I got a list of number (n=9) and would like to draw them out in a 3*3 square grid and each grid fill with corresponding number. How can I do this in R without installing additional package e.g. plotrix. Many thanks!
Here is a ggplot solution that was a little harder than I expected:
# Setup the data
m <- matrix(c(8,3,4,1,5,9,6,7,2), nrow=3, ncol=3)
df <- expand.grid(x=1:ncol(m),y=1:nrow(m))
df$val <- m[as.matrix(df[c('y','x')])]
library(ggplot2)
library(scales)
ggplot(df, aes(x=x, y=y, label=val)) +
geom_tile(fill='transparent', colour = 'black') +
geom_text(size = 14) +
scale_y_reverse() +
theme_classic() +
theme(axis.text = element_blank(),
panel.grid = element_blank(),
axis.line = element_blank(),
axis.ticks = element_blank(),
axis.title = element_blank())
Here is a good solution using just base R, and outputting to a png. Note the default png device has equal width and height.
png("magic_square.png")
par(mar=c(.5,.5,.5,.5))
plot(x=df$x,y=df$y,pch=as.character(df$val),
asp=1, xlim=c(0.5,3.5),ylim=c(0.5,3.5),xaxt="n",yaxt="n",xlab="",ylab="",
xaxs="i", yaxs="i", axes=F)
abline(v=0.5+(0:3),h=0.5+(0:3))
dev.off()
You can use cex in the plot call to make the numbers appear larger.
And you can add circles as follows. Note the abline locations.
symbols(1.5,1.5,circles=1,add=TRUE)
And to annotate as shown in the comment, set the background of the circle and use points to draw additional text annotations.
symbols(1.5,1.5,circles=1,bg="white",add=TRUE)
text(x=1.5,y=1.5,labels="17",cex=3)
Of course the real key to doing this well will be mastering the data structures to make calls into plot, symbols, and text efficient.
Here's one using plotrix (sorry, but it's much easier if you use a package!) and #nograpes's df data.
library(plotrix)
xt <- xtabs(val ~ ., df[c(2,1,3)])
color2D.matplot(xt, vcex = 3, show.values = 1, axes = FALSE, xlab = "",
ylab = "", cellcolors = rep("white", length(xt)))
In case other answers ever change, df was constructed with
m <- matrix(c(8,3,4,1,5,9,6,7,2), nrow = 3, ncol = 3)
df <- expand.grid(x = 1:ncol(m),y = 1:nrow(m))
df$val <- m[as.matrix(df[c('y', 'x')])]
Related
I am trying to create a vector mask to a raster. The raster is some color gradient created elswhere. Here I am discussing only the vector mask.
Using the raster and sf packages seems to be an overkill for the simple case. The best way I came up with is to plot the vector object, ggsave it to a raster file, read it back and then overlay it on the original raster.
will be happy to hear any better suggestion.
Anyway, when I write the plot to the the file there is always a small frame around it. It may not be visible when displaying the file on screen but its problematic in my case.
I could remove the frame but I cannot rely on color only and I am not sure that its always the same size. Here is my exampe:
library(tidyverse)
library(reshape2)
library(bmp)
pol <- tibble(x = c(1, 3, 5, 4), y = c(3,5, 4, 1))
p <- ggplot(pol) +
geom_polygon(aes(x,y), fill = "red") +
theme(panel.background = element_rect(fill = "black"),
panel.grid = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank(),
axis.text = element_blank())
ggsave("pol.bmp", p, dpi = "screen")
bmp <- read.bmp("pol.bmp")
bmp <- melt(bmp, varnames = c("y", "x")) %>%
mutate(value = as.factor(value))
ggplot(bmp) +
geom_raster(aes(x,y, fill = value)) +
theme(legend.position="none")
The initial plot
The raterized plot (ignore colors)
Please advise
I would like to adjust the spacing between plots that are aligned in a panel using the cowplot package when some plots contain axis titles/labels, and others don't.
Example
Let's create three plots:
library(tidyverse)
library(cowplot)
set.seed(123)
df <- data.frame(x = rnorm(n = 100),
y = rnorm(n = 100))
plot <- ggplot(data = df, aes(x, y)) + geom_point()
plot_grid(plot, plot, plot, nrow = 1, align = "vh")
These plots are aligned perfectly! But often, I have a scenario in which I would like to create a 'cleaner' panel figure. One way to do this is to remove the titles/text of the y-axis of the second and third plots.
