Converting a base graph one by one to their grid equivalent using the solution with gridGraphics package (here) works without issues. However, when I try to put that in a loop I do not get the expected. Here is an example:
library(gridGraphics)
### Make a list of 3 base plots -----
p <- vector(mode = "list", length = 3)
for (i in 1:3){
plot(1:5^i)
p[[i]] <- recordPlot()
}
### Attempt to convert each base plot to its grid equivalent -----
grobs <- vector(mode = "list", length = 3)
for (i in 1:3){
plot.new() # clean up device
p[[i]] # redraw
# Echo graphics output using grid graphics
grid.echo()
# Creates a gTree object from the current grid display list
a_gTree <- grid.grab()
grobs[[i]] <- editGrob(grob = a_gTree,
vp = viewport(width = unit(5, "cm"),
height = unit(5, "cm"),
angle = 90)) # rotates 90 dg
}
If I run the chunk of code inside the loop for each step I get what I need, but when I run the loop in one shot, then all grobs seems to display nothing. I feel that there is something obvious that I'm missing ...
Here is a desired output (obtained by running step by step):
cowplot::plot_grid(grobs[[1]],
grobs[[2]],
grobs[[3]])
Thanks to #user20650 to pointing out the usage of print() in the loop, so using print(p[[i]]) instead of p[[i]]. Or even better, I prefer his elegant suggestion to save some lines with using a_gTree <- grid.grabExpr(grid.echo(p[[i]])). Where grid.grabExpr captures the output from an expression without drawing anything. Also plot.new() seems optional.
for (i in 1:3){
# Grab grid output
a_gTree <- grid.grabExpr(grid.echo(p[[i]]))
# Edit/modify the grob
grobs[[i]] <- editGrob(grob = a_gTree,
vp = viewport(width = unit(5, "cm"),
height = unit(5, "cm"),
angle = 90)) # rotates 90 dg
}
Related
This is a follow on question to my original here
I am currently trying to save the outputs of a ggplot graph to .pdf but I am running into some problems.
I run the following on the dput data on the original question (I repaste everything below).
library(gridExtra)
pdf("Plots.pdf", onefile = TRUE)
for(j in 1:length(plotList)) {
grid.arrange(plotList[[j]], nrow = 2)
}
dev.off()
This saves the files as a pdf document but instead of getting two graphs per page I get one graph which takes up half a page. Is it possible to resize the graphs, when I select nrow = 3 I get the same problem, I get one graph in the top 3rd / half of the page and a blank space for the rest. I provide a screen shot of the output:
Here is a minimal example:
# Make empty list for plots
plotList <- list()
# Build plots
library(ggplot2)
for(i in 1:2){
plotList[[i]] <-
ggplot(mtcars, aes(mpg, cyl)) +
geom_point() +
labs(title = i)
}
# Save plots
library(gridExtra)
pdf("Plots.pdf", onefile = TRUE)
for(j in 1:length(plotList)) {
grid.arrange(plotList[[j]], nrow = 2)
}
dev.off()
Credit to #LachlanO
You problem comes from how you are calling grid.arrange. By including it in a loop, you are telling it to create multiple separate plots, like this:
grid.arrange(plotList[[1]], nrow = 2)
grid.arrange(plotList[[2]], nrow = 2)
grid.arrange(plotList[[3]], nrow = 2)
What you actually are trying to do is create one grid.arrange object which contains all the plots. To do this, you need call the function against the list:
do.call("grid.arrange", c(plotList, nrow=2))
Alternatively, you can use the cowplot package and use:
cowplot::plot_grid(plotlist = plotList, nrow = 2)
So to save the PDF you can use:
pdf("Plots.pdf", onefile = TRUE)
do.call("grid.arrange", c(plotList, nrow=2))
dev.off()
I want to create a grid of 9 images with equal spacing between them. Until now I managed to get something to work with par() and layout().
layout(matrix(1:9, widths=rep(lcm(4),9), heights=rep(lcm(3),9))
for (i in 1:9) {
imNew <- readImage(img_ar[i])
EBImage::display(imNew, method="raster")
}
gives me this
while using par:
layout(matrix(1:9, widths=rep(lcm(4),9), heights=rep(lcm(3),9))
for (i in 1:9) {
imNew <- readImage(img_ar[i])
EBImage::display(imNew,method="raster")
}
gives me this:
I also tried different options for par() like oma, mai and mar but these didn't change the spacing in between the individual images. What I like to have is an equal distance between the individual images like this:
Could anyone help me please?
