在途库存追踪与全链路可视化 — 海运/空运实物流信息流双轨监控

"""
在途库存追踪与全链路可视化系统
功能：ETA预测 + 异常检测 + 虚拟库存计算 + 全链路状态机
"""
import numpy as np
import pandas as pd
from dataclasses import dataclass, field
from typing import List, Dict, Optional, Tuple
from datetime import datetime, timedelta
from enum import Enum
import warnings
warnings.filterwarnings('ignore')


class TransitStatus(Enum):
    """在途状态"""
    FACTORY_PICKUP = "工厂提货"
    DOMESTIC_CUSTOMS = "国内清关"
    VESSEL_LOADED = "已装船"
    IN_OCEAN = "海运中"
    DESTINATION_ARRIVED = "目的港到达"
    CUSTOMS_CLEARANCE = "目的港清关"
    WAREHOUSE_RECEIVED = "已入仓"
    DELAYED = "延误"
    EXCEPTION = "异常"


@dataclass
class TransitBatch:
    """在途批次"""
    batch_id: str
    bl_number: str              # 提单号
    container_id: str           # 集装箱号
    carrier: str                # 船公司
    origin_port: str            # 出发港
    dest_port: str              # 目的港
    departure_date: datetime    # 出发日期
    planned_eta: datetime       # 计划到港日期
    skus: Dict[str, int]        # {sku_id: qty}
    unit_costs: Dict[str, float] # {sku_id: unit_cost}
    current_status: TransitStatus = TransitStatus.IN_OCEAN
    last_position_update: Optional[datetime] = None
    current_location: str = ""
    actual_arrival: Optional[datetime] = None


class ETAPredictor:
    """ETA预测模型（简化版GBT）"""
    
    # 航线历史均值和标准差（天）
    ROUTE_STATS = {
        ('YANTIAN', 'LOS_ANGELES'): (32, 3.5),
        ('SHANGHAI', 'LOS_ANGELES'): (28, 4.0),
        ('GUANGZHOU', 'LONG_BEACH'): (30, 3.8),
        ('NINGBO', 'SEATTLE'): (25, 3.2),
        ('SHENZHEN', 'NEW_YORK'): (38, 5.0),
        ('QINGDAO', 'LOS_ANGELES'): (28, 4.2),
    }
    
    # 港口拥堵指数影响（额外天数）