Add axis support to alphabet and order

[goruha]

Summary

• add stable slice-as-element factorization along an explicit axis for core alphabet and order
• keep order one-dimensional while preserving alphabet rank and axis placement for numpy.take reconstruction
• extend partials alphabet and order with whole-slice gap handling and mixed-mask validation
• add multidimensional tests, documentation, ASV benchmarks, and the completed OpenSpec change
• include the earlier archive of the completed refactor-congeneric-characteristics OpenSpec change

Verification

• 510 pytest tests passed
• Black, isort, and flake8 passed
• MkDocs build succeeded
• ASV benchmark validation and smoke tests passed
• OpenSpec strict validation passed

[coveralls]

Coverage Report for CI Build 34821860873

Coverage increased (+0.8%) to 96.748%

Details

• Coverage increased (+0.8%) from the base build.
• Patch coverage: 6 uncovered changes across 4 files (424 of 430 lines covered, 98.6%).
• No coverage regressions found.

Uncovered Changes

File	Changed	Covered	%
src/foapy/core/_factorize.py	101	98	97.03%
src/foapy/core/_axis_transform.py	41	40	97.56%
src/foapy/core/_intervals_chain_validation.py	19	18	94.74%
src/foapy/core/_intervals_distribution.py	35	34	97.14%
Total (13 files)	430	424	98.6%

Coverage Regressions

No coverage regressions found.

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Coverage Stats

Relevant Lines:	984
Covered Lines:	952
Line Coverage:	96.75%
Coverage Strength:	2.9 hits per line

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💛 - Coveralls

[github-actions]

