I have been using the plot_grid command from cowplot to arrange my plots. I use the labeling feature, and my plots all look the same in that regard. However, when I 'hv' align some plots that have very different y-axis limits, such as the one below, it appears the height of the plot with shortest range of y is used.
If I just 'v' align the plot it looks better in some respects, but it is hard to resize the plot and have the labels looking good. I'd prefer the plot height not consider the x-axis labels, etc, like above.
Using gtables, I can get the desired width/height (below), but these leaves me without the consistent labels across all the figures in a document. Can I use the 'hv' alignment with cowplot and specify which plot height to use?
library(ggplot2)
library(dplyr)
library(scales)
library(grid)
library(cowplot)
data(iris)
iris <- iris %>% mutate(Petal.Width2 = ifelse(Species == "setosa", Petal.Width * 75, Petal.Width))
p1 <- ggplot(data=iris, aes(x = factor(Species), y=Sepal.Width)) +
geom_bar(stat="identity") +
labs(x = NULL, y = "Plot One") +
scale_y_continuous(labels = percent) +
theme(axis.text.x = element_blank(),
axis.title.y = element_text(vjust=1), plot.margin=unit(c(2,2,0,2),"mm"))
p2 <- ggplot(data=iris, aes(x = factor(Species), y=Petal.Width2)) + geom_bar(stat="identity") +
labs(x = NULL, y = "Plot Two") +
scale_y_continuous(labels = percent) +
theme(axis.text.x = element_blank(),
axis.title.y = element_text(vjust=1), plot.margin=unit(c(0,2,0,2),"mm"))
p3 <- ggplot(data=iris, aes(x = factor(Species), y=Petal.Length*0+.01)) + geom_bar(stat="identity") +
labs(x = "SPECIES", y = "The Third plot") +
scale_y_continuous(labels = percent) +
theme( axis.title.y = element_text(vjust=1, color="blue"), plot.margin=unit(c(0,2,0,2),"mm"),
axis.text.x = element_text(angle = 90, hjust=1, vjust=1,face ="italic", size=10))
plot_grid(p1,p2,p3,ncol=1, align="v", labels=c("A", "B", "C"))
# https://stackoverflow.com/a/27408589/1670053
plots <- list(p1, p2, p3)
grobs = lapply(plots, ggplotGrob)
g = do.call(rbind, c(grobs, size="first"))
g$widths = do.call(unit.pmax, lapply(grobs, "[[", "widths"))
grid.newpage()
grid.draw(g)
it's easy as to add labels,
plots <- list(p1, p2, p3)
grobs = lapply(plots, ggplotGrob)
library(gridExtra)
g = do.call(rbind, grobs) # uses gridExtra::rbind.gtable
panels <- g$layout[g$layout$name=="panel",]
g <- gtable::gtable_add_grob(g, lapply(LETTERS[1:nrow(panels)],
textGrob, vjust=1, y=1,
gp=gpar(fontface=2)),
t=panels$t, l=2)
grid.newpage()
grid.draw(g)
Related
I have three different subplotts, each with their own legend. I want to combine each of these 3 legends into one common legend at the bottom of the plot. I have found many similar questions combining the legends of different sub plots into one common legend when all the subplots had the same legend. Yet, not when the legends are different. Attempts to change the code were not succesful.
grid_arrange_shared_legend <- function(...) {
plots <- list(...)
