R/icytracks.R

In burgerga/icytracks: Read Icy Tracks File

#' icytracks:  Read Icy Tracks XLS
#'
#' Reads the .xls files generated by the Icy 'Export Tracks to XLS' Track
#' Processor and convert it to a data.frame.
#'
#' @docType package
#' @name icytracks
#' @importFrom magrittr "%>%"
#' @importFrom dplyr filter_ select_ mutate_ bind_rows
NULL

utils::globalVariables(c(".", "%>%"))

#' Read an Icy tracks XLS
#'
#' Reads the .xls files generated by the Icy 'Export Tracks to XLS' Track
#' Processor and convert it to a data.frame.
#'
#' @param file The Icy XLS file with the tracks.
#'
#' @family icytracks functions
#'
#' @export
#'
#' @examples
#' \dontrun{
#' read.icy.track.xls('~/icytrack.xls')
#' }
read.icy.track.xls <- function(file) {
 xls_data <- readIcyXlsData(file)
 track_bounds <- getTrackBoundsFromXlsData(xls_data)
 getTrackDF(xls_data, track_bounds)
}

readIcyXlsData <- function(file) {
  # Read in data, remove first column (which contains the "track #")
  xls_data <- gdata::read.xls(file, header = F, stringsAsFactors=F) %>% select_(-1)
  # Give sensible names
  names(xls_data) <- c('track', 't', 'x', 'y', 'z' )
  xls_data
}

getTrackBoundsFromXlsData <- function(xls_data) {
  track_df <- xls_data %>%
    tibble::rownames_to_column() %>%
    filter_(~!is.na(track)) %>%
    select_(~track, begin = ~rowname)
  # Begin is 2 lines after track line, end is one line before next track line.
  # (blank lines are skipped while reading in xls_data)
  track_df <- track_df %>%
    mutate_(
       begin = ~as.numeric(begin),
       end = ~lead(begin) - 1,
       begin = ~begin + 2
       )
  # Fix last entry
  track_df[nrow(track_df),]$end <- nrow(xls_data)
  track_df
}

getTrackDF <- function(xls_data, track_bounds) {
  track_bound_l <- split(track_bounds, seq(nrow(track_bounds)))
  track_df_l <- invisible(lapply(track_bound_l, function(x) {
    # Get correct rows from xls_data
    t <- xls_data[x$begin:x$end,]
    # Put in the correct track
    t$track <- x$track
    t
  }))
  # Bind list together to get the DF, then convert to data matrix (make numeric),
  # then back to DF
  as.data.frame(data.matrix(bind_rows(track_df_l)))
}