Crop to a spatial subset

Spatially subset an object x using object y. Giotto spatial subobjects respond to terra::crop. For giottoPoints and giottoPolygon, an alternative faster crop operation is implemented through data.table manipulation of the geometry information and are used by default. This mode also only allows rectangular subsetting. Additionally, giottoPolygons will be cropped using their centroids so that the entire polygon is either present or not instead of the default crop behavior that would keep the portion of the polygon that does fall within the selected crop region. Set DT = FALSE in order to use the default style of terra::crop behavior that also allows usage of additional params through ...

Usage

# S4 method for class 'giottoLargeImage'
crop(x, y, ...)

# S4 method for class 'giottoAffineImage'
crop(x, y, ...)

# S4 method for class 'spatLocsObj'
crop(x, y, ...)

# S4 method for class 'spatialNetworkObj'
crop(x, y, ...)

# S4 method for class 'giottoPoints'
crop(x, y, DT = TRUE, xmin = NULL, xmax = NULL, ymin = NULL, ymax = NULL, ...)

# S4 method for class 'giottoPolygon'
crop(x, y, DT = TRUE, xmin = NULL, xmax = NULL, ymin = NULL, ymax = NULL, ...)

Arguments

x

object

y

any object that has a SpatExtent or returns a SpatExtent

...

additional params to pass to terra::crop

DT

logical. Use alternative DT subsetting for crop operation

xmin, xmax, ymin, ymax

only used if DT = TRUE. Set extent bounds independently

Value

SpatRaster

Examples

g <- GiottoData::loadGiottoMini("visium")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> 3.2 read Giotto spatial centroid information
#> 3.3 read Giotto spatial overlap information
#> 4. read Giotto image information
#> python already initialized in this session
#>  active environment : 'giotto_env'
#>  python version : 3.10
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#>  "/usr/share/miniconda/envs/giotto_env/bin/python"
g_image <- getGiottoImage(g, image_type = "largeImage")
crop(g_image, g_image)
#> An object of class giottoLargeImage : "alignment"
#> Image extent            : 2364.5, 6522.5, -5425.25, -2620.75 (xmin, xmax, ymin, ymax)
#> Original image extent   : 2364.5, 6522.5, -5425.25, -2620.75 (xmin, xmax, ymin, ymax)
#> Scale factor            : 13.2420382165605, 13.2287735849057 (x, y)
#> Resolution              : 0.0755170755170755, 0.0755927972900695 (x, y)
#> Layers                  : 4 
#> Estimated max intensity : 174 
#> Estimated min intensity : 0 
#> Values                  : integers
#> File path               : '/home/runner/work/_temp/Library/GiottoData/Mini_datasets/Visium/VisiumObject/Images/alignment_spatRaster'