gplan-2/game/smoke/adventure_monte_carlo.gd

# VERTICAL SLICE - NOT FOR PRODUCTION
# Date: 2026-09-21
# 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，
# 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
# 按冒险结构现行设计自动兑付），逐局独立种子，输出：
#   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/
#      刷新/行进序列/逐战上限序列——后续统计分析的取数面）；
#   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，
#      run 行携带种子/策略切分局次，落 user://logs/）。
# 本工具只采集与落盘数据，不做统计判读（通关率/败因分布归分析会话）。
# 运行：Godot_console.exe --headless --path . --script res://smoke/adventure_monte_carlo.gd -- [N] [seed0] [normal|perfect|both] [route min|max]
extends SceneTree


var _run_cursor := 0   # 全局局序号（seed = seed0 + cursor，逐局独立消费一次）


func _initialize() -> void:
	var args := OS.get_cmdline_user_args()
	var n := 200
	if args.size() >= 1 and args[0].is_valid_int():
		n = maxi(5, int(args[0]))
	var seed0 := 71000
	if args.size() >= 2 and args[1].is_valid_int():
		seed0 = int(args[1])
	var policy_arg := "both"
	if args.size() >= 3 and args[2] in ["normal", "perfect", "both"]:
		policy_arg = args[2]
	var policies: Array = ["normal"]
	if policy_arg == "perfect":
		policies = ["perfect"]
	elif policy_arg == "both":
		policies = ["normal", "perfect"]
	var route := "min"
	if args.size() >= 4 and args[3] in ["min", "max"]:
		route = args[3]
	# 同调分层开关（迭代 11 第①批 T8——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）
	var attune_mode := "off"
	if args.size() >= 5 and args[4] in ["off", "on"]:
		attune_mode = args[4]
	# 商店分层开关（迭代 11 第②批 T5——off=legacy 对照缺省零扰动；on=共享池货架面，终局池读数随行）
	var shop_mode := "off"
	if args.size() >= 6 and args[5] in ["off", "on"]:
		shop_mode = args[5]
	# 特性/树分层开关（迭代 12 T7/T10——off=基线；formed=成型画像开局注入七流派各 2 件档一成型集
	# 〔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
	# rule 键集——A/B 面两侧差 <~3pp 验收载体）
	var feat_mode := "off"
	if args.size() >= 7 and args[6] in ["off", "formed", "ab_a", "ab_b"]:
		feat_mode = args[6]
	var feat_profile := {}
	if feat_mode == "formed":
		# 迭代 20 T8 画像换代——旧 14 件随老 27 件退役；新画像=五事件族覆盖 14 件
		# （开格 4/插旗 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）
		feat_profile = {"mode": "on", "seed_ids": [
			"twin_pick", "geologist", "hard_hat", "frontier_miner",
			"seal_echo", "seal_smith", "seal_stake",
			"pain_memory", "trap_instinct", "chain_traps", "blood_honey",
			"last_drop", "market_close",
			"execution_scholar"]}
	elif feat_mode == "ab_a":
		feat_profile = {"mode": "off", "tree_rules": ["posture_first_strike"]}
	elif feat_mode == "ab_b":
		feat_profile = {"mode": "off", "tree_rules": ["posture_bulwark"]}
	var db = load("res://core/config_db.gd").new()
	if not db.load_tables("res://data/tables", false):
		print("表加载失败")
		quit(1)
		return
	var attune_profile := {}
	if attune_mode == "on":
		# 贪心画像：Slots=3（迭代 21 V14 换代——槽位判定源=树同调位节点点亮数，模拟画像=三节点
		# 全点亮常量；原「中间进度计数经谓词表求值」随 attunement_growth 谓词表退役）；装配序 =
		# 表序 passive 优先至 Slots-1 + 首个 active（slots=3 → [淬毒刃纹, 标中殉爆, 掘进蓄能]，
		# provisional 画像归调参批）；Y = 营地升级 Lv1 表值 1。autoplay 默认不刷——Y 仅注入容量，
		# 刷新消费归玩家策略面（钓鱼归玩家）。
		var slots: int = 3
		var passives: Array = []
		var actives: Array = []
		for r in db.treasure_attunement_rows():
			if String(r.get("form", "")) == "passive":
				passives.append(String(r.get("item_id", "")))
			elif String(r.get("form", "")) == "active_charged":
