plot.fs {feature}R Documentation

Feature signficance plot for 1- to 3-dimensional data

Description

Feature signficance plot for 1- to 3-dimensional data.

Usage

## S3 method for class 'fs':
plot(x, ..., xlab, ylab, zlab, xlim, ylim, zlim,
   add=FALSE, addData=FALSE, scaleData=FALSE, addDataNum=1000,
   addKDE=TRUE, jitterRug=TRUE,  
   addSignifGradRegion=FALSE, addSignifGradData=FALSE,
   addSignifCurvRegion=FALSE, addSignifCurvData=FALSE,
   addAxes3d=TRUE, densCol, dataCol="black", gradCol="green4",
   curvCol="blue", axisCol="black", bgCol="white",
   dataAlpha=0.1, gradDataAlpha=0.3, gradRegionAlpha=0.2,
   curvDataAlpha=0.3, curvRegionAlpha=0.3)

Arguments

x an object of class fs (output from featureSignif function)
xlim, ylim, zlim x-, y-, z-axis limits
xlab, ylab, zlab x-, y-, z-axis labels
scaleData flag for scaling the data i.e. transforming to unit variance for each dimension
add flag for adding to an existing plot
addData flag for display of the data
addDataNum maximum number of data points plotted in displays
addKDE flag for display of kernel density estimates
jitterRug flag for jittering of rug-plot for univariate data display
addSignifGradRegion flag for display of significant gradient regions
addSignifGradData flag for display of significant gradient data points
addSignifCurvRegion flag for display of significant curvature regions
addSignifCurvData flag for display of significant curvature data points
addAxes3d flag for displaying axes in 3-d displays
densCol colour of density estimate curve
dataCol colour of data points
gradCol colour of significant gradient regions points
curvCol colour of significant curvature regions points
axisCol colour of axes
bgCol colour of background
dataAlpha transparency of data points
gradDataAlpha transparency of significant gradient data points
gradRegionAlpha transparency of significant gradient regions
curvDataAlpha transparency of significant curvature data points
curvRegionAlpha transparency of significant curvature regions
... other graphics parameters

Value

Plot of 1-d and 2-d kernel density estimates are sent to graphics window. Plot for 3-d is sent to RGL window.

See Also

featureSignif

Examples

library(MASS)
data(geyser)
fs <- featureSignif(geyser, bw=c(4.5, 0.37))
plot(fs, addKDE=FALSE, addData=TRUE)  ## data only
plot(fs, addKDE=TRUE)                 ## KDE plot only
plot(fs, addSignifGradRegion=TRUE)    
plot(fs, addKDE=FALSE, addSignifCurvRegion=TRUE)
plot(fs, addSignifCurvData=TRUE, curvCol="cyan")

[Package feature version 1.2.2 Index]