I'm trying to create a Venn diagram where each circle has a unique colour, and the intersections blend those colours.
I can make the circles with the ggforce package. And I can blend the colours by setting the alpha values to, say, 0.75:
library(ggplot2)
library(ggforce)
propositions <- data.frame(
cirx = c(-.75 , .75),
ciry = c(0 , 0),
r = c(1.5 , 1.5),
labx = c(-2.25 , 2.25),
laby = c(1 , 1),
labl = c("A", "B")
)
ggplot(propositions) +
theme_void() + coord_fixed() +
xlim(-3,3) + ylim(-2,2) +
theme(panel.border = element_rect(colour = "black", fill = NA, size = 1)) +
geom_circle(aes(x0 = cirx, y0 = ciry, r = r), fill = "red", alpha = .6, data = propositions[1,]) +
geom_circle(aes(x0 = cirx, y0 = ciry, r = r), fill = "blue", alpha = .6, data = propositions[2,]) +
geom_text(aes(x = labx, y = laby, label = labl),
fontface = "italic", size = 10, family = "serif")
But the results are pretty poor:
The colours are washed out, and the intersection's colour isn't as distinct from the right-side circle's as I'd like. I want something closer to this (photoshopped) result:
I could do this if there was some way to designate and fill the intersection. In principle, this could be done with geom_ribbon(), I think. But that seems painful, and hacky. So I'm hoping for a more elegant solution.
Here's the workaround using geom_ribbon(). It's not a proper solution though, since it won't generalize to other shapes and intersections without manually redefining the boundaries of the ribbon, which can get real hairy fast.
There's gotta be a way to get ggplot2 to automatically do the work of blending colours across layers, right?
library(ggplot2)
library(ggforce)
x <- seq(-.75, .75, 0.01)
upper <- function(x) {
a <- sqrt(1.5^2 - (x[x < 0] - .75)^2)
b <- sqrt(1.5^2 - (x[x >= 0] + .75)^2)
c(a,b)
}
lower <- function(x) {
-upper(x)
}
ggplot() +
coord_fixed() + theme_void() +
xlim(-3,3) + ylim(-2,2) +
geom_circle(aes(x0 = -.75, y0 = 0, r = 1.5), fill = "red") +
geom_circle(aes(x0 = .75, y0 = 0, r = 1.5), fill = "blue") +
geom_ribbon(aes(x = x, ymin = upper(x), ymax = lower(x)), fill = "purple", colour = "black") +
theme(panel.border = element_rect(colour = "black", fill = NA, size = 1)) +
geom_text(aes(x = c(-2.25, 2.25), y = c(1, 1), label = c("A", "B")),
fontface = "italic", size = 10, family = "serif")
Related
First of all, some data similar to what I am working with.
rawdata <- data.frame(Score = rnorm(1000, seq(1, 0, length.out = 10), sd = 1),
Group = rep(LETTERS[1:3], 10000))
rawdata$Score <- ifelse(rawdata$Group == "A", rawdata$Score+2,rawdata$Score)
rawdata$Score <- ifelse(rawdata$Group == "C", rawdata$Score-2,rawdata$Score)
stdev <- c(10.78,10.51,9.42)
col <- c("#004d8d", "#cc2701", "#e5b400")
Now, the code of my geom_density_ridges with quantile lines, which in this case they will be white.
p <- ggplot(rawdata, aes(x = Score, y = Group)) +
scale_y_discrete() +
geom_rect(inherit.aes = FALSE, mapping = aes(ymin = 0, ymax = Inf, xmin = -0.1 * min(stdev), xmax = 0.1 * max(stdev)),
fill = "grey", alpha = 0.5) +
geom_density_ridges(scale = -0.5, size = 1, alpha=0.5, show.legend = FALSE,
quantile_lines = TRUE, quantiles = c(0.025, 0.975),
vline_color = "white", aes(fill = Group)) +
scale_color_manual(values = col) +
scale_fill_manual(values = col) +
labs(title="Toy Graph", y="Group", x="Value") +
coord_flip(xlim = c(-8, 8), ylim = NULL, expand = TRUE, clip = "on")
p
An we obtain the following plot, which is perfectly adjusted to expectation.
