I'm trying to show the available range of travel of a machine that has 360 degrees of rotation and that has another axis of motion with a range of -5 to 152 that is independent of yaw. All of the bar graph drawing functions I can find assume that data start at 0 and this leaves a hole in the middle of the graph between -5 and 0. Is it possible to tell geom_bar() or geom_col() to start drawing at -5 instead of 0?
Here is the code that I'm using and an example graph.
df <- data.frame(0:360)
colnames(df) = "Yaw"
df$Max.Static <- ((runif(361) * 157)-5)
library(ggplot2)
ggplot(df, aes(x =Yaw , y = Max.Static)) +
geom_col(width = 1, alpha = .5 , fill = "#69B600") +
scale_y_continuous(
limits = c(-5,152),
breaks = seq(0,140,20)
) +
scale_x_continuous(
limits = c(-1,361),
breaks = seq(0,360,45),
minor_breaks = seq(0,360,15)
) +
coord_polar(theta = "x") +
labs(x = NULL, y = NULL) +
theme(axis.text.y = element_blank(),
axis.ticks = element_blank())
Bit of a weird hack, but the following works if you can tolerate a warning:
df <- data.frame(0:360)
colnames(df) = "Yaw"
df$Max.Static <- ((runif(361) * 157)-5)
library(ggplot2)
ggplot(df, aes(x =Yaw , y = Max.Static)) +
geom_col(width = 1, alpha = .5 , fill = "#69B600",
aes(ymin = after_scale(-Inf))) + ######## <- Change this line
scale_y_continuous(
limits = c(-5,152),
breaks = seq(0,140,20)
) +
scale_x_continuous(
limits = c(-1,361),
breaks = seq(0,360,45),
minor_breaks = seq(0,360,15)
) +
coord_polar(theta = "x") +
labs(x = NULL, y = NULL) +
theme(axis.text.y = element_blank(),
axis.ticks = element_blank())
#> Warning: Ignoring unknown aesthetics: ymin
Created on 2021-01-20 by the reprex package (v0.3.0)
It works because we can access the rectangle parameters (xmin, xmax, ymin, ymax) after the bar parametrisation has been converted to rectangles with after_scale().
The -Inf instructs ggplot that the variable should be at the minimum of the scale (even after expansion), hence closing the gap.
Technically, you should be looking at geom_segment or geom_rect, rather than geom_bar, as conceptually bar graphs represent count, therefore always starting at 0
Here with geom_segment. No hack needed.
df <- data.frame(0:360)
colnames(df) = "Yaw"
df$Max.Static <- ((runif(361) * 157)-5)
df$y <- -5
library(ggplot2)
ggplot(df, aes(Yaw , y, xend = Yaw, yend = Max.Static)) +
geom_segment( color = "#69B600", size = .2) +
scale_y_continuous(
limits = c(-5,152),
breaks = seq(0,140,20)
) +
scale_x_continuous(
limits = c(-1,361),
breaks = seq(0,360,45),
minor_breaks = seq(0,360,15)
) +
coord_polar(theta = "x") +
labs(x = NULL, y = NULL) +
theme(axis.text.y = element_blank(),
axis.ticks = element_blank())
or, with geom_rect, to get the windmill style
ggplot(df, aes(xmin = Yaw-0.4 , ymin = y, xmax = Yaw +0.4, ymax = Max.Static)) +
geom_rect( fill = "#69B600") +
scale_y_continuous(
limits = c(-5,152),
breaks = seq(0,140,20)
) +
scale_x_continuous(
limits = c(-1,361),
breaks = seq(0,360,45),
minor_breaks = seq(0,360,15)
) +
coord_polar(theta = "x") +
labs(x = NULL, y = NULL) +
theme(axis.text.y = element_blank(),
axis.ticks = element_blank())
Related
I want to show a tick mark for theta axis in the ggplot2 poar plot. However, both axis.ticks.y and axis.ticks.y in the theme() does not work for theta axis. Any help would be appreciated, thanks
library(ggplot2)
df <- data.frame(
start = c(0, 121, 241),
end = c(120, 240, 359),
group = letters[1:3]
)
# a example circular ring plot
base <- ggplot(df, aes(ymax = end, ymin = start,
xmin = 0.8, xmax = 1,
fill = group)) +
geom_rect() +
coord_polar(theta = "y") +
xlim(c(0, 1))
base
# the tick of y axis can be changed
base + theme(axis.ticks.y = element_blank(), axis.text.y = element_blank())
# set the tick of x axis not worked for the theta axis
base + theme(axis.ticks.x = element_line(color = "black", size = 2))
Thanks for #Vishal A., the answer from Controlling ticks and odd text in a pie chart generated from a factor variable in ggplot2 used the panel.grid.major.y. However, it will add the major grids rather than ticks like the following:
base + theme(panel.grid.major.y = element_line(colour = "black"))
Created on 2021-12-20 by the reprex package (v2.0.1)
I see two options. You can use the panel grids, but you need to hide them. The usefulness of this solution depends on your intended plot background. I've used white, but this can be customised, of course.
