R/utils-plot.R

In gpw13/rapporteur: Reports on triple billion data

get_scenario_colour <- function(col) {
  those_col <- unique(col)

  base_colours <- c(
    "Estimated" = "grey30",
    "Reported" = "grey30",
    "Imputed" = "grey",
    "Projected" = "#e35f66",
    "Acceleration" = "Purple",
    "Base" = "grey30",
    "SDG" = "#a6611a",
    "Pre-COVID-19 trajectories" = "lightblue",
    "COVID-19 shock" = "#d7191c",
    "COVID-19 Delayed Return" = "#488f31",
    "COVID-19 Sustained Disruption" = "#ffa600"
  )

  extended_palette_no_red_no_purple <- RColorBrewer::brewer.pal(12, "Paired")[-c(1, 4, 6, 10)]

  not_base_colour <- those_col[!those_col %in% names(base_colours)]

  if (length(not_base_colour) > length(extended_palette_no_red_no_purple)) {
    warning("More than 7 scenarios were passed to be plotted on top of acceleration and sdg. Only the 9 first will be displayed.")
  }

  for (i in seq_along(not_base_colour)) {
    this_colour <- extended_palette_no_red_no_purple[i]
    names(this_colour) <- not_base_colour[i]
    base_colours <- c(base_colours, this_colour)
  }

  for (i in seq_along(col)) {
    col[i] <- base_colours[[col[i]]]
  }

  return(col)
}

theme_billionaiRe <- function() {
  ggplot2::theme(
    panel.background = ggplot2::element_rect(fill = "white"),
    panel.border = ggplot2::element_rect(colour = "grey90", fill = NA),
    axis.line.x = ggplot2::element_line(colour = "grey"),
    axis.line.y = ggplot2::element_line(colour = "grey"),
    panel.grid.major = ggplot2::element_blank(),
    panel.grid.minor = ggplot2::element_blank(),
    axis.text = ggplot2::element_text(colour = "gray25", size = 15),
    axis.title = ggplot2::element_blank(),
    strip.background = ggplot2::element_blank(),
    strip.text.x = ggplot2::element_blank(),
    strip.placement = "inside",
    axis.text.y = ggplot2::element_text(size = 6), axis.text.x = ggplot2::element_text(size = 6),
    text = ggplot2::element_text(size = 15),
    legend.key = ggplot2::element_blank(),
    legend.position = "bottom",
    legend.background = ggplot2::element_blank(),
    legend.text = ggplot2::element_text(size = 8),
    legend.title = ggplot2::element_blank(),
    plot.title = ggplot2::element_text(size = 25)
  )
}

integer_breaks <- function(n = 5, ...) {
  fxn <- function(x) {
    breaks <- floor(pretty(x, n, ...))
    names(breaks) <- attr(breaks, "labels")
    breaks
  }
  return(fxn)
}

connect_lines <- function(df,
                          plot_group,
                          value_col,
                          plot_line_color,
                          plot_line_type,
                          base_scenario = "Base"){

  base_df <- df %>%
    dplyr::filter(.data[[plot_group]] == base_scenario)

  df_parameters <- df %>%
    dplyr::filter(.data[[plot_group]] != base_scenario) %>%
    dplyr::group_by(
      dplyr::across(
        dplyr::any_of(c("iso3","ind",!!plot_group)))) %>%
    dplyr::filter(.data[["year"]] == min(.data[["year"]])) %>%
    dplyr::select(dplyr::all_of(c("iso3", "year", "ind", plot_group, plot_line_color, plot_line_type))) %>%
    dplyr::rename(last_year = !!"year", this_ind = "ind", this_plot_group = !!plot_group, this_iso3 = "iso3",
                  this_plot_line_color = !!plot_line_color,
                  this_line_type = !!plot_line_type) %>%
    dplyr::distinct() %>%
    dplyr::ungroup()

   furrr::future_pmap_dfr(df_parameters, get_previous_year_row, df = base_df) %>%
     dplyr::bind_rows(df)
}

get_previous_year_row <- function(df,
                                  last_year,
                                  this_iso3,
                                  this_ind,
                                  this_plot_group,
                                  this_plot_line_color,
                                  this_line_type,
                                  plot_group = "plot_group",
                                  plot_line_color = "plot_line_color",
                                  plot_line_type = "plot_line_type"){
  df %>%
    dplyr::filter(.data[["iso3"]] == this_iso3,
                  .data[["ind"]] == this_ind) %>%
    dplyr::filter(.data[["year"]] %in% min(max(.data[["year"]]), last_year - 1)) %>%
    dplyr::mutate(
      "{plot_group}" := this_plot_group,
      "{plot_line_color}" := this_plot_line_color,
      "{plot_line_type}" := this_line_type
      )
}