""" orgstate.core — the pure analytical core of OrgState Engine. This package is intentionally dependency-free (stdlib only) and I/O-free. It contains the canonical data model and the deterministic signal/drift math. Everything else (storage, API, connectors, verticals, delivery) builds on top. Stage 0 migration: events, state, ontology, signals, drift, decisions were moved here verbatim from legacy/orgstate_engine/ — they had zero cross-imports, so no import rewrites were needed. See ../MIGRATION_MAP.md. """ from .calibration import ( Calibration, MetricCalibration, calibrate, robust_scale, ) from .config import ( HIGHER_IS_WORSE, LOWER_IS_WORSE, EntityTypeConfig, MetricConfig, VerticalConfig, load_yaml_config, ) from .decisions import DecisionItem, recommendation_for_issue from .drift import ( DEFAULT_DRIFT_WEIGHTS, DEFAULT_SEVERITY_THRESHOLDS, DriftIssue, drift_score, severity_from_score, ) from .events import CanonicalEvent from .ontology import ENTITY_TYPES, Entity from .pipeline import ( Observation, PipelineResult, calibrate_from_observations, collect_history, run_pipeline, ) from .signals import ( anomaly_xi, change_delta, coefficient_of_variation, coherence_kappa, health_omega, latency_gamma, safe_mean, safe_std, stability_psi, weighted_geometric_mean, ) from .state import EntityState __all__ = [ # data model "CanonicalEvent", "EntityState", "Entity", "ENTITY_TYPES", # signals "safe_mean", "safe_std", "coefficient_of_variation", "stability_psi", "anomaly_xi", "change_delta", "latency_gamma", "coherence_kappa", "weighted_geometric_mean", "health_omega", # drift / decisions "DriftIssue", "drift_score", "severity_from_score", "DEFAULT_DRIFT_WEIGHTS", "DEFAULT_SEVERITY_THRESHOLDS", "DecisionItem", "recommendation_for_issue", # config (Stage 1) "MetricConfig", "EntityTypeConfig", "VerticalConfig", "load_yaml_config", "HIGHER_IS_WORSE", "LOWER_IS_WORSE", # calibration (Stage 1) "MetricCalibration", "Calibration", "calibrate", "robust_scale", # pipeline (Stage 1) "Observation", "PipelineResult", "run_pipeline", "calibrate_from_observations", "collect_history", ]