Like this:
plot2 <- plot + theme(axis.title.y = element_blank(),
axis.text.y = element_blank())
plot_grid(plot, plot2, plot2, nrow = 1, align = "vh")
Again, perfectly aligned, but the spacing between the first and the second plot (and the second and third plot) is quite large. I would like to reduce the spacing to create a more compact plot, while the axis remain exactly the same size.
Expected output
Is this possible with cowplot? Or is there another way to do this?
Referencing this post on github, plot_grid() doesn't add any space by default and uses the margins of your plot. To remove the space outside your plot area, you can use them(plot.margin=...) to remove.
With that being said... that's not what's going on here! Printing either plot or plot2 will yield a plot with no margins. It appears the issue is with the use of the align= argument in plot_grid(). I'm not sure why, but setting it to anything other than the default values (align="none") results in the extra whitespace around the plots. Very strange... needless to say, removing that argument fixes your problem:
Original code using align="vh"
plot_grid(plot, plot2, plot2, nrow = 1, align="vh")
Using align="none"
plot_grid(plot, plot2, plot2, nrow = 1, align="none")
Any further space would be added according to your graphics device, since the actual plot you get depends on the size and resolution of that device.
Here is a solution using the patchwork package
library(tidyverse)
set.seed(123)
df <- data.frame(x = rnorm(n = 100),
y = rnorm(n = 100))
plot1 <- ggplot(data = df, aes(x, y)) + geom_point()
plot2 <- plot1 + theme(axis.title.y = element_blank(),
axis.text.y = element_blank())
# install.packages("patchwork", dependencies = TRUE)
library(patchwork)
plot1 + plot2 + plot2 +
plot_layout(ncol = 3)
Created on 2020-07-24 by the reprex package (v0.3.0)
Sample of the dataset.
nq
0.140843018
0.152855833
0.193245919
0.156860105
0.171658019
0.186281942
0.290739146
0.162779517
0.164694042
0.171658019
0.195866609
0.166967913
0.136841748
0.108907644
0.264136384
0.356655651
0.250508305
I would like to make a Percentage Bar plot/Histogram like this question: RE: Alignment of numbers on the individual bars with ggplot2
The max value of NQ for full dataset is 21 and minimum value is 0.00005
But I am unable to adapt the code as I don't have a Freq column and I have one series.
I have made a mockup of the figure I am trying to make.
Could you please help?
Would that work for you?
nq <- read.table(text = "
0.140843018
0.152855833
0.193245919
0.156860105
0.171658019
0.186281942
0.290739146
0.162779517
0.164694042
0.171658019
0.195866609
0.166967913
0.136841748
0.108907644
0.264136384
0.356655651
0.250508305", header = F) # Your data
nq$V2 <- cut(nq$V1, 5, include.lowest = T)
nq2 <- aggregate(V1 ~ V2, nq, length)
nq2$V3 <- nq2$V1/sum(nq2$V1)
library(ggplot2)
ggplot() + geom_bar(data = nq2, aes(V2, V1), stat = "identity", width=1, fill = "white", col = "black", size = 2) +
geom_text(vjust=1, fontface="bold", data = nq2, aes(label = paste(sprintf("%.1f", V3*100), "%", sep=""), x = V2, y = V1 + 0.4), size = 5) +
theme_bw() +
scale_x_discrete(expand = c(0,0), labels = sprintf("%.3f",seq(min(nq$V1), max(nq$V1), by = max(nq$V1)/6))) +
ylab("No. of Cases") + xlab("") +
scale_y_continuous(expand = c(0,0)) +
theme(
axis.title.y = element_text(size = 20, face = "bold", angle = 0),
panel.grid.major = element_blank() ,
panel.grid.minor = element_blank() ,
panel.border = element_blank() ,
panel.background = element_blank(),
axis.line = element_line(color = 'black', size = 2),
axis.text.x = element_text(face="bold"),
axis.text.y = element_text(face="bold")
)
I thought this would be easy, but it turned out to be frustrating. So perhaps the "right" way is to transform your data before using ggplot as it looks like #DavidArenburg has done. But, if you feel like hacking ggplot, here's what I ended up doing.
