Draw an independent proposal per walker for full-covariance GaussianMove - #571
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…sianMove rng.multivariate_normal was called without a size argument when a full covariance matrix was supplied, so a single random vector was generated and broadcast to every walker's position. This made all proposed steps identical within an iteration, breaking the ensemble walkers' independence for GaussianMove(cov) with a 2D cov matrix. Signed-off-by: Mike German <mike@stepsventures.com>
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When
GaussianMoveis built with a full (2D) covariance matrix,rng.multivariate_normal(...)was called withoutsize=, so it drew a single random vector that got broadcast identically onto every walker's coordinates. That destroys inter-walker independence, which ensemble MCMC relies on. The fix addssize=x0.shape[0]so each walker gets its own draw.Reproduced on current main: all 8 walkers received bit-identical proposal deltas. Existing integration tests missed it because they only check aggregate marginal statistics, not per-walker independence. Added
test_full_covariance_proposal_is_independent_per_walker, which fails before the fix and passes after. Full suite 129/129.