R/polar_windroseMap.R

In openairmaps: Create Maps of Air Pollution Data

#' Wind rose plots on interactive leaflet maps
#'
#' [windroseMap()] creates a `leaflet` map using wind roses as markers. Multiple
#' layers of markers can be added and toggled between using `control`.
#'
#' @family interactive directional analysis maps
#'
#' @inheritParams polarMap
#' @param data A data frame. The data frame must contain the data to plot a
#'   [openair::windRose()], which includes wind speed (`ws`), and wind direction
#'   (`wd`). In addition, `data` must include a decimal latitude and longitude.
#' @param ws.int The wind speed interval. Default is 2 m/s but for low met masts
#'   with low mean wind speeds a value of 1 or 0.5 m/s may be better.
#' @param breaks Most commonly, the number of break points for wind speed in
#'   windRose. For windRose and the ws.int default of 2 m/s, the default, 4,
#'   generates the break points 2, 4, 6, 8 m/s. Breaks can also be used to set
#'   specific break points. For example, the argument breaks = c(0, 1, 10, 100)
#'   breaks the data into segments <1, 1-10, 10-100, >100.
#' @param draw.legend Should a shared legend be created at the side of the map?
#'   Default is `TRUE`.
#' @inheritDotParams openair::windRose -ws.int -breaks -mydata -plot -annotate
#'   -pollutant -type -cols -key
#' @return A leaflet object.
#' @export
#'
#' @seealso the original [openair::windRose()]
#' @seealso [windroseMapStatic()] for the static `ggmap` equivalent of
#'   [windroseMap()]
#'
#' @examples
#' \dontrun{
#' windroseMap(polar_data,
#'   provider = "Stamen.Toner"
#' )
#' }
windroseMap <- function(data,
                        ws.int = 2,
                        breaks = 4,
                        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::windroseMap(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

  # need to put ws in a separate column to work with the rest of openairmaps
  # utilities...
  data$ws_dup <- data$ws

  # 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 = "ws_dup",
      control = control,
      "ws",
      "wd",
      latitude,
      longitude,
      popup,
      label
    )

  # work out breaks
  # needs to happen before plotting to ensure same scales
  breaks <-
    getBreaks(
      breaks = breaks,
      ws.int = ws.int,
      vec = data$conc,
      polrose = FALSE
    )

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

  # define function
  fun <- function(data) {
    openair::windRose(
      data,
      plot = FALSE,
      ws.int = ws.int,
      breaks = breaks,
      cols = cols,
      alpha = alpha,
      key = key,
      annotate = FALSE,
      ...,
      par.settings = list(axis.line = list(col = "transparent"))
    )
  }

  # 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 (draw.legend) {
    map <-
      leaflet::addLegend(
        map,
        pal = leaflet::colorBin(
          palette = openair::openColours(cols),
          domain = breaks,
          bins = breaks
        ),
        values = breaks,
        title = "Wind Speed"
      )
  }

  return(map)
}

#' Wind rose plots on a static ggmap
#'
#' [windroseMapStatic()] creates a `ggplot2` map using wind roses as markers. As
#' this function returns a `ggplot2` object, further customisation can be
#' achieved using functions like [ggplot2::theme()] and [ggplot2::guides()]. See
#' [openair::polarPlot()] for more information.
#'
#' @inheritSection polarMapStatic Further customisation using ggplot2
#'
#' @family static directional analysis maps
#'
#' @inheritParams polarMapStatic
#' @param ws.int The wind speed interval. Default is 2 m/s but for low met masts
#'   with low mean wind speeds a value of 1 or 0.5 m/s may be better.
#' @param breaks Most commonly, the number of break points for wind speed in
#'   windRose. For windRose and the ws.int default of 2 m/s, the default, 4,
#'   generates the break points 2, 4, 6, 8 m/s. Breaks can also be used to set
#'   specific break points. For example, the argument breaks = c(0, 1, 10, 100)
#'   breaks the data into segments <1, 1-10, 10-100, >100.
#' @inheritDotParams openair::polarAnnulus -mydata -pollutant -period -limits
#'   -type -cols -key -plot
#'
#' @seealso the original [openair::windRose()]
#' @seealso [windroseMap()] for the interactive `leaflet` equivalent of
#'   [windroseMapStatic()]
#'
#' @return a `ggplot2` plot with a `ggmap` basemap
#' @export
windroseMapStatic <- function(data,
                              ggmap = NULL,
                              ws.int = 2,
                              breaks = 4,
                              facet = NULL,
                              latitude = NULL,
                              longitude = 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

  # need to put ws in a separate column to work with the rest of openairmaps
  # utilities...
  data$ws_dup <- data$ws

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

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

  # work out breaks
  # needs to happen before plotting to ensure same scales
  breaks <-
    getBreaks(
      breaks = breaks,
      ws.int = ws.int,
      vec = data$conc,
      polrose = FALSE
    )

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

  # define function
  fun <- function(data) {
    openair::windRose(
      data,
      plot = FALSE,
      ws.int = ws.int,
      breaks = breaks,
      cols = cols,
      alpha = alpha,
      key = key,
      annotate = FALSE,
      ...,
      par.settings = list(axis.line = list(col = "transparent"))
    )
  }

  # 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 = "ws",
      facet = facet,
      facet.nrow = facet.nrow,
      d.icon = d.icon
    )

  # sort out legend
  intervals <- attr(plots_df$plot[[1]]$data, "intervals")
  intervals <- factor(intervals, intervals)
  pal <- openair::openColours(scheme = cols, n = length(intervals)) %>%
    stats::setNames(intervals)

  plt <-
    plt +
    ggplot2::geom_point(
      data = plots_df,
      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 = openair::quickText("ws"))

  # return plot
  return(plt)
}