With Gadfly it is possible to combine plots in a grid and save the combined plot in a file:
using Gadfly, Compose
x=1:0.1:5;
grid = Array(Compose.Context, (2, 2));
grid[1,1] = render(plot( x=x, y = x, Geom.line));
grid[1,2] = render(plot( x=x, y = x.^2, Geom.line));
grid[2,1] = render(plot( x=x, y = log(x), Geom.line));
grid[2,2] = render(plot( x=x, y = sqrt(x), Geom.line));
draw(SVG("example.svg", 100mm, 100mm), gridstack(grid));
I wrote a function that creates such a plot and this function creates a file. It is a little bit unintuitive for someone who wants to use this function why exactly this function creates a file, while the results of all the other plotting functions with single plots are displayed directly in the browser.
So, is it possible to call a function (in place of draw?) such that the combined plot defined by the grid is displayed directly in the browser like "normal" plots?
function as_temp_html(gadflyplot)
thefilepath=tempname() * ".html"
write(open(thefilepath,"w"),stringmime("text/html",gadflyplot))
return thefilepath
end
You can open this file in your browser by re-using Gadfly's crossplatform "open_file" method:
function open_file(filename)
if is_apple()
run(`open $(filename)`)
elseif is_linux() || is_bsd()
run(`xdg-open $(filename)`)
elseif is_windows()
run(`$(ENV["COMSPEC"]) /c start $(filename)`)
else
warn("Showing plots is not supported on OS $(string(Compat.KERNEL))")
end
end
EDIT: now the answer uses Gadfly-exclusive code
Related
I want to plot the function
4(x)^2 = ((y)^2/(1-y));
how can I plot this?
--> 4*(x) = ((y^2)*(1-y)^-1)^0.5;
4*(x) = ((y^2)*(1-y)^-1)^0.5;
^^
Error: syntax error, unexpected =, expecting end of file
Since Scilab 6.1.0, plotimplicit() does it:
plotimplicit "4*x^2 = y^2/(1-y)"
xgrid()
Can't do more simple. Result:
Well, you have to first create a function and for that you have to express one variable in terms of the other.
function x = f(y)
x = (((y^2)*(1-y)^-1)^0.5)/4;
endfunciton
Then you need to generate the input data (i.e, the points at which you want to evaluate the function)
ydata = linspace(1, 10)
Now you push your input point through the function to get your output points
xdata = f(ydata)
Then, you can plot the pairs of x and y using:
plot(xdata, ydata)
Or even easier, without the intermediate step of generating the output data, you can simply do:
plot(f(ydata), ydata)
BTW. I find it strange that the function you are trying to plot is x in terms of y, usually, x is the input variable, but I hope you know what you are trying to accomplish.
Reference: https://www.scilab.org/tutorials/getting-started/plotting
Take care that y must be in [-inf 1[
y=linspace(-10 ,1.00001,1000);
x = sqrt(y^2./(1-y))/4;
clf; plot(y,x),plot(y,-x)
If x is a solution -x is also solution
Two questions in one: Given a line plotted in Julia, how can I
delete it from the plot and legend (without clearing the whole plot)
change its properties (such as color, thickness, opacity)
As a concrete example in the code below, how can I 1. delete previous regression lines OR 2. change their opacity to 0.1?
using Plots; gr()
f = x->.3x+.2
g = x->f(x)+.2*randn()
x = rand(2)
y = g.(x)
plt = scatter(x,y,c=:orange)
plot!(0:.1:1, f, ylim=(0,1), c=:green, alpha=.3, linewidth=10)
anim = Animation()
for i=1:200
r = rand()
x_new, y_new = r, g(r)
push!(plt, x_new, y_new)
push!(x, x_new)
push!(y, y_new)
A = hcat(fill(1., size(x)), x)
coefs = A\y
plot!(0:.1:1, x->coefs[2]*x+coefs[1], c=:blue) # plot new regression line
# 1. delete previous line
# 2. set alpha of previous line to .1
frame(anim)
end
gif(anim, "regression.gif", fps=5)
I tried combinations of delete, pop! and remove but without success.
A related question in Python can be found here: How to remove lines in a Matplotlib plot
Here is a fun and illustrative example of how you can use pop!() to undo plotting in Julia using Makie. Note that you will see this goes back in the reverse order that everything was plotted (think, like adding and removing from a stack), so deleteat!(scene.plots, ind) will still be necessary to remove a plot at a specific index.
using Makie
x = range(0, stop = 2pi, length = 80)
f1(x) = sin.(x)
f2(x) = exp.(-x) .* cos.(2pi*x)
y1 = f1(x)
y2 = f2(x)
scene = lines(x, y1, color = :blue)
scatter!(scene, x, y1, color = :red, markersize = 0.1)
lines!(scene, x, y2, color = :black)
scatter!(scene, x, y2, color = :green, marker = :utriangle, markersize = 0.1)
display(scene)
sleep(10)
pop!(scene.plots)
display(scene)
sleep(10)
pop!(scene.plots)
display(scene)
You can see the images above that show how the plot progressively gets undone using pop(). The key idea with respect to sleep() is that if we were not using it (and you can test this on your own by running the code with it removed), the fist and only image shown on the screen will be the final image above because of the render time.
