&引用；“无”不是发电机；Python中的El-Farol算法_Python_Class_Generator_Netlogo

&引用；“无”不是发电机；Python中的El-Farol算法

python class netlogo

&引用；“无”不是发电机；Python中的El-Farol算法,python,class,generator,netlogo,Python,Class,Generator,Netlogo,我正在用Python从Netlogo编写El Farol模型。但是，我一直收到这个错误，我不知道如何继续： Traceback (most recent call last): File "<ipython-input-444-99b2c0f618f2>", line 3, in <module> village.run() File "<ipython-input-441-cb8708c7230d>", line 143, in run

我正在用Python从Netlogo编写El Farol模型。但是，我一直收到这个错误，我不知道如何继续：

Traceback (most recent call last):
  File "<ipython-input-444-99b2c0f618f2>", line 3, in <module>
    village.run()
  File "<ipython-input-441-cb8708c7230d>", line 143, in run
    Agent(self)
  File "<ipython-input-441-cb8708c7230d>", line 22, in __init__
    self.village.env.process(self.move())
  File "C:\Users\jkowalczyk002\AppData\Local\Continuum\Anaconda3\lib\site-packages\simpy\events.py", line 272, in __init__
    raise ValueError('%s is not a generator.' % generator)
ValueError: None is not a generator.

它应该从

move

gen\u loc

najlepsza

（英语-最佳）->

do\u baru

（E-到bar），但它得到的是

None

全部代码：

import simpy
import random
import math

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.colors
from gridplot import GridPlot

white_green = matplotlib.colors.ListedColormap(["green","white"])
plt.register_cmap(cmap=white_green)

class Agent:
    def __init__(self,village):
        self.village = village
        self.color = 1
        self.loc = self.gen_loc()
        self.village.env.process(self.move())

    def gen_loc(self):
        if self.najlepsza()<self.village.threshold:
            self.loc = (random.randrange(math.floor(self.village.village_dim/2)+1,self.village.village_dim),
                        random.randrange(math.floor(self.village.village_dim/2)+1,self.village.village_dim))
            if self.loc not in self.village.occupied:
                self.village.occupied[self.loc] = self
        elif random.random()>0.33:
            self.loc =(random.randrange(0,math.floor(self.village.village_dim/2)-1,
                       random.randrange(0,self.village.village_dim)))
            if self.loc not in self.village.occupied:
                self.village.occupied[self.loc] = self
        else:
            self.loc =(random.randrange(math.floor(self.village.village_dim/2),self.village.village_dim),
            random.randrange(0,math.floor(self.village.village_dim/2)-1))
            if self.loc not in self.village.occupied:
                self.village.occupied[self.loc] = self

    def najlepsza(self):
        if self.village.env.now<2:
                strategia=[]
                for j in range(village.liczbastr):
                    for i in range(village.memorysize):
                        strategia.append(random.random())
                sumy=[]
                for j in range(village.liczbastr):
                    sumy.append(sum(strategia[i+village.memorysize*j] for i in range(village.memorysize)))
                strategia1=[]
                for j in range(village.liczbastr):
                    for i in range(village.memorysize):
                        strategia1.append(strategia[i+j*village.memorysize]/sumy[j])
                listypre=[strategia1[i:i+village.memorysize] for i in range(0, village.memorysize*village.liczbastr, village.memorysize)]
                zestaw1=np.array(listypre)
        historia1=village.historia
        wynikstrat=[]
        for j in range(village.liczbastr):
            for k in range(village.memorysize):
                wynikstrat.append(sum(historia1[-i-2-k]*zestaw1[j,-i-1] for i in range(village.memorysize)))
        listypre=[]
        listypre=[wynikstrat[i:i+village.memorysize] for i in range(0, village.memorysize*village.liczbastr, village.memorysize)]
        tabela1=np.array(listypre)+10
        wynik=village.memorysize*100
        naj=village.liczbastr
        pred=0
        for j in range(village.liczbastr):
            if (sum(abs(tabela1[j,i]-historia1[-i-1]) for i in range(village.memorysize)))<wynik:
                wynik=sum(abs(tabela1[j,i]-historia1[-i-1]) for i in range(village.memorysize))
                naj=j
        pred=sum(historia1[-1-i]*zestaw1[naj,-i-1] for i in range(village.memorysize))
        return(pred)

