"""#1743 批量变体独立选片纯核心测试（packages/domain/variant_plan_selector.py）。 覆盖： - 固定种子下 N 次独立选片：素材组合/片段顺序/起点显著不同（降重核心） - 批次内同素材区间重叠 >20% 触发避让重选 - 异常输入：空源片段/空素材池/时长全 0 → ValueError（严禁退回同源） - 非 main 片段（intro/outro/overlay）保留源骨架素材，仅重算起点 - 跨变体 batch_segments 就地累加（串行选片天然避让） - 文案/转场/速度等骨架字段透传 """ from __future__ import annotations import random import sys from pathlib import Path from unittest.mock import patch import pytest REPO_ROOT = Path(__file__).resolve().parents[2] for sub in ("packages", ""): p = str(REPO_ROOT / sub) if sub else str(REPO_ROOT) if p not in sys.path: sys.path.insert(0, p) from packages.domain import variant_plan_selector as vps # noqa: E402 from packages.domain.variant_plan_selector import ( # noqa: E402 BATCH_CLIP_OVERLAP_LIMIT, _clip_overlap_ratio, reselect_clips_for_variant, ) def _source_clips(assets=("a1", "a2", "a3"), dur=5.0, with_non_main=False): """构造源片段骨架：main 片段若干，可选 intro/outro 固定角色片段。""" clips = [] order = 0 if with_non_main: clips.append( { "order": order, "asset_id": "intro_asset", "start_time": 0.0, "duration": 3.0, "clip_type": "intro", "playback_speed": 1.0, "transition_effect": "fade", "transition_duration": 0.5, "text_content": "片头", "config": {"role": "intro"}, } ) order += 1 for i, aid in enumerate(assets): clips.append( { "order": order, "asset_id": aid, "start_time": float(i * 10), "duration": dur, "clip_type": "main", "playback_speed": 1.2, "transition_effect": "cut", "transition_duration": 0.0, "text_content": f"文案{i}", "config": {}, } ) order += 1 if with_non_main: clips.append( { "order": order, "asset_id": "outro_asset", "start_time": 0.0, "duration": 2.0, "clip_type": "outro", "playback_speed": 1.0, "transition_effect": "fade", "transition_duration": 0.5, "text_content": "片尾", "config": {"role": "outro"}, } ) return clips def _durations(asset_ids, total=120.0, extra=None): d = {a: total for a in asset_ids} if extra: d.update(extra) return d class TestReselectClipsValidation: def test_empty_source_clips_raises(self): with pytest.raises(ValueError, match="源 plan 无片段"): reselect_clips_for_variant( [], ["a1"], asset_durations={"a1": 60.0}, rng=random.Random(1), ) def test_empty_asset_pool_raises(self): with pytest.raises(ValueError, match="素材池为空"): reselect_clips_for_variant( _source_clips(), [], asset_durations={}, rng=random.Random(1), ) def test_all_zero_duration_raises(self): with pytest.raises(ValueError, match="时长全部未知"): reselect_clips_for_variant( _source_clips(), ["a1", "a2"], asset_durations={"a1": 0.0, "a2": 0.0}, rng=random.Random(1), ) class TestReselectClipsDifferentiation: def test_three_variants_differ_in_assets_order_and_starts(self): """核心验收：固定种子连续 3 次独立选片，素材组合/顺序/起点显著不同。""" source = _source_clips(assets=("a1", "a2", "a3", "a4")) pool = ["a1", "a2", "a3", "a4", "a5", "a6"] durations = _durations(pool, total=300.0) batch_segments: dict = {} variants = [] for seed in range(3): clips = reselect_clips_for_variant( source, pool, asset_durations=durations, batch_segments=batch_segments, # 串行调用：上一变体区间参与避让 rng=random.Random(100 + seed), ) variants.append(clips) main_sequences = [] for clips in variants: main = [c for c in clips if c["clip_type"] == "main"] main_sequences.append([(c["asset_id"], round(c["start_time"], 2)) for c in main]) # 1) 每个变体片段数与源骨架一致 for clips in variants: main_clips = [c for c in clips if c["clip_type"] == "main"] assert len(main_clips) == 4 # 2) 三个变体的素材序列不全相同（素材洗牌 + main 顺序洗牌生效） seq_sets = {tuple(a for a, _ in seq) for seq in main_sequences} assert len(seq_sets) >= 2, f"变体素材序列应存在差异，实际全部相同: {seq_sets}" # 3) 起点组合不全相同（起点重选生效） start_sets = {tuple(s for _, s in seq) for seq in main_sequences} assert len(start_sets) >= 2, f"变体起点组合应存在差异，实际全部相同: {start_sets}" # 4) batch_segments 跨变体累加（串行避让链路存在） total_segments = sum(len(v) for v in batch_segments.values()) assert total_segments >= 12, f"3 变体 × 4 main 片段应累加 >=12 区间，实际 {total_segments}" def test_skeleton_fields_preserved(self): """文案/转场/速度等骨架字段随片段透传（只换素材与起点）。""" source = _source_clips(assets=("a1", "a2"), with_non_main=True) pool = ["a1", "a2", "a3"] durations = _durations(pool, total=120.0, extra={"intro_asset": 30.0, "outro_asset": 30.0}) clips = reselect_clips_for_variant( source, pool, asset_durations=durations, rng=random.Random(7), ) by_order = {c["order"]: c for c in clips} # intro/outro 骨架字段保留 intro = next(c for c in clips if c["clip_type"] == "intro") outro = next(c for c in clips if c["clip_type"] == "outro") assert intro["asset_id"] == "intro_asset" assert intro["text_content"] == "片头" assert intro["transition_effect"] == "fade" assert intro["transition_duration"] == 0.5 assert outro["asset_id"] == "outro_asset" assert outro["text_content"] == "片尾" # main 片段文案/速度随骨架 order 保留 for c in clips: if c["clip_type"] == "main": assert c["playback_speed"] == 1.2 assert c["text_content"].startswith("文案") class TestBatchOverlapAvoidance: def test_overlap_ratio_calculation(self): segs = {"a1": [(10.0, 20.0)]} # 已占 10s 区间 # 新区间 [10,20) 完全重叠 → 1.0 assert _clip_overlap_ratio("a1", 10.0, 10.0, segs) == pytest.approx(1.0) # 新区间 [20,30) 零重叠 → 0.0 assert _clip_overlap_ratio("a1", 20.0, 10.0, segs) == pytest.approx(0.0) # 新区间 [15,25) 重叠 5s / 10s → 0.5 assert _clip_overlap_ratio("a1", 15.0, 10.0, segs) == pytest.approx(0.5) # 空 asset / 零时长 → 0 assert _clip_overlap_ratio("", 0.0, 10.0, segs) == 0.0 assert _clip_overlap_ratio("a1", 10.0, 0.0, segs) == 0.0 def test_over_limit_triggers_reselect_to_non_overlapping(self): """批次已占满素材前段时，避让重选应把起点挪到重叠 ≤20% 的位置。""" source = _source_clips(assets=("a1",), dur=10.0) durations = {"a1": 120.0} # 批次已选区间：a1 [0, 100) 几乎占满前段 batch_segments = {"a1": [(0.0, 100.0)]} # _resolve_start_time 第一次返回高重叠起点（2.0），之后 rng 抖动应找到低重叠位置 call_count = {"n": 0} def fake_resolve(asset_id, clip_duration, asset_durations, used_segments, scene_points=None, on_exhausted=None): call_count["n"] += 1 return 2.0 if call_count["n"] == 1 else None # 后续回退 rng.uniform with patch.object(vps, "_resolve_start_time", side_effect=fake_resolve): # rng.uniform 返回 105.0（与 [0,100) 零重叠）；rng 是 random.Random 实例， # 需 patch 类方法 uniform 才能生效 with patch.object(random.Random, "uniform", return_value=105.0): clips = reselect_clips_for_variant( source, ["a1"], asset_durations=durations, batch_segments=batch_segments, rng=random.Random(3), ) main = [c for c in clips if c["clip_type"] == "main"] assert len(main) == 1 start = main[0]["start_time"] ratio = _clip_overlap_ratio("a1", start, 10.0, {"a1": [(0.0, 100.0)]}) assert ratio <= BATCH_CLIP_OVERLAP_LIMIT, f"避让后重叠应 ≤20%，实际 {ratio:.2%}" # #1749：选片改 0.25s 窗口扫描找最优错开起点（不再依赖 rng.uniform 单点）， # 落点只需满足语义：与已用区间 [0,100) 不完全重叠且重叠 ≤20% assert start > 0.0 # start+10 区间与 [0,100) 的重叠段（若有）≤ 2s overlap = max(0.0, min(start + 10.0, 100.0) - max(start, 0.0)) assert overlap <= 2.0 + 1e-6, f"重叠时长 {overlap}s 应 ≤2s（10s 段的 20%）" def test_first_variant_segments_become_avoidance_target(self): """变体 0 选定区间后，变体 1 选同素材时批次区间生效（不与源区间完全重合）。""" source = _source_clips(assets=("a1", "a2"), dur=8.0) pool = ["a1", "a2", "a3"] durations = _durations(pool, total=600.0) batch_segments: dict = {} v1 = reselect_clips_for_variant( source, pool, asset_durations=durations, batch_segments=batch_segments, rng=random.Random(11) ) v1_main = [(c["asset_id"], c["start_time"], c["duration"]) for c in v1 if c["clip_type"] == "main"] # 快照 v1 之后的批次避让集（v2 调用会就地追加 v2 自身区间，断言必须用调用前快照） import copy batch_snapshot = copy.deepcopy(batch_segments) v2 = reselect_clips_for_variant( source, pool, asset_durations=durations, batch_segments=batch_segments, rng=random.Random(12) ) # v2 与 v1（快照）同素材片段的区间重叠占比均 ≤20% for c in v2: if c["clip_type"] != "main" or not c["asset_id"]: continue ratio = _clip_overlap_ratio(c["asset_id"], c["start_time"], c["duration"], batch_snapshot) assert ( ratio <= BATCH_CLIP_OVERLAP_LIMIT + 1e-6 ), f"变体间片段重叠超限: asset={c['asset_id']} start={c['start_time']} ratio={ratio:.2%}" # v1 片段确实进入了批次避让集 assert any(a in batch_segments for a, _, _ in v1_main)