Now I was wondering if there was a way to make only this little white quantile line transparent to the background. I tried first to set the vline_color = "transparent" and leaving the aes(fill = Group) at the end of geom_density_ridges at the logic that options where drew in order but it gets transparent not to the different shades of grey background but to the density fill (so the quantile line disappears), which is not what I am trying to achieve.
Thanks in advance for your ideas!
Colors can be modified with scales::alpha. This can be passed to your color argument.
library(ggridges)
library(ggplot2)
rawdata <- data.frame(Score = rnorm(1000, seq(1, 0, length.out = 10), sd = 1),
Group = rep(LETTERS[1:3], 10000))
rawdata$Score <- ifelse(rawdata$Group == "A", rawdata$Score+2,rawdata$Score)
rawdata$Score <- ifelse(rawdata$Group == "C", rawdata$Score-2,rawdata$Score)
stdev <- c(10.78,10.51,9.42)
col <- c("#004d8d", "#cc2701", "#e5b400")
ggplot(rawdata, aes(x = Score, y = Group)) +
scale_y_discrete() +
geom_rect(inherit.aes = FALSE, mapping = aes(ymin = 0, ymax = Inf, xmin = -0.1 * min(stdev), xmax = 0.1 * max(stdev)),
fill = "grey", alpha = 0.5) +
geom_density_ridges(scale = -0.5, size = 1, alpha=0.5, show.legend = FALSE,
quantile_lines = TRUE, quantiles = c(0.025, 0.975),
### The only change is here
vline_color = alpha("white", .5), aes(fill = Group)) +
scale_color_manual(values = col) +
scale_fill_manual(values = col) +
labs(title="Toy Graph", y="Group", x="Value") +
coord_flip(xlim = c(-8, 8), ylim = NULL, expand = TRUE, clip = "on")
#> Picking joint bandwidth of 0.148
#> Warning: Using the `size` aesthietic with geom_segment was deprecated in ggplot2 3.4.0.
#> ℹ Please use the `linewidth` aesthetic instead.
Created on 2022-11-14 with reprex v2.0.2
No, if you make something transparent you will see what's underneath, which is the density plot.
However, you can replicate the visual effect of "seeing through to the background" by simply setting the line colour to the same as the background.
Your grey rectangle is currently plotted underneath the density plots, therefore the "background" doesn't have a single colour. This can be solved by plotting it on top instead. Instead of a 50% grey with 50% alpha, you can replicate the same effect with a 0% grey (aka black) with a 25% alpha. Move the geom_rect later than the density plots and it will be layered on top.
Finally, your geom_rect is being called once for each row of raw_data, since it inherits the same data as the main plot. You probably don't want that, so specify a (dummy) data source instead.
ggplot(rawdata, aes(x = Score, y = Group)) +
scale_y_discrete() +
geom_density_ridges(scale = -0.5, size = 1, alpha=0.5, show.legend = FALSE,
quantile_lines = TRUE, quantiles = c(0.025, 0.975),
vline_color = "grey90", aes(fill = Group)) +
scale_color_manual(values = col) +
scale_fill_manual(values = col) +
labs(title="Toy Graph", y="Group", x="Value") +
geom_rect(data=data.frame(), inherit.aes = FALSE, mapping = aes(
ymin = 0, ymax = Inf, xmin = -0.1 * min(stdev), xmax = 0.1 * max(stdev)
), fill = "black", alpha = 0.25) +
coord_flip(xlim = c(-8, 8), ylim = NULL, expand = TRUE, clip = "on")
Note: I'm not sure the background colour is really "grey90", I've eyeballed it. You may want to specify it explicitly with theme if you want to be exact.
