1 file (125 of 126 lines covered, 99.21%).
• No coverage regressions found.

Uncovered Changes

File	Changed	Covered	%
src/foapy/core/_intervals_tuple.py	37	36	97.3%

Coverage Regressions

No coverage regressions found.

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Coverage Stats

Relevant Lines:	406
Covered Lines:	380
Line Coverage:	93.6%
Coverage Strength:	5.56 hits per line

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💛 - Coveralls

[github-actions]

Change	Before [58bd76e] <0.0.22>	After [4004d36]	Ratio	Benchmark (Parameter)
-	17.5±0.09μs	15.6±0.1μs	0.89	bench_alphabet.AlphabetSuite.time_alphabet(500, 'Normal')
-	19.8±0.1μs	16.0±0.09μs	0.81	bench_alphabet.AlphabetSuite.time_alphabet(500, 'Worst')
-	28.8±0.2μs	24.5±0.08μs	0.85	bench_alphabet.AlphabetSuite.time_alphabet(5000, 'Best')
-	156±1μs	119±0.7μs	0.76	bench_alphabet.AlphabetSuite.time_alphabet(5000, 'DNA')
-	264±0.4μs	128±1μs	0.48	bench_alphabet.AlphabetSuite.time_alphabet(5000, 'Normal')
-	345±0.8μs	133±1μs	0.38	bench_alphabet.AlphabetSuite.time_alphabet(5000, 'Worst')
-	4.69±0.1ms	3.72±0.02ms	0.79	bench_alphabet.AlphabetSuite.time_alphabet(500000, 'Best')
-	49.4±0.1μs	38.5±0.3μs	0.78	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5, 'Best')
-	64.2±2μs	44.8±1μs	0.7	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5, 'DNA')
-	50.1±2μs	39.3±1μs	0.78	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5, 'Normal')
-	52.7±0.6μs	40.5±0.6μs	0.77	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5, 'Worst')
-	50.7±0.7μs	38.7±0.1μs	0.76	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(50, 'Best')
-	65.9±1μs	46.3±0.3μs	0.7	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(50, 'DNA')
-	54.5±0.5μs	41.8±0.08μs	0.77	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(50, 'Normal')
-	54.7±0.4μs	42.1±0.1μs	0.77	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(50, 'Worst')
-	55.3±0.2μs	42.2±0.05μs	0.76	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(500, 'Best')
-	80.0±0.6μs	57.9±0.9μs	0.72	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(500, 'DNA')
-	74.1±0.7μs	57.3±0.3μs	0.77	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(500, 'Normal')
-	75.9±0.2μs	58.8±0.4μs	0.78	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(500, 'Worst')
-	92.9±0.5μs	72.1±0.6μs	0.78	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5000, 'Best')
-	390±4μs	235±5μs	0.6	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5000, 'Normal')
-	427±3μs	276±10μs	0.65	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(5000, 'Worst')
-	53.6±0.4μs	36.4±0.4μs	0.68	bench_ma_order.MaOrderSuite.time_order(5, 'Best')
-	60.3±2μs	40.3±0.09μs	0.67	bench_ma_order.MaOrderSuite.time_order(5, 'DNA')
-	55.4±1μs	36.3±1μs	0.66	bench_ma_order.MaOrderSuite.time_order(5, 'Normal')
-	61.3±0.5μs	39.7±0.2μs	0.65	bench_ma_order.MaOrderSuite.time_order(5, 'Worst')