Change	Before [ee4b10a]	After [12a24c5]	Ratio	Benchmark (Parameter)
-	15.7±0.6μs	13.7±0.2μs	0.87	bench_congenerics_order.CongenericsOrderSuite.time_order(10000, 'DNA')
-	48.0±0.6μs	34.9±0.8μs	0.73	bench_congenerics_sequences.CongenericsSequencesSuite.time_sequences(100, 'Best')
-	66.5±3μs	46.0±1μs	0.69	bench_congenerics_sequences.CongenericsSequencesSuite.time_sequences(1000, 'Best')
-	198±4μs	155±8μs	0.79	bench_congenerics_sequences.CongenericsSequencesSuite.time_sequences(1000, 'Normal')
-	510±8μs	458±6μs	0.9	bench_congenerics_sequences.CongenericsSequencesSuite.time_sequences(1000, 'Worst')
-	226±2μs	136±2μs	0.6	bench_congenerics_sequences.CongenericsSequencesSuite.time_sequences(10000, 'Best')
-	38.2±0.7μs	33.2±0.3μs	0.87	bench_intervals.IntervalsSuite.time_intervals(500, 'Worst', 1, 2)
-	2.80±0.04ms	2.49±0.04ms	0.89	bench_intervals.IntervalsSuite.time_intervals(50000, 'DNA', 2, 1)
-	97.7±30μs	70.5±0.6μs	0.72	bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Best', 2, 1)
-	106±30μs	70.4±0.4μs	0.67	bench_intervals_chain.IntervalsChainSuite.time_intervals_chain(10000, 'Best', 2, 2)
-	62.8M	51.8M	0.82	bench_order.OrderSuite.peakmem_order(500000, 'Best')
-	66.3M	58.2M	0.88	bench_order.OrderSuite.peakmem_order(500000, 'Normal')
-	73.3M	66.3M	0.9	bench_order.OrderSuite.peakmem_order(500000, 'Worst')
-	11.8±0.2μs	3.93±0.09μs	0.33	bench_order.OrderSuite.time_order(5, 'Best')
-	12.9±0.1μs	11.4±0.2μs	0.89	bench_order.OrderSuite.time_order(5, 'DNA')
-	12.5±0.4μs	4.17±0.2μs	0.33	bench_order.OrderSuite.time_order(5, 'Normal')
-	12.5±0.2μs	4.00±0.1μs	0.32	bench_order.OrderSuite.time_order(50, 'Best')
-	15.1±0.5μs	12.7±0.5μs	0.85	bench_order.OrderSuite.time_order(50, 'Normal')
-	14.6±0.7μs	12.5±0.2μs	0.86	bench_order.OrderSuite.time_order(50, 'Worst')
-	17.8±0.3μs	5.48±0.06μs	0.31	bench_order.OrderSuite.time_order(500, 'Best')
-	40.7±2μs	24.0±0.8μs	0.59	bench_order.OrderSuite.time_order(500, 'Normal')
-	44.2±1μs	23.4±0.4μs	0.53	bench_order.OrderSuite.time_order(500, 'Worst')
-	65.1±0.4μs	19.7±0.3μs	0.3	bench_order.OrderSuite.time_order(5000, 'Best')
-	401±4μs	141±3μs	0.35	bench_order.OrderSuite.time_order(5000, 'Normal')
-	408±10μs	145±2μs	0.35	bench_order.OrderSuite.time_order(5000, 'Worst')
-	1.13±0.03ms	296±40μs	0.26	bench_order.OrderSuite.time_order(50000, 'Best')
-	5.26±0.1ms	1.67±0.05ms	0.32	bench_order.OrderSuite.time_order(50000, 'Normal')
-	6.30±0.03ms	2.19±0.03ms	0.35	bench_order.OrderSuite.time_order(50000, 'Worst')
-	10.6±0.3ms	2.95±0.3ms	0.28	bench_order.OrderSuite.time_order(500000, 'Best')
-	29.8±0.1ms	26.7±0.5ms	0.9	bench_order.OrderSuite.time_order(500000, 'DNA')
-	70.7±0.4ms	22.7±0.3ms	0.32	bench_order.OrderSuite.time_order(500000, 'Normal')
-	84.8±1ms	31.6±0.2ms	0.37	bench_order.OrderSuite.time_order(500000, 'Worst')
-	104M	79.8M	0.77	bench_partials_intervals_chain.PartialsIntervalsChainSuite.peakmem_intervals_chain(1000000, 'Dense', 1, 1)
-	104M	79.9M	0.77	bench_partials_intervals_chain.PartialsIntervalsChainSuite.peakmem_intervals_chain(1000000, 'Dense', 1, 2)
-	112M	79.7M	0.71	bench_partials_intervals_chain.PartialsIntervalsChainSuite.peakmem_intervals_chain(1000000, 'Dense', 2, 1)
-	112M	79.8M	0.71	bench_partials_intervals_chain.PartialsIntervalsChainSuite.peakmem_intervals_chain(1000000, 'Dense', 2, 2)
-	24.0±0.2μs	13.8±0.3μs	0.58	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(100, 'Dense', 1, 1)
-	24.7±1μs	14.7±0.2μs	0.59	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(100, 'Dense', 1, 2)
-	26.0±0.3μs	15.1±0.4μs	0.58	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(100, 'Dense', 2, 1)
-	27.3±0.7μs	15.5±0.4μs	0.57	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(100, 'Dense', 2, 2)
-	123±3μs	73.6±1μs	0.6	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(10000, 'Dense', 1, 1)
-	124±3μs	76.5±2μs	0.62	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(10000, 'Dense', 1, 2)
-	275±9μs	80.6±0.2μs	0.29	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(10000, 'Dense', 2, 1)
-	293±7μs	82.4±0.9μs	0.28	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(10000, 'Dense', 2, 2)
-	21.8±0.8ms	12.2±0.8ms	0.56	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(1000000, 'Dense', 1, 1)
-	22.2±0.8ms	13.4±0.4ms	0.6	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(1000000, 'Dense', 1, 2)
-	26.8±1ms	14.7±1ms	0.55	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(1000000, 'Dense', 2, 1)
-	27.5±2ms	16.2±1ms	0.59	bench_partials_intervals_chain.PartialsIntervalsChainSuite.time_intervals_chain(1000000, 'Dense', 2, 2)
-	64.3M	51.7M	0.8	bench_partials_order.PartialsOrderSuite.peakmem_order(500000, 'Unmasked')
-	34.2±0.4μs	22.7±0.7μs	0.66	bench_partials_order.PartialsOrderSuite.time_order(5, 'PartialNormal')
-	28.5±1μs	18.2±0.3μs	0.64	bench_partials_order.PartialsOrderSuite.time_order(5, 'Unmasked')
-	29.2±0.9μs	17.6±0.6μs	0.6	bench_partials_order.PartialsOrderSuite.time_order(50, 'Unmasked')
-	56.1±3μs	42.8±1μs	0.76	bench_partials_order.PartialsOrderSuite.time_order(500, 'PartialNormal')
-	35.1±1μs	20.6±0.4μs	0.59	bench_partials_order.PartialsOrderSuite.time_order(500, 'Unmasked')
-	268±7μs	132±3μs	0.49	bench_partials_order.PartialsOrderSuite.time_order(5000, 'PartialNormal')
-	89.8±0.7μs	40.0±0.5μs	0.44	bench_partials_order.PartialsOrderSuite.time_order(5000, 'Unmasked')
-	2.92±0.1ms	1.13±0.06ms	0.39	bench_partials_order.PartialsOrderSuite.time_order(50000, 'PartialNormal')
-	1.26±0.02ms	442±40μs	0.35	bench_partials_order.PartialsOrderSuite.time_order(50000, 'Unmasked')
-	39.4±2ms	14.1±1ms	0.36	bench_partials_order.PartialsOrderSuite.time_order(500000, 'PartialNormal')
-	11.5±1ms	3.88±0.1ms	0.34	bench_partials_order.PartialsOrderSuite.time_order(500000, 'Unmasked')
-	163±1μs	108±2μs	0.66	bench_pipeline_full.PipelineFullSuite.time_pipeline_full(10000, 'Best')