#' Category vector

#'

#' Convert an object containing binary (`integer`) fields (columns) into a

#' `1`.

#'

#' @param x `matrix`, `data.frame`, [`Spatial-class`],

#'   value of zero. Also, note that in the argument to `x`, each row must

#'   contain only a single value equal to `1`.

#'

#'

#' @seealso [base::max.col()]

#'

#' @param budget `numeric` value specifying the maximum expenditure of

#'   the prioritization. For problems with multiple zones, the argument

#'   to `budget` can be a single `numeric` value to specify a budget

#'   a budget for each each management zone.

#'

#' @details

#'

#' \describe{

#'

#'   planning units should be locked for the solution. This argument is only

#'   compatible with problems that contain a single zone.}

#'

#'   `FALSE` values that indicate which planning units should be locked

#'   in the solution. This argument is only compatible with problems that

#'   contain a single zone.}

#'   zone. Thus each row should only contain at most a single `TRUE`

#'   value.}

#'

#'   that indicate if planning units should be locked for the solution.

#'   This format is only

#'   compatible if the planning units in the argument to `x` are a

#'

#' \describe{

#'

#'   contain penalty values for planning units. This format is only

#'   compatible if the planning units in the argument to `x` are a

#'   [`Spatial-class`], [sf::sf()], or

#'   contain multiple zones, the argument to `data` must

#'   contain a field name for each zone.}

#'

#'   planning units. These values must not contain any missing

#'   (`NA`) values. Note that this format is only available

#'   for planning units that contain a single zone.}

#'

#' \describe{

#'

#'   Note that this format cannot be used to specify weights for problems with

#'   multiple zones.}

#'

#'   Note that all layers for a given zone must have `NA` values in exactly the

#'   same cells.}

#' \item{planning unit data are a [`Spatial-class`] or `data.frame`

#'   be supplied to specify the expected amount of each feature under each

#'   zone. Note that these columns must not contain any `NA` values.}

#' \item{planning unit data are a [`Spatial-class`], `data.frame`, or

#' fulfill as many targets as possible while ensuring that the cost of the

#' solution does not exceed a budget.

#'

#'

#' @details

#' The maximum feature representation objective is an enhanced version of the

#' @param n `integer` number of threads.

#'

#' @details This function returns a `list` containing an element for

#'   specifying the indices that the worker should process.

#'

#' @return `list` object.

#' @details

#' This function adds general purpose constraints that can be used to

#' ensure that solutions meet certain criteria

#' For example, these constraints can be used to add multiple budgets.

#' They can also be used to ensure that the total number of planning units

#' allocated to a certain administrative area (e.g. country) does not exceed

#' they can also be used to ensure that features have a minimal level

#' function that aims to enhance feature representation given a budget

#' (e.g. [add_min_shortfall_objective()]).

#'

#' planning units \eqn{i \in I}{i in I} for zones \eqn{z \in Z}{z in Z}

#' (argument to `data`, if supplied as a `matrix` object),

#' \eqn{\theta} denote the constraint sense

#'

#' \deqn{

#' }{

#' sum_i^I sum (Diz * Xiz) \theta t

#' }

#' This function was inspired by Faith (1992) and Rodrigues *et al.*

#' (2002).

#'

#'

#' @param tree [phylo()] object specifying a phylogenetic tree

#'   for the conservation features.

#'

#' @param budget `numeric` value specifying the maximum expenditure of

#'   the prioritization. For problems with multiple zones, the argument

#'

#' @details

#' The maximum utility objective seeks to maximize the overall level of

#' history as possible. This function was inspired by Faith (1992),

#' Rodrigues *et al.* (2002), and Rosauer *et al.* (2009).

#'

#'

#' @details

#' The maximum phylogenetic endemism objective finds the set of

#' The object returned from this function depends on the argument to

#' `a`. If the argument to `a` is an

#' [`OptimizationProblem-class`] object, then the

#' of each planning unit in each zone. However, in most cases, the argument

#' to `a` will be a [`ConservationProblem-class`] object, and so

#' the type of object returned depends on the number of solutions

#'

#' \describe{

#'

#'   feature.

#'   Additionally, for convenience, this format can be a single

#'   value to assign the same target to each feature. Note that this format

#'   `x`, and each cell contains the target value for a given feature

#'   that the solution needs to secure in a given zone.}

#'

#'   (columns) in the feature data associated with the argument to `x` that

#'   contain targets. This format can only be used when the

#'   feature data associated with `x` is a `data.frame`.

#'

#' @param name `character` name of parameter.

#'

#'

#'

#'   value for each element in `value`. Defaults to the

#'   smallest possible number on the system.

#'

#'   value for each element in `value`. Defaults to the

#'   largest  possible number on the system.

#'