R/internals.R

Defines functions .set_internal_character .set_internal_numeric .set_internal_missing .get_internal_character .get_internal_integer .get_internal_missing .set_internal_names .get_internal_names .set_internal_all .get_internal_all

#' @title
#' Internal SingleCellExperiment functions 
#' 
#' @description
#' Methods to get or set internal fields from the SingleCellExperiment class.
#' Thse functions are intended for package developers who want to add protected fields to a SingleCellExperiment.
#' They should \emph{not} be used by ordinary users of the \pkg{SingleCellExperiment} package.
#' 
#' @section Getters:
#' In the following code snippets, \code{x} is a \linkS4class{SingleCellExperiment}.
#' \describe{
#' \item{\code{int_elementMetadata(x)}:}{Returns a \linkS4class{DataFrame} of internal row metadata,
#' with number of rows equal to \code{nrow(x)}.
#' This is analogous to the user-visible \code{\link{rowData}}.}
#' \item{\code{int_colData(x)}:}{Returns a \linkS4class{DataFrame} of internal column metadata,
#' with number of rows equal to \code{ncol(x)}.
#' This is analogous to the user-visible \code{\link{colData}}.}
#' \item{\code{int_metadata(x)}:}{Returns a list of internal metadata, analogous to the user-visible \code{\link{metadata}}.}
#' }
#'
#' It may occasionally be useful to return both the visible and the internal \code{colData} in a single DataFrame.
#' This is facilitated by the following methods:
#' \describe{
#' \item{\code{rowData(x, ..., internal=FALSE)}:}{Returns a \linkS4class{DataFrame} of the user-visible row metadata.
#' If \code{internal=TRUE}, the internal row metadata is added column-wise to the user-visible metadata.
#' A warning is emitted if the user-visible metadata column names overlap with the internal fields.
#' Any arguments in \code{...} are passed to \code{\link{rowData,SummarizedExperiment-method}}.}
#' \item{\code{colData(x, ..., internal=FALSE)}:}{Returns a \linkS4class{DataFrame} of the user-visible column metadata.
#' If \code{internal=TRUE}, the internal column metadata is added column-wise to the user-visible metadata.
#' A warning is emitted if the user-visible metadata column names overlap with the internal fields.
#' Any arguments in \code{...} are passed to \code{\link{colData,SummarizedExperiment-method}}.}
#' } 
#'
#' @section Setters:
#' In the following code snippets, \code{x} is a \linkS4class{SingleCellExperiment}.
#' \describe{
#' \item{\code{int_elementMetadata(x) <- value}:}{Replaces the internal row metadata with \code{value},
#' a \linkS4class{DataFrame} with number of rows equal to \code{nrow(x)}.
#' This is analogous to the user-visible \code{\link{rowData<-}}.}
#' \item{\code{int_colData(x) <- value}:}{Replaces the internal column metadata with \code{value},
#' a \linkS4class{DataFrame} with number of rows equal to \code{ncol(x)}.
#' This is analogous to the user-visible \code{\link{colData<-}}.}
#' \item{\code{int_metadata(x) <- value}:}{Replaces the internal metadata with \code{value}, 
#' analogous to the user-visible \code{\link{metadata<-}}.}
#' }
#'
#' @section Comments:
#' The internal metadata fields allow easy and extensible storage of additional elements
#' that are parallel to the rows or columns of a \linkS4class{SingleCellExperiment} class.
#' This avoids the need to specify new slots and adjust the subsetting/combining code for a new data element.
#' For example, \code{\link{altExps}} and \code{\link{reducedDims}} are implemented as fields in the internal column metadata.
#'
#' That these elements are internal is important as this ensures that the implementation details are abstracted away.
#' Any user interaction with these internal fields should be done via the designated getter and setter methods,
#' e.g., \code{\link{reducedDim}} and friends for retrieving or modifying reduced dimensions.
#' This provides developers with more freedom to change the internal representation without breaking user code.
#' 
#' Package developers intending to use these methods to store their own content should read the development vignette for guidance.
#' 
#' @seealso
#' \code{\link{colData}}, \code{\link{rowData}} and \code{\link{metadata}} for the user-visible equivalents.
#'
#' @author Aaron Lun
#'
#' @name SCE-internals
#' @rdname internals
#' @docType methods
#' @aliases
#' int_colData
#' int_elementMetadata
#' int_metadata
#' int_colData,SingleCellExperiment-method
#' int_elementMetadata,SingleCellExperiment-method
#' int_metadata,SingleCellExperiment-method
#' int_colData<-
#' int_elementMetadata<-
#' int_metadata<-
#' int_colData<-,SingleCellExperiment-method
#' int_elementMetadata<-,SingleCellExperiment-method
#' int_metadata<-,SingleCellExperiment-method
#' colData,SingleCellExperiment-method
#' rowData,SingleCellExperiment-method
#' parallel_slot_names,SingleCellExperiment-method
#'
#' @examples
#' example(SingleCellExperiment, echo=FALSE) # Using the class example
#' int_metadata(sce)$whee <- 1
NULL

