"""
报告生成模块

将因果分析各阶段结果整合为统一的 JSON 报告。
"""

import json
from typing import Any, Dict, List, Optional


def generate_report(
    query_interpretation: Dict[str, str],
    causal_graph: Dict[str, Any],
    identification: Dict[str, Any],
    estimation: Dict[str, Any],
    extra_warnings: Optional[List[Dict[str, str]]] = None,
) -> Dict[str, Any]:
    """生成标准化 JSON 报告"""
    warnings = list(extra_warnings) if extra_warnings else []
    warnings.extend(estimation.get("warnings", []))

    warnings.append(
        {
            "type": "unobserved_confounding",
            "message": "可能存在未观测混杂，建议进行敏感性分析。",
        }
    )

    report = {
        "query_interpretation": query_interpretation,
        "causal_graph": causal_graph,
        "identification": {
            "strategy": identification.get("strategy", "Backdoor Adjustment"),
            "adjustment_set": identification.get("adjustment_set", []),
            "reasoning": identification.get("reasoning", ""),
        },
        "estimation": {
            "ATE_Outcome_Regression": estimation.get("ATE_Outcome_Regression"),
            "ATE_IPW": estimation.get("ATE_IPW"),
            "95%_CI": estimation.get("95%_CI"),
            "interpretation": estimation.get("interpretation", ""),
        },
        "diagnostics": {
            "balance_check": estimation.get("balance_check", {}),
            "overlap_assumption": estimation.get("overlap_assumption", "未知"),
            "robustness": estimation.get("robustness", "未知"),
        },
        "warnings": warnings,
    }
    return report


def print_report(report: Dict[str, Any]) -> None:
    """美观地打印报告"""
    print("\n" + "=" * 60)
    print("因果推断分析报告")
    print("=" * 60)
    print(json.dumps(report, indent=2, ensure_ascii=False))
    print("=" * 60)