mirror of
https://github.com/gsi-upm/soil
synced 2024-11-13 06:52:28 +00:00
87 lines
2.4 KiB
Python
87 lines
2.4 KiB
Python
from models import *
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from nxsim import NetworkSimulation
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import numpy
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from matplotlib import pyplot as plt
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import networkx as nx
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import settings
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import models
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import math
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import json
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settings.init() # Loads all the data from settings
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models.init() # Loads the models and network variables
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####################
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# Network creation #
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####################
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if settings.network_type == 0:
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G = nx.complete_graph(settings.number_of_nodes)
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if settings.network_type == 1:
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G = nx.barabasi_albert_graph(settings.number_of_nodes,10)
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if settings.network_type == 2:
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G = nx.margulis_gabber_galil_graph(settings.number_of_nodes, None)
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# More types of networks can be added here
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##############
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# Simulation #
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##############
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sim = NetworkSimulation(topology=G, states=init_states, agent_type=SpreadModelM2,
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max_time=settings.max_time, num_trials=settings.num_trials, logging_interval=1.0)
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sim.run_simulation()
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###########
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# Results #
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###########
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x_values = []
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y_values = []
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attribute_plot = 'status'
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for time in range(0, settings.max_time):
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value = settings.sentiment_about[0]
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real_time = time * settings.timeout
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activity= False
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for x in range(0, settings.number_of_nodes):
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if attribute_plot in models.networkStatus["agente_%s" % x]:
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if real_time in models.networkStatus["agente_%s" % x][attribute_plot]:
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if models.networkStatus["agente_%s" % x][attribute_plot][real_time] == 1: ##Representar infectados
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value += 1
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activity = True
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if activity:
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x_values.append(real_time)
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y_values.append(value)
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activity=False
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plt.plot(x_values,y_values)
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plt.show()
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#################
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# Visualization #
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#################
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for x in range(0, settings.number_of_nodes):
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for empresa in models.networkStatus["agente_%s"%x]:
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emotionStatusAux=[]
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for tiempo in models.networkStatus["agente_%s"%x][empresa]:
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prec = 2
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output = math.floor(models.networkStatus["agente_%s"%x][empresa][tiempo] * (10 ** prec)) / (10 ** prec) #Para tener 2 decimales solo
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emotionStatusAux.append((output,tiempo,None))
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attributes = {}
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attributes[empresa] = emotionStatusAux
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G.add_node(x, attributes)
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print("Done!")
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with open('data.txt', 'w') as outfile:
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json.dump(models.networkStatus, outfile, sort_keys=True, indent=4, separators=(',', ': '))
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nx.write_gexf(G,"test.gexf", version="1.2draft")
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