"""Simulation result model.""" import json from datetime import datetime from sqlalchemy import Column, Integer, String, Text, DateTime, ForeignKey, Float from ..database import Base class SimulationResult(Base): """A single simulation result row (from scan_results.csv). P3-M1: Extended with fidelity level, confidence grade, constraint margins, surrogate prediction, and cross-validation per third-party review. """ __tablename__ = "simulation_results" id = Column(Integer, primary_key=True, index=True) plan_id = Column(Integer, ForeignKey("simulation_plans.id"), nullable=False, index=True) run_index = Column(Integer, default=0) status = Column(String(20), default="OK") # OK / FAILED / UNCERTAIN solve_time_s = Column(Float, default=0.0) params_json = Column(Text, default="{}") # JSON: parameter values metrics_json = Column(Text, default="{}") # JSON: metric values # Lossless Motor-CAD export archive: JSON list of # {section, name, value, unit} covering every exported EM+thermal field. raw_json = Column(Text, default="[]") error_message = Column(Text, default="") created_at = Column(DateTime, default=datetime.utcnow) # P3: Multi-fidelity and confidence fields fidelity_level = Column(String(30), default="L1_motorcad_emag", index=True) # L0-L4 confidence_grade = Column(String(2), default="C", index=True) # A/B/C/D model_template_version = Column(String(100), default="") # Motor-CAD template / PCB model version solver_settings_hash = Column(String(64), default="") # Hash of solver config constraint_margins_json = Column(Text, default="{}") # JSON: hard constraint margins surrogate_prediction_json = Column(Text, default="{}") # JSON: surrogate prediction + uncertainty cross_validation_json = Column(Text, default="{}") # JSON: Motor-CAD vs Maxwell/JMAG deviation convergence_status_json = Column(Text, default="{}") # JSON: six-type convergence status def get_params(self) -> dict: try: return json.loads(self.params_json) if self.params_json else {} except (json.JSONDecodeError, TypeError): return {} def set_params(self, data: dict) -> None: self.params_json = json.dumps(data, ensure_ascii=False) def get_metrics(self) -> dict: try: return json.loads(self.metrics_json) if self.metrics_json else {} except (json.JSONDecodeError, TypeError): return {} def set_metrics(self, data: dict) -> None: self.metrics_json = json.dumps(data, ensure_ascii=False) def get_raw(self) -> list: """Full-fidelity export rows: [{section, name, value, unit}, ...].""" try: data = json.loads(self.raw_json) if self.raw_json else [] return data if isinstance(data, list) else [] except (json.JSONDecodeError, TypeError): return [] def set_raw(self, data: list) -> None: self.raw_json = json.dumps(data or [], ensure_ascii=False) # P3: Helper methods for extended fields def get_constraint_margins(self) -> dict: try: return json.loads(self.constraint_margins_json) if self.constraint_margins_json else {} except (json.JSONDecodeError, TypeError): return {} def set_constraint_margins(self, data: dict) -> None: self.constraint_margins_json = json.dumps(data, ensure_ascii=False) def get_surrogate_prediction(self) -> dict: try: return json.loads(self.surrogate_prediction_json) if self.surrogate_prediction_json else {} except (json.JSONDecodeError, TypeError): return {} def set_surrogate_prediction(self, data: dict) -> None: self.surrogate_prediction_json = json.dumps(data, ensure_ascii=False) def get_cross_validation(self) -> dict: try: return json.loads(self.cross_validation_json) if self.cross_validation_json else {} except (json.JSONDecodeError, TypeError): return {} def set_cross_validation(self, data: dict) -> None: self.cross_validation_json = json.dumps(data, ensure_ascii=False) def get_convergence_status(self) -> dict: try: return json.loads(self.convergence_status_json) if self.convergence_status_json else {} except (json.JSONDecodeError, TypeError): return {} def set_convergence_status(self, data: dict) -> None: self.convergence_status_json = json.dumps(data, ensure_ascii=False)