Help

[BENFREDJRima-34]

Hello everyone, can anyone tell me where is the error?

from mesa import Agent, Model
from mesa.space import MultiGrid
from mesa.visualization.modules import CanvasGrid
import random
import time, enum, math 
from enum import Enum
import numpy as np
from mesa.time import RandomActivation
from mesa.visualization.ModularVisualization import ModularServer

class Inno(): 
    R_advantage = random.uniform(0,1)
    Copl = random.uniform(0,1)
    Cop = random.uniform(0,1)
    Obs = 1
    trb=0.5
class State (enum.IntEnum):
    Nadoter = 0
    Adoter= 1
class MyAgent(Agent):
    """An agent with fixed initial wealth."""
    def __init__(self, unique_id, model):
        super().__init__(unique_id, model)
        self.unique_id = unique_id
        self.state = State.Nadoter
        self.RA = Inno.R_advantage
        self.Acc = random.uniform(0,1) 
        self.Uncer = Inno.Copl
        self.Infl = 0 
        self.Compa= Inno.Cop
        self.Opens = random.uniform(0,1)
        self.Consci = random.uniform(0,1)
        self.Extr= random.uniform(0,1)
        self.Agre = random.uniform(0,1)
        self.Ner = random.uniform(0,1)
        self.innovativeness = random.uniform(0,1)
    def percept (self): 
        
        if self.state == State.Nadoter:
           if (self.Opens ==  random. uniform (0.75,1)) :
               self.innovativeness= random.uniform(0.75,1)
               self.Acc= random.uniform(0.75,1)
               self.Uncer= random.uniform(0,0.2)
               self.Compa=random.uniform(0.75,1) 
           if (self.Compa == random.uniform(0.75,1)) and (self.Acc > self.Uncer):
               self.state = State.Adoter
               
              
    def contact(self):
        neighbors =  self.model.grid.get_neighborhood(
            self.pos, True, include_center=False
        ) 
        adopter_neighbors = [ 
            agent
            for agent in self.model.grid.get_cell_list_contents( neighbors)
            if agent.state is State.Adoter
        ]
        
        def pers (self):
            while len (contact.adoter_neighbors)> 0:
                if self.Ner == random. uniform (0.8,1.0):
                    self.infl = random. uniform (0,0.2) 
                if (self.Extr == random. uniform (0.75,1.0)) or (self.Agree == random. uniform (0.75,1.0)) : 
                    self.Infl = random. uniform (0.8,1.0) 
                self.Uncer - Inno.trb and Inno.Obs
                self.RA + self.Infl
                  
    def decision (self):
            if (self.Compa > 0.99) and (self.Uncer<0.01):
                self.state = State.Adoter
            else:
                self.Uncer - Inno.trb
                if (self.Acc == random. uniform (0.75,1.0))& (self.Uncer==random. uniform (0,0.2) )& (self.RA > 0):
                    self.Compa = random.uniform(0.75,1)
                    self.state = State.Adoter
  
    def step(self):
        self.percept()
        self.contact()
        self.decision()
        
class MyModel(Model):
    """A model with some number of agents."""
    def __init__(self, N, width, height):
        self.num_agents = N
        self.grid = MultiGrid(width, height, True)
        self.schedule = RandomActivation(self)
        self.running = True 
        
        # Create agents
        for i in range(self.num_agents):
            a = MyAgent(i, self)
            

            # Add the agent to a random grid cell
            x = self.random.randrange(self.grid.width)
            y = self.random.randrange(self.grid.height)
            self.grid.place_agent(a, (x, y))
            self.schedule.add(a)
            #make some agents adoter at start
           
            adter =  np.random.choice([0,1], p=[0.9,0.1])
            if adter == 1:
                a.state = State.Adoter
            
    
    def step( self):
        self.schedule.step()

def agent_portrayal(agent):
    
    portrayal = {"Shape": "circle", "r": 0.5, "Filled": "true", "Layer": 0}
    if agent.state is State.Nadoter:
        portrayal["Color"] = "Red"
        
        portrayal["Color"] = ["#FF0000", "#FF9999"]
        portrayal["stroke_color"] = "#00FF00"
       
    else:
        portrayal["Color"] = ["#0000FF", "#9999FF"]
        portrayal["stroke_color"] = "#000000"
        return portrayal

grid = CanvasGrid(agent_portrayal,10,10,500,500)
server= ModularServer(MyModel, [grid],
                       " Model", {"N":100,"width":10,"height":10}
                      )
server.port = 8521 # The default
server.launch()

the problem is: Once, I run the program in the browser will display an environment with some blue agents, however, the program is planned to display red agents and some blue agents and when I start the simulation the red agents will change its color to blue

[rht]

Just a note: make sure to use triple backticks when formatting multi-line code: https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/creating-and-highlighting-code-blocks. I had to manually edit your posts in the past, but would be great if it is correctly formatted from now on.

[BENFREDJRima-34]

Thank you for the information, every time, I can't make it.

[rht]

The problem is this function

def agent_portrayal(agent):
    
    portrayal = {"Shape": "circle", "r": 0.5, "Filled": "true", "Layer": 0}
    if agent.state is State.Nadoter:
        portrayal["Color"] = "Red"
        
        portrayal["Color"] = ["#FF0000", "#FF9999"]
        portrayal["stroke_color"] = "#00FF00"
       
    else:
        portrayal["Color"] = ["#0000FF", "#9999FF"]
        portrayal["stroke_color"] = "#000000"
        return portrayal

return portrayal is accidentally indented, and so it only returns the portrayal dict on the else clause. Once you dedent it, it should work. Moral of the story is: be careful with Python indentation.

[rht]

That's because the probability for the state change in any of your code is practically 0. (self.Uncer== 0) is not going to happen for any continuous random variable. You have to specify an interval instead, e.g. lower <= self.Uncer <= upper.

[BENFREDJRima-34]

def decision (self):
            if (0.75<self.Compa < 0.99) and (0<self.Uncer<0.01):
                self.state = State.Adoter
            else:
                self.Uncer - Inno.trb
                if (self.Acc == random. uniform (0.75,1.0))& (self.Uncer==random. uniform (0,0.2) )& (self.RA > 0):
                    self.Compa = random.uniform(0.75,1)
                    self.state = State.Adoter

[BENFREDJRima-34]

@rht, like this??? can you explain to me more where I should change!!!!

[rht]

You should search the internet for "probability of continuous random variable", which has several articles which explain it better than me. self.Compa > 0.99 is better than 1, because then the probability of this happening is 1%. But 1% is still very unlikely.

[BENFREDJRima-34]

OK, I'll look it up