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soil/examples/mesa/social_wealth.py
J. Fernando Sánchez d9947c2c52 WIP: all tests pass
Documentation needs some improvement

The API has been simplified to only allow for ONE topology per
NetworkEnvironment.
This covers the main use case, and simplifies the code.
2022-10-16 17:56:23 +02:00

127 lines
3.9 KiB
Python

'''
This is an example that adds soil agents and environment in a normal
mesa workflow.
'''
from mesa import Agent as MesaAgent
from mesa.space import MultiGrid
# from mesa.time import RandomActivation
from mesa.datacollection import DataCollector
from mesa.batchrunner import BatchRunner
import networkx as nx
from soil import NetworkAgent, Environment, serialization
def compute_gini(model):
agent_wealths = [agent.wealth for agent in model.agents]
x = sorted(agent_wealths)
N = len(list(model.agents))
B = sum( xi * (N-i) for i,xi in enumerate(x) ) / (N*sum(x))
return (1 + (1/N) - 2*B)
class MoneyAgent(MesaAgent):
"""
A MESA agent with fixed initial wealth.
It will only share wealth with neighbors based on grid proximity
"""
def __init__(self, unique_id, model, wealth=1):
super().__init__(unique_id=unique_id, model=model)
self.wealth = wealth
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):
print("Crying wolf", self.pos)
self.move()
if self.wealth > 0:
self.give_money()
class SocialMoneyAgent(NetworkAgent, MoneyAgent):
wealth = 1
def give_money(self):
cellmates = set(self.model.grid.get_cell_list_contents([self.pos]))
friends = set(self.get_neighboring_agents())
self.info("Trying to give money")
self.info("Cellmates: ", cellmates)
self.info("Friends: ", friends)
nearby_friends = list(cellmates & friends)
if len(nearby_friends):
other = self.random.choice(nearby_friends)
other.wealth += 1
self.wealth -= 1
def graph_generator(n=5):
G = nx.Graph()
for ix in range(n):
G.add_edge(0, ix)
return G
class MoneyEnv(Environment):
"""A model with some number of agents."""
def __init__(self, width, height, N, generator=graph_generator,
agent_class=SocialMoneyAgent,
topology=None, **kwargs):
generator = serialization.deserialize(generator)
agent_class = serialization.deserialize(agent_class, globs=globals())
topology = generator(n=N)
super().__init__(topology=topology,
N=N,
**kwargs)
self.grid = MultiGrid(width, height, False)
self.populate_network(agent_class=agent_class)
# Create agents
for agent in self.agents:
x = self.random.randrange(self.grid.width)
y = self.random.randrange(self.grid.height)
self.grid.place_agent(agent, (x, y))
self.datacollector = DataCollector(
model_reporters={"Gini": compute_gini},
agent_reporters={"Wealth": "wealth"})
if __name__ == '__main__':
fixed_params = {"generator": nx.complete_graph,
"width": 10,
"network_agents": [{"agent_class": SocialMoneyAgent,
'weight': 1}],
"height": 10}
variable_params = {"N": range(10, 100, 10)}
batch_run = BatchRunner(MoneyEnv,
variable_parameters=variable_params,
fixed_parameters=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)