g <- ggplotGrob(plots[[1]] + theme(legend.position = "bottom"))$grobs
legend <- g[[which(sapply(g, function(x) x$name) == "guide-box")]]
lheight <- sum(legend$height)
grid.arrange(
do.call(arrangeGrob, lapply(plots, function(x)
x + theme(legend.position="none"))),
legend,
ncol = 1,
heights = unit.c(unit(1, "npc") - lheight, lheight))
}
data = read.table("fermentation_run.csv", header=TRUE, sep=",", fileEncoding="UTF-8-BOM")
p1 <- ggplot(data, aes(x = time)) +
geom_line(aes(y = cdw*5, colour = "CDW"), size=1) +
geom_line(aes(y = glucose, colour = "glucose"), size=1) +
geom_step(aes(y = substrate, colour = "substrate"), size=1) +
theme_classic() + ylab("Concentration (g/l)") +
xlab("Time (h)") +
scale_colour_manual(values = c("grey", "red", "black"))
theme(legend.position="bottom", legend.title=element_blank())
p2 <- ggplot(data, aes(x=time)) +
geom_line(aes(y = alkyl, colour = "alkyl SS"), size=1) +
geom_line(aes(y = oleyl, colour = "oleyl alcohol"), size=1) +
theme_classic() +
xlab("Time (h)") +
ylab("Concentration (g/l)") +
scale_colour_manual(values = c("green", "blue"))
theme(legend.position="bottom", legend.title=element_blank())
p3 <- ggplot(data, aes(x=time)) +
geom_step(aes(y = aeration, colour="aeration"), size=1) +
geom_line(aes(y = do/2, colour="dissolved oxygen"), size=1) +
theme_classic() +
xlab("Time (h)") +
ylab("Aeration (lpm)") +
scale_y_continuous(sec.axis = sec_axis(~.*2, name = "Dissolved oxygen (%)")) +
theme(legend.position="bottom", legend.title=element_blank())
grid_arrange_shared_legend(p1, p2,p3)
This returns only the legend of the first plot and not of the three plots combined.
I think the key is to add all the legends in your first plot. To achieve this, you could add some fake rows in your data and label them according to your legends for all plots. Let's assume those legends are "a", "b", "c", "d", "e", and "f" in the following:
library(tidyverse)
# insert several rows with values outside your plot range
data <- add_row(mtcars,am=c(2, 3, 4, 5), mpg = 35, disp = 900)
data1<-data %>%
mutate (
by1 = factor(am, levels = c(0, 1, 2, 3, 4, 5),
labels = c("a", "b","c","d", "e","f")))
p1 <- ggplot(data1, aes(x = mpg, y=disp, col=by1)) +
geom_point() +
ylim(50,500)
You will get all the legends you need, and grid_arrange_shared_legend(p1, p2,p3) will pick up this. As you can see only "a" and "b" are for the first plot, and the rest are for other plots.
I don't have your data so I'll illustrate it with some basic datasets. The method isn't perfect with respect to some whitespace around the legends, but maybe someone in the comments knows a solution.
The answer I'm proposing is getting dirty with gtables and patchwork and internal functions thereof.
library(ggplot2)
library(grid)
library(patchwork) #https://github.com/thomasp85/patchwork
# Make plots as usual
g1 <- ggplot(iris, aes(Sepal.Width, Sepal.Length)) +
geom_point(aes(colour = Species))
g2 <- ggplot(mtcars, aes(mpg, disp)) +
geom_point(aes(colour = as.factor(cyl)))
# specify a legend position and a orientation for plots
position <- "bottom"
orientation <- "vertical"
# Add as many plots as you want to this list
plots <- list(g1, g2)
# Grab legends from plots in list
legends <- lapply(plots, function(p) {
p <- ggplotGrob(p + theme(legend.position = position))$grobs
p[[which(sapply(p, function(x) x$name) == "guide-box")]]
})
# Combine the legends
legend <- switch(position,
"bottom" = do.call(gtable:::cbind.gtable, legends),
"right" = do.call(gtable:::rbind.gtable, legends))
# Now make versions of the plots without the legend
stripped <- lapply(plots, function(p) p + theme(legend.position = "none"))
# Combine all the plots
stripped <- switch(orientation,
"horizontal" = do.call(patchwork:::ggplot_add.ggplot, stripped),
"vertical" = do.call(patchwork:::`/.ggplot`, stripped))
# Combine plots with legend
out <- switch(position,
"bottom" = stripped / legend,
"right" = stripped + legend)
out
Created on 2019-08-17 by the reprex package (v0.3.0)
If the whitespace really is a problem, you could supply a plot layout, but this would have to be a manual judgement to make:
out + plot_layout(heights = c(1,1,0.2))
I have this code for a dendrogram. How can I decrease the size of dendrogram (or y-axis)?
