R/read_fgeo.R

In forestgeo/fgeo.utils: Import and Manipulate 'ForestGEO' Data

read_fgeo <- function(col_types) {
  function(file, delim = NULL, na = c("", "NA", "NULL"), ...) {
    delim <- delim %||% guess_comma_or_tab(file, names(col_types))

    # The point of this function is to handle rather than warn/inform issues
    dfm <- suppressMessages(suppressWarnings(
      read_delim_(delim, file = file, col_types = col_types, na = na, ...)
    ))

    # If input has rownames, we end up with more columns than we need
    result <- dfm[names(col_types)]
    readr::type_convert(result, col_types = col_types)
  }
}

read_delim_ <- function(delim, file, col_types, na, ...) {
  dfm <- switch(delim,
    "," = readr::read_csv(
      file = file, col_types = readr::cols(.default = "c"), na = na, ...
    ),
    "\t" = readr::read_tsv(
      file = file, col_types = readr::cols(.default = "c"), na = na, ...
    ),
    abort("Unexpected `delim`.")
  )
}

#' Import _ViewFullTable_ or _ViewTaxonomy_ data from a .tsv or .csv file.
#'
#' [read_vft()] and [read_taxa()] help you to read _ViewFullTable_ and
#' _ViewTaxonomy_ data from text files delivered by the ForestGEO database.
#' These functions avoid common problems about column separators, missing
#' values, column names, and column types.
#'
#' @section Acknowledgments:
#' Thanks to Shameema Jafferjee Esufali for inspiring the feature that
#' automatically detects `delim` (issue 65).
#'
#' @param file A path to a file.
#' @inheritParams readr::read_delim
#' @param delim Single character used to separate fields within a record. The
#'   default (`delim = NULL`) is to guess between comma or tab (`","` or `"\t"`).
#' @param ... Other arguments passed to [readr::read_delim()].
#'
#' @seealso [readr::read_delim()], [type_vft()], [type_taxa()].
#'
#' @return A [tibble][tibble::tibble-package].
#'
#' @examples
#' assert_is_installed("fgeo.x")
#' library(fgeo.x)
#'
#' example_path()
#'
#' file_vft <- example_path("view/vft_4quad.csv")
#' read_vft(file_vft)
#'
#' file_taxa <- example_path("view/taxa.csv")
#' read_taxa(file_taxa)
#' @family functions to read text files delivered by ForestgGEO's database
#' @family functions to import a single file of ForestGEO data
#' @family functions to import ForestGEO data
#' @export
read_vft <- read_fgeo(col_types = type_vft())

#' @rdname read_vft
#' @export
read_taxa <- read_fgeo(col_types = type_taxa())



#' Help to read ForestGEO data safely, with consistent columns type.
#'
#' @description
#' A common cause of problems is feeding functions with data which columns are
#' not all of the expected type. The problem often begins when reading data from
#' a text file with functions such as [utils::read.csv()],
#' [utils::read.delim()], and friends -- which commonly guess wrongly the column
#' type that you more likely expect. These common offenders are strongly
#' discouraged; instead consider using `readr::read_csv()`, `readr::read_tsv()`,
#' and friends, which guess column types correctly much more often than their
#' analogs from the __utils__ package.
#'
#' @description
#' `type_vft()` and `type_taxa()` help you to read data more safely by
#' explicitly specifying what type to expect from each column of known datasets.
#' These functions output the specification of column types used internally by
#' [read_vft()] and [read_taxa()]:
#' * `type_vft():` Type specification for _ViewFullTable_.
#' * `type_taxa():` Type specification for _ViewFullTaxonomy_.
#'
#' @details
#' Types reference (for more details see [read_delim()]):
#' * c = character,
#' * i = integer,
#' * n = number,
#' * d = double,
#' * l = logical,
#' * D = date,
#' * T = date time,
#' * t = time,
#' * ? = guess,
#' * or _/- to skip the column.'.
#'
#' @seealso [readr::read_delim()].
#'
#' @return A list.
#'
#' @examples
#' assert_is_installed("fgeo.x")
#' library(fgeo.x)
#' library(readr)
#'
#' str(type_vft())
#'
#' read_csv(example_path("view/vft_4quad.csv"), col_types = type_vft())
#'
#' str(type_taxa())
#'
#' read_csv(example_path("view/taxa.csv"), col_types = type_taxa())
#' @family functions to operate on column types
#' @family functions to read text files delivered by ForestgGEO's database
#' @family functions to import/export ForestGEO data
#' @keywords internal
#' @export
type_vft <- function() {
  list(
    DBHID = "i",
    PlotName = "c",
    PlotID = "i",
    Family = "c",
    Genus = "c",
    SpeciesName = "c",
    Mnemonic = "c",
    Subspecies = "c",
    SpeciesID = "i",
    SubspeciesID = "c",
    QuadratName = "c",
    QuadratID = "i",
    PX = "d",
    PY = "d",
    QX = "d",
    QY = "d",
    TreeID = "i",
    Tag = "c",
    StemID = "i",
    StemNumber = "i",
    StemTag = "i",
    PrimaryStem = "c",
    CensusID = "i",
    PlotCensusNumber = "i",
    DBH = "d",
    HOM = "d",
    ExactDate = "D",
    Date = "i",
    ListOfTSM = "c",
    HighHOM = "i",
    LargeStem = "c",
    Status = "c"
  )
}

#' @rdname type_vft
#' @export
type_taxa <- function() {
  list(
    ViewID = "i",
    SpeciesID = "i",
    SubspeciesID = "c",
    Family = "c",
    Mnemonic = "c",
    Genus = "c",
    SpeciesName = "c",
    Rank = "c",
    Subspecies = "c",
    Authority = "c",
    IDLevel = "c",
    subspMnemonic = "c",
    subspAuthority = "c",
    FieldFamily = "c",
    Lifeform = "c",
    Description = "c",
    wsg = "d",
    wsglevel = "c",
    ListOfOldNames = "c",
    Specimens = "c",
    Reference = "c"
  )
}

guess_comma_or_tab <- function(file, nms) {
  comma <- suppressWarnings(suppressMessages(readr::read_csv(file, n_max = 0)))
  if (all(nms %in% names(comma))) {
    return(",")
  }

  "\t"
}