From 6291f6ec147e72f53ee89e9edd1c8639c3c5593b Mon Sep 17 00:00:00 2001 From: HelenaLC Date: Mon, 11 May 2026 08:43:57 +0200 Subject: [PATCH 1/6] fix duckdb/python clash --- NAMESPACE | 2 ++ R/sdFrame.R | 17 +++++++++++++++-- 2 files changed, 17 insertions(+), 2 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index 4b99b3f..30d6754 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -164,8 +164,10 @@ importFrom(dplyr,sql) importFrom(dplyr,tally) importFrom(duckspatial,as_duckspatial_df) importFrom(duckspatial,ddbs_bbox) +importFrom(duckspatial,ddbs_create_conn) importFrom(duckspatial,ddbs_intersects) importFrom(duckspatial,ddbs_open_dataset) +importFrom(duckspatial,ddbs_write_table) importFrom(graph,"edgeData<-") importFrom(graph,"edgeDataDefaults<-") importFrom(graph,"nodeData<-") diff --git a/R/sdFrame.R b/R/sdFrame.R index 5488392..0dd8a01 100644 --- a/R/sdFrame.R +++ b/R/sdFrame.R @@ -138,13 +138,26 @@ SpatialDataPoint <- \(data=NULL, meta=SpatialDataAttrs(type="frame"), metadata=l #' @rdname SpatialDataFrame #' @importFrom methods is #' @importFrom S4Vectors metadata<- +#' @importFrom duckspatial ddbs_create_conn +#' @importFrom duckspatial ddbs_write_table #' @importFrom duckspatial as_duckspatial_df SpatialDataShape <- \(data=NULL, meta=SpatialDataAttrs(type="frame"), metadata=list(), ...) { data <- .df_to_sf(data, "POLYGON") # always ensure internal data is 'duckspatial_df' if (isTRUE(nrow(data) > 0L) && - !is(data, "duckspatial_df")) - data <- as_duckspatial_df(data, crs=NA) + !is(data, "duckspatial_df")) { + #data <- as_duckspatial_df(data, crs=NA) + conn <- ddbs_create_conn() + ddbs_write_table( + conn=conn, + data=data, + name="sdShape", + overwrite=TRUE, + temp_view=FALSE) + data <- as_duckspatial_df( + x="sdShape", conn=conn, crs=NA, + geom_col=attr(data, "sf_column")) + } x <- .SpatialDataShape(data=data, meta=meta, ...) metadata(x) <- metadata return(x) From 36f3aaa9634150f23fe2f6b1746a6ba30d3bc765 Mon Sep 17 00:00:00 2001 From: HelenaLC Date: Mon, 11 May 2026 08:44:14 +0200 Subject: [PATCH 2/6] fix duckdb/python clash --- R/sdFrame.R | 1 - 1 file changed, 1 deletion(-) diff --git a/R/sdFrame.R b/R/sdFrame.R index 0dd8a01..9395927 100644 --- a/R/sdFrame.R +++ b/R/sdFrame.R @@ -146,7 +146,6 @@ SpatialDataShape <- \(data=NULL, meta=SpatialDataAttrs(type="frame"), metadata=l # always ensure internal data is 'duckspatial_df' if (isTRUE(nrow(data) > 0L) && !is(data, "duckspatial_df")) { - #data <- as_duckspatial_df(data, crs=NA) conn <- ddbs_create_conn() ddbs_write_table( conn=conn, From 9183e8b270e76dfaf5bf4c54e3adb886e7380640 Mon Sep 17 00:00:00 2001 From: HelenaLC Date: Mon, 11 May 2026 11:55:10 +0200 Subject: [PATCH 3/6] used shared DuckDB connection --- NAMESPACE | 1 - R/mask.R | 1 + R/read.R | 9 +++++++-- R/sdFrame.R | 16 ++++++++-------- tests/testthat/test-mask.R | 7 +++---- 5 files changed, 19 insertions(+), 15 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index 30d6754..6db2e2a 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -164,7 +164,6 @@ importFrom(dplyr,sql) importFrom(dplyr,tally) importFrom(duckspatial,as_duckspatial_df) importFrom(duckspatial,ddbs_bbox) -importFrom(duckspatial,ddbs_create_conn) importFrom(duckspatial,ddbs_intersects) importFrom(duckspatial,ddbs_open_dataset) importFrom(duckspatial,ddbs_write_table) diff --git