R/df.to.gbi.focal.R

In SebastianSosa/ant: Animal Network Toolkit Software

# Copyright (C) 2018  Sebastian Sosa, Ivan Puga-Gonzalez, Hu Feng He, Xiaohua Xie, Cédric Sueur
#
# This file is part of Animal Network Toolkit Software (ANTs).
#
# ANT 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 2 of the License, or
# (at your option) any later version.
#
# ANT 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.

#' @title Converts a data frame of individual associations into a group by individual matrix.
#' @description Converts a data frame of individual associations into a group by individual matrix.
#' @param df a data frame in which to include a control column.
#' @param scan a numeric or character vector representing one or more columns used as scan factors.
#' @param id a numeric or character vector indicating the column holding ids of individuals.
#' @return The same data frame input with an extra column named 'control', representing the control factors.
#' @details Control factors are used in permutation approaches to constrain their permutations.
#' @author Sebastian Sosa, Ivan Puga-Gonzalez.
#' @examples
#' df.to.gbi.focal(df=sim.focal.undirected,focal='focal', alters='alter',ctrl='nfocal')
#' @keywords internal
df.to.gbi.focal <- function(df, focal, alters, ctrl) {
  # Find columns ids  corresponding to individuals, corresponding focal and cotnrol factor(s)----------------------
  col.alters <- df.col.findId(df, alters)
  col.focal <- df.col.findId(df, focal)
  col.ctrl <- df.col.findId(df, ctrl)

  # Create new column with a collapse between focal and control factor(s)----------------------
  ctrl <- c(col.ctrl, col.focal)
  df <- df.ctrlFactor(df, control = ctrl)
  df$control <- as.factor(df$control)

  # Find all unique individuals----------------------
  Vecids <- unique(c(as.character(df[, col.focal]), as.character(df[, col.alters])))

  # Find all uniquecontrols----------------------
  group_scan <- unique(df$control)

  # Convert data frames to a matrix of Group By Individuals (GBI)----------------------
  GBI <- df_to_gbi(df, col.ctrl, col.alters, Vecids, group_scan)
  GBI
}