R/polar_percentileMap.R

In openairmaps: Create Maps of Air Pollution Data

#' Percentile roses on interactive leaflet maps
#'
#' [percentileMap()] creates a `leaflet` map using percentile roses as markers.
#' Any number of pollutants can be specified using the `pollutant` argument, and
#' multiple layers of markers can be added and toggled between using `control`.
#'
#' @family interactive directional analysis maps
#'
#' @inheritParams polarMap
#' @param percentile The percentile value(s) to plot. Must be between 0–100. If
#'   `percentile = NA` then only a mean line will be shown.
#' @param intervals One of:
#' - `"fixed"` (the default) which ensures all of the markers use the same radial axis scale.
#' - `"free"` which allows all of the markers to use different radial axis scales.
#' - A numeric vector defining a sequence of numbers to use as the intervals, e.g., `intervals = c(0, 10, 30, 50)`.
#' @param draw.legend Should a shared legend be created at the side of the map?
#'   Default is `TRUE`.
#' @inheritDotParams openair::percentileRose -mydata -pollutant -percentile
#'   -type -cols -key -plot -intervals
#' @return A leaflet object.
#' @export
#'
#' @seealso the original [openair::percentileRose()]
#' @seealso [percentileMapStatic()] for the static `ggmap` equivalent of
#'   [percentileMap()]
#'
#' @examples
#' \dontrun{
#' percentileMap(polar_data,
#'   pollutant = "nox",
#'   provider = "Stamen.Toner"
#' )
#' }
percentileMap <- function(data,
                          pollutant = NULL,
                          percentile = c(25, 50, 75, 90, 95),
                          intervals = "fixed",
                          latitude = NULL,
                          longitude = NULL,
                          control = NULL,
                          popup = NULL,
                          label = NULL,
                          provider = "OpenStreetMap",
                          cols = "turbo",
                          alpha = 1,
                          key = FALSE,
                          draw.legend = TRUE,
                          collapse.control = FALSE,
                          d.icon = 200,
                          d.fig = 3.5,
                          type = deprecated(),
                          ...) {
  if (lifecycle::is_present(type)) {
    lifecycle::deprecate_soft(
      when = "0.5.0",
      what = "openairmaps::percentileMap(type)",
      details = c(
        "Different sites are now automatically detected based on latitude and longitude",
        "Please use the `popup` argument to create popups."
      )
    )
  }

  # assume lat/lon
  latlon <- assume_latlon(data = data,
                          latitude = latitude,
                          longitude = longitude)
  latitude <- latlon$latitude
  longitude <- latlon$longitude

  # auto limits
  intervals <- check_multipoll(intervals, pollutant)

  if ("fixed" %in% intervals) {
    data <-
      dplyr::mutate(data, latlng = paste(.data[[latitude]], .data[[longitude]]))

    type <- control
    if (is.null(control)) {
      type <- "default"
    }

    testplots <-
      openair::percentileRose(
        data,
        pollutant = pollutant,
        type = c("latlng", type),
        plot = FALSE
      )$data

    theIntervals <- pretty(testplots[[pollutant]])
  } else if ("free" %in% intervals) {
    theIntervals <- NA
  } else if (is.numeric(intervals)) {
    theIntervals <- intervals
  } else {
    cli::cli_abort(
      c("!" = "Do not recognise {.field intervals} value of {.code {intervals}}",
        "i" = "{.field intervals} should be one of {.code 'fixed'}, {.code 'free'} or a numeric vector.")
    )
  }

  # cut data
  data <- quick_cutdata(data = data, type = control)

  # deal with popups
  if (length(popup) > 1) {
    data <-
      quick_popup(
        data = data,
        popup = popup,
        latitude = latitude,
        longitude = longitude,
        control = control
      )
    popup <- "popup"
  }

  # prep data
  data <-
    prepMapData(
      data = data,
      pollutant = pollutant,
      control = control,
      "wd",
      latitude,
      longitude,
      popup,
      label
    )

  # identify splitting column (defaulting to pollutant)
  if (length(pollutant) > 1) {
    split_col <- "pollutant_name"
  } else if (!is.null(control)) {
    data[control] <- as.factor(data[[control]])
    split_col <- control
  } else {
    split_col <- "pollutant_name"
  }

  # define function
  fun <- function(data) {
    if (!"free" %in% intervals) {
      openair::percentileRose(
        data,
        pollutant = "conc",
        percentile = percentile,
        plot = FALSE,
        cols = cols,
        alpha = alpha,
        key = key,
        intervals = theIntervals,
        ...,
        par.settings = list(axis.line = list(col = "transparent"))
      )$plot
    } else {
      openair::percentileRose(
        data,
        pollutant = "conc",
        percentile = percentile,
        plot = FALSE,
        cols = cols,
        alpha = alpha,
        key = key,
        ...,
        par.settings = list(axis.line = list(col = "transparent"))
      )$plot
    }
  }

  # plot and save static markers
  plots_df <-
    create_polar_markers(
      fun = fun,
      data = data,
      latitude = latitude,
      longitude = longitude,
      split_col = split_col,
      d.fig = d.fig,
      popup = popup,
      label = label
    )

  # create leaflet map
  map <-
    make_leaflet_map(
      plots_df,
      latitude,
      longitude,
      provider,
      d.icon,
      popup,
      label,
      split_col,
      collapse.control
    )

