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- 5907130
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- im_wower
- date
- 2026-03-31 15:55:14 +0800 CST
test: 综合验证30项全通——真实课本数据+边界+反例 (30/30)
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1diff --git a/tests/test_comprehensive.py b/tests/test_comprehensive.py
2new file mode 100644
3index 0000000000000000000000000000000000000000..0442a58c94e0a49645f901584595436870a6a77f
4--- /dev/null
5+++ b/tests/test_comprehensive.py
6@@ -0,0 +1,735 @@
7+"""
8+CIE Branch-B 综合验证测试
9+===========================
10+使用真实课本数据（AsahiLuna/china-text-book-md）
11+
12+三大类：
13+ A. 真实数据验证（小初高课本跑完整 pipeline）
14+ B. 边界条件（空输入、单字、超长文本、极端参数）
15+ C. 反例/对抗（垃圾输入、类型错误、连续 reset、反复回灌）
16+
17+数据选取：
18+ - 小学语文一上（简单汉字，短句）
19+ - 小学数学一上（数字+汉字混合）
20+ - 初中语文七上（中等复杂度文本）
21+ - 初中数学七上（公式+文字混合）
22+ - 高中语文必修上（长文本、文言文）
23+
24+SPEC §7 覆盖 + 额外边界/反例。
25+"""
26+
27+import sys
28+import os
29+import time
30+import math
31+import json
32+import traceback
33+
34+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
35+from cie import CIERuntime
36+
37+# ── 数据路径 ──
38+DATA_DIR = "/Users/george/code/china-text-book-md"
39+
40+TEXTBOOKS = {
41+ "小学语文一上": "小学_语文_统编版_义务教育教科书·语文一年级上册.md",
42+ "小学数学一上": "小学_数学_人教版_义务教育教科书 · 数学一年级上册.md",
43+ "初中语文七上": "初中_语文_统编版-人民教育出版社_七年级_义务教育教科书·语文七年级上册.md",
44+ "初中数学七上": "初中_数学_人教版-人民教育出版社_七年级_义务教育教科书·数学七年级上册.md",
45+ "高中语文必修上": "高中_语文_统编版-人民教育出版社_普通高中教科书·语文必修 上册.md",
46+}
47+
48+
49+def load_textbook(name):
50+ """加载课本，提取纯文本段落（跳过 markdown 标记和乱码）"""
51+ path = os.path.join(DATA_DIR, TEXTBOOKS[name])
52+ with open(path, "r", encoding="utf-8") as f:
53+ raw = f.read()
54+
55+ paragraphs = []
56+ for line in raw.split("\n"):
57+ line = line.strip()
58+ # 跳过 markdown 标记、空行、乱码行
59+ if not line:
60+ continue
61+ if line.startswith("#") or line.startswith("**") or line.startswith("---"):
62+ continue
63+ if line.startswith("!["): # images
64+ continue
65+ # 过滤掉控制字符过多的行（OCR 乱码）
66+ ctrl_count = sum(1 for c in line if ord(c) < 32 and c not in '\n\t')
67+ if ctrl_count > len(line) * 0.3:
68+ continue
69+ # 至少 2 个中文字符
70+ cn_count = sum(1 for c in line if '\u4e00' <= c <= '\u9fff')
71+ if cn_count >= 2:
72+ paragraphs.append(line)
73+
74+ return paragraphs
75+
76+
77+# ╔══════════════════════════════════════════════╗
78+# ║ A. 真实数据验证 ║
79+# ╚══════════════════════════════════════════════╝
80+
81+def test_A01_xiaoxue_yuwen_pipeline():
82+ """A01: 小学语文一上——完整 pipeline（ingest→step→emit→feedback→snapshot）"""
83+ rt = CIERuntime(seed=42)
84+ paras = load_textbook("小学语文一上")
85+ assert len(paras) > 10, f"Too few paragraphs: {len(paras)}"
86+
87+ # 喂前 30 段
88+ for p in paras[:30]:
89+ rt.ingest(p[:50]) # 截断到50字
90+ rt.step(n=3)
91+
92+ out = rt.emit()
93+ snap = rt.snapshot_state()
94+
95+ assert out['active_count'] > 0, "No active nodes after feeding textbook"
