Rescale individual polygons by a x and y factor
Usage
rescalePolygons(
gobject,
poly_info = "cell",
name = "rescaled_cell",
fx = 0.5,
fy = 0.5,
calculate_centroids = TRUE,
return_gobject = TRUE
)Examples
g <- GiottoData::loadGiottoMini("vizgen")
#> 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"
rescalePolygons(g, poly_info = "aggregate")
#> Setting polygon info [rescaled_cell]
#> An object of class giotto
#> >Active spat_unit: z0
#> >Active feat_type: rna
#> dimensions : 337, 498 (features, cells)
#> [SUBCELLULAR INFO]
#> polygons : z0 z1 aggregate rescaled_cell
#> features : rna
#> [AGGREGATE INFO]
#> expression -----------------------
#> [z0][rna] raw
#> [z1][rna] raw
#> [aggregate][rna] raw normalized scaled pearson
#> spatial locations ----------------
#> [z0] raw
#> [z1] raw
#> [aggregate] raw
#> spatial networks -----------------
#> [aggregate] Delaunay_network kNN_network
#> spatial enrichments --------------
#> [aggregate][rna] cluster_metagene
#> dim reduction --------------------
#> [aggregate][rna] pca umap tsne
#> nearest neighbor networks --------
#> [aggregate][rna] sNN.pca
#> attached images ------------------
#> images : 4 items...
#>
#>
#> Use objHistory() to see steps and params used