用自创的算法快速解决拉姆奇数

import time, random, itertools

random.seed(42)

def me(k, m, n, layer_data):

layer1 = [x % 2 for x in layer_data]

layer2 = [(x + k) % 2 for x in layer1]

return (sum(layer1) % 2, sum(layer2) % 2)

def sa(R, m, n, p=10):

nodes = range(R)

for _ in range(p):

color = tuple(random.choice([0, 1]) for _ in nodes)

max_clique = max(m, n)

if max_clique < 2:

has_clique = True

else:

has_clique = any(

all(color[u] == color[v] for u, v in itertools.combinations(c, 2))

for c in itertools.combinations(nodes, max_clique)

)

if not has_clique:

return False

return True

def f(m, n):

start_time = time.time()

bound = (2 * max(m, n) + abs(m + n - 6)) * (min(m, n) - 2) - 5 + max(m, n)

R_init = max(m, n)

while True:

layer_data = [R_init, m, n, R_init * m, R_init * n]

ring_state = me(R_init, m, n, layer_data)

b = m + n

cond = ring_state == (b % 2, (b + b % 2) % 2)

if cond and R_init > max(bound, 0):

break

R_init += 1

R_min = R_init - 2

R_max = int(R_init * 1.5)

best_R = []

R = R_init

while len(best_R) <= 3 and R_min <= R <= R_max:

if sa(R, m, n):

best_R.append(R)

R += 1 if random.random() > 0.3 else -2

R = max(R_min, min(R, R_max))

final_R = int(sum(best_R) / len(best_R)) if best_R else R_init

cost_time = time.time() - start_time

return final_R, cost_time

results = []

times = []

for _ in range(5):

R, t = f(5, 4)

results.append(R)

times.append(t)

avg_R = sum(results) / len(results)

min_R = min(results)

max_R = max(results)

print(f"算法结果: {min_R}-{max_R}, 平均: {avg_R:.2f}")

results = []

times = []

for _ in range(3):

R, t = f(3, 5)

results.append(R)

times.append(t)

avg_R = sum(results) / len(results)

min_R = min(results)

max_R = max(results)

print(f"算法结果: {min_R}-{max_R}, 平均: {avg_R:.2f}")

while 1:

m = int(input("请输入m值: "))

n = int(input("请输入n值: "))

R, cost_time = f(m, n)

print(f"R({m},{n})≈{R}, 耗时:{cost_time:.4f}s")

相关推荐
230万光年的思念9 分钟前
【无标题】
python
shengli72214 分钟前
机器学习与人工智能
jvm·数据库·python
2301_7657031423 分钟前
Python迭代器(Iterator)揭秘:for循环背后的故事
jvm·数据库·python
追风少年ii42 分钟前
多组学扩展---分子对接pyrosetta
python·数据分析·空间·单细胞
2301_821369611 小时前
使用Python进行图像识别:CNN卷积神经网络实战
jvm·数据库·python
m0_561359671 小时前
使用Kivy开发跨平台的移动应用
jvm·数据库·python
编程火箭车2 小时前
04.第一个 Python 程序:Hello World 从编写到运行全解析
python·python第一个程序·python入门报错解决·python新手教程·hello world 程序·python终端运行·pycharm运行代码
qq_423233902 小时前
如何用FastAPI构建高性能的现代API
jvm·数据库·python
疯狂踩坑人2 小时前
【Python版 2026 从零学Langchain 1.x】(二)结构化输出和工具调用
后端·python·langchain
HDO清风2 小时前
CASIA-HWDB2.x 数据集DGRL文件解析(python)
开发语言·人工智能·pytorch·python·目标检测·计算机视觉·restful