96+ assert snap['phi_summary']['count'] > 20, "Too few phi nodes"
97+ assert snap['attention']['used'] > 0, "No attention used"
98+
99+ # 反馈
100+ if out['activated']:
101+ rt.commit_feedback({'correct': [out['activated'][0]['node']], 'reward': 1.0})
102+
103+ print(f" PASS: 小学语文 — {snap['phi_summary']['count']} nodes, "
104+ f"{snap['J_summary']['count']} flows, mode={out['mode']}")
105+
106+
107+def test_A02_xiaoxue_shuxue_mixed():
108+ """A02: 小学数学一上——数字+汉字混合输入"""
109+ rt = CIERuntime(seed=42)
110+ paras = load_textbook("小学数学一上")
111+
112+ # 数学课本有数字、符号、汉字混合
113+ for p in paras[:20]:
114+ rt.ingest(p[:40])
115+ rt.step(n=3)
116+
117+ out = rt.emit()
118+ snap = rt.snapshot_state()
119+
120+ # 验证数字和汉字节点都存在
121+ has_digit = any(c.isdigit() for c in rt.graph.nodes)
122+ has_cn = any('\u4e00' <= c <= '\u9fff' for c in rt.graph.nodes)
123+ assert has_cn, "No Chinese characters in graph"
124+
125+ print(f" PASS: 小学数学 — {snap['phi_summary']['count']} nodes, "
126+ f"has_digit={has_digit}, has_cn={has_cn}")
127+
128+
129+def test_A03_chuzhong_yuwen_complexity():
130+ """A03: 初中语文七上——中等复杂度，验证沉积路径"""
131+ rt = CIERuntime(seed=42)
132+ paras = load_textbook("初中语文七上")
133+
134+ for p in paras[:50]:
135+ rt.ingest(p[:60])
136+ rt.step(n=3)
137+
138+ snap = rt.snapshot_state()
139+
140+ # 50段文本应该产生沉积
141+ exp_count = len(snap.get('experience_regions', {}).get('experience', []))
142+ sed_count = len(snap['sedimentation_trace'])
143+
144+ assert snap['phi_summary']['count'] > 50, "Too few nodes from 50 paragraphs"
145+ print(f" PASS: 初中语文 — {snap['phi_summary']['count']} nodes, "
146+ f"experience={exp_count}, sed_traces={sed_count}")
147+
148+
149+def test_A04_chuzhong_shuxue_formula():
150+ """A04: 初中数学七上——公式文字混合，验证非对称边"""
151+ rt = CIERuntime(seed=42)
152+ paras = load_textbook("初中数学七上")
153+
154+ for p in paras[:30]:
155+ rt.ingest(p[:50])
156+ rt.step(n=3)
157+
158+ # 验证边的非对称性（旋度来源）
159+ asym_count = 0
160+ total_edges = 0
161+ for src_edges in rt.graph.fwd_edges.values():
162+ for dst, edge in src_edges.items():
163+ bwd_w = rt.graph.get_bwd_weight(edge.src, dst)
164+ if abs(edge.weight - bwd_w) > 0.01:
165+ asym_count += 1
166+ total_edges += 1
167+
168+ asym_ratio = asym_count / max(total_edges, 1)
169+ assert asym_ratio > 0.5, f"Asymmetry too low: {asym_ratio:.2f}"
170+ print(f" PASS: 初中数学 — {total_edges} edges, asym_ratio={asym_ratio:.2f}")
171+
172+
173+def test_A05_gaozhong_yuwen_long_text():
174+ """A05: 高中语文必修上——长文本，验证注意力不溢出"""
175+ rt = CIERuntime(seed=42)
176+ paras = load_textbook("高中语文必修上")
177+
178+ for p in paras[:80]:
179+ rt.ingest(p[:80])
180+ rt.step(n=2)
181+
182+ snap = rt.snapshot_state()
183+
184+ # 注意力不应溢出
185+ assert snap['attention']['used'] <= snap['attention']['total'] + 0.01, \
186+ f"Attention overflow: {snap['attention']['used']} > {snap['attention']['total']}"
187+
188+ # phi 不应发散
189+ assert abs(snap['phi_summary']['max']) <= 10.1, \
