R/get_dups_between_groups.R

In battleVerse/scenarioMaker: Build scenarios for the battleVerse

#' @title Find duplicates between groups in a dataframe
#'
#' @description Identify identical rows in a dataframe belonging to different groups. Used by Nautilus's plot_compare_track_status
#'
#' @param df the dataframe you want to examine
#' @param idcol the column which identifies the group each row belongs to

#'
#' @return Return the vector of which entries are duplicated across groups
#'
#'
#' @export
#'


get_dups_between_groups <- function (df, idcol) {
    #this function taken from: http://www.cookbook-r.com/Manipulating_data/Comparing_data_frames/ on 8/25/2017
    # df: the data frame
    # idcol: the column which identifies the group each row belongs to

    # Get the data columns to use for finding matches
    datacols <- setdiff(names(df), idcol)

    # Sort by idcol, then datacols. Save order so we can undo the sorting later.
    sortorder <- do.call(order, df)
    df <- df[sortorder,]

    # Find duplicates within each id group (first copy not marked)
    dupWithin <- duplicated(df)

    # With duplicates within each group filtered out, find duplicates between groups.
    # Need to scan up and down with duplicated() because first copy is not marked.
    dupBetween = rep(NA, nrow(df))
    dupBetween[!dupWithin] <- duplicated(df[!dupWithin,datacols])
    dupBetween[!dupWithin] <- duplicated(df[!dupWithin,datacols], fromLast=TRUE) | dupBetween[!dupWithin]

    # ============= Replace NA's with previous non-NA value ==============
    # This is why we sorted earlier - it was necessary to do this part efficiently

    # Get indexes of non-NA's
    goodIdx <- !is.na(dupBetween)

    # These are the non-NA values from x only
    # Add a leading NA for later use when we index into this vector
    goodVals <- c(NA, dupBetween[goodIdx])

    # Fill the indices of the output vector with the indices pulled from
    # these offsets of goodVals. Add 1 to avoid indexing to zero.
    fillIdx <- cumsum(goodIdx)+1

    # The original vector, now with gaps filled
    dupBetween <- goodVals[fillIdx]

    # Undo the original sort
    dupBetween[sortorder] <- dupBetween

    # Return the vector of which entries are duplicated across groups
    return(dupBetween)
}