I have data where each point lays on a spectrum between two centroids. I have generated a color for each point by specifying a color for each centroid, then setting the color of each point as a function of its position between its two centroids. I used this to manually specify colors for each point and plotted the data in the following way:
lb.plot.dat <- data.frame('UMAP1' = lb.umap$layout[,1], 'UMAP2' = lb.umap$layout[,2],
'sample' = as.factor(substr(colnames(lb.vip), 1, 5)),
'fuzzy.class' = color.vect))
p3 <- ggplot(lb.plot.dat, aes(x = UMAP1, y = UMAP2)) + geom_point(aes(color = color.vect)) +
ggtitle('Fuzzy Classification') + scale_color_identity()
p3 + facet_grid(cols = vars(sample)) + theme(legend.) +
ggsave(filename = 'ref-samps_bcell-vip-model_fuzzy-class.png', height = 8, width = 16)
(color.vect is the aforementioned vector of colors for each point in the plot)
I would like to generate a legend of this plot that gives the color used for each centroid. I have a named vector class.cols that contains the colors used for each centroid and is named according to the corresponding class.
Is there a way to transform this vector into a legend for the plot even though it is not explicitly used in the plotting call?
You can turn on legend drawing in scale_color_identity() by setting guide = "legend". You'll have to specify the breaks and labels in the scale function so that the legend correctly states what each color represents, and not just the name of the color.
library(ggplot2)
df <- data.frame(x = 1:3, y = 1:3, color = c("red", "green", "blue"))
# no legend by default
ggplot(df, aes(x, y, color = color)) +
geom_point() +
scale_color_identity()
# legend turned on
ggplot(df, aes(x, y, color = color)) +
geom_point() +
scale_color_identity(guide = "legend")
Created on 2019-12-15 by the reprex package (v0.3.0)
Related
I intended to color lines in pink, and points in yellow. I don't want to use colour argument in respective geom(), I want to use scale to change colour.
p3 <- ggplot(dfcc,aes(x = yr, y = mean)) +
geom_line(aes(color = '')) +
geom_point(aes(color = ''))
p3 + scale_colour_manual(values =c('pink', 'yellow'))
This gives this plot, both lines and points are not in the right colours.
Hence, I have two questions
can I use "scale_colour_manual" to change the line and point colors in one go?
if having multiple geoms and multiple scales, how does the system know which scale applies to which geom?
Any help and explanation would be much appreciated!
Use package ggnewscale.
set.seed(2022)
df1 <- data.frame(x = 1:20, y = cumsum(rnorm(20, 2)))
library(ggplot2)
ggplot(df1, aes(x, y)) +
geom_line(color = "pink", linewidth = 2) +
ggnewscale::new_scale_color() +
geom_point(color = "yellow", size = 3) +
theme_classic()
Created on 2022-12-25 with reprex v2.0.2
I'm trying to use ggplot2 to make some sort of timeline using values from a dataframe (df). I've managed to plot the data exactly how I want it (the different colored line segments connecting the x-marks in this exact order, i.e., from left to right: 'early', 'unknown', 'late', 'sub'). The startpoint and endpoint columns in the dataframe are used to define the positions of the points and line segments.
The problem is that the legend doesn't show the color of the 'x' icons, they are just grey. I've tried adding scale_color_manual() and scale_fill_manual() commands but they don't seem to change anything. The legend does display the correct color when I change the shape to shape = 21, however, I really want the shape to be 4 (x icons). I don't care about the shape of the legend though but scale_shape_manual() again didn't change anything about the legend.
I have also tried placing different color arguments inside and outside the aes() argument of ggplot(), geom_segment() and/or geom_point().
How can I make the icons from the legend show the correct color?
Below I added a piece of code to reproduce the problem.
library(ggplot2)
library(RColorBrewer)
## Define dataframe
df <- data.frame(Var = c("sub","late","unknown","early"),
Time = c(10,267,0,1256),
Endpoint = c(1533,1523,1256,1256),
Startpoint = c(1523,1256,1256,0))
colorscheme <- RColorBrewer::brewer.pal(9, "Set1")[c(1,4,2,3)]
## Make plot
ggplot(df, aes(x="", y=Endpoint, fill=Var), color =colorscheme) +
geom_segment( aes(x="", xend="", y=Startpoint, yend=Endpoint), color = colorscheme) +
geom_point(aes(x="", y=Endpoint),size=5, shape=4 , color = colorscheme) +
coord_flip()
Thanks in advance for any suggestions!