Second option is to fake the ticks with annotation, e.g., with the symbol "|".
Further smaller comments in the code below.
library(tidyverse)
df <- data.frame(
start = c(0, 121, 241),
end = c(120, 240, 359),
group = letters[1:3]
)
ggplot(df) +
## annotate with a rectangle, effectively covering your central hole
annotate(geom = "rect", xmin = 0, xmax = 1, ymin = min(df$start), ymax = max(df$end),
fill = "white") +
## move aes to the geom_layer
geom_rect(aes(ymax = end, ymin = start,
xmin = 0.8, xmax = 1,
fill = group)) +
coord_polar(theta = "y") +
xlim(c(0, 1)) +
theme(panel.grid.major.y = element_line(colour = "black"))
## Option 2 - fake the ticks
## the position along the theta axis is defined by y
## you need to change the angle of your fake ticks according to the angle.
df_annot <-
data.frame(y = seq(0,300,100), x = Inf, angle = 360-seq(0,300,100))
ggplot(df) +
## annotate with text, along your y
## by placing it beneath your geom_rect layer it will automatically be covered
geom_text(data = df_annot, aes(x, y, label = "|", angle = angle)) +
## move aes to the geom_layer
geom_rect(aes(ymax = end, ymin = start,
xmin = 0.8, xmax = 1,
fill = group)) +
coord_polar(theta = "y") +
xlim(c(0, 1))
Created on 2021-12-21 by the reprex package (v2.0.1)
You need to use panel.grid.minor.y instead of axis.ticks.y in order to change the ticks.
Your code will look like this:
base + theme(axis.ticks.y = element_blank(), axis.text.y = element_blank())
base + theme(panel.grid.minor.y = element_line(color = "black", size = 1))
The output will look like this:
I would like to create a raincloud plot. I have successfully done it. But I would like to know if instead of the density curve, I can put a histogram (it's better for my dataset).
This is my code if it can be usefull
ATSC <- ggplot(data = data, aes(y = atsc, x = numlecteur, fill = numlecteur)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0), alpha = .5) +
geom_point(aes(y = atsc, color = numlecteur), position = position_jitter(width = .15), size = .5, alpha = 0.8) +
geom_point(data = sumld, aes(x = numlecteur, y = mean), position = position_nudge(x = 0.25), size = 2.5) +
geom_errorbar(data = sumld, aes(ymin = lower, ymax = upper, y = mean), position = position_nudge(x = 0.25), width = 0) +
guides(fill = FALSE) +
guides(color = FALSE) +
scale_color_brewer(palette = "Spectral") +
scale_y_continuous(breaks=c(0,2,4,6,8,10), labels=c("0","2","4","6","8","10"))+
scale_fill_brewer(palette = "Spectral") +
coord_flip() +
theme_bw() +
expand_limits(y=c(0, 10))+
xlab("Lecteur") + ylab("Age total sans check")+
raincloud_theme
I think we can maybe put the "geom_histogram()" but it doesn't work
Thank you in advance for your help !
(sources : https://peerj.com/preprints/27137v1.pdf
https://neuroconscience.wordpress.com/2018/03/15/introducing-raincloud-plots/)
This is actually not quite easy. There are a few challenges.
geom_histogram is "horizontal by nature", and the custom geom_flat_violin is vertical - as are boxplots. Therefore the final call to coord_flip in that tutorial. In order to combine both, I think best is switch x and y, forget about coord_flip, and use ggstance::geom_boxploth instead.
