##' add insets in a tree
 ##'
 ##' 
 ##' @title inset
 ##' @param tree_view tree view
 ##' @param insets a list of ggplot objects, named by node number
 ##' @param width width of inset
 ##' @param height height of inset
 ##' @param hjust horizontal adjustment
 ##' @param vjust vertical adjustment
 ##' @param x x position, one of 'node' and 'branch'
 ##' @return tree view with insets
 ##' @export
 ##' @author Guangchuang Yu

 inset <- function(tree_view, insets, width=0.1, height=0.1, hjust=0, vjust=0, x="node") {

     df <- tree_view$data[as.numeric(names(insets)),]

     x <- match.arg(x, c("node", "branch", "edge"))
 
     if (x == 'node') {
         xx <- df$x
     } else {
         xx <- df$branch
     }
     yy <- df$y
     
     xx <- xx - hjust
     yy <- yy - vjust
 
     for (i in seq_along(insets)) {
         tree_view %<>% subview(insets[[i]],
                                x = xx[i],
                                y = yy[i],
                                width = width,
                                height = height)
     }
     return(tree_view)
 }
 
 ##' generate a list of bar charts for results of ancestral state reconstruction
 ##'
 ##' 
 ##' @title nodebar
 ##' @param position position of bar, one of 'stack' and 'dodge'
 ##' @inheritParams nodepie
 ##' @return list of ggplot objects
 ##' @export
 ##' @importFrom ggplot2 geom_bar
 ##' @importFrom tidyr gather
 ##' @author Guangchuang Yu
 nodebar <- function(data, cols, color, alpha=1, position="stack") {
     if (! "node" %in% colnames(data)) {
         stop("data should have a column 'node'...")
     }
     type <- value <- NULL
     
     ldf <- gather(data, type, value, cols) %>% split(., .$node)
     bars <- lapply(ldf, function(df) ggplot(df, aes_(x=1, y=~value, fill=~type)) +
                                      geom_bar(stat='identity', alpha=alpha, position=position) +
                                      theme_inset()
                    )
 
     if (missingArg(color) || is.null(color) || is.na(color)) {
         ## do nothing
     } else {
         bars <- lapply(bars, function(p) p+scale_fill_manual(values=color))
     }
     return(bars)
 }
 
 ##' generate a list of pie charts for results of ancestral stat reconstruction
 ##'
 ##' 
 ##' @title nodepie
 ##' @param data a data.frame of stats with an additional column of node number
 ##' @param cols column of stats
 ##' @param color color of bar
 ##' @param alpha alpha
 ##' @return list of ggplot objects
 ##' @export
 ##' @author Guangchuang Yu
 nodepie <- function(data, cols, color, alpha=1) {
     if (! "node" %in% colnames(data)) {
         stop("data should have a column 'node'...")
     }
     type <- value <- NULL
     if (missingArg(color)) {
         color <- NA
     }
     ldf <- gather(data, type, value, cols) %>% split(., .$node)
     lapply(ldf, function(df) ggpie(df, y=~value, fill=~type, color, alpha))
 }
 
 
 ggpie <- function(data, y, fill, color, alpha=1) {
     p <- ggplot(data, aes_(x=1, y=y, fill=fill)) +
         geom_bar(stat='identity', alpha=alpha) +
         coord_polar(theta='y') + theme_inset()
     
     if (missingArg(color) || is.null(color) || is.na(color)) {
         ## do nothing
     } else {
         p <- p+scale_fill_manual(values=color)
     }
     return(p)
 }