mirror of
https://github.com/gsi-upm/soil
synced 2024-11-13 06:52:28 +00:00
Enterprise basic logic
This commit is contained in:
parent
a8e4e2efe6
commit
99090b1494
@ -45,8 +45,8 @@ def init():
|
||||
##Users
|
||||
tweet_probability_users = 0.44
|
||||
tweet_relevant_probability = 0.25
|
||||
tweet_probability_about = [0.25, 0.25]
|
||||
sentiment_about = [0, 0]
|
||||
tweet_probability_about = [0, 0]
|
||||
sentiment_about = [0, 0] #Valores por defecto
|
||||
##Enterprises
|
||||
tweet_probability_enterprises = [0.5, 0.5]
|
||||
|
||||
|
46
soil.py
46
soil.py
@ -7,6 +7,7 @@ import random
|
||||
import numpy as np
|
||||
import networkx as nx
|
||||
import settings
|
||||
import math
|
||||
|
||||
settings.init() # Loads all the data from settings
|
||||
|
||||
@ -73,14 +74,9 @@ class BigMarketModel(BaseNetworkAgent):
|
||||
|
||||
def run(self):
|
||||
while True:
|
||||
if(self.id == 0 or self.id == 1):
|
||||
# Empresa
|
||||
print("He entrado a empresa")
|
||||
if(self.id < 2): # Empresa
|
||||
self.enterpriseBehaviour()
|
||||
|
||||
else:
|
||||
# Usuario
|
||||
print("He entrado a usuario")
|
||||
else: # Usuario
|
||||
self.userBehaviour()
|
||||
yield self.env.timeout(settings.timeout)
|
||||
|
||||
@ -89,10 +85,19 @@ class BigMarketModel(BaseNetworkAgent):
|
||||
def enterpriseBehaviour(self):
|
||||
|
||||
if random.random()< self.tweet_probability: #Twittea
|
||||
aware_neighbors = self.get_neighboring_agents(state_id=2)
|
||||
aware_neighbors = self.get_neighboring_agents(state_id=2) #Nodos vecinos usuarios
|
||||
for x in aware_neighbors:
|
||||
x.sentiment_about[0] += 0.01 #Aumenta para empresa 0
|
||||
emotionStatus[x.id][self.env.now]=x.sentiment_about[0]
|
||||
if random.uniform(0,10) < 5:
|
||||
x.sentiment_about[self.id] += 0.01 #Aumenta para empresa
|
||||
else:
|
||||
x.sentiment_about[self.id] -= 0.01 #Reduce para empresa
|
||||
# Establecemos limites
|
||||
if x.sentiment_about[self.id] > 1:
|
||||
x.sentiment_about[self.id] = 1
|
||||
if x.sentiment_about[self.id] < -1:
|
||||
x.sentiment_about[self.id] = -1
|
||||
#Guardamos estado para visualizacion
|
||||
emotionStatus[x.id][self.env.now]=x.sentiment_about[self.id]
|
||||
|
||||
|
||||
|
||||
@ -101,6 +106,7 @@ class BigMarketModel(BaseNetworkAgent):
|
||||
|
||||
if random.random() < self.tweet_probability: #Twittea
|
||||
if random.random() < self.tweet_relevant_probability: #Twittea algo relevante
|
||||
|
||||
#Probabilidad de tweet para cada empresa
|
||||
for i in range(len(self.tweet_probability_about)):
|
||||
random_num = random.random()
|
||||
@ -108,13 +114,23 @@ class BigMarketModel(BaseNetworkAgent):
|
||||
#Se ha cumplido la condicion, evaluo los sentimientos hacia esa empresa
|
||||
if self.sentiment_about[i] < 0:
|
||||
#NEGATIVO
|
||||
print("Sentimiento negativo")
|
||||
self.userTweets("negative",i)
|
||||
elif self.sentiment_about[i] == 0:
|
||||
#NEUTRO
|
||||
print("Sentimiento neutro")
|
||||
pass
|
||||
else:
|
||||
#POSITIVO
|
||||
print("Sentimiento positivo")
|
||||
self.userTweets("positive",i)
|
||||
|
||||
def userTweets(self,sentiment,enterprise):
|
||||
aware_neighbors = self.get_neighboring_agents(state_id=2) #Nodos vecinos usuarios
|
||||
for x in aware_neighbors:
|
||||
if sentiment == "positive":
|
||||
x.sentiment_about[enterprise] +=0
|
||||
elif sentiment == "negative":
|
||||
x.sentiment_about[enterprise] -=0
|
||||
else:
|
||||
pass
|
||||
|
||||
|
||||
|
||||
@ -360,7 +376,9 @@ for x in range(0, settings.number_of_nodes):
|
||||
emotionStatusAux=[]
|
||||
for tiempo in emotionStatus[x]:
|
||||
if tiempo != 'id':
|
||||
emotionStatusAux.append((emotionStatus[x][tiempo],tiempo,None))
|
||||
prec = 2
|
||||
output = math.floor(emotionStatus[x][tiempo] * (10 ** prec)) / (10 ** prec) #Para tener 2 decimales solo
|
||||
emotionStatusAux.append((output,tiempo,None))
|
||||
G.add_node(x, emotion= emotionStatusAux)
|
||||
|
||||
#lista = nx.nodes(G)
|
||||
|
Loading…
Reference in New Issue
Block a user