#' Convert BSseq object to edgeR methylation matrix
 #'
 #' @param bsseq the BSseq object.

 #' @param regions the regions to calculate log-methylation ratios over. If left NULL, ratios will be calculated per
 #'   site.

 #'
 #' @return a matrix compatible with the edgeR differential methylation pipeline
 #' @export
 #'
 #' @examples
 #' methy <- system.file("methy_subset.tsv.bgz", package = "NanoMethViz")
 #' bsseq <- methy_to_bsseq(methy)
 #' edger_mat <- bsseq_to_edger(bsseq)

 bsseq_to_edger <- function(bsseq, regions = NULL) {

     edger_col_names <- .get_edger_col_names(bsseq)

 
     if (!is.null(regions)) {
         assertthat::assert_that(is(regions, "data.frame"))
         regions <- GenomicRanges::GRanges(regions)
         edger_row_names <- regions$gene_id
     } else {
         edger_row_names <- .get_edger_row_names(bsseq)
     }

 
     # construct matrix

     methylated <- .get_me_mat(bsseq, regions)
     unmethylated <- .get_un_mat(bsseq, regions)

 
     edger_mat <- matrix(
         0,
         ncol = 2*ncol(methylated),
         nrow = nrow(methylated),
         dimnames = list(edger_row_names, edger_col_names)
     )
 
     for (i in 0:(ncol(methylated) - 1)) {
         edger_mat[, 2*i + 1] <- methylated[, i + 1]
         edger_mat[, 2*i + 2] <- unmethylated[, i + 1]
     }
 
     edger_mat
 }
 

 #' Convert NanoMethResult object to edgeR methylation matrix
 #'
 #' @inheritParams methy_to_bsseq
 #' @param regions the regions to calculate log-methylation ratios over. If left
 #' NULL, ratios will be calculated per site.
 #'
 #' @return a matrix compatible with the edgeR differential methylation pipeline
 #' @export
 #'
 #' @examples
 #' nmr <- load_example_nanomethresult()
 #' edger_mat <- methy_to_edger(nmr)
 #'
 methy_to_edger <- function(methy, regions = NULL, out_folder = tempdir(), verbose = TRUE) {
     bsseq <- methy_to_bsseq(methy = methy, out_folder = out_folder, verbose = verbose)
     bsseq_to_edger(bsseq, regions = regions)
 }
 

 #' Convert BSseq object to log-methylation-ratio matrix
 #'
 #' Creates a log-methylation-ratio matrix from a BSseq object that is useful for
 #' dimensionality reduction plots.
 #'
 #' @param bsseq the BSseq object.

 #' @param regions the regions to calculate log-methylation ratios over. If left NULL, ratios will be calculated per
 #'   site.

 #' @param prior_count the prior count added to avoid taking log of 0.
 #'
 #' @return a matrix containing log-methylation-ratios.
 #' @export
 #'
 #' @examples

 #' nmr <- load_example_nanomethresult()
 #' bsseq <- methy_to_bsseq(nmr)
 #' regions <- exons_to_genes(NanoMethViz::exons(nmr))
 #' log_m_ratio <- bsseq_to_log_methy_ratio(bsseq, regions)

 bsseq_to_log_methy_ratio <- function(bsseq, regions = NULL, prior_count = 2) {

     if (prior_count < 1) {
         warning("prior_count of 1 or higher is recommended")

     }
 

     if (!is.null(regions)) {
         assertthat::assert_that(is(regions, "data.frame"))
         regions <- GenomicRanges::GRanges(regions)
         row_names <- regions$gene_id
     } else {
         row_names <- .get_edger_row_names(bsseq)
     }
 

     col_names <- SummarizedExperiment::colData(bsseq)$sample

     methylated <- .get_me_mat(bsseq, regions)
     unmethylated <- .get_un_mat(bsseq, regions)

 
     log_mat <- log2(methylated + prior_count) - log2(unmethylated + prior_count)
 
     dimnames(log_mat) <- list(row_names, col_names)
 
     log_mat
 }
 

 .get_me_mat <- function(bsseq, regions) {
     if (!is.null(regions)) {
         bsseq::getCoverage(bsseq, regions, type = "M", what = "perRegionTotal")
     } else {
         bsseq::getCoverage(bsseq, type = "M")
     }

 }
 

 .get_un_mat <- function(bsseq, regions) {
     if (!is.null(regions)) {
         cov <- bsseq::getCoverage(bsseq, regions, type = "Cov", what = "perRegionTotal")
     } else {
         cov <- bsseq::getCoverage(bsseq, type = "Cov")
     }
     me_mat <- .get_me_mat(bsseq, regions)

     cov - me_mat
 }
 
 .get_edger_col_names <- function(bsseq) {
     samples <- SummarizedExperiment::colData(bsseq)$sample
     me_names <- paste0(samples, "_Me")
     un_names <- paste0(samples, "_Un")
     edger_col_names <- character(2 * length(samples))
     for (i in 0:(length(samples) - 1)) {
         edger_col_names[2*i + 1] <- me_names[i + 1]
         edger_col_names[2*i + 2] <- un_names[i + 1]
     }
 
     edger_col_names
 }
 
 .get_edger_row_names <- function(bsseq) {

     gr <- bsseq::getBSseq(bsseq, type = "gr")

     seq <- as.character(SummarizedExperiment::seqnames(gr))
     pos <- as.integer(SummarizedExperiment::start(gr))
     edger_row_names <- paste(seq, pos, sep = "-")
 
     edger_row_names
 }