Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

set.mcOption

Options for parallel support


Description

Provides support for the use of parallel computation in the parallel package.

Usage

set.mcOption(value)
get.mcOption()
set.coresOption(value)
get.coresOption()
set.ClusterOption(cl)
get.ClusterOption()

Arguments

value

valid replacement value

cl

a cluster object created by makeCluster in parallel

Details

Options in the spatialreg package are held in an environment local to the package namespace and not exported. Option values are set and retrieved with pairs of access functions, get and set. The mc option is set by default to FALSE on Windows systems, as they cannot fork the R session; by default it is TRUE on other systems, but may be set FALSE. If mc is FALSE, the Cluster option is used: if mc is FALSE and the Cluster option is NULL no parallel computing is done, or the Cluster option is passed a “cluster” object created by the parallel or snow package for access without being passed as an argument. The cores option is set to NULL by default, and can be used to store the number of cores to use as an integer. If cores is NULL, facilities from the parallel package will not be used.

Value

The option access functions return their current settings, the assignment functions usually return the previous value of the option.

Note

An extended example is shown in the documentation of mom_calc, including treatment of seeding of RNG for multicore/cluster.

Author(s)

Roger Bivand Roger.Bivand@nhh.no

Examples

ls(envir=spatialreg:::.spatialregOptions)
library(parallel)
nc <- detectCores(logical=FALSE)
nc
# set nc to 1L here
if (nc > 1L) nc <- 1L
#nc <- ifelse(nc > 2L, 2L, nc)
coresOpt <- get.coresOption()
coresOpt
if (!is.na(nc)) {
 invisible(set.coresOption(nc))
 print(exists("mom_calc"))
 if(.Platform$OS.type == "windows") {
# forking not permitted on Windows - start cluster
# removed for Github actions 210502
## Not run: 
  print(get.mcOption())
  cl <- makeCluster(get.coresOption())
  print(clusterEvalQ(cl, exists("mom_calc")))
  set.ClusterOption(cl)
  clusterEvalQ(get.ClusterOption(), library(spatialreg))
  print(clusterEvalQ(cl, exists("mom_calc")))
  clusterEvalQ(get.ClusterOption(), detach(package:spatialreg))
  set.ClusterOption(NULL)
  print(clusterEvalQ(cl, exists("mom_calc")))
  stopCluster(cl)

## End(Not run)
 } else {
  mcOpt <- get.mcOption()
  print(mcOpt)
  print(mclapply(1:get.coresOption(), function(i) exists("mom_calc"),
   mc.cores=get.coresOption()))
  invisible(set.mcOption(FALSE))
  cl <- makeCluster(nc)
  print(clusterEvalQ(cl, exists("mom_calc")))
  set.ClusterOption(cl)
  clusterEvalQ(get.ClusterOption(), library(spatialreg))
  print(clusterEvalQ(cl, exists("mom_calc")))
  clusterEvalQ(get.ClusterOption(), detach(package:spatialreg))
  set.ClusterOption(NULL)
  print(clusterEvalQ(cl, exists("mom_calc")))
  stopCluster(cl)
  invisible(set.mcOption(mcOpt))
 }
 invisible(set.coresOption(coresOpt))
}

spatialreg

Spatial Regression Analysis

v1.1-8
GPL-2
Authors
Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Gianfranco Piras [aut], Luc Anselin [ctb], Andrew Bernat [ctb], Eric Blankmeyer [ctb], Yongwan Chun [ctb], Virgilio Gómez-Rubio [ctb], Daniel Griffith [ctb], Martin Gubri [ctb], Rein Halbersma [ctb], James LeSage [ctb], Angela Li [ctb], Jielai Ma [ctb], Abhirup Mallik [ctb, trl], Giovanni Millo [ctb], Kelley Pace [ctb], Pedro Peres-Neto [ctb], Tobias Rüttenauer [ctb], Mauricio Sarrias [ctb], JuanTomas Sayago [ctb], Michael Tiefelsdorf [ctb]
Initial release
2021-05-03

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.