174 lines
8.8 KiB
GDScript
174 lines
8.8 KiB
GDScript
# VERTICAL SLICE - NOT FOR PRODUCTION
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# 冒险全流程期望扫描（三关连探零加成基线批量试玩——run_adventure 的蒙特卡洛批量工具，
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# 补 level_monte_carlo 只测单关的空白面）：固定 atk+0%/hp+0%（零天赋格加成，关间大奖励
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# 按冒险结构现行设计自动兑付），逐局独立种子，输出：
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# ① 每局一行 RUNSUM JSON（stdout，局级摘要：策略/种子/result/summary/战斗轮数/承伤/踩雷/
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# 刷新/行进序列/逐战上限序列——后续统计分析的取数面）；
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# ② 全量操作日志 = playtest_logger 共享会话 JSONL（与真人试玩同合规口径，每策略一批一文件，
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# run 行携带种子/策略切分局次，落 user://logs/）。
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# 本工具只采集与落盘数据，不做统计判读（关卡完成率/败因分布归分析会话）。
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# 运行：Godot_console.exe --headless --path . --script res://sim/adventure_monte_carlo.gd -- [N] [seed0] [normal|perfect|both] [route min|max]
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extends SceneTree
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var _run_cursor := 0 # 全局局序号（seed = seed0 + cursor，逐局独立消费一次）
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func _initialize() -> void:
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var args := OS.get_cmdline_user_args()
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var n := 200
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if args.size() >= 1 and args[0].is_valid_int():
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n = maxi(5, int(args[0]))
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var seed0 := 71000
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if args.size() >= 2 and args[1].is_valid_int():
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seed0 = int(args[1])
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var policy_arg := "both"
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if args.size() >= 3 and args[2] in ["normal", "perfect", "both"]:
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policy_arg = args[2]
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var policies: Array = ["normal"]
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if policy_arg == "perfect":
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policies = ["perfect"]
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elif policy_arg == "both":
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policies = ["normal", "perfect"]
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var route := "min"
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if args.size() >= 4 and args[3] in ["min", "max"]:
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route = args[3]
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# 同调分层开关（off=现行基线零装配零扰动；on=贪心装配画像，确定性同种子可复放）
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var attune_mode := "off"
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if args.size() >= 5 and args[4] in ["off", "on"]:
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attune_mode = args[4]
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# 商店分层开关（off=legacy 对照缺省零扰动；on=共享池货架面，终局池读数随行）
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var shop_mode := "off"
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if args.size() >= 6 and args[5] in ["off", "on"]:
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shop_mode = args[5]
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# 特性/树分层开关（off=基线；formed=成型画像开局注入五事件族 14 件成型集
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# 〔测量面专用 params.relics_seed——真实局规则改写型特性只走局内随机渠道〕；ab_a/ab_b=Fork posture 两侧
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# rule 键集——A/B 面两侧差 <~3pp 验收载体；rules=任意树规则键集注入〔逗号分隔 args[7]——V19 三组配对载体〕）
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var feat_mode := "off"
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if args.size() >= 7 and args[6] in ["off", "formed", "ab_a", "ab_b", "rules"]:
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feat_mode = args[6]
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var db = load("res://core/config_db.gd").new()
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if not db.load_tables("res://data/tables", false):
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print("表加载失败")
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quit(1)
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return
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var feat_profile := {}
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if feat_mode == "formed":
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# 成型画像=五事件族覆盖 14 件
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# （开格 4/封印 3/踩雷 4/节奏 2/战斗 1——每族含跨事件账本件，账本件=攒层/计数面 MC 读数承载）
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feat_profile = {"mode": "on", "seed_ids": [
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"twin_pick", "geologist", "hard_hat", "frontier_miner",
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"seal_echo", "seal_smith", "seal_stake",
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"pain_memory", "trap_instinct", "chain_traps", "blood_honey",
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"last_drop", "market_close",
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"execution_scholar"]}
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elif feat_mode == "ab_a":
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feat_profile = {"mode": "off", "tree_rules": _tree_rule_dict(db, ["posture_first_strike"])}
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elif feat_mode == "ab_b":
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feat_profile = {"mode": "off", "tree_rules": _tree_rule_dict(db, ["posture_bulwark"])}
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elif feat_mode == "rules":
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feat_profile = {"mode": "off", "tree_rules": _tree_rule_dict(db, Array(String(args[7] if args.size() >= 8 else "").split(",", false)))} # V19——任意键集配对注入（规则键参数字典形态）
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var attune_profile := {}
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if attune_mode == "on":
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# 贪心画像：Slots=3（槽位判定源=树同调位节点点亮数，模拟画像=三节点
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# 全点亮常量）；装配序 =
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# 表序 passive 优先至 Slots-1 + 首个 active（slots=3 → 表序头三件占满示例，
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# provisional 画像归调参）；Y = 营地升级 Lv1 表值 1。autoplay 默认不刷——Y 仅注入容量，
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# 刷新消费归玩家策略面（钓鱼归玩家）。
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var slots: int = 3
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var passives: Array = []
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var actives: Array = []
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for r in db.crossrun.treasure_items.attunement_rows():
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if String(r.get("form", "")) == "passive":
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passives.append(String(r.get("item_id", "")))
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elif String(r.get("form", "")) == "active_charged":
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actives.append(String(r.get("item_id", "")))
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var equipped: Array = []
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for p in passives:
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if equipped.size() >= maxi(0, slots - 1):
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break
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equipped.append(p)
