I'm trying to create a user defined function in R with an optional argument to save the plot as a pdf. I have the required parameter to default to FALSE. If TRUE, then save to pdf with filename.pdf. Have I gotten some syntax wrong:
seeplot <-function (save=FALSE) {
x <- seq(1,10,1)
y <- x^2
plot (x,y,type="l")
if (save==TRUE) pdf(file="save")
}
Thanks.
I think it's from not reading ?pdf carefully that you're experiencing troubles. I'd let you struggle a bit (as struggle is good, shoot I often battle R) but I think maybe the logical save approach is not the best so I'll chime in. Here's 3 mistakes I see:
You call pdf but then never plot after that
You never say dev.off
There's no file extension to the pdf
Here is your function fixed:
seeplot <-function (save=FALSE) {
x <- seq(1,10,1)
y <- x^2
plot (x,y,type="l")
if (save) {
pdf(file="save.pdf")
plot (x,y,type="l")
dev.off()
}
}
But may I recommend supplying a file name instead of a logical save. This allows the user to name the file as they please:
seeplot <-function (file=NULL) {
x <- seq(1,10,1)
y <- x^2
plot (x,y,type="l")
if (!is.null(file)) {
pdf(file=file)
plot (x,y,type="l")
dev.off()
}
}
Related
I believe the answer to this is that I cannot, but rather than give in utterly to depraved desperation, I will turn to this lovely community.
How can I add points (or any additional layer) to a ggplot after already plotting it? Generally I would save the plot to a variable and then just tack on + geom_point(...), but I am trying to include this in a function I am writing. I would like the function to make a new plot if plot=T, and add points to the existing plot if plot=F. I can do this with the basic plotting package:
fun <- function(df,plot=TRUE,...) {
...
if (!plot) { points(dYdX~Time.Dec,data=df2,col=col) }
else { plot(dYdX~Time.Dec,data=df2,...) }}
I would like to run this function numerous times with different dataframes, resulting in a plot with multiple series plotted.
For example,
fun(df.a,plot=T)
fun(df.b,plot=F)
fun(df.c,plot=F)
fun(df.d,plot=F)
The problem is that because functions in R don't have side-effects, I cannot access the plot made in the first command. I cannot save the plot to -> p, and then recall p in the later functions. At least, I don't think I can.
have a ggplot plot object be returned from your function that you can feed to your next function call like this:
ggfun = function(df, oldplot, plot=T){
...
if(plot){
outplot = ggplot(df, ...) + geom_point(df, ...)
}else{
outplot = oldplot + geom_point(data=df, ...)
}
print(outplot)
return(outplot)
}
remember to assign the plot object returned to a variable:
cur.plot = ggfun(...)
I am a beginner in R. For example i have a function called w whose code is listed below:
w<-function(x){
a<-x+2
plot(a)
}
How can i add these arguments in the function so that
Export: a number equal to 0 if result should be allowed on screen and to 1 if the result should be printed in a text file.
Tfile: name of the text file where the results will be written to;
Gfile:name of the pdf file where the graph will be written to.
To include further arguments in a function, simply list them in function().
w <- function(x, export, tfile, gfile) {
a <- x + 2
if (export == 1) {
write.csv(a, file = tfile)
} else if (export == 0) {
pdf(file = gfile)
plot(a)
dev.off()
}
}
For more information on writing and debugging functions in R, see this article.
As the others have pointed out, just separate additional arguments with commas. You can have as many as you want.
w <- function(x, export, tfile, gfile)
Assigning values within the function definition allows them to have default arguments, so you can choose not to include them
w <- function(x, export = 0, tfile = "w.csv", gfile = "w.pdf")
I will add that a handy thing for plot functions (and many other functions) is the ellipsis ... construct, which basically means "any other relevant arguments". For instance, doing something like this allows you to optionally pass further graphical parameters to your plot (e.g. label names, title).
w <- function(x, ...){
a <- x + 2
plot(a, ...)
