extends RefCounted

# 用例：核心公式（MultiplierSet / PrestigeModel / OfflineModel）

func run(a, _data) -> void:
	# ---- MultiplierSet 三乘区 + 软上限 ----
	var m := MultiplierSet.new(16.0, 8.0, 64.0)
	m.set_click_levels(4, 0.0, 0.01)
	a.near(m.click_mult(), 16.0, 1e-9, "点击区 4 级 = ×16")
	m.set_click_levels(5, 0.0, 0.01)
	a.near(m.click_mult(), 16.0, 1e-9, "点击区 5 级仍钳 ×16")
	m.set_gen_eff("gen_01_youhun", 6)
	a.near(m.gen_mult("gen_01_youhun"), 7.0, 1e-9, "班底区 6 级 = ×7")
	m.set_gen_eff("gen_01_youhun", 99)
	a.near(m.gen_mult("gen_01_youhun"), 8.0, 1e-9, "班底区钳 ×8")
	m.set_global_add(63.0)
	a.near(m.global_mult(), 64.0, 1e-9, "全局区 ×64")
	m.set_global_add(100.0)
	a.near(m.global_mult(), 64.0, 1e-9, "全局区钳 ×64")
	m.set_click_levels(4, 8.0, 0.01)
	a.near(m.click_value(1.0, 1000.0), 96.0, 1e-6, "click_value = 1×16 + 1000×8%")

	# ---- PrestigeModel ----
	a.eq(PrestigeModel.suihui_gain(1.5e9, 1e6, 5.0, 0.0, 0.0), 193, "宿慧 1.5B → 193")
	a.eq(PrestigeModel.suihui_gain(1.25e7, 1e6, 5.0, 0.0, 0.0), 17, "宿慧 12.5M → 17")
	a.eq(PrestigeModel.suihui_gain(1.5e9, 1e6, 5.0, 0.0, 0.3), 135, "宿慧 30% 削减 → 135")
	a.eq(PrestigeModel.suihui_gain(1.5e9, 1e6, 5.0, 0.45, 0.0), 279, "宿慧 m03×3 → 279")
	a.eq(PrestigeModel.suihui_gain(0.0, 1e6, 5.0, 0.0, 0.0), 0, "零累计 → 0 宿慧")
	a.eq(PrestigeModel.wrath_layer_cost(1, 8.0, 1.8), 8, "怨煞层 1 成本 8")
	a.eq(PrestigeModel.wrath_layer_cost(2, 8.0, 1.8), 28, "怨煞层 2 成本 28")
	a.eq(PrestigeModel.wrath_layer_cost(22, 8.0, 1.8), 2087, "怨煞层 22 成本 2087")
	a.near(PrestigeModel.wrath_penalty(10, 0.03, 0.3, 0.0), 0.3, 1e-9, "冤气削减封顶 30%")
	a.near(PrestigeModel.wrath_penalty(10, 0.03, 0.3, 0.15), 0.15, 1e-9, "m07 改 15%")
	a.near(PrestigeModel.wrath_penalty(5, 0.03, 0.3, 0.0), 0.15, 1e-9, "5 层 = 15%")
	a.eq(PrestigeModel.skip_count(23, 5), 4, "skip 23/5 = 4")
	a.eq(PrestigeModel.skip_count(23, 4), 5, "skip 23/4 = 5（m04）")
	a.near(PrestigeModel.restart_target(0), 1.0, 1e-9, "重开曲线 R1")
	a.near(PrestigeModel.restart_target(3), 0.3, 1e-9, "重开曲线 R4")
	a.near(PrestigeModel.restart_target(4), 0.25, 1e-9, "重开曲线 R5 触底")
	a.true_(PrestigeModel.enthrone_available(2, 2), "敕封：转世 2 可")
	a.true_(not PrestigeModel.enthrone_available(1, 2), "敕封：转世 1 不可")