Creating separate histograms for each category is another challenge. My workaround to create facets and "merge them together".
The histograms are scaled way bigger than the width of the points/boxplots. My workaround scale via after_stat function.
How to nudge the histograms to the right position above Boxplot and points - I am converting the discrete scale to a continuous by mapping a constant numeric to the global y aesthetic, and then using the facet labels for discrete labels.
library(tidyverse)
my_data<-read.csv("https://data.bris.ac.uk/datasets/112g2vkxomjoo1l26vjmvnlexj/2016.08.14_AnxietyPaper_Data%20Sheet.csv")
my_datal <-
my_data %>%
pivot_longer(cols = c("AngerUH", "DisgustUH", "FearUH", "HappyUH"), names_to = "EmotionCondition", values_to = "Sensitivity")
# use y = -... to position boxplot and jitterplot below the histogram
ggplot(data = my_datal, aes(x = Sensitivity, y = -.5, fill = EmotionCondition)) +
# after_stat for scaling
geom_histogram(aes(y = after_stat(count/100)), binwidth = .05, alpha = .8) +
# from ggstance
ggstance::geom_boxploth( width = .1, outlier.shape = NA, alpha = 0.5) +
geom_point(aes(color = EmotionCondition), position = position_jitter(width = .15), size = .5, alpha = 0.8) +
# merged those calls to one
guides(fill = FALSE, color = FALSE) +
# scale_y_continuous(breaks = 1, labels = unique(my_datal$EmotionCondition))
scale_color_brewer(palette = "Spectral") +
scale_fill_brewer(palette = "Spectral") +
# facetting, because each histogram needs its own y
# strip position = left to fake discrete labels in continuous scale
facet_wrap(~EmotionCondition, nrow = 4, scales = "free_y" , strip.position = "left") +
# remove all continuous labels from the y axis
theme(axis.title.y = element_blank(), axis.text.y = element_blank(),
axis.ticks.y = element_blank())
Created on 2021-04-15 by the reprex package (v1.0.0)
I have an NMDS ordination that I've plotted using ggplot2. I've added environmental vectors on top (from the envfit() function in vegan) using geom_segment() and added corresponding labels to the same coordinates as the segments using geom_text() (code below):
ggplot() +
geom_point(data = nmds.sites.plot, aes(x = NMDS1, y = NMDS2, col = greening), size = 2) +
labs(title = "Study Area",
col = "Sites") +
geom_polygon(data = hull.data, aes(x = NMDS1, y = NMDS2, fill = grp, group = grp), alpha = 0.2) +
scale_fill_discrete(name = "Ellipses",
labels = c("High", "Moderate", "Control")) +
xlim(c(-1, 1)) +
guides(shape = guide_legend(order = 1),
colour = guide_legend(order = 2)) +
geom_segment(data = env.arrows,
aes(x = 0, xend = NMDS1, y = 0, yend = NMDS2),
arrow = arrow(length = unit(0.25, "cm")),
colour = "black", inherit.aes = FALSE) +
geom_text(data = env.arrows, aes(x = NMDS1, y = NMDS2, label = rownames(env.arrows))) +
coord_fixed() +
theme_bw() +
theme(text = element_text(size = 14))
However, since the labels are justified to centre, part of the label sometimes overlaps with the end of the arrow. I want to have the text START at the end of the arrow. In some other cases, if the arrow is pointing up, it pushes into the middle of the text. Essentially, I want to be able to see both the arrow head AND the text.
I have tried using geom_text_repel() from the ggrepel package but the placement seems random (and will also repel from other points or text in the plot (or just not do anything at all).
[EDIT]
Below are the coordinates of the NMDS vectors (this is the env.arrows object from the example code above):
NMDS1 NMDS2
Variable1 -0.46609087 0.27567532
Variable2 -0.21524887 -0.10128795
Variable3 0.59093184 0.03423775
Variable4 -0.00136418 0.46550043
Variable5 -0.30900813 -0.19659929
Variable6 0.53510347 -0.36387227
Variable7 0.66376246 -0.05220685
In the code below, we create a radial shift function to move the labels away from the arrows. The shift includes a constant amount plus an additional shift that varies with the absolute value of the cosine of the label's angle to the x-axis. This is because labels with theta near 0 or 180 degrees have a larger length of overlap with the arrows, and therefore need to be moved farther, than labels with theta near 90 or 270 degrees.