a/R/mask.R b/R/mask.R index 633b92f..d82f14e 100644 --- a/R/mask.R +++ b/R/mask.R @@ -120,6 +120,7 @@ setMethod(".mask", c("SpatialDataImage", "SpatialDataLabel"), \(i, j, how=NULL, "POINT"=mutate(data(j), geometry=ST_Buffer(geometry, radius)), data(j)) ddbs_intersects(df_j, data(i), sparse=TRUE) + } #' @noRd diff --git a/R/read.R b/R/read.R index 355ae1f..d0cc232 100644 --- a/R/read.R +++ b/R/read.R @@ -75,13 +75,17 @@ readPoint <- function(x, ...) { pq <- list.files(x, "\\.parquet$", full.names=TRUE) md <- read_zarr_attributes(x) ax <- unlist(md$axes) - df <- ddbs_open_dataset(pq) |> + df <- ddbs_open_dataset(pq, conn=CONN) |> mutate(geometry=sql(sprintf("ST_Point(%s, %s)", ax[1], ax[2]))) |> as_duckspatial_df(crs=NA_character_) |> select(-all_of(ax)) SpatialDataPoint(data=df, meta=SpatialDataAttrs(md)) } +# create DuckDB connection +# (to be used everywhere!) +CONN <- duckspatial::ddbs_create_conn() + #' @rdname readSpatialData #' @importFrom Rarr read_zarr_attributes #' @importFrom duckspatial ddbs_open_dataset @@ -90,7 +94,8 @@ readPoint <- function(x, ...) { readShape <- function(x, ...) { md <- read_zarr_attributes(x) pq <- list.files(x, "\\.parquet$", full.names=TRUE) - SpatialDataShape(data=ddbs_open_dataset(pq), meta=SpatialDataAttrs(md)) + df <- ddbs_open_dataset(pq, conn=CONN, crs=NA_character_) + SpatialDataShape(data=df, meta=SpatialDataAttrs(md)) } #' @export diff --git a/R/sdFrame.R b/R/sdFrame.R index 9395927..5f36399 100644 --- a/R/sdFrame.R +++ b/R/sdFrame.R @@ -114,7 +114,7 @@ SpatialDataPoint <- \(data=NULL, meta=SpatialDataAttrs(type="frame"), metadata=l "found: ", paste(gt, collapse=", ")) # always ensure internal data is 'duckspatial_df' if (!is(data, "duckspatial_df")) - data <- as_duckspatial_df(data, crs=NA) + data <- as_duckspatial_df(data, crs=NA_character_) } # update 'spatialdata_attrs' if keys are provided za <- as.list(meta) @@ -138,23 +138,23 @@ SpatialDataPoint <- \(data=NULL, meta=SpatialDataAttrs(type="frame"), metadata=l #' @rdname SpatialDataFrame #' @importFrom methods is #' @importFrom S4Vectors metadata<- -#' @importFrom duckspatial ddbs_create_conn #' @importFrom duckspatial ddbs_write_table #' @importFrom duckspatial as_duckspatial_df SpatialDataShape <- \(data=NULL, meta=SpatialDataAttrs(type="frame"), metadata=list(), ...) { data <- .df_to_sf(data, "POLYGON") # always ensure internal data is 'duckspatial_df' - if (isTRUE(nrow(data) > 0L) && - !is(data, "duckspatial_df")) { - conn <- ddbs_create_conn() + if (!is(data, "duckspatial_df") && isTRUE(nrow(data) > 0L)) { + suppressMessages( # silent complaint re: missing CRS ddbs_write_table( - conn=conn, + conn=CONN, data=data, name="sdShape", overwrite=TRUE, - temp_view=FALSE) + temp_view=FALSE)) data <- as_duckspatial_df( - x="sdShape", conn=conn, crs=NA, + x="sdShape", + conn=CONN, + crs=NA_character_, geom_col=attr(data, "sf_column")) } x <- .SpatialDataShape(data=data, meta=meta, ...) diff --git a/tests/testthat/test-mask.R b/tests/testthat/test-mask.R index ba86271..0351275 100644 --- a/tests/testthat/test-mask.R +++ b/tests/testthat/test-mask.R @@ -21,7 +21,7 @@ test_that("mask,unaligned", { # non-existent expect_error( mask(x, i, j, "x"), - "should be \"global\"") + "should be “global”") # not shared za <- meta(image(x, i)) @@ -157,9 +157,8 @@ test_that("mask,sdShape,sdShape", { y <- setTable(x, i, se) # out-of-bounds masking - t <- translation(s, c(1e3,1e3)) - shape(y, "out") <- t - expect_error(mask(y, i, "out")) + shape(y, "out") <- translation(s, c(1e3,1e3)) + expect_error(mask(y, i, "out", how="sum")) # note: data at "0" are from non-intersecting instances; # here, all data should be aggregated to column "1" From 3f0b3a5936411d9c1d94d718e30b41418d1aeed1 Mon Sep 17 00:00:00 2001 From: HelenaLC Date: Mon, 11 May 2026 12:42:52 +0200 Subject: [PATCH 4/6] init conn as global env var --- NAMESPACE | 1 + R/read.R | 17 +- R/sdFrame.R | 4 +- vignettes/SpatialData.html | 1103 ------------------------------------ 4 files changed, 15 insertions(+), 1110 deletions(-) delete mode 100644 vignettes/SpatialData.html diff --git a/NAMESPACE b/NAMESPACE index 6db2e2a..30d6754 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -164,6 +164,7 @@ importFrom(dplyr,sql) importFrom(dplyr,tally) importFrom(duckspatial,as_duckspatial_df) importFrom(duckspatial,ddbs_bbox) +importFrom(duckspatial,ddbs_create_conn) importFrom(duckspatial,ddbs_intersects) importFrom(duckspatial,ddbs_open_dataset) importFrom(duckspatial,ddbs_write_table) diff --git a/R/read.R b/R/read.R index d0cc232..eb77d6d 100644 --- a/R/read.R +++ b/R/read.R @@ -75,16 +75,23 @@ readPoint <- function(x, ...) { pq <- list.files(x, "\\.parquet$", full.names=TRUE) md <- read_zarr_attributes(x) ax <- unlist(md$axes) - df <- ddbs_open_dataset(pq, conn=CONN) |> + df <- ddbs_open_dataset(pq, conn=.conn()) |> mutate(geometry=sql(sprintf("ST_Point(%s, %s)", ax[1], ax[2]))) |> as_duckspatial_df(crs=NA_character_) |> select(-all_of(ax)) SpatialDataPoint(data=df, meta=SpatialDataAttrs(md)) } -# create DuckDB connection -# (to be used everywhere!) -CONN <- duckspatial::ddbs_create_conn() +# create DuckDB connection (to be used everywhere!) +#' @importFrom duckspatial ddbs_create_conn +.conn <- \() { + nm <- ".SpatialData_DuckDB_conn" + if (!exists(nm, envir=.GlobalEnv) || + !DBI::dbIsValid(.GlobalEnv[[nm]])) { + .GlobalEnv[[nm]] <- ddbs_create_conn() + } + .GlobalEnv[[nm]] +} #' @rdname readSpatialData #' @importFrom Rarr read_zarr_attributes @@ -94,7 +101,7 @@ CONN <- duckspatial::ddbs_create_conn() readShape <- function(x, ...) { md <- read_zarr_attributes(x) pq <- list.files(x, "\\.parquet$", full.names=TRUE) - df <- ddbs_open_dataset(pq, conn=CONN, crs=NA_character_) + df <- ddbs_open_dataset(pq, conn=.conn(), crs=NA_character_) SpatialDataShape(data=df, meta=SpatialDataAttrs(md)) } diff --git a/R/sdFrame.R b/R/sdFrame.R index 5f36399..442dbef 100644 --- a/R/sdFrame.R +++ b/R/sdFrame.R @@ -146,14 +146,14 @@ SpatialDataShape <- \(data=NULL, meta=SpatialDataAttrs(type="frame"), metadata=l if (!is(data, "duckspatial_df") && isTRUE(nrow(data) > 0L)) { suppressMessages( # silent complaint re: missing CRS ddbs_write_table( - conn=CONN, + conn=.conn(), data=data, name="sdShape", overwrite=TRUE, temp_view=FALSE)) data <- as_duckspatial_df( x="sdShape", - conn=CONN, + conn=.conn(), crs=NA_character_, geom_col=attr(data, "sf_column")) } diff --git a/vignettes/SpatialData.html b/vignettes/SpatialData.html deleted file mode 100644 index bfa10dc..0000000 --- a/vignettes/SpatialData.html +++ /dev/null @@ -1,1103 +0,0 @@ - - - - - - - - - - - - - - -Introduction to SpatialData - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - - - -

Contents

- - - -
-

1 Introduction

-

The SpatialData package provides an R interface to the -SpatialData framework, a unified ecosystem -for handling spatial omics data. Developed as part of the -scverse project (Virshup et al. 2023), SpatialData aims to solve the -challenges of integrating diverse spatial datasets—including imaging, spatial -transcriptomics, and proteomics—by employing the -OME-NGFF (Next Generation File Format) -standard (Marconato et al. 2024).

-

The Python implementation and core specifications can be found at the -official SpatialData website.

-
-

1.1 Data Representation in R

-

The core of the package is the SpatialData class, which serves as a container -for multiple layers of spatial information:

-
    -
  • Images: Multiscale, multi-channel raster data, represented as ZarrArray objects via the Rarr and ZarrArray packages.
    • -
  • Labels: Segmentation masks (e.g., cell or nuclei boundaries), also stored as ZarrArrays.
    • -
  • Points: High-resolution coordinates (e.g., individual transcript molecules), handled as arrow tables or duckdb-backed data frames for efficient out-of-memory processing.
    • -
  • Shapes: Polygonal regions of interest or circular markers, represented similarly to points but with geometric metadata.
    • -
  • Tables: Functional annotations (e.g., gene expression counts), stored as SingleCellExperiment objects.
    • -
-
-
-
-

2 Getting Started

-

First, we load the necessary libraries:

-
library(SpatialData)
-library(SingleCellExperiment)
-
-

2.1 Reading Data

-

SpatialData objects are typically read from .zarr stores. The package provides -the readSpatialData() function to ingest an entire store.

-
# Path to a toy dataset included in the package
-path <- system.file("extdata", "blobs.zarr", package="SpatialData")
-
-# Read the complete SpatialData object
-sd <- readSpatialData(path)
-sd
-
## class: SpatialData
-## - images(2):
-##   - blobs_image (3,64,64)
-##   - blobs_multiscale_image (3,64,64)
-## - labels(2):
-##   - blobs_labels (64,64)
-##   - blobs_multiscale_labels (64,64)
-## - points(1):
-##   - blobs_points (200)
-## - shapes(3):
-##   - blobs_circles (5,circle)
-##   - blobs_multipolygons (2,polygon)
-##   - blobs_polygons (5,polygon)
-## - tables(1):
-##   - table (3,10) [blobs_labels]
-## coordinate systems(5):
-## - global(8): blobs_image blobs_multiscale_image ... blobs_polygons
-##   blobs_points
-## - scale(1): blobs_labels
-## - translation(1): blobs_labels
-## - affine(1): blobs_labels
-## - sequence(1): blobs_labels
-
-
-

2.2 AnnData Integration with anndataR

-

For spatial omics datasets, functional annotations are often stored as -AnnData objects in Python. The -anndataR package (Deconinck et al. 2025) is used by -SpatialData to seamlessly read these .zarr-backed AnnData objects into -R as SingleCellExperiment objects.

