I am trying to create and record plots in a 1x1 device:
par(mfrow = c(1, 1) )
plot(rnorm(10) )
p1 <- recordPlot()
plot(rnorm(20) )
p2 <- recordPlot()
and then to put them in a new layout (e.g., a 1x2 device):
par(mfrow = c(1, 2) )
p1
p2
However, this produce the same effect (i.e., plotting each plot in a 1x1 device). It seems replaying plots uses the original layout (graphical parameters) that was in effect when they were recorded.
Is there some method that allows a saved plot to be replayed in a new layout ?
NB: I am aware this would be easier via ggplot2, but my question is about base plots.
I did some digging, and I don't think this is possible. I used the following to look at what attributes are available inside the object. None of them seemed to indicate the layout could be adjusted.
summary(p1)
p1[[1]]
p1[[2]]
If you need the same plot across two different layouts could you use set.seed() to recreated the same plot? See the example below.
par(mfrow = c(1, 1))
set.seed(1234)
plot(rnorm(10))
par(mfrow = c(1, 2))
set.seed(1234)
plot(rnorm(10))
I'd be interested to see if anyone else has a better answer!
Related
I am trying to automate a series of analyses which are intended to save a number of plots for later inspection. One of the plots will be accompanied by a table of values. I'd like to have them in the same pdf so that the users don't have to jump between files.
I have checked numerous questions on SO regarding outputting data frames to pdf, here are a couple of reasons why existing answers aren't satisfactory in my case:
Not familiar with knitr/Sweave
Batch generation of figures mean that I cannot do it manually via RStudio Viewer
grid.table based solutions do not generate the entire table.
Which brings me to my problems, say I have a table 48 x 5 in proportions. If I try to plot it out with grid.table(geno) it results in a cropped table showing some 20-30 rows in the middle. If I go with grid.table(geno, gp = gpar(fontsize=8)) to decrease the fontsize I get the following error message.
Error in gtable_table(d, name = "core", fg_fun = theme$core$fg_fun, bg_fun = theme$core$bg_fun, :
unused argument (gp = list(fontsize = 8)
)
Essentially I would like to be able to use it in this way:
library(grid)
library(gridExtra)
pdf(file="gtype.pdf", title = "Genotype data")
plotGenotype(geno, text_size = 10) # outputs a custom plot
grid.newpage()
grid.table(geno) # grid.table(geno, gp = gpar(fontsize=8))
dev.off()
The problem here is that I either get a cropped table or nothing at all, on the second page. I noticed that many people add height=11, width=8.5 to the pdf() call. I am not sure if/why that would make a difference but setting paper="a4" or height/width according to A4 does not make any difference in my case.
Q1: Is it not possible to get grid.table to resize based on content and not paper?
Q2: Is there some other way to get a data frame printed to a pdf without having to go through LaTeX based solutions?
(I am currently running R 3.3.1 and gridExtra 2.2.1)
Q1: Is it not possible to get grid.table to resize based on content and not paper?
It is possible, but generally not desirable. A table is meant to be read, and if text and spacings were determined by the page rather than the content, it would often yield unreadable results. Thus the usual advice: manually tweak the font size and padding, or split the table.
It is by no means a technical limitation: feel free to set the cell size to fit the page:
grid.newpage()
pushViewport(viewport(width=unit(0.8,"npc"), height=unit(0.8,"npc")))
g <- g2 <- tableGrob(iris[1:4, 1:3], cols = NULL, rows=NULL)
g2$heights <- unit(rep(1/nrow(g2), nrow(g2)), "npc")
grid.arrange(rectGrob(), rectGrob(), nrow=1, newpage = FALSE)
grid.arrange(g, g2, nrow=1, newpage = FALSE)
but with too much content for the page it's unclear what result is better
grid.newpage()
pushViewport(viewport(width=unit(0.8,"npc"), height=unit(0.8,"npc")))
g <- g2 <- tableGrob(iris[1:20, 1:3], cols = NULL, rows=NULL)
g3 <- tableGrob(iris[1:20, 1:3], cols = NULL, rows=NULL, theme=ttheme_default(base_size=7))
g2$heights <- g3$heights <- unit(rep(1/nrow(g2), nrow(g2)), "npc")
grid.arrange(rectGrob(), rectGrob(), rectGrob(), nrow=1, newpage = FALSE)
grid.arrange(g, g2, g3, nrow=1, newpage = FALSE)
If the page size can be changed, it is usually the best option. One can query the table size before drawing, convert it to inches, and pass it to the device.
g1 <- tableGrob(iris[1:4, 1:5])
g2 <- tableGrob(iris[1:20, 1:5])
maxheight <- convertHeight(sum(g2$heights), "in", TRUE)
pdf("fit.pdf", height=maxheight)
grid.draw(g1)
grid.newpage()
grid.draw(g2)
dev.off()
However, as far as I know all pages in a given pdf will have to have the same size (there might be ways around it, but tricky).
