Py.Cafe

import mesa
import solara
from matplotlib.figure import Figure
from mesa.visualization import SolaraViz, make_plot_component, make_space_component
from mesa.visualization.utils import update_counter
# Import the local MoneyModel.py
from MoneyModel import MoneyModel


def agent_portrayal(agent):
    size = 10
    color = "tab:red"
    if agent.wealth > 0:
        size = 50
        color = "tab:blue"
    return {"size": size, "color": color}

@solara.component
def Histogram(model):
    update_counter.get() # This is required to update the counter
    # Note: you must initialize a figure using this method instead of
    # plt.figure(), for thread safety purpose
    fig = Figure()
    ax = fig.subplots()
    wealth_vals = [agent.wealth for agent in model.agents]
    # Note: you have to use Matplotlib's OOP API instead of plt.hist
    # because plt.hist is not thread-safe.
    ax.hist(wealth_vals, bins=10)
    solara.FigureMatplotlib(fig)

model_params = {
    "n": {
        "type": "SliderInt",
        "value": 50,
        "label": "Number of agents:",
        "min": 10,
        "max": 100,
        "step": 1,
    },
    "width": 10,
    "height": 10,
}

# Create initial model instance
model1 = MoneyModel(50, 10, 10)

SpaceGraph = make_space_component(agent_portrayal)
GiniPlot = make_plot_component("Gini")

#Create the Dashboard
page = SolaraViz(
    model1,
    components=[SpaceGraph, GiniPlot, Histogram],
    model_params=model_params,
    name="Boltzmann Wealth Model",
)
# This is required to render the visualization in the Jupyter notebook
page