I'm trying to execute the below code that display a plot:
using Plots, Measures
pyplot()
data = [rand(100), rand(100)];
histogram(data, layout = 2,
title = ["Dataset A" "Dataset B"], legend = false,
ylabel = "ylabel", margin = 5mm)
I do not get any output once I execute it from the command line!!
Knowing that I tried it in 3 different ways and it works (Jupyter, Juni, Julia session), though I'm confused about the way it works in the Juno, kinldy see my observations below:
With Jupyter it is functioning perfectly:
With Juno, I've to run the file TWICE!! the first time looks to be for compilation, second time for execution, maybe!!
And if I closed the plot, I've to close the Julia session, restart it, then re-execute the file TWICE!! and sometimes nothing is appearing!!
With Julia session, it take time for first time execution, then if I closed the plot and run it again, it is appearing smoothly.
The commands like histogram or plot typically don't display the plots for users, they only generate and return the plots.
What displays the plots is actually the display system in Julia.
When Julia is in interactive use, like in REPL, Jupyter and Juno, the display system will be invoked automatically with commands not ending with ";". That's why you see plots displayed in REPL, Jupyter and Juno.
But when executing the file from the command line, the display system is not automatically activated. So you first have to invoke display yourself like this:
using Plots, Measures
pyplot()
data = [rand(100), rand(100)];
h = histogram(data, layout = 2,
title = ["Dataset A" "Dataset B"], legend = false,
ylabel = "ylabel", margin = 5mm)
display(h)
But even this will not give you the picture, but only text representation of the plot. This is because in command line julia, only a very simple text display system is in place, and it doesn't have "full" support for plots from Plots. To display the plots, you have to write your own display mechanism and push it to Julia display system, which is not hard but a little tedious. I will give an example when I have more time.
BTW, if you just want plots generated from command line, another way is to save it to files, which is more direct than making a display mechanism yourself.
Update
Here is a simple display, which mimics the display system used in Julia REPL. The code here is for Julia 0.7/1.0.
const output = IOBuffer()
using REPL
const out_terminal = REPL.Terminals.TerminalBuffer(output)
const basic_repl = REPL.BasicREPL(out_terminal)
const basic_display = REPL.REPLDisplay(basic_repl)
Base.pushdisplay(basic_display)
Using it before the previous code will show the plot. Please note that you use pyplot() backend for Plots, whose default is to open a new window and display the plot in the window, but when the julia finish execution in the command line, it will close the plot window. To deal with this, we could either change ways for the default display, or use another backend to show the plot, for example, plotly() backend will display the plot through html. The complete code may look like following:
const output = IOBuffer()
using REPL
const out_terminal = REPL.Terminals.TerminalBuffer(output)
const basic_repl = REPL.BasicREPL(out_terminal)
const basic_display = REPL.REPLDisplay(basic_repl)
Base.pushdisplay(basic_display)
using Plots, Measures
plotly()
data = [rand(100), rand(100)];
h = histogram(data, layout = 2,
title = ["Dataset A" "Dataset B"], legend = false,
ylabel = "ylabel", margin = 5mm)
display(h)
Use readline() to get such destination that close the plot window by typing enter.
using GR
y = rand(20,1)
p = plot(y,linewidth=2,title="My Plot")
readline()
Related
I have a Juypter Notebook cell with some code (not mine) that generates a Bokeh plot. Last command in the cell is a Bokeh show() command. What I want is for the plot to appear in the output cell below, and then to be able to continue running subsequent cells in the notebook.
What happens instead is that when I run the cell the plot appears below, but the cell with the code continues to run (asterisk in the left-hand brackets) and never stops. So I can't continue to run any other cells unless I click the stop button (which leaves the plot intact in the output cell, but follows it with many lines of error trace-back messages).
My understanding is that executing the output_notebook() function should result in show() giving the behavior I want, as described here:
https://docs.bokeh.org/en/latest/docs/user_guide/notebook.html
In their screenshot, the cell with the show() command has clearly finished running (no asterisk).
I'm not sure if it makes any difference, but in my case I am running the notebook on a remote server and using port-forwarding to view it on my laptop computer browser.
Does anyone know how I can get the show() command to finish running?
