#' Parameter with uniform distribution over integer range
#' for hyperparameter optimization
#' @export
#' @param name Name of the parameter, must match the input to `eval_func`.
#' @param lower Lower bound of the parameter
#' @param upper Upper bound of the parameter
#' @examples
#' p1 <- par_integer('x1', 3, 8)
#' class(p1)
#' print(p1)
#' table(p1$generate(runif(1000)))
par_integer <- function(name, lower, upper) {
R6_par_integer$new(
name=name,
lower=lower,
upper=upper
)
}
#' Parameter with uniform distribution over integer range
#' for hyperparameter optimization
#' @export
#' @field name Name of the parameter, must match the input to `eval_func`.
#' @field lower Lower bound of the parameter
#' @field upper Upper bound of the parameter
# @field fromraw Function to convert from raw scale to transformed scale
# @field toraw Function to convert from transformed scale to raw scale
#' @field ggtrans Transformation for ggplot, see ggplot2::scale_x_continuous()
#' @importFrom R6 R6Class
#' @examples
#' p1 <- R6_par_integer$new('x1', 0, 2)
#' class(p1)
#' print(p1)
R6_par_integer <- R6::R6Class(
# R6_par_integer ----
classname="par_integer",
inherit = R6_par_hype,
public=list(
name=NULL,
lower=NULL,
upper=NULL,
#' @description Function to convert from raw scale to transformed scale
#' @param x Value of raw scale
fromraw=function(x) {x}, #identity,
#' @description Function to convert from transformed scale to raw scale
#' @param x Value of transformed scale
toraw= function(x) {x}, #identity,
#' @description Generate values in the raw space based on quantiles.
#' @param q In [0,1].
generate = function(q) {
stopifnot(is.numeric(q), q>=0, q<=1)
# Use the 1e-16 to avoid 1 mapping above upper
self$lower + floor(q*(1-1e-16) * (self$upper + 1 - self$lower))
},
#' @description Get a sequence, uniform on the transformed scale
#' @param n Number of points. Ignored for discrete.
getseq = function(n) {
s <- unique(self$generate(seq(0,1,l=n)))
list(
trans=self$fromraw(s),
raw=s
)
},
#' @description Check if input is valid for parameter
#' @param x Parameter value
isvalid = function(x) {
is.numeric(x) &
(abs(x - round(x)) < 1e-8) &
(x >= self$lower) &
(x <= self$upper)
},
#' @description Convert this to a parameter for the
#' mixopt R package.
#' @param raw_scale Should it be on the raw scale?
convert_to_mopar = function(raw_scale=FALSE) {
mixopt::mopar_ordered(values=self$lower:self$upper)
},
ggtrans="identity", # ggplot trans to give to scale_x_continuous
#' @description Create a hyperparameter with uniform distribution
#' @param name Name of the parameter, must match the input to `eval_func`.
#' @param lower Lower bound of the parameter
#' @param upper Upper bound of the parameter
initialize = function(name, lower, upper) {
self$name <- name
stopifnot(is.numeric(lower), length(lower) == 1)
stopifnot(is.numeric(upper), length(upper) == 1)
lowerint <- as.integer(lower)
upperint <- as.integer(upper)
stopifnot(abs(lower - lowerint) < 1e-8)
stopifnot(abs(upper - upperint) < 1e-8)
stopifnot(lower < upper)
self$lower <- lowerint
self$upper <- upperint
},
#' @description Print details of the object.
#' @param ... not used,
print = function(...) {
s <- paste0("hype par_integer(name = ", self$name,
", lower = ", self$lower,
", upper = ", self$upper, ")")
cat(s)
invisible(self)
}
)
)
if (F) {
p1 <- par_integer('x1', 4, 9)
print(p1)
class(p1)
p1$generate(runif(22))
table(p1$generate(runif(6e5)))
}
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