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

In ggdendro: Create Dendrograms and Tree Diagrams Using 'ggplot2'

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

Description

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.

Details

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

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

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)

### 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)
}


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

ggdendro documentation built on May 29, 2024, 6:12 a.m.