Problem with margins using plot function with as.dendrogram object

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In this blog post, we will discuss a problem that arises when trying to customize a clustering plot using both base R functions and the dendextend package. We will delve into the details of how the as.dendrogram class affects the margins of the plot area.

Background

The hclust() function is used to perform hierarchical clustering on a dataset. The resulting object can be converted into an as.dendrogram object, which provides additional functionality for customizing the plot.

One such customization involves coloring the branches defined by k=groups using the set() function from the dendextend package.

The Problem

When we use the plot() function with an as.dendrogram object and customize the plot using points, text, and other functions, we sometimes encounter issues with the margins of the plot area. Specifically, the plot area may shrink mainly below the x-axis.

This problem can be particularly frustrating, especially when trying to create a custom clustering plot that requires precise control over the margins and appearance.

The Solution

To solve this issue, we need to use the mar argument in the par() function. This argument controls the margins of the plot area.

By adding a value to the first element of the mar vector, we can increase the space available for the y-axis labels and customize the plot accordingly.

Example Code

Here is an example code snippet that demonstrates how to use the mar argument to solve this problem:

library(dendextend)
# ?color_branches

par(mar=c(5 + 5,4,4,2) + 0.1)

dend <- USArrests %>% 
  dist() %>% 
  hclust(method = "ave") %>% 
  as.dendrogram()
d2 <- color_branches(dend, 5)
plot(d2)

In this code snippet, we add +0.1 to the first element of the mar vector, which increases the space available for the y-axis labels.

Additional Tips and Considerations

Here are some additional tips and considerations that may help when working with clustering plots using the dendextend package:

Customize the plot area: Use the mar argument to customize the margins of the plot area. This can be particularly useful when trying to create a custom clustering plot that requires precise control over the appearance.
Use the hang option: The hang option in the set() function from the dendextend package allows you to adjust the horizontal positioning of the labels on the dendrogram. This can be particularly useful when trying to customize the layout of the plot.
Experiment with different parameters: Don’t be afraid to experiment with different parameters and options when working with clustering plots. This can help you find the perfect balance between aesthetics and functionality.

Reproducing the Example Using the USArrest Dataset

The USArrest dataset can be used as an alternative example for reproducing the code snippet above:

dend <- USArrests %>% 
  dist() %>% 
  hclust(method = "ave") %>% 
  as.dendrogram()
d2 <- color_branches(dend, 5)
plot(d2)

points(seq(1:30), rep(0, 30), col=alpha(color_cluster, 0.8), pch=c(rep(19, 4), rep(15,17), rep(17, 9)), cex=1.5)
text(seq(1:30), rep(-0.5,30), labels=dend$order, cex=0.8, col=color_cluster, font=2)

In this code snippet, we use the USArrest dataset to create a clustering plot using hierarchical clustering and customize the appearance using points and text functions.

Conclusion

In conclusion, this blog post has discussed a problem that arises when trying to customize a clustering plot using both base R functions and the dendextend package. We have explored the details of how the as.dendrogram class affects the margins of the plot area and provided an example code snippet that demonstrates how to use the mar argument to solve this problem.

By following the tips and considerations outlined in this blog post, you should be able to create custom clustering plots with precise control over the appearance and functionality.

Last modified on 2023-11-08