soil/soil.py

from nxsim import NetworkSimulation
from nxsim import BaseNetworkAgent
from nxsim import BaseLoggingAgent
from random import randint
from matplotlib import pyplot as plt
import random
import numpy as np
import networkx as nx
import settings

settings.init() # Loads all the data from settings

####################
# Network creation #
####################

if settings.network_type == 0:
    G = nx.complete_graph(settings.number_of_nodes)
if settings.network_type == 1:
    G = nx.barabasi_albert_graph(settings.number_of_nodes,3)
if settings.network_type == 2:
    G = nx.margulis_gabber_galil_graph(settings.number_of_nodes, None)
# More types of networks can be added here


##############################
# Variables initializitation #
##############################

myList=[] # List just for debugging
networkStatus=[] # This list will contain the status of every node of the network
for x in range(0, settings.number_of_nodes):
    networkStatus.append({'id':x})

# Initialize agent states. Let's assume everyone is normal.
init_states = [{'id': 0, } for _ in range(settings.number_of_nodes)]  # add keys as as necessary, but "id" must always refer to that state category

# Seed a zombie, just for zombie model
#init_states[5] = {'id': 1}
#init_states[3] = {'id': 1}

####################
# Available models #
####################

class BigMarketModel(BaseNetworkAgent):
    def __init__(self, environment=None, agent_id=0, state=()):
        super().__init__(environment=environment, agent_id=agent_id, state=state)
        self.time_awareness = 0
        networkStatus[self.id][self.env.now]=0
        if self.id == 0:            #Empresa 1
            self.state['id']=0
            self.tweet_probability = settings.tweet_probability_1
        elif self.id == 1:          #Empresa 2
            self.state['id']=1
            self.tweet_probability = settings.tweet_probability_2
        else:                       #Usuarios normales
            self.state['id']=2
            self.tweet_probability = settings.tweet_probability_users
            self.tweet_relevant_probability = settings.tweet_relevant_probability
            self.tweet_probability_about = settings.tweet_probability_about #Lista
            self.sentiment_about = settings.sentiment_about #Lista

    def run(self):
        while True:

            ##Usuario

            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)):
                        if random.random() < self.tweet_probability_about[i]:
                            #Se ha cumplido la condicion, evaluo los sentimientos hacia esa empresa
                            if self.sentiment_about[i] < 0:
                                #NEGATIVO
                            elif self.sentiment_about[i] == 0:
                                #NEUTRO
                            else:
                                #POSITIVO



            aware_neighbors_1_time_step=[]
            #Outside effects
            if random.random() < settings.innovation_prob:
                if self.state['id'] == 0:
                    self.state['id'] = 1
                    myList.append(self.id)
                    networkStatus[self.id][self.env.now]=1
                    self.time_awareness = self.env.now #Para saber cuando se han contagiado
                    yield self.env.timeout(settings.timeout)
                else:
                    yield self.env.timeout(settings.timeout)

            #Imitation effects
            if self.state['id'] == 0:
                aware_neighbors = self.get_neighboring_agents(state_id=1)
                for x in aware_neighbors:
                    if x.time_awareness == (self.env.now-1):
                        aware_neighbors_1_time_step.append(x)
                num_neighbors_aware = len(aware_neighbors_1_time_step)
                if random.random() < (settings.imitation_prob*num_neighbors_aware):
                    myList.append(self.id)
                    self.state['id'] = 1
                    networkStatus[self.id][self.env.now]=1
                    yield self.env.timeout(settings.timeout)
                else:
                    yield self.env.timeout(settings.timeout)

class SentimentCorrelationModel(BaseNetworkAgent):
    def __init__(self, environment=None, agent_id=0, state=()):
        super().__init__(environment=environment, agent_id=agent_id, state=state)
        self.outside_effects_prob = settings.outside_effects_prob
        self.anger_prob = settings.anger_prob
        self.joy_prob = settings.joy_prob
        self.sadness_prob = settings.sadness_prob
        self.disgust_prob = settings.disgust_prob
        self.time_awareness=[]
        for i in range(4):  #En este modelo tenemos 4 sentimientos
            self.time_awareness.append(0)     #0-> Anger, 1-> joy, 2->sadness, 3 -> disgust
        networkStatus[self.id][self.env.now]=0


    def run(self):
        while True:

