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)
