我的 Python 散景图未在浏览器中显示：“raise ProtocolError（”令牌已过期。

问：

我正在联系一个基于 Python 代理的示例代码，我一直在研究以模拟灾难期间的疏散。在大多数情况下，我的逻辑似乎在按预期运作。但是，我的交互式模拟图遇到了一个问题，它的行为不符合预期。

我对 Python 中的库比较陌生。我的目的是在浏览器中显示交互式绘图，但不幸的是，它在将近一个小时后继续超时。bokeh

我在下面包含了我的完整代码供您参考。

我将非常感谢您能提供的任何帮助。

先谢谢你。

from mesa import Agent, Model
from mesa.time import RandomActivation
from mesa.space import MultiGrid
from mesa.datacollection import DataCollector
import random
from bokeh.plotting import figure, show, curdoc
from bokeh.models import ColumnDataSource
# from bokeh.io import push_notebook
from bokeh.io import push_notebook, output_notebook
from bokeh.layouts import column
from bokeh.server.server import Server


class Person(Agent):
    """
    A class representing a person in the evacuation model.
    """

    def __init__(self, unique_id, model):
        """
        Initialize a person agent.

        Args:
            unique_id (int): Unique identifier for the agent.
            model: Reference to the model containing the agent.
        """
        super().__init__(unique_id, model)
        self.evacuated = False

    def move(self):
        """
        Move the person agent to a random neighboring cell if within grid boundaries and not evacuated.
        """
        if not self.evacuated:
            possible_moves = self.model.grid.get_neighborhood(
                self.pos,
                moore=True,
                include_center=False
            )
            new_position = random.choice(possible_moves)
            if self.model.grid.is_cell_empty(new_position):
                self.model.grid.move_agent(self, new_position)

    def step(self):
        """
        Method called in each step of the model's execution.
        """
        if not self.evacuated:
            self.move()
            x, y = self.pos
            if x < 0 or x >= self.model.grid.width or y < 0 or y >= self.model.grid.height:
                self.evacuated = True


class EvacuationModel(Model):
    """
    A class representing the evacuation model.
    """

    def __init__(self, width, height, num_agents):
        """
        Initialize the evacuation model.

        Args:
            width (int): Width of the grid.
            height (int): Height of the grid.
            num_agents (int): Number of person agents in the model.
        """
        self.num_agents = num_agents
        self.grid = MultiGrid(width, height, True)
        self.schedule = RandomActivation(self)

        # Create agents
        for i in range(self.num_agents):
            agent = Person(i, self)
            x = random.randrange(self.grid.width)
            y = random.randrange(self.grid.height)
            self.grid.place_agent(agent, (x, y))
            self.schedule.add(agent)

        # Bokeh setup
        self.source = ColumnDataSource(data={'x': [], 'y': [], 'evacuated': []})
        self.plot = figure(width=800, height=800, title='Agent Evacuation Process',
                           x_range=[0, self.grid.width], y_range=[0, self.grid.height])
        self.plot.square(x='x', y='y', source=self.source, size=20, color='blue')

        self.datacollector = DataCollector(
            agent_reporters={"Evacuated": "evacuated"}
        )

    def step(self):
        """
        Method called in each step of the model's execution.
        Collects data and advances the model by one step.
        """
        self.datacollector.collect(self)
        self.schedule.step()

        # Update Bokeh data
        agent_data = [{'x': agent.pos[0], 'y': agent.pos[1], 'evacuated': agent.evacuated} for agent in
                      self.schedule.agents]
        self.source.data = {'x': [data['x'] for data in agent_data],
                            'y': [data['y'] for data in agent_data],
                            'evacuated': [data['evacuated'] for data in agent_data]}
        push_notebook()


# Set up the server
def modify_doc(doc):
    width = 10
    height = 10
    num_agents = 50

    evacuation_model = EvacuationModel(width, height, num_agents)

    # Run the simulation for 10 steps with interactive plotting
    output_notebook()
    show(evacuation_model.plot, notebook_handle=True)

    for i in range(10):
        evacuation_model.step()


# To access the visualization, run this server code in your Python environment
server = Server({'/': modify_doc}, num_procs=1)
server.start()

if __name__ == '__main__':
    print('Opening Bokeh application on http://localhost:5006/')
    server.io_loop.add_callback(server.show, "/")
    server.io_loop.start()