Using ggplot2, how can I draw a trendline which runs between facets.
library(ggplot2)
df <- data.frame(y=c(1,2,3),x=1,Set=LETTERS[1:3])
ggplot(df,aes(x,y)) +
theme_bw() + theme(legend.position=c(0,1),legend.justification=c(0,1)) +
geom_point(aes(fill=Set),color="black",shape=21,size=3) +
facet_grid(~Set) +
xlim(1,5)
Which produces the following:
In the above, I would like to draw a line between the three points, moving across facets.
Updated to ggplot2 V3.0.0
You could do this, but turning clip off might have unwanted consequences,
library(ggplot2)
df <- data.frame(y=c(1,2,3),x=1,Set=LETTERS[1:3])
p <- ggplot(df,aes(x,y)) +
theme_bw() + theme(legend.position=c(.01,.99),legend.justification=c(0,1)) +
geom_point(aes(fill=Set),color="black",shape=21,size=3) +
facet_grid(~Set) +
xlim(1,5)
gb <- ggplot_build(p)
g <- ggplot_gtable(gb)
library(gtable)
library(grid)
# ggplot2 doesn't use native units in data space
# instead, the data is rescaled to npc, i.e from 0 to 1
# so we need to use the build info to convert from data to [0,1]
ranges <- gb$layout$panel_params
data2npc <- function(x, range) scales::rescale(c(range, x), c(0,1))[-c(1,2)]
start <- c(data2npc(1, ranges[[1]][["x.range"]]),
data2npc(1, ranges[[1]][["y.range"]]))
end <- c(data2npc(1, ranges[[3]][["x.range"]]),
data2npc(3, ranges[[3]][["y.range"]]))
# starting position in the first panel
g <- gtable_add_grob(g, moveToGrob(start[1],start[2]),
t = 8, l = 5)
# draw line to end position in last panel
g <- gtable_add_grob(g, lineToGrob(end[1],end[2]),
t = 8, l = 9, z=Inf)
# turn clip off to see the line across panels
g$layout$clip <- "off"
grid.newpage()
grid.draw(g)
Related
I am using the ndodge function explained by #jan-glx here;
https://stackoverflow.com/a/60650595/13399047
However I could not figure out how to align the axis ticks aligned as for example;
I should probably use theme(axis.ticks.length=) but I am not sure how to do it in an even/odd way.
Please help!
As far as I am aware there is no build in way to do this in ggplot, though that might change when they rewrite the guide system.
It is neither pretty nor easy, but here is an example how you could do it by messing around in the gtable / grid.
library(ggplot2)
library(grid)
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
g <- ggplot(diamonds, aes(cut, carat)) +
geom_boxplot() +
scale_x_discrete(guide = guide_axis(n.dodge = 2))
# Convert to gtable
gt <- ggplotGrob(g)
# Grab bottom axis
is_axis <- grep("axis-b", gt$layout$name)
axisgrob <- gt$grobs[is_axis][[1]]
axis <- axisgrob$children$axis
# Grab tickmarks
is_ticks <- which(vapply(axis$grobs, inherits, logical(1), "polyline"))
ticks <- axis$grobs[[is_ticks]]
# Modify tickmarks
labelheight <- axis$heights[[2]] # First row of labels
modify <- which(seq_along(ticks$y) %% 4 == 0) - 1 # Change every the 3rd item in every quadruplet
ticks$y[modify] <- ticks$y[modify] - labelheight
# Insert ticks back into axis back into table
axis$grobs[[is_ticks]] <- ticks
axisgrob$children$axis <- axis
gt$grobs[[is_axis]] <- axisgrob
# Plot
grid.newpage()
grid.draw(gt)
Created on 2020-05-18 by the reprex package (v0.3.0)
Here is a solution using just ggplot2 stuff and not modifying any grobs. It requires ggplot2 3.0.0 and is based off https://stackoverflow.com/a/51312611/6615512
library(ggplot2)
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
tick_min_pos_odd = -0.6
tick_min_pos_even = -0.4
custom_ticks = data.frame(cut = sort(unique(diamonds$cut)))
n_discrete_x_values = nrow(custom_ticks)
# Alternate tick lengths
custom_ticks$tick_min_pos = ifelse(1:n_discrete_x_values %% 2 == 0, tick_min_pos_odd, tick_min_pos_even)
ggplot(diamonds, aes(cut, carat)) +
geom_boxplot() +
scale_x_discrete(guide = guide_axis(n.dodge = 2)) +
geom_linerange(data = custom_ticks, # The custom tickmarks
aes(x=cut, ymax=-0.25, ymin=tick_min_pos),
size=0.5, color='black',
inherit.aes = F) +
coord_cartesian(clip='off', ylim=c(0,NA)) + # Clip off makes it so the geoms can be drawn outside the plot
