I'm plotting a survival curve with the survival library, and I haven't found any way to change the breaks range.
For example:
library(survival)
temps <- c(5,15,25,30,18,16,38,40,40,40,40,40,40,40,40,40)
deces <- c(1,0,1,1,1,0,1,1,0,0,0,0,0,0,0,0)
plot(survfit(Surv(temps,deces)~1))
Gives us this plot:
If I want, I can change the range of the whole axis with xlim=c(), the scale of abscissa numbers with xscale.
But the x breaks ranges will always stay at every 5 or 10 units (10,20,30,40).
It's impossible to change them to 12 for example, as I want (12, 24,36,...) because they should represent months.
Is this possible to change them? Or do I have to use the survminer library?
To customized the axes, save the survfit object and plot it with graphics parameter xaxt = "n", meaning, no x axis. Then plot the x axis with axis().
library(survival)
temps <- c(5,15,25,30,18,16,38,40,40,40,40,40,40,40,40,40)
deces <- c(1,0,1,1,1,0,1,1,0,0,0,0,0,0,0,0)
sv <- survfit(Surv(temps, deces) ~ 1)
plot(sv, xaxt = "n")
axis(1, at = seq(0, max(temps) + 12, by = 12))
Related
I am plotting the density of a two-dimensional, weighted spatial point pattern. I'd like to make the plot without a colour scale legend, and save it with no (or minimal) boarders on all sides, like this: My problem is that I can't remove the colour scale legend. Reproducible code below:
## Install libraries:
library(spatstat) #spatial package
library(RColorBrewer) #create custom colour ramps
## Create reproducible data:
data <- data.frame(matrix(ncol = 3, nrow = 50))
x <- c("x", "y", "weight")
colnames(data) <- x
data$x <- runif(50, 0, 20)
data$y <- runif(50, 0, 20)
data$weight <- sample(1:200, 50)
## Set plotting window and colours:
plot.win <- owin(c(0,20), c(0,20)) # plot window as 20x20m
spat.bat.frame <- NULL # create a frame to store values in
cols1<-colorRampPalette(brewer.pal(9,"Blues"))(100) #define colour ramp for density plots
## Create and save plots:
jpeg(filename = "Bad plot.jpeg", res = 300, units = "cm", width = 20, height = 20)
par(mar=c(0,0,0,0),oma=c(0,0,0,0),lwd=1)
ppp_01 <- ppp(x = data$x, y = data$y, window = plot.win)
ppp_02 <- ppp(x = data$x, y = data$y, window = plot.win)
plot(density(ppp_01, weights = data$weights), main=NULL, col=cols1, sigma = 1)
plot(ppp_02, add=TRUE) #add spp points to density plot
dev.off()
I've tried legend=FALSE, auto.key=FALSE, colorkey=FALSE, which don't seem to be compatible with plot() (i.e. they don't give an error but don't change anything). I've also tried some work-arounds like saving a cropped image with dev.off.crop() or by adjusting margins with par(), but haven't been able to completely remove the legend. Does anyone have any suggestions on how to remove a colour scale legend of a density spp (real-valued pixel image) using plot()?
I specifically need to plot the density of the spatial point pattern, to specify a custom colour ramp, and to overlay the spp points onto the density image. I could try plotting with spplot() instead, but I'm not sure this will allow for these three things, and I feel like I'm missing a simple fix with plot(). I can't crop the figures manually after saving from R because there are 800 of them, and I need them all to be exactly the same size and in the exact same position.
Thank you!
Since plot is a generic function, the options available for controlling the plot will depend on the class of object that is being plotted. You want to plot the result of density(ppp_01, weights = data$weights). Let's call this Z:
Z <- density(ppp_01, weights = data$weights, sigma=1)
Note: the smoothing bandwidth sigma should be given inside the call to density
To find out about Z, you can just print it, or type class(Z).
The result is that Z is an object of class"im" (pixel image).
So you need to look up the help file for plot.im, the plot method for class "im". Typing ?plot.im shows that there is an argument ribbon that controls whether or not the colour ribbon is displayed. Simply set ribbon=FALSE in the call to plot:
plot(Z, ribbon=FALSE, main="", col=cols1)
Or in your original code
plot(density(ppp_01, weights=data$weights, sigma=1), main="", col=cols1)
However I strongly recommend separating this into two lines, one which creates the image object, and one which plots the image. This makes it much easier to spot mistakes like the misplacement of the sigma argument.
I'm trying to use base R (and would like to stick to it for this problem) to plot a specific portion of a dataset.
My example data looks like below:
x <- c(1:100)
y <- sort(runif(100, min=0, max=1000))
When I plot this with plot(x,y, type='l'), I get a plot with a y axis that shows 0 to 1000. However, when I plot only a specific x range, my y axis still shows 0 to 1000. I would like to zoom in to reduce the y axis range.