    def do_baru(self):
        return(self.najlepsza() <= self.village.threshold)

    def move(self):
        new_loc = self.gen_loc()
        del self.village.occupied[self.loc]
        self.loc = new_loc
        self.village.data[self.loc] = 1

class Village:
    def __init__(self, env, village_dim, memorysize, liczbastr,threshold):
        self.village_dim = village_dim
        self.memorysize = memorysize
        self.liczbastr = liczbastr
        self.threshold = threshold
        self.env=env
        self.historia=self.historialos()

    def historialos(self):
        if self.env.now<2:
            historia=[]
            for i in range(2*self.memorysize):
                historia.append(random.randint(0,100))
        return(historia)

    def histupdate(self):
        for i in range(2*self.memorysize):
            self.historia[i-1]=self.historia[i]
        self.historia[2*self.memorysize-1]=self.attendance()
        return(self.historia)

    def attendance(self):
        attend=0
        for v in self.occupied.values():
            if v.do_baru():
                attend = attend+1

    def plot(self, start):
        self.data = np.zeros((self.village_dim, self.village_dim))
        for agent in self.occupied:
            self.data[agent] = self.occupied[agent].color
        self.gp = GridPlot(self.data, ["white", "green"])

    def run(self):
        self.occupied = dict()
        agent_count = 100
        print(self.historia)
        for i in range(agent_count):
            Agent(self)
        self.env.process(self.plot())
        self.histupdate()

env = simpy.Environment()
village = Village(env, 50,10,5,50)
village.run()

导入simpy
随机输入
输入数学
将matplotlib.pyplot作为plt导入
将numpy作为np导入
导入matplotlib.colors
从gridplot导入gridplot
白色\绿色=matplotlib.colors.ListedColormap（[“绿色”、“白色”]）
plt.寄存器\u cmap（cmap=白色\u绿色）
类代理：
定义初始（自我，村庄）：
self.village=村庄
self.color=1
self.loc=self.gen_loc（）
self.village.env.process（self.move（））
def gen_loc（自身）：
如果self.najlepsza（）0.33：
self.loc=（random.randrange（0，数学层（self.village.village_dim/2）-1，
random.randrange（0，self.village.village_dim）））
如果self.loc不在self.village.occumped内：
self.village.och[self.loc]=self
其他：
self.loc=（random.randrange（数学层（self.village.village\u dim/2）、self.village.village\u dim），
random.randrange（0，数学层（self.village.village_dim/2）-1））
如果self.loc不在self.village.occumped内：
self.village.och[self.loc]=self
def najlepsza（自身）：
如果self.village.env.now根据，则过程
方法需要一个生成器参数，但是您没有从移动
方法中产生任何结果，因此您会得到错误。
将新属性添加到初始化
方法之外的类实例被认为是一个非常坏的习惯，但您还是这样做了。应在初始化步骤中创建所有属性。如果没有正确的值，请将它们设置为None，但将它们放在它们所属的位置。
import simpy
import random
import math

