def __init__(self, resultfile_prefix = "pit_"): Simulation.__init__(self, resultfile_prefix)
graphs_similarities.append( ("Spectral embedding - " + str(clusters) + "clusters", "AutoEncoder embedding - " + str(clusters) + "clusters")) print(prog_st_ + str(100 * ((clusters + 1) / 5.)) + "%") #Graphs simulations and performances checks print( info_st_ + "Performs simulations on graphs and perfomance checks \n --------------------------------------------------------" ) print(info_st_ + "Results will be saved to file at the end") for graph_name in Graphs.keys(): current_G = Graphs[graph_name][0] clusters = Graphs[graph_name][1] sim = Simulation(current_G, nodes_activity, nodes_hash, trace_table) num_of_nodes = str(len(nx.nodes(current_G))) num_of_edges = str(len(nx.edges(current_G))) graph_is_connected = nx.is_connected(current_G) simulation_avg_hops = 0 if graph_is_connected: simulation_avg_hops = sim.run_avg_dist() results = results.append( pd.DataFrame([[ trace_name, graph_name, clusters, simulation_avg_hops, num_of_edges, num_of_nodes, graph_is_connected ]], columns=results.columns)) results.reset_index(inplace=True, drop=True)