Nothing
###############################################################################
# Emir: EmiR: Evolutionary minimization forR #
# Copyright (C) 2021 Davide Pagano & Lorenzo Sostero #
# #
# This program is free software: you can redistribute it and/or modify #
# it under the terms of the GNU General Public License as published by #
# the Free Software Foundation, either version 3 of the License, or #
# any later version. #
# #
# This program is distributed in the hope that it will be useful, but #
# WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY #
# or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License #
# for more details: <https://www.gnu.org/licenses/>. #
###############################################################################
#' Configuration object for the Cuckoo Search Algorithm
#'
#' Create a configuration object for the Cuckoo Search Algorithm (CS). At minimum the number of iterations
#' (parameter `iterations`) and the number of host nests (parameter `population_size`) have
#' to be provided.
#'
#' @param iterations maximum number of iterations.
#' @param population_size number of host nests.
#' @param iterations_same_cost maximum number of consecutive iterations with the \emph{same}
#' (see the parameter `absolute_tol`) best cost before ending the minimization. If `NULL` the
#' minimization continues for the number of iterations specified by the parameter `iterations`.
#' Default is `NULL`.
#' @param absolute_tol absolute tolerance when comparing best costs from consecutive iterations.
#' If `NULL` the machine epsilon is used. Default is `NULL`.
#' @param discovery_rate probability for the egg laid by a cuckoo to be discovered by the host bird. It
#' should be between 0 and 1. Default is `0.25`.
#' @param step_size step size of the Levy flight. Default is `1.0`.
#' @return `config_cs` returns an object of class `CSConfig`.
#' @importFrom Rdpack reprompt
#' @references \insertRef{Yang2009}{EmiR}
#' @export
#'
#' @examples
#' conf <- config_cs(iterations = 100, population_size = 50, iterations_same_cost = NULL,
#' absolute_tol = NULL, discovery_rate = 0.25, step_size = 1.0)
#'
#'
config_cs <- function(iterations,
population_size,
iterations_same_cost = NULL,
absolute_tol = NULL,
discovery_rate = 0.25,
step_size = 1.0) {
p <- new("CSConfig")
commonOpt <- checkCommonConfigOptions(iterations, population_size, iterations_same_cost, absolute_tol)
p@iterations <- commonOpt$iterations
p@population_size <- commonOpt$population_size
p@iterations_same_cost <- commonOpt$iterations_same_cost
p@absolute_tol <- commonOpt$absolute_tol
p@discovery_rate <- discovery_rate
p@step_size <- step_size
return(p)
}
check_algo_options_cs <- function(p, ...) {
config_options <- list(...)
if (length(config_options) == 0) return(p)
for (i in 1:length(config_options)) {
if (names(config_options[i]) == "discovery_rate") {
p@discovery_rate <- config_options[[i]]
} else if (names(config_options[i]) == "step_size") {
p@step_size <- config_options[[i]]
} else {
stop(paste0("Unknown option '", names(config_options[i]), "' for algorithm CS."))
}
}
return(p)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.