Extract cluster data from a model into a list of data frames.

This function provides a generic mechanism to extract relevant plotting data, typically line segments and labels, from a variety of cluster models.

Extract line segment and label data from stats::dendrogram() or stats::hclust() object. The resulting object is a list of data frames containing line segment data and label data.

Usage

dendro_data(model, ...)

# Default S3 method
dendro_data(model, ...)

# S3 method for class 'dendrogram'
dendro_data(model, type = c("rectangle", "triangle"), ...)

# S3 method for class 'hclust'
dendro_data(model, type = c("rectangle", "triangle"), ...)

# S3 method for class 'twins'
dendro_data(model, type = c("rectangle", "triangle"), ...)

Arguments

model

object of class "dendrogram", e.g. the output of as.dendrogram()

...

ignored

type

The type of plot, indicating the shape of the dendrogram. "rectangle" will draw rectangular lines, while "triangle" will draw triangular lines.

Value

a list of data frames that contain the data appropriate to each cluster model

A list with components:

segments

Line segment data

labels

Label data

Details

For stats::dendrogram() and tree::tree() models, extracts line segment data and labels.

See also

There are several implementations for specific cluster algorithms:

• dendro_data.hclust()

• dendro_data.dendrogram()

• dendro_data.tree()

• dendro_data.rpart()

To extract the data for line segments, labels or leaf labels use:

• segment(): the line segment data

• label(): the text for each end segment

• leaf_label(): the leaf labels of a tree diagram

ggdendrogram()

Other dendro_data methods: dendro_data.rpart(), dendro_data.tree(), dendrogram_data(), rpart_labels()

Other dendrogram/hclust functions: dendrogram_data()

Examples

require(ggplot2)
#> Loading required package: ggplot2

### Demonstrate dendro_data.dendrogram

model <- hclust(dist(USArrests), "ave")
dendro <- as.dendrogram(model)

# Rectangular lines
ddata <- dendro_data(dendro, type = "rectangle")
ggplot(segment(ddata)) +
  geom_segment(aes(x = x, y = y, xend = xend, yend = yend)) +
  coord_flip() +
  scale_y_reverse(expand = c(0.2, 0)) +
  theme_dendro()


# Triangular lines
ddata <- dendro_data(dendro, type = "triangle")
ggplot(segment(ddata)) +
  geom_segment(aes(x = x, y = y, xend = xend, yend = yend)) +
  theme_dendro()


# Demonstrate dendro_data.hclust

require(ggplot2)
hc <- hclust(dist(USArrests), "ave")

# Rectangular lines
hcdata <- dendro_data(hc, type = "rectangle")
ggplot(segment(hcdata)) +
  geom_segment(aes(x = x, y = y, xend = xend, yend = yend)) +
  coord_flip() +
  scale_y_reverse(expand = c(0.2, 0)) +
  theme_dendro()


# Triangular lines
hcdata <- dendro_data(hc, type = "triangle")
ggplot(segment(hcdata)) +
  geom_segment(aes(x = x, y = y, xend = xend, yend = yend)) +
  theme_dendro()

### Demonstrate the twins of agnes and diana, from package cluster

if (require(cluster)) {
  model <- agnes(votes.repub, metric = "manhattan", stand = TRUE)
  dg <- as.dendrogram(model)
  ggdendrogram(dg)
}
#> Loading required package: cluster



if (require(cluster)) {
  model <- diana(votes.repub, metric = "manhattan", stand = TRUE)
  dg <- as.dendrogram(model)
  ggdendrogram(dg)
}