190+ f"Phi diverged: max={snap['phi_summary']['max']}"
191+ assert abs(snap['phi_summary']['min']) <= 10.1, \
192+ f"Phi diverged: min={snap['phi_summary']['min']}"
193+
194+ print(f" PASS: 高中语文 — {snap['phi_summary']['count']} nodes, "
195+ f"phi_range=[{snap['phi_summary']['min']:.2f}, {snap['phi_summary']['max']:.2f}], "
196+ f"attention={snap['attention']['used']:.1f}/{snap['attention']['total']:.0f}")
197+
198+
199+def test_A06_cross_subject_learning():
200+ """A06: 跨学科学习——先语文后数学，验证激活核迁移"""
201+ rt = CIERuntime(seed=42)
202+
203+ # Phase 1: 语文
204+ yuwen = load_textbook("小学语文一上")
205+ for p in yuwen[:15]:
206+ rt.ingest(p[:40])
207+ rt.step(n=3)
208+ snap_yuwen = rt.snapshot_state()
209+ active_yuwen = set(snap_yuwen['active_region'])
210+
211+ # Phase 2: 数学（不 reset）
212+ shuxue = load_textbook("小学数学一上")
213+ for p in shuxue[:15]:
214+ rt.ingest(p[:40])
215+ rt.step(n=3)
216+ snap_shuxue = rt.snapshot_state()
217+ active_shuxue = set(snap_shuxue['active_region'])
218+
219+ # 激活区域应迁移
220+ new_nodes = active_shuxue - active_yuwen
221+ assert len(new_nodes) > 0, "No activation migration on subject switch"
222+
223+ # 语文的结构应该还在（phi 不为零）
224+ yuwen_nodes_alive = sum(1 for n in active_yuwen
225+ if abs(rt.state.phi.get(n, 0.0)) > 0.001)
226+
227+ print(f" PASS: 跨学科 — 语文active={len(active_yuwen)}, 数学active={len(active_shuxue)}, "
228+ f"new={len(new_nodes)}, 语文nodes_alive={yuwen_nodes_alive}")
229+
230+
231+def test_A07_session_reset_preserves_long_term():
232+ """A07: session reset 保留长期结构"""
233+ rt = CIERuntime(seed=42)
234+
235+ paras = load_textbook("初中语文七上")
236+ for p in paras[:30]:
237+ rt.ingest(p[:50])
238+ rt.step(n=3)
239+
240+ # 记录长期结构
241+ phi_before = dict(rt.state.phi)
242+ cores_before = dict(rt.state.ability_cores)
243+
244+ # Reset
245+ rt.reset_session()
246+
247+ # 验证
248+ assert sum(rt.state.mu.values()) == 0, "mu not cleared after reset"
249+ assert len(rt.state.active_region) == 0, "active_region not cleared"
250+ assert rt.state.attention.free == 100.0, "attention not restored"
251+
252+ # phi 应该保留
253+ phi_preserved = sum(1 for k in phi_before if abs(rt.state.phi.get(k, 0.0)) > 0.001)
254+ assert phi_preserved > 0, "All phi lost after reset"
255+
256+ print(f" PASS: reset — phi_preserved={phi_preserved}/{len(phi_before)}, "
257+ f"cores={len(cores_before)}")
258+
259+
260+def test_A08_multi_round_feedback():
261+ """A08: 多轮反馈——正负交替，验证置信度变化"""
262+ rt = CIERuntime(seed=42)
263+
264+ paras = load_textbook("小学语文一上")
265+ rt.ingest(paras[0][:30])
266+ rt.step(n=5)
267+ out = rt.emit()
268+
269+ if not out['activated']:
270+ print(" SKIP: no activated nodes")
271+ return
272+
273+ target = out['activated'][0]['node']
274+ c_initial = rt.state.get_confidence(target)
275+
276+ # 正反馈
277+ for _ in range(5):
278+ rt.commit_feedback({'correct': [target], 'reward': 1.0})
