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Taylor diagramDescription
Display a Taylor diagram.
Usage taylor.diagram(ref,model,add=FALSE,col="red",pch=19,pos.cor=TRUE, xlab="",ylab="",main="Taylor Diagram",show.gamma=TRUE,ngamma=3, sd.arcs=0,ref.sd=FALSE,grad.corr.lines=c(0.2,0.4,0.6,0.8,0.9), pcex=1,normalize=FALSE,...)Arguments
Details
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.
Both the standard deviation arcs and the gamma lines are optional in the pos.cor=TRUE version. Setting sd.arcs or grad.corr.lines to zero or FALSE will cause them not to be displayed. If more than one value is passed for sd.arcs, the function will try to use the values passed, otherwise it will call prettyto calculate the values.
Value
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.
Author(s)
Olivier Eterradossi with modifications by Jim Lemon
References
Taylor, K.E. (2001) Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research, 106: 7183-7192.
Examples # 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") 复制代码
[Package plotrix version 2.6-1
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