NetworkX提供了4種常見網絡的建模方法，分別是：規則圖，ER隨機圖，WS小世界網絡和BA無標度網絡。
一. 規則圖
規則圖差不多是最沒有復雜性的一類圖，random_graphs.random_regular_graph(d, n)方法可以生成一個含有n個節點，每個節點有d個鄰居節點的規則圖。
下面一段示例代碼，生成了包含20個節點、每個節點有3個鄰居的規則圖：
1 import networkx as nx
2 import matplotlib.pyplot as plt
3
4 # regular graphy
5 # generate a regular graph which has 20 nodes & each node has 3 neghbour nodes.
6 RG = nx.random_graphs.random_regular_graph(3, 20)
7 # the spectral layout
8 pos = nx.spectral_layout(RG)
9 # draw the regular graphy
10 nx.draw(RG, pos, with_labels = False, node_size = 30)
11 plt.show()
二、ER隨機圖
ER隨機圖是早期研究得比較多的一類“復雜”網絡，模型的基本思想是以概率p連接N個節點中的每一對節點。用random_graphs.erdos_renyi_graph(n,p)方法生成一個含有n個節點、以概率p連接的ER隨機圖：
1 import networkx as nx
2 import matplotlib.pyplot as plt
3
4 # erdos renyi graph
5 # generate a graph which has n=20 nodes, probablity p = 0.2.
6 ER = nx.random_graphs.erdos_renyi_graph(20, 0.2)
7 # the shell layout
8 pos = nx.shell_layout(ER)
9 nx.draw(ER, pos, with_labels = False, node_size = 30)
10 plt.show()
三、WS小世界網絡
用random_graphs.watts_strogatz_graph(n, k, p)方法生成一個含有n個節點、每個節點有k個鄰居、以概率p隨機化重連邊的WS小世界網絡。
下面是一個例子：
1 import networkx as nx
2 import matplotlib.pyplot as plt
3
4 # WS network
5
6 # generate a WS network which has 20 nodes,
7 # each node has 4 neighbour nodes,
8 # random reconnection probability was 0.3.
9 WS = nx.random_graphs.watts_strogatz_graph(20, 4, 0.3)
10 # circular layout
11 pos = nx.circular_layout(WS)
12 nx.draw(WS, pos, with_labels = False, node_size = 30)
13 plt.show()
四、BA無標度網絡
用random_graphs.barabasi_albert_graph(n, m)方法生成一個含有n個節點、每次加入m條邊的BA無標度網絡。
下面是一個例子：
1 import networkx as nx
2 import matplotlib.pyplot as plt
3
4 # BA scale-free degree network
5 # generalize BA network which has 20 nodes, m = 1
6 BA = nx.random_graphs.barabasi_albert_graph(20, 1)
7 # spring layout
8 pos = nx.spring_layout(BA)
9 nx.draw(BA, pos, with_labels = False, node_size = 30)
10 plt.show()
