One interesting feature of RStudio is it allows to save multiple plots generated from a script. This however opens up the problem of how to edit multiple plots. My issue at the moment is adding lines to histograms using the abline() function. This function was designed however to work with the last plot generated by the environment. One way of course would be ad the lines as soon as the plot is generated, however I have to calculate the coordinates at the end of the algorithm, by then I have transformed the data and generated multiple plots from it. So I was wondering if there isn't a way to tell R to search for a given plot and add the line to it. I read abline() documentation but found nothing regarding it. One can always save the data necessary to generate the plot and generate it at the end of the script, but I was wondering if there isn't a less consuming memory method.
One way to get around this issue is:
1.Save your graphics as variables, for ex: hist_1=hist(x, plot=FALSE)
2.Write any code u like, for ex: very complicated code give y as a number for output
3.plot(hist_1)
4.abline(hist_1, v=y)
gives a general idea of how to edit multiple plots without having to save multiple copies of datasets and without overloading Rstudio interface. Works well with the R ubuntu terminal too.
Related
I am trying to use the default plot() function in R to try and plot a shapefile that is about 100MB, using RStudio. When I try and plot the shapefile, the command doesn't finish executing for around 5 minutes, and when it finally does, the plotting window remains blank. When I execute the same process exactly in VS Code, the plot appears almost instantly, as expected.
I have tried uninstalling and reinstalling RStudio with no success.
I can't speak for what VStudio does, but I can guarantee that plotting 100MB worth of data points is useless (unless the final plot is going to be maybe 6 by 10 meters in size).
First thing: can you load the source file into R at all? One would hope so since that's not a grossly huge data blob. Then use your choice of reduction algorithms to get a reasonable number of points to plot, e.g. 800 by 1600, which is all a monitor can display anyway.
Next try plotting a small subset to verify the data are in a valid form, etc.
Then consider reducing the data by collapsing maybe each 10x10 region to a single average value, or by using ggplot2:geom_hex .
I'm trying to, within a for loop, create and save multiple plots from fb prophet and save them to jpeg files.
Despite following the code for many questions related to saving R plots in a loop on stackoverflow, none of the solutions seem to be working and I can't figure out what I'm doing wrong. The below code would be within a for loop:
jpeg(filename="plot1.jpeg")
plot(model, future_forecast) + ggtitle(Material_name)
dev.off()
#now plot seasonalities
jpeg(filename="plot2.jpeg")
prophet_plot_components(model, future_forecast)
dev.off()
I expect that this code would create two separate plots using the prophet plotting functionality, and save them to jpeg files. What actually happens is that the program saves one plot file correctly, and a second plot file as a blank plot.
When you execute (or source) a script as opposed to running it line-by-line, some of the output is suppressed. This is what is happening here. In order to force the output of your plot, just enclose the statement within the print function.
For example:
print(prophet_plot_components(model, future_forecast))
my questions involves the following: I have the basic task of visualizing the steps in a sorting algorithm by plotting the vector as a bar graph. That's no problem and I already have my solution. The only problem is that I consider my solution ugly in the sense, that I always make a call to a plotting function and thus get a new window all the time, resulting in a lot of them.
Question: Can I somehow make a function that takes the previous plot as an argument and plots the graph in the same window? Or something similar.
Thanks
You should just use the Jupyter notebook from within Sage (using a SageMath kernel). Then you can just reevaluate the cell when you want to update your graph. Or, if I'm understanding the question correctly, you could have
Cell 1 - basic functions
Cell 2 - function that updates graph using P += new_plot syntax
Cell 3 - cell where you do the plotting
I'm not certain I've understood, though.
Previously:
You should probably try using the Sage notebook.
I am trying to render 739455 data point on a graph using R, but on the x-axis I can not view all those numbers, is there a way I can do that?
I am new to R.
Thank you
As others suggested, try hist, hexbin, plot(density(node)), as these are standard methods for dealing with more points than pixels. (I like to set hist with the parameter breaks = "FD" - it tends to have better breakpoints than the default setting.)
Where you may find some joy is in using the iplots package, an interactive plotting package. The corresponding commands include ihist, iplot, and more. As you have a Mac, the more recent Acinonyx package may be even more fun. You can zoom in and out quite easily. I recommend starting with the iplots package as it has more documentation and a nice site.
If you have a data frame with several variables, not just node, then being able to link the different plots such that brushing points in one plot highlights them in another will make the whole process more stimulating and efficient.
That's not to say that you should ignore hexbin and the other ideas - those are still very useful. Be sure to check out the options for hexbin, e.g. ?hexbin.
I made a plot in R and I want to repeat all the commands (like plot(), legend() or line()) that were carried out for this plot, with some minor changes. For example I want to set the axes to logarithmic scale and change the title of the plot.
In gnuplot I would use the replot command.
plot ...
set title "The same plot with logarithmic axes"
set logscale
replot
Is something like this possible in R. The only thing that comes to my mind of doing this (besides changing the values manually and re-run the lines of codes) would be setting up a function, that asks for all parameters that might be changed by the user.
Thanks for your help,
Sven
R uses a pen and paper graphics model - once the plot has been drawn on the device that is it. If you want to change some aspect of the plot, you need to replay the graphics function calls that produce the plot with the changes made to the code.
Depending on what you are really doing there are two options:
If this is just for you, write code in a text editor / IDE that knows R and can send chunks of code at a time to R. That way the code to produce the figure is recorded in a separate script which you can paste into/send to R making the changes you need each time to the script.
If you are going to be doing this often, then write yourself a wrapper plotting function that encapsulates the plot code you want but allows you to pass in arguments to alter the aspects you want.
Lattice and ggplot2 are a little different as they are based on grid graphics and create objects that when printed produce a plot on the device. One can manipulate that object to alter what is drawn, and with grid one can push and pop things on to / off a viewport.