R/drafts.R

In BWAM/stayCALM: Stay Calm when Applying a Consolidated Assessment Listing Methodology (CALM)

less_than_greater_than <- function(x, direction_col, standard_col, value_col) {
  direction_col <- rlang::enquo(direction_col)
  standard_col <- rlang::enquo(standard_col)
  value_col <- rlang::enquo(value_col)

  direction.vec <- x %>%
    pull(!!direction_col) %>%
    unique()

  if (any(!direction.vec %in% c("less", "greater"))) stop("direction_col can only contain character strings 'less' or 'greater'")

  x %>%
    dplyr::mutate(impaired = dplyr::if_else(!!direction_col %in% "less",
                                            !!value_col < !!standard_col,
                                            !!value_col > !!standard_col)) %>%
    dplyr::pull(impaired)
}

daily_average_do <- function(x) {

  final.df <- do.df %>%
    filter(wqs.type %in% "average",
           wqs.time %in% "daily") %>%
    group_by(SEG_ID, date, clean_class, CHEMICAL_NAME, wqs.narrative,
             wqs.type,
             wqs.violation.direction, wqs.numeric, units) %>%
    summarize(daily_average = mean(RESULT_NUMERIC, na.rm = TRUE)) %>%
    ungroup() %>%
    mutate(impaired = less_than_greater_than(x = .,
                                             direction_col = wqs.violation.direction,
                                             standard_col = wqs.numeric,
                                             value_col = daily_average))
}

impairment_do <- function(x, value_col) {

  do.df <- x %>%
    filter(CHEMICAL_NAME %in% "Dissolved Oxygen")



  min_thresh.df <- do.df %>%
    filter(wqs.type %in% "threshold",
           wqs.time %in% "single") %>%
    select(SEG_ID, date, clean_class, CHEMICAL_NAME, wqs.narrative,
           wqs.type,
           wqs.violation.direction, wqs.numeric, units, RESULT_NUMERIC) %>%
    mutate(impaired = less_than_greater_than(x = .,
                                             direction_col = wqs.violation.direction,
                                             standard_col = wqs.numeric,
                                             value_col = RESULT_NUMERIC)) %>%
    select(-RESULT_NUMERIC)

  bound.df <- dplyr::bind_rows(daily_avg.df, min_thresh.df) %>%
    group_by(SEG_ID, date, clean_class, CHEMICAL_NAME, wqs.narrative,
             wqs.violation.direction, units) %>%
    summarize(impaired = any(impaired == TRUE))
}

mean_agg <- function(x, wqs_type, wqs_time) {


}