-

By default, readSpatialData(..., anndataR=TRUE) will use this package to -ingest any tables found in the Zarr store.

-
-
-
-

3 Coordinate Systems and Transformations

-

A key feature of the SpatialData framework is its robust handling of -coordinate systems. Each element can exist in multiple coordinate spaces -simultaneously, defined by transformations in its metadata.

-
-

3.1 Coordinate Transformation Graph

-

The relationships between different elements and their respective coordinate -spaces can be complex. SpatialData provides the CTgraph() function to -visualize these relationships as a directed graph.

-
if (requireNamespace("Rgraphviz", quietly = TRUE)) {
-    g <- CTgraph(sd)
-    CTplot(g)
-}
-
-Coordinate transformation graph for the 'blobs' dataset. -

-Figure 1: Coordinate transformation graph for the ‘blobs’ dataset
-

-
-

In this graph:

-
    -
  • source nodes (prefixed with _) represent the individual data layers (images, labels, etc.).
    • -
  • target nodes represent the coordinate systems (e.g., global, sequence).
    • -
  • edges represent the transformations (scale, translation, etc.) required to map an element into a specific space.
    • -
-
-
-

3.2 Applying Transformations

-

The transform() function resolves the necessary steps to project an element -into a target coordinate system by traversing this graph:

-
# Retrieve a point element
-p <- point(sd, 1)
-
-# Project it into the 'global' coordinate space
-q <- SpatialData::transform(p, "global")
-
-
-
-

4 Spatial Queries

-

SpatialData supports sophisticated spatial operations such as cropping, -which are propagated across all layers:

-
# Define a bounding box for cropping
-bb <- list(xmin=10, xmax=50, ymin=10, ymax=50)
-
-# Crop the entire object
-(sp <- crop(sd, bb, j="global"))
-
## class: SpatialData
-## - images(2):
-##   - blobs_image (3,40,40)
-##   - blobs_multiscale_image (3,40,40)
-## - labels(2):
-##   - blobs_labels (40,40)
-##   - blobs_multiscale_labels (40,40)
-## - points(1):
-##   - blobs_points (92)
-## - shapes(3):
-##   - blobs_circles (5,circle)
-##   - blobs_multipolygons (2,polygon)
-##   - blobs_polygons (5,polygon)
-## - tables(1):
-##   - table (3,10) [blobs_labels]
-## coordinate systems(5):
-## - global(8): blobs_image blobs_multiscale_image ... blobs_polygons
-##   blobs_points
-## - scale(1): blobs_labels
-## - translation(1): blobs_labels
-## - affine(1): blobs_labels
-## - sequence(1): blobs_labels
-
-
-

5 Integration with Tables

-

Tables (SCE objects) link to specific labels or shapes using region and -instance_key identifiers, allowing for seamless integration of spatial and -feature-level information.

-
(sce <- SpatialData::table(sd))
-
## class: SingleCellExperiment 
-## dim: 3 10 
-## metadata(0):
-## assays(1): X
-## rownames(3): channel_0_sum channel_1_sum channel_2_sum
-## rowData names(0):
-## colnames(10): 3 4 ... 15 16
-## colData names(0):
-## reducedDimNames(0):
-## mainExpName: NULL
-## altExpNames(0):
-
# Check which region this table annotates
-region(sce)
-
## [1] "blobs_labels"
-
# Check which instances are being annotated
-instances(sce)
-
##  [1]  3  4  5  8 10 11 12 13 15 16
-
-
-

6 Conclusion

-

The SpatialData package brings the power of the scverse spatial ecosystem to -R, providing a scalable and interoperable foundation for spatial omics analysis. -By adhering to the OME-NGFF standard and integrating with established -Bioconductor objects, it enables seamless cross-platform workflows.