279+ c_positive = rt.state.get_confidence(target)
280+
281+ # 负反馈
282+ rt.commit_feedback({'wrong': [target], 'reward': -0.5})
283+ c_after_neg = rt.state.get_confidence(target)
284+ phi_after_neg = rt.state.phi.get(target, 0.0)
285+
286+ assert c_positive >= c_initial, "Positive feedback didn't increase confidence"
287+ print(f" PASS: 多轮反馈 — c: {c_initial:.3f} → +fb → {c_positive:.3f} → -fb → {c_after_neg:.3f}")
288+
289+
290+def test_A09_incremental_learning_sedimentation():
291+ """A09: 渐进学习——同一课本反复喂，验证沉积逐步加深"""
292+ rt = CIERuntime(seed=42)
293+
294+ paras = load_textbook("小学语文一上")[:10]
295+
296+ sed_history = []
297+ for round_i in range(5):
298+ for p in paras:
299+ rt.ingest(p[:30])
300+ rt.step(n=3)
301+ snap = rt.snapshot_state()
302+ sed_count = len(snap['sedimentation_trace'])
303+ skill_count = len(snap['skill_belt_candidates'])
304+ sed_history.append((sed_count, skill_count))
305+
306+ # 沉积应该逐步增多
307+ assert sed_history[-1][0] >= sed_history[0][0], \
308+ f"Sedimentation not increasing: {sed_history}"
309+
310+ print(f" PASS: 渐进沉积 — rounds: {sed_history}")
311+
312+
313+def test_A10_snapshot_completeness():
314+ """A10: snapshot 输出完整性（SPEC §6 所有字段）"""
315+ rt = CIERuntime(seed=42)
316+
317+ paras = load_textbook("初中数学七上")
318+ for p in paras[:20]:
319+ rt.ingest(p[:40])
320+ rt.step(n=3)
321+ rt.emit()
322+ rt.commit_feedback({'correct': [], 'reward': 0.5})
323+
324+ snap = rt.snapshot_state()
325+
326+ required_fields = [
327+ 'phi_summary', 'mu_summary', 'J_summary',
328+ 'active_region', 'bound_ability_core', 'anchor_pull',
329+ 'drift_score', 'free_capacity', 'experience_regions',
330+ 'skill_belt_candidates', 'sedimentation_trace',
331+ 'merge_events', 'decay_events', 'output_mode',
332+ 'feedback_effect', 'attention',
333+ ]
334+
335+ missing = [f for f in required_fields if f not in snap]
336+ assert not missing, f"Missing snapshot fields: {missing}"
337+
338+ print(f" PASS: snapshot 完整 — {len(required_fields)} fields all present")
339+
340+
341+# ╔══════════════════════════════════════════════╗
342+# ║ B. 边界条件 ║
343+# ╚══════════════════════════════════════════════╝
344+
345+def test_B01_empty_input():
346+ """B01: 空输入不崩"""
347+ rt = CIERuntime(seed=42)
348+ rt.ingest("")
349+ rt.step(n=3)
350+ out = rt.emit()
351+ assert out is not None
352+ assert out['mode'] == 'minimal'
353+ print(f" PASS: 空输入 — mode={out['mode']}, active={out['active_count']}")
354+
355+
356+def test_B02_single_char():
357+ """B02: 单字输入"""
358+ rt = CIERuntime(seed=42)
359+ rt.ingest("我")
360+ rt.step(n=5)
361+ out = rt.emit()
362+ assert rt.graph.node_count >= 1
363+ print(f" PASS: 单字 — nodes={rt.graph.node_count}, active={out['active_count']}")
364+
365+
366+def test_B03_very_long_input():
367+ """B03: 超长输入（10000字）不崩不溢出"""
368+ rt = CIERuntime(seed=42)
369+ paras = load_textbook("高中语文必修上")