If you want literal see-through portions of your density curves, you will need to make the gaps yourself:
library(tidyverse)
rawdata %>%
mutate(GroupNum = as.numeric(as.factor(Group))) %>%
group_by(GroupNum, Group) %>%
summarise(yval = first(GroupNum) - density(Score)$y,
xval = density(Score)$x,
q025 = quantile(Score, 0.025),
q975 = quantile(Score, 0.975)) %>%
mutate(Q = ifelse(xval < q025, 'low', ifelse(xval > q975, 'hi', 'mid'))) %>%
ggplot(aes(xval, yval, group = interaction(Group, Q))) +
geom_line(size = 1) +
geom_ribbon(aes(ymax = GroupNum, ymin = yval, fill = Group),
color = NA, alpha = 0.5, outline.type = 'full',
data = . %>% filter(abs(q025 - xval) > 0.03 &
abs(q975 - xval) > 0.03)) +
coord_flip() +
scale_fill_manual(values = col) +
scale_y_continuous(breaks = 1:3, labels = levels(factor(rawdata$Group)),
name = 'Group') +
labs(x = 'Score')
I have a set of angles that I want to plot, compare and visualise in a circular scale and then patch them into a comparative figure panel. I understand the plot function does what I want for an individual dataset. However, I have multiple of them and want to compare and visualise them with better aesthetics (like in ggplots). Primarily I want to overlay 2 circles on each other and compare them. Here is a sample of my data
a<-c(289.25, 279.61, 288.09, 208.22, 295.74, 214.48, 192.51, 269.93, 225.89, 215.65)
a
ap<-circular(a, template = "geographics", modulo = "2pi")
plot(ap)
arrows.circular(ap, col = "blue", length = 0.25, angle = 30)
enter image description here
I tried the as.ggplot function from the ggplotify package as suggested here. However, I cannot add arrows or layers to my base plot by using as.ggplot (i.e) It converts the plot(ap)part in my example into a ggplot object but the next part (arrows.circular(ap, col = "blue", length = 0.25, angle = 30) is not working.
Is there a way I can draw these plots in ggplot or is there a way to convert the layers of base plots into ggplots using as.ggplot??
Any suggestions would be helpful. Thanks in advance!
You can recreate the plot using ggplot like this:
library(ggplot2)
ggplot(data.frame(a = a %% (2 * pi))) +
geom_segment(aes(x = a, xend = a, y = 0, yend = 1), color = 'blue',
arrow = arrow()) +
geom_hline(yintercept = 1) +
annotate('text', x = 0:3 * pi/2, y = 0.9, label = c('N', 'E', 'S', 'W'),
size = 5) +
geom_point(aes(x = a, y = 1)) +
scale_x_continuous(limits = c(0, 2 * pi)) +
coord_polar() +
theme_void()
And it's certainly possible to alter its appearance to make it look a bit 'softer' and more professional, though this is of course a matter of taste:
library(ggplot2)
ggplot(data.frame(a = a %% (2 * pi))) +
annotate('rect', xmin = -Inf, xmax = Inf, ymin = 0, ymax = 1,
fill = 'gray97') +
geom_hline(yintercept = 1, color = 'gray60') +
geom_segment(aes(x = a, xend = a, y = 0, yend = 1),
color = 'deepskyblue4', size = 1, alpha = 0.5,
arrow = arrow(angle = 25, length = unit(4, 'mm'))) +
annotate('text', x = 0:3 * pi/2, y = 0.9, label = c('N', 'E', 'S', 'W'),
size = 7, fontface = 2, color = 'gray30') +
geom_point(aes(x = a, y = 1)) +
scale_x_continuous(limits = c(0, 2 * pi)) +
coord_polar() +
theme_void() +
theme(plot.background = element_rect(color = NA, fill = '#ecf1f4'))
I am trying to add labels to a ggplot object. The labels do not look neat and tidy due to their positioning. I have tried using various geom_label_repel and geom_text_repel options but am not having much luck.
I cannot share the data unfortunately, but I have inserted one of my codes below and a screenshot of one section of the redacted graph. The graph has multiple peaks that need labelling. Each label has 2 lines.
I would like the lines connecting the labels to be directly above each peak on the x axis, then turn at a right angle and the line continue horizontally slightly. I would then like the label to sit on top of this horizontal section of the line.
Some peaks are very close together, so the labels will end up being pushed up the y axis so they are able to stack up neatly.
