Is it possible to run callr::r with a different R version than the one currently used? An example would be to call the following from R3.5.1, but execute it with R3.4.1.
callr::r(
func = R.version.string,
r_binary = '..../R3.4.1/bin' # inexistent argument
)
It should return something like "3.4.1". I have looked into callr:::setup_r_binary_and_args, but it takes the current R version.
Related
I'm making a package which contains a function that calls rstudioapi::jobRunScript(), and I would like to to be able to write tests for this function that can be run normally by devtools::test(). The package is only intended for use during interactive RStudio sessions.
Here's a minimal reprex:
After calling usethis::create_package() to initialize my package, and then usethis::use_r("rstudio") to create R/rstudio.R, I put:
foo_rstudio <- function(...) {
script.file <- tempfile()
write("print('hello')", file = script.file)
rstudioapi::jobRunScript(
path = script.file,
name = "foo",
importEnv = FALSE,
exportEnv = "R_GlobalEnv"
)
}
I then call use_test() to make an accompanying test file, in which I put:
test_that("foo works", {
foo_rstudio()
})
I then run devtools::test() and get:
I think I understand the basic problem here: devtools runs a separate R session for the tests, and that session doesn't have access to RStudio. I see here that rstudioapi can work inside child R sessions, but seemingly only those "normally launched by RStudio."
I'd really like to use devtools to test my function as I develop it. I suppose I could modify my function to accept an argument passed from the test code which will simply run the job in the R session itself or in some other kind of child R process, instead of an RStudio job, but then I'm not actually testing the normal intended functionality, and if there's an issue which is specific to the rstudioapi::jobRunScript() call and which could occur during normal use, then my tests wouldn't be able to pick it up.
Is there a way to initialize an RStudio process from within a devtools::test() session, or some other solution here?
I have a bunch of sf objects I'd like to export to GDB from R. I'm running R 4.0.2 on Windows 10. In this case the sf objects are all vector point data. The main reasons to export to GDB are to keep longer field names (the shapefile truncation is very annoying), and because GDBs are more desirable storage locations for our workflows.
Yes, I know about the ArcGisBinding package. I've got it to work in a test script but it's pretty unstable - often crashing and requiring a restart of R. This is a problem, because the sf objects I'd like to export come after an already long Rmd that reads in, formats and cleans the data. So it's not a simple manner of re-running the script until arc.write doesn't break. I could break up the script, but then I'd still have to read in a bunch of shapefiles. One option I haven't yet explored is using reticulate to call a python script instead of trying to do everything in R, but we're trying to do our analysis all in one place, if possible.
I'm pretty sure I've managed to set up RPyGeo appropriately, first setting my python path using the reticulate package. I'm doing it this way because IT restrictions means I can't edit PATH variables on my machine.
#package calls
library(sf)
library(spData)
library(reticulate)
#set python version in reticulate
py_path <- "C:/Program Files/ArcGIS/Pro/bin/Python/envs/arcgispro-py3/python.exe"
reticulate::use_python(python = py_path, required = TRUE)
#call RPyGeo
library(RPyGeo) # for potential point export
#output gdb
out.gdb <- "C:/LOCAL_PROJECTS/Output/Output.gdb"