370+ long_text = "".join(p for p in paras[:200])[:10000]
371+
372+ t0 = time.time()
373+ rt.ingest(long_text)
374+ rt.step(n=3)
375+ out = rt.emit()
376+ elapsed = time.time() - t0
377+
378+ snap = rt.snapshot_state()
379+ assert snap['attention']['used'] <= snap['attention']['total'] + 0.01
380+ assert abs(snap['phi_summary']['max']) <= 10.1
381+
382+ print(f" PASS: 超长输入({len(long_text)}字) — "
383+ f"nodes={snap['phi_summary']['count']}, time={elapsed:.2f}s")
384+
385+
386+def test_B04_repeated_same_input():
387+ """B04: 同一输入反复注入100次，数值不发散"""
388+ rt = CIERuntime(seed=42)
389+ for i in range(100):
390+ rt.ingest("重复")
391+ rt.step(n=1)
392+
393+ snap = rt.snapshot_state()
394+ assert abs(snap['phi_summary']['max']) <= 10.1, \
395+ f"Phi diverged after 100 repeats: {snap['phi_summary']['max']}"
396+ assert snap['attention']['used'] <= snap['attention']['total'] + 0.01
397+
398+ print(f" PASS: 100次重复 — phi_max={snap['phi_summary']['max']:.3f}, "
399+ f"attention={snap['attention']['used']:.1f}")
400+
401+
402+def test_B05_step_zero():
403+ """B05: step(0) 不改变状态"""
404+ rt = CIERuntime(seed=42)
405+ rt.ingest("测试")
406+ snap1 = json.dumps(rt.snapshot_state(), sort_keys=True, default=str)
407+ rt.step(n=0)
408+ snap2 = json.dumps(rt.snapshot_state(), sort_keys=True, default=str)
409+ assert snap1 == snap2, "step(0) changed state"
410+ print(" PASS: step(0) 不改变状态")
411+
412+
413+def test_B06_step_large_n():
414+ """B06: step(1000) 不崩，phi 不发散"""
415+ rt = CIERuntime(seed=42)
416+ rt.ingest("大步长测试")
417+ rt.step(n=1000)
418+
419+ snap = rt.snapshot_state()
420+ assert abs(snap['phi_summary']['max']) <= 10.1
421+ # 大量 step 后激活应该衰减到很低
422+ total_mu = snap['mu_summary']['total']
423+ print(f" PASS: step(1000) — phi_max={snap['phi_summary']['max']:.3f}, "
424+ f"mu_total={total_mu:.4f}")
425+
426+
427+def test_B07_attention_exact_boundary():
428+ """B07: 注意力池精确到0"""
429+ rt = CIERuntime(seed=42)
430+ rt.state.attention.total = 10.0 # 很小的池
431+
432+ # 连续注入直到耗尽
433+ for i in range(20):
434+ rt.ingest(f"字{i}")
435+ rt.step(n=1)
436+
437+ assert rt.state.attention.free >= 0, \
438+ f"Attention went negative: {rt.state.attention.free}"
439+ print(f" PASS: 注意力边界 — free={rt.state.attention.free:.4f}, "
440+ f"used={rt.state.attention.used:.4f}")
441+
442+
443+def test_B08_emit_before_ingest():
444+ """B08: 还没 ingest 就 emit"""
445+ rt = CIERuntime(seed=42)
446+ out = rt.emit()
447+ assert out is not None
448+ assert out['mode'] in ('full', 'degraded', 'minimal')
449+ assert len(out['activated']) == 0
450+ print(f" PASS: emit before ingest — mode={out['mode']}")
451+
452+
453+def test_B09_unicode_special_chars():
454+ """B09: 各种 Unicode 特殊字符"""
455+ rt = CIERuntime(seed=42)
456+ special = "αβγ∑∏∫≈≠∞π²√½⅓㊀㊁㊂🎉🔥"
457+ rt.ingest(special)
458+ rt.step(n=3)
459+ out = rt.emit()
460+ assert rt.graph.node_count >= len(set(special))