}
w(10, main="Main title")
w(15, type='l', col='red')
I am new to R. I've been trying to work on my code but I am having trouble understanding which 'parts' go where. This is the code I was given:
df=10
boxplot(rt(1000,df),rnorm(1000),names=c(paste("t,df=",df),"Standard Normal"))
x=seq(0,1,length=150)
plot(qt(x,df),qnorm(x),xlab=paste("t, df=",df),ylab="standard
Normal",main="qq-plot")
abline(0,1)
curve(dnorm(x),-3.5,3.5,main="Density Comparison")
curve(dt(x,df),lty=2,add=TRUE)
legend("topright",legend=c("standard
normal",paste("t,df=",df)),lty=c(1,2))
I am supposed to create a user defined function that takes df as the input and output 3 types of plots. I need to use: df=5,10,25, and 50.
This is what I have so far. Please dumb it down for me since I'm not very familiar with R terminology and I am not sure I am placing things where they are supposed to go..:
my.plot = function(n, df) {
a = rt(n,df)
b=rnorm(1000)
x= seq(0,1,length=150)
qt=qt(x,df)
qn=qnorm(x)
dn=dnorm(x)
ledt=dt(x,df)
n=1000
}
thebox= boxplot(a,b,names=c(paste("t,df=",df),"Stand rd Normal")) #1boxplot.
theplot= plot(qt,qn,xlab=paste("t, df=",df),ylab="standard Normal",main="qq-plot")
abline(0,1)
onecurve= curve(dn,-3.5,3.5,main="Density Comparison") #density curve
twocurve= curve(ledt, lty=2,add=TRUE)
legend("topright",legend=c("standard normal",paste("t,df=",df)),lty=c(1,2)
}
return(thebox)
return(theplot)
return(oneplot)
return(twocurve)
}
par(mfrow=c(1,3))
my.plot(1000,5)
my.plot(1000,10)
my.plot(1000,25)
my.plot(1000,50)
It works like this:
1. Your only input parameter is df. So your function will have only one input variable.
2. Since you already have the remaining code functional (i.e. after defining df) that code can be used as it is.
Below is a simple implementation from your demo code. You can modify it to suite your needs.
my.plot <- function(df) {
par(mfrow=c(1,3))
boxplot(rt(1000,df),rnorm(1000),names=c(paste("t,df=",df),"Standard Normal"))
x=seq(0,1,length=150)
plot(qt(x,df),qnorm(x),xlab=paste("t, df=",df),ylab="standard
Normal",main="qq-plot")
abline(0,1)
curve(dnorm(x),-3.5,3.5,main="Density Comparison")
curve(dt(x,df),lty=2,add=TRUE)
legend("topright",legend=c("standard
normal",paste("t,df=",df)),lty=c(1,2))
par(mfrow=c(1,1))
}
my.plot(5)
for(df in c(5,10,15,25)) my.plot(df)
I have written a function that draws some plots, and returns a list, similar in style to the following format:
myfun <- function(x, y){
plot(x, y)
points(x+1, y+1)
abline(v=x[1])
mylist <- list(x=x,y=y,line=x[1])
return(mylist)
}
This works fine. However, in R, one generally plots from functions in the following way:
x <- rnorm(100)
y <- rnorm(100)
lin <- lm(x~y)
plot(lin)
i.e., one creates an object using the function, then uses plot(object) to get the plot. How can I set up my function to behave in this way? I've had a look at a few guides to writing R packages (including hadley's), but I couldn't find reference to this problem.
I would like to create this functionality so I can upload what I've created to CRAN or R-Forge.
You could create your own S3 class for it (
R provides a lot of object oriented systems (S3, S4, R5, R.oo, ...), see also: http://adv-r.had.co.nz/OO-essentials.html):
# create an object with an own class
lin = list(x=rnorm(100), y=rnorm(100))
class(lin) = "mylin"
# overload plotting function
plot.mylin = function(l) {
plot(l$x, l$y)
points(l$x+1, l$y+1, col=2)
abline(v=l$x[1])
}
# run it
plot(lin)
R's plotting is great for data exploration, as it often has very intelligent defaults. For example, when plotting with a formula the labels for the plot axes are derived from the formula. In other words, the following two calls produce the same output:
plot(x~y)
plot(x~y, xlab="x", ylab="y")
Is there any way to get a similar "intelligent auto-title"?