  # add legend
  if (all(!is.na(percentile)) & draw.legend) {
    percs <- unique(c(0, percentile))
    map <-
      leaflet::addLegend(
        title = "Percentile",
        map,
        pal = leaflet::colorBin(
          palette = openair::openColours(scheme = cols, n = length(percs)),
          bins = percs,
          domain = 0:100
        ),
        values = 0:100
      )
  }

  # return map
  return(map)
}

#' Percentile roses on a static ggmap
#'
#' [percentileMapStatic()] creates a `ggplot2` map using percentile roses as
#' markers. As this function returns a `ggplot2` object, further customisation
#' can be achieved using functions like [ggplot2::theme()] and
#' [ggplot2::guides()].
#'
#' @inheritSection polarMapStatic Further customisation using ggplot2
#'
#' @family static directional analysis maps
#'
#' @inheritParams polarMapStatic
#' @inheritParams percentileMap
#' @param percentile The percentile value(s) to plot. Must be between 0–100. If
#'   `percentile = NA` then only a mean line will be shown.
#' @inheritDotParams openair::percentileRose -mydata -pollutant -percentile
#'   -type -cols -key -plot -intervals
#'
#' @seealso the original [openair::percentileRose()]
#' @seealso [percentileMap()] for the interactive `leaflet` equivalent of
#'   [percentileMapStatic()]
#'
#' @return a `ggplot2` plot with a `ggmap` basemap
#' @export
percentileMapStatic <- function(data,
                                pollutant = NULL,
                                ggmap,
                                percentile = c(25, 50, 75, 90, 95),
                                intervals = "fixed",
                                latitude = NULL,
                                longitude = NULL,
                                facet = NULL,
                                cols = "turbo",
                                alpha = 1,
                                key = FALSE,
                                facet.nrow = NULL,
                                d.icon = 150,
                                d.fig = 3,
                                ...) {
  # check that there is a ggmap
  check_ggmap(missing(ggmap))

  # assume lat/lon
  latlon <- assume_latlon(data = data,
                          latitude = latitude,
                          longitude = longitude)
  latitude <- latlon$latitude
  longitude <- latlon$longitude

  # auto limits
  intervals <- check_multipoll(intervals, pollutant)

  if ("fixed" %in% intervals) {
    data <-
      dplyr::mutate(data, latlng = paste(.data[[latitude]], .data[[longitude]]))

    type <- facet
    if (is.null(facet)) {
      type <- "default"
    }

    testplots <-
      openair::percentileRose(
        data,
        pollutant = pollutant,
        type = c("latlng", type),
        plot = FALSE
      )$data

    theIntervals <- pretty(testplots[[pollutant]])

  } else if ("free" %in% intervals) {
    theIntervals <- NA
  } else if (is.numeric(intervals)) {
    theIntervals <- intervals
  } else {
    cli::cli_abort(
      c("!" = "Do not recognise {.field intervals} value of {.code {intervals}}",
        "i" = "{.field intervals} should be one of {.code 'fixed'}, {.code 'free'} or a numeric vector.")
    )
  }

  # cut data
  data <- quick_cutdata(data = data, type = facet)

  # prep data
  data <-
    prepMapData(
      data = data,
      pollutant = pollutant,
      control = facet,
      "wd",
      latitude,
      longitude
    )

  # identify splitting column (defaulting to pollutant)
  if (length(pollutant) > 1) {
    split_col <- "pollutant_name"
  } else if (!is.null(facet)) {
    data[facet] <- as.factor(data[[facet]])
    split_col <- facet
  } else {
    split_col <- "pollutant_name"
  }

  # define function
  fun <- function(data) {
    if (!"free" %in% intervals) {
      openair::percentileRose(
        data,
        pollutant = "conc",
        percentile = percentile,
        plot = FALSE,
        cols = cols,
        alpha = alpha,
        key = key,
        intervals = theIntervals,
        ...,
        par.settings = list(axis.line = list(col = "transparent"))
      )$plot
    } else {
      openair::percentileRose(
        data,
        pollutant = "conc",
        percentile = percentile,
        plot = FALSE,
        cols = cols,
        alpha = alpha,
        key = key,
        ...,
        par.settings = list(axis.line = list(col = "transparent"))
      )$plot
    }
  }

  # plot and save static markers
  plots_df <-
    create_polar_markers(
      fun = fun,
      data = data,
      latitude = latitude,
      longitude = longitude,
      split_col = split_col,
      d.fig = d.fig
    )

  # create static map - deals with basics & facets
  plt <-
    create_static_map(
      ggmap = ggmap,
      plots_df = plots_df,
      latitude = latitude,
      longitude = longitude,
      split_col = split_col,
      pollutant = pollutant,
      facet = facet,
      facet.nrow = facet.nrow,
      d.icon = d.icon
    )

  # create legend
  percs <- unique(c(0, percentile))
  intervals <-
    stringr::str_c(percs, dplyr::lead(percs), sep = " - ")
  intervals <- intervals[!is.na(intervals)]
  intervals <- factor(intervals, intervals)
  pal <-
    openair::openColours(scheme = cols, n = length(intervals)) %>%
    stats::setNames(intervals)

  plt <-
    plt +
    ggplot2::geom_point(
      ggplot2::aes(.data[[longitude]], .data[[latitude]],
                   fill = intervals[1]),
      size = 0,
      key_glyph = ggplot2::draw_key_rect
    ) +
    ggplot2::scale_fill_manual(values = pal, drop = FALSE) +
    ggplot2::labs(fill = "percentile")

  # return plot
  return(plt)
}