I am using this code as example. In my dataset, I have large labels so I do not have space enough to include it. For that reason, I would like to reduce the space used for y axis, decrease the distance between 0 and 150. Also, when I save the figure as tiff, most of figure is the dendogram and I can not see labels clearly.
df <- USArrests # really bad idea to muck up internal datasets
labs <- paste("sta_",1:50,sep="") # new labels
rownames(df) <- labs # set new row names
library(ggplot2)
library(ggdendro)
hc <- hclust(dist(df), "ave") # heirarchal clustering
dendr <- dendro_data(hc, type="rectangle") # convert for ggplot
clust <- cutree(hc,k=2) # find 2 clusters
clust.df <- data.frame(label=names(clust), cluster=factor(clust))
# dendr[["labels"]] has the labels, merge with clust.df based on label column
dendr[["labels"]] <- merge(dendr[["labels"]],clust.df, by="label")
# plot the dendrogram; note use of color=cluster in geom_text(...)
ggplot() +
geom_segment(data=segment(dendr), aes(x=x, y=y, xend=xend, yend=yend)) +
geom_text(data=label(dendr),
aes(x, y, label=label, hjust=0, color=cluster),
size=3) +
coord_flip() +
scale_y_reverse(expand=c(0.2, 0)) +
theme(axis.line.y=element_blank(),
axis.ticks.y=element_blank(),
axis.text.y=element_blank(),
axis.title.y=element_blank(),
panel.background=element_rect(fill="white"),
panel.grid=element_blank())
How can I decrease the size of dendogram similar than this heatmap?
(source: r-graph-gallery.com)
Thanks you so much
For flexibility, I recommend putting the dendrogram labels on the x-axis itself, rather than text labels within the plot. Otherwise no matter what values you choose for expand in the y-axis, part of the labels could be cut off for some image sizes / dimensions.
Define colour palette for the dendrogram labels:
library(dplyr)
label.colour = label(dendr)$cluster %>%
factor(levels = levels(.),
labels = scales::hue_pal()(n_distinct(.))) %>%
as.character()
For the purpose of illustration, make some labels very long:
label.values <- forcats::fct_recode(
label(dendr)$label,
sta_45_abcdefghijklmnop = "sta_45",
sta_31_merrychristmas = "sta_31",
sta_6_9876543210 = "sta_6")
Plot:
p <- ggplot(segment(dendr)) +
geom_segment(aes(x=x, y=y, xend=xend, yend=yend)) +
coord_flip() +
scale_x_continuous(breaks = label(dendr)$x,
# I'm using label.values here because I made
# some long labels for illustration. you can
# simply use `labels = label(dendr)$label`
labels = label.values,
position = "top") +
scale_y_reverse(expand = c(0, 0)) +
theme_minimal() +
theme(axis.title = element_blank(),
axis.text.y = element_text(size = rel(0.9),
color = label.colour),
panel.grid = element_blank())
p
# or if you want a color legend for the clusters
p + geom_point(data = label(dendr),
aes(x = x, y = y, color = cluster), alpha = 0) +
scale_color_discrete(name = "Cluster",
guide = guide_legend(override.aes = list(alpha = 1))) +
theme(legend.position = "bottom")
You can do this by adding a size parameter to axis.text.y like so:
theme(axis.line.y=element_blank(),
axis.ticks.y=element_blank(),
axis.text.y=element_text(size=12),
axis.title.y=element_blank(),
panel.background=element_rect(fill="white"),
panel.grid=element_blank())
Using this SO solution I created a facet with two "empty" plots, with the aim of combining with another group of facet_wrap plots, as shown below. The purpose is to have two y-axis labels for different unit measurements. How can I make the grid layout look like the top image, which produces the arrangement I want, but not the axis labels? This was accomplished with plot_grid with individual plots. My current output does not scale correctly and overlaps the other plots, as seen in the second image, but provides the axis labels.