You should use color instead of fill. To remove the line from the legend, use guides(color = guide_legend(override.aes = list(linetype = 0))) or use show.legend = F in geom_segment.
Also, arguments passed in ggplot need not to be repeated afterward.
ggplot(df, aes(x="", y=Endpoint, color=Var), colorscheme) +
geom_segment(aes(xend="", y=Startpoint, yend=Endpoint)) +
geom_point(size=5, shape=4) +
coord_flip() +
guides(color = guide_legend(override.aes = list(linetype = 0)))
#or
ggplot(df, aes(x="", y=Endpoint, color=Var), colorscheme) +
geom_segment(aes(xend="", y=Startpoint, yend=Endpoint)) +
geom_point(size=5, shape=4) +
coord_flip()
Try this:
ggplot(df, aes(x = "", y = Endpoint, color = Var), colorscheme) +
geom_segment(aes(x = "", xend = "", y = Startpoint, yend = Endpoint), show.legend = FALSE) +
geom_point(aes(x = "", y = Endpoint), size = 5, shape = 4) +
coord_flip()
In this way legend will show only X
I would like to plot densities of two variables ("red_variable", "green_variable") from two independent dataframes on one density plot, using red and green color for the two variables.
This is my attempt at coding:
library(ggplot2)
### Create dataframes
red_dataframe <- data.frame(red_variable = c(10,11,12,13,14))
green_dataframe <- data.frame(green_variable = c(6,7,8,9,10))
mean(red_dataframe$red_variable) # mean is 12
mean(green_dataframe$green_variable) # mean is 8
### Set colors
red_color= "#FF0000"
green_color= "#008000"
### Trying to plot densities with correct colors and correct legend entries
ggplot() +
geom_density(aes(x=red_variable, fill = red_color, alpha=0.5), data=red_dataframe) +
geom_density(aes(x=green_variable, fill = green_color, alpha=0.5), data=green_dataframe) +
scale_fill_manual(labels = c("Density of red_variable", "Density of green_variable"), values = c(red_color, green_color)) +
xlab("X value") +
ylab("Density") +
labs(fill = "Legend") +
guides(alpha=FALSE)
Result: The legend shows correct colors, but the colors on the plot are wrong: The "red" variable is plotted with green color, the "green" variable with red color. The "green" density (mean=8) should appear left and the "red" density (mean=12) on the right on the x-axis. This behavior of the plot doesn't make any sense to me.
I can in fact get the desired result by switching red and green in the code:
### load ggplot2
library(ggplot2)
### Create dataframes
red_dataframe <- data.frame(red_variable = c(10,11,12,13,14))
green_dataframe <- data.frame(green_variable = c(6,7,8,9,10))
mean(red_dataframe$red_variable) # mean is 12
mean(green_dataframe$green_variable) # mean is 8
### Set colors
red_color= "#FF0000"
green_color= "#008000"
### Trying to plot densities with correct colors and correct legend entries
ggplot() +
geom_density(aes(x=red_variable, fill = green_color, alpha=0.5), data=red_dataframe) +
geom_density(aes(x=green_variable, fill = red_color, alpha=0.5), data=green_dataframe) +
scale_fill_manual(labels = c("Density of red_variable", "Density of green_variable"), values = c(red_color, green_color)) +
xlab("X value") +
ylab("Density") +
labs(fill = "Legend") +
guides(alpha=FALSE)
... While the plot makes sense now, the code doesn't. I cannot really trust code doing the opposite of what I would expect it to do. What's the problem here? Am I color blind?
