#' Heatmap Plot (Upper Triangle)
#'
#' Minimal ggplot2 relationship structure plot showing the upper triangle
#' in the top-right corner with no axis labels.
#' @param R A square numeric correlation matrix
#' @param title Optional plot title
#'
#' @return A ggplot object
#'
#' @examples
#' X <- matrix(data = rnorm(100), nrow = 10)
#' R <- cor(X)
#' heatmap(R, title = 'Example Correlation Plot')
#'
#' @importFrom reshape2 melt
#' @import ggplot2
#' @export
heatmap <- function(R, title = NULL){
	R_list <- tryCatch({
		if(is.matrix(R)){
			cnames <- colnames(R)
			rnames <- rownames(R)
			if(nrow(R) == ncol(R)){
				list(
					R = R[upper.tri(R)],
					cnames = cnames,
					rnames = rnames,
					p = ncol(R)
				)
			}
		}else if(is.vector(R)){
			m <- length(R)
			n <- (1 + sqrt(1 + 8 * m)) / 2
			if(n == floor(n)){
				list(
					R = R,
					cnames = NULL,
					rnames = NULL,
					p = n
				)
			}else{
				stop('Input length not compatible with upper triangle')
			}
		}else{
			Rm <- as.matrix(R)
			cnames <- colnames(Rm)
			rnames <- rownames(Rm)
			if(nrow(Rm) == ncol(Rm)){
				list(
					R = Rm[upper.tri(Rm)],
					cnames = cnames,
					rnames = rnames,
					p = ncol(Rm)
				)
			}
		}
	}, error = function(e){
		stop(paste('Invalid input for corplot:', e$message))
	})

	if(is.null(R_list$cnames)){
		R_list$cnames <- as.character(seq_len(R_list$p))
	}
	if(is.null(R_list$rnames)){
		R_list$rnames <- as.character(seq_len(R_list$p))
	}

	# Now get a df from the upper triangle
	m <- length(R_list$R)
	n <- as.integer((1 + sqrt(1 + 8 * m)) / 2)
	M <- matrix(NA, n, n)
	M[upper.tri(M)] <- R_list$R
	colnames(M) <- R_list$cnames
	rownames(M) <- R_list$rnames
	df <- reshape2::melt(M, na.rm = TRUE)
	colnames(df) <- c('i', 'j', 'value')

	col_label_df <- data.frame(
		j = seq_len(n)[-1],
		i = 0,
		label = R_list$cnames[-1]
	)
	row_label_df <- data.frame(
		j = seq_len(n)[-n],
		i = seq_len(n)[-n],
		label = R_list$cnames[-n]
	)

	max_nchar <- max(nchar(R_list$cnames))
	top_margin <- 5 + max_nchar * 2

	# And plot it
	p <- ggplot2::ggplot(
		data = df,
		ggplot2::aes(x = .data$j, y = .data$i, fill = .data$value)
	) +
	ggplot2::geom_tile() +
	ggplot2::geom_text(
		data = col_label_df,
		ggplot2::aes(x = .data$j, y = .data$i, label = .data$label),
		inherit.aes = FALSE,
		angle = 90,
		hjust = 0,
		vjust = 0.5
	) +
	ggplot2::geom_text(
		data = row_label_df,
		ggplot2::aes(x = .data$j, y = .data$i, label = .data$label),
		inherit.aes = FALSE,
		hjust = 1,
		vjust = 0.5
	) +
	ggplot2::scale_fill_gradient2(
		low = 'red',
		mid = 'white',
		high = 'blue',
		midpoint = 0,
		limits = c(-1, 1),
		name = NULL,
		guide = 'none'
	) +
	ggplot2::scale_y_reverse() +
	ggplot2::coord_fixed(clip = 'off') +
	ggplot2::theme_void() +
	ggplot2::theme(
		plot.margin = ggplot2::margin(
			t = top_margin,
			r = 5,
			b = 5,
			l = 5
		)
	)

	if(!is.null(title)){
		p <- p +
		ggplot2::ggtitle(title) +
		ggplot2::theme(
			plot.title = ggplot2::element_text(hjust = 0.5)
		)
	}
	return(p)
}