#RPyGeo Parameters
# Note that, in order to use RPyGeo you need a working ArcMap or ArcGIS Pro installation on your computer.
# python path - note that this will change depending on which version of Arc one is using
# py_path <- "C:/Program Files/ArcGIS/Pro/bin/Python/envs/arcgispro-py3/python.exe"
arcpy <- rpygeo_build_env(workspace = out.gdb,
overwrite = TRUE,
extensions = c("Spatial","DataInteroperability"),
path = py_path)
I've tried a bunch of different tools to export an sf object, here using dummy data also used in the RPyGeo vignette
data(nz, package = "spData")
arcpy$Copy_management(in_data = nz,out_data = "nz_test")
arcpy$Copy_management(in_data = nz,out_data = file.path(out.gdb,"nz"))
arcpy$FeatureClassToGeodatabase_conversion(Input_Features = nz,Output_Geodatabase = out.gdb)
arcpy$FeatureClassToFeatureClass_conversion(in_features = nz,out_path = out.gdb,out_name = "nz")
arcpy$QuickExport_interop(Input = nz,Output = file.path(out.gdb,"nz"))
arcpy$CopyFeatures_management(in_features = nz,out_feature_class = file.path(out.gdb,"nz"))
arcpy$CopyFeatures_management(in_features = nz,out_feature_class = "nz")
Each time I get an error, for example:
Error in py_call_impl(callable, dots$args, dots$keywords) :
RuntimeError: Object: Error in executing tool
Detailed traceback:
File "C:\Program Files\ArcGIS\Pro\Resources\ArcPy\arcpy\management.py", line 3232, in CopyFeatures
raise e
File "C:\Program Files\ArcGIS\Pro\Resources\ArcPy\arcpy\management.py", line 3229, in CopyFeatures
retval = convertArcObjectToPythonObject(gp.CopyFeatures_management(*gp_fixargs((in_features, out_feature_class, config_keyword, spatial_grid_1, spatial_grid_2, spatial_grid_3), True)))
File "C:\Program Files\ArcGIS\Pro\Resources\ArcPy\arcpy\geoprocessing\_base.py", line 511, in <lambda>
return lambda *args: val(*gp_fixargs(args, True))
I'm not an expert in ArcPy by any means. Nor am I an expert in tracing errors inside packages. Am I making a simple syntax mistake? Is there something else that I'm missing? Any help would be much appreciated!
Is there any package for calling a python function from R by passing the function arguments through R? Now i have directly called the python file using system in R.
a<-system('/home/anaconda3/bin/python /home/Desktop/myfile.py' ,intern = TRUE)
But this myfile.py file is having a function with paramenter. How to specify the parameter in R?
I have tried system('/home/anaconda3/bin/python /home/Desktop/myfile.py argument',wait=FALSE,intern = TRUE) .But it returns 0.
for example I want to pass the number of core that my python script can use:
system(paste('/home/anaconda3/bin/python','home/Desktop/myfile.py',NCORE))
Then in Python Script before launch the function I can read my parameter in this way:
n_core = int(sys.argv[1])
sys.argv is a list in Python, which contains the command-line arguments passed to the script.
please look at reticulate
library(reticulate)
os <- import("os")
os$listdir(".")
I search for a command to compute Walsh-Hadamard Transform of an image in R, but I don't find anything. In MATLAB fwht use for this. this command implement Walsh-Hadamard Tranform to each row of matrix. Can anyone introduce a similar way to compute Walsh-Hadamard on rows or columns of Matrix in R?
I find a package here:
http://www2.uaem.mx/r-mirror/web/packages/boolfun/boolfun.pdf
But why this package is not available when I want to install it?
Packages that are not maintained get put in the Archive. They get put there when that aren't updated to match changing requirements or start making errors with changing R code base. https://cran.r-project.org/web/packages/boolfun/index.html
It's possible that you might be able to extract useful code from the archive version, despite the relatively ancient version of R that package was written under.
The R code for walshTransform calls an object code routine:
walshTransform <- function ( truthTable ) # /!\ should check truthTable values are in {0,1}
{
len <- log(length(truthTable),base=2)
if( len != round(len) )
stop("bad truth table length")
res <- .Call( "walshTransform",
as.integer(truthTable),
as.integer(len))
res
}
Installing the package succeeded on my Mac, but would require the appropriate toolchain on whatever OS you are working in.
I am calling R script from within Matlab. The R script is a function that should load the data generated from Matlab and then passes it through the R function, and finally computes a result and sends it back to Matlab. I have included a very simplified code below. The Matlab and R file are in the same path. The R_script.R is the following:
require("mclust")
group = function(data, num_cls){
Mclustmodel = Mclust(data, num_cls)
return(Mclustmodel$class)
}
In Matlab, the code is:
system( 'Rscript ./R_script.R' )
X = rand(10);
K = 3;
class = group(X, K);
My question is: Can I load X and K into the R function group, and directly calculate the answer?
I am using a Linux system.
Thanks.
You could try RMatlab. See this blog post for instructions. RMatlab is biderctional so you can run it from Matlab, send commands to R and get results as Matlab variables. It works on unix systems.