On your code, in order to have color at the right position, you need to specify fill = red_color or fill = green_color (as well as alpha as it is a constant - as pointed out by #Gregor) outside of the aes such as:
...+
geom_density(aes(x=red_variable), alpha=0.5, fill = red_color, data=red_dataframe) +
geom_density(aes(x=green_variable), alpha=0.5, fill = green_color, data=green_dataframe) + ...
Alternatively, you can bind your dataframes together, reshape them into a longer format (much more appropriate to ggplot) and then add color column that you can use with scale_fill_identity function (https://ggplot2.tidyverse.org/reference/scale_identity.html):
df <- cbind(red_dataframe,green_dataframe)
library(tidyr)
library(ggplot2)
library(dplyr)
df <- df %>% pivot_longer(.,cols = c(red_variable,green_variable), names_to = "var",values_to = "val") %>%
mutate(Color = ifelse(grepl("red",var),red_color,green_color))
ggplot(df, aes(val, fill = Color))+
geom_density(alpha = 0.5)+
scale_fill_identity(guide = "legend", name = "Legend", labels = levels(as.factor(df$var)))+
xlab("X value") +
ylab("Density")
Does it answer your question ?
You're trying to use ggplot as if it's base graphics... the mindset shift can take a little while to get used to. dc37's answer shows how you should do it. I'll try to explain what goes wrong in your attempt:
When you put fill = green_color inside aes(), because it's inside aes() ggplot essentially creates a new column of data filled with the green_color values in your green_data_frame, i.e., "#008000", "#008000", "#008000", .... Ditto for the red color values in the red data frame. We can see this if we modify your plot by simply deleting your scale:
ggplot() +
geom_density(aes(x = red_variable, fill = green_color, alpha = 0.5), data =
red_dataframe) +
geom_density(aes(x = green_variable, fill = red_color, alpha = 0.5), data =
green_dataframe) +
xlab("X value") +
ylab("Density") +
labs(fill = "Legend") +
guides(alpha = FALSE)
We can actually get what you want by putting the identity scale, which is designed for the (common in base, rare in ggplot2) case where you actually put color values in the data.
ggplot() +
geom_density(aes(x = red_variable, fill = green_color, alpha = 0.5), data =
red_dataframe) +
geom_density(aes(x = green_variable, fill = red_color, alpha = 0.5), data =
green_dataframe) +
scale_fill_identity() +
xlab("X value") +
ylab("Density") +
labs(fill = "Legend") +
guides(alpha = FALSE)
When you added your scale_fill_manual, ggplot was like "okay, cool, you want to specify colors and labels". But you were thinking in the order that you added the layers to the plot (much like base graphics), whereas ggplot was thinking of these newly created variables "#FF0000" and "#008000", which it ordered alphabetically by default (just as if they were factor or character columns in a data frame). And since you happened to add the layers in reverse alphabetical order, it was switched.
dc37's answer shows a couple better methods. With ggplot you should (a) work with a single, long-format data frame whenever possible (b) don't put constants inside aes() (constant color, constant alpha, etc.), (c) set colors in a scale_fill_* or scale_color_* function when they're not constant.
I am trying to display background data in grey in a ggplot with legend automatically. My aim is to either include the grey datapoints in the legend, or to make a second legend with a manual title. However I fail at doing any of the two. My data is in long format.
require(ggplot2)
xx<-data.frame(observation="all cats",x=1:2,y=1:2)
yy<-data.frame(observation=c("red cats","blue cats"),x=3:4,y=3:4)
g<-ggplot() +
geom_point(aes(x,y, colour=factor(observation)), colour="grey60", size=5, data=xx) +
geom_point(aes(x,y, colour=factor(observation)), size=5, data=yy) +
scale_color_discrete(name = "ltitle")
g
I tried to merge the data.frames with rbind.data.frame, which produces a nice legend, but then I am not able to colour the background data in grey and keep ggplot colours at the same time.
I also realized that this solves the problem:
g<-ggplot(aes(x,y, colour=factor(observation)), colour="grey60", data=xx) +
geom_point(size=5) +
geom_point(aes(x,y, colour=factor(observation)), size=5, data=yy) +
scale_color_discrete(name = "ltitle")
g
however I can't do this, because I'm using a function which creates a complicated empty plot before, in which I then add the geom_points.