	# ---- OfflineModel 分带 + 72h 封顶 + 时钟回拨 + 长明灯加法 + 硬顶 ----
	# W4 契约 v2（systems-spec §2.4/§2.5）：第三参数由 offline_mult（乘性）改为
	#   offline_add（加法，直接加在各档速率上，各档硬顶 100%）。
	var r1: Dictionary = OfflineModel.settle(3600.0, 10.0, 0.0, 2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1, 72.0)
	a.near(r1["effective_hours"], 1.0, 1e-9, "离线 1h = 1h 等效")
	a.near(r1["merit"], 36000.0, 1e-6, "离线 1h × 10/s")
	var r8: Dictionary = OfflineModel.settle(8.0 * 3600.0, 10.0, 0.0, 2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1, 72.0)
	a.near(r8["effective_hours"], 6.2, 1e-9, "离线 8h = 6.2h 等效（契约 v2：77.5%）")
	a.near(r8["merit"], 223200.0, 1e-6, "离线 8h 收益")
	var r24: Dictionary = OfflineModel.settle(24.0 * 3600.0, 10.0, 0.0, 2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1, 72.0)
	a.near(r24["effective_hours"], 12.6, 1e-9, "离线 24h = 12.6h 等效（契约 v2）")
	var r100: Dictionary = OfflineModel.settle(100.0 * 3600.0, 10.0, 0.0, 2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1, 72.0)
	a.near(r100["effective_hours"], 17.4, 1e-9, "离线 100h → 72h 封顶 = 17.4h 等效（24.2%）")
	var rneg: Dictionary = OfflineModel.settle(-5.0, 10.0, 0.0, 2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1, 72.0)
	a.near(rneg["merit"], 0.0, 1e-9, "时钟回拨 → 0")
	a.near(OfflineModel.ratio_8h_over_1h(2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1), 6.2, 1e-9,
		"历史口径比率 6.2（契约 v2 起门 #9 改判等效小时，见 SimGates.gate_offline_v2）")
	# 长明灯加法：+30%（6 级）⇒ 2-8h 档 70%+30% = 100%（硬顶）⇒ 8h = 8.0h（效率 100%）
	var r8l: Dictionary = OfflineModel.settle(8.0 * 3600.0, 10.0, 0.30, 2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1, 72.0)
	a.near(r8l["effective_hours"], 8.0, 1e-9, "长明灯满级 8h = 8.0h 等效（硬顶 100%）")
	a.near(r8l["merit"], 288000.0, 1e-6, "长明灯满级 8h 收益")
	# 加法不越过硬顶：+55%（6 级 + m05）仍 = 8.0h；8-24h 档 40%+30% = 70%
	var r8m: Dictionary = OfflineModel.settle(8.0 * 3600.0, 10.0, 0.55, 2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1, 72.0)
	a.near(r8m["effective_hours"], 8.0, 1e-9, "加法 +55% 仍钳 8.0h（0-2h/2-8h 双档顶格）")
	var r24l: Dictionary = OfflineModel.settle(24.0 * 3600.0, 10.0, 0.30, 2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1, 72.0)
	a.near(r24l["effective_hours"], 2.0 + 6.0 + 16.0 * 0.7, 1e-9, "长明灯满级 24h = 19.2h（8-24h 档 70%）")
	# 效率硬顶：任意加成下等效 ≤ 实际（离线不得优于在线）
	for dur_h in [1.0, 8.0, 24.0, 72.0]:
		for add in [0.0, 0.30, 0.55, 5.0]:
			var rr: Dictionary = OfflineModel.settle(dur_h * 3600.0, 10.0, add,
				2.0, 1.0, 8.0, 0.7, 24.0, 0.4, 0.1, 72.0)
			a.true_(float(rr["effective_hours"]) <= dur_h + 1e-9,
				"效率硬顶：%gh 离线 加法 +%g ⇒ 等效 %.2fh ≤ %gh" % [dur_h, add, float(rr["effective_hours"]), dur_h])

	# ---- BigNumber 红线 ----
	a.true_(BigNumber.assert_within(1e13, "test"), "1e13 不过红线")
	a.true_(not BigNumber.assert_within(1e15, "test"), "1e15 触红线")