-
-
-

Session Info

-
sessionInfo()
-
## R version 4.6.0 (2026-04-24)
-## Platform: aarch64-apple-darwin23
-## Running under: macOS Sequoia 15.6.1
-## 
-## Matrix products: default
-## BLAS:   /Library/Frameworks/R.framework/Versions/4.6/Resources/lib/libRblas.0.dylib 
-## LAPACK: /Library/Frameworks/R.framework/Versions/4.6/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1
-## 
-## locale:
-## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
-## 
-## time zone: Europe/Madrid
-## tzcode source: internal
-## 
-## attached base packages:
-## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
-## [8] base     
-## 
-## other attached packages:
-##  [1] SingleCellExperiment_1.33.2 SummarizedExperiment_1.41.1
-##  [3] Biobase_2.71.0              GenomicRanges_1.63.2       
-##  [5] Seqinfo_1.1.0               IRanges_2.45.0             
-##  [7] S4Vectors_0.49.3            BiocGenerics_0.57.1        
-##  [9] generics_0.1.4              MatrixGenerics_1.23.0      
-## [11] matrixStats_1.5.0           SpatialData_0.99.31        
-## [13] BiocStyle_2.39.0           
-## 
-## loaded via a namespace (and not attached):
-##  [1] DBI_1.3.0           bitops_1.0-9        RBGL_1.87.0        
-##  [4] httr2_1.2.2         anndataR_1.1.2      rlang_1.2.0        
-##  [7] magrittr_2.0.5      Rarr_1.99.44        otel_0.2.0         
-## [10] e1071_1.7-17        compiler_4.6.0      dir.expiry_1.19.0  
-## [13] paws.storage_0.9.0  png_0.1-9           fftwtools_0.9-11   
-## [16] vctrs_0.7.3         pkgconfig_2.0.3     wk_0.9.5           
-## [19] crayon_1.5.3        fastmap_1.2.0       dbplyr_2.5.2       
-## [22] magick_2.9.1        XVector_0.51.0      paws.common_0.8.9  
-## [25] rmarkdown_2.31      graph_1.89.1        tinytex_0.59       
-## [28] purrr_1.2.2         bit_4.6.0           xfun_0.57          
-## [31] cachem_1.1.0        jsonlite_2.0.0      blob_1.3.0         
-## [34] DelayedArray_0.37.1 uuid_1.2-2          jpeg_0.1-11        
-## [37] tiff_0.1-12         parallel_4.6.0      R6_2.6.1           
-## [40] bslib_0.10.0        reticulate_1.46.0   jquerylib_0.1.4    
-## [43] Rcpp_1.1.1-1.1      bookdown_0.46       assertthat_0.2.1   
-## [46] knitr_1.51          R.utils_2.13.0      Matrix_1.7-5       
-## [49] tidyselect_1.2.1    duckspatial_1.0.0   rstudioapi_0.18.0  
-## [52] abind_1.4-8         yaml_2.3.12         EBImage_4.53.0     
-## [55] curl_7.1.0          lattice_0.22-9      tibble_3.3.1       
-## [58] withr_3.0.2         evaluate_1.0.5      sf_1.1-0           
-## [61] units_1.0-1         proxy_0.4-29        pillar_1.11.1      
-## [64] BiocManager_1.30.27 filelock_1.0.3      KernSmooth_2.23-26 
-## [67] RCurl_1.98-1.18     nanoarrow_0.8.0     class_7.3-23       
-## [70] glue_1.8.1          tools_4.6.0         locfit_1.5-9.12    
-## [73] grid_4.6.0          basilisk_1.23.0     duckdb_1.5.2       
-## [76] cli_3.6.6           rappdirs_0.3.4      S4Arrays_1.11.1    
-## [79] arrow_23.0.1.2      dplyr_1.2.1         Rgraphviz_2.55.0   
-## [82] geoarrow_0.4.2      R.methodsS3_1.8.2   sass_0.4.10        
-## [85] digest_0.6.39       classInt_0.4-11     SparseArray_1.11.13
-## [88] ZarrArray_0.99.5    htmlwidgets_1.6.4   htmltools_0.5.9    
-## [91] R.oo_1.27.1         lifecycle_1.0.5     bit64_4.8.0
-
-
-

