R/helper_plot_spiechart.R

In INDperform: Evaluation of Indicator Performances for Assessing Ecosystem States

#' Helper function for plot_spiechart
#'
#' This is the actual plotting function used by the wrapper
#' function \code{\link{plot_spiechart}} for each indicator.
#'
#' @keywords internal
#' @seealso \code{\link{plot_spiechart}}
#' @export
plot_spie <- function(split_input, scale, parting,
	cat, summary_tbl, ground, n_c8_c11, n_c9_c10, col_crit8_11,
	x_ring1, theme_infog, edge = "grey30", ind, lab_size,
	title_size) {


	# Data reorganization (now IND-specific)
	# ---------------

	# Borders for press_type for outer ring2
	temp <- vector(mode = "integer", length = nrow(cat))
	for (i in 1:length(temp)) {
		temp[i] <- sum(cat$n[1:i], na.rm = TRUE) *
			sum(n_c9_c10) + any(n_c8_c11)
	}
	if (all(n_c8_c11)) {
		border <- c(parting, scale[temp] + parting/2,
			360)
		x_ring2 <- c(parting, 360 - parting, 360 -
				parting, parting)
	} else {
		if (any(n_c8_c11)) {
			border <- c(parting/2, scale[temp], 360 -
					parting/2)
			x_ring2 <- c(parting/2, 360 - parting/2,
				360 - parting/2, parting/2)
		} else {
			border <- c(0, scale[temp] + parting/2,
				360)
			x_ring2 <- c(0, 360, 360, 0)
		}
	}

	# Get (IND-specific) plotting information
	# ----------------

	# Which values from scale are needed

	if (nrow(split_input) > 0) {
		take <- suppressMessages(
			split_input %>% dplyr::group_by(!!as.name("press_type")) %>%
				dplyr::summarise(n_press = unique(!!as.name("n_press"))) %>%
				dplyr::left_join(cat, .)
		)
		take$n_press[is.na(take$n_press)] <- 0
	} else {
		take <- cat
		take$n_press <- 0
	}

	x <- vector(mode = "list", length = nrow(take))
	for (i in 1:nrow(take)) {
		x[[i]] <- rep(FALSE, times = take$n[i] - take$n_press[i])
		x[[i]] <- c(x[[i]], rep(TRUE, times = take$n_press[i] *
				2))
		x[[i]] <- c(x[[i]], rep(FALSE, times = take$n[i] -
				take$n_press[i]))
	}

	take <- unlist(x)
	if (!all(n_c9_c10)) {
		take <- take[seq(from = 1, to = length(take),
			by = 2)]
	}

	# Get x values for pressures
	if (any(take)) {
		x_bar_press <- scale[which(take == TRUE) +
				any(n_c8_c11)]
	} else {
		x_bar_press <- c(scale[2:3])
	}

	# Changes in x_bar_press if not all c8/c11
	if (!all(n_c8_c11)) {
		if (any(n_c8_c11)) {
			x_bar_press <- x_bar_press - parting/2
		}
	}
	# Get y values for pressures
	y_bar_press <- NULL
	for (i in 1:nrow(split_input)) {
		# Choose only what is present indicated by n_c9_c10
		y_bar_press <- c(y_bar_press, unlist(split_input[i,
			c("C9_in%", "C10_in%")[n_c9_c10]]))
	}

	# Get x values for labels
	if (all(n_c9_c10)) {
		x_lab <- x_bar_press[seq(from = 1, to = length(x_bar_press),
			by = 2)]
	} else {
		x_lab <- x_bar_press
	}

	# Get labels for the pressure slices
	lab <- c(split_input$press)

	# Assign colors
	if (all(n_c9_c10)) {
		# Colors for the slices if c9 and 10 are present
		col_slice <- c(rep(split_input$col, each = 2))
		alpha <- c(rep(c(1, 0.5), times = nrow(split_input)))
	} else {
		# Colors for the slices if only c9 or c10 is
		# present
		col_slice <- split_input$col
		alpha <- rep(c(1, 0.5)[n_c9_c10], times = nrow(split_input))
	}