You can use your original idea to separate images by including additional empty rows and columns in your layout, as in the following example. Note, however, that in order to achieve equal horizontal and vertical spacing you will need to tweak the device dimensions.
library(EBImage)
# load sample image
img <- readImage(system.file("images", "sample-color.png", package="EBImage"))
# downsample to reduce memory consumption and for faster processing
img <- resize(img, 192)
# build the layout matrix with additional separating cells
nx <- 4 # number of images in a row
ny <- 3 # number of images in a column
cols <- 2*nx-1
rows <- 2*ny-1
m <- matrix(0, cols, rows)
m[2*(1:nx)-1, 2*(1:ny)-1] <- 1:(nx*ny)
m <- t(m)
# relative spacing
pad <- .1
w <- rep(1, cols)
w[!(1:cols)%%2] <- pad
h <- rep(1, rows)
h[!(1:rows)%%2] <- pad * dim(img)[1L]/dim(img)[2L]
layout(m, widths = w, heights = h)
layout.show(nx*ny)
for (i in 1:(nx*ny)) {
display(img, method="raster")
}
A better approach is to use display() on an image stack. Then individual frames can be displayed arranged in a grid by setting all=TRUE.
## construct sample image stack
img_stack <- combine(replicate(nx*ny, img, simplify=FALSE))
display(img_stack, method="raster", all=TRUE)
Unfortunately, until recently it was not possible to adjust the spacing between the frames. To facilitate this, I've added an argument to display() specifying the spacing. Currently this new feature is available in the development version of EBImage, which can be obtained either from GitHub devtools::install_github("aoles/EBImage"), or from the Bioconductor devel branch.
The spacing can be provided as a fraction of frame dimensions (positive numbers <1) or in pixels (numbers >=1). Additionally, you can have different horizontal and vertical separation by providing a vector, e.g. spacing = (10, 20) will separate the columns by 10px, and the rows by 20px.
display(img_stack, method="raster", all=TRUE, spacing=.1)
Furthermore, you can add a margin around the grid, and control its layout by nx. The background can be set through bg passed to par().
Finally, a completely different way of drawing images in a grid is to construct one big composite image with tile. This approach might be useful, for example, when saving the result to a file. Note the additional border around the whole grid.
## tiled composite image
img_tiles <- tile(img_stack, nx=nx, lwd=20, fg.col="white", bg.col="white")
display(img_tiles, method="raster")
The ggplot2 way with marrangeGrob() from gridExtra:
library(RCurl)
library(png)
library(grid)
library(gridExtra)
library(ggplot2)
# read a few MNIST images
urls <- c('https://i.imgur.com/TEbkTqu.png', 'https://i.imgur.com/tnsjMFJ.png', 'https://i.imgur.com/VUZgJBs.png', 'https://i.imgur.com/FZ28d3w.png')
imgs <- list()
for (i in 1:length(urls)) {
imgs[[i]] <- readPNG(getURLContent(urls[i]))
}
# plot grid and show images
plist <- list()
for (i in 1:length(imgs)) {
plist[[i]] <- ggplot() +
annotation_custom(rasterGrob(imgs[[i]], interpolate=TRUE), xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) +
labs(x = NULL, y = NULL) +
guides(x = "none", y = "none") +
theme_bw() +
theme(legend.position = "none", panel.border = element_blank(), panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
}
marrangeGrob(plist, nrow=2, ncol=2, respect=TRUE)
(Demonstrated here in the shiny app too)
Im trying to use the caTools package to combine multiple plots into a gif.
My basic code looks like :
for( i in 1:100){
plot(....) // plots few points and lines, changes slightly with each i
}
I would like to combine these to a gif to see the "evolution" of the plot.
However for write.gif() from caTools, I need to give an image as an input.