I have example data below, just copy and run the code to input it.
library(ggplot2)
library(grid)
library(cowplot)
clipboard <- readClipboard()
test.data <- read.table(file = "clipboard", sep = ",", header=TRUE)
test.data1 <- test.data[1:24, ]
test.data2 <- test.data[25:32, ]
testplot1 <- ggplot(test.data1, aes(Station, value)) +
geom_point() +
labs(x = "Stations", y = "Scale A") +
theme(legend.position = "none", legend.title = element_blank()) +
facet_wrap( ~ constituent, ncol = 3, scales = "free_y")
testplot2 <- ggplot(test.data2, aes(Station, value)) +
geom_point() +
labs(x = "Stations", y = "Scale B") +
theme(legend.position = "none", legend.title = element_blank(), axis.title.y = element_text(hjust = 0.2)) +
facet_wrap( ~ constituent, ncol = 1, scales = "free_y")
blankplots <- ggplotGrob(testplot2)
rm_grobs <- blankplots$layout$name %in% c("panel-1-1", "panel-2-1", "strip-t-1-1", "strip-t-1-2")
blankplots$grobs[rm_grobs] <- NULL
blankplots$layout <- blankplots$layout[!rm_grobs, ]
grid.newpage()
emptygrids <- grid.draw(blankplots)
plot_grid(emptygrids, MPLOOplot1)
Example date is below:
Station,constituent,value
A1,A,1
B1,A,1
A1,B,2
B1,B,2
A1,C,3
B1,C,3
A1,D,4
B1,D,4
A1,E,5
B1,E,5
A1,F,6
B1,F,6
A1,G,7
B1,G,7
A1,H,8
B1,H,8
A1,I,9
B1,I,9
A1,J,10
B1,J,10
A1,K,11
B1,K,11
A1,L,1.4
B1,L,1.4
A1,Blank1,NA
B1,Blank1,NA
A1,Blank2,NA
B1,Blank2,NA
A1,XX,0.52
B1,XX,0.52
A1,YY,0.355
B1,YY,0.355
I'm not sure I understand exactly what you're trying to do, so let me know if this is what you had in mind. I wasn't sure what you wanted colour to be mapped to, so I just used constituent for this example.
library(gridExtra)
library(ggplot2)
library(dplyr)
library(cowplot)
theme_set(theme_classic())
testplot1 <- ggplot(test.data1, aes(Station, value, colour=constituent)) +
geom_point() +
labs(x = "Stations", y = "Scale A") +
theme(legend.title = element_blank()) +
facet_wrap( ~ constituent, ncol = 3, scales = "free_y") +
guides(colour=guide_legend(ncol=2))
testplot2 <- ggplot(test.data2 %>% filter(!grepl("Blank", constituent)),
aes(Station, value, colour=constituent)) +
geom_point() +
labs(x = "Stations", y = "Scale B") +
theme(legend.title = element_blank(),
axis.title.y = element_text(hjust = 0.2)) +
facet_wrap( ~ constituent, ncol = 1, scales = "free_y")
leg1 = get_legend(testplot1)
leg2 = get_legend(testplot2)
testplot1 = testplot1 + guides(colour=FALSE)
testplot2 = testplot2 + guides(colour=FALSE)
Now we lay out the plots and legends with grid.arrange. This requires some manual tweaking of the heights and widths.
grid.arrange(
arrangeGrob(
arrangeGrob(nullGrob(), leg2, leg1, nullGrob(), ncol=4, widths=c(1,4,4,1)),
testplot2, ncol=1, heights=c(4.2,5)
),
testplot1, ncol=2, widths=c(1.1,3))
I would like to combine some graphs together using cowplot. But I cannot change the margin sizes. I want to use only one y-axes, but than the margin is still quite large, which I want to decrease. I have used the plot.margin code from ggplot, although that works when I look at the single plot, it doesn't seem to work when the plots are combined.
