| taylor.diagram {plotrix} | R Documentation |
Display a Taylor diagram.
taylor.diagram(ref,model,add=FALSE,col="red",pch=19,pos.cor=TRUE, xlab="",ylab="",main="Taylor Diagram",show.gamma=TRUE,ref.sd=FALSE, pcex=1,normalize=FALSE,...)
ref |
numeric vector - the reference values. |
model |
numeric vector - the predicted model values. |
add |
whether to draw the diagram or just add a point. |
col |
the color for the points displayed. |
pch |
the type of point to display. |
pos.cor |
whether to display only positive (TRUE) or all
values of correlation (FALSE). |
xlab,ylab |
plot axis labels. |
main |
title for the plot. |
show.gamma |
whether to display standard deviation arcs around
the reference point (only for pos.cor=TRUE). |
ref.sd |
whether to display the arc representing the reference standard deviation. |
pcex |
character expansion for the plotted points. |
normalize |
whether to normalize the models so that the reference has a standard deviation of 1. |
... |
Additional arguments passed to plot. |
The Taylor diagram is used to display the quality of model predictions against the reference values, typically direct observations.
A diagram is built by plotting one model against the reference,
then adding alternative model points. If normalize=TRUE
when plotting the first model, remember to set it to TRUE
when plotting additional models.
Two displays are available. One displays the entire range of correlations
from -1 to 1. Setting pos.cor to FALSE will produce this
display. The -1 to 1 display includes a radial grid for the correlation
values. When pos.cor is set to TRUE, only the
range from 0 to 1 will be displayed. The gamma lines and the arc at
the reference standard deviation are optional in this display.
The values of par that preceded the function. This allows the
user to add points to the diagram, then restore the original values. This
is only necessary when using the 0 to 1 correlation range.
Olivier Eterradossi with modifications by Jim Lemon
Taylor, K.E. (2001) Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research, 106: 7183-7192.
# fake some reference data
ref<-rnorm(30,sd=2)
# add a little noise
model1<-ref+rnorm(30)/2
# add more noise
model2<-ref+rnorm(30)
# display the diagram with the better model
oldpar<-taylor.diagram(ref,model1)
# now add the worse model
taylor.diagram(ref,model2,add=TRUE,col="blue")
# get approximate legend position
lpos<-1.5*sd(ref)
# add a legend
legend(lpos,lpos,legend=c("Better","Worse"),pch=19,col=c("red","blue"))
# now restore par values
par(oldpar)
# show the "all correlation" display
taylor.diagram(ref,model1,pos.cor=FALSE)
taylor.diagram(ref,model2,add=TRUE,col="blue")