mirror of
https://github.com/gsi-upm/soil
synced 2024-11-14 07:22:29 +00:00
3776c4e5c5
* Removed references to `set_state` * Split some functionality from `agents` into separate files (`fsm` and `network_agents`) * Rename `neighboring_agents` to `neighbors` * Delete some spurious functions
138 lines
3.7 KiB
Python
138 lines
3.7 KiB
Python
"""
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This is an example that adds soil agents and environment in a normal
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mesa workflow.
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"""
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from mesa import Agent as MesaAgent
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from mesa.space import MultiGrid
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# from mesa.time import RandomActivation
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from mesa.datacollection import DataCollector
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from mesa.batchrunner import BatchRunner
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import networkx as nx
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from soil import NetworkAgent, Environment, serialization
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def compute_gini(model):
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agent_wealths = [agent.wealth for agent in model.agents]
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x = sorted(agent_wealths)
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N = len(list(model.agents))
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B = sum(xi * (N - i) for i, xi in enumerate(x)) / (N * sum(x))
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return 1 + (1 / N) - 2 * B
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class MoneyAgent(MesaAgent):
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"""
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A MESA agent with fixed initial wealth.
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It will only share wealth with neighbors based on grid proximity
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"""
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def __init__(self, unique_id, model, wealth=1):
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super().__init__(unique_id=unique_id, model=model)
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self.wealth = wealth
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def move(self):
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possible_steps = self.model.grid.get_neighborhood(
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self.pos, moore=True, include_center=False
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)
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new_position = self.random.choice(possible_steps)
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self.model.grid.move_agent(self, new_position)
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def give_money(self):
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cellmates = self.model.grid.get_cell_list_contents([self.pos])
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if len(cellmates) > 1:
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other = self.random.choice(cellmates)
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other.wealth += 1
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self.wealth -= 1
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def step(self):
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print("Crying wolf", self.pos)
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self.move()
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if self.wealth > 0:
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self.give_money()
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class SocialMoneyAgent(NetworkAgent, MoneyAgent):
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wealth = 1
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def give_money(self):
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cellmates = set(self.model.grid.get_cell_list_contents([self.pos]))
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friends = set(self.get_neighbors())
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self.info("Trying to give money")
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self.info("Cellmates: ", cellmates)
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self.info("Friends: ", friends)
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nearby_friends = list(cellmates & friends)
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if len(nearby_friends):
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other = self.random.choice(nearby_friends)
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other.wealth += 1
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self.wealth -= 1
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def graph_generator(n=5):
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G = nx.Graph()
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for ix in range(n):
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G.add_edge(0, ix)
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return G
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class MoneyEnv(Environment):
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"""A model with some number of agents."""
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def __init__(
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self,
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width,
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height,
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N,
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generator=graph_generator,
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agent_class=SocialMoneyAgent,
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topology=None,
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**kwargs
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):
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generator = serialization.deserialize(generator)
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agent_class = serialization.deserialize(agent_class, globs=globals())
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topology = generator(n=N)
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super().__init__(topology=topology, N=N, **kwargs)
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self.grid = MultiGrid(width, height, False)
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self.populate_network(agent_class=agent_class)
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# Create agents
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for agent in self.agents:
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x = self.random.randrange(self.grid.width)
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y = self.random.randrange(self.grid.height)
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self.grid.place_agent(agent, (x, y))
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self.datacollector = DataCollector(
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model_reporters={"Gini": compute_gini}, agent_reporters={"Wealth": "wealth"}
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)
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if __name__ == "__main__":
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fixed_params = {
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"generator": nx.complete_graph,
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"width": 10,
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"network_agents": [{"agent_class": SocialMoneyAgent, "weight": 1}],
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"height": 10,
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}
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variable_params = {"N": range(10, 100, 10)}
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batch_run = BatchRunner(
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MoneyEnv,
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variable_parameters=variable_params,
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fixed_parameters=fixed_params,
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iterations=5,
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max_steps=100,
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model_reporters={"Gini": compute_gini},
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)
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batch_run.run_all()
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run_data = batch_run.get_model_vars_dataframe()
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run_data.head()
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print(run_data.Gini)
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