# VERTICAL SLICE - NOT FOR PRODUCTION
# 战斗期望蒙特卡洛：当前参数下"胜轮数 / 每轮承伤 / 清图次数 / 开格数"的分布实测。
# 政策 = 理性玩家近似：挖最近可挖格（AutoPlayer 单一实现）。
# 运行：Godot_console.exe --headless --path . --script res://sim/monte_carlo.gd
extends SceneTree

const BattleDriver := preload("res://sim/battle_driver.gd")   # T6 收口：挖掘驱动循环单点（策略仍归 AutoPlayer 单一实现）

const N := 30
const SEED0 := 42


func _initialize() -> void:
	var db = load("res://core/config_db.gd").new()
	db.load_tables("res://data/tables", false)
	for L in [1, 2]:
		_run_encounter(db, L)
	quit(0)


func _run_encounter(db, L: int) -> void:
	var rounds_v: Array = []       # 胜利战斗的轮数
	var dmg_per_round: Array = []  # 每战斗 每轮承伤
	var dmg_total: Array = []
	var safe_opened: Array = []
	var clears: Array = []         # 每战斗清图（换新板）次数
	var buff_grants: Array = []    # attack_up+ac_up 授予数
	var losses := 0
	var timeouts := 0
	for i in range(N):
		var seed_val: int = SEED0 + i
		var r := _run_battle(db, seed_val, L)
		if r.result == "victory":
			rounds_v.append(r.rounds)
			dmg_total.append(r.hero_dmg)
			dmg_per_round.append(float(r.hero_dmg) / float(r.rounds))
			safe_opened.append(r.safe_opened)
			clears.append(r.board_swaps)
			buff_grants.append(r.buffs)
		elif r.result == "defeat":
			losses += 1
		else:
			timeouts += 1
	print("=== L%d · %d 种子（败 %d / 超时 %d）===" % [L, N, losses, timeouts])
	print("  胜利轮数   均值 %.2f  中位 %d  p10 %.1f  p90 %.1f  分布 %s" % [_mean(rounds_v), _median(rounds_v), _pct_f(rounds_v, 0.1), _pct_f(rounds_v, 0.9), _hist(rounds_v)])
	print("  每轮承伤   均值 %.2f  中位 %.1f  p90 %.1f" % [_mean(dmg_per_round), _median_f(dmg_per_round), _pct_f(dmg_per_round, 0.9)])
	print("  整场承伤   均值 %.1f  中位 %.0f（主角 max_hp=%d）" % [_mean(dmg_total), _median_f(dmg_total), int(db.hero.max_hp)])
	print("  开安全格   均值 %.1f  中位 %d" % [_mean(safe_opened), _median(safe_opened)])
	print("  清图(换板) 均值 %.2f  中位 %d" % [_mean(clears), _median(clears)])
	print("  攻防buff授予 均值 %.2f" % [_mean(buff_grants)])


func _run_battle(db, seed_val: int, L: int) -> Dictionary:
	var rng = load("res://core/rng_service.gd").new()
	rng.set_master_seed(seed_val)
	var settlement = load("res://core/battle_orchestrator.gd").new(db, rng)
	var out := {"rounds": 0, "result": "", "hero_dmg": 0, "safe_opened": 0, "board_swaps": 0, "buffs": 0}
	settlement.battle_finished.connect(func(payload): out.result = payload.get("result", ""))
	settlement.board_changed.connect(func(): out.board_swaps += 1)
	settlement.step_row.connect(func(row):
		if row.type == "damage" and row.source_class == "enemy_action":
			out.hero_dmg += int(row.value)
		elif row.type == "effect" and row.source_class == "safe_cell" and (row.effect_id == "attack_up" or row.effect_id == "ac_up"):
			out.buffs += 1)
	settlement.minesweeper.cell_revealed.connect(func(evt):
		if evt.kind == "safe" and evt.channel != "initial":
			out.safe_opened += 1)
	if not settlement.begin_battle({"level_index": L, "node_depth": 0, "hero_hp": int(db.hero.max_hp)}):
		return out
	var guard_rounds := 40
	while out.result == "" and guard_rounds > 0:
		guard_rounds -= 1
		out.rounds += 1
		BattleDriver.drive_round(settlement, func() -> bool: return out.result == "")
	if out.result == "":
		out.result = "timeout"
	return out



func _mean(a: Array) -> float:
	if a.is_empty():
		return 0.0
	var t := 0.0
	for v in a:
		t += float(v)
	return t / a.size()


func _median(a: Array) -> int:
	return int(_median_f(a))


func _median_f(a: Array) -> float:
	if a.is_empty():
		return 0.0
	var b := a.duplicate()
	b.sort()
	return float(b[b.size() / 2])


func _pct_f(a: Array, p: float) -> float:
	if a.is_empty():
		return 0.0
	var b := a.duplicate()
	b.sort()
	return float(b[mini(b.size() - 1, int(p * b.size()))])


func _hist(a: Array) -> String:
	var h := {}
	for v in a:
		h[v] = int(h.get(v, 0)) + 1
	var keys := h.keys()
	keys.sort()
	var parts: Array = []
	for k in keys:
		parts.append("%d轮×%d" % [k, h[k]])
	return "{" + ", ".join(parts) + "}"