graphs.py

def createTable(variableToChange, graphFunc):
  table = []
  p = 0.05
  n = 300


  if variableToChange == "N":
    for n in range(100, 1000, 50):
      G = erdos_renyi_graph(n, p) if graphFunc == 'erdos_renyi_graph' else watts_strogatz_graph(n, 4, p)

      table.append({
          "N": n,
          "Número de arestas": G.number_of_edges(),
          "Grau médio": grau_medio(G),
          "Coef. de agrupamento médio": nx.average_clustering(G),
          "Distância média": nx.average_shortest_path_length(G) if nx.is_connected(G) else np.nan,
          "Componentes conexos": nx.number_connected_components(G),
      })
  elif variableToChange == "P":
    for p in range(5, 101, 5):
      p = p / 100
      G = erdos_renyi_graph(n, p) if graphFunc == 'erdos_renyi_graph' else watts_strogatz_graph(n, 4, p)

      table.append({
          "P": p,
          "Número de arestas": G.number_of_edges(),
          "Grau médio": grau_medio(G),
          "Coef. de agrupamento médio": nx.average_clustering(G),
          "Distância média": nx.average_shortest_path_length(G) if nx.is_connected(G) else np.nan,
          "Componentes conexos": nx.number_connected_components(G),
      })
    
  return pd.DataFrame(table)

def plotTable(df, variableToChange):
  for col in ["Grau médio","Coef. de agrupamento médio","Distância média","Componentes conexos"]:
    dfToPlot =  df.dropna(how = 'any') if col == "Distância média" else df
    fig = plt.figure()
    fig.patch.set_facecolor('w')
    plt.plot(dfToPlot[variableToChange], dfToPlot[col])
    plt.title(col)
    plt.xlabel(variableToChange)
    plt.ylabel(col)
    plt.show()