First, some sample data.
set.seed(15)
dd<-data.frame(x=sample(1:25, 100, replace=T, prob=25:1))
br <- seq(0,25, by=5) # break points
My first attempt was
library(ggplot2)
ggplot(dd, aes(x)) +
stat_bin(position="stack", breaks=br) +
geom_text(aes(y=..count.., label=..density..*..width.., ymax=..count..+1),
vjust=-.5, breaks=br, stat="bin")
but that didn't make "pretty labels"
so i thought i'd use the percent() function from the scales package to make it pretty. However, silly ggplot doesn't really make it possible to use functions with ..().. variables because it evaluates them in the data.frame only (then the empty baseenv()). It doesn't have a way to find the function you use. So this is when I turned to hacking. First i'll extract the "Layer" definition from ggplot and the map_statistic from it. (NOTE: this was done with "ggplot2_1.0.0" and is specific to that version; this is a private function that may change in future releases)
orig.map_statistic <- ggplot2:::Layer$map_statistic
new.map_statistic <- orig.map_statistic
body(new.map_statistic)[[9]]
# stat_data <- as.data.frame(lapply(new, eval, data, baseenv()))
here's the line that's causing grief I would prefer it the function resolved other names in the plot environment that are not found in the data.frame. So I decided to change it with
body(new.map_statistic)[[9]] <- quote(stat_data <- as.data.frame(lapply(new, eval, data, plot$plot_env)))
assign("map_statistic", new.map_statistic, envir=ggplot2:::Layer)
So now I can use functions with ..().. variables. So I can do
library(scales)
ggplot(dd, aes(x)) +
stat_bin(position="stack", breaks=br) +
geom_text(aes(y=..count.., ymax=..count..+2,
label=percent(..density..*..width..)),
vjust=-.5, breaks=br, stat="bin")
to get
So i'm not sure why ggplot has this default behavior. There could be some good reason for it but I don't know what it is. This does change how ggplot will behave for the rest of the session. You can change back to default with
assign("map_statistic", orig.map_statistic, envir=ggplot2:::Layer)
Context
I have some datasets/variables and I want to plot them, but I want to do this in a compact way. To do this I want them to share the same y-axis but distinct x-axis and, because of the different distributions, I want one of the x-axis to be log scaled and the other linear scaled.
Example
Suppose I have a long tailed variable (that I want the x-axis to be log-scaled when plotted):
library(PtProcess)
library(ggplot2)
set.seed(1)
lambda <- 1.5
a <- 1
pareto <- rpareto(1000,lambda=lambda,a=a)
x_pareto <- seq(from=min(pareto),to=max(pareto),length=1000)
y_pareto <- 1-ppareto(x_pareto,lambda,a)
df1 <- data.frame(x=x_pareto,cdf=y_pareto)
ggplot(df1,aes(x=x,y=cdf)) + geom_line() + scale_x_log10()
And a normal variable:
set.seed(1)
mean <- 3
norm <- rnorm(1000,mean=mean)
x_norm <- seq(from=min(norm),to=max(norm),length=1000)
y_norm <- pnorm(x_norm,mean=mean)
df2 <- data.frame(x=x_norm,cdf=y_norm)
ggplot(df2,aes(x=x,y=cdf)) + geom_line()
I want to plot them side by side using the same y-axis.
Attempt #1
I can do this with facets, which looks great, but I don't know how to make each x-axis with a different scale (scale_x_log10() makes both of them log scaled):
df1 <- cbind(df1,"pareto")
colnames(df1)[3] <- 'var'
df2 <- cbind(df2,"norm")
colnames(df2)[3] <- 'var'
df <- rbind(df1,df2)
ggplot(df,aes(x=x,y=cdf)) + geom_line() +
facet_wrap(~var,scales="free_x") + scale_x_log10()
Attempt #2
Use grid.arrange, but I don't know how to keep both plot areas with the same aspect ratio:
library(gridExtra)
p1 <- ggplot(df1,aes(x=x,y=cdf)) + geom_line() + scale_x_log10() +
theme(plot.margin = unit(c(0,0,0,0), "lines"),
plot.background = element_blank()) +
ggtitle("pareto")
p2 <- ggplot(df2,aes(x=x,y=cdf)) + geom_line() +
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank(),
plot.margin = unit(c(0,0,0,0), "lines"),
plot.background = element_blank()) +
ggtitle("norm")
grid.arrange(p1,p2,ncol=2)
PS: The number of plots may vary so I'm not looking for an answer specifically for 2 plots
Extending your attempt #2, gtable might be able to help you out. If the margins are the same in the two charts, then the only widths that change in the two plots (I think) are the spaces taken by the y-axis tick mark labels and axis text, which in turn changes the widths of the panels. Using code from here, the spaces taken by the axis text should be the same, thus the widths of the two panel areas should be the same, and thus the aspect ratios should be the same. However, the result (no margin to the right) does not look pretty. So I've added a little margin to the right of p2, then taken away the same amount to the left of p2. Similarly for p1: I've added a little to the left but taken away the same amount to the right.
