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Reading `SpatialData`

Source: R/read.R
readSpatialData.Rd

Reading `SpatialData`

Usage

readImage(x, ...)

readLabel(x, ...)

readPoint(x, ...)

readShape(x, ...)

readTable(x)

readSpatialData(
  x,
  images = TRUE,
  labels = TRUE,
  points = TRUE,
  shapes = TRUE,
  tables = TRUE
)

Arguments

x

For readImage/Label/Point/Shape/Table, path to a SpatialData element. For readSpatialData, path to a SpatialData-.zarr store.

...

option arguments passed to and from other methods.

images, labels, points, shapes, tables

Control which elements should be read for each layer. The default, NULL, reads all elements; alternatively, may be FALSE to skip a layer, or a integer vector specifying which elements to read.

Value

  • For readSpatialData, a SpatialData.,

  • For element readers, a SpatialDataImage/Label/Point/Shape or SingleCellExperiment.

Examples

zs <- file.path("extdata", "blobs.zarr")
zs <- system.file(zs, package="SpatialData")

# read complete Zarr store
(sd <- readSpatialData(zs))
#> 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

# helper that gets path to last element in layer 'l'
fn <- \(.) tail(list.files(file.path(zs, .), full.names=TRUE), 1)

# read individual elements
(i <- readImage(fn("images")))
#> class:  SpatialDataImage (MultiScale) 
#> Scales (3): (3,64,64 3,32,32 3,16,16)
channels(i)
#> label label label 
#>     0     1     2 

(p <- readPoint(fn("points")))
#> class: SpatialDataPoint
#> count: 200 
#> data(4): genes instance_id __null_dask_index__ geometry
as.data.frame(head(p))
#>    genes instance_id __null_dask_index__      geometry
#> 1 gene_b           9                   0  POINT (6 48)
#> 2 gene_b           7                   1 POINT (41 28)
#> 3 gene_b           3                   2 POINT (27 54)
#> 4 gene_a           9                   3  POINT (6 44)
#> 5 gene_b           4                   4  POINT (13 6)
#> 6 gene_b           5                   5 POINT (33 61)

(s <- readShape(fn("shapes")))
#> class: SpatialDataShape
#> count: 5 
#> data(1): geometry
data(s)
#> # A duckspatial lazy spatial table
#> # ● CRS: NA 
#> # ● Geometry column: geometry 
#> # ● Geometry type: POLYGON 
#> # ● Bounding box: xmin: 18.741 ymin: 23.578 xmax: 55.838 ymax: 57.732 
#> # Data backed by DuckDB (dbplyr lazy evaluation)
#> # Use ddbs_collect() or st_as_sf() to materialize to sf
#> #
#> # Source:   table<temp_view_719ddbc0_2ce2_4093_aa26_90c22fc58cdc> [?? x 1]
#> # Database: DuckDB 1.5.2 [unknown@Linux 6.17.0-1013-azure:R 4.6.0/:memory:]
#>   geometry                                                                      
#>   <wk_wkb>                                                                      
#> 1 <POLYGON ((42.52463 32.27672, 39.52212 24.63317, 36.38277 25.66096, 42.52463 …
#> 2 <POLYGON ((35.51764 52.5567, 33.40608 46.41484, 32.37829 57.73151, 35.51764 5…
#> 3 <POLYGON ((25.39938 28.69106, 35.68826 25.55172, 24.37159 35.21175, 25.39938 …
#> 4 <POLYGON ((30.05745 24.60573, 28.40081 23.57794, 18.74077 30.03591, 30.05745 …
#> 5 <POLYGON ((55.83783 43.67915, 52.63577 32.36248, 46.1778 39.86363, 55.83783 4…