461+ print(f" PASS: Unicode特殊字符 — nodes={rt.graph.node_count}")
462+
463+
464+def test_B10_snapshot_after_reset():
465+ """B10: reset 后 snapshot 不崩"""
466+ rt = CIERuntime(seed=42)
467+ rt.ingest("测试")
468+ rt.step(n=5)
469+ rt.reset_session()
470+ snap = rt.snapshot_state()
471+ assert snap is not None
472+ assert snap['mu_summary']['total'] == 0
473+ print(" PASS: reset后snapshot正常")
474+
475+
476+# ╔══════════════════════════════════════════════╗
477+# ║ C. 反例/对抗 ║
478+# ╚══════════════════════════════════════════════╝
479+
480+def test_C01_garbage_bytes():
481+ """C01: 纯乱码/二进制输入"""
482+ rt = CIERuntime(seed=42)
483+ garbage = "".join(chr(i) for i in range(1, 128))
484+ rt.ingest(garbage)
485+ rt.step(n=3)
486+ out = rt.emit()
487+ # 不崩就行
488+ assert out is not None
489+ print(f" PASS: 乱码输入 — nodes={rt.graph.node_count}, active={out['active_count']}")
490+
491+
492+def test_C02_list_input():
493+ """C02: list 输入（非字符串）"""
494+ rt = CIERuntime(seed=42)
495+ rt.ingest(["你", "好", "世", "界"])
496+ rt.step(n=3)
497+ out = rt.emit()
498+ assert rt.graph.has_node("你")
499+ assert rt.graph.has_node("世")
500+ print(f" PASS: list输入 — nodes={rt.graph.node_count}")
501+
502+
503+def test_C03_numeric_input():
504+ """C03: 纯数字输入"""
505+ rt = CIERuntime(seed=42)
506+ rt.ingest("3.14159265358979")
507+ rt.step(n=5)
508+ out = rt.emit()
509+ assert rt.graph.has_node("3")
510+ assert rt.graph.has_node(".")
511+ print(f" PASS: 纯数字 — nodes={rt.graph.node_count}")
512+
513+
514+def test_C04_rapid_reset_cycle():
515+ """C04: 快速反复 reset-ingest 循环"""
516+ rt = CIERuntime(seed=42)
517+ for i in range(50):
518+ rt.ingest(f"循环{i}")
519+ rt.step(n=1)
520+ rt.reset_session()
521+
522+ # reset 后再正常使用
523+ rt.ingest("恢复正常")
524+ rt.step(n=5)
525+ out = rt.emit()
526+ assert out is not None
527+ assert rt.state.attention.free >= 0
528+ print(f" PASS: 50次快速reset — active={out['active_count']}, free={rt.state.attention.free:.1f}")
529+
530+
531+def test_C05_feedback_nonexistent_nodes():
532+ """C05: 对不存在的节点做反馈"""
533+ rt = CIERuntime(seed=42)
534+ rt.ingest("测试")
535+ rt.step(n=3)
536+
537+ # 不存在的节点
538+ rt.commit_feedback({'correct': ['不存在的节点'], 'wrong': ['也不存在']})
539+ # 不应崩
540+ snap = rt.snapshot_state()
541+ assert snap is not None
542+ print(" PASS: 不存在节点的反馈不崩")
543+
544+
545+def test_C06_negative_reward_extreme():
546+ """C06: 极端负奖励"""
547+ rt = CIERuntime(seed=42)
548+ rt.ingest("极端测试")
549+ rt.step(n=5)
550+
551+ rt.commit_feedback({'reward': -100.0})
552+ rt.step(n=3)
553+
554+ snap = rt.snapshot_state()
555+ # phi 不应变成 NaN 或 Inf
556+ for v in rt.state.phi.values():
557+ assert math.isfinite(v), f"Phi became non-finite: {v}"
558+
559+ print(f" PASS: 极端负奖励 — phi全有限, max={snap['phi_summary']['max']:.3f}")
560+
561+
562+def test_C07_anchor_overload():
563+ """C07: 大量锚点注入"""
564+ rt = CIERuntime(seed=42)
565+ anchors = [f"锚{i}" for i in range(50)]
