#' getDimensionality
 #' 
 #' Returns the estimated intrinsic dimensionality of a dataset.
 #'

 #' @param dat A Seurat or SCE object with a pca embedding.
 #' @param method The dimensionality method to use.

 #' @param maxDims Deprecated and ignored.
 #'
 #' @return An integer.
 #'
 #' @importFrom Seurat Stdev
 #' @importFrom SingleCellExperiment reducedDim
 #' @import intrinsicDimension
 getDimensionality <- function(dat, method, maxDims=NULL){
   if(is(dat, "Seurat")){
     x <- dat[["pca"]]@cell.embeddings
     sdv <- Stdev(dat, "pca")
   } else {
     if(method=="jackstraw.elbow")
       stop("the jackstraw.elbow method is only available for Seurat objects.")
     x <- reducedDim(dat, "PCA")
     sdv <- attr(reducedDim(dat, "PCA"), "percentVar")
   }
   # conversion for backward compatibility:
   conv <- c( "fisherSeparability"="FisherSeparability",
              "scran.denoisePCA"="scran.ndims.wrapper", 
              "jackstraw.elbow"="js.wrapper"
   )
   if(method %in% names(conv)) method <- as.character(conv[method])
   
   x <- switch(method,
               essLocal.a=essLocalDimEst(x),
               essLocal.b=essLocalDimEst(x, ver="b"),
               pcaLocal.FO=pcaLocalDimEst(x,ver="FO"),
               pcaLocal.fan=pcaLocalDimEst(x, ver="fan"),
               pcaLocal.maxgap=pcaLocalDimEst(x, ver="maxgap"),
               maxLikGlobal=maxLikGlobalDimEst(x, k=20, unbiased=TRUE),
               pcaOtpmPointwise.max=pcaOtpmPointwiseDimEst(x,N=10),
               elbow=farthestPoint(sdv)-1,
               ifelse( !is.function(method) && 
                         !( is.character(method) && 
                              is.function(method <- get(method)) ),
                       stop("Unknown dimensionality method!"),
                       method(dat) )
   )
   if(is.list(x) && "dim.est" %in% names(x)) x <- max(x$dim.est)
   as.integer(round(x))
 }
 
 
 # sce2se conversion
 # not exported
 #' @import SingleCellExperiment Seurat

 #' @importFrom SummarizedExperiment assayNames

 seWrap <- function(sce, min.cells=10, min.features=0){
   if(is(sce,"Seurat")) return(sce)
   suppressPackageStartupMessages(library(Seurat))
   se <- CreateSeuratObject( counts=counts(sce), 
                             min.cells=min.cells, 
                             min.features=min.features, 
                             meta.data=as.data.frame(colData(sce)), 
                             project = "scRNAseq" )
   se@misc$rowData <- as.data.frame(rowData(sce))
   if("logcounts" %in%  assayNames(sce)){
     se <- ScaleData(se, verbose = FALSE)
     se@assays$RNA@data <- logcounts(sce)
   } 
   if(!is.null(metadata(sce)$VariableFeats)) 
     VariableFeatures(se) <- metadata(sce)$VariableFeats
   if(length(reducedDimNames(sce)) != 0) 
     se[["pca"]] <- CreateDimReducObject(embeddings=reducedDim(sce), key="PC_", 
                                         assay="RNA")
   se
 }
 
 # se2sce conversion
 # not exported
 #' @import SingleCellExperiment Seurat

 #' @importFrom SummarizedExperiment rowData<-

 sceWrap <- function(seu) {
   suppressPackageStartupMessages({
     library(SingleCellExperiment)
     library(Seurat)
   })

   sce <- SingleCellExperiment(
     list(counts=GetAssayData(seu, assay="RNA", slot="counts")), 
     colData = seu[[]] )

   if(nrow(norm <- GetAssayData(seu, slot="scale.data"))>0){
     sce <- sce[row.names(norm),]
     logcounts(sce) <- norm
   }
   rowData(sce) <- seu@misc$rowData[row.names(sce),]
   if(length(VariableFeatures(seu)))
     metadata(sce)$VariableFeats <- VariableFeatures(seu)
   if(length(Reductions(seu))>0){

     reducedDims(sce) <- lapply( seu@reductions, 
                                 FUN=function(x) [email protected] )

   }
   sce
 }