#' @export
setMethod("int_elementMetadata", "SingleCellExperiment", function(x) x@int_elementMetadata)

#' @export
setReplaceMethod("int_elementMetadata", "SingleCellExperiment", function(x, value) {
    x@int_elementMetadata <- value
    return(x)
})

#' @export
#' @importFrom S4Vectors parallel_slot_names
setMethod("parallel_slot_names", "SingleCellExperiment", function(x) {
    c("int_elementMetadata", callNextMethod())
})

#' @export
setMethod("int_colData", "SingleCellExperiment", function(x) x@int_colData)

#' @export
setReplaceMethod("int_colData", "SingleCellExperiment", function(x, value) {
    x@int_colData <- value
    return(x)
})

#' @export
setMethod("int_metadata", "SingleCellExperiment", function(x) x@int_metadata)

#' @export
setReplaceMethod("int_metadata", "SingleCellExperiment", function(x, value) {
    x@int_metadata <- value
    return(x)
})

#' @export
#' @importFrom SummarizedExperiment colData
setMethod("colData", "SingleCellExperiment", function(x, ..., internal=FALSE) {
    if(internal) {
        cn <- colnames(x@colData) # need explicit slot reference to avoid recursive colData() calling.
        conflict <- cn %in% colnames(int_colData(x))
        if (any(conflict)) {
            cn <- cn[conflict]
            if (length(cn) > 2) {
                cn <- c(cn[seq_len(2)], "...")
            }
            warning("overlapping names in internal and external colData (", paste(cn, collapse = ", "), ")")
        }
        cbind(callNextMethod(x, ...), int_colData(x))
    } else {
        callNextMethod(x, ...)
  }
})

#' @export
#' @importFrom S4Vectors mcols
#' @importFrom SummarizedExperiment rowData
setMethod("rowData", "SingleCellExperiment", function(x, ..., internal=FALSE) {
    if (internal) {
        cn <- colnames(mcols(x))
        conflict <- cn %in% colnames(int_elementMetadata(x))
        if (any(conflict)) {
            cn <- cn[conflict]
            if (length(cn) > 2) {
                cn <- c(cn[seq_len(2)], "...")
            }
            warning("overlapping names in internal and external rowData (", paste(cn, collapse = ", "), ")")
        }
        cbind(callNextMethod(x, ...), int_elementMetadata(x))
    } else {
        callNextMethod(x, ...)
    }
})

##################################################
### Defining getters/setters for the internals ###
##################################################

#' @importClassesFrom S4Vectors SimpleList
.get_internal_all <- function(x, getfun, key, convertfun) {
    x <- updateObject(x)
    as(getfun(x)[[key]], "SimpleList")
}

#' @importFrom methods as
#' @importFrom S4Vectors DataFrame
.set_internal_all <- function(x, value, getfun, setfun, key, convertfun, xdimfun, vdimfun, funstr, xdimstr, vdimstr) {
    x <- updateObject(x)

    if (length(value) == 0L) {
        collected <- getfun(x)[, 0]
    } else {
        if (!is.null(convertfun)) {
            value <- lapply(value, convertfun)
        }

