# R/select_population.R In UMN-BarleyOatSilphium/GSSimTPUpdate: Code and data to accompany the publication [TITLE]

#### Documented in select.population

```#' Apply selection on a population
#'
#' @param value.mat A matrix of values (phenotypic, genotypic, or breeding) on
#' which to apply selection.
#' @param sel.intensity Either the proportion to select (i.e. from 0 to 1) or
#' the number of individuals to select.
#' @param selection The method of selection. Can be \code{"best"} (default),
#' \code{"worst"}, \code{"random"}, or \code{"tails"}.
#' @param exlcusion A vector of line names to exclude when making selection.
#'
#' @details
#' The \code{"best"} method selects the top \code{sel.intensity} entries based on
#' the values in the \code{value.mat}, the \code{"worst"} method selects the
#' bottom entries, the \code{"random"} method select entries randomly, and the
#' \code{"tails"} method select the top \eqn{sel.intensity/2} entries
#' and the bottom \eqn{sel.intensity/2} entries.
#'
#' @import dplyr
#'
#' @export
#'
select.population <- function(value.mat, sel.intensity, selection = "best",
exclusion = NULL) {

# Exclude based on the provided exclusion vector
value.mat <- value.mat[!row.names(value.mat) %in% exclusion,] %>%
as.matrix()

# Number in the pheno.vec
N.tot <- nrow(value.mat)

# If the sel.intensity is between 0 and 1, find the total number to keep
if (all(sel.intensity > 0, sel.intensity < 1)) {
# Number to select
N.sel <- sel.intensity * N.tot
} else {
N.sel <- sel.intensity
}

if (selection == "best") {
# Sort the values
value.mat.ordered <- value.mat[order(value.mat, decreasing = T),] %>%
as.matrix()
value.sel <- value.mat.ordered[seq(N.sel),]
}

# If using the "worst" method, select the bottom N.sel
if (selection == "worst") {
# Sort the values
value.mat.ordered <- value.mat[order(value.mat, decreasing = F),] %>%
as.matrix()
value.sel <- value.mat.ordered[seq(N.sel),]
}

# If using "random", randomly select the lines
if (selection == "random") {
value.sel <- value.mat[sample(seq(N.tot), size = N.sel),]
}

# If using "tails", select the top and bottom
if (selection == "tails") {
# Top
value.mat.ordered <- value.mat[order(value.mat, decreasing = T),] %>%
as.matrix()
value.sel.top <- value.mat.ordered[seq(N.sel/2),]

value.mat.ordered <- value.mat[order(value.mat, decreasing = F),] %>%
as.matrix()
value.sel.bottom <- value.mat.ordered[seq(N.sel/2),]

value.sel <- c(value.sel.top, value.sel.bottom)

}

# Sort the selections based on name
value.sel <- value.sel[order(names(value.sel))]
# Retrieve the names
line.names <- names(value.sel)

# Create output list
output.list <- list(value.sel = as.matrix(value.sel), lines.sel = line.names)

# Return the selections
return(output.list)
} # Close the function
```
UMN-BarleyOatSilphium/GSSimTPUpdate documentation built on June 3, 2017, 6:42 a.m.