mirror of
https://github.com/gsi-upm/soil
synced 2024-09-20 15:31:43 +00:00
e1be3a730e
* Pandas integration * Improved environment * Logging and data dumps * Tests * Added Finite State Machine models * Rewritten ipython notebook and documentation
50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
import random
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from . import BaseAgent
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class IndependentCascadeModel(BaseAgent):
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"""
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Settings:
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innovation_prob
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imitation_prob
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"""
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def __init__(self, environment=None, agent_id=0, state=()):
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super().__init__(environment=environment, agent_id=agent_id, state=state)
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self.innovation_prob = environment.environment_params['innovation_prob']
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self.imitation_prob = environment.environment_params['imitation_prob']
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self.state['time_awareness'] = 0
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self.state['sentimentCorrelation'] = 0
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def step(self):
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self.behaviour()
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def behaviour(self):
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aware_neighbors_1_time_step = []
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# Outside effects
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if random.random() < self.innovation_prob:
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if self.state['id'] == 0:
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self.state['id'] = 1
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self.state['sentimentCorrelation'] = 1
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self.state['time_awareness'] = self.env.now # To know when they have been infected
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else:
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pass
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return
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# Imitation effects
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if self.state['id'] == 0:
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aware_neighbors = self.get_neighboring_agents(state_id=1)
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for x in aware_neighbors:
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if x.state['time_awareness'] == (self.env.now-1):
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aware_neighbors_1_time_step.append(x)
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num_neighbors_aware = len(aware_neighbors_1_time_step)
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if random.random() < (self.imitation_prob*num_neighbors_aware):
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self.state['id'] = 1
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self.state['sentimentCorrelation'] = 1
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else:
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pass
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return
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