from typing import Optional, Tuple

import pandas as pd
from algorithms.location import classify_zone
from algorithms.fishing_pattern import detect_fishing_segments, detect_trawl_uturn
from algorithms.dark_vessel import detect_ais_gaps
from algorithms.spoofing import detect_teleportation


def compute_vessel_risk_score(
    mmsi: str,
    df_vessel: pd.DataFrame,
    zone_info: Optional[dict] = None,
    is_permitted: Optional[bool] = None,
) -> Tuple[int, str]:
    """선박별 종합 위반 위험도 (0~100점).

    Returns: (risk_score, risk_level)
    """
    if len(df_vessel) == 0:
        return 0, 'LOW'

    score = 0

    # 1. 위치 기반 (최대 40점)
    if zone_info is None:
        last = df_vessel.iloc[-1]
        zone_info = classify_zone(last['lat'], last['lon'])

    zone = zone_info.get('zone', '')
    if zone == 'TERRITORIAL_SEA':
        score += 40
    elif zone == 'CONTIGUOUS_ZONE':
        score += 10

    # 2. 조업 행위 (최대 30점)
    segs = detect_fishing_segments(df_vessel)
    ts_fishing = [s for s in segs if s.get('in_territorial_sea')]
    if ts_fishing:
        score += 20
    elif segs:
        score += 5

    uturn = detect_trawl_uturn(df_vessel)
    if uturn.get('trawl_suspected'):
        score += 10

    # 3. AIS 조작 (최대 35점)
    teleports = detect_teleportation(df_vessel)
    if teleports:
        score += 20

    gaps = detect_ais_gaps(df_vessel)
    critical_gaps = [g for g in gaps if g['gap_min'] >= 60]
    if critical_gaps:
        score += 15
    elif gaps:
        score += 5

    # 4. 허가 이력 (최대 20점)
    if is_permitted is not None and not is_permitted:
        score += 20

    score = min(score, 100)

    if score >= 70:
        level = 'CRITICAL'
    elif score >= 50:
        level = 'HIGH'
    elif score >= 30:
        level = 'MEDIUM'
    else:
        level = 'LOW'

    return score, level