You can see if you run this code that the window renders and then sleeps for 10 seconds (in order to give it time to render) and then uses pop!() to step back through the plot.
Docs for sleep()
I have to say that I don't know what the formal way is to accomplish them.
There is a cheating method.
plt.series_list stores all the plots (line, scatter...).
If you have 200 lines in the plot, then length(plt.series_list) will be 200.
plt.series_list[1].plotattributes returns a dictionary containing attributes for the first line(or scatter plot, depends on the order).
One of the attributes is :linealpha, and we can use it to modify the transparency of a line or let it disappear.
# your code ...
plot!(0:.1:1, x->coefs[2]*x+coefs[1], c=:blue) # plot new regression line
# modify the alpha value of the previous line
if i > 1
plt.series_list[end-1][:linealpha] = 0.1
end
# make the previous line invisible
if i > 2
plt.series_list[end-2][:linealpha] = 0.0
end
frame(anim)
# your code ...
You cannot do that with the Plots package. Even the "cheating" method in the answer by Pei Huang will end up with the whole frame getting redrawn.
You can do this with Makie, though - in fact the ability to interactively change plots was one of the reasons for creating that package (point 1 here http://makie.juliaplots.org/dev/why-makie.html)
Not sure about the other popular plotting packages for Julia.
I'm trying to trouble shoot why Drake plots are not showing up with readd() - the rest of the pipeline seem's to have worked though.
Not sure if this is caused by minfi::densityPlot or some other reason; my thoughts are the later as it's also not working for the barplot function which is base R.
In the RMarkdown report I have readd(dplot1) etc. in the chunks but the output is NULL
This is the code I have in my R/setup.R file:
library(drake)
library(tidyverse)
library(magrittr)
library(minfi)
library(DNAmArray)
library(methylumi)
library(RColorBrewer)
library(minfiData)
pkgconfig::set_config("drake::strings_in_dots" = "literals") # New file API
# Your custom code is a bunch of functions.
make_beta <- function(rgSet){
rgSet_betas = minfi::getBeta(rgSet)
}
make_filter <- function(rgSet){
rgSet_filtered = DNAmArray::probeFiltering(rgSet)
}
This is my R/plan.R file:
# The workflow plan data frame outlines what you are going to do
plan <- drake_plan(
baseDir = system.file("extdata", package = "minfiData"),
targets = read.metharray.sheet(baseDir),
rgSet = read.metharray.exp(targets = targets),
mSetSq = preprocessQuantile(rgSet),
detP = detectionP(rgSet),
dplot1 = densityPlot(rgSet, sampGroups=targets$Sample_Group,main="Raw", legend=FALSE),
dplot2 = densityPlot (getBeta (mSetSq), sampGroups=targets$Sample_Group, main="Normalized", legend=FALSE),
pal = RColorBrewer::brewer.pal (8,"Dark2"),
dplot3 = barplot (colMeans (detP[,1:6]), col=pal[ factor (targets$Sample_Group[1:6])], las=2, cex.names=0.8, ylab="Mean detection p-values"),
report = rmarkdown::render(
knitr_in("report.Rmd"),
output_file = file_out("report.html"),
quiet = TRUE
)
)
After using make(plan) it looks like everything ran smoothly:
config <- drake_config(plan)
vis_drake_graph(config)
I am able to use loadd() to load the objects needed for one of these plots and then make the plots, like this:
loadd(rgSet)
loadd(targets)
densityPlot(rgSet, sampGroups=targets$Sample_Group,main="Raw", legend=FALSE)
But the readd() command doesn't work?
The output in the .html for dplot3 looks weird...
Fortunately, this is expected behavior. drake targets are return values of commands, and so the value of dplot3 is supposed to be the return value of barplot(). The return value of barplot() is actually not a plot. The "Value" section of the help file (?barplot) explains the return value.
A numeric vector (or matrix, when beside = TRUE), say mp, giving the coordinates of all the bar midpoints drawn, useful for adding to the graph.
If beside is true, use colMeans(mp) for the midpoints of each group of bars, see example.
So what is going on? As with most base graphics functions, the plot from barplot() is actually a side effect. barplot() sends the plot to a graphics device and then returns something else to the user.
