update

.Rbuildignore

@@ -5,3 +5,6 @@
 ^pkgdown$
 ^images
 ^data-raw$
+^.github$
+^vignettes/merfish_mousePOA_raw.RDS$
+^vignettes/formatting-SpatialExperiment-for-SEraster.Rmd$

.gitignore

@@ -4,6 +4,4 @@
 .Rhistory
 .RData
 .Ruserdata
-R/.DS_Store
-.DS_Store
-
+.DS_Store

NAMESPACE

@@ -32,6 +32,7 @@ importFrom(ggplot2,scale_fill_viridis_d)
 importFrom(ggplot2,theme)
 importFrom(ggplot2,theme_bw)
 importFrom(methods,as)
+importFrom(methods,is)
 importFrom(rearrr,midrange)
 importFrom(rearrr,rotate_2d)
 importFrom(sf,st_as_sf)

R/main.R

@@ -1,3 +1,6 @@
+# Define global variables
+utils::globalVariables(c("fill"))
+
 #' rasterizeMatrix
 #' 
 #' @description Function to rasterize a given input matrix (both dense or sparse) based on a given position matrix.
@@ -57,7 +60,7 @@
 #' @importFrom sf st_make_grid st_coordinates st_centroid st_as_sf st_intersects
 #' @importFrom BiocParallel MulticoreParam bpstart bplapply bpstop
 #' @importFrom Matrix rowMeans rowSums
-#' @importFrom methods as
+#' @importFrom methods as is
 #' 
 #' @export
 #' 
@@ -107,7 +110,7 @@ rasterizeMatrix <- function(data, pos, bbox, resolution = 100, square = TRUE, fu
 
   ## check to see if bbox input is of class numeric or bbox, if numeric, convert to st_bbox
   stopifnot("bbox must be of class 'numeric' or 'bbox' (as generated by sf::st_bbox)" = class(bbox) %in% c('numeric', 'bbox'))
-  if (class(bbox)=='numeric') {
+  if (is(bbox, 'numeric')) {
     stopifnot("Bounding box for rasterization must be defined by a numeric vector of length four, with xmin, ymin, xmax and ymax values or object of class bbox (as generated by sf::st_bbox)" = length(bbox)==4)
     bbox <- sf::st_bbox(c(xmin = bbox[1], ymin = bbox[2], xmax = bbox[3], ymax = bbox[4]))
   } 
@@ -276,12 +279,14 @@ rasterizeMatrix <- function(data, pos, bbox, resolution = 100, square = TRUE, fu
 #' out <- rasterizeGeneExpression(merfish_mousePOA, assay_name = "volnorm", fun = "mean")
 #' 
 #' # rasterize a single SpatialExperiment object with user-defined resolution and hexagonal pixels
-#' out <- rasterizeGeneExpression(merfish_mousePOA, assay_name = "volnorm", resolution = 200, square = FALSE, fun = "mean")
+#' out <- rasterizeGeneExpression(merfish_mousePOA, assay_name = "volnorm", resolution = 200, 
+#' square = FALSE, fun = "mean")
 #' 
 #' # rasterize a list of SpatialExperiment objects (in this case, permutated datasets 
 #' # with 3 different rotations)
 #' spe_list <- permutateByRotation(merfish_mousePOA, n_perm = 3)
-#' out_list <- rasterizeGeneExpression(spe_list, assay_name = "volnorm", resolution = 100, square = TRUE, fun = "mean")
+#' out_list <- rasterizeGeneExpression(spe_list, assay_name = "volnorm", resolution = 100, 
+#' square = TRUE, fun = "mean")
 #' 
 rasterizeGeneExpression <- function(input, assay_name = NULL, resolution = 100, square = TRUE, fun = "mean", n_threads = 1, BPPARAM = NULL, verbose = FALSE) {
   if (is.list(input)) {
@@ -449,12 +454,14 @@ rasterizeGeneExpression <- function(input, assay_name = NULL, resolution = 100,
 #' out <- rasterizeCellType(merfish_mousePOA, col_name = "celltype", fun = "sum")
 #' 
 #' # rasterize a single SpatialExperiment object with user-defined resolution and hexagonal pixels
-#' out <- rasterizeCellType(merfish_mousePOA, col_name = "celltype", resolution = 200, square = FALSE, fun = "sum")
+#' out <- rasterizeCellType(merfish_mousePOA, col_name = "celltype", resolution = 200, 
+#' square = FALSE, fun = "sum")
 #' 
 #' # rasterize a list of SpatialExperiment objects (in this case, permutated datasets 
 #' # with 3 different rotations)
 #' spe_list <- permutateByRotation(merfish_mousePOA, n_perm = 3)
-#' out_list <- rasterizeCellType(spe_list, col_name = "celltype", resolution = 100, square = TRUE, fun = "sum")
+#' out_list <- rasterizeCellType(spe_list, col_name = "celltype", resolution = 100, 
+#' square = TRUE, fun = "sum")
 #' 
 rasterizeCellType <- function(input, col_name, resolution = 100, square = TRUE, fun = "sum", n_threads = 1, BPPARAM = NULL, verbose = FALSE) {
   if (is.list(input)) {
@@ -769,7 +776,8 @@ permutateByRotation <- function(input, n_perm = 1, verbose = FALSE) {
 #' plotRaster(out, feature_name = "Esr1", name = "Esr1")
 #' 
 #' # rasterize cell-type labels with user-defined resolution and hexagonal pixels
-#' out <- rasterizeCellType(merfish_mousePOA, col_name = "celltype", resolution = 50, square = FALSE, fun = "sum")
+#' out <- rasterizeCellType(merfish_mousePOA, col_name = "celltype", resolution = 50, 
+#' square = FALSE, fun = "sum")
 #' 
 #' # plot total cell counts per pixel (there is only one assay_name in out and default 
 #' # for feature_name argument is "sum"; therefore, these arguments are not specified)
@@ -795,27 +803,27 @@ plotRaster <- function(input, assay_name = NULL, feature_name = "sum", factor_le
   df_sf <- sf::st_sf(geometry = colData(input)$geometry, row.names = rownames(colData(input)))
   # add pixel values
   if (feature_name == "sum") {
-    df_sf <- cbind(df_sf, fill_var = colSums(mat))
+    df_sf <- cbind(df_sf, fill = colSums(mat))
   } else if (feature_name == "mean") {
-    df_sf <- cbind(df_sf, fill_var = colMeans(mat))
+    df_sf <- cbind(df_sf, fill = colMeans(mat))
   } else {
     stopifnot(is.character(feature_name))
     stopifnot("feature_name does not exist in the input SpatialExperiment object's assay slot" = feature_name %in% rownames(mat))
-    df_sf <- cbind(df_sf, fill_var = mat[feature_name,])
+    df_sf <- cbind(df_sf, fill = mat[feature_name,])
   }
 
   if (is.null(factor_levels)) {
     plt <- ggplot2::ggplot() +
       ggplot2::coord_fixed() +
-      ggplot2::geom_sf(data = df_sf, ggplot2::aes(fill = fill_var)) +
+      ggplot2::geom_sf(data = df_sf, ggplot2::aes(fill = fill)) +
       ggplot2::scale_fill_viridis_c(...) +
       ggplot2::theme_bw() +
       ggplot2::theme(panel.grid = ggplot2::element_blank())
   } else {
-    df_sf$fill_var <- factor(df_sf$fill_var, levels = factor_levels)
+    df_sf$fill <- factor(df_sf$fill, levels = factor_levels)
     plt <- ggplot2::ggplot() +
       ggplot2::coord_fixed() +
-      ggplot2::geom_sf(data = df_sf, ggplot2::aes(fill = fill_var)) +
+      ggplot2::geom_sf(data = df_sf, ggplot2::aes(fill = fill)) +
       ggplot2::scale_fill_viridis_d(...) +
       ggplot2::theme_bw() +
       ggplot2::theme(panel.grid = ggplot2::element_blank())