I hope that description makes sense. I would appreciate it if anyone is able to help.
Thank you!
library(ggplot2)
library(ggrepel)
library(dplyr)
upper_plot <- ggplot() +
geom_point(data = plot_data[which(analysis == "Analysis1"),],
aes(x = rel_pos, y = logged_p, color = as.factor(chr)),
size = 0.25) +
scale_color_manual(values = rep(my_upper_colors, nrow(axis_df))) +
geom_point(data=upper_highlight_pos2_old,
aes(x = rel_pos, y = logged_p),
color= c('grey'),
size=0.75,
pch = 16) +
geom_point(data=upper_labels_old,
aes(x = rel_pos, y = logged_p),
color='dark grey',
size=2,
pch = 18) +
geom_point(data=upper_highlight_pos2_novel,
aes(x = rel_pos, y = logged_p),
color= c('black'),
size=0.75,
pch = 16) +
geom_point(data=upper_labels_novel,
aes(x = rel_pos, y = logged_p),
color='black',
size=2,
pch = 18) +
scale_x_continuous(labels = axis_df$chr,
breaks = axis_df$chr_center,
expand = expansion(mult = 0.01)) +
scale_y_continuous(limits = c(0, maxp),
expand = expansion(mult = c(0.02, 0.06))) +
# geom_hline(yintercept = -log10(1e-5), color = "red", linetype = "dashed",
# size = 0.3) +
geom_hline(yintercept = -log10(5e-8), color = "black", linetype = "dashed",
size = 0.3) +
labs(x = "", y = bquote(atop('GWAS', '-log'[10]*'(p)'))) +
theme_classic() +
theme(legend.position = "none",
axis.title.x = element_blank(),
plot.margin = margin(t=5, b = 5, r=5, l = 10)) +
geom_label_repel(data = upper_labels,
aes(x = rel_pos, y = logged_p, label = label),
ylim = c(maxp / 3, NA),
size = 2,
force_pull = 0,
nudge_x = 0.5,
box.padding = 0.5,
nudge_y = 0.5,
min.segment.length = 0, # draw all lines no matter how short
segment.size = 0.2,
segment.curvature = -0.1,
segment.ncp = 3,
segment.angle = 45,
label.size=NA, #no border/box
fill = NA, #no background
)
This is my current untidy layout...
EDIT:
This is the sort of layout I am after. The lines will need to be flexible and either be right-handed or left-handed depending on space (source: https://www.nature.com/articles/s41588-020-00725-7)
I tried lately to annotate a graph with boxes above a ggplot.
Here is what I want:
I found a way using grid, but I find it too complicated, and I am quite sure there is a better way to do it, more ggplot2 friendly. Here is the example and my solution:
the data:
y2 <- 350
mesure_pol <- data.frame(x1 = c(1,4,7),
x2 = c(4,7,10),
politiquecat = c(1:3),
politique = c("Phase 1\n","Phase 2\n","Phase 3\n"),
y = c(y2,y2,y2)
)
mesure_pol$x_median <- (mesure_pol$x1 + mesure_pol$x2)/2
colorpal <- viridis::inferno(n=3,direction = -1)
plot
the main plot
p <- ggplot(data = mesure_pol) +
geom_rect(aes(xmin = x1,
xmax = x2,
ymin = 0,
ymax = 300,
fill = as.factor(politiquecat)),
fill = colorpal,
color = "black",
size = 0.3,
alpha = 0.2)+
theme(plot.margin=unit(c(60, 5.5, 5.5, 5.5), "points"))+
coord_cartesian(clip = 'off')
the annotation part
Here is the part I am not happy with:
for (i in 1:dim(mesure_pol)[1]) {
text <- textGrob(label = mesure_pol[i,"politique"], gp = gpar(fontsize=7,fontface="bold"),hjust = 0.5)
rg <- rectGrob(x = text$x, y = text$y, width = stringWidth(text$label) - unit(3,"mm") ,
height = stringHeight(text$label) ,gp = gpar(fill=colorpal[i],alpha = 0.3))
p <- p + annotation_custom(
grob = rg,
ymin = mesure_pol[i,"y"], # Vertical position of the textGrob
ymax = mesure_pol[i,"y"],
xmin = mesure_pol[i,"x_median"], # Note: The grobs are positioned outside the plot area
xmax = mesure_pol[i,"x_median"]) +
annotation_custom(
grob = text,
ymin = mesure_pol[i,"y"], # Vertical position of the textGrob
ymax = mesure_pol[i,"y"],
xmin = mesure_pol[i,"x_median"], # Note: The grobs are positioned outside the plot area
xmax = mesure_pol[i,"x_median"])
}
Is there a simplier/nicer way to obtain similar result ? I tried with annotate, label but without any luck.
