创建并绘制图形。基于每个边缘所属的双连接组件的边缘颜色。

s = [1 1 2 2 3 4 4 5 6 6 7 7 8];t = [2 3 3 4 4 5 7 6 7 10 8 9 9];G =图（S，T）;p =图（g，'行宽'，2）;

p.edgecdata = biconncomp（g）;

此示例显示了如何从图作为子图的图中提取双连接的组件，然后使用原始图中的节点索引在每个子图中标记每个子图中的节点。

创建并绘制图形。

s = [1 1 2 2 3 4 4 5 6 6 7 7 8];t = [2 3 3 4 4 5 7 6 7 10 8 9 9];G =图（S，T）;plot(G)

Group the graph nodes into bins based on which biconnected component(s) each node belongs to. Then, loop through each of the bins and extract a subgraph for each biconnected component. Label the nodes in each subgraph using their original node indices.

bincell = Biconncomp（g，“输出形式”，，，，'细胞'）; n = length(bincell);为了ii = 1:n subplot(2,2,ii) plot(subgraph(G, bincell{ii}),'Nodelabel'，，，，bincell{ii});结尾

标识图中的切割顶点，然后在图图中突出显示这些顶点。

创建并绘制图形。Calculate which biconnected component each graph edge belongs to, and specify a second output to return a vector identifying the cut vertices.

s = [1 1 2 2 3 4 4 5 6 6 7 7 8];t = [2 3 3 4 4 5 7 6 7 10 8 9 9];G =图（S，T）;p =图（g）;

[Edgebins，IC] = BiconnComp（G）

Edgebins =1×134 4 4 4 4 3 3 3 3 2 1 1 1

ic =1×34 6 7

Nodes 4, 6, and 7 are the cut vertices of graphG。利用highlightto enlarge the cut vertices referenced in我知道了。

highlight(p, iC)