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105 lines
4.4 KiB
Python
105 lines
4.4 KiB
Python
import random
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from ..BaseBehaviour import *
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class BigMarketModel(BaseBehaviour):
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"""
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Settings:
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Names:
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enterprises [Array]
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tweet_probability_enterprises [Array]
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Users:
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tweet_probability_users
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tweet_relevant_probability
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tweet_probability_about [Array]
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sentiment_about [Array]
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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.enterprises = environment.environment_params['enterprises']
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self.type = ""
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self.number_of_enterprises = len(environment.environment_params['enterprises'])
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if self.id < self.number_of_enterprises: # Enterprises
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self.state['id'] = self.id
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self.type = "Enterprise"
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self.tweet_probability = environment.environment_params['tweet_probability_enterprises'][self.id]
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else: # normal users
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self.state['id'] = self.number_of_enterprises
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self.type = "User"
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self.tweet_probability = environment.environment_params['tweet_probability_users']
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self.tweet_relevant_probability = environment.environment_params['tweet_relevant_probability']
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self.tweet_probability_about = environment.environment_params['tweet_probability_about'] # List
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self.sentiment_about = environment.environment_params['sentiment_about'] # List
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def step(self, now):
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if self.id < self.number_of_enterprises: # Enterprise
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self.enterpriseBehaviour()
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else: # Usuario
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self.userBehaviour()
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for i in range(self.number_of_enterprises): # So that it never is set to 0 if there are not changes (logs)
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self.attrs['sentiment_enterprise_%s'% self.enterprises[i]] = self.sentiment_about[i]
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super().step(now)
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def enterpriseBehaviour(self):
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if random.random()< self.tweet_probability: # Tweets
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aware_neighbors = self.get_neighboring_agents(state_id=self.number_of_enterprises) # Nodes neighbour users
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for x in aware_neighbors:
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if random.uniform(0,10) < 5:
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x.sentiment_about[self.id] += 0.1 # Increments for enterprise
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else:
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x.sentiment_about[self.id] -= 0.1 # Decrements for enterprise
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# Establecemos limites
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if x.sentiment_about[self.id] > 1:
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x.sentiment_about[self.id] = 1
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if x.sentiment_about[self.id]< -1:
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x.sentiment_about[self.id] = -1
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x.attrs['sentiment_enterprise_%s'% self.enterprises[self.id]] = x.sentiment_about[self.id]
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def userBehaviour(self):
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if random.random() < self.tweet_probability: # Tweets
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if random.random() < self.tweet_relevant_probability: # Tweets something relevant
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# Tweet probability per enterprise
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for i in range(self.number_of_enterprises):
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random_num = random.random()
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if random_num < self.tweet_probability_about[i]:
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# The condition is fulfilled, sentiments are evaluated towards that enterprise
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if self.sentiment_about[i] < 0:
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# NEGATIVO
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self.userTweets("negative",i)
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elif self.sentiment_about[i] == 0:
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# NEUTRO
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pass
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else:
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# POSITIVO
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self.userTweets("positive",i)
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def userTweets(self,sentiment,enterprise):
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aware_neighbors = self.get_neighboring_agents(state_id=self.number_of_enterprises) # Nodes neighbours users
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for x in aware_neighbors:
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if sentiment == "positive":
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x.sentiment_about[enterprise] +=0.003
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elif sentiment == "negative":
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x.sentiment_about[enterprise] -=0.003
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else:
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pass
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# Establecemos limites
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if x.sentiment_about[enterprise] > 1:
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x.sentiment_about[enterprise] = 1
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if x.sentiment_about[enterprise] < -1:
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x.sentiment_about[enterprise] = -1
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x.attrs['sentiment_enterprise_%s'% self.enterprises[enterprise]] = x.sentiment_about[enterprise]
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