Migrate all seeded functions from global random state to local RNG instances

[leotrs]

Summary

• Add seed parameter to previously unseeded stochastic functions: h_eigenvector_centrality, uniform_h_eigenvector_centrality, degree_assortativity, simulate_kuramoto, and random_edge_shuffle
• Migrate all seeded functions from global-state seeding (np.random.seed() / random.seed()) to local Generator instances (np.random.default_rng(seed))
• Eliminate all stdlib random usage from xgi source — everything now uses numpy's RNG exclusively
• Update the geometric() helper to accept a numpy rng parameter instead of relying on global state
• Fix various doctests and test expected values affected by the changed random streams
• Update tutorial notebook seed to match new random output

Motivation

The previous approach of calling np.random.seed(seed) / random.seed(seed) pollutes global state, isn't thread-safe, and means seeding one function can affect another called later. The Scientific Python best practices recommend np.random.default_rng(seed) with local Generator instances.

Files changed

Source (13 files)

• xgi/utils/utilities.py — geometric() now takes a numpy rng parameter
• xgi/algorithms/centrality.py — h_eigenvector_centrality, uniform_h_eigenvector_centrality
• xgi/algorithms/assortativity.py — degree_assortativity, _choose_degrees
• xgi/algorithms/connected.py — doctest update
• xgi/dynamics/synchronization.py — simulate_kuramoto
• xgi/core/hypergraph.py — random_edge_shuffle
• xgi/drawing/layout.py — random_layout + removed unnecessary random.seed() from spring layouts
• xgi/generators/random.py — all 5 generator functions
• xgi/generators/uniform.py — all 3 generator functions
• xgi/generators/simplicial_complexes.py — 4 functions
• xgi/generators/randomizing.py — shuffle_hyperedges

Tests (2 files)

• tests/dynamics/test_synchronization.py — updated expected values
• tests/generators/test_uniform.py — updated seed

Tutorials (1 file)

• tutorials/in_depth/In Depth 4 - Drawing multilayer-style.ipynb — updated seed

Test plan

• All 393 unit tests pass across ubuntu/macos/windows × Python 3.10–3.13
• All 112 doctests pass
• Tutorial tests pass
• Verified reproducibility: same seed → identical output
• Verified no global state pollution: seeded call doesn't affect subsequent unseeded calls
• Zero import random and zero legacy np.random.seed() calls remain in xgi source

🤖 Generated with Claude Code

[codecov]

Codecov Report

❌ Patch coverage is 90.27778% with 7 lines in your changes missing coverage. Please review.
✅ Project coverage is 93.67%. Comparing base (cc32ef6) to head (44283ed).

Files with missing lines	Patch %	Lines
xgi/generators/random.py	78.57%	3 Missing ⚠️
xgi/dynamics/synchronization.py	50.00%	2 Missing ⚠️
xgi/generators/randomizing.py	83.33%	1 Missing ⚠️
xgi/generators/simplicial_complexes.py	83.33%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #689      +/-   ##
==========================================
+ Coverage   93.59%   93.67%   +0.08%     
==========================================
  Files          66       66              
  Lines        5123     5110      -13     
==========================================
- Hits         4795     4787       -8     
+ Misses        328      323       -5     

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