R/flux_flag_count.R

In fluxible: Ecosystem Gas Fluxes Calculations for Closed Loop Chamber Setup

#' Counts quality flags
#' @description Provides a table of how many fluxes were attributed
#' which quality flag. This function is incorporated in
#' \link[fluxible]{flux_quality} as a message, but can be used alone to extract
#' a dataframe with the flag count.
#' @param flags_df dataframe of flux slopes
#' @param f_flags list of flags used in the dataset
#' (if different from default from flux_quality).
#' If not provided, it will list only the flags that are
#' present in the dataset (no showing 0).
#' @param f_fluxid column containing fluxes unique ID
#' @param f_quality_flag column containing the quality flags
#' @return a dataframe with the number of fluxes for each quality flags
#' and their proportion to the total
#' @importFrom dplyr all_of select group_by summarise
#' tibble right_join filter distinct arrange desc
#' @importFrom tidyr replace_na
#' @author Vincent Belde
#' @examples
#' data(co2_conc)
#' slopes <- flux_fitting(co2_conc, conc, datetime, fit_type = "exp_zhao18")
#' slopes_flag <- flux_quality(slopes, conc)
#' flux_flag_count(slopes_flag)
#' @export


flux_flag_count <- function(flags_df,
                            f_fluxid = f_fluxid,
                            f_quality_flag = f_quality_flag,
                            f_flags = c(
                              "ok",
                              "discard",
                              "zero",
                              "force_discard",
                              "start_error",
                              "no_data",
                              "force_ok",
                              "force_zero",
                              "force_lm",
                              "no_slope"
                            )) {

  flag_df <- flags_df |>
    mutate(
      f_quality_flag = as.factor({{f_quality_flag}})
    ) |>
    select({{f_fluxid}}, {{f_quality_flag}}) |>
    distinct()

  flags <- tibble({{f_quality_flag}} := factor(f_flags))

  count_table <- flag_df |>
    summarise(
      n = length({{f_quality_flag}}),
      .by = {{f_quality_flag}}
    ) |>
    right_join(flags, by = join_by({{f_quality_flag}})) |>
    mutate(
      n = replace_na(.data$n, 0),
      ratio = .data$n / sum(.data$n)
    ) |>
    arrange(desc(.data$n))

  count_table
}