如何分析R中的亲和力传播聚类的图结果？

我已经安装了R的相似性传播集群包，并阅读了分解书。聚类虹膜数据的基本脚本是：

data(iris)
apIris1 <- apcluster(negDistMat(r=2), iris)
apIris1

通过此代码，形成了六个群集。此外，可以使用以下代码以图形方式查看结果：

plot(apIris1, iris)

产生的图形如下：

关于此图的可用信息是：每种颜色对应一个群集。每个群集的示例都用一个框标记，并且所有群集成员都通过线连接到其示例。 还有其他方法可以分析此图吗？例如：每个包含六个群集的大盒子（包含彩色数据）之间有什么区别？它们之间有什么关系？当我尝试仅使用绘制数据时plot(iris)，会产生相同的绘制，而没有颜色（黑点）并且没有聚类。如何分析数据图？

此外，可以生成heatmap(apIris1)如下的热图：

As seen in the plot above, the different colors on the top and left side depicts the total number of clusters. How can I analyze this plot in detail?

Any help, please!

Sorry for the lengthy post!

Update:

Here, The large boxes connected by 1,3, and 4 (excluding the boxes with feature name) have similar kind of data distribution, respectively. However, boxes connected by 2 has mirrored distribution. What does this different data distribution really say? If there were just one large box plot, it would be easy to visualize. However, the boxes with different data distribution/pattern have confused me. Can we relate each row or column with their respective feature name?