You may need to tweak the code a bit to get the labels exactly where you want them. Also, you'll likely need to add an additional adjustment if the variable names can have different widths.
One additional note: I've turned the variable names into a data column. You should do this with your data as well and then map that data column to the label argument of aes. Using rownames(env.arrows) for the labels reaches outside the ggplot function environment to the external data frame env.arrows and breaks the mapping to the data frame you've provided in the data argument to geom_text (although it likely won't cause a problem in this particular case).
library(tidyverse)
library(patchwork)
# data
env.arrows = read.table(text=" var NMDS1 NMDS2
Variable1 -0.46609087 0.27567532
Variable2 -0.21524887 -0.10128795
Variable3 0.59093184 0.03423775
Variable4 -0.00136418 0.46550043
Variable5 -0.30900813 -0.19659929
Variable6 0.53510347 -0.36387227
Variable7 0.66376246 -0.05220685", header=TRUE)
# Radial shift function
rshift = function(r, theta, a=0.03, b=0.07) {
r + a + b*abs(cos(theta))
}
# Calculate shift
env.arrows = env.arrows %>%
mutate(r = sqrt(NMDS1^2 + NMDS2^2),
theta = atan2(NMDS2,NMDS1),
rnew = rshift(r, theta),
xnew = rnew*cos(theta),
ynew = rnew*sin(theta))
p = ggplot() +
geom_segment(data = env.arrows,
aes(x = 0, xend = NMDS1, y = 0, yend = NMDS2),
arrow = arrow(length = unit(0.25, "cm")),
colour = "black", inherit.aes = FALSE) +
geom_text(data = env.arrows, aes(x = NMDS1, y = NMDS2, label = var)) +
coord_fixed() +
theme_bw() +
theme(text = element_text(size = 14))
pnew = ggplot() +
geom_segment(data = env.arrows,
aes(x = 0, xend = NMDS1, y = 0, yend = NMDS2),
arrow = arrow(length = unit(0.2, "cm")),
colour = "grey60", inherit.aes = FALSE) +
geom_text(data = env.arrows, aes(x = xnew, y = ynew, label = var), size=3.5) +
coord_fixed() +
theme_bw() +
theme(text = element_text(size = 14)) +
scale_x_continuous(expand=expansion(c(0.12,0.12))) +
scale_y_continuous(expand=expansion(c(0.07,0.07)))
p / pnew
I am using the windrose function posted here: Wind rose with ggplot (R)?
I need to have the percents on the figure showing on the individual lines (rather than on the left side), but so far I have not been able to figure out how. (see figure below for depiction of goal)
Here is the code that makes the figure:
p.windrose <- ggplot(data = data,
aes(x = dir.binned,y = (..count..)/sum(..count..),
fill = spd.binned)) +
geom_bar()+
scale_y_continuous(breaks = ybreaks.prct,labels=percent)+
ylab("")+
scale_x_discrete(drop = FALSE,
labels = waiver()) +
xlab("")+
coord_polar(start = -((dirres/2)/360) * 2*pi) +
scale_fill_manual(name = "Wind Speed (m/s)",
values = spd.colors,
drop = FALSE)+
theme_bw(base_size = 12, base_family = "Helvetica")
I marked up the figure I have so far with what I am trying to do! It'd be neat if the labels either auto-picked the location with the least wind in that direction, or if it had a tag for the placement so that it could be changed.
I tried using geom_text, but I get an error saying that "aesthetics must be valid data columns".
Thanks for your help!
