How can I change the grey facet labels (A and B) into say red background with white text?
library(data.table)
A = data.table(x = 1:4, y = 1:4, z = c('A','A','B','B'))
ggplot(A) + geom_point(aes(x = x, y = y)) + facet_wrap(~z) + theme_bw()
You can do:
ggplot(A) +
geom_point(aes(x = x, y = y)) +
facet_wrap(~z) +
theme_bw()+
theme(strip.background =element_rect(fill="red"))+
theme(strip.text = element_text(colour = 'white'))
For anyone else looking to change individual facet labels, there's a solution here:
g <- ggplot_gtable(ggplot_build(p))
stripr <- which(grepl('strip-r', g$layout$name))
fills <- c("red","green","blue","yellow")
k <- 1
for (i in stripr) {
j <- which(grepl('rect', g$grobs[[i]]$grobs[[1]]$childrenOrder))
g$grobs[[i]]$grobs[[1]]$children[[j]]$gp$fill <- fills[k]
k <- k+1
}
grid::grid.draw(g)
Related
I'm trying to implement the log_2(x + 1) transformation in ggplot2 but am running into issues.
Here is an MWE
library(ggplot2)
x <- rexp(100)
y <- rexp(100)
df <- data.frame(x = x, y = y)
p <- ggplot(df, aes(x = x, y = y)) + geom_point(colour = "blue") +
scale_x_continuous(trans = "log2") +
scale_y_continuous(trans = "log2")
print(p)
However, I'm unsure how to best go about transforming the axes, as well as labelling the axes as log_2{x + 1) and log_2(y + 1).
You could use log2_trans from scales with a function to add 1 like this:
library(ggplot2)
library(scales)
x <- rexp(100)
y <- rexp(100)
df <- data.frame(x = x, y = y)
p <- ggplot(df, aes(x = x, y = y)) + geom_point(colour = "blue") +
scale_x_continuous(trans = log2_trans(),
breaks = trans_breaks("log2", function(x) x + 1),
labels = trans_format("log2", math_format(.x + 1))) +
scale_y_continuous(trans = log2_trans(),
breaks = trans_breaks("log2", function(x) x + 1),
labels = trans_format("log2", math_format(.x + 1)))
print(p)
Created on 2022-11-04 with reprex v2.0.2
Hi have some code to simulate a Gaussian process. Please can someone help me add a legend to my plots on the top right corner. I want to state the different parameter values for each of the line styles/colours, e.g. l=1, l=5, l=10. Thanks.
# simulate a gaussian process
simGP = function(K){
n = nrow(K)
U = chol(K) # cholesky decomposition
z = rnorm(n)
c(t(U) %*% z)
}
# choose points to simulate the covariance.
x = seq(-1, 1, length.out = 500)
# Exponential kernel ------------------------------------------------------
kernel_exp = function(x, l = 1) {
d = as.matrix(dist(x))/l
K = exp(-d)
diag(K) = diag(K) + 1e-8
K
}
{y1 = simGP(kernel_exp(x,l=10))
y2 = simGP(kernel_exp(x,l=1))
y3 = simGP(kernel_exp(x,l=0.1))
data1 <- as.data.frame(x,y1)
data2 <- as.data.frame(x,y2)
data3 <- as.data.frame(x,y3)
df=data.frame(data1,data2,data3)
ggplot() +
geom_line(data=data1, aes(x=x, y=y1), color="green4", linetype = "twodash", size=0.5) +
geom_line(data=data2, aes(x=x, y=y2), color='red', linetype="longdash", size=0.5) +
geom_line(data=data3, aes(x=x, y=y3), color='blue') +
scale_color_manual(values = colors) +
theme_classic() +
labs(x='input, x',
y='output, f(x)')+
theme(axis.text=element_text(size=16),
axis.title=element_text(size=14))}
You can do it using a dataframe variable to group the linetype and colour.
If you want to specify color and linetype, use scale_color_discrete and scale_linetype_discrete
y1 = simGP(kernel_exp(x,l=10))
y2 = simGP(kernel_exp(x,l=1))
y3 = simGP(kernel_exp(x,l=0.1))
data1 <- data.frame(x, y = y1, value = "10")
data2 <- data.frame(x, y = y2, value = "1")
data3 <- data.frame(x, y = y3, value = "0.1")
df=rbind(data1,data2,data3)
ggplot(data = df, aes(x=x, y=y, color = value, linetype = value, group = value)) +
geom_line(size=0.5) +
theme_classic() +
labs(x='input, x',
y='output, f(x)')+
theme(axis.text=element_text(size=16),
axis.title=element_text(size=14))
I want to change the background inside guides geometry (those in gray that are signaled by the red arrows)
library(ggplot2)
dat <- data.frame(x = 1:5, y = 1:5, p = 1:5, q = factor(1:5),
r = factor(1:5))
p <- ggplot(dat, aes(x, y, colour = p, size = q, shape = r)) + geom_point()
p
ggplot(dat, aes(x, y, colour = p, size = q, shape = r)) +
geom_point() +
theme(legend.key = element_rect(fill = "green"))
I would like to change the spread display of the legend bar as on the jpeg below. In example 1, I'd like to display the "100" threshold value in the middle of the legend bar. In example 2, I'd like to display the mean value (white colour) in the middle of the legend bar. I suspect both would require similar line of code. Could someone very kindly help me with this?
#library
library(raster)
library(ggplot2)
#sample raster
r <- raster(ncol=36, nrow=18)
r[] <- (-ncell(r)/2+1):(ncell(r)/2)
r[1,] <- 5000
plot(r)
var_df <- as.data.frame(rasterToPoints(r))
### example 1
p <- ggplot()
p <- p + geom_raster(data = var_df , aes(x = x, y = y, fill = layer))
p <- p + coord_equal()
p <- p + scale_fill_gradientn(
colours=c("red", "yellow", "skyblue", "darkblue"),
values = rescale(c(min(var_df$layer),
100,
100.01,
max(var_df$layer))))
p
### example 2
meanval <- mean(var_df$layer)
p <- ggplot()
p <- p + geom_raster(data = var_df , aes(x = x, y = y, fill = layer))
p <- p + coord_equal()
p <- p + scale_fill_gradient2(low = muted("red"), mid = "white",
high = muted("blue"), midpoint = meanval)
p
I am using the ggplot function to plot this kind of graph
image
I want to add the specific value of the x-axis as shown in the picture
this is my code :
quantiles <- quantile(mat,prob = quant)
x <- as.vector(mat)
d <- as.data.frame(x=x)
p <- ggplot(data = d,aes(x=x)) + theme_bw() +
geom_histogram(aes(y = ..density..), binwidth=0.001,color="black",fill="white") +
geom_density(aes(x=x, y = ..density..),fill="blue", alpha=0.5, color = 'black')
x.dens <- density(x)
df.dens <- data.frame(x = x.dens$x, y = x.dens$y)
p <- p + geom_area(data = subset(df.dens, x <= quantiles), aes(x=x,y=y),
fill = 'green', alpha=0.6)
print(p)