An alternative approach to achieve the desired result would be to make the annotations via a second ggplot which could be glued to the main plot via e.g. patchwork.
For the annotation plot I basically used your code for the main plot, added a geom_text layer, get rid of the axix, etc. via theme_void and set the limits in line with main plot. Main difference is that I restrict the y-axis to a 0 to 1 scale. Besides that I shifted the xmin, xmax, ymin and ymax values to add some space around the rectangels (therefore it is important to set the limits).
library(ggplot2)
library(patchwork)
y2 <- 350
mesure_pol <- data.frame(x1 = c(1,4,7),
x2 = c(4,7,10),
politiquecat = c(1:3),
politique = c("Phase 1\n","Phase 2\n","Phase 3\n"),
y = c(y2,y2,y2)
)
mesure_pol$x_median <- (mesure_pol$x1 + mesure_pol$x2)/2
colorpal <- viridis::inferno(n=3,direction = -1)
p <- ggplot(data = mesure_pol) +
geom_rect(aes(xmin = x1,
xmax = x2,
ymin = 0,
ymax = 300,
fill = as.factor(politiquecat)),
fill = colorpal,
color = "black",
size = 0.3,
alpha = 0.2)
ann <- ggplot(data = mesure_pol) +
geom_rect(aes(xmin = x1 + 1,
xmax = x2 - 1,
ymin = 0.2,
ymax = 0.8,
fill = as.factor(politiquecat)),
fill = colorpal,
color = "black",
size = 0.3,
alpha = 0.2) +
geom_text(aes(x = x_median, y = .5, label = politique), vjust = .8, fontface = "bold", color = "black") +
coord_cartesian(xlim = c(1, 10), ylim = c(0, 1)) +
theme_void()
ann / p +
plot_layout(heights = c(1, 4))
By setting a second x-axis and filling the background of the new axis labels with element_markdown from the ggtext package. You may achieve this:
Here is the code:
library(ggtext)
y2 <- 350
mesure_pol <- data.frame(x1 = c(1,4,7),
x2 = c(4,7,10),
politiquecat = c(1:3),
politique = c("Phase 1\n","Phase 2\n","Phase 3\n"),
y = c(y2,y2,y2)
)
mesure_pol$x_median <- (mesure_pol$x1 + mesure_pol$x2)/2
p <- ggplot(data = mesure_pol) +
geom_rect(aes(xmin = x1,
xmax = x2,
ymin = 0,
ymax = 300,
fill = as.factor(politiquecat)),
fill = c("yellow", "red", "black"),
color = "black",
size = 0.3,
alpha = 0.2) +
scale_x_continuous(sec.axis = dup_axis(name = "",
breaks = c(2.5, 5.5, 8.5),
labels = c("Phase 1", "Phase 2", "Phase 3"))) +
theme(plot.margin=unit(c(60, 5.5, 5.5, 5.5), "points"),
axis.ticks.x.top = element_blank(),
axis.text.x.top = element_markdown(face = "bold",
size = 12,
fill = adjustcolor(c("yellow", "red", "black"),
alpha.f = .2)))+
coord_cartesian(clip = 'off')
I was trying to plot some predicted vs. actual data, something that resembles the following:
# Some random data
x <- seq(1: 10)
y_pred <- runif(10, min = -10, max = 10)
y_obs <- y_pred + rnorm(10)
# Faking a CI
Lo.95 <- y_pred - 1.96
Hi.95 <- y_pred + 1.96
my_df <- data.frame(x, y_pred, y_obs, Lo.95, Hi.95)
ggplot(my_df, aes(x = x, y = y_pred)) +
geom_line(aes(colour = "Forecasted Data"), size = 1.2) +
geom_point(aes(x = x, y = y_obs, colour = "Actual Data"), size = 3) +
geom_ribbon(aes(ymin=Lo.95, ymax=Hi.95, x=x, linetype = NA, colour = "Confidence Interval"), alpha=0.2) +
theme_grey() +
scale_colour_manual(
values = c("gray30", "blue", "red"),
guide = guide_legend(override.aes = list(
border=c(NA, NA, NA),
fill=c("gray30", "white", "white"),
linetype = c("blank", "blank", "solid"),
shape = c(NA, 19, NA))))
The plot looks like this:
The only issue I have with this plot is the red border surrounding the legend item symbol for the line (i.e. the forecasted data). Is there any way I can remove it without breaking the rest of my plot?
