R/subset_data.R

In respR: Import, Process, Analyse, and Calculate Rates from Respirometry Data

#' Subset a `data.frame`, `inspect`, or `inspect.ft` object
#'
#' `subset_data` subsets a `data.frame`, `inspect`, or `inspect.ft` object based
#' on a given set of criteria. The function is ideal for passing only selected
#' regions of data to other functions such as [`calc_rate()`] and
#' [`auto_rate()`], either by saving the output as a new object or via the use
#' of pipes (`%>%` or `%>%`). It is also very useful in analysis of
#' intermittent-flow data, where in a loop each replicate can be extracted and
#' passed to an analytical function such as `calc_rate` or `auto_rate`. See
#' examples and vignettes.
#'
#' The function can subset data based on ranges of `"time"`, `"oxygen"`, or
#' `"row"`. For data frames, to subset by `"time"` or `"oxygen"` the time data
#' is assumed to be in the first column, and oxygen data in the second column.
#' For [`inspect()`] and [`inspect.ft()`] objects, the data will have been
#' coerced to this structure already. In these cases the `$dataframe` element in
#' the output is replaced by the subset, and in `inspect.ft` the `$data` element
#' is also subset and replaced. Note for `inspect.ft` objects, the oxygen data
#' in column 2 will be either `out.oxy` data or `delta.oxy` data depending on
#' what was inspected. The function can subset *any* data frame by `row`.
#'
#' When multiple columns are present, for example time in column 1, and multiple
#' columns of oxygen data, the subset object will include *all* columns. In the
#' case of subsetting `by = "oxygen"`, subsetting is based on the *first* column
#' of oxygen data only (i.e. column 2), and all subsequent columns are subset
#' between the same rows regardless of oxygen values.
#'
#' For all methods, if exact matching values of `from` and `to` are not present
#' in the data, the closest values are used. For `"time"` and `"row"`
#' subsetting, `from` and `to` should be in the correct order. No warning or
#' messages are given if the input values are outside those in the data frame.
#' For instance, if `to = 100` and there are only 50 rows in the data, the last
#' row (50) will be used instead. The same for `from` and `to` time values
#' outside those in the data frame.
#'
#' For `"oxygen"` subsetting, `from` and `to` are generally interchangeable, and
#' the function will subset data *between* the first and last occurrences (or
#' closest occurrences) of these values. It works best with generally increasing
#' or decreasing oxygen data, and results may vary with other data such as
#' intermittent flow data or those in `inspect.ft` objects.
#'
#' **Note for `inspect` and `inspect.ft` object inputs:** after subsetting the
#' locations of any data issues highlighted when the object was originally
#' inspected will no longer be accurate. If these are important, best practice
#' is to subset the original dataframe, and then process the subset through
#' `inspect` or `inspect.ft`.
#'
#' A summary of the subset can be printed to the console if the default `quiet =
#' FALSE` is changed to `TRUE`.
#'
#' ## More
#'
#' For additional help, documentation, vignettes, and more visit the `respR`
#' website at <https://januarharianto.github.io/respR/>
#'
#' @return **Output**: If the input is an `inspect`, or `inspect.ft` object, the
#'   output is an object of the same class containing the subset data. For
#'   `data.frame` inputs the output is a `data.table` of the subset.
#'
#' @param x `data.frame`, `inspect`, or `inspect.ft` object. The data from which
#'   to produce a subset.
#' @param from numeric. The lower bounds of the subset based on the `by` input.
#' @param to numeric. The upper bounds of the subset based on the `by` input.
#' @param by string. `"time"`, `"row"`, or `"oxygen"`. Method by which to apply
#'   the `from` and `to` inputs.
#' @param quiet logical. Controls if a summary of the output is printed to the
#'   console. Default is `TRUE`.
#'
#' @export
#'
#' @examples
#' \donttest{
#' # Subset by time:
#' x <- subset_data(squid.rd, from = 2000, to = 4000, by = "time")
#'
#' # Subset by oxygen:
#' subset_data(sardine.rd, from = 94, to = 91, by = "oxygen")
#'
#' # Subset by row:
#' subset_data(flowthrough.rd, from = 10, to = 750, by = "row")
#'
#' # Subset multiple columns:
#' # In this case subsetting is based on the first two columns
#' subset_data(flowthrough.rd, from = 50, to = 600, by = "time")
#'
#' # Pass (via piping) only a subset of a dataset to inspect() and auto_rate()
#' subset_data(sardine.rd, from = 94, to = 91, by = "oxygen") %>%
#'    inspect(time = 1, oxygen = 2) %>%
#'    auto_rate()
#'    }

