73 lines
2.8 KiB
Python
73 lines
2.8 KiB
Python
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# ============================================================
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# 偏好时间衰减加权黄金测试（plan.md §8.3 / 矩阵 66 行剩余项）
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# 覆盖：新样本主导偏好（衰减）、久远样本权重趋近 0、
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# 舍入后当天信号近似整数、既有计数语义兼容。
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# ============================================================
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from __future__ import annotations
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import datetime
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from pathlib import Path
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from server.knowledge.preferences import PreferenceStore
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def _store(tmp_path: Path) -> PreferenceStore:
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return PreferenceStore(str(tmp_path / "pref.json"))
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def _sample(strategy: str, *, days_ago: float, project_id: str | None = "p1") -> dict:
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at = (datetime.datetime.now() - datetime.timedelta(days=days_ago)).strftime("%Y-%m-%d %H:%M")
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return {"strategy": strategy, "source": "schedule.run", "actor": "u1",
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"projectId": project_id, "at": at}
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def test_recent_signal_dominates_stale(tmp_path: Path):
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"""时间衰减：30 天前的旧偏好不应压过今天的信号（偏好漂移）。"""
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ps = _store(tmp_path)
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ps.samples = [
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_sample("DELIVERY_FIRST", days_ago=30),
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_sample("CAPACITY_BALANCE", days_ago=0),
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]
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scores = ps._decayed_scores("p1")
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assert scores["CAPACITY_BALANCE"] > scores["DELIVERY_FIRST"]
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assert scores["DELIVERY_FIRST"] < 0.5 # 30 天（>1 半衰期）显著衰减
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strategy, _ = ps.preferred_strategy(project_id="p1")
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assert strategy == "CAPACITY_BALANCE"
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def test_same_source_two_recent_samples_half_life(tmp_path: Path):
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"""半衰期：14 天前样本权重约为今天的 0.5。"""
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ps = _store(tmp_path)
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ps.samples = [
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_sample("A", days_ago=14),
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_sample("B", days_ago=0),
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]
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scores = ps._decayed_scores("p1")
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ratio = scores["A"] / scores["B"]
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assert 0.45 <= ratio <= 0.55, f"半衰期比值应≈0.5，got {ratio}"
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def test_today_scores_round_to_ints(tmp_path: Path):
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"""当天样本（同源同策略×2）评分≈2（保留既有计数语义兼容）。"""
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ps = _store(tmp_path)
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ps.samples = [
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_sample("DELIVERY_FIRST", days_ago=0),
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_sample("DELIVERY_FIRST", days_ago=0),
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]
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strategy, scores = ps.preferred_strategy(project_id="p1")
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assert strategy == "DELIVERY_FIRST"
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assert abs(scores["DELIVERY_FIRST"] - 2.0) < 0.01
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def test_decay_preserves_apply_weight(tmp_path: Path):
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"""来源权重叠加衰减：采用(2×decay) > 试排(1×decay) 同时间。"""
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ps = _store(tmp_path)
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ps.samples = [
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_sample("CAPACITY_BALANCE", days_ago=0),
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_sample("DELIVERY_FIRST", days_ago=0),
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]
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# 同时间同来源权重应相等；改其中一个为采用验证权重
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ps.samples[0]["source"] = "scenario.apply"
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scores = ps._decayed_scores("p1")
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assert abs(scores["CAPACITY_BALANCE"] - 2 * scores["DELIVERY_FIRST"]) < 0.05
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