gloss.strategies — the three streams

Global stream

gloss.strategies.global_best.find_global_best(surrogate, space, n_points, excluded, direction, tolerance=0.0, n_random_samples=10000, n_top=10, kappa=2.0, diversity_radius=0.0, diversity_metric='euclidean')[source]

Find globally optimal points according to surrogate predictions.

Uses UCB acquisition (mu + kappa*sigma) when the surrogate supports uncertainty estimation, otherwise falls back to plain predicted value. kappa=0 disables UCB and uses pure predicted mean.

diversity_radius: minimum distance between selected points in the batch.

0.0 (default) disables diversity enforcement.

diversity_metric: ‘euclidean’ (default) or ‘jaccard’ for Tanimoto distance.

Local stream

gloss.strategies.local_best.find_local_best(surrogate, space, n_points, excluded, direction, tolerance=0.0, window_radius=None, n_random_samples=10000, distance_metric='euclidean', top_k=None)[source]

Find locally optimal points — better than all neighbors within a window.

top_k controls the O(K) truncation in discrete mode:
  • None (default): use max(500, n_points * 50) — production default

  • int >= 1: scan exactly top-k candidates by predicted mean

  • 0: scan all candidates (O(n) — no truncation; for ablation)

Has no effect in continuous mode.

Unexplored stream

gloss.strategies.unexplored.find_unexplored(surrogate, space, n_points, explored, excluded, direction, tolerance=0.0, unexplored_threshold=None, n_random_samples=10000, distance_metric='euclidean')[source]

Find points in unexplored regions with best predicted values.