kcg-monitoring/prediction/models/result.py

105 lines
2.8 KiB
Python

from dataclasses import dataclass, field
from datetime import datetime, timezone
from typing import Optional
@dataclass
class AnalysisResult:
"""vessel_analysis_results 테이블 28컬럼 매핑."""
mmsi: str
timestamp: datetime
# 분류 결과
vessel_type: str = 'UNKNOWN'
confidence: float = 0.0
fishing_pct: float = 0.0
cluster_id: int = -1
season: str = 'UNKNOWN'
# ALGO 01: 위치
zone: str = 'EEZ_OR_BEYOND'
dist_to_baseline_nm: float = 999.0
# ALGO 02: 활동 상태
activity_state: str = 'UNKNOWN'
ucaf_score: float = 0.0
ucft_score: float = 0.0
# ALGO 03: 다크 베셀
is_dark: bool = False
gap_duration_min: int = 0
# ALGO 04: GPS 스푸핑
spoofing_score: float = 0.0
bd09_offset_m: float = 0.0
speed_jump_count: int = 0
# ALGO 05+06: 선단
cluster_size: int = 0
is_leader: bool = False
fleet_role: str = 'NOISE'
# ALGO 07: 위험도
risk_score: int = 0
risk_level: str = 'LOW'
# ALGO 08: 환적 의심
is_transship_suspect: bool = False
transship_pair_mmsi: str = ''
transship_duration_min: int = 0
# 특징 벡터
features: dict = field(default_factory=dict)
# 메타
analyzed_at: Optional[datetime] = None
def __post_init__(self):
if self.analyzed_at is None:
self.analyzed_at = datetime.now(timezone.utc)
def to_db_tuple(self) -> tuple:
import json
def _f(v: object) -> float:
"""numpy float → Python float 변환."""
return float(v) if v is not None else 0.0
def _i(v: object) -> int:
"""numpy int → Python int 변환."""
return int(v) if v is not None else 0
# features dict 내부 numpy 값도 변환
safe_features = {k: float(v) for k, v in self.features.items()} if self.features else {}
return (
str(self.mmsi),
self.timestamp,
str(self.vessel_type),
_f(self.confidence),
_f(self.fishing_pct),
_i(self.cluster_id),
str(self.season),
str(self.zone),
_f(self.dist_to_baseline_nm),
str(self.activity_state),
_f(self.ucaf_score),
_f(self.ucft_score),
bool(self.is_dark),
_i(self.gap_duration_min),
_f(self.spoofing_score),
_f(self.bd09_offset_m),
_i(self.speed_jump_count),
_i(self.cluster_size),
bool(self.is_leader),
str(self.fleet_role),
_i(self.risk_score),
str(self.risk_level),
bool(self.is_transship_suspect),
str(self.transship_pair_mmsi),
_i(self.transship_duration_min),
json.dumps(safe_features),
self.analyzed_at,
)