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soil/examples/mesa/wealth.py
J. Fernando Sánchez 880a9f2a1c black formatting
2022-10-17 20:23:57 +02:00

88 lines
2.4 KiB
Python

from mesa import Agent, Model
from mesa.space import MultiGrid
from mesa.time import RandomActivation
from mesa.datacollection import DataCollector
from mesa.batchrunner import BatchRunner
def compute_gini(model):
agent_wealths = [agent.wealth for agent in model.schedule.agents]
x = sorted(agent_wealths)
N = model.num_agents
B = sum(xi * (N - i) for i, xi in enumerate(x)) / (N * sum(x))
return 1 + (1 / N) - 2 * B
class MoneyAgent(Agent):
"""An agent with fixed initial wealth."""
def __init__(self, unique_id, model):
super().__init__(unique_id, model)
self.wealth = 1
def move(self):
possible_steps = self.model.grid.get_neighborhood(
self.pos, moore=True, include_center=False
)
new_position = self.random.choice(possible_steps)
self.model.grid.move_agent(self, new_position)
def give_money(self):
cellmates = self.model.grid.get_cell_list_contents([self.pos])
if len(cellmates) > 1:
other = self.random.choice(cellmates)
other.wealth += 1
self.wealth -= 1
def step(self):
self.move()
if self.wealth > 0:
self.give_money()
class MoneyModel(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 = MoneyAgent(i, self)
self.schedule.add(a)
# 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.datacollector = DataCollector(
model_reporters={"Gini": compute_gini}, agent_reporters={"Wealth": "wealth"}
)
def step(self):
self.datacollector.collect(self)
self.schedule.step()
if __name__ == "__main__":
fixed_params = {"width": 10, "height": 10}
variable_params = {"N": range(10, 500, 10)}
batch_run = BatchRunner(
MoneyModel,
variable_params,
fixed_params,
iterations=5,
max_steps=100,
model_reporters={"Gini": compute_gini},
)
batch_run.run_all()
run_data = batch_run.get_model_vars_dataframe()
run_data.head()
print(run_data.Gini)