library(PtProcess)
library(ggplot2)
library(gtable)
library(grid)
library(gridExtra)
set.seed(1)
lambda <- 1.5
a <- 1
pareto <- rpareto(1000,lambda=lambda,a=a)
x_pareto <- seq(from=min(pareto),to=max(pareto),length=1000)
y_pareto <- 1-ppareto(x_pareto,lambda,a)
df1 <- data.frame(x=x_pareto,cdf=y_pareto)
set.seed(1)
mean <- 3
norm <- rnorm(1000,mean=mean)
x_norm <- seq(from=min(norm),to=max(norm),length=1000)
y_norm <- pnorm(x_norm,mean=mean)
df2 <- data.frame(x=x_norm,cdf=y_norm)
p1 <- ggplot(df1,aes(x=x,y=cdf)) + geom_line() + scale_x_log10() +
theme(plot.margin = unit(c(0,-.5,0,.5), "lines"),
plot.background = element_blank()) +
ggtitle("pareto")
p2 <- ggplot(df2,aes(x=x,y=cdf)) + geom_line() +
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank(),
plot.margin = unit(c(0,1,0,-1), "lines"),
plot.background = element_blank()) +
ggtitle("norm")
gt1 <- ggplotGrob(p1)
gt2 <- ggplotGrob(p2)
newWidth = unit.pmax(gt1$widths[2:3], gt2$widths[2:3])
gt1$widths[2:3] = as.list(newWidth)
gt2$widths[2:3] = as.list(newWidth)
grid.arrange(gt1, gt2, ncol=2)
EDIT
To add a third plot to the right, we need to take more control over the plotting canvas. One solution is to create a new gtable that contains space for the three plots and an additional space for a right margin. Here, I let the margins in the plots take care of the spacing between the plots.
p1 <- ggplot(df1,aes(x=x,y=cdf)) + geom_line() + scale_x_log10() +
theme(plot.margin = unit(c(0,-2,0,0), "lines"),
plot.background = element_blank()) +
ggtitle("pareto")
p2 <- ggplot(df2,aes(x=x,y=cdf)) + geom_line() +
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank(),
plot.margin = unit(c(0,-2,0,0), "lines"),
plot.background = element_blank()) +
ggtitle("norm")
gt1 <- ggplotGrob(p1)
gt2 <- ggplotGrob(p2)
newWidth = unit.pmax(gt1$widths[2:3], gt2$widths[2:3])
gt1$widths[2:3] = as.list(newWidth)
gt2$widths[2:3] = as.list(newWidth)
# New gtable with space for the three plots plus a right-hand margin
gt = gtable(widths = unit(c(1, 1, 1, .3), "null"), height = unit(1, "null"))
# Instert gt1, gt2 and gt2 into the new gtable
gt <- gtable_add_grob(gt, gt1, 1, 1)
gt <- gtable_add_grob(gt, gt2, 1, 2)
gt <- gtable_add_grob(gt, gt2, 1, 3)
grid.newpage()
grid.draw(gt)
The accepted answer is exactly what makes people run when comes to plotting using R! This is my solution:
library('grid')
g1 <- ggplot(...) # however you draw your 1st plot
g2 <- ggplot(...) # however you draw your 2nd plot
grid.newpage()
grid.draw(cbind(ggplotGrob(g1), ggplotGrob(g2), size = "last"))
This takes care of the y axis (minor and major) guide-lines to align in multiple plots, effortlessly.
Dropping some axis text, unifying the legends, ..., are other tasks that can be taken care of while creating the individual plots, or by using other means provided by grid or gridExtra packages.
The accepted answer looks a little too daunting to me. So I find two ways to get around it with less efforts. Both are based on your Attempt #2 grid.arrange() method.
1. Make plot 1 no y-axis as well
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank()
So all the plots will be the same. You won't have problems with different aspects ratios. You will need to generate a separate y-axis with R or your favorite image editting app.
2. Fix and respect aspects ratio
Add aspect.ratio = 1 or whatever ratio you desire to theme() of individual plots. Then use respect=TRUE in your grid.arrange()
This way you can keep y-axis in plot1 and still maintains aspects ratio in all plots. Inspired by this answer.