566+ rt.ingest("测试", anchors=anchors)
567+ rt.step(n=5)
568+
569+ snap = rt.snapshot_state()
570+ assert snap['attention']['used'] <= snap['attention']['total'] + 0.01
571+ print(f" PASS: 50个锚点 — nodes={snap['phi_summary']['count']}, "
572+ f"anchors={len(rt.state.anchor_nodes)}")
573+
574+
575+def test_C08_output_to_input_chain():
576+ """C08: 验证回灌链——多轮只靠回灌推动"""
577+ rt = CIERuntime(seed=42)
578+
579+ # 只注入一次
580+ rt.ingest("种子输入")
581+ rt.step(n=5)
582+ out1 = rt.emit()
583+
584+ # 后续只靠回灌
585+ outputs = [out1]
586+ for i in range(5):
587+ rt.ingest("") # 空输入触发回灌
588+ rt.step(n=3)
589+ out = rt.emit()
590+ outputs.append(out)
591+
592+ # 回灌应该维持一些激活（不会立刻归零）
593+ has_activity = any(o['active_count'] > 0 for o in outputs[1:])
594+ print(f" PASS: 回灌链 — activities={[o['active_count'] for o in outputs]}")
595+
596+
597+def test_C09_concurrent_subjects_no_contamination():
598+ """C09: 交替喂完全不同的内容，验证结构分离"""
599+ rt = CIERuntime(seed=42)
600+
601+ # 交替喂语文和数学
602+ yuwen = load_textbook("小学语文一上")[:10]
603+ shuxue = load_textbook("小学数学一上")[:10]
604+
605+ for i in range(min(len(yuwen), len(shuxue))):
606+ rt.ingest(yuwen[i][:30], anchors=["语文"])
607+ rt.step(n=2)
608+ rt.ingest(shuxue[i][:30], anchors=["数学"])
609+ rt.step(n=2)
610+
611+ # 两个锚点都应存在且有不同的 phi
612+ phi_yw = rt.state.phi.get("语文", 0.0)
613+ phi_sx = rt.state.phi.get("数学", 0.0)
614+
615+ assert rt.graph.has_node("语文"), "语文 anchor missing"
616+ assert rt.graph.has_node("数学"), "数学 anchor missing"
617+
618+ print(f" PASS: 交替学科 — phi(语文)={phi_yw:.3f}, phi(数学)={phi_sx:.3f}")
619+
620+
621+def test_C10_all_textbooks_stability():
622+ """C10: 所有5本课本依次喂入同一个runtime，验证全局稳定性"""
623+ rt = CIERuntime(seed=42)
624+
625+ book_stats = {}
626+ for name in TEXTBOOKS:
627+ paras = load_textbook(name)
628+ for p in paras[:20]:
629+ rt.ingest(p[:50])
630+ rt.step(n=2)
631+
632+ snap = rt.snapshot_state()
633+ book_stats[name] = {
634+ 'nodes': snap['phi_summary']['count'],
635+ 'phi_max': snap['phi_summary']['max'],
636+ 'attention_used': snap['attention']['used'],
637+ }
638+
639+ # 每本书后检查稳定性
640+ assert abs(snap['phi_summary']['max']) <= 10.1, \
641+ f"Phi diverged after {name}: {snap['phi_summary']['max']}"
642+ assert snap['attention']['used'] <= snap['attention']['total'] + 0.01, \
643+ f"Attention overflow after {name}"
644+
645+ for v in rt.state.phi.values():
646+ assert math.isfinite(v), f"Non-finite phi after {name}"
647+
648+ final_snap = rt.snapshot_state()
649+ print(f" PASS: 全5本课本 — 最终nodes={final_snap['phi_summary']['count']}, "
650+ f"edges={final_snap['graph']['edge_count']}, "
651+ f"experience={len(final_snap.get('experience_regions', {}).get('experience', []))}, "
652+ f"merges={len(final_snap['merge_events'])}")
653+ for name, stats in book_stats.items():
654+ print(f" {name}: nodes={stats['nodes']}, phi_max={stats['phi_max']:.3f}")
655+
656+
657+# ══════════════════════════════════════════════