	# col alpha and lab if nrow(split_input) == 0
	if (nrow(split_input) == 0) {
		col_slice <- NA
		alpha <- NA
		lab <- NA
	}
	# Get x and y for pressure-unspecific values
	if (!any(n_c8_c11)) {
		# if no trend/ management is plotted -->
		# parting_ind = 0
		parting_ind <- 0
		x_bar_ind <- x_bar_press[1]
		y_bar_ind <- 0
		edge <- NA
		col_crit8_11 <- NA
	}
	if (any(n_c8_c11)) {
		x_bar_ind <- scale[c(1, length(scale))]
		y_bar_ind <- c(unlist(summary_tbl[summary_tbl$ind ==
				ind, c("C8_in%", "C11_in%")[n_c8_c11]]))
		parting_ind <- parting
		# Double value for remaining crit if one is
		# excluded
		if (!all(n_c8_c11)) {
			x_bar_ind <- x_bar_ind + c(-parting/4,
				parting/4)
			y_bar_ind <- rep(y_bar_ind, times = 2)
			edge <- NA
			parting_ind <- parting/2
			# Choose the colour for the remaining crit
			if (is.na(col_crit8_11[n_c8_c11])) {
				# If only one col_crit is provided (since you dont
				# provide two col_crits if you exclude c8, but in
				# that case col_crit8_11[n_c8_c11] is NA!)
				col_crit8_11 <- rep(col_crit8_11, times = 2)
			} else {
				# If the default is used
				col_crit8_11 <- rep(col_crit8_11[n_c8_c11],
					times = 2)
			}
		}
	}

	# Actual plot -----------------------

	x_plot <- ground$x
	y_plot <- ground$y

	p <-	ggplot2::ggplot() + theme_infog +
		# Create a white background
		ggplot2::geom_polygon(
			data = data.frame(x_plot = x_plot, y_plot = y_plot),
			mapping = ggplot2::aes(x = !!rlang::sym("x_plot"), y = !!rlang::sym("y_plot")),
			fill = "white") + # Create the outer ring
		ggplot2::geom_polygon(
			data = data.frame(x_ring1 = x_ring1, yring1 = c(120, 120, 130, 130)),
			mapping = ggplot2::aes(x = !!rlang::sym("x_ring1"), y = !!rlang::sym("yring1")),
			fill = "grey30") +
		ggplot2::geom_polygon(
			data = data.frame(x_ring2 = x_ring2, yring2 = c(120, 120, 130, 130)),
			mapping = ggplot2::aes(x = !!rlang::sym("x_ring2"), y = !!rlang::sym("yring2")),
			fill = "grey60") +
		# Make the barplot to a spie chart
		ggplot2::coord_polar() + # Create the white borders between the categories
		ggplot2::geom_segment(
			data = data.frame(border = border, y_start = 100, y_end = 140),
			mapping = ggplot2::aes(x = !!rlang::sym("border"), xend = !!rlang::sym("border"),
				y = !!rlang::sym("y_start"), yend = !!rlang::sym("y_end")),
			colour = "white", cex = 2) +
		ggplot2::geom_segment(
			data = data.frame(border = border, y_start = 0, y_end = 100),
			mapping = ggplot2::aes(x = !!rlang::sym("border"), xend = !!rlang::sym("border"),
				y = !!rlang::sym("y_start"), yend = !!rlang::sym("y_end")),
			colour = "grey60", linetype = 2) +
		# Plot the pressure specific data
		ggplot2::geom_bar(
			data = data.frame(x_bar_press = x_bar_press, y_bar_press = y_bar_press),
			mapping = ggplot2::aes(x = !!rlang::sym("x_bar_press"), y = !!rlang::sym("y_bar_press")),
			stat = "identity", width = parting,
			fill = col_slice, alpha = alpha, col = "grey30",
			na.rm = TRUE) + # Plot the pressure-unspecific data
		ggplot2::geom_bar(
			data = data.frame(x_bar_ind = x_bar_ind, y_bar_ind = y_bar_ind),
			mapping = ggplot2::aes(x = !!rlang::sym("x_bar_ind"), y = !!rlang::sym("y_bar_ind")),
			stat = "identity", width = parting_ind,
			fill = col_crit8_11, col = edge, na.rm = TRUE) +
		# Add 100% line
		ggplot2::geom_abline(intercept = 100, slope = 0,
			linetype = 1, col = "grey60") + # Add labels for sig pressures
		ggplot2::geom_text(ggplot2::aes(x = x_lab, y = 100,
			label = lab), size = lab_size, na.rm = TRUE) +
		# Add title
		ggplot2::geom_text(ggplot2::aes(x = x_ring1[1],
			y = 150, label = ind), size = title_size, na.rm = TRUE)

	return(p)
}