Package 'DendSer'

Title: Dendrogram Seriation: Ordering for Visualisation
Description: Re-arranges a dendrogram to optimize visualisation-based cost functions.
Authors: Catherine B. Hurley and Denise Earle
Maintainer: Catherine Hurley <[email protected]>
License: GPL-2
Version: 1.0.2
Built: 2024-05-11 05:39:38 UTC
Source: https://github.com/cbhurley/dendser

Help Index

Cost functions for DendSer

Description

Each of these functions evaluates the cost of an ordering.

Usage

costARc(sw, o, target = nrow(sw) - 1, ...)
costBAR(sw, o, target=max(2,floor(nrow(sw)/5)),...)
costLS(sw, o, target=seq_along(sw),...)
costPL(sw, o, ...)
costLPL(sw, o, target=(nrow(sw)-1):1,...)
costED(sw, o, node,se,...)

Arguments

sw

For cost=costLS, this is a vector of object weights. Otherwise is a symmetric matrix.

o

An ordering vector.

node

The node

se

Extra info

target

Parameter used by cost function.

...

Other args.

Value

Result of cost

Author(s)

Catherine Hurley & Denise Earle

Cost function from seriation criterion

Description

Returns a cost function from seriation criterion (package seriation)

Usage

crit2cost(crit)

Arguments

crit

One of seriation::list_criterion_methods("dist")

Examples

require(DendSer) 			

d<- dist(iris[1:20,-5])
h <- hclust(d)
DendSer(h,d,cost=function(x,o,...) criterion(as.dist(x),o,method="AR_deviations"))
DendSer(h,d,cost=crit2cost("AR_deviations")) # short version of above
DendSer(h,d,cost=crit2cost("ME"))

# use DendSer methods via seriate
# get_order(seriate(d,method="Dendser", control=list(hclust=h,cost=costARc))) 
DendSer(h,d,cost=costARc)

Implements dendrogram seriation

Description

Implements dendrogram seriation.

Usage

DendSer(h, ser_weight, cost = costBAR, node_op = NULL, costArg = NULL, 
maxloops = NULL, saveinfo = FALSE, direction = NULL,  GW=NULL,...)

Arguments

h

An object of class hclust

ser_weight

Used by cost function to evaluate ordering. For cost=costLS, this is a vector of object weights. Otherwise is a dist or symmetric matrix.

cost

Function used to evaluate permutation.Current choices are costLS, costPL, costLPL, costED, costARc, costBAR.
node_op

Function used to reorder branches at a dendrogram node. DendSer picks default depending on cost function. NULL means use default depending on cost.

costArg

Other args for cost function.
maxloops

Maximum number of iterations allowed. NULL means use default depending on cost.

saveinfo

Logical, whether info associated with search is saved.

direction

Order of visiting nodes. Values are "up" or "down", for nodes in order of increasing or decreasing height.NULL means use default depending on cost.
GW

Logical, initial GW step or not. NULL means use default depending on cost.
...

Not used.

Details

costED uses the Gruvaeus and Wainer 1972 algorithm, as provided by package gclus.

Value

Numeric vector giving an optimal dendrogram order

Author(s)

Catherine Hurley & Denise Earle

References

Gruvaeus, G. \& Wainer, H. (1972), “Two additions to hierarchical cluster analysis”, British Journal of Mathematical and Statistical Psychology, 25, 200-206.

See Also

dser

Examples

require(DendSer) 			

d<- dist(iris[,-5])
h <- hclust(d,method="average")
ob<- DendSer(h,d)
opl<- DendSer(h,d,cost=costPL)
plotAsColor(d,ob)

w <- rowSums(iris[,-5])
ow <- DendSer(h,w,cost=costLS) # arranges cases by size, within hclust
stars(iris[ow,-5],labels=NULL, col.stars=cutree(h,3)[ow]) # and color by cluster
#stars(iris[ow,-5],labels=NULL, col.stars=iris[ow,5]) # or by species

Implements dendrogram seriation. Interface to DendSer.

Description

Implements dendrogram seriation. Interface to DendSer.

Usage

dser(x,ser_weight,cost=costBAR, ...)

## S3 method for class 'data.frame'
dser(x,ser_weight,cost=costBAR,...)

## S3 method for class 'matrix'
dser(x,ser_weight,cost=costBAR,scale=TRUE,dmethod="euclidean",...)

## S3 method for class 'dist'
dser(x,ser_weight,cost=costBAR,hmethod="average",...)

## S3 method for class 'hclust'
dser(x,ser_weight,cost=costBAR,...)

Arguments

x

Used to select method.
ser_weight

Seriation weights. For cost=costLS, defaults to first column of matrix x, otherwise to symmetric matrix version of dist d.
cost

Current choices are costLS, costPL, costLPL, costED, costARc, costBAR.
scale

Logical value,controls whether matrix x should be scaled prior to forming dist.
dmethod

Method of dist calculation. See function dist.
hmethod

Method of hclust calculation. See function hclust.
...

Other args

Details

When x is a matrix or data.drame, forms a dist of rows using function dist with method = dmethod. When x is a dist, forms a hclust with method = hmethod which is then reordered.

Value

Numeric vector giving an optimal dendrogram order

Author(s)

Catherine Hurley & Denise Earle

Examples

require(DendSer) 			

iriss <- scale(iris[,-5])
plotAsColor(iriss,order.row=dser(iriss))



w <- prcomp(iris[,-5],scale=TRUE)$x[,1]
h<- hclust(dist(iriss))
h$order <- ow <- dser(h,w,cost=costLS) # arranges cases along first PC, within dendrogram


# compare re-rordered dendrogram to PC scores, w
dev.new(width=10,height=5)
par(mar=c(0,2,1,1))
layout(matrix(1:2, nrow = 2), heights = c(4,1.5) )
par(cex=.7)
plot(h,main="",xlab="",hang=-1,labels=FALSE)
u <- par("usr")
par(mar=c(1,2,0,1))
 

plot.new()
par(usr=c(u[1:2],min(w),max(w)))

x<- 1:length(w)
rect(x-.5,0,x+.5,w[ow],col=cutree(h,3)[ow]+1)

Function that plots a matrix as a color image

Description

Function that plots a matrix as a color image, in matrix order.

Usage

plotAsColor(m,  order = NULL, order.col = order, order.row = order, 
rank = FALSE, border.color = "grey70", labels = FALSE,x=1:ncol(d),y=1:nrow(d), ...)

Arguments

m

Numeric matrix.

order

Default order used for rows and columns.

order.col

Column order.

order.row

Row order

rank

Logical, whether matrix m should be converted to ranks or not.
border.color

Color of border. Null for no border.

labels

If TRUE, add labels obtained from m.

x

X coordinates, passed to image.
y

Y coordinates, passed to image.
...

passed to image.

See Also

See Also as image.

Examples

require(DendSer) 			

d<- dist(scale(iris[,-5]))
plotAsColor(d,dser(d,hmethod="average"))