# import simpy
#
# def task(env, name, resource, start_time, duration):
#     """任务进程"""
#     yield env.timeout(start_time)  # 等待任务开始时间
#     print(f"{name} tries to use the resource at {env.now}")
#     with resource.request() as req:
#         yield req
#         print(f"{name} starts using the resource at {env.now}")
#         yield env.timeout(duration)
#         print(f"{name} finishes using the resource at {env.now}")
#
# # 创建仿真环境
# env = simpy.Environment()
#
# # 创建共享资源
# resource = simpy.Resource(env, capacity=1)
#
# # 启动任务进程
# env.process(task(env, "Task A", resource, 0, 5))  # 任务A，从时间0开始，持续5个时间单位
# env.process(task(env, "Task B", resource, 2, 3))  # 任务B，从时间2开始，持续3个时间单位
#
# # 运行仿真
# env.run()

import simpy
import numpy as np
import matplotlib.pyplot as plt

def task(env, name, resource, start_time, duration, conflicts,taskID):
    """任务进程"""
    yield env.timeout(start_time)  # 等待任务开始时间
    print(f"{name} tries to use the resource at {env.now}")
    with resource.request() as req:
        yield req
        print(f"{name} starts using the resource at {env.now}")
        if resource.count == 1:  # 检查是否发生冲突
            conflicts[0] = 1  # 记录冲突事件
        yield env.timeout(duration)
        print(f"{name} finishes using the resource at {env.now}")

def run_simulation(num_tasks, num_rounds):
    """运行多轮仿真"""
    # 存储冲突概率的列表
    conflict_probabilities = []
    task_start_times = np.random.randint(0, 10, num_tasks)  # 任务开始时间均匀分布
    count = 0
    for round_num  in range(num_rounds):
        count = count + 1
        print("=============第" + str(count) + "轮=============")
        # 创建仿真环境
        env = simpy.Environment()

        # 创建共享资源
        resource = simpy.Resource(env, capacity=1)

        # 记录冲突事件的列表
        conflicts = [0]

        # 仿真参数
        task_durations = np.random.normal(5, 1, num_tasks)  # 任务持续时间正态分布


        a = np.zeros([num_rounds,num_tasks])
        print(task_start_times[0],task_start_times[1])
        # 启动任务进程
        for i in range(num_tasks):
            ##conflicts[i] = 0
            env.process(task(env, f"Task {i}", resource, task_start_times[i], 10, conflicts, i))
        # 运行仿真
        env.run()
        print("=============end=============")
        for j in range(1, num_tasks):
            task_start_times[j] = task_start_times[j] + 10
        # 计算并记录冲突概率
        conflict_probabilities.append(conflicts[0] / num_tasks)

    return conflict_probabilities

# 参数设置
num_tasks = 2
num_rounds = 2

# 运行多轮仿真
conflict_probabilities = run_simulation(num_tasks, num_rounds)

# 绘制多个冲突概率曲线
plt.plot(conflict_probabilities)
plt.xlabel('Simulation Round')
plt.ylabel('Conflict Probability')
plt.title('Conflict Probability Across Simulation Rounds')
plt.grid(True)
plt.show()