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.colors
from gridplot import GridPlot

white_green = matplotlib.colors.ListedColormap(["green","white"])
plt.register_cmap(cmap=white_green)

class Agent:
    def __init__(self,village):
        self.village = village
        self.color = 1
        self.loc = self.gen_loc()
        self.village.env.process(self.move())

    def gen_loc(self):
        if self.najlepsza()<self.village.threshold:
            self.loc = (random.randrange(math.floor(self.village.village_dim/2)+1,self.village.village_dim),
                        random.randrange(math.floor(self.village.village_dim/2)+1,self.village.village_dim))
            if self.loc not in self.village.occupied:
                self.village.occupied[self.loc] = self
        elif random.random()>0.33:
            self.loc =(random.randrange(0,math.floor(self.village.village_dim/2)-1,
                       random.randrange(0,self.village.village_dim)))
            if self.loc not in self.village.occupied:
                self.village.occupied[self.loc] = self
        else:
            self.loc =(random.randrange(math.floor(self.village.village_dim/2),self.village.village_dim),
            random.randrange(0,math.floor(self.village.village_dim/2)-1))
            if self.loc not in self.village.occupied:
                self.village.occupied[self.loc] = self

    def najlepsza(self):
        if self.village.env.now<2:
                strategia=[]
                for j in range(village.liczbastr):
                    for i in range(village.memorysize):
                        strategia.append(random.random())
                sumy=[]
                for j in range(village.liczbastr):
                    sumy.append(sum(strategia[i+village.memorysize*j] for i in range(village.memorysize)))
                strategia1=[]
                for j in range(village.liczbastr):
                    for i in range(village.memorysize):
                        strategia1.append(strategia[i+j*village.memorysize]/sumy[j])
                listypre=[strategia1[i:i+village.memorysize] for i in range(0, village.memorysize*village.liczbastr, village.memorysize)]
                zestaw1=np.array(listypre)
        historia1=village.historia
        wynikstrat=[]
        for j in range(village.liczbastr):
            for k in range(village.memorysize):
                wynikstrat.append(sum(historia1[-i-2-k]*zestaw1[j,-i-1] for i in range(village.memorysize)))
        listypre=[]
        listypre=[wynikstrat[i:i+village.memorysize] for i in range(0, village.memorysize*village.liczbastr, village.memorysize)]
        tabela1=np.array(listypre)+10
        wynik=village.memorysize*100
        naj=village.liczbastr
        pred=0
        for j in range(village.liczbastr):
            if (sum(abs(tabela1[j,i]-historia1[-i-1]) for i in range(village.memorysize)))<wynik:
                wynik=sum(abs(tabela1[j,i]-historia1[-i-1]) for i in range(village.memorysize))
                naj=j
        pred=sum(historia1[-1-i]*zestaw1[naj,-i-1] for i in range(village.memorysize))
        return(pred)

    def do_baru(self):
        return(self.najlepsza() <= self.village.threshold)

    def move(self):
        new_loc = self.gen_loc()
        del self.village.occupied[self.loc]
        self.loc = new_loc
        self.village.data[self.loc] = 1

class Village:
    def __init__(self, env, village_dim, memorysize, liczbastr,threshold):
        self.village_dim = village_dim
        self.memorysize = memorysize
        self.liczbastr = liczbastr
        self.threshold = threshold
        self.env=env
        self.historia=self.historialos()

    def historialos(self):
        if self.env.now<2:
            historia=[]
            for i in range(2*self.memorysize):
                historia.append(random.randint(0,100))
        return(historia)

    def histupdate(self):
        for i in range(2*self.memorysize):
            self.historia[i-1]=self.historia[i]
        self.historia[2*self.memorysize-1]=self.attendance()
        return(self.historia)

    def attendance(self):
        attend=0
        for v in self.occupied.values():
            if v.do_baru():
                attend = attend+1

    def plot(self, start):
        self.data = np.zeros((self.village_dim, self.village_dim))
        for agent in self.occupied:
            self.data[agent] = self.occupied[agent].color
        self.gp = GridPlot(self.data, ["white", "green"])

    def run(self):
        self.occupied = dict()
        agent_count = 100
        print(self.historia)
        for i in range(agent_count):
            Agent(self)
        self.env.process(self.plot())
        self.histupdate()

env = simpy.Environment()
village = Village(env, 50,10,5,50)
village.run()