I have made some example code:
library(ggplot2)
library(cowplot)
x <- c("a", "b")
y1 <- c(3,6)
y2 <- c(10,15)
data1 <- data.frame(x,y1)
data2 <- data.frame(x, y2)
ylab1 <- ylab("Very nice y values")
xlab1 <- xlab("Very nice factors")
plot1 <- ggplot(data1, aes(x=x, y = y1)) +
geom_bar(stat ="identity", position=position_dodge(), fill = "grey")+
theme(plot.margin = unit(c(0.5,0.5,0.5,0.5), "cm")) + xlab1 + ylab1
plot1
ylab2 <- ylab("")
xlab2 <- xlab("Very nice factors")
plot2 <- ggplot(data2, aes(x=x, y = y2)) +
geom_bar(stat = "identity",position=position_dodge(), fill = "grey")+
theme(plot.margin = unit(c(0.5,0.5,0.5,-0.5), "cm")) + xlab2 + ylab2
plot2
plot3 <- plot_grid(plot1, plot2, labels = c("A", "B"), align = "hv",nrow = 1, ncol = 2)
plot3 # Quite large margin between the two plots
I am aware that I could avoid this problem by using facets, however my real plot is rather more complicated than this graph.
Increasing the space between plots in plot_grid was also addressed in this issue.
An extra interesting solution is the one suggested in this comment - try to add an extra empty plot between the two plots and adjust the relative columns widths:
plot4 <- plot_grid(plot1, NULL, plot2, rel_widths = c(1, 0, 1), align = "hv",
labels = c("A", "B"), nrow = 1)
plot4
Can even try negative values in rel_widths, which gives better results:
plot5 <- plot_grid(plot1, NULL, plot2, rel_widths = c(1, -0.1, 1), align = "hv",
labels = c("A", "B"), nrow = 1)
plot5
So, try a combination of adjusting the plot.margin (as answered by #J.Con) and adding an extra empty plot with tweaking rel_widths.
EDIT 2019-12-11
Also check out this comment of the author of cowplot (Claus Wilke):
For those kinds of problems I would now recommend the patchwork library. It's inherently difficult with plot_grid(), due to its underlying design
So, a fast example with patchwork based on their vignette Adding Annotation and Style goes like this:
library(patchwork)
plot3 <- plot1 + plot2 +
plot_annotation(tag_levels = 'A') &
theme(plot.tag = element_text(size = 8))
plot3
Created on 2019-12-11 by the reprex package (v0.3.0)
Your plot.margins were actually working against you. Set them to zero to fill up that white space.
plot1 <- ggplot(data1, aes(x=x, y = y1)) +
geom_bar(stat ="identity", position=position_dodge(), fill = "grey")+
theme(plot.margin = unit(c(0,0,0,0), "cm")) + xlab1 + ylab1
plot1
ylab2 <- ylab("")
xlab2 <- xlab("Very nice factors")
plot2 <- ggplot(data2, aes(x=x, y = y2)) +
geom_bar(stat = "identity",position=position_dodge(), fill = "grey")+
theme(plot.margin = unit(c(0,0,0,0), "cm")) + xlab2 + ylab2
plot2
plot3 <- plot_grid(plot1, plot2, labels = c("A", "B"), align = "hv",nrow = 1, ncol = 2)
plot3
I'm interested in trying to create simple corner labels for a multipanel figure I am preparing in ggplot. This is similar to this previously asked question, but the answers only explained how to include a label at the top of the plot, not produce a corner label in the format required by many journals. I hope to replicate something similar to the plotrix function corner.label() in ggplot2.
Here is an example using plottrix of what I would like to recreate in ggplot2.
require(plotrix)
foo1<-rnorm(50,25,5)
foo2<-rpois(50,25)
foo3<-rbinom(50,25,0.5)
foo4<-rnbinom(50,25,0.5)
par(mfrow=c(2,2))
hist(foo1)
corner.label(label='a',figcorner=T)
hist(foo2)
corner.label(label='b',figcorner=T)
hist(foo3)
corner.label(label='c',figcorner=T)
hist(foo4)
corner.label(label='d',figcorner=T)
This produces the following:
Thanks for any help in advance!