            angry_neighbors_1_time_step=[]
            joyful_neighbors_1_time_step=[]
            sad_neighbors_1_time_step=[]
            disgusted_neighbors_1_time_step=[]


            angry_neighbors = self.get_neighboring_agents(state_id=1)
            for x in angry_neighbors:
                if x.time_awareness[0] > (self.env.now-500):
                    angry_neighbors_1_time_step.append(x)
            num_neighbors_angry = len(angry_neighbors_1_time_step)


            joyful_neighbors = self.get_neighboring_agents(state_id=2)
            for x in joyful_neighbors:
                if x.time_awareness[1] > (self.env.now-500):
                    joyful_neighbors_1_time_step.append(x)
            num_neighbors_joyful = len(joyful_neighbors_1_time_step)


            sad_neighbors = self.get_neighboring_agents(state_id=3)
            for x in sad_neighbors:
                if x.time_awareness[2] > (self.env.now-500):
                    sad_neighbors_1_time_step.append(x)
            num_neighbors_sad = len(sad_neighbors_1_time_step)


            disgusted_neighbors = self.get_neighboring_agents(state_id=4)
            for x in disgusted_neighbors:
                if x.time_awareness[3] > (self.env.now-500):
                    disgusted_neighbors_1_time_step.append(x)
            num_neighbors_disgusted = len(disgusted_neighbors_1_time_step)


            anger_prob= settings.anger_prob+(len(angry_neighbors_1_time_step)*settings.anger_prob)
            joy_prob= settings.joy_prob+(len(joyful_neighbors_1_time_step)*settings.joy_prob)
            sadness_prob = settings.sadness_prob+(len(sad_neighbors_1_time_step)*settings.sadness_prob)
            disgust_prob = settings.disgust_prob+(len(disgusted_neighbors_1_time_step)*settings.disgust_prob)
            outside_effects_prob= settings.outside_effects_prob


            num = random.random()


            if(num<outside_effects_prob):
                self.state['id'] = random.randint(1,4)
                myList.append(self.id)
                networkStatus[self.id][self.env.now]=self.state['id'] #Almaceno cuando se ha infectado para la red dinamica
                self.time_awareness[self.state['id']-1] = self.env.now
                yield self.env.timeout(settings.timeout)


            if(num<anger_prob):

                myList.append(self.id)
                self.state['id'] = 1
                networkStatus[self.id][self.env.now]=1
                self.time_awareness[self.state['id']-1] = self.env.now
            elif (num<joy_prob+anger_prob and num>anger_prob):

                myList.append(self.id)
                self.state['id'] = 2
                networkStatus[self.id][self.env.now]=2
                self.time_awareness[self.state['id']-1] = self.env.now
            elif (num<sadness_prob+anger_prob+joy_prob and num>joy_prob+anger_prob):

                myList.append(self.id)
                self.state['id'] = 3
                networkStatus[self.id][self.env.now]=3
                self.time_awareness[self.state['id']-1] = self.env.now
            elif (num<disgust_prob+sadness_prob+anger_prob+joy_prob and num>sadness_prob+anger_prob+joy_prob):

                myList.append(self.id)
                self.state['id'] = 4
                networkStatus[self.id][self.env.now]=4
                self.time_awareness[self.state['id']-1] = self.env.now

            yield self.env.timeout(settings.timeout)


class BassModel(BaseNetworkAgent):
    def __init__(self, environment=None, agent_id=0, state=()):
        super().__init__(environment=environment, agent_id=agent_id, state=state)
        self.innovation_prob = settings.innovation_prob
        self.imitation_prob = settings.imitation_prob
        networkStatus[self.id][self.env.now]=0

    def run(self):
        while True:


            #Outside effects
            if random.random() < settings.innovation_prob:
                if self.state['id'] == 0:
                    self.state['id'] = 1
                    myList.append(self.id)
                    networkStatus[self.id][self.env.now]=1
                    yield self.env.timeout(settings.timeout)
                else:
                    yield self.env.timeout(settings.timeout)