For example, I would like to call
plot(x~y, main=<something>)
And produce the same output as calling
plot(x~y, main="plot(x~y)")
Where the <something> inserts the call used using some kind of introspection.
Is there a facility for doing this in R, either through some standard mechanism or an external package?
edit: One suggestion was to specify the formula as a string, and supply that as the argument to a formula() call as well as main. This is useful, but it misses out on parameters than can affect a plot, such as using subsets of data. To elaborate, I'd like
x<-c(1,2,3)
y<-c(1,2,3)
z<-c(0,0,1)
d<-data.frame(x,y,z)
plot(x~y, subset(d, z==0), main=<something>)
To have the same effect as
plot(x~y, subset(d, z==0), main="plot(x~y, subset(d, z==0))")
I don't think this can be done without writing a thin wrapper around plot(). The reason is that R evaluates "supplied arguments" in the evaluation frame of the calling function, in which there's no way to access the current function call (see here for details).
By contrast, "default arguments" are evaluated in the evaluation frame of the function, from where introspection is possible. Here are a couple of possibilities (differing just in whether you want "myPlot" or "plot" to appear in the title:
## Function that reports actual call to itself (i.e. 'myPlot()') in plot title.
myPlot <- function(x,...) {
cl <- deparse(sys.call())
plot(x, main=cl, ...)
}
## Function that 'lies' and says that plot() (rather than myPlot2()) called it.
myPlot2 <- function(x,...) {
cl <- sys.call()
cl[[1]] <- as.symbol("plot")
cl <- deparse(cl)
plot(x, main=cl, ...)
}
## Try them out
x <- 1:10
y <- 1:10
par(mfcol=c(1,2))
myPlot(x,y)
myPlot2(y~x)
Here's a more general solution:
plotCaller <- function(plotCall, ...) {
main <- deparse(substitute(plotCall))
main <- paste(main, collapse="\n")
eval(as.call(c(as.list(substitute(plotCall)), main=main, ...)))
}
## Try _it_ out
plotCaller(hist(rnorm(9999), breaks=100, col="red"))
library(lattice)
plotCaller(xyplot(rnorm(10)~1:10, pch=16))
## plotCaller will also pass through additional arguments, so they take effect
## without being displayed
plotCaller(xyplot(rnorm(10)~1:10), pch=16)
deparse will attempt to break deparsed lines if they get too long (the default is 60 characters). When it does this, it returns a vector of strings. plot methods assume that 'main' is a single string, so the line main <- paste(main, collapse='\n') deals with this by concatenating all the strings returned by deparse, joining them using \n.
Here is an example of where this is necessary:
plotCaller(hist(rnorm(9999), breaks=100, col="red", xlab="a rather long label",
ylab="yet another long label"))
Of course there is! Here ya go:
x = rnorm(100)
y = sin(x)
something = "y~x"
plot(formula(something),main=something)
You might be thinking of the functionality of match.call. However that only really works when called inside of a function, not passed in as an argument. You could create your wrapper function that would call match.call then pass everything else on to plot or use substitute to capture the call then modify it with the call before evaluating:
x <- runif(25)
y <- rnorm(25, x, .1)
myplot <- function(...) {
tmp <- match.call()
plot(..., main=deparse(tmp))
}
myplot( y~x )
myplot( y~x, xlim=c(-.25,1.25) )
## or
myplot2 <- function(FUN) {
tmp1 <- substitute(FUN)
tmp2 <- deparse(tmp1)
tmp3 <- as.list(tmp1)
tmp4 <- as.call(c(tmp3, main=tmp2))
eval(tmp4)
}
myplot2( plot(y~x) )
myplot2( plot(y~x, xlim=c(-.25,1.25) ) )