plot.fs {feature} | R Documentation |
Feature signficance plot for 1- to 3-dimensional data.
## 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)
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 |
Plot of 1-d and 2-d kernel density estimates are sent to graphics window. Plot for 3-d is sent to RGL window.
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")