hist,flowClust-method {flowClust}R Documentation

1-D Density Plot (Histogram) of Clustering Results

Description

This method generates a one-dimensional density plot for the specified dimension (variable) based on the robust model-based clustering results. A histogram of the actual data or cluster assignment is optional for display.

Usage

## S4 method for signature 'flowClust':
hist(x, data=NULL, subset=1, include=1:(x@K), histogram=TRUE, 
     labels=TRUE, xlim=NULL, ylim=NULL, xlab=NULL, ylab="Density", 
     main=NULL, breaks=50, col=NULL, pch=20, cex=0.6, ...)

Arguments

x Object returned from flowClust or from running filter on a flowFrame object.
data A numeric vector, matrix, data frame of observations, or object of class flowFrame. This is the object on which flowClust or filter was performed.
subset An integer indicating which variable is selected for the plot. Alternatively, a character string containing the name of the variable is allowed if x@varNames is not NULL.
include A numeric vector specifying which clusters will be shown on the plot. By default, all clusters are included.
histogram A logical value indicating whether a histogram of the actual data is made in addition to the density plot or not.
labels A logical value indicating whether information about cluster assignment is shown or not.
xlim The range of x-values for the plot. If NULL, the data range will be used.
ylim The range of y-values for the plot. If NULL, an optimal range will be determined automatically.
xlab, ylab Labels for the x- and y-axes respectively.
main Title of the plot.
breaks Content to be passed to the breaks argument of the generic hist function, if histogram is TRUE. Default is 50, meaning that 50 vertical bars with equal binwidths will be drawn.
col Colors of the plotting characters displaying the cluster assignment (if labels is TRUE). If NULL (default), it will be determined automatically.
pch Plotting character used to show the cluster assignment.
cex Size of the plotting character showing the cluster assignment.
... Further arguments passed to curve (and also hist if histogram is TRUE).

Author(s)

Raphael Gottardo <raph@stat.ubc.ca>, Kenneth Lo <c.lo@stat.ubc.ca>

References

Lo, K., Brinkman, R. R. and Gottardo, R. (2008) Automated Gating of Flow Cytometry Data via Robust Model-based Clustering. Cytometry A 73, 321-332.

See Also

flowClust, plot, density

Examples

res <- flowClust(iris[,1:4], K=3)
hist(res, data=iris, subset="Petal.Length", breaks=30)
hist(res, data=iris, subset=3, histogram=FALSE, labels=FALSE)
hist(res, data=iris, subset="Petal.Length", breaks=30, include=2:3)

[Package flowClust version 1.3.2 Index]