供应链反事实情景仿真 — 决策前的数字沙盘，支撑Palantir高风险Action验证

"""
供应链反事实情景仿真系统
功能：SCM建模 / 历史反事实 / 前瞻反事实 / 多方案对比 / Palantir决策验证
输入：供应链状态 + 干预方案
输出：各方案结果分布 + 最优建议 + 置信区间
"""
import numpy as np
from dataclasses import dataclass, field
from typing import Optional
import warnings
warnings.filterwarnings('ignore')


@dataclass
class ScenarioResult:
    """情景仿真结果——直接映射到Palantir Action验证报告"""
    scenario_name: str
    treatment_value: float
    expected_outcome: float
    outcome_std: float
    outcome_ci: tuple
    net_benefit: float           # 相对于基准情景的净收益
    confidence: float
    palantir_action: str
    recommendation: str


class SupplyChainCounterfactualEngine:
    """
    供应链反事实推理引擎
    基于结构因果模型（SCM）的数字孪生仿真
    """
    
    def __init__(self, sku_id: str, n_simulations: int = 1000):
        self.sku_id = sku_id
        self.n_sim = n_simulations
        
        # 供应链动力学参数（从历史数据估计）
        self.params = {
            'daily_demand_mean': 50,
            'daily_demand_std': 12,
            'bsr_demand_elasticity': -0.002,  # 每单位BSR变化对销量的影响
            'recovery_rate': 0.85,             # 断货后恢复速度
            'stockout_bsr_penalty': 15,        # 每天断货BSR下降
        }
    
    def _simulate_single(self, initial_stock: float, days: int,
                          inbound: float, inbound_delay: int,
                          current_bsr: float) -> dict:
        """单次蒙特卡洛仿真"""
        stock = initial_stock
        total_sales = 0
        total_lost_sales = 0
        bsr = current_bsr
        stockout_days = 0
        
        for day in range(days):
            # 入库（考虑延迟）
            if day == inbound_delay:
                stock += inbound