For example,
plot(x,y, type='l', xlim=c(40,60))
plot(x,y, type='l', xlim=c(80,90))
both produces plots with a y axis that ranges c(0,1000). But I'd like to zoom in so that the y axis range for the first plot is something like c(300,700) and that for the second plot is c(700,1000). (300, 700 and 1000 are all arbitrary numbers just to illustrate the purpose to really zoom into the plot). Is there a way to do this without setting specific ylim?
I'd like to avoid using ylim because I'm plotting and saving in a for loop and I can't write a ylim that is suitable for all plots. I've thought of doing something like ylim = max(y)*1.5, but again, since I'm cutting the y values off based on xlim, this doesn't help with zooming in whenever xlim changes.
Subset the relevant data and plot that
lower = 40
upper = 60
ind = which(x >= lower & x <= upper)
plot(x[ind], y[ind], type = "l")
Let's consider a vector and plot it.
s1 <- sample(100:1000,32,replace = T)
plot(s1)
The plot I get has a Y-Axis that ranges from 0-1000 with points in the intervals of 200 (0,200,400,600,800,1000) and this is happening implicitly.
If I use ylim argument, apparently or to be honest, evidently, I can now have a custom range,
plot(s1,ylim = c(0,1500))
The points on Y Axis now are 0-1500 as indicated but with the points in the intervals of 500 (0,500,1000,1500), this is happening without my control.
My question, how can I have custom points with custom intervals on the X or Y axis?
use axis() to set your limits : on either x, y, or both
s1 <- sample(100:1000,32,replace = T)
plot(s1, yaxt = "n") # `yaxt` prevents y-axis labels to be printed
axis(2, yaxp=c(10, 1000, 10), las=2) # 'las' helps to align the tick mark labels along the axis or perpendicular
# 'yaxp' helps to set the break points you desire. Learn more from ?par
I regularly do all kinds of scatter plots in R using the plot command.
Sometimes both, sometimes only one of the plot axes is labelled in scientific notation. I do not understand when R makes the decision to switch to scientific notation. Surprisingly, it often prints numbers which no sane human would write in scientific notation when labelling a plot, for example it labels 5 as 5e+00. Let's say you have a log-axis going up to 1000, scientific notation is unjustified with such "small" numbers.
I would like to suppress that behaviour, I always want R to display integer values. Is this possible?
I tried options(scipen=10) but then it starts writing 5.0 instead of 5, while on the other axis 5 is still 5 etc. How can I have pure integer values in my R plots?
I am using R 2.12.1 on Windows 7.
Use options(scipen=5) or some other high enough number. The scipen option determines how likely R is to switch to scientific notation, the higher the value the less likely it is to switch. Set the option before making your plot, if it still has scientific notation, set it to a higher number.
You can use format or formatC to, ahem, format your axis labels.
For whole numbers, try
x <- 10 ^ (1:10)
format(x, scientific = FALSE)
formatC(x, digits = 0, format = "f")
If the numbers are convertable to actual integers (i.e., not too big), you can also use
formatC(x, format = "d")
How you get the labels onto your axis depends upon the plotting system that you are using.
Try this. I purposely broke out various parts so you can move things around.
library(sfsmisc)
#Generate the data
x <- 1:100000
y <- 1:100000
#Setup the plot area
par(pty="m", plt=c(0.1, 1, 0.1, 1), omd=c(0.1,0.9,0.1,0.9))
#Plot a blank graph without completing the x or y axis
plot(x, y, type = "n", xaxt = "n", yaxt="n", xlab="", ylab="", log = "x", col="blue")
mtext(side=3, text="Test Plot", line=1.2, cex=1.5)
#Complete the x axis
eaxis(1, padj=-0.5, cex.axis=0.8)
mtext(side=1, text="x", line=2.5)
#Complete the y axis and add the grid
aty <- seq(par("yaxp")[1], par("yaxp")[2], (par("yaxp")[2] - par("yaxp")[1])/par("yaxp")[3])
axis(2, at=aty, labels=format(aty, scientific=FALSE), hadj=0.9, cex.axis=0.8, las=2)
mtext(side=2, text="y", line=4.5)
grid()
#Add the line last so it will be on top of the grid
lines(x, y, col="blue")
You can use the axis() command for that, eg :
x <- 1:100000
y <- 1:100000
marks <- c(0,20000,40000,60000,80000,100000)
plot(x,y,log="x",yaxt="n",type="l")
axis(2,at=marks,labels=marks)
gives :
EDIT : if you want to have all of them in the same format, you can use the solution of #Richie to get them :
x <- 1:100000
y <- 1:100000
format(y,scientific=FALSE)
plot(x,y,log="x",yaxt="n",type="l")
axis(2,at=marks,labels=format(marks,scientific=FALSE))
You could try lattice:
require(lattice)
x <- 1:100000
y <- 1:100000
xyplot(y~x, scales=list(x = list(log = 10)), type="l")
The R graphics package has the function axTicks that returns the tick locations of the ticks that the axis and plot functions would set automatically. The other answers given to this question define the tick locations manually which might not be convenient in some situations.