Two recent changes have made this a lot easier:
The latest release of ggplot2 has added the tag caption which can be used to label subplots.
The package patchwork makes it really easy to plot multiple ggplot objects. https://github.com/thomasp85/patchwork
This means that no altering of grobs is required. Adapting the reproducible example provided by Kev:
library(ggplot2)
# install.package("patchwork")
library(patchwork)
a <- 1:20
b <- sample(a, 20)
c <- sample(b, 20)
d <- sample(c, 20)
mydata <- data.frame(a, b, c, d)
myplot1 <- ggplot(mydata, aes(x=a, y=b)) + geom_point() + labs(tag = "A")
myplot2 <- ggplot(mydata, aes(x=b, y=c)) + geom_point() + labs(tag = "B")
myplot3 <- ggplot(mydata, aes(x=c, y=d)) + geom_point() + labs(tag = "C")
myplot4 <- ggplot(mydata, aes(x=d, y=a)) + geom_point() + labs(tag = "D")
myplot1 + myplot2 + myplot3 + myplot4
Extension: Changing Style:
If you want to change the labelling style, you can either set this individually for each plot or set a theme default. I would recommend the second approach. Add the following line before you build your plots to make the font bold and blue
ggplot2::theme_update(plot.tag = element_text(face = "bold", colour = "blue"))
For more information on customising the theme of ggplot2, see here.
I had the same problem and came up with the following solution, which is a bit different:
loading r packages
library(ggplot2)
library(grid)
library(gridExtra)
example data
a <- 1:20
b <- sample(a, 20)
c <- sample(b, 20)
d <- sample(c, 20)
create a data frame
mydata <- data.frame(a, b, c, d)
create example plots
myplot1 <- ggplot(mydata, aes(x=a, y=b)) + geom_point()
myplot2 <- ggplot(mydata, aes(x=b, y=c)) + geom_point()
myplot3 <- ggplot(mydata, aes(x=c, y=d)) + geom_point()
myplot4 <- ggplot(mydata, aes(x=d, y=a)) + geom_point()
set corner labels
myplot1 <- arrangeGrob(myplot1, top = textGrob("A", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times Roman")))
myplot2 <- arrangeGrob(myplot2, top = textGrob("B", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times Roman")))
myplot3 <- arrangeGrob(myplot3, top = textGrob("C", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times Roman")))
myplot4 <- arrangeGrob(myplot4, top = textGrob("D", x = unit(0, "npc")
, y = unit(1, "npc"), just=c("left","top"),
gp=gpar(col="black", fontsize=18, fontfamily="Times Roman")))
plotting all plots on one page
grid.arrange(myplot1, myplot2, myplot3, myplot4, ncol = 2)
An example:
d <- data.frame(x = runif(16),
y = runif(16),
grp = rep(letters[1:4],each = 4))
ggplot(d,aes(x = x,y = y)) +
facet_wrap(~grp) +
geom_point() +
theme(strip.text = element_text(hjust = -0.05),
strip.background = element_blank())
Here's a solution using a custom labeller function. This doesn't invovle any manipulations to the data. Currently it only works with 1-dimensional facets (facet_wrap). I'm still working on how to increment along a 2-D grid...
Define the labeller function
make_labelstring <- function(mypanels) {
mylabels <- sapply(mypanels,
function(x) {LETTERS[which(mypanels == x)]})
return(mylabels)
}
label_panels <- ggplot2::as_labeller(make_labelstring)
Pass label_panels as the labeller to facet_wrap
library(ggplot2)
data("diamonds")
# create a faceted plot
ggplot(data = diamonds, aes(x = depth, y = price)) +
geom_point() +
facet_wrap(~cut, labeller = label_panels) +
theme(strip.text = element_text(hjust = -0),
strip.background = element_blank())