R/geocode_maps.R

In KimBaldry/mapSOOSWG:

#' @title Create multiple SOOS Geocoded Maps from a file
#'
#' @author Kimberlee Baldry
#' @description This script contains a function to create all SOOS WG maps from a file. The function: - acesses the file - applies data from rows of the file to 1. plot a WG map using plot_WG_map() and 2. save the file as a .png file using save_map() - outputs a message for each sucessfull map and when the run is complete
#'
#' @note v.0.1
#'
#' @return It will let you know if the code worked!
#' @param SOOS_WG_data A data frame. The data frame must contain the columns named "Acronym" (for the WG), "Affiliations" and "Countries.Represented" (optional). See "example_WG_data" for an example.
#' @param outdir The directory where you would like .png files saved
#' @param country_names_data A data frame. The data frame must contain 2 columns labeled "Country" (what SOOS records the country as) and "ISO3_name". See "example_country_data" for an example. This data frame is optional - do you want participating countries coloured?
#' @param institution_names_data A data frame. The data frame must contain 4 columns labeled "Name" (what SOOS records the Affiliations as), "Type", "Latitude" and "Longitude". SSee example_institution_data for an example.
#' @param add_countries If set to TRUE, participating countries will be coloured.
#' @param ... see base_plot() and plot_WG_map() for further plot options (background_colour, world_map_colour, border_colour, plot_border_thickness)
#'
#' @import ggplot2
#' @import data.table
#' @import broom
#' @import rgeos
#' @import rworldmap
#' @import ggimage
#' @import tidyverse
#' @import raster
#' @import sf
#'
#' @export

geocode_maps <- function(SOOS_WG_data, outdir, country_names_data = NULL, institution_names_data, add_countries = F, filter_types = "all", ...){

  # prepare data
  WG_names = SOOS_WG_data$Acronym

  ### country data
  if(add_countries){
      # prepare data
      countries = lapply(SOOS_WG_data$Countries.Represented, FUN = function(x){unlist(strsplit(x, split = "; "))})
      # check that all countries to be plotted appear in the country lookup table
      check = check_country_names(countries, country_names_data)
      if(any(check == "Failed")){break}
      countries = check
  }else{countries = vector("list", length(WG_names))}

  ### institution data
  # prepare data
  inst = lapply(SOOS_WG_data$Affiliations, FUN = function(x){unlist(strsplit(x, split = "; "))})
  # check that all institutions to be plotted appear in the lookup table
  check = check_institution_names(inst, institution_names_data)
  if(any(check == "Failed")){break}
  inst_data = check

  ### loop through WG and plot
  for(rw in 1:length(WG_names)){
    ## filter by TYPE
    if(filter_types != "all"){
      only_plot = institution_names_data %>% filter(Type %in% filter_types)
      inst_data[[rw]] = inst_data[[rw]] %>% filter(inst %in% only_plot$Name)
    }

    # make plot object
    map = plot_geocode_map(WG_name = WG_names[rw], WG_institutions = inst_data[[rw]], WG_countries = countries[[rw]], hilight_countries = add_countries, ...)
    # save plot
    save_map(map,WG_names[rw], outdir)
  }
  print("Sucess! All maps were created")
}