# ============================================================
# 偏好时间衰减加权黄金测试（plan.md §8.3 / 矩阵 66 行剩余项）
# 覆盖：新样本主导偏好（衰减）、久远样本权重趋近 0、
#       舍入后当天信号近似整数、既有计数语义兼容。
# ============================================================
from __future__ import annotations

import datetime
from pathlib import Path

from server.knowledge.preferences import PreferenceStore


def _store(tmp_path: Path) -> PreferenceStore:
    return PreferenceStore(str(tmp_path / "pref.json"))


def _sample(strategy: str, *, days_ago: float, project_id: str | None = "p1") -> dict:
    at = (datetime.datetime.now() - datetime.timedelta(days=days_ago)).strftime("%Y-%m-%d %H:%M")
    return {"strategy": strategy, "source": "schedule.run", "actor": "u1",
            "projectId": project_id, "at": at}


def test_recent_signal_dominates_stale(tmp_path: Path):
    """时间衰减：30 天前的旧偏好不应压过今天的信号（偏好漂移）。"""
    ps = _store(tmp_path)
    ps.samples = [
        _sample("DELIVERY_FIRST", days_ago=30),
        _sample("CAPACITY_BALANCE", days_ago=0),
    ]
    scores = ps._decayed_scores("p1")
    assert scores["CAPACITY_BALANCE"] > scores["DELIVERY_FIRST"]
    assert scores["DELIVERY_FIRST"] < 0.5             # 30 天（>1 半衰期）显著衰减
    strategy, _ = ps.preferred_strategy(project_id="p1")
    assert strategy == "CAPACITY_BALANCE"


def test_same_source_two_recent_samples_half_life(tmp_path: Path):
    """半衰期：14 天前样本权重约为今天的 0.5。"""
    ps = _store(tmp_path)
    ps.samples = [
        _sample("A", days_ago=14),
        _sample("B", days_ago=0),
    ]
    scores = ps._decayed_scores("p1")
    ratio = scores["A"] / scores["B"]
    assert 0.45 <= ratio <= 0.55, f"半衰期比值应≈0.5，got {ratio}"


def test_today_scores_round_to_ints(tmp_path: Path):
    """当天样本（同源同策略×2）评分≈2（保留既有计数语义兼容）。"""
    ps = _store(tmp_path)
    ps.samples = [
        _sample("DELIVERY_FIRST", days_ago=0),
        _sample("DELIVERY_FIRST", days_ago=0),
    ]
    strategy, scores = ps.preferred_strategy(project_id="p1")
    assert strategy == "DELIVERY_FIRST"
    assert abs(scores["DELIVERY_FIRST"] - 2.0) < 0.01


def test_decay_preserves_apply_weight(tmp_path: Path):
    """来源权重叠加衰减：采用(2×decay) > 试排(1×decay) 同时间。"""
    ps = _store(tmp_path)
    ps.samples = [
        _sample("CAPACITY_BALANCE", days_ago=0),
        _sample("DELIVERY_FIRST", days_ago=0),
    ]
    # 同时间同来源权重应相等；改其中一个为采用验证权重
    ps.samples[0]["source"] = "scenario.apply"
    scores = ps._decayed_scores("p1")
    assert abs(scores["CAPACITY_BALANCE"] - 2 * scores["DELIVERY_FIRST"]) < 0.05