Call the Ripley's k function.

# S4 method for STGrid
plot_rip_k(
  object,
  correction = c("border", "isotropic", "Ripley", "translate"),
  max_feat_label = 8,
  color = NULL,
  size = 4
)

Arguments

object: A STCompR object.
correction: kind of correction should be displayed.
max_feat_label: The maximum number of features to display. The features with the highest correction value (whatever the radius) are displayed.
color: The colors for the features to be displayed.
size: The size of the labels.

Examples

example_dataset()
#> |-- INFO :  Dataset 11284233/files/Xenium_Mouse_Brain_Coronal_7g was already loaded. 
plot_rip_k(compute_k_ripley(Xenium_Mouse_Brain_Coronal_7g[c("Ano1", "Chat", "Ebf3")]))
#> |-- INFO :  >>> Estimating Ripley's reduced second moment function for all features. 
#> 
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