R/import_file.R

In jaspwn/LucifR:

import_file <- function() {

  requireNamespace("data.table", quietly = TRUE)

  # GLOBALS
  cn <- c("readtime", "plategroup", "well", "position", "counttime", "CPS")

  # generate a list of files
  first_file <- file.choose()
  file_dir <- dirname(first_file)
  data_files <- list.files(file_dir, full.names = TRUE)
  names(data_files) <- basename(data_files)

  # read the data
  data_list <- lapply(data_files,
                      fread,
                      skip = 1,
                      header = TRUE,
                      col.names = cn,
                      strip.white = TRUE,
                      blank.lines.skip = TRUE)

  # make a data table
  raw_data <- rbindlist(data_list, idcol = "fileListID")

  # generate the metadata
  metadata_list <- lapply(data_files,
                          fread,
                          nrows = 1)
  metadata <- rbindlist(metadata_list,
                        idcol = "fileListID",
                        fill = TRUE)
  # mung the metadata
  metadata[, time := as.POSIXct(
    paste(V6, V7),
    format = "%d/%m/%Y %H:%M:%S")]

  metadata[, temp := as.numeric(gsub("^[^[:digit:]]+(.*)C$", "\\1", V9))]

  # merge the metadata
  tidy_data <- merge(raw_data,
                     metadata[, c("fileListID", "time", "temp")],
                     by = "fileListID")

  #Label plates according to experimental groups
  tidy_data[, fileID := as.numeric(gsub(".*\\.", "", fileListID))]
  tidy_data[(fileID - 1) %% 5 == 0, group := "plate01"]
  tidy_data[(fileID - 2) %% 5 == 0, group := "plate02"]
  tidy_data[(fileID - 3) %% 5 == 0, group := "plate03"]
  tidy_data[(fileID - 4) %% 5 == 0, group := "plate04"]
  tidy_data[(fileID) %% 5 == 0, group := "plate05"]

  setkey(tidy_data, group, time)

  returndata <<- tidy_data

}