        N <- vapply(value, vdimfun, 0L)
        if (!all(N == xdimfun(x))) {
            stop("invalid 'value' in '", funstr, "(<", class(x), ">) <- value'\n",
                "each element of 'value' should have number of ", vdimstr, " equal to '", xdimstr, "(x)'")
        }

        collected <- do.call(DataFrame, lapply(value, I))
        if (is.null(names(value))) {
            colnames(collected) <- paste0(.unnamed, seq_along(value))
        }
    }

    tmp <- getfun(x)
    tmp[[key]] <- collected
    setfun(x, tmp)
}

.get_internal_names <- function(x, getfun, key) {
    x <- updateObject(x)
    colnames(getfun(x)[[key]])
}

.set_internal_names <- function(x, value, getfun, setfun, key) {
    x <- updateObject(x)
    tmp <- getfun(x)
    colnames(tmp[[key]]) <- value
    setfun(x, tmp)
}

.get_internal_missing <- function(x, basefun, namefun, funstr, ...) {
    if (identical(length(namefun(x)), 0L)) {
        stop("no available entries for '", funstr, "(<", class(x), ">, ...)'")
    }
    basefun(x, 1L, ...)
}

.get_internal_integer <- function(x, index, getfun, key, funstr, substr) {
    x <- updateObject(x)
    internals <- getfun(x)[[key]]

    tryCatch({
        internals[, index]
    }, error=function(err) {
        stop("invalid subscript '", substr, "' in '", funstr, "(<", class(x), ">, type=\"numeric\", ...)':\n  ",
            conditionMessage(err))
    })
}

.get_internal_character <- function(x, index, getfun, key, funstr, substr, namestr) {
    x <- updateObject(x)
    internals <- getfun(x)[[key]]

    tryCatch({
        internals[, index]
    }, error=function(err) {
        stop("invalid subscript '", substr, "' in '", funstr, "(<", class(x), ">, type=\"character\", ...)':\n  ",
            "'", index, "' not in '", namestr, "(<", class(x), ">)'")
    })
}

.set_internal_missing <- function(x, value, basefun, namefun) {
    if (length(namefun(x))){
        type <- 1L
    } else {
        type <- paste0(.unnamed, 1L)
    }
    basefun(x, type, value=value)
}

.set_internal_numeric <- function(x, type, value, getfun, setfun, key, 
    convertfun, xdimfun, vdimfun, funstr, xdimstr, vdimstr, substr) 
{
    x <- updateObject(x)

    if (!is.null(value)) {
        if (!is.null(convertfun)) {
            value <- convertfun(value)
        }
        if (!identical(vdimfun(value), xdimfun(x))) {
            stop("invalid 'value' in '", funstr, "(<", class(x), ">, type=\"numeric\") <- value':\n  ",
                "'value' should have number of ", vdimstr, " equal to '", xdimstr, "(x)'")
        }
    }

    internals <- getfun(x)
    if (type[1] > ncol(internals[[key]])) {
        stop("'", substr, "' out of bounds in '", funstr, "(<", class(x), ">, type='numeric')")
    }

    internals[[key]][[type]] <- value
    setfun(x, internals)
}

.set_internal_character <- function(x, type, value, getfun, setfun, key, 
    convertfun, xdimfun, vdimfun, funstr, xdimstr, vdimstr, substr) 
{
    x <- updateObject(x)

    if (!is.null(value)) {
        if (!is.null(convertfun)) {
            value <- convertfun(value)
        }
        if (!identical(vdimfun(value), xdimfun(x))) {
            stop("invalid 'value' in '", funstr, "(<", class(x), ">, type=\"character\") <- value':\n  ",
                "'value' should have number of ", vdimstr, " equal to '", xdimstr, "(x)'")
        }
    }

    internals <- getfun(x)
    internals[[key]][[type]] <- value
    setfun(x, internals)
}    

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SingleCellExperiment documentation built on Nov. 8, 2020, 7:51 p.m.