still errorring god..

.github/workflows/check-standard.yaml

@@ -45,5 +45,5 @@ jobs:
 
       - uses: r-lib/actions/check-r-package@v2
         with:
-          upload-snapshots: true
+          upload-snapshots: false
           build_args: 'c("--no-manual")'

NAMESPACE

@@ -34,7 +34,6 @@ export(fftRtsne)
 export(make.autograph)
 export(make.colour.plot)
 export(make.multi.plot)
-export(make.network.plot)
 export(make.pheatmap)
 export(make.spatial.plot)
 export(make.volcano.plot)
@@ -45,20 +44,19 @@ export(prep.cytonorm)
 export(read.files)
 export(read.spatial.files)
 export(run.align)
-export(run.chronoclust)
 export(run.cytonorm)
 export(run.fitsne)
 export(run.flowsom)
 export(run.harmony)
 export(run.knn.classifier)
 export(run.pca)
 export(run.phenograph)
-export(run.prepare.chronoclust)
 export(run.rpca)
 export(run.ruv)
 export(run.spatial.analysis)
 export(run.tsne)
 export(run.umap)
+export(spatial)
 export(train.cytonorm)
 export(train.knn.classifier)
 export(write.files)

R/create.sumtable.R

@@ -19,7 +19,8 @@
 #' @examples
 #' ## Calculate and export results from demonstration data
 #' dat <- Spectre::demo.clustered
-#' counts <- data.frame('Sample' = unique(dat[['Sample']]), 'Counts' = c(rep(100000, 6), rep(1000000, 6)))
+#' counts <- data.frame('Sample' = unique(dat[['Sample']]), 
+#' 'Counts' = c(rep(100000, 6), rep(1000000, 6)))
 #' 
 #' sum.dat <- create.sumtable(dat = dat,
 #'                             sample.col = "Sample",

R/do.add.masks.R

@@ -46,7 +46,7 @@ do.add.masks <- function(dat, # list of spatial objects
 
       message('Reading in mask files')
 
-      if(class(dat) != 'list'){
+      if(!is.list(dat)){
         stop("Your input data 'dat' needs to be a list of spectre spatial objects")
       }
 

R/do.align.R

@@ -2,7 +2,8 @@
 #'
 #' This function allows you to align multiple batches of a dataset, using either a "Quantile" approach, or using "CytoNorm"
 #'
-#' @usage do.align(ref.dat, target.dat, batch.col, align.cols, method, goal, nQ, Qmin, Qmax, write.ref.fcs, write.target.fcs)
+#' @usage do.align(ref.dat, target.dat, batch.col, align.cols, method, goal, 
+#' nQ, Qmin, Qmax, write.ref.fcs, write.target.fcs)
 #'
 #' @param ref.dat NO DEFAULT. If using method = "CytoNorm", this must be a FlowSOM object created by Spectre::do.prep.fsom. If using "Quantiles", then this must be
 #' @param target.dat NO DEFAULT. A data.table of data you wish to align

R/do.logicle.R

@@ -34,7 +34,8 @@
 #'   Value greater than 0 will bring the prescribed additional range into the transformed values
 #'   
 #' @usage 
-#' do.logicle(dat, use.cols, linearisation.width, max.scale.val, full.transform.width, additional.negative.range)
+#' do.logicle(dat, use.cols, linearisation.width, max.scale.val, 
+#' full.transform.width, additional.negative.range)
 #'   
 #' @examples 
 #' library(Spectre)

R/make.autograph.R

@@ -26,7 +26,9 @@
 #' @param max.y DEFAULT = 1.4. Multiplier for plot heigh -- allowing room for stats.
 #' @param path DEFAULT = getwd(). The location to save plots. By default, will save to current working directory. Can be overidden.
 #'
-#' @usage make.autograph(dat, x.axis, y.axis, colour.by, colours, y.axis.label, grp.order, title, filename, scale, dot.size, width, height, path)
+#' @usage make.autograph(dat, x.axis, y.axis, colour.by, colours, 
+#' y.axis.label, grp.order, title, filename, scale, dot.size, width, 
+#' height, path)
 #'
 #' @examples
 #' dat <- data.frame(Samples = c("Mock_01", "Mock_02", "Mock_03", "WNV_01", "WNV_02", "WNV_03"),

R/make.multi.plot.R

@@ -28,7 +28,10 @@
 #' @param blank.axis DEFAULT = FALSE. Logical. Do you want a minimalist graph?
 #' @param save.each.plot DEFAULT = FALSE. Logical. Do you want to save each plot?
 #'
-#' @usage make.multi.plot(dat, x.axis, y.axis, plot.by, divide.by, add.density, col.type, figure.title, align.xy.by, align.col.by, colours, dot.size, col.min.threshold, col.max.threshold, path, plot.width, plot.height, blank.axis, save.each.plot)
+#' @usage make.multi.plot(dat, x.axis, y.axis, plot.by, divide.by, add.density, 
+#' col.type, figure.title, align.xy.by, align.col.by, colours, dot.size, 
+#' col.min.threshold, col.max.threshold, path, plot.width, plot.height, 
+#' blank.axis, save.each.plot)
 #'
 #' @examples
 #' # Create grid of plots on demonstration data

R/make.pheatmap.R

@@ -25,7 +25,9 @@
 #' @param fold.colours DEFAULT = "Spectre". Character, a custom blue:black:red fold-change colour scheme. Can also be "RdYlBu", "YlGnBu", "viridis", "magma", "inferno", "spectral", "Blues", "Reds", "Greys", or "rev(RdBu)".
 #' @param path DEFAULT = NULL. The location to save plots. By default, will save to current working directory. Can be overidden by entering a sub-directory name (e.g. if you have a subdirectory under your working directory called 'plots', you can enter this here).
 #'
-#' @usage make.pheatmap(dat, sample.col, plot.cols, annot.cols, file.name, plot.title, transpose, is.fold, fold.range, normalise, dendrograms, row.sep, col.sep, cell.size, standard.colours, path)
+#' @usage make.pheatmap(dat, sample.col, plot.cols, annot.cols, file.name, 
+#' plot.title, transpose, is.fold, fold.range, normalise, dendrograms, 
+#' row.sep, col.sep, cell.size, standard.colours, path)
 #'
 #' @examples
 #' ## MFI cluster vs marker heatmap

R/package.check.R

@@ -1,6 +1,7 @@
 #' package.check - a function to check the installation of all required packages.
 #'
 #' This function allows you to check to see if all the common use packages dependencies for Spectre are installed.
+#' See \url{https://sydneycytometry.org.au/spectre} for usage instructions and vignettes.
 #'
 #' @return returns an error message if one of the common use packages are not installed. Proceeds in order of package importance, and only the first error message encountered will be returned.
 #'
@@ -10,7 +11,7 @@
 #'
 #' @references \url{https://sydneycytometry.org.au/spectre}
 #'
-#' @usage See \url{https://sydneycytometry.org.au/spectre} for usage instructions and vignettes.
+#' 
 #'
 #' @examples
 #' package.check()

R/package.install.R

@@ -1,6 +1,7 @@
 #' package.install - a function to install packages required for Spectre.
 #'
 #' This function allows you to check to see if all the common use packages dependencies for Spectre are installed. Will only install if the package has not been installed, will not update packages.
+#' See \url{https://sydneycytometry.org.au/spectre} for usage instructions and vignettes.
 #'
 #' @return returns an error message if one of the common use packages are not installed. Proceeds in order of package importance, and only the first error message encountered will be returned.
 #'
@@ -11,7 +12,7 @@
 #'
 #' @references \url{https://sydneycytometry.org.au/spectre}
 #'
-#' @usage See \url{https://sydneycytometry.org.au/spectre} for usage instructions and vignettes.
+#' 
 #'
 #' @examples
 #' package.install()

R/package.load.R

@@ -1,6 +1,7 @@
 #' package.load - a function to load (library) all required packages.
 #'
 #' This function allows you to load all of the common use packages dependencies for Spectre.
+#' See \url{https://sydneycytometry.org.au/spectre} for usage instructions and vignettes.
 #'
 #' @return loads all the common use package libraries.
 #'
@@ -11,7 +12,6 @@
 #'
 #' @references \url{https://sydneycytometry.org.au/spectre}
 #'
-#' @usage See \url{https://sydneycytometry.org.au/spectre} for usage instructions and vignettes.
 #'
 #' @examples
 #' package.load()

R/read.spatial.files.R

@@ -77,8 +77,8 @@ read.spatial.files <- function(dir,
             message("  -- reading single band in TIFF:", i)
             tiff.list[[i]] <- raster(tiff.list[[i]])
           }
-
-          if(class(tiff.list[[i]]) != 'matrix'){
+          if(! is.matrix(tiff.list[[i]])){
+          # if(class(tiff.list[[i]]) != 'matrix'){
             if('array' %in% class(tiff.list[[i]])){
 
               message("  -- merging multiple bands in TIFF:", i)

R/run.fitsne.R

@@ -67,14 +67,17 @@
 #'   substructure in the embedding. See Kobak et al. (2019) for details.
 #'   
 #' @usage 
-#' run.fitsne(dat, use.cols, seed = 42, fitsne.x.name = "FItSNE_X", fitsne.y.name = "FItSNE_Y",
-#'   dims = 2, perplexity = 30, theta = 0.5, max_iter = 750, fft_not_bh = TRUE, ann_not_vptree = TRUE,
-#'   stop_early_exag_iter = 250, exaggeration_factor = 12.0, no_momentum_during_exag = FALSE,
-#'   start_late_exag_iter = -1, late_exag_coeff = 1.0, mom_switch_iter = 250, momentum = 0.5, 
-#'   final_momentum = 0.8, learning_rate = 'auto', n_trees = 50, search_k = -1, nterms = 3, 
-#'   intervals_per_integer = 1, min_num_intervals = 50, K = -1, sigma = -30, initialization = 'pca',
-#'   max_step_norm = 5, load_affinities = NULL, fast_tsne_path = NULL, nthreads = 0, 
-#'   perplexity_list = NULL, get_costs = FALSE,  df = 1.0)
+#' run.fitsne(dat, use.cols, seed = 42, fitsne.x.name = "FItSNE_X", 
+#' fitsne.y.name = "FItSNE_Y", dims = 2, perplexity = 30, theta = 0.5, 
+#' max_iter = 750, fft_not_bh = TRUE, ann_not_vptree = TRUE,
+#'   stop_early_exag_iter = 250, exaggeration_factor = 12.0, 
+#'   no_momentum_during_exag = FALSE,start_late_exag_iter = -1, 
+#'   late_exag_coeff = 1.0, mom_switch_iter = 250, momentum = 0.5, 
+#'   final_momentum = 0.8, learning_rate = 'auto', n_trees = 50, 
+#'   search_k = -1, nterms = 3, intervals_per_integer = 1, 
+#'   min_num_intervals = 50, K = -1, sigma = -30, initialization = 'pca',
+#'   max_step_norm = 5, load_affinities = NULL, fast_tsne_path = NULL, 
+#'   nthreads = 0, perplexity_list = NULL, get_costs = FALSE,  df = 1.0)
 #'   
 #' @examples
 #' dat <- demo.clustered