-	55.0±0.2μs	36.6±0.07μs	0.67	bench_ma_order.MaOrderSuite.time_order(50, 'Best')
-	64.6±0.5μs	42.3±0.2μs	0.65	bench_ma_order.MaOrderSuite.time_order(50, 'DNA')
-	65.7±0.9μs	42.6±0.2μs	0.65	bench_ma_order.MaOrderSuite.time_order(50, 'Normal')
-	67.2±0.4μs	44.8±0.3μs	0.67	bench_ma_order.MaOrderSuite.time_order(50, 'Worst')
-	61.9±0.4μs	42.6±0.1μs	0.69	bench_ma_order.MaOrderSuite.time_order(500, 'Best')
-	83.8±0.7μs	58.4±0.4μs	0.7	bench_ma_order.MaOrderSuite.time_order(500, 'DNA')
-	140±0.6μs	111±3μs	0.79	bench_ma_order.MaOrderSuite.time_order(500, 'Normal')
-	264±2μs	231±1μs	0.87	bench_ma_order.MaOrderSuite.time_order(500, 'Worst')
-	120±0.3μs	92.4±0.2μs	0.77	bench_ma_order.MaOrderSuite.time_order(5000, 'Best')
-	288±5μs	221±3μs	0.77	bench_ma_order.MaOrderSuite.time_order(5000, 'DNA')
-	10.9±0.4ms	8.29±0.1ms	0.76	bench_ma_order.MaOrderSuite.time_order(5000, 'Normal')
-	39.1±0.3ms	27.0±1ms	0.69	bench_ma_order.MaOrderSuite.time_order(5000, 'Worst')
-	15.2±0.2μs	13.3±0.02μs	0.87	bench_order.OrderSuite.time_order(5, 'Best')
-	15.5±0.05μs	13.6±0.08μs	0.87	bench_order.OrderSuite.time_order(5, 'DNA')
-	15.3±0.07μs	13.3±0.02μs	0.87	bench_order.OrderSuite.time_order(5, 'Normal')
-	15.5±0.1μs	13.4±0.02μs	0.87	bench_order.OrderSuite.time_order(5, 'Worst')
-	16.0±0.2μs	13.8±0.07μs	0.87	bench_order.OrderSuite.time_order(50, 'Best')
-	17.1±0.04μs	14.7±0.03μs	0.86	bench_order.OrderSuite.time_order(50, 'DNA')
-	16.8±0.08μs	14.5±0.1μs	0.87	bench_order.OrderSuite.time_order(50, 'Normal')
-	16.9±0.3μs	14.6±0.04μs	0.86	bench_order.OrderSuite.time_order(50, 'Worst')
-	21.2±0.06μs	18.9±0.02μs	0.89	bench_order.OrderSuite.time_order(500, 'Best')
-	30.2±0.1μs	26.9±0.08μs	0.89	bench_order.OrderSuite.time_order(500, 'DNA')
-	31.5±0.1μs	27.4±0.3μs	0.87	bench_order.OrderSuite.time_order(500, 'Normal')
-	33.9±0.2μs	28.3±0.2μs	0.84	bench_order.OrderSuite.time_order(500, 'Worst')
-	208±3μs	159±1μs	0.77	bench_order.OrderSuite.time_order(5000, 'DNA')
-	309±1μs	176±1μs	0.57	bench_order.OrderSuite.time_order(5000, 'Normal')
-	397±0.8μs	206±3μs	0.52	bench_order.OrderSuite.time_order(5000, 'Worst')
-	1.63±0.07ms	1.46±0.01ms	0.9	bench_order.OrderSuite.time_order(50000, 'Best')
-	12.0±0.5ms	10.5±0.1ms	0.87	bench_order.OrderSuite.time_order(500000, 'Best')
Change	Before [58bd76e] <0.0.22>	After [4004d36]	Ratio	Benchmark (Parameter)
----------	------------------------------	---------------------	---------	------------------------------------------------------------------
+	50.9±0.9ms	56.5±1ms	1.11	bench_alphabet.AlphabetSuite.time_alphabet(500000, 'Normal')
+	70.7±0.8ms	79.3±0.5ms	1.12	bench_alphabet.AlphabetSuite.time_alphabet(500000, 'Worst')
+	4.72±0.2ms	5.21±0.1ms	1.1	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(50000, 'Normal')
+	4.71±0.02ms	5.38±0.1ms	1.14	bench_ma_alphabet.MaAlphabetSuite.time_alphabet(50000, 'Worst')
+	83.0±0.3ms	92.2±0.4ms	1.11	bench_order.OrderSuite.time_order(500000, 'Worst')