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#' @rdname readImgData
#' @title Read images & scale factors for 10x Genomics Visium
#'
#' @description
#' Function to read in images and scale factors for 10x Genomics Visium data,
#' and return as a valid \code{\link{imgData}} \code{DataFrame}.
#'
#' @param path a path where to find one or more images
#' @param sample_id the \code{sample_id} for the \code{\link{SpatialExperiment}}
#' object
#' @param imageSources the images source path(s)
#' @param scaleFactors the .json file where to find the scale factors
#' @param load logical; should the image(s) be loaded into memory
#' as a \code{grob}? If FALSE, will store the path/URL instead.
#'
#' @return a \code{\link{DataFrame}}
#'
#' @author Helena L. Crowell
#'
#' @examples
#' dir <- system.file(
#' file.path("extdata", "10xVisium", "section1", "outs", "spatial"),
#' package = "SpatialExperiment")
#'
#' # base directory contains
#' # - scale factors (scalefactors_json.json)
#' # - one image (tissue_lowres_image.png)
#' list.files(dir)
#'
#' # read in images & scale factors
#' # as valid 'imgData' 'DFrame'
#' readImgData(dir, sample_id = "foo")
#'
#' @importFrom rjson fromJSON
#' @importFrom magick image_read image_info
#' @export
# TODO: change 'as' to 'load = TRUE/FALSE' &
# support images to be supplied as path or URL
readImgData <- function(path=".", sample_id=names(path),
imageSources=file.path(path, "tissue_lowres_image.png"),
scaleFactors=file.path(path, "scalefactors_json.json"),
load=TRUE) {
# get sample identifiers
if (is.null(sample_id))
stop("'sample_id' mustn't be NULL")
stopifnot(
is.character(sample_id),
length(unique(sample_id)) == length(path))
names(path) <- names(scaleFactors) <- sample_id
# put images into list with one element per sample
images <- lapply(path, function(.)
grep(., imageSources, value=TRUE, fixed=TRUE))
dfs <- lapply(sample_id, function(sid)
{
sfs <- fromJSON(file=scaleFactors[sid])
dfs <- lapply(images[[sid]], function(img)
{
# get image identifier
img_nm <- gsub("\\..*", "", basename(img))
iid <- switch(img_nm,
tissue_lowres_image="lowres",
tissue_hires_image="hires",
detected_tissue_image="detected",
aligned_fiducials="aligned")
# get scale factor
sf_nm <- switch(iid,
lowres="tissue_lowres_scalef",
"tissue_hires_scalef")
sf <- sfs[[grep(sf_nm, names(sfs))]]
# get 'imgData'
.get_imgData(img, sf, sid, iid, load)
})
do.call(rbind, dfs)
})
do.call(rbind, dfs)
}
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