One of the things you could do is to make an extra data.frame that you use for the labels. Since the data isn't available from your question, I'll illustrate with mock data below:
library(ggplot2)
# Mock data
df <- data.frame(
x = 1:360,
y = runif(360, 0, 0.20)
)
labels <- data.frame(
x = 90,
y = scales::extended_breaks()(range(df$y))
)
ggplot(data = df,
aes(x = as.factor(x), y = y)) +
geom_point() +
geom_text(data = labels,
aes(label = scales::percent(y, 1))) +
scale_x_discrete(breaks = seq(0, 1, length.out = 9) * 360) +
coord_polar() +
theme(axis.ticks.y = element_blank(), # Disables default y-axis
axis.text.y = element_blank())
#teunbrand answer got me very close! I wanted to add the code I used to get everything just right in case anyone in the future has a similar problem.
# Create the labels:
x_location <- pi # x location of the labels
# Get the percentage
T_data <- data %>%
dplyr::group_by(dir.binned) %>%
dplyr::summarise(count= n()) %>%
dplyr::mutate(y = count/sum(count))
labels <- data.frame(x = x_location,
y = scales::extended_breaks()(range(T_data$y)))
# Create figure
p.windrose <- ggplot() +
geom_bar(data = data,
aes(x = dir.binned, y = (..count..)/sum(..count..),
fill = spd.binned))+
geom_text(data = labels,
aes(x=x, y=y, label = scales::percent(y, 1))) +
scale_y_continuous(breaks = waiver(),labels=NULL)+
scale_x_discrete(drop = FALSE,
labels = waiver()) +
ylab("")+xlab("")+
coord_polar(start = -((dirres/2)/360) * 2*pi) +
scale_fill_manual(name = "Wind Speed (m/s)",
values = spd.colors,
drop = FALSE)+
theme_bw(base_size = 12, base_family = "Helvetica") +
theme(axis.ticks.y = element_blank(), # Disables default y-axis
axis.text.y = element_blank())
I'm looking for a way to move every second x-axis tick downwards and have the tick line go down with it.
I can change the general margin and tick length for all ticks with:
#MWE
library(ggplot2)
ggplot(cars, aes(dist, speed))+
geom_point()+
theme(
axis.ticks.length.x = unit(15, "pt")
)
But, I would like the x-axis ticks 0, 50, and 100 (i.e., every second tick) to be without the added top margin.
A generalized answer is preferred as my x-axis is categorical and not numerical (and contains 430 ticks, so nothing I can set by hand).
Any ideas?
Edit:
Output should be:
Edit2:
A more intricate example would be:
#MWE
ggplot(diamonds, aes(cut, price, fill = clarity, group = clarity))+
geom_col(position = 'dodge')+
theme(
axis.ticks.length.x = unit(15, "pt")
)
Edit -- added categorical approach at bottom.
Here's a hack. Hope there's a better way!
ticks <- data.frame(
x = 25*0:5,
y = rep(c(-0.2, -2), 3)
)
ggplot(cars, aes(dist, speed))+
geom_point()+
geom_rect(fill = "white", xmin = -Inf, xmax = Inf,
ymin = 0, ymax = -5) +
geom_segment(data = ticks,
aes(x = x, xend = x,
y = 0, yend = y)) +
geom_text(data = ticks,
aes(x = x, y = y, label = x), vjust = 1.5) +
theme(axis.ticks.x = element_blank()) +
scale_x_continuous(breaks = 25*0:5, labels = NULL, name = "") +
coord_cartesian(clip = "off")
Here's a similar approach used with a categorical x.
cats <- sort(as.character(unique(diamonds$cut)))
ticks <- data.frame(x = cats)
ticks$y = ifelse(seq_along(cats) %% 2, -500, -2000)
ggplot(diamonds, aes(cut, price, fill = clarity, group = clarity))+
geom_col(position = 'dodge') +
annotate("rect", fill = "white",
xmin = 0.4, xmax = length(cats) + 0.6,
ymin = 0, ymax = -3000) +
geom_segment(data = ticks, inherit.aes = F,
aes(x = x, xend = x,
y = 0, yend = y)) +
geom_text(data = ticks, inherit.aes = F,
aes(x = x, y = y, label = x), vjust = 1.5) +
scale_x_discrete(labels = NULL, name = "cut") +
scale_y_continuous(expand = expand_scale(mult = c(0, 0.05))) +
theme(axis.ticks.x = element_blank()) +
coord_cartesian(clip = "off")