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#' @description
#' \subsection{The acmap data object}{
#' The fundamental unit of the Racmacs package is the [acmap]
#' object, short for Antigenic Cartography MAP. This object contains all the
#' information about an antigenic map. You can read in a new acmap object from a
#' file with the function [read.acmap] and create a new acmap object within an
#' R session using the [acmap] function.
#'
#' Key information associated with each acmap object is summarized in the
#' sections below.
#' }
#'
#' \subsection{The titer table}{
#' Each [acmap] object is built upon a table of data of measurements the
#' reactivity of a set of different sera against a set of different antigens.
#' Typically these measurements are HI assay measurements, but it is also
#' possible to use other similar assays as input data.
#'
#' For the table of data it is always assumed that sera form the _columns_ and
#' antigens form the _rows_, as below. You can get and set titer data with
#' [titerTable].
#' }
#'
#' \subsection{Optimizations}{
#' Another key component of the [acmap] object is a list of optimizations.
#' While acmap objects only have one table of data, they can have many
#' optimizations or none at all.
#'
#' Each optimization has the following main attributes (see the vignette on
#' optimizing antigenic maps for more details on minimum column bases and
#' stress):
#'
#' - __Antigen coordinates__, the coordinates of each antigen in this
#' optimization.
#' - __Sera coordinates__, the coordinates of each serum in this optimization.
#' - __Minimum column basis__, the minimum column basis assumed when calculating
#' this optimization.
#' - __Stress__, the stress of this optimization.
#' - __Dimensions__, the number of dimensions of this optimization.
#' }
#'
#' \subsection{Plotting styles}{
#' The final type of information that is contained in the acmap object is
#' information on point styles when plotting. By altering these attributes you
#' can change the appearance of the antigen and serum points in any maps
#' plotted, the main ones include:
#'
#' - Size
#' - Shape
#' - Fill color
#' - Outline color
#'
#' }
#'
#' @keywords internal
#' @useDynLib Racmacs
#' @importFrom Rcpp `sourceCpp`
#' @importFrom ggplot2 `ggplot`
#' @importFrom ggplot2 `.data`
#' @importFrom grid `drawDetails`
#' @importFrom grid `preDrawDetails`
#' @importFrom grid `postDrawDetails`
#' @importFrom magrittr `%>%`
#' @importFrom rlang `.data`
"_PACKAGE"
.onLoad <- function(...) {
vctrs::s3_register("grid::drawDetails", "acpoint")
vctrs::s3_register("grid::preDrawDetails", "acpoint")
vctrs::s3_register("grid::postDrawDetails", "acpoint")
vctrs::s3_register("ggplot2::ggplot", "acmap")
}
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