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if slots > equipped.size() and not actives.is_empty():
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equipped.append(actives[0])
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for p in passives:
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if equipped.size() >= slots:
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break
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if not equipped.has(p):
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equipped.append(p)
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attune_profile = {"equipped": equipped, "refresh_y": 1}
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var autoplay = load("res://sim/level_autoplay.gd")
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var t0 := Time.get_ticks_msec()
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print("=== 冒险全流程扫描：三关连探 · N=%d/策略 · 种子 %d 起逐局独立 · 策略=%s · atk+0%%/hp+0%% 零加成 · route=%s ===" % [n, seed0, policy_arg, route])
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for policy in policies:
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# 每策略一个共享日志会话（全量 JSONL 体量随局数增长，分文件便于定位）
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var logger = load("res://presentation/playtest_logger.gd").new()
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logger.ap_per_round = int(db.run.action_economy.ap_per_round)
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var log_path: String = logger.start_session(seed0)
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var tally := {}
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for i in range(n):
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var seed_val := seed0 + _run_cursor
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_run_cursor += 1
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var st = autoplay.run_adventure(db, seed_val, 0, 0, false, logger, policy, route, {}, attune_profile,
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{"mode": "pool"} if shop_mode == "on" else {}, feat_profile)
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var sum: Dictionary = st["summary"]
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var rec := {
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"policy": policy, "seed": seed_val, "atk_pct": 0, "hp_pct": 0, "route": route,
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"attune": attune_mode, "equipped": attune_profile.get("equipped", []),
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"feat_mode": feat_mode,
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"result": st["result"],
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"cleared": bool(sum.get("cleared", false)),
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"levels_cleared": int(sum.get("levels_cleared", -1)),
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"stopped_at": int(sum.get("stopped_at", -1)),
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"keystone_total": int(sum.get("keystone_total", -1)),
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"battles": int(st["battles"]), "rounds": int(st["rounds"]),
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"hero_dmg": int(st["hero_dmg"]), "mine_hits": int(st["mine_hits"]),
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"mine_dmg": int(st.get("mine_dmg", 0)),
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"taken": int(st["hero_dmg"]) + int(st.get("mine_dmg", 0)),
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"refreshes": int(st["refreshes"]), "choices": int(st["choices"]),
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# 封印经济五字段（η=seal_hit÷seal_placed、标空率=seal_miss÷seal_placed
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# 派生归分析侧；gain/penalty=结算流水行值合计（原始行值口径，等价换算归判读侧——登记））
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"seal_placed": int(st.get("seal_placed", 0)), "seal_hit": int(st.get("seal_hit", 0)),
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"seal_miss": int(st.get("seal_miss", 0)),
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"seal_hit_gain": int(st.get("seal_hit_gain", 0)),
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"seal_miss_penalty": int(st.get("seal_miss_penalty", 0)),
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"relics": st.get("relics", []),
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"visited_count": (st["visited_ids"] as Array).size(),
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"encounter_max_hp_seq": st["encounter_max_hp_seq"],
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"reward_events": st["reward_events"],
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"shop_gp_seq": st["shop_gp_seq"],
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"level_maps": st.get("level_maps", []),
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"wallet_count": (st["wallet_events"] as Array).size(),
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}
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if shop_mode == "on":
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# pool 面增量字段（off 行零新增保对拍逐位干净）
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rec["shop_mode"] = "pool"
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rec["shop_buys"] = int(st.get("shop_buys", 0))
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rec["pool_stock"] = st.get("pool_stock", {})
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var rs := String(sum.get("result", ""))
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tally[rs] = int(tally.get(rs, 0)) + 1
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print("RUNSUM " + JSON.stringify(rec))
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if (i + 1) % 20 == 0:
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print("... %s 进度 %d/%d（耗时 %.1f 秒）" % [policy, i + 1, n, float(Time.get_ticks_msec() - t0) / 1000.0])
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logger.close_session()
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print("BATCH %s N=%d 终局计数=%s 日志=%s" % [policy, n, JSON.stringify(tally), log_path])
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print("（口径注：零加成 = atk/hp 天赋格百分比均 0；关间大奖励（HP 上限提升+回满）按冒险结构设计自动兑付，未额外剥离 · 全程日志见 user://logs/ · 总耗时 %.1f 秒）" % [float(Time.get_ticks_msec() - t0) / 1000.0])
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quit(0)
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## 树规则参数字典构造（A/B 面注入单点——扫 meta_tree Fork 行 effects_a/b，命中 keys 集的键取其
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## 参数字典原样透传；db 参鸭子型沿 board_generator 先例——sim 面不在 S9 扫描面）
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static func _tree_rule_dict(db, keys: Array[Variant]) -> Dictionary[Variant, Variant]:
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var out: Dictionary[Variant, Variant] = {}
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var keyset := {}
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for k in keys:
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keyset[String(k)] = true
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for row in db.crossrun.meta_tree.rows:
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if String(row.get("kind", "")) != "fork":
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continue
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for skey in ["effects_a", "effects_b"]:
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var fx: Dictionary = row.get(skey, {}) as Dictionary
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for rk in fx.keys():
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if keyset.has(String(rk)) and not out.has(String(rk)):
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out[String(rk)] = fx[rk]
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return out
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