				actives.append(String(r.get("item_id", "")))
		var equipped: Array = []
		for p in passives:
			if equipped.size() >= maxi(0, slots - 1):
				break
			equipped.append(p)
		if slots > equipped.size() and not actives.is_empty():
			equipped.append(actives[0])
		for p in passives:
			if equipped.size() >= slots:
				break
			if not equipped.has(p):
				equipped.append(p)
		attune_profile = {"equipped": equipped, "refresh_y": 1}
	var autoplay = load("res://smoke/level_autoplay.gd")
	var t0 := Time.get_ticks_msec()
	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])
	for policy in policies:
		# 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）
		var logger = load("res://presentation/playtest_logger.gd").new()
		logger.ap_per_round = int(db.action_economy.ap_per_round)
		var log_path: String = logger.start_session(seed0)
		var tally := {}
		for i in range(n):
			var seed_val := seed0 + _run_cursor
			_run_cursor += 1
			var st = autoplay.run_adventure(db, seed_val, 0, 0, false, logger, policy, route, {}, attune_profile,
				{"mode": "pool"} if shop_mode == "on" else {}, feat_profile)
			var sum: Dictionary = st["summary"]
			var rec := {
				"policy": policy, "seed": seed_val, "atk_pct": 0, "hp_pct": 0, "route": route,
				"attune": attune_mode, "equipped": attune_profile.get("equipped", []),
				"feat_mode": feat_mode,
				"result": st["result"],
				"cleared": bool(sum.get("cleared", false)),
				"levels_cleared": int(sum.get("levels_cleared", -1)),
				"stopped_at": int(sum.get("stopped_at", -1)),
				"keystone_total": int(sum.get("keystone_total", -1)),
				"battles": int(st["battles"]), "rounds": int(st["rounds"]),
				"hero_dmg": int(st["hero_dmg"]), "mine_hits": int(st["mine_hits"]),
				"mine_dmg": int(st.get("mine_dmg", 0)),
				"taken": int(st["hero_dmg"]) + int(st.get("mine_dmg", 0)),
				"refreshes": int(st["refreshes"]), "choices": int(st["choices"]),
				# 旗经济五字段（迭代14②判式换代批 T1——η=flag_hit÷flag_placed、标空率=flag_miss÷flag_placed
				# 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））
				"flag_placed": int(st.get("flag_placed", 0)), "flag_hit": int(st.get("flag_hit", 0)),
				"flag_miss": int(st.get("flag_miss", 0)),
				"flag_hit_gain": int(st.get("flag_hit_gain", 0)),
				"flag_miss_penalty": int(st.get("flag_miss_penalty", 0)),
				"relics": st.get("relics", []),
				"visited_count": (st["visited_ids"] as Array).size(),
				"encounter_max_hp_seq": st["encounter_max_hp_seq"],
				"reward_events": st["reward_events"],
				"shop_gp_seq": st["shop_gp_seq"],
				"level_templates": st.get("level_templates", []),
				"wallet_count": (st["wallet_events"] as Array).size(),
			}
			if shop_mode == "on":
				# pool 面增量字段（迭代 11 第②批 T5——off 行零新增保对拍逐位干净）
				rec["shop_mode"] = "pool"
				rec["shop_buys"] = int(st.get("shop_buys", 0))
				rec["pool_stock"] = st.get("pool_stock", {})
			var rs := String(sum.get("result", ""))
			tally[rs] = int(tally.get(rs, 0)) + 1
			print("RUNSUM " + JSON.stringify(rec))
			if (i + 1) % 20 == 0:
				print("... %s 进度 %d/%d（耗时 %.1f 秒）" % [policy, i + 1, n, float(Time.get_ticks_msec() - t0) / 1000.0])
		logger.close_session()
		print("BATCH %s N=%d 终局计数=%s 日志=%s" % [policy, n, JSON.stringify(tally), log_path])
	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])
	quit(0)