For reference, this is the code:
# Use the PCA projection
dset = proj_pca
# Select the dimensions in the projection
dim1 = 0
dim2 = 1
p = figure(plot_width=945, plot_height=560)
p.title.text = 'PCA projection: PC' + str(dim1+1) + ' vs PC' + str(dim2+1)
for cont in continents:
for pop in pop_by_continent[cont]:
projections_within_population = dset[indices_of_population_members[pop]]
p.circle(projections_within_population[:,dim1], projections_within_population[:,dim2],
legend=name_by_code[pop], color = color_dict[pop])
#p.legend.visible = False
p.legend.location = "top_center"
p.legend.click_policy="hide"
output_file("interactive_pca.html", title="PCA projection")
output_notebook()
#save(p)
show(p)
I'm creating a script to cluster my data in a server. I need to save the text output and the images as well. The text output works just fine but when I try to use the png() + plot() + dev.off() thing to save the plots, no image is created.
[ADDED FOR CLARIFICATION]
What I need to do is to SAVE the plot (i.e. generate an image file) in running mode. If I run the code step by step, the file is created.
I already tried to change the image format to PDF and JPG using the corresponding functions but I'm still getting no images as output when running the code as script. When stepping, it works great.
Since it takes a little while for R to render the image when I'm running step by step, I tried to add Sys.sleep(2) in between commands (code below) but nothing changed.
I think the problem might be related to the package that I'm using and the type of object it generates (library(NMF)). I looked at the documentation to see if there was something about the way the plot() function works with the type of object that the clustering algorithm generates but the text is vague:
"The result (of estim.r <- nmf(esGolub, 2:6, nrun=10, seed=123456) for example) is a S3 object of class NMF.rank, that contains a data.frame with the quality measures in column, and the values of r in row. It also contains a list of the consensus matrix for
each value of r".
"All the measures can be plotted at once with the method plot (Figure 1), and the function consensusmap generates heatmaps of the consensus matrix for each value of the rank".
There is another type of image that can be generated after the clustering runs: the consensusmap. This one works on both cases (stepping and running).
The script is pretty short. Here it is:
library(NMF)
data = read.csv('R.csv', header=TRUE, sep=";")
res1 <- nmf(data, rank=2:5, nrun=1, "brunet", "random")
# this always works
capture.output(summary(res1) ,file = "summary.txt", append = TRUE)
# this always works too
png(filename = 'consensus.png', width = 1366, height = 768, units = 'px')
consensusmap(res1)
dev.off()
# this does not work on 'running mode', only 'stepping mode'
png(filename = 'metrics.png', width = 1366, height = 768, units = 'px')
# added hoping it would fix the issue. It didn't
Sys.sleep(2)
plot(res1)
# added hoping it would fix the issue. It didn't
Sys.sleep(2)
dev.off()
The summary.txt file is generated, the consensus.png too. The metrics.png is not. What's going on here??
I have issue with plotting lines over my existing plot in .Rmd in RStudio. I ran the code within the code chunk in .Rmd (⌘ + return) and the plot gives me a graph within the .Rmd (new feature of RStudio v1.0), however when I ran the second code lines, an error shows up.
plot(density(with$glucose),
ylim = c(0.00, 0.02),
xlab = "Glucose Level",
main = "Figure",
lwd = 2)
lines(density(without$glucose),
col = "red",
lwd = 2)
Error in plot.xy(xy.coords(x, y), type = type, ...) : plot.new has not been called yet
On the other hand, if I copy and paste the codes into the console, I could get the plot I want, in the plot viewer within RStudio.
In addition, when I ran some other codes within the .Rmd (⌘ + return), my plots in the plot viewer in RStudio disappear. This means I have to do copy-paste into the console instead of using the (⌘ + return) shortcut.
Does anyone have the same problem?
This is a known problem, but you can solve it very easy: Press Ctrl+Shift+Enter to run the complete chunk, then everything works fine and you don't have to copy-and-paste all thing to the console.
So do all your plots in one chunk and run this chunk. This will produce you the plot within the RMD file (as you mentioned: new feature of RStudio 1.0)
If you're not a fan of the inline output / notebook mode for R Markdown documents, you can also disable it within the Global Options dialog -- try disabling the option:
Show output inline for all R Markdown document
I would like to print multiple graphs in one pdf file. I know there has been a lot on this, but I would like to print different window/graph sizes for each page, i.e. first page a 8.5x11, second page 11x8.5 and so on. I tried this:
pdf(file="Combined_Graphs.pdf",onefile=TRUE,bg="white",width=8.5,height=11)
hist(rnorm(100))
pdf(file="Combined_Graphs.pdf",onefile=TRUE,width=11, height=8.5, bg="white")
hist(rnorm(100,10,2),col="blue")
dev.off()
I must be using onefile=TRUE wrong as it only generates the last graphic before closing. Is there a better way to size the graphic device without having to call the pdf function twice?