subset_data <- function(x, from = NULL, to = NULL, by = "time", quiet = TRUE) {

  # Check if object is from respR function(s)
  if (any(class(x) %in% "inspect")) {
    dt <- data.table(x$dataframe)
    if (length(dt) > 2)
      message("subset_data: Multi-column dataset detected in input! \nsubset_data is intended to subset datasets containing single time and oxygen columns. \nSubsetting will proceed anyway using columns 1 and 2 as time and oxygen respectively. All other columns will be ignored.")
  } else if (any(class(x) %in% "inspect.ft")) {
    dt <- data.table(x$dataframe)
  } else {
    dt <- data.table(x)
    if (length(dt) > 2)
      message("subset_data: Multi-column dataset detected in input! \nsubset_data is generally intended to subset data already passed through inspect(), or 2-column data frames where time and oxygen are in columns 1 and 2 respectively. \nSubsetting will proceed anyway based on this assumption, but please ensure you understand what you are doing.")
  }

  ## verify by input
  by <- by_val(by, msg = "subset_data")

  ## replace NULL inputs
  if(is.null(from)){
    if(by == "time") from <- min(nainf.omit(dt[[1]]))
    if(by == "row") from <- 1
    if(by == "oxygen") from <- dt[[2]][1] # first oxygen value
  }
  if(is.null(to)){
    if(by == "time") to <- max(nainf.omit(dt[[1]]))
    if(by == "row") to <- nrow(dt)
    if(by == "oxygen") to <- dt[[2]][nrow(dt)] # last oxygen value
  }

  ## if time, 'from' required, single val, not bigger than max value in time
  if(by == "time") {
    input.val(from,  num = TRUE, int = FALSE, req = FALSE,
              max = 1, min = 1, range = c(0, max(nainf.omit(dt[[1]]))),
              msg = "subset_data: 'from' -")
    ## if time, 'to' required, single val, greater than from
    input.val(to,  num = TRUE, int = FALSE, req = FALSE,
              max = 1, min = 1, range = c(from, Inf),
              msg = "subset_data: 'to' -")
  }

  ## if row, 'from' required, single val, integer
  if(by == "row") {
    input.val(from,  num = TRUE, int = TRUE, req = FALSE,
              max = 1, min = 1, range = c(1, nrow(dt)),
              msg = "subset_data: 'from' -")
    ## if row, 'to' required, single val, integer, greater than from
    input.val(to,  num = TRUE, int = TRUE, req = FALSE,
              max = 1, min = 1, range = c(from+1, Inf),
              msg = "subset_data: 'to' -")}

  ## if oxygen, 'from' & 'to' required, single val, numeric
  if(by == "oxygen") {
    input.val(from,  num = TRUE, int = FALSE, req = FALSE,
              max = 1, min = 1, range = c(-Inf, Inf),
              msg = "subset_data: 'from' -")
    input.val(to,  num = TRUE, int = FALSE, req = FALSE,
              max = 1, min = 1, range = c(-Inf, Inf),
              msg = "subset_data: 'to' -")}

  # Perform subset
  out <- truncate_data(dt, from, to, by)

  # inspect.ft has an additional element that needs subset - $data
  if (any(class(x) %in% "inspect.ft")) {

    # get indices of start and end of subset
    # Must be a better way of doing this...

    # collapse list of lists to list of dfs
    dt2 <- sapply(x$data, function(z) rbind.data.frame(z))
    # collapse list of dfs to dt
    dt2 <- as.data.table(dt2)
    # for some stupid reason the names get changed
    names(dt2) <- names(x$dataframe)

    # start and end of rows which are identical
    start <- min(which(duplicated(rbind(dt2, out), fromLast = TRUE)))
    end <- max(which(duplicated(rbind(dt2, out), fromLast = TRUE)))

    # if out was empty, start and end are now Inf & -Inf, which produces errors
    if(start == Inf || start == -Inf) start <- 0
    if(end == Inf || end == -Inf) end <- 0

    # subset x$data elements
    data_sub <- lapply(x$data, function(y) {
      lapply(y, function(z){
        z[start:end]
      })
    })

    x$data <- data_sub
  }

  if(!quiet) {
    cat("\n# subset_data # -------------------------\n")
    cat("Original data:\n")
    print(dt, topn = 2)
    cat("\nSubset data:\n")
    print(data.table(out), topn = 2)
    cat("-----------------------------------------\n")
  }

  # if out is empty, warn.
  # Still return in case this would break loops or whatever
  if(nrow(out) == 0)
    warning("subset_data: subsetting criteria result in empty dataset!")

  if (any(class(x) %in% "inspect")) {
    x$dataframe <- out
    return(invisible(x))
  } else if (any(class(x) %in% "inspect.ft")) {
    x$dataframe <- out
    return(invisible(x))
  } else return(invisible(out))
}