            #Imitation effects
            if self.state['id'] == 0:
                aware_neighbors = self.get_neighboring_agents(state_id=1)
                num_neighbors_aware = len(aware_neighbors)
                if random.random() < (settings.imitation_prob*num_neighbors_aware):
                    myList.append(self.id)
                    self.state['id'] = 1
                    networkStatus[self.id][self.env.now]=1
                    yield self.env.timeout(settings.timeout)
                else:
                    yield self.env.timeout(settings.timeout)

class IndependentCascadeModel(BaseNetworkAgent):
    def __init__(self, environment=None, agent_id=0, state=()):
        super().__init__(environment=environment, agent_id=agent_id, state=state)
        self.innovation_prob = settings.innovation_prob
        self.imitation_prob = settings.imitation_prob
        self.time_awareness = 0
        networkStatus[self.id][self.env.now]=0

    def run(self):
        while True:
            aware_neighbors_1_time_step=[]
            #Outside effects
            if random.random() < settings.innovation_prob:
                if self.state['id'] == 0:
                    self.state['id'] = 1
                    myList.append(self.id)
                    networkStatus[self.id][self.env.now]=1
                    self.time_awareness = self.env.now #Para saber cuando se han contagiado
                    yield self.env.timeout(settings.timeout)
                else:
                    yield self.env.timeout(settings.timeout)

            #Imitation effects
            if self.state['id'] == 0:
                aware_neighbors = self.get_neighboring_agents(state_id=1)
                for x in aware_neighbors:
                    if x.time_awareness == (self.env.now-1):
                        aware_neighbors_1_time_step.append(x)
                num_neighbors_aware = len(aware_neighbors_1_time_step)
                if random.random() < (settings.imitation_prob*num_neighbors_aware):
                    myList.append(self.id)
                    self.state['id'] = 1
                    networkStatus[self.id][self.env.now]=1
                    yield self.env.timeout(settings.timeout)
                else:
                    yield self.env.timeout(settings.timeout)


class ZombieOutbreak(BaseNetworkAgent):
    def __init__(self, environment=None, agent_id=0, state=()):
        super().__init__(environment=environment, agent_id=agent_id, state=state)
        self.bite_prob = settings.bite_prob
        networkStatus[self.id][self.env.now]=0


    def run(self):
        while True:
            if random.random() < settings.heal_prob:
                if self.state['id'] == 1:
                    self.zombify()
                    yield self.env.timeout(settings.timeout)
                else:
                    yield self.env.timeout(settings.timeout)
            else:
                if self.state['id'] == 1:
                    print("Soy el zombie " + str(self.id) + " y me voy a curar porque el num aleatorio ha sido " + str(num))
                    networkStatus[self.id][self.env.now]=0
                    if self.id in myList:
                        myList.remove(self.id)
                    self.state['id'] = 0
                    yield self.env.timeout(settings.timeout)
                else:
                    yield self.env.timeout(settings.timeout)


    def zombify(self):
        normal_neighbors = self.get_neighboring_agents(state_id=0)
        for neighbor in normal_neighbors:
            if random.random() < self.bite_prob:
                print("Soy el zombie " + str(self.id) + " y voy a contagiar a " + str(neighbor.id))
                neighbor.state['id'] = 1 # zombie
                myList.append(neighbor.id)
                networkStatus[self.id][self.env.now]=1
                networkStatus[neighbor.id][self.env.now]=1
                print(self.env.now, "Soy el zombie: "+ str(self.id), "Mi vecino es: "+ str(neighbor.id), sep='\t')
                break


##############
# Simulation #
##############

sim = NetworkSimulation(topology=G, states=init_states, agent_type=SentimentCorrelationModel,
                        max_time=settings.max_time, num_trials=settings.num_trials, logging_interval=1.0)


sim.run_simulation()

###########
# Results #
###########

myList = sorted(myList, key=int)
#print("Los zombies son: " + str(myList))

trial = BaseLoggingAgent.open_trial_state_history(dir_path='sim_01', trial_id=0)
status_census = [sum([1 for node_id, state in g.items() if state['id'] == 1]) for t,g in trial.items()]


#################
# Visualization #
#################

#lista = nx.nodes(G)
#print('Nodos: ' + str(lista))
for x in range(0, settings.number_of_nodes):
    networkStatusAux=[]
    for tiempo in networkStatus[x]:
        if tiempo != 'id':
	        networkStatusAux.append((networkStatus[x][tiempo],tiempo,None))
    G.add_node(x, status= networkStatusAux)
#print(networkStatus)


nx.write_gexf(G,"test.gexf", version="1.2draft")
plt.plot(status_census)
plt.draw()  # pyplot draw()
plt.savefig("status.png")
#print(networkStatus)
#nx.draw(G)
#plt.show()
#plt.savefig("path.png")