Assuming your plot doesn't have other geoms that require a fill parameter, the following is a workaround that fixes the colour of your background data geom_point layer without affecting the other geom_point layers:
g <- ggplot() +
geom_point(aes(x, y,
fill = "label"), # key change 1
shape = 21, # key change 2
color = "grey50", size = 5,
data = xx) +
geom_point(aes(x, y, colour = factor(observation)), size = 5, data = yy) +
scale_color_discrete(name = "ltitle") +
scale_fill_manual(name = "", values = c("label" = "grey50")) # key change 3
g
shape = 21 gives you a shape that looks like the default round dot, but accepts a fill parameter in addition to the colour parameter. You can then set xx's geom_point layer's fill to grey in scale_fill_manual() (this creates a fill legend), while leaving color = "grey50" outside aes() (this does not add to the colour legend).
The colour scale for yy's geom_point layer is not affected by any of this.
p.s. Just realized I used "grey50" instead of "grey60"... But everything else still applies. :)
One solution is to create color vector and pass it to scale_color_manual.
xx <- data.frame(observation = "all cats",x = 1:2,y = 1:2)
yy <- data.frame(observation = c("red cats", "blue cats"),x = 3:4,y = 3:4)
# rbind both datasets
# OP tried to use rbind.data.frame here
plotData <- rbind(xx, yy)
# Create color vector
library(RColorBrewer)
# Extract 3 colors from brewer Set1 palette
colorData <- brewer.pal(length(unique(plotData$observation)), "Set1")
# Replace first color first wanted grey
colorData[1] <- "grey60"
# Plot data
library(ggplot2)
ggplot(plotData, aes(x, y, colour = observation)) +
geom_point(size = 5)+
scale_color_manual(values = colorData, name = "ltitle")
I came up with pretty much same solution as Z.Lin but using the combined dataframe from rbind.data.frame. Similarly, it uses scale_colour_manual with a vector colors specifying the color mapping:
require(ggplot2)
xx<-data.frame(observation="all cats",x=1:2,y=1:2)
yy<-data.frame(observation=c("red cats","blue cats"),x=3:4,y=3:4)
zz <- rbind.data.frame(xx,yy)
colors <- c(
"all cats" = "grey60",
"red cats" = "red",
"blue cats" = "blue"
)
g<-ggplot() +
geom_point(aes(x,y, colour=factor(observation)), size=5, data=zz) +
scale_color_manual(values= colors, name = "ltitle")
g
I'm trying to add shapes on the lines plotted using geom_freqpoly to give more visibility to them if the plot is printed b/w on paper.
data <- data.frame(time=runif(1000,0,20000),
class=c("a","b","c","d"))
ggplot(data, aes(time, colour = class)) + geom_freqpoly(binwidth = 1000) + geom_point(aes(shape=class))
but this generates this error:
'Error: geom_point requires the following missing aesthetics: y'
How can I solve this error?
Another thing is that I want to use a single colour (eg. blue) to draw the lines
but with scale_colour_brewer() I can't change the colour scale, I want to change it because the lightest colour is nearly white and you can barely see it.
How can I add a custom min and max for the colours?
How about this? The error you are getting is being produced by geom_point which needs x and y, so I removed it.
ggplot(data, aes(x = time, color = class)) +
geom_freqpoly(binwidth = 1000) +
scale_color_brewer(palette = "Blues") +
theme_dark()
If you don't want the dark background, pass manual values from RColorBrewer. The following example uses every second color to increase the contrast.
p1 <- ggplot(data, aes(x = time, color = class)) +
geom_freqpoly(binwidth = 1000) +
scale_color_manual(values = RColorBrewer::brewer.pal(9, name = "Blues")[c(3, 5, 7, 9)])
EDIT
You can extract summarised data from a ggplot object using layer_data function.
xy <- layer_data(p1)
ggplot(xy, aes(x = x, y = count, color = colour)) +
theme_bw() +
geom_line() +
geom_point() +
scale_color_manual(values = RColorBrewer::brewer.pal(9, name = "Blues")[c(3, 5, 7, 9)])