"""
质量门禁 — 执行前检查测试数据是否满足覆盖率和边界要求。

Phase 1 可用: 决策点覆盖、段落覆盖
Phase 2 启用: HINA 必须项、字段覆盖
"""

from __future__ import annotations

from typing import Any


def check(
    complete_tests: list,
    hina_result: dict,
    coverage: dict,
    decision_threshold: float = 0.90,
    paragraph_threshold: float = 1.0,
) -> dict:
    """质量门禁检查。

    Args:
        complete_tests: 完整的测试数据集
        hina_result: HINA 分类结果
        coverage: check_coverage() 输出的覆盖率数据
        decision_threshold: 决策点覆盖率阈值
        paragraph_threshold: 段落覆盖率阈值

    Returns:
        dict with: passed, score, issues
    """
    issues = {}

    branch_rate = coverage.get("branch_rate", 0.0)
    if branch_rate < decision_threshold:
        issues["decision_gaps"] = coverage.get("uncovered_decision_ids", [])

    paragraph_rate = coverage.get("paragraph_rate", 0.0)
    if paragraph_rate < paragraph_threshold:
        issues.setdefault("paragraph_gaps", []).append(
            f"段落覆盖率不足: {paragraph_rate:.0%}"
        )

    if not complete_tests:
        issues["no_data"] = True

    passed = len(issues) == 0
    score = _compute_score(coverage, hina_result)

    return {"passed": passed, "score": score, "issues": issues}


def _compute_score(coverage: dict, hina_result: dict) -> float:
    """质量评分公式（COBOL 版）。

    评分 = 覆盖质量 × 0.6 + 边界质量 × 0.4
    覆盖质量 = 段落覆盖率 × 0.5 + 分支覆盖率 × 0.5
    边界质量 = HINA 必须项覆盖率（Phase 2 后启用，默认 1.0）
    """
    paragraph_rate = coverage.get("paragraph_rate", 0.0)
    branch_rate = coverage.get("branch_rate", 0.0)

    coverage_quality = paragraph_rate * 0.5 + branch_rate * 0.5
    boundary_quality = 1.0

    return round(coverage_quality * 0.6 + boundary_quality * 0.4, 2)


def compute_quality_score(
    static_coverage: dict[str, Any],
    gcov_coverage: dict[str, Any] | None = None,
    confidence: float = 0.5,
) -> float:
    """双模式质量评分。

    模式 1 — gcov 未启用 (gcov_coverage is None):
        score = branch_rate × 0.5 + paragraph_rate × 0.5 + confidence × 0.4
        其中 confidence 作为加分项（最高 +0.4）

    模式 2 — gcov 启用:
        score = static_cov × 0.3 + gcov_cov × 0.4 + confidence × 0.3
        其中 static_cov = branch_rate × 0.5 + paragraph_rate × 0.5

    Args:
        static_coverage: 静态覆盖率数据
            {"branch_rate": float, "paragraph_rate": float, ...}
        gcov_coverage: gcov 动态覆盖率数据，None 表示未启用
            {"gcov_cov": float, ...} 或 None
        confidence: 确信度 (0.0 ~ 1.0)

    Returns:
        float: 质量评分 (0.0 ~ 1.0)
    """
    branch_rate = static_coverage.get("branch_rate", 0.0)
    paragraph_rate = static_coverage.get("paragraph_rate", 0.0)
    static_cov = branch_rate * 0.5 + paragraph_rate * 0.5

    if gcov_coverage is not None:
        # 模式 2: gcov 启用
        gcov_cov = gcov_coverage.get("gcov_cov", 0.0)
        score = static_cov * 0.3 + gcov_cov * 0.4 + confidence * 0.3
    else:
        # 模式 1: gcov 未启用 — confidence 作为加分
        score = branch_rate * 0.5 + paragraph_rate * 0.5 + confidence * 0.4

    return round(min(score, 1.0), 4)