
Last chance! 50% off unlimited learning
Sale ends in
Given a series of 2-d points and values at these segments, the function colors the segments according to a color scale and the segment values. This is essentially an image plot restricted to line segments.
ribbon.plot(x,y,z,zlim=NULL, col=tim.colors(256),
transparent.color="white",...)
x locations of line segments
y locations of line segments
Values associated with each segment.
Range for z values to determine color scale.
Color table used for strip. Default is our favorite tim.colors being a scale from a dark blue to dark red.
Color used for missing values. Default is that missing values make the ribbon transparent.
Optional graphical arguments that are passed to the
segment
plotting function. A favorite is lwd to make a broad
ribbon.
Besides possible 2-d applications, this function is useful to annotate a curve on a surface using colors. The values mapped to acolor scheme could indicate a feature other than the height of the surface. For example, this function could indicate the slope of the surface.
image.plot, arrow.plot, add.image, colorbar.plot
# NOT RUN {
plot( c(-1.5,1.5),c(-1.5,1.5), type="n")
temp<- list( x= seq( -1,1,,40), y= seq( -1,1,,40))
temp$z <- outer( temp$x, temp$y, "+")
contour( temp, add=TRUE)
t<- seq( 0,.5,,50)
y<- sin( 2*pi*t)
x<- cos( pi*t)
z<- x + y
ribbon.plot( x,y,z, lwd=10)
persp( temp, phi=15, shade=.8, col="grey")-> pm
trans3d( x,y,z,pm)-> uv
ribbon.plot( uv$x, uv$y, z**2,lwd=5)
# }
Run the code above in your browser using DataLab