hist,flowClust-method {flowClust} | R Documentation |
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.
## 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, ...)
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 are 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 ). |
Raphael Gottardo <raph@stat.ubc.ca>, Kenneth Lo <c.lo@stat.ubc.ca>
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.
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)