R/popsCompute.R

In IFC: Tools for Imaging Flow Cytometry

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# This file is released under the GNU General Public License, Version 3, GPL-3 #
# Copyright (C) 2020 Yohann Demont                                             #
#                                                                              #
# It is part of IFC package, please cite:                                      #
# -IFC: An R Package for Imaging Flow Cytometry                                #
# -YEAR: 2020                                                                  #
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#                     Jean-Pierre Marolleau, Loïc Garçon,                      #
#                     INSERM, UPD, CHU Amiens                                  #
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#' @title IFC_pops Computation
#' @description
#' Function used to compute `IFC_pops` object\cr
#' It requires pops, regions and features.
#' @param pops list of populations that will be coerced by \code{\link{buildPopulation}}.
#' @param regions an object of class `IFC_regions`, list of regions.
#' @param features an object of class `IFC_features`, data.frame of features.
#' @param pnt_in_poly_algorithm algorithm used to determine if object belongs to a polygon region or not. Default is 1.\cr
#' Note that for the moment only 1(Trigonometry) is available.
#' @param pnt_in_poly_epsilon epsilon to determine if object belongs to a polygon region or not. It only applies when algorithm is 1. Default is 1e-12.
#' @param display_progress whether to display a progress bar. Default is TRUE.
#' @param title_progress character string, giving the title of the progress bar. Default is "".
#' @param ... other arguments to be passed.
#' @source For pnt_in_poly_algorithm, Trigonometry, is an adaptation of Jeremy VanDerWal's code \url{https://github.com/jjvanderwal/SDMTools}
#' @return an object of class `IFC_pops`.
#' @export
popsCompute <- function(pops, regions, features,
                        pnt_in_poly_algorithm = 1, pnt_in_poly_epsilon = 1e-12,
                        display_progress = TRUE, title_progress = "", ...) {
  dots = list(...)
  P = pops
  pops = sapply(pops, simplify = FALSE, USE.NAMES = TRUE, FUN=function(p) do.call(what=buildPopulation, args=p))
  for(i in seq_along(P)) {
    attributes(pops[[i]])[setdiff(names(attributes(pops[[i]])), "names")] <- NULL
    for(k in setdiff(names(attributes(P[[i]])),"names")) {
      attr(pops[[i]], k) <- attr(P[[i]], k)
    }
  }
  class(pops) = "IFC_pops"
  
  # compute pops
  pops = popsGetAffiliation(pops)
  pops = popsOrderNodes(pops)
  return(popsWithin(pops = pops, regions = regions, features = features, 
                    pnt_in_poly_algorithm = pnt_in_poly_algorithm, 
                    pnt_in_poly_epsilon = pnt_in_poly_epsilon, 
                    display_progress = display_progress, title_progress = title_progress, ...))
}