#' Generate HTML file for scatter plots which all data points are highlighted by IPCAPS clusters
#'
#' @description Generate HTML file called 'tree_scatter_cluster.html' from the
#' result of \code{\link{ipcaps}}. This function is a part of workflow in
#' \code{\link{save.plots}}. The clustering result is shown as a tree rendering
#' by the online Google Organizational Chart library. Note that the Internet is
#' required to view the HTML file.
#'
#' @param output.dir A result directory as the \code{$output} object returned
#' from the \code{\link{ipcaps}} function.
#'
#' @return \code{NULL}
#'
#' @details After running, this function generates the file called 'tree_scatter_cluster.html'
#' in the same result directory. All plots are generated and saved as image files
#' in the sub-directory 'images'.
#'
#' @export
#'
#' @include output.template.R
#'
#' @seealso \code{\link{save.html}},
#' \code{\link{save.plots}},
#' \code{\link{save.eigenplots.html}},
#' and \code{\link{save.plots.label.html}}
#'
#' @examples
#'
#' # Importantly, bed file, bim file, and fam file are required
#' # Use the example files embedded in the package
#'
#' BED.file <- system.file("extdata","ipcaps_example.bed",package="IPCAPS")
#' LABEL.file <- system.file("extdata","ipcaps_example_individuals.txt.gz",package="IPCAPS")
#'
#' my.cluster <- ipcaps(bed=BED.file,label.file=LABEL.file,lab.col=2,out=tempdir())
#'
#' #Here, to generate HTML file
#' save.plots.cluster.html(my.cluster$output.dir)
save.plots.cluster.html <- function(output.dir){
tree <- NULL
label <- NULL
min.in.group <- NULL
leaf.node <- NULL
load(file.path(output.dir,"RData","leafnode.RData"))
load(file.path(output.dir,"RData","tree.RData"))
load(file.path(output.dir,"RData","condition.RData"))
node.list = sort(tree$node)
txt_data = ""
txt_leafnode = ""
test.dir=file.path(output.dir,"images.new")
img.dir="images"
if (file.exists(test.dir)){
img.dir="images.new"
}
for (i in node.list){
parent_node = ""
if (i > 1){
parent_node = tree$parent.node[which(tree$node == i)]
}
PCs.file = file.path(output.dir,"RData",paste0("node",i,".RData"))
load(PCs.file)
list.sum = c()
u.label = sort(unique(label))
for (j in 1:length(u.label)){
co = length(label[label == u.label[j]])
strout = paste0(u.label[j]," (",co,")")
list.sum = c(list.sum,strout)
}
content = ""
for (s in list.sum){
content = paste0(content,s,"
")
}
if (file.exists(file.path(output.dir,"images",paste0("scatterplot_preview",i,".jpg")))){
txt_data = paste0(txt_data,"[{v:'",i,"', f:'
Node ",i,"
Node ",i,"
under cutoff (<",min.in.group,")