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119 lines
4.3 KiB
Python
119 lines
4.3 KiB
Python
from . import FSM, state, default_state
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class BigMarketModel(FSM):
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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, *args, **kwargs):
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super().__init__(*args, **kwargs)
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self.enterprises = self.env.environment_params["enterprises"]
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self.type = ""
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if self.id < len(self.enterprises): # Enterprises
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self._set_state(self.enterprise.id)
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self.type = "Enterprise"
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self.tweet_probability = environment.environment_params[
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"tweet_probability_enterprises"
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][self.id]
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else: # normal users
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self.type = "User"
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self._set_state(self.user.id)
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self.tweet_probability = environment.environment_params[
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"tweet_probability_users"
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]
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self.tweet_relevant_probability = environment.environment_params[
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"tweet_relevant_probability"
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]
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self.tweet_probability_about = environment.environment_params[
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"tweet_probability_about"
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] # List
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self.sentiment_about = environment.environment_params[
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"sentiment_about"
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] # List
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@state
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def enterprise(self):
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if self.random.random() < self.tweet_probability: # Tweets
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aware_neighbors = self.get_neighbors(
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state_id=self.number_of_enterprises
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) # Nodes neighbour users
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for x in aware_neighbors:
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if self.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[
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"sentiment_enterprise_%s" % self.enterprises[self.id]
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] = x.sentiment_about[self.id]
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@state
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def user(self):
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if self.random.random() < self.tweet_probability: # Tweets
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if (
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self.random.random() < self.tweet_relevant_probability
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): # Tweets something relevant
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# Tweet probability per enterprise
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for i in range(len(self.enterprises)):
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random_num = self.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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for i in range(
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len(self.enterprises)
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): # So that it never is set to 0 if there are not changes (logs)
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self.attrs[
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"sentiment_enterprise_%s" % self.enterprises[i]
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] = self.sentiment_about[i]
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def userTweets(self, sentiment, enterprise):
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aware_neighbors = self.get_neighbors(
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state_id=self.number_of_enterprises
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) # 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[
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"sentiment_enterprise_%s" % self.enterprises[enterprise]
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] = x.sentiment_about[enterprise]
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