# ylim sets the y-axis from 0 to the max.
theme(plot.margin = margin(0,0,20,0), # Add some whitespace to the bottom of the plot
axis.title.x = element_text(vjust=-1.5), # nudge the x-axis title and text down a tad
axis.text.x = element_text(vjust=-1.5))
Say I have a plot like this:
# Load libraries
library(ggplot2)
library(grid)
# Load data
data(mtcars)
# Plot results
p <- ggplot(data = mtcars)
p <- p + geom_bar(aes(cyl))
p <- p + coord_flip()
p <- p + facet_wrap(~am)
print(p)
Now, I want to plot lines all the way across both facets where the bars are. I add this:
p <- p + geom_vline(aes(xintercept = cyl))
which adds the lines, but they don't cross both facets. So, I try to turn off clipping using this solution:
# Turn off clipping
gt <- ggplot_gtable(ggplot_build(p))
gt$layout$clip[gt$layout$name == "panel"] <- "off"
# Plot results
grid.draw(gt)
but that doesn't solve the problem: the lines are still clipped. So, I wondered if this is specific to geom_vline and tried approaches with geom_abline and geom_line (the latter with values across ±Inf), but the results are the same. In other posts, the clipping solution seems to work for text and points, but presumably in this case the lines are only defined within the limits of the figure. (I even tried gt$layout$clip <- "off" to switch off all possible clipping, but that didn't solve the problem.) Is there a workaround?
library(grid)
library(gtable)
# Starting from your plot `p`
gb <- ggplot_build(p)
g <- ggplot_gtable(gb)
# Get position of y-axis tick marks
ys <- gb$layout$panel_ranges[[1]][["y.major"]]
# Add segments at these positions
# subset `ys` if you only want to add a few
# have a look at g$layout for relevant `l` and `r` positions
g <- gtable_add_grob(g, segmentsGrob(y0=ys, y1=ys,
gp=gpar(col="red", lty="dashed")),
t = 7, l = 4, r=8)
grid.newpage()
grid.draw(g)
see ggplot, drawing multiple lines across facets for how to rescale values for more general plotting. ie
data2npc <- function(x, panel = 1L, axis = "x") {
range <- pb$layout$panel_ranges[[panel]][[paste0(axis,".range")]]
scales::rescale(c(range, x), c(0,1))[-c(1,2)]
}
start <- sapply(c(4,6,8), data2npc, panel=1, axis="y")
g <- gtable_add_grob(g, segmentsGrob(y0=start, y1=start),
t=7, r=4, l=8)
I drew two panels in a column using ggplot2 facet, and would like to add two vertical lines across the panels at x = 4 and 8. The following is the code:
library(ggplot2)
library(gtable)
library(grid)
dat <- data.frame(x=rep(1:10,2),y=1:20+rnorm(20),z=c(rep("A",10),rep("B",10)))
P <- ggplot(dat,aes(x,y)) + geom_point() + facet_grid(z~.) + xlim(0,10)
Pb <- ggplot_build(P);Pg <- ggplot_gtable(Pb)
for (i in c(4,8)){
Pg <- gtable_add_grob(Pg, moveToGrob(i/10,0),t=8,l=4)
Pg <- gtable_add_grob(Pg, lineToGrob(i/10,1),t=6,l=4)
}
Pg$layout$clip <- "off"
grid.newpage()
grid.draw(Pg)
The above code is modified from:ggplot, drawing line between points across facets.
And .
There are two problems in this figure. First, only one vertical line was shown. It seems that moveToGrob only worked once.. Second, the shown line is not exact at x = 4. I didn't find the Pb$panel$ranges variable, so is there a way that I can correct the range as well? Thanks a lot.