Have you considered ggplot2? The return value of ggplot() is actually a plot object, which is more intuitive. If you want to stick with base graphics, maybe you could save the plot to an output file.
plan <- drake_plan(
...,
dplot3 = {
pdf(file_out("dplot3.pdf"))
barplot(...)
dev.off()
}
)
I've been trying to draw two plots using R's ggplot library in RStudio. Problem is, when I draw two within one function, only the last one displays (in RStudio's "plots" view) and the first one disappears. Even worse, when I run ggsave() after each plot - which saves them to a file - neither of them appear (but the files save as expected). However, I want to view what I've saved in the plots as I was able to before.
Is there a way I can both display what I'll be plotting in RStudio's plots view and also save them? Moreover, when the plots are not being saved, why does the display problem happen when there's more than one plot? (i.e. why does it show the last one but not the ones before?)
The code with the plotting parts are below. I've removed some parts because they seem unnecessary (but can add them if they are indeed relevant).
HHIplot = ggplot(pergame)
# some ggplot geoms and misc. here
ggsave(paste("HHI Index of all games,",year,"Finals.png"),
path = plotpath, width = 6, height = 4)
HHIAvePlot = ggplot(AveHHI, aes(x = AveHHI$n_brokers))
# some ggplot geoms and misc. here
ggsave(paste("Average HHI Index of all games,",year,"Finals.png"),
path = plotpath, width = 6, height = 4)
I've already taken a look here and here but neither have helped. Adding a print(HHIplot) or print(HHIAvePlot) after the ggsave() lines has not displayed the plot.
Many thanks in advance.
Update 1: The solution suggested below didn't work, although it works for the answer's sample code. I passed the ggplot objects to .Globalenv and print() gives me an empty gray box on the plot area (which I imagine is an empty ggplot object with no layers). I think the issue might lie in some of the layers or manipulators I have used, so I've brought the full code for one ggplot object below. Any thoughts? (Note: I've tried putting the assign() line in all possible locations in relation to ggsave() and ggplot().)
HHIplot = ggplot(pergame)
HHIplot +
geom_point(aes(x = pergame$n_brokers, y = pergame$HHI)) +
scale_y_continuous(limits = c(0,10000)) +
scale_x_discrete(breaks = gameSizes) +
labs(title = paste("HHI Index of all games,",year,"Finals"),
x = "Game Size", y = "Herfindahl-Hirschman Index") +
theme(text = element_text(size=15),axis.text.x = element_text(angle = 0, hjust = 1))
assign("HHIplot",HHIplot, envir = .GlobalEnv)
ggsave(paste("HHI Index of all games,",year,"Finals.png"),
path = plotpath, width = 6, height = 4)
I'll preface this by saying that the following is bad practice. It's considered bad practice to break a programming language's scoping rules for something as trivial as this, but here's how it's done anyway.
So within the body of your function you'll create both plots and put them into variables. Then you'll use ggsave() to write them out. Finally, you'll use assign() to push the variables to the global scope.
library(ggplot2)
myFun <- function() {
#some sample data that you should be passing into the function via arguments
df <- data.frame(x=1:10, y1=1:10, y2=10:1)
p1 <- ggplot(df, aes(x=x, y=y1))+geom_point()
p2 <- ggplot(df, aes(x=x, y=y2))+geom_point()
ggsave('p1.jpg', p1)
ggsave('p2.jpg', p2)
assign('p1', p1, envir=.GlobalEnv)
assign('p2', p2, envir=.GlobalEnv)
return()
}
Now, when you run myFun() it will write out your two plots to .jpg files, and also drop the plots into your global environment so that you can just run p1 or p2 on the console and they'll appear in RStudio's Plot pane.
ONCE AGAIN, THIS IS BAD PRACTICE
Good practice would be to not worry about the fact that they're not popping up in RStudio. They wrote out to files, and you know they did, so go look at them there.
Background
Hey everyone!
I'm new to using R, and became interested in using it after having a team member give a tutorial of how useful it can be in an academic setting.
I am trying to write a script to automatically read my data from multiple files and then plot the resultant graphs to multiple files, so that they can be easily added to a manuscript (PowerPoint, latex, etc.)
Problem
I have found that the following code will allow me to produce a graph
p = qplot(factor(step), y, data=x, colour=c))
p = p + theme_bw()
# etc...
wrapping this around a png call will allow me to output the plot to a PNG:
png("test.png")
p = qplot(factor(step), y, data=x, colour=c))
p = p + theme_bw()
# etc...
p
dev.off()
I wanted to put the graph creation into a function so that I can create graphs and consequent seperate PNGs. So I put everything into a function:
func <- function()
{
png("test.png")
p = qplot(factor(step), y, data=x, colour=c))
p = p + theme_bw()
# etc...
p
dev.off()
}
If I call func() A PNG is created, but it is empty. Is there any specific reason why I can do this without the function but can't when I'm calling it from a function?
When using ggplot2 or lattice non-interactively (i.e. not from the command-line), you need to explicitly print() plots that you've constructed. So just do print(p) in the final line of your code, and all should be fine.
This is unintuitive enough that it's one of the most frequent of all FAQs.