What I would do is produce seperate PDF's and them combine them later. I use the PDF toolkit for this. Wrapping this in an R function using a system call through system even makes it scriptable from R. The call to pdftk will look something like:
pdftk *pdf cat output combined.pdf
or in R:
system("pdftk *pdf cat output combined.pdf")
combine_pdfs = function(path, output_pdf) {
system(sprintf("pdftk %s/*pdf cat output %s"), path, output_pdf)
}
I think what you are trying to do cannot be done in R, i.e., you need to use external tools such as the PDF toolkit as suggested by Paul Hiemstra to combine separate PDF files with varying page dimensions (an alternative tool is PDFjam).
If you set onefile = TRUE in your call to pdf(), each plot that is written to that PDF device will be printed on a separate page, yet with the same page dimensions. In your example, you open a first PDF device, write one plot to it, then you open a second PDF device, write a different plot to it, and then close the second PDF device but leave the first PDF device open. Since you use the same file argument for both pdf() calls, you might not notice that the first PDF device is still open. If you closed it, only the first plot would end up in "Combined_Graphs.pdf".
Here is a modified version of your example that illustrates how PDF devices are opened, filled with content, and closed:
pdf(file = "foo.pdf", onefile = TRUE, width = 8.5, height = 11)
hist(rnorm(100))
hist(rnorm(100, 10, 2), col = "red")
pdf(file = "bar.pdf", width =11, height = 8.5)
hist(rnorm(100, 10, 2), col = "blue")
dev.off()
dev.off()
I do a lot of data exploration in R and I would like to keep every plot I generate (from the interactive R console). I am thinking of a directory where everything I plot is automatically saved as a time-stamped PDF. I also do not want this to interfere with the normal display of plots.
Is there something that I can add to my ~/.Rprofile that will do this?
The general idea is to write a script generating the plot in order to regenerate it. The ESS documentation (in a README) says it well under 'Philosophies for using ESS':
The source code is real. The objects are realizations of the
source code. Source for EVERY user modified object is placed in a
particular directory or directories, for later editing and
retrieval.
With any editor allows stepwise (or regionwise) execution of commands you can keep track of your work this way.
The best approach is to use a script file (or sweave or knitr file) so that you can just recreate all the graphs when you need them (into a pdf file or other).
But here is the start of an approach that does the basics of what you asked:
savegraphs <- local({i <- 1;
function(){
if(dev.cur()>1){
filename <- sprintf('graphs/SavedPlot%03d.pdf', i)
dev.copy2pdf( file=filename )
i <<- i + 1
}
}
})
setHook('before.plot.new', savegraphs )
setHook('before.grid.newpage', savegraphs )
Now just before you create a new graph the current one will be saved into the graphs folder of the current working folder (make sure that it exists). This means that if you add to a plot (lines, points, abline, etc.) then the annotations will be included. However you will need to run plot.new in order for the last plot to be saved (and if you close the current graphics device without running another plot.new then that last plot will not be saved).
This version will overwrite plots saved from a previous R session in the same working directory. It will also fail if you use something other than base or grid graphics (and maybe even with some complicated plots then). I would not be surprised if there are some extra plots on occasion that show up (when internally a plot is created to get some parameters, then immediatly replaced with the one of interest). There are probably other things that I have overlooked as well, but this might get you started.
you could write your own wrapper functions for your commonly used plot functions. This wrapper function would call both the on-screen display and a timestamped pdf version. You could source() this function in your ~/.Rprofile so that it's available every time you run R.
For latice's xyplot, using the windows device for the on-screen display:
library(lattice)
my.xyplot <- function(...){
dir.create(file.path("~","RPlots"))
my.chart <- xyplot(...)
trellis.device(device="windows",height = 8, width = 8)
print(my.chart)
trellis.device(device = "pdf",
file = file.path("~", "RPlots",
paste("xyplot",format(Sys.time(),"_%Y%m%d_%H-%M-%S"),
".pdf", sep = "")),
paper = "letter", width = 8, height = 8)
print(my.chart)
dev.off()
}
my.data <- data.frame(x=-100:100)
my.data$y <- my.data$x^2
my.xyplot(y~x,data=my.data)
As others have said, you should probably get in the habit of working from an R script, rather than working exclusively from the interactive terminal. If you save your scripts, everything is reproducible and modifiable in the future. Nonetheless, a "log of plots" is an interesting idea.