Updated to ggplot2 V3.0.0
In the simple scenario where panels have common axes and the lines extend across the full y range you can draw lines over the whole gtable cells, having found the correct npc coordinates conversion (cf previous post, updated because ggplot2 keeps changing),
library(ggplot2)
library(gtable)
library(grid)
dat <- data.frame(x=rep(1:10,2),y=1:20+rnorm(20),z=c(rep("A",10),rep("B",10)))
p <- ggplot(dat,aes(x,y)) + geom_point() + facet_grid(z~.) + xlim(0,10)
pb <- ggplot_build(p)
pg <- ggplot_gtable(pb)
data2npc <- function(x, panel = 1L, axis = "x") {
range <- pb$layout$panel_params[[panel]][[paste0(axis,".range")]]
scales::rescale(c(range, x), c(0,1))[-c(1,2)]
}
start <- sapply(c(4,8), data2npc, panel=1, axis="x")
pg <- gtable_add_grob(pg, segmentsGrob(x0=start, x1=start, y0=0, y1=1, gp=gpar(lty=2)), t=7, b=9, l=5)
grid.newpage()
grid.draw(pg)
You can just use geom_vline and avoid the grid mess altogether:
ggplot(dat, aes(x, y)) +
geom_point() +
geom_vline(xintercept = c(4, 8)) +
facet_grid(z ~ .) +
xlim(0, 10)
I have 2 plots of the exact same thing, excepts the colors filling the bars are different on each plot. Since the legend on the different plots have different widths because of the size of the names on it, the ratio between graph and legend becomes different on each plot. I need to make both look the same.
This is an example:
library(ggplot2)
x = c(rep("a",20),rep("b",10))
y = c(x = c(rep("BIGTEXT",20),rep("EVENBIGGERTEXT",10)))
df = data.frame(x,y)
p1 = ggplot(df,aes(x,fill=x)) + geom_bar()
p2 = ggplot(df,aes(y,fill=y)) + geom_bar()
p1
p2
You can set the gtable widths to a common value,
library(gtable)
library(grid)
gl <- lapply(list(p1, p2), ggplotGrob)
gwidth <- do.call(unit.pmax, lapply(gl, "[[", "widths"))
gl <- lapply(gl, "[[<-", "widths", value = gwidth)
gridExtra::grid.arrange(grobs=gl)
Alternatively, you can set the panel size to a fixed value.
Following up #baptiste's comment: Fiddly but yes, it can be done. But no guarantees that this will work in future versions. The solution was taken from here, but that solution too needed updating.
library(ggplot2) # v2.2.1
library(gtable) # v0.2.0
library(grid)
library(gridExtra) # v2.2.1
x = c(rep("a",20),rep("b",10))
y = c(x = c(rep("BIGTEXT",20),rep("EVENBIGGERTEXT",10)))
df = data.frame(x,y)
p1 = ggplot(df,aes(x,fill=x)) + geom_bar()
p2 = ggplot(df,aes(y,fill=y)) + geom_bar()
# Get the grobs
gA <- ggplotGrob(p1)
gB <- ggplotGrob(p2)
# Get the widths of the legends
index = which(gA$layout$name == "guide-box")
leg1 <- convertX(sum(with(gA$grobs[[index]], grobs[[1]]$widths)), "mm")
leg2 <- convertX(sum(with(gB$grobs[[index]], grobs[[1]]$widths)), "mm")
# Add an empty column of width "abs(diff(c(leg1, leg2))) mm" to the right of
# legend box for gA (the smaller legend box)
gA$grobs[[index]] <- gtable_add_cols(gA$grobs[[index]], unit(abs(diff(c(leg1, leg2))), "mm"))
# Set widths to maximums of corresponding widths
gl <- list(gA, gB)
gwidth <- do.call(unit.pmax, lapply(gl, "[[", "widths"))
gl <- lapply(gl, "[[<-", "widths", value = gwidth)
# Draw the plots
grid.newpage()
grid.draw(gl[[1]])
grid.newpage()
grid.draw(gl[[2]])
Is there a way to modify the legend of a heat map that was generated with geom_tile from the ggplot2 package? I would like to increase the number of tiles in the legend and to set the minimum and maximum of the shown value there.
In this example from the manual page the legend contains five colored tiles representing values from -0.4 to 0.4. How could I let e.g. 9 tile be displayed instead?
library (ggplot2)
pp <- function (n,r=4) {
x <- seq(-r*pi, r*pi, len=n)
df <- expand.grid(x=x, y=x)
df$r <- sqrt(df$x^2 + df$y^2)
df$z <- cos(df$r^2)*exp(-df$r/6)
df
}
p <- ggplot(pp(20), aes(x=x,y=y))
p + geom_tile(aes(fill=z))
I guess there are several possible ways to archive this. One solution would be to specify the breaks for the legend manually.
d = pp(20)
ggplot(d, aes(x=x,y=y,fill=z)) + geom_tile() +
scale_fill_continuous( breaks = round( seq(-.4, .4, length.out = 10 ), 1) )