gh-423: Factorize jackknife_cls for parallelism

[ucapbba]

fixes: #423

The jackknife_cls method has been factorized into individual methods _compute_single_jk_alm _compute_single_jk_cls. For now the old jackknife_cls has been renamed to jackknife_cls_old should any additional comparison be required.

I have tested both methods are the same by comparing the cls for delete 1 and delete 2 (notebook available on demand). I have also implemented the individual methods in a fully parallel setup, giving significant performance improvement.

[codecov]

Codecov Report

❌ Patch coverage is 86.20690% with 8 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
heracles/dices/jackknife.py	86.20%	8 Missing ⚠️

Flag	Coverage Δ
py3.10	83.40% <86.20%> (+0.02%)	⬆️
py3.11	83.40% <86.20%> (+0.02%)	⬆️
py3.12	83.36% <86.20%> (+0.02%)	⬆️
py3.13	82.94% <86.20%> (+0.03%)	⬆️
py3.9	83.60% <85.96%> (+0.02%)	⬆️

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Files with missing lines	Coverage Δ
heracles/dices/jackknife.py	95.25% <86.20%> (-0.77%)	⬇️

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[ucapbba]

Hey @JaimeRZP, thanks for your suggestions. I have removed the old code and removed any updates to init.py. The ipynb should run without needing any changes.

[JaimeRZP]

@ucapbba All good and checked the notebook runs as usual

[ucapbba]

@JaimeRZP - that's great. Could you approve so I can merge? I guess Nicolas won't have time.