《经济物理学》期末论文代码附件

单次测试获得详细数据：

import random


#依次读入agentA,agentB对于分别生产牛奶与苹果的效率
agentA_apple_eff    = int(input("agentA牛奶生产效率："))
agentA_milk_eff = int(input("agentA苹果生产效率："))
agentB_apple_eff    = int(input("agentB牛奶生产效率："))
agentB_milk_eff = int(input("agentB苹果生产效率："))


#agentA,agentB生产牛奶的时间
agentA_apple_time    = random.randint(0,24)
agentA_milk_time = 24-agentA_apple_time
agentB_apple_time    = random.randint(0,24)
agentB_milk_time = 24-agentB_apple_time




#记录agentA,agentB在每次实验中的效用值以及生产时间
agentA_eff_lst = []
agentB_eff_lst = []
agentA_apple_time_lst = []
agentB_apple_time_lst = []
agentA_milk_time_lst = []
agentB_milk_time_lst = []


#默认试验次数为100次
ex_time = 100


#agentA与agentB所拥有的牛奶与苹果（分别表示牛奶与苹果）
agentA_have = [0,0]
agentB_have = [0,0]


#交易函数（当某人苹果比牛奶多且另一人牛奶比苹果多的时候，尽量交换多余部分）
def exchange():
    if (agentA_have[0] > agentA_have[1]) :
        if (agentB_have[0] < agentB_have[1]) :
            exchange_num = min(agentA_have[0] - agentA_have[1],agentB_have[1] - agentB_have[0])
            agentA_have[0] -= exchange_num//2
            agentA_have[1] += exchange_num//2
            agentB_have[0] += exchange_num//2
            agentB_have[1] -= exchange_num//2
    elif (agentA_have[0] < agentA_have[1]) :
        if (agentB_have[0] > agentB_have[1]) :
            exchange_num = min(agentA_have[1] - agentA_have[0],agentB_have[0] - agentB_have[1])
            agentA_have[0] += exchange_num//2
            agentA_have[1] -= exchange_num//2
            agentB_have[0] -= exchange_num//2
            agentB_have[1] += exchange_num//2


#获取效用函数值
def Get_Eff():
    #global agentA_eff
    #global agentB_eff
    agentA_eff = 3*min(agentA_have[0],agentA_have[1]) + abs(agentA_have[0]-agentA_have[1])
    agentB_eff = 3*min(agentB_have[0],agentB_have[1]) + abs(agentB_have[0]-agentB_have[1])
    agentA_eff_lst.append(agentA_eff)
    agentB_eff_lst.append(agentB_eff)


#根据生产效率与生产时间生产
def production():
    agentA_have[0] = agentA_apple_eff*agentA_apple_time
    agentA_have[1] = agentA_milk_eff*agentA_milk_time
    agentB_have[0] = agentB_apple_eff*agentB_apple_time
    agentB_have[1] = agentB_milk_eff*agentB_milk_time


#输出函数
def printf(time):
    print("试验次数：   ","%5d"%(time+1))
    print("%13s"%"agentA","|","%16d"%agentA_apple_time,"|","%16d"%agentA_milk_time)
    print("%13s"%"agentB","|","%16d"%agentB_apple_time,"|","%16d"%agentB_milk_time)
    print("总效用为：   ","%5d"%(agentA_eff_lst[time] + agentB_eff_lst[time]))
    print()

print("%13s"%"","|","%9s"%"生产牛奶的时间","|","%9s"%"生产苹果的时间")

#首次实验
production()
exchange()
Get_Eff()
printf(0)
print()

#生产时间进行震荡
t1=random.randint(-3,3)
t2=random.randint(-3,3)
if(agentA_apple_time+t1<=24 and agentA_apple_time+t1>=0):
    agentA_apple_time += t1
    agentA_milk_time -= t1
if(agentB_apple_time+t1<=24 and agentB_apple_time+t1>=0):
    agentB_apple_time += t2
    agentB_milk_time -= t2
agentA_apple_time_lst.append(agentA_apple_time)
agentB_apple_time_lst.append(agentB_apple_time)
agentA_milk_time_lst.append(agentA_milk_time)
agentB_milk_time_lst.append(agentB_milk_time)


#第二次实验
production()
exchange()
Get_Eff()
printf(1)
print()
agentA_apple_time_lst.append(agentA_apple_time)
agentB_apple_time_lst.append(agentB_apple_time)
agentA_milk_time_lst.append(agentA_milk_time)
agentB_milk_time_lst.append(agentB_milk_time)


#进行循环实验
for i in range(2,ex_time):

    #若效用降低，则回溯到前一次的生产时间，否则根据上次实验效用调整生产时间
    if(agentA_eff_lst[i-1]+agentB_eff_lst[i-1]<agentA_eff_lst[i-2]+agentB_eff_lst[i-2]):
        agentA_apple_time=agentA_apple_time_lst[i-2]
        agentA_milk_time=agentA_milk_time_lst[i-2]
        agentB_apple_time=agentB_apple_time_lst[i-2]
        agentB_milk_time=agentB_milk_time_lst[i-2]
    else:
        t1=random.randint(-2,2)
        t2=random.randint(-2,2)
        if(agentA_apple_time+t1<=24 and agentA_apple_time+t1>=0):
            agentA_apple_time += t1
            agentA_milk_time -= t1
        if(agentB_apple_time+t2<=24 and agentB_apple_time+t2>=0):
            agentB_apple_time += t2
            agentB_milk_time -= t2
    agentA_apple_time_lst.append(agentA_apple_time)
    agentB_apple_time_lst.append(agentB_apple_time)
    agentA_milk_time_lst.append(agentA_milk_time)
    agentB_milk_time_lst.append(agentB_milk_time)
    production()
    exchange()
    Get_Eff()
    printf(i)
    

