CODEWITHSUNDEEP
rplot
Nane
Nane

Reputation: 15

Sensitivity analysis with R: How can I make my own plot

Do you know the method to do my own plot of sensitivity analysis result using R?

For example (using fast99() and a toy model): 

> library(sensitivity)
> x <- fast99(model = ishigami.fun, factors = 3, n = 1000,
              q = "qunif", q.arg = list(min = -pi, max = pi))
> print(x)
> Call:
> fast99(model = ishigami.fun, factors = 3, n = 1000, q = "qunif",
         q.arg = list(min = -pi, max = pi))
> Model runs: 3000 
> Estimations of the indices:
>    first order     total order
> X1 3.076874e-01   0.5506015
> X2 4.419659e-01   0.4697538
> X3 3.431342e-29   0.2391275

I just want to pick the data of the estimations of the indices (X1, X2, X3), to put them in a matrix... Any ideas?

Upvotes: 1

Views: 2685

Answers (1)

MrFlick
MrFlick

Reputation: 206253

Perhaps something like this could work. First, a helper function to turn the fast99 data into a data.frame

as.data.frame.fast99 <- function(x, ...) {
    if (!is.null(x$y)) {
        S <- data.frame(X=colnames(x$X), x$D1/x$V, 1 - x$Dt/x$V)
        colnames(S)[-1] <- c("first.order", "total.order")
        S
    }
}

And now we plot the data. (Here I use the ggplot library but you could easily use others)

dd<-as.data.frame(x)
library(ggplot2)
ggplot(dd, aes(x=X)) + 
   geom_point(aes(y=first.order, color="first")) + 
   geom_point(aes(y=total.order, color="total")) + 
   scale_color_manual(values=c(first="red",total="blue"), name="order")

enter image description here

Upvotes: 2

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