I think geom_ribbon was the problem. If we take its color & fill out of aes, everything looks fine
library(ggplot2)
# Some random data
x <- seq(1: 10)
y_pred <- runif(10, min = -10, max = 10)
y_obs <- y_pred + rnorm(10)
# Faking a CI
Lo.95 <- y_pred - 1.96
Hi.95 <- y_pred + 1.96
my_df <- data.frame(x, y_pred, y_obs, Lo.95, Hi.95)
m1 <- ggplot(my_df, aes(x = x, y = y_pred)) +
geom_point(aes(x = x, y = y_obs, colour = "Actual"), size = 3) +
geom_line(aes(colour = "Forecasted"), size = 1.2) +
geom_ribbon(aes(x = x, ymin = Lo.95, ymax = Hi.95),
fill = "grey30", alpha = 0.2) +
scale_color_manual("Legend",
values = c("blue", "red"),
labels = c("Actual", "Forecasted")) +
guides( color = guide_legend(
order = 1,
override.aes = list(
color = c("blue", "red"),
fill = c("white", "white"),
linetype = c("blank", "solid"),
shape = c(19, NA)))) +
theme_bw() +
# remove legend key border color & background
theme(legend.key = element_rect(colour = NA, fill = NA),
legend.box.background = element_blank())
m1
As we leave Confidence Interval out of aes, we no longer have its legend. One workaround is to create an invisible point and take one unused geom to manually create a legend key. Here we can use size/shape (credit to this answer)
m2 <- m1 +
geom_point(aes(x = x, y = y_obs, size = "Confidence Interval", shape = NA)) +
guides(size = guide_legend(NULL,
order = 2,
override.aes = list(shape = 15,
color = "lightgrey",
size = 6))) +
# Move legends closer to each other
theme(legend.title = element_blank(),
legend.justification = "center",
legend.spacing.y = unit(0.05, "cm"),
legend.margin = margin(0, 0, 0, 0),
legend.box.margin = margin(0, 0, 0, 0))
m2
Created on 2018-03-19 by the reprex package (v0.2.0).
A better way to address this question would be to specify show.legend = F option in the geom_ribbon(). This will eliminate the need for the second step for adding and merging the legend key for the confidence interval. Here is the code with slight modifications.
ggplot(my_dff, aes(x = x, y = y_pred)) +
geom_line(aes(colour = "Forecasted Data"), size = 1) +
geom_point(aes(x = x, y = y_obs, colour = "Actual Data"), size = 1) +
geom_ribbon(aes(ymin=Lo.95, ymax=Hi.95, x=x, linetype = NA, colour = "Confidence Interval"), alpha=0.2, show.legend = F) +
theme_grey() +
scale_colour_manual(
values = c("blue", "gray30", "red"))+
guides(color = guide_legend(
override.aes = list(linetype = c(1, 1, 0)),
shape = c(1, NA, NA),
reverse = T))
My plot
Credit to https://stackoverflow.com/users/4282026/marblo
for their answer to similar question.