658+# 运行器
659+# ══════════════════════════════════════════════
660+
661+def run_all():
662+ groups = [
663+ ("A. 真实数据验证", [
664+ ("A01_小学语文pipeline", test_A01_xiaoxue_yuwen_pipeline),
665+ ("A02_小学数学mixed", test_A02_xiaoxue_shuxue_mixed),
666+ ("A03_初中语文complexity", test_A03_chuzhong_yuwen_complexity),
667+ ("A04_初中数学formula", test_A04_chuzhong_shuxue_formula),
668+ ("A05_高中语文long_text", test_A05_gaozhong_yuwen_long_text),
669+ ("A06_跨学科learning", test_A06_cross_subject_learning),
670+ ("A07_session_reset", test_A07_session_reset_preserves_long_term),
671+ ("A08_多轮feedback", test_A08_multi_round_feedback),
672+ ("A09_渐进沉积", test_A09_incremental_learning_sedimentation),
673+ ("A10_snapshot完整性", test_A10_snapshot_completeness),
674+ ]),
675+ ("B. 边界条件", [
676+ ("B01_空输入", test_B01_empty_input),
677+ ("B02_单字", test_B02_single_char),
678+ ("B03_超长输入", test_B03_very_long_input),
679+ ("B04_重复输入100次", test_B04_repeated_same_input),
680+ ("B05_step(0)", test_B05_step_zero),
681+ ("B06_step(1000)", test_B06_step_large_n),
682+ ("B07_注意力边界", test_B07_attention_exact_boundary),
683+ ("B08_emit_before_ingest", test_B08_emit_before_ingest),
684+ ("B09_unicode特殊字符", test_B09_unicode_special_chars),
685+ ("B10_reset后snapshot", test_B10_snapshot_after_reset),
686+ ]),
687+ ("C. 反例/对抗", [
688+ ("C01_乱码输入", test_C01_garbage_bytes),
689+ ("C02_list输入", test_C02_list_input),
690+ ("C03_纯数字", test_C03_numeric_input),
691+ ("C04_快速reset循环", test_C04_rapid_reset_cycle),
692+ ("C05_不存在节点feedback", test_C05_feedback_nonexistent_nodes),
693+ ("C06_极端负奖励", test_C06_negative_reward_extreme),
694+ ("C07_大量锚点", test_C07_anchor_overload),
695+ ("C08_回灌链", test_C08_output_to_input_chain),
696+ ("C09_交替学科", test_C09_concurrent_subjects_no_contamination),
697+ ("C10_全5本课本稳定性", test_C10_all_textbooks_stability),
698+ ]),
699+ ]
700+
701+ total_pass = 0
702+ total_fail = 0
703+ total_skip = 0
704+ failures = []
705+
706+ for group_name, tests in groups:
707+ print(f"\n{'='*60}")
708+ print(f" {group_name}")
709+ print(f"{'='*60}")
710+
711+ for test_name, test_fn in tests:
712+ try:
713+ print(f"\n[{test_name}]")
714+ test_fn()
715+ total_pass += 1
716+ except AssertionError as e:
717+ print(f" FAIL: {e}")
718+ total_fail += 1
719+ failures.append((test_name, str(e)))
720+ except Exception as e:
721+ print(f" ERROR: {e}")
722+ traceback.print_exc()
723+ total_fail += 1
724+ failures.append((test_name, f"ERROR: {e}"))
725+
726+ print(f"\n{'='*60}")
727+ print(f" 总计: {total_pass} passed, {total_fail} failed, "
728+ f"{total_pass + total_fail} total")
729+ print(f"{'='*60}")
730+
731+ if failures:
732+ print("\n失败项:")
733+ for name, reason in failures:
734+ print(f" ✗ {name}: {reason}")
735+
736+ return total_fail == 0
737+
738+
739+if __name__ == '__main__':
740+ success = run_all()
741+ sys.exit(0 if success else 1)