For each i, how do I convert the plot into an image without
saving to disc as an intermediate step
depending on ImageMagick or similar external dependencies.
Please feel free to point out if this is a duplicate. [ Creating a Movie from a Series of Plots in R doesnt seem to answer this ]
EDIT: Basically this requires us to convert a plot to a matrix. Since this very likely happens every time someone saves a plot, it should not be very difficult. However Im not able to get hold of how to exactly do this.
I suggest using the animation package and ImageMagick instead:
library(animation)
## make sure ImageMagick has been installed in your system
saveGIF({
for (i in 1:10) plot(runif(10), ylim = 0:1)
})
Otherwise you could try it in the veins of this (plenty of room for optimization):
library(png)
library(caTools)
library(abind)
# create gif frames and write them to pngs in a temp dir
dir.create(dir <- tempfile(""))
for (i in 1:8) {
png(file.path(dir, paste0(sprintf("%04d", i), ".png")))
plot(runif(10), ylim = 0:1, col = i)
dev.off()
}
# read pngs, create global palette, convert rasters to integer arrays and write animated gif
imgs <- lapply(list.files(dir, full.names = T), function(fn) as.raster(readPNG(fn)))
frames <- abind(imgs, along = 3) # combine raster pngs in list to an array
cols <- unique(as.vector(frames)) # determine unique colors, should be less then 257
frames <- aperm(array(match(frames, cols) - 1, dim = dim(frames)), c(2,1,3)) # replace rgb color codes (#ffffff) by integer indices in cols, beginning with 0 (note: array has to be transposed again, otherwise images are flipped)
write.gif(
image = frames, # array of integers
filename = tf <- tempfile(fileext = ".gif"), # create temporary filename
delay = 100, # 100/100=1 second delay between frames
col = c(cols, rep("#FFFFFF", 256-length(cols))) # color palette with 256 colors (fill unused color indices with white)
)
# open gif (windows)
shell.exec(tf)
Is that what you are looking for?
library(ggplot2)
a <- 0:10
df <- data.frame(a=a,b=a)
steps <-function(end){
a <- ggplot(df[1:end,], aes(a,b)) +
geom_point() +
scale_x_continuous(limits=c(0,10)) +
scale_y_continuous(limits=c(0,10))
print(a)
}
gif <- function() {
lapply(seq(1,11,1), function(i) {
steps(i)
})
}
library(animation)
saveGIF(gif(), interval = .2, movie.name="test.gif")
I liked #ttlngr's answer but I wanted something a bit simpler (it still uses ImageMagick).
saveGIF({
for (i in 1:10){
a <- ggplot(df[1:i,], aes(a,b)) +
geom_point() +
scale_x_continuous(limits=c(0,10)) +
scale_y_continuous(limits=c(0,10))
print(a)}
}, interval = .2, movie.name="test.gif")
I would like to save multiple plots (with ggplot2) to a list during a large for-loop. And then subsequently display the images in a grid (with grid.arrange)
I have tried two solutions to this:
1 storing it in a list, like so:
pltlist[["qplot"]] <- qplot
however for some reason this does save the plot correctly.
So I resorted to a second strategy which is recordPlot()
This was able to save the plot correctly, but unable to
use it in a grid.
Reproducable Example:
require(ggplot2);require(grid);require(gridExtra)
df <- data.frame(x = rnorm(100),y = rnorm(100))
histoplot <- ggplot(df, aes(x=x)) + geom_histogram(aes(y=..density..),binwidth=.1,colour="black", fill="white")
qplot <- qplot(sample = df$y, stat="qq")
pltlist <- list()
pltlist[["qplot"]] <- qplot
pltlist[["histoplot"]] <- histoplot
grid.arrange(pltlist[["qplot"]],pltlist[["histoplot"]], ncol=2)
above code works but produces the wrong graph
in my actual code
Then I tried recordPlot()
print(histoplot)
c1 <- recordPlot()
print(qplot)
c2 <- recordPlot()
I am able to display all the plots individually
but grid.arrange produces an error:
grid.arrange(replayPlot(c1),replayPlot(c2), ncol=2) # = Error
Error in gList(list(wrapvp = list(x = 0.5, y = 0.5, width = 1, height = 1, :
only 'grobs' allowed in "gList"
In this thread Saving grid.arrange() plot to file
They dicuss a solution which utilizes arrangeGrob() instead
arrangeGrob(c1, c1, ncol=2) # Error
Error in vapply(x$grobs, as.character, character(1)) :
values must be length 1,
but FUN(X[[1]]) result is length 3
I am forced to use the recordPlot() instead of saving to a list since this does not produce the same graph when saved as when it is plotted immediately, which I unfortunately cannot replicate, sorry.
