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Big market model init started
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46
soil.py
46
soil.py
@ -43,6 +43,52 @@ init_states = [{'id': 0, } for _ in range(settings.number_of_nodes)] # add keys
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# Available models #
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####################
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class BigMarketModel(BaseNetworkAgent):
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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.time_awareness = 0
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networkStatus[self.id][self.env.now]=0
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if self.id == 0: #Empresa 1
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self.state['id']=0
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self.tweet_probability_1 = settings.tweet_probability_1
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elif self.id == 1: #Empresa 2
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self.state['id']=1
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self.tweet_probability_2 = settings.tweet_probability_2
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else: #Usuarios normales
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self.state['id']=2
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self.tweet_probability_users = settings.tweet_probability_users
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self.tweet_probability_about = settings.tweet_probability_about
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self.sentiment_about = settings.sentiment_about
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def run(self):
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while True:
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aware_neighbors_1_time_step=[]
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#Outside effects
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if random.random() < settings.innovation_prob:
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if self.state['id'] == 0:
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self.state['id'] = 1
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myList.append(self.id)
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networkStatus[self.id][self.env.now]=1
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self.time_awareness = self.env.now #Para saber cuando se han contagiado
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yield self.env.timeout(settings.timeout)
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else:
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yield self.env.timeout(settings.timeout)
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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() < (settings.imitation_prob*num_neighbors_aware):
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myList.append(self.id)
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self.state['id'] = 1
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networkStatus[self.id][self.env.now]=1
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yield self.env.timeout(settings.timeout)
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else:
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yield self.env.timeout(settings.timeout)
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class SentimentCorrelationModel(BaseNetworkAgent):
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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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