Nothing
## ----nomessages, echo = FALSE-------------------------------------------------
knitr::opts_chunk$set(
warning = FALSE,
message = FALSE,
fig.height = 5,
fig.width = 5
)
options(digits=4)
par(mar=c(3,3,1,1)+.1)
## ----include=FALSE------------------------------------------------------------
set.seed(1234)
## -----------------------------------------------------------------------------
obj1 <- 10
obj2 <- 20
## -----------------------------------------------------------------------------
myfun <- function(x) obj1 + obj2
myfun(1)
## ----eval = FALSE-------------------------------------------------------------
# library(parallel)
# cl <- makeCluster(2)
# res <- try(parSapply(cl=cl, 1:4, myfun))
# res
## ----echo=FALSE---------------------------------------------------------------
library(parallel)
cl <- makeCluster(2)
cat("Error in checkForRemoteErrors(val) :
2 nodes produced errors; first error: object 'obj1' not found")
## -----------------------------------------------------------------------------
clusterExport(cl=cl, c('obj1', 'obj2'))
parSapply(cl=cl, 1:4, myfun)
## ----echo=FALSE---------------------------------------------------------------
stopCluster(cl)
## -----------------------------------------------------------------------------
library(SimDesign)
#SimFunctions(comments = FALSE)
### Define design conditions and number of replications
Design <- createDesign(N = c(10, 20, 30))
replications <- 1000
# define custom functions and objects (or use source() to read these in from an external file)
SD <- 2
my_gen_fun <- function(n, sd) rnorm(n, sd = sd)
my_analyse_fun <- function(x) c(p = t.test(x)$p.value)
fixed_objects <- list(SD=SD)
#---------------------------------------------------------------------------
Generate <- function(condition, fixed_objects) {
Attach(condition) # make condition names available (e.g., N)
# further, can use with() to use 'SD' directly instead of 'fixed_objects$SD'
ret <- with(fixed_objects, my_gen_fun(N, sd=SD))
ret
}
Analyse <- function(condition, dat, fixed_objects) {
ret <- my_analyse_fun(dat)
ret
}
Summarise <- function(condition, results, fixed_objects) {
ret <- EDR(results, alpha = .05)
ret
}
#---------------------------------------------------------------------------
### Run the simulation
res <- runSimulation(Design, replications, verbose=FALSE, fixed_objects=fixed_objects,
generate=Generate, analyse=Analyse, summarise=Summarise, debug='none')
res
## ----eval=FALSE---------------------------------------------------------------
# res <- runSimulation(Design, replications, verbose=FALSE, fixed_objects=fixed_objects,
# generate=Generate, analyse=Analyse, summarise=Summarise, debug='none',
# parallel = TRUE)
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