acdc_simplify.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/acdc_simplify.R
\name{acdc_simplify}
\alias{acdc_simplify}
\title{Simplify the outputs of the AC/DC algorithms}
\usage{
acdc_simplify(
  archive,
  type = c("acs", "dc"),
  mask = NULL,
  normalise = TRUE,
  keep_chunks = FALSE
)
}
\arguments{
\item{archive}{An \code{\link[flapper]{acdc_archive-class}} object returned by \code{\link[flapper]{ac}}, \code{\link[flapper]{dc}} or \code{\link[flapper]{acdc}}.}

\item{type}{A character that defines whether the function should be implemented for the outputs of a call to an AC* algorithm (\code{\link[flapper]{ac}} or \code{\link[flapper]{acdc}}), in which case \code{type = "acs"}, or the DC algorithm (\code{\link[flapper]{dc}}), in which case \code{type = "dc"}.}

\item{mask}{(optional) A spatial mask (e.g., the argument passed to \code{bathy} in \code{\link[flapper]{ac}}, \code{\link[flapper]{dc}} or \code{\link[flapper]{acdc}}) to mask areas (e.g., land) from the overall map. If implemented, cells in masked areas are assigned NAs rather than a score of 0.}

\item{normalise}{A logical input that defines whether or not to normalise the overall map so that cell scores sum to one. If \code{normalise = FALSE}, the overall map represents the expected number of time steps spent in each grid cell; if \code{normalise = TRUE}, the overall map represents the expected proportion of time steps spent in each grid cell.}

\item{keep_chunks}{A logical variable that defines whether or not to retain all chunk-specific information.}
}
\value{
The function returns an object of class \code{\link[flapper]{acdc_record-class}}.
}
\description{
This function simplifies the output of \code{\link[flapper]{ac}}, \code{\link[flapper]{dc}} and \code{\link[flapper]{acdc}}, by processing information from the 'archive' elements of an \code{\link[flapper]{acdc_archive-class}} object that hold the results of calls to the workhorse routines. This is especially useful if the algorithm(s) have been applied chunk-wise, in which case the results for each chunk are returned in a list. The function aggregates information across chunks to generate a continuous time series of results and a map of the expected proportion of time steps spent in each grid cell.
}
\details{
If the \code{\link[flapper]{ac}}, \code{\link[flapper]{dc}} or \code{\link[flapper]{acdc}} function was implemented step-wise, this function simply extracts the necessary information and re-packages it into an \code{\link[flapper]{acdc_record-class}} object. For a chunk-wise implementation, the function (a) computes the map of where the individual could have spent more or less time by aggregating the chunk-specific maps) and (b) simplifies chunk-specific records into a single contiguous time series, with re-defined time stamps from the start to the end of the time series (for AC* algorithm(s)) to return an \code{\link[flapper]{acdc_record-class}} object.
}
\seealso{
The AC, DC and ACDC algorithms are implemented by \code{\link[flapper]{ac}}, \code{\link[flapper]{dc}} and \code{\link[flapper]{acdc}}. After simplification, \code{\link[flapper]{acdc_plot_trace}}, \code{\link[flapper]{acdc_plot_record}} and \code{\link[flapper]{acdc_animate_record}} can be implemented to visualise time-specific results.
}
\author{
Edward Lavender
}