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1398681 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | """Configuration for a SPECTRA-RSI loop instance."""
from dataclasses import dataclass, field
@dataclass
class SpectraConfig:
# --- capability space ---
n_slices: int = 400 # n: capability slices
n_experts: int = 16 # E: experts / dictionary groups
rank_per_expert: int = 2 # r_e: retained response rank per expert
# --- probing (counterfactual dictionary) ---
probe_magnitude: float = 0.4 # h: signed probe step (within trust region)
probe_items: int = 400 # items per slice per probe evaluation
# --- sketching ---
m_coarse: int = 60 # stage-I sketch rows
m_focused: int = 90 # stage-II sketch rows
row_density: float = 0.10 # expected fraction of nonzero weights per row
items_per_row: int = 200 # item budget per sketch row (Neyman-allocated)
explore_fraction: float = 0.15 # measurement mass outside nominated groups
# --- recovery ---
lambda_l1: float = 2e-3
lambda_group: float = 8e-3
prior_gamma: float = 0.5 # w_e = (p_e + eps)^(-gamma)
prior_clip: tuple = (0.05, 0.95)
fista_iters: int = 600
bootstrap_reps: int = 60
# --- trust region / pilot ---
pilot_items: int = 120
trust_region_residual: float = 0.5 # relative pilot residual triggering fallback
# --- drift ---
drift_alpha: float = 0.05
drift_window: int = 50
# --- anytime-valid gate ---
alpha_risk: float = 0.05 # total false-acceptance budget over critical anchors
tau_margin: float = 0.02 # material-regression margin tau_j
max_anchor_items: int = 24000 # total sequential anchor budget
anchor_batch: int = 100
# --- misc ---
seed: int = 0
audit_dir: str = "audit_logs"
def __post_init__(self):
assert 0 < self.row_density <= 1
assert 0 <= self.explore_fraction < 1
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