myTicks = axTicks(1)
axis(1, at = myTicks, labels = formatC(myTicks, format = 'd'))
A minimal example would be
plot(10^(0:10), 0:10, log = 'x', xaxt = 'n')
myTicks = axTicks(1)
axis(1, at = myTicks, labels = formatC(myTicks, format = 'd'))
There is also an log parameter in the axTicks function but in this situation it does not need to be set to get the proper logarithmic axis tick location.
Normally setting axis limit # max of your variable is enough
a <- c(0:1000000)
b <- c(0:1000000)
plot(a, b, ylim = c(0, max(b)))
I regularly do all kinds of scatter plots in R using the plot command.
Sometimes both, sometimes only one of the plot axes is labelled in scientific notation. I do not understand when R makes the decision to switch to scientific notation. Surprisingly, it often prints numbers which no sane human would write in scientific notation when labelling a plot, for example it labels 5 as 5e+00. Let's say you have a log-axis going up to 1000, scientific notation is unjustified with such "small" numbers.
I would like to suppress that behaviour, I always want R to display integer values. Is this possible?
I tried options(scipen=10) but then it starts writing 5.0 instead of 5, while on the other axis 5 is still 5 etc. How can I have pure integer values in my R plots?
I am using R 2.12.1 on Windows 7.
Use options(scipen=5) or some other high enough number. The scipen option determines how likely R is to switch to scientific notation, the higher the value the less likely it is to switch. Set the option before making your plot, if it still has scientific notation, set it to a higher number.
You can use format or formatC to, ahem, format your axis labels.
For whole numbers, try
x <- 10 ^ (1:10)
format(x, scientific = FALSE)
formatC(x, digits = 0, format = "f")
If the numbers are convertable to actual integers (i.e., not too big), you can also use
formatC(x, format = "d")
How you get the labels onto your axis depends upon the plotting system that you are using.
Try this. I purposely broke out various parts so you can move things around.
library(sfsmisc)
#Generate the data
x <- 1:100000
y <- 1:100000
#Setup the plot area
par(pty="m", plt=c(0.1, 1, 0.1, 1), omd=c(0.1,0.9,0.1,0.9))
#Plot a blank graph without completing the x or y axis
plot(x, y, type = "n", xaxt = "n", yaxt="n", xlab="", ylab="", log = "x", col="blue")
mtext(side=3, text="Test Plot", line=1.2, cex=1.5)
#Complete the x axis
eaxis(1, padj=-0.5, cex.axis=0.8)
mtext(side=1, text="x", line=2.5)
#Complete the y axis and add the grid
aty <- seq(par("yaxp")[1], par("yaxp")[2], (par("yaxp")[2] - par("yaxp")[1])/par("yaxp")[3])
axis(2, at=aty, labels=format(aty, scientific=FALSE), hadj=0.9, cex.axis=0.8, las=2)
mtext(side=2, text="y", line=4.5)
grid()
#Add the line last so it will be on top of the grid
lines(x, y, col="blue")
You can use the axis() command for that, eg :
x <- 1:100000
y <- 1:100000
marks <- c(0,20000,40000,60000,80000,100000)
plot(x,y,log="x",yaxt="n",type="l")
axis(2,at=marks,labels=marks)
gives :
EDIT : if you want to have all of them in the same format, you can use the solution of #Richie to get them :
x <- 1:100000
y <- 1:100000
format(y,scientific=FALSE)
plot(x,y,log="x",yaxt="n",type="l")
axis(2,at=marks,labels=format(marks,scientific=FALSE))
You could try lattice:
require(lattice)
x <- 1:100000
y <- 1:100000
xyplot(y~x, scales=list(x = list(log = 10)), type="l")
The R graphics package has the function axTicks that returns the tick locations of the ticks that the axis and plot functions would set automatically. The other answers given to this question define the tick locations manually which might not be convenient in some situations.
myTicks = axTicks(1)
axis(1, at = myTicks, labels = formatC(myTicks, format = 'd'))
A minimal example would be
plot(10^(0:10), 0:10, log = 'x', xaxt = 'n')
myTicks = axTicks(1)
axis(1, at = myTicks, labels = formatC(myTicks, format = 'd'))
There is also an log parameter in the axTicks function but in this situation it does not need to be set to get the proper logarithmic axis tick location.
Normally setting axis limit # max of your variable is enough
a <- c(0:1000000)
b <- c(0:1000000)
plot(a, b, ylim = c(0, max(b)))