In my actual code I am doing a large for-loop, looping through several variables, making a correlation with each and making scatterplots, where I name the scatterplots dependent on their significans level. I then want to re-display the plots that were significant in a grid, in a dynamic knitr report.
I am aware that I could just re-plot the plots that were significant after the for-loop instead of saving them, (I can't save as png while doing knitr either). However I would like to find a way to dynammically save the plots as R-objects and then replot them in a grid afterwards.
Thanks for Reading
"R version 3.2.1"
Windows 7 64bit - RStudio - Version 0.99.652
attached base packages:
[1] grid grDevices datasets utils graphics stats methods base
other attached packages:
[1] gridExtra_2.0.0 ggplot2_1.0.1
I can think of two solutions.
1. If your goal is to just save the list of plots as R objects, I recommend:
saveRDS(object = pltlist, file = "file_path")
This way when you wish to reload in these graphs, you can just use readRDS(). You can then put them in cowplot or gridarrange. This command works for all lists and R Objects.
One caveat to this approach is if settings/labeling for ggplot2 is dependent upon things in the environment (not the data, but stuff like settings for point size, shape, or coloring) instead of the ggplot2 function used to make the graph), your graphs won't work until you restore your dependencies. One reason to save some dependencies is to modularize your scripts to make the graphs.
Another caveat is performance: From my experience, I found it is actually faster to read in the data and remake individual graphs than load in an RDS file of all the graphs when you have a large number of graphs (100+ graphs).
2. If your goal is to save an 'image' or 'picture' of each graph (single and/or multiplot as .png, .jpeg, etc.), and later adjust things in a grid manually outside of R such as powerpoint or photoshop, I recommend:
filenames <- c("Filename_1", "Filename_2") #actual file names you want...
lapply(seq_along(pltlist), function(i) {
ggsave(filename = filenames[i], plot = pltlist[[i]], ...) #use your settings here
})
Settings I like for single plots:
lapply(seq_along(pltlist), function(i) ggsave(
plot = pltlist[[i]],
filename = paste0("plot_", i, "_", ".tiff"), #you can even paste in pltlist[[i]]$labels$title
device = "tiff", width=180, height=180, units="mm", dpi=300, compression = "lzw", #compression for tiff
path = paste0("../Blabla") #must be an existing directory.
))
You may want to do the manual approach if you're really OCD about the grid arrangement and you don't have too many of them to make for publications. Otherwise, when you do grid.arrange you'll want to do all the specifications there (adjusting font, increasing axis label size, custom colors, etc.), then adjust the width and height accordingly.
Reviving this post to add multiplot here, as it fits exactly.
require(ggplot2)
mydd <- setNames( data.frame( matrix( rep(c("x","y","z"), each=10) ),
c(rnorm(10), rnorm(10), rnorm(10)) ), c("points", "data") )
