R/env_fingerprint_plot.R

In neonSoilFlux: Compute Soil Carbon Fluxes for the National Ecological Observatory Network Sites

#' @title Helper function to plot QF results for environmental measurements.
#'
#' @author
#' John Zobitz \email{zobitz@augsburg.edu}

#' @description
#' Given a flux measurement data frame, show when the environmental measurements produced a QF value
#' @param input_fluxes data frame of computed fluxes
#'
#' @return A ggplot graph where we have ordered factors showing the QA values a given environmental measurement
#' @export
#'
#' @examples
#' # Make a fingerprint plot for environmental variables:
#' env_fingerprint_plot(sjer_flux_2022_06)

# changelog and author contributions / copyrights
#   John Zobitz (2024-04-07)
#     original creation
#     2024-04-08: update to get namespaces correct
#     2024-05-07: colorscheme updates

env_fingerprint_plot <- function(input_fluxes) {

  .data = NULL  # Appease R CMD Check

  prep_env <- input_fluxes |>
    dplyr::select(-.data[["flux_compute"]], -.data[["diffusivity"]]) |>
    dplyr::mutate(
      week_day = lubridate::wday(.data[["startDateTime"]]),
      decimal_hour = lubridate::hour(.data[["startDateTime"]]) + lubridate::minute(.data[["startDateTime"]]) / 60,
      day = lubridate::floor_date(.data[["startDateTime"]], unit = "day"),
    ) |>
    tidyr::pivot_longer(cols = c("soilCO2concentrationMeanQF":"staPresMeanQF")) |>
    dplyr::mutate(name = stringr::str_extract(.data[["name"]],pattern=".+(?=MeanQF)"))

  prep_env |>
    dplyr::mutate(value = as.factor(.data[["value"]])) |>
    ggplot2::ggplot() +
    ggplot2::geom_tile(ggplot2::aes(x = .data[["decimal_hour"]], y = .data[["day"]], fill =.data[["value"]])) +
    ggplot2::facet_grid(horizontalPosition ~ name) +
    ggplot2::labs(fill = "QF Check:", x = "Hour of Day", y = "Date") +
    ggplot2::scale_y_datetime(breaks = "7 day") +
    ggplot2::theme(legend.position = "bottom")  +
    ggplot2::scale_fill_manual(
      values=c("#33CC00","#FFC333", "#FF3333"),
      labels = c("0"="Pass", "1"="Monthly Mean", "2"="Fail"),
      drop = FALSE
    )



}