perf: remove dead work and vectorize loops in modifier construction

[henryiii]

🤖 AI text below 🤖

Part of the code review in #2706.

Summary

Performance and dead-code cleanups in the modifier construction layer. These touch numerical code, so the focus is correctness-preserving refactors rather than the (small) speedups.

• shapesys: delete the never-read self.__shapesys_info tensor (a large (mods, samples, 3, bins) array built and immediately discarded; confirmed unused across src/ and tests/, including the name-mangled _shapesys_combined__shapesys_info).
• shapesys / staterror: hoist default_backend.astensor(self._shapesys_mask) (resp. self._staterror_mask) out of the per-systematic _reindex_access_field loop so the full mask is tensorized once instead of once per systematic.
• staterror.finalize: vectorize relerrs. The previous per-(sample, bin) Python comprehension with scalar indexing is replaced by default_backend array ops. A where-guarded denominator keeps bins with nomsall <= 0 at 0.0 and avoids emitting a divide-by-zero warning (pytest runs with filterwarnings=error). Verified numerically identical to the old logic, including the nomsall <= 0 edge case.
• shapefactor: vectorize the access-field population. The element-wise triple loop is replaced by a per-(s, t) clipped gather plus np.where over batch_access < len(selection), preserving the exact else 0 fallback semantics.
• normfactor.apply: hoist normfactors = self.param_viewer.get(pars) above the batch_size if/else (it was identical in both branches).
• shapesys.apply: remove a duplicated back-to-back tensorlib, _ = get_backend().
• paramview._precompute: build self.all_indices with dtype="int" to match self._all_indices (built with dtype="int"). Downstream int-casts in consumers are intentionally left in place to keep this PR contained. This change caused no backend test failures.

Test plan

Ran with both numpy and jax backends:

• pytest tests/test_modifiers.py tests/test_pdf.py tests/test_constraints.py tests/test_validation.py tests/test_backend_consistency.py — all pass (97 passed, 6 skipped).
• Broader fast suite pytest --ignore=tests/test_notebooks.py --ignore=tests/contrib --ignore=tests/benchmarks — 1114 passed. The only failures (7 tests in tests/test_infer.py, e.g. test_upper_limit*, test_toms748_scan) are a pre-existing RuntimeWarning: divide by zero in src/pyhf/infer/calculators.py:441, reproduced identically on clean main and unrelated to this PR.
• Direct numerical equivalence check of the staterror relerrs vectorization against the original scalar comprehension (including a nomsall <= 0 bin): exact match.
• prek -a (lint/format) clean.

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ℹ️ Review info

⚙️ Run configuration

Configuration used: Organization UI

Review profile: ASSERTIVE

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Run ID: 854877b4-4920-46ef-bb67-e641a5f85e5e

📥 Commits

Reviewing files that changed from the base of the PR and between 0e54a51 and 73aa8d0.

📒 Files selected for processing (5)

• src/pyhf/modifiers/normfactor.py
• src/pyhf/modifiers/shapefactor.py
• src/pyhf/modifiers/shapesys.py
• src/pyhf/modifiers/staterror.py
• src/pyhf/parameters/paramview.py

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 96.51%. Comparing base (0e54a51) to head (73aa8d0).
⚠️ Report is 2 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2715      +/-   ##
==========================================
- Coverage   98.28%   96.51%   -1.77%     
==========================================
  Files          65       65              
  Lines        4305     4309       +4     
  Branches      465      464       -1     
==========================================
- Hits         4231     4159      -72     
- Misses         46      118      +72     
- Partials       28       32       +4     

Flag	Coverage Δ
contrib	?
doctest	?
unittests-3.10	?
unittests-3.11	96.47% <100.00%> (+<0.01%)	⬆️
unittests-3.12	?
unittests-3.13	?
unittests-3.9	96.54% <100.00%> (+<0.01%)	⬆️

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