多次测试获得概率：

import random

#改变量dp
dp=int(input("请输入改变量i："))
#实验次数T
T=int(input("请输入试验次数T："))
#手动计算得出最大值
max=int(input("请输入整体最大效用和："))
#效率
agentA_apple_eff    = int(input("agentA牛奶生产效率："))
agentA_milk_eff     = int(input("agentA苹果生产效率："))
agentB_apple_eff    = int(input("agentB牛奶生产效率："))
agentB_milk_eff     = int(input("agentB苹果生产效率："))

def exchange():
    if (agentA_have[0] > agentA_have[1]) :
        if (agentB_have[0] < agentB_have[1]) :
            exchange_num = min(agentA_have[0] - agentA_have[1],agentB_have[1] - agentB_have[0])
            agentA_have[0] -= exchange_num//2
            agentA_have[1] += exchange_num//2
            agentB_have[0] += exchange_num//2
            agentB_have[1] -= exchange_num//2
    elif (agentA_have[0] < agentA_have[1]) :
        if (agentB_have[0] > agentB_have[1]) :
            exchange_num = min(agentA_have[1] - agentA_have[0],agentB_have[0] - agentB_have[1])
            agentA_have[0] += exchange_num//2
            agentA_have[1] -= exchange_num//2
            agentB_have[0] -= exchange_num//2
            agentB_have[1] += exchange_num//2


def Get_Eff():
    #global agentA_eff
    #global agentB_eff
    agentA_eff = 3*min(agentA_have[0],agentA_have[1]) + abs(agentA_have[0]-agentA_have[1])
    agentB_eff = 3*min(agentB_have[0],agentB_have[1]) + abs(agentB_have[0]-agentB_have[1])
    agentA_eff_lst.append(agentA_eff)
    agentB_eff_lst.append(agentB_eff)


def production():
    agentA_have[0] = agentA_apple_eff*agentA_apple_time
    agentA_have[1] = agentA_milk_eff*agentA_milk_time
    agentB_have[0] = agentB_apple_eff*agentB_apple_time
    agentB_have[1] = agentB_milk_eff*agentB_milk_time


wa=0
for j in range(1000):
    agentA_apple_time    = random.randint(0,24)
    agentA_milk_time = 24-agentA_apple_time
    agentB_apple_time    = random.randint(0,24)
    agentB_milk_time = 24-agentB_apple_time
    agentA_eff_lst = []
    agentB_eff_lst = []
    agentA_apple_time_lst = []
    agentB_apple_time_lst = []
    agentA_milk_time_lst = []
    agentB_milk_time_lst = []
    agentA_have = [0,0]
    agentB_have = [0,0]
    #print(wa)
    production()
    exchange()
    Get_Eff()
    t1=random.randint(-dp,dp)
    t2=random.randint(-dp,dp)
    if(agentA_apple_time+t1<=24 and agentA_apple_time+t1>=0):
        agentA_apple_time += t1
        agentA_milk_time -= t1
    if(agentB_apple_time+t1<=24 and agentB_apple_time+t1>=0):
        agentB_apple_time += t2
        agentB_milk_time -= t2
    agentA_apple_time_lst.append(agentA_apple_time)
    agentB_apple_time_lst.append(agentB_apple_time)
    agentA_milk_time_lst.append(agentA_milk_time)
    agentB_milk_time_lst.append(agentB_milk_time)
    production()
    exchange()
    Get_Eff()
    agentA_apple_time_lst.append(agentA_apple_time)
    agentB_apple_time_lst.append(agentB_apple_time)
    agentA_milk_time_lst.append(agentA_milk_time)
    agentB_milk_time_lst.append(agentB_milk_time)
    i=1
    #进行循环实验
    while(agentA_eff_lst[i] + agentB_eff_lst[i]<max):
        i+=1
        if i>T:
            wa+=1
            break
        #若效用降低，则回溯到前一次的生产时间，否则根据上次实验效用调整生产时间
        if(agentA_eff_lst[i-1]+agentB_eff_lst[i-1]<agentA_eff_lst[i-2]+agentB_eff_lst[i-2]):
            agentA_apple_time=agentA_apple_time_lst[i-2]
            agentA_milk_time=agentA_milk_time_lst[i-2]
            agentB_apple_time=agentB_apple_time_lst[i-2]
            agentB_milk_time=agentB_milk_time_lst[i-2]
        else:
            t1=random.randint(-dp,dp)
            t2=random.randint(-dp,dp)
            if(agentA_apple_time+t1<=24 and agentA_apple_time+t1>=0):
                agentA_apple_time += t1
                agentA_milk_time -= t1
            if(agentB_apple_time+t2<=24 and agentB_apple_time+t2>=0):
                agentB_apple_time += t2
                agentB_milk_time -= t2
        agentA_apple_time_lst.append(agentA_apple_time)
        agentB_apple_time_lst.append(agentB_apple_time)
        agentA_milk_time_lst.append(agentA_milk_time)
        agentB_milk_time_lst.append(agentB_milk_time)
        production()
        exchange()
        Get_Eff()
        
print("概率为：",wa/1000)