# points data
# 1 x 0.733013658
# 2 x 0.218838717
# 3 x -0.008303382
# 4 x 2.225820069
# ...
p1 <- ggplot( mydd[mydd$point == "x",] ) + geom_line( aes( 1:10, data, col=points ) )
p2 <- ggplot( mydd[mydd$point == "y",] ) + geom_line( aes( 1:10, data, col=points ) )
p3 <- ggplot( mydd[mydd$point == "z",] ) + geom_line( aes( 1:10, data, col=points ) )
multiplot(p1,p2,p3, cols=1)
multiplot:
multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) {
library(grid)
# Make a list from the ... arguments and plotlist
plots <- c(list(...), plotlist)
numPlots = length(plots)
# If layout is NULL, then use 'cols' to determine layout
if (is.null(layout)) {
# Make the panel
# ncol: Number of columns of plots
# nrow: Number of rows needed, calculated from # of cols
layout <- matrix(seq(1, cols * ceiling(numPlots/cols)),
ncol = cols, nrow = ceiling(numPlots/cols))
}
if (numPlots==1) {
print(plots[[1]])
} else {
# Set up the page
grid.newpage()
pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout))))
# Make each plot, in the correct location
for (i in 1:numPlots) {
# Get the i,j matrix positions of the regions that contain this subplot
matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE))
print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row,
layout.pos.col = matchidx$col))
}
}
}
Result:
I’d really appreciate your help with the following problem. I know several ways to save a single plot to a file. My question is: How do I correctly save a multiplot to a file?
To begin with, I’m not an experienced R user. I use ggplot2 to create my plots, and another thing I should probably mention is that I use the RStudio GUI. Using an example from the R Cookbook, I'm able to create multiple plots in one window.
I would like to save this so-called multiplot to a file (preferably as jpeg), but somehow fail to do this.
I’m creating the multiplot as follows:
##define multiplot function
multiplot <- function(..., plotlist=NULL, cols) {
require(grid)
# Make a list from the ... arguments and plotlist
plots <- c(list(...), plotlist)
numPlots = length(plots)
# Make the panel
plotCols = cols # Number of columns of plots
plotRows = ceiling(numPlots/plotCols) # Number of rows needed, calculated from # of cols
# Set up the page
grid.newpage()
pushViewport(viewport(layout = grid.layout(plotRows, plotCols)))
vplayout <- function(x, y)
viewport(layout.pos.row = x, layout.pos.col = y)
# Make each plot, in the correct location
for (i in 1:numPlots) {
curRow = ceiling(i/plotCols)
curCol = (i-1) %% plotCols + 1
print(plots[[i]], vp = vplayout(curRow, curCol ))
}
}
## define subplots (short example here, I specified some more aesthetics in my script)
plot1a <- qplot(variable1,variable2,data=Mydataframe1)
plot1b <- qplot(variable1,variable3,data=Mydataframe1)
plot1c <- qplot(variable1,variable2,data=Mydataframe2)
plot1d <- qplot(variable1,variable3,data=Mydataframe2)
## plot in one frame
Myplot <- multiplot(plot1a,plot1b,plot1c,plot1d, cols=2)
This gives the desired result. The problem arises when I try to save to a file. I can do this manually in RStudio (using Export -> Save plot as image), but I would like to run everything in a script. I manage to save only subplot1d (which is last_plot()), and not the complete multiplot.
What I’ve tried so far:
Using ggsave
ggsave(filename = "D:/R/plots/Myplots.jpg")
This results in only subplot 1d being saved.
Using jpeg(), print() and dev.off()
jpeg(filename = "Myplot.jpg", pointsize =12, quality = 200, bg = "white", res = NA, restoreConsole = TRUE)
print(Myplot)
dev.off()
This results in a completely white image (just the background I assume). print(Myplot) returns NULL.
Not sure what I’m doing wrong here. My lack of understanding R is the reason I am stuck trying to find a solution. Can anyone explain what I’m doing wrong and perhaps suggest a way to solve my problem(s)?
Its because Myplot is the returned value from your multiplot function, and it returns nothing (its job is to print the graphs). You need to call multiplot with the jpeg device open:
jpeg(filename = "Myplot.jpg", pointsize =12, quality = 200, bg = "white", res = NA, restoreConsole = TRUE)
multiplot(plot1a,plot1b,plot1c,plot1d, cols=2)
dev.off()
should work.
Using the example code (R cookbook), it works for me
png("chickweight.png")
multiplot(p1, p2, p3, p4, cols=2)
dev.off()
And for completeness sake, ggsave does not work as it only saves the last printed ggplot object, which in your case is just the last plot. This is caused by the fact that multiplot creates the plot by drawing the ggplot objects onto different subsets of the total graphics device. An alternative is to create the plot by combining the ggplot objects into one big ggplot object, and then printing the object. This would be compatible with ggsave. This approach is implemented by arrangeGrob in the gridExtra package.