References

-
-
-Deconinck, Louise, Luke Zappia, Robrecht Cannoodt, et al. 2025. “anndataR improves interoperability between R and Python in single-cell transcriptomics.” bioRxiv, 2025.08.18.669052. https://doi.org/10.1101/2025.08.18.669052. -
-
-Marconato, Luca, Giovanni Palla, Kevin A Yamauchi, et al. 2024. “SpatialData: an open and universal data framework for spatial omics.” Nature Methods, ahead of print. https://doi.org/10.1038/s41592-024-02212-x. -
-
-Virshup, Isaac, Danila Bredikhin, Lukas Heumos, et al. 2023. “The scverse project provides a computational ecosystem for single-cell omics data analysis.” Nature Biotechnology 41 (5): 604–6. https://doi.org/10.1038/s41587-023-01733-8. -
-
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- - - - -
- - - - - - - - - - - - - - - - - - From a5a2ae1615247a62105004b21b6f45d9a59f3e08 Mon Sep 17 00:00:00 2001 From: HelenaLC Date: Mon, 11 May 2026 12:54:42 +0200 Subject: [PATCH 5/6] fix error message check --- tests/testthat/test-mask.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/testthat/test-mask.R b/tests/testthat/test-mask.R index 0351275..14acd26 100644 --- a/tests/testthat/test-mask.R +++ b/tests/testthat/test-mask.R @@ -21,7 +21,7 @@ test_that("mask,unaligned", { # non-existent expect_error( mask(x, i, j, "x"), - "should be “global”") + "'arg' should be") # not shared za <- meta(image(x, i)) From b1d3f9dd9095a26e8f95a8bd84015c1e5064c90c Mon Sep 17 00:00:00 2001 From: HelenaLC Date: Mon, 11 May 2026 13:09:06 +0200 Subject: [PATCH 6/6] +Imports:DBI --- DESCRIPTION | 1 + NAMESPACE | 1 + R/read.R | 6 ++++-- 3 files changed, 6 insertions(+), 2 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index dbd0b63..aa490c4 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -54,6 +54,7 @@ Authors@R: c( Imports: anndataR (>= 1.1.3), BiocGenerics, + DBI, DelayedArray, dplyr, duckspatial, diff --git a/NAMESPACE b/NAMESPACE index 30d6754..3ea9571 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -117,6 +117,7 @@ importFrom(BiocGenerics,as.data.frame) importFrom(BiocGenerics,colnames) importFrom(BiocGenerics,combine) importFrom(BiocGenerics,rownames) +importFrom(DBI,dbIsValid) importFrom(DelayedArray,DelayedArray) importFrom(EBImage,rotate) importFrom(Matrix,sparseMatrix) diff --git a/R/read.R b/R/read.R index eb77d6d..4bc4d06 100644 --- a/R/read.R +++ b/R/read.R @@ -82,12 +82,14 @@ readPoint <- function(x, ...) { SpatialDataPoint(data=df, meta=SpatialDataAttrs(md)) } -# create DuckDB connection (to be used everywhere!) +# create DuckDB connection +# (to be used everywhere!) +#' @importFrom DBI dbIsValid #' @importFrom duckspatial ddbs_create_conn .conn <- \() { nm <- ".SpatialData_DuckDB_conn" if (!exists(nm, envir=.GlobalEnv) || - !DBI::dbIsValid(.GlobalEnv[[nm]])) { + !dbIsValid(.GlobalEnv[[nm]])) { .GlobalEnv[[nm]] <- ddbs_create_conn() } .GlobalEnv[[nm]]