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#' Save the results
#'
#'@param sEnv the environment that BSL functions operate in. Default is "simEnv" so use that to avoid specifying when calling functions
#'@param summarize If TRUE a matrix with breeding cycles in rows and replications in columns, with the first set of columns being cycle means and the second set of columns cycle variances. If FALSE a list as long as the number of replications, with each list element containing a list of all simulation objects.
#'@param saveDataFileName NULL or string of the file name to save the simulated data, like "result1_1". A path can be specified, like "simDirectory/result1_1" (in which case "simDirectory" must exist). Default: NULL.
#'
#'@return If saveDataFileName is NULL, data is return as an object, else data is saved as a ".rds" file. To examine the data, use the readRDS function.
#'
#'@export
outputResults <- function(sEnv=NULL, summarize=T, saveDataFileName=NULL){
if(is.null(sEnv)){
if(exists("simEnv", .GlobalEnv)){
sEnv <- get("simEnv", .GlobalEnv)
} else{
stop("No simulation environment was passed")
}
}
if(summarize){
getMean <- function(data){
tapply(data$gValue, data$genoRec$basePopID, mean)
}
getVar <- function(data){
tapply(data$gValue, data$genoRec$basePopID, stats::var)
}
muSim <- matrix(sapply(sEnv$sims, getMean), ncol=sEnv$nSim)
varSim <- matrix(sapply(sEnv$sims, getVar), ncol=sEnv$nSim)
BSLoutput <- cbind(muSim, varSim)
colnames(BSLoutput) <- c(paste("mu", 1:sEnv$nSim, sep=""), paste("var", 1:sEnv$nSim, sep=""))
}else{
BSLoutput <- sEnv$sims
}
if (is.null(saveDataFileName)) return(BSLoutput) else saveRDS(BSLoutput, file=paste(saveDataFileName, ".rds", sep=""))
}
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