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54 lines
1.8 KiB
Python
54 lines
1.8 KiB
Python
import random
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from ..BaseBehaviour import *
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from .. import sentimentCorrelationNodeArray
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class IndependentCascadeModel(BaseBehaviour):
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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.time_awareness = 0
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sentimentCorrelationNodeArray[self.id][self.env.now] = 0
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def step(self, now):
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self.behaviour()
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super().step(now)
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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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sentimentCorrelationNodeArray[self.id][self.env.now] = 1
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self.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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self.attrs['status'] = self.state['id']
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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.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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sentimentCorrelationNodeArray[self.id][self.env.now] = 1
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else:
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pass
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self.attrs['status'] = self.state['id']
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return
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