Hope you find these helpful!
Is this possible to reproduce this lattice plot with ggplot2?
library(latticeExtra)
data(mtcars)
x <- t(as.matrix(scale(mtcars)))
dd.row <- as.dendrogram(hclust(dist(x)))
row.ord <- order.dendrogram(dd.row)
dd.col <- as.dendrogram(hclust(dist(t(x))))
col.ord <- order.dendrogram(dd.col)
library(lattice)
levelplot(x[row.ord, col.ord],
aspect = "fill",
scales = list(x = list(rot = 90)),
colorkey = list(space = "left"),
legend =
list(right =
list(fun = dendrogramGrob,
args =
list(x = dd.col, ord = col.ord,
side = "right",
size = 10)),
top =
list(fun = dendrogramGrob,
args =
list(x = dd.row,
side = "top",
size = 10))))
EDIT
From 8 August 2011 the ggdendro package is available on CRAN
Note also that the dendrogram extraction function is now called dendro_data instead of cluster_data
Yes, it is. But for the time being you will have to jump through a few hoops:
Install the ggdendro package (available from CRAN). This package will extract the cluster information from several types of cluster methods (including Hclust and dendrogram) with the express purpose of plotting in ggplot.
Use grid graphics to create viewports and align three different plots.
The code:
First load the libraries and set up the data for ggplot:
library(ggplot2)
library(reshape2)
library(ggdendro)
data(mtcars)
x <- as.matrix(scale(mtcars))
dd.col <- as.dendrogram(hclust(dist(x)))
col.ord <- order.dendrogram(dd.col)
dd.row <- as.dendrogram(hclust(dist(t(x))))
row.ord <- order.dendrogram(dd.row)
xx <- scale(mtcars)[col.ord, row.ord]
xx_names <- attr(xx, "dimnames")
df <- as.data.frame(xx)
colnames(df) <- xx_names[[2]]
df$car <- xx_names[[1]]
df$car <- with(df, factor(car, levels=car, ordered=TRUE))
mdf <- melt(df, id.vars="car")
Extract dendrogram data and create the plots
ddata_x <- dendro_data(dd.row)
ddata_y <- dendro_data(dd.col)
### Set up a blank theme
theme_none <- theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.title.x = element_text(colour=NA),
axis.title.y = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
axis.line = element_blank()
#axis.ticks.length = element_blank()
)
### Create plot components ###
# Heatmap
p1 <- ggplot(mdf, aes(x=variable, y=car)) +
geom_tile(aes(fill=value)) + scale_fill_gradient2()
# Dendrogram 1
p2 <- ggplot(segment(ddata_x)) +
geom_segment(aes(x=x, y=y, xend=xend, yend=yend)) +
theme_none + theme(axis.title.x=element_blank())
# Dendrogram 2
p3 <- ggplot(segment(ddata_y)) +
geom_segment(aes(x=x, y=y, xend=xend, yend=yend)) +
coord_flip() + theme_none
Use grid graphics and some manual alignment to position the three plots on the page
### Draw graphic ###
grid.newpage()
print(p1, vp=viewport(0.8, 0.8, x=0.4, y=0.4))
print(p2, vp=viewport(0.52, 0.2, x=0.45, y=0.9))
print(p3, vp=viewport(0.2, 0.8, x=0.9, y=0.4))
As Ben says, everything is possible. Some work to support dendrograms has been done. Andrie de Vries has made a fortify method of tree objects. However, the resulting graphic is not pretty as you can see.
The tile would be easy to do. For the dendrogram I would inspect plot.dendrogram (using getAnywhere) to see how the coordinates for the segments are calculated. Extract those coordinates and use geom_segment to plot the dendrogram. Then use viewports to plot the tiles and the dendrogram together. Sorry I can't give a example, it's a lot of work and it's too late.
I hope this helps
Cheers
Doubtful. I do not see any functions in the Index for ggplot2 that would suggest support for dendrograms, and when this blogger put together a set of translations of the illustrations in Sarkar's Lattice book, he was unable to get a ggplot dendrogram legend:
http://learnr.wordpress.com/2009/08/10/ggplot2-version-of-figures-in-lattice-multivariate-data-visualization-with-r-part-9/
These links provide a solution for heatmaps with dendrograms in ggplot2:
https://gist.github.com/chr1swallace/4672065
https://github.com/chr1swallace/random-functions/blob/master/R/ggplot-heatmap.R
and also this one:
Align ggplot2 plots vertically