I have been following a basic manual of Maxima, I need to solve a differencial ecuation system.
First of all, I loaded both of the packets, load(dynamics); and load(draw);
In order to obtain the points I have:
solutionsPoints: rk([4-x^2-4*y^2,y^2-x^2+1],[x,y],[-1.25,0.75],[t,0,4,0.02]);
I got all the points needed, now to represent this,
draw3d(points_joined = true, point_type = dot, points(solutionsPoints), terminal = eps);
Maxima in this case returns:
[gr3d(points)]
What should I do to have this representation?
Thanks
I see that you have terminal = eps, therefore draw3d will create a .eps file and it won't display the image. I tried draw3d as you showed it, and it created maxima_out.eps in the current directory, and I can use a viewer (I used evince) to look at it, and it seems OK.
If you cut out the terminal = eps part, it will display the curve immediately, without creating an output file.
Related
I am trying to have a live plot of a datafile that is being dynamically updated inside the main program. I am plotting using the following .plt file
set pm3d map
set xrange[ -6.0000000000000000 : 6.0000000000000000 ]
set yrange[ -6.0000000000000000 : 6.0000000000000000 ]
sp'fpf.dat'u 1:2:3 w pm3d
pause 0.1
reread
But on running the program, the animation I am obtaining is getting distorted.
I think the problem is taking place because as the file is being dynamically updated, even before gnuplot is able to generate the full plot using the temporarily stored data, the file is being updated again and again. What is the solution?
First, I suggest not to use reread but instead create a loop that you have more control over.
set pm3d
set view map
while (some-condition) {
sp'fpf.dat'u 1:2:3 w pm3d
pause 0.1
}
Now several options come to mind
1) The program that is creating the data could over-write the previous data in place
rather than creating (or truncating) the file each time.
2) Instead of putting gnuplot in a loop based on refreshing every tenth of a second, use explicit synchronization between the data file creation and the subsequent plot. There are many ways you might do this depending on your environment and your control over the programs involved. For example you might replace the pause statement with a second loop that spins until the data file modification time changes (specific commands available depend on your OS and shell)
oldtime = timestamp
while (timestamp == oldtime) {
timestamp = system( "stat --format=%X file.dat" )
pause 0.1
}
# we exited the previous loop because the file timestamp changed
3) You could try using multiplot mode (set multiplot before starting to loop), so that each new plot is drawn on top of the previous plot rather than replacing it. If your diagnosis is correct that the white sections are due to incomplete data, then instead of a blank area you will see the content of the previous plot.
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 am trying to create a plot and eventually save it as a file. But because I am making a lot of changes and want to test it out, I want to be able to view and save the plot at the same time. I have looked at this page to do what I want to do but in my system, it does not seem to be working as it is supposed to.
Here are my codes:
png('Save.png')
sample.df <- data.frame(group = c('A','B','A','C','B','A','A','C','B','C','C','C','B'),
X = c(2,11,3,4,1,6,3,7,5,9,10,2,8),
Y = c(3,8,5,2,7,9,3,6,6,1,3,4,10))
plot(Y ~ X, data = sample.df)
dev.copy(png, 'Save.png')
dev.off()
There are several issues (I am new to R so I might be missing something entirely):
(1) When I use png(), I cannot view the plot in RStudio so I used dev.copy() but it does not allow me to view my plot in R studio
(2) Even after I use dev.off(), I cannot view the saved file until I close the RStudio (says "Windows Photo Viewer can't open this picture because the picture is being edited in another program"). I need to restart every time so it is very inconvenient.
What am I doing wrong and how could I view and view saved file without restarting RStudio every time? Thank you in advance!
Addition
Based on Love Tätting's comments, when I run dev.list(), this is what I get.
> png('Save.png')
>
> sample.df <- data.frame(group = c('A','B','A','C','B','A','A','C','B','C','C','C','B'),
+ X = c(2,11,3,4,1,6,3,7,5,9,10,2,8),
+ Y = c(3,8,5,2,7,9,3,6,6,1,3,4,10))
>
> plot(Y ~ X, data = sample.df)
>
> dev.copy(png, 'Save.png')
png
3
> dev.off()
png
2
> dev.list()
png
2
> dev.off()
null device
1
> dev.list()
NULL
Why do I not get RStudioGD?
RStudio has its own device, "RStudioGD". You can see it with dev.list(), where it by default is the first and only one.
R's design for decoupling rendering and backend is by the abstraction of devices. Which ones you can use is platform and environment dependent. dev.list() shows the stack of current devices.
If I understand your problem correctly you want to display the graph first in RStudio, and then decide whether you want to save it or not. Depending on how often you save th image you could use the 'export' button in the plot pane in RStudio and save it manually.
Otherwise, your choice of trying to copy it would be the obvious one for me as well.
To my knowledge the device abstraction in R does not allow one to encapsulate the device as an object, so one for example could make it an argument to a function that does the actual plot. Since dev.set() takes an index as argument, passing the index as argument will be dependent on state of the stack of devices.
I have not come up with a clean solution to this myself and have sometimes retorted to bracketing the plot rendering code with a call to a certain device and saving it right after, and switching device depending on a global.
So, if you can, use RStudios export functionality, otherwise an abstraction would need to maintain the state of the global stack of devices and do extensive testing of its state as it is global and you cannot direct a plot call to a certain device, it simply plots to the current device (to my knowledge).
Edit after OP comment
It seems that it is somewhat different behaviour you are experiencing if you cannot watch the file after dev.off, but also need to quit RStudio. For some type of plot frameworks there is a need to call print on the graphical object to have it actually print to the file. Perhaps this is done by RStudio at shutdown as part of normal teardown procedures of open devices? In that ase the file should be empty if you forcibly look in its contents before quiting RStudio.
The other thing that sometimes work is to call dev.off twice. I don't know exactly why, but sometimes more devices get created than I have anticipated. After you have done dev.off, what does dev.list show?
Edit after OP's edit
I can see that you do, png(); dev.copy(); dev.off(). This will leave you with one more device opened than closed. You will still have the first graphics device that you started open as can be seen when you do the listing. You can simply remove dev.copy(). The image will be saved on dev.off() and should be able to open from the filesystem.
As to why you cannot see the RStudio graphics device, I am not entirely sure. It might be that other code is messing with your device stack. I would check in a clean session if it is there to make sure other code isn't tampering with the device stack. From RStudio forums and other SO questions there seem to have been plot pane related problems in RStudio that have resolved after updating RStudio to the latest. If that is a viable solution for you I would try that.
I've just added support for RStudio's RStudioGD device to the developer's version of R.devices package (I'm the author). This will allow you to do the following in RStudio:
library("R.devices")
sample.df <- data.frame(
group = c('A','B','A','C','B','A','A','C','B','C','C','C','B'),
X = c(2,11,3,4,1,6,3,7,5,9,10,2,8),
Y = c(3,8,5,2,7,9,3,6,6,1,3,4,10)
)
figs <- devEval(c("RStudioGD", "png"), name = "foo", {
plot(Y ~ X, data = sample.df)
})
You can specify any set of output target types, e.g. c("RStudioGD", "png", "pdf", "x11"). The devices that output to file will by default write the files in folder figures/ with filenames as <name>.<ext>, e.g. figures/foo.png in the above example.
The value of the call, figs, holds references to all figures produced, e.g. figs$png. You can open them directly from R using the operator !. For example:
> figs$png
[1] "figures/foo.png"
> !figs$png
[1] "figures/foo.png"
The latter call should show the PNG file using your system's PNG viewer.
Until I submit these updates to CRAN, you can install the developer's version (2.15.1.9000) as:
remotes::install_github("HenrikBengtsson/R.devices#develop")
I've made different plots (more than a hundred) for a project and I haven't capture them on the way (yes it's bad , i know). Now, I need to save them all at once but without running again my script (which takes hours). Is there a way to do so within Rstudio ?
Edit: All the plot are already there and I don't want to run them again.
In RStudio, every session has a temporary directory that can be obtained using tempdir(). Inside that temporary directory, there is another directory that always starts with "rs-graphics" and contains all the plots saved as ".png" files. Therefore, to get the list of ".png" files you can do the following:
plots.dir.path <- list.files(tempdir(), pattern="rs-graphics", full.names = TRUE);
plots.png.paths <- list.files(plots.dir.path, pattern=".png", full.names = TRUE)
Now, you can copy these files to your desired directory, as follows:
file.copy(from=plots.png.paths, to="path_to_your_dir")
Additional feature:
As you will notice, the .png file names are automatically generated (e.g., 0078cb77-02f2-4a16-bf02-0c5c6d8cc8d8.png). So if you want to number the .png files according to their plotting order in RStudio, you may do so as follows:
plots.png.detials <- file.info(plots.png.paths)
plots.png.detials <- plots.png.detials[order(plots.png.detials$mtime),]
sorted.png.names <- gsub(plots.dir.path, "path_to_your_dir", row.names(plots.png.detials), fixed=TRUE)
numbered.png.names <- paste0("path_to_your_dir/", 1:length(sorted.png.names), ".png")
# Rename all the .png files as: 1.png, 2.png, 3.png, and so on.
file.rename(from=sorted.png.names, to=numbered.png.names)
Hope it helps.
Although this discussion has been inactive for a while, there are some persons, like myself, who still come across the same problem, and the other solutions don't really seem to even get what the actual question is.
So, hands on. Your plot history gets saved in a variable called .SavedPlots. You can either access it directly, assign it to another variable in code or do the latter from the plots window.
# ph for plot history
ph <- .SavedPlots
In R 3.4.2, I could index ph to reproduce the corresponding plot in a device. What follows is rather straightforward:
Open a new device (png, jpeg, pdf...).
Reproduce your plot ph[index_of_plot_in_history].
Close the device (or keep plotting if it is a pdf with multiple pages).
Example:
for(i in 1:lastplot) {
png('plotname.png')
print(ph[i])
dev.off()
}
Note: Sometimes this doesn't happen because of poor programming. For instance, I was using the MICE package to impute many datasets with a large number of variables, and plotting as shown in section 4.3 of this paper. Problem was, that only three variables per plot were displayed, and if I used a png device in my code, only the last plot of each dataset would be saved. However, if the plots were printed to a window, all the plots of each dataset would be recorded.
If your plots are 3d, you can take a snapshot of all your plots and save them as a .png file format.
snapshot3d(filename = '../Plots/SnapshotPlots.png', fmt = 'png')
Or else, the best way is to create a multi-paneled plotting window using the par(mfrow) function. Try the following
plotsPath = "../Plots/allPlots.pdf"
pdf(file=plotsPath)
for (x in seq(1,100))
{
par(mfrow = c(2,1))
p1=rnorm(x)
p2=rnorm(x)
plot(p1,p2)
}
dev.off()
You can also use png, bmp, tiff, and jpeg functions instead of pdf. You can read their advantages and disadvantages and choose the one you think is good for your needs.
I am not sure how Rstudio opens the device where the plot are drawn, but I guess it uses dev.new(). In that case one quick way to save all opened graphs is to loop through all the devices and write them using dev.print.
Something like :
lapply(dev.list(),function(d){dev.set(d);dev.print(pdf,file=file.path(folder,paste0("graph_",d,".pdf"))})
where folder is the path of the folder where you want to store your graph (could be for example folder="~" if you are in linux and want to store all your graph in your home folder).
If you enter the following function all that will follow will be save in a document:
pdf("nameofthedocument.pdf")
plot(x~y)
plot(...
dev.off()
You can also use tiff(), jpg()... see ?pdf
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.