I have found that the beanplot is the best way to represent my data. I want to look at multiple beanplots together to visualize my data. Each of my plots contains 3 variables, so each one looks something like what would be generated by this code:
library(beanplot)
a <- rnorm(100)
b <- rnorm(100)
c <- rnorm(100)
beanplot(a, b ,c ,ylim = c(-4, 4), main = "Beanplot",
col = c("#CAB2D6", "#33A02C", "#B2DF8A"), border = "#CAB2D6")
(Would have just included an image but my reputation score is not high enough, sorry)
I have 421 of these that I want to put into one long PDF (EDIT: One plot per page is fine, this was just poor wording on my part). The approach I have taken was to first generate the beanplots in a for loop and store them in a list at each iteration. Then I will use the multiplot function (from the R Cookbook page on multiplot) to display all of my plots on one long column so I can begin my analysis.
The problem is that the beanplot function does not appear to be set up to assign plot objects as a variable. Example:
library(beanplot)
a <- rnorm(100)
b <- rnorm(100)
plot1 <- beanplot(a, b, ylim = c(-5,5), main = "Beanplot",
col = c("#CAB2D6", "#33A02C", "#B2DF8A"), border = "#CAB2D6")
plot1
If you then type plot1 into the R console, you will get back two of the plot parameters but not the plot itself. This means that when I store the plots in the list, I am unable to graph them with multiplot. It will simply return the plot parameters and a blank plot.
This behavior does not seem to be the case with qplot for example which will return a plot when you recall the stored plot. Example:
library(ggplot2)
a <- rnorm(100)
b <- rnorm(100)
plot2 <- qplot(a,b)
plot2
There is no equivalent to the beanplot that I know of in ggplot. Is there some sort of workaround I can use for this issue?
Thank you.
You can simply open a PDF device with pdf() and keep the default parameter onefile=TRUE. Then call all your beanplot()s, one after the other. They will all be in one PDF document, each one on a separate page. See here.
I have the following Problem. After running an ordered logit model, I want to R's effects package to visualize the results. This works fine and I did so for two independent variables, then I tried to combine the two plots. However, this does not seem to work. I provide a little replicable example here so you can see my problem for yourself:
library(car)
data(Chile)
mod <- polr(vote ~ age + log(income), data=Chile)
eff <- effect("log(income)", mod)
plot1 <- plot(eff, style="stacked",rug=F, key.args=list(space="right"))
eff2 <- effect("age", mod)
plot2 <- plot(eff2, style="stacked",rug=F, key.args=list(space="right"))
I can print these two plots now independently, but when I try to plot them together, the first plot is overwritten. I tried setting par(mfrow=c(2,1)), which didn't work. Next I tried the following:
print(plot1, position=c(0, .5, 1, 1), more=T)
print(plot2, position=c(0,0, 1, .5))
In this latter case, the positions of the two plots are just fine, but still the first plot vanishes once I add the second (or better, it is overwritten). Any suggestions how to prevent this behavior would be appreciated.
Reading down the long list of arguments to ?print.eff we see that there are some arguments for doing just this:
plot(eff, style="stacked",rug=F, key.args=list(space="right"),
row = 1,col = 1,nrow = 1,ncol = 2,more = TRUE)
plot(eff2, style="stacked",rug=F, key.args=list(space="right"),
row = 1,col = 2,nrow = 1,ncol = 2)
The reason par() didn't work is because this package is using lattice graphics, which are based on the grid system, which is incompatible with base graphics. Neither par() nor layout will have any effect on grid graphics.
This seems to work:
plot(eff,col=1,row=2,ncol=1,nrow=2,style="stacked",rug=F,
key.args=list(space="right"),more=T)
plot(eff2,col=1,row=1,ncol=1,nrow=2,style="stacked",rug=F,
key.args=list(space="right"))
edit: Too late...
I'm trying to plot 6 days of intraday data as 6 charts. Quantmod's experimental chart_Series() function works with par() settings. I've pre-loaded the data into bars (a vector of XTS objects) so my code looks like this:
par(mfrow=c(3,2)) #3 rows, 2 columns
for(d in bars){
print(chart_Series(d, type = "candlesticks") )
}
This works, but each chart has its own different y-axis scale. I wanted to set a y-range that covers all 6 days, but cannot find a way to do this. I tried this:
ylim=c(18000,20000)
print(chart_Series(d, type = "candlesticks",ylim=ylim) )
but it fails with the "unused argument(s)" error. yrange=ylim also fails.
I can use chartSeries(d,yrange=ylim), and it works. But as far as I know I cannot put multiple charts in one display (?).
(It might strictly be off-subject, but suggestions for alternative R packages that can draw nice-looking candlestick charts, allow y-axis control and can draw multiple charts on one image would also be very welcome.)
With chartSeries, you can set the layout argument to NULL to prevent the layout() command from being called: this is what disables the mfrow setting.
library(quantmod)
getSymbols("AA")
op <- par(mfrow=c(3,2))
for(i in 1:6) {
chartSeries(
AA["2011-01"], "candlesticks",
TA=NULL, # No volume plot
layout=NULL,
yrange=c(15,18)
)
}
par(op)
If you want to keep the volume, you can call layout instead of setting mfrow: it does basically the same thing, but allows you to have plots of different sizes and choose the order in which they are plotted.
layout( matrix( c(
1, 3,
2, 4,
5, 7,
6, 8,
9, 11,
10, 12
), nc=2, byrow=TRUE),
heights = rep( c(2,1), 3 )
)
#layout.show(12) # To check that the order is as desired
for(i in 1:6) {
chartSeries(
AA[sprintf("2011-%02d",i)],
"candlesticks", layout=NULL, yrange=c(15,19)
)
}
Googling to understand Vincent's answer led me to the layout() command. It seems incompatible with par(mfrow), but some more experimentation found it can be used as an alternative.
ylim=c(18000,20000)
layout(matrix(1:12,nrow=6,ncol=2), height=c(4,2,4,2,4,2))
for(d in bars){
chartSeries(d,layout=NULL,TA=c(addVo(),addBBands()),yrange=ylim)
}
(You'll notice I added bollinger bands too, to be sure overlays still work too.)
I would like to place two (somewhat non-standard) grid graphics in a single plot in R.
Try:
require(vcd)
mosaic(Titanic)
assoc(Titanic)
The trouble is that these aren't lattice graphics, and to my knowledge do not come with a layout argument or similar. And since these are grid graphs, they're impervious to base graph tricks like par(mfrow=c(1,2)).
How can I place the two graphs above in a single plot, with both graphs on the same line?
I already tried the suggestions in How to plot grid plots on a same page?, but they don't seem to work for vcd plots. Ultimately I would like to obtain something similar to:
Neither plot seems to return any object and I cant see how to grab the grobs from looking at grid.ls(). So using the idea from this answer
library(vcd)
library(gridGraphics)
library(gridExtra)
mosaic(Titanic)
m <- grid.grab()
assoc(Titanic)
a <- grid.grab()
grid.newpage()
grid.arrange(m, a, ncol=2)
Im sure there will be a more grid-like approach but ...
Something similar to the solution in How to plot grid plots on a same page? can also be used for vcd displays. The difference is that you need to set newpage = FALSE (to prevent opening a new display) and you need to push and pop the viewport yourself (which can be handy when re-using vcd graphics in more complicated displays such as partykit trees).
The mosaic and association display for the Titanic data can be visualized as:
grid.newpage()
pushViewport(viewport(layout = grid.layout(1, 2)))
pushViewport(viewport(layout.pos.col = 1, layout.pos.row = 1))
mosaic(Titanic, newpage = FALSE)
popViewport()
pushViewport(viewport(layout.pos.row = 1, layout.pos.col = 2))
assoc(Titanic, newpage = FALSE)
popViewport()
yielding
Another option is vcd’s mplot() function (for details, see ?vcd::mplot):
library(vcd)
mplot(
mosaic(Titanic, return_grob = TRUE),
assoc(Titanic, return_grob = TRUE),
keep_aspect_ratio = FALSE
)