Add rworkflows

.Rbuildignore

@@ -11,4 +11,4 @@
 ^pkgdown$
 ^vignettes/diagrams/*\.mmd$
 ^vignettes/diagrams/*\.svg$
-^vignettes/design\.Rmd$
+^vignettes/design\.Rmd$

.github/workflows/lint.yaml

@@ -17,7 +17,7 @@ jobs:
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       - uses: r-lib/actions/setup-r@v2
         with:

.github/workflows/rworkflows.yml

@@ -0,0 +1,60 @@
+name: rworkflows
+'on':
+  push:
+    branches:
+    - master
+    - main
+    - devel
+    - RELEASE_**
+    - rworkflows
+  pull_request:
+    branches:
+    - master
+    - main
+    - devel
+    - RELEASE_**
+    - rworkflows
+jobs:
+  rworkflows:
+    permissions: write-all
+    runs-on: ${{ matrix.config.os }}
+    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+    container: ${{ matrix.config.cont }}
+    strategy:
+      fail-fast: ${{ false }}
+      matrix:
+        config:
+        - os: ubuntu-latest
+          bioc: devel
+          r: auto
+          cont: ghcr.io/bioconductor/bioconductor_docker:devel
+          rspm: ~
+        - os: macOS-latest
+          bioc: release
+          r: auto
+          cont: ~
+          rspm: ~
+        - os: windows-latest
+          bioc: release
+          r: auto
+          cont: ~
+          rspm: ~
+    steps:
+    - name: Install Python dependencies for reticulate
+      run: |
+        reticulate::install_miniconda()
+        reticulate::py_install(c("anndata", "scanpy"), pip = TRUE)
+      shell: Rscript {0}
+    - uses: neurogenomics/rworkflows@master
+      with:
+        run_bioccheck: ${{ true }}
+        run_rcmdcheck: ${{ true }}
+        as_cran: ${{ true }}
+        run_vignettes: ${{ true }}
+        has_testthat: ${{ true }}
+        run_covr: ${{ true }}
+        run_pkgdown: ${{ true }}
+        has_runit: ${{ false }}
+        has_latex: ${{ false }}
+        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run_docker: ${{ true }}

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: anndataR
 Title: AnnData interoperability in R
-Version: 0.0.0.9000
+Version: 0.99.1 
 Authors@R: c(
     person(
         "Robrecht", "Cannoodt", 
@@ -57,11 +57,14 @@ Description: Bring the power and flexibility of AnnData to the R
 License: MIT + file LICENSE
 URL: https://scverse.org/anndataR, https://github.com/scverse/anndataR
 BugReports: https://github.com/scverse/anndataR/issues
+BioViews:
+  Software
 Depends: 
-    R (>= 3.2.0)
+    R (>= 4.3.0)
 Imports:
     Matrix,
     methods,
+    stats,
     R6
 Suggests:
     anndata,
@@ -83,5 +86,9 @@ Config/Needs/website: pkgdown, tibble, knitr, rprojroot, stringr, readr,
 Config/testthat/edition: 3
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE, r6 = TRUE)
+<<<<<<< HEAD
 RoxygenNote: 7.2.3
 biocViews: SingleCell, DataImport, DataRepresentation
+=======
+RoxygenNote: 7.2.3.9000
+>>>>>>> 3a22fe5dbde8f24cb3156e150427d537c904a79c

NAMESPACE

@@ -2,16 +2,25 @@
 
 export(AnnData)
 export(InMemoryAnnData)
+export(dummy_data)
+export(from_DimReduc)
 export(from_Seurat)
 export(from_SingleCellExperiment)
 export(read_h5ad)
+<<<<<<< HEAD
+export(to_DimReduc)
+=======
+export(setup_conda)
+>>>>>>> 3a22fe5dbde8f24cb3156e150427d537c904a79c
 export(to_HDF5AnnData)
 export(to_InMemoryAnnData)
 export(to_Seurat)
 export(to_SingleCellExperiment)
 export(write_h5ad)
 importFrom(Matrix,as.matrix)
+importFrom(Matrix,rsparsematrix)
 importFrom(Matrix,sparseMatrix)
 importFrom(Matrix,t)
 importFrom(R6,R6Class)
 importFrom(methods,as)
+importFrom(stats,runif)

NEWS.md

@@ -1,5 +1,58 @@
+# anndataR 0.99.1
+
+## New features
+
+* Harmonise all references to `h5ad_file` (`file`,`h5ad_path`,`ad`)
+* Harmonise all references to `ad` (`adata`)
+* Use `@returns` in Roxygen notes to allow multi-line notes.
+* Export helper function `dummy_data`
+  - Makes examples much less verbose and more consistent.
+  - Include "obsm","varm","obsp","varp" and "layers" wherever possible.
+* *Seurat.R*
+  - Add/extract `DimRed` elements whenever available.
+  - Add unit tests for `from_Seurat`.
+* New functions
+  - `graphs_to_anndata`:  When converting Seurat --> AnnData, 
+    store `obsp` and `varp` anndata slots from `graphs`. Does some inference 
+    about whether each matrix should go into the `obsp` vs. `varp` slot based 
+    on whether they have the same dimensions as the number of rows. 
+  - `anndata_to_graphs`: When converting AnnData --> Seurat, 
+    store `obsp` and `varp` anndata slots in `graphs`. 
+* *DimReduc.R*
+  - New functions for converting Seurat's DimReduc objects.
+
+## Bug fixes
+
+* *DESCRIPTION*:
+  - Add "email" tag to `Authors`.
+  - Add `BiocViews`
+* Fix `BiocCheck` WARNINGS:
+  - `Empty or missing \value sections found in man pages.`
+* Fix `BiocCheck` NOTES:
+  - Make all vignettes use `BiocStyle`
+  - `Update R version dependency from 3.2.0 to 4.3.0.`
+  - `'sessionInfo' not found in vignette(s)`
+  - `Avoid the use of 'paste' in condition signals` 
+  - `Avoid 'cat' and 'print' outside of 'show' methods`
+  - `Consider adding runnable examples to man pages that document exported objects.`
+  - Added helper function `messager` to avoid notes about pasting inside messages.
+    Can also easily turn off verbosity by setting the env var "ANNDATAR_VERBOSE".
+* Fix all unit tests given updates.
+
+# anndataR 0.99.0
+
+## New features
+
+- Add `rworkflows` CI.
+- Update *lint.yaml* to use `actions/checkout@v4` (which has less issues).
+- New function `setup_conda` automatically installs miniconda 
+  and sets up conda env: #97
+- Change version to Bioc-recommended devel version: 0.99.0
+
 # anndataR 0.1.0
 
+## New features
+
 Initial release of anndataR, providing support for working with AnnData objects in R.
 
 Feature list:
@@ -18,4 +71,4 @@ Feature list:
 
 * Converters:
   - SingleCellExperiment
-  - Seurat
+  - Seurat

R/AbstractAnnData.R

@@ -9,6 +9,7 @@
 #'   Abstract [R6][R6::R6Class] class representing an AnnData
 #'   object. Defines the interface.
 #' @importFrom R6 R6Class
+#' @returns An [R6][R6::R6Class] object of class "AbstractAnnData".
 AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
   active = list(
     #' @field X NULL or an observation x variable matrix (without
@@ -77,8 +78,9 @@ AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
     #'   computationally expensive.
     #' @param ... Optional arguments to print method.
     print = function(...) {
-      cat("AnnData object with n_obs \u00D7 n_vars = ", self$n_obs(), " \u00D7 ", self$n_vars(), "\n", sep = "")
-
+      messager("AnnData object with n_obs \u00D7 n_var =",
+               self$n_obs(), "\u00D7 ",
+               self$n_var(), "\n") 
       for (attribute in c(
         "obs",
         "var",
@@ -97,7 +99,7 @@ AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
             NULL
           }
         if (length(keys) > 0) {
-          cat(
+          messager(
             "    ", attribute, ":",
             paste("'", keys, "'", collapse = ", "),
             "\n",
@@ -111,15 +113,15 @@ AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
     shape = function() {
       c(
         self$n_obs(),
-        self$n_vars()
+        self$n_var()
       )
     },
     #' @description Number of observations in the AnnData object.
     n_obs = function() {
       length(self$obs_names)
     },
     #' @description Number of variables in the AnnData object.
-    n_vars = function() {
+    n_var = function() {
       length(self$var_names)
     },
     #' @description Keys ('column names') of `obs`.
@@ -180,20 +182,22 @@ AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
         if (nrow(mat) != self$n_obs()) {
           stop("nrow(", label, ") should be the same as nrow(obs)")
         }
-        if (ncol(mat) != self$n_vars()) {
+        if (ncol(mat) != self$n_var()) {
           stop("ncol(", label, ") should be the same as nrow(var)")
         }
 
         if (!is.null(rownames(mat))) {
           warning(wrap_message(
-            "rownames(", label, ") should be NULL, removing them from the matrix"
+            "rownames(", label, 
+            ") should be NULL, removing them from the matrix"
           ))
           rownames(mat) <- NULL
         }
 
         if (!is.null(colnames(mat))) {
           warning(wrap_message(
-            "colnames(", label, ") should be NULL, removing them from the matrix"
+            "colnames(", label, 
+            ") should be NULL, removing them from the matrix"
           ))
           colnames(mat) <- NULL
         }
@@ -211,13 +215,18 @@ AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
     # @param shape Expected dimensions of matrix
     # @param expected_rownames
     # @param excepted_colnames
-    .validate_aligned_array = function(mat, label, shape, expected_rownames = NULL, expected_colnames = NULL) {
+    .validate_aligned_array = function(mat, 
+                                       label,
+                                       shape,
+                                       expected_rownames = NULL,
+                                       expected_colnames = NULL) {
       mat_dims <- dim(mat)
       for (i in seq_along(shape)) {
         expected_dim <- shape[i]
         found_dim <- mat_dims[i]
         if (found_dim != expected_dim) {
-          stop("dim(", label, ")[", i, "] should have shape: ", expected_dim, ", found: ", found_dim, ".")
+          stop("dim(", label, ")[", i, "] should have shape: ",
+               expected_dim, ", found: ", found_dim, ".")
         }
       }
       if (!is.null(expected_rownames) & !is.null(rownames(mat))) {
@@ -250,17 +259,25 @@ AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
     # @param collection A named list of 0 or more matrix elements with
     #   whose entries will be validated
     # @param label The label of the collection, used for error messages
-    # @param shape Expected dimensions of arrays. Arrays may have more dimensions than specified here
+    # @param shape Expected dimensions of arrays. Arrays may have more
+    # dimensions than specified here
     # @param expected_rownames
     # @param expected_colnames
-    .validate_aligned_mapping = function(collection, label, shape, expected_rownames = NULL, expected_colnames = NULL) {
+    .validate_aligned_mapping = function(collection, 
+                                         label, 
+                                         shape, 
+                                         expected_rownames = NULL, 
+                                         expected_colnames = NULL) {
       if (is.null(collection)) {
         return(collection)
       }
 
       collection_names <- names(collection)
-      if (!is.list(collection) || ((length(collection) != 0) && is.null(collection_names))) {
-        stop(paste0(label, " must be a named list, was ", class(collection)))
+      if (!is.list(collection) || 
+          ((length(collection) != 0) &&
+           is.null(collection_names))) {
+        stp <- paste0(label, " must be a named list, was ", class(collection))
+        stop(stp)
       }
 
       for (mtx_name in collection_names) {
@@ -286,7 +303,7 @@ AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
 
       expected_nrow <- switch(label,
         obs = self$n_obs(),
-        var = self$n_vars()
+        var = self$n_var()
       )
 
       if (is.null(df)) {
@@ -308,7 +325,8 @@ AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
 
       if (.row_names_info(df) > 0) {
         warning(wrap_message(
-          "'", label, "' should not have any rownames, removing them from the data frame."
+          "'", label, 
+          "' should not have any rownames, removing them from the data frame."
         ))
         rownames(df) <- NULL
       }
@@ -320,22 +338,26 @@ AbstractAnnData <- R6::R6Class("AbstractAnnData", # nolint
     #   are NULL or consistent with the dimensions of `obs` or `var`.
     # @param names A vector to validate
     # @param label Must be `"obs"` or `"var"`
-    .validate_obsvar_names = function(names, label = c("obs", "var"), check_length = TRUE) {
+    .validate_obsvar_names = function(names,
+                                      label = c("obs", "var"), 
+                                      check_length = TRUE) {
       label <- match.arg(label)
 
       if (is.null(names)) {
         stop(wrap_message(label, "_names should be defined."))
       }
 
-      # only check whether sizes match if the obsvar names has already been defined
+      # only check whether sizes match if the obsvar names has
+      # already been defined.
       prev_names <- attr(self, paste0(label, "_names"))
       if (!is.null(prev_names)) {
         expected_len <- length(prev_names)
 
         if (length(names) != expected_len) {
-          size_check_label <- if (label == "obs") "n_obs" else "n_vars"
+          size_check_label <- if (label == "obs") "n_obs" else "n_var"
           stop(wrap_message(
-            "length(", label, "_names) should be the same as ad$", size_check_label, "()"
+            "length(", label, "_names) should be the same as ad$", 
+            size_check_label, "()"
           ))
         }
       }