This is a short question.
Is there a way to perform abstractive text summarization in R?
There are ways to perform extractive summary (ie extract few relevant sentences), as shown here Text summarization in R language
However, I was unable to find a way to do abstractive summary "purely" in R. I understand that abstractive summary is way more complex and typically requires model training. The two methods that might work so far are using python through reticulate package or use on of google's APIs. was wondering if anyone is aware of R package that does that without external dependencies.
thank you in advance
Related
After forming the matrix( which is my resultant image ) from certain data I am trying to display the image using the "imagesc" in r. The same thing I already had done in Matlab. To do the same in r I found out "imagesc" in r. but when I use this function it is showing the following error message
No documentation for ‘imagesc’ in specified packages and libraries:
you could try ‘??imagesc’
Even I already incorporated
library(R.matlab)
please help me to resolve the issue? I am a beginner in r programming.
You are looking for the function imagesc in the wrong package.
The package R.matlab doesn't have such function (see R.matlab).
You can find it in the matlab package, though.
So just do:
install.packages("matlab")
library(matlab)
and you'll be good to go with imagesc.
That said, if your task is going to be a recurrent one, I think it's a good idea to use native R solutions, instead of Matlab's. In such case, you may want to check ggplot2::geom_tile.
Check this image, for instance:
is there any way to write a flowchart in R markdown to have it as an introduction in the html_output_file?
Yes, there are number of packages which can help do this. DiagrammeR and DiagrammeRsvg are two I have used successfully.
You might like to refer to the fairly simple source for the package PRISMAstatement which implements the standard PRISMA flow chart for systematic reviews using an intermediate dot format.
I am currently testing various community detection algorithms in the igraph package to compare against my implementation.
I am able to run the algorithms on different graphs but I was wondering if there was a way for me to write the clustering to a file, where all nodes in one community are written to one line and so on. I am able to obtain the membership of each node using membership(communities_object) and write that to a file using dput() but I don't know how to write it the way I want.
This is the first time I am working with R as well. I apologize if this has been asked before.
This does not have to do much with igraph, the clustering is given by a simple numeric vector. See ?write.
write(membership(communities_object), file="myfile", ncolumns=1)
write(communities_object$membership, file="myfile", ncolumns=1) also work
This question already has an answer here:
Automatic documentation of datasets
(1 answer)
Closed 8 years ago.
Is there any code self-documenting system for R?
I think writing documentation is a very important part of any statistical analysis. There are always important details in your code or the steps of data cleaning that are not reflected in the final analysis report. I wonder whether there is any efficient self-documenting system (or approach) in R that can help me documenting my codes including my comments o my codes with structure files explaining the structure of the datasets (or tables) used in my code?
Beyond using Sweave or knitr in R, is there any other way of doing that?
I'd suggest bundling up your code and data sets in an R package. There's a steep learning curve the first time you do it, but if you're at the point where you're asking, "how can I better manage this code documentation thing", you're likely ready to take the plunge.
Plus, doesn't the idea of typing ?myOwnFunction or ?myOwnDataset, and having the appropriate help file pop up (just as it does when you do ?mean or ?iris) sound appealing?
You might try writing your code as a Sweave or kntr file, which contains LaTeX text along with R code. This process produces a pdf of your text, including your code, and executes your code.
If you choose to organise your analysis as package, you can use roxygen2 for documentation of your code and data.
I frequently find myself doing some analysis in R and then wanting to make a quick map. The standard plot() function does a reasonable job of quick, but I quickly find that I need to go to ggplot2 when I want to make something that looks nice or has more complex symbology requirements. Ggplot2 is great, but is sometimes cumbersome to convert a SpatialPolygonsDataFrame into the format required by Ggplot2. Ggplot2 can also be a tad slow when dealing with large maps that require specific projections.
It seems like I should be able to use Mapnik to plot spatial objects directly from R, but after exhausting my Google-fu, I cannot find any evidence of bindings. Rather than assume that such a thing doesn't exist, I thought I'd check here to see if anyone knows of an R - Mapnik binding.
The Mapnik FAQ explicitly mentions Python bindings -- as does the wiki -- with no mention of R, so I think you are correct that no (Mapnik-sponsored, at least) R bindings currently exist for Mapnik.
You might get a more satisfying (or at least more detailed) answer by asking on the Mapnik users list. They will know for certain if any projects exist to make R bindings for Mapnik, and if not, your interest may incite someone to investigate the possibility of generating bindings for R.
I would write the SpatialWotsitDataFrames to Shapefiles and then launch a Python Mapnik script. You could even use R to generate the Python script (package 'brew' is handy for making files from templates and inserting values form R).