Is there any "add" parameter (like in graphics::curve) for ggplot2? - r

Question

i got some trouble with the ggplot. I drew some functions with ggplot and want to have them on the same graph.
With the curve function for instance i used to set the parameter add = T so the next plot will be put on the same graph.
curve(f.probit(x),add=T,col=col,lwd=lwd,lty=lty)
Now, i'm using the ggplot2 library... and want to do the same like with curve. Is there a parameter in ggplot like add, which allows to plot 2 curves on the graph?
qplot(my.data, aes(x, y, group = model, color = model)) +
geom_point() +
#geom_line() +
stat_function(fun = f.probit(x), geom = "line", aes(group = model, colour = model)) +
# Draw 2 lines at 50% and 90% through the y-axis
geom_hline(yintercept = c(50, 90), linetype = "dotted") + # draw dotted horizontal lines at 50 and 90
scale_x_continuous(x.lab, breaks = seq(-10, -4, 1), labels = my_labels) +
labs(title = "Graph", x = x.lab, y = y.lab)
Hier is my f.probit function:
beta1 <- -4.827511
beta2 <- -0.8401166
minv <- 0.05
maxv <- 1
f.probit <- function(x,beta1,beta2,minv,maxv){
return(pnorm(beta1+beta2*x)*(maxv-minv)+minv)
}
And i want to plot it on the graph with stat_function... But it doesn't work. I'm expecting some around this Graph:
these are the Data:
> xy
x y
[1,] -10 1.14259527
[2,] -9 1.15024188
[3,] -8 1.10517450
[4,] -7 1.00961311
[5,] -6 0.71238360
[6,] -5 0.20355333
[7,] -4 0.04061895
[8,] -10 1.11022461
[9,] -9 1.11083317
[10,] -8 1.07867942
[11,] -7 0.98422000
[12,] -6 0.73539660
[13,] -5 0.36134577
[14,] -4 0.18124645
[15,] -10 2.13212408
[16,] -9 1.14529425
[17,] -8 1.25102307
[18,] -7 1.16045169
[19,] -6 0.50321380
[20,] -5 0.15422609
[21,] -4 0.10198811
[22,] -10 1.16539392
[23,] -9 1.15855333
[24,] -8 1.11766975
[25,] -7 0.97204379
[26,] -6 0.53504417
[27,] -5 0.17431435
[28,] -4 0.29470416
[29,] -10 1.03683145
[30,] -9 1.07524250
[31,] -8 1.07761291
[32,] -7 0.96401682
[33,] -6 0.78346457
[34,] -5 0.32783725
[35,] -4 0.08103084
[36,] -10 0.81372339
[37,] -9 0.85402909
[38,] -8 0.86584396
[39,] -7 0.80705470
[40,] -6 0.53086151
[41,] -5 0.15711034
[42,] -4 0.11496499

Answer 1

You can layer as many plots as you want to:
dat1 <- data.frame(x=c(0, 10))
dat2 <- data.frame(x=c(4, 14))
my_tan <- function(x) { tan(x) }
ggplot() +
stat_function(data=dat1, aes(x), fun=sin, colour="red") +
stat_function(data=dat2, aes(x), fun=cos, colour="blue") +
stat_function(data=dat1, aes(x), fun=my_tan, colour="black") +
stat_function(data=dat2, aes(x), fun=my_tan, colour="white", linetype="dashed")

Answer 2

Edit: Response to OP's comment, and the addition of data in the question.
I see now what your problem is: if your function has arguments in addition to x, you have to pass these in stat_function(...) using the args=list(...) argument, as follows:
library(ggplot2)
ggplot(my.data, aes(x=x, y=y)) +
geom_point() +
stat_function(fun=f.probit, args=list(beta1, beta2, minv, maxv))
Your question illustrates a common misconception about ggplot. The graphics functions in base R plot the graph (or render the image). The ggplot functions create a ggplot object, but do not plot it. You have to use print(...) or plot(...) on the ggplot object to render the image.
Consider the following:
library(ggplot2)
ggp <- ggplot(mtcars, aes(x=wt, y=mpg)) +
geom_point() +
stat_function(fun=function(x) 60/x)
Notice that there is no image. You have to use print(ggp) or plot(ggp) to do that.
print(ggp)
Of course, typing the variable name at the command line will invoke the print method for that object, so
ggp
does the same thing. And of course, just typing an expression at the command line will evaluate the expression and print the result, which is why you get the image if you leave out the assigment:
# evaluate the expression to create ggplot object and then print it automatically.
ggplot(mtcars, aes(x=wt, y=mpg)) +
geom_point() +
stat_function(fun=function(x) 60/x)
Once you create a ggplot object (ggp in this example) you can add layers using +, so for instance
ggp + stat_function(fun=function(x) 30/x, color="red")
Finally, one of the great things about ggplot is that adding layers modifies the object (including the x- and y-limits). So for instance
ggp + stat_function(fun=function(x) 100/x, color="red")
Notice how the y-axis has been expanded to account for the new curve. Base R graphics do not work that way:
plot(mpg~wt, mtcars)
curve(100/x, add=TRUE)
Notice how the x- and y-limits have been defined in the initial call to plot(...).