walk

Graph random-walk primitives:

• Unbiased random walks
• Node2Vec / Node2Vec-style biased walks (including precomputed alias tables)
• PageRank and personalized PageRank

Determinism

Most APIs take a WalkConfig { seed, .. }. For fixed seed and identical inputs, walk generation is intended to be reproducible.

Graph interfaces

• Graph: returns owned neighbor lists (Vec<usize>) per query (simple but allocates per step)
• GraphRef: returns borrowed neighbor slices (&[usize]) per query (faster for walking)

Sampling integration

This crate uses kuji for reservoir sampling via sample_start_nodes_reservoir, which is useful when node_count is too large to materialize 0..node_count just to choose a subset of starts.

Examples

• cargo run --example ppr_hard_pool: generate a seeded SBM graph, compute PPR from an anchor, then sample a stochastic top-(k) candidate pool using Gumbel-top-k on (\log(\mathrm{PPR})).
  • uses testdata/karate_club.edgelist by default (small real graph)
  • set WALK_DATASET=lesmis or WALK_DATASET=florentine for other bundled graphs
  • set WALK_EDGELIST=/path/to/edges.txt to run on your own graph

References (starting points)

• Page et al. (1999): PageRank.
• Grover & Leskovec (